Back to nature: ecological genomics of loblolly pine (Pinus taeda, Pinaceae)

SNP discovery in candidate adaptive genes using exon capture in a free-ranging alpine ungulate

Identification of genes underlying genomic signatures of natural selection is key to understanding adaptation to local conditions. We used targeted resequencing to identify SNP markers in 5321 candidate adaptive genes associated with known immunological, metabolic and growth functions in ovids and other ungulates. We selectively targeted 8161 exons in protein-coding and nearby 5' and 3' untranslated regions of chosen candidate genes. Targeted sequences were taken from bighorn sheep (Ovis canadensis) exon capture data and directly from the domestic sheep genome (Ovis aries v. 3; oviAri3). The bighorn sheep sequences used in the Dall's sheep (Ovis dalli dalli) exon capture aligned to 2350 genes on the oviAri3 genome with an average of 2 exons each. We developed a microfluidic qPCR-based SNP chip to genotype 476 Dall's sheep from locations across their range and test for patterns of selection. Using multiple corroborating approaches (lositan and bayescan), we detected 28 SNP loci potentially under selection. We additionally identified candidate loci significantly associated with latitude, longitude, precipitation and temperature, suggesting local environmental adaptation. The three methods demonstrated consistent support for natural selection on nine genes with immune and disease-regulating functions (e.g. Ovar-DRA, APC, BATF2, MAGEB18), cell regulation signalling pathways (e.g. KRIT1, PI3K, ORRC3), and respiratory health (CYSLTR1). Characterizing adaptive allele distributions from novel genetic techniques will facilitate investigation of the influence of environmental variation on local adaptation of a northern alpine ungulate throughout its range. This research demonstrated the utility of exon capture for gene-targeted SNP discovery and subsequent SNP chip genotyping using low-quality samples in a nonmodel species.

Major histocompatibility complex diversity is positively associated with stream water temperatures in proximate populations of sockeye salmon

Local adaptation to heterogeneous environments generates population diversity within species, significantly increasing ecosystem stability and flows of ecosystem services. However, few studies have isolated the specific mechanisms that create and maintain this diversity. Here, we examined the relationship between water temperature in streams used for spawning and genetic diversity at a gene involved in immune function [the major histocompatibility complex (MHC)] in 14 populations of sockeye salmon (Oncorhynchus nerka) sampled across the Wood River basin in south-western Alaska. The largest influence on MHC diversity was lake basin, but we also found a significant positive correlation between average water temperature and MHC diversity. This positive relationship between temperature and MHC diversity appears to have been produced by natural selection at very local scales rather than neutral processes, as no correlation was observed between temperature and genetic diversity at 90 neutral markers. Additionally, no significant relationship was observed between temperature variability and MHC diversity. Although lake basin was the largest driver of differences in MHC diversity, our results also demonstrate that fine-scale differences in water temperature may generate variable selection regimes in populations that spawn in habitats separated by as little as 1 km. Additionally, our results indicated that some populations may be reaching a maximum level of MHC diversity. We postulate that salmon from populations in warm streams may delay spawning until late summer to avoid thermal stress as well as the elevated levels of pathogen prevalence and virulence associated with warm temperatures earlier in the summer.

Local Adaptation in European Firs Assessed through Extensive Sampling across Altitudinal Gradients in Southern Europe

BACKGROUND

Local adaptation is a key driver of phenotypic and genetic divergence at loci responsible for adaptive traits variations in forest tree populations. Its experimental assessment requires rigorous sampling strategies such as those involving population pairs replicated across broad spatial scales.

METHODS

A hierarchical Bayesian model of selection (HBM) that explicitly considers both the replication of the environmental contrast and the hierarchical genetic structure among replicated study sites is introduced. Its power was assessed through simulations and compared to classical 'within-site' approaches (FDIST, BAYESCAN) and a simplified, within-site, version of the model introduced here (SBM).

RESULTS

HBM demonstrates that hierarchical approaches are very powerful to detect replicated patterns of adaptive divergence with low false-discovery (FDR) and false-non-discovery (FNR) rates compared to the analysis of different sites separately through within-site approaches. The hypothesis of local adaptation to altitude was further addressed by analyzing replicated Abies alba population pairs (low and high elevations) across the species' southern distribution range, where the effects of climatic selection are expected to be the strongest. For comparison, a single population pair from the closely related species A. cephalonica was also analyzed. The hierarchical model did not detect any pattern of adaptive divergence to altitude replicated in the different study sites. Instead, idiosyncratic patterns of local adaptation among sites were detected by within-site approaches.

CONCLUSION

Hierarchical approaches may miss idiosyncratic patterns of adaptation among sites, and we strongly recommend the use of both hierarchical (multi-site) and classical (within-site) approaches when addressing the question of adaptation across broad spatial scales.

Environmental Correlation Analysis for Genes Associated with Protection against Malaria

Genome-wide searches for loci involved in human resistance to malaria are currently being conducted on a large scale in Africa using case-control studies. Here, we explore the utility of an alternative approach-"environmental correlation analysis, ECA," which tests for clines in allele frequencies across a gradient of an environmental selection pressure-to identify genes that have historically protected against death from malaria. We collected genotype data from 12,425 newborns on 57 candidate malaria resistance loci and 9,756 single nucleotide polymorphisms (SNPs) selected at random from across the genome, and examined their allele frequencies for geographic correlations with long-term malaria prevalence data based on 84,042 individuals living under different historical selection pressures from malaria in coastal Kenya. None of the 57 candidate SNPs showed significant (P < 0.05) correlations in allele frequency with local malaria transmission intensity after adjusting for population structure and multiple testing. In contrast, two of the random SNPs that had highly significant correlations (P < 0.01) were in genes previously linked to malaria resistance, namely, CDH13, encoding cadherin 13, and HS3ST3B1, encoding heparan sulfate 3-O-sulfotransferase 3B1. Both proteins play a role in glycoprotein-mediated cell-cell adhesion which has been widely implicated in cerebral malaria, the most life-threatening form of this disease. Other top genes, including CTNND2 which encodes δ-catenin, a molecular partner to cadherin, were significantly enriched in cadherin-mediated pathways affecting inflammation of the brain vascular endothelium. These results demonstrate the utility of ECA in the discovery of novel genes and pathways affecting infectious disease.

