Core share and HTML view are not available for this content. However, as you have access to this content, a full PDF is available via the ‘Save PDF’ action button.
Microsatellite loci have become important in population genetics because of their high level of
polymorphism in natural populations, very frequent occurrence throughout the genome, and
apparently high mutation rate. Observed repeat numbers (alleles size) in natural populations and
expectations based on computer simulations suggest that the range of repeat numbers at a
microsatellite locus is restricted. This range is a key parameter that should be properly estimated in
order to proceed with calculations of divergence times in phylogenetic studies and to better
investigate the within- and between-population variability. The ‘plug-in’ estimate of range based
on the minimum and maximum value observed in a sample is not satisfactory because of the
relatively large number of alleles in comparison with typical sample sizes. In this paper, a set of
data from 30 dinucleotide microsatellite loci is analysed under the assumption of independence
among loci. Bayesian inference on range for one locus is obtained by assuming that constraints on
range values exist as sharp bounds. Closed-form calculations and robustness revealed by our
analysis suggest that the proposed Bayesian approach might be routinely used by researchers to
classify microsatellite loci according to the estimated value of their allelic range.
