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

RACE: Remote Analysis Computation for gene Expression data

The Remote Analysis Computation for gene Expression data (RACE) suite is a collection of bioinformatics web tools designed for the analysis of DNA microarray data. RACE performs probe-level data preprocessing, extensive quality checks, data visualization and data normalization for Affymetrix GeneChips. In addition, it offers differential expression analysis on normalized expression levels from any array platform. RACE estimates the false discovery rates of lists of potentially regulated genes and provides a Gene Ontology-term analysis tool for GeneChip data to support the biological interpretation and annotation of results. The analysis is fully automated but can be customized by flexible parameter settings. To offer a convenient starting point for subsequent analyses, and to provide maximum transparency, the R scripts used to generate the results can be downloaded along with the output files. RACE is freely available for use at http://race.unil.ch.

Genomic islands of speciation in Anopheles gambiae

The African malaria mosquito, Anopheles gambiae sensu stricto (A. gambiae), provides a unique opportunity to study the evolution of reproductive isolation because it is divided into two sympatric, partially isolated subtaxa known as M form and S form. With the annotated genome of this species now available, high-throughput techniques can be applied to locate and characterize the genomic regions contributing to reproductive isolation. In order to quantify patterns of differentiation within A. gambiae, we hybridized population samples of genomic DNA from each form to Affymetrix GeneChip microarrays. We found that three regions, together encompassing less than 2.8 Mb, are the only locations where the M and S forms are significantly differentiated. Two of these regions are adjacent to centromeres, on Chromosomes 2L and X, and contain 50 and 12 predicted genes, respectively. Sequenced loci in these regions contain fixed differences between forms and no shared polymorphisms, while no fixed differences were found at nearby control loci. The third region, on Chromosome 2R, contains only five predicted genes; fixed differences in this region were also verified by direct sequencing. These “speciation islands” remain differentiated despite considerable gene flow, and are therefore expected to contain the genes responsible for reproductive isolation. Much effort has recently been applied to locating the genes and genetic changes responsible for reproductive isolation between species. Though much can be inferred about speciation by studying taxa that have diverged for millions of years, studying differentiation between taxa that are in the early stages of isolation will lead to a clearer view of the number and size of regions involved in the genetics of speciation. Despite appreciable levels of gene flow between the M and S forms of A. gambiae, we were able to isolate three small regions of differentiation where genes responsible for ecological and behavioral isolation are likely to be located. We expect reproductive isolation to be due to changes at a small number of loci, as these regions together contain only 67 predicted genes. Concentrating future mapping experiments on these regions should reveal the genes responsible for reproductive isolation between forms.

Using DNA microarrays, the authors identify 3 small regions of the genome that differ between two forms of hybridizing mosquitoes; regions that are likely to contain the genes responsible for reproductive isolation.

A statistical multiprobe model for analyzing cis and trans genes in genetical genomics experiments with short-oligonucleotide arrays

Short-oligonucleotide arrays typically contain multiple probes per gene. In genetical genomics applications a statistical model for the individual probe signals can help in separating "true" differential mRNA expression from "ghost" effects caused by polymorphisms, misdesigned probes, and batch effects. It can also help in detecting alternative splicing, start, or termination.

Simpleaffy: a BioConductor package for Affymetrix Quality Control and data analysis

Quality Control is a fundamental aspect of successful microarray data analysis. Simpleaffy is a BioConductor package that provides access to a variety of QC metrics for assessing the quality of RNA samples and of the intermediate stages of sample preparation and hybridization. Simpleaffy also offers fast implementations of popular algorithms for generating expression summaries and detection calls.

AVAILABILITY

Simpleaffy can be downloaded from http://www.bioconductor.org.

SUPPLEMENTARY INFORMATION

Additional information can be found on the supplementary website located at http://bioinformatics.picr.man.ac.uk.

