Primer Design with Specific PCR Product using Particle Swarm Optimization
Before performing polymerase chain reactions (PCR), a feasible primer set is required. Many primer design methods have been proposed for design a feasible primer set. However, the majority of these methods require a relatively long time to obtain an optimal solution since large quantities of template DNA need to be analyzed. Furthermore, the designed primer sets usually do not provide a specific PCR product. In recent years, evolutionary computation has been applied to PCR primer design and yielded promising results. In this paper, a particle swarm optimization (PSO) algorithm is proposed to solve primer design problems associated with providing a specific product for PCR experiments. A test set of the gene CYP1A1, associated with a heightened lung cancer risk was analyzed and the comparison of accuracy and running time with the genetic algorithm (GA) and memetic algorithm (MA) was performed. A comparison of results indicated that the proposed PSO method for primer design finds optimal or near-optimal primer sets and effective PCR products in a relatively short time.
[1] K. B. Mullis and F. A. Faloona, "Specific synthesis of DNA in vitro via a
polymerase-catalyzed chain reaction," Methods Enzymol, vol. 155, pp.
335-50, 1987.
[2] T. Kämpke, M. Kieninger, and M. Mecklenburg, "Efficient primer
design algorithms," Bioinformatics, vol. 17, pp. 214-25, Mar 2001.
[3] S. H. Chen, C. Y. Lin, C. S. Cho, C. Z. Lo, and C. A. Hsiung, "Primer
Design Assistant (PDA): A web-based primer design tool," Nucleic
Acids Res, vol. 31, pp. 3751-4, Jul 1 2003.
[4] M. H. Hsieh, W. C. Hsu, S. K. Chiu, and C. M. Tzeng, "An efficient
algorithm for minimal primer set selection," Bioinformatics, vol. 19, pp.
285-6, Jan 22 2003.
[5] J. Wang, K. B. Li, and W. K. Sung, "G-PRIMER: greedy algorithm for
selecting minimal primer set," Bioinformatics, vol. 20, pp. 2473-5, Oct
12 2004.
[6] J. S. Wu, C. Lee, C. C. Wu, and Y. L. Shiue, "Primer design using genetic
algorithm," Bioinformatics, vol. 20, pp. 1710-7, Jul 22 2004.
[7] F. Miura, C. Uematsu, Y. Sakaki, and T. Ito, "A novel strategy to design
highly specific PCR primers based on the stability and uniqueness of
3'-end subsequences," Bioinformatics, vol. 21, pp. 4363-70, Dec 15
2005.
[8] W. Qu, Z. Shen, D. Zhao, Y. Yang, and C. Zhang, "MFEprimer: multiple
factor evaluation of the specificity of PCR primers," Bioinformatics, vol.
25, pp. 276-8, Jan 15 2009.
[9] J. Kennedy and R. Eberhart, "Particle swarm optimization." vol. 4, 1995.
[10] J. Kennedy and R. C. Eberhart, "A discrete binary version of the particle
swarm algorithm." vol. 5, 1997.
[11] J. F. Kennedy, R. C. Eberhart, Y. Shi, and ScienceDirect, Swarm
intelligence: Springer, 2001.
[12] R. B. Wallace, J. Shaffer, R. F. Murphy, J. Bonner, T. Hirose, and K.
Itakura, "Hybridization of synthetic oligodeoxyribonucleotides to phi chi
174 DNA: the effect of single base pair mismatch," Nucleic Acids Res,
vol. 6, pp. 3543-57, Aug 10 1979.
[13] E. T. Bolton and B. J. McCarthy, "A General Method for the Isolation of
RNA Complementary to DNA." vol. 48: National Acad Sciences, 1962,
pp. 1390-1397.
[14] E. Elbeltagi, T. Hegazy, and D. Grierson, "Comparison among five
evolutionary-based optimization algorithms." vol. 19: Elsevier, 2005, pp.
43-53.
[15] I. S. Oh, J. S. Lee, and B. R. Moon, "Hybrid genetic algorithms for
feature selection," IEEE Trans Pattern Anal Mach Intell, vol. 26, pp.
1424-37, Nov 2004.
[16] X. H. Shi, Y. C. Liang, H. P. Lee, C. Lu, and L. M. Wang, "An improved
GA and a novel PSO-GA-based hybrid algorithm." vol. 93: Elsevier,
2005, pp. 255-261.
[17] Y. Rahmat-Samii, "Genetic algorithm (GA) and particle swarm
optimization (PSO) in engineering electromagnetics," 2003, pp. 1-5.
[1] K. B. Mullis and F. A. Faloona, "Specific synthesis of DNA in vitro via a
polymerase-catalyzed chain reaction," Methods Enzymol, vol. 155, pp.
