affy--analysis of Affymetrix GeneChip data at the probe level

Improving reliability and performance of DNA microarrays

A great many platforms and versions of the microarray technology, with different characteristics and applications, have been developed. This review will describe some key issues in reliability and performance with the two most commonly used platforms for gene expression analysis, in situ-synthesized oligonucleotide microarrays or GeneChips and spotted microarrays. Some recent advances and new applications within the field will be mentioned briefly.

Distinct developmental defense activations in barley embryos identified by transcriptome profiling

Proper embryo development is crucial for normal growth and development of barley. Numerous related aspects of this process--for example how the embryo establishes and sustains disease resistance for extended periods during dormancy--remain largely unknown. Here we report the results of microarray analyses of >22,000 genes, which together with measurements of jasmonic acid and salicylic acid during embryo development provide new information on the initiation in the developing barley embryo of at least two distinct types of developmental defense activation (DDA). Early DDA is characterized by the up-regulation of a specific set of genes around 20 days after flowering, including co-regulation of those for encoding 9-lipoxygenase and several oxylipin-generating enzymes, possibly leading to the formation of alpha-ketols. The same developmental phase includes an up-regulation of several defense genes, and indications of co-regulation of those for enzymes involved in the generation of phenylpropanoid phytoalexins. Late DDA is initiated prior to grain desiccation, around 37 days after flowering, with up-regulation of several genes encoding proteins with roles in antioxidant responses as well as a simultaneous up-regulation of several PR genes is notable. Throughout barley embryo development, there are no indications of an increased biosynthesis of either jasmonic acid or salicylic acid. Collectively, the results help explain how the proposed DDA enables protection of the developing barley embryo and grain for purposes of disease resistance.

Development of Arabidopsis whole-genome microarrays and their application to the discovery of binding sites for the TGA2 transcription factor in salicylic acid-treated plants

We have developed two long-oligonucleotide microarrays for the analysis of genome features in Arabidopsis thaliana, in particular for the high-throughput identification of transcription factor-binding sites. The first platform contains 190,000 probes representing the 2-kb regions upstream of all annotated genes at a density of seven probes per promoter. The second platform is divided into three chips, each of over 390,000 features, and represents the entire Arabidopsis genome at a density of one probe per 90 bases. Protein-DNA complexes resulting from the formaldehyde fixation of leaves of plants 2 h after exposure to 1 mm salicylic acid (SA) were immunoprecipitated using antibodies against the TGA2 transcription factor. After reversal of the cross-links and amplification, the resulting ChIP sample was hybridized to both platforms. High signal ratios of the ChIP sample versus raw chromatin for clusters of neighboring probes provided evidence for 51 putative binding sites for TGA2, including the only previously confirmed site in the promoter of PR-1 (At2g14610). Enrichment of several regions was confirmed by quantitative real-time PCR. Motif search revealed that the palindromic octamer TGACGTCA was found in 55% of the enriched regions. Interestingly, 15 of the putative binding sites for TGA2 lie outside the presumptive promoter regions. The effect of the 2-h SA treatment on gene expression was measured using Affymetrix ATH1 arrays, and SA-induced genes were found to be significantly over-represented among genes neighboring putative TGA2-binding sites.

Systemic transcriptional analysis in survivor and non-survivor septic shock patients: A preliminary study

The second phase of septic shock is characterized by an anti-inflammatory state and patients rapidly develop features consistent with immunosuppression. The mechanisms sustaining this disease step are far from being well understood. The objective of the present study was to perform a genome-wide survey of mRNA expression in septic shock patients in order to investigate the bases of sepsis-induced immunoparalysis. We used Affymetrix HG-U133A oligonucleotide arrays to compare systemic gene expression patterns of survivors and non-survivors after the first 24 h of the syndrome (n = 38 patients). Supervised analysis identified a set of 28 genes efficiently discriminating non-survivors from survivors with a sensitivity of 100% and a specificity of 86%. The microarray findings were confirmed by qRT-PCR and the ability of the selected probe sets to function as a classifier of outcome was verified with an independent set of additional microarray analyses. Noteworthy, of gene overexpressed in survivors, many are known to participate in innate immunity (cytokine, chemokine receptor, effectors of the Toll-receptor pathways). It supports the hypothesis that restoration of inflammatory/immune functions is a key step for survival after septic shock. The consistency of our results into the context of sepsis-induced immunoparalysis tends to indicate that blood transcriptional profiling is a valuable approach not only for patients stratification but also to identity new genes possibly involved in sepsis pathophysiology.

Next station in microarray data analysis: GEPAS

The Gene Expression Profile Analysis Suite (GEPAS) has been running for more than four years. During this time it has evolved to keep pace with the new interests and trends in the still changing world of microarray data analysis. GEPAS has been designed to provide an intuitive although powerful web-based interface that offers diverse analysis options from the early step of preprocessing (normalization of Affymetrix and two-colour microarray experiments and other preprocessing options), to the final step of the functional annotation of the experiment (using Gene Ontology, pathways, PubMed abstracts etc.), and include different possibilities for clustering, gene selection, class prediction and array-comparative genomic hybridization management. GEPAS is extensively used by researchers of many countries and its records indicate an average usage rate of 400 experiments per day. The web-based pipeline for microarray gene expression data, GEPAS, is available at http://www.gepas.org.

Gene expression associated with compatible viral diseases in grapevine cultivars

Viral diseases affect grapevine cultures without inducing any resistance response. Thus, these plants develop systemic diseases and are chronically infected. Molecular events associated with viral compatible infections responsible for disease establishment and symptoms development are poorly understood. In this study, we surveyed viral infection in grapevines at a transcriptional level. Gene expression in the Vitis vinifera red wine cultivars Carménère and Cabernet-Sauvignon naturally infected with GLRaV-3 were evaluated using a genome-wide expression profiling with the Vitis vinifera GeneChip from Affymetrix. We describe numerous genes that are induced or repressed in viral infected grapevines leaves. Changes in gene expression involved a wide spectrum of biological functions, including processes of translation and protein targeting, metabolism, transport, and cell defense. Considering cellular localization, the membrane and endomembrane systems appeared with the highest number of induced genes, while chloroplastic genes were mostly repressed. As most induced genes associated with the membranous system are involved in transport, the possible effect of virus in this process is discussed. Responses of both cultivars are analyzed and the results are compared with published data from other species. This is the first study of global gene profiling in grapevine in response to viral infections using DNA microarray.

Gene expression analysis of mouse chromosome substitution strains

An analysis of transcriptional variation in the liver using a panel of B.A chromosome substitution strains identified 4209 transcripts that are differentially expressed relative to the C57BL/6J background and 1010 transcripts that are differentially expressed between C57BL/6J and A/J strains. A subset of these strains (substituting Chromosomes 1, 6, and 15) was used to identify 386 additional differentially expressed transcripts in the kidney. Approximately 15% of differentially expressed transcripts are located on the substituted chromosome. These cis-QTL are codirectionally expressed with the donor strain A/J. By comparison, trans-regulated loci comprise 85% of differentially expressed transcripts, often show opposite direction of change compared with A/J, and can be regulated by multiple chromosome substitutions. Gene expression differences in this study provide evidence for transgressive segregation: Only 438 of 4209 QTL in liver were inside the parental range. By combining QTL data with known biological functions, we were able to identify physiologic pathways altered in multiple strains. In many cases the same pathways were altered by multiple distinct chromosome substitutions. Taken together, these results suggest that widespread epistatic background effects may result in complex and overlapping transcriptional relationships among different chromosome substitution strains. Transcriptional profiling of chromosome substitution strains reveals a complex genetic architecture of transcriptional regulation.

