Resource and hardware options for microarray-based experimentation.

DNA microarray technology permits the study of biological systems and processes on a genome-wide scale. Arrays based on cDNA clones, oligonucleotides and genomic clones have been developed for investigations of gene expression, genetic analysis and genomic changes associated with disease. Over the past 3-4 years, microarrays have become more widely available to the research community. This has occurred through increased commercial availability of custom and generic arrays and the development of robotic equipment that has enabled array printing and analysis facilities to be established in academic research institutions. This brief review examines the public and commercial resources, the microarray fabrication and data capture and analysis equipment currently available to the user.     

Impact of DNA chips on haematological oncology

As the Human Genome Project hurtles towards completion, DNA microarray technology offers the potential to open wide new windows into the study of genome complexity. DNA chips can be used for many different purposes, most prominently to measure levels of gene expression (messenger RNA abundance) for tens of thousands of genes simultaneously. But how much of this data is useful and is some superfluous? Can array data be used to identify a handful of critical genes that will lead to a more detailed taxonomy of haematological malignancies and can this or similar array data be used to predict clinical outcome? It is still too early to predict what the ultimate impact of DNA chips will be on our understanding of cancer biology. There are many critically important questions about this new field that are yet unaddressed. By the publication of this article, it is hoped that the technology of DNA chips will be opened up and demystified, and that additional opportunities for creative exploration will be catalysed.     

In silico gene selection strategy for custom microarray design

Microarray technology has become an important tool for studying large-scale gene expression for a diversity of biological applications. However, there are a number of experimental settings for which commercial arrays are either unsuitable or unavailable despite the existence of sequence information. With the increasing availability of custom array manufacturing services, it is now feasible to design high-density arrays for any organism having sequence data. However, there have been relatively few reports discussing gene selection, an important first step in array design. Here we propose an in silico strategy for custom microarray gene selection that is applicable to a wide range of organisms, based on utilizing public domain microarray information to interrogate existing sequence data and to identify a set of homologous genes in any organism of interest. We demonstrate the utility of this approach by applying it to the selection of candidate genes for a custom Xenopus laevis microarray. A significant finding of this study is that 3%-4% of Xenopus expressed sequence tags (ESTs) are in an orientation contrary to that indicated in the public database entry (http://mssaha.people.wm.edu/suppMSS.html).     

Current issues for DNA microarrays: platform comparison, double linear amplification, and universal RNA reference

DNA microarray technology has been widely used to simultaneously determine the expression levels of thousands of genes. A variety of approaches have been used, both in the implementation of this technology and in the analysis of the large amount of expression data. However, several practical issues still have not been resolved in a satisfactory manner, and among the most critical is the lack of agreement in the results obtained in different array platforms. In this study, we present a comparison of several microarray platforms [Affymetrix oligonucleotide arrays, custom complementary DNA (cDNA) arrays, and custom oligo arrays printed with oligonucleotides from three different sources] as well as analysis of various methods used for microarray target preparation and the reference design. The results indicate that the pairwise correlations of expression levels between platforms are relative low overall but that the log ratios of the highly expressed genes are strongly correlated, especially between Affymetrix and cDNA arrays. The microarray measurements were compared with quantitative real-time-polymerase chain reaction (QRT-PCR) results for 23 genes, and the varying degrees of agreement for each platform were characterized. We have also developed and tested a double amplification method which allows the use of smaller amounts of starting material. The added round of amplification produced reproducible results as compared to the arrays hybridized with single round amplified targets. Finally, the reliability of using a universal RNA reference for two-channel microarrays was tested and the results suggest that comparisons of multiple experimental conditions using the same control can be accurate.     

Characterization of DNA chips by nanogold staining

DNA microarray is an important tool in biomedical research. Up to now, there are no chips that can allow both quality analysis and hybridization using the same chip. It is risky to draw conclusions from results of different chips if there is no knowledge of the quality of the chips before hybridization. In this article, we report a colorimetric method to do quality control on an array. The quality analysis of probe spots can be obtained by using gold nanoparticles with positive charges to label DNA through electrostatic attraction. The probe spots can also be detected by a simple personal computer scanner. Gold nanoparticles deposited on a glass surface can be dissolved in bromine-bromide solution. The same microarray treated with gold particles staining and destaining can still be used for hybridization with nearly the same efficiency. This approach makes quality control of a microarray chip feasible and should be a valuable tool for biomarker discovery in the future.     

