An evaluation of the performance of cDNA microarrays for detecting changes in global mRNA expression

Selectively reduced expression of synaptic plasticity-related genes in amyloid precursor protein + presenilin-1 transgenic mice

A critical question in Alzheimer's disease (AD) research is the cause of memory loss that leads to dementia. The amyloid precursor protein + presenilin-1 (APP+PS1) transgenic mouse is a model for amyloid deposition, and like AD, the mice develop memory deficits as amyloid deposits accumulate. We profiled gene expression in these transgenic mice by microarray and quantitative RT-PCR (qRT-PCR). At the age when these animals developed cognitive dysfunction, they had reduced mRNA expression of several genes essential for long-term potentiation and memory formation (Arc, Zif268, NR2B, GluR1, Homer-1a, Nur77/TR3). These changes appeared to be related to amyloid deposition, because mRNA expression was unchanged in the regions that did not accumulate amyloid. Transgene expression was similar in both amyloid-containing and amyloid-free regions of the brain. Interestingly, these changes occurred without apparent changes in synaptic structure, because a number of presynaptic marker mRNAs (growth-associated protein-43, synapsin, synaptophysin, synaptopodin, synaptotagmin, syntaxin) remained stable. Additionally, a number of genes related to inflammation were elevated in transgenic mice, primarily in the regions containing amyloid. In AD cortical tissue, the same memory-associated genes were downregulated. However, all synaptic and neuronal transcripts were reduced, implying that the loss of neurons and synapses contributed to these changes. We conclude that reduced expression of selected genes associated with memory consolidation are linked to memory loss in both circumstances. This suggests that the memory loss in APP+PS1 transgenic mice may model the early memory dysfunction in AD before the degeneration of synapses and neurons.

Oligodeoxyribonucleotide probe accessibility on a three-dimensional DNA microarray surface and the effect of hybridization time on the accuracy of expression ratios

BACKGROUND

DNA microarrays are now routinely used to monitor the transcript levels of thousands of genes simultaneously. However, the array fabrication method, hybridization conditions, and oligodeoxyribonucleotide probe length can impact the performance of a DNA microarray platform.

RESULTS

We demonstrate solution-phase hybridization behavior of probe:target interactions by showing a strong correlation between the effect of mismatches in probes attached to a three dimensional matrix of a microarray and solution-based, thermodynamic duplex melting studies. The effects of mismatches in the probes attached to the microarray also demonstrate that most, if not all, of the oligodeoxyribonucleotide is available for hybridization. Kinetic parameters were also investigated. As anticipated, hybridization signals increased in a transcript concentration-dependent manner, and mismatch specificity increased with hybridization time. Unexpectedly, hybridization time increased the accuracy of fold changes by relieving the compression observed in expression ratios, and this effect may be more dramatic for larger fold changes.

CONCLUSIONS

Taken together, these studies demonstrate that a three-dimensional surface may enable use of shorter oligodeoxyribonucleotide probes and that hybridization time may be critical in improving the accuracy of microarray data.

Use of a three-color cDNA microarray platform to measure and control support-bound probe for improved data quality and reproducibility

Construction methodologies for cDNA microarrays lack the ability to determine array integrity prior to hybridization, leaving the array itself a source of uncontrolled experimental variation. We solved this problem through development of a three-color cDNA array platform whereby printed probes are tagged with fluorescein and are compatible with Cy3 and Cy5 target labeling dyes when using confocal laser scanners possessing narrow bandwidths. Here we use this approach to: (i) develop a tracking system to monitor the printing of probe plates at predicted coordinates; (ii) define the quantity of immobilized probe necessary for quality hybridized array data to establish pre-hybridization array selection criteria; (iii) investigate factors that influence probe availability for hybridization; and (iv) explore the feasibility of hybridized data filtering using element fluorescein intensity. A direct and significant relationship (R2 = 0.73, P < 0.001) between pre-hybridization average fluorescein intensity and subsequent hybridized replicate consistency was observed, illustrating that data quality can be improved by selecting arrays that meet defined pre-hybridization criteria. Furthermore, we demonstrate that our three-color approach provides a means to filter spots possessing insufficient bound probe from hybridized data sets to further improve data quality. Collectively, this strategy will improve microarray data and increase its utility as a sensitive screening tool.

High-resolution voxelation mapping of human and rodent brain gene expression

Voxelation allows high-throughput acquisition of multiple volumetric images of brain gene expression, similar to those obtained from biomedical imaging systems. To obtain these images, the method employs analysis of spatially registered voxels (cubes). For creation of high-resolution maps using voxelation, relatively small voxel sizes are necessary and instruments will be required for semiautomated harvesting of such voxels. Here, we describe two devices that allow spatially registered harvesting of voxels from the human and rodent brain, giving linear resolutions of 3.3 and 1 mm, respectively. Gene expression patterns obtained using these devices showed good agreement with known expression patterns. The voxelation instruments and their future iterations represent a valuable approach to the genome scale acquisition of gene expression patterns in the human and rodent brain.

Reduced cellulose synthesis invokes lignification and defense responses in Arabidopsis thaliana

The cell wall determines the shape of plant cells and is also the primary interface for pathogen interactions. The structure of the cell wall can be modified in response to developmental and environmental cues, for example to strengthen the wall and to create barriers to pathogen ingress. The ectopic lignin 1-1 and 1-2 (eli1-1 and eli1-2) mutations lead to an aberrant deposition of lignin, a complex phenylpropanoid polymer. We show that the eli1 mutants occur in the cellulose synthase gene CESA3 in Arabidopsis thaliana and cause reduced cellulose synthesis, providing further evidence for the function of multiple CESA subunits in cellulose synthesis. We show that reduced levels of cellulose synthesis, caused by mutations in cellulose synthase genes and in genes affecting cell expansion, activate lignin synthesis and defense responses through jasmonate and ethylene and other signaling pathways. These observations suggest that mechanisms monitoring cell wall integrity can activate lignification and defense responses.

DNA microarrays: translation of the genome from laboratory to clinic

As the complete sequences of human and other mammalian genomes become available we are faced with the challenge of understanding how variation in sequence and gene expression contributes to neurological and psychiatric disorders. DNA microarrays, or DNA chips, provide the means to measure simultaneously where and when thousands of genes are expressed. Microarrays are changing the way that researchers approach work at the bench and have already yielded new insights into brain tumours, multiple sclerosis, acute neurological insults such as stroke and seizures, and schizophrenia. The study of disease-related changes in gene expression is the first step in the long process in translation of genome research to the clinic. Eventually, the changes observed in microarray studies will need to be independently confirmed and we wil need to understand how gene expression changes translate into functional effects at the cellular level in the nervous system. Progress in these studies will translate into array-based disease classification schemes and help optimise therapy for individual patients based on gene expression patterns or their genetic background.

