A multivalent three-point linkage analysis model of autotetraploids

Yafei Lu, Xiaoxia Yang, Chunfa Tong, Xin Li, Sisi Feng, Zhong Wang, Xiaoming Pang, Yaqun Wang, Ningtao Wang, Christian M. Tobias, Rongling Wu

Research output: Contribution to journalArticlepeer-review

8 Scopus citations

Abstract

Because of its widespread occurrence and role in shaping evolutionary processes in the biological kingdom, especially in plants, polyploidy has been increasingly studied from cytological to molecular levels. By inferring gene order, gene distances and gene homology, linkage mapping with molecular markers has proven powerful for investigating genome structure and organization. Here we review and assess a general statistical model for three-point linkage analysis in autotetraploids by integrating double reduction, a phenomenon that commonly occurs in autopolyploids whose chromosomes are derived from a single ancestral species. This model does not require any assumption on the distribution of the occurrence of double reduction and can handle the complexity of multilocus linkage in terms of crossover interference. Implemented with the expectation-maximization (EM) algorithms, the model can estimate and test the recombination fractions between less informative dominant markers, thus facilitating its practical implications for any autopolyploids in most of which inexpensive dominant markers are still used for their genetic and evolutionary studies. The model was applied to reanalyze a published data in tetraploid switchgrass, validating its practical usefulness and utilization.

Original languageEnglish (US)
Article numberbbs051
Pages (from-to)460-468
Number of pages9
JournalBriefings in bioinformatics
Volume14
Issue number4
DOIs
StatePublished - Jul 2013

All Science Journal Classification (ASJC) codes

  • Information Systems
  • Molecular Biology

Fingerprint Dive into the research topics of 'A multivalent three-point linkage analysis model of autotetraploids'. Together they form a unique fingerprint.

Cite this