Molecular diversity and landscape genomics of the crop wild relative Triticum urartu across the Fertile Crescent

Modern plant breeding can benefit from the allelic variation that exists in natural populations of crop wild relatives that evolved under natural selection in varying pedoclimatic conditions. In this study, next‐generation sequencing was used to generate 1.3 million genome‐wide single nucleotide polymorphisms (SNPs) on ex situ collections of Triticum urartu L., the wild donor of the A^u subgenome of modern wheat. A set of 75 511 high‐quality SNPs were retained to describe 298 T. urartu accessions collected throughout the Fertile Crescent. Triticum urartu showed a complex pattern of genetic diversity, with two main genetic groups distributed sequentially from west to east. The incorporation of geographical information on sampling points showed that genetic diversity was correlated to the geographical distance (R² = 0.19) separating samples from Jordan and Lebanon, from Syria and southern Turkey, and from eastern Turkey, Iran and Iraq. The wild emmer genome was used to derive the physical positions of SNPs on the seven chromosomes of the A^u subgenome, allowing us to describe a relatively slow decay of linkage disequilibrium in the collection. Outlier loci were described on the basis of the geographic distribution of the T. urartu accessions, identifying a hotspot of directional selection on chromosome 4A. Bioclimatic variation was derived from grid data and related to allelic variation using a genome‐wide association approach, identifying several marker–environment associations (MEAs). Fifty‐seven MEAs were associated with altitude and temperature measures while 358 were associated with rainfall measures. The most significant MEAs and outlier loci were used to identify genomic loci with adaptive potential (some already reported in wheat), including dormancy and frost resistance loci. We advocate the application of genomics and landscape genomics on ex situ collections of crop wild relatives to efficiently identify promising alleles and genetic materials for incorporation into modern crop breeding.     

Contemporary evolution of a Lepidopteran species,Heliothis virescens,in response to modern agricultural practices

Adaptation to human‐induced environmental change has the potential to profoundly influence the genomic architecture of affected species. This is particularly true in agricultural ecosystems, where anthropogenic selection pressure is strong. Heliothis virescens primarily feeds on cotton in its larval stages, and US populations have been declining since the widespread planting of transgenic cotton, which endogenously expresses proteins derived from Bacillus thuringiensis (Bt). No physiological adaptation to Bt toxin has been found in the field, so adaptation in this altered environment could involve (i) shifts in host plant selection mechanisms to avoid cotton, (ii) changes in detoxification mechanisms required for cotton‐feeding vs. feeding on other hosts or (iii) loss of resistance to previously used management practices including insecticides. Here, we begin to address whether such changes occurred in H. virescens populations between 1997 and 2012, as Bt‐cotton cultivation spread through the agricultural landscape. For our study, we produced an H. virescens genome assembly and used this in concert with a ddRAD‐seq‐enabled genome scan to identify loci with significant allele frequency changes over the 15‐year period. Genetic changes at a previously described H. virescens insecticide target of selection were detectable in our genome scan and increased our confidence in this methodology. Additional loci were also detected as being under selection, and we quantified the selection strength required to elicit observed allele frequency changes at each locus. Potential contributions of genes near loci under selection to adaptive phenotypes in the H. virescens cotton system are discussed.     

The adaptive genomic landscape of beak morphology in Darwin's finches

Beak shape in Darwin's ground finches (Geospiza) is emblematic of natural selection and adaptive radiation, yet our understanding of the genetic basis of beak shape variation, and thus the genetic target of natural selection, is still evolving. Here we reveal the genomic architecture of beak shape variation using genomewide comparisons of four closely related and hybridizing species across 13 islands subject to parallel natural selection. Pairwise contrasts among species were used to identify a large number of genomic loci that are consistently related to species differences across a complex landscape. These loci are associated with hundreds of genes that have enriched GO categories significantly associated with development. One genomic region of particular interest is a section of Chromosome 1A with many candidate genes and increased linkage. The distinct, pointed beak shape of the cactus finch is linked to an excess of intermediate frequency alleles and increased heterozygosity in significant SNPs, but not across the rest of the genome. Alleles associated with pointier beaks among species were associated with pointier‐beaked populations within each species, thus establishing a common basis for natural selection, species divergence and adaptive radiation. The adaptive genomic landscape for Darwin's finches mirrors theoretical expectations based on morphological variation. The implication that a large number of genes are actively maintained to facilitate beak variation across parallel populations with documented interspecies admixture challenges our understanding of evolutionary processes in the wild.     

