DoGFinder: a software for the discovery and quantification of readthrough transcripts from RNA-seq

Abstract

BackgroundRecent studies have described a widespread induction of transcriptional readthrough as a consequence of various stress conditions in mammalian cells. This novel phenomenon, initially identified from analysis of RNA-seq data, suggests intriguing new levels of gene expression regulation. However, the mechanism underlying naturally occurring transcriptional readthrough, as well as its regulatory consequences, still remain elusive. Furthermore, the readthrough response to stress has thus far not been investigated outside of mammalian species, and the occurrence of readthrough in many physiological and disease conditions remains to be explored.ResultsTo facilitate a wider investigation into transcriptional readthrough, we created the DoGFinder software package, for the streamlined identification and quantification of readthrough transcripts, also known as DoGs (Downstream of Gene-containing transcripts), from any RNA-seq dataset. Using DoGFinder, we explore the dependence of DoG discovery potential on RNA-seq library depth, and show that stress-induced readthrough induction discovery is robust to sequencing depth, and input parameter settings. We further demonstrate the use of the DoGFinder software package on a new publically available RNA-seq dataset, and discover DoG induction in human PME cells following hypoxia – a previously unknown readthrough inducing stress type.ConclusionsDoGFinder will enable users to explore, in a few simple steps, the readthrough phenomenon in any condition and organism.DoGFinder is freely available at https://github.com/shalgilab/DoGFinder.Electronic supplementary materialThe online version of this article (10.1186/s12864-018-4983-4) contains supplementary material, which is available to authorized users.

Hyperosmotic stress alters the RNA polymerase II interactome and induces readthrough transcription despite widespread transcriptional repression

“…Read-in values used to define clean genes were generated using ARTDeco (Roth et al 2020). DoGs were identified using DoGFinder (Wiesel et al 2018). Differential expression analysis of normalized read counts in gene bodies and in DoG .…”

SETD5 Regulates Chromatin Methylation State and Preserves Global Transcriptional Fidelity during Brain Development and Neuronal Wiring

“…The decrease in elongation rate may cause defects in cotranslational mechanisms such as splicing events, correct interpretation of end sites, and cryptic transcription within gene bodies. To investigate this eventuality, we analyzed differential exon and/or isoform abundance between Setd5 mutant and control NSCs in RNA-seq datasets (using DEXSeq and DoGFinder) (Li et al, 2015;Wiesel et al, 2018). Setd5 mutant cells exhibited massive misregulation of exon usage events that largely occurred in SETD5 targets ($40%), with 3.82 events per target gene versus 2.17 in non-target genes (Figure S7C; Table S2).…”

“…Differential exon usage and the resulting alternative splicing events were calculated with DEXSeq (Li et al, 2015) and rMATS (Shen et al, 2014b). Discovery and quantification of readthrough transcripts were performed with DoGFinder (Wiesel et al, 2018). Statistical and downstream bioinformatics analysis were performed within the R environment.…”

Hyperosmotic stress induces downstream-of-gene transcription and alters the RNA Polymerase II interactome despite widespread transcriptional repression

“…Read-in values used to define clean genes were generated using ARTDeco (Roth et al 2020). DoGs were identified using DoGFinder (Wiesel et al 2018). Differential expression analysis of normalized read counts in gene bodies and in DoG regions was done using DESeq2 (Love et al 2014).…”