Deciphering the gene regulatory network controlling vertebrate endodermal fates

破译控制脊椎动物内胚层命运的基因调控网络

基本信息

批准号：
8561007
负责人：
Ken W.Y. Cho
金额：
$ 62.8万
依托单位：
UNIVERSITY OF CALIFORNIA-IRVINE
依托单位国家：
美国
项目类别：
财政年份：
2013
资助国家：
美国
起止时间：
2013-07-05 至 2018-04-30
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/8561007
关键词：
Adult Binding Bioinformatics Biological Models Biology Cell Lineage ChIP-seq Collaborations Communities Complex Computer Simulation Coupled DNA DNA Binding Data Data Set Development Developmental Process Ectoderm Embryo Embryonic Development Endoderm Endoderm Cell Engineering Feeds Gene Expression Regulation Genes Genetic Transcription Genome Genomics Germ Layers Goals Graph Human Intestines Knowledge Liver Logic Lung Measurement Measures Mediating Mesoderm Methods Modeling Molecular Molecular Profiling Mus NIH Program Announcements Organ Organogenesis Outcome Output Pancreas Pathway interactions Pattern Play Production RNA Rana Regulator Genes Research Research Personnel Staging Stem cells Surveys System Testing Thyroid Gland Time Tissues Translating Tube United States National Institutes of Health Xenopus base cell type computerized tools epigenomics gastrulation genome-wide human data human disease human stem cells insight network models programs public health relevance skills stem cell biology tool transcription factor transcriptome sequencing vertebrate genome

项目摘要

DESCRIPTION (provided by applicant): Many human diseases are associated with organs originating from the embryonic gut tube, including the intestine, pancreas, liver, lungs, and thyroid. So far, only a handful of transcription factors (TFs) are known to play key roles in endoderm development, and how these TFs functionally interact in a gene regulatory network (GRN) is poorly understood and the extent to which they modulate endoderm patterning and early organogenesis is unknown. Large-scale genomic analyses are needed to generate a GRN with predictive power and to gain a systems-level understanding of the regulatory logic controlling endoderm development. We propose to utilize the experimental advantages of the Xenopus embryo coupled with several high- throughput sequencing methods to survey the global landscape of cis-regulatory modules (CRMs) active in the early Xenopus embryo and use these datasets to build and to analyze an endoderm GRN that is robust enough to be predictive when perturbed. Our modeling will provide testable hypotheses for performing double knockdowns to test the predictive quality of our GRN and to reveal the importance of multifactorial control over endodermal genes. Double knockdowns are difficult to perform in developing mammalian embryos, but are straightforward in Xenopus. This results in further elaboration of the GRN and yields deeper insights into gene regulation, which is not possible by performing additional single gene knockdown studies. We will compare our resulting GRNs in Xenopus to human data and identify critical network interactions that can be manipulated to engineer endodermal tissues from human stem cells. Our specific aims are: Aim 1: Generate genome-wide datasets of the inputs and outputs of transcriptional networks in order to build an endodermal GRN. Aim 2: Computationally integrate ChIP-seq, DNA-seq, and RNA-seq across a developmental time course to build an embryonic interactome graph. Aim 3: Model an endodermal GRN, make predictions that identify critical nodes, and test the model. This project will generate a predictive GRN model with an unprecedented systems level view of endoderm development in the vertebrate embryo. This will have a significant impact on our understanding of germ layer formation and how GRNs coordinate embryogenesis. Our GRN models will have an impact beyond the Xenopus community because researchers studying mammalian development and stem cell biology will derive testable hypotheses to drive their research programs. Similarly, the tools developed in this proposal will be applicable to building GRNs for other vertebrate and mammalian systems.

描述（由申请人提供）：许多人类疾病与源自胚胎肠管的器官有关，包括肠、胰腺、肝脏、肺和甲状腺。到目前为止，只有少数转录因子 (TF) 已知在内胚层发育中发挥关键作用，并且这些转录因子如何在基因调控网络 (GRN) 中功能性相互作用以及它们调节内胚层模式和早期发育的程度知之甚少。器官发生未知。需要大规模基因组分析来生成具有预测能力的 GRN，并获得对控制内胚层发育的调控逻辑的系统级理解。我们建议利用非洲爪蟾胚胎的实验优势以及几种高通量测序方法来调查早期非洲爪蟾胚胎中活跃的顺式调控模块（CRM）的全局景观，并使用这些数据集来构建和分析内胚层GRN它足够强大，可以在受到干扰时进行预测。我们的模型将为执行双敲低提供可检验的假设，以测试我们的 GRN 的预测质量，并揭示内胚层基因多因素控制的重要性。双重敲低在发育中的哺乳动物胚胎中很难进行，但在非洲爪蟾中却很简单。这导致了 GRN 的进一步阐述，并对基因调控产生了更深入的了解，这是通过进行额外的单基因敲低研究不可能实现的。我们将把非洲爪蟾中产生的 GRN 与人类数据进行比较，并确定可用于从人类干细胞中改造内胚层组织的关键网络相互作用。我们的具体目标是：目标 1：生成转录网络输入和输出的全基因组数据集，以构建内胚层 GRN。目标 2：在整个发育时间过程中通过计算整合 ChIP-seq、DNA-seq 和 RNA-seq，以构建胚胎相互作用组图。目标 3：对内胚层 GRN 进行建模，做出识别关键节点的预测，并测试模型。该项目将生成一个预测 GRN 模型，具有脊椎动物胚胎内胚层发育的前所未有的系统级视图。这将对我们对胚层形成以及 GRN 如何协调胚胎发生的理解产生重大影响。我们的 GRN 模型将产生超出非洲爪蟾群体的影响，因为研究哺乳动物发育和干细胞生物学的研究人员将得出可检验的假设来推动他们的研究计划。同样，本提案中开发的工具将适用于为其他脊椎动物和哺乳动物系统构建 GRN。