This is a draft schedule. Presentation dates, times and locations may be subject to change.

175
Construction of an Association Weight Matrix to Identify SNP That Play a Role in Performance of Angus Cattle at Higher Elevations

Monday, July 10, 2017: 2:45 PM
315 (Baltimore Convention Center)
K. J. Jennings, Department of Animal Sciences, Colorado State University, Fort Collins, CO
X. Zeng, Department of Animal Sciences, Colorado State University, Fort Collins, CO
A. Reverter, CSIRO Agriculture, Brisbane, Australia
T. N. Holt, College of Veterinary Medicine and Biomedical Sciences, Colorado State University, Fort Collins, CO
S. J. Coleman, Department of Animal Sciences, Colorado State University, Fort Collins, CO
R. M. Enns, Department of Animal Sciences, Colorado State University, Fort Collins, CO
S. E. Speidel, Department of Animal Sciences, Colorado State University, Fort Collins, CO
M. G. Thomas, Department of Animal Sciences, Colorado State University, Fort Collins, CO
High Altitude Disease (HAD) is of low incidence, but occurs in cattle at altitudes >1,500 m. Histopathologically, this condition is characterized by pulmonary arterial vasoconstriction resulting in reduced diameter of arterioles subsequently causing pulmonary hypertension and right heart failure. Mean pulmonary arterial pressure (mPAP) is commonly used as an indicator trait of pulmonary hypertension leading to HAD. Animals with mPAP measurements < 41 mmHg are considered to be of low risk for the development of HAD. Because mPAP is a trait difficult to measure, studies have identified SNP that may be of interest in selecting cattle more tolerant of higher altitudes. These SNP, if evaluated in polygenic models, could elucidate ways to implement genomic selection by establishing genetic pathways that will identify cattle better suited for high altitudes. In previous genome wide association studies (GWAS), SNP were associated with mPAP as well as traits of birth weight, milking ability, weaning weight, post-weaning gain, and yearling weight. The objective of this study was to identify relationships among previously identified SNP by means of an association weight matrix (AWM) with mPAP as the primary trait of interest. Significant SNP from six GWAS were included in the AWM if they accounted for > 0.001% of the genetic variance for mPAP. Based on that criterion, 954 SNP were identified for the AWM. Those SNP specifically associated with mPAP were then utilized to calculate the average number of phenotypes (Ap) a SNP should be associated in order to be included in the AWM. By averaging the number of additional phenotypes that SNP related to mPAP were associated with, an Ap of 0.266 was obtained, which was then rounded to one. All SNP that were significant at a genetic variance of > 0.001% and associated with at least one phenotype were included in the AWM. Results indicated that significant SNP for the AWM spanned all 29 autosomal chromosomes as well as the X chromosome. Of the 262 SNP associated with mPAP, 17, 19, and 11 were associated with birth, weaning, and yearling weights respectively. This supports previous studies indicating that the genetic correlations between mPAP and performance traits were weak to moderate rg < 0.27. Results from this study can be utilized to construct gene networks of SNP that are associated with mPAP as an effort to develop multi-trait genomic selection tools for high altitude beef production systems.