CRISPR/Cas9 is a promising tool in prokaryotic genome engineering, but its 2 0 success is limited by the widely varying on-target activity of single guide RNAs (sgRNAs).
1Based on the association of CRISPR/Cas9-induced DNA cleavage with cellular lethality, we 2 2 systematically profiled sgRNA activity by co-expressing a genome-scale library dataset, we constructed a comprehensive and high-density sgRNA activity map, which enables 2 5 selecting highly active sgRNAs for any locus across the genome in this model organism. We 2 6 also identified 'resistant' genomic loci with respect to CRISPR/Cas9 activity, notwithstanding 2 7 the highly accessible DNA in bacterial cells. Moreover, we found that previous sgRNA activity 2 8 prediction models that were trained on mammalian cell datasets were inadequate when coping 2 9with our results, highlighting the key limitations and biases of previous models. We hence 3 0 developed an integrated algorithm to accurately predict highly effective sgRNAs, aiming to 3 1 facilitate the design of CRISPR/Cas9-based genome engineering or screenings in bacteria. We 3 2 also isolated the important sgRNA features that contribute to DNA cleavage and characterized 3 3