Published online before print
June 12, 2003, 10.1101/gr.1048803
Genome Res. 13:1775-1785, 2003
©2003 by Cold Spring Harbor Laboratory Press; ISSN 1088-9051/03 $5.00
Methods
Spotted Long Oligonucleotide Arrays for Human Gene Expression Analysis
Andrea Barczak1,
Madeleine Willkom Rodriguez1,
Kristina Hanspers2,
Laura L. Koth1,
Yu Chuan Tai3,
Benjamin M. Bolstad3,
Terence P. Speed4,5 and
David J. Erle1,6
1 Department of Medicine, University of California, San Francisco, San
Francisco, California 94143, USA
2 Gladstone Institute of Cardiovascular Disease, San Francisco, California
94141, USA
3 Group in Biostatistics, University of California, Berkeley, California
94720, USA
4 Department of Statistics, University of California, Berkeley, California
94720, USA
5 Division of Genetics and Bioinformatics, The Walter and Eliza Hall
Institute of Medical Research, Parkville, Vic 3050, Australia
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  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.
Article and publication are at
http://www.genome.org/cgi/doi/10.1101/gr.1048803.
6 Corresponding author.
E-MAIL
erle{at}itsa.ucsf.edu;
FAX (415) 206-4123.
Article published online before print in June 2003.
[Data from this study are available from GEO
(http://www.ncbi.nlm.nih.gov/geo)and are listed under the following accession
numbers: GSE344 (for the entire experimental series), GSM4843-GSM4865 (for the
expression data from individual arrays), and GPL91, GPL273, and GPL274 (for
the three array platforms).]
 CiteULike  Connotea  Del.icio.us  Digg  Reddit  Technorati What's this?
This article has been cited by other articles:
|
|
|
|
 
E. Garrett-Mayer, G. Parmigiani, X. Zhong, L. Cope, and E. Gabrielson
Cross-study validation and combined analysis of gene expression microarray data
Biostat.,
April 1, 2008;
9(2):
333 - 354.
[Abstract]
[Full Text]
[PDF]
|
|
|
|
|
|
|
J. C. Cheng, K. M. Sakamoto, E. M. Horwitz, S. L. Karsten, L. Shoemaker, H. I. Kornblumc, and P. Malik
Report on the Workshop "New Technologies in Stem Cell Research," Society for Pediatric Research, San Francisco, California, April 29, 2006
Stem Cells,
April 1, 2007;
25(4):
1070 - 1088.
[Abstract]
[Full Text]
[PDF]
|
|
|
|
|
|
|
G. D. Sgarlato and H. H. Sussman
Representational fragment amplification: exponential amplification of fragmented cDNA enables multimillion-fold expression testing.
Clin. Chem.,
November 1, 2006;
52(11):
2164 - 2168.
[Full Text]
[PDF]
|
|
|
|
|
|
|
J. Quackenbush
Microarray analysis and tumor classification.
N. Engl. J. Med.,
June 8, 2006;
354(23):
2463 - 2472.
[Full Text]
[PDF]
|
|
|
|
|
|
|
M. J. Hessner, B. Xiang, S. Jia, R. Geoffrey, S. Holmes, L. Meyer, S. Muheisen, and X. Wang
Three-color cDNA microarrays with prehybridization quality control yield gene expression data comparable to that of commercial platforms
Physiol Genomics,
March 13, 2006;
25(1):
166 - 178.
[Abstract]
[Full Text]
[PDF]
|
|
|
|
|
|
|
K. L. Thompson, B. A. Rosenzweig, P. S. Pine, J. Retief, Y. Turpaz, C. A. Afshari, H. K. Hamadeh, M. A. Damore, M. Boedigheimer, E. Blomme, et al.
Use of a mixed tissue RNA design for performance assessments on multiple microarray formats
Nucleic Acids Res.,
December 23, 2005;
33(22):
e187 - e187.
[Abstract]
[Full Text]
[PDF]
|
|
|
|
|
|
|
P. R. Nambiar, S. R. Boutin, R. Raja, and D. W. Rosenberg
Global Gene Expression Profiling: A Complement to Conventional Histopathologic Analysis of Neoplasia
Vet. Pathol.,
November 1, 2005;
42(6):
735 - 752.
[Abstract]
[Full Text]
[PDF]
|
|
|
|
|
|
|
J A Alvarado, R G Alvarado, R F Yeh, L Franse-Carman, G R Marcellino, and M J Brownstein
A new insight into the cellular regulation of aqueous outflow: how trabecular meshwork endothelial cells drive a mechanism that regulates the permeability of Schlemm's canal endothelial cells
Br. J. Ophthalmol.,
November 1, 2005;
89(11):
1500 - 1505.
[Abstract]
[Full Text]
[PDF]
|
|
|
|
|
|
|
M. Barnes, J. Freudenberg, S. Thompson, B. Aronow, and P. Pavlidis
Experimental comparison and cross-validation of the Affymetrix and Illumina gene expression analysis platforms
Nucleic Acids Res.,
October 19, 2005;
33(18):
5914 - 5923.
