To help establish controls and guidelines for performing informative microarray experiments, the US Food and Drug Administration initiated the MicroArray Quality Control (MAQC) Project. A series of studies that included reagents and instruments from Ambion and Applied Biosystems, addressed the quality, reproducibility, and comparability of seven microarray platforms. Phase I results were published in the September 2006 issue of Nature Biotechnology [1-6].

MicroArray Quality Control (MAQC) Project

The MAQC Project, developed from US Food and Drug Administration’s Critical Path Initiative, was established to identify medical product development problems for improved public health. Microarray technology was identified because of its potential impact on pharmacogenomics and toxicogenomics. The goal was to provide an important data resource that will help establish quality measures for experiments and data processing.

The MAQC Consortium consists of scientists and statisticians from over 50 regulatory, academic, and industrial groups (including Ambion, an Applied Biosystems Business, and Applied Biosystems), who analyzed the data from more than 1,300 arrays. Their data, results, and protocols are freely available—see the sidebar, Links to Articles, Data Sets, and SOPs, to obtain this information.

Reproducibility of Gene Expression Measurements [1]

In the main study, expression data from seven microarray platforms (including Applied Biosystems Genome Survey Microarrays) and three alternative assays (Applied Biosystems TaqMan® Gene Expression Assays, Panomics QuantiGene® Assays, and Gene Express StaRT-PCR™ Assays) were generated at multiple test sites. The results indicate that inter- and intra- platform microarray data were reproducible regardless of probe sequence, labeling protocols, and expression detection method.

Validation of Microarray Results [2]

Expression measurements from 997 TaqMan Gene Expression Assays and two other quantitative platforms were used to validate the microarray data sets. The large number of TaqMan Gene Expression Assays used in the study allowed the authors to examine the sources of variability among microarray platforms as well as the differences between the hybridization-based platforms and the PCR-based platform focusing on sensitivity, dynamic range, ratio compression, as well as fold change concordance. Good correlation between quantitative assays and microarray data increased confidence in the concordance observed between microarray platforms and enabled the authors to examine the possible reasons for the discordance (found in 1% of detected genes) among microarray platforms.

Microarray Performance and Normalization Techniques [3]

Two RNA samples (i.e., Ambion FirstChoice® Human Brain Reference RNA and Stratagene's Universal Human Reference RNA) and two titration mixtures were analyzed on five microarray platforms. The authors focused on >12,000 genes common to all platforms to determine each platform’s ability to detect the correct titration response (direction and magnitude of change). They reported high qualitative and quantitative correspondence across platforms.

External RNA Controls [4]

External RNA controls (ERC) are synthetic or naturally occurring RNA species added to microarray samples as quality controls. This group used the MAQC data set to identify key attributes of ERC performance when ERC was added either to the total RNA sample before amplification or to the amplified RNA before hybridization. Four recommendations were presented.

Comparison of One- and Two-Color Microarray Platforms [5]

This project addresses a fundamental issue in microarray experimental design: whether to (1) hybridize a single sample to one microarray or (2) label two samples (e.g., experimental and control) with different fluorophores and cohybridize both samples to a single array. Both approaches are discussed in terms of their strengths and weaknesses, but the results suggest that the data quality from both experimental designs are, to a large extent, equivalent.

Microarray Platform Consistency in a Toxicogenomic Study [6]

MAQC participants generated a biologically relevant toxicogenomics data set using four microarray platforms and rat RNA treated with three chemicals. Consistent with the main MAQC study [4], good concordance was found among the data sets from multiple test sites and platforms.

Summary

The MAQC study is the largest and most comprehensive microarray initiative to date. Project scale, number of test sites, and access to data differentiated the MAQC Project from previous studies. This research also used two RNA samples that are arguably the most well characterized samples with public access to expression information. In addition to advancing technology, the Consortium is helping to implement microarrays in clinical and regulatory settings.

References

1. Shi L, Reid LH, Jones WD, et al. (2006) The MicroArray Quality Control (MAQC) project shows inter- and intraplatform reproducibility of gene expression measurements. Nat Biotechnol 24(9):1151–1161.

2. Canales RD, Luo Y, Willey JC, et al. (2006) Evaluation of DNA microarray results with quantitative gene expression platforms. Nat Biotechnol 24(9):1115–1122.

3. Shippy R, Fulmer-Smentek S, Jensen RV, et al. (2006) Using RNA sample titrations to assess microarray platform performance and normalization techniques. Nat Biotechnol 24(9):1123–1131.

4. Tong W, Lucas AB, Shippy R, et al. (2006) Evaluation of external RNA controls for the assessment of microarray performance. Nat Biotechnol 24(9):1132–1139.

5. Patterson TA, Lobenhofer EK, Fulmer-Smentek SB, et al. (2006) Performance comparison of one-color and two-color platforms within the MicroArray Quality Control (MAQC) project. Nat Biotechnol 24(9):1140–1150.

6. Guo L, Lobenhofer EK, Wang C, et al. (2006) Rat toxicogenomic study reveals analytical consistency across microarray platforms. Nat Biotechnol 24(9):1162–1169.

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