Molecular marker prediction for days open and pregnancy rate in Holstein cows managed in a warm climate

Abstract

Reproductive management in lactating Holstein cattle is a challenge for dairy producers in Northwestern Mexico where a semi-desert, yet humid, environment is predominant. Under such conditions, a superior cow's ability to get pregnant early during postpartum is desirable to reduce the number of days open and improve fertility parameters. The objective of this study was to predict days open (DO) and pregnancy rate (PR) using molecular markers associated with fertility in lactating Holstein cows managed in a warm climate. This study included 510 cows from three dairy herds located in the Yaqui Valley of Sonora. A blood sample was collected from every cow and spotted onto FTA cards. Each cow was genotyped for 179 tag single nucleotide polymorphisms (SNPs) within 43 genes in the prolactin and GH-IGF1 pathways. An association mixed-effects model identified three SNPs within the genes AVPR1A, PRLR and SSTR2 associated with DO (P < 0.05), and five SNPs within the genes IGFBP2, IGFBP5, PRLR, PIAS1 and SSTR2 associated with PR (P < 0.05). The SNP effects were estimated and used to calculate the individual molecular breeding values (MBV) for DO and PR. Average MBV were 20.91 ± 0.21 d and 0.29 ± 0.003% for DO and PR, respectively. The correlation between the MBV and DO was 0.0008 (P = 0.968), whereas correlation between MBV and the estimated breeding value (EBV) for DO was −0.16 (P < 0.001) with an adjusted coefficient of determination (R2) of 2.5%. For PR, its correlation with the MBV was 0.15 (P < 0.001) with a R2 of 2.2%, whereas the correlation between MBV and the EBV for PR was 0.31 (P < 0.001) with a R2 of 9.6%. Heritability estimates were 0.06 ± 0.11 and 0.04 ± 0.06 for DO and PR, respectively. In conclusion, candidate gene SNPs from the prolactin and GH-IGF1 pathways were effectively used to construct an MBV for fertility traits in heat-stressed Holstein cattle. These SNPs explained only a small amount of variation for PR, but not for DO; therefore, additional research using denser SNP panels and a larger population is suggested to improve the power of the MBV as genetic predictor for fertility traits in lactating dairy cows managed under warm environmental conditions.