Detection and Mitigation of Spurious Antisense RNA-seq Reads with RoSA

Kira Mourão, Nicholas J. Schurch, Radoslaw Lukoszek, Kimon Froussios, Katarzyna Mackinnon, Celine Duc, Gordon Simpson (Lead / Corresponding author), Geoffrey Barton (Lead / Corresponding author)

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Motivation: Antisense transcription is known to have a range of impacts on sense gene expression, including (but not limited to) impeding transcription initiation, disrupting post-transcriptional processes, and enhancing, slowing, or even preventing transcription of the sense gene. Strand-specific RNA-Seq protocols preserve the strand information of the original RNA in the data, and so can be used to identify where antisense transcription may be implicated in regulating gene expression. However, our analysis of 199 strand-specific RNA-Seq experiments reveals that spurious antisense reads are often present in these datasets at levels greater than 1% of sense gene expression levels. Furthermore, these levels can vary substantially even between replicates in the same experiment, potentially disrupting any downstream analysis, if the incorrectly assigned antisense counts dominate the set of genes with high antisense transcription levels. Currently, no tools exist to detect or correct for this spurious antisense signal.

Results: Our tool, RoSA (Removal of Spurious Antisense), detects the presence of high levels of spurious antisense read alignments in strand-specific RNA-Seq datasets. It uses incorrectly spliced reads on the antisense strand and/or ERCC spike-ins (if present in the data) to calculate both global and gene-specific antisense correction factors. We demonstrate the utility of our tool to filter out spurious antisense transcript counts in an Arabidopsis thaliana RNA-Seq experiment.
Original languageEnglish
Article number819
Pages (from-to)1-7
Number of pages7
JournalF1000 Research
Early online date7 Jun 2019
Publication statusPublished - 7 Jun 2019


  • RNA-seq
  • antisense expression
  • gene expression
  • Arabidopsis thaliana


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