49 Prediction of Beef Heifer Reproductive Potential Using Molecular Markers

Abstract

Abstract Heifer infertility has a negative impact on beef cattle production and profit on the livestock industry. The ability to identify heifers early based on reproductive potential would help improve the sustainability of beef production. The omics technologies have provided opportunities to improve reproductive efficiency. Previously, we have explored the ability of plasma metabolic profiles and mRNA profiles in the peripheral white blood cells (PWBCs) to serve as molecular markers of reproductive potential, at the time of artificial insemination (AI). Recently, we have integrated these data to identify the potential genetic pathways involved. We used RNA-Seq paired data and untargeted metabolomics from six AI-pregnant (AI-P) and six nonpregnant (NP) Angus-Simmental crossbred heifers at AI. Based on network co-expression analysis, we identified 17 and 37 hub genes in the AI-P and NP groups, respectively. We also identified TGM2, TMEM51, TAC3, NDRG4, and PDGFB as more connected in the NP heifers’ network. Metabolomic analysis identified 18 and 15 hub metabolites in the AI-P and NP networks. Tryptophan in the NP network, and allantoic acid in the AI-P network, exhibited a connectivity gain. Gene-metabolite integration identified tocopherol-a as positively correlated with ENSBTAG00000009943 in the AI-P group. Conversely, tocopherol-a was negatively correlated in the NP group with EXOSC2, TRNAUIAP, and SNX12. In the NP group, α-ketoglutarate-SMG8 and putrescine-HSD17B13 were positively correlated, whereas a-ketoglutarate-ALAS2 and tryptophan-MTMR1 were negatively correlated. These multiple interactions identified novel targets and pathways underlying fertility in bovines. Next, we hypothesized that gene expression from PWBCs at weaning could potentially predict the future fertility potential of beef heifers. We used the RNA-Seq approach to gain insights into the gene expression profile of PWBC at weaning from Angus-Simmental crossbred heifers. The heifers were retrospectively classified as pregnant through artificial insemination (AI-P, n = 8) and non-pregnant (NP, n = 7). We identified 92 differentially expressed genes between the groups, including MORN4, TFF2, MXD1, PHF8, KAT2B and CLEC4D. Based on a network co-expression analysis, we identified 14 and 52 hub targets, out of which ENSBTAG00000052659, OLR1, TFF2 and NAIP were exclusive to the AI-P group while 42 hubs were exclusive to the NP group. The differential connectivity between the networks of each group revealed a gain in connectivity due to the rewiring of major regulators in the NP group. The rewiring of major regulators unveiled in this study likely modulates the expression of gene targets as a response to infertility. The exclusive hub targets from AI-P are over-represented for the CXCR chemokine receptor pathway and inflammasome complex. In contrast, the 42 hub targets are over-represented for immune response and cytokine production pathways. These multiple interactions identified novel targets and pathways predicting fertility potential at an early stage of heifer development.