Metagenomics, the study of genetic material directly extracted from environmental samples, has revolutionised microbial research by enabling culture-independent investigation of microbial diversity, community structure, and potential. It has become a potent tool in livestock production systems for addressing major challenges related to animal health, productivity, environmental sustainability, antimicrobial resistance, and greenhouse gas emissions. Metagenomic approaches have provided critical insights into ruminal microbial ecology, host–microbiome interactions, feed efficiency, milk production, heat stress resilience, metabolic disorders, and methane emissions, in addition to facilitating the identification of microbial biomarkers and functional pathways associated with economically important traits. Furthermore, metagenomics has improved One Health surveillance through characterization of resistomes, mobile genetic elements, zoonotic pathogens, and microbial reservoirs of antimicrobial resistance. Applications also extend to uterine and faecal microbiome research, viral detection, novel enzyme discovery, therapeutic development, and biodegradation. The use of metagenomics in precision nutrition, microbiome-informed breeding, disease monitoring, and sustainable livestock management has been greatly increased by recent developments in high-throughput sequencing, bioinformatics, and multi-omics integration. This review highlights the revolutionary potential of metagenomics in livestock production systems by examining its methodological advancements, historical background, and diverse applications.
Dibyasha Kar, Ritik Kumar Singh, Deepti Sinha et al.· Journal of Pure and Applied...· 0 citations
Background: This study aimed to identify genomic regions under selection in Kangayam cattle of Tamil Nadu using a de-correlated composite of multiple signals (DCMS) framework. Methods: BovineHD SNP array data were retrieved from the WIDDE repository and the ICAR Krishi-Kosh portal. After quality control, autosomal SNPs were used for subsequent analyses. Fixation index, integrated haplotype score, modified haplotype homozygosity, Tajima’s D and nucleotide diversity, were calculated and integrated using the DCMS approach. Genomic windows with false discovery rate (FDR) adjusted q less than 0.001 scores were considered for subsequent analysis. Functional annotation, QTL enrichment, protein–protein interaction (PPI) network analysis and hub gene identification were performed to interpret biological relevance. Result: Genomic regions identified after DCMS analysis, harbored genes related to muscle development, metabolism, immunity, thermotolerance, reproduction and milk composition, including MSTN, BMP7, PRKAG3, BoLA-DRB3, IL8R, ABCA1 and members of the SLCO gene family. PPI and hub gene analyses highlighted transport and metabolic pathways, with SLC22A7 and ABCC9 emerging as key nodes. This study presents the first DCMS-based selection signature map for Kangayam cattle, uncovering coordinated selection across interconnected biological pathways.
Asad Khan, Ishmeet Kumar, J. Vyas et al.· Indian Journal of Animal Res...· 0 citations
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