High-throughput technology for automated single cell expression analysis for C. e

描述(申请人提供)：研究领域：本提案针对06：使能技术和特定挑战主题HG-102技术，用于从复杂组织中的单个活细胞获取基因组、蛋白质组和代谢数据。摘要大多数现有技术只能测量一组细胞的属性，而不能测量单个细胞的属性。线虫在模式生物中是独一无二的，因为已经知道了完整的细胞谱系，使人们能够识别个体中的每个细胞核。我们已经开发了一种自动细胞谱系分析仪，能够从表达GFP报告基因的蠕虫的共聚焦图像中提取数字的单细胞表达信息。该细胞分析仪可用于以半高通量方式提取表达数据。作为原理验证，我们建立了L1期幼虫363个特定细胞中93个基因的表达谱，并能够定量分析每个基因的表达以及每个细胞的分子表达特征。这一建议是首先开发一种通用的方法来自动从共焦图像中注释细胞核，方法是从细胞谱系中为它们指定一个特定的名称。然后，我们将在数据管道中使用自动细胞谱系分析仪来分析8000张共焦图像中来自6个不同发育阶段的1000个基因的图像。通过在接下来的两年中生成单个细胞表达式数据库，我们将在未来许多年创建一个丰富的新数据源。目前，共焦数据堆栈中的蠕虫图像只能手动浏览，一次只能浏览一个基因。我们的数据库将把图像转换成适合计算分析的表达式表中的定量表达式值。单细胞表达分析是研究线虫发育和衰老的一种概念上的新方法，它使用定量分子签名而不是细胞形态。例如，我们可以使用分子签名来确定在谱系中总共959个细胞中形成了多少不同的细胞类型，确定细胞在发育过程中何时何地开始表达不同的基因集，以及寻找分子命运在细胞谱系中重复的方式，以便提取指导发育模式的潜在调控模块。这个数字化的单细胞表达数据库将是独一无二的，因为线虫是唯一可以绘制单个核身份图的模式生物，据我们所知，我们是唯一拥有细胞谱系注释器的群体，能够从幼虫和成虫中提取单细胞表达信息。

DESCRIPTION (provided by applicant): Research Area: This proposal is for 06: Enabling Technologies and specific Challenge Topic HG-102 Technologies for obtaining genomic, proteomic, and metabolomic data from individual viable cells in complex tissues. Abstract Most existing technologies can only measure the properties of a population of cells and not the properties of individual cells. C. elegans is unique among model organisms in that the complete cell lineage is known, enabling one to identify each nucleus in an individual. We have developed an automated cell lineage analyzer capable of extracting digital, single-cell expression information from confocal images of worms expressing GFP reporters. This cell analyzer can be used to extract expression data in a semi-high throughput manner. As proof-of-principle, we generated expression profiles of 93 genes in 363 specific cells from L1 stage larvae, and were able to quantitatively analyze expression of each gene as well as the molecular expression signature for each cell. This proposal is to first develop a generalized method to automatically annotate nuclei from confocal images, by assigning them a specific name from the cell lineage. We will then use the automated cell lineage analyzer in a data pipeline to analyze images from 1000 genes at six different developmental stages in 8000 confocal images. By generating a single cell expression database over the next two years, we will create a rich, new source of data for many years to come. Currently, images of worms in confocal data stacks can only be browsed manually, one gene at a time. Our database will convert images to quantitative expression values in an expression table that is suitable for computational analysis. Single cell expression analysis is a conceptually new way to study development and aging in C. elegans, using quantitative molecular signatures rather than cellular morphology. For instance, we can use the molecular signatures to determine how many different cell types are formed out of the total 959 cells in the lineage, to determine when and where during development cells begin to express different sets of genes, and to look for the way in which molecular fates are repeated in the cell lineage in order to extract the underlying regulatory modules that guide developmental pattern. This digital, single-cell expression database will be unique because C. elegans is the only model organism in which we can map the identities of individual nuclei and to our knowledge, we are the only group with a cell lineage annotator capable of extracting single cell expression information from larvae and adults.