Genome-wide expression analysis of lipopolysaccharide-induced mastitis in a mouse model

To better understand the acute host response to Escherichia coli mastitis, we analyzed gene expression patterns of approximately 23,000 transcripts 4 h after an intramammary infusion of lipopolysaccharide (LPS) in a mouse model. A total of 489 genes were significantly affected, of which 391 were induced and 98 were repressed. Gene ontology analysis demonstrated that most of the induced genes were associated with the innate immune response, apoptosis, and cell proliferation. Substantial induction of the chemokines CXCL1, CXCL2, and S100A8; the acute-phase protein SAA3; and the LPS binding protein CD14 were confirmed by Northern blot analysis. A subsequent time course experiment revealed CXCL1 induction prior to that of CD14 and SAA3. Mammary epithelial cell cultures also showed marked expression of these factors in response to LPS. The expression of immune-related genes in mammary epithelial cells indicates the importance of this cell type in initiating the inflammatory responses. Repressed genes include several carbohydrate and fatty acid metabolic enzymes and potassium transporters, which may contribute to milk composition changes during mastitis. Therefore, the overall transcription profile, in conjunction with gene ontology analysis, provides a detailed picture of the molecular mechanisms underlying the complex biological processes that occur during LPS-induced mastitis.

Hybridization interactions between probesets in short oligo microarrays lead to spurious correlations

Background

Microarrays measure the binding of nucleotide sequences to a set of sequence specific probes. This information is combined with annotation specifying the relationship between probes and targets and used to make inferences about transcript- and, ultimately, gene expression. In some situations, a probe is capable of hybridizing to more than one transcript, in others, multiple probes can target a single sequence. These 'multiply targeted' probes can result in non-independence between measured expression levels.

Results

An analysis of these relationships for Affymetrix arrays considered both the extent and influence of exact matches between probe and transcript sequences. For the popular HGU133A array, approximately half of the probesets were found to interact in this way. Both real and simulated expression datasets were used to examine how these effects influenced the expression signal. It was found not only to lead to increased signal strength for the affected probesets, but the major effect is to significantly increase their correlation, even in situations when only a single probe from a probeset was involved. By building a network of probe-probeset-transcript relationships, it is possible to identify families of interacting probesets. More than 10% of the families contain members annotated to different genes or even different Unigene clusters. Within a family, a mixture of genuine biological and artefactual correlations can occur.

Conclusion

Multiple targeting is not only prevalent, but also significant. The ability of probesets to hybridize to more than one gene product can lead to false positives when analysing gene expression. Comprehensive annotation describing multiple targeting is required when interpreting array data.

Transcriptomic footprints disclose specificity of reactive oxygen species signaling in Arabidopsis

Reactive oxygen species (ROS) are key players in the regulation of plant development, stress responses, and programmed cell death. Previous studies indicated that depending on the type of ROS (hydrogen peroxide, superoxide, or singlet oxygen) or its subcellular production site (plastidic, cytosolic, peroxisomal, or apoplastic), a different physiological, biochemical, and molecular response is provoked. We used transcriptome data generated from ROS-related microarray experiments to assess the specificity of ROS-driven transcript expression. Data sets obtained by exogenous application of oxidative stress-causing agents (methyl viologen, Alternaria alternata toxin, 3-aminotriazole, and ozone) and from a mutant (fluorescent) and transgenic plants, in which the activity of an individual antioxidant enzyme was perturbed (catalase, cytosolic ascorbate peroxidase, and copper/zinc superoxide dismutase), were compared. In total, the abundance of nearly 26,000 transcripts of Arabidopsis (Arabidopsis thaliana) was monitored in response to different ROS. Overall, 8,056, 5,312, and 3,925 transcripts showed at least a 3-, 4-, or 5-fold change in expression, respectively. In addition to marker transcripts that were specifically regulated by hydrogen peroxide, superoxide, or singlet oxygen, several transcripts were identified as general oxidative stress response markers because their steady-state levels were at least 5-fold elevated in most experiments. We also assessed the expression characteristics of all annotated transcription factors and inferred new candidate regulatory transcripts that could be responsible for orchestrating the specific transcriptomic signatures triggered by different ROS. Our analysis provides a framework that will assist future efforts to address the impact of ROS signals within environmental stress conditions and elucidate the molecular mechanisms of the oxidative stress response in plants.

p63 regulates an adhesion programme and cell survival in epithelial cells

p63 is critical for epithelial development yet little is known about the transcriptional programmes it regulates. By characterising transcriptional changes and cellular effects following modulation of p63 expression, we have defined a vital role for p63 in cellular adhesion. Knockdown of p63 expression caused downregulation of cell adhesion-associated genes, cell detachment and anoikis in mammary epithelial cells and keratinocytes. Conversely, overexpression of the TAp63gamma or deltaNp63alpha isoforms of p63 upregulated cell adhesion molecules, increased cellular adhesion and conferred resistance to anoikis. Apoptosis induced by loss of p63 was rescued by signalling downstream of beta4 integrin. Our results implicate p63 as a key regulator of cellular adhesion and survival in basal cells of the mammary gland and other stratified epithelial tissues.

High-density haplotyping with microarray-based expression and single feature polymorphism markers in Arabidopsis

Expression microarrays hybridized with RNA can simultaneously provide both phenotypic (gene expression) and genotypic (marker) data. We developed two types of genetic markers from Affymetrix GeneChip expression data to generate detailed haplotypes for 148 recombinant inbred lines (RILs) derived from Arabidopsis thaliana accessions Bayreuth and Shahdara. Gene expression markers (GEMs) are based on differences in transcript levels that exhibit bimodal distributions in segregating progeny, while single feature polymorphism (SFP) markers rely on differences in hybridization to individual oligonucleotide probes. Unlike SFPs, GEMs can be derived from any type of DNA-based expression microarray. Our method identifies SFPs independent of a gene's expression level. Alleles for each GEM and SFP marker were ascertained with GeneChip data from parental accessions as well as RILs; a novel algorithm for allele determination using RIL distributions capitalized on the high level of genetic replication per locus. GEMs and SFP markers provided robust markers in 187 and 968 genes, respectively, which allowed estimation of gene order consistent with that predicted from the Col-0 genomic sequence. Using microarrays on a population to simultaneously measure gene expression variation and obtain genotypic data for a linkage map will facilitate expression QTL analyses without the need for separate genotyping. We have demonstrated that gene expression measurements from microarrays can be leveraged to identify polymorphisms across the genome and can be efficiently developed into genetic markers that are verifiable in a large segregating RIL population. Both marker types also offer opportunities for massively parallel mapping in unsequenced and less studied species.

Correction of scaling mismatches in oligonucleotide microarray data

BACKGROUND

Gene expression microarray data is notoriously subject to high signal variability. Moreover, unavoidable variation in the concentration of transcripts applied to microarrays may result in poor scaling of the summarized data which can hamper analytical interpretations. This is especially relevant in a systems biology context, where systematic biases in the signals of particular genes can have severe effects on subsequent analyses. Conventionally it would be necessary to replace the mismatched arrays, but individual time points cannot be rerun and inserted because of experimental variability. It would therefore be necessary to repeat the whole time series experiment, which is both impractical and expensive.

RESULTS

We explain how scaling mismatches occur in data summarized by the popular MAS5 (GCOS; Affymetrix) algorithm, and propose a simple recursive algorithm to correct them. Its principle is to identify a set of constant genes and to use this set to rescale the microarray signals. We study the properties of the algorithm using artificially generated data and apply it to experimental data. We show that the set of constant genes it generates can be used to rescale data from other experiments, provided that the underlying system is similar to the original. We also demonstrate, using a simple example, that the method can successfully correct existing imbalances in the data.

CONCLUSION

The set of constant genes obtained for a given experiment can be applied to other experiments, provided the systems studied are sufficiently similar. This type of rescaling is especially relevant in systems biology applications using microarray data.

