Population-scale cellular GUIDE-seq-2 and biochemical CHANGE-seq-R profiles reveal human genetic variation frequently
Abstract:
Genome editing enzymes can introduce targeted changes to the DNA in living cells 1-4 , transforming biological research and enabling the first approved gene editing therapy for sickle cell disease 5 . However, their genome-wide activity can be altered by genetic variation at on- or off-target sites 6-8 , potentially impacting both their precision and therapeutic safety. Due to a lack of scalable methods to measure genome-wide editing activity in cells from large populations and diverse target libraries, the frequency and extent of these variant effects on editing remains unknown. Here, we present the first population-scale study of how genetic variation affects the cellular genome-wide activity of CRISPR-Cas9, enabled by a novel, sensitive, and unbiased cellular assay, GUIDE-seq-2 with improved scalability and accuracy compared to the original broadly adopted method 9 . Analyzing Cas9 genome-wide activity at 1,115 on- and off-target sites across six guide RNAs in cells from 95 individuals spanning four genetically diverse populations, we found that variants frequently overlap off-target sites, with 13% significantly altering Cas9 editing activity by up to 33% indels. To understand common features of high-impact variants, we developed a new massively parallel biochemical assay, CHANGE-seq-R, to measure Cas9 activity across millions of mismatched target sites, and trained a deep neural network model, CHANGE-net, to accurately predict and interpret the effects of single-nucleotide variants on off-targets with up to six mismatches. Taken together, our findings illuminate a path to account for genetic variation when designing genome editing strategies for research and therapeutics.
