Evidence map›Paper›PMID 32005150›Full record

ArticleBMC genomics2020

Identification of functional regulatory elements in the human genome using pooled CRISPR screens.

Samantha M Borys, Scott T Younger

Open access · goldAbstract read
In one paragraph

Article in BMC genomics, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed
1.3field-weighted citation impact, top 20% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

11 citing papers in PubMed, 73 citations in OpenAlex.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors at 1 institution in 1 country.

Samantha M BorysBroad Institute of MIT and Harvard, Cambridge, MA, 02142, USA.
Scott T YoungerBroad Institute of MIT and Harvard, Cambridge, MA, 02142, USA. styounger@cmh.edu.ORCID http://orcid.org/0000-0002-6237-445X
Broad Institute · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundGenome-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, silencers) that influence cellular processes but high-throughput methods for evaluating their essentiality have yet to be established.

resultsHere, 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.

conclusionsThis work diversifies the applications for pooled CRISPR screens and provides a framework for future functional studies focused on noncoding regulatory elements.

Indexed as

CRISPR-Cas SystemsBinding SitesCell Line, TumorCell ProliferationGene Knockout TechniquesGenome, HumanHumansNeoplasmsRegulatory Elements, TranscriptionalTumor Suppressor Protein p53TP53 protein, humanTumor Suppressor Protein p53CRISPRCRISPR screenEnhancerp53Regulatory element

Identifiers

PMID32005150
PMCPMC6995077
OpenAlexW3013709003

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.