Noncoding RNAs (ncRNAs) are transcripts that are not translated to proteins but act as functional RNAs. Several well-known ncRNAs such as transfer RNAs or ribosomal RNAs can be found throughout the tree of life. They fulfill central functions in the cell and thus have been studied for a long time.
However, over the past years a few key discoveries have shown that ncRNAs have a much richer functional spectrum than anticipated1
. The discovery of microRNAs for example changed our view of how genes are regulated2,3
. Another surprising observation revealed by high-throughput methods is that in human 90% of the genome is transcribed at some time in some tissue4
. Although the full extent and functional consequences of this pervasive transcription remains highly controversial5,6
, the vast amount of transcripts produced suggests that many important ncRNA functions are yet to be discovered.
In particular, long noncoding RNAs (lncRNAs) – transcripts that can be several kilobases in length, spliced and processed like mRNAs but lack obvious coding potential – seem to be a rich source of novel functions7
. All these ncRNAs have been suggested to form a hidden layer of regulation that is necessary to establish the complexity of eukaryotic genomes8
Prokaryotic genomes also contain many surprises. Riboswitches9
, small regulatory RNAs10
, or completely unknown structured RNAs11
suggest that ncRNAs also form an important functional layer in bacteria.
Understanding the function of ncRNAs – in particular in the age of high-throughput experiments – is clearly not possible without computational approaches. Algorithms to annotate, organize and functionally characterize ncRNAs are of increasing relevance. In this paper, we give a broad overview of programs and resources to analyze many different aspects of ncRNAs ().
Outline of the main topics covered in this review. Many topics overlap, depend on each other or share similar concepts. The most important of these interconnections are shown by arrows.