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Large dataset enables prediction of repair after CRISPR-Cas9 editing in primary T cells.
Leenay, Ryan T; Aghazadeh, Amirali; Hiatt, Joseph; Tse, David; Roth, Theodore L; Apathy, Ryan; Shifrut, Eric; Hultquist, Judd F; Krogan, Nevan; Wu, Zhenqin; Cirolia, Giana; Canaj, Hera; Leonetti, Manuel D; Marson, Alexander; May, Andrew P; Zou, James.
Afiliação
  • Leenay RT; Chan-Zuckerberg Biohub, San Francisco, CA, USA.
  • Aghazadeh A; Department of Electrical Engineering, Stanford University, Stanford, CA, USA.
  • Hiatt J; Biomedical Sciences Graduate Program, University of California, San Francisco, San Francisco, CA, USA.
  • Tse D; Department of Microbiology and Immunology, University of California, San Francisco, San Francisco, CA, USA.
  • Roth TL; Diabetes Center, University of California, San Francisco, San Francisco, CA, USA.
  • Apathy R; Medical Scientist Training Program, University of California, San Francisco, San Francisco, CA, USA.
  • Shifrut E; J. David Gladstone Institutes, San Francisco, CA, USA.
  • Hultquist JF; Department of Electrical Engineering, Stanford University, Stanford, CA, USA.
  • Krogan N; Department of Microbiology and Immunology, University of California, San Francisco, San Francisco, CA, USA.
  • Wu Z; Department of Microbiology and Immunology, University of California, San Francisco, San Francisco, CA, USA.
  • Cirolia G; Department of Microbiology and Immunology, University of California, San Francisco, San Francisco, CA, USA.
  • Canaj H; J. David Gladstone Institutes, San Francisco, CA, USA.
  • Leonetti MD; Department of Cellular and Molecular Pharmacology, University of California, San Francisco, San Francisco, CA, USA.
  • Marson A; Quantitative Biosciences Institute (QBI), University of California, San Francisco, San Francisco, CA, USA.
  • May AP; Division of Infectious Diseases, Northwestern University Feinberg School of Medicine, Chicago, IL, USA.
  • Zou J; J. David Gladstone Institutes, San Francisco, CA, USA.
Nat Biotechnol ; 37(9): 1034-1037, 2019 09.
Article em En | MEDLINE | ID: mdl-31359007
ABSTRACT
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.
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Texto completo: 1 Base de dados: MEDLINE Assunto principal: Linfócitos T / RNA Guia de Cinetoplastídeos / Sistemas CRISPR-Cas / Edição de Genes Idioma: En Ano de publicação: 2019 Tipo de documento: Article
Texto completo
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Texto completo: 1 Base de dados: MEDLINE Assunto principal: Linfócitos T / RNA Guia de Cinetoplastídeos / Sistemas CRISPR-Cas / Edição de Genes Idioma: En Ano de publicação: 2019 Tipo de documento: Article