SgRNAcas9: a Software Package for Designing CRISPR SgRNA and Evaluating Potential Off-target Cleavage Sites
Overview
Affiliations
Although the CRISPR/Cas9/sgRNA system efficiently cleaves intracellular DNA at desired target sites, major concerns remain on potential "off-target" cleavage that may occur throughout the whole genome. In order to improve CRISPR-Cas9 specificity for targeted genome editing and transcriptional control, we describe a bioinformatics tool "sgRNAcas9", which is a software package developed for fast design of CRISPR sgRNA with minimized off-target effects. This package consists of programs to perform a search for CRISPR target sites (protospacers) with user-defined parameters, predict genome-wide Cas9 potential off-target cleavage sites (POT), classify the POT into three categories, batch-design oligonucleotides for constructing 20-nt (nucleotides) or truncated sgRNA expression vectors, extract desired length nucleotide sequences flanking the on- or off-target cleavage sites for designing PCR primer pairs to validate the mutations by T7E1 cleavage assay. Importantly, by identifying potential off-target sites in silico, the sgRNAcas9 allows the selection of more specific target sites and aids the identification of bona fide off-target sites, significantly facilitating the design of sgRNA for genome editing applications. sgRNAcas9 software package is publicly available at BiooTools website (www.biootools.com) under the terms of the GNU General Public License.
Metabolic engineering of for high-level production of pneumocandin B.
Zhang X, Cheng S, Yang J, Lu L, Deng Z, Bian G Synth Syst Biotechnol. 2025; 10(2):381-390.
PMID: 39830076 PMC: 11742615. DOI: 10.1016/j.synbio.2024.12.008.
Jiang J, Liu D, Li J, Tian C, Zhuang Y, Xia J Microb Cell Fact. 2024; 23(1):295.
PMID: 39488710 PMC: 11531171. DOI: 10.1186/s12934-024-02570-3.
Lv Y, Zeng M, Yan Z, Zhang P, Ban N, Yuan D BMC Biol. 2024; 22(1):232.
PMID: 39394161 PMC: 11470741. DOI: 10.1186/s12915-024-02029-2.
Papouskova K, Akinola J, Ruiz-Castilla F, Morrissey J, Ramos J, Sychrova H FEMS Yeast Res. 2024; 24.
PMID: 39363175 PMC: 11484806. DOI: 10.1093/femsyr/foae031.
Codon usage and expression-based features significantly improve prediction of CRISPR efficiency.
Bergman S, Tuller T NPJ Syst Biol Appl. 2024; 10(1):100.
PMID: 39227603 PMC: 11372048. DOI: 10.1038/s41540-024-00431-8.