High performance computation of landscape genomic models including local indicators of spatial association

With the increasing availability of both molecular and topo‐climatic data, the main challenges facing landscape genomics – that is the combination of landscape ecology with population genomics – include processing large numbers of models and distinguishing between selection and demographic processes (e.g. population structure). Several methods address the latter, either by estimating a null model of population history or by simultaneously inferring environmental and demographic effects. Here we present sam βada , an approach designed to study signatures of local adaptation, with special emphasis on high performance computing of large‐scale genetic and environmental data sets. sam βada identifies candidate loci using genotype–environment associations while also incorporating multivariate analyses to assess the effect of many environmental predictor variables. This enables the inclusion of explanatory variables representing population structure into the models to lower the occurrences of spurious genotype–environment associations. In addition, sam βada calculates local indicators of spatial association for candidate loci to provide information on whether similar genotypes tend to cluster in space, which constitutes a useful indication of the possible kinship between individuals. To test the usefulness of this approach, we carried out a simulation study and analysed a data set from Ugandan cattle to detect signatures of local adaptation with sam βada , bayenv , lfmm and an F_ST outlier method (FDIST approach in arlequin ) and compare their results. sam βada – an open source software for Windows, Linux and Mac OS X available at http://lasig.epfl.ch/sambada – outperforms other approaches and better suits whole‐genome sequence data processing.     

Genetic analysis of differentiation among breeding ponds reveals a candidate gene for local adaptation in Rana arvalis

One of the main questions in evolutionary and conservation biology is how geographical and environmental features of the landscape shape neutral and adaptive genetic variation in natural populations. The identification of genomic polymorphisms that account for adaptive variation can aid in finding candidate loci for local adaptation. Consequently, a comparison of spatial patterns in neutral markers and loci under selection may help disentangle the effects of gene flow, genetic drift and selection at the landscape scale. Many amphibians breed in wetlands, which differ in environmental conditions and in the degree of isolation, enhancing the potential for local adaptation. We used microsatellite markers to measure genetic differentiation among 17 local populations of Rana arvalis breeding in a network of wetlands. We found that locus RC08604 deviated from neutral expectations, suggesting that it is a good candidate for directional selection. We used a genetic network analysis to show that the allele distribution in this locus is correlated with habitat characteristics, whereas this was not the case at neutral markers that displayed a different allele distribution and population network in the study area. The graph approach illustrated the genomic heterogeneity (neutral loci vs. the candidate locus for directional selection) of gene exchange and genetic divergence among populations under directional selection. Limited gene flow between wetlands was only observed at the candidate genomic region under directional selection. RC08604 is partially located inside an up‐regulated thyroid‐hormone receptor (TRβ) gene coordinating the expression of other genes during metamorphosis and appears to be linked with variation in larval life‐history traits found among R. arvalis populations. We suggest that directional selection on genes coding larval life‐history traits is strong enough to maintain the divergence in these genomic regions, reducing the effective recombination of locally adapted alleles but not in other regions of the genome. Integrating this knowledge into conservation plans at the landscape scale will improve the design of management strategies to preserve adaptive genetic diversity in wetland networks.     

The genomic footprint of climate adaptation in Chironomus riparius

The gradual heterogeneity of climatic factors poses varying selection pressures across geographic distances that leave signatures of clinal variation in the genome. Separating signatures of clinal adaptation from signatures of other evolutionary forces, such as demographic processes, genetic drift and adaptation, to nonclinal conditions of the immediate local environment is a major challenge. Here, we examine climate adaptation in five natural populations of the harlequin fly Chironomus riparius sampled along a climatic gradient across Europe. Our study integrates experimental data, individual genome resequencing, Pool‐Seq data and population genetic modelling. Common‐garden experiments revealed significantly different population growth rates at test temperatures corresponding to the population origin along the climate gradient, suggesting thermal adaptation on the phenotypic level. Based on a population genomic analysis, we derived empirical estimates of historical demography and migration. We used an F_ST outlier approach to infer positive selection across the climate gradient, in combination with an environmental association analysis. In total, we identified 162 candidate genes as genomic basis of climate adaptation. Enriched functions among these candidate genes involved the apoptotic process and molecular response to heat, as well as functions identified in studies of climate adaptation in other insects. Our results show that local climate conditions impose strong selection pressures and lead to genomic adaptation despite strong gene flow. Moreover, these results imply that selection to different climatic conditions seems to converge on a functional level, at least between different insect species.     