Differential Expression Profiling of the Hepatic Proteome in a Rat Model of Dioxin Resistance

One characteristic feature of acute 2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD) toxicity is dramatic interspecies and interstrain variability in sensitivity. This complicates dioxin risk assessment for humans. However, this variability also provides a means of characterizing mechanisms of dioxin toxicity. Long-Evans (Turku/AB) rats are orders of magnitude more susceptible to TCDD lethality than Han/Wistar (Kuopio) rats, and this difference constitutes a very useful model for identifying mechanisms of dioxin toxicity. We adopted a proteomic approach to identify the differential effects of TCDD exposure on liver protein expression in Han/Wistar rats as compared with Long-Evans rats. This allows determination of which, if any, protein markers are indicative of differences in dioxin susceptibility and/or responsible for conferring resistance. Differential protein expression in total liver protein was assessed using two-dimensional gel electrophoresis, computerized gel image analysis, in-gel digestion, and mass spectrometry. We observed significant changes in the abundance of several proteins, which fall into three general classes: (i) TCDD-independent and exclusively strain-specific (e.g. isoforms of the protein-disulfide isomerase A3, regucalcin, and agmatine ureohydrolase); (ii) strain-independent and only dependent on TCDD exposure (e.g. aldehyde dehydrogenase 3A1 and rat selenium-binding protein 2); (iii) dependent on both TCDD exposure and strain (e.g. oxidative stress-related proteins, apoptosis-inducing factor, and MAWD-binding protein). By integrating transcriptomic (microarray) data and genomic data (computational search of regulatory elements), we found that protein expression levels were mainly controlled at the level of transcription. These results reveal, for the first time, a subset of hepatic proteins that are differentially regulated in response to TCDD in a strain-specific manner. Some of these differential responses may play a role in establishing the major differences in TCDD response between these two strains of rats. As such, our work is expected to lead to new insights into the mechanism of TCDD toxicity and resistance.

Transcriptional profiling of mesenchymal stromal cells from young and old rats in response to Dexamethasone

Background

Marrow-derived stromal cells (MSCs) maintain the capability of self-renewal and differentiation into multiple lineages in adult life. Age-related changes are recognized by a decline in the stemness potential that result in reduced regeneration potential of the skeleton. To explore the molecular events that underline skeletal physiology during aging we catalogued the profile of gene expression in ex vivo cultured MSCs derived from 3 and 15 month old rats. The ex vivo cultured cells were analyzed following challenge with or without Dexamethasone (Dex). RNA retrieved from these cells was analyzed using Affymetrix Gene Chips to compare the effect of Dex on gene expression in both age groups.

Results

The molecular mechanisms that underline skeletal senescence were studied by gene expression analysis of RNA harvested from MSCs. The analysis resulted in complex profiles of gene expression of various differentiation pathways. We revealed changes of lineage-specific gene expression; in general the pattern of expression included repression of proliferation and induction of differentiation. The functional analysis of genes clustered were related to major pathways; an increase in bone remodeling, osteogenesis and muscle formation, coupled with a decrease in adipogenesis. We demonstrated a Dex-related decrease in immune response and in genes that regulate bone resorption and an increase in osteoblastic differentiation. Myogenic-related genes and genes that regulate cell cycle were induced by Dex. While Dex repressed genes related to adipogenesis and catabolism, this decrease was complementary to an increase in expression of genes related to osteogenesis.

Conclusion

This study summarizes the genes expressed in the ex vivo cultured mesenchymal cells and their response to Dex. Functional clustering highlights the complexity of gene expression in MSCs and will advance the understanding of major pathways that trigger the natural changes underlining physiological aging. The high throughput analysis shed light on the anabolic effect of Dex and the relationship between osteogenesis, myogenesis and adipogenesis in the bone marrow cells.

Accurate and precise transcriptional profiles from 50 pg of total RNA or 100 flow-sorted primary lymphocytes

We have developed a total RNA amplification and labeling strategy for use with Affymetrix GeneChips. Our protocol, which we denote BIIB, employs two rounds of linear T7 amplification followed by Klenow labeling to generate a biotinylated cDNA. In benchmarking studies using a titration of mouse universal total RNA, BIIB outperformed commercially available kits in terms of sensitivity, accuracy, and amplified target length, while providing equivalent results for technical reproducibility. BIIB maintained 50 and 44% present calls from 100 and 50 pg of total RNA, respectively. Inter- and intrasample precision studies indicated that BIIB produces an unbiased and complete expression profile within a range of 5 ng to 50 pg of starting total RNA. From a panel of spiked exogenous transcripts, we established the BIIB linear detection limit to be 20 absolute copies. Additionally, we demonstrate that BIIB is sensitive enough to detect the stochastic events inherent in a highly diluted sample. Using RNA isolated from whole tissues, we further validated BIIB accuracy and precision by comparison of 224 expression ratios generated by quantitative real-time PCR. The utility of our method is ultimately illustrated by the detection of biologically expected trends in a T cell/B cell titration of 100 primary cells flow sorted from a healthy mouse spleen.

Assessment of the relationship between pre-chip and post-chip quality measures for Affymetrix GeneChip expression data

BACKGROUND

Gene expression microarray experiments are expensive to conduct and guidelines for acceptable quality control at intermediate steps before and after the samples are hybridised to chips are vague. We conducted an experiment hybridising RNA from human brain to 117 U133A Affymetrix GeneChips and used these data to explore the relationship between 4 pre-chip variables and 22 post-chip outcomes and quality control measures.

RESULTS

We found that the pre-chip variables were significantly correlated with each other but that this correlation was strongest between measures of RNA quality and cRNA yield. Post-mortem interval was negatively correlated with these variables. Four principal components, reflecting array outliers, array adjustment, hybridisation noise and RNA integrity, explain about 75% of the total post-chip measure variability. Two significant canonical correlations existed between the pre-chip and post-chip variables, derived from MAS 5.0, dChip and the Bioconductor packages affy and affyPLM. The strongest (CANCOR 0.838, p < 0.0001) correlated RNA integrity and yield with post chip quality control (QC) measures indexing 3'/5' RNA ratios, bias or scaling of the chip and scaling of the variability of the signal across the chip. Post-mortem interval was relatively unimportant. We also found that the RNA integrity number (RIN) could be moderately well predicted by post-chip measures B_ACTIN35, GAPDH35 and SF.

CONCLUSION

We have found that the post-chip variables having the strongest association with quantities measurable before hybridisation are those reflecting RNA integrity. Other aspects of quality, such as noise measures (reflecting the execution of the assay) or measures reflecting data quality (outlier status and array adjustment variables) are not well predicted by the variables we were able to determine ahead of time. There could be other variables measurable pre-hybridisation which may be better associated with expression data quality measures. Uncovering such connections could create savings on costly microarray experiments by eliminating poor samples before hybridisation.

ModuleFinder and CoReg: alternative tools for linking gene expression modules with promoter sequences motifs to uncover gene regulation mechanisms in plants

BACKGROUND

Uncovering the key sequence elements in gene promoters that regulate the expression of plant genomes is a huge task that will require a series of complementary methods for prediction, substantial innovations in experimental validation and a much greater understanding of the role of combinatorial control in the regulation of plant gene expression.

RESULTS

To add to this larger process and to provide alternatives to existing prediction methods, we have developed several tools in the statistical package R. ModuleFinder identifies sets of genes and treatments that we have found to form valuable sets for analysis of the mechanisms underlying gene co-expression. CoReg then links the hierarchical clustering of these co-expressed sets with frequency tables of promoter elements. These promoter elements can be drawn from known elements or all possible combinations of nucleotides in an element of various lengths. These sets of promoter elements represent putative cis-acting regulatory elements common to sets of co-expressed genes and can be prioritised for experimental testing. We have used these new tools to analyze the response of transcripts for nuclear genes encoding mitochondrial proteins in Arabidopsis to a range of chemical stresses. ModuleFinder provided a subset of co-expressed gene modules that are more logically related to biological functions than did subsets derived from traditional hierarchical clustering techniques. Importantly ModuleFinder linked responses in transcripts for electron transport chain components, carbon metabolism enzymes and solute transporter proteins. CoReg identified several promoter motifs that helped to explain the patterns of expression observed.

CONCLUSION

ModuleFinder identifies sets of genes and treatments that form useful sets for analysis of the mechanisms behind co-expression. CoReg links the clustering tree of expression-based relationships in these sets with frequency tables of promoter elements. These sets of promoter elements represent putative cis-acting regulatory elements for sets of genes, and can then be tested experimentally. We consider these tools, both built on an open source software product to provide valuable, alternative tools for the prioritisation of promoter elements for experimental analysis.

