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Computational BAC clone contig assembly for comprehensive genome analysis.

Anna Lapuk1, Stanislav Volik, Robert Vincent

  • 1Department of Laboratory Medicine and UCSF Comprehensive Cancer Center, University of California San Francisco, USA.

Genes, Chromosomes & Cancer
|March 23, 2004
PubMed
Summary
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This study introduces a new computer program for assembling bacterial artificial chromosome (BAC) contigs, improving resolution for array comparative genomic hybridization (aCGH) in cancer research. This enhances the detection of genome copy number changes in ovarian and breast cancers.

Area of Science:

  • Genomics
  • Cancer Research
  • Bioinformatics

Background:

  • Comparative genomic hybridization (CGH) detects genome copy number changes in diseases like cancer.
  • Array CGH offers higher resolution for identifying genomic aberrations.
  • Bacterial artificial chromosomes (BACs) are crucial for high-resolution array CGH.

Purpose of the Study:

  • To develop a computational tool for automatically assembling minimally overlapping BAC contigs.
  • To enhance the resolution of array CGH for detecting genomic abnormalities in cancer.
  • To analyze specific chromosomal regions recurrently altered in ovarian and breast cancers.

Main Methods:

  • Developed a computer program to assemble BAC contigs using BAC end-sequences and normal genome data.

Related Experiment Videos

  • Utilized array CGH with contiguous BAC arrays for high-resolution analysis.
  • Focused on chromosome bands 3q25-q27, 8q24, and chromosome arm 20q in cancer cell lines.

    • Main Results:

    • Successfully assembled and annotated BAC contigs for key cancer-associated chromosomal regions.
    • Demonstrated the utility of the program in characterizing copy number alterations.
    • Illustrative analyses showed amplifications in breast and ovarian tumor cell lines.

    Conclusions:

    • The developed program automates BAC contig assembly, enabling higher resolution array CGH.
    • This approach facilitates the precise mapping of genomic aberrations in human cancers.
    • Improved detection of copy number changes aids in understanding cancer development.