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

Area of Science:

• Genomics
• Molecular Biology
• Bioinformatics

Background:

• Transcriptional readthrough, a phenomenon observed under cellular stress, suggests novel gene expression regulation.
• Mechanisms and regulatory impacts of transcriptional readthrough remain largely unexplored.
• Investigating stress-induced readthrough beyond mammalian species and in various physiological/disease states is needed.

Purpose of the Study:

• To develop a streamlined software package for identifying and quantifying transcriptional readthrough transcripts (DoGs).
• To enable broader research into the phenomenon of transcriptional readthrough across diverse conditions and organisms.

Main Methods:

• Development of the DoGFinder software package for analyzing RNA-seq data.
• Assessment of DoGFinder's performance concerning RNA-seq library depth and parameter settings.
• Application of DoGFinder to a public RNA-seq dataset to identify stress-induced DoG induction.

Main Results:

• DoGFinder facilitates the identification and quantification of DoGs from any RNA-seq dataset.
• Stress-induced readthrough discovery using DoGFinder is robust to sequencing depth and parameter variations.
• Hypoxia was identified as a novel stress-inducing type for DoG induction in human PME cells.

Conclusions:

• DoGFinder provides a user-friendly tool for exploring transcriptional readthrough.
• The software supports the investigation of readthrough phenomena in any experimental condition and organism.
• DoGFinder is freely available for public use.