The next generation of microarray research: applications in evolutionary and ecological genomics

Microarray technology is one of the key developments in recent years that has propelled biological research into the post-genomic era. With the ability to assay thousands to millions of features at the same time, microarray technology has fundamentally changed how biological questions are addressed, from examining one or a few genes to a collection of genes or the whole genome. This technology has much to offer in the study of genome evolution. After a brief introduction on the technology itself, we then focus on the use of microarrays to examine genome dynamics, to uncover novel functional elements in genomes, to unravel the evolution of regulatory networks, to identify genes important for behavioral and phenotypic plasticity, and to determine microbial community diversity in environmental samples. Although there are still practical issues in using microarrays, they will be alleviated by rapid advances in array technology and analysis methods, the availability of many genome sequences of closely related species and flexibility in array design. It is anticipated that the application of microarray technology will continue to better our understanding of evolution and ecology through the examination of individuals, populations, closely related species or whole microbial communities.     

Antibody microarrays: current status and key technological advances

Antibody-based microarrays are among the novel classes of rapidly evolving proteomic technologies that holds great promise in biomedicine. Miniaturized microarrays (< 1 cm2) can be printed with thousands of individual antibodies carrying the desired specificities, and with biological sample (e.g., an entire proteome) added, virtually any specifically bound analytes can be detected. While consuming only minute amounts (< microL scale) of reagents, ultra- sensitive assays (zeptomol range) can readily be performed in a highly multiplexed manner. The microarray patterns generated can then be transformed into proteomic maps, or detailed molecular fingerprints, revealing the composition of the proteome. Thus, protein expression profiling and global proteome analysis using this tool will offer new opportunities for drug target and biomarker discovery, disease diagnostics, and insights into disease biology. Adopting the antibody microarray technology platform, several biomedical applications, ranging from focused assays to proteome-scale analysis will be rapidly emerging in the coming years. This review will discuss the current status of the antibody microarray technology focusing on recent technological advances and key issues in the process of evolving the methodology into a high-performing proteomic research tool.     

An introduction to DNA chips: principles, technology, applications and analysis

This review describes the recently developed GeneChip technology that provides efficient access to genetic information using miniaturised, high-density arrays of DNA or oligonucleotide probes. Such microarrays are powerful tools to study the molecular basis of interactions on a scale that would be impossible using conventional analysis. The recent development of the microarray technology has greatly accelerated the investigation of gene regulation. Arrays are mostly used to identify which genes are turned on or off in a cell or tissue, and also to evaluate the extent of a gene's expression under various conditions. Indeed, this technology has been successfully applied to investigate simultaneous expression of many thousands of genes and to the detection of mutations or polymorphisms, as well as for their mapping and sequencing.     

Application of DNA microarray technology for detection, identification, and characterization of food-borne pathogens

DNA microarrays represent the latest advance in molecular technology. In combination with bioinformatics, they provide unparalleled opportunities for simultaneous detection of thousands of genes or target DNA sequences and offer tremendous potential for studying food-borne microorganisms. This review provides an up-to-date look at the application of DNA microarray technology to detect food-borne pathogenic bacteria, viruses, and parasites. In addition, it covers the advantages of using microarray technology to further characterize microorganisms by providing information for specific identification of isolates, to understand the pathogenesis based on the presence of virulence genes, and to indicate how new pathogenic strains evolved epidemiologically and phylogenetically.     

Plant–Pathogen Interactions: What Microarray Tells About It?

Plant defense responses are mediated by elementary regulatory proteins that affect expression of thousands of genes. Over the last decade, microarray technology has played a key role in deciphering the underlying networks of gene regulation in plants that lead to a wide variety of defence responses. Microarray is an important tool to quantify and profile the expression of thousands of genes simultaneously, with two main aims: (1) gene discovery and (2) global expression profiling. Several microarray technologies are currently in use; most include a glass slide platform with spotted cDNA or oligonucleotides. Till date, microarray technology has been used in the identification of regulatory genes, end-point defence genes, to understand the signal transduction processes underlying disease resistance and its intimate links to other physiological pathways. Microarray technology can be used for in-depth, simultaneous profiling of host/pathogen genes as the disease progresses from infection to resistance/susceptibility at different developmental stages of the host, which can be done in different environments, for clearer understanding of the processes involved. A thorough knowledge of plant disease resistance using successful combination of microarray and other high throughput techniques, as well as biochemical, genetic, and cell biological experiments is needed for practical application to secure and stabilize yield of many crop plants. This review starts with a brief introduction to microarray technology, followed by the basics of plant–pathogen interaction, the use of DNA microarrays over the last decade to unravel the mysteries of plant–pathogen interaction, and ends with the future prospects of this technology.     

