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Updated: Nov 8, 2025
The Use of an Automated System GreenFeed to Monitor Enteric Methane and Carbon Dioxide Emissions from Ruminant Animals
Published on: September 7, 2015
A dimensional reduction approach to modulate the core ruminal microbiome associated with methane emissions via
Alejandro Saborío-Montero1, Adrían López-García2, Mónica Gutiérrez-Rivas2
1Departamento de mejora genética animal, Instituto Nacional de Investigación y Tecnología Agraria y Alimentaria, Crta. de la Coruña km 7.5, 28040 Madrid, Spain; Escuela de Zootecnia y Centro de Investigación en Nutrición Animal, Universidad de Costa Rica, 11501 San José, Costa Rica.
Selective breeding using cow hologenome data can reduce methane emissions. Combining host and rumen metagenomic data identifies key microbial components linked to lower greenhouse gas output in cattle.
Area of Science:
- Animal Genomics
- Microbial Ecology
- Agricultural Science
Background:
- The rumen microbiome significantly impacts greenhouse gas emissions and feed efficiency in cattle.
- Selective breeding strategies are crucial for sustainable livestock production.
Purpose of the Study:
- To integrate host and rumen metagenomic data for selective breeding of cows with reduced methane emissions.
- To identify genetic components of the cow hologenome influencing methane production.
Main Methods:
- Analysis of nanopore long-read rumen metagenome data from 437 Holstein cows.
- Application of Principal Component Analysis (PCA) to aggregate complex microbial data.
- Utilizing bivariate animal models to assess genetic correlations between microbial proxies and methane production.
Main Results:
- Principal components derived from rumen metagenome data showed significant heritability (~0.30) controlled by the cow genome.
- Strong genetic correlations (≥0.70) were observed between the first principal component and methane production.
- Enteric methane production was positively associated with eukaryotic abundance (protozoa, fungi) within the rumen.
Conclusions:
- The study demonstrates the feasibility of using combined host and metagenomic data for breeding programs.
- Aggregated microbial variables can serve as effective proxies for selective breeding to reduce cattle methane emissions.
- Nanopore sequencing facilitates core rumen metagenome characterization for improved livestock sustainability.
