Reproducibility of oligonucleotide arrays using small samples

BackgroundLow RNA yields from small tissue samples can limit the use of oligonucleotide microarrays (Affymetrix GeneChips®). Methods using less cRNA for hybridization or amplifying the cRNA have been reported to reduce the number of transcripts detected, but the effect on realistic experiments designed to detect biological differences has not been analyzed. We systematically explore the effects of using different starting amounts of RNA on the ability to detect differential gene expression.ResultsThe standard Affymetrix protocol can be used starting with only 2 micrograms of total RNA, with results equivalent to the recommended 10 micrograms. Biological variability is much greater than the technical variability introduced by this change. A simple amplification protocol described here can be used for samples as small as 0.1 micrograms of total RNA. This amplification protocol allows detection of a substantial fraction of the significant differences found using the standard protocol, despite an increase in variability and the 5' truncation of the transcripts, which prevents detection of a subset of genes.ConclusionsBiological differences in a typical experiment are much greater than differences resulting from technical manipulations in labeling and hybridization. The standard protocol works well with 2 micrograms of RNA, and with minor modifications could allow the use of samples as small as 1 micrograms. For smaller amounts of starting material, down to 0.1 micrograms RNA, differential gene expression can still be detected using the single cycle amplification protocol. Comparisons of groups of four arrays detect many more significant differences than comparisons of three arrays.

[1]  R. F.,et al.  Mathematical Statistics , 1944, Nature.

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

[3]  D T Wong,et al.  Laser capture microdissection-generated target sample for high-density oligonucleotide array hybridization. , 2000, BioTechniques.

[4]  David E. Misek,et al.  Gene-expression profiles predict survival of patients with lung adenocarcinoma , 2002, Nature Medicine.

[5]  D. Botstein,et al.  The transcriptional program of sporulation in budding yeast. , 1998, Science.

[6]  Marcello Pagano,et al.  Principles of Biostatistics , 1992 .

[7]  S. Ginsberg,et al.  RNA Amplification in Brain Tissues , 2002, Neurochemical Research.

[8]  E. Myers,et al.  Basic local alignment search tool. , 1990, Journal of molecular biology.

[9]  J. Warrington,et al.  A high-density probe array sample preparation method using 10- to 100-fold fewer cells , 1999, Nature Biotechnology.

[10]  Neil Winegarden,et al.  Representation is faithfully preserved in global cDNA amplified exponentially from sub-picogram quantities of mRNA , 2002, Nature Biotechnology.

[11]  S. P. Fodor,et al.  High density synthetic oligonucleotide arrays , 1999, Nature Genetics.

[12]  J. Dwyer,et al.  Evaluation of the effects of 17beta-estradiol (17beta-e2) on gene expression in experimental autoimmune encephalomyelitis using DNA microarray. , 2002, Endocrinology.

[13]  G Rennert,et al.  Organ-specific molecular classification of primary lung, colon, and ovarian adenocarcinomas using gene expression profiles. , 2001, The American journal of pathology.

[14]  Michael Ruogu Zhang,et al.  Comprehensive identification of cell cycle-regulated genes of the yeast Saccharomyces cerevisiae by microarray hybridization. , 1998, Molecular biology of the cell.

[15]  J. Dwyer,et al.  Evaluation of the Effects of 17β-Estradiol (17β-E2) on Gene Expression in Experimental Autoimmune Encephalomyelitis Using DNA Microarray. , 2002, Endocrinology.