Genome‐wide signatures of flowering adaptation to climate temperature: Regional analyses in a highly diverse native range of Arabidopsis thaliana

Current global change is fueling an interest to understand the genetic and molecular mechanisms of plant adaptation to climate. In particular, altered flowering time is a common strategy for escape from unfavourable climate temperature. In order to determine the genomic bases underlying flowering time adaptation to this climatic factor, we have systematically analysed a collection of 174 highly diverse Arabidopsis thaliana accessions from the Iberian Peninsula. Analyses of 1.88 million single nucleotide polymorphisms provide evidence for a spatially heterogeneous contribution of demographic and adaptive processes to geographic patterns of genetic variation. Mountains appear to be allele dispersal barriers, whereas the relationship between flowering time and temperature depended on the precise temperature range. Environmental genome‐wide associations supported an overall genome adaptation to temperature, with 9.4% of the genes showing significant associations. Furthermore, phenotypic genome‐wide associations provided a catalogue of candidate genes underlying flowering time variation. Finally, comparison of environmental and phenotypic genome‐wide associations identified known (Twin Sister of FT, FRIGIDA‐like 1, and Casein Kinase II Beta chain 1) and new (Epithiospecifer Modifier 1 and Voltage‐Dependent Anion Channel 5) genes as candidates for adaptation to climate temperature by altered flowering time. Thus, this regional collection provides an excellent resource to address the spatial complexity of climate adaptation in annual plants.     

The genetic architecture of freezing tolerance varies across the range of Arabidopsis thaliana

The capacity to tolerate freezing temperatures limits the geographical distribution of many plants, including several species of agricultural importance. However, the genes involved in freezing tolerance remain largely unknown. Here, we describe the variation in constitutive freezing tolerance that occurs among worldwide accessions of Arabidopsis thaliana. We found that although plants from high latitudes tend to be more freezing tolerant than plants from low latitudes, the environmental factors that shape cold adaptation differ across the species range. Consistent with this, we found that the genetic architecture of freezing tolerance also differs across its range. Conventional genome‐wide association studies helped identify a priori and other promising candidate genes. However, simultaneously modelling climate variables and freezing tolerance together pinpointed other excellent a priori candidate genes. This suggests that if the selective factor underlying phenotypic variation is known, multi‐trait mixed models may aid in identifying the genes that underlie adaptation.     

Candidate gene SNP variation in floodplain populations of pedunculate oak (Quercus robur L.) near the species' southern range margin: Weak differentiation yet distinct associations with water availability

Populations residing near species' low‐latitude range margins (LLMs) often occur in warmer and drier environments than those in the core range. Thus, their genetic composition could be shaped by climatic drivers that differ from those occurring at higher latitudes, resulting in potentially adaptive variants of conservation value. Such variants could facilitate the adaptation of populations from other portions of the geographical range to similar future conditions anticipated under ongoing climate change. However, very few studies have assessed standing genetic variation at potentially adaptive loci in natural LLM populations. We investigated standing genetic variation at single nucleotide polymorphisms (SNPs) located within 117 candidate genes and its links to putative climatic selection pressures across 19 pedunculate oak (Quercus robur L.) populations distributed along a regional climatic gradient near the species' southern range margin in southeastern Europe. These populations are restricted to floodplain forests along large lowland rivers, whose hydric regime is undergoing significant shifts under modern rapid climate change. The populations showed very weak geographical structure, suggesting extensive genetic connectivity and gene flow or shared ancestry. We identified eight (6.2%) positive F_ST‐outlier loci, and genotype–environment association analyses revealed consistent associations between SNP allele frequencies and several climatic variables linked to water availability. A total of 61 associations involving 37 SNPs (28.5%) from 35 annotated genes provided important insights into putative functional mechanisms in our system. Our findings provide empirical support for the role of LLM populations as sources of potentially adaptive variation that could enhance species’ resilience to climate change‐related pressures.     

