A status report on MAGE

Recently, the Microarray Gene Expression Data Society (MGED,www.mged.org) was awarded funds from NHGRI/NIH to continue developmentof MAGE, the MGED Ontology (MO) and related technologies forcommunication and interpretation of microarray data. This awardreflects NIH's substantial commitment of resources to microarrayexperimentation and the recognition that these data should bepreserved. In this editorial I discuss MGED's goals, show howMGED's efforts have helped the microarray community and describeMGED's future efforts in the context of the recent award. What is MGED Trying to Do? MGED's efforts are 2-fold. First, it is committed to ensurethat microarray experiments are scientifically sound. Second,it is involved in building the infrastructure that will support     

Transcriptional signatures of normal human mammary epithelial cells in response to benzo[a]pyrene exposure: a comparison of three microarray platforms

Microarrays are used to study gene expression in a variety of biological systems. A number of different platforms have been developed, but few studies exist that have directly compared the performance of one platform with another. The goal of this study was to determine array variation by analyzing the same RNA samples with three different array platforms. Using gene expression responses to benzo[a]pyrene exposure in normal human mammary epithelial cells (NHMECs), we compared the results of gene expression profiling using three microarray platforms: photolithographic oligonucleotide arrays (Affymetrix), spotted oligonucleotide arrays (Amersham), and spotted cDNA arrays (NCI). While most previous reports comparing microarrays have analyzed pre-existing data from different platforms, this comparison study used the same sample assayed on all three platforms, allowing for analysis of variation from each array platform. In general, poor correlation was found with corresponding measurements from each platform. Each platform yielded different gene expression profiles, suggesting that while microarray analysis is a useful discovery tool, further validation is needed to extrapolate results for broad use of the data. Also, microarray variability needs to be taken into consideration, not only in the data analysis but also in specific probe selection for each array type.     

Normalization of microarray data: single-labeled and dual-labeled arrays

DNA microarray is a powerful tool for high-throughput analysis of biological systems. Various computational tools have been created to facilitate the analysis of the large volume of data produced in DNA microarray experiments. Normalization is a critical step for obtaining data that are reliable and usable for subsequent analysis such as identification of differentially expressed genes and clustering. A variety of normalization methods have been proposed over the past few years, but no methods are still perfect. Various assumptions are often taken in the process of normalization. Therefore, the knowledge of underlying assumption and principle of normalization would be helpful for the correct analysis of microarray data. We present a review of normalization techniques from single-labeled platforms such as the Affymetrix GeneChip array to dual-labeled platforms like spotted array focusing on their principles and assumptions.     

SuperSAGE array: the direct use of 26-base-pair transcript tags in oligonucleotide arrays

We developed a new platform for genome-wide gene expression analysis in any eukaryotic organism, which we called SuperSAGE array. The SuperSAGE array is a microarray onto which 26-bp oligonucleotides corresponding to SuperSAGE tag sequences are directly synthesized. A SuperSAGE array combines the advantages of the highly quantitative SuperSAGE expression analysis with the high-throughput microarray technology. We demonstrated highly reproducible gene expression profiling by the SuperSAGE array for 1,000 genes (tags) in rice. We also applied this technology to the detailed study of expressed genes identified by SuperSAGE in Nicotiana benthamiana, an organism for which sufficient genome sequence information is not available. We propose that the SuperSAGE array system represents a new paradigm for microarray construction, as no genomic or cDNA sequence data are required for its preparation.     

Microarrays in brain research: the good, the bad and the ugly

Making sense of microarray data is a complex process, in which the interpretation of findings will depend on the overall experimental design and judgement of the investigator performing the analysis. As a result, differences in tissue harvesting, microarray types, sample labelling and data analysis procedures make post hoc sharing of microarray data a great challenge. To ensure rapid and meaningful data exchange, we need to create some order out of the existing chaos. In these ground-breaking microarray standardization and data sharing efforts, NIH agencies should take a leading role     

DNA microarray technology in toxicogenomics of aquatic models: methods and applications

Toxicogenomics represents the merging of toxicology with genomics and bioinformatics to investigate biological functions of genome in response to environmental contaminants. Aquatic species have traditionally been used as models in toxicology to characterize the actions of environmental stresses. Recent completion of the DNA sequencing for several fish species has spurred the development of DNA microarrays allowing investigators access to toxicogenomic approaches. However, since microarray technology is thus far limited to only a few aquatic species and derivation of biological meaning from microarray data is highly dependent on statistical arguments, the full potential of microarray in aquatic species research has yet to be realized. Herein we review some of the issues related to construction, probe design, statistical and bioinformatical data analyses, and current applications of DNA microarrays. As a model a recently developed medaka (Oryzias latipes) oligonucleotide microarray was described to highlight some of the issues related to array technology and its application in aquatic species exposed to hypoxia. Although there are known non-biological variations present in microarray data, it remains unquestionable that array technology will have a great impact on aquatic toxicology. Microarray applications in aquatic toxicogenomics will range from the discovery of diagnostic biomarkers, to establishment of stress-specific signatures and molecular pathways hallmarking the adaptation to new environmental conditions.     

