Statistical inference of the rate of RNA polymerase II elongation by total RNA sequencing

MOTIVATION: Sequencing total RNA without poly-A selection enables us to obtain a transcriptomic profile of nascent RNAs undergoing transcription with co-transcriptional splicing. In general, the RNA-seq reads exhibit a sawtooth pattern in a gene, which is characterized by a monotonically decreasing gradient across introns in the 5’–3’ direction, and by substantially higher levels of RNA-seq reads present in exonic regions. Such patterns result from the process of underlying transcription elongation by RNA polymerase II, which traverses the DNA strand in a 5’–3’ direction as it performs a complex series of mRNA synthesis and processing. Therefore, data of sequenced total RNAs could be utilized to infer the rate of transcription elongation by solving the inverse problem. RESULTS: Though solving the inverse problem in total RNA-seq has the great potential, statistical methods have not yet been fully developed. We demonstrate what extent the newly developed method can be useful. The objective is to reconstruct the spatial distribution of transcription elongation rates in a gene from a given noisy, sawtooth-like profile. It is necessary to recover the signal source of the elongation rates separately from several types of nuisance factors, such as unobserved modes of co-transcriptionally occurring mRNA splicing, which exert significant influences on the sawtooth shape. The present method was tested using published total RNA-seq data derived from mouse embryonic stem cells. We investigated the spatial characteristics of the estimated elongation rates, focusing especially on the relation to promoter-proximal pausing of RNA polymerase II, nucleosome occupancy and histone modification patterns. AVAILABILITY AND IMPLEMENTATION: A C implementation of PolSter and sample data are available at https://github.com/yoshida-lab/PolSter. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.