Challenges and prospects in genome-wide quantitative trait loci mapping of standing genetic variation in natural populations

Selection on the promoter regions plays an important role in complex traits during duck domestication

BACKGROUND

Identifying the key factors that underlie complex traits during domestication is a great challenge for evolutionary and biological studies. In addition to the protein-coding region differences caused by variants, a large number of variants are located in the noncoding regions containing multiple types of regulatory elements. However, the roles of accumulated variants in gene regulatory elements during duck domestication and economic trait improvement are poorly understood.

RESULTS

We constructed a genomics, transcriptomics, and epigenomics map of the duck genome and assessed the evolutionary forces that have been in play across the whole genome during domestication. In total, 304 (42.94%) gene promoters have been specifically selected in Pekin duck among all selected genes. Joint multi-omics analysis reveals that 218 genes (72.01%) with selected promoters are located in open and active chromatin, and 267 genes (87.83%) with selected promoters were highly and differentially expressed in domestic trait-related tissues. One important candidate gene ELOVL3, with a strong signature of differentiation on the core promoter region, is known to regulate fatty acid elongation. Functional experiments showed that the nearly fixed variants in the top selected ELOVL3 promoter in Pekin duck decreased binding ability with HLF and increased gene expression, with the overexpression of ELOVL3 able to increase lipid deposition and unsaturated fatty acid enrichment.

CONCLUSIONS

This study presents genome resequencing, RNA-Seq, Hi-C, and ATAC-Seq data of mallard and Pekin duck, showing that selection of the gene promoter region plays an important role in gene expression and phenotypic changes during domestication and highlights that the variants of the ELOVL3 promoter may have multiple effects on fat and long-chain fatty acid content in ducks.

Functional genomic tools for emerging model species

Most studies in the field of ecology and evolution aiming to connect genotype to phenotype rarely validate identified loci using functional tools. Recent developments in RNA interference (RNAi) and clustered regularly interspaced palindromic repeats (CRISPR)-Cas genome editing have dramatically increased the feasibility of functional validation. However, these methods come with specific challenges when applied to emerging model organisms, including limited spatial control of gene silencing, low knock-in efficiencies, and low throughput of functional validation. Moreover, many functional studies to date do not recapitulate ecologically relevant variation, and this limits their scope for deeper insights into evolutionary processes. We therefore argue that increased use of gene editing by allelic replacement through homology-directed repair (HDR) would greatly benefit the field of ecology and evolution.

Comparing mixed models and Random Forest association tests using naturalGWAS and a Striped Bass SNP dataset

In this study, we used the phenotype simulation package naturalGWAS to test the performance of Zhao's Random Forest method in comparison to an uncorrected Random Forest test, latent factor mixed models (LFMM), genome-wide efficient mixed models (GEMMA), and confounder adjusted linear regression (CATE). We created 400 sets of phenotypes, corresponding to five effect sizes and 2, 5, 15, or 30 causal loci, simulated from two empirical datasets containing SNPs from Striped Bass representing three and 13 populations. All association methods were evaluated for their ability to detect genotype-phenotype associations based on power, false discovery rates, and number of false positives. Genomic inflation was highest for uncorrected Random Forest and LFMM tests and lowest for Gemma and Zhao's Random Forest. All association tests had similar power to detect causal loci, and Zhao's Random Forest had the lowest false discovery rate in all scenarios. To measure the performance of association tests in small datasets with few loci surrounding a causal gene we also ran analyses again after removing causal loci from each dataset. All association tests were only able to find true positives, defined as loci located within 30k bp of a causal locus, in 3%-18% of simulations. In contrast, at least one false positive was found in 17%-44% of simulations. Zhao's Random Forest again identified the fewest false positives of all association tests studied. The ability to test the power of association tests for individual empirical datasets can be an extremely useful first step when designing a GWAS study.

Implications of Large-Effect Loci for Conservation: A Review and Case Study with Pacific Salmon

The increasing feasibility of assembling large genomic datasets for non-model species presents both opportunities and challenges for applied conservation and management. A popular theme in recent studies is the search for large-effect loci that explain substantial portions of phenotypic variance for a key trait(s). If such loci can be linked to adaptations, 2 important questions arise: 1) Should information from these loci be used to reconfigure conservation units (CUs), even if this conflicts with overall patterns of genetic differentiation? 2) How should this information be used in viability assessments of populations and larger CUs? In this review, we address these questions in the context of recent studies of Chinook salmon and steelhead (anadromous form of rainbow trout) that show strong associations between adult migration timing and specific alleles in one small genomic region. Based on the polygenic paradigm (most traits are controlled by many genes of small effect) and genetic data available at the time showing that early-migrating populations are most closely related to nearby late-migrating populations, adult migration differences in Pacific salmon and steelhead were considered to reflect diversity within CUs rather than separate CUs. Recent data, however, suggest that specific alleles are required for early migration, and that these alleles are lost in populations where conditions do not support early-migrating phenotypes. Contrasting determinations under the US Endangered Species Act and the State of California's equivalent legislation illustrate the complexities of incorporating genomics data into CU configuration decisions. Regardless how CUs are defined, viability assessments should consider that 1) early-migrating phenotypes experience disproportionate risks across large geographic areas, so it becomes important to identify early-migrating populations that can serve as reliable sources for these valuable genetic resources; and 2) genetic architecture, especially the existence of large-effect loci, can affect evolutionary potential and adaptability.

