Computational Methods for Genome-Wide CRISPR Screens

 描述（由申请人提供）：CRISPR/Cas9系统是哺乳动物细胞基因组编辑的革命性方法。CRISPR/Cas9敲除技术以及与效应蛋白融合的dCas 9的最新发展实现了高通量成本效益的基因功能筛选，但产生了计算挑战。我们开发了一种基于模型的全基因组CRISPR/Cas9敲除分析（MAGeCK）方法，用于从基因组规模的CRISPR/Cas9筛选中调用基因和途径。MAGeCK表现出比以前的方法更好的性能，并确定强大的命中，包括新的，从几个已发表的屏幕。在这项提案中，我们的目标是开发统计和计算方法来改进MAGeCK算法，以实现CRISPR屏幕数据的质量控制，数据分析和交互式可视化。在一个统一的统计模型中，所提出的方法在gRNA水平上校正批次效应，同时估计gRNA效率和基因选择，并且在多种条件下识别差异基因和途径选择，并且考虑测序偏差和细胞倍增时间。具体而言，我们建议：目标1。为CRISPR筛选开发强大的数据标准化方法。目标二。开发统计和计算框架，从多个CRISPR筛选实验和条件中调用细胞和条件特异性必需基因和途径。目标3。开发减轻异常gRNA效应的方法，并使用蛋白质相互作用网络来增强CRISPR筛选基因调用的性能。目标4。开发用户友好的软件功能，如CRISPR筛选的质量控制、可视化、设计和分析软件。在这些研究结束时，我们将在不同的实验环境下为CRISPR筛选开发出更通用、更可靠的分析算法。这些方法可以应用于CRISPR敲除筛选、CRISPRi/a筛选、基于测序的si/shRNA筛选，并且表型可以是细胞生长、迁移、分化或GFP标记的基因表达的分选。我们提出的方法将极大地促进许多实验生物学小组采用该技术，因此他们可以在不同的实验环境下使用强大的全基因组CRISPR筛选来回答有关基因调控和药物反应的重要生物学问题。

 DESCRIPTION (provided by applicant): The CRISPR/Cas9 system is a revolutionary approach for genome editing of mammalian cells. Recent developments in CRISPR/Cas9 knockout technology as well as dCas9 fused with effector proteins enable high throughput cost-effective gene functional screens but create computational challenges. We have developed a Model-based Analysis of Genome-wide CRISPR/Cas9 Knockout (MAGeCK) method for calling genes and pathways from genome-scale CRISPR/Cas9 screens. MAGeCK demonstrates better performance than previous methods and identify robust hits, including novel ones, from several published screens. In this proposal, we aim to develop the statistical and computational methods to improve the MAGeCK algorithm to enable quality control, data analysis, and interactive visualizations of CRISPR screen data. In one unified statistical model, the proposed method corrects batch effect at gRNA level, simultaneously estimates gRNA efficiency and gene selection, and identifies differential gene and pathway selection over multiple conditions, and considers sequencing bias and cell doubling time. Specifically, we propose to: Aim 1. Develop robust data normalization methods for CRISPR screens. Aim 2. Develop the statistical and computational framework to call cell- and condition-specific essential genes and pathways from multiple CRISPR screen experiments and conditions. Aim 3. Develop methods to mitigate outlier gRNA effects and use protein interaction network to enhance the performance of CRISPR screen gene calling. Aim 4. Develop user-friendly software features, such as quality control, visualization, design and analysis software for CRISPR screens. At the conclusion of these studies, we will have developed more versatile and reliable analysis algorithms for CRISPR screens under diverse experimental settings. These methods could be applied to CRISPR knockout screens, CRISPRi/a screens, sequencing-based si/shRNA screens, and the phenotype could be cell growth, migration, differentiation, or sorting of GFP-labeled gene expression. Our proposed methods will greatly facilitate the technology adoption to many experimental biology groups, so they can use the powerful genome-wide CRISPR screens under diverse experimental settings to answer important biological questions about gene regulation and drug response.