Local adaptation to temperature and precipitation in naturally fragmented populations of Cephalotaxus oliveri, an endangered conifer endemic to China

Cephalotaxus oliveri is an endangered tertiary relict conifer endemic to China. The species survives in a wide range from west to east with heterogeneous climatic conditions. Precipitation and temperature are main restrictive factors for distribution of C. oliveri. In order to comprehend the mechanism of adaptive evolution to climate variation, we employed ISSR markers to detect adaptive evolution loci, to identify the association between variation in temperature and precipitation and adaptive loci, and to investigate the genetic structure for 22 C. oliveri natural populations. In total, 14 outlier loci were identified, of which five were associated with temperature and precipitation. Among outlier loci, linkage disequilibrium (LD) was high (42.86%), which also provided strong evidence for selection. In addition, C. oliveri possessed high genetic variation (93.31%) and population differentiation, which may provide raw material to evolution and accelerate local adaptation, respectively. Ecological niche modeling showed that global warming will cause a shift for populations of C. oliveri from south to north with a shrinkage of southern areas. Our results contribute to understand the potential response of conifers to climatic changes, and provide new insights for conifer resource management and conservation strategies.

Sorting duplicated loci disentangles complexities of polyploid genomes masked by genotyping by sequencing

Many plants and animals of polyploid origin are currently enjoying a genomics explosion enabled by modern sequencing and genotyping technologies. However, routine filtering of duplicated loci in most studies using genotyping by sequencing introduces an unacceptable, but often overlooked, bias when detecting selection. Retained duplicates from ancient whole-genome duplications (WGDs) may be found throughout genomes, whereas retained duplicates from recent WGDs are concentrated at distal ends of some chromosome arms. Additionally, segmental duplicates can be found at distal ends or nearly anywhere in a genome. Evidence shows that these duplications facilitate adaptation through one of two pathways: neo-functionalization or increased gene expression. Filtering duplicates removes distal ends of some chromosomes, and distal ends are especially known to harbour adaptively important genes. Thus, filtering of duplicated loci impoverishes the interpretation of genomic data as signals from contiguous duplicated genes are ignored. We review existing strategies to genotype and map duplicated loci; we focus in detail on an overlooked strategy of using gynogenetic haploids (1N) as a part of new genotyping by sequencing studies. We provide guidelines on how to use this haploid strategy for studies on polyploid-origin vertebrates including how it can be used to screen duplicated loci in natural populations. We conclude by discussing areas of research that will benefit from better inclusion of polyploid loci; we particularly stress the sometimes overlooked fact that basing genomic studies on dense maps provides value added in the form of locating and annotating outlier loci or colocating outliers into islands of divergence.

Transcriptome sequencing reveals population differentiation in gene expression linked to functional traits and environmental gradients in the South African shrub Protea repens

Understanding the environmental and genetic mechanisms underlying locally adaptive trait variation across the ranges of species is a major focus of evolutionary biology. Combining transcriptome sequencing with common garden experiments on populations spanning geographical and environmental gradients holds promise for identifying such mechanisms. The South African shrub Protea repens displays diverse phenotypes in the wild along drought and temperature gradients. We grew plants from seeds collected at 19 populations spanning this species' range, and sequenced the transcriptomes of these plants to reveal gene pathways associated with adaptive trait variation. We related expression in co-expressed gene networks to trait phenotypes measured in the common garden and to source population climate. We found that expression in gene networks correlated with source-population environment and with plant traits. In particular, the activity of gene networks enriched for growth related pathways correlated strongly with source site minimum winter temperature and with leaf size, stem diameter and height in the garden. Other gene networks with enrichments for photosynthesis related genes showed associations with precipitation. Our results strongly suggest that this species displays population-level differences in gene expression that have been shaped by source population site climate, and that are reflected in trait variation along environmental gradients.

Landscape genomic analysis of candidate genes for climate adaptation in a California endemic oak, Quercus lobata

PREMISE OF THE STUDY

The ability of California tree populations to survive anthropogenic climate change will be shaped by the geographic structure of adaptive genetic variation. Our goal is to test whether climate-associated candidate genes show evidence of spatially divergent selection in natural populations of valley oak, Quercus lobata, as preliminary indication of local adaptation.

METHODS

Using DNA from 45 individuals from 13 localities across the species' range, we sequenced portions of 40 candidate genes related to budburst/flowering, growth, osmotic stress, and temperature stress. Using 195 single nucleotide polymorphisms (SNPs), we estimated genetic differentiation across populations and correlated allele frequencies with climate gradients using single-locus and multivariate models.

RESULTS

The top 5% of FST estimates ranged from 0.25 to 0.68, yielding loci potentially under spatially divergent selection. Environmental analyses of SNP frequencies with climate gradients revealed three significantly correlated SNPs within budburst/flowering genes and two SNPs within temperature stress genes with mean annual precipitation, after controlling for multiple testing. A redundancy model showed a significant association between SNPs and climate variables and revealed a similar set of SNPs with high loadings on the first axis. In the RDA, climate accounted for 67% of the explained variation, when holding climate constant, in contrast to a putatively neutral SSR data set where climate accounted for only 33%.

CONCLUSIONS

Population differentiation and geographic gradients of allele frequencies in climate-associated functional genes in Q. lobata provide initial evidence of adaptive genetic variation and background for predicting population response to climate change.

Gene flow and natural selection shape spatial patterns of genes in tree populations: implications for evolutionary processes and applications

A central question in evolutionary biology is how gene flow and natural selection shape geographic patterns of genotypic and phenotypic variation. My overall research program has pursued this question in tree populations through complementary lines of inquiry. First, through studies of contemporary pollen and seed movement, I have studied how limited gene movement creates fine-scale genetic structure, while long-distance gene flow promotes connectivity. My collaborators and I have provided new tools to study these processes at a landscape scale as well as statistical tests to determine whether changes in landscape conditions or dispersal vectors affect gene movement. Second, my research on spatial patterns of genetic variation has investigated the interacting impacts of geography and climate on gene flow and selection. Third, using next-generation genomic tools, I am now studying genetic variation on the landscape to find initial evidence of climate-associated local adaptation and epigenetic variation to explore its role in plant response to the climate. By integrating these separate lines of inquiry, this research provides specific insight into real-world mechanisms shaping evolution in tree populations and potential impacts of landscape transformation and climate change on these populations, with the prospective goal of contributing to their management and conservation.

