1-Mb Resolution Array-Based Comparative Genomic Hybridization Using a BAC Clone Set Optimized for Cancer Gene Analysis (original) (raw)

  1. Joel Greshock1,
  2. Tara L. Naylor1,
  3. Adam Margolin1,
  4. Sharon Diskin1,
  5. Stephen H. Cleaver2,
  6. P. Andrew Futreal3,
  7. Pieter J. deJong4,
  8. Shaying Zhao5,
  9. Michael Liebman1, and
  10. Barbara L. Weber1,6
  11. 1 Abramson Family Cancer Research Institute, University of Pennsylvania, Philadelphia, Pennsylvania 19104, USA
  12. 2 Georgia State University, Atlanta, Georgia 30303, USA
  13. 3 Wellcome Trust Sanger Institute, Hinxton CB10 15A, UK
  14. 4 Children's Hospital Oakland-BACPAC Resources, Oakland, California 94609, USA
  15. 5 The Institute for Genomic Research, Rockville, Maryland 20850, USA

Abstract

Array-based comparative genomic hybridization (aCGH) is a recently developed tool for genome-wide determination of DNA copy number alterations. This technology has tremendous potential for disease-gene discovery in cancer and developmental disorders as well as numerous other applications. However, widespread utilization of a CGH has been limited by the lack of well characterized, high-resolution clone sets optimized for consistent performance in aCGH assays and specifically designed analytic software. We have assembled a set of ∼4100 publicly available human bacterial artificial chromosome (BAC) clones evenly spaced at ∼1-Mb resolution across the genome, which includes direct coverage of ∼400 known cancer genes. This aCGH-optimized clone set was compiled from five existing sets, experimentally refined, and supplemented for higher resolution and enhancing mapping capabilities. This clone set is associated with a public online resource containing detailed clone mapping data, protocols for the construction and use of arrays, and a suite of analytical software tools designed specifically for aCGH analysis. These resources should greatly facilitate the use of aCGH in gene discovery.

Footnotes