Genome-wide patterns of genetic variation in worldwide Arabidopsis thaliana accessions from the RegMap panel

The Effects of Both Recent and Long-Term Selection and Genetic Drift Are Readily Evident in North American Barley Breeding Populations

Barley was introduced to North America ∼400 yr ago but adaptation to modern production environments is more recent. Comparisons of allele frequencies among growth habits and spike (inflorescence) types in North America indicate that significant genetic differentiation has accumulated in a relatively short evolutionary time span. Allele frequency differentiation is greatest among barley with two-row vs. six-row spikes, followed by spring vs. winter growth habit. Large changes in allele frequency among breeding programs suggest a major contribution of genetic drift and linked selection on genetic variation. Despite this, comparisons of 3613 modern North American cultivated barley breeding lines that differ for spike-type and growth habit permit the discovery of 142 single nucleotide polymorphism (SNP) outliers putatively linked to targets of selection. For example, SNPs within the Cbf4, Ppd-H1, and Vrn-H1 loci, which have previously been associated with agronomically adaptive phenotypes, are identified as outliers. Analysis of extended haplotype sharing identifies genomic regions shared within and among breeding populations, suggestive of a number of genomic regions subject to recent selection. Finally, we are able to identify recent bouts of gene flow between breeding populations that could point to the sharing of agronomically adaptive variation. These results are supported by pedigrees and breeders’ understanding of germplasm sharing.

Genetic diversity and population structure of Arabidopsis thaliana along an altitudinal gradient

The natural genetic variation within a plant species is primarily a consequence of its phylogeography and evolutionary history. This variation largely determines its present-day population structure. Arabidopsis thaliana, as a model plant, has been studied in great detail including its probable origin, local as well as global genetic diversity pattern, population structure, adaptation, etc. However, no such studies have so far been reported from the Indian Himalayan region. Here, we describe a comprehensive study on the genetic diversity and population structure of A. thaliana from an altitudinal range of 700-3400 m above mean sea level the highest altitudinal range reported so far. We also compare these populations with previously reported worldwide populations. A total of 48 accessions representing six populations were analysed using 19 microsatellites and 11 chloroplast markers. Genetic diversity analysis indicated populations to be highly diverse and comparable with worldwide populations. STRUCTURE, principal coordinate and isolation by distance (IBD) analyses showed that genetic variation in different populations is structured at geographical and altitudinal level. Further analyses indicate that these populations are genetically distinct from the rest of the world populations. Different parameters of the demographic expansion model support a rapid expansion. Based on mismatch distribution, the initial time of expansion of west Himalayan populations was found to be about 130 000 years. Bayesian analysis of divergence time indicated that these populations have a long evolutionary history in this region. Based on the results of genetic diversity parameters, demographic expansion and divergence time estimation, it appears that west Himalayan populations may be the source of the west-east expansion model.

The Multi-allelic Genetic Architecture of a Variance-Heterogeneity Locus for Molybdenum Concentration in Leaves Acts as a Source of Unexplained Additive Genetic Variance

Genome-wide association (GWA) analyses have generally been used to detect individual loci contributing to the phenotypic diversity in a population by the effects of these loci on the trait mean. More rarely, loci have also been detected based on variance differences between genotypes. Several hypotheses have been proposed to explain the possible genetic mechanisms leading to such variance signals. However, little is known about what causes these signals, or whether this genetic variance-heterogeneity reflects mechanisms of importance in natural populations. Previously, we identified a variance-heterogeneity GWA (vGWA) signal for leaf molybdenum concentrations in Arabidopsis thaliana. Here, fine-mapping of this association reveals that the vGWA emerges from the effects of three independent genetic polymorphisms that all are in strong LD with the markers displaying the genetic variance-heterogeneity. By revealing the genetic architecture underlying this vGWA signal, we uncovered the molecular source of a significant amount of hidden additive genetic variation or “missing heritability”. Two of the three polymorphisms underlying the genetic variance-heterogeneity are promoter variants for Molybdate transporter 1 (MOT1), and the third a variant located ~25 kb downstream of this gene. A fourth independent association was also detected ~600 kb upstream of MOT1. Use of a T-DNA knockout allele highlights Copper Transporter 6; COPT6 (AT2G26975) as a strong candidate gene for this association. Our results show that an extended LD across a complex locus including multiple functional alleles can lead to a variance-heterogeneity between genotypes in natural populations. Further, they provide novel insights into the genetic regulation of ion homeostasis in A. thaliana, and empirically confirm that variance-heterogeneity based GWA methods are a valuable tool to detect novel associations of biological importance in natural populations.

Most biological traits vary in natural populations, and understanding the genetic basis of this variation remains an important challenge. Genome-wide association (GWA) studies have emerged as a powerful tool to address this challenge by dissecting the genetic architecture of trait variation into the contribution of individual genes. This contribution has traditionally been measured as the difference in the phenotypic means between groups of individuals with alternative genotypes at one, or multiple loci. However, instead of altering the trait mean, certain loci alter the variability of the trait. Here, we describe the genetic dissection of one such variance-controlling locus that drives variation in leaf molybdenum concentrations amongst natural accessions of Arabidopsis thaliana. The variance-controlling locus was found to result from the contributions of multiple alleles at multiple loci that are closely linked on the chromosome and is a major contributor to the “missing heritability” for this trait identified in previous studies. This illustrates that multi-allelic genetic architectures can hide large amounts of additive genetic variation, and that it is possible to uncover this hidden variation using the appropriate experimental designs and statistical methods described here.

Misspecification in Mixed-Model-Based Association Analysis

Additive genetic variance in natural populations is commonly estimated using mixed models, in which the covariance of the genetic effects is modeled by a genetic similarity matrix derived from a dense set of markers. An important but usually implicit assumption is that the presence of any nonadditive genetic effect increases only the residual variance and does not affect estimates of additive genetic variance. Here we show that this is true only for panels of unrelated individuals. In the case that there is genetic relatedness, the combination of population structure and epistatic interactions can lead to inflated estimates of additive genetic variance.

A Flexible, Efficient Binomial Mixed Model for Identifying Differential DNA Methylation in Bisulfite Sequencing Data

Identifying sources of variation in DNA methylation levels is important for understanding gene regulation. Recently, bisulfite sequencing has become a popular tool for investigating DNA methylation levels. However, modeling bisulfite sequencing data is complicated by dramatic variation in coverage across sites and individual samples, and because of the computational challenges of controlling for genetic covariance in count data. To address these challenges, we present a binomial mixed model and an efficient, sampling-based algorithm (MACAU: Mixed model association for count data via data augmentation) for approximate parameter estimation and p-value computation. This framework allows us to simultaneously account for both the over-dispersed, count-based nature of bisulfite sequencing data, as well as genetic relatedness among individuals. Using simulations and two real data sets (whole genome bisulfite sequencing (WGBS) data from Arabidopsis thaliana and reduced representation bisulfite sequencing (RRBS) data from baboons), we show that our method provides well-calibrated test statistics in the presence of population structure. Further, it improves power to detect differentially methylated sites: in the RRBS data set, MACAU detected 1.6-fold more age-associated CpG sites than a beta-binomial model (the next best approach). Changes in these sites are consistent with known age-related shifts in DNA methylation levels, and are enriched near genes that are differentially expressed with age in the same population. Taken together, our results indicate that MACAU is an efficient, effective tool for analyzing bisulfite sequencing data, with particular salience to analyses of structured populations. MACAU is freely available at www.xzlab.org/software.html.

