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.     

Production of custom microarrays for neuroscience research

Microarray chips produced by commercial vendors and academic laboratories are mostly generic in nature to facilitate wide applicability. With the sequencing of the human, mouse, and rat genomes, the thrust is to expand clone and oligonucleotide sets and increase the number of genes represented on a particular array. This is appropriate for discovery based investigations where microarray technology has been successfully utilized. However, array technology can also be employed to perform hypothesis based studies if optimized chips can be produced with relevant content. Existing array technology available at core facilities can be effectively utilized to produce a custom microarrays with genes that are most relevant to the research interests of individual investigators or research groups for use as a standard molecular tool. The power of this technology can be harnessed to further our understanding of specific biological problems without involvement in extensive data mining and analysis. The custom microarray approach is presented with procedural details for design and production in the context of neurobiological investigations.     

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.     

A statistical framework for the design of microarray experiments and effective detection of differential gene expression

MOTIVATION: Microarray experiments generate a high data volume. However, often due to financial or experimental considerations, e.g. lack of sample, there is little or no replication of the experiments or hybridizations. These factors combined with the intrinsic variability associated with the measurement of gene expression can result in an unsatisfactory detection rate of differential gene expression (DGE). Our motivation was to provide an easy to use measure of the success rate of DGE detection that could find routine use in the design of microarray experiments or in post-experiment assessment. RESULTS: In this study, we address the problem of both random errors and systematic biases in microarray experimentation. We propose a mathematical model for the measured data in microarray experiments and on the basis of this model present a t-based statistical procedure to determine DGE. We have derived a formula to determine the success rate of DGE detection that takes into account the number of microarrays, the number of genes, the magnitude of DGE, and the variance from biological and technical sources. The formula and look-up tables based on the formula, can be used to assist in the design of microarray experiments. We also propose an ad hoc method for estimating the fraction of non-differentially expressed genes within a set of genes being tested. This will help to increase the power of DGE detection. AVAILABILITY: The functions to calculate the success rate of DGE detection have been implemented as a Java application, which is accessible at http://www.le.ac.uk/mrctox/microarray_lab/Microarray_Softwares/Microarray_Softwares.htm     

Functional genomics and cell wall biosynthesis in loblolly pine

Loblolly pine (Pinus taeda L.) is the most widely planted tree species in the USA and an important tree in commercial forestry world-wide. The large genome size and long generation time of this species present obstacles to both breeding and molecular genetic analysis. Gene discovery by partial DNA sequence determination of cDNA clones is an effective means of building a knowledge base for molecular investigations of mechanisms governing aspects of pine growth and development, including the commercially relevant properties of secondary cell walls in wood. Microarray experiments utilizing pine cDNA clones can be used to gain additional information about the potential roles of expressed genes in wood formation. Different methods have been used to analyze data from first-generation pine microarrays, with differing degrees of success. Disparities in predictions of differential gene expression between cDNA sequencing experiments and microarray experiments arise from differences in the nature of the respective analyses, but both approaches provide lists of candidate genes which should be further investigated for potential roles in cell wall formation in differentiating pine secondary xylem. Some of these genes seem to be specific to pine, while others also occur in model plants such as Arabidopsis, where they could be more efficiently investigated.     

Stripping custom microRNA microarrays and the lessons learned about probe-slide interactions

Microarrays have been used extensively in gene expression profiling and genotyping studies. To reduce the high cost and enhance the consistency of microarray experiments, it is often desirable to strip and reuse microarray slides. Our genome-wide analysis of microRNA expression involves the hybridization of fluorescently labeled nucleic acids to custom-made, spotted DNA microarrays based on GAPSII-coated slides. We describe here a simple and effective method to regenerate such custom microarrays that uses a very low-salt buffer to remove labeled nucleic acids from microarrays. Slides can be stripped and reused multiple times without significantly compromising data quality. Moreover, our analyses of the performance of regenerated slides identifies parameters that influence the attachment of oligonucleotide probes to GAPSII slides, shedding light on the interactions between DNA and the microarray surface and suggesting ways in which to improve the design of oligonucleotide probes.     

Experimental design for gene expression microarrays

We examine experimental design issues arising with gene expression microarray technology. Microarray experiments have multiple sources of variation, and experimental plans should ensure that effects of interest are not confounded with ancillary effects. A commonly used design is shown to violate this principle and to be generally inefficient. We explore the connection between microarray designs and classical block design and use a family of ANOVA models as a guide to choosing a design. We combine principles of good design and A-optimality to give a general set of recommendations for design with microarrays. These recommendations are illustrated in detail for one kind of experimental objective, where we also give the results of a computer search for good designs.     

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.     

