Utilizing RNA-seq Data to Infer Bacterial Transcription Termination Sites and Validate Predictions.

The transcription termination process is an important part of the gene expression process in the cell. It has been studied extensively, but many aspects of the mechanism are not well understood. The widespread availability of experimental RNA-seq data from high-throughput experiments provides a unique opportunity to infer the end of the transcription units genome wide. This data is available for both Rho-dependent and Rho-independent termination pathways that drive transcription termination in bacteria. Our book chapter gives an overview of the current knowledge of Rho-independent transcription termination mechanisms and the prediction approaches currently deployed to infer the termination sites. Thereafter, we describe our method that uses cluster hairpins to detect Rho-independent transcription termination sites. These clusters are a group of hairpins that lies at <15 bp from each other and are together capable of enforcing the termination process. The idea of a group of hairpins being extensively used for transcription termination is new, and results show that at least 52% of the total cases are of this type, while in the remaining cases, a single strong hairpin is capable of driving transcription termination. The reads derived from the RNA-seq data for corresponding bacteria have been used to validate the predicted sites. The predictions that match these RNA-seq derived sites have higher confidence, and we find almost 98% of the predicted sites, including alternate termination sites, to match the RNA-seq data. We discuss the features of predicted hairpins in detail for a better understanding of the Rho-independent transcription termination mechanism in bacteria. We also explain how users can use the tools developed by us to do transcription terminator predictions and design their experiments through genome-level visualization of the transcription termination sites from the precomputed INTERPIN database.