Abstract
Objective: To design and implement a simple and highly integrated primer design software for detection of highly variable bacteria. Methods: Firstly, gene named entity recognition technology was applied to annotate the genes in the literature, thus the conservative gene knowledge base of highly variable bacteria could be established. Then, new primer design workflow was created by integrating Clustal Omega, Gblocks, Primer3, MFEprimer3.0, which achieves high-performance specificity detection with improved index algorithms and parallel computing. Finally, multiple primers could be obtained by combining primers designed by different conservative genes based on the greedy algorithm. Results: A web-based primer design software was implemented. Primers were designed for five highly variable bacteria, including Escherichia coli, Shigella, Listeria monocytogenes, Staphylococcus aureus, and Salmonella. By comparison, the single primers designed by our software were more specific and sensitive than primers in the literature for detecting the same conservative gene. The multiple primers designed for each bacterium have strong specificity, and the coverage rate of Escherichia coli primers is 93. 14% in terms of sensitivity, and the coverage rate of other bacterial primers is more than 99%. Conclusion: The software can be applied to the design of PCR primers for the detection of highly variable bacteria.
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Hu, D., Qu, W., Tong, F., Zheng, X., Li, J., Zhao, D. (2022). An Efficient and User-Friendly Software for PCR Primer Design for Detection of Highly Variable Bacteria. In: Bansal, M.S., Cai, Z., Mangul, S. (eds) Bioinformatics Research and Applications. ISBRA 2022. Lecture Notes in Computer Science(), vol 13760. Springer, Cham. https://doi.org/10.1007/978-3-031-23198-8_13
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