Lineage‐specific adaptation to climate involves flowering time in North American Arabidopsis lyrata

Adaptation to local climatic conditions is commonly found within species, but whether it involves the same intraspecific genomic variants is unknown. We studied this question in North American Arabidopsis lyrata, whose current distribution is shaped by post‐glacial range expansion from two refugia, resulting in two distinct genetic clusters covering comparable climatic gradients. Using pooled whole‐genome sequence data of 41 outcrossing populations, we identified loci associated with three niche‐determining climatic variables in the two clusters and compared these outliers. Little evidence was found for parallelism in climate adaptation for single nucleotide polymorphisms (SNPs) and for genes with an accumulation of outlier SNPs. Significantly increased selection coefficients supported them as candidates of climate adaptation. However, the fraction of gene ontology (GO) terms shared between clusters was higher compared to outlier SNPs and outlier genes, suggesting that selection acts on similar pathways but not necessarily the same genes. Enriched GO terms involved responses to abiotic and biotic stress, circadian rhythm and development, with flower development and reproduction being among the most frequently detected. In line with GO enrichment, regulators of flowering time were detected as outlier genes. Our results suggest that while adaptation to environmental gradients on the genomic level are lineage‐specific in A. lyrata, similar biological processes seem to be involved. Differential loss of standing genetic variation, probably driven by genetic drift, can in part account for the lack of parallel evolution on the genomic level.     

Climatic adaptation and ecological divergence between two closely related pine species in Southeast China

Climate is one of the most important drivers for adaptive evolution in forest trees. Climatic selection contributes greatly to local adaptation and intraspecific differentiation, but this kind of selection could also have promoted interspecific divergence through ecological speciation. To test this hypothesis, we examined intra‐ and interspecific genetic variation at 25 climate‐related candidate genes and 12 reference loci in two closely related pine species, Pinus massoniana Lamb. and Pinus hwangshanensis Hisa, using population genetic and landscape genetic approaches. These two species occur in Southeast China but have contrasting ecological preferences in terms of several environmental variables, notably altitude, although hybrids form where their distributions overlap. One or more robust tests detected signals of recent and/or ancient selection at two‐thirds (17) of the 25 candidate genes, at varying evolutionary timescales, but only three of the 12 reference loci. The signals of recent selection were species specific, but signals of ancient selection were mostly shared by the two species likely because of the shared evolutionary history. F_ST outlier analysis identified six SNPs in five climate‐related candidate genes under divergent selection between the two species. In addition, a total of 24 candidate SNPs representing nine candidate genes showed significant correlation with altitudinal divergence in the two species based on the covariance matrix of population history derived from reference SNPs. Genetic differentiation between these two species was higher at the candidate genes than at the reference loci. Moreover, analysis using the isolation‐with‐migration model indicated that gene flow between the species has been more restricted for climate‐related candidate genes than the reference loci, in both directions. Taken together, our results suggest that species‐specific and divergent climatic selection at the candidate genes might have counteracted interspecific gene flow and played a key role in the ecological divergence of these two closely related pine species.     

Genome-Wide Association Analysis of Adaptation Using Environmentally Predicted Traits

Current methods for studying the genetic basis of adaptation evaluate genetic associations with ecologically relevant traits or single environmental variables, under the implicit assumption that natural selection imposes correlations between phenotypes, environments and genotypes. In practice, observed trait and environmental data are manifestations of unknown selective forces and are only indirectly associated with adaptive genetic variation. In theory, improved estimation of these forces could enable more powerful detection of loci under selection. Here we present an approach in which we approximate adaptive variation by modeling phenotypes as a function of the environment and using the predicted trait in multivariate and univariate genome-wide association analysis (GWAS). Based on computer simulations and published flowering time data from the model plant Arabidopsis thaliana, we find that environmentally predicted traits lead to higher recovery of functional loci in multivariate GWAS and are more strongly correlated to allele frequencies at adaptive loci than individual environmental variables. Our results provide an example of the use of environmental data to obtain independent and meaningful information on adaptive genetic variation.     

Altitudinal and climatic adaptation is mediated by flowering traits and FRI, FLC, and PHYC genes in Arabidopsis

