Article in Nature communications, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
0numbers the graph read from it
0cells of the map it votes in
2citing 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.
Gregory W GoldbergInstitute for Systems Genetics and Department of Biochemistry and Molecular Pharmacology, NYU Langone Health, New York, NY, USA. Gregory.Goldberg@nyulangone.org.ORCID 0000-0002-5022-9976
Manjunatha KogenaruInstitute for Systems Genetics and Department of Biochemistry and Molecular Pharmacology, NYU Langone Health, New York, NY, USA.ORCID 0000-0001-6570-7857
Sarah KeeganInstitute for Systems Genetics and Department of Biochemistry and Molecular Pharmacology, NYU Langone Health, New York, NY, USA.
Max A B HaaseInstitute for Systems Genetics and Department of Biochemistry and Molecular Pharmacology, NYU Langone Health, New York, NY, USA.
Larisa KagermazovaInstitute for Systems Genetics and Department of Biochemistry and Molecular Pharmacology, NYU Langone Health, New York, NY, USA.ORCID 0009-0004-7494-284X
Mauricio A AriasCourant Institute of Mathematical Sciences, New York University, New York, NY, USA.
Kenenna OnyebekeInstitute for Systems Genetics and Department of Biochemistry and Molecular Pharmacology, NYU Langone Health, New York, NY, USA.
Samantha AdamsInstitute for Systems Genetics and Department of Biochemistry and Molecular Pharmacology, NYU Langone Health, New York, NY, USA.
Daniel K BeyerInstitute for Systems Genetics and Department of Biochemistry and Molecular Pharmacology, NYU Langone Health, New York, NY, USA.
David FenyöInstitute for Systems Genetics and Department of Biochemistry and Molecular Pharmacology, NYU Langone Health, New York, NY, USA.
Marcus B NoyesInstitute for Systems Genetics and Department of Biochemistry and Molecular Pharmacology, NYU Langone Health, New York, NY, USA. Marcus.Noyes@nyulangone.org.ORCID 0000-0002-3065-1096
Jef D BoekeInstitute for Systems Genetics and Department of Biochemistry and Molecular Pharmacology, NYU Langone Health, New York, NY, USA. Jef.Boeke@nyulangone.org.ORCID 0000-0001-5322-4946
Funding
Supplement for Center for Synthetic Regulatory Genomics: Building CACNA1C alleles associated with Neuropsychiatric DisordersRM1HG009491 · NHGRI · NEW YORK UNIVERSITY SCHOOL OF MEDICINE · PI Jef D BOEKE · 2018 to 2026
$20.9M
The systematic definition of human protein-peptide interactions, their variants, and the microbiomeR01GM133936 · NIGMS · NEW YORK UNIVERSITY SCHOOL OF MEDICINE · PI NOYES, MARCUS BLAINE · 2019 to 2022
$2.1M
Defining the multi-dimensional code of zinc finger specificity-Resubmission-1R01GM118851 · NIGMS · NEW YORK UNIVERSITY SCHOOL OF MEDICINE · PI NOYES, MARCUS BLAINE · 2017 to 2021
$2.0M
Streamlining temperate phage engineering to facilitate precise in situ manipulation of gut microbiotaK99GM147604 · NIGMS · NEW YORK UNIVERSITY SCHOOL OF MEDICINE · PI GOLDBERG, GREGORY WILLIAM · 2022 to 2023
$225k
Exploiting simultaneous positive and negative selection to advance directed evolution of orthogonal RNA-guided nucleasesF32GM137482 · NIGMS · NEW YORK UNIVERSITY SCHOOL OF MEDICINE · PI GOLDBERG, GREGORY WILLIAM · 2020 to 2021
$134k
NHGRI NIH HHS RM1 HG009491NIGMS NIH HHS F32 GM137482NIGMS NIH HHS K99 GM147604NIGMS NIH HHS R01 GM118851NIGMS NIH HHS R01 GM133936U.S. Department of Health & Human Services | NIH | National Human Genome Research Institute (NHGRI) RM1HG009491U.S. Department of Health & Human Services | NIH | National Institute of General Medical Sciences (NIGMS) F32GM137482U.S. Department of Health & Human Services | NIH | National Institute of General Medical Sciences (NIGMS) K99GM147604U.S. Department of Health & Human Services | NIH | National Institute of General Medical Sciences (NIGMS) R01GM118851
6 · The paper itself
Abstract
DNA targeting Class 2 CRISPR-Cas effector nucleases, including the well-studied Cas9 proteins, evolved protospacer-adjacent motif (PAM) and guide RNA interactions that sequentially license their binding and cleavage activities at protospacer target sites. Both interactions are nucleic acid sequence specific but function constitutively; thus, they provide intrinsic spatial control over DNA targeting activities but naturally lack temporal control. Here we show that engineered Cas9 fusion proteins which bind to nascent RNAs near a protospacer can facilitate spatiotemporal coupling between transcription and DNA targeting at that protospacer: Transcription-associated Cas9 Targeting (TraCT). Engineered TraCT is enabled in eukaryotic yeast or human cells when suboptimal PAM interactions limit basal activity and when one or more nascent RNA substrates are still tethered to the actively transcribed target DNA in cis. Using yeast, we further show that this phenomenon can be applied for selective editing at one of two identical targets in distinct gene loci, or, in diploid allelic loci that are differentially transcribed. Our work demonstrates that temporal control over Cas9's targeting activity at specific DNA sites may be engineered without modifying Cas9's core domains and guide RNA components or their expression levels. More broadly, it establishes co-transcriptional RNA binding as a cis-acting mechanism that can conditionally stimulate CRISPR-Cas DNA targeting in eukaryotic cells.
Indexed as
CRISPR-Associated Protein 9CRISPR-Cas SystemsRNA, Guide, CRISPR-Cas SystemsSaccharomyces cerevisiaeTranscription, GeneticDNAEukaryotic CellsGene EditingGenetic EngineeringHEK293 CellsHumansCRISPR-Associated Protein 9DNARNA, Guide, CRISPR-Cas Systems
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.
Engineered transcription-associated Cas9 targeting in eukaryotic cells. · full record | OpenQuestion