Jonathan Sebat Explains the ROMA Microarray Technique
July 28, 2004
At A Glance
Jonathan Sebat, Postdoctoral Fellow, Cold Spring Harbor Laboratory
Education: 2002 - PhD, microbiology, molecular biology and biochemistry, University of Idaho
1995 - BA, biology, University of California, Santa Barbara
This past week, the journal Science published a paper detailing the use of a relatively new microarray technique developed in the laboratory of noted Cold Spring Harbor Laboratory researcher Michael Wigler. The technique, called representational oligonucleotide microarray analysis (ROMA), detects chromosomal deletions and amplifications. The method combines DNA microarray analysis and representational difference analysis, a gene discovery technique also developed by Wigler. The study published in Science was authored by Jonathan Sebat, who has been with CSHL since 2002. In his work there, he is using the ROMA technique to study the genetic causes of several diseases, including Parkinson’s, autism, congenital heart disease, and mental retardation. Sebat explained the ROMA technique and its potential uses in an interview this week with BioArray News.
How did you get started in this field?
I did my PhD at the University of Idaho and my background was in genomic analysis of bacteria. So, I was using microarrays and actually environmental DNA samples consisting mostly of bacterial DNA and using them to monitor the presence or absence of specific strains of bacteria and specific bacterial genes. I saw that the most promising applications for the technology now was for analysis of the human genome. So, I looked at who was making the greatest progress in the field and was fortunate enough to learn about Mike Wigler, who at the time had not published his new method. I came and interviewed, saw the technology and the potential and was fortunate enough for Mike to have me come and do this work.
Tells us about the ROMA technology. What’s different about it?
Let’s start with what’s the same. Essentially it is a microarray technique, and like virtually all microarray experiments you measure gene copy number by hybridizing sample A versus sample B. Here’s what’s different about ROMA: Our technique has essentially increased the sensitivity substantially, by two means. The first, and possibly the most important, is how the sample is prepared. The preparation of a sample for ROMA uses another technology developed in the Wigler lab called representational difference analysis. You make a representation of the genome to reduce the complexity. So, instead of hybridizing total genomic DNA to an array of probes, you’re hybridizing a three percent representation of the total genome. The representation is made by cleaning the genome with a restriction enzyme…and then you amplify the genome by PCR. For example, you prepare a sample from a tumor, you prepare a sample from a normal genome, and amplify them in parallel. We’ve learned that PCR is surprisingly reliable and you get consistent amplification of the individual fragments. Because you’ve eliminated a tremendous amount of the background by eliminating the complexity of the sample, you get very high signal to background.
The second aspect is we’ve been using custom oligonucleotide arrays, which are provided by NimbleGen. The NimbleGen arrays enable us to make hundreds of thousands of different probes and do a series of preliminary experiments to optimize our probe set to only have those probes that give us the best signal. Through many rounds of optimization you get a sample preparation that gives you good signal and you get a chip that is optimized for a particular type of representation. There’s a lot of fairly clever informatics that goes into that and the downstream data analysis as well.
What other equipment are you using in employing this technique?
Besides the NimbleGen chips, we use an Axon scanner and the data is imported into S-Plus, which is a statistical programming language.
What can you tell us about the paper that was published this past week in Science?
The paper is the result of an investigation of normal genetic variation, or normal copy number variation in the human genome. We were actually looking at normal DNA from unrelated individuals and observing a surprising amount of variation in gene dosage between normal, unrelated individuals.
What are the potential applications of the ROMA technology?
Besides research uses, probably the biggest commercial application is for diagnostics in cancer and pediatric genetics.
Who holds the rights to the ROMA technology?
The patent is pending, and the two main inventors are Robert Lucito and Michael Wigler at Cold Spring Harbor Laboratory.
At some point, though, this will be licensed out to a commercial entity?
Absolutely. It’s really a matter of getting it packaged up and finding a commercial partner that can help get a diagnostic company off the ground.