PolyOrigin: Haplotype Reconstruction in Tetraploid Multiparent Populations
By Chaozhi Zheng, Wageningen, The Netherlands
Biography: Chaozhi Zheng is a researcher at the Biometris group at the Wageningen University and Research. Zheng obtained his Ph.D. in statistical ecology from the University of Helsinki in 2009. He was a postdoctoral researcher in statistical genetics at the University of Washington, Seattle from 2010 to 2012. He nurtures a keen interest in developing statistical and computational methods for biological data analysis. At the Biometris group since 2013, he has been working on the methodological development for genetic analysis in diploid and polyploid multiparental populations.
Many diploid multiparent populations have been developed to increase genetic diversity and quantitative trait loci (QTL) mapping resolution. Haplotype reconstruction for these populations has been used to increase QTL detection power compared to genetic analysis with the marker alleles per se. To realize similar benefits in autotetraploids (and eventually higher ploidies), a statistical framework for haplotype reconstruction in autotetraploid multiparent populations has been developed and implemented in the software PolyOrigin. Haplotype reconstruction proceeds in two steps: first, parental genotypes are phased; second, genotype probabilities for the parental alleles are inferred in the progeny. PolyOrigin can utilize genetic marker data from SNP arrays or from sequence-based genotyping; in the latter case, bi-allelic read counts can be used (and are preferred) as input data to minimize the influence of genotype call errors at low depth. To account for errors in the input map, PolyOrigin includes functionality for filtering markers, inferring inter-marker distances, and refining local marker ordering. Simulation studies were used to investigate the effect of several variables—including the mating design, number of parents, population size, and sequencing depth—on the accuracy of haplotype reconstruction. We further evaluated PolyOrigin using an autotetraploid potato dataset with a 3×3 half-diallel mating design.
