EvoOligo: Oligonucleotide Probe Design With Multiobjective Evolutionary Algorithms

Probe design is one of the most important tasks in successful deoxyribonucleic acid microarray experiments. We propose a multiobjective evolutionary optimization method for oligonucleotide probe design based on the multiobjective nature of the probe design problem. The proposed multiobjective evolutionary approach has several distinguished features, compared with previous methods. First, the evolutionary approach can find better probe sets than existing simple filtering methods with fixed threshold values. Second, the multiobjective approach can easily incorporate the user's custom criteria or change the existing criteria. Third, our approach tries to optimize the combination of probes for the given set of genes, in contrast to other tools that independently search each gene for qualifying probes. Lastly, the multiobjective optimization method provides various sets of probe combinations, among which the user can choose, depending on the target application. The proposed method is implemented as a platform called EvoOligo and is available for service on the Web. We test the performance of EvoOligo by designing probe sets for 19 types of Human Papillomavirus and 52 genes in the Arabidopsis Calmodulin multigene family. The design results from EvoOligo are proven to be superior to those from well-known existing probe design tools, such as OligoArray and OligoWiz.

[1]  Jungwon Yoon,et al.  The Arabidopsis Information Resource (TAIR): a model organism database providing a centralized, curated gateway to Arabidopsis biology, research materials and community , 2003, Nucleic Acids Res..

[2]  Kalyanmoy Deb,et al.  Towards a Quick Computation of Well-Spread Pareto-Optimal Solutions , 2003, EMO.

[3]  M. Zuker,et al.  OligoArray 2.0: design of oligonucleotide probes for DNA microarrays using a thermodynamic approach. , 2003, Nucleic acids research.

[4]  Yu-Chang Tsai,et al.  Handling calcium signaling: Arabidopsis CaMs and CMLs. , 2005, Trends in plant science.

[5]  J. SantaLucia,et al.  A unified view of polymer, dumbbell, and oligonucleotide DNA nearest-neighbor thermodynamics. , 1998, Proceedings of the National Academy of Sciences of the United States of America.

[6]  Byoung-Tak Zhang,et al.  Multiobjective evolutionary optimization of DNA sequences for reliable DNA computing , 2005, IEEE Transactions on Evolutionary Computation.

[7]  R. Drmanac,et al.  Gene-representing cDNA clusters defined by hybridization of 57,419 clones from infant brain libraries with short oligonucleotide probes. , 1996, Genomics.

[8]  Byoung-Tak Zhang,et al.  Multiplex PCR Assay Design by Hybrid Multiobjective Evolutionary Algorithm , 2006, EMO.

[9]  Xiaowei Wang,et al.  Selection of Oligonucleotide Probes for Protein Coding Sequences , 2003, Bioinform..

[10]  Byoung-Tak Zhang,et al.  Microarray Probe Design Using epsilon-Multi-Objective Evolutionary Algorithms with Thermodynamic Criteria , 2006, EvoWorkshops.

[11]  Michael Zuker,et al.  Mfold web server for nucleic acid folding and hybridization prediction , 2003, Nucleic Acids Res..

[12]  Hans Lehrach,et al.  Information theoretical probe selection for hybridisation experiments , 2000, Bioinform..

[13]  Christoph W Sensen,et al.  Osprey: a comprehensive tool employing novel methods for the design of oligonucleotides for DNA sequencing and microarrays. , 2004, Nucleic acids research.

[14]  Gary D. Stormo,et al.  Selection of optimal DNA oligos for gene expression arrays , 2001, Bioinform..

[15]  W. J. Kent,et al.  BLAT--the BLAST-like alignment tool. , 2002, Genome research.

[16]  Jizhong Zhou,et al.  Empirical Establishment of Oligonucleotide Probe Design Criteria , 2005, Applied and Environmental Microbiology.

[17]  S Rozen,et al.  Primer3 on the WWW for general users and for biologist programmers. , 2000, Methods in molecular biology.

[18]  J. Peto,et al.  Human papillomavirus is a necessary cause of invasive cervical cancer worldwide , 1999, The Journal of pathology.

[19]  Chunlei Wu,et al.  Sequence dependence of cross-hybridization on short oligo microarrays , 2005, Nucleic acids research.

[20]  Marco Laumanns,et al.  Combining Convergence and Diversity in Evolutionary Multiobjective Optimization , 2002, Evolutionary Computation.

[21]  Henrik Bjørn Nielsen,et al.  OligoWiz 2.0—integrating sequence feature annotation into the design of microarray probes , 2005, Nucleic Acids Res..

[22]  Rodrigo Lopez,et al.  Multiple sequence alignment with the Clustal series of programs , 2003, Nucleic Acids Res..

[23]  A D Tsodikov,et al.  Thermodynamic calculations and statistical correlations for oligo-probes design. , 2003, Nucleic acids research.

[24]  R. K. Ursem.  Multi-objective Optimization using Evolutionary Algorithms , 2009 .

[25]  Byoung-Tak Zhang,et al.  EXPERIMENTAL ANALYSIS OF 2-MULTIOBJECTIVE EVOLUTIONARY ALGORITHM , 2004 .

[26]  Anireddy S N Reddy,et al.  Genes Encoding Calmodulin-binding Proteins in the Arabidopsis Genome* 210 , 2002, The Journal of Biological Chemistry.