Discovery and characterization of new transcripts from RNA-seq data in mouse CD4+ T cells

Despite the routine application of RNA-seq technology to profile cellular transcriptomes and report novel splice variants, the identification and validation of new transcripts remain underexplored. We prepared two RNA-seq libraries from resting and T cell receptor-stimulated mouse CD4+ T cells. Transcripts unknown to Ensembl represent as much as 5% of the assembled transcripts and are robustly expressed but do not show the same degree of evolutionary conservation or exon distribution of known transcripts, or of novel splice isoforms. Here we present a straightforward and generally applicable computational/experimental workflow that we apply to characterise and experimentally validate 23 mouse transcripts from the RNA-seq libraries that were uncharacterised by Ensembl. Of these, 7 are not supported by any transcript database and therefore are likely to encode new messages. Furthermore, we also report the fast up-regulation of important regulatory molecules only 4 h post-stimulation of the T cell receptor, which calls for a more detailed investigation into early CD4+ T cell activation mechanisms.

► A computational/experimental workflow to characterise new transcripts from RNA-seq.
► Transcripts unknown to Ensembl are 5% of all assembled transcripts in CD4+ T cells.
► Unknown transcripts are not evolutionarily conserved but harbor identifiable domains.
► Identified and experimentally validated 23 mouse transcripts.
► 7 are not supported by any public EST/mRNA databases and hence are new messages.