EXPLOITING PATTERNS OF GENE ESSENTIALITY IN HUMAN CELLS TO PREDICT GENE FUNCTION, SYNTHETIC LETHALITY, AND CANCER TARGETS

项目概要/摘要 必需基因是遗传学和功能基因组学的基础。系统性敲除研究 酵母定义了第一套完整的细胞增殖所必需的基因，随后的调查如何 基因的重要性在不同的环境和遗传背景中的变化揭示了以下基本原则： 功能基因组学：当一个基因在存在的情况下变得至关重要时， 另一个基因的突变或功能丧失，在同一生物过程中运作的基因往往 当在不同背景下测定时，具有相同的功能丧失表型。 CRISPR/Cas9系统对人类的适应使我们的基因组变得易于处理，在我的研究中， 博士后培训，并在我目前的职位作为助理教授在MD安德森癌症中心，我有 在CRISPR筛选方面做出了重要贡献。我领导了第一个基因剔除研究， 癌细胞中的核心和环境特异性必需基因（哈特等人，Cell，2015），并领导了 将FZD 5鉴定为RNF 43突变胰腺癌中的特异性脆弱性的努力（Steinhartet al.，Nat Med，2017）。我设计了这些研究中使用的所有CRISPR试剂，随后整合了经验数据， 在许多已发布的屏幕上创建一个更小、更高效的库（TKOv 3;可在 Addgene）。我的实验室通过开发算法来分类CRISPR信息学， 必需基因和确定药物-基因相互作用，我们已经定义了黄金标准的基准， 必需和非必需的基因已经通过了每一个主要的筛选研究。 人类细胞中的CRISPR筛选工作开始取得成果，并获得高质量的数据 从数百个细胞系中分离出来。我们寻求将我们的综合专业知识应用于综合分析和高- 通量生物学来探索关于跨细胞谱系的基因重要性的变化的问题， 基因型和环境。与酵母一样，具有类似敲除适应性特征的基因组可能 参与相同的生物过程，为破译基因功能提供了一条途径。三分之一的 蛋白质编码基因是组成型和恒定表达的，但其中一半没有被敲除 表型。许多可能是由旁系同源缓冲，潜在的合成致命的相互作用的丰富来源。核心 每个细胞都需要的必需品，当在癌症中半合子缺失时， 细胞，这可能有助于解释从第一原则的健身约束拷贝数重排， 癌细胞在全球范围内，共享的遗传脆弱性模式可能会揭示意想不到的肿瘤亚型， 这是我们数据驱动、基于网络的综合分析方法的一个关键目标。最后，我们寻求一种预测性的， 基因重要性的过程水平模型，可以解释谱系和基因型之间的变化， 进一步可用于开发简化代表性的CRISPR试剂，其能够实现高信息、低干扰、高效率的CRISPR。 成本筛选方法，更集中的生物应用。

Project summary/abstract Essential genes are fundamental to genetics and functional genomics. Systematic knockout studies in yeast defined the first complete set of genes essential for cellular proliferation, and subsequent surveys of how gene essentiality varied across environmental and genetic backgrounds revealed foundational principles of functional genomics: that “synthetic lethality” arises when one gene becomes essential in the presence of another gene's mutation or loss of function, and that genes operating in the same biological processes tend to have the same loss-of-function phenotypes when assayed across diverse backgrounds. The adaptation of the CRISPR/Cas9 system to humans has rendered our genome tractable, and in my postdoctoral training and in my current position as Assistant Professor at MD Anderson Cancer Center, I have made fundamental contributions advances in CRISPR screening. I led the first gene knockout study to identify both core and context-specific essential genes in cancer cells (Hart et al., Cell, 2015), and led the informatics effort that identified FZD5 as a specific vulnerability in RNF43-mutant pancreatic cancer (Steinhart et al., Nat Med, 2017). I designed all CRISPR reagents used in these studies, and subsequently integrated empirical data across many published screens to create a much smaller, vastly more efficient library (TKOv3; available on Addgene). My lab has advanced the state of the art in CRISPR informatics by developing algorithms to classify essential genes and to identify drug-gene interactions, and we have defined benchmarks of gold-standard essential and nonessential genes that have been adopted by every major screening study. The CRISPR screening effort in human cells is beginning to bear fruit, with high-quality data available from hundreds of cell lines. We seek to apply our combined expertise in integrative analysis and high- throughput biology to explore questions about the variation in gene essentiality across cellular lineage, genotype, and environment. As with yeast, groups of genes with similar knockout fitness profiles are likely involved in the same biological processes, providing an avenue for deciphering gene function. One-third of all protein-coding genes are constitutively and invariantly expressed, yet half of these show no knockout phenotype. Many are likely buffered by paralogs, potentially a rich source of synthetic lethal interactions. Core essentials, required in every cell, are more sensitive to perturbation when hemizygously deleted in cancer cells, which may help explain from first principles the fitness constraints on copy number rearrangement in cancer cells. Globally, patterns of shared genetic vulnerability are likely to reveal unexpected tumor subtypes, a key goal of our data-driven, network-based integrative analytical approach. Finally, we seek a predictive, process-level model of gene essentiality that can explain variations across lineage and genotype, and that further can be used to develop reduced-representation CRISPR reagents that enable high-information, low- cost screening approaches for more focused biological applications.