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Sample records for microarray transcriptome analysis

  1. Transcriptome analysis of zebrafish embryogenesis using microarrays.

    Directory of Open Access Journals (Sweden)

    Sinnakaruppan Mathavan

    2005-08-01

    Full Text Available Zebrafish (Danio rerio is a well-recognized model for the study of vertebrate developmental genetics, yet at the same time little is known about the transcriptional events that underlie zebrafish embryogenesis. Here we have employed microarray analysis to study the temporal activity of developmentally regulated genes during zebrafish embryogenesis. Transcriptome analysis at 12 different embryonic time points covering five different developmental stages (maternal, blastula, gastrula, segmentation, and pharyngula revealed a highly dynamic transcriptional profile. Hierarchical clustering, stage-specific clustering, and algorithms to detect onset and peak of gene expression revealed clearly demarcated transcript clusters with maximum gene activity at distinct developmental stages as well as co-regulated expression of gene groups involved in dedicated functions such as organogenesis. Our study also revealed a previously unidentified cohort of genes that are transcribed prior to the mid-blastula transition, a time point earlier than when the zygotic genome was traditionally thought to become active. Here we provide, for the first time to our knowledge, a comprehensive list of developmentally regulated zebrafish genes and their expression profiles during embryogenesis, including novel information on the temporal expression of several thousand previously uncharacterized genes. The expression data generated from this study are accessible to all interested scientists from our institute resource database (http://giscompute.gis.a-star.edu.sg/~govind/zebrafish/data_download.html.

  2. Transcriptome analysis in non-model species: a new method for the analysis of heterologous hybridization on microarrays

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    Jouventin Pierre

    2010-05-01

    Full Text Available Abstract Background Recent developments in high-throughput methods of analyzing transcriptomic profiles are promising for many areas of biology, including ecophysiology. However, although commercial microarrays are available for most common laboratory models, transcriptome analysis in non-traditional model species still remains a challenge. Indeed, the signal resulting from heterologous hybridization is low and difficult to interpret because of the weak complementarity between probe and target sequences, especially when no microarray dedicated to a genetically close species is available. Results We show here that transcriptome analysis in a species genetically distant from laboratory models is made possible by using MAXRS, a new method of analyzing heterologous hybridization on microarrays. This method takes advantage of the design of several commercial microarrays, with different probes targeting the same transcript. To illustrate and test this method, we analyzed the transcriptome of king penguin pectoralis muscle hybridized to Affymetrix chicken microarrays, two organisms separated by an evolutionary distance of approximately 100 million years. The differential gene expression observed between different physiological situations computed by MAXRS was confirmed by real-time PCR on 10 genes out of 11 tested. Conclusions MAXRS appears to be an appropriate method for gene expression analysis under heterologous hybridization conditions.

  3. A microarray analysis of the rice transcriptome and its comparison to Arabidopsis

    DEFF Research Database (Denmark)

    Ma, Ligeng; Chen, Chen; Liu, Xigang

    2005-01-01

    Arabidopsis and rice are the only two model plants whose finished phase genome sequence has been completed. Here we report the construction of an oligomer microarray based on the presently known and predicted gene models in the rice genome. This microarray was used to analyze the transcriptional...... with similar genome-wide surveys of the Arabidopsis transcriptome, our results indicate that similar proportions of the two genomes are expressed in their corresponding organ types. A large percentage of the rice gene models that lack significant Arabidopsis homologs are expressed. Furthermore, the expression...... patterns of rice and Arabidopsis best-matched homologous genes in distinct functional groups indicate dramatic differences in their degree of conservation between the two species. Thus, this initial comparative analysis reveals some basic similarities and differences between the Arabidopsis and rice...

  4. Microarray-based transcriptomic analysis of differences between long-term gregarious and solitarious desert locusts.

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    Liesbeth Badisco

    Full Text Available Desert locusts (Schistocerca gregaria show an extreme form of phenotypic plasticity and can transform between a cryptic solitarious phase and a swarming gregarious phase. The two phases differ extensively in behavior, morphology and physiology but very little is known about the molecular basis of these differences. We used our recently generated Expressed Sequence Tag (EST database derived from S. gregaria central nervous system (CNS to design oligonucleotide microarrays and compare the expression of thousands of genes in the CNS of long-term gregarious and solitarious adult desert locusts. This identified 214 differentially expressed genes, of which 40% have been annotated to date. These include genes encoding proteins that are associated with CNS development and modeling, sensory perception, stress response and resistance, and fundamental cellular processes. Our microarray analysis has identified genes whose altered expression may enable locusts of either phase to deal with the different challenges they face. Genes for heat shock proteins and proteins which confer protection from infection were upregulated in gregarious locusts, which may allow them to respond to acute physiological challenges. By contrast the longer-lived solitarious locusts appear to be more strongly protected from the slowly accumulating effects of ageing by an upregulation of genes related to anti-oxidant systems, detoxification and anabolic renewal. Gregarious locusts also had a greater abundance of transcripts for proteins involved in sensory processing and in nervous system development and plasticity. Gregarious locusts live in a more complex sensory environment than solitarious locusts and may require a greater turnover of proteins involved in sensory transduction, and possibly greater neuronal plasticity.

  5. The Plasmodium falciparum Sexual Development Transcriptome: A Microarray Analysis using Ontology-Based Pattern Identification

    National Research Council Canada - National Science Library

    Young, Jason A; Fivelman, Quinton L; Blair, Peter L; de la Vega, Patricia; Le Roch, Karine G; Zhou, Yingyao; Carucci, Daniel J; Baker, David A; Winzeler, Elizabeth A

    2005-01-01

    ... a full-genome high-density oligonucleotide microarray. The interpretation of this transcriptional data was aided by applying a novel knowledge-based data-mining algorithm termed ontology-based pattern identification (OPI...

  6. A comprehensive comparison of RNA-Seq-based transcriptome analysis from reads to differential gene expression and cross-comparison with microarrays: a case study in Saccharomyces cerevisiae

    DEFF Research Database (Denmark)

    Nookaew, Intawat; Papini, Marta; Pornputtapong, Natapol

    2012-01-01

    RNA-seq, has recently become an attractive method of choice in the studies of transcriptomes, promising several advantages compared with microarrays. In this study, we sought to assess the contribution of the different analytical steps involved in the analysis of RNA-seq data generated with the I......RNA-seq, has recently become an attractive method of choice in the studies of transcriptomes, promising several advantages compared with microarrays. In this study, we sought to assess the contribution of the different analytical steps involved in the analysis of RNA-seq data generated...... gene expression identification derived from the different statistical methods, as well as their integrated analysis results based on gene ontology annotation are in good agreement. Overall, our study provides a useful and comprehensive comparison between the two platforms (RNA-seq and microrrays...

  7. Analysis of the effects of sex hormone background on the rat choroid plexus transcriptome by cDNA microarrays.

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    Telma Quintela

    Full Text Available The choroid plexus (CP are highly vascularized branched structures that protrude into the ventricles of the brain, and form a unique interface between the blood and the cerebrospinal fluid (CSF, the blood-CSF barrier, that are the main site of production and secretion of CSF. Sex hormones are widely recognized as neuroprotective agents against several neurodegenerative diseases, and the presence of sex hormones cognate receptors suggest that it may be a target for these hormones. In an effort to provide further insight into the neuroprotective mechanisms triggered by sex hormones we analyzed gene expression differences in the CP of female and male rats subjected to gonadectomy, using microarray technology. In gonadectomized female and male animals, 3045 genes were differentially expressed by 1.5-fold change, compared to sham controls. Analysis of the CP transcriptome showed that the top-five pathways significantly regulated by the sex hormone background are olfactory transduction, taste transduction, metabolism, steroid hormone biosynthesis and circadian rhythm pathways. These results represent the first overview of global expression changes in CP of female and male rats induced by gonadectomy and suggest that sex hormones are implicated in pathways with central roles in CP functions and CSF homeostasis.

  8. Salmon louse (Lepeophtheirus salmonis transcriptomes during post molting maturation and egg production, revealed using EST-sequencing and microarray analysis

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    Jonassen Inge

    2008-03-01

    Full Text Available Abstract Background Lepeophtheirus salmonis is an ectoparasitic copepod feeding on skin, mucus and blood from salmonid hosts. Initial analysis of EST sequences from pre adult and adult stages of L. salmonis revealed a large proportion of novel transcripts. In order to link unknown transcripts to biological functions we have combined EST sequencing and microarray analysis to characterize female salmon louse transcriptomes during post molting maturation and egg production. Results EST sequence analysis shows that 43% of the ESTs have no significant hits in GenBank. Sequenced ESTs assembled into 556 contigs and 1614 singletons and whenever homologous genes were identified no clear correlation with homologous genes from any specific animal group was evident. Sequence comparison of 27 L. salmonis proteins with homologous proteins in humans, zebrafish, insects and crustaceans revealed an almost identical sequence identity with all species. Microarray analysis of maturing female adult salmon lice revealed two major transcription patterns; up-regulation during the final molting followed by down regulation and female specific up regulation during post molting growth and egg production. For a third minor group of ESTs transcription decreased during molting from pre-adult II to immature adults. Genes regulated during molting typically gave hits with cuticula proteins whilst transcripts up regulated during post molting growth were female specific, including two vitellogenins. Conclusion The copepod L.salmonis contains high a level of novel genes. Among analyzed L.salmonis proteins, sequence identities with homologous proteins in crustaceans are no higher than to homologous proteins in humans. Three distinct processes, molting, post molting growth and egg production correlate with transcriptional regulation of three groups of transcripts; two including genes related to growth, one including genes related to egg production. The function of the regulated

  9. A microarray analysis of sex- and gonad-biased gene expression in the zebrafish: Evidence for masculinization of the transcriptome

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    Mo Qianxing

    2009-12-01

    Full Text Available Abstract Background In many taxa, males and females are very distinct phenotypically, and these differences often reflect divergent selective pressures acting on the sexes. Phenotypic sexual dimorphism almost certainly reflects differing patterns of gene expression between the sexes, and microarray studies have documented widespread sexually dimorphic gene expression. Although the evolutionary significance of sexual dimorphism in gene expression remains unresolved, these studies have led to the formulation of a hypothesis that male-driven evolution has resulted in the masculinization of animal transcriptomes. Here we use a microarray assessment of sex- and gonad-biased gene expression to test this hypothesis in zebrafish. Results By using zebrafish Affymetrix microarrays to compare gene expression patterns in male and female somatic and gonadal tissues, we identified a large number of genes (5899 demonstrating differences in transcript abundance between male and female Danio rerio. Under conservative statistical significance criteria, all sex-biases in gene expression were due to differences between testes and ovaries. Male-enriched genes were more abundant than female-enriched genes, and expression bias for male-enriched genes was greater in magnitude than that for female-enriched genes. We also identified a large number of genes demonstrating elevated transcript abundance in testes and ovaries relative to male body and female body, respectively. Conclusion Overall our results support the hypothesis that male-biased evolutionary pressures have resulted in male-biased patterns of gene expression. Interestingly, our results seem to be at odds with a handful of other microarray-based studies of sex-specific gene expression patterns in zebrafish. However, ours was the only study designed to address this specific hypothesis, and major methodological differences among studies could explain the discrepancies. Regardless, all of these studies agree

  10. DNA Microarrays in Comparative Genomics and Transcriptomics

    DEFF Research Database (Denmark)

    Willenbrock, Hanni

    2007-01-01

    at identifying the exact breakpoints where DNA has been gained or lost. In this thesis, three popular methods are compared and a realistic simulation model is presented for generating artificial data with known breakpoints and known DNA copy number. By using simulated data, we obtain a realistic evaluation......During the past few years, innovations in the DNA sequencing technology has led to an explosion in available DNA sequence information. This has revolutionized biological research and promoted the development of high throughput analysis methods that can take advantage of the vast amount of sequence...... data. For this, the DNA microarray technology has gained enormous popularity due to its ability to measure the presence or the activity of thousands of genes simultaneously. Microarrays for high throughput data analyses are not limited to a few organisms but may be applied to everything from bacteria...

  11. Polyadenylation state microarray (PASTA) analysis.

    Science.gov (United States)

    Beilharz, Traude H; Preiss, Thomas

    2011-01-01

    Nearly all eukaryotic mRNAs terminate in a poly(A) tail that serves important roles in mRNA utilization. In the cytoplasm, the poly(A) tail promotes both mRNA stability and translation, and these functions are frequently regulated through changes in tail length. To identify the scope of poly(A) tail length control in a transcriptome, we developed the polyadenylation state microarray (PASTA) method. It involves the purification of mRNA based on poly(A) tail length using thermal elution from poly(U) sepharose, followed by microarray analysis of the resulting fractions. In this chapter we detail our PASTA approach and describe some methods for bulk and mRNA-specific poly(A) tail length measurements of use to monitor the procedure and independently verify the microarray data.

  12. MARS: Microarray analysis, retrieval, and storage system

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    Scheideler Marcel

    2005-04-01

    Full Text Available Abstract Background Microarray analysis has become a widely used technique for the study of gene-expression patterns on a genomic scale. As more and more laboratories are adopting microarray technology, there is a need for powerful and easy to use microarray databases facilitating array fabrication, labeling, hybridization, and data analysis. The wealth of data generated by this high throughput approach renders adequate database and analysis tools crucial for the pursuit of insights into the transcriptomic behavior of cells. Results MARS (Microarray Analysis and Retrieval System provides a comprehensive MIAME supportive suite for storing, retrieving, and analyzing multi color microarray data. The system comprises a laboratory information management system (LIMS, a quality control management, as well as a sophisticated user management system. MARS is fully integrated into an analytical pipeline of microarray image analysis, normalization, gene expression clustering, and mapping of gene expression data onto biological pathways. The incorporation of ontologies and the use of MAGE-ML enables an export of studies stored in MARS to public repositories and other databases accepting these documents. Conclusion We have developed an integrated system tailored to serve the specific needs of microarray based research projects using a unique fusion of Web based and standalone applications connected to the latest J2EE application server technology. The presented system is freely available for academic and non-profit institutions. More information can be found at http://genome.tugraz.at.

  13. A cross strain Plasmodium falciparum microarray optimized for the transcriptome analysis of Plasmodium falciparum patient derived isolates

    KAUST Repository

    Subudhi, Amit

    2016-07-20

    Malarial parasite P. falciparum, an apicomplexan protozoan has a 23.3 MB nuclear genome and encodes ~ 5600 transcripts. The genetic diversity of the parasite within and across geographical zones is a challenge to gene expression studies which are essential for understanding of disease process, outcome and developing markers for diagnostics and prognostics. Here, we describe the strategy involved in designing a custom P. falciparum 15K array using the Agilent platform and Genotypic\\'s Right Design methodology to study the transcriptome of Indian field isolates for which genome sequence information is limited. The array contains probes representing genome sequences of two distinct geographical isolates (i.e. 3D7 and HB3) and sub-telomeric var gene sequences of a third isolate (IT4) known to adhere in culture condition. Probes in the array have been selected based on their efficiency to detect transcripts through a 244K array experimentation. Array performance for the 15K array, was evaluated and validated using RNA materials from P. falciparum clinical isolates. A large percentage (91%) of the represented transcripts was detected from Indian P. falciparum patient isolates. Replicated probes and multiple probes representing the same gene showed perfect correlation between them suggesting good probe performance. Additional transcripts could be detected due to inclusion of unique probes representing HB3 strain transcripts. Variant surface antigen (VSA) transcripts were detected by optimized probes representing the VSA genes of three geographically distinct strains. The 15K cross strain P. falciparum array has shown good efficiency in detecting transcripts from P. falciparum parasite samples isolated from patients. The low parasite loads and presence of host RNA makes arrays a preferred platform for gene expression studies over RNA-Seq.

  14. A cross strain Plasmodium falciparum microarray optimized for the transcriptome analysis of Plasmodium falciparum patient derived isolates

    KAUST Repository

    Subudhi, Amit; Boopathi, P.A.; Middha, Sheetal; Acharya, Jyoti; Rao, Sudha Narayana; Mugasimangalam, Raja C.; Sirohi, Paramendra; Kochar, Sanjay K.; Kochar, Dhanpat K.; Das, Ashis

    2016-01-01

    Malarial parasite P. falciparum, an apicomplexan protozoan has a 23.3 MB nuclear genome and encodes ~ 5600 transcripts. The genetic diversity of the parasite within and across geographical zones is a challenge to gene expression studies which are essential for understanding of disease process, outcome and developing markers for diagnostics and prognostics. Here, we describe the strategy involved in designing a custom P. falciparum 15K array using the Agilent platform and Genotypic's Right Design methodology to study the transcriptome of Indian field isolates for which genome sequence information is limited. The array contains probes representing genome sequences of two distinct geographical isolates (i.e. 3D7 and HB3) and sub-telomeric var gene sequences of a third isolate (IT4) known to adhere in culture condition. Probes in the array have been selected based on their efficiency to detect transcripts through a 244K array experimentation. Array performance for the 15K array, was evaluated and validated using RNA materials from P. falciparum clinical isolates. A large percentage (91%) of the represented transcripts was detected from Indian P. falciparum patient isolates. Replicated probes and multiple probes representing the same gene showed perfect correlation between them suggesting good probe performance. Additional transcripts could be detected due to inclusion of unique probes representing HB3 strain transcripts. Variant surface antigen (VSA) transcripts were detected by optimized probes representing the VSA genes of three geographically distinct strains. The 15K cross strain P. falciparum array has shown good efficiency in detecting transcripts from P. falciparum parasite samples isolated from patients. The low parasite loads and presence of host RNA makes arrays a preferred platform for gene expression studies over RNA-Seq.

  15. Transcriptomic identification of candidate genes involved in sunflower responses to chilling and salt stresses based on cDNA microarray analysis

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    Paniego Norma

    2008-01-01

    Full Text Available Abstract Background Considering that sunflower production is expanding to arid regions, tolerance to abiotic stresses as drought, low temperatures and salinity arises as one of the main constrains nowadays. Differential organ-specific sunflower ESTs (expressed sequence tags were previously generated by a subtractive hybridization method that included a considerable number of putative abiotic stress associated sequences. The objective of this work is to analyze concerted gene expression profiles of organ-specific ESTs by fluorescence microarray assay, in response to high sodium chloride concentration and chilling treatments with the aim to identify and follow up candidate genes for early responses to abiotic stress in sunflower. Results Abiotic-related expressed genes were the target of this characterization through a gene expression analysis using an organ-specific cDNA fluorescence microarray approach in response to high salinity and low temperatures. The experiment included three independent replicates from leaf samples. We analyzed 317 unigenes previously isolated from differential organ-specific cDNA libraries from leaf, stem and flower at R1 and R4 developmental stage. A statistical analysis based on mean comparison by ANOVA and ordination by Principal Component Analysis allowed the detection of 80 candidate genes for either salinity and/or chilling stresses. Out of them, 50 genes were up or down regulated under both stresses, supporting common regulatory mechanisms and general responses to chilling and salinity. Interestingly 15 and 12 sequences were up regulated or down regulated specifically in one stress but not in the other, respectively. These genes are potentially involved in different regulatory mechanisms including transcription/translation/protein degradation/protein folding/ROS production or ROS-scavenging. Differential gene expression patterns were confirmed by qRT-PCR for 12.5% of the microarray candidate sequences. Conclusion

  16. Transcriptome sequencing of the Microarray Quality Control (MAQC RNA reference samples using next generation sequencing

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    Thierry-Mieg Danielle

    2009-06-01

    Full Text Available Abstract Background Transcriptome sequencing using next-generation sequencing platforms will soon be competing with DNA microarray technologies for global gene expression analysis. As a preliminary evaluation of these promising technologies, we performed deep sequencing of cDNA synthesized from the Microarray Quality Control (MAQC reference RNA samples using Roche's 454 Genome Sequencer FLX. Results We generated more that 3.6 million sequence reads of average length 250 bp for the MAQC A and B samples and introduced a data analysis pipeline for translating cDNA read counts into gene expression levels. Using BLAST, 90% of the reads mapped to the human genome and 64% of the reads mapped to the RefSeq database of well annotated genes with e-values ≤ 10-20. We measured gene expression levels in the A and B samples by counting the numbers of reads that mapped to individual RefSeq genes in multiple sequencing runs to evaluate the MAQC quality metrics for reproducibility, sensitivity, specificity, and accuracy and compared the results with DNA microarrays and Quantitative RT-PCR (QRTPCR from the MAQC studies. In addition, 88% of the reads were successfully aligned directly to the human genome using the AceView alignment programs with an average 90% sequence similarity to identify 137,899 unique exon junctions, including 22,193 new exon junctions not yet contained in the RefSeq database. Conclusion Using the MAQC metrics for evaluating the performance of gene expression platforms, the ExpressSeq results for gene expression levels showed excellent reproducibility, sensitivity, and specificity that improved systematically with increasing shotgun sequencing depth, and quantitative accuracy that was comparable to DNA microarrays and QRTPCR. In addition, a careful mapping of the reads to the genome using the AceView alignment programs shed new light on the complexity of the human transcriptome including the discovery of thousands of new splice variants.

