Exact and approximation algorithms for sorting by reversals, with application to genome rearrangement Article Received: 09 October 1992 Revised: 19 February 1993 DOI :
10.1007/BF01188586

Cite this article as: Kececioglu, J. & Sankoff, D. Algorithmica (1995) 13: 180. doi:10.1007/BF01188586 Abstract Motivated by the problem in computational biology of reconstructing the series of chromosome inversions by which one organism evolved from another, we consider the problem of computing the shortest series of reversals that transform one permutation to another. The permutations describe the order of genes on corresponding chromosomes, and areversal takes an arbitrary substring of elements, and reverses their order.

For this problem, we develop two algorithms: a greedy approximation algorithm, that finds a solution provably close to optimal inO (n ^{2} ) time and0(n) space forn -element permutations, and a branch- and-bound exact algorithm, that finds an optimal solution in0(mL(n, n)) time and0 (n ^{2} ) space, wherem is the size of the branch- and-bound search tree, andL(n, n) is the time to solve a linear program ofn variables andn constraints. The greedy algorithm is the first to come within a constant factor of the optimum; it guarantees a solution that uses no more than twice the minimum number of reversals. The lower and upper bounds of the branch- and-bound algorithm are a novel application of maximum-weight matchings, shortest paths, and linear programming.

In a series of experiments, we study the performance of an implementation on random permutations, and permutations generated by random reversals. For permutations differing byk random reversals, we find that the average upper bound on reversal distance estimatesk to within one reversal fork <1/2n andn <100. For the difficult case of random permutations, we find that the average difference between the upper and lower bounds is less than three reversals forn <50. Due to the tightness of these bounds, we can solve, to optimality, problems on 30 elements in a few minutes of computer time. This approaches the scale of mitochondrial genomes.

Key words Computational biology Approximation algorithms Branch- and-bound algorithms Experimental analysis of algorithms Edit distance Permutations Sorting by reversals Chromosome inversions Genome rearrangements This research was supported by a postdoctoral fellowship from the Program in Mathematics and Molecular Biology of the University of California at Berkeley under National Science Foundation Grant DMS-8720208, and by a fellowship from the Centre de recherches mathématiques of the Université de Montréal.

This research was supported by grants from the Natural Sciences and Engineering Research Council of Canada, and the Fonds pour la formation de chercheurs et l'aide à la recherche (Québec). The author is a fellow of the Canadian Institute for Advanced Research.

Communicated by E. W. Myers.

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Authors and Affiliations 1. Department of Computer Science The University of Georgia Athens USA 2. Centre de recherches mathématiques Université de Montréal Montréal Canada