ArticlebioRxiv : the preprint server for biology2023
Rewriting regulatory DNA to dissect and reprogram gene expression.
Gabriella E Martyn, Michael T Montgomery, Hank Jones, Katherine Guo, Benjamin R Doughty, Johannes Linder, Ziwei Chen, Kelly Cochran, Kathryn A Lawrence, Glen Munson and 6 more
Open access · greenAbstract readPreprint
In one paragraphArticle 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.
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0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
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 registryThe 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 literatureWho cites it
0 citing papers in PubMed, 19 citations in OpenAlex.
No citing paper in PubMed yet.
4 · The recordCorrections and comments
5 · Who and what moneyAuthors and funding
16 authors at 3 institutions in 1 country.
Gabriella E MartynDepartment of Genetics, Stanford University School of Medicine, Stanford, CA, USA.ORCID 0000-0001-5024-428X Michael T MontgomeryDepartment of Genetics, Stanford University School of Medicine, Stanford, CA, USA.ORCID 0000-0002-6748-2329 Katherine GuoDepartment of Genetics, Stanford University School of Medicine, Stanford, CA, USA.
Benjamin R DoughtyDepartment of Genetics, Stanford University School of Medicine, Stanford, CA, USA.
Ziwei ChenDepartment of Computer Science, Stanford University, Stanford, CA, USA.
Kelly CochranDepartment of Computer Science, Stanford University, Stanford, CA, USA.
Kathryn A LawrenceDepartment of Genetics, Stanford University School of Medicine, Stanford, CA, USA.
Glen MunsonThe Novo Nordisk Foundation Center for Genomic Mechanisms of Disease, Broad Institute of MIT and Harvard, Cambridge, MA, USA.
Anusri PampariDepartment of Computer Science, Stanford University, Stanford, CA, USA.
Eric S LanderBroad Institute of MIT and Harvard, Cambridge, MA, USA.
Stanford University · USBroad Institute · USEnzo Life Sciences (United States) · US
Funding
INSTITUTIONAL TRAINING GRANT IN GENOME SCIENCET32HG000044 · NHGRI · STANFORD UNIVERSITY · PI MICHAEL P. SNYDER · 1995 to 2026
$32.2MStanford Center for Connecting DNA Variants to Function and PhenotypeUM1HG011972 · NHGRI · STANFORD UNIVERSITY · PI JESSE M ENGREITZ, THOMAS QUERTERMOUS · 2021 to 2026
$10.5MPredicting context-specific molecular and phenotypic effects of genetic variation through the lens of the cis-regulatory codeU01HG012069 · NHGRI · STANFORD UNIVERSITY · PI Anshul Kundaje · 2021 to 2026
$3.9MSystematic mapping and prediction of gene-enhancer connectionsR00HG009917 · NHGRI · STANFORD UNIVERSITY · PI ENGREITZ, JESSE M · 2020 to 2022
$796kSystematic mapping and prediction of gene-enhancer connectionsK99HG009917 · NHGRI · BROAD INSTITUTE, INC. · PI ENGREITZ, JESSE M · 2018 to 2019
$65kNHGRI NIH HHS K99 HG009917NHGRI NIH HHS R00 HG009917NHGRI NIH HHS T32 HG000044NHGRI NIH HHS U01 HG012069NHGRI NIH HHS UM1 HG011972
6 · The paper itselfAbstract
Regulatory DNA sequences within enhancers and promoters bind transcription factors to encode cell type-specific patterns of gene expression. However, the regulatory effects and programmability of such DNA sequences remain difficult to map or predict because we have lacked scalable methods to precisely edit regulatory DNA and quantify the effects in an endogenous genomic context. Here we present an approach to measure the quantitative effects of hundreds of designed DNA sequence variants on gene expression, by combining pooled CRISPR prime editing with RNA fluorescence
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PMID38187584
PMCPMC10769263
OpenAlexW4390052751
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