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Microbiota Analysis Using Two-step PCR and Next-generation 16S rRNA Gene Sequencing
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Computational methods for high-throughput comparative analyses of natural microbial communities.

Sarah P Preheim1, Allison R Perrotta, Jonathan Friedman

  • 1Biological Engineering, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA.

Methods in Enzymology
|September 25, 2013
PubMed
Summary

This study details best practices for analyzing microbial community surveys using ribosomal RNA (rRNA) gene sequencing. It guides researchers in transforming raw data into insights on diversity, taxonomic affiliation, and ecological roles.

Keywords:
16S ribosomal RNA surveycommunity distance metriccorrelation analysisdiversity estimatesoperational taxonomic units

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Area of Science:

  • Microbiology
  • Bioinformatics
  • Genomics

Background:

  • Metagenomics commonly uses ribosomal RNA (rRNA) gene sequencing for microbial community analysis.
  • 16S rRNA gene surveys reveal prokaryotic diversity, taxonomic affiliations, and ecological functions.
  • High-throughput sequencing has greatly expanded our understanding of uncultured organisms.

Purpose of the Study:

  • To outline best practices for comparative analyses of microbial community surveys.
  • To guide researchers in transforming raw sequencing data into meaningful units for analysis.
  • To explain methods for assessing microbial diversity, community distances, and species associations.

Main Methods:

  • Focuses on comparative analyses of microbial community surveys.
  • Explains data transformation from raw sequencing reads to analytical units.
  • Details calculation of sample diversity and community distance metrics.
  • Describes methods for identifying species-metadata associations and inter-species correlations.
  • Utilizes data from next-generation sequencing platforms, specifically the Illumina platform.

Main Results:

  • Provides a framework for robust analysis of microbial community data.
  • Enables deeper insights into microbial ecology and function.
  • Facilitates discovery of relationships between microbial communities and their environments.

Conclusions:

  • Standardized analysis practices enhance the reliability and comparability of metagenomic studies.
  • Effective data analysis is crucial for uncovering the ecological significance of microbial communities.
  • This chapter serves as a guide for researchers, particularly those new to the field, using Illumina sequencing data.