Strong selection within a given population locally reduces genetic variability not only in the selected gene itself but also in neighbouring loci. This so-called hitch-hiking effect is related to the initial linkage disequilibrium between markers and the selected gene, and depends mainly on the number of copies of the beneficial allele at the start of the selection phase. Contrary to the classical case, in which selection acts on a single, newly arisen beneficial mutation, we considered selection from standing variation (soft selective sweeps) on a gene (Rht-B1) with a major effect on plant height, a selected trait in an experimental wheat population grown for 17 generations, and we documented the evolution of gene diversity and linkage disequilibrium near this gene. As expected, Rht-B1 was found to be under strong selection (s = 0.15) and its variation in frequency accounted for 15% of the total trait evolution. This led to a smaller genetic effective population size at Rht-B1 (N(eg) = 18) compared to the whole genome estimation (N(eg) = 167). When compared with expectations under genetic drift only, no significant decrease in gene diversity was found at the closest loci. We computed expected di-locus frequencies for any linked marker-Rht-B1 pair due to hitch-hiking effects. We found that hitch-hiking was expected to affect the two most closely linked loci, but expected reduction in gene diversity was not greater than that due to genetic drift, which was consistent with the observations. Such limited effect was attributed to the low level of linkage disequilibrium (0.16) estimated after parental intercrosses, together with a relatively high initial frequency of the gene. This situation is favourable to candidate gene approaches where small linkage disequilibrium around selected genes is expected.

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Microsatellite markers are extensively used to evaluate genetic diversity in natural or experimental evolving populations. Their high degree of polymorphism reflects their high mutation rates. Estimates of the mutation rates are therefore necessary when characterizing diversity in populations. As a complement to the classical experimental designs, we propose to use experimental populations, where the initial state is entirely known and some intermediate states have been thoroughly surveyed, thus providing a short timescale estimation together with a large number of cumulated meioses. In this article, we derived four original gene genealogy-based methods to assess mutation rates with limited bias due to relevant model assumptions incorporating the initial state, the number of new alleles, and the genetic effective population size. We studied the evolution of genetic diversity at 21 microsatellite markers, after 15 generations in an experimental wheat population. Compared to the parents, 23 new alleles were found in generation 15 at 9 of the 21 loci studied. We provide evidence that they arose by mutation. Corresponding estimates of the mutation rates ranged from 0 to 4.97 3 10 À3 per generation (i.e., year). Sequences of several alleles revealed that length polymorphism was only due to variation in the core of the microsatellite. Among different microsatellite characteristics, both the motif repeat number and an independent estimation of the Nei diversity were correlated with the novel diversity. Despite a reduced genetic effective size, global diversity at microsatellite markers increased in this population, suggesting that microsatellite diversity should be used with caution as an indicator in biodiversity conservation issues. B ECAUSE microsatellite markers (tandemly repeated DNA motifs of 1-6 bp in length) are highly polymorphic and since they are distributed across the whole genome (Wu and Tanksley 1993;Plaschke et al. 1995;Pejic et al. 1998), they constitute a powerful tool to assess the level of genetic differentiation within and among experimental or natural populations at different generations. The high degree of polymorphism at microsatellite markers is directly related to their underlying mutation rates, which can be explained by two mutational mechanisms: polymerase slippage during DNA replication and unequal crossing over during recombinationbut not excluding SNP mutations at a lower rate. These two mechanisms involve changes in the number of motif repeats. Understanding the evolutionary properties of microsatellites is hence necessary for correctly interpreting diversity data when studying populations across generations and/or populations that have spatially diverged (Ellegren 2004).An increasing number of studies have been devoted to the estimation of mutation rates at microsatellite loci (e.g., Schug et al. 1998;Symonds and Lloyd 2003;Denver et al. 2004;Thuillet et al. 2004), which reveal a far more complex scheme for microsatellite evolution than previously stated (Schlö tterer 2000;Elleg...