Naturally occurring variation in bristle number and DNA polymorphisms at the scabrous locus of Drosophila melanogaster

Pleiotropy, epistasis and the genetic architecture of quantitative traits

Pleiotropy (whereby one genetic polymorphism affects multiple traits) and epistasis (whereby non-linear interactions between genetic polymorphisms affect the same trait) are fundamental aspects of the genetic architecture of quantitative traits. Recent advances in the ability to characterize the effects of polymorphic variants on molecular and organismal phenotypes in human and model organism populations have revealed the prevalence of pleiotropy and unexpected shared molecular genetic bases among quantitative traits, including diseases. By contrast, epistasis is common between polymorphic loci associated with quantitative traits in model organisms, such that alleles at one locus have different effects in different genetic backgrounds, but is rarely observed for human quantitative traits and common diseases. Here, we review the concepts and recent inferences about pleiotropy and epistasis, and discuss factors that contribute to similarities and differences between the genetic architecture of quantitative traits in model organisms and humans.

Cryptic genetic variation accelerates evolution by opening access to diverse adaptive peaks

Cryptic genetic variation can facilitate adaptation in evolving populations. To elucidate the underlying genetic mechanisms, we used directed evolution in Escherichia coli to accumulate variation in populations of yellow fluorescent proteins and then evolved these proteins toward the new phenotype of green fluorescence. Populations with cryptic variation evolved adaptive genotypes with greater diversity and higher fitness than populations without cryptic variation, which converged on similar genotypes. Populations with cryptic variation accumulated neutral or deleterious mutations that break the constraints on the order in which adaptive mutations arise. In doing so, cryptic variation opens paths to adaptive genotypes, creates historical contingency, and reduces the predictability of evolution by allowing different replicate populations to climb different adaptive peaks and explore otherwise-inaccessible regions of an adaptive landscape.

Charting the genotype-phenotype map: lessons from the Drosophila melanogaster Genetic Reference Panel

Understanding the genetic architecture (causal molecular variants, their effects, and frequencies) of quantitative traits is important for precision agriculture and medicine and predicting adaptive evolution, but is challenging in most species. The Drosophila melanogaster Genetic Reference Panel (DGRP) is a collection of 205 inbred strains with whole genome sequences derived from a single wild population in Raleigh, NC, USA. The large amount of quantitative genetic variation, lack of population structure, and rapid local decay of linkage disequilibrium in the DGRP and outbred populations derived from DGRP lines present a favorable scenario for performing genome-wide association (GWA) mapping analyses to identify candidate causal genes, polymorphisms, and pathways affecting quantitative traits. The many GWA studies utilizing the DGRP have revealed substantial natural genetic variation for all reported traits, little evidence for variants with large effects but enrichment for variants with low P-values, and a tendency for lower frequency variants to have larger effects than more common variants. The variants detected in the GWA analyses rarely overlap those discovered using mutagenesis, and often are the first functional annotations of computationally predicted genes. Variants implicated in GWA analyses typically have sex-specific and genetic background-specific (epistatic) effects, as well as pleiotropic effects on other quantitative traits. Studies in the DGRP reveal substantial genetic control of environmental variation. Taking account of genetic architecture can greatly improve genomic prediction in the DGRP. These features of the genetic architecture of quantitative traits are likely to apply to other species, including humans. WIREs Dev Biol 2018, 7:e289. doi: 10.1002/wdev.289 This article is categorized under: Invertebrate Organogenesis > Flies.

Charting the genotype-phenotype map: lessons from the Drosophila melanogaster Genetic Reference Panel

Understanding the genetic architecture (causal molecular variants, their effects, and frequencies) of quantitative traits is important for precision agriculture and medicine and predicting adaptive evolution, but is challenging in most species. The Drosophila melanogaster Genetic Reference Panel (DGRP) is a collection of 205 inbred strains with whole genome sequences derived from a single wild population in Raleigh, NC, USA. The large amount of quantitative genetic variation, lack of population structure, and rapid local decay of linkage disequilibrium in the DGRP and outbred populations derived from DGRP lines present a favorable scenario for performing genome-wide association (GWA) mapping analyses to identify candidate causal genes, polymorphisms, and pathways affecting quantitative traits. The many GWA studies utilizing the DGRP have revealed substantial natural genetic variation for all reported traits, little evidence for variants with large effects but enrichment for variants with low P-values, and a tendency for lower frequency variants to have larger effects than more common variants. The variants detected in the GWA analyses rarely overlap those discovered using mutagenesis, and often are the first functional annotations of computationally predicted genes. Variants implicated in GWA analyses typically have sex-specific and genetic background-specific (epistatic) effects, as well as pleiotropic effects on other quantitative traits. Studies in the DGRP reveal substantial genetic control of environmental variation. Taking account of genetic architecture can greatly improve genomic prediction in the DGRP. These features of the genetic architecture of quantitative traits are likely to apply to other species, including humans. WIREs Dev Biol 2018, 7:e289. doi: 10.1002/wdev.289 This article is categorized under: Invertebrate Organogenesis > Flies.

QUANTITATIVE GENETICS OF OVARIOLE NUMBER IN DROSOPHILA MELANOGASTER. I. SEGREGATING VARIATION AND FITNESS

The number of ovarioles of the Drosophila melanogaster ovary is a trait thought to be associated with female fecundity, and therefore is expected to be under strong natural selection. This hypothesis may be tested by examining patterns of genetic and environmental variation for ovariole number in natural populations, and by determining the association between ovariole number and fitness in isogenic lines derived from a natural population. We measured ovariole number, and competitive fitness and its components, for 48 homozygous chromosome 3 substitution lines in a standard inbred background; and body size in a sample of 15 chromosome 3 substitution lines. We found significant segregating genetic variation for ovariole number, with a broad-sense heritability (H² ) of 0.403 and correspondingly high coefficients of genetic variation (CV_C = 20.8) and residual variation (CV_R = 25.3). Estimates of quantitative genetic parameters for body size (H² = 0.191, CV_G = 2.15, and CV_R = 3.87) are similar to those previously reported for this trait. Although the isogenic chromosome 3 substitution lines varied significantly for components of fitness, there was no significant linear or quadratic association of ovariole number and body size with fitness. There was, however, highly significant sex × genotype interaction for fitness among these lines. This special case of genotype × environment interaction for fitness may contribute to the maintenance of genetic variation for fitness in natural populations.