Evolutionary Quantitative Genomics of Populus trichocarpa

Forest trees generally show high levels of local adaptation and efforts focusing on understanding adaptation to climate will be crucial for species survival and management. Here, we address fundamental questions regarding the molecular basis of adaptation in undomesticated forest tree populations to past climatic environments by employing an integrative quantitative genetics and landscape genomics approach. Using this comprehensive approach, we studied the molecular basis of climate adaptation in 433 Populus trichocarpa (black cottonwood) genotypes originating across western North America. Variation in 74 field-assessed traits (growth, ecophysiology, phenology, leaf stomata, wood, and disease resistance) was investigated for signatures of selection (comparing Q_ST -F_ST) using clustering of individuals by climate of origin (temperature and precipitation). 29,354 SNPs were investigated employing three different outlier detection methods and marker-inferred relatedness was estimated to obtain the narrow-sense estimate of population differentiation in wild populations. In addition, we compared our results with previously assessed selection of candidate SNPs using the 25 topographical units (drainages) across the P. trichocarpa sampling range as population groupings. Narrow-sense Q_ST for 53% of distinct field traits was significantly divergent from expectations of neutrality (indicating adaptive trait variation); 2,855 SNPs showed signals of diversifying selection and of these, 118 SNPs (within 81 genes) were associated with adaptive traits (based on significant Q_ST). Many SNPs were putatively pleiotropic for functionally uncorrelated adaptive traits, such as autumn phenology, height, and disease resistance. Evolutionary quantitative genomics in P. trichocarpa provides an enhanced understanding regarding the molecular basis of climate-driven selection in forest trees and we highlight that important loci underlying adaptive trait variation also show relationship to climate of origin. We consider our approach the most comprehensive, as it uncovers the molecular mechanisms of adaptation using multiple methods and tests. We also provide a detailed outline of the required analyses for studying adaptation to the environment in a population genomics context to better understand the species’ potential adaptive capacity to future climatic scenarios.

Genetic Adaptation to Climate in White Spruce Involves Small to Moderate Allele Frequency Shifts in Functionally Diverse Genes

Understanding the genetic basis of adaptation to climate is of paramount importance for preserving and managing genetic diversity in plants in a context of climate change. Yet, this objective has been addressed mainly in short-lived model species. Thus, expanding knowledge to nonmodel species with contrasting life histories, such as forest trees, appears necessary. To uncover the genetic basis of adaptation to climate in the widely distributed boreal conifer white spruce (Picea glauca), an environmental association study was conducted using 11,085 single nucleotide polymorphisms representing 7,819 genes, that is, approximately a quarter of the transcriptome.

Linear and quadratic regressions controlling for isolation-by-distance, and the Random Forest algorithm, identified several dozen genes putatively under selection, among which 43 showed strongest signals along temperature and precipitation gradients. Most of them were related to temperature. Small to moderate shifts in allele frequencies were observed. Genes involved encompassed a wide variety of functions and processes, some of them being likely important for plant survival under biotic and abiotic environmental stresses according to expression data. Literature mining and sequence comparison also highlighted conserved sequences and functions with angiosperm homologs.

Our results are consistent with theoretical predictions that local adaptation involves genes with small frequency shifts when selection is recent and gene flow among populations is high. Accordingly, genetic adaptation to climate in P. glauca appears to be complex, involving many independent and interacting gene functions, biochemical pathways, and processes. From an applied perspective, these results shall lead to specific functional/association studies in conifers and to the development of markers useful for the conservation of genetic resources.

Genome-wide patterns of recombination, linkage disequilibrium and nucleotide diversity from pooled resequencing and single nucleotide polymorphism genotyping unlock the evolutionary history of Eucalyptus grandis

We used high-density single nucleotide polymorphism (SNP) data and whole-genome pooled resequencing to examine the landscape of population recombination (ρ) and nucleotide diversity (ϴw ), assess the extent of linkage disequilibrium (r(2) ) and build the highest density linkage maps for Eucalyptus. At the genome-wide level, linkage disequilibrium (LD) decayed within c. 4-6 kb, slower than previously reported from candidate gene studies, but showing considerable variation from absence to complete LD up to 50 kb. A sharp decrease in the estimate of ρ was seen when going from short to genome-wide inter-SNP distances, highlighting the dependence of this parameter on the scale of observation adopted. Recombination was correlated with nucleotide diversity, gene density and distance from the centromere, with hotspots of recombination enriched for genes involved in chemical reactions and pathways of the normal metabolic processes. The high nucleotide diversity (ϴw = 0.022) of E. grandis revealed that mutation is more important than recombination in shaping its genomic diversity (ρ/ϴw = 0.645). Chromosome-wide ancestral recombination graphs allowed us to date the split of E. grandis (1.7-4.8 million yr ago) and identify a scenario for the recent demographic history of the species. Our results have considerable practical importance to Genome Wide Association Studies (GWAS), while indicating bright prospects for genomic prediction of complex phenotypes in eucalypt breeding.

Common garden experiments in the genomic era: new perspectives and opportunities

The study of local adaptation is rendered difficult by many evolutionary confounding phenomena (for example, genetic drift and demographic history). When complex traits are involved in local adaptation, phenomena such as phenotypic plasticity further hamper evolutionary biologists to study the complex relationships between phenotype, genotype and environment. In this perspective paper, we suggest that the common garden experiment, specifically designed to deal with phenotypic plasticity, has a clear role to play in the study of local adaptation, even (if not specifically) in the genomic era. After a quick review of some high-throughput genotyping protocols relevant in the context of a common garden, we explore how to improve common garden analyses with dense marker panel data and recent statistical methods. We then show how combining approaches from population genomics and genome-wide association studies with the settings of a common garden can yield to a very efficient, thorough and integrative study of local adaptation. Especially, evidence from genomic (for example, genome scan) and phenotypic origins constitute independent insights into the possibility of local adaptation scenarios, and genome-wide association studies in the context of a common garden experiment allow to decipher the genetic bases of adaptive traits.

Landscape genomics reveal signatures of local adaptation in barley (Hordeum vulgare L.)

Land plants are sessile organisms that cannot escape the adverse climatic conditions of a given environment. Hence, adaptation is one of the solutions to surviving in a challenging environment. This study was aimed at detecting adaptive loci in barley landraces that are affected by selection. To that end, a diverse population of barley landraces was analyzed using the genotyping by sequencing approach. Climatic data for altitude, rainfall and temperature were collected from 61 weather sites near the origin of selected landraces across Ethiopia. Population structure analysis revealed three groups whereas spatial analysis accounted significant similarities at shorter geographic distances (< 40 Km) among barley landraces. Partitioning the variance between climate variables and geographic distances indicated that climate variables accounted for most of the explainable genetic variation. Markers by climatic variables association analysis resulted in altogether 18 and 62 putative adaptive loci using Bayenv and latent factor mixed model (LFMM), respectively. Subsequent analysis of the associated SNPs revealed putative candidate genes for plant adaptation. This study highlights the presence of putative adaptive loci among barley landraces representing original gene pool of the farming communities.

