TY - JOUR

T1 - Symposium review

T2 - Mining metagenomic and metatranscriptomic data for clues about microbial metabolic functions in ruminants1

AU - Li, Fuyong

AU - Neves, Andre L.A.

AU - Ghoshal, Bibaswan

AU - Guan, Le Luo

N1 - Funding Information: We thank the Alberta Livestock and Meat Agency (Edmonton, AB, Canada) for their grant support (no. 2013R029R). We also appreciate the financial support to F. Li from the Alberta Innovates-Technology Futures Graduate Student Scholarship and the Natural Sciences and Engineering Research Council of Canada (NSERC; Ottawa, ON, Canada) discovery grant for L. L. Guan. Publisher Copyright: © 2018 American Dairy Science Association

PY - 2018/6

Y1 - 2018/6

N2 - 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.

AB - 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.

KW - metagenomics

KW - metatranscriptomics

KW - microbiome

KW - microbiota

KW - rumen

U2 - 10.3168/jds.2017-13356

DO - 10.3168/jds.2017-13356

M3 - Journal article

C2 - 29274958

AN - SCOPUS:85038928587

VL - 101

SP - 5605

EP - 5618

JO - Journal of Dairy Science

JF - Journal of Dairy Science

SN - 0022-0302

IS - 6

ER -