335-50, 1987.
[2] T. Kämpke, M. Kieninger, and M. Mecklenburg, "Efficient primer
design algorithms," Bioinformatics, vol. 17, pp. 214-25, Mar 2001.
[3] S. H. Chen, C. Y. Lin, C. S. Cho, C. Z. Lo, and C. A. Hsiung, "Primer
Design Assistant (PDA): A web-based primer design tool," Nucleic
Acids Res, vol. 31, pp. 3751-4, Jul 1 2003.
[4] M. H. Hsieh, W. C. Hsu, S. K. Chiu, and C. M. Tzeng, "An efficient
algorithm for minimal primer set selection," Bioinformatics, vol. 19, pp.
285-6, Jan 22 2003.
[5] J. Wang, K. B. Li, and W. K. Sung, "G-PRIMER: greedy algorithm for
selecting minimal primer set," Bioinformatics, vol. 20, pp. 2473-5, Oct
12 2004.
[6] J. S. Wu, C. Lee, C. C. Wu, and Y. L. Shiue, "Primer design using genetic
algorithm," Bioinformatics, vol. 20, pp. 1710-7, Jul 22 2004.
[7] F. Miura, C. Uematsu, Y. Sakaki, and T. Ito, "A novel strategy to design
highly specific PCR primers based on the stability and uniqueness of
3'-end subsequences," Bioinformatics, vol. 21, pp. 4363-70, Dec 15
2005.
[8] W. Qu, Z. Shen, D. Zhao, Y. Yang, and C. Zhang, "MFEprimer: multiple
factor evaluation of the specificity of PCR primers," Bioinformatics, vol.
25, pp. 276-8, Jan 15 2009.
[9] J. Kennedy and R. Eberhart, "Particle swarm optimization." vol. 4, 1995.
[10] J. Kennedy and R. C. Eberhart, "A discrete binary version of the particle
swarm algorithm." vol. 5, 1997.
[11] J. F. Kennedy, R. C. Eberhart, Y. Shi, and ScienceDirect, Swarm
intelligence: Springer, 2001.
[12] R. B. Wallace, J. Shaffer, R. F. Murphy, J. Bonner, T. Hirose, and K.
Itakura, "Hybridization of synthetic oligodeoxyribonucleotides to phi chi
174 DNA: the effect of single base pair mismatch," Nucleic Acids Res,
vol. 6, pp. 3543-57, Aug 10 1979.
[13] E. T. Bolton and B. J. McCarthy, "A General Method for the Isolation of
RNA Complementary to DNA." vol. 48: National Acad Sciences, 1962,
pp. 1390-1397.
[14] E. Elbeltagi, T. Hegazy, and D. Grierson, "Comparison among five
evolutionary-based optimization algorithms." vol. 19: Elsevier, 2005, pp.
43-53.
[15] I. S. Oh, J. S. Lee, and B. R. Moon, "Hybrid genetic algorithms for
feature selection," IEEE Trans Pattern Anal Mach Intell, vol. 26, pp.
1424-37, Nov 2004.
[16] X. H. Shi, Y. C. Liang, H. P. Lee, C. Lu, and L. M. Wang, "An improved
GA and a novel PSO-GA-based hybrid algorithm." vol. 93: Elsevier,
2005, pp. 255-261.
[17] Y. Rahmat-Samii, "Genetic algorithm (GA) and particle swarm
optimization (PSO) in engineering electromagnetics," 2003, pp. 1-5.
@article{"International Journal of Electrical, Electronic and Communication Sciences:55415", author = "Cheng-Hong Yang and Yu-Huei Cheng and Hsueh-Wei Chang and Li-Yeh Chuang", title = "Primer Design with Specific PCR Product using Particle Swarm Optimization", abstract = "Before performing polymerase chain reactions (PCR), a feasible primer set is required. Many primer design methods have been proposed for design a feasible primer set. However, the majority of these methods require a relatively long time to obtain an optimal solution since large quantities of template DNA need to be analyzed. Furthermore, the designed primer sets usually do not provide a specific PCR product. In recent years, evolutionary computation has been applied to PCR primer design and yielded promising results. In this paper, a particle swarm optimization (PSO) algorithm is proposed to solve primer design problems associated with providing a specific product for PCR experiments. A test set of the gene CYP1A1, associated with a heightened lung cancer risk was analyzed and the comparison of accuracy and running time with the genetic algorithm (GA) and memetic algorithm (MA) was performed. A comparison of results indicated that the proposed PSO method for primer design finds optimal or near-optimal primer sets and effective PCR products in a relatively short time.
", keywords = "polymerase chain reaction (PCR), primer design,
evolutionary computation, particle swarm optimization (PSO).", volume = "3", number = "5", pages = "1144-6", }
