Multiobjective optimization-driven primer design mechanism: towards user-specified parameters of PCR primer

Cheng-Hong Yang; Yu-Huei Cheng; Emirlyn Cheng Yang; Li-Yeh Chuang; Yu-Da Lin

doi:10.1093/bib/bbac121

Multiobjective optimization-driven primer design mechanism: towards user-specified parameters of PCR primer

Brief Bioinform. 2022 May 13;23(3):bbac121. doi: 10.1093/bib/bbac121.

Authors

Cheng-Hong Yang^{1

2

3}, Yu-Huei Cheng⁴, Emirlyn Cheng Yang⁵, Li-Yeh Chuang⁶, Yu-Da Lin⁷

Affiliations

¹ Department of Electronic Engineering, National Kaohsiung University of Science and Technology, Kaohsiung, 80778, Taiwan.
² Ph. D. Program in Biomedical Engineering, Kaohsiung Medical University, Kaohsiung, 80708, Taiwan.
³ School of Dentistry, Kaohsiung Medical University, Kaohsiung, 80708, Taiwan.
⁴ Department of Information and Communication Engineering, Chaoyang University of Technology, Taichung, 413310, Taiwan.
⁵ Department of Biochemistry, The University of Hong Kong, Pok Fu Lam, Hong Kong.
⁶ Department of Chemical Engineering & Institute of Biotechnology and Chemical Engineering, I-Shou University, Kaohsiung, 84001, Taiwan.
⁷ Department of Computer Science and Information Engineering, National Penghu University of Science and Technology, Penghu, 880011, Taiwan.

PMID: 35397164
DOI: 10.1093/bib/bbac121

Abstract

Primers are critical for polymerase chain reaction (PCR) and influence PCR experimental outcomes. Designing numerous combinations of forward and reverse primers involves various primer constraints, posing a computational challenge. Most PCR primer design methods limit parameters because the available algorithms use general fitness functions. This study designed new fitness functions based on user-specified parameters and used the functions in a primer design approach based on the multiobjective particle swarm optimization (MOPSO) algorithm to address the challenge of primer design with user-specified parameters. Multicriteria evaluation was conducted simultaneously based on primer constraints. The fitness functions were evaluated using 7425 DNA sequences and compared with a predominant primer design approach based on optimization algorithms. Each DNA sequence was run 100 times to calculate the difference between the user-specified parameters and primer constraint values. The algorithms based on fitness functions with user-specified parameters outperformed the algorithms based on general fitness functions for 11 primer constraints. Moreover, MOPSO exhibited superior implementation in all experiments. Practical gel electrophoresis was conducted to verify the PCR experiments and established that MOPSO effectively designs primers based on user-specified parameters.

Keywords: multiobjective optimization; polymerase chain reaction; primer design; user-specified parameters.

Publication types

Research Support, Non-U.S. Gov't

MeSH terms

Algorithms*
Base Sequence
DNA Primers / genetics
Polymerase Chain Reaction / methods
Software*

Substances

DNA Primers