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MultiTwin: A Software Suite to Analyze Evolution at Multiple Levels of Organization Using Multipartite Graphs.

Eduardo Corel1, Jananan S Pathmanathan1, Andrew K Watson1

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Evolutionary biology benefits from network analysis, integrating mobile genetic elements and hosts. MultiTwin software simplifies analyzing complex gene-sharing networks for evolutionary insights.

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Area of Science:

  • Evolutionary biology
  • Genomics
  • Bioinformatics

Background:

  • Introgressive processes offer a flexible view of evolution.
  • Network-based methods in comparative genomics can incorporate extrachromosomic elements like viruses.
  • Integrating multiple biological organization levels aids gene sharing analysis and classification.

Purpose of the Study:

  • To present MultiTwin, an integrated software suite for constructing, structuring, and analyzing multipartite graphs in evolutionary biology.
  • To provide accessible algorithmic tools for researchers without extensive programming skills.

Main Methods:

  • Development of the MultiTwin software suite for multipartite graph analysis.
  • Application of a bipartite approach using gene family-genome graphs.
  • Comparative analysis of gene content in microbial communities and mobile genetic elements.

Main Results:

  • MultiTwin facilitates the analysis of gene sharing patterns across diverse biological entities.
  • The software enables comprehensive evolutionary studies by integrating various biological organization levels.
  • Demonstrated utility in analyzing pathogenicity traits in prokaryotes using a bipartite graph approach.

Conclusions:

  • MultiTwin democratizes the analysis of complex evolutionary networks.
  • The tool enhances understanding of gene sharing and evolutionary relationships.
  • Facilitates evolutionary insights into microbial communities and pathogenicity.