An antibody-based microarray assay for the simultaneous detection of aflatoxin B<Subscript>1</Subscript> and fumonisin B<Subscript>1</Subscript>

Advances in microsystem technology have enabled protein and nucleic acid-based microarrays to be used in various applications, including the study of diseases, drug discovery, genetic screening, and clinical and food diagnostics. Analytical methods for the detection of mycotoxins, however, remain largely based on thin layer chromatography (TLC), high pressure liquid chromatography (HPLC), or enzyme-linked Immunosorbent assay (ELISA) . The aim of our work, therefore, was to transfer an immunological assay from microtitrr plates into microarray format, in order to develop a multiparametric, rapid, sensitive and inexpensive method for the detection of mycotoxins for use in food safety applications. Microarray technology enables the fast and parallel analysis of a multitude of biologically relevant parameters. Not only nucleic acid-based tests but also peptide, antigen, and antibody assays, using different formats of microarrays, have evolved within the last decade. Antibody-based microarrays provide a powerful tool that can be used to generate rapid and detailed expression profiles of a defined set of analytes in complex samples and are potentially useful for generating rapid immunological assays of food contaminants. In this paper, we report a feasibility study of the application of antibody microarrays for the simultaneous (or independent) detection of two common mycotoxins, Aflatoxin B₁ and Fumonisin B₁. We present the development of microarray detection of aflatoxin B1 and fumonisin B1 in standard solutions with detection limits of 3 ng/ml of AFB1 and 43 ng/ml for FB1, and have developed a competitive immunoassay in microarray format for simultaneous analyses. The quality of the microarray data is comparable to data generated by microplate-based immunoassay (ELISA), but further investigations are needed in order to characterise our method more fully. We hope that these preliminary results might suggest that further research is warranted in order to develop hapten microarrays for the immunochemical simultaneous analysis of mycotoxins, as well as for other small molecules (e.g. bacterial toxins or biological warfare agents).     

Storage and retrieval of microarray data and open source microarray database software

Microarray technology has been widely adopted by researchers who use both home-made microarrays and microarrays purchased from commercial vendors. Associated with the adoption of this technology has been a deluge of complex data, both from the microarrays themselves, and also in the form of associated meta data, such as gene annotation information, the properties and treatment of biological samples, and the data transformation and analysis steps taken downstream. In addition, standards for annotation and data exchange have been proposed, and are now being adopted by journals and funding agencies alike. The coupling of large quantities of complex data with extensive and complex standards require all but the most small-scale of microarray users to have access to a robust and scaleable database with various tools. In this review, we discuss some of the desirable properties of such a database, and look at the features of several freely available alternatives.     

Microarray data assembler

SUMMARY: Large volumes of microarray data are generated and deposited in public databases. Most of this data is in the form of tab-delimited text files or Excel spreadsheets. Combining data from several of these files to reanalyze these data sets is time consuming. Microarray Data Assembler is specifically designed to simplify this task. The program can list files and data sources, convert selected text files into Excel files and assemble data across multiple Excel worksheets and workbooks. This program thus makes data assembling easy, saves time and helps avoid manual error. AVAILABILITY: The program is freely available for non-profit use, via email request from the author, after signing a Material Transfer Agreement with Johns Hopkins University.     

cDNA Labeling Strategies for Microarrays Using Fluorescent Dyes

Microarray analysis has become a key experimental tool in the study of genome‐wide patterns of gene expression. The labeling step of target molecules such as cDNA or cRNA plays a key role in a microarray experiment because the amount of mRNA is measured indirectly by the labeled molecules. In this paper, the most widely used cDNA labeling strategies in microarray experiments are reviewed in detail, including direct labeling and indirect labeling methods along with a discussion of the merits and disadvantages of these methods. Furthermore, various RNA amplification approaches were surveyed to obtain a target nucleic acid sufficient for microarray experiments from minute amounts of mRNA. Finally, the labeling strategies of commonly used microarray platforms (e.g., Affymetrix GeneChip®, CodeLink? Bioarray, Agilent and spotted microarrays) were compared.     

The effects of mismatches on hybridization in DNA microarrays: determination of nearest neighbor parameters

Quantifying interactions in DNA microarrays is of central importance for a better understanding of their functioning. Hybridization thermodynamics for nucleic acid strands in aqueous solution can be described by the so-called nearest neighbor model, which estimates the hybridization free energy of a given sequence as a sum of dinucleotide terms. Compared with its solution counterparts, hybridization in DNA microarrays may be hindered due to the presence of a solid surface and of a high density of DNA strands. We present here a study aimed at the determination of hybridization free energies in DNA microarrays. Experiments are performed on custom Agilent slides. The solution contains a single oligonucleotide. The microarray contains spots with a perfect matching (PM) complementary sequence and other spots with one or two mismatches (MM) : in total 1006 different probe spots, each replicated 15 times per microarray. The free energy parameters are directly fitted from microarray data. The experiments demonstrate a clear correlation between hybridization free energies in the microarray and in solution. The experiments are fully consistent with the Langmuir model at low intensities, but show a clear deviation at intermediate (non-saturating) intensities. These results provide new interesting insights for the quantification of molecular interactions in DNA microarrays.     

Blood meal induces global changes in midgut gene expression in the disease vector, Aedes aegypti

Blood feeding is an essential developmental process for many arthropods and plays a significant role in disease transmission. Understanding physiological responses in the midgut is important because it is the primary site of blood meal digestion and pathogenic infection. Processes that occur in the midgut in response to a blood meal have been studied but are poorly understood. Here, we use cDNA microarrays to examine midgut gene expression on a global level in response to blood feeding to assist in unraveling these processes. We have developed Aedes aegypti microarrays consisting of clones obtained from an expressed sequence tag project. Individual clones were amplified by polymerase chain reaction and printed onto glass slides. These microarrays were used to study the effects of a blood meal on midgut gene expression over a 72-h time course. As a result, a number of genes involved in processes such as nutrient uptake and metabolism, cellular stress responses, ion balance, and PM formation, as well as a number of unknown genes were induced or repressed in response to a blood meal based on this microarray data.