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Modeling Functional Elements using CRISPR Screening

使用 CRISPR 筛选对功能元件进行建模

基本信息

批准号：
10227147
负责人：
Wei Li
金额：
$ 44.63万
依托单位：
CHILDREN'S RESEARCH INSTITUTE
依托单位国家：
美国
项目类别：
财政年份：
2019
资助国家：
美国
起止时间：
2019-08-08 至 2024-05-31
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/10227147
关键词：
Address Affect Algorithm Design Algorithmic Analysis Algorithms Animal Model Biological CRISPR screen CRISPR/Cas technology Cell Line Cells Clustered Regularly Interspaced Short Palindromic Repeats Code Computational algorithm Computer Analysis Computer Models Computing Methodologies Data Development Disease Elements Enhancers Essential Genes Genes Genetic Genetic Screening Genetic study Genome engineering Genomics Genotype Goals Guide RNA Human Genome Institutes Knock-out Libraries Methodology Methods Modeling Paper Pathway Analysis Pathway interactions Phenotype Physiology Principal Investigator Proteins Public Domains Publishing Quality Control RNA Interference Research Series Software Design Specificity Statistical Methods Statistical Models Supervision System Techniques Technology Time Untranslated RNA Visualization Weight Work base biological systems cell type cohort cost effective design genetic predictors genome wide screen genome-wide graduate student improved innovation interest knock-down knockout gene multidimensional data novel protein function screening transcriptome sequencing

项目摘要

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.

项目总结