Fifteen years of genomewide scans for selection: trends, lessons and unaddressed genetic sources of complication

Genomewide scans for natural selection (GWSS) have become increasingly common over the last 15 years due to increased availability of genome-scale genetic data. Here, we report a representative survey of GWSS from 1999 to present and find that (i) between 1999 and 2009, 35 of 49 (71%) GWSS focused on human, while from 2010 to present, only 38 of 83 (46%) of GWSS focused on human, indicating increased focus on nonmodel organisms; (ii) the large majority of GWSS incorporate interpopulation or interspecific comparisons using, for example F(ST), cross-population extended haplotype homozygosity or the ratio of nonsynonymous to synonymous substitutions; (iii) most GWSS focus on detection of directional selection rather than other modes such as balancing selection; and (iv) in human GWSS, there is a clear shift after 2004 from microsatellite markers to dense SNP data. A survey of GWSS meant to identify loci positively selected in response to severe hypoxic conditions support an approach to GWSS in which a list of a priori candidate genes based on potential selective pressures are used to filter the list of significant hits a posteriori. We also discuss four frequently ignored determinants of genomic heterogeneity that complicate GWSS: mutation, recombination, selection and the genetic architecture of adaptive traits. We recommend that GWSS methodology should better incorporate aspects of genomewide heterogeneity using empirical estimates of relevant parameters and/or realistic, whole-chromosome simulations to improve interpretation of GWSS results. Finally, we argue that knowledge of potential selective agents improves interpretation of GWSS results and that new methods focused on correlations between environmental variables and genetic variation can help automate this approach.

Contrasting patterns of genetic diversity across the ranges of Pinus monticola and P. strobus: a comparison between eastern and western North American postglacial colonization histories

• Premises of the study: Understanding the influence of recent glacial and postglacial periods on species' distributions is key for predicting the effects of future environmental changes. We investigated the influence of two physiographic landscapes on population structure and postglacial colonization of two white pine species of contrasting habitats: P. monticola, which occurs in the highly mountainous region of western North America, and P. strobus, which occurs in a much less mountainous area in eastern North America.•

METHODS

To characterize the patterns of genetic diversity and population structure across the ranges of both species, 158 and 153 single nucleotide polymorphism (SNP) markers derived from expressed genes were genotyped on range-wide samples of 61 P. monticola and 133 P. strobus populations, respectively.•

KEY RESULTS

In P. monticola, a steep latitudinal decrease in genetic diversity likely resulted from postglacial colonization involving rare long-distance dispersal (LDD) events. In contrast, no geographic patterns of diversity were detected in P. strobus, suggesting recolonization via a gradually advancing front or frequent LDD events. For each species, structure analyses identified two distinct southern and northern genetic groups that likely originated from two different glacial lineages. At a finer scale, and for the two species, smaller subgroups were detected that could be remnants of cryptic refugia.•

CONCLUSION

During postglacial colonization, the western and eastern North American landscapes had different impacts on genetic signatures in P. monticola compared with P. strobus. We discuss the importance of our findings for conservation programs and predictions of species' response to climate change.

Detecting adaptive evolution based on association with ecological gradients: orientation matters!

Population genetic signatures of local adaptation are frequently investigated by identifying loci with allele frequencies that exhibit high correlation with ecological variables. One difficulty with this approach is that ecological associations might be confounded by geographic variation at selectively neutral loci. Here, we consider populations that underwent spatial expansion from their original range, and for which geographical variation of adaptive allele frequency coincides with habitat gradients. Using range expansion simulations, we asked whether our ability to detect genomic regions involved in adaptation could be impacted by the orientation of the ecological gradients. For three ecological association methods tested, we found, counter-intuitively, fewer false-positive associations when ecological gradients aligned along the main axis of expansion than when they aligned along any other direction. This result has important consequences for the analysis of genomic data under non-equilibrium population genetic models. Alignment of gradients with expansion axes is likely to be common in scenarios in which expanding species track their ecological niche during climate change while adapting to changing environments at their rear edge.

Genomic patterns of species diversity and divergence in Eucalyptus

We examined genome-wide patterns of DNA sequence diversity and divergence among six species of the important tree genus Eucalyptus and investigated their relationship with genomic architecture. Using c. 90 range-wide individuals of each Eucalyptus species (E. grandis, E. urophylla, E. globulus, E. nitens, E. dunnii and E. camaldulensis), genetic diversity and divergence were estimated from 2840 polymorphic diversity arrays technology markers covering the 11 chromosomes. Species differentiating markers (SDMs) identified in each of 15 pairwise species comparisons, along with species diversity (HHW ) and divergence (FST ), were projected onto the E. grandis reference genome. Across all species comparisons, SDMs totalled 1.1-5.3% of markers and were widely distributed throughout the genome. Marker divergence (FST and SDMs) and diversity differed among and within chromosomes. Patterns of diversity and divergence were broadly conserved across species and significantly associated with genomic features, including the proximity of markers to genes, the relative number of clusters of tandem duplications, and gene density within or among chromosomes. These results suggest that genomic architecture influences patterns of species diversity and divergence in the genus. This influence is evident across the six species, encompassing diverse phylogenetic lineages, geography and ecology.

Micro- and macro-geographic scale effect on the molecular imprint of selection and adaptation in Norway spruce

Forest tree species of temperate and boreal regions have undergone a long history of demographic changes and evolutionary adaptations. The main objective of this study was to detect signals of selection in Norway spruce (Picea abies [L.] Karst), at different sampling-scales and to investigate, accounting for population structure, the effect of environment on species genetic diversity. A total of 384 single nucleotide polymorphisms (SNPs) representing 290 genes were genotyped at two geographic scales: across 12 populations distributed along two altitudinal-transects in the Alps (micro-geographic scale), and across 27 populations belonging to the range of Norway spruce in central and south-east Europe (macro-geographic scale). At the macrogeographic scale, principal component analysis combined with Bayesian clustering revealed three major clusters, corresponding to the main areas of southern spruce occurrence, i.e. the Alps, Carpathians, and Hercynia. The populations along the altitudinal transects were not differentiated. To assess the role of selection in structuring genetic variation, we applied a Bayesian and coalescent-based F_ST-outlier method and tested for correlations between allele frequencies and climatic variables using regression analyses. At the macro-geographic scale, the F_ST-outlier methods detected together 11 F_ST-outliers. Six outliers were detected when the same analyses were carried out taking into account the genetic structure. Regression analyses with population structure correction resulted in the identification of two (micro-geographic scale) and 38 SNPs (macro-geographic scale) significantly correlated with temperature and/or precipitation. Six of these loci overlapped with F_ST-outliers, among them two loci encoding an enzyme involved in riboflavin biosynthesis and a sucrose synthase. The results of this study indicate a strong relationship between genetic and environmental variation at both geographic scales. It also suggests that an integrative approach combining different outlier detection methods and population sampling at different geographic scales is useful to identify loci potentially involved in adaptation.

