High-density microarrays for gene expression analysis

摘要

Changes in gene expression are associated with many important biological phenomena including morphogenesis and aging, cancer and disease states, and adaptive responses to the environment. To detect these changes, molecular biologists have, over the years, developed a variety of techniques including RNA blots (1), differential display (2), ribonuclease protection assays (3), and reverse transcription–polymerase chain reaction (RT-PCR) (4). Although these methods are effective, being sensitive and accurate, their dependence on gel electrophoresis places an empirical limit on the number of samples that can be simultaneously analyzed. High-density microarrays, first described by Schena et al. (5), provide the important advantage of allowing parallel quantification of the expression levels of an almost unlimited number of genes from a given genome. This greatly accelerates the characterization of individual genes and provides the means to decipher complex, multigenic patterns of gene expression (6). The importance of the high-throughput capability of microarrays is particularly relevant in the context of the recent explosion in genomic sequence acquisition. Each day, the human genome sequencing project alone deposits an estimated 2 million bases of DNA sequence into the GenBank database (7). For other eukaryotes, including Saccharomyces cerevisiae (8), Caenorhabditis elegans (9), and Drosophila melanogaster (10), the complete genomic sequence has already been reported. By the end of the year 2000, the list of organisms having fully sequenced genomes should comprise at least 36 different species (11), including the higher plant Arabidopsis thaliana. The rapid growth in accumulation of genomic sequences has been paralleled by the growth in collections of expressed sequence tags (ESTs), each of which contains the partial sequence of an expressed gene (12). For genomic or EST sequences to be truly informative, the genes that they identify must be assigned biological functions. Expression profiling using microarrays provides a powerful tool for correlating gene functions with DNA sequences. DNA microarrays also are useful for identifying differentially expressed genes in organisms for which the available DNA sequence data are limited. This advantage is not shared by other high-throughput methods of expression analysis such as serial analysis of gene expression (SAGE) (13). The use of microarrays for expression profiling is based on two fundamental principles. First, for many genes, a predominant factor underlying changes in expression is an alteration in the abundance of the cognate mRNA. It is clear that posttranscriptional factors also can affect gene expression, but these factors are not considered in this review because they are not generally amenable to microarray analysis. Second, only DNA strands possessing complementary sequences can hybridize to each other to form a stable, double-stranded molecule. Microarrays exploit this property through the immobilization of millions of single-strand copies of a gene as individual array elements on a solid support surface. The array surface is then incubated with a mixture of labeled DNA molecules; the surface contains a proportional representation of all of the genes that are being expressed in a given tissue sample. Out of this mixture, only the labeled molecules that represent the same gene as the immobilized DNA elements can form heteroduplexes. By measuring the amount of label that is bound to each array element at the end of the hybridization reaction, a researcher can determine the relative transcript abundance level of each gene. Because each microarray comprises many elements, RNA abundance levels for thousands of genes can be measured in a single experiment. By comparing abundance levels from several experiments, the investigator can correlate patterns of gene expression with particular tissues or experimental conditions. Despite being a relatively new field of research, some aspe