DOI: 10.6084/m9.figshare.28955183.v3
title: <b>Disentangling precursor and mature epitranscriptomes unveils the single-cell velocity of RNA modification</b>

description: RNA modifications play critical roles in regulating gene expression, yet their dynamic behavior at single-cell resolution remains largely unexplored. To address this, we developed VeloRM, a computational framework that models the kinetics of RNA modifications—such as m⁶A methylation and A-to-I editing—by quantifying their gain and loss over pseudotime at single-nucleotide resolution. Applying VeloRM to scDART-seq data, we uncovered distinct regulatory programs: most m⁶A modifications occur prior to splicing, though a subset arises post-splicing; in contrast, A-to-I editing primarily takes place during or after splicing, following markedly different kinetics from m⁶A. VeloRM accurately reconstructs modification-associated cellular trajectories and identifies stage-specific modification patterns that influence RNA fate. Notably, m⁶A levels correlate with mRNA decay, with most regulatory effects observed in pre-mRNA, although some modification sites show a positive association with mature mRNA abundance. Together, these findings provide new insights into the dynamic regulation of the epitranscriptome at single-cell resolution and establish a powerful framework for studying RNA modification kinetics in development and disease.<br><b>Code</b>The repository includes R Markdown scripts for analyzing both <b>scDART-seq data</b> and <b>RNA-Seq A-to-I editing data</b>.<b>scDART-seq Data Analysis</b>The analysis is divided into three main stages: <b>(1) raw data preprocessing</b>, <b>(2) data processing</b>, and <b>(3) downstream analysis</b>.<b>1. Raw Data (origin)</b><b>SNP_all</b>: SNP information for candidate m6A sites.<b>frequency_pre_YTH</b>: Methylated and unmethylated read counts in pre-mRNA of test (YTH-WT) cells.<b>frequency_pre_YTHmut</b>: Methylated and unmethylated read counts in pre-mRNA of control (YTH-mutant) cells.<b>frequency_spliced_YTH</b>: Methylated and unmethylated read counts in mature mRNA of test cells.<b>frequency_spliced_YTHmut</b>: Methylated and unmethylated read counts in mature mRNA of control cells.<b>frequency_isoform_YTH</b>: Methylated and unmethylated read counts in ambiguous (isoform-level) mRNA of test cells.<b>frequency_isoform_YTHmut</b>: Methylated and unmethylated read counts in ambiguous mRNA of control cells.<b>label_SigRM</b>: Cell cycle stage labels from <i>Statistical modeling of single-cell epitranscriptomics enabled trajectory and regulatory inference of RNA methylation</i> (Cell Genomics).<b>expression_TPM</b>: Gene expression data (TPM) from the same study.<b>gene_informations</b>: Gene annotation data from the same study.<b>2. Preprocessing</b><b>SNP_37199</b>: Subset of SNPs used for downstream m6A analysis.<b>test_list</b>: Processed read counts for test cells, including:<code>spliced_meth_test</code>, <code>spliced_unmeth_test</code><code>pre_meth_test</code>, <code>pre_unmeth_test</code><code>isoform_meth_test</code>, <code>isoform_unmeth_test</code><b>control_list</b>: Processed read counts for control cells, similarly structured.<b>res_preprocess</b>: Preprocessed input formatted for VeloRM.<b>res_DESeq2</b>: Differential expression analysis results using DESeq2.<b>SigRMtest_res_unspliced</b>: SigRM test results on unspliced reads (test vs. control).<b>SigRMtest_res_spliced</b>: SigRM test results on spliced reads (test vs. control).<b>3. Analysis</b><b>splicing_junction_analysis</b>: Data frame with distances between SNPs and the nearest splicing junctions.<b>res_m6A_velocity</b>: m6A velocity results computed by VeloRM.<b>res_expression_velocity</b>: Site-level expression velocity estimated by VeloRM.<b>res_transcriptional_impact_analysis_spearman</b>: Transcriptional impact results (Spearman correlation-based) from VeloRM.<b>cell_cycle_sites</b>: Cell cycle-related methylation site analysis performed with VeloRM.<b>RNA-Seq A-to-I Data Analysis</b><b>1. Raw Data (origin)</b><b>SNP_all</b>: SNP information of candidate A-to-I editing sites.<b>pre_A-to-I</b>: Read counts (methylated and unmethylated) in pre-mRNA of test cells.<b>spliced_A_to_I</b>: Read counts in mature mRNA of test cells.<b>isoform_A_to_I</b>: Read counts in ambiguous mRNA of test cells.<b>2. Preprocessing</b><b>SNP_1159</b>: Filtered SNPs for downstream A-to-I analysis.<b>test_list</b>: Read counts for test cells, including:<code>spliced_meth_test</code>, <code>spliced_unmeth_test</code><code>pre_meth_test</code>, <code>pre_unmeth_test</code><code>isoform_meth_test</code>, <code>isoform_unmeth_test</code><b>control_list</b>: <code>NULL</code> (no control group in this dataset).<b>res_preprocess</b>: Preprocessed data formatted for VeloRM.<b>res_DESeq2</b>: Differential analysis results via DESeq2.<b>3. Analysis</b><b>splicing_junction_analysis</b>: Distances between candidate sites and nearest splice junctions.<b>cell_cycle_sites</b>: Cell cycle-related A-to-I site analysis via VeloRM.<br>