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Updated: Jun 14, 2025

Identification of Functionally-Relevant Lentivirus Integration Sites in an Insertional Mutagenesis Cell Library
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skandiver: a divergence-based analysis tool for identifying intercellular mobile genetic elements.

Xiaolei Brian Zhang1,2, Grace Oualline1,2, Jim Shaw3

  • 1Department of Biological Sciences, Carnegie Mellon University, Pittsburgh, PA 15213, United States.

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|September 4, 2024
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Summary

A new tool, skandiver, efficiently detects mobile genetic elements (MGEs) in bacterial genomes using divergence. It offers a scalable method for discovering novel MGEs without relying on curated databases.

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Area of Science:

  • Genomics
  • Bioinformatics
  • Microbiology

Background:

  • Mobile genetic elements (MGEs) are diverse and can transfer antibiotic resistance genes between bacteria.
  • Characterizing MGEs is challenging due to their varied nature and limitations in current detection methods.
  • Existing tools often disagree on MGE identification, hindering comprehensive analysis.

Purpose of the Study:

  • To propose a novel divergence-based characterization for mobile genetic elements.
  • To introduce skandiver, an efficient tool for detecting MGEs from whole-genome assemblies.
  • To enable scalable identification of MGEs, including novel elements, without gene annotation.

Main Methods:

  • Developed skandiver, a tool leveraging genome fragmentation, average nucleotide identity (ANI), and divergence time for MGE detection.
  • Integrated skandiver with the scalable skani software for efficient ANI computation.
  • Evaluated skandiver's performance against existing methods like MobileElementFinder and geNomad.

Main Results:

  • skandiver efficiently detects MGEs from genomic sequences using a divergence-based approach.
  • The tool queries large genome datasets rapidly, requiring minimal memory.
  • While skandiver's recall for isolated plasmids is lower than some methods, it excels in identifying integrated plasmids and novel MGEs without database comparison.

Conclusions:

  • skandiver provides a scalable and efficient method for elucidating mobile element profiles in bacterial genomes.
  • The tool's ability to detect novel MGEs without reference databases makes it valuable for discovery.
  • Divergence-based characterization offers a robust paradigm for understanding MGE diversity and mobility.