A Bayesian approach to inferring population structure from dominant markers

Abstract

Molecular markers derived from PCR amplification of genomic DNA are an important part of the toolkit of evolutionary geneticists. RAPDs, AFLPs, and ISSR polymorphisms allow analysis of species for which prior DNA sequence information is lacking, but dominance makes it impossible to apply standard techniques to calculate F -statistics. We describe a Bayesian method that allows direct estimates of F st from dominant markers. In contrast to existing alternatives, we do not assume prior knowledge of the degree of within-population inbreeding. In particular, we do not assume that genotypes within populations are in Hardy-Weinberg proportions. Our estimate of F st incorporates uncertainty about the magnitude of within-population inbreeding. Simulations show that samples from even a relatively small number of loci and populations produce reliable estimates of F st . Moreover, some information about the degree of within population inbreeding (F is ) is available from data sets with a large number of loci and populations. We illustrate 1 the method with a reanalysis of RAPD data from 14 populations of a North American orchid, Platanthera leucophaea.

Increased inbreeding and strong kinship structure in Taxus baccata estimated from both AFLP and SSR data

“…Although estimation of inbreeding levels is the aim of many genetic studies (especially in endangered species), AFLP markers are typically considered to be poorly informative about inbreeding owing to low polymorphism (bi-allelic system) and complete dominance (Holsinger et al, 2002). In this paper we introduced a Bayesian method for inference of the within-population inbreeding coefficient that takes full advantage of multilocus phenotypes derived from dominant markers.…”

“…At the extreme, if all the F i values in our model (see for example, equation (1)) were the same across all individuals, they would behave as a single parameter F. Such an F would be near-impossible to estimate, because it could take any value easily counterbalanced by specific allele frequencies to give the same likelihood. The same property makes the simultaneous maximum likelihood inference of F and allele frequencies based on dominant markers impossible (Holsinger et al, 2002). However, as long as some variation in F i is expected (for example, owing to mixed mating system), the algorithm proposed in this study provides robust estimates of within-population inbreeding.…”

Is floral divergence sufficient to maintain species boundaries upon secondary contact in Mediterranean food-deceptive orchids?

“…We used the Bayesian approach proposed by Holsinger et al (2002), as implemented in HICKORY v. 1.1 (http://darwin.eeb.uconn.edu/ hickory/software.html) using the f free model run to estimate F ST for dominant AFLP markers.…”

New molecular evidence for fragmentation between two distant populations of the threatened stingless bee Melipona subnitida Ducke (Hymenoptera, Apidae, Meliponini)

“…The program HICKORY v.1.1, which implements the Bayesian method (Holsinger et al 2002), was used for estimating θ B (F ST analogue), heterozygosity (H S ), and the inbreeding coefficient (f), an F IS analogue for dominant markers. Analysis of Molecular Variance (AMOVA) was conducted using all the amplified loci to check the occurrence of population structure among sampling localities using ARLEQUIN v.3.11 (Excoffier et al 2006).…”

“…Of the models applied to the ISSR dataset, the full model, in which θ and f are estimated simultaneously, was preferred primarily because of its smaller deviant information criterion (DIC) value (657.47), with a difference of more than six units required to indicate strong support over all the other models (Holsinger et al 2002). In the Bayesian approach θ B (analogue to Wright's F ST ), f (analogue to F IS ), and H S (average panmictic heterozygosity across populations) were estimated to be 0.33, 0.31 and 0.29, respectively, indicating a pronounced genetic differentiation between populations, possibly caused by restricted gene flow and random genetic drift (Epperson 1995).…”