Harnessing meta-omics to unveil and mitigate methane emissions in ruminants: Integrative approaches and future directions.

Sci Total Environ

Beijing Key Laboratory of Dairy Cow Nutrition, College of Animal Science and Technology, Beijing University of Agriculture, Beijing 102206, China. Electronic address:

Published: November 2024

Methane emissions from enteric fermentation present a dual challenge globally: they not only contribute significantly to atmospheric greenhouse gases but also represent a considerable energy loss for ruminant animals. Utilizing high-throughput omics technologies to analyze rumen microbiome samples (meta-omics, i.e., metagenomics, metatranscriptomics, metaproteomics, metabolomics) holds vast potential for uncovering the intricate interplay between diet, microbiota, and methane emissions in these animals. The primary obstacle is the effective integration of diverse meta-omic approaches and their broader application across different ruminant species. Genetic variability significantly impacts methane production in ruminants, suggesting that genomic selection could be a viable strategy to reduce emissions. While substantial research has been conducted on the microbiological aspects of methane production, there remains a critical need to delineate the specific genetic interactions between the host and its microbiome. Advancements in meta-omics technologies are poised to shed light on these interactions, enhancing our understanding of the genetic factors that govern methane output. This review explores the potential of meta-omics to accelerate genetic advancements that could lead to reduced methane emissions in ruminants. By employing a systems biology approach, the integration of various omics technologies allows for the identification of key genomic regions and genetic markers linked to methane production. These markers can then be leveraged in selective breeding programs to cultivate traits associated with lower emissions. Moreover, the review addresses current challenges in applying genomic selection for this purpose and discusses how omics technologies can overcome these obstacles. The systematic integration and analysis of diverse biological data provide deeper insights into the genetic underpinnings and overall biology of methane production traits in ruminants. Ultimately, this comprehensive approach not only aids in reducing the environmental impact of agriculture but also contributes to the sustainability and efficiency of livestock management.

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Source
http://dx.doi.org/10.1016/j.scitotenv.2024.175732DOI Listing

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