Assessment of clone identity and sequence fidelity for 1189 IMAGE cDNA clones

An Esterase with Increased Acetone Tolerance from Bacillus subtilis E9 over Expressed in E. coli BL21 Using pTac Bs-est Vector

Bacillus subtilis E9 was identified as a potential strain producing esterase. The gene coding esterase from B. subtilis E9 was amplified using esterase-specific primers and the sequence was translated in silico. The presence of conserved catalytic triad amino acid residues (His-Ser-Asp/Glu) confirmed the functional nature of the esterase enzyme. Docking studies conducted with modeled protein and the ligand p-nitrophenyl acetate showed that the amino acid residues interacting with the ligand were Ser77, His76, and Gly103. The gene coding for esterase from B. subtilis E9 was cloned into an assembled vector having Tac promoter (pTac), pUC origin of replication, Ni-Histidine residues, ampicillin cassette, and T7 terminator using Golden gate DNA assembly method. The generated pTac Bs-est (4598 bp) recombinant plasmid was transformed and heterologously expressed in Escherichia coli BL21 (DE3) strain. The tagged recombinant protein was purified to yield 43.4% pure protein with specific activity of 772 U/mg. The purified recombinant protein was subjected to peptide sequencing and the identity was confirmed as esterase by peptide tandem mass fragmentation method using the LC-MS/MS analysis. The purified recombinant esterase was found to be organic solvent stable and tolerant up to 5 days retaining around 95% residual activity in 30-90% v/v Acetone. The recombinant esterase expressed in our study was found to exhibit better organic solvent stability and tolerance than compared to the original bacterial esterase from B. subtilis E9, a property which could be explored in the biocatalytic and synthetic transformation reactions for industrial applications.

Identification of a Herbal Powder by Deoxyribonucleic Acid Barcoding and Structural Analyses

BACKGROUND

Authentic identification of plants is essential for exploiting their medicinal properties as well as to stop the adulteration and malpractices with the trade of the same.

OBJECTIVE

To identify a herbal powder obtained from a herbalist in the local vicinity of Rajkot, Gujarat, using deoxyribonucleic acid (DNA) barcoding and molecular tools.

MATERIALS AND METHODS

The DNA was extracted from a herbal powder and selected Cassia species, followed by the polymerase chain reaction (PCR) and sequencing of the rbcL barcode locus. Thereafter the sequences were subjected to National Center for Biotechnology Information (NCBI) basic local alignment search tool (BLAST) analysis, followed by the protein three-dimension structure determination of the rbcL protein from the herbal powder and Cassia species namely Cassia fistula, Cassia tora and Cassia javanica (sequences obtained in the present study), Cassia Roxburghii, and Cassia abbreviata (sequences retrieved from Genbank). Further, the multiple and pairwise structural alignment were carried out in order to identify the herbal powder.

RESULTS

The nucleotide sequences obtained from the selected species of Cassia were submitted to Genbank (Accession No. JX141397, JX141405, JX141420). The NCBI BLAST analysis of the rbcL protein from the herbal powder showed an equal sequence similarity (with reference to different parameters like E value, maximum identity, total score, query coverage) to C. javanica and C. roxburghii. In order to solve the ambiguities of the BLAST result, a protein structural approach was implemented. The protein homology models obtained in the present study were submitted to the protein model database (PM0079748-PM0079753). The pairwise structural alignment of the herbal powder (as template) and C. javanica and C. roxburghii (as targets individually) revealed a close similarity of the herbal powder with C. javanica.

CONCLUSION

A strategy as used here, incorporating the integrated use of DNA barcoding and protein structural analyses could be adopted, as a novel rapid and economic procedure, especially in cases when protein coding loci are considered.

SUMMARY

Authentic identification of plants is essential for exploiting their medicinal properties as well as to stop the adulteration and malpractices with the trade of the same. A herbal powder was obtained from a herbalist in the local vicinity of Rajkot, Gujarat. An integrated approach using DNA barcoding and structural analyses was carried out to identify the herbal powder. The herbal powder was identified as Cassia javanica L.

Impact of experimental noise and annotation imprecision on data quality in microarray experiments

Data quality is intrinsically influenced by design, technical, and analytical parameters. Quality parameters have not yet been well defined for gene expression analysis by microarrays, though ad interim, following recommended good experimental practice guidelines should ensure generation of reliable and reproducible data. Here we summarize essential practical recommendations for experimental design, technical considerations, feature annotation issues, and standardization efforts.

Deciphering c-MYC-regulated genes in two distinct tissues

Background

The transcription factor MYC is a critical regulator of diverse cellular processes, including both replication and apoptosis. Differences in MYC-regulated gene expression responsible for such opposing outcomes in vivo remain obscure. To address this we have examined time-dependent changes in global gene expression in two transgenic mouse models in which MYC activation, in either skin suprabasal keratinocytes or pancreatic islet β-cells, promotes tissue expansion or involution, respectively.

Results

Consistent with observed phenotypes, expression of cell cycle genes is increased in both models (albeit enriched in β-cells), as are those involved in cell growth and metabolism, while expression of genes involved in cell differentiation is down-regulated. However, in β-cells, which unlike suprabasal keratinocytes undergo prominent apoptosis from 24 hours, there is up-regulation of genes associated with DNA-damage response and intrinsic apoptotic pathways, including Atr, Arf, Bax and Cycs. In striking contrast, this is not the case for suprabasal keratinocytes, where pro-apoptotic genes such as Noxa are down-regulated and key anti-apoptotic pathways (such as Igf1-Akt) and those promoting angiogenesis are up-regulated. Moreover, dramatic up-regulation of steroid hormone-regulated Kallikrein serine protease family members in suprabasal keratinocytes alone could further enhance local Igf1 actions, such as through proteolysis of Igf1 binding proteins.

Conclusions

Activation of MYC causes cell growth, loss of differentiation and cell cycle entry in both β-cells and suprabasal keratinocytes in vivo. Apoptosis, which is confined to β-cells, may involve a combination of a DNA-damage response and downstream activation of pro-apoptotic signalling pathways, including Cdc2a and p19^Arf/p53, and downstream targets. Conversely, avoidance of apoptosis in suprabasal keratinocytes may result primarily from the activation of key anti-apoptotic signalling pathways, particularly Igf1-Akt, and induction of an angiogenic response, though intrinsic resistance to induction of p19^Arf by MYC in suprabasal keratinocytes may contribute.

