Meta‐Analysis of Transcriptomic Datasets Reveals Key Immune Gene Profiles and Signaling Pathways in <i>Bos taurus</i>

ABSTRACT Improving disease resistance in cattle relies on informed breeding and vaccine development, both depend on our understanding of immune mechanisms in cattle. However, transcriptomic studies of bovine immune responses often show considerable variability due to differences in tissue type, pathogen, time point, and experimental design, limiting the generalizability. Meta‐analysis integrates multiple transcriptomic studies to identify consistent gene expression patterns and enhance statistical power. We integrated bovine RNA‐seq datasets using immune‐response specific keywords, species constraints, and high‐throughput sequencing filters to prioritize biologically comparable and meta‐analysis‐ready studies. Specifically, in this study, we performed a meta‐analysis of four bovine transcriptomic datasets to identify immune‐related differentially expressed genes (DEGs) in Bos taurus . These datasets showed consistent results across analyses and represent immune responses related to mycobacterial infections ( Mycobacterium bovis and Mycobacterium avium subsp. paratuberculosis ), making them suitable for combined analysis. Our pipeline included FastQC, Trimmomatic, Bowtie2, SAMtools, FeatureCounts, DESeq2, and MetaRNASeq, identifying 28 DEGs (12 upregulated and 16 downregulated). We identified key immune‐related genes ( IL1A , RGS2 , RCAN1 , ZBP1 , TIMD4 , PPARG , TLR10 , and ACP5 ) with known regulatory roles in immunity. KEGG enrichment analysis revealed involvement in necroptosis, osteoclast differentiation, oxytocin signaling, and cGMP–PKG signaling pathways, associated with inflammatory cell death, cytokine signaling, and immune cell differentiation. Using reproducible transcriptomic signals across systematically selected bovine immune datasets rather than relying on single‐experiment analyses, we provide a robust meta‐analytic framework. This meta‐analysis enhances our understanding of conserved immune signaling mechanisms in cattle for identifying conserved immune mechanisms with broader biological and translational relevance.