UPS 2.0: unique probe selector for probe design and oligonucleotide microarrays at the pangenomic/ genomic level

BackgroundNucleic acid hybridization is an extensively adopted principle in biomedical research, in which the performance of any hybridization-based method depends on the specificity of probes to their targets. To determine the optimal probe(s) for detecting target(s) from a sample cocktail, we developed a novel algorithm, which has been implemented into a web platform for probe designing. This probe design workflow is now upgraded to satisfy experiments that require a probe designing tool to take the increasing volume of sequence datasets.ResultsAlgorithms and probe parameters applied in UPS 2.0 include GC content, the secondary structure, melting temperature (Tm), the stability of the probe-target duplex estimated by the thermodynamic model, sequence complexity, similarity of probes to non-target sequences, and other empirical parameters used in the laboratory. Several probe background options,Unique probe within a group,Unique probe in a specific Unigene set,Unique probe based onthe pangenomic level, and Unique Probe in the user-defined genome/transcriptome, are available to meet the scenarios that the experiments will be conducted. Parameters, such as salt concentration and the lower-bound Tm of probes, are available for users to optimize their probe design query. Output files are available for download on the result page. Probes designed by the UPS algorithm are suitable for generating microarrays, and the performance of UPS-designed probes has been validated by experiments.ConclusionsThe UPS 2.0 evaluates probe-to-target hybridization under a user-defined condition to ensure high-performance hybridization with minimal chance of non-specific binding at the pangenomic and genomic levels. The UPS algorithm mimics the target/non-target mixture in an experiment and is very useful in developing diagnostic kits and microarrays. The UPS 2.0 website has had more than 1,300 visits and 360,000 sequences performed the probe designing task in the last 30 months. It is freely accessible at http://array.iis.sinica.edu.tw/ups/.Screen cast: http://array.iis.sinica.edu.tw/ups/demo/demo.htm

[1]  Sophie Lemoine,et al.  An evaluation of custom microarray applications: the oligonucleotide design challenge , 2009, Nucleic acids research.

[2]  Ronald W. Davis,et al.  Quantitative Monitoring of Gene Expression Patterns with a Complementary DNA Microarray , 1995, Science.

[3]  Harald Meier,et al.  46. ARB: A Software Environment for Sequence Data , 2011 .

[4]  Jean-Marie Rouillard,et al.  OligoArrayDb: pangenomic oligonucleotide microarray probe sets database , 2009, Nucleic Acids Res..

[5]  Patrick S. Schnable,et al.  Picky: oligo microarray design for large genomes , 2004, Bioinform..

[6]  F. Cohen,et al.  Expression profiling of the schizont and trophozoite stages of Plasmodium falciparum with a long-oligonucleotide microarray , 2003, Genome Biology.

[7]  Michael Zuker,et al.  DINAMelt web server for nucleic acid melting prediction , 2005, Nucleic Acids Res..

[8]  Eugene W. Myers,et al.  Basic local alignment search tool. Journal of Molecular Biology , 1990 .

[9]  Eric K. Nordberg,et al.  YODA: selecting signature oligonucleotides , 2005, Bioinform..

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

[11]  Amanda B. Herzog,et al.  Influence of Dangling Ends and Surface-Proximal Tails of Targets on Probe-Target Duplex Formation in 16S rRNA Gene-Based Diagnostic Arrays , 2006, Applied and Environmental Microbiology.

[12]  Gianluca De Bellis,et al.  ORMA: a tool for identification of species-specific variations in 16S rRNA gene and oligonucleotides design , 2009, Nucleic acids research.

[13]  J. Fry,et al.  PRIMROSE: a computer program for generating and estimating the phylogenetic range of 16S rRNA oligonucleotide probes and primers in conjunction with the RDP-II database. , 2002, Nucleic acids research.

[14]  Christoph Gille,et al.  Oligodb-interactive design of oligo DNA for transcription profiling of human genes , 2002, Bioinform..

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

[16]  David R. C. Hill,et al.  GoArrays: highly dynamic and efficient microarray probe design , 2005, Bioinform..

[17]  E. Myers,et al.  Basic local alignment search tool. , 1990, Journal of molecular biology.

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

[19]  Jean-Marie Rouillard,et al.  OligoArray: genome-scale oligonucleotide design for microarrays , 2002, Bioinform..

[20]  K. Schleifer,et al.  ARB: a software environment for sequence data. , 2004, Nucleic acids research.

[21]  Jan-Ming Ho,et al.  A Review of the Major Penaeid Shrimp EST Studies and the Construction of a Shrimp Transcriptome Database Based on the ESTs from Four Penaeid Shrimp , 2011, Marine Biotechnology.

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

[23]  Chung-Yen Lin,et al.  The unique probe selector: a comprehensive web service for probe design and oligonucleotide arrays , 2008, BMC Bioinformatics.

[24]  Jizhong Zhou,et al.  Selection of optimal oligonucleotide probes for microarrays using multiple criteria, global alignment and parameter estimation , 2005, Nucleic acids research.

[25]  Marie-Claude Potier,et al.  Selection of oligonucleotides for whole-genome microarrays with semi-automatic update , 2008, Bioinform..