CRISPR-Cas9 induces large structural variants at on-target and off-target sites in vivo that segregate across generations.


Journal

Nature communications
ISSN: 2041-1723
Titre abrégé: Nat Commun
Pays: England
ID NLM: 101528555

Informations de publication

Date de publication:
02 02 2022
Historique:
received: 08 10 2021
accepted: 04 01 2022
entrez: 3 2 2022
pubmed: 4 2 2022
medline: 16 2 2022
Statut: epublish

Résumé

CRISPR-Cas9 genome editing has potential to cure diseases without current treatments, but therapies must be safe. Here we show that CRISPR-Cas9 editing can introduce unintended mutations in vivo, which are passed on to the next generation. By editing fertilized zebrafish eggs using four guide RNAs selected for off-target activity in vitro, followed by long-read sequencing of DNA from >1100 larvae, juvenile and adult fish across two generations, we find that structural variants (SVs), i.e., insertions and deletions ≥50 bp, represent 6% of editing outcomes in founder larvae. These SVs occur both at on-target and off-target sites. Our results also illustrate that adult founder zebrafish are mosaic in their germ cells, and that 26% of their offspring carries an off-target mutation and 9% an SV. Hence, pre-testing for off-target activity and SVs using patient material is advisable in clinical applications, to reduce the risk of unanticipated effects with potentially large implications.

Identifiants

pubmed: 35110541
doi: 10.1038/s41467-022-28244-5
pii: 10.1038/s41467-022-28244-5
pmc: PMC8810904
doi:

Substances chimiques

RNA, Guide 0
DNA 9007-49-2

Types de publication

Journal Article Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Pagination

627

Informations de copyright

© 2022. The Author(s).

