Cross-species hybridisation of pig RNA to human nylon microarrays

Background

The objective of this research was to investigate the reproducibility of cross-species microarray hybridisation. Comparisons between same- and cross-species hybridisations were also made. Nine hybridisations between a single pig skeletal muscle RNA sample and three human cDNA nylon microarrays were completed. Three replicate hybridisations of two different amounts of pig RNA, and of human skeletal muscle RNA were completed on three additional microarrays.

Results

Reproducibility of microarray hybridisations of pig cDNA to human microarrays was high, as determined by Spearman and Pearson correlation coefficients and a Kappa statistic. Variability among replicate hybridisations was similar for human and pig data, indicating the reproducibility of results were not compromised in cross-species hybridisations. The concordance between data generated from hybridisations using pig and human skeletal muscle RNA was high, further supporting the use of human microarrays for the analysis of gene expression in the pig. No systematic effect of stripping and re-using nylon microarrays was found, and variability across microarrays was minimal.

Conclusion

The majority of genes generated highly reproducible data in cross-species microarray hybridisations, although approximately 6% were identified as highly variable. Experimental designs that include at least three replicate hybridisations for each experimental treatment will enable the variability of individual genes to be considered appropriately. The use of cross-species microarray analysis looks promising. However, additional validation is needed to determine the specifiCity of cross-species hybridisations, and the validity of results.     

Optimization and evaluation of T7 based RNA linear amplification protocols for cDNA microarray analysis

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.     

Compatible solutes from hyperthermophiles improve the quality of DNA microarrays

Background

DNA microarrays are among the most widely used technical platforms for DNA and RNA studies, and issues related to microarrays sensitivity and specificity are therefore of general importance in life sciences. Compatible solutes are derived from hyperthermophilic microorganisms and allow such microorganisms to survive in environmental and stressful conditions. Compatible solutes show stabilization effects towards biological macromolecules, including DNA.

Results

We report here that compatible solutes from hyperthermophiles increased the performance of the hybridization buffer for Affymetrix GeneChip^® arrays. The experimental setup included independent hybridizations with constant RNA over a wide range of compatible solute concentrations. The dependence of array quality and compatible solute was assessed using specialized statistical tools provided by both the proprietary Affymetrix quality control system and the open source Bioconductor suite.

Conclusion

Low concentration (10 to 25 mM) of hydroxyectoine, potassium mannosylglycerate and potassium diglycerol phosphate in hybridization buffer positively affected hybridization parameters and enhanced microarrays outcome. This finding harbours a strong potential for the improvement of DNA microarray experiments.     

Optimized procedures for microarray analysis of histological specimens processed by laser capture microdissection

Analysis of cell-specific gene expression patterns using microarrays can reveal genes that are differentially expressed in diseased and normal tissue, as well as identify genes associated with specialized cellular functions. However, the cellular heterogeneity of the tissues precludes the resolution of expression profiles of specific cell types. While laser capture microdissection (LCM) can be used to obtain purified cell populations, the limited quantity of RNA isolated makes it necessary to perform an RNA amplification step prior to microarray analysis. The linearity and reproducibility of two RNA amplification protocols--the Baugh protocol (Baugh et al., 2001, Nucleic Acids Res 29:E29) and an in-house protocol have been assessed by conducting microarray analyses. Cy3-labeled total RNA from the colorectal cell line Colo-205 was compared to Cy5-labeled Colo-205 amplified RNA (aRNA) generated with each of the two protocols, using a human 10K cDNA array. The correlation of the gene intensities between amplified and total RNA measured in the two channels of each microarray was 0.72 and 0.61 for the Baugh protocol and the in-house protocol, respectively. The two protocols were further evaluated using aRNA obtained from normal colonic crypt cross-sections isolated via LCM. In both cases a microarray profile representative of colonic mucosa was obtained; statistically, the Baugh protocol was superior. Furthermore, a substantial overlap between highly expressed genes in the Colo-205 cells and colonic crypts underscores the reliability of the microarray analysis of LCM-derived material. Taken together, these results demonstrate that LCM-derived tissue from histological specimens can generate abundant amounts of high-quality aRNA for subsequent microarray analysis.     

