Genome-environment Association Research Articles

Local adaptation of Pinus leiophylla under climate and land use change models in the Avocado Belt of Michoacán.

Climate change and land use change are two main drivers of global biodiversity decline, decreasing the genetic diversity that populations harbour and altering patterns of local adaptation. Landscape genomics allows measuring the effect of these anthropogenic disturbances on the adaptation of populations. However, both factors have rarely been considered simultaneously. Based on a set of 3660 SNPs from which 130 were identified as outliers by a genome-environment association analysis (LFMM), we modelled the spatial turnover of allele frequencies in 19 localities of Pinus leiophylla across the Avocado Belt in Michoacán state, Mexico. Then, we evaluated the effect of climate change and land use change scenarios, in addition to evaluating assisted gene flow strategies and connectivity metrics across the landscape to identify priority conservation areas for the species. We found that localities in the centre-east of the Avocado Belt would be more vulnerable to climate change, while localities in the western area are more threatened by land conversion to avocado orchards. Assisted gene flow actions could aid in mitigating both threats. Connectivity patterns among forest patches will also be modified by future habitat loss, with central and eastern parts of the Avocado Belt maintaining the highest connectivity. These results suggest that areas with the highest priority for conservation are in the eastern part of the Avocado Belt, including the Monarch Butterfly Biosphere Reserve. This work is useful as a framework that incorporates distinct layers of information to provide a more robust representation of the response of tree populations to anthropogenic disturbances.

The geno-geo-climate nexus: contributions of geographic and ecological factors in shaping the genomic divergence of two closely related threatened rainforest species of Fontainea Heckel (Euphorbiaceae)

ContextProcesses that shape genomic and ecological divergence can reveal important evolutionary dynamics to inform the conservation of threatened species. Fontainea is a genus of rainforest shrubs and small trees including critically endangered and threatened species restricted to narrow, but complex geographic and ecological regions. Several species of Fontainea are subject to spatially explicit conditions and experience limited intra-specific gene flow, likely generating genetic differentiation and local adaptation.ObjectivesHere, we explored the genetic and ecological mechanisms underlying patterns of diversification in two, closely related threatened Fontainea species. Our aim was to compare spatial patterns of genetic variation between the vulnerable Fontainea australis (Southern Fontainea) and critically endangered F. oraria (Coastal Fontainea), endemic to the heterogeneous subtropical region of central, eastern Australia, where large-scale clearing has severely reduced rainforest habitat to a fraction (< 1%) of its pre-European settlement extent.MethodsWe used a set of 10,000 reduced-representation markers to infer genetic relationships and the drivers of spatial genetic variation across the two species. In addition, we employed a combination of univariate and multivariate genome-environment association analysis using a set of topo-climatic variables to explore potential patterns of local adaptation as a factor impacting genomic divergence.ResultsOur study revealed that Coastal Fontainea have a close genetic relationship with Southern Fontainea. We showed that isolation by distance has played a key role in their genetic variation, indicating that vicariance can explain the spatial genetic distribution of the two species. Genotype-environment analyses showed a strong association with temperature and topographic features, suggesting adaptation to localised thermal environments. We used a multivariate redundancy analysis to identify a range of putatively adapted loci associated with local environmental conditions.ConclusionsDivergent selection at the local-habitat scale as a result of dispersal limitations and environmental heterogeneity (including physical barriers) are likely contributors to adaptive divergence between the two Fontainea species. Our findings have presented evidence to indicate that Southern and Coastal Fontainea were comprised of distinct genetic groups and ecotypes, that together may form a single species continuum, with further phenotype research suggested to confirm the current species boundaries. Proactive conservation actions, including assisted migration to enhance the resilience of populations lacking stress-tolerant single nucleotide polymorphisms (SNPs) may be required to secure the long-term future of both taxa. This is especially vital for the critically endangered Coastal Fontainea given projections of habitat decline for the species under future climate scenarios.