Molecular proxies for climate maladaptation in a long-lived tree (Pinus pinaster Aiton, Pinaceae)

Understanding adaptive genetic responses to climate change is a main challenge for preserving biological diversity. Successful predictive models for climate-driven range shifts of species depend on the integration of information on adaptation, including that derived from genomic studies. Long-lived forest trees can experience substantial environmental change across generations, which results in a much more prominent adaptation lag than in annual species. Here, we show that candidate-gene SNPs (single nucleotide polymorphisms) can be used as predictors of maladaptation to climate in maritime pine (Pinus pinaster Aiton), an outcrossing long-lived keystone tree. A set of 18 SNPs potentially associated with climate, 5 of them involving amino acid-changing variants, were retained after performing logistic regression, latent factor mixed models, and Bayesian analyses of SNP-climate correlations. These relationships identified temperature as an important adaptive driver in maritime pine and highlighted that selective forces are operating differentially in geographically discrete gene pools. The frequency of the locally advantageous alleles at these selected loci was strongly correlated with survival in a common garden under extreme (hot and dry) climate conditions, which suggests that candidate-gene SNPs can be used to forecast the likely destiny of natural forest ecosystems under climate change scenarios. Differential levels of forest decline are anticipated for distinct maritime pine gene pools. Geographically defined molecular proxies for climate adaptation will thus critically enhance the predictive power of range-shift models and help establish mitigation measures for long-lived keystone forest trees in the face of impending climate change.

Genetic differentiation and evolutionary adaptation in Cryptomeria japonica

Local adaptation of plant species is a central issue for survival during global climate change, especially for long-lived forest trees, with their lengthy regeneration time and spatially limited gene flow. Identification of loci and/or genomic regions associated with local adaptation is necessary for knowledge of both evolution and molecular breeding for climate change. Cryptomeria japonica is an important species for forestry in Japan; it has a broad natural distribution and can survive in a range of different environments. The genetic structure of 14 natural populations of this species was investigated using 3930 SNP markers. Populations on the Pacific Ocean side of Japan are clearly different from those on the Japan Sea side, as discussed in previous studies. Structure analysis and population network trees show that peripheral populations, including the most northerly and southerly ones, have unique features. We found that the genetic differentiation coefficient is low, F_ST = 0.05, although it must account for the presence of important genes associated with adaptation to specific environments. In total, 208 outlier loci were detected, of which 43 were associated with environmental variables. Four clumped regions of outlier loci were detected in the genome by linkage analysis. Linkage disequilibrium (LD) was quite high in these clumps of outlier loci, which were found in linkage groups (LGs) 2, 7, 10, and 11, especially between populations of two varieties, and when interchromosomal LD was also detected. The LG7 region is characteristic of the Yakushima population, which is a large, isolated, peripheral population occupying a specific environment resulting from isolation combined with volcanic activity in the region. The detected LD may provide strong evidence for selection between varieties.

Cross-species outlier detection reveals different evolutionary pressures between sister species

Lodgepole pine (Pinus contorta var. latifolia) and jack pine (Pinus banksiana) hybridize in western Canada, an area of recent mountain pine beetle range expansion. Given the heterogeneity of the environment, and indications of local adaptation, there are many unknowns regarding the response of these forests to future outbreaks. To better understand this we aim to identify genetic regions that have adaptive potential. We used data collected on 472 single nucleotide polymorphism (SNP) loci from 576 tree samples collected across 13 lodgepole pine-dominated sites and four jack pine-dominated sites. We looked at the relationship of genetic diversity with the environment, and we identified candidate loci using both frequency-based (arlequin and bayescan) and correlation-based (matsam and bayenv) methods. We found contrasting relationships between environmental variation and genetic diversity for the species. While we identified a number of candidate outliers (34 in lodgepole pine, 25 in jack pine, and 43 interspecific loci), we did not find any loci in common between lodgepole and jack pine. Many of the outlier loci identified were correlated with environmental variation. Using rigorous criteria we have been able to identify potential outlier SNPs. We have also found evidence of contrasting environmental adaptations between lodgepole and jack pine which could have implications for beetle spread risk.

Targeting environmental adaptation in the monocot model Brachypodium distachyon: a multi-faceted approach

BACKGROUND

The local environment plays a major role in the spatial distribution of plant populations. Natural plant populations have an extremely poor displacing capacity, so their continued survival in a given environment depends on how well they adapt to local pedoclimatic conditions. Genomic tools can be used to identify adaptive traits at a DNA level and to further our understanding of evolutionary processes. Here we report the use of genotyping-by-sequencing on local groups of the sequenced monocot model species Brachypodium distachyon. Exploiting population genetics, landscape genomics and genome wide association studies, we evaluate B. distachyon role as a natural probe for identifying genomic loci involved in environmental adaptation.

RESULTS

Brachypodium distachyon individuals were sampled in nine locations with different ecologies and characterized with 16,697 SNPs. Variations in sequencing depth showed consistent patterns at 8,072 genomic bins, which were significantly enriched in transposable elements. We investigated the structuration and diversity of this collection, and exploited climatic data to identify loci with adaptive significance through i) two different approaches for genome wide association analyses considering climatic variation, ii) an outlier loci approach, and iii) a canonical correlation analysis on differentially sequenced bins. A linkage disequilibrium-corrected Bonferroni method was applied to filter associations. The two association methods jointly identified a set of 15 genes significantly related to environmental adaptation. The outlier loci approach revealed that 5.7% of the loci analysed were under selection. The canonical correlation analysis showed that the distribution of some differentially sequenced regions was associated to environmental variation.

CONCLUSIONS

We show that the multi-faceted approach used here targeted different components of B. distachyon adaptive variation, and may lead to the discovery of genes related to environmental adaptation in natural populations. Its application to a model species with a fully sequenced genome is a modular strategy that enables the stratification of biological material and thus improves our knowledge of the functional loci determining adaptation in near-crop species. When coupled with population genetics and measures of genomic structuration, methods coming from genome wide association studies may lead to the exploitation of model species as natural probes to identify loci related to environmental adaptation.

