Untranslated Parts of Genes Interpreted: Making Heads or Tails of High‐Throughput Transcriptomic Data via Computational Methods

Abstract

In this review we highlight 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. We 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. We 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.

Detection of Differentially Expressed Cleavage Site Intervals Within 3′ Untranslated Regions Using CSI-UTR Reveals Regulated Interaction Motifs

“…For PolyA-Seq, the primer is modified to T 10 VN, allowing for shorter polyA tails and more favorable hybridization kinetics (Derti et al, 2012). More recent approaches have considered the use of these data for modeling polyadenylation sites (Ji et al, 2015; Szkop and Nobeli, 2017).…”

Profiling Alternative 3′ Untranslated Regions in Sorghum using RNA-seq Data

“…Type 4 programs detect sudden fluctuations of read density at the 3 end of mRNAs in order to model 3 UTR usage. Type 4 programs tend to identify 3 UTR shortening events and have more inaccurate predictions caused by the heterogeneity of read coverage and non-biological variations (Szkop and Nobeli, 2017). Based on the information above, the type 2 methods which rely on transcript reconstruction and infer 3 UTR from assembled transcripts may be a potentially better choice for alternative 3 UTR study for non-model plant species with reference genome available.…”

flexiMAP: a regression-based method for discovering differential alternative polyadenylation events in standard RNA-seq data

“…However, as these methods are still not widely used and many legacy transcriptome surveys were carried out using standard RNA-seq sequencing instead, it would be useful to have computational methods that can identify differential APA in RNA-seq data. A few such methods exist already ( Xia et al ., 2014 ; Grassi et al ., 2016 ; Ha et al ., 2018 ; Ye et al ., 2018 ; Arefeen et al ., 2018 ) but they have caveats ( Szkop and Nobeli, 2017 ). For example, all methods must solve the problem of how to deal with biological replicates; some test the replicates individually, losing the advantage of having replicates in the first place; others, average values from replicates, effectively losing track of the within-group variability.…”