No abstract

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.

Most adaptive traits are controlled by large number of genes that may all together be the targets of selection. Adaptation may thus involve multiple but not necessarily substantial allele frequency changes. This has important consequences for the detection of selected loci and implies that a quantitative genetics framework may be more appropriate than the classical 'selective sweep' paradigm. Preferred methods to detect loci involved in local adaptation are based on the detection of 'outlier' values of the allelic differentiation F ST . A quantitative genetics framework is adopted here to review theoretical expectations for how allelic differentiation at quantitative trait loci (F STQ ) relates to (i), neutral genetic differentiation (F ST ) and (ii), phenotypic differentiation (Q ST ). We identify cases where results of outlier-based methods are likely to be poor and where differentiation at selected loci conveys little information regarding local adaptation. A first case is when neutral differentiation is high, so that local adaptation does not necessitate increased differentiation. A second case is when local adaptation is reached via an increased covariance of allelic effects rather than via allele frequency changes, which is more likely under high gene flow when the number of loci is high and selection is recent. The comparison of theoretical predictions with observed data from the literature suggests that polygenic local adaptation involving only faint allele frequency changes are very likely in some species such as forest trees and for climate-related traits. Recent methodological improvements that may alleviate the weakness of F ST -based detection methods are presented.

Microsatellites (or SSRs: simple sequence repeats) are among the most frequently used DNA markers in many areas of research. The use of microsatellite markers is limited by the difficulties involved in their de novo isolation from species for which no genomic resources are available. We describe here a high-throughput method for isolating microsatellite markers based on coupling multiplex microsatellite enrichment and next-generation sequencing on 454 GS-FLX Titanium platforms. The procedure was calibrated on a model species (Apis mellifera) and validated on 13 other species from various taxonomic groups (animals, plants and fungi), including taxa for which severe difficulties were previously encountered using traditional methods. We obtained from 11,497 to 34,483 sequences depending on the species and the number of detected microsatellite loci ranged from 199 to 5791. We thus demonstrated that this procedure can be readily and successfully applied to a large variety of taxonomic groups, at much lower cost than would have been possible with traditional protocols. This method is expected to speed up the acquisition of high-quality genetic markers for nonmodel organisms.

Rapid phenotypic evolution of quantitative traits can occur within years, but its underlying genetic architecture remains uncharacterized. Here we test the theoretical prediction that genes with intermediate pleiotropy drive adaptive evolution in nature. Through a resurrection experiment, we grew Arabidopsis thaliana accessions collected across an 8-year period in six micro-habitats representative of that local population. We then used genome-wide association mapping to identify the single-nucleotide polymorphisms (SNPs) associated with evolved and unevolved traits in each micro-habitat. Finally, we performed a selection scan by testing for temporal differentiation in these SNPs. Phenotypic evolution was consistent across micro-habitats, but its associated genetic bases were largely distinct. Adaptive evolutionary change was most strongly driven by a small number of quantitative trait loci (QTLs) with intermediate degrees of pleiotropy; this pleiotropy was synergistic with the per-trait effect size of the SNPs, increasing with the degree of pleiotropy. In addition, weak selection was detected for frequent micro-habitat-specific QTLs that shape single traits. In this population, A. thaliana probably responded to local warming and increased competition, in part mediated by central regulators of flowering time. This genetic architecture, which includes both synergistic pleiotropic QTLs and distinct QTLs within particular micro-habitats, enables rapid phenotypic evolution while still maintaining genetic variation in wild populations.