Advances in Genetics, Vol. 62 [1st ed.] 978-0-12-374443-2

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Advances in Genetics, Volume 62

Serial Editors

Jeffrey C. Hall Orono, Maine

Jay C. Dunlap Hanover, New Hampshire

Theodore Friedmann La Jolla, California

Veronica van Heyningen Edinburgh, United Kingdom

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First edition 2008 Copyright ß 2008 Elsevier Inc. All rights reserved No part of this publication may be reproduced, stored in a retrieval system or transmitted in any form or by any means electronic, mechanical, photocopying, recording or otherwise without the prior written permission of the publisher Permissions may be sought directly from Elsevier’s Science & Technology Rights Department in Oxford, UK: phone (+44) (0) 1865 843830; fax (+44) (0) 1865 853333; email: [email protected]. Alternatively you can submit your request online by visiting the Elsevier web site at http://www.elsevier.com/locate/permissions, and selecting Obtaining permission to use Elsevier material Notice No responsibility is assumed by the publisher for any injury and/or damage to persons or property as a matter of products liability, negligence or otherwise, or from any use or operation of any methods, products, instructions or ideas contained in the material herein. Because of rapid advances in the medical sciences, in particular, independent verification of diagnoses and drug dosages should be made ISBN: 978-0-12-374443-2 ISSN: 0065-2660 For information on all Academic Press publications visit our website at elsevierdirect.com Printed and bound in USA 08 09 10 11 12

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CONTRIBUTORS Numbers in parentheses indicate the pages on which the authors’ contributions begin.

Larry D. Atwood (33) Department of Neurology, Boston University School of Medicine, Boston, Massachusetts 02118; Department of Biostatistics, Boston University School of Public Health, Boston, Massachusetts 02118 Emelia J. Benjamin (33) NHLBI’s Framingham Heart Study, Framingham, Massachusetts 01702; Department of Cardiology, Boston University School of Medicine, Boston, Massachusetts 02118; Department of Epidemiology, Boston University School of Public Health, Boston, Massachusetts 02118 Stephen Chanock (1) Laboratory of Translation Genomics, Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, Maryland 20892; Core Genotyping Facility, Advanced Technology Center, Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, Maryland 20892 L. Adrienne Cupples (33) Department of Biostatistics, Boston University School of Public Health, Boston, Massachusetts 02118 Ralph B. D’Agostino (33) Department of Biostatistics, Boston University School of Public Health, Boston, Massachusetts 02118; NHLBI’s Framingham Heart Study, Framingham, Massachusetts 01702 Caroline S. Fox (33) NHLBI’s Framingham Heart Study, Framingham, Massachusetts 01702 Diddahally R. Govindaraju (33) Department of Neurology, Boston University School of Medicine, Boston, Massachusetts 02118 Jeffrey C. Hall (67) School of Biology and Ecology, University of Maine, Orono, Maine William B. Kannel (33) NHLBI’s Framingham Heart Study, Framingham, Massachusetts 01702 Andreas E. Kulozik (185) Department for Pediatric Oncology, Hematology and Immunology, University Hospital Heidelberg and Molecular Medicine Partnership Unit, University of Heidelberg and European Molecular Biology Laboratory, Im Neuenheimer Feld 156, 69120 Heidelberg, Germany vii

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Contributors

Marty Larson (33) NHLBI’s Framingham Heart Study, Framingham, Massachusetts 01702 Daniel Levy (33) NHLBI’s Framingham Heart Study, Framingham, Massachusetts 01702 Joanne Murabito (33) NHLBI’s Framingham Heart Study, Framingham, Massachusetts 01702; Section of General Internal Medicine, Boston University School of Medicine, Boston, Massachusetts 02118 Gabriele Neu-Yilik (185) Department for Pediatric Oncology, Hematology and Immunology, University Hospital Heidelberg and Molecular Medicine Partnership Unit, University of Heidelberg and European Molecular Biology Laboratory, Im Neuenheimer Feld 156, 69120 Heidelberg, Germany Christopher J. O’Donnell (33) NHLBI’s Framingham Heart Study, Framingham, Massachusetts 01702 Nick Orr (1) Laboratory of Translation Genomics, Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, Maryland 20892 Greta Lee Splansky (33) NHLBI’s Framingham Heart Study, Framingham, Massachusetts 01702 Ramachandran S. Vasan (33) NHLBI’s Framingham Heart Study, Framingham, Massachusetts 01702; Department of Cardiology, Boston University School of Medicine, Boston, Massachusetts 02118; Department of Epidemiology, Boston University School of Public Health, Boston, Massachusetts 02118 Adriana Villella (67) Department of Biology, Brandeis University, Waltham, Massachusetts Philip A. Wolf (33) Department of Neurology, Boston University School of Medicine, Boston, Massachusetts 02118

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Common Genetic Variation and Human Disease Nick Orr* and Stephen Chanock*,† *Laboratory of Translation Genomics, Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, Maryland 20892 †Core Genotyping Facility, Advanced Technology Center, Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, Maryland 20892

I. Introduction II. Variation in the Human Genome A. Single-nucleotide polymorphisms B. Factors influencing SNP frequencies in populations C. SNPs in health and disease D. Other categories of genomic variation III. Utilization of Genetic Variation in Gene Mapping Studies IV. Mapping Complex Disease Genes Using Association A. Linkage and association: Out with the old and in with the new? B. Genetic association testing: The direct approach C. Genetic association testing: The indirect approach D. tagSNPs E. Quantifying LD in the genome F. Testing association using haplotypes V. Genome-wide Association Studies VI. Study Design and Data Analysis A. Introduction B. Type I error and the multiple testing problem C. Additional sources of error

Advances in Genetics, Vol. 62

0065-2660/08 $35.00 DOI: 10.1016/S0065-2660(08)00601-9

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VII. Significance for Public Health VIII. Concluding Remarks References

ABSTRACT The landscape of human genetics has changed remarkably in a relatively short space of time. The field has progressed from comparatively small studies of rare genetic diseases to vast consortia based efforts that target the inherited components of common complex diseases and which typically involve thousands of individual samples. In particular, genome wide association studies have become possible as a result of a new generation of genotyping platforms. At the time of writing, these have led to the discovery of more than 150 novel susceptibility loci across a broad spectrum of diseases, a few in genes with high biological plausibility but the majority in others that had not been considered candidates. Here, we provide an overview of the field of complex disease genetics pertaining to mapping by association and consider the many pitfalls and caveats that have arisen. ß 2008, Elsevier Inc.

I. INTRODUCTION Annotation of genetic variation in the human genome coupled with advances in bioinformatics and technology have significantly changed the landscape of human genetics. Now geneticists are in a strong position to answer questions pertaining to the heritability of common conditions. In particular, we are able to address the contribution of common germ line genetic variation to disease susceptibility and outcome. In the near future looms the potential to sequence entire human genomes (Bennett et al., 2005; Binladen et al., 2007; Margulies et al., 2005), which will yield insights into the significance of less common genetic variants, perhaps in both common and uncommon diseases. Successes in the analysis of single-gene disorders using linkage or reverse cloning (e.g., hemophilia (Youssoufian et al., 1988), cystic fibrosis (Kerem et al., 1989), thrombosis (Bertina et al., 1994), and chronic granulomatous disease (Royer-Pokora et al., 1986) have, until recently, eluded polygenic conditions. The etiology of these diseases may even be further influenced by environmental challenges (Hunter, 2005). Complex diseases do not necessarily follow traditional patterns of Mendelian inheritance. The identification of diseasecausing genes using conventional linkage-based approaches has been less than successful because studies do not have the requisite statistical power to detect

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low-penetrance, high-frequency alleles. During the course of this review, we will discuss advances in the approaches for mapping genetic variants that contribute to complex diseases, particularly those that utilize unrelated subjects. We will outline the goals and limitations of current procedures and will discuss the recent successes seen in genome-wide association studies (GWAS). We will also touch upon issues underlying the pre-GWAS paucity of replicable findings.

II. VARIATION IN THE HUMAN GENOME A. Single-nucleotide polymorphisms The human genome is composed of over three billion bases of DNA encoding between 25,000 and 30,000 genes (International Human Genome Sequencing Consortium, 2004; Lander et al., 2001; Venter et al., 2001). The most common form of variation in the genome is the single-nucleotide polymorphism (SNP). SNPs are DNA variants in which a single nucleotide at a fixed position in the genome is substituted with another. It has been estimated that there are in excess of 10 million common [minor allele frequency (MAF)>1%] SNPs within the genome (Kruglyak and Nickerson, 2001; Reich and Lander, 2001); a small subset of these likely give rise to the observable phenotypic differences in and between populations, including disease susceptibility and outcome. One may expect to observe a single-nucleotide difference between two haploid genomes in the range of 1 in every 300–1000 base pairs. Although the vast majority of SNPs are shared between populations (Conrad et al., 2006; Hinds et al., 2005; International HapMap Consortium, 2005), it is evident that many are specific to populations or continental grouping of populations that share recent history. In this regard, it is possible to identify sets of markers that can be used to measure admixture in populations and that in some circumstances may be utilized to map genes that could partially account for differences in disease incidence between populations (Freedman et al., 2006; Patterson et al., 2004; Shriver et al., 2005).

B. Factors influencing SNP frequencies in populations Because the chemical structure of DNA influences the rate of mutation, there is bias in the frequency distribution of categories of mutational events. Transitions, which preserve the class of nucleotide (e.g., purine substituted for purine or pyrimidine for pyrimidine, A $ G or C $ T, respectively) are more common than transversions, which result in a switch of a pyrimidine for a purine or purine for a pyrimidine (A $ C, A $ T, G $ C, or G $ T) (Topal and Fresco, 1976). New SNPs arise via mutation and with time they either disappear or reach fixation, replacing the ancestral allele. The time taken for either of these

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extremes to be reached is proportional to population size; generally, as population size increases, so too does the number of generations in which a new SNP will be observed in its heterozygous state. It is thought that the lifespan of most SNPs is under the influence of neutral selection because they are inconsequential with respect to the fitness of an organism. SNPs that confer a selective advantage among members of a population may become enriched within that population through positive selection. Signatures of positive selection, though rare in genes, can be useful for the identification of those that have played an important role in the adaptation of a species to its local environment (Bersaglieri et al., 2004; Nielsen et al., 2005). For example, the frequency of lactose intolerance is low in European populations that have historically relied heavily on dairy farming for nutrition (Scrimshaw and Murray, 1988). This is due to the rapid expansion of a lactase variant that remains expressed in adulthood. Carriers of the variant thus have a selective advantage over those who lose the ability to metabolize lactose. Positive selection at the lactase gene is characterized by functional variants that lie on high-frequency, long-range haplotypes with often substantial frequency differences between populations (Bersaglieri et al., 2004). Patterns of selection observed in the human genome are not uniform and in fact vary according to gene function. Balancing selection at immune system loci can act to sustain a high level of functional diversity relative to other gene classes (Hughes et al., 2005) and provides a mechanism by which diversity at antigen recognition sites may be maintained, providing significant host advantage upon immune challenge. In contrast, purifying selection acting at sites of nonsynonymous nucleotide substitution is manifest as reduced heterozygosity and involves the process of elimination of variation with only slightly detrimental effects (Hughes et al., 2003).

C. SNPs in health and disease It has been estimated that 50,000–200,000 SNPs may be biologically important (Chanock, 2001; Risch, 2000; Sachidanandam et al., 2001). Nucleotide substitutions in the genome have the potential to directly contribute to disease pathogenesis, acting in a variety of ways depending on where they occur. Gene-centric SNPs can have serious consequences for the function or structural stability of a protein if they cause its primary structure to change. Exonic SNPs that lead to amino acid substitutions are referred to as “nonsynonymous.” Exonic SNPs are the best characterized class of genetic polymorphism; they are subject to detection bias and their functional effects are often readily assayable. The relative severity of an amino acid substitution may be predicted by consideration of the

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biochemical properties of the side chains in question. Reference tables and algorithms (e.g., SIFT and PolyPhen) have been developed to aid investigators in assessing the significance of amino acid substitutions (Grantham, 1974; Ng and Henikoff, 2003; Ramensky et al., 2002). Many investigators choose to prioritize the analysis of nonsynonymous SNPs in their genetic association studies, on the basis that they may be extremely biologically significant. Nucleotide substitutions in the protein-coding portions of genes sometimes result in the premature insertions of codons that cause the termination of protein translation. These often become alleles that are effectively null because their transcribed mRNA is rapidly degraded by nonsense mediated decay (LykkeAndersen, 2001). SNPs occurring in the exons of genes that do not alter protein primary structure are called “synonymous.” Historically, while of interest to population and evolutionary geneticists, synonymous SNPs had been thought to be functionally uninteresting. Recent experimental evidence has shown, however, that they can effect mRNA stability (Capon et al., 2004; Wang et al., 2005) and alter splicing signals in genes; the latter mechanism is known to be involved in androgen-insensitivity syndrome, Glanzmann thrombasthenia, and cerebrotendinous xanthomatosis (Chamary et al., 2006). SNPs in introns, regulatory, and gene-distant regions can also be functionally important, primarily by affecting gene regulation. A relatively common variant (MAF of 1–2%), G21210A, in the 3 prime UTR of the prothrombin gene, F2, increases its expression, and carriers of the minor allele are at significantly increased risk for venous thrombosis (Poort et al., 1996). SNPs in the upstream untranslated region of neuregulin 1 have been associated with schizophrenia and, in particular, with expression levels of splice variants of the gene (Law et al., 2006). Indeed, SNPs that occur in apparent gene deserts have been associated with disease risk, three studies having independently identified and validated variants on chromosome 8 that increase susceptibility to prostate cancer and that are located 250 kb away from the nearest gene (Gudmundsson et al., 2007; Haiman et al., 2007; Yeager et al., 2007). In some cases, genetic variants may mediate protection from a particular disease. In the field of infectious diseases especially, there are a number of examples in which the success of a pathogen is subject to the genetic makeup of its host. Hope within the HIV research community was triggered by the discovery that a deletion variant of the chemokine receptor gene, CCR5, is highly associated with increased resistance to HIV infection, even in the face of multiple exposures to the virus (Liu et al., 1996). Similarly, SNPs in CCR5 and other chemokine receptor genes have been shown to be associated with disease progression, substantially waylaying the onset of AIDS (O’Brien and Nelson, 2004; Smith et al., 1997).

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D. Other categories of genomic variation There are many alternative classes of DNA variation that can have an impact on human health. Short tandem repeats (STRs) and variable number tandem repeats (VNTRs), collectively termed microsatellites, are head to tail repeats of multiple copies of a sequence motif, with STRs comprising a smaller number of individual bases than VNTRs. They are often extremely heterogeneous within a population and as such are useful for mapping purposes and for establishing relatedness. Large expansions of trinucleotide repeats can lead to genomic instability, the classic example being fragile X syndrome. A dinucleotide repeat (DG8S737) on chromosome 8 has been shown to be strongly associated with prostate cancer in African-Americans (Cheng et al., 2008; Freedman et al., 2006), though its functional importance has yet to be established. Whether or not modest variation in STR and VNTR length impacts on disease remains to be determined, though evidence suggests that some may act as binding sites for nuclear proteins (Richards et al., 1993). Structural variants comprising large regions of variable copy number occur in the human genome (Iafrate et al., 2004; Sebat et al., 2004) and can have MAFs>1%. Copy number variants (CNVs) therefore comprise part of the common genetic variation in a population. It has been estimated that a pair of individuals from a population will differ by a minimum of 11 CNVs (Sebat et al., 2004). The technology required to detect and assay CNVs has not reached a similar level of accessibility and versatility as for that of SNPs; this is reflected experimentally in a lack of overlap between publications describing CNVs, largely due to differences in assay methodology (Eichler, 2006). CNVs may encompass entire genes including promoter regions (Iafrate et al., 2004) and therefore may have an impact on phenotype. CNVs can have dose effects; the CCL3L1 gene duplication in HIV highly exposed individuals is a fine example of how varying gene dosage can alter host susceptibility to infection (Gonzalez et al., 2005). CCL3L1 copy number is inversely correlated with HIV susceptibility. We can be certain that complex disease phenotypes will involve genetic contributions from both SNPs and CNVs, but resolving those of the latter will be slower in the immediate future because of a comparative lack of available analytical resources. Insertion and deletion polymorphisms, ranging in size from a few to several thousand kilobases of DNA, often appear to be in strong linkage disequilibrium (LD) (see below) with surrounding SNPs (Hinds et al., 2006; McCarroll et al., 2006). Existing repositories of SNP data may be explored for clues as to the whereabouts of insertion and deletion polymorphisms because they often leave telltale traces, including deviation from Hardy-Weinberg equilibrium (HWE) (McCarroll et al., 2006). Indeed, it may be prudent to reevaluate past association study data in which SNPs excluded on the basis of deviation from

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genotypic proportions expected under HWE because this may indicate underlying structural variation (Wittke-Thompson et al., 2005). Plans are under way to comprehensively map population-wide structural variation (Eichler et al., 2007).

III. UTILIZATION OF GENETIC VARIATION IN GENE MAPPING STUDIES The goal of disease gene discovery projects is to identify biologically functional variants in sets of genes. However, it cannot be overemphasized that the numbers of such variants are vastly overshadowed by those of functionally silent SNPs and it is these which are of most relevance to the discussions that follow. SNPs can serve as surrogate markers for functional variants when mapping disease genes and this has fueled much of the drive toward characterizing and understanding genomic variation. A clear distinction must be drawn between SNPs with biological function and those used solely for the purpose of mapping because they are utilized differently in genetic association studies (Fig. 1.1). Historically, much emphasis has been placed on the investigation of candidate SNPs, driven by a specific hypothesis. But, with the rapid expansion of the characterization of common variants, the concept of “SNPs as markers” has emerged as the primary approach, partly because so few SNPs have been adequately characterized in laboratory evaluations. By analyzing and assaying the distribution of marker SNPs, we can capture the impact of functional ones in proximity. Two main approaches have been used to identify disease-causing genes, namely linkage analysis and association studies. Both methods are similar in that they use genetic variation to mark genomic loci and then attempt to detect cosegregation of marker and disease. A sine qua non of any disease mapping study, whether by linkage or association, is the knowledge of the stable position and frequency of the markers that are to be used, which can be a daunting challenge in the context of the rapid evolution of content, knowledge, and tools for cataloging and display. Initial efforts to discover, validate, and catalogue SNPs were gene-centric. APOE was one of the first targets of attempts to build high-density SNP maps for association studies in complex disease (Lai et al., 1998). Subsequently, large-scale gene resequencing projects have been established in an effort to characterize genetic variation within genes of interest for a number of diseases. The SeattleSNPs discovery resource aims to resequence genes involved in inflammatory processes (http://pga.gs.washington.edu/), whereas the Environmental Genome Project focuses upon the genetic components of diseases with a clear environmental component (Wilson and Olden, 2004). Of particular interest to cancer molecular epidemiologists is the SNP500Cancer project (Packer et al., 2006) maintained by the NCI Cancer Genome Anatomy Project (http://cgap.nci.nih.gov) that aims to resequence genes of significance in cancer

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i a

b

c

d

e

f

d

e

f

e

f

ii Direct test

a

b

c

iii Indirect test

a

b

Indirect test

c

d

c

d

iv 1 2 3

a b

f e

Figure 1.1. Direct versus indirect association testing. Part (i) shows six common SNPs as they would be represented in a population sample. SNP-c is responsible for conferring a disease phenotype upon carriers. In a direct test (ii), SNP-c would be directly assayed and tested for association with the disease, perhaps based on prior evidence of structural or functional consequences of variation at this site. In contrast, the indirect approach (iii) is agnostic with regard to functional variation. The assayed markers need only be in LD with the causative variant to achieve a signal of association. The caveat with this method is that care must be taken to type the appropriate markers needed to ensure thorough coverage of a given region. In the hypothetical example shown, tests of association between disease status and genotype at SNP-b, SNP-e, or SNP-f would prove nonsignificant. Only SNP-a and SNP-d are indirectly associated with the disease. The reason is shown in part (iv) that illustrates the concept that SNPs arise on independent haplotypic backgrounds and that many common haplotypes exist at a given locus (three are illustrated in the example, but in reality many more are likely to be present). If we assume that SNP-c arose on haplotype 1, we can see that assaying the SNPs that define haplotypes 2 and 3 will not be useful in demonstrating an association of this locus with the disease. Instead, to fully analyze this region, we must assay at least one haplotype “tagging” SNP from each of the observed haplotypes.

in four ethnically diverse populations. A review of a small number of the most significant SNP databases, along with a brief outline of their relative merits, can be found in Table 1.1.

Table 1.1. Widely Used SNP Data Repositories Database dbSNP

HapMap

SNP500

Notes

No. of SNPs

Population

Web url

References

NCBI repository for SNP data from (at present) 35 organisms. It includes small insertion/deletion polymorphisms. No stipulation as to minimum MAF, therefore many SNPs are potentially singletons. International effort designed to catalogue common human genetic variation across the genome in four ethnically distinct populations. Its primary purpose is to aid in the identification of haplotype-tagging SNPs that may be used to facilitate association study design and as such it is of great value to medical geneticists. In addition, it has yielded much information regarding the evolutionary genetics of populations. The SNP500 database is home to resequencing data from genes thought to be of importance in cancer. It aims to provide a framework of use to molecular epidemiologists in the design of cancer-based association studies. Validated sequencing and genotyping assay conditions are openly available from the SNP500 website and data may be extracted preformatted for use in a number of genetic analysis programs. There is a heavy SNP selection bias in favor of putative functional polymorphism and as such, SNP500 is almost entirely gene-centric.

>10 million human SNPS, 4.8 million validated

Diverse—no restriction on population

http://www.ncbi. nlm.nih.gov/ projects/SNP/

Sherry ST, et al. Nucleic Acids Res. 2001; 29: 308–311

>5.8 million

4 populations; 30 Yoruba trios, 30 Caucasian trios, 45 Chinese individuals, and 45 Japanese individuals

www.hapmap.org

International HapMap Consortium Nature. 2005 Oct 27;437 (7063): 1299–1320.

>13800 (updated daily)

102 individuals from 4 ethnically diverse groups

http:// snp500cancer. nci.nih.gov/ home_1.cfm

Packer et al. Nucleic Acids Res. 2006; 34: D617–D621

(Continues)

Table 1.1. (Continued ) Database Gene SNPs/The Environmental Genome Project (EGP)

Seattle SNPs

HGMD

Notes The premise of the EGP is to identify polymorphic variation in candidate genes that are believed to be at the interface between genetics and response to environmental stimulus. Approximately 500 genes drawn from cell cycle, DNA repair, apoptosis, and signaling, among others, have been chosen for inclusion. It is hoped that the EGP will be valuable in the elucidation of the genetic components of diseases with strong environmental etiology. Concentrates on genes with relevance to inflammation, but also clotting and heart lung and blood-related phenotypes. Provides assay conditions and resources for assay design. This database is particularly useful for physicians, researchers, and genetic counselors. It aims to collate data on genetic variation pertaining to human disease. About 70% of the lesions described are SNPs, but the remainder comprises the full mutational spectrum, from small indels to gross chromosomal abnormalities. The mutations are germ line in nature; somatic and mitochondrial variants are excluded. Important to note that the HGMD relies on the opinion of submitters as to the pathogenic significance of their entries and as such there are likely to be many nonfunctional polymorphisms in the database.

No. of SNPs Approximately 30,000

Over 30,700

More than 50,000 entries, approximately 35,000 SNPs

Population

Web url

90 sample population from the polymorphism discovery resource of the Coriell Repository including European, African-Americans, Mexican, Native Americans, and AsianAmericans 48 African-Americans and 47 Americans with European ancestry

http://www. genome.utah. edu/genesnps/

Wilson and Olden Mol. Interv. 4: 147–156

http://pga.mbt. washington. edu/

Na

http://www. hgmd.cf.ac.uk

Stenson PD, et al. Hum Mutat. 2003 Jun;21 (6):577–581.

No restriction on population

References

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IV. MAPPING COMPLEX DISEASE GENES USING ASSOCIATION A. Linkage and association: Out with the old and in with the new? A great proportion of the success observed in Mendelian disease mapping was due to the strong heritability of the traits in families and the fact that mutation of a single gene was the driving force behind disease pathogenesis; in almost all instances, a strong genotype–phenotype correlation could be drawn. Genetic linkage analysis (Elston, 1995; Ott, 1999; Risch, 1991; Teare and Barrett, 2005), in its various guises, became established as the method of choice for finding disease-associated genes and at the beginning of the new century, its success is compelling, with over 1200 Mendelian disorders having been identified (Hamosh et al., 2005). Buoyed by these remarkable achievements, many geneticists turned their attention to the pressing problem of complex diseases that pose a much greater burden from a public health point of view. Unfortunately, linkage analysis did not fare well when applied to diseases resulting from moderate genetic contributions from multiple loci. Risch and Merikangas (1996) published a seminal paper highlighting the shortcomings of the linkage approach when applied to complex disease. By conducting simulations of hypothetical diseases with predefined genotypic risk and causative allele frequencies, they were able to show that studies of association in populations of unrelated subjects were more powerful than linkage and also that, assuming individual genes implicated in complex disease each contribute modest risk, linkage methods will rarely detect effects in study samples of the size typically available. Although there have been isolated cases of success such as in the identification of variants in the ALOX5AP gene that confer increased risk for myocardial infarction and stroke (Helgadottir et al., 2004), these are the exception, and it is unlikely that many complex disease genes will be found in this manner using linkage analysis. Association testing is the preferred method in the situation where a disease is caused by a small number of genes, each with low to modest contribution. The promise of association analysis is founded in the demonstration that sample size can be reduced dramatically in comparison to that required for linkage, to within realistic ranges, and yet sufficient power to detect small genetic effects can be achieved (Morton and Collins, 2002; Risch, 2000; Risch and Merikangas, 1996). Genetic association testing most commonly uses unrelated, population-based cases and controls. The principle of association is simply to determine if there is a statistically significant difference in frequency of one or more genetic markers between the two groups. If this is shown to be the case, it is possible that the marker may either be causative, but it is more likely that it is closely associated with the causative mutation (Rothman et al., 2001). Association testing depends on the supposition that the variants contributing to

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common diseases arise on ancestral genetic backbones that are shared by a large proportion of those affected. This is the basis for the common disease, common variant hypothesis of complex disease (CDCV) (Reich and Lander, 2001). Metaanalysis of over 300 independent but overlapping studies testing 25 reported associations concluded that common variants were most likely to be responsible for a significant number of the positive findings (Lohmueller et al., 2003). The impact of rare variants must not be discounted; a small number of recent studies have highlighted the importance of population-based resequencing for comprehensive association analysis (Cohen et al., 2006; Romeo et al., 2007). Until the recent GWAS revolution, there have been few cases where the reality of association study performance lived up to predictions. Analysis of candidate gene association studies highlights the paucity of confirmed findings; in fact, only a handful of associations from over 600 studies have been replicated more than twice (Hirschhorn et al., 2002; Lohmueller et al., 2003). The advent of whole genome scans has spawned the opportunity to pursue sets of candidate genes or regions marked by the GWAS and so in this regard, we will never leave candidate gene studies behind.

B. Genetic association testing: The direct approach Genetic association may be tested either directly or indirectly (see Fig. 1.1). Direct association testing assumes that the polymorphism under examination is itself the disease-causing variant. This assumption poses the problem of how to sift through the millions of SNPs that have been catalogued and choose an appropriate subset for study: there are simply too many SNPs in the genome to consider testing each and every one. Instead, investigators often select variants with known or predicted functional consequences, perhaps changing protein structure or regulating gene expression, because it is easy to envisage how these might contribute to disease processes. The chance of success may be greatly improved if candidate genes, perhaps implicated in disease pathogenesis by nature of accompanying experimental evidence, can be identified. Such an example is the association of the NAT2 slow acetylation genotype in smokers with bladder cancer (Garcia-Closas et al., 2005). Biological plausibility for this association comes from the fact that aromatic monoamines, which are a constituent carcinogen found in cigarette smoke, are detoxified by N-acetylation. Subjects with the NAT2 slow acetylation genotype have an increased overall risk of bladder cancer—a finding which, crucially, has been replicated multiple times. Recently, a candidate gene approach has yielded promising results for type 1 diabetes, in which immune deregulation is suspected, strong association to the CD25 locus being demonstrated in a large population-based case control study (Vella et al., 2005) and in the replication of highly significant findings in PTPN22 for the same disease (Bottini et al., 2004; Smyth et al., 2004) and in myocardial infarction where

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association with LTB4 in the leukotriene pathway has been reported (Helgadottir et al., 2006). The candidate approach is heavily biased by biological intuition and the overwhelming limitation of the direct testing approach is that the a priori probability of testing the correct SNP within the correct gene is very small. Current awareness of the biological functionality of nonprotein encoding genetic variation makes choosing SNPs solely on the basis of coding potential seem rather outdated. Nonetheless, while it is extremely straightforward to identify exonic and splice boundary SNPs in a gene of interest, methodologies for prediction of functional intronic or regulatory SNPs are in their infancy. The promise of comparative genomics in this area is currently being evaluated; by identifying regions of high similarity between homologous genes or genomic regions in different species, it is possible to accentuate conserved noncoding sequences (Bejerano et al., 2004, 2005). It is hypothesized that many of these are likely to be domains of functional importance and that they should be considered as higher priority candidates in which any observed variation should be assayed for association. Of great utility in this approach is the bioinformatics portal at the University of California Santa Cruz Genome website and the Vista comparative genomic browser (Frazer et al., 2004; Hinrichs et al., 2006; Kent et al., 2002). Direct testing may be a satisfactory strategy when applied to one or a few genes with a high prior involvement in the pathogenesis of a given disease. But, a consequence of their inherent bias is the publication of associations that are of moderate statistical significance and which subsequently fail to replicate. Multicenter studies using pooled samples may be a solution to this problem. In a recent Lancet Oncology article, Rothman et al. (2006) describe an association study designed to test the hypothesis that variations in immune and inflammatory response genes influence susceptibility to non-Hodgkin lymphoma. Focusing on a small number of variants, each with putative functional significance, the authors present evidence of association of variants in TNF and IL10 with diffused large B-cell lymphoma. The findings presented were highly significant in the primary pooled analysis. However, had a consortia-based approach not been adopted, it is likely the overall significance would not have been determined until a later metaanalysis was performed. The article also serves as an example of how study power may be improved by multicenter efforts with concomitant reductions in type I error.

C. Genetic association testing: The indirect approach As stated in the preceding section, the odds of selecting the true causative SNP for direct testing in an association study are, generally, impossibly low. The alternative is to genotype subsets of SNPs that exploit correlation between markers, thereby reducing redundancy while providing comprehensive coverage of interesting loci. Indirect study designs offer the opportunity to map disease genes, while remaining agnostic with regard to function, by detecting causal

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variants by proxy as a consequence of the correlation between a marker SNP and the true functional variant. Intermarker correlation is slowly eroded by recombination (International HapMap Consortium, 2005; Reich et al., 2002) and markers on the same chromosome that remain strongly associated with one another in the face of such recombination are said to be in LD with one another. The patterns of LD in present day populations are the result of meiotic events that occurred in previous generations. In populations of unrelated individuals, LD deteriorates rapidly as the distance between markers increases; the collective population-wide effects of recombination diminish LD such that it is maintained only over relatively short genomic regions. When LD is plotted across the genome, it appears to create blocks of common genetic variation separated by hotspots of recombination (Myers et al., 2005). Each haplotype block is characterized by having relatively low haplotypic diversity in a given population. At present, there is no evidence for the existence of mechanisms that regulate the size of haplotype block boundaries, although the size and distribution of haplotype blocks varies between populations (Conrad et al., 2006; International HapMap Consortium, 2005; Reich et al., 2001). In general, the average block size in African populations is smaller than for other populations studied (e.g., North European Caucasians or East Asians). This is the result of an ancestral population bottleneck event that occurred during the migration of modern humans out of Africa; reductions in population size led to diminished genetic diversity within that population. Some haplotypes may be relatively large, extending over hundreds of kilobases, evidence that parts of the genome are perhaps relatively protected from recombination. Initially, SNP discovery efforts were needed to characterize common variation at a locus of interest; this was usually achieved by resequencing in small numbers of individuals. Thankfully, with the advent of the HapMap (International HapMap Consortium, 2005), this time-consuming and expensive practice has become unnecessary for first pass analysis and currently is primarily reserved for fine mapping. The main objective of the HapMap was to genotype SNPs with sufficient density across the human genome, eventually achieving a resolution of one SNP in every one to two kilobases. Crucially, three ethnically diverse populations were included in the study. The patterns of LD in the genome vary according to population genetic history and it is important therefore to ensure that the appropriate reference population be selected when using SNP repository data in pursuing an indirect testing strategy. It is critical to consider the applicability of data from HapMap to other populations. In this regard, the transportability of markers should be assessed prior to conducting the full scale analysis (Cullen et al., 1997; de Bakker et al., 2006; Gonzalez-Neira et al., 2006; Ribas et al., 2006; Smith et al., 2006; Willer et al., 2006). This systematic approach of the HapMap in the annotation of common variation has provided the genetics community with the means to select highly informative sets of SNPs

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to efficiently interrogate a region of interest. In addition, it has provided an invaluable resource for an unprecedented examination of the evolutionary history of human populations (Conrad et al., 2006).

D. tagSNPs Knowledge of the nature of LD in the human genome as gleaned from the HapMap has enabled the selection of minimally redundant panels of SNP markers that can be used in indirect genetic association studies. Called tagSNPs, their aim is to significantly reduce the marker genotyping burden required for a typical association study (Johnson et al., 2001; Sebastiani et al., 2003). Carlson et al. (2004) developed a “greedy” algorithm that groups SNPs according to pairwise correlation (see below) into bins for tag selection; a high performance variant of this algorithm is incorporated in the NCI’s Tagzilla package (http://tagzilla.nci.nih.gov) that has the ability to select a genome-wide panel of tag-SNPs using HapMap CEPH data in under 6 h, running on a standard desktop PC. A number of algorithms have been written solely for the purpose of identifying the tag SNPs and the reader is directed toward the review of Stram (2005) for detailed discussion. TagSNP selection will likely require further optimization, especially in admixed populations and for analyzing multimarker-based haplotype tags (e.g., where two or more SNPs act as proxy for a single untested SNP) (de Bakker et al., 2005).

E. Quantifying LD in the genome Several measures of pairwise LD are routinely used when describing marker– marker correlation (Devlin and Risch, 1995) and are central to SNP tagging. The two most commonly used are D0 (standardized LD coefficient, D) and r2 (correlation coefficient). Both D0 and r2 have maximal values of one, indicating complete LD between markers in a two-SNP haplotype; values of less than one can be more difficult to interpret. A maximum D0 value of 1 is reached when less than the total of four possible two-SNP haplotypes is observed in a population. Alternatively, r2 is a direct measure of pairwise correlation and has several properties that make it particularly applicable to tag-SNP selection. For a value of one to be reached, it requires that only two of the four possible two-SNP haplotypes are observed. The values of r2 (and to a lesser extent, D0 ) often appear to fluctuate in a seemingly disparate manner when viewed linearly; though this seems somewhat counterintuitive, it can be explained by coalescent theory (Donnelly and Tavare, 1995). When designing indirect testing studies, r2 has the useful property that the sample size adjustments required to achieve the equivalent power of a direct test are a function of the inverse of the correlation coefficient (Pritchard and Przeworski, 2001; Table 1.2).

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Additional samples required (%)

1.0 0.9 0.8 0.7 0.6 0.5

na 11 25 43 67 100

F. Testing association using haplotypes Haplotypes are sets of alleles on chromosomes that are inherited together. They neatly encapsulate the genetic events that have taken place over time between common ancestor and the present day population. At some point in the past, mutations that influence disease susceptibility occurred on the backbone of a particular haplotype. Under certain circumstances, analysis of haplotypes may increase power to detect disease loci relative to that of single SNPs (Clark, 2004). If mutations at a given locus arise on a large number of independent haplotypes, rather than on one or a few that are common, the power of association-based studies will be reduced because they rely on a moderately low degree of allelic heterogeneity at the locus of interest (Pritchard and Cox, 2002). A possible solution to this problem may be to search for association primarily using haplotype analysis (Pritchard, 2001). Unlike SNP genotypes, an individual’s diplotype (pair of haplotypes) cannot easily be determined using molecular methods (Xu, 2006). Current DNA sequencing platforms generate reads of diploid sequence with which it is not possible to determine haplotype phase. Statistical algorithms for haplotype inference have been developed, as an alternative to direct experimental observation, that estimate haplotype probabilities from population-based genotype data (Clark, 1990; Excoffier and Slatkin, 1995; Stephens et al., 2001). Methods vary subtly by sensitivity to genotyping error rate, deviation from HWE, and various other inherent population genetic properties but in general all perform well and have been widely implemented (Marchini et al., 2006; Salem et al., 2005). It is important, however, that uncertainty in haplotype phase assignments be accounted for in haplotype based tests of association. The most appropriate method for testing haplotypes for phenotypic association is much debated. In general, there is no one size fits all solution. In some circumstances, such as when a single risk haplotype is thought to be present, it may be appropriate to collapse all but the risk haplotype into a single

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group and then compare the frequencies in cases and controls to that of the risk haplotype. In lieu of knowledge of the true risk haplotype, this process must be completed for all haplotypes in the group and so the procedure must incur a penalty for multiple testing. Alternatively, a single global test of association may be used, which is the preferred approach if multiple haplotypes contribute to disease risk, but with the caveat that power is adversely affected when the level of haplotype diversity is high. Recently, novel techniques that attempt to circumvent these shortcomings have been proposed (Li et al., 2007).

V. GENOME-WIDE ASSOCIATION STUDIES In a relatively short space of time, genetic association studies have progressed from the study of a small number of candidate genes to candidate pathways and now have finally reached the point at which the entire genome can be examined. This has been realized via synergism between technological platforms (Gunderson et al., 2005; Kennedy et al., 2003; Matsuzaki et al., 2004a,b; Steemers et al., 2006), novel sophisticated algorithms for data analysis, awareness in issues relating to the storage of the immense volumes of data generated, and the completion of the International HapMap project, an invaluable resource for tagSNP selection (de Bakker et al., 2006; Pe´er et al., 2006). Now in the relative aftermath of the first batch of GWAS studies, it is prudent to reflect on many of the issues that had given rise to considerable debate within the community. One of the major advantages of the GWAS approach is that, unlike candidate gene studies, it facilitates a hypothesis-free approach to genetic epidemiological investigations of common diseases. This has paid dividends in that novel loci have been identified in a wide spectrum of conditions, many of which are in genes that had not previously been considered to be involved in their pathogenesis (Manolio et al., 2008). Thus, new light has been shed on biological process relevant to disease. Sobering, however, is the observation of replicable associations in regions of the genome in which there are no known genes (Amundadottir et al., 2006; Gudbjartsson et al., 2007; Moffatt et al., 2007; Stacey et al., 2007), perhaps implicating mechanisms of long-range gene regulation that will require considerable effort to unravel. Now the challenge in the wake of such data is to unravel the biology underlying them; the real payoff for whole genome association studies will come when insights into novel mechanisms underlying health and disease can be established. In a typical GWAS, a daunting number of markers must be tested to ensure adequate coverage of the entire genome. Commercially available genotyping arrays have increased their content capabilities from numbers in the low 100,000s to 1 million or more SNPs. It has been estimated that approximately half a million SNPs will ensure a high degree of coverage of the Caucasian

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genome with substantial increases needed to attain a similar level of coverage in African and African-American populations (Barrett and Cardon, 2006). The majority of commercially available products for GWAS are composed of manufacturer-chosen SNPs, selected according to their suitability for LD-based indirect association testing. A small number of arrays allow for a certain amount of user-defined content in addition to the preselected SNPs. Regardless of the criteria for inclusion of a SNP on an array, the overwhelming factor in a GWAS study is the unparalleled capacity for data generation and the concomitant issues that are involved both in ensuring a consistently high level of data quality and in the need for statistical methodologies that are required to make sense of it. The requirement for robust raw genotype data cannot be overstated. Stringent quality control measures including completion rate by both sample and assay and genotype concordance between duplicate samples should be mandatory. Tests for deviation of genotype frequencies from Hardy-Weinberg proportions may be useful for the detection of systematic genotyping error. However, care should be taken because such departures may also be signatures of true association (Wittke-Thompson et al., 2005). Of particular concern is the observation that sample extraction procedures can introduce biases in genotype calls, as this has serious implications for studies that require samples from multiple sources to attain critical mass (Clayton et al., 2005). We have chosen not to labor upon analytic approaches specifically tailored toward GWAS as they have been well reviewed in a number of recent articles (McCarthy et al., 2008; Pearson and Manolio, 2008) and often are similar in all but scale to the methods used in candidate studies, which are briefly touched upon in the subsequent section. We would like though to emphasize what we feel are essential criteria for the validation of GWAS signals. The problem of statistical noise generated by conducting hundreds of thousands of tests for association is discussed below. Here, we will focus on standards that are of particular relevance to GWAS and which have been agreed upon by experts in the field, with the aim of minimizing the trend of publication of false positive reports that have traditionally dominated complex disease genetic epidemiology (Chanock et al., 2007). Replication of interesting findings in independent studies is currently the de facto standard approach in any genetic association study, GWAS or otherwise. Care should be taken to ensure the same criteria in replication studies for case-control selection so that comparable populations are utilized. Preferably, either the same SNPs or those in perfect LD should be genotyped as in the original report. Care should be taken to assess the raw genotypic clusters for highly associated SNPs and the genotype data should be assessed on a secondary platform. GWAS studies in particular may benefit from careful meta-analysis across studies and as such, investigators are strongly encourage to make genotyping data available to others, satisfactory to confidentiality agreements required to protect the identities of individual study

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participants. It is likely in future that the largest and best funded endeavors will incorporate distinct exploratory and multiple replication phases into single studies; the NCI’s CGEMS project (http://cgems.cancer.gov) (Yeager et al., 2007) (Hunter et al., 2007a,b; Thomas et al., 2008) is one such example of this approach and combines a prospective exploratory cohort with subsequent sequential validation of the top SNPs from each round of replication.

VI. STUDY DESIGN AND DATA ANALYSIS A. Introduction Study designs for genetic association testing follow closely the patterns laid out by traditional epidemiology. Although simple case-control types are often adopted, some may adopt nested or prospective approaches. The ability to generate substantial numbers of genotypes has created a requirement for robust statistical methods that address the hypotheses underlying the study. The simplest approach in association analysis is based on contingency tables and tests for differences between the observed versus expected allele frequencies of a marker between cases and controls and a null hypothesis of no association. The same approach can easily be expanded to consider genotype frequencies and this is perhaps more appropriate given the nature of genetic inheritance. Further adaption is possible so that specific genetic models may be tested, the most common being dominant, recessive, overdominant, and additive. Logistic regression models may be constructed if one wishes, as is likely in complex disease epidemiology, to incorporate environmental covariates into the analysis.

B. Type I error and the multiple testing problem In genetic epidemiology, the challenge of sorting true findings from false positives (type I error) is daunting. Chance false positive findings are the most likely cause of failure to replicate findings in follow-up studies of association (Colhoun et al., 2003). If we consider that thousands of SNPs may be tested in a study scrutinizing hundreds of genes in a candidate pathway or that hundreds of thousands may be tested in a whole genome association study, it quickly becomes clear that vast numbers of spurious associations will be detected at conventional thresholds of statistical significance. It is generally accepted that classical approaches to correct for multiple testing are too conservative in genetic epidemiology. Bonferroni-type corrections that aim to limit the possibility of accepting a single false positive association aim to minimize the study-wise error rate. In other words, the price for looking is steep; overly stringent penalization of p-values may lead to truly associated markers dropped from replication analysis.

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Some have argued that it may be better to downplay this problem on the basis that it will be easier to discredit false positive findings at a later date than to resurrect false negatives after they have been discarded. An alternative approach has been to weight genes according to the prior probability that they are biologically involved in disease pathogenesis, perhaps based upon knowledge of pathways or other functional evidence (Wacholder et al., 2004). False positive rate probability (FPRP) considers each test separately and does not exact a significant penalty for testing multiple hypotheses. It takes into account the power of a study and accounts for correlative information and is a measure of positive predictive value. In this regard, the FPRP is only as good as the subjective decision concerning the prior probability. Moreover, its merit lies in using ranges to determine if a hypothesis is noteworthy. Alternatively, and widely applied is the false discovery rate (FDR) that controls the expected proportion of type I errors in the overall group of rejected null hypotheses (Benjamini and Hochberg, 1995). The FDR limits the study-wise error rate but does not exact a high penalty for testing more hypotheses with low priors. The relative merits and shortcomings of three of these methods have been summarized in Table 1.3.

C. Additional sources of error Population stratification (substructure in the study population that leads to inflated type I error) in genetic association testing had been thought by some to be a considerable source for concern. Recent data from GWAS has largely waylaid this apprehension because it seems that stratification may be avoided by careful matching of cases and controls (Wellcome Trust Case Control Consortium, 2007). In populations without substantial admixture, the effect is small to nonexistent (Freedman et al., 2004; Wacholder et al., 2000). If present, it can be corrected with relative ease (Devlin and Roeder, 1999; Epstein et al., 2007; Price et al., 2006; Pritchard and Rosenberg, 1999). Whether the effect of cryptic relatedness, or different population genetics history, the challenge of population stratification is likely to be confined to populations with recent admixture. Biases in genetic epidemiology can be introduced by differences in ascertainment between cases and controls, sample handling procedures, and use of multiple genotyping platforms, among others. One must be highly selective with regard to the participant selection criteria, which regulate entry into a study. Thus, careful phenotype collection is crucial. It is notable that all published examples of irrefutable association and replication have involved conditions with standardized and widely adopted classification criteria (Manolio et al., 2008). In spite of the benefit of association versus linkage with respect to power, many studies remain only moderately powered to detect association because of suboptimal sample size. There may be considerable gains in power by combining multiple individual, studies and meta-analysis has been touted as a possible way

Table 1.3. Advantages and Disadvantages of Statistical Corrections for Type I Error Commonly Used in Genetic Association Studies Test Bonferroni correction

False positive report probability

False discovery rate

Description Derived threshold for significance determined by dividing the significance value for rejection of the null hypotheses,  (usually 0.05) by the number of tests conducted. Genome-wide association study Bonferroni corrected threshold of significance would be 510–7 for 100,000 SNPs.

Strategy to reduce the number of false reports of positive association by enabling biological credibility to be factored into the error correction. Dependent on observed p-value, prior probability of association and statistical power.

Defines a global probability threshold as a proportion of the number of expected incidences of type I error over the total number of rejections of the null hypothesis. Yields proportion of statistically significant findings that are actually false positives.

Advantages

Disadvantages

Ease of application

Treats each SNP in an association study as an independent test, making no allowance for LD between markers.

High stringency for acceptance

Allows for no weighting according to prior biological knowledge.

Threshold FPRP levels can be adjusted to suit study design

Potentially too harsh leading to inflated rejection of modest but real association. Difficulty in assessing prior probabilities for genes, pathways, or SNPs.

Sensible selection of prior probability ranges enhances power to detect modest genetic association Applicable to meta-analysis Adaptive to the study set under examination

Predicated on biological insight(s) not always available.

Less conservative than the Bonferroni correction

Does not take LD between markers into account. Does not consider prior probabilities.

Does not provide a “corrected” p-value.

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to achieve this (Ioannidis et al., 2006). The utility of meta-analysis has been comprehensively reviewed (Munafo and Flint, 2004). Meta-analysis has the potential to uncover significant associations from multiple studies which appeared insignificant when analyzed individually (Ntais et al., 2005; Vineis et al., 2001; Vogl et al., 2004). However, special care needs to be taken to minimize and account for heterogeneity between each study.

VII. SIGNIFICANCE FOR PUBLIC HEALTH A fundamental goal of the human genome project was to facilitate genomic medicine, both though the identification of novel targets for therapeutic intervention and by enabling so-called personalized medicine in which an individual’s genomic profile could be incorporated into diagnostic algorithms and treatment of disease. In reality, both of these objectives will likely take many years to come to fruition, at least in the setting of general practice. Although immensely exciting, it is crucial that enthusiasm to translate the findings from the first batch of GWAS from array to bedside be tempered by the need for caution in attempting to make risk predictions based on estimates generated from retrospective studies. Indeed, at the time of writing, the number of new loci that have been identified for any individual disease is low and identification of the full spectrum of independent variants is a long way off. Thus, for each of the diseases that have been studied, we currently have in hand a few variants which each explain only a very small proportion of a person’s overall risk. In addition, few of the studies so far have been designed with the intention of determining the nature of gene–environment interactions that are sure to be central in complex disease pathogenesis (Hunter, 2005). It is alarming therefore to note the rapid emergence of commercial enterprises that offer direct to consumer predictions of risk based solely on their individual genomic profile (Hunter et al., 2008). Such ventures should be regarded with a healthy dose of skepticism by the general public until the impact of new loci has been properly assessed in prospective studies. Of any of the currently reported loci, only those associated with age-related macular degeneration (AMD) (Edwards et al., 2005; Haines et al., 2005; Hughes et al., 2006; Klein et al., 2005), a late onset disease resulting in blindness, appreciably alter risk at levels that may be clinically relevant (Hughes et al., 2007). However, given that the interpretation of genetic profiles is epidemiologically complex (Ware, 2006), it seems prudent that these analyses be performed only under the direction of experienced physicians and genetic councilors. The potential for direct to consumer personalized genomic profiles to be misconstrued is such that legislation designed to tightly regulate their application both in commercial and clinical practice is urgently needed (Hunter et al., 2008; Offit, 2008).

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Screening for a limited number of genetic variants has, however, begun to filter into the clinical decision making process. Pharmacogenomics, the prediction of drug response and toxicity from genotype analysis, is the most prominent example (Roses, 2001). The anticancer drug CPT-11 is a clinically important agent whose efficacy is widely variable. This variability has become the focus of many pharmacogenetic studies (Ando and Hasegawa, 2005; Charasson et al., 2004; Nagar and Blanchard, 2006; O’Dwyer and Catalano, 2006). CPT-11 requires hydrolysis for metabolic activity and is degraded by members of the UDP glucuronosyltransferase 1 (UGT1) family before being excreted in the intestines, where it may be reactivated by -glucuronidase. This reactivation can induce intestinal toxicity. Polymorphisms in the UGT1A1 gene have been associated with increased incidences of diarrhea and neutropenia (Iyer et al., 1998). Many physicians advocate screening for UGT1A1 polymorphisms prior to treatment with CPT-11 so as to enable dose modification in an effort to reduce unwanted side effects associated with the drug (Maitland et al., 2006). Indeed, the FDA now recommends that reduced doses should be given to carriers of specific UGT1A1 variants. Similar approaches to other drugs are likely to be employed using individual genetic profiles in concert with traditional indices used to determine appropriate treatment regimens.

VIII. CONCLUDING REMARKS Understanding the forces that drive and shape genetic variation is central to our goal of elucidating the basis of common and uncommon diseases. The recent success of the GWAS approach has done much for the morale of those initially discouraged by its apparent lack of reproducibility. The last 5 years have seen much effort in the laying of a core set of tools to facilitate future such studies; their continuing maturation, coupled with advances in statistical methods, will likely yield many more significant findings. It would be somewhat naive to think that association studies will provide clarity for linking genotypes with phenotype in every complex condition. Elucidation of the environmental components of common disorders deserves equal merit and may prove to have an even greater impact on public health. Undoubtedly, the ability to make informed lifestyle choices and reduce exposures to harmful external stimuli will be much easier than influencing or altering one’s genetic makeup. Nonetheless, the groundwork provided by past research in the field of genetic variation and disease mapping by association should have a profound impact on the well-being of generations to come, especially if we are to realize the promise of personalized medicine (Collins, 1999). One of the ironies of personalized medicine is that to define the markers that one can apply to a specific individual, the science underlying

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the foundation of personalized medicine will be based on large-scale studies using populations. In this regard, genetics will continue to search for the dialectic between common markers and individual or unique risk.

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Genetics of the Framingham Heart Study Population Diddahally R. Govindaraju,* L. Adrienne Cupples,† William B. Kannel,‡ Christopher J. O’Donnell,‡ Larry D. Atwood,*,† Ralph B. D’Agostino, Sr.,†,‡ Caroline S. Fox,‡ Marty Larson,‡ Daniel Levy,‡ Joanne Murabito,‡,§ Ramachandran S. Vasan,‡,¶,|| Greta Lee Splansky,‡ Philip A. Wolf,* and Emelia J. Benjamin‡,¶,k *Department of Neurology, Boston University School of Medicine, Boston, Massachusetts 02118 † Department of Biostatistics, Boston University School of Public Health, Boston, Massachusetts 02118 ‡ NHLBI’s Framingham Heart Study, Framingham, Massachusetts 01702 } Section of General Internal Medicine, Boston University School of Medicine, Boston, Massachusetts 02118 ¶ Department of Cardiology, Boston University School of Medicine, Boston, Massachusetts 02118 k Department of Epidemiology, Boston University School of Public Health, Boston, Massachusetts 02118

I. Introduction II. The Study Population A. Demography B. Multigenerational cohorts and examinations C. Diversity of traits measured: Phenotypic, physiological, and environmental D. Multifactorial nature of the heart disease III. Phenotypic and Genetic Architecture of Complex Traits A. Inheritance patterns of CHD

Advances in Genetics, Vol. 62 Copyright 2008, Elsevier Inc. All rights reserved.

