Quality assessment of microarray experiments

Detection of altered extracellular matrix in surface layers of unstable carotid plaque: an optical spectroscopy, birefringence and microarray genetic analysis

Erosion and rupture of surface layers in atherosclerotic plaque can cause heart attack and stroke; however, changes in luminal surface composition are incompletely defined. Laser-induced fluorescence spectroscopy (LIFS), with limited tissue penetration, was used to investigate the surface of unstable carotid plaque and correlated with microscopy, birefringence and gene expression. Arterial matrix collagens I, III and elastin were assessed in unstable plaques (n = 25) and reference left internal mammary arteries (LIMA, n = 10). LIFS in addition to selective histological staining with picrosirius red, Movat pentachrome and immunostaining revealed decreased elastin and increased collagen I and III (P < 0.05) in carotid plaque when compared with LIMA. Within plaque, collagen I was elevated in the internal carotid region versus the common carotid region. Polarized light microscopy detected layers of aligned collagen and associated mechanical rigidity of the fibrous cap. Microarray analysis of three carotid and three LIMA specimens confirmed up-regulation of collagen I, III and IV, lysyl oxidase and MMP-12. In conclusion, LIFS analysis coupled with microscopy revealed marked regional differences in collagen I, III and elastin in surface layers of carotid plaque; indicative of plaque instability. Birefringence measurements demonstrated mechanical rigidity and weakening of the fibrous cap with complementary changes in ECM gene expression.

Absolute quantification of microRNAs by using a universal reference

MicroRNAs (miRNAs) are a species of small RNAs approximately 21-23-nucleotides long that have been shown to play an important role in many different cellular, developmental, and physiological processes. Accordingly, numerous PCR-, sequencing-, or hybridization-based methods have been established to identify and quantify miRNAs. Their short length results in a high dynamic range of melting temperatures and therefore impedes a proper selection of detection probes or optimized PCR primers. While miRNA microarrays allow for massive parallel and accurate relative measurement of all known miRNAs, they have so far been less useful as an assay for absolute quantification. Here, we present a microarray-based approach for global and absolute quantification of miRNAs. The method relies on the parallel hybridization of the sample of interest labeled with Cy5 and a universal reference of 954 synthetic miRNAs in equimolar concentrations that are labeled with Cy3 on a microarray slide containing probes for all human, mouse, rat, and viral miRNAs (miRBase 12.0). Each single miRNA is quantified with respect to the universal reference canceling biases related to sequence, labeling, or hybridization. We demonstrate the accuracy of the method by various spike-in experiments. Furthermore, we quantified miRNA copy numbers in liver samples and CD34(+)/CD133(-) hematopoietic progenitor cells.

Quality control in microarray assessment of gene expression in human airway epithelium

Background

Microarray technology provides a powerful tool for defining gene expression profiles of airway epithelium that lend insight into the pathogenesis of human airway disorders. The focus of this study was to establish rigorous quality control parameters to ensure that microarray assessment of the airway epithelium is not confounded by experimental artifact. Samples (total n = 223) of trachea, large and small airway epithelium were collected by fiberoptic bronchoscopy of 144 individuals and hybridized to Affymetrix microarrays. The pre- and post-chip quality control (QC) criteria established, included: (1) RNA quality, assessed by RNA Integrity Number (RIN) ≥ 7.0; (2) cRNA transcript integrity, assessed by signal intensity ratio of GAPDH 3' to 5' probe sets ≤ 3.0; and (3) the multi-chip normalization scaling factor ≤ 10.0.

Results

Of the 223 samples, all three criteria were assessed in 191; of these 184 (96.3%) passed all three criteria. For the remaining 32 samples, the RIN was not available, and only the other two criteria were used; of these 29 (90.6%) passed these two criteria. Correlation coefficients for pairwise comparisons of expression levels for 100 maintenance genes in which at least one array failed the QC criteria (average Pearson r = 0.90 ± 0.04) were significantly lower (p < 0.0001) than correlation coefficients for pairwise comparisons between arrays that passed the QC criteria (average Pearson r = 0.97 ± 0.01). Inter-array variability was significantly decreased (p < 0.0001) among samples passing the QC criteria compared with samples failing the QC criteria.

Conclusion

Based on the aberrant maintenance gene data generated from samples failing the established QC criteria, we propose that the QC criteria outlined in this study can accurately distinguish high quality from low quality data, and can be used to delete poor quality microarray samples before proceeding to higher-order biological analyses and interpretation.

