DNA Binding Properties of Zinc Finger Proteins

锌指蛋白的 DNA 结合特性

基本信息

批准号：
10006589
负责人：
Petko M Petkov
金额：
$ 36.76万
依托单位：
JACKSON LABORATORY
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：
2018-09-01 至 2022-08-31
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/10006589
关键词：
Address Affect Affinity Amino Acid Substitution Amino Acids Base Pairing Binding Binding Proteins Binding Sites Biological Biological Assay Cell Culture System Cell Culture Techniques ChIP-seq Chromatin Remodeling Factor Computational algorithm DNA DNA Binding DNA Methylation DNA Sequence DNA analysis DNA-Binding Proteins Data Development Disease Engineering Evolution Fingers Genes Genetic Genetic Engineering Genetic Recombination Genomic DNA Human Human Genome In Vitro Infertility Knowledge Malignant Neoplasms Measures Meiotic Recombination Metabolic Diseases Methods Methylation Modeling Mus Mutation Analysis Nucleotides Oligonucleotides Orthologous Gene Physiological Positioning Attribute Process Property Protein Array Proteins Regulation Sensitivity and Specificity Site Source Specificity Study models System Testing Variant Zinc Fingers base cost deep sequencing ds-DNA gene function genome-wide human disease improved in vivo mammalian genome novel paralogous gene prediction algorithm predictive modeling programs transcription factor

项目摘要

The human genome contains over 700 genes encoding proteins with zinc finger domains, more than half of which contain eight or more fingers organized in a tandem fashion. Many of these genes function as transcription factors, insulator binding proteins, or chromatin modifiers. Despite their importance, we still lack a comprehensive knowledge on the rules that determine these proteins’ binding to DNA, and the existing prediction programs do not perform satisfactorily. Recently, we have developed two new methods for isolation and deep sequencing of zinc finger protein binding sites. The first, Affinity-seq directly determines the relative affinity of tens of thousands of binding sites genome-wide with high binding specificity. It also provides the opportunity for mutational analysis of binding site specificities using alternate sources of genomic DNA. The second, Spec-sec, determines the changes in binding energy for thousands of variants of a preferred sequence, and their sensitivity to DNA methylation. We propose to apply these methods for comprehensive analysis of DNA binding sites of over twenty mouse and human natural protein variants of the recombination regulator PRDM9, as well as over one hundred other human and mouse zinc finger proteins, which represent different groups of long zinc finger array proteins, and whose binding sites has not been determined previously. In Aim 1, we will determine the specificities of PRDM9 protein variants binding to DNA. Aim 1a will determine how systematic changes in contact amino acids, numbers, and interactions between ZFs in PRDM9 protein variants affect their DNA binding by Affinity-seq. Aim 1b will determine the quantitative specificity and sensitivity to DNA methylation of each PRDM9 protein variant by Spec-seq. Aim 1c will use cell culture approaches to determine how conserved features of ZF arrays and combinations of motifs in the same array affect the biological activity of engineered PRDM9 protein variants. In Aim 2, we will determine whether DNA- binding specificities of different laZFP groups co-evolve with their additional domains. Aim 2a will determine the commonality or uniqueness of the rules governing binding to DNA of laZFPs belonging to BTB-, SCAN-, SET-, and KRAB- containing groups, and those without additional domains, by Affinity-seq. Aim 2b will determine their quantitative specificity and sensitivity to CpG methylation (mCpG) status by Spec-seq. In Aim 3, we will develop new and improved computational algorithms for binding site modeling and motif prediction based on laZFP sequences, including mCpG sensitivity. Aim 3a will develop enhanced specificity representations of ZFPs that take full advantage of the Spec-seq data and don’t impose the positional independence inherent in PWM models. Aim 3b will develop improved motif prediction models including methylation sensitivity.

人类基因组包含 700 多个编码具有锌指结构域的蛋白质的基因，其中一半以上这些基因包含八个或更多以串联方式组织的手指。转录因子、绝缘体结合蛋白或染色质修饰剂尽管很重要，但我们仍然缺乏。关于决定这些蛋白质与 DNA 结合的规则的全面知识，以及现有的最近，我们开发了两种新的隔离方法。和锌指蛋白结合位点的深度测序第一，Affinity-seq直接确定相对值。它还提供了全基因组数万个结合位点的亲和力，具有高结合特异性。使用基因组 DNA 的替代来源进行结合位点特异性突变分析的机会。第二，Spec-sec，确定优选的数千个变体的结合能的变化序列，以及它们对 DNA 甲基化的敏感性，我们建议应用这些方法进行综合。分析重组的 20 多个小鼠和人类天然蛋白质变体的 DNA 结合位点调节剂 PRDM9 以及一百多个其他人类和小鼠锌指蛋白，它们代表不同组的长锌指阵列蛋白，其结合位点之前尚未确定。在目标 1 中，我们将确定 PRDM9 蛋白变体与 DNA 结合的特异性。 PRDM9 蛋白中的接触氨基酸、数量和 ZF 之间的相互作用如何发生系统性变化目标 1b 将确定定量特异性和 Spec-seq Aim 1c 对每个 PRDM9 蛋白变体 DNA 甲基化的敏感性将使用细胞培养物。确定 ZF 阵列和同一阵列中基序组合的保守特征的方法影响工程 PRDM9 蛋白变体的生物活性在目标 2 中，我们将确定 DNA 是否- 不同 laZFP 基团与其附加结构域共同进化的结合特异性将决定目标 2a。属于 BTB-、SCAN-、SET- 的 laZFP 与 DNA 结合的规则的共性或独特性，包含 KRAB 的基团，以及那些没有额外结构域的基团，将由 Affinity-seq 确定。在目标 3 中，我们将通过 Spec-seq 检测它们对 CpG 甲基化 (mCpG) 状态的特异性和敏感性。开发新的和改进的计算算法，用于基于 laZFP 序列，包括 mCpG 敏感性，将开发增强的特异性表示。 ZFP 充分利用 Spec-seq 数据，并且不强加固有的位置独立性 Aim 3b 将开发改进的基序预测模型，包括甲基化敏感性。