“VAAST is an integrative tool that uses a number of inputs to rank the [DNA] variants based on clinical gene importance in an automatic way,” says Reese. The mutation tracking software is designed to screen individual human genome sequences for clinically significant mutations.
In the Genome Research paper, Yandell, Reese and colleagues show that VAAST can accurately and swiftly analyze the variations in a handful of personal genome sequences to identify the causative mutation. In fact, this can be done in as few as three genomes from unrelated children, or the parents and two children. Other approaches to filtering genomic data for causative mutations are also paying dividends (see “Endeavor Aids Disease Gene Hunt.”)
The program works like the classic sequence homology program BLAST—hence the name. “In BLAST, you take a sequence and run it against a background database, asking: How similar is my sequence to the other databases? VAAST does the same thing for personal genomes, but does it for dissimilarities,” says Reese.
“SIFT and Polyphen, and other academic [mutation prediction] platforms—they’re all a collection you have to run,” says Reese. “But VAAST does it integrated in one program. It looks at a mutation and its [putative] physiological function. Then it also looks at the frequency of that mutation in a background distribution. You can use the frequency from the 1000 Genomes project or other sources, or you can put in your own background distributions.”
By incorporating variant frequency data in the algorithm, VAAST is able to rapidly zero in on the likely causative mutation, which would be expected to be present very rarely in the population. The program compares variations from a patient against dozens or hundreds of healthy genomes, and automatically scores those mutations in the form of a gene-by-gene ranking summary.
In the Genome Research paper, Yandell and colleagues describe a proof-of-principle studying patients with Miller syndrome, a rare genetic disorder whose genetic basis was uncovered last year. The group looked at six Miller patients, each of whom is a compound heterozygote (harboring two different mutations in the same gene, one inherited from each parent).
When VAAST was run on a single patient, the known Miller syndrome gene ranked #86 out of 20,000 genes in the human genome. Adding a second patient, the gene rose to #2 in the list, and jumped to the top with just three or more patients. (Like BLAST, VAAST provides a P value of statistical significance in the results.)
Reese adds that running the VAAST program retrospectively on the family that was sequenced last year to discover the Miller syndrome gene, the analysis took about a day, compared to several months.
“VAAST solves many of the practical and theoretical problems that currently plague mutation hunts using personal genome sequences,” said Yandell. “This tool substantially improves upon existing methods with regard to statistical power, flexibility, and scope of use. Further, VAAST is automated, fast, works across all variant population frequencies and is sequencing platform independent.”
X Marks Spot
Writing in the American Journal of Human Genetics, Gholson Lyon at the Children’s Hospital of Philadelphia, Yandell and colleagues show how VAAST can be applied to tease out the mutation responsible for a devastating childhood syndrome of unknown etiology.
Lyon, who was formerly at the University of Utah, had been working with a family in the area in which four affected boys had severe neurological damage and signs of progeria (premature aging), and died by the age of 4. Recognizing that the disorder was X-linked, Lyon restricted the next-generation sequencing to the coding regions of the X chromosome. But even then, using traditional tools, he was only able to narrow down the list of candidates to five genes.
Lyon gave Yandell the data, which he ran through VAAST. Within an hour, he was certain he had found the gene, NAA10, which had been one of Lyon’s original candidates. A few weeks after the manuscript was originally submitted, one of the reviewers contacted the authors, as he had seen a family with similar characteristics. Affected members in that family proved to have the same gene mutation. The disorder has been preliminarily called Ogden syndrome.
“One of most important and exciting opportunities in genomic medicine is the newfound ability to pinpoint the root cause of an unknown idiopathic disease in an individual,” commented Eric Topol, director of the Scripps Translational Science Institute. The VAAST tool will markedly facilitate this and represents a major advance in the field.”
The VAAST IP is shared by the University of Utah and Omicia says Reese. Omicia plans to commercially release its Genome Analysis System in late 2011, and integration with VAAST in 2012. Meanwhile Yandell is offering academic collaborations under academic-only licenses via his website.
Reese says his team is starting to apply VAAST to cancer and other areas. “VAAST works really well right now on rare genetic diseases, but we need more feeling on it. There’s a whole bunch of applications where VAAST can work—we just need to run it through and improve it in the next 6-12 months.” •