Genomics stands at a remarkable moment of scientific opportunity and technological ferment. DNA sequence information is becoming an increasingly powerful for investigating biological question, and new technologies promise to decrease dramatically the cost of DNA sequencing and thereby further expand its reach. At the same time, the scientific and technological path forward has many uncertainties and obstacles. For these reasons, NHGRI seeks to support genome centers with the ability to provide both scientific and technological leadership through this exciting period of transition. This proposal has three specific aims:
Aim 1. Current technology. We propose to operate a state-of-the-art genome center using current sequencing technology, continuing our 15-year track record of high throughput, low cost and flexibility. Our annual throughput will exceed 61 billion bases, with costs decreasing to $0.29/kQ20 base by the end of Year 4. The capacity will have the potential to be allocated flexibly across shotgun sequencing, targeted sequencing and finishing/improvement.
Aim 2. New technology. In parallel, we aim to completely replace the current generation with new, disruptive technologies, with the goal of dramatically decreasing cost and increasing output. During the first year, we will operate two new sequencing platforms (454 and Solexa) at sufficient scale to understand their true performance, cost and utility and to produce valuable data. Based on the results, we aim to scale-up one or both platforms as soon as possible. This work requires more than simply implementing new instruments at production scale, although this is a substantial challenge. The greater challenge is that the two platforms are not currently suited to NHGRI's key genomic applications ? namely, genome assembly and directed re-sequencing. We will develop the full set of laboratory and computational tools required to adapt the technologies to these key applications. Our goal will be to achieve a cost reduction of >30-fold in these key applications by the end of the grant period.
Aim 3. Scientific leadership. We will continue to serve as an intellectual resource for the scientific community, by pioneering new approaches for using DNA sequence to solve important biomedical problems and by working with the community to rapidly disseminate ideas, methods and data.

Agency
National Institute of Health (NIH)
Institute
National Human Genome Research Institute (NHGRI)
Type
Specialized Center--Cooperative Agreements (U54)
Project #
5U54HG003067-08
Application #
7751342
Study Section
Special Emphasis Panel (ZHG1-HGR-P (A1))
Program Officer
Felsenfeld, Adam
Project Start
2003-11-10
Project End
2011-10-31
Budget Start
2009-11-01
Budget End
2010-10-31
Support Year
8
Fiscal Year
2010
Total Cost
$46,572,133
Indirect Cost
Name
Broad Institute, Inc.
Department
Type
DUNS #
623544785
City
Cambridge
State
MA
Country
United States
Zip Code
02142
Hmeljak, Julija; Sanchez-Vega, Francisco; Hoadley, Katherine A et al. (2018) Integrative Molecular Characterization of Malignant Pleural Mesothelioma. Cancer Discov 8:1548-1565
Ding, Li; Bailey, Matthew H; Porta-Pardo, Eduard et al. (2018) Perspective on Oncogenic Processes at the End of the Beginning of Cancer Genomics. Cell 173:305-320.e10
Breuss, Martin W; Nguyen, An; Song, Qiong et al. (2018) Mutations in LNPK, Encoding the Endoplasmic Reticulum Junction Stabilizer Lunapark, Cause a Recessive Neurodevelopmental Syndrome. Am J Hum Genet 103:296-304
Seiler, Michael; Peng, Shouyong; Agrawal, Anant A et al. (2018) Somatic Mutational Landscape of Splicing Factor Genes and Their Functional Consequences across 33 Cancer Types. Cell Rep 23:282-296.e4
Sanchez-Vega, Francisco; Mina, Marco; Armenia, Joshua et al. (2018) Oncogenic Signaling Pathways in The Cancer Genome Atlas. Cell 173:321-337.e10
Liu, Yang; Sethi, Nilay S; Hinoue, Toshinori et al. (2018) Comparative Molecular Analysis of Gastrointestinal Adenocarcinomas. Cancer Cell 33:721-735.e8
Way, Gregory P; Sanchez-Vega, Francisco; La, Konnor et al. (2018) Machine Learning Detects Pan-cancer Ras Pathway Activation in The Cancer Genome Atlas. Cell Rep 23:172-180.e3
Wang, S-H; Hsiao, P-C; Yeh, L-L et al. (2018) Polygenic risk for schizophrenia and neurocognitive performance in patients with schizophrenia. Genes Brain Behav 17:49-55
Ricketts, Christopher J; De Cubas, Aguirre A; Fan, Huihui et al. (2018) The Cancer Genome Atlas Comprehensive Molecular Characterization of Renal Cell Carcinoma. Cell Rep 23:313-326.e5
Arbesman, Joshua; Ravichandran, Sairekha; Funchain, Pauline et al. (2018) Melanoma cases demonstrate increased carrier frequency of phenylketonuria/hyperphenylalanemia mutations. Pigment Cell Melanoma Res 31:529-533

Showing the most recent 10 out of 349 publications