Symposium review: Mining metagenomic and metatranscriptomic data for clues about microbial metabolic functions in ruminants

J Dairy Sci. 2018 Jun;101(6):5605-5618. doi: 10.3168/jds.2017-13356. Epub 2017 Dec 21.

Abstract

Metagenomics and metatranscriptomics can capture the whole genome and transcriptome repertoire of microorganisms through sequencing total DNA/RNA from various environmental samples, providing both taxonomic and functional information with high resolution. The unique and complex rumen microbial ecosystem is receiving great research attention because the rumen microbiota coevolves with the host and equips ruminants with the ability to convert cellulosic plant materials to high-protein products for human consumption. To date, hundreds to thousands of microbial phylotypes have been identified in the rumen using culture-independent molecular-based approaches, and genomic information of rumen microorganisms is rapidly accumulating through the single genome sequencing. However, functional characteristics of the rumen microbiome have not been well described because there are numerous uncultivable microorganisms in the rumen. The advent of metagenomics and metatranscriptomics along with advanced bioinformatics methods can help us better understand mechanisms of the rumen fermentation, which is vital for improving nutrient utilization and animal productivity. Therefore, in this review, we summarize a general workflow to conduct rumen metagenomics and metatranscriptomics and discuss how the data can be interpreted to be useful information. Moreover, we review recent literatures studying associations between the rumen microbiome and host phenotypes (e.g., feed efficiency and methane emissions) using these approaches, aiming to provide a useful guide to include studying the rumen microbiome as one of the research objectives using these 2 approaches.

Keywords: metagenomics; metatranscriptomics; microbiome; microbiota; rumen.

Publication types

  • Review

MeSH terms

  • Animals
  • Gene Expression Profiling
  • Metagenomics*
  • Methane / metabolism
  • Microbiota
  • Rumen / microbiology*
  • Ruminants*
  • Transcriptome

Substances

  • Methane