Inferring Gene Orders from Gene Maps Using the Breakpoint Distance

  • Guillaume Blin
  • Eric Blais
  • Pierre Guillon
  • Mathieu Blanchette
  • Nadia El-Mabrouk
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4205)


Preliminary to most comparative genomics studies is the annotation of chromosomes as ordered sequences of genes. Unfortunately, different genetic mapping techniques usually give rise to different maps with unequal gene content, and often containing sets of unordered neighboring genes. Only partial orders can thus be obtained from combining such maps. However, once a total order O is known for a given genome, it can be used as a reference to order genes of a closely related species characterized by a partial order P. In this paper, the problem is to find a linearization of P that is as close as possible to O in term of the breakpoint distance. We first prove an NP-complete complexity result for this problem. We then give a dynamic programming algorithm whose running time is exponential for general partial orders, but polynomial when the partial order is derived from a bounded number of genetic maps. A time-efficient greedy heuristic is then given for the general case, with a performance higher than 90% on simulated data. Applications to the analysis of grass genomes are presented.


Partial Order Total Order Dynamic Programming Algorithm Greedy Heuristic Maize Chromosome 
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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Guillaume Blin
    • 1
  • Eric Blais
    • 2
  • Pierre Guillon
    • 1
  • Mathieu Blanchette
    • 2
  • Nadia El-Mabrouk
    • 3
  1. 1.IGM-LabInfo – UMR CNRS 8049Université de Marne-la-ValléeFrance
  2. 2.McGill Centre for BioinformaticsMcGill UniversityCanada
  3. 3.DIROUniversité de MontréalCanada

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