Development and validation of a Xanthomonas axonopodis pv. citri DNA microarray platform (XACarray) generated from the shotgun libraries previously used in the sequencing of this bacterial genome

BACKGROUND

From shotgun libraries used for the genomic sequencing of the phytopathogenic bacterium Xanthomonas axonopodis pv. citri (XAC), clones that were representative of the largest possible number of coding sequences (CDSs) were selected to create a DNA microarray platform on glass slides (XACarray). The creation of the XACarray allowed for the establishment of a tool that is capable of providing data for the analysis of global genome expression in this organism.

FINDINGS

The inserts from the selected clones were amplified by PCR with the universal oligonucleotide primers M13R and M13F. The obtained products were purified and fixed in duplicate on glass slides specific for use in DNA microarrays. The number of spots on the microarray totaled 6,144 and included 768 positive controls and 624 negative controls per slide. Validation of the platform was performed through hybridization of total DNA probes from XAC labeled with different fluorophores, Cy3 and Cy5. In this validation assay, 86% of all PCR products fixed on the glass slides were confirmed to present a hybridization signal greater than twice the standard deviation of the deviation of the global median signal-to-noise ration.

CONCLUSIONS

Our validation of the XACArray platform using DNA-DNA hybridization revealed that it can be used to evaluate the expression of 2,365 individual CDSs from all major functional categories, which corresponds to 52.7% of the annotated CDSs of the XAC genome. As a proof of concept, we used this platform in a previously work to verify the absence of genomic regions that could not be detected by sequencing in related strains of Xanthomonas.

Microarray probes and probe sets

DNA microarrays have gained wide use in biomedical research by simultaneously monitoring the expression levels of a large number of genes. The successful implementation of DNA microarray technologies requires the development of methods and techniques for the fabrication of microarrays, the selection of probes to represent genes, the quantification of hybridization, and data analysis. In this paper, we concentrate on probes that are either spotted or synthesized on the glass slides through several aspects: sources of probes, the criteria for selecting probes, tools available for probe selections, and probes used in commercial microarray chips. We then provide a detailed review of one type of DNA microarray: Affymetrix GeneChips, discuss the need to re-annotate probes, review different methods for regrouping probes into probe sets, and compare various redefinitions through public available datasets.

FragIdent--automatic identification and characterisation of cDNA-fragments

BACKGROUND

Many genetic studies and functional assays are based on cDNA fragments. After the generation of cDNA fragments from an mRNA sample, their content is at first unknown and must be assigned by sequencing reactions or hybridisation experiments. Even in characterised libraries, a considerable number of clones are wrongly annotated. Furthermore, mix-ups can happen in the laboratory. It is therefore essential to the relevance of experimental results to confirm or determine the identity of the employed cDNA fragments. However, the manual approach for the characterisation of these fragments using BLAST web interfaces is not suited for larger number of sequences and so far, no user-friendly software is publicly available.

RESULTS

Here we present the development of FragIdent, an application for the automatic identification of open reading frames (ORFs) within cDNA-fragments. The software performs BLAST analyses to identify the genes represented by the sequences and suggests primers to complete the sequencing of the whole insert. Gene-specific information as well as the protein domains encoded by the cDNA fragment are retrieved from Internet-based databases and included in the output. The application features an intuitive graphical interface and is designed for researchers without any bioinformatics skills. It is suited for projects comprising up to several hundred different clones.

CONCLUSION

We used FragIdent to identify 84 cDNA clones from a yeast two-hybrid experiment. Furthermore, we identified 131 protein domains within our analysed clones. The source code is freely available from our homepage at http://compbio.charite.de/genetik/FragIdent/.

A multiway analysis for identifying high integrity bovine BACs

BACKGROUND

In large genomics projects involving many different types of analyses of bacterial artificial chromosomes (BACs), such as fingerprinting, end sequencing (BES) and full BAC sequencing there are many opportunities for the identities of BACs to become confused. However, by comparing the results from the different analyses, inconsistencies can be identified and a set of high integrity BACs preferred for future research can be defined.

RESULTS

The location of each bovine BAC in the BAC fingerprint-based genome map and in the genome assembly were compared based on the reported BESs, and for a smaller number of BACs the full sequence. BACs with consistent positions in all three datasets, or if the full sequence was not available, for both the fingerprint map and BES-based alignments, were deemed to be correctly positioned. BACs with consistent BES-based and fingerprint-based locations, but with conflicting locations based on the fully sequenced BAC, appeared to have been misidentified during sequencing, and included a number of apparently swapped BACs. Inconsistencies between BES-based and fingerprint map positions identified thirty one plates from the CHORI-240 library that appear to have suffered substantial systematic problems during the end-sequencing of the BACs. No systematic problems were identified in the fingerprinting of the BACs. Analysis of BACs overlapping in the assembly identified a small overrepresentation of clones with substantial overlap in the library and a substantial enrichment of highly overlapping BACs on the same plate in the CHORI-240 library. More than half of these BACs appear to have been present as duplicates on the original BAC-library plates and thus should be avoided in subsequent projects.

CONCLUSION

Our analysis shows that approximately 95% of the bovine CHORI-240 library clones with both a BAC fingerprint and two BESs mapping to the genome in the expected orientations (approximately 27% of all BACs) have consistent locations in the BAC fingerprint map and the genome assembly. We have developed a broadly applicable methodology for checking the integrity of BAC-based datasets even where only incomplete and partially assembled genomic sequence is available.

Development of a human mitochondrial oligonucleotide microarray (h-MitoArray) and gene expression analysis of fibroblast cell lines from 13 patients with isolated F1Fo ATP synthase deficiency

Background

To strengthen research and differential diagnostics of mitochondrial disorders, we constructed and validated an oligonucleotide microarray (h-MitoArray) allowing expression analysis of 1632 human genes involved in mitochondrial biology, cell cycle regulation, signal transduction and apoptosis. Using h-MitoArray we analyzed gene expression profiles in 9 control and 13 fibroblast cell lines from patients with F₁F_o ATP synthase deficiency consisting of 2 patients with mt9205ΔTA microdeletion and a genetically heterogeneous group of 11 patients with not yet characterized nuclear defects. Analysing gene expression profiles, we attempted to classify patients into expected defect specific subgroups, and subsequently reveal group specific compensatory changes, identify potential phenotype causing pathways and define candidate disease causing genes.