Extensive natural variation has been described for the timing of flowering initiation in many annual plants, including the model wild species Arabidopsis (Arabidopsis thaliana), which is presumed to be involved in adaptation to different climates. However, the environmental factors that might shape this genetic variation, as well as the molecular bases of climatic adaptation by modifications of flowering time, remain mostly unknown. To approach both goals, we characterized the flowering behavior in relation to vernalization of 182 Arabidopsis wild genotypes collected in a native region spanning a broad climatic range. Phenotype-environment association analyses identified strong altitudinal clines (0-2600 m) in seven out of nine flowering-related traits. Altitudinal clines were dissected in terms of minimum winter temperature and precipitation, indicating that these are the main climatic factors that might act as selective pressures on flowering traits. In addition, we used an association analysis approach with four candidate genes, FRIGIDA (FRI), FLOWERING LOCUS C (FLC), PHYTOCHROME C (PHYC), and CRYPTOCHROME2, to decipher the genetic bases of this variation. Eleven different loss-of-function FRI alleles of low frequency accounted for up to 16% of the variation for most traits. Furthermore, an FLC allelic series of six novel putative loss- and change-of-function alleles, with low to moderate frequency, revealed that a broader FLC functional diversification might contribute to flowering variation. Finally, environment-genotype association analyses showed that the spatial patterns of FRI, FLC, and PHYC polymorphisms are significantly associated with winter temperatures and spring and winter precipitations, respectively. These results support that allelic variation in these genes is involved in climatic adaptation.     

The genomic footprint of climate adaptation in Chironomus riparius

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

Identification of loci controlling adaptation in Chinese soya bean landraces via a combination of conventional and bioclimatic GWAS

Landraces often contain genetic diversity that has been lost in modern cultivars, including alleles that confer enhanced local adaptation. To comprehensively identify loci associated with adaptive traits in soya bean landraces, for example flowering time, a population of 1938 diverse landraces and 97 accessions of the wild progenitor of cultivated soya bean, Glycine soja was genotyped using tGBS^®. Based on 99 085 high‐quality SNPs, landraces were classified into three sub‐populations which exhibit geographical genetic differentiation. Clustering was inferred from STRUCTURE, principal component analyses and neighbour‐joining tree analyses. Using phenotypic data collected at two locations separated by 10 degrees of latitude, 17 trait‐associated SNPs (TASs) for flowering time were identified, including a stable locus Chr12:5914898 and previously undetected candidate QTL/genes for flowering time in the vicinity of the previously cloned flowering genes, E1 and E2. Using passport data associated with the collection sites of the landraces, 27 SNPs associated with adaptation to three bioclimatic variables (temperature, daylength, and precipitation) were identified. A series of candidate flowering genes were detected within linkage disequilibrium (LD) blocks surrounding 12 bioclimatic TASs. Nine of these TASs exhibit significant differences in flowering time between alleles within one or more of the three individual sub‐populations. Signals of selection during domestication and/or subsequent landrace diversification and adaptation were detected at 38 of the 44 flowering and bioclimatic TASs. Hence, this study lays the groundwork to begin breeding for novel environments predicted to arise following global climate change.     

How to be early flowering: an evolutionary perspective

In wild and cultivated annual plant species, flowering time is an important life-history trait that coordinates the life cycle with local environmental conditions. Extensive studies on the genetic basis of flowering time in the model species Arabidopsis thaliana have revealed a complex genetic network that can detect environmental and internal signals. Based on this knowledge and on known pleiotropic effects associated with flowering time genes, we suggest that a natural shift towards an early-flowering life cycle might involve only particular functional regions in a limited number of genes. Our predictions are supported by genetic theories of adaptation and by recent data about genes associated with natural variation. We analyse the extent to which these predictions can also apply to crop species.     

Using connectivity to identify climatic drivers of local adaptation

Understanding the climatic drivers of local adaptation is vital. Such knowledge is not only of theoretical interest but is critical to inform management actions under climate change, such as assisted translocation and targeted gene flow. Unfortunately, there are a vast number of potential trait–environment combinations, and simple relationships between trait and environment are ambiguous: representing either plastic or evolved variation. Here, we show that by incorporating connectivity as an index of gene flow, we can differentiate trait–environment relationships reflecting genetic variation vs. phenotypic plasticity. In this way, we rapidly shorten the list of trait–environment combinations that are of significance. Our analysis of an existing data set on geographic variation in a tropical lizard shows that we can effectively rank climatic variables by the strength of their role in local adaptation. The promise of our method is a rapid and general approach to identifying the environmental drivers of local adaptation.     

