AVATAR: highly parallel analysis of variation in transcription factors and their DNA binding sites

AVATAR：转录因子及其 DNA 结合位点变异的高度并行分析

基本信息

批准号：
9767247
负责人：
MARTHA L BULYK
金额：
$ 22.38万
依托单位：
BRIGHAM AND WOMEN'S HOSPITAL
依托单位国家：
美国
项目类别：
财政年份：
2018
资助国家：
美国
起止时间：
2018-08-20 至 2021-05-31
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/9767247
关键词：
Adult Affect Affinity Alleles Binding Binding Proteins Binding Sites Biological Assay Bypass Catalysis Cell Culture Techniques Cells Code Collection Complex DNA DNA Binding DNA Binding Domain DNA Damage DNA Library DNA Sequence Defect Development Directed Molecular Evolution Disease Emulsions Enhancers Enzymes Genes Genetic Genetic Polymorphism Genetic Transcription Genetic Variation Genomics Goals Human Human Genetics Hybrids In Vitro Individual Libraries Microfluidics Mutation Nucleic Acid Regulatory Sequences Oils Onset of illness Phenotype Plasmids Predictive Factor Prevalence Proteins Regulator Genes Regulatory Element Reporter Role Site Specificity Surveys Technology Testing Time Untranslated RNA Variant Water aqueous base experimental study genetic variant high throughput technology improved member new technology novel precision medicine trait transcription factor vector

项目摘要

Abstract The interactions between transcription factors (TFs) and their DNA binding sites are central to gene regulatory networks. Genetic variation in TFs or their DNA binding sites can contribute to differences in traits among individuals. However, the role of interactions among such genetic variants remains poorly understood. Existing high-throughput technologies for assaying the DNA binding activities of TFs (or TF variants) are “1-by-many” approaches, in which a given protein is assayed for its binding to a large library of different DNA sequences, or alternatively assay a large library of protein variants for activity from a given DNA sequence. A major hurdle in characterization of TF coding variants and DNA noncoding variants is the lack of a high-throughput “many-by-many” technology that would enable testing of a large collection of TF coding variants for binding to a library of different DNA binding site sequences; such DNA binding site sequences could represent either a large collection of substitutions in a TF's DNA binding site motif, or alternatively putative cis-regulatory variants. The primary goal of this project is to develop novel technology, termed All-Variant Analysis of Transcription factor Affinity and Recognition (AVATAR), for highly parallel analysis of a library of TF coding variants for interaction with a library of variants in their DNA binding sites. We will prioritize human TFs that are associated with diseases and for which disease-associated mutations or naturally occurring polymorphisms predicted to have damaged DNA binding activity have been identified. Such technology would permit: more extensive experimental testing of putatively damaging TF coding variants whose precise effects on DNA binding activity are not currently predictable (unpublished results); an improved understanding of specificity- determining residues and TF-DNA `recognition rules' for various TF classes; and identification of potential genetic interactions between TF coding variants and noncoding variants in TF binding sites (TFBSs). !

抽象的转录因子 (TF) 与其 DNA 结合位点之间的相互作用至关重要 TF 或其 DNA 结合位点的遗传变异可能有助于基因网络调控。然而，个体之间的特征差异是遗传之间相互作用的作用。变体仍然知之甚少。现有的高通量技术用于测定 TF（或 TF）的 DNA 结合活性变体）是“一对多”方法，其中分析给定蛋白质与不同 DNA 序列的大型文库，或者分析蛋白质变体的大型文库给定 DNA 序列的活性是表征 TF 编码变体的主要障碍。 DNA非编码变体的原因是缺乏高通量的“多对多”技术将能够测试大量 TF 编码变体集合，以绑定到不同的库 DNA结合位点序列；这样的DNA结合位点序列可以代表大的 TF DNA 结合位点基序中的取代集合，或者推定的顺式调节变种。该项目的主要目标是开发新技术，称为全变异分析转录因子亲和力和识别 (AVATAR)，用于高度并行分析文库 TF 编码变体，用于与 DNA 结合位点的变体库相互作用。优先考虑与疾病相关的人类 TF，以及与疾病相关的人类 TF 预测会损害 DNA 结合的突变或自然发生的多态性此类技术将允许：进行更广泛的实验。测试假定具有破坏性的 TF 编码变体，其对 DNA 结合活性的精确影响目前无法预测（未发表的结果）；确定各种 TF 类别的残基和 TF-DNA“识别规则”； TF 结合中 TF 编码变体和非编码变体之间潜在的遗传相互作用站点（TFBS）。！