Results

Molecular studies, in combination with unsupervised clustering methods, defined three subgroups of patient cell lines – M group with mtDNA mutation and N1 and N2 groups with nuclear defect. Comparison of expression profiles and functional annotation, gene enrichment and pathway analyses of differentially expressed genes revealed in the M group a transcription profile suggestive of synchronized suppression of mitochondrial biogenesis and G1/S arrest. The N1 group showed elevated expression of complex I and reduced expression of complexes III, V, and V-type ATP synthase subunit genes, reduced expression of genes involved in phosphorylation dependent signaling along MAPK, Jak-STAT, JNK, and p38 MAP kinase pathways, signs of activated apoptosis and oxidative stress resembling phenotype of premature senescent fibroblasts. No specific functionally meaningful changes, except of signs of activated apoptosis, were detected in the N2 group. Evaluation of individual gene expression profiles confirmed already known ATP6/ATP8 defect in patients from the M group and indicated several candidate disease causing genes for nuclear defects.

Conclusion

Our analysis showed that deficiency in the ATP synthase protein complex amount is generally accompanied by only minor changes in expression of ATP synthase related genes. It also suggested that the site (mtDNA vs nuclear DNA) and the severity (ATP synthase content) of the underlying defect have diverse effects on cellular gene expression phenotypes, which warrants further investigation of cell cycle regulatory and signal transduction pathways in other OXPHOS disorders and related pharmacological models.

Optimization of cDNA microarrays procedures using criteria that do not rely on external standards

Background

The measurement of gene expression using microarray technology is a complicated process in which a large number of factors can be varied. Due to the lack of standard calibration samples such as are used in traditional chemical analysis it may be a problem to evaluate whether changes done to the microarray procedure actually improve the identification of truly differentially expressed genes. The purpose of the present work is to report the optimization of several steps in the microarray process both in laboratory practices and in data processing using criteria that do not rely on external standards.

Results

We performed a cDNA microarry experiment including RNA from samples with high expected differential gene expression termed "high contrasts" (rat cell lines AR42J and NRK52E) compared to self-self hybridization, and optimized a pipeline to maximize the number of genes found to be differentially expressed in the "high contrasts" RNA samples by estimating the false discovery rate (FDR) using a null distribution obtained from the self-self experiment. The proposed high-contrast versus self-self method (HCSSM) requires only four microarrays per evaluation. The effects of blocking reagent dose, filtering, and background corrections methodologies were investigated. In our experiments a dose of 250 ng LNA (locked nucleic acid) dT blocker, no background correction and weight based filtering gave the largest number of differentially expressed genes. The choice of background correction method had a stronger impact on the estimated number of differentially expressed genes than the choice of filtering method. Cross platform microarray (Illumina) analysis was used to validate that the increase in the number of differentially expressed genes found by HCSSM was real.

Conclusion

The results show that HCSSM can be a useful and simple approach to optimize microarray procedures without including external standards. Our optimizing method is highly applicable to both long oligo-probe microarrays which have become commonly used for well characterized organisms such as man, mouse and rat, as well as to cDNA microarrays which are still of importance for organisms with incomplete genome sequence information such as many bacteria, plants and fish.

Detection of early signals of hepatotoxicity by gene expression profiling studies with cultures of metabolically competent human hepatocytes

Xenobiotic induced liver injury is a leading cause for drug withdrawal and toxicogenomics may help to identify molecular causes. Here we report studies with cultures of human hepatocytes to detect early responses of liver toxicity upon treatment with the hepatotoxin Aroclor 1254. We studied transcript abundance of 302 genes with biological functions in detoxification, cell proliferation, tumor development, stress response, signal transduction, apoptosis and cell cycle regulation. More than 40 genes were regulated by at least twofold change, the majority coding for xenobiotic defense. In the case of CYP monooxygenases induction of coded protein was confirmed by Western immunoblotting whereas catalytic activities were determined by assaying for testosterone hydroxylase activity. There was good agreement between gene and protein expression and enzyme activity of CYP monooxygenases. In conclusion, xenobiotic induced hepatotoxicity may arise via several mechanisms and gene expression profiling helps to pinpoint location and pathways perturbed by drugs and chemicals.

Gene expression profiling in sarcomas

Sarcomas are a heterogeneous group of malignant mesenchymal tumors of difficult classification. There is considerable variability in both histological appearance and responsiveness to therapy. Their overall poor clinical prognosis is reflected by the fact that >65% of patients suffering retroperitoneal soft tissue sarcoma die within 5 years [Heslin MJ, et al. Prognostic factors associated with long-term survival for retroperitoneal sarcoma: implications for management. J Clin Oncol 1997;15(8):2832-9]. A greater understanding of the biology of sarcomas is needed in order to increase the potential for identifying new therapeutic targets and strategies. Microarray analysis permits a global approach to gene expression analysis of thousands of genes at the same time and has proven to be useful for further molecular characterization of tumor tissue and cell lines. This article provides a comprehensive review of possible new biomarkers identified in gene expression studies of sarcomas. These markers give new insight into the pathogenesis of sarcomas, such as malignant fibrous histiocytoma [Lee YF, et al. Molecular classification of synovial sarcomas, leiomyosarcomas and malignant fibrous histiocytomas by gene expression profiling. Br J Cancer 2003;88(4):510-5], allow a further subclassifcation of tumors like calponin-positive and calponin-negative leiomyosarcoma, or may help to predict treatment responsiveness and prognosis in patients based on an individual gene expression pattern. In some studies candidate targets for possible new treatment strategies were identified. For instance newly identified markers such as ERBB2 [Allander SV, et al. Expression profiling of synovial sarcoma by cDNA microarrays: association of ERBB2, IGFBP2, and ELF3 with epithelial differentiation. Am J Pathol 2002;161(5):1587-95] and EGFR [Nielsen TO, et al. Molecular characterization of soft tissue tumours: a gene expression study. Lancet 2002;359(9314):1301-7] might lead to the possible therapeutic use of Trastuzumab, Gefitinib or Cetuximab in synovial sarcoma, comparable to the use of tyrosine kinase inhibitor STI (Gleevec) that is the standard treatment today of CD117-positive gastrointestinal stromal tumors.

Review of the literature examining the correlation among DNA microarray technologies

DNA microarray technologies are used in a variety of biological disciplines. The diversity of platforms and analytical methods employed has raised concerns over the reliability, reproducibility and correlation of data produced across the different approaches. Initial investigations (years 2000-2003) found discrepancies in the gene expression measures produced by different microarray technologies. Increasing knowledge and control of the factors that result in poor correlation among the technologies has led to much higher levels of correlation among more recent publications (years 2004 to present). Here, we review the studies examining the correlation among microarray technologies. We find that with improvements in the technology (optimization and standardization of methods, including data analysis) and annotation, analysis across platforms yields highly correlated and reproducible results. We suggest several key factors that should be controlled in comparing across technologies, and are good microarray practice in general.