Parallel multiplicity and error discovery rate (EDR) in microarray experiments

Background  

In microarray gene expression profiling experiments, differentially expressed genes (DEGs) are detected from among tens of thousands of genes on an array using statistical tests. It is important to control the number of false positives or errors that are present in the resultant DEG list. To date, more than 20 different multiple test methods have been reported that compute overall Type I error rates in microarray experiments. However, these methods share the following dilemma: they have low power in cases where only a small number of DEGs exist among a large number of total genes on the array.     

Microarray data quality - review of current developments

DNA microarray technologies have evolved rapidly to become a key high-throughput technology for the simultaneous measurement of the relative expression levels of thousands of individual genes. However, despite the widespread adoption of DNA microarray technology, there remains considerable uncertainty and scepticism regarding data obtained using these technologies. Comparing results from seemingly identical experiments from different laboratories or even from different days can prove challenging; these challenges increase further when data from different array platforms need to be compared. To comply with emerging regulations, the quality of the data generated from array experiments needs to be clearly demonstrated. This review describes several initiatives that aim to improve confidence in data generated by array experiments, including initiatives to develop standards for data reporting and storage, external spike-in controls, quality control procedures, best practice guidelines, and quality metrics.     

Toward optimized antibody microarrays: a comparison of current microarray support materials

With the advent of protein and antibody microarray technology several different coatings and protocols have been published, which may be broadly divided into two types: gel-coated surfaces and plain non-gel-coated glass or plastic surfaces, some with chemical groups attached. We have screened 11 different array surfaces of both types and compared them with respect to their detection limit, inter- and intrachip variation, and storage characteristics. Five different antibodies were immobilized onto each type of microarray support, with total protein concentrations ranging from 40 fmol to 25 amol per spot. From these results, it was seen that some antibodies were more suited for use on antibody arrays. All measurements were performed in quadruplicate, and the results revealed high signal uniformity and reproducibility of most plain glass and plastic slides. Lower detection limits were obtained with polyacrylamide-coated slides, making them more suitable for the detection of very low concentrations of antigen. All microarray coatings could be stored for a period of 8 weeks; however, improved results were seen after 2 weeks of storage. In conclusion, the results indicate the need to test each antibody to be used on an antibody array and to select the microarray coating based on experimental requirements.     

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.     

Development and characterization of a Chinese hamster ovary cell-specific oligonucleotide microarray

The Chinese hamster ovary (CHO) cell line is one of the most widely used mammalian cell lines for biopharmaceutical production. We have developed and characterized a gene expression microarray (WyeHamster2a) specific for CHO cells that has enabled the study of ~3,500 sequences. Analysis of multiple sets of replicate scans showed that data derived from the WyeHamster2a array is highly reproducible confirming it as a robust tool for profiling. Twelve gene sequences were selected for follow-up RT-qPCR to confirm the accuracy and precision of the microarray results. In all but the most subtle gene expression differences, the microarray proved to be a reliable measure of differential gene expression. Finally, we were able to quantify the difference between using a bona fide CHO-specific microarray for profiling CHO cells versus an alternate, commercially available, rodent microarray such as a mouse or rat-specific format.     

Accurate detection of aneuploidies in array CGH and gene expression microarray data

MOTIVATION: Chromosomal copy number changes (aneuploidies) are common in cell populations that undergo multiple cell divisions including yeast strains, cell lines and tumor cells. Identification of aneuploidies is critical in evolutionary studies, where changes in copy number serve an adaptive purpose, as well as in cancer studies, where amplifications and deletions of chromosomal regions have been identified as a major pathogenetic mechanism. Aneuploidies can be studied on whole-genome level using array CGH (a microarray-based method that measures the DNA content), but their presence also affects gene expression. In gene expression microarray analysis, identification of copy number changes is especially important in preventing aberrant biological conclusions based on spurious gene expression correlation or masked phenotypes that arise due to aneuploidies. Previously suggested approaches for aneuploidy detection from microarray data mostly focus on array CGH, address only whole-chromosome or whole-arm copy number changes, and rely on thresholds or other heuristics, making them unsuitable for fully automated general application to gene expression datasets. There is a need for a general and robust method for identification of aneuploidies of any size from both array CGH and gene expression microarray data. RESULTS: We present ChARM (Chromosomal Aberration Region Miner), a robust and accurate expectation-maximization based method for identification of segmental aneuploidies (partial chromosome changes) from gene expression and array CGH microarray data. Systematic evaluation of the algorithm on synthetic and biological data shows that the method is robust to noise, aneuploidal segment size and P-value cutoff. Using our approach, we identify known chromosomal changes and predict novel potential segmental aneuploidies in commonly used yeast deletion strains and in breast cancer. ChARM can be routinely used to identify aneuploidies in array CGH datasets and to screen gene expression data for aneuploidies or array biases. Our methodology is sensitive enough to detect statistically significant and biologically relevant aneuploidies even when expression or DNA content changes are subtle as in mixed populations of cells. AVAILABILITY: Code available by request from the authors and on Web supplement at http://function.cs.princeton.edu/ChARM/     

