Genome-Wide Analysis of Cold Adaptation in Indigenous Siberian Populations

Following the dispersal out of Africa, where hominins evolved in warm environments for millions of years, our species has colonised different climate zones of the world, including high latitudes and cold environments. The extent to which human habitation in (sub-)Arctic regions has been enabled by cultural buffering, short-term acclimatization and genetic adaptations is not clearly understood. Present day indigenous populations of Siberia show a number of phenotypic features, such as increased basal metabolic rate, low serum lipid levels and increased blood pressure that have been attributed to adaptation to the extreme cold climate. In this study we introduce a dataset of 200 individuals from ten indigenous Siberian populations that were genotyped for 730,525 SNPs across the genome to identify genes and non-coding regions that have undergone unusually rapid allele frequency and long-range haplotype homozygosity change in the recent past. At least three distinct population clusters could be identified among the Siberians, each of which showed a number of unique signals of selection. A region on chromosome 11 (chr11:66–69 Mb) contained the largest amount of clustering of significant signals and also the strongest signals in all the different selection tests performed. We present a list of candidate cold adaption genes that showed significant signals of positive selection with our strongest signals associated with genes involved in energy regulation and metabolism (CPT1A, LRP5, THADA) and vascular smooth muscle contraction (PRKG1). By employing a new method that paints phased chromosome chunks by their ancestry we distinguish local Siberian-specific long-range haplotype signals from those introduced by admixture.     

Adaptations to climate in candidate genes for common metabolic disorders

Evolutionary pressures due to variation in climate play an important role in shaping phenotypic variation among and within species and have been shown to influence variation in phenotypes such as body shape and size among humans. Genes involved in energy metabolism are likely to be central to heat and cold tolerance. To test the hypothesis that climate shaped variation in metabolism genes in humans, we used a bioinformatics approach based on network theory to select 82 candidate genes for common metabolic disorders. We genotyped 873 tag SNPs in these genes in 54 worldwide populations (including the 52 in the Human Genome Diversity Project panel) and found correlations with climate variables using rank correlation analysis and a newly developed method termed Bayesian geographic analysis. In addition, we genotyped 210 carefully matched control SNPs to provide an empirical null distribution for spatial patterns of allele frequency due to population history alone. For nearly all climate variables, we found an excess of genic SNPs in the tail of the distributions of the test statistics compared to the control SNPs, implying that metabolic genes as a group show signals of spatially varying selection. Among our strongest signals were several SNPs (e.g., LEPR R109K, FABP2 A54T) that had previously been associated with phenotypes directly related to cold tolerance. Since variation in climate may be correlated with other aspects of environmental variation, it is possible that some of the signals that we detected reflect selective pressures other than climate. Nevertheless, our results are consistent with the idea that climate has been an important selective pressure acting on candidate genes for common metabolic disorders.     

Signatures of environmental genetic adaptation pinpoint pathogens as the main selective pressure through human evolution

Previous genome-wide scans of positive natural selection in humans have identified a number of non-neutrally evolving genes that play important roles in skin pigmentation, metabolism, or immune function. Recent studies have also shown that a genome-wide pattern of local adaptation can be detected by identifying correlations between patterns of allele frequencies and environmental variables. Despite these observations, the degree to which natural selection is primarily driven by adaptation to local environments, and the role of pathogens or other ecological factors as selective agents, is still under debate. To address this issue, we correlated the spatial allele frequency distribution of a large sample of SNPs from 55 distinct human populations to a set of environmental factors that describe local geographical features such as climate, diet regimes, and pathogen loads. In concordance with previous studies, we detected a significant enrichment of genic SNPs, and particularly non-synonymous SNPs associated with local adaptation. Furthermore, we show that the diversity of the local pathogenic environment is the predominant driver of local adaptation, and that climate, at least as measured here, only plays a relatively minor role. While background demography by far makes the strongest contribution in explaining the genetic variance among populations, we detected about 100 genes which show an unexpectedly strong correlation between allele frequencies and pathogenic environment, after correcting for demography. Conversely, for diet regimes and climatic conditions, no genes show a similar correlation between the environmental factor and allele frequencies. This result is validated using low-coverage sequencing data for multiple populations. Among the loci targeted by pathogen-driven selection, we found an enrichment of genes associated to autoimmune diseases, such as celiac disease, type 1 diabetes, and multiples sclerosis, which lends credence to the hypothesis that some susceptibility alleles for autoimmune diseases may be maintained in human population due to past selective processes.     