0065-2660/08 $35.00 DOI: 10.1016/S0065-2660(08)00602-0

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IV. Linkage and Association Studies A. Mapping with microsatellite markers B. Association studies V. Genotype–Environment Interactions VI. Ethical Issues VII. Prospects and Conclusions Acknowledgments References

ABSTRACT This chapter provides an introduction to the Framingham Heart Study and the genetic research related to cardiovascular diseases conducted in this unique population. It briefly describes the origins of the study, the risk factors that contribute to heart disease, and the approaches taken to discover the genetic basis of some of these risk factors. The genetic architecture of several biological risk factors has been explained using family studies, segregation analysis, heritability, and phenotypic and genetic correlations. Many quantitative trait loci underlying cardiovascular diseases have been discovered using different molecular markers. Additionally, initial results from genome-wide association studies using 116,000 markers and the prospects of using 550,000 markers for association studies are presented. Finally, the use of this unique sample to study genotype and environment interactions is described. ß 2008, Elsevier Inc. Nature is all that a man brings with himself into the world; nurture is every influence from without that affects him after his birth. Francis Galton (1890a, p. 9) Why should you, . . . put yourself to the trouble of being measured, weighed and otherwise tested? Why should I. . .and why should others, take the trouble of persuading you to go through the process? . . . A comparison of the measures made from time to time will show whether the child maintains his former rank, or whether he is gaining on it or losing it. Francis Galton (1890b)

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I. INTRODUCTION Coronary heart disease (CHD) has remained a major cause of morbidity and mortality in the United States, affecting nearly 13 million people and causing approximately 1 million deaths per year (Thom et al., 2006). Although the incidence of cardiovascular diseases (CVDs) has gradually declined since the 1960s in the United States (Cooper et al., 2000), it is reaching epidemic proportions in many countries of Europe and the developing world (Yusuf et al., 2001). In the 1940s, CHD was recognized as the leading cause of mortality in the United States accounting for approximately half of all deaths (Kannel, 1990). Nonetheless, knowledge of the factors that disposed individuals to CVDs was “virtually nonexistent” 60 years ago and was perceived to be an inevitable consequence of “aging or genetic predisposition” of individuals (Dawber and Kannel, 1999). Fortunately, the US Public Health Service recognized the necessity for understanding the causal factors of the epidemic and decided to establish a prospective longitudinal observational epidemiological study in 1947, in the town of Framingham, Massachusetts, in collaboration with the Massachusetts State Department of Health and Harvard Medical School. The “Framingham Study” was formally established in 1948 to identify factors that contribute to CVD (Dawber et al., 1951; Kagan et al., 1962; Levy and Brink, 2005). This study, nearly six decades later and now known as the “Framingham Heart Study” (FHS), is the longest running, multigenerational longitudinal study in medical history (Butler, 1999). It has helped identify factors, also called risk factors, that have cumulative effects (see below) on the manifestation of CVD. Indeed, the term “risk factor” was coined by Framingham investigators (Kannel et al., 1961). Framingham investigators have also elucidated the pathogenesis of atherosclerosis and thus have laid a firm foundation toward preventive cardiology (Kannel, 1990). Furthermore, the study has acquired an iconic status in public health and preventive cardiology and has been listed as the “fourth significant achievement in medicine” [after the development of antibiotic treatments, immunization against infectious diseases, and the understanding of the roles of vitamins (Anonymous, 1999)], and the second greatest discovery (behind electrocardiography) in that led to decline in the heart diseases through preventive measures (Mehta and Khan, 2002). The investigators of the original protocol of the “Framingham Study” recognized a wide range of variation among individuals in human populations in response to “stresses and insults” (Gordon and Kannel, 1970). Instead of focusing on just one or a few independent causal factors that might influence CVD, they took an integrated approach and hypothesized that CVD may arise from “multiple causes which work slowly within the individual.” However, family history for

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CVD received the highest importance among many variables selected for studying its manifestation among the participants (Dawber et al., 1951). In general, at least three major variables were assumed to contribute to the onset of CVD: constitutional (heredity) factors, conditioning (environmental) factors, as well as the length of time taken by the conditional factors to act on constitutional factors ultimately resulting in a clinically recognizable condition (Gordon and Kannel, 1970). Although the role of hereditary factors in the development of CVD was acknowledged from the very beginning of the Framingham study, genetic studies did not receive much attention until the late 1980s. In the last 20 years, however, a number of investigators have utilized the rich resource available at the study and have attempted to understand the genetic basis of CVD using various approaches. In this chapter, we briefly discuss: (1) some of the salient features of the FHS and (2) approaches taken by the Framingham investigators toward identifying the genetic bases of CVD and some of its risk factors.

II. THE STUDY POPULATION A. Demography The FHS is composed largely of whites of European descent. However, individuals from the Italian, Irish, and English ancestry are predominant in the sample. About 85% of the Original cohort (first generation participants; see below) was born in the United States or Canada, including 19% born in Framingham and another 40% born in other parts of Massachusetts. Thirty-five percent identify themselves with ethnic origins in the British Isles, including 15% from Ireland; another 19% are of Italian ethnicity, 32% of other Western European ancestry, 5% of Canadian, and 6% of Eastern European. Less than 4% are of non-European origins or of unknown ethnicity (Table 2.1).

B. Multigenerational cohorts and examinations The study was formally established from 1948 to 1953 in the town of Framingham, MA, located about 20 miles west of Boston. Approximately 10,000 individuals were found to be of ages 30–59 years from a total population of 28,000. It was determined that if 6000 individuals were invited into the study from the 10,000 in the target age range, about 5000 individuals would not only be free of CVD but also provide sufficient sample size for the analysis of factors contributing to the development of CHD among the selected individuals over a period of 20 years. In such a time span, approximately 400, 900, and 2150 would develop CHD at the end of 5th, 10th, and 20th year, respectively, from the initial

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Table 2.1. Geographic and Ethnic Identities of the FHS Participants 30 Geographic diversity

Ethnic diversity

Birth place

Percent

Ethnicity

Percent

Framingham Other regions of Massachusetts Other regions of New England Other US regions Canada England, Scotland, and Wales Ireland Italy Other Unknown

19.15 40.31 9.79 9.81 5.46 1.28 1.37 7.26 3.32 2.26

England, Scotland, and Wales Ireland Italy French Canadian Other Canadian Eastern Europe Western Europe Other Unknown

19.86 14.95 19.00 2.26 2.63 5.93 31. 77 2.67 0.94

Total

100.00

Total

100.00

examination. Therefore, all the households in Framingham listed in the town census were categorized by the number of eligible individuals, and every third household was excluded. Approximately 6600 individuals were so selected. As expected, the number was diminished by losses, deaths, and refusals. There were also 740 volunteers from the town of Framingham included. At the beginning of the study, 5209 people, men and women, joined from January 1948 through March 1953 (Kagan et al., 1962), of which 45% and 55% were men and women, respectively. A total of 5128 of 5209 these participants were found to be free of “overt CHD.” Thus, the group consisting of 5209 participants constitutes the “Original cohort” of the study. The participants would undergo examinations every 2 years (Dawber et al., 1951). The Offspring and Third Generation cohorts consisting of 5124 and 4095 individuals, respectively, were recruited in 1971– 1975 and 2002–2005, respectively. The children of the Original cohort and their spouses are included in the Offspring cohort. Participants in the Offspring cohort have been examined every 4–8 years. The Third Generation cohort was recruited from children of the Offspring cohort. The participants of the Original, Offspring, and Third Generation cohorts have been examined 29, 5, and 1 time, respectively, for a large number of variables that may have a bearing on CVDs (Figs. 2.1 and 2.2). Thus, most participants of the study are members of 754 extended pedigrees. These welldefined pedigrees consist of parents, children, grand children, cousins, avuncular cousins, aunts, and uncles and range in size from 3 to 230 individuals with a median of 9 (Fig. 2.3).

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1948

1958

1968

1978

1988

1998

2008

Original cohort: 29 exams every 2 years 1971

2008

Offspring cohort: 8 exams approximately every 4 years 2002

2008

Third-generation cohort: 1 exam Figure 2.1. Initiation and progression of examinations among three generations of participants in the Framingham Heart Study. Note that the frequency of examination varies among the Original, Offspring, and the Third Generation cohorts.

Original cohort (N = 5209) Spouse pairs (n = 1644 pairs) + other individuals (n = 1921) Ages: 28–62 years

Offspring cohort (N = 5124) Offspring (n = 3548) + offspring spouses (n = 1576) Spouse pairs (n = 1729 pairs) + others (n = 1666) Ages: 5–70 years

New offspring spouses (n = 103)

Third-generation cohort (N = 4095) Both parents in offspring cohort (n = 2944) 1 parent in offspring + 1 parent in new offspring (n = 296) 1 parent in offspring cohort (n = 850) 2 parents in new offspring spouses (n = 3) 1 parent in offspring + 1 parent in third generation (n = 2) Ages: 19–72 years Total number of participants = 14,531 Figure 2.2. Distribution of participants in each of the three generations included in the Framingham Heart Study.

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Number of families

180 160 140 120 100 80 60 40 20 0 3

11

19 50 90 130 170 Number of family members

210

Figure 2.3. Distribution of families in relation to pedigree sizes in the Framingham Heart Study.

C. Diversity of traits measured: Phenotypic, physiological, and environmental At the initiation of the study, a committee consisting of 11 physician– epidemiologists developed a list of criteria and measured variables that may have a “bearing on the development of (CVD” under the following 6 categories [see Dawber et al. (1951) for details]. 1. Medical history—family history of CVD among parents, siblings, and children, symptoms such as chest pain, sleeping habits, alcohol, and tobacco consumption. 2. Physical examination—aimed at detecting cardiovascular abnormalities and diseases as well as height, weight, chest, and waist circumference, thyroid enlargement, pulmonary disease, cardiac murmurs or gallops, blood pressure, liver enlargement, and varicose veins. 3. Chest X-ray examination. 4. Electrocardiogram using 12 leads. Electrokymographic tracing at 12 points on the cardiac silhouette. 5. Blood examination for hemoglobin, serum cholesterol, phospholipids, and glucose concentrations. 6. Urine analysis. This tradition of routine ascertainment of physical examination, lifestyle and habits, medical history, laboratory analysis, noninvasive, and end-point data has been applied to all three generations of participants (Table 2.2). The number of variables, however, has increased over time and varies from one examination to the next. For example, in the first examination, data were

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Table 2.2. Major Classes of Phenotypic Data Collected on the Participants of the FHS Population Data categories Physical examinations Lifestyle and habits Medical history Laboratory analysis Noninvasive Endpoints

Routine examinations Anthropometry, blood pressure, lungs, heart, abdomen, ABI, neurological, and cognition Smoking, alcohol, exercise, diet, and psychosocial factors Medications, hospitalization, diagnostic testing, and cancer Lipids, diabetes, kidney, novel biomarkers, and DNA ECG, echo, Holter monitor, carotid, vascular testing, PFT, brain and cardiac MRI, and computed tomography CVD, cancer, neurological, pulmonary, bone, and cause-specific mortality

collected on 30 major variables. Over time, the diversity and complexity of phenotyping has expanded due to additional discoveries made on the components of CVD. For instance, in recent examinations, the participants of the Offspring generation have undergone additional testing including carotid ultrasound, echocardiography, brachial reactivity, arterial tonometry, 6-min walk, ankle-brachial blood pressure measurement, pulmonary function testing; and subsets have received cardiac and brain magnetic resonance imaging, cardiac multidetector computed tomography, and bone densitometry (www.nhlbi.nih. gov/resources/deca/fhsc/docindex.htm). Such detailed examinations have led to further understanding of the precursors of CVDs. For example, gradual thickening of the left ventricle of the heart (ventricular hypertrophy) leads to cardiovascular morbidity and mortality. Using echocardiography, Levy et al. (1988) determined that 33% of men and 49% of women age 70 or older developed ventricular hypertrophy. Similarly, Wolf et al. (1991) determined that abnormal heart rhythms (atrial fibrillation) may cause cerebral emboli leading to stroke. In a recent survey, approximately 1500 variables were found to have been measured on the FHS cohort. However, not all traits have been measured on all of the individuals; hence, the number of phenotypes measured varies among individuals, examination cycles, and cohorts.

D. Multifactorial nature of the heart disease Several key factors either independently or cumulatively have been found to exert influence disproportionately to the development of CVD. These factors were designated as “risk factors.” The primary risk factors include age, systolic blood pressure (SBP), body mass index (BMI), total/high-density lipoprotein (HDL) ratio, diabetes, and smoking (Dawber et al., 1959; Kannel et al., 1961). Additional risk factors and their components including morphological (e.g., left ventricular (LV) hypertrophy; Kannel et al., 1969), physiological (e.g.,

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Table 2.3. Established major risk factors of Coronary Heart Disease in the Framingham Heart Study Population Modifiable Lipids: total cholesterol, HDL, LDL, and triglycerides Blood pressure Diabetes Obesity Sedentary lifestyle Alcohol intake Smoking

Probably modifiable

Fixed

Lipids: Lp(a), Oxidized LDL

Age

Left ventricular hypertrophy Glucose intolerance Hematological Stress

Sex Family history

LDL, low-density lipoprotein; HDL, high-density lipoprotein; Lp(a), lipoprotein-a. Source:Wilson (1994).

fibrinogen—Fbg; Kannel et al., 1987), and lifestyle (e.g., Posner et al., 1993) have been added over time. These are further categorized into modifiable, probably modifiable, and fixed risk factors (Table 2.3; Wilson, 1994, 1998). The Framingham investigators have assigned “weights” to these risk factors and have developed “prediction scores” to predict the development of CHD (Truett et al. 1967). These indices known as coronary heart prediction scores are robust and have been applied to both whites and African-Americans to predict risk of heart disease (D’Agostino et al., 2001). Distribution of various risk factors in all the three cohorts as well as between men and women is provided in Table 2.4.

III. PHENOTYPIC AND GENETIC ARCHITECTURE OF COMPLEX TRAITS Biological variation may be understood at two levels: phenotypic and genetic. Many of the CVD risk factors such as HDL-cholesterol (HDL-C), total cholesterol, and blood pressure are quantitative traits. The phenotypic variation of a quantitative trait may be represented by VP ¼ VG þ VE þ 2covGE, where G, E, and 2covGE are genetic, environmental and their interaction variances, respectively (Falconer and Mackay, 1996). An understanding of the genetic architecture of a quantitative trait requires knowledge of its inheritance pattern, association with other traits, and molecular characterization of genes that underlie the phenotype (Mackay and Lyman, 2005). These principles have been extended to discover the architecture of CVD and its components in the FHS population. DNA collection for genetic studies on each of the participants from the Original and Offspring cohorts was initiated in the late 1980s, continued during the 1990s, and was expanded to Third Generation participants at their first examination.

Table 2.4. Means and Standard Deviations (in parenthesis) of Certain Variables in the FHS Population Among the Three Generation Cohorts Cohorts Variables Age (years) Current smoking (%) Systolic BP (mmHg) Diastolic BP (mmHg) Hypertensive medication (%) Hypertension (%) BMI (kg/m2) BMI 30 kg/m2 (%) Blood glucose (mg/dl) Total cholesterol (mg/dl) HDL-C (mg/dl) Lipid lowering medication (%) Prevalent CVD (%)

Original Cohort 1948–1953 Men, N ¼ 2336

Offspring Cohort 1971–1975

Women, N ¼ 2873 Men, N ¼ 2483

44 (9) 78 136 (19) 86 (12) 0 45 25.8 (3.5) 12 82 (24) 221 (43)

44 (9) 41 135 (24) 84 (13) 0 39 25.4 (4.7) 15 82 (20) 221 (46)

4

2

37 (11) 45 126 (16) 82 (11) 4 26 26.4 (3.7) 15 106 (16) 201 (40) 44 (12) 1 3

Women, N ¼ 2641 36 (10) 44 118 (16) 76 (10) 3 13 24.0 (4.6) 10 99 (15) 192 (39) 56 (15) 0.3 1

Third Generation 2002–2005 Men, N ¼ 1912 40 (9) 19 121 (13) 78 (9) 10 13 27.9 (4.7) 26 99 (18) 193 (37) 47 (12) 11 2

Women, N ¼ 2183 40 (9) 16 113 (14) 73 (9) 7 8 26.0 (6.1) 21 92 (18) 185 (34) 61 (16) 4 1

Over the years, smoking, blood pressure indices (systolic and diastolic), and the incidence of hypertension as well as total cholesterol have decreased. Blood glucose level has increased, however. Prevalence of cardiovascular diseases has also declined substantially. BMI, body mass index; HDL-C, high-density lipoprotein-cholesterol; CVD, cardiovascular disease.

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A. Inheritance patterns of CHD

1. Family studies The fact that both morphological and disease traits cluster in families has been known to human geneticists for a long time (Galton, 1886; Garrod, 1902), and family history is a significant predictor of heart diseases (Friedlander et al., 1985). The Framingham investigators indeed recognized the fact that CHD “runs in families” (Kannel and Stokes, 1985; Kannel et al., 1979); yet the relative contribution of genetic factors and shared environment toward developing cardiovascular risk was debated because “family members eat at the same table” (Kannel and Stokes, 1985; Kannel et al., 1979). On the contrary, Havlik et al. (1979) reported significant correlations between parents and offspring and sibling pairs for blood pressure. They attributed the correlation between spouses to assortative marriages for age, body weight, and habits such as smoking and alcohol consumption. Similarly, Myers et al. (1990) demonstrated that CVD in parents could be an independent risk factor. Similar studies have been carried out at the FHS for other traits such as cardiac heart disease (Brand et al., 1992), lens opacities (Anonymous, 1994), stroke and hypertension (Reed et al., 2000), atrial fibrillation (Fox et al., 2004a), and heart failure (Lee et al., 2006). These studies clearly established that the CVD and its component risk factors are inherited form parents and offspring (Fig. 2.4; Lloyd-Jones et al., 2004), and hence show a strong genetic component.

8-year CVD risk/1000

140 120

Parental CVD Absent Present

100 80 60 40 20 0 1

2 3 4 Risk of cardiovascular disease (in quintiles)

5

Figure 2.4. Cardiovascular risk between parents and offspring in relation to quintiles of major risk factors: systolic blood pressure, body mass index, total to high-density lipoproteincholesterol, diabetes, and smoking (Lloyd-Jones et al., 2004). Offspring of parents with CVD tend to have higher incidence of heart disease and vice versa.

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Family studies point toward the aggregation and inheritance of diseasecausing factors among individuals within families. They do not, however, indicate if the mode of genetic transmission from parent to offspring is simple or complex. Segregation analysis, on the other hand, provides insights on whether the inheritance is Mendelian (simple) or complex. For example, using the FHS family data, Felson et al. (1998) reported the presence of a major recessive gene and a multifactorial component for generalized arthritis. On the other hand, pulmonary function was found to be governed by a polygenic component (Givelber et al., 1998). Interestingly, a number of risk factors appear to differ among men and women (Table 2.4), which could ultimately contribute to their susceptibility to CVD (Fig. 2.5; Hubert et al., 1983).

2. Heritability and genetic correlations The relative contribution of genetic and environmental factors on the expression of quantitative traits is determined using the index known as heritability. It represents the amount of phenotypic variability or variance explained by genetic factors and is estimated as a ratio of genetic to phenotypic variance. Either broad (H2) or narrow sense (h2) estimates are used for this purpose (Sham, 1988). Knowledge of heritability is useful in finding genes underlying a given trait using different mapping strategies (see below). In general, moderate to high

14 Men 12

Women

Percent

10 8 6 4 2 35

40

45

50 55 Age (Years)

60

65

70

Figure 2.5. Sex difference in susceptibility to cardiovascular diseases over 26 years in the Framingham Heart Study population (Hubert et al., 1983). Men tend to have greater incidence of cardiovascular disease.

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heritability has been reported for most traits examined (Table 2.5). However, variation of heritability estimates are also seen for various traits in the FHS sample (Table 2.5). For example, Brown et al. (2003) demonstrated a general Table 2.5. Heritability Estimates of Some of the Traits that are Related to Cardiovascular Diseases and Aging

Trait

Narrow sense heritability

Abdominal aortic calcification Age at natural menopause Ankle-brachial index Body mass index Glucose Systolic blood pressure High-density lipoprotein cholesterol (HDL) Total cholesterol (TC) Triglycerides (TG) Low-density lipoprotein (LDL) TG/HDL ratio LDL/HDL ratio TC/HDL ratio

0.49 0.52 0.21 0.39 0.23 0.24 0.40 0.47 0.42 0.50 0.45 0.46 0.46

O’Donnell et al. (2002) Murabito et al. (2005) Murabito et al. (2006) Liu et al. (2003)

Bone mineral density Creatinine Estimated glomerular filtration rate Creatinine clearance

0.47–0.67 0.29 0.33 0.46

Karasik et al. (2003) Fox et al. (2004)

Hand osteoarthritis Heart rate variability Left ventricular mass Mean arterial pressure Carotid femoral pulse wave velocity Brachial artery diameter Flow-mediated dilation (%) Internal carotid intimal medial thickness Platelet aggregation QT interval White matter hyperintensity

0.28–0.34 0.13–0.23 0.24–0.32 0.33 0.40 0.33 0.14 0.35 0.48–0.62 0.25 0.55 (men) 0.52 (women) 0.44 0.35 0.24 0.28 0.30 0.14 0.44

Demisse et al. (2002) Singh et al. (1999) Post et al. (1997) Mitchell et al. (2005)

N-terminal proatrial natriuretic peptide Brain natriuretic peptide (BNP) Intercellular adhesion molecule-1 C-reactive protein Intercellular adhesion molecule-1 Interleukin-6 Monocyte chemoattractant protein-1

http://www.framinghamheartstudy.org/research/data/index.html

First Author (year)

Benjamin et al. (2004) Fox et al. (2003) O’Donnell et al. (2001) Newton-Cheh et al. (2004) Atwood et al. (2005) Wang et al. (2003) Keaney et al. (2004) Dupius et al. (2005)

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decrease in estimated heritability in 70- versus 40-year-old individuals (Fig. 2.6). Furthermore, Atwood et al. (2005) indicated that heritability for white matter hyperintensity (bright foci seen in the parenchyma of the brain and are associated with heart disease and stroke; they increase in number and size over time) decreased in women, but increased slightly in men with advancing age (Fig. 2.7). Relationships among morphological and biochemical traits are described using correlations. Genetic correlations among traits arise from pleiotropic effects of genes on multiple traits and/or linkage disequilibria among distinct

70

Age group

60 50 40 30 20 10 0 Height

Weight Age 40

BMI Age 55

SBP

Age 70

Heritability

Figure 2.6. Variation of heritability across age groups among four traits (Brown et al., 2003). Heritability declined over time for the traits shown.

1 0.9 0.8 0.7 0.6 0.5 0.4 0.3 0.2 0.1 0

All Females Males 40

60

50

70

Age group Figure 2.7. Variation of heritability for white matter hyperintensity (WMH) volume between males and females over time (Atwood et al., 2005). Heritability for WMH differs greatly between males and females at younger ages. However, while heritability increased slightly over the years for males, it decreased gradually for females.

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loci (Cheverud, 2001). Genetic correlations could also reflect allelic complexes at multiple loci as well as coadaptation (Churchill, 2006). Conversely, genetic correlations might indicate widespread association among loci, due to linkage and/or pleiotropy at the genomic level, that in turn could govern the integration of both morphological and disease-related traits (Churchill op cit). Phenotypic, genetic, and environmental correlations have been determined among five risk factors (cholesterol, HDL, SBP, triglycerides, and BMI) in the FHS (Table 2.6). The results indicate that the phenotypic and genetic correlations have similar magnitudes. In other cases, whereas the magnitude differed, the direction of the correlation was conserved. These results may be attributed to both genetic and environmental factors. For instance, both phenotypic and genetic correlations between cholesterol and triglyceride are 0.35 and 0.32, respectively. These suggest that the correlation may be due to linkage disequilibrium between the underlying genes that determine both cholesterol and triglyceride levels. Alternatively, while genetic correlation between BMI and HDL are negative ( 0.13), these traits showed slight positive relationship (0.03), suggesting that the association between these is affected by environment.

3. Physiological and molecular markers Phenotypes are linked to genes via biochemical pathways, and therefore, biochemical (bio) markers or biological traits provide logical surrogates to establish the relations between disease phenotypes and genotypes. These molecules or traits, also called endophenotypes or risk factors, in turn reflect the action of underlying genes and their expression patterns (Rice et al., 2001). Hence, measuring informative biochemical markers to predict the behavior of phenotypes is often favored in CVD (Vasan, 2006), as they simultaneously provide

Table 2.6. Genetic (above the diagonal) and Phenotypic Correlations (below the diagonal) and Environmental Correlations (in parenthesis) Among Five Risk Factors (Martin et al., 2003) Cholesterol Cholesterol HDL-C SBP TG BMI

– 0.12 (0.27) 0.03 (0.02) 0.35 (0.38) 0.08 (0.06)

HDL-C 0.06 – 0.03 (0.13) 0.34 ( 0.24) 0.20 ( 0.24)

SBP 0.04 0.22 – 0.10 (0.02) 0.16 (0.22)

TG 0.32 0.46 0.29 – 0.18 (0.29)

BMI 0.11 0.13 0.01 0.03 –

HDL-C, high-density lipoprotein-cholesterol; SBP, systolic blood pressure; TG, triglycerides; BMI, body mass index.

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insights on the links that may exist among phenotypes, genes, and their respective biochemical pathways. For example, activation of biochemical markers such as low-density lipoprotein (LDL), oxidized LDL, C-reactive protein (CRP), interleukin-6, -10, and -18 (IL-6, IL-10, and IL-18), Fbg, and tumor necrosis factor are associated with plaque formation in the arteries that eventually lead to acute arterial lesions prone to rupture (Vasan op cit). Biomarkers have been used to establish relations between biomarkers and risk for CVD in the FHS population. For example, Seman et al. (1999) reported a positive association between lipoprotein (a) cholesterol concentrations and CHD in men but not in women. Keaney et al. (2004) determined that ICAM-1 concentrations were associated with age, female gender, total/HDL-C ratio, BMI, blood glucose, smoking, and prevalent CVD. High concentrations of total homocysteine have been implicated in CVD (Arnesen et al., 1995) and dementia (Sheshadri et al., 2002). Similarly, Wang et al. (2002) reported a close association between the concentrations of CRP (a marker of inflammation) and carotid atherosclerosis, but the relationship was found only in women but not in men. In a comprehensive analysis involving nine biomarkers (CRP, Fbg, plasminogen activator inhibitor-1, aldosterone, renin, B-type natriuretic peptide, N-terminal proatrial nariuretic peptide, homocysteine, and urinary albumin/creatinin ratio) that are implicated in the onset of hypertension, Wang et al. (2007) found that the entire panel of markers were found to be associated (p ¼ 0.002) with hypertension. However, further statistical analysis showed that only three markers (CRP, plasminogen activator inhibitor-1, and urinary albumin/creatinin ratio) exerted disproportionately greater influence on the onset of hypertension relative to others in the panel, suggesting that abnormalities in multiple biological pathways antedate the onset of overt hypertension. In humans, different molecular markers have been employed to describe both genetic variation and to discover the genetic basis of phenotypic traits including complex diseases. These include allozymes (Harris, 1966), restriction fragment length polymorphisms (RFLPs; Botstein et al., 1980; Solomon and Bodmer, 1979), variable number of tandem repeats (Jeffreys et al., 1985), microsatellites (Weber and May, 1989), and, more recently, single-nucleotide polymorphisms (SNPs). Briefly, RFLPs are the products obtained by digesting the DNA molecules with restriction enzymes; microsatellites are two [e.g., (CA)n] to five [(TTTTA)n] repeat sequences of DNA found distributed throughout the genome and are known to be highly polymorphic. SNPs arise from mutations at specific nucleotides in the DNA molecule and represent the most abundant class of polymorphisms in the human genome [see Strachan and Read (2003), for details]. The Framingham investigators have utilized primarily three families of molecular markers—RFLPs, microsatellites, and SNPs—to establish associations between molecular markers and cardiovascular risk factors. For example, Fabsitz et al. (1989) tested the association between human leukocyte antigen and obesity

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on 348 individuals and found that the Bw35 allele was significantly associated (p ¼ 0.003) with obesity. Similarly, RFLPs (for restriction enzymes, MspI, PstI, SstI, PvuII, and XbaI) in the apolipoprotein gene cluster A-I, C-III, and A-IV were tested (Ordovas et al., 1991) on 202 patients with coronary artery disease and 145 normal individuals. They found that individuals with SstI had 38% greater concentration of triglycerides than the referents. Wilson et al. (1994) examined the relationship among the 2, 3, and 4 alleles of the apolipoprotein E locus in relation to CHD among 1034 men and 916 women aged 40–70. They found that 4 allele was associated with elevated LDL-cholesterol (LDL-C) concentrations, as well as CHD in both men and women.

IV. LINKAGE AND ASSOCIATION STUDIES The availability of pedigree information and heritability estimates on cardiovascular risk factors in the FHS has facilitated mapping complex traits using two well-known approaches: linkage and association. Linkage methods employ family information to make inferences about the relative positions of genetic loci that influence quantitative traits (quantitative trait loci; QTLs) in the genome. Discovery of QTLs has been accomplished using primarily two types of linkage analyses: model based (parametric) and model free (nonparametric). In the former, parameters such as the mode of inheritance of the disease, frequency of the causal allele, and its penetrance must be specified a priori. The likelihood of genetic linkage between two loci is determined by a logarithm of odd (LOD) scores. Briefly, a LOD score is defined as a ratio between likelihood that two loci are linked at a given recombination rate and the likelihood that the loci are unlinked at recombination of 0.5. When the two loci segregate independently, the recombination rate is 0.5; but it ranges between 0.0 and 0.5, if the two loci are linked. In general, for a Mendelian disorder, a LOD score of >3.0 is considered evidence for linkage (Sham, 1998). Parametric approaches have been successfully used for identifying the genetic basis of simple Mendelian disorders. Cardiovascular disorders reveal complex or non-Mendelian inheritance patterns that make it difficult to assign inheritance patterns (Jorde et al., 2006). Therefore, analytical approaches that do not require a priori definition of allele frequencies or mode of inheritance (also known as model-free analysis) are commonly used to map quantitative traits. This approach requires that the identity of specific alleles or set of linked alleles (haplotypes) that are inherited among relatives be identified, by means of identity-by-descent. In other words, identity-by-descent is central to model-free linkage analysis. Model-free approaches have been used at the FHS more extensively to understand the genetic bases of quantitative traits employing microsatellite markers.

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A. Mapping with microsatellite markers Approximately 612 microsatellite markers have been typed on the largest 330 pedigrees consisting of 1702 individuals belonging to generations 1 and 2 of the FHS. These data have been used to map genes underlying several CVD risk factors, including blood pressure, arterial stiffness, lipid traits, adiposity glycemic traits, circulating biomarkers (e.g., inflammation, natriuretic peptide), pulmonary function, renal function, and bone traits (Table 2.7). Besides identifying candidate loci for a number of risk factors, the availability of correlated traits and longitudinal data on families has facilitated FHS researchers to ask additional interesting questions. For example, does age variation influence the magnitude of LOD scores? Or does it lead to a shift in the location of a candidate gene region? Also, are several distinct yet correlated phenotypes influenced by the gene(s) located in a specific region? For instance, it is known that decreased HDLs are inversely correlated with high cardiovascular risk. Arya et al. (2003) mapped a region on chromosome 6q that influences both BMI and HDL-C. These traits showed very high genetic correlation suggesting the presence of common genes influencing both traits. They ran statistical tests to discover if the region contains only one gene that influences two traits (pleiotropy) or if two linked genes influenced these correlated traits. The results

Table 2.7. Chromosomal Locations of Quantitative Trait Loci and the Associated LOD Scores for Various Phenotypes Trait Blood pressure Body mass index Bone mineral density Hematocrit HDL3 cholesterol Hypertension Internal carotid artery Intimal medial thickness Monocyte chemoattractant Protein-1 (MCP-1) Obesity and HDL-C Plasma triglyceride Pulmonary function Waist circumference Weight change

Chromosomal location

LOD score

17q12 6q23-25 21q22.3 6q23-24 6q24.2 10q24.32

4.7 4.6 3.1 3.4 4.0 5.5

Levy et al. (2000) Atwood et al. (2002) Karasik et. al. (2002) Lin et al. (2005) Yang et. al. (2005) Guo et al. (2003)

12q24.33

4.1

Fox et. al. (2004b)

1q25.1 2q21.3 6q24.3 6q27 6q23 20q13.12

4.3 6.2 3.1 5.0 3.3 3.1

Dupuis et al. (2005) Arya et. al. (2003) Lin (2003) Wilk et al. (2003) Fox et al. (2004c) Fox et. al. (2005)

Only LOD scores above 3.0 have been listed.

References

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indicated that a putative major gene influenced both the BMI and HDL-C, suggesting pleiotropic gene action. Similarly, Lin (2003) reported a common region, 6q24.3, to be influencing two inversely correlated traits, plasma triglycerides and HDL-C levels. Atwood et al. (2002), on the other hand, performed linkage analysis on BMI measured across 28 years to determine the impact of measurement errors across age groups. The results indicated that although the magnitude of LOD scores varied across six measurements taken over 28 years, ranging from 0.61 to 3.27, all the regions across measurements mapped to 11q14 suggesting that at least one QTL in this region influences BMI. Thus, measurement errors do not influence the location of the QTL in the genome.

B. Association studies Linkage studies have been employed to map numerous genes underlying Mendelian diseases. This approach, however, is less powerful to map complex disorders as they are governed by many genes and the influence of each causal allele on the phenotype (allelic effects) is generally low. As noted earlier, parametric linkage approaches work best when the effect of the causal allele is large and least influenced by environmental factors. Complex traits, on the contrary, are greatly affected by environmental factors, making it more difficult to use linkage analysis. Risch and Merikangas (1996) proposed an alternative solution to this problem. They conjectured that association studies using a large number of markers (in the neighborhood of a million) may be more useful for studying the genetic bases of complex disease than linkage studies. In association studies, a comparative analysis of alleles between individuals that carry the disease and healthy individuals is carried out, with the important assumption that the marker may be embedded in the causal gene or close to it. Additionally, association studies may or may not require pedigree information and could also be performed using samples that are unrelated or family-based. This approach has been feasible by the discovery and deployment of the most abundant class of molecular markers—SNPs—for association studies (see below). Usually, two approaches are taken to establish an association between a putative causal site within a known gene (or any unknown site in the entire genome), with a given phenotype. Markers are identified at regular intervals along the length of the gene or across the genome, with the assumption that the markers so placed may be in linkage disequilibrium (LD) with the causal allele. In other words, information on how a marker can predict the presence or absence of disease-causing alleles or locus could be determined using a linkage disequilibrium approach. Briefly, linkage disequilibrium is an index of nonrandom association of two alleles on a chromosome in a population (Ardlie et al., 2002). If a new mutation occurs at any location of the genome, it is in complete linkage disequilibrium with the surrounding marker alleles. Among several measures proposed to

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measure linkage disequilibrium (Devlin and Risch, 1995), two methods, D0 (Lewontin, 1964) and r2 (Hill and Weir, 1994), are most frequently used.

Lewontin’s measure of linkage disequilibrium (D0 ) Supposing the frequencies (P) of alleles at loci A and B are PA, Pa, PB, and Pb, then linkage disequilibrium (D) is defined by: D ¼ PAB PAPB. Maximum value that D can have is determined by the allele frequencies. However, in practice, frequencies are obtained by arbitrary labeling of the alleles, which could lead to errors in the estimates of D. To avoid the dependency of D on allele frequencies, a normalized D or Dapos; (Dprime) is used. Accordingly, if D is positive (D > 0), the highest possible disequilibrium, Dmax ¼ minðPA Pb ; Pa PB Þ Alternatively, if D is negative (D < 0), Dmax ¼ minðPA PB ; Pa Pb Þ Thus, D0 ¼ D/Dmax. The sign of D0 is generally ignored, and therefore |D | is often used than D0 . Linkage disequilibrium is also defined as the square of the correlation coefficient (r2) between loci A and B. Accordingly, r2 ¼ D2/PAPaPBPb (Weiss and Clark, 2002). Strong LD between the marker and a causal allele (>0.8) is used as an index toward identifying a functional allele. Both of these two approaches have been used in FHS data, and some of these results are presented below. 0

1. Association of known polymorphisms in candidate genes with cardiovascular risk factors Causal polymorphisms within candidate genes that affect the cardiovascular pathway have been described in the literature. FHS investigators have typed the same polymorphisms in FHS participants to confirm or refute the previously published associations. Examples include the association between two polymorphisms in the estrogen receptor- gene (ESR2) with LV mass and wall thickness (WT) in women with hypertension (Peter et al., 2005). These polymorphisms showed significant association (p < 0.0007) with both LV mass and

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WT suggesting their role in LV remodeling. The L162 polymorphisms of the peroxisome proliferator-activated receptor- (PPARA) and plasma lipids were shown to be associated (p < 0.01) in relation to polyunsaturated fatty acid levels indicating gene–environment interaction (Tai et al., 2002). Mutations in the ATP-binding cassette transporter 1 (ABCA1) are known to cause a rare form of genetic HDL deficiency known as Tangier disease, in which extremely low levels of HDL-C and LDL-C are common. Tangier disease patients show depositions of cholesteryl esters in tissues throughout the body that predisposes them to heart disease (Sefarty-Lacrosniere et al., 1994). Brousseau et al. (2001) reported that one SNP (C3456C) in the ABCA1 exerted 2.71 time more risk (p < 0.004) of developing CHD relative to individuals that did not have this SNP in the FHS population. Additionally, SNPs in 200 genes of the cardiovascular pathway have been typed and association studies have been performed with the following six echocardiographic phenotypes of the FHS cohort: LV mass, LV internal dimension, LV WT, left atrial dimension, and aortic dimension (diameter, radius, and WT). Phenotype–genotype association and/or gene–environment interactions of 61 genes are presented in a grid form (http://cardiogenomics.med.harvard. edu/home; Levy et al., 2006). Occasionally, however, a single SNP may suggest weak or no association with a given phenotype, but several SNPs in linkage disequilibrium (also known as haplotypes) may improve the strength of association. For example, Kathiresan et al. (2006) found a triallelic haplotype containing C-T-A alleles of the CRP gene to be associated (p < 0.0001) with serum C-reactive concentration.

2. Genome-wide association studies Although linkage and candidate gene studies have revealed many potential regions and SNPs of interest, there have been relatively few successes in uncovering a comprehensive set of genetic variants responsible for common complex disease (Carlson et al., 2004; Todd, 2006). For example, in a meta-analyses of 301 association studies performed on 25 candidate genes implicated in complex diseases such as type II diabetes, hypertension, schizophrenia, and Alzheimer disease, Lohmueller et al. (2003) recorded that only 59 studies showed association at p < 0.05 level (versus only 15 studies expected by chance). Alternatively, Ioannidis et al. (2003) examined the results of 55 meta-analyses consisting of 579 small and large studies (sample sizes ranging from 700 to 19,000), and found that only 9 (or 16%) of genetic association could be repeated without bias. In 14 (26%) studies, the association was stronger than in subsequent studies. A limitation of candidate gene studies is that they are constrained by existing, often incomplete, knowledge of the pathophysiology of disease. Technological breakthroughs in high throughput genotyping using 100–500 thousand well-

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characterized, informative markers—SNPs—in combination with novel analytical techniques have opened the possibility of conducting genome-wide association studies as presented by Hirschhorn and Daly (2005). These approaches have also received an additional impetus from the success of the HapMap project (Altshuler et al., 2005; http://www.hapmap.org). The project was initiated to “create a resource that would accelerate the identification of genetic factors that influence medical traits” and was completed in 2005. The study included 269 DNA samples representing three major ethnic groups: Yoruba Africans (n ¼ 90), Han Chinese (n ¼ 45), and Japanese (n ¼ 45) (collapsed into one group; n ¼ 89) and a population from Utah (n ¼ 90). These samples were genotyped with 1,007,329 SNPs]. The discovery and replication of the association between CFH (Complement Factor-H) gene and age-related macular degeneration, using informative SNPs obtained thorough the HapMap, provided an early indication of the power of genome-wide association studies to accelerate gene discovery (Klein et al., 2005). Following such leads, the Framingham investigators have taken a two-tier approach to conduct genome-wide association in two separate studies using the Affymetrix chip technology. The first study was based on 116,000 SNPs; the second on-going study represents 550,000 SNPs provided by Affymetrix (see below).

a. 100K study in the FHS population In 2005, an Affymetrix 116K SNP genome-wide scan was conducted in about 1350 family members of the Original and Offspring cohorts of the FHS. Herbert et al. identified a common genetic variant (rs7566605) associated with BMI in the upstream of the transcription start site of INSIG2 (Insulin-induced gene-2) gene in the Framingham participants. They replicated the finding in four separate populations composed of individuals of Western European ancestry and African-Americans. The CC genotype of INSIG2 gene was associated with obesity in three different family-based samples and three studies of unrelated individuals (Herbert et al., 2006). These investigators have further identified 251 putative associations for additional phenotypic traits: BMI (50), DBP (24), SBP (24), LDL-C (18), triglycerides (15), VLDL cholesterol (32), plasma cholesterol (36), HDL-C (28), and blood glucose (24) (Herbert et al., 2007).

b. The SNP-Health Association Resource study In 2006, the National Heart Lung and Blood Institute has embarked on an ambitious collaboration with Boston University and Affymetrix to conduct a 550K genome-wide association study of 10,000 Original, Offspring, and Third Generation Cohort participants and to post the aggregate results at the NCBI “dbGaP” (http://www.nih.gov/news/pr/dec2006/nlm-12.htm) website.

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V. GENOTYPE–ENVIRONMENT INTERACTIONS The FHS has firmly established the role of environmental factors such as the use of tobacco (Doyle et al., 1962) and high intake of dietary fat (Posner et al., 1993) on cardiovascular phenotypes. Because genes are also known to interact with various environmental factors, their interaction may be reflected in the magnitude or in the direction of association. Polymorphisms in several candidate genes have been evaluated to determine their interaction with environmental factors. Examples include effects of dietary fatty acids on apolipoprotein A5 polymorphisms (Lai et al., 2006), fatty acid binding protein (FABP2) in relation to plasma lipids (Galluzzi et al., 2001), apolipoprotein E polymorphisms, and alcohol consumption (Corella et al., 2001). Ordovas et al. (2002) evaluated the relations between dietary fat intake and three genotypes of the 514(C/T) polymorphisms of the hepatic lipase gene (LIPC). They found a dose-dependent association of T allele with higher HDL-C in subjects consuming less than 30% of the energy from fat (Fig. 2.8). Also, the slopes formed by the genotypes in relation to energy intake gradients intersected each other reflecting the results shown in classical genotype–environmental interactions; slopes remain parallel to each other, if there is no interaction (Lynch and Walsh, 1998). These studies are providing valuable insights toward designing other large studies involving hundreds of thousands to millions of individuals (Couzin, 2007; Manolio et al., 2006).

1.6 P for interaction HL *fat 90% mating proficiency observed for various control males (including those in which this Gr driver activated UAS-tntI). Furthermore, the Gr68a/tnt males that did mate showed significantly longer-thannormal mating-initiation latencies (a time measurement that augmented the elementary scoring of “mating or not”). Both of these decrements were correlated with subnormal “courtship index” (CI) values obtained from observations of the toxin-impaired males paired with virgin females. [CI values have long been employed to measure overall courtship vigor involving male–female or male–male pairs of D. melanogaster, harking back to the studies of Hall (1978) and Siegel and Hall (1979).] “RNA interference” (aka inhibitory RNA, RNAi, or IR) was applied as a companion disruptor of taste sensations [via well-known molecular tactic that is reviewed, among a host of examples of such summaries, by Kavi et al. (2005) and Montgomery (2004)]. The idea in the current context is that “something else” within the PNS neurons in question could be responsible for the TNT effect. But when Gr68a-gal4 was combined with UAS-Gr68aIR (Bray and Amrein, 2003), males suffered similar courtship decrements: They took longer than normal to initiate the sequence and to start mating, as well as exhibiting lowerthan-normal numbers of wing vibrations and mating attempts, essentially the same subnormal behavior as that which was observed for Gr68a-gal4/UAS-tnt males. The effects on courtship of expressing neurally disruptive transgenes under the control of this Gr-gal4 driver appeared to be specific to these malespecific foreleg structures: Two other such Gr genes—Gr22e and Gr66a, which are expressed in numerous gustatory sensory neurons including those extending beyond the forelegs—led to mild (Gr22e) or no (Gr66a) mating-initiation or proficiency decrements when manipulated to drive UAS-tnt (Bray and Amrein, 2003). There is no overlap among the expression patterns in the forelegs for these three genes (Dunipace et al., 2001). For Gr22e’s part, the most widely expressed Gr gene known (encompassing ca 100 such neurons, distributed over the antenna, maxillary palps, proboscis, wings, and legs), the TNT-induced courtship and mating impairments were much less than those mediated by manipulation of Gr68a in context of its limited expression. All well and good, especially because the spatial pattern just noted is male-specific.

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However, these results do not easily fit with two sets of gustation-related findings—one contemporary and the other from long ago: The first stems from discovery of a small protein that is putatively secreted from nonneuronal cells associated with a subset of taste structures on the male forelegs (Xu et al., 2002). This CheB42a molecule was shown to be specifically contained within sheath cells surrounding taste neurons expressing the Gr68a gene (Park et al., 2006). Isolation of a Che42a deletion mutant (by imprecise excision of a nearby transposon that removed the 50 half of this gene) led to perhaps surprising observations that not only courtships performed by mutant males were undecremented (Lin et al., 2005), but also these flies attempted to mate sooner and more frequently with females than did control males (Park et al., 2006). So, if Che42B positively “supports” courtship-related chemoreception by Gr68a, effects of eliminating the former factor are the opposite of what one might expect (cf Bray and Amrein, 2003). Second, and returning to the foreleg-surgical experiments, recall that in the intraspecific side of this study Manning (1959) found no decrements in the levels of courtship displayed by such mutilated D. melanogaster males in the presence of conspecific females. In this regard, a theme emerging in the discussion of courtship-sensory studies is that a known (Manning, 1959) or a presumed (Bray and Amrein, 2003) elimination of all inputs to one type of PNS structure tend to cause modest or no apparent decreases in the vigor by which reproductive behavior is performed or in its successful outcome.

C. Visually mediated courtship actions As the male orients toward the female and follows her when she moves, visual stimuli would seem to be in play. Such inputs are indeed important for the male’s proper tracking of a moving female (Cook, 1979, 1980), although not essential for finding her “in general”: D. melanogaster court and mate in the dark or when the male is genetically blind [reviewed by Tompkins (1984); for more recent experiments, see Sakai et al. (1997)]. Mutant males that are visually impaired—such as those affected by white (w), optomotor blind (omb), or eyeless (ey) mutations— displayed female-tracking abilities that ranged from anomalously brief bouts of courtship to complete loss of tracking (Cook, 1980). When males and females could not see because they were courting in the dark (Sakai et al., 1997), similar defects were noted, albeit not involving heavy quantification of “tracking parameters” per se (the females’ status was kept constant in this study because flies of that sex, paired with males in the dark or in the light, carried a physiological blinding mutation). Furthermore, male optomotor blindness (via a special mutation at the vital omb locus) had as severe an effect on mating initiation kinetics as did total blindness (Tompkins et al., 1982). In this regard, visual impairments have tended to cause more severe courtship and mating decrements compared

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with the aforementioned “smellblindness” (Gailey et al., 1986). But even total blindness did not eliminate the fly’s ability to perform certain microbehaviors in a quasi-proper manner: When a male impaired in this way was close enough to the female, he could distinguish the head from her abdomen, presumably by using olfactory and/or contact cues (Cook, 1980). This prompts a further remark about the (overly) intense focus on chemosensory components of male–female interactions, including those which occur in a learning context, but we will see in Section IV that visual inputs to Drosophila “trainees” are also an important component of conditioned courtship. With regard to the manner by which Drosophila integrates visual inputs to generate coordinated behavioral responses, not that much is known. Descriptive information emerging about CNS regions that receive inputs from external photoreceptors will be given in some detail, because the anatomical assessments performed so far are based almost exclusively on genetically manipulated entities. At the “pre-CNS” input end, the compound eye of D. melanogaster is made up of approximately 800 ommatidia (a few more per female eye compared with a male one); each such facet contains eight primary photoreceptors cells, which send axons to relay stations in the optic lobes (e.g., Fischbach and Dittrich, 1989; Hardie, 1985). Within and between these four pair of relatively peripheral ganglia, there are four types of “circuit” neurons: photoreceptor axons, local neurons (arborizing within a given optic-lobe neuropil), interneurons connecting the neuropil between optic lobes, and visual projection neurons (VPNs) that connect proximal portions of the optic–ganglia complex to the central brain. Axons from the photoreceptors terminate either within the distal lamina (lobe) or in the medulla; neurites projecting centripetally from the latter form connections within the lobula and lobula plate (the proximal-most structures, which are separated from the lamina by the medulla). At last, the more centrally located components of an overall wiring diagram for the visual system have begun to be elucidated. A large-scale screen for putative “VPN enhancer traps” was performed, whereby the gal4 drivers just alluded to drove a GFP marker; 44 such lines were identified (Otsuna and Ito, 2006). Fourteen of them were deemed to mark VPNs arborizing “specifically” in the lobula; 10 gave more complex patterns, with GFP-expressing neurites observed in the medulla and lobula plate as well as the lobula. Portions of the wiring diagram gleaned from these enhancer-trap types were mostly devoted to establishing lobula-to-brain connections. Further in this regard, Otsuna and Ito (2006) observed that lobula-specific VPNs projected to three central-brain regions: VentroLateral PRotocerebrum (VLPR), PosterioLateral PRotocerebrum (PLPR), and OPtic TUbercle (OPTU). The main target of these VPNs appeared to be the VLPR. The OPTU region receives apparent inputs from a much more limited subset of lobula-originating VPNs. It remains to be determined which, if any, elements of these relatively central portions of the visual pathways and

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targets implied by these descriptions may include processing, within central-brain structures harbored within males and females, of stimuli that originate from courtship movements of opposite-sex flies. A rather deeply located component of the CNS that could be involved in visual control of male–female interactions is the central complex (CC). Situated between the protocerebral hemispheres of an insect brain, this entity is composed of the fan shaped body, the ellipsoid body, the protocerebral bridge, and four neuropilar regions; it has been implicated in the control of generic locomotor behavior (reviewed by Strauss, 2002). The CC is believed “eventually” to receive elements of the visual inputs that reach the deep brain, but not exclusively the results of such stimuli (Strauss, 2002). These CC basics have been extended to behavioral studies, which have shown that flies with anatomically defective CCs show slower than normal walking abilities, do not orient normally to landmarks, and do not react as quickly to changing visual stimuli in certain flight assays (Strauss and Heisenberg, 1993; Strauss et al., 1992; reviewed by Heisenberg, 1994). The CC may have relevance to the sensory processing, and its locomotor consequences, underlying a Drosophila male’s sustained following of a female.

D. Courting flies hearing other ones or themselves One of the more overt components of apparent communication between male and female Drosophila involves acoustics. The male’s frequent wing displays during courtship are almost always accompanied by production of sounds, which are species-specific [for one of the earliest relevant reports devoted to D. melanogaster and its close relatives, see Cowling and Burnet (1981); for another random example, see Gleason (2005)]. Auditory stimuli are detected by the male and female and cause each to modify their behavior. For example, when a simulated courtship song of D. melanogaster is played back to males, it triggers a group of wingless (thus mute) males to increase their locomotor activity and court each other episodically (Eberl et al., 1997; Kyriacou and Hall, 1984; von Schilcher, 1976a). The male song has the opposite effect on females, who exhibit decreasing locomotion in response to these acoustic stimuli (von Schilcher, 1976a, cf Bennet-Clark et al., 1973). Antennaless (or aristaless) males or females respond poorly to these auditory-cum-mechanosensory cues (e.g., Manning, 1967; von Schilcher, 1976a). Therefore, the antenna is a “love song receptor” (Ewing, 1978; reviewed by Tauber and Eberl, 2003; Todi et al., 2004) as well as a structure that can input courtship-related odorants. With regard to the fruit fly’s “inner ear”—Johnston’s organ (JO) located in the second antennal segment—afferent projections from this auditory-receptor structure were analyzed most recently by genetic methods analogous to descriptions of peripheral-to-central pathways in the visual system. Thus, increasingly detailed auditory-system potrayals relied using transgenes that

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themselves encode or can drive neurite markers. One such enhancer trap carries Escherichia coli lacZ and is expressed in a large proportion of JO sensory neurons (Sivan-Loukianova and Eberl, 2005); the other transposons were gleaned from a screen through ca 4000 gal4 enhancer-trap strains, resulting in 4 that label JO neurons (JONs) when combined with UAS-gfp (Kamikouchi et al., 2006). Thus, the antennal nerve as a whole was observed at the point of brain entry to involve defasciculation of “thin fibers” away from larger-diameter neurites (SivanLoukianova and Eberl, 2005). The former fiber types primarily represent axons from olfactory sensors in the third segment; the latter are projections from the JO. Compared with the thin fibers that terminate anteriorly in the ALs, JON afferents course toward the back of the brain to the antennomechanosensory center (AMC). This relatively deep-brain structure is located in a region posterior and ventral to the ALs. (This basic anatomy had been established previously by elementary morphological observations.) As the JON “thick fibers” approach the AMC, many such axons dissociate from one another, while others remain fasciculated in small bundles (Sivan-Loukianova and Eberl, 2005). Such collections of JONs continue to branch out from the antennal nerve, and transgenebased marker tactics permitted deep-brain targets of these neurites to be scrutinized in special detail: four of the bundles were observed to terminate in the AMC (which is also called the Antennal Mechanosensory and Motor Center); a further one extends to ramify within the VLPR and the SOG; within each of these five “zones,” JONs were observed to contact various combinations of “subareas” (Kamikouchi et al., 2006). An extra twist to these studies entailed Sivan-Loukianova’s and Eberl’s ultrastrucural observations of JO axon terminals in the AMC (allowed for by the electron-dense nature of an Xgal reaction product that results from activity of bacterial -galactosidase emanating from the transgene applied by these investigators). Extensive contacts between fibers projecting from the JO and target interneurons in the AMC were thus observed—including “mixed synapses” that reflected substructures that would mediate chemical neurotransmission as well as that which occurs via gap junctions (Sivan-Loukianova and Eberl, 2005). The latter kind of interneuronal communication is relatively fast, prompting these investigators to speculate that JO synapses may have the ability to “process” temporally discrete types of acoustic information. The rapidly generated outputs that comprise courting singing behavior in D. melanogaster indeed entail different time bases: a pulse rate of ca 30 Hz, pulse “carrier frequencies” of ca 220  120 Hz, and ca 150  50 Hz hums [As examples of the relevant numbers, the “” values just quoted refer to the range of Hzs among sounds produced within the songs of an “average” individual male (Wheeler et al., 1988).]. In addition to certain male-produced chemosensory stimuli that apparently act to inhibit intermale courtship (see above; also Ferveur and Sureau, 1996; Lacaille et al., 2007; Scott et al., 1988), males exhibit rejection sounds

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when placed with other males. These acoustic signals have been characterized for D. melanogaster and D. simulans (Paillette et al., 1991). Rejection sounds are emitted not only by adult males, but also by younger flies of either sex (these sounds do not differ significantly between sexes). They differ from love song sounds: intervals between pulses of tone (interpulse intervals ¼ IPIs) during a bout of rejection wing flicking and vibration are twice as long (80 msec) as are the IPIs associated with courtship song, and intrapulse frequencies for the former type of sound are generally higher (ranging from 200 to 600 Hz) compared with song pulses [Paillette et al. (1991); cf Villella et al. (1997); Wheeler et al. (1988), the latter two studies being among those that performed spectral analysis of song pulses and found them to be in the baritone or bass-note range].