Genomic signatures of adaptation to Sahelian and Soudanian climates in sorghum landraces of Senegal

Uncovering the genomic basis of climate adaptation in traditional crop varieties can provide insight into plant evolution and facilitate breeding for climate resilience. In the African cereal sorghum (Sorghum bicolor L. [Moench]), the genomic basis of adaptation to the semiarid Sahelian zone versus the subhumid Soudanian zone is largely unknown. To address this issue, we characterized a large panel of 421 georeferenced sorghum landrace accessions from Senegal and adjacent locations at 213,916 single‐nucleotide polymorphisms (SNPs) using genotyping‐by‐sequencing. Seven subpopulations distributed along the north‐south precipitation gradient were identified. Redundancy analysis found that climate variables explained up to 8% of SNP variation, with climate collinear with space explaining most of this variation (6%). Genome scans of nucleotide diversity suggest positive selection on chromosome 2, 4, 5, 7, and 10 in durra sorghums, with successive adaptation during diffusion along the Sahel. Putative selective sweeps were identified, several of which colocalize with stay‐green drought tolerance (Stg) loci, and a priori candidate genes for photoperiodic flowering and inflorescence morphology. Genome‐wide association studies of photoperiod sensitivity and panicle compactness identified 35 and 13 associations that colocalize with a priori candidate genes, respectively. Climate‐associated SNPs colocalize with Stg3a, Stg1, Stg2, and Ma6 and have allelic distribution consistent with adaptation across Sahelian and Soudanian zones. Taken together, the findings suggest an oligogenic basis of adaptation to Sahelian versus Soudanian climates, underpinned by variation in conserved floral regulatory pathways and other systems that are less understood in cereals.     

Population genomic footprints of selection and associations with climate in natural populations of Arabidopsis halleri from the Alps

Natural genetic variation is essential for the adaptation of organisms to their local environment and to changing environmental conditions. Here, we examine genomewide patterns of nucleotide variation in natural populations of the outcrossing herb Arabidopsis halleri and associations with climatic variation among populations in the Alps. Using a pooled population sequencing (Pool‐Seq) approach, we discovered more than two million SNPs in five natural populations and identified highly differentiated genomic regions and SNPs using F_ST‐based analyses. We tested only the most strongly differentiated SNPs for associations with a nonredundant set of environmental factors using partial Mantel tests to identify topo‐climatic factors that may underlie the observed footprints of selection. Possible functions of genes showing signatures of selection were identified by Gene Ontology analysis. We found 175 genes to be highly associated with one or more of the five tested topo‐climatic factors. Of these, 23.4% had unknown functions. Genetic variation in four candidate genes was strongly associated with site water balance and solar radiation, and functional annotations were congruent with these environmental factors. Our results provide a genomewide perspective on the distribution of adaptive genetic variation in natural plant populations from a highly diverse and heterogeneous alpine environment.     

EVOLUTION OF FLOWERING TIME IN EXPERIMENTAL WHEAT POPULATIONS: A COMPREHENSIVE APPROACH TO DETECT GENETIC SIGNATURES OF NATURAL SELECTION

In annual plant species, flowering time is a major adaptive trait that synchronizes the initiation of reproduction with favorable environmental conditions. Here, we aimed at studying the evolution of flowering time in three experimental populations of bread wheat, grown in contrasting environments (Northern to Southern France) for 12 generations. By comparing the distribution of phenotypic and presumably neutral variation, we first showed that flowering time responded to selection during the 12 generations of the experiment. To get insight into the genetic architecture of that trait, we then tested whether the distribution of genetic polymorphisms at six candidate genes, presumably involved in the trait expression, departed from neutral expectation. To that end, we focused on the temporal variation during the course of the experiment, and on the spatial differentiation at the end of the experiment, using previously published methods adapted to our experimental design. Only those genes that were strongly associated with flowering time variation were detected as responding to selection. For genes that had low‐to‐moderate phenotypic effects, or when there was interaction across different genes, we did not find evidence of selection using methods based on the distribution of temporal or spatial variation. In such cases, it might be more informative to consider multilocus and multiallelic combinations across genes, which could be the targets of selection.     

Intraspecific trait variation across elevation predicts a widespread tree species' climate niche and range limits

Global change is widely altering environmental conditions which makes accurately predicting species range limits across natural landscapes critical for conservation and management decisions. If climate pressures along elevation gradients influence the distribution of phenotypic and genetic variation of plant functional traits, then such trait variation may be informative of the selective mechanisms and adaptations that help define climatic niche limits. Using extensive field surveys along 16 elevation transects and a large common garden experiment, we tested whether functional trait variation could predict the climatic niche of a widespread tree species (Populus angustifolia) with a double quantile regression approach. We show that intraspecific variation in plant size, growth, and leaf morphology corresponds with the species' total climate range and certain climatic limits related to temperature and moisture extremes. Moreover, we find evidence of genetic clines and phenotypic plasticity at environmental boundaries, which we use to create geographic predictions of trait variation and maximum values due to climatic constraints across the western US. Overall, our findings show the utility of double quantile regressions for connecting species distributions and climate gradients through trait‐based mechanisms. We highlight how new approaches like ours that incorporate genetic variation in functional traits and their response to climate gradients will lead to a better understanding of plant distributions as well as identifying populations anticipated to be maladapted to future environments.     