Références

Frangoul, H. et al. CRISPR-Cas9 gene editing for sickle cell disease and beta-thalassemia. N. Engl. J. Med. 384, 252–260 (2021).
pubmed: 33283989 doi: 10.1056/NEJMoa2031054
Gillmore, J. D. et al. CRISPR-Cas9 in vivo gene editing for transthyretin amyloidosis. N. Engl. J. Med. 385, 493–502 (2021).
Lu, Y. et al. Safety and feasibility of CRISPR-edited T cells in patients with refractory non-small-cell lung cancer. Nat. Med. 26, 732–740 (2020).
pubmed: 32341578 doi: 10.1038/s41591-020-0840-5
Stadtmauer, E. A. et al. CRISPR-engineered T cells in patients with refractory cancer. Science 367, eaba7365 (2020).
Fu, Y. et al. High-frequency off-target mutagenesis induced by CRISPR-Cas nucleases in human cells. Nat. Biotechnol. 31, 822–826 (2013).
pubmed: 23792628 pmcid: 3773023 doi: 10.1038/nbt.2623
Hsu, P. D. et al. DNA targeting specificity of RNA-guided Cas9 nucleases. Nat. Biotechnol. 31, 827–832 (2013).
pubmed: 23873081 pmcid: 3969858 doi: 10.1038/nbt.2647
Aryal, N. K., Wasylishen, A. R. & Lozano, G. CRISPR/Cas9 can mediate high-efficiency off-target mutations in mice in vivo. Cell Death Dis. 9, 1099 (2018).
pubmed: 30368519 pmcid: 6204134 doi: 10.1038/s41419-018-1146-0
Cradick, T. J., Fine, E. J., Antico, C. J. & Bao, G. CRISPR/Cas9 systems targeting beta-globin and CCR5 genes have substantial off-target activity. Nucleic Acids Res. 41, 9584–9592 (2013).
pubmed: 23939622 pmcid: 3814385 doi: 10.1093/nar/gkt714
Luo, X. et al. Trio deep-sequencing does not reveal unexpected off-target and on-target mutations in Cas9-edited rhesus monkeys. Nat. Commun. 10, 5525 (2019).
pubmed: 31797925 pmcid: 6892871 doi: 10.1038/s41467-019-13481-y
Iyer, V. et al. No unexpected CRISPR-Cas9 off-target activity revealed by trio sequencing of gene-edited mice. PLoS Genet. 14, e1007503 (2018).
pubmed: 29985941 pmcid: 6057650 doi: 10.1371/journal.pgen.1007503
Kosicki, M., Tomberg, K. & Bradley, A. Repair of double-strand breaks induced by CRISPR-Cas9 leads to large deletions and complex rearrangements. Nat. Biotechnol. 36, 765–771 (2018).
pubmed: 30010673 pmcid: 6390938
Adikusuma, F. et al. Large deletions induced by Cas9 cleavage. Nature 560, E8–E9 (2018).
pubmed: 30089922 doi: 10.1038/s41586-018-0380-z
Owens, D. D. G. et al. Microhomologies are prevalent at Cas9-induced larger deletions. Nucleic Acids Res. 47, 7402–7417 (2019).
pubmed: 31127293 pmcid: 6698657 doi: 10.1093/nar/gkz459
Simeonov, D. R. et al. A large CRISPR-induced bystander mutation causes immune dysregulation. Commun. Biol. 2, 70 (2019).
pubmed: 30793048 pmcid: 6379443 doi: 10.1038/s42003-019-0321-x
Alanis-Lobato, G. et al. Frequent loss of heterozygosity in CRISPR-Cas9-edited early human embryos. Proc. Natl Acad. Sci. USA 118, e2004832117 (2021).
Cullot, G. et al. CRISPR-Cas9 genome editing induces megabase-scale chromosomal truncations. Nat. Commun. 10, 1136 (2019).
pubmed: 30850590 pmcid: 6408493 doi: 10.1038/s41467-019-09006-2
Papathanasiou, S. et al. Whole chromosome loss and genomic instability in mouse embryos after CRISPR-Cas9 genome editing. Nat. Commun. 12, 5855 (2021).
pubmed: 34615869 pmcid: 8494802 doi: 10.1038/s41467-021-26097-y
Przewrocka, J., Rowan, A., Rosenthal, R., Kanu, N. & Swanton, C. Unintended on-target chromosomal instability following CRISPR/Cas9 single gene targeting. Ann. Oncol. 31, 1270–1273 (2020).
pubmed: 32422169 doi: 10.1016/j.annonc.2020.04.480
Rayner, E. et al. CRISPR-Cas9 causes chromosomal instability and rearrangements in cancer cell lines, detectable by cytogenetic. Methods CRISPR J. 2, 406–416 (2019).
pubmed: 31742432 doi: 10.1089/crispr.2019.0006
Zuccaro, M. V. et al. Allele-specific chromosome removal after Cas9 cleavage in human embryos. Cell 183, 1650–1664 e1615 (2020).
pubmed: 33125898 doi: 10.1016/j.cell.2020.10.025
Leibowitz, M. L. et al. Chromothripsis as an on-target consequence of CRISPR-Cas9 genome editing. Nat. Genet. 53, 895–905 (2021).
Stemmer, M., Thumberger, T., Del Sol Keyer, M., Wittbrodt, J. & Mateo, J. L. CCTop: An intuitive, flexible and reliable CRISPR/Cas9 target prediction tool. PLoS One 10, e0124633 (2015).
pubmed: 25909470 pmcid: 4409221 doi: 10.1371/journal.pone.0124633
Moreno-Mateos, M. A. et al. CRISPRscan: Designing highly efficient sgRNAs for CRISPR-Cas9 targeting in vivo. Nat. Methods 12, 982–988 (2015).
pubmed: 26322839 pmcid: 4589495 doi: 10.1038/nmeth.3543
Labun, K., Montague, T. G., Gagnon, J. A., Thyme, S. B. & Valen, E. CHOPCHOP v2: A web tool for the next generation of CRISPR genome engineering. Nucleic Acids Res. 44, W272–W276 (2016).
pubmed: 27185894 pmcid: 4987937 doi: 10.1093/nar/gkw398
Haeussler, M. et al. Evaluation of off-target and on-target scoring algorithms and integration into the guide RNA selection tool CRISPOR. Genome Biol. 17, 148 (2016).
pubmed: 27380939 pmcid: 4934014 doi: 10.1186/s13059-016-1012-2
Bae, S., Park, J. & Kim, J. S. Cas-OFFinder: A fast and versatile algorithm that searches for potential off-target sites of Cas9 RNA-guided endonucleases. Bioinformatics 30, 1473–1475 (2014).
pubmed: 24463181 pmcid: 4016707 doi: 10.1093/bioinformatics/btu048
Cameron, P. et al. Mapping the genomic landscape of CRISPR-Cas9 cleavage. Nat. Methods 14, 600–606 (2017).
pubmed: 28459459 doi: 10.1038/nmeth.4284