The genetic basis of a novel reproductive strategy in Sulawesi ricefishes: How modularity and a low number of loci shape pelvic brooding

The evolution of complex phenotypes like reproductive strategies is challenging to understand, as they often depend on multiple adaptations that only jointly result in a specific functionality. Sulawesi ricefishes (Adrianichthyidae) evolved a reproductive strategy termed as pelvic brooding. In contrast to the more common transfer brooding, female pelvic brooders carry an egg bundle connected to their body for weeks until the fry hatches. To examine the genetic architecture of pelvic brooding, we crossed the pelvic brooding Oryzias eversi and the transfer brooding Oryzias nigrimas (species divergence time: ∼3.6 my). We hypothesize, that a low number of loci and modularity have facilitated the rapid evolution of pelvic brooding. Traits associated to pelvic brooding, like rib length, pelvic fin length, and morphology of the genital papilla, were correlated in the parental species but correlations were reduced or lost in their F1 and F2 hybrids. Using the Castle-Wright estimator, we found that generally few loci underlie the studied traits. Further, both parental species showed modularity in their body plans. In conclusion, morphological traits related to pelvic brooding were based on a few loci and the mid-body region likely could evolve independently from the remaining body parts. Both factors presumably facilitated the evolution of pelvic brooding.

Genomic architecture of phenotypic extremes in a wild cervid

Identifying the genes underlying fitness-related traits such as body size and male ornamentation can provide tools for conservation and management and are often subject to various selective pressures. Here we performed high-depth whole genome re-sequencing of pools of individuals representing the phenotypic extremes for antler and body size in white-tailed deer (Odocoileus virginianus). Samples were selected from a tissue repository containing phenotypic data for 4,466 male white-tailed deer from Anticosti Island, Quebec, with four pools representing the extreme phenotypes for antler and body size after controlling for age. Our results revealed a largely homogenous population but detected highly divergent windows between pools for both traits, with the mean allele frequency difference of 14% for and 13% for antler and body SNPs in outlier windows, respectively. Genes in outlier antler windows were enriched for pathways associated with cell death and protein metabolism and some of the most differentiated windows included genes associated with oncogenic pathways and reproduction, processes consistent with antler evolution and growth. Genes associated with body size were more nuanced, suggestive of a highly complex trait. Overall, this study revealed the complex genomic make-up of both antler morphology and body size in free-ranging white-tailed deer and identified target loci for additional analyses.

Genome-Wide Association Mapping of Crown and Brown Rust Resistance in Perennial Ryegrass

A population of 239 perennial ryegrass (Lolium perenne L.) genotypes was analyzed to identify marker-trait associations for crown rust (Puccinia coronata f. sp. lolii) and brown rust (Puccinia graminis f. sp. loliina) resistance. Phenotypic data from field trials showed a low correlation (r = 0.17) between the two traits. Genotypes were resequenced, and a total of 14,538,978 SNPs were used to analyze population structure, linkage disequilibrium (LD), and for genome-wide association study. The SNP heritability (h²_SNP) was 0.4 and 0.8 for crown and brown rust resistance, respectively. The high-density SNP dataset allowed us to estimate LD decay with the highest possible precision to date for perennial ryegrass. Results showed a low LD extension with a rapid decay of r² value below 0.2 after 520 bp on average. Additionally, QTL regions for both traits were detected, as well as candidate genes by applying Genome Complex Trait Analysis and Multi-marker Analysis of GenoMic Annotation. Moreover, two significant genes, LpPc6 and LpPl6, were identified for crown and brown rust resistance, respectively, when SNPs were aggregated to the gene level. The two candidate genes encode proteins with phosphatase activity, which putatively can be induced by the host to perceive, amplify and transfer signals to downstream components, thus activating a plant defense response.

