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Related Experiment Video

Updated: Jan 19, 2026

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The RIPper, a web-based tool for genome-wide quantification of Repeat-Induced Point (RIP) mutations.

Stephanie van Wyk1, Christopher H Harrison2, Brenda D Wingfield1

  • 1Department of Biochemistry, Genetics and Microbiology, Forestry and Agricultural Biotechnology Institute (FABI), University of Pretoria, Pretoria, Gauteng, South Africa.

Peerj
|September 17, 2019
PubMed
Summary

The RIPper tool automates the analysis of Repeat-Induced Point (RIP) mutations in fungal genomes. This bioinformatics solution identifies RIP-affected genomic regions and quantifies mutation frequencies for genome-wide studies.

Keywords:
Fine-scale RIP analysesGenome-wide quantificationLarge RIP affected regionsRIPRIP profileRepeat-Induced Point mutationsThe RIPperWeb-based tool

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Area of Science:

  • Bioinformatics
  • Genomics
  • Mycology

Background:

  • Repeat-Induced Point (RIP) mutations are a fungal genome defense mechanism against mobile DNA elements.
  • RIP introduces cytosine to thymine transitions in repeated DNA motifs, deactivating them.
  • Analyzing RIP mutation frequency and patterns is crucial for understanding genome evolution and defense.

Purpose of the Study:

  • To introduce The RIPper, a novel bioinformatics tool for automated analysis of RIP mutations.
  • To facilitate the investigation of RIP product and substrate nucleotide frequencies in fungal genomes.
  • To enable genome-wide assessment of RIP activity and its impact on genomic regions.

Main Methods:

  • Development of a web-based bioinformatics tool, The RIPper.
  • Application of a sliding window approach for genome-wide RIP analysis.
  • Fine-scale analysis of gene regions and transposable elements for RIP mutation detection.

Main Results:

  • The RIPper successfully detected and quantified RIP mutations in known affected sequences, including *Neurospora crassa*.
  • Genome-wide analysis revealed extensive RIP mutation patterns, with affected regions showing reduced GC content.
  • Fine-scale analyses confirmed high RIP mutation frequencies in gene and transposable element sequences.

Conclusions:

  • The RIPper tool efficiently identifies RIP-targeted genomic regions and provides comprehensive RIP statistics.
  • The software enables genome-wide RIP analyses, including the proportion of the genome affected by RIP.
  • The RIPper is a valuable resource for researchers studying fungal genome defense mechanisms.