Research Project
7281553
[unreadable] DESCRIPTION (provided by applicant): We propose to develop a flexible means of genomic DNA sample preparation that will select and enrich one hundred thousand specific loci from the human genome that can readily be sequenced using random library sequencing pipelines. For the Cancer Genomes Atlas (CGAT) project, this technique will allow sequence analyses to be focused on known functional elements in the genome, maximizing both the cost effectiveness of analyzes and the depth of coverage of regions of the genome that are most likely to be involved in cancer initiation and progression. The core of this technique utilizes the flexibility and long-oligonucleotide synthesis capability of the NimbleGen high-density microarray platform to develop microarrays as programmable affinity columns directed against exons and regulatory elements in the human genome. This strategy will be compatible with whole genome amplification strategies, and will allow rapid, low- cost production of functional element libraries from <100 [unreadable]g of genomic DNA that can be sequenced using standard capillary sequencing pipelines, microarray-based sequencing, or recently developed parallel sequencing by synthesis technologies. It is anticipated that upon successfully completion of the goals described here: Synergies between the current sequencing platforms and this approach will allow sequencing of 25% of the known functional genome of an individual tumor for under $100,000 today. Sequencing costs will drop rapidly over the next few years significantly reducing the cost per functional genome. Selective enrichment coupled with sequencing will detect rare mutations found in heterogeneous samples. This project will be collaboration between Thomas Albert, Director of Molecular Research of NimbleGen Systems Inc., and Richard Gibbs and George Weinstock, Director and Co-Director of the Baylor College of Medicine Human Genome Sequencing Center (BCM-HGSC). Public Health Relevance Statement The work proposed in this application will lower the cost and improve the data quality of mutational discovery in the human genome. The proposal is particularly relevant to the Cancer Genomes Atlas Project, because identification of mutations that underlie the transformation of normal tissues into malignant tumors will be essential in formulating better prevention measures and treatments for cancer. This proposal, if successful, would revolutionize or ability to discover and track these mutations. [unreadable] [unreadable] [unreadable]
