There is a strict interplay between metabolic networks and transcriptional regulation in bacteria; indeed, the transcriptome regulation, affecting the expression of large gene sets, can be used to predict the likely “on” or “off” state of metabolic genes as a function of environmental factors. Up to date, many bacterial transcriptomes have been studied by RNAseq, hundreds of experiments have been performed, and Giga bases of sequences have been produced. All this transcriptional information could potentially be integrated into metabolic networks in order to obtain a more comprehensive view of their regulation and to increase their prediction power.To get high-quality transcriptomic data, to be integrated into metabolic networks, it is paramount to clearly know how to produce highly informative RNA sequencing libraries and how to manage RNA sequencing data.
Researchers from the National Research Council, Italy describe the main steps of an RNAseq experiment: from removal of ribosomal RNAs, to strand-specific library preparation, till data analysis and integration. They share their experience and know-how, to give you a precise protocol to follow, and some useful recommendations or tips and tricks to adopt in order to go straightforward toward a successful RNAseq experiment.
Ribosomal RNA removal (a) and strand-specific library preparation for RNAseq (b)