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Probe Design Strategies for Oligonucleotide Microarrays

  • Nicolas Parisot
  • Eric Peyretaillade
  • Eric Dugat-Bony
  • Jérémie Denonfoux
  • Antoine Mahul
  • Pierre Peyret
Part of the Methods in Molecular Biology book series (MIMB, volume 1368)

Abstract

Oligonucleotide microarrays have been widely used for gene detection and/or quantification of gene expression in various samples ranging from a single organism to a complex microbial assemblage. The success of a microarray experiment, however, strongly relies on the quality of designed probes. Consequently, probe design is of critical importance and therefore multiple parameters should be considered for each probe in order to ensure high specificity, sensitivity, and uniformity as well as potentially quantitative power. Moreover, to assess the complete gene repertoire of complex biological samples such as those studied in the field of microbial ecology, exploratory probe design strategies must be also implemented to target not-yet-described sequences. To design such probes, two algorithms, KASpOD and HiSpOD, have been developed and they are available via two user-friendly web services. Here, we describe the use of this software necessary for the design of highly effective probes especially in the context of microbial oligonucleotide microarrays by taking into account all the crucial parameters.

Key words

KASpOD HiSpOD DNA microarrays Probe design Explorative probe 

Notes

Acknowledgements

This work was supported by the French “Direction Générale de l’Armement” (DGA) and the programme Investissements d’avenir AMI 2011 VALTEX.

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Copyright information

© Springer Science+Business Media New York 2016

Authors and Affiliations

  • Nicolas Parisot
    • 1
  • Eric Peyretaillade
    • 1
  • Eric Dugat-Bony
    • 2
  • Jérémie Denonfoux
    • 3
  • Antoine Mahul
    • 4
  • Pierre Peyret
    • 1
  1. 1.Université d’Auvergne, EA 4678, CIDAMClermont UniversitéClermont-FerrandFrance
  2. 2.Génie et Microbiologie des Procédés Alimentaires, Centre de Biotechnologies Agro-IndustriellesINRA, AgroParisTech, UMR 782Thiverval-GrignonFrance
  3. 3.Genomic Platform and R&DGenoscreen, Campus de l’Institut PasteurLilleFrance
  4. 4.CRRIClermont UniversitéAubièreFrance

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