Sequence differentiation in regions identified by a genome scan for local adaptation

Genome scans using large numbers of randomly selected markers have revealed a small proportion of loci that deviate from neutral expectations and so may mark genomic regions that contribute to local adaptation. Measurements of sequence differentiation and identification of genes in these regions is important but difficult, especially in organisms with limited genetic information available. We have followed up a genome scan in the marine gastropod, Littorina saxatilis, by searching a bacterial artificial chromosome library with differentiated and undifferentiated markers, sequencing four bacterial artificial chromosomes and then analysing sequence variation in population samples for fragments at, and close to the original marker polymorphisms. We show that sequence differentiation follows the patterns expected from the original marker frequencies, that differentiated markers identify independent and highly localized sites and that these sites fall outside coding regions. Two differentiated loci are characterized by insertions of putative transposable elements that appear to have increased in frequency recently and which might influence expression of downstream genes. These results provide strong candidate loci for the study of local adaptation in Littorina. They demonstrate an approach that can be applied to follow up genome scans in other taxa and they show that the genome scan approach can lead rapidly to candidate genes in nonmodel organisms.     

Conditional neutrality at two adjacent NBS-LRR disease resistance loci in natural populations of Arabidopsis lyrata

We examined patterns of nucleotide diversity at a genomic region containing two linked candidate disease resistance (NBS-LRR) genes in seven populations of the outcrossing plant Arabidopsis lyrata. In comparison with two adjacent control genes and neutral reference genes across the genome, the NBS-LRR genes exhibited elevated nonsynonymous variation and a large number of major-effect polymorphisms causing early stop codons and/or frameshift mutations. In contrast, analysis of synonymous diversity provided no evidence that the region was subject to long-term balancing selection or recent selective sweeps in any of the seven populations surveyed. Also in contrast with earlier surveys of one of these R genes, there was no evidence that the resistance genes or the major-effect mutations were subject to elevated differentiation between populations. We suggest that conditional neutrality in the absence of the corresponding pathogen, rather than long-term balancing selection or local adaptation, may in some circumstances be a significant cause of elevated functional polymorphism at R genes. In contrast with the R genes, analysis of diversity and differentiation at the flanking FERONIA locus showed high population divergence, suggesting local adaptation on this locus controlling male-female signalling during fertilization.     

Discovery of genomic regions and candidate genes controlling shelling percentage using QTL‐seq approach in cultivated peanut (Arachis hypogaea L.)

Cultivated peanut (Arachis hypogaea L.) is an important grain legume providing high‐quality cooking oil, rich proteins and other nutrients. Shelling percentage (SP) is the 2nd most important agronomic trait after pod yield and this trait significantly affects the economic value of peanut in the market. Deployment of diagnostic markers through genomics‐assisted breeding (GAB) can accelerate the process of developing improved varieties with enhanced SP. In this context, we deployed the QTL‐seq approach to identify genomic regions and candidate genes controlling SP in a recombinant inbred line population (Yuanza 9102 × Xuzhou 68‐4). Four libraries (two parents and two extreme bulks) were constructed and sequenced, generating 456.89–790.32 million reads and achieving 91.85%–93.18% genome coverage and 14.04–21.37 mean read depth. Comprehensive analysis of two sets of data (Yuanza 9102/two bulks and Xuzhou 68‐4/two bulks) using the QTL‐seq pipeline resulted in discovery of two overlapped genomic regions (2.75 Mb on A09 and 1.1 Mb on B02). Nine candidate genes affected by 10 SNPs with non‐synonymous effects or in UTRs were identified in these regions for SP. Cost‐effective KASP (Kompetitive Allele‐Specific PCR) markers were developed for one SNP from A09 and three SNPs from B02 chromosome. Genotyping of the mapping population with these newly developed KASP markers confirmed the major control and stable expressions of these genomic regions across five environments. The identified candidate genomic regions and genes for SP further provide opportunity for gene cloning and deployment of diagnostic markers in molecular breeding for achieving high SP in improved varieties.     

