Characterizing genomic variation of Arabidopsis thaliana: the roles of geography and climate

Arabidopsis thaliana inhabits diverse climates and exhibits varied phenology across its range. Although A. thaliana is an extremely well‐studied model species, the relationship between geography, growing season climate and its genetic variation is poorly characterized. We used redundancy analysis (RDA) to quantify the association of genomic variation [214 051 single nucleotide polymorphisms (SNPs)] with geography and climate among 1003 accessions collected from 447 locations in Eurasia. We identified climate variables most correlated with genomic variation, which may be important selective gradients related to local adaptation across the species range. Climate variation among sites of origin explained slightly more genomic variation than geographical distance. Large‐scale spatial gradients and early spring temperatures explained the most genomic variation, while growing season and summer conditions explained the most after controlling for spatial structure. SNP variation in Scandinavia showed the greatest climate structure among regions, possibly because of relatively consistent phenology and life history of populations in this region. Climate variation explained more variation among nonsynonymous SNPs than expected by chance, suggesting that much of the climatic structure of SNP correlations is due to changes in coding sequence that may underlie local adaptation.     

Signatures of polygenic adaptation associated with climate across the range of a threatened fish species with high genetic connectivity

Adaptive differences across species’ ranges can have important implications for population persistence and conservation management decisions. Despite advances in genomic technologies, detecting adaptive variation in natural populations remains challenging. Key challenges in gene–environment association studies involve distinguishing the effects of drift from those of selection and identifying subtle signatures of polygenic adaptation. We used paired‐end restriction site‐associated DNA sequencing data (6,605 biallelic single nucleotide polymorphisms; SNPs) to examine population structure and test for signatures of adaptation across the geographic range of an iconic Australian endemic freshwater fish species, the Murray cod Maccullochella peelii. Two univariate gene–association methods identified 61 genomic regions associated with climate variation. We also tested for subtle signatures of polygenic adaptation using a multivariate method (redundancy analysis; RDA). The RDA analysis suggested that climate (temperature‐ and precipitation‐related variables) and geography had similar magnitudes of effect in shaping the distribution of SNP genotypes across the sampled range of Murray cod. Although there was poor agreement among the candidate SNPs identified by the univariate methods, the top 5% of SNPs contributing to significant RDA axes included 67% of the SNPs identified by univariate methods. We discuss the potential implications of our findings for the management of Murray cod and other species generally, particularly in relation to informing conservation actions such as translocations to improve evolutionary resilience of natural populations. Our results highlight the value of using a combination of different approaches, including polygenic methods, when testing for signatures of adaptation in landscape genomic studies.     

Physical geography,isolation by distance and environmental variables shape genomic variation of wild barley (Hordeum vulgare L. ssp. spontaneum) in the Southern Levant

Determining the extent of genetic variation that reflects local adaptation in crop-wild relatives is of interest for the purpose of identifying useful genetic diversity for plant breeding. We investigated the association of genomic variation with geographical and environmental factors in wild barley (Hordeum vulgare L. ssp. spontaneum) populations of the Southern Levant using genotyping by sequencing (GBS) of 244 accessions in the Barley 1K+ collection. The inference of population structure resulted in four genetic clusters that corresponded to eco-geographical habitats and a significant association between lower gene flow rates and geographical barriers, e.g. the Judaean Mountains and the Sea of Galilee. Redundancy analysis (RDA) revealed that spatial autocorrelation explained 45% and environmental variables explained 15% of total genomic variation. Only 4.5% of genomic variation was solely attributed to environmental variation if the component confounded with spatial autocorrelation was excluded. A synthetic environmental variable combining latitude, solar radiation, and accumulated precipitation explained the highest proportion of genomic variation (3.9%). When conditioned on population structure, soil water capacity was the most important environmental variable explaining 1.18% of genomic variation. Genome scans with outlier analysis and genome-environment association studies were conducted to identify adaptation signatures. RDA and outlier methods jointly detected selection signatures in the pericentromeric regions, which have reduced recombination, of the chromosomes 3H, 4H, and 5H. However, selection signatures mostly disappeared after correction for population structure. In conclusion, adaptation to the highly diverse environments of the Southern Levant over short geographical ranges had a limited effect on the genomic diversity of wild barley. This highlighted the importance of nonselective forces in genetic differentiation.Subject terms: Genetic variation, Agriculture, Evolutionary ecology, Evolutionary genetics, Plant evolution     