  17. A flexible whole-genome microarray for transcriptomics in three-spine stickleback (Gasterosteus aculeatus

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    Primmer Craig R

    2009-09-01

    Full Text Available Abstract Background The use of microarray technology for describing changes in mRNA expression to address ecological and evolutionary questions is becoming increasingly popular. Since three-spine stickleback are an important ecological and evolutionary model-species as well as an emerging model for eco-toxicology, the ability to have a functional and flexible microarray platform for transcriptome studies will greatly enhance the research potential in these areas. Results We designed 43,392 unique oligonucleotide probes representing 19,274 genes (93% of the estimated total gene number, and tested the hybridization performance of both DNA and RNA from different populations to determine the efficacy of probe design for transcriptome analysis using the Agilent array platform. The majority of probes were functional as evidenced by the DNA hybridization success, and 30,946 probes (14,615 genes had a signal that was significantly above background for RNA isolated from liver tissue. Genes identified as being expressed in liver tissue were grouped into functional categories for each of the three Gene Ontology groups: biological process, molecular function, and cellular component. As expected, the highest proportions of functional categories belonged to those associated with metabolic functions: metabolic process, binding, catabolism, and organelles. Conclusion The probe and microarray design presented here provides an important step facilitating transcriptomics research for this important research organism by providing a set of over 43,000 probes whose hybridization success and specificity to liver expression has been demonstrated. Probes can easily be added or removed from the current design to tailor the array to specific experiments and additional flexibility lies in the ability to perform either one-color or two-color hybridizations.

  18. Design, construction and validation of a Plasmodium vivax microarray for the transcriptome profiling of clinical isolates

    KAUST Repository

    Boopathi, Pon Arunachalam

    2016-10-09

    High density oligonucleotide microarrays have been used on Plasmodium vivax field isolates to estimate whole genome expression. However, no microarray platform has been experimentally optimized for studying the transcriptome of field isolates. In the present study, we adopted both bioinformatics and experimental testing approaches to select best optimized probes suitable for detecting parasite transcripts from field samples and included them in designing a custom 15K P. vivax microarray. This microarray has long oligonucleotide probes (60 mer) that were in-situ synthesized onto glass slides using Agilent SurePrint technology and has been developed into an 8X15K format (8 identical arrays on a single slide). Probes in this array were experimentally validated and represents 4180 P. vivax genes in sense orientation, of which 1219 genes have also probes in antisense orientation. Validation of the 15K array by using field samples (n =14) has shown 99% of parasite transcript detection from any of the samples. Correlation analysis between duplicate probes (n = 85) present in the arrays showed perfect correlation (r(2) = 0.98) indicating the reproducibility. Multiple probes representing the same gene exhibited similar kind of expression pattern across the samples (positive correlation, r >= 0.6). Comparison of hybridization data with the previous studies and quantitative real-time PCR experiments were performed to highlight the microarray validation procedure. This array is unique in its design, and results indicate that the array is sensitive and reproducible. Hence, this microarray could be a valuable functional genomics tool to generate reliable expression data from P. vivax field isolates. (C) 2016 Published by Elsevier B.V.

  19. Design, construction and validation of a Plasmodium vivax microarray for the transcriptome profiling of clinical isolates

    KAUST Repository

    Boopathi, Pon Arunachalam; Subudhi, Amit; Middha, Sheetal; Acharya, Jyoti; Mugasimangalam, Raja Chinnadurai; Kochar, Sanjay Kumar; Kochar, Dhanpat Kumar; Das, Ashis

    2016-01-01

    High density oligonucleotide microarrays have been used on Plasmodium vivax field isolates to estimate whole genome expression. However, no microarray platform has been experimentally optimized for studying the transcriptome of field isolates. In the present study, we adopted both bioinformatics and experimental testing approaches to select best optimized probes suitable for detecting parasite transcripts from field samples and included them in designing a custom 15K P. vivax microarray. This microarray has long oligonucleotide probes (60 mer) that were in-situ synthesized onto glass slides using Agilent SurePrint technology and has been developed into an 8X15K format (8 identical arrays on a single slide). Probes in this array were experimentally validated and represents 4180 P. vivax genes in sense orientation, of which 1219 genes have also probes in antisense orientation. Validation of the 15K array by using field samples (n =14) has shown 99% of parasite transcript detection from any of the samples. Correlation analysis between duplicate probes (n = 85) present in the arrays showed perfect correlation (r(2) = 0.98) indicating the reproducibility. Multiple probes representing the same gene exhibited similar kind of expression pattern across the samples (positive correlation, r >= 0.6). Comparison of hybridization data with the previous studies and quantitative real-time PCR experiments were performed to highlight the microarray validation procedure. This array is unique in its design, and results indicate that the array is sensitive and reproducible. Hence, this microarray could be a valuable functional genomics tool to generate reliable expression data from P. vivax field isolates. (C) 2016 Published by Elsevier B.V.

  20. Microarray-mediated transcriptome analysis of the tributyltin (TBT)-resistant bacterium Pseudomonas aeruginosa 25W in the presence of TBT.

    Science.gov (United States)

    Dubey, Santosh K; Tokashiki, Tsutomu; Suzuki, Satoru

    2006-04-01

    The tributyltin (TBT)-resistant bacterium, Pseudomonas aeruginosa 25W, which was isolated in seawater from the Arabian Sea, was subjected to transcriptome analysis in the presence of high concentrations of TBT. Only slight effects were observed at TBT concentration of 50 microM, but exposure to 500 microM resulted in the upregulation of 6 genes and the downregulation of 75. Among the 75 downregulated genes, 53% (40 out of 75) were of hypothetical function, followed by 14 transcriptional regulation- and translation-associated genes. The results of this study indicated that although the 25W strain was highly resistant to TBT, high concentrations of TBT result in toxic effect on the transcriptional and translational levels. The target genes likely belong to a specific category of transcription- and translation-associated genes rather than to other gene categories.

  1. A trispecies Aspergillus microarray: Comparative transcriptomics of three Aspergillus species

    DEFF Research Database (Denmark)

    Andersen, Mikael Rørdam; Vongsangnak, Wanwipa; Panagiotou, Gianni

    2008-01-01

    The full-genome sequencing of the filamentous fungi Aspergillus nidulans, Aspergillus niger, and Aspergillus oryzae has opened possibilities for studying the cellular physiology of these fungi on a systemic level. As a tool to explore this, we are making available an Affymetrix GeneChip developed...... data identified 23 genes to be a conserved response across Aspergillus sp., including the xylose transcriptional activator XlnR. A promoter analysis of the up-regulated genes in all three species indicates the conserved XInR-binding site to be 5'-GGNTAAA-3'. The composition of the conserved gene......-set suggests that xylose acts as a molecule, indicating the presence of complex carbohydrates such as hemicellulose, and triggers an array of degrading enzymes. With this case example, we present a validated tool for transcriptome analysis of three Aspergillus species and a methodology for conducting cross...

  2. Microarray analysis in the archaeon Halobacterium salinarum strain R1.

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    Jens Twellmeyer

    Full Text Available BACKGROUND: Phototrophy of the extremely halophilic archaeon Halobacterium salinarum was explored for decades. The research was mainly focused on the expression of bacteriorhodopsin and its functional properties. In contrast, less is known about genome wide transcriptional changes and their impact on the physiological adaptation to phototrophy. The tool of choice to record transcriptional profiles is the DNA microarray technique. However, the technique is still rarely used for transcriptome analysis in archaea. METHODOLOGY/PRINCIPAL FINDINGS: We developed a whole-genome DNA microarray based on our sequence data of the Hbt. salinarum strain R1 genome. The potential of our tool is exemplified by the comparison of cells growing under aerobic and phototrophic conditions, respectively. We processed the raw fluorescence data by several stringent filtering steps and a subsequent MAANOVA analysis. The study revealed a lot of transcriptional differences between the two cell states. We found that the transcriptional changes were relatively weak, though significant. Finally, the DNA microarray data were independently verified by a real-time PCR analysis. CONCLUSION/SIGNIFICANCE: This is the first DNA microarray analysis of Hbt. salinarum cells that were actually grown under phototrophic conditions. By comparing the transcriptomics data with current knowledge we could show that our DNA microarray tool is well applicable for transcriptome analysis in the extremely halophilic archaeon Hbt. salinarum. The reliability of our tool is based on both the high-quality array of DNA probes and the stringent data handling including MAANOVA analysis. Among the regulated genes more than 50% had unknown functions. This underlines the fact that haloarchaeal phototrophy is still far away from being completely understood. Hence, the data recorded in this study will be subject to future systems biology analysis.

  3. Cell cycle, apoptosis, cellular uptake and whole-transcriptome microarray gene expression analysis of HeLa cells treated with a ruthenium(II)-arene complex with an isoquinoline-3-carboxylic acid ligand.

    Science.gov (United States)

    Jovanović, Katarina K; Tanić, Miljana; Ivanović, Ivanka; Gligorijević, Nevenka; Dojčinović, Biljana P; Radulović, Siniša

    2016-10-01

    Ruthenium(II)-arene complexes are promising drug candidates for the therapy of solid tumors. In previous work, seven new compounds of the general formula [Ru(η 6 -p-cymene)(L 1-7 )Cl] were synthesized and characterized, of which the complex with L=isoquinoline-3-carboxylic acid (RuT 7 ) was two times as active on HeLa cells compared to normal cell line MRC-5, as indicated by IC 50 values determined after 48h of incubation (45.4±3.0 vs. 84.2±5.7μM, respectively). In the present study, cell cycle analysis of HeLa cells treated with RuT 7 showed S phase arrest and an increase in sub-G1 population. The apoptotic potential of the title compound was confirmed with the Annexin V-FITC/PI assay together with a morphological evaluation of cells using fluorescent microscopy. Analysis of the intracellular accumulation of ruthenium showed 8.9ng Ru/10 6 cells after 6h of incubation. To gain further insight in the molecular mechanism of action of RuT 7 on HeLa cells, a whole-transcriptome microarray gene expression analysis was performed. Analysis of functional categories and signaling and biochemical pathways associated with the response of HeLa cells to treatment with RuT 7 showed that it leads the cells through the intrinsic (mitochondrial) apoptotic pathway, via indirect DNA damage due to the action of reactive oxygen species, and through direct DNA binding of RuT 7 . Statistical analysis for enrichment of gene sets associated with known drug-induced toxicities identified fewer associated toxicity profiles in RuT 7 -treated cells compared to cisplatin treatment. Altogether these results provide the basis for further development of RuT 7 in animal and pre-clinical studies as a potential drug candidate. Copyright © 2016 Elsevier Inc. All rights reserved.

  4. The EADGENE Microarray Data Analysis Workshop

    DEFF Research Database (Denmark)

    de Koning, Dirk-Jan; Jaffrézic, Florence; Lund, Mogens Sandø

    2007-01-01

    Microarray analyses have become an important tool in animal genomics. While their use is becoming widespread, there is still a lot of ongoing research regarding the analysis of microarray data. In the context of a European Network of Excellence, 31 researchers representing 14 research groups from...... 10 countries performed and discussed the statistical analyses of real and simulated 2-colour microarray data that were distributed among participants. The real data consisted of 48 microarrays from a disease challenge experiment in dairy cattle, while the simulated data consisted of 10 microarrays...... statistical weights, to omitting a large number of spots or omitting entire slides. Surprisingly, these very different approaches gave quite similar results when applied to the simulated data, although not all participating groups analysed both real and simulated data. The workshop was very successful...

  5. A comparison of the Giardia lamblia trophozoite and cyst transcriptome using microarrays

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    Widmer Giovanni

    2011-05-01

    Full Text Available Abstract Background Compared with many protists, Giardia lamblia has a simple life cycle alternating between cyst and trophozoite. Most research on the molecular biology of Giardia parasites has focused on trophozoites and the processes of excystation and encystation, whereas cysts have attracted less interest. The striking morphological differences between the dormant cyst and the rapidly dividing and motile trophozoite implies profound changes in the metabolism as the parasite encysts in the host's intestine and excysts upon ingestion by a new host. Results To investigate the magnitude of the transcriptional changes occurring during the G. lamblia life cycle we compared the transcriptome of G. lamblia trophozoites and cysts using single-color oligonucleotide microarrays. Cysts were found to possess a much smaller transcriptome, both in terms of mRNA diversity and abundance. Genes encoding proteins related to ribosomal functions are highly over-represented. The comparison of the transcriptome of cysts generated in culture or extracted from feces revealed little overlap, raising the possibility of significant biological differences between the two types of cysts. Conclusions The comparison of the G. lamblia cyst and trophozoite transcriptome showed that transcripts of most genes are present at a lower level in cysts. This global view of the cyst and trophozoite transcriptome complements studies focused on the expression of selected genes during trophozoite multiplication, encystation and excystation.

  6. Metric learning for DNA microarray data analysis

    International Nuclear Information System (INIS)

    Takeuchi, Ichiro; Nakagawa, Masao; Seto, Masao

    2009-01-01

    In many microarray studies, gene set selection is an important preliminary step for subsequent main task such as tumor classification, cancer subtype identification, etc. In this paper, we investigate the possibility of using metric learning as an alternative to gene set selection. We develop a simple metric learning algorithm aiming to use it for microarray data analysis. Exploiting a property of the algorithm, we introduce a novel approach for extending the metric learning to be adaptive. We apply the algorithm to previously studied microarray data on malignant lymphoma subtype identification.

  7. IsoGeneGUI : Multiple approaches for dose-response analysis of microarray data using R

    NARCIS (Netherlands)

    Otava, Martin; Sengupta, Rudradev; Shkedy, Ziv; Lin, Dan; Pramana, Setia; Verbeke, Tobias; Haldermans, Philippe; Hothorn, Ludwig A.; Gerhard, Daniel; Kuiper, Rebecca M.; Klinglmueller, Florian; Kasim, Adetayo

    2017-01-01

    The analysis of transcriptomic experiments with ordered covariates, such as dose-response data, has become a central topic in bioinformatics, in particular in omics studies. Consequently, multiple R packages on CRAN and Bioconductor are designed to analyse microarray data from various perspectives

  8. Cross-platform analysis of cancer microarray data improves gene expression based classification of phenotypes

    Directory of Open Access Journals (Sweden)

    Eils Roland

    2005-11-01

    Full Text Available Abstract Background The extensive use of DNA microarray technology in the characterization of the cell transcriptome is leading to an ever increasing amount of microarray data from cancer studies. Although similar questions for the same type of cancer are addressed in these different studies, a comparative analysis of their results is hampered by the use of heterogeneous microarray platforms and analysis methods. Results In contrast to a meta-analysis approach where results of different studies are combined on an interpretative level, we investigate here how to directly integrate raw microarray data from different studies for the purpose of supervised classification analysis. We use median rank scores and quantile discretization to derive numerically comparable measures of gene expression from different platforms. These transformed data are then used for training of classifiers based on support vector machines. We apply this approach to six publicly available cancer microarray gene expression data sets, which consist of three pairs of studies, each examining the same type of cancer, i.e. breast cancer, prostate cancer or acute myeloid leukemia. For each pair, one study was performed by means of cDNA microarrays and the other by means of oligonucleotide microarrays. In each pair, high classification accuracies (> 85% were achieved with training and testing on data instances randomly chosen from both data sets in a cross-validation analysis. To exemplify the potential of this cross-platform classification analysis, we use two leukemia microarray data sets to show that important genes with regard to the biology of leukemia are selected in an integrated analysis, which are missed in either single-set analysis. Conclusion Cross-platform classification of multiple cancer microarray data sets yields discriminative gene expression signatures that are found and validated on a large number of microarray samples, generated by different laboratories and

  9. Genomotyping of Pseudomonas putida strains using P. putida KT2440-based high-density DNA microarrays: Implications for transcriptomics studies

    NARCIS (Netherlands)

    Ballerstedt, H.; Volkers, R.J.M.; Mars, A.E.; Hallsworth, J.E.; Santos, V.A.M.D.; Puchalka, J.; Duuren, J. van; Eggink, G.; Timmis, K.N.; Bont, J.A.M. de; Wery, J.

    2007-01-01

    Pseudomonas putida KT2440 is the only fully sequenced P. putida strain. Thus, for transcriptomics and proteomics studies with other P. putida strains, the P. putida KT2440 genomic database serves as standard reference. The utility of KT2440 whole-genome, high-density oligonucleotide microarrays for

  10. Changes in the peripheral blood transcriptome associated with occupational benzene exposure identified by cross-comparison on two microarray platforms

    Energy Technology Data Exchange (ETDEWEB)

    McHale, Cliona M.; Zhang, Luoping; Lan, Qing; Li, Guilan; Hubbard, Alan E.; Forrest, Matthew S.; Vermeulen, Roel; Chen, Jinsong; Shen, Min; Rappaport, Stephen M.; Yin, Songnian; Smith, Martyn T.; Rothman, Nathaniel

    2009-03-01

    Benzene is an established cause of leukemia and a possible cause of lymphoma in humans but the molecular pathways underlying this remain largely undetermined. This study sought to determine if the use of two different microarray platforms could identify robust global gene expression and pathway changes associated with occupational benzene exposure in the peripheral blood mononuclear cell (PBMC) gene expression of a population of shoe-factory workers with well-characterized occupational exposures to benzene. Microarray data was analyzed by a robust t-test using a Quantile Transformation (QT) approach. Differential expression of 2692 genes using the Affymetrix platform and 1828 genes using the Illumina platform was found. While the overall concordance in genes identified as significantly associated with benzene exposure between the two platforms was 26% (475 genes), the most significant genes identified by either array were more likely to be ranked as significant by the other platform (Illumina = 64%, Affymetrix = 58%). Expression ratios were similar among the concordant genes (mean difference in expression ratio = 0.04, standard deviation = 0.17). Four genes (CXCL16, ZNF331, JUN and PF4), which we previously identified by microarray and confirmed by real-time PCR, were identified by both platforms in the current study and were among the top 100 genes. Gene Ontology analysis showed over representation of genes involved in apoptosis among the concordant genes while Ingenuity{reg_sign} Pathway Analysis (IPA) identified pathways related to lipid metabolism. Using a two-platform approach allows for robust changes in the PBMC transcriptome of benzene-exposed individuals to be identified.

  11. Principles of gene microarray data analysis.

    Science.gov (United States)

    Mocellin, Simone; Rossi, Carlo Riccardo

    2007-01-01

    The development of several gene expression profiling methods, such as comparative genomic hybridization (CGH), differential display, serial analysis of gene expression (SAGE), and gene microarray, together with the sequencing of the human genome, has provided an opportunity to monitor and investigate the complex cascade of molecular events leading to tumor development and progression. The availability of such large amounts of information has shifted the attention of scientists towards a nonreductionist approach to biological phenomena. High throughput technologies can be used to follow changing patterns of gene expression over time. Among them, gene microarray has become prominent because it is easier to use, does not require large-scale DNA sequencing, and allows for the parallel quantification of thousands of genes from multiple samples. Gene microarray technology is rapidly spreading worldwide and has the potential to drastically change the therapeutic approach to patients affected with tumor. Therefore, it is of paramount importance for both researchers and clinicians to know the principles underlying the analysis of the huge amount of data generated with microarray technology.

  12. Tissue Microarray Analysis Applied to Bone Diagenesis

    OpenAIRE

    Barrios Mello, Rafael; Regis Silva, Maria Regina; Seixas Alves, Maria Teresa; Evison, Martin; Guimarães, Marco Aurélio; Francisco, Rafaella Arrabaça; Dias Astolphi, Rafael; Miazato Iwamura, Edna Sadayo

    2017-01-01

    Taphonomic processes affecting bone post mortem are important in forensic, archaeological and palaeontological investigations. In this study, the application of tissue microarray (TMA) analysis to a sample of femoral bone specimens from 20 exhumed individuals of known period of burial and age at death is described. TMA allows multiplexing of subsamples, permitting standardized comparative analysis of adjacent sections in 3-D and of representative cross-sections of a large number of specimens....

