, Volume 69, Issue 1-4, pp 261-273

Moderately and Highly Polymorphic Microsatellites Provide Discordant Estimates of Population Divergence in Sockeye Salmon, Oncorhynchus nerka

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Abstract

Mutation rate can vary widely among microsatellite loci. This variation may cause discordant single-locus and multi-locus estimates of FST, the commonly used measure of population divergence. We use 16 microsatellite and five allozyme loci from 14 sockeye salmon populations to address two questions about the affect of mutation rate on estimates of FST: (1) does mutation rate influence FST estimates from all microsatellites to a similar degree relative to allozymes?; (2) does the influence of mutation rate on FST estimates from microsatellites vary with geographic scale in spatially structured populations? For question one we find that discordant estimates of FST among microsatellites as well as between the two marker classes are correlated with mean within-population heterozygosity (HS) and thus are likely due to differences in mutation rate. Highly polymorphic microsatellites (HS > 0.84) provide significantly lower estimates of FST than moderately polymorphic microsatellites and allozymes (HS < 0.60). Estimates of FST from binned allele frequency data and RST provide more accurate measures of population divergence for highly polymorphic but not for moderately polymorphic microsatellites. We conclude it is more important to pool loci of like HS rather than marker class when estimating FST. For question two we find the FST values for moderately and highly polymorphic loci, while significantly different, are positively correlated for geographically proximate but not geographically distant population pairs. These results are consistent with expectations from the equilibrium approximation of Wright's infinite island model and confirm that the influence of mutation on estimates of FST can vary in spatially structured populations presumably because the rate of migration varies inversely with geographic scale.