E. Interrogating the multiplicity of reproductively related sensations It is important to reiterate that these courtship cues involve multiple PNS inputs, no one of which is crucial for male–female interactions and their matings. As alluded above, Drosophila males multiply deprived of inputs by way of surgeries almost never mated when observed in lighted conditions (Robertson, 1983). Similar results were obtained in experiments involving fly pairs in the dark, the males of which were wingless (thus mute), and with both males and females expressing a parasbl mutation; “resupply” of any individual component of the (genetically or environmentally deprived) cues led to reasonably proficient matings (Gailey et al., 1986). In a more modern molecular-genetic context, analogous results were obtained by mutating a gene in D. melanogaster called ppk25, which encodes a DEG/ENaC type of sodium channel subunit “expressed at highest levels” in legs, antennae, and wings—at least some of which PNS structures take in courtship-chemosensory cues (Fig. 3.1). Cationic channels of this “family” are known in mammals to involve gustatory detection of certain substances, notably ion-based tastants (Miyamoto et al., 2000), which may or may not have anything to do with reproductive responses in insects. In Drosophila, imprecise excision of a transposon inserted near ppk25 led to absence of this gene’s mRNA, and such mutant males failed to interact with females in the dark; but when light was supplied to male–female pairs, ppk25-null males “execute[d] all of the normal steps of courtship” (Lin et al., 2005). Therefore, this instance of reverse genetics, starting with discovery of a factor that could participate in regulating input of courtship cues, would have been a behavioral bust if the flies had not been multiply deprived of putatively relevant sensory stimuli (cf Ejima et al., 2005; Gailey et al., 1986; Robertson, 1983). These results raise questions as to what happens in conjunction with courtship sensory stimuli being “sent” toward the various CNS locations described in several of the foregoing subsections: in context of the different modalities of inputs sending their received cues toward regions of the CNS that are in part distinct

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(Fig. 3.1)—how are courtship-related stimuli processed centrally at a “base level?” More important, perhaps, where and how are the qualitatively different kinds of cues processed in an integrative manner? Or, does this occur at all (maybe the processing occurs solely in parallel)? But it seems as if some of the separate sensations could each converge on certain “association centers” in the brain (not speaking to brain regions involved in associative learning), owing to the surgical and behavior-genetic results that have been pulled together in section. Related questions must be asked about where males versus females putatively differentially send courtship-modulating cues from the periphery into their respective brains. (At least some of the interneurons located in the latter location are anatomically sex-specific.) And would sex-specific brain morphologies (different kinds of association centers?) fully explain how males and females, respond to separate stimuli produced by their partners by performing substantially different Drosophila behaviors.

F. Female flies sensing males Stemming from the foregoing remark, recall that “her” role during Drosophila courtship was introduced toward the top of the piece as being ostensibly passive, notwithstanding the female’s elementary walking behavior and that she exhibits so-called rejecting actions when she is a virgin or a mated fly. These consist of flicking her wings (a behavior performed mostly by young virgin females, which are not yet ready to mate), kicking her legs toward the courting male (observed among the behaviors of mature virgin females), and extruding her ovipositor in his face, if she had been inseminated and he approaches her from behind (Connolly and Cook, 1973). A mnemonic device for apprehending these behaviors is that such female actions, especially those performed by virgins, comprise “coyness”: For this insect species, the female may need to “summate” sensory cues (auditory and chemical) in order to discern that the courting male is behaviorally robust quantitatively and of her species qualitatively (discussed at length by Bastock and Manning, 1955). The ovipositor extrusion performed by mated females is correlated with the relatively low level of courtship that she elicits. Therefore, the pertinent stimuli and behaviors associated with interactions between fertilized females and “standard” males include attractive and inhibitory pheromones (which combine to stimulate male actions, but at levels below those directed at virgins) and blockage of copulation attempts when the ovipositor is being extruded. As will be expanded upon in Section IV, the behavior of males when paired with mated females has been used extensively to study a fruit fly’s ability to learn and remember (Mehren et al., 2004; Siwicki and Ladewski, 2003).

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III. NEUROGENETICS OF THE CNS’S CONTROL OF SEX-SPECIFIC BEHAVIORS A. Genetic variants applied to analysis of basic courtship control How does the function of definable brain structures and other CNS regions give rise to sex-specific behaviors? What putatively separate structures are involved in different features of male courtship behavior? One approach has involved analysis of the aforementioned sex mosaics, starting with application of genetic tools to create male (1-X) versus female (2-X) regions of neural tissue within a given Drosophila. From behavioral then neural analyses of these gynandromorphs, regions within the brain that underly male-specific courtship components were identified (Hall, 1977, 1979). But the sex-related neural substrate of song-pulse production was “mosaicially mapped” to the ventral nerve cord (VNC): An additional series of X//XX gyandromorphs that harbor 1-X brain tissue and courted normal females “through” the wing-extension stage (Hall, 1977, 1979) were found to require chromosomally male tissue within the VNC for the sexmixed fly to generate song sounds (von Schilcher and Hall, 1979). Furthermore, an “IPI rhythm” of oscillating pulse rate (e.g., Hall and Kyriacou, 1990), which is affected by mutations in the period “clock gene” (cf Section VI), was found by Konopka et al. (1996) to be abnormal if and only if per-mutant tissue was contained in the VNC of mosaic males. The problem with these gyandormoph approaches is that each individual is unique, making it impossible to reproduce a given specific category of X//XX mosaic (e.g., with a certain region of the brain genetically “always” male and a certain portion of the VNC female, or vice versa). Moreover, the resolution that is desirably associated with precisely mapping sex-relevant CNS regions is limited by the relatively large size of X versus XX “patches” created in these mosaics. To refine this mosaic approach and map more accurately the courtship foci that had been previously implicated in male courtship, the previously introduced female (RNA-splice) form of the tra gene was used to feminize various regions of the CNS; the UAS-traF-containing transgene was driven by various gal4 enhancer-trap transposons, whose various CNS-expression patterns were revealed (in separate tests) by driving of a UAS-marker transgene [cf Ferveur et al. (1997), whose abovementioned enhancer traps activated markers skewed toward abdominal expression.] The idea for the “brain-behavioral” experiments was to correlate the GAL4 patterns with various components of male behavior or the lack thereof (Ferveur and Greenspan, 1998). When traF was thus expressed in otherwise genetically male flies, a given category of “transgenic gynandromorphs” did or did not perform a given courtship behavior, depending on the enhancer trap applied in the test. In the context of the various CNS patterns so feminized, these transgenic mosaics fell into different classes based on the different courtship behaviors observed: (1)

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“transgenic gynanders” that courted females but never attempted copulation or mated, displayed low levels of wing extensions (for some of these types), and showed low levels of licking; (2) those that mostly did not attempt copulation or mating; in addition, they showed low levels of licking, but basically normal wing displays; (3) genetically mixed flies that showed moderate attempts at copulation, rarely leading to mating, but normal wing extensions and licking; and finally, (4) mosaics that behaved in a nearly normal manner for all male-specific behaviors, except for slight reductions in copulation attempts and mating per se. The behaviors of these gynandromorphs (Ferveur and Greenspan, 1998) were decremented mostly at later stages of the courtship sequences, in that they tended to progress through earlier ones pretty much as does a standard male; this pattern was consistent with mosaic studies previously performed by Hall (1977, 1979). Moreover, all three of these studies showed that if a sexmosaic’s behavior was altered early in the courtship sequence, the later stages were also affected (usually absent). Thus, essentially no partly masculinized mosaics would skip early steps and perform only later-stage courtship actions. Some of the GAL4 transgenes applied by Ferveur and Greenspan (1998), when combined with traF, led to external morphological changes (including absence of sex combs, and female-like abdominal pigmentation), which was not correlated with whether they attempted to copulate or mated successfully. This breadth-ofexpression issue brings up an important point: most of these GAL4 lines are problematical in two ways: (1) a sharply refined spatial-expression pattern is not in the cards for hardly any enhancer-trap transposons—which, ideally, would include transgenes producing GAL4 solely in highly localized portions of the brain; (2) most of these gal4 “lines” have been examined for UAS-marker patterns in adults only, not throughout development. Thus, the extent of feminization for a given line in the current experiments tended to be inconveniently broad, on the one hand, and not appreciated comprehensively, on the other. The latter issue speaks to the matter of “determining” sexual differentiation of the nervous system, in part during development and in part as a matter of ongoing male- or female-like functioning of neurons in the mature fly (an issue that will reappear within Section V). Nevertheless, by correlating the anatomical patterns with the behavioral variations, Ferveur and Greenspan (1998) were able to refine more definitively what regions of the CNS are important for various male-specific behaviors. Furthermore, “fate mapping” the areas of the nervous system that affect specific courtship steps was performed by giving the best fit to sites that had highest probability of correlating the CNS expression pattern with male-like actions. In particular, the aforementioned Class-1 type mosaics were “linked” to the neuropil of the dorsoposterior brain, close to the -lobes of the MBs, and also to the region of the LPR. Elements of the latter brain region receive projections directly from the ALs and also indirectly from the MBs (see above). Class-1

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mosaics also exhibited significant expression in (thus feminization of) various regions within the prothoracic ganglion, which may be involved in receiving sensory information from structures on the forelegs. Class-2 mosaics mostly differed from Class-1 ones by showing slightly higher licking levels along with near normal wing displays and, as a neural corollary, showed the highest probability of marker expression—compared with Classes 3 and 4—in the anterior SOG. A second “high probability of feminization” region for the Class-2 types, again compared with Classes 3 and 4, was in the posterior-most part of the VNC, the abdominal ganglion (ABG). Class-3 mosaics, which exhibited near normal levels of licking and reasonable attempts at copulation (with a few successful ones), were mostly “in common” with regard to neural maleness within a portion of the medial SOG. A second masculine site shared by the different mosaics within this class was in the vicinity of the ABG. Finally, Class-4 mosaics, which showed the most “complete” performances of courtship steps (aside from copulation), exhibited maleness in few sites that were not fully in common among the mosaics of this category, nor observed in any of the other classes. However, certain of the Class-4 mosaics expressed their gal4s within CNS regions that were in proximity to the marker patterns encompassed by the Class-1 transgenics. In summary, these are the “major male courtship foci”: (1) a region of the posterior-dorsal brain, implicated in orienting toward females, along with following them and wing extensions at them (Ferveur and Greenspan, 1998; Hall, 1977, 1979); (2) the LPR (Ferveur and Greenspan, 1998), a posteriormedial brain region whose genetic maleness is linked to licking behavior (Ferveur and Greenspan, 1998; Hall, 1979); (3) the anterior SOG and sites within the dorsal-mid and -posterior brain, suggested for the first time by Ferveur and Greenspan (1998) to be involved in attempted copulation and copulation per se; (4) the prothoracic ganglion (Ferveur and Greenspan, 1998), implicated in induction of courtship wing vibrations—or at least wing displays (Ferveur and Greenspan, 1998; Ferveur and Sureau, 1996, who did not perform acoustical recordings of putative song sounds, though they did score wing vibrations instead of merely the performance of wing extension); (5) the mesothoracic ganglion for the courtship song produced when the male extends his wings (von Schilcher and Hall, 1979), although an ambiguity about this point will appear later on; and (6) the ABG for attempted copulation without the achievement of actual mating (Ferveur and Greenspan, 1998; Hall, 1977, 1979). Because of the subtle nature of female behavior during courtship, not many sex mosaics studies have been performed to get a better understanding of what tissue is important in determining the female’s behavior. An abdominal tissue must be genetically female for a Drosophila gynandromorph to have “sex appeal” (e.g., Hall, 1977; Jallon and Hotta, 1979). In order for a female to copulate with a male, the mosaic’s genitalia must obviously be female. But an anterior focus,

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with an XX requirement, has been suggested to be important for receptivity to mating (Cook, 1978; Szabad and Fajszi, 1982). This “receptivity center” was inferred to be distinct from the focus for “any” male-like courtship (initiation of the sequence) because certain gynandromorphs with female abdomens accepted mating attempts in one test and courted females in another (Cook, 1978). In this regard, Tompkins and Hall (1983) identified and mapped a cluster of bilaterally symmetrical cells in the anterior brain, which, when genetically female, was correlated with mating receptivity of gynandromorphs. This brain region is largely separate from those required to be male for courtship behavior (Fig. 3.2).

B. Molecular-genetic disruptions of male-specific behavior MB

Anterior brain Ventral nerve cord

Mate recognition

(ventral view)

LH mAL

Prothorax Initiation

AL

Governor of proper Courtship pace Orientation/following Wing extension

SOG

Dorsal

Meso

MB

Posterior brain

Meta

Wing vibration and song

Ventral

Licking Attempted copulation

CC

ABG SOG

Copulation Seminal fluid transfer Mating receptivity

Figure 3.2. Portions of the CNS comprising neural substrates for discrete components of reproductive behavior in Drosophila. These diagrams are loosely based on those presented by Billeter et al. (2006a), which were largely devoted to CNS “courtship centers” whose structures, functions, or both are influenced by the sex gene fruitless. For example, the neural and behavioral effects of the original fru mutation suggest that a brain region near the antennal lobes (AL)—called mAL—is involved in recognition by the male of a “proper” courtship partner (thus the gray indicators within the top-left diagram). The current pictorial summary highlights neural substrates of courtship in Drosophila melanogaster that include the purview of fru (as just exemplified) but also portions of the brain and VNC that have been interrogated for their sexual meaning in other kinds of molecular-neurogenetic studies. Most of these CNS structures or regions were depicted in Fig. 3.1. But this is barely the case for the optic lobes, here indicated as quasispheres partly colored in purple (owing to the effects of combining visual-system mutations with a fruitless one and the attendant effects on the latter’s “mate recognition” anomaly). See above for the definition of mAL. Also, CC represents central complex; and the ventral nerve cord is divided here into the three thoracic ganglia (pro-, meso-, and meta-) plus the posterior-most abdominal ganglion (ABG). Elements of these CNS/behavioral correlations are inconsistent among each other, (Continues)

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Another approach to neural dissection of reproductive behavior has entailed perturbing certain regions of the CNS that had been previously implicated to be involved in courtship, then observing the effects on behavior. One region of the CNS that has been studied extensively is the subset of the olfactory system located downstream of its sensory components (which were discussed in some detail earlier). To examine the function of the olfactory pathway in Drosophila, as will be mentioned at the end of this legend. First, let it be noted that almost all of the colored indicators listed at the right refer to portions of the CNS reported to participate in regulating male-specific behavior. For example, the empurpled “mate-recognition”related region flanking the brain refers to whether a D. melanogaster male will bias his courtship strongly toward females; this item is chosen for mentioning here because experimental “neurodissection” results are minimal for this matter (compared with most of the other CNS regions colored in and connected with behavioral events listed at the right). However, the effects of fruitless mutations on mate recognition and the effects of visual-system mutations on intermale courtship exhibited by a fru mutant type, and expression of this gene in the visual system (Kimura et al., 2005; Lee et al., 2000; Manoli et al., 2005; Stockinger et al., 2005) prompted purple coloration of this large (even though presumptive) pair of courtship-controlling, brain-flanking CNS regions. Exception to matters revolving round brain-behavior analysis of males: the anteriorCNS region (and box to the right) designated in pink, which was reported to require XX brain tissue if a female is to be receptive to male mating attempts; the color code just noted along with the /// indicators mark an anterior portion of the dorsal brain [above the esophagus, drawn as an oval dorsal to the Sub-esOphageal Ganglion (SOG)]; this otherwise featureless “female focus” (deduced to exist from a brain-behavioral study of gynandromorphs) is located above the region where the antennal nerve enters the brain. Other genetically based results—notably those involving CNS expressions of genes defined by mutations affecting female courtship—implicate neural regions other than the mosaically determined site just referred to; included here is the possibility that appreciable proportions of broadly based spatial-expression patterns of “female genes” such as icebox and dead-ringer are involved in controlling interactions of such flies with Drosophila males. In addition to highlighting the positively construed neural substrates for various features of (in the main) male-specific behavior, the following discrepancies must be pointed out: Whether functioning of MB neurons is closely connected to the basic ability of a male to court is controversial and has been empirically downplayed in most of the relevant studies—prompting insertion of a red? within the top-left diagram (mirrored by the hedge included among the boxed keys at the right). This colored question mark also signifies ambiguity as to which MB substructures are involved in mate recognition (enhancer traps used to feminize the various lobes, which induced intermale courtships, entailed spatial patterns that are mutually inconsistent). Certain transgenically produced mosaics performed all early-to-late stages of the courtship sequence (in terms of male actions) but did not entail thoroughly in-common brain regions that had been neurally disrupted). Another putative oddity involved a lateral brain region that, when feminized, led to a courtship-initiation subnormality, but these neurons seem not to express the male-specific form of FRU protein (thus, see sea-green?). Genetic maleness in the VNC (probably the metathoracic ganglion within it, highlighted in light blue) was found to be necessary for production of song sounds; but certain central complex (CC) brain mutants were reported to sing defectively (see yellow? attached to the CC indicator).

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Heimbeck et al. (2001) expressed, under GAL4 control, UAS-tnt in the PNs and in a subset of MB neurons. One GAL4 line, GH146, used by Heimbeck and coworkers is expressed predominantly in the ALs and in approximately 100 PNs (this transgene also produced GAL4 in various scattered brain neurons). Most of these particular PNs send axons to the MB calyx and to the LPR via the antennocerebral tract; the remaining PNs project directly to the LPR, bypassing the MB calyx. GH146/tnt flies were affected in their response to odors (at lower concentrations), but not gustatory responses to sucrose (based on a proboscisextension assay). What is most on-point here is that GH146/tnt males displayed abnormal courtship behavior toward intact females and decapitated ones (the latter eliminates of any cues given off by an active female, who needs her brain to move and be followed, and who might not emit all of her usual pheromones if she is brainless). This reduced courtship was observed both in normal and in red light, ostensibly factoring out courtship-related visual cues. In separate “noncourtship” tests, GH146/tnt flies exhibited abnormal visually stimulated behaviors that require motion detection, but they were only partially impaired in so-called “landmark” detection. To ask whether the neural circuitry implied by these results is sexually dimorphic, Heimbeck et al. (2001) mediated traF expression via GH146. Feminization of the putative neural pathway led to males that courted females normally and did not court other males—providing no evidence for sexual dimorphism of these particular GAL4-containing structures. This study supports the idea that the direct projection of olfactory-system neurites to the LPR are required to process these “experience-independent” reproductive behaviors—and not the MBs, which had previously been implicated in experience-dependent male courtship (see Section IV). An additional type of transgene-based disruptor applied in CNS contexts involves RNAi (introduced above in a PNS circumstance). In a brain-behavioral context involving male courtship, an example provided by Manoli and Baker (2004) used a particular GAL4 line (P52a) whose expression pattern overlaps with elements of the fruitless gene’s spatial domain (see Section V). Thus, a P52a/ UAS-fruMIR combination—with the latter transgene encoding a double-stranded RNA designed to knock down transcripts that encode male-specific forms of FRU protein—were indeed “FRUM minus” in cells of a certain neuronal cluster within the brain. The UAS drivee would presumably have no effects across most of P52a’s expression domain, in which UAS-marker and FRUM coexpression was not observed (Manoli and Baker, 2004). The behavioral consequence of combining these two transgenes was a dramatic change in the males’ courtships: they exhibited inappropriately fast initiation of the sequence, skipped certain steps (orientating and tapping), but did display some of the later-stage behaviors. These anomalies were induced by the fruMIR disruptor being driven within a brain structure known as the “median bundle.” Similarly weird behavior was induced by P52a driving of UAS-traF, designed to feminize the median bundle and compare that effect to

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fruMIR-induced “demasculinization.” None of the part-masculine//part-feminine mosaics produced in previous studies were reported to exhibit this kind of behavioral anomaly. Conceivably, median-bundle region was feminine (XX, thus TRAF-containing) in certain of the older mosaics, but these individuals did not court at all, because the dorsal-brain region necessary for any male courtship to occur did not happen to possess the single-X genotype. The brain region that is part of the P52a transgenes’s pattern is near the esophagus (Manoli and Baker, 2004) and was heretofore unknown to influence male courtship. Thus, these results are informative—and described here—because male-specific actions that occur too quickly and leapfrog across certain courtship stages have not been observed in studies of males expressing straightforward fruitless mutations (Section V), let alone in observations of gynandromorphs. A further approach to uncover regions of the CNS that control various aspects of courtship involves disrupting neural activity in opposite manners within a given study; one of these molecular-genetic tactics entails a conditional disturbance of neuronal function. For this, a UAS transgene was constructed to contain a temperature-sensitive dynamin mutation, shibireTS (shiTS), which suppresses synaptic transmission at high temperature even when the normal shiþ allele is present (reviewed by Kitamoto, 2002b). The advantage of this tactic is that one can monitor the biological effects of shiTS before the flies are heated, followed by asking whether alterations of behavior occur at a “restrictive” temperature. The power of this tool is signified by application of the usual protocol: Drosophila carrying UAS-shiTS are reared at a “permissive” (relatively low) temperature, so that any heat-induced abnormalities should not have a developmental etiology. In contrast, GAL4-driving of UAS-tnt is known to alter certain neuronal morphologies, as well as synaptic transmission in mature flies, for any gal4 transgene that is expressed during development as well as in adults (reviewed by Martin et al., 2002). A companion factor for the experiments in question was derived from the ether-a-go-go (eag) gene, whose potassium-channel mutations increase neuronal excitability; similar effects occur under the “dominant-negative” (dom-neg) influence of a truncated form (TR) of this channel polypeptide (created by engineering a shorter-than-normal form of eag). As was implied during the discussion of Heimbeck et al.’s (2001) application of UAS-tnt, usage of the shiTS and eagTR transgenes in brain-behavioral experiments can expand one’s appreciation of relevant CNS regions beyond those that are sexually dimorphic. (Again, the latter are pointed to by structures and functions that would be affected by UAS-traF or UAS-fruMIR.) In the exemplary study, Broughton et al. (2004) screened numerous GAL4-expressing lines and compared the effects on male courtship of driving UAS-shiTS versus UAS-eagTR. Their behavioral measurements included latency to courtship initiation, how long various behaviors lasted (including courtship-unrelated ones) and durations of wing extensions and (as claimed by

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the authors) “vibrations.” Bear in mind over the course of the ensuing discussion that these investigators made no attempts to record courtship-song sounds—or possibly to reveal that males bearing certain transgene combinations could extend their wings but would generate anomalous sounds or none at all. By quantifying whether a certain courtship behavior was diminished (or absent) or whether the male’s action became more pronounced, Broughton et al. (2004) aimed to map regions of the brain that could be ascribed to mediate either courtship-inhibitory or -excitatory actions. In other words, if expression of UAS-shiTS in a certain region of the brain led to an increase in courtship performance, the neurons would be judged as inhibitory, whereas a UAS-shiTS-induced decrement (under the influence of different drivers) would allow inferences about excitatory structures. Contrarily, if a given element of courtship was compromised by driving UAS-eagTR in a given brain region— under the influence of a particular gal4 transposon—the suggestion would be that that enhancer-trap’s spatial pattern defines an inhibitory region, whereas a UASeagTR-induced accentuation of one or more courtship elements (as revealed by drivers other than the one just hypothesized) would point to an excitatory zone. Recall the difficulty of homing in on behavioral relevant brain sites via UAS-regulated expression of “whatever” by a given enhancer-trap transposon. One cannot mention enough times how broad are these expression patterns. To deal with this problem (better than in previous studies), Broughton et al. (2004) analyzed overlapping expression patterns of the various transgenic lines using an imaging software package called AMIRA (Rein et al., 2002), such that a semiautomated “Venn-diagram” approach accentuated the chances of making proper brain-behavior correlations. In particular, among the GAL4 lines screened with UAS-eagTR and UAS-shiTS, three transgenic types (lines MJ286, MJ146, and MJ63) drove significant defects in latencies to courtship initiation (see below); when AMIRA-aligned, the key GAL4-containing sites came down to a region within the LPR. Specifically, two of the doubly transgenic male types (which included the MJ286 or MJ146 driver) showed abnormally long courtship-initiation latencies when combined UAS-shiTS, and reciprocal initiationlatency abnormalities (shorter than observed for controls) were effected by UAS-eagTR. This suggests that these dorsolateral brain cells play a role in the activation of courtship. This part of the region had been previously implicated as involved in male-specific behavior (e.g., Ferveur and Greenspan, 1998; Heimbeck et al., 2001; Joiner and Griffith, 1999). It is notable that, in the more recent study, the groups of LPR cells as defined by elements of the MJ286 and MJ146 patterns are located adjacent to each other, but expression of these two drivers is nonoverlapping. A further driver type employed, MJ63, was implicated to label an inhibitory courtship “center,” based on the designed increase in neuronal activity that putatively occurs by driving UAS-eagTR; this transgene

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combination led to longer-than-normal latency at the beginning of the behavioral pathway. In summary, a group of brain cells in the LPR—some inhibitory and some excitatory—are involved in regulation of courtship initiation. Is sexual dimorphism within this brain region connected with courtship control? Potentially to answer this question, Broughton et al. (2004) combined the enhancer traps just described with UAS-traF and tested for male-like behavior: only MJ286/UAS-traF males displayed significantly longer courtship latencies than those exhibited by controls. Therefore, MJ286-labeled region can be imagined as involved in courtship initiation, in context of what is further surmised to be usual maleness of these lateral-brain neurons (whether this involves sex-specific circuitry or neuronal function is unknown). Interestingly, although sexual dimorphism was inferred in the LPR region in which MJ286’s GAL4 drives marker expression, Broughton et al. (2004) did not detect overlap with elements of the FRUM protein pattern (as introduced earlier and as will be elaborated later on). Further in this “negative” light, the MJ146/UAS-traF combination induced no effect on sex-specific behavior, but MJ146 mediated marker expression in a few cells that overlap with a small part of the FRUM pattern. Returning to the matter of MJ286—the only driver that affected courtship when combined with UAS-traF—the following suggests itself: Although fru functions are not required in the “MJ286 cells,” another sex gene may be expressed in some of them. This could be doublesex (dsx), whose mutations affect male courtship (Villella and Hall, 1996) and whose gene is expressed in the CNS, including the brain (Lee et al., 2002). Details of the dsx case will be dealt with in Section V. The versatile shiTS disruptor of courtship-related neuronal function has been applied by Sakai and Kitamoto (2006). Their results indicated two brain regions, the MBs and CC, to be involved in male-specific behavior. Both of these structures had been extensively studied previously for their contribution to Drosophila behavior (see above). By blocking synaptic transmission within the MBs via various GAL4-encoding enhancer traps, Sakai and Kitamoto found the doubly transgenic males to take longer to initiate courtship with females and to exhibit shorter-than-normal courtship bouts. Young male Drosophila are also courtship-eliciting objects; they are as stimulatory as virgin females (e.g., Cook and Cook, 1975; Jallon and Hotta, 1979; Tompkins et al., 1980) and possess a special type of aphrodisiac pheromone (Vaias et al., 1993). Sakai and Kitamoto’s UAS-shiTS-containing transgenic males courted young males vigorously, with no effect on initiation of courtship or bout length. When synaptic transmission was impaired in the fan-shaped body, encompassed within the CC, there was no effect on courtship initiation but a slight reduction of overall courtship vigor directed toward either virgin females or young males. Therefore, Sakai and Kitamoto (2006) inferred that neuronal activity within the MBs plays a role in courtship initiation, perhaps via processing of pheromonal inputs originating

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from females, and it also would be involved in the maintenance of male courtship. But the CC influences only the latter behavior, independent of what the stimulatory cues may be. Elements of these conclusions seem inconsistent with those of Broughton et al. (2004). Recall from the discussion of their study that courtship-initiation defects were observed with gal4 lines that did not induce a shiTS effect in the MBs. Another study—performed by Kido and Ito (2002), discussed in detail below—also downplays “MB control” of male courtship. This messy situation may arise from the poor power of enhancer-trap applications. (Where is a given such transgene really expressing GAL4, at all the life-cycle stages that one needs to interrogate?) Nonetheless, Sakai and Kitamoto (2006) attempted to deconvolute the conundrum at hand by musing about different-sized chambers used in the separate studies (these could lead to inconsistencies among latency measurements) and about variations between heat-shock protocols used prior to behavioral testing. Do realize, in any case, that the 2004 and 2006 studies pointed to deleterious effects of inducing shiTS in the MBs on courtship vigor after the sequence gets initiated. With regard to MB control of basic Drosophila courtship, results within reports now on the table (e.g., Ferveur et al., 1995; O’Dell et al., 1995; Sakai and Kitamoto, 2006) create a muddled picture. Therefore, the findings of Kido and Ito (2002) must now be presented. These investigators showed that the MBs are not required, in the context of sex specificity, for courtship to occur between naive males and females. Thus, Kido and Ito combined, in turn, numerous enhancer-trap lines with UAS-traF against an immediate backdrop of meticulously examining marker driving by each gal4-containing transgene; and they did not bias themselves to application of drivers that might be described as “predominantly” expressed in the MBs or ALs (there may be no such enhancer trap line, as we keep harping on). Flies carrying these particular gal4/UAS-traF combinations did not exhibit external feminization (implying that the enhancers that got trapped in these cases were not “wildly” active in their spatial distributions). Two gal4 lines—MZ490 and NP218, when combined with UAS-traF—led to almost complete suppression of male-specific behavior: these partially and internally feminized males exhibited next to no courtship in the presence of females (or, for that matter, of other males). Despite the minimal courtship exhibited by such doubly transgenic types, certain sexual behaviors were observed: NP218/traF males essentially skipped the courtship-song step but exhibited the subsequent step of licking. Moreover, line MZ490/traF flies elicited courtship from wild-type males (this was probably due to feminization of the oenocytes, since MZ490s gal4 was shown to drive marker expression in these abdominal structures, cf Ferveur et al., 1997). Neither of these two enhancer traps mediated detectable expression within the MBs or the ALs.

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The key findings reported by Kido and Ito (2002), derived from the two gal4 lines just noted, were further verified by reevaluating the role of the MBs and ALs in the context of bisexual behavior. Thus, hydroxyurea (HU) treatments of developing wild-type led to MB-ablated males that behaved heterosexually, although there was a decrease in courtship levels that was not due to the flies being less active in general. McBride et al. (1999) had shown that general courtship performance of HU-treated males toward females (before performing conditioning experiments, as will be discussed within Section IV) was not affected—findings that are mildly at variance with those of Kido and Ito (2002). In any case, the modest male–female courtship decrements observed by these investigators suggested that the MBs are “involved,” even though feminizing them had no effect on male-specific behavior. In this light, HU-ablating the MBs of the MZ490/UAS-traF or NP218/UAS-traF combinations, which caused markedly diminished male courtship, led to no further changes in phenotype as a result of the chemical treatment. When Kido and Ito HU-treated the previously published bisexual types [carrying the doubly transgenic gal4/UAS-traF genotypes of Ferveur et al. (1995) and of O’Dell et al. (1995)], little change in the males’ behavior occurred. These partly feminized, MB-ablated flies showed essentially the same bisexual tendencies as did MB-intact control transgenics. One of the transgene manipulations effected by Kido and Ito (2002) in a way jars us out of our enhancer-trap complacency: An actually specified regulatory sequence was employed, derived from the prospero (pros) gene, which is expressed in essentially all neuroblasts and immature neurons, but only within a small number of neurons and some glial cells in the mature central brain (pros-gal4 barely expressed within the MBs or ALs of adults). A pros regulatory sequence was fused to gal4 and used to drive UAS-traF; the result was elevated intermale courtship. but these doubly transgenic males courted females normally. However, when UAS-traF was expressed under the control of an elav-related enhancer trap (called c155), which drives expression in all neurons throughout most of the life cycle, male courtship was basically abolished. This implies that “relatively late feminization” (vis-a`-vis that mediated by pros-gal4) is necessary and sufficient for courtship suppression. The upshot of the several findings of Kido and Ito (2002) force us to reorient views of how the MBs and ALs are involved in male-specific reproductive behavior. With regard to the bisexual courtship that resulted from applying some of these transgene combinations, how would such behavior occur or not occur as a consequence of ectopically expressing traF in different regions of the brain? One way to explain a negative result, obtained by applying a given driver but not jibing with the effects of a similarly expressed enhancer trap, is that the former gal4 does not mediate traF expression within the appropriate cells during development. It also might be that traF itself, or the level of its expression driven by

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certain gal4 transgenes, is not capable of completely feminizing neurons, even though the brain region in question could suppress basic courtship (cf Ferveur and Greenspan, 1998) if it were completely demasculinized. Enhancer traps that each induced intermale courtship and were noted to be expressed in the MBs and/or AL also produced GAL4 in other brain regions. Such locations were nonoverlapping when one takes into account all of these drivers—those causing nearly the same behavioral effects when combined with UAS-traF (Ferveur and Greenspan, 1998). Thus, ectopically expressing this feminizing factor in various separate regions of the brain can cause bisexual behavior. Furthermore, the effects of HU treatments on the brain structures now being considered are ambiguous: Certain Kenyon-cell neurons within the MBs are spared after HU application (Kido and Ito, 2002) at the relevant developmental stage—cells that arise during embryogenesis and eventually project axons into the -lobes of the MB (Kurusu et al., 2002). If this structure-within-the-structure had been eliminated by the chemical treatment, perhaps levels of courtship among males would have been modulated. The argument against this is that the pros-gal4 transgene drove no detectable marking of these cells, yet these males displayed bisexual behavior when combined with UAS-traF. A similar case can be made about a structure called the LH (introduced in Section II.A and sometimes referred to in this piece by the abbreviation LPR, a brain region which includes the LH); it receives interneuronal inputs from elements of the olfactory pathway (see Figure 3.1). The LH [which Stocker et al. (1997) showed to be unaffected by HU treatment] has been proposed to comprise an alternative “courtship center.” This laterally located brain region is so implicated because expressing UAS-tnt in most of the PNs connecting with the LH caused to males to exhibit severe courtship decrements (Heimbeck et al., 2001). Recall from earlier that, when Heimbeck et al. (2001) feminized these PNs (cf Fig. 3.1), no abnormalities of male courtship resulted. One interpretive problem here is that TNT would have been blocking communication not only to the LH but additionally to downstream interneurons that would presumably pass olfactoryoriginating signals farther along information through these structures. Hence, the observed suppression of courtship observed may involve some sort of “deeper center” —heretofore unidentified—at which the combined effects of several sensory modalities are working together. Here, we allude to end-product neuronal activities that are in some way inhibitory, with reference to the supposition that “overly positive” recognition of a male by another one is maladaptive. All in all, definitive information as to whether (let alone how) a given CNS structure is involved in normal sex recognition, thus inhibition of bisexually directed male behavior, is lacking. An analogous and perhaps equally unsatisfying state of current affairs is that separate regions within the male brain may be able independently to process courtship cues and thus mediate discrimination of a female from a mature male.

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A similar but more sanguine scenario suggests itself with regard to transgene-induced decrements of the basic interactions between males and females (commencing moments after sex recognition has been properly established): Disrupting a neural pathway at various anatomical stages could inprinciple block the behavioral pathway at the same step. Recall that sensory neurons (in the male foreleg), or relatively peripheral interneurons (PNs) within the antenna-to-CNS path, were reported to suppress male–female courtship when either such cell type was eliminated or disrupted. Aside from the dubiousness of these results (i.e., that other obstructions of a single chemosensory-input pathway had little or no effect on courtship), it was found that transgene-induced abnormalities in more centrally located interneurons can also diminish or block the courtship pathway at an early step. These structures are located in CNS regions that may or may not be in common among the pertinent driver patterns. Thus, it cannot be ruled out that multiple brain “foci” are involved in controlling male-specific behavior at its basic level: Will such a fly, once he has perceived that another one is a female, begin to court her? This question of course leaves intact the notion that there must be an array of different neural foci for subsequent stages of the pathway (such as singing behavior, attempted copulation). Within two passages of this piece, it was noted that one of the most salient steps along the courtship pathway is male wing extension. Recommendation, by the way: Investigators should keep to themselves various attempts at “scoring” wing vibrations, unless they actually record the associated sounds. This problem harks back to Hotta and Benzer (1976), who presented some dubious data about a putative “neural focus” for the control of male-specific wing vibration; unbeknownst to them, a gynandromorph can vibrate a unilaterally extended wing but generate no courtship-song sounds (von Schilcher and Hall, 1979). As mentioned in passing earlier, production of “real” singing sounds by X// XX mosaics was observed only if these gyandromorphs possessed haplo-X tissue in their VNCs (along with genetic maleness within their brains). But this does not rule out the involvement of other neural regions in song production—only a requirement for genetic maleness in the VNC. This brings us to the effects of brain-damaging mutations on courtship sounds. Mercifully, two MB-defective mutations, or HU ablation of that brain structure, all left male wing extensions and song components in grossly normal states (Popov et al., 2003); however, the (literal) MB-defective mutant exhibited the feeblest unilateral wing displays among all six of the neurally damaged types. This alludes to testing effects of three CC mutations on song sounds per se: Two such male types were defective to varying degrees: (1) The CC-broad mutation caused certain tone pulses to be anomalously polycyclic, and pulse trains containing such sounds were defined by overly variable IPIs. (2) The central complex (cex) mutant was an odd duck, flywise, because males suffering the effects of this mutation generated weirdly

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irregular sounds (no normal pulses or hum-like sine sing) when they courted fertilized females, but singing behaviors displayed by cex males were quasinormal or rather regular when they were in the presence of wild-type virgin females or cex virgins, respectively (Popov et al., 2003). These oddities notwithstanding, it would seem as if we need to roll in a brain structure as a participant in song control. There are two disclaimers, however: (1) For cex males in the presence of mated females, Popov et al. (2003) noted that “wing movements accompanying sound production were disordered and wing position was extremely variable,” which hypothetically connects with the mosaic “focus” for wing extension having been mapped to the brain (Hall, 1977, 1979; Hotta and Benzer, 1976); thus cex’s highly abnormal singing in this circumstance could have an anterior CNS etiology. (2) These CC variants have not been ruled out as to whether they harbor VNC “damage” as well as the brain-structure abnormalities that gave the mutants their names; therefore, perhaps the normally singing calyx bulging mutant (Popov et al., 2003), which is doubly defective for CC and MB morphology, is devoid of structural or other problems within its thoracic ganglia, but the songaffecting CC mutations could cause more pleiotropic CNS abnormalities. Furthermore, the generic locomotor abnormalities caused by CC mutations (alluded to above) could contribute to poor wing usage in a courtship context. At all events, the findings just summarized bring us back to the CNS and the supposedly brain limited manipulations effected by Broughton et al. (2004). We should bear in mind once again that the male’s wing-usage anomalies observed in these transgenic experiments did not occur in conjunction with alterations of neural sex. Thus, two of the so-called MB gal4 enhancer traps applied by Broughton et al. (2004), C309 and C747, led to decrements in durations of wing extensions when combined with UAS-shiTS (these investigators were coaxing the reader into supposing that courtship wing vibrations had been scored). It was not possible to pin down a neural region that was correlated with this male-specific behavior, given certain particulars of these experimental tactics and results: C309/shiTS males showed a decrease in duration of wing extension, implying that elements of the “C309 pattern” (see below) may be involved in sustaining this behavior. In contrast, the C747/shiTS combination induced longer than normal wing extensions, such that C747s gal4 could be expressed in regions that are normally inhibitory. Both of the enhancer traps drive GAL4 in the MBs, but they have quite different patterns of expression elsewhere. Although Broughton et al. (2004) claimed that C309s expression is limited to a few neural cells aside from those in the MBs, we will see that this is thoroughly unsupported by the results of other studies (see shortly below as well as Section V). Another effect of the C309 driver, when combined with UAS-shiTS, was to induce intermale courtship at a restrictive temperature (Kitamoto, 2002a). The C309 enhancer trap, initially claimed to a “MB-predominant” line (Connolly et al., 1996),

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turned out to be robustly expressed in a much broader pattern than just the MBs: C309s GAL4 driver marker expression is in most major regions of the CNS and PNS (Kitamoto, 2002a; Villella et al., 2005; Waddell et al., 2000). This makes the neural etiology of C309/shiTS-induced behavior minimally interpretable. Nonetheless, this courtship anomaly is similar to that caused by fruitless mutations: frumutant males follow each other, perform wing extensions, and form so-called “courtship chains” (e.g., Gailey and Hall, 1989; Lee and Hall, 2000; Villella et al., 1997). When C309/shiTS males were placed individually with wild-type males at high temperature, they courted them significantly more than normal— another fru-like behavior. The transgene-induced intermale courtship was not due to a general increase in sexual activity: When C309/shiTS males were paired with females at the restrictive temperature, the former courted at lower levels compared with a permissive-temperature control, and C309/shiTS males mated in an inefficient manner after they were heated (Kitamoto, 2002a). As we will see in Section V, reduction in male–female interactions is another salient effect of fruitless mutations. Returning to the matter of what causes induced intermale courtships performed by C309/shiTS males: Previous studies showed that traF-induced feminization of MB subsets (including calyces, pedunculi, - and -lobes), or certain regions of the ALs, or both of these structures caused males to behave bisexually (Ferveur et al., 1995). In other words, the pertinent gal4 transgenes, used to drive sexually mosaic brains, turned these flies into fru-like males (under the influence of most such mutations, these flies will court females in one test and do so toward males in a separate one). In a companion transgenic study, O’Dell et al. (1995) assessed effects of combining various gal4 enhancer traps with UAS-traF male courtship directed at either female or (mature) males. The lines used in this study were expressed “predominantly” in different parts of the MBs (c35, 201y, c739), or mostly in afferents from the antennal nerve as well as a group of cells surrounding the AL (c123a), or within the CC’s ellipsoid body (c232). Two of lines (201y and c739) just mentioned, expressing in the various regions of the MBs and the one that produces GAL4 in “association” with the ALs (c123a), induced high levels of intermale courtship. A proviso, however: When the c739 enhancer trap drove traF, the flies were female-like in their external appearances; this could lead to “self-elicitation” and cause these transgenic males to court “anything” (as opposed to the intermale courtship representing a breakdown in brain-controlled sex recognition). This possibility seemed belied by the fact that c35/traF mosaics, which also exhibited many female-like attributes externally, did not court males; but this doubly transgenic type, along with the c739/traF one, elicited high levels of courtship from standard males. Given the various details of these results just outlined, O’Dell et al. (1995) concluded that the MB subset defined by 201y’s GAL4 pattern plays a role in mate discrimination. This enhancer-trap—unlike the c35 one, which produces GAL4 within Kenyon cells that

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project to all three lobes and outer elements of the - and -lobes—is expressed almost solely in these MB perikarya that make up core elements of the - and -lobes and within a subset of fibers that make up the -lobe. Therefore, because the marker patterns driven by 201Y and c35 are different in terms of all three lobes of the MBs, it is difficult to pin down which particular regions are associated with the aberrant behaviors observed. Indeed, all enhancer traps used in this are also expressed elsewhere in the brain, in patterns that differed among lines (naturally). Regarding O’Dell et al.’s so-called “AL-effect” of the c123a transgene, these antennal afferents and nearby CNS cells were contemporaneously implicated in sex recognition by Ferveur et al. (1995). But this enhancer trap is expressed in too many additional brain regions to allow for a definitive conclusion. We now return to a consideration of the C309 gal4 transgene, its MB expression, and the effects on intermale courtship induced by combining it with UAS-shiTS. In line with elements of the suppositions stated by O’Dell et al. (1995), a breakdown in sex recognition may be due to conditional inactivation of MB neurons driven by C309. This is not a fully satisfactory scenario, however: When other would-be “MB-specific” enhancer traps were tested in combination with UAS-shiTS, groups of males did not perform chaining behavior at a restrictive temperature (Kitamoto, 2002a; A. Villella, unpublished observations). Better to refine the neural cells putatively responsible for inducing intermale courtship, Kitamoto (2002a) made a construct in which the 50 flanking region of the Choline acetyltransferase (Cha) gene was fused to yeast-derived DNA that encodes the GAL4 antagonizer GAL80 (reviewed by Lee and Luo, 2001). This regulatory region of Cha directs expression in a large subset of cholinergic neurons and in most chemosensory neurons of the PNS (Kitamoto et al., 1992, 1995). By combining Cha-gal80 with C309, efficacy of the latter’s GAL4 was therefore broadly suppressed. The behavior of the relevant triple transgenic males (C309/ shiTSþ Cha-gal80) involved no formation of courtship chains at a restrictive temperature, implying that cholinergic neurons are involved in this aberrant behavior (GAL4 action was “subtracted” from neural regions that coexpress C309 and Cha, against a backdrop of the former inducing chaining when it alone is combined with UAS-shiTS.) Unfortunately, Kitamoto (2002a) only looked at interactions among triply transgenic males and did not examine how these males behave with wild-type males or virgin females. Nonetheless, let us step back from elements of these results to register this: C309/shiTS courtship chaining is specific to an increase in temperature that causes synaptic transmission to cease, in cells that coexpress this gal4 enhancer trap and the Cha-gal80 transgene, in the context of an effect on the nervous system of adults; in other words, a breakdown in normal sex recognition can have a neural-function etiology, as opposed to necessitating feminization of neural structures during development. The latter may well have occurred in the enhancer-trap/traF experiments of Ferveur et al. (1995) and O’Dell et al. (1995).

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Furthermore, Kitamoto’s findings imply that a putative CNS circuit underlying a normal male’s being blocked in terms of courting another male vigorously is inhibitory, because shiTS-induced nonfunction (of wherever this hypothetical circuit may be located) leads to inappropriate intermale courtship. Yet, we need to have in mind that C309 is expressed in gustatory neurons of the proboscis and the legs (Kitamoto, 2002a), which could be used to detect female aphrodisiac substances when the male taps or licks a target fly during courtship; perhaps the relevant genetically abnormal males fail to sense inhibitory cues when these PNS neurons are inactivated (or are not male-like). Indeed, Kitamoto (2002a) found that adding Cha-gal80 to males carrying C309 suppressed the latter’s GAL4 driving of marker expression in most of the (usual) leg-tarsi and labial neurons—reflecting on the possibility that unfettered C309 inactivation of those PNS is involved in poor sensation of an inappropriate courtship object. It must be said in this regard that tapping or licking of another male by a genetically abnormal one has not been definitively scored in any of the courtship studies now being discussed. The point just made strays somewhat from the main theme of the current section, which has been aiming to delve deep into the nervous system, compared with solely considering structures that bring courtship-related stimuli to the various ganglia of the CNS (cf Section II). Therefore, we close Section III by directing the reader to a pictorial summary of centrally located neural elements that support the ability of Drosophila to act in various sex-specific ways. Few such summations have appeared in the secondary literature (although see Billeter et al., 2006a), and we are aware of none that point out the problematical features of these brain-behavioral conclusions. In order to peruse one that attempts to deal with such disclaimers, see Fig. 3.2.

