OR13
Global-scale CRISPR gene editor specificity profiling by ONE-seq identifies population-specific, variant off-target effects.
K Petri¹ ² ³ ⁴ D Y Kim¹ ² ³ K E Sasaki¹ ² ³ M C Canver¹ ² ⁴ X Wang⁸ H Shah¹ ² ³ H Lee¹ ² ³ J E Horng¹ ² ³ K Clement¹ ² ³ ⁴ S Iyer¹ S P Garcia¹ J A Guo¹ ² ³ G A Newby⁵ ⁶ ⁷ L Pinello¹ ² ⁴ D R Liu⁵ ⁶ ⁷ M J Aryee¹ ² ³ ⁴ ⁹ K Musunuru⁸ J K Joung *¹ ² ³ ⁴ V Pattanayak*¹ ² ³ ⁴
1:Molecular Pathology Unit, Massachusetts General Hospital, Charlestown, MA, USA.; 2:Center for Cancer Research, Massachusetts General Hospital, Charlestown, MA, USA.; 3:Center for Computational and Integrative Biology, Massachusetts General Hospital, Charlestown, MA, USA.; 4:Department of Pathology, Harvard Medical School, Boston, MA, USA.; 5:Merkin Institute of Transformative Technologies in Healthcare, Broad Institute of Harvard and MIT, Cambridge, MA, USA.; 6:Department of Chemistry and Chemical Biology, Harvard University, Cambridge, MA, USA.; 7:Howard Hughes Medical Institute, Harvard University, Cambridge, MA, USA.; 8:Division of Cardiology and Cardiovascular Institute, Department of Medicine, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA, USA.; 9:Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, USA.
Characterising CRISPR gene editor off-target profiles remains a crucial challenge for therapeutic use of these technologies. Previous methods can identify gene editor off-targets induced on a single genome but are not able to account for the diversity of genetic sequence variation within whole populations. Here we describe OligoNucleotide Enrichment and sequencing (ONE-seq), an in vitro method leveraging high-throughput DNA synthesis instead of genomic DNA from individual genomes to assess gene editor off-targets. We demonstrate that ONE-seq is at least as sensitive as existing single-genome methods for identifying bona fide CRISPR-Cas9 off-targets. We used ONE-seq to establish the first experimental population-scale off-target profiles for Cas9 nucleases characterising the influence of genetic variants from >2,500 human genomes of the 1000 Genomes Project. We confirmed that ONE-seq-nominated, variant-sensitive and population-specific off-target sites show increased mutation frequencies in genetic variant-harbouring lymphoblastoid cells (LCLs). Our data demonstrate that ONE-seq is a highly sensitive off-target nomination method that can detect population subgroup-linked differences in gene editor off-target profiles. ONE-seq uniquely enables facile assessment of the impacts of human genetic sequence diversity on gene editor off-targets, thereby permitting a broader and more all-inclusive approach to profile the specificities of these transformative therapeutic technologies.