Nucleotide conversion RNA sequencing techniques interrogate chemical RNA modifications in cellular transcripts, resulting in mismatch-containing reads. Biases in mapping the resulting reads to reference genomes remain poorly understood. We present splice_sim, a splice-aware RNA-seq simulation and evaluation pipeline that introduces user-defined nucleotide conversions at set frequencies, creates mixture models of converted and unconverted reads, and calculates mapping accuracies per genomic annotation. By simulating nucleotide conversion RNA-seq datasets under realistic experimental conditions, including metabolic RNA labeling and RNA bisulfite sequencing, we measure mapping accuracies of state-of-the-art spliced-read mappers for mouse and human transcripts and derive strategies to prevent biases in the data interpretation.

Gene expression is controlled at multiple levels, including RNA transcription and turnover. But determining the relative contributions of RNA biogenesis and decay to the steady-state abundance of cellular transcripts remains challenging because conventional transcriptomics approaches do not provide the temporal resolution to derive the kinetic parameters underlying steady-state gene expression.Here, we describe a protocol that combines metabolic RNA labeling by 4-thiouridine with chemical nucleoside conversion and whole-transcriptome sequencing followed by bioinformatics analysis to determine RNA stability in cultured cells at a genomic scale. Time-resolved transcriptomics by thiol (SH)-linked alkylation for the metabolic sequencing of RNA (SLAMseq) provides accurate information on transcript half-lives across annotated features in the genome, including by-products of transcription, such as introns. We provide a step-by-step instruction for time-resolved transcriptomics, which enhances traditional RNA sequencing protocols to acquire the temporal resolution required to directly measure the cellular kinetics of RNA turnover under physiological conditions.

The varying rates at which mRNAs decay are tightly coordinated with transcriptional changes to shape gene expression during development and disease. But currently available RNA sequencing approaches lack the temporal information to determine the relative contribution of RNA biogenesis, processing and turnover to the establishment of steady-state gene expression profiles.Here, we describe a protocol that combines metabolic RNA labeling with chemical nucleoside conversion by thiol-linked alkylation of 4-thiouridine to determine RNA stability in cultured cells (SLAMseq). When coupled to cost-effective mRNA 3\' end sequencing approaches, SLAMseq determines the half-life of polyadenylated transcripts in a global and transcript-specific manner using untargeted or targeted cDNA library preparation protocols.We provide a step-by-step instruction for time-resolved mRNA 3\' end sequencing, which augments traditional RNA-seq approaches to acquire the temporal resolution necessary to study the molecular principles that control gene expression.