Environmental Association Identifies Candidates for Tolerance to Low Temperature and Drought

Environmental genomic selection to leverage polygenic local adaptation in barley landraces

Climate change is threatening agricultural production across the globe. Germplasm collections provide an opportunity to explore where variation exists with important crop species. Genome environment association (GEA) is a standard approach for investigating the genetic basis of adaptation to natural environments. While these analyses provide insight into local adaptation, they have not been widely adopted in breeding or conservation programs. This may be attributable to the difficulty in identifying the best individuals for transplantation/relocation in conservation efforts or identification of the best parents in breeding programs. To explore the potential utility in future breeding programs, we used the cereal crop - barley (Hordeum vulgare L.) due to its wide adaptability to different environments and agroecologies, ranging from marginal and low input fields to high-productive farms. Here, we conduct environmental genomic selection (EGS) on 753 landrace barley accessions using a mini-core of 31 landrace accessions and a de-novo core of 100 as the training populations. Since local adaptation to the environment is polygenic, a whole-genome approach is likely to be more accurate for selection. Here we show how an integrative approach coupling environmental genomic selection and species distribution modelling can help identify key parents for adaptation to specific environmental variables.

Association analyses reveal both anthropic and environmental selective events during eggplant domestication

Eggplant (Solanum melongena) is one of the four most important Solanaceous crops, widely cultivated and consumed in Asia, the Mediterranean basin, and Southeast Europe. We studied the genome-wide association of historical genebank phenotypic data on a genotyped worldwide collection of 3449 eggplant accessions. Overall, 334 significant associations for key agronomic traits were detected. Significant correlations were obtained between different types of phenotypic data, some of which were not obvious, such as between fruit size/yield and fruit color components, suggesting simultaneous anthropic selection for genetically unrelated traits. Anthropic selection of traits like leaf prickles, fruit color, and yield, acted on distinct genomic regions in the two domestication centers (India and Southeast Asia), further confirming the multiple domestication of eggplant. To discriminate anthropic from environmental selection in domestication centers, we conducted a genotype-environment association (GEA) on a subset of georeferenced accessions from the Indian subcontinent. The population structure in this area revealed four genetic clusters, corresponding to a latitudinal gradient, and environmental factors explained 31% of the population structure when the effect of spatial distances was removed. GEA and outlier association identified 305 candidate regions under environmental selection, containing genes for abiotic stress responses, plant development, and flowering transition. Finally, in the Indian domestication center anthropic and environmental selection acted largely independently, and on different genomic regions. These data allow a better understanding of the different effects of environmental and anthropic selection during domestication of a crop, and the different world regions where some traits were initially selected by humans.

Natural selection drives emergent genetic homogeneity in a century-scale experiment with barley

Direct observation is central to our understanding of adaptation, but evolution is rarely documented in a large, multicellular organism for more than a few generations. In this study, we observed evolution across a century-scale competition experiment, barley composite cross II (CCII). CCII was founded in 1929 in Davis, California, with thousands of genotypes, but we found that natural selection has massively reduced genetic diversity, leading to a single lineage constituting most of the population by generation 50. Selection favored alleles originating from climates similar to that of Davis and targeted loci contributing to reproductive development, including the barley diversification loci Vrs1, HvCEN, Ppd-H1, and Vrn-H2. Our findings point to selection as the predominant force shaping genomic variation in one of the world's oldest biological experiments.

