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The chimeric mapping problem: algorithmic strategies and performance evaluation on synthetic genomic data

D Greenberg1, S Istrail

  • 1Sandia National Laboratories, Algorithms and Discrete Mathematics Department, Albuquerque, NM.

Computers & Chemistry
|September 1, 1994
PubMed
Summary
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This study introduces new algorithms to address chimerism in DNA physical mapping, improving chromosome reconstruction accuracy for the Human Genome Project. The developed methods effectively identify and resolve chimeric DNA fragments, leading to higher quality genomic maps.

Area of Science:

  • Genomics
  • Bioinformatics
  • Computational Biology

Background:

  • Physical mapping of chromosomes is crucial for the Human Genome Project.
  • Current DNA mapping techniques lose information and order during fragmentation.
  • Chimeric DNA clones, fusions of distinct DNA pieces, complicate accurate map reconstruction.

Purpose of the Study:

  • To present the first algorithms for analyzing and correcting chimerism in DNA physical mapping.
  • To develop software that improves the accuracy and efficiency of chromosome map reconstruction.
  • To address the critical but under-researched problem of chimeric DNA in genomic mapping.

Main Methods:

  • Developed algorithms based on Lander's model for analyzing chimerism.
  • Created optimization functions with minimizations correlating to physical map quality.

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  • Employed two distinct optimization functions to mitigate solution bias.

    • Main Results:

    • Algorithms are guaranteed to produce near-optimal solutions for NP-complete problems.
    • Minimizing chimeric fragments or maximum fragments per clone correlates with high-quality maps.
    • Simulated data experiments show potential for high-quality solutions with real genomic data.

    Conclusions:

    • The presented algorithms offer a significant advancement in handling chimerism for DNA physical mapping.
    • These methods have the potential to improve the accuracy of chromosome reconstruction in genomic research.
    • Further testing on real-world data from major genomic centers is planned.