Biology subjects

Veenbaas, S. D.

Publications and source records attributed to Veenbaas, S. D..

2 recordsLinked to original sources

bioRxiv2026

Alternative polyadenylation drives isoform-dependent m6A remodeling during Zika virus infection

Alternative RNA processing generates extensive transcript diversity, yet how transcript architecture influences selective m6A deposition is incompletely understood. Exon-junction-based models explain where m6A is excluded, but a positive determinant of m6A accumulation remains undefined. Here, we leverage Zika virus-induced changes in m6A deposition to uncover determinants of transcript-selective methylation. By integrating GLORI-seq, native METTL3 RNA immunoprecipitation, and nanopore direct RNA sequencing, we generate a single-nucleotide, isoform-resolved map of m6A dynamics during infection. We identify over 2,000 dynamic m6A sites, many arising from changes in transcript architecture, and pinpoint proximal polyadenylation sites as positive determinants of m6A accumulation. The cleavage stimulation factors CSTF2 and CSTF2T drive this remodeling through two routes: redundant induction of intronic polyadenylation, which converts internal exons into terminal exons that expose DRACH motifs to METTL3, and non-redundant, cleavage-independent recruitment of METTL3 near proximal polyadenylation sites, establishing alternative polyadenylation as a key architectural determinant of the m6A landscape.

molecular biology↗

bioRxiv2025

Ligand-binding pockets in RNA, and where to find them

RNAs are critical regulators of gene expression, and their functions are often mediated by complex secondary and tertiary structures. Structured regions in RNA can selectively interact with small molecules - via well-defined ligand binding pockets - to modulate the regulatory repertoire of an RNA. The broad potential to modulate biological function intentionally via RNA-ligand interactions remains unrealized, however, due to challenges in identifying compact RNA motifs with the ability to bind ligands with good physicochemical properties (often termed drug-like). Here, we devise fpocketR, a computational strategy that accurately detects pockets capable of binding drug-like ligands in RNA structures. Remarkably few, roughly 50, of such pockets have ever been visualized. We experimentally confirmed the ligandability of novel pockets detected with fpocketR using a fragment-based approach introduced here, Frag-MaP, that detects ligand-binding sites in cells. Analysis of pockets detected by fpocketR and validated by Frag-MaP reveals dozens of newly identified sites able to bind drug-like ligands, supports a model for RNA secondary structural motifs able to bind quality ligands, and creates a broad framework for understanding the RNA ligand-ome.

biophysics↗