Landscape genomics reveals genetic signals of environmental adaptation of African wild eggplants

Crop wild relatives (CWR) provide a valuable resource for improving crops. They possess desirable traits that confer resilience to various environmental stresses. To fully utilize crop wild relatives in breeding and conservation programs, it is important to understand the genetic basis of their adaptation. Landscape genomics associates environments with genomic variation and allows for examining the genetic basis of adaptation. Our study examined the differences in allele frequency of 15,416 single nucleotide polymorphisms (SNPs) generated through genotyping by sequencing approach among 153 accessions of 15 wild eggplant relatives and two cultivated species from Africa, the principal hotspot of these wild relatives. We also explored the correlation between these variations and the bioclimatic and soil conditions at their collection sites, providing a comprehensive understanding of the genetic signals of environmental adaptation in African wild eggplant. Redundancy analysis (RDA) results showed that the environmental variation explained 6% while the geographical distances among the collection sites explained 15% of the genomic variation in the eggplant wild relative populations when controlling for population structure. Our findings indicate that even though environmental factors are not the main driver of selection in eggplant wild relatives, it is influential in shaping the genomic variation over time. The selected environmental variables and candidate SNPs effectively revealed grouping patterns according to the environmental characteristics of sampling sites. Using four genotype-environment association methods, we detected 396 candidate SNPs (2.5% of the initial SNPs) associated with eight environmental factors. Some of these SNPs signal genes involved in pathways that help adapt to environmental stresses such as drought, heat, cold, salinity, pests, and diseases. These candidate SNPs will be useful for marker-assisted improvement and characterizing the germplasm of this crop for developing climate-resilient eggplant varieties. The study provides a model for applying landscape genomics to other crops' wild relatives.

Landscape genomics reveals adaptive genetic differentiation driven by multiple environmental variables in naked barley on the Qinghai-Tibetan Plateau

Understanding the local adaptation of crops has long been a concern of evolutionary biologists and molecular ecologists. Identifying the adaptive genetic variability in the genome is crucial not only to provide insights into the genetic mechanism of local adaptation but also to explore the adaptation potential of crops. This study aimed to identify the climatic drivers of naked barley landraces and putative adaptive loci driving local adaptation on the Qinghai-Tibetan Plateau (QTP). To this end, a total of 157 diverse naked barley accessions were genotyped using the genotyping-by-sequencing approach, which yielded 3123 high-quality SNPs for population structure analysis and partial redundancy analysis, and 37,636 SNPs for outlier analysis. The population structure analysis indicated that naked barley landraces could be divided into four groups. We found that the genomic diversity of naked barley landraces could be partly traced back to the geographical and environmental diversity of the landscape. In total, 136 signatures associated with temperature, precipitation, and ultraviolet radiation were identified, of which 13 had pleiotropic effects. We mapped 447 genes, including a known gene HvSs1. Some genes involved in cold stress and regulation of flowering time were detected near eight signatures. Taken together, these results highlight the existence of putative adaptive loci in naked barley on QTP and thus improve our current understanding of the genetic basis of local adaptation.

UDP-glucosyltransferase HvUGT13248 confers type II resistance to Fusarium graminearum in barley

Fusarium head blight (FHB) of barley (Hordeum vulgare) causes yield losses and accumulation of trichothecene mycotoxins (e.g. deoxynivalenol [DON]) in grains. Glucosylation of DON to the nontoxic DON-3-O-glucoside (D3G) is catalyzed by UDP-glucosyltransferases (UGTs), such as barley UGT13248. We explored the natural diversity of UGT13248 in 496 barley accessions and showed that all carried potential functional alleles of UGT13248, as no genotypes showed strongly increased seedling sensitivity to DON. From a TILLING population, we identified 2 mutant alleles (T368I and H369Y) that, based on protein modeling, likely affect the UDP-glucose binding of UGT13248. In DON feeding experiments, DON-to-D3G conversion was strongly reduced in spikes of these mutants compared to controls, and plants overexpressing UGT13248 showed increased resistance to DON and increased DON-to-D3G conversion. Moreover, field-grown plants carrying the T368I or H369Y mutations inoculated with Fusarium graminearum showed increased FHB disease severity and reduced D3G production. Barley is generally considered to have type II resistance that limits the spread of F. graminearum from the infected spikelet to adjacent spikelets. Point inoculation experiments with F. graminearum showed increased infection spread in T368I and H369Y across the spike compared to wild type, while overexpression plants showed decreased spread of FHB symptoms. Confocal microscopy revealed that F. graminearum spread to distant rachis nodes in T368I and H369Y mutants but was arrested at the rachis node of the inoculated spikelet in wild-type plants. Taken together, our data reveal that UGT13248 confers type II resistance to FHB in barley via conjugation of DON to D3G.

