Coupling older and newer technologies, a group of researchers at the Itawe Biotechnology Research Center in Japan recently published a paper detailing the fusion of serial analysis of gene expression with microarrays.
Published in the May 23 issue of Nature Methods, the invention, called SuperSAGE array, marries DNA microarrays with the older, more time-intensive analysis method.
According to the paper, the SuperSAGE array uses 26-base pair oligonucleotides corresponding to SAGE tag sequences to perform genome-wide gene expression analysis in "any eukaryotic organism." Rather than using the SAGE method of counting copy number changes, SuperSAGE can detect genomic variations by comparing gene-expression patterns.
Lead author Hideo Matsumura told BioArray News in an e-mail last week that he believes SuperSAGE is the first array of its kind to combine SAGE tags with microarray technology.
"There were several reports [previously published] on the comparison of SAGE and microarray data. But, these are the first results, which demonstrated the combination of SAGE and microarray [technology]," Matsumura said.
Moreover, Matsumura said that the new arrays offer a cost-effective medium for researchers investigating infectious diseases or specific genomic regions in non-model organisms. The paper describes SuperSAGE arrays for rice and Nicotiana benthamiana, a tobacco species.
"Our [method] facilitates oligo-array construction in any eukaryotic organism," Matsumura said. "Generally, whole genome sequences or large numbers of cDNA sequences are required for microarray construction, but large-scale sequencing takes huge time and costs," he added.
Matsumura said that researchers using SuperSAGE can obtain a "list of non-redundant expressed genes as 26bp tags … within 3-4 weeks in every eukaryotic organism."
"We expect that any labs or scientists can start large-scale expression analysis in any non-model organisms using a SuperSAGE Array," he said.
Matsumura's team used NimbleGen Systems' custom array service to design the 26-bp probe arrays. He said that researchers had difficulties creating SAGE arrays in the past due to the difficulty associated in designing 26-base pair probes. So Matsumura's team relied on NimbleGen's photolithography method to produce the arrays, and used NimbleGen's 12-well array system for the experiments.
According to Matsumura, all array production and hybridization experiments were carried out by NimbleGen and its Japanese distributor Genefrontier.
Dan Clutter, the NimbleGen's VP of business development, called the SAGE array development "a normal NimbleGen custom array project."
"The customer wanted to do something, the distributor [Gene Frontier] worked with them on the design and ran the experiment through our regular service pipeline," he said.
Still, others in the space that have experimented with SAGE and microarrays, like Kornelia Polyak, an assistant professor of medicine at Harvard Medical School affiliated with the Dana-Farber Cancer Institute, believe that some of the advantages of SAGE may be lost in an array experiment.
"The main difference between SAGE and arrays is that SAGE is a counting-based method, so you basically count the copy number of the gene in the cell, whereas with the arrays you develop your relative ratio based on a hybridization signal," Polyak told BioArray News last week. "Because they made these arrays based on SAGE tags they kind of lose that advantage," she said.
Polyak also noted that emerging technologies, such as sequencing tools being sold or developed by companies like Helicos, 454 Life Sciences, and Solexa, may ultimately be more quantitative than SAGE arrays.
"To be honest, there are better technologies in development that would be high-throughput and still quantitative, like single molecular sequencing," Polyak said.
Matsumura said that he does not think that pairing SAGE with array technology would reduce the reliability of the data generated. He also said that targeted SuperSAGE arrays would benefit from using newer sequencing technologies.
"By employing these novel and huge DNA sequencing technologies, time and costs for SuperSAGE will be reduced," he said. "Also, whole genome sequence information will be available in every organism, so the genome sequence data will be quite useful for SuperSAGE analysis."
Justin Petrone ([email protected])