Some life-sciences tool vendors have pledged that digital gene-expression applications performed on their second-generation sequencing platforms will eventually dominate the gene-expression market at the expense of arrays.
However, a variety of experts familiar with both technologies say cost, data analysis, and throughput issues are continuing to encourage researchers to choose arrays over DGE.
Both Illumina and Applied Biosystems, now called Life Technologies after merging with Invitrogen last month, have launched gene-expression applications on their sequencing instruments over the past two years.
To date, Illumina has three DGE applications on its Genome Analyzer: mRNA-seq, to identify and quantify full-length poly-A transcript isoforms; tag profiling, to sequence short 3 prime-end transcript fragments to quantify known and novel transcripts from any eukaryotic species; and small RNA discovery and analysis. The company has stated publicly on several occasions that DGE will eventually replace traditional microarrays as the platform of choice for gene expression profiling (see BAN 2/12/2008).
ABI last year decided to shutter its expression array business, opting to push its customers to pursue gene expression studies on its SOLiD second-gen sequencing system (see BAN 10/30/2007). The company this year launched a gene-expression profiling application on the SOLiD.
But while Illumina and ABI look to bite off a chunk of the expression array market, which Illumina has estimated is currently worth around $700 million, some users familiar with both array-based and sequencing-based expression profiling say the two applications are different and predict that arrays will continue to be a valuable platform for researchers, at least for the next few years.
Gary Hardiman, director of the Biomedical Genomics Microarray Facility at the University of California in San Diego, told BioArray News this week that researchers may split in regards to what platform they use based on their different research projects.
“I think that researchers just interested in which genes are altered with regards to expression in response to a biological phenomenon will stick with arrays for the time being — this analog information, the lists of genes that are altered, and the pathway and ontology analyses you can do with these lists, will continue to provide valuable insights into biological questions,” Hardiman said.
Hardiman — whose facility offers both Illumina and Agilent expression arrays — said that he has performed DGE on the Genome Analyzer and was impressed with the results. He believes that those who are interested in looking at splice variants and alternative transcripts will be the “initial heavy users of DGE.” According to Hardiman, researchers studying organisms with limited or no sequence data are also likely to move projects over to DGE.
At the same time, Hardiman said that experiment design will not be the only indicator of which scientists use arrays and which ones use sequencers for expression profiling. He said that cost will continue to be a “major factor in the minds of many researchers.”
“I really don’t think there is going to be erosion in array demand due to the sequencers.”
In the long term, though, Hardiman said that added multiplexing capacity on sequencers, such as enabling many samples per flow cell, with each bar coded with distinct tag sequences, will drive costs down, spurring adoption of DGE. “It is only a matter of time until this technology replaces arrays entirely,” Hardiman said.
Shawn Levy, director of the Vanderbilt University Microarray Shared Resource in Nashville, Tenn., told BioArray News this week that DGE is currently “compatible and complementary” to arrays.
“As it stands today and for the next year, I wouldn’t consider it to be competitive to arrays for the majority of experimental designs,” he said. Levy agreed that DGE could become competitive with arrays over the next few years, but argued that array vendors are also likely to develop more-efficient and less-expensive products too.
“Looking forward, as sequencing output goes up and preparation methodologies get better, you could certainly envision that the sequencers would take a bite out of arrays,” said Levy. “But, that would happen only if the array manufacturers would not generate more content or smaller, more efficient arrays, while pushing price down.”
Vanderbilt currently offers expression on the Affymetrix, Agilent, and Roche NimbleGen platforms. Levy said that while there has been notable buzz around DGE, users of the VMSR still tend to pick arrays over DGE due to cost constraints, lack of data analysis tools for DGE, and throughput considerations.
“We have seen demand, but a different kind of demand for what we have seen with arrays,” said Levy. “It absolutely is a key technology, but I would say that, by and large, the experimental designs that benefit most from arrays are a little bit different than the experimental designs that you would use on the sequencers, at least in the short term.”
According to Levy, an experimental design that includes profiling anything more than a dozen samples is “vastly more efficient on arrays compared to sequencers,” while sequencers are more applicable in “applications where there are a smaller number of samples and a much more in-depth question.”
