Literature DB >> 12805270

Spotted long oligonucleotide arrays for human gene expression analysis.

Andrea Barczak1, Madeleine Willkom Rodriguez, Kristina Hanspers, Laura L Koth, Yu Chuan Tai, Benjamin M Bolstad, Terence P Speed, David J Erle.   

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.

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Year:  2003        PMID: 12805270      PMCID: PMC403751          DOI: 10.1101/gr.1048803

Source DB:  PubMed          Journal:  Genome Res        ISSN: 1088-9051            Impact factor:   9.043


  17 in total

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Authors:  M D Kane; T A Jatkoe; C R Stumpf; J Lu; J D Thomas; S J Madore
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2.  A statistical method for flagging weak spots improves normalization and ratio estimates in microarrays.

Authors:  M C Yang; Q G Ruan; J J Yang; S Eckenrode; S Wu; R A McIndoe; J X She
Journal:  Physiol Genomics       Date:  2001-10-10       Impact factor: 3.107

3.  Summaries of Affymetrix GeneChip probe level data.

Authors:  Rafael A Irizarry; Benjamin M Bolstad; Francois Collin; Leslie M Cope; Bridget Hobbs; Terence P Speed
Journal:  Nucleic Acids Res       Date:  2003-02-15       Impact factor: 16.971

4.  A comparison of normalization methods for high density oligonucleotide array data based on variance and bias.

Authors:  B M Bolstad; R A Irizarry; M Astrand; T P Speed
Journal:  Bioinformatics       Date:  2003-01-22       Impact factor: 6.937

5.  Analysis of gene expression in single live neurons.

Authors:  J Eberwine; H Yeh; K Miyashiro; Y Cao; S Nair; R Finnell; M Zettel; P Coleman
Journal:  Proc Natl Acad Sci U S A       Date:  1992-04-01       Impact factor: 11.205

6.  Parallel human genome analysis: microarray-based expression monitoring of 1000 genes.

Authors:  M Schena; D Shalon; R Heller; A Chai; P O Brown; R W Davis
Journal:  Proc Natl Acad Sci U S A       Date:  1996-10-01       Impact factor: 11.205

7.  Exploring the metabolic and genetic control of gene expression on a genomic scale.

Authors:  J L DeRisi; V R Iyer; P O Brown
Journal:  Science       Date:  1997-10-24       Impact factor: 47.728

8.  Expression profiling using microarrays fabricated by an ink-jet oligonucleotide synthesizer.

Authors:  T R Hughes; M Mao; A R Jones; J Burchard; M J Marton; K W Shannon; S M Lefkowitz; M Ziman; J M Schelter; M R Meyer; S Kobayashi; C Davis; H Dai; Y D He; S B Stephaniants; G Cavet; W L Walker; A West; E Coffey; D D Shoemaker; R Stoughton; A P Blanchard; S H Friend; P S Linsley
Journal:  Nat Biotechnol       Date:  2001-04       Impact factor: 54.908

9.  Expression monitoring by hybridization to high-density oligonucleotide arrays.

Authors:  D J Lockhart; H Dong; M C Byrne; M T Follettie; M V Gallo; M S Chee; M Mittmann; C Wang; M Kobayashi; H Horton; E L Brown
Journal:  Nat Biotechnol       Date:  1996-12       Impact factor: 54.908

10.  Microarray results: how accurate are they?

Authors:  Ravi Kothapalli; Sean J Yoder; Shrikant Mane; Thomas P Loughran
Journal:  BMC Bioinformatics       Date:  2002-08-23       Impact factor: 3.169

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  60 in total

1.  Evaluation of gene expression measurements from commercial microarray platforms.

Authors:  Paul K Tan; Thomas J Downey; Edward L Spitznagel; Pin Xu; Dadin Fu; Dimiter S Dimitrov; Richard A Lempicki; Bruce M Raaka; Margaret C Cam
Journal:  Nucleic Acids Res       Date:  2003-10-01       Impact factor: 16.971

Review 2.  Methods for transcriptional profiling in plants. Be fruitful and replicate.

Authors:  Blake C Meyers; David W Galbraith; Timothy Nelson; Vikas Agrawal
Journal:  Plant Physiol       Date:  2004-06-01       Impact factor: 8.340

3.  Optimization of probe length and the number of probes per gene for optimal microarray analysis of gene expression.

Authors:  Cheng-Chung Chou; Chun-Houh Chen; Te-Tsui Lee; Konan Peck
Journal:  Nucleic Acids Res       Date:  2004-07-08       Impact factor: 16.971

4.  Quantitative assessment of a novel flow-through porous microarray for the rapid analysis of gene expression profiles.

Authors:  Ying Wu; Peggy de Kievit; Lars Vahlkamp; Dirk Pijnenburg; Maarten Smit; Martijn Dankers; Diana Melchers; Martijn Stax; Piet J Boender; Colin Ingham; Niek Bastiaensen; Rik de Wijn; Dirk van Alewijk; Henk van Damme; Anton K Raap; Alan B Chan; Rinie van Beuningen
Journal:  Nucleic Acids Res       Date:  2004-08-27       Impact factor: 16.971

5.  Genome-wide analysis of spatial gene expression in Arabidopsis flowers.

Authors:  Frank Wellmer; José Luis Riechmann; Márcio Alves-Ferreira; Elliot M Meyerowitz
Journal:  Plant Cell       Date:  2004-04-20       Impact factor: 11.277

Review 6.  In control: systematic assessment of microarray performance.

Authors:  Harm van Bakel; Frank C P Holstege
Journal:  EMBO Rep       Date:  2004-10       Impact factor: 8.807

7.  Comparison of transcript profiling on Arabidopsis microarray platform technologies.

Authors:  Jeffrey D Pylatuik; Pierre R Fobert
Journal:  Plant Mol Biol       Date:  2005-07       Impact factor: 4.076

8.  Transporter and ion channel gene expression after Caco-2 cell differentiation using 2 different microarray technologies.

Authors:  Christopher P Landowski; Pascale Anderle; Duxin Sun; Wolfgang Sadee; Gordon L Amidon
Journal:  AAPS J       Date:  2004-09-07       Impact factor: 4.009

Review 9.  Associating phenotypes with molecular events: recent statistical advances and challenges underpinning microarray experiments.

Authors:  Yulan Liang; Arpad Kelemen
Journal:  Funct Integr Genomics       Date:  2005-11-15       Impact factor: 3.410

10.  Mammary ductal morphogenesis requires paracrine activation of stromal EGFR via ADAM17-dependent shedding of epithelial amphiregulin.

Authors:  Mark D Sternlicht; Susan W Sunnarborg; Hosein Kouros-Mehr; Ying Yu; David C Lee; Zena Werb
Journal:  Development       Date:  2005-08-03       Impact factor: 6.868

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