Fabrice Roux

Genome-wide association study of 107 phenotypes in Arabidopsis thaliana inbred lines

Although pioneered by human geneticists as a potential solution to the challenging problem of finding the genetic basis of common human diseases, genome-wide association (GWA) studies have, owing to advances in genotyping and sequencing technology, become an obvious general approach for studying the genetics of natural variation and traits of agricultural importance. They are particularly useful when inbred lines are available, because once these lines have been genotyped they can be phenotyped multiple times, making it possible (as well as extremely cost effective) to study many different traits in many different environments, while replicating the phenotypic measurements to reduce environmental noise. Here we demonstrate the power of this approach by carrying out a GWA study of 107 phenotypes in Arabidopsis thaliana, a widely distributed, predominantly self-fertilizing model plant known to harbour considerable genetic variation for many adaptively important traits. Our results are dramatically different from those of human GWA studies, in that we identify many common alleles of major effect, but they are also, in many cases, harder to interpret because confounding by complex genetics and population structure make it difficult to distinguish true associations from false. However, a-priori candidates are significantly over-represented among these associations as well, making many of them excellent candidates for follow-up experiments. Our study demonstrates the feasibility of GWA studies in A. thaliana and suggests that the approach will be appropriate for many other organisms.

Adaptation to Climate Across the Arabidopsis thaliana Genome

Alleles that are under selection in Arabidopsis serve as genetic markers that can be used to predict local adaptation. Understanding the genetic bases and modes of adaptation to current climatic conditions is essential to accurately predict responses to future environmental change. We conducted a genome-wide scan to identify climate-adaptive genetic loci and pathways in the plant Arabidopsis thaliana. Amino acid–changing variants were significantly enriched among the loci strongly correlated with climate, suggesting that our scan effectively detects adaptive alleles. Moreover, from our results, we successfully predicted relative fitness among a set of geographically diverse A. thaliana accessions when grown together in a common environment. Our results provide a set of candidates for dissecting the molecular bases of climate adaptations, as well as insights about the prevalence of selective sweeps, which has implications for predicting the rate of adaptation.

Linkage and Association Mapping of Arabidopsis thaliana Flowering Time in Nature

Flowering time is a key life-history trait in the plant life cycle. Most studies to unravel the genetics of flowering time in Arabidopsis thaliana have been performed under greenhouse conditions. Here, we describe a study about the genetics of flowering time that differs from previous studies in two important ways: first, we measure flowering time in a more complex and ecologically realistic environment; and, second, we combine the advantages of genome-wide association (GWA) and traditional linkage (QTL) mapping. Our experiments involved phenotyping nearly 20,000 plants over 2 winters under field conditions, including 184 worldwide natural accessions genotyped for 216,509 SNPs and 4,366 RILs derived from 13 independent crosses chosen to maximize genetic and phenotypic diversity. Based on a photothermal time model, the flowering time variation scored in our field experiment was poorly correlated with the flowering time variation previously obtained under greenhouse conditions, reinforcing previous demonstrations of the importance of genotype by environment interactions in A. thaliana and the need to study adaptive variation under natural conditions. The use of 4,366 RILs provides great power for dissecting the genetic architecture of flowering time in A. thaliana under our specific field conditions. We describe more than 60 additive QTLs, all with relatively small to medium effects and organized in 5 major clusters. We show that QTL mapping increases our power to distinguish true from false associations in GWA mapping. QTL mapping also permits the identification of false negatives, that is, causative SNPs that are lost when applying GWA methods that control for population structure. Major genes underpinning flowering time in the greenhouse were not associated with flowering time in this study. Instead, we found a prevalence of genes involved in the regulation of the plant circadian clock. Furthermore, we identified new genomic regions lacking obvious candidate genes.

The Scale of Population Structure in Arabidopsis thaliana

The population structure of an organism reflects its evolutionary history and influences its evolutionary trajectory. It constrains the combination of genetic diversity and reveals patterns of past gene flow. Understanding it is a prerequisite for detecting genomic regions under selection, predicting the effect of population disturbances, or modeling gene flow. This paper examines the detailed global population structure of Arabidopsis thaliana. Using a set of 5,707 plants collected from around the globe and genotyped at 149 SNPs, we show that while A. thaliana as a species self-fertilizes 97% of the time, there is considerable variation among local groups. This level of outcrossing greatly limits observed heterozygosity but is sufficient to generate considerable local haplotypic diversity. We also find that in its native Eurasian range A. thaliana exhibits continuous isolation by distance at every geographic scale without natural breaks corresponding to classical notions of populations. By contrast, in North America, where it exists as an exotic species, A. thaliana exhibits little or no population structure at a continental scale but local isolation by distance that extends hundreds of km. This suggests a pattern for the development of isolation by distance that can establish itself shortly after an organism fills a new habitat range. It also raises questions about the general applicability of many standard population genetics models. Any model based on discrete clusters of interchangeable individuals will be an uneasy fit to organisms like A. thaliana which exhibit continuous isolation by distance on many scales.

