Spatial multiomic mapping of gene function with CRISPRoff

项目摘要/摘要 人类生物学的一个标志性目标是定义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定义基因是如何 表达程序赋予生命所需的专门的和适应性的人类细胞功能。 我们特别感兴趣的是转录因子和表观遗传调节因子如何使细胞 特定类型的基因表达程序决定细胞在早期发育过程中的功能。 阐明单个基因如何调节转录从而对细胞进行编程 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基因干扰方法 人多细胞的活性、单细胞分子表型分析和稳健模型 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 由单一死亡的Cas9融合蛋白组成，可持久而有力地沉默基因 表情。与CRISPR突变方法不同，CRISPRoff基因沉默是有效的 在多克隆细胞群体中在靶基因mRNA和蛋白水平上编程空等位基因 而不会导致DNA损伤或DNA修复过程的不可预测性。我们是 建议优化可推广的多组体CRISPROF平台用于分子检测 人类发育的多细胞模型中单细胞分辨率的零等位基因表型。 然后，我们将使用这个CRISPRoff平台来创建单细胞分子多组图 核基因的功能跨越了空间和时间。最后，我们将评估遗传补偿和 多细胞模型中的并列对数功能冗余。我们提议的研究将有助于 演示该多组学CRISPRoff平台在表征零等位基因和 推动推广这一方法以功能性地映射所有基因的空等位基因表型 由人类基因组编码。拟议研究的结果将作为 广泛的生物医学科学家社区的基本资源和路线图，以及 让我们了解基因在人类生物学和疾病中的作用。

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.