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RepBox: a toolbox for the identification of repetitive elements.

Shelvasha Burkes-Patton1, Elizabeth A Cooper1,2, Jessica Schlueter3

  • 1Department of Bioinformatics and Genomics, University of North Carolina at Charlotte, Charlotte, NC, 28223, USA.

BMC Bioinformatics
|August 23, 2023
PubMed
Summary

RepBox is a new Python tool that improves the detection and classification of transposable elements (TEs) in plant genomes. It identifies more diverse TE families than existing methods, aiding future genomic studies.

Keywords:
Bioinformatics pipelineDetection softwareGenomicsTransposable elements

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Area of Science:

  • Genomics
  • Bioinformatics

Background:

  • Transposable elements (TEs) are mobile DNA sequences crucial for eukaryotic genome evolution.
  • Efficient identification and categorization of TEs are vital for genomic research.
  • The growing number of de novo assembled genomes necessitates advanced TE detection tools.

Purpose of the Study:

  • To develop an efficient and user-friendly pipeline for transposable element detection.
  • To integrate multiple family-specific TE detection methods into a single tool.

Main Methods:

  • Developed RepBox, a suite of Python scripts.
  • Combined several pre-existing family-specific TE detection methods.
  • Evaluated RepBox against standard TE detection software (RepeatModeler) on plant genomes.

Main Results:

  • RepBox consistently classifies a higher number of transposable elements compared to RepeatModeler.
  • RepBox identifies a more diverse range of TE families in plant genomes.
  • The tool demonstrated superior performance on two distinct plant genomes.

Conclusions:

  • RepBox offers a significant advancement over current TE detection methods.
  • The RepBox toolbox is expected to enhance future transposable element annotation efforts across various species.
  • This tool will facilitate a deeper understanding of TE roles in genome dynamics.