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Microbiota Analysis Using Two-step PCR and Next-generation 16S rRNA Gene Sequencing
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RiboTagger: fast and unbiased 16S/18S profiling using whole community shotgun metagenomic or metatranscriptome
Chao Xie1,2, Chin Lui Wesley Goi3, Daniel H Huson4,5
1Singapore Centre for Environmental Life Sciences Engineering, National University of Singapore, Singapore, 117456, Singapore. xiechaos@gmail.com.
BMC Bioinformatics
|February 4, 2017
Summary
RiboTagger efficiently extracts small subunit ribosomal RNA (SSU) sequences from large shotgun sequencing datasets. This method enables unbiased taxonomic profiling of microbial communities across all domains of life.
Area of Science:
- Microbiology
- Bioinformatics
- Genomics
Background:
- Small subunit ribosomal RNA (SSU) amplicon sequencing (16S or 18S) is standard for microbial community taxonomic profiling.
- Environmental shotgun sequencing typically focuses on functional analysis, but contains abundant SSU sequences.
- These SSU sequences in shotgun data can be leveraged for unbiased taxonomic analysis.
Purpose of the Study:
- To introduce RiboTagger, a novel program for extracting SSU sequences from shotgun data.
- To enable high-throughput, unbiased taxonomic profiling of microbial communities.
Main Methods:
- Development of RiboTagger software.
- Identification and extraction of taxonomically informative ribotags from SSU genes.
- Application to large shotgun sequencing datasets.
Main Results:
- RiboTagger effectively identifies and extracts SSU sequences from shotgun metagenomic data.
- The program demonstrates high sensitivity and specificity in taxonomic assignment.
- RiboTagger offers a significant speed advantage over existing methods.
Conclusions:
- RiboTagger facilitates rapid recovery of SSU-RNA sequences from complex microbial communities.
- The tool supports taxonomic analysis across all three domains of life.
- RiboTagger provides a faster and efficient alternative for SSU-based taxonomic profiling using shotgun data.
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