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.

项目摘要/摘要 基因组特定位置的转录因子结合的收益或损失已与宽 人类疾病范围。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 基因组中的表观遗传变异。我们对整合的一体化的理解仍然存在一些关键差距 有关内源性基因组DNA的序列和非序列信息，这些DNA引起了全基因组 转录因子的结合模式。我们的长期视野是阐明基因组和表观基因组 变异导致转录因子全基因组靶标变异，会影响调节 细胞网络以及引起表型多样性的基因表达程序。 我们先前的研究表征了500多个转录因子的全基因组结合位置 在参考基因组上的拟南芥中。我们的集成计算分析揭示了特征 内源性基因组环境，由序列基序，DNA形状和5-甲基环肽修饰组成 基因组DNA，在确定主要的转录因子的结合景观中起作用 结构家庭。进一步研究由天然基因组和 表观基因组变异，我们产生了全基因组，5-甲基胞嘧啶的基础分辨率图，一种表观基因组学 在DNA上的标记，在全球范围内有1000多家A. Thaliana的天然菌株（加入）收藏 补充这些登录中分类基因组序列变化的努力。在多样性的指导下 在基因组和表观基因组中，大量的表型数据以及提示转录的初步结果 这些加入的因素约束变化，我们未来五年的目标是解决三个主要 理解转录因子结合的自然变异的挑战：1）确定全基因组的挑战 多个登录基因组之间的转录因子结合变化； 2）表征 其全基因组结合特异性和靶基因上的转录因子编码变体；和3）到 研究蛋白质蛋白质相互作用的自然变化如何改变靶基因和全基因组结合 相互作用转录因子的特异性。这三个项目将使用计算建模来评估 绑定站点环境中功能的贡献。 我们提出的实验和计算模型将通过表征来产生广泛的影响 转录因子的结合变化和理解序列和非序列起的作用 内源性基因组DNA的特征。我们的结果将阐明 基因组和表观基因组变异的调节功能，赋予发现和预测 调节变体及其分子机制。