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Mining mouse microarray data
Dennis A Wigle, Janet Rossant, Igor Jurisica
Genome Biology , 2001, DOI: 10.1186/gb-2001-2-7-reviews1019
Abstract: Most articles on microarray technology, particularly reviews, begin with some over-reaching statement on their potential to illuminate the biological world. While resisting this temptation, we must acknowledge the increasing power of high-throughput expression profiling using high-density arrays. A quick Medline search of all papers referenced with the term 'microarray' shows an exponential increase since the first paper describing the approach by Pat Brown's group six years ago [1] (Figure 1). A calculated projection based on the number of papers this year to date predicts a total of around 500 microarray publications for 2001. The technology is quickly becoming a mainstay in the 'array' of tools available to the molecular biologist, and we expect it to be broadly applicable to our favorite genetically tractable organism, the laboratory mouse.The production of mouse microarrays has lagged somewhat behind the production of arrays from humans and from those model organisms for which full genome sequence is available, such as yeast or Caenorhabditis elegans. Oligonucleotide-based arrays from sources such as Affymetrix (Santa Clara, CA, USA) have been in production for a number of years, but their high cost has been a barrier to widespread general use in academia. The cDNA array effort has been hampered largely by the scarcity of large, well-annotated cDNA clone sets from mouse tissues. Fortunately, a number of recent publications have addressed this issue. Minoru Ko at the National Institute on Aging (NIA; National Institutes of Health, Bethesda, MD, USA) has developed a 15,247 clone set derived from mice largely at early developmental time points, with libraries covering stages from the early blastocyst to embryonic day (E) 7.5 (for which there are embryo and ectoplacental cone samples) [2]. This set will have added to it later this year a further 11,000 clones derived from sequencing of similar libraries, and libraries from trophoblast stem cells, hematopoietic stem
Comparison of gene coverage of mouse oligonucleotide microarray platforms
Ricardo A Verdugo, Juan F Medrano
BMC Genomics , 2006, DOI: 10.1186/1471-2164-7-58
Abstract: A MySQL relational database was created to store the mapping information for 25,416 mouse genes and for the probes in five microarray platforms (gene coverage level in parenthesis): Affymetrix430 2.0 (75.6%), ABI Genome Survey (81.24%), Agilent (79.33%), Codelink (78.09%), Sentrix (90.47%); and four array-ready oligosets: Sigma (47.95%), Operon v.3 (69.89%), Operon v.4 (84.03%), and MEEBO (84.03%). The differences in coverage between platforms were highly conserved across chromosomes. Differences in the number of redundant and unspecific probes were also found among arrays. The database can be queried to compare specific genomic regions using a web interface. The software used to create, update and query the database is freely available as a toolbox named ArrayGene.The software developed here allows researchers to create updated custom databases by using public or proprietary information on genes for any organisms. ArrayGene allows easy comparisons of gene coverage between microarray platforms for any region of the genome. The comparison presented here reveals that the commercial microarray Sentrix, which is based on the MEEBO public oligoset, showed the best mouse genome coverage currently available. We also suggest the creation of guidelines to standardize the minimum set of information that vendors should provide to allow researchers to accurately evaluate the advantages and disadvantages of using a given platform.The wide use of DNA microarrays to query expression of genes has created the need for updated, consistent and meaningful annotations on the probes included in the microarrays. We refer to gene annotation as a recognizable label or gene id identifying the gene that is targeted by a given probe. Gene ids should be stable, widely used and allow reliable associations among genomic databases. Several microarray annotation systems are available for investigators, aiming to address specific user demands. For instance, the KARMA [1] web server provides periodic
Application of functional genomics to the chimeric mouse model of HCV infection: optimization of microarray protocols and genomics analysis
Kathie-Anne Walters, Michael A Joyce, Jill C Thompson, Sean Proll, James Wallace, Maria W Smith, Jeff Furlong, D Lorne Tyrrell, Michael G Katze
Virology Journal , 2006, DOI: 10.1186/1743-422x-3-37
