Metagenomic insights into the host–microbiome interaction for genetic mitigation of methane emissions in cattle
Year: 2026
Type: conference-abstract
Abstract: The agricultural sector contributes 56% of total methane emissions in the EU, with cattle responsible for about two-thirds of these emissions. Targeting rumen methanogenic microbes represents a promising and direct strategy for methane mitigation in livestock. Emerging evidence shows that methane production and methanogen abundance are partly under host genetic control, making selection for low-emitting animals with a favourable rumen microbiome a sustainable, long-term solution for climate-smart livestock breeding. To advance low-methane breeding, we investigated the genetic parameters of methane emissions and the host control of the rumen microbiome using data from 500 Holstein cows. All cows were genotyped using a 70K SNP array, and methane emissions were measured using sniffers installed in automatic milking systems. Both 16S rRNA amplicon sequencing and whole-metagenome sequencing were applied to identify key microbial species, genes, and pathways, and to evaluate how microbiome information can improve the prediction of breeding values for methane. We observed, while metagenomic sequencing provides deeper insights into microbial functional potential, it tends to underestimate low-abundance taxa. Conversely, amplicon sequencing captures low-abundance methane-related species more effectively, although it is affected by biases from variable gene copy numbers and PCR amplification. Using the newly developed MetaMAG pipeline https://github.com/msatti123/MetaMAG_Explorer), we identified 111 novel microbial species, several of which participate in hydrogen-utilizing and fermentation pathways, including acetate, fumarate, succinate, and acetyl-CoA pathway. Notably, the succinate pathway emerged as a key mechanism that may redirect energy flow from CH4 formation toward propionate production, while the acetyl-CoA pathway supports acetate synthesis, both VFA that provide energy to the host animal. Preliminary analyses indicate that approximately half of the microbiome species (n = 3,493) exhibit heritable abundance patterns, with heritability estimates ranging from 0.05 to 0.56. Among these, 52 species belong to archaea. GWAS identified significant loci for 139 microbial species (p < 3.45 × 10–9), with most associated variants located in regulatory regions, suggesting that host control of the rumen microbiome is largely mediated through gene regulatory mechanisms. Statistical models were evaluated to estimate breeding values for methane emissions by integrating genetic and microbiome information. Furthermore, the models were used to quantify the relative contributions of host genetics and the rumen microbiome to the observed variation in methane emissions. Rumen microbiome explained 0.06-0.38% of the phenotypic variation in methane, though its genetic component was limited. Contribution of rumen microbiome to methane heritability was largest with 16S rRNA amplicon data compared to metagenome sequencing, suggesting that 16S rRNA amplicon data can be useful to incorporate into genomic prediction of methane. The prediction accuracy of methane was doubled when 16S rRNA amplicon data was added on top of genetic marker data. Amplicon-based microbiome profiles outperformed metagenomic data due to better detection of low-abundance taxa relevant to methanogenesis.
Language: English
Subfield: Animal Science and Zoology
Domain: Life Sciences
SDGs: Climate action, Zero hunger
Open Access status: green
OpenAlex ID: W7213382714