Oryza CLIMtools: A genome–environment association resource reveals adaptive roles for heterotrimeric G proteins in the regulation of rice agronomic traits

Modern crop varieties display a degree of mismatch between their current distributions and the suitability of the local climate for their productivity. To address this issue, we present Oryza CLIMtools (https://gramene.org/CLIMtools/oryza_v1.0/), the first resource for pan-genome prediction of climate-associated genetic variants in a crop species. Oryza CLIMtools consists of interactive web-based databases that enable the user to (1) explore the local environments of traditional rice varieties (landraces) in South-East Asia and (2) investigate the environment by genome associations for 658 Indica and 283 Japonica rice landrace accessions collected from georeferenced local environments and included in the 3K Rice Genomes Project. We demonstrate the value of these resources by identifying an interplay between flowering time and temperature in the local environment that is facilitated by adaptive natural variation in OsHD2 and disrupted by a natural variant in OsSOC1. Prior quantitative trait locus analysis has suggested the importance of heterotrimeric G proteins in the control of agronomic traits. Accordingly, we analyzed the climate associations of natural variants in the different heterotrimeric G protein subunits. We identified a coordinated role of G proteins in adaptation to the prevailing potential evapotranspiration gradient and revealed their regulation of key agronomic traits, including plant height and seed and panicle length. We conclude by highlighting the prospect of targeting heterotrimeric G proteins to produce climate-resilient crops.

Genomic insights into differentiation and adaptation of Amorphophallus yunnanensis in the mountainous region of Southwest China.

The role of geographical isolation and environmental adaptation in driving the differentiation and radiation of species has been a hotspot in evolutionary biology. The extremely complicated and fragmented geography of the mountainous region of Southwest China provides an excellent system for investigating the process of species divergence in heterogeneous habitats. Amorphophallus yunnanensis is a species of extreme habitat preference that resides mainly in the mountainous region of Southwest China. Here, we used restriction site-associated DNA sequencing (RAD-seq) to characterize the geographic pattern of genetic variation among 19 populations of A. yunnanensis as well as the genomic basis of environmental adaptation. A pattern of low population genetic diversity and high level of genetic differentiation was observed. The genomic data revealed a clear east-west genetic differentiation, with two distinct genetic lineages corresponding to the Guizhou plateau and Yunnan plateau, respectively. However, we discovered demographic expansion of the Guizhou Plateau lineage and recent hybridization in populations at the contact region. Significant levels of isolation by distance along with isolation by environment were detected. Outlier tests and genome-environment association analyses identified 89 putatively adaptive loci that might play a role in environmental adaptation. Our results suggest that the genetic divergence of A. yunnanensis is attributed to geographical isolation together with divergent selection in the mountainous region of Southwest China.

Genome-environment association analyses reveal geographically restricted adaptive divergence across the range of the widespread Eurasian carnivore Lynx lynx (Linnaeus, 1758).

Local adaptations to the environment are an important aspect of the diversity of a species and their discovery, description and quantification has important implications for the fields of taxonomy, evolutionary and conservation biology. In this study, we scan genomes from several populations across the distributional range of the Eurasian lynx, with the objective of finding genomic windows under positive selection which may underlie local adaptations to different environments. A total of 394 genomic windows are found to be associated to local environmental conditions, and they are enriched for genes involved in metabolism, behaviour, synaptic organization and neural development. Adaptive genetic structure, reconstructed from SNPs in candidate windows, is considerably different than the neutral genetic structure of the species. A widespread adaptively homogeneous group is recovered occupying areas of harsher snow and temperature climatic conditions in the north-western, central and eastern parts of the distribution. Adaptively divergent populations are recovered in the westernmost part of the range, especially within the Baltic population, but also predicted for different patches in the western and southern part of the range, associated with different snow and temperature regimes. Adaptive differentiation driven by climate does not correlate much with the subspecies taxonomic delimitations, suggesting that subspecific divergences are mostly driven by neutral processes of genetic drift and gene flow. Our results will aid the selection of source populations for assisted gene flow or genetic rescue programs by identifying what climatic patterns to look for as predictors of pre-adaptation of individuals. Particularly, the Carpathian population is confirmed as the best source of individuals for the genetic rescue of the endangered, isolated and genetically eroded Balkan population. Additionally, reintroductions in central and western Europe, currently based mostly on Carpathian lynxes, could consider the Baltic population as an additional source to increase adaptive variation and likely improve adaptation to their milder climate.

