IDH1-Associated m6A Methylation Is Linked to Transcriptomic Heterogeneity in Glioma

Characterizing the m6A epigenetic landscape is essential for understanding glioma biology, yet transcriptome-wide mapping of these modifications at isoform resolution across specific tumor subtypes has remained limited. Conventional short-read approaches lack the capacity to resolve full-length transcript isoforms or assign m6A modifications to individual transcripts, representing a critical gap in glioma where alternative splicing is pervasive.

We performed direct RNA nanopore sequencing and transcriptome-wide m6A analysis in 14 glioma tumor tissues, including IDH1-mutant astrocytoma, oligodendroglioma, and IDH1 wild-type glioblastoma, enabling isoform-resolved profiling not accessible by conventional short-read approaches. m6A sites were predicted computationally using the m6Anet deep learning framework, which has been independently benchmarked against MeRIP-seq-derived sites, and high-confidence calls were defined at a probability threshold of ≥0.9 and required detection across multiple patients within each subtype.

IDH1-mutant gliomas showed a higher overall burden of computationally inferred m6A-modified sites, transcripts, and genes than IDH1 wild-type glioblastoma, along with variation in transcript biotypes, regional distribution of m6A sites, and extent of isoform methylation. Differential methylation analysis identified subtype-specific patterns of m6A localization, many of which were observed without corresponding changes in gene-level expression, indicating that m6A variation represents a post-transcriptional regulatory layer not captured by gene-level analysis alone. Integration of gene expression, isoform usage, and m6A status further identified variation in isoform composition and transcript features between astrocytoma and glioblastoma. Analysis of m6A regulators showed subtype-associated expression patterns among readers, writers, and erasers, and exploratory analyses identified isoform-level associations with survival that were not apparent at the gene level.

Overall, these data describe subtype-specific patterns of m6A marking and isoform architecture across glioma tissues, derived from computational inference using direct RNA sequencing in a modestly sized cohort and warrant validation by orthogonal methods in larger studies. These findings are consistent with concurrent independent evidence that isoform-specific m6A deposition is evolutionarily conserved across mammals and that long-read isoform resolution reveals transcript diversity in glioma not captured by gene-level analysis. While cohort size and the absence of orthogonal site-level validation suggest that the data require cautious interpretation, this work provides a hypothesis-generating resource and methodological framework for future mechanistic and translational investigation of the glioma epitranscriptome.