[Abstract]
[Full Text]
[PDF]
|
|
|
|
|
|
|
M. D. Sternlicht, S. W. Sunnarborg, H. Kouros-Mehr, Y. Yu, D. C. Lee, and Z. Werb
Mammary ductal morphogenesis requires paracrine activation of stromal EGFR via ADAM17-dependent shedding of epithelial amphiregulin
Development,
September 1, 2005;
132(17):
3923 - 3933.
[Abstract]
[Full Text]
[PDF]
|
|
|
|
|
|
|
M. Fluck, C. Dapp, S. Schmutz, E. Wit, and H. Hoppeler
Transcriptional profiling of tissue plasticity: role of shifts in gene expression and technical limitations
J Appl Physiol,
August 1, 2005;
99(2):
397 - 413.
[Abstract]
[Full Text]
[PDF]
|
|
|
|
|
|
|
J. Li, M. L. Spletter, and J. A. Johnson
Dissecting tBHQ induced ARE-driven gene expression through long and short oligonucleotide arrays
Physiol Genomics,
March 21, 2005;
21(1):
43 - 58.
[Abstract]
[Full Text]
[PDF]
|
|
|
|
|
|
|
J. Schlingemann, O. Thuerigen, C. Ittrich, G. Toedt, H. Kramer, M. Hahn, and P. Lichter
Effective transcriptome amplification for expression profiling on sense-oriented oligonucleotide microarrays
Nucleic Acids Res.,
February 17, 2005;
33(3):
e29 - e29.
[Abstract]
[Full Text]
[PDF]
|
|
|
|
|
|
|
J. Allemeersch, S. Durinck, R. Vanderhaeghen, P. Alard, R. Maes, K. Seeuws, T. Bogaert, K. Coddens, K. Deschouwer, P. Van Hummelen, et al.
Benchmarking the CATMA Microarray. A Novel Tool forArabidopsis Transcriptome Analysis
Plant Physiology,
February 1, 2005;
137(2):
588 - 601.
[Abstract]
[Full Text]
[PDF]
|
|
|
|
|
|
|
V Choesmel, F Foucault, J P Thiery, and N Blin
Design of a real time quantitative PCR assay to assess global mRNA amplification of small size specimens for microarray hybridisation
J. Clin. Pathol.,
December 1, 2004;
57(12):
1278 - 1287.
[Abstract]
[Full Text]
[PDF]
|
|
|
|
|
|
|
Y. Wu, P. de Kievit, L. Vahlkamp, D. Pijnenburg, M. Smit, M. Dankers, D. Melchers, M. Stax, P. J. Boender, C. Ingham, et al.
Quantitative assessment of a novel flow-through porous microarray for the rapid analysis of gene expression profiles
Nucleic Acids Res.,
August 27, 2004;
32(15):
e123 - e123.
[Abstract]
[Full Text]
[PDF]
|
|
|
|
|
|
|
L. J. Joseph
RNA Reference Materials for Gene Expression Studies: Counterpoint: RNA Metrology: Forecast Calls for Partial Clearing
Clin. Chem.,
August 1, 2004;
50(8):
1290 - 1292.
[Full Text]
[PDF]
|
|
|
|
|
|
|
C.-C. Chou, C.-H. Chen, T.-T. Lee, and K. Peck
Optimization of probe length and the number of probes per gene for optimal microarray analysis of gene expression
Nucleic Acids Res.,
July 8, 2004;
32(12):
e99 - e99.
[Abstract]
[Full Text]
[PDF]
|
|
|
|
|
|
|
B. C. Meyers, D. W. Galbraith, T. Nelson, and V. Agrawal
Methods for Transcriptional Profiling in Plants. Be Fruitful and Replicate
Plant Physiology,
June 1, 2004;
135(2):
637 - 652.
[Full Text]
[PDF]
|
|
|
|
|
|
|
F. Wellmer, J. L. Riechmann, M. Alves-Ferreira, and E. M. Meyerowitz
Genome-Wide Analysis of Spatial Gene Expression in Arabidopsis Flowers
PLANT CELL,
May 1, 2004;
16(5):
1314 - 1326.
[Abstract]
[Full Text]
[PDF]
|
|
|
|
|
|
|
E.-S. Han, Y. Wu, R. McCarter, J. F. Nelson, A. Richardson, and S. G. Hilsenbeck
Reproducibility, Sources of Variability, Pooling, and Sample Size: Important Considerations for the Design of High-Density Oligonucleotide Array Experiments
J. Gerontol. A Biol. Sci. Med. Sci.,
April 1, 2004;
59(4):
B306 - B315.
[Abstract]
[Full Text]
[PDF]
|
|
|
|
|
|
|
P. K. Tan, T. J. Downey, E. L. Spitznagel Jr, P. Xu, D. Fu, D. S. Dimitrov, R. A. Lempicki, B. M. Raaka, and M. C. Cam
Evaluation of gene expression measurements from commercial microarray platforms
Nucleic Acids Res.,
October 1, 2003;
31(19):
5676 - 5684.
[Abstract]
[Full Text]
[PDF]
|
|
|
|
|
![[Feedback]](/icons/banner/feedbackACT.gif){kind=icon}
![[For Subscribers]](/icons/banner/subscriberACT.gif){kind=icon}
![[Archive]](/icons/banner/archiveACT.gif){kind=icon}
![[Search]](/icons/banner/searchACT.gif){kind=icon}
![[Contents]](/icons/banner/tocACT.gif){kind=icon}
