A mechanistic model of linkage analysis in allohexaploids

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This paper presents a computational framework to model linkage analysis in allohexaploids by incorporating preferential chromosomal pairing into a mixture model, estimating pairing factors and recombination fractions from simulated and real data.

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Abstract

Despite their pivotal role in agriculture and biological research, polyploids, a group of organisms with more than two sets of chromosomes, are very difficult to study. Increasing studies have used high-density genetic linkage maps to investigate the genome structure and function of polyploids and to identify genes underlying polyploid traits. However, although models for linkage analysis have been well established for diploids, with some essential modifications for tetraploids, no models have been available thus far for polyploids at higher ploidy levels. The linkage analysis of polyploids typically requires knowledge about their meiotic mechanisms, depending on the origin of polyplody. Here we describe a computational modeling framework for linkage analysis in allohexaploids by integrating their preferential chromosomal-pairing meiotic feature into a mixture model setting. The framework, implemented with the EM algorithm, allows the simultaneous estimates of preferential pairing factors and the recombination fraction. We investigated statistical properties of the framework through extensive computer simulation and validated its usefulness and utility by analyzing a real data from a full-sib family of allohexaploid persimmon. Our attempt in linkage analysis of allohexaploids by incorporating their meiotic mechanism lays a foundation for allohexaploid genetic mapping and also provides a new horizon to explore allohexaploid parental kinship.

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