Exploring genomic approaches to fast-track genetic gains in breechstrike resistance in Merino sheep
S. Dominik
A D , A. Reverter B , L. R. Porto-Neto B , J. C. Greeff C and J. L. Smith A
A CSIRO Agriculture and Food, FD McMasters Laboratories, 9308 New England Highway, Armidale, NSW 2350, Australia.
B CSIRO Agriculture and Food, Queensland Bioprecinct, 306 Carmody Road, St Lucia, Qld 4067, Australia.
C Department of Primary Industries and Regional Development, 3 Baron-Hay Court, South Perth, WA 6151, Australia.
D Corresponding author. Email: Sonja.dominik@csiro.au
Animal Production Science - https://doi.org/10.1071/AN21124
Submitted: 5 March 2021 Accepted: 9 July 2021 Published online: 30 August 2021
Journal Compilation © CSIRO 2021 Open Access CC BY-NC-ND
Abstract
Context: Breech flystrike is a costly trait to measure. Industry investment into genetic solutions for breech flystrike has resulted in the availability of estimated breeding values for indicator traits, such as breech wrinkle, breech cover and dag. However, selection is based on indicator traits rather than breech flystrike itself, and genetic gains could be enhanced through genomic selection approaches.
Aim: This study investigated whether genomic approaches based on major genes, such as marker-assisted selection, or genomic selection based on genomic breeding values, would be the most efficient application of genomic information to enhance genetic gains for breech flystrike resistance.
Methods: The analysis comprised 1535 sheep of the Merino Breeding for Breech Flystrike Resistance Resource flocks from New South Wales and Western Australia with high density genotypes (actual and imputed). A genome-wide association study was conducted on breech flystrike and its indicator traits, namely, breech wrinkle, dag and breech cover. The study also estimated genomic breeding values and their accuracy.
Key results: The SNP associations found in this study did not point to the existence of few genes with major effects on breech flystrike resistance or its indicator traits. Throughout the genome, associations of small effect were found, which enabled the estimation of genomic breeding values. However, these were of low accuracy, as expected for the size of the dataset.
Conclusion: Genomic prediction of breeding values for breech flystrike resistance is a feasible tool for applying genomic technology in the Merino industry.
Implications: A reference population of appropriate size needs to be established for this difficult-to-measure trait, and a dispersed reference population could be an effective option.
Keywords: flystrike, Merino sheep, mulesing, genomic selection.
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