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.     

Population genomics and geographic dispersal in Chagas disease vectors: Landscape drivers and evidence of possible adaptation to the domestic setting

Accurate prediction of vectors dispersal, as well as identification of adaptations that allow blood-feeding vectors to thrive in built environments, are a basis for effective disease control. Here we adopted a landscape genomics approach to assay gene flow, possible local adaptation, and drivers of population structure in Rhodnius ecuadoriensis, an important vector of Chagas disease. We used a reduced-representation sequencing technique (2b-RADseq) to obtain 2,552 SNP markers across 272 R. ecuadoriensis samples from 25 collection sites in southern Ecuador. Evidence of high and directional gene flow between seven wild and domestic population pairs across our study site indicates insecticide-based control will be hindered by repeated re-infestation of houses from the forest. Preliminary genome scans across multiple population pairs revealed shared outlier loci potentially consistent with local adaptation to the domestic setting, which we mapped to genes involved with embryogenesis and saliva production. Landscape genomic models showed elevation is a key barrier to R. ecuadoriensis dispersal. Together our results shed early light on the genomic adaptation in triatomine vectors and facilitate vector control by predicting that spatially-targeted, proactive interventions would be more efficacious than current, reactive approaches.     

Patterns of divergence across the geographic and genomic landscape of a butterfly hybrid zone associated with a climatic gradient

Hybrid zones are a valuable tool for studying the process of speciation and for identifying the genomic regions undergoing divergence and the ecological (extrinsic) and nonecological (intrinsic) factors involved. Here, we explored the genomic and geographic landscape of divergence in a hybrid zone between Papilio glaucus and Papilio canadensis. Using a genome scan of 28,417 ddRAD SNPs, we identified genomic regions under possible selection and examined their distribution in the context of previously identified candidate genes for ecological adaptations. We showed that differentiation was genomewide, including multiple candidate genes for ecological adaptations, particularly those involved in seasonal adaptation and host plant detoxification. The Z chromosome and four autosomes showed a disproportionate amount of differentiation, suggesting genes on these chromosomes play a potential role in reproductive isolation. Cline analyses of significantly differentiated genomic SNPs, and of species‐diagnostic genetic markers, showed a high degree of geographic coincidence (81%) and concordance (80%) and were associated with the geographic distribution of a climate‐mediated developmental threshold (length of the growing season). A relatively large proportion (1.3%) of the outliers for divergent selection were not associated with candidate genes for ecological adaptations and may reflect the presence of previously unrecognized intrinsic barriers between these species. These results suggest that exogenous (climate‐mediated) and endogenous (unknown) clines may have become coupled and act together to reinforce reproductive isolation. This approach of assessing divergence across both the genomic and geographic landscape can provide insight about the interplay between the genetic architecture of reproductive isolation and endogenous and exogenous selection.     

Genome scans on experimentally evolved populations reveal candidate regions for adaptation to plant resistance in the potato cyst nematode Globodera pallida

Improving resistance durability involves to be able to predict the adaptation speed of pathogen populations. Identifying the genetic bases of pathogen adaptation to plant resistances is a useful step to better understand and anticipate this phenomenon. Globodera pallida is a major pest of potato crop for which a resistance QTL, GpaV_vrn, has been identified in Solanum vernei. However, its durability is threatened as G. pallida populations are able to adapt to the resistance in few generations. The aim of this study was to investigate the genomic regions involved in the resistance breakdown by coupling experimental evolution and high‐density genome scan. We performed a whole‐genome resequencing of pools of individuals (Pool‐Seq) belonging to G. pallida lineages derived from two independent populations having experimentally evolved on susceptible and resistant potato cultivars. About 1.6 million SNPs were used to perform the genome scan using a recent model testing for adaptive differentiation and association to population‐specific covariables. We identified 275 outliers and 31 of them, which also showed a significant reduction in diversity in adapted lineages, were investigated for their genic environment. Some candidate genomic regions contained genes putatively encoding effectors and were enriched in SPRYSECs, known in cyst nematodes to be involved in pathogenicity and in (a)virulence. Validated candidate SNPs will provide a useful molecular tool to follow frequencies of virulence alleles in natural G. pallida populations and define efficient strategies of use of potato resistances maximizing their durability.     