A map of recent positive selection in the human genome

The identification of signals of very recent positive selection provides information about the adaptation of modern humans to local conditions. We report here on a genome-wide scan for signals of very recent positive selection in favor of variants that have not yet reached fixation. We describe a new analytical method for scanning single nucleotide polymorphism (SNP) data for signals of recent selection, and apply this to data from the International HapMap Project. In all three continental groups we find widespread signals of recent positive selection. Most signals are region-specific, though a significant excess are shared across groups. Contrary to some earlier low resolution studies that suggested a paucity of recent selection in sub-Saharan Africans, we find that by some measures our strongest signals of selection are from the Yoruba population. Finally, since these signals indicate the existence of genetic variants that have substantially different fitnesses, they must indicate loci that are the source of significant phenotypic variation. Though the relevant phenotypes are generally not known, such loci should be of particular interest in mapping studies of complex traits. For this purpose we have developed a set of SNPs that can be used to tag the strongest ∼250 signals of recent selection in each population.     

Finding needles in a genomic haystack: targeted capture identifies clear signatures of selection in a nonmodel plant species

Teasing apart neutral and adaptive genomic processes and identifying loci that are targets of selection can be difficult, particularly for nonmodel species that lack a reference genome. However, identifying such loci and the factors driving selection have the potential to greatly assist conservation and restoration practices, especially for the management of species in the face of contemporary and future climate change. Here, we focus on assessing adaptive genomic variation within a nonmodel plant species, the narrow‐leaf hopbush (Dodonaea viscosa ssp. angustissima), commonly used for restoration in Australia. We used a hybrid‐capture target enrichment approach to selectively sequence 970 genes across 17 populations along a latitudinal gradient from 30°S to 36°S. We analysed 8462 single‐nucleotide polymorphisms (SNPs) for F_ST outliers as well as associations with environmental variables. Using three different methods, we found 55 SNPs with significant correlations to temperature and water availability, and 38 SNPs to elevation. Genes containing SNPs identified as under environmental selection were diverse, including aquaporin and abscisic acid genes, as well as genes with ontologies relating to responses to environmental stressors such as water deprivation and salt stress. Redundancy analysis demonstrated that only a small proportion of the total genetic variance was explained by environmental variables. We demonstrate that selection has led to clines in allele frequencies in a number of functional genes, including those linked to leaf shape and stomatal variation, which have been previously observed to vary along the sampled environmental cline. Using our approach, gene regions subject to environmental selection can be readily identified for nonmodel organisms.     

Climatic adaptation and ecological divergence between two closely related pine species in Southeast China

Climate is one of the most important drivers for adaptive evolution in forest trees. Climatic selection contributes greatly to local adaptation and intraspecific differentiation, but this kind of selection could also have promoted interspecific divergence through ecological speciation. To test this hypothesis, we examined intra‐ and interspecific genetic variation at 25 climate‐related candidate genes and 12 reference loci in two closely related pine species, Pinus massoniana Lamb. and Pinus hwangshanensis Hisa, using population genetic and landscape genetic approaches. These two species occur in Southeast China but have contrasting ecological preferences in terms of several environmental variables, notably altitude, although hybrids form where their distributions overlap. One or more robust tests detected signals of recent and/or ancient selection at two‐thirds (17) of the 25 candidate genes, at varying evolutionary timescales, but only three of the 12 reference loci. The signals of recent selection were species specific, but signals of ancient selection were mostly shared by the two species likely because of the shared evolutionary history. F_ST outlier analysis identified six SNPs in five climate‐related candidate genes under divergent selection between the two species. In addition, a total of 24 candidate SNPs representing nine candidate genes showed significant correlation with altitudinal divergence in the two species based on the covariance matrix of population history derived from reference SNPs. Genetic differentiation between these two species was higher at the candidate genes than at the reference loci. Moreover, analysis using the isolation‐with‐migration model indicated that gene flow between the species has been more restricted for climate‐related candidate genes than the reference loci, in both directions. Taken together, our results suggest that species‐specific and divergent climatic selection at the candidate genes might have counteracted interspecific gene flow and played a key role in the ecological divergence of these two closely related pine species.     

