Multilocus tetrasomic linkage analysis using hidden Markov chain model

Lindsey Leach, L Wang, Michael Kearsey, Zewei Luo

Research output: Contribution to journalArticle

12 Citations (Scopus)

Abstract

The availability of reliable genetic linkage maps is crucial for functional and evolutionary genomic analyses. Established theory and methods of genetic linkage analysis have made map construction a routine exercise in diploids. However, many evolutionarily, ecologically, and/or agronomically important species are autopolyploids, with autotetraploidy being a typical example. These species undergo much more complicated chromosomal segregation and recombination at meiosis than diploids. In addition, there is evidence of polyploidy-induced and highly dynamic changes in the structure of the genome. These polysomic characteristics indicate the inappropriateness of the theory and methods of linkage analysis in diploids for use in these species and a gap in the theory and methodology of tetraploid map construction. This paper presents a theoretical model and statistical framework for multilocus linkage analysis in autotetraploids for use with dominant and/or codominant DNA molecular markers. The theory and methods incorporate the essential features of allele segregation and recombination under tetrasomic inheritance and the major challenges in statistical modeling and marker data analysis. We validated the method and explored its statistical properties by intensive simulation study and demonstrated its utility by analysis of AFLP and SSR marker data from an outbred autotetraploid potato population.
Original languageEnglish
Pages (from-to)4270-4274
Number of pages5
JournalNational Academy of Sciences. Proceedings
Volume107
Issue number9
DOIs
Publication statusPublished - 2 Mar 2010

Fingerprint

Dive into the research topics of 'Multilocus tetrasomic linkage analysis using hidden Markov chain model'. Together they form a unique fingerprint.

Cite this