Modeling Functional Elements using CRISPR Screening

项目摘要 全基因组CRISPR/Cas9筛选技术（“CRISPR筛选”）的最新发展 以快速和高通量的方式鉴定与感兴趣的表型相关的功能基因。 除了蛋白质编码基因，新的筛选技术使非蛋白质的功能询问成为可能。 编码元件和遗传相互作用。我们已经开发了一系列的计算算法， 用于CRISPR筛选的设计、质量控制、分析、可视化和解释的软件。 其中，MAGeCK/MAGeCK-VISPR算法已被广泛用于分析 筛选数据。 在这个建议中，我们的目标是开发统计和计算模型，以提高功能 询问蛋白质编码基因，并将其扩展到研究非编码元件和遗传 交互.具体而言，我们建议：目标1。通过CRISPR改进功能基因鉴定 筛选，从整合筛选数据从异质背景和查看数据在一个 途径方式;目标2。开发非编码CRISPR功能的设计和分析算法 研究，并预测各种细胞类型的功能增强子。目标3。研究遗传相互作用 从CRISPR筛选靶向基因对，通过建模这种新型的筛选数据。 在这些研究结束时，我们将开发出几种CRISPR分析算法。 各种类型的筛选，促进基因，非编码元件和遗传学的功能研究 交互.这些算法将变得简单和方便实验生物学家回答 关于蛋白质编码基因、非编码元件和 基因相互作用

Project Summary The recent development of genome-wide CRISPR/Cas9 screening technology (“CRISPR screens”) identifies functional genes associated with phenotype of interest in a fast and high-throughput manner. Besides protein-coding genes, novel screening techniques enable the functional interrogation of non- coding elements and genetic interactions. We have developed a series of computational algorithms and softwares for the design, quality control, analysis, visualization and interpretation of CRISPR screens. Among these, the MAGeCK/MAGeCK-VISPR algorithms have been widely used for analyzing screening data. In this proposal, we aim to develop the statistical and computational models to improve the functional interrogation of protein-coding genes, and to extend it to study non-coding elements and genetic interactions. Specifically, we propose to: Aim 1. Improve functional gene identification from CRISPR screens, from integrating screening data from heterogenous background and viewing the data in a pathway manner; Aim 2. Develop the design and analysis algorithms for non-coding CRISPR functional studies, and predict functional enhancers across various cell types. Aim 3. Study genetic interactions from CRISPR screens targeting gene pairs, by modeling this novel type of screening data. At the conclusion of these studies, we will have developed several analysis algorithms for CRISPR screens of various types, facilitating the functional studies of genes, non-coding elements and genetic interactions. These algorithms will be made easy and convenient for experimental biologists to answer important biological questions about the functions of protein-coding genes, non-coding elements and genetic interactions.