Primerize-2D: automated primer design for RNA multidimensional chemical mapping

Area of Science:

• Molecular Biology
• Bioinformatics
• Structural Biology

Background:

• Rapid RNA synthesis is crucial for structural studies.
• Current methods for creating RNA mutant libraries are labor-intensive and prone to errors.
• Informatics tools are needed to manage primer design and organization for large-scale library synthesis.

Purpose of the Study:

• To develop and present an informatics tool that accelerates the design and organization of primers for synthesizing large RNA mutant libraries.
• To provide a user-friendly platform for researchers to create custom RNA mutant libraries efficiently.
• To reduce errors and costs associated with large-scale RNA synthesis protocols.

Main Methods:

• Development of an online tool (Primerize-2D server) and a stand-alone Python package for primer design.
• Utilizing PCR assembly of DNA templates and in vitro transcription for RNA synthesis.
• Experimental validation of the tool for RNA domains up to 300 nucleotides and libraries up to 960 variants.

Main Results:

• Successful acceleration of large RNA mutant library synthesis through efficient primer design and organization.
• Demonstrated cost-effectiveness by enabling primer sharing across constructs.
• Validated the tool's performance in laboratory settings for synthesizing up to 960 RNA variants.

Conclusions:

• Primerize-2D significantly streamlines the process of generating comprehensive single and targeted multiple RNA mutant libraries.
• The tool enhances the feasibility of multidimensional chemical approaches for RNA structure determination.
• Freely available online server and Python package promote broader adoption in RNA research.