1-Mb resolution array-based comparative genomic hybridization using a BAC clone set optimized for cancer gene analysis

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 approximately 4100 publicly available human bacterial artificial chromosome (BAC) clones evenly spaced at approximately 1-Mb resolution across the genome, which includes direct coverage of approximately 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.

Figure 1

Flow chart describing the optimization process and the number of clones removed or added at each step. ^*Poor hybridization performance is defined in the text. ^**A list of the cancer-related genes can be found in the Supplemental data.

Figure 2

UCSC Human Genome Browser view of chromosome 2 (http://www.genome.ucsc.edu) with coverage of the optimized clone set (top track), the initial clone set (middle track), and the BAC Resource Consortium set (bottom track, from Cheung et al. 2001). The improved resolution of the optimized set is representative of that seen genome-wide.

Figure 3

Cancer cell line dye-swap experiments loaded into the CGHAnalyzer main window (chromosome 1). Columns depict the copy number profile of each cell line with respect to its genome position on chromosome 2. Copy number gains are shown in green, losses are shown in red. Selecting a clone or region gives access to these data and the raw data in another window.

Figure 4

CircleViewer screen shots summarizing data from two cancer cell lines (NB13, left; PA1, right). The concentric circles represent chromosomes in order of size, and each spot represents a BAC clone. Gains (green) and losses (red) are derived from intensity ratios above or below an adjustable threshold (here, deletion ≤ 0.8, gains ≥). BAC clones can be identified and raw data accessed interactively.

Figure 5

CGHBrowser screen shot depicting a chromosome 1p deletion flanked by a copy number increase in the lung cancer cell line NCI-H209. This view can be used to access raw data and estimate the amplitude of copy number changes. Scores from any spot-calling algorithm and Cy3/Cy5 ratios in a log₂ and linear scale can also be visualized. The abscissa can be set to display data scaled to genome coordinates or in linear order (shown here). Intensity ratios with tumor DNA labeled with Cy3-dCTP are red; the same DNA labeled with Cy5-dCTP is represented in yellow. Ratios above or below the threshold for normal variation that represent true copy number gain or loss should have a dye-swap match of equal magnitude above or below y = 1 or y = -1, respectively (arrow A). Clones not conforming to this pattern consistently in normal:normal cohybridizations were eliminated from the set (arrow B).