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

描述（由申请人提供）：研究领域：本提案为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中获取基因组，蛋白质组学和代谢组学数据。大多数现有技术只能测量细胞群体的特性，而不能测量单个细胞的特性。秀丽隐杆线虫在模式生物中是独一无二的，因为完整的细胞谱系是已知的，使人们能够识别个体的每个细胞核。我们开发了一种自动化的细胞谱系分析仪，能够从表达GFP报告蛋白的蠕虫共聚焦图像中提取数字单细胞表达信息。该细胞分析仪可用于半高通量提取表达数据。作为原理证明，我们在363个L1期幼虫的特定细胞中生成了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。本文首先提出了一种通用的方法，通过从细胞谱系中给细胞核指定一个特定的名称，来自动地从共聚焦图像中标注细胞核。然后，我们将使用数据管道中的自动细胞谱系分析仪来分析8000张共聚焦图像中来自6个不同发育阶段的1000个基因的图像。通过在未来两年内生成单个细胞表达数据库，我们将为未来许多年创建一个丰富的新数据源。目前，共聚焦数据栈中的蠕虫图像只能手动浏览，每次只能浏览一个基因。我们的数据库将图像转换为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秀丽隐杆线虫发育和衰老的一种概念上的新方法，使用定量的分子特征而不是细胞形态学。例如，我们可以使用分子特征来确定在谱系中总共959个细胞中形成了多少种不同的细胞类型，确定发育过程中细胞何时何地开始表达不同的基因集，并寻找分子命运在细胞谱系中重复的方式，以提取指导发育模式的潜在调节模块。这个数字单细胞表达数据库将是独一无二的，因为秀丽隐杆线虫是唯一一个我们可以绘制单个细胞核身份的模式生物，而且据我们所知，我们是唯一一个能够从幼虫和成虫中提取单细胞表达信息的细胞谱系注释器的群体。

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.