Az orvos-, egészségtudományi- és gyógyszerészképzés tudományos műhelyeinek fejlesztése(EFOP-3.6.3-VEKOP-16-2017-00009)
Funder: EFOP-VEKOP
(2018-1.1.1-MKI-2018-00081) Funder: NRDIO
(K-119287) Funder: NRDIO
(K125607) Funder: HSRF
(LP2012/35) Funder: MTA Lendület
Subjects:
Bioinformatics
Detailed target-selectivity information and experiment-based efficacy prediction tools
are primarily available for Streptococcus pyogenes Cas9 (SpCas9). One obstacle to
develop such tools is the rarity of accurate data. Here, we report a method termed
‘Self-targeting sgRNA Library Screen’ (SLS) for assaying the activity of Cas9 nucleases
in bacteria using random target/sgRNA libraries of self-targeting sgRNAs. Exploiting
more than a million different sequences, we demonstrate the use of the method with
the SpCas9-HF1 variant to analyse its activity and reveal motifs that influence its
target-selectivity. We have also developed an algorithm for predicting the activity
of SpCas9-HF1 with an accuracy matching those of existing tools. SLS is a facile alternative
to the much more expensive and laborious approaches used currently and has the capability
of delivering sufficient amount of data for most of the orthologs and variants of
SpCas9.