Gene expression arrays as a tool to unravel mechanisms of normal tissue radiation injury and prediction of response

Over the past 5 years there has been a rapid increase in the use of microarray technology in the field of cancer research. The majority of studies use microarray analysis of tumor biopsies for profiling of molecular characteristics in an attempt to produce robust classifiers for prognosis. There are now several published gene sets that have been shown to predict for aggressive forms of breast cancer, where patients are most likely to benefit from adjuvant chemotherapy and tumors most likely to develop distant metastases, or be resistant to treatment. The number of publications relating to the use of microarrays for analysis of normal tissue damage, after cancer treatment or genotoxic exposure, is much more limited. A PubMed literature search was conducted using the following keywords and combination of terms: radiation, normal tissue, microarray, gene expression profiling, prediction. With respect to normal tissue radiation injury, microarrays have been used in three ways: (1) to generate gene signatures to identify sensitive and resistant populations (prognosis); (2) to identify sets of biomarker genes for estimating radiation exposure, either accidental or as a result of terrorist attack (diagnosis); (3) to identify genes and pathways involved in tissue response to injury (mechanistic). In this article we will review all (relevant) papers that covered our literature search criteria on microarray technology as it has been applied to normal tissue radiation biology and discuss how successful this has been in defining predisposition markers for radiation sensitivity or how it has helped us to unravel molecular mechanisms leading to acute and late tissue toxicity. We also discuss some of the problems and limitations in application and interpretation of such data.

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.

Cross-species microarray hybridizations: a developing tool for studying species diversity

The use of cross-species hybridization (CSH) to DNA microarrays, in which the target RNA and microarray probe are from different species, has increased in the past few years. CSH is used in comparative, evolutionary and ecological studies of closely related species, and for gene-expression profiling of many species that lack a representative microarray platform. However, unlike species-specific hybridization, CSH is still considered a non-standard use of microarrays. Here, we present the recent developments in the field of CSH for cDNA and oligomer microarray platforms. We discuss issues that influence the quality of CSH results, including platform choice, experiment design and data analysis, and suggest strategies that can lead to improvement of CSH studies to investigate species diversity.

Analysis of microarray experiments of gene expression profiling

The study of gene expression profiling of cells and tissue has become a major tool for discovery in medicine. Microarray experiments allow description of genome-wide expression changes in health and disease. The results of such experiments are expected to change the methods employed in the diagnosis and prognosis of disease in obstetrics and gynecology. Moreover, an unbiased and systematic study of gene expression profiling should allow the establishment of a new taxonomy of disease for obstetric and gynecologic syndromes. Thus, a new era is emerging in which reproductive processes and disorders could be characterized using molecular tools and fingerprinting. The design, analysis, and interpretation of microarray experiments require specialized knowledge that is not part of the standard curriculum of our discipline. This article describes the types of studies that can be conducted with microarray experiments (class comparison, class prediction, class discovery). We discuss key issues pertaining to experimental design, data preprocessing, and gene selection methods. Common types of data representation are illustrated. Potential pitfalls in the interpretation of microarray experiments, as well as the strengths and limitations of this technology, are highlighted. This article is intended to assist clinicians in appraising the quality of the scientific evidence now reported in the obstetric and gynecologic literature.

Microarray analysis reveals differential gene expression in hybrid sunflower species

This paper describes the creation of a cDNA microarray for annual sunflowers and its use to elucidate patterns of gene expression in Helianthus annuus, Helianthus petiolaris, and the homoploid hybrid species Helianthus deserticola. The array comprises 3743 ESTs (expressed sequence tags) representing approximately 2897 unique genes. It has an average clone/EST identity rate of 91%, is applicable across species boundaries within the annual sunflowers, and shows patterns of gene expression that are highly reproducible according to real-time RT-PCR (reverse transcription-polymerase chain reaction) results. Overall, 12.8% of genes on the array showed statistically significant differential expression across the three species. Helianthus deserticola displayed transgressive, or extreme, expression for 58 genes, with roughly equal numbers exhibiting up- or down-regulation relative to both parental species. Transport-related proteins were strongly over-represented among the transgressively expressed genes, which makes functional sense given the extreme desert floor habitat of H. deserticola. The potential adaptive value of differential gene expression was evaluated for five genes in two populations of early generation (BC2) hybrids between the parental species grown in the H. deserticola habitat. One gene (a G protein-coupled receptor) had a significant association with fitness and maps close to a QTL controlling traits that may be adaptive in the desert habitat.

Identical probes on different high-density oligonucleotide microarrays can produce different measurements of gene expression

Background

There are many potential sources of variability in a microarray experiment. Variation can arise from many aspects of the collection and processing of samples for gene expression analysis. Oligonucleotide-based arrays are thought to minimize one source of variability as identical oligonucleotides are expected to recognize the same transcripts during hybridization.

Results

We demonstrate that although the probes on the U133A GeneChip arrays are identical in sequence to probes designed for the U133 Plus 2.0 arrays the values obtained from an experimental hybridization can be quite different. Nearly half of the probesets in common between the two array types can produce slightly different values from the same sample. Nearly 70% of the individual probes in these probesets produced array specific differences.

Conclusion

The context of the probe may also contribute some bias to the final measured value of gene expression. At a minimum, this should add an extra level of caution when considering the direct comparison of experiments performed in two microarray formats. More importantly, this suggests that it may not be possible to know which value is the most accurate representation of a biological sample when comparing two formats.

Three-color cDNA microarrays with prehybridization quality control yield gene expression data comparable to that of commercial platforms

Despite their lower cost and high content flexibility, a limitation of in-house-prepared arrays has been their susceptibility to quality control (QC) issues and lack of QC standards across laboratories. Therefore, we developed a novel three-color array system that allows prehybridization QC as well as the Matarray software to facilitate acquisition of accurate gene expression data. In this study, we compared performance of our rat cDNA array to the Affymetrix RG-U34A and Agilent G4130A arrays using 2,824 UniGenes represented on all three arrays. Before data filtering, poor interplatform agreement was observed; however, after data filtering, differentially expressed UniGenes exhibited correlation coefficients of 0.91, 0.88, and 0.92 between the Affymetrix vs. Agilent, Affymetrix vs. cDNA, and Agilent vs. cDNA arrays, respectively. The Affymetrix, Agilent, and cDNA arrays agreed well with quantitative RT-PCR conducted on 42 UniGenes, yielding correlation coefficients of 0.90, 0.90, and 0.96, respectively. Each platform underestimated ratios relative to quantitative RT-PCR, possessing respective slopes of 0.86 ( R2 = 0.81), 0.65 ( R2 = 0.81), and 0.70 ( R2 = 0.92). Overall, these data show that the combination of our novel technical and analytic approaches yield an accurate platform for functional genomics that is concordant with commercial discovery arrays in terms of identifying regulated genes and pathways.