Abstract: The results indicate that hybridization of mouse mRNA to the corresponding human gene probe on Agilent Human 22 K oligonucleotide microarray does occur. The number of genes affected by such cross-hybridization was subsequently reduced to approximately 300 genes both by increasing the hybridization temperature and using liver samples which contain at least 80% human tissue. In addition, Real Time quantitative RT-PCR using human specific probes was shown to be a valid method to verify the expression level in human cells of known cross-hybridizing genes.The identification of genes affected by cross-hybridization of mouse liver RNA on human oligonucleotide microarrays makes it feasible to use functional genomics approaches to study the chimeric SCID-beige/Alb-uPA mouse model of HCV infection. This approach used to study cross-species hybridization on oligonucleotide microarrays can be adapted to other chimeric systems of viral disease to facilitate selective analysis of human gene expression.Hepatitis C virus (HCV), a blood-borne pathogen belonging to the Flaviviridae family, is a major cause of chronic hepatitis, progressive liver disease and hepatocellular carcinoma [1,2]. The HCV genome is positive-strand 9.6 kb RNA which encodes a single open reading frame (ORF) flanked by 5'and 3' highly structured un-translated regions (UTR) [3]. Translation of the 3,011 amino acid HCV polyprotein is initiated at an internal ribosome entry site (IRES) located within the 5' UTR [3]. The HCV polyprotein is co-and post-translationally cleaved into the viral structural (core and envelope glycoproteins E1 and E2) as well as nonstructural proteins (NS2, NS3, NS4A, NS4B, NS5A and NS5B) by both host signal peptidases and viral proteases.Recently, an in vivo model of hepatitis C virus (HCV) infection was developed involving a SCID mouse carrying a urokinase plasminogen activator (uPA) transgene under the control of the albumin promoter [4-7]. Expression of the uPA transgene in the mouse li
Microarray studies reveal novel genes associated with endocrine resistance in breast cancer
RS Burmi, RA McClelland, D Barrow, IO Ellis, JFR Robertson, RI Nicholson, JMW Gee
Breast Cancer Research , 2006, DOI: 10.1186/bcr1554
Abstract: Microarray technology (BD Atlas Plastic Human 12 K Microarrays; GeneSifter software), verified by PCR, western blotting and immunocytochemisty, was used to identify genes increased in acquired resistant models to tamoxifen (TamR) or faslodex (FasR) as potential predictive/prognostic markers and new therapeutic targets.Alongside known breast cancer genes (β-catenin, PEA3, vitronectin, CD44), two novel genes in endocrine resistance were revealed (the latter never previously described in breast cancer): a securin/cell cycle regulator Pituitary Tumour Transforming Gene-1 (PTTG1), and GDNF receptor-alpha 3 (GFRα3) reported to promote cell survival signalling via RET coreceptor. Altered levels of PTTG1, GFRα3, or their associated family members were observed in further endocrine resistant states, including an additional faslodex resistant model that has progressed to a highly-aggressive state (FasR-Lt) and XMCF-7 cells resistant to oestrogen deprivation. PTTG1 and GFRα3 induction were also implicated in limiting response to anti-EGFR agents currently in breast cancer trials, with GFRα3 ligand (artemin) largely overcoming drug response. mRNA studies in clinical disease revealed PTTG1 associated with lymph node spread, high tumour grade and proliferation, while GFRα3 was enriched in ER-negative tumours and those expressing EGFR, profiles implying roles in clinical resistance and aggressive tumour behaviour. Promisingly, PTTG1 or GFRα3 siRNA knockdown promoted cell kill and inhibited proliferation in the resistant models.Cumulatively, these data indicate PTTG1 and GFRα3 may provide useful biomarkers, and perhaps clinically relevant therapeutic targets for multiple resistant states.Funding from Breast Cancer Campaign is gratefully acknowledged.
Microarray analysis of gene expression in the liver of transgenic mouse model of HCV infection  [PDF]
Masoud Ghorbani, Turaya Naas, Catalina Soare, Rashmi Kothary, Francisco Diaz-Mitoma
Advances in Bioscience and Biotechnology (ABB) , 2012, DOI: 10.4236/abb.2012.38141
Abstract: Background: The molecular interactions of hepatitis C virus (HCV) with hepatic tissue have yet to be completely elucidated and understood. The purpose of this study was to compare differential gene expression patterns in the livers of non-transgenic and transgenic mouse model expressing HCV structural proteins Core, Envelope 1 (E1) and Envelope 2 (E2) using complementary DNA (cDNA) microarrays. Results: Total RNA extracted from the livers of HCV transgenic and non-transgenic mice was analyzed with cDNA microarray and differentially expressed genes confirmed by real-time RT-PCR. Relative expression ratios of individual genes were determined by comparing hybridization of Cy5-labelled cDNA from transgenic mouse livers and Cy3-labelled cDNA from non-transgenic mouse livers. The spot array images were quantified using QuantArray software and the outlier spots was normalized and filtered using five different criteria. 15,297 genes were analyzed using three different analytical methods. Depending on these methods, twenty-one genes were found to be differentially expressed at a statistically significant level. From these, 6 genes had a consistent differential expression. Several genes were directly involved in lipid metabolism and lipid β-oxidation. 5-azacytidine induced gene 2 (AZ2), which is involved in the methylation of genes was down regulated in HCV transgenic mice. Altered transcript levels of these 6 genes were confirmed by real-time RT-PCR analysis. Conclusion: Interactions between HCV and hepatocytes not only involve lipid metabolism and redox balance, but this interaction may also influence DNA methylation, indicating a potential association with the development of hepatocellular carcinoma.
