Genomic selection for improved fertility of dairy cows with emphasis on cyclicity and pregnancy

Abstract Text:

The overall goal of this ongoing integrated project (research, extension, and education) is to make use of advanced genomic technologies to improve dairy cattle fertility, with emphasis on cyclicity and pregnancy. The Specific Aims are: 1) Development of a fertility database with genotypes and phenotypes based on objective and direct measures of fertility in Holstein dairy cows; 2) Identification of genome regions associated with fertility traits and utilization of this information on prediction models that can be applied in selection of dairy cattle for improved fertility; 3) Development and implementation of a comprehensive extension program on best management and genomic selection practices to improve fertility of dairy herds; and 4) Development of an education component targeting the general public as well as students in animal and veterinary sciences. In this presentation we will describe the development and outcomes on Specific Aim 1, as well as some preliminary analyses and results related to Specific Aim 2. A total of 12,000 Holsteins cows from 7 states (NY, MN, WI, TX, CA, FL, OH), comprising 2 to 3 farms per state, were enrolled at calving and weekly monitored until pregnancy. Main events were uterine health, metabolic disorders, cyclicity, estrus, pregnancy per A.I., and pregnancy loss, together with milk yield until 305 DIM. A reproductive index, calculating the predicted probability of pregnancy at first A.I. after calving, was generated using a logistic regression model that included cow-level variables such as diseases incidence, anovulation, BCS, and milk yield. Within each farm cows were stratified as pregnant on d 60 after the first AI (high-fertility population) and as non-pregnant on d 60 after 2 A.I. (low-fertility population). A selective genotyping approach was implemented using the reproductive index developed, with selected cows from the high-fertility pregnant (850 cows) and the low-fertility non-pregnant (1,750 cows) groups. Preliminary analyses of the phenotypic data have been implemented, including the estimation of genetic parameters of cyclicity and other fertility indicators, as well as the impact of post-partum diseases on lactation curves. Heritability estimates ranged from 0.03 to 0.12 for the various traits, and many factors influencing the lactation curve have been detected. The next step of the project will include multi-trait and network analyses of the fertility indicators, as well as genome-wide association and gene-set enrichment analyses for detection of genomic regions and sets of genes affecting fertility traits in dairy cattle.

Keywords: genomics, fertility, dairy