The green-brown polymorphism of the club-legged grasshopper Gomphocerus sibiricus is heritable and appears genetically simple

Background

Local coexistence of distinct, genetically determined color morphs can be unstable and transitional. Stable, long-term coexistence requires some form of balancing selection to protect morphs from getting lost by directional selection or genetic drift. However, not all phenotypic polymorphism need to have a genetic basis. We here report on the genetic basis of two color polymorphisms in the club-legged grasshopper Gomphocerus sibiricus: a green-brown polymorphism that is phylogenetically and geographically widespread among orthopteran insects and a pied-brown pattern polymorphism that is shared among many gomphocerine grasshoppers.

Results

We found a remarkably clear outcome of matings within and between morph that suggest not only that the green-brown polymorphism is heritable in this species, but that results can be most parsimoniously explained by a single autosomal locus with two alleles in which the green allele is dominant over the brown allele. A few individuals did not match this pattern and suggest the existence of genetic modifiers and/or developmental phenocopies. We also show that the pied-brown polymorphism is highly heritable, although the evidence for the involvement of one or more loci is less clear-cut.

Conclusions

Overall, our data demonstrate that the two polymorphisms are heritable in the club-legged grasshopper and appear genetically simple, at least with respect to green morphs. The results are consistent with the idea that the synthesis or transport of a pigment involved in the production of green coloration (likely biliverdin) is lost by homozygosity for loss-of-function alleles in brown individuals. The apparently simple genetic architecture of the green-brown polymorphism offer potential for studying balancing selection in the field and for genetic mapping in this species.

Genome-wide identification of loci associated with growth in rainbow trout

Background

Growth is a major economic production trait in aquaculture. Improvements in growth performance will reduce time and cost for fish to reach market size. However, genes underlying growth have not been fully explored in rainbow trout.

Results

A previously developed 50 K gene-transcribed SNP chip, containing ~ 21 K SNPs showing allelic imbalances potentially associated with important aquaculture production traits including body weight, muscle yield, was used for genotyping a total of 789 fish with available phenotypic data for bodyweight gain. Genotyped fish were obtained from two consecutive generations produced in the NCCCWA growth-selection breeding program. Weighted single-step GBLUP (WssGBLUP) was used to perform a genome-wide association (GWA) analysis to identify quantitative trait loci (QTL) associated with bodyweight gain. Using genomic sliding windows of 50 adjacent SNPs, 247 SNPs associated with bodyweight gain were identified. SNP-harboring genes were involved in cell growth, cell proliferation, cell cycle, lipid metabolism, proteolytic activities, chromatin modification, and developmental processes. Chromosome 14 harbored the highest number of SNPs (n = 50). An SNP window explaining the highest additive genetic variance for bodyweight gain (~ 6.4%) included a nonsynonymous SNP in a gene encoding inositol polyphosphate 5-phosphatase OCRL-1. Additionally, based on a single-marker GWA analysis, 33 SNPs were identified in association with bodyweight gain. The highest SNP explaining variation in bodyweight gain was identified in a gene coding for thrombospondin-1 (THBS1) (R² = 0.09).

Conclusion

The majority of SNP-harboring genes, including OCRL-1 and THBS1, were involved in developmental processes. Our results suggest that development-related genes are important determinants for growth and could be prioritized and used for genomic selection in breeding programs.

A multitrophic perspective on biodiversity-ecosystem functioning research

Concern about the functional consequences of unprecedented loss in biodiversity has prompted biodiversity-ecosystem functioning (BEF) research to become one of the most active fields of ecological research in the past 25 years. Hundreds of experiments have manipulated biodiversity as an independent variable and found compelling support that the functioning of ecosystems increases with the diversity of their ecological communities. This research has also identified some of the mechanisms underlying BEF relationships, some context-dependencies of the strength of relationships, as well as implications for various ecosystem services that mankind depends upon. In this paper, we argue that a multitrophic perspective of biotic interactions in random and non-random biodiversity change scenarios is key to advance future BEF research and to address some of its most important remaining challenges. We discuss that the study and the quantification of multitrophic interactions in space and time facilitates scaling up from small-scale biodiversity manipulations and ecosystem function assessments to management-relevant spatial scales across ecosystem boundaries. We specifically consider multitrophic conceptual frameworks to understand and predict the context-dependency of BEF relationships. Moreover, we highlight the importance of the eco-evolutionary underpinnings of multitrophic BEF relationships. We outline that FAIR data (meeting the standards of findability, accessibility, interoperability, and reusability) and reproducible processing will be key to advance this field of research by making it more integrative. Finally, we show how these BEF insights may be implemented for ecosystem management, society, and policy. Given that human well-being critically depends on the multiple services provided by diverse, multitrophic communities, integrating the approaches of evolutionary ecology, community ecology, and ecosystem ecology in future BEF research will be key to refine conservation targets and develop sustainable management strategies.

