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Optimising the analysis of transcript data using high density oligonucleotide arrays and genomic DNA-based probe selection

Graham, N. S., Broadley, M. R., Hammond, J. P., White, P. J. and May, S. T. (2007) Optimising the analysis of transcript data using high density oligonucleotide arrays and genomic DNA-based probe selection. BMC Genomics, 8. 344. ISSN 1471-2164

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To link to this item DOI: 10.1186/1471-2164-8-344

Abstract/Summary

Background: Affymetrix GeneChip arrays are widely used for transcriptomic studies in a diverse range of species. Each gene is represented on a GeneChip array by a probe- set, consisting of up to 16 probe-pairs. Signal intensities across probe- pairs within a probe-set vary in part due to different physical hybridisation characteristics of individual probes with their target labelled transcripts. We have previously developed a technique to study the transcriptomes of heterologous species based on hybridising genomic DNA (gDNA) to a GeneChip array designed for a different species, and subsequently using only those probes with good homology. Results: Here we have investigated the effects of hybridising homologous species gDNA to study the transcriptomes of species for which the arrays have been designed. Genomic DNA from Arabidopsis thaliana and rice (Oryza sativa) were hybridised to the Affymetrix Arabidopsis ATH1 and Rice Genome GeneChip arrays respectively. Probe selection based on gDNA hybridisation intensity increased the number of genes identified as significantly differentially expressed in two published studies of Arabidopsis development, and optimised the analysis of technical replicates obtained from pooled samples of RNA from rice. Conclusion: This mixed physical and bioinformatics approach can be used to optimise estimates of gene expression when using GeneChip arrays.

Item Type:Article
Refereed:Yes
Divisions:Interdisciplinary centres and themes > Centre for Food Security
Faculty of Life Sciences > School of Agriculture, Policy and Development > Biodiversity, Crops and Agroecosystems Division > Crops Research Group
ID Code:33856
Publisher:BioMed Central

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