Detection of locally adapted genomic regions in wild rice (Oryza rufipogon) using environmental association analysis

Oryza rufipogon is the wild progenitor of cultivated rice Oryza sativa and exhibits high levels of genetic diversity across its distribution, making it a useful resource for the identification of abiotic stress-tolerant varieties and genes that could limit future climate-changed-induced yield losses. To investigate local adaptation in O. rufipogon, we analyzed single nucleotide polymorphism (SNP) data from a panel of 286 samples located across a diverse range of climates. Environmental association analysis (EAA), a genome-wide association study (GWAS)-based method, was used and revealed 15 regions of the genome significantly associated with various climate factors. Genes within these environmentally associated regions have putative functions in abiotic stress response, phytohormone signaling, and the control of flowering time. This provides an insight into potential local adaptation in O. rufipogon and reveals possible locally adaptive genes that may provide opportunities for breeding novel rice varieties with climate change-resilient phenotypes.

Where the wild things are: genetic associations of environmental adaptation in the Oryza rufipogon species complex

Crop wild relatives host unique adaptation strategies that enable them to thrive across a wide range of habitats. As pressures from a changing climate mount, a more complete understanding of the genetic variation that underlies this adaptation could enable broader utilization of wild materials for crop improvement. Here, we carry out environmental association analyses (EAA) in the Oryza rufipogon species complex (ORSC), the wild progenitor of cultivated Asian rice, to identify genomic regions associated with environmental adaptation characterized by variation in bioclimatic and soil variables. We further examine regions for colocalizations with phenotypic associations within the same collection. EAA results indicate that significant regions tend to associate with single environmental variables, although 2 significant loci on chromosomes 3 and 5 are detected as common across multiple variable types (i.e. precipitation, temperature, and/or soil). Distributions of allele frequencies at significant loci across subpopulations of cultivated Oryza sativa indicate that, in some cases, adaptive variation may already be present among cultivars, although evaluation in cultivated populations is needed to empirically test this. This work has implications for the potential utility of wild genetic resources in pre-breeding efforts for rice improvement.

Genomic-environmental associations in wild cranberry (Vaccinium macrocarpon Ait.)

Understanding the genetic basis of local adaptation in natural plant populations, particularly crop wild relatives, may be highly useful for plant breeding. By characterizing genetic variation for adaptation to potentially stressful environmental conditions, breeders can make targeted use of crop wild relatives to develop cultivars for novel or changing environments. This is especially appealing for improving long-lived woody perennial crops such as the American cranberry (Vaccinium macrocarpon Ait.), the cultivation of which is challenged by biotic and abiotic stresses. In this study, we used environmental association analyses in a collection of 111 wild cranberry accessions to identify potentially adaptive genomic regions for a range of bioclimatic and soil conditions. We detected 126 significant associations between SNP marker loci and environmental variables describing temperature, precipitation, and soil attributes. Many of these markers tagged genes with functional annotations strongly suggesting a role in adaptation to biotic or abiotic conditions. Despite relatively low genetic variation in cranberry, our results suggest that local adaptation to divergent environments is indeed present, and the identification of potentially adaptive genetic variation may enable a selective use of this germplasm for breeding more stress-tolerant cultivars.

Worldwide Selection Footprints for Drought and Heat in Bread Wheat (Triticum aestivum L.)