Towards identifying genes underlying ecologically relevant traits in Arabidopsis thaliana

A major challenge in evolutionary biology and plant breeding is to identify the genetic basis of complex quantitative traits, including those that contribute to adaptive variation. Here we review the development of new methods and resources to fine-map intraspecific genetic variation that underlies natural phenotypic variation in plants. In particular, the analysis of 107 quantitative traits reported in the first genome-wide association mapping study in Arabidopsis thaliana sets the stage for an exciting time in our understanding of plant adaptation. We also argue for the need to place phenotype–genotype association studies in an ecological context if one is to predict the evolutionary trajectories of plant species.

Evolutionary‐thinking in agricultural weed management

Agricultural weeds evolve in response to crop cultivation. Nevertheless, the central importance of evolutionary ecology for understanding weed invasion, persistence and management in agroecosystems is not widely acknowledged. This paper calls for more evolutionarily-enlightened weed management, in which management principles are informed by evolutionary biology to prevent or minimize weed adaptation and spread. As a first step, a greater knowledge of the extent, structure and significance of genetic variation within and between weed populations is required to fully assess the potential for weed adaptation. The evolution of resistance to herbicides is a classic example of weed adaptation. Even here, most research focuses on describing the physiological and molecular basis of resistance, rather than conducting studies to better understand the evolutionary dynamics of selection for resistance. We suggest approaches to increase the application of evolutionary-thinking to herbicide resistance research. Weed population dynamics models are increasingly important tools in weed management, yet these models often ignore intrapopulation and interpopulation variability, neglecting the potential for weed adaptation in response to management. Future agricultural weed management can benefit from greater integration of ecological and evolutionary principles to predict the long-term responses of weed populations to changing weed management, agricultural environments and global climate.

Genome-Wide Epigenetic Perturbation Jump-Starts Patterns of Heritable Variation Found in Nature

We extensively phenotyped 6000 Arabidopsis plants with experimentally perturbed DNA methylomes as well as a diverse panel of natural accessions in a common garden. We found that alterations in DNA methylation not only caused heritable phenotypic diversity but also produced heritability patterns closely resembling those of the natural accessions. Our findings indicate that epigenetically induced and naturally occurring variation in complex traits share part of their polygenic architecture and may offer complementary adaptation routes in ecological settings.

The Dominance of the Herbicide Resistance Cost in Several Arabidopsis thaliana Mutant Lines

Resistance evolution depends upon the balance between advantage and disadvantage (cost) conferred in treated and untreated areas. By analyzing morphological characters and simple fitness components, the cost associated with each of eight herbicide resistance alleles (acetolactate synthase, cellulose synthase, and auxin-induced target genes) was studied in the model plant Arabidopsis thaliana. The use of allele-specific PCR to discriminate between heterozygous and homozygous plants was used to provide insights into the dominance of the resistance cost, a parameter rarely described. Morphological characters appear more sensitive than fitness (seed production) because 6 vs. 4 differences between resistant and sensitive homozygous plants were detected, respectively. Dominance levels for the fitness cost ranged from recessivity (csr1-1, ixr1-2, and axr1-3) to dominance (axr2-1) to underdominance (aux1-7). Furthermore, the dominance level of the herbicide resistance trait did not predict the dominance level of the cost of resistance. The relationship of our results to theoretical predictions of dominance and the consequences of fitness cost and its dominance in resistance management are discussed.

Utilization of the three high-throughput SNP genotyping methods, the GOOD assay, Amplifluor and TaqMan, in diploid and polyploid plants

The application of high-throughput SNP genotyping is a great challenge for many research projects in the plant genetics domain. The GOOD assay for mass spectrometry, Amplifluor® and TaqMan® are three methods that rely on different principles for allele discrimination and detection, specifically, primer extension, allele-specific PCR and hybridization, respectively. First, with the goal of assessing allele frequencies by means of SNP genotyping, we compared these methods on a set of three SNPs present in the herbicide resistance genes CSR, AXR1 and IXR1 of Arabidopsis thaliana. In this comparison, we obtained the best results with TaqMan® based on PCR specificity, flexibility in primer design and success rate. We also used mass spectrometry for genotyping polyploid species. Finally, a combination of the three methods was used for medium- to high-throughput genotyping in a number of different plant species. Here, we show that all three genotyping technologies are successful in discriminating alleles in various plant species and discuss the factors that must be considered in assessing which method to use for a given application.

A unified approach to the estimation and interpretation of resistance costs in plants.

Plants exhibit a number of adaptive defence traits that endow resistance to past and current abiotic and biotic stresses. It is generally accepted that these adaptations will incur a cost when plants are not challenged by the stress to which they have become adapted—the so-called ‘cost of adaptation’. The need to minimise or account for allelic variation at other fitness-related loci (genetic background control) is frequently overlooked when assessing resistance costs associated with plant defence traits. We provide a synthesis of the various experimental protocols that accomplish this essential requirement. We also differentiate those methods that enable the identification of the trait-specific or mechanistic basis of costs (direct methods) from those that provide an estimate of the impact of costs by examining the evolutionary trajectories of resistance allele frequencies at the population level (indirect methods). The advantages and disadvantages for each proposed experimental design are discussed. We conclude that plant resistance systems provide an ideal model to address fundamental questions about the cost of adaptation to stress. We also propose some ways to expand the scope of future studies for further fundamental and applied insight into the significance of adaptation costs.