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.

Finding genes involved in adaptation to the environment has long been of interest to evolutionary biologists and ecologists. Most commonly, researchers look for loci whose differences in allelic state correlate with differences in a particular trait or environmental variable such as temperature. The implicit assumption behind such methods is that natural selection by the environment will shape variation in adaptive traits through associated changes in allele frequencies. This means that both environmental and phenotypic variation are relevant for detecting adaptive genes, although we have incomplete knowledge of how the two types of variation relate to adaptation. Here we present a method that aims to identify adaptive genes by combining phenotypic and environmental data. We first predict trait variation from a set of environmental variables as a way to extract the most biologically relevant information from the environment and then look for genes associated with both the predicted and observed trait. Using simulations and published data from the model plant Arabidopsis thaliana, we show that this approach may find adaptive genes more effectively compared to existing methods. We also demonstrate that predicted traits can be used to identify relevant loci in individuals for which no phenotypic data is available.

Population Genomics for Understanding Adaptation in Wild Plant Species

Darwin's theory of evolution by natural selection is the foundation of modern biology. However, it has proven remarkably difficult to demonstrate at the genetic, genomic, and population level exactly how wild species adapt to their natural environments. We discuss how one can use large sets of multiple genome sequences from wild populations to understand adaptation, with an emphasis on the small herbaceous plant Arabidopsis thaliana. We present motivation for such studies; summarize progress in describing whole-genome, species-wide sequence variation; and then discuss what insights have emerged from these resources, either based on sequence information alone or in combination with phenotypic data. We conclude with thoughts on opportunities with other plant species and the impact of expected progress in sequencing technology and genome engineering for studying adaptation in nature.

A Genome-Wide Association Analysis Reveals Epistatic Cancellation of Additive Genetic Variance for Root Length in Arabidopsis thaliana

Efforts to identify loci underlying complex traits generally assume that most genetic variance is additive. Here, we examined the genetics of Arabidopsis thaliana root length and found that the genomic narrow-sense heritability for this trait in the examined population was statistically zero. The low amount of additive genetic variance that could be captured by the genome-wide genotypes likely explains why no associations to root length could be found using standard additive-model-based genome-wide association (GWA) approaches. However, as the broad-sense heritability for root length was significantly larger, and primarily due to epistasis, we also performed an epistatic GWA analysis to map loci contributing to the epistatic genetic variance. Four interacting pairs of loci were revealed, involving seven chromosomal loci that passed a standard multiple-testing corrected significance threshold. The genotype-phenotype maps for these pairs revealed epistasis that cancelled out the additive genetic variance, explaining why these loci were not detected in the additive GWA analysis. Small population sizes, such as in our experiment, increase the risk of identifying false epistatic interactions due to testing for associations with very large numbers of multi-marker genotypes in few phenotyped individuals. Therefore, we estimated the false-positive risk using a new statistical approach that suggested half of the associated pairs to be true positive associations. Our experimental evaluation of candidate genes within the seven associated loci suggests that this estimate is conservative; we identified functional candidate genes that affected root development in four loci that were part of three of the pairs. The statistical epistatic analyses were thus indispensable for confirming known, and identifying new, candidate genes for root length in this population of wild-collected A. thaliana accessions. We also illustrate how epistatic cancellation of the additive genetic variance explains the insignificant narrow-sense and significant broad-sense heritability by using a combination of careful statistical epistatic analyses and functional genetic experiments.

Complex traits, such as many human diseases or climate adaptation and production traits in crops, arise through the action and interaction of many genes and environmental factors. Classic approaches to identify contributing genes generally assume that these factors contribute mainly additive genetic variance. Recent methods, such as genome-wide association studies, often adhere to this additive genetics paradigm. However, additive models of complex traits do not reflect that genes can also contribute with non-additive genetic variance. In this study, we use Arabidopsis thaliana to determine the additive and non-additive genetic contributions to the phenotypic variation in root length. Surprisingly, much of the observed phenotypic variation in root length across genetically divergent strains was explained by epistasis. We mapped seven loci contributing to the epistatic genetic variance and validated four genes in these loci with mutant analysis. For three of these genes, this is their first implication in root development. Together, our results emphasize the importance of considering both non-additive and additive genetic variance when dissecting complex trait variation, in order not to lose sensitivity in genetic analyses.

DNA Crossover Motifs Associated with Epigenetic Modifications Delineate Open Chromatin Regions in Arabidopsis

The rate of crossover, the reciprocal exchanges of homologous chromosomal segments, is not uniform along chromosomes differing between male and female meiocytes. To better understand the factors regulating this variable landscape, we performed a detailed genetic and epigenetic analysis of 737 crossover events in Arabidopsis thaliana. Crossovers were more frequent than expected in promoters. Three DNA motifs enriched in crossover regions and less abundant in crossover-poor pericentric regions were identified. One of these motifs, the CCN repeat, was previously unknown in plants. The A-rich motif was preferentially associated with promoters, while the CCN repeat and the CTT repeat motifs were preferentially associated with genes. Analysis of epigenetic modifications around the motifs showed, in most cases, a specific epigenetic architecture. For example, we show that there is a peak of nucleosome occupancy and of H3K4me3 around the CCN and CTT repeat motifs while nucleosome occupancy was lowest around the A-rich motif. Cytosine methylation levels showed a gradual decrease within ∼2 kb of the three motifs, being lowest at sites where crossover occurred. This landscape was conserved in the decreased DNA methylation1 mutant. In summary, the crossover motifs are associated with epigenetic landscapes corresponding to open chromatin and contributing to the nonuniformity of crossovers in Arabidopsis.

