Modeling Functional Elements using CRISPR Screening

NIH RePORTER · NIH · R01 · $446,250 · view on reporter.nih.gov ↗

Abstract

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.

Key facts

NIH application ID
10404656
Project number
5R01HG010753-04
Recipient
CHILDREN'S RESEARCH INSTITUTE
Principal Investigator
Wei Li
Activity code
R01
Funding institute
NIH
Fiscal year
2022
Award amount
$446,250
Award type
5
Project period
2019-08-08 → 2024-05-31