Genome analysis based on the integration of DNA sequence and shape
基于DNA序列和形状整合的基因组分析
基本信息
- 批准号:8632246
- 负责人:
- 金额:$ 33.43万
- 依托单位:
- 依托单位国家:美国
- 项目类别:
- 财政年份:2014
- 资助国家:美国
- 起止时间:2014-02-01 至 2018-01-31
- 项目状态:已结题
- 来源:
- 关键词:AffectAffinityAlgorithmsBHLH ProteinBase PairingBase SequenceBenchmarkingBindingBinding SitesBiological ProcessChIP-on-chipChIP-seqCharacteristicsCommunitiesComputational algorithmDNADNA BindingDNA DatabasesDNA MethylationDNA SequenceDNA StructureDNA-Binding ProteinsDNase-I FootprintingDataData AnalysesDatabasesDeoxyribonuclease IDevelopmentDrosophila genusEmbryonic DevelopmentFamilyFunctional RNAGene Expression RegulationGenetic TranscriptionGenomeGenome ScanGenomicsGeometryGoalsGuanine + Cytosine CompositionHelix-Turn-Helix MotifsHumanHybridsHydroxyl RadicalIn VitroInternetLeadLengthLettersLinear RegressionsMachine LearningMalignant NeoplasmsMeasurementMeasuresMethodsMethylationMiningMinor GrooveModelingMolecular BiologyNMR SpectroscopyNucleotidesPilot ProjectsPlayProcessPropertyProtein BindingProtein FamilyProteinsPublishingQuantitative Trait LociRelative (related person)ResolutionRoleScanningSequence AnalysisShapesSignal TransductionSingle Nucleotide PolymorphismSiteSpecificityStructureSystemTechniquesTechnologyTestingTrainingValidationVariantWidthX-Ray CrystallographyYeastsbasedesignflexibilitygenetic evolutiongenome analysisgenome wide association studygenome-widehomeodomainhuman diseasein vivoinsightmembernovelnovel strategiespublic health relevanceresearch studythree dimensional structuretooltranscription factorvector
项目摘要
Title: Genome analysis based on the integration of DNA sequence and shape
PI: Rohs, Remo (USC); Co-I: Noble, William Stafford (UW); Co-I: Tullius, Thomas D. (BU)
PROJECT SUMMARY
Current techniques for genome analysis are mainly based on the one-dimensional DNA sequence, comprised
of the letters A, C, G, and T. However, proteins recognize DNA as a three-dimensional (3D) object. Nuances in
DNA shape at single nucleotide resolution play a crucial role in the binding specificity of transcription factors
(TFs), including those involved in embryonic development and human cancer. This project involves the
development of a battery of tools for genome analysis, through the integration of information derived from the
DNA sequence and the 3D structure of DNA, or "DNA shape". The basis for these novel tools is a high-
throughput (HT) method for the prediction of multiple features of local DNA shape at the genomic scale. Data
will be made available to the community in the UCSC Genome Browser track format through a web server
interface. These tools will enable users to analyze the shape of any number or length of DNA sequences,
including whole genomes and the effect of DNA methylation. HT shape predictions will be validated based on
X-ray crystallography, NMR spectroscopy, and hydroxyl radical cleavage data. Predictions will be combined
with ORChID, an ENCODE project that infers DNA minor groove geometry from hydroxyl radical cleavage
experiments. The HT method will be used to study how paralogous TFs select different target sites in vivo
despite sharing core-binding motifs or having similar binding properties in vitro. To study this question, we will
investigate the effect of flanking sequences on multiple structural features of TF binding sites (TFBSs). The
initial focus of this study will be homeodomains and basic helix-loop-helix (bHLH) TFs. Other protein families
will later be included and used to construct a comprehensive TFBS database that provides shape features for
binding motifs derived from JASPAR and other motif databases. Structural effects of single nucleotide
polymorphisms (SNPs) will also be analyzed. Some SNPs are associated with deleterious functions, whereas
others have no apparent effect. The HT shape prediction method will be used to predict the function of SNPs in
non-coding regions based on DNA shape. We will correlate quantitative effects of SNPs on DNA structure with
expression quantitative trait loci (eQTLs) and genome-wide association study (GWAS) signals, to develop a
predictive tool for the functional effect of SNPs. The HT shape prediction approach will be used to design DNA
sequences with different AT/GC contents but similar shapes. The relative contributions of sequence and shape
to binding will be tested with analytic models including multiple linear regression (MLR) and support vector
regression (SVR). For systems in which the integration of sequence and shape proves advantageous, novel
motif finding tools will be developed based on an extended alphabet that combines sequence with informative
structural features, selected by machine learning and feature selection approaches. Sequence+shape motifs
will be tested by motif scanning, compared to sequence-only motifs, and integrated into the MEME Suite. The
goal of this sequence-shape integration is to increase the accuracy of finding in vivo TFBSs in the genome.
