Microbiome

Advanced Microbiome Analysis Reveals Dual Pathways Linking Agro-Industrial By-Products to Methane Reduction in Dairy Cows

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Abstract

Rumen fluid samples (n=15) were collected from 15 mid-lactating Holstein dairy cows which were fed three diets over a period of 24 days. Treatments included control (basal TMR), apple pomace (15% DM), and hempseed cake (12% DM) (Xue, et al. 2025). Methane emissions (CH₄, g/d) were measured using the GreenFeed system, which provides high-frequency, individual animal methane output data. While the cows in this study were not pre-selected for specific genetic backgrounds, they represent a typical commercial Holstein population. Rumen fluid samples underwent shotgun metagenomic sequencing. Beyond standard diversity analysis, we applied five specialized microbiome methods: (1) compositional data analysis with center log-ratio (CLR) transformation to address mathematical constraints in relative abundance data; (2) network-based correlation analysis using bacterial centrality measures; (3) distance-based redundancy analysis (dbRDA) for community-level effects; (4) Bayesian correlation analysis with uncertainty quantification; and (5) sparse canonical correlation analysis for multivariate bacterial signatures. Mixed-effects models first removed treatment and period effects, then residual analysis tested 224 bacteria-metadata relationships with stringent FDR correction.This study demonstrates that agro-industrial by-products influence dairy cow performance through dual microbiome pathways: dominant treatment-mediated effects that reshape bacterial communities toward beneficial configurations, and subtle but significant intrinsic relationships where natural microbiome variation independently affects production traits. Although the cows were not under explicit genetic selection, our results highlight the potential for integrating microbiome profiles, such as Prevotella bryantii abundance and community diversity, as biomarkers in precision breeding and selection strategies.

Keywords: 2026

How to Cite:

Carballo, O., Chen, X., EBRAHIMPOUR GORJI, A., Sadkowski, T., Shirali, M., Stergiadis, S., Theodoridou, K., Xue, B. & Yan, T., (2026) “Advanced Microbiome Analysis Reveals Dual Pathways Linking Agro-Industrial By-Products to Methane Reduction in Dairy Cows”, World Congress on Genetics Applied to Livestock Production Digital Archive 2026(1): 2285809. doi: https://doi.org/10.31274/wcgalp.23801

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