Characterisation of adaptive genetic diversity in environmentally contrasted populations of Eucalyptus camaldulensis Dehnh. (river red gum)

As an increasing number of ecosystems face departures from long standing environmental conditions under climate change, our understanding of the capacity of species to adapt will become important for directing conservation and management of biodiversity. Insights into the potential for genetic adaptation might be gained by assessing genomic signatures of adaptation to historic or prevailing environmental conditions. The river red gum (Eucalyptus camaldulensis Dehnh.) is a widespread Australian eucalypt inhabiting riverine and floodplain habitats which spans strong environmental gradients. We investigated the effects of adaptation to environment on population level genetic diversity of E. camaldulensis, examining SNP variation in candidate gene loci sampled across 20 climatically diverse populations approximating the species natural distribution. Genetic differentiation among populations was high (F(ST) = 17%), exceeding previous estimates based on neutral markers. Complementary statistical approaches identified 6 SNP loci in four genes (COMT, Dehydrin, ERECTA and PIP2) which, after accounting for demographic effects, exhibited higher than expected levels of genetic differentiation among populations and whose allelic variation was associated with local environment. While this study employs but a small proportion of available diversity in the eucalyptus genome, it draws our attention to the potential for application of wide spread eucalypt species to test adaptive hypotheses.

Genome-wide association implicates numerous genes underlying ecological trait variation in natural populations of Populus trichocarpa

In order to uncover the genetic basis of phenotypic trait variation, we used 448 unrelated wild accessions of black cottonwood (Populus trichocarpa) from much of its range in western North America. Extensive data from large-scale trait phenotyping (with spatial and temporal replications within a common garden) and genotyping (with a 34 K Populus single nucleotide polymorphism (SNP) array) of all accessions were used for gene discovery in a genome-wide association study (GWAS). We performed GWAS with 40 biomass, ecophysiology and phenology traits and 29,355 filtered SNPs representing 3518 genes. The association analyses were carried out using a Unified Mixed Model accounting for population structure effects among accessions. We uncovered 410 significant SNPs using a Bonferroni-corrected threshold (P<1.7×10(-6)). Markers were found across 19 chromosomes, explained 1-13% of trait variation, and implicated 275 unique genes in trait associations. Phenology had the largest number of associated genes (240 genes), followed by biomass (53 genes) and ecophysiology traits (25 genes). The GWAS results propose numerous loci for further investigation. Many traits had significant associations with multiple genes, underscoring their genetic complexity. Genes were also identified with multiple trait associations within and/or across trait categories. In some cases, traits were genetically correlated while in others they were not.

Complex patterns of local adaptation in teosinte

Populations of widely distributed species encounter and must adapt to local environmental conditions. However, comprehensive characterization of the genetic basis of adaptation is demanding, requiring genome-wide genotype data, multiple sampled populations, and an understanding of population structure and potential selection pressures. Here, we used single-nucleotide polymorphism genotyping and data on numerous environmental variables to describe the genetic basis of local adaptation in 21 populations of teosinte, the wild ancestor of maize. We found complex hierarchical genetic structure created by altitude, dispersal events, and admixture among subspecies, which complicated identification of locally beneficial alleles. Patterns of linkage disequilibrium revealed four large putative inversion polymorphisms showing clinal patterns of frequency. Population differentiation and environmental correlations suggest that both inversions and intergenic polymorphisms are involved in local adaptation.

Genome-wide admixture and ecological niche modelling reveal the maintenance of species boundaries despite long history of interspecific gene flow

The maintenance of species boundaries despite interspecific gene flow has been a continuous source of interest in evolutionary biology. Many hybridizing species have porous genomes with regions impermeable to introgression, conferring reproductive barriers between species. We used ecological niche modelling to study the glacial and postglacial recolonization patterns between the widely hybridizing spruce species Picea glauca and P. engelmannii in western North America. Genome-wide estimates of admixture based on a panel of 311 candidate gene single nucleotide polymorphisms (SNP) from 290 genes were used to assess levels of admixture and introgression and to identify loci putatively involved in adaptive differences or reproductive barriers between species. Our palaeoclimatic modelling suggests that these two closely related species have a long history of hybridization and introgression, dating to at least 21,000 years ago, yet species integrity is maintained by a combination of strong environmental selection and reduced current interspecific gene flow. Twenty loci showed evidence of divergent selection, including six loci that were both Fst outliers and associated with climatic gradients, and fourteen loci that were either outliers or showed associations with climate. These included genes responsible for carbohydrate metabolism, signal transduction and transcription factors.

Ecological genomics and process modeling of local adaptation to climate

Locally adapted genotypes have higher fitness in their native site in comparison to foreign genotypes. Recent studies have demonstrated both local adaptation to and genomic associations with a range of climate variables. For climate adaptation, the most common genomic pattern is conditional neutrality, as proven by weak across-environment correlations, frequent SNP×environment interactions, and the topology of some developmental and physiological pathways potentially involved in local adaptation. Genomic association approaches readily translate to non-model systems, and genetically explicit climate envelope models will predict future species' distributions under changing climates. Here, we review recent evidence for local adaptation to climate, focusing primarily on the model system, Arabidopsis thaliana, and on studies incorporating genomic tools into field studies or climate analyses.

Genome-wide distribution of genetic diversity and linkage disequilibrium in a mass-selected population of maritime pine

Background

The accessibility of high-throughput genotyping technologies has contributed greatly to the development of genomic resources in non-model organisms. High-density genotyping arrays have only recently been developed for some economically important species such as conifers. The potential for using genomic technologies in association mapping and breeding depends largely on the genome wide patterns of diversity and linkage disequilibrium in current breeding populations. This study aims to deepen our knowledge regarding these issues in maritime pine, the first species used for reforestation in south western Europe.

Results

Using a new map merging algorithm, we first established a 1,712 cM composite linkage map (comprising 1,838 SNP markers in 12 linkage groups) by bringing together three already available genetic maps. Using rigorous statistical testing based on kernel density estimation and resampling we identified cold and hot spots of recombination. In parallel, 186 unrelated trees of a mass-selected population were genotyped using a 12k-SNP array. A total of 2,600 informative SNPs allowed to describe historical recombination, genetic diversity and genetic structure of this recently domesticated breeding pool that forms the basis of much of the current and future breeding of this species. We observe very low levels of population genetic structure and find no evidence that artificial selection has caused a reduction in genetic diversity. By combining these two pieces of information, we provided the map position of 1,671 SNPs corresponding to 1,192 different loci. This made it possible to analyze the spatial pattern of genetic diversity (H_e) and long distance linkage disequilibrium (LD) along the chromosomes. We found no particular pattern in the empirical variogram of H_e across the 12 linkage groups and, as expected for an outcrossing species with large effective population size, we observed an almost complete lack of long distance LD.

