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Heuristics for Reversal Distance Between Genomes with Duplicated Genes

  • Gabriel Siqueira
  • Klairton Lima BritoEmail author
  • Ulisses Dias
  • Zanoni Dias
Conference paper
  • 38 Downloads
Part of the Lecture Notes in Computer Science book series (LNCS, volume 12099)

Abstract

In comparative genomics, one goal is to find similarities between genomes of different organisms. Comparisons using genome features like genes, gene order, and regulatory sequences are carried out with this purpose in mind.

Genome rearrangements are mutational events that affect large extensions of the genome. They are responsible for creating extant species with conserved genes in different positions across genomes.

Close species—from an evolutionary point of view—tend to have the same set of genes or share most of them. When we consider gene order to compare two genomes, it is possible to use a parsimony criterion to estimate how close the species are. We are interested in the shortest sequence of genome rearrangements capable of transforming one genome into the other, which is named rearrangement distance.

Reversal is one of the most studied genome rearrangements events. This event acts in a segment of the genome, inverting the position and possibly the orientation of genes in it.

When the genome has no gene repetition, a common approach is to map it as a permutation such that each element represents a conserved block.

When genomes have replicated genes, this mapping is usually performed using strings. The number of replicas depends on the organisms being compared, but in many scenarios, it tends to be small. In this work, we study the reversal distance between genomes with duplicated genes considering that the orientation of genes is unknown. We present three heuristics that use techniques like genetic algorithms and local search. We conduct experiments using a database of simulated genomes and compared our results with other algorithms from the literature.

Keywords

Genome rearrangement Reversal Heuristics Duplicated genes 

Notes

Acknowledgments

This work was supported by the National Council for Scientific and Technological Development - CNPq (grants 400487/2016-0, 425340/2016-3, 304380/2018-0, and 140466/2018-5), the São Paulo Research Foundation - FAPESP (grants 2015/11937-9, 2017/12646-3, and 2017/16246-0), the Brazilian Federal Agency for the Support and Evaluation of Graduate Education - CAPES, and the CAPES/COFECUB program (grant 831/15).

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Copyright information

© Springer Nature Switzerland AG 2020

Authors and Affiliations

  1. 1.Institute of ComputingUniversity of CampinasCampinasBrazil
  2. 2.School of TechnologyUniversity of CampinasLimeiraBrazil

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