Landscape genomics reveals adaptive divergence of indigenous sheep in different ecological environments of Xinjiang, China

Sheep are important livestock animals that have evolved under various ecological pressures. Xinjiang is a region with diverse and harsh environments that have shaped many local sheep breeds with unique characteristics and environmental adaptability. However, these breeds are losing ecological flexibility due to the promotion of intensive farming practices. Here we sequenced 14 local sheep breeds from Xinjiang and analyzed their genetic structure and gene flow with other sheep breeds from neighboring regions. The Tibetan Plateau was the geographic origin of Xinjiang native sheep evolution. We performed genome-environment association analysis and identified Bio9: Mean Temperature of Driest Quarter and Bio15: Precipitation Seasonality as the key environmental factors affecting Xinjiang local sheep and the key genes involved in their survival and adaptation. We classified Xinjiang native sheep breeds into six groups based on their differential genes by pairwise selective sweep analysis and Community Network Analysis. We analyzed transcriptome expression data of 832 sheep tissues and detected tissue-specific enrichment of six group-specific genes in different biological systems. Our results revealed the genetic basis of year-round estrus, drought tolerance, hypoxia resistance, and cold tolerance traits of Xinjiang sheep breeds. Moreover, we proposed conservation strategies for Xinjiang local sheep breeds and provided theoretical guidance for breeding new sheep breeds under global extreme environments.

Genetic structure and first genome-wide insights into the adaptation of a wild relative of grapevine, Vitis berlandieri.

In grafted plants, such as grapevine, increasing the diversity of rootstocks available to growers is an ideal strategy for helping plants to adapt to climate change. The rootstocks used for grapevine are hybrids of various American Vitis, including V. berlandieri. The rootstocks currently use in vineyards are derived from breeding programs involving very small numbers of parental individuals. We investigated the structure of a natural population of V. berlandieri and the association of genetic diversity with environmental variables. In this study, we collected seeds from 78 wild V. berlandieri plants in Texas after open fertilization. We genotyped 286 individuals to describe the structure of the population, and environmental information collected at the sampling site made it possible to perform genome-environment association analysis (GEA). De novo long-read whole-genome sequencing was performed on V. berlandieri and a STRUCTURE analysis was performed. We identified and filtered 104,378 SNPs. We found that there were two subpopulations associated with differences in elevation, temperature, and rainfall between sampling sites. GEA identified three QTL for elevation and 15 QTL for PCA coordinates based on environmental parameter variability. This original study is the first GEA study to be performed on a population of grapevines sampled in natural conditions. Our results shed new light on rootstock genetics and could open up possibilities for introducing greater diversity into genetic improvement programs for grapevine rootstocks.

Historical Selection, Adaptation Signatures, and Ambiguity of Introgressions in Wheat.

Wheat was one of the crops domesticated in the Fertile Crescent region approximately 10,000 years ago. Despite undergoing recent polyploidization, hull-to-free-thresh transition events, and domestication bottlenecks, wheat is now grown in over 130 countries and accounts for a quarter of the world's cereal production. The main reason for its widespread success is its broad genetic diversity that allows it to thrive in different environments. To trace historical selection and hybridization signatures, genome scans were performed on two datasets: approximately 113K SNPs from 921 predominantly bread wheat accessions and approximately 110K SNPs from about 400 wheat accessions representing all ploidy levels. To identify environmental factors associated with the loci, a genome-environment association (GEA) was also performed. The genome scans on both datasets identified a highly differentiated region on chromosome 4A where accessions in the first dataset were dichotomized into a group (n = 691), comprising nearly all cultivars, wild emmer, and most landraces, and a second group (n = 230), dominated by landraces and spelt accessions. The grouping of cultivars is likely linked to their potential ancestor, bread wheat cv. Norin-10. The 4A region harbored important genes involved in adaptations to environmental conditions. The GEA detected loci associated with latitude and temperature. The genetic signatures detected in this study provide insight into the historical selection and hybridization events in the wheat genome that shaped its current genetic structure and facilitated its success in a wide spectrum of environmental conditions. The genome scans and GEA approaches applied in this study can help in screening the germplasm housed in gene banks for breeding, and for conservation purposes.

