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

点击翻译按钮获取中文摘要

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.