Reliability and reproducibility issues in DNA microarray measurements

DNA microarrays enable researchers to monitor the expression of thousands of genes simultaneously. However, the current technology has several limitations. Here we discuss problems related to the sensitivity, accuracy, specificity and reproducibility of microarray results. The existing data suggest that for relatively abundant transcripts the existence and direction (but not the magnitude) of expression changes can be reliably detected. However, accurate measurements of absolute expression levels and the reliable detection of low abundance genes are difficult to achieve. The main problems seem to be the sub-optimal design or choice of probes and some incorrect probe annotations. Well-designed data-analysis approaches can rectify some of these problems.

A human ImmunoChip cDNA microarray provides a comprehensive tool to study immune responses

DNA microarray technology has developed rapidly in recent years and has become an essential tool, providing novel approaches to biomedical research. In this paper, we describe a self-designed ImmunoChip cDNA array for immunological research. With a comprehensive selection of genes of interest, we can focus on key signalling pathways and molecular mechanisms at relatively low cost compared to commercial platforms which are usually targeted at global screening of gene expression. To validate the efficiency of the ImmunoChip, we studied T helper cell polarization to functionally distinct subsets (Th1 and Th2). We also developed a tool for quality control of cDNA microarrays that assesses the technical quality of an ImmunoChip. The information produced with the quality control tool is shown to be valuable for extracting correct information from cDNA microarrays. Gene expression measurements with ImmunoChip are in agreement with the results obtained using oligonucleotide microarrays and with published quantitative RT-PCR data. The ImmunoChip provides reliable measurements and gives new insights into various aspects of human immune responses.

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.

Dissection of the inflammatory bowel disease transcriptome using genome-wide cDNA microarrays

BACKGROUND

The differential pathophysiologic mechanisms that trigger and maintain the two forms of inflammatory bowel disease (IBD), Crohn disease (CD), and ulcerative colitis (UC) are only partially understood. cDNA microarrays can be used to decipher gene regulation events at a genome-wide level and to identify novel unknown genes that might be involved in perpetuating inflammatory disease progression.

METHODS AND FINDINGS

High-density cDNA microarrays representing 33,792 UniGene clusters were prepared. Biopsies were taken from the sigmoid colon of normal controls (n = 11), CD patients (n = 10) and UC patients (n = 10). 33P-radiolabeled cDNA from purified poly(A)+ RNA extracted from biopsies (unpooled) was hybridized to the arrays. We identified 500 and 272 transcripts differentially regulated in CD and UC, respectively. Interesting hits were independently verified by real-time PCR in a second sample of 100 individuals, and immunohistochemistry was used for exemplary localization. The main findings point to novel molecules important in abnormal immune regulation and the highly disturbed cell biology of colonic epithelial cells in IBD pathogenesis, e.g., CYLD (cylindromatosis, turban tumor syndrome) and CDH11 (cadherin 11, type 2). By the nature of the array setup, many of the genes identified were to our knowledge previously uncharacterized, and prediction of the putative function of a subsection of these genes indicate that some could be involved in early events in disease pathophysiology.

CONCLUSION

A comprehensive set of candidate genes not previously associated with IBD was revealed, which underlines the polygenic and complex nature of the disease. It points out substantial differences in pathophysiology between CD and UC. The multiple unknown genes identified may stimulate new research in the fields of barrier mechanisms and cell signalling in the context of IBD, and ultimately new therapeutic approaches.

Three microarray platforms: an analysis of their concordance in profiling gene expression

Background

Microarrays for the analysis of gene expression are of three different types: short oligonucleotide (25–30 base), long oligonucleotide (50–80 base), and cDNA (highly variable in length). The short oligonucleotide and cDNA arrays have been the mainstay of expression analysis to date, but long oligonucleotide platforms are gaining in popularity and will probably replace cDNA arrays. As part of a validation study for the long oligonucleotide arrays, we compared and contrasted expression profiles from the three formats, testing RNA from six different cell lines against a universal reference standard.

Results

The three platforms had 6430 genes in common. In general, correlation of gene expression levels across the platforms was good when defined by concordance in the direction of expression difference (upregulation or downregulation), scatter plot analysis, principal component analysis, cell line correlation or quantitative RT-PCR. The overall correlations (r values) between platforms were in the range 0.7 to 0.8, as determined by analysis of scatter plots. When concordance was measured for expression ratios significant at p-values of <0.05 and at expression threshold levels of 1.5 and 2-fold, the agreement among the platforms was very high, ranging from 93% to 100%.

Conclusion

Our results indicate that the long oligonucleotide platform is highly suitable for expression analysis and compares favorably with the cDNA and short oligonucleotide varieties. All three platforms can give similar and reproducible results if the criterion is the direction of change in gene expression and minimal emphasis is placed on the magnitude of change.

eXPRESSION: an in silico tool to predict patterns of gene expression

In embryological studies, expression pattern analyses are of special importance since genes that have temporally and spatially restricted expression are not only essential as lineage markers but are often causative in formation of specific fates. Further, where a molecule is expressed can be quite revealing in regard to its endogenous function. We present a gene discovery tool, termed eXPRESSION, that utilizes the public EST databases to identify genes matching desired transcriptional profiles. We first tested and validated the ability of eXPRESSION to discover tissue-specific genes in the adult mouse; empirically as well as with DNA microarrays and RT-PCRs. These studies showed that eXPRESSION predictions could identify genes that are specifically expressed in adult mouse tissues. Next, we developed a novel search strategy to find genes that are expressed in specific regions or tissues of the developing mouse embryo. With these tools, we identified several novel genes that exhibited a neural-specific or neural-enriched expression pattern during murine development. The data show that eXPRESSION is widely applicable and may be used to identify both adult and embryonic tissue- or organ-specific genes with minimal cost and effort.

A sequence-based identification of the genes detected by probesets on the Affymetrix U133 plus 2.0 array

One of the biggest problems facing microarray experiments is the difficulty of translating results into other microarray formats or comparing microarray results to other biochemical methods. We believe that this is largely the result of poor gene identification. We re-identified the probesets on the Affymetrix U133 plus 2.0 GeneChip array. This identification was based on the sequence of the probes and the sequence of the human genome. Using the BLAST program, we matched probes with documented and postulated human transcripts. This resulted in the redefinition of approximately 37% of the probes on the U133 plus 2.0 array. This updated identification specifically points out where the identification is complicated by cross-hybridization from splice variants or closely related genes. More than 5000 probesets detect multiple transcripts and therefore the exact protein affected cannot be readily concluded from the performance of one probeset alone. This makes naming difficult and impacts any downstream analysis such as associating gene ontologies, mapping affected pathways or simply validating expression changes. We have now automated the sequence-based identification and can more appropriately annotate any array where the sequence on each spot is known.