The Genetic Architecture of Adaptation to Leaf and Root Bacterial Microbiota inArabidopsis thaliana

Understanding the role of the host genome in modulating microbiota variation is a need to shed light on the holobiont theory and overcome the current limits on the description of host-microbiota interactions at the genomic and molecular levels. However, the host genetic architecture structuring microbiota is only partly described in plants. In addition, most association genetic studies on microbiota are often carried out outside the native habitats where the host evolves and the identification of signatures of local adaptation on the candidate genes has been overlooked. To fill these gaps and dissect the genetic architecture driving adaptive plant-microbiota interactions, we adopted a genome-environment association (GEA) analysis on 141 whole-genome sequenced natural populations of Arabidopsis thaliana characterized in situ for their leaf and root bacterial communities in fall and spring, and a large range of nonmicrobial ecological factors (i.e., climate, soil, and plant communities). A much higher fraction of among-population microbiota variance was explained by the host genetics than by nonmicrobial ecological factors. Importantly, the relative importance of host genetics and nonmicrobial ecological factors in explaining the presence of particular operational taxonomic units (OTUs) differs between bacterial families and genera. In addition, the polygenic architecture of adaptation to bacterial communities was highly flexible between plant compartments and seasons. Relatedly, signatures of local adaptation were stronger on quantitative trait loci (QTLs) of the root microbiota in spring. Finally, plant immunity appears as a major source of adaptive genetic variation structuring bacterial assemblages in A. thaliana.

Detection of the local adaptive and genome-wide associated loci in southeast Nigerian taro (Colocasia esculenta (L.) Schott) populations

BackgroundTaro has a long history of being consumed and remains orphan and on the hand Nigeria farmers. The role of farmer-driven artificial selection is not negligible to fit landraces to a particular ecological condition. Limited study has been conducted on genome-wide association and no study has been conducted on genome-environment association for clinal adaptation for taro. Therefore, the objective of this study was to detect loci that are associated with environmental variables and phenotype traits and forward input to breeders. The study used 92 geographical referred taro landraces collected from Southeast (SE) Nigeria.ResultsThe result indicates that SE Nigerian taro has untapped phenotype and genetic variability with low admixture. Redundancy analysis indicated that collinear explained SNP variation more than single climatic variable. Overall, the results indicated that no single method exclusively was able to capture population confounding effects better than the others for all six traits. Nevertheless, based on overall model performance, Blink seemed to provide slight advantage over other models and was selected for all subsequent assessment of genome-environment association (GEA) and genome-wide association study (GWAS) models. Genome scan and GEA identified local adapted loci and co-located genes. A total of nine SNP markers associated with environmental variables. Some of the SNP markers (such as S_101024366) co-located with genes which previously reported for climatic adaptation such as astringency, diaminopimelate decarboxylase and MYB transcription factor. Genome-wide association also identified 45, 40 and 34 significant SNP markers associated with studied traits in combined, year 1 and year 2 data sets, respectively. Out of these, five SNP markers (S1_18891752 S3_100795476, S1_100584471 S1_100896936 and S2_10058799) were consistent in two different data sets.ConclusionsThe findings from this study improve our understanding of the genetic control of adaptive and phenotypic traits in Nigerian taro. However, the study suggests further study on identification of local adaptive loci and GWAS through collection of more landraces throughout the country, and across different agro-ecologies.

Whole-genome resequencing reveals signature of local adaptation and divergence in wild soybean.

Global climate change has threatened world crop production and food security. Decoding the adaptive genetic basis of wild relatives provides an invaluable genomic resource for climate-smart crop breedinG.Here, we performed whole-genome sequencing of 185 diverse wild soybean (Glycine soja) accessions collected from three major agro-ecological zones in China to parse the genomic basis of local adaptation in wild soybean. The population genomic diversity pattern exhibited clear agro-ecological zone-based population structure, and multiple environmental factors were observed to contribute to the genetic divergence. Demographic analysis shows that wild soybeans from the three ecological zones diverged about 1 × 105years ago, and then the effective population sizes have undergone different degrees of expansions. Genome-environment association identified multiple genes involved in the local adaptation, such as flowering time and temperature-related genes. A locus containing two adjacent MADS-box transcription factors on chromosome 19 was identified for multiple environmental factors, and it experienced positive selection that enables the adaptation to high-latitude environment. This study provides insights into the genetic mechanism of ecological adaptation in wild soybean that may facilitate climate-resilient soybean breeding.

