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Algorithms for the quantitative Lock/Key model of cytoplasmic incompatibility.

Tiziana Calamoneri1, Mattia Gastaldello2,3,1, Arnaud Mary2,3

  • 1Department of Computer Science, Sapienza University of Rome, viale Regina Elena 295, 00161 Rome, Italy.

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|July 25, 2020
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Summary
This summary is machine-generated.

Cytoplasmic incompatibility (CI) is a reproductive manipulation by Wolbachia parasites. This study models CI using graph theory, developing algorithms to find all solutions for parasite-host interactions.

Keywords:
Chain subgraph cover problemCytoplasmic incompatibilityEnumeration algorithmsExact exponential algorithmsInterval order

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Area of Science:

  • Evolutionary Biology
  • Computational Biology
  • Parasitology

Background:

  • Cytoplasmic incompatibility (CI) is a phenomenon where Wolbachia endosymbionts alter host reproduction.
  • The precise molecular mechanisms underlying CI are not fully understood.
  • Theoretical models, like the Lock-Key model, are crucial for understanding CI dynamics.

Purpose of the Study:

  • To model Cytoplasmic incompatibility (CI) using graph theory, specifically the problem of covering bipartite graphs with chain subgraphs.
  • To develop and analyze algorithms for finding minimal and maximal chain subgraph covers.
  • To address the issue of multiple biologically distinct optimal solutions in CI modeling.

Main Methods:

  • Modeling CI as finding minimal chain subgraph covers of a bipartite graph.
  • Developing an exponential time algorithm for the NP-hard edge cover problem.
  • Designing a quasi-polynomial time algorithm for enumerating all minimal chain subgraph covers.
  • Improving algorithms for enumerating maximal chain subgraphs.

Main Results:

  • An exponential algorithm for the CI bipartite graph covering problem.
  • A quasi-polynomial time algorithm for enumerating all minimal chain subgraph covers.
  • Enhanced methods for enumerating maximal chain subgraphs.
  • Demonstration of the practical application of these methods on real-world data.

Conclusions:

  • The developed algorithms provide new tools for analyzing Cytoplasmic incompatibility (CI) and Wolbachia-host interactions.
  • Addressing multiple optimal solutions is critical for accurate biological interpretation.
  • The computational approach offers insights into the complex reproductive manipulations driven by parasites.