Deciphering the gene regulatory network controlling vertebrate endodermal fates

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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.