15.6: Genomic Approaches- The DNA Microarray

Traditionally, if cellular protein levels changed in response to a chemical effector, molecular studies focused on the regulation of its gene. These studies often revealed that the regulation was at the level of transcription, turning a gene on or off through interactions of transcription factors with DNA. However, protein levels are also controlled posttranscriptionally, by the regulation of the rate of mRNA translation or degradation. Studies of transcriptional and posttranscriptional regulation mechanisms are seminal to our understanding of how the correct protein is made in the right amounts at the right time. We may have suspected, but now we know that control of gene expression and cellular responses can be more complex than increasing or decreasing the transcription of a single gene or translation of a single protein.

Newer technologies make possible the study of the expression of virtually all genes in a cell at the same time, a broadly defined field of investigation called genomics. As Plato might have said, necessity was ‘the mother of invention’ of the microarray, a technology that can reveal networks of regulated genes that must be understood to explain developmental and physiological changes in an organism. To hear how Patrick O. Brown conceived of microarrays as a tool to study whole genomes, and then how he made them, check out Using Microarrays to Study Cancer; What’s On a Microarray; Making a DNA Microarray; The Genome is the Script; and From the Microarray to Impossible Foods. Figure 15.30 is a simulated microarray simultaneously probing multiple transcripts.

Figure 15.30: This simulation of a glass-slide microarray shows multiple-color fluorescent spots (enlarged in the inset at the upper left), indicating a hunt for more than one DNA sequence at the same time.

Microarrays are typically made by “spotting” cloned DNA from a genomic or cDNA library, PCR products, or oligonucleotides on a glass slide, or chip. In microarray language, the slide is the probe. Spotting a chip is a robotic process. Since the DNA spots are microscopic, a cellspecific transcriptome (e.g., a cDNA library) can fit on a single chip. A small prokaryotic or viral genome microarray might also fit on a single chip. Larger genomes need several slides. In the simulated microarray above, the colored spots come from three different fluorescent tags on specific DNA sequences. If the spots are three specific cDNAs synthesized from cellular RNA, the microarray reveals that at least three different genes of interest were being actively transcribed in those cells at the time of RNA extraction.

In another use of microarrays, spotted genomic clones could be used to probe cDNAs made from total cellular mRNAs all of which attached to a single fluorescent tag. In this case, the question is not if as few specific genes were being specific genes are expressed, but rather which and how many genes are being expressed in the cell at the time of mRNA extraction. It is an approach to characterizing a cell’s transcriptome. This is a more global question. Identifying the proteins encoded by all those genes would be the next step. Microarrays can be quantitative, so that the brightness (intensity) of the signal from each probe can be measured. Quantitative microarrays can be designed to show how global gene expression changes in cells during normal differentiation or in response to chemical signals.

DNA microarrays are also valuable for genotyping, (i.e., characterizing the genes in an organism). They are so sensitive that they can distinguish between genes or DNA regions that differ by a single nucleotide. See Single Nucleotide Polymorphisms (SNPs) to learn more.

By analogy to genomics and transcriptomics, proteomics is the field of study of global protein interactions. Primary tools of proteomics include mass spectroscopy (which can distinguish slight differences in the mass of molecules), Western blotting (which can identify specific proteins immunologically after electrophoresis), and protein microarrays.

Because mass spectroscopy can detect the specific proteins and protein variants in samples, it was applied to an analysis of a Leonardo Da Vinci painting (Donna Nuda) to determine if it was actually painted by the renaissance master, an artist or artists of his school, or someone else entirely (look at Proteomics Determine Donna Nuda Provenance to learn the verdict!). As you might imagine, Western blotting has other research and medical applications. The protein microarray is the most recent power tool of proteomics.

Protein microarrays are in some ways similar to DNA microarrays, but they can look globally at protein-protein interactions, as well as the different states of proteins under different cellular conditions. Read even more about these exciting developments and their impact on basic and clinical research at Protein Microarrays from NCBI. Now think about this! Can we create a proteomic library analogous to a genomic library? This would seem a daunting prospect, but efforts are underway. Check out Trying to Map a Human Proteome for original research leading to the sampling of a tissue-specific human proteome, and see Strategies for Approaching the Proteome for more general information.

Microarrays and related technologies are powerful tools that can shift our focus from how single molecules influence events to how webs of biochemical interactions could more completely explain molecular and physiological causes and effects. Table 15.2 (adapted from Wikipedia) summarizes different applications of microarrays.

Table 15.2

* The Power of Microarrays

Application or Technology	Synopsis
Gene-expression profiling	In a transcription (mRNA or gene expression) profiling experiment, the expression levels of thousands of genes are simultaneously monitored to study the effects of certain treatments, diseases, and developmental stages of gene expression.
Comparative genomic hybridization	Genome content is assessed in different cells or in closely related organisms, in which one organism’s genome is the probe for a target genome from a different species.
GeneID	Small microarrays check the IDs of organisms in food and feed for genetically modified organisms (GMOs), mycoplasmas in cell culture, or pathogens for disease detection. These detection protocols often combine PCR and microarray technology.
ChIP (chromatin immunoprecipitation)	DNA sequences bound to a particular protein can be isolated by immunoprecipitating the protein. The fragments can be hybridized to a microarray (such as a tiling array) allowing the determination of protein binding-site occupancy throughout the genome.
DamID	Analogously to ChIP, genomic regions bound by a protein of interest can be isolated and used to probe a microarray to determine binding site occupancy. Unlike ChIP, DamID does not require antibodies but makes use of adenine methylation near the protein’s binding sites to selectively amplify those regions, introduced by expressing minute amounts of the protein of interest fused to bacterial DNA-adenine methyltransferase.
SNP detection	Microarrays allow the detection of single-nucleotide polymorphism among alleles within or between populations. Some microarray applications make use of SNP detection, including genotyping, forensic analysis, measuring predisposition to disease, identifying drug-candidates, evaluating germline mutations in individuals or somatic mutations in cancers, assessing loss of heterozygosity, or analyzing genetic linkage.
Alternative splicing detection	An exon-junction array uses probes specific to expected or potential splice sites of predicted exons for a gene. Its density (coverage) is intermediate to gene expression arrays (one to three probes per gene) and genomic tiling arrays (hundreds or thousands of probes per gene). It assays the expression of alternative splice forms of a gene. Exon arrays employ probes designed to detect each individual exon for known or predicted genes, and they can be used for detecting different splicing isoforms.
Tiling array	An exon-junction array uses probes specific to expected or potential splice sites of predicted exons for a gene. Its density (coverage) is intermediate to gene expression arrays (one to three probes per gene) and genomic tiling arrays (hundreds or thousands of probes per gene). It assays the expression of alternative splice forms of a gene. Exon arrays employ probes designed to detect each individual exon for known or predicted genes, and they can be used for detecting different splicing isoforms.

275-2 The Power of Microarrays