URP1: a member of a novel family of PH and FERM domain-containing membrane-associated proteins is significantly over-expressed in lung and colon carcinomas

In a concerted effort to identify biomarkers for lung and colon carcinomas by genome-wide transcriptional profiling, we describe the identification and cloning of one such gene as well as two additional closely related genes. Due to the strong sequence homology to the C. elegans UNC-112 we call this gene URP1, for UNC-112 related protein. We have also isolated the full-length clones for another novel related gene, URP2 and the previously discovered MIG-2 gene. Collectively, these proteins, together with two from Drosophila, appear to form a novel membrane-associated FERM and PH domain-containing protein family. Transcriptional analysis shows that only URP1 is significantly differentially regulated, being over-expressed in 70% of the colon carcinomas and 60% of the lung carcinomas tested. Quantification of URP1 expression by qRT-PCR showed up-regulation of the gene by 60-fold in lung tumors and up to nearly 6-fold in colon tumors. Northern blot analysis of URP1 indicates that normal expression is restricted to neuromuscular tissues. In contrast, the expression of URP2 appears to be confined primarily to tissues of the immune system. SNP analysis of URP1 reveals that it is highly polymorphic, containing seven sites, four of which are in the coding region and one position that results in the interchangeable substitution of glutamic acid and lysine. Finally, we have shown that the genomic structure for all three genes is nearly identical with all encoded by 15 exons although URP1 gene localized to chromosome 20p13, URP2 to 11q12 and MIG-2 to 14q22. This conserved exon structure suggests that all three members probably arose by gene duplication from one ancestral gene. The presence of multiple FERM domains characteristic of cytoplasmic plasma membrane to cytoskeleton linkers and a PH domain typical of membrane-anchored proteins involved in signal transduction suggest an important role for URP1 in tumorigenesis.

Identification of reciprocally regulated gene modules in regenerating dorsal root ganglion neurons and activated peripheral or central nervous system glia

Differential gene expression in the rat after injury of dorsal root ganglion neurons in vivo, and simulation injury of Schwann cells and oligodendrocytes in vitro was analyzed using high-density cDNA microarrays. The analyses were carried out to study the genetic basis of peripheral nerve regeneration, and to compare gene regulation in glia of the central (oligodendrocyte) and peripheral (Schwann cell) nervous systems. The genes showing significant differential regulation in the three study groups represented all aspects of cellular metabolism. However, two unexpected observations were made. Firstly, a number of identical genes were differentially regulated in activated Schwann cells, activated oligodendrocytes and regenerating DRG neurons. Specifically, a group of 113 out of 210 genes that were down-regulated in Schwann cells upon lipopolysaccharide (LPS) treatment, were identical to genes up-regulated in the injured, regenerating DRG. Furthermore, a group of 53 out of 71 genes that were down-regulated in interferon gamma (IFN-gamma)/LPS-activated oligodendrocytes, were identical to genes up-regulated in the DRG neurons. Finally, 22 genes were common to these three groups, i.e., down-regulated in activated oligodendrocytes, down-regulated in activated Schwann cells, and up-regulated in regenerating DRG neurons. Secondly, a group of 16 cell-cycle and proliferation-related genes were up-regulated in the DRG following sciatic nerve crush, despite the absence of cells undergoing mitosis in the DRG, or any significant presence of apoptosis-related gene expression. Therefore, it appears that in these three cell types, large sets of genes are reciprocally regulated upon injury and/or activation. This suggests that the activation of the injury-related gene expression program in cell derivatives of the neuroectoderm involves, in part, highly conserved genetic elements.

Expression profiling of osteosarcoma cells transfected with MDR1 and NEO genes: regulation of cell adhesion, apoptosis, and tumor suppression-related genes

The expression patterns of the osteosarcoma cell line U-2 OS, and three derived subclones containing stably transfected MDR1, NEO and MDR1/NEO genes were compared using cDNA microarrays comprising 8976 known genes and expressed sequenced tags. Data provided new insights into three critical issues. First, MDR1 overexpression was associated with altered expression of genes related to several cellular pathways, including (a). drug influx/efflux (eg, dynamin 3), (b). metabolic enzymes (eg, monoamine oxidase A), (c). cell adhesion (eg, EPCAM), (d). apoptotic signaling (eg, I-TRAF), (e). senescence (eg, telomerase RNA binding protein staufen), (f). tumor suppression-related genes (eg, KISS-1 and ephrin B3), and (g). immune system receptors (eg, LENG2). MDR1, EPCAM, and ephrin B3 expression was confirmed by immunohistochemistry. Second, MDR1 transfected cells selected with either doxorubicin or neomycin showed distinct expression profiles that could be related to differential selection. Moreover, hierarchical clustering indicated that cells transfected with MDR1 alone, or cotransfected with NEO, displayed more closely related expression profiles than cells transfected only with NEO. Third, transfection with NEO and selection with neomycin produced a considerable number of expression changes within the cell. This study further elucidates the genetic events associated with MDR1 expression and identifies novel targets associated with multidrug resistance.

Effect of oxidized low-density lipoprotein on differential gene expression in primary human endothelial cells

Oxidative modification of low-density lipoprotein (LDL) plays an important role in the initiation and progression of atherosclerosis. It has been proposed that the biological action of oxidized LDL (ox-LDL) may be partially attributed to its effect on a shift of the pattern of gene expression in endothelial cells. To examine the transcriptional response to ox-LDL, we applied cDNA array technology to cultured primary human endothelial cells challenged with oxidized human LDL. A twofold or greater difference in the expression of a particular gene was considered a significant difference in transcript abundance. Seventy-eight of the 588 genes analyzed were differentially expressed in response to the treatment. Ox-LDL significantly affected the expression of genes encoding for transcription factors, cell receptors, growth factors, adhesion molecules, extracellular matrix proteins, and enzymes involved in cholesterol metabolism. The alteration of the expression pattern of several genes was substantiated post hoc using RT-PCR. The experimental strategy identified several novel ox-LDL-sensitive genes associated with a "response to injury" providing a conceptual background to be utilized for future studies addressing the molecular basis of the early stages of atherogenesis.

Modeling gene expression measurement error: a quasi-likelihood approach

BACKGROUND

Using suitable error models for gene expression measurements is essential in the statistical analysis of microarray data. However, the true probabilistic model underlying gene expression intensity readings is generally not known. Instead, in currently used approaches some simple parametric model is assumed (usually a transformed normal distribution) or the empirical distribution is estimated. However, both these strategies may not be optimal for gene expression data, as the non-parametric approach ignores known structural information whereas the fully parametric models run the risk of misspecification. A further related problem is the choice of a suitable scale for the model (e.g. observed vs. log-scale).

