Evidence map›Paper›PMID 36712129›Full record

ArticlebioRxiv : the preprint server for biology2023

Efficient gene knockout and genetic interactions: the IN4MER CRISPR/Cas12a multiplex knockout platform.

Nazanin Esmaeili Anvar, Chenchu Lin, Xingdi Ma, Lori L Wilson, Ryan Steger, Annabel K Sangree, Medina Colic, Sidney H Wang, John G Doench, Traver Hart

Open access · greenAbstract readPreprint
In one paragraph

Article in bioRxiv : the preprint server for biology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
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

0 citing papers in PubMed, 9 citations in OpenAlex.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

10 authors at 3 institutions in 1 country.

Nazanin Esmaeili AnvarDepartment of Bioinformatics and Computational Biology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA.
Chenchu LinDepartment of Bioinformatics and Computational Biology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA.
Xingdi MaDepartment of Bioinformatics and Computational Biology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA.
Lori L WilsonDepartment of Bioinformatics and Computational Biology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA.
Ryan StegerGenetic Perturbation Platform, Broad Institute of MIT and Harvard, Cambridge, MA, USA.
Annabel K SangreeGenetic Perturbation Platform, Broad Institute of MIT and Harvard, Cambridge, MA, USA.
Medina ColicDepartment of Bioinformatics and Computational Biology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA.
Sidney H WangCenter for Human Genetics, The Brown foundation Institute of Molecular Medicine, The University of Texas Health Science Center at Houston, Houston, TX, USA.
John G DoenchGenetic Perturbation Platform, Broad Institute of MIT and Harvard, Cambridge, MA, USA.
Traver HartDepartment of Bioinformatics and Computational Biology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA.
The University of Texas MD Anderson Cancer Center · USBroad Institute · USCenter for Human Genetics · US

Funding

Tumor Evolution and Metastasis ProgramP30CA016672 · NCI · UNIVERSITY OF TX MD ANDERSON CAN CTR · PI Fabien Delerue · 1985 to 2026
$290.8M
Identifying and targeting collateral lethal vulnerabilities in cancersU01CA275886 · NCI · UNIVERSITY OF TX MD ANDERSON CAN CTR · PI RONALD ANTHONY DEPINHO, Traver Hart · 2023 to 2026
$3.9M
High-content microscopy platform for multiplex perturbation/multiplex readout studiesR35GM130119 · NIGMS · UNIVERSITY OF TX MD ANDERSON CAN CTR · PI Traver Hart · 2018 to 2026
$3.9M
Advanced tools for HCMI model genetic perturbation and metastasis characterizationU01CA250565 · NCI · BROAD INSTITUTE, INC. · PI DOENCH, JOHN GERARD · 2020 to 2022
$2.4M
Expanding the known coding genome: identifying biological function for novel tORFsR01GM139980 · NIGMS · UNIVERSITY OF TEXAS HLTH SCI CTR HOUSTON · PI WANG, SIDNEY · 2021 to 2025
$1.5M
NCI NIH HHS P30 CA016672NCI NIH HHS U01 CA250565NCI NIH HHS U01 CA275886NIGMS NIH HHS R01 GM139980NIGMS NIH HHS R35 GM130119
6 · The paper itself

Abstract

Genetic interactions mediate the emergence of phenotype from genotype, but initial technologies for combinatorial genetic perturbation in mammalian cells suffer from inefficiency and are challenging to scale. Recent focus on paralog synthetic lethality in cancer cells offers an opportunity to evaluate different approaches and improve on the state of the art. Here we report a meta-analysis of CRISPR genetic interactions screens, identifying a candidate set of background-independent paralog synthetic lethals, and find that the Cas12a platform provides superior sensitivity and assay replicability. We demonstrate that Cas12a can independently target up to four genes from a single guide array, and we build on this knowledge by constructing a genome-scale library that expresses arrays of four guides per clone, a platform we call 'in4mer'. Our genome-scale human library, with only 49k clones, is substantially smaller than a typical CRISPR/Cas9 monogenic library while also targeting more than four thousand paralog pairs, triples, and quads. Proof of concept screens in four cell lines demonstrate discrimination of core and context-dependent essential genes similar to that of state-of-the-art CRISPR/Cas9 libraries, as well as detection of synthetic lethal and masking/buffering genetic interactions between paralogs of various family sizes, a capability not offered by any extant library. Importantly, the in4mer platform offers a fivefold reduction in the number of clones required to assay genetic interactions, dramatically improving the cost and effort required for these studies.

Identifiers

PMID36712129
PMCPMC9881895
OpenAlexW4313535506

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.