Are data from different gene expression microarray platforms comparable?

Many commercial and custom-made microarray formats are routinely used for large-scale gene expression surveys. Here, we sought to determine the level of concordance between microarray platforms by analyzing breast cancer cell lines with in situ synthesized oligonucleotide arrays (Affymetrix HG-U95v2), commercial cDNA microarrays (Agilent Human 1 cDNA), and custom-made cDNA microarrays from a sequence-validated 13K cDNA library. Gene expression data from the commercial platforms showed good correlations across the experiments (r = 0.78-0.86), whereas the correlations between the custom-made and either of the two commercial platforms were lower (r = 0.62-0.76). Discrepant findings were due to clone errors on the custom-made microarrays, old annotations, or unknown causes. Even within platform, there can be several ways to analyze data that may influence the correlation between platforms. Our results indicate that combining data from different microarray platforms is not straightforward. Variability of the data represents a challenge for developing future diagnostic applications of microarrays.

How consistent are expression chip platforms?

DNA arrays are now widely used in academia and industry, and expression profiling is recognised as a major tool for basic research as well as for drug development. It is also likely, in the near future, that DNA arrays will be used in clinical laboratories for diagnostic and prognostic purposes. Since several types of arrays are being used, the coherence of results obtained using these diverse platforms becomes an important issue: to what extent can data obtained in different laboratories and with different equipment be combined? Several recent papers address this issue and demonstrate that the expected agreement is not necessarily found. Consistent results can be obtained, but this requires careful identification of the genes assessed by the arrays, and scrupulous adherence to strict experimental procedures.

Molecular classification of human endometrial cycle stages by transcriptional profiling

Endometrium is a dynamic tissue that undergoes cyclic changes each month, under the overall control of estrogen and progesterone. The aims of this study were to investigate the changing global gene expression profile of human endometrium during the menstrual cycle using microarray technology and to determine the correlation between histopathological evaluation and molecular profile of the samples. Standard two-colour cDNA microarrays were performed on the 43 samples against a common reference, using a 10.5 K cDNA glass slide microarray. The results were validated using real-time PCR. Analysis of expression data was carried out using parametric analysis of variance with Benjamini-Hochberg correction. Hierarchical clustering reveals a strong relationship between histopathology and transcriptional profile of the samples. The study identified 1452 genes that showed significant changes in expression (P< or =0.05) across the menstrual cycle, with 425 genes having changes that are at least 2-fold. The data were also independently analysed by a CSIRO algorithm called GeneRaVE that identified a small subset of genes whose expression profiles could be used to classify nearly all the biopsies into their correct cycle stage. We also identified and validated three genes [(natural cytotoxicity triggering receptor (NCR)3, fucosyl transferase (FUT)4 and Fyn-binding protein (FYB)] that had not been shown to have significant cyclic changes in the human endometrium, previously. We have shown for the first time that endometrial cycle stage prediction is possible based on global gene expression profile.

A comparison of cDNA, oligonucleotide, and Affymetrix GeneChip gene expression microarray platforms

We have conducted a study to compare the variability in measured gene expression levels associated with three types of microarray platforms. Total RNA samples were obtained from liver tissue of four male mice, two each from inbred strains A/J and C57BL/6J. The same four samples were assayed on Affymetrix Mouse Genome Expression Set 430 GeneChips (MOE430A and MOE430B), spotted cDNA microarrays, and spotted oligonucleotide microarrays using eight arrays of each type. Variances associated with measurement error were observed to be comparable across all microarray platforms. The MOE430A GeneChips and cDNA arrays had higher precision across technical replicates than the MOE430B GeneChips and oligonucleotide arrays. The Affymetrix platform showed the greatest range in the magnitude of expression levels followed by the oligonucleotide arrays. We observed good concordance in both estimated expression level and statistical significance of common genes between the Affymetrix MOE430A GeneChip and the oligonucleotide arrays. Despite their apparently high precision, cDNA arrays showed poor concordance with other platforms.

A molecular description of brain trauma pathophysiology using microarray technology: an overview

It has been estimated that 50% of human transcriptome, the collection of mRNA in a cell, is expressed in the brain, making it one of the most complex organs to understand in terms of genomic responses to injury. The availability of genome sequences for several organisms coupled with the increasing affordability of microarray technologies makes it feasible to monitor the mRNA levels of thousands of genes simultaneously. In this paper, we provide an overview of findings using both cDNA- and oligonucleotide-based microarray analyses after experimental traumatic brain injury (TBI). Specifically, the utility of this methodology as a means of cataloging the biochemical sequelae of brain trauma and elucidating novel genes or pathways for further study is discussed. Furthermore, we offer future directions for the continued evaluation of microarray results and discuss the usefulness of microarray techniques as a testing format for determining the efficacy of mechanism-based therapies.

Confirming microarray data--is it really necessary?

The generation of corroborative data has become a commonly used approach for ensuring the veracity of microarray data. Indeed, the need to conduct corroborative studies has now become official editorial policy for at least 2 journals, and several more are considering introducing such a policy. The issue of corroborating microarray data is a challenging one-there are good arguments for and against conducting such experiments. However, we believe that the introduction of a fixed requirement to corroborate microarray data, especially if adopted by more journals, is overly burdensome and may, in at least several applications of microarray technology, be inappropriate. We also believe that, in cases in which corroborative studies are deemed essential, a lack of clear guidance leaves researchers unclear as to what constitutes an acceptable corroborative study. Guidelines have already been outlined regarding the details of conducting microarray experiments. We propose that all stakeholders, including journal editorial boards, reviewers, and researchers, should undertake concerted and inclusive efforts to address properly and clarify the specific issue of corroborative data. In this article we highlight some of the thorny and vague areas for discussion surrounding this issue. We also report the results of a poll in which 76 life science journals were asked about their current or intended policies on the inclusion of corroborative studies in papers containing microarray data.

FlyGEM, a full transcriptome array platform for the Drosophila community

We have constructed a DNA microarray to monitor expression of predicted genes in Drosophila. By using homotypic hybridizations, we show that the array performs reproducibly, that dye effects are minimal, and that array results agree with systematic northern blotting. The array gene list has been extensively annotated and linked-out to other databases. Incyte and the NIH have made the platform available to the community via academic microarray facilities selected by an NIH committee.