Transcriptome assembly for a colour-polymorphic grasshopper (Gomphocerus sibiricus) with a very large genome size

BACKGROUND

The club-legged grasshopper Gomphocerus sibiricus is a Gomphocerinae grasshopper with a promising future as model species for studying the maintenance of colour-polymorphism, the genetics of sexual ornamentation and genome size evolution. However, limited molecular resources are available for this species. Here, we present a de novo transcriptome assembly as reference resource for gene expression studies. We used high-throughput Illumina sequencing to generate 5,070,036 paired-end reads after quality filtering. We then combined the best-assembled contigs from three different de novo transcriptome assemblers (Trinity, SOAPdenovo-trans and Oases/Velvet) into a single assembly.

RESULTS

This resulted in 82,251 contigs with a N50 of 1357 and a TransRate assembly score of 0.325, which compares favourably with other orthopteran transcriptome assemblies. Around 87% of the transcripts could be annotated using InterProScan 5, BLASTx and the dammit! annotation pipeline. We identified a number of genes involved in pigmentation and green pigment metabolism pathways. Furthermore, we identified 76,221 putative single nucleotide polymorphisms residing in 8400 contigs. We also assembled the mitochondrial genome and investigated levels of sequence divergence with other species from the genus Gomphocerus. Finally, we detected and assembled Wolbachia sequences, which revealed close sequence similarity to the strain pel wPip.

CONCLUSIONS

Our study has generated a significant resource for uncovering genotype-phenotype associations in a species with an extraordinarily large genome, while also providing mitochondrial and Wolbachia sequences that will be useful for comparative studies.

Genome-Wide Association Study Identifies Genomic Loci Affecting Filet Firmness and Protein Content in Rainbow Trout

Filet quality traits determine consumer satisfaction and affect profitability of the aquaculture industry. Soft flesh is a criterion for fish filet downgrades, resulting in loss of value. Filet firmness is influenced by many factors, including rate of protein turnover. A 50K transcribed gene SNP chip was used to genotype 789 rainbow trout, from two consecutive generations, produced in the USDA/NCCCWA selective breeding program. Weighted single-step GBLUP (WssGBLUP) was used to perform genome-wide association (GWA) analyses to identify quantitative trait loci affecting filet firmness and protein content. Applying genomic sliding windows of 50 adjacent SNPs, 212 and 225 SNPs were associated with genetic variation in filet shear force and protein content, respectively. Four common SNPs in the ryanodine receptor 3 gene (RYR3) affected the aforementioned filet traits; this association suggests common mechanisms underlying filet shear force and protein content. Genes harboring SNPs were mostly involved in calcium homeostasis, proteolytic activities, transcriptional regulation, chromatin remodeling, and apoptotic processes. RYR3 harbored the highest number of SNPs (n = 32) affecting genetic variation in shear force (2.29%) and protein content (4.97%). Additionally, based on single-marker analysis, a SNP in RYR3 ranked at the top of all SNPs associated with variation in shear force. Our data suggest a role for RYR3 in muscle firmness that may be considered for genomic- and marker-assisted selection in breeding programs of rainbow trout.

Accounting for heteroscedasticity and censoring in chromosome partitioning analyses

A fundamental assumption in quantitative genetics is that traits are controlled by many loci of small effect. Using genomic data, this assumption can be tested using chromosome partitioning analyses, where the proportion of genetic variance for a trait explained by each chromosome (h²_c), is regressed on its size. However, as h²_c‐estimates are necessarily positive (censoring) and the variance increases with chromosome size (heteroscedasticity), two fundamental assumptions of ordinary least squares (OLS) regression are violated. Using simulated and empirical data we demonstrate that these violations lead to incorrect inference of genetic architecture. The degree of bias depends mainly on the number of chromosomes and their size distribution and is therefore specific to the species; using published data across many different species we estimate that not accounting for this effect overall resulted in 28% false positives. We introduce a new and computationally efficient resampling method that corrects for inflation caused by heteroscedasticity and censoring and that works under a large range of dataset sizes and genetic architectures in empirical datasets. Our new method substantially improves the robustness of inferences from chromosome partitioning analyses.

Wild GWAS-association mapping in natural populations

The increasing affordability of sequencing and genotyping technologies has transformed the field of molecular ecology in recent decades. By correlating marker variants with trait variation using association analysis, large-scale genotyping and phenotyping of individuals from wild populations has enabled the identification of genomic regions that contribute to phenotypic differences among individuals. Such "gene mapping" studies are enabling us to better predict evolutionary potential and the ability of populations to adapt to challenges, such as changing environment. These studies are also allowing us to gain insight into the evolutionary processes maintaining variation in natural populations, to better understand genotype-by-environment and epistatic interactions and to track the dynamics of allele frequency change at loci contributing to traits under selection. Gene mapping in the wild using genomewide association scans (GWAS) do, however, come with a number of methodological challenges, not least the population structure in space and time inherent to natural populations. We here provide an overview of these challenges, summarize the exciting methodological advances and applications of association mapping in natural populations reported in this special issue and provide some guidelines for future "wild GWAS" research.

