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- Title
Haplotype reconstruction in connected tetraploid F1 populations.
- Authors
Chaozhi Zheng; Amadeu, Rodrigo R.; Munoz, Patricio R.; Endelman, Jeffrey B.
- Abstract
In diploid species, many multiparental populations have been developed to increase genetic diversity and quantitative trait loci (QTL) mapping resolution. In these populations, haplotype reconstruction has been used as a standard practice to increase the power of QTL detection in comparison with the marker-based association analysis. However, such software tools for polyploid species are few and limited to a single biparental F1 population. In this study, a statistical framework for haplotype reconstruction has been developed and implemented in the software PolyOrigin for connected tetraploid F1 populations with shared parents, regardless of the number of parents or mating design. Given a genetic or physical map of markers, PolyOrigin first phases parental genotypes, then refines the input marker map, and finally reconstructs offspring haplotypes. PolyOrigin can utilize single nucleotide polymorphism (SNP) data coming from arrays or from sequencebased genotyping; in the latter case, bi-allelic read counts can be used (and are preferred) as input data to minimize the influence of genotype calling errors at low depth. With extensive simulation we show that PolyOrigin is robust to the errors in the input genotypic data and marker map. It works well for various population designs with ≥ 30 offspring per parent and for sequences with read depth as low as 10x. PolyOrigin was further evaluated using an autotetraploid potato dataset with a 3×3 half-diallel mating design. In conclusion, PolyOrigin opens up exciting new possibilities for haplotype analysis in tetraploid breeding populations.
- Subjects
COMPUTER software; COMPUTER simulation; SEQUENCE analysis; SINGLE nucleotide polymorphisms; ALLELES; HAPLOTYPES; CHROMOSOME abnormalities; GENETIC markers; GENOTYPES; GENOMES; GENETIC techniques; STATISTICAL models; ALGORITHMS
- Publication
Genetics, 2021, Vol 219, Issue 2, p1
- ISSN
0016-6731
- Publication type
Article
- DOI
10.1093/genetics/iyab106