Jingya Li , Jun Li

Animal Science Research Center, Cuixi Academy of Biotechnology, Zhuji, 311800, Zhejiang, China
Author    Correspondence author
Computational Molecular Biology, 2025, Vol. 15, No. 5   
Received: 19 Jul., 2025    Accepted: 31 Aug., 2025    Published: 23 Sep., 2025

This is an open access article published under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

The milk production trait of dairy cows is a complex quantitative trait with high economic value. With the development of high-throughput technology, integrating multi-omics data such as genomics, transcriptomics, epigenomics, proteomics and metabolomics has become an important means to reveal the genetic basis of milk production traits. This study, through a multi-omics integration strategy, explored the core genes and regulatory networks that affect milk production and its related traits, reviewed the main milk production traits and their related quantitative trait loci (QTLS), systematically sorted out the characteristics of various omics data and their integrated analysis methods, such as weighted gene co-expression network analysis (WGCNA) and multi-omics factor analysis (MOFA), the focus is on key genes (such as STAT5A, CSN2) in the breast development and lactation regulatory pathways, the interaction network between miRNA and mRNA, as well as functional enrichment pathways. This study demonstrates the potential of multi-omics integration in analyzing complex traits, providing a scientific basis for promoting the intelligence and efficiency of molecular breeding in dairy cows, and also offering ideas for future functional gene verification and optimization of precise breeding strategies.

Dairy cows; Milk production characteristics; Multi-omics integration; Gene regulatory network; Candidate gene identification