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Updated: May 20, 2026

Microbiota Analysis Using Two-step PCR and Next-generation 16S rRNA Gene Sequencing
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Microbiota Analysis Using Two-step PCR and Next-generation 16S rRNA Gene Sequencing

Published on: October 15, 2019

High throughput whole rumen metagenome profiling using untargeted massively parallel sequencing.

Elizabeth M Ross1, Peter J Moate, Carolyn R Bath

  • 1Biosciences Research Division, Department of Primary Industries, Bundoora, VIC 3083, Australia. elizabeth.ross@dpi.vic.gov.au

BMC Genetics
|July 4, 2012
PubMed
Summary

Researchers developed a new method using massively parallel sequencing (MPS) to create rumen metagenome profiles. Rumen microbial communities were repeatable within cows, but fecal samples did not predict rumen profiles.

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Purifying the Impure: Sequencing Metagenomes and Metatranscriptomes from Complex Animal-associated Samples

Published on: December 22, 2014

Area of Science:

  • Microbial ecology
  • Metagenomics
  • Animal science

Background:

  • Rumen microorganism variation in cattle is linked to feed efficiency and methane emissions.
  • Untargeted massively parallel sequencing (MPS) can improve resolution in studying rumen microbial communities.
  • Developing a robust method for rumen metagenome profiling is crucial for understanding these variations.

Purpose of the Study:

  • To develop a method for generating "rumen metagenome profiles" using MPS.
  • To assess the repeatability of these profiles within individual cows.
  • To determine if rumen metagenome profiles can be predicted from fecal samples.

Main Methods:

  • Utilized untargeted massively parallel sequencing (MPS) data.
  • Developed a quantitative profiling method based on read alignment to a reference metagenome.
  • Compared microbial community profiles from rumen fluid and fecal samples across multiple cows.

Main Results:

  • Rumen metagenome profiles were highly repeatable within individual cows, irrespective of sampling location (P < 0.00001).
  • The repeatability estimate was 9%, with a high standard error due to the small sample size.
  • Fecal microbial profiles were not predictive of rumen microbial profiles; rumen and fecal communities differed significantly within the same animal.

Conclusions:

  • A simple, high-throughput method for metagenome profiling was successfully developed and applied.
  • The method enables the assessment of whole metagenome similarity using widely available freeware.
  • This approach is valuable for exploring and comparing complex microbial communities, particularly in the rumen.