The authors have declared that no competing interests exist.
Current address: Department of Epigenetics and Molecular Carcinogenesis, University of Texas MD Anderson Cancer Center, Houston, TX, United States of America
The recently developed CRISPR screen technology, based on the CRISPR/Cas9 genome editing system, enables genome-wide interrogation of gene functions in an efficient and cost-effective manner. Although many computational algorithms and web servers have been developed to design single-guide RNAs (sgRNAs) with high specificity and efficiency, algorithms specifically designed for conducting CRISPR screens are still lacking. Here we present CRISPR-FOCUS, a web-based platform to search and prioritize sgRNAs for CRISPR screen experiments. With official gene symbols or RefSeq IDs as the only mandatory input, CRISPR-FOCUS filters and prioritizes sgRNAs based on multiple criteria, including efficiency, specificity, sequence conservation, isoform structure, as well as genomic variations including Single Nucleotide Polymorphisms and cancer somatic mutations. CRISPR-FOCUS also provides pre-defined positive and negative control sgRNAs, as well as other necessary sequences in the construct (e.g., U6 promoters to drive sgRNA transcription and RNA scaffolds of the CRISPR/Cas9). These features allow users to synthesize oligonucleotides directly based on the output of CRISPR-FOCUS. Overall, CRISPR-FOCUS provides a rational and high-throughput approach for sgRNA library design that enables users to efficiently conduct a focused screen experiment targeting up to thousands of genes.
(CRISPR-FOCUS is freely available at
The Clustered Regularly Interspaced Short Palindromic Repeats (CRISPR)–CRISPR-associated system genes 9 (Cas9) system has been proving itself to be a prominent genome-editing technique [
Many CRISPR screening experiments are conducted as unbiased, genome-scale approaches, where several genome-wide screening libraries are available [
To design libraries for CRISPR screens (especially focused screens), several computational tools can be applied [
Another issue of library design comes from the rational sgRNA evaluation and selection based on multiple criteria. Preferably, sgRNA should have fewer off-target effects (based on the alignment of spacer sequence across the whole genome [
In light of requirements from CRISPR screen experiments, we developed CRISPR-FOCUS, a web-based method for library design of CRISPR screens. With minimum user input, CRISPR-FOCUS selects different numbers of sgRNAs targeting up to one thousand genes in human or mouse genome. SgRNAs in the output are ranked by their summary score, which is a comprehensive evaluation of efficiency, specificity, as well as target sequence conservation and the target of multiple isoforms. To our knowledge, CRISPR-FOCUS is the only web-based tool that is specially optimized for CRISPR screening experiments.
The scheme of CRISPR-FOCUS is presented in
To reach the best CRISPR-based knockout effect, the selection of sgRNAs should be optimized to (1) maximize their on-target cleavage effects (
The cleavage efficiency of a sgRNA is a major factor that determines the sensitivity of a screen experiment [
For each candidate sgRNA, CRISPR-FOCUS first calculated its specificity score [
SgRNAs are usually designed based on the reference genome sequence. The knockout efficiencies of these sgRNAs may be affected by the genomic sequences in cells that are different from the reference, especially mutation. CRISPR-FOCUS prefers sgRNAs that cover no or fewer mutations, including Single Nucleotide Polymorphisms (SNPs) and somatic mutations (especially in cancer). CRISPR-FOCUS retrieved SNP information from dbSNP [
Regions in a gene with higher conservation rates across species are more likely to be important, as they usually encode conserved functional domains (like catalytic center for enzyme or DNA binding domain for transcriptional factor) whose knockout are more likely to disrupt gene function [
Some genes have multiple isoforms (or transcripts) with different structures. To completely knockout a gene, a sgRNA should ideally target as many isoforms as possible. For each exon region, CRISPR-FOCUS calculates an “isoform commonality score”, which is defined as the percentage of isoforms that uses this exon. SgRNAs targeting exon regions with higher scores are preferred.
For each gene in the query, CRISPR-FOCUS first retrieves all genomic coordinates of all exons, and collects all sgRNA candidates that overlap with these regions. It will next perform a “filter and rescue” procedure (described in
If the number of remaining sgRNAs does not reach the desired number, CRISPR-FOCUS will execute a “rescue” step to retrieve more possible sgRNAs. At this stage, sgRNAs with potential off-target hits will be rescued in the following order: (1) sgRNAs with non-exon off-target hits only, (2) sgRNAs with off-target hits located on non-coding elements but not coding regions, (3) sgRNAs with off-target hits located on coding regions. sgRNAs within the same category will be prioritized based on their number of off-target hits, or by the summary score if two candidates have the same number of hits within the same category. A detailed flowchart of the whole procedure is depicted in
The sgRNA selection/ranking process in CRISPR-FOCUS is composed of (A) a filter step and (B) a rescue step.
The web portal of CRISPR-FOCUS (
A screenshot of the CRISPR-FOCUS website (
CRISPR-FOCUS also provides other options to accommodate different requirements, including the selection of different sgRNA lengths (19 or 20nt) [
CRISPR-FOCUS provides a high throughput platform for rational sgRNA library design of CRISPR screen experiment. It could accomplish a full scale design (up to 1000 target genes with 30 sgRNAs for each) within about twenty seconds. To our knowledge, CRISPR-FOCUS is now the only web-based sgRNA design tool that provides batch processing mode for custom CRISPR library design, as well as the most comprehensive tool in sgRNA performance evaluation. By shortening the distance from “silico to bench”, CRISPR-FOCUS facilitates the design of screening experiments and promotes high-throughput functional studies in various scopes.
(DOCX)
(DOCX)
The authors thank Hanfei Sun, Chenfei Wang, Binbin Wang and Jinzeng Wang for their help on web server deployment and maintenance, and Wenyan Cui for help on plotting and decorating some of the figures.