Probe Selection for Pathway-Specific Microarray Probe Design Minimizing Melting Temperature Variance
In molecular biology, microarray technology is widely and successfully utilized to efficiently measure gene activity. If working with less studied organisms, methods to design custom-made microarray probes are available. One design criterion is to select probes with minimal melting temperature variances thus ensuring similar hybridization properties. If the microarray application focuses on the investigation of metabolic pathways, it is not necessary to cover the whole genome. It is more efficient to cover each metabolic pathway with a limited number of genes. Firstly, an approach is presented which minimizes the overall melting temperature variance of selected probes for all genes of interest. Secondly, the approach is extended to include the additional constraints of covering all pathways with a limited number of genes while minimizing the overall variance. The new optimization problem is solved by a bottom-up programming approach which reduces the complexity to make it computationally feasible. The new method is exemplary applied for the selection of microarray probes in order to cover all fungal secondary metabolite gene clusters for Aspergillus terreus.
[1] P. A. Jensen and J. A. Papin, "Functional integration of a metabolic
network model and expression data without arbitrary thresholding."
Bioinformatics, vol. 27, no. 4, pp. 541-547, Feb 2011. (Online).
Available: http://dx.doi.org/10.1093/bioinformatics/btq702
[2] J.-M. Schwartz, C. Gaugain, J. C. Nacher, A. de Daruvar, and
M. Kanehisa, "Observing metabolic functions at the genome scale."
Genome Biol, vol. 8, no. 6, p. R123, 2007. (Online). Available:
http://dx.doi.org/10.1186/gb-2007-8-6-r123
[3] S. Lemoine, F. Combes, and S. L. Crom, "An evaluation of custom
microarray applications: the oligonucleotide design challenge." Nucleic
Acids Res, vol. 37, no. 6, pp. 1726-1739, Apr 2009. (Online).
Available: http://dx.doi.org/10.1093/nar/gkp053
[4] J. SantaLucia and D. H. Turner, "Measuring the thermodynamics of
RNA secondary structure formation." Biopolymers, vol. 44, no. 3, pp.
309-319, 1997. (Online). Available: http://dx.doi.org/3.0.CO;2-Z
[5] N. L. Nov`ere, "MELTING, computing the melting temperature of
nucleic acid duplex." Bioinformatics, vol. 17, no. 12, pp. 1226-1227,
Dec 2001.
[6] S. Graf, F. G. G. Nielsen, S. Kurtz, M. A. Huynen, E. Birney,
H. Stunnenberg, and P. Flicek, "Optimized design and assessment
of whole genome tiling arrays." Bioinformatics, vol. 23, no. 13,
pp. i195-i204, Jul 2007. (Online). Available: http://dx.doi.org/10.1093/
bioinformatics/btm200
[7] L. Jourdren, A. Duclos, C. Brion, T. Portnoy, H. Mathis, A. Margeot,
and S. L. Crom, "Teolenn: an efficient and customizable workflow
to design high-quality probes for microarray experiments." Nucleic
Acids Res, vol. 38, no. 10, p. e117, Jun 2010. (Online). Available:
http://dx.doi.org/10.1093/nar/gkq110
[8] F. Horn, H.-W. Nutzmann, V. Schroeckh, R. Guthke, and C. Hummert,
"Optimization of a microarray probe design focusing on the minimization
of cross-hybridization," in Proceedings of the International Conference
on Bioinformatics and Computational Biology (BIOCOMP-11),
H. R. Arabnia and Quoc-Nam, Eds., 2011, ISBN: 1-60132-172-4.
[9] H.-W. Nutzmann, Y. Reyes-Dominguez, K. Scherlach, V. Schroeckh,
F. Horn, A. Gacek, J. Schumann, C. Hertweck, J. Strauss, and A. A.
Brakhage, "Bacteria-induced natural product formation in the fungus
Aspergillus nidulans requires Saga/Ada-mediated histone acetylation."
