Determining the cell fate programs of mammalian retina development

确定哺乳动物视网膜发育的细胞命运程序

• 批准号: 10316121
• 负责人: Martin Tran
• 金额: $ 4.6万
• 依托单位: CALIFORNIA INSTITUTE OF TECHNOLOGY
• 依托单位国家: 美国
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-09-01 至 2025-08-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10316121
• 关键词: Address; Adult; Animal Model; Bar Codes; Biological; Biology; Birth Order; Blindness; Brain; Cell Communication; Cell Lineage; Cell division; Cells; Collaborations; Core Facility; Data Set; Development; Developmental Biology; Developmental Process; Disease; Disease Progression; Doctor of Philosophy; Educational process of instructing; Embryonic Development; Engineering; Family; Fellowship; Frequencies; Funding; Gene Expression; Gene Expression Profile; Generations; Genetic Transcription; Genome; Goals; Grant; Heritability; Heterogeneity; Image; In Situ; Individual; Investigation; Knowledge; Lead; Learning; Maps; Measurement; Methods; Modeling; Molecular; Mus; Mutation; Neurobiology; Neurons; Operative Surgical Procedures; Paper; Pattern; Pharmacology; Positioning Attribute; Procedures; Process; Publications; Recording of previous events; Regenerative Medicine; Research; Research Personnel; Resolution; Rest; Retina; Retinal Diseases; Role; Sampling; Seminal; Series; Signal Transduction; Spatial Distribution; Statistical Models; Stochastic Processes; Structure; System; Techniques; Technology; Time; Tissues; Training Programs; Trees; Work; Writing; base; career; cell type; doctoral student; experimental study; genome editing; image processing; insight; large scale data; novel; novel strategies; novel therapeutic intervention; progenitor; programs; reconstruction; regenerative; retinal progenitor cell; single molecule; single-cell RNA sequencing; statistics; student mentoring; symposium; tool; transcriptomics; visual stimulus

Project Summary/Abstract The overarching goal of this proposal is to understand how the stereotypical structure of retina forms during embryonic development. Towards this goal, this proposal seeks to develop novel molecular recording technologies that allow the reconstruction of lineage history based on endpoint measurements. This method leverages genome editing techniques to stochastically create heritable mutations within synthetic barcode arrays that accumulate edits over time. Because readout of these arrays is compatible with spatial transcriptomics technologies, these methods when combined will allow the simultaneous capturing of transcriptional cell state, lineage relationships, and spatial position of single cells within retina tissue. The resulting lineage tree datasets will then be analyzed using a novel statistical tool termed Lineage Motif Analysis, a computational approach to identify all significantly over- or under-represented cellular patterns. This approach systematically enumerates all possible arrangements of observed fates on progressively larger subtrees and then compares their frequencies to those expected in a null model based on uncorrelated cell fate between cell divisions. Lineage trees will reveal how birth-order of cell types is regulated on the clonal level and lineage motifs will reveal the extent to which lineage in the retina is stochastic or preprogrammed. Furthermore, lineage motifs represent direct insight into the “rules” that govern how the retina forms during development, and provide a way to describe how such “rules” change in different contexts like disease or pharmacological perturbation. The datasets and analysis proposed here will inform the development of new therapeutic strategies for regenerative medicine to treat retinal diseases that lead to blindness. My training program outlined here will equip me with the necessary tools and knowledge to (1) carry out the aims of this proposal and gain novel biological understanding, and (2) advance me towards my career goal of leading a research team focused on studying the fundamental principles that underlie embryonic development and disease progression. I will work with Dr. Long Cai, a pioneer in spatial transcriptomics, to learn imaging and image processing techniques, as well as Dr. Carlos Lois, an expert in neurobiology, to learn mouse manipulation and surgical procedures. Dr. Elowitz and I will meet regularly to discuss my research progress, writing plans for paper publications and grants, teaching/mentoring students, and opportunities to present my research at Caltech and national conferences. As a PhD student at Caltech, I will have access to leaders well-versed in applying quantitative approaches to study developmental biology, state-of-the-art core facilities, and cutting-edge coursework in both biology and statistics. By funding the rest of my PhD research, this fellowship will enable me to uncover the fundamental principles that underlie retina development and set me up for independence as I transition towards becoming an independent investigator in my later career.

项目总结/摘要 这项建议的首要目标是了解视网膜的常规结构如何形成 在胚胎发育期间。为了实现这一目标，本提案寻求开发新的分子记录 允许基于端点测量重建谱系历史的技术。该方法 利用基因组编辑技术在合成条形码中随机创建可遗传的突变 随着时间的推移累积编辑的数组。由于这些阵列的读出与空间分辨率兼容， 转录组学技术，这些方法结合起来将允许同时捕获 转录细胞状态、谱系关系和视网膜组织内单个细胞的空间位置。的 然后，将使用一种名为Lineage Motif的新型统计工具对生成的谱系树数据集进行分析 分析，一种计算方法，用于识别所有显著过度或不足的细胞模式。这 一种方法系统地列举了所有可能的安排，观察到的命运，逐步扩大 子树，然后将它们的频率与基于不相关单元格的空模型中的预期频率进行比较 细胞分裂之间的命运谱系树将揭示细胞类型的出生顺序是如何在克隆细胞上调节的。 水平和谱系基序将揭示视网膜中谱系是随机的或预编程的程度。 此外，谱系图案代表了对控制视网膜在发育过程中如何形成的“规则”的直接洞察。 发展，并提供一种方法来描述这种“规则”如何在不同的情况下变化，如疾病或 药理学干扰。这里提出的数据集和分析将为新的 再生医学治疗导致失明的视网膜疾病的治疗策略。 我在此概述的培训计划将使我具备必要的工具和知识，以（1）执行 这一建议的目的，并获得新的生物学理解，（2）推进我对我的职业目标 领导一个研究小组，专注于研究胚胎发育的基本原理， 发展和疾病进展。我将与空间转录组学的先驱蔡龙博士合作， 学习成像和图像处理技术，以及神经生物学专家卡洛斯洛伊斯博士学习 鼠标操作和外科手术。埃洛维茨博士和我会定期见面讨论我的研究 进展，书面出版物和赠款的写作计划，教学/指导学生，以及机会， 在加州理工学院和全国会议上展示我的研究成果。作为加州理工学院的博士生，我将有机会 领导者精通应用定量方法研究发育生物学，最先进的核心 设施，以及生物学和统计学方面的尖端课程。通过资助我剩下的博士研究， 这个奖学金将使我能够揭示视网膜发育的基本原理， 在我以后的职业生涯中，当我向成为一名独立调查员过渡时，我开始独立。