Specific age-related signatures in Drosophila body parts transcriptome

BACKGROUND

During the last two decades progress in the genetics of aging in invertebrate models such as C. elegans and D. melanogaster has clearly demonstrated the existence of regulatory pathways that control the rate of aging in these organisms, such as the insulin-like pathway, the Jun kinase pathway and the Sir2 deacetylase pathway. Moreover, it was rapidly shown that some of these pathways are conserved from yeast to humans. In parallel to genetic studies, genomic expression approaches have given us significant information on the gene expression modifications that occur during aging either in wild type or long-lived mutant animals. But most of the genomic studies of invertebrate models have been performed so far on whole animals, while several recent studies in mammals have shown that the effects of aging are tissue specific.

RESULTS

We used oligonucleotide microarrays to address the specificities of transcriptional responses in aging Drosophila in head, thorax or whole body. These fly parts are enriched in transcripts that represent different and complementary sets of genes. We present evidence for both specific and common transcriptional responses during the aging process in these tissues. About half of the genes described as downregulated with age are linked to reproduction and enriched in gonads. Greater downregulation of mitochondrial genes, activation of the JNK pathway and upregulation of proteasome subunits in the thorax of aged flies all suggest that muscle may be particularly sensitive to aging. Simultaneous age-related impairment of synaptic transmission gene expression is observed in fly heads. In addition, a detailed comparison with other microarray data indicates that in aged flies there are significant deviations from the canonical responses to oxidative stress and immune stress.

CONCLUSION

Our data demonstrates the advantages and value of regionalized and comparative analysis of gene expression in aging animals. Adding to the age-regulated genes already identified in whole animal studies, it provides lists of new regionalized genes to be studied for their functional role in the aging process. This work also emphasizes the need for such experiments to reveal in greater detail the consequences of the transcriptional modifications induced by aging regulatory pathways.

Inference of gene regulatory networks and compound mode of action from time course gene expression profiles

MOTIVATION

Time series expression experiments are an increasingly popular method for studying a wide range of biological systems. Here we developed an algorithm that can infer the local network of gene-gene interactions surrounding a gene of interest. This is achieved by a perturbation of the gene of interest and subsequently measuring the gene expression profiles at multiple time points. We applied this algorithm to computer simulated data and to experimental data on a nine gene network in Escherichia coli.

RESULTS

In this paper we show that it is possible to recover the gene regulatory network from a time series data of gene expression following a perturbation to the cell. We show this both on simulated data and on a nine gene subnetwork part of the DNA-damage response pathway (SOS pathway) in the bacteria E. coli.

CONTACT

dibernardo@tigem.it SUPLEMENTARY INFORMATION: Supplementary data are available at http://dibernado.tigem.it

SScore: an R package for detecting differential gene expression without gene expression summaries

SUMMARY

SScore is an R package that facilitates the comparison of gene expression between Affymetrix GeneChips using the S-score algorithm. The S-score algorithm uses probe level data directly to assess differences in gene expression, without requiring a preliminary separate step of probe set expression summary estimation. Therefore, the algorithm avoids introduction of error associated with the expression summary estimation process and has been demonstrated to improve the accuracy of identifying differentially expressed genes. The S-score produces accurate results even when few or no replicates are available.

AVAILABILITY

The R package SScore is available from Bioconductor at http://www.bioconductor.org

Empirical validation of the S-Score algorithm in the analysis of gene expression data

Background

Current methods of analyzing Affymetrix GeneChip^® microarray data require the estimation of probe set expression summaries, followed by application of statistical tests to determine which genes are differentially expressed. The S-Score algorithm described by Zhang and colleagues is an alternative method that allows tests of hypotheses directly from probe level data. It is based on an error model in which the detected signal is proportional to the probe pair signal for highly expressed genes, but approaches a background level (rather than 0) for genes with low levels of expression. This model is used to calculate relative change in probe pair intensities that converts probe signals into multiple measurements with equalized errors, which are summed over a probe set to form the S-Score. Assuming no expression differences between chips, the S-Score follows a standard normal distribution, allowing direct tests of hypotheses to be made. Using spike-in and dilution datasets, we validated the S-Score method against comparisons of gene expression utilizing the more recently developed methods RMA, dChip, and MAS5.

Results

The S-score showed excellent sensitivity and specificity in detecting low-level gene expression changes. Rank ordering of S-Score values more accurately reflected known fold-change values compared to other algorithms.

Conclusion

The S-score method, utilizing probe level data directly, offers significant advantages over comparisons using only probe set expression summaries.

Control of the C. albicans cell wall damage response by transcriptional regulator Cas5

The fungal cell wall is vital for growth, development, and interaction of cells with their environment. The response to cell wall damage is well understood from studies in the budding yeast Saccharomyces cerevisiae, where numerous cell wall integrity (CWI) genes are activated by transcription factor ScRlm1. Prior evidence suggests the hypothesis that both response and regulation may be conserved in the major fungal pathogen Candida albicans. We have tested this hypothesis by using a new C. albicans genetic resource: we have screened mutants defective in putative transcription factor genes for sensitivity to the cell wall biosynthesis inhibitor caspofungin. We find that the zinc finger protein CaCas5, which lacks a unique ortholog in S. cerevisiae, governs expression of many CWI genes. CaRlm1 has a modest role in this response. The transcriptional coactivator CaAda2 is also required for expression of many CaCas5-dependent genes, as expected if CaCas5 recruits CaAda2 to activate target gene transcription. Many caspofungin-induced C. albicans genes specify endoplasmic reticulum and secretion functions. Such genes are not induced in S. cerevisiae, but promote its growth in caspofungin. We have used a new resource to identify a key C. albicans transcriptional regulator of CWI genes and antifungal sensitivity. Our gene expression findings indicate that both divergent and conserved response genes may have significant functional roles. Our strategy may be broadly useful for identification of pathogen-specific regulatory pathways and critical response genes.

For microbial pathogens, the cell wall is critical for interaction with both host and environment. The major fungal pathogen, Candida albicans, has a cell wall that resembles that of the model yeast Saccharomyces cerevisiae, and much of what is known about C. albicans cell wall biogenesis and repair comes via extrapolation from S. cerevisiae. Here, Bruno and colleagues inquired directly into the mechanisms that C. albicans uses to respond to disruption of cell wall biogenesis by the antifungal drug caspofungin, using a genetic strategy newly developed for C. albicans. They found that the response itself has many similarities to that of S. cerevisiae, but the regulatory circuitry is distinct: the major C. albicans regulatory gene has no clear counterpart among S. cerevisiae genes. Their findings provide a new example of a unique C. albicans regulatory function and one that may prove useful in identifying new drugs and in understanding possible resistance mechanisms.

An improved single-cell cDNA amplification method for efficient high-density oligonucleotide microarray analysis

A systems-level understanding of a small but essential population of cells in development or adulthood (e.g. somatic stem cells) requires accurate quantitative monitoring of genome-wide gene expression, ideally from single cells. We report here a strategy to globally amplify mRNAs from single cells for highly quantitative high-density oligonucleotide microarray analysis that combines a small number of directional PCR cycles with subsequent linear amplification. Using this strategy, both the representation of gene expression profiles and reproducibility between individual experiments are unambiguously improved from the original method, along with high coverage and accuracy. The immediate application of this method to single cells in the undifferentiated inner cell masses of mouse blastocysts at embryonic day (E) 3.5 revealed the presence of two populations of cells, one with primitive endoderm (PE) expression and the other with pluripotent epiblast-like gene expression. The genes expressed differentially between these two populations were well preserved in morphologically differentiated PE and epiblast in the embryos one day later (E4.5), demonstrating that the method successfully detects subtle but essential differences in gene expression at the single-cell level among seemingly homogeneous cell populations. This study provides a strategy to analyze biophysical events in medicine as well as in neural, stem cell and developmental biology, where small numbers of distinctive or diseased cells play critical roles.

Targeting of GFP to newborn rods by Nrl promoter and temporal expression profiling of flow-sorted photoreceptors

The Maf-family transcription factor Nrl is a key regulator of photoreceptor differentiation in mammals. Ablation of the Nrl gene in mice leads to functional cones at the expense of rods. We show that a 2.5-kb Nrl promoter segment directs the expression of enhanced GFP specifically to rod photoreceptors and the pineal gland of transgenic mice. GFP is detected shortly after terminal cell division, corresponding to the timing of rod genesis revealed by birthdating studies. In Nrl-/- retinas, the GFP+ photoreceptors express S-opsin, consistent with the transformation of rod precursors into cones. We report the gene profiles of freshly isolated flow-sorted GFP+ photoreceptors from wild-type and Nrl-/- retinas at five distinct developmental stages. Our results provide a framework for establishing gene regulatory networks that lead to mature functional photoreceptors from postmitotic precursors. Differentially expressed rod and cone genes are excellent candidates for retinopathies.

