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RNA-seq03:21

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Updated: Sep 25, 2025

iCLIP - Transcriptome-wide Mapping of Protein-RNA Interactions with Individual Nucleotide Resolution
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Spatial correlation statistics enable transcriptome-wide characterization of RNA structure binding.

Veronica F Busa1,2, Alexander V Favorov3,4, Elana J Fertig1,3,5,6

  • 1McKusick-Nathans Department of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA.

Cell Reports Methods
|April 27, 2022
PubMed
Summary
This summary is machine-generated.

We developed nearBynding, a novel computational tool to analyze spatial relationships between RNA features. This algorithm helps uncover how RNA-binding proteins (RBPs) interact with RNA structures and modifications across the transcriptome.

Keywords:
RNA modificationRNA structureRNA-binding proteinbinding motifcross-link immunoprecipitation (CLIP)spatial correlation statisticstranscriptome feature correlation

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Area of Science:

  • Computational Biology
  • Transcriptomics
  • Bioinformatics

Background:

  • Understanding molecular interactions on RNA is crucial for RNA modification and regulation.
  • Existing tools lack the flexibility to model spatial correlations between diverse transcriptomic data types.
  • Identifying spatial relationships between RNA-binding proteins (RBPs), RNA structure, and modifications is challenging.

Purpose of the Study:

  • To introduce nearBynding, a versatile algorithm and software pipeline for modeling spatial correlations in transcriptomic data.
  • To provide a tool for analyzing relationships between transcriptome-wide features, including RNA-binding protein (RBP) binding, RNA structure, and modifications.
  • To make the correlation of transcriptomic features broadly accessible on personal computers.

Main Methods:

  • Developed nearBynding, a flexible algorithm capable of processing and correlating interval and continuous transcriptomic data.
  • Incorporated experimentally derived and in silico predicted transcriptomic tracks.
  • Utilized visualization functions to identify colocalizations and adjacent features, and applied it to RNA-binding protein (RBP) data.

Main Results:

  • nearBynding successfully correlated RNA-binding protein (RBP) binding preferences with other RBPs, RNA structure, and RNA modifications.
  • Cross-correlation of RBP binding and RNA structure data recapitulated known RBP binding to structural motifs.
  • Provided novel biological insights into the binding preferences of RBPs for G-quadruplexes.

Conclusions:

  • nearBynding is an accessible and powerful tool for analyzing spatial relationships between diverse transcriptomic features.
  • The software enables researchers to investigate RNA-binding protein (RBP) interactions and their functional implications.
  • nearBynding facilitates a deeper understanding of RNA regulation and modification through spatial correlation analysis.