Dynamic genetic regulation of gene expression in diverse differentiation trajectories with human embryoid bodies

人胚体不同分化轨迹基因表达的动态遗传调控

• 批准号: 10607614
• 负责人: Joshua Popp
• 金额: $ 4.77万
• 依托单位: JOHNS HOPKINS UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-01-17 至 2026-07-16
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10607614
• 关键词: 3-Dimensional; Acceleration; Adult; Biological; Biological Assay; Body mass index; Cells; Chicago; Chromatin; Complex; Computing Methodologies; Coronary Arteriosclerosis; Data; Data Set; Disease; Fetal Tissues; Gene Expression; Gene Expression Regulation; Genes; Genetic; Genetic Risk; Genetic Variation; Genome; Heterogeneity; Human; Human Genetics; Human Genome; In Vitro; Individual; Individual Differences; Link; Maps; Measures; Mediating; Modeling; Molecular; Noise; Nucleic Acid Regulatory Sequences; Pattern; Positioning Attribute; Quantitative Trait Loci; Regulation; Research; Research Personnel; Sampling; Schizophrenia; Specificity; Statistical Methods; Statistical Models; System; Testing; Tissue Sample; Tissues; Universities; Validation; Variant; Work; body system; cell type; disorder risk; genetic variant; genome wide association study; genomic locus; human disease; human embryoid body; improved; in vivo; induced pluripotent stem cell; insight; novel; risk variant; single cell analysis; single-cell RNA sequencing; statistics; tool; trait

Understanding the functional impact of genetic variation, particularly its impact on disease, remains a key challenge in human genetics. Most disease-associated genetic loci lie in regulatory regions of the human genome and are suspected to act by regulating the expression levels of nearby genes. Yet despite extensive efforts to characterize genetic regulatory effects on gene expression, most disease loci have not been explained by association with expression levels. Pervasive context-specificity of these regulatory effects introduces one key bottleneck contributing to this discrepancy. Detecting regulatory effects requires observation of gene expression in the specific cell states where the effect is active, and large-scale efforts have primarily focused on measuring expression levels in healthy adult tissues. Characterizing genetic regulation in increasingly diverse and dynamic cellular contexts will therefore reveal novel genetic regulatory effects which may help elucidate molecular mechanisms of disease loci. To analyze genetic regulation of gene expression in diverse cellular contexts we will leverage single-cell RNA-sequencing of embryoid bodies from multiple human donors. Embryoid bodies are three-dimensional aggregates of induced pluripotent stem cells that spontaneously differentiate into dozens of non-discrete cell types. Analysis of expression at the single-cell level will enable us to cut through the heterogeneity of these complex aggregates and map each cell to a unique position within a clearly defined differentiation landscape. Embryoid bodies thus offer a unified experimental framework for the study of diverse differentiation trajectories, accelerating the exploration of genetic regulation across the many cell states that may contribute to human disease. In this proposed research, I will develop novel computational and statistical tools that leverage the expansive and multifurcating landscape of cellular differentiation to improve our ability to resolve context-specific and dynamic genetic regulatory effects. I will develop a probabilistic model to compare gene expression dynamics between individuals, and a hypothesis testing framework to attribute inter-individual differences to genetic variation. I will validate the dynamic genetic regulatory effects we discover using in vitro and in vivo chromatin accessibility data. Finally, I will search for overlap between newly discovered regulatory variants and known disease loci to reveal novel insights into the target genes mediating genetic effects on common diseases.

了解遗传变异的功能影响，特别是其对 疾病，仍然是人类遗传学的一个关键挑战。大多数与疾病相关的基因位点位于 人类基因组的调控区，并被怀疑通过调节表达 附近的基因。然而，尽管广泛的努力，以表征遗传调控效应， 在基因表达方面，大多数疾病位点不能用与表达相关来解释， 程度.这些调节效应的普遍背景特异性引入了一个关键瓶颈 造成了这种差异。检测调控效应需要观察基因 在特定的细胞状态下表达，其中效果是活跃的，并且大规模的努力已经取得了进展。 主要集中于测量健康成人组织中的表达水平。表征 因此，在日益多样化和动态的细胞环境中的遗传调控将揭示 可能有助于阐明疾病分子机制的新的遗传调节作用 的位点 为了分析不同细胞环境中基因表达的遗传调控，我们将 利用来自多个人类供体的胚状体的单细胞RNA测序。 类胚体是诱导多能干细胞的三维聚集体， 自发分化成几十种非离散细胞类型。分析在联合国 单细胞水平将使我们能够切断这些复杂聚集体的异质性， 将每个细胞映射到明确定义的分化景观中的独特位置。胚状 因此，身体为研究多样性分化提供了一个统一的实验框架。 轨迹，加速探索遗传调控的许多细胞状态， 可能导致人类疾病。 在这项拟议的研究中，我将开发新的计算和统计工具， 利用细胞分化的广阔和多分叉景观来改善我们的 解决特定环境和动态遗传调控效应的能力。我将开发一个 概率模型来比较个体之间的基因表达动态，以及 假设检验框架将个体间差异归因于遗传变异。我会 验证了我们在体外和体内染色质中发现的动态遗传调控效应 可访问性数据。最后，我将搜索新发现的监管变体之间的重叠 和已知的疾病位点，以揭示介导遗传效应的靶基因的新见解 关于常见疾病。