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ARS Home » Northeast Area » Beltsville, Maryland (BARC) » Beltsville Agricultural Research Center » Animal Genomics and Improvement Laboratory » Research » Publications at this Location » Publication #327369

Research Project: Improving Genetic Predictions in Dairy Animals Using Phenotypic and Genomic Information

Location: Animal Genomics and Improvement Laboratory

Title: Genomic analysis of lactation persistency in four breeds of dairy cattle

Author
item Cole, John
item Null, Daniel
item Parker Gaddis, Kristen - University Of Florida

Submitted to: Journal of Dairy Science
Publication Type: Abstract Only
Publication Acceptance Date: 4/21/2016
Publication Date: 7/9/2016
Citation: Cole, J.B., Null, D.J., Parker Gaddis, K.L. 2016. Genomic analysis of lactation persistency in four breeds of dairy cattle. Journal of Dairy Science. 99(E-Suppl. 1)/Journal of Animal Science. 94(E-Suppl. 5):156(abstr. 0333).

Interpretive Summary:

Technical Abstract: The objectives of this study were to determine gains in reliability from the addition of genomic information to genetic evaluations for best predictions of lactation persistency in US Ayrshire (AY), Brown Swiss (BS), Holstein (HO), and Jersey (JE) cattle, and to identify genomic regions with large effects on those traits. Data consisted of lactations initiated by calvings on or after January 1, 1997, stored in the national dairy database (NDDB) at the Council on Dairy Cattle Breeding (Bowie, MD). Persistencies were computed by multiple-trait best prediction for milk (PM), fat (PF), and protein (PP) yields. Genetic analyses were conducted on a within-breed basis using identical repeatability animal models and breed-specific (co)variance components. Traditional and genomic PTA and reliabilities were computed by GBLUP using the national genomic evaluation system. Gain in reliability from the addition of genomic information was calculated as the difference between the realized genomic reliability and the reliability of traditional PA using a cutoff study. Predictor populations consisted of animals with traditional genetic evaluations in April 2014, and validation sets included animals with traditional genetic evaluations in August 2009. Allele effects were converted to additive genetic standard deviations, and closestBed 2.17.0 was used to obtain a list of genes that contained SNP or were within 25 kbp of a genotyped SNP. Gene names and coordinates were those published in Cow Ensembl Release 79. Reliability gains averaged 8% in AY, 5% in BS, 12% in HO, and 12% in JE. The SNP ARS-BFGL-NGS-4939 at 1,801,116 bp on BTA14, downstream of the DGAT1 gene, had the largest effects on PM and PF in HO and MP in JE of any marker in the analysis. BovineHD1600000386 at 1,554,597 bp on BTA16 had largest effect on FP and PP in JE, in a region previously reported to effect fat and protein yields and percentages. The SNP with the largest effects in AY were located on the X chromosome in regions reported to affect fat and protein yields and percentages in HO. The largest effect for MP in BS was in a region of BTA19 associated with MY in Chinese Holsteins, while the largest FP and PP effects were in regions of the X chromosome reported to affect fat and protein yield in US Holsteins. Genetic correlations of yield with persistency range from -0.32 to 0.26, so loci with large effects on yield also can affect persistency.