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Weighted Genomic Distance Can Hardly Impose a Bound on the Proportion of Transpositions

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Book cover Research in Computational Molecular Biology (RECOMB 2011)

Part of the book series: Lecture Notes in Computer Science ((LNBI,volume 6577))

Abstract

Genomic distance between two genomes, i.e., the smallest number of genome rearrangements required to transform one genome into the other, is often used as a measure of evolutionary closeness of the genomes in comparative genomics studies. However, in models that include rearrangements of significantly different “power” such as reversals (that are “weak” and most frequent rearrangements) and transpositions (that are more “powerful” but rare), the genomic distance typically corresponds to a transformation with a large proportion of transpositions, which is not biologically adequate.

Weighted genomic distance is a traditional approach to bounding the proportion of transpositions by assigning them a relative weight α > 1. A number of previous studies addressed the problem of computing weighted genomic distance with α ≤ 2.

Employing the model of multi-break rearrangements on circular genomes, that captures both reversals (modelled as 2-breaks) and transpositions (modelled as 3-breaks), we prove that for α ∈ (1,2], a minimum-weight transformation may entirely consist of transpositions, implying that the corresponding weighted genomic distance does not actually achieve its purpose of bounding the proportion of transpositions. We further prove that for α ∈ (1,2), the minimum-weight transformations do not depend on a particular choice of α from this interval. We give a complete characterization of such transformations and show that they coincide with the transformations that at the same time have the shortest length and make the smallest number of breakages in the genomes.

Our results also provide a theoretical foundation for the empirical observation that for α < 2, transpositions are favored over reversals in the minimum-weight transformations.

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References

  1. Alekseyev, M.A.: Multi-Break Rearrangements and Breakpoint Re-uses: from Circular to Linear Genomes. Journal of Computational Biology 15(8), 1117–1131 (2008)

    Article  MathSciNet  Google Scholar 

  2. Alekseyev, M.A., Pevzner, P.A.: Are There Rearrangement Hotspots in the Human Genome? PLoS Computational Biology 3(11), e209 (2007)

    Article  MathSciNet  Google Scholar 

  3. Alekseyev, M.A., Pevzner, P.A.: Multi-Break Rearrangements and Chromosomal Evolution. Theoretical Computer Science 395(2-3), 193–202 (2008)

    Article  MathSciNet  MATH  Google Scholar 

  4. Bader, M., Ohlebusch, E.: Sorting by weighted reversals, transpositions, and inverted transpositions. Journal of Computational Biology 14(5), 615–636 (2007)

    Article  MathSciNet  MATH  Google Scholar 

  5. Bafna, V., Pevzner, P.A.: Genome rearrangements and sorting by reversals. SIAM Journal on Computing 25, 272–289 (1996)

    Article  MathSciNet  MATH  Google Scholar 

  6. Blanchette, M., Kunisawa, T., Sankoff, D.: Parametric genome rearrangement. Gene 172(1), GC11–GC17 (1996)

    Article  Google Scholar 

  7. Christie, D.A.: Sorting permutations by block-interchanges. Information Processing Letters 60(4), 165–169 (1996)

    Article  MathSciNet  MATH  Google Scholar 

  8. Elias, I., Hartman, T.: A 1.375-approximation algorithm for sorting by transpositions. IEEE/ACM Transactions on Computational Biology and Bioinformatics 3, 369–379 (2006)

    Article  Google Scholar 

  9. Eriksen, N.: (1 + ε)-Approximation of Sorting by Reversals and Transpositions. In: Gascuel, O., Moret, B.M.E. (eds.) WABI 2001. LNCS, vol. 2149, pp. 227–237. Springer, Heidelberg (2001)

    Chapter  Google Scholar 

  10. Fertin, G., Labarre, A., Rusu, I., Tannier, E.: Combinatorics of Genome Rearrangements. The MIT Press, Cambridge (2009)

    Book  MATH  Google Scholar 

  11. Hannenhalli, S., Pevzner, P.: Transforming men into mouse (polynomial algorithm for genomic distance problem). In: Proceedings of the 36th Annual Symposium on Foundations of Computer Science, pp. 581–592 (1995)

    Google Scholar 

  12. Hannenhalli, S., Pevzner, P.A.: Transforming Cabbage into Turnip (polynomial algorithm for sorting signed permutations by reversals). In: Proceedings of the 27th Annual ACM Symposium on the Theory of Computing, pp. 178–189 (1995); full version appeared in Journal of ACM 46, 1–27 (1995)

    Google Scholar 

  13. Radcliffe, A.J., Scott, A.D., Wilmer, E.L.: Reversals and Transpositions Over Finite Alphabets. SIAM J. Discrete Math. 19, 224–244 (2005)

    Article  MathSciNet  MATH  Google Scholar 

  14. Yancopoulos, S., Attie, O., Friedberg, R.: Efficient sorting of genomic permutations by translocation, inversion and block interchange. Bioinformatics 21, 3340–3346 (2005)

    Article  Google Scholar 

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Jiang, S., Alekseyev, M.A. (2011). Weighted Genomic Distance Can Hardly Impose a Bound on the Proportion of Transpositions. In: Bafna, V., Sahinalp, S.C. (eds) Research in Computational Molecular Biology. RECOMB 2011. Lecture Notes in Computer Science(), vol 6577. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-20036-6_13

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  • DOI: https://doi.org/10.1007/978-3-642-20036-6_13

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-20035-9

  • Online ISBN: 978-3-642-20036-6

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