RMVar

RMVar catalogs and annotates 1,678,126 genetic variants associated with nine RNA modifications (m6A, m6Am, m1A, pseudouridine, m5C, m5U, 2'-O-Me, A-to-I, and m7G) to enable analysis of their posttranscriptional regulatory roles and associations with human diseases including cancers.

Key Features:

• Variant collection: Contains 1,678,126 RNA modification-associated variants across nine modification types: m6A, m6Am, m1A, pseudouridine, m5C, m5U, 2'-O-Me, A-to-I, and m7G.
• Confidence levels: Variants are categorized into three confidence levels to facilitate robustness of analyses.
• Experimental datasets: Integrates experimental epitranscriptomic datasets including miCLIP, PA-m6A-Seq, m6ACE-Seq, DART-Seq, m6A-REF-Seq, MAZTER-seq, m1A-quant-seq, m1A-IP-Seq, m1A-MAP, m7G-seq, BS-Seq, Nm-Seq, RiboMeth-Seq, ψ-Seq, DM-ψ-Seq, Ceu-Seq, RBS-Seq, m6A-Seal-Seq, and MeRIP-Seq.
• Predicted modification sites: Includes predicted RNA modification sites in addition to experimentally derived sites.
• Regulatory annotations: Annotates variants with RNA-binding protein (RBP) binding regions, miRNA targets, splicing events, and circular RNAs (circRNAs).
• Disease associations: Integrates disease-related information from ClinVar and genome-wide association studies (GWAS).

Scientific Applications:

• Functional impact analysis: Assess the functional impact of genetic variants on specific RNA modifications such as m6A and m1A.
• Posttranscriptional regulation studies: Investigate effects of variants on posttranscriptional regulation mediated by RBPs, miRNAs, splicing, and circRNAs.
• Disease variant prioritization: Prioritize and interpret variants for disease association studies, including cancer research, using ClinVar and GWAS annotations.
• Epitranscriptome comparative analyses: Enable comparison between experimentally detected and predicted modification sites across multiple sequencing platforms.

Methodology:

Integration of experimental epitranscriptomic sequencing datasets and predicted modification sites, classification of variants into three confidence levels, and annotation of variants with RBP binding regions, miRNA targets, splicing events, circRNAs, and disease information from ClinVar and GWAS.