ArticleBMC genomics2015
The rumen microbial metagenome associated with high methane production in cattle.
Article in BMC genomics, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 206 papers, 1 of them a synthesis that pooled it.
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Who cites it
206 citing papers in PubMed, 1 synthesis or guideline pooled it, 412 citations in OpenAlex.
- Genomic dissection of methane emission traits in cattle: A meta-GWAS and heritability analysis across populations.PloS one · 2026Pooled it
- Methane emissions in beef cattle: A review of measurements and mitigation strategies.Veterinary and animal science · 2026Review
- Can seaweed mitigate methane from cows on a global scale?Proceedings of the National Academy of Sciences of the United States of America · 2026Article
- The Dietary Inclusion of Corn and Peas Affects the Fecal Bacterial Diversity and Composition of Sarda Goats.Animals : an open access journal from MDPI · 2026Article
- Optimisation of selection for methane mitigation by integrating production traits with ruminal microbiome-driven breeding in beef cattle.Genetics, selection, evolution : GSE · 2026Article
- From Composition to Function: Lime Essential Oil (Molecules (Basel, Switzerland) · 2026Article
- Effects of Dietary NFC/NDF and Allicin Supplementation on Serum Electrolytes, Nitrogen and Phosphorus Excretion, and Fecal Microbiota in Beef Bulls.Animals : an open access journal from MDPI · 2026Article
- Unexpected Microbial and Genetic Diversity in the Gut of Chinese Giant Salamander.Integrative zoology · 2026Article
- Differential rumen and hindgut microbiome and metabolome in Holstein female calves with divergent feed efficiency.Microbiome · 2026Article
- The Hungate1000 prokaryotic culture collection encodes a wide variety of bacteriocins.mSystems · 2026Article
- Variations in methane emissions from dairy cows: associations with rumen microbial synergy and metabolic pathway divergence.Journal of animal science and biotechnology · 2026Article
- Article
- Effects of Dietary Concentrate-to-Roughage Ratio on Rumen Microbiota, Functional Profiles, and Fermentation Characteristics in Yak.Microorganisms · 2026Article
- A bibliometric review about scientific trends and advances on residual feed intake (RFI) and feed efficiency in ruminants.Tropical animal health and production · 2026Review
- Harnessing gastrointestinal microbial co-association networks to predict feed efficiency and methane emissions across beef and dairy cattle.Microbial genomics · 2026Article
- In Vitro Evaluation of Spearmint Essential Oil (Animals : an open access journal from MDPI · 2026Article
- Article
- Impact of chitosan supplementation on metabolomic profiles and microbial community dynamics in total mixed ration silage and rumen fluid.Animal bioscience · 2026Article
- Metagenomic analysis of fecal microbiomes reveals genetic potential for diverse hydrogen management strategies in marsupials.mSystems · 2026Article
- Rumen Microbial Composition and Fermentation Variables Associated with Methane Production in Italian Simmental Dairy Cows.Animals : an open access journal from MDPI · 2026Article
146 more citing papers are in PubMed but not listed here.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
9 authors at 3 institutions in 1 country.
Funding
Abstract
backgroundMethane represents 16 % of total anthropogenic greenhouse gas emissions. It has been estimated that ruminant livestock produce ca. 29 % of this methane. As individual animals produce consistently different quantities of methane, understanding the basis for these differences may lead to new opportunities for mitigating ruminal methane emissions. Metagenomics is a powerful new tool for understanding the composition and function of complex microbial communities. Here we have applied metagenomics to the rumen microbial community to identify differences in the microbiota and metagenome that lead to high- and low-methane-emitting cattle phenotypes.
methodsFour pairs of beef cattle were selected for extreme high and low methane emissions from 72 animals, matched for breed (Aberdeen-Angus or Limousin cross) and diet (high or medium concentrate). Community analysis was carried out by qPCR of 16S and 18S rRNA genes and by alignment of Illumina HiSeq reads to the GREENGENES database. Total genomic reads were aligned to the KEGG genes databasefor functional analysis.
resultsDeep sequencing produced on average 11.3 Gb per sample. 16S rRNA gene abundances indicated that archaea, predominantly Methanobrevibacter, were 2.5× more numerous (P = 0.026) in high emitters, whereas among bacteria Proteobacteria, predominantly Succinivibrionaceae, were 4-fold less abundant (2.7 vs. 11.2 %; P = 0.002). KEGG analysis revealed that archaeal genes leading directly or indirectly to methane production were 2.7-fold more abundant in high emitters. Genes less abundant in high emitters included acetate kinase, electron transport complex proteins RnfC and RnfD and glucose-6-phosphate isomerase. Sequence data were assembled de novo and over 1.5 million proteins were annotated on the subsequent metagenome scaffolds. Less than half of the predicted genes matched matched a domain within Pfam. Amongst 2774 identified proteins of the 20 KEGG orthologues that correlated with methane emissions, only 16 showed 100 % identity with a publicly available protein sequence.
conclusionsThe abundance of archaeal genes in ruminal digesta correlated strongly with differing methane emissions from individual animals, a finding useful for genetic screening purposes. Lower emissions were accompanied by higher Succinovibrionaceae abundance and changes in acetate and hydrogen production leading to less methanogenesis, as similarly postulated for Australian macropods. Large numbers of predicted protein sequences differed between high- and low-methane-emitting cattle. Ninety-nine percent were unknown, indicating a fertile area for future exploitation.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.