  13. The Porcelain Crab Transcriptome and PCAD, the Porcelain Crab Microarray and Sequence Database

    Energy Technology Data Exchange (ETDEWEB)

    Tagmount, Abderrahmane; Wang, Mei; Lindquist, Erika; Tanaka, Yoshihiro; Teranishi, Kristen S.; Sunagawa, Shinichi; Wong, Mike; Stillman, Jonathon H.

    2010-01-27

    Background: With the emergence of a completed genome sequence of the freshwater crustacean Daphnia pulex, construction of genomic-scale sequence databases for additional crustacean sequences are important for comparative genomics and annotation. Porcelain crabs, genus Petrolisthes, have been powerful crustacean models for environmental and evolutionary physiology with respect to thermal adaptation and understanding responses of marine organisms to climate change. Here, we present a large-scale EST sequencing and cDNA microarray database project for the porcelain crab Petrolisthes cinctipes. Methodology/Principal Findings: A set of ~;;30K unique sequences (UniSeqs) representing ~;;19K clusters were generated from ~;;98K high quality ESTs from a set of tissue specific non-normalized and mixed-tissue normalized cDNA libraries from the porcelain crab Petrolisthes cinctipes. Homology for each UniSeq was assessed using BLAST, InterProScan, GO and KEGG database searches. Approximately 66percent of the UniSeqs had homology in at least one of the databases. All EST and UniSeq sequences along with annotation results and coordinated cDNA microarray datasets have been made publicly accessible at the Porcelain Crab Array Database (PCAD), a feature-enriched version of the Stanford and Longhorn Array Databases.Conclusions/Significance: The EST project presented here represents the third largest sequencing effort for any crustacean, and the largest effort for any crab species. Our assembly and clustering results suggest that our porcelain crab EST data set is equally diverse to the much larger EST set generated in the Daphnia pulex genome sequencing project, and thus will be an important resource to the Daphnia research community. Our homology results support the pancrustacea hypothesis and suggest that Malacostraca may be ancestral to Branchiopoda and Hexapoda. Our results also suggest that our cDNA microarrays cover as much of the transcriptome as can reasonably be captured in

  14. Transcriptome sequencing and comparative transcriptome analysis of the scleroglucan producer Sclerotium rolfsii

    Directory of Open Access Journals (Sweden)

    Stahl Ulf

    2010-05-01

    Full Text Available Abstract Background The plant pathogenic basidiomycete Sclerotium rolfsii produces the industrially exploited exopolysaccharide scleroglucan, a polymer that consists of (1 → 3-β-linked glucose with a (1 → 6-β-glycosyl branch on every third unit. Although the physicochemical properties of scleroglucan are well understood, almost nothing is known about the genetics of scleroglucan biosynthesis. Similarly, the biosynthetic pathway of oxalate, the main by-product during scleroglucan production, has not been elucidated yet. In order to provide a basis for genetic and metabolic engineering approaches, we studied scleroglucan and oxalate biosynthesis in S. rolfsii using different transcriptomic approaches. Results Two S. rolfsii transcriptomes obtained from scleroglucan-producing and scleroglucan-nonproducing conditions were pooled and sequenced using the 454 pyrosequencing technique yielding ~350,000 reads. These could be assembled into 21,937 contigs and 171,833 singletons, for which 6,951 had significant matches in public protein data bases. Sequence data were used to obtain first insights into the genomics of scleroglucan and oxalate production and to predict putative proteins involved in the synthesis of both metabolites. Using comparative transcriptomics, namely Agilent microarray hybridization and suppression subtractive hybridization, we identified ~800 unigenes which are differently expressed under scleroglucan-producing and non-producing conditions. From these, candidate genes were identified which could represent potential leads for targeted modification of the S. rolfsii metabolism for increased scleroglucan yields. Conclusions The results presented in this paper provide for the first time genomic and transcriptomic data about S. rolfsii and demonstrate the power and usefulness of combined transcriptome sequencing and comparative microarray analysis. The data obtained allowed us to predict the biosynthetic pathways of scleroglucan and

  15. Microarray Я US: a user-friendly graphical interface to Bioconductor tools that enables accurate microarray data analysis and expedites comprehensive functional analysis of microarray results.

    Science.gov (United States)

    Dai, Yilin; Guo, Ling; Li, Meng; Chen, Yi-Bu

    2012-06-08

    Microarray data analysis presents a significant challenge to researchers who are unable to use the powerful Bioconductor and its numerous tools due to their lack of knowledge of R language. Among the few existing software programs that offer a graphic user interface to Bioconductor packages, none have implemented a comprehensive strategy to address the accuracy and reliability issue of microarray data analysis due to the well known probe design problems associated with many widely used microarray chips. There is also a lack of tools that would expedite the functional analysis of microarray results. We present Microarray Я US, an R-based graphical user interface that implements over a dozen popular Bioconductor packages to offer researchers a streamlined workflow for routine differential microarray expression data analysis without the need to learn R language. In order to enable a more accurate analysis and interpretation of microarray data, we incorporated the latest custom probe re-definition and re-annotation for Affymetrix and Illumina chips. A versatile microarray results output utility tool was also implemented for easy and fast generation of input files for over 20 of the most widely used functional analysis software programs. Coupled with a well-designed user interface, Microarray Я US leverages cutting edge Bioconductor packages for researchers with no knowledge in R language. It also enables a more reliable and accurate microarray data analysis and expedites downstream functional analysis of microarray results.

  16. Microarray-Based Gene Expression Analysis for Veterinary Pathologists: A Review.

    Science.gov (United States)

    Raddatz, Barbara B; Spitzbarth, Ingo; Matheis, Katja A; Kalkuhl, Arno; Deschl, Ulrich; Baumgärtner, Wolfgang; Ulrich, Reiner

    2017-09-01

    High-throughput, genome-wide transcriptome analysis is now commonly used in all fields of life science research and is on the cusp of medical and veterinary diagnostic application. Transcriptomic methods such as microarrays and next-generation sequencing generate enormous amounts of data. The pathogenetic expertise acquired from understanding of general pathology provides veterinary pathologists with a profound background, which is essential in translating transcriptomic data into meaningful biological knowledge, thereby leading to a better understanding of underlying disease mechanisms. The scientific literature concerning high-throughput data-mining techniques usually addresses mathematicians or computer scientists as the target audience. In contrast, the present review provides the reader with a clear and systematic basis from a veterinary pathologist's perspective. Therefore, the aims are (1) to introduce the reader to the necessary methodological background; (2) to introduce the sequential steps commonly performed in a microarray analysis including quality control, annotation, normalization, selection of differentially expressed genes, clustering, gene ontology and pathway analysis, analysis of manually selected genes, and biomarker discovery; and (3) to provide references to publically available and user-friendly software suites. In summary, the data analysis methods presented within this review will enable veterinary pathologists to analyze high-throughput transcriptome data obtained from their own experiments, supplemental data that accompany scientific publications, or public repositories in order to obtain a more in-depth insight into underlying disease mechanisms.

  17. Removing Batch Effects from Longitudinal Gene Expression - Quantile Normalization Plus ComBat as Best Approach for Microarray Transcriptome Data.

    Directory of Open Access Journals (Sweden)

    Christian Müller

    Full Text Available Technical variation plays an important role in microarray-based gene expression studies, and batch effects explain a large proportion of this noise. It is therefore mandatory to eliminate technical variation while maintaining biological variability. Several strategies have been proposed for the removal of batch effects, although they have not been evaluated in large-scale longitudinal gene expression data. In this study, we aimed at identifying a suitable method for batch effect removal in a large study of microarray-based longitudinal gene expression. Monocytic gene expression was measured in 1092 participants of the Gutenberg Health Study at baseline and 5-year follow up. Replicates of selected samples were measured at both time points to identify technical variability. Deming regression, Passing-Bablok regression, linear mixed models, non-linear models as well as ReplicateRUV and ComBat were applied to eliminate batch effects between replicates. In a second step, quantile normalization prior to batch effect correction was performed for each method. Technical variation between batches was evaluated by principal component analysis. Associations between body mass index and transcriptomes were calculated before and after batch removal. Results from association analyses were compared to evaluate maintenance of biological variability. Quantile normalization, separately performed in each batch, combined with ComBat successfully reduced batch effects and maintained biological variability. ReplicateRUV performed perfectly in the replicate data subset of the study, but failed when applied to all samples. All other methods did not substantially reduce batch effects in the replicate data subset. Quantile normalization plus ComBat appears to be a valuable approach for batch correction in longitudinal gene expression data.

  18. Extended -Regular Sequence for Automated Analysis of Microarray Images

    Directory of Open Access Journals (Sweden)

    Jin Hee-Jeong

    2006-01-01

    Full Text Available Microarray study enables us to obtain hundreds of thousands of expressions of genes or genotypes at once, and it is an indispensable technology for genome research. The first step is the analysis of scanned microarray images. This is the most important procedure for obtaining biologically reliable data. Currently most microarray image processing systems require burdensome manual block/spot indexing work. Since the amount of experimental data is increasing very quickly, automated microarray image analysis software becomes important. In this paper, we propose two automated methods for analyzing microarray images. First, we propose the extended -regular sequence to index blocks and spots, which enables a novel automatic gridding procedure. Second, we provide a methodology, hierarchical metagrid alignment, to allow reliable and efficient batch processing for a set of microarray images. Experimental results show that the proposed methods are more reliable and convenient than the commercial tools.

  19. Microarray BASICA: Background Adjustment, Segmentation, Image Compression and Analysis of Microarray Images

    Directory of Open Access Journals (Sweden)

    Jianping Hua

    2004-01-01

    Full Text Available This paper presents microarray BASICA: an integrated image processing tool for background adjustment, segmentation, image compression, and analysis of cDNA microarray images. BASICA uses a fast Mann-Whitney test-based algorithm to segment cDNA microarray images, and performs postprocessing to eliminate the segmentation irregularities. The segmentation results, along with the foreground and background intensities obtained with the background adjustment, are then used for independent compression of the foreground and background. We introduce a new distortion measurement for cDNA microarray image compression and devise a coding scheme by modifying the embedded block coding with optimized truncation (EBCOT algorithm (Taubman, 2000 to achieve optimal rate-distortion performance in lossy coding while still maintaining outstanding lossless compression performance. Experimental results show that the bit rate required to ensure sufficiently accurate gene expression measurement varies and depends on the quality of cDNA microarray images. For homogeneously hybridized cDNA microarray images, BASICA is able to provide from a bit rate as low as 5 bpp the gene expression data that are 99% in agreement with those of the original 32 bpp images.

  20. Xylella fastidiosa gene expression analysis by DNA microarrays

    Directory of Open Access Journals (Sweden)

    Regiane F. Travensolo

    2009-01-01

    Full Text Available Xylella fastidiosa genome sequencing has generated valuable data by identifying genes acting either on metabolic pathways or in associated pathogenicity and virulence. Based on available information on these genes, new strategies for studying their expression patterns, such as microarray technology, were employed. A total of 2,600 primer pairs were synthesized and then used to generate fragments using the PCR technique. The arrays were hybridized against cDNAs labeled during reverse transcription reactions and which were obtained from bacteria grown under two different conditions (liquid XDM2 and liquid BCYE. All data were statistically analyzed to verify which genes were differentially expressed. In addition to exploring conditions for X. fastidiosa genome-wide transcriptome analysis, the present work observed the differential expression of several classes of genes (energy, protein, amino acid and nucleotide metabolism, transport, degradation of substances, toxins and hypothetical proteins, among others. The understanding of expressed genes in these two different media will be useful in comprehending the metabolic characteristics of X. fastidiosa, and in evaluating how important certain genes are for the functioning and survival of these bacteria in plants.

  1. Tissue Microarray Analysis Applied to Bone Diagenesis.

    Science.gov (United States)

    Mello, Rafael Barrios; Silva, Maria Regina Regis; Alves, Maria Teresa Seixas; Evison, Martin Paul; Guimarães, Marco Aurelio; Francisco, Rafaella Arrabaca; Astolphi, Rafael Dias; Iwamura, Edna Sadayo Miazato

    2017-01-04

    Taphonomic processes affecting bone post mortem are important in forensic, archaeological and palaeontological investigations. In this study, the application of tissue microarray (TMA) analysis to a sample of femoral bone specimens from 20 exhumed individuals of known period of burial and age at death is described. TMA allows multiplexing of subsamples, permitting standardized comparative analysis of adjacent sections in 3-D and of representative cross-sections of a large number of specimens. Standard hematoxylin and eosin, periodic acid-Schiff and silver methenamine, and picrosirius red staining, and CD31 and CD34 immunohistochemistry were applied to TMA sections. Osteocyte and osteocyte lacuna counts, percent bone matrix loss, and fungal spheroid element counts could be measured and collagen fibre bundles observed in all specimens. Decalcification with 7% nitric acid proceeded more rapidly than with 0.5 M EDTA and may offer better preservation of histological and cellular structure. No endothelial cells could be detected using CD31 and CD34 immunohistochemistry. Correlation between osteocytes per lacuna and age at death may reflect reported age-related responses to microdamage. Methodological limitations and caveats, and results of the TMA analysis of post mortem diagenesis in bone are discussed, and implications for DNA survival and recovery considered.

  2. TRAM (Transcriptome Mapper: database-driven creation and analysis of transcriptome maps from multiple sources

    Directory of Open Access Journals (Sweden)

    Danieli Gian

    2011-02-01

    Full Text Available Abstract Background Several tools have been developed to perform global gene expression profile data analysis, to search for specific chromosomal regions whose features meet defined criteria as well as to study neighbouring gene expression. However, most of these tools are tailored for a specific use in a particular context (e.g. they are species-specific, or limited to a particular data format and they typically accept only gene lists as input. Results TRAM (Transcriptome Mapper is a new general tool that allows the simple generation and analysis of quantitative transcriptome maps, starting from any source listing gene expression values for a given gene set (e.g. expression microarrays, implemented as a relational database. It includes a parser able to assign univocal and updated gene symbols to gene identifiers from different data sources. Moreover, TRAM is able to perform intra-sample and inter-sample data normalization, including an original variant of quantile normalization (scaled quantile, useful to normalize data from platforms with highly different numbers of investigated genes. When in 'Map' mode, the software generates a quantitative representation of the transcriptome of a sample (or of a pool of samples and identifies if segments of defined lengths are over/under-expressed compared to the desired threshold. When in 'Cluster' mode, the software searches for a set of over/under-expressed consecutive genes. Statistical significance for all results is calculated with respect to genes localized on the same chromosome or to all genome genes. Transcriptome maps, showing differential expression between two sample groups, relative to two different biological conditions, may be easily generated. We present the results of a biological model test, based on a meta-analysis comparison between a sample pool of human CD34+ hematopoietic progenitor cells and a sample pool of megakaryocytic cells. Biologically relevant chromosomal segments and gene

  3. DNA microarray unravels rapid changes in transcriptome of MK-801 treated rat brain

    Science.gov (United States)

    Kobayashi, Yuka; Kulikova, Sofya P; Shibato, Junko; Rakwal, Randeep; Satoh, Hiroyuki; Pinault, Didier; Masuo, Yoshinori

    2015-01-01

    AIM: To investigate the impact of MK-801 on gene expression patterns genome wide in rat brain regions. METHODS: Rats were treated with an intraperitoneal injection of MK-801 [0.08 (low-dose) and 0.16 (high-dose) mg/kg] or NaCl (vehicle control). In a first series of experiment, the frontoparietal electrocorticogram was recorded 15 min before and 60 min after injection. In a second series of experiments, the whole brain of each animal was rapidly removed at 40 min post-injection, and different regions were separated: amygdala, cerebral cortex, hippocampus, hypothalamus, midbrain and ventral striatum on ice followed by DNA microarray (4 × 44 K whole rat genome chip) analysis. RESULTS: Spectral analysis revealed that a single systemic injection of MK-801 significantly and selectively augmented the power of baseline gamma frequency (30-80 Hz) oscillations in the frontoparietal electroencephalogram. DNA microarray analysis showed the largest number (up- and down- regulations) of gene expressions in the cerebral cortex (378), midbrain (376), hippocampus (375), ventral striatum (353), amygdala (301), and hypothalamus (201) under low-dose (0.08 mg/kg) of MK-801. Under high-dose (0.16 mg/kg), ventral striatum (811) showed the largest number of gene expression changes. Gene expression changes were functionally categorized to reveal expression of genes and function varies with each brain region. CONCLUSION: Acute MK-801 treatment increases synchrony of baseline gamma oscillations, and causes very early changes in gene expressions in six individual rat brain regions, a first report. PMID:26629322

  4. Design of oligonucleotides for microarrays and perspectives for design of multi-transcriptome arrays

    DEFF Research Database (Denmark)

    Nielsen, Henrik Bjørn; Wernersson, Rasmus; Knudsen, Steen

    2003-01-01

    with an overview of these parameters. We present here a flexible tool named OligoWiz for designing oligonucleotides for multiple purposes. OligoWiz presents a set of parameter scores in a graphical interface to facilitate an overview for the user. Additional custom parameter scores can easily be added......Optimal design of oligonucleotides for microarrays involves tedious and laborious work evaluating potential oligonucleotides relative to a series of parameters. The currently available tools for this purpose are limited in their flexibility and do not present the oligonucleotide designer...... to the program to extend the default parameters: homology, DeltaTm, low-complexity, position and GATC-only. Furthermore we present an analysis of the limitations in designing oligonucleotide sets that can detect transcripts from multiple organisms. OligoWiz is available at www.cbs.dtu.dk/services/OligoWiz/....

  5. Reproducibility of oligonucleotide microarray transcriptome analyses - An interlaboratory comparison using chemostat cultures of Saccharomyces cerevisiae

    DEFF Research Database (Denmark)

    Piper, M.D.W.; Daran-Lapujade, P.; Bro, Christoffer

    2002-01-01

    . In each of the laboratories, three independent replicate cultures were grown aerobically as well as anaerobically. Although variations introduced by in vitro handling steps were small and unbiased, greater variation from replicate cultures underscored that, to obtain reliable information, experimental...... replication is essential. Under aerobic conditions, 86% of the most highly expressed yeast genes showed an average intra-laboratory coefficient of variation of 0.23. This is significantly lower than previously reported for shake-flask-culture transcriptome analyses and probably reflects the strict control...... of growth conditions in chemostats. Using the triplicate data sets and appropriate statistical analysis, the change calls from anaerobic versus aerobic comparisons yielded an over 95% agreement between the laboratories for transcripts that changed by over 2-fold, leaving only a small fraction of genes...

  6. EST and microarray analysis of horn development in Onthophagus beetles

    Directory of Open Access Journals (Sweden)

    Tang Zuojian

    2009-10-01

    Full Text Available Abstract Background The origin of novel traits and their subsequent diversification represent central themes in evo-devo and evolutionary ecology. Here we explore the genetic and genomic basis of a class of traits that is both novel and highly diverse, in a group of organisms that is ecologically complex and experimentally tractable: horned beetles. Results We developed two high quality, normalized cDNA libraries for larval and pupal Onthophagus taurus and sequenced 3,488 ESTs that assembled into 451 contigs and 2,330 singletons. We present the annotation and a comparative analysis of the conservation of the sequences. Microarrays developed from the combined libraries were then used to contrast the transcriptome of developing primordia of head horns, prothoracic horns, and legs. Our experiments identify a first comprehensive list of candidate genes for the evolution and diversification of beetle horns. We find that developing horns and legs show many similarities as well as important differences in their transcription profiles, suggesting that the origin of horns was mediated partly, but not entirely, by the recruitment of genes involved in the formation of more traditional appendages such as legs. Furthermore, we find that horns developing from the head and prothorax differ in their transcription profiles to a degree that suggests that head and prothoracic horns are not serial homologs, but instead may have evolved independently from each other. Conclusion We have laid the foundation for a systematic analysis of the genetic basis of horned beetle development and diversification with the potential to contribute significantly to several major frontiers in evolutionary developmental biology.

