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Pinpoint Insertions/Deletions With A SNP Assay
Innovators
by Gina Shaw
Something about the results she was getting from her GoldenGate assay puzzled
Deborah Nickerson. There were inconsistencies: it appeared that the GoldenGate
assay, designed for studying SNPs, was detecting structural variance within the
genome.
Dr. Nickerson, a Professor of Genome Sciences at the University of Washington, knew that her colleague, Evan Eichler, an Associate Professor of Genome Sciences, was studying insertion/deletions. She brought the unusual results to Dr. Eichler, and the next step seemed logical to both scientists: Why not use the Golden Gate assay (Illumina, Inc., San Diego, CA) to probe for in/dels? "It was pretty straightforward: instead of looking for a SNP, we'd take an insertion allele that exists in one person and doesn't in another, and lay down Golden Gate probes specifically in that region," said Dr. Eichler.
The team targeted four regions of the genome for which it already had complete sequences. "In three out of four cases, using the Golden Gate assay, we could clearly distinguish hemizygotes from homozygous deletions from homozygous insertions," Eichler said. "PCR validated all of these; we had essentially 99% correspondence, which was fantastic. We found that you don't even have to lay it within a SNP; you just have to have the insertion sequence which is of course part of the challenge. You have to find those sequences, and some aren't even represented in current genome cataloging." (Eichler and Nickerson’s results appeared in Human Molecular Genetics on April 1, 15(7):1159-67.)
What about the fourth region? It seems to be more complex, according to Eichler. "We got lots of assays back, but couldn't make sense of it. It appears to be a region where there is also a lot of copy number variation as well as insertion/deletions." That's one shortcoming of this use of the assay: it appears to be very effective for binary areas, where there is a simple plus-or-minus insertion-or-deletion situation, but not so effective in cases of copy number variation.
"But based on our analysis, probably a good 50% of structural variation involves insertion/deletions, so there is a great deal we can learn from using the Golden Gate assay this way," he said.
Insertion/deletions are fairly common in the population at large, but few companies
have focused on this area in developing
assays. "Although there are a lot of claims, right now there really isn't a genotyping
platform out there that can go through thousands of individuals very quickly to
detect the presence or absence of a sequence."
That may change with Eichler and Nickerson's discovery of the Golden Gate assay's capabilities. "Some companies are beginning to explore this. We have a collaboration right now with Agilent, and Affymetrix also recognizes that they may have this hidden signal in some of their data," Eichler said.
The next step, according to Eichler, is to use the assay to target more regions. "We'll clearly be going after those that are binary, and also looking at other technologies that might be able to get us at some of the more complex, copy number variant regions."
Sidebar
Evan Eichler's primary research focus is developing an understanding of the evolution,
pathology and mechanisms of gene duplication and DNA transposition in the human
genome. He received his Ph.D. in 1995 from the Department of Molecular and Human
Genetics at Baylor College of Medicine. He is an editor of Genome Research,
a member of the organizing committee for the International Human Genome Organization
(HUGO), and has served on various scientific advisory boards for both NIH and
NSF. Dr. Eichler was named a Howard Hughes Medical Investigator in April 2005.
Human polymorphism expert Deborah Nickerson has spent more than a decade focused on identifying and typing common SNPs in an effort to understand the patterns of sequence variation in the human genome and to improve approaches for association mapping of common human diseases. She received her Ph.D. in Immunology from the University of Tennessee.
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