QUANTITATIVE GENETIC ANALYSIS OF DIVERGENCE IN MALE SECONDARY SEXUAL TRAITS BETWEEN DROSOPHILA SIMULANS AND DROSOPHILA MAURITIANA

The sibling species Drosophila simulans and D. mauritiana differ significantly in a number of male secondary sexual traits, providing an ideal system for genetic analysis of interspecific morphological divergence. In the experiment reported here, F₁ hybrids from a cross of two inbred lines were backcrossed in both directions and about 200 flies from each backcross were scored for several traits (bristle numbers and cuticle areas), as well as 18 markers distributed throughout the genome. Each trait was analyzed by composite interval mapping to identify quantitative trait loci (QTL) and estimate their effects. For each trait, from one to eight loci were detected, with more divergent traits showing evidence for greater numbers of QTL. Estimates of additive effects varied widely, with a range of 0.4 to 4.1 environmental standard deviation units and an average of 2.2 units. There was substantial evidence for nonadditive effects, since the magnitude of estimates often differed significantly between the two backcrosses. The sign of the estimated effect differed among QTL for bristle traits, but not for cuticle area traits, suggesting that these two types of trait may have undergone different types of selection. Finally, several similarities were found between different traits in the estimated positions of QTL, suggesting that pleiotropy and/or linkage of QTL may have been important in the evolution of these traits.

The Decay of Disease Association with Declining Linkage Disequilibrium: A Fine Mapping Theorem

Several important and fundamental aspects of disease genetics models have yet to be described. One such property is the relationship of disease association statistics at a marker site closely linked to a disease causing site. A complete description of this two-locus system is of particular importance to experimental efforts to fine map association signals for complex diseases. Here, we present a simple relationship between disease association statistics and the decline of linkage disequilibrium from a causal site. Specifically, the ratio of Chi-square disease association statistics at a marker site and causal site is equivalent to the standard measure of pairwise linkage disequilibrium, r². A complete derivation of this relationship from a general disease model is shown. Quite interestingly, this relationship holds across all modes of inheritance. Extensive Monte Carlo simulations using a disease genetics model applied to chromosomes subjected to a standard model of recombination are employed to better understand the variation around this fine mapping theorem due to sampling effects. We also use this relationship to provide a framework for estimating properties of a non-interrogated causal site using data at closely linked markers. Lastly, we apply this way of examining association data from high-density genotyping in a large, publicly-available data set investigating extreme BMI. We anticipate that understanding the patterns of disease association decay with declining linkage disequilibrium from a causal site will enable more powerful fine mapping methods and provide new avenues for identifying causal sites/genes from fine-mapping studies.

Reflections on the Field of Human Genetics: A Call for Increased Disease Genetics Theory

Development of human genetics theoretical models and the integration of those models with experiment and statistical evaluation are critical for scientific progress. This perspective argues that increased effort in disease genetics theory, complementing experimental, and statistical efforts, will escalate the unraveling of molecular etiologies of complex diseases. In particular, the development of new, realistic disease genetics models will help elucidate complex disease pathogenesis, and the predicted patterns in genetic data made by these models will enable the concurrent, more comprehensive statistical testing of multiple aspects of disease genetics predictions, thereby better identifying disease loci. By theoretical human genetics, I intend to encompass all investigations devoted to modeling the heritable architecture underlying disease traits and studies of the resulting principles and dynamics of such models. Hence, the scope of theoretical disease genetics work includes construction and analysis of models describing how disease-predisposing alleles (1) arise, (2) are transmitted across families and populations, and (3) interact with other risk and protective alleles across both the genome and environmental factors to produce disease states. Theoretical work improves insight into viable genetic models of diseases consistent with empirical results from linkage, transmission, and association studies as well as population genetics. Furthermore, understanding the patterns of genetic data expected under realistic disease models will enable more powerful approaches to discover disease-predisposing alleles and additional heritable factors important in common diseases. In spite of the pivotal role of disease genetics theory, such investigation is not particularly vibrant.

CardioGxE, a catalog of gene-environment interactions for cardiometabolic traits

Background

Genetic understanding of complex traits has developed immensely over the past decade but remains hampered by incomplete descriptions of contribution to phenotypic variance. Gene-environment (GxE) interactions are one of these contributors and in the guise of diet and physical activity are important modulators of cardiometabolic phenotypes and ensuing diseases.

Results

We mined the scientific literature to collect GxE interactions from 386 publications for blood lipids, glycemic traits, obesity anthropometrics, vascular measures, inflammation and metabolic syndrome, and introduce CardioGxE, a gene-environment interaction resource. We then analyzed the genes and SNPs supporting cardiometabolic GxEs in order to demonstrate utility of GxE SNPs and to discern characteristics of these important genetic variants. We were able to draw many observations from our extensive analysis of GxEs. 1) The CardioGxE SNPs showed little overlap with variants identified by main effect GWAS, indicating the importance of environmental interactions with genetic factors on cardiometabolic traits. 2) These GxE SNPs were enriched in adaptation to climatic and geographical features, with implications on energy homeostasis and response to physical activity. 3) Comparison to gene networks responding to plasma cholesterol-lowering or regression of atherosclerotic plaques showed that GxE genes have a greater role in those responses, particularly through high-energy diets and fat intake, than do GWAS-identified genes for the same traits. Other aspects of the CardioGxE dataset were explored.

Conclusions

Overall, we demonstrate that SNPs supporting cardiometabolic GxE interactions often exhibit transcriptional effects or are under positive selection. Still, not all such SNPs can be assigned potential functional or regulatory roles often because data are lacking in specific cell types or from treatments that approximate the environmental factor of the GxE. With research on metabolic related complex disease risk embarking on genome-wide GxE interaction tests, CardioGxE will be a useful resource.

A test for selection employing quantitative trait locus and mutation accumulation data

Evolutionary biologists attribute much of the phenotypic diversity observed in nature to the action of natural selection. However, for many phenotypic traits, especially quantitative phenotypic traits, it has been challenging to test for the historical action of selection. An important challenge for biologists studying quantitative traits, therefore, is to distinguish between traits that have evolved under the influence of strong selection and those that have evolved neutrally. Most existing tests for selection employ molecular data, but selection also leaves a mark on the genetic architecture underlying a trait. In particular, the distribution of quantitative trait locus (QTL) effect sizes and the distribution of mutational effects together provide information regarding the history of selection. Despite the increasing availability of QTL and mutation accumulation data, such data have not yet been effectively exploited for this purpose. We present a model of the evolution of QTL and employ it to formulate a test for historical selection. To provide a baseline for neutral evolution of the trait, we estimate the distribution of mutational effects from mutation accumulation experiments. We then apply a maximum-likelihood-based method of inference to estimate the range of selection strengths under which such a distribution of mutations could generate the observed QTL. Our test thus represents the first integration of population genetic theory and QTL data to measure the historical influence of selection.