A Novel Pathophysiological Mechanism for Osteoporosis Suggested by an in Vivo Gene Expression Study of Circulating Monocytes

Bone mineral density (BMD) is a major risk factor for osteoporosis. Circulating monocytes may serve as early progenitors of osteoclasts and produce a wide variety of factors important to bone metabolism. However, little is known about the roles of circulating monocytes in relation to the pathophysiology of osteoporosis. Using the Affymetrix HG-U133A GeneChip(R) array, we performed a comparative gene expression study of circulating monocytes in subjects with high and low BMD. We identified in total 66 differentially expressed genes including some novel as well as some already known to be relevant to bone metabolism. Three genes potentially contributing to bone metabolism, CCR3 (chemokine receptor 3), HDC (histidine decarboxylase, i.e. the histamine synthesis enzyme), and GCR (glucocorticoid receptor), were confirmed by quantitative real-time reverse transcriptase-PCR as up-regulated in subjects with lower BMD. In addition, significant negative correlation was observed between expression levels of the genes and BMD Z-scores. These three genes and/or their products mediate monocyte chemotaxis, histamine production, and/or sensitivity to glucocorticoids. Our results suggest a novel pathophysiological mechanism for osteoporosis that is characterized by increased recruitment of circulating monocyte into bone, enhanced monocyte differentiation into osteoclasts, as well as osteoclast stimulation via monocyte functional changes. This is the first in vivo microarray study of osteoporosis in humans. The results may contribute to identification of new genes and their functions for osteoporosis and suggest genetic markers to discern individuals at higher risk to osteoporosis with an aim for preventive intervention and treatment.

Genetic and pharmacological inactivation of adenosine A2A receptor reveals an Egr-2-mediated transcriptional regulatory network in the mouse striatum

The adenosine A2A receptor (A2AR) is highly expressed in the striatum, where it modulates motor and emotional behaviors. We used both microarray and bioinformatics analyses to compare gene expression profiles by genetic and pharmacological inactivation of A2AR and inferred an A2AR-controlled transcription network in the mouse striatum. A comparison between vehicle (VEH)-treated A2AR knockout (KO) mice (A2AR KO-VEH) and wild-type (WT) mice (WT-VEH) revealed 36 upregulated genes that were partially mimicked by treatment with SCH-58261 (SCH; an A2AR antagonist) and 54 downregulated genes that were not mimicked by SCH treatment. We validated the A2AR as a specific drug target for SCH by comparing A2AR KO-SCH and A2AR KO-VEH groups. The unique downregulation effect of A2AR KO was confirmed by comparing A2AR KO-SCH with WT-SCH gene groups. The distinct striatal gene expression profiles induced by A2AR KO and SCH should provide clues to the molecular mechanisms underlying the different phenotypes observed after genetic and pharmacological inactivation of A2AR. Furthermore, bioinformatics analysis discovered that Egr-2 binding sites were statistically overrepresented in the proximal promoters of A2AR KO-affected genes relative to the unaffected genes. This finding was further substantiated by the demonstration that the Egr-2 mRNA level increased in the striatum of both A2AR KO and SCH-treated mice and that striatal Egr-2 binding activity in the promoters of two A2AR KO-affected genes was enhanced in A2AR KO mice as assayed by chromatin immunoprecipitation. Taken together, these results strongly support the existence of an Egr-2-directed transcriptional regulatory network controlled by striatal A2ARs.

Quality assessment of microarrays: visualization of spatial artifacts and quantitation of regional biases

BACKGROUND

Quality-control is an important issue in the analysis of gene expression microarrays. One type of problem is regional bias, in which one region of a chip shows artifactually high or low intensities (or ratios in a two-channel array) relative to the majority of the chip. Current practice in quality assessment for microarrays does not address regional biases.

RESULTS

We present methods implemented in R for visualizing regional biases and other spatial artifacts on spotted microarrays and Affymetrix chips. We also propose a statistical index to quantify regional bias and investigate its typical distribution on spotted and Affymetrix arrays. We demonstrate that notable regional biases occur on both Affymetrix and spotted arrays and that they can make a significant difference in the case of spotted microarray results. Although strong biases are also seen at the level of individual probes on Affymetrix chips, the gene expression measures are less affected, especially when the RMA method is used to summarize intensities for the probe sets. A web application program for visualization and quantitation of regional bias is provided at http://www.discover.nci.nih.gov/affytools.