Integrating candidate gene and quantitative genetic approaches to understand variation in timing of breeding in wild tit populations

Two commonly used techniques for estimating the effect of genes on traits in wild populations are the candidate gene approach and quantitative genetic analyses. However, whether these two approaches measure the same underlying processes remains unresolved. Here, we use these two methods to test whether they are alternative or complementary approaches to understanding genetic variation in the timing of reproduction - a key trait involved in adaptation to climate change - in wild tit populations. Our analyses of the candidate gene Clock show weak correlates with timing variables in blue tits, but no association in great tits, confirming earlier results. Quantitative genetic analyses revealed very low levels of both direct (female) and indirect (male) additive genetic variation in timing traits for both species, in contrast to previous studies on these traits, and much lower than generally assumed. Hence, neither method suggests strong genetic effects on the timing of breeding in birds, and further work should seek to assess the generality of these conclusions. We discuss how differences in the genetic control of traits, species life-history and confounding environmental variables may determine how useful integrating these two techniques is to understand the phenotypic variation in wild populations.     

Climate variables explain neutral and adaptive variation within salmonid metapopulations: the importance of replication in landscape genetics

Understanding how environmental variation influences population genetic structure is important for conservation management because it can reveal how human stressors influence population connectivity, genetic diversity and persistence. We used riverscape genetics modelling to assess whether climatic and habitat variables were related to neutral and adaptive patterns of genetic differentiation (population‐specific and pairwise F_ST) within five metapopulations (79 populations, 4583 individuals) of steelhead trout (Oncorhynchus mykiss) in the Columbia River Basin, USA. Using 151 putatively neutral and 29 candidate adaptive SNP loci, we found that climate‐related variables (winter precipitation, summer maximum temperature, winter highest 5% flow events and summer mean flow) best explained neutral and adaptive patterns of genetic differentiation within metapopulations, suggesting that climatic variation likely influences both demography (neutral variation) and local adaptation (adaptive variation). However, we did not observe consistent relationships between climate variables and F_ST across all metapopulations, underscoring the need for replication when extrapolating results from one scale to another (e.g. basin‐wide to the metapopulation scale). Sensitivity analysis (leave‐one‐population‐out) revealed consistent relationships between climate variables and F_ST within three metapopulations; however, these patterns were not consistent in two metapopulations likely due to small sample sizes (N = 10). These results provide correlative evidence that climatic variation has shaped the genetic structure of steelhead populations and highlight the need for replication and sensitivity analyses in land and riverscape genetics.     

The Genetic Architecture of Flowering Time and Photoperiod Sensitivity in Maize as Revealed by QTL Review and Meta Analysis

The control of flowering is not only important for reproduction,but also plays a key role in the processes of domestication and adaptation.To reveal the genetic architecture for flowering time and photoperiod sensitivity,a comprehensive evaluation of the relevant literature was performed and followed by meta analysis.A total of 25 synthetic consensus quantitative trait loci(QTL)and four hot-spot genomic regions were identified for photoperiod sensitivity including 11 genes related to photoperiod response or flower morphogenesis and development.Besides,a comparative analysis of the QTL for flowering time and photoperiod sensitivity highlighted the regions containing shared and unique QTL for the two traits.Candidate genes associated with maize flowering were identified through integrated analysis of the homologous genes for flowering time in plants and the consensus QTL regions for photoperiod sensitivity in maize(Zea mays L.).Our results suggest that the combination of literature review,meta-analysis and homologous blast is an efficient approach to identify new candidate genes and create a global view of the genetic architecture for maize photoperiodic flowering.Sequences of candidate genes can be used to develop molecular markers for various models of marker-assisted selection,such as marker-assisted recurrent selection and genomic selection that can contribute significantly to crop environmental adaptation.