Genome–environment Associations (GEA) or Environmental Genome-Wide Association scans (EnvGWAS) have been poorly applied for studying the genomics of adaptive traits in bread wheat landraces (Triticum aestivum L.). We analyzed 990 landraces and seven climatic variables (mean temperature, maximum temperature, precipitation, precipitation seasonality, heat index of mean temperature, heat index of maximum temperature, and drought index) in GEA using the FarmCPU approach with GAPIT. Historical temperature and precipitation values were obtained as monthly averages from 1970 to 2000. Based on 26,064 high-quality SNP loci, landraces were classified into ten subpopulations exhibiting high genetic differentiation. The GEA identified 59 SNPs and nearly 89 protein-encoding genes involved in the response processes to abiotic stress. Genes related to biosynthesis and signaling are mainly mediated by auxins, abscisic acid (ABA), ethylene (ET), salicylic acid (SA), and jasmonates (JA), which are known to operate together in modulation responses to heat stress and drought in plants. In addition, we identified some proteins associated with the response and tolerance to stress by high temperatures, water deficit, and cell wall functions. The results provide candidate regions for selection aimed to improve drought and heat tolerance in bread wheat and provide insights into the genetic mechanisms involved in adaptation to extreme environments.

The evolutionary patterns of barley pericentromeric chromosome regions, as shaped by linkage disequilibrium and domestication

The distribution of recombination events along large cereal chromosomes is uneven and is generally restricted to gene-rich telomeric ends. To understand how the lack of recombination affects diversity in the large pericentromeric regions, we analysed deep exome capture data from a final panel of 815 Hordeum vulgare (barley) cultivars, landraces and wild barleys, sampled from across their eco-geographical ranges. We defined and compared variant data across the pericentromeric and non-pericentromeric regions, observing a clear partitioning of diversity both within and between chromosomes and germplasm groups. Dramatically reduced diversity was found in the pericentromeres of both cultivars and landraces when compared with wild barley. We observed a mixture of completely and partially differentiated single-nucleotide polymorphisms (SNPs) between domesticated and wild gene pools, suggesting that domesticated gene pools were derived from multiple wild ancestors. Patterns of genome-wide linkage disequilibrium, haplotype block size and number, and variant frequency within blocks showed clear contrasts among individual chromosomes and between cultivars and wild barleys. Although most cultivar chromosomes shared a single major pericentromeric haplotype, chromosome 7H clearly differentiated the two-row and six-row types associated with different geographical origins. Within the pericentromeric regions we identified 22 387 non-synonymous SNPs, 92 of which were fixed for alternative alleles in cultivar versus wild accessions. Surprisingly, only 29 SNPs found exclusively in the cultivars were predicted to be 'highly deleterious'. Overall, our data reveal an unconventional pericentromeric genetic landscape among distinct barley gene pools, with different evolutionary processes driving domestication and diversification.

Genome-Environment Associations, an Innovative Tool for Studying Heritable Evolutionary Adaptation in Orphan Crops and Wild Relatives

Leveraging innovative tools to speed up prebreeding and discovery of genotypic sources of adaptation from landraces, crop wild relatives, and orphan crops is a key prerequisite to accelerate genetic gain of abiotic stress tolerance in annual crops such as legumes and cereals, many of which are still orphan species despite advances in major row crops. Here, we review a novel, interdisciplinary approach to combine ecological climate data with evolutionary genomics under the paradigm of a new field of study: genome-environment associations (GEAs). We first exemplify how GEA utilizes in situ georeferencing from genotypically characterized, gene bank accessions to pinpoint genomic signatures of natural selection. We later discuss the necessity to update the current GEA models to predict both regional- and local- or micro-habitat-based adaptation with mechanistic ecophysiological climate indices and cutting-edge GWAS-type genetic association models. Furthermore, to account for polygenic evolutionary adaptation, we encourage the community to start gathering genomic estimated adaptive values (GEAVs) for genomic prediction (GP) and multi-dimensional machine learning (ML) models. The latter two should ideally be weighted by de novo GWAS-based GEA estimates and optimized for a scalable marker subset. We end the review by envisioning avenues to make adaptation inferences more robust through the merging of high-resolution data sources, such as environmental remote sensing and summary statistics of the genomic site frequency spectrum, with the epigenetic molecular functionality responsible for plastic inheritance in the wild. Ultimately, we believe that coupling evolutionary adaptive predictions with innovations in ecological genomics such as GEA will help capture hidden genetic adaptations to abiotic stresses based on crop germplasm resources to assist responses to climate change. "I shall endeavor to find out how nature's forces act upon one another, and in what manner the geographic environment exerts its influence on animals and plants. In short, I must find out about the harmony in nature" Alexander von Humboldt-Letter to Karl Freiesleben, June 1799.

