The SSV Evaluation System: A Tool to Prioritize Short Structural Variants for Studies of Possible Regulatory and Causal Variants.
Short structural variants (SSVs) are short genomic variants (<50 bp) other than SNPs. It has been suggested that SSVs contribute to many human complex traits. However, high-throughput analysis of SSVs presents numerous technical challenges. In order to facilitate the discovery and assessment of SSVs, we have developed a prototype bioinformatics tool, "SSV evaluation system," which is a searchable, annotated database of SSVs in the human genome, with associated customizable scoring software that is used to evaluate and prioritize SSVs that are most likely to have significant biological effects and impact on disease risk. This new bioinformatics tool is a component in a larger strategy that we have been using to discover potentially important SSVs within candidate genomic regions that have been identified in genome-wide association studies, with the goal to prioritize potential functional/causal SSVs and focus the follow-up experiments on a relatively small list of strong candidate SSVs. We describe our strategy and discuss how we have used the SSV evaluation system to discover candidate causal variants related to complex neurodegenerative diseases. We present the SSV evaluation system as a powerful tool to guide genetic investigations aiming to uncover SSVs that underlie human complex diseases including neurodegenerative diseases in aging.
Polymorphic DNA Technologies, Alameda, California, 94501.
Robert
R
Saul
Department of Neurology, Duke University Medical Center, Durham, North Carolina, 27710.
Michael W
MW
Lutz
Zinfandel Pharmaceuticals, Chapel Hill, North Carolina, 27710.
Daniel K
DK
Burns
Department of Neurology, Duke University Medical Center, Durham, North Carolina, 27710.|Zinfandel Pharmaceuticals, Chapel Hill, North Carolina, 27710.
Allen D
AD
Roses
Department of Neurology, Duke University Medical Center, Durham, North Carolina, 27710.|Center for Genomic and Computational Biology, Duke University Medical Center, Durham, North Carolina, 27710.
Ornit
O
Chiba-Falek
D019295:Computational Biology / Q000379:methods*; D020022:Genetic Predisposition to Disease; D014644:Genetic Variation; D055106:Genome-Wide Association Study; D023281:Genomics; D006801:Humans; D012984:Software
STR; bioinformatics tool; causal variants; human complex diseases; structural variants