IV. GENETIC MANIPULATIONS OF EXPERIENCE-DEPENDENT REPRODUCTIVE BEHAVIOR In most neurobiological investigations of associative conditioning in Drosophila, the MBs have been analyzed extensively in conjunction with behavior that can be modified by applications of artificial odorants and electric shock (innovated originally by Quinn et al., 1974; reviewed recently by Davis, 2005). Many of the studies that point to the fly’s MB as a “learning and memory center” have depended on—you guessed it—enhancer-trap driving of various neural-disruptive factors. Also, ablation of the MBs by treatment of developing Drosophila with HU led to learning deficits (e.g., de Belle and Heisenberg, 1994). Moreover, accumulation in adult MB neurons of mammal-derived TAU protein [previously shown by Williams et al. (2000), to disrupt cellular morphology when ectopically expressed within Drosophila neurons] affected associative learning and memory

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(Mershin et al., 2004), but there was no effect on the flies’ basic responses to aversive odors (the ones used as conditioning stimuli) or to electric shocks [used as the unconditioned stimulus (US)]. Elements of the fly’s courtship experiences also seem to be learned and remembered. As a lead-in to the brain-behavioral experiments devoted to this (real) behavior, the relevant behavioral paradigms are now described: A courtship conditioning assay was first introduced by Siegel and Hall (1979); it involves exposing a male to a mated female for various numbers of minutes, followed by observing the male’s sexual behavior after this experience. When the pair is first grouped together, the male initially exhibits high Courtship Indices (the CI metric introduced above), but these values progressively decline over the course of, for example, a 30-min observation period. When such a male is subsequently presented with a virgin female, he exhibits much lower levels of courtship than a naive male: It seems that this decline in the male’s courtship is due to both stimulatory and inhibitory olfactory stimuli given off by the mated female. As reviewed by Siwicki and Ladewski (2003), a male initially responds positively to the former cues then begins to react negatively to the latter. How different kinds of pheromonal stimuli modulate conditioned courtship was substantially elaborated by Ejima et al. (2005). One new feature of these findings entailed the implication that one or more substances produced by immature virgin females— which are unreceptive to male mating attempts (cf Connolly and Cook, 1973)— can train a male to suppress his courtship subsequently. In conjunction with a mated female eliciting relatively low-level courtship, she actively blocks any copulation attempts by extruding her ovipositor at her hapless suitor. Therefore, goes the argument, it is a waste of time for such a male to court a mated female, and he learns to exhibit relatively little courtship not only to one that he encounters subsequently but also to a virgin female, because he associated stimulating substances with a mated female’s antiaphrodisiac(s) [see Tompkins et al. (1983), for the first foray into this phenomenon as an associative-conditioning one]. An intensive instance of this training experience might mean that many such inseminated females are in his presence, so even if he encounters a virgin, her aphrodisiac(s) “should” serve as a conditioned stimulus (CS) to modify his behavior in the downward direction. Siwicki et al. (2005) present the most recently obtained evidence about these substances and thus discuss tangible CS candidates—which “must” include 9-pentacosene as well as, possibly instead of, heptocosadiene (cf Section II.A). The retention of this kind courtship suppression can last up to 2–3 h after a relatively brief experience with a mated female. However long is such an after-effect—does it represent information storage and retrieval? The original suggestion that that is so was provided by Siegel and Hall (1979), owing to their test of a mutant called amnesiac (amn). It was originally isolated via “shock-odor” associative-conditioning tests effected a while after the training sessions; this

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screen was aimed identifying novel genetic variants that would exhibit no odoravoidance memory, because they either did not learn in the first place or forgot too fast (Quinn et al., 1979). Thus, amn as a mutant of the latter type, and with regard to a wholly different kind of behavior, courtship-suppression, males expressing this mutation showed a normal reduction in subsequent behavior after they courted a mated female, but amn males did not retain the courtship inhibition as long as normal ones do (Siegel and Hall, 1979). Additional conditioning learning mutants, also discovered via shock-odor paradigms (reviewed by Davis, 2005; Waddell and Quinn, 2001), were subsequently revealed to exhibit abnormal behavior in two courtship-suppression situations. The first such study entailed discovery of a new kind of experience-dependent courtship: After a mature male is exposed to an “attractive” immature male (see above), this causes the former subsequently to “avoid” courtship of another young male, a suppression effect that can last up to 6 h (Gailey et al., 1982). The main difference between the two courtship conditioning assays is that the one involving mated females has been demonstrated to involve an associative learning process, whereas the young-male courtship assay entails habituation: An immature male (courtship directed at which is also time-wasting) gives off only positive chemosensory cues, and a mature male’s exposure to them alone is sufficient for subsequent courtship suppression (documented most explicitly by Vaias et al., 1993; also see Siwicki and Ladewski, 2003). Another (classical) learning variant that entered the reproductive arena is dunce (dnc), which again was found by shock-odor testing (Dudai et al., 1976). dnc males basically failed to learn that they were courting either a mated female immature male or an immature male in separate tests (Gailey et al., 1982, 1984). Moreover, males hemizygous for a dnc mutation were shown to be at a selective disadvantage after courting an immature males and subsequently placed with a mixture of such flies and a virgin female; in contrast, wild-type males learned to “ignore” the second set of immature males and readily mated with the female (Gailey et al., 1985). Further aspects of how long a mated-female after-affect can last— beyond the 2–3 h for wild-type males, let alone the 30 min. (Remember

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that normal memory in this paradigm last for at least 2 h.) A further group of HUtreated wild-type Drosophila led to males that were deemed either completely MBablated or only partially so. Individuals from both groups displayed CIs that were significantly reduced immediately after training (compared with the behavior of naive males); similar to the experiment involving the 30Y transgenic type, courtship of these HU-treated males anomalously bounced back to normal levels at 60 min posttraining (McBride et al., 1999). In the seminal HU treatments performed in context of brain-behavioral experiments, application of this agent to ablate MBs also caused the ALs to be smaller than normal (de Belle and Heisenberg, 1994). So could it be that the shortterm memory deficit observed in mated-female experiments was possibly due to AL damage in HU treated males? To address this, McBride et al. (1999) evaluated these brain structures for all trained males and separated them into distinct groups: those with apparently normal ALs and those with size-reduced lobes. This was done for trained males from both the 30Y transgenic line and a wild-type strain. There was no apparent correlation between the males’ learning performances (immediately posttraining) and the size of their ALs. However, by 30 min posttraining, only those males with reduced ALs displayed CIs that had anomalously returned to the levels of naive male performed; and by 60 min, both groups were back to naive levels. In conclusion, damaging the ALs in HU-treated males caused the males to show a deficit in memory at 30 min after training, whereas normally appearing ones were correlated with normal memory at this “early” time point; bear in mind that the MBs had been pretty-much completely ablated in both groups. This suggests that the memory of associative courtship conditioning lasts longer in MB-ablated males that did not also suffer from AL damage. Long-term memory associated with courtship conditioning was also analyzed in MB-ablated males [see Kamyshev et al. (1999), for the first foray into this feature of the courtship-suppression phenomenon]. For the brain-behavioral study in question, McBride et al. (1999) modified the mated-female conditioning assay by using longer training periods: one involved “spaced” intervals between a given exposure of the male to the mated female and the other entailed no such interruptions (so-called “massed” training). Memory was thereby extended to 5 days for both types of training paradigms (both types of trained males behaved with CIs that were reduced to 50–60% of those measured for naive males). In particular, 30Y transgenic males that were not treated with HU, CI levels remained low for 5 consecutive days after training, compared with those of untrained males. Moreover, CI levels for trained 30Y males were reduced to approximately one-fourth the initial values (courtship vigor quantified immediately after training), compared with the performance of naive flies. In contrast, MB-ablated 30Y males, by one day after they were mass-trained, performed courtships at levels that bounced back up to those typical of naı¨vemale controls. These findings indicate that ablation of MBs causes long-term

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memory of courtship conditioning to be impaired. Furthermore, McBride et al. (1999) showed that courtship responses measured immediately after training were abnormal in MB-ablated males: Their degrees of courtship suppression were only one-third those measured for control males that had been subjected to massed training. The GAL4/UAS system has also been (inevitably) exploited, further to analyze the neural substrates of experience-dependent courtship. The pertinent background information for this stemmed from interrogating roles by calcium/ calmodulin kinase—Drosophila’s version of CaM kinase II—in these processes. A dom-neg construct was designed to bring down the level of this enzymatic activity in a neurochemically normal genetic background; the requisite transgene was engineered by replacing the phosphorylatable residue threonine, at intra-CaMKII position 287, with alanine. Activation of this transgene in males or females led to impaired experience-dependent courtship. One set of assays involved the (familiar) training of males by their courtship of mated females (Griffith et al., 1993; Joiner and Griffith, 1997). Other tests of the dom-neg CaMKII construct (Griffith et al., 1993) were based on a sensitization-like phenomenon—that female Drosophila can be acoustically “primed” for enhanced mating receptivity by playing song sounds to them before they are courted (cf Kyriacou and Hall, 1984; von Schilcher, 1976b). The effects of this dominant negativity (improperly suppressed male courtship or diminished priming of females) presumably had neural etiologies. But the putative CNS structures involved could not be inferred because the engineered transgene was turned on all over the fly by a heat-shock promoter (hsp), fused upstream of the sequence encoding the Ala-substituted oligopeptide (Griffith et al., 1993). Thus, Joiner and Griffith (1999) delved into the main feature of the CaMkinase experiments, by introducing enhancer traps into males destined to be conditioned by exposure to and courtship of fertilized females. The driven transgene in this case was called UAS-ala, named after the AA substitution originally engineered into the CaM-Kinase coding sequence (within the hsp-CaMK construct). The various gal4 lines applied were, as usual, simultaneously scrutinized for expression patterns by crossing them to either UAS-lacZ or UAS-gfp. For conditioning, transgenic males were placed with mated females for 1 h, and CIs were measured during the first and last 10 min of this conditioning period. Immediately following this “training” time, the males were tested with an anesthetized virgin female. Controls consisted of males that were kept alone (sham) in the chamber for 1 h then tested in the same manner as the experimental males. A normally conditioned (“learned”) response was taken to be signified by CIfinal/ CIinitial values  0.5 (cf Joiner and Griffith, 1997); but ratios > 0.5 indicated that males did not respond normally to the mated female during their training time (“final” values were too high, so that not enough of a courtship decrement occurred during this period, as usually occurs). Memory was measured by taking the test CI (courtship vigor measured soon after the male was paired with a mated female) and

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comparing it with the value for sham males (CItest/CIsham); a male was deemed to exhibit normal conditioning if these memory ratios were 0.5, compared with defective performance indicated by values >0.5. The foregoing behavioral details were presented because (1) elements of computations resulting from the learning and memory tests are not necessarily the same in other mnemogenetic studies of this type, and (2) the results now to be summarized represent essentially the only molecular-genetic foray into neurobiological features of conditioned courtship. Thus, Joiner and Griffith (1999) found that the response to mated females during conditioning was not affected when CaM kinase was “locally” inhibited by combining four of the five so-called MB gal4 enhancer traps (applied in these particular experiments) with UAS-ala. But memory was disrupted for males carrying four of these transgene combinations (not the same exact ones that caused defective courtship suppression during training). Comparing details of these MB expression patterns among the enhancer traps that resulted in conditioning defects, it appeared that most of this brain structure is involved in normal memory formation, although the -lobes may be most “important.” This supposition was based on the fact that one of these MB gal4s that gave a negative result in the memory tests was said to be primarily expressed in the - and -lobes. Other enhancer traps applied here are expressed within a given subregions of the aforementioned CC (“predominantly” within the CCs ellipsoid body or the fan-shaped body). Combining these gal4s with UAS-ala led to no disruption of learning; however, memory was disrupted in three of the four CC lines tested. Memory was disrupted severely when UAS-ala was driven by other enhancer traps that produce GAL4 in the LPR; certain of these gal4s drove marker expression within a subset of this brain region that did not overlap with the patterns of other LPR lines. Combining only one of them with UAS-ala led to a lower-than-normal learning score. When CaMKII activity was reduced via two separate gal4 enhancer traps expressed in the ALs, one of the doubly transgenic male types showed subnormal responsiveness to mated females during conditioning but no memory deficits; males carrying the other transgene combinations (with UAS-ala in common) showed normal conditioning and memory. These so-called antennal lines were manufacturing GAL4 within similar portions of the ALs; but, overall, the sets of marked glomeruli were different between them. Moreover, one of these transposons drove strong marking in the maxillary palps (which mediate olfactory inputs, as depicted in Fig. 3.1) and within the MBs. Interestingly, this particular gal4 was the one that led to abnormal learning (when combined with UAS-ala) with mated females but no memory defect. The nonexistence of a memory defect for this transgenic male type suggests that there may be a threshold level of expression required for the ala peptide to function. CaMKII has been perturbed in courtship contexts by a molecularly mediated change aimed at affecting its activity in manner opposite to that which applied the enzyme-inhibiting transgene. At the same intrapolypeptide

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site where that ala site-change was engineered, a constitutively active (calciumindependent) form of the enzyme was achieved by an in vitro mutagenesis designed to substitute aspartate (D) for the normal threonine (T). Transgenemediated overexpression in males of this T287D construct, which we will call asp, decreased their initial level of courtship directed at mated females (even more so than the extent to which such males are already “down”) and enhanced the rate at which such courters become further suppressed (Mehren and Griffith, 2004). This experiment entailed a gene-manipulation twist, by which the aforementioned 30Y enhancer trap’s driving of constitutively active CaMKII was activated only in adults, not developing Drosophila. (This alludes to the “tTA/ tetO system” that was originally developed in mouse to allow for both spatial and temporal control of transgene expressions.) The next step was to dissect the neurochemical properties of 30Y-expression brain neurons. For this, the previously introduced Cha-gal80 construct was applied in conjunction with the other requisite transgenes [of types that are reviewed by Mansuy and Bujard (2000)]. AL expression of a UAS-maker was thereby eliminated, but other domains of the usual 30Y pattern remained (including that within and associated with the MBs)—implying that the AL neurons in question are cholinergic (Mehren and Griffith, 2006). The behavioral side of this study showed, first, that “removing” the cholinergic component of the 30Y gal4 pattern by combining that enhancer trap with Cha-gal80 and UAS-asp did not alter the effects of the latter CaMKII construct on initial interactions between these triply transgenic males and mated females (Mehren and Griffith, 2006)—the same result as initially reported by Mehren and Griffith (2004) for unfettered 30Y. Therefore, brain cells that express 30Y—driving UAS-asp—to affect this courtship character were inferred to be not cholinergic. For stage 2 of these behavioral experiments, recall that the 30Y/UAS-asp combination enhances courtship suppression that occurs as male training ensues (subsequent to monitoring the “initial interactions”); this effect was mimicked by combining Cha-gal4 with the in vitro-mutated CaMK transgene but then got eliminated when 30Y was combined with Cha-gal80 (Mehren and Griffith, 2006). It was concluded, therefore, that changes in “trainer-specific suppression” of courtship between males and mated females are mediated by expression of the constitutively active enzyme in cholinergic neurons. Additional neural manipulations performed by this research group (1) showed that CaM kinase inhibition mediated by enhancer traps that were not even called “MB” or “AL” lines because they drove conspicuous marker expression in both brain regions, caused both learning defects and memory ones; and (2) uncovered a role for visual inputs as modulators of courtship-related learning and memory. For this, Joiner and Griffith (2000) tested various drivers of UAS-ala for their effects in white-light versus dark conditions (the latter meaning red light). For example, three so-called LPR enhancer traps, and a CC one, led to acquisition of male courtship suppression only when the lights were

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on (a fourth LPR-expressed gal4 type allowed acquisition of courtship-suppressive learning in a “vision-independent” manner). None of these lines, nor MB enhancer traps when applied to inhibit CaMKII, disrupted courtship memory in white light (Joiner and Griffith, 2000); but any of these LPR, CC, or MB drivers had caused suppressive aftereffects when training and testing were performed in the dark (Joiner and Griffith, 1999). Point (2) reveals a “second level” of sensory influence on this experience-dependent feature of male behavior: Apparently, if such a fly can see the mated female with whom he is interacting, chemosensory elements of the circuitry underlying courtship suppression are modulated enough to override the manner by which this information storage is retrieved—at least with regard to CaMKII control of these processes. Among the implications of the broad spectrum of brain-behavioral findings discussed throughout this section—insofar as the olfactory side of the story is concerned—are that the contributions of CaM-kinase II to conditioned courtship occur via the ALs with regard to the learning phase of the process, whereas this neurochemical function is “significant” in the MBs (perhaps mainly within the -lobe) with respect to memory formation. What the putatively (to-be) phosphorylated targets of this catalytic activity may be within neurons in these brain regions are unknown. Another question that tacitly suggests itself harks back to MB ablation experiments of McBride et al. (1999). Recall their application of a transgenic type (called 30Y) used to monitor MB integrity; when treated with HU, these males exhibited reduced courtship immediately after training with fertilized females, but by one day later such MB-ablated males courted as vigorously as do naive ones. Interestingly, the study by Joiner and Griffith (1999) demonstrated that this particular gal4 enhancer-trap line, when combined with UAS-ala, showed a learning decrement, assessed immediately after training. But these investigators did not ask whether memory was also disrupted (cf McBride et al., 1999). In any case, the “learning and memory centers” (if you will) underlying conditioned courtship, as gleaned from the pharmacological experiments and molecular-genetic manipulations, are summarized in Fig. 3.3.

V. fruitless: A CRUCIAL SINGLE-GENE REGULATOR OF MALE-SPECIFIC BEHAVIOR AND SEXUAL DIFFERENTIATION OF THE NERVOUS SYSTEM A. Basic features of fru-mutational effects on sexual characteristics The original fruitless mutation (fru1) was isolated by Gill (1963) as an X-ray induced mutation that caused males to be behaviorally sterile and to exhibit intermale courtship. When this mutant began to be studied with some intensity (as published in full reports, compared with Gill’s brief note), Hall (1978) and

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Figure 3.3. Portions of the CNS comprising neural substrates for conditioned courtship in Drosophila. The brain regions depicted at the top—in various colors that correspond to the “brainbehavior” information boxed below—are drawn according to an image of Drosophila melanogaster’s anterior-CNS ganglia presented by Rein et al. (2002). The superscripted numbers contained within the five-color-coded boxes (aside from the italicized mutantallele designations) refer to certain details of the behavioral methods and findings that have been devoted to and resulted from analyses of experience-dependent reproductive

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Gailey and Hall (1989) documented that fruitless males court females robustly but do not even attempt to copulate, let alone mate; fru males court one another to form the aforementioned chains; and they stimulate wild-type males to court them. Moreover, when a fru1 male was placed with a wild-type one, the former exhibits subnormal levels of wing-flick rejections (Hall, 1978). So, could this deficit contribute to mutant males being courted at anomalously vigorous levels?—although this would not explain why fru1 court wild-type males vigorously (Hall, 1978), even though the latter perform energetic rejections. The reverse behavior—wild-type males courting fru1 ones, even if the latter were rendered immobile (Hall, 1978)—was shown by Gailey and Hall (1989) to have a different genetic etiology compared with the radiation-induced lesion that causes the mutant not to mate with females and actively to court other males. In other words, the syndrome of overall reproductive defects and anomalies demonstrated for the original mutant is caused by a double mutation. Additional fruitless mutant alleles (see below) are “singly hit” at the fru locus per se, and these mutations do not cause anomalous courtship elicitation (Villella et al., 1997). In this regard, it is important to mention that the various fru mutations and chromosomal lesions at the locus create an allelic series connected with subnormalities all along the courtship pathway. Some such mutant males are nearly courtless in the presence of females (e.g., Goodwin et al., 2000; Villella et al., 1997); others are blocked between the stage of wing extension and male-specific song-generating vibrations (Villella et al., 1997); one mutant (the original) is obstructed between the postsinging stage of licking and

behavior: (1): learning as measured by McBride et al. (1999) is equivalent to memory as measured by Joiner and Griffith (1997, 1999, 2000) and by Mehren and Griffith (2004); (2): Joiner and Griffith (1997, 2000) tested both learning and memory in white (w) and red (r) light; (3): Neckameyer (1998a) looked at habituation of males to immature males, tested in conjunction with mushroom body (MB) ablation; (4): these experiencedependent effects tested in conjunction with MB ablation; and (5): Mehren and Griffith (2004) performed conditioning tests in red light. This depiction of courtship-learning neurobiology otherwise speaks for itself, partly because the brain regions shown at the top have been diagrammed and named within Figs. 3.1 and 3.2; also because tabulated features of the current figure do a reasonable job of indicating the brain-behavioral connections in a standalone manner, compared with the possibility that the various rows and columns require elaboration here, which would inappropriately repeat too many of the main-text passages in Section IV (although not all the studies cited here were discussed in the text). Suffice it to say that the manner by which specifiable portions of the anterior CNS that effect inputting then processing of stimuli involved in experience-dependent courtship now warrants these summarizing pictures and words. This speaks to the fact that neurobiological analyses of these learning and memory phenomena have been increasingly coming to the fore but have not yet been pulled together in a synopsis—however dense the current one may be

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attempted copulation (Hall, 1978); still further fru mutant types actually mate but exhibit striking increases in durations of copulation as well as erratic ejaculation abilities (Lee et al., 2001; Villella et al., 2006). A key inference from this array of results is that the fruitless gene in its normal form regulates essentially all stages of the courtship pathway (Fig. 3.4). A notable exception (which we perceive routinely to be ignored by other fruitless folk) is that certain fru-mutant types that are blocked, or nearly so, at an early or intermediate step are able to “skip ahead” and perform licking behavior. (Even the nearly courtless frusat mutant diagrammed at the beginning of the pathway in Fig. 3.4 licks a bit when males of this type do court, as documented by Goodwin et al., 2000.) Nevertheless, to appreciate the claim about “essentially all stages,” we ask these questions:

freeze

Following

Wing extension

Courtship song fru3

fru Dfs

fru4

Licking

Attempted copulation fru1

Begin copulation

3

u 4 1 /fr u r fru u1 /f fr

frusat

celibate platonic

coitus interuptus fickle okina platonic lingerer stuck dissatisfaction

Disengage

4

Tapping

Non-courting male

cacophony croaker dissonance doublesex slowpoke

fr fru u 1/f 1 ru 3 /fr u

courtless flamenco he’s not interested quick to court nerd

Transfer of sperm and precious bodily fluids

Figure 3.4. The courtship pathway in Drosophila melanogaster and effects of mutations on these behaviors. The individual actions (indicated by words printed in Roman) describe mostly male-specific behaviors, although close interactions between that kind of fly and a female are involved in certain steps of the pathway (e.g., male Tapping of the female abdomen with his forelegs; Licking of the female’s genitalia by extension of the male’s proboscis). Above the pathway itself are mutations, entered in italics, which if present affect male behavior such that the behavioral step marked by a given genetic variant is performed defectively, or the pathway is blocked at that step. Few of these courtship mutants were discussed in the text because little or no neurogenetic information has been obtained about them. Futher information about these genetic variants is presented in the reviews of Yamamoto et al. (1997), Goodwin (1999), Hall (2002), and Sisodia and Singh (2005). Below the pathway, the effects of various fruitless mutations are indicated, again by placement of a given fru-variant type at the step that involves either a behavioral abnormality or a pathway block; the phenotypic effects of such genetic variants are reported in Hall (1978), Gailey and Hall (1989), Ito et al. (1996), Ryner et al. (1996), Villella et al. (1997, 2006), Goodwin et al. (2000), and Lee et al. (2001). One of these genotypically defective types, here called fru Dfs, involves certain pairs of deletions, each of which removes a small portion of chromosome 3 in D. melanogaster including elements of the fru locus; one Df for a given pair of them (in heterozygous condition) is missing most of the gene’s coding region, whereas the other one is intact for that informational content but devoid of fru’s “upstream” regulatory region (including that the “sex promoter,” discussed in the text, is deleted).

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What if only near-courtless fruitless mutants had been found? Could any such mutation be said to affect the male’s ability to sing or to attempt copulation? No, because performance of intermediate- or late-stage actions is moot if a mutant male does not even start down the path. But a mutation—notably the seminal fru1 one—that allows for vigorous courtship (of females) up to and including the song-production step can be said directly to affect the male’s wherewithal to bend his abdomen toward the female’s genitalia (Fig. 3.4). Speaking of this body region, an entry-level study of “fruitless biology” showed that, in addition to exhibiting behavioral abnormalities, fru-variant males lack or are subnormal for formation of a male-specific abdominal structure known as the muscle of Lawrence, affectionately called the MOL (Gailey et al., 1991a). The relevant developmental event entails recruitment during male metamorphosis of a group of myoblasts (from a sex nonspecific “pool”), resulting eventually in a pair of MOLs (Taylor and Knittel, 1995); such structures are larger than any of the female’s abdominal muscles. It can be surmised that these defects in muscular morphology are rooted in neural cells influenced by fru, because Lawrence and Johnston (1986) showed that the MOL forms if any only if it is innervated by posterior CNS neurons that are genetically male. These investigators deduced as much from their analysis of sex mosaics in which the single- versus double-X genotypes of abdominal nerves and muscles were marked by expression of a gratuitous biochemical factor. Subsequently it was shown, albeit not by manipulating the sexual genotype of these structures, that MOL formation requires innervation of the relevant myoblasts by certain motor neurons that project from the ABG (Currie and Bate, 1995). To enhance the potential for understanding how this gene is involved in the generation and operation of “neural maleness,” DNA corresponding to most or all of the fruitless locus was cloned contemporaneously by Ito et al. (1996) and by Ryner et al. (1996). These accomplishments rested largely on the insertion of mobile genetic elements within the fru gene—identified by their effects on male behavior (Castrillon et al., 1993; Gailey et al., 1991a; Ito et al., 1996)—and the transposon-tagging opportunities created by such molecularly tractable inserts.

B. Roles played by fruitless within the sex-determination hierarchy of gene actions and analysis of fru’s molecular structure Sex determination and sexual differentiation are controlled by a hierarchy of genes that act within the sex-determination hierarchy (SDH) in Drosophila [reviewed by Burtis (1993) and Schu¨tt and No¨thiger (2000), among many other examples]. In summary, the ratio of X chromosomes to autosomal set of chromosomes determines the sex of the fly (if the ratio is 1: female, if 0.5: male); and this is dependent on the functions of SDH genes acting downstream of chromosomal sex. Near the top of the hierarchy is the Sex-lethal (Sxl) gene whose

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RNA-binding function regulates translatability of the aforementioned transformer (tra) gene’s primary transcript, by regulating splicing of the pre-mRNA of tra; therefore, as necessarily noted in earlier sections, TRA protein is produced only in females. Products of tra and transformer-2 (tra-2) regulate splicing of the doublesex (dsx) pre-mRNA (e.g., Ryner and Baker, 1991), resulting in two alternative forms of mature transcript that produce female-specific (DSXF) and male-specific forms of the protein (DSXM). In situations where mutations eliminate functional products from Sxl or tra, the result is a default dsx splice form from which DSXM is translated. For several years, dsx was the relatively downstream gene that got analyzed most extensively (compared with, for example, intersex, which is not necessary to go into here, although see Garrett-Engele et al., 2002). In this regard, many features of overt maleness versus femaleness come under the sway of DSX control, as do certain internal workings such as yolk-protein production in females. One could therefore be coaxed into surmising that dsx does not “have much to do with neural sex.” Whereas this particular supposition will be demolished later on, there is meaning to the last two words in the phrase just quoted: Certain portions of the CNS do differentiate in diverse ways within a male versus a female as these ganglia are forming. Most of these differences have been determined by gross volumetric measurements of CNS ganglia, notably the optic lobes (Heisenberg et al., 1995; Rein et al., 1999, 2002). The MBs (alas) are also sexually dimorphic anatomically, as determined in this case by counting neurite numbers within the aforementioned MB -lobes (Technau, 1984). Certain of the points should cause two things to be borne in mind: (1) dsx is not without significance for sexual differentiation of the nervous system—moreso than conventional (non)wisdom would have it (Section V.F). (2) Most of the “base-level” morphological differences uncovered by analyses of CNS tissues in wild-type males versus females are not yet connected (if the following shall be possible) with known anatomical effects of genetic variants that are of prime relevance to the current section: dsx-mutated or fru-mutated flies. Additional dribs and drabs resulting mainly from anatomically describing elements of male and female nervous systems in Drosophila are that (1) efferent neurites projecting caudally from the posterior-most part of the VNC— the ABG—are sexually dimorphic, as they essentially must be, because innervation of internal tissues at the ass end of the abdomen involves substantially different structures (at least with regard to reproductive plumbing); and (2) certain male-specific neuroblasts have been observed to form within the ABG relatively late in development (Taylor and Truman, 1992). These sexually dimorphic structural elements connect with actions of the dsx and fru genes, as we will see. This brings us to the elementary (albeit complicated) molecular genetics of fru. That it is an SDH factor was signified early on by the demonstration that one type of primary fru transcript emanating from the gene is sex-specifically

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spliced; a` la the case of dsx, this differential RNA splicing is controlled by TRA and TRA-2 (e.g., Heinrichs et al., 1998), and mutation-induced absence in females of either of two RNA-binding proteins results in default male-like splicing (Ryner et al., 1996). Therefore, tra or tra-2 mutations “turn XX flies into males” but have no effect on flies carrying one X chromosome (see the SDH reviews cited above). The primary RNA just referred to is transcribed under the control of a promoter located farthest from the bulk of fru’s coding region; the associated transcription-start sequence is the first one encountered as one moves into the locus from the 50 end and is called P1. Additional promoters, P2 through P4, are farther downstream; transcriptions initiated from these sites generate RNAs that are not sex-specifically spliced (e.g., Anand et al., 2001). But transcripts emanating from P1 are processed to produce mRNAs in males that get translated into FRUM polypeptides; these contain extra 101 amino acids (AAs) at the Nterminus of the male-specific proteins (residues not found in FRUs resulting from P2–P4 activities). Female-specific mRNA originating from the upstream “sex promoter” could produce a normal-sized FRU protein (ca 700 AAs) lacking the N-terminal 101 residues. However, and despite the relatively 50 -located start codon within the female mRNA, this transcript type is not translated (UsuiAoki et al., 2000), or it makes a would-be “FRUF protein” that cannot accumulate (also see Lee et al., 2000). There are additional alternatively spliced forms of fru RNA that involve sequences relatively near the 30 ends of the primary transcripts (e.g., Anand et al., 2001; Billeter et al., 2006b; Goodwin et al., 2000). These RNA processings result in an array of FRU isoforms differing with respect to pairs of zinc-finger (Zn-F) motifs, which suggests that the polypeptides comprise a set of DNA-binding proteins. Consistent with this is the fact that FRU immunoreactivity, discussed in neuro-detail below, is detectable solely within neuronal nuclei (Lee et al., 2000). Relatively near their N-termini, but downstream of the male-specific 101-mer in FRUM, those polypeptides and all other FRU ones possess a stretch of ca 115 AAs called the BTB domain. This motif is characteristic of a subcategory of Zn-F factors encoded by many genes in Drosophila and in other species (e.g., Collins et al., 2001).

C. Where fruitless is expressed and how this correlates with behavior and other features of neural sex From the perspective of fru’s involvement in male-specific biology, the “sex promoter” of the gene is expressed in approximately 1700 neurons (and no detectable glia) in the CNS of males (Lee et al., 2000). This was inferred from analyzing FRUM antigenicity (detected by antibodies made against most of the male-specific N-terminal AA sequence), as scored during the pupal stage. Anti-FRUM led to

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staining of the male nervous system only, meaning that there were next to no signals in nonneural tissues (more about this below, when some special types of fru-related transgenics come into play) and none anywhere in female preparations. However, the latter express the apparently untranslatable sex transcripts in spatial patterns throughout the CNS that are essentially the same as in males [e.g., Lee et al. (2000) and Ryner et al. (1996), who documented a modest mRNA sexual dimorphism within the VNC]. [Incidentally, the total numbers of pupal or adult CNS neurons in D. melanogaster of either sex is often quoted as “100,000” (most recently by Billeter et al. (2006a) and Manoli et al. (2006). But it is unclear where this approximation comes from, and it has to be an underestimate: A bona fide cell count for just one of the eight optic lobes led Fischbach and Heisenberg (1981) to an estimate of 40,000.] It is during metamorphosis when antibody-elicited histochemical signals, and those quantified via in situ hybridization to detected “sex mRNAs” transcribed from the upstream fru promoter, exhibit peak intensities (Lee et al., 2000). That promoter becomes active near the end of larval life and continues to generate FRUM-encoding mRNA into adulthood. In contrast, the sex-nonspecific promoters are used to make mRNAs and so-called FRUCOM starting early in development, then continuing throughout the life cycle. The “common” types of this protein (referring to an AA sequence that is common to all FRU isoforms and was used as an immunogen to generate anti-FRUCOM) are also quasipromiscuous in terms of their tissue distribution within animals of both sexes (e.g., Dornan et al., 2005; Lee et al., 2000). Chromosomal lesions at the fru locus that largely eliminate FRUCOMs cause such males and females to die at a very late developmental stage or as young adults and to exhibit a variety of external morphological abnormalities (Anand et al., 2001; Ryner et al., 1996). But we should judiciously eschew discussing this “other function” of the fruitless gene (which is in no way devoted to sex-specific neurobiology and behavior), allowing concentration from now on the functional meaning of FRUM. In context of highlighting the matter of these male-specific protein types having the potential to be both developmental factors and those that influence functioning of the mature nervous system, the number and spatial distributions of FRUM-immunoreactive cells are similar in the pupal nervous system (Lee et al., 2000) and that of adults (e.g., Billeter and Goodwin, 2004; Villella et al., 2005). However, “fru neuron counts” for a given CNS region that contains FRUM cells, as performed by different investigators, are not in great agreement. What has been consistently observed is that assemblages of FRUM neurons—rather tightly clustered in some locations, more loosely groups in others—are found in essentially all major regions of the metamorphosing and the mature CNS: within central-brain ganglia, an optic lobe, and all four VNC ganglia (e.g., Billeter and Goodwin, 2004; Lee et al., 2000; Usui-Aoki et al., 2000, 2005).

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The “anatomies” just summarized have principally been described by figuring out the locations of neuronal perikarya that express the fruitless gene— via application of fru nucleic-acid probes, which mark only the “bodies” of such cells, or anti-FRUM, which leads to labeling only of nucleic within these cell bodies. Despite the locations of these perikaryal clusters and numbers of cells per group seeming to be much the same in the CNS of males and females, via the mRNA signals just noted, this does not belie the possibility that structural sexual dimorphisms are involved. To examine this issue, Kimura et al. (2005) scrutinized certain cell groups with enhanced intensity and included neurite marking of fru-expressing neurons. By screening numerous enhancer-trap lines, these investigators looked for sex differences in marker-driven patterns and found one strain, called NP21 that led to differential (GFP) marking in males versus female brains. The gal4-containing NP21 transgene is inserted within one of fru’s introns. The sexual dimorphisms in question were observed within the optic lobe and in the region just dorsal to the ALs, a fru cluster known as mAL (Lee et al., 2000). Indeed, all of the latter cells, marked under the influence of NP21, were immunoreactive for FRUM (Kimura et al., 2005). In the relevant NP21 females (heterozygous for this transposon), there was no detectable GFP-expressing cells in the female’s optic lobes; and within the mAL region of female brains, there were very few marked cells (ca five neurons) compared with NP21 heterozygous males (ca 30). To determine whether fruitless functions affect sex differences in cell numbers within the mAL cluster, NP21 was combined with various fru-variants (then brains from both males and females were scrutinized with regard to GAL4 driving of GFP). All males showed significantly reduced numbers of marked mAL cells, bringing the level of mutation-affected expression down to that observed in females. A mosaic-generating method called MARCM (Lee and Luo, 2001) was then applied, allowing Kimura et al. (2005) to focus on the projections patterns associated with mAL cells. The limited mosaically marked expression permitted homing in on such neurites, without having to cope with the massive tangle of vines that would obtain in nonmosaic brains expressing fruitless in all its usual locations. Specifically, somatic recombination can be induced at different developmental stages by timing an hsp-inducible recombinase (transgene-encoded); marking subsets of cells usually active for fruþ was effected by expression of the aforementioned membrane-bound, neurite-filling form of green fluorescent protein (usage of MEMBR-GFP is a feature of the MARCM tactic). Application of this method in conjunction with fru-mutational effects on the enhancer-trap’s expression showed that female-like neuronal projection patterns were observed in males, although elements of the “fruþ male pattern” were retained. This mAL neuronal group should be borne in mind for its possible functional significance, to be discussed shortly in context of a fru-mutational effect on behavior and on brain expression. Meanwhile, we need to register that mAL axon projections terminate both ipsi- and contralaterally with regard to the

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brain’s hemispheres); in females, the projections are solely contralateral. In both sexes, projections from the mAL extend dorsally to the superior LPR and ventrally to the SOG. Single-cell labeling effected within the relatively small cluster of mAL cells in females nailed a key feature of these anatomical points: Certain ipsilateral projections were missing vis-a`-vis the male pattern. In addition, projections toward the SOG involved a female-specific forked pattern of projections (with reference to the distal elements of these axons). Arborization of neurites within the protocerebrum was quite extensive compared with the near absence of branching for intra-SOG termini. In this regard, a presynaptic marker (synaptotagmin immunoreactivity) was detected at the termini of “fru neurites” in the superiorlateral protocerebrum but was not associated with those in the SOG (Kimura et al., 2005)—as if the former fibers represent neuronal outputs (axons) and the latter inputs (dendrites). Remember that the SOG has been implicated as a gustatory “processing center” (Stocker, 1994; Thorne et al., 2004). This prompted Kimura et al. to come up with the idea that male-specific input to the SOG may deal with pheromonal inputs originating at the antennae, such that the deep-brain effects of those stimuli would interact with the consequences of gustatory inputs. This brain region (or at least one that is nearby) will come into play in further passages that will present suppositions about neural effects of the original fru mutation on the intrabrain pattern of FRUM, in context of how this mutant behaves in the presence of other males (see above and below). Meanwhile, it is worth mentioning one further feature of the sexdimorphism substory told by Kimura et al. (2005). The relative paucity of fruexpressing neuronal entities in females is a developmental consequence of enhanced “cell-death” events that occur within an XX CNS, owing to the absence of FRUM in the brain regions under consideration. The mechanistic details of this “sculpting” process are neither here nor there for the moment. Suffice it to say that the cellular etiology of these female versus male morphological differences within the anterior CNS speak to fruitless as a developmental factor (the gene is at least partly that). This same conclusion is also demanded by the effects of fru variants on formation of the MOL (Gailey et al., 1991a). It remains to be determined whether additional pieces of sexually dimorphic anatomy— considered rather broadly, as in Heisenberg et al. (1995)—will be uncovered in the specific context of fruþ expression and effects of mutations at the genetic locus. In this regard, keep in mind that it was a “fru enhancer trap” driving marker labeling in only a portion of the overall fruþ pattern that prompted analysis of the intrabrain male versus female dimorphism that is currently under discussion. Lest we authors be deemed hypocritical for having poked fun at enhancer traps in earlier passages—the one currently being considered is of a more “dedicated” type, entailing as it does a gal4-containing insert within a particular subset of well-defined genetic locus (also see Dornan et al., 2005).

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When one stands back from the 20 groups of neurons that are immunoreactive for male-specific FRUM—cells that are distributed from stem to stern within the CNS—parallels can be drawn to the array of courtship and mating abnormalities caused by fruitless mutations. Thus, expression of this protein (really “these,” with reference to the variable Zn-F isoforms) within one or more brain clusters can be hypothesized to influence the early stages of the courtship sequence: sex recognition, tapping, orientation, and following. Recall in this regard the nearly courtless fru types (Fig. 3.4). Additionally, when a male follows a female, he is “tracking” her, using visual cues in the main (e.g., Cook, 1980), and this may have something to do with FRUM’s presence in the optic ganglion alluded to in the previous paragraph. An intermediate courtship step, wing extension (Fig. 3.4), could also come under the sway of “fruitless brain control” because chromosomal maleness in that part of the CNS is necessary and sufficient for displays of this appendage (Section III.1). Furthermore, the songless fru mutants that perform wing extension do so in a quantitatively subnormal manner (Villella et al., 1997)—which brings us to FRUM’s presence within VNC ganglia, one or more of which may need to carry out normal expression of the gene if a male is to generate song sounds. (This notion is presumed to fit with the fact that, in gynandromorphs, the VNC must possess singleX tissue if such a mosaic is to sing.) Moving down the fly and toward end-of-sequence phenotypes (Fig. 3.4), it would seem that fru expression within the above-mentioned ABG would be connected with attempted copulation and ejaculation of seminal fluids—along with MOL development. Recollect that that male-specific muscle requires innervation by single-X neurons if it is to form during metamorphosis. The suppositions just listed are based on descriptive findings alone, and these behavioral plus gene-expression data are, in a way, too far apart empirically. This means that the effects of fru variants were considered (shortly above) solely in terms of gross phenotypes, usually whole-organismal ones. What about the effects of such mutations on the male’s inner workings (in addition to functioning of the MOL, whatever that may be)? First, certain of the courtlessinducing genotypes, involving combinations of chromosomal breakpoints within the locus (the Dfs in Fig. 3.4), should eliminate staining for male-specific forms of the protein—and do (which, by the way, served as a nice control for the specificity of anti-FRUM). Three additional fru mutations, caused by transposons inserted within the locus, also were almost blank for FRUM-immunoreactive neurons in the CNS (Lee and Hall, 2001); one such mutant (frusat) courts almost not-at-all, but the other two (fru3, fru4) follow and wing-extend toward females to a modest degree. These findings could be rationalized by the demonstration that fru3 and fru4 lead to lower-than-normal but above-zero levels of sex transcripts—not high enough, apparently, to allow for detectability of translated protein by a particular anti-FRUM serum. Indeed, these mutants possess “residual” levels of FRUM-encoding mRNAs, which were detectable by more sensitive methods (Goodwin et al., 2000). It could not be quantified as to whether the

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“transcript residue” in frusat males was even lower than in fru3 or fru4 ones; but one hypothesizes that this is so for frusat, owing to that mutant’s near courtlessness. The final fruitless mutant to be considered this context is fru1. Such males court both females and other males rather robustly, including that groups of fru1 males exhibit by far the most vigorous chaining behavior (Lee and Hall, 2000; Villella et al., 1997). It was therefore intriguing to find that this mutation, which is caused by a chromosomal lesion in fru’s 50 -flanking region (Ryner et al., 1996; cf Billeter and Goodwin, 2004), causes nonrandom “dropouts” of FRUM staining in only two of the usual brain clusters; one such neuronal group is near the ALs (Lee and Hall, 2001). Could this have something to do with the effects of gal4 driving UAS-traF within apparently similar (overlapping?) portions of the brain? Feminization of these near-AL regions caused intermale courtships (Ferveur et al., 1995), and it should be underscored that the presence of TRAF protein blocks production of the fru splice-form which encodes FRUM. In other words, from an SDH perspective, traF-mediated feminization could be equivalent to demasculinization induced by fru mutations. Thus, the following scenario suggests itself: A near-AL structure functions somehow as a “sex-recognition center” (perhaps integrating sensory cues, including putatively courtship-inhibitory ones produced by males). If such neurons formed abnormally or function that way, the usual biased-toward-females recognition breaks down. This can be revealed as “wild” courtship between and among males, if other brain regions involved in “beyondrecognition” stages (initiating courtship steps and sustaining intrapathway actions) are FRUM-enabled. Indeed they are in fru1 mutant brains, although certain other CNS cell groups aside from the dropout ones gave subnormal neuronal counts in males homozygous for this mutation, exhibited ectopic staining of cells that usually are not FRUM-positive, or both (Lee and Hall, 2001). [In this respect, perhaps depleted cells within one or more VNC ganglia—in terms of their presence or FRUM content—(Lee and Hall, 2001) are responsible for the “slow singing” behavior of fru1 males (Villella et al., 1997; Wheeler et al., 1989).] What about the frusat, fru3, and fru4 mutants, which are also blank for the relevant immunoreactivity in the near-AL region (Lee and Hall, 2001)? These males should be broken-down for normal recognition of a male versus a female—and all three types perform relatively low levels of intermale chaining (Goodwin et al., 2000; Lee and Hall, 2000; Villella et al., 1997). But the severe FRUM decrements in most or all other brain regions would disallow vigorous reproductive behavior, including that which involves the formation and sustenance of courtship chains. One more remark is warranted about the fruitless-expressing brain region now being considered—in context of the aforementioned anatomical sexual dimorphism in this part of the CNS. One possibility that arises from these morphological descriptions, especially those related to male-specific neurite projections (Kimura et al., 2005), is that the fru neurons in question are

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involved in processing chemosensory cues, possibly integrating separate such stimuli. Might it be, therefore, that the pertinent cellular cluster near the ALs is involved in sex recognition via interpretation by a male of pheromonal information received from another fly in his presence? This could be so, but we should also muse about the possibility that visually triggered, male-specific behavior is “important” [see Section II, as well as the microdiscussion of Sharma (1977) and Hing and Carlson (1996), a short distance below]. Therefore, a wild-type fly of this sex might be able to discern the difference between another male and a female by sight: Movement of the latter would generate an optomotor stimulus by virtue of the male’s side-view of abdominal-segment “stripes” moving in the horizontal plane. In contrast, a moving male presents in part a quite different visual cue because of the wide stripe (more of a black box, really) of which his posterior abdomen is composed at the level of external pigmentation. This supposition is modestly supported the effects of mutations that impinge on the flies’ sensory responses; these were joined with homozygosity for fru1. By itself, the latter creates a wide range over which modulation of chaining insensity might occur, in that this fruitless mutation makes males court in groups during about three-quarters of an observation period (see shortly below). But when a blinding norpA mutation or an eyes-absent (eya) one was combined with fru1, the metric used to quantify chaining levels yielded values that were dramatically reduced compared with the effect of this fruitless mutation by itself (A. Villella and J.C. Hall, unpublished): Courtship among three or more males, within a group of eight, occurred 79% of the time for the fru1 control in this case, a “Chaining Index” (ChI) value very similar to those determined previously (Lee and Hall, 2000; Villella et al., 1997). Compared with this ChI ¼ 79  4 (n ¼ 8 male groups), the value for norpA fru1 was 10  1 (n ¼ 8) and for eya fru1 was 14  2 (n ¼ 15). In contrast, a male’s genetic blindness causes relatively modest 2X reductions in “basic” courtship vigor, as measured for male–female pairs (reviewed by Tompkins, 1984). Another double mutant was generated potentially to eliminate the ability of fru1 males to smell their mates; but combining that mutation with parasbl (cf Gailey et al., 1986) caused ChI values to be 53  3 (n ¼ 8). (Three types of fru1/þmale groups were also tested in this experiment, each expressing the fully mutant effects of norpA, eya, or parasbl; all ChI values were 0, n ¼ 6, 10, and 6 groups, respectively.) It must be mentioned that genetic variation at the fruitless locus is not the only causation of intermale chaining, even though the effects of the fru1 mutation represent the most theatrical breakdown of the manner by which a fly of that sex “recognizes” another such individual. But while we are at it: (1) The dissatisfaction mutation (dsf), when homozygous in males, causes such flies to court other males (Finley et al., 1997; Lee and Hall, 2000) and even to attempt copulation with them, which fruitless males do not except for the most mildly mutated type (fru2); dsf mRNA was found by Finley et al. (1998) to be localized

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in “extremely limited set of neurons” within the anterior brain of both sexes (see Section VII for more about dsf effects on females). It is unknown whether any of these cells contain FRU proteins; but this could be so, because (a) one of the three dsf cell-groups in question can be construed to be in the vicinity of the above-mentioned fru-expressing cluster located near the ALs (cf Lee and Hall, 2001), and (b) traF-induced feminization mediated by a dsf “enhancer” caused such transgenic males to perform intermale courtship (Finley et al., 1998). Speaking of transgene effects: (2) Perhaps the most occult case of inducing similar interfly interactions involved stumbling upon what happens when Drosophila ectopically “misexpress” the classical white gene. Thus, Zhang and Odenwald (1995) found that males carrying an hsp-wþ construct chained like crazy after they were heated to induce transcription of wþ (presumably) all over the fly, including throughout the CNS (although this was not assessed directly). These investigators wondered whether serotonin depletion could be occurring when “too much wþ product” is distributed all over the brain. [Oddly enough, the plain-old normal allele of the white gene turned out to be expressed in the brain (Campbell and Nash, 2001)— although it was not very well defined just-where—as well as within the eye and testis sheath.] The WHITE protein in question is a tryptophan/guanine transporter (see FlyBase at http://flybase.bio.indiana.edu/), which puts a precursor of 5-hydroxy-tryptamine (5HT=serotonin) into cells that possess this function. So Trp being soaked up by way more than the usual 5HT neurons within the Drosophila CNS (consisting of a goodly number of such cells, albeit not a huge one, e.g., Valle´s and White, 1988) could cause the latter to be relatively 5HT-diminished. So what? Well, Zhang and Odenwald (1995) made note of some old mammalian studies, in which males treated with inhibitors of 5HT synthesis caused anomalous intermale interactions that included what amounted to chaining behavior (e.g., Gessa and Tagliamonte, 1974). Does the behavioral effect of this hsp-wþ transgene have anything to do with fruitlessness, whether there might be a “serotonin connection” with the latter gene? Follow-ups to Zhang and Odenwald’s study included (1) the demonstration that intermale courtship induced by hsp-wþ is attenuated when the flies cannot see (Hing and Carlson, 1996), which brings to mind an old case of lightdependent (anomalous) interactions among males that was associated with a chromosome aberration (Sharma, 1977); (2) a control test of whether transgenic feminization of brain regions led to intermale courtships (O’Dell et al., 1995) because wþ was included in the relevant transgenes (no: An et al., 2000); and (3) the following findings from Nilsson et al. (2000): A particular fruitless mutations—frusat, which causes near courtlessness when such males are placed with females (Goodwin et al., 2000)—suppressed bisexual behaviors induced by either ectopic expression of white (emanating from hsp-wþ ). This epistatic effect of frusat suggested that the fru gene and the w-encoded transporter act along brainbehavioral pathways that have elements in common.

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D. Transgene-induced courtship among males redux, now analyzed intensively in a fruitless context The molecular-genetic neurobiology just presented with respect to fruitless largely involved descriptive findings. To consider one of the experimental approaches to fru-controlled behavior, we start with a recollection of the fact that combining the C309 enhancer-trap transposon with UAS-shiTS induced fru-like intermale courtship, or caused decrements in male–female interactions, after such transgenic males were heat-treated (Kitamoto, 2002a). An additional courtship defect was specified by Villella et al. (2005), who showed that XY/ C309/UAS-shiTS flies extended their wings (feebly) toward females (cf Broughton et al., 2004) yet generated almost no song sounds (at high temperature); this result was confounded by the poor flying ability of this transgenic type. But if other elements of the courtship defects and anomalies exhibited by C309/ shiTS males are deemed interpretable, would these abnormalities occur because certain “FRUM neurons” are inactivated by shiTS? If so, then C309 and fruitless would be of course coexpressed to some degree. It might follow that, if C309 were to be combined with UAS-traF, males would court one another because of TRAinduced blockage of FRUM production in the relevant GAL4-containing cells. Indeed, C309-induced feminization led to male chaining behavior (Villella et al., 2005). Furthermore, when C309/UAS-traF males were observed in single pairs with wild-type ones, the former behaved with CIs significantly higher compared with those recorded for control male pairs (Villella et al., 2005). One problem with interpreting these findings involves the extensive expression of C309’s gal4. For example, Villella et al. (2005) published pictures showing that XY/C309/UAS-traF flies are externally feminized (albeit not entirely), which makes it difficult to interpret the high levels of intermale courtship just noted. As introduced earlier, one could argue that the chaining behavior observed for this double transgenic type occurs in part because a given (female-oid) courtee elicits male following. In contrast, various fru-mutant chainers, which do not elicit courtship performed by wild-type males in separate tests, exhibit intermale interactions owing to some sort of inherent breakdown in their sex-recognition capacities. That C309 driving traF largely feminizes a male indicates that this driver is expressed during development, as was confirmed for the pupal CNS by direct observation of C309-containing animals at that stage (Villella et al., 2005). This speaks to the etiology of C309/traF-induced intermale courtship: If it is in part due to the transgenic courter’s disinhibition of courting another male (not entirely a matter of the courtees’ elicitation qualities), abnormal development of the C309/FRUM coexpressing neurons may be pertinent. Therefore, malfunction (per se) of these neurons (C309/shiTS) or anomalous formation and cell differentiation of them (C309/traF) could each lead to “too much” courtship directed at the wrong kind of fly.

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In any case, the behavioral findings just discussed suggested that C309produced GAL4 and FRUM protein would be colocalized. Indeed, considerable overlap of C309-expressing CNS neurons with FRUM-immunoreactive ones was observed (Villella et al., 2005)—within 10 of the previously defined 20 FRUM neuronal “clusters” in the CNS (cf Lee et al., 2000). A most conspicuous component of these histological findings is that, irrespective of “staining for FRU,” C309-driven marking was observed in a large proportion of essentially all CNS ganglia (a very different pattern from the way that this transgenic type has been advertised as an “MB line”). Some of the 10 FRUM cell groups that coexpress C309’s gal4 within a subset of their neurons are in the regions of the brain or VNC that have been implicated in courtship behavior (via gynadromorph analyses and the endlessly discussed manipulations of neuronal function effected by applications of other transgenes). Further to analyze the C309/fru connection, this enhancer trap transposon was combined with the fru-inhibitory-RNA construct, mentioned a long way above in conjunction with the “hypercourt” effect of driving UAS-fruMIR within a certain FRUM cluster (Manoli and Baker, 2004). C309/fruMIR males courted wild-type males vigorously in single-pair tests but did not appear feminized and did not elicit courtship (as do XY/C309/traF chromosomal flies). Thus, the C309/fruMIR combination caused only one of the fruitless phenotypes to be mimicked (in that male–female interactions were normal, singing was robust, and these doubly transgenic males exhibited no chaining behavior). Moreover, the C309/traF combination did not create a mimic of C309/shiTS phenotypes: The former male types courted other such males (including chain formation); but these C309/traF transgenic types courted females robustly and sang to them normally, unlike the behavior of C309/shiTS males (Villella et al., 2005). Histological corollaries to the behavioral results are that C309 driving of traF knocked down FRUM immunoreactivity to a considerable extent (but never completely) within a given one of the coexpressing neuronal groups; yet, the fruMIR drivee was far less efficacious in its effects on expression of the (endogenous) fruitless gene (Villella et al., 2005). The erratic “I” effects of this particular “R” construct (cf Manoli and Baker, 2004) exemplify that the inhibitory-RNA ploy is nowhere near a panacea for reverse-genetic approaches to neurogenetic problems in Drosophila (also see Echeverri et al., 2006; Kulkarni et al., 2006).