A Database of Gene-Environment Interactions Pertaining to Blood Lipid Traits, Cardiovascular Disease and Type 2 Diabetes

As the role of the environment - diet, exercise, alcohol and tobacco use and sleep among others - is accorded a more prominent role in modifying the relationship between genetic variants and clinical measures of disease, consideration of gene-environment (GxE) interactions is a must. To facilitate incorporation of GxE interactions into single-gene and genome-wide association studies, we have compiled from the literature a database of GxE interactions relevant to nutrition, blood lipids, cardiovascular disease and type 2 diabetes. Over 550 such interactions have been incorporated into a single database, along with over 1430 instances where a lack of statistical significance was found. This database will serve as an important resource to researchers in genetics and nutrition in order to gain an understanding of which points in the human genome are sensitive to variations in diet, physical activity and alcohol use, among other lifestyle choices. Furthermore, this GxE database has been designed with future integration into a larger database of nutritional phenotypes in mind.

Mutations and quantitative genetic variation: lessons from Drosophila

A central issue in evolutionary quantitative genetics is to understand how genetic variation for quantitative traits is maintained in natural populations. Estimates of genetic variation and of genetic correlations and pleiotropy among multiple traits, inbreeding depression, mutation rates for fitness and quantitative traits and of the strength and nature of selection are all required to evaluate theoretical models of the maintenance of genetic variation. Studies in Drosophila melanogaster have shown that a substantial fraction of segregating variation for fitness-related traits in Drosophila is due to rare deleterious alleles maintained by mutation-selection balance, with a smaller but significant fraction attributable to intermediate frequency alleles maintained by alleles with antagonistic pleiotropic effects, and late-age-specific effects. However, the nature of segregating variation for traits under stabilizing selection is less clear and requires more detailed knowledge of the loci, mutation rates, allelic effects and frequencies of molecular polymorphisms affecting variation in suites of pleiotropically connected traits. Recent studies in D. melanogaster have revealed unexpectedly complex genetic architectures of many quantitative traits, with large numbers of pleiotropic genes and alleles with sex-, environment- and genetic background-specific effects. Future genome wide association analyses of many quantitative traits on a common panel of fully sequenced Drosophila strains will provide much needed empirical data on the molecular genetic basis of quantitative traits.

Linkage disequilibrium and population structure in wild and domesticated populations of Phaseolus vulgaris L

Together with the knowledge of the population structure, a critical aspect for the planning of association and/or population genomics studies is the level of linkage disequilibrium (LD) that characterizes the species and the population used for such an analysis. We have analyzed the population structure and LD in wild and domesticated populations of Phaseolus vulgaris L. using amplified fragment length polymorphism markers, most of which were genetically mapped in two recombinant inbred populations. Our results reflect the previous knowledge of the occurrence of two major wild gene pools of P. vulgaris, from which two independent domestication events originated, one in the Andes and one in Mesoamerica. The high level of LD in the whole sample was mostly due to the gene pool structure, with a much higher LD in domesticated compared to wild populations. In relation to association studies, our results also suggest that whole-genome-scan approaches are feasible in the common bean. Interestingly, an excess of inter-chromosomal LD was found in the domesticated populations, which suggests an important role for epistatic selection during domestication. Moreover, our results indicate the occurrence of a strong bottleneck in the Andean wild population before domestication, suggesting a Mesoamerican origin of P. vulgaris. Finally, our data support the occurrence of a single domestication event in Mesoamerica, and the same scenario in the Andes.

Genetic architecture of quantitative traits in mice, flies, and humans

We compare and contrast the genetic architecture of quantitative phenotypes in two genetically well-characterized model organisms, the laboratory mouse, Mus musculus, and the fruit fly, Drosophila melanogaster, with that found in our own species from recent successes in genome-wide association studies. We show that the current model of large numbers of loci, each of small effect, is true for all species examined, and that discrepancies can be largely explained by differences in the experimental designs used. We argue that the distribution of effect size of common variants is the same for all phenotypes regardless of species, and we discuss the importance of epistasis, pleiotropy, and gene by environment interactions. Despite substantial advances in mapping quantitative trait loci, the identification of the quantitative trait genes and ultimately the sequence variants has proved more difficult, so that our information on the molecular basis of quantitative variation remains limited. Nevertheless, available data indicate that many variants lie outside genes, presumably in regulatory regions of the genome, where they act by altering gene expression. As yet there are very few instances where homologous quantitative trait loci, or quantitative trait genes, have been identified in multiple species, but the availability of high-resolution mapping data will soon make it possible to test the degree of overlap between species.

The genetic architecture of complex traits in teosinte (Zea mays ssp. parviglumis): new evidence from association mapping

Previous association analyses showed that variation at major regulatory genes contributes to standing variation for complex traits in Balsas teosinte, the progenitor of maize. This study expands our previous association mapping effort in teosinte by testing 123 markers in 52 candidate genes for association with 31 traits in a population of 817 individuals. Thirty-three significant associations for markers from 15 candidate genes and 10 traits survive correction for multiple testing. Our analyses suggest several new putative causative relationships between specific genes and trait variation in teosinte. For example, two ramosa genes (ra1 and ra2) associate with ear structure, and the MADS-box gene, zagl1, associates with ear shattering. Since zagl1 was previously shown to be a target of selection during maize domestication, we suggest that this gene was under selection for its effect on the loss of ear shattering, a key domestication trait. All observed effects were relatively small in terms of the percentage of phenotypic variation explained (<10%). We also detected several epistatic interactions between markers in the same gene that associate with the same trait. Candidate-gene-based association mapping appears to be a promising method for investigating the inheritance of complex traits in teosinte.

Of flies and man: Drosophila as a model for human complex traits

Understanding the genetic and environmental factors affecting human complex genetic traits and diseases is a major challenge because of many interacting genes with individually small effects, whose expression is sensitive to the environment. Dissection of complex traits using the powerful genetic approaches available with Drosophila melanogaster has provided important lessons that should be considered when studying human complex traits. In Drosophila, large numbers of pleiotropic genes affect complex traits; quantitative trait locus alleles often have sex-, environment-, and genetic background-specific effects, and variants associated with different phenotypic are in noncoding as well as coding regions of candidate genes. Such insights, in conjunction with the strong evolutionary conservation of key genes and pathways between flies and humans, make Drosophila an excellent model system for elucidating the genetic mechanisms that affect clinically relevant human complex traits, such as alcohol dependence, sleep, and neurodegenerative diseases.