Deafness Gene Expression Patterns in the Mouse Cochlea Found by Microarray Analysis  [PDF]
Hidekane Yoshimura, Yutaka Takumi, Shin-ya Nishio, Nobuyoshi Suzuki, Yoh-ichiro Iwasa, Shin-ichi Usami
PLOS ONE , 2014, DOI: 10.1371/journal.pone.0092547
Abstract: Background Tonotopy is one of the most fundamental principles of auditory function. While gradients in various morphological and physiological characteristics of the cochlea have been reported, little information is available on gradient patterns of gene expression. In addition, the audiograms in autosomal dominant non syndromic hearing loss can be distinctive, however, the mechanism that accounts for that has not been clarified. We thought that it is possible that tonotopic gradients of gene expression within the cochlea account for the distinct audiograms. Methodology/Principal Findings We compared expression profiles of genes in the cochlea between the apical, middle, and basal turns of the mouse cochlea by microarray technology and quantitative RT-PCR. Of 24,547 genes, 783 annotated genes expressed more than 2-fold. The most remarkable finding was a gradient of gene expression changes in four genes (Pou4f3, Slc17a8, Tmc1, and Crym) whose mutations cause autosomal dominant deafness. Expression of these genes was greater in the apex than in the base. Interestingly, expression of the Emilin-2 and Tectb genes, which may have crucial roles in the cochlea, was also greater in the apex than in the base. Conclusions/Significance This study provides baseline data of gradient gene expression in the cochlea. Especially for genes whose mutations cause autosomal dominant non syndromic hearing loss (Pou4f3, Slc17a8, Tmc1, and Crym) as well as genes important for cochlear function (Emilin-2 and Tectb), gradual expression changes may help to explain the various pathological conditions.
Mouse strain specific gene expression differences for illumina microarray expression profiling in embryos
Petra Kraus, Xing Xing, Siew Lim, Max E Fun, V Sivakamasundari, Sook Yap, Haixia Lee, R Karuturi, Thomas Lufkin
BMC Research Notes , 2012, DOI: 10.1186/1756-0500-5-232
Abstract: Wild type embryos of 11 mouse strains commonly used in transgenic and molecular genetic studies at three developmental time points were subjected to Illumina microarray expression profiling in a strain-by-strain comparison. Our data robustly reflects known gene expression patterns during mid-gestation development. Decreasing diversity of the input tissue and/or increasing strain diversity raised the sensitivity of the array towards the genetic background. Consistent strain sensitivity of some probes was attributed to genetic polymorphisms or probe design related artifacts.Our study provides an extensive reference list of gene expression profiling background noise of value to anyone in the field of developmental biology and transgenic research performing microarray expression profiling with the widely used Illumina microarray platform. Probes identified as strain specific background noise further allow for microarray expression profiling on its own to be a valuable tool for establishing genealogies of mouse inbred strains.Mouse models are a fundamental tool in gaining a better understanding of mammalian development in general and human pathology in particular [1]. By studying gene expression patterns in the developing mouse embryo, important genetic pathways and signaling cascades have been revealed, for example in limb patterning (for review see [2]), the central nervous system (for review see [3])and the digestive system (for review see [4]). However, gene expression profiling techniques have leaped forward in recent years from the classical RNA in situ hybridization analysis to the more detailed and advanced methodologies of microarray analysis [5-8] providing a powerful tool for in depth analysis of genome wide differential gene expression. Yet, by increasing the assay sensitivity and being able to detect more subtle changes in expression profiles, questions arise in how far differences in the mouse genetic background affect the outcome of this advanced type of g
Transcript copy number estimation using a mouse whole-genome oligonucleotide microarray
Mark G Carter, Alexei A Sharov, Vincent VanBuren, Dawood B Dudekula, Condie E Carmack, Charlie Nelson, Minoru SH Ko
Genome Biology , 2005, DOI: 10.1186/gb-2005-6-7-r61
Abstract: One of the most tantalizing promises of gene-expression profiling technology has been to develop assays that measure expression of all genes in a given species [1]. This is especially important for the mouse, which is a standard model for various human diseases. The early and rapid development of murine bioinformatics resources such as the draft genome assembly [2] and numerous expressed sequence tag (EST) projects have bolstered the feasibility of developing such microarray platforms for the mouse. However, because it has been difficult to identify all murine genes and correctly group genomic and expressed sequences into genes and transcripts, microarray platforms intended to cover all mouse genes are only now being made widely available, long after the draft assembly was released.Relatively recent microarray technologies, which require sequence information instead of clones as input, allow investigators to design microarray platforms to detect genes without having