Evidence map›Paper›PMID 39554033›Full record

ArticlebioRxiv : the preprint server for biology2024

Combinatorial effector targeting (COMET) for transcriptional modulation and locus-specific biochemistry.

Caroline M Wilson, Greg C Pommier, Daniel D Richman, Nicholas Sambold, Jeffrey A Hussmann, Jonathan S Weissman, Luke A Gilbert

Abstract readPreprint
In one paragraph

Article in bioRxiv : the preprint server for biology, 2024. 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.

No citing paper in PubMed yet.

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

7 authors.

Caroline M WilsonTetrad Graduate Program, University of California, San Francisco, CA 94158, USA.ORCID 0000-0002-2553-4151
Greg C PommierDepartment of Urology, University of California, San Francisco, CA 94158, USA.
Daniel D RichmanDepartment of Computer Science, Stanford University, Stanford, CA 94305, USA.
Nicholas SamboldArc Institute, Palo Alto, CA 94304, USA.
Jeffrey A HussmannCurrent Address: Prime Medicine, Cambridge, MA 02142, USA.
Jonathan S WeissmanHoward Hughes Medical Institute, Massachusetts Institute of Technology, Cambridge, MA 02139, USA.
Luke A GilbertDepartment of Urology, University of California, San Francisco, CA 94158, USA.ORCID 0000-0001-5854-0825

Funding

Translational InformaticsP30CA082103 · NCI · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI Kate Taylor Shumate · 1999 to 2026
$209.7M
PROMINENT - UCSFOT2CA278665 · NCI · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI ALLAN BALMAIN · 2022 to 2026
$8.9M
Spatial multiomic mapping of gene function with CRISPRoffUM1HG012660 · NHGRI · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI Luke Gilbert · 2022 to 2026
$8.2M
A GENETIC INTERACTION MAP OF THE HUMAN NUCLEUSDP2CA239597 · NCI · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI GILBERT, LUKE · 2018 to 2018
$2.4M
Acquisition of Covaris E220 and Sciclone G3 systems for high throughput sequencinS10OD010786 · OD · UNIVERSITY OF CALIFORNIA AT DAVIS · PI COMAI, LUCA · 2012 to 2012
$311k
NCI NIH HHS DP2 CA239597NCI NIH HHS OT2 CA278665NCI NIH HHS P30 CA082103NHGRI NIH HHS UM1 HG012660NIH HHS S10 OD010786
6 · The paper itself

Abstract

Understanding how human gene expression is coordinately regulated by functional units of proteins across the genome remains a major biological goal. Here, we present COMET, a high-throughput screening platform for combinatorial effector targeting for the identification of transcriptional modulators. We generate libraries of combinatorial dCas9-based fusion proteins, containing two to six effector domains, allowing us to systematically investigate more than 110,000 combinations of effector proteins at endogenous human loci for their influence on transcription. Importantly, we keep full proteins or domains intact, maintaining catalytic cores and surfaces for protein-protein interactions. We observe more than 5800 significant hits that modulate transcription, we demonstrate cell type specific transcriptional modulation, and we further investigate epistatic relationships between our effector combinations. We validate unexpected combinations as synergistic or buffering, emphasizing COMET as both a method for transcriptional effector discovery, and as a functional genomics tool for identifying novel domain interactions and directing locus-specific biochemistry.

Identifiers

PMID39554033
PMCPMC11565746

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LicenceCC BY-NC-ND
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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.