Leveraging Natural Genetic Diversity and Systems Genetics to Elucidate the Complex Hierarchy of Gene Regulation Underlying Ground State Pluripotency, Cell Fate Decisions and Tissue Homeostasis

项目摘要 精准医学计划旨在利用人口规模的基因组测序数据来定制治疗 针对每个人的特定疾病病因和遗传背景制定策略。然而，常见的疾病是 越来越多的人认识到，这是高度多基因和多效性，许多成人发病的疾病可能源于 至少部分来自早期胚胎发生期间对细胞分化的损伤。这种复杂性呈现出一种陡峭的 实现精准医学目标的挑战，并指出需要动物和细胞模型， 充分剖析分子层次和时间动态联系遗传病变的近端影响基因 调节和细胞决策，以及对疾病的远端影响。我的研究项目利用了 强大的小鼠作图群体-多样性远交（DO）和协作杂交（CC）-和 胚胎干细胞系来源于这些人群，并整合了多尺度基因组学和先进的 统计方法来解码分离遗传变异如何扰乱基因调控网络， 影响基态多能性、细胞分化轨迹和成年器官功能。本人已发表 研究已经对肝脏蛋白质组的转录后调节产生了重要的见解。项目1 在这个建议中，我将在这些以前和正在进行的努力的基础上，定义遗传变异的后果。 对肝脏中蛋白质翻译和磷酸化的定量测量。这个多维基因组 分析将提供一个前所未有的观点，遗传变异如何影响分子层次， 调节蛋白质丰度和功能的转录和转录后机制。在项目2中， 我将应用类似的系统遗传学方法来表征遗传决定因素和转录 遗传多样性小鼠基态多能性和分化潜能的动力学基础 胚胎干细胞（mESC）系。我实验室的这一新的研究重点源于一个内部的多- 研究人员合作和成功的试点项目，并已经揭示了如何分离遗传 变异影响染色质可接近性、转录本丰度和基态的维持。 项目2将扩展这一分子表征，包括定量蛋白质组学和时间单细胞 转录组学，并将整合统计建模工具，以推断分子因果链，连接遗传 个体细胞命运决定的变化。这些拟议的项目将产生重要的见解 蛋白质组的转录后调节、组织稳态和基态的维持 多能性和分化潜力，以及分离自然遗传变异对 控制这些过程的复杂的分子层次结构。未来的研究将寻求进一步联系这一详细的 用下游器官功能和细胞分化测定进行分子表征， 测试这些过程的预测模型，并最终将这些见解从鼠标中转化为信息， 细胞分化、器官稳态和人群中的疾病过程。

PROJECT SUMMARY The Precision Medicine Initiative aims to leverage population-scale genome sequencing data to tailor treatment strategies to each individual's specific disease etiology and genetic background. However, common disease is increasingly understood to be both highly polygenic and pleiotropic, and many adult onset diseases likely stem at least in part from insults to cell differentiation during early embryogenesis. This complexity presents a steep challenge for achieving the goal of precision medicine, and points to the need for animal and cell models to fully dissect the molecular hierarchy and temporal dynamics linking genetic lesions to proximal effects on gene regulation and cell decisions, and to distal effects on disease. My research program takes advantage of powerful mouse mapping populations – the Diversity Outbred (DO) and Collaborative Cross (CC) – and embryonic stem cell lines derived from these populations, and integrates multi-scale genomics and advanced statistical approaches to decode how segregating genetic variation perturbs gene regulatory networks and influences ground state pluripotency, cell differentiation trajectories, and adult organ function. My published studies have yielded important insights into post-transcriptional regulation of the liver proteome. In Project 1 of this proposal, I will build on these previous and ongoing efforts to define the consequences of genetic variation on quantitative measures of protein translation and phosphorylation in the liver. This multidimensional genomic analysis will provide an unprecedented view of how genetic variation affects the molecular hierarchy of transcriptional and post-transcriptional mechanisms that regulate protein abundance and function. In Project 2, I will apply a similar systems genetic approach to characterize the genetic determinants and transcriptional dynamics underlying ground state pluripotency and differentiation potential in genetically diverse mouse embryonic stem cell (mESC) lines. This new research focus for my laboratory stems from an internal multi- investigator collaboration and successful pilot project, and has already revealed how segregating genetic variation influences chromatin accessibility, transcript abundance, and maintenance of the ground state. Project 2 will extend this molecular characterization to include quantitative proteomics and temporal single-cell transcriptomics, and will integrate statistical modeling tools to infer the molecular causal chain that links genetic variation to the fate decisions of individual cells. Together, the proposed projects will yield important insights into post-transcriptional regulation of the proteome, tissue homeostasis, and maintenance of ground state pluripotency and differentiation potential, and the influence of segregating natural genetic variation on the complex molecular hierarchy governing these processes. Future research will seek to further link this detailed molecular characterization with downstream assays of organ function and cell differentiation to construct and test predictive models of these processes, and ultimately to translate these insights from the mouse to inform cell differentiation, organ homeostasis, and disease processes in the human population.