An unusually low microsatellite mutation rate in Dictyostelium discoideum, an organism with unusually abundant microsatellites

The genome of the social amoeba Dictyostelium discoideum is known to have a very high density of microsatellite repeats, including thousands of triplet microsatellite repeats in coding regions that apparently code for long runs of single amino acids. We used a mutation accumulation study to see if unusually high microsatellite mutation rates contribute to this pattern. There was a modest bias toward mutations that increase repeat number, but because upward mutations were smaller than downward ones, this did not lead to a net average increase in size. Longer microsatellites had higher mutation rates than shorter ones, but did not show greater directional bias. The most striking finding is that the overall mutation rate is the lowest reported for microsatellites: approximately 1 x 10(-6) for 10 dinucleotide loci and 6 x 10(-6) for 52 trinucleotide loci (which were longer). High microsatellite mutation rates therefore do not explain the high incidence of microsatellites. The causal relation may in fact be reversed, with low mutation rates evolving to protect against deleterious fitness effects of mutation at the numerous microsatellites.

Major regulatory genes in maize contribute to standing variation in teosinte (Zea mays ssp. parviglumis)

In plants, many major regulatory genes that control plant growth and development have been identified and characterized. Despite a detailed knowledge of the function of these genes little is known about how they contribute to the natural variation for complex traits. To determine whether major regulatory genes of maize contribute to standing variation in Balsas teosinte we conducted association mapping in 584 Balsas teosinte individuals. We tested 48 markers from nine candidate regulatory genes against 13 traits for plant and inflorescence architecture. We identified significant associations using a mixed linear model that controls for multiple levels of relatedness. Ten associations involving five candidate genes were significant after correction for multiple testing, and two survive the conservative Bonferroni correction. zfl2, the maize homolog of FLORICAULA of Antirrhinum, was associated with plant height. zap1, the maize homolog of APETALA1 of Arabidopsis, was associated with inflorescence branching. Five SNPs in the maize domestication gene, teosinte branched1, were significantly associated with either plant or inflorescence architecture. Our data suggest that major regulatory genes in maize do play a role in the natural variation for complex traits in teosinte and that some of the minor variants we identified may have been targets of selection during domestication.

Quantitative phenotype analysis for localization and identification of disease-related genes in a complex genetic background

Results from genetic investigations of blood pressure and other variables in inbred rodent models are reviewed here to illustrate the power of quantitative approaches for the detection of linkage and the ultimate identification of the underlying genes. Different studies-involving angiotensinogen and hypertension, angiotensin I-converting enzyme and cardiovascular diseases, and other traits-are used to illustrate the possibility of similar approaches to multifactorial disorders in humans.

Nucleotide diversity and linkage disequilibrium in 11 expressed resistance candidate genes in Lolium perenne

BACKGROUND

Association analysis is an alternative way for QTL mapping in ryegrass. So far, knowledge on nucleotide diversity and linkage disequilibrium in ryegrass is lacking, which is essential for the efficiency of association analyses.

RESULTS

11 expressed disease resistance candidate (R) genes including 6 nucleotide binding site and leucine rich repeat (NBS-LRR) like genes and 5 non-NBS-LRR genes were analyzed for nucleotide diversity. For each of the genes about 1 kb genomic fragments were isolated from 20 heterozygous genotypes in ryegrass. The number of haplotypes per gene ranged from 9 to 27. On average, one single nucleotide polymorphism (SNP) was present per 33 bp between two randomly sampled sequences for the 11 genes. NBS-LRR like gene fragments showed a high degree of nucleotide diversity, with one SNP every 22 bp between two randomly sampled sequences. NBS-LRR like gene fragments showed very high non-synonymous mutation rates, leading to altered amino acid sequences. Particularly LRR regions showed very high diversity with on average one SNP every 10 bp between two sequences. In contrast, non-NBS LRR resistance candidate genes showed a lower degree of nucleotide diversity, with one SNP every 112 bp. 78% of haplotypes occurred at low frequency (<5%) within the collection of 20 genotypes. Low intragenic LD was detected for most R genes, and rapid LD decay within 500 bp was detected.

CONCLUSION

Substantial LD decay was found within a distance of 500 bp for most resistance candidate genes in this study. Hence, LD based association analysis is feasible and promising for QTL fine mapping of resistance traits in ryegrass.

Joint estimates of quantitative trait locus effect and frequency using synthetic recombinant populations of Drosophila melanogaster

We develop and implement a strategy to map QTL in two synthetic populations of Drosophila melanogaster each initiated with eight inbred founder strains. These recombinant populations allow simultaneous estimates of QTL location, effect, and frequency. Five X-linked QTL influencing bristle number were resolved to intervals of approximately 1.3 cM. We confirm previous observations of bristle number QTL distal to 4A at the tip of the chromosome and identify two novel QTL in 7F-8C, an interval that does not include any classic bristle number candidate genes. If QTL at the tip of the X are biallelic they appear to be intermediate in frequency, although there is evidence that these QTL may reside in multiallelic haplotypes. Conversely, the two QTL mapping to the middle of the X chromosome are likely rare: in each case the minor allele is observed in only 1 of the 16 founders. Assuming additivity and biallelism we estimate that identified QTL contribute 1.0 and 8.7%, respectively, to total phenotypic variation in male abdominal and sternopleural bristle number in nature. Models that seek to explain the maintenance of genetic variation make different predictions about the population frequency of QTL alleles. Thus, mapping QTL in eight-way recombinant populations can distinguish between these models.

