Molecular Cloning Fourth Edition, A Laboratory Manual, by Michael R. Green and Joseph Sambrook

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Chapter 10: Nucleic Acid Platform Technologies

Rando Oliver, Department of Biochemistry and Molecular Pharmacology, University of Massachusetts Medical School, Worcester, Massachusetts 01605



EVERYMICROARRAY EXPERIMENT IS BASED ON A COMMON format (Fig. 1). First, a large number of nucleotide spots are arrayed onto a substrate, typically a glass slide, a silicon chip, or microbeads. Second, a complex population of nucleic acids (isolated from cells, selected from in vitrosynthesized libraries, or obtained from another source) is labeled, typically with fluorescent dyes. Third, the labeled nucleic acids are allowed to hybridize to their complementary spot(s) on the microarray. Fourth, the hybridized microarray is washed, allowing the amount of hybridized label to then be quantified. Analysis of the raw data generates a readout of the levels of each species of RNA in the original complex population.

Microarrays can be run in one-color or two-color formats. In a one-color microarray, a single sample (e.g., RNA from liver cells) is labeled, and the abundance of a species of RNA is inferred from the intensity of the spot(s) complementary to the relevant gene. Because, for each spot, hybridization is affected by a panoply of factors, interpretation of single-color experiments can be complicated. Practically, however, many of these complicating factors are resolvable by using the proper bioinformatics tools during data analysis. Two-color microarrays (Fig. 1) use a competitive hybridization in which one nucleic acid sample is labeled with one color (green), and a related sample is labeled with a second color (red). Following hybridization and removal of unbound nucleic acid, the microarray is scanned with lasers to detect where the red- and green-labeled molecules have bound. The intensity of each spot is determined, and the red/green ratio is measured for each spot. During data analysis, this ratio can be used to measure the ratio of the amount of related nucleic acid molecules in the two samples. For example, if RNA from normal liver is tagged green and RNA from a liver tumor is labeled red, then red spots would represent RNAs that are up-regulated in the tumor, and green spots would represent down-regulated RNAs.

Tiling microarrays consist of regularly spaced oligonucleotides that provide dense coverage of a genome or portion of a genome. For example, yeast chromosome III was tiled using oligonucleotides 50 nucleotides long spaced every 20 bases; that is, spot 1 comprised bases 150, spot 2 bases 2170, and so forth. Tiling microarrays therefore interrogate continuously along a chromosomal path, enabling applications, such as transcript structure and protein localization, to be performed with almost complete genomic coverage. One disadvantage to tiling microarrays is that not all genomic sequence is equally suited to microarray applications. For example, not all 50-mers in a genome are unique, leading to gaps in the tiling path where hybridization-based approaches cannot determine whether the hybridizing material comes from copy 1 or copy 2 (or copy N) in the genome. Furthermore, hybridization-related properties such as the percentage of A and T residues and oligonucleotide melting temperature vary from probe to probe, although many issues like these can be resolved by normalizing two-color arrays. Normalization, which compensates for systematic technical differences between spots and/or arrays, clarifies the systematic biological differences between samples.

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