  7. Gene Expression Analysis Using Agilent DNA Microarrays

    DEFF Research Database (Denmark)

    Stangegaard, Michael

    2009-01-01

    Hybridization of labeled cDNA to microarrays is an intuitively simple and a vastly underestimated process. If it is not performed, optimized, and standardized with the same attention to detail as e.g., RNA amplification, information may be overlooked or even lost. Careful balancing of the amount ...

  8. Insights into the iron and sulfur energetic metabolism of Acidithiobacillus ferrooxidans by microarray transcriptome profiling

    Energy Technology Data Exchange (ETDEWEB)

    R. Quatrini; C. Appia-Ayme; Y. Denis; J. Ratouchniak; F. Veloso; J. Valdes; C. Lefimil; S. Silver; F. Roberto; O. Orellana; F. Denizot; E. Jedlicki; D. Holmes; V. Bonnefoy

    2006-09-01

    Acidithiobacillus ferrooxidans is a well known acidophilic, chemolithoautotrophic, Gram negative, bacterium involved in bioleaching and acid mine drainage. In aerobic conditions, it gains energy mainly from the oxidation of ferrous iron and/or reduced sulfur compounds present in ores. After initial oxidation of the substrate, electrons from ferrous iron or sulfur enter respiratory chains and are transported through several redox proteins to oxygen. However, the oxidation of ferrous iron and reduced sulfur compounds has also to provide electrons for the reduction of NAD(P) that is subsequently required for many metabolic processes including CO2 fixation. To help to unravel the enzymatic pathways and the electron transfer chains involved in these processes, a genome-wide microarray transcript profiling analysis was carried out. Oligonucleotides corresponding to approximately 3000 genes of the A. ferrooxidans type strain ATCC23270 were spotted onto glass-slides and hybridized with cDNA retrotranscribed from RNA extracted from ferrous iron and sulfur grown cells. The genes which are preferentially transcribed in ferrous iron conditions and those preferentially transcribed in sulfur conditions were analyzed. The expression of a substantial number of these genes has been validated by real-time PCR, Northern blot hybridization and/or immunodetection analysis. Our results support and extend certain models of iron and sulfur oxidation and highlight previous observations regarding the possible presence of alternate electron pathways. Our findings also suggest ways in which iron and sulfur oxidation may be co-ordinately regulated. An accompanying paper (Appia-Ayme et al.) describes results pertaining to other metabolic functions.

  9. Advanced spot quality analysis in two-colour microarray experiments

    Directory of Open Access Journals (Sweden)

    Vetter Guillaume

    2008-09-01

    Full Text Available Abstract Background Image analysis of microarrays and, in particular, spot quantification and spot quality control, is one of the most important steps in statistical analysis of microarray data. Recent methods of spot quality control are still in early age of development, often leading to underestimation of true positive microarray features and, consequently, to loss of important biological information. Therefore, improving and standardizing the statistical approaches of spot quality control are essential to facilitate the overall analysis of microarray data and subsequent extraction of biological information. Findings We evaluated the performance of two image analysis packages MAIA and GenePix (GP using two complementary experimental approaches with a focus on the statistical analysis of spot quality factors. First, we developed control microarrays with a priori known fluorescence ratios to verify the accuracy and precision of the ratio estimation of signal intensities. Next, we developed advanced semi-automatic protocols of spot quality evaluation in MAIA and GP and compared their performance with available facilities of spot quantitative filtering in GP. We evaluated these algorithms for standardised spot quality analysis in a whole-genome microarray experiment assessing well-characterised transcriptional modifications induced by the transcription regulator SNAI1. Using a set of RT-PCR or qRT-PCR validated microarray data, we found that the semi-automatic protocol of spot quality control we developed with MAIA allowed recovering approximately 13% more spots and 38% more differentially expressed genes (at FDR = 5% than GP with default spot filtering conditions. Conclusion Careful control of spot quality characteristics with advanced spot quality evaluation can significantly increase the amount of confident and accurate data resulting in more meaningful biological conclusions.

  10. AMDA: an R package for the automated microarray data analysis

    Directory of Open Access Journals (Sweden)

    Foti Maria

    2006-07-01

    Full Text Available Abstract Background Microarrays are routinely used to assess mRNA transcript levels on a genome-wide scale. Large amount of microarray datasets are now available in several databases, and new experiments are constantly being performed. In spite of this fact, few and limited tools exist for quickly and easily analyzing the results. Microarray analysis can be challenging for researchers without the necessary training and it can be time-consuming for service providers with many users. Results To address these problems we have developed an automated microarray data analysis (AMDA software, which provides scientists with an easy and integrated system for the analysis of Affymetrix microarray experiments. AMDA is free and it is available as an R package. It is based on the Bioconductor project that provides a number of powerful bioinformatics and microarray analysis tools. This automated pipeline integrates different functions available in the R and Bioconductor projects with newly developed functions. AMDA covers all of the steps, performing a full data analysis, including image analysis, quality controls, normalization, selection of differentially expressed genes, clustering, correspondence analysis and functional evaluation. Finally a LaTEX document is dynamically generated depending on the performed analysis steps. The generated report contains comments and analysis results as well as the references to several files for a deeper investigation. Conclusion AMDA is freely available as an R package under the GPL license. The package as well as an example analysis report can be downloaded in the Services/Bioinformatics section of the Genopolis http://www.genopolis.it/

  11. Bystander effect: Biological endpoints and microarray analysis

    Energy Technology Data Exchange (ETDEWEB)

    Chaudhry, M. Ahmad [Department of Medical Laboratory and Radiation Sciences, College of Nursing and Health Sciences, University of Vermont, 302 Rowell Building, Burlington, VT 05405 (United States) and DNA Microarray Facility, University of Vermont, Burlington, VT 05405 (United States)]. E-mail: mchaudhr@uvm.edu

    2006-05-11

    In cell populations exposed to ionizing radiation, the biological effects occur in a much larger proportion of cells than are estimated to be traversed by radiation. It has been suggested that irradiated cells are capable of providing signals to the neighboring unirradiated cells resulting in damage to these cells. This phenomenon is termed the bystander effect. The bystander effect induces persistent, long-term, transmissible changes that result in delayed death and neoplastic transformation. Because the bystander effect is relevant to carcinogenesis, it could have significant implications for risk estimation for radiation exposure. The nature of the bystander effect signal and how it impacts the unirradiated cells remains to be elucidated. Examination of the changes in gene expression could provide clues to understanding the bystander effect and could define the signaling pathways involved in sustaining damage to these cells. The microarray technology serves as a tool to gain insight into the molecular pathways leading to bystander effect. Using medium from irradiated normal human diploid lung fibroblasts as a model system we examined gene expression alterations in bystander cells. The microarray data revealed that the radiation-induced gene expression profile in irradiated cells is different from unirradiated bystander cells suggesting that the pathways leading to biological effects in the bystander cells are different from the directly irradiated cells. The genes known to be responsive to ionizing radiation were observed in irradiated cells. Several genes were upregulated in cells receiving media from irradiated cells. Surprisingly no genes were found to be downregulated in these cells. A number of genes belonging to extracellular signaling, growth factors and several receptors were identified in bystander cells. Interestingly 15 genes involved in the cell communication processes were found to be upregulated. The induction of receptors and the cell

  12. Bystander effect: Biological endpoints and microarray analysis

    International Nuclear Information System (INIS)

    Chaudhry, M. Ahmad

    2006-01-01

    In cell populations exposed to ionizing radiation, the biological effects occur in a much larger proportion of cells than are estimated to be traversed by radiation. It has been suggested that irradiated cells are capable of providing signals to the neighboring unirradiated cells resulting in damage to these cells. This phenomenon is termed the bystander effect. The bystander effect induces persistent, long-term, transmissible changes that result in delayed death and neoplastic transformation. Because the bystander effect is relevant to carcinogenesis, it could have significant implications for risk estimation for radiation exposure. The nature of the bystander effect signal and how it impacts the unirradiated cells remains to be elucidated. Examination of the changes in gene expression could provide clues to understanding the bystander effect and could define the signaling pathways involved in sustaining damage to these cells. The microarray technology serves as a tool to gain insight into the molecular pathways leading to bystander effect. Using medium from irradiated normal human diploid lung fibroblasts as a model system we examined gene expression alterations in bystander cells. The microarray data revealed that the radiation-induced gene expression profile in irradiated cells is different from unirradiated bystander cells suggesting that the pathways leading to biological effects in the bystander cells are different from the directly irradiated cells. The genes known to be responsive to ionizing radiation were observed in irradiated cells. Several genes were upregulated in cells receiving media from irradiated cells. Surprisingly no genes were found to be downregulated in these cells. A number of genes belonging to extracellular signaling, growth factors and several receptors were identified in bystander cells. Interestingly 15 genes involved in the cell communication processes were found to be upregulated. The induction of receptors and the cell

  13. Gaucher disease: transcriptome analyses using microarray or mRNA sequencing in a Gba1 mutant mouse model treated with velaglucerase alfa or imiglucerase.

    Directory of Open Access Journals (Sweden)

    Nupur Dasgupta

    Full Text Available Gaucher disease type 1, an inherited lysosomal storage disorder, is caused by mutations in GBA1 leading to defective glucocerebrosidase (GCase function and consequent excess accumulation of glucosylceramide/glucosylsphingosine in visceral organs. Enzyme replacement therapy (ERT with the biosimilars, imiglucerase (imig or velaglucerase alfa (vela improves/reverses the visceral disease. Comparative transcriptomic effects (microarray and mRNA-Seq of no ERT and ERT (imig or vela were done with liver, lung, and spleen from mice having Gba1 mutant alleles, termed D409V/null. Disease-related molecular effects, dynamic ranges, and sensitivities were compared between mRNA-Seq and microarrays and their respective analytic tools, i.e. Mixed Model ANOVA (microarray, and DESeq and edgeR (mRNA-Seq. While similar gene expression patterns were observed with both platforms, mRNA-Seq identified more differentially expressed genes (DEGs (∼3-fold than the microarrays. Among the three analytic tools, DESeq identified the maximum number of DEGs for all tissues and treatments. DESeq and edgeR comparisons revealed differences in DEGs identified. In 9V/null liver, spleen and lung, post-therapy transcriptomes approximated WT, were partially reverted, and had little change, respectively, and were concordant with the corresponding histological and biochemical findings. DEG overlaps were only 8-20% between mRNA-Seq and microarray, but the biological pathways were similar. Cell growth and proliferation, cell cycle, heme metabolism, and mitochondrial dysfunction were most altered with the Gaucher disease process. Imig and vela differentially affected specific disease pathways. Differential molecular responses were observed in direct transcriptome comparisons from imig- and vela-treated tissues. These results provide cross-validation for the mRNA-Seq and microarray platforms, and show differences between the molecular effects of two highly structurally similar ERT

  14. Transcriptome

    Science.gov (United States)

    ... Also: Talking Glossary of Genetic Terms Definitions for genetic terms used on this page En Español: Transcriptoma Transcriptome What is a transcriptome? What can a transcriptome tell us? How can transcriptome data be used to explore gene function? What is ...

  15. How does exposure to nickel and cadmium affect the transcriptome of yellow perch (Perca flavescens) – Results from a 1000 candidate-gene microarray

    International Nuclear Information System (INIS)

    Bougas, Bérénice; Normandeau, Eric; Pierron, Fabien; Campbell, Peter G.C.; Bernatchez, Louis; Couture, Patrice

    2013-01-01

    Highlights: •The transcriptional responses of Perca flavescens to both metal and non metal stressors were measured with a 1000 candidate-gene microarray. •475, 287 and 176 genes were differentially transcribed depending on temperature, Ni and Cd concentrations, respectively. •Genes involved in iron metabolism, transcriptional and translational processes, vitamin metabolism, blood coagulation, and calcium transport were impacted by metals. •The developed microarray contributes to a better characterization of the impact of different stressors on the transcriptome. -- Abstract: The molecular mechanisms underlying nickel (Ni) and cadmium (Cd) toxicity and their specific effects on fish are poorly understood. Documenting gene transcription profiles offers a powerful approach toward identifying the molecular mechanisms affected by these metals and to discover biomarkers of their toxicity. However, confounding environmental factors can complicate the interpretation of the results and the detection of biomarkers for fish captured in their natural environment. In the present study, a 1000 candidate-gene microarray, developed from a previous RNA-seq study on a subset of individual fish from contrasting level of metal contamination, was used to investigate the transcriptional response to metal (Ni and Cd) and non metal (temperature, oxygen, and diet) stressors in yellow perch (Perca flavescens). Specifically, we aimed at (1) identifying transcriptional signatures specific to Ni and Cd exposure, (2) investigating the mechanisms of their toxicity, and (3) developing a predictive tool to identify the sublethal effects of Ni and Cd contaminants in fish sampled from natural environments. A total of 475 genes displayed significantly different transcription levels when temperature varied while 287 and 176 genes were differentially transcribed at different concentrations of Ni and Cd, respectively. These metals were found to mainly affect the transcription level of genes

  16. How does exposure to nickel and cadmium affect the transcriptome of yellow perch (Perca flavescens) – Results from a 1000 candidate-gene microarray

    Energy Technology Data Exchange (ETDEWEB)

    Bougas, Bérénice, E-mail: Berenice.Bougas@ete.inrs.ca [Institut National de la Recherche Scientifique, Centre INRS Eau Terre et Environnement, 490, rue de la Couronne, Québec, Québec G1K 9A9 (Canada); Département de biologie, Institut de Biologie Intégrative et des Systèmes (IBIS), Université Laval, Québec, Québec G1V 0A6 (Canada); Normandeau, Eric [Département de biologie, Institut de Biologie Intégrative et des Systèmes (IBIS), Université Laval, Québec, Québec G1V 0A6 (Canada); Pierron, Fabien [Université de Bordeaux, EPOC, UMR 5805, F-33400 Talence (France); CNRS, EPOC, UMR 5805, F-33400 Talence (France); Campbell, Peter G.C. [Institut National de la Recherche Scientifique, Centre INRS Eau Terre et Environnement, 490, rue de la Couronne, Québec, Québec G1K 9A9 (Canada); Bernatchez, Louis [Département de biologie, Institut de Biologie Intégrative et des Systèmes (IBIS), Université Laval, Québec, Québec G1V 0A6 (Canada); Couture, Patrice [Institut National de la Recherche Scientifique, Centre INRS Eau Terre et Environnement, 490, rue de la Couronne, Québec, Québec G1K 9A9 (Canada)

    2013-10-15

    Highlights: •The transcriptional responses of Perca flavescens to both metal and non metal stressors were measured with a 1000 candidate-gene microarray. •475, 287 and 176 genes were differentially transcribed depending on temperature, Ni and Cd concentrations, respectively. •Genes involved in iron metabolism, transcriptional and translational processes, vitamin metabolism, blood coagulation, and calcium transport were impacted by metals. •The developed microarray contributes to a better characterization of the impact of different stressors on the transcriptome. -- Abstract: The molecular mechanisms underlying nickel (Ni) and cadmium (Cd) toxicity and their specific effects on fish are poorly understood. Documenting gene transcription profiles offers a powerful approach toward identifying the molecular mechanisms affected by these metals and to discover biomarkers of their toxicity. However, confounding environmental factors can complicate the interpretation of the results and the detection of biomarkers for fish captured in their natural environment. In the present study, a 1000 candidate-gene microarray, developed from a previous RNA-seq study on a subset of individual fish from contrasting level of metal contamination, was used to investigate the transcriptional response to metal (Ni and Cd) and non metal (temperature, oxygen, and diet) stressors in yellow perch (Perca flavescens). Specifically, we aimed at (1) identifying transcriptional signatures specific to Ni and Cd exposure, (2) investigating the mechanisms of their toxicity, and (3) developing a predictive tool to identify the sublethal effects of Ni and Cd contaminants in fish sampled from natural environments. A total of 475 genes displayed significantly different transcription levels when temperature varied while 287 and 176 genes were differentially transcribed at different concentrations of Ni and Cd, respectively. These metals were found to mainly affect the transcription level of genes

  17. Significance analysis of lexical bias in microarray data

    Directory of Open Access Journals (Sweden)

    Falkow Stanley

    2003-04-01

    Full Text Available Abstract Background Genes that are determined to be significantly differentially regulated in microarray analyses often appear to have functional commonalities, such as being components of the same biochemical pathway. This results in certain words being under- or overrepresented in the list of genes. Distinguishing between biologically meaningful trends and artifacts of annotation and analysis procedures is of the utmost importance, as only true biological trends are of interest for further experimentation. A number of sophisticated methods for identification of significant lexical trends are currently available, but these methods are generally too cumbersome for practical use by most microarray users. Results We have developed a tool, LACK, for calculating the statistical significance of apparent lexical bias in microarray datasets. The frequency of a user-specified list of search terms in a list of genes which are differentially regulated is assessed for statistical significance by comparison to randomly generated datasets. The simplicity of the input files and user interface targets the average microarray user who wishes to have a statistical measure of apparent lexical trends in analyzed datasets without the need for bioinformatics skills. The software is available as Perl source or a Windows executable. Conclusion We have used LACK in our laboratory to generate biological hypotheses based on our microarray data. We demonstrate the program's utility using an example in which we confirm significant upregulation of SPI-2 pathogenicity island of Salmonella enterica serovar Typhimurium by the cation chelator dipyridyl.

  18. DNA microarray data and contextual analysis of correlation graphs

    Directory of Open Access Journals (Sweden)

    Hingamp Pascal

    2003-04-01

    Full Text Available Abstract Background DNA microarrays are used to produce large sets of expression measurements from which specific biological information is sought. Their analysis requires efficient and reliable algorithms for dimensional reduction, classification and annotation. Results We study networks of co-expressed genes obtained from DNA microarray experiments. The mathematical concept of curvature on graphs is used to group genes or samples into clusters to which relevant gene or sample annotations are automatically assigned. Application to publicly available yeast and human lymphoma data demonstrates the reliability of the method in spite of its simplicity, especially with respect to the small number of parameters involved. Conclusions We provide a method for automatically determining relevant gene clusters among the many genes monitored with microarrays. The automatic annotations and the graphical interface improve the readability of the data. A C++ implementation, called Trixy, is available from http://tagc.univ-mrs.fr/bioinformatics/trixy.html.

  19. GenePublisher: automated analysis of DNA microarray data

    DEFF Research Database (Denmark)

    Knudsen, Steen; Workman, Christopher; Sicheritz-Ponten, T.

    2003-01-01

    GenePublisher, a system for automatic analysis of data from DNA microarray experiments, has been implemented with a web interface at http://www.cbs.dtu.dk/services/GenePublisher. Raw data are uploaded to the server together with aspecification of the data. The server performs normalization...

  20. Microarray analysis of the gene expression profile in triethylene ...

    African Journals Online (AJOL)

    Microarray analysis of the gene expression profile in triethylene glycol dimethacrylate-treated human dental pulp cells. ... Conclusions: Our results suggest that TEGDMA can change the many functions of hDPCs through large changes in gene expression levels and complex interactions with different signaling pathways.

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

    Directory of Open Access Journals (Sweden)

    Christine M Costello

    2005-08-01

    Full Text Available BACKGROUND: The differential pathophysiologic mechanisms that trigger and maintain the two forms of inflammatory bowel disease (IBD, Crohn disease (CD, and ulcerative colitis (UC are only partially understood. cDNA microarrays can be used to decipher gene regulation events at a genome-wide level and to identify novel unknown genes that might be involved in perpetuating inflammatory disease progression. METHODS AND FINDINGS: High-density cDNA microarrays representing 33,792 UniGene clusters were prepared. Biopsies were taken from the sigmoid colon of normal controls (n = 11, CD patients (n = 10 and UC patients (n = 10. 33P-radiolabeled cDNA from purified poly(A+ RNA extracted from biopsies (unpooled was hybridized to the arrays. We identified 500 and 272 transcripts differentially regulated in CD and UC, respectively. Interesting hits were independently verified by real-time PCR in a second sample of 100 individuals, and immunohistochemistry was used for exemplary localization. The main findings point to novel molecules important in abnormal immune regulation and the highly disturbed cell biology of colonic epithelial cells in IBD pathogenesis, e.g., CYLD (cylindromatosis, turban tumor syndrome and CDH11 (cadherin 11, type 2. By the nature of the array setup, many of the genes identified were to our knowledge previously uncharacterized, and prediction of the putative function of a subsection of these genes indicate that some could be involved in early events in disease pathophysiology. CONCLUSION: A comprehensive set of candidate genes not previously associated with IBD was revealed, which underlines the polygenic and complex nature of the disease. It points out substantial differences in pathophysiology between CD and UC. The multiple unknown genes identified may stimulate new research in the fields of barrier mechanisms and cell signalling in the context of IBD, and ultimately new therapeutic approaches.

