We presented a deletion genotyping (copy-number estimation) method that leverages population-scale whole genome sequence variants data from 1K bull genomes project (1KBGP) to build reference panel for imputation. To estimate deletion-genotype likelihood, we extracted read-depth (RD) data of all the bi-allelic variants within a given deletion locus, and fitted a Gaussian mixture model to the observed RD. We validated our method on brachyspina associated deletion of chromosome 21 (Chr21:21,184,869-21,188,202), which was segregating in our deletion-discovery population of Holstein cattle. We analysed the RD data of 55 progeny tested Holstein bulls with published recessive code for brachyspina (8 carriers and 47 non-carriers) along with 5 carriers from the discovery population (confirmed by assembling the breakpoint sequences). Using our approach we were able to genotype the carriers and non-carriers with 95% accuracy, and a false discovery rate of 18.8%. Keywords: read-depth genotyping, Gaussian mixture model, deletion, copy number variation, dairy cattle

Md Mesbah-Uddin, Bernt Guldbrandtsen, Mogens Sandø Lund, Goutam Sahana

Proceedings of the World Congress on Genetics Applied to Livestock Production, Volume Electronic Poster Session - Molecular Genetics 3, , 662, 2018
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