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Updated: Mar 27, 2026

Improving Small RNA-seq: Less Bias and Better Detection of 2'-O-Methyl RNAs
Published on: September 16, 2019
DETECTION OF BACTERIAL SMALL TRANSCRIPTS FROM RNA-SEQ DATA: A COMPARATIVE ASSESSMENT
Lourdes Peña-Castillo1, Marc Grüell, Martin E Mulligan
1Department of Computer Science, Memorial University of Newfoundland, St. John's, NL, Canada2Department of Biology, Memorial University of Newfoundland, St. John's, NL, Canada, lourdes@mun.ca.
Abstract:
Small non-coding RNAs (sRNAs) are regulatory RNA molecules that have been identified in a multitude of bacterial species and shown to control numerous cellular processes through various regulatory mechanisms. In the last decade, next generation RNA sequencing (RNA-seq) has been used for the genome-wide detection of bacterial sRNAs. Here we describe sRNA-Detect, a novel approach to identify expressed small transcripts from prokaryotic RNA-seq data. Using RNA-seq data from three bacterial species and two sequencing platforms, we performed a comparative assessment of five computational approaches for the detection of small transcripts. We demonstrate that sRNA-Detect improves upon current standalone computational approaches for identifying novel small transcripts in bacteria.
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