Prediction of RNA Methylation Status From Gene Expression Data Using Classification and Regression Methods

m6A modification of VEGFA mRNA by RBM15/YTHDF2/IGF2BP3 contributes to angiogenesis of hepatocellular carcinoma

Vascular endothelial growth factor A (VEGFA) plays a critical role as a potent angiogenesis factor and is highly expressed in hepatocellular carcinoma (HCC). Although the expression of VEGFA has been strongly linked to the aggressive nature of HCC, the specific posttranscriptional modifications that might contribute to VEGFA expression and HCC angiogenesis are not yet well understood. In this study, we aimed to investigate the epitranscriptome regulation of VEGFA in HCC. A comprehensive analysis integrating MeRIP-seq, RNA-seq, and crosslinking-immunprecipitation-seq data revealed that VEGFA was hypermethylated in HCC and identified the potential m6A regulators of VEGFA including a m6A methyltransferase complex component RBM15 and the two readers, YTHDF2 and IGF2BP3. Through rigorous cell and molecular biology experiments, RBM15 was validated as a key component of methyltransferase complex responsible for m6A methylation of VEGFA, which was subsequently recognized and stabilized by IGF2BP3 and YTHDF2, leading to enhanced VEGFA expression and VEGFA-related functions such as human umbilical vascular endothelial cells (HUVEC) migration and tube formation. In the HCC xenograft model, knockdown of RBM15, IGF2BP3, or YTHDF2 resulted in reduced expression of VEGFA, accompanied by significant inhibition of tumor growth closely associated with VEGFA expression and angiogenesis. Furthermore, our analysis of HCC clinical samples identified positive correlations between the expression levels of VEGFA and the regulators RBM15, IGF2BP3, and YTHDF2. Collectively, these findings offer novel insights into the posttranscriptional modulation of VEGFA and provide potential avenues for alternative approaches to antiangiogenesis therapy targeting VEGFA.

Recent advances in functional annotation and prediction of the epitranscriptome

RNA modifications, in particular N⁶-methyladenosine (m⁶A), participate in every stages of RNA metabolism and play diverse roles in essential biological processes and disease pathogenesis. Thanks to the advances in sequencing technology, tens of thousands of RNA modification sites can be identified in a typical high-throughput experiment; however, it remains a major challenge to decipher the functional relevance of these sites, such as, affecting alternative splicing, regulation circuit in essential biological processes or association to diseases. As the focus of RNA epigenetics gradually shifts from site discovery to functional studies, we review here recent progress in functional annotation and prediction of RNA modification sites from a bioinformatics perspective. The review covers naïve annotation with associated biological events, e.g., single nucleotide polymorphism (SNP), RNA binding protein (RBP) and alternative splicing, prediction of key sites and their regulatory functions, inference of disease association, and mining the diagnosis and prognosis value of RNA modification regulators. We further discussed the limitations of existing approaches and some future perspectives.

PIANO: A Web Server for Pseudouridine-Site (Ψ) Identification and Functional Annotation

Known as the "fifth RNA nucleotide", pseudouridine (Ψ or psi) is the first-discovered and most abundant RNA modification occurring at the Uridine site, and it plays a prominent role in a number of biological processes. Thousands of Ψ sites have been identified within different biological contexts thanks to the advancement in high-throughput sequencing technology; nevertheless, the transcriptome-wide distribution, biomolecular functions, regulatory mechanisms, and disease relevance of pseudouridylation are largely elusive. We report here a web server-PIANO-for pseudouridine site (Ψ) identification and functional annotation. PIANO was built upon a high-accuracy predictor that takes advantage of both conventional sequence features and 42 additional genomic features. When tested on six independent datasets generated from four independent Ψ-profiling technologies (Ψ-seq, RBS-seq, Pseudo-seq, and CeU-seq) as benchmarks, PIANO achieved an average AUC of 0.955 and 0.838 under the full transcript and mature mRNA models, respectively, marking a substantial improvement in accuracy compared to the existing in silico Ψ-site prediction methods, i.e., PPUS (0.713 and 0.707), iRNA-PseU (0.713 and 0.712), and PseUI (0.634 and 0.652). Besides, PIANO web server systematically annotates the predicted Ψ sites with post-transcriptional regulatory mechanisms (miRNA-targets, RBP-binding regions, and splicing sites) in its prediction report to help the users explore potential machinery of Ψ. Moreover, a concise query interface was also built for 4,303 known Ψ sites, which is currently the largest collection of experimentally validated human Ψ sites. The PIANO website is freely accessible at: http://piano.rnamd.com.