Sequencing genes in silico using single nucleotide polymorphisms
1 Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, WA, 98109, USA
2 Division of Clinical Research, Fred Hutchinson Cancer Research Center, Seattle, WA, 98109, USA
3 School of Medicine, University of Washington, Seattle, WA, 98195, USA
BMC Genetics 2012, 13:6 doi:10.1186/1471-2156-13-6Published: 30 January 2012
The advent of high throughput sequencing technology has enabled the 1000 Genomes Project Pilot 3 to generate complete sequence data for more than 906 genes and 8,140 exons representing 697 subjects. The 1000 Genomes database provides a critical opportunity for further interpreting disease associations with single nucleotide polymorphisms (SNPs) discovered from genetic association studies. Currently, direct sequencing of candidate genes or regions on a large number of subjects remains both cost- and time-prohibitive.
To accelerate the translation from discovery to functional studies, we propose an
Prior to the general availability of routine sequencing of all subjects, the ISS method proposed here provides a time- and cost-effective approach to broadening the characterization of disease associated SNPs and regions, and facilitating the prioritization of candidate genes for more detailed functional and mechanistic studies.