The implications of microarray technology for animal use in scientific research

Microarray technology has the potential to affect the number of laboratory animals used, the severity of animal experiments, and the development of non-animal alternatives in several areas scientific research. Microarrays can contain hundreds or thousands of microscopic spots of DNA, immobilised on a solid support, and their use enables global patterns of gene expression to be determined in a single experiment. This technology is being used to improve our understanding of the operation of biological systems during health and disease, and their responses to chemical insults. Although it is impossible to predict with certainty any future trends regarding animal use, microarray technology might not initially reduce animal use, as is often claimed to be the case. The accelerated pace of research as a result of the use of microarrays could increase overall animal use in basic and applied biological research, by increasing the numbers of interesting genes identified for further analysis, and the number of potential targets for drug development. Each new lead will require further evaluation i n studies that could involve animals. In toxicity testing, microarray studies could lead to increases in animal studies, if further confirmatory and other studies are performed. However, before such technology can be used more extensively, several technical problems need to be overcome, and the relevance of the data to biological processes needs to be assessed. Were microarray technology to be used in the manner envisaged by its protagonists, there need to be efforts to increase the likelihood that its application will create new opportunities for reducing, refining and replacing animal use. This comment is a critical assessment of the possible implications of the application of microarray technology on animal experimentation in various research areas, and makes some recommendations for maximising the application of the Three Rs.     

Genomics and microarray for detection and diagnostics

Genomics provided biomedical scientists an inventory of all genes and sequences present in a living being. This provides an unique opportunity to the scientists to predict and study biological functions of these genes. The changes in the gene expression regulated by genomic sequences therefore reflect changes in the molecular processes working in a cell or tissue in response to external factors including exposure to toxic compounds and pathogens. Microarray offers a biotechnological revolution with the help of DNA chemistry, silicon chip technology and optics to be used to monitor gene expression for thousands of genes in one single experiment. Briefly, 20,000 to 100,000 unique DNA molecules get applied by a robot to the surface of silicon wafers (approximately the size of a microscope slide). Using a single microarray experiment, the expression level of 20,000 to 100,000 genes will be examined in one single experiment. Genomics and microarray have a significant role and impact on the design and development of modern detection and diagnostic tools in several different ways. Microarray tools are now used on regular basis for monitoring gene expression of large number of genes and also frequently applied to DNA sequence analysis, immunology, genotyping, and molecular diagnosing. For diagnostics, these tools can be used to distinguish and differentiate between different DNA fragments that differ by as little as a single nucleotide polymorphism (SNP). These microarrays can be divided based on the gene density spots that will be high density (>10,000 spots) per slide, medium (< 1000 > 100) and low density (< 100). High-density arrays have proven to be very useful in disease diagnosis especially in diagnosis and classification of different types of cancers. These microarray tools hold tremendous potential for pathogen detection, which will be comprised, of unique sets of genes (also referred to as "signatures") able to unambiguously identify the species and strain of pathogens of interest.     

Robotic spotting of cDNA and oligonucleotide microarrays

DNA microarrays are a uniquely efficient method for simultaneously assessing the expression levels of thousands of genes. Owing to their flexibility and value, mechanically spotted microarrays remain the most popular platform. Here, we review recent technological advances with a focus on spotted arrays. Robotic spotting still poses numerous technical challenges. To reduce artefacts, many laboratories have recently investigated ways of improving the spotting process. We compare alternative options and discuss implications for next-generation systems. Together with modern approaches to data analysis, such developments bring greatly improved reliability to individual microarray experiments. Advancing towards the ultimate goal of delivering calibrated, truly quantitative gene-expression measurements on a genomic scale, microarray technology remains at the forefront of post-genomic systems biology.     

A Robust Statistical Method for Detecting Differentially Expressed Genes

DNA microarray technology allows researchers to monitor the expressions of thousands of genes under different conditions, and to measure the levels of thousands of different DNA molecules at a given point in the life of an organism, tissue or cell. A wide variety of different diseases that are characterised by unregulated gene expression, DNA replication, cell division and cell death, can be detected early using microarrays. One of the major objectives of microarray experiments is to identify differentially expressed genes under various conditions. The detection of differential gene expression under two different conditions is very important in biological studies, and allows us to identify experimental variables that affect different biological processes. Most of the tests available in the literature are based on the assumption of normal distribution. However, the assumption of normality may not be true in real-life data, particularly with respect to microarray data.A test is proposed for the identification of differentially expressed genes in replicated microarray experiments conducted under two different conditions. The proposed test does not assume the distribution of the parent population; thus, the proposed test is strictly nonparametric in nature. We calculate the p-value and the asymptotic power function of the proposed test statistic. The proposed test statistic is compared with some of its competitors under normal, gamma and exponential population setup using the Monte Carlo simulation technique. The application of the proposed test statistic is presented using microarray data. The proposed test is robust and highly efficient when populations are non-normal.     

Clinical and functional target validation using tissue and cell microarrays

Expression levels of thousands of genes or proteins can be readily determined using microarray techniques. However, this represents only the first step in understanding the biological and medical significance of these molecules. New high-throughput techniques, such as tissue and cell microarrays, will facilitate clinical and functional analysis of molecular targets.     