SNP-skimming: A fast approach to map loci generating quantitative variation in natural populations

Genome-wide association mapping (GWAS) is a method to estimate the contribution of segregating genetic loci to trait variation. A major challenge for applying GWAS to nonmodel species has been generating dense genome-wide markers that satisfy the key requirement that marker data are error-free. Here, we present an approach to map loci within natural populations using inexpensive shallow genome sequencing. This "SNP-skimming" approach involves two steps: an initial genome-wide scan to identify putative targets followed by deep sequencing for confirmation of targeted loci. We apply our method to a test data set of floral dimension variation in the plant Penstemon virgatus, a member of a genus that has experienced dynamic floral adaptation that reflects repeated transitions in primary pollinator. The ability to detect SNPs that generate phenotypic variation depends on population genetic factors such as population allele frequency, effect size and epistasis, as well as sampling effects contingent on missing data and genotype uncertainty. However, both simulations and the Penstemon data suggest that the most significant tests from the initial SNP skim are likely to be true positives-loci with subtle but significant quantitative effects on phenotype. We discuss the promise and limitations of this method and consider optimal experimental design for a given sequencing effort. Simulations demonstrate that sampling a larger number of individual at the expense of average read depth per individual maximizes the power to detect loci.

Success and failure in replication of genotype-phenotype associations: How does replication help in understanding the genetic basis of phenotypic variation in outbred populations?

Recent developments in sequencing technologies have facilitated genomewide mapping of phenotypic variation in natural populations. Such mapping efforts face a number of challenges potentially leading to low reproducibility. However, reproducible research forms the basis of scientific progress. We here discuss the options for replication and the reasons for potential nonreproducibility. We then review the evidence for reproducible quantitative trait loci (QTL) with a focus on natural animal populations. Existing case studies of replication fall into three categories: (i) traits that have been mapped to major effect loci (including chromosomal inversion and supergenes) by independent research teams; (ii) QTL fine-mapped in discovery populations; and (iii) attempts to replicate QTL across multiple populations. Major effect loci, in particular those associated with inversions, have been successfully replicated in several cases within and across populations. Beyond such major effect variants, replication has been more successful within than across populations, suggesting that QTL discovered in natural populations may often be population-specific. This suggests that biological causes (differences in linkage patterns, allele frequencies or context-dependencies of QTL) contribute to nonreproducibility. Evidence from other fields, notably animal breeding and QTL mapping in humans, suggests that a significant fraction of QTL is indeed reproducible in direction and magnitude at least within populations. However, there is also a large number of QTL that cannot be easily reproduced. We put forward that more studies should explicitly address the causes and context-dependencies of QTL signals, in particular to disentangle linkage differences, allele frequency differences and gene-by-environment interactions as biological causes of nonreproducibility of QTL, especially between populations.

Gene Expression Contributes to the Recent Evolution of Host Resistance in a Model Host Parasite System

Heritable population differences in immune gene expression following infection can reveal mechanisms of host immune evolution. We compared gene expression in infected and uninfected threespine stickleback (Gasterosteus aculeatus) from two natural populations that differ in resistance to a native cestode parasite, Schistocephalus solidus. Genes in both the innate and adaptive immune system were differentially expressed as a function of host population, infection status, and their interaction. These genes were enriched for loci controlling immune functions known to differ between host populations or in response to infection. Coexpression network analysis identified two distinct processes contributing to resistance: parasite survival and suppression of growth. Comparing networks between populations showed resistant fish have a dynamic expression profile while susceptible fish are static. In summary, recent evolutionary divergence between two vertebrate populations has generated population-specific gene expression responses to parasite infection, affecting parasite establishment and growth.

Genetics of dispersal

Dispersal is a process of central importance for the ecological and evolutionary dynamics of populations and communities, because of its diverse consequences for gene flow and demography. It is subject to evolutionary change, which begs the question, what is the genetic basis of this potentially complex trait? To address this question, we (i) review the empirical literature on the genetic basis of dispersal, (ii) explore how theoretical investigations of the evolution of dispersal have represented the genetics of dispersal, and (iii) discuss how the genetic basis of dispersal influences theoretical predictions of the evolution of dispersal and potential consequences.

