A Bayesian Approach to Inferring Rates of Selfing and Locus-Specific Mutation.
Abstract
We present a Bayesian method for characterizing the mating system of populations reproducing
through a mixture of self-fertilization and random outcrossing. Our method uses patterns
of genetic variation across the genome as a basis for inference about reproduction
under pure hermaphroditism, gynodioecy, and a model developed to describe the self-fertilizing
killifish Kryptolebias marmoratus. We extend the standard coalescence model to accommodate
these mating systems, accounting explicitly for multilocus identity disequilibrium,
inbreeding depression, and variation in fertility among mating types. We incorporate
the Ewens sampling formula (ESF) under the infinite-alleles model of mutation to obtain
a novel expression for the likelihood of mating system parameters. Our Markov chain
Monte Carlo (MCMC) algorithm assigns locus-specific mutation rates, drawn from a common
mutation rate distribution that is itself estimated from the data using a Dirichlet
process prior model. Our sampler is designed to accommodate additional information,
including observations pertaining to the sex ratio, the intensity of inbreeding depression,
and other aspects of reproduction. It can provide joint posterior distributions for
the population-wide proportion of uniparental individuals, locus-specific mutation
rates, and the number of generations since the most recent outcrossing event for each
sampled individual. Further, estimation of all basic parameters of a given model permits
estimation of functions of those parameters, including the proportion of the gene
pool contributed by each sex and relative effective numbers.
Type
Journal articleSubject
AnimalsFundulidae
Caryophyllaceae
Bayes Theorem
Microsatellite Repeats
Mutation
Algorithms
Models, Biological
Computer Simulation
Female
Male
Biological Evolution
Self-Fertilization
Data Accuracy
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https://hdl.handle.net/10161/21887Published Version (Please cite this version)
10.1534/genetics.115.179093Publication Info
Redelings, Benjamin D; Kumagai, Seiji; Tatarenkov, Andrey; Wang, Liuyang; Sakai, Ann
K; Weller, Stephen G; ... Uyenoyama, Marcy K (2015). A Bayesian Approach to Inferring Rates of Selfing and Locus-Specific Mutation. Genetics, 201(3). pp. 1171-1188. 10.1534/genetics.115.179093. Retrieved from https://hdl.handle.net/10161/21887.This is constructed from limited available data and may be imprecise. To cite this
article, please review & use the official citation provided by the journal.
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Show full item recordScholars@Duke
Marcy K. Uyenoyama
Professor of Biology
Marcy Uyenoyama studies mechanisms of evolutionary change at the molecular and population
levels. Among the questions under study include the prediction and detection of the
effects of natural selection on genomic structure. A major area of research addresses
the development of maximum-likelihood and Bayesian methods for inferring evolutionary
processes from the pattern of molecular variation. Evolutionary processes currently
under study include characterization of population structure acr
Liuyang Wang
Assistant Research Professor of Molecular Genetics and Microbiology
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