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Spotted long oligonucleotide arrays for human gene expression analysis.

ABSTRACT: DNA microarrays produced by deposition (or 'spotting')of a single long oligonucleotide probe for each gene may be an attractive alternative to other types of arrays. We produced spotted oligonucleotide arrays using two large collections of approximately 70-mer probes, and used these arrays to analyze gene expression in two dissimilar human RNA samples. These samples were also analyzed using arrays produced by in situ synthesis of sets of multiple short (25-mer) oligonucleotides for each gene (Affymetrix GeneChips). We compared expression measurements for 7344 genes that were represented in both long oligonucleotide probe collections and the in situ-synthesized 25-mer arrays. We found strong correlations (r = 0.8-0.9) between relative gene expression measurements made with spotted long oligonucleotide probes and in situ-synthesized 25-mer probe sets. Spotted long oligonucleotide arrays were suitable for use with both unamplified cDNA and amplified RNA targets, and are a cost-effective alternative for many functional genomics applications. Most previously reported evaluations of microarray technologies have focused on expression measurements made on a relatively small number of genes. The approach described here involves far more gene expression measurements and provides a useful method for comparing existing and emerging techniques for genome-scale expression analysis.

SUBMITTER: Barczak A

PROVIDER: S-EPMC403751 | biostudies-literature | 2003 Jul

REPOSITORIES: biostudies-literature

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Spotted long oligonucleotide arrays for human gene expression analysis.

Barczak Andrea A Rodriguez Madeleine Willkom MW Hanspers Kristina K Koth Laura L LL Tai Yu Chuan YC Bolstad Benjamin M BM Speed Terence P TP Erle David J DJ

Genome research 20030612 7

DNA microarrays produced by deposition (or 'spotting')of a single long oligonucleotide probe for each gene may be an attractive alternative to other types of arrays. We produced spotted oligonucleotide arrays using two large collections of approximately 70-mer probes, and used these arrays to analyze gene expression in two dissimilar human RNA samples. These samples were also analyzed using arrays produced by in situ synthesis of sets of multiple short (25-mer) oligonucleotides for each gene (Af ...[more]

PMID: 12805270

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Project description:BackgroundOne of the important challenges in microarray analysis is to take full advantage of previously accumulated data, both from one's own laboratory and from public repositories. Through a comparative analysis on a variety of datasets, a more comprehensive view of the underlying mechanism or structure can be obtained. However, as we discover in this work, continual changes in genomic sequence annotations and probe design criteria make it difficult to compare gene expression data even from different generations of the same microarray platform.ResultsWe first describe the extent of discordance between the results derived from two generations of Affymetrix oligonucleotide arrays, as revealed in cluster analysis and in identification of differentially expressed genes. We then propose a method for increasing comparability. The dataset we use consists of a set of 14 human muscle biopsy samples from patients with inflammatory myopathies that were hybridized on both HG-U95Av2 and HG-U133A human arrays. We find that the use of the probe set matching table for comparative analysis provided by Affymetrix produces better results than matching by UniGene or LocusLink identifiers but still remains inadequate. Rescaling of expression values for each gene across samples and data filtering by expression values enhance comparability but only for few specific analyses. As a generic method for improving comparability, we select a subset of probes with overlapping sequence segments in the two array types and recalculate expression values based only on the selected probes. We show that this filtering of probes significantly improves the comparability while retaining a sufficient number of probe sets for further analysis.ConclusionsCompatibility between high-density oligonucleotide arrays is significantly affected by probe-level sequence information. With a careful filtering of the probes based on their sequence overlaps, data from different generations of microarrays can be combined more effectively.

Dataset Information

Spotted long oligonucleotide arrays for human gene expression analysis.

Publications

Spotted long oligonucleotide arrays for human gene expression analysis.

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