Proc Natl Acad Sci U S A, vol. 108, no. 34, pp. 14 282-14 287, Aug
2011. (Online). Available: http://dx.doi.org/10.1073/pnas.1103523108
[10] F. Bidard, S. Imbeaud, N. Reymond, O. Lespinet, P. Silar,
C. Clav'e, H. Delacroix, V. Berteaux-Lecellier, and R. Debuchy, "A
general framework for optimization of probes for gene expression
microarray and its application to the fungus Podospora anserina."
BMC Res Notes, vol. 3, p. 171, 2010. (Online). Available:
http://dx.doi.org/10.1186/1756-0500-3-171
[11] R. Wernersson and H. B. Nielsen, "OligoWiz 2.0-integrating sequence
feature annotation into the design of microarray probes." Nucleic
Acids Res, vol. 33, no. Web Server issue, pp. W611-W615, Jul 2005.
(Online). Available: http://dx.doi.org/10.1093/nar/gki399
[12] A. A. Brakhage and V. Schroeckh, "Fungal secondary metabolites
- strategies to activate silent gene clusters." Fungal Genet Biol,
vol. 48, no. 1, pp. 15-22, Jan 2011. (Online). Available: http:
//dx.doi.org/10.1016/j.fgb.2010.04.004
[13] N. Khaldi, F. T. Seifuddin, G. Turner, D. Haft, W. C. Nierman,
K. H. Wolfe, and N. D. Fedorova, "SMURF: Genomic mapping
of fungal secondary metabolite clusters." Fungal Genet Biol,
vol. 47, no. 9, pp. 736-741, Sep 2010. (Online). Available:
http://dx.doi.org/10.1016/j.fgb.2010.06.003
[14] G. Bhanot, Y. Louzoun, J. Zhu, and C. DeLisi, "The importance
of thermodynamic equilibrium for high throughput gene expression
arrays." Biophys J, vol. 84, no. 1, pp. 124-135, Jan 2003. (Online).
Available: http://dx.doi.org/10.1016/S0006-3495(03)74837-1
[1] P. A. Jensen and J. A. Papin, "Functional integration of a metabolic
network model and expression data without arbitrary thresholding."
Bioinformatics, vol. 27, no. 4, pp. 541-547, Feb 2011. (Online).
Available: http://dx.doi.org/10.1093/bioinformatics/btq702
[2] J.-M. Schwartz, C. Gaugain, J. C. Nacher, A. de Daruvar, and
M. Kanehisa, "Observing metabolic functions at the genome scale."
Genome Biol, vol. 8, no. 6, p. R123, 2007. (Online). Available:
http://dx.doi.org/10.1186/gb-2007-8-6-r123
[3] S. Lemoine, F. Combes, and S. L. Crom, "An evaluation of custom
microarray applications: the oligonucleotide design challenge." Nucleic
Acids Res, vol. 37, no. 6, pp. 1726-1739, Apr 2009. (Online).
Available: http://dx.doi.org/10.1093/nar/gkp053
[4] J. SantaLucia and D. H. Turner, "Measuring the thermodynamics of
RNA secondary structure formation." Biopolymers, vol. 44, no. 3, pp.
309-319, 1997. (Online). Available: http://dx.doi.org/3.0.CO;2-Z
[5] N. L. Nov`ere, "MELTING, computing the melting temperature of
nucleic acid duplex." Bioinformatics, vol. 17, no. 12, pp. 1226-1227,
Dec 2001.
[6] S. Graf, F. G. G. Nielsen, S. Kurtz, M. A. Huynen, E. Birney,
H. Stunnenberg, and P. Flicek, "Optimized design and assessment
of whole genome tiling arrays." Bioinformatics, vol. 23, no. 13,
pp. i195-i204, Jul 2007. (Online). Available: http://dx.doi.org/10.1093/
bioinformatics/btm200
[7] L. Jourdren, A. Duclos, C. Brion, T. Portnoy, H. Mathis, A. Margeot,
and S. L. Crom, "Teolenn: an efficient and customizable workflow
to design high-quality probes for microarray experiments." Nucleic
Acids Res, vol. 38, no. 10, p. e117, Jun 2010. (Online). Available:
http://dx.doi.org/10.1093/nar/gkq110
[8] F. Horn, H.-W. Nutzmann, V. Schroeckh, R. Guthke, and C. Hummert,
"Optimization of a microarray probe design focusing on the minimization
of cross-hybridization," in Proceedings of the International Conference
on Bioinformatics and Computational Biology (BIOCOMP-11),
H. R. Arabnia and Quoc-Nam, Eds., 2011, ISBN: 1-60132-172-4.
[9] H.-W. Nutzmann, Y. Reyes-Dominguez, K. Scherlach, V. Schroeckh,
F. Horn, A. Gacek, J. Schumann, C. Hertweck, J. Strauss, and A. A.
Brakhage, "Bacteria-induced natural product formation in the fungus
Aspergillus nidulans requires Saga/Ada-mediated histone acetylation."
Proc Natl Acad Sci U S A, vol. 108, no. 34, pp. 14 282-14 287, Aug
2011. (Online). Available: http://dx.doi.org/10.1073/pnas.1103523108
[10] F. Bidard, S. Imbeaud, N. Reymond, O. Lespinet, P. Silar,
C. Clav'e, H. Delacroix, V. Berteaux-Lecellier, and R. Debuchy, "A
general framework for optimization of probes for gene expression
microarray and its application to the fungus Podospora anserina."
BMC Res Notes, vol. 3, p. 171, 2010. (Online). Available:
http://dx.doi.org/10.1186/1756-0500-3-171
[11] R. Wernersson and H. B. Nielsen, "OligoWiz 2.0-integrating sequence
feature annotation into the design of microarray probes." Nucleic
Acids Res, vol. 33, no. Web Server issue, pp. W611-W615, Jul 2005.
(Online). Available: http://dx.doi.org/10.1093/nar/gki399
[12] A. A. Brakhage and V. Schroeckh, "Fungal secondary metabolites
- strategies to activate silent gene clusters." Fungal Genet Biol,
vol. 48, no. 1, pp. 15-22, Jan 2011. (Online). Available: http:
//dx.doi.org/10.1016/j.fgb.2010.04.004
[13] N. Khaldi, F. T. Seifuddin, G. Turner, D. Haft, W. C. Nierman,
K. H. Wolfe, and N. D. Fedorova, "SMURF: Genomic mapping
of fungal secondary metabolite clusters." Fungal Genet Biol,
vol. 47, no. 9, pp. 736-741, Sep 2010. (Online). Available:
http://dx.doi.org/10.1016/j.fgb.2010.06.003
[14] G. Bhanot, Y. Louzoun, J. Zhu, and C. DeLisi, "The importance
of thermodynamic equilibrium for high throughput gene expression
arrays." Biophys J, vol. 84, no. 1, pp. 124-135, Jan 2003. (Online).
Available: http://dx.doi.org/10.1016/S0006-3495(03)74837-1
@article{"International Journal of Biological, Life and Agricultural Sciences:53531", author = "Fabian Horn and Reinhard Guthke", title = "Probe Selection for Pathway-Specific Microarray Probe Design Minimizing Melting Temperature Variance", abstract = "In molecular biology, microarray technology is widely and successfully utilized to efficiently measure gene activity. If working with less studied organisms, methods to design custom-made microarray probes are available. One design criterion is to select probes with minimal melting temperature variances thus ensuring similar hybridization properties. If the microarray application focuses on the investigation of metabolic pathways, it is not necessary to cover the whole genome. It is more efficient to cover each metabolic pathway with a limited number of genes. Firstly, an approach is presented which minimizes the overall melting temperature variance of selected probes for all genes of interest. Secondly, the approach is extended to include the additional constraints of covering all pathways with a limited number of genes while minimizing the overall variance. The new optimization problem is solved by a bottom-up programming approach which reduces the complexity to make it computationally feasible. The new method is exemplary applied for the selection of microarray probes in order to cover all fungal secondary metabolite gene clusters for Aspergillus terreus.
", keywords = "bottom-up approach, gene clusters, melting temperature,
metabolic pathway, microarray probe design, probe selection", volume = "6", number = "3", pages = "64-6", }