Loci and candidate gene identification for resistance to Sclerotinia sclerotiorum in soybean (Glycine max L. Merr.) via association and linkage maps

Soybean white mold (SWM), caused by Sclerotinia sclerotiorum ((Lib.) W. Phillips), is currently considered to be the second most important cause of soybean yield loss due to disease. Research is needed to identify SWM-resistant germplasm and gain a better understanding of the genetic and molecular basis of SWM resistance in soybean. Stem pigmentation after treatment with oxaloacetic acid is an effective indicator of resistance to SWM. A total of 128 recombinant inbred lines (RILs) derived from a cross of 'Maple Arrow' (partial resistant to SWM) and 'Hefeng 25' (susceptible) and 330 diverse soybean cultivars were screened for the soluble pigment concentration of their stems, which were treated with oxalic acid. Four quantitative trait loci (QTLs) underlying soluble pigment concentration were detected by linkage mapping of the RILs. Three hundred and thirty soybean cultivars were sequenced using the whole-genome encompassing approach and 25 179 single-nucleotide polymorphisms (SNPs) were detected for the fine mapping of SWM resistance genes by genome-wide association studies. Three out of five SNP markers representing a linkage disequilibrium (LD) block and a single locus on chromosome 13 (Gm13) were significantly associated with the soluble pigment content of stems. Three more SNPs that represented three minor QTLs for the soluble pigment content of stems were identified on another three chromosomes by association mapping. A major locus with the largest effect on Gm13 was found both by linkage and association mapping. Four potential candidate genes involved in disease response or the anthocyanin biosynthesis pathway were identified at the locus near the significant SNPs (<60 kbp). The beneficial allele and candidate genes should be useful in soybean breeding for improving resistance to SWM.

Juxtaposition of heterozygous and homozygous regions causes reciprocal crossover remodelling via interference during Arabidopsis meiosis

During meiosis homologous chromosomes undergo crossover recombination. Sequence differences between homologs can locally inhibit crossovers. Despite this, nucleotide diversity and population-scaled recombination are positively correlated in eukaryote genomes. To investigate interactions between heterozygosity and recombination we crossed Arabidopsis lines carrying fluorescent crossover reporters to 32 diverse accessions and observed hybrids with significantly higher and lower crossovers than homozygotes. Using recombinant populations derived from these crosses we observed that heterozygous regions increase crossovers when juxtaposed with homozygous regions, which reciprocally decrease. Total crossovers measured by chiasmata were unchanged when heterozygosity was varied, consistent with homeostatic control. We tested the effects of heterozygosity in mutants where the balance of interfering and non-interfering crossover repair is altered. Crossover remodeling at homozygosity-heterozygosity junctions requires interference, and non-interfering repair is inefficient in heterozygous regions. As a consequence, heterozygous regions show stronger crossover interference. Our findings reveal how varying homolog polymorphism patterns can shape meiotic recombination.

Planting molecular functions in an ecological context with Arabidopsis thaliana

The vascular plant Arabidopsis thaliana is a central genetic model and universal reference organism in plant and crop science. The successful integration of different fields of research in the study of A. thaliana has made a large contribution to our molecular understanding of key concepts in biology. The availability and active development of experimental tools and resources, in combination with the accessibility of a wealth of cumulatively acquired knowledge about this plant, support the most advanced systems biology approaches among all land plants. Research in molecular ecology and evolution has also brought the natural history of A. thaliana into the limelight. This article showcases our current knowledge of the natural history of A. thaliana from the perspective of the most closely related plant species, providing an evolutionary framework for interpreting novel findings and for developing new hypotheses based on our knowledge of this plant.

Uncovering genes and ploidy involved in the high diversity in root hair density, length and response to local scarce phosphate in Arabidopsis thaliana

Plant root hairs increase the root surface to enhance the uptake of sparingly soluble and immobile nutrients, such as the essential nutrient phosphorus, from the soil. Here, root hair traits and the response to scarce local phosphorus concentration were studied in 166 accessions of Arabidopsis thaliana using split plates. Root hair density and length were correlated, but highly variable among accessions. Surprisingly, the well-known increase in root hair density under low phosphorus was mostly restricted to genotypes that had less and shorter root hairs under P sufficient conditions. By contrast, several accessions with dense and long root hairs even had lower hair density or shorter hairs in local scarce phosphorus. Furthermore, accessions with whole-genome duplications developed more dense but phosphorus-insensitive root hairs. The impact of genome duplication on root hair density was confirmed by comparing tetraploid accessions with their diploid ancestors. Genome-wide association mapping identified candidate genes potentially involved in root hair responses tp scarce local phosphate. Knock-out mutants in identified candidate genes (CYR1, At1g32360 and RLP48) were isolated and differences in root hair traits in the mutants were confirmed. The large diversity in root hair traits among accessions and the diverse response when local phosphorus is scarce is a rich resource for further functional analyses.

Coselected genes determine adaptive variation in herbivore resistance throughout the native range of Arabidopsis thaliana

The "mustard oil bomb" is a major defense mechanism in the Brassicaceae, which includes crops such as canola and the model plant Arabidopsis thaliana. These plants produce and store blends of amino acid-derived secondary metabolites called glucosinolates. Upon tissue rupture by natural enemies, the myrosinase enzyme hydrolyses glucosinolates, releasing defense molecules. Brassicaceae display extensive variation in the mixture of glucosinolates that they produce. To investigate the genetics underlying natural variation in glucosinolate profiles, we conducted a large genome-wide association study of 22 methionine-derived glucosinolates using A. thaliana accessions from across Europe. We found that 36% of among accession variation in overall glucosinolate profile was explained by genetic differentiation at only three known loci from the glucosinolate pathway. Glucosinolate-related SNPs were up to 490-fold enriched in the extreme tail of the genome-wide [Formula: see text] scan, indicating strong selection on loci controlling this pathway. Glucosinolate profiles displayed a striking longitudinal gradient with alkenyl and hydroxyalkenyl glucosinolates enriched in the West. We detected a significant contribution of glucosinolate loci toward general herbivore resistance and lifetime fitness in common garden experiments conducted in France, where accessions are enriched in hydroxyalkenyls. In addition to demonstrating the adaptive value of glucosinolate profile variation, we also detected long-distance linkage disequilibrium at two underlying loci, GS-OH and GS-ELONG. Locally cooccurring alleles at these loci display epistatic effects on herbivore resistance and fitness in ecologically realistic conditions. Together, our results suggest that natural selection has favored a locally adaptive configuration of physically unlinked loci in Western Europe.

The effective founder effect in a spatially expanding population

The gradual loss of diversity and the establishment of clines in allele frequencies associated with range expansions are patterns observed in many species, including humans. These patterns can result from a series of founder events occurring as populations colonize previously unoccupied areas. We develop a model of an expanding population and, using a branching process approximation, show that spatial gradients reflect different amounts of genetic drift experienced by different subpopulations. We then use this model to measure the net average strength of the founder effect, and we demonstrate that the predictions from the branching process model fit simulation results well. We further show that estimates of the effective founder size are robust to potential confounding factors such as migration between subpopulations. We apply our method to data from Arabidopsis thaliana. We find that the average founder effect is approximately three times larger in the Americas than in Europe, possibly indicating that a more recent, rapid expansion occurred.