CONCLUSION

Researchers should visualize and measure the regional biases and should estimate their impact on gene expression measurements obtained. Here, we (i) introduce pictorial visualizations of the spatial biases; (ii) present for Affymetrix chips a useful resolution of the biases into two components, one related to background, the other to intensity scale factor; (iii) introduce a single parameter to reflect the global bias present across an array. We also examine the pattern distribution of such biases and conclude that algorithms based on smoothing are unlikely to compensate adequately for them.

The MAP kinase substrate MKS1 is a regulator of plant defense responses

Arabidopsis MAP kinase 4 (MPK4) functions as a regulator of pathogen defense responses, because it is required for both repression of salicylic acid (SA)-dependent resistance and for activation of jasmonate (JA)-dependent defense gene expression. To understand MPK4 signaling mechanisms, we used yeast two-hybrid screening to identify the MPK4 substrate MKS1. Analyses of transgenic plants and genome-wide transcript profiling indicated that MKS1 is required for full SA-dependent resistance in mpk4 mutants, and that overexpression of MKS1 in wild-type plants is sufficient to activate SA-dependent resistance, but does not interfere with induction of a defense gene by JA. Further yeast two-hybrid screening revealed that MKS1 interacts with the WRKY transcription factors WRKY25 and WRKY33. WRKY25 and WRKY33 were shown to be in vitro substrates of MPK4, and a wrky33 knockout mutant was found to exhibit increased expression of the SA-related defense gene PR1. MKS1 may therefore contribute to MPK4-regulated defense activation by coupling the kinase to specific WRKY transcription factors.

Differential effects of Gq alpha, G14 alpha, and G15 alpha on vascular smooth muscle cell survival and gene expression profiles

Gqalpha family members (Gqalpha, G11alpha, G14alpha, and G15/16alpha) stimulate phospholipase Cbeta (PLCbeta) and inositol lipid signaling but differ markedly in amino acid sequence and tissue distribution predicting unappreciated functional diversity. To examine functional differences, we compared the signaling properties of Gqalpha, G14alpha, and G15alpha and their cellular responses in vascular smooth muscle cells (VSMC). Constitutively active forms of Gqalpha, G14alpha, or G15alpha elicit markedly different responses when introduced to VSMC. Whereas each Galpha stimulated PLCbeta to similar extents when expressed at equal protein levels, Gqalpha and G14alpha but not G15alpha initiated profound cell death within 48 h. This response was the result of activation of apoptotic pathways, because Gqalpha and G14alpha, but not G15alpha, stimulated caspase-3 activation and did not alter phospho-Akt, a regulator of cell survival pathways. Gqalpha and G14alpha stimulate nuclear factor of activated T cell (NFAT) activation in VSMC, but Galpha-induced cell death seems independent of PKC, InsP(3)/Ca(2+), and NFAT, in that pharmacological inhibitors of these pathways did not block cell death. Gene expression analysis indicates that Gqalpha, G14alpha, and G15alpha each elicit markedly different profiles of altered gene sets in VSMC after 24 h. Whereas all three Galpha stimulated changes (> or =2-fold) in 50 shared mRNA, Gqalpha and G14alpha (but not G15alpha) stimulated changes in 221 shared mRNA, many of which are reported to be pro-apoptotic and/or involved with TNF-alpha signaling. We were surprised to find that each Galpha also stimulated changes in nonoverlapping Galpha-specific gene sets. These findings demonstrate that Gqalpha family members activate both overlapping and distinct signaling pathways and are more functionally diverse than previously thought.

