Inferring gene regulatory circuitry from functional genomics data

从功能基因组数据推断基因调控电路

基本信息

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
项目类别：
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

项目摘要

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）：项目摘要早就知道基因组DNA的甲基化会影响基因表达。然而，基本的基本结构机制在很大程度上仍然晦涩难懂。在这个项目中，我们将采取一种新的策略来预测甲基化如何影响转录因子（TF）结合，从而影响局部染色质结构的复杂基因组结构和基因表达的复杂范围，并影响每个细胞的基因表达。我们将探讨以下假设：甲基化会导致DNA形状的局部变化，从而改变TF结合亲和力。动机来自我们最近对内核酸酶DNase I的内在特异性I的分析。我们发现，胞嘧啶甲基化大大提高了DNase I裂解与CPG夹克固醇相邻的DNA骨架的速率。 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基于形状的非甲基化DNA序列中TF结合偏好的分析，为此，可以为此提供充足的高通量体外结合数据。为了探讨这一点，我们将首先开发和拟合TF结合特异性的模型，通过扩展我们的特征化算法的生物物理模型来整合DNA碱基和形状读数，以包括来自自由DNA分子的计算机模拟的DNA形状的信息。接下来，我们将使用这些集成的基础/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敏感性。在一种平行的方法中，我们将通过使用甲基化和未甲基化的DNA配体的条形码混合物来扩展我们最近开发的SELEX-SEQ方法，从而创建甲基化对TFS的结合亲和力的影响的详细图。最后，我们将分析 TF的结合特异性如何取决于其氨基酸序列使用家族级建模。使用对同一结构TF家族的大量TF估计的生物物理基础和形状识别参数，以及基础偏好的新几何几何表示，我们将预测基本螺旋 - 环 - 螺旋（BHLH）的结合特异性如何在氨基酶（BZIP）蛋白质的基本蛋白质（BZIP）蛋白质变化时变化时，并实验了这些预测。我们将使用相同的基于家庭的方法来证明BHLH因子的替代二聚体结合模式的存在，并研究是否可以从其蛋白质序列中预测TF使用这些替代模式的倾向。