Genome-wide patterns of genetic variation among silkworms

Although the draft genome sequence of silkworm is available for a decade, its genetic variations, especially structural variations, are far from well explored. In this study, we identified 1,298,659 SNPs and 9,731 indels, of which 32 % of SNPs and 92.2 % of indels were novel compared to previous silkworm re-sequencing analysis. In addition, we applied a read depth-based approach to investigate copy number variations among 21 silkworm strains at genome-wide level. This effort resulted in 562 duplicated and 41 deleted CNV regions, and among them 442 CNV were newly identified. Functional annotation of genes affected by these genetic variations reveal that these genes include a wide spectrum of molecular functions, such as immunity and drug detoxification, which are important for the adaptive evolution of silkworms. We further validated the predicted CNV regions using q-PCR. 94.7 % (36/38) of the selected regions show divergent copy numbers compared to a single-copy gene OR2. In addition, potential presence/absence variations are also observed in our study: 11 genes are present in the reference genome, but absent in other strains. Overall, we draw an integrative map of silkworm genetic variation at genome-wide level. The identification of genetic variations in this study improves our understanding that these variants play important roles in shaping phenotypic variations between wild and domesticated silkworms.

Genomic variation in Arabidopsis: tools and insights from next-generation sequencing

The release of a reference genome for Arabidopsis thaliana in 2000 has been an enormous boon for the study of plant genetics. Less than a decade later, however, a revolution in sequencing technology had enabled rapid and inexpensive re-sequencing of whole A. thaliana genomes. Large-scale efforts to characterize natural genomic variation in A. thaliana have revealed remarkable intra-specific variation in this species, ranging from single-nucleotide differences to large structural rearrangements. The partitioning of this variation by geography and local adaptation has been described using powerful new methods and tools. Simultaneously, an ambitious research agenda has emerged to sequence 1001 A. thaliana lines from around the world, while sequencing of related species is enabling powerful evolutionary genomic analyses. In this review, I summarize recent progress in genomic analysis of natural variation in A. thaliana and its close relatives. This progress has set the stage for the emergence of Arabidopsis as a model genus for evolutionary and functional genomics.

Genome-wide association mapping in plants exemplified for root growth in Arabidopsis thaliana

Genome-wide association (GWA) mapping is a powerful technique to address the molecular basis of genotype to phenotype relationships and to map regulators of biological processes. This chapter presents a protocol for genome-wide association mapping in Arabidopsis thaliana using the user-friendly internet application GWAPP, and provides a specific protocol for acquiring root trait data suitable for GWA studies using the semi-automated, high-throughput phenotyping pipeline BRAT for early root growth.

Investigation of the multifunctional gene AOP3 expands the regulatory network fine-tuning glucosinolate production in Arabidopsis

Quantitative trait loci (QTL) mapping studies enable identification of loci that are part of regulatory networks controlling various phenotypes. Detailed investigations of genes within these loci are required to ultimately understand the function of individual genes and how they interact with other players in the network. In this study, we use transgenic plants in combination with natural variation to investigate the regulatory role of the AOP3 gene found in GS-AOP locus previously suggested to contribute to the regulation of glucosinolate defense compounds. Phenotypic analysis and QTL mapping in F2 populations with different AOP3 transgenes support that the enzymatic function and the AOP3 RNA both play a significant role in controlling glucosinolate accumulation. Furthermore, we find different loci interacting with either the enzymatic activity or the RNA of AOP3 and thereby extend the regulatory network controlling glucosinolate accumulation.

The molecular biology of meiosis in plants

Meiosis is the cell division that reshuffles genetic information between generations. Recently, much progress has been made in understanding this process; in particular, the identification and functional analysis of more than 80 plant genes involved in meiosis have dramatically deepened our knowledge of this peculiar cell division. In this review, we provide an overview of advancements in the understanding of all aspects of plant meiosis, including recombination, chromosome synapsis, cell cycle control, chromosome distribution, and the challenge of polyploidy.

Metabolic fingerprinting of Arabidopsis thaliana accessions

In the post-genomic era much effort has been put on the discovery of gene function using functional genomics. Despite the advances achieved by these technologies in the understanding of gene function at the genomic and proteomic level, there is still a big genotype-phenotype gap. Metabolic profiling has been used to analyze organisms that have already been characterized genetically. However, there is a small number of studies comparing the metabolic profile of different tissues of distinct accessions. Here, we report the detection of over 14,000 and 17,000 features in inflorescences and leaves, respectively, in two widely used Arabidopsis thaliana accessions. A predictive Random Forest Model was developed, which was able to reliably classify tissue type and accession of samples based on LC-MS profile. Thereby we demonstrate that the morphological differences among A. thaliana accessions are reflected also as distinct metabolic phenotypes within leaves and inflorescences.

Marker-based estimation of heritability in immortal populations

Heritability is a central parameter in quantitative genetics, from both an evolutionary and a breeding perspective. For plant traits heritability is traditionally estimated by comparing within- and between-genotype variability. This approach estimates broad-sense heritability and does not account for different genetic relatedness. With the availability of high-density markers there is growing interest in marker-based estimates of narrow-sense heritability, using mixed models in which genetic relatedness is estimated from genetic markers. Such estimates have received much attention in human genetics but are rarely reported for plant traits. A major obstacle is that current methodology and software assume a single phenotypic value per genotype, hence requiring genotypic means. An alternative that we propose here is to use mixed models at the individual plant or plot level. Using statistical arguments, simulations, and real data we investigate the feasibility of both approaches and how these affect genomic prediction with the best linear unbiased predictor and genome-wide association studies. Heritability estimates obtained from genotypic means had very large standard errors and were sometimes biologically unrealistic. Mixed models at the individual plant or plot level produced more realistic estimates, and for simulated traits standard errors were up to 13 times smaller. Genomic prediction was also improved by using these mixed models, with up to a 49% increase in accuracy. For genome-wide association studies on simulated traits, the use of individual plant data gave almost no increase in power. The new methodology is applicable to any complex trait where multiple replicates of individual genotypes can be scored. This includes important agronomic crops, as well as bacteria and fungi.

Genome-wide association mapping identifies a new arsenate reductase enzyme critical for limiting arsenic accumulation in plants

Inorganic arsenic is a carcinogen, and its ingestion through foods such as rice presents a significant risk to human health. Plants chemically reduce arsenate to arsenite. Using genome-wide association (GWA) mapping of loci controlling natural variation in arsenic accumulation in Arabidopsis thaliana allowed us to identify the arsenate reductase required for this reduction, which we named High Arsenic Content 1 (HAC1). Complementation verified the identity of HAC1, and expression in Escherichia coli lacking a functional arsenate reductase confirmed the arsenate reductase activity of HAC1. The HAC1 protein accumulates in the epidermis, the outer cell layer of the root, and also in the pericycle cells surrounding the central vascular tissue. Plants lacking HAC1 lose their ability to efflux arsenite from roots, leading to both increased transport of arsenic into the central vascular tissue and on into the shoot. HAC1 therefore functions to reduce arsenate to arsenite in the outer cell layer of the root, facilitating efflux of arsenic as arsenite back into the soil to limit both its accumulation in the root and transport to the shoot. Arsenate reduction by HAC1 in the pericycle may play a role in limiting arsenic loading into the xylem. Loss of HAC1-encoded arsenic reduction leads to a significant increase in arsenic accumulation in shoots, causing an increased sensitivity to arsenate toxicity. We also confirmed the previous observation that the ACR2 arsenate reductase in A. thaliana plays no detectable role in arsenic metabolism. Furthermore, ACR2 does not interact epistatically with HAC1, since arsenic metabolism in the acr2 hac1 double mutant is disrupted in an identical manner to that described for the hac1 single mutant. Our identification of HAC1 and its associated natural variation provides an important new resource for the development of low arsenic-containing food such as rice.