High degree of genetic differentiation in marine three‐spined sticklebacks (Gasterosteus aculeatus)

Populations of widespread marine organisms are typically characterized by a low degree of genetic differentiation in neutral genetic markers, but much less is known about differentiation in genes whose functional roles are associated with specific selection regimes. To uncover possible adaptive population divergence and heterogeneous genomic differentiation in marine three‐spined sticklebacks (Gasterosteus aculeatus), we used a candidate gene‐based genome‐scan approach to analyse variability in 138 microsatellite loci located within/close to (<6 kb) functionally important genes in samples collected from ten geographic locations. The degree of genetic differentiation in markers classified as neutral or under balancing selection—as determined with several outlier detection methods—was low (F_ST = 0.033 or 0.011, respectively), whereas average F_ST for directionally selected markers was significantly higher (F_ST = 0.097). Clustering analyses provided support for genomic and geographic heterogeneity in selection: six genetic clusters were identified based on allele frequency differences in the directionally selected loci, whereas four were identified with the neutral loci. Allelic variation in several loci exhibited significant associations with environmental variables, supporting the conjecture that temperature and salinity, but not optic conditions, are important drivers of adaptive divergence among populations. In general, these results suggest that in spite of the high degree of physical connectivity and gene flow as inferred from neutral marker genes, marine stickleback populations are strongly genetically structured in loci associated with functionally relevant genes.     

Ecological genomics of local adaptation in Cornus florida L. by genotyping by sequencing

Discovering local adaptation, its genetic underpinnings, and environmental drivers is important for conserving forest species. Ecological genomic approaches coupled with next‐generation sequencing are useful means to detect local adaptation and uncover its underlying genetic basis in nonmodel species. We report results from a study on flowering dogwood trees (Cornus florida L.) using genotyping by sequencing (GBS). This species is ecologically important to eastern US forests but is severely threatened by fungal diseases. We analyzed subpopulations in divergent ecological habitats within North Carolina to uncover loci under local selection and associated with environmental–functional traits or disease infection. At this scale, we tested the effect of incorporating additional sequencing before scaling for a broader examination of the entire range. To test for biases of GBS, we sequenced two similarly sampled libraries independently from six populations of three ecological habitats. We obtained environmental–functional traits for each subpopulation to identify associations with genotypes via latent factor mixed modeling (LFMM) and gradient forests analysis. To test whether heterogeneity of abiotic pressures resulted in genetic differentiation indicative of local adaptation, we evaluated F_st per locus while accounting for genetic differentiation between coastal subpopulations and Piedmont‐Mountain subpopulations. Of the 54 candidate loci with sufficient evidence of being under selection among both libraries, 28–39 were Arlequin–BayeScan F_st outliers. For LFMM, 45 candidates were associated with climate (of 54), 30 were associated with soil properties, and four were associated with plant health. Reanalysis of combined libraries showed that 42 candidate loci still showed evidence of being under selection. We conclude environment‐driven selection on specific loci has resulted in local adaptation in response to potassium deficiencies, temperature, precipitation, and (to a marginal extent) disease. High allele turnover along ecological gradients further supports the adaptive significance of loci speculated to be under selection.     

