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CRISPR and crRNAs02:53

CRISPR and crRNAs

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Bacteria and archaea are susceptible to viral infections just like eukaryotes; therefore, they have developed a unique adaptive immune system to protect themselves. Clustered regularly interspaced short palindromic repeats and CRISPR-associated proteins (CRISPR-Cas) are present in more than 45% of known bacteria and 90% of known archaea.
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Related Experiment Video

Updated: Sep 21, 2025

In Silico Identification and Characterization of circRNAs During Host-Pathogen Interactions
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circRIP: an accurate tool for identifying circRNA-RBP interactions.

Xin Dong1, Ke Chen2, Wenbo Chen1

  • 1School of Basic Medical Sciences, Wuhan University, Wuhan 430071, China.

Briefings in Bioinformatics
|May 31, 2022
PubMed
Summary
This summary is machine-generated.

Researchers developed circRIP, an efficient algorithm to identify genome-wide interactions between circular RNAs (circRNAs) and RNA-binding proteins (RBPs). This tool enhances understanding of circRNA functions by analyzing RIP-Seq and eCLIP data.

Keywords:
RIP-SeqRNA-binding proteincircRNAeCLIP

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Area of Science:

  • Molecular Biology
  • Bioinformatics
  • Genomics

Background:

  • Circular RNAs (circRNAs) are key regulators of gene expression, primarily through interactions with RNA-binding proteins (RBPs).
  • Identifying circRNA-RBP interactions genome-wide is crucial for understanding circRNA function, but efficient computational tools are lacking.

Purpose of the Study:

  • To develop and validate an efficient algorithm, circRIP, for identifying circRNA-RBP interactions from RIP-Seq and eCLIP data.
  • To demonstrate the utility of circRIP in discovering circRNA-RBP interactions in specific biological contexts.

Main Methods:

  • Development of the circRIP algorithm for analyzing RIP-Seq and eCLIP datasets to predict circRNA-RBP interactions.
  • Simulation testing to evaluate the sensitivity and specificity of the circRIP algorithm.
  • Application of circRIP to identify circRNAs bound by IGF2BP3 and to survey circRNA-RBP interactions in K562 and HepG2 cell lines.

Main Results:

  • The circRIP algorithm demonstrated high sensitivity and specificity in simulation tests.
  • Identification of 95 IGF2BP3-binding circRNAs using IGF2BP3 RIP-Seq data.
  • Discovery of 2823 and 1333 circRNAs interacting with over 100 RBPs in K562 and HepG2 cell lines, respectively, using eCLIP data.

Conclusions:

  • circRIP is an accurate and sensitive tool for systematically identifying RBP and circRNA interactions.
  • The tool facilitates genome-wide surveys of circRNA-RBP interactions, significantly aiding functional exploration of circRNAs.
  • This work provides a valuable resource for researchers investigating the roles of circRNAs and their protein interactions.