Deciphering the gene regulatory network controlling vertebrate endodermal fates

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、肺和甲状腺。到目前为止，只有少数转录因子（tf）在内胚层发育中发挥关键作用，这些tf如何在基因调控网络（GRN）中发挥功能相互作用尚不清楚，它们在多大程度上调节内胚层模式和早期器官发生尚不清楚。需要大规模的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。我们建议利用爪蟾胚胎的实验优势，结合几种高通量测序方法，调查在早期爪蟾胚胎中活跃的顺式调控模块（CRMs）的全球格局，并利用这些数据集构建和分析内胚层GRN，该GRN具有足够的鲁棒性，可以在受到干扰时进行预测。我们的模型将为执行双敲除提供可测试的假设，以测试我们的GRN的预测质量，并揭示对内胚层基因的多因子控制的重要性。双敲除在哺乳动物胚胎发育中很难实现，但在非洲爪蟾中很容易实现。这导致了对GRN的进一步阐述，并对基因调控产生了更深入的了解，这是不可能通过进行额外的单基因敲低研究来实现的。我们将把我们在非洲爪蟾中得到的grn与人类数据进行比较，并确定可以操纵的关键网络相互作用，以从人类干细胞中设计内胚层组织。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。目的2：通过计算整合ChIP-seq、DNA-seq和RNA-seq，构建胚胎相互作用组图。目标3：建立一个内胚层GRN模型，做出预测，识别关键节点，并测试模型。该项目将产生一个预测GRN模型，具有前所未有的脊椎动物胚胎内胚层发育的系统水平视图。这将对我们理解胚层形成和grn如何协调胚胎发生产生重大影响。我们的GRN模型的影响将超越爪蟾群体，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测试的假设来推动他们的研究项目。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。

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.