Combining population genomics and quantitative genetics: finding the genes underlying ecologically important traits

A central challenge in evolutionary biology is to identify genes underlying ecologically important traits and describe the fitness consequences of naturally occurring variation at these loci. To address this goal, several novel approaches have been developed, including 'population genomics,' where a large number of molecular markers are scored in individuals from different environments with the goal of identifying markers showing unusual patterns of variation, potentially due to selection at linked sites. Such approaches are appealing because of (1) the increasing ease of generating large numbers of genetic markers, (2) the ability to scan the genome without measuring phenotypes and (3) the simplicity of sampling individuals without knowledge of their breeding history. Although such approaches are inherently applicable to non-model systems, to date these studies have been limited in their ability to uncover functionally relevant genes. By contrast, quantitative genetics has a rich history, and more recently, quantitative trait locus (QTL) mapping has had some success in identifying genes underlying ecologically relevant variation even in novel systems. QTL mapping, however, requires (1) genetic markers that specifically differentiate parental forms, (2) a focus on a particular measurable phenotype and (3) controlled breeding and maintenance of large numbers of progeny. Here we present current advances and suggest future directions that take advantage of population genomics and quantitative genetic approaches - in both model and non-model systems. Specifically, we discuss advantages and limitations of each method and argue that a combination of the two provides a powerful approach to uncovering the molecular mechanisms responsible for adaptation.

How repeatable are associations between polymorphisms in achaete-scute and bristle number variation in Drosophila?

Currently, the relevance of common genetic variants--particularly those significantly associated with phenotypic variation in laboratory studies--to standing phenotypic variation in the wild is poorly understood. To address this, we quantified the relationship between achaete-scute complex (ASC) polymorphisms and Drosophila bristle number phenotypes in several new population samples. MC22 is a biallelic, nonrepetitive-length polymorphism 97 bp downstream of the scute transcript. It has been previously shown to be associated with sternopleural bristle number variation in both sexes in a set of isogenic lines. We replicated this association in a large cohort of wild-caught Drosophila melanogaster. We also detected a significant association at MC22 in an outbred population maintained under laboratory conditions for approximately 25 years, but the phenotypic effects in this sample were opposite from the direction estimated in the initial study. Finally, no significant associations were detected in a second large wild-caught cohort or in a set of 134 nearly isogenic lines. Our ability to repeat the initial association in wild samples suggests that it was not spurious. Nevertheless, inconsistent results from the other three panels suggest that the relationship between polymorphic genetic markers and loci contributing to continuous variation is not a simple one.

Pairwise linkage disequilibrium under disease models

Many genetic studies of disease association rely heavily on linkage disequilibrium (LD) patterns between pairs of markers to detect susceptibility markers. This is true of large-scale positional mapping approaches as well as haplotype construction, selection of tagging single-nucleotide polymorphisms and population genetic analyses. Whereas the distribution of different LD measures has been investigated for randomly selected chromosomes from populations undergoing a variety of demographic effects, little is known about LD within disease-affected samples, and how various disease models influence the difference in LD between patients and the general population. As whole-genome efforts are now underway to characterize and utilize LD patterns in randomly sampled individuals, knowledge about the extent that LD differs between patients and the general population becomes crucial. Such information will allow investigators to design improved mapping experiments and better understand haplotype information arising from such experiments. In this paper, we explore two-site LD measures in the context of single gene disease models. Analytic expressions are presented for infinite populations and properties of sampling densities are reported for different disease models. Interestingly, results indicate that 'underdominant', some dominant, recessive and 'protective' disease models generate weaker LD levels in patients compared to the general population, whereas other models produce stronger LD among affected individuals. Analytic results are also presented for the ratio of LD in patients to the LD in the general population as a function of recombination fraction using a Haldane model. In addition, we explore the impact of various allele frequency combinations on LD differences.

Dissecting the complex genetic basis of mate choice

The genetic analysis of mate choice is fraught with difficulties. Males produce complex signals and displays that can consist of a combination of acoustic, visual, chemical and behavioural phenotypes. Furthermore, female preferences for these male traits are notoriously difficult to quantify. During mate choice, genes not only affect the phenotypes of the individual they are in, but can influence the expression of traits in other individuals. How can genetic analyses be conducted to encompass this complexity? Tighter integration of classical quantitative genetic approaches with modern genomic technologies promises to advance our understanding of the complex genetic basis of mate choice.

A wing expressed sequence tag resource for Bicyclus anynana butterflies, an evo-devo model

BACKGROUND

Butterfly wing color patterns are a key model for integrating evolutionary developmental biology and the study of adaptive morphological evolution. Yet, despite the biological, economical and educational value of butterflies they are still relatively under-represented in terms of available genomic resources. Here, we describe an Expression Sequence Tag (EST) project for Bicyclus anynana that has identified the largest available collection to date of expressed genes for any butterfly.

RESULTS

By targeting cDNAs from developing wings at the stages when pattern is specified, we biased gene discovery towards genes potentially involved in pattern formation. Assembly of 9,903 ESTs from a subtracted library allowed us to identify 4,251 genes of which 2,461 were annotated based on BLAST analyses against relevant gene collections. Gene prediction software identified 2,202 peptides, of which 215 longer than 100 amino acids had no homology to any known proteins and, thus, potentially represent novel or highly diverged butterfly genes. We combined gene and Single Nucleotide Polymorphism (SNP) identification by constructing cDNA libraries from pools of outbred individuals, and by sequencing clones from the 3' end to maximize alignment depth. Alignments of multi-member contigs allowed us to identify over 14,000 putative SNPs, with 316 genes having at least one high confidence double-hit SNP. We furthermore identified 320 microsatellites in transcribed genes that can potentially be used as genetic markers.

CONCLUSION

Our project was designed to combine gene and sequence polymorphism discovery and has generated the largest gene collection available for any butterfly and many potential markers in expressed genes. These resources will be invaluable for exploring the potential of B. anynana in particular, and butterflies in general, as models in ecological, evolutionary, and developmental genetics.

Phenotypic variation and natural selection at catsup, a pleiotropic quantitative trait gene in Drosophila

Quantitative traits are shaped by networks of pleiotropic genes . To understand the mechanisms that maintain genetic variation for quantitative traits in natural populations and to predict responses to artificial and natural selection, we must evaluate pleiotropic effects of underlying quantitative trait genes and define functional allelic variation at the level of quantitative trait nucleotides (QTNs). Catecholamines up (Catsup), which encodes a negative regulator of tyrosine hydroxylase , the rate-limiting step in the synthesis of the neurotransmitter dopamine, is a pleiotropic quantitative trait gene in Drosophila melanogaster. We used association mapping to determine whether the same or different QTNs at Catsup are associated with naturally occurring variation in multiple quantitative traits. We sequenced 169 Catsup alleles from a single population and detected 33 polymorphisms with little linkage disequilibrium (LD). Different molecular polymorphisms in Catsup are independently associated with variation in longevity, locomotor behavior, and sensory bristle number. Most of these polymorphisms are potentially functional variants in protein coding regions, have large effects, and are not common. Thus, Catsup is a pleiotropic quantitative trait gene, but individual QTNs do not have pleiotropic effects. Molecular population genetic analyses of Catsup sequences are consistent with balancing selection maintaining multiple functional polymorphisms.