Tests for differential gene expression using weights in oligonucleotide microarray experiments

Background

Microarray data analysts commonly filter out genes based on a number of ad hoc criteria prior to any high-level statistical analysis. Such ad hoc approaches could lead to conflicting conclusions with no clear guidance as to which method is most likely to be reproducible. Furthermore, the number of tests performed with concomitant inflation in type I error also plagues the statistical analysis of microarray data, since the number of tested quantities in a study significantly affects the family-wise error rate. It would, therefore, be very useful to develop and adopt strategies that allow quantification of the quality of each probeset, to filter out or give little credence to low-quality or unexpressed probesets, and to incorporate these strategies into gene selection within a multiple testing framework.

Results

We have proposed a unified scheme for filtering and gene selection. For Affymetrix gene expression microarrays, we developed new methods for measuring the reliability of a particular probeset in a single array, and we used these to develop measures for a set of arrays. These measures are then used as weights in standard t-statistic calculations, and are incorporated into the multiple testing procedures. We demonstrated the advantages of our methods using simulated data, publicly available spiked-in data as well as data comparing normal muscle to muscle from patients with Duchenne muscular dystrophy (DMD), in which a set of truly differentially expressed genes is known.

Conclusion

Our quality measures provide convenient ways to search for individual genes of high quality. The quality weighting strategies we proposed for testing differential gene expression have demonstrable improvement on the traditional filtering methods, the standard t-statistic and a regularized t-statistic in Affymetrix data analysis.

Nonrandom divergence of gene expression following gene and genome duplications in the flowering plant Arabidopsis thaliana

Analysis of expression data of duplicated genes in Arabidopsis thaliana shows that the mode of duplication, the time since duplication and the function of the duplicated genes play a role in the divergence of their expression.

Background

Genome analyses have revealed that gene duplication in plants is rampant. Furthermore, many of the duplicated genes seem to have been created through ancient genome-wide duplication events. Recently, we have shown that gene loss is strikingly different for large- and small-scale duplication events and highly biased towards the functional class to which a gene belongs. Here, we study the expression divergence of genes that were created during large- and small-scale gene duplication events by means of microarray data and investigate both the influence of the origin (mode of duplication) and the function of the duplicated genes on expression divergence.

Results

Duplicates that have been created by large-scale duplication events and that can still be found in duplicated segments have expression patterns that are more correlated than those that were created by small-scale duplications or those that no longer lie in duplicated segments. Moreover, the former tend to have highly redundant or overlapping expression patterns and are mostly expressed in the same tissues, while the latter show asymmetric divergence. In addition, a strong bias in divergence of gene expression was observed towards gene function and the biological process genes are involved in.

Conclusion

By using microarray expression data for Arabidopsis thaliana, we show that the mode of duplication, the function of the genes involved, and the time since duplication play important roles in the divergence of gene expression and, therefore, in the functional divergence of genes after duplication.

BAMarraytrade mark: Java software for Bayesian analysis of variance for microarray data

Background

DNA microarrays open up a new horizon for studying the genetic determinants of disease. The high throughput nature of these arrays creates an enormous wealth of information, but also poses a challenge to data analysis. Inferential problems become even more pronounced as experimental designs used to collect data become more complex. An important example is multigroup data collected over different experimental groups, such as data collected from distinct stages of a disease process. We have developed a method specifically addressing these issues termed Bayesian ANOVA for microarrays (BAM). The BAM approach uses a special inferential regularization known as spike-and-slab shrinkage that provides an optimal balance between total false detections and total false non-detections. This translates into more reproducible differential calls. Spike and slab shrinkage is a form of regularization achieved by using information across all genes and groups simultaneously.

Results

BAMarray™ is a graphically oriented Java-based software package that implements the BAM method for detecting differentially expressing genes in multigroup microarray experiments (up to 256 experimental groups can be analyzed). Drop-down menus allow the user to easily select between different models and to choose various run options. BAMarray™ can also be operated in a fully automated mode with preselected run options. Tuning parameters have been preset at theoretically optimal values freeing the user from such specifications. BAMarray™ provides estimates for gene differential effects and automatically estimates data adaptive, optimal cutoff values for classifying genes into biological patterns of differential activity across experimental groups. A graphical suite is a core feature of the product and includes diagnostic plots for assessing model assumptions and interactive plots that enable tracking of prespecified gene lists to study such things as biological pathway perturbations. The user can zoom in and lasso genes of interest that can then be saved for downstream analyses.

Conclusion

BAMarray™ is user friendly platform independent software that effectively and efficiently implements the BAM methodology. Classifying patterns of differential activity is greatly facilitated by a data adaptive cutoff rule and a graphical suite. BAMarray™ is licensed software freely available to academic institutions. More information can be found at .

Evaluation of various housekeeping genes for their applicability for normalization of mRNA expression in dioxin-treated rats

Quantitative reverse transcription-polymerase chain reaction (qRT-PCR) is an extremely sensitive, convenient and rapid method to measure mRNA levels in cells and tissues, and is gaining popularity in toxicology. To correct for sample-to-sample variation, normalization of the expression data is required. The conventional way to perform normalization is to select a reference gene whose expression is believed to remain stable across all experimental conditions, then relate the concentrations of gene(s) of interest to those of this housekeeping gene. Since recent evidence shows that some housekeeping genes are actually not as refractory to experimental manipulations as previously thought, we validated a large number (18) of commonly used housekeeping genes for acute toxicity studies of 2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD), an extremely potent environmental toxin known to regulate a wide variety of genes. Microarray and qRT-PCR analyses coherently demonstrated that about 50% of the housekeeping genes examined were responsive to TCDD in rat liver with the magnitudes of change up to nearly 10-fold. Extension of the study to spleen and hypothalamus verified that phosphoglycerate kinase 1 (Pgk1) and glyceraldehyde-3-phosphate dehydrogenase (GAPDH) retained their basal expression levels in all experimental settings, although body weight loss-generated repression may mask a slight induction of GAPDH by TCDD in liver. These findings show that normalization genes for qRT-PCR must be carefully validated in advance, especially if the study involves a potent modifier of gene expression.

Regional and cellular gene expression changes in human Huntington's disease brain

Huntington's disease (HD) pathology is well understood at a histological level but a comprehensive molecular analysis of the effect of the disease in the human brain has not previously been available. To elucidate the molecular phenotype of HD on a genome-wide scale, we compared mRNA profiles from 44 human HD brains with those from 36 unaffected controls using microarray analysis. Four brain regions were analyzed: caudate nucleus, cerebellum, prefrontal association cortex [Brodmann's area 9 (BA9)] and motor cortex [Brodmann's area 4 (BA4)]. The greatest number and magnitude of differentially expressed mRNAs were detected in the caudate nucleus, followed by motor cortex, then cerebellum. Thus, the molecular phenotype of HD generally parallels established neuropathology. Surprisingly, no mRNA changes were detected in prefrontal association cortex, thereby revealing subtleties of pathology not previously disclosed by histological methods. To establish that the observed changes were not simply the result of cell loss, we examined mRNA levels in laser-capture microdissected neurons from Grade 1 HD caudate compared to control. These analyses confirmed changes in expression seen in tissue homogenates; we thus conclude that mRNA changes are not attributable to cell loss alone. These data from bona fide HD brains comprise an important reference for hypotheses related to HD and other neurodegenerative diseases.

affylmGUI: a graphical user interface for linear modeling of single channel microarray data

SUMMARY

affylmGUI is a graphical user interface (GUI) to an integrated workflow for Affymetrix microarray data. The user is able to proceed from raw data (CEL files) to QC and pre-processing, and eventually to analysis of differential expression using linear models with empirical Bayes smoothing. Output of the analysis (tables and figures) can be exported to an HTML report. The GUI provides user-friendly access to state-of-the-art methods embodied in the Bioconductor software repository.

