UniBind: maps of high-confidence direct TF-DNA interactions across nine species

Background: Transcription factors (TFs) bind specifically to TF binding sites (TFBSs) at cis-regulatory regions to control transcription. It is critical to locate these TF-DNA interactions to understand transcriptional regulation. Efforts to predict bona fide TFBSs benefit from the availability of experimental data mapping DNA binding regions of TFs (chromatin immunoprecipitation followed by sequencing - ChIP-seq). Results: In this study, we processed similar to 10,000 public ChIP-seq datasets from nine species to provide high-quality TFBS predictions. After quality control, it culminated with the prediction of similar to 56 million TFBSs with experimental and computational support for direct TF-DNA interactions for 644 TFs in > 1000 cell lines and tissues. These TFBSs were used to predict > 197,000 cis-regulatory modules representing clusters of binding events in the corresponding genomes. The high-quality of the TFBSs was reinforced by their evolutionary conservation, enrichment at active cis-regulatory regions, and capacity to predict combinatorial binding of TFs. Further, we confirmed that the cell type and tissue specificity of enhancer activity was correlated with the number of TFs with binding sites predicted in these regions. All the data is provided to the community through the UniBind database that can be accessed through its web-interface (https://unibind.uio.no/), a dedicated RESTful API, and as genomic tracks. Finally, we provide an enrichment tool, available as a web-service and an R package, for users to find TFs with enriched TFBSs in a set of provided genomic regions. Conclusions: UniBind is the first resource of its kind, providing the largest collection of high-confidence direct TF-DNA interactions in nine species.

Automated summary

This study processed around 10,000 ChIP-seq datasets to predict approximately 56 million TFBSs, supporting direct TF-DNA interactions for 644 TFs in multiple cell lines and tissues, and predicting over 197,000 cis-regulatory modules. The high-quality of TFBSs was reinforced by their evolutionary conservation, enrichment at active cis-regulatory regions, and ability to predict combinatorial binding of TFs.