CROP: A CRISPR/Cas9 guide selection program based on mapping guide variants

Abstract

The off-target effect, in which DNA cleavage was conducted outside the targeted region, is a major problem which limits the applications of CRISPR/Cas9 genome editing system. CRISPR Offtarget Predictor (CROP) is standalone program developed to address this problem by predicting offtarget propensity of guide RNAs and thereby allowing the user to select the optimum guides. The approach used by CROP involves generating substitution, deletion and insertion combinations which are then mapped into the reference genome. Based on these mapped variants, scoring and alignment are conducted and then reported as a table comprising the off-target propensity of all guide RNAs from a given gene sequence. The Python script for this program is freely available from: https://github.com/vaprilyanto/crop.

A quantitative model for the dynamics of target recognition and off-target rejection by the CRISPR-Cas Cascade complex

“…The development of engineered effector variants (Amrani et al, 2018;Chen et al, 2017;Edraki et al, 2019;Gleditzsch et al, 2016;Kleinstiver et al, 2016;Lee et al, 2018;Luo et al, 2016;Ran et al, 2015;Slaymaker et al, 2016;Songailiene et al, 2019;Tuminauskaite et al, 2020;Wu et al, 2018) could recently reduce but not abolish off-targeting (Frock et al, 2015;Slaymaker et al, 2016). A frequently used complementary approach to prevent off-targets are in silico off-target predictors that promise to identify crRNAs with least promiscuity (Aprilyanto et al, 2021;Bae et al, 2014;Charlier et al, 2021;Haeussler et al, 2016;Lei et al, 2014;Lin and Wong, 2018;Minkenberg et al, 2019;Singh et al, 2015;Stemmer et al, 2015;Xu et al, 2017). Such prediction tools use heuristic scoring functions that try to reproduce sequence and mismatch position patterns from high throughput studies.…”