BACKGROUND: Recent 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.
RESULTS: To 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.
CONCLUSIONS: DoGFinder 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 .