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Transcript mapping based on dRNA-seq data

Thorsten Bischler12, Matthias Kopf1 and Björn Voß1*

Author Affiliations

1 Genetics & Experimental Bioinformatics, Institute for Biology 3, Faculty of Biology, Albert-Ludwigs-University Freiburg, Schänzlestr. 1, 79104 Freiburg, Germany

2 Julius-Maximilians-University Würzburg, Institute for Molecular Infection Biology, Josef-Schneider-Str. 2/D15, 97080 Würzburg, Germany

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BMC Bioinformatics 2014, 15:122  doi:10.1186/1471-2105-15-122

Published: 29 April 2014



RNA-seq and its variant differential RNA-seq (dRNA-seq) are today routine methods for transcriptome analysis in bacteria. While expression profiling and transcriptional start site prediction are standard tasks today, the problem of identifying transcriptional units in a genome-wide fashion is still not solved for prokaryotic systems.


We present RNASEG, an algorithm for the prediction of transcriptional units based on dRNA-seq data. A key feature of the algorithm is that, based on the data, it distinguishes between transcribed and un-transcribed genomic segments. Furthermore, the program provides many different predictions in a single run, which can be used to infer the significance of transcriptional units in a consensus procedure. We show the performance of our method based on a well-studied dRNA-seq data set for Helicobacter pylori.


With our algorithm it is possible to identify operons and 5’- and 3’-UTRs in an automated fashion. This alleviates the need for labour intensive manual inspection and enables large-scale studies in the area of comparative transcriptomics.

RNA-seq; Differential RNA-seq; Segmentation; Transcriptional unit; Transcriptome; Transcriptional start site; Dynamic programming