Masters Theses
Date of Award
8-2023
Degree Type
Thesis
Degree Name
Master of Science
Major
Animal Science
Major Professor
Troy N. Rowan
Committee Members
Sarah E. Moorey, Jonathan E. Beever
Abstract
Reproduction plays a major role in the production efficiency of livestock species. However, cow-centric reproductive traits are lowly heritable and are not expressed until later in an animal’s lifetime, making phenotypic selection ineffective at generating genetic gain. We can generate genetic progress by focusing selection on the genetic component of reproductive traits using Expected Progeny Differences (EPDs). We used the American Simmental Association’s performance and Total Herd Enrollment data, made up of 533,155 calving records from 303,158 females (132,403 cows and 170,755 heifers), 33,732 of which are genotyped, to develop two continuous and two discrete phenotypes focused on quantifying early and sustained fertility in beef cows. We analyzed calving interval (days between calves), calving date (cow’s calving date relative to the start of the calving season), heifer pregnancy (did animal calve as 2-year-old), and discrete early calving (did animal calve in the first 30 days of the calving season) as distinct, but correlated measures of fertility. This dataset provides insight into population-wide trends related to cow attrition, calving season lengths, and phenotypic variation in fertility. We used pedigree and genomic REML to estimate the genetic, permanent environment, and temporary environmental variance components of these four phenotypes. Pedigree estimated heritabilities were 0.02 (±0.000003) for calving date, 0.08 (±0.000026) for calving interval, 0.05 (±0.000095) for discrete early calving, and 0.23 (±0.000105) for heifer pregnancy, consistent with other fertility traits across beef and dairy cattle. The incorporation of genomics increased the heritability estimates for heifer pregnancy (0.24 ±0.000098) and calving date (0.03 ±0.000003) and decreased for calving interval (0.07 ±0.000005). All measured phenotypes had positive genetic correlations with each other (rG = 0.11-0.96). indicating that selection for any of these phenotypes will positively impact the others. These results call for further research into the genetic architecture of cow rebreeding phenotypes through genome-wide studies.
Recommended Citation
Catrett, Cassidy, "Using Novel Phenotypes to Understand and Predict Fertility in Beef Cows. " Master's Thesis, University of Tennessee, 2023.
https://trace.tennessee.edu/utk_gradthes/9958