Conclusions

These results are a stepping stone for the development of strategies for studies in population genomics, association mapping and genomic prediction in this economical and ecologically important forest tree species.

Unique features of the loblolly pine (Pinus taeda L.) megagenome revealed through sequence annotation

The largest genus in the conifer family Pinaceae is Pinus, with over 100 species. The size and complexity of their genomes (∼20-40 Gb, 2n = 24) have delayed the arrival of a well-annotated reference sequence. In this study, we present the annotation of the first whole-genome shotgun assembly of loblolly pine (Pinus taeda L.), which comprises 20.1 Gb of sequence. The MAKER-P annotation pipeline combined evidence-based alignments and ab initio predictions to generate 50,172 gene models, of which 15,653 are classified as high confidence. Clustering these gene models with 13 other plant species resulted in 20,646 gene families, of which 1554 are predicted to be unique to conifers. Among the conifer gene families, 159 are composed exclusively of loblolly pine members. The gene models for loblolly pine have the highest median and mean intron lengths of 24 fully sequenced plant genomes. Conifer genomes are full of repetitive DNA, with the most significant contributions from long-terminal-repeat retrotransposons. In depth analysis of the tandem and interspersed repetitive content yielded a combined estimate of 82%.

Environmental variables explain genetic structure in a beetle-associated nematode

The distribution of a species is a complex expression of its ecological and evolutionary history and integrating population genetic, environmental, and ecological data can provide new insights into the effects of the environment on the population structure of species. Previous work demonstrated strong patterns of genetic differentiation in natural populations of the hermaphroditic nematode Pristionchus pacificus in its La Réunion Island habitat, but gave no clear understanding of the role of the environment in structuring this variation. Here, we present what is to our knowledge the first study to statistically evaluate the role of the environment in shaping the structure and distribution of nematode populations. We test the hypothesis that genetic structure in P. pacificus is influenced by environmental variables, by combining population genetic analyses of microsatellite data from 18 populations and 370 strains, with multivariate statistics on environmental data, and species distribution modelling. We assess and quantify the relative importance of environmental factors (geographic distance, altitude, temperature, precipitation, and beetle host) on genetic variation among populations. Despite the fact that geographic populations of P. pacificus comprise vast genetic diversity sourced from multiple ancestral lineages, we find strong evidence for local associations between environment and genetic variation. Further, we show that significantly more genetic variation in P. pacificus populations is explained by environmental variation than by geographic distances. This supports a strong role for environmental heterogeneity vs. genetic drift in the divergence of populations, which we suggest may be influenced by adaptive forces.

On the stability of the Bayenv method in assessing human SNP-environment associations

Background

Phenotypic variation along environmental gradients has been documented among and within many species, and in some cases, genetic variation has been shown to be associated with these gradients. Bayenv is a relatively new method developed to detect patterns of polymorphisms associated with environmental gradients. Using a Bayesian Markov Chain Monte Carlo (MCMC) approach, Bayenv evaluates whether a linear model relating population allele frequencies to environmental variables is more probable than a null model based on observed frequencies of neutral markers. Although this method has been used to detect environmental adaptation in a number of species, including humans, plants, fish, and mosquitoes, stability between independent runs of this MCMC algorithm has not been characterized. In this paper, we explore the variability of results between runs and the factors contributing to it.

Results

Independent runs of the Bayenv program were carried out using genome-wide single-nucleotide polymorphism (SNP) data from samples from 60 worldwide human populations following previous applications of the Bayenv method. To assess factors contributing to the method's stability, we used varying numbers of MCMC iterations and also analyzed a second modified data set that excluded two Siberian populations with extreme climate variables. Between any two runs, correlations between Bayes factors and the overlap of SNPs in the empirical p value tails were surprisingly low. Enrichments of genic versus non-genic SNPs in the empirical tails were more robust than the empirical p values; however, the significance of the enrichments for some environmental variables still varied among runs, contradicting previously published conclusions. Runs with a greater number of MCMC iterations slightly reduced run-to-run variability, and excluding the Siberian populations did not have a large effect on the stability of the runs.

Conclusions

Because of high run-to-run variability, we advise against making conclusions about genome-wide patterns of adaptation based on only one run of the Bayenv algorithm and recommend caution in interpreting previous studies that have used only one run. Moving forward, we suggest carrying out multiple independent runs of Bayenv and averaging Bayes factors between runs to produce more stable and reliable results. With these modifications, future discoveries of environmental adaptation within species using the Bayenv method will be more accurate, interpretable, and easily compared between studies.

In situ genetic association for serotiny, a fire-related trait, in Mediterranean maritime pine (Pinus pinaster)

Wildfire is a major ecological driver of plant evolution. Understanding the genetic basis of plant adaptation to wildfire is crucial, because impending climate change will involve fire regime changes worldwide. We studied the molecular genetic basis of serotiny, a fire-related trait, in Mediterranean maritime pine using association genetics. A single nucleotide polymorphism (SNP) set was used to identify genotype : phenotype associations in situ in an unstructured natural population of maritime pine (eastern Iberian Peninsula) under a mixed-effects model framework. RR-BLUP was used to build predictive models for serotiny in this region. Model prediction power outside the focal region was tested using independent range-wide serotiny data. Seventeen SNPs were potentially associated with serotiny, explaining approximately 29% of the trait phenotypic variation in the eastern Iberian Peninsula. Similar prediction power was found for nearby geographical regions from the same maternal lineage, but not for other genetic lineages. Association genetics for ecologically relevant traits evaluated in situ is an attractive approach for forest trees provided that traits are under strong genetic control and populations are unstructured, with large phenotypic variability. This will help to extend the research focus to ecological keystone non-model species in their natural environments, where polymorphisms acquired their adaptive value.

Environmental versus geographical determinants of genetic structure in two subalpine conifers

Alpine ecosystems are facing rapid human-induced environmental changes, and so more knowledge about tree adaptive potential is needed. This study investigated the relative role of isolation by distance (IBD) versus isolation by adaptation (IBA) in explaining population genetic structure in Abies alba and Larix decidua, based on 231 and 233 single nucleotide polymorphisms (SNPs) sampled across 36 and 22 natural populations, respectively, in the Alps and Apennines. Genetic structure was investigated for both geographical and environmental groups, using analysis of molecular variance (AMOVA). For each species, nine environmental groups were defined using climate variables selected from a multiple factor analysis. Complementary methods were applied to identify outliers based on these groups, and to test for IBD versus IBA. AMOVA showed weak but significant genetic structure for both species, with higher values in L. decidua. Among the potential outliers detected, up to two loci were found for geographical groups and up to seven for environmental groups. A stronger effect of IBD than IBA was found in both species; nevertheless, once spatial effects had been removed, temperature and soil in A. alba, and precipitation in both species, were relevant factors explaining genetic structure. Based on our findings, in the Alpine region, genetic structure seems to be affected by both geographical isolation and environmental gradients, creating opportunities for local adaptation.

