Assessment of accuracy of genomic prediction for French Lacaune dairy sheep

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Abstract

Genomic selection in Lacaune dairy sheep was investigated based on genotypes from the OvineSNP50 BeadChip (Illumina Inc., San Diego, CA). Historical artificial insemination progeny-tested rams formed a population of 2,892 genotyped rams. Additional ungenotyped rams and females were included by single-step genomic BLUP (ssGBLUP). Three prediction strategies were tried: pseudo-BLUP (using all rams and daughter yield deviations), pseudo-ssGBLUP (using all rams and daughter yield deviations), and regular ssGBLUP (using all phenotypes and pedigree in an animal model). The population linkage disequilibrium was determined, with an average squared correlation coefficient of 0.11 for markers closer than 0.1. cM (lower than in dairy cattle). The estimated effective population is 370 individuals. Gain in accuracy of genomic selection over parent averages ranged from 0.10 to 0.20. Highest accuracies and lowest bias were found using regular ssGBLUP. Transition to a genomic breeding scheme is possible but costs need to be carefully evaluated. © 2014 American Dairy Science Association.

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APA

Baloche, G., Legarra, A., Sallé, G., Larroque, H., Astruc, J. M., Robert-Granié, C., & Barillet, F. (2014). Assessment of accuracy of genomic prediction for French Lacaune dairy sheep. Journal of Dairy Science, 97(2), 1107–1116. https://doi.org/10.3168/jds.2013-7135

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