SNPs in stress-responsive rice genes: validation, genotyping, functional relevance and population structure

ABSTRACT: BACKGROUND: Single nucleotide polymorphism (SNP) validation and large-scale genotyping are required to maximize the use of DNA sequence variation and determine the functional relevance of candidate genes for complex stress tolerance traits through genetic association in rice. We used the bead array platform-based Illumina GoldenGate assay to validate and genotype SNPs in a select set of stress-responsive genes to understand their functional relevance and study the population structure in rice. RESULTS: Of the 384 putative SNPs assayed, we successfully validated and genotyped 362 (94.3%). Of these 325 (84.6%) showed polymorphism among the 91 rice genotypes examined. Physical distribution, degree of allele sharing, admixtures and introgression, and amino acid replacement of SNPs in 263 abiotic and 62 biotic stress-responsive genes provided clues for identification and targeted mapping of trait-associated genomic regions. We assessed the functional and adaptive significance of validated SNPs in a set of contrasting drought tolerant upland and sensitive lowland rice genotypes by correlating their allelic variation with amino acid sequence alterations in catalytic domains and three-dimensional secondary protein structure encoded by stress-responsive genes. We found a strong genetic association among SNPs in the nine stress-responsive genes with upland and lowland ecological adaptation. Higher nucleotide diversity was observed in indica accessions compared with other rice sub-populations based on different population genetic parameters. The inferred ancestry of 16% among rice genotypes was derived from admixed populations with the maximum between upland aus and wild Oryza species. CONCLUSIONS: SNPs validated in biotic and abiotic stress-responsive rice genes can be used in association analyses to identify candidate genes and develop functional markers for stress tolerance in rice.     

Rapid genotyping of soybean cultivars using high throughput sequencing

Soybean (Glycine max) breeding involves improving commercially grown varieties by introgressing important agronomic traits from poor yielding accessions and/or wild relatives of soybean while minimizing the associated yield drag. Molecular markers associated with these traits are instrumental in increasing the efficiency of producing such crosses and Single Nucleotide Polymorphisms (SNPs) are particularly well suited for this task, owing to high density in the non-genic regions and thus increased likelihood of finding a tightly linked marker to a given trait. A rapid method to develop SNP markers that can differentiate specific loci between any two parents in soybean is thus highly desirable. In this study we investigate such a protocol for developing SNP markers between multiple soybean accessions and the reference Williams 82 genome. To restrict sampling frequency reduced representation libraries (RRLs) of genomic DNA were generated by restriction digestion followed by library construction. We chose to sequence four accessions Dowling (PI 548663), Dwight (PI 597386), Komata (PI200492) and PI 594538A for their agronomic importance as well as Williams 82 as a control.MseI was chosen to digest genomic DNA based on predictions that it will cut sparingly in the mathematically defined high-copy-number regions of the genome. All RRLs were sequenced on the Illumina genome analyzer. Reads were aligned to the Glyma1 reference assembly and SNP calls made from the alignments. We identified from 4294 to 14550 SNPs between the four accessions and the Williams 82 reference. In addition a small number of SNPs (1142) were found by aligning Williams 82 reads to the reference assembly (Glyma1) suggesting limited genetic variation within the Williams 82 line. The SNP data allowed us to estimate genetic diversity between the four lines and Williams 82. Restriction digestion of soybean genomic DNA with MseI followed by high throughput sequencing provides a rapid and reproducible method for generating SNP markers.     

