UTTAR PRADESH JOURNAL OF ZOOLOGY

The demand for efficient and sustainable livestock production is increasing due to global population growth and changing dietary preferences. Conventional breeding methods, although successful, are often limited in addressing complex traits controlled by multiple genes and environmental interactions. Transcriptomics, which focuses on the comprehensive analysis of RNA expression, has emerged as a transformative approach for understanding functional genomics in livestock species. With the advancement of high-throughput sequencing technologies such as RNA sequencing and single-cell transcriptomics, researchers can now investigate gene expression patterns with high precision. Additionally, spatial transcriptomics enables localization of gene expression within tissue architecture, providing deeper insights into cellular heterogeneity and functional organization. AI-driven bioinformatics integration further enhances transcriptomic data analysis by enabling predictive modelling, pattern recognition, and multi-omics data interpretation. This review provides an overview of transcriptomic technologies, highlighting their applications in improving disease resistance, productivity, reproduction, and environmental adaptability in livestock. The integration of transcriptomics with advanced computational tools and multi-omics approaches holds great promise for next-generation livestock improvement strategies.