In the presence of population structure: From genomics to candidate genes underlying local adaptation

Understanding the genomic signatures, genes, and traits underlying local adaptation of organisms to heterogeneous environments is of central importance to the field evolutionary biology. To identify loci underlying local adaptation, models that combine allelic and environmental variation while controlling for the effects of population structure have emerged as the method of choice. Despite being evaluated in simulation studies, there has not been a thorough investigation of empirical evidence supporting local adaptation across these alleles. To evaluate these methods, we use 875 Arabidopsis thaliana Eurasian accessions and two mixed models (GEMMA and LFMM) to identify candidate SNPs underlying local adaptation to climate. Subsequently, to assess evidence of local adaptation and function among significant SNPs, we examine allele frequency differentiation and recent selection across Eurasian populations, in addition to their distribution along quantitative trait loci (QTL) explaining fitness variation between Italy and Sweden populations and cis‐regulatory/nonsynonymous sites showing significant selective constraint. Our results indicate that significant LFMM/GEMMA SNPs show low allele frequency differentiation and linkage disequilibrium across locally adapted Italy and Sweden populations, in addition to a poor association with fitness QTL peaks (highest logarithm of odds score). Furthermore, when examining derived allele frequencies across the Eurasian range, we find that these SNPs are enriched in low‐frequency variants that show very large climatic differentiation but low levels of linkage disequilibrium. These results suggest that their enrichment along putative functional sites most likely represents deleterious variation that is independent of local adaptation. Among all the genomic signatures examined, only SNPs showing high absolute allele frequency differentiation (AFD) and linkage disequilibrium (LD) between Italy and Sweden populations showed a strong association with fitness QTL peaks and were enriched along selectively constrained cis‐regulatory/nonsynonymous sites. Using these SNPs, we find strong evidence linking flowering time, freezing tolerance, and the abscisic‐acid pathway to local adaptation.     

Genetic signatures of natural selection in response to air pollution in red spruce (Picea rubens,Pinaceae)

One of the most important drivers of local adaptation for forest trees is climate. Coupled to these patterns, however, are human‐induced disturbances through habitat modification and pollution. The confounded effects of climate and disturbance have rarely been investigated with regard to selective pressure on forest trees. Here, we have developed and used a population genetic approach to search for signals of selection within a set of 36 candidate genes chosen for their putative effects on adaptation to climate and human‐induced air pollution within five populations of red spruce (Picea rubens Sarg.), distributed across its natural range and air pollution gradient in eastern North America. Specifically, we used F_ST outlier and environmental correlation analyses to highlight a set of seven single nucleotide polymorphisms (SNPs) that were overly correlated with climate and levels of sulphate pollution after correcting for the confounding effects of population history. Use of three age cohorts within each population allowed the effects of climate and pollution to be separated temporally, as climate‐related SNPs (n = 7) showed the strongest signals in the oldest cohort, while pollution‐related SNPs (n = 3) showed the strongest signals in the youngest cohorts. These results highlight the usefulness of population genetic scans for the identification of putatively nonneutral evolution within genomes of nonmodel forest tree species, but also highlight the need for the development and application of robust methodologies to deal with the inherent multivariate nature of the genetic and ecological data used in these types of analyses.     

