Integrative Multi-Omics Approaches to Enhance Milk Yield, Health, and Efficiency in Dairy Cattle: A Systematic Review Authors: Kamran Ahmad Nasir, Hassan Abbas, Kashif Raza Zaidi Journal: Journal of Animal and Plant Sciences (JAPS) ISSN: 1018-7081 (Print), 2309-8694 (Online) Volume: 36 Issue: 5 Year: 2026 DOI: https://doi.org/10.36899/JAPS.2026.5.0110 URL: https://doi.org/https://doi.org/10.36899/JAPS.2026.5.0110 Publisher: Pakistan Agricultural Scientists Forum Abstract:

This review incorporates peer-reviewed studies up to June 2025, including recent advancements in multi-omics integration for mastitis, metritis, milk yield, and host-microbiome interactions, ensuring an up-to-date synthesis of dairy cattle genomics and trait prediction. Studies were found through systematic database searches and were screened for inclusion based on pre-agreed criteria. Target characteristics, omics layers used, integration methods, study designs, and analytical tools were the key parameters extracted in this study. Among the 60 studies included in this review, genomics was the most frequently applied omics layer (22 studies, 37%), followed by transcriptomics (14 studies, 23%), metabolomics (9 studies, 15%), microbiomics (8 studies, 13%), and proteomics (7 studies, 12%). Twelve studies (20%) employed integrated multi-omics approaches, most commonly combining genomics with transcriptomics or metabolomics. Integrated omics models significantly improved the prediction accuracy of low-heritability traits such as fertility and disease resistance. The primary area of interest was milk yield and disease characteristics, while the research focused on sustainability-related traits, such as methane emission and heat tolerance, which were relatively low. Despite the use of various analytical approaches, the integration pipelines are still not commonly standardised. This review, in addition to the apparent changes resulting from the implementation of multi-omics for precision breeding and ecological dairy farming, highlights the need to emphasise the shortcomings in breed representation, tissue sampling, and functional testing. This review identifies key research gaps and offers recommendations to standardize integration pipelines and expand breed diversity for future precision dairy applications.

Keywords: Multi-omics, Dairy cattle, Genomics, Transcriptomics, Microbiome, Metabolomics, Systems biology, Trait prediction, Precision breeding