Application of High-Throughput Sequencing to Evaluate the Genetic Diversity Among Wild Apple Species Indigenous to Shandong,China, and Introduced Cultivars

The Taiyi mountainous region of Shandong province in eastern China has an abundance of wild Malus species. We evaluated the genetic diversity of 88 Malus accessions (45 Asian apple cultivars, 10 American apple cultivars, 12 European apple cultivars, 19 Chinese wild apples, and two apple cultivars with unknown origins) based on single-nucleotide polymorphism (SNP) markers. A total of 38,364 SNPs were obtained with an average of 2256 SNPs per chromosome. The average of the polymorphism information content (PIC), gene diversity, and allele frequency for SNPs was 0.268, 0.306, and 0.364, respectively. A circular phylogenetic tree constructed based on SNP data revealed that the 88 Malus accessions could be divided into three groups. However, a population structure analysis suggested the 88 Malus accessions could be divided into four groups. A principal component analysis (PCA) revealed some population stratification. The first three PCs accounted for 41.62% of the population-wide SNP variation, with PC1 accounting for 33.9%. Moreover, the kinship values of the 88 Malus accessions ranged from 0 to 2.36, with 96.42% of the kinship values between 0 and 0.2. A phylogenetic tree and a PCA indicated the Chinese wild apples widely distributed among the cultivated apples had a diverse genetic background. Characterizing the genetic relationships between cultivated apples and Chinese wild apples is essential for increasing the genetic diversity of the germplasms used by apple breeders.

     

Genomic divergence across ecological gradients in the Central African rainforest songbird (Andropadus virens)

The little greenbul, a common rainforest passerine from sub‐Saharan Africa, has been the subject of long‐term evolutionary studies to understand the mechanisms leading to rainforest speciation. Previous research found morphological and behavioural divergence across rainforest–savannah transition zones (ecotones), and a pattern of divergence with gene flow suggesting divergent natural selection has contributed to adaptive divergence and ecotones could be important areas for rainforests speciation. Recent advances in genomics and environmental modelling make it possible to examine patterns of genetic divergence in a more comprehensive fashion. To assess the extent to which natural selection may drive patterns of differentiation, here we investigate patterns of genomic differentiation among populations across environmental gradients and regions. We find compelling evidence that individuals form discrete genetic clusters corresponding to distinctive environmental characteristics and habitat types. Pairwise F_ST between populations in different habitats is significantly higher than within habitats, and this differentiation is greater than what is expected from geographic distance alone. Moreover, we identified 140 SNPs that showed extreme differentiation among populations through a genomewide selection scan. These outliers were significantly enriched in exonic and coding regions, suggesting their functional importance. Environmental association analysis of SNP variation indicates that several environmental variables, including temperature and elevation, play important roles in driving the pattern of genomic diversification. Results lend important new genomic evidence for environmental gradients being important in population differentiation.     

The population genomic signature of environmental association and gene flow in an ecologically divergent tree species Metrosideros polymorpha (Myrtaceae)

Genomewide markers enable us to study genetic differentiation within a species and the factors underlying it at a much higher resolution than before, which advances our understanding of adaptation in organisms. We investigated genomic divergence in Metrosideros polymorpha, a woody species that occupies a wide range of ecological habitats across the Hawaiian Islands and shows remarkable phenotypic variation. Using 1659 single nucleotide polymorphism (SNP) markers annotated with the genome assembly, we examined the population genetic structure and demographic history of nine populations across five elevations and two ages of substrates on Mauna Loa, the island of Hawaii. The nine populations were differentiated into two genetic clusters distributed on the lower and higher elevations and were largely admixed on the middle elevation. Demographic modelling revealed that the two genetic clusters have been maintained in the face of gene flow, and the effective population size of the high‐altitude cluster was much smaller. A F_ST‐based outlier search among the 1659 SNPs revealed that 34 SNPs (2.05%) were likely to be under divergent selection and the allele frequencies of 21 of them were associated with environmental changes along elevations, such as temperature and precipitation. This study shows a genomic mosaic of M. polymorpha, in which contrasting divergence patterns were found. While most genomic polymorphisms were shared among populations, a small fraction of the genome was significantly differentiated between populations in diverse environments and could be responsible for the dramatic adaptation to a wide range of environments.     