Evaluating the evidence for transmission distortion in human pedigrees

Children of a heterozygous parent are expected to carry either allele with equal probability. Exceptions can occur, however, due to meiotic drive, competition among gametes, or viability selection, which we collectively term "transmission distortion" (TD). Although there are several well-characterized examples of these phenomena, their existence in humans remains unknown. We therefore performed a genome-wide scan for TD by applying the transmission disequilibrium test (TDT) genome-wide to three large sets of human pedigrees of European descent: the Framingham Heart Study (FHS), a founder population of European origin (HUTT), and a subset of the Autism Genetic Resource Exchange (AGRE). Genotyping error is an important confounder in this type of analysis. In FHS and HUTT, despite extensive quality control, we did not find sufficient evidence to exclude genotyping error in the strongest signals. In AGRE, however, many signals extended across multiple SNPs, a pattern highly unlikely to arise from genotyping error. We identified several candidate regions in this data set, notably a locus in 10q26.13 displaying a genome-wide significant TDT in combined female and male transmissions and a signature of recent positive selection, as well as a paternal TD signal in 6p21.1, the same region in which a significant TD signal was previously observed in 30 European males. Neither region replicated in FHS, however, and the paternal signal was not visible in sperm competition assays or as allelic imbalance in sperm. In maternal transmissions, we detected no strong signals near centromeres or telomeres, the regions predicted to be most susceptible to female-specific meiotic drive, but we found a significant enrichment of top signals among genes involved in cell junctions. These results illustrate both the potential benefits and the challenges of using the TDT to study transmission distortion and provide candidates for investigation in future studies.     

Synonymous SNPs Provide Evidence for Selective Constraint on Human Exonic Splicing Enhancers

The human SNP database was used to detect selection on 238 hexamers previously identified as exonic splicing enhancers (ESEs). We compared the distribution of the 238 putative ESEs in biallelic and triallelic SNPs within five different functional categories of the SNP database: synonymous, nonsynonymous, introns, UTRs, and nongenic SNPs. Since true ESEs do not function outside of exons, SNPs that disrupt ESE motifs were expected to be more common in nonexonic portions of the genome. Our results supported this expectation: ESEs were least prevalent within synonymous SNPs and most common in nongenic SNPs. There were ∼11% fewer ESEs within synonymous biallelic SNPs than expected under no selective constraint. We also compared the frequency of neutral SNPs, those where neither allele was an ESE, with deleterious SNPs, those where one or more alleles was an ESE, across the five different functional classes of SNPs. In comparison with the other functional classes of SNPs, synonymous SNPs contained an excess of neutral variants (+1.64% and +6.04% for biallelic and triallelic SNPs, respectively) and a dearth of deleterious variants (−13.11% and −52.39% for biallelic and triallelic SNPs, respectively). The observed patterns were consistent with purifying selection on the 238 hexamers to maintain their function as ESEs. However, in contrast to previous work, we did not find evidence for selection to maintain ESE function at nonsynonymous SNPs because selection at the protein level probably obscured any difference at the level of ESE function.     

Lineage‐specific adaptation to climate involves flowering time in North American Arabidopsis lyrata

Adaptation to local climatic conditions is commonly found within species, but whether it involves the same intraspecific genomic variants is unknown. We studied this question in North American Arabidopsis lyrata, whose current distribution is shaped by post‐glacial range expansion from two refugia, resulting in two distinct genetic clusters covering comparable climatic gradients. Using pooled whole‐genome sequence data of 41 outcrossing populations, we identified loci associated with three niche‐determining climatic variables in the two clusters and compared these outliers. Little evidence was found for parallelism in climate adaptation for single nucleotide polymorphisms (SNPs) and for genes with an accumulation of outlier SNPs. Significantly increased selection coefficients supported them as candidates of climate adaptation. However, the fraction of gene ontology (GO) terms shared between clusters was higher compared to outlier SNPs and outlier genes, suggesting that selection acts on similar pathways but not necessarily the same genes. Enriched GO terms involved responses to abiotic and biotic stress, circadian rhythm and development, with flower development and reproduction being among the most frequently detected. In line with GO enrichment, regulators of flowering time were detected as outlier genes. Our results suggest that while adaptation to environmental gradients on the genomic level are lineage‐specific in A. lyrata, similar biological processes seem to be involved. Differential loss of standing genetic variation, probably driven by genetic drift, can in part account for the lack of parallel evolution on the genomic level.     

