Evidence map›Paper›PMID 29190685›Full record

ArticlePLoS biology2017

Evaluation of RNAi and CRISPR technologies by large-scale gene expression profiling in the Connectivity Map.

Ian Smith, Peyton G Greenside, Ted Natoli, David L Lahr, David Wadden, Itay Tirosh, Rajiv Narayan, David E Root, Todd R Golub, Aravind Subramanian and 1 more

Open access · goldAbstract readEvaluation Study
In one paragraph

Article in PLoS biology, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 112 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
112citing papers in PubMed, 1 pooled it
9.1field-weighted citation impact, top 1% 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

112 citing papers in PubMed, 1 synthesis or guideline pooled it, 178 citations in OpenAlex.

  1. Pooled it
  2. CRISPR/Cas Systems: Biological Basis and Genome Editing Applications.Methods in molecular biology (Clifton, N.J.) · 2027
    Review
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52 more citing papers are in PubMed but not listed here.

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

11 authors at 1 institution in 1 country.

Ian SmithBroad Institute of MIT and Harvard, Cambridge, Massachusetts, United States of America.
Peyton G GreensideBroad Institute of MIT and Harvard, Cambridge, Massachusetts, United States of America.
Ted NatoliBroad Institute of MIT and Harvard, Cambridge, Massachusetts, United States of America.
David L LahrBroad Institute of MIT and Harvard, Cambridge, Massachusetts, United States of America.
David WaddenBroad Institute of MIT and Harvard, Cambridge, Massachusetts, United States of America.
Itay TiroshBroad Institute of MIT and Harvard, Cambridge, Massachusetts, United States of America.
Rajiv NarayanBroad Institute of MIT and Harvard, Cambridge, Massachusetts, United States of America.
David E RootBroad Institute of MIT and Harvard, Cambridge, Massachusetts, United States of America.
Todd R GolubBroad Institute of MIT and Harvard, Cambridge, Massachusetts, United States of America.
Aravind SubramanianBroad Institute of MIT and Harvard, Cambridge, Massachusetts, United States of America.
John G DoenchBroad Institute of MIT and Harvard, Cambridge, Massachusetts, United States of America.ORCID http://orcid.org/0000-0002-3707-9889
Broad Institute · US

Funding

Discovering existing medicines that abrogate cellular responses to SARS CoV-2 infectionU54HL127366 · NHLBI · BROAD INSTITUTE, INC. · PI GOLUB, TODD R. · 2014 to 2020
$14.3M
Large scale gene expression analysis of cellular statesU54HG006093 · NHGRI · BROAD INSTITUTE, INC. · PI GOLUB, TODD R., SUBRAMANIAN, ARAVIND · 2010 to 2013
$9.1M
LINCS Data Coordination and Integration CenterU01HG008699 · NHGRI · BROAD INSTITUTE, INC. · PI GOLUB, TODD R., SUBRAMANIAN, ARAVIND · 2015 to 2019
$3.2M
NHGRI NIH HHS U01 HG008699NHGRI NIH HHS U54 HG006093NHLBI NIH HHS U54 HL127366
6 · The paper itself

Abstract

The application of RNA interference (RNAi) to mammalian cells has provided the means to perform phenotypic screens to determine the functions of genes. Although RNAi has revolutionized loss-of-function genetic experiments, it has been difficult to systematically assess the prevalence and consequences of off-target effects. The Connectivity Map (CMAP) represents an unprecedented resource to study the gene expression consequences of expressing short hairpin RNAs (shRNAs). Analysis of signatures for over 13,000 shRNAs applied in 9 cell lines revealed that microRNA (miRNA)-like off-target effects of RNAi are far stronger and more pervasive than generally appreciated. We show that mitigating off-target effects is feasible in these datasets via computational methodologies to produce a consensus gene signature (CGS). In addition, we compared RNAi technology to clustered regularly interspaced short palindromic repeat (CRISPR)-based knockout by analysis of 373 single guide RNAs (sgRNAs) in 6 cells lines and show that the on-target efficacies are comparable, but CRISPR technology is far less susceptible to systematic off-target effects. These results will help guide the proper use and analysis of loss-of-function reagents for the determination of gene function.

Indexed as

Clustered Regularly Interspaced Short Palindromic RepeatsGene Expression ProfilingCells, CulturedGene Expression Regulation, NeoplasticGene Regulatory NetworksGenomicsHep G2 CellsHT29 CellsHumansMCF-7 CellsRNA InterferenceRNA, Small InterferingTranscriptomeRNA, Small Interfering

Identifiers

PMID29190685
PMCPMC5726721
OpenAlexW2950461129

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.