Computational methods to discover and quantify isoforms with alternative untranslated regions

University of London researchers discuss the importance of defining the untranslated parts of transcripts, and present a number of computational approaches for the discovery and quantification of alternative transcription start and poly-adenylation events in high-throughput transcriptomic data. The fate of eukaryotic transcripts is closely linked to their untranslated regions, which are determined by the position at which transcription starts and ends at a genomic locus. Although the extent of alternative transcription starts and alternative poly-adenylation sites has been revealed by sequencing methods focused on the ends of transcripts, the application of these methods is not yet widely adopted by the community. The researchers suggest that computational methods applied to standard high-throughput technologies are a useful, albeit less accurate, alternative to the expertise-demanding 5′ and 3′ sequencing and they are the only option for analysing legacy transcriptomic data. They review these methods here, focusing on technical challenges and arguing for the need to include better normalization of the data and more appropriate statistical models of the expected variation in the signal.

Schematic representation of alternative transcription start site
and alternative poly-adenylation events


The presence of two alternative TSS and two alternative PAS creates four possible transcripts from the same genomic locus (top). TSS1 creates transcripts with longer 5′ UTRs compared with TSS2, whereas PAS1 creates transcripts with shorter 3′UTRs compared with PAS2. The use of alternative TSS/PAS regulates the inclusion or exclusion of functional elements such as upstream open reading frames (uORFs) in the 5′ UTR or miRNA and protein-binding sites in the 3′ UTR. The coding regions (light gray boxes and gray lines) may or may not be different between the transcripts, depending on the action of alternative splicing. In this review we are only concerned with differences in the untranslated regions (blue and yellow).

Szkop KJ, Nobeli I. (2017) Untranslated Parts of Genes Interpreted: Making Heads or Tails of High-Throughput Transcriptomic Data via Computational Methods: Computational methods to discover and quantify isoforms with alternative untranslated regions. Bioessays [Epub ahead of print]. [abstract]

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