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We present a Bayesian method for characterizing the mating system ofpopulations reproducing through a mixture of self-fertilization and randomoutcrossing. Our method uses patterns of genetic variation across the genome asa basis for inference about pure hermaphroditism, androdioecy, and gynodioecy.We extend the standard coalescence model to accommodate these mating systems,accounting explicitly for multilocus identity disequilibrium, inbreedingdepression, and variation in fertility among mating types. We incorporate theEwens Sampling Formula (ESF) under the infinite-alleles model of mutation toobtain a novel expression for the likelihood of mating system parameters. OurMarkov chain Monte Carlo (MCMC) algorithm assigns locus-specific mutationrates, drawn from a common mutation rate distribution that is itself estimatedfrom the data using a Dirichlet Process Prior (DPP) model. Among the parametersjointly inferred are the population-wide rate of self-fertilization,locus-specific mutation rates, and the number of generations since the mostrecent outcrossing event for each sampled individual.

Bayesian co-estimation of selfing rate and locus-specific mutation rates for a partially selfing population