Obtaining reliable information from minute amounts of RNA using cDNA microarrays

Background  

High density cDNA microarray technology provides a powerful tool to survey the activity of thousands of genes in normal and diseased cells, which helps us both to understand the molecular basis of the disease and to identify potential targets for therapeutic intervention. The promise of this technology has been hampered by the large amount of biological material required for the experiments (more than 50 μg of total RNA per array). We have modified an amplification procedure that requires only 1 μg of total RNA. Analyses of the results showed that most genes that were detected as expressed or differentially expressed using the regular protocol were also detected using the amplification protocol. In addition, many genes that were undetected or weakly detected using the regular protocol were clearly detected using the amplification protocol. We have carried out a series of confirmation studies by northern blotting, western blotting, and immunohistochemistry assays.     

M<Superscript>3</Superscript>G: Maximum Margin Microarray Gridding

Background  

Complementary DNA (cDNA) microarrays are a well established technology for studying gene expression. A microarray image is obtained by laser scanning a hybridized cDNA microarray, which consists of thousands of spots representing chains of cDNA sequences, arranged in a two-dimensional array. The separation of the spots into distinct cells is widely known as microarray image gridding.     

Protein microarrays for highly parallel detection and quantitation of specific proteins and antibodies in complex solutions

Background

We describe a method for printing protein microarrays, and using these microarrays in a comparative fluorescence assay to measure the abundance of many specific proteins in complex solutions. A robotic device was used to print hundreds of specific antibody or antigen solutions in an array on the surface of derivatized microscope slides. Two complex protein samples, one serving as a standard for comparative quantitation, and the other representing an experimental sample in which the concentrations of specific proteins were to be measured, were labeled by covalent attachment of spectrally-resolvable fluorescent dyes. Specific antibody-antigen interactions localized specific components of the complex mixtures to defined cognate spots in the array, where the relative intensity of the fluorescent signals representing the experimental sample and the reference standard provided a measure of each protein's abundance in the experimental sample. To characterize the specificity, sensitivity and accuracy of this assay, we analyzed the performance of 115 antibody/antigen pairs.

Results

50% of the arrayed antigens, and 20% of the arrayed antibodies, provided specific and accurate measurements of their cognate ligands at or below concentrations of 1.6 µg/ml and 0.34 µg/ml, respectively. Some of the antibody/antigen pairs allowed detection of the cognate ligands at absolute concentrations below 1 ng/ml, and partial concentrations of less than 1 part in 10⁶, sensitivities sufficient for measurement of many clinically important proteins in patient blood samples.

Conclusions

Protein microarrays can provide a simple and practical means to characterize patterns of variation in hundreds or thousands of different proteins, in clinical or research applications.     

Quantifying stability in gene list ranking across microarray derived clinical biomarkers

Background

Genomic instability in cancer leads to abnormal genome copy number alterations (CNA) as a mechanism underlying tumorigenesis. Using microarrays and other technologies, tumor CNA are detected by comparing tumor sample CN to normal reference sample CN. While advances in microarray technology have improved detection of copy number alterations, the increase in the number of measured signals, noise from array probes, variations in signal-to-noise ratio across batches and disparity across laboratories leads to significant limitations for the accurate identification of CNA regions when comparing tumor and normal samples.

Methods

To address these limitations, we designed a novel "Virtual Normal" algorithm (VN), which allowed for construction of an unbiased reference signal directly from test samples within an experiment using any publicly available normal reference set as a baseline thus eliminating the need for an in-lab normal reference set.

Results

The algorithm was tested using an optimal, paired tumor/normal data set as well as previously uncharacterized pediatric malignant gliomas for which a normal reference set was not available. Using Affymetrix 250K Sty microarrays, we demonstrated improved signal-to-noise ratio and detected significant copy number alterations using the VN algorithm that were validated by independent PCR analysis of the target CNA regions.