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.

Genome-wide signatures in flax pinpoint to adaptive evolution along its ecological gradient

Flax is one of the eight founder crops of agriculture. It is believed to have been domesticated as a long-day plant that has since spread to survive in a wide range of eco-geographic regions extending from the warm Indian subcontinent to the low latitude east African highlands and to the cool and high-latitude Eurasia. Understanding the genetic basis underlying its adaptation and selection events throughout its dispersion is essential to develop cultivars adapted to local environmental conditions.Here we detected genetic signatures of local adaptation and selection events of flax based on 385 accessions from all major flax growing regions of the world using genome scan methods and three genomic datasets: (1) a genome-wide dataset of more than 275K single nucleotide polymorphisms (SNPs), (2) a filtered dataset of 23K SNPs with minor allele frequency >10% and, (3) a 34K exon-derived SNP dataset.Principal component (PC) and fixation index (FS⁢T)-based genome scans yielded consistent outlier SNP loci on chromosomes 1, 8, 9 and 12. Additional loci on chromosomes 3, 7, 8, 10, 11, 13 and 14 were detected using both the PC and FS⁢T methods in two of the three datasets. A genome-environment association (GEA) analysis using the 23K dataset and the first PC of cropping season temperature, day-length and latitude identified significant SNPs on chromosomes 3, 7, 9 and 13.Most of the loci detected by the three methods harbored relevant genes for local adaptation, including some that play roles in day-length, light and other biotic and abiotic stresses responses. Such genetic signatures may help to select pre-breeding materials potentially adapted to specific growing niches prior to field performance trials. Given the current low genotyping cost and freely available environmental data, the genome scans along with GEA can readily provide opportunity to sort out materials suitable to various environmental conditions from large set of germplasm in gene banks and/or in situ, thereby assisting the breeding and genetic conservation efforts.

Population structure and adaptive variation of Helichrysum italicum (Roth) G. Don along eastern Adriatic temperature and precipitation gradient

Immortelle (Helichrysum italicum (Roth) G. Don; Asteraceae) is a perennial plant species native to the Mediterranean region, known for many properties with wide application mainly in perfume and cosmetic industry. A total of 18 wild H. italicum populations systematically sampled along the eastern Adriatic environmental gradient were studied using AFLP markers to determine genetic diversity and structure and to identify loci potentially responsible for adaptive divergence. Results showed higher levels of intrapopulation diversity than interpopulation diversity. Genetic differentiation among populations was significant but low, indicating extensive gene flow between populations. Bayesian analysis of population structure revealed the existence of two genetic clusters. Combining the results of FST - outlier analysis (Mcheza and BayeScan) and genome-environment association analysis (Samβada, LFMM) four AFLP loci strongly associated with the bioclimatic variables Bio03 Isothermality, Bio08 Mean temperature of the wettest quarter, Bio15 Precipitation seasonality, and Bio17 Precipitation of driest quarter were found to be the main variables driving potential adaptive genetic variation in H. italicum along the eastern Adriatic environmental gradient. Redundancy analysis revealed that the partitioning of genetic variation was mainly associated with the adaptation to temperature oscillations. The results of the research may contribute to a clearer understanding of the importance of local adaptations for the genetic differentiation of Mediterranean plants and allow the planning of appropriate conservation strategies. However, considering that the identified outlier loci may be linked to genes under selection rather than being the target of natural selection, future studies must aim at their additional analysis.

Genome-environment association methods comparison supports omnigenic adaptation to ecological niche in malaria vector mosquitoes.

