Network analyses unraveled complex interactions in the rumen microbiome associated with methane emission in cattle

Abstract Methane emissions from livestock, particularly from dairy cattle, represent a significant source of greenhouse gas (GHG), contributing to global climate crisis. This study employed Weighted Gene Co-expression Network Analysis (WGCNA) to investigate the complex interactions within the rumen microbiome that influence methane emissions. By integrating rumen microbiome sequencing data with precise methane emission measurements in 750 Holstein dairy cattle, our research identifies distinct microbial communities and their associations with methane production. Key findings revealed that specific WGCNA modules (MEturquoise, MEbrown, MEblue, and MEgreen) with taxa (Prevotella, Clostridium, Anaeroplasma, YRC22, BF311, and Succinogenes), and complex network interactions are significantly correlated with methane emissions. The application of WGCNA provided a comprehensive understanding of the microbiome-methane emission and microbiome-microbiome relationship, serving as an innovative approach for microbiome-phenotype association studies in cattle.