Improved RNA-DNA interaction calling suggests RNA-based gene regulation of phenotypic transitions

1 June 2026·
Simonida Zehr
,
Sandra Seredinski
,
Katalin Pálfi
,
James A. Oo
,
Emma C. Walsh
,
Alessandro Bonetti
,
Matthias S. Leisegang
,
Ralf P. Brandes
,
Marcel H. Schulz
,
Dr. Timothy Warwick
· 0 min read
DOI
Abstract
Chromatin-localized RNAs play diverse roles in gene regulation and nuclear architecture. Mapping genome-wide RNA-DNA interactions is possible using a variety of molecular methods, including using bridging oligonucleotides to ligate RNA and DNA in proximity. While molecular methods have progressed, a robust computational method for calling biologically meaningful RNA-DNA interactions from these data is lacking. Herein, we present RADIAnT, a reads-to-interactions pipeline for analyzing RNA-DNA ligation data. RADIAnT calls interactions against a dataset-specific, unified background, which considers RNA binding site-TSS distance and genomic region bias, and outperforms previously proposed methods in the accurate recall of genome-wide RNA-DNA interactions. Accurate RNA-DNA interaction calling enables the analysis of gene regulatory RNAs in dynamic biological contexts. Here, dynamically chromatin-associated RNAs were identified in the physiologically- and pathologically relevant process of endothelial-to-mesenchymal transition. By depleting candidate chromatin-associated lncRNAs, their gene regulatory behavior at bound target genes important to endothelial phenotype maintenance could be validated. These data demonstrate how effective RNA-DNA interaction calling can help to place RNAs at key points in gene regulatory networks governing cellular behavior.
Type
Publication
Nucleic Acids Research
publications
Authors
PhD Student
Alex Johnson is a Senior AI Research Scientist at Meta AI. His research has been published in top conferences like NeurIPS and ICML, with over 10,000 citations. Alex is passionate about pushing the boundaries of AI while ensuring ethical development.
Authors
Senior AI Research Scientist
Alex Johnson is a Senior AI Research Scientist at Meta AI. His research has been published in top conferences like NeurIPS and ICML, with over 10,000 citations. Alex is passionate about pushing the boundaries of AI while ensuring ethical development.