Natural CMT2 variation is associated with genome-wide methylation changes and temperature seasonality

As Arabidopsis thaliana has colonized a wide range of habitats across the world it is an attractive model for studying the genetic mechanisms underlying environmental adaptation. Here, we used public data from two collections of A. thaliana accessions to associate genetic variability at individual loci with differences in climates at the sampling sites. We use a novel method to screen the genome for plastic alleles that tolerate a broader climate range than the major allele. This approach reduces confounding with population structure and increases power compared to standard genome-wide association methods. Sixteen novel loci were found, including an association between Chromomethylase 2 (CMT2) and temperature seasonality where the genome-wide CHH methylation was different for the group of accessions carrying the plastic allele. Cmt2 mutants were shown to be more tolerant to heat-stress, suggesting genetic regulation of epigenetic modifications as a likely mechanism underlying natural adaptation to variable temperatures, potentially through differential allelic plasticity to temperature-stress.

Genome-wide association study of Arabidopsis thaliana leaf microbial community

Identifying the factors that influence the outcome of host-microbial interactions is critical to protecting biodiversity, minimizing agricultural losses and improving human health. A few genes that determine symbiosis or resistance to infectious disease have been identified in model species, but a comprehensive examination of how a host genotype influences the structure of its microbial community is lacking. Here we report the results of a field experiment with the model plant Arabidopsis thaliana to identify the fungi and bacteria that colonize its leaves and the host loci that influence the microbe numbers. The composition of this community differs among accessions of A. thaliana. Genome-wide association studies (GWAS) suggest that plant loci responsible for defense and cell wall integrity affect variation in this community. Furthermore, species richness in the bacterial community is shaped by host genetic variation, notably at loci that also influence the reproduction of viruses, trichome branching and morphogenesis.

Natural variation of root traits: from development to nutrient uptake

The root system has a crucial role for plant growth and productivity. Due to the challenges of heterogeneous soil environments, diverse environmental signals are integrated into root developmental decisions. While root growth and growth responses are genetically determined, there is substantial natural variation for these traits. Studying the genetic basis of the natural variation of root growth traits can not only shed light on their evolution and ecological relevance but also can be used to map the genes and their alleles responsible for the regulation of these traits. Analysis of root phenotypes has revealed growth strategies and root growth responses to a variety of environmental stimuli, as well as the extent of natural variation of a variety of root traits including ion content, cellular properties, and root system architectures. Linkage and association mapping approaches have uncovered causal genes underlying the variation of these traits.

Root-secreted nicotianamine from Arabidopsis halleri facilitates zinc hypertolerance by regulating zinc bioavailability

Hyperaccumulators tolerate and accumulate extraordinarily high concentrations of heavy metals. Content of the metal chelator nicotianamine (NA) in the root of zinc hyperaccumulator Arabidopsis halleri is elevated compared with nonhyperaccumulators, a trait that is considered to be one of the markers of a hyperaccumulator. Using metabolite-profiling analysis of root secretions, we found that excess zinc treatment induced secretion of NA in A. halleri roots compared with the nonhyperaccumulator Arabidopsis thaliana. Metal speciation analysis further revealed that the secreted NA forms a stable complex with Zn(II). Supplying NA to a nonhyperaccumulator species markedly increased plant zinc tolerance by decreasing zinc uptake. Therefore, NA secretion from A. halleri roots facilitates zinc hypertolerance through forming a Zn(II)-NA complex outside the roots to achieve a coordinated zinc uptake rate into roots. Secretion of NA was also found to be responsible for the maintenance of iron homeostasis under excess zinc. Together our results reveal root-secretion mechanisms associated with hypertolerance and hyperaccumulation.

Lineage-specific conserved noncoding sequences of plant genomes: their possible role in nucleosome positioning

Many studies on conserved noncoding sequences (CNSs) have found that CNSs are enriched significantly in regulatory sequence elements. We conducted whole-genome analysis on plant CNSs to identify lineage-specific CNSs in eudicots, monocots, angiosperms,and vascular plants based on the premise that lineage-specific CNSs define lineage-specific characters and functions in groups of organisms. We identified 27 eudicot, 204 monocot, 6,536 grass, 19 angiosperm, and 2 vascular plant lineage-specific CNSs(lengths range from 16 to 1,517 bp) that presumably originated in their respective common ancestors. A stronger constraint on the CNSs located in the untranslated regions was observed. The CNSs were often flanked by genes involved in transcription regulation. A drop of A+T content near the border of CNSs was observed and CNS regions showed a higher nucleosome occupancy probability. These CNSs are candidate regulatory elements, which are expected to define lineage-specific features of various plant groups.

Natural variation in abiotic stress responsive gene expression and local adaptation to climate in Arabidopsis thaliana

Gene expression varies widely in natural populations, yet the proximate and ultimate causes of this variation are poorly known. Understanding how variation in gene expression affects abiotic stress tolerance, fitness, and adaptation is central to the field of evolutionary genetics. We tested the hypothesis that genes with natural genetic variation in their expression responses to abiotic stress are likely to be involved in local adaptation to climate in Arabidopsis thaliana. Specifically, we compared genes with consistent expression responses to environmental stress (expression stress responsive, "eSR") to genes with genetically variable responses to abiotic stress (expression genotype-by-environment interaction, "eGEI"). We found that on average genes that exhibited eGEI in response to drought or cold had greater polymorphism in promoter regions and stronger associations with climate than those of eSR genes or genomic controls. We also found that transcription factor binding sites known to respond to environmental stressors, especially abscisic acid responsive elements, showed significantly higher polymorphism in drought eGEI genes in comparison to eSR genes. By contrast, eSR genes tended to exhibit relatively greater pairwise haplotype sharing, lower promoter diversity, and fewer nonsynonymous polymorphisms, suggesting purifying selection or selective sweeps. Our results indicate that cis-regulatory evolution and genetic variation in stress responsive gene expression may be important mechanisms of local adaptation to climatic selective gradients.

