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Probe selection for DNA microarrays using OligoWiz

Abstract

Nucleotide abundance measurements using DNA microarray technology are possible only if appropriate probes complementary to the target nucleotides can be identified. Here we present a protocol for selecting DNA probes for microarrays using the OligoWiz application. OligoWiz is a client–server application that offers a detailed graphical interface and real-time user interaction on the client side, and massive computer power and a large collection of species databases (400, summer 2007) on the server side. Probes are selected according to five weighted scores: cross-hybridization, ΔTm, folding, position and low-complexity; and probes can be placed with respect to sequence annotation using regular expressions. This protocol provides recommendations related to the design and parameter settings, and it also offers a comprehensive walkthrough of the design steps. The protocol requires limited computer skills and can be executed from any Internet-connected computer. The probe selection procedure for a standard microarray design targeting all yeast transcripts can be completed in 1 h.

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Figure 1: CLN2 profile.
Figure 2: Signal intensity decrease for degenerated short oligonucleotides.
Figure 3: Launching a query.
Figure 4: Main probe selection/inspection interface.
Figure 5: Usage of the species databases.
Figure 6: Avoiding regions with high similarity to other transcripts.
Figure 7: Tm distribution in optimized length intervals of oligonucleotides.
Figure 8: The five position scores in OligoWiz 2.0.
Figure 9
Figure 10: Visualization of the principles behind the probe placement filters in OligoWiz.
Figure 11: Experimental validation of probe quality.

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References

  1. Hekstra, D., Taussig, A.R., Magnasco, M. & Naef, F. Absolute mRNA concentrations from sequence-specific calibration of oligonucleotide arrays. Nucleic Acids Res. 31, 1962–1968 (2003).

    Article  CAS  Google Scholar 

  2. Zhang, L., Miles, M.F. & Aldape, K.D. A model of molecular interactions on short oligonucleotide microarrays. Nat. Biotechnol. 21, 818–821 (2003).

    Article  CAS  Google Scholar 

  3. Wu, Z., Irizarry, R., Gentleman, R., Martinez-Murillo, F. & Spencer, F. A model-based background adjustment for oligonucleotide expression arrays. J. Am. Stat. Assoc. 99, 909 (2004).

    Article  Google Scholar 

  4. Wu, Z. & Irizarry, R.A. Preprocessing of oligonucleotide array data. Nat. Biotechnol. 22, 656–658 (2004).

    Article  CAS  Google Scholar 

  5. Bruun, G.M., Wernersson, R., Juncker, A.S., Willenbrock, H. & Nielsen, H.B. Improving comparability between microarray probe signals by thermodynamic intensity correction. Nucleic Acids Res. 35, e48 (2007).

    Article  Google Scholar 

  6. Leiske, D.L., Karimpour-Fard, A., Hume, P.S., Fairbanks, B.D. & Gill, R.T. A comparison of alternative 60-mer probe designs in an in-situ synthesized oligonucleotide microarray. BMC Genomics 7, 72 (2006).

    Article  Google Scholar 

  7. Eklund, A.C. et al. Replacing cRNA targets with cDNA reduces microarray cross-hybridization. Nat. Biotechnol. 24, 1071–1073 (2006).

    Article  CAS  Google Scholar 

  8. SantaLucia, J. Jr. A unified view of polymer, dumbbell, and oligonucleotide DNA nearest-neighbor thermodynamics. Proc. Natl. Acad. Sci. USA 95, 1460–1465 (1998).

    Article  CAS  Google Scholar 

  9. Mei, R. et al. Probe selection for high-density oligonucleotide arrays. Proc. Natl. Acad. Sci. USA 100, 11237–11242 (2003).

    Article  CAS  Google Scholar 

  10. Naef, F. & Magnasco, M.O. Solving the riddle of the bright mismatches: labeling and effective binding in oligonucleotide arrays. Phys. Rev. E Stat. Nonlin. Soft Matter Phys. 68 (1 Pt 1): 011906 (2003).

    Article  Google Scholar 

  11. Hughes, T.R. et al. Expression profiling using microarrays fabricated by an ink-jet oligonucleotide synthesizer. Nat. Biotechnol. 19, 342–347 (2001).

    Article  CAS  Google Scholar 

  12. He, Z., Wu, L., Li, X., Fields, M.W. & Zhou, J. Empirical establishment of oligonucleotide probe design criteria. Appl. Environ. Microbiol. 71, 3753–3760 (2005).

    Article  CAS  Google Scholar 

  13. Kane, M.D. et al. Assessment of the sensitivity and specificity of oligonucleotide (50mer) microarrays. Nucleic Acids Res. 28, 4552–4557 (2000).

