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Approximate Search for Known Gene Clusters in New Genomes Using PQ-Trees

Authors Galia R. Zimerman, Dina Svetlitsky, Meirav Zehavi, Michal Ziv-Ukelson



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Author Details

Galia R. Zimerman
  • Ben Gurion University of the Negev, Beer Sheva, Israel
Dina Svetlitsky
  • Ben Gurion University of the Negev, Beer Sheva, Israel
Meirav Zehavi
  • Ben Gurion University of the Negev, Beer Sheva, Israel
Michal Ziv-Ukelson
  • Ben Gurion University of the Negev, Beer Sheva, Israel

Acknowledgements

Many thanks to Lev Gourevitch for his excellent implementation of a PQ-tree builder. We also thank the anonymous WABI reviewers for their very helpful comments.

Cite AsGet BibTex

Galia R. Zimerman, Dina Svetlitsky, Meirav Zehavi, and Michal Ziv-Ukelson. Approximate Search for Known Gene Clusters in New Genomes Using PQ-Trees. In 20th International Workshop on Algorithms in Bioinformatics (WABI 2020). Leibniz International Proceedings in Informatics (LIPIcs), Volume 172, pp. 1:1-1:24, Schloss Dagstuhl - Leibniz-Zentrum für Informatik (2020)
https://doi.org/10.4230/LIPIcs.WABI.2020.1

Abstract

We define a new problem in comparative genomics, denoted PQ-Tree Search, that takes as input a PQ-tree T representing the known gene orders of a gene cluster of interest, a gene-to-gene substitution scoring function h, integer parameters d_T and d_S, and a new genome S. The objective is to identify in S approximate new instances of the gene cluster that could vary from the known gene orders by genome rearrangements that are constrained by T, by gene substitutions that are governed by h, and by gene deletions and insertions that are bounded from above by d_T and d_S, respectively. We prove that the PQ-Tree Search problem is NP-hard and propose a parameterized algorithm that solves the optimization variant of PQ-Tree Search in O^*(2^{γ}) time, where γ is the maximum degree of a node in T and O^* is used to hide factors polynomial in the input size. The algorithm is implemented as a search tool, denoted PQFinder, and applied to search for instances of chromosomal gene clusters in plasmids, within a dataset of 1,487 prokaryotic genomes. We report on 29 chromosomal gene clusters that are rearranged in plasmids, where the rearrangements are guided by the corresponding PQ-tree. One of these results, coding for a heavy metal efflux pump, is further analysed to exemplify how PQFinder can be harnessed to reveal interesting new structural variants of known gene clusters.

Subject Classification

ACM Subject Classification
  • Applied computing → Bioinformatics
Keywords
  • PQ-Tree
  • Gene Cluster
  • Efflux Pump

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