Mapping Disease: Microarrays Super-Power Genetic Content Analysis

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Article ImageNew DNA microarrays that can profile more than 500,000 exact genetic variations are giving researchers a better view of the genetic causes of many illnesses and helping them work towards more personalized treatments. While experts are nothing but pleased by the new crop of gene chips, which cover nearly every gene in the genome, they say that five to ten years from now researchers may shift away from current profiling methods toward new sequencing technologies that are currently in their infancy.

Microarray developers are releasing new products at a seemingly breakneck pace. Last year both Santa Clara, Calif.-based Affymetrix and San Diego-based Illumina released 500,000-plus arrays, significantly bettering previous efforts that detected 100,000 variations. Already both companies have announced first quarter 2007 releases for 1,000,000-plus chips.

A microarray, commonly known as a DNA chip or gene chip, is a collection of DNA spots attached to a plastic, glass, or silicon chip used to sift through and examine the data in a genome.

For medical researchers, microarrays make it easier to measure the expression of specific genes within diseased cells. If a researcher wants to know whether gene A is expressed in a particular tissue, the researcher would make a new spot on a microarray using a small piece of the gene in question. When the tissue is filtered through the array, any instance of gene A will bond ("hybridize") with the spot, creating a radioactive signal that tells researchers gene A is expressed in the tissue sample. First used for profiling in 1995, a single microarray experiment can perform tens of thousands of genetic tests in parallel, depending on the number of spots on the array.

Illumina spokeswoman Maurissa Bornstein attributes the rash of new development to the late-2005 release of data from Phase I of the HapMap project, an international collaboration aimed at describing the common patterns of human genetic variation that comprised academic, nonprofit, and private research groups. She says, "The technology has evolved since the HapMap project initiated and a lot of data has been released."

Based in part on this HapMap data, Illumina's humanHap550 microarray takes a "full circle look at all the data that comprises a genome," Bornstein says, providing a "comprehensive" look at gene expression in a human cell.

This new spate of development has genetic data analysis companies like Illumina and Affymetrix brushing elbows along very similar paths.

Illumina has recently announced research partnerships with the Mayo Clinic and the Children's Hospital of Eastern Ontario where it will use its arrays to develop molecular diagnostic tests for complex diseases like spinal muscular atrophy.

Likewise, Affymetrix recently announced a licensing partnership with Baylor College of Medicine and has teamed up with the Muscular Dystrophy Association to use it's GeneChip Human Mapping 500K Array Set to research Lou Gehrig's Disease.

Perhaps the best indicators of the competitive direction of these developments are the six pending lawsuits filed by Affymetrix against Illumina for infringing on patents awarded between 1996 and 2003. When reached, Affymetrix declined to comment for this article.

Gavin Sherlock is one of many researchers benefiting from the new microarray releases. As a co-principal investigator at Stanford's Microarray Database, he employs commercial microarrays from Affymetrix and Illumina alongside his lab's own Stanford-produced arrays to investigate diseases like breast cancer, African swine fever, and multiple sclerosis.

"Now you can sequence an entire organism in a week whereas it once took six months to do that," he says of the progress of current profiling methods. Despite this progress, Sherlock says the number of detectable genetic variations by a single array is approaching saturation point—individual chips can't do much better. Rather than cram even more spots onto future arrays, he says the next step for the genetic data management industry should be to instead lower costs (his lab currently pays $1,000 for individual non-reusable Affymetrix arrays) and to ramp up array throughput so researchers can run more arrays at once during experiments.

But even these improvements would be only evolutionary steps, he says. The next big development in genetic data analysis he expects to see during the next decade is the maturation of new "novel sequencing technologies," several techniques still in their infancy which could eventually "sequence data at two to three orders of magnitude higher resolution than [microarrays] can now." He says his lab is keeping an eye on new methods like Branford, Conn.-based 454 Life Science's sequencing-by-synthesis approach, a faster but currently more complicated technique.

For now though, companies like Illumina and Affymetrix will continue rapid-fire development of "bigger and better" microarrays, believing, as Bornstein says, that "there's an ongoing need for content to be developed so the research community can meet its research needs. And the more content you have, the more data you're going to get out of your research."