E. Manipulations of gene expression and neural disruptions effected by transgenes inserted at the fruitless locus Possibly to achieve the most powerful manipulations of fruitless expression, knock-ins of molecular constructs at the genetic locus were effected. General features of such gene targetings, and the homologous-recombination events involved, were previously described (far above in Section II). Certain of the

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incoming transgenes related to the fru cases carried our old friend, the yeast gal4 gene. These knock-ins were targeted to the 50 portion of the locus, near the sex promoter, aka P1, which has been heavily discussed already—vis-a`-vis more downstream promoters that are numbered 2 through 4. This leads to a quick side point of sorts, referring to one of the intragenic fru mutations: fru4; it, like most such mutations, is a transposon insert but not that versatile a one because it does not contain gal4. Therefore, and further to exemplify the matter of how nicely transposon-based gene knock-ins are achieved these days, Dornan et al. (2005) carried out the requisite genetic crosses that resulted in precise replacement of fru4’s “P element” with a gal4-containing analogue. Owing to this intragenic site being well downstream of the P1 sex promoter (e.g., Goodwin et al., 2000; Ryner et al., 1996), Dornan et al. predicted that certain sex-nonspecific promoters would have their activities mimicked by the novel fru4/gal4 variant—in terms of how it would drive UAS-gfp or -lacZ marking. Indeed, reporter expression in these double transgenics recapitulated (but not perfectly) the patterns FRUCOM protein production, inferred by Dornan et al. (2005) to be under the control of fru’s relatively downstream P3 and P4 promoters. These broad-based tissue patterns were assessed both within and without the CNS, in context of the biological significance of FRUCOM proteins extending well beyond the fly’s neurobiology and behavior and being required for normal development of both males and females (see above, especially with reference to Anand et al., 2001). Regarding one of the upstream sex-promoter knock-ins, Manoli et al. (2005) showed that the fruP1-gal4 insert they engineered mediates expression of a GAL-driven marker that seemed faithfully to mimic the pattern of FRUM immunoreactivity (emanating from expression of the endogenous gene in males, present in fruþ /fruP1-gal4 heterozygotes). However, Ferri et al. (2008) showed that all CNS neurons exhibiting marking driven by this fruP1-gal4 are immunoreactive for FRUM, but many additional cells contain the marker (encoded by a UAS-including transgene). In a companion study, Stockinger et al. (2005) also engineered a transgene-driver insert, called fruGAL4, near the 50 end of the locus. When this sex-promoter-controlled knock-in drove a nuclear form of GFP, the marker appeared better to mimic the FRUM pattern in wild-type males (cf Billeter and Goodwin, 2004; Lee et al., 2000). Moreover, as was the case with Manoli et al. gal4 “transcriptional” knock-in, fruGAL4 mediated marker expression in the CNS of both males and females; in general, the numbers of labeled cells within a given FRUM-defined neuronal cluster was the same in both sexes, except that higher number was counted within the fru-aSP2 brain group within the brain of males (Stockinger et al., 2005). Against this background of sex nonspecificity for the spatial expression patterns observed after bringing the yeast transcription factor under fru’s P1 control, questions could be asked as to whether production of FRU protein in a

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male-like pattern would be sufficient to cause females to behave like opposite-sex flies. One way this got accomplished was by Demir and Dickson (2005), who knocked-in constructs that would cause fruitless RNA to be jammed into either male(M)- or female(F)-like modes of alternative splicing (vis-a`-vis primary transcripts emanating, as usual, from the upstream sex promoter). In the fruM version of these knock-in types, the female-specific region of the relevant upstream “sex exon” was deletable (by inclusion of a recombinase-encoding transgene that scissors out this cassette, which had been engineered to be DNA targets of that enzyme). For the fruF type of knock-in, a point mutation had been created at the male splice donor site, with reference to the same sex exon, which would result in an absence of posttranscriptional processing at that site, but otherwise would not affect FRU coding potential of the anomalously unspliced transcripts. A third 50 -knock-in was produced: the fruDtra type, predesigned to be deleted of RNA nucleotides normally recognized by TRA protein in females. One prediction stemming from these gene manipulations was that, when female splicing is forced in males (fruF), such flies should exhibit little or no courtship toward females. This was indeed the case (Demir and Dickson, 2005), indicating that the male mode of splicing in flies of that sex is crucial for mediation, by whatever are the pertinent neurons, of male-specific behavior. But fruF expressed in XY flies has at least one positive influence on sex-specific behavior: This transgene type was found to make chromosomal males “fight” females (much moreso than to court them), in observations of flies placed within a chamber “designed to promote aggressive interactions” (Vrontou et al., 2006). These experiments were rooted in sex-specific aggression that is believed to be part of Drosophila’s behavioral repertoire. Background: D. melanogaster males and those of certain other species exhibit interactions that are arguably antagonistic (e.g., Dow and von Schilcher, 1975; Ringo et al., 1983; reviewed by Kravitz and Huber, 2003); and fru mutant males exhibit aggression-like “head buttings” (Lee and Hall, 2000), which were later interpreted to be like the fighting bouts exhibited in groups of genetically normal females (cf Nilsen et al., 2004). Returning to the main matter at hand—courtship—the actions of Demir’s and Dickson’s fruM and fruDtra constructs in female nervous systems were predicted to cause such flies to behave in a male-like manner (because male-like splicing was designed to occur within the requisite neurons). Indeed, both such XX knock-in types courted other females (Demir and Dickson (2005). However, the quantified levels of such courtships were significantly different from the performances of various control males (Demir and Dickson, 2005). For example, females engineered to be molecularly male-like (fru-wise) exhibited more tapping behavior, much less licking, and fewer wing extensions compared with control males. (Courtship songs were not recorded for these fru-engineered flies.) Another (predicted) control result was that females harboring the fruF knock-in construct did not court companion flies of that type. All in all,

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however, male-like splicing of fru transcripts within the “proper” tissue substrates of sex-specific behavior (owing to knocking the fruM and fruDtra constructs into the requisite promoter region) can be provisionally deemed sufficient for “any” fly to perform at least partially in a male-like manner. Further implications of these results will be discussed below. Manoli et al. (2005) made contemporaneous attempts to elucidate these matters of necessity and sufficiency. First, they applied their fruP1-gal4 knock-in to drive UAS-tra2 Inhibitory RNA in females, designed to masculinize FRUM neurons in flies of that sex. (This tra2IR construct should bring down the level of endogenous tra2þ mRNA and putatively mimic the effect of a tra2 mutation, which is to turn an XX Drosophila into a male, mostly.) Such manipulated females, in the presence of wild-type ones, performed early steps of the male courtship sequence—orientation and tapping—but not the later ones: no wing or proboscis extensions, no copulation attempts. These masculinized females could, however, be coaxed into displaying male-like wing extensions and licking events when numerous fruP1-gal4/UAS-tra2IR females were placed with a single normal male. He courted the transgenic females (who should not have had their overall “attractiveness” affected by these gene manipulations), and these nearby behavioral events (perhaps involving sound stimulation) induced the fruP1-gal4/ UAS-tra2IR flies to exhibit occasional bouts of wing extension and licking (directed at the other transgenic females in their midst). Once again, the male mode of fruitless gene expression turned a female into fly that behaves like male, but only modestly so. The availability of GAL4-encoding DNA brought under the control of fru’s sex promoter facilitated additional appraisals of the gene’s spatial expression. For this, a whole-animal marking tactic (using UAS-gfp, naturally) led to the discovery that many PNS structures and sensory neurons within most of them were labeled (Billeter and Goodwin, 2004; Manoli et al., 2005; Stockinger et al., 2005). This widespread peripheral pattern included (1) the developing eye (transient expression only, during metamorphosing flies examined by Manoli et al., 2005), but not observed in photoreceptors (Stockinger et al., 2005), and (2) ORNs within the third segment of the antenna that project to 3–4 glomeruli of a given AL. With regard to the latter sensory subsystem, Stockinger et al. (2005) observed their fruGAL4 ORNs projecting to glomeruli called DA1, VA1v, and VL2a (weaker staining was seen in other such intra-AL targets). The DA1 and VA1v structures are located close together and are larger in males than females (Kondoh et al., 2003); VL2a exhibits the same kind of sexual dimorphism (Stockinger et al., 2005). It is worth dropping in a related sex-genetic study that was performed with regard to the morphology of DA1: Feminization of this glomerulis—induced by ectopic expression of traF in a male, naturally—caused it to develop into relatively small female-like structure (Kondoh et al., 2003). One problem connected with this result was that flabbily apprehended

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expression of the pertinent gal4 enhancer trap (including but not limited to antennal sensory neurons and “some central” ones) made Kondoh et al. “unable to specify the cells that mediated the traF activity to reduce the volume of the DA1 glomerulus in a male.” And as has always been the case when portions of an XY fly got transgenically feminized this way, it was unknown whether this particular TRAF effect was acting through fruitless. (Did the only meaningful demasculinization in this AL situation involve RNA transcribed from that gene?) This brings us back to expression of that gene in additional PNS locations: Thus, marker signals brought to light by knocking gal4 into the fru locus were observed (variously) by Billeter and Goodwin (2004), Manoli et al. (2005), and Stockinger et al. (2005) in the JO (which contains auditory-receptor neurons), proboscis (GRNs), maxillary palps (olfactory), forelegs (gustatory, mechanosensory), a few (presumably) sensory neurons of the mid- and hindlegs, wing “joints” (near where these appendages extent from the thoracic box) plus the dorsal radius of this appendage, and finally in neurons contained within the male’s external genitalia (observed in both of the knock-in-based studies). Needless to say, these peripheral structures can be apprehended to play roles in courtship and mating, although the sensory-functional meanings fruitless expression within these widely dispersed PNS neurons is unknown. For example, do such cells need to be genetically male (thus FRUM-producing) for “any” malelike behavior to occur? No, because certain gynandromorphs with, for example, external femaleness on the entirety of their head capsules courted (wild-type) females, with the proviso that such mosaics contained single-X tissue within their brains (Section III.A). So, for now, only the descriptive features of fruitless expression in the PNS warrant comment, in context of the “nervous-system-specific” pattern defined by immunoreactivity of the male-specific protein having previously been documented only by way of whole-mounting CNS specimens (e.g., Lee et al., 2000; Usui-Aoki et al., 2000). Inasmuch as PNS stainings mediated by antiFRUM seemed to be the same as marking driven by fruP1-gal4 (Manoli et al., 2005), the current view of this gene’s spatial domain now means PNS plus CNS. Manoli and coworkers concluded, furthermore, that no sex differences were defined by marker expressions driven by fruP1-gal4 in single- versus double-X flies. Whereas this is probably not really true (cf Kimura et al., 2005), it is valuable to reiterate that a “transcriptional insert” of the type just italicized could lead to largely equivalent production of GAL4-encoding RNA in males and females, because the male-specificity of native fruþ expression emanating from the sex promoter principally involves posttranscriptional events. The specifics of the fru-targeted site for the construct under consideration predicted that flies homozygous for fruP1-gal4 should possess no immunoreactivity for FRUM, with reference to all of the relevant antibodies having been

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produced using the male-specific N-terminal oligopeptide as immunogen. Indeed, such homozygotes were unstained after one of these serum types was applied (Manoli et al., 2005). This modest adjunct to the study turned out to involve a more than workmanlike finding, because the following conundrum arose: The initial behavioral findings presented by Manoli et al. (2005) were that males homozygous for fruP1-gal4 males did not court females at all. This is as it should be, if such flies possess no male-specific FRU protein, which means something different than an absence of staining mediated by application of anti-FRUM. However, we found that the original fruP1-gal4 homozygous type of male does court females (Ferri et al., 2008); the average CI was ca 30, a value 40–50% of that routinely recorded for wild-type male–female pairs. When we replaced the white-eye mutation carried within the fruP1-gal4 strain (as originally gene-targeted and inserted), wþ males homozygous for the knock-in gave a normal average CI of about 75. Moreover, when fruP1-gal4 was placed heterozygous with other fruitless variants (including a deletion of the entire locus), the resulting males courted females quite vigorously, with CIs in the range of 60–80. To drive home the point that the fruP1-gal4 knock-in comes nowhere near eliminating male courtship, fertility values for w or wþ fruP1-gal4 homozygotes were 60% (n ¼ 20) and 90% (n ¼ 30), respectively, and 88% for fruP1-gal4/fru3 (n ¼ 40). Therefore, the narrow-sense conclusion is that the male-specific “M” component of FRUM, the above-mentioned N-terminal oligopeptide, is not necessary for male courtship. What about behavioral effects of the analogous gal4 knock-in, acting alone? First, a digression about homozygosity for this fruGAL4 insert in females, and that Stockinger et al. (2005) found such XX flies to be fully viable and fertile. In contrast, females homozygous for fruP1-gal4 exhibited 0% fertility (Ferri et al., 2008); mercifully, the causation of this phenotypic oddity was demonstrable as not mapping to the fru locus (the site of the knock-in). Second, to the main matter at hand: the behavior of males homozygous for Stockinger et al.’s fruGAL4 insert (which, incidentally, was not examined as to whether this knock-in caused an absence of FRUM immunoreactivity). These flies courted (wild-type) females within normal ranges, different from the erroneous claim made for fruP1-gal4 homozygotes by Manoli et al. (2005). However, when fruGAL4 was placed in heterozygous condition with either fru3 or fru4, such males gave drastically reduced courtship values (Stockinger et al., 2005). Moving on to the matter of mutant fertility, Stockinger et al. (2005) reported that homozygous fruGAL4 males were subnormal for this character: a % mating value of ca 45, compared with wild-type performances (which are typically near 100%); and the decrements were worse when fruGAL4 got placed over either fru3 or fru4. Our further examination of this aspect of the reproductive capacities of such flies (A. Villella and S. L. Ferri, unpublished observation) led to fertility percentages of 97% for fruGAL4/fruGAL4 males (n ¼ 30) and a ca 40% reduction in fertility for the fruGAL4/fru3 type (n ¼ 25).

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Pulling together the pertinent courtship quantifications and fertility values from the reports of Manoli et al. (2005) and Stockinger et al. (2005)— and pitting them against the reevaluations just given for these behavioral assessments—we are left with something better than negative implications of an erratic array of findings. More to the positive point: The absence of FRUM immunoreactivity, known so far to result from homozygosity for one of the gal4 insertions into the fruitless gene (Manoli et al., 2005), does not mean that the relevant neurons lack the remainder of FRU polypeptides. Such cells do not so lack (see below), which means that the male-specific N-terminus possessed by a (usual) FRUM polypeptide is not necessary for male behavior. How to rationalize these results? For this, RT-PCRs were performed on flies carrying fruP1-gal4 (Ferri et al., 2008). The upstream primer type was complementary to a sequence located in the 30 direction from fru’s sex promoter and in the 50 one from the gal4 insert site. The specific location of the latter is diagrammed by Manoli et al. (2005); the former (P1) was specified in highresolution molecular detail by Billeter and Goodwin (2004), including that this regulatory part of the gene contains a “downstream promoter element” (slightly 30 of the transcription-start site, cf Kutach and Kadonaga, 2000). The 30 primer type for this RT-PCR analysis corresponded to a portion of the aforementioned BTB domain (a motif contained in all FRU isoforms, downstream of where the male-specific AAs are located within a FRUM polypeptide). Amplicons resulting from the requisite RNA extractions and primer applications implied the existence of transcript types, emanating from the fruP1gal4 “allele,” that would have resulted from posttranscriptional in-frame splicing “from” the vicinity of P1 “down to” the BTB-encoding portion of fruitless’s open-reading frame. So, the more upstream coding sequence that specifies the “male N-terminus” was inferred to have been skipped over. Therefore, under sex-promoter control, FRU protein should be present within neurons that usually express fruþ in males to generate FRUM; but the fruP1-gal4 homozygotes in question would lack the male N-terminus for the protein in these cells. It follows, once again, that the intrinsic male-specific quality of FRU proteins within these male CNS neuron is not the key consequence of fruitless gene expression, insofar as courtship enabling is concerned: The male-specific attribute of the polypeptide (in wild-type flies) is dispensable, as long as a goodly amount of FRU is present in the correct neural locations (also at the right life-cycle stages). A final fillip to this substory is that Stockinger et al. (2005) carried out RT-PCR tests to ask whether any sex-specific transcripts (with largely full ORFs) are derived from the P1 promoter region “damaged” by their fruGAL4 insert, in males homozygous for the knock-in. Such mRNAs were detected in this manner, although at markedly subnormal levels. An irony suggests itself about the reproductive behaviors associated with the gal4 knock-ins (per se), which is that none of these insert effects were necessarily compelling to examine phenotypically. This means that one of the principal

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opportunities presented by bringing a (heterologous) transcription factor under the control of fru’s sex promoter would involve driving molecular disruptors (in addition to applying the tra2IR transgene noted above). Thus, Stockinger et al. (2005) set up to block synaptic transmission in most neurons that normally express fruitless. They combined fruGAL4 with a construct that included DNA targets (designated “>”) of the FLP recombinase along with a transgene called eyeless-FLP that makes this (yeast-derived) enzyme in adult derivatives of the eye/antenna imaginal disc. The drivee of fru-controlled GAL4 was UAS>shiTS>stop. The latter item within this construct contains stop codons, so shiTS would be expressed in all fru neurons except the sensory ones that (naturally) express the eyeless (ey) gene. These triply transgenic males courted females subnormally at a restrictive temperature (with reference to the heat-sensitive shiTS mutation). A more local disruption of synaptic transmission was achieved by combining fruGAL4 and ey-FLP separately with UAS>stop>shiTS or UAS>stop>tnt. Now only ey-expressing fru sensory cells would be neurally “silenced,” with the idea that FRUM functions within ORNs of the antenna were the principally relevant disruptees. The results were that fru-controlled GAL4, driving UAS-shiTS in this spatially local manner, caused males to court females much less than did control males at a restrictive temperature compared with a permissive one. Reduced courtship levels were also observed for the fruGAL4/eyFLP/UAS>stop>tnt males. (These decrements were similar to those observed when shiTS was blocking synaptic transmission “all over” the fru pattern except within ey-expressing cells.) When analogous flies were scrutinized for their expression pattern by combining fruGAL4, ey-FLP, and UAS>stop>MEMBR-gfp, GFP was detected in the fru ORNs, JO within the antenna, optic lobes, MBs, and few cells within the VNC. Therefore, reduced courtship levels for males carrying the disruptor of synaptic transmission may not be specifically due to shiTS or tetanus-toxin affects on fruGAL4 ORNs. To ramp-up toward a further test of fruitless olfactory-neuron function, a preliminary experiment was performed: The fruM females in the study of Demir and Dickson (2005) were placed with other males that had feminized pheromones; such partly female-like males were created by combining oenocyte-gal4 transgene with UAS-traF (cf Ferveur et al., 1997). These feminized males elicited courtship from the fruM flies but otherwise appeared and behave like normal males. That these sex-transformed XX flies would court partially transformed XY flies indicates that this “neuronally male” type does not need female-like optomotor cues to in order to court the male-appearing oenocyte-gal4/UAS-traF flies. In any case, relevance of the sensory inputs at hand was focused upon by testing quadruply-transgenic XX flies: fruM/fruGAL4/ey-FLP/UAS >stop>shiTS or UAS>stop>tnt. Both types courted subnormally, compared with the no-shiTS and no-TNT situations (Stockinger et al., 2005). Referring to the original experiment of this kind, involving straight XY males, “leakage” of the disruptors into non-fru

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parts of the nervous system might have occurred somehow, whereas the fruM situation provides sharper focus on only the neurons that were made to be malelike in an overwhelmingly female setting. An additional fru-based manipulation of ORNs was effected by Manoli et al. (2005). They combined their fruP1-gal4 (heterozygous with an untransformed chromosome) separately with the UAS-traF feminizer and with the UAS-shiTS blocker of synaptic transmission. The resulting males exhibited no courtship behavior (for the latter doubly transgenic type, after such flies were heated to bring the damaging effect of shiTS into action). Having in mind that fruP1-gal4 was described to direct marker expression with the olfactory system (see above), Manoli et al. (2005) dealt with this matter experimentally. The behavior in question revolved round the aforementioned habituation-like “learning” that occurs during and after a normal male is paired with courtship-eliciting immature one (Gailey et al., 1982, 1985; Vaias et al., 1993). In the current case, FRUM was putatively decremented via UAS-fruMIR, under the control of either Or83b-gal4, a driver that is active in most ORNs, or SG18-gal4, whose expression pattern overlaps that of fruP1-gal4 in terms of ORNs that project to the “fru-targeted” glomeruli noted above. Males carrying either of these transgene combination types did not habituate (Manoli et al., 2005): They sustained nearly same levels of courtship directed at young males during a 1-h observation period, compared with the ever-decreasing courtship that occurs when a wild-type Drosophila is paired with a same-sexed but immature male. These experiments exemplify the utility of this fruP1-gal4 insert—as a driver of disruptive factors, which can lead to meaningful results, as opposed to the supposed courtship decrements caused by homozygosity for this knock-in (alone). With respect to other features of experience-dependent courtship, the MBs had been previously interrogated only in terms of conditioning males by exposing them to mated females (Fig. 3.3). Further in this regard, Manoli et al. manipulated fruitless expression of the male MB, in context of the following: No such signals were detected during the pupal stage (cf Lee et al., 2000), but “weak” fru expression was observed in the region of the MB’s Kenyon cells within young-adult males. When fruP1-gal4 was combined with UAS-MEMBR-gfp, green fluorescence was detected in the -lobe axons of the MB and in a few such neurites within the and -lobes. [These findings can be sandwiched with observations, reported by Billeter and Goodwin (2004), of sexually dimorphic expression of FRUM in the MB.] Inhibition of FRUM production, using UAS-fruMIR driven by various MB-gal4 enhancer-traps that are expressed differentially among the lobes, led to FRUM depletion either throughout the entire MBs or in its -lobe neurons and caused males to be conditioned subnormally after exposure to mated females; fruMIRinduced inhibition in only - and -lobe neurons was efficacious as well but caused less-marked reductions (Manoli et al., 2005). These results may (or may not) add much to our understanding of the neural substrates underlying associative courtship conditioning. But this substory at least draws our attention to a connection of the

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yet another genetic factor with the MBs. And it should be recalled that this structure is sexually dimorphic in wild-type Drosophila (Technau, 1984). Furthermore, “fru in the MBs” comprises one feature of the temporal dynamics by which this gene is expressed at varying levels across late stages of the life cycle. In light of this feature of fruþ expression, most contemporary studies have focused on the gene-products’ presence within the nervous system of mature flies. What is going on during metamorphosis in terms of a putative neuralformation role for this gene has been tacitly downplayed. Another investigation that concentrated on fru expression in adults took a different tack compared with the knock-in approach. Thus, Billeter and Goodwin (2004) created a more oldfashioned type of fru-gal4 fusion transgene. A 16-kb fru-DNA fragment flanking the P1 promoter in the 50 direction was used to produce GAL4. However, the spatial pattern poorly mimicked the normal FRUM one in the CNS of adults: Not all such (usual) neurons neurons contained GAL-driven marking, and there were many “extra” such cells that were devoid of any FRUM immunoreactivity (which turned out unfortunately to be true, as well, with regard to expression of Manoli et al.’s fru gal4 knock-in). This is sort of like an enhancer-trap deal, such as the one highlighted by C309: partial overlap of gal4 expression with that of fruþ in males and extension beyond where the latter gene normally makes its product (Villella et al., 2005). With respect to the inadequacy and “supranormalilty” of the fruregulatory DNA fused to gal4 by Billeter and Goodwin (2004), it would seem as if this 16 kb of 50 -flanking DNA lacks some of the enhancers present at the chromosomal locus and also is missing hypothetical fru “silencer” sequences. Nonetheless, Billeter and Goodwin (2004) used their fru(16)-gal4 transgenic type to present entry-level results pertaining to fruitless expression in the PNS [elaborated more famously by Manoli et al. (2005) and Stockinger et al. (2005)]. Within the CNS, the highest degree of overlap between FRUM and fru (16)-gal4 was observed by Billeter and Goodwin (2004) in the ABG subset of the VNC (64% of neurons stained by an anti-FRUM contained GAL-driven marking). It could be, therefore, that some of the caudally projecting axons from the fru(16)gal4 neurons would innervate the MOL. Even though formation of these malespecific structures had been known since the 1980s to require “input” from genetically male neurons (see above), it was not until the current century that fruitlessness came explicitly into the picture. Thus, Billeter and Goodwin (2004) showed that certain ABG neurons, whose axons contained fru(16)gal4-driven MEMB-GFP transgene, contact the MOL and that such neuromuscular junctions are sexually dimorphic in morphology. The latter feature of these findings was already on the table, actually, thanks to a previous study that involved different transgene-based tactics. Thus, Usui-Aoki et al. (2000) ectopically expressed fru cDNAs under the control of a transgene called D42-gal4, which is transcribed in most motor neurons but not in muscles. Certain such neurons, emanating from the ABG and contacting the MOL, exhibited the same kind of male/female difference confirmed by Billeter and

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Goodwin (2004). The latter results were not superfluous because both the diver and the drivees [fru(16)-gal4 and UAS-fru/cDNAs] were fruitless specific, at least in part, whereas the D42-gal4 applied by Usui-Aoki et al. (2000) is not. When those investigators combined the motor-neuron driver with a UAS-fru cDNA construct, MOLs formed in female abdomens. This was the first demonstration of “fru sufficiency” for elaboration of a male-like character (cf Demir and Dickson, 2005; Manoli et al., 2005). The fru cDNAs fused downstream of UAS worked even if such proteincoding material could not produce the male-specific N-terminal AAs contained (by definition) within the FRUM polypeptides of wild-type XY Drosophila. Therefore, the study of Usui-Aoki et al. (2000) provided the first finding that spoke to the extra 101 “M” residues—a salient element of FRU proteins produced in the male neural pattern—being unknown as to their functional significance. Remember that producing M-less FRU protein in the “right places” was also good enough to allow for male-specific behavior. So, perhaps the male-specific N-terminal AAs are a vestigial molecular appendage to the FRU polypeptides in question. In this light, Gailey et al. (2006) showed that this portion of a male-specific protein is distinctly nonconserved when comparing FRU in D. melanogaster to what is encoded by the corresponding portion of the fru ORF in a mosquito. Yet, this limited interspecific comparison was misleading in a way—because Ferri et al. (2008) showed that nucleotide sequences encoding FRU’s M amino acids are highly conserved among Drosophila species closely related to D. melanogaster.

F. Behavioral and neural meanings of separate FRU-protein isoforms: Posterior CNS neurochemistry and connections with the doublesex gene The following introductory points are considered against a background of the demonstrations and inferences presented by Usui-Aoki et al. (2000) plus Billeter and Goodwin (2004), with respect to fru functioning on behalf of MOL formation. Here, the functional meaning of other kinds of FRU isoforms will come into play. We refer to the “30 splice” variants that create an array of polypeptides varying according to different ZnF pairs harbored within ORF DNA at the fruitless locus. First, Usui-Aoki et al. (2000) determined that they could rescue MOL nonformation, caused by homozygosity for the frusat in males, with either A- or C-type isoforms of FRU [using the terminology of, e.g., Anand et al. (2001) and Billeter and Goodwin (2004), to name these polypeptides that vary among their relatively C-terminal regions]. Other fru cDNA types (harboring separate 30 -splice variants) were ineffective. Production of FRUA or FRUC was induced in these mutant males by the D42-gal4 motor-neuronal driver and in a separate test by driving fruA or fruC sequences with a generic heat-shock promoter (Usui-Aoki et al., 2000). For MOL rescue by the latter, hsp-fru(cDNA) transgenes were activated between the third-instar larval stage through the pupal one; no rescue

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was observed when animals were heated during earlier stages. Thus, and as previewed above for ectopic FRU expression within the posterior motor neurons of females, the male-specific FRUMA or FRUMC polypeptides are not required for MOL development in males (referring to the fact that FRUA or FRUC are representative of the proteins that are “in common” between males and females and not expressed in the FRUM like pattern within an XX nervous system). Billeter et al. (2006b) made a further application of their fru(16)-gal4 construct to show that this driver could rescue fru-mutation-induced absence of the MOL, but only if such males carried a C-type FRU isoform; neither the A nor B type was effective, a result that does not jibe with an element of Usui-Aoki and coworkers findings. However, and as expected from Usui-Aoki et al. (2000), who drove expression of UAS-fruC by introducing D42-gal4 into chromosomal females (the hsp-fru construct did not work): fru(16)-gal4 caused developing females to form an MOL (Billeter et al., 2006b). Application of this sex nonspecific (transcriptional) fruitless driver worked in XX flies only when the drivee was FRUM-C (the possibly efficacy of an M-less FRUC-encoding construct was not tested). The meaning of these transgenic manipulations was given a significant boost by induction of the first fruitless mutant that involves a primary molecular change within the gene’s coding region. (To respecify a previously made point: all other in-vivo-produced mutants are caused by transposons inserted within fru’s largest intron or by chromosomal breakpoints.) Thus, Billeter et al. (2006b) induced a nearly sterile fru mutant by placing chemically treated third chromosomes in heterozygous condition with a deletion of the genetic locus. The effect of the mutagen was to remove seven base pairs from a relatively 30 region of the fru ORF; the attendant frame shift should eliminate FRUC isoforms and only them. This was confirmed by application of antibodies specific to different kinds of Zn-F-varying polypeptides. This mutation was named fruDC. Among the effects of homozygosity for it are (1) subnormal courtship in the presence of females and substantial intermale chaining behavior [modest spatial expression of UAS-fruMC, driven by the partly adequate fru(16)-gal4 transgene created by Billeter and Goodwin (2004), failed to rescue these behavioral subnormalities and anomalies but did restore high-level fertility to fruDC males]; (2) external morphological defects, analogous to those exhibited by the dying pharate adults that are largely devoid of all fruitless products (Anand et al., 2001), which jibes with the molecular genetics of fruDC: its intragenic deletion should cause an absence of C isoforms that either contain the male-specific N-terminus or the male- and female-produced proteins that are devoid of these AAs (i.e., FRUCOM polypeptides); and (3) the lack of MOL formation by nearly all such males, even though 10% of these fruDC flies exhibited subnormally formed versions of this abdominal muscle (Billeter et al., 2006b). Specifically, FRUMC-less males develop four small muscles in the “MOL region” (cf Taylor and Knittel, 1995), each of which is innervated by a motor

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neuron, whereas only one such axon (projecting from a fru-expressing cell body) ramifies over the large MOL in a wild-type male (Billeter and Goodwin, 2004; Billeter et al., 2006b; cf Usui-Aoki et al., 2000). The abdominal phenotypes caused by fruDC are similar to the effects of severe fru mutations that affect production of all the C-terminal isoforms. Recalling that the latter type of mutant defect is rescued for MOL formation by transgenically adding only the FRUMC form (in experiments by Billeter et al.), the additional inference derived from the fruDC effect on this male-specific muscle is that the C form of FRUM is the only one that controls neural induction of MOL development. A fair fraction of the experiments prompted by the discovery of this isoform-specific fruitless mutation was dedicated to an influence of this gene on the serotonin content of certain ABG neurons. Background: (1) Lee and Hall (2001) found that FRUM colocalized with 5HT immunoreactivity in a small number of ABG neurons in males (there is no such FRU protein here in females, by definition, and the relatively large FRUM/5HT cells appeared to be anatomically malespecific). (2) Various fru mutations either decreased the cellular extents of 5HT (e.g., fru1) or eliminated such staining entirely (e.g., fru3)—that is, from the relevant coexpressing cells (Lee and Hall, 2001; Lee et al., 2001). It follows that (3) many additional CNS neurons in Drosophila contain this neurotransmitter (Valle´s and White, 1988) but are FRUM-less; and because almost 2K CNS neurons normally express this protein, only a tiny proportion of them are serotonergic (again, only a small handful of cells in the ABG). The further set of phenomena that are worth certifying here (before fruDC comes into play, 5HT-wise) revolve around (1) innervation of internal male-reproductive organs by axons projecting posteriorly from FRUM/5HT cell bodies; (2) subnormal numbers of such neurites in terms of 5HT immunoreactivity deficits, in fru-mutant males carrying genotypes that allow for semifertility, correlated with their ejaculation defects (Lee et al., 2001; Villella et al., 2006); and (c) labeling the (usually) FRUM/5HT axons with a nerve-terminal marker in males that were genetically FRUM-less, which led to the conclusion that there is normal anatomy of the reproductive-organ innervation pattern (Lee et al., 2001)—that is, all the relevant neurites seemed to be present but were devoid of serotonin. That transmitter substance is not the only neurochemical factor function on behalf of “intramating” activities (as delved into most intensively with regard to fru and 5HT by Villella et al., 2006): Acebes et al. (2004) transgenically manipulated cholinergic neurons in the ABG of males, and certain of these genetic treatments succeeded in separating the effects of seminal-fluid constituents on female fecundity versus receptivity to subsequent matings (cf Section IV). As Billeter et al. (2006b) began to delve into the fruitless-related features of “mating neurochemistry” (not in this case related to intramating behavior), they discovered an additional cluster of FRUM/5HT cells within the ABG. The newly identified serotonergic (S) neuronal group is in a more ventral (v) region of this VNC structure than the dorsal location (dS) of the

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originally discovered cluster (Lee and Hall, 2001). Neither the vS-ABG cluster nor the dS-ABG one contained 5HT immunoreactivity in FRUM-null mutants (compared with normal males, in which both the ventral and dorsal cell groups are composed of ca 10 neurons that coexpress male-specific FRU along with serotonin, with the axons projecting from each cell group innervating the same male organs). More interesting, probably, was the finding that an average of ca 20% and 5% of the normal complements for dS-ABG and vS-ABG cells (respectively) were 5HT-positive in males that were genotypically null for FRUMC (created by Billeter et al., 2006b, via generation of males heterozygous for fruDC over fru3). It follows that other Zn-Finger FRU types should be involved in this process (unlike the MOL situation); and whereas adding UAS-fruMA to a genotype null for all FRUM’s did not rescue any 5HT neurons in the ABG, UAS-fruMB induced such differentiation for a subset of the dS-ABG cluster; and adding UASfruMC led to partial rescue within both the dorsal and ventral cell groups (Billeter et al., 2006b). Therefore, two of these FRUM Zn-F forms act additively on behalf of these neurochemically differentiated cells—not redundantly, which would have been concluded if, for example, the remaining presence of FRUMB in the fruDC mutant had fully covered the effects of that mutation. Findings from wildtype males that fit with the additivity conclusion came from applying the isoform-specific antibodies mentioned above: FRUMC was detected in all FRUM neurons, but FRUMA exhibited a much more restricted pattern and was undetectable in fru-controlled 5HT neurons of the ABG (Billeter et al., 2006b). Now, and in distinct contradiction of the earliest report about fru-mutational effects on this “neurochemical sub-system” within the VNC, Billeter et al. (2006b) showed that either globally FRUM-null or specifically FRUMC-null types of males exhibited subnormal numbers of organ-innervating neurites (the latter genotype being less severe in its effects, assessed by applying a “neuronal-membrane-specific antibody” different from the reagent used by Lee et al., 2001). A correlated result was that the fruDC mutation caused numbers of ABG neurons stained by an anti-FRUM (which detects all of the C-terminally varying isoforms) to be reduced from ca 285 to 245. Among the tests of how “non-C” isoforms could be involved in these processes was the demonstration that FRUM-null males were partly rescued for 5HT-positive neurons in the dS-ABG cluster by driving UAS-fruMB (there was no effect on serotonin’s absence in vS-ABG cells); but UAS-fruMA was ineffective. However, expression within female ABGs of any of the three isoforms in question (FRUM-A, -B, or -C) caused appreciable proportions of such flies to exhibit “ectopic” 5HT neurons, which would mean that either novel cells formed or “extra” ones took on this cell-differentiation quality (in context of a plain-old female already containing 5HT cells in this region of the VNC); additionally, nerve terminals connecting to certain female reproductive organs, which are not serotonergic in wild-type females, were immunoreactive for 5HT in these partly masculinized transgenic flies (Billeter et al., 2006b).

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The final feature of this FRU-isoform study to be discussed brings in a sexrelated gene that was briefly introduced in Section V.B: doublesex. It was discovered by a mutation that makes either XY or XX flies look equivalently intersexual in terms of their external morphology. As was noted earlier, dsx became firmly entrenched in the SDH, largely by demonstrating that the gene’s primary transcript is sex-specifically spliced under the control of TRA and TRA-2 proteins (reviewed by, e.g., Baker et al., 2001; Billeter et al., 2006a). What gets molecularly targeted by the TRAs is a set of repeated nucleotides within an untranslated region of dsx RNA. Who cares? Well, one of the molecular “entry points” for cloning fruitless was based on the idea that that hypothetical SDH gene might also harbor “doublesex repeats” (cf Heinrichs et al., 1998; Lam et al., 2003). Indeed, this led to the isolation of genomic clones that hybridized to a repeat-containing probe; one type of such isolates molecularly defined part of the fru gene (Ryner et al., 1996). Unlike the manner by which fru expression is “downstream of the TRAs,” dsx mRNAs produce sex-specific proteins in both males and females; these alternative forms of DSX are ZnF proteins differing at their C-termini. One consequence of this molecular genetics was the demonstration that a special dsx mutation jams the gene’s posttranscriptional expression into the male mode in flies of either chromosomal sex; therefore, XX Drosophila affected by this mutation are thoroughly malelike in their external appearance, but they do not court females (Taylor et al., 1994). This brings us to the notion that—with both of these SDH factors operating roughly and at the same level within this hierarchy of gene interactions—dsx could be devoted to most of the “general” aspects of sexual differentiation, with fru homing in on neural and behavioral features of sex specificity. Musing about this possibility goes back many years (Taylor et al., 1994) and has been amplified to a canard that keeps cropping up in the secondary literature— for example, the statement that “with the exception of the central nervous system, the Dsx proteins determine the sexual fate (male or female) of each somatic cell of the fly” (Vincent et al., 2001). To dispense with this notion that the actions of dsx are dramatically skewed in a “nonbehavioral” direction, let these pieces of background information be registered (before we return to the matter of sex-specific differentiation of serotonergic neurons): With regard to active aspects of male courtship: (1) dsx mutations in XY flies caused subnormal behavior in the presence of (wild-type) females (Villella and Hall, 1996), although not down to the very low levels inferred from testing the effects of one mutant allele (McRobert and Tompkins, 1985); and whereas XY flies homozygous for a given dsx mutation vigorously generated pulse sounds by performing courtship wing vibrations, they never produced the “sine song” (hum) component of this male-specific behavior (Villella and Hall, 1996). As a further test of doublesex’s influence on male behavior (2): Combining heterozygosity for such mutations (dsx/þ ) with fru-variant combinations that by themselves cause rather high levels of intermale courtship caused such doubly mutant males to exhibit reduced levels of these homosexual interactions (Shirangi et al., 2006).

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As far as explicit contributions of dsx to sexual neurobiology are concerned: (3) Recall the male-specific expression of a gustatory-receptor gene studied by Bray and Amrein (2003), who showed that chromosomal females homozygous for a dsx mutation (thus devoid of the DSXF protein normally possessed by XX flies) ectopically exhibited the male-like foreleg pattern of Gr68a expression; these mutant intersexes do not make FRUM, because they are chromosomally female, focusing one’s attention on dsx control over this feature of PNS sex-specificity. With respect to dsx in the CNS: (4) The gene is unequivocally expressed in the brain and VNC of both developing and mature Drosophila; a few discrete clusters of neurons and glia were stained by anti-DSX in late-larvae, pupae, and adults of either sex; the numbers of such cell groups and cells per se were many fewer than those defined by the overall fruitless CNS pattern (Lee et al., 2002). Within one CNS region—the ABG, which that contains the most DSX-immunoreactive cells (Lee et al., 2002)—coexpression of this protein and FRUM was examined, and ca 50% of the former type of cells were also immunoreactive for the male-specific fru product (Billeter et al., 2006b). With regard to involvements of doublesex in female-like qualities: (5) Homozygosity for dsx mutations made XY flies elicit abnormally high levels of courtship as performed by (wild-type) males (Villella and Hall, 1996). And dsxþ males ectopically expressing DSXF were vigorously courted by other males (likely due to the induction of female pheromones by presence of the female-specific protein in males, cf Jallon et al., 1988); such elicitation qualities were enhanced when DSXF expression was ectopically mediated in XY flies mutant for dsx, which completed the sequence by mating with wild-type males (Waterbury et al., 1999). After identifying the dead-ringer (dri) sex mutant (aka retained) in a behavioral screen for mating-deficient females: (6) Adding heterozygosity for a dsx mutation to a particular retn/retn genotype, which by itself caused a modest decrement in female receptivity, enhanced this abnormality (Shirangi et al., 2006). The same “sensitizing” effect of dsx/þ occurred with regard the malelike behavior of females carrying two retn mutations: the extent to which the latter genotype caused such a female to court another one was enhanced >3X when heterozygosity for a dsx mutation was included in the genetic background. (The case of retained is elaborated further within Section VII.) An influence of doublesex on the fly’s pheromonal quality (Jallon et al., 1988; Villella and Hall, 1996; Waterbury et al., 1999) is not a neural issue but does involve internal tissues (cf Ferveur et al., 1997), by analogy to dsx regulation of yolk-protein production in females (see Vincent et al., 2001). This is one of the reasons that dsxþ expression within the CNS (Lee et al., 2002) did not come as a shock. The relevant descriptive study (just cited), which reinvigorated ideas about a neural role for doublesex, harks back to a customarily ignored study, which detected male-specific neuroblasts within the developing ABG; their

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formation was found to be under dsx control, in context of the attendant neurogenesis being extended into early metamorphosis in wild-type males but not females (Taylor and Truman, 1992). Developmental result: 20 “extra” neurons within this portion of the VNC in males, loosely analogous to the sexspecific neuron-number difference observed by Kimura et al. (2005) within one region of the brain. Sustained formation of those anterior-CNS cells are under fru control and involve a different mechanism (sex-specific cell death). Given the influence of fruitless on the neurochemical quality of certain ABG neurons and the findings of Taylor and Truman (1992), it seemed natural to ask whether these serotonergic cells are affected by doublesex. Thus, in dsx-null XY flies, about half the number of the male-specific 5HT cells were observed; both dSABG and vS-ABG neuronal clusters were similarly affected (Billeter et al., 2006b). In dsx-null XX intersexes, ectopic 5HT neurons were observed, with three to four extra such cells detected in a dorsal or ventral region of the ABG (depending on the individual). Homozygosity for the tra mutation in chromosomal females was assessed for effects on these posterior-CNS cells, given that these sex-transformed animals express both DSXM and the FRUM isoforms: As if both protein types would be required for normal formation, differentiation, or both of the S-ABG neurons— their numbers and intraganglionic distribution in the XX tra/tra flies were found to be the same as in wild-type males (Billeter et al., 2006b). These findings should deepen one’s appreciation of doublesex as in part a neural gene. It can act in concert with fruitless, if you will, referring to an involvement of both genes in the development and intracellular quality of neurons within a discrete portion of the CNS. And within a subset of ABG neurons, DSXM and FRUM proteins may act as sharply defined companion factors, alluding to partial overlaps of the expression domains for the two genes. Comparing the separately determined spatial patterns (Lee et al., 2000, 2002) permits a guess that fru and dsx may also be coexpressed within more anteriorly located ganglia, but this has not been determined. Yet, colocalization of these gene products could not possibly be “total” because so many fewer CNS cells harbor DSX compared with those that contain FRUM. Moreover, the DSX content of certain CNS glia means that they could not be FRU cells, all of which were found to be neurons by coexpression of a pan-neuronal, nonglial protein called ELAV (Lee et al., 2000).

G. Gene targets surmised to be under the control of hypothetical FRU transcription factors None of the characterizations of FRU polypeptides—that they all contain a BTB domain-along with ZnF ones—established these proteins as transcription factors, nor did the results of manipulating the latter motifs, which on paper allow such molecules to bind to DNA. Other better-characterized BTB/Zn-F proteins are, however, known from biochemical studies to be transcriptional regulators

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(Collins et al., 2001). Nevertheless, discussion in the previous subsection of abdominal-ganglionic neurons that contain serotonin, with the proviso that fruþ is functioning in these cells, suggests that certain specifiable factors are directly regulated by FRU polypeptides. Such hypothetical DNA targets would comprise portions of the genes that encode dopa-decarboxylase and tryptophan hydroxylase (both of which are well in hand molecularly: FlyBase, http://flybase. bio.indiana.edu/). These enzymes catalyze the synthesis of 5HT in a two-step process starting with the substrate tryptophan. And Ddc mutations (in a gene whose product uses two substrates) are known to cause 5HT decrements, along with reducing dopamine levels (reviewed by Restifo and White, 1990). There is one recently obtained mutation at the Trh (aka DPHN) locus; its neurochemical effect (lower-than-normal levels of 5HT immunoreactivity in the CNS) was recently reported (Neckameyer et al., 2007). Despite the fact that one effect of fru mutations on 5HT-containing ABG neurons is developmental (Billeter et al., 2006b), the remaining cell bodies and neurites that should contain this substance in such mutants can be hypothesized to fail to express Ddcþ, Trhþ, or both because there is no FRUM available to activate these genes. How could this be? FRUM is neither necessary nor sufficient for 5HT production in general: Many Drosophila neurons contain this neurotransmitter but do not express fruitless, and the overwhelming majority of FRU neurons do not make serotonin (Lee and Hall, 2001; Valle´s and White, 1988). Here, then, is a possible scenario: The 5HT-synthesizing enzymes are activated by transcription factors other than FRU in most of the relevant cells; in the few such neurons that express fruþ and contain the neurotransmitter, at least some of the usually required “other” factors are not present, so FRU helps do the job. Further in this regard, FRU would form transcriptionally active heterodimers in the 5HT cells— partnering let us say with another BTB transcription factor (cf Collins et al., 2001)—one that may participate in activating the enzymes in question within non-FRU neurons. This BTB-with-BTB association of the two polypeptides would be necessary and sufficient for 5HT production within the ABG neurons under consideration, but non-FRU cells would “cope” with synthesis of this neurotransmitter by virtue of separate kinds of BTB:BTB protein associations. These ostensibly errant speculations are worthy of reflection because of the idea that different kinds of neuronal functions should come under fruitless control, depending on the varying locations within the nervous system where the gene is expressed and owing to the compelling notion that, for example, FRU neurons within a given brain region mediate different sex-related functions compared with other such neurons located elsewhere (such as in some subset of the VNC). In other words, FRU should not control activities of the same downstream genes in separate portions of its expression domain. This supposition almost certainly connects with tissue-specific alternative splicing, which leads to the presence of certain isoforms worth of FRUM ZnF transcription factors (probable

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such proteins) in only a subset of the overall male-specific expression pattern of the gene (Billeter et al., 2006a,b). This scenario allows for the obvious possibility that qualitatively different kinds of regulatees could be in play, depending on which cofactors are expressed along with a given form of FRUM within the cells of a given cluster of fruitless neurons. Furthermore, the gene targets of FRU, in terms of how those polypeptides participate in their transcriptional control, must involve both the development of certain “sex neurons” and the acute functional capacities of other such cells. This redeclaration about the gene’s versatility is warranted for three reasons: (1) fru’s sex promoter is expressed during the second half of the fly’s development, and it continues to be active in mature flies. (2) Formation of certain neural and neuromuscular structures come under the sway of fruitless actions, with regard to discrete elements of the gene’s expression domain (Billeter et al., 2006b; Gailey et al., 1991a; Kimura et al., 2005). (3) Neuronal differentiation of other fru neurons—unrelated to their formative anatomy, but involving their intracellular content—requires the ongoing action of the gene in mature flies (Billeter et al., 2006b; Lee et al., 2001, 2006). This statement is connected not only to serotonin molecules contained within the relevant neurons of the posterior CNS but also to additional entities that would be regulated downstream of fruitless action (see below, including Section VI). There are not yet “that many” candidates for controlees of FRU. But the two more-or-less hard contenders are rather interesting in their own rights (as opposed to comprising genes that would be investigated solely from the “reductionist” perspective of a transcription factor binding to regulatory DNA, irrespective of the coding sequences that are being regulated). Thus, the yellow (y) gene was found to be influenced by fruitless. Arguably, the (upcoming) molecular and cellularly based questions were asked in part because y mutations have long been known to cause subnormal male courtship activities and mating abilities. These studies go all the way back to what was probably the first behavioralgenetic investigation, performed by Sturtevant (1915). Males expressing a given y mutation were subsequently assessed for their reproductive-behavioral capacities in varying degrees of detail (Bastock, 1956; Burnet and Wilson, 1980; Dow, 1975; Drapeau et al., 2006; Threlkeld et al., 1974; Wilson et al., 1976). One could imagine that the body-color anomaly exhibited by yellow flies (by definition), and their less than thoroughly healthy overall biology, are what underlie the mutants’ mediocre courtship. In this respect, y males do not exhibit truly discrete behavioral deficits. They are unlike certain fru mutant types that are qualitatively “blocked” at a given courtship step (Fig. 3.4), nor is an individual feature of the behavioral sequence “specifically” aberrant (as in the case of Drosophila “song mutants,” which are depicted above in Fig. 3.4 and mentioned below in Section VII). Having said this, Drapeau et al. (see below) surmise that y mutations may primarily cause decrements in male wing extension behaviors at

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an intermediate step of the courtship sequence (cf Fig. 3.4). Having said that, it is not easy to imagine how the normal yellow gene product (http://flybase.bio. indiana.edu/)—a molecular relative of “royal jelly protein” in bees (Albert et al., 1999)—might be involved in neuronal functions that subserve a particular courtship action or any other kind of behavior. In any case, this speaks to the fact that factor’s biological significance extends beyond pigmentation of the cuticle: Y protein is found within the CNS of maturing Drosophila larvae, and several of the apparent neuroblasts determined to possess immunoreactivity to this protein were observed to be stained by antiFRUM (Radovic et al., 2002). These cells are located in the dorsoposterior brain of third-instar larvae, at the stage when the fru “sex promoter” is activated shortly before metamorphosis commences (e.g., Lee et al., 2000). As far as can be teased out from the more extensive subsequent study of this phenomenon (Drapeau et al., 2003), all FRUM larval-brain neurons were immunoreactive for Y; but additional cells of the latter type, in males and females, did not express fruþ. To determine whether the coexpression is more than a coincidence, the (usually) FRUM/Y neuroblasts were scrutinized in the nearly FRUM-less fru3 and fru4 mutants (cf Lee and Hall, 2001), and such brains did “not have elevated Yellow levels.” This alludes to the fact that neuroblast staining for the royal-jelly protein is, in wildtype larvae, appreciably more intense compared with that observed in nonFRUM cells (Drapeau et al., 2003). This study confirmed that no FRUM is detectable in second-instar larvae (cf Lee et al., 2000), nor did the brains of such animals exhibit Y immunoreactivity. However, a UAS-fruþ construct, encoding a certain FRUM isoform (Usui-Aoki et al., 2000), led to yellow expression in the brains of second-instar larvae when it was activated by the developmentally promiscuous pan-neuronal elav-gal4 driver, and Y staining in third-instar female brains was boosted to the high male-like level in this doubly transgenic type (Drapeau et al., 2003). [The FRUM polypeptide expressed here under GAL4/UAS control had been called “B” by Usui-Aoki et al. (2000)—aka C-type in the argot of Anand et al. (2001), Billeter et al. (2006b), and authors overlapping with these investigators.] Drapeau et al. (2003) showed further that, by driving a separate UAS-fruþ encoding FRUM of the “A” ZnF type, they “did not find a single instance of upregulation of Yellow” (cf analogous effects of isoform-specific UAS-fruþ s on MOL formation). Thus, adding FRUM containing the appropriate ZnF pair to brain tissue at the “wrong” time or place was sufficient to mediate expression of a factor that (somehow) acts downstream of fruitless. To put some phenotypic meat on these molecular neurobiological bones, Drapeau et al. (2003) asked whether “ectopic” (including presumably boosted) expression of normal yellow coding DNA would cause an increase in wing extension—compared with that displayed by a y mutant male, whose

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courtship actions of this type are on the order of one-third to one-half normal, but nowhere near zero. Thus, when UAS-yþ was driven by an Actin driver or a so-called “third instar CNS-specific” gal4 transgene—in males carrying a y mutation—Wing-Extension Indices (proportions of observation periods during which such wing displays occurred) increased to 33% and 37% (respectively), compared with the control value of 18% (recorded for y males carrying UAS-yþ but no driver). [These values are valuably compared with WEIs measured for fru3 and fru4 in the presence of females: 0% and 2%, respectively (the former mutant type did intermittently extend its wings in recordings of male–male pairs); control WEIs determined in parallel for wild-type males and those heterozygous for fruþ and either fru3 or fru4 were in the range of 45–59% (Villella et al., 1997).] So, the yellow gene product remains in business as not only a courtship factor but also one that is connected with neural-specific fruitless expression. Owing to the narrow focus on Y protein in the larval CNS, it is unknown whether y and fru are “coacting” as developmental factors within the neuroblasts in question, or whether the former gene via its regulation by the latter is gearing up to play a functional role in the eventually behaving male. A final substory about an apparent piece of neurochemistry that is influenced by fruitless began to be told by describing the spatial distribution of neuropeptide F (NPF) within the larval brain of Drosophila. This substance is similar to neuropeptide Y in mammals (which has nothing to with insect YELLOW!). Lee et al. (2006) provide references to this background information in context of their own study that focused mostly on the brain of adult flies. These investigators ended up connecting NPF with sexually dimorphic neurochemistry and with Drosophila’s rhythm system, including certain “clock neurons,” which have been heavily analyzed in many earlier studies (reviewed by Hall, 2003, 2005). For NPF’s part, the basic features of its neurobiology were given a boost by Lee et al. (2006), who first showed that the small number of larval neurons containing this substance (n ¼ 6) is expanded during metamorphosis: About 26 pairs of neurons contain npf mRNA in the brain of an adult male; ca 20 pairs of such cells were counted in mature female brains (Lee et al., 2006). An npf-gal4 transgene drove marker expression (emanating from UAS-gfp) that was congruent with the wild-type pattern and included the same sexually dimorphic feature. With regard to the above-mentioned clock neurons, certain of the male-specific NPF neurons implied by the cell counts just given seemed as if they might coincide with a cluster of brain cells long known to express rhythm-related genes, notably period (per) and timeless (tim). The dorsolateral neuronal group in question (LNd) indeed is such that about half of the cells within it (2–3 of ca 6, per hemibrain) coexpress the npf gene along with TIM immunoreactivity. Furthermore, either of two clock mutations—in the Clock (Clk)

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and the cycle (cyc) genes, which together activate expression of per and tim in the various LN cell groups—nearly eliminated npf mRNA from the usual subset of such neurons (Lee et al., 2006). An additional level of regulation suggested itself from the fact that npf is expressed mainly in the LNds of males; an average of less than one such cell contained the product of this neuropeptide gene in females (whereas per and tim exhibit no such sexual dimorphism). Furthermore, two discrete sets of NPF neurons (among the 26  2 total) were found to be completely male-specific, consisting of ca three pairs and one pair of such cells. Inevitably, perhaps, fruitless came into play when it was found that (1) anti-FRUM colabeled the malespecific npf neurons (marked in this test via npf-gal4/UAS-gfp) and (2) a FRUM-eliminating genotype (the so-called Df combination noted in Fig. 3.4) abolished the male-specific npf RNA signals; also, the severely FRUM-depleted fru4 mutant exhibited ca three- to tenfold decrements of npf-positive cells, depending on which of the male-specific cell groups was being counted. There were no effects of fru variants on the sex-nonspecific NPF neurons (distributed among five-cell groups beyond the three pointed to within the foregoing passages), nor did a doublesex mutation affect numbers of npf RNA-containing cells in the sexually dimorphic groups. The sex-specific component of this neuropeptide’s expression pattern appears to have functional meaning. This was gleaned from the effects of combining npf-gal4 with one of the aforementioned types of UAS-cell-killers: Males carrying both transgenes showed decreased courtship vigor; much of the decrement was accounted for by the stretched-out latencies exhibited by these brain-damaged flies in terms of how long it took them to start interacting with females (Lee et al., 2006). As far as rhythm-related behavior is concerned, npfgal4/UAS-ablater males, but not the corresponding females, displayed subnormal “evening anticipation” compared with the usual ramping up of locomotion that occurs toward the end of the light period of a 12-h:12-h light:dark cycle (Lee et al., 2006). This prompts one to wonder “what is going on” with regard to coregulation of the npf gene (within certain types of brain neuron), by the three transcription factors that were interrogated for their effects in this study. In other words, or least as a for instance: Are FRUM, CLK, and CYC proteins simultaneously targeting an npf regulatory sequence in LNd brain cells, such that if any one of these factors is missing: no NPF production? Or might a fruitless function be devoted to regulating npf via its first-stage regulation of Clk and cyc within this highly localized portion of the CNS? As a final fillip, we mention in passing another brain neuropeptide, a 13-mer called SIFamide. Transgenically mediated ablation of the (merely) four neurons in a dorsal-brain neuroendocrine structure called the Pars Intercerebralis (PI) that contains this substance led to a fru-like behavior—“indiscriminate” courtship by males directed at other flies of either sex (Terhzaz et al., 2007).

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Driving a UAS-SIFaIR construct with the SIGa-gal4 transgene just implied led to the same courtship anomaly. No sexual dimorphism associated with the peptide’s presence within the PI was recognized, which in a way fit with the fact SIGa-gal4/ UAS-SIFaIR females also behaved abnormally by exhibiting faster-than-normal mating receptivity (Terhzaz et al., 2007).

