RNA sequences of a gene can have single nucleotide variants (SNVs) due to single nucleotide polymorphisms (SNPs) in the genome, or RNA editing events within the RNA. By comparing RNA-seq data of a given cell type before and after a specific perturbation, we can detect and quantify SNVs in the RNA and discover SNVs with altered frequencies between distinct cellular states. Such differential variants in RNA (DVRs) may reflect allele-specific changes in gene expression or RNA processing, as well as changes in RNA editing in response to cellular perturbations or stimuli.
UCLA researchers have developed rMATS-DVR, a convenient and user-friendly software program to streamline the discovery of DVRs between two RNA-seq sample groups with replicates. rMATS-DVR combines a stringent GATK-based pipeline for calling SNVs including SNPs and RNA editing events in RNA-seq reads, with a rigorous rMATS statistical model for identifying differential isoform ratios using RNA-seq sequence count data with replicates. The researchers applied rMATS-DVR to RNA-seq data of the human chronic myeloid leukemia cell line K562 in response to shRNA knockdown of the RNA editing enzyme ADAR1. rMATS-DVR discovered 1,372 significant DVRs between knockdown and control. These DVRs encompassed known SNPs and RNA editing sites as well as novel SNVs, with the majority of DVRs corresponding to known RNA editing sites repressed after ADAR1 knockdown.
(A) Major steps of rMATS-DVR. (B) Classifications of DVRs into known SNPs, known RNA editing sites, and novel variants in the ADAR1 knockdown RNA-seq data. The variants are denoted as the reference -> alternative nucleotide on the sense RNA strand. (C) Barplot showing the allelic ratios of a SNP-type of DVR (rs143204328; C->T on the RNA sense strand) in control and ADAR1 knockdown samples. The error bar indicates standard deviation based on binomial distribution.
Availability: rMATS-DVR is available at https://github.com/Xinglab/rMATS-DVR