Conclusions

We developed and validated an algorithm to provide a virtual normal reference signal directly from tumor samples and minimize noise in the derivation of the raw CN signal. The algorithm reduces the variability of assays performed across different reagent and array batches, methods of sample preservation, multiple personnel, and among different laboratories. This approach may be valuable when matched normal samples are unavailable or the paired normal specimens have been subjected to variations in methods of preservation.     

Real-time polymerase chain reaction-based exponential sample amplification for microarray gene expression profiling

Conventional approaches to target labeling for gene expression analysis using microarray technology typically require relatively large amounts of RNA, a serious limitation when the available sample is limited. Here we describe an alternative exponential sample amplification method by using quantitative real-time polymerase chain reaction (QRT-PCR) to follow the amplification and eliminate the overamplified cDNA which could distort the quantitative ratio of the starting mRNA population. Probes generated from nonamplified, PCR-amplified, and real-time-PCR-amplified cDNA samples were generated from lipopolysaccharide-treated and nontreated mouse macrophages and hybridized to mouse cDNA microarrays. Signals obtained from the three protocols were compared. Reproducibility and reliability of the methods were determined. The Pearson correlation coefficients for replica experiments were r=0.927 and r=0.687 for QRT-PCR-amplification and PCR-overamplification protocols, respectively. Chi2 test showed that overamplification resulted in major biases in expression ratios, while these alterations could be eliminated by following the cycling status with QRT-PCR. Our exponential sample amplification protocol preserves the original expression ratios and allows unbiased gene expression analysis from minute amounts of starting material.     

Comparative evaluation of linear and exponential amplification techniques for expression profiling at the single-cell level

Background  

Single-cell microarray expression profiling requires 10⁸-10⁹-fold amplification of the picogram amounts of total RNA typically found in eukaryotic cells. Several methods for RNA amplification are in general use, but little consideration has been given to the comparative analysis of those methods in terms of the overall validity of the data generated when amplifying from single-cell amounts of RNA, rather than their empirical performance in single studies.     

MicroRNA-125a is over-expressed in insulin target tissues in a spontaneous rat model of Type 2 Diabetes

Background

The methods used for sample selection and processing can have a strong influence on the expression values obtained through microarray profiling. Laser capture microdissection (LCM) provides higher specificity in the selection of target cells compared to traditional bulk tissue selection methods, but at an increased processing cost. The benefit gained from the higher tissue specificity realized through LCM sampling is evaluated in this study through a comparison of microarray expression profiles obtained from same-samples using bulk and LCM processing.

Methods

Expression data from ten lung adenocarcinoma samples and six adjacent normal samples were acquired using LCM and bulk sampling methods. Expression values were evaluated for correlation between sample processing methods, as well as for bias introduced by the additional linear amplification required for LCM sample profiling.

Results

The direct comparison of expression values obtained from the bulk and LCM sampled datasets reveals a large number of probesets with significantly varied expression. Many of these variations were shown to be related to bias arising from the process of linear amplification, which is required for LCM sample preparation. A comparison of differentially expressed genes (cancer vs. normal) selected in the bulk and LCM datasets also showed substantial differences. There were more than twice as many down-regulated probesets identified in the LCM data than identified in the bulk data. Controlling for the previously identified amplification bias did not have a substantial impact on the differences identified in the differentially expressed probesets found in the bulk and LCM samples.

Conclusion

LCM-coupled microarray expression profiling was shown to uniquely identify a large number of differentially expressed probesets not otherwise found using bulk tissue sampling. The information gain realized from the LCM sampling was limited to differential analysis, as the absolute expression values obtained for some probesets using this study's protocol were biased during the second round of amplification. Consequently, LCM may enable investigators to obtain additional information in microarray studies not easily found using bulk tissue samples, but it is of critical importance that potential amplification biases are controlled for.