Multidimensional cell recording with single-cell genomics

单细胞基因组学的多维细胞记录

基本信息

批准号：
9921447
负责人：
Aaron H McKenna
金额：
$ 24.31万
依托单位：
DARTMOUTH COLLEGE
依托单位国家：
美国
项目类别：
财政年份：
2019
资助国家：
美国
起止时间：
2019-05-01 至 2022-02-28
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/9921447
关键词：
Address Adult Animal Model Animals Award Bar Codes Binding Biochemistry Biological Biological Models Brain CRISPR/Cas technology Caenorhabditis elegans Cell Differentiation process Cell Lineage Cell division Cells Cellular Assay Complex Computer software Computing Methodologies Coupled Cues DNA DNA sequencing Data Development Developmental Process Dimensions Disease Drosophila genus Drosophila melanogaster Elements Encapsulated Engineering Etiology Event Fertilization Future Gene Expression Gene Expression Profiling Genealogical Tree Generations Genetic Genome Genomics Goals Grant Health Human Individual Knowledge Life Link Malignant Neoplasms Maps Measurement Measures Memory Methods Mission Modeling Molecular Molecular Profiling Mus Mutation National Human Genome Research Institute Neuroglia Neurons Organ Organism Pattern Phase Plant Roots Population Process Recording of previous events Records Recovery Resolution Seminal Sequence Alignment Series Shapes Signal Transduction Supporting Cell System Technology Testing Time Tissues Transcript Trees Vision Work base cell type developmental disease egg experimental study flexibility fly genome editing improved in vivo insertion/deletion mutation method development new technology next generation novel strategies progenitor programs reconstruction scaffold single cell sequencing single-cell RNA sequencing stem cells transcription factor USF transcriptome zygote

项目摘要

Abstract. A zygote - a single cell - successively divides to ultimately give rise to a highly organized mass of 40 trillion cells that constitutes an adult human. This complex cell lineage tree is shaped by genetic, molecular and environmental cues. Despite enormous progress over the past one hundred and fifty years – how, when and where the decisions are made that determine the developmental lineage tree remain poorly understood for not only humans but nearly all multicellular organisms. Together with colleagues, I pioneered GESTALT (genome editing of synthetic target array for lineage tracing), a new technology based on in vivo genome editing during development that is capable of tracing cell lineage at the scale of whole animals. In our experiments to date, we have successfully captured the interrelated fates of hundreds of thousands of cells within a single organism, a critical step towards our eventual goal of globally mapping cell lineage in key model organisms. In this K99/R01 proposal, I describe how my lab will expand our initial proof-of-concept of GESTALT into a rich, flexible platform for biological recording, including molecular signals and cell lineage history in conjunction with transcriptomes, regulatory landscapes, and other measurements of single cell state. In the K99 phase of my award, I will enhance the information capacity of GESTALT system and further develop the requisite computational methods (Aim 1), and also integrate lineage recording with single cell transcriptional profiling (Aim 2). In the R00 phase of my award, I will expand GESTALT into a fully-fledged information recording platform, capable of recording key signaling events over the span of organismal development (Aim 3), and then apply this integrated platform to produce an annotated tree of brain development in Drosophila. The methods that I develop here will empower my lab, and the field at large, to answer long-standing questions about normal development as well as about the origins of diseases with complex etiologies rooted in cell lineage (e.g. cancer, developmental disorders).

摘要：受精卵（单个细胞）不断分裂，最终产生高度组织化的 40 个细胞团。构成成年人的数万亿个细胞，这个复杂的细胞谱系树是由遗传、分子和细胞因子塑造的。尽管过去一百五十年来取得了巨大的进步——如何、何时以及决定发育谱系树的决定仍然知之甚少我与同事一起开创了 GESTALT（基因组）。用于谱系追踪的合成靶阵列的编辑），一种基于体内基因组编辑的新技术在迄今为止的实验中，我们开发了能够在整个动物规模上追踪细胞谱系的技术。已成功捕获单个生物体内数十万个细胞的相互关联的命运，在这个 K99/R01 中，我们朝着全球绘制关键模型生物体细胞谱系的最终目标迈出了关键的一步。在提案中，我描述了我的实验室将如何将 GESTALT 的初始概念验证扩展为一个丰富、灵活的平台用于生物记录，包括与转录组相关的分子信号和细胞谱系历史，在我的奖项的 K99 阶段，我将加强监管景观和单细胞状态的其他测量。 GESTALT系统的信息容量并进一步开发必要的计算方法（目标1），并将谱系记录与单细胞转录分析相结合（目标 2）。获奖后，我将把 GESTALT 扩展为一个成熟的信息记录平台，能够记录关键信息整个生物发育过程中的信号事件（目标 3），然后应用这个集成平台生成一个带注释的果蝇大脑发育树，我在这里开发的方法将增强功能。我的实验室和整个领域，回答有关正常发育以及有关具有复杂病因的疾病起源于细胞谱系（例如癌症、发育障碍）。