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Inference of individual ploidy level using codominant markers
Author(s) -
Huang Kang,
Dunn Derek W.,
Li Zhonghu,
Zhang Pei,
Dai Yu,
Li Baoguo
Publication year - 2019
Publication title -
molecular ecology resources
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.96
H-Index - 136
eISSN - 1755-0998
pISSN - 1755-098X
DOI - 10.1111/1755-0998.13032
Subject(s) - biology , ploidy , allele , genetics , genotyping , genotype , chromosome , polyploid , null allele , inference , evolutionary biology , gene , artificial intelligence , computer science
A significant portion of plant species are polyploids, with ploidy levels sometimes varying among individuals and/or populations. Current techniques to determine the individual ploidy, e.g., flow cytometry, chromosome counting or genotyping-by-sequencing, are often cumbersome. Based on the genotypic probabilities for polysomic inheritance under double-reduction, we developed a model to estimate allele frequency and infer the ploidy status of individuals from the allelic phenotypes of codominant genetic markers. The allele frequencies are estimated by an expectation-maximization algorithm in the presence of null alleles, false alleles, negative amplifications and self-fertilization, and the posterior probabilities are used to assign individuals into different levels of ploidy. The accuracy of this method under different conditions is evaluated. Our methods are freely available in a new software package, ploidyinfer, for use by other researchers which can be downloaded from http://github.com/huangkang1987/ploidyinfer.