RESULTS

Here a simple semi-parametric model for gene expression measurement error is presented. In this approach inference is based an approximate likelihood function (the extended quasi-likelihood). Only partial knowledge about the unknown true distribution is required to construct this function. In case of gene expression this information is available in the form of the postulated (e.g. quadratic) variance structure of the data. As the quasi-likelihood behaves (almost) like a proper likelihood, it allows for the estimation of calibration and variance parameters, and it is also straightforward to obtain corresponding approximate confidence intervals. Unlike most other frameworks, it also allows analysis on any preferred scale, i.e. both on the original linear scale as well as on a transformed scale. It can also be employed in regression approaches to model systematic (e.g. array or dye) effects.

CONCLUSIONS

The quasi-likelihood framework provides a simple and versatile approach to analyze gene expression data that does not make any strong distributional assumptions about the underlying error model. For several simulated as well as real data sets it provides a better fit to the data than competing models. In an example it also improved the power of tests to identify differential expression.

Sex- and age-dependent human transcriptome variability: implications for chronic heart failure

Heart failure (HF) is the end result of progressive and diverse biological adaptations within the diseased myocardium. We used cDNA microarrays and quantitative PCR to examine the transcriptomes of 38 left ventricles from failing and nonfailing human myocardium. After identification of a pool of putative HF-responsive candidate genes by microarrays on seven nonfailing and eight failing hearts, we used quantitative PCR and a general linear statistical model in a larger sample set (n = 34) to validate and examine the role of contributing biological variables (age and sex). We find that most HF-candidate genes (transcription factors, Cebpb, Npat; signaling molecules, Map2k3, Map4k5; extracellular matrix proteins, Lum, Cola1; and metabolic enzymes, Mars) demonstrated significant changes in gene expression; however, the majority of differences among samples depended on variables such as sex and age, and not on HF alone. Some HF-responsive gene products also demonstrated highly significant changes in expression as a function of age and/or sex, but independent of HF (Ngp1, Cd163, and Npat). These results emphasize the need to account for biological variables (HF, sex and age interactions) to elucidate genomic correlates that trigger molecular pathways responsible for the progression of HF syndromes.

Transcriptional profiling of Krüppel-like factor 4 reveals a function in cell cycle regulation and epithelial differentiation

Krüppel-like factor 4 (KLF4) is an epithelially enriched, zinc finger-containing transcription factor, the expression of which is associated with growth arrest. Constitutive expression of KLF4 inhibits G1/S transition of the cell cycle but the manner by which it accomplishes this effect is unclear. To better understand the biochemical function of KLF4, we identified its target genes using cDNA microarray analysis in an established human cell line containing inducible KLF4. RNA extracted from induced and control cells were hybridized differentially to microarray chips containing 9600 human cDNAs. In all, 84 genes with significantly increased expression and 107 genes with significantly reduced expression due to KLF4 induction were identified. The affected genes are sorted to several clusters on the basis of functional relatedness. A major cluster belongs to genes involved in cell-cycle control. Within this cluster, many up-regulated genes are inhibitors of the cell cycle and down-regulated genes are promoters of the cell cycle. Another up-regulated gene cluster includes nine keratin genes, of which seven are located in a specific region on chromosome 12. The results indicate that KLF4 is involved in the control of cell proliferation and does so by eliciting changes in expression of numerous cell-cycle regulatory genes in a concerted manner. Furthermore, KLF4 regulates expression of a group of epithelial-specific keratin genes in a manner consistent with a potential locus control region function.

Three color cDNA microarrays: quantitative assessment through the use of fluorescein-labeled probes

Gene expression studies using microarrays have great potential to generate new insights into human disease pathogenesis, but data quality remains a major obstacle. In particular, there does not exist a method to determine prior to hybridization whether an array will yield high quality data, given good study design and target preparation. We have solved this problem through development of a three-color cDNA microarray platform where printed probes are fluorescein labeled, but are spectrally compatible with Cy3 and Cy5 dye-labeled targets when using confocal laser scanners possessing narrow bandwidths. This approach enables prehybridization evaluation of array/spot morphology, DNA deposition and retention and background levels. By using these measurements and the intra-slide coefficient of variation for fluorescence intensity we show that slides in the same batch are not equivalent and measurable prehybridization parameters can be predictive of hybridization performance as determined by replicate consistency. When hybridizing target derived from two cell lines to high and low quality replicate pairs (n = 50 pairs), a direct and significant relationship between prehybridization signal-to-background noise and post-hybridization reproducibility (R2 = 0.80, P < 0.001) was observed. We therefore conclude that slide selection based upon prehybridization quality scores will greatly benefit the ability to generate reliable gene expression data.

Determination of variations in gene expression during fracture healing

The genetic make-up and physiological state of a cell or tissue in an organism interact to determine the level at which specific genes are expressed. Identifying genes differentially expressed between 2 genetic or physiological states often gives insight into the molecular mechanisms controlled by the process in question. Various methods have been devised to identify differentially expressed genes and to quantify the expression of differentially regulated genes at the RNA or protein level. These methods are most accurate when the experimental samples are derived from highly controlled and reproducible sources, such as cultured cells. However, no simple in vitro models have been developed to study all biological processes and some are still best studied in the context of the whole organism. Using bone fracture healing as a model, we quantified the expression of 2 housekeeping and 2 regulatory genes during this complex biological process to determine the statistical parameters required to study differential gene expression in tissue samples derived from entire organisms. Our analysis shows that 5 samples in each group are needed to identify genes differentially expressed by a factor of 3 between 2 physiological or genetic states.

Error-correcting microarray design

We describe a microarray design based on the concept of error-correcting codes from digital communication theory. Currently, microarrays are unable to efficiently deal with "drop-outs," when one or more spots on the array are corrupted. The resulting information loss may lead to decoding errors in which no quantitation of expression can be extracted for the corresponding genes. This issue is expected to become increasingly problematic as the number of spots on microarrays expands to accommodate the entire genome. The error-correcting approach employs multiplexing (encoding) of more than one gene onto each spot to efficiently provide robustness to drop-outs in the array. Decoding then allows fault-tolerant recovery of the expression information from individual genes. The error-correcting method is general and may have important implications for future array designs in research and diagnostics.

MicroSAGE is highly representative and reproducible but reveals major differences in gene expression among samples obtained from similar tissues

BACKGROUND

Serial analysis of gene expression using small amounts of starting material (microSAGE) has not yet been conclusively shown to be representative, reproducible or accurate.

