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September 10, 2025Communications Biology0 citationsOpen Access

A pilot multi-omics study reveals genetic mechanisms regulating milk component traits in dairy cattle

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WZWeijie ZhengJZJunnan ZhangJHJinfeng Huang

Key Points

  • This study reveals significant genetic mechanisms that influence milk composition traits in dairy cattle, potentially improving milk quality.
  • Nine candidate genes involved in milk protein and fat synthesis were identified, highlighting the role of specific signalling pathways.
  • Using a multi-omics approach, integrated data from RNA-seq, ATAC-seq, and cis-QTLs datasets provided insight into genetic regulation.
  • Findings suggest further exploration with larger sample sizes is essential for robust validation of identified genetic influences.

Abstract

Milk protein percentage (PP) and fat percentage (FP) are important indicators for measuring milk quality, but only a few causative genes such as DGAT1, GHR, and ABCG2, have been identified, indicating substantial potential for further exploration. Here, we integrated genotyping, RNA-seq, ATAC-seq, single-cell atlas and cis-QTLs datasets from the liver and mammary gland to investigate their genetic regulation. We identified cell type affecting milk composition, such as HPE2 and LumSec-HSPH1, and highlighted nine candidate genes (EFNA1, ERBB3, DUSP16, DEPTOR, TRIM46, HSTN, CIDEA, ACACA and SPP1) that are involved in the regulation of milk protein and fat synthesis through MAPK, AMPK, PI3K-Akt, and mTOR signalling pathways. Notably, EFNA1 was consistently identified across all omics analyses, showing increased promoter accessibility in the high PP group, potentially driven by CTCF and RXRA-mediated transcriptional activation. Overall, this study reveals potential cell types, candidate genes, and regulatory mechanisms influencing milk composition, offering insights to support milk quality improvement. The limited sample size represents the main constraint of this work, and future efforts will focus on population-scale genetic analyses and wet-lab validation.

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Cite This Study

Zheng et al. (2025) studied this question.

synapsesocial.com/papers/68c1b19354b1d3bfb60e8b06https://doi.org/10.1038/s42003-025-08615-6
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