Abstract
BackgroundTaxonomic profiling of microbial communities is often performed using small subunit ribosomal RNA (SSU) amplicon sequencing (16S or 18S), while environmental shotgun sequencing is often focused on functional analysis. Large shotgun datasets contain a significant number of SSU sequences and these can be exploited to perform an unbiased SSU--based taxonomic analysis.ResultsHere we present a new program called RiboTagger that identifies and extracts taxonomically informative ribotags located in a specified variable region of the SSU gene in a high-throughput fashion.ConclusionsRiboTagger permits fast recovery of SSU-RNA sequences from shotgun nucleic acid surveys of complex microbial communities. The program targets all three domains of life, exhibits high sensitivity and specificity and is substantially faster than comparable programs.
Highlights
Taxonomic profiling of microbial communities is often performed using small subunit ribosomal RNA (SSU) amplicon sequencing (16S or 18S), while environmental shotgun sequencing is often focused on functional analysis
After examining all bacterial and archaeal 16S sequences in the RDP database [20] we designed a combination of probe patterns and Position Specific Scoring Matrices (PSSM) to recognize the conserved site immediately outside a hypervariable region as recognition sequence (RS), which we describe as a universal recognition profile (Fig. 1)
Each ribotag was assigned a taxon based on the set of SSU sequences that contain it, using the majority taxon in the case of discordance
Summary
We have developed software for the fast recovery of SSU-RNA sequences from shotgun nucleic acid surveys of complex microbial communities. Our code is fast, completing an analysis of about 40 M reads within 1.5 h, and will output an annotated matrix of read counts that can be used for downstream community profiling analysis with minimal further processing. Additional, we note that our approach avoids the use of OTU generation, which recent analyses suggest may carry significant advantages in resolving intra-community dynamics for some classes of experimental design, such as time series experiments [25]. Ethics approval and consent to participate Not applicable. Author details 1Singapore Centre for Environmental Life Sciences Engineering, National University of Singapore, Singapore 117456, Singapore. Author details 1Singapore Centre for Environmental Life Sciences Engineering, National University of Singapore, Singapore 117456, Singapore. 2Centre for Bioinformatics, Tuebingen University, Tuebingen 72076, Germany. 3Life Sciences Institute, National University of Singapore, Singapore 117456, Singapore. 4Department of Biochemistry, Yong Loo Lin School of Medicine, National University of Singapore, Singapore 117596, Singapore. 5Current address: Human Longevity Inc, Singapore, Singapore
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