RESULTS

We show that microSAGE is highly representative, reproducible and accurate, but that pronounced differences in gene expression are seen between tissue samples taken from different individuals.

CONCLUSIONS

MicroSAGE is a reliable method of comprehensively profiling differences in gene expression among samples, but care should be taken in generalizing results obtained from libraries constructed from tissue obtained from different individuals and/or processed or stored differently.

Global identification of target genes regulated by APETALA3 and PISTILLATA floral homeotic gene action

Identifying the genes regulated by the floral homeotic genes APETALA3 (AP3) and PISTILLATA (PI) is crucial for understanding the molecular mechanisms that lead to petal and stamen formation. We have used microarray analysis to conduct a broad survey of genes whose expression is affected by AP3 and PI activity. DNA microarrays consisting of 9216 Arabidopsis ESTs were screened with probes corresponding to mRNAs from different mutant and transgenic lines that misexpress AP3 and/or PI. The microarray results were further confirmed by RNA gel blot analyses. Our results suggest that AP3 and PI regulate a relatively small number of genes, implying that many genes used in petal and stamen development are not tissue specific and likely have roles in other processes as well. We recovered genes similar to previously identified petal- and stamen-expressed genes as well as genes that were not implicated previously in petal and stamen development. A very low percentage of the genes recovered encoded transcription factors. This finding suggests that AP3 and PI act relatively directly to regulate the genes required for the basic cellular processes responsible for petal and stamen morphogenesis.

Molecular and functional profiling of memory CD8 T cell differentiation

How and when memory T cells form during an immune response are long-standing questions. To better understand memory CD8 T cell development, a time course of gene expression and functional changes in antigen-specific T cells during viral infection was evaluated. The expression of many genes continued to change after viral clearance in accordance with changes in CD8 T cell functional properties. Even though memory cell precursors were present at the peak of the immune response, these cells did not display hallmark functional traits of memory T cells. However, these cells gradually acquired the memory cell qualities of self-renewal and rapid recall to antigen suggesting the model that antigen-specific CD8 T cells progressively differentiate into memory cells following viral infection.

Analysis of far-red light-regulated genome expression profiles of phytochrome A pathway mutants in Arabidopsis

Phytochrome A (phyA) is the primary photoreceptor responsible for various far-red (FR) light-mediated responses. Previous studies have identified multiple phyA signaling mutants, including both positive and negative regulators of the phyA-mediated responses. How these defined intermediates act to mediate FR light responses is largely unknown. Here a cDNA microarray was used to examine effects of those mutations on the far-red light control of genome expression. Clustering analysis of the genome expression profiles supports the notion that phyA signaling may entail a network with multiple paths, controlling overlapping yet distinct sets of gene expression. FHY1, FAR1 and FHY3 most likely act upstream in the phyA signaling network, close to the phyA photoreceptor itself. FIN219, SPA1 and REP1 most likely act somewhere more downstream in the network and control the expression of smaller sets of genes. Further, this study also provides genomics evidence for the partial functional redundancy between FAR1 and FHY3. These two homologous proteins control the expression of a largely overlapping set of genes, and likely act closely together in the phyA-mediated FR light responses.

DNA microarray analysis of cortical gene expression during early recirculation after focal brain ischemia in rat

Focal brain ischemia is followed by changes in gene expression as reflected by altered mRNA levels. DNA microarray analysis can be used to survey thousands of genes for differential expression triggered by ischemic metabolic stress. In this study, Sprague-Dawley rats were subjected to 2 h of middle cerebral artery occlusion (MCAO) using an intravascular poly-L-lysine-coated filament, and brains were removed after 3 h of recirculation for mRNA isolation. A differential measurement of mRNAs from post-ischemic and sham control animals was performed using the Mouse UniGene 1 microarray. Established values for differential expression were used (> or =1.7 or < or =-1.7 fold), and hits (n=2-3 arrays) divided into known 'ischemia-hypoxia response' genes and 'newly connected' annotated genes. n=28 ischemia-hypoxia response genes were up-regulated and n=6 were down-regulated. Regulated genes comprised immediate early genes, heat shock proteins, anti-oxidative enzymes, trophic factors, and genes involved in RNA metabolism, inflammation and cell signaling. Based on the ability of the microarray to replicate known changes in gene expression, n=35 newly connected genes were found up-regulated and n=41 down-regulated. DNA microarray analysis allows one to develop novel working hypotheses for responses to brain ischemia based on the regulation of annotated genes.

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.

DNA microarrays and toxicogenomics: applications for ecotoxicology?

Toxicogenomics attempts to define how the regulation and expression of genes mediate the toxicological effects associated with exposure to a chemical. DNA microarrays are rapidly becoming one of the tools of choice for large-scale toxicogenomic studies. An approach in modern toxicogenomics has been to classify toxicity based on gene transcriptional patterns; comparing the transcriptional responses of a chemical with unknown toxicity to those for which the transcriptional profiles and toxicological endpoints have been well characterized. Recent evidence suggests that gene expression microarrays may be instrumental in defining mechanisms of action of toxicants. However, several assumptions are inherent to a toxicogenomic-based approach in toxicology, many of which remain to be validated. Gene expression profiling using DNA microarrays represents a snapshot of the gene transcriptional responses occurring at a particular time and within a particular tissue. Toxicity, on the other hand, represents a continuum of possible effects governed by both temporal and spatial factors that are inextricably contingent upon the exposure conditions. The perceived toxicological properties of any chemical are dependent on the route, dose, and duration of the exposure, and as such, gene expression patterns are also subject to these variables. Correct interpretation of DNA microarray data for the assessment of the toxicological properties of chemicals will require that temporal and spatial gene expression profiles be accounted for. These considerations are further compounded in ecotoxicological studies, during which altered gene expression patterns induced from exposure to an anthropogenic substance must be discernible over and above the complex effects that phenotypic, genotypic, and environmental variables have on gene expression. To this end, the greatest utility of DNA microarrays in the field of ecotoxicology may be in predicting the toxicological modes of action of anthropogenic substances on host physiology, particularly in non-model organisms. Predictable and accurate assessment of the impacts of a chemical substance in ecotoxicology will require that classical toxicological endpoints be used to validate any effects predicted based on gene expression profiling. Validated expression profiling may subsequently find utility in ecotoxicological-based computer simulation models, such as the Biotic Ligand Model (BLM), in which gene expression information may be integrated with geochemical, pharmacokinetic, and physiological data to accurately assess and predict toxicity of metals to aquatic organisms.

