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

Ryan T Leenay; Amirali Aghazadeh; Joseph Hiatt; David Tse; Theodore L Roth; Ryan Apathy; Eric Shifrut; Judd F Hultquist; Nevan Krogan; Zhenqin Wu; Giana Cirolia; Hera Canaj; Manuel D Leonetti; Alexander Marson; Andrew P May; James Zou

doi:10.1038/s41587-019-0203-2

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

Nat Biotechnol. 2019 Sep;37(9):1034-1037. doi: 10.1038/s41587-019-0203-2. Epub 2019 Jul 29.

Authors

Ryan T Leenay^#¹, Amirali Aghazadeh^#², Joseph Hiatt^#^{3

4

5

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7}, David Tse², Theodore L Roth⁴, Ryan Apathy⁴, Eric Shifrut⁴, Judd F Hultquist^{7

8

9

10}, Nevan Krogan^{7

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9}, Zhenqin Wu¹¹, Giana Cirolia¹, Hera Canaj¹, Manuel D Leonetti¹, Alexander Marson^{12

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14

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17}, Andrew P May^{18

19}, James Zou^{20

21

22}

Affiliations

¹ Chan-Zuckerberg Biohub, San Francisco, CA, USA.
² Department of Electrical Engineering, Stanford University, Stanford, CA, USA.
³ Biomedical Sciences Graduate Program, University of California, San Francisco, San Francisco, CA, USA.
⁴ Department of Microbiology and Immunology, University of California, San Francisco, San Francisco, CA, USA.
⁵ Diabetes Center, University of California, San Francisco, San Francisco, CA, USA.
⁶ Medical Scientist Training Program, University of California, San Francisco, San Francisco, CA, USA.
⁷ J. David Gladstone Institutes, San Francisco, CA, USA.
⁸ Department of Cellular and Molecular Pharmacology, University of California, San Francisco, San Francisco, CA, USA.
⁹ Quantitative Biosciences Institute (QBI), University of California, San Francisco, San Francisco, CA, USA.
¹⁰ Division of Infectious Diseases, Northwestern University Feinberg School of Medicine, Chicago, IL, USA.
¹¹ Department of Chemistry, Stanford University, Stanford, CA, USA.
¹² Chan-Zuckerberg Biohub, San Francisco, CA, USA. alexander.marson@ucsf.edu.
¹³ Department of Microbiology and Immunology, University of California, San Francisco, San Francisco, CA, USA. alexander.marson@ucsf.edu.
¹⁴ Diabetes Center, University of California, San Francisco, San Francisco, CA, USA. alexander.marson@ucsf.edu.
¹⁵ Innovative Genomics Institute, University of California, Berkeley, Berkeley, CA, USA. alexander.marson@ucsf.edu.
¹⁶ Department of Medicine, University of California, San Francisco, San Francisco, CA, USA. alexander.marson@ucsf.edu.
¹⁷ Parker Institute for Cancer Immunotherapy, San Francisco, CA, USA. alexander.marson@ucsf.edu.
¹⁸ Chan-Zuckerberg Biohub, San Francisco, CA, USA. apmay1@gmail.com.
¹⁹ Sana Biotechnology, South San Francisco, CA, USA. apmay1@gmail.com.
²⁰ Chan-Zuckerberg Biohub, San Francisco, CA, USA. jamesz@stanford.edu.
²¹ Department of Electrical Engineering, Stanford University, Stanford, CA, USA. jamesz@stanford.edu.
²² Department of Biomedical Data Science, Stanford University, Stanford, CA, USA. jamesz@stanford.edu.

^# Contributed equally.

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.

Publication types

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

MeSH terms

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

Substances

RNA, Guide, CRISPR-Cas Systems

Abstract

Publication types

MeSH terms

Substances

Grants and funding