Genome-scale pooled CRISPR screens are powerful tools for identifying genetic dependencies across varied cellular processes. The vast majority of CRISPR screens reported to date have focused exclusively on the perturbation of protein-coding gene function. However, protein-coding genes comprise <2% of the sequence space in the human genome leaving a substantial portion of the genome uninterrogated. Noncoding regions of the genome harbor important regulatory elements (e.g. promoters, enhancers, suppressors) that influence cellular processes but high-throughput methods for evaluating their essentiality have yet to be established. Here, we describe a CRISPR-based screening approach that facilitates the functional profiling of thousands of noncoding regulatory elements in parallel. We selected the tumor suppressor p53 as a model system and designed a pooled CRISPR library targeting thousands of p53 binding sites throughout the genome. Following transduction into dCas9-KRAB-expressing cells we identified several regulatory elements that influence cell proliferation. Moreover, we uncovered multiple elements that are required for the p53-mediated DNA damage response. Surprisingly, many of these elements are located deep within intergenic regions of the genome that have no prior functional annotations. This work diversifies the applications for pooled CRISPR screens and provides a framework for future functional studies focused on noncoding regulatory elements.
Overall design: Pooled CRISPR screens targeting p53-regulated genes and p53 binding sites in human renal adenocarcinoma cells (769P)
| Accession | PRJNA521541; GEO: GSE126320 |
| Scope | Multispecies |
| Publications | Borys SM et al., "Identification of functional regulatory elements in the human genome using pooled CRISPR screens.", BMC Genomics, 2020 Jan 31;21(1):107 |
| Submission | Registration date: 8-Feb-2019 Children's Mercy Kansas City |
| Relevance | Unknown |
Project Data:
| Resource Name | Number of Links |
|---|
| Sequence data |
| SRA Experiments | 29 |
| Publications |
| PubMed | 1 |
| PMC | 1 |
| Other datasets |
| BioSample | 29 |
| GEO DataSets | 1 |