Genome architecture and diverged selection shaping pattern of genomic differentiation in wild barley

Divergent selection of populations in contrasting environments leads to functional genomic divergence. However, the genomic architecture underlying heterogeneous genomic differentiation remains poorly understood. Here, we de novo assembled two high-quality wild barley (Hordeum spontaneum K. Koch) genomes and examined genomic differentiation and gene expression patterns under abiotic stress in two populations. These two populations had a shared ancestry and originated in close geographic proximity but experienced different selective pressures due to their contrasting micro-environments. We identified structural variants that may have played significant roles in affecting genes potentially associated with well-differentiated phenotypes such as flowering time and drought response between two wild barley genomes. Among them, a 29-bp insertion into the promoter region formed a cis-regulatory element in the HvWRKY45 gene, which may contribute to enhanced tolerance to drought. A single SNP mutation in the promoter region may influence HvCO5 expression and be putatively linked to local flowering time adaptation. We also revealed significant genomic differentiation between the two populations with ongoing gene flow. Our results indicate that SNPs and small SVs link to genetic differentiation at the gene level through local adaptation and are maintained through divergent selection. In contrast, large chromosome inversions may have shaped the heterogeneous pattern of genomic differentiation along the chromosomes by suppressing chromosome recombination and gene flow. Our research offers novel insights into the genomic basis underlying local adaptation and provides valuable resources for the genetic improvement of cultivated barley.     

Signatures of local adaptation in candidate genes of oaks (Quercus spp.) with respect to present and future climatic conditions

Testing how populations are locally adapted and predicting their response to their future environment is of key importance in view of climate change. Landscape genomics is a powerful approach to investigate genes and environmental factors involved in local adaptation. In a pooled amplicon sequencing approach of 94 genes in 71 populations, we tested whether >3500 single nucleotide polymorphisms (SNPs) in the three most common oak species in Switzerland (Quercus petraea, Q. pubescens, Q. robur) show an association with abiotic factors related to local topography, historical climate and soil characteristics. In the analysis including all species, the most frequently associated environmental factors were those best describing the habitats of the species. In the species‐specific analyses, the most important environmental factors and associated SNPs greatly differed among species. However, we identified one SNP and seven genes that were associated with the same environmental factor across all species. We finally used regressions of allele frequencies of the most strongly associated SNPs along environmental gradients to predict the risk of nonadaptedness (RONA), which represents the average change in allele frequency at climate‐associated loci theoretically required to match future climatic conditions. RONA is considerable for some populations and species (up to 48% in single populations) and strongly differs among species. Given the long generation time of oaks, some of the required allele frequency changes might not be realistic to achieve based on standing genetic variation. Hence, future adaptedness requires gene flow or planting of individuals carrying beneficial alleles from habitats currently matching future climatic conditions.     

Contrasting patterns of local adaptation along climatic gradients between a sympatric parasitic and autotrophic tree species

Sympatric tree species are subject to similar climatic drivers, posing a question as to whether they display comparable adaptive responses. However, no study has explicitly examined local adaptation of co‐occurring parasitic and autotrophic plant species to the abiotic environment. Here we test the hypotheses that a generalist parasitic tree would display a weaker signal of selection and that genomic variation would associate with fewer climatic variables (particularly precipitation) but have similar spatial patterns to a sympatric autotrophic tree species. To test these hypotheses, we collected samples from 17 sites across the range of two tree species, the hemiparasite Nuytsia floribunda (n = 264) and sympatric autotroph Melaleuca rhaphiophylla (n = 272). We obtained 5,531 high‐quality genome‐wide single nucleotide polymorphisms (SNPs) for M. rhaphiophylla and 6,727 SNPs for N. floribunda using DArTseq genome scan technology. Population differentiation and environmental association approaches were used to identify signals of selection. Generalized dissimilarly modelling was used to detect climatic and spatial patterns of local adaptation across climatic gradients. Overall, 322 SNPs were identified as putatively adaptive for the autotroph, while only 57 SNPs were identified for the parasitic species. We found genomic variation to associate with different sets of bioclimatic variables for each species, with precipitation relatively less important for the parasite. Spatial patterns of predicted adaptive variability were different and indicate that co‐occurring species with disparate life history traits may not respond equally to selective pressures (i.e., temperature and precipitation). Together, these findings provide insight into local adaptation of sympatric parasitic and autotrophic tree species to abiotic environments.     