Analysis of altered genomic expression profiles in the senescent and diseased myocardium using cDNA microarrays

Cardiac function deteriorates with aging or disease. Short term, any changes in heart function may be beneficial, but long term the alterations are often detrimental. At a molecular level, functional adaptations involve quantitative and qualitative changes in gene expression. Analysis of all the RNA transcripts present in a cell's population (transcriptome) offers unprecedented opportunities to map these transitions. Microarrays (chips), capable of evaluating thousands of transcripts in one assay, are ideal for transcriptome analyses. Gene expression profiling provides information about the dynamics of total genome expression in response to environmental changes and may point to candidate genes responsible for the cascade of events that result in disease or are a consequence of aging. The aim of this review is to describe how comparisons of cellular transcriptomes by cDNA array based techniques provide information about the dynamics of total gene expression, and how the results can be applied to the study of cardiovascular disease and aging.

Gene expression profiles in a transgenic animal model of fragile X syndrome

Fragile X syndrome is the most common inherited form of mental retardation. Although this syndrome originates from the absence of the RNA-binding protein FMRP, the molecular mechanisms underlying the cognitive deficits are unknown. The expression pattern of 6789 genes was studied in the brains of wild-type and FMR1 knockout mice, a fragile X syndrome animal model that has been associated with cognitive deficits. Differential expression of more than two-fold was observed for the brain mRNA levels of 73 genes. Differential expression of nine of these genes was confirmed by real-time quantitative reverse transcription-polymerase chain reaction and by in situ hybridization. In addition to corroborating the microarray data, the in situ hybridization analysis showed distinct spatial distribution patterns of microtubule-associated protein 2 and amyloid beta precursor protein. A number of differentially expressed genes associated with the fragile X syndrome phenotype have been previously involved in other memory or cognitive disorders.

A common reference for cDNA microarray hybridizations

Comparisons of expression levels across different cDNA microarray experiments are easier when a common reference is co-hybridized to every microarray. Often this reference consists of one experimental control sample, a pool of cell lines or a mix of all samples to be analyzed. We have developed an alternative common reference consisting of a mix of the products that are spotted on the array. Pooling part of the cDNA PCR products before they are printed and their subsequent amplification towards either sense or antisense cRNA provides an excellent common reference. Our results show that this reference yields a reproducible hybridization signal in 99.5% of the cDNA probes spotted on the array. Accordingly, a ratio can be calculated for every spot, and expression levels across different hybridizations can be compared. In dye-swap experiments this reference shows no significant ratio differences, with 95% of the spots within an interval of +/-0.2-fold change. The described method can be used in hybridizations with both amplified and non-amplified targets, is time saving and provides a constant batch of common reference that lasts for thousands of hybridizations.

Expression profiling of primary non-small cell lung cancer for target identification

Using a panel of cDNA microarrays comprising 47 650 transcript elements, we have carried out a dual-channel analysis of gene expression in 39 resected primary human non-small cell lung tumours versus normal lung tissue. Whilst approximately 11 000 elements were scored as differentially expressed at least twofold in at least one sample, 96 transcripts were scored as over-represented fourfold or more in at least seven out of 39 tumours and 30 sequences 16-fold in at least two out of 39 tumours, including 24 transcripts in common. Transcripts (178) were found under-represented fourfold in at least seven out of 39 tumours, 31 of which are under-represented 16-fold in at least two out of 39 lesions. The relative expression levels of representative genes from these lists were analysed by comparative multiplex RT-PCR and found to be broadly consistent with the microarray data. Two dramatically over-represented genes, previously designated as potential tumour suppressors in breast (maspin) and lung and breast (S100A2) cancers, were analysed more extensively and demonstrate the effectiveness of this approach in identifying potential lung cancer diagnostic or therapeutic targets. Whilst it has been reported that S100A2 is downregulated in NSCLC at an early stage, our microarray, cmRT-PCR, Western and immunohistochemistry data indicate that it is strongly expressed in the majority of tumours.

Expression profiling with oligonucleotide arrays: technologies and applications for neurobiology

DNA microarrays have been used in applications ranging from the assignment of gene function to analytical uses in prognostics. However, the detection sensitivity, cross hybridization, and reproducibility of these arrays can affect experimental design and data interpretation. Moreover, several technologies are available for fabrication of oligonucleotide microarrays. We review these technologies and performance attributes and, with data sets generated from human brain RNA, present statistical tools and methods to analyze data quality and to mine and visualize the data. Our data show high reproducibility and should allow an investigator to discern biological and regional variability from differential expression. Although we have used brain RNA as a model system to illustrate some of these points, the oligonucleotide arrays and methods employed in this study can be used with cell lines, tissue sections, blood, and other fluids. To further demonstrate this point, we provide data generated from total RNA sample sizes of 200 ng.

Altered expression of novel genes in the cerebral cortex following experimental brain injury

Damage to the cerebral cortex results in neurological impairments such as motor, attention, memory and executive dysfunctions. To examine the molecular mechanisms contributing to these deficits, mRNA expression was profiled using high-density cDNA microarray hybridization after experimental cortical impact injury in mice. The mRNA levels at 2 h, 6 h, 24 h, 3 days and 14 days after injury were compared with those of control animals. This revealed 86 annotated genes and 24 expression sequence tags (ESTs) as being differentially expressed with a 1.5-fold or greater change. Quantitative real-time PCR analysis was used to independently verify these results for selected genes. Seven functional classes of genes were found to be altered following injury, including transcription factors, signal transduction genes and inflammatory proteins. While a few of these genes have been previously reported to be differentially regulated following injury, the most of the genes have not been previously implicated in traumatic brain injury (TBI) pathophysiology. For example, consistent with previous reports, the transcription factor c-jun and the neurotrophic factor bdnf mRNA levels were altered as a result of TBI. Among the novel genes, the mRNA levels for the high mobility group protein 1 (hmg-1), the regulator of G-protein signaling 2 (rgs-2), the transforming growth factor beta inducible early growth response (tieg), the inhibitor of DNA binding 3 (id3), and the heterogeneous nuclear ribonucleoprotein H (hnrnp h) were changed following injury. The functional significance of these genes in neurite outgrowth, neuronal regeneration, and plasticity following injury are discussed.