Dispersal has a detectable genetic basis in many organisms, from bacteria to plants and animals. Generally, there is evidence for significant genetic variation for dispersal or dispersal‐related phenotypes or evidence for the micro‐evolution of dispersal in natural populations. Dispersal is typically the outcome of several interacting traits, and this complexity is reflected in its genetic architecture: while some genes of moderate to large effect can influence certain aspects of dispersal, dispersal traits are typically polygenic. Correlations among dispersal traits as well as between dispersal traits and other traits under selection are common, and the genetic basis of dispersal can be highly environment‐dependent.

By contrast, models have historically considered a highly simplified genetic architecture of dispersal. It is only recently that models have started to consider multiple loci influencing dispersal, as well as non‐additive effects such as dominance and epistasis, showing that the genetic basis of dispersal can influence evolutionary rates and outcomes, especially under non‐equilibrium conditions. For example, the number of loci controlling dispersal can influence projected rates of dispersal evolution during range shifts and corresponding demographic impacts. Incorporating more realism in the genetic architecture of dispersal is thus necessary to enable models to move beyond the purely theoretical towards making more useful predictions of evolutionary and ecological dynamics under current and future environmental conditions. To inform these advances, empirical studies need to answer outstanding questions concerning whether specific genes underlie dispersal variation, the genetic architecture of context‐dependent dispersal phenotypes and behaviours, and correlations among dispersal and other traits.

Insights into the genetic architecture of morphological traits in two passerine bird species

Knowledge about the underlying genetic architecture of phenotypic traits is needed to understand and predict evolutionary dynamics. The number of causal loci, magnitude of the effects and location in the genome are, however, still largely unknown. Here, we use genome-wide single-nucleotide polymorphism (SNP) data from two large-scale data sets on house sparrows and collared flycatchers to examine the genetic architecture of different morphological traits (tarsus length, wing length, body mass, bill depth, bill length, total and visible badge size and white wing patches). Genomic heritabilities were estimated using relatedness calculated from SNPs. The proportion of variance captured by the SNPs (SNP-based heritability) was lower in house sparrows compared with collared flycatchers, as expected given marker density (6348 SNPs in house sparrows versus 38 689 SNPs in collared flycatchers). Indeed, after downsampling to similar SNP density and sample size, this estimate was no longer markedly different between species. Chromosome-partitioning analyses demonstrated that the proportion of variance explained by each chromosome was significantly positively related to the chromosome size for some traits and, generally, that larger chromosomes tended to explain proportionally more variation than smaller chromosomes. Finally, we found two genome-wide significant associations with very small-effect sizes. One SNP on chromosome 20 was associated with bill length in house sparrows and explained 1.2% of phenotypic variation (V_P), and one SNP on chromosome 4 was associated with tarsus length in collared flycatchers (3% of V_P). Although we cannot exclude the possibility of undetected large-effect loci, our results indicate a polygenic basis for morphological traits.

Pleiotropy, constraint, and modularity in the evolution of life histories: insights from genomic analyses

Multicellular organisms display an enormous range of life history (LH) strategies and present an evolutionary conundrum; despite strong natural selection, LH traits are characterized by high levels of genetic variation. To understand the evolution of life histories and maintenance of this variation, the specific phenotypic effects of segregating alleles and the genetic networks in which they act need to be elucidated. In particular, the extent to which LH evolution is constrained by the pleiotropy of alleles contributing to LH variation is generally unknown. Here, we review recent empirical results that shed light on this question, with an emphasis on studies employing genomic analyses. While genome-scale analyses are increasingly practical and affordable, they face limitations of genetic resolution and statistical power. We describe new research approaches that we believe can produce new insights and evaluate their promise and applicability to different kinds of organisms. Two approaches seem particularly promising: experiments that manipulate selection in multiple dimensions and measure phenotypic and genomic response and analytical approaches that take into account genome-wide associations between markers and phenotypes, rather than applying a traditional marker-by-marker approach.

Building strong relationships between conservation genetics and primary industry leads to mutually beneficial genomic advances

Several reviews in the past decade have heralded the benefits of embracing high-throughput sequencing technologies to inform conservation policy and the management of threatened species, but few have offered practical advice on how to expedite the transition from conservation genetics to conservation genomics. Here, we argue that an effective and efficient way to navigate this transition is to capitalize on emerging synergies between conservation genetics and primary industry (e.g., agriculture, fisheries, forestry and horticulture). Here, we demonstrate how building strong relationships between conservation geneticists and primary industry scientists is leading to mutually-beneficial outcomes for both disciplines. Based on our collective experience as collaborative New Zealand-based scientists, we also provide insight for forging these cross-sector relationships.

