|Yang, Xiaoxia -|
|Lu, Yafei -|
|Pang, Xiaoming -|
|Tong, Chunfa -|
|Wang, Zhong -|
|Li, Xin -|
|Feng, Sisi -|
|Wu, Rongling -|
Submitted to: Briefings in Bioinformatics
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: February 20, 2012
Publication Date: April 12, 2012
Citation: Yang, X., Lu, Y., Pang, X., Tong, C., Wang, Z., Li, X., Feng, S., Tobias, C.M., Wu, R. 2012. A unifying framework for bivalent multilocus linkage analysis of allotetraploids. Briefings in Bioinformatics. 14:96-108. Interpretive Summary: We describe and assess a theoretical algorithmic framework for linkage analysis in allopolyploids. The framework integrates the preferential pairing factor, a parameter defined to describe chromosomal pairing in allopolyploids, into a multilocus linkage analysis model, allowing the simultaneous estimation of the linkage, genetic interference and chromosome pairing behavior. This is an improvement over existing techniques for map construction in polyploids that do not take into consideration the complexities of genetic interference and potential genetic exchange through infrequent recombination between independent subgenomes.
Technical Abstract: Allotetraploids are polyploids with chromosomes derived from different diploid species, that undergo meiotic behavior that is qualitatively different from the diploids. According to a traditional view, meiotic pairing occurs only between homologous chromosomes, but new evidence indicates that homoeologous chromosomes may also pair to a lesser extent compared with homolog pairing. Here, we describe and assess a unifying analytical framework that incorporates differential chromosomal pairing into a multilocus linkage model. The preferential pairing factor is used to quantify the probability difference of pairing occurring between homologous chromosomes and between homoeologous chromosomes. The unifying framework allows simultaneous estimation of the linkage, genetic interference, and preferential pairing factor using commonly existing multiplex markers. We compared the unifying approach and traditional approaches assuming random chromosomal pairing by analyzing marker data collected in a full-sib family of tetraploid switchgrass, a bioenergy species whose diploid origins are undefined, but with subgenomes that are genetically well differentiated. The unifying framework provides a better tool for estimating the meiotic linkage and constructing a genetic map for allotetraploids.