Dissecting natural variation in transcription factor - DNA interactions

剖析转录因子 - DNA 相互作用的自然变异

• 批准号: 10200847
• 负责人: Shao-shan Carol Huang
• 金额: $ 39.08万
• 依托单位: NEW YORK UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-07-01 至 2025-04-30
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10200847
• 关键词: Address; Affect; Binding; Binding Sites; Catalogs; Cells; Code; Collection; Complement; Computer Analysis; Computer Models; DNA; Development; Elements; Environment; Epigenetic Process; Gene Expression; Genes; Genetic; Genetic Variation; Genome; Genomic DNA; Goals; Knowledge; Light; Link; Location; Maps; Mediating; Modification; Molecular; Mouse-ear Cress; Pattern; Phenotype; Play; Research; Resolution; Role; Shapes; Specificity; Variant; Vision; base; empowered; epigenetic variation; epigenome; epigenomics; experimental study; family structure; genome-wide; human disease; novel; phenotypic data; precision medicine; programs; protein protein interaction; reference genome; trait; transcription factor

PROJECT SUMMARY/ABSTRACT Gains or losses of transcription factor binding at specific locations in the genome have been linked to a wide range of human diseases. Despite our knowledge about the determinants of transcription factor-DNA interaction, it is still challenging to accurately predict changes in transcription factor binding due to genetic and epigenetic variants in the genome. Several critical gaps remain in our understanding of the integration of sequence and non-sequence information on endogenous genomic DNA that give rise to the genome-wide binding patterns of transcription factors. Our long-term vision is to shed light on how genome and epigenome variation, which leads to variation in the genome-wide targets of transcription factors, affects the regulatory networks of the cell, and the gene expression programs that give rise to phenotypic diversity. Our previous study characterized the genome-wide binding locations of more than 500 transcription factors in Arabidopsis thaliana on the reference genome. Our integrative computational analysis revealed the features of endogenous genome context, consisting of sequence motif, DNA shape, and 5-methylcytosine modification of genomic DNA, that play a role in determining the binding landscape of transcription factors of major structural families. To further study the variability of these binding sites, driven by native genome and epigenome variation, we generated genome-wide, base-resolution maps of 5-methylcytosine, an epigenomic mark on DNA, in a collection of over 1,000 world-wide, natural strains (accessions) of A. thaliana, complementing the efforts to catalog genome sequence variation in these accessions. Guided by the diversity in the genome and epigenome, a wealth of phenotypic data, and preliminary results suggesting transcription factor binding variation in these accessions, our goals for the next five years are to address three major challenges in understanding natural variation in transcription factor binding: 1) to determine the genome-wide transcription factor binding variation across multiple accession genomes; 2) to characterize the effect of transcription factor coding variants on their genome-wide binding specificities and target genes; and 3) to investigate how natural variation of protein-protein interactions alters target genes and genome-wide binding specificities for interacting transcription factors. All three projects will use computational modeling to evaluate the contributions from features in the binding site environment. Our proposed experiments and computational models will make a broad impact by characterizing transcription factor binding variation and understanding the role played by sequence and non-sequence features of endogenous genomic DNA. Our results will shed light on the fundamental principles underlying the regulatory functions of genome and epigenome variation, empowering the discovery and prediction of regulatory variants and their molecular mechanisms.

项目概要/摘要 转录因子在基因组特定位置结合的获得或丧失与广泛的 一系列人类疾病。尽管我们了解转录因子 DNA 的决定因素 相互作用，准确预测由于遗传和遗传因素导致的转录因子结合的变化仍然具有挑战性。 基因组中的表观遗传变异。我们对整合的理解仍然存在一些关键差距 内源基因组 DNA 的序列和非序列信息，产生全基因组 转录因子的结合模式。我们的长期愿景是阐明基因组和表观基因组如何 变异会导致转录因子的全基因组靶标发生变异，从而影响调控 细胞网络以及产生表型多样性的基因表达程序。 我们之前的研究描述了 500 多个转录因子的全基因组结合位置 在拟南芥的参考基因组上。我们的综合计算分析揭示了这些特征 内源基因组背景，由序列基序、DNA 形状和 5-甲基胞嘧啶修饰组成 基因组 DNA，在确定主要转录因子的结合景观中发挥作用 结构性家庭。为了进一步研究这些结合位点的变异性，由天然基因组和 表观基因组变异，我们生成了 5-甲基胞嘧啶（表观基因组）的全基因组碱基分辨率图谱。 在全球 1,000 多个拟南芥天然品系（种质）的 DNA 上进行标记， 补充对这些种质中基因组序列变异进行编目的努力。以多样性为导向 在基因组和表观基因组中，大量的表型数据和初步结果表明转录 这些种质的因子结合变异，我们未来五年的目标是解决三个主要问题 理解转录因子结合自然变异的挑战：1）确定全基因组范围 跨多个登录基因组的转录因子结合变异； 2) 表征效果 转录因子编码变体的全基因组结合特异性和靶基因； 3) 至 研究蛋白质-蛋白质相互作用的自然变异如何改变靶基因和全基因组结合 相互作用的转录因子的特异性。所有三个项目都将使用计算模型来评估 结合位点环境中特征的贡献。 我们提出的实验和计算模型将通过表征产生广泛的影响 转录因子结合变异以及理解序列和非序列所发挥的作用 内源基因组DNA的特征。我们的结果将揭示潜在的基本原则 基因组和表观基因组变异的调节功能，促进发现和预测 调控变异及其分子机制。