Large dataset enables prediction of repair after CRISPR-Cas9 editing in primary T cells.

CRISPR-Cas Systems Cell Line Gene Editing / methods Gene Expression Regulation Genome Genomics Humans Induced Pluripotent Stem Cells / physiology RNA, Guide, Kinetoplastida / genetics T-Lymphocytes / physiology

Journal

Nature biotechnology
ISSN: 1546-1696
Titre abrégé: Nat Biotechnol
Pays: United States
ID NLM: 9604648

Informations de publication

Date de publication:
09 2019
Historique:
received: 19 10 2018
accepted: 27 06 2019
pubmed: 31 7 2019
medline: 7 11 2019
entrez: 31 7 2019
Statut: ppublish

Résumé

Understanding of repair outcomes after Cas9-induced DNA cleavage is still limited, especially in primary human cells. We sequence repair outcomes at 1,656 on-target genomic sites in primary human T cells and use these data to train a machine learning model, which we have called CRISPR Repair Outcome (SPROUT). SPROUT accurately predicts the length, probability and sequence of nucleotide insertions and deletions, and will facilitate design of SpCas9 guide RNAs in therapeutically important primary human cells.

Identifiants

DOI: 10.1038/s41587-019-0203-2 PMID: 31359007 PMC: PMC7388783
pubmed: 31359007
doi: 10.1038/s41587-019-0203-2
pii: 10.1038/s41587-019-0203-2
pmc: PMC7388783
mid: NIHMS1577182
doi:

Substances chimiques

RNA, Guide 0

Types de publication

Journal Article Research Support, N.I.H., Extramural Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Pagination

1034-1037

Subventions

Organisme : NIA NIH HHS
ID : P30 AG059307
Pays : United States
Organisme : NIAID NIH HHS
ID : U19 AI135990
Pays : United States
Organisme : NIAID NIH HHS
ID : K22 AI136691
Pays : United States
Organisme : NHGRI NIH HHS
ID : R01 HG008164
Pays : United States
Organisme : NIGMS NIH HHS
ID : P50 GM082250
Pays : United States
Organisme : NCI NIH HHS
ID : U54 CA209891
Pays : United States
Organisme : NIAID NIH HHS
ID : P50 AI150476
Pays : United States
Organisme : NIDA NIH HHS
ID : DP2 DA042423
Pays : United States

Références

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Auteurs

Ryan T Leenay (RT)

Chan-Zuckerberg Biohub, San Francisco, CA, USA.

Amirali Aghazadeh (A)

Department of Electrical Engineering, Stanford University, Stanford, CA, USA.
ORCID: 0000-0003-0223-0873

Joseph Hiatt (J)

Biomedical Sciences Graduate Program, University of California, San Francisco, San Francisco, CA, USA.
Department of Microbiology and Immunology, University of California, San Francisco, San Francisco, CA, USA.
Diabetes Center, University of California, San Francisco, San Francisco, CA, USA.
Medical Scientist Training Program, University of California, San Francisco, San Francisco, CA, USA.
J. David Gladstone Institutes, San Francisco, CA, USA.
ORCID: 0000-0002-8015-9614

David Tse (D)

Department of Electrical Engineering, Stanford University, Stanford, CA, USA.

Theodore L Roth (TL)

Department of Microbiology and Immunology, University of California, San Francisco, San Francisco, CA, USA.

Ryan Apathy (R)

Department of Microbiology and Immunology, University of California, San Francisco, San Francisco, CA, USA.

Eric Shifrut (E)

Department of Microbiology and Immunology, University of California, San Francisco, San Francisco, CA, USA.

Judd F Hultquist (JF)

J. David Gladstone Institutes, San Francisco, CA, USA.
Department of Cellular and Molecular Pharmacology, University of California, San Francisco, San Francisco, CA, USA.
Quantitative Biosciences Institute (QBI), University of California, San Francisco, San Francisco, CA, USA.
Division of Infectious Diseases, Northwestern University Feinberg School of Medicine, Chicago, IL, USA.

