RNAcode: robust discrimination of coding and noncoding regions in comparative sequence data

RNA. 2011 Apr;17(4):578-94. doi: 10.1261/rna.2536111. Epub 2011 Feb 28.


With the availability of genome-wide transcription data and massive comparative sequencing, the discrimination of coding from noncoding RNAs and the assessment of coding potential in evolutionarily conserved regions arose as a core analysis task. Here we present RNAcode, a program to detect coding regions in multiple sequence alignments that is optimized for emerging applications not covered by current protein gene-finding software. Our algorithm combines information from nucleotide substitution and gap patterns in a unified framework and also deals with real-life issues such as alignment and sequencing errors. It uses an explicit statistical model with no machine learning component and can therefore be applied "out of the box," without any training, to data from all domains of life. We describe the RNAcode method and apply it in combination with mass spectrometry experiments to predict and confirm seven novel short peptides in Escherichia coli and to analyze the coding potential of RNAs previously annotated as "noncoding." RNAcode is open source software and available for all major platforms at http://wash.github.com/rnacode.

MeSH terms

  • Algorithms
  • Animals
  • Base Pairing
  • Drosophila melanogaster / genetics
  • Escherichia coli / genetics
  • Genetic Code*
  • Mass Spectrometry
  • Molecular Sequence Annotation
  • Molecular Sequence Data
  • Open Reading Frames
  • Peptides / genetics
  • RNA, Messenger / genetics*
  • RNA, Untranslated / genetics
  • Sequence Alignment / methods*
  • Sequence Analysis, RNA / methods*
  • Software*


  • Peptides
  • RNA, Messenger
  • RNA, Untranslated