  2. Hematopoietic Lineage Transcriptome Stability and Representation in PAXgeneTM Collected Peripheral Blood Utilising SPIA Single-Stranded cDNA Probes for Microarray

    Directory of Open Access Journals (Sweden)

    Laura Kennedy

    2008-01-01

    Full Text Available Peripheral blood as a surrogate tissue for transcriptome profiling holds great promise for the discovery of diagnostic and prognostic disease biomarkers, particularly when target tissues of disease are not readily available. To maximize the reliability of gene expression data generated from clinical blood samples, both the sample collection and the microarray probe generation methods should be optimized to provide stabilized, reproducible and representative gene expression profiles faithfully representing the transcriptional profiles of the constituent blood cell types present in the circulation. Given the increasing innovation in this field in recent years, we investigated a combination of methodological advances in both RNA stabilisation and microarray probe generation with the goal of achieving robust, reliable and representative transcriptional profiles from whole blood. To assess the whole blood profiles, the transcriptomes of purified blood cell types were measured and compared with the global transcriptomes measured in whole blood. The results demonstrate that a combination of PAXgeneTM RNA stabilising technology and single-stranded cDNA probe generation afforded by the NuGEN Ovation RNA amplification system V2TM enables an approach that yields faithful representation of specific hematopoietic cell lineage transcriptomes in whole blood without the necessity for prior sample fractionation, cell enrichment or globin reduction. Storage stability assessments of the PAXgeneTM blood samples also advocate a short, fixed room temperature storage time for all PAXgeneTM blood samples collected for the purposes of global transcriptional profiling in clinical studies.

  3. Hematopoietic Lineage Transcriptome Stability and Representation in PAXgene Collected Peripheral Blood Utilising SPIA Single-Stranded cDNA Probes for Microarray.

    Science.gov (United States)

    Kennedy, Laura; Vass, J Keith; Haggart, D Ross; Moore, Steve; Burczynski, Michael E; Crowther, Dan; Miele, Gino

    2008-08-25

    Peripheral blood as a surrogate tissue for transcriptome profiling holds great promise for the discovery of diagnostic and prognostic disease biomarkers, particularly when target tissues of disease are not readily available. To maximize the reliability of gene expression data generated from clinical blood samples, both the sample collection and the microarray probe generation methods should be optimized to provide stabilized, reproducible and representative gene expression profiles faithfully representing the transcriptional profiles of the constituent blood cell types present in the circulation. Given the increasing innovation in this field in recent years, we investigated a combination of methodological advances in both RNA stabilisation and microarray probe generation with the goal of achieving robust, reliable and representative transcriptional profiles from whole blood. To assess the whole blood profiles, the transcriptomes of purified blood cell types were measured and compared with the global transcriptomes measured in whole blood. The results demonstrate that a combination of PAXgene() RNA stabilising technology and single-stranded cDNA probe generation afforded by the NuGEN Ovation RNA amplification system V2() enables an approach that yields faithful representation of specific hematopoietic cell lineage transcriptomes in whole blood without the necessity for prior sample fractionation, cell enrichment or globin reduction. Storage stability assessments of the PAXgene() blood samples also advocate a short, fixed room temperature storage time for all PAXgene() blood samples collected for the purposes of global transcriptional profiling in clinical studies.

  4. Hematopoietic Lineage Transcriptome Stability and Representation in PAXgene™ Collected Peripheral Blood Utilising SPIA Single-Stranded cDNA Probes for Microarray

    Science.gov (United States)

    Kennedy, Laura; Vass, J. Keith; Haggart, D. Ross; Moore, Steve; Burczynski, Michael E.; Crowther, Dan; Miele, Gino

    2008-01-01

    Peripheral blood as a surrogate tissue for transcriptome profiling holds great promise for the discovery of diagnostic and prognostic disease biomarkers, particularly when target tissues of disease are not readily available. To maximize the reliability of gene expression data generated from clinical blood samples, both the sample collection and the microarray probe generation methods should be optimized to provide stabilized, reproducible and representative gene expression profiles faithfully representing the transcriptional profiles of the constituent blood cell types present in the circulation. Given the increasing innovation in this field in recent years, we investigated a combination of methodological advances in both RNA stabilisation and microarray probe generation with the goal of achieving robust, reliable and representative transcriptional profiles from whole blood. To assess the whole blood profiles, the transcriptomes of purified blood cell types were measured and compared with the global transcriptomes measured in whole blood. The results demonstrate that a combination of PAXgene™ RNA stabilising technology and single-stranded cDNA probe generation afforded by the NuGEN Ovation RNA amplification system V2™ enables an approach that yields faithful representation of specific hematopoietic cell lineage transcriptomes in whole blood without the necessity for prior sample fractionation, cell enrichment or globin reduction. Storage stability assessments of the PAXgene™ blood samples also advocate a short, fixed room temperature storage time for all PAXgene™ blood samples collected for the purposes of global transcriptional profiling in clinical studies. PMID:19578521

  5. Integrating Biological Perspectives:. a Quantum Leap for Microarray Expression Analysis

    Science.gov (United States)

    Wanke, Dierk; Kilian, Joachim; Bloss, Ulrich; Mangelsen, Elke; Supper, Jochen; Harter, Klaus; Berendzen, Kenneth W.

    2009-02-01

    Biologists and bioinformatic scientists cope with the analysis of transcript abundance and the extraction of meaningful information from microarray expression data. By exploiting biological information accessible in public databases, we try to extend our current knowledge over the plant model organism Arabidopsis thaliana. Here, we give two examples of increasing the quality of information gained from large scale expression experiments by the integration of microarray-unrelated biological information: First, we utilize Arabidopsis microarray data to demonstrate that expression profiles are usually conserved between orthologous genes of different organisms. In an initial step of the analysis, orthology has to be inferred unambiguously, which then allows comparison of expression profiles between orthologs. We make use of the publicly available microarray expression data of Arabidopsis and barley, Hordeum vulgare. We found a generally positive correlation in expression trajectories between true orthologs although both organisms are only distantly related in evolutionary time scale. Second, extracting clusters of co-regulated genes implies similarities in transcriptional regulation via similar cis-regulatory elements (CREs). Vice versa approaches, where co-regulated gene clusters are found by investigating on CREs were not successful in general. Nonetheless, in some cases the presence of CREs in a defined position, orientation or CRE-combinations is positively correlated with co-regulated gene clusters. Here, we make use of genes involved in the phenylpropanoid biosynthetic pathway, to give one positive example for this approach.

  6. Transcriptome analysis of monocyte-HIV interactions

    Directory of Open Access Journals (Sweden)

    Tran Huyen

    2010-06-01

    /macrophage dysfunction is involved may only now be emerging or remain yet to be discovered, in particular in view of the limited number of studies focussing on the monocyte response to ART 32. In order to generate novel hypotheses rather than test pre-existing ones in the context of monocyte-HIV interactions, we performed a transcriptome analysis on monocyte samples from patients in different stages of HIV infection and/or combination ART treatment, using a parallel approach of genome-wide microarray analysis and focused gene expression profiling to identify broad areas of monocyte dysfunction and to pinpoint genes which are potentially involved in one or several of these dysfunctions. In particular the factors which are exploited by the monocyte/macrophage to communicate with and/or modulate other immune cells were of interest, as they represent a particularly relevant population 3334 which is a primary target for intervention.

  7. Global meta-analysis of transcriptomics studies.

    Directory of Open Access Journals (Sweden)

    José Caldas

    Full Text Available Transcriptomics meta-analysis aims at re-using existing data to derive novel biological hypotheses, and is motivated by the public availability of a large number of independent studies. Current methods are based on breaking down studies into multiple comparisons between phenotypes (e.g. disease vs. healthy, based on the studies' experimental designs, followed by computing the overlap between the resulting differential expression signatures. While useful, in this methodology each study yields multiple independent phenotype comparisons, and connections are established not between studies, but rather between subsets of the studies corresponding to phenotype comparisons. We propose a rank-based statistical meta-analysis framework that establishes global connections between transcriptomics studies without breaking down studies into sets of phenotype comparisons. By using a rank product method, our framework extracts global features from each study, corresponding to genes that are consistently among the most expressed or differentially expressed genes in that study. Those features are then statistically modelled via a term-frequency inverse-document frequency (TF-IDF model, which is then used for connecting studies. Our framework is fast and parameter-free; when applied to large collections of Homo sapiens and Streptococcus pneumoniae transcriptomics studies, it performs better than similarity-based approaches in retrieving related studies, using a Medical Subject Headings gold standard. Finally, we highlight via case studies how the framework can be used to derive novel biological hypotheses regarding related studies and the genes that drive those connections. Our proposed statistical framework shows that it is possible to perform a meta-analysis of transcriptomics studies with arbitrary experimental designs by deriving global expression features rather than decomposing studies into multiple phenotype comparisons.

  8. A strand-specific RNA-Seq analysis of the transcriptome of the typhoid bacillus Salmonella typhi.

    Directory of Open Access Journals (Sweden)

    Timothy T Perkins

    2009-07-01

    Full Text Available High-density, strand-specific cDNA sequencing (ssRNA-seq was used to analyze the transcriptome of Salmonella enterica serovar Typhi (S. Typhi. By mapping sequence data to the entire S. Typhi genome, we analyzed the transcriptome in a strand-specific manner and further defined transcribed regions encoded within prophages, pseudogenes, previously un-annotated, and 3'- or 5'-untranslated regions (UTR. An additional 40 novel candidate non-coding RNAs were identified beyond those previously annotated. Proteomic analysis was combined with transcriptome data to confirm and refine the annotation of a number of hpothetical genes. ssRNA-seq was also combined with microarray and proteome analysis to further define the S. Typhi OmpR regulon and identify novel OmpR regulated transcripts. Thus, ssRNA-seq provides a novel and powerful approach to the characterization of the bacterial transcriptome.

  9. A comprehensive hybridization model allows whole HERV transcriptome profiling using high density microarray.

    Science.gov (United States)

    Becker, Jérémie; Pérot, Philippe; Cheynet, Valérie; Oriol, Guy; Mugnier, Nathalie; Mommert, Marine; Tabone, Olivier; Textoris, Julien; Veyrieras, Jean-Baptiste; Mallet, François

    2017-04-08

    Human endogenous retroviruses (HERVs) have received much attention for their implications in the etiology of many human diseases and their profound effect on evolution. Notably, recent studies have highlighted associations between HERVs expression and cancers (Yu et al., Int J Mol Med 32, 2013), autoimmunity (Balada et al., Int Rev Immunol 29:351-370, 2010) and neurological (Christensen, J Neuroimmune Pharmacol 5:326-335, 2010) conditions. Their repetitive nature makes their study particularly challenging, where expression studies have largely focused on individual loci (De Parseval et al., J Virol 77:10414-10422, 2003) or general trends within families (Forsman et al., J Virol Methods 129:16-30, 2005; Seifarth et al., J Virol 79:341-352, 2005; Pichon et al., Nucleic Acids Res 34:e46, 2006). To refine our understanding of HERVs activity, we introduce here a new microarray, HERV-V3. This work was made possible by the careful detection and annotation of genomic HERV/MaLR sequences as well as the development of a new hybridization model, allowing the optimization of probe performances and the control of cross-reactions. RESULTS: HERV-V3 offers an almost complete coverage of HERVs and their ancestors (mammalian apparent LTR-retrotransposons, MaLRs) at the locus level along with four other repertoires (active LINE-1 elements, lncRNA, a selection of 1559 human genes and common infectious viruses). We demonstrate that HERV-V3 analytical performances are comparable with commercial Affymetrix arrays, and that for a selection of tissue/pathological specific loci, the patterns of expression measured on HERV-V3 is consistent with those reported in the literature. Given its large HERVs/MaLRs coverage and additional repertoires, HERV-V3 opens the door to multiple applications such as enhancers and alternative promoters identification, biomarkers identification as well as the characterization of genes and HERVs/MaLRs modulation caused by viral infection.

  10. Unraveling the rat blood genome-wide transcriptome after oral administration of lavender oil by a two-color dye-swap DNA microarray approach

    Directory of Open Access Journals (Sweden)

    Motohide Hori

    2016-06-01

    Full Text Available Lavender oil (LO is a commonly used essential oil in aromatherapy as non-traditional medicine. With an aim to demonstrate LO effects on the body, we have recently established an animal model investigating the influence of orally administered LO in rat tissues, genome-wide. In this brief, we investigate the effect of LO ingestion in the blood of rat. Rats were administered LO at usual therapeutic dose (5 mg/kg in humans, and following collection of the venous blood from the heart and extraction of total RNA, the differentially expressed genes were screened using a 4 × 44-K whole-genome rat chip (Agilent microarray platform; Agilent Technologies, Palo Alto, CA, USA in conjunction with a two-color dye-swap approach. A total of 834 differentially expressed genes in the blood were identified: 362 up-regulated and 472 down-regulated. These genes were functionally categorized using bioinformatics tools. The gene expression inventory of rat blood transcriptome under LO, a first report, has been deposited into the Gene Expression Omnibus (GEO: GSE67499. The data will be a valuable resource in examining the effects of natural products, and which could also serve as a human model for further functional analysis and investigation.

  11. Microarray Analysis of Late Response to Boron Toxicity in Barley (Hordeum vulgare L.) Leaves

    NARCIS (Netherlands)

    Oz, M.T.; Yilmaz, R.; Eyidogan, F.; Graaff, de L.H.; Yucel, M.; Oktem, H.A.

    2009-01-01

    DNA microarrays, being high-density and high-throughput, allow quantitative analyses of thousands of genes and their expression patterns in parallel. In this study, Barley1 GereChip was used to investigate transcriptome changes associated with boron (B) toxicity in a sensitive barley cultivar

  12. Bioinformatics and Microarray Data Analysis on the Cloud.

    Science.gov (United States)

    Calabrese, Barbara; Cannataro, Mario

    2016-01-01

    High-throughput platforms such as microarray, mass spectrometry, and next-generation sequencing are producing an increasing volume of omics data that needs large data storage and computing power. Cloud computing offers massive scalable computing and storage, data sharing, on-demand anytime and anywhere access to resources and applications, and thus, it may represent the key technology for facing those issues. In fact, in the recent years it has been adopted for the deployment of different bioinformatics solutions and services both in academia and in the industry. Although this, cloud computing presents several issues regarding the security and privacy of data, that are particularly important when analyzing patients data, such as in personalized medicine. This chapter reviews main academic and industrial cloud-based bioinformatics solutions; with a special focus on microarray data analysis solutions and underlines main issues and problems related to the use of such platforms for the storage and analysis of patients data.

  13. Microarray Analysis of the Developing Rat Mandible

    Institute of Scientific and Technical Information of China (English)

    Hideo KABURAGI; Naoyuki SUGANO; Maiko OSHIKAWA; Ryosuke KOSHI; Naoki SENDA; Kazuhiro KAWAMOTO; Koichi ITO

    2007-01-01

    To analyze the molecular events that occur in the developing mandible, we examined the expression of 8803 genes from samples taken at different time points during rat postnatal mandible development.Total RNA was extracted from the mandibles of 1-day-old, 1-week-old, and 2-week-old rats. Complementary RNA (cRNA) was synthesized from cDNA and biotinylated. Fragmented cRNA was hybridized to RGU34A GeneChip arrays. Among the 8803 genes tested, 4344 were detectable. We identified 148 genes with significantly increased expression, and 19 genes with significantly decreased expression. A comprehensive analysis appears to be an effective method of studying the complex process of development.

  14. MAGMA: analysis of two-channel microarrays made easy.

    Science.gov (United States)

    Rehrauer, Hubert; Zoller, Stefan; Schlapbach, Ralph

    2007-07-01

    The web application MAGMA provides a simple and intuitive interface to identify differentially expressed genes from two-channel microarray data. While the underlying algorithms are not superior to those of similar web applications, MAGMA is particularly user friendly and can be used without prior training. The user interface guides the novice user through the most typical microarray analysis workflow consisting of data upload, annotation, normalization and statistical analysis. It automatically generates R-scripts that document MAGMA's entire data processing steps, thereby allowing the user to regenerate all results in his local R installation. The implementation of MAGMA follows the model-view-controller design pattern that strictly separates the R-based statistical data processing, the web-representation and the application logic. This modular design makes the application flexible and easily extendible by experts in one of the fields: statistical microarray analysis, web design or software development. State-of-the-art Java Server Faces technology was used to generate the web interface and to perform user input processing. MAGMA's object-oriented modular framework makes it easily extendible and applicable to other fields and demonstrates that modern Java technology is also suitable for rather small and concise academic projects. MAGMA is freely available at www.magma-fgcz.uzh.ch.

  15. Microarray analysis of gene expression profiles in ripening pineapple fruits.

    Science.gov (United States)

    Koia, Jonni H; Moyle, Richard L; Botella, Jose R

    2012-12-18

    Pineapple (Ananas comosus) is a tropical fruit crop of significant commercial importance. Although the physiological changes that occur during pineapple fruit development have been well characterized, little is known about the molecular events that occur during the fruit ripening process. Understanding the molecular basis of pineapple fruit ripening will aid the development of new varieties via molecular breeding or genetic modification. In this study we developed a 9277 element pineapple microarray and used it to profile gene expression changes that occur during pineapple fruit ripening. Microarray analyses identified 271 unique cDNAs differentially expressed at least 1.5-fold between the mature green and mature yellow stages of pineapple fruit ripening. Among these 271 sequences, 184 share significant homology with genes encoding proteins of known function, 53 share homology with genes encoding proteins of unknown function and 34 share no significant homology with any database accession. Of the 237 pineapple sequences with homologs, 160 were up-regulated and 77 were down-regulated during pineapple fruit ripening. DAVID Functional Annotation Cluster (FAC) analysis of all 237 sequences with homologs revealed confident enrichment scores for redox activity, organic acid metabolism, metalloenzyme activity, glycolysis, vitamin C biosynthesis, antioxidant activity and cysteine peptidase activity, indicating the functional significance and importance of these processes and pathways during pineapple fruit development. Quantitative real-time PCR analysis validated the microarray expression results for nine out of ten genes tested. This is the first report of a microarray based gene expression study undertaken in pineapple. Our bioinformatic analyses of the transcript profiles have identified a number of genes, processes and pathways with putative involvement in the pineapple fruit ripening process. This study extends our knowledge of the molecular basis of pineapple fruit

  16. Colorectal cancer stages transcriptome analysis.

    Directory of Open Access Journals (Sweden)

    Tianyao Huo

    Full Text Available Colorectal cancer (CRC is the third most common cancer and the second leading cause of cancer-related deaths in the United States. The purpose of this study was to evaluate the gene expression differences in different stages of CRC. Gene expression data on 433 CRC patient samples were obtained from The Cancer Genome Atlas (TCGA. Gene expression differences were evaluated across CRC stages using linear regression. Genes with p≤0.001 in expression differences were evaluated further in principal component analysis and genes with p≤0.0001 were evaluated further in gene set enrichment analysis. A total of 377 patients with gene expression data in 20,532 genes were included in the final analysis. The numbers of patients in stage I through IV were 59, 147, 116 and 55, respectively. NEK4 gene, which encodes for NIMA related kinase 4, was differentially expressed across the four stages of CRC. The stage I patients had the highest expression of NEK4 genes, while the stage IV patients had the lowest expressions (p = 9*10-6. Ten other genes (RNF34, HIST3H2BB, NUDT6, LRCh4, GLB1L, HIST2H4A, TMEM79, AMIGO2, C20orf135 and SPSB3 had p value of 0.0001 in the differential expression analysis. Principal component analysis indicated that the patients from the 4 clinical stages do not appear to have distinct gene expression pattern. Network-based and pathway-based gene set enrichment analyses showed that these 11 genes map to multiple pathways such as meiotic synapsis and packaging of telomere ends, etc. Ten of these 11 genes were linked to Gene Ontology terms such as nucleosome, DNA packaging complex and protein-DNA interactions. The protein complex-based gene set analysis showed that four genes were involved in H2AX complex II. This study identified a small number of genes that might be associated with clinical stages of CRC. Our analysis was not able to find a molecular basis for the current clinical staging for CRC based on the gene expression patterns.

