Spatial multiomic mapping of gene function with CRISPRoff

项目总结/摘要 人类生物学的一个标志性目标是确定基因和表型之间的关系。 绘制人类细胞中每个基因的功能图谱将使我们能够开始确定基因是如何在细胞中表达的。 表达程序赋予生命所需的特化和适应性人类细胞功能。 我们特别感兴趣的是转录因子和表观遗传调节因子如何调控细胞 类型特异性基因表达程序在早期发育期间决定细胞功能。 阐明单个基因如何发挥作用来调节转录，从而编程细胞 表型将改变我们对人类生物学、发育和疾病的理解。 对基因功能的机械理解需要可扩展的方法来干扰基因 活性、单细胞分子表型分析和人类多细胞免疫的稳健模型 生物学我们最近开发了CRISPRoff-一种可编程的表观遗传记忆写入器 由一个单一的死亡Cas9融合蛋白组成， 表情与CRISPR诱变方法不同，CRISPRoff基因沉默有效地 在多克隆细胞群体中在靶基因mRNA和蛋白质水平上编程无效等位基因 而不诱导DNA损伤或DNA修复过程的不可预测性。我们 建议优化一个可推广的多组CRISPRoff平台， 在人类发育的多细胞模型中以单细胞分辨率对无效等位基因进行表型分型。 然后，我们将使用这个CRISPRoff平台来创建单细胞分子多组学图谱， 核基因在空间和时间上的功能最后，我们将评估遗传补偿， 在多细胞模型中的paramentary功能冗余。我们提出的研究将有助于 证明了这种多组学CRISPRoff平台用于表征无效等位基因的实用性， 激发扩展该方法以功能性地映射所有基因的无效等位基因表型 由人类基因组编码。这项研究的结果将作为 为广大生物医学科学家提供基本资源和路线图， 让我们了解基因在人类生物学和疾病中的功能。

PROJECT SUMMARY / ABSTRACT A hallmark goal in human biology is to define the relationship between genes and phenotypes. Mapping the function of every gene in human cells will enable us to begin to define how gene expression programs impart specialized and adaptive human cellular functions required for life. We are especially interested in how transcription factors and epigenetic regulators enact cell type specific gene expression programs to dictate cell function during early development. Elucidating how individual genes function to regulate transcription and thus to program cell phenotypes will transform our understanding of human biology, development and disease. A mechanistic understanding of gene function requires scalable approaches for perturbing gene activity, single cell molecular phenotyping assays and robust models of human multicellular biology. We recently developed CRISPRoff— a programmable epigenetic memory writer consisting of a single dead Cas9 fusion protein that durably and robustly silences gene expression. Unlike CRISPR mutagenesis approaches, CRISPRoff gene silencing effectively programs null alleles at the level of target gene mRNA and protein in polyclonal cell populations without induction of DNA damage or the unpredictability of DNA repair processes. We are proposing to optimize a generalizable multiomic CRISPRoff platform for molecularly phenotyping null alleles at single-cell resolution in multicellular models of human development. We will then use this CRISPRoff platform to create single-cell molecular multiomic maps of nuclear gene function across space and time. Lastly, we will evaluate genetic compensation and paralog functional redundancy in multicellular models. Our proposed research will serve to demonstrate the utility of this multiomics CRISPRoff platform for characterizing null alleles and motivate extending this approach to functionally map null allele phenotypes for all genes encoded by the human genome. The results of the proposed research will serve as a fundamental resource and roadmap for a broad community of biomedical scientists and greatly inform our understanding of gene function in human biology and disease.