Ecological genomics of local adaptation

It is increasingly important to improve our understanding of the genetic basis of local adaptation because of its relevance to climate change, crop and animal production, and conservation of genetic resources. Phenotypic patterns that are generated by spatially varying selection have long been observed, and both genetic mapping and field experiments provided initial insights into the genetic architecture of adaptive traits. Genomic tools are now allowing genome-wide studies, and recent theoretical advances can help to design research strategies that combine genomics and field experiments to examine the genetics of local adaptation. These advances are also allowing research in non-model species, the adaptation patterns of which may differ from those of traditional model species.

Demonstration of genome-wide association studies for identifying markers for wood property and male strobili traits in Cryptomeria japonica

Genome-wide association studies (GWAS) are an alternative to bi-parental QTL mapping in long-lived perennials. In the present study, we examined the potential of GWAS in conifers using 367 unrelated plus trees of Cryptomeria japonica D. Don, which is the most widely planted and commercially important tree species in Japan, and tried to detect significant associations between wood property traits and quantity of male strobili on the one hand, and 1,032 single nucleotide polymorphisms (SNPs) assigned to 1,032 genes on the other. Association analysis was performed with the mixed linear model taking into account kinship relationships and subpopulation structure. In total, 6 SNPs were found to have significant associations with the variations in phenotype. These SNPs were not associated with the positions of known genes and QTLs that have been reported to date, thus they may identify novel QTLs. These 6 SNPs were all found in sequences showing similarities with known genes, although further analysis is required to dissect the ways in which they affect wood property traits and abundance of male strobili. These presumptive QTL loci provide opportunities for improvement of C. japonica, based on a marker approach. The results suggest that GWAS has potential for use in future breeding programs in C. japonica.

Vitis phylogenomics: hybridization intensities from a SNP array outperform genotype calls

Understanding relationships among species is a fundamental goal of evolutionary biology. Single nucleotide polymorphisms (SNPs) identified through next generation sequencing and related technologies enable phylogeny reconstruction by providing unprecedented numbers of characters for analysis. One approach to SNP-based phylogeny reconstruction is to identify SNPs in a subset of individuals, and then to compile SNPs on an array that can be used to genotype additional samples at hundreds or thousands of sites simultaneously. Although powerful and efficient, this method is subject to ascertainment bias because applying variation discovered in a representative subset to a larger sample favors identification of SNPs with high minor allele frequencies and introduces bias against rare alleles. Here, we demonstrate that the use of hybridization intensity data, rather than genotype calls, reduces the effects of ascertainment bias. Whereas traditional SNP calls assess known variants based on diversity housed in the discovery panel, hybridization intensity data survey variation in the broader sample pool, regardless of whether those variants are present in the initial SNP discovery process. We apply SNP genotype and hybridization intensity data derived from the Vitis9kSNP array developed for grape to show the effects of ascertainment bias and to reconstruct evolutionary relationships among Vitis species. We demonstrate that phylogenies constructed using hybridization intensities suffer less from the distorting effects of ascertainment bias, and are thus more accurate than phylogenies based on genotype calls. Moreover, we reconstruct the phylogeny of the genus Vitis using hybridization data, show that North American subgenus Vitis species are monophyletic, and resolve several previously poorly known relationships among North American species. This study builds on earlier work that applied the Vitis9kSNP array to evolutionary questions within Vitis vinifera and has general implications for addressing ascertainment bias in array-enabled phylogeny reconstruction.

The evolutionary genetics of the genes underlying phenotypic associations for loblolly pine (Pinus taeda, Pinaceae)

A primary goal of evolutionary genetics is to discover and explain the genetic basis of fitness-related traits and how this genetic basis evolves within natural populations. Unprecedented technological advances have fueled the discovery of genetic variants associated with ecologically relevant phenotypes in many different life forms, as well as the ability to scan genomes for deviations from selectively neutral models of evolution. Theoretically, the degree of overlap between lists of genomic regions identified using each approach is related to the genetic architecture of fitness-related traits and the strength and type of natural selection molding variation at these traits within natural populations. Here we address for the first time in a plant the degree of overlap between these lists, using patterns of nucleotide diversity and divergence for >7000 unique amplicons described from the extensive expressed sequence tag libraries generated for loblolly pine (Pinus taeda L.) in combination with the >1000 published genetic associations. We show that loci associated with phenotypic traits are distinct with regard to neutral expectations. Phenotypes measured at the whole plant level (e.g., disease resistance) exhibit an approximately twofold increase in the proportion of adaptive nonsynonymous substitutions over the genome-wide average. As expected for polygenic traits, these signals were apparent only when loci were considered at the level of functional sets. The ramifications of this result are discussed in light of the continued efforts to dissect the genetic basis of quantitative traits.

Robust identification of local adaptation from allele frequencies

Comparing allele frequencies among populations that differ in environment has long been a tool for detecting loci involved in local adaptation. However, such analyses are complicated by an imperfect knowledge of population allele frequencies and neutral correlations of allele frequencies among populations due to shared population history and gene flow. Here we develop a set of methods to robustly test for unusual allele frequency patterns and correlations between environmental variables and allele frequencies while accounting for these complications based on a Bayesian model previously implemented in the software Bayenv. Using this model, we calculate a set of "standardized allele frequencies" that allows investigators to apply tests of their choice to multiple populations while accounting for sampling and covariance due to population history. We illustrate this first by showing that these standardized frequencies can be used to detect nonparametric correlations with environmental variables; these correlations are also less prone to spurious results due to outlier populations. We then demonstrate how these standardized allele frequencies can be used to construct a test to detect SNPs that deviate strongly from neutral population structure. This test is conceptually related to FST and is shown to be more powerful, as we account for population history. We also extend the model to next-generation sequencing of population pools-a cost-efficient way to estimate population allele frequencies, but one that introduces an additional level of sampling noise. The utility of these methods is demonstrated in simulations and by reanalyzing human SNP data from the Human Genome Diversity Panel populations and pooled next-generation sequencing data from Atlantic herring. An implementation of our method is available from http://gcbias.org.