Joining genetic linkage maps using a joint likelihood function

TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik
Xin-Sheng HuKermit Ritland

Abstract

We present an efficient method to join genetic maps derived from different crosses, which is especially appropriate for dominant markers. In contrast to the "JoinMap" algorithm, which estimates information about recombination in a given cross from the LOD values and then combines estimates among crosses assuming a binomial sampling distribution, we construct a joint likelihood function that combines information across all crosses, to obtain a joint estimate of recombination. Simulations indicated that the difference between these two approaches is small when codominant markers are used, but that the joint likelihood approach shows substantially improved estimates when dominant or a mixture of dominant and codominant markers are used. This is because the joint likelihood implicitly finds the optimal weights among different classes of data, while the former method does not accurately predict the information from crosses involving dominant markers. Application of our method is illustrated by the construction of a linkage map for Linanthus using both backcrosses and the F2 of a cross between Linanthus jepsonii and L. bicolor, assayed with amplified fragment length polymorphisms (AFLP).

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Citations

May 26, 2011·TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik·Jixiang WuXiang-Yang Lou
Jan 12, 2013·TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik·Woo Kyu LeeSoon-Chun Jeong
Dec 15, 2010·Genetics Research·Xin-Sheng Hu, Zhiquan Wang
Apr 25, 2013·Heredity·C Chen, K Ritland
Aug 12, 2005·Genome Génome / Conseil National De Recherches Canada·M PekkinenM J Sillanpää

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