Statistical models for genetic mapping in polyploids: Challenges and opportunities

Jiahan Li, Kiranmoy Das, Jingyuan Liu, Guifang Fu, Yao Li, Christian Tobias, Rongling Wu

Research output: Chapter in Book/Report/Conference proceedingChapter

7 Scopus citations

Abstract

Statistical methods for genetic mapping have well been developed for diploid species but are lagging in the more complex polyploids. The genetic mapping of polyploids, where genome number is higher than two, is complicated by uncertainty about the genotype-phenotype correspondence, inconsistent meiotic mechanisms, heterozygous genome structures, and increased allelic (action) and nonallelic (interaction) combinations. According to their meiotic configurations, polyploids can be classified as bivalent polyploids, in which only two chromosomes pair during meiosis at a time, and multivalent polyploids, where multiple chromosomes pair simultaneously. For some polyploids, these two types of pairing occur at the same time, leading to a mixed category. This chapter reviews several challenges due to the complexities of linkage analysis in polyploids and describes statistical models and algorithms that have been developed for linkage mapping based on their distinct meiotic characteristics. We discuss several issues that should be addressed to better understand the genome structure and organization of polyploids and the genetic architecture of complex traits for this unique group of plants.

Original languageEnglish (US)
Title of host publicationQuantitative Trait Loci (QTL)
Subtitle of host publicationMethods and Protocols
PublisherHumana Press Inc.
Pages245-261
Number of pages17
ISBN (Print)9781617797842
DOIs
StatePublished - Jan 1 2012

Publication series

NameMethods in Molecular Biology
Volume871
ISSN (Print)1064-3745

All Science Journal Classification (ASJC) codes

  • Molecular Biology
  • Genetics

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