An evaluation of the performance of cDNA microarrays for detecting changes in global mRNA expression.

The cDNA microarray is one technological approach that has the potential to accurately measure changes in global mRNA expression levels. We report an assessment of an optimized cDNA microarray platform to generate accurate, precise and reliable data consistent with the objective of using microarrays as an acquisition platform to populate gene expression databases. The study design consisted of two independent evaluations with 70 arrays from two different manufactured lots and used three human tissue sources as samples: placenta, brain and heart. Overall signal response was linear over three orders of magnitude and the sensitivity for any element was estimated to be 2 pg mRNA. The calculated coefficient of variation for differential expression for all non-differentiated elements was 12-14% across the entire signal range and did not vary with array batch or tissue source. The minimum detectable fold change for differential expression was 1.4. Accuracy, in terms of bias (observed minus expected differential expression ratio), was less than 1 part in 10 000 for all non-differentiated elements. The results presented in this report demonstrate the reproducible performance of the cDNA microarray technology platform and the methods provide a useful framework for evaluating other technologies that monitor changes in global mRNA expression.

[1]  G. Church,et al.  Systematic management and analysis of yeast gene expression data. , 2000, Genome research.

[2]  Ji Huang,et al.  [Serial analysis of gene expression]. , 2002, Yi chuan = Hereditas.

[3]  M Schena,et al.  Fluorescence-based expression monitoring using microarrays. , 1999, Methods in enzymology.

[4]  M. Erlander,et al.  TOGA: an automated parsing technology for analyzing expression of nearly all genes. , 2000, Proceedings of the National Academy of Sciences of the United States of America.

[5]  A. Kerlavage,et al.  Complementary DNA sequencing: expressed sequence tags and human genome project , 1991, Science.

[6]  Rithy K. Roth,et al.  Gene expression analysis by massively parallel signature sequencing (MPSS) on microbead arrays , 2000, Nature Biotechnology.

[7]  Luis A. Escobar,et al.  Statistical Intervals: A Guide for Practitioners , 1991 .

[8]  J. Beckmann,et al.  A new dimension for the human genome project: towards comprehensive expression maps , 1997, Nature Genetics.

[9]  D. Lockhart,et al.  Expression monitoring by hybridization to high-density oligonucleotide arrays , 1996, Nature Biotechnology.

[10]  R. Littell.  SAS System for Mixed Models , 1996 .

[11]  J Khan,et al.  DNA microarray technology: the anticipated impact on the study of human disease. , 1999, Biochimica et biophysica acta.

[12]  A Buckpitt,et al.  Development of a toxicological gene array and quantitative assessment of this technology. , 2000, Archives of biochemistry and biophysics.

[13]  Mark Schena,et al.  Microarray Biochip Technology , 2000 .

[14]  G. Zweiger,et al.  Knowledge discovery in gene-expression-microarray data: mining the information output of the genome. , 1999, Trends in biotechnology.

[15]  Ronald W. Davis,et al.  Quantitative Monitoring of Gene Expression Patterns with a Complementary DNA Microarray , 1995, Science.

[16]  The FlyBase database of the Drosophila genome projects and community literature. , 2003, Nucleic acids research.

[17]  E. Mardis,et al.  An encyclopedia of mouse genes , 1999, Nature Genetics.

[18]  K. Kinzler,et al.  Serial Analysis of Gene Expression , 1995, Science.