A Bayesian Approach to Inferring Rates of Selfing and Locus-Specific Mutation.

dc.contributor.author

Redelings, Benjamin D

dc.contributor.author

Kumagai, Seiji

dc.contributor.author

Tatarenkov, Andrey

dc.contributor.author

Wang, Liuyang

dc.contributor.author

Sakai, Ann K

dc.contributor.author

Weller, Stephen G

dc.contributor.author

Culley, Theresa M

dc.contributor.author

Avise, John C

dc.contributor.author

Uyenoyama, Marcy K

dc.date.accessioned

2020-12-08T20:40:24Z

dc.date.available

2020-12-08T20:40:24Z

dc.date.issued

2015-11

dc.date.updated

2020-12-08T20:40:21Z

dc.description.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.

dc.identifier

genetics.115.179093

dc.identifier.issn

0016-6731

dc.identifier.issn

1943-2631

dc.identifier.uri

https://hdl.handle.net/10161/21887

dc.language

eng

dc.publisher

Oxford University Press (OUP)

dc.relation.ispartof

Genetics

dc.relation.isversionof

10.1534/genetics.115.179093

dc.subject

Animals

dc.subject

Fundulidae

dc.subject

Caryophyllaceae

dc.subject

Bayes Theorem

dc.subject

Microsatellite Repeats

dc.subject

Mutation

dc.subject

Algorithms

dc.subject

Models, Biological

dc.subject

Computer Simulation

dc.subject

Female

dc.subject

Male

dc.subject

Biological Evolution

dc.subject

Self-Fertilization

dc.subject

Data Accuracy

dc.title

A Bayesian Approach to Inferring Rates of Selfing and Locus-Specific Mutation.

dc.type

Journal article

duke.contributor.orcid

Wang, Liuyang|0000-0001-9556-2361

duke.contributor.orcid

Uyenoyama, Marcy K|0000-0001-8249-1103

pubs.begin-page

1171

pubs.end-page

1188

pubs.issue

3

pubs.organisational-group

Trinity College of Arts & Sciences

pubs.organisational-group

Biology

pubs.organisational-group

Duke

pubs.organisational-group

School of Medicine

pubs.organisational-group

Molecular Genetics and Microbiology

pubs.organisational-group

Basic Science Departments

pubs.publication-status

Published

pubs.volume

201

Files

Original bundle

Now showing 1 - 1 of 1
Loading...
Thumbnail Image
Name:
redelingsKumagaiTatarenkovUyenoyama2015.pdf
Size:
1.75 MB
Format:
Adobe Portable Document Format