DNA microarray experiments: biological and technological aspects

DNA microarray technologies, such as cDNA and oligonucleotide microarrays, promise to revolutionize biological research and further our understanding of biological processes. Due to the complex nature and sheer amount of data produced from microarray experiments, biologists have sought the collaboration of experts in the analytical sciences, including statisticians, among others. However, the biological and technical intricacies of microarray experiments are not easily accessible to analytical experts. One aim for this review is to provide a bridge to some of the relevant biological and technical aspects involved in microarray experiments. While there is already a large literature on the broad applications of the technology, basic research on the technology itself and studies to understand process variation remain in their infancy. We emphasize the importance of basic research in DNA array technologies to improve the reliability of future experiments.     

ARROGANT: an application to manipulate large gene collections

ARROGANT (ARRay OrGANizing Tool) is a software tool developed to facilitate the identification, annotation and comparison of large collections of genes or clones. The objective is to enable users to compile gene/clone collections from different databases, allowing them to design experiments and analyze the collections as well as associated experimental data efficiently. ARROGANT can relate different sequence identifiers to their common reference sequence using the UniGene database, allowing for the comparison of data from two different microarray experiments. ARROGANT has been successfully used to analyze microarray expression data for colon cancer, to compile genes potentially related to cardiac diseases for subsequent resequencing (to identify single nucleotide polymorphisms, SNPs), to design a new comprehensive human cDNA microarray for cancer, to combine and compare expression data generated by different microarrays and to provide annotation for genes on custom and Affymetrix chips.     

Gene expression signatures in primary immunodeficiencies: the experience from human disease and mouse models

Extensive research on molecular genetics in recent decades has provided a wealth of information regarding the underlying mechanisms of primary immunodeficiency diseases. The microarray technology has made its entry into the molecular biology research area and hereby enabled signature expression profiling of whole species genomes. Perhaps no other methodological approach has transformed molecular biology more in recent years than the use of microarrays. Microarray technology has led the way from studies of the individual biological functions of a few related genes, proteins or, at best, pathways towards more global investigations of cellular activity. The development of this technology immediately yielded new and interesting information, and has produced more data than can be currently dealt with. It has also helped to realize that even a 'horizontally exhaustive' molecular analysis is insufficient. Applications of this tool in primary immunodeficiency studies have generated new information, which has led to a better understanding of the underlying basic biology of the diseases. Also, the technology has been used as an exploratory tool to disease genes in immunodeficiency diseases of unknown cause as in the case of the CD3Delta-chain and the MAPBPIP deficiency. For X-linked agammaglobulinemia, the technique has provided better understanding of the genes influenced by Btk. There is considerable hope that the microarray technology will lead to a better understanding of disease processes and the molecular phenotypes obtained from microarray experiments may represent a new tool for diagnosis of the disease.     

Protein micro- and macroarrays: digitizing the proteome

The early applications of microarrays and detection technologies have been centered on DNA-based applications. The application of array technologies to proteomics is now occurring at a rapid rate. Numerous researchers have begun to develop technologies for the creation of microarrays of protein-based screening tools. The stability of antibody molecules when bound to surfaces has made antibody arrays a starting point for proteomic microarray technology. To minimize disadvantages due to size and availability, some researchers have instead opted for antibody fragments, antibody mimics or phage display technology to create libraries for protein chips. Even further removed from antibodies are libraries of aptamers, which are single-stranded oligonucleotides that express high affinity for protein molecules. A variation on the theme of protein chips arrayed with antibody mimics or other protein capture ligand is that of affinity MS where the protein chips are directly placed in a mass spectrometer for detection. Other approaches include the creation of intact protein microarrays directly on glass slides or chips. Although many of the proteins may likely be denatured, successful screening has been demonstrated. The investigation of protein-protein interactions has formed the basis of a technique called yeast two-hybrid. In this method, yeast "bait" proteins can be probed with other yeast "prey" proteins fused to DNA binding domains. Although the current interpretation of protein arrays emphasizes microarray grids of proteins or ligands on glass slides or chips, 2-D gels are technically macroarrays of authentic proteins. In an innovative departure from the traditional concept of protein chips, some researchers are implementing microfluidic printing of arrayed chemistries on individual protein spots blotted onto membranes. Other researchers are using in-jet printing technology to create protein microarrays on chips. The rapid growth of proteomics and the active climate for new technology is driving a new generation of companies and academic efforts that are developing novel protein microarray techniques for the future.     