A population genomic scan in Chorthippus grasshoppers unveils previously unknown phenotypic divergence

Understanding the genetics of speciation and the processes that drive it is a central goal of evolutionary biology. Grasshoppers of the Chorthippus species group differ strongly in calling song (and corresponding female preferences) but are exceedingly similar in other characteristics such as morphology. Here, we performed a population genomic scan on three Chorthippus species (Chorthippus biguttulus, C. mollis and C. brunneus) to gain insight into the genes and processes involved in divergence and speciation in this group. Using an RNA‐seq approach, we examined functional variation between the species by calling SNPs for each of the three species pairs and using F_ST‐based approaches to identify outliers. We found approximately 1% of SNPs in each comparison to be outliers. Between 37% and 40% of these outliers were nonsynonymous SNPs (as opposed to a global level of 17%) indicating that we recovered loci under selection. Among the outliers were several genes that may be involved in song production and hearing as well as genes involved in other traits such as food preferences and metabolism. Differences in food preferences between species were confirmed with a behavioural experiment. This indicates that multiple phenotypic differences implicating multiple evolutionary processes (sexual selection and natural selection) are present between the species.     

Whole‐genome resequencing uncovers molecular signatures of natural and sexual selection in wild bighorn sheep

The identification of genes influencing fitness is central to our understanding of the genetic basis of adaptation and how it shapes phenotypic variation in wild populations. Here, we used whole‐genome resequencing of wild Rocky Mountain bighorn sheep (Ovis canadensis) to >50‐fold coverage to identify 2.8 million single nucleotide polymorphisms (SNPs) and genomic regions bearing signatures of directional selection (i.e. selective sweeps). A comparison of SNP diversity between the X chromosome and the autosomes indicated that bighorn males had a dramatically reduced long‐term effective population size compared to females. This probably reflects a long history of intense sexual selection mediated by male–male competition for mates. Selective sweep scans based on heterozygosity and nucleotide diversity revealed evidence for a selective sweep shared across multiple populations at RXFP2, a gene that strongly affects horn size in domestic ungulates. The massive horns carried by bighorn rams appear to have evolved in part via strong positive selection at RXFP2. We identified evidence for selection within individual populations at genes affecting early body growth and cellular response to hypoxia; however, these must be interpreted more cautiously as genetic drift is strong within local populations and may have caused false positives. These results represent a rare example of strong genomic signatures of selection identified at genes with known function in wild populations of a nonmodel species. Our results also showcase the value of reference genome assemblies from agricultural or model species for studies of the genomic basis of adaptation in closely related wild taxa.     

Genome scans for the contemporary response to selection in quantitative traits

Genome scans have been an important approach for discovering historical signatures of selection in both model and nonmodel species. An exciting new experimental design for genome scans is to measure the change in allele frequency before and after contemporary selection within a generation, from a single population. The most widely‐used methods, however, have two major limitations: they are based on testing one locus at a time, and they only have power to uncover loci that have evolved under relatively strong selection. On the other hand, complex quantitative traits are common in nature and are caused by several loci of small effect. Selection on a quantitative trait at the phenotypic level is predicted to be accompanied by subtle allele frequency changes in many loci that covary (a polygenic soft sweep), rather than a large, single‐effect allele (a selective sweep). In this issue of Molecular Ecology, Bourret et al. (2014) measure the contemporary response to natural selection across the genome in multiple cohorts of Atlantic salmon during their first year at sea. They introduce a multilocus framework based on groups of markers that covary in their genotypic distribution. While the traditional, single‐locus approach did not find evidence for repeated patterns of selection, the multivariate approach found that a group of covarying SNPs was selected for in different cohorts at one site. Their multilocus framework has potential to be a more fruitful approach for uncovering the genomic basis of adaptation in quantitative traits, although caution should be applied as the framework has yet to be validated with simulated data.     

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.     

