Genome Rearrangement Phylogeny Using Weighbor

  • Li-San Wang 
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 2452)

Abstract

Evolution operates on whole genomes by operations that change the order and strandedness of genes within the genomes. This type of data presents new opportunities for discoveries about deep evolutionary rearrangement events. Several distance-based phylogenetic reconstruction methods have been proposed [12],[21],[19] that use neighbor joining (NJ) [16] with the expected breakpoint or inversion distances after k rearrangement events. In this paper we study the variance of the breakpoint and inversion distances. The result is combined with Weighbor [5], an improved version of NJ using the variance of true evolutionary distance estimators, to yield two new methods, Weighbor-IEBP and Weighbor-EDE. Experiments show the new methods have better accuracy than all previous distance-based methods, and are robust against model parameter misspecifications.

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    K. Atteson. The performance of the neighbor-joining methods of phylogenetic reconstruction. Algorithmica, 25(2/3):251–278, 1999.MATHCrossRefMathSciNetGoogle Scholar
  2. 2.
    D. A. Bader, B. M. E. Moret, and M. Yan. A linear-time algorithm for computing inversion distances between signed permutations with an experimental study. J. Comput. Biol., 8(5):483–491, 2001.CrossRefGoogle Scholar
  3. 3.
    V. Bafna and P. Pevzner. Sorting permutations by transpositions. In Proc. 6th Annual ACM-SIAM Symp. on Disc. Alg. SODA95, pages 614–623. ACM Press, 1995.Google Scholar
  4. 4.
    M. Blanchette, M. Kunisawa, and D. Sankoff. Gene order breakpoint evidence in animal mitochondrial phylogeny. J. Mol. Evol., 49:193–203, 1999.CrossRefGoogle Scholar
  5. 5.
    W. J. Bruno, N. D. Socci, and A. L. Halpern. Weighted neighbor joining: A likelihood-based approach to distance-based phylogeny reconstruction. Mol. Biol. Evol., 17:189–197, 2000. http://www.t10.lanl.gov/billb/weighbor/.Google Scholar
  6. 6.
    S. R. Downie and J. D. Palmer. Use of chloroplast DNA rearrangements in reconstructing plant phylogeny. In P. Soltis, D. Soltis, and J.J. Doyle, editors, Molecular Systematics of Plants, volume 49, pages 14–35. Chapman & Hall, 1992.Google Scholar
  7. 7.
    O. Gascuel. BIONJ: an improved version of the nj algorithm based on a smple model of sequence data. Mol. Biol. Evol., 14:685–695, 1997. http://www.crt.umontreal.ca/~olivierg/bionj.html.Google Scholar
  8. 8.
    O. Gascuel. Personal communication, April 2001.Google Scholar
  9. 9.
    R. L. Graham, D. E. Knuth, and O. Patashnik. Concrete Mathematics. Addison-Wesley, 1994. 2nd ed.Google Scholar
  10. 10.
    S. Hannenhalli and P. Pevzner. Transforming cabbage into turnip (polynomial algorithm for genomic distance problems). In Proc. 27th Annual ACM Symp. on Theory of Comp. STOC95, pages 178–189. ACM Press, NY, 1995.Google Scholar
  11. 11.
    S. Kumar. Minimum evolution trees. Mol. Biol. Evol., 15:584–593, 1996.Google Scholar
  12. 12.
    B. M. E. Moret, L.-S. Wang, T. Warnow, and S. Wyman. New approaches for reconstructing phylogenies based on gene order. In Proc. 9th Intl. Conf. on Intel. Sys. for Mol. Bio. (ISMB 2001), pages 165–173. AAAI Press, 2001.Google Scholar
  13. 13.
    G. W. Oehlert. A note on the delta method. Amer. Statist., 46:27–29, 1992.CrossRefMathSciNetGoogle Scholar
  14. 14.
    R. G. Olmstead and J. D. Palmer. Chloroplast DNA systematics: a review of methods and data analysis. Amer. J. Bot., 81:1205–1224, 1994.CrossRefGoogle Scholar
  15. 15.
    L. A. Raubeson and R. K. Jansen. Chloroplast DNA evidence on the ancient evolutionary split in vascular land plants. Science, 255:1697–1699, 1992.CrossRefGoogle Scholar
  16. 16.
    N. Saitou and M. Nei. The neighbor-joining method: A new method for reconstructing phylogenetic trees. Mol. Biol. & Evol., 4:406–425, 1987.Google Scholar
  17. 17.
    D. Sankoff and M. Blanchette. Probability models for genome rearrangements and linear invariants for phylogenetic inference. Proc. 3rd Int’l Conf. on Comput. Mol. Bio. (RECOMB99), pages 302–309, 1999.Google Scholar
  18. 18.
    D. Swoffrd. PAUP* 4.0. Sinauer Associates Inc, 2001.Google Scholar
  19. 19.
    L.-S. Wang. Improving the accuracy of evolutionary distances between genomes. In Lec. Notes in Comp. Sci. No. 2149: Proc. 1st Workshop for Alg. & Bio. Inform. WABI 2001, pages 175–188. Springer Verlag, 2001.Google Scholar
  20. 20.
    L.-S. Wang, R. K. Jansen, B. M. E. Moret, L. A. Raubeson, and T. Warnow. Fast phylogenetic methods for the analysis of genome rearrangement data: An empirical study. In Proc. 7th Pacific Symp. Biocomputing (PSB 2002), pages 524–535, 2002.Google Scholar
  21. 21.
    L.-S. Wang and T. Warnow. Estimating true evolutionary distances between genomes. In Proc. 33th Annual ACM Symp. on Theory of Comp. (STOC 2001), pages 637–646. ACM Press, 2001.Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2002

Authors and Affiliations

  • Li-San Wang 
    • 1
  1. 1.Department of Computer SciencesUniversity of TexasAustinUSA

Personalised recommendations