AVAILABILITY

affylmGUI is an R package freely available from http://www.bioconductor.org. It requires R version 1.9.0 or later and tcl/tk 8.3 or later and has been successfully tested on Windows 2000, Windows XP, Linux (RedHat and Fedora distributions) and Mac OS/X with X11. Further documentation is available at http://bioinf.wehi.edu.au/affylmGUI CONTACT: keith@wehi.edu.au.

Exploration of global gene expression in human liver steatosis by high-density oligonucleotide microarray

Understanding the molecular mechanisms underlying fatty liver disease (FLD) in humans is of major importance. We used high-density oligonucleotide microarrays (22.3 K) to assess the mechanisms responsible for the development of human liver steatosis. We compared global gene expression in normal (n=9) and steatotic (n=9) livers without histological signs of inflammation or fibrosis. A total of 34 additional human samples including normal (n=11), steatosis (n=11), HCV-related steatosis (n=4) or steatohepatitis associated with alcohol consumption (n=4) or obesity (n=4) were used for immunohistochemistry or quantitative real-time PCR studies. With unsupervised classification (no gene selection), all steatotic liver samples clustered together. Using step-down maxT multiple testing procedure for controlling the Family-Wise Error-Rate at level 5%, 110 cDNAs (100 over- and 10 underexpressed) were found to be differentially expressed in steatotic and normal livers. Of them were genes involved in mitochondrial phosphorylative and oxidative metabolism. The mean ratio of mitochondrial DNA to nuclear DNA content was higher in liver steatosis compared to normal liver biopsies (1.12+/-0.14 vs 0.67+/-0.10; P=0.01). An increased expression of genes involved in inflammation (IL-1R family, TGFB) was also observed and confirmed by quantitative RT-PCR or immunochemistry. In steatohepatitis, an increase of the protein expression of mitochondrial antigens, IL-1R1, IGF2 and TGFB1 was also observed, interleukin 1 receptor being always strongly expressed in steatohepatitis linked to alcohol or obesity. In conclusion, mitochondrial alterations play a major role in the development of steatosis per se. Activation of inflammatory pathways is present at a very early stage of steatosis, even if no morphological sign of inflammation is observed.

Modeling gene expression networks using fuzzy logic

Gene regulatory networks model regulation in living organisms. Fuzzy logic can effectively model gene regulation and interaction to accurately reflect the underlying biology. A new multiscale fuzzy clustering method allows genes to interact between regulatory pathways and across different conditions at different levels of detail. Fuzzy cluster centers can be used to quickly discover causal relationships between groups of coregulated genes. Fuzzy measures weight expert knowledge and help quantify uncertainty about the functions of genes using annotations and the gene ontology database to confirm some of the interactions. The method is illustrated using gene expression data from an experiment on carbohydrate metabolism in the model plant Arabidopsis thaliana. Key gene regulatory relationships were evaluated using information from the gene ontology database. A new regulatory relationship concerning trehalose regulation of carbohydrate metabolism was also discovered in the extracted network.

Gene expression profile of B 16(F10) murine melanoma cells exposed to hypoxic conditions in vitro

Hypoxia is an important feature of tumor microenvironment, exerting far-reaching effects on cells and contributing to cancer progression. Previous studies have established substantial differences in hypoxia response between various cell lines. Investigating this phenomenon in melanoma cells contributes to a better understanding of cell lineage-specific hypoxia response and could point out novel hypoxia-regulated genes. We investigated transcriptional activity of B 16(F10) murine melanoma cells cultured for 24 h under hypoxic (nominal 1% O2, 15 samples including controls) and hypoxia-mimicking conditions (cobalt chloride, 100 or 200 microM, 6 samples including controls). Gene expression profiles were analyzed using MG-U74Av2 oligonucleotide microarrays. Data analysis revealed 2541 probesets (FDR <5%) for 1% oxygen experiment and 364 probesets (FDR <5%) for cobalt chloride, which showed differences in expression levels. Analysis of hypoxia-regulated genes (true hypoxia, 1% O2) by stringent Family-Wise Error Rate estimation indicated 454 significantly changed transcripts (p < 0.05). The most upregulated genes were Lgals3, Selenbpl, Nppb (more than ten-fold increase). We observed significant differences in expression levels of genes regulating glycolysis (Pfkp, Hk2, Aldo3, Eno2), apoptosis (Bnip3, Bnip31, Cdknla), transcription (Bhlhb2, Sap30, Atf3, Mxil), angiogenesis (Vegfa, Adm, Anxa2, Ctgf), adhesion (Pkp2, Itga4, Mcam), migration (Cnn2, Tmsb4x), and other processes. Both true hypoxia and hypoxia mimicry induced HIF-1-regulated genes. However, unsupervised analysis (Singular Value Decomposition) revealed distinct differences in gene expression between these two experimental conditions. Contrary to hypoxia, cobalt chloride caused suppression of gene expression rather than stimulation, especially concerning transcripts related to proliferation, immune response, DNA repair, and melanin biosynthesis.

Microarray expression technology: from start to finish

The recent introduction of new microarray expression technologies and the further development of established platforms ensure that the researcher is presented with a range of options for performing an experiment. Whilst this has opened up the possibilities for future applications, such as exon-specific arrays, increased sample throughput and ‘chromatin immunoprecipitation (ChIP) on chip’ experiments, the initial decision processes and experiment planning are made more difficult. This review will give an overview of the various technologies that are available to perform a microarray expression experiment, from the initial planning stages through to the final data analysis. Both practical aspects and data analysis options will be considered. The relative advantages and disadvantages will be discussed with insights provided for future directions of the technology.

Aryl hydrocarbon receptor regulates distinct dioxin-dependent and dioxin-independent gene batteries

Conventional biochemical and molecular techniques identified previously several genes whose expression is regulated by the aryl hydrocarbon receptor (AHR). We sought to map the complete spectrum of AHR-dependent genes in male adult liver using expression arrays to contrast mRNA profiles in Ahr-null mice (Ahr(-/-)) with those in mice with wild-type AHR (Ahr(+)(/)(+)). Transcript profiles were determined both in untreated mice and in mice treated 19 h earlier with 1000 microg/kg 2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD). Expression of 456 ProbeSets was significantly altered by TCDD in an AHR-dependent manner, including members of the classic AHRE-I gene battery, such as Cyp1a1, Cyp1a2, Cyp1b1, and Nqo1. In the absence of exogenous ligand, AHR status alone affected expression of 392 ProbeSets, suggesting that the AHR has multiple functions in normal physiology. In Ahr(-/-) mice, only 32 ProbeSets exhibited responses to TCDD, indicating that the AHR is required for virtually all transcriptional responses to dioxin exposure in liver. The flavin-containing monooxygenases, Fmo2 and Fmo3, considered previously to be uninducible, were highly induced by TCDD in an AHR-dependent manner. The estrogen receptor alpha as well as two estrogen-receptor-related genes (alpha and gamma) exhibit AHR-dependent expression, thereby extending cross-talk opportunities between the intensively studied AHR and estrogen receptor pathways. p53 binding sites are over-represented in genes down-regulated by TCDD, suggesting that TCDD inhibits p53 transcriptional activity. Overall, our study identifies a wide range of genes that depend on the AHR, either for constitutive expression or for response to TCDD.

Dynamic histone acetylation of late embryonic genes during seed germination

Histone acetylation is involved in the regulation of gene expression in plants and eukaryotes. Histone deacetylases (HDACs) are enzymes that catalyze the removal of acetyl groups from histones, which is associated with the repression of gene expression. To study the role of histone acetylation in the regulation of gene expression during seed germination, trichostatin A (TSA), a specific inhibitor of histone deacetylase, was used to treat imbibing Arabidopsis thaliana seeds. GeneChip arrays were used to show that TSA induces up-regulation of 45 genes and down-regulation of 27 genes during seed germination. Eight TSA-up-regulated genes were selected for further analysis - RAB18, RD29B, ATEM1, HSP70 and four late embryogenesis abundant protein genes (LEA). A gene expression time course shows that these eight genes are expressed at high levels in the dry seed and repressed upon seed imbibition at an exponential rate. In the presence of TSA, the onset of repression of the eight genes is not affected but the final level of repressed expression is elevated. Chromatin immunoprecipitation and HDAC assays show that there is a transient histone deacetylation event during seed germination at 1 day after imbibition, which serves as a key developmental signal that affects the repression of the eight genes.