Levy predicted that users will probably seek to take the best from both platforms by, for instance, surveying a larger number of patient samples with arrays, identifying representative samples or outliers, and then applying DGE to that smaller number of samples.
“I really don’t think there is going to be erosion in array demand due to the sequencers. I think there will be a minor change in technology for key projects,” said Levy. “50 to 60 percent that have projects that they think they would like to run on the sequencers for RNA expression ultimately do not, simply because they did not have the money to do it or they did not realize the overhead of the data analysis in comparison to the arrays,” he said.
Neil Winegarden, head of operations at the University Health Network Microarray Centre in Toronto, said that “people have definitely bought into the idea” that DGE is “the future,” but cautioned that data analysis challenges were likely to encourage users to stick with arrays.
“People tend to like the [DGE] data, but the biggest issue is that the data analysis support just is not there,” Winegarden said. “Even if you talk to ABI and Illumina, they are going to tell you that right up front, that it is a big challenge. The technology is just developing so much faster than the data analysis is right now,” he said.
Winegarden also said that cost will motivate users to pick arrays over DGE, but he suggested that the two technologies “may very well be synergistic with one another, rather than competitive.”
While users weigh the merits of using arrays or sequencers in their studies, companies that sell microarrays for expression profiling are in different positions, while most appear to agree that data analysis challenges and the cost of sequencing applications will persuade some users to choose arrays for their projects in the near term.
Illumina, which provides both DGE and expression microarrays, has acknowledged that bioinformatics challenges coupled with better arrays will continue to buoy its array business going forward.
Joel McComb, senior vice president and general manager of life sciences at Illumina, last month told analysts at the firm’s analyst day event in San Diego thatthe “ability to do sample preparation and then the imaging of the analysis and the time required is going to continue the balance between how much work goes on in sequencing and how much work goes on in the array business.”
McComb argued that arrays “continue to be easier to prep, as far as the sample goes, and image analysis is faster and more convenient on the array technology.” According to McComb, Illumina sees the “two technologies working together,” and agrees that “bioinformatics will play a key role in how that business transitions from one area to the other area.”
While Illumina sees the two applications it sells as complementary, Affymetrix is in a different position in the market, having focused on acquiring lower-throughput technologies, rather than a second-generation sequencing platform that could support digital gene expression. Moreover, Affy is still the market leader in regards to array-based gene expression, which means it could take the most substantial hit to its business should DGE gain wider adoption at the expense of arrays.
Jeremy Preston, associate director of product marketing at Affy, this week told BioArray News that the company views “next-generation sequencing as a complementary technology” that “may generate content which we can put on microarrays.”
Preston said that researchers who currently use DGE are “early technology adopters” and it will be “some time before DGE makes its way into the mainstream market.” According to Preston, customers consider three issues when choosing between DGE and microarray-based research, namely cost, throughput, and data analysis.
“The cost of DGE is coming down rapidly,” he said, but “the cost of gene expression experiments using microarrays is also coming down dramatically.” Preston added that “data analysis is still and will continue to be a big bottleneck for those using next-generation sequencing,” and pointed out that “DGE currently generates far more information than researchers can easily manage, which may lengthen the time it takes to arrive at concise results.”
Of the larger array vendors, Agilent Technologies is in yet a different position. Agilent’s array business is built largely on sales of custom arrays; a market that a company official this week said is largely immune to the success, or failure, of DGE.
“Agilent’s ability to provide our customers with custom microarrays in multipack formats of up to eight arrays per slide means that we offer a very flexible and affordable product,” said Chris Grimley, Agilent’s senior marketing manager for genomics. “At this point in time next-generation sequencing cannot offer an equivalent product at a comparable price point.”
Grimley said that “DGE may be impacting array manufacturers who focus primarily on whole-genome, fixed content arrays,” but said that since a “significant amount of Agilent’s business is in custom arrays we are still seeing solid performance in this business.”
Grimley added that Agilent will continue to develop its gene expression portfolio, and said the company will debut new protocol for obtaining high quality results from formalin-fixed, paraffin-embedded samples early next year.