Embryonic gene regulatory networks from spatially resolved transcriptomes

 描述(申请人提供)：系统发育生物学的一个主要目标是创建描述、模拟和预测胚胎发育过程中完整的基因调控相互作用的数据集和模型。这样的数据集和模型对于充分理解基因组信息如何转化为解剖结构是必不可少的。简化论方法已经确定了数十个基因之间的相互作用，但技术限制阻碍了在高空间分辨率和全基因组尺度上对系统范围内调控关系的阐明。该项目将解决这一挑战，并使用新技术，使单个细胞的大规模突变和全基因组表达谱能够生成基因调控网络模型。斑马鱼囊胚将被用作脊椎动物模型系统，因为它与哺乳动物胚胎相似，并且适用于强大的遗传、成像和基因组方法。该项目建立在长期合作的基础上，将Schier实验室在发育生物学、成像和遗传学方面的专业知识与Regev实验室在计算生物学、基因组学和系统生物学方面的专业知识相结合。优化的一代CRISPR/Cas9基因组编辑将用于为早期胚胎发育过程中表达的数十个转录调节因子产生突变。突变体的特征是使用一种名为Seurat的新技术生成全基因组高分辨率基因表达图谱。Seurat将单细胞RNA测序与细胞到胚胎中特定区域和细胞类型的计算映射相结合。得到的转录组图谱作为输入，使用基于聚类的方法和贝叶斯建模方法来生成基因调控网络活动的模型。通过分析转录调节器扰动下的基因表达，将在体内测试在电子计算机中预测的调节相互作用。该项目实现了PAR-15-020规定的目的，即“补充现代发育生物学的简化论重点，并提供对导致正常和异常胚胎发育的因果关系的更全面的理解”。在这个项目中发现的基因调控相互作用将有助于为编程和重新编程方法提供信息，并将确定可能涉及出生缺陷发展的候选相互作用。该项目将为发育和系统生物学家生成大量高质量的数据集和地图集，并提供一个框架来剖析其他系统中的基因调控网络。

 DESCRIPTION (provided by applicant): A major goal of systems developmental biology is to create datasets and models that describe, simulate and predict the full complement of gene regulatory interactions during embryogenesis. Such datasets and models are essential to fully understand how genomic information is translated into anatomical structure. Reductionist approaches have identified interactions among dozens of genes, but technical limitations have hindered the systems-wide elucidation of regulatory relationships at both high spatial resolution and whole-genome scale. This project will address this challenge and use novel technologies that enable large-scale mutagenesis and genome-wide expression profiling of single cells to generate gene regulatory network models. The zebrafish blastula will be used as a vertebrate model system, because of its similarities to mammalian embryos and the applicability of powerful genetic, imaging and genomic approaches. The project builds on a long-standing collaboration that combines the Schier lab's expertise in developmental biology, imaging and genetics with the Regev's lab expertise in computational biology, genomics and systems biology. Optimized one-generation CRISPR/Cas9 genome editing will be used to generate mutants for dozens of transcription regulators expressed during early embryogenesis. Mutants will be characterized by generating whole-genome high-resolution gene expression atlases using a novel technology called Seurat. Seurat combines single-cell RNA sequencing with computational mapping of cells to specific regions and cell types in the embryo. The resulting transcriptome maps serve as the inputs to generate models for gene regulatory network activity using clustering-based and Bayesian modeling approaches. Regulatory interactions predicted in silico will be tested in vivo by analyzing gene expression upon perturbation of transcription regulators. The project fulfills the stated purpose of PAR-15-020 "to complement the reductionist focus of modern developmental biology and provide a more comprehensive understanding of the causal relationships leading to normal and abnormal embryogenesis". The gene regulatory interactions discovered in this project will help inform programming and reprogramming approaches and will identify candidate interactions that might be involved in the development of birth defects. The project will generate extensive high-quality datasets and atlases for developmental and systems biologists and provide a framework to dissect gene regulatory networks in other systems.