Mapping QTL Contributing to Variation in Posterior Lobe Morphology between Strains of Drosophila melanogaster

Closely-related, and otherwise morphologically similar insect species frequently show striking divergence in the shape and/or size of male genital structures, a phenomenon thought to be driven by sexual selection. Comparative interspecific studies can help elucidate the evolutionary forces acting on genital structures to drive this rapid differentiation. However, genetic dissection of sexual trait divergence between species is frequently hampered by the difficulty generating interspecific recombinants. Intraspecific variation can be leveraged to investigate the genetics of rapidly-evolving sexual traits, and here we carry out a genetic analysis of variation in the posterior lobe within D. melanogaster. The lobe is a male-specific process emerging from the genital arch of D. melanogaster and three closely-related species, is essential for copulation, and shows radical divergence in form across species. There is also abundant variation within species in the shape and size of the lobe, and while this variation is considerably more subtle than that seen among species, it nonetheless provides the raw material for QTL mapping. We created an advanced intercross population from a pair of phenotypically-different inbred strains, and after phenotyping and genotyping-by-sequencing the recombinants, mapped several QTL contributing to various measures of lobe morphology. The additional generations of crossing over in our mapping population led to QTL intervals that are smaller than is typical for an F₂ mapping design. The intervals we map overlap with a pair of lobe QTL we previously identified in an independent mapping cross, potentially suggesting a level of shared genetic control of trait variation. Our QTL additionally implicate a suite of genes that have been shown to contribute to the development of the posterior lobe. These loci are strong candidates to harbor naturally-segregating sites contributing to phenotypic variation within D. melanogaster, and may also be those contributing to divergence in lobe morphology between species.

Genome-wide association mapping in a wild avian population identifies a link between genetic and phenotypic variation in a life-history trait

Understanding the genetic basis of traits involved in adaptation is a major challenge in evolutionary biology but remains poorly understood. Here, we use genome-wide association mapping using a custom 50 k single nucleotide polymorphism (SNP) array in a natural population of collared flycatchers to examine the genetic basis of clutch size, an important life-history trait in many animal species. We found evidence for an association on chromosome 18 where one SNP significant at the genome-wide level explained 3.9% of the phenotypic variance. We also detected two suggestive quantitative trait loci (QTLs) on chromosomes 9 and 26. Fitness differences among genotypes were generally weak and not significant, although there was some indication of a sex-by-genotype interaction for lifetime reproductive success at the suggestive QTL on chromosome 26. This implies that sexual antagonism may play a role in maintaining genetic variation at this QTL. Our findings provide candidate regions for a classic avian life-history trait that will be useful for future studies examining the molecular and cellular function of, as well as evolutionary mechanisms operating at, these loci.

Whole-genome resequencing of extreme phenotypes in collared flycatchers highlights the difficulty of detecting quantitative trait loci in natural populations

Dissecting the genetic basis of phenotypic variation in natural populations is a long-standing goal in evolutionary biology. One open question is whether quantitative traits are determined only by large numbers of genes with small effects, or whether variation also exists in large-effect loci. We conducted genomewide association analyses of forehead patch size (a sexually selected trait) on 81 whole-genome-resequenced male collared flycatchers with extreme phenotypes, and on 415 males sampled independent of patch size and genotyped with a 50K SNP chip. No SNPs were genomewide statistically significantly associated with patch size. Simulation-based power analyses suggest that the power to detect large-effect loci responsible for 10% of phenotypic variance was <0.5 in the genome resequencing analysis, and <0.1 in the SNP chip analysis. Reducing the recombination by two-thirds relative to collared flycatchers modestly increased power. Tripling sample size increased power to >0.8 for resequencing of extreme phenotypes (N = 243), but power remained <0.2 for the 50K SNP chip analysis (N = 1245). At least 1 million SNPs were necessary to achieve power >0.8 when analysing 415 randomly sampled phenotypes. However, power of the 50K SNP chip to detect large-effect loci was nearly 0.8 in simulations with a small effective population size of 1500. These results suggest that reliably detecting large-effect trait loci in large natural populations will often require thousands of individuals and near complete sampling of the genome. Encouragingly, far fewer individuals and loci will often be sufficient to reliably detect large-effect loci in small populations with widespread strong linkage disequilibrium.

The role of parasite-driven selection in shaping landscape genomic structure in red grouse (Lagopus lagopus scotica)

