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RIBO-seq in Bacteria: a Sample Collection and Library Preparation Protocol for NGS Sequencing
12:05

RIBO-seq in Bacteria: a Sample Collection and Library Preparation Protocol for NGS Sequencing

Published on: August 7, 2021

How deep is deep enough for RNA-Seq profiling of bacterial transcriptomes?

Brian J Haas1, Melissa Chin, Chad Nusbaum

  • 1Genome Sequencing and Analysis Program, The Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA.

BMC Genomics
|December 29, 2012
PubMed
Summary

Determining RNA sequencing (RNA-Seq) read depth for bacterial transcriptomes is crucial. This study shows typical sequencing depths often exceed needs, potentially introducing spurious data, and offers guidance for optimal experimental design.

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RIBO-seq in Bacteria: a Sample Collection and Library Preparation Protocol for NGS Sequencing
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Rup (RNA-seq Usability Assessment Pipeline) - Quality Control for Bulk RNA-seq Experiments in Eukaryotes
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Area of Science:

  • Microbiology
  • Genomics
  • Bioinformatics

Background:

  • Bacterial transcriptomics research heavily relies on high-throughput sequencing of cDNA libraries (RNA-Seq).
  • A key challenge is determining the necessary number of reads per sample for accurate transcript detection and quantification across a wide abundance range.

Purpose of the Study:

  • To systematically examine the impact of varying RNA-Seq read counts on bacterial transcriptome profiling.
  • To assess how sequencing depth affects the comparison of gene expression between bacterial samples.

Main Methods:

  • Systematic analysis of RNA-Seq data from bacterial samples with varying read depths.
  • Evaluation of transcript detection and differential gene expression analysis at different sequencing coverages.

Main Results:

  • Current RNA-Seq read numbers frequently exceed requirements for saturating bacterial transcriptomes in monoculture.
  • Increased sequencing depth can lead to the detection of spurious cDNAs and genomic DNA contamination.
  • Sufficient transcript detection and identification of differentially expressed genes are achievable even with multiplexed libraries in a single lane.

Conclusions:

  • Provides a framework for researchers to establish appropriate sequencing depths for bacterial RNA-Seq studies.
  • Highlights the potential for over-sequencing and the introduction of artifacts.
  • Offers practical guidance for optimizing RNA-Seq experimental design in bacterial species.