Cas-Database: web-based genome-wide guide RNA library design for gene knockout screens using CRISPR-Cas9

Area of Science:

• Molecular Biology
• Bioinformatics
• Genomics

Background:

• CRISPR-derived RNA guided endonucleases (RGENs) are powerful tools for gene editing, enabling gene knockout and knock-in.
• The application of RGENs for large-scale forward genetic screens is hindered by the difficulty in selecting single guide RNA (sgRNA) sequences.

Purpose of the Study:

• To develop an accessible online tool for designing genome-wide sgRNA libraries.
• To facilitate the selection of optimal target sequences for Streptococcus pyogenes Cas9 (SpCas9) nucleases.

Main Methods:

• Development of Cas-Database, an online tool with a user-friendly web interface.
• Implementation of filtering conditions for selecting optimal target sequences.
• Provision of functionality to select multiple optimal target sequences for genome-wide library creation.
• Inclusion of a web API for advanced bioinformatics users.

Main Results:

• Cas-Database enables efficient selection of optimal SpCas9 target sequences.
• The tool supports the design of genome-wide sgRNA libraries by allowing simultaneous selection of thousands of target sequences.
• An integrated web API caters to advanced users for programmatic access.

Conclusions:

• Cas-Database simplifies and enhances the process of designing sgRNA libraries for large-scale CRISPR screens.
• The tool democratizes access to genome-wide CRISPR screening capabilities through its intuitive interface and powerful features.