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Originally published as Genetics Published Articles Ahead of Print on March 31, 2005.

Genetics, Vol. 170, 899-907, June 2005, Copyright © 2005
doi:10.1534/genetics.104.035816

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A General Framework for Statistical Linkage Analysis in Multivalent Tetraploids

Rongling Wu1 and Chang-Xing Ma

Department of Statistics, University of Florida, Gainesville, Florida 32611

1 Corresponding author: Department of Statistics, 533 McCarty Hall C, University of Florida, Gainesville, FL 32611.
E-mail: rwu{at}stat.ufl.edu

In multivalent polyploids, simultaneous pairings among homologous chromosomes at meiosis result in a unique cytological phenomenon—double reduction. Double reduction casts an impact on chromosome evolution in higher plants, but because of its confounded effect on the pattern of gene cosegregation, it complicates linkage analysis and map construction with polymorphic molecular markers. In this article, we have proposed a general statistical model for simultaneously estimating the frequencies of double reduction, the recombination fraction, and optimal parental linkage phases between any types of markers, both fully and partially informative, or dominant and codominant, for a tetraploid species that undergoes only multivalent pairing. This model provides an in-depth extension of our earlier linkage model that was built upon Fisher's classifications for different gamete formation modes during the polysomic inheritance of a multivalent polyploid. By implementing a two-stage hierarchical EM algorithm, we derived a closed-form solution for estimating the frequencies of double reduction through the estimation of gamete mode frequencies and the recombination fraction. We performed different settings of simulation studies to demonstrate the statistical properties of our model for estimating and testing double reduction and the linkage in multivalent tetraploids. As shown by a comparative analysis, our model provides a general framework that covers existing statistical approaches for linkage mapping in polyploids that are predominantly multivalent. The model will have great implications for understanding the genome structure and organization of polyploid species.




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Z. W. Luo and Z. Zhang
Commentary on Wu and Ma
Genetics, December 1, 2005; 171(4): 2149 - 2150.
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