Journal article

Improving Genomic Prediction of Crossbred and Purebred Dairy Cattle

M Khansefid, ME Goddard, M Haile-Mariam, KV Konstantinov, C Schrooten, G de Jong, EG Jewell, E O’Connor, JE Pryce, HD Daetwyler, IM MacLeod

Frontiers in Genetics | Published : 2020

Open access

Abstract

This study assessed the accuracy and bias of genomic prediction (GP) in purebred Holstein (H) and Jersey (J) as well as crossbred (H and J) validation cows using different reference sets and prediction strategies. The reference sets were made up of different combinations of 36,695 H and J purebreds and crossbreds. Additionally, the effect of using different sets of marker genotypes on GP was studied (conventional panel: 50k, custom panel enriched with, or close to, causal mutations: XT_50k, and conventional high-density with a limited custom set: pruned HDnGBS). We also compared the use of genomic best linear unbiased prediction (GBLUP) and Bayesian (emBayesR) models, and the traits tested w..

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University of Melbourne Researchers

Grants

Funding Acknowledgements

We acknowledge the financial support from CRV and DairyBio. DairyBio is a joint venture of Dairy Australia, The Gardiner Foundation, and Agriculture Victoria (Melbourne, Australia).