Genes · 2026
Integrated Gene-Metabolite Network Analysis Identifies Pathways Associated with Immune Regulation and Metabolic Remodeling in Subfertile Beef Heifers.
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Banerjee Priyanka, Phillips Rachel, Holliman Anna G, Rodning Soren P, Diniz Wellison J S, Dyce Paul W
Аннотация
BACKGROUND/OBJECTIVES: Reproductive inefficiency remains a major contributor to heifer culling and reduced herd longevity in beef systems. This study examined the molecular basis of fertility by analyzing granulosa cells and follicular fluid from Angus-Simmental crossbred heifers classified as fertile or subfertile.
METHODS: Granulosa cells and follicular fluid were collected for RNA sequencing and metabolomic analysis. Differential expression, network, and gene-metabolite integration analyses identified genes, metabolites, and pathways associated with fertility differences between groups.
RESULTS: We identified 90 differentially expressed genes from the granulosa cells, including CXCL12 and HOXD family members, CALCRL, DNER, GADD45G, immune-related genes, and nine metabolites differentially abundant in follicular fluid, including parabanic acid, pimelic acid, α-tocopherol, glycine, and arachidonic acid. Network analysis revealed extensive rewiring in the network from the subfertile heifers for both genes and metabolites as compared to the fertile heifers. The gene-metabolite integration revealed a high degree of connectivity between arachidonic acid and α-tocopherol, correlating with immune and signaling genes, and between CXCL12 and carbohydrate intermediates. Pathway over-representation analysis highlighted carbohydrate and purine metabolism in fertile heifers, and aminoacyl-tRNA biosynthesis, alanine/aspartate/glutamate metabolism, and Hippo signaling in the subfertile heifers. ABC transporters, ferroptosis, mineral absorption, and glyoxylate/dicarboxylate metabolism were common pathways identified in both groups. Integrative granulosa-follicular fluid analysis revealed coordinated gene-metabolite rewiring in subfertility, including functional candidates (CXCL12, CALCRL, DNER; α-tocopherol, arachidonic acid, fucose, parabanic acid) and fertility-associated pathways.
CONCLUSIONS: These signatures provide novel targets and pathways underlying beef heifer fertility.
METHODS: Granulosa cells and follicular fluid were collected for RNA sequencing and metabolomic analysis. Differential expression, network, and gene-metabolite integration analyses identified genes, metabolites, and pathways associated with fertility differences between groups.
RESULTS: We identified 90 differentially expressed genes from the granulosa cells, including CXCL12 and HOXD family members, CALCRL, DNER, GADD45G, immune-related genes, and nine metabolites differentially abundant in follicular fluid, including parabanic acid, pimelic acid, α-tocopherol, glycine, and arachidonic acid. Network analysis revealed extensive rewiring in the network from the subfertile heifers for both genes and metabolites as compared to the fertile heifers. The gene-metabolite integration revealed a high degree of connectivity between arachidonic acid and α-tocopherol, correlating with immune and signaling genes, and between CXCL12 and carbohydrate intermediates. Pathway over-representation analysis highlighted carbohydrate and purine metabolism in fertile heifers, and aminoacyl-tRNA biosynthesis, alanine/aspartate/glutamate metabolism, and Hippo signaling in the subfertile heifers. ABC transporters, ferroptosis, mineral absorption, and glyoxylate/dicarboxylate metabolism were common pathways identified in both groups. Integrative granulosa-follicular fluid analysis revealed coordinated gene-metabolite rewiring in subfertility, including functional candidates (CXCL12, CALCRL, DNER; α-tocopherol, arachidonic acid, fucose, parabanic acid) and fertility-associated pathways.
CONCLUSIONS: These signatures provide novel targets and pathways underlying beef heifer fertility.