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Deciphering the regulatory code that specifies different cell fates in development using single cell genomics

使用单细胞基因组学破译指定发育过程中不同细胞命运的监管代码

基本信息

批准号：
10579182
负责人：
Antonio J Giraldez
金额：
$ 56.04万
依托单位：
YALE UNIVERSITY
依托单位国家：
美国
项目类别：
财政年份：
2020
资助国家：
美国
起止时间：
2020-05-07 至 2025-02-28
项目状态：
未结题

来源：
https://reporter.nih.gov/project-details/10579182
关键词：
ATAC-seq Address Affect Architecture Binding Cell Differentiation process Cell Lineage Cells Chromatin Code Collaborations Complex Computing Methodologies DNA Data Data Set Development Disease Embryo Embryonic Development Engineering Epigenetic Process Etiology Evolution Fertilization Foundations Gene Expression Gene Expression Profile Genes Genetic Genetic Transcription Genome Genomics Goals Human Human Development In Vitro Individual Learning Logic Maps Mathematics Mediating Molecular Mutate Outcome Regenerative Medicine Regulator Genes Repression Shapes Signal Transduction Specific qualifier value System Testing Time Totipotent Vertebrates Work cell fate specification cell type combinatorial computer framework developmental disease gene regulatory network in vivo loss of function mutant novel posttranscriptional predictive modeling programs recruit segregation single cell sequencing single-cell RNA sequencing transcription factor vertebrate embryos

项目摘要

Summary The vertebrate embryo contains hundreds of functionally diverse cell types, however we lack a complete understanding of the regulatory code that specifies each cell type and how disruptions in this code affect relationships between lineages. Here, we propose two aims to dissect the accessible regions of the chromatin, the regulatory motifs and the putative transcription factors that mediate the specification of multiple cell types during embryogenesis. First, (Aim 1), we will utilize single cell ATAC-seq and scRNA-seq to uncover the dynamics of chromatin accessibility and the transcriptional profiles that define discrete cell types during early development. We will define the regulatory motifs in accessible regions of the chromatin that are preferentially engaged in different cell types. Second (Aim 2), we will use manifold learning approaches to define co- regulated gene modules and apply a regulatory network inference framework for scRNA-seq and scATAC-seq data, and test the regulatory interactions by mutating key pioneer factors and investigate how they cooperate with other TFs to regulate chromatin accessibility and cell differentiation during development. This project will generate extensive, high-quality datasets as well as novel computational methods to enable quantitative and predictive models of embryonic development with the goal to decipher the gene regulatory network specifying cellular identity during development. Given that early development is conserved across vertebrate species, our findings have the potential to inform human development, and lay the foundation to investigate the etiologies of human developmental disorders and to engineer novel cell types and lineages in vitro for regenerative medicine.

总结