Characterisation of Adaptive Genetic Diversity in Environmentally Contrasted Populations of Eucalyptus camaldulensis Dehnh. (River Red Gum)

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

Ecological and evolutionary genomics in the wild tomatoes (Solanum sect. Lycopersicon)

The plant group Solanum section Lycopersicon (the clade containing the domesticated tomato and its wild relatives) is ideal for integrating genomic tools and approaches into ecological and evolutionary research. Wild species within Lycopersicon span broad morphological, physiological, life history, mating system, and biochemical variation, and are separated by substantial, but incomplete postmating reproductive barriers, making this an ideal system for genetic analyses of these traits. This ecological and evolutionary diversity is matched by many logistical advantages, including extensive historical occurrence records for all species in the group, publicly available germplasm for hundreds of known wild accessions, demonstrated experimental tractability, and extensive genetic, genomic, and functional tools and information from the tomato research community. Here I introduce the numerous advantages of this system for Ecological and Evolutionary Functional Genomics (EEFG), and outline several ecological and evolutionary phenotypes and questions that can be fruitfully tackled in this system. These include biotic and abiotic adaptation, reproductive trait evolution, and the genetic basis of speciation. With the modest enhancement of some research strengths, this system is poised to join the best of our currently available model EEFG systems.     

Development and evaluation of a 9K SNP array for peach by internationally coordinated SNP detection and validation in breeding germplasm

Although a large number of single nucleotide polymorphism (SNP) markers covering the entire genome are needed to enable molecular breeding efforts such as genome wide association studies, fine mapping, genomic selection and marker-assisted selection in peach [Prunus persica (L.) Batsch] and related Prunus species, only a limited number of genetic markers, including simple sequence repeats (SSRs), have been available to date. To address this need, an international consortium (The International Peach SNP Consortium; IPSC) has pursued a coordinated effort to perform genome-scale SNP discovery in peach using next generation sequencing platforms to develop and characterize a high-throughput Illumina Infinium® SNP genotyping array platform. We performed whole genome re-sequencing of 56 peach breeding accessions using the Illumina and Roche/454 sequencing technologies. Polymorphism detection algorithms identified a total of 1,022,354 SNPs. Validation with the Illumina GoldenGate® assay was performed on a subset of the predicted SNPs, verifying ∼75% of genic (exonic and intronic) SNPs, whereas only about a third of intergenic SNPs were verified. Conservative filtering was applied to arrive at a set of 8,144 SNPs that were included on the IPSC peach SNP array v1, distributed over all eight peach chromosomes with an average spacing of 26.7 kb between SNPs. Use of this platform to screen a total of 709 accessions of peach in two separate evaluation panels identified a total of 6,869 (84.3%) polymorphic SNPs.The almost 7,000 SNPs verified as polymorphic through extensive empirical evaluation represent an excellent source of markers for future studies in genetic relatedness, genetic mapping, and dissecting the genetic architecture of complex agricultural traits. The IPSC peach SNP array v1 is commercially available and we expect that it will be used worldwide for genetic studies in peach and related stone fruit and nut species.     