to obtain clones, including genes which have yet to be cloned or confirmed as an expressed transcript [3]. Platforms that utilize long oligonucleotides give high sensitivity, with the potential for transcript specificity sufficient to distinguish transcripts from the same locus or closely related gene-family members [4,5].While microarray-based methods can provide very accurate relative (ratio-based) expression measurements, they usually do not provide absolute expression measurements (that is, transcript copy number). One notable exception described in the literature does provide absolute expression measurements in yeast, but not as copy numbers [6]. That method relies on labeled oligonucleotides complementary to common sequence in each cDNA probe, which are hybridized against each slide as the reference target. In the case of long-oligonucleotide-based microarrays, there is no sequence common to all probes, so such a strategy is not feasible. An appropriate approach for such microarray platforms is to
Cell-specific microarray profiling experiments reveal a comprehensive picture of gene expression in the C. elegans nervous system
Stephen E Von Stetina, Joseph D Watson, Rebecca M Fox, Kellen L Olszewski, W Clay Spencer, Peter J Roy, David M Miller
Genome Biology , 2007, DOI: 10.1186/gb-2007-8-7-r135
Abstract: We employed complementary microarray-based strategies to profile gene expression in the embryonic and larval nervous systems. In the MAPCeL (Microarray Profiling C. elegans cells) method, we used fluorescence activated cell sorting (FACS) to isolate GFP-tagged embryonic neurons for microarray analysis. To profile the larval nervous system, we used the mRNA-tagging technique in which an epitope-labeled mRNA binding protein (FLAG-PAB-1) was transgenically expressed in neurons for immunoprecipitation of cell-specific transcripts. These combined approaches identified approximately 2,500 mRNAs that are highly enriched in either the embryonic or larval C. elegans nervous system. These data are validated in part by the detection of gene classes (for example, transcription factors, ion channels, synaptic vesicle components) with established roles in neuronal development or function. Of particular interest are 19 conserved transcripts of unknown function that are also expressed in the mammalian brain. In addition to utilizing these profiling approaches to define stage-specific gene expression, we also applied the mRNA-tagging method to fingerprint a specific neuron type, the A-class group of cholinergic motor neurons, during early larval development. A comparison of these data to a MAPCeL profile of embryonic A-class motor neurons identified genes with common functions in both types of A-class motor neurons as well as transcripts with roles specific to each motor neuron type.We describe microarray-based strategies for generating expression profiles of embryonic and larval C. elegans neurons. These methods can be applied to particular neurons at specific developmental stages and, therefore, provide an unprecedented opportunity to obtain spatially and temporally defined snapshots of gene expression in a simple model nervous system.The nematode Caenorhabditis elegans is a widely used model system for developmental studies. The major tissues of complex metazoans, (muscle, intest
SNP microarray analyses reveal copy number alterations and progressive genome reorganization during tumor development in SVT/t driven mice breast cancer  [cached]
Standfu? Christoph,Pospisil Heike,Klein Andreas
BMC Cancer , 2012, DOI: 10.1186/1471-2407-12-380
Abstract: Background Tumor development is known to be a stepwise process involving dynamic changes that affect cellular integrity and cellular behavior. This complex interaction between genomic organization and gene, as well as protein expression is not yet fully understood. Tumor characterization by gene expression analyses is not sufficient, since expression levels are only available as a snapshot of the cell status. So far, research has mainly focused on gene expression profiling or alterations in oncogenes, even though DNA microarray platforms would allow for high-throughput analyses of copy number alterations (CNAs). Methods We analyzed DNA from mouse mammary gland epithelial cells using the Affymetrix Mouse Diversity Genotyping array (MOUSEDIVm520650) and calculated the CNAs. Segmental copy number alterations were computed based on the probeset CNAs using the circular binary segmentation algorithm. Motif search was performed in breakpoint regions (inter-segment regions) with the MEME suite to identify common motif sequences. Results Here we present a four stage mouse model addressing copy number alterations in tumorigenesis. No considerable changes in CNA were identified for non-transgenic mice, but a stepwise increase in CNA was found during tumor development. The segmental copy number alteration revealed informative chromosomal fragmentation patterns. In inter-segment regions (hypothetical breakpoint sides) unique motifs were found. Conclusions Our analyses suggest genome reorganization as a stepwise process that involves amplifications and deletions of chromosomal regions. We conclude from distinctive fragmentation patterns that conserved as well as individual breakpoints exist which promote tumorigenesis.
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