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Depletion of Ribosomal RNA for Mosquito Gut Metagenomic RNA-seq
Published on: April 7, 2013
DepStep: An Efficient One-Step rRNA Depletion Workflow for RNA Sequencing in Non-model Organisms
Suleman M Qasim1,2, Peter L Sarin1,3
1RNAcious Laboratory, Department of Molecular and Integrative Biosciences, Faculty of Biological and Environmental Sciences, University of Helsinki, Helsinki, Finland.
Bio-Protocol
|August 13, 2026
Summary
DepStep is a new workflow for one-step ribosomal RNA (rRNA) depletion in prokaryotic RNA sequencing (RNA-seq). This cost-effective method efficiently removes rRNA, increasing coding DNA sequence (CDS) reads for better transcriptomic analysis.
Area of Science:
- Molecular Biology
- Genomics
- Bioinformatics
Background:
- RNA sequencing (RNA-seq) is crucial for transcriptomics but requires efficient ribosomal RNA (rRNA) depletion, especially for prokaryotes lacking poly(A) tails.
- Commercial rRNA depletion kits can be proprietary and inefficient for non-model organisms, limiting broad application.
Purpose of the Study:
- To develop and validate DepStep, a cost-effective, one-step rRNA depletion workflow for prokaryotic RNA-seq.
- To provide guidelines for designing species-specific biotinylated antisense probes for rRNA removal.
Main Methods:
- DepStep utilizes species-specific biotinylated antisense probes for targeted rRNA hybridization and removal.
- RNA-seq libraries of *Shewanella glacialimarina* TZS-4T were prepared using DepStep and a commercial kit for benchmarking.
Main Results:
- DepStep achieved >98.6% rRNA depletion, yielding >80% coding DNA sequence (CDS) reads.
- DepStep demonstrated a 3x lower cost-per-sample compared to the commercial kit.
- DepStep performed comparably to commercial products in rRNA removal efficiency.
Conclusions:
- DepStep offers a simple, cost-effective, and efficient alternative for rRNA depletion in prokaryotic RNA-seq, particularly for non-model species.
- The workflow provides a valuable tool for budget-conscious laboratories seeking to enhance transcriptomic data quality.
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