An integrated bioinformatics approach to improve two-color microarray quality-control: impact on biological conclusions

Omics technology used for large-scale measurements of gene expression is rapidly evolving. This work pointed out the need of an extensive bioinformatics analyses for array quality assessment before and after gene expression clustering and pathway analysis. A study focused on the effect of red wine polyphenols on rat colon mucosa was used to test the impact of quality control and normalisation steps on the biological conclusions. The integration of data visualization, pathway analysis and clustering revealed an artifact problem that was solved with an adapted normalisation. We propose a possible point to point standard analysis procedure, based on a combination of clustering and data visualization for the analysis of microarray data.

Quality control of microarray assays for toxicogenomic and in vitro diagnostic applications

The generation of high-quality microarray data for toxicogenomics can be affected by the study design and methods used for sample acquisition, preparation, and processing. Bias can be introduced during animal treatment, tissue handling, and sample preparation. Metrics and controls used in assessing RNA integrity and the quality of microarray sample generation are reviewed in this chapter. Regulations and guidelines involved in the application of microarrays as a commercial in vitro diagnostic device are also described.

Methodological considerations for gene expression profiling of human brain

Gene expression profiles of postmortem brain tissue represent important resources for understanding neuropsychiatric illnesses. The impact(s) of quality covariables on the analysis and results of gene expression studies are important questions. This paper addressed critical variables which might affect gene expression in two brain regions. Four broad groups of quality indicators in gene expression profiling studies (clinical, tissue, RNA, and microarray quality) were identified. These quality control indicators were significantly correlated, however one quality variable did not account for the total variance in microarray gene expression. The data showed that agonal factors and low pH correlated with decreased integrity of extracted RNA in two brain regions. These three parameters also modulated the significance of alterations in mitochondrial-related genes. The average F-ratio summaries across all transcripts showed that RNA degradation from the AffyRNAdeg program accounted for higher variation than all other quality factors. Taken together, these findings confirmed prior studies, which indicated that quality parameters including RNA integrity, agonal factors, and pH are related to differences in gene expression profiles in postmortem brain. Individual candidate genes can be evaluated with these quality parameters in post hoc analysis to help strengthen the relevance to psychiatric disorders. We find that clinical, tissue, RNA, and microarray quality are all useful variables for collection and consideration in study design, analysis, and interpretation of gene expression results in human postmortem studies.

Ankyrin G overexpression in Hutchinson-Gilford progeria syndrome fibroblasts identified through biological filtering of expression profiles

Hutchinson-Gilford progeria syndrome (HGPS; MIM 176670) is a rare disease characterized by accelerated aging. In this study, light and immunofluorescence microscopy were used to assess morphological changes, measures of cell growth kinetics and gene expression profiles in HGPS cells and normal fibroblasts in culture. A filtering strategy was developed based on differentially expressed transcripts seen consistently across three culture stages based on cell passage number. This filtering strategy produced a list of 66 unique differentially expressed genes, of which approximately 40% were upregulated in HGPS cells compared to normal fibroblasts. The increased mRNA expression in HGPS cells that was seen for one gene defined using this strategy--namely ANK3--was validated using quantitative reverse-transcriptase amplification, Western analysis and immunofluorescence microscopy, all of which showed significantly increased ankyrin G expression. These findings demonstrate differences in morphology, growth kinetics and mRNA expression profiles in HGPS cells compared to normal fibroblasts in culture, including increased expression of ANK3/ankyrin G. Furthermore, other genes that co-clustered with ANK3 might provide mechanistic clues regarding senescence in cultured HGPS cells.

Functional annotation of IFN-alpha-stimulated gene expression profiles from sensitive and resistant renal cell carcinoma cell lines

The antiproliferative, antiviral, and immunomodulatory properties of interferons (IFNs) have led to its therapeutic implementation. IFNs effects are mediated by a complex network of signal transducers, culminating in IFN-stimulated gene (ISG) induction. This complexity leads to diverse clinical responses to IFN, from no response to complete regression of disease. Elucidation of ISG induction patterns is, therefore, essential to understand and maximize its therapeutic potential. To correlate ISG expression profiles with IFN responsiveness, two renal cell carcinoma (RCC) cell lines differing in antiviral and apoptotic response to IFN were treated with IFN-alpha for different times, and expression profiles were analyzed using a customized microarray containing 850 unique putative ISGs. Genes with similar kinetics of induction in both cell lines were clustered and analyzed for gene function. Seven sets of coordinately regulated genes were identified by k-means cluster analysis, and significant functional similarities were identified for five of the seven sets. Strikingly, expression of genes associated with transcription temporally preceded expression of those involved in signal transduction. Enhanced antiviral sensitivity to IFN was coincident with sustained expression of ISGs involved in transcriptional regulation. However, no difference in Stat1 activation was observed between the cell lines. Analysis of ISG expression patterns suggests that subtle differences in transcription profiles contribute to differences in IFN responsiveness.