Null allele allelic dropouts or rare sex detection in clonal organisms: simulations and application to real data sets of pathogenic microbes

摘要

BackgroundPathogens and their vectors are organisms whose ecology is often only accessible through population genetics tools based on spatio-temporal variability of molecular markers. However, molecular tools may present technical difficulties due to the masking of some alleles (allelic dropouts and/or null alleles), which tends to bias the estimation of heterozygosity and thus the inferences concerning the breeding system of the organism under study. This is especially critical in clonal organisms in which deviation from panmixia, as measured by Wright’s FIS, can, in principle, be used to infer both the extent of clonality and structure in a given population. In particular, null alleles and allelic dropouts are locus specific and likely produce high variance of Wright’s FIS across loci, as rare sex is expected to do. In this paper we propose a tool enabling to discriminate between consequences of these technical problems and those of rare sex.