VI. NEUROGENETIC RELATIONSHIPS BETWEEN THE REGULATION OF REPRODUCTION AND RHYTHMS The NPF factor and genetic effects on its brain expression provide an entre´e into the last subtopic within this chapter. The question that arises accordingly is whether there is a “special” connection between the regulation of reproduction and rhythmicity. Or, do so many behavioral and neural genes in Drosophila act pleiotropically “anyway” (Hall, 1994b) that something like npf could easily turn out to be making its product within certain cells that are sex neurons as well as clock ones? One way to approach sex-with-rhythm connections is to consider sexual dimorphisms of the latter phenotypes. One should perhaps start by registering that wild-type male and female Drosophila exhibit differences in their patterns of daily locomotor cycles (Helfrich-Fo¨rster, 2000), against a background of locomotion more generally being accompanied by sexual dimorphisms in this insect. The latter phenotypes have been explored as to how they are controlled by neuroendocrine factors (Belgacem and Martin, 2002) and other humoral entities (Belgacem and Martin, 2002, 2006). But a “factor” that is more on point within the current section is rhythm mutation with sex-differential effects: This is the aforementioned cycle mutant (due to the original cyc01 null mutation in the gene), which has been tested for phenomena associated with sleeping fruit flies (reviewed by Ho and Sehgal, 2005). Thus, Drosophila homozygous for cyc01 exhibited abnormal “rest-rebound” after they were “sleep-deprived”; this compensatory quiescence was exaggerated in females and largely absent in males (Hendricks et al., 2003) or was such this flies of this sex “recovered 100% of lost sleep” (Shaw et al., 2002). That this mutant male type does not exhibit properly “healthful” behavior in this context seemed correlated with the demonstration that cyc01 shortened the life span of males but not females [Hendricks et al. (2003); cf other sleep-associated lethal effects of this mutation, as reported by Shaw et al. (2002)]. The foregoing passages do not establish the cycle clock gene to be also a sex factor per se. And fruitless mutants, incidentally, exhibit no readily appreciable abnormalities for their daily locomotor rhythms (Villella et al., 1997). This brings us back to our “main” genes because there is a further instance of fru being

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tied to the function of a chronogenetic factor (in addition to the npf connection). Thus, consider takeout (to), a gene discovered by So et al. (2000) who isolated an mRNA present at anomalously low concentration in extracts of flies expressing the cyc01 mutation. to transcripts were subsequently shown to exhibit a daily cycle of oscillating RNA levels (So et al., 2000). This gene encodes a relatively small protein (larger than NPF, however), whose sequence implies it to be a secreted factor that binds small lipophilic molecules. The TAKEOUT (TO) polypeptide also exhibits a daily oscillation with the same peak time as for the encoding mRNA (Sarov-Blat et al., 2000). takeout was reidentified in “microarray screens” performed to identify rhythmically expressed genes and those whose overall levels are affected by clock mutations (as initially reported by McDonald and Rosbash, 2001). This widely applied molecular tactic (reviewed in a rhythm context by Etter and Ramaswami, 2002) encountered—among a plethora of cycling mRNAs—additional transcript types that encode molecules related to TO, thus the takeout “gene family.” There is minimal evidence as to the chronobiological significance of TAKEOUT and its protein relatives, although Sarov-Blat et al. (2000) presented some dubious evidence about a behavioral deficit exhibit by a to mutant in context of monitoring such flies for daily rhythms of generic locomotion. (This mutant was serendipitously found to be segregating in a laboratory stock.) These investigators oddly missed the fact that to makes its products almost exclusively in males (Dauwalder et al., 2002). In this regard, most of what is known about the biological meaning of TO is in the realm of reproductive genetics. First, to was shown to be activated in males by the combined actions of the doublesex and fruitless genes (Dauwalder et al., 2002). The DSXF transcription factor present solely in females largely represses to expression in Drosophila of that sex (with no fru involvement). Furthermore, a to-gal4 fusion transgene constructed by Dauwalder et al. (2002), then introduced into males carrying UAS-traF (a combination that mediates DSXF production within to cells), caused such flies to exhibit markedly reduced courtship in the presence of (normal) females. When this type of gal4 transgene drove UAS-marker expression in males, the tissue pattern was essentially the same as that of native toþ (e.g., certain PNS structures and thoracic alimentary ones). A conspicuous part of the pattern encompassed fat-body (FB) tissue near the brain and less intense marking of fat cells distributed throughout the thorax and abdomen. Fujii and Amrein (2002) and Wolfner (2003) discuss additional kinds of connections between fat bodies and Drosophila genes with sex-biased expression. Dauwalder et al. (2002) detected neither to products nor marker expression mediated by that gene within the CNS—referring to an irreproducible feature of Sarov-Blat et al.’s results (supposed brain signals in adult flies, whose sex was not specified). Finally, the straight to mutant was tested by Dauwalder et al. (2002) for male courtship and found to behave subnormally (but only in one

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genetic background). With regard to fruitless involvement, there were synergistic such defects when the takeout mutation was combined with heterozygosity for each of two separate fruitless mutations. (The fru homozygotes would have been largely epistatic to any to effect, because the former cause such severe behavioral decrements.) How could the action of toþ interact with those of fruþ , given non-CNS expression of the former? Lazareva et al. (2007) interrogated this matter in context of takout’s FB expression. An FB-gal4 transgene was created (using regulatory DNA cloned from a poorly named Larval-serum-protein gene) that drove UAS-marker expression in the FBs of developing and adult Drosophila. Such tissues were then feminized by combining the driver with UAS-traF in XY flies—which were shown to court females subnormally. These experiments included a dissectional component from the perspective of life-cycle stages: An FB-gal4 construct with a quite short regulatory sequence, which drives expression only in larval FB tissues, did not cause courtship abnormalities when combined with UAS-traF (Lazareva et al., 2007). Nonetheless, courtship relevance of the FB’s sexual nature in adult Drosophila drives home the point that not all features of male-specific behavior come under the sway of fruitless gene action in the nervous system. We now revive a consideration of the fru-gene manipulations in XX Drosophila—those that which were aimed at turning them into “she-males” that would court other females. These flies did do, although in overinterpreted manners, because quantitative and even some qualitative features of the courtship displayed were substandard (Section V.E). Possibly to improve the situation, Lazareva et al. (2007) recreated one type of fru-effected she-maleness and genetically augmented the degree of masculinization by including the FB-gal4 (adult-expressing) transgene to drive a UAS-tra2IR construct (cf Section V.E). This addition made the relevant multiply-transgenic XX flies court females in an enhanced manner—although still not up to par with reference to the robustness of wild-type male behavior. Nonetheless, the principle restated here is that neural masculinization, effected by diddling fru expression alone, is insufficient for thoroughgoing maleness. The role played by TAKEOUT-“releasing” tissue, as to how something about that protein could be interacting with the manner by which neuronal maleness underlies sex-specific behavior, was examined by looking for TO protein in the adult hemolymph. Antibody-mediated signals were observed when the diffusible proteins were taken from males, but hemolymph from to mutant males or from females was blank for TO-ir. Therefore, it was surmised that the circulating TAKEOUT polypeptide could get to a male’s CNS, somehow to modulate the function of sex-related neurons. A dollop of additional zest was added to this study, by Lazareza et al.’s wondering whether TO might ooze into the hemolymph from a tissue source in addition to the FB. They drew upon the courtship decrement exhibit by homozygous to-mutant males that were simultaneously heterozygous for a fru mutation (cf Dauwalder et al., 2002).

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This compound genotype was augmented by including either of two kinds of oenocyte drivers (cf Section II.A), each of whose GAL4 productions activated UAS-toþ (in separately generated types of doubly transgenic, doubly mutant males). The result was “full rescue” of the fru- plus to-induced courtship subnormality (Lazareva et al., 2007). Elements of the substory just told connect loosely with other ways that rhythm-related factors have been transgenically manipulated—in part to ask whether reproductive behavior would go awry. Thus, introducing a novel type of neural disruptor into “clock cells” was effected by application of a transgene that includes regulatory DNA cloned from the timeless gene; this famous chronogenetic factor was introduced above in context of brain cells that contain NPF. Here, a tim-gal4 construct was joined with one in which UAS was fused to a sequence encoding a neurotoxic protein called MJD. The latter contains polyglutamine (polyGln) repeats and is named after named after a neurodegenerative/elongated-polyGln mutant in humans called Machado-Joseph Disease. The former tim-containing transgene should (and does) drive marker signals in the brain’s clock cells (cf Lee et al., 2006), but neither it nor the endogenous timeless gene are well enough characterized as to whether they are expressed in the fatbody tissue of the fly’s head (reviewed by Hall, 2005). This apparently stray remark is made because infusion of the microarray approach into the MJD situation uncovered mRNAs whose levels were affected by combining tim-gal4 with UAS-MJD. Some such gene products had been shown to be sex-specific and located within certain brain regions as well as in fat-body tissue flanking that part of the CNS; among the genes encoding such materials were members of the takeout family (Kadener et al., 2006). Could these molecular findings be related to the possibility that takeout variants “act through” fruitless by the former affecting fat-body functions, which somehow would interface with sex-related ones operating within the brain? Unknown, but it must be mentioned that the timgal4/UAS-MJD combination led to decrements of FRUM immunoreactivity normally observed in certain dorsolateral brain regions (Kadener et al., 2006). Finally, and to provide an another connection between courtship and circadian rhythmicity, tim-gal4/UAS-MJD males or females paired with unimpaired flies of the opposite sex performed very poorly in terms of mating initiation; there was an especially pronounced deficit for the doubly transgenic males (Kadener et al., 2006). Presumably these effects were “neuronal”—not fat-body mediated—although this supposition is based on MJD toxicity advertised to be specific for the former cell types. Coexpression of fruitless and clock factors does encompass part of the neural domains of the respective genes (Lee et al., 2006). But matters revolving round fru are appreciable solely from the perspective of maleness (and by the way, mutations in that gene have no detectable effect on female courtship or mating: Villella et al., 1997). Therefore, the “female effect” of tim-gal4/UAS-MJD may

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occur through brain cells expressing the timeless gene that are unknown as to their significance for flies of that sex. In this regard: recall that female receptivity “maps to the head” and the brain (concluded from mosaic experiments), and register that tim makes its products within ca 75 pairs of brain neurons as well as in hundreds of glial cells in that part of the CNS (reviewed by Hall, 2003, 2005). A more interpretable effect of the tim-gal4/UAS-MJD combination on behavior was that this transgenic type exhibited severe arrhythmicity for its general locomotion (Kadener et al., 2006). All conventional wisdom about timeless control of circadian rhythms says that the gene’s expression within a certain subsets of TIM’s spatial pattern within the brain is responsible: Other tim-involved transgene manipulations of within and among these CNS locations in cells have led to various abnormalities of daily rhythmicity (reviewed by Hall, 2003, 2005). The seminal clock gene discovered in any organism is period in D. melanogaster (reviewed by Hall, 2003). Various effects of per mutations and manipulations of that gene on behavior have established an additional array of connections between rhythms and sex. Remember from before the rhythmic component of courtship song and—its ca one-minute periodicity notwithstanding—that circadian mutations affect the cycle duration associated with this acoustical character. There is some neurobiology related to analysis of rhythmic singing because a period mutation was found to exert its effect on the short-term rhythm via the VNC (Konopka et al., 1996), whereas per’s influence on daily locomotor cycles are seated within the brain (inferred from a variety of geneticmosaic tests of this supposition, in addition to the one performed by Konopka et al.). With reference to the latter CNS region containing several clusters of so-called clock neurons (ca 150 of them, as introduced above), the thoracic and abdominal ganglia possess only “PER glia” in terms of immunoreactivity for that protein (Ewer et al., 1992). It is a total mystery as to how the function of these nonneuronal VNC cells might modulate the “song circuitry” (if there is such a thing), to influence the oscillatory feature of song-pulse production. Easier to appreciate it seems are daily rhythms of mating propensity in Drosophila (Sakai and Ishida, 2001; Tauber et al., 2003). This cyclically varying phenomenon is affected by per-gene variants—possibly reflecting an element of the fly’s “basic” locomotor rhythmicity. Peak “mating times” are temporally similar to one of the daily maxima for general locomotion, and recall that behavioral “parameters” associated with such behavior are subtly different for wild-type males versus females (Helfrich-Fo¨rster, 2000). This influence of the period gene on sexual behavior warrants two sets of remarks (brief ones, because neurobiological knowledge has yet to be obtained with regard to the following): (1) per mutant females were found to be responsible for changes in the (usual) components of 24-h periodicity associated with this reproductive-behavioral cycle (Sakai and Ishida, 2001), as if the “propensity” in question is a matter of female receptivity to male mating attempts. (2) Variations of mating proclivity described for D. melanogaster

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versus D. pseudoobscura males and females are regulated by the period gene (which of course differs molecularly between these two species): An interspecific transfer of perþ (cf Wheeler et al., 1991)—cloned from the latter species and transformed into melanogaster hosts—caused such transgenic flies to take on pseudoobscura-like reproductive rhythmicity (Tauber et al., 2003). Because both behavioral rhythms and learning and memory are pieces of biology rooted in time bases, it was imagined that rhythm mutants might be defective in experience-dependent phenotype as well. With respect to shortterm features of conditioned courtship, the first test of this supposition yielded positive results (Jackson et al., 1983), although these findings proved largely irreproducible (Gailey et al., 1991b; van Swinderen and Hall, 1995). This doleful state of affairs would not be worth mentioning if the matter had not resurfaced. Thus, longer-term components of conditioned courtship (discussed in Section IV) were reported to be altered by period mutations (Sakai et al., 2004). Again, nothing is known about the neurobiological underpinnings (if any) that would connect this feature of reproductive behavior to the action of a clock gene. This brings us to the last wheeze worth of a point to be made within this penultimate part of the piece: If only because the phenotype just referred to involves an element of female-linked reproduction, which has been underanalyzed in neurogenetic studies of Drosophila, why not register that specific features of the above-mentioned brain control of overall behavioral rhythmicity are not cellularly connected with the manner by which a daily rhythm of oviposition is regulated (Howlader et al., 2006)? One of the discursive points to appear in the final section, which commences immediately below, will touch further on female-specific biology and behavior.

VII. CONCLUSIONS AND PROSPECTS The behavioral neurogenetics of Drosophila reproduction has come a long way. The question we pose at the outset of this final section is: how far has it come? Is our understanding of these processes ever deepening these days; or, for example, are we stuck at the level of contemplating too many inadequacies, ambiguities, and conundrums? It is fair to say that, from modest beginnings during the 1970s, studies delving into the fly’s nervous system have expanded dramatically. This refers, first, to the “culture” of genetic neurobiology in Drosophila, which seems to have warmed to analysis of behavior. Plain-old behavior genetics was the caboose of the investigatory train for quite a while: The phenotypes gave one the impression that they were too “soft,” compared with more solid, more worthily studied phenomena such as neural development. But such adult actions seem no longer to be apprehended as involving merely amusing and otherwise marginal

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phenotypes—an emerging attitude adjustment that dovetails with the second reason underpinning the fact that many contemporary investigators are going after an understanding of factors substantively involved in the Drosophila behavior: Tools for neural and molecular dissection of these activities are being discovered or made available with increasing frequency. The words “factors and tools” refer to genetic entities that are pointed to by more than identification of chromosomal variants; these items, and instruments with both high-level and more mundane attributes, are also in hand molecularly. This makes their substantive nature as well as manipulability more interesting and forceful, compared with the more “superficial” studies that were performable in the early days only at the level of phenogenetics. Thus, certain molecular-genetic investigators have entered this subfield by virtue of their interest in sex as such: “Can I understand maleness or femaleness by exploiting ‘hard’ articles that seem to pointing the way?” Other neurogeneticists have developed entry-level knowledge about factors involved in function of the nervous system “in general,” followed by the realization that certain such items point to sex specificity. Take chemosensory control of behavior, for example. Following the lead of molecular neurobiologists studying mammals, most of the olfactory- and gustatory-receptor genes are now identified in D. melanogaster. What if studies of the encoded products stayed stuck at the level of how the molecules receive “any” chemical stimuli (such as artificial odorants)? These investigations would probably include elucidation of details of about how the stimuli are transduced within sensory neurons. But such studies might eventually become as dry as dust, if analysis of whole-animal behaviors did not also become a part of the “system.” Therefore, reception by the fly’s antenna of courtship odors, and by the male or female legs of contact-chemosensory cues, suggests potentially beguiling avenues of inquiry. These investigatory routes—the starting points for which included male-specific expression of a “courtship gene” in the antenna and the same kind of expression of a gustatory receptor in the male’s legs—would presumably proceed into the CNS as to how the stimuli are processed to mediate sex-specific behavior. Before these gedanken studies come to the fore, it would be warranted to identify definitively the actual stimulating molecules: Next to nothing is known about what a male may taste as he taps or licks a courtship partner. And how other pheromones are putatively smelled remains substandard in terms of knowledge about the several differentially located sensory cells that are no-doubt involved. (A side point here is that the identification of so-called aphrodisiac substances has never been deepened to learn whether the long-chain hydrocarbons are smelled or tasted; also, it is unlikely that the two current candidates for this kind of material are the only aphrodisiacs involved.)

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Nevertheless, certain incipient studies are in the wind as to which chemosensory organs could be involved in courtship control (because of descriptive sex specificity) and whether they are implicated (via damages inflicted on the structure of function of peripheral cells or interneurons located at relatively early stages of the anatomical pathways). But the positive results from these experiments—that is, substantial courtship decrements—seem minimally to take account of studies performed earlier. The latter involved “low-tech” manipulations of putatively relevant sensations. Whereas the simple surgeries performed were intrinsically uninteresting, compared with the design and construction of neuralmanipulating transgenes, one cannot denigrate this old-fashioned approach. We are not merely scolding the “modern experimentalist” here, but instead pointing to the substantive matter of integrating multiple sensory stimuli, as to how this phenomenon underlies the initiation (at least) of male–female interactions and how these processes may also be involved in the male’s tendency to avoid sustained courtship of another male. The “integration” issue in question is signified by the fact that little or no courtship decrements occur when only certain limited chemosensory organs are removed from wild-type flies. In contrast, elimination of visual inputs—via simple darkness or application of blinding or of optomotorblinding mutations—leads to more substantial courtship and mating impairments. And causing a male to be mute, by elementary removal of his wings, has a marked negative effect on the female’s mating receptivity (even though a songless male courts her normally). But visual and acoustical cues are not all-out necessary either because these sensory-deprived flies remain robustly fertile (given enough time for the requisite male–female interactions). In any case, here is something for the future: Where do all kinds of sensory inputs end up in terms of sex-specific CNS processing and (thus) integration? Can “PNS neurogeneticists” get unstuck from chemosensory monomania (referring in part to identification and manipulation of interneurons in these pathways)? At least for the sake of reproductive phenomena, it would be great if PNS-to-CNS signals originating from visual and acoustical stimuli would come online in terms of neurobehavioral knowledge. For the latter kind of sensory input, it seems that some of those who contemplate the antenna as in part a “PNS sex organ” have in mind that they are only dealing with olfactory stimuli, subconsciously downplaying the fact that this appendage is also the fly’s ear. For the former sensation, vision, Drosophila neurobiology needs better to understand where and how these stimuli are processed within the CNS—deeper than the many “optic-lobe” studies that have been devoted to the phenomenon. We made note of the first foray into this morphological matter (Otsuna and Ito, 2006) and await further progress of this kind (the authors just referred provided a preview of three further reports about how optic-lobe interneurons connect with the central brain). This incipiently sanguine state of visual affairs refers to the basics of the situation, in advance of us wondering whether sex-specific

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optomotor stimulation can be elucidated neurobiologically. Further in this respect, we need to consider how the multiplicity of externally originating cues seem to converge by eventual identification of the hypothetical integration centers that are implied by the synergistic effects of several separate sensory inputs. In other words, one gap in our knowledge involves the current lacuna that would be defined by interneurons communicating between multiple sensory structures and deep-brain ones that are beginning to be identified in terms of sex specificity within subterranean portions of the CNS. There will be more discussion of the latter structures below. Meanwhile, a brief return to the matter of courtship song. If only because this behavior involves such discrete and measurable actions, it would be great if more than reception and processing of the acoustical inputs could be better understood. In other words, song stimuli are intrinsically interesting, in part because of their specificity: Only one sex sings, males of different species do so in markedly different manners, and the wing vibrations in question are quite different from those that support flight. This includes that fact that sine song, which consists of flight-like buzzing sounds, is produced at distinctly different frequencies compared to the latter kind of vibrations (e.g., Villella et al., 1997). Therefore, control of these behaviorally specific outputs, aside from where and how they are input, seems ripe for neurogenetic dissection. And whereas it is known that genetic maleness in a portion of the CNS—the VNC—is necessary to enable song production, nothing is known about just where this occurs within the VNC, let alone how. Owing to the scattered information available for the Drosophila about sexspecific anatomical elements of the PNS and CNS, one can surmise that there is a sex-specific, morphologically differentiated “song circuit” somewhere in the thoracic ganglia (possibly within the brain as well, as suggested by Popov et al., 2003). If so, these structures need to be identified, in parallel with attempts to understand the several brain regions that are hypothesized or known to be different in males versus females. But what if song control is mostly a matter of functional sexspecificity, against a backdrop of no difference between the interneuronal or neuromuscular anatomy of males versus females? In this respect, the current review did not get into the following (because little is known about it neurally), but we now should mention the sex-specific effects of certain neurophysiological mutations: ion-channel variants that alter the qualities of song sounds (reviewed by Hall, 2002; also see the current Fig. 3.4). It is possible that these genes are expressed variably with regard to cell differentiation of certain VNC neurons in wild-type males—vis-a`-vis those in females, which may, for instance, differentially express alternative-splice forms of the channel-encoding transcripts in question. (Such varying isoforms are known to emanate from the cacophony and the slowpoke genes that specify calcium-channel polypeptides and those comprising calciumdependent potassium-channel ones, respectively; when mutated, cac or slo have

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marked effects on the “pulse” component of courtship song.) The issue now being discussed, if legitimate, can be appreciated to dovetail with other examples of neuronal specificity—involving intracellular substances—which were described for separate regions of the male versus female nervous system (within the brain and the ABG, as will be discussed later in this section). Whatever components of courtship control are worthy of being neurally dissected, it is notable that a widely applied genetic approach to these questions involves enhancer-trapping transgenes. A large collection of such factors has been applied to “drive” expression of markers and neural disruptors within PNSto-CNS pathways and in deeper locations within the brain—principally that part of the CNS as opposed to the VNC. Most of these enhancer traps are expressed with the latter tissues as well as within the brain. Thus, VNC manipulations of, for example, chemosensory inputs via the legs or acoustical outputs via the wings could have been embraced by investigations that rely on these kinds of transgenes; but “no,” so far. Could it be—even better for these posterior-CNS purposes—that certain enhancer-trapped strains would be identified on the basis of VNC specificity? One worries that this kind of transgenic will not be recognizable, and this speaks to problems revolving round the enhancer-trap approach to behavioral neurogenetics. Without recalling the specifics of the puzzling findings made in this manner, suffice it to say here that “brain centers” involved in reproductive behavior encompass a few-too-many anatomical sites. Mutual consistency among the results of such investigations is not at hand (Fig. 3.2). One frets, in turn, about the possibility that further examination of these issues will not result in a more salutary situation, whereby overlaps in three dimensions among the marker patterns mediated by enhancer traps will come down to a dependable set of “sex centers.” The reason for this pessimism is that the full and true features of the expression patterns driver by these kinds of transgenes remain unknown. Too many of the driver strains in question are said to mediate marking, in conjunction with the hope that rather local disruptions are being effected in parallel, in context of errant claims about “predominant” expression in one brain region or the other. Just as bad: a paltry number of these enhancer-trapping transposons have been assessed for their expression during development. In contrast, certain “dedicated” drivers are now coming online for transgenic dissection of courtship control. One set of such molecular-genetic types involves the fruitless gene, elements of which have been fused to the relevant driver-encoding sequence. The idea here is that the expression patterns of this actual gene are well characterized, including assessments of life-cycle stages as well as spatial configurations (where fru products are found within the CNS and PNS). Thus, one would hope that a “fru-gal4 fusion” will properly mimic the manner by which the normal form of the gene is expressed; this could dovetail with interpretable effects of GAL4-induced disruptions of neuronal structure and function. We discussed a “fruitless problem” in this regard—difficulties pointed to by the

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fact that one kind of fru-gal4 construct, transformed into arbitrary chromosomal sites, led to expression patterns that neither encompassed all of the normal fruþ spatial pattern, nor was it limited to neurons that contain male-specific FRUM protein in wild-type males. In other words, this type of transgene came out little better than a case of enhancer trapping! —for which the gal4-including factor drove a marker pattern that cut across portions of the fruitless one but also extended well beyond the latter’s spatial domain. In this regard, may we propose a moratorium on the execution of any further enhancer-trap approaches to these problems, which might even include abandoning attempts identifying “fru enhancers” by pulling them away from the locus and fusing them to the (famed) factor from yeast? Continuing application or creation of these dull tools could fail to propel the analytical stories appreciably and possibly could promote a scenario in which understanding of the reproductive phenomena will wallow in some disarray. The second part of the recommendation just given about “50 -flanking/ gal4 fusion constructs” probably goes too far. This thought alludes to the alternative tactic, involving gal4 knock-ins at the chromosomal locus of interest. Here, the target for that yeast-derived factor is shortly downstream of the gene’s sex promoter and other of its regulatory sequences, such that all such entities are retained in their normal milieu. The claim to fame, accordingly, is that gal4 will be expressed in a thoroughgoingly proper manner with respect to life-cycle stages and tissue types. This salutary state of affairs was reasonably well realized in the case of two gal4 knock-ins near fru’s sex promoter (Manoli et al., 2005; Stockinger et al., 2005; but see Ferri et al., 2008). In contrast, “pulling out” fru DNA including the promoter in question and genomic material located 50 to it, then fusing this 16-kb fragment to gal4 along the way to transforming it into (arbitrarily located) chromosomal sites led to GAL4-driven marking that was little better than an enhancer-trap situation. In particular, we refer to the gal4-containing transposon called C309 (inserted at “a” chromosomal locus about which no information is available), which mediates CNS marking that includes some of the fruþ pattern but also extends beyond it (Villella et al., 2005). This is what happened in the fru(16)-gal4 transgenic type that was just (re)described (Billeter and Goodwin, 2004). The implication (to reiterate what we surmised in Section V. E) is that the 16 kb of fru 50 -flanking DNA lacks some of the wild-type allele’s enhancers and is devoid of hypothetical silencer sequences that are naturally part of the gene’s expression control. This supposition speaks to the idea that—after all—there is analytical power associated with the 50 -flanking fusion approach. In the current case, in-principle more than 16 kb of fru-locus material could be fused to gal4, eventually leading to a transgene type in which GAL4 would drive a marker pattern that recapitulates the fruþ one. In other words, extending what gets fused to gal4 farther in the 50 direction from the 16-kb segment would coral the “missing” enhancer(s) and silencers(s). Thereby, some potentially most useful information about regulatory subsets of the (overall) 50 -flanking material would

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be gathered. This knowledge could be exploited to make derivative 50 -flanking/ gal4 fusion transgenes in which nicely defined subsets of the fruþ pattern are in play. Therefore, perturbations of those subsets (e.g., of a certain part of the FRUM pattern in the brain or of specifiable regions within the overall VNC) would be permitted: In this kind of experiment, what particular aspects of the fru-involved reproductive sequence (cf Fig. 3.4) would be blocked or go awry? The “regulatory dissection” proposal just given is not quite as easy to conceptualize in context of knocking-in gal4 to the chromosomal locus—because, in that tactical context, how much material sequences 5’ to the insertion site, comprising all the relevant regulatory material, would be relatively difficult to manipulate piece-by-piece in their native chromosomal setting. Yet, for the further 50 -flanking/gal4 fusions that may be in the gene’s future, it is known first of all that the natural regulatory sequences must be within 35 kb of the sex promoter. [Billeter and Goodwin (2004) molecularly analyzed a strain that is deleted of a chromosomal segment near the fru locus, although that deletion is fruþ; one of the two “breakpoints” harbored by this chromosome aberration, the one nearest to the fru locus is ca 35 kb away from the gene’s sex promoter.] Thus, one could restart the fusion-transgene approach by producing a “fru(35)-gal4” transgenic type and, for instance, whittle away from there (referring to the 50 end of the 35-kb segment). This cavalierly stated proposal would have fallen on deaf ears of fly folk a short while ago, because transgene constructs carrying that much DNA (inserted into the relevant transformation vectors) were most difficult to deal with successfully—until methods based on bacterial artificial chromosomes came to the fore “for targeted insertion of large DNA fragments in D. melanogaster” (Venken et al., 2006). While we are at it in terms of wondering with the 50 -flanking fusion along with the knock-in approach should be juggled in parallel in upcoming assaults on fruitless—we cannot help mention a worry about the latter type of transgenic: It is not all that easy to be convinced by the explicit claims and tacit assumptions presented for these knock-in transgenic types. For example, is the GAL4-driven marking for the fru-gal4 knock-ins really much the same within male and female nervous systems? Will the marker patterns driver by these gal4 inserts at the locus be demonstrably the same manner as is known (but decreasingly well appreciated) for fruþ during late-larval and pupal stages? The latter such assessments have not been attempted—for any of the fru-related, gal4-including transgenic types—as investigators are turning evermore to where fruitless makes its products within the nervous system of adults. But this gene is arguably a “developmental factor” as well, and not only because fru RNAs emanating from the gene’s sex promoter are found during formative stages. It is also notable that sex-specific components of brain anatomy have been uncovered, in part by applying fruderived transgenes. One supposes that the functional meaning of these dimorphic structures will be elucidated in time, accompanied by understanding of how sexspecific neuronal “wiring” comes to exist within the developing nervous system.

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This hope is a relatively substantial one, compared with that which might be pinned on more flabbily apprehended features of sexually dimorphic anatomy (those stemming from gross descriptions of CNS ganglia in wild-type males versus females). Furthermore, one hopes that increasing numbers of questions will be asked about sexually dimorphic morphologies within the VNC, by supplementary applications of the pertinent fru transgenics. So far, essentially all this is known about this part of the animal from a morphological perspective is that certain thoracic taste-sensory neurons have sex-specific features; these cellular phenotypes involve more than gustatory-receptor qualities (axonal pathways as well) and have been analyzed with respect to sex-determination factors (Possidente and Murphey, 1989), but not fruitless-wise. Thankfully, more posteriorly located VNC neurons are now being rolled into the fru arena (principally, as of two years ago, by Billeter et al., 2006b). In this (anatomical) ballpark, we already know that the posterior-most elements of the VNC are sexually dimorphic, as these neurons “must be” on behalf of innervating the obviously different structures defined by male versus female reproductive “plumbing” within the abdomen. This matter speaks in part to neurochemical differentiation of sex neurons; and it is hoped that this frurelated phenomenon will promote definitive understanding of how the intracellular qualities of these cells participate in reproductive regulation. Entry-level studies of this sort identified male-specific ABG neurons within which the presence of serotonin is under fruitless control. The initial such analyses pointed to no influence of the gene on the anatomy in question (innervation by fruexpressing efferents of male reproductive organs); although, at present, it is concluded that fruitless affects the development (or maintenance) of certain such cells and axons, as well as the neurochemical differentiation of the companion processes (anatomical ones that project caudally from the posterior VNC and remain in place in males lacking FRUM proteins). One idea that suggests itself in this regard is that other components of fruitless’s wide-ranging expression pattern of course involve not only different structures— including brain regions in addition to VNC ones—but also different kinds of cellular differentiation. If only because serotonin is not found within any FRUM neurons in anterior regions of the CNS, there must be other kinds of substances whose presence is controlled “downstream” of this gene-product’s action. So what? Well, could it be that fru-related regulation of, for example, early courtship steps involves the same substances as those connected with latestage actions? Unlikely. In other words, the broad significance of this gene, involving almost all steps of the behavioral pathway, would encompass differential neurochemistry as well as separate portions of the CNS and PNS. A seminal investigation of that speaks to this issue uncovered a neuropeptide whose malespecific expression is indeed downstream of fruitless within the brain, bringing that portion of the CNS into focus and expanding one’s view of these phenomena, beyond the case involving serotonergic neurons at the other end of the animal.

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But we seem to be stuck too tightly on fruitless as the sex gene, manipulations of which will answer all our questions: What is the sum total of differently located neural substrates for the several components of sex-specific behavior, and how do the various actions of this genic factor mediate the anatomical and celldifferentiational features of these separate structural elements? Whether identification of downstream-of-FRUM substances is in its infancy (true), we must also bear in mind that “higher-up” regulators in addition to fruitless are worthy of consideration. Perhaps none of these is even on the table, which can be surmised by perusing fru-ocentric summaries of recently performed studies. Such views of the situation are at least inadequate and at worst false because the (more classical) sex-determination gene doublesex is also known to affect reproductive behavior when mutated and to make its products within the CNS as well as within at least one sex-related portion of the PNS. There really is only one contemporary study that has dovetailed experimental analysis of dsx effects with those of fru (with respect to only one portion of the “coexpression” pattern of these two genes). The conceptually, let alone cellularly, based “overlaps” of how both factors contribute to some of the relevant reproductive phenotypes should not be downplayed over the course of upcoming investigations. Here is a bet: The “she-males” created by application of certain fruitless knock-ins, who do not truly behave in a male-like manner, might do so if the female-specific forms of DSX protein were genetically replaced by DSXM [discussed in effect by Billeter et al. (2006b)]. All that Taylor et al. (1994) learned from testing the behavior of XX dsxM-only flies is that that genotype is insufficient to mediate any male-like behavior, but DSXM may be—is actually—necessary for full-blown courtship of this type [referring, for example, to elements of the studies reported by Villella and Hall (1996) and Bray and Amrein (2003)]. Another thing to be borne in mind about doublsex is that the gene generates products that function on behalf of behavioral femaleness as well as male courtship. (In contrast, fruitless’s sex control seems connected with solely with male-specific gene products.) Even though there is one set of findings that focused upon an influence of DSXF on the female’s sex-behavioral qualities (Waterbury et al., 1999), nothing is known about the hypothetical consequences of this protein as it acts within a diplo-X nervous system. A larger point in this context is that neurogenetic analysis of female reproduction has been lying relatively fallow for far too long. Perhaps this is because the courtship actions of D. melanogaster females are difficult for human observers to appreciate: Early in the sequence, such a fly performs subtle microbehaviors that are apprehended as rejection-like actions (female coyness?). Later on, she is receptive (or not) to mating attempts, which again involves subtle alterations in her “courtship locomotion” and, once more, rather delicate operation of posterior structures that are difficult for humans to perceive. If a female is to be receptive—in the first place, this depends in part on her virgin versus mated status; but how she mediates a quite conspicuous component of her “rejection

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repertoire,” ovipositor extrusion toward the face of a following male, is unknown in terms of CNS and motor-neuronal control. (This sour note is sounded for the sake of a positive twist: that conditioned features of courtship, which in part involves interactions between males and mated females, provide one of the best opportunities for neurogenetic dissection of learning and memory in Drosophila—as the foregoing section about these phenomena aimed to imply.) The second vaguely understood feature of receptivity, referring to the behavior of a virgin female, is that “brain control” is involved, at least in terms of the requirement for 2X chromosomes to be contained within neurons of a CNS region that was mapped at low resolution. (This study was performed more than 20 years ago, and there has been no follow-up.) Even if upstream regulatory factors will not soon be recognized as to whether and how they participate in these features of sex specificity, one hopes that other kinds of genes will be identified as involved. Candidates for such factors are few and far between, although not vanishingly rare: There is the spinster (spin) mutant in D. melanogaster, which leads to “enhanced mate refusal” (Suzuki et al., 1997); also, icebox (ibx) genetic variants pointed to initially by a mutation that similarly causes mediocre mating receptivity (Kerr et al., 1997). The dissatisfaction (dsf) and the retained/dead-ringer (retn/dri) genes affect female receptivity in their mutant forms, as well as aspects of male behavior (Ditch et al., 2005; Finley et al., 1997). In fact, retn females display male-like courtship toward other females, although not as vigorously as XY Drosophila do and not because such a mutation (aka dri) anomalously upregulates FRUM production in XX flies (Ditch et al., 2005). These factors barely entered the main-text story because the catchas-catch-can aspects of female-related neurogenetics do not yet create one or more coherent pictures (cf Figs. 3.1–3) about the structure and function of neural regions that subserve her behavior. What can be neurobiologically appreciated so far is the following: The spin gene encodes a “novel” membrane protein (Nakano et al., 2001), mutation of which interferes with programmed cell death and leads to neural degeneration, generically appreciable; a subsequent study, which again was unconnected with any deep features of femaleness, revealed the spin-specified “endosomal” protein to be involved in regulation of synaptic growth (Sweeney and Davis, 2002). For ibx’s part, the behavior mutant turned out to reidentify a gene previously discovered to encode a substance known as NEUROGLIAN (Carhan et al., 2005; Kerr et al., 1997), which exerts broad influence on nervous-system development but is anonymous in terms of sex-specific components thereof. In conjunction with isolating the dsf mutation, it was found to cause abnormal morphology of abdominal “motor neurons” in females as well as males (no doubt correlated with egg-laying deficit exhibited by the former and “maladroit” abdominal curling performed by the latter). However, as of several years after this gene got cloned (Finley et al., 1998), studies of its product seemed

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to have slipped sideways into purely molecular studies of the DSF “nuclear receptor” (Pitman et al., 2002). The case of retained/dead-ringer is another on-point story (at least in terms of the innards of its biology that are now emerging). Thus, the apparent DNA-binding protein encoded by this gene (pointed to initially by female-sterile mutant before dri was found in a behavioral screen) had its neural expression pattern described, by applying a retn-gal4 driver, in the pupal MBs, SOG, VNC, and the developing eye; these patterns were the same in both sexes (Ditch et al., 2005). Creation of “MARCM mosaics” and scrutiny of clones homozygous for a retn variant within a subset of the overall spatial domain of this gene revealed axonal “misprojection” defects in the SOG and for one category of photoreceptor axons (Ditch et al., 2005). Therefore, this particular gene, part of whose significance is on the female side, is being ratcheted-up in terms of neurobiological examinations; and we should recall from Section V.F how retnþ functions are being analyzed as to how they dovetail with actions of the dsx gene—and with fru as well, referring to a principal feature of the most recent retained-based study (Shirangi et al., 2006). Indeed, the two genes would appear to interact because, for example, retn fru doubly mutant males courted females or other males at higher levels than exhibited by fru single mutants, although the CNS expression patterns of the two genes are almost entirely nonoverlapping. But neither these findings about the retn gene nor those obtained for spin, ibx, and dsf have risen to a level that would allow formulation of “female neural substrate” portrait like that presented for male-specific behavior in Fig. 3.2. As behavioral and molecular-neurobiological studies of Drosophila reproduction proceed, it is hoped that one’s view of the genetic horizon will be expanded, at least by increasingly in-depth analyses of the female nervous system and the behaviors it supports. Discoveries of further reproductively regulating factors are no-doubt in our future, and such genes may or may not turn out to act sex specifically. Those that are already known to do on behalf of the male’s nervous system and his courtship and mating are getting to be so well-appreciated that contemporary summaries of these sexual phenomena are taking on characteristics of a molecular-genetic extravaganza. That is all to the good, one supposes, although such a person might wish to keep the current treatment of this subject in one’s pocket—just in case these attempts at full disclosure will be valuable to refer to as time goes by.

Acknowledgments We appreciate the many intellectual and empirical contributions to studies of Drosophila reproductive genetics and its molecular-neurobiological components, which have long been provided by coworkers within our laboratory at Brandeis University and by collaborating or otherwise interacting investigators elsewhere. The latter collection of colleagues have toiled in the research groups of

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Bruce S. Baker (Stanford University), Richard W. Siegel (University of California, Los Angeles), and Barbara J. Taylor (Oregon State University), as well as in those headed by “alumni” of our laboratory: Donald A. Gailey (California State University, Hayward), Stephen F. Goodwin (Glasgow University), Ralph J. Greenspan (The Neuroscience Institute, San Diego, CA), Charalambos P. Kyriacou (University of Leicester, UK), Jae H. Park and Gyunghee Lee (University of Tennessee), Kathleen K. Siwicki (Swarthmore College, Swarthmore, PA), and Laurie Tompkins (formerly at Temple University, Philadelphia, PA). We thank Edward Dougherty, Hayden Lincicome, and Elizabeth Rideout for assisting in figure preparation. We are indebted to Stephen F. Goodwin and Dennis C. Chang for critiquing draft versions of this chapter. The many collegial inputs referred to at the beginning of this paragraph led to several (but of course nowhere near all) of the findings reviewed in this work; these Brandeis-based and collaborative studies were supported by two research grants from the US NIH: GM-21473 and NS-33352.

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4

NMD: Multitasking Between mRNA Surveillance and Modulation of Gene Expression Gabriele Neu-Yilik and Andreas E. Kulozik Department for Pediatric Oncology, Hematology and Immunology, University Hospital Heidelberg and Molecular Medicine Partnership Unit, University of Heidelberg and European Molecular Biology Laboratory, Im Neuenheimer Feld 156, 69120 Heidelberg, Germany

I. Introduction II. Mechanism and Actors A. General rules B. Factors III. Targets of NMD IV. Disobedient NMD Targets V. Good Cop, Bad Cop: Medical Importance of NMD VI. Moonlighting NMD Proteins: Moonlighting Pathway? A. NMD factors and translation B. Other mRNA turnover pathways C. NMD factors and genome stability VII. Conclusions Acknowledgments References

ABSTRACT Gene expression is a highly specific and regulated multilayer process with a plethora of interconnections as well as safeguard and feedback mechanisms. Messenger RNA, long neglected as a mere subcarrier of genetic information, is more recently Advances in Genetics, Vol. 62 Copyright 2008, Elsevier Inc. All rights reserved.

0065-2660/08 $35.00 DOI: 10.1016/S0065-2660(08)00604-4

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recognized as a linchpin of regulation and control of gene expression. Moreover, the awareness of not only proteins but also mRNA as a modulator of genetic disorders has vastly increased in recent years. Nonsense-mediated mRNA decay (NMD) is a posttranscriptional surveillance mechanism that uses an intricate network of nuclear and cytoplasmic processes to eliminate mRNAs, containing premature termination codons. It thus helps limit the synthesis of potentially harmful truncated proteins. However, recent results suggest functions of NMD that go far beyond this role and affect the expression of wild-type genes and the modulation of whole pathways. In both respects—the elimination of faulty transcripts and the regulation of error-free mRNAs—NMD has many medical implications. Therefore, it has earned increasing interest from researchers of all fields of the life sciences. In the following text, we (1) present current knowledge about the NMD mechanism and its targets, (2) define its relevance in the regulation of important biochemical pathways, (3) explore its medical significance and the prospects of therapeutic interventions, and (4) discuss additional functions of NMD effectors, some of which may be networked to NMD. The main focus of this chapter lies on mammalian NMD and resorts to the features and factors of NMD in other organisms if these help to complete or illuminate the picture. ß 2008, Elsevier Inc.

I. INTRODUCTION After 15 years or so of a somewhat shadowy existence, nonsense-mediated mRNA decay (NMD) research has only recently left this sheltered realm and has developed into one of the hottest fields both in molecular and cellular biology and in molecular medicine. Both—the previously arcane life of NMD and the present surge of interest also from unexpected directions—are fuelled by the amazing features of this complex and still enigmatic mechanism and its molecular actors. Early on, nonsense mutations were recognized to be linked to or to underlie many human disease phenotypes, yet the most frequent impact of nonsense mutations often escaped (and still escapes) many researchers: contrary to intuition and to the most prevalent interpretation, a premature termination codon (PTC), that is a stop codon within an open reading frame (ORF), does not usually induce the synthesis of a truncated protein to which the observed phenotype could be, and often is, ascribed; instead, it triggers the decay of the mutated mRNA. This phenomenon—that cells already monitor the quality of gene expression products at intermediate steps—is astounding in itself but the way it is enacted is even more prodigous. To discriminate between termination codons that specify the end of an ORF and those that interrupt it, mammals interlock two pivotal yet spatially separate processes in gene expression: nuclear splicing and cytoplasmic translation. Interestingly, the details differ in various organisms yet the phenomenon of

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NMD itself is common to all metazoans, thus underscoring its vital significance. Yet, the differences in the details are significant and stress the importance of screening the DNA and protein databases not only for similarities as the most important functional features because evolution has treasured them but also because it is as much difference as kinship that matters in evolution. NMD is complex. This basic property is evident in a multitude of aspects. First, on the biochemical level, NMD is complex because it combines both nuclear and cytoplasmic events. In addition, NMD seems to dispose of several entrance gates that guide potential substrates to degradation and for these options it uses common yet also divergent sets of molecules. In that respect, NMD may turn out to be paradigmatic for many other cellular processes; cellular systems increasingly present themselves as densely meshed, interactive, dynamic, and flexible networks rather than as linear pathways in which one step has to be completed before the next can occur. It looks as if gene expression is better described as a fluid rather than a stepwise process. Therefore, NMD could serve as a model for the elicudation of principles that also underly many other poorly understood mechanisms; its study could help to purge the too prevalent mechanical perceptions of biochemical processes that have been borrowed from nineteenth-century industry. Second, NMD is complex in that it not only serves the recognition and elimination of faulty transcripts but also appears to modulate the expression of a plethora of physiological transcripts. These physiological substrates have one feature in common with their pathological counterparts: they possess a termination codon that is, by NMD standards, conceived as premature. This applies, for example, to the termination codons of upstream ORFs, to termination codons that are followed by splice events in the 30 untranslated region (UTR), or to termination codons that are introduced into an ORF as the result of somatic DNA rearrangements, alternative splicing, ribosomal frameshifting, or mRNA editing. In some cases, these features are exploited for self-regulatory mechanisms. For example, when a gene product induces the alternative splicing of its own transcript, a PTC may be introduced into its ORF or a splice junction may be generated 30 to the termination codon, thus directing the resulting alternative transcript to NMD. Moreover, it is suspected that potentially NMD-sensitive physiological transcripts can stand at crossing points of pathways or networks and thus modulate such pathways as a whole. This, of course, implies that such a potential “regulator transcript” at the center of a pathway can be either exposed to or concealed from NMD or that NMD itself is regulated so that the putative regulator at times escapes NMD and at others is downmodulated by it. There are indications that both of these options occur. Third, NMD is complex because with respect to its role in human disease, it is janus-faced. It can be beneficial for heterozygous carriers of nonsense mutations because it destroys the product of the faulty allele and prevents

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dominant negative impacts of truncated proteins. Yet, it can also result in the clinical picture of protein deficiency in those cases where it prevents the production of a protein that, albeit truncated, would convey at least a residual function. Fourth, the intricacy of NMD is enhanced in that it emerges as a biological multiplayer. Single or cohorts of its effectors or maybe even itself as a whole seem to moonlight both in other branches of mRNA metabolism and in apparently unrelated functions. This chapter presents the current state of knowledge about the mechanism of nonsense-mediated mRNA decay and its molecular actors. Moreover, it tries to illuminate the intricate network of contacts with other cellular pathways and to pinpoint the switch of function of several of its effectors that moonlight in these other pathways. Finally, it highlights the importance of NMD for the understanding of many opaque genotype–phenotype relationships of human hereditary and acquired disease conditions.

II. MECHANISM AND ACTORS A. General rules NMD specifically recognizes and degrades mRNAs with PTCs and thus protects the cell from potentially harmful C-terminally truncated polypeptides. To accomplish the task of discrimination between premature and physiological termination codons, NMD uses a complicated and stunning network composed of early and late elements of gene expression (reviewed in Conti and Izaurralde, 2005; Hentze and Kulozik, 1999; Lejeune and Maquat, 2005; Maquat, 2004). Premature termination or nonsense codons can be introduced into the mRNA by point mutations, transcriptional errors, and lesions that generate shifts in the translational reading frame such as deletions, insertions, and aberrant splicing. PTCs need to be in frame with the initiator AUG in order to be discernible for the NMD machinery. Congruously, the most important feature of NMD shared by all eukaryotes (but also with other decay pathways) is that the substrate transcript needs to be translated and translation needs to be terminated at the PTC. Furthermore, in all organisms that dispose of this mechanism, NMD displays a “position effect” regarding the recognition of PTCs. PTCs in proximity to the natural termination codon are inefficiently recognized, whereas more 50 PTCs direct the mutated transcript to rapid decay. Mammalian NMD offers an explanation for this surprising observation (Fig. 4.1). Here, both splicing and translation are essential as shown by NMD insensitivity of intronless genes and untranslated mRNAs (Brocke et al., 2002; Maquat and Li, 2001; Neu-Yilik et al., 2001; Thermann et al., 1998). During splicing, a dynamic multiprotein assembly, the so-called exon junction complex (EJC), is deposited 20–24 nucleotides 50 to

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Figure 4.1. Simplified model of mammalian NMD according to current thinking. Pre-mRNAs are spliced in the nucleus by the spliceosme and a dynamic multiprotein complex, the exon junction complex (EJC, dark gray oval form) is deposited 50 to the exon junctions. UPF3 (3, light gray) is recruited to the exon junctions in the nucleus. UPF2 (2, light gray oval) joins the EJC immediately after nuclear export. The EJCs help to recruit ribosomes to (Continues)

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the exon junctions and accompanies the mRNA into the cytoplasm and polysomes (Dostie and Dreyfuss, 2002; Kataoka et al., 2000; Le Hir et al., 2000a,b, 2001; Tange et al., 2004, 2005). If positioned in the 30 UTR, it serves during translation as spatial reference point for the discrimination between premature and physiological termination codons. In contrast, if positioned within the ORF, it enhances translation (Kunz et al., 2006; Nott et al., 2004; Wilkinson, 2005). A translation termination codon is generally interpreted as “normal” if no exon junction follows more than 50–55 nucleotides downstream, a circumstance that has been dubbed “50 nucleotide-rule” (Nagy and Maquat, 1998). Consequently, most physiological termination codons reside in the final exons (Nagy and Maquat, 1998). Yet, this “NMD boundary” also implies that PTCs in the NMD-resistant area (i.e., if they reside closer than 50 nt 50 to the last exon– exon junction or within the last exon) are invisible to the NMD machinery, potentially promoting the production of dominant negative C-terminally truncated proteins. Although the position effect with respect to more 50 and 30 PTCs has also been observed in yeast and fruitfly, exon junctions appear to play no role in NMD of these organisms.

B. Factors

1. UPF and SMG proteins . . . Diversities of NMD between different organisms are reflected by disparities in the main NMD factors (reviewed in Conti and Izaurralde, 2005; Maquat, 2004; Table 4.1). Three fundamental effectors in yeast (Upf1–3) and seven in Caenorhabditis elegans (Smg-1 to 7) have been identified by genetic screens. The Upf1p, Upf2p, and Upf3p proteins in yeast correspond to Smg-2, Smg-3, and Smg-4 in C. elegans, are essential for NMD and orthologues of all exist in mammals. In contrast, Smg-1, Smg-5, and Smg-6 have been found in all multicellular organisms but not in yeast, at least not as regulators of NMD (see below). A Smg-7 orthologue has been detected in human cells [but not in fruitfly the mRNA. The translating ribosome displaces all EJCs during the first round of translation and terminates at the physiological termination codon. Thereby, the mRNA is validated as normal and remains stable (left part of the graph). Whether UPF1 (white oval) participates in a normal termination event is unknown. When the translating ribosome encounters a PTC and at least one EJC is still bound 30 to the PTC, UPF1 interacts with the eukaryotic release factors 1 and 3 (eRF1/3) and subsequently with the EJC. This interaction is thought to be mediated in many cases by UPF2. Phosphorylation (asterisk) of UPF1 by SMG1 (dark gray) triggers mRNA decay after an as yet poorly understood sequence of events. The dotted line signifies the nuclear envelope. NMD can occur in the cytoplasm or in close association with the nucleus, possibly in transit from the nuclear pore (nucleus-associated NMD). For further details, see text.

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4. Multitasking of NMD Table 4.1. Upf- and SMG Proteins Across Organisms Species

Protein

Yeast

Upf1p

Worm

Upf2p (Nmd2) Upf3p Est1p (orthologue of SMG5–7) Smg-1

Fruitfly

Smg-2 (Upf1) Smg-3 (Upf2) Smg-4 (Upf3) Smg-5 Smg-6 Smg-7 Upf1

Mammalia

Upf2 Upf3 Smg-1 Smg-5 Smg-6 UPF1 (RENT1) UPF2 (RENT2) UPF3B (UPF3X) SMG1

Comment All not essential; gene deletion of any interrupts NMD and impairs fidelity of termination

No known NMD function Deletion of any disrupts NMD but is not lethal; Smg-1 and Smg-3 to 7 are needed for phosphorylation/dephosphorylation of Smg-1

Knockdown of Upf1, Upf2, or Upf3 disrupts NMD and induces G2/M arrest. Deletion of Upf1 leads to embryonic death

Smg-1 not essential for NMD in embryos Knockdown of Smg-5 and Smg-6 disrupts NMD Knockdown of any interrupts NMD Upf1 knockout is lethal in mice; knockdown of UPF1 in cells induces S-phase arrest Knockdown of SMG1 induces G2/M arrest SMG5/EST1B and SMG6/EST1A associate with telomerase in extracts; overexpression of SMG6/EST1A alters telomere structure

SMG5 (EST1B) SMG6 (EST1A) SMG7 (EST1C)

(Gatfield et al., 2003)] and is required for human NMD. Deletion of either of the three upf genes in yeast (Leeds et al., 1992) or either of the seven smg genes in C. elegans (Cali et al., 1999; Pulak and Anderson, 1993) disrupts NMD in these organisms, and siRNA-mediated knockdown of the human orthologues or expression of dominant-negative versions of the human orthologues of upf and smg genes impair NMD efficiency in human cells (Gehring et al., 2003, 2005; Kashima et al., 2006; Mendell et al., 2002, 2004; Sun et al., 1998; Unterholzner and Izaurralde, 2004; Wang et al., 2002b; Wittmann et al., 2006). Besides these manipulations, tethering experiments have been of great value to elucidate the

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Figure 4.2. Tethering assay. Proteins that are hypothesized to influence NMD via interaction with the EJC are fused to an RNA-binding peptide (MS2 or N). Fusion proteins are transiently expressed in cells together with a reporter transcript that has the targetbinding site engineered into its 30 UTR at least 50 nucleotides 30 to its termination codon. The binding of the fusion protein to the tethering sites elicits NMD if this protein is a component of the NMD-inducing complex that assembles at exon junctions of natural transcripts.

impact of individual proteins on NMD and their respective interdependence. In this type of experiments, proteins with a suspected role in NMD are fused to an RNA-binding domain and then are tethered to specific protein- or peptidebinding sites inserted into the 30 UTR of a reporter transcript (Fig. 4.2). If a protein whose function is necessary for NMD and whose mode of action is related to the EJC is tethered at an NMD-competent position (>50 nt downstream of the termination codon), the reporter expression is considerably downmodulated. In this way, UPF1, UPF2, UPF3A, and UPF3B (Lykke-Andersen et al., 2000) were demonstrated to be bona fide NMD factors in human cells. In all organisms, Upf1 appears to be a key effector of NMD. Upf1 is an RNA/DNA-dependent ATPase and 50 –30 helicase and the yeast and human orthologues have been extensively characterized, both on the biochemical level and on the functional level (Fig. 4.3). The central region that is most conserved between organisms contains two cysteine-rich zinc-finger motifs with unknown function and seven group I helicase motifs. The ATPase activity of UPF1 resides in the helicase region and is essential for NMD in both yeast and humans. In immunofluorescence studies, UPF1 primarily localizes to the cytoplasm. However, other experimental approaches indicate that it shuttles between nucleus and cytoplasm (Mendell et al., 2002) and points to additional and NMD-independent nuclear functions (see below). In coimmunoprecipitation and tandem affinity purification studies, UPF1 has been found in a variety of complexes containing other NMD factors such as UPF2 and UPF3 proteins and constituents of the EJC, but also with other proteins, sometimes with no obvious or unclear relationship to NMD (Kaygun and Marzluff, 2005a; Kim et al., 2005;

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Figure 4.3. Domain organization of UPF1. CR: N-terminal region conserved between Upf1 proteins in all species; light gray bars: putative zinc-fingers; black bars: superfamily I (SF1) helicase motifs; NLS: unconventional nuclear localization signal; NES: unconventional nuclear export signal; asterisks: sites phosphorylated by SMG1; (A): mutations in this region abolish the function of yeast Upf1p in translation termination but not in NMD; (B): mutations in this region inactivate the function of yeast Upf1p in NMD but not in translation termination.