Riverscape genomics of a threatened fish across a hydroclimatically heterogeneous river basin

Understanding how natural selection generates and maintains adaptive genetic diversity in heterogeneous environments is key to predicting the evolutionary response of populations to rapid environmental change. Detecting selection in complex spatial environments remains challenging, especially for threatened species where the effects of strong genetic drift may overwhelm signatures of selection. We carried out a basinwide riverscape genomic analysis in the threatened southern pygmy perch (Nannoperca australis), an ecological specialist with low dispersal potential. High‐resolution environmental data and 5162 high‐quality filtered SNPs were used to clarify spatial population structure and to assess footprints of selection associated with a steep hydroclimatic gradient and with human disturbance across the naturally and anthropogenically fragmented Murray–Darling Basin (Australia). Our approach included F_ST outlier tests to define neutral loci, and a combination of spatially explicit genotype–environment association analyses to identify candidate adaptive loci while controlling for the effects of landscape structure and shared population history. We found low levels of genetic diversity and strong neutral population structure consistent with expectations based on spatial stream hierarchy and life history. In contrast, variables related to precipitation and temperature appeared as the most important environmental surrogates for putatively adaptive genetic variation at both regional and local scales. Human disturbance also influenced the variation in candidate loci for adaptation, but only at a local scale. Our study contributes to understanding of adaptive evolution along naturally and anthropogenically fragmented ecosystems. It also offers a tangible example of the potential contributions of landscape genomics for informing in situ and ex situ conservation management of biodiversity.     

Lack of genetic diversity across diverse immune genes in an endangered mammal,the Tasmanian devil (Sarcophilus harrisii)

The Tasmanian devil (Sarcophilus harrisii) is threatened with extinction due to the spread of devil facial tumour disease. Polymorphisms in immune genes can provide adaptive potential to resist diseases. Previous studies in diversity at immune loci in wild species have almost exclusively focused on genes of the major histocompatibility complex (MHC); however, these genes only account for a fraction of immune gene diversity. Devils lack diversity at functionally important immunity loci, including MHC and Toll‐like receptor genes. Whether there are polymorphisms at devil immune genes outside these two families is unknown. Here, we identify polymorphisms in a wide range of key immune genes, and develop assays to type single nucleotide polymorphisms (SNPs) within a subset of these genes. A total of 167 immune genes were examined, including cytokines, chemokines and natural killer cell receptors. Using genome‐level data from ten devils, SNPs within coding regions, introns and 10 kb flanking genes of interest were identified. We found low polymorphism across 167 immune genes examined bioinformatically using whole‐genome data. From this data, we developed long amplicon assays to target nine genes. These amplicons were sequenced in 29–220 devils and found to contain 78 SNPs, including eight SNPS within exons. Despite the extreme paucity of genetic diversity within these genes, signatures of balancing selection were exhibited by one chemokine gene, suggesting that remaining diversity may hold adaptive potential. The low functional diversity may leave devils highly vulnerable to infectious disease, and therefore, monitoring and preserving remaining diversity will be critical for the long‐term management of this species. Examining genetic variation in diverse immune genes should be a priority for threatened wildlife species. This study can act as a model for broad‐scale immunogenetic diversity analysis in threatened species.     

Landscape genomics and a common garden trial reveal adaptive differentiation to temperature across Europe in the tree species Alnus glutinosa

The adaptive potential of tree species to cope with climate change has important ecological and economic implications. Many temperate tree species experience a wide range of environmental conditions, suggesting high adaptability to new environmental conditions. We investigated adaptation to regional climate in the drought‐sensitive tree species Alnus glutinosa (Black alder), using a complementary approach that integrates genomic, phenotypic and landscape data. A total of 24 European populations were studied in a common garden and through landscape genomic approaches. Genotyping‐by‐sequencing was used to identify SNPs across the genome, resulting in 1990 SNPs. Although a relatively low percentage of putative adaptive SNPs was detected (2.86% outlier SNPs), we observed clear associations among outlier allele frequencies, temperature and plant traits. In line with the typical drought avoiding nature of A. glutinosa, leaf size varied according to a temperature gradient and significant associations with multiple outlier loci were observed, corroborating the ecological relevance of the observed outlier SNPs. Moreover, the lack of isolation by distance, the very low genetic differentiation among populations and the high intrapopulation genetic variation all support the notion that high gene exchange combined with strong environmental selection promotes adaptation to environmental cues.     