All SNPs Are Not Created Equal: Genome-Wide Association Studies Reveal a Consistent Pattern of Enrichment among Functionally Annotated SNPs

Recent results indicate that genome-wide association studies (GWAS) have the potential to explain much of the heritability of common complex phenotypes, but methods are lacking to reliably identify the remaining associated single nucleotide polymorphisms (SNPs). We applied stratified False Discovery Rate (sFDR) methods to leverage genic enrichment in GWAS summary statistics data to uncover new loci likely to replicate in independent samples. Specifically, we use linkage disequilibrium-weighted annotations for each SNP in combination with nominal p-values to estimate the True Discovery Rate (TDR = 1−FDR) for strata determined by different genic categories. We show a consistent pattern of enrichment of polygenic effects in specific annotation categories across diverse phenotypes, with the greatest enrichment for SNPs tagging regulatory and coding genic elements, little enrichment in introns, and negative enrichment for intergenic SNPs. Stratified enrichment directly leads to increased TDR for a given p-value, mirrored by increased replication rates in independent samples. We show this in independent Crohn''s disease GWAS, where we find a hundredfold variation in replication rate across genic categories. Applying a well-established sFDR methodology we demonstrate the utility of stratification for improving power of GWAS in complex phenotypes, with increased rejection rates from 20% in height to 300% in schizophrenia with traditional FDR and sFDR both fixed at 0.05. Our analyses demonstrate an inherent stratification among GWAS SNPs with important conceptual implications that can be leveraged by statistical methods to improve the discovery of loci.     

Genomic Patterns of Geographic Differentiation in Drosophila simulans

Geographic patterns of genetic differentiation have long been used to understand population history and to learn about the biological mechanisms of adaptation. Here we present an examination of genomic patterns of differentiation between northern and southern populations of Australian and North American Drosophila simulans, with an emphasis on characterizing signals of parallel differentiation. We report on the genomic scale of differentiation and functional enrichment of outlier SNPs. While, overall, signals of shared differentiation are modest, we find the strongest support for parallel differentiation in genomic regions that are associated with regulation. Comparisons to Drosophila melanogaster yield potential candidate genes involved in local adaptation in both species, providing insight into common selective pressures and responses. In contrast to D. melanogaster, in D. simulans we observe patterns of variation that are inconsistent with a model of temperate adaptation out of a tropical ancestral range, highlighting potential differences in demographic and colonization histories of this cosmopolitan species pair.     

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.     

Standing genomic variation within coding and regulatory regions contributes to the adaptive capacity to climate in a foundation tree species

Global climate is rapidly changing, and the ability for tree species to adapt is dependent on standing genomic variation; however, the distribution and abundance of functional and adaptive variants are poorly understood in natural systems. We test key hypotheses regarding the genetics of adaptive variation in a foundation tree: genomic variation is associated with climate, and genomic variation is more likely to be associated with temperature than precipitation or aridity. To test these hypotheses, we used 9,593 independent, genomic single‐nucleotide polymorphisms (SNPs) from 270 individuals sampled from Corymbia calophylla's entire distribution in south‐western Western Australia, spanning orthogonal temperature and precipitation gradients. Environmental association analyses returned 537 unique SNPs putatively adaptive to climate. We identified SNPs associated with climatic variation (i.e., temperature [458], precipitation [75] and aridity [78]) across the landscape. Of these, 78 SNPs were nonsynonymous (NS), while 26 SNPs were found within gene regulatory regions. The NS and regulatory candidate SNPs associated with temperature explained more deviance (27.35%) than precipitation (5.93%) and aridity (4.77%), suggesting that temperature provides stronger adaptive signals than precipitation. Genes associated with adaptive variants include functions important in stress responses to temperature and precipitation. Patterns of allelic turnover of NS and regulatory SNPs show small patterns of change through climate space with the exception of an aldehyde dehydrogenase gene variant with 80% allelic turnover with temperature. Together, these findings provide evidence for the presence of adaptive variation to climate in a foundation species and provide critical information to guide adaptive management practices.     

