A statisticalmodel for QTL mapping in polysomic autotetraploids underlying double reduction

Fang Xu, Yafei Lyu, Chunfa Tong, Weimiao Wu, Xuli Zhu, Danni Yin, Qin Yan, Jian Zhang, Xiaoming Pang, Christian M. Tobias, Rongling Wu

Research output: Contribution to journalArticlepeer-review

9 Scopus citations


As a group of economically important species, linkage mapping of polysomic autotetraploids, including potato, sugarcane and rose, is difficult to conduct due to their unique meiotic property of double reduction that allows sister chromatids to enter into the same gamete. We describe and assess a statisticalmodel for mapping quantitative trait loci (QTLs) in polysomic autotetraploids. The model incorporates double reduction, built in the mixture model-based framework and implemented with the expectation-maximization algorithm. It allows the simultaneous estimation of QTL positions, QTL effects and the degree of double reduction as well as the assessment of the estimation precision of these parameters. We performed computer simulation to examine the statistical properties of the method and validate its use through analyzing real data in tetraploid switchgrass.

Original languageEnglish (US)
Pages (from-to)1044-1056
Number of pages13
JournalBriefings in bioinformatics
Issue number6
StatePublished - Aug 2 2013

All Science Journal Classification (ASJC) codes

  • Information Systems
  • Molecular Biology


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