Resolving microsatellite genotype ambiguity in populations of allopolyploid and diploidized autopolyploid organisms using negative correlations between allelic variables

Clark, Lindsay V.; Schreier, Andrea Drauch

doi:10.1111/1755-0998.12639

Title: Resolving microsatellite genotype ambiguity in populations of allopolyploid and diploidized autopolyploid organisms using negative correlations between allelic variables

Journal Article · Thu Jan 05 00:00:00 EST 2017 · Molecular Ecology Resources

DOI:https://doi.org/10.1111/1755-0998.12639· OSTI ID:1399593

Clark, Lindsay V. ^[1]; Schreier, Andrea Drauch ^[2]

Department of Crop Sciences University of Illinois, Urbana‐Champaign 1201 W. Gregory Drive Urbana IL 61801 USA
Department of Animal Science University of California – Davis Davis CA 95616 USA

Abstract A major limitation in the analysis of genetic marker data from polyploid organisms is non‐Mendelian segregation, particularly when a single marker yields allelic signals from multiple, independently segregating loci (isoloci). However, with markers such as microsatellites that detect more than two alleles, it is sometimes possible to deduce which alleles belong to which isoloci. Here, we describe a novel mathematical property of codominant marker data when it is recoded as binary (presence/absence) allelic variables: under random mating in an infinite population, two allelic variables will be negatively correlated if they belong to the same locus, but uncorrelated if they belong to different loci. We present an algorithm to take advantage of this mathematical property, sorting alleles into isoloci based on correlations, then refining the allele assignments after checking for consistency with individual genotypes. We demonstrate the utility of our method on simulated data, as well as a real microsatellite data set from a natural population of octoploid white sturgeon ( Acipenser transmontanus ). Our methodology is implemented in the R package polysat version 1.6.

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Sponsoring Organization:: USDOE

Grant/Contract Number:: DE‐SC0012379

OSTI ID:: 1399593

Journal Information:: Molecular Ecology Resources, Journal Name: Molecular Ecology Resources Vol. 17 Journal Issue: 5; ISSN 1755-098X

Publisher:: Wiley-BlackwellCopyright Statement

Country of Publication:: United Kingdom

Language:: English

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Cited by: 24 works

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References (18)

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