Publication: CHANGE-seq reveals genetic and epigenetic effects on CRISPR-Cas9 genome-wide activity.
CHANGE-seq reveals genetic and epigenetic effects on CRISPR-Cas9 genome-wide activity.
Lazzarotto CR , Malinin NL , Li Y , Zhang R , Yang Y , Lee G , Cowley E , He Y , Lan X , Jividen K , Katta V , Kolmakova NG , Petersen CT , Qi Q , Strelcov E , Maragh S , Krenciute G , Ma J , Cheng Y , Tsai SQ
PII: 10.1038/s41587-020-0555-7;
PUBMED: 32541958;
PMC: PMC7652380;
MID: NIHMS1591991;
DOI: 10.1038/s41587-020-0555-7;
ABSTRACT: Current methods can illuminate the genome-wide activity of CRISPR-Cas9 nucleases, but are not easily scalable to the throughput needed to fully understand the principles that govern Cas9 specificity. Here we describe 'circularization for high-throughput analysis of nuclease genome-wide effects by sequencing' (CHANGE-seq), a scalable, automatable tagmentation-based method for measuring the genome-wide activity of Cas9 in vitro. We applied CHANGE-seq to 110 single guide RNA targets across 13 therapeutically relevant loci in human primary T cells and identified 201,934 off-target sites, enabling the training of a machine learning model to predict off-target activity. Comparing matched genome-wide off-target, chromatin modification and accessibility, and transcriptional data, we found that cellular off-target activity was two to four times more likely to occur near active promoters, enhancers and transcribed regions. Finally, CHANGE-seq analysis of six targets across eight individual genomes revealed that human single-nucleotide variation had significant effects on activity at ~15.2% of off-target sites analyzed. CHANGE-seq is a simplified, sensitive and scalable approach to understanding the specificity of genome editors.
ABSTRACT: Current methods can illuminate the genome-wide activity of CRISPR-Cas9 nucleases, but are not easily scalable to the throughput needed to fully understand the principles that govern Cas9 specificity. Here we describe 'circularization for high-throughput analysis of nuclease genome-wide effects by sequencing' (CHANGE-seq), a scalable, automatable tagmentation-based method for measuring the genome-wide activity of Cas9 in vitro. We applied CHANGE-seq to 110 single guide RNA targets across 13 therapeutically relevant loci in human primary T cells and identified 201,934 off-target sites, enabling the training of a machine learning model to predict off-target activity. Comparing matched genome-wide off-target, chromatin modification and accessibility, and transcriptional data, we found that cellular off-target activity was two to four times more likely to occur near active promoters, enhancers and transcribed regions. Finally, CHANGE-seq analysis of six targets across eight individual genomes revealed that human single-nucleotide variation had significant effects on activity at ~15.2% of off-target sites analyzed. CHANGE-seq is a simplified, sensitive and scalable approach to understanding the specificity of genome editors.