Schell et al., 2003). Moreover, UPF1 interacts with translation termination factors both in yeast and in humans. Since in tethering experiments, the requirement for UPF1 for the decay of a reporter transcript cannot be bypassed by other NMD effectors (with the exception of SMG7), it is conventionally thought to act late in NMD. For its NMD activity in multicellular organisms, UPF1 has to undergo phosphorylation/dephosphorylation cycles (Fig. 4.4). Phosphorylation is mediated by Smg-1/SMG1, Smg-3/UPF2, and Smg-4/UPF3, whereas Smg-5/ SMG5, Smg-6/SMG6, and Smg-7/SMG7 are essential for its dephosphorylation (Ohnishi et al., 2003; Page et al., 1999). SMG1 is a phosphatidylinositol-3kinase-related kinase (PIKK) and phosphorylates in vitro at least 4 of 28 possible S/T-Q phosphorylation sites of human UPF1. All four reside in a C-terminal S/T-Q rich cluster that contains 14 of the 28 putative phosphorylation sites (Fig. 4.5). SMG5, SMG6, and SMG7 induce the protein phosphatase 2A (PP2A) to engage in dephosphorylation of Upf1. The N-terminus of UPF1, which is missing from yeast Upf1p, is essential for the binding of SMG5 (Ohnishi et al., 2003). Furthermore, SMG1 and SMG5–7 are found in multiple hitherto poorly defined and possibly transient complexes with other NMD factors, which hopefully will help to define the intricate network of interactions that finally lead to the degradation of nonsense-mutated transcripts. Beyond their role in NMD, UPF1 as well as several of the SMG proteins have been associated with additional and presumably NMD-independent functions. These, as well as their functions in NMD, will be elaborated in more detail in the following text. The N-terminus of UPF1 contains a UPF2-interacting domain between amino acids 1 and 415 (Kadlec et al., 2006) and its deletion or mutation of C162 abolishes UPF2 binding (Kashima et al., 2006). The role of Upf2 in NMD is

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Figure 4.4. Hypothetical model of the phosphorylation cycle of UPF1. SMG1 associates with UPF1 (1) and is recruited to the terminating ribosome. The SMG1–UPF1 complex interacts with UPF2 (2), UPF3B (3B), and UPF3AL (3AL) at the exon junction complex and UPF1 is phosphorylated. Subsequent to UPF1 phosphorylation, UPF2, UPF3AL, and possibly SMG1 dissociate. UPF3AS (3AS), SMG5 (5), SMG7 (7), and protein phosphatase 2A (PP2A) are recruited and trigger UPF1 dephosphorylation.

Figure 4.5. S/T-Q phosphorylation sites in UPF1. Diamonds: not efficiently phosphorylated by SMG1 in vitro; closed circles: efficiently phosphorylated by SMG1 in vitro; open circles: not investigated; asterisks: recognized by the so far only available antibody against P-UPF1.

somewhat obscure. In yeast and fruitfly, it appears to be an essential NMD factor because its deletion or siRNA-mediated depletion interrupts NMD of reporter mRNAs and yields results in genetic profiling similar to the ones obtained with UPF1 depletion. In human cells, experiments using either the yeast-two-hybrid system or the concomitant overexpression of UPF1, UPF2, and UPF3A or UPF3B demonstrated that UPF1 interacts with UPF2 and that UPF2 interacts with UPF1, UPF3A, and UPF3B (Mendell et al., 2000; Serin et al., 2001). Therefore, and because the subcellular localization of UPF2 is mainly perinuclear, it was speculated that UPF2 might be recruited to the EJC by UPF3 during nuclear export and that UPF2 mediates the physical interaction between UPF1 and EJC after PTC recognition, which is thought to be necessary for the decay of a nonsense-mutated transcript (Kim et al., 2001; Lykke-Andersen et al., 2001). However, recent studies suggested that UPF2 (at least as an EJC component) is dispensible for the NMD of some transcripts (Gehring et al., 2003, 2005). Although UPF2 can target a -globin transcript to NMD when bound 30 to its

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termination codon, this appears not to reflect an indispensable requirement of -globin NMD for UPF2 because a tethered UPF3B mutant that cannot interact with UPF2 still destabilizes such an mRNA in a UPF1-dependent fashion (Gehring et al., 2003). Moreover, NMD activated by tethered UPF3B or EJC factors Y14, MAGOH, or eIF4A3 is insensitive to UPF2 depletion. By contrast, NMD induced by tethering the EJC component RNPS1 displays a strong UPF2 requirement (Gehring et al., 2005). While it may be debatable if tethered function analysis fully reflects natural NMD, the concept of a UPF2-independent branch of NMD has been supported by the identification of natural NMD targets that are downmodulated even after UPF2 depletion. Furthermore, genomic profiling revealed that UPF2 silencing in human cells upmodulates a much smaller set of putative endogenous NMD targets than UPF1 depletion (Mendell et al., 2004; Wittmann et al., 2006) and cellular mRNAs regulated by UPF1 followed either a branch of NMD specified by RNPS1/UPF2-dependence or a second branch that depends on the presence of the EJC factor Barentsz (BTZ) (Gehring et al., 2005). It is therefore conceivable that different transcripts or introns assemble NMD-competent mRNPs with variable EJC compositions, all of which can provide an entry point into NMD (Fig. 4.6). While it is not yet clear if UPF2 fulfills the predicted role of bridging the EJC and the termination site, it may function in modulating NMD through phosphorylation of UPF1 because UPF2 silencing causes a reduction of UPF1 phosphorylation in HeLa cells (Wittmann et al., 2006). In support of the idea that

Figure 4.6. Branched model of mammalian NMD. Exon junctions can assemble at least two distinct sets of proteins that mediate NMD if they reside at an NMD-competent position 30 to a termination codon. One (left) minimally consists of eIF4A3, BTZ, Y14/MAGOH, and UPF3B, but is independent of UPF2 and RNPS1. The other (right) contains RNPS1, UPF3B, and UPF2, but is independent of eIF4A3, BTZ, and Y14/MAGOH. Both branches require UPF1 to elicit NMD.

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UPF2 assists in NMD-related phosphorylation events, in immunoprecipitation experiments, UPF2 directly binds SMG1 and is essential for the association of SMG1 with the postsplicing mRNP (Kashima et al., 2006). This is reminiscent of the situation in C. elegans where phosphorylation of Smg-2 requires, besides Smg-1, the UPF2 and UPF3 orthologues Smg-3 and Smg-4, respectively (Page et al., 1999). Whether UPF2, like Upf2p in yeast, has a role in translation termination and/or triggering the decay step of NMD within P-bodies (see below) remains to be determined. The human genome contains two UPF3 genes, designated UPF3A (also known as UPF3) and UPF3B (UPF3X) (Lykke-Andersen et al., 2000; Serin et al., 2001), that differ slightly between each other in structure and largely in function. Both UPF3A and UPF3B are alternatively spliced. UPF3B isoforms alternatively splice exon 8, whereas UPF3AL and UPF3AS retain or skip exon 4 (LykkeAndersen et al., 2000; Serin et al., 2001). All UPF3 proteins shuttle between nucleus and cytoplasm. In tethered function analysis, UPF3A is only marginally NMD active despite its high homology with UPF3B (Kunz et al., 2006). UPF3A and UPF3B differ from each other in the conservation of a C-terminal domain that in UPF3B is required for complex formation with the EJC protein Y14 (Gehring et al., 2003) and mediates the difference in the NMD activity of UPF3 proteins (Kunz et al., 2006). Moreover, UPF3AS, in contrast to UPF3AL, is unable to bind UPF2 due to the partial lack of an N-terminal domain that in other UPF3 proteins constitutes the UPF2-binding surface (Kadlec et al., 2004). Interestingly, all UPF3 proteins in immunoprecipitation experiments interact with UPF1, SMG5, and the EJC protein RNPS1. Among the UPF3 proteins, UPF3AS is most effective in co-precipitating UPF1 and likewise, mutation of the UPF2-binding site of UPF1 enhances its ability to bind UPF3AS (Kashima et al., 2006). This indicates that binding of UPF1, SMG5, and RNPS1 does not discriminate between NMD-active and NMD-inactive UPF3 variants and that UPF2 is dispensible (if not detrimental) for binding of UPF1 to members of the UPF3 family (Kunz et al., 2006). While it is as yet not clear whether UPF3A proteins play a role in NMD, they show other additional interesting and differential liaisons with known NMD factors (Fig. 4.4). UPF3AS and UPF3AL appear to specify at least two independent UPF1-containing complexes, one (“large complex”) containing phosphorylated UPF1 (P-UPF1), UPF2, UPF3B, and UPF3AL but not SMG5 and SMG7 and the other (“wee complex”) containing P-UPF1, UPF3B, SMG5, SMG7, and UPF3AS but not UPF2 (Ohnishi et al., 2003; Schell et al., 2003). Building on these results, it has been hypothesized that phosphorylated UPF1 recruits the SMG5–SMG7 complex and forms together with PP2A and UPF3AS the so-called wee complex that induces dephosphorylation of UPF1 (Anders et al., 2003; Ohnishi et al., 2003). Hence, the exchange of UPF3AL for UPF3AS might represent the transit between a postphosphorylation (P-UPF1/UPF2/UPF3B/UPF3AL) and a predephosphorylation (P-UPF1/SMG5/

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SMG7/UPF3AS) complex (Ohnishi et al., 2003; Wilkinson, 2003). This predephosphorylation complex is in its composition similar to a UPF1/SMG5/SMG7 complex that has been reported to assemble in cytoplasmic processing bodies (P-bodies), the presumed sites of mRNA degradation (Eulalio et al., 2007; Unterholzner and Izaurralde, 2004) (see below). In the light of results that implicate Y14 and UPF3B in the phosphorylation of UPF1, in addition to UPF2, it is conceivable that upon recognition of a PTC a complex forms that contains UPF1, Y14, UPF3B, and optionally UPF2, and triggers the phosphorylation of UPF1 by SMG1. At this point, UPF3AL and SMG7 may join the complex and target it to P-bodies where 3AL is exchanged for 3AS and SMG5 and the phosphatase are recruited. Since UPF3A proteins appear not to be essential for NMD, it is as yet unclear which exact role they play. The discovery that they can interact with a complex containing UPF1 and the release factors eRF1 and eRF3 (Kashima et al., 2006) even when binding of UPF2, UPF3B, and components of the EJC to UPF1 is abolished could also indicate that they have a role in the translation termination at a PTC rather than in the degradation phase of NMD. In contrast to the UPF3A proteins, UPF3B is a bona fide NMD effector. It joins the prespliced mRNA at an early step of splicing during or immediately after 50 exon cleavage and intron lariat formation (Kataoka and Dreyfuss, 2004). For its recruitment to the EJC, it does not need Y14, which joins the mRNP at a later step, but both proteins accompany the mRNA to the polysomes and their interaction is essential for NMD (Gehring et al., 2003). Whether this reflects the necessity of both proteins for phosphorylation of UPF1 (Kashima et al., 2006) is not clear. It is probably fair to assume that both proteins are recruited to all EJCs and not only to PTC-mutated transcripts. This as well as the observation that they—like other NMD factors—direct transcripts to polysomes and enhance the efficiency of translation if they are bound within an ORF (Nott et al., 2004) indicates that they probably have additional functions beyond NMD (see below).

2. . . . and all the others While in yeast the three Upf proteins and in C. elegans the seven SMG proteins are so far the only factors implied in NMD, in mammalia a plethora of other proteins that have been assigned a role in NMD has been identified. These proteins fall into several groups that reflect the stages of NMD: the nuclear processes of capping and splicing on the one hand and translation on the other. This specifies two hallmarks of mammalian NMD and at the same time presents its biggest and so far unsolved problem: how can the two indispensable features, translation termination at the PTC, and the presence of at least one downstream exon junction be merged into a sensible concept. A lot of data have been collected on both loose ends and models founding on diverse sets of these data have been

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constructed during the last decade but conceptually it is still difficult to tessellate them into a coherent mosaic that does not require warping or blinding out some of the pieces.

a. Nuclear events: The cap-binding complex . . .

The 50 end of mRNAs is a modified guanine residue that is added to the growing transcript as soon as it is about 25 nucleotides long. This so-called cap is furnished cotranscriptionally with a nuclear cap-binding complex (CBC) consisting of the cap-binding proteins (CBPs), CBP20 and CBP80. These proteins are thought to serve at least three functions: protection of the 50 end from nucleolytic attack, splicing of the first exon, and intranuclear transport. In the cytoplasm, the nuclear CBPs are exchanged for the translation initiation factor eIF4E that promotes recruitment of the small ribosomal subunit to the mRNA and is thought to interact with poly(A)-binding protein 1(PABP1) to form the closed loop structure of translating polysomes (Borman et al., 2000; Wells et al., 1998). Recently, it has become a prevailing hypothesis that the pioneer round of translation is special and initiates on transcripts that still retain the nuclear CBC, possibly in transit from the nuclear pore. In extension, it has been proposed that NMD occurs exclusively during this pioneer round of translation and that transcripts that have exchanged the CBC for eIF4E are NMD insensitive (Chiu et al., 2004; Ishigaki et al., 2001; Lejeune et al., 2002). This model fits nicely into the concept of a complete remodeling of the mRNP from a “quasi-nuclear” or postexport to a cytoplasmic condition. The former besides the CBC would also include many exon junction proteins (see below). The CBC, after the pioneer round of translation, would be exchanged for eIF4E (Lejeune et al., 2002). Remodeled mRNPs that survive the pioneer round of translation would be validated as error-free and be retained in the translatable pool of transcripts. This pioneer round of translation model for NMD has been proposed based on several observations: 1. In immunopurification experiments, nonsense-containing mRNAs copurified with CBP80 and already exhibited a reduced level comparable to the level of PTC-containing mRNAs associated with eIF4E (Ishigaki et al., 2001). 2. Cycloheximide or suppressor tRNAs increased the level of PTC-containing CBP80-bound mRNA (Lejeune et al., 2002). 3. In immunoprecipitation experiments, core EJC components were detected on CBP80- but not an eIF4E-bound mRNA (Lejeune et al., 2002). 4. The translation initiation factor eIF4G was found to functionally interact with the CBC and copurify with UPF proteins and the EJC core component eIF4A3 (Lejeune et al., 2004). 5. Coimmunoprecipitation experiments indicated recruitment of UPF1 by the 80 kDa subunit of the CBC (Hosoda et al., 2005).

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However, this translation model is hard to reconcile with some other data. For example, it has been shown that NMD can occur on transcripts that are clearly not nucleus-associated, such as the mRNA for selenium-dependent glutathione peroxidase 1 (GPx1) encoding a selenoprotein, and further that NMD of GPx1 mRNA is not restricted to newly made transcripts. Selenoprotein-encoding mRNAs can be productively translated when in the presence of selenium, a UGA codon within the ORF is interpreted as a selenocysteine codon or can alternatively under selenium deprivation be defined as an NMD target and directed to degradation (Moriarty et al., 1998; Sun et al., 2000, 2001). It is conceptually difficult to assume that these transcripts retain the CBC until the advent of the very round of translation that under conditions of selenium deprivation unveils their UGA codon to the NMD machinery. At least for these transcripts, recognition of the PTC in any round of translation and with eIF4E bound to the cap must be possible, thus casting doubt on the unconditional necessity of the CBC for mammalian NMD. In addition, yeast CBC is dispensible for both translation (Baron-Benhamou et al., 2004) and NMD (Gao et al., 2005; Kuperwasser et al., 2004) and shows only weak translation initiation activity (Fortes et al., 2000). Translation initiation activity of the CBC has not been shown for the CBC in other eukaryotes. Moreover, NMD in yeast can occur in any round of translation (Gao et al., 2005; Maderazo et al., 2003). The pioneer round of translation model posits that NMD occurs only on CBC-bound mRNAs (Chiu et al., 2004; Lejeune et al., 2004). Importantly, it also posits that the CBC promotes the recruitment of UPF1 and the interaction of UPF1 with UPF2 (Hosoda et al., 2005). This hypothesis is challenged by the observation that translation initiated from an internal ribosome entry sequence (IRES) of the encephalomyocarditis virus (EMCV) can elicit NMD (Holbrook et al., 2006). The EMCV IRES is capable of recruiting ribosomes directly and drives cap-independent translation. These data support a model of NMD in which translating ribosomes per se are required for NMD and that this function is independent of the mode of ribosomal entry.

b. . . . and the EJC In metazoans, pre-mRNA splicing deposits the EJC 20–24 nucleotides upstream of exon–exon junctions and thereby imprints the transcript in a way that is relevant for subsequent requirements of mRNA metabolism. The core EJC consists of four proteins, the heterodimer Y14/Magoh, BTZ and eIF4AIII, a DExH/D box helicase that directly binds to the mRNA and is thought to anchor the EJC to the exon junction. This core EJC provides a platform for the dynamic assembly (and disassembly) of a plethora of additional nuclear and cytoplasmic factors into function-specific RNP domains that participate in mRNA transport, subcellular localization, translation, and turnover (Maquat, 2004; Merz et al., 2007;

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Tange et al., 2004, 2005). Surprisingly, at least some of the core and peripheral EJC factors overlap in the latter two functions (Nott et al., 2004) (see below). For mammalian NMD, at least one EJC at an NMD-competent position 30 to the PTC is necessary for the cell to identify a termination codon as premature. According to current models, RNPS1, a general splicing coactivator, and UPF3B (among other proteins relevant for other functions) join the EJC in the nucleus. UPF3B is assumed to remain bound to the EJC and to recruit UPF2 during or immediately after export on the cytoplasmic side of the nuclear pore, whereas RNPS1 is generally thought to dissociate during or shortly after mRNA export. Yet, the fact that RNPS1 coimmunoprecipitates with UPF1, UPF2, and UPF3A/B is in conflict with this notion, considering that UPF1 most likely interacts with the EJC only after PTC recognition. Once in the cytoplasm, the majority of EJCs, especially those that reside within the ORF, are assumed to be removed during the first round of translation by the translating ribosome (Fig. 4.1). This hypothesis was experimentally supported by the observation that the EJC protein Y14 remains associated with untranslated mRNAs but is removed from translationally active mRNAs (Dostie and Dreyfuss, 2002). Whether this is true for all EJC core components or whether some remain bound and attract yet another set of proteins or reassociate with the mRNA remains to be determined. Using tethered function analysis, it was possible to prove that not only the UPF proteins but also the EJC components RNPS1, eIF4AIII, BTZ, Y14, and Magoh (Gehring et al., 2003, 2005) function as activators of mammalian NMD; moreover, this type of experiment helped to reveal that Y14 and Magoh act as one heterodimeric functional unit and that Y14 and UPF3B form a UPF2independent NMD-activating complex (Gehring et al., 2003). siRNA-mediated UPF1 depletion abrogates the NMD-activating effect of all NMD proteins that have been tested in tethered function analysis except SMG7 whereas replenishing cells with exogenous UPF1 after depletion restore it. Therefore, UPF1 is thought to interact with EJC components late in the sequence of events that ultimately lead to the decay of a nonsense-mutated mRNA. Most interestingly, an experimental setting that combines tethering, mutation analysis, immunoprecipitations, and siRNA-mediated depletion of candidate proteins revealed that at least two sets of proteins can assemble on core EJCs, thus specifying distinct entry routes into the NMD pathway used by particular subsets of PTCcontaining transcripts. These entry routes merge into a UPF1-dependent degradation pathway as do, interestingly, two other transcript-specific and UPF1-dependent mRNA turnover pathways. In both Staufen 1-mediated mRNA decay (SMD) and replication-dependent histone mRNA degradation, the regulated and translation-dependent recruitment of UPF1 to the 30 UTR of specific classes of mRNAs induces their decay (see below).

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It is experimentally supported that EJC components residing in the ORF are removed by the translating ribosome during the first round of translation (Dostie and Dreyfuss, 2002; Lejeune et al., 2002). However, in the case of transcripts that can potentially mask and unmask their PTCs as a means for posttranscriptional regulation, NMD-active core or peripheral EJC components either can be recruited back to a position 30 to the PTC or the requirement for the EJC can be circumvented in subsequent rounds of translation. Moreover, there is at least one example of mammalian NMD where UPF1 but not an EJC is required (Buhler et al., 2006). Thus, on the level of the nuclear proteins that have been shown or suggested to play an essential role in NMD, it appears to be necessary to reevaluate the prevailing models and design alternative experiments that could help to solve the conceptual conflicts about the mechanisms underlying mammalian NMD.

3. Cytoplasmic events: Translational termination The second loose end in current models of NMD is the imperative requirement for translational termination and the interaction of NMD factors with the termination site. Biochemical studies revealed RNA-dependent ATPase, 50 -30 ATP-dependent RNA helicase, and RNA-binding activities of both yeast Upf1p (Czaplinski et al., 1995; Weng et al., 1996b) and UPF1 (Bhattacharya et al., 2000) and functions of Upf1p in both NMD and translational termination. Initially, the notion that Upf1p might be involved in termination arose from the observation that a yeast upf1D strain displayed a nonsense suppression phenotype leading to the conclusion that Upf1p enhances translational termination at least at nonsense codons (Weng et al., 1996a). Consistently, a direct interaction between Upf1p and translation termination factors eukaryotic release factor (eRF) 1 and eRF3 has been shown (Czaplinski et al., 1998). Mutations in the helicase region of Upf1p inactivate its mRNA decay function but still support translational termination at a nonsense codon, whereas mutations in the cystidine-histidine rich region do not affect the mRNA decay function but suppress nonsense codons (Fig. 4.3). Thus, the Upf1 protein’s mRNA decay functions can be separated from its functions in nonsense suppression and hence in translational termination (reviewed in Czaplinski et al., 1999; Gonzalez et al., 2001). The separability of both Upf1p functions indicate that they do not depend on each other, that is that a function of Upf1p in the termination event at a nonsense codon is not necessary for yeast NMD. Accordingly, in yeast, interaction of Upf1p with the release factors inhibits its ATPase activity and eRF3 prevents formation of the complex between Upf1p and RNA, suggesting that the ATPase/helicase and RNA-binding functions of Upf1p are dispensible for its function in translational termination.

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Since eRF3 prevents the Upf1p–RNA complex formation and since binding of ATP to Upf1p destabilizes the Upf1p–RNA complex irrespective of its ATPase function, it has been suggested that ATP is a cofactor that regulates the interaction of Upf1p with RNA and release factors, respectively and may serve to switch Upf1p between its functions in NMD and translational termination. Early in vitro (Wang et al., 2001) experiments revealed that UPF1, the human orthologue of Upf1p, also interacts with eRF1 and eRF3. More recently, an in vivo complex between SMG1, UPF1, eRF1, and eRF3 was identified (see above) and referred to as SURF (Behm-Ansmant and Izaurralde, 2006b; Kashima et al., 2006) (Fig. 4.7A). SURF thus implicates mammalian UPF1 in translational termination. However, the same study revealed that SMG1 is also found on the postsplicing mRNP in association with the EJC components UPF2, UPF3B, eIF4III, MAGOH, and Y14. Interestingly, phosphorylation of UPF1 by SMG1 that is essential for NMD depends on interaction of SMG1 with UPF2 and Y14. Depletion of UPF2 or Y14 (which equates with prevention of UPF1 phosphorylation and in many cases with abrogation of NMD) or expression of a UPF1 mutant that is unable to bind UPF2 greatly enhanced the association of UPF1 with the eRFs and with SMG1 (the SURF complex). The fact that SMG1 coimmunoprecipitates UPF1 and eRFs on the one hand as well as EJC components and UPF1 on the other suggests that SURF forms at the termination site and subsequently interacts with the 30 EJC to form a decay-inducing complex (DECID) (Fig. 4.7A). Assembly of the as yet hypothetical DECID is thought to trigger UPF1 phosphorylation and dissociation of the release factors (Kashima et al., 2006). Yet, the data are also compatible with two independent complexes, which may represent two possibly independent functions of UPF1 in translational termination and NMD. The only currently available antibody against phosphorylated UPF1 detects only 2 of the 28 available S/T-Q sites in this molecule that reside in the C-terminal cluster of phosphorylation sites, and only 13 of the 28 possible PIKK phosphorylation target sites have been assessed in vitro as putative SMG1 targets (Yamashita et al., 2001; Fig. 4.5). Detection of P-UPF1 in a complex with SMG1, UPF2, UPF3B, and Y14 indicates that UPF1 is phosphorylated at these two residues when it interacts with the EJC. At present, it is unclear if UPF1 at the termination site is not phosphorylated at all or at other sites that may not be detected by the P-UPF1 antibody. Differential phosphorylation or alternatively phosphorylation per se could specify the functions of UPF1 in translation termination and decay. Intriguingly, UPF1 can be coimmunoprecipitated by both the N-terminal and the C-terminal half of SMG1. The N-terminal half pulls down UPF1, SMG7, and UPF3AS, whereas the C-terminal half coprecipitates UPF1 and the EJC components Y14, MAGOH, UPF3B, and UPF2 (Kashima et al., 2006). This observation is consistent with the idea that SMG1 may bind to different UPF1 portions to phosphorylate distinct S/T-Q sites or sets of S/T-Q sites, thereby specifying distinct UPF1 functions. Moreover, although

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Figure 4.7. Options of UPF1 function in translation and NMD. (A) SURF/DECID model. UPF1 is recruited together with SMG1 to the termination site and interacts with the release factors 1 and 3 (RF1/3) to form the SURF complex. Recognition of the PTC induces interaction of SURF with UPF2, UPF3B, and Y14 at the exon junction complex (EJC) to form the decay-inducing complex (DECID). DECID triggers UPF1 phosphorylation followed by dissociation of the release factors and mRNA degradation. The physical (Continues)

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not thoroughly investigated, phosphorylation of UPF1 is wortmannin-sensitive and also rapamycin-sensitive (Pal et al., 2001). Since SMG1 is not influenced by rapamycin (Denning et al., 2001), this points to the involvement of an mTORlike kinase. However, because of the multitude of putative phosphorylation sites, modulation of activities or functions of UPF1 by other kinases is equally conceivable. The postulated interaction of SURF with components of the EJC bears another conceptual problem: this interaction has to be able to bridge long distances that may separate the PTC from the next EJC. This problem is not unusual and finds its (equally unresolved) parallels in the distances that have to be bridged by molecular machines engaged in transcription, splicing, and translational regulation. Several scenarios are imaginable (Fig. 4.7A–D): (1) looping of the 30 UTR that would thus juxtapose termination site and EJC; such a scenario is comparable to gene loops that have been identified during transcription of long genes and that may function to proofread control sequences before transcriptional elongation (O’Sullivan et al., 2004), as well as to intron looping and lariat formation during pre-mRNA splicing; (2) the formation of a posttermination surveillance complex (possibly including the small ribosomal subunit) that inspects the 30 UTR for the presence of an EJC; (3) two independent UPF1-containing complexes; and (4) migration of UPF1 to the EJC, analogous to the migration of other ssDNA or RNA helicases. The crystal structure of the UPF1 helicase domain in AMPPNP-, ADP-, and phosphate-bound forms suggests a mechanism by which ATP binding and -hydrolysis could specify functions of UPF1 (Cheng et al., 2007). The helicase domain of UPF1 belongs to superfamily 1 (SF1) of DNA/RNA helicases, which are involved in most aspects of nucleic acid metabolism. These molecules generally promote

interaction between the termination site and factors bound to the exon junction requires looping of the sometimes very long RNA stretch in-between. (B) Scanning model. Recognition of the PTC induces formation of a surveillance complex that includes UPF1, SMG1, and possibly the small ribosomal subunit and scans the 30 UTR. Interaction with an EJC triggers UPF1 phosphorylation and mRNA decay. (C) Two-complex model. UPF1 functions in translation termination at a PTC and may to this end be phosphorylated by SMG1 or another kinase (?) at other sites than the ones involved in its NMD function (P in a rhombus). Moreover, UPF1 is a component of an NMDinducing complex that forms at the exon junction and includes UPF2, UPF3, and Y14. Here, it is phosphorylated by SMG1 at least at residues 1078 and 1096. This complex labels the 30 UTR as aberrant. Both complexes are necessary to induce NMD. (D) Migration model. UPF1 interacts in the ATP-bound form with the release factors. When termination is completed, the release factors dissociate and the ATPase function of the UPF1 is activated. ADP-bound or ligand-free UPF1 binds to the RNA and uses first helicase activity to migrate along 30 UTR until it encounters an EJC. Interaction with the EJC triggers UPF1 phosphorylation and mRNA decay.

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transitions in RNP structures and have been suggested to use conformational changes driven by ATP binding and hydrolysis to migrate along bound nucleic acids (Mackintosh and Raney, 2006). Consistently, ATP binding reduces but not abolishes binding of UPF1 to ssRNA, whereas ATP hydrolysis induces conformational changes that enhance RNA binding. This is in line with the abovementioned results in yeast which indicated that interaction with release factors and inhibition of ATPase activity mediate the role of Upf1p in termination whereas ATP hydrolysis is necessary for its function in NMD. Thus, it is conceivable that UPF1 either uses ATP hydrolysis to induce conformational changes at the termination site or the exon junction or both that ultimately lead to mRNA decay. Any mutation that blocks the ATPase activity of Upf1p leads to an increased accumulation of P-bodies. This may indicate that ATP hydrolysis after termination and release of the eRFs serve Upf1p/UPF1 as a motor to translocate from the termination site to the EJC where the interaction with UPF2, UPF3B, and EJC components would trigger NMD (Fig. 4.7D).

a. Beyond termination: The role of the 30 UTR Whereas at least one splice event 30 to the termination codon is essential for mammalian NMD and hence, intronless mammalian mRNAs are resistant to NMD, neither yeast nor fruitflies use EJCs to discriminate between premature and regular termination events. In yeast, the majority of transcripts are not spliced, whereas many Drosophila pre-mRNAs are spliced and assemble EJCs containing homologues of the EJC components that are essential for mammalian NMD. Yet, in this organism, EJCs appear to be predominantly used for mRNA transport and localization and do not play a role in NMD (Gatfield et al., 2003). In yeast, binding of the protein Hrp1p to a loosely defined nucleotide sequence named downstream sequence element has been proposed to function analogously to the EJC in that it has to be present 30 to the PTC to trigger NMD (Cui et al., 1999; Gonzalez et al., 2000). More recently, for both yeast and fruitfly, an alternative model has been put forward which posits that termination at a PTC encounters a “faux 30 UTR”, that is, an aberrant 30 UTR RNP domain that influences termination and thus serves as determinant for mRNA decay (Amrani et al., 2004; Behm-Ansmant and Izaurralde, 2006a). Interestingly, NMD in higher plants may provide a link between yeast and fruitfly NMD on the one hand and mammalian NMD on the other in that both aberrant 30 UTRs and splicing 30 to a termination codon direct plant transcripts to NMD (Kertesz et al., 2006). The faux 30 UTR model, originally formulated by Hilleren and Parker (1999), proposes that instead of active recognition of a faulty transcript by a posttermination surveillance complex that has to interact with “something” downstream, the 30 mRNP domain affects the nature of termination itself. The presence of an improper or faux 30 UTR as is the case if translation terminates upstream of the proper termination codon would slow down termination and

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recruit Upf1p. The discrimination between a proper and an improper termination event would occur via an internal timing or kinetic proofreading mechanism that depends on the rate of ATP hydrolysis by Upf1p (Hilleren and Parker, 1999). Originally based on the observation that abnormally extended 30 UTRs direct yeast transcripts to NMD (Muhlrad and Parker, 1999) and that deletion of each of the three NMD effectors in yeast, Upf1p, Upf2p and Upf3p, reduces the fidelity of translational termination albeit to various extents, this model has found additional support in various recent findings both in yeast and in Drosophila. The low cellular levels of all three Upf proteins (Maderazo et al., 2000), as well as the fact that their deletion is not lethal in yeast, make it unlikely that they have essential roles in normal termination. Consistently, toeprint analysis revealed that premature termination in yeast differs from normal termination in that ribosomes that encounter a PTC fail to be released (Amrani et al., 2004) and instead engage in both backward and forward scanning for a reinitiation codon. This latter activity is inhibited by the deletion of upf1 or upf2 genes, indicating that their products regulate ribosomal behavior at PTCs. In accordance with the faux 30 UTR hypothesis, the deletion of the coding sequences between the PTC and the normal 30 UTR stabilized transcripts otherwise sensitive to NMD and eliminated aberrant toeprints. Likewise, mimicking a normal 30 UTR by tethering the poly(A)-binding protein Pab1 to a site close to a PTC antagonized NMD, presumably by providing a 30 UTR environment that allows the assembly of factors that promote proper translation termination. In yeast, 30 UTRs are relatively short and similar in length so that a uniform and therefore discernibly “proper” or “improper” 30 UTR RNP assembly is conceivable. Yet, this is not true for 30 UTRs of higher eukaryotes that can vary in length from a few to several thousand nucleotides, and neither in fruitfly (Rehwinkel et al., 2005) nor in mammalian cells (Neu-Yilik et al., 2001; Thermann et al., 1998), abnormally extended 30 UTRs direct the respective transcripts to NMD. However, tethering of PABC1, the homologue of Pab1 in multicellular organisms, to a region 30 to a PTC on a fruitfly mRNA also suppresses NMD and thus links fruitfly to yeast NMD (Rehwinkel et al., 2006). Furthermore, even in mammalia, at least in some cases, NMD depends on 30 UTR length (Buhler et al., 2006) or on the nature of the 30 UTR mRNP (Weil and Beemon, 2006). It has even been suggested that the scenario in mammals might be similar if not identical to that in yeast and that the influence of EJCs on NMD lies simply in the fact that they enhance the translation rate and thus simultaneously the turnover rate of nonsense-mutated mRNAs (Culbertson and Neeno-Eckwall, 2005; Ford et al., 2006; Hilleren and Parker, 1999). However, even though EJCs appear to promote initial polysome formation and translation (Nott et al., 2004), many nonsense-mutated mRNAs would have sufficient EJCs in their ORFs 50 to the PTC to fulfill that requirement; nevertheless, at least one EJC 30 to the PTC is necessary for its recognition by the NMD machinery.

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Thus, the relationship between a termination event and the 30 UTR, whether specified by length and/or sequences which bind factors that ought not to be found on a proper 30 UTR, emerges as a unifying feature between the NMD of different organisms and the NMD of different transcripts within one organism. In the light of this hypothesis, it can even be asked if NMD, SMD, and replicationdependent histone mRNA decay (see below in Section VI) are all variants of the same theme: a termination event in the wrong 30 UTR context. The spatial and molecular requirements differ in several respects between pathways and organisms but also show some interesting mutual overlaps (Table 4.2 and Fig. 4.8). Thus, yeast, fruitfly, and mammalian NMD, SMD, and replication-dependent histone mRNA decay all are unified by certain restrictions concerning the spatial relationship between the termination event and special features of their 30 UTR. In mammalian NMD, an EJC must be located at least 25 nucleotides 30 to the termination codon. The same is true for the sequence element that binds the UPF1-recruiting protein Staufen 1. The stem loop in the 30 UTR of histone mRNAs that is involved in regulated histone mRNA decay must be located 22–77 nucleotides 30 to the termination codon in order to trigger UPF1-dependet decay (Kaygun and Marzluff, 2005b). The length of both yeast transcripts and mammalian histone transcripts are usually restricted to less than 100 nucleotides, yet while unusually long 30 UTRs in yeast trigger NMD, increasing the distance between the termination codon and the stem loop stabilizes histone mRNAs (Kaygun and Marzluff, 2005b). In mammalia and fruitfly, the length of the 30 UTR appears to play no dominant role in NMD. However, while mammalian NMD requires the EJC, fruitfly and yeast NMD rather appear to need Pab1p/PABPC1 in an as yet unclear way. It remains to be shown if all these mechanisms funnel transcripts into the same degradation pathways specified by identical molecular actors. Likewise, it remains to be determined how Upf1-containing complexes and/or the PABC1/Pab1p proteins bound to poly(A) tails can influence termination, especially in the case of the sometimes very long fruitfly 30 UTRs. Similarly, it is an open question if SMD and replication-dependent histone mRNA decay require a specific type of termination event, as has been suggested for NMD.

4. Degradation (or sometimes not) Although a collection of jigsaw pieces of data from different organisms is available, the exact mechanism of degradation of nonsense-mutated mRNAs is an unresolved question. In contrast to bulk mRNA turnover, in yeast the degradation phase of NMD circumvents the normal requirement for deadenylation, and PTC-containing transcripts are rapidly degraded after decapping by the 50 –30 exonuclease Xrn1p (Cao and Parker, 2003; Muhlrad et al., 1994). Yet, PTC-dependent accelerated deadenylation has also been reported (Mitchell and

Table 4.2. Molecular and Spatial Requirements of Upf1-Dependent mRNA Turnover Pathways

Yeast NMD Fruitfly NMD Mammalian NMD SMD Replication-dependent histone mRNA decay

Translation termination

UPF1

30 UTR cis-acting elements

30 UTR RNP

Yes (aberrant) Yes Yes

Yes

DSE?

Pab1p

Yes Yes

PABPC1? EJC

Yes Yes

Yes Yes

? At least 1 exon junction SBS Histone 30 UTR stem loop

Staufen 1 SLBP

Spatial requirement Unnaturally long 30 UTR, aberrant distance between stop codon and poly(A) tail 30 UTR length unrestricted Exon junction > ~50 nt 30 to stop codon; EJC > 25 nt 30 to stop codon SBS > 25 nt 30 to stop codon Stem loop 22–77 nt 30 to stop codon

Abbreviations: NMD, nonsense-mediated mRNA decay; SMD, Staufen 1-mediated mRNA decay; DSE, downstream sequence element; SBS, Staufen 1-binding site; Pab1, yeast poly(A)-binding protein; PABPC1, fruitfly poly(A)-binding protein; SLBP, stem loop-binding protein; EJC, exon junction complex.

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Figure 4.8. 30 UTR-RNP requirements for NMD, SMD, and replication-dependent histone mRNA decay. (A) Yeast NMD. The normal 30 UTR of yeast mRNAs is usually less than 100 nucleotides long and constitutes a positive signal for termination. A PTC disrupts the proper 30 UTR RNP and the proper distance of a termination site to the Pab1p bound to the poly(A) tail. Therefore, premature termination is confronted with an improper 30 UTR conformation. This “faux” 30 UTR serves as a negative signal, leads to aberrant termination, and ultimately directs the mRNA to NMD. It is unknown if Upf1p in yeast NMD has a function in the 30 UTR. (B) Mammalian NMD. UPF1 bound to an exon junction complex (EJC) at a distance of at least 25 nucleotides 30 to the PTC constitutes (Continues)

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Tollervey, 2003). In mammals, NMD accelerates the rates of decapping, deadenylation, and in some cases endonucleolytic cleavage (Bremer et al., 2003; Chen and Shyu, 2003; Couttet and Grange, 2004; Lejeune et al., 2003; Stevens et al., 2002; Yamashita et al., 2005) and involves the decapping enzymes DCP1 and DCP2 (Lykke-Andersen, 2002; Yamashita et al., 2005), the deadenylation factors (Yamashita et al., 2005), as well as exonucleases such as XRN1 and the cytoplasmic exosome (Chen and Shyu, 2003; Lejeune et al., 2003). In fruitflies, NMD appears to rely mainly or exclusively on endonucleolytic activities within the vicinity of the PTC without prior decapping of the 50 fragment or deadenylation of the 30 fragment. The 50 fragment is subsequently degraded by the exosome and the 30 intermediate by dXrn1 (Gatfield et al., 2003). In yeast and mammalian cells, decapping and 50 –30 mRNA degradation are thought to occur in specialized cytoplasmic bodies, P-bodies in yeast and GW bodies or mammalian P-bodies in human cells. These structures are enriched in decapping and other mRNA decay enzymes, mRNAs and mRNA intermediates (Cougot et al., 2004; Eulalio et al., 2007; Eystathioy et al., 2003; Ingelfinger et al., 2002; Sheth and Parker, 2003, 2006). In both organisms, intriguing links between NMD and these cytoplasmic foci have been identified. In yeast, Upf1p targets PTC-containing transcripts to P-bodies. Targeting (at least of transcripts that carry PTCs in the 50 portion of their ORFs) is independent of Upf2p and Upf3p; however, these two proteins as well as the ATPase activity of Upf1p are necessary for transcript degradation. Interestingly, Upf1p also targets normal mRNAs to P-bodies as shown in a strain overexpressing an ATPasedeficient upf1 allele, but the ATP hydrolysis activity of Upf1p is likely to be required for recycling of these transcripts to the translating pool (Sheth and Parker, 2003, 2006). Based on these observations, two modes of NMD factor assembly have been suggested (Culbertson and Neeno-Eckwall, 2005): (1) “nuclear marking” for the first round of translation and (2) “reverse assembly” for each subsequent round. In yeast, NMD can occur in any round of translation (Gao et al., 2005; Maderazo et al., 2003), so that at least in this organism, NMD factors must be recruited back to the mRNA after the first round of translation. According to this model, the assembly of NMD-competent mRNPs in yeast a 30 UTR RNP domain that serves as a negative signal to induce NMD. (C) Staufen 1-mediated mRNA decay (SMD). UPF1 bound to a complex that contains Staufen 1 at the Staufen 1-binding site (SBS) at a distance of at least 25 nucleotides to the termination codon constitutes a 30 RNP domain that serves as a negative signal to induce mRNA decay. (D) Replication-dependent histone mRNA decay. UPF1 bound to a complex that contains the Stem loop-binding protein (SLBP) and the histone 30 UTR stem loop (hairpin) at a distance of 22–77 nucleotides to the termination codon constitutes a 30 RNP domain that serves as a negative signal to induce mRNA decay. Note that increasing the distance between the termination codon and the stem loop abrogates the decay. It is unknown if in B, C, and D, UPF1 is involved in translation termination.

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likely occurs in two steps that are independent from each other (Atkin et al., 1997; Culbertson and Neeno-Eckwall, 2005). One subcomplex contains Upf2p and Upf3p and the other Upf1p, eRF1, and eRF3. During nuclear marking, Upf3p binds to the transcript, possibly mediated by Hrp1, and is assumed to subsequently recruit Upf2p. The Upf1p/eRF complex is formed during translational termination of the first round of translation before finally the so-called surveillance complex assembles. During any subsequent round of translation, the subcomplexes are suggested to form in the reverse order: Upf1p assembles with the RFs at the premature termination site and this complex subsequently recruits Upf2p/3p via Upf1p and/or eRF3. Since targeting of PTC-containing (and some error-free) mRNAs to P-bodies depends on Upf1p but not on Upf2p and Upf3p, it is conceivable that PTC-containing (but not error-free) transcripts later pick up Upf2p/3p in association with P-body formation where these proteins are needed to trigger decay. For mammalian NMD, it is generally assumed that the translating ribosome displaces NMD factors from the to-be-translated mRNA and therefore, NMD is necessarily and exclusively restricted to the first round of translation. The idea of reassembly of an NMD-competent mRNP before subsequent rounds might help to conceptually rethink some unresolved issues also in mammalian NMD. For example, a role of UPF1 in translational termination at a PTC on the one hand and targeting of the transcript to P-bodies on the other plus an independent role of UPF2 and UPF3 in triggering decay within the P-bodies would liberate mammalian NMD from the necessity of a direct interaction between the termination site and the potentially far downstream EJC (see above). If a transcript that is targeted to P-bodies by UPF1 still retains UPF3 and/or UPF2 or alternatively picks them up there, it will be degraded. Consistently, depletion of mammalian UPF2 or UPF3 leads to the accumulation of the SURF complex (Kashima et al., 2006), thus highlighting the independence of UPF1 activity from the other UPF proteins. As has been suggested (Sheth and Parker, 2006), UPF2 and UPF3 in P-bodies may activate decay by supporting the phosphorylation of UPF1. It remains to be determined whether this corresponds to phosphorylation of UPF1 at the premature termination site that is directed by a direct physical interaction with the EJC or whether it corresponds to phosphorylation of UPF1 that is independently recruited to the EJC together with UPF2, UPF3, and others. However, some experimental evidence for P-body resident UPF1 phosphorylation exist. In human cells, transiently expressed SMG5, SMG7, and UPF1 are localized to mammalian P-bodies (Fukuhara et al., 2005). SMG7 is thought to recruit SMG5 and UPF1 to the decay foci via its C-terminal domain and to trigger ultimate decay in a mechanism that involves the decapping enzyme DCP2 and the 50 –30 exonuclease XRN1. The necessity of SMG7 for the degradation per se is supported by the observation that SMG7 degrades a reporter even when tethered upstream of a stop codon or

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when tethered 50 to the ORF; this means, it acts late in the NMD pathway and even downstream to UPF1 and likely is recruited to the mRNA after PTC recognition. SMG5, SMG6, and SMG7 have conventionally been considered to function together with PP2A in the dephosphorylation of UPF1 (Chiu et al., 2003; Ohnishi et al., 2003; Page et al., 1999). Consistently, the 14-3-3 like domains present in all three proteins bind phosphorylated UPF1 (Fukuhara et al., 2005) and therefore they probably mediate the interaction between UPF1 and PP2A. However, this appears not to be their sole function. Besides the task of SMG7 in targeting UPF1-bound mRNAs to decay foci, recent investigations of the PIN-domains of SMG5 and SMG6 point to an intrinsic nuclease activity of SMG6 (but not SMG5) that may contribute to the degradation of PTC-containing transcripts (Glavan et al., 2006). However, although SMG6 is essential for NMD, it does not colocalize with SMG5 and SMG7 to P-bodies and can be bypassed by SMG7. This may indicate that the transcripts that localize to P-bodies mediated by a nuclease-inactive UPF1/SMG7/SMG5 complex are degraded there by the resident nucleases whereas SMG6 may act in a second NMD pathway adding to the differential cofactor requirements that have been described for distinct routes of NMD (Gehring et al., 2005). Alternatively, it has been suggested that the nuclease activity of SMG6 and the final SMG5/SMG7-mediated degradation of PTC-mutated transcripts are consecutive steps in a common pathway (Glavan et al., 2006). Finally, it is equally possible that the function of SMG6 in NMD is restricted to UPF1 dephosphorylation whereas its nuclease functions are NMD independent and may be related to its role in telomere maintenance (see below) or an as yet unrelated moonlighting task.

III. TARGETS OF NMD The class of NMD substrates that first comes to mind is mRNAs with an erroneous in-frame stop codon that interrupts their ORF. PTCs can be acquired by nonsense and frameshift mutations. Furthermore, unproductive somatic DNA rearrangements [in the case of T-cell receptor (TCR) and immunoglobulin genes], transcriptional errors, and splice errors can result in frameshifts and subsequently in reading frames that terminate prematurely. Other types of faulty transcripts are exemplified by pre-mRNAs that escaped nuclear retention, pseudogene transcripts, mRNAs that host snoRNAs in their introns and transcripts encoded by transposable elements, or their long-terminal repeat (LTR) sequences (reviewed in Conti and Izaurralde, 2005; Holbrook et al., 2004). In all of these cases, NMD is thought to exert a vacuum cleaner function by ridding the cell from the burden of faulty RNAs.

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Another likewise heterogenous group of NMD substrates can be classified as “physiological targets” because their expression appears to be modulated instead of inhibited by NMD. This group can be divided into several subcategories. One is represented by transcripts that can activate an alternative splice pattern that may result in multiple isoforms with PTCs; this phenomenon, termed unproductive regulated splicing (Lewis et al., 2003), has been described for a number of genes (Cuccurese et al., 2005; Sureau et al., 2001; Wollerton et al., 2004) and is at least in some cases thought to be triggered by the protein products of these genes thus autoregulating the expression of the canonical protein-encoding isoforms. It seems worthwhile to mention that it is not all that clear if the sometimes very complex splice patterns that arise in response to normal isoform overexpression are really unproductive in terms of protein expression and that they sometimes include PTC-free transcript isoforms as well (Sureau et al., 2001). More thorough investigations are necessary to elucidate whether in fact, gene expression actually is shunted into the production of several protein isoforms expressed by the same gene. A conceptually and functionally similar subcategory is represented by transcripts that use translational þ1 ribosomal frameshifting. This class of NMD targets has been identified in genome-wide expression profiles of NMD-deficient yeast cells and the PTCs in their ORFs are assumed to be introduced by regulated þ1 ribosomal frameshifting in situations when downmodulation of these transcripts’ expression is desired. At present, it is not yet clear if transcripts with regulated ribosomal frameshifting are also targeted by mammalian NMD. Messenger RNA editing is potentially another means to posttranscriptionally include PTCs into a transcript although it is generally not known if these mRNAs can be directed to NMD. However, the case of ApoB demonstrates that PTCs that are the result of mRNA editing can be concealed from NMD (Chester et al., 2003). It is conceivable that this is a regulated process and that under changing physiological conditions, the PTC could be unveiled and the transcript degraded. Finally, NMD is involved in the regulation of selenoprotein synthesis. These transcripts contain in-frame UGA triplets that code for selenocysteine when selenium is abundant, and are interpreted as a PTC when selenium levels are low (Moriarty et al., 1998; Sun et al., 2001). A common feature of all these processes is that NMD can be potentially used to adapt protein expression to the physiological needs of the cell. It is as yet not clear if NMD here is solely—as commonly assumed—used to limit protein expression or if under certain circumstances NMD itself can be regulated thus allowing the functionally important expression of truncated protein. For instance, an alternative splice product of F"RI containing a PTC at an NMD-competent position is translated into low levels of the truncated protein that competes with the full-length isoform in a physiologically relevant way (Donnadieu et al., 2003). A similar example is seen in the

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unc-49 locus of C. elegans, which produces a PTC-containing splice form that not only is expressed at significant levels but also codes for a GABA-receptor isoform essential for worm locomotion (Bamber et al., 1999). Early on NMD has been implicated in the regulation of genes with upstream open reading frames (uORFs) and uORF-containing transcripts have concordantly surfaced in gene expression profiling analyses after NMD-factor silencing in yeast, fruitfly, and human cells. Thus, these messages appear to be conserved NMD targets and here the requirement for regulation is evident. According to changing necessities, NMD must be approved or prohibited in a regulated fashion. NMD activation by uORFs has mostly been studied in yeast. In the presence of artificial uORFs, mRNA levels of the yeast genes CAT (Oliveira et al., 1993) and CYC1 (Pinto et al., 1992) are reduced. The genes GCN4 and YAP1 naturally harbor several uORFs. Interestingly, they were shown to contain stabilizing elements (STE) that actively prevent degradation of their mRNAs via NMD (Ruiz-Echevarria and Peltz, 1996, 2000; Ruiz-Echevarria et al., 1998). These STEs are located between the uORFs and the start codon. An alternative example of how such a regulation can be exerted is provided by the yeast CPA1 gene. Here, the arginine attenuator peptide encoded by the uORF in the presence of arginine induces ribosome stalling at the termination codon of the uORF and thereby negatively regulates CPA1 expression on two levels: by preventing ribosomes from reaching the downstream ORF and by triggering NMD, probably due to defective termination (Gaba et al., 2005). However, uORF-containing NMD-insensitive mammalian transcripts have also been described (Stockklausner et al., 2006). NMD resistance could be due to as yet unknown protective cis- or trans-acting features, or perhaps the physiological situations that make such mRNAs accessible for the NMD have not yet been recognized. On a general scale, NMD appears to modulate the expression of 3–10% of the transcriptome (Rehwinkel et al., 2006) in yeast (Guan et al., 2006; He et al., 2003; Lelivelt and Culbertson, 1999), plants (Hori and Watanabe, 2005; Yoine et al., 2006), fruitfly (Rehwinkel et al., 2005), and human cells (Mendell et al., 2004; Wittmann et al., 2006). It has been suggested that NMD may influence whole pathways by modulating the expression of target transcripts that stand at the beginning or a node of these pathways. This implies that either the “visibility” of such transcripts for NMD can change or that general or specific physiological situations influence the effectiveness of the NMD pathway itself. Although within an organism natural NMD targets can be grouped into clusters of proteins that function in similar pathways, these rarely overlap in different organisms (Rehwinkel et al., 2005, 2006). Consistently, these groups of upmodulated NMD-sensitive targets are supplemented by a number of additional, albeit downmodulated transcripts that may function downstream of a primary NMD target. In human cells, UPF1 depletion upregulates several transcripts involved in amino acid metabolism, including two transcription

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factors that function in the response to amino acid starvation (Mendell et al., 2004; Weischenfeldt et al., 2005). Inhibition of general translation and thereby of NMD by amino acid starvation may thus serve to stabilize these transcripts to allow a rapid response when conditions change. The concomitant reinstallment of NMD by restored translation would equally rapidly downregulate these mRNAs and thus provide a feedback mechanism in hemostasis of amino acid metabolism (Mendell et al., 2004; Weischenfeldt et al., 2005). Studies in plants may open an unexpected avenue to the appreciation of metabolic pathways that are influenced by NMD. Distinct mutations in the plant orthologues of UPF1 and UPF3 exhibit a range of vegetative and floral abnormalities that will have to be systematically addressed to identify the endogenous and probably NMD-regulated set of genes that underly these developmental phenotypes (Arciga-Reyes et al., 2006). The notable exceptions to the functional diversity between organisms of candidate NMD-regulated pathways are genes involved in genome surveillance in general or telomere maintenance in particular (Rehwinkel et al., 2006). In yeast, a whole cluster of genes with functions in telomere maintenance, premRNA splicing, peroxisomal function, and DNA repair were upregulated in strains with deletions or mutations of NMD factors (He et al., 2003; Guan et al., 2006). The coordinate upregulation of genes participating in telomere maintenance by NMD inactivation was also observed in an earlier study (Lelivelt and Culbertson, 1999) and has since sparked interesting follow-up investigations. The yeast NMD pathway or components thereof was found to accelerate the rate of senescence promoted by loss of telomerase or erosion of telomeres by altering the stochiometry of telomere cap components (Dahlseid et al., 2003; Enomoto et al., 2004; Lew et al., 1998). At least one likely primary target of NMD is the mRNA of Stn1p, an essential protein involved in chromosome end protection. The observation that 35.9% of all ORFs encoded in the telomere region were upregulated in nmdD strains (Guan et al., 2006; He et al., 2003) further illustrates that NMD may preferentially (albeit indirectly) control the genes near telomere ends. These genes are usually silenced and may be derepressed when the protection of chromosome ends is disturbed by the loss of NMD. This enlightening example demonstrates how NMD can interfere with whole pathways by regulating the mRNA expression of one or few primary targets thereby influencing expression or function of a whole group of downstream secondary or higher order effectors. Among the yeast genes that are involved in telomere maintenance and are upregulated by loss of NMD function is Est1p that is orthologous to the NMD factors SMG5, SMG6, and SMG7 (also known as human EST1B, EST1A, and EST1C, respectively) in mammalia (Reichenbach et al., 2003; Snow et al., 2003). SMG5 transcript expression is upregulated on disruption of the NMD pathways in mammalia and fruitflies (Mendell et al., 2004; Rehwinkel et al., 2005). In addition, ATM/Tel1, which plays an eminent

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role in DNA repair and telomere maintenance, is regulated by NMD in both fruitfly and yeast (Rehwinkel et al., 2005). In mammalia, ATM together with SMG1 coordinately phosphorylates UPF1 (Brumbaugh et al., 2004). Although it is not yet clear, if this phosphorylation event is related to NMD, it would be interesting to know if ATM expression in mammalian cells is regulated by NMD as well. Intriguingly, a recent publication that identified C-terminal alternative splice variants of AUF1/HNRNPD as natural NMD targets unveiled another possibility as to how NMD could play a part in telomere maintenance (and a plethora of other pathways) in mammalia and, importantly, demonstrated that there are more NMD-regulated genes than identified so far by genome profiling (Banihashemi et al., 2006). Besides their role in ARE-mediated decay of shortlived mRNAs in the cell cycle, apoptosis, and signaling, AUF protein isoforms are involved in telomere maintenance through interaction with single-stranded telomere repeats. These proteins have been suggested to protect the telomere 30 overhang and to interact with telomerase in vitro (Eversole and Maizels, 2000; Enokizono et al., 2005). Four AUF1 isoforms resulting from selective inclusion of exons 2 and 7 can be alternatively spliced within an ultraconserved region of the 30 UTR between exons 8 and 10, potentially creating transcripts with five distinct C-terminal ends, four of which have been identified in K562 cells. Since the physiological termination codon resides in exon 8, two of these alternative splice events create transcript variants with an exon–exon junction > 50 nt downstream of this stop codon and therefore render them putative NMD targets. Both UPF1 and UPF2 knockdowns induced their upregulation and thus validated their NMD sensitivity. Moreover, they are differentially expressed during mouse embryogenesis. Regulation of AUF expression by NMD would potentially entail an avalanche of direct and indirect consequences for the expression of AUF targets in a variety of biochemical pathways, including telomere maintenance. The fact that in all organisms groups of genes with functions in genome maintenance and stress response are directly or indirectly modulated by NMD is complemented by recent results that point to additional functions of some NMD effectors in these very functional areas (see below). Taken together, these results indicate that NMD has the potential to directly and indirectly influence many biochemical pathways. The example of AUF1 highlights the potential of NMD in development and exemplifies the complexity with which researchers will be challenged if they set out to unravel the role of NMD-mediated pathway regulation. At this point, a central question surfaces: If NMD can serve as a tool to fine-tune the expression of its primary targets with possibly vast consequences for downstream effectors, then NMD itself must be a highly regulated process, something that clearly goes beyond its vacuum cleaner tasks. If so, what then are the “upstream regulators” of NMD itself?

