Inferring gene regulatory circuitry from functional genomics data

从功能基因组数据推断基因调控电路

• 批准号: 8584808
• 负责人: Harmen J Bussemaker
• 金额: $ 53万
• 依托单位: COLUMBIA UNIV NEW YORK MORNINGSIDE
• 依托单位国家: 美国
• 财政年份: 2004
• 资助国家: 美国
• 起止时间: 2004-08-13 至 2016-06-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8584808
• 关键词: Accounting; Affect; Affinity; Algorithms; Amino Acid Sequence; Amino Acids; Base Sequence; Binding; Biological Assay; Cells; Chromatin Structure; Cleaved cell; Computer Simulation; CpG dinucleotide; Cytosine; DNA; DNA Binding; DNA Methylation; DNA Sequence; Data; Deoxyribonuclease I; Disease; Electrostatics; Epigenetic Process; Family; Free Energy; Gene Expression; Gene Expression Regulation; Genes; Genetic Transcription; Genome; Genomics; Goals; Helix-Turn-Helix Motifs; Hybrids; In Vitro; Laboratories; Ligands; Link; Literature; Major Groove; Mammals; Maps; Mediating; Memory; Methods; Methylation; Minor Groove; Modeling; Modification; Molecular; Motivation; Mutate; Nucleotides; Organism; Peptide Sequence Determination; Positioning Attribute; Protein Binding; Proteins; Regulator Genes; Shapes; Side; Specificity; Vertebral column; Writing; Yeasts; base; computerized tools; deep sequencing; endonuclease; functional genomics; genetic regulatory protein; genome sequencing; genome-wide; high throughput technology; human CREB3 protein; inorganic phosphate; methyl group; novel; preference; public health relevance; response; transcription factor

DESCRIPTION (provided by applicant): PROJECT SUMMARY It has long been known that methylation of genomic DNA influences gene expression. The underlying structural mechanisms, however, largely remain obscure. In this project, we will pursue a new strategy for predicting how methylation affects transcription factor (TF) binding, thereby influencing the intricate genomewide landscape of local chromatin structure and gene expression that characterizes each cell. We will explore the hypothesis that methylation causes local changes in DNA shape, which in turn modify TF binding affinity. Motivation comes from our recent analysis of the intrinsic specificity of the endonuclease DNase I. We found that cytosine methylation greatly increases the rate at which DNase I cleaves the DNA backbone adjacent to CpG dinucleotides. The explanation for this is that adding a methyl group in the major groove causes changes in DNA shape that locally narrow the minor groove and enhance the electrostatic interaction between negative backbone phosphates of the DNA and positive amino-acid residues of DNase I. Recognition of DNA shape via the minor groove can also contribute to the binding specificity of eukaryotic TFs, suggesting that methylation sensitivity can be predicted from a shape-based analysis of TF binding preferences among unmethylated DNA sequences, for which ample high-throughput in vitro binding data is available. To explore this, we will first develop and fit models of TF binding specificity that integrate DNA base and shape readout by extending the biophysical model underlying our FeatureREDUCE algorithm to include information about DNA shape from computer simulations of free DNA molecules. Next, we will use these integrated base/shape recognition models to make predictions regarding the methylation sensitivity of TFs, and validate these experimentally. In a parallel approach, we will extend our recently developed SELEX-seq method by using barcoded mixtures of methylated and unmethylated DNA ligands to create detailed maps of the effect of methylation on binding affinity for a representative set of TFs. Finally, we will analyze how the binding specificity of a TF depends on its amino-acid sequence using family-level modeling. Using biophysical base and shape recognition parameters estimated for a large number of TFs from the same structural TF family, along with a novel geometric representation of base preference, we will predict how the binding specificity of basic helix-loop-helix (bHLH) and basic leucine zipper (bZIP) proteins changes when amino-acid residues are mutated, and experimentally validate these predictions. We will use the same family-based approach to demonstrate the existence of alternative dimeric binding modes for bHLH factors, and investigate whether the propensity of a TF to use these alternative modes can be predicted from its protein sequence.

描述（由申请人提供）： 基因组DNA的甲基化影响基因表达，这一点早已为人们所知。然而，基本的结构机制在很大程度上仍然模糊不清。在这个项目中，我们将寻求一种新的策略来预测甲基化如何影响转录因子（TF）结合，从而影响每个细胞特有的局部染色质结构和基因表达的复杂全基因组景观。我们将探讨甲基化导致DNA形状局部变化的假设，这反过来又会改变TF结合亲和力。动机来自我们最近对核酸内切酶DNase I内在特异性的分析。我们发现胞嘧啶甲基化大大增加了DNA酶I切割CpG二核苷酸附近的DNA骨架的速率。对此的解释是，在大沟中添加甲基会导致DNA形状的变化，使小沟局部变窄，并增强DNA的负骨架磷酸盐与DNA酶I的正氨基酸残基之间的静电相互作用。通过小沟识别DNA形状也可以有助于真核TF的结合特异性，这表明甲基化敏感性可以从基于形状的TF结合偏好分析中预测未甲基化的DNA序列，其中有足够的高通量体外结合数据。为了探索这一点，我们将首先开发和拟合TF结合特异性的模型，通过扩展我们的生物物理模型来整合DNA碱基和形状读出，以包括来自游离DNA分子的计算机模拟的DNA形状信息。接下来，我们将使用这些集成的碱基/形状识别模型来预测TF的甲基化敏感性，并通过实验验证这些预测。在一种平行的方法中，我们将通过使用甲基化和未甲基化DNA配体的条形码混合物来扩展我们最近开发的SELEX-seq方法，以创建甲基化对一组代表性TF的结合亲和力的影响的详细地图。最后，我们将分析 TF的结合特异性如何依赖于其氨基酸序列，使用家族水平建模。使用生物物理基础和形状识别参数估计大量的TF从相同的结构TF家族，沿着一个新的几何表示的基础偏好，我们将预测如何结合特异性的碱性螺旋-环-螺旋（bHLH）和碱性亮氨酸拉链（bZIP）蛋白质的变化时，氨基酸残基突变，并通过实验验证这些预测。我们将使用相同的家庭为基础的方法来证明存在的替代bHLH因子的二聚体结合模式，并调查是否TF的倾向，使用这些替代模式可以从其蛋白质序列预测。