Genome‐wide analyses suggest parallel selection for universal traits may eclipse local environmental selection in a highly mobile carnivore

Ecological and environmental heterogeneity can produce genetic differentiation in highly mobile species. Accordingly, local adaptation may be expected across comparatively short distances in the presence of marked environmental gradients. Within the European continent, wolves (Canis lupus) exhibit distinct north–south population differentiation. We investigated more than 67‐K single nucleotide polymorphism (SNP) loci for signatures of local adaptation in 59 unrelated wolves from four previously identified population clusters (northcentral Europe n = 32, Carpathian Mountains n = 7, Dinaric‐Balkan n = 9, Ukrainian Steppe n = 11). Our analyses combined identification of outlier loci with findings from genome‐wide association study of individual genomic profiles and 12 environmental variables. We identified 353 candidate SNP loci. We examined the SNP position and neighboring megabase (1 Mb, one million bases) regions in the dog (C. lupus familiaris) genome for genes potentially under selection, including homologue genes in other vertebrates. These regions included functional genes for, for example, temperature regulation that may indicate local adaptation and genes controlling for functions universally important for wolves, including olfaction, hearing, vision, and cognitive functions. We also observed strong outliers not associated with any of the investigated variables, which could suggest selective pressures associated with other unmeasured environmental variables and/or demographic factors. These patterns are further supported by the examination of spatial distributions of the SNPs associated with universally important traits, which typically show marked differences in allele frequencies among population clusters. Accordingly, parallel selection for features important to all wolves may eclipse local environmental selection and implies long‐term separation among population clusters.     

Minimum sample sizes for population genomics: an empirical study from an Amazonian plant species

High‐throughput DNA sequencing facilitates the analysis of large portions of the genome in nonmodel organisms, ensuring high accuracy of population genetic parameters. However, empirical studies evaluating the appropriate sample size for these kinds of studies are still scarce. In this study, we use double‐digest restriction‐associated DNA sequencing (ddRADseq) to recover thousands of single nucleotide polymorphisms (SNPs) for two physically isolated populations of Amphirrhox longifolia (Violaceae), a nonmodel plant species for which no reference genome is available. We used resampling techniques to construct simulated populations with a random subset of individuals and SNPs to determine how many individuals and biallelic markers should be sampled for accurate estimates of intra‐ and interpopulation genetic diversity. We identified 3646 and 4900 polymorphic SNPs for the two populations of A. longifolia, respectively. Our simulations show that, overall, a sample size greater than eight individuals has little impact on estimates of genetic diversity within A. longifolia populations, when 1000 SNPs or higher are used. Our results also show that even at a very small sample size (i.e. two individuals), accurate estimates of F_ST can be obtained with a large number of SNPs (≥1500). These results highlight the potential of high‐throughput genomic sequencing approaches to address questions related to evolutionary biology in nonmodel organisms. Furthermore, our findings also provide insights into the optimization of sampling strategies in the era of population genomics.     

SNP discovery in nonmodel organisms: strand bias and base‐substitution errors reduce conversion rates

Single nucleotide polymorphisms (SNPs) have become the marker of choice for genetic studies in organisms of conservation, commercial or biological interest. Most SNP discovery projects in nonmodel organisms apply a strategy for identifying putative SNPs based on filtering rules that account for random sequencing errors. Here, we analyse data used to develop 4723 novel SNPs for the commercially important deep‐sea fish, orange roughy (Hoplostethus atlanticus), to assess the impact of not accounting for systematic sequencing errors when filtering identified polymorphisms when discovering SNPs. We used SAMtools to identify polymorphisms in a velvet assembly of genomic DNA sequence data from seven individuals. The resulting set of polymorphisms were filtered to minimize ‘bycatch’—polymorphisms caused by sequencing or assembly error. An Illumina Infinium SNP chip was used to genotype a final set of 7714 polymorphisms across 1734 individuals. Five predictors were examined for their effect on the probability of obtaining an assayable SNP: depth of coverage, number of reads that support a variant, polymorphism type (e.g. A/C), strand‐bias and Illumina SNP probe design score. Our results indicate that filtering out systematic sequencing errors could substantially improve the efficiency of SNP discovery. We show that BLASTX can be used as an efficient tool to identify single‐copy genomic regions in the absence of a reference genome. The results have implications for research aiming to identify assayable SNPs and build SNP genotyping assays for nonmodel organisms.     