Keeping it local: evidence for positive selection in Swedish Arabidopsis thaliana

Detecting positive selection in species with heterogeneous habitats and complex demography is notoriously difficult and prone to statistical biases. The model plant Arabidopsis thaliana exemplifies this problem: In spite of the large amounts of data, little evidence for classic selective sweeps has been found. Moreover, many aspects of the demography are unclear, which makes it hard to judge whether the few signals are indeed signs of selection, or false positives caused by demographic events. Here, we focus on Swedish A. thaliana and we find that the demography can be approximated as a two-population model. Careful analysis of the data shows that such a two island model is characterized by a very old split time that significantly predates the last glacial maximum followed by secondary contact with strong migration. We evaluate selection based on this demography and find that this secondary contact model strongly affects the power to detect sweeps. Moreover, it affects the power differently for northern Sweden (more false positives) as compared with southern Sweden (more false negatives). However, even when the demographic history is accounted for, sweep signals in northern Sweden are stronger than in southern Sweden, with little or no positional overlap. Further simulations including the complex demography and selection confirm that this is not compatible with global selection acting on both populations, and thus can be taken as evidence for local selection within subpopulations of Swedish A. thaliana. This study demonstrates the necessity of combining demographic analyses and sweep scans for the detection of selection, particularly when selection acts predominantly local.

DELAY OF GERMINATION 1 mediates a conserved coat-dormancy mechanism for the temperature- and gibberellin-dependent control of seed germination

Seed germination is an important life-cycle transition because it determines subsequent plant survival and reproductive success. To detect optimal spatiotemporal conditions for germination, seeds act as sophisticated environmental sensors integrating information such as ambient temperature. Here we show that the delay of germination 1 (DOG1) gene, known for providing dormancy adaptation to distinct environments, determines the optimal temperature for seed germination. By reciprocal gene-swapping experiments between Brassicaceae species we show that the DOG1-mediated dormancy mechanism is conserved. Biomechanical analyses show that this mechanism regulates the material properties of the endosperm, a seed tissue layer acting as germination barrier to control coat dormancy. We found that DOG1 inhibits the expression of gibberellin (GA)-regulated genes encoding cell-wall remodeling proteins in a temperature-dependent manner. Furthermore we demonstrate that DOG1 causes temperature-dependent alterations in the seed GA metabolism. These alterations in hormone metabolism are brought about by the temperature-dependent differential expression of genes encoding key enzymes of the GA biosynthetic pathway. These effects of DOG1 lead to a temperature-dependent control of endosperm weakening and determine the optimal temperature for germination. The conserved DOG1-mediated coat-dormancy mechanism provides a highly adaptable temperature-sensing mechanism to control the timing of germination.

Multiple FLC haplotypes defined by independent cis-regulatory variation underpin life history diversity in Arabidopsis thaliana

A key question in evolutionary biology is how molecular variation relates to phenotypic diversity. Arabidopsis FLOWERING LOCUS C (FLC) plays a key role in controlling vernalization—the acceleration of flowering by prolonged cold. Li et al. identify five functionally distinct FLC haplotypes, defined by noncoding sequence variation, which vary in FLC expression level and silencing. Allelic heterogeneity at this single locus accounts for a large proportion of variation in Arabidopsis vernalization. This study advances our understanding of adaptation and provides a new paradigm for analysis of complex traits.

Relating molecular variation to phenotypic diversity is a central goal in evolutionary biology. In Arabidopsis thaliana, FLOWERING LOCUS C (FLC) is a major determinant of variation in vernalization—the acceleration of flowering by prolonged cold. Here, through analysis of 1307 A. thaliana accessions, we identify five predominant FLC haplotypes defined by noncoding sequence variation. Genetic and transgenic experiments show that they are functionally distinct, varying in FLC expression level and rate of epigenetic silencing. Allelic heterogeneity at this single locus accounts for a large proportion of natural variation in vernalization that contributes to adaptation of A. thaliana.

Activation of the Arabidopsis thaliana immune system by combinations of common ACD6 alleles

A fundamental question in biology is how multicellular organisms distinguish self and non-self. The ability to make this distinction allows animals and plants to detect and respond to pathogens without triggering immune reactions directed against their own cells. In plants, inappropriate self-recognition results in the autonomous activation of the immune system, causing affected individuals to grow less well. These plants also suffer from spontaneous cell death, but are at the same time more resistant to pathogens. Known causes for such autonomous activation of the immune system are hyperactive alleles of immune regulators, or epistatic interactions between immune regulators and unlinked genes. We have discovered a third class, in which the Arabidopsis thaliana immune system is activated by interactions between natural alleles at a single locus, ACCELERATED CELL DEATH 6 (ACD6). There are two main types of these interacting alleles, one of which has evolved recently by partial resurrection of a pseudogene, and each type includes multiple functional variants. Most previously studies hybrid necrosis cases involve rare alleles found in geographically unrelated populations. These two types of ACD6 alleles instead occur at low frequency throughout the range of the species, and have risen to high frequency in the Northeast of Spain, suggesting a role in local adaptation. In addition, such hybrids occur in these populations in the wild. The extensive functional variation among ACD6 alleles points to a central role of this locus in fine-tuning pathogen defenses in natural populations.

Plants and their pathogens are engaged in an endless evolutionary battle. The invention of new strategies by pathogens pushes plants to continuously update their defenses. This in turn leads the pathogens to circumvent these new defenses, and so on. Given the abundance of potential enemies, it is therefore not surprising that genes involved in defense against pathogens are among the most variable in plants. A drawback of this extreme variation in pathogen-recognition mechanisms is that at times the plant mistakes itself for an enemy, leading to autonomous activation of defense responses in the absence of pathogens. Conventional models for this phenomenon, called hybrid necrosis, require the interaction between two different genes. Here we show instead that hybrid necrosis can be triggered by interactions between variants of a single gene, ACD6 (ACCELERATED CELL DEATH 6). Several of these variants are common in natural Arabidopsis thaliana populations and can interact to give different levels of activation of the immune system. Our results provide important information into the evolution and operation of the plant defense system. Moreover, the abundant presence of ACD6 functional variation suggests a major role for this gene in modulating plant defenses in nature.

Association mapping of germination traits in Arabidopsis thaliana under light and nutrient treatments: searching for G×E effects

In the natural world, genotype expression is influenced by an organism’s environment. Identifying and understanding the genes underlying phenotypes in different environments is important for making advances in fields ranging from evolution to medicine to agriculture. With the availability of genome-wide genetic-marker datasets, it is possible to look for genes that interact with the environment. Using the model organism, Arabidopsis thaliana, we looked for genes underlying phenotypes as well as genotype-by-environment interactions in four germination traits under two light and two nutrient conditions. We then performed genome-wide association tests to identify candidate genes underlying the observed phenotypes and genotype-by-environment interactions. Of the four germination traits examined, only two showed significant genotype-by-environment interactions. While genome-wide association analyses did not identify any markers or genes explicitly linked to genotype-by-environment interactions, we did identify a total of 55 markers and 71 genes associated with germination differences. Of the 71 genes, four—ZIGA4, PS1, TOR, and TT12—appear to be strong candidates for further study of germination variation under different environments.