    Article  CAS  Google Scholar 

  14. Marcelino, L.A. et al. Accurately quantifying low-abundant targets amid similar sequences by revealing hidden correlations in oligonucleotide microarray data. Proc. Natl. Acad. Sci. USA 103, 13629–13634 (2006).

    Article  CAS  Google Scholar 

  15. Shchepinov, M.S., Case-Green, S.C. & Southern, E.M. Steric factors influencing hybridisation of nucleic acids to oligonucleotide arrays. Nucleic Acids Res. 25, 1155–1161 (1997).

    Article  CAS  Google Scholar 

  16. Vainrub, A. & Pettitt, B.M. Surface electrostatic effects in oligonucleotide microarrays: control and optimization of binding thermodynamics. Biopolymers 68, 265–270 (2003).

    Article  CAS  Google Scholar 

  17. Duggan, D.J., Bittner, M., Chen, Y., Meltzer, P. & Trent, J.M. Expression profiling using cDNA microarrays. Nat. Genet. 21, 10–14 (1999).

    Article  CAS  Google Scholar 

  18. Devoe, H. & Tinoco, I. Jr. The stability of helical polynucleotides: base contributions. J. Mol. Biol. 4, 500–517 (1962).

    Article  CAS  Google Scholar 

  19. Crothers, D.M. & Zimm, B.H. Theory of the melting transition of synthetic polynucleotides: evaluation of the stacking free energy. J. Mol. Biol. 116, 1–9 (1964).

    Article  Google Scholar 

  20. Gray, D.M. & Tinoco, I. Jr. A new approach to the study of sequence-dependent properties of polynucleotides. Biopolymers 9, 223–244 (1970).

    Article  CAS  Google Scholar 

  21. Tinoco, I. Jr. et al. Improved estimation of secondary structure in ribonucleic acids. Nat. New Biol. 246, 40–41 (1973).

    Article  CAS  Google Scholar 

  22. Uhlenbeck, O.C., Borer, P.N., Dengler, B. & Tinoco, I. Jr. Stability of RNA hairpin loops: A 6 -C m -U 6. J. Mol. Biol. 73, 483–496 (1973).

    Article  CAS  Google Scholar 

  23. Borer, P.N., Dengler, B., Tinoco, I. Jr. & Uhlenbeck, O.C. Stability of ribonucleic acid double-stranded helices. J. Mol. Biol. 86, 843–853 (1974).

    Article  CAS  Google Scholar 

  24. Chou, C.C., Chen, C.H., Lee, T.T. & Peck, K. Optimization of probe length and the number of probes per gene for optimal microarray analysis of gene expression. Nucleic Acids Res. 32, e99 (2004).

    Article  Google Scholar 

  25. Nielsen, H.B., Wernersson, R. & Knudsen, S. Design of oligonucleotides for microarrays and perspectives for design of multi-transcriptome arrays. Nucleic Acids Res. 31, 3491–3496 (2003).

    Article  CAS  Google Scholar 

  26. Wernersson, R. & Nielsen, H.B. OligoWiz 2.0—integrating sequence feature annotation into the design of microarray probes. Nucleic Acids Res. 33, W611–W615 (2005).

    Article  CAS  Google Scholar 

  27. Pontius JU, W.L. Schuler GD UniGene: a unified view of the transcriptome. The NCBI Handbook. (The National Center for Biotechnology Information).

  28. Altschul, S.F., Gish, W., Miller, W., Myers, E.W. & Lipman, D.J. Basic local alignment search tool. J. Mol. Biol. 215, 403–410 (1990).

    Article  CAS  Google Scholar 

  29. Altschul, S.F. et al. Gapped BLAST and PSI-BLAST: a new generation of protein database search programs. Nucleic Acids Res. 25, 3389–3402 (1997).

    Article  CAS  Google Scholar 

  30. Bonnet, G., Tyagi, S., Libchaber, A. & Kramer, F.R. Thermodynamic basis of the enhanced specificity of structured DNA probes. Proc. Natl. Acad. Sci. USA 96, 6171–6176 (1999).

    Article  CAS  Google Scholar 

  31. Nguyen, H.K. & Southern, E.M. Minimising the secondary structure of DNA targets by incorporation of a modified deoxynucleoside: implications for nucleic acid analysis by hybridisation. Nucleic Acids Res. 28, 3904–3909 (2000).

    Article  CAS  Google Scholar 

  32. Zuker, M. On finding all suboptimal foldings of an RNA molecule. Science 244, 48–52 (1989).

    Article  CAS  Google Scholar 

  33. Workman, C. et al. A new non-linear normalization method for reducing variability in DNA microarray experiments. Genome Biol. 3 research0048 (2002).