Signatures of selection in the Iberian honey bee (Apis mellifera iberiensis) revealed by a genome scan analysis of single nucleotide polymorphisms

Understanding the genetic mechanisms of adaptive population divergence is one of the most fundamental endeavours in evolutionary biology and is becoming increasingly important as it will allow predictions about how organisms will respond to global environmental crisis. This is particularly important for the honey bee, a species of unquestionable ecological and economical importance that has been exposed to increasing human‐mediated selection pressures. Here, we conducted a single nucleotide polymorphism (SNP)‐based genome scan in honey bees collected across an environmental gradient in Iberia and used four F_ST‐based outlier tests to identify genomic regions exhibiting signatures of selection. Additionally, we analysed associations between genetic and environmental data for the identification of factors that might be correlated or act as selective pressures. With these approaches, 4.4% (17 of 383) of outlier loci were cross‐validated by four F_ST‐based methods, and 8.9% (34 of 383) were cross‐validated by at least three methods. Of the 34 outliers, 15 were found to be strongly associated with one or more environmental variables. Further support for selection, provided by functional genomic information, was particularly compelling for SNP outliers mapped to different genes putatively involved in the same function such as vision, xenobiotic detoxification and innate immune response. This study enabled a more rigorous consideration of selection as the underlying cause of diversity patterns in Iberian honey bees, representing an important first step towards the identification of polymorphisms implicated in local adaptation and possibly in response to recent human‐mediated environmental changes.     

Population structure of Atlantic mackerel inferred from RAD‐seq‐derived SNP markers: effects of sequence clustering parameters and hierarchical SNP selection

Restriction‐site‐associated DNA sequencing (RAD‐seq) and related methods are revolutionizing the field of population genomics in nonmodel organisms as they allow generating an unprecedented number of single nucleotide polymorphisms (SNPs) even when no genomic information is available. Yet, RAD‐seq data analyses rely on assumptions on nature and number of nucleotide variants present in a single locus, the choice of which may lead to an under‐ or overestimated number of SNPs and/or to incorrectly called genotypes. Using the Atlantic mackerel (Scomber scombrus L.) and a close relative, the Atlantic chub mackerel (Scomber colias), as case study, here we explore the sensitivity of population structure inferences to two crucial aspects in RAD‐seq data analysis: the maximum number of mismatches allowed to merge reads into a locus and the relatedness of the individuals used for genotype calling and SNP selection. Our study resolves the population structure of the Atlantic mackerel, but, most importantly, provides insights into the effects of alternative RAD‐seq data analysis strategies on population structure inferences that are directly applicable to other species.     

Outlier loci highlight the direction of introgression in oaks

Loci considered to be under selection are generally avoided in attempts to infer past demographic processes as they do not fit neutral model assumptions. However, opportunities to better reconstruct some aspects of past demography might thus be missed. Here we examined genetic differentiation between two sympatric European oak species with contrasting ecological dynamics (Quercus robur and Quercus petraea) with both outlier (i.e. loci possibly affected by divergent selection between species or by hitchhiking effects with genomic regions under selection) and nonoutlier loci. We sampled 855 individuals in six mixed forests in France and genotyped them with a set of 262 SNPs enriched with markers showing high interspecific differentiation, resulting in accurate species delimitation. We identified between 13 and 74 interspecific outlier loci, depending on the coalescent simulation models and parameters used. Greater genetic diversity was predicted in Q. petraea (a late‐successional species) than in Q. robur (an early successional species) as introgression should theoretically occur predominantly from the resident species to the invading species. Remarkably, this prediction was verified with outlier loci but not with nonoutlier loci. We suggest that the lower effective interspecific gene flow at loci showing high interspecific divergence has better preserved the signal of past asymmetric introgression towards Q. petraea caused by the species' contrasting dynamics. Using markers under selection to reconstruct past demographic processes could therefore have broader potential than generally recognized.