Summary1 Long-distance dispersal events are biologically very important for plants because they aect colonization probabilities, the probabilities of population persistence in a fragmented habitat, and metapopulation structure. They are, however, very dicult to investigate because of their low frequency. We reviewed the use of molecular markers in the population genetics approach to studying dispersal. With these methods the consequences of long-distance dispersal are studied, rather than the frequency of the dispersal events themselves. 2 Molecular markers vary, displaying dierent amounts of variation and dierent modes of inheritance: they may be either dominant or codominant, and may or may not be subjected to genetic recombination. Use of markers has inspired the development of maximum likelihood techniques that take the evolutionary history of alleles into account while estimating gene¯ow. 3 Inferring seed dispersal rates from indirect measurements of gene¯ow involves three steps: (i) quantifying genetic dierentiation among populations and using this to estimate the rate of gene¯ow; (ii) producing a genetic dispersal curve by regressing geographical distance among populations against the amount of gene¯ow; and (iii) separating seed-mediated from pollen-mediated gene¯ow, by comparing dierentiation in nuclear vs. cytoplasmic molecular markers. In this way, potentially very low levels of gene¯ow can be detected. 4 The indirect approach is based on a number of assumptions. The validity of each assumption should be assessed by independent methods or the estimates of genē ow and dispersal should be mainly used in a comparative context. In metapopulations, with frequent extinction and colonization, the relationship between genetic dierentiation and gene¯ow is not straightforward, and other methods should be used. 5 Highly variable molecular markers, especially microsatellites, have facilitated a direct genetic approach to measuring gene¯ow, based on parental analyses. 6 The population genetic approach provides dierent information about dispersal than ecological methods. Thus population genetic and ecological methods may supplement each other, and together lead to a better insight into the dispersal process than either of the methods on its own.
Despite the increasing number of genomic tools, identifying the genetics underlying adaptive complex traits remains challenging in the model species Arabidopsis thaliana. This is due, at least in part, to the lack of data on the geographical scale of adaptive phenotypic variation. The aims of this study were (i) to tease apart the historical roles of adaptive and nonselective processes in shaping phenological variation in A. thaliana in France and (ii) to gain insights into the spatial scale of adaptive variation by identifying the putative selective agents responsible for this selection. Forty-nine natural stands from four climatically contrasted French regions were characterized (i) phenologically for six traits, (ii) genetically using 135 SNP markers and (iii) ecologically for 42 variables. Up to 63% of phenological variation could be explained by neutral genetic diversity. The remaining phenological variation displayed stronger associations with ecological variation within regions than among regions, suggesting the importance of local selective agents in shaping adaptive phenological variation. Although climatic conditions have often been suggested as the main selective agents acting on phenology in A. thaliana, both edaphic conditions and interspecific competition appear to be strong selective agents in some regions. In a first attempt to identify the genetics of phenological variation at different geographical scales, we phenotyped worldwide accessions and local polymorphic populations from the French RegMap in a genome-wide association (GWA) mapping study. The genomic regions associated with phenological variation depended upon the geographical scale considered, stressing the need to account for the scale of adaptive phenotypic variation when choosing accession panels for GWAS.
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