A unified framework for mapping quantitative trait loci in bivalent tetraploids using single-dose restriction fragments: a case study from alfalfa.
The development of statistical methodologies for quantitative trait locus (QTL) mapping in polyploids is complicated by complex polysomic inheritance. In this article, we propose a statistical method for mapping QTL in tetraploids undergoing bivalent formation at meiosis by using single-dose restriction fragments. Our method is based on a unified framework, one that uses chromosome bivalent pairing configuration and gametic recombination to discern different mechanisms of gamete formation. Our bivalent polyploid model can not only provide a simultaneous estimation of the linkage and chromosome pairing configuration-a cytological parameter of evolutionary and systematic interest-but also enhances the precision of estimating QTL effects and position by correctly characterizing gene segregation during polyploid meiosis. By using our method and a linkage map constructed in a previous study, we successfully identify several QTL affecting winter hardiness in bivalent tetraploid alfalfa. Moreover, our results reveal significant preferential chromosome pairing at meiosis in an F1 hybrid population, which indicates the importance of reassessing the traditional view of random chromosome segregation in alfalfa.
Ma
Chang-Xing
CX
Department of Statistics, University of Florida, Gainesville, Florida 32611, USA.
Casella
George
G
Shen
Zuo-Jun
ZJ
Osborn
Thomas C
TC
Wu
Rongling
R
D023902:Chromosome Pairing / Q000235:genetics; D020090:Chromosome Segregation / Q000235:genetics; D019295:Computational Biology / Q000379:methods; D003198:Computer Simulation; D005819:Genetic Markers / Q000235:genetics; D000455:Medicago sativa / Q000235:genetics*; D008540:Meiosis / Q000235:genetics; D008957:Models, Genetic; D015233:Models, Statistical; D012150:Polymorphism, Restriction Fragment Length; D011123:Polyploidy; D040641:Quantitative Trait Loci / Q000235:genetics*; D015183:Restriction Mapping / Q000379:methods* / Q000706:statistics & numerical data*
D005819:Genetic Markers