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https://hdl.handle.net/1959.11/30771
Title: | Small SNP panels for breed proportion estimation in Indian crossbred dairy cattle |
Contributor(s): | Strucken, Eva M (author) ; Swaminathan, Marimuthu (author); Gibson, John P (author) |
Publication Date: | 2021-11 |
Early Online Version: | 2021-03-09 |
Open Access: | Yes |
DOI: | 10.1111/jbg.12544 |
Handle Link: | https://hdl.handle.net/1959.11/30771 |
Abstract: | | Reliably identifying breed proportions in crossbred cattle in smallholder farms is a crucial step to improve mating decisions and optimizing management in these systems. High-density genotype information is able to estimate higher-order breed proportions accurately, but, are too expensive for mass application in smallholder systems. We used high-density genotype information (777 k SNPs) of 623 crossbred cattle from India that had Holstein-Friesian (HFX) and/or Jersey and indigenous breeds in their ancestry to select a smaller number of SNPs for breed proportion estimation. The accuracy of estimates obtained from panels with 100-500 SNP was compared to estimates based on all SNPs. Panels were selected for highest absolute allele frequency difference between exotic dairy versus indigenous Bos indicus, or between HFX versus Jersey breeds. A step-wise pruning approach was developed showing that and increased physical distances between markers of 8.5 Mb improved breed proportion estimation compared to a standard 1 Mb distance. A panel of 500 SNPs optimized to estimate HFX versus Jersey versus indicine ancestry was able to estimate indicine breed proportions with r2 = .991, HFX proportions with r2 = .979 and Jersey proportions with r2 = .949. The number of markers was a deciding factor in estimation accuracy, together with the distribution of markers across the genome.
Publication Type: | Journal Article |
Source of Publication: | Journal of Animal Breeding and Genetics, 138(6), p. 698-707 |
Publisher: | Wiley-Blackwell Verlag GmbH |
Place of Publication: | Germany |
ISSN: | 1439-0388 0931-2668 |
Fields of Research (FoR) 2020: | 300305 Animal reproduction and breeding |
Socio-Economic Objective (SEO) 2020: | 100402 Dairy cattle |
Peer Reviewed: | Yes |
HERDC Category Description: | C1 Refereed Article in a Scholarly Journal |
Appears in Collections: | Journal Article School of Environmental and Rural Science
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