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Updated: May 21, 2026
07:21
Tick Microbiome Characterization by Next-Generation 16S rRNA Amplicon Sequencing
Published on: August 25, 2018
Optimizing read mapping to reference genomes to determine composition and species prevalence in microbial communities
John Martin1, Sean Sykes, Sarah Young
1The Genome Institute, Washington University School of Medicine, St Louis, Missouri, United States of America.
Plos One
|June 22, 2012
Summary
The Human Microbiome Project (HMP) developed an efficient alignment strategy for analyzing metagenomic data. This method accurately maps microbial sequences, crucial for understanding the human microbiome.
Area of Science:
- Microbiology
- Bioinformatics
- Genomics
Background:
- The Human Microbiome Project (HMP) aims to comprehensively characterize microbial communities across 18 body sites in healthy individuals.
- HMP generates extensive shotgun sequencing data, necessitating robust analysis strategies for accurate metagenomic community profiling.
Purpose of the Study:
- To evaluate and identify an optimal alignment strategy for analyzing HMP metagenomic data.
- To determine the best approach for mapping microbial sequences to reference genomes for accurate community composition analysis.
Main Methods:
- Six next-generation aligners were assessed using a known microbial community composition against a reference database.
- Aligner performance was evaluated based on speed, memory requirements, and mapping capabilities.
- Key parameters like alignment length and similarity thresholds were optimized to balance sensitivity and specificity.
Main Results:
- All tested aligners achieved high genome coverage (>97%) for adequately covered strains.
- Aligner performance varied significantly in terms of speed, memory usage, and database limitations.
- Constraining alignment length proved more critical for sensitivity than similarity, especially when dealing with closely related species.
Conclusions:
- An optimized alignment strategy was identified, enabling the mapping of over 3 terabases of microbial sequence against a large reference database efficiently.
- This strategy enhances the accuracy and feasibility of large-scale human microbiome research.
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