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Following Market Debut of 1M SNP Arrays, Firms Ponder Ways to Sell More CNV Content

The recent launch of 1-million-SNP chips from Illumina and Affymetrix showcased the ability of the rival array firms to produce high-density genotyping tools, but also marked their continued decision to include copy number variation content on these chips in order to reach a market that is still trying to figure out just how to survey CNV data in future studies.
Indeed, both commercial and academic sources have said in recent weeks that now that the CNV content has been deployed on the Affy and Illumina chips, the debate over the way that vendors will make CNV information available to users in the future is intensifying. While vendors have yet to decide whether new products will take the form of a standalone “CNV chip” or if they will bundle the content into existing product lines for array comparative genome hybridization or SNP genotyping, most agree that CNV content will play an important role in next-generation microarray products.
One of the central themes in the debate is whether the current model of viewing CNV content alongside SNP data is the correct avenue for studying copy number variants. According to Illumina CEO Jay Flatley, the firm believes “there is a place in the market for a CNV-focused chip and that is the reason why we included this content on the Human 1M and Human 370CNV-Duo BeadChips.”
Flatley wrote BioArray News in an e-mail this week that “in addition to genotyping, SNP arrays provide allele information that can be used to identify copy neutral [loss of heterozygosity].” He added that Illumina employs the same design strategy for CNV regions without SNP coverage that it does for ones with coverage, and that it uses probes in order to “offer the same average redundancy on the array and optimize normalization conditions for copy number analysis.”
Currently, Illumina’s Human 1M and Human370CNV-Duo BeadChips include more than 14,000 known and novel CNV regions, Flatley added.
Another proponent of using the high-density SNP genotyping tools to study CNVs is Joris Veltman, head of the microarray facility at the Radboud University Nijmegen Medical Center in the Netherlands. Veltman has been using Affy 500K Mapping Arrays to diagnose mentally retarded patients and this month partnered with two other European labs to form a European Cytogenetics Research Initiative using Affy’s SNP arrays (see BAN 7/17/2007).
“I think the simultaneous analysis of CNVs and SNPs in one assay is very powerful and will have an added value both in our research as well as in diagnostics,” Veltman wrote in an e-mail to BioArray News last week. “It will help us to identify copy number neutral events but also will allow us to perform association-type studies once we have large enough datasets available.”
Steve McCarroll, a population and medical genetics team member at the Broad Institute, wrote that the CNV content offered on Affymetrix’s SNP arrays has also been favorably received by researchers at the Cambridge, Mass.-based institute.
“We have little idea how much CNVs affect common phenotypes; but the observations that CNVs are common, large, and affect functional sequences such as genes have made us excited to test their contribution to disease risk and other phenotypes,” McCarroll wrote in an e-mail to BioArray News this week.
The Broad is currently using the Affymetrix 5.0 and 6.0 arrays in disease association studies for several common diseases, including lupus, autism, and myocardial infarction, he wrote. “We are getting excellent performance for SNP genotyping call rates of about 99.5 percent, and our first opportunity to systematically test whether CNVs are associated with the risk of acquiring these diseases,” he added. 
A CNV Chip?
According to Steve Scherer, a senior scientist at the Hospital for Sick Children in Toronto, researchers are generally pleased to have access to the CNV content provided by the Affymetrix and Illumina SNP chips. Scherer is currently using custom NimbleGen arrays to help construct a map of copy number variants in the human genome as part of the Genome Structural Variation Consortium. According to Scherer, bioinformatics challenges and advancements in studying CNVs could catalyze the emergence of CNV chips in the marketplace.

“I think the SNP-plus-CNV products are very powerful, but if the primary goal is to do an association study alone for CNVs I am not sure if the ones out there will make the cut.”

“You will get good info out of the new products, but we are still early days,” Scherer told BioArray News last week. “I am looking foirward to see the data coming off these platforms. I think the SNP-plus-CNV products are very powerful, but if the primary goal is to do an association study alone for CNVs I am not sure if the ones out there will make the cut. You might need a special chip just to look for CNVs,” he said.
Scherer said that the real problem his lab is facing is a lack of computational tools to look at the data. “Partek has something out there now, but it is very rudimentary. We will have to wait and see how good and sensitive the coverage is,” he said. Radboud University’s Veltman also wrote that he believed R&D resources should be spent on developing better software to characterize CNVs.
Scherer said he is skeptical that the current generation of products can meet the long-term needs of researchers doing association studies with CNVs in mind. “If you want to do whole-genome association studies, based on the current products I don’t think it will work very well,” he said. “With that in mind there would be room for a CNV-specific array.”
By pairing with NimbleGen to construct a CNV-specific array, Scherer has also stumbled upon another core theme in the debate over the role that copy number variation will play in future products: one of content available for custom arrays or off-the-shelf products sold by any number of array vendors.
According to Jay Kaufman, marketing director for genomics at Agilent Technologies, the firm is weighing its options in how to channel innovative CNV-focused research collaborations into next-generation Agilent microarrays.
“The copy number variation landscape is still very much evolving, and there is not yet a consensus on which genomic regions are of the most relevant,” he wrote in an e-mail to BioArray News this week. “Agilent Labs is collaborating with several thought leaders in the area of [CNV] and these interactions are helping us define the next generation of products.”
According to Kaufman, while “some researchers might be best served by catalog CNV microarrays, most research in this area today lends itself towards custom arrays.” Agilent believes that its SurePrint platform is “equally well-suited for both approaches, and we’re continuing to refine and improve its capabilities.” To better serve the custom market, Kaufman added that Agilent will implement a major upgrade of its eArray web designing portal this fall.
Illumina’s Flatley wrote that the company is aware of the informatics needs of the CNV research community and has added to its BeadStudio software a comprehensive analysis function that types CNV regions using SNPs and probes. He declined to comment on whether Illumina has plans to sell a CNV-specific array in the future.

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