Biomic study of human myeloid leukemia cells differentiation to macrophages using DNA array, proteomic, and bioinformatic analytical methods

A biomic approach by integrating three independent methods, DNA microarray, proteomics and bioinformatics, is used to study the differentiation of human myeloid leukemia cell line HL-60 into macrophages when induced by 12-O-tetradecanoyl-phorbol-13-acetate (TPA). Analysis of gene expression changes at the RNA level using cDNA against an array of 6033 human genes showed that 5950 (98.6%) of the genes were expressed in the HL-60 cells. A total of 624 genes (10.5%) were found to be regulated during HL-60 cell differentiation. Most of these genes have not been previously associated with HL-60 cells and include genes encoded for secreted proteins as well as genes involved in cell adhesion, signaling transduction, and metabolism. Protein analysis using two-dimensional gel electrophoresis showed a total of 682 distinct protein spots; 136 spots (19.9%) exhibited quantitative changes between HL-60 control and macrophages. These differentially expressed proteins were identified by mass spectrometry. We developed a bioinformatics program, the Bulk Gene Search System (BGSS, http://www.sinica.edu.tw:8900/perl/genequery.pl) to search for the functions of genes and proteins identified by cDNA microarrays and proteomics. The identified regulated proteins and genes were classified into seven groups according to subcellular locations and functions. This powerful holistic biomic approach using cDNA microarray, proteomics coupled to bioinformatics can provide in-depth information on the impact and importance of the regulated genes and proteins for HL-60 differentiation.

Defining signal thresholds in DNA microarrays: exemplary application for invasive cancer

BACKGROUND

Genome-wide or application-targeted microarrays containing a subset of genes of interest have become widely used as a research tool with the prospect of diagnostic application. Intrinsic variability of microarray measurements poses a major problem in defining signal thresholds for absent/present or differentially expressed genes. Most strategies have used fold-change threshold values, but variability at low signal intensities may invalidate this approach and it does not provide information about false-positives and false negatives.

RESULTS

We introduce a method to filter false-positives and false-negatives from DNA microarray experiments. This is achieved by evaluating a set of positive and negative controls by receiver operating characteristic (ROC) analysis. As an advantage of this approach, users may define thresholds on the basis of sensitivity and specificity considerations. The area under the ROC curve allows quality control of microarray hybridizations. This method has been applied to custom made microarrays developed for the analysis of invasive melanoma derived tumor cells. It demonstrated that ROC analysis yields a threshold with reduced missclassified genes in microarray experiments.

CONCLUSIONS

Provided that a set of appropriate positive and negative controls is included on the microarray, ROC analysis obviates the inherent problem of arbitrarily selecting threshold levels in microarray experiments. The proposed method is applicable to both custom made and commercially available DNA microarrays and will help to improve the reliability of predictions from DNA microarray experiments.

Analysis of repeatability in spotted cDNA microarrays

We report a strategy for analysis of data quality in cDNA microarrays based on the repeatability of repeatedly spotted clones. We describe how repeatability can be used to control data quality by developing adaptive filtering criteria for microarray data containing clones spotted in multiple spots. We have applied the method on five publicly available cDNA microarray data sets and one previously unpublished data set from our own laboratory. The results demonstrate the feasibility of the approach as a foundation for data filtering, and indicate a high degree of variation in data quality, both across the data sets and between arrays within data sets.

Transcriptional response of Pasteurella multocida to nutrient limitation

Bacteria often encounter environments where nutrient availability is limited, and they must adapt accordingly. To identify Pasteurella multocida genes that are differentially expressed during nutrient limitation, we utilized whole-genome microarrays to compare levels of gene expression during growth in rich and minimal media. Our analysis showed that the levels of expression of a total of 669 genes, representing approximately one-third of the genome, were detectably altered over the course of the experiment. A large number (n = 439) of genes, including those involved in energy metabolism, transport, protein synthesis, and binding, were expressed at higher levels in rich medium, suggesting that, upon exposure to a rich environment, P. multocida immediately begins to turn on many energy-intensive biosynthetic pathways or, conversely, turns these genes off when it is exposed to a nutrient-deficient environment. Genes with increased expression in minimal medium (n = 230) included those encoding amino acid biosynthesis and transport systems, outer membrane proteins, and heat shock proteins. Importantly, our analysis also identified a large number (n = 164) of genes with unknown functions whose expression was altered during nutrient limitation. Overall, the results of our study show that a wide repertoire of genes, many of which have yet to be functionally classified, undergo transcriptional regulation in P. multocida in response to growth in minimal medium and provide a strong foundation to investigate the transcriptional response of this multispecies pathogen to growth in a nutrient-limited environment.

Microarray optimizations: increasing spot accuracy and automated identification of true microarray signals

In this paper, fluorescent microarray images and various analysis techniques are described to improve the microarray data acquisition processes. Signal intensities produced by rarely expressed genes are initially correctly detected, but they are often lost in corrections for background, log or ratio. Our analyses indicate that a simple correlation between the mean and median signal intensities may be the best way to eliminate inaccurate microarray signals. Unlike traditional quality control methods, the low intensity signals are retained and inaccurate signals are eliminated in this mean and median correlation. With larger amounts of microarray data being generated, it becomes increasingly more difficult to analyze data on a visual basis. Our method allows for the automatic quantitative determination of accurate and reliable signals, which can then be used for normalization. We found that a mean to median correlation of 85% or higher not only retains more data than current methods, but the retained data is more accurate than traditional thresholds or common spot flagging algorithms. We have also found that by using pin microtapping and microvibrations, we can control spot quality independent from initial PCR volume.

A highly reproducible, linear, and automated sample preparation method for DNA microarrays

DNA microarrays are powerful tools to detect changes in transcript abundance in multiple samples in parallel. However, detection of differential transcript levels requires a reproducible sample (target) preparation method in addition to a high-performance microarray. Therefore, we optimized a target-preparation method that converts the poly(A)(+) RNA fraction of total RNA into complementary DNA, then generates biotin-labeled complementary RNA from the cDNA. We measured the efficiency of incorporation of biotin-containing nucleotides by an enzymatic digestion, followed by resolution via analytical high-performance liquid chromatography (HPLC). When the target was hybridized to a sensitive and reproducible microarray platform, low coefficients of variation in both hybridization intensities and differential expression ratios across target preparations were observed. Nearly identical hybridization intensities and expression ratios are observed regardless of whether poly(A)(+)-enriched RNA or total RNA is used as the starting material. We show the ability to discern biological and production variability through the use of different lots of commercial samples as visualized by hierarchical clustering. Automation of the target-preparation procedure shows equivalence to the manual procedure, reproducible yields of target, and low variability as measured by hybridization to microarrays. Most importantly, RNA mixing experiments show a linear and quantitative amplification in probe hybridization signals for >6000 genes across the entire signal range.

Functional genomics in neuropsychiatric disorders and in neuropharmacology

The rapidly accumulating amount of information concerning gene and protein expression patterns produced by functional genomics, proteomics and bioinformatics is presently providing new targets for drug development. Furthermore, the analysis of gene expression in cells and tissues affected by a disease may reveal the underlying metabolic pathways and cellular processes affected. Finally, changes in gene expression may be used in either diagnostics or the monitoring of drug responses. This review focuses on advances in the use of functional genomics in neurological and neuropsychiatric diseases and neuropsychopharmacology. Although the number of published studies in this field is still limited, it already appears that this strategy may become a fruitful means in the analysis of the aetiology of neuropsychiatric disorders and the search for novel neuropharmacological drugs.