Frock, R. L. et al. Genome-wide detection of DNA double-stranded breaks induced by engineered nucleases. Nat. Biotechnol. 33, 179–186 (2015).
pubmed: 25503383 doi: 10.1038/nbt.3101
Kim, D. et al. Digenome-seq: genome-wide profiling of CRISPR-Cas9 off-target effects in human cells. Nat. Methods 12, 237–243 (2015).
pubmed: 25664545 doi: 10.1038/nmeth.3284
Kim, D., Kim, S., Kim, S., Park, J. & Kim, J. S. Genome-wide target specificities of CRISPR-Cas9 nucleases revealed by multiplex Digenome-seq. Genome Res. 26, 406–415 (2016).
pubmed: 26786045 pmcid: 4772022 doi: 10.1101/gr.199588.115
Tsai, S. Q. et al. CIRCLE-seq: a highly sensitive in vitro screen for genome-wide CRISPR-Cas9 nuclease off-targets. Nat. Methods 14, 607–614 (2017).
pubmed: 28459458 pmcid: 5924695 doi: 10.1038/nmeth.4278
Tsai, S. Q. et al. GUIDE-seq enables genome-wide profiling of off-target cleavage by CRISPR-Cas nucleases. Nat. Biotechnol. 33, 187–197 (2015).
pubmed: 25513782 doi: 10.1038/nbt.3117
Hoijer, I. et al. Amplification-free long-read sequencing reveals unforeseen CRISPR-Cas9 off-target activity. Genome Biol. 21, 290 (2020).
pubmed: 33261648 pmcid: 7706270 doi: 10.1186/s13059-020-02206-w
Nikpay, M. et al. A comprehensive 1,000 Genomes-based genome-wide association meta-analysis of coronary artery disease. Nat. Genet. 47, 1121–1130 (2015).
pubmed: 26343387 pmcid: 4589895 doi: 10.1038/ng.3396
den Hoed, M. et al. Identification of heart rate-associated loci and their effects on cardiac conduction and rhythm disorders. Nat. Genet. 45, 621–631 (2013).
doi: 10.1038/ng.2610
Willer, C. J. et al. Discovery and refinement of loci associated with lipid levels. Nat. Genet. 45, 1274–1283 (2013).
pubmed: 24097068 pmcid: 3838666 doi: 10.1038/ng.2797
Bandaru, M. K. et al. Zebrafish larvae as a model system for systematic characterization of drugs and genes in dyslipidemia and atherosclerosis. Preprint at bioRxiv https://doi.org/10.1101/502674 (2019).
von der Heyde, B. et al. Translating GWAS-identified loci for cardiac rhythm and rate using an in vivo image- and CRISPR/Cas9-based approach. Sci. Rep. 10, 11831 (2020).
pubmed: 32678143 pmcid: 7367351 doi: 10.1038/s41598-020-68567-1
Hoshijima, K. et al. Highly efficient CRISPR-Cas9-based methods for generating deletion mutations and F0 embryos that lack gene function in zebrafish. Dev. Cell 51, 645–657 e644 (2019).
pubmed: 31708433 pmcid: 6891219 doi: 10.1016/j.devcel.2019.10.004
van Overbeek, M. et al. DNA repair profiling reveals nonrandom outcomes at Cas9-mediated breaks. Mol. Cell 63, 633–646 (2016).
pubmed: 27499295 doi: 10.1016/j.molcel.2016.06.037
Hoijer, I. et al. Detailed analysis of HTT repeat elements in human blood using targeted amplification-free long-read sequencing. Hum. Mutat. 39, 1262–1272 (2018).
pubmed: 29932473 pmcid: 6175010 doi: 10.1002/humu.23580
Kovaka, S., Fan, Y., Ni, B., Timp, W. & Schatz, M. C. Targeted nanopore sequencing by real-time mapping of raw electrical signal with UNCALLED. Nat. Biotechnol. 39, 431–441 (2021).
pubmed: 33257863 doi: 10.1038/s41587-020-0731-9
Madsen, E. B., Hoijer, I., Kvist, T., Ameur, A. & Mikkelsen, M. J. Xdrop: Targeted sequencing of long DNA molecules from low input samples using droplet sorting. Hum. Mutat. 41, 1671–1679 (2020).
pubmed: 32516842 pmcid: 7496172 doi: 10.1002/humu.24063
Payne, A. et al. Readfish enables targeted nanopore sequencing of gigabase-sized genomes. Nat. Biotechnol. 39, 442–450 (2021).
pubmed: 33257864 doi: 10.1038/s41587-020-00746-x
Stangl, C. et al. Partner independent fusion gene detection by multiplexed CRISPR-Cas9 enrichment and long read nanopore sequencing. Nat. Commun. 11, 2861 (2020).
pubmed: 32504042 pmcid: 7275081 doi: 10.1038/s41467-020-16641-7
Turchiano, G. et al. Quantitative evaluation of chromosomal rearrangements in gene-edited human stem cells by CAST-Seq. Cell Stem Cell 28, 1136–1147 e1135 (2021).
pubmed: 33626327 doi: 10.1016/j.stem.2021.02.002
Blondal, T. et al. Verification of CRISPR editing and finding transgenic inserts by Xdrop indirect sequence capture followed by short- and long-read sequencing. Methods 191, 68–77 (2021).
pubmed: 33582298 doi: 10.1016/j.ymeth.2021.02.003
Li, H. Minimap2: Pairwise alignment for nucleotide sequences. Bioinformatics 34, 3094–3100 (2018).
pubmed: 29750242 pmcid: 6137996
Madeira, F. et al. The EMBL-EBI search and sequence analysis tools APIs in 2019. Nucleic Acids Res. 47, W636–W641 (2019).
pubmed: 30976793 pmcid: 6602479 doi: 10.1093/nar/gkz268
Sedlazeck, F. J. et al. Accurate detection of complex structural variations using single-molecule sequencing. Nat. Methods 15, 461–468 (2018).
pubmed: 29713083 pmcid: 5990442 doi: 10.1038/s41592-018-0001-7
Ramirez, F., Dundar, F., Diehl, S., Gruning, B. A. & Manke, T. deepTools: A flexible platform for exploring deep-sequencing data. Nucleic Acids Res. 42, W187–W191 (2014).
pubmed: 24799436 pmcid: 4086134 doi: 10.1093/nar/gku365
Bunikis, I. & Ameur, A. Insider—integration & cleavage site detection. Github https://github.com/UppsalaGenomeCenter/InSiDeR https://doi.org/10.5281/zenodo.4159442 (2020).
van Schendel, R., Schimmel, J. & Tijsterman, M. SIQ—Sequence Interrogation and Qualification. GitHub https://github.com/RobinVanSchendel/SIQ (2021).