基于DNA序列和形状整合的基因组分析
PI:RoHS,Remo(南加州大学);Co-I:Noble,William Stafford(UW);Co-I:Tullius,Thomas D.(BU)
项目总结
目前的基因组分析技术主要基于一维DNA序列,包括
然而,在字母A、C、G和T中,蛋白质将DNA识别为三维对象。的细微差别
单核苷酸分辨的DNA形状对转录因子的结合特异性起着至关重要的作用
(TFS),包括与胚胎发育和人类癌症有关的那些。这个项目涉及到
开发一系列用于基因组分析的工具,通过整合来自
DNA序列和DNA的3D结构,或DNA形状。这些新工具的基础是高-
用于在基因组尺度上预测局部DNA形状的多个特征的吞吐量(HT)方法。数据
将通过网络服务器以UCSC Genome浏览器Track格式向社区提供
界面。这些工具将使用户能够分析任意数量或长度的DNA序列的形状,
包括整个基因组和DNA甲基化的影响。HT形状预测将基于以下内容进行验证
X-射线结晶学、核磁共振光谱和羟基自由基裂解数据。预测将结合在一起
对于兰花,一个ENCODE项目,根据羟基自由基裂解推断DNA小槽几何形状
实验。HT方法将被用来研究平行的TF如何在活体内选择不同的靶点
尽管在体外具有相同的核心结合基序或具有相似的结合特性。为了研究这个问题,我们将
研究侧翼序列对Tf结合位点(TFBs)多种结构特征的影响。这个
这项研究的最初焦点将是同源结构域和基本螺旋-环-螺旋(BHLH)转录因子。其他蛋白质家族
稍后将包括并用于构建全面的TFBS数据库,该数据库为以下内容提供形状特征
来自Jaspar和其他基序数据库的结合基序。单核苷酸的结构效应
多态(SNP)也将被分析。一些SNP与有害功能有关,而
其他的则没有明显的效果。将使用HT形状预测方法预测SNPs在中国的作用
基于DNA形状的非编码区。我们将把SNPs对DNA结构的定量影响与
表达数量性状基因座(EQTL)和全基因组关联研究(GWAS)信号,以开发一种
SNPs功能效应的预测工具。用于DNA设计的HT形状预测方法
AT/GC含量不同但形状相似的序列。序列与形状的相对贡献
将使用包括多元线性回归(MLR)和支持向量在内的分析模型来测试TO结合
回归(SVR)。对于序列和形状的整合被证明是有利的、新颖的系统
将开发基于扩展字母表的基序查找工具,该字母表将序列与信息量相结合
结构特征,通过机器学习和特征选择方法选择。序列+造型图案
将通过基序扫描进行测试,与纯序列基序进行比较,并整合到表情包套件中。这个
这种序列形状整合的目的是提高在基因组中发现体内TFBS的准确性。
项目成果
期刊论文数量(0)
专著数量(0)
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会议论文数量(0)
专利数量(0)
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Remo Rohs其他文献
Remo Rohs的其他文献
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{{ truncateString('Remo Rohs', 18)}}的其他基金
Quantitative Modeling of Transcription Factor-DNA Binding
转录因子-DNA 结合的定量建模
- 批准号:
10431863 - 财政年份:2019
- 资助金额:
$ 33.43万 - 项目类别:
Quantitative Modeling of Transcription Factor-DNA Binding
转录因子-DNA 结合的定量建模
- 批准号:
10650775 - 财政年份:2019
- 资助金额:
$ 33.43万 - 项目类别:
Quantitative Modeling of Transcription Factor-DNA Binding
转录因子-DNA 结合的定量建模
- 批准号:
10189652 - 财政年份:2019
- 资助金额:
$ 33.43万 - 项目类别:
Quantitative Modeling of Transcription Factor-DNA Binding
转录因子-DNA 结合的定量建模
- 批准号:
9975181 - 财政年份:2019
- 资助金额:
$ 33.43万 - 项目类别:
Genome analysis based on the integration of DNA sequence and shape
基于DNA序列和形状整合的基因组分析
- 批准号:
8795204 - 财政年份:2014
- 资助金额:
$ 33.43万 - 项目类别:
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