Integrated transcriptome and regulatory network analyses identify candidate genes and pathways modulating ewe fertility

Fertility in ewes is closely linked to ovulation rate and can be predicted by transcriptome profiling to identify candidate genes, biomarkers, and underlying molecular mechanisms. Our objective was to explore the genetic basis of ewe fertility by combining RNA-Seq data analyses of ovarian tissues from high and low fertility ewes with published transcriptome studies (i.e., literature mining). Integration of these 2 sources identified 113 differen-tially expressed genes (DEGs) associated with ewe fertility. Among these, 21 genes (CTNNB1, BMPR1B, BMP2, GDF9, BMP15, FSHR, TGFBR2, C -MET, KIT, MMP9, FST, LHCGR, SPP1, CYP19, CTSS, C1QB, FGF1, FGF18, BMP7, INHBA, and PAX8) were identified as hub (highly connected) genes for ewe fertility and were subjected to protein-protein interaction (PPI) network, mRNA-miRNA regulatory bipartite network, and subnets construction. Gene ontology (GO) terms enrichment analysis of the DEG represented 28, 23, and 21 GO terms associated with ewe fertility in categories of biological process, molecular functions, and cellular components, respectively. Based on annotation results, DEGs have major roles in signaling pathways related to cytokine-cytokine receptor interactions, ovarian steroidogenesis, and the TGF-beta, MAPK, Hippo, PI3K-Akt, Rap1, and Ras signaling pathways. Identification of these genes, metabolic and signaling pathways, and their related functions, could provide new insights into biological mechanisms of transcriptome profiling in the ovary and inform future studies of biomarkers for ewe fertility.