Recent developments in DNA microarrays

DNA microarrays are used to quantify tens of thousands of DNA or RNA sequences in a single assay. Upon their introduction approximately six years ago, DNA microarrays were viewed as a disruptive technology that would fundamentally alter the scientific landscape. Supporting this view, the number of applications of DNA microarray technology has since expanded exponentially. Here, we review recent advances in microarray technology and selected new applications of the technology.     

Methods for assessing reproducibility of clustering patterns observed in analyses of microarray data

MOTIVATION: Recent technological advances such as cDNA microarray technology have made it possible to simultaneously interrogate thousands of genes in a biological specimen. A cDNA microarray experiment produces a gene expression 'profile'. Often interest lies in discovering novel subgroupings, or 'clusters', of specimens based on their profiles, for example identification of new tumor taxonomies. Cluster analysis techniques such as hierarchical clustering and self-organizing maps have frequently been used for investigating structure in microarray data. However, clustering algorithms always detect clusters, even on random data, and it is easy to misinterpret the results without some objective measure of the reproducibility of the clusters. RESULTS: We present statistical methods for testing for overall clustering of gene expression profiles, and we define easily interpretable measures of cluster-specific reproducibility that facilitate understanding of the clustering structure. We apply these methods to elucidate structure in cDNA microarray gene expression profiles obtained on melanoma tumors and on prostate specimens.     

Combining multiple microarrays in the presence of controlling variables

MOTIVATION: Microarray technology enables the monitoring of expression levels for thousands of genes simultaneously. When the magnitude of the experiment increases, it becomes common to use the same type of microarrays from different laboratories or hospitals. Thus, it is important to analyze microarray data together to derive a combined conclusion after accounting for the differences. One of the main objectives of the microarray experiment is to identify differentially expressed genes among the different experimental groups. The analysis of variance (ANOVA) model has been commonly used to detect differentially expressed genes after accounting for the sources of variation commonly observed in the microarray experiment. RESULTS: We extended the usual ANOVA model to account for an additional variability resulting from many confounding variables such as the effect of different hospitals. The proposed model is a two-stage ANOVA model. The first stage is the adjustment for the effects of no interests. The second stage is the detection of differentially expressed genes among the experimental groups using the residuals obtained from the first stage. Based on these residuals, we propose a permutation test to detect the differentially expressed genes. The proposed model is illustrated using the data from 133 microarrays collected at three different hospitals. The proposed approach is more flexible to use, and it is easier to accommodate the individual covariates in this model than using the meta-analysis approach. AVAILABILITY: A set of programs written in R will be electronically sent upon request.     

Multipathogen oligonucleotide microarray for environmental and biodefense applications

Food-borne pathogens are a major health problem. The large and diverse number of microbial pathogens and their virulence factors has fueled interest in technologies capable of detecting multiple pathogens and multiple virulence factors simultaneously. Some of these pathogens and their toxins have potential use as bioweapons. DNA microarray technology allows the simultaneous analysis of thousands of sequences of DNA in a relatively short time, making it appropriate for biodefense and for public health uses. This paper describes methods for using DNA microarrays to detect and analyze microbial pathogens. The FDA-1 microarray was developed for the simultaneous detection of several food-borne pathogens and their virulence factors including Listeria spp., Campylobacter spp., Staphylococcus aureus enterotoxin genes and Clostridium perfringens toxin genes. Three elements were incorporated to increase confidence in the microarray detection system: redundancy of genes, redundancy of oligonucleotide probes (oligoprobes) for a specific gene, and quality control oligoprobes to monitor array spotting and target DNA hybridization. These elements enhance the reliability of detection and reduce the chance of erroneous results due to the genetic variability of microbes or technical problems with the microarray. The results presented demonstrate the potential of oligonucleotide microarrays for detection of environmental and biodefense relevant microbial pathogens.     

蛋白质微技术及其在医学领域中的应用

蛋白质微阵列是生物芯片的一种,其主要优势在于应用平面上的有序排列的许多管、腔（孔）或各自独立的点来进行样本检测,使大量样本的平行分析成为可能。应用此技术可同时分析诸多蛋白质的生物化学活性、蛋白质与蛋白质间、蛋白质与DNA间、蛋白质与RNA间,以及蛋白质与配体间的相互作用,从而在临床诊断、药物研究、环境监测、食品卫生等方面显示出其广阔的应用前景。     

DNA microarrays--perspective of application for drug effectivity and safety evaluation

Microarray technology provides a unique tool for the determination of gene expression at the level of messenger RNA (mRNA). Microarray has been successfully applied to the high throughput simultaneous expression of many thousands of genes in a single experiment. One important application of DNA microarray technology, within the context of drugs effectiveness and safety evaluation studies, is its use as a screening tool for the identification of biochemical pathways, potential targets for novel molecular therapeutics, for the identification of molecular mechanisms of toxicity and to understand and predict individual drug sensitivity and resistance. The purpose of this review is presentation of the utility of DNA microarray technology in all phases of the drug discovery process.     

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.