Outlier analyses to test for local adaptation to breeding grounds in a migratory arctic seabird

Investigating the extent (or the existence) of local adaptation is crucial to understanding how populations adapt. When experiments or fitness measurements are difficult or impossible to perform in natural populations, genomic techniques allow us to investigate local adaptation through the comparison of allele frequencies and outlier loci along environmental clines. The thick‐billed murre (Uria lomvia) is a highly philopatric colonial arctic seabird that occupies a significant environmental gradient, shows marked phenotypic differences among colonies, and has large effective population sizes. To test whether thick‐billed murres from five colonies along the eastern Canadian Arctic coast show genomic signatures of local adaptation to their breeding grounds, we analyzed geographic variation in genome‐wide markers mapped to a newly assembled thick‐billed murre reference genome. We used outlier analyses to detect loci putatively under selection, and clustering analyses to investigate patterns of differentiation based on 2220 genomewide single nucleotide polymorphisms (SNPs) and 137 outlier SNPs. We found no evidence of population structure among colonies using all loci but found population structure based on outliers only, where birds from the two northernmost colonies (Minarets and Prince Leopold) grouped with birds from the southernmost colony (Gannet), and birds from Coats and Akpatok were distinct from all other colonies. Although results from our analyses did not support local adaptation along the latitudinal cline of breeding colonies, outlier loci grouped birds from different colonies according to their non‐breeding distributions, suggesting that outliers may be informative about adaptation and/or demographic connectivity associated with their migration patterns or nonbreeding grounds.     

Controlling false discoveries in genome scans for selection

Population differentiation (PD) and ecological association (EA) tests have recently emerged as prominent statistical methods to investigate signatures of local adaptation using population genomic data. Based on statistical models, these genomewide testing procedures have attracted considerable attention as tools to identify loci potentially targeted by natural selection. An important issue with PD and EA tests is that incorrect model specification can generate large numbers of false‐positive associations. Spurious association may indeed arise when shared demographic history, patterns of isolation by distance, cryptic relatedness or genetic background are ignored. Recent works on PD and EA tests have widely focused on improvements of test corrections for those confounding effects. Despite significant algorithmic improvements, there is still a number of open questions on how to check that false discoveries are under control and implement test corrections, or how to combine statistical tests from multiple genome scan methods. This tutorial study provides a detailed answer to these questions. It clarifies the relationships between traditional methods based on allele frequency differentiation and EA methods and provides a unified framework for their underlying statistical tests. We demonstrate how techniques developed in the area of genomewide association studies, such as inflation factors and linear mixed models, benefit genome scan methods and provide guidelines for good practice while conducting statistical tests in landscape and population genomic applications. Finally, we highlight how the combination of several well‐calibrated statistical tests can increase the power to reject neutrality, improving our ability to infer patterns of local adaptation in large population genomic data sets.     

Population genetic differentiation and genomic signatures of adaptation to climate in an abundant lizard

Species distributed across climatic gradients will typically experience spatial variation in selection, but gene flow can prevent such selection from causing population genetic differentiation and local adaptation. Here, we studied genomic variation of 415 individuals across 34 populations of the common wall lizard (Podarcis muralis) in central Italy. This species is highly abundant throughout this region and populations belong to a single genetic lineage, yet there is extensive phenotypic variation across climatic regimes. We used redundancy analysis to, first, quantify the effect of climate and geography on population genomic variation in this region and, second, to test if climate consistently sorts specific alleles across the landscape. Climate explained 5% of the population genomic variation across the landscape, about half of which was collinear with geography. Linear models and redundancy analyses identified loci that were significantly differentiated across climatic regimes. These loci were distributed across the genome and physically associated with genes putatively involved in thermal tolerance, regulation of temperature-dependent metabolism and reproductive activity, and body colouration. Together, these findings suggest that climate can exercise sufficient selection in lizards to promote genetic differentiation across the landscape in spite of high gene flow.Subject terms: Genetic variation, Genetic variation     

AFLP genome scan to detect genetic structure and candidate loci under selection for local adaptation of the invasive weed Mikania micrantha