Fast large scale oligonucleotide selection using the longest common factor approach

We present a fast method that selects oligonucleotide probes (such as DNA 25-mers) for microarray experiments on a truly large scale. For example, reliable oligos for human genes can be found within four days, a speedup of one to two orders of magnitude compared to previous approaches. This speed is attained by using the longest common substring as a specificity measure for candidate oligos. We present a space- and time-efficient algorithm, based on a suffix array with additional information, to compute matching statistics (lengths of longest matches) between all candidate oligos and all remaining sequences. With the matching statistics available, we show how to incorporate constraints such as oligo length, melting temperature, and self-complementarity into the selection process at a postprocessing stage. As a result, we can now design custom oligos for any sequenced genome, just as the technology for on-site chip synthesis is becoming increasingly mature.     

Genomic DNA microarrays for Entamoeba histolytica: applications for use in expression profiling and strain genotyping

The parasite Entamoeba histolytica is a causative agent of dysentery and liver abscesses. Found predominantly in developing countries, this parasitic infection is responsible for significant morbidity and mortality. We have developed a genomic DNA microarray for E. histolytica. The array composed of 11,328 clones contains >2000 unique genes and was utilized for expression profiling and comparative genomic hybridizations of Entamoeba strains. We present a synopsis of our results to date and potential future applications of microarray technology for the study of Entamoeba biology.     

Intra-Platform Repeatability and Inter-Platform Comparability of MicroRNA Microarray Technology

Over the last decade, DNA microarray technology has provided a great contribution to the life sciences. The MicroArray Quality Control (MAQC) project demonstrated the way to analyze the expression microarray. Recently, microarray technology has been utilized to analyze a comprehensive microRNA expression profiling. Currently, several platforms of microRNA microarray chips are commercially available. Thus, we compared repeatability and comparability of five different microRNA microarray platforms (Agilent, Ambion, Exiqon, Invitrogen and Toray) using 309 microRNAs probes, and the Taqman microRNA system using 142 microRNA probes. This study demonstrated that microRNA microarray has high intra-platform repeatability and comparability to quantitative RT-PCR of microRNA. Among the five platforms, Agilent and Toray array showed relatively better performances than the others. However, the current lineup of commercially available microRNA microarray systems fails to show good inter-platform concordance, probably because of lack of an adequate normalization method and severe divergence in stringency of detection call criteria between different platforms. This study provided the basic information about the performance and the problems specific to the current microRNA microarray systems.     

Differences in gene expression between B-cell chronic lymphocytic leukemia and normal B cells: a meta-analysis of three microarray studies

MOTIVATION: A major focus of current cancer research is to identify genes that can be used as markers for prognosis and diagnosis, and as targets for therapy. Microarray technology has been applied extensively for this purpose, even though it has been reported that the agreement between microarray platforms is poor. A critical question is: how can we best combine the measurements of matched genes across microarray platforms to develop diagnostic and prognostic tools related to the underlying biology? RESULTS: We introduce a statistical approach within a Bayesian framework to combine the microarray data on matched genes from three investigations of gene expression profiling of B-cell chronic lymphocytic leukemia (CLL) and normal B cells (NBC) using three different microarray platforms, oligonucleotide arrays, cDNA arrays printed on glass slides and cDNA arrays printed on nylon membranes. Using this approach, we identified a number of genes that were consistently differentially expressed between CLL and NBC samples.     

