Multiplex PCR Assay Design by Hybrid Multiobjective Evolutionary Algorithm | SpringerLink
Skip to main content

Multiplex PCR Assay Design by Hybrid Multiobjective Evolutionary Algorithm

  • Conference paper
Evolutionary Multi-Criterion Optimization (EMO 2007)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 4403))

Included in the following conference series:

  • 7012 Accesses

Abstract

Multiplex Polymerase Chain Reaction (PCR) assay is to amplify multiple target DNAs simultaneously using different primer pairs for each target DNA. Recently, it is widely used for various biology applications such as genotyping. For sucessful experiments, both the primer pairs for each target DNA and grouping of targets to be actually amplified in one tube should be optimized. This involves multiple conflicting objectives such as minimizing the interaction of primers in a group and minimizing the number of groups required for the assay. Therefore, a multiobjective evolutionary approach may be an appropriate approach. In this paper, a hybrid multiobjective evolutionary algorithm which combines ε-multiobjective evolutionary algorithm with local search is proposed for multiplex PCR assay design. The proposed approach was compared with another multiobjective method, called MuPlex, and showed comparative performance by covering all of the given target sequences.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

Similar content being viewed by others

References

  1. Cortez, A.L.L., Carvalho, A.C., Ikuno, A.A., Bürger, K.P., Vidal-Martins, A.M.C.: Identification of Salmonella spp. isolates from chicken abattoirs by multiplex-PCR. Research in Veterinary Science 81(3), 340–344 (2006)

    Article  Google Scholar 

  2. Aquilante, C.L., Langaee, T.Y., Anderson, P.L., Zineh, I., Fletcher, C.V.: Multiplex PCR-pyrosequencing assay for genotyping CYP3A5 polymorphisms. Clinica Chimica Acta 372(1–2), 195–198 (2006)

    Article  Google Scholar 

  3. Jääskeläinen, A.J., Piiparinen, H., Lappalainen, M., Koskiniemi, M., Antti, V.: Multiplex-PCR and oligonucleotide microarray for detection of eight different herpesviruses from clinical specimens. Journal of Clinical Virology 37(2), 83–90 (2006)

    Article  Google Scholar 

  4. Nicodème, P., Steyaert, J.-M.: Selecting optimal oligonucleotide primers for multiplex PCR. In: Proceedings of the 5th International Conference on Intelligent Systems for Molecular Biology, pp. 210–213 (1997)

    Google Scholar 

  5. Rouchka, E.C., Khalyfa, A., Cooper, N.G.F.: MPrime: efficient large scale multiple primer and oligonucleotide design for customized gene microarrays. BMC Bioinformatics 6(175) (2005)

    Google Scholar 

  6. Schoske, R., Vallone, P.M., Ruitberg, C.M., Butler, J.M.: Multiplex PCR design strategy used for the simultaneous amplification of 10 Y chromosome short tandem repeat (STR) loci. Analytical and Bioanalytical Chemistry 375, 333–343 (2003)

    Google Scholar 

  7. Liang, H.-L., Lee, C., Wu, J.-S.: Multiplex PCR primer design for gene family using genetic algorithm. In: GECCO ’05, Washington, DC, USA, pp. 67–74. ACM Press, New York (2005)

    Chapter  Google Scholar 

  8. Lin, F.-M., Huang, H.-D., Huang, H.-Y., Horng, J.-T.: Primer design for multiplex PCR using a genetic algorithm. In: GECCO ’05, Washington, DC, USA, pp. 475–476. ACM Press, New York (2005)

    Chapter  Google Scholar 

  9. Kaplinski, L., Andreson, P., Puurand, T., Remm, M.: MultiPLX: automatic grouping and evaluation of PCR primers. Bioinformatics 21(8), 1701–1702 (2005)

    Article  Google Scholar 

  10. Rachlin, J., Ding, C., Cantor, C., Kasif, S.: MuPlex: multi-objective multiplex PCR assay design. Nucleic Acids Research 33, W544–W547 (2005)

    Article  Google Scholar 

  11. Lee, C., Wu, J.-S., Shiue, Y.-L., Liang, H.-L.: MultiPrimer: Software for multiple primer design. Applied Bioinformatics 5(2), 99–109 (2006)

    Article  Google Scholar 

  12. Yamada, T., Soma, H., Morishita, S.: PrimerStation: a highly specific multiplex genomic PCR primer design server for the human genome. Nucleic Acids Research 34, W665–W669 (2006)

    Article  Google Scholar 

  13. Rachlin, J., Ding, C., Cantor, C., Kasif, S.: Computational tradeoffs in multiplex PCR assay design for SNP genotyping. BMC Genomics 6(102) (2005)

    Google Scholar 

  14. Garey, M.R., Johnson, D.S.: Computers and Intractability: A Guide to the Theory of NP-completeness. W.H. Freeman and company, New York (1979)

    MATH  Google Scholar 

  15. Laumanns, M., Thiele, L., Deb, K., Zitzler, E.: Combining convergence and diversity in evolutionary multi-objective optimization. Evolutionary Computation 10(3), 263–282 (2002)

    Article  Google Scholar 

  16. Shin, S.-Y., Lee, I.-H., Zhang, B.-T.: Multi-objective evolutionary optimization of DNA sequences for reliable DNA computing. IEEE Transactions on Evolutionary Computation 9(2), 143–158 (2005)

    Article  Google Scholar 

  17. Rozen, S., Skaletsky, H.J.: Primer3 on the www for general users and for biologist programmers. In: Krawetz, S., Misener, S. (eds.) Bioinformatics Methods and Protocols: Methods in Molecular Biology, pp. 365–386. Humana Press, Totowa (2000), Source code available at, http://fokker.wi.mit.edu/primer3/

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Shigeru Obayashi Kalyanmoy Deb Carlo Poloni Tomoyuki Hiroyasu Tadahiko Murata

Rights and permissions

Reprints and permissions

Copyright information

© 2007 Springer Berlin Heidelberg

About this paper

Cite this paper

Lee, IH., Shin, SY., Zhang, BT. (2007). Multiplex PCR Assay Design by Hybrid Multiobjective Evolutionary Algorithm. In: Obayashi, S., Deb, K., Poloni, C., Hiroyasu, T., Murata, T. (eds) Evolutionary Multi-Criterion Optimization. EMO 2007. Lecture Notes in Computer Science, vol 4403. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-70928-2_30

Download citation

  • DOI: https://doi.org/10.1007/978-3-540-70928-2_30

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-70927-5

  • Online ISBN: 978-3-540-70928-2

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics