Quantitative PCR deconstruction of discrepancies between results reported by different hybridization platforms.

Differences in hybridization platforms used in gene array analysis experiments can lead to significant differences in hybridization results. In this study we used quantitative reverse transcription-polymerase chain reaction (qRT-PCR) to investigate discrepant results between the National Institute of Environmental Health Sciences cDNA and Affymetrix oligo platforms used to evaluate hepatic gene expression changes in rats exposed to methapyrilene. Caldesmon cDNA platform hybridization results showed decreases in gene expression levels for the high-dose methapyrilene 7-day pooled samples compared with their controls. By contrast, the Affymetrix oligonucleotide platform showed increases in expression levels for these samples. Quantitative gene expression measurements provide an explanation for the discrepancies observed for these samples. In the case of caldesmon, there is a 74-base sequence in the cDNA clone that is absent in the Affymetrix sequence. The amplicon based on the cDNA clone shows > 100-fold suppression relative to the day 7 high-dose methapyrilene-pooled control. These data demonstrate the importance of using a "gold standard," such as qRT-PCR to confirm key hybridization results as well as to understand the sources of discrepancies resulting from different hybridization platforms

The Reproducibility of Lists of Differentially Expressed Genes in Microarray Studies

Reproducibility is a fundamental requirement in scientific experiments and clinical contexts. Recent publications raise concerns about the reliability of microarray technology because of the apparent lack of agreement between lists of differentially expressed genes (DEGs). In this study we demonstrate that (1) such discordance may stem from ranking and selecting DEGs solely by statistical significance (P) derived from widely used simple t-tests; (2) when fold change (FC) is used as the ranking criterion, the lists become much more reproducible, especially when fewer genes are selected; and (3) the instability of short DEG lists based on P cutoffs is an expected mathematical consequence of the high variability of the t-values. We recommend the use of FC ranking plus a non-stringent P cutoff as a baseline practice in order to generate more reproducible DEG lists. The FC criterion enhances reproducibility while the P criterion balances sensitivity and specificity

Cross-platform comparability of microarray technology: Intra-platform consistency and appropriate data analysis procedures are essential

BACKGROUND: The acceptance of microarray technology in regulatory decision-making is being challenged by the existence of various platforms and data analysis methods. A recent report (E. Marshall, Science, 306, 630–631, 2004), by extensively citing the study of Tan et al. (Nucleic Acids Res., 31, 5676–5684, 2003), portrays a disturbingly negative picture of the cross-platform comparability, and, hence, the reliability of microarray technology. RESULTS: We reanalyzed Tan's dataset and found that the intra-platform consistency was low, indicating a problem in experimental procedures from which the dataset was generated. Furthermore, by using three gene selection methods (i.e., p-value ranking, fold-change ranking, and Significance Analysis of Microarrays (SAM)) on the same dataset we found that p-value ranking (the method emphasized by Tan et al.) results in much lower cross-platform concordance compared to fold-change ranking or SAM. Therefore, the low cross-platform concordance reported in Tan's study appears to be mainly due to a combination of low intra-platform consistency and a poor choice of data analysis procedures, instead of inherent technical differences among different platforms, as suggested by Tan et al. and Marshall. CONCLUSION: Our results illustrate the importance of establishing calibrated RNA samples and reference datasets to objectively assess the performance of different microarray platforms and the proficiency of individual laboratories as well as the merits of various data analysis procedures. Thus, we are progressively coordinating the MAQC project, a community-wide effort for microarray quality control

Microarray scanner calibration curves: characteristics and implications

BACKGROUND: Microarray-based measurement of mRNA abundance assumes a linear relationship between the fluorescence intensity and the dye concentration. In reality, however, the calibration curve can be nonlinear. RESULTS: By scanning a microarray scanner calibration slide containing known concentrations of fluorescent dyes under 18 PMT gains, we were able to evaluate the differences in calibration characteristics of Cy5 and Cy3. First, the calibration curve for the same dye under the same PMT gain is nonlinear at both the high and low intensity ends. Second, the degree of nonlinearity of the calibration curve depends on the PMT gain. Third, the two PMTs (for Cy5 and Cy3) behave differently even under the same gain. Fourth, the background intensity for the Cy3 channel is higher than that for the Cy5 channel. The impact of such characteristics on the accuracy and reproducibility of measured mRNA abundance and the calculated ratios was demonstrated. Combined with simulation results, we provided explanations to the existence of ratio underestimation, intensity-dependence of ratio bias, and anti-correlation of ratios in dye-swap replicates. We further demonstrated that although Lowess normalization effectively eliminates the intensity-dependence of ratio bias, the systematic deviation from true ratios largely remained. A method of calculating ratios based on concentrations estimated from the calibration curves was proposed for correcting ratio bias. CONCLUSION: It is preferable to scan microarray slides at fixed, optimal gain settings under which the linearity between concentration and intensity is maximized. Although normalization methods improve reproducibility of microarray measurements, they appear less effective in improving accuracy

The balance of reproducibility, sensitivity, and specificity of lists of differentially expressed genes in microarray studies

<p>Abstract</p> <p>Background</p> <p>Reproducibility is a fundamental requirement in scientific experiments. Some recent publications have claimed that microarrays are unreliable because lists of differentially expressed genes (DEGs) are not reproducible in similar experiments. Meanwhile, new statistical methods for identifying DEGs continue to appear in the scientific literature. The resultant variety of existing and emerging methods exacerbates confusion and continuing debate in the microarray community on the appropriate choice of methods for identifying reliable DEG lists.</p> <p>Results</p> <p>Using the data sets generated by the MicroArray Quality Control (MAQC) project, we investigated the impact on the reproducibility of DEG lists of a few widely used gene selection procedures. We present comprehensive results from inter-site comparisons using the same microarray platform, cross-platform comparisons using multiple microarray platforms, and comparisons between microarray results and those from TaqMan – the widely regarded "standard" gene expression platform. Our results demonstrate that (1) previously reported discordance between DEG lists could simply result from ranking and selecting DEGs solely by statistical significance (<it>P</it>) derived from widely used simple <it>t</it>-tests; (2) when fold change (FC) is used as the ranking criterion with a non-stringent <it>P</it>-value cutoff filtering, the DEG lists become much more reproducible, especially when fewer genes are selected as differentially expressed, as is the case in most microarray studies; and (3) the instability of short DEG lists solely based on <it>P</it>-value ranking is an expected mathematical consequence of the high variability of the <it>t</it>-values; the more stringent the <it>P</it>-value threshold, the less reproducible the DEG list is. These observations are also consistent with results from extensive simulation calculations.</p> <p>Conclusion</p> <p>We recommend the use of FC-ranking plus a non-stringent <it>P </it>cutoff as a straightforward and baseline practice in order to generate more reproducible DEG lists. Specifically, the <it>P</it>-value cutoff should not be stringent (too small) and FC should be as large as possible. Our results provide practical guidance to choose the appropriate FC and <it>P</it>-value cutoffs when selecting a given number of DEGs. The FC criterion enhances reproducibility, whereas the <it>P </it>criterion balances sensitivity and specificity.</p

Strategic paths for biomarker qualification. Toxicology

Biomarkers may be qualified using different qualification processes. A passive approach for qualification has been to accept the end of discussions in the scientific literature as an indication that a biomarker has been accepted. An active approach to qualification requires development of a comprehensive process by which a consensus may be reached about the qualification of a biomarker. Active strategies for qualification include those associated with context-independent as well as context-dependent qualifications

Regulation of Gene Expression by Pegylated IFN-α2b and IFN-α2b in Human Peripheral Blood Mononuclear Cells

The pleiotropic biologic effects of interferon (IFN) are mediated through regulation of the expression of numerous IFN-sensitive genes. Peripheral blood mononuclear cells (PBMCs) obtained from healthy donors were analyzed to study the immunoregulatory and antiviral messenger RNAs (mRNAs) and proteins regulated by pegylated IFN-α2b (PEG-IFN-α2b) and IFN-α2b. A dose-dependent and time-dependent response for multiple IFN-regulated genes was observed. IFN-dependent protein production and secretion were correlated with IFN-regulated mRNA induction. Overall regulation of gene expression patterns for PEG-IFN-α2b and IFN-α2b was comparable, even though the antiviral activity of PEG-IFN-α2b demonstrated a longer biologic halflife in vitro compared with IFN-α2b. To study the heterogeneity of responses, PBMCs obtained from over 25 healthy donors were analyzed. Within a particular donor dataset, gene-specific and dose-dependent responses to PEG-IFN-α2b treatment, demonstrated in both the amplitude of transcriptional upregulation and the duration of sustained mRNA upregulation, were observed. However because of donor heterogeneity, the amplitude of a given transcriptional response could not be predicted for a specific dose of PEG-IFN-α2b. Notably, mRNA levels of oligoadenylate synthetase (OAS), double-stranded RNA (dsRNA)-activated protein kinase (PKR), IP-10, IFN-stimulated gene 54 (ISG54), and ISG15 were upregulated after 120 h of continuous PEG-IFN-α2b treatment. These results suggest that the use of antiviral and immunoregulatory protein mRNA levels as markers to assess the therapeutic efficacy of IFN-α2b and PEG-IFN-α2b against viral and neoplastic diseases in clinical trials is promising but will require further analysis using clinical patient samples