Landscape genomics promises to provide novel insights into how neutral and adaptive processes shape genome-wide variation within and among populations. However, there has been little emphasis on examining whether individual-based phenotype-genotype relationships derived from approaches such as genome-wide association (GWAS) manifest themselves as a population-level signature of selection in a landscape context. The two may prove irreconcilable as individual-level patterns become diluted by high levels of gene flow and complex phenotypic or environmental heterogeneity. We illustrate this issue with a case study that examines the role of the highly prevalent gastrointestinal nematode Trichostrongylus tenuis in shaping genomic signatures of selection in red grouse (Lagopus lagopus scotica). Individual-level GWAS involving 384 SNPs has previously identified five SNPs that explain variation in T. tenuis burden. Here, we examine whether these same SNPs display population-level relationships between T. tenuis burden and genetic structure across a small-scale landscape of 21 sites with heterogeneous parasite pressure. Moreover, we identify adaptive SNPs showing signatures of directional selection using F(ST) outlier analysis and relate population- and individual-level patterns of multilocus neutral and adaptive genetic structure to T. tenuis burden. The five candidate SNPs for parasite-driven selection were neither associated with T. tenuis burden on a population level, nor under directional selection. Similarly, there was no evidence of parasite-driven selection in SNPs identified as candidates for directional selection. We discuss these results in the context of red grouse ecology and highlight the broader consequences for the utility of landscape genomics approaches for identifying signatures of selection.

Replicated analysis of the genetic architecture of quantitative traits in two wild great tit populations

Currently, there is much debate on the genetic architecture of quantitative traits in wild populations. Is trait variation influenced by many genes of small effect or by a few genes of major effect? Where is additive genetic variation located in the genome? Do the same loci cause similar phenotypic variation in different populations? Great tits (Parus major) have been studied extensively in long‐term studies across Europe and consequently are considered an ecological ‘model organism’. Recently, genomic resources have been developed for the great tit, including a custom SNP chip and genetic linkage map. In this study, we used a suite of approaches to investigate the genetic architecture of eight quantitative traits in two long‐term study populations of great tits—one in the Netherlands and the other in the United Kingdom. Overall, we found little evidence for the presence of genes of large effects in either population. Instead, traits appeared to be influenced by many genes of small effect, with conservative estimates of the number of contributing loci ranging from 31 to 310. Despite concordance between population‐specific heritabilities, we found no evidence for the presence of loci having similar effects in both populations. While population‐specific genetic architectures are possible, an undetected shared architecture cannot be rejected because of limited power to map loci of small and moderate effects. This study is one of few examples of genetic architecture analysis in replicated wild populations and highlights some of the challenges and limitations researchers will face when attempting similar molecular quantitative genetic studies in free‐living populations.

Use of a natural hybrid zone for genomewide association mapping of craniofacial traits in the house mouse

The identification of the genes involved in morphological variation in nature is still a major challenge. Here, we explore a new approach: we combine 178 samples from a natural hybrid zone between two subspecies of the house mouse (Mus musculus domesticus and Mus musculus musculus), and high coverage of the genome (~ 145K SNPs) to identify loci underlying craniofacial shape variation. Due to the long history of recombination in the hybrid zone, high mapping resolution is anticipated. The combination of genomes from subspecies allows the mapping of both, variation within subspecies and inter-subspecific differences, thereby increasing the overall amount of causal genetic variation that can be detected. Skull and mandible shape were measured using 3D landmarks and geometric morphometrics. Using principal component axes as phenotypes, and a linear mixed model accounting for genetic relatedness in the mapping populations, we identified nine genomic regions associated with skull shape and 10 with mandible shape. High mapping resolution (median size of significant regions = 148 kb) enabled identification of single or few candidate genes in most cases. Some of the genes act as regulators or modifiers of signalling pathways relevant for morphological development and bone formation, including several with known craniofacial phenotypes in mice and humans. The significant associations combined explain 13% and 7% of the skull and mandible shape variation, respectively. In addition, a positive correlation was found between chromosomal length and proportion of variation explained. Our results suggest a complex genetic architecture for shape traits and support a polygenic model.

Population genomics of marine fishes: next-generation prospects and challenges

Over the past few years, technological advances have facilitated giant leaps forward in our ability to generate genome-wide molecular data, offering exciting opportunities for gaining new insights into the ecology and evolution of species where genomic information is still limited. Marine fishes are valuable organisms for advancing our understanding of evolution on historical and contemporary time scales, and here we highlight areas in which research on these species is likely to be particularly important in the near future. These include possibilities for gaining insights into processes on ecological time scales, identifying genomic signatures associated with population divergence under gene flow, and determining the genetic basis of phenotypic traits. We also consider future challenges pertaining to the implementation of genome-wide coverage through next-generation sequencing and genotyping methods in marine fishes. Complications associated with fast decay of linkage disequilibrium, as expected for species with large effective population sizes, and the possibility that adaptation is associated with both soft selective sweeps and polygenic selection, leaving complex genomic signatures in natural populations, are likely to challenge future studies. However, the combination of high genome coverage and new statistical developments offers promising solutions. Thus, the next generation of studies is likely to truly facilitate the transition from population genetics to population genomics in marine fishes. This transition will advance our understanding of basic evolutionary processes and will offer new possibilities for conservation and management of valuable marine resources.