  17. Transcriptomic analysis reveals ethylene as stimulator and auxin as regulator of adventitious root formation in petunia cuttings

    OpenAIRE

    Druege, Uwe; Franken, Philipp; Lischewski, Sandra; Ahkami, Amir H.; Zerche, Siegfried; Hause, Bettina; Hajirezaei, Mohammad R.

    2014-01-01

    Adventitious root (AR) formation in the stem base of cuttings is the basis for propagation of many plant species and petunia is used as model to study this developmental process. Following AR formation from 2 to 192 hours after excision (hpe) of cuttings, transcriptome analysis by microarray revealed a change of the character of the rooting zone from stem base to root identity. The greatest shift in the number of differentially expressed genes was observed between 24 and 72 hpe, when the cate...

  18. DNA microarray analysis of fim mutations in Escherichia coli

    DEFF Research Database (Denmark)

    Schembri, Mark; Ussery, David; Workman, Christopher

    2002-01-01

    Bacterial adhesion is often mediated by complex polymeric surface structures referred to as fimbriae. Type I fimbriae of Escherichia coli represent the archetypical and best characterised fimbrial system. These adhesive organelles mediate binding to D-mannose and are directly associated...... we have used DNA microarray analysis to examine the molecular events involved in response to fimbrial gene expression in E. coli K-12. Observed differential expression levels of the fim genes were in good agreement with our current knowledge of the stoichiometry of type I fimbriae. Changes in fim...

  19. Supervised group Lasso with applications to microarray data analysis

    Directory of Open Access Journals (Sweden)

    Huang Jian

    2007-02-01

    Full Text Available Abstract Background A tremendous amount of efforts have been devoted to identifying genes for diagnosis and prognosis of diseases using microarray gene expression data. It has been demonstrated that gene expression data have cluster structure, where the clusters consist of co-regulated genes which tend to have coordinated functions. However, most available statistical methods for gene selection do not take into consideration the cluster structure. Results We propose a supervised group Lasso approach that takes into account the cluster structure in gene expression data for gene selection and predictive model building. For gene expression data without biological cluster information, we first divide genes into clusters using the K-means approach and determine the optimal number of clusters using the Gap method. The supervised group Lasso consists of two steps. In the first step, we identify important genes within each cluster using the Lasso method. In the second step, we select important clusters using the group Lasso. Tuning parameters are determined using V-fold cross validation at both steps to allow for further flexibility. Prediction performance is evaluated using leave-one-out cross validation. We apply the proposed method to disease classification and survival analysis with microarray data. Conclusion We analyze four microarray data sets using the proposed approach: two cancer data sets with binary cancer occurrence as outcomes and two lymphoma data sets with survival outcomes. The results show that the proposed approach is capable of identifying a small number of influential gene clusters and important genes within those clusters, and has better prediction performance than existing methods.

  20. DNA Microarray Data Analysis: A Novel Biclustering Algorithm Approach

    Directory of Open Access Journals (Sweden)

    Tewfik Ahmed H

    2006-01-01

    Full Text Available Biclustering algorithms refer to a distinct class of clustering algorithms that perform simultaneous row-column clustering. Biclustering problems arise in DNA microarray data analysis, collaborative filtering, market research, information retrieval, text mining, electoral trends, exchange analysis, and so forth. When dealing with DNA microarray experimental data for example, the goal of biclustering algorithms is to find submatrices, that is, subgroups of genes and subgroups of conditions, where the genes exhibit highly correlated activities for every condition. In this study, we develop novel biclustering algorithms using basic linear algebra and arithmetic tools. The proposed biclustering algorithms can be used to search for all biclusters with constant values, biclusters with constant values on rows, biclusters with constant values on columns, and biclusters with coherent values from a set of data in a timely manner and without solving any optimization problem. We also show how one of the proposed biclustering algorithms can be adapted to identify biclusters with coherent evolution. The algorithms developed in this study discover all valid biclusters of each type, while almost all previous biclustering approaches will miss some.

  1. Integrative analysis of metabolomics and transcriptomics data

    DEFF Research Database (Denmark)

    Brink-Jensen, Kasper; Bak, Søren; Jørgensen, Kirsten

    2013-01-01

    ) measurements from the same samples, to identify genes controlling the production of metabolites. Due to the high dimensionality of both LC-MS and DNA microarray data, dimension reduction and variable selection are key elements of the analysis. Our proposed approach starts by identifying the basis functions......The abundance of high-dimensional measurements in the form of gene expression and mass spectroscopy calls for models to elucidate the underlying biological system. For widely studied organisms like yeast, it is possible to incorporate prior knowledge from a variety of databases, an approach used...... ("building blocks") that constitute the output from a mass spectrometry experiment. Subsequently, the weights of these basis functions are related to the observations from the corresponding gene expression data in order to identify which genes are associated with specific patterns seen in the metabolite data...

  2. Multivariate analysis of microarray data: differential expression and differential connection.

    Science.gov (United States)

    Kiiveri, Harri T

    2011-02-01

    Typical analysis of microarray data ignores the correlation between gene expression values. In this paper we present a model for microarray data which specifically allows for correlation between genes. As a result we combine gene network ideas with linear models and differential expression. We use sparse inverse covariance matrices and their associated graphical representation to capture the notion of gene networks. An important issue in using these models is the identification of the pattern of zeroes in the inverse covariance matrix. The limitations of existing methods for doing this are discussed and we provide a workable solution for determining the zero pattern. We then consider a method for estimating the parameters in the inverse covariance matrix which is suitable for very high dimensional matrices. We also show how to construct multivariate tests of hypotheses. These overall multivariate tests can be broken down into two components, the first one being similar to tests for differential expression and the second involving the connections between genes. The methods in this paper enable the extraction of a wealth of information concerning the relationships between genes which can be conveniently represented in graphical form. Differentially expressed genes can be placed in the context of the gene network and places in the gene network where unusual or interesting patterns have emerged can be identified, leading to the formulation of hypotheses for future experimentation.

  3. Multivariate analysis of microarray data: differential expression and differential connection

    Directory of Open Access Journals (Sweden)

    Kiiveri Harri T

    2011-02-01

    Full Text Available Abstract Background Typical analysis of microarray data ignores the correlation between gene expression values. In this paper we present a model for microarray data which specifically allows for correlation between genes. As a result we combine gene network ideas with linear models and differential expression. Results We use sparse inverse covariance matrices and their associated graphical representation to capture the notion of gene networks. An important issue in using these models is the identification of the pattern of zeroes in the inverse covariance matrix. The limitations of existing methods for doing this are discussed and we provide a workable solution for determining the zero pattern. We then consider a method for estimating the parameters in the inverse covariance matrix which is suitable for very high dimensional matrices. We also show how to construct multivariate tests of hypotheses. These overall multivariate tests can be broken down into two components, the first one being similar to tests for differential expression and the second involving the connections between genes. Conclusion The methods in this paper enable the extraction of a wealth of information concerning the relationships between genes which can be conveniently represented in graphical form. Differentially expressed genes can be placed in the context of the gene network and places in the gene network where unusual or interesting patterns have emerged can be identified, leading to the formulation of hypotheses for future experimentation.

  4. Microarray analysis of toxicogenomic effects of Ortho-phenylphenol in Staphylococcus aureus

    Directory of Open Access Journals (Sweden)

    Toghrol Freshteh

    2008-09-01

    Full Text Available Abstract Background Staphylococcus aureus (S. aureus, is responsible for many infectious diseases, ranging from benign skin infections to life-threatening endocarditis and toxic shock syndrome. Ortho-phenylphenol (OPP is an antimicrobial agent and an active ingredient of EPA-registered disinfectants with wide human exposure in various agricultural, hospital and veterinary disinfectant products. Despite many uses, an understanding of a cellular response to OPP and it's mechanism of action, targeted genes, and the connectivity between targeted genes and the rest of cell metabolism remains obscure. Results Herein, we performed a genome-wide transcriptome analysis of the cellular responses of S. aureus when exposed to 0.82 mM of OPP for 20 and 60 min. Our data indicated that OPP downregulated the biosynthesis of many amino acids, which are required for protein synthesis. In particular, the genes encoding the enzymes of the diaminopimelate (DAP pathway which results in lysine biosynthesis were significantly downregualted. Intriguingly, we revealed that the transcription of genes encoding ribosomal proteins was upregulated by OPP and at the same time, the genes encoding iron acquisition and transport were downregulated. The genes encoding virulence factors were upregulated and genes encoding phospholipids were downregulated upon 20 min exposure to OPP. Conclusion By using microarray analysis that enables us to simultaneously and globally examine the complete transcriptome during cellular responses, we have revealed novel information regarding the mode of action of OPP on Staphylococcus: OPP inhibits anabolism of many amino acids and highly downregulates the genes that encode the enzymes involved in the DAP pathway. Lysine and DAP are essential for building up the peptidoglycan cell wall. It was concluded that the mode of action of OPP is similar to the mechanism of action of some antibiotics. The discovery of this phenomenon provides useful

  5. An Introduction to MAMA (Meta-Analysis of MicroArray data) System.

    Science.gov (United States)

    Zhang, Zhe; Fenstermacher, David

    2005-01-01

    Analyzing microarray data across multiple experiments has been proven advantageous. To support this kind of analysis, we are developing a software system called MAMA (Meta-Analysis of MicroArray data). MAMA utilizes a client-server architecture with a relational database on the server-side for the storage of microarray datasets collected from various resources. The client-side is an application running on the end user's computer that allows the user to manipulate microarray data and analytical results locally. MAMA implementation will integrate several analytical methods, including meta-analysis within an open-source framework offering other developers the flexibility to plug in additional statistical algorithms.

  6. A statistical framework for differential network analysis from microarray data

    Directory of Open Access Journals (Sweden)

    Datta Somnath

    2010-02-01

    Full Text Available Abstract Background It has been long well known that genes do not act alone; rather groups of genes act in consort during a biological process. Consequently, the expression levels of genes are dependent on each other. Experimental techniques to detect such interacting pairs of genes have been in place for quite some time. With the advent of microarray technology, newer computational techniques to detect such interaction or association between gene expressions are being proposed which lead to an association network. While most microarray analyses look for genes that are differentially expressed, it is of potentially greater significance to identify how entire association network structures change between two or more biological settings, say normal versus diseased cell types. Results We provide a recipe for conducting a differential analysis of networks constructed from microarray data under two experimental settings. At the core of our approach lies a connectivity score that represents the strength of genetic association or interaction between two genes. We use this score to propose formal statistical tests for each of following queries: (i whether the overall modular structures of the two networks are different, (ii whether the connectivity of a particular set of "interesting genes" has changed between the two networks, and (iii whether the connectivity of a given single gene has changed between the two networks. A number of examples of this score is provided. We carried out our method on two types of simulated data: Gaussian networks and networks based on differential equations. We show that, for appropriate choices of the connectivity scores and tuning parameters, our method works well on simulated data. We also analyze a real data set involving normal versus heavy mice and identify an interesting set of genes that may play key roles in obesity. Conclusions Examining changes in network structure can provide valuable information about the

  7. Network Analysis of Rodent Transcriptomes in Spaceflight

    Science.gov (United States)

    Ramachandran, Maya; Fogle, Homer; Costes, Sylvain

    2017-01-01

    Network analysis methods leverage prior knowledge of cellular systems and the statistical and conceptual relationships between analyte measurements to determine gene connectivity. Correlation and conditional metrics are used to infer a network topology and provide a systems-level context for cellular responses. Integration across multiple experimental conditions and omics domains can reveal the regulatory mechanisms that underlie gene expression. GeneLab has assembled rich multi-omic (transcriptomics, proteomics, epigenomics, and epitranscriptomics) datasets for multiple murine tissues from the Rodent Research 1 (RR-1) experiment. RR-1 assesses the impact of 37 days of spaceflight on gene expression across a variety of tissue types, such as adrenal glands, quadriceps, gastrocnemius, tibalius anterior, extensor digitorum longus, soleus, eye, and kidney. Network analysis is particularly useful for RR-1 -omics datasets because it reinforces subtle relationships that may be overlooked in isolated analyses and subdues confounding factors. Our objective is to use network analysis to determine potential target nodes for therapeutic intervention and identify similarities with existing disease models. Multiple network algorithms are used for a higher confidence consensus.

  8. Transcriptome Analysis of Early Responsive Genes in Rice during Magnaporthe oryzae Infection

    Directory of Open Access Journals (Sweden)

    Yiming Wang

    2014-12-01

    Full Text Available Rice blast disease caused by Magnaporthe oryzae is one of the most serious diseases of cultivated rice (Oryza sativa L. in most rice-growing regions of the world. In order to investigate early response genes in rice, we utilized the transcriptome analysis approach using a 300 K tilling microarray to rice leaves infected with compatible and incompatible M. oryzae strains. Prior to the microarray experiment, total RNA was validated by measuring the differential expression of rice defense-related marker genes (chitinase 2, barwin, PBZ1, and PR-10 by RT-PCR, and phytoalexins (sakuranetin and momilactone A with HPLC. Microarray analysis revealed that 231 genes were up-regulated (>2 fold change, p < 0.05 in the incompatible interaction compared to the compatible one. Highly expressed genes were functionally characterized into metabolic processes and oxidation-reduction categories. The oxidative stress response was induced in both early and later infection stages. Biotic stress overview from MapMan analysis revealed that the phytohormone ethylene as well as signaling molecules jasmonic acid and salicylic acid is important for defense gene regulation. WRKY and Myb transcription factors were also involved in signal transduction processes. Additionally, receptor-like kinases were more likely associated with the defense response, and their expression patterns were validated by RT-PCR. Our results suggest that candidate genes, including receptor-like protein kinases, may play a key role in disease resistance against M. oryzae attack.

  9. The application of DNA microarrays in gene expression analysis

    NARCIS (Netherlands)

    Hal, van N.L.W.; Vorst, O.; Houwelingen, van A.M.M.L.; Kok, E.J.; Peijnenburg, A.A.C.M.; Aharoni, A.; Tunen, van A.J.; Keijer, J.

    2000-01-01

    DNA microarray technology is a new and powerful technology that will substantially increase the speed of molecular biological research. This paper gives a survey of DNA microarray technology and its use in gene expression studies. The technical aspects and their potential improvements are discussed.

  10. Exon microarray analysis of human dorsolateral prefrontal cortex in alcoholism.

    Science.gov (United States)

    Manzardo, Ann M; Gunewardena, Sumedha; Wang, Kun; Butler, Merlin G

    2014-06-01

    Alcohol abuse is associated with cellular and biochemical disturbances that impact upon protein and nucleic acid synthesis, brain development, function, and behavioral responses. To further characterize the genetic influences in alcoholism and the effects of alcohol consumption on gene expression, we used a highly sensitive exon microarray to examine mRNA expression in human frontal cortex of alcoholics and control males. Messenger RNA was isolated from the dorsolateral prefrontal cortex (dlPFC; Brodmann area 9) of 7 adult alcoholic (6 males, 1 female, mean age 49 years) and 7 matched controls. Affymetrix Human Exon 1.0 ST array was performed according to standard procedures and the results analyzed at the gene level. Microarray findings were validated using quantitative reverse transcription polymerase chain reaction, and the ontology of disturbed genes characterized using Ingenuity Pathway Analysis (IPA). Decreased mRNA expression was observed for genes involved in cellular adhesion (e.g., CTNNA3, ITGA2), transport (e.g., TF, ABCA8), nervous system development (e.g., LRP2, UGT8, GLDN), and signaling (e.g., RASGRP3, LGR5) with influence over lipid and myelin synthesis (e.g., ASPA, ENPP2, KLK6). IPA identified disturbances in network functions associated with neurological disease and development including cellular assembly and organization impacting on psychological disorders. Our data in alcoholism support a reduction in expression of dlPFC mRNA for genes involved with neuronal growth, differentiation, and signaling that targets white matter of the brain. Copyright © 2014 by the Research Society on Alcoholism.

  11. A Parallel Software Pipeline for DMET Microarray Genotyping Data Analysis

    Directory of Open Access Journals (Sweden)

    Giuseppe Agapito

    2018-06-01

    Full Text Available Personalized medicine is an aspect of the P4 medicine (predictive, preventive, personalized and participatory based precisely on the customization of all medical characters of each subject. In personalized medicine, the development of medical treatments and drugs is tailored to the individual characteristics and needs of each subject, according to the study of diseases at different scales from genotype to phenotype scale. To make concrete the goal of personalized medicine, it is necessary to employ high-throughput methodologies such as Next Generation Sequencing (NGS, Genome-Wide Association Studies (GWAS, Mass Spectrometry or Microarrays, that are able to investigate a single disease from a broader perspective. A side effect of high-throughput methodologies is the massive amount of data produced for each single experiment, that poses several challenges (e.g., high execution time and required memory to bioinformatic software. Thus a main requirement of modern bioinformatic softwares, is the use of good software engineering methods and efficient programming techniques, able to face those challenges, that include the use of parallel programming and efficient and compact data structures. This paper presents the design and the experimentation of a comprehensive software pipeline, named microPipe, for the preprocessing, annotation and analysis of microarray-based Single Nucleotide Polymorphism (SNP genotyping data. A use case in pharmacogenomics is presented. The main advantages of using microPipe are: the reduction of errors that may happen when trying to make data compatible among different tools; the possibility to analyze in parallel huge datasets; the easy annotation and integration of data. microPipe is available under Creative Commons license, and is freely downloadable for academic and not-for-profit institutions.

  12. PIVOT: platform for interactive analysis and visualization of transcriptomics data.

    Science.gov (United States)

    Zhu, Qin; Fisher, Stephen A; Dueck, Hannah; Middleton, Sarah; Khaladkar, Mugdha; Kim, Junhyong

    2018-01-05

    Many R packages have been developed for transcriptome analysis but their use often requires familiarity with R and integrating results of different packages requires scripts to wrangle the datatypes. Furthermore, exploratory data analyses often generate multiple derived datasets such as data subsets or data transformations, which can be difficult to track. Here we present PIVOT, an R-based platform that wraps open source transcriptome analysis packages with a uniform user interface and graphical data management that allows non-programmers to interactively explore transcriptomics data. PIVOT supports more than 40 popular open source packages for transcriptome analysis and provides an extensive set of tools for statistical data manipulations. A graph-based visual interface is used to represent the links between derived datasets, allowing easy tracking of data versions. PIVOT further supports automatic report generation, publication-quality plots, and program/data state saving, such that all analysis can be saved, shared and reproduced. PIVOT will allow researchers with broad background to easily access sophisticated transcriptome analysis tools and interactively explore transcriptome datasets.

  13. Gene expression patterns during the larval development of European sea bass (dicentrarchus labrax) by microarray analysis.

    Science.gov (United States)

    Darias, M J; Zambonino-Infante, J L; Hugot, K; Cahu, C L; Mazurais, D

    2008-01-01

    During the larval period, marine teleosts undergo very fast growth and dramatic changes in morphology, metabolism, and behavior to accomplish their metamorphosis into juvenile fish. Regulation of gene expression is widely thought to be a key mechanism underlying the management of the biological processes required for harmonious development over this phase of life. To provide an overall analysis of gene expression in the whole body during sea bass larval development, we monitored the expression of 6,626 distinct genes at 10 different points in time between 7 and 43 days post-hatching (dph) by using heterologous hybridization of a rainbow trout cDNA microarray. The differentially expressed genes (n = 485) could be grouped into two categories: genes that were generally up-expressed early, between 7 and 23 dph, and genes up-expressed between 25 and 43 dph. Interestingly, among the genes regulated during the larval period, those related to organogenesis, energy pathways, biosynthesis, and digestion were over-represented compared with total set of analyzed genes. We discuss the quantitative regulation of whole-body contents of these specific transcripts with regard to the ontogenesis and maturation of essential functions that take place over larval development. Our study is the first utilization of a transcriptomic approach in sea bass and reveals dynamic changes in gene expression patterns in relation to marine finfish larval development.

