Multi-Omics Analysis Revealed the Molecular Mechanisms Affecting Average Daily Gain in Cattle

The average daily gain (ADG) is a critical index for evaluating growth rates in cattle and is closely linked to the economic benefits of the cattle industry. Heredity is one of the factors affecting the daily gain of cattle. However, the molecular mechanisms regulating ADG remain incompletely understood. This study aimed to systematically unravel the molecular mechanisms underlying the divergence in ADG between high average daily gain (HADG) and low average daily gain (LADG) Angus cattle through integrated multi-omics analyses (microbiome, metabolome, and transcriptome), hypothesizing that the gut microbiota-host gene-metabolism axis is a key regulatory network driving ADG divergence. Thirty Angus cattle were classified according to their HADG and LADG. Fecal and serum samples were collected for 16S, fecal metabolome, and blood transcriptome analysis. The results showed that compared with the LADG group, the abundance of Firmicutes increased in the HADG group, while the abundance of Bacteroidetes and Proteobacteria decreased. Metabolomics and transcriptomic analysis revealed that KEGG pathways associated with differentially expressed genes (DEGs) and differentially abundant metabolites (DAMs) were enriched in bile acid metabolism. Spearman correlation analysis showed that <i>Oscillospira</i> was positively correlated with <i>ZBTB20</i> and negatively correlated with <i>RADIL</i>. <i>ZBTB20</i> was negatively correlated with <i>dgA-11_gut_group</i>. This study analyzed the regulatory mechanism of average daily gain of beef cattle from genetic, metabolic, and microbial levels, providing a theoretical basis for analyzing the mechanism of differential daily gain of beef cattle, and has important significance for improving the production performance of beef cattle. The multi-omics network provides biomarker foundations for machine learning-based ADG prediction models, offering potential applications in precision breeding. While these biomarkers show promise for precision breeding, their causal roles require further validation. The conclusions are derived from a single breed (Angus) and gender (castrated males). Future studies should include females and diverse breeds to assess generalizability.

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Publication Details

Journal
International Journal of Molecular Sciences
Published
2025-03-06
DOI
https://doi.org/10.3390/ijms26052343
Citations
4
Primary Topic
Genetic and phenotypic traits in livestock
Type
article
Field-Weighted Citation Impact
7.27

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article

Multi-Omics Analysis Revealed the Molecular Mechanisms Affecting Average Daily Gain in Cattle

Caixia Shi, Mingjuan Gu, Shuai Li, Yu Wang et al.
4 citations
International Journal of Molecular Sciences
Genetic and phenotypic traits in livestock
7.27
article

Multi-Omics Analysis Revealed the Molecular Mechanisms Affecting Average Daily Gain in Cattle

Caixia Shi, Mingjuan Gu, Shuai Li, Yu Wang, Wenguang Zhang, Lin Zhu, Risu Na, Fengying Ma, Hongyu Jiang, Yaqiang Guo
article en
4 citations

Abstract

The average daily gain (ADG) is a critical index for evaluating growth rates in cattle and is closely linked to the economic benefits of the cattle industry. Heredity is one of the factors affecting the daily gain of cattle. However, the molecular mechanisms regulating ADG remain incompletely understood. This study aimed to systematically unravel the molecular mechanisms underlying the divergence in ADG between high average daily gain (HADG) and low average daily gain (LADG) Angus cattle through integrated multi-omics analyses (microbiome, metabolome, and transcriptome), hypothesizing that the gut microbiota-host gene-metabolism axis is a key regulatory network driving ADG divergence. Thirty Angus cattle were classified according to their HADG and LADG. Fecal and serum samples were collected for 16S, fecal metabolome, and blood transcriptome analysis. The results showed that compared with the LADG group, the abundance of Firmicutes increased in the HADG group, while the abundance of Bacteroidetes and Proteobacteria decreased. Metabolomics and transcriptomic analysis revealed that KEGG pathways associated with differentially expressed genes (DEGs) and differentially abundant metabolites (DAMs) were enriched in bile acid metabolism. Spearman correlation analysis showed that <i>Oscillospira</i> was positively correlated with <i>ZBTB20</i> and negatively correlated with <i>RADIL</i>. <i>ZBTB20</i> was negatively correlated with <i>dgA-11_gut_group</i>. This study analyzed the regulatory mechanism of average daily gain of beef cattle from genetic, metabolic, and microbial levels, providing a theoretical basis for analyzing the mechanism of differential daily gain of beef cattle, and has important significance for improving the production performance of beef cattle. The multi-omics network provides biomarker foundations for machine learning-based ADG prediction models, offering potential applications in precision breeding. While these biomarkers show promise for precision breeding, their causal roles require further validation. The conclusions are derived from a single breed (Angus) and gender (castrated males). Future studies should include females and diverse breeds to assess generalizability.

International Journal of Molecular SciencesVol. 26(5)
Inner Mongolia Agricultural University (CN)
Natural Science Foundation of Inner Mongolia
Openalex Percentile: Top 3%
Genetic and phenotypic traits in livestock
7.27
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