Variation in Drosophila melanogaster central metabolic genes appears driven by natural selection both within and between populations

In this report, we examine the hypothesis that the drivers of latitudinal selection observed in the eastern US Drosophila melanogaster populations are reiterated within seasons in a temperate orchard population in Pennsylvania, USA. Specifically, we ask whether alleles that are apparently favoured in northern populations are also favoured early in the spring, and decrease in frequency from the spring to autumn with the population expansion. We use SNP data collected for 46 metabolic genes and 128 SNPs representing the central metabolic pathway and examine for the aggregate SNP allele frequencies whether the association of allele change with latitude and that with increasing days of spring–autumn season are reversed. Testing by random permutation, we observe a highly significant negative correlation between these associations that is consistent with this expectation. This correlation is stronger when we confine our analysis to only those alleles that show significant latitudinal changes. This pattern is not caused by association with chromosomal inversions. When data are resampled using SNPs for amino acid change the relationship is not significant but is supported when SNPs associated with cis-expression are only considered. Our results suggest that climate factors driving latitudinal molecular variation in a metabolic pathway are related to those operating on a seasonal level within populations.     

Disentangling the roles of history and local selection in shaping clinal variation of allele frequencies and gene expression in Norway spruce (Picea abies)

Understanding the genetic basis of local adaptation is challenging due to the subtle balance among conflicting evolutionary forces that are involved in its establishment and maintenance. One system with which to tease apart these difficulties is clines in adaptive characters. Here we analyzed genetic and phenotypic variation in bud set, a highly heritable and adaptive trait, among 18 populations of Norway spruce (Picea abies), arrayed along a latitudinal gradient ranging from 47°N to 68°N. We confirmed that variation in bud set is strongly clinal, using a subset of five populations. Genotypes for 137 single-nucleotide polymorphisms (SNPs) chosen from 18 candidate genes putatively affecting bud set and 308 control SNPs chosen from 264 random genes were analyzed for patterns of genetic structure and correlation to environment. Population genetic structure was low (F(ST) = 0.05), but latitudinal patterns were apparent among Scandinavian populations. Hence, part of the observed clinal variation should be attributable to population demography. Conditional on patterns of genetic structure, there was enrichment of SNPs within candidate genes for correlations with latitude. Twenty-nine SNPs were also outliers with respect to F(ST). The enrichment for clinal variation at SNPs within candidate genes (i.e., SNPs in PaGI, PaPhyP, PaPhyN, PaPRR7, and PaFTL2) indicated that local selection in the 18 populations, and/or selection in the ancestral populations from which they were recently derived, shaped the observed cline. Validation of these genes using expression studies also revealed that PaFTL2 expression is significantly associated with latitude, thereby confirming the central role played by this gene in the control of phenology in plants.     

Experimental migration upward in elevation is associated with strong selection on life history traits

One of the strongest biological impacts of climate change has been the movement of species poleward and upward in elevation. Yet, what is not clear is the extent to which the spatial distribution of locally adapted lineages and ecologically important traits may also shift with continued climate change. Here, we take advantage of a transplant experiment mimicking up‐slope seed dispersal for a suite of ecologically diverse populations of yellow monkeyflower (Mimulus guttatus sensu lato) into a high‐elevation common garden during an extreme drought period in the Sierra Nevada mountains, California, USA. We use a demographic approach to quantify fitness and test for selection on life history traits in local versus lower‐elevation populations and in normal versus drought years to test the potential for up‐slope migration and phenotypic selection to alter the distribution of key life history traits in montane environments. We find that lower‐elevation populations tend to outperform local populations, confirming the potential for up‐slope migration. Although selection generally favored some local montane traits, including larger flowers and larger stem size at flowering, drought conditions tended to select for earlier flowering typical of lower‐elevation genotypes. Taken together, this suggests that monkeyflower lineages moving upward in elevation could experience selection for novel trait combinations, particularly under warmer and drier conditions that are predicted to occur with continued climate change.