Understanding how long RNA molecules last inside cells is crucial for studying gene expression and cellular function. A new tool called Halfpipe, developed by researchers at the University of Cologne, helps scientists analyze RNA sequencing (RNA-seq) data from metabolic labeling experiments. This tool provides precise measurements of RNA stability, a key factor in gene regulation.

Halfpipe is particularly useful for experiments using SLAM-seq, a method that tracks newly synthesized RNA by detecting specific molecular changes (T>C conversions) introduced during labeling. One major challenge in these experiments is the low efficiency of RNA labeling, which can introduce errors in data analysis. Halfpipe corrects these biases, allowing researchers to accurately estimate the half-life of RNA molecules—the time it takes for half of a given RNA to degrade.

Halfpipe workflow

The input consists of a sample sheet, a reference genome, an annotation file with genomic coordinates of 3′UTRs, and an annotation file with known SNPs. Data preprocessing includes read mapping and quality filtering to the reference genome, T>C calling under the exclusion of known and sample-specific potential SNPs and RNA editing sites. The intermediate result is a T>C conversion count table. These counts can be used by bioinformaticians, who are developing their own method for quantifying the 4sU incorporation rate. Halfpipe estimates the new/total RNA ratios in each sample during the modeling phase. These ratios are also saved as intermediate outputs, for which they can be integrated by workflows that are implementing new multi-compartment models. Finally, the parameters of a one- or two-compartment model of mRNA metabolism are fitted to these ratios using Markov chain Monte Carlo (MCMC) sampling and optimization. This results in RNA metabolic rate estimates for each compartment and transcript and extensive quality metrics.

To demonstrate its effectiveness, the researchers used Halfpipe to measure RNA metabolism in human cells at two different stages of the cell cycle: G1 phase (when cells grow and prepare to divide) and mitosis (when cells split into two new cells). They found that the half-lives of constantly expressed RNAs remain stable between these two phases, suggesting that RNA degradation rates do not change significantly throughout the cell cycle. These findings align well with previous research and known RNA sequence properties.

With its ability to improve the accuracy of RNA metabolism studies, Halfpipe provides a powerful new tool for researchers investigating gene expression, cell cycle regulation, and RNA stability. This could lead to deeper insights into diseases where RNA processing is disrupted, such as cancer and neurodegenerative disorders.

Availability – Halfpipe is freely available at https://github.com/IMSBCompBio/Halfpipe.