Monoclonal B-cell hyperplasia and leukocyte imbalance precede development of B-cell malignancies in uracil-DNA glycosylase deficient mice

Ung-deficient mice have reduced class switch recombination, skewed somatic hypermutation, lymphatic hyperplasia and a 22-fold increased risk of developing B-cell lymphomas. We find that lymphomas are of follicular (FL) and diffuse large B-cell type (DLBCL). All FLs and 75% of the DLBCLs were monoclonal while 25% were biclonal. Monoclonality was also observed in hyperplasia, and could represent an early stage of lymphoma development. Lymphoid hyperplasia occurs very early in otherwise healthy Ung-deficient mice, observed as a significant increase of splenic B-cells. Furthermore, loss of Ung also causes a significant reduction of T-helper cells, and 50% of the young Ung(-/-) mice investigated have no detectable NK/NKT-cell population in their spleen. The immunological imbalance is confirmed in experiments with spleen cells where the production of the cytokines interferon gamma, interleukin 6 and interleukin 2 is clearly different in wild type and in Ung-deficient mice. This suggests that Ung-proteins, directly or indirectly, have important functions in the immune system, not only in the process of antibody maturation, but also for production and functions of immunologically important cell types. The immunological imbalances shown here in the Ung-deficient mice may be central in the development of lymphomas in a background of generalised lymphoid hyperplasia.

Increased expression of chemokines in the skin of chronic proliferative dermatitis mutant mice

Chemokines direct the migration of leukocytes to sites of inflammation and are potential targets for anti-inflammatory therapy. Chronic proliferative dermatitis (cpdm/cpdm) mutant mice develop a persistent eosinophilic dermatitis associated with increased T(H)2 cytokines in the skin. Expression patterns of chemokines in the skin of cpdm/cpdm mice were evaluated to define the mechanisms driving cutaneous infiltration by leukocytes. RNA isolated from the skin of mutant and littermate control mice revealed a significant increase in Ccl1 (TCA-3), Ccl2 (MCP-1), Ccl11 (eotaxin), Ccl17 (TARC), Cxcl10 (IP-10), and the chemokine receptor Ccr3. The concentration of CCL11 protein was increased two- to threefold in the skin of cpdm/cpdm mice by enzyme-linked immunosorbent assay. In vitro culture of primary dermal fibroblasts from cpdm/cpdm and control mice with tumor necrosis factor, IL-4, and IL-13 stimulation did not reveal differences in their ability to secrete CCL11, suggesting that the increased chemokine expression observed in the skin of cpdm/cpdm mice is most likely caused by the increased T(H)2 cytokines in the dermis of this mouse model. Treatment of cpdm/cpdm mice with CCL11-neutralizing polyclonal antibodies did not affect the number of eosinophils in the skin or the severity of the dermatitis. Neutralizing multiple chemokines or chemokine receptors may be necessary to decrease eosinophil accumulation. The cpdm/cpdm mutant mouse is a potentially useful model to determine the role of various chemokines in eosinophil accumulation in chronic inflammation.

Evolutionary regulation of the blind subterranean mole rat, Spalax, revealed by genome-wide gene expression

We applied genome-wide gene expression analysis to the evolutionary processes of adaptive speciation of the Israeli blind subterranean mole rats of the Spalax ehrenbergi superspecies. The four Israeli allospecies climatically and adaptively radiated into the cooler, mesic northern domain (N) and warmer, xeric southern domain (S). The kidney and brain mRNAs of two N and two S animals were examined through cross-species hybridizations with two types of Affymetrix arrays (mouse and rat) and muscle mRNA of six N and six S animals with spotted cDNA mouse arrays. The initial microarray analysis was hypothesis-free, i.e., conducted without reference to the origin of animals. Principal component analysis revealed that 20-30% of the expression signal variability could be explained by the differentiation of N-S species. Similar N-S effects were obtained for all tissues and types of arrays: two Affymetrix microarrays using probe oligomer signals and the spotted array. Likewise, ANOVA and t test statistics demonstrated significant N-S ecogeographic divergence and region-tissue specificity in gene expression. Analysis of differential gene expression between species corroborates previous results deduced by allozymes and DNA molecular polymorphisms. Functional categories show significant N-S ecologic putative adaptive divergent up-regulation of genes highlighting a higher metabolism in N, and potential adaptive brain activity and kidney urine cycle pathways in S. The present results confirm ecologic-genomic separation of blind mole rats into N and S. Gene expression regulation appears to be central to the evolution of blind mole rats.

Maximum significance clustering of oligonucleotide microarrays

MOTIVATION

Affymetrix high-density oligonucleotide microarrays measure the expression of DNA transcripts using probesets, i.e. multiple probes per transcript. Usually, these multiple measurements are transformed into a single probeset expression level before data analysis proceeds; any information on variability is lost. In this paper we demonstrate how individual probe measurements can be used in a statistic for differential expression. Furthermore, we show how this statistic can serve as a criterion for clustering microarrays.

RESULTS

A novel clustering algorithm using this maximum significance criterion is demonstrated to be more efficient with the measured data than competing techniques for dealing with repeated measurements, especially when the sample size is small.

New weakly expressed cell cycle-regulated genes in yeast

We present an approach combining bioinformatics prediction with experimental microarray validation to identify new cell cycle-regulated genes in Saccharomyces cerevisiae. We identify in the order of 100 new cell cycle-regulated genes and show by independent data that these genes in general tend to be more weakly expressed than the genes identified hitherto. Among the genes not previously suggested to be periodically expressed we find genes linked to DNA repair, cell size monitoring and transcriptional control, as well as a number of genes of unknown function. Several of the gene products are believed to be phosphorylated by Cdc28. For many of these new genes, homologues exist in Schizosaccharomyces pombe and Homo sapiens for which the expression also varies with cell cycle progression.

Enhanced tolerance to environmental stress in transgenic plants expressing the transcriptional coactivator multiprotein bridging factor 1c

Abiotic stresses cause extensive losses to agricultural production worldwide. Acclimation of plants to abiotic conditions such as drought, salinity, or heat is mediated by a complex network of transcription factors and other regulatory genes that control multiple defense enzymes, proteins, and pathways. Associated with the activity of different transcription factors are transcriptional coactivators that enhance their binding to the basal transcription machinery. Although the importance of stress-response transcription factors was demonstrated in transgenic plants, little is known about the function of transcriptional coactivators associated with abiotic stresses. Here, we report that constitutive expression of the stress-response transcriptional coactivator multiprotein bridging factor 1c (MBF1c) in Arabidopsis (Arabidopsis thaliana) enhances the tolerance of transgenic plants to bacterial infection, heat, and osmotic stress. Moreover, the enhanced tolerance of transgenic plants to osmotic and heat stress was maintained even when these two stresses were combined. The expression of MBF1c in transgenic plants augmented the accumulation of a number of defense transcripts in response to heat stress. Transcriptome profiling and inhibitor studies suggest that MBF1c expression enhances the tolerance of transgenic plants to heat and osmotic stress by partially activating, or perturbing, the ethylene-response signal transduction pathway. Present findings suggest that MBF1 proteins could be used to enhance the tolerance of plants to different abiotic stresses.

Genome-wide gene expression in response to parasitoid attack in Drosophila

BACKGROUND

Parasitoids are insect parasites whose larvae develop in the bodies of other insects. The main immune defense against parasitoids is encapsulation of the foreign body by blood cells, which subsequently often melanize. The capsule sequesters and kills the parasite. The molecular processes involved are still poorly understood, especially compared with insect humoral immunity.