Accuracy and calibration of commercial oligonucleotide and custom cDNA microarrays

We compared the accuracy of microarray measurements obtained with oligonucleotide arrays (GeneChip, Affymetrix) with a laboratory-developed cDNA array by assaying test RNA samples from an experiment using a paradigm known to regulate many genes measured on both arrays. We selected 47 genes represented on both arrays, including both known regulated and unregulated transcripts, and established reference relative expression measurements for these genes in the test RNA samples using quantitative reverse transcriptase real-time PCR (QRTPCR) assays. The validity of the reproducible (average coefficient of variation = 11.8%) QRTPCR measurements were established through application of a new mathematical model. The performance of both array platforms in identifying regulated and non-regulated genes was identical. With either platform, 16 of 17 definitely regulated genes were correctly identified, and no definitely unregulated transcript was falsely identified as regulated. Accuracy of the fold-change measurements obtained with each platform was assessed by determining measurement bias. Both platforms consistently underestimate the relative changes in mRNA expression between experimental and control samples. The bias observed with cDNA arrays was predictable for fold-changes <250-fold by QRTPCR and could be corrected by the calibration function F(c) = F(a(cDNA))(q), where F(a(cDNA)) is the microarray-determined fold-change comparing experimental with control samples, q is the correction factor and F(c) is the calibrated value. The bias observed with the commercial oligonucleotide arrays was less predictable and calibration was unfeasible. Following calibration, fold-change measurements generated by custom cDNA arrays were more accurate than those obtained by commercial oligonucleotide arrays. Our study demonstrates systematic bias of microarray measurements and identifies a calibration function that improves the accuracy of cDNA array data.

Analysis of gene expression profile induced by hepatocyte nuclear factor 4alpha in hepatoma cells using an oligonucleotide microarray

Hepatocyte nuclear factor 4alpha (HNF-4alpha), a liver-specific transcription factor, plays a significant role in many liver-specific functions, including lipid, glucose, drug, and ammonia metabolism, and also in embryonal liver development. However, its functions and regulation are not yet clearly understood. In this study, we constructed an adenovirus vector carrying rat HNF-4alpha cDNA and transfected the adenovirus to human hepatoma cells, HuH-7, to enforce expression of the exogenous HNF-4alpha gene. We analyzed HNF-4alpha-induced genes using cDNA microarray technology, which included over 9000 genes. As a result, 62 genes showed a greater than 2.0-fold change in expression level after the viral transfection. Fifty-six genes were consistently induced by HNF-4alpha overexpression, and six genes were repressed. To assess HNF-4alpha function, we attempted to classify the genes, which had been classified by their encoding protein functions in a previous report. We could classify 45 genes. The rest of the HNF-4alpha-sensitive genes were unclassified (4 genes) or not identified (13 genes). Among the classified genes, almost half of the induced genes (26 of 40) were related to metabolism genes and particularly to lipid metabolism-related genes. This cDNA microarray analysis showed that HNF-4alpha is one of the central liver metabolism regulators.

An assessment of Motorola CodeLink microarray performance for gene expression profiling applications

DNA microarrays enable users to obtain information on differences in transcript abundance on a massively parallel scale. Recently, however, data analyses have revealed potential pitfalls related to image acquisition, variability and misclassifications in replicate measurements, cross-hybridization and sensitivity limitations. We have generated a series of analytical tools to address the manufacturing, detection and data analysis components of a microarray experiment. Together, we have used these tools to optimize performance in an expression profiling study. We demonstrate three significant advantages of the Motorola CodeLink platform: sensitivity of one copy per cell, coefficients of variation of 10% in the hybridization signals across slides and across target preparations, and specificity in distinguishing highly homologous sequences. Slides where oligonucleotide probes are spotted in 6-fold redundancy were used to demonstrate the effect of replication on data quality. Lastly, the differential expression ratios obtained with the CodeLink expression platform were validated against those obtained with quantitative reverse transcription-PCR assays for 54 genes.

Improved procedures to mine data obtained from spotted cDNA arrays

We studied six types of errors that affect the experimental results obtained with the spotted cDNA technology, proposing a new experimental strategy and a four-step algorithm to improve data accuracy. In an experiment analyzed with this method, mRNA extracted from neuroblastoma (N2A) cells and a clone transfected with the neuronal gap junction protein Cx36 were hybridized on 10 chips, each spotted with 2512 known mouse cDNAs. We found 53 upregulated and 23 downregulated genes with expression ratios exceeding 1.5-fold. By contrast, the newly introduced standard gene expression score, which considers the normal variability of gene expression in the reference cells, revealed that Cx36 transfection (p < 0.05) upregulated 161 genes and downregulated 61 genes. These results demonstrate the necessity to correct the raw data obtained from cDNA microarrays for systematic errors and indicate that use of the standard expression score significantly extends the identification of gene expression changes following experimental intervention.

A novel sensitive microarray approach for differential screening using probes labelled with two different radioelements

We have developed a novel microarray approach for differential screening using probes labelled with two different radioelements. The complementary DNAs from the reverse transcription of mRNAs from two different biological samples were labelled with radioelements of significantly different energies (3H and 35S or 33P). Radioactive images corresponding to the expressed genes were acquired with a MicroImager, a real time, high resolution digital autoradiography system. An algorithm was used to process the data such that the initially acquired radioactive image was filtered into two subimages, each representative of the hybridisation result specific for one probe. The simultaneous screening of gene expression in two different biological samples requires <100 ng mRNA without any amplification. In such conditions, the technique is sensitive enough to directly quantify the amount of mRNA even when present in small amounts: 10(7) molecules in the probe as assessed with an added control sequence and 2 x 10(5) molecules with an endogenous tyrosine hydroxylase mRNA. This novel technique of double radioactive labelling on a microarray is thus suitable for the comparison of gene expression in two different biological samples available in only small quantities. Consequently, it has great potential for various biological fields, such as neuroscience.

Within the fold: assessing differential expression measures and reproducibility in microarray assays

BACKGROUND

'Fold-change' cutoffs have been widely used in microarray assays to identify genes that are differentially expressed between query and reference samples. More accurate measures of differential expression and effective data-normalization strategies are required to identify high-confidence sets of genes with biologically meaningful changes in transcription. Further, the analysis of a large number of expression profiles is facilitated by a common reference sample, the construction of which must be carefully addressed.

