Use of short-read RNA-Seq data to identify transcripts that can translate novel ORFs

Abstract

Identification of as of yet unannotated or undefined novel open reading frames (nORFs) and exploration of their functions in multiple organisms has revealed that vast regions of the genome have remained unexplored or 'hidden'. Present within both protein-coding and noncoding regions, these nORFs signify the presence of a much more diverse proteome than previously expected. Given the need to study nORFs further, proper identification strategies must be in place, especially because they cannot be identified using conventional gene signatures. Although Ribo-Seq and proteogenomics are frequently used to identify and investigate nORFs, in this study, we propose a workflow for identifying nORF containing transcripts using our precompiled database of nORFs with translational evidence, using sample transcript information. Further, we discuss the potential uses of this identification, the caveats involved in such a transcript identification and finally present a few representative results from our analysis of naive mouse B and T cells, human post-mortem brain and cichlid fish transcriptome. Our proposed workflow can identify noncoding transcripts that can potentially translate intronic, intergenic and several other classes of nORFs. One-line summary:A systematic workflow to identify nORF containing transcripts using sample transcript information.

Reference: OC/EFSA/GMO/2021/01: Refinement of the Risk Assessment Methodology for Open Reading Frames in GMO Applications

“…In more recent years, it was found that specific workflows can identify noncoding transcripts that can potentially translate intronic, intergenic and several other classes of ORFs (Fickett, 1994;Erady, Puntambekar and Prabakaran, 2020). A pipeline focused on genes coding for transcription factors was shown to increase isoform detection by an order of magnitude when compared to unenriched samples.…”