The concept of a fundamental ecological niche is central to questions of geographic distribution, population demography, species conservation, and evolutionary potential. However, robust inference of genomic regions associated with evolutionary adaptation to particular environmental conditions remains difficult due to the myriad of potential confounding processes that can generate heterogeneous patterns of variation across the genome. Here, we interrogate the potential role of genome environment association (GEA) testing as an initial step in building an understanding of the genetic basis of ecological niche. We leverage publicly available genomic data from the Anopheles gambiae 1000 Genomes (Ag1000g) Consortium to test the ability of multiple analytically unique GEA methods to handle confounding patterns of genetic variation, control false positive rates, and discern associations with broadly relevant climate variables from random allele frequency patterns throughout the genome. We found evidence supporting the ability of commonly implemented GEA methods to account for confounding patterns of spatial and genetic variation, and control false positive rates. However, we fail to find evidence supporting the ability of GEA tests to reject signals of adaptation to randomly simulated environmental variables, indicating that discerning between true signals of genome environment adaptation and genome environment correlations resulting from alternative evolutionary processes, remains challenging. Because signals of environmental adaptation are so diffuse and confounded throughout the genome, we argue that genomic adaptation to ecological niche is likely best understood under an omnigenic model wherein highly interconnected, genome-wide gene regulatory networks shape genomic adaptation to key environmental conditions.

Genome-Environment Association Analysis for Bio-Climatic Variables in Common Bean (Phaseolus vulgaris L.) from Brazil.

Abiotic stress is a limiting factor for common bean (Phaseolus vulgaris L.) production globally. The study of the genotypic, phenotypic, and bio-climatic variables in a broad set of accessions may assist the identification of genomic regions involved in the climatic adaptation of the common bean. We conducted a genotyping-by-sequencing analysis using 28,823 SNPs on 110 georeferenced common bean accessions from Brazil to discover associations between SNPs and bio-climatic indexes. The population structure analysis clustered the accessions into two groups corresponding to the Andean and Mesoamerican gene pools. Of the 19 bioclimatic variables, 17 exhibited a significant association with SNPs on chromosomes Pv01, Pv02, Pv03, Pv04, Pv06, Pv09, Pv10, and Pv11 of common bean. Ten candidate genes were associated with specific bio-climatic variables related to temperature and precipitation. The candidate genes associated with this significant Pv09 region encode a Platz transcription factor family protein previously reported to be an essential regulator of drought stress. The SNP markers and candidate genes associated with the bio-climatic variables should be validated in segregating populations for water stress, which could further be used for marker-assisted selection. As a result, bean breeding programs may be able to provide advances in obtaining drought-tolerant cultivars.

The ecological, genetic and genomic architecture of local adaptation and population differentiation in Boechera stricta.

Differential local adaptation restricts gene flow between populations inhabiting distinct environments, resulting in isolation by adaptation. In addition to the statistical inferences of genotype-environment associations, an integrative approach is needed to investigate the effect of local adaptation on population divergence at the ecological, genetic and genomic scale. Here, we combine reciprocal transplant, genome-environment association and QTL mapping to investigate local adaptation in Boechera stricta (Drummond's rockcress). With reciprocal transplant experiment, we found local genetic groups exhibit phenotypic characteristics corresponding to the distinct selection forces from different water availability. At the genetic level, the local allele of a major fitness QTL confers higher and sturdier flowering stalks, maximizing the fecundity fitness component under sufficient water supply, and its genetic variation is associated with precipitation across the landscape. At the genomewide scale, we further showed that multiple loci associated with precipitation are highly differentiated between genetic groups, suggesting that local adaptation has a widespread effect on reducing gene flow. This study provides one of the few comprehensive examples demonstrating how local adaptation facilitates population divergence at the trait, gene and genome level.

Genetic diversity of Ethiopian sorghum reveals signatures of climatic adaptation.