The elongata mutants identify a functional Elongator complex in plants with a role in cell proliferation during organ growth

The key enzyme for transcription of protein-encoding genes in eukaryotes is RNA polymerase II (RNAPII). The recruitment of this enzyme during transcription initiation and its passage along the template during transcription elongation is regulated through the association and dissociation of several complexes. Elongator is a histone acetyl transferase complex, consisting of six subunits (ELP1-ELP6), that copurifies with the elongating RNAPII in yeast and humans. We demonstrate that point mutations in three Arabidopsis thaliana genes, encoding homologs of the yeast Elongator subunits ELP1, ELP3 (histone acetyl transferase), and ELP4 are responsible for the phenotypes of the elongata2 (elo2), elo3, and elo1 mutants, respectively. The elo mutants are characterized by narrow leaves and reduced root growth that results from a decreased cell division rate. Morphological and molecular phenotypes show that the ELONGATA (ELO) genes function in the same biological process and the epistatic interactions between the ELO genes can be explained by the model of complex formation in yeast. Furthermore, the plant Elongator complex is genetically positioned in the process of RNAPII-mediated transcription downstream of Mediator. Our data indicate that the Elongator complex is evolutionarily conserved in structure and function but reveal that the mechanism by which it stimulates cell proliferation is different in yeast and plants.

Substantial changes in gene expression of Wnt, MAPK and TNFalpha pathways induced by TGF-beta1 in cervical cancer cell lines

Transforming growth factor-beta 1 (TGF-beta1) is a potent inhibitor of epithelial cell proliferation. During the development of cervical carcinoma however, an increase in production of TGF-beta1 is accompanied by decreased sensitivity for the growth-limiting effect of TGF-beta1. TGF-beta1 has an anti-proliferative effect on cells of the immune system and thus can be advantageous for tumor progression. The aim of the present study was to determine the effect of TGF-beta1 on mRNA expression profile of genes in pathways involved in cell growth and cell death, in cervical carcinoma cell lines with different sensitivity to TGF-beta1. For this purpose, we have investigated changes in gene expression in TGF-beta1 stimulated cervical cancer cell lines with high (CC10B), intermediate (SiHa) and low (HeLa) sensitivity to the anti-proliferative effect of TGF-beta1, at timepoints 0, 6, 12 and 24 h. Microarray analysis, using Affymetrics focus arrays, representing 8973 genes, was used to measure gene expression. In our study novel target genes involved in tumor necrosis factor alpha (TNFalpha), mitogen-activated protein kinase (MAPK) and wingless type (Wnt) pathways in response to TGF-beta1 were found. Substantial differences in gene expression between TGF-beta1 sensitive and insensitive cell lines were observed involving genes in TNFalpha, MAPK, Wnt and Smad pathways. Since these pathways are implicated in cell proliferation and cell death, these pathways may play a role in determining the overall sensitivity of a cell to TGF-beta1 induced cell growth inhibition. The results were subsequently validated by quantitative real-time PCR. Increased resistance to TGF-beta1 induced cell growth inhibition was correlated with an elevated production of TGF-beta1 by the cell lines, as measured by enzyme linked immunosorbent assay. TGF-beta1 production did not inhibit cell growth, since blocking TGF-beta1 protein by anti-TGF-beta had no effect on cell proliferation. TGF-beta1 excretion by tumor cells more likely contributes to paracrine stimulation of tumor development.

Increased DNA microarray hybridization specificity using sscDNA targets

Background

The most widely used amplification method for microarray analysis of gene expression uses T7 RNA polymerase-driven in vitro transcription (IVT) to produce complementary RNA (cRNA) that can be hybridized to arrays. However, multiple rounds of amplification are required when assaying very small amounts of starting RNA. Moreover, certain cRNA-DNA mismatches are more stable than the analogous cDNA-DNA mismatches and this might increase non-specific hybridization. We sought to determine whether a recently developed linear isothermal amplification method (ribo-SPIA) that produces single stranded cDNA would offer advantages over traditional IVT-based methods for microarray-based analyses of transcript expression.

Results

A single round of ribo-SPIA amplification produced sufficient sscDNA for hybridizations when as little as 5 ng of starting total RNA was used. Comparisons of probe set signal intensities obtained from replicate amplifications showed consistently high correlations (r = 0.99). We compared gene expression in two different human RNA samples using ribo-SPIA. Compared with one round IVT, ribo-SPIA had a larger dynamic range and correlated better with quantitative PCR results even though we used 1000-fold less starting RNA. The improved dynamic range was associated with decreases in hybridization to mismatch control probes.

