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Background on Microarrays

Microarrays MediaBook
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Microarrays are based on the process of DNA hybridization. Tens of thousands of genes are placed on a glass slide, allowing mRNA levels to be measured on a global scale. The hybridizations performed on this single gene chip are equivalent to performing thousands of Southern or Northern blots (Southern, 1975; Alwine, 1977) in one day.

Microarray analysis consists of these major components:

  1. Array fabrication (Schena et al., 1995)--PCR-amplified cDNA clones or oligonucleotides are spotted (i.e., printed) onto glass microscope slides that have been coated with poly-L-lysine or aminosilane; a robotic system is used to construct the arrays. These tethered DNA elements are usually referred to as the "TARGET."

  2. Sample preparation, "PROBE" labeling, and hybridization--Total or poly(A)+ RNA is extracted from control and sample sources; the RNA is then converted to cDNA by reverse transcriptase. Fluorescently labeled cDNA samples are prepared by direct or indirect methods. The labeled PROBES prepared from the two RNA sources are co-hybridized to the same DNA chip.

    RNA isolation is a critical step in the experimental procedure; the purified RNA must always be visualized by denaturing gel electrophoresis to verify the integrity of the 26S (yeast)/28S (mammalian) and 18S ribosomal RNA bands.

  3. Data collection and analysis--The hybridized array is scanned with a confocal laser that is capable of differentiating the fluorescently labeled probes. After scanning, a grid must be placed on the image and the spots representing the arrayed genes must be identified; then the background is calculated locally for each spot and is subtracted from the hybridization intensities. Following normalization of the relative fluorescence intensities in each scanned channel, differentially expressed genes can be identified.

    Typically, the sample label is red (Cy5) and the control label is green (Cy3). A yellow spot indicates no change in the expression level, red indicates an upregulation, and green indicates a downregulation.

With just one experimental condition and a control, the data analysis will be limited to a list of regulated genes ranked by the fold-change or by the significance of the change determined in a t-test.

With multiple experimental conditions (e.g., mutants or patients in a drug study), the genes are often grouped into clustersthat behave similarly under the different conditions. Complex computational methods such as heirarchical clustering or k-means are used to analyze the massive amounts of data generated by these experiments. Gene clusters are visualized with trees or color-coded matrices.

Microarrays are a powerful tool to investigate gene expression, but it is important to remember some limitations of expression analysis:

However, microarray studies provide invaluable insights into the patterns of gene expression and how these patterns change during disease, development, or exposure to agents such as drugs or the environment.


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Copyright, Acknowledgements, and Intended Use
Created by B. Beason (bbeason@rice.edu), Rice University, 11 July 2002
Updated 7 March 2007