Evaluation of quantitative miRNA expression platforms in the microRNA quality control (miRQC) study.

MicroRNAs are important negative regulators of protein-coding gene expression and have been studied intensively over the past years. Several measurement platforms have been developed to determine relative miRNA abundance in biological samples using different technologies such as small RNA sequencing, reverse transcription-quantitative PCR (RT-qPCR) and (microarray) hybridization. In this study, we systematically compared 12 commercially available platforms for analysis of microRNA expression. We measured an identical set of 20 standardized positive and negative control samples, including human universal reference RNA, human brain RNA and titrations thereof, human serum samples and synthetic spikes from microRNA family members with varying homology. We developed robust quality metrics to objectively assess platform performance in terms of reproducibility, sensitivity, accuracy, specificity and concordance of differential expression. The results indicate that each method has its strengths and weaknesses, which help to guide informed selection of a quantitative microRNA gene expression platform for particular study goals.

Agilent microRNA microarray profiling system.

MicroRNA (miRNA) profiling is of great interest because of the significant roles these short noncoding RNA molecules play in cellular regulation. Signature profiles, usually involving several miRNAs, have also been associated with dysfunctional cellular regulation such as in cancer. Profiling miRNAs can be done using the Agilent Technologies miRNA profiling system, which is a sensitive and accurate miRNA microarray assay. The assay is based on a highly efficient labeling method linked to a novel probe design strategy. The labeling method uses a simple, single-vial approach where 100 ng of nonfractionated total RNA is directly labeled by ligation of a Cy3 labeled pCp molecule to the 3' end of the RNA. The labeled cytosine interacts with the guanidine at the 5' end of the probe which adds stability to the hybridization complex. In addition, the probes have been designed to provide both sequence and size discrimination, generally resulting in highly specific detection of closely related mature miRNAs. The labeling and probe design strategies allow for a precise and accurate measurement that spans a linear dynamic range of greater than four orders of magnitude from at least 0.2 amol to 2 fmol of miRNA and a detection limit of less than 0.1 amol. The assay works over a wide range of sample types including FFPE samples. Agilent's microarray technology is a flexible design platform allowing quick array design iterations and incorporation of the latest miRBase content.

mRNA and microRNA expression profiles of the NCI-60 integrated with drug activities.

As part of the Spotlight on Molecular Profiling series, we present here new profiling studies of mRNA and microRNA expression for the 60 cell lines of the National Cancer Institute (NCI) Developmental Therapeutics program (DTP) drug screen (NCI-60) using the 41,000-probe Agilent Whole Human Genome Oligo Microarray and the 15,000-feature Agilent Human microRNA Microarray V2. The expression levels of approximately 21,000 genes and 723 human microRNAs were measured. These profiling studies include quadruplicate technical replicates for six and eight cell lines for mRNA and microRNA, respectively, and duplicates for the remaining cell lines. The resulting data sets are freely available and searchable online in our CellMiner database. The result indicates high reproducibility for both platforms and an essential biological similarity across the various cell types. The mRNA and microRNA expression levels were integrated with our previously published 1,429-compound database of anticancer activity obtained from the NCI DTP drug screen. Large blocks of both mRNAs and microRNAs were identified with predominately unidirectional correlations to approximately 1,300 drugs, including 121 drugs with known mechanisms of action. The data sets presented here will facilitate the identification of groups of mRNAs, microRNAs, and drugs that potentially affect and interact with one another.

Using RNA sample titrations to assess microarray platform performance and normalization techniques.

We have assessed the utility of RNA titration samples for evaluating microarray platform performance and the impact of different normalization methods on the results obtained. As part of the MicroArray Quality Control project, we investigated the performance of five commercial microarray platforms using two independent RNA samples and two titration mixtures of these samples. Focusing on 12,091 genes common across all platforms, we determined the ability of each platform to detect the correct titration response across the samples. Global deviations from the response predicted by the titration ratios were observed. These differences could be explained by variations in relative amounts of messenger RNA as a fraction of total RNA between the two independent samples. Overall, both the qualitative and quantitative correspondence across platforms was high. In summary, titration samples may be regarded as a valuable tool, not only for assessing microarray platform performance and different analysis methods, but also for determining some underlying biological features of the samples.

Performance comparison of one-color and two-color platforms within the MicroArray Quality Control (MAQC) project.

Microarray-based expression profiling experiments typically use either a one-color or a two-color design to measure mRNA abundance. The validity of each approach has been amply demonstrated. Here we provide a simultaneous comparison of results from one- and two-color labeling designs, using two independent RNA samples from the Microarray Quality Control (MAQC) project, tested on each of three different microarray platforms. The data were evaluated in terms of reproducibility, specificity, sensitivity and accuracy to determine if the two approaches provide comparable results. For each of the three microarray platforms tested, the results show good agreement with high correlation coefficients and high concordance of differentially expressed gene lists within each platform. Cumulatively, these comparisons indicate that data quality is essentially equivalent between the one- and two-color approaches and strongly suggest that this variable need not be a primary factor in decisions regarding experimental microarray design.