Genomic Software Offers Faster Interpretations for Diagnosis

(James. J. Caras, National Science Foundation)

Software developed by scientists from University of Utah in Salt Lake City and Omicia Inc. in Emeryville, California, improves the speed and ability to identify and interpret genetic variations for the diagnosis of disease. The researchers that developed the software describe their findings in the current issue of the journal Genome Research.

The team led by Utah geneticist Mark Yandell and Omicia CEO Martin Reese developed the Variant Annotation, Analysis and Selection Tool (VAAST), an algorithm that finds disease-causing gene variations much faster than before. The software, according to its creators, meets the need to quickly interpret the information generated by genomic sequencing, which has become more readily available as the costs for sequencing have dropped.

Reese identifies a major challenge facing genomic medicine as “how to sift through the millions of variants in a personal genome sequence to identify the disease-relevant variations.” In their paper, he and Yandell show that VAAST offers a means to meet this goal. The authors demonstrate that as few as three genomes from unrelated children, or those of the parents and their two children, are sufficient to identify disease-causing mutations.

A separate paper in the online issue of American Journal of Human Genetics demonstrates this capability (paid subscription required). Gholson Lyon, previously a colleague of Yandell’s at Utah and now at the Children’s Hospital of Philadelphia, and colleagues report the use of VAAST as part of an effort to identify the mutation responsible for a newly discovered childhood disease, in this case with data from only two families.

The illness, known as Ogden Syndrome for the city of residence where the first case occurred, is characterized by aged appearance, craniofacial abnormalities, cardiac arrhythmias, and other symptoms. The team used VAAST with other genomic tools to quickly identify the disease-causing mutation in the N(alpha)-acetyltransferase 10 (NAA10) gene that resulted in this disease in children of two unrelated families.

The mutation of the NAA10 gene alters an enzyme that had not previously been shown to cause a human disorder. In this case, the disruption resulted in symptoms ultimately causing the death of the Ogden, Utah infant.

A second research group at the National Human Genome Research Institute notified Lyon that they too had identified the same NAA10 mutation in a second family with three boys who had similar symptoms to those found in the Ogden family. Further analysis showed the two families were unrelated, which indicates that the disorder is a syndrome and not an isolated condition found only in one family.

The development of VAAST was funded by the National Human Genome Research Institute through an American Recovery and Reinvestment Act Grand Opportunity grant. Omicia plans to integrate VAAST into its Genome Analysis System currently in development for clinical applications.

Read more:

• New Analytical Tools Reveal Cancer DNA Properties
• Open-Source Genome Analysis Software Developed

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