Modeling Functional Elements using CRISPR Screening

项目概要 全基因组CRISPR/Cas9筛选技术（“CRISPR筛选”）的最新进展 以快速、高通量的方式识别与感兴趣的表型相关的功能基因。 除了蛋白质编码基因外，新颖的筛选技术还可以对非蛋白质编码基因进行功能性询问。 编码元件和遗传相互作用。我们开发了一系列的计算算法和 用于 CRISPR 屏幕的设计、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。 在本提案中，我们的目标是开发统计和计算模型以改进功能 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 互动。具体来说，我们建议： 目标 1. 改进 CRISPR 的功能基因鉴定 屏幕，从整合来自异质背景的筛选数据并在一个 路径方式；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剂。目标 3. 研究遗传相互作用 通过对这种新型筛选数据进行建模，从针对基因对的 CRISPR 筛选中获得结果。 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、非编码元件和遗传的功能研究 互动。这些算法将使实验生物学家能够简单方便地回答 关于蛋白质编码基因、非编码元件和蛋白质功能的重要生物学问题 遗传相互作用。

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.