A large collection of Ethiopian sorghum landraces, characterized by agro-ecology and racial-group, was found to contain high levels of diversity and admixture, with significant SNP associations identified for environmental adaptation. Sorghum [Sorghum bicolor L. (Moench)] is a major staple food crop in Ethiopia, exhibiting extensive genetic diversity with adaptations to diverse agroecologies. The environmental and climatic drivers, as well as the genomic basis of adaptation, are poorly understood in Ethiopian sorghum and are critical elements for the development of climate-resilient crops. Exploration of the genome-environment association (GEA) is important for identifying adaptive loci and predicting phenotypic variation. The current study aimed to better understand the GEA of a large collection of Ethiopian sorghum landraces (n = 940), characterized with genome-wide SNP markers, to investigate key traits related to adaptation to temperature, precipitation and altitude. The Ethiopian sorghum landrace collection was found to consist of 12 subpopulations with high levels of admixture (47%), representing all the major racial groups of cultivated sorghum with the exception of kafir. Redundancy analysis indicated that agroecology explained up to 10% of the total SNP variation, and geographical location up to 6%. GEA identified 18 significant SNP markers for environmental variables. These SNPs were found to be significantly enriched (P < 0.05) for a priori QTL for drought and cold adaptation. The findings from this study improve our understanding of the genetic control of adaptive traits in Ethiopian sorghum. Further, the Ethiopian sorghum germplasm collection provides sources of adaptation to harsh environments (cold and/or drought) that could be deployed in breeding programs globally for abiotic stress adaptation.

Canonical correlations reveal adaptive loci and phenotypic responses to climate in perennial ryegrass.

Germplasm from perennial ryegrass (Lolium perenne L.) natural populations is useful for breeding because of its adaptation to a wide range of climates. Climate-adaptive genes can be detected from associations between genotype, phenotype and climate but an integrated framework for the analysis of these three sources of information is lacking. We used two approaches to identify adaptive loci in perennial ryegrass and their effect on phenotypic traits. First, we combined Genome-Environment Association (GEA) and GWAS analyses. Then, we implemented a new test based on a Canonical Correlation Analysis (CANCOR) to detect adaptive loci. Furthermore, we improved the previous perennial ryegrass gene set by de novo gene prediction and functional annotation of 39,967 genes. GEA-GWAS revealed eight outlier loci associated with both environmental variables and phenotypic traits. CANCOR retrieved 633 outlier loci associated with two climatic gradients, characterized by cold-dry winter versus mild-wet winter and long rainy season versus long summer, and pointed out traits putatively conferring adaptation at the extremes of these gradients. Our CANCOR test also revealed the presence of both polygenic and oligogenic climatic adaptations. Our gene annotation revealed that 374 of the CANCOR outlier loci were positioned within or close to a gene. Co-association networks of outlier loci revealed a potential utility of CANCOR for investigating the interaction of genes involved in polygenic adaptations. The CANCOR test provides an integrated framework to analyse adaptive genomic diversity and phenotypic responses to environmental selection pressures that could be used to facilitate the adaptation of plant species to climate change.

A comprehensive phenotypic and genomic characterization of Ethiopian sorghum germplasm defines core collection and reveals rich genetic potential in adaptive traits.

Understanding population genetic structure and diversity of a crop is essential in designing selection strategies in plant breeding. About 2010 Ethiopian sorghum accessions were phenotyped for different traits at multiple locations. A subset of the collection, 1628 accessions, predominantly landraces, some improved varieties, and inbred lines were genotyped by sequencing. Phenotypic data revealed association of important traits with different sorghum growing agro-climatic regions, high genetic diversity and the presence of rare natural variation in the Ethiopian sorghum germplasm. Subsequent genotypic analysis determined optimum number of sub-populations, distinct cluster groups and ancestries of each sorghum accessions. To improve utilization of germplasm, a core subset of 387 lines were selected following posteriorigroupingof genotypes based on cluster groups obtained through GBS analysis followed by stratified random sampling using quantitative traits. In order to evaluate how well this new sorghum and millet innovation lab (SMIL) collection from Ethiopia is represented within the largest world sorghum collection at United States Department of Agriculture - National Plant Germplasm System (USDA-NPGS) and the sorghum association panel (SAP), comparisons were conducted based on SNP data. The SMIL collection displayed high genetic diversity with some redundancy with the USDA-NPGS germplasm but SAP showed clear distinction. Furthermore, genome-environment association analysis identified candidate genes associated with adaptation to abiotic factors, that will be important for exploitation of adaptive potential to different environments.In summary, our results described the diversity and relationship of sorghum collections, representativeness of developed core and provide novel insights into candidate genes associated to abiotic stress tolerance.