Evolutionary Puzzles: An Introduction to Genome Rearrangement

  • Mathieu Blanchette
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 2074)


This paper is intended to serve as an introduction to genome rearrangement and its use for inferring phylogenetic trees. We begin with a brief description of the major players of the field (chromosomes, genes, etc.) and the types of mutations that can affect them, focussing obviously on genome rearrangement. This leads to a simple mathematical representation of the data (the order of the genes on the chromosomes), and the operations that modify it (inversions, transpositions, and translocations).

We then consider the problem of inferring phylogenetic (evolutionary) trees from genetic data. We briefly present the two major approaches to solve this problem. The first one, called distance matrix method, relies on the estimation of the evolutionary distance between each pair of species considered. In the context of gene order data, a useful measure of evolutionary distance is the minimum number of basic operations needed to transform the gene order of one species into that of another. This family of algorithmic problems has been extensively studied, and we review the major results in the field.

The second approach to inferring phylogenetic trees consists of finding a minimal Steiner tree in the space of the data considered, whose leaves are the species of interest. This approach leads to much harder algorithmic problems. The main results obtained here are based on a simple evolutionary metric, the number of breakpoints.

Throughout the paper, we report on various biological data analyses done using the different techniques discussed. We also point out some interesting open problems and current research directions.


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. 1.
    V. Bafna and P. A. Pevzner. Sorting by transpositions. Proceedings of the 6th Annual ACM-SIAM Symposium on Discrete Algorithms (SODA 95), 614–623, 1995.Google Scholar
  2. 2.
    V. Bafna and P. A. Pevzner. Sorting by reversals: Genome rearrangements in plant organelles and evolutionary history of X chromosome. Molecular Biology and Evolution, 12: 239–246, 1995.Google Scholar
  3. 3.
    M. Blanchette, T. Kunisawa and D. Sankoff. Gene order breakpoint evidence in animal mitochondrial phylogeny. Journal of Molecular Evolution, 49, 193–203, 1998.CrossRefGoogle Scholar
  4. 4.
    M. Blanchette, T. Kunisawa and D. Sankoff. Parametric genome rearrangement. Gene, 172,GC:11–17, 1996.Google Scholar
  5. 5.
    A. Caprara. Sorting by Reversals is Difficult. Proceedings of the First Annual International Conference on Computational Molecular Biology (RECOMB 97), 75–83, 1997.Google Scholar
  6. 6.
    Cosner, M. E., Jansen, R. K., Moret, B. M. E., Raubeson, L. A., Wang, L. S., Warnow, T., and Wyman, S.. A new fast heuristic for computing the breakpoint phylogeny and a phylogenetic analysis of a group of highly rearranged chloroplast genomes.Proc. 8th Int’l Conf. on Intelligent Systems for Molecular Biology ISMB-2000, San Diego, 104–115, 2000.Google Scholar
  7. 7.
    S. Hannenhalli and P. A. Pevzner. Transforming men into mice (polynomial algorithm for genomic distance problem). Proceedings of the IEEE 36th Annual Symposium on Foundations of Computer Science, 581–592, 1995.Google Scholar
  8. 8.
    H. Kaplan, R. Shamir and R. E. Tarjan. Faster and Simpler Algorithm for Sorting Signed Permutations by Reversals. Proceedings of the Eighth Annual ACM-SIAM Symposium on Discrete Algorithms (SODA 97), 1997.Google Scholar
  9. 9.
    J. Kececioglu and D. Sankoff. Exact and approximation algorithms for sorting by reversals, with application to genome rearrangement. Algorithmica, 13: 180–210, 1995.MATHCrossRefMathSciNetGoogle Scholar
  10. 10.
    E. L. Lawler, J. K. Lenstra, A. H. G. Rinnooy Kan, and D. B. Shmoys The Travelling Salesman Problem. John Wiley and Sons, 1985.Google Scholar
  11. 11.
    I. Pe’er and R. Shamir. The median problems for breakpoints are NP-complete. Electronic Colloquium on Computational Complexity, Technical Report 98-071, 1998.Google Scholar
  12. 12.
    Sankoff, D. and Blanchette, M. Multiple genome rearrangement and breakpoint phylogeny. Journal of Computational Biology 5, 555–570, 1998.CrossRefGoogle Scholar
  13. 13.
    D. Sankoff, G. Leduc, N. Antoine, B. Paquin, B. F. Lang and R. Cedergren. Gene order comparisons for phylogenetic inference: Evolution of the mitochondrial genome. Proceedings of the National Academy of Sciences USA, 89: 6575–6579, 1992.CrossRefGoogle Scholar
  14. 14.
    Swoórd, D. L., G. J. Olsen, P. J. Waddell, and D. M. Hillis. In Molecular Systematics (2nd ed., D. M. Hillis, C. Moritz, and B. K. Mable, eds.). Sinauer Assoc. Sunderland, MA. Ch. 11 (pp. 407–514), 1996.Google Scholar
  15. 15.
    G. A. Watterson, W. J. Ewens, T. E. Hallet A. Morgan. The chromosome inversion problem. Journal of Theoretical Biology, 99: 1–7, 1982.CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2001

Authors and Affiliations

  • Mathieu Blanchette
    • 1
  1. 1.Department of Computer Science and EngineeringUniversity of WashingtonSeattleUSA

Personalised recommendations