A Scalable Open-Source Pipeline for Large-Scale Root Phenotyping of Arabidopsis

Large-scale phenotyping of multicellular organisms is one of the current challenges in biology. We present a comprehensive and scalable pipeline that allows for the efficient phenotyping of root growth traits on a large scale. This includes a high-resolution, low-cost acquisition setup as well as the automated image processing software BRAT. We assess the performance of this pipeline in Arabidopsis thaliana under multiple growth conditions and show its utility by performing genome-wide association studies on 16 root growth traits quantified by BRAT each day during a 5-d time-course experiment. The most significantly associated genome region for root growth rate is a locus encoding a calcium sensing receptor. We find that loss of function and overexpression of this gene can significantly alter root growth in a growth condition dependent manner and that the minor natural allele of the Calcium Sensor Receptor locus is highly significantly enriched in populations in coastal areas, demonstrating the power of our approach to identify regulators of root growth that might have adaptive relevance.

The landscape of nucleotide polymorphism among 13,500 genes of the conifer picea glauca, relationships with functions, and comparison with medicago truncatula

Gene families differ in composition, expression, and chromosomal organization between conifers and angiosperms, but little is known regarding nucleotide polymorphism. Using various sequencing strategies, an atlas of 212k high-confidence single nucleotide polymorphisms (SNPs) with a validation rate of more than 92% was developed for the conifer white spruce (Picea glauca). Nonsynonymous and synonymous SNPs were annotated over the corresponding 13,498 white spruce genes representative of 2,457 known gene families. Patterns of nucleotide polymorphisms were analyzed by estimating the ratio of nonsynonymous to synonymous numbers of substitutions per site (A/S). A general excess of synonymous SNPs was expected and observed. However, the analysis from several perspectives enabled to identify groups of genes harboring an excess of nonsynonymous SNPs, thus potentially under positive selection. Four known gene families harbored such an excess: dehydrins, ankyrin-repeats, AP2/DREB, and leucine-rich repeat. Conifer-specific sequences were also generally associated with the highest A/S ratios. A/S values were also distributed asymmetrically across genes specifically expressed in megagametophytes, roots, or in both, harboring on average an excess of nonsynonymous SNPs. These patterns confirm that the breadth of gene expression is a contributing factor to the evolution of nucleotide polymorphism. The A/S ratios of Medicago truncatula genes were also analyzed: several gene families shared between P. glauca and M. truncatula data sets had similar excess of synonymous or nonsynonymous SNPs. However, a number of families with high A/S ratios were found specific to P. glauca, suggesting cases of divergent evolution at the functional level.

The impact of linked selection on plant genomic variation

Understanding the forces that shape patterns of genetic variation across the genome is a major aim in evolutionary genetics. An emerging insight from analyses of genome-wide polymorphism and divergence data is that selection on linked sites can have an important impact on neutral genetic variation. However, in contrast to Drosophila, which exhibits a signature of recurrent hitchhiking, many plant genomes studied so far seem to mainly be affected by background selection. Moreover, many plants do not exhibit classic signatures of linked selection, such as a correlation between recombination rate and neutral diversity. In this review, I discuss the impact of genome architecture and mating system on the expected signature of linked selection in plants and review empirical evidence for linked selection, with a focus on plant model systems. Finally, I discuss the implications of linked selection for inference of demographic history in plants.

Initiation of meiotic recombination: how and where? Conservation and specificities among eukaryotes

Meiotic recombination is essential for fertility in most sexually reproducing species. This process also creates new combinations of alleles and has important consequences for genome evolution. Meiotic recombination is initiated by the formation of DNA double-strand breaks (DSBs), which are repaired by homologous recombination. DSBs are catalyzed by the evolutionarily conserved SPO11 protein, assisted by several other factors. Some of them are absolutely required, whereas others are needed only for full levels of DSB formation and may participate in the regulation of DSB timing and frequency as well as the coordination between DSB formation and repair. The sites where DSBs occur are not randomly distributed in the genome, and remarkably distinct strategies have emerged to control their localization in different species. Here, I review the recent advances in the components required for DSB formation and localization in the various model organisms in which these studies have been performed.

Genetic resources for quantitative trait analysis: novelty and efficiency in design from an Arabidopsis perspective

The use of genetic resources for the analysis of quantitative traits finds its roots in crop breeding but has seen a rejuvenation in Arabidopsis thaliana thanks to specific tools and genomic approaches. Although widely used in numerous crop and natural species, many approaches were first developed in this reference plant. We will discuss the scientific background and historical use of mapping populations in Arabidopsis and highlight the technological innovations that drove the development of novel strategies. We will especially lay emphasis on the methodologies used to generate the diverse population types and designate possible applications. Finally we highlight some of the most recent developments in generating genetic mapping resources and suggest specific usage for these novel tools and concepts.

An experimental test on the probability of extinction of new genetic variants

In 1927, J.B.S. Haldane reasoned that the probability of fixation of new beneficial alleles is twice their fitness effect. This result, later generalized by M. Kimura, has since become the cornerstone of modern population genetics. There is no experimental test of Haldane's insight that new beneficial alleles are lost with high probability. Here we demonstrate that extinction rates decrease with increasing initial numbers of beneficial alleles, as expected, by performing invasion experiments with inbred lines of the nematode Caenorhabditis elegans. We further show that the extinction rates of deleterious alleles are higher than those of beneficial alleles, also as expected. Interestingly, we also find that for these inbred lines, when at intermediate frequencies, the fate of invaders might not result in their ultimate fixation or loss but on their maintenance. Our study confirms the key results from classical population genetics and highlights that the nature of adaptation can be complex.

Metabolic efficiency underpins performance trade-offs in growth of Arabidopsis thaliana

Growth often involves a trade-off between the performance of contending tasks; metabolic plasticity can play an important role. Here we grow 97 Arabidopsis thaliana accessions in three conditions with a differing supply of carbon and nitrogen and identify a trade-off between two tasks required for rosette growth: increasing the physical size and increasing the protein concentration. We employ the Pareto performance frontier concept to rank accessions based on their multitask performance; only a few accessions achieve a good trade-off under all three growth conditions. We determine metabolic efficiency in each accession and condition by using metabolite levels and activities of enzymes involved in growth and protein synthesis. We demonstrate that accessions with high metabolic efficiency lie closer to the performance frontier and show increased metabolic plasticity. We illustrate how public domain data can be used to search for additional contending tasks, which may underlie the sub-optimality in some accessions.

