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Rumen metagenome as a genomic selection target to reduce enteric methane emissions.

B J Sepulveda1, O González-Recio2, A J Chamberlain1

  • 1Agriculture Victoria Research, AgriBio, Centre for AgriBioscience, Bundoora, VIC 3083, Australia; School of Applied Systems Biology, La Trobe University, Bundoora, VIC 3083, Australia.

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Summary

Reducing methane emissions from cattle is crucial for climate and efficiency. Scientists identified specific rumen microbes that can be used in breeding programs to significantly lower enteric methane emissions (EME) in dairy cows.

Keywords:
genomic selectionmetagenomicsmethane productionrumen microorganisms

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Area of Science:

  • Animal Science
  • Microbiology
  • Environmental Science

Background:

  • Ruminant digestion produces methane, a greenhouse gas that impacts global warming and feed efficiency.
  • Measuring enteric methane emissions (EME) on commercial farms is difficult and expensive.
  • Varied measurement technologies lead to poor correlations, hindering population comparisons.

Purpose of the Study:

  • To identify reliable metagenomic features in the rumen for selecting cattle with lower methane emissions.
  • To develop methods for reducing EME through genomic selection using these microbial features.
  • To establish a common core of rumen features for cross-population EME prediction.

Main Methods:

  • Sequencing of rumen metagenomes from dairy cows in Australia and Spain.
  • Identification of a core set of metagenomic features present in over 90% of animals.
  • Development of breeding core subsets for indirect selection on EME.
  • Estimation of EME reduction through direct, indirect, and combined selection strategies.

Main Results:

  • A core group of rumen metagenomic features was identified across diverse cattle populations.
  • Indirect selection using breeding core subsets showed greater EME reduction potential than direct selection.
  • Combined selection strategies, including principal components and microbial genera, further enhanced EME reduction.
  • An R Shiny application was developed to estimate potential EME reductions.

Conclusions:

  • Rumen metagenome features can serve as effective selection criteria for genomic selection programs to reduce EME.
  • These features offer a consistent method for predicting EME across different measurement systems and populations.
  • A global effort is recommended to validate a common core of EME-associated rumen features for widespread application.