  34. Sugimoto, N. et al. Thermodynamic parameters to predict stability of RNA/DNA hybrid duplexes. Biochemistry 34, 11211–11216 (1995).

    Article  CAS  Google Scholar 

  35. Willenbrock, H. et al. Design of a seven-genome Escherichia coli microarray for comparative genomic profiling. J. Bacteriol. 188, 7713–7721 (2006).

    Article  CAS  Google Scholar 

  36. de Lichtenberg, U. et al. New weakly expressed cell cycle-regulated genes in yeast. Yeast 22, 1191–1201 (2005).

    Article  CAS  Google Scholar 

  37. Mogensen, J., Nielsen, H.B., Hofmann, G. & Nielsen, J. Transcription analysis using high-density micro-arrays of Aspergillus nidulans wild-type and creA mutant during growth on glucose or ethanol. Fungal Genet. Biol. 43, 593–603 (2006).

    Article  CAS  Google Scholar 

  38. Garrigues, C., Lauridsen, B.S. & Johansen, E. Characterisation of Bifidobacterium animalis subsp. lactis BB-12 and other probiotic bacteria using genomics, transcriptomics and proteomics (keynote address). Austr. J. Dairy Technol. 60, 84–92 (2005).

    CAS  Google Scholar 

  39. Pedersen, M.B., Iversen, S.L., Sørensen, K.I. & Johansen, E. The long and winding road from the research laboratory to industrial applications of lactic acid bacteria. FEMS Microbiol. Rev. 29, 611–624 (2005).

    Article  CAS  Google Scholar 

  40. Benson, D.A., Karsch-Mizrachi, I., Lipman, D.J., Ostell, J. & Wheeler, D.L. GenBank. Nucleic Acids Res. 35, D21–D25 (2007).

    Article  CAS  Google Scholar 

  41. Wernersson, R. FeatureExtract—extraction of sequence annotation made easy. Nucleic Acids Res. 33, W567–W569 (2005).

    Article  CAS  Google Scholar 

  42. Rouillard, J.M., Herbert, C.J. & Zuker, M. OligoArray: genome-scale oligonucleotide design for microarrays. Bioinformatics 18, 486–487 (2002).

    Article  CAS  Google Scholar 

  43. Rouillard, J.M., Zuker, M. & Gulari, E. OligoArray 2.0: design of oligonucleotide probes for DNA microarrays using a thermodynamic approach. Nucleic Acids Res 31, 3057–3062 (2003).

    Article  CAS  Google Scholar 

  44. Mrowka, R., Schuchhardt, J. & Gille, C. Oligodb—interactive design of oligo DNA for transcription profiling of human genes. Bioinformatics 18, 1686–1687 (2002).

    Article  CAS  Google Scholar 

  45. Wang, X. & Seed, B. Selection of oligonucleotide probes for protein coding sequences. Bioinformatics 19, 796–802 (2003).

    Article  CAS  Google Scholar 

  46. Bozdech, Z. et al. Expression profiling of the schizont and trophozoite stages of Plasmodium falciparum with a long-oligonucleotide microarray. Genome Biol 4, R9 (2003).

    Article  Google Scholar 

  47. Chen, H. & Sharp, B.M. Oliz, a suite of Perl scripts that assist in the design of microarrays using 50mer oligonucleotides from the 3′ untranslated region. BMC Bioinformatics 3, 27 (2002).

    Article  Google Scholar 

  48. Reymond, N. et al. ROSO: optimizing oligonucleotide probes for microarrays. Bioinformatics 20, 271–273 (2004).

    Article  CAS  Google Scholar 

  49. Chou, H.H., Hsia, A.P., Mooney, D.L. & Schnable, P.S. Picky: oligo microarray design for large genomes. Bioinformatics 20, 2893–2902 (2004).

    Article  CAS  Google Scholar 

  50. Nordberg, E.K. YODA: selecting signature oligonucleotides. Bioinformatics 21, 1365–1370 (2005).

    Article  CAS  Google Scholar 

  51. Li, C. & Wong, W.H. Model-based analysis of oligonucleotide arrays: expression index computation and outlier detection. Proc. Natl. Acad. Sci. USA 98, 31–36 (2001).

    Article  CAS  Google Scholar 

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Correspondence to Rasmus Wernersson.

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Wernersson, R., Juncker, A. & Nielsen, H. Probe selection for DNA microarrays using OligoWiz. Nat Protoc 2, 2677–2691 (2007). https://doi.org/10.1038/nprot.2007.370

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