Development of an Efficient High Throughput Technique for the Identification of High-Impact Non-Coding Somatic Variants Across Multiple Tissue Types
开发一种高效的高通量技术,用于鉴定跨多种组织类型的高影响力非编码体细胞变异
基本信息
- 批准号:10662860
- 负责人:
- 金额:$ 44.83万
- 依托单位:
- 依托单位国家:美国
- 项目类别:
- 财政年份:2023
- 资助国家:美国
- 起止时间:2023-04-01 至 2025-03-31
- 项目状态:未结题
- 来源:
- 关键词:ATAC-seqAddressAlgorithmsAllelesBenchmarkingBindingBiologyBrainCancer EtiologyCatalogsCell divisionChromatinChromatin StructureComputer softwareConceptionsCost AnalysisDNADNA RepairDNA purificationDNA sequencingDataData SetDetectionDevelopmentDiseaseGenetic Enhancer ElementGenomeGenomic SegmentGenomicsGoalsHumanHuman BiologyIndividualMalignant NeoplasmsMethodsModificationMosaicismMutagensMutateMutationMutation DetectionNormal tissue morphologyNucleic Acid Regulatory SequencesPhasePhenotypeProtocols documentationPublishingRecurrenceResearchSamplingSensitivity and SpecificitySiteSomatic MutationTechniquesTechnologyTestingTissue MicroarrayTissuesTrainingUntranslated RNAValidationVariantage relatedbaseblastocystbrain tissuecell typecomputerized toolscostcost effectivedesigndetection methoddisorder riskgenetic variantgenome sequencinghuman tissueimprovedlarge datasetsmosaicpromoterscale uptargeted sequencingtechnology developmenttooltranscription factorwhole genome
项目摘要
Project summary
Somatic mutations accumulate in normal tissues and are increasingly recognized as a crucial
determinant of disease risk, especially in age-related conditions and cancer. Somatic mutations show
enrichment in portions of the noncoding genome that show “open” chromatin structure, such as active
promoter and enhancer elements, because open chromatin is more vulnerable to mutagens. Furthermore,
transcription factors binding appears to obstruct DNA repair, increasing the likelihood of forming fixed, double-
stranded mutations. The channeling effects of these mechanisms result in a concentration of somatic
mutations in restricted, yet critical, regions of the genome. Somatic mutations with an increased likelihood of
causing diseases frequently arise at recurrent genomic sites, and often even recurrent mutations at specific
bases, allowing for the development of targeted methods with greater sensitivity, lower cost, and higher
throughput to identify somatic mutations than traditional sequencing techniques.
Present methods for identifying somatic mutations generally utilize deep (≥250X) whole genome
sequencing (WGS) and tend to be expensive, create large datasets that are computationally challenging to
analyze, and have limited ability to detect somatic variants with very low allele fractions. We propose a two
phase approach to developing a new tool to address these shortcomings. In the first phase we will develop a
method of detecting somatic mutations using ATAC-seq. ATAC-seq targets the open chromatin regions of the
genome so is focused on regions with increased somatic mutations that have an increased likelihood of being
biologically meaningful, only incorporates a fraction of the genome creating a more manageable dataset, and
allows for deeper sequencing to increase the sensitivity of somatic mutation detection. This phase of the
proposal includes three aims: modification of the ATAC-seq protocol to allow for detection of somatic
mutations; development of analysis software to analyze the data; and testing of the protocol.
In the second phase of the protocol, data obtained from phase one will be used to develop a panel
sequencing protocol to further narrow the genomic regions looked at, reduce the cost of the analysis, and allow
for extracted DNA to be directly analyzed (rather than the intact chromatin needed for ATAC-seq). This phase
will also involve three aims: expansion of ATAC-seq analysis to determine the best regions to include on the
sequencing panel; development of the sequencing panel; and testing of the panel on a range of individuals and
tissue types.
This project will provide rapid and inexpensive methods for the detection of potentially critical somatic
mutations in any tissue type. At a research level, it will allow for the analysis of a large number of samples to
provide critical information on biologically important somatic mutations and thus be an important tool that will
help illuminate the spectrum of somatic mutation in the noncoding genome.
项目总结
项目成果
期刊论文数量(0)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
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Peter J Park其他文献
Identification of regions in the HOX cluster that can confer repression in a Polycomb-dependent manner
- DOI:
10.1186/1756-8935-6-s1-p86 - 发表时间:
2013-03-01 - 期刊:
- 影响因子:3.500
- 作者:
Caroline J Woo;Peter V Kharchenko;Laurence Daheron;Peter J Park;Robert E Kingston - 通讯作者:
Robert E Kingston
Peter J Park的其他文献
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{{ truncateString('Peter J Park', 18)}}的其他基金
Data Analysis Center for Somatic Mosaicism Across Human Tissues Network
人体组织网络体细胞镶嵌数据分析中心
- 批准号:
10662721 - 财政年份:2023
- 资助金额:
$ 44.83万 - 项目类别:
Mutational signature analysis: methods and applications to the clinic
突变特征分析:方法和临床应用
- 批准号:
10418967 - 财政年份:2022
- 资助金额:
$ 44.83万 - 项目类别:
Mutational signature analysis: methods and applications to the clinic
突变特征分析:方法和临床应用
- 批准号:
10618248 - 财政年份:2022
- 资助金额:
$ 44.83万 - 项目类别:
Interoperability and Collaboration with the Common Fund Data Ecosystem to Improve Utility of 4DN Data
与共同基金数据生态系统的互操作性和协作,以提高 4DN 数据的实用性
- 批准号:
10683513 - 财政年份:2021
- 资助金额:
$ 44.83万 - 项目类别:
Interoperability and Collaboration with the Common Fund Data Ecosystem to Improve Utility of 4DN Data
与共同基金数据生态系统的互操作性和协作,以提高 4DN 数据的实用性
- 批准号:
10406676 - 财政年份:2021
- 资助金额:
$ 44.83万 - 项目类别:
Interoperability and Collaboration with the Common Fund Data Ecosystem to Improve Utility of 4DN Data
与共同基金数据生态系统的互操作性和协作,以提高 4DN 数据的实用性
- 批准号:
10907133 - 财政年份:2021
- 资助金额:
$ 44.83万 - 项目类别:
Identification of Transposable Element Insertions in the Kids First Data
Kids First 数据中转座元件插入的识别
- 批准号:
10172875 - 财政年份:2020
- 资助金额:
$ 44.83万 - 项目类别:
1/2-Somatic mosaicism and autism spectrum disorder
1/2-躯体镶嵌和自闭症谱系障碍
- 批准号:
9246015 - 财政年份:2016
- 资助金额:
$ 44.83万 - 项目类别:
Linking sequence and copy number variation to eye diseases by regulatory genomics
通过调控基因组学将序列和拷贝数变异与眼部疾病联系起来
- 批准号:
9044785 - 财政年份:2016
- 资助金额:
$ 44.83万 - 项目类别:
Visual Analysis of Genomic and Clinical Data from Large Patient Cohorts
对大型患者队列的基因组和临床数据进行可视化分析
- 批准号:
8875824 - 财政年份:2015
- 资助金额:
$ 44.83万 - 项目类别:
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