A comparison of oligonucleotide and cDNA-based microarray systems

Large-scale public data mining will become more common as public release of microarray data sets becomes a corequisite for publication. Therefore, there is an urgent need to clarify whether data from different microarray platforms are comparable. To assess the compatibility of microarray data, results were compared from the two main types of high-throughput microarray expression technologies, namely, an oligonucleotide-based and a cDNA-based platform, using RNA obtained from complex tissue (human colonic mucosa) of five individuals. From 715 sequence-verified genes represented on both platforms, 64% of the genes matched in "present" or "absent" calls made by both platforms. Calls were influenced by spurious signals caused by Alu repeats in cDNA clones, clone annotation errors, or matched probes that were designed to different regions of the gene; however, these factors could not completely account for the level of call discordance observed. Expression levels in sequence-verified, platform-overlapping genes were not related, as demonstrated by weakly positive rank order correlation. This study demonstrates that there is only moderate overlap in the results from the two array systems. This fact should be carefully considered when performing large-scale analyses on data originating from different microarray platforms.

Application of a customized pathway-focused microarray for gene expression profiling of cellular homeostasis upon exposure to nicotine in PC12 cells

Maintenance of cellular homeostasis is integral to appropriate regulation of cellular signaling and cell growth and division. In this study, we report the development and quality assessment of a pathway-focused microarray comprising genes involved in cellular homeostasis. Since nicotine is known to have highly modulatory effects on the intracellular calcium homeostasis, we therefore tested the applicability of the homeostatic pathway-focused microarray on the gene expression in PC-12 cells treated with 1 mM nicotine for 48 h relative to the untreated control cells. We first provided a detailed description of the focused array with respect to its gene and pathway content and then assessed the array quality using a robust regression procedure that allows for the exclusion of unreliable measurements while decreasing the number of false positives. As a result, the mean correlation coefficient between duplicate measurements of the arrays used in this study (control vs. nicotine treatment, three samples each) has increased from 0.974+/-0.017 to 0.995+/-0.002. Furthermore, we found that nicotine affected various structural and signaling components of the AKT/PKB signaling pathway and protein synthesis and degradation processes in PC-12 cells. Since modulation of intracellular calcium concentrations ([Ca(2+)](i)) and phosphatidylinositol signaling are important in various biological processes such as neurotransmitter release and tissue pathogenesis including tumor formation, we expect that the homeostatic pathway-focused microarray potentially can be used for the identification of unique gene expression profiles in comparative studies of drugs of abuse and diverse environmental stimuli, such as starvation and oxidative stress.

Deciphering the mechanisms of homeostatic plasticity in the hypothalamo-neurohypophyseal system—genomic and gene transfer strategies

The hypothalamo-neurohypophyseal system (HNS) is the specialised brain neurosecretory apparatus responsible for the production of a peptide hormone, vasopressin, that maintains water balance by promoting water conservation at the level of the kidney. Dehydration evokes a massive increase in the regulated release of hormone from the HNS, and this is accompanied by a plethora of changes in morphology, electrical properties and biosynthetic and secretory activity, all of which are thought to facilitate hormone production and delivery, and hence the survival of the organism. We have adopted a functional genomic strategy to understand the activity dependent plasticity of the HNS in terms of the co-ordinated action of cellular and genetic networks. Firstly, using microarray gene-profiling technologies, we are elucidating which genes are expressed in the HNS, and how the pattern of expression changes following physiological challenge. The next step is to use transgenic rats to probe the functions of these genes in the context of the physiological integrity of the whole organism.

Comparison and meta-analysis of microarray data: from the bench to the computer desk

The upcoming availability of public microarray repositories and of large compendia of gene expression information opens up a new realm of possibilities for microarray data analysis. An essential challenge is the efficient integration of microarray data generated by different research groups on different array platforms. This review focuses on the problems associated with this integration, which are: (1) the efficient access to and exchange of microarray data; (2) the validation and comparison of data from different platforms (cDNA and short and long oligonucleotides); and (3) the integrated statistical analysis of multiple data sets.

Gene expression profiling of ErbB receptor and ligand-dependent transcription

Overexpression of ErbB2 and ErbB4 receptors in breast cancers may be accompanied by contrasting clinical outcomes. To investigate the molecular mechanisms contributing to these differences, we undertook a comparative study of gene expression regulated by the two receptors. Agonistic antibodies were employed to activate ErbB2 and ErbB4 in isolation from the other ErbBs in breast cancer cells. Gene expression profiling using a 16 755-gene oligonucleotide array was performed to identify transcriptional targets of receptor activation. Our results indicate that, in the same cell line, ErbB2 and ErbB4 activation influence gene transcription differentially. Although there are genes that are regulated by signaling from both receptors, there are also receptor-specific targets that are preferentially regulated by each receptor. We further show that two ligands acting via the same receptor homodimer may activate different subsets of genes. Many of the induced genes are hitherto unidentified targets of ErbB signaling. These include ErbB4 targets EPS15R, GATA4, and RAB2 and ErbB2-activated HRY/HES1 and PPAP2A. Targets of ErbB2 homodimer signaling may be especially important as markers in breast cancer, where ErbB2 homodimerization mediated by overexpression and ligand-independent activation is common.

Construction of a cDNA-based microarray forDrosophila melanogaster: a comparison of gene transcription profiles from SL2 and Kc167 cells

We have constructed a DNA microarray that represents approximately 6900 of the estimated 13 598 genes in the Drosophila melanogaster genome. The microarray contains 5756 target cDNAs from the Berkeley Drosophila Genome Project, 1078 cDNAs from the National Institutes of Health Drosophila testis cDNA library, and 546 gene fragments that were amplified from genomic DNA. The methods for DNA amplification and microarray manufacture are presented. Academic researchers can obtain the microarray from the Canadian Drosophila Microarray Centre. To evaluate the utility of these arrays, we compared the gene transcription profiles of two commonly used Drosophila cell lines. Analysis revealed that 5412 spot pairs gave signals consistently above the average background in Kc167 cells, whereas 5636 spot pairs met this criterion in SL2 cells. When the expression profiles of the cell lines were compared, 1437 genes displayed at least a 1.5-fold difference, and 170 genes had a threefold or greater difference between the two cell lines. In each case, with respect to Kc167 when compared with SL2 cells, the number of genes that were upregulated was nearly equal to the number of downregulated genes. This result demonstrates that despite the similar embryonic derivation of both cell lines, their transcriptional profiles are very different.Key words: DNA microarray, Drosophila, transcriptional regulation, SL2, Kc167.

