Genome-wide modelling of transcription kinetics reveals patterns of RNA production delays

TL;DR

This study develops a genome-wide model combining transcription activation and mRNA accumulation to infer kinetic parameters, revealing significant RNA production delays linked to splicing in breast cancer cells.

Contribution

It introduces a joint mechanistic and statistical model for transcription kinetics, enabling inference of delays, transcription rates, and degradation rates from high-throughput sequencing data.

Findings

11% of genes show delays over 20 minutes in mRNA production

Long delays are more common in shorter genes

High delays correlate with late intron retention

Abstract

Genes with similar transcriptional activation kinetics can display very different temporal mRNA profiles due to differences in transcription time, degradation rate and RNA processing kinetics. Recent studies have shown that a splicing-associated RNA production delay can be significant. We introduce a joint model of transcriptional activation and mRNA accumulation which can be used for inference of transcription rate, RNA production delay and degradation rate given genome-wide data from high-throughput sequencing time course experiments. We combine a mechanistic differential equation model with a non-parametric statistical modelling approach allowing us to capture a broad range of activation kinetics, and use Bayesian parameter estimation to quantify the uncertainty in the estimates of the kinetic parameters. We apply the model to data from estrogen receptor (ER-{\alpha}) activation in the MCF-7 breast cancer cell line. We use RNA polymerase II (pol-II) ChIP-Seq time course data to characterise transcriptional activation and mRNA-Seq time course data to quantify mature transcripts. We find that 11% of genes with a good signal in the data display a delay of more than 20 minutes between completing transcription and mature mRNA production. The genes displaying these long delays are significantly more likely to be short. We also find a statistical association between high delay and late intron retention in pre-mRNA data, indicating significant splicing-associated production delays in many genes.