Abstract
Methane emissions from livestock, particularly dairy cattle, represent a significant source of greenhouse gas (GHG), contributing to climate changes. This study employed Weighted Gene Co-expression Network Analysis (WGCNA) to investigate the complex interactions within the rumen microbiome that influence methane emissions in 750 Holstein dairy cattle. By integrating extensive rumen microbiome sequencing data with precise methane emission measurements, our research identifies distinct microbial communities and their associations with methane production. Key findings reveal that specific WGCNA modules (MEblue, MEyellow, MEturquoise, and MEbrown), taxa (VadinCA11, Methanobrecivecter, Methanosphaera, Prevotella and Treponema), and network interactions (VadinCA11-ko00680, Prevotella-ko00680) significantly correlated with methane emissions. The application of WGCNA provided a comprehensive understanding of the microbiome-methane emission relationship, providing its potential as an innovative approach for microbiome-traits associated studies in cattle. Our findings underscore the potential of microbial management as a strategy for environmental impact reduction in agriculture, highlighting critical pathways and interactions that could be targeted for intervention.
| Original language | English |
|---|---|
| Journal | Animal Microbiome |
| Publication status | Submitted - 26 Jul 2024 |
Keywords
- Rumen microbiome
- Methane emissions
- Cattle
- Network analysis