Genomic associations with poxvirus across divergent island populations in Berthelot's pipit

Understanding the mechanisms and genes that enable animal populations to adapt to pathogens is important from an evolutionary, health and conservation perspective. Berthelot's pipit (Anthus berthelotii) experiences extensive and consistent spatial heterogeneity in avian pox infection pressure across its range of island populations, thus providing an excellent system with which to examine how pathogen-mediated selection drives spatial variation in immunogenetic diversity. Here we test for evidence of genetic variation associated with avian pox at both an individual and population-level. At the individual level, we find no evidence that variation in MHC class I and TLR4 (both known to be important in recognising viral infection) was associated with pox infection within two separate populations. However, using genotype-environment association (Bayenv) in conjunction with genome-wide (ddRAD-seq) data, we detected strong associations between population-level avian pox prevalence and allele frequencies of single nucleotide polymorphisms (SNPs) at a number of sites across the genome. These sites were located within genes involved in cellular stress signalling and immune responses, many of which have previously been associated with responses to viral infection in humans and other animals. Consequently, our analyses indicates that pathogen-mediated selection may play a role in shaping genomic variation among relatively recently colonised island bird populations and highlights the utility of genotype-environment associations for identifying candidate genes potentially involved in host-pathogen interactions.

Genome-Wide Association Study of Waterlogging Tolerance in Barley (Hordeum vulgare L.) Under Controlled Field Conditions

Waterlogging is one of the main abiotic stresses severely reducing barley grain yield. Barley breeding programs focusing on waterlogging tolerance require an understanding of genetic loci and alleles in the current germplasm. In this study, 247 worldwide spring barley genotypes grown under controlled field conditions were genotyped with 35,926 SNPs with minor allele frequency (MAF) > 0.05. Significant phenotypic variation in each trait, including biomass, spikes per plant, grains per plant, kernel weight per plant, plant height and chlorophyll content, was observed. A genome-wide association study (GWAS) based on linkage disequilibrium (LD) for waterlogging tolerance was conducted. Population structure analysis divided the population into three subgroups. A mixed linkage model using both population structure and kinship matrix (Q+K) was performed. We identified 17 genomic regions containing 51 significant waterlogging-tolerance-associated markers for waterlogging tolerance response, accounting for 5.8-11.5% of the phenotypic variation, with a majority of them localized on chromosomes 1H, 2H, 4H, and 5H. Six novel QTL were identified and eight potential candidate genes mediating responses to abiotic stresses were located at QTL associated with waterlogging tolerance. To our awareness, this is the first GWAS for waterlogging tolerance in a worldwide barley collection under controlled field conditions. The marker-trait associations could be used in the marker-assisted selection of waterlogging tolerance and will facilitate barley breeding.