Genome‐wide single nucleotide polymorphisms reveal population history and adaptive divergence in wild guppies

Adaptation of guppies (Poecilia reticulata) to contrasting upland and lowland habitats has been extensively studied with respect to behaviour, morphology and life history traits. Yet population history has not been studied at the whole‐genome level. Although single nucleotide polymorphisms (SNPs) are the most abundant form of variation in many genomes and consequently very informative for a genome‐wide picture of standing natural variation in populations, genome‐wide SNP data are rarely available for wild vertebrates. Here we use genetically mapped SNP markers to comprehensively survey genetic variation within and among naturally occurring guppy populations from a wide geographic range in Trinidad and Venezuela. Results from three different clustering methods, Neighbor‐net, principal component analysis (PCA) and Bayesian analysis show that the population substructure agrees with geographic separation and largely with previously hypothesized patterns of historical colonization. Within major drainages (Caroni, Oropouche and Northern), populations are genetically similar, but those in different geographic regions are highly divergent from one another, with some indications of ancient shared polymorphisms. Clear genomic signatures of a previous introduction experiment were seen, and we detected additional potential admixture events. Headwater populations were significantly less heterozygous than downstream populations. Pairwise F_ST values revealed marked differences in allele frequencies among populations from different regions, and also among populations within the same region. F_ST outlier methods indicated some regions of the genome as being under directional selection. Overall, this study demonstrates the power of a genome‐wide SNP data set to inform for studies on natural variation, adaptation and evolution of wild populations     

Quantifying effects of environmental and geographical factors on patterns of genetic differentiation

Elucidating the factors influencing genetic differentiation is an important task in biology, and the relative contribution from natural selection and genetic drift has long been debated. In this study, we used a regression-based approach to simultaneously estimate the quantitative contributions of environmental adaptation and isolation by distance on genetic variation in Boechera stricta, a wild relative of Arabidopsis. Patterns of discrete and continuous genetic differentiation coexist within this species. For the discrete differentiation between two major genetic groups, environment has larger contribution than geography, and we also identified a significant environment-by-geography interaction effect. Elsewhere in the species range, we found a latitudinal cline of genetic variation reflecting only isolation by distance. To further confirm the effect of environmental selection on genetic divergence, we identified the specific environmental variables predicting local genotypes in allopatric and sympatric regions. Water availability was identified as the possible cause of differential local adaptation in both geographical regions, confirming the role of environmental adaptation in driving and maintaining genetic differentiation between the two major genetic groups. In addition, the environment-by-geography interaction is further confirmed by the finding that water availability is represented by different environmental factors in the allopatric and sympatric regions. In conclusion, this study shows that geographical and environmental factors together created stronger and more discrete genetic differentiation than isolation by distance alone, which only produced a gradual, clinal pattern of genetic variation. These findings emphasize the importance of environmental selection in shaping patterns of species-wide genetic variation in the natural environment.     

Drivers of population genetic differentiation in the wild: isolation by dispersal limitation,isolation by adaptation and isolation by colonization

Empirical population genetic studies have been dominated by a neutralist view, according to which gene flow and drift are the main forces driving population genetic structure in nature. The neutralist view in essence describes a process of isolation by dispersal limitation (IBDL) that generally leads to a pattern of isolation by distance (IBD). Recently, however, conceptual frameworks have been put forward that view local genetic adaptation as an important driver of population genetic structure. Isolation by adaptation (IBA) and monopolization (M) posit that gene flow among natural populations is reduced as a consequence of local genetic adaptation. IBA stresses that effective gene flow is reduced among habitats that show dissimilar ecological characteristics, leading to a pattern of isolation by environment. In monopolization, local genetic adaptation of initial colonizing genotypes results in a reduction in gene flow that fosters the persistence of founder effects. Here, we relate these different processes driving landscape genetic structure to patterns of IBD and isolation by environment (IBE). We propose a method to detect whether IBDL, IBA and M shape genetic differentiation in natural landscapes by studying patterns of variation at neutral and non‐neutral markers as well as at ecologically relevant traits. Finally, we reinterpret a representative number of studies from the recent literature by associating patterns to processes and identify patterns associated with local genetic adaptation to be as common as IBDL in structuring regional genetic variation of populations in the wild. Our results point to the importance of quantifying environmental gradients and incorporating ecology in the analysis of population genetics.