283 Validation of Quantitative Trait Loci Associated with Grazing Distribution Traits in Beef Cattle Using Bayes C. (7th December 2018)

• Record Type: Journal Article
• Authors: Pierce, C; Bailey, D; Medrano, J; Cánovas, A; Speidel, S; Coleman, S; Enns, R; Thomas, M
• Is Part Of: Journal of animal science. Volume 96(2018)Supplement 3
• Page Start: 105
• Page End: 105
• Publication Date: 2018-12-07
• Subjects: cattle -- grazing distribution -- QTL; Livestock -- Periodicals; Livestock; Electronic journals; Periodicals; 636.005
• DOI: 10.1093/jas/sky404.232
• Languages: English
• ISSNs: 0021-8812

Abstract

Abstract: Concentrated grazing may destroy wildlife habitat, reduce forage harvest, and degrade riparian areas; therefore, it is necessary to develop tools to improve grazing distribution for extensive pastures in beef production systems. A previous genome-wide association study identified 5 QTL on BTA 4, 12, 17, and 29 that were associated with grazing distribution indices (rolling and rough). The objective of this study was to validate these QTL using additional association analyses with a Bayesian approach. Global positioning system (GPS) technology was used to collect grazing distribution phenotypes from 80 beef cows on 5 ranches in New Mexico, Montana, and Arizona. Percent slope, elevation, and distance from water were calculated using GPS coordinates and incorporated into two terrain-use indices (rough and rolling). Cows were genotyped with 777, 962 SNP and after applying standard SNP quality filters, 733, 713 SNP from 75 cows were available for analysis. A single chromosome (BTA 4, 12, 17, 29) association analysis was performed for both the rough and rolling indices using Bayes C (within the BOLT software package. The posterior inclusion probability (PIP) for each SNP was estimated. The association between rs109619368 on BTA 17 and the rough index was confirmed (PIP = 2.1%); however, the QTL on BTA 4, 12, and 29 were not verified. To further investigate this, 50 SNP spanning 0.2 MB on BTA 29 were analyzed with the rolling index. Two SNP were confirmed in this analysis: rs42161939 (PIP = 54.9%) and rs43744222 (PIP = 21.6%). The Bayesian approach applied in this study, in which markers are simultaneously fit in the model, revealed 3 QTL concordant with previous analyses which used a single-marker regression approach. These results suggest that grazing distribution traits are under genetic control; however, a greater number of observations are needed to confirm the QTL associated with grazing distribution (SW15-015).