Modeling Functional Elements using CRISPR Screening

项目摘要 全基因组CRISPR/Cas9筛选技术(CRISPR筛选)的最新进展 以快速和高通量的方式识别与感兴趣的表型相关的功能基因。 除了编码蛋白质的基因外，新的筛选技术还使非编码基因的功能询问成为可能 编码元素和遗传交互作用。我们开发了一系列计算算法和 CRISPR屏幕的设计、质量控制、分析、可视化和解释软件。 其中，MAGeCK/MAGeCK-VISPR算法被广泛用于分析 筛选数据。 在这项建议中，我们的目标是开发统计和计算模型来改善泛函 蛋白质编码基因的询问，并将其扩展到研究非编码元件和遗传 互动。具体地说，我们提出：目的1.改进CRISPR中的功能基因识别 屏幕，从集成来自不同背景的筛选数据到在 途径方式；目的2.开发非编码CRISPR函数的设计和分析算法 研究并预测各种细胞类型的功能增强剂。目的3.研究遗传交互作用 从CRISPR筛选针对基因对，通过对这种新型筛选数据进行建模。 在这些研究的结论中，我们将为CRISPR开发几种分析算法 各种类型的筛选，促进基因、非编码元件和基因的功能研究 互动。这些算法将使实验生物学家的回答变得容易和方便 关于蛋白质编码基因、非编码元件和基因功能的重要生物学问题 基因的相互作用。

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.