NOVEL METHODS FOR VAST INCREASE IN THROUGHPUT AND ACCURACY OF CIS-REG ANALYSES
NOVEL METHODS FOR VAST INCREASE IN THROUGHPUT AND ACCURACY OF CIS-REG ANALYSES
批准号:
7817303
负责人:
ERIC H DAVIDSON
金额:
$47.51万
依托单位国家:
美国
项目类别:
财政年份:
2009
资助国家:
美国
项目状态:
已结题
起止时间:
2009-09-22 至 2011-06-30
关键词:
AddressAreaBiological AssayCell SeparationComplexComputer softwareDNADataDevelopmentDiseaseEmbryoFutureGene TransferGenesGenomicsGrantHuman ResourcesIndiumIndividualInjection of therapeutic agentInstructionKnock-in MouseLifeMeasurementMeasuresMethodsMolecular ProfilingOrganismOutputPopulationPrevalenceProcessPublished CommentRegulator GenesResearchResolutionResourcesSea UrchinsSolidSolutionsSorting - Cell MovementStructureSubgroupSystemTechnologyTestingTimeTissuesTranscriptUnited States National Institutes of HealthValidationWorkbasedesignhigh throughput technologyinstrumentationinterestnetwork modelsnew technologynovelnovel strategiesprogramsresearch studytoolvector
中文摘要
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英文摘要
DESCRIPTION (provided by applicant): This Application addresses broad Challenge Area (08), Genomics, and Specific Challenge Topic 08-HG-101 "Technology and resources for high throughput functional analysis of functional elements in genomic sequences". A two year project is proposed to expand, to exploit, to extend, and to apply on a demonstration basis a completely novel approach to high throughput cis-regulatory analysis. We have very recently developed the initial component of this new technology as a tool for rapid validation of sea urchin embryo gene regulatory network models, and demonstrated its efficacy in facilitating the discovery and in measuring the quantitative activity of previously unknown cis-regulatory modules with a throughput of up to 100x that of traditional methods. The essential principle of this approach is use of sequence-tagged "barcoded" vectors which can be introduced together in large number in a single experiment and de-convolved later. But there remain many additional spinoffs and additional developments to be brought to practice, and the Challenge Grant program offers the opportunity to mount a "crash program" and bring these opportunities on line in the immediate future. In addition, the methods we have so far developed measure quantitative cis-regulatory output and not spatial activity. We propose additional technological developments to generate higher quality spatial expression data than obtainable by any other means and a high throughput method of recovering large sets of cis-regulatory modules operating in any given spatial regulatory state. The specific aims of this proposal include adapting the sequence tag method to NanoString technology to permit simultaneous assessment of activity of > 100 different cis-regulatory modules; demonstrate the use of this method to obtain temporal output profiles of large numbers of cis-regulatory modules simultaneously; develop a very high accuracy method of determining spatial expression profiles of unknown cis-regulatory modules by use of NanoString measurements; and tune for general use a high throughput technology for isolating all cis-regulatory modules of a large unknown set which operate in a given time-space domain of the organism. Two additional comments are important: first, there is no a priori reason why these technologies should not be transferrable to any other system in which gene transfer by direct DNA injection is utilized; and second, in order to accomplish these objectives we shall have to build a new research subgroup. This will require hiring additional personnel, and in this respect both the scientific and organizational aspects of the proposal synergize with the objectives of the A.R.R.A. NIH initiative. This work is about finding the causal lines of control that determine how fundamental life processes are executed according to the instructions encoded in the genomic regulatory system. The most powerful approach to general solutions to complex disease states requires solid understanding of their control circuitry. Our practice must get beyond struggling to ameliorate effects rather than altering causes. This research shows the way to discovery of structure and function in causal genomic control systems.
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会议论文
Depth and Breadth of Explanatory Power in Developmental GRNs
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批准号:8752112
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项目类别:
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GLOBAL GENE REGULATORY NETWORKS FOR SPECIFIC CELL TYPES OF THE SEA URCHIN EMBRYO
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财政年份:2010
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依托单位:
Global Genomic Regulatory Code for the gastrula stage sea urchin embryo
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批准号:8092699
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资助金额:$68.02万
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Specialized Research Support Core (SRC CORE)
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批准号:8092702
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资助金额:$30.0万
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财政年份:2010
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依托单位:
GLOBAL GENE REGULATORY NETWORKS FOR SPECIFIC CELL TYPES OF THE SEA URCHIN EMBRYO
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批准号:8463580
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项目类别:
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资助金额:$56.17万
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资助金额:$17.13万
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财政年份:2010
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依托单位:
GLOBAL GENE REGULATORY NETWORKS FOR SPECIFIC CELL TYPES OF THE SEA URCHIN EMBRYO
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项目类别:
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资助金额:$66.63万
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财政年份:2010
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依托单位:
Egg to Embryo: Gene Regulatory Circuitry in Development
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项目类别:
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财政年份:2010
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负责人:ERIC H DAVIDSON
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依托单位:
Egg to Embryo: Gene Regulatory Circuitry in Development
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批准号:7881821
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项目类别:
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资助金额:$0.8万
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财政年份:2009
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负责人:ERIC H DAVIDSON
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依托单位:
Global Genomic Regulatory Code for the gastrula stage sea urchin embryo
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批准号:8055256
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项目类别:
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资助金额:$3.56万
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财政年份:2009
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负责人:ERIC H DAVIDSON
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依托单位:
NOVEL METHODS FOR VAST INCREASE IN THROUGHPUT AND ACCURACY OF CIS-REG ANALYSES
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批准号:7935508
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项目类别:
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资助金额:$46.91万
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负责人:ERIC H DAVIDSON
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依托单位:
Specialized Research Support Core (SRC CORE)
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批准号:7751736
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项目类别:
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资助金额:$28.04万
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财政年份:2009
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依托单位:
Scientific and Administrative Coordination Core (SAC CORE)
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批准号:7751737
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项目类别:
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资助金额:$16.0万
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财政年份:2009
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负责人:ERIC H DAVIDSON
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依托单位:
Computational Model of Gene Regulatory Program
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批准号:7904729
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项目类别:
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资助金额:$42.66万
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财政年份:2009
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负责人:ERIC H DAVIDSON
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依托单位:
Gene Library Resource for the Sea Urchin S. purpuratus
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批准号:7885892
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项目类别:
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资助金额:$92.76万
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财政年份:2009
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依托单位:
Egg to Embryo: Gene Regulatory Circuitry in Development
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批准号:7931083
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项目类别:
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资助金额:$21.98万
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财政年份:2009
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依托单位:
Global Genomic Regulatory Code for the gastrula stage sea urchin embryo
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批准号:7751701
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项目类别:
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资助金额:$59.03万
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财政年份:2009
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负责人:ERIC H DAVIDSON
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依托单位:
Regulatory Genomics: BAC-GFP Library of Control Genes
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批准号:7091837
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财政年份:2006
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Regulatory Genomics: BAC-GFP Library of Control Genes
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资助金额:$25.49万
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