Genome wide association mapping of grain arsenic, copper, molybdenum and zinc in rice (Oryza sativa L.) grown at four international field sites

The mineral concentrations in cereals are important for human health, especially for individuals who consume a cereal subsistence diet. A number of elements, such as zinc, are required within the diet, while some elements are toxic to humans, for example arsenic. In this study we carry out genome-wide association (GWA) mapping of grain concentrations of arsenic, copper, molybdenum and zinc in brown rice using an established rice diversity panel of ∼300 accessions and 36.9 k single nucleotide polymorphisms (SNPs). The study was performed across five environments: one field site in Bangladesh, one in China and two in the US, with one of the US sites repeated over two years. GWA mapping on the whole dataset and on separate subpopulations of rice revealed a large number of loci significantly associated with variation in grain arsenic, copper, molybdenum and zinc. Seventeen of these loci were detected in data obtained from grain cultivated in more than one field location, and six co-localise with previously identified quantitative trait loci. Additionally, a number of candidate genes for the uptake or transport of these elements were located near significantly associated SNPs (within 200 kb, the estimated global linkage disequilibrium previously employed in this rice panel). This analysis highlights a number of genomic regions and candidate genes for further analysis as well as the challenges faced when mapping environmentally-variable traits in a highly genetically structured diversity panel.

A recent local sweep at the PHYA locus in the Northern European Spiterstulen population of Arabidopsis lyrata

Northern and central European Arabidopsis lyrata ssp. petraea populations are locally adapted to prevailing climatic conditions through differences in timing of life history events. The timing of flowering and, in perennials, the timing of growth cessation influence fitness. Phytochrome A may have an important role in regulating these life history traits as it perceives changes in daylength. We asked whether PHYA has contributed to local adaptation to the northern conditions in A. l. petraea. To search for signals of directional selection at the PHYA locus, we resequenced PHYA and 9 short fragments around PHYA from a 57-kb region from a German (Plech) and a Norwegian (Spiterstulen) population and compared patterns of differentiation and diversity to a set of 19 reference loci around the genome. First, we found that the populations were highly differentiated: there were three nonsynonymous fixed differences at the PHYA locus, which was in stark contrast with the total four fixed differences in the 19 reference loci. Compatible with a sweep hypothesis, variation was almost completely removed from the 9.4-kb region around PHYA in the northern Spiterstulen population. The overall level of linkage disequilibrium (LD) was higher in Spiterstulen, but there was no LD across the PHYA locus in the population, which is also a known consequence of a selective sweep. The sweep has likely occurred after the last glacial maximum, which suggests that it has contributed to adaptation to the northern conditions.

The genetic structure of Arabidopsis thaliana in the south-western Mediterranean range reveals a shared history between North Africa and southern Europe

BACKGROUND

Deciphering the genetic structure of Arabidopsis thaliana diversity across its geographic range provides the bases for elucidating the demographic history of this model plant. Despite the unique A. thaliana genomic resources currently available, its history in North Africa, the extreme southern limit in the biodiversity hotspot of the Mediterranean Basin, remains virtually unknown.

RESULTS

To approach A. thaliana evolutionary history in North Africa, we have analysed the genetic diversity and structure of 151 individuals collected from 20 populations distributed across Morocco. Genotyping of 249 genome-wide SNPs indicated that Morocco contains substantially lower diversity than most analyzed world regions. However, IBD, STRUCTURE and PCA clustering analyses showed that genetic variation is strongly geographically structured. We also determined the genetic relationships between Morocco and the closest European region, the Iberian Peninsula, by analyses of 201 populations from both regions genotyped with the same SNPs. These analyses detected four genetic groups, but all Moroccan accessions belonged to a common Iberian/Moroccan cluster that appeared highly differentiated from the remaining groups. Thus, we identified a genetic lineage with an isolated demographic history in the south-western Mediterranean region. The existence of this lineage was further supported by the study of several flowering genes and traits, which also found Moroccan accessions similar to the same Iberian group. Nevertheless, genetic diversity for neutral SNPs and flowering genes was higher in Moroccan than in Iberian populations of this lineage. Furthermore, we analyzed the genetic relationships between Morocco and other world regions by joint analyses of a worldwide collection of 337 accessions, which detected an additional weak relationship between North Africa and Asia.

CONCLUSIONS

The patterns of genetic diversity and structure of A. thaliana in Morocco show that North Africa is part of the species native range and support the occurrence of a glacial refugium in the Atlas Mountains. In addition, the identification of a genetic lineage specific of Morocco and the Iberian Peninsula indicates that the Strait of Gibraltar has been an A. thaliana migration route between Europe and Africa. Finally, the genetic relationship between Morocco and Asia suggests another migration route connecting north-western Africa and Asia.

Characterization and identification of cis-regulatory elements in Arabidopsis based on single-nucleotide polymorphism information

Identifying regulatory elements and revealing their role in gene expression regulation remains a central goal of plant genome research. We exploited the detailed genomic sequencing information of a large number of Arabidopsis (Arabidopsis thaliana) accessions to characterize known and to identify novel cis-regulatory elements in gene promoter regions of Arabidopsis by relying on conservation as the hallmark signal of functional relevance. Based on the genomic layout and the obtained density profiles of single-nucleotide polymorphisms (SNPs) in sequence regions upstream of transcription start sites, the average length of promoter regions in Arabidopsis could be established at 500 bp. Genes associated with high degrees of variability of their respective upstream regions are preferentially involved in environmental response and signaling processes, while low levels of promoter SNP density are common among housekeeping genes. Known cis-elements were found to exhibit a decreased SNP density than sequence regions not associated with known motifs. For 15 known cis-element motifs, strong positional preferences relative to the transcription start site were detected based on their promoter SNP density profiles. Five novel candidate cis-element motifs were identified as consensus motifs of 17 sequence hexamers exhibiting increased sequence conservation combined with evidence of positional preferences, annotation information, and functional relevance for inducing correlated gene expression. Our study demonstrates that the currently available resolution of SNP data offers novel ways for the identification of functional genomic elements and the characterization of gene promoter sequences.

Genome wide association mapping of grain arsenic, copper, molybdenum and zinc in rice (Oryza sativa L.) grown at four international field sites

The mineral concentrations in cereals are important for human health, especially for individuals who consume a cereal subsistence diet. A number of elements, such as zinc, are required within the diet, while some elements are toxic to humans, for example arsenic. In this study we carry out genome-wide association (GWA) mapping of grain concentrations of arsenic, copper, molybdenum and zinc in brown rice using an established rice diversity panel of ∼ 300 accessions and 36.9 k single nucleotide polymorphisms (SNPs). The study was performed across five environments: one field site in Bangladesh, one in China and two in the US, with one of the US sites repeated over two years. GWA mapping on the whole dataset and on separate subpopulations of rice revealed a large number of loci significantly associated with variation in grain arsenic, copper, molybdenum and zinc. Seventeen of these loci were detected in data obtained from grain cultivated in more than one field location, and six co-localise with previously identified quantitative trait loci. Additionally, a number of candidate genes for the uptake or transport of these elements were located near significantly associated SNPs (within 200 kb, the estimated global linkage disequilibrium previously employed in this rice panel). This analysis highlights a number of genomic regions and candidate genes for further analysis as well as the challenges faced when mapping environmentally-variable traits in a highly genetically structured diversity panel.