Conclusion

The use of amplified sscDNA may offer substantial advantages over IVT-based amplification methods, especially when very limited amounts of starting RNA are available. The use of sscDNA targets instead of cRNA targets appears to improve hybridization specificity.

BarleyBase--an expression profiling database for plant genomics

BarleyBase (BB) (www.barleybase.org) is an online database for plant microarrays with integrated tools for data visualization and statistical analysis. BB houses raw and normalized expression data from the two publicly available Affymetrix genome arrays, Barley1 and Arabidopsis ATH1 with plans to include the new Affymetrix 61K wheat, maize, soybean and rice arrays, as they become available. BB contains a broad set of query and display options at all data levels, ranging from experiments to individual hybridizations to probe sets down to individual probes. Users can perform cross-experiment queries on probe sets based on observed expression profiles and/or based on known biological information. Probe set queries are integrated with visualization and analysis tools such as the R statistical toolbox, data filters and a large variety of plot types. Controlled vocabularies for gene and plant ontologies, as well as interconnecting links to physical or genetic map and other genomic data in PlantGDB, Gramene and GrainGenes, allow users to perform EST alignments and gene function prediction using Barley1 exemplar sequences, thus, enhancing cross-species comparison.

Albumin Activates ERKViaEGF Receptor in Human Renal Epithelial Cells

Emerging clinical and experimental evidence strongly implicates proteinuria in the progression of kidney disease. One pathway involves the activation of NFkappaB by albumin, and it has been demonstrated that the activation of NFkappaB induced by albumin is dependent on mitogen-activated protein kinase ERK1/ERK2. To study the effect of albumin on gene expression, primary human renal tubular cells were exposed in vitro to albumin (1%) for 6 h, and gene expression profiling was performed with the human oligonucleotide microarray, U133A Affymetrix Gene Chip. In all, 223 genes were differentially regulated by albumin, including marked upregulation of the EGF receptor (EGFR) and IL-8. Accordingly, the authors sought to delineate the signaling pathway linking albumin to the EGFR and activation of ERK1/ERK2. It was found that albumin led to a dose- and time-dependent activation of ERK1/ERK2. Treatment with albumin led to EGFR phosphorylation, but the activation of ERK1/ERK2 was prevented by pretreatment of the cells with AG-1478, the EGFR kinase inhibitor, at a dose that inhibited EGF-induced ERK1/ERK2 activation. Exogenously administered reactive oxygen species (ROS) were found to activate ERK1/ERK2 via the EGFR and src tyrosine kinase activity and pretreatment of cells with the antioxidant N-acetylcysteine (NAC) and the NADPH oxidase inhibitor DPI abrogated albumin-induced activation of ERK1/ERK2. The src tyrosine kinase inhibitor, PP2, also inhibited the albumin-induced activation of ERK1/ERK2. Finally, pretreatment with AG-1478, the MEK inhibitor UO126, and NAC prevented the albumin-induced increase in IL-8 expression. The authors conclude that the EGF receptor plays a central role in the signaling pathway that links albumin to the activation of ERK1/ERK2 and increased expression of IL-8. Gene profiling studies suggest that there may be a positive feedback loop through the EGFR that amplifies the response of the proximal tubule cell to albumin. Taken together, these results suggest that the EGFR may be an important treatment target for kidney disease associated with proteinuria.

Combining Affymetrix microarray results

BACKGROUND

As the use of microarray technology becomes more prevalent it is not unusual to find several laboratories employing the same microarray technology to identify genes related to the same condition in the same species. Although the experimental specifics are similar, typically a different list of statistically significant genes result from each data analysis.

