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

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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Publication Details

Journal
Communications Biology
Published
2025-08-04
DOI
https://doi.org/10.1038/s42003-025-08615-6
Citations
4
Primary Topic
Single-cell and spatial transcriptomics
Type
article
Field-Weighted Citation Impact
3.22
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article

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

Jinfeng Huang, Dongxiao Sun, Yanan Liu, Bo Han et al.
4 citations
Communications Biology
Single-cell and spatial transcriptomics
3.22
article

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

Jinfeng Huang, Dongxiao Sun, Yanan Liu, Bo Han, Weijie Zheng, Junnan Zhang
article en
4 citations

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.

Communications BiologyVol. 8(1)
Guangdong Urban & Rural Planning and Design Institute (CN), Ministry of Agriculture (ID), Ministry of Agriculture and Rural Affairs (CN)
Zero hunger
Openalex Percentile: Top 8%
Single-cell and spatial transcriptomics
3.22
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A pilot multi-omics study reveals genetic mechanisms regulating milk component traits in dairy cattle — Jinfeng Huang, Dongxiao Sun, et al. · Communications Biology (2025) | TGRS Research Map | TGRS