Auteurs

Ida Höijer (I)

Science for Life Laboratory, Department of Immunology, Genetics and Pathology, Uppsala University, Uppsala, Sweden. ida.hoijer@igp.uu.se.

Anastasia Emmanouilidou (A)

Science for Life Laboratory, Department of Immunology, Genetics and Pathology, Uppsala University, Uppsala, Sweden.
The Beijer laboratory and Department of Immunology, Genetics and Pathology, Uppsala University, Uppsala, Sweden.

Rebecka Östlund (R)

Science for Life Laboratory, Department of Immunology, Genetics and Pathology, Uppsala University, Uppsala, Sweden.

Robin van Schendel (R)

Department of Human Genetics, Leiden University Medical Center, Leiden, The Netherlands.

Selma Bozorgpana (S)

Science for Life Laboratory, Department of Immunology, Genetics and Pathology, Uppsala University, Uppsala, Sweden.

Marcel Tijsterman (M)

Department of Human Genetics, Leiden University Medical Center, Leiden, The Netherlands.

Lars Feuk (L)

Science for Life Laboratory, Department of Immunology, Genetics and Pathology, Uppsala University, Uppsala, Sweden.

Ulf Gyllensten (U)

Science for Life Laboratory, Department of Immunology, Genetics and Pathology, Uppsala University, Uppsala, Sweden.

Marcel den Hoed (M)

Science for Life Laboratory, Department of Immunology, Genetics and Pathology, Uppsala University, Uppsala, Sweden.
The Beijer laboratory and Department of Immunology, Genetics and Pathology, Uppsala University, Uppsala, Sweden.

Adam Ameur (A)

Science for Life Laboratory, Department of Immunology, Genetics and Pathology, Uppsala University, Uppsala, Sweden. adam.ameur@igp.uu.se.

Articles similaires

[Redispensing of expensive oral anticancer medicines: a practical application].

Lisanne N van Merendonk, Kübra Akgöl, Bastiaan Nuijen
1.00
Humans Antineoplastic Agents Administration, Oral Drug Costs Counterfeit Drugs

Smoking Cessation and Incident Cardiovascular Disease.

Jun Hwan Cho, Seung Yong Shin, Hoseob Kim et al.
1.00
Humans Male Smoking Cessation Cardiovascular Diseases Female
Humans United States Aged Cross-Sectional Studies Medicare Part C
1.00
Humans Yoga Low Back Pain Female Male

Classifications MeSH