TECHNICAL ADVANCES: A microarray for large-scale genomic and transcriptional analyses of the zebra finch (Taeniopygia guttata) and other passerines

The microarray technology has revolutionized biological research in the last decade. By monitoring the expression of many genes simultaneously, microarrays can elucidate gene function, as well as scan entire genomes for candidate genes encoding complex traits. However, because of high costs of sequencing and design, microarrays have largely been restricted to a few model species. Cross-species microarray (CSM) analyses, where microarrays are used for other species than the one they were designed for, have had varied success. We have conducted a CSM analysis by hybridizing genomic DNA from the common whitethroat (Sylvia communis) on a newly developed Affymetrix array designed for the zebra finch (Taeniopygia guttata), the Lund-zf array. The results indicate a very high potential for the zebra finch array to act as a CSM utility in other passerine birds. When hybridizing zebra finch genomic DNA, 98% of the gene representatives had higher signal intensities than the background cut-off, and for the common whitethroat, we found the equivalent proportion to be as high as 96%. This was surprising given the fact that finches and warblers diverged 25-50 million years ago, but may be explained by a relatively low sequence divergence between passerines (89-93%). Passerine birds are widely used in studies of ecology and evolution, and a zebra finch array that can be used for many species may have a large impact on future research directions.     

Development of an internally controlled antibody microarray

Antibody microarrays are a high throughput technology used to concurrently screen for protein expression. Most antibody arrays currently used are based on the ELISA sandwich approach that uses two antibodies to screen for the expression of a limited number of proteins. Also because antigen-antibody interactions are concentration-dependent, antibody microarrays need to normalize the amount of antibody that is used. In response to the limitations with the currently existing technology we have developed a single antibody-based microarray where the quantity of antibody spotted is used to standardize the antigen concentration. In addition, this new array utilizes an internally controlled system where one color represents the amount of antibody spotted, and the other color represents the amount of the antigen that is used to quantify the level of protein expression. When compared with median fluorescence intensity alone, normalization for antibody spot intensity decreased variability and lowered the limits of detection. This new antibody array was tested using standard cytokine proteins and also cell lysates obtained from mouse macrophages stimulated in vitro and evaluated for the expression of the cytokine proteins interleukin (IL)-1beta, IL-5, IL-6, and macrophage inflammatory proteins 1alpha and 1beta. The levels of protein expression seen with the antibody microarray was compared with that obtained with Western blot analysis, and the magnitude of protein expression observed was similar with both technologies with the antibody array actually showing a greater degree of sensitivity. In summary, we have developed a new type of antibody microarray to screen for protein expression that utilizes a single antibody and controls for the amount of antibody spotted. This type of array appears at least as sensitive as Western blot analysis, and the technology can be scaled up for high throughput screening for hundreds of proteins in complex biofluids such as blood.     

Rapid and quantitative quality control of microarrays using cationic nanoparticles

The fabrication quality of microarrays significantly influences the accuracy and reproducibility of microarray experiments. In this report, we present a simple and fast quality control (QC) method for spotted oligonucleotide and cDNA microarrays. It employs a nonspecific electrostatic interaction of colloidal gold nanoparticles with the chemical groups of DNA molecules and other biomolecules immobilized on the microarray surface that bear positive or negative charges. An inexpensive flatbed scanner is used to visualize and quantify the binding of cationic gold particles to the anionic DNA probes on the microarray surface. An image analysis software was designed to assess the various parameters of the array spots including spot intensity, shape and array homogeneity, calculate the overall array quality score, and save the detailed array quality report in an Excel file. The gold staining technique is fast and sensitive. It can be completed in 10 min and detect less than 1% of the probe amount commonly recommended for microarrays. Compared to the current microarray QC method that utilizes the hybridization of probes with short random sequence oligonucleotides labeled with fluorophore, our gold staining method requires less time for the analysis, reduces the reagent cost, and eliminates the need for the expensive laser scanner. Biotechnol. Bioeng. 2009; 102: 960–964. © 2008 Wiley Periodicals, Inc.     

Application of carbohydrate microarray technology for the detection of Burkholderia pseudomallei, Bacillus anthracis and Francisella tularensis antibodies

We developed a microarray platform by immobilizing bacterial 'signature' carbohydrates onto epoxide modified glass slides. The carbohydrate microarray platform was probed with sera from non-melioidosis and melioidosis (Burkholderia pseudomallei) individuals. The platform was also probed with sera from rabbits vaccinated with Bacillus anthracis spores and Francisella tularensis bacteria. By employing this microarray platform, we were able to detect and differentiate B. pseudomallei, B. anthracis and F. tularensis antibodies in infected patients, and infected or vaccinated animals. These antibodies were absent in the sera of na?ve test subjects. The advantages of the carbohydrate microarray technology over the traditional indirect hemagglutination and microagglutination tests for the serodiagnosis of melioidosis and tularemia are discussed. Furthermore, this array is a multiplex carbohydrate microarray for the detection of all three biothreat bacterial infections including melioidosis, anthrax and tularemia with one, multivalent device. The implication is that this technology could be expanded to include a wide array of infectious and biothreat agents.