Transcript mapping based on dRNA-seq data

BMC Bioinformatics. 2014 Apr 29;15:122. doi: 10.1186/1471-2105-15-122.


Background: 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.

Results: 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.

Conclusions: 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.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Algorithms*
  • Gene Expression Profiling / methods*
  • Genomics
  • Helicobacter pylori / genetics
  • Operon
  • Sequence Analysis, RNA / methods*
  • Transcription Initiation Site
  • Untranslated Regions


  • Untranslated Regions