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Genetics, Vol. 159, 1339-1350, November 2001, Copyright © 2001

A Multivalent Pairing Model of Linkage Analysis in Autotetraploids

Samuel S. Wua, Rongling Wua, Chang-Xing Maa,b, Zhao-Bang Zengc, Mark C. K. Yanga, and George Casellaa
a Department of Statistics, University of Florida, Gainesville, Florida 32611,
b Department of Statistics, Nankai University, Tianjin 300071, People's Republic of China
c Department of Statistics, North Carolina State University, Raleigh, North Carolina 27695

Corresponding author: Samuel S. Wu, Division of Biostatistics, P. O. Box 100212, University of Florida, Gainesville, FL 32610., samwu{at}biostat.ufl.edu (E-mail)

Communicating editor: J. B. WALSH

Polyploidy has been recognized as an important step in the evolutionary diversification of flowering plants and may have a significant impact on plant breeding. Statistical analyses for linkage mapping in polyploid species can be difficult due to considerable complexities in polysomic inheritance. In this article, we develop a novel statistical method for linkage analysis of polymorphic markers in a full-sib family of autotetraploids. This method is established on multivalent pairings of homologous chromosomes at meiosis and can provide a simultaneous maximum-likelihood estimation of the double reduction frequencies of and recombination fraction between two markers. The EM algorithm is implemented to provide a tractable way for estimating relative proportions of different modes of gamete formation that generate identical gamete genotypes due to multivalent pairings. Extensive simulation studies were performed to demonstrate the statistical properties of this method. The implications of the new method for understanding the genome structure and organization of polyploid species are discussed.





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