RMzyme: regulations of RNA-modifying enzymes in humans

TL;DR

This paper explores RNA-modifying enzymes in humans using multiomics data to understand their roles in gene regulation and disease.

Contribution

The study introduces RMzyme, a platform integrating multiomics data to analyze RNA-modifying enzymes and their regulatory roles.

Findings

RMPs like ALKBH5 influence m6A dynamics and pathways in acute myeloid leukemia.

Cell type-specific RNA modification patterns were identified in ALKBH5-enriched AML stem cells.

Proteogenomic data revealed PTM-associated regulatory networks linked to RNA-modifying enzymes.

Abstract

RNA modifications represent a dynamic layer of gene expression regulation, RNA stability, and translation with profound implications for cellular function and disease. However, the critical regulation and functions of RNA-modifying proteins (RMPs) remain poorly understood. Here, we present a large-scale characterization of RMPs through 378 multiomics datasets encompassing genomics, bulk and single-cell transcriptomics, epitranscriptomics, proteomics, and posttranslational modifications (PTMs) across 63 human tissues. Our analysis of experimental perturbations of RMPs revealed dynamic differential modification peaks and expressed genes. We applied nonnegative matrix factorization to annotate RMP-mediated cell types in single-cell transcriptomes. Functional annotations in acute myeloid leukemia (AML) revealed RMPs such as ALKBH5 as critical mediators of m6A dynamics, influencing pathways involved in translation initiation, immune regulation, and tumorigenesis. We revealed cell type-specific modification patterns, including those in ALKBH5-enriched AML stem cells with special ligand‒receptor interactions and genetic variations modulated by m6A. We integrated proteogenomic data to uncover PTM-associated regulatory, mutation, and protein‒protein interaction networks linked to RMPs. We developed RMzyme, a platform that consolidates our findings and provides insights into RMPs and their downstream effects. This resource is expected to facilitate biomedical research into the molecular mechanisms of human diseases through the lens of RNA modifications and multiomics data integration.

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