We studied the genomic positions of 38,129 putative ncRNAs from the RIKEN dataset in relation to protein-coding genes. We found that the dataset has 41% sense, 6% antisense, 24% intronic and 29% intergenic transcripts. Interestingly, 17,678 (47%) of the FANTOM3 transcripts were found to potentially be internally primed from longer transcripts. The highest fraction of these transcripts was found among the intronic transcripts and as many as 77% or 6929 intronic transcripts were both internally primed and unspliced. We defined a filtered subset of 8535 transcripts that did not overlap with protein-coding genes, did not contain ORFs longer than 100 residues and were not internally primed. This dataset contains 53% of the FANTOM3 transcripts associated to known ncRNA in RNAdb and expands previous similar efforts with 6523 novel transcripts. This bioinformatic filtering of the FANTOM3 non-coding dataset has generated a lead dataset of transcripts without signs of being artefacts, providing a suitable dataset for investigation with hybridization-based techniques.
Keywords: Computational Biology; Databases, Genetic; EST; Expressed Sequence Tags; FANTOM3; Genome, Human; Humans; Introns; ncRNA; Non-coding RNA; Proteins; RIKEN; RNA, Messenger; RNA, Untranslated; Sequence Analysis, RNA; snoRNA; Transcription, Genetic