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Big results from small samples: evaluation of amplification protocols for gene expression profiling.

ABSTRACT: Microarrays have revolutionized many areas of biology due to our technical ability to quantify tens of thousands of transcripts within a single experiment. However, there are still many areas that cannot benefit from this technology due to the amount of biological material needed for microarray analysis. In response to this demand, chemistries have been developed that boast the capability of generating targets from nanogram amounts of total RnA, reflecting minimal amounts of biological material, on the order of several hundred or thousand cells. Herein, we describe the evaluation of four chemistries for RnA amplification in terms of reproducibility, sensitivity, accuracy, and comparability to results from a single round of T7 amplification. No evidence for false-positive measurements of differential expression was observed. In contrast, clear differences between chemistries in sensitivity and accuracy were detected. PCR validation showed an interaction of probe sequence on the array and target labeling chemistry, resulting in a chemistry-dependent probe set sensitivity varying over an order of magnitude.

SUBMITTER: Viale A

PROVIDER: S-EPMC2062549 | biostudies-literature | 2007 Jul

REPOSITORIES: biostudies-literature

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Big results from small samples: evaluation of amplification protocols for gene expression profiling.

Viale Agnes A Li Juan J Tiesman Jay J Hester Susan S Massimi Aldo A Griffin Chandi C Grills George G Khitrov Greg G Lilley Kathryn K Knudtson Kevin K Ward Bill B Kornacker Karl K Chu Chin-Yi CY Auer Herbert H Brooks Andrew I AI

Journal of biomolecular techniques : JBT 20070701 3

Microarrays have revolutionized many areas of biology due to our technical ability to quantify tens of thousands of transcripts within a single experiment. However, there are still many areas that cannot benefit from this technology due to the amount of biological material needed for microarray analysis. In response to this demand, chemistries have been developed that boast the capability of generating targets from nanogram amounts of total RnA, reflecting minimal amounts of biological material, ...[more]

PMID: 17595311

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Project description:BackgroundCross-species gene expression analyses using oligonucleotide microarrays designed to evaluate a single species can provide spurious results due to mismatches between the interrogated transcriptome and arrayed probes. Based on the most recent human and chimpanzee genome assemblies, we developed updated and accessible probe masking methods that allow human Affymetrix oligonucleotide microarrays to be used for robust genome-wide expression analyses in both species. In this process, only data from oligonucleotide probes predicted to have robust hybridization sensitivity and specificity for both transcriptomes are retained for analysis.ResultsTo characterize the utility of this resource, we applied our mask protocols to existing expression data from brains, livers, hearts, testes, and kidneys derived from both species and determined the effects probe numbers have on expression scores of specific transcripts. In all five tissues, probe sets with decreasing numbers of probes showed non-linear trends towards increased variation in expression scores. The relationships between expression variation and probe number in brain data closely matched those observed in simulated expression data sets subjected to random probe masking. However, there is evidence that additional factors affect the observed relationships between gene expression scores and probe number in tissues such as liver and kidney. In parallel, we observed that decreasing the number of probes within probe sets lead to linear increases in both gained and lost inferences of differential cross-species expression in all five tissues, which will affect the interpretation of expression data subject to masking.ConclusionWe introduce a readily implemented and updated resource for human and chimpanzee transcriptome analysis through a commonly used microarray platform. Based on empirical observations derived from the analysis of five distinct data sets, we provide novel guidelines for the interpretation of masked data that take the number of probes present in a given probe set into consideration. These guidelines are applicable to other customized applications that involve masking data from specific subsets of probes.

Project description:This SuperSeries is composed of the following subset Series: GSE3557: Effect of the amount of input total RNA on T7 amplification GSE3558: Effect of in vitro transcription time on the fidelity of T7-based RNA linear amplification GSE3559: Variation in cDNA microarray analysis of gene expression using unamplified poly(A)+ RNA GSE3560: Effects of template switching (TS) primer and cDNA cleanup columns on T7 based RNA linear amplification GSE3561: Effect of ligase on T7 based RNA linear amplification GSE3562: Effect of column cleanup on T7 based RNA linear amplification GSE3563: Correlation between expression levels of different tumors measured by poly(A)+RNA and aRNA Abstract: BACKGROUND: T7 based linear amplification of RNA is used to obtain sufficient antisense RNA for microarray expression profiling. We optimized and systematically evaluated the fidelity and reproducibility of different amplification protocols using total RNA obtained from primary human breast carcinomas and high-density cDNA microarrays. RESULTS: Using an optimized protocol, the average correlation coefficient of gene expression of 11,123 cDNA clones between amplified and unamplified samples is 0.82 (0.85 when a virtual array was created using repeatedly amplified samples to minimize experimental variation). Less than 4% of genes show changes in expression level by 2-fold or greater after amplification compared to unamplified samples. Most changes due to amplification are not systematic both within one tumor sample and between different tumors. Amplification appears to dampen the variation of gene expression for some genes when compared to unamplified poly(A)+ RNA. The reproducibility between repeatedly amplified samples is 0.97 when performed on the same day, but drops to 0.90 when performed weeks apart. The fidelity and reproducibility of amplification is not affected by decreasing the amount of input total RNA in the 0.3-3 micrograms range. Adding template-switching primer, DNA ligase, or column purification of double-stranded cDNA does not improve the fidelity of amplification. The correlation coefficient between amplified and unamplified samples is higher when total RNA is used as template for both experimental and reference RNA amplification. CONCLUSION: T7 based linear amplification reproducibly generates amplified RNA that closely approximates original sample for gene expression profiling using cDNA microarrays. Refer to individual Series

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Big results from small samples: evaluation of amplification protocols for gene expression profiling.

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Big results from small samples: evaluation of amplification protocols for gene expression profiling.

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