June 2013
Volume 54, Issue 15
ARVO Annual Meeting Abstract  |   June 2013
Utilizing Golden Helix SVS Software to Facilitate in the Identification of Genes for Ocular Diseases
Author Affiliations & Notes
  • Khanh-Nhat Tran-Viet
    Center for Human Genetics, Duke University, Durham, NC
  • Elizabeth St.Germain
    Center for Human Genetics, Duke University, Durham, NC
  • Greta Peterson
    Golden Helix, Bozeman, MT
  • Autumn Laughbaum
    Golden Helix, Bozeman, MT
  • Vincent Soler
    UMRS 563, Centre de Physiopathologie de Toulouse Purpan, Université Paul Sabatier, Toulouse, France
  • Tammy Yanovitch
    The Department of Ophthalmology, University of Oklahoma/Dean McGee Eye Institute, Oklahoma City, OK
  • Steve Rozen
    Duke-National University of Singapore Graduate Medical School, Singapore, Singapore
  • Terri Young
    Center for Human Genetics, Duke University, Durham, NC
    Duke-National University of Singapore Graduate Medical School, Singapore, Singapore
  • Footnotes
    Commercial Relationships Khanh-Nhat Tran-Viet, Golden Helix (R); Elizabeth St.Germain, None; Greta Peterson, Golden Helix, Inc. (E); Autumn Laughbaum, Golden Helix (E); Vincent Soler, None; Tammy Yanovitch, None; Steve Rozen, None; Terri Young, National Institutes of Health (F)
  • Footnotes
    Support None
Investigative Ophthalmology & Visual Science June 2013, Vol.54, 3381. doi:
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      Khanh-Nhat Tran-Viet, Elizabeth St.Germain, Greta Peterson, Autumn Laughbaum, Vincent Soler, Tammy Yanovitch, Steve Rozen, Terri Young; Utilizing Golden Helix SVS Software to Facilitate in the Identification of Genes for Ocular Diseases. Invest. Ophthalmol. Vis. Sci. 2013;54(15):3381.

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      © ARVO (1962-2015); The Authors (2016-present)

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Purpose: Technological advances in next generation sequencing provide clinicians and researchers with more effective methods to identify pathogenic gene mutations for heritable diseases. To date, the National Eye Institute Bank lists over 450 genes associated with eye-related disorders. There are a plethora of applications that can be used to determine causal gene variants ranging from targeted resequencing, exome sequencing, and whole genome sequencing strategies. Analytical processing of the large data sets generated can be cumbersome for all parties involved and some issues that can cause inefficiencies include learning programming languages and reliance on inconsistent freeware. Herein, we demonstrate the ability to utilize a commercially available software tool to help identify known and novel genes for various ocular diseases.

Methods: 84 DNA samples from patients with various ocular phenotypes underwent whole exome sequencing. Sequencing results were aligned, and cleaned. Variants were called using Burrows-Wheeler Aligner (BWA), SAMtools, and Genome Analysis Toolkit (GATK), respectively. Variant calling files generated were imported into the Golden Helix SNP & Variation Suite (SVS) v7.6.11 program for analysis. Multiple filtering strategies were employed based on mode of inheritance. Current public databases and internal exome controls were used in conjunction to assist in the filtering process. Variant(s) of interest were validated using Sanger Sequencing, bioinformatics, and functional studies.

Results: The following mutations were identified: a novel nonsense mutation in a Stickler/Wagner phenotype, compound heterozygous mutations in CYP1B1 in a family with heritable primary congenital glaucoma, a novel premature stop codon in a high-grade myopia family, and a de novo mutation for a rare corneal intraepithelial dyskeratosis.

Conclusions: Appropriate systematic filtering techniques using SVS efficiently identified an array of mutations. SVS provides the end-user with a simple, transparent method to identify mutations in ocular phenotypes. Clinicians and researchers now have tools with simple click-based filtering methods to analyze, identify, and perform complex analyses, eliminating the need to rely heavily on bioinformatics infrastructure. Filtering and validation of variants are currently underway for other ocular phenotypes.

Keywords: 539 genetics • 537 gene screening • 440 candidate gene analysis  

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