  14. A tiling microarray for global analysis of chloroplast genome expression in cucumber and other plants

    Directory of Open Access Journals (Sweden)

    Pląder Wojciech

    2011-09-01

    Full Text Available Abstract Plastids are small organelles equipped with their own genomes (plastomes. Although these organelles are involved in numerous plant metabolic pathways, current knowledge about the transcriptional activity of plastomes is limited. To solve this problem, we constructed a plastid tiling microarray (PlasTi-microarray consisting of 1629 oligonucleotide probes. The oligonucleotides were designed based on the cucumber chloroplast genomic sequence and targeted both strands of the plastome in a non-contiguous arrangement. Up to 4 specific probes were designed for each gene/exon, and the intergenic regions were covered regularly, with 70-nt intervals. We also developed a protocol for direct chemical labeling and hybridization of as little as 2 micrograms of chloroplast RNA. We used this protocol for profiling the expression of the cucumber chloroplast plastome on the PlasTi-microarray. Owing to the high sequence similarity of plant plastomes, the newly constructed microarray can be used to study plants other than cucumber. Comparative hybridization of chloroplast transcriptomes from cucumber, Arabidopsis, tomato and spinach showed that the PlasTi-microarray is highly versatile.

  15. The application of DNA microarrays in gene expression analysis.

    Science.gov (United States)

    van Hal, N L; Vorst, O; van Houwelingen, A M; Kok, E J; Peijnenburg, A; Aharoni, A; van Tunen, A J; Keijer, J

    2000-03-31

    DNA microarray technology is a new and powerful technology that will substantially increase the speed of molecular biological research. This paper gives a survey of DNA microarray technology and its use in gene expression studies. The technical aspects and their potential improvements are discussed. These comprise array manufacturing and design, array hybridisation, scanning, and data handling. Furthermore, it is discussed how DNA microarrays can be applied in the working fields of: safety, functionality and health of food and gene discovery and pathway engineering in plants.

  16. Application of microarray analysis on computer cluster and cloud platforms.

    Science.gov (United States)

    Bernau, C; Boulesteix, A-L; Knaus, J

    2013-01-01

    Analysis of recent high-dimensional biological data tends to be computationally intensive as many common approaches such as resampling or permutation tests require the basic statistical analysis to be repeated many times. A crucial advantage of these methods is that they can be easily parallelized due to the computational independence of the resampling or permutation iterations, which has induced many statistics departments to establish their own computer clusters. An alternative is to rent computing resources in the cloud, e.g. at Amazon Web Services. In this article we analyze whether a selection of statistical projects, recently implemented at our department, can be efficiently realized on these cloud resources. Moreover, we illustrate an opportunity to combine computer cluster and cloud resources. In order to compare the efficiency of computer cluster and cloud implementations and their respective parallelizations we use microarray analysis procedures and compare their runtimes on the different platforms. Amazon Web Services provide various instance types which meet the particular needs of the different statistical projects we analyzed in this paper. Moreover, the network capacity is sufficient and the parallelization is comparable in efficiency to standard computer cluster implementations. Our results suggest that many statistical projects can be efficiently realized on cloud resources. It is important to mention, however, that workflows can change substantially as a result of a shift from computer cluster to cloud computing.

  17. Analysis of Chromothripsis by Combined FISH and Microarray Analysis.

    Science.gov (United States)

    MacKinnon, Ruth N

    2018-01-01

    Fluorescence in situ hybridization (FISH) to metaphase chromosomes, in conjunction with SNP array, array CGH, or whole genome sequencing, can help determine the organization of abnormal genomes after chromothripsis and other types of complex genome rearrangement. DNA microarrays can identify the changes in copy number, but they do not give information on the organization of the abnormal chromosomes, balanced rearrangements, or abnormalities of the centromeres and other regions comprised of highly repetitive DNA. Many of these details can be determined by the strategic use of metaphase FISH. FISH is a single-cell technique, so it can identify low-frequency chromosome abnormalities, and it can determine which chromosome abnormalities occur in the same or different clonal populations. These are important considerations in cancer. Metaphase chromosomes are intact, so information about abnormalities of the chromosome homologues is preserved. Here we describe strategies for working out the organization of highly rearranged genomes by combining SNP array data with various metaphase FISH methods. This approach can also be used to address some of the uncertainties arising from whole genome or mate-pair sequencing data.

  18. Variance estimation in the analysis of microarray data

    KAUST Repository

    Wang, Yuedong; Ma, Yanyuan; Carroll, Raymond J.

    2009-01-01

    Microarrays are one of the most widely used high throughput technologies. One of the main problems in the area is that conventional estimates of the variances that are required in the t-statistic and other statistics are unreliable owing

  19. Transcriptome analysis of the rhizosphere bacterium Azospirillum brasilense reveals an extensive auxin response.

    Science.gov (United States)

    Van Puyvelde, Sandra; Cloots, Lore; Engelen, Kristof; Das, Frederik; Marchal, Kathleen; Vanderleyden, Jos; Spaepen, Stijn

    2011-05-01

    The rhizosphere bacterium Azospirillum brasilense produces the auxin indole-3-acetic acid (IAA) through the indole-3-pyruvate pathway. As we previously demonstrated that transcription of the indole-3-pyruvate decarboxylase (ipdC) gene is positively regulated by IAA, produced by A. brasilense itself or added exogenously, we performed a microarray analysis to study the overall effects of IAA on the transcriptome of A. brasilense. The transcriptomes of A. brasilense wild-type and the ipdC knockout mutant, both cultured in the absence and presence of exogenously added IAA, were compared.Interfering with the IAA biosynthesis/homeostasis in A. brasilense through inactivation of the ipdC gene or IAA addition results in much broader transcriptional changes than anticipated. Based on the multitude of changes observed by comparing the different transcriptomes, we can conclude that IAA is a signaling molecule in A. brasilense. It appears that the bacterium, when exposed to IAA, adapts itself to the plant rhizosphere, by changing its arsenal of transport proteins and cell surface proteins. A striking example of adaptation to IAA exposure, as happens in the rhizosphere, is the upregulation of a type VI secretion system (T6SS) in the presence of IAA. The T6SS is described as specifically involved in bacterium-eukaryotic host interactions. Additionally, many transcription factors show an altered regulation as well, indicating that the regulatory machinery of the bacterium is changing.

  20. Addressable droplet microarrays for single cell protein analysis.

    Science.gov (United States)

    Salehi-Reyhani, Ali; Burgin, Edward; Ces, Oscar; Willison, Keith R; Klug, David R

    2014-11-07

    Addressable droplet microarrays are potentially attractive as a way to achieve miniaturised, reduced volume, high sensitivity analyses without the need to fabricate microfluidic devices or small volume chambers. We report a practical method for producing oil-encapsulated addressable droplet microarrays which can be used for such analyses. To demonstrate their utility, we undertake a series of single cell analyses, to determine the variation in copy number of p53 proteins in cells of a human cancer cell line.

  1. A comparative analysis of DNA barcode microarray feature size

    Directory of Open Access Journals (Sweden)

    Smith Andrew M

    2009-10-01

    Full Text Available Abstract Background Microarrays are an invaluable tool in many modern genomic studies. It is generally perceived that decreasing the size of microarray features leads to arrays with higher resolution (due to greater feature density, but this increase in resolution can compromise sensitivity. Results We demonstrate that barcode microarrays with smaller features are equally capable of detecting variation in DNA barcode intensity when compared to larger feature sizes within a specific microarray platform. The barcodes used in this study are the well-characterized set derived from the Yeast KnockOut (YKO collection used for screens of pooled yeast (Saccharomyces cerevisiae deletion mutants. We treated these pools with the glycosylation inhibitor tunicamycin as a test compound. Three generations of barcode microarrays at 30, 8 and 5 μm features sizes independently identified the primary target of tunicamycin to be ALG7. Conclusion We show that the data obtained with 5 μm feature size is of comparable quality to the 30 μm size and propose that further shrinking of features could yield barcode microarrays with equal or greater resolving power and, more importantly, higher density.

  2. Network analysis of oyster transcriptome revealed a cascade of cellular responses during recovery after heat shock.

    Directory of Open Access Journals (Sweden)

    Lingling Zhang

    Full Text Available Oysters, as a major group of marine bivalves, can tolerate a wide range of natural and anthropogenic stressors including heat stress. Recent studies have shown that oysters pretreated with heat shock can result in induced heat tolerance. A systematic study of cellular recovery from heat shock may provide insights into the mechanism of acquired thermal tolerance. In this study, we performed the first network analysis of oyster transcriptome by reanalyzing microarray data from a previous study. Network analysis revealed a cascade of cellular responses during oyster recovery after heat shock and identified responsive gene modules and key genes. Our study demonstrates the power of network analysis in a non-model organism with poor gene annotations, which can lead to new discoveries that go beyond the focus on individual genes.

  3. Microarray technology for major chemical contaminants analysis in food: current status and prospects.

    Science.gov (United States)

    Zhang, Zhaowei; Li, Peiwu; Hu, Xiaofeng; Zhang, Qi; Ding, Xiaoxia; Zhang, Wen

    2012-01-01

    Chemical contaminants in food have caused serious health issues in both humans and animals. Microarray technology is an advanced technique suitable for the analysis of chemical contaminates. In particular, immuno-microarray approach is one of the most promising methods for chemical contaminants analysis. The use of microarrays for the analysis of chemical contaminants is the subject of this review. Fabrication strategies and detection methods for chemical contaminants are discussed in detail. Application to the analysis of mycotoxins, biotoxins, pesticide residues, and pharmaceutical residues is also described. Finally, future challenges and opportunities are discussed.

  4. Transcriptome analysis reveals key differentially expressed genes involved in wheat grain development

    Directory of Open Access Journals (Sweden)

    Yonglong Yu

    2016-04-01

    Full Text Available Wheat seed development is an important physiological process of seed maturation and directly affects wheat yield and quality. In this study, we performed dynamic transcriptome microarray analysis of an elite Chinese bread wheat cultivar (Jimai 20 during grain development using the GeneChip Wheat Genome Array. Grain morphology and scanning electron microscope observations showed that the period of 11–15 days post-anthesis (DPA was a key stage for the synthesis and accumulation of seed starch. Genome-wide transcriptional profiling and significance analysis of microarrays revealed that the period from 11 to 15 DPA was more important than the 15–20 DPA stage for the synthesis and accumulation of nutritive reserves. Series test of cluster analysis of differential genes revealed five statistically significant gene expression profiles. Gene ontology annotation and enrichment analysis gave further information about differentially expressed genes, and MapMan analysis revealed expression changes within functional groups during seed development. Metabolic pathway network analysis showed that major and minor metabolic pathways regulate one another to ensure regular seed development and nutritive reserve accumulation. We performed gene co-expression network analysis to identify genes that play vital roles in seed development and identified several key genes involved in important metabolic pathways. The transcriptional expression of eight key genes involved in starch and protein synthesis and stress defense was further validated by qRT-PCR. Our results provide new insight into the molecular mechanisms of wheat seed development and the determinants of yield and quality.

  5. Microarray analysis of subcutaneous adipose tissue from mature cows with divergent body weight gain after feed restriction and realimentation

    Directory of Open Access Journals (Sweden)

    H.C. Cunningham

    2018-02-01

    Full Text Available Body weight response to periods of feed restriction and realimentation is critical and relevant to the agricultural industry. The purpose of this study was to evaluate differentially expressed genes identified in subcutaneous adipose tissue collected from cows divergent in body weight (BW gain after feed restriction and realimentation. We compared adipose samples from cows with greater gain based on average daily gain (ADG during realimentation with samples from cows with lesser gain. Specifically, there were four comparisons including two comparing the high and low gain animals across each feeding period (feed restriction and realimentation and two that compared differences in feed restriction and realimentation across high or low gain classifications. Using microarray analysis, we provide a set of differentially expressed genes identified between the high and low gain at both periods of nutrient restriction and realimentation. These data identify multiple differentially expressed genes between these two phenotypes across both nutritional environments. Keywords: Beef cows, Subcutaneous fat, Transcriptome

  6. Gene Expression Signature in Endemic Osteoarthritis by Microarray Analysis

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    Xi Wang

    2015-05-01

    Full Text Available Kashin-Beck Disease (KBD is an endemic osteochondropathy with an unknown pathogenesis. Diagnosis of KBD is effective only in advanced cases, which eliminates the possibility of early treatment and leads to an inevitable exacerbation of symptoms. Therefore, we aim to identify an accurate blood-based gene signature for the detection of KBD. Previously published gene expression profile data on cartilage and peripheral blood mononuclear cells (PBMCs from adults with KBD were compared to select potential target genes. Microarray analysis was conducted to evaluate the expression of the target genes in a cohort of 100 KBD patients and 100 healthy controls. A gene expression signature was identified using a training set, which was subsequently validated using an independent test set with a minimum redundancy maximum relevance (mRMR algorithm and support vector machine (SVM algorithm. Fifty unique genes were differentially expressed between KBD patients and healthy controls. A 20-gene signature was identified that distinguished between KBD patients and controls with 90% accuracy, 85% sensitivity, and 95% specificity. This study identified a 20-gene signature that accurately distinguishes between patients with KBD and controls using peripheral blood samples. These results promote the further development of blood-based genetic biomarkers for detection of KBD.

  7. Transcriptome analysis of Anopheles stephensi embryo using ...

    Indian Academy of Sciences (India)

    Germ band retraction (GBR) stage is one of the important stages during insect development. It is associated with an extensive epithelial morphogenesis and may also be pivotal in generation of morphological diversity in insects. Despite its importance, only a handful of studies report the transcriptome repertoire of this stage ...

  8. Meta-Analysis of Placental Transcriptome Data Identifies a Novel Molecular Pathway Related to Preeclampsia.

    Science.gov (United States)

    van Uitert, Miranda; Moerland, Perry D; Enquobahrie, Daniel A; Laivuori, Hannele; van der Post, Joris A M; Ris-Stalpers, Carrie; Afink, Gijs B

    2015-01-01

    Studies using the placental transcriptome to identify key molecules relevant for preeclampsia are hampered by a relatively small sample size. In addition, they use a variety of bioinformatics and statistical methods, making comparison of findings challenging. To generate a more robust preeclampsia gene expression signature, we performed a meta-analysis on the original data of 11 placenta RNA microarray experiments, representing 139 normotensive and 116 preeclamptic pregnancies. Microarray data were pre-processed and analyzed using standardized bioinformatics and statistical procedures and the effect sizes were combined using an inverse-variance random-effects model. Interactions between genes in the resulting gene expression signature were identified by pathway analysis (Ingenuity Pathway Analysis, Gene Set Enrichment Analysis, Graphite) and protein-protein associations (STRING). This approach has resulted in a comprehensive list of differentially expressed genes that led to a 388-gene meta-signature of preeclamptic placenta. Pathway analysis highlights the involvement of the previously identified hypoxia/HIF1A pathway in the establishment of the preeclamptic gene expression profile, while analysis of protein interaction networks indicates CREBBP/EP300 as a novel element central to the preeclamptic placental transcriptome. In addition, there is an apparent high incidence of preeclampsia in women carrying a child with a mutation in CREBBP/EP300 (Rubinstein-Taybi Syndrome). The 388-gene preeclampsia meta-signature offers a vital starting point for further studies into the relevance of these genes (in particular CREBBP/EP300) and their concomitant pathways as biomarkers or functional molecules in preeclampsia. This will result in a better understanding of the molecular basis of this disease and opens up the opportunity to develop rational therapies targeting the placental dysfunction causal to preeclampsia.

  9. Meta-Analysis of Placental Transcriptome Data Identifies a Novel Molecular Pathway Related to Preeclampsia.

    Directory of Open Access Journals (Sweden)

    Miranda van Uitert

    Full Text Available Studies using the placental transcriptome to identify key molecules relevant for preeclampsia are hampered by a relatively small sample size. In addition, they use a variety of bioinformatics and statistical methods, making comparison of findings challenging. To generate a more robust preeclampsia gene expression signature, we performed a meta-analysis on the original data of 11 placenta RNA microarray experiments, representing 139 normotensive and 116 preeclamptic pregnancies. Microarray data were pre-processed and analyzed using standardized bioinformatics and statistical procedures and the effect sizes were combined using an inverse-variance random-effects model. Interactions between genes in the resulting gene expression signature were identified by pathway analysis (Ingenuity Pathway Analysis, Gene Set Enrichment Analysis, Graphite and protein-protein associations (STRING. This approach has resulted in a comprehensive list of differentially expressed genes that led to a 388-gene meta-signature of preeclamptic placenta. Pathway analysis highlights the involvement of the previously identified hypoxia/HIF1A pathway in the establishment of the preeclamptic gene expression profile, while analysis of protein interaction networks indicates CREBBP/EP300 as a novel element central to the preeclamptic placental transcriptome. In addition, there is an apparent high incidence of preeclampsia in women carrying a child with a mutation in CREBBP/EP300 (Rubinstein-Taybi Syndrome. The 388-gene preeclampsia meta-signature offers a vital starting point for further studies into the relevance of these genes (in particular CREBBP/EP300 and their concomitant pathways as biomarkers or functional molecules in preeclampsia. This will result in a better understanding of the molecular basis of this disease and opens up the opportunity to develop rational therapies targeting the placental dysfunction causal to preeclampsia.

  10. Literature-aided meta-analysis of microarray data: a compendium study on muscle development and disease

    Directory of Open Access Journals (Sweden)

    van Ommen Gert-Jan B

    2008-06-01

    Full Text Available Abstract Background Comparative analysis of expression microarray studies is difficult due to the large influence of technical factors on experimental outcome. Still, the identified differentially expressed genes may hint at the same biological processes. However, manually curated assignment of genes to biological processes, such as pursued by the Gene Ontology (GO consortium, is incomplete and limited. We hypothesised that automatic association of genes with biological processes through thesaurus-controlled mining of Medline abstracts would be more effective. Therefore, we developed a novel algorithm (LAMA: Literature-Aided Meta-Analysis to quantify the similarity between transcriptomics studies. We evaluated our algorithm on a large compendium of 102 microarray studies published in the field of muscle development and disease, and compared it to similarity measures based on gene overlap and over-representation of biological processes assigned by GO. Results While the overlap in both genes and overrepresented GO-terms was poor, LAMA retrieved many more biologically meaningful links between studies, with substantially lower influence of technical factors. LAMA correctly grouped muscular dystrophy, regeneration and myositis studies, and linked patient and corresponding mouse model studies. LAMA also retrieves the connecting biological concepts. Among other new discoveries, we associated cullin proteins, a class of ubiquitinylation proteins, with genes down-regulated during muscle regeneration, whereas ubiquitinylation was previously reported to be activated during the inverse process: muscle atrophy. Conclusion Our literature-based association analysis is capable of finding hidden common biological denominators in microarray studies, and circumvents the need for raw data analysis or curated gene annotation databases.

  11. Comparative analysis of methods for gene transcription profiling data derived from different microarray technologies in rat and mouse models of diabetes

    Directory of Open Access Journals (Sweden)

    Bihoreau Marie-Thérèse

    2009-02-01

    Full Text Available Abstract Background Microarray technologies are widely used to quantify the abundance of transcripts corresponding to thousands of genes. To maximise the robustness of transcriptome results, we have tested the performance and reproducibility of rat and mouse gene expression data obtained with Affymetrix, Illumina and Operon platforms. Results We present a thorough analysis of the degree of reproducibility provided by analysing the transcriptomic profile of the same animals of several experimental groups under different popular microarray technologies in different tissues. Concordant results from inter- and intra-platform comparisons were maximised by testing many popular computational methods for generating fold changes and significances and by only considering oligonucleotides giving high expression levels. The choice of Affymetrix signal extraction technique was shown to have the greatest effect on the concordance across platforms. In both species, when choosing optimal methods, the agreement between data generated on the Affymetrix and Illumina was excellent; this was verified using qRT-PCR on a selection of genes present on all platforms. Conclusion This study provides an extensive assessment of analytical methods best suited for processing data from different microarray technologies and can assist integration of technologically different gene expression datasets in biological systems.