Drosophila bristles and the nature of quantitative genetic variation

Numbers of Drosophila sensory bristles present an ideal model system to elucidate the genetic basis of variation for quantitative traits. Here, we review recent evidence that the genetic architecture of variation for bristle numbers is surprisingly complex. A substantial fraction of the Drosophila genome affects bristle number, indicating pervasive pleiotropy of genes that affect quantitative traits. Further, a large number of loci, often with sex- and environment-specific effects that are also conditional on background genotype, affect natural variation in bristle number. Despite this complexity, an understanding of the molecular basis of natural variation in bristle number is emerging from linkage disequilibrium mapping studies of individual candidate genes that affect the development of sensory bristles. We show that there is naturally segregating genetic variance for environmental plasticity of abdominal and sternopleural bristle number. For abdominal bristle number this variance can be attributed in part to an abnormal abdomen-like phenotype that resembles the phenotype of mutants defective in catecholamine biosynthesis. Dopa decarboxylase (Ddc) encodes the enzyme that catalyses the final step in the synthesis of dopamine, a major Drosophila catecholamine and neurotransmitter. We found that molecular polymorphisms at Ddc are indeed associated with variation in environmental plasticity of abdominal bristle number.

The effect of polymorphisms in the enhancer of split gene complex on bristle number variation in a large wild-caught cohort of Drosophila melanogaster

The Enhancer of split complex [E(spl)-C] in Drosophila encompasses a variety of functional elements controlling bristle patterning and on the basis of prior work is a strong candidate for harboring alleles having subtle effects on bristle number variation. Here we extend earlier studies identifying associations between complex phenotypes and polymorphisms segregating among inbred laboratory lines of Drosophila and test the influence of E(spl)-C on bristle number variation in a natural cohort. We describe results from an association mapping study using 203 polymorphisms spread throughout the E(spl)-C genotyped in 2000 wild-caught Drosophila melanogaster. Despite power to detect associations accounting for as little as 2% of segregating variation for bristle number, and saturating the region with single-nucleotide polymorphisms (SNPs), we identified no single SNP marker showing a significant (additive over loci) effect after correcting for multiple tests. Using a newly developed test we conservatively identify six regions of the E(spl)-C in which the insertion of transposable elements as a class contributes to variation in bristle number, apparently in a sex- or trait-limited fashion. Finally, we carry out all possible 20,503 two-way tests for epistasis and identify a slight excess of marginally significant interactions, although none survive multiple-testing correction. It may not be straightforward to extend the results of laboratory-based association studies to natural populations.

Tests for the replication of an association between Egfr and natural variation in Drosophila melanogaster wing morphology

Background

Quantitative differences between individuals stem from a combination of genetic and environmental factors, with the heritable variation being shaped by evolutionary forces. Drosophila wing shape has emerged as an attractive system for genetic dissection of multi-dimensional traits. We utilize several experimental genetic methods to validation of the contribution of several polymorphisms in the Epidermal growth factor receptor (Egfr) gene to wing shape and size, that were previously mapped in populations of Drosophila melanogaster from North Carolina (NC) and California (CA). This re-evaluation utilized different genetic testcrosses to generate heterozygous individuals with a variety of genetic backgrounds as well as sampling of new alleles from Kenyan stocks.

Results

Only one variant, in the Egfr promoter, had replicable effects in all new experiments. However, expanded genotyping of the initial sample of inbred lines rendered the association non-significant in the CA population, while it persisted in the NC sample, suggesting population specific modification of the quantitative trait nucleotide QTN effect.

Conclusion

Dissection of quantitative trait variation to the nucleotide level can identify sites with replicable effects as small as one percent of the segregating genetic variation. However, the testcross approach to validate QTNs is both labor intensive and time-consuming, and is probably less useful than resampling of large independent sets of outbred individuals.

Generating phenotypic variation: prospects from "evo-devo" research on Bicyclus anynana wing patterns

Understanding the generation of phenotypic variation is an important challenge for modern evolutionary biology, and butterfly wing patterns are an exciting system that can shed some light on this issue. Here, we report on recent advances in the genetics of Bicyclus anynana butterflies. This system provides the potential for a fully integrated study of the evolutionary and developmental processes underlying diversity in morphology.

Using genome scans of DNA polymorphism to infer adaptive population divergence

Elucidating the genetic basis of adaptive population divergence is a goal of central importance in evolutionary biology. In principle, it should be possible to identify chromosomal regions involved in adaptive divergence by screening genome-wide patterns of DNA polymorphism to detect the locus-specific signature of positive directional selection. In the case of spatially separated populations that inhabit different environments or sympatric populations that exploit different ecological niches, it is possible to identify loci that underlie divergently selected traits by comparing relative levels of differentiation among large numbers of unlinked markers. In this review I first address the question of whether diversifying selection on polygenic traits can be expected to produce predictable patterns of allelic variation at the underlying quantitative trait loci (QTL), and whether the locus-specific effects of selection can be reliably detected against the genome-wide backdrop of stochastic variability. I then review different approaches that have been developed to identify loci involved in adaptive population divergence and I discuss the relative merits of model-based approaches that rely on assumptions about population structure vs. model-free approaches that are based on empirical distributions of summary statistics. Finally, I consider the evolutionary and functional insights that might be gained by conducting genome scans for loci involved in adaptive population divergence.

Replication of an Egfr-wing shape association in a wild-caught cohort of Drosophila melanogaster

Linkage disequilibrium mapping has been used extensively in medical and evolutionary genetics to map causal polymorphisms within genes associated with disease status or phenotypic variation for a trait. However, the initial findings of most nonhuman studies have not been replicated in subsequent studies, due in part to false positives, as well as additional factors that can render true positives unreplicable. These factors may be more severe when the initial study is performed using an experimental population of organisms reared under controlled lab conditions. We demonstrate that despite considerable phenotypic differences for wing shape between a lab-reared experimental population and a wild-caught cohort of Drosophila melanogaster, an association between a putative regulatory polymorphism in Egfr and wing shape can be replicated. These results are discussed both within the framework of future association-mapping studies and within the context of the evolutionary dynamics of alleles in populations.

