Co-expression network and integrative analysis of metabolome and transcriptome uncovers biological pathways for fertility in beef heifers

Authors: BANERJEE, P - Auburn University; RODNING, S - Auburn University; DINIZ, W - Auburn University; DYCE, P - Auburn University

Submitted to: Metabolites
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 7/28/2022
Publication Date: 7/29/2022
Citation: Banerjee, P., Rodning, S.P., Diniz, W.J., Dyce, P.W. 2022. Co-expression network and integrative analysis of metabolome and transcriptome uncovers biological pathways for fertility in beef heifers. Metabolites. 12:708. https://doi.org/10.3390/metabo12080708.
DOI: https://doi.org/10.3390/metabo12080708

Interpretive Summary: Reproductive failure remains a significant challenge to the beef industry. The omics technologies have provided opportunities to improve reproductive efficiency. A study was conducted on multistaged analysis from blood profiles to integrate metabolome (plasma) and transcriptome (peripheral white blood cells) in beef heifers. This study identified multiple interactions for novel targets and pathways underlying fertility in bovines.

Technical Abstract: Reproductive failure remains a significant challenge to the beef industry. The omics technologies have provided opportunities to improve reproductive efficiency. We used a multistaged analysis from blood profiles to integrate metabolome (plasma) and transcriptome (peripheral white blood cells) in beef heifers. We used untargeted metabolomics and RNA-Seq paired data from six AI-pregnant (AI-P) and six nonpregnant (NP) Angus-Simmental crossbred heifers at artificial nsemination (AI). Based on network co-expression analysis, we identified 17 and 37 hub genes in the AI-P and NP groups, respectively. Further, we identified TGM2, TMEM51, TAC3, NDRG4, and PDGFB as more connected in the NP heifers’ network. The NP gene network showed a connectivity gain due to the rewiring of major regulators. The metabolomic analysis identified 18 and 15 hub metabolites in the AI-P and NP networks. Tryptophan and allantoic acid exhibited a connectivity gain in the NP and AI-P networks, respectively. The 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, -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.