Major flowering time genes of barley: allelic diversity, effects, and comparison with wheat

This review summarizes the allelic series, effects, interactions between genes and with the environment, for the major flowering time genes that drive phenological adaptation of barley. The optimization of phenology is a major goal of plant breeding addressing the production of high-yielding varieties adapted to changing climatic conditions. Flowering time in cereals is regulated by genetic networks that respond predominately to day length and temperature. Allelic diversity at these genes is at the basis of barley wide adaptation. Detailed knowledge of their effects, and genetic and environmental interactions will facilitate plant breeders manipulating flowering time in cereal germplasm enhancement, by exploiting appropriate gene combinations. This review describes a catalogue of alleles found in QTL studies by barley geneticists, corresponding to the genetic diversity at major flowering time genes, the main drivers of barley phenological adaptation: VRN-H1 (HvBM5A), VRN-H2 (HvZCCTa-c), VRN-H3 (HvFT1), PPD-H1 (HvPRR37), PPD-H2 (HvFT3), and eam6/eps2 (HvCEN). For each gene, allelic series, size and direction of QTL effects, interactions between genes and with the environment are presented. Pleiotropic effects on agronomically important traits such as grain yield are also discussed. The review includes brief comments on additional genes with large effects on phenology that became relevant in modern barley breeding. The parallelisms between flowering time allelic variation between the two most cultivated Triticeae species (barley and wheat) are also outlined. This work is mostly based on previously published data, although we added some new data and hypothesis supported by a number of studies. This review shows the wide variety of allelic effects that provide enormous plasticity in barley flowering behavior, which opens new avenues to breeders for fine-tuning phenology of the barley crop.

Introgression Breeding in Barley: Perspectives and Case Studies

Changing production scenarios resulting from unstable climatic conditions are challenging crop improvement efforts. A deeper and more practical understanding of plant genetic resources is necessary if these assets are to be used effectively in developing improved varieties. In general, current varieties and potential varieties have a narrow genetic base, making them prone to suffer the consequences of new and different abiotic and biotic stresses that can reduce crop yield and quality. The deployment of genomic technologies and sophisticated statistical analysis procedures has generated a dramatic change in the way we characterize and access genetic diversity in crop plants, including barley. Various mapping strategies can be used to identify the genetic variants that lead to target phenotypes and these variants can be assigned coordinates in reference genomes. In this way, new genes and/or new alleles at known loci present in wild ancestors, germplasm accessions, land races, and un-adapted introductions can be located and targeted for introgression. In principle, the introgression process can now be streamlined and linkage drag reduced. In this review, we present an overview of (1) past and current efforts to identify diversity that can be tapped to improve barley yield and quality, and (2) case studies of our efforts to introgress resistance to stripe and stem rust from un-adapted germplasm. We conclude with a description of a modified Nested Association Mapping (NAM) population strategy that we are implementing for the development of multi-use naked barley for organic systems and share perspectives on the use of genome editing in introgression breeding.

The Fate of Deleterious Variants in a Barley Genomic Prediction Population

Targeted identification and purging of deleterious genetic variants has been proposed as a novel approach to animal and plant breeding. This strategy is motivated, in part, by the observation that demographic events and strong selection associated with cultivated species pose a "cost of domestication." This includes an increase in the proportion of genetic variants that are likely to reduce fitness. Recent advances in DNA resequencing and sequence constraint-based approaches to predict the functional impact of a mutation permit the identification of putatively deleterious SNPs (dSNPs) on a genome-wide scale. Using exome capture resequencing of 21 barley lines, we identified 3855 dSNPs among 497,754 total SNPs. We generated whole-genome resequencing data of Hordeum murinum ssp. glaucum as a phylogenetic outgroup to polarize SNPs as ancestral vs. derived. We also observed a higher proportion of dSNPs per synonymous SNPs (sSNPs) in low-recombination regions of the genome. Using 5215 progeny from a genomic prediction experiment, we examined the fate of dSNPs over three breeding cycles. Adjusting for initial frequency, derived alleles at dSNPs reduced in frequency or were lost more often than other classes of SNPs. The highest-yielding lines in the experiment, as chosen by standard genomic prediction approaches, carried fewer homozygous dSNPs than randomly sampled lines from the same progeny cycle. In the final cycle of the experiment, progeny selected by genomic prediction had a mean of 5.6% fewer homozygous dSNPs relative to randomly chosen progeny from the same cycle.