Dr. Sung and colleagues developed DNase2Hotspots and DNase2TF programs a few years ago. The transcription factor footprint detection program DNase2TF was ranked in the top two public analysis software packages in an exhaustive comparison of existing algorithms in terms of speed and accuracy for the prediction of transcription factor occupancy in chromatin which is observed by ChIP-seq. Dr. Sung and colleagues showed that the extent of footprint depth for transcription factors depends on their DNA binding residence times measured by live cell microscopy techniques such as single molecule tracking and FRAP (fluorescence recovery after photobleaching). She correlated the epigenetic patterns detected from DNase-seq data to the kinetic data from quantitative live cell microscopy of proteins that act upon the epigenome. Her cross-cutting analysis revealed an unexpected phenomenon: Some types of transcription factor proteins do not leave footprints at their binding sites in the genome, as assessed by the recently introduced footprinting method based on DNase-seq. This work revealed a previously unappreciated limitation of the genomic footprinting method regarding transcription factors with highly dynamic interactions with target chromatin, thereby providing researchers with a pointer as to where future efforts must be focused. The Perspective article in the journal Nature Methods generated a lot of interest and realization in the research community about unresolved limitations and issues involving DNase-based genomic footprinting. The genomic footprinting method has previously been used in several high profile publications to characterize tissue-specific protein occupancy in the genome. The journal Nature Methods had a cover on the topic and featured three articles in the March 2016 issue. Our article has received many online social media comments from scientists: For gene regulation crowd, this was one of the most interesting articles in the last couple of months., Must-read before doing DNAse-seq are some twitter feeds posted by readers at the journal website. The program DNase2TF developed by Dr. Sung and colleagues and used in this work has been downloaded more than 3,000 times (as of August 2016) since the source code was released to the public.