Protection of lungs from hyperoxic injury: gene expression analysis of cyclosporin A therapy

We have previously shown that cyclosporin A (CsA), an inhibitor of protein phosphatase 2B (calcineurin), attenuates hyperoxia-induced reductions in murine lung compliance. CsA protected against hyperoxia-induced changes in neutrophil infiltration, capillary congestion, edema, and hyaline membrane formation. Gene expression studies were conducted to identify the gene expression patterns underlying the protective effects of CsA during hyperoxic lung injury. After 72 h of simultaneous treatment with >95% oxygen and CsA (50 mg x kg(-1) x day(-1)), RNA was isolated from murine lungs. RNA from treated and untreated lungs was reverse transcribed to cDNA, competitively hybridized, and used to probe 8,734 complimentary DNAs on the Incyte mouse GEM 1 array. Several known genes and expressed sequence tags (ESTs) showed increased (GenBank accession numbers: AA125385, AA241295, W87197, syntaxin, and cyclin G) or decreased [AA036517, AA267567, AA217009, W82577, uteroglobin, stromal cell-derived factor 1, and surfactant protein C (SP-C)] expression after hyperoxia. Hyperoxia-stimulated reductions in SP-C gene expression were confirmed through Northern blot analysis. The increase in gene expression of one expressed sequence tag (AA125385) with hyperoxia was reversed by CsA treatment. Sequence data demonstrated that this EST has high homology to murine cyclin B1. Western blot analysis did not demonstrate any changes in distal lung cyclin B1 expression after hyperoxia. Protein expression of cyclin B1 in the distal lung was observed in the endothelial cells, bronchiolar epithelial cells, and both the type I and type II alveolar epithelial cells. Further analysis of cyclin B1 may elucidate the protective actions of CsA in hyperoxic injury.

Genetics and susceptibility to toxic chemicals: do you (or should you) know your genetic profile?

This review is based on a symposium/roundtable session, sponsored by the Division of Toxicology of the American Society for Pharmacology and Experimental Therapeutics, that was held at the 2002 Experimental Biology meeting in New Orleans, LA. The focus is on the role of pharmacogenomics in determining individual susceptibility to chemically induced toxicity. An individual's risk of disease from exposure to toxic chemicals is determined by a complex interplay between genetics, physiology, and concurrent or prior exposures to drugs and other chemicals. The first section of the review defines the basics of pharmacogenetics and pharmacogenomics and assesses the current state of the science. Selected applications to specific enzyme systems are summarized by way of example. New, state-of-the-art approaches to studying genetic determinants of susceptibility, including analytical methods and transgenic technology, are then discussed. Finally, ethical and legal concerns with the application of this knowledge and methodology to human health will be discussed.

Methods in molecular cardiology: microarray technology

It has become more and more evident that changes in expression levels of genes can play an important role in cardiovascular diseases. Specific gene expression profiles may explain, for example, the pathophysiology of myocardial hypertrophy and pump failure and may provide clues for therapeutic interventions. Knowledge of gene expression patterns can also be applied for diagnostic and prognostic purposes, in which differences in gene activity can be used for classification. DNA microarray technology has become the method of choice to simultaneously study the expression of many different genes in a single assay. Each microarray contains many thousands of different DNA sequences attached to a glass slide. The amount of messenger RNA, which is a measure of gene activity, is compared for each gene on the microarray by labelling the mRNA with different fluorescently labelled nucleotides (Cy3 or Cy5) for the test and reference samples. After hybridisation to the microarray the relative amounts of a particular gene transcript in the two samples can be determined by measuring the signal intensities for the fluorescent groups (Cy3 and Cy5) and calculating signal ratios. This paper describes the development of in-house microarray technology, using commercially available cDNA collections. Several technical approaches will be compared and an overview of the pitfalls and possibilities will be presented. The technology will be explained in the context of our project to determine gene expression differences between normal, hypertrophic and failing heart.

Standardization of protocols in cDNA microarray analysis

Systematic variations can occur at various steps of a cDNA microarray experiment and affect the measurement of gene expression levels. Accepted standards integrated into every cDNA microarray analysis can assess these variabilities and aid the interpretation of cDNA microarray experiments from different sources. A universally applicable approach to evaluate parameters such as input and output ratios, signal linearity, hybridization specificity and consistency across an array, as well as normalization strategies, is the utilization of exogenous control genes as spike-in and negative controls. We suggest that the use of such control sets, together with a sufficient number of experimental repeats, in-depth statistical analysis and thorough data validation should be made mandatory for the publication of cDNA microarray data.

Breast cancer revisited using DNA array-based gene expression profiling

Breast cancer is a complex genetic disease characterized by the accumulation of multiple molecular alterations. The resulting clinical heterogeneity makes current diagnostic and therapeutic strategies less than perfectly adapted to each patient. Pathological and clinical factors are insufficient to capture the complex cascade of events that drive the clinical behavior of tumors. High-throughput molecular technologies provide novel tools to tackle this complexity. In particular, DNA arrays allow the simultaneous and quantitative analysis of the mRNA expression levels of thousands of genes in a single assay. Potential applications are multiple in the cancer field and the first research results are promising; comprehensive gene expression profiles of breast tumors are providing insights into mammary oncogenesis and are revealing new tumor subgroups previously indistinguishable. Significant advances will be the identification of new diagnostic, prognostic and predictive biomarkers as well as the discovery of new potential therapeutic targets. This review presents recent applications of DNA arrays in breast cancer research and discusses some issues to address in the near future to allow the technology to reach its full potential.

Gene expression profiling: methodological challenges, results, and prospects for addiction research

This review describes the current methods used to profile gene expression. These methods include microarrays, spotted arrays, serial analysis of gene expression (SAGE), and massive parallel signature sequencing (MPSS). Methodological and statistical problems in interpreting microarray and spotted array experiments are also discussed. Methods and formats such as minimum information about microarray experiments (MIAME) needed to share gene expression data are described. The last part of the review provides an overview of the application of gene-expression profiling technology to substance abuse research and discusses future directions.

Options available--from start to finish--for obtaining data from DNA microarrays II

Microarray technology has undergone a rapid evolution. With widespread interest in large-scale genomic research, an abundance of equipment and reagents have now become available and affordable to a large cross section of the scientific community. As protocols become more refined, careful investigators are able to obtain good quality microarray data quickly. In most recent times, however, perhaps one of the biggest obstacles researchers face is not the manufacture and use of microarrays at the bench, but storage and analysis of the array data. This review discusses the most recent equipment, reagents and protocols available to the researcher, as well as describing data analysis and storage options available from the evolving field of microarray informatics.