Nevan Krogan (N)

J. David Gladstone Institutes, San Francisco, CA, USA.
Department of Cellular and Molecular Pharmacology, University of California, San Francisco, San Francisco, CA, USA.
Quantitative Biosciences Institute (QBI), University of California, San Francisco, San Francisco, CA, USA.

Zhenqin Wu (Z)

Department of Chemistry, Stanford University, Stanford, CA, USA.
ORCID: 0000-0002-0148-7055

Giana Cirolia (G)

Chan-Zuckerberg Biohub, San Francisco, CA, USA.

Hera Canaj (H)

Chan-Zuckerberg Biohub, San Francisco, CA, USA.

Manuel D Leonetti (MD)

Chan-Zuckerberg Biohub, San Francisco, CA, USA.
ORCID: 0000-0002-4881-405X

Alexander Marson (A)

Chan-Zuckerberg Biohub, San Francisco, CA, USA. alexander.marson@ucsf.edu.
Department of Microbiology and Immunology, University of California, San Francisco, San Francisco, CA, USA. alexander.marson@ucsf.edu.
Diabetes Center, University of California, San Francisco, San Francisco, CA, USA. alexander.marson@ucsf.edu.
Innovative Genomics Institute, University of California, Berkeley, Berkeley, CA, USA. alexander.marson@ucsf.edu.
Department of Medicine, University of California, San Francisco, San Francisco, CA, USA. alexander.marson@ucsf.edu.
Parker Institute for Cancer Immunotherapy, San Francisco, CA, USA. alexander.marson@ucsf.edu.
ORCID: 0000-0002-2734-5776

Andrew P May (AP)

Chan-Zuckerberg Biohub, San Francisco, CA, USA. apmay1@gmail.com.
Sana Biotechnology, South San Francisco, CA, USA. apmay1@gmail.com.
ORCID: 0000-0003-3567-3435

James Zou (J)

Chan-Zuckerberg Biohub, San Francisco, CA, USA. jamesz@stanford.edu.
Department of Electrical Engineering, Stanford University, Stanford, CA, USA. jamesz@stanford.edu.
Department of Biomedical Data Science, Stanford University, Stanford, CA, USA. jamesz@stanford.edu.
ORCID: 0000-0001-8880-4764

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Classifications MeSH

questionsmedicales.fr › Phénomènes génétiques › Régulation de l'expression des gènes › Épigenèse génétique › Extinction de l'expression des gènes › Systèmes CRISPR-Cas › Large dataset enables prediction of repair...
questionsmedicales.fr › Cellules › Cellules cultivées › Lignée cellulaire › Large dataset enables prediction of repair...
questionsmedicales.fr › Techniques d'investigation › Techniques génétiques › Génie génétique › Édition de gène › Large dataset enables prediction of repair...
questionsmedicales.fr › Phénomènes génétiques › Régulation de l'expression des gènes › Large dataset enables prediction of repair...
questionsmedicales.fr › Phénomènes génétiques › Structures génétiques › Génome › Large dataset enables prediction of repair...
questionsmedicales.fr › Disciplines des sciences naturelles › Disciplines des sciences biologiques › Biologie › Génétique › Génomique › Large dataset enables prediction of repair...
questionsmedicales.fr › Eucaryotes › Animaux › Chordés › Vertébrés › Mammifères › Eutheria › Primates › Haplorhini › Catarrhini › Hominidae › Humains › Large dataset enables prediction of repair...
questionsmedicales.fr › Cellules › Cellules souches › Cellules souches pluripotentes › Cellules souches pluripotentes induites › Large dataset enables prediction of repair...
questionsmedicales.fr › Acides nucléiques, nucléotides et nucléosides › Acides nucléiques › ARN › ARN non traduit › Petit ARN non traduit › ARN guide › Large dataset enables prediction of repair...
questionsmedicales.fr › Systèmes sanguin et immunitaire › Système immunitaire › Leucocytes › Agranulocytes › Lymphocytes › Lymphocytes T › Large dataset enables prediction of repair...