RESULTS

We propose a statistically-based meta-analytic approach to microarray analysis for the purpose of systematically combining results from the different laboratories. This approach provides a more precise view of genes that are significantly related to the condition of interest while simultaneously allowing for differences between laboratories. Of particular interest is the widely used Affymetrix oligonucleotide array, the results of which are naturally suited to a meta-analysis. A simulation model based on the Affymetrix platform is developed to examine the adaptive nature of the meta-analytic approach and to illustrate the usefulness of such an approach in combining microarray results across laboratories. The approach is then applied to real data involving a mouse model for multiple sclerosis.

CONCLUSION

The quantitative estimates from the meta-analysis model tend to be closer to the "true" degree of differential expression than any single lab. Meta-analytic methods can systematically combine Affymetrix results from different laboratories to gain a clearer understanding of genes' relationships to specific conditions of interest.

Issues for consideration in the analysis of microarray data in behavioural studies

Microarrays are one of several technologies that allow for measurement the expression of thousands of genes simultaneously. This technological advance provides a challenge for the analysis of these data. In this review we discuss these analytical issues from the initial quality control to normalization, differential expression, clustering and finally functional pathway analysis. We focus on Affymetrix data but many of the issues are the same for other array platforms.

DNA Macroarray profiling of Lactococcus lactis subsp. lactis IL1403 gene expression during environmental stresses

This report describes the use of an oligonucleotide macroarray to profile the expression of 375 genes in Lactococcus lactis subsp. lactis IL1403 during heat, acid, and osmotic stress. A set of known stress-associated genes in IL1403 was used as the internal control on the array. Every stress response was accurately detected using the macroarray, compared to data from previous reports. As a group, the expression patterns of the investigated metabolic genes were significantly altered by heat, acid, and osmotic stresses. Specifically, 13 to 18% of the investigated genes were differentially expressed in each of the environmental stress treatments. Interestingly, the methionine biosynthesis pathway genes (metA-metB1 and metB2-cysK) were induced during heat shock, but methionine utilization genes, such as metK, were induced during acid stress. These data provide a possible explanation for the differences between acid tolerance mechanisms of L. lactis strains IL1403 and MG1363 reported previously. Several groups of transcriptional responses were common among the stress treatments, such as repression of peptide transporter genes, including the opt operon (also known as dpp) and dtpT. Reduction of peptide transport due to environmental stress will have important implications in the cheese ripening process. Although stress responses in lactococci were extensively studied during the last decade, additional information about this bacterium was gained from the use of this metabolic array.

Cytosolic ascorbate peroxidase 1 is a central component of the reactive oxygen gene network of Arabidopsis

Reactive oxygen species (ROS), such as O2- and H2O2, play a key role in plant metabolism, cellular signaling, and defense. In leaf cells, the chloroplast is considered to be a focal point of ROS metabolism. It is a major producer of O2- and H2O2 during photosynthesis, and it contains a large array of ROS-scavenging mechanisms that have been extensively studied. By contrast, the function of the cytosolic ROS-scavenging mechanisms of leaf cells is largely unknown. In this study, we demonstrate that in the absence of the cytosolic H2O2-scavenging enzyme ascorbate peroxidase 1 (APX1), the entire chloroplastic H2O2-scavenging system of Arabidopsis thaliana collapses, H2O2 levels increase, and protein oxidation occurs. We further identify specific proteins oxidized in APX1-deficient plants and characterize the signaling events that ensue in knockout-Apx1 plants in response to a moderate level of light stress. Using a dominant-negative approach, we demonstrate that heat shock transcription factors play a central role in the early sensing of H2O2 stress in plants. Using knockout plants for the NADPH oxidase D protein (knockout-RbohD), we demonstrate that RbohD might be required for ROS signal amplification during light stress. Our study points to a key role for the cytosol in protecting the chloroplast during light stress and provides evidence for cross-compartment protection of thylakoid and stromal/mitochondrial APXs by cytosolic APX1.