A potential regulatory polymorphism upstream of hairy is not associated with bristle number variation in wild-caught Drosophila

To extend results from laboratory genetic mapping experiments to natural populations it is necessary to estimate the phenotypic effects attributable to laboratory-identified genetic factors in nature. We retested a polymorphism found to be strongly associated with an increase of 0.35 sternopleural bristles in laboratory strains in two large samples of wild-caught Drosophila melanogaster. Despite >90% power to detect effects as low as 0.27 bristles (<1% of the total variation in bristle number) we did not replicate the association in nature. Potential explanations for this result are explored.

Microclinal variation for ovariole number and body size in Drosophila melanogaster in ?Evolution Canyon?

Sites that display strong environmental contrasts in close proximity, such as 'Evolution Canyon' on Mt. Carmel, Israel, are natural theatres for investigating adaptive evolution in action. We reared Drosophila melanogaster from collection sites along altitudinal transects on the north- and south-facing canyon slopes in each of three temperature environments, and assessed genetic variation in ovariole number and body size between and within collection sites, and temperature plasticity. Both traits exhibited significant genetic variation within collection sites and phenotypic plasticity in response to temperature, but not genetic variation for plasticity. Between-site genetic variation in ovariole number was negatively correlated with altitude on both slopes of the canyon, and collections from the north- and south-facing slopes were genetically differentiated for male, but not female, body size. Genetic variation between sites within easy dispersal range is consistent with the action of strong natural selection, although neither the selective agent(s) nor the direct targets of selection are known.

Association between nucleotide variation in Egfr and wing shape in Drosophila melanogaster

As part of an effort to dissect quantitative trait locus effects to the nucleotide level, association was assessed between 238 single-nucleotide and 20 indel polymorphisms spread over 11 kb of the Drosophila melanogaster Egfr locus and nine relative warp measures of wing shape. One SNP in a conserved potential regulatory site for a GAGA factor in the promoter of alternate first exon 2 approaches conservative experiment-wise significance (P < 0.00003) in the sample of 207 lines for association with the location of the crossveins in the central region of the wing. Several other sites indicate marginal association with one or more other aspects of shape. No strong effects of sex or population of origin were detected with measures of shape, but two different sites were strongly associated with overall wing size in interaction with these fixed factors. Whole-gene sequencing in very large samples, rather than selective genotyping, would appear to be the only strategy likely to be successful for detecting subtle associations in species with high polymorphism and little haplotype structure. However, these features severely limit the ability of linkage disequilibrium mapping in Drosophila to resolve quantitative effects to single nucleotides.

Quantitative genetic analyses of complex behaviours in Drosophila

Behaviours are exceptionally complex quantitative traits. Sensitivity to environmental variation and genetic background, the presence of sexual dimorphism, and the widespread functional pleiotropy that is inherent in behavioural phenotypes pose daunting challenges for unravelling their underlying genetics. Drosophila melanogaster provides an attractive system for elucidating the unifying principles of the genetic architectures that drive behaviours, as genetically identical individuals can be reared rapidly in controlled environments and extensive publicly accessible genetic resources are available. Recent advances in quantitative genetic and functional genomic approaches now enable the extensive characterization of complex genetic networks that mediate behaviours in this important model organism.

Effects of population structure and sex on association between serotonin receptors and Drosophila heart rate

As a first step toward population and quantitative genetic analysis of neurotransmitter receptors in Drosophila melanogaster, we describe the parameters of nucleotide variation in three serotonin receptors and their association with pupal heart rate. Thirteen kilobases of DNA including the complete coding regions of 5-HT1A, 5-HT1B, and 5-HT2 were sequenced in 216 highly inbred lines extracted from two North American populations in California and North Carolina. Nucleotide and amino acid polymorphism is in the normal range for Drosophila genes and proteins, and linkage disequilibrium decays rapidly such that haplotype blocks are typically only a few SNPs long. However, intron 1 of 5-HT1A consists of two haplotypes that are at significantly different frequencies in the two populations. Neither this region of the gene nor any of the common amino acid polymorphisms in the three loci associate with either heart rate or heart rate variability. A cluster of SNPs in intron 2 of 5-HT1A, including a triallelic site, do show a highly significant interaction between genotype, sex, and population. While it is likely that a combination of weak, complex selection pressures and population structure has helped shape variation in the serotonin receptors of Drosophila, much larger sampling strategies than are currently adopted in evolutionary genetics will be required to disentangle these effects.

Do quantitative trait loci (QTL) for a courtship song difference between Drosophila simulans and D. sechellia coincide with candidate genes and intraspecific QTL?

The genetic architecture of traits influencing sexual isolation can give insight into the evolution of reproductive isolation and hence speciation. Here we report a quantitative trait loci (QTL) analysis of the difference in mean interpulse interval (IPI), an important component of the male courtship song, between Drosophila simulans and D. sechellia. Using a backcross analysis, we find six QTL that explain a total of 40.7% of the phenotypic variance. Three candidate genes are located in the intervals bounded by two of the QTL and there are no significant QTL on the X chromosome. The values of mean IPI for hybrid individuals imply the presence of dominant alleles or epistasis. Because unisexual hybrid sterility prevents an F(2) analysis, we cannot distinguish dominant from additive genetic effects at the scale of QTL. A comparison with a study of QTL for intraspecific variation in D. melanogaster shows that, for these strains, the QTL we have identified for interspecific variation cannot be those that contribute to intraspecific variation. We find that the QTL have bidirectional effects, which indicates that the genetic architecture is compatible with divergence due to genetic drift, although other possibilities are discussed.

Polygenic variation maintained by balancing selection: pleiotropy, sex-dependent allelic effects and G x E interactions

We investigate three alternative selection-based scenarios proposed to maintain polygenic variation: pleiotropic balancing selection, G x E interactions (with spatial or temporal variation in allelic effects), and sex-dependent allelic effects. Each analysis assumes an additive polygenic trait with n diallelic loci under stabilizing selection. We allow loci to have different effects and consider equilibria at which the population mean departs from the stabilizing-selection optimum. Under weak selection, each model produces essentially identical, approximate allele-frequency dynamics. Variation is maintained under pleiotropic balancing selection only at loci for which the strength of balancing selection exceeds the effective strength of stabilizing selection. In addition, for all models, polymorphism requires that the population mean be close enough to the optimum that directional selection does not overwhelm balancing selection. This balance allows many simultaneously stable equilibria, and we explore their properties numerically. Both spatial and temporal G x E can maintain variation at loci for which the coefficient of variation (across environments) of the effect of a substitution exceeds a critical value greater than one. The critical value depends on the correlation between substitution effects at different loci. For large positive correlations (e.g., rho(ij)2>3/4), even extreme fluctuations in allelic effects cannot maintain variation. Surprisingly, this constraint on correlations implies that sex-dependent allelic effects cannot maintain polygenic variation. We present numerical results that support our analytical approximations and discuss our results in connection to relevant data and alternative variance-maintaining mechanisms.

