Journal
JOURNAL OF DAIRY SCIENCE
Volume 102, Issue 2, Pages 1341-1353Publisher
ELSEVIER SCIENCE INC
DOI: 10.3168/jds.2018-15038
Keywords
dairy cattle; fertility; genetic parameters; producer-recorded data; single-step genome-wide association study (GWAS)
Funding
- Agriculture and Agri-Food Canada (Guelph, ON, Canada)
- Dairy Farmers of Canada (Ottawa, ON, Canada)
- Canadian Dairy Network (Guelph, ON, Canada)
- Canadian Dairy Commission (Ottawa, ON, Canada) under the Agri-Science Clusters Initiative
- CAPES (Brazilian Federal Agency for Support and Evaluation of Graduate Education, Brazil)
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In Canada, reproductive disorders known to affect the profitability of dairy cattle herds have been recorded by producers on a voluntary basis since 2007. Previous studies have shown the feasibility of using producer-recorded health data for genetic evaluations. Despite low heritability estimates and limited availability of phenotypic information, sufficient genetic variation has been observed for those traits to indicate that genetic progress, although slow, can be achieved. Pedigree- and genomic-based analyses were performed on producer-recorded health data of reproductive disorders, including retained placenta (RETP), metritis (METR), and cystic ovaries (CYST) using traditional BLUP and single-step genomic BLUP. Genome-wide association studies and functional analyses were carried out to unravel significant genomic regions and biological pathways, and to better understand the genetic mechanisms underlying RETP, METR, and CYST. Heritability estimates (posterior standard deviation in parentheses) were 0.02 (0.003), 0.01 (0.004), and 0.02 (0.003) for CYST, METR, and RETP, respectively. A moderate to strong genetic correlation of 0.69 (0.102) was found between METR and RETP. Averaged over all traits, sire proof reliabilities increased by approximately 11 percentage points with the incorporation of genomic data using a multiple-trait linear model. Biological pathways and associated genes underlying the studied traits were identified and will contribute to a better understanding of the biology of these 3 health disorders in dairy cattle.
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