Mammalian male germ cells are fertile ground for expression profiling of sexual reproduction

Recent large-scale transcriptional profiling experiments of mammalian spermatogenesis using rodent model systems and different types of microarrays have yielded insight into the expression program of male germ cells. These studies revealed that an astonishingly large number of loci are differentially expressed during spermatogenesis. Among them are several hundred transcripts that appear to be specific for meiotic and post-meiotic germ cells. This group includes many genes that were previously implicated in spermatogenesis and/or fertility and others that are as yet poorly characterized. Profiling experiments thus reveal candidates for regulation of spermatogenesis and fertility as well as targets for innovative contraceptives that act on gene products absent in somatic tissues. In this review, consolidated high density oligonucleotide microarray data from rodent total testis and purified germ cell samples are analyzed and their impact on our understanding of the transcriptional program governing male germ cell differentiation is discussed.

DBC2 significantly influences cell-cycle, apoptosis, cytoskeleton and membrane-trafficking pathways

The tumor suppressor DBC2 belongs to a previously uncharacterized gene family, RHOBTB (Bric-a-brac, Tramtrack, Broad-complex). The biological roles of RHOBTB proteins, including DBC2, remain unclear. To understand the physiological functions of DBC2, a global approach was applied. Expression of DBC2 was manipulated in HeLa cells and RNA profiling of the cells was performed by microarray analyses. DBC2 was introduced into HeLa cells by a mammalian expression vector with a constitutive promoter. DBC2 knockdown was achieved by RNA interference with small interfering RNA. RNA profiles of these samples were performed by microarray analysis using Affymetrix GeneChip HG-U133A 2.0. The microarray data were analyzed by Microarray Suite 5.0 (MAS 5.0) and Robust Multichip Average (RMA). A list of genes whose expression was significantly altered (p<0.001) was generated and overlaid onto a cellular pathway map in the Ingenuity Systems' Pathway Knowledge Base (Winter'04 Release). Two networks were found to react substantially to DBC2 expression; namely, more than half of participating genes are affected. One of the networks regulates cell growth through cell-cycle control and apoptosis. The other network is related to cytoskeleton and membrane trafficking. Our findings suggest that the biological roles of DBC2 are related directly and/or indirectly to these cellular machineries.

The role of CTLs in persistent viral infection: cytolytic gene expression in CD8+ lymphocytes distinguishes between individuals with a high or low proviral load of human T cell lymphotropic virus type 1

The proviral load in human T cell lymphotropic virus type 1 (HTLV-1) infection is typically constant in each infected host, but varies by >1000-fold between hosts and is strongly correlated with the risk of HTLV-1-associated inflammatory disease. However, the factors that determine an individual's HTLV-1 proviral load remain uncertain. Experimental evidence from studies of host genetics, viral genetics, and lymphocyte function and theoretical considerations suggest that a major determinant of the equilibrium proviral load is the CD8+ T cell response to HTLV-1. In this study, we tested the hypothesis that the gene expression profile in circulating CD8+ and CD4+ lymphocytes distinguishes between individuals with a low proviral load of HTLV-1 and those with a high proviral load. We show that circulating CD8+ lymphocytes from individuals with a low HTLV-1 proviral load overexpressed a core group of nine genes with strong functional coherence: eight of the nine genes encode granzymes or other proteins involved in cell-mediated lysis or Ag recognition. We conclude that successful suppression of the HTLV-1 proviral load is associated with strong cytotoxic CD8+ lymphocyte activity in the peripheral blood.

Implementation of a gene expression index calculation method based on the PDNN model

Gene expression index calculations from Affymetrix GeneChips have been dominated by the Affymetrix MAS, dChip, and RMA methods. A new method to estimate the gene expression value utilizing the probe sequence information named position-dependent nearest-neighbor (PDNN) has been suggested by Zhang et al. (2003). Here we describe an open source implementation of the PDNN method for the statistical language R.

AVAILABILITY

The package can be downloaded from http://www.bioconductor.org/repository/devel/package/html/affypdnn.html

CONTACT

hbjorn@cbs.dtu.dk.