Why some species become successful invaders is an important issue in invasive biology. However, limited genomic resources make it very difficult for identifying candidate genes involved in invasiveness. Mikania micrantha H.B.K. (Asteraceae), one of the world's most invasive weeds, has adapted rapidly in response to novel environments since its introduction to southern China. In its genome, we expect to find outlier loci under selection for local adaptation, critical to dissecting the molecular mechanisms of invasiveness. An explorative amplified fragment length polymorphism (AFLP) genome scan was used to detect candidate loci under selection in 28 M. micrantha populations across its entire introduced range in southern China. We also estimated population genetic parameters, bottleneck signatures, and linkage disequilibrium. In binary characters, such as presence or absence of AFLP bands, if all four character combinations are present, it is referred to as a character incompatibility. Since character incompatibility is deemed to be rare in populations with extensive asexual reproduction, a character incompatibility analysis was also performed in order to infer the predominant mating system in the introduced M. micrantha populations. Out of 483 AFLP loci examined using stringent significance criteria, 14 highly credible outlier loci were identified by Dfdist and Bayescan. Moreover, remarkable genetic variation, multiple introductions, substantial bottlenecks and character compatibility were found to occur in M. micrantha. Thus local adaptation at the genome level indeed exists in M. micrantha, and may represent a major evolutionary mechanism of successful invasion. Interactions between genetic diversity, multiple introductions, and reproductive modes contribute to increase the capacity of adaptive evolution.     

Origin matters: Using a local reference genome improves measures in population genomics

Genome sequencing enables answering fundamental questions about the genetic basis of adaptation, population structure and epigenetic mechanisms. Yet, we usually need a suitable reference genome for mapping population-level resequencing data. In some model systems, multiple reference genomes are available, giving the challenging task of determining which reference genome best suits the data. Here, we compared the use of two different reference genomes for the three-spined stickleback (Gasterosteus aculeatus), one novel genome derived from a European gynogenetic individual and the published reference genome of a North American individual. Specifically, we investigated the impact of using a local reference versus one generated from a distinct lineage on several common population genomics analyses. Through mapping genome resequencing data of 60 sticklebacks from across Europe and North America, we demonstrate that genetic distance among samples and the reference genomes impacts downstream analyses. Using a local reference genome increased mapping efficiency and genotyping accuracy, effectively retaining more and better data. Despite comparable distributions of the metrics generated across the genome using SNP data (i.e. π, Tajima's D and F_ST), window-based statistics using different references resulted in different outlier genes and enriched gene functions. A marker-based analysis of DNA methylation distributions had a comparably high overlap in outlier genes and functions, yet with distinct differences depending on the reference genome. Overall, our results highlight how using a local reference genome decreases reference bias to increase confidence in downstream analyses of the data. Such results have significant implications in all reference-genome-based population genomic analyses.     

Local Adaptation in the Flowering-Time Gene Network of Balsam Poplar, Populus balsamifera L

Identifying the signature and targets of local adaptation is an increasingly important goal in empirical population genetics. Using data from 443 balsam poplar Populus balsamifera trees sampled from 31 populations, we tested for evidence of geographically variable selection shaping diversity at 27 homologues of the Arabidopsis flowering-time network. These genes are implicated in the control of seasonal phenology, an important determinant of fitness. Using 335 candidate and 412 reference single nucleotide polymorphisms (SNPs), we tested for evidence of local adaptation by searching for elevated population differentiation using F(ST)-based outlier analyses implemented in BayeScan or a Hierarchical Model in Arelquin and by testing for significant associations between allele frequency and environmental variables using BAYENV. A total of 46 SNPs from 14 candidate genes had signatures of local adaptation-either significantly greater population differentiation or significant covariance with one or more environmental variable relative to reference SNP distributions. Only 11 SNPs from two genes exhibited both elevated population differentiation and covariance with one or more environmental variables. Several genes including the abscisic acid gene ABI1B and the circadian clock genes ELF3 and GI5 harbored a large number of SNPs with signatures of local adaptation-with SNPs in GI5 strongly covarying with both latitude and precipitation and SNPs in ABI1B strongly covarying with temperature. In contrast to several other systems, we find little evidence that photoreceptors, including phytochromes, play an important role in local adaptation. Our results additionally show that detecting local adaptation is sensitive to the analytical approaches used and that model-based significance thresholds should be viewed with caution.