A Systems Biology Approach to Prioritize SNP and Genes Affecting Fertility in Tropical Beef Cattle

Improvements in fertility of bulls and cows increase on-farm productivity, especially in the tropics where fertility rates are lower. We identified SNP and genes with potential pleiotropic effects across several phenotypes, and tested these for the amount of genetic variance of production traits that they captured. A total of 40 high-density genome-wide association studies were conducted including ten phenotypes in bulls and ten in cows from Brahman and Tropical Composite cattle, and a pleiotropy test was performed. The tested traits were fertility related (e.g. age at puberty, and percent normal sperm) and other production traits (e.g. yearling weight, and eye muscle area). Applying the PCIT algorithm on the SNP selected in the previous step, four networks were built, one for each breed-sex combination. Gene pairs (SNP, n=1,412) that were present in all four networks included 105 transcription factors (TF) that had on average more connections than the remaining genes (12.63 v. 9.65). We built genetic relationship matrices (GRM) using these TF SNP, computed the amount of genetic variance explained and compared it to the GRM based on the full dataset (n>700K SNP). We found that on average across forty traits and two populations, the 105 SNP in TF accounted for 31% of the genetic variance ranging from 15.6% of mature height in cows to 62.2% of age at which bulls reached 26cm scrotal circumference, both in Brahman. Systems biology based approaches can assist the identification of small panels of markers that together explains a reasonable proportion of the genetic variation.