Novel computational methods for increasing PCR primer design effectiveness in directed sequencing.

Area of Science:

• Genomics
• Bioinformatics
• Molecular Biology

Background:

• Polymerase Chain Reaction (PCR) is vital for directed sequencing and polymorphism discovery.
• Current computational primer design tools often lack integration with laboratory protocols, leading to iterative optimization and failed amplifications.
• This inefficiency is particularly problematic in high-throughput settings targeting numerous genes.

Purpose of the Study:

• To develop a fully integrated computational pipeline for Polymerase Chain Reaction (PCR) primer design.
• To improve the success rate of high-throughput directed sequencing.
• To identify novel computational methods for predicting and preventing PCR failures.

Main Methods:

• Developed a computational PCR primer design pipeline integrated into a high-throughput directed sequencing workflow.
• Enabled target region specification using descriptors like Ensembl accessions and genomic coordinates.
• Implemented computational screening of primer pairs against two PCR amplification protocols to ensure success criteria are met.

Main Results:

• Achieved a sequencing success rate exceeding 95% for exons.
• Discovered novel computational methods for accurately identifying primers prone to PCR failure.
• Revealed laboratory protocols and empirically determined computational parameters for primer design.

Conclusions:

• The high-throughput PCR primer design pipeline provides a basis for high-quality directed sequencing, reducing labor and reprocessing costs.
• The software's modular design allows integration of additional primer critique tests based on laboratory feedback.
• The pipeline, combined with laboratory protocols, is a powerful tool for both low and high-throughput primer design, enabling successful directed sequencing.