Strategy for the design of custom cDNA microarrays

DNA microarrays are valuable but expensive tools for expression profiling of cells, tissues, and organs. The design of custom microarrays leads to cost reduction without necessarily compromising their biological value. Here we present a strategy for designing custom cDNA microarrays and constructed a microarray for mouse immunology research (ImmunoChip). The strategy used interrogates expressed sequence tag databases available in the public domain but overcomes many of the problems encountered. Immunologically relevant clusters were selected based on the expression of expressed sequence tags in relevant libraries. Selected clusters were organized in modules, and the best representative clones were identified. When tested, this microarray was found to have minimal clone identity errors or phage contamination and identified molecular signatures of lymphoid cell lines. Our proposed design of custom microarrays avoids probe redundancy, allows the organization of the chip to optimize chip production, and reduces microarray production costs. The strategy described is also useful for the design of oligonucleotide microarrays.     

Quantitative analysis of DNA array autoradiographs

DNA arrays and chips are powerful new tools for gene expression profiling. Current arrays contain hundreds or thousands of probes and large scale sequencing and screening projects will likely lead to the creation of global genomic arrays. DNA arrays and chips will be key in understanding how genes respond to specific changes of environment and will also greatly assist in drug discovery and molecular diagnostics. To facilitate widespread realization of the quantitative potential of this approach, we have designed procedures and software which facilitate analysis of autoradiography films with accuracy comparable to phosphorimaging devices. Algorithms designed for analysis of DNA array autoradiographs incorporate 3-D peak fitting of features on films and estimation of local backgrounds. This software has a flexible grid geometry and can be applied to different types of DNA arrays, including custom arrays.     

The application of single nucleotide polymorphism microarrays in cancer research

The development of microarray technology has had a significant impact on the genetic analysis of human disease. The recently developed single nucleotide polymorphism (SNP) array can be used to measure both DNA polymorphism and dosage changes. Our laboratory has applied SNP microarray analysis to uncover frequent uniparental disomies and sub-microscopic genomic copy number gains and losses in different cancers. This review will focus on the wide range of applications of SNP microarray analysis to cancer research. SNP array genotyping can determine loss of heterozygosity, genomic copy number changes and DNA methylation alterations of cancer cells. The same technology can also be used to investigate allelic association in cancers. Therefore, it can be applied to the identification of cancer predisposition genes, oncogenes and tumor suppressor genes in specific types of tumors. As a consequence, they have potential in cancer risk assessment, diagnosis, prognosis and treatment selection.     

Microarray Meta-Analysis Identifies Acute Lung Injury Biomarkers in Donor Lungs That Predict Development of Primary Graft Failure in Recipients

Objectives

To perform a meta-analysis of gene expression microarray data from animal studies of lung injury, and to identify an injury-specific gene expression signature capable of predicting the development of lung injury in humans.

Methods

We performed a microarray meta-analysis using 77 microarray chips across six platforms, two species and different animal lung injury models exposed to lung injury with or/and without mechanical ventilation. Individual gene chips were classified and grouped based on the strategy used to induce lung injury. Effect size (change in gene expression) was calculated between non-injurious and injurious conditions comparing two main strategies to pool chips: (1) one-hit and (2) two-hit lung injury models. A random effects model was used to integrate individual effect sizes calculated from each experiment. Classification models were built using the gene expression signatures generated by the meta-analysis to predict the development of lung injury in human lung transplant recipients.

Results

Two injury-specific lists of differentially expressed genes generated from our meta-analysis of lung injury models were validated using external data sets and prospective data from animal models of ventilator-induced lung injury (VILI). Pathway analysis of gene sets revealed that both new and previously implicated VILI-related pathways are enriched with differentially regulated genes. Classification model based on gene expression signatures identified in animal models of lung injury predicted development of primary graft failure (PGF) in lung transplant recipients with larger than 80% accuracy based upon injury profiles from transplant donors. We also found that better classifier performance can be achieved by using meta-analysis to identify differentially-expressed genes than using single study-based differential analysis.

Conclusion

Taken together, our data suggests that microarray analysis of gene expression data allows for the detection of “injury" gene predictors that can classify lung injury samples and identify patients at risk for clinically relevant lung injury complications.