No evidence for an association between common nonsynonymous polymorphisms in delta and bristle number variation in natural and laboratory populations of Drosophila melanogaster

We test the hypothesis that naturally occurring nonsynonymous variants in the Delta ligand of the Notch signaling pathway contribute to standing variation in sternopleural and/or abdominal bristle number in Drosophila melanogaster, for both a large cohort of wild-caught flies and previously described laboratory lines. We sequenced the transcribed region of Delta for 16 naturally occurring chromosomes and 65 SNPs, including 7 nonsynonymous SNPs (nsSNPs), were observed. Identified nsSNPs and 6 additional common SNPs, all located in exon 6 and the 3' UTR, were genotyped in 2060 wild-caught flies using an OLA-based methodology and genotyped in 38 additional natural chromosomes via DNA sequencing. None of the genotyped nsSNPs were significantly associated with natural variation in bristle number as assessed by a permutation test. A 95% upper bound on the additive genetic variance attributable to each genotyped SNP in the large natural cohort is <2% of the total phenotypic variation. Results suggest that two previously detected genotype/phenotype associations between bristle number and variants in the introns of Delta cannot be explained by linkage disequilibrium between these variants and nearby nonsynonymous variants. Unidentified regulatory variants more parsimoniously explain previous observations.

Genetic dissection of a behavioral quantitative trait locus shows that Rgs2 modulates anxiety in mice

Here we present a strategy to determine the genetic basis of variance in complex phenotypes that arise from natural, as opposed to induced, genetic variation in mice. We show that a commercially available strain of outbred mice, MF1, can be treated as an ultrafine mosaic of standard inbred strains and accordingly used to dissect a known quantitative trait locus influencing anxiety. We also show that this locus can be subdivided into three regions, one of which contains Rgs2, which encodes a regulator of G protein signaling. We then use quantitative complementation to show that Rgs2 is a quantitative trait gene. This combined genetic and functional approach should be applicable to the analysis of any quantitative trait.

Components of variance underlying fitness in a natural population of the great tit Parus major

Traits that are closely associated with fitness tend to have lower heritabilities (h2) than those that are not. This has been interpreted as evidence that natural selection tends to deplete genetic variation more rapidly for traits more closely associated with fitness (a corollary of Fisher's fundamental theorem), but Price and Schluter (1991) suggested the pattern might be due to higher residual variance in traits more closely related to fitness. The relationship between 10 different traits for females, seven traits for males, and overall fitness (lifetime recruitment) was quantified for great tits (Parus major) studied in their natural environment of Wytham Wood, England, using data collected over 39 years. Heritabilities and the coefficients of additive genetic and residual variance (CVA and CVR, respectively) were estimated using an "animal model." For both males and females, a trait's correlation (r) with fitness was negatively related to its h2 but positively related to its CVR. The CVA was not related to the trait's correlation with fitness in either sex. This is the third study using directly measured fitness in a wild population to show the important role of residual variation in determining the pattern of lower heritabilities for traits more closely related to fitness.

Polygenic Variation Maintained by Balancing Selection: Pleiotropy, Sex-Dependent Allelic Effects and G × E Interactions

We investigate three alternative selection-based scenarios proposed to maintain polygenic variation: pleiotropic balancing selection, G × E interactions (with spatial or temporal variation in allelic effects), and sex-dependent allelic effects. Each analysis assumes an additive polygenic trait with n diallelic loci under stabilizing selection. We allow loci to have different effects and consider equilibria at which the population mean departs from the stabilizing-selection optimum. Under weak selection, each model produces essentially identical, approximate allele-frequency dynamics. Variation is maintained under pleiotropic balancing selection only at loci for which the strength of balancing selection exceeds the effective strength of stabilizing selection. In addition, for all models, polymorphism requires that the population mean be close enough to the optimum that directional selection does not overwhelm balancing selection. This balance allows many simultaneously stable equilibria, and we explore their properties numerically. Both spatial and temporal G × E can maintain variation at loci for which the coefficient of variation (across environments) of the effect of a substitution exceeds a critical value greater than one. The critical value depends on the correlation between substitution effects at different loci. For large positive correlations (e.g., ρij2&gt;3∕4), even extreme fluctuations in allelic effects cannot maintain variation. Surprisingly, this constraint on correlations implies that sex-dependent allelic effects cannot maintain polygenic variation. We present numerical results that support our analytical approximations and discuss our results in connection to relevant data and alternative variance-maintaining mechanisms.

Clines and adaptive evolution in the methuselah gene region in Drosophila melanogaster

In an effort to characterize further the patterns of selection and adaptive evolution at the methuselah locus in Drosophila species, we extended an analysis of geographical variation to include single nucleotide polymorphisms (SNPs) in adjacent genes on either side of the mth locus, and examined the molecular variation in a neighbouring methuselah paralogue (mth2). An analysis of 13 SNPs spanning a region of nearly 19 kilobases surrounding the mth locus demonstrated that a clinal pattern associated with the most common mth haplotype does not extend to adjacent gene loci, providing compelling evidence that the clinal pattern results from selection on as yet unidentified sites associated with the functional mth locus. mth2 exhibited a significant pattern of adaptive divergence among D. melanogaster, D. simulans and D. yakuba similar to that seen at mth. However, Ka : Ks ratios indicate a difference in levels of functional constraint at the two methuselah, loci with mth2 exhibiting a five- to six-fold reduction in levels of amino acid divergence relative to mth.

Genetics and the making of Homo sapiens

Understanding the genetic basis of the physical and behavioural traits that distinguish humans from other primates presents one of the great new challenges in biology. Of the millions of base-pair differences between humans and chimpanzees, which particular changes contributed to the evolution of human features after the separation of the Pan and Homo lineages 5-7 million years ago? How can we identify the 'smoking guns' of human genetic evolution from neutral ticks of the molecular evolutionary clock? The magnitude and rate of morphological evolution in hominids suggests that many independent and incremental developmental changes have occurred that, on the basis of recent findings in model animals, are expected to be polygenic and regulatory in nature. Comparative genomics, population genetics, gene-expression analyses and medical genetics have begun to make complementary inroads into the complex genetic architecture of human evolution.