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IV. DISOBEDIENT NMD TARGETS According to current mechanistic understanding in mammalia, PTCs that reside >50 nt 50 to the last exon–exon junction should elicit NMD. Consistent with and obedient to this rule, mRNAs transcribed from intronless genes and transcripts with PTCs that reside beyond this border are NMD resistant (Brocke et al., 2002; Maquat and Li, 2001; Neu-Yilik et al., 2001). However, the picture is more complicated than these results imply. The sensitivity of transcripts to NMD varies widely. As previously mentioned, most PTC-containing NMD-sensitive transcripts that obey the 50 nt-rule are reduced in expression level to 10–40% of wild type. Exceptions are the immunoglobulin (Ig) and TCR transcripts where NMD is much more efficient and degrades PTC-containing mRNAs to less than 10% of wild-type levels. PTCs in Ig and TCR mRNAs arise frequently from unproductive gene segment rearrangements so that T- and B-cell precursors may carry a heavy burden of faulty transcripts, which may be a reason for the evolution of a more efficient mechanism. NMD of Ig and TCR mRNAs is also special in that it does not abide by the 50 nt rule; PTCs that are as close as 8 nt to an exon junction can still elicit efficient NMD (Buhler et al., 2004; Gudikote and Wilkinson, 2006; Li and Wilkinson, 1998; Wang et al., 2002a). Additionally, the only current example of EJC-independent and 30 UTR-dependent NMD of a bona fide mammalian transcript has been demonstrated for an immunoglobulin gene (Buhler et al., 2006). Some transcripts appear to undergo NMD despite having a PTC in the last exon (Chan et al., 1998). In contrast, other expected NMD substrates have been reported to be NMD insensitive, including pathological transcripts (Asselta et al., 2001; Danckwardt et al., 2002; Inacio et al., 2004; Romao et al., 2000; Silva et al., 2006), normal splice variants (Bamber et al., 1999; Mango, 2001), and uORF-containing transcripts (see above). Phospholipid hydroperoxide GPx mRNA that encodes a selenoprotein is a bona fide NMD substrate in cell culture under conditions of selenium deprivation but appears to be masked from NMD in rat tissues (Sun et al., 2000). A possible mechanism that protects transcripts from NMD has been documented for a PTC-containing form of ApoB where a protein complex conceals the PTC from NMD (Chester et al., 2003) and thus enables the production of the truncated apoB48 protein isoform. This implies that not only the PTC-carrying transcripts are translated but also the PTC is used as a productive termination codon in order to generate apoB48. However, how termination at the PTC can occur without stripping off the protecting protein complex, and thereby allowing the communication between the termination site and downstream EJCs that is generally believed to be required for mammalian NMD is unclear.

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Although a single peptide bond formation is sufficient for NMD to occur and therefore a nonsense codon at position þ1 with respect to the initiator AUG can trigger NMD (Lew et al., 1998), many independent observations collectively hint at a low NMD sensitivity of transcripts that bear PTCs in the first exon or close to their 50 end (Asselta et al., 2001; Buzina and Shulman, 1999; Denecke et al., 2004; Harries et al., 2005; Inacio et al., 2004; Perrin-Vidoz et al., 2002; Romao et al., 2000; Silva et al., 2006). In some cases, this results from reinitiation of translation 30 to the PTC (Buisson et al., 2006; Buzina and Shulman, 1999; Denecke et al., 2004; Lew et al., 1998; Paulsen et al., 2006; Perrin-Vidoz et al., 2002) but in others, the mechanism is unknown but appears to involve proximity of the PTC to the initiator ATG (Inacio et al., 2004; Romao et al., 2000; Silva et al., 2006). In addition to this “first-exon phenomenon,” the extent to which PTCs at different positions within the same transcript trigger NMD can vary substantially (Romao et al., 2000; Ware et al., 2006). Besides these exceptions, there appear to be intertissue (Bateman et al., 2003) and interindividual (Kerr et al., 2001; Linde et al., 2007; Resta et al., 2006) variations in NMD efficiency. At present, it is mostly unknown which factors may influence NMD efficiency, yet this is clearly of cardinal interest in order to understand both the regulation of physiological NMD targets and the often obscure genotype–phenotype relationships of NMD-related diseases. It is possible that translation of residual PTC-containing mRNA can potentially lead to functionally important expression of truncated protein because (1) NMD fails to degrade some eligible transcripts, (2) NMD appears to operate with variable efficiency, and (3) NMD does not completely degrade all PTC-containing transcripts, even for NMD-competent mRNAs. Therefore, it is important to appreciate that PTC-containing mRNAs can neither a priori be assumed to result in the synthesis of considerable amounts of truncated proteins nor can they a priori be assumed to be degraded by NMD. Thus, the functional consequences of a PTC mutation must be established by experiment. In this context, a quantitative method of mRNA analysis (i.e., Northern blotting, RNAse protection analysis, or quantitative PCR) is required for determining the extent of transcript downregulation. Currently, reducing UPF1 expression by specific siRNA treatment is the best available functional assay to assess the NMD sensitivity of a PTC-containing transcript, although the recently discovered alternative functions of UPF1 must be considered. Pleiotropic inhibitors of translation (i.e., cycloheximide) may also be used, although the effects are less specific. To appraise whether significant translation of truncated protein occurs, the presence and degree of protein expression should be established. Furthermore, given that in all transcripts NMD-sensitive and-resistant PTC mutations most likely occur, a transcript map, as exemplified for -globin in Fig. 4.9, could be helpful to decipher the position-dependent influence of PTCs on disease phenotypes.

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Figure 4.9. “NMD map” of a transcript exemplified by the NMD-competent and -incompetent regions of the -globin mRNA. PTCs close to the AUG are not recognized by the NMD machinery. Furthermore, PTCs in the last exon and less than 50–55 nucleotides (nt) 50 to the last exon junction are usually resistant to NMD. These position-dependent effects of PTC mutations are representative for many other genes. However, in larger genes, the NMD-competent region is likely to be much more extended.

V. GOOD COP, BAD COP: MEDICAL IMPORTANCE OF NMD Genetic disorders are commonly caused by nonsense or frameshift mutations that introduce PTCs, and NMD helps to avoid the production of large amounts of C-terminally truncated peptides. The medical importance of NMD is well documented in -thalassemia, which exemplifies the phenotypic impact of the polar effect of PTC mutations at different positions within the same gene (Holbrook et al., 2004 and references therein). If PTC mutations are located at positions that activate NMD, the common recessive mode of inheritance with asymptomatic heterozyguous carriers results. In contrast, PTCs at positions within the last exon do not activate NMD and yield a stable mRNA that is available to direct the synthesis of truncated polypeptides. These aberrant translation products act in a dominant negative fashion, resulting in a symptomatic form of -thalassemia in heterozygotes and a dominant mode of inheritance (Hall and Thein, 1994; Thein et al., 1990). Thus, NMD protects heterozygote carriers of nonsense mutations in the NMD-competent area of the -globin gene against the production of faulty proteins. The situation is, however, complicated by the recent discovery that most PTCs in the first exon of the -globin gene do not abide by the 50 nt rule, in that they do not elicit NMD although they reside at an expected NMD-competent position (Romao et al., 2000). These PTCs do not induce a symptomatic form of -thalassemia, most likely due to degradation of the small peptide that may be produced from the small ORFs generated by first exon PTCs. The complex pattern of NMD responsiveness of -globin PTCs is paradigmatic for the multifaceted genotype–phenotype relationships that can arise from nonsense mutations. Nonsense mutations in the NMD-active area of a gene are frequently associated with a recessive mode of inheritance whereas

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PTCs in the NMD-resistant area of a gene are frequently associated with a more severe and dominantly inherited phenotype in heterozygous carriers most likely due to dominant negative activities of the truncated polypeptides produced from such a defective mRNA. Other examples besides -thalassemia for this type of disease-modulating influence and the protective impact of NMD on heterozygous carriers of nonsense mutations in the NMD-competent area of an affected gene are susceptibility to mycobacterial infections, brachydactyly type B, von Willebrand disease, factor X deficiency, and retinal degeneration and others (Holbrook et al., 2004; Khajavi et al., 2006 and references therein). Even when disease results from NMD-induced haploinsufficiency, this phenotype may be milder than (but also can be more severe than) and different from that caused by a truncated protein. This is exemplified by a recently investigated form of abnormal neural development, where NMD-competent mutations of the SOX10 gene led to a haploinsufficiency phenotype, whereas NMD-resistant mutations resulted in a more complex condition with additional features (Inoue et al., 2004). NMD may have a similar protective role in some acquired genetic diseases (Holbrook et al., 2004). This is supported by experiments with truncated versions of the tumor suppressor proteins BRCA1, TP53, or WT1 that were expressed from intronless cDNAs in cell lines or animal models. The dominant negative effects of these aberrant proteins included elevated chemoresistance, decreased apoptosis, enhanced carcinogenicity, and impaired functionality of the truncated proteins (Cardinali et al., 1997; Fan et al., 2001; Sylvain et al., 2002). NMD has been shown to limit the expression of transcripts with truncation mutations and would thus be expected to protect the cell from effects of aberrant tumor suppressor proteins that would otherwise promote tumor development. TP53 and WT1 exemplify another NMD-dependent mechanism to maintain homeostasis of gene expression. In these cases, only one of several alternative splice variants contains a PTC and the proportionality of functionally differing proteins resulting from alternative splicing is disturbed by either reducing the amount of the transcript variant with the PTC or allowing the production of a truncated protein (Cardinali et al., 1997; Englert et al., 1995; Reddy et al., 1995). The involvement of NMD in such complex systems is hard to tackle, although the pathological consequences may turn out to be very frequent. There is increasing evidence that a considerable portion of human pre-mRNAs (if not most) are alternatively spliced. Moreover, whole groups of alternatively spliced genes are dysregulated or defective in human diseases, such as members of the TP53, TP63, and TP73 families, apoptotic factors (Schwerk and SchulzeOsthoff, 2005), proteins involved in signaling cascades or in regulation of the cell cycle (Shin and Manley, 2004), and many others (Srebrow and Kornblihtt, 2006). In all of these cases, abnormalities of NMD are likely to disturb a finetuned balance of gene products.

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While in many instances NMD has a beneficial effect on the clinical outcome of nonsense mutations, in others it appears to be rather detrimental in that it eliminates mRNAs that would otherwise support the synthesis of partially or fully functional proteins. In these cases, NMD induces the clinical picture of protein deficiency. Such a genotype–phenotype relationship has been reported for cystic fibrosis, Duchenne muscular dystrophie, Hurler syndrome, and X-linked nephrogenic diabetes insipidus reviewed by Holbrook et al. (2004). In these instances, the nonsense-mutated mRNAs are the substrate for therapeutic strategies that promote translational readthrough at stop codons thus generating missense-mutated but functionally active proteins. Aminoglycoside antibiotics have been tested in this context in the genetic disorders mentioned above. Aminoglycosides bind to the decoding center of the ribosome and decrease the accuracy requirements for codon–anticodon pairing (Brogna, 1999). Recognition of stop codons is suppressed and, instead of chain termination, an amino acid is incorporated into the polypeptide chain. Aminoglycosides are highly active against bacterial ribosomes and the sensitivity of eukaryotic ribosomes to some aminoglycosides, such as gentamicin and G-418 has been viewed as an unwanted side effect associated with these antibacterial drugs. Yet, this “side” effect, in principle, permits their use for the treatment of patients with disease-causing nonsense mutations because in the presence of such aminoglycosides, PTC-mutated transcripts are not recognized by the NMD machinery and full-length albeit missense proteins are synthesized. Studies in tissue-cultured cells as well as in mouse models showed that aminoglycosides can promote readthrough of disease-causing PTCs and partially restore the expression and/or the function of these proteins (Arakawa et al., 2003; Barton-Davis et al., 1999; Bedwell et al., 1997; Du et al., 2002; Howard et al., 1996, 2004; Lai et al., 2004; Sleat et al., 2001; Wolstencroft et al., 2005; Zsembery et al., 2002). Moreover, clinical trials in patients with Duchenne muscular dystrophy (DMD) (Politano et al., 2003; Wagner et al., 2001), Becker muscular dystrophy (Wagner et al., 2001), and cystic fibrosis (CF) (Clancy et al., 2001; Wilschanski et al., 2003) showed that aminoglycosides can promote in vivo readthrough of nonsense mutations and can lead to the expression of full-length proteins and/or the correction of protein function. However, this effect appears to be variable and some studies did not demonstrate expression of full-length protein (Bidou et al., 2004; Clancy et al., 2001; Howard et al., 2004; Politano et al., 2003; Wilschanski et al., 2003). Similar to gentamicin, PTC124, a 1,2,4-oxidiazole compound, which is in development by PTC Therapeutics, Inc., can promote readthrough of PTCs. In CF and DMD animal models, it has been shown to effectively restore the production of full-length protein. PTC124 is currently being evaluated in phase II clinical trials with cystic fibrosis and DMD patients. The drug can be orally

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administered and in phase I trials its immediate side effects appear to be rare and mild (Ainsworth, 2005; Hamed, 2006). If the trials underway prove clinical benefit, PTC124 could also be tested with other NMD-related diseases. Another approach to interfere with harmful consequences of PTC mutations are repair strategies that aim at the elimination of the PTC-carrying portion of a mutated transcript or its exchange for a “healthy” nucleotide stretch. One such application is the use of antisense oligoribonucleotides to redirect splicing, thereby avoiding the production of PTCs in the first place. This strategy employs antisense 20 -O-methylribonucleotides (2OMeAO) that hybridize to splice sites or branch point junctions of aberrantly spliced pre-mRNA, thereby restoring normal splicing in a significant fraction of molecules (Cartegni and Krainer, 2003; Dominski and Kole, 1993; Harding et al., 2007; Mann et al., 2001; McClorey et al., 2006; Wilton and Fletcher, 2006a,b). Treatment with antisense oligos and their delivery has been assessed in animals and tissue cultures. However, a systemic delivery method needs to be developed, and as with all forms of gene therapy, the issues of transfection efficiency, potential immune responses, and side effects must be addressed. A further potential approach—although currently very far from realization—may be to modulate NMD itself, rather than modulating recognition of PTCs. Selective targeting of the central NMD protein UPF1 using RNA interference has been shown to be useful in disrupting NMD in cell culture, and might be a starting point for development of therapeutics. In addition, some biological evidence exists to suggest that individuals with identical genetic mutations may exhibit different phenotypic severities as a result of variability in NMD efficiency (Kerr et al., 2001). Although no upstream factors acting on NMD have been discovered yet, identification of such regulatory effectors could permit development of therapies to fine-tune the NMD mechanism, potentially allowing more targeted interventions in patients with PTC-related disease (Holbrook et al., 2004). Nothing is known about the clinical consequences of defective NMD factors or whether they naturally occur in viable organisms other than yeast. Since NMD controls the expression level not only of erroneous but also of physiological transcripts and is even supposed to regulate whole pathways (see above), a disease phenotype resulting from a defect or from a loss of a central NMD factor can be expected to be severe and complex, similar to those induced by mutations in constitutive or alternative splice factors (Cartegni and Krainer, 2002; Faustino and Cooper, 2003; Neu-Yilik and Kulozik, 2004). In conclusion, NMD will probably remain difficult to target as a disease modulator. Attacking NMD systemically in order to enable the production of a PTC-mutated, albeit partially functional protein, may have serious long-term side effects. On the other hand, many conventional and highly successful therapeutic strategies, such

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as those employed to treat cancer, cause serious side effects that have to be balanced against the efficacy of these drugs. Such a balance will likely have to be found for therapeutic strategies involving NMD.

VI. MOONLIGHTING NMD PROTEINS: MOONLIGHTING PATHWAY? NMD factors either alone or in teams entertain a multitude of contacts to other cellular pathways and functions. These range from an as yet poorly understood role of Upf1, Smg-5, and Smg-6 in RNAi of C. elegans (Domeier et al., 2000) and of Upf1 in RNAi in plants (Arciga-Reyes et al., 2006), over roles of various NMD factors in translation, UPF1 functions in nonsense-associated altered splicing (NAS) (Mendell et al., 2002; Zhang and Krainer, 2006) and in other mRNA turnover pathways, and tasks of SMG5 and SMG6 in telomere maintenance to a multitude of functions in genome stability (Table 4.2). At present it is unknown if these additional tasks are always or usually independent from NMD or if they point to one (or several) functional network(s) that utilizes common effectors as molecular switches. The latter possibility finds some support in the multifaceted tangencies between NMD and/or single NMD factors on the one hand and the mechanisms that protect the cell from genotoxic or oxidative damage on the other.

A. NMD factors and translation UPF1 has at least two roles in translation that could be unrelated to NMD. UPF1 may have a function in translational termination (see above) and it is unknown if this function is restricted to aberrant termination. The same is true in yeast for Upf2p and Upf3p, which in this organism are also required for efficient termination (Czaplinski et al., 1998; Maderazo et al., 2003; Wang et al., 2001). Furthermore, UPF1 as well as several other NMD effectors (UPF2, UPF3A, UPF3B, RNPS1, Y14, and MAGOH) not only cooperate in NMD when associated with an exon junction downstream of a termination codon but curiously also promote polysome association and translation when associated with an exon junction within the ORF (Kunz et al., 2006; Nott et al., 2004). Originally, it was found that pre-mRNA splicing enhances polysome association and translational yield of mRNAs (Le Hir et al., 2003; Matsumoto et al., 1998; Nott et al., 2003) and subsequently this effect could be ascribed to the EJC (Nott et al., 2004; Wiegand et al., 2003). Tethering of individual EJC and UPF proteins within the ORF of intronless reporter transcripts enhances both polysome association and protein expression. All these proteins are presumed to be removed during the first round of translation, so that the question arises as to how they could enhance

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translation in subsequent rounds. Possibly, the mRNP characterized by the presence of EJCs is needed for successful initial recruitment of ribosomes or initiation factors or localization of the mRNA to a translation-promoting subcellular environment (Nott et al., 2004). This is an example of moonlighting of possibly the whole “staff” of a pathway in two functionally related but different tasks. In this context, it is interesting that the NMD functions and the translation stimulating functions of UPF3A and UPF3B proteins require different protein regions and interacting factors so that they are functionally separable from each other. While the interaction of UPF3 proteins with Y14/MAGOH/ eIF4A3/BTZ is essential to trigger NMD, their translation stimulatory activity is independent from these EJC proteins (Kunz et al., 2006). This observation is surprising since tethering of Y14 and MAGOH stimulates translation as well (Nott et al., 2004) and indicates that these second functions are dependent on other protein–protein interactions than those that are important for NMD (Table 4.3).

B. Other mRNA turnover pathways In yeast, the NMD factors Upf1p, Upf2p, and Upf3p are not essential for cell viability. In contrast, the deletion of Upf1 is lethal for the mouse embryo (Medghalchi et al., 2001), and siRNA-mediated depletion of UPF1 in HeLa cells severely reduces the survival rate of these cells. This effect is enhanced by additional stress like concomitant transfection with reporter plasmids. These observations led to the hypothesis that NMD is of more vital importance in higher eukaryotes than in yeast. Yet, more recent results indicate that the influence on cell viability might be associated with functions of UPF1 that are additional or unrelated to its role in NMD. UPF1 ushers not only PTC-mutated mRNAs or physiological NMD substrates to their final destiny but also serves in other mRNA turnover pathways to identify their targets. In each of these functions, it acts independently from other NMD factors, such as UPF2 or UPF3, and does not need other requirements that are typical for mammalian NMD such as existence of at least one downstream exon junction. In a process termed SMD, the recruitment of UPF1 to the 30 UTR of specific transcripts by Staufen 1 triggers their translationdependent degradation without any known involvement of other NMD effectors (Kim et al., 2005). The regulated degradation of replication-dependent histone mRNAs is also similar to NMD in several respects: it requires both translation and a cis-acting element on the mRNA—the stem loop structure at the 30 end of histone mRNAs—at a defined position relative to the termination codon that binds the stem loop-binding protein (SLBP). Furthermore, it requires UPF1 but not the other NMD effectors (Kaygun and Marzluff, 2005a). Thus, the unifying and somewhat intriguing feature of all three pathways is that specific classes of

Table 4.3. Functions of NMD Factors in NMD and Alternative Pathways Biological phenomenon

Species

mRNA features

NMD factors involved UPF1, UPF2, UPF3B, EJC proteins in at least two subsets; SMG1, SMG5, SMG6, SMG7 UPF1

NMD

H.s.

A PTC and at least one exon junction >50 nt downstream

SMD

H.s.

Replication-dependent histone mRNA decay

H.s.

Translation

H.s.

A termination codon and a Staufen 1-binding site in the 30 UTR A termination codon and a conserved stem loop in the 30 UTR Exon junctions within the ORF

Telomere maintenance

H.s.

Does not apply

Genome stability

H.s.

Does not apply

SMG1

H.s.

Does not apply

UPF1

PTC in pre-mRNA

Smg-2, Smg-5, Smg-6 Upf1 UPF1

RNAi NAS

C.e. A. H.s.

Role of NMD factors involved

Other proteins involved

See text

Unknown but expected

Recruitment of UPF1 by Staufen 1 elicits decay

Staufen 1

UPF1

Recruitment of UPF1 by the SLBP elicits decay

SLBP, ATR

UPF1, UPF2, UPF3B, RNPS1, Y14, MAGOH others? SMG6/EST1B, (SMG5/ EST1A, SMG7/EST1C)

Translation stimulation

Unknown

Protection of telomere ends, regulation of telomere length UPF1 and P53-phosphorylation, G2/M-phase progression, protection against DNA damage and apoptosis DNA replication S-phase progression Persistence of RNAi RNAi amplification? Unknown but involved in alternative splicing

Unknown

ATM

ATR, DNA polymerase ? Unknown Unknown

Abbreviations: NMD, nonsense-mediated mRNA decay; SMD, Staufen 1-mediated mRNA decay; PTC, premature termination codon; RNAi, RNA interference; NAS, nonsense-associated altered splicing; SLBP, stem loop-binding protein); ORF, open reading frame; UTR, untranslated region; H.s., Homo sapiens; C.e., Caenorhabditis elegans; A., Arabidopsis.

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transcripts, all of which first have to be translated and to terminate translation, are marked for decay by a 30 UTR RNP domain which contains or interacts with UPF1. With the future discovery of the involvement of UPF1 in even more mRNA degradation pathways, it may turn out that this protein serves to restrict the life span of faulty as well as error-free transcripts—a final marker that labels the transcript for decay. So far, all UPF1-mediated mRNA turnover processes discovered require the recruitment of UPF1 to the 30 UTR of the respective transcripts and the formation of 30 UTR mRNP domains that contain UPF1 and other factors that specify the degradation pathway. It would be interesting to know if UPF1 participates in these (possibly specific) termination events and if it is assisted by other proteins found in NMD-related termination complexes (see above) and if SMD and regulated histone mRNA decay require similar phosphorylation/dephosphorylation cycles of UPF1 mediated by SMG1 and SMG5–7.

C. NMD factors and genome stability Interestingly, the histone mRNA turnover mechanism stands at the intersection of two other complex pathways to which UPF1 has been connected more recently and which, at first sight, also appear to be unrelated to its role in NMD: genotoxic stress and S-phase progression. SMG1—among other approaches—isolated in a search for new PIK family members besides ATM, ATR, and DNA-dependent protein kinase. These proteins function in genome surveillance, and SMG1 was found to be a genotoxic stress-activated kinase as well with some functional overlap with ATM (Brumbaugh et al., 2004). Both SMG1 and ATM phosphorylate S/T-Q motifs in p53 and UPF1 and depletion of SMG1 leads to spontaneous DNA damage and increased sensitivity to ionizing irradiation. The phosphorylation state of UPF1 is modulated by genotoxic stress and ATM, in addition to SMG1, contributes to the phosphorylation of UPF1. Depletion of either PIK-like kinase leads to increased UPF1 phosphorylation by the remaining family member and only the elimination of both severely impairs (yet cannot completely inhibit) phosphorylation of UPF1. Interestingly, under basal cell culture conditions, ATM depletion differs from SMG1 depletion in that it has no influence on NMD efficiency. This leads to the conclusion that phosphorylation of UPF1 by ATM serves an NMD-unrelated function. However, the simultaneous depletion of SMG1 and

-irradiation of Calu-6 cells that endogenously express nonsense-mutated TP53 transcripts unveiled an inhibitory effect of genotoxic stress on NMD that was mediated by ATM (Brumbaugh et al., 2004). Thus, it can be envisioned that under conditions of genotoxic stress phosphorylation of UPF1 by ATM competes with SMG1-mediated phosphorylation to redirect UPF1 from its functions in

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NMD to other tasks. In that context, it is interesting that the depletion of both SMG1 and UPF1 triggers a genotoxic stress response and both proteins are therefore required for the maintenance of genome stability in mammalian cells. In addition, phosphorylation of UPF1 by the third PIKK family member, ATR, may contribute to diversify its functions even more in at least two ways. ATR-mediated phosphorylation of UPF1 is necessary for replicationdependent histone mRNA degradation after S-phase (Kaygun and Marzluff, 2005a). Furthermore, ATR-mediated UPF1 hyperphosphorylation also promotes the association of UPF1 with chromatin in S-phase, as well as S-phase progression (Azzalin and Lingner, 2006b). UPF1-depleted cells can initiate but not complete DNA replication, which may indicate that chromatin-bound UPF1 uses its helicase activity to unwind the DNA in front of the replication fork (Azzalin and Lingner, 2006a). This view is supported by the fact that UPF1 can physically interact with DNA polymerase  (Azzalin and Lingner, 2006b; Carastro et al., 2002). It seems that these effects are not related to NMD because UPF1–UPF2 complexes do not contain DNA polymerase  and the depletion of UPF2 influences neither cell cycle progression nor genome stability, although one has to keep in mind that NMD of some transcripts is UPF2-independent (Gehring et al., 2005). While SMG1 depletion elevates the level of chromatinbound UPF1 in -irradiated cells, the depletion of ATR considerably reduces loading of UPF1 onto chromatin (Azzalin and Lingner, 2006b). Because depletion of the other two PIKK family members that can phosphorylate UPF1, SMG1, and ATM did not negatively interfere with chromatin loading of UPF1 and because ATR depletion does not interfere detectably with NMD (of two test substrates), the previously identified roles of UPF1 in RNA and genome surveillance are separable and likely independent from each other. This is supported by the fact that UPF1 is promiscuous in the choice of its partners with which it can form complexes that might specify these respective functions: NMD, SMD, regulated decay of histone mRNAs, and potentially several functions in cell cycle progression and genome surveillance. In this context, it is interesting that, as outlined above, even within NMD there appears to exist a certain variability of complexes that finally recruit or interact with UPF1. However, it is possible that the different functions are intertwined at a more subtle level as was revealed by the ATM-dependent negative influence of -irradiation on NMD, which could only be discerned after simultaneous elimination of SMG1 and ATM. It is appealing to hypothesize that both transcriptome and genome surveillance could be modulated in concert by differential phosphorylation of UPF1. As has been discussed earlier, NMD may modulate the expression of specific classes of normal transcripts and that the protein products of these mRNAs in turn regulate a plethora of downstream effectors. This requires NMD to be a regulated process in itself, yet so far no distinct stimuli that could enhance or blunt its efficiency have been identified. However, the

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discovery that UPF1 is phosphorylated by at least three PIKK family members inspires testable hypotheses. For example, the siphoning of UPF1 to an NMDunrelated function by alternative or competitive phosphorylation under yet-tobe-defined cellular conditions could stabilize NMD-sensitive physiological transcripts or alternative splice variants of proteins, which then in turn could have a function in the genome surveillance or cell cycle. The findings that (1) -irradiation increased the impairment of NMD induced by SMG1 depletion (Brumbaugh et al., 2004) and that (2) SMG1 depletion increased loading of UPF1 onto chromatin (Azzalin and Lingner, 2006b) are consistent with such a model (Fig. 4.10). The exclusive, overlapping, or competitive (and maybe cell compartment- and/ or cell cycle-specific) phosphorylation of UPF1 by various PIKK family members and possibly other kinases could, on the one hand, promote the interaction of UPF1 with transcript-specific mRNP domains leading to the degradation of the UPF1-labeled mRNA, and on the other hand, serve to channel UPF1 into its various functions in transcriptome and genome surveillance. SMG1, like UPF1, appears to have a role in genome maintenance that may or not be related to its functions in NMD. However, the effects of the elimination of either protein differ in that UPF1 depletion causes cells to arrest in early S-phase whereas SMG1 depletion results in the accumulation of cells in the G2/M phase. Interestingly, depletion of UPF1, UPF2, or UPF3 in fruitfly also leads to G2/M arrest (Rehwinkel et al., 2005). SMG1, in contrast to the other UPF1 phosphorylating PIKKs, appears to be a predominantly cytoplasmic protein, although a minor subpopulation has also been detected in the nucleus and/ or perinuclear compartment (Brumbaugh et al., 2004; Ohnishi et al., 2003). Within this cytoplasmic SMG1 population, a significant subfraction is found at the outer surface of mitochondria (Abraham, 2004). This inspired the hypothesis that SMG1 could be involved in cellular sensitivity to apoptosis. Consistently, SMG1 depletion from certain malignant cell lines (but not from a noncancerous human mammary epithelial cell line) sensitizes these cells to TNF- and TRAIL-induced apoptosis in a manner that is apparently unrelated to NMD. These preliminary data require a more detailed investigation but are intriguing especially with respect to the possibility of therapeutic intervention they may offer in the future. Similar to UPF1 and SMG1, the NMD effectors SMG5, SMG6, and SMG7 have NMD-independent functions in genome surveillance. SMG5, SMG6, and SMG7 are identical to hEST1B, hEST1A, and hEST1C, respectively. These proteins have been identified as orthologues of the yeast Est1 protein (Est1p) that recruits telomerase to the ends of chromosomes thereby promoting telomere elongation. The function of the SMG5–7/Est1A–C proteins in telomere maintenance and NMD, respectively, may be true moonlighting and may thus not be connected to each other. The role of SMG5 and SMG6 in NMD may be directly

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Figure 4.10. UPF1 in genome and transcriptome surveillance. (A) UPF1 is involved both in genome and transcriptome surveillance and is phosphorylated by the members of the PIK-like kinase family. At least SMG1 is found in both the nucleus and the cytoplasm and may function as a UPF1 kinase in both genome and transcriptome surveillance. It is unknown if the ATM, ATR, and SMG1 phosphorylate the same or distinct sites in UPF1 and if UPF functions triggered by these kinases are partially overlapping. (B) Functional consequences of UPF1 phosphorylation by PIK-like kinases.

connected to their PIN domains (see above) that distinguishes them from yeast Est1 but which they have in common with C. elegans SMG5 and SMG6. SMG6/ EST1A and SMG5/EST1B associate in immunoprecipitation experiments from

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HeLa cell extracts with telomerase activity. Overexpression of SMG6/EST1A induces telomere–telomere associations and subsequently triggers a rapid apoptotic response in HT1080 cells, and leads to progressive telomere shortening in HEK293 cells. These two results suggest functions of SMG6/EST1A in modulation of telomere structure and regulation of telomere length. Yet, the function of SMG5–7/Est1A-C in NMD complicates the analysis of their telomeric function since any of the observed effects could instead follow from the deregulation of endogenous NMD targets that are involved in telomere metabolism (Azzalin et al., 2006). Finally, NMD itself as a regulator of certain cohorts of physiological transcripts provides several links to genome surveillance (see above). Gene expression profiling of NMD-deficient yeast cells consistently demonstrated upregulation of several telomeric factors and the telomeres in these cells were unusually short (Dahlseid et al., 2003). In yeast, deletion of any of the three NMD effector genes upf1, upf2, or upf3 promoted this effect suggesting that it is most likely the NMD pathway as a whole that modulates the expression of genes involved in telomeric function. A similar effect could so far not be observed in UPF1-depleted human cells, but the picture would possibly change—as foreshadowed by the identification of AUF-splice variants as NMD targets (Banihashemi et al., 2006)—if profiling were performed with cells in defined situations such as specific stages of the cell cycle, telomeric stress, or replication (Abraham, 2004). In line with the competition hypothesis outlined in Fig. 4.10, telomere damage could trigger a stress response that channels UPF1 via phosphorylation to NMD-unrelated functions and thereby stabilizes transcripts whose products are involved in telomere maintenance. Alternatively, SMG5–7/Est1A–C could assist SMG1 in the phosphorylation/dephosphorylation cycle of targets other than UPF1, for example p53, thereby influencing telomeric functions. In this context, it is noteworthy that the sequence similarity between Est1p in yeast to SMG5–7 in C. elegans and Homo sapiens challenges the notion prevalent in the NMD field that SMG5–7 have no homologues in yeast (Azzalin et al., 2006). Other reports strengthen the notion that NMD plays a crucial role in the response to genotoxic insults. In fission yeast, Upf1p controls the expression of more than 100 genes that are transcriptionally induced in response to oxidative stress and deletion of either upf1 or upf2 sensitizes these cells against hypoxia (Rodriguez-Gabriel et al., 2006). Importantly, the influence on the abundance of several of these transcripts was only visible after induction of oxidative stress. In budding yeast, 35% of physiological protein-coding NMD targets fall into two functional groups: (1) transcripts that encode proteins with a role in the dynamics of plasma membrane and cell wall, and (2) transcripts that encode proteins involved in replication and maintenance of telomeres, chromatin structure, chromatin-mediated silencing, and postreplication events related to transmission of chromosomes during cell division (Guan et al., 2006). It is noteworthy

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that many NMD targets appear to be expressed below the threshold of detection on microarrays and may therefore escape the attention of researchers who are specifically interested in the role of NMD in the regulation of physiological targets or whole pathways (Taylor et al., 2005). Moreover, it is possible that NMD effects on endogenous and low abundance transcripts may only be visible under defined physiological circumstances. This is exemplified by the influence of ATM on NMD after -irradiation or the discovery of NMD-sensitive transcripts after oxidative insult in fission yeast. Therefore, it will be necessary to develop new and more sophisticated experimental approaches to uncover the important role of NMD as a whole, or single NMD effectors in these vital cellular functions.

VII. CONCLUSIONS Substantial progress has been made in the last decade to elucidate the mechanism of NMD, the factors involved, and their mode of action, as well as to identify pathological and physiological NMD targets. Moreover, the understanding of the multiple functions of NMD has been considerably deepened. However, as is customary in science, each step forward confronts us with new and surprising enigmas. There are several burning issues to tackle. (1) It is an unsolved and important question whether, as in yeast, termination at a PTC in mammalia differs from that at a normal termination codon. This is not only of academic interest but could provide therapeutical options for the treatment of those NMDrelated diseases where translation of the mutated protein is desirable. (2) Likewise, it has to be clarified if the pioneer round of translation, specified by the presence of the CBC, is a general and indispensible feature of mammalian NMD or if, alternatively, NMD can be triggered irrespective of the nature of the CBPs or even of the round of translation. (3) Related to this is the problem of the dynamic remodeling of mRNPs on their way from the site of transcription until their degradation. Of particular interest is the assembly of EJCs in general and the generation of structurally diverse EJCs that connect to the NMD machinery via different routes. (4) Another unresolved question is the exact sequence of events that leads from PTC recognition to the recognition of an EJC in the 30 UTR and from there to the degradation of the mutated transcript. (5) Of utmost importance, but still a field of research in its fledgling stages are the questions as to how NMD regulates the expression of physiological transcripts or whole pathways and how NMD itself is regulated. Here, thrilling new insights into NMD and the discovery of connections to other cellular functions can be expected. Moreover, studies of this kind are likely to enable the development of promising strategies for the treatment of PTC-related diseases.

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Acknowledgments The authors thank Jill Holbrook for critical reading of the manuscript and the members of the Kulozik laboratory for insightful and inspiring discussions.

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Index A Affymetrix chip technology, 54 Aminoglycoside antibiotics, 221 AMIRA software, 101 amnesiac (amn) gene, 111 Antennomechanosensory center (AMC), 91 Antiaphrodisiac 7-tricosene presence, 73–74 cis-vaccenyl acetate, 79 Aphrodisiac compound, 73 B -thalassemia and NMD, 219–220 C C309 transposon, D. melanogaster fruitless gene, 132–133 wing extensions, 107–110 C747 transposon, D. melanogaster, 107 Calcium/calmodulin kinase (CaMKII), D. melanogaster domain-negative influence, 115 neural manipulations, 117–118 Cap-binding complex (CBC). See Cap-binding proteins (CBPs) Cap-binding proteins (CBPs) and NMD mRNP remodeling, 198 selenoprotein-encoding mRNA, 199 Cardiovascular diseases (CVD), FHS biochemical markers, 47–48 cohorts and examination, 36–39 data collection, 39–40 demography, 36–37 developmental causes, 35–36 environmental factors, 55 ethical issues, 55 family inheritance patterns, 43–44 genetic association test, 51–52

genetic correlation, 46–47 genome-wide association study, 54 heritability, 44–46 linkage analysis, 49–50 molecular markers, 48–49 polymorphism, 52–53 risk factors, 40–42 CBPs. See Cap-binding proteins CC-broad mutation, 106 central complex (cex) mutant, 106 Chaining index (ChI) value, 130 Choline acetyltransferase (Cha) gene, 109 Cis-vaccenol (cVOH), 79 Cis-vaccenyl acetate (cVA) antiaphrodisiac activity, 79 and cVOH, 79–80 Clock mutation, 153–154 Copy number variants (CNVs), 6 Courtship conditioning assay CI values, 111 shock-odor test, 111–112 Courtship index (CI), 21 Courtship pathway, D.melanogaster, 121–122 Courtship song, D. melanogaster, 90 cycle mutation, 155–156 D Decay-inducing complex (DECID), 202–203 Disease-associated gene mapping genetic association test direct approach, 12–13 indirect approach, 13–15 haplotypes testing, 16–17 linkage analysis, 11 linkage disequilibrium, 15–16 single nucleotide polymorphism, 7–8 and tagSNPs, 15 doublesex (dsx) gene and ABG neurons, 149 female-like quality, 148 245

246 doublesex (dsx) gene (cont.) male courtship, 147 mutation, 102 pheromone quality, 148–149 sex-specific proteins, 147 Drosophila melanogaster, courtship and mating acoustic stimuli courtship song, 90 Johnston’s organ, 90–91 rejection sounds, 91–92 chemical pheromones aphrodisiac compounds, 73 cis-vaccenyl acetate (cVA), 79–80 functional mutants, 78 GAL4/UAS system, 80–82 interfly interactions, 84 maxillary palps and wild-type male, 77–78 olfactory pathways, 77 sensory-neuronal afferent, 74–77 suppressed male courtship, 83 UAS-traF, molecular construct, 85 and D. simulans, 86–87 fruitless gene C309 transposon, 132–133 and doublesex gene, 147–149 expression and FRUM antigenicity, 124–131 intermale courtship, 118 manipulation of gene and knock-ins at locus, 133–143 molecular genetics, 123–124 protein isoforms, 143–146 sex characteristic features, 118–122 sex-determination hierarchy, 122–123 transcription factors and gene target, 149–155 genetic manipulation courtship conditioning assay, 111–112 GAL4/UAS system, 115–118 hydroxyurea ablation, 113–115 mushroom bodies, 110 genetic variation fate mapping, 95 major male courtship foci, 96 receptivity center, 97 sex mosaics, 94, 96 gustatory study Gr68a gene, 87 male-specific forelegs, 87–88

Index structure and olfaction, 85 subesophageal ganglion and receptor neurons, 86 tarsi in male flies, 86 molecular-genetic disruptions C309 gal4 transgene, 109–110 enhancer trap expression, 104–105 intermale courtship and C309 enhancer, 107–108 male wing extension, 106–107 mushroom body control, 103–104 neural activity, 100–101 neural pathway, 106 olfactory pathway, 99 overlapping expression patterns, 101–102 RNAi transgene and fruitless gene, 99–100 sexual dimorphism, 102 peripheral nervous system inputs, 92–93 rhythmicity and reproduction fruitless gene, 157 locomotor cycles, 155 period gene, 159–160 takeout gene, 156 timeless gene, 158–159 sensory cues, female flies, 93 visual stimuli central complex, in CNS, 90 mutant males and blindness, 88–89 VPNs and photoreceptors, 89 D. simulans acoustic signals, 92 gustatory study, 86–87 DSXF transcription factor, 156 E Endophenotypes, 47 Environmental Genome Project, 7 ether-a-go-go (eag) gene, 100 Eukaryotic release factor (eRF), 202 Exonic SNPs, 4 Exon junction complex (EJC) 30 UTR termination, 206 mRNA degradation and splicing, 188–190 SURF complex, 202–204 transcription and translation, 201 UPF proteins, 194–195, 200

247

Index F False discovery rate (FDR), 20. See also Genetic association test False positive rate probability (FPRP), 20. See also Genetic association test Faux 30 UTR model mRNA decay, 205 spatial and molecular requirements, 207 UPF protein role, 206 Framingham Ethics Advisory Board, 55 Framingham Heart Study (FHS) cardiovascular diseases biochemical markers, 47–48 developmental causes, 35–36 environmental factors, 55 family inheritance patterns, 43–44 genetic association testing, 51–52 genetic correlation, 46–47 genome-wide association study, 54 heritability, 44–46 linkage analysis, 49–50 microsatellite markers, 50–51 molecular markers, 48–49 polymorphism, 52–53 risk factors, 40–42 cohorts and examination, 36–39 demography, 36–37 ethical issues, 55 phenotypic data, 39–40 Fruitless (fru) gene C309 transposon and courtship defect, 132 FRUM overlap, 133 and doublesex gene ABG neurons, 149 female-like quality, 148 male courtship, 147 pheromone quality, 148–149 sex-specific proteins, 147 expression and FRUM antigenicity genetic variation of locus, 130–131 immunoreactive neurons, 128 labeling of nucleic-acid, 126–127 mutants and effects, 128–130 nervous system staining, 124–125 sex mRNA detection, 125 gene manipulation and knock-ins fru-gal4 fusion transgene, 142 fruP1-gal4, 136–139 FRU protein, 134–135

male mushroom body, 141–142 male-specific protein, 143 olfactory-neuron function, 140–141 peripheral nervous system, 137 types of knock-ins, 135 yeast gal4 gene, 133–134 molecular genetics, 123–124 protein isoforms 5 HT cells, 145–146 fru
 mutation, 144–145 muscle of Lawrence, 143–144 rhythmicity and reproduction, 157 sex characteristic features allelic series creation, 120 courtship pathway, 121–122 isolation, 118 muscle of Lawrence, 122 sex-determination hierarchy, 122–123 transcription factors and gene target 5HT cell production, 150 BTB/Zn-F proteins, 149–150 gene targets, 151 neuropeptide F, 153–155 yellow gene, 151–153 FRU protein 5HT cell production, 150 BTB/Zn-F proteins, 149–150 gene targets, 151 isoforms 5 HT cells, 145–146 fru
 mutation, 144–145 muscle of Lawrence, 143–144 neuropeptide F brain neuropeptides, 154–155 clock neurons, 153 expression, 154 yellow gene male flies, 151 neural-specific expression, 153 protein form, 152 G GAL4 transposon (30Y), 113 GAL4/UAS system and Gr68a gene, 87 Or67dGAL4 gene, 82 Or67d gene, courtship capacity, 80–81 sequence fusing, 80 Gene-centric SNPs, 4

248 Gene mapping association testing cardiovascular diseases, 51–52 direct approach, 12–13 false positive findings and multiple tests, 19–20 indirect approach, 13–15 population stratification, 20–22 haplotype test, 16–17 linkage analysis cardiovascular diseases, 49–50 disease gene mapping, 11 linkage disequilibrium, 15–16 microsatellite markers, 50 tagSNPs, 15 Genetic association test direct approach, 12–13 false positive findings and multiple tests, 19–20 indirect approach, 13–15 Lewontin’s measure of LD, 51–52 population stratification, 20–22 Genetic correlation, cardiovascular disease, 46–47 Genetic linkage analysis cardiovascular diseases and FHS, 49–50 disease gene mapping, 11 Genetic manipulation, in D. melanogaster courtship conditioning assay, 111–112 GAL4/UAS system, 115–118 hydroxyurea ablation, 113–115 mushroom bodies, 110 Genome stability UPF and SMG proteins genotoxic stress, 226–227 s-phase progression, 227 transcriptome and genome surveillance, 227–231 Genome variation disease gene mapping association testing, 12–15 haplotype tasting, 16–17 linkage analysis, 11 linkage disequilibrium, 15–16 SNPs, 7–8 tagSNPs, 15 D. melanogaster, courtship and mating fate mapping, 95 major male courtship foci, 96 receptivity center, 97 sex mosaics, 94

Index genomic medicine, 22 screening of variants, 23 single-nucleotide polymorphism factors influencing, 3–4 in health and diseases, 4–5 mapping study, 7–8 tandem repeats and CNVs, 6–7 Genome-wide association studies (GWAS) advantages, 17 Affymetrix chip technology, 54 in complex diseases, 53–54 and SNPs, 17–19 Gentamicin, 221. See also Aminoglycoside antibiotics Gr68a gene cheB42a molecule, 88 gal4/UAS system, 87 Gustatory-receptor (Gr) genes, 86–87 Gustatory-receptor neurons (GRNs), 84 Gynandromorph approach. See Mosaic approach H Haplotypes, disease gene mapping, 16–17 HapMap project, 14 Heritability, in cardiovascular disease, 44–46 Human genome variation disease-associated gene mapping, 12–17 single-nucleotide polymorphism, 3–5 tandem repeats and CNVs, 6–7 Hydroxyurea (HU) ablation, in Drosophila antenna lobe damage, 114 dopamine manipulation, 113 male–female interactions, 113–114 J Johnston’s organ (JO), 90–91 L Lateral horn (LH), 77 Lateral protocerebrum (LPR), D. melanogaster enhancer traps, 117 as male courtship foci, 96 neural dissection, 99 Linkage disequilibrium (LD) disease gene mapping, 15–16 Lewontin’s measure, 52 Logarithm of odd (LOD) score, 49

249

Index M MARCM, mosaic clone marker, 126 MB gal4 enhancer traps, 107, 116 Median bundle, 100 Mosaic approach CNS-expression patterns, 94 gal4 transgenes, 95 major male courtship foci, 96 receptivity center, 97 sex mosaic, classes, 96 mRNP remodel process, 198 Muscle of Lawrence (MOL) fruitless gene, 122 FRU protein isoform, 143–144 Mushroom bodies (MBs), D. melanogaster ablated male flies, 114–115 courtship control, 103 defective mutants, 106 fru gene expression, 141–142 gene manipulation, 110 molecular-genetic disruptions, 109–110 N National Heart Lung and Blood Institute, 54 NCI Cancer Genome Anatomy Project, 7 Neuropeptide F (NPF) and FRU protein, 153–155 Nonsense-mediated mRNA decay (NMD) cap-binding proteins mRNP remodeling, 198 selenoprotein coding, 199 complex properties nonsense mutations, 187–188 transcription and nuclear events, 187 degradation process deadenylation, 207–210 decapping, 210 factor assembly mode, 210–211 UPF proteins role, 211–212 and exon junction complex core proteins, 199 termination codon and upf proteins, 200 transcription and translation, 201 faux 30 UTR termination Hrp1 protein, 205 spatial and molecular requirements, 207 UPF protein role, 206 and gene expression, 186 medical importance in acquired genetic diseases, 220

aminoglycoside antibiotics, 221–222 antisense oligoribonucleotides, 222 -thalassemia, 219–220 modulating recognition of PTCs, 222 protein deficiencies, 221 metabolic pathways, 215 mRNA turnover pathways, 224–226 physiological targets AUF1/HNRNPD proteins, 216 gene regulation and uORF, 214 transcription and translation, 213 upmodulated and downmodulated, 214–215 premature termination codon splicing, 188 transcription, 217–219 translation, 190 SMG proteins different organisms, 190–191 genome surveillance, 227–231 genotoxic stress, 226–227 phosphorylation cycle, 193–194 s-phase progression, 227 translation termination nonsense codons, 201 RNA complex and eRF, 202 SURF and DECID complex, 202–205 UPF proteins in different organisms, 190–191 domain organization, 192–193 exon junction, 194–195 genome surveillance, 227–231 human genome and upf3 genes, 196–197 phosphorylation cycle, 193–194 s-phase progression, 227 tethering assay, 192 in translation, 223–224 O Observational Study Monitoring Board (OSMB), 55 Olfactory pathway, D. melanogaster, 99 Olfactory-receptor gene, 74 olfC mutation, 78–79 20 -O-methylribonucleotides (2OMeAO), 222 Or67d gene, 80–81 P Parasbl mutation, 78 Pars intercerebralis (PI), 154 period (per) gene, 159–160

250

Index

ppk25 gene, 92 Premature termination codon (PTC) and NMD and gene expression, 186 splicing, 188 transcription apoB48 protein, 217 Ig and TCR tanscripts, 217 mutation and mRNA analysis, 218–219 translation, 190 prospero (pros) gene, 104–105 PTC124 drug, 221–222

T tagSNPs, 15 takeout (to) gene, 156 TAKEOUT (TO) polypeptide, 156–157 timeless (tim) gene, 158–159 Transcriptome nonsense-mediated mRNA decay, 214 UPF and SMG proteins, 227–231 transformer (tra) gene, 85, 123 Transgenic gynandromorphs, 94 Translational frameshift, 213 Tyrosine hydroxylase inhibitor (31Y), 113

Q Quantitative trait loci (QTLs), 49 S Sex-determination hierarchy (SDH), in Drosophila doublesex gene, 147 fruitless gene, 122–123 shibireTS (shiTS) mutation, 100 Short tandem repeats (STRs), 6 SIFamide, 154 Single-nucleotide polymorphisms (SNPs) association testing, 7–8 cardiovascular diseases, 53 databases used, 8–10 disease-assosiated gene mapping genotype subset, 13–15 variants selection, 12–13 factors influencing DNA structure, 3–4 positive selection, 4 GWAS study, 18 health and diseases, 4–5 phenotypic differences, 3 SMG proteins and NMD different organisms, 190–191 genome surveillance, 227–231 genotoxic stress, 226–227 phosphorylation cycle, 193–194 s-phase progression, 227–228 SNP500Cancer project, 7 Subesophageal ganglion (SOG), 86 SURF complex, 202–204 Surveillance complex assembly, 211 Synonymous SNPs, 5

U Unproductive regulated splicing, 213 Upf1p-RNA complex formation, 202 UPF proteins mRNA turnover pathways, 224–226 and nonsense-mediated mRNA decay degradation process, 211–212 different organisms, 190–191 domain organization, 192–193 exon junction complex, 194–195 human genome and upf3 genes, 196–197 phosphorylation cycle, 193–194 s-phase progression and genome surveillance, 227–228 tethering assay, 192 translation termination nonsense codons, 201 restricted to aberrant termination, 223–224 RNA complex and eRF, 202 SURF and DECID complex, 202–205 Upstream open reading frames (uORFs), 214 V Variable number tandem repeats (VNTRs), 6 Visual projection neurons (VPNs), Drosophila, 89 W Wee complex, 196 Wing-Extension Indices (WEI), 153 Y yellow (y) gene, 151–153