Ischemic but not pharmacological preconditioning elicits a gene expression profile similar to unprotected myocardium

Pharmacological (PPC) and ischemic preconditioning (IschPC) provide comparable protection against ischemia in the heart. However, the genomic phenotype may depend on the type of preconditioning. Isolated perfused rat hearts were used to evaluate transcriptional responses to PPC and IschPC in the presence (mediator/effector response) or absence (trigger response) of 40 min of test ischemia using oligonucleotide microarrays. IschPC was induced by 3 cycles of 5 min of ischemia, and PPC by 15 min of 2.1 vol% isoflurane. Unsupervised analysis methods were used to identify gene expression patterns. PPC and IschPC were accompanied by marked alterations in gene expression. PPC and IschPC shared only approximately 25% of significantly up- and downregulated genes after triggering. The two types of preconditioning induced a more uniform genomic response after ischemia/reperfusion. Numerous genes separated preconditioned from unprotected ischemic hearts. Three stable gene clusters were identified in the trigger response to preconditioning, while eight stable clusters related to cytoprotection, inflammation, remodeling, and long interspersed nucleotide elements (LINEs) were delineated after prolonged ischemia. A single stable sample cluster emerged from cluster analysis for both IschPC and unprotected myocardium, indicating a close molecular relationship between these two treatments. Principal component analysis revealed differences between PPC vs. IschPC, and trigger vs. mediator/effector responses in transcripts predominantly related to biosynthesis and apoptosis. IschPC and PPC similarly but distinctly reprogram the genetic response to ischemic injury. IschPC elicits a postischemic gene expression profile closer to unprotected myocardium than PPC, which may be therefore more advantageous as therapeutic strategy in cardioprotection.

BarleyExpress: a web-based submission tool for enriched microarray database annotations

BarleyExpress is a web-based microarray experiment data submission tool for BarleyBase, a public data resource of Affymetrix GeneChip data for plants. BarleyExpress uses the Plant Ontology vocabularies and enhances the MIAME guidelines to standardize the annotation of microarray gene expression experiments. In addition, BarleyExpress provides explicit support for factorial experiment design and template loading methods to ease the submission process for large experiments.

AVAILABILITY

http://barleybase.org

SUPPLEMENTARY INFORMATION

BarleyExpress Users Manual.

Alternative mapping of probes to genes for Affymetrix chips

BACKGROUND

Short oligonucleotide arrays have several probes measuring the expression level of each target transcript. Therefore the selection of probes is a key component for the quality of measurements. However, once probes have been selected and synthesized on an array, it is still possible to re-evaluate the results using an updated mapping of probes to genes, taking into account the latest biological knowledge available.

METHODS

We investigated how probes found on recent commercial microarrays for human genes (Affymetrix HG-U133A) were matching a recent curated collection of human transcripts: the NCBI RefSeq database. We also built mappings and used them in place of the original probe to genes associations provided by the manufacturer of the arrays.

RESULTS

In a large number of cases, 36%, the probes matching a reference sequence were consistent with the grouping of probes by the manufacturer of the chips. For the remaining cases there were discrepancies and we show how that can affect the analysis of data.

CONCLUSIONS

While the probes on Affymetrix arrays remain the same for several years, the biological knowledge concerning the genomic sequences evolves rapidly. Using up-to-date knowledge can apparently change the outcome of an analysis.

Sequence-matched probes produce increased cross-platform consistency and more reproducible biological results in microarray-based gene expression measurements

Cancer derived microarray data sets are routinely produced by various platforms that are either commercially available or manufactured by academic groups. The fundamental difference in their probe selection strategies holds the promise that identical observations produced by more than one platform prove to be more robust when validated by biology. However, cross-platform comparison requires matching corresponding probe sets. We are introducing here sequence-based matching of probes instead of gene identifier-based matching. We analyzed breast cancer cell line derived RNA aliquots using Agilent cDNA and Affymetrix oligonucleotide microarray platforms to assess the advantage of this method. We show, that at different levels of the analysis, including gene expression ratios and difference calls, cross-platform consistency is significantly improved by sequence- based matching. We also present evidence that sequence-based probe matching produces more consistent results when comparing similar biological data sets obtained by different microarray platforms. This strategy allowed a more efficient transfer of classification of breast cancer samples between data sets produced by cDNA microarray and Affymetrix gene-chip platforms.