RESULTS

We explored the transcriptional response to parasitoid attack in Drosophila larvae at nine time points following parasitism, hybridizing five biologic replicates per time point to whole-genome microarrays for both parasitized and control larvae. We found significantly different expression profiles for 159 probe sets (representing genes), and we classified them into 16 clusters based on patterns of co-expression. A series of functional annotations were nonrandomly associated with different clusters, including several involving immunity and related functions. We also identified nonrandom associations of transcription factor binding sites for three main regulators of innate immune responses (GATA/srp-like, NF-kappaB/Rel-like and Stat), as well as a novel putative binding site for an unknown transcription factor. The appearance or absence of candidate genes previously associated with insect immunity in our differentially expressed gene set was surveyed.

CONCLUSION

Most genes that exhibited altered expression following parasitoid attack differed from those induced during antimicrobial immune responses, and had not previously been associated with defense. Applying bioinformatic techniques contributed toward a description of the encapsulation response as an integrated system, identifying putative regulators of co-expressed and functionally related genes. Genome-wide studies such as ours are a powerful first approach to investigating novel genes involved in invertebrate immunity.

A comparison of match-only algorithms for the analysis of Plasmodium falciparum oligonucleotide arrays

This study is motivated by two data sets which employ a custom Plasmodium falciparum version of the Affymetrix GeneChip, containing only perfect match (PM) oligonucleotides. A PM-only chip cannot be analysed using the standard Affymetrix-supplied software. We compared the performance of three match-only algorithms on these data: the Match Only Integral Distribution (MOID) algorithm, Robust Multichip Analysis (RMA), and the Model Based Expression Index (MBEI). We validated the differential expression of several genes using quantitative reverse transcriptase-PCR. We also performed a comparison using two publicly available 'benchmarking' data sets: the Latin Square spike-in data set generated by Affymetrix, and the Gene Logic dilution series. Since we know what the true fold changes are in these special data sets, they are helpful for assessment of expression algorithms.

Altered cortical glutamatergic and GABAergic signal transmission with glial involvement in depression

Abnormalities in L-glutamic acid (glutamate) and GABA signal transmission have been postulated to play a role in depression, but little is known about the underlying molecular determinants and neural mechanisms. Microarray analysis of specific areas of cerebral cortex from individuals who had suffered from major depressive disorder demonstrated significant down-regulation of SLC1A2 and SLC1A3, two key members of the glutamate/neutral amino acid transporter protein family, SLC1. Similarly, expression of L-glutamate-ammonia ligase, the enzyme that converts glutamate to nontoxic glutamine was significantly decreased. Together, these changes could elevate levels of extracellular glutamate considerably, which is potentially neurotoxic and can affect the efficiency of glutamate signaling. The astroglial distribution of the two glutamate transporters and L-glutamate-ammonia ligase strongly links glia to the pathophysiology of depression and challenges the conventional notion that depression is solely a neuronal disorder. The same cortical areas displayed concomitant up-regulation of several glutamate and GABA(A) receptor subunits, of which GABA(A)alpha1 and GABA(A)beta3 showed selectivity for individuals who had died by suicide, indicating their potential utility as biomarkers of suicidality. These findings point to previously undiscovered molecular underpinnings of the pathophysiology of major depression and offer potentially new pharmacological targets for treating depression.

The zinc-finger protein Zat12 plays a central role in reactive oxygen and abiotic stress signaling in Arabidopsis

Plant acclimation to environmental stress is controlled by a complex network of regulatory genes that compose distinct stress-response regulons. In contrast to many signaling and regulatory genes that are stress specific, the zinc-finger protein Zat12 responds to a large number of biotic and abiotic stresses. Zat12 is thought to be involved in cold and oxidative stress signaling in Arabidopsis (Arabidopsis thaliana); however, its mode of action and regulation are largely unknown. Using a fusion between the Zat12 promoter and the reporter gene luciferase, we demonstrate that Zat12 expression is activated at the transcriptional level during different abiotic stresses and in response to a wound-induced systemic signal. Using Zat12 gain- and loss-of-function lines, we assign a function for Zat12 during oxidative, osmotic, salinity, high light, and heat stresses. Transcriptional profiling of Zat12-overexpressing plants and wild-type plants subjected to H(2)O(2) stress revealed that constitutive expression of Zat12 in Arabidopsis results in the enhanced expression of oxidative- and light stress-response transcripts. Under specific growth conditions, Zat12 may therefore regulate a collection of transcripts involved in the response of Arabidopsis to high light and oxidative stress. Our results suggest that Zat12 plays a central role in reactive oxygen and abiotic stress signaling in Arabidopsis.

Oligonucleotide arrays: information from replication and spatial structure

MOTIVATION

The introduction of oligonucleotide DNA arrays has resulted in much debate concerning appropriate models for the measurement of gene expression. By contrast, little account has been taken of the possibility of identifying the physical imperfections in the raw data.

RESULTS

This paper demonstrates that, with the use of replicates and an awareness of the spatial structure, deficiencies in the data can be identified, the possibility of their correction can be ascertained and correction can be effected (by use of local scaling) where possible. The procedures were motivated by data from replicates of Arabidopsis thaliana using the GeneChip ATH1-121501 microarray. Similar problems are illustrated for GeneChip Human Genome U133 arrays and for the newer and larger GeneChip Wheat Genome microarray.

AVAILABILITY

R code is freely available on request.

Conditional expression demonstrates the role of the homeodomain transcription factor Pdx1 in maintenance and regeneration of beta-cells in the adult pancreas

The homeodomain transcription factor Pdx1 is essential for pancreas development. To investigate the role of Pdx1 in the adult pancreas, we employed a mouse model in which transcription of Pdx1 could be reversibly repressed by administration of doxycycline. Repression of Pdx1 in adult mice impaired expression of insulin and glucagon, leading to diabetes within 14 days. Pdx1 repression was associated with increased cell proliferation predominantly in the exocrine pancreas and upregulation of genes implicated in pancreas regeneration. Following withdrawal of doxycycline and derepression of Pdx1, normoglycemia was restored within 28 days; during this period, Pdx1(+)/Ins(+) and Pdx(+)/Ins(-) cells were observed in association with the duct epithelia. These findings confirm that Pdx1 is required for beta-cell function in the adult pancreas and indicate that in the absence of Pdx1 expression, a regenerative program is initiated with the potential for Pdx1-dependent beta-cell neogenesis.

A global survey of gene regulation during cold acclimation in Arabidopsis thaliana

Many temperate plant species such as Arabidopsis thaliana are able to increase their freezing tolerance when exposed to low, nonfreezing temperatures in a process called cold acclimation. This process is accompanied by complex changes in gene expression. Previous studies have investigated these changes but have mainly focused on individual or small groups of genes. We present a comprehensive statistical analysis of the genome-wide changes of gene expression in response to 14 d of cold acclimation in Arabidopsis, and provide a large-scale validation of these data by comparing datasets obtained for the Affymetrix ATH1 Genechip and MWG 50-mer oligonucleotide whole-genome microarrays. We combine these datasets with existing published and publicly available data investigating Arabidopsis gene expression in response to low temperature. All data are integrated into a database detailing the cold responsiveness of 22,043 genes as a function of time of exposure at low temperature. We concentrate our functional analysis on global changes marking relevant pathways or functional groups of genes. These analyses provide a statistical basis for many previously reported changes, identify so far unreported changes, and show which processes predominate during different times of cold acclimation. This approach offers the fullest characterization of global changes in gene expression in response to low temperature available to date.

Freezing tolerance is an important determinant of geographical distribution of plant species, and freezing damage in crop plants leads to severe losses in agriculture. Many temperate plants increase their freezing tolerance during exposure to low, but nonfreezing temperatures, a process known as cold acclimation. Freezing tolerance and cold acclimation are complex, quantitative genetic traits. The number and functional roles of the responsible genes are not known for any plant species. Using the model plant Arabidopsis thaliana, which is moderately freezing tolerant and able to cold acclimate, the global regulation of gene expression during exposure to 4 °C for 14 d was analyzed by microarray hybridization. For validation of gene expression data, triplicate biological samples were hybridized to two different oligonucleotide arrays. Results from the two platforms showed good agreement, indicating the reliability of the measurements. The authors combined their data with all publicly available data on cold-regulated gene expression in A. thaliana to compile a database detailing the cold responsiveness of 22,043 genes as a function of exposure time. In addition, thorough statistical analysis was used to identify metabolic pathways and physiological processes that are predominantly involved in the plant cold-acclimation process.