RESULTS

We carried out a series of 'self-self' hybridizations in which aliquots of the same RNA sample were labeled separately with Cy3 and Cy5 fluorescent dyes and co-hybridized to the same microarray. From this, we can analyze the intensity-dependent behavior of microarray data, define a statistically significant measure of differential expression that exploits the structure of the fluorescent signals, and measure the inherent reproducibility of the technique. We also devised a simple procedure for identifying and eliminating low-quality data for replicates within and between slides. We examine the properties required of a universal reference RNA sample and show how pooling a small number of samples with a diverse representation of expressed genes can outperform more complex mixtures as a reference sample.

CONCLUSION

Analysis of cell-line samples can identify systematic structure in measured gene-expression levels. A general procedure for analyzing cDNA microarray data is proposed and validated. We show that pooled reference samples should be based not only on the expression of individual genes in each cell line but also on the expression levels of genes within cell lines.

An efficient binding chemistry for glass polynucleotide microarrays

A variety of methods have been described for making synthetic polynucleotide microarrays. These include in situ synthesis directly on the array surface, for example, by photolithography or ink-jet printing technologies, and the application of presynthesized polynucleotides that are derivatized with various nucleophiles or electrophiles. In the latter case, a variety of surface chemistries have been developed, and several are available commercially. These chemistries must be compatible with nanoliter-scale volumes of polynucleotide reagents, which contact the array over a small portion of their surface. We reasoned that a three-dimensional polymer coating could potentially offer greater surface contact and higher binding efficiency. Here we describe a polyethylenimine-based coating chemistry that provides exceptional binding and hybridization characteristics. In our preferred process, size-fractionated polyethylenimine polymers are cross-linked onto an aminopropylsilanated glass surface in the presence of cyanuric chloride. The resulting three-dimensional coating binds polynucleotides through a mixture of covalent and noncovalent interactions as evidenced by comparisons between 5'-aminoalkyl modified and unmodified polynucleotides. Binding and hybridization comparisons are presented including analogous two-dimensional electrophilic and electrostatic chemistries.

Statistical evaluation of differential expression on cDNA nylon arrays with replicated experiments

In this paper we focus on the detection of differentially expressed genes according to changes in hybridization signals using statistical tests. These tests were applied to 14 208 zebrafish cDNA clones that were immobilized on a nylon support and hybridized with radioactively labeled target mRNA from wild-type and lithium-treated zebrafish embryos. The methods were evaluated with respect to 16 control clones that correspond to eight different genes which are known to be involved in dorso-ventral axis specification. Moreover, 4608 Arabidopsis thaliana clones on the same array were used to judge statistical significance of expression changes and to control the false positive rates of the test decisions. Utilizing this special array design we show that differential expression of a high proportion of cDNA clones (15/16) and the respective genes (7/8) were identified, with a false positive error of <5% using the constant control data. Furthermore, we investigated the influence of the number of repetitions of experiments on the accuracy of the procedures with experimental and simulated data. Our results suggest that the detection of differential expression with repeated hybridization experiments is an accurate and sensitive way of identifying even small expression changes (1:1.5) of a large number of genes in parallel.

New molecular phenotypes in the dst mutants of Arabidopsis revealed by DNA microarray analysis

In this study, DNA microarray analysis was used to expand our understanding of the dst1 mutant of Arabidopsis. The dst (downstream) mutants were isolated originally as specifically increasing the steady state level and the half-life of DST-containing transcripts. As such, txhey offer a unique opportunity to study rapid sequence-specific mRNA decay pathways in eukaryotes. These mutants show a threefold to fourfold increase in mRNA abundance for two transgenes and an endogenous gene, all containing DST elements, when examined by RNA gel blot analysis; however, they show no visible aberrant phenotype. Here, we use DNA microarrays to identify genes with altered expression levels in dst1 compared with the parental plants. In addition to verifying the increase in the transgene mRNA levels, which were used to isolate these mutants, we were able to identify new genes with altered mRNA abundance in dst1. RNA gel blot analysis confirmed the microarray data for all genes tested and also was used to catalog the first molecular differences in gene expression between the dst1 and dst2 mutants. These differences revealed previously unknown molecular phenotypes for the dst mutants that will be helpful in future analyses. Cluster analysis of genes altered in dst1 revealed new coexpression patterns that prompt new hypotheses regarding the nature of the dst1 mutation and a possible role of the DST-mediated mRNA decay pathway in plants.

New molecular phenotypes in the dst mutants of Arabidopsis revealed by DNA microarray analysis

In this study, DNA microarray analysis was used to expand our understanding of the dst1 mutant of Arabidopsis. The dst (downstream) mutants were isolated originally as specifically increasing the steady state level and the half-life of DST-containing transcripts. As such, txhey offer a unique opportunity to study rapid sequence-specific mRNA decay pathways in eukaryotes. These mutants show a threefold to fourfold increase in mRNA abundance for two transgenes and an endogenous gene, all containing DST elements, when examined by RNA gel blot analysis; however, they show no visible aberrant phenotype. Here, we use DNA microarrays to identify genes with altered expression levels in dst1 compared with the parental plants. In addition to verifying the increase in the transgene mRNA levels, which were used to isolate these mutants, we were able to identify new genes with altered mRNA abundance in dst1. RNA gel blot analysis confirmed the microarray data for all genes tested and also was used to catalog the first molecular differences in gene expression between the dst1 and dst2 mutants. These differences revealed previously unknown molecular phenotypes for the dst mutants that will be helpful in future analyses. Cluster analysis of genes altered in dst1 revealed new coexpression patterns that prompt new hypotheses regarding the nature of the dst1 mutation and a possible role of the DST-mediated mRNA decay pathway in plants.

A gene expression profile of Alzheimer's disease

Postmortem analysis of brains of patients with Alzheimer's disease (AD) has led to diverse theories about the causes of the pathology, suggesting that this complex disease involves multiple physiological changes. In an effort to better understand the variety and integration of these changes, we generated a gene expression profile for AD brain. Comparing affected and unaffected brain regions in nine controls and six AD cases, we showed that 118 of the 7050 sequences on a broadly representative cDNA microarray were differentially expressed in the amygdala and cingulate cortex, two regions affected early in the disease. The identity of these genes suggests the most prominent upregulated physiological correlates of pathology involve chronic inflammation, cell adhesion, cell proliferation, and protein synthesis (31 upregulated genes). Conversely, downregulated correlates of pathology involve signal transduction, energy metabolism, stress response, synaptic vesicle synthesis and function, calcium binding, and cytoskeleton (87 downregulated genes). The results support several separate theories of the causes of AD pathology, as well as add to the list of genes associated with AD. In addition, approximately 10 genes of unknown function were found to correlate with the pathology.