  12. Comparative transcriptomic analysis of roots of contrasting Gossypium herbaceum genotypes revealing adaptation to drought

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    Ranjan Alok

    2012-11-01

    Full Text Available Abstract Background Root length and its architecture govern the adaptability of plants to various stress conditions, including drought stress. Genetic variations in root growth, length, and architecture are genotypes dependent. In this study, we compared the drought-induced transcriptome of four genotypes of Gossypium herbaceum that differed in their drought tolerance adaptability. Three different methodologies, namely, microarray, pyrosequencing, and qRT–PCR, were used for transcriptome analysis and validation. Results The variations in root length and growth were found among four genotypes of G.herbaceum when exposed to mannitol-induced osmotic stress. Under osmotic stress, the drought tolerant genotypes Vagad and GujCot-21 showed a longer root length than did by drought sensitive RAHS-14 and RAHS-IPS-187. Further, the gene expression patterns in the root tissue of all genotypes were analyzed. We obtained a total of 794 differentially expressed genes by microarray and 104928 high-quality reads representing 53195 unigenes from the root transcriptome. The Vagad and GujCot-21 respond to water stress by inducing various genes and pathways such as response to stresses, response to water deprivation, and flavonoid pathways. Some key regulatory genes involved in abiotic stress such as AP2 EREBP, MYB, WRKY, ERF, ERD9, and LEA were highly expressed in Vagad and GujCot-21. The genes RHD3, NAP1, LBD, and transcription factor WRKY75, known for root development under various stress conditions, were expressed specifically in Vagad and GujCot-21. The genes related to peroxidases, transporters, cell wall-modifying enzymes, and compatible solutes (amino acids, amino sugars, betaine, sugars, or sugar alcohols were also highly expressed in Vagad and Gujcot-21. Conclusion Our analysis highlights changes in the expression pattern of genes and depicts a small but highly specific set of drought responsive genes induced in response to drought stress. Some of these

  13. Application of the Gini correlation coefficient to infer regulatory relationships in transcriptome analysis.

    Science.gov (United States)

    Ma, Chuang; Wang, Xiangfeng

    2012-09-01

    One of the computational challenges in plant systems biology is to accurately infer transcriptional regulation relationships based on correlation analyses of gene expression patterns. Despite several correlation methods that are applied in biology to analyze microarray data, concerns regarding the compatibility of these methods with the gene expression data profiled by high-throughput RNA transcriptome sequencing (RNA-Seq) technology have been raised. These concerns are mainly due to the fact that the distribution of read counts in RNA-Seq experiments is different from that of fluorescence intensities in microarray experiments. Therefore, a comprehensive evaluation of the existing correlation methods and, if necessary, introduction of novel methods into biology is appropriate. In this study, we compared four existing correlation methods used in microarray analysis and one novel method called the Gini correlation coefficient on previously published microarray-based and sequencing-based gene expression data in Arabidopsis (Arabidopsis thaliana) and maize (Zea mays). The comparisons were performed on more than 11,000 regulatory relationships in Arabidopsis, including 8,929 pairs of transcription factors and target genes. Our analyses pinpointed the strengths and weaknesses of each method and indicated that the Gini correlation can compensate for the shortcomings of the Pearson correlation, the Spearman correlation, the Kendall correlation, and the Tukey's biweight correlation. The Gini correlation method, with the other four evaluated methods in this study, was implemented as an R package named rsgcc that can be utilized as an alternative option for biologists to perform clustering analyses of gene expression patterns or transcriptional network analyses.

  14. Application of the Gini Correlation Coefficient to Infer Regulatory Relationships in Transcriptome Analysis[W][OA

    Science.gov (United States)

    Ma, Chuang; Wang, Xiangfeng

    2012-01-01

    One of the computational challenges in plant systems biology is to accurately infer transcriptional regulation relationships based on correlation analyses of gene expression patterns. Despite several correlation methods that are applied in biology to analyze microarray data, concerns regarding the compatibility of these methods with the gene expression data profiled by high-throughput RNA transcriptome sequencing (RNA-Seq) technology have been raised. These concerns are mainly due to the fact that the distribution of read counts in RNA-Seq experiments is different from that of fluorescence intensities in microarray experiments. Therefore, a comprehensive evaluation of the existing correlation methods and, if necessary, introduction of novel methods into biology is appropriate. In this study, we compared four existing correlation methods used in microarray analysis and one novel method called the Gini correlation coefficient on previously published microarray-based and sequencing-based gene expression data in Arabidopsis (Arabidopsis thaliana) and maize (Zea mays). The comparisons were performed on more than 11,000 regulatory relationships in Arabidopsis, including 8,929 pairs of transcription factors and target genes. Our analyses pinpointed the strengths and weaknesses of each method and indicated that the Gini correlation can compensate for the shortcomings of the Pearson correlation, the Spearman correlation, the Kendall correlation, and the Tukey’s biweight correlation. The Gini correlation method, with the other four evaluated methods in this study, was implemented as an R package named rsgcc that can be utilized as an alternative option for biologists to perform clustering analyses of gene expression patterns or transcriptional network analyses. PMID:22797655

  15. An integrative genomic and transcriptomic analysis reveals potential targets associated with cell proliferation in uterine leiomyomas.

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    Priscila Daniele Ramos Cirilo

    Full Text Available Uterine Leiomyomas (ULs are the most common benign tumours affecting women of reproductive age. ULs represent a major problem in public health, as they are the main indication for hysterectomy. Approximately 40-50% of ULs have non-random cytogenetic abnormalities, and half of ULs may have copy number alterations (CNAs. Gene expression microarrays studies have demonstrated that cell proliferation genes act in response to growth factors and steroids. However, only a few genes mapping to CNAs regions were found to be associated with ULs.We applied an integrative analysis using genomic and transcriptomic data to identify the pathways and molecular markers associated with ULs. Fifty-one fresh frozen specimens were evaluated by array CGH (JISTIC and gene expression microarrays (SAM. The CONEXIC algorithm was applied to integrate the data.The integrated analysis identified the top 30 significant genes (P<0.01, which comprised genes associated with cancer, whereas the protein-protein interaction analysis indicated a strong association between FANCA and BRCA1. Functional in silico analysis revealed target molecules for drugs involved in cell proliferation, including FGFR1 and IGFBP5. Transcriptional and protein analyses showed that FGFR1 (P = 0.006 and P<0.01, respectively and IGFBP5 (P = 0.0002 and P = 0.006, respectively were up-regulated in the tumours when compared with the adjacent normal myometrium.The integrative genomic and transcriptomic approach indicated that FGFR1 and IGFBP5 amplification, as well as the consequent up-regulation of the protein products, plays an important role in the aetiology of ULs and thus provides data for potential drug therapies development to target genes associated with cellular proliferation in ULs.

  16. Analysis of the Citrullus colocynthis transcriptome during water deficit stress.

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    Zhuoyu Wang

    Full Text Available Citrullus colocynthis is a very drought tolerant species, closely related to watermelon (C. lanatus var. lanatus, an economically important cucurbit crop. Drought is a threat to plant growth and development, and the discovery of drought inducible genes with various functions is of great importance. We used high throughput mRNA Illumina sequencing technology and bioinformatic strategies to analyze the C. colocynthis leaf transcriptome under drought treatment. Leaf samples at four different time points (0, 24, 36, or 48 hours of withholding water were used for RNA extraction and Illumina sequencing. qRT-PCR of several drought responsive genes was performed to confirm the accuracy of RNA sequencing. Leaf transcriptome analysis provided the first glimpse of the drought responsive transcriptome of this unique cucurbit species. A total of 5038 full-length cDNAs were detected, with 2545 genes showing significant changes during drought stress. Principle component analysis indicated that drought was the major contributing factor regulating transcriptome changes. Up regulation of many transcription factors, stress signaling factors, detoxification genes, and genes involved in phytohormone signaling and citrulline metabolism occurred under the water deficit conditions. The C. colocynthis transcriptome data highlight the activation of a large set of drought related genes in this species, thus providing a valuable resource for future functional analysis of candidate genes in defense of drought stress.

  17. Comparative Analysis of the Arabidopsis Pollen Transcriptome

    Czech Academy of Sciences Publication Activity Database

    Honys, David; Twell, D.

    2003-01-01

    Roč. 132, - (2003), s. 640ů652 ISSN 0032-0889 R&D Projects: GA AV ČR IAA5038207 Grant - others:Royal Society(GB) NATO Postdoctoral Fellowship (to D.H.) Institutional research plan: CEZ:AV0Z5038910; CEZ:MSM 113100003 Keywords : transcriptome profiling * Arabidopsis pollen * male gametophyte Subject RIV: EB - Genetics ; Molecular Biology Impact factor: 5.634, year: 2003

  18. Network Expansion and Pathway Enrichment Analysis towards Biologically Significant Findings from Microarrays

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    Wu Xiaogang

    2012-06-01

    Full Text Available In many cases, crucial genes show relatively slight changes between groups of samples (e.g. normal vs. disease, and many genes selected from microarray differential analysis by measuring the expression level statistically are also poorly annotated and lack of biological significance. In this paper, we present an innovative approach - network expansion and pathway enrichment analysis (NEPEA for integrative microarray analysis. We assume that organized knowledge will help microarray data analysis in significant ways, and the organized knowledge could be represented as molecular interaction networks or biological pathways. Based on this hypothesis, we develop the NEPEA framework based on network expansion from the human annotated and predicted protein interaction (HAPPI database, and pathway enrichment from the human pathway database (HPD. We use a recently-published microarray dataset (GSE24215 related to insulin resistance and type 2 diabetes (T2D as case study, since this study provided a thorough experimental validation for both genes and pathways identified computationally from classical microarray analysis and pathway analysis. We perform our NEPEA analysis for this dataset based on the results from the classical microarray analysis to identify biologically significant genes and pathways. Our findings are not only consistent with the original findings mostly, but also obtained more supports from other literatures.

  19. Gametogenesis in the Pacific oyster Crassostrea gigas: a microarrays-based analysis identifies sex and stage specific genes.

    Directory of Open Access Journals (Sweden)

    Nolwenn M Dheilly

    Full Text Available BACKGROUND: The Pacific oyster Crassostrea gigas (Mollusca, Lophotrochozoa is an alternative and irregular protandrous hermaphrodite: most individuals mature first as males and then change sex several times. Little is known about genetic and phenotypic basis of sex differentiation in oysters, and little more about the molecular pathways regulating reproduction. We have recently developed and validated a microarray containing 31,918 oligomers (Dheilly et al., 2011 representing the oyster transcriptome. The application of this microarray to the study of mollusk gametogenesis should provide a better understanding of the key factors involved in sex differentiation and the regulation of oyster reproduction. METHODOLOGY/PRINCIPAL FINDINGS: Gene expression was studied in gonads of oysters cultured over a yearly reproductive cycle. Principal component analysis and hierarchical clustering showed a significant divergence in gene expression patterns of males and females coinciding with the start of gonial mitosis. ANOVA analysis of the data revealed 2,482 genes differentially expressed during the course of males and/or females gametogenesis. The expression of 434 genes could be localized in either germ cells or somatic cells of the gonad by comparing the transcriptome of female gonads to the transcriptome of stripped oocytes and somatic tissues. Analysis of the annotated genes revealed conserved molecular mechanisms between mollusks and mammals: genes involved in chromatin condensation, DNA replication and repair, mitosis and meiosis regulation, transcription, translation and apoptosis were expressed in both male and female gonads. Most interestingly, early expressed male-specific genes included bindin and a dpy-30 homolog and female-specific genes included foxL2, nanos homolog 3, a pancreatic lipase related protein, cd63 and vitellogenin. Further functional analyses are now required in order to investigate their role in sex differentiation in oysters

  20. Metabolomic Dynamic Analysis of Hypoxia in MDA-MB-231 and the Comparison with Inferred Metabolites from Transcriptomics Data

    Directory of Open Access Journals (Sweden)

    Yufeng Jane Tseng

    2013-05-01

    Full Text Available Hypoxia affects the tumor microenvironment and is considered important to metastasis progression and therapy resistance. Thus far, the majority of global analyses of tumor hypoxia responses have been limited to just a single omics level. Combining multiple omics data can broaden our understanding of tumor hypoxia. Here, we investigate the temporal change of the metabolite composition with gene expression data from literature to provide a more comprehensive insight into the system level in response to hypoxia. Nuclear magnetic resonance spectroscopy was used to perform metabolomic profiling on the MDA-MB-231 breast cancer cell line under hypoxic conditions. Multivariate statistical analysis revealed that the metabolic difference between hypoxia and normoxia was similar over 24 h, but became distinct over 48 h. Time dependent microarray data from the same cell line in the literature displayed different gene expressions under hypoxic and normoxic conditions mostly at 12 h or earlier. The direct metabolomic profiles show a large overlap with theoretical metabolic profiles deduced from previous transcriptomic studies. Consistent pathways are glycolysis/gluconeogenesis, pyruvate, purine and arginine and proline metabolism. Ten metabolic pathways revealed by metabolomics were not covered by the downstream of the known transcriptomic profiles, suggesting new metabolic phenotypes. These results confirm previous transcriptomics understanding and expand the knowledge from existing models on correlation and co-regulation between transcriptomic and metabolomics profiles, which demonstrates the power of integrated omics analysis.

  1. Metabolomic Dynamic Analysis of Hypoxia in MDA-MB-231 and the Comparison with Inferred Metabolites from Transcriptomics Data

    Energy Technology Data Exchange (ETDEWEB)

    Tsai, I-Lin [Department of Pharmacy, National Taiwan University, No. 1, Jen-Ai Road, Section 1 Taipei 10051, Taiwan (China); The Metabolomics Group, National Taiwan University, Taipei 106, Taiwan (China); Center for Genomic Medicine, National Taiwan University, Taipei 10051, Taiwan (China); Kuo, Tien-Chueh [The Metabolomics Group, National Taiwan University, Taipei 106, Taiwan (China); Graduate Institute of Biomedical Electronic and Bioinformatics, National Taiwan University, Room 410 BL Building, No. 1, Roosevelt Road, Sec. 4, Taipei 106, Taiwan (China); Ho, Tsung-Jung [The Metabolomics Group, National Taiwan University, Taipei 106, Taiwan (China); Department of Computer Science and Information Engineering, National Taiwan University, No. 1, Sec. 4, Roosevelt Rd., Taipei 10617, Taiwan (China); Harn, Yeu-Chern [The Metabolomics Group, National Taiwan University, Taipei 106, Taiwan (China); Graduate Institute of Networking and Multimedia, National Taiwan University, No. 1, Sec. 4, Roosevelt Rd., Taipei 10617, Taiwan (China); Wang, San-Yuan [The Metabolomics Group, National Taiwan University, Taipei 106, Taiwan (China); Department of Computer Science and Information Engineering, National Taiwan University, No. 1, Sec. 4, Roosevelt Rd., Taipei 10617, Taiwan (China); Fu, Wen-Mei [Department of Pharmacology, National Taiwan University, 11 F No. 1 Sec. 1, Ren-ai Rd., Taipei 10051, Taiwan (China); Kuo, Ching-Hua, E-mail: kuoch@ntu.edu.tw [Department of Pharmacy, National Taiwan University, No. 1, Jen-Ai Road, Section 1 Taipei 10051, Taiwan (China); The Metabolomics Group, National Taiwan University, Taipei 106, Taiwan (China); Center for Genomic Medicine, National Taiwan University, Taipei 10051, Taiwan (China); Tseng, Yufeng Jane, E-mail: kuoch@ntu.edu.tw [Department of Pharmacy, National Taiwan University, No. 1, Jen-Ai Road, Section 1 Taipei 10051, Taiwan (China); The Metabolomics Group, National Taiwan University, Taipei 106, Taiwan (China); Center for Genomic Medicine, National Taiwan University, Taipei 10051, Taiwan (China); Graduate Institute of Biomedical Electronic and Bioinformatics, National Taiwan University, Room 410 BL Building, No. 1, Roosevelt Road, Sec. 4, Taipei 106, Taiwan (China); Department of Computer Science and Information Engineering, National Taiwan University, No. 1, Sec. 4, Roosevelt Rd., Taipei 10617, Taiwan (China)

    2013-05-03

    Hypoxia affects the tumor microenvironment and is considered important to metastasis progression and therapy resistance. Thus far, the majority of global analyses of tumor hypoxia responses have been limited to just a single omics level. Combining multiple omics data can broaden our understanding of tumor hypoxia. Here, we investigate the temporal change of the metabolite composition with gene expression data from literature to provide a more comprehensive insight into the system level in response to hypoxia. Nuclear magnetic resonance spectroscopy was used to perform metabolomic profiling on the MDA-MB-231 breast cancer cell line under hypoxic conditions. Multivariate statistical analysis revealed that the metabolic difference between hypoxia and normoxia was similar over 24 h, but became distinct over 48 h. Time dependent microarray data from the same cell line in the literature displayed different gene expressions under hypoxic and normoxic conditions mostly at 12 h or earlier. The direct metabolomic profiles show a large overlap with theoretical metabolic profiles deduced from previous transcriptomic studies. Consistent pathways are glycolysis/gluconeogenesis, pyruvate, purine and arginine and proline metabolism. Ten metabolic pathways revealed by metabolomics were not covered by the downstream of the known transcriptomic profiles, suggesting new metabolic phenotypes. These results confirm previous transcriptomics understanding and expand the knowledge from existing models on correlation and co-regulation between transcriptomic and metabolomics profiles, which demonstrates the power of integrated omics analysis.

  2. Metabolomic Dynamic Analysis of Hypoxia in MDA-MB-231 and the Comparison with Inferred Metabolites from Transcriptomics Data

    International Nuclear Information System (INIS)

    Tsai, I-Lin; Kuo, Tien-Chueh; Ho, Tsung-Jung; Harn, Yeu-Chern; Wang, San-Yuan; Fu, Wen-Mei; Kuo, Ching-Hua; Tseng, Yufeng Jane

    2013-01-01

    Hypoxia affects the tumor microenvironment and is considered important to metastasis progression and therapy resistance. Thus far, the majority of global analyses of tumor hypoxia responses have been limited to just a single omics level. Combining multiple omics data can broaden our understanding of tumor hypoxia. Here, we investigate the temporal change of the metabolite composition with gene expression data from literature to provide a more comprehensive insight into the system level in response to hypoxia. Nuclear magnetic resonance spectroscopy was used to perform metabolomic profiling on the MDA-MB-231 breast cancer cell line under hypoxic conditions. Multivariate statistical analysis revealed that the metabolic difference between hypoxia and normoxia was similar over 24 h, but became distinct over 48 h. Time dependent microarray data from the same cell line in the literature displayed different gene expressions under hypoxic and normoxic conditions mostly at 12 h or earlier. The direct metabolomic profiles show a large overlap with theoretical metabolic profiles deduced from previous transcriptomic studies. Consistent pathways are glycolysis/gluconeogenesis, pyruvate, purine and arginine and proline metabolism. Ten metabolic pathways revealed by metabolomics were not covered by the downstream of the known transcriptomic profiles, suggesting new metabolic phenotypes. These results confirm previous transcriptomics understanding and expand the knowledge from existing models on correlation and co-regulation between transcriptomic and metabolomics profiles, which demonstrates the power of integrated omics analysis

  3. Transcriptomic Analysis and Meta-Analysis of Human Granulosa and Cumulus Cells.

    Directory of Open Access Journals (Sweden)

    Tanja Burnik Papler

    Full Text Available Specific gene expression in oocytes and its surrounding cumulus (CC and granulosa (GC cells is needed for successful folliculogenesis and oocyte maturation. The aim of the present study was to compare genome-wide gene expression and biological functions of human GC and CC. Individual GC and CC were derived from 37 women undergoing IVF procedures. Gene expression analysis was performed using microarrays, followed by a meta-analysis. Results were validated using quantitative real-time PCR. There were 6029 differentially expressed genes (q < 10-4; of which 650 genes had a log2 FC ≥ 2. After the meta-analysis there were 3156 genes differentially expressed. Among these there were genes that have previously not been reported in human somatic follicular cells, like prokineticin 2 (PROK2, higher expressed in GC, and pregnancy up-regulated nonubiquitous CaM kinase (PNCK, higher expressed in CC. Pathways like inflammatory response and angiogenesis were enriched in GC, whereas in CC, cell differentiation and multicellular organismal development were among enriched pathways. In conclusion, transcriptomes of GC and CC as well as biological functions, are distinctive for each cell subpopulation. By describing novel genes like PROK2 and PNCK, expressed in GC and CC, we upgraded the existing data on human follicular biology.

  4. Assessment of centrifugation using for accelerated immunological microarray analysis for blood cells investigation

    Directory of Open Access Journals (Sweden)

    A. V. Shishkin

    2011-01-01

    Full Text Available Phase of incubation microarray with cell suspension is prolonged when cells are investigated. It takes from 20 to 60 min if cell sedimentation on the surface of microarray is the result of gravity . Decrease of this stage duration is possible due to centrifugation. In th is article influence of centrifugation on results of analysis is considered. Changes of morphological description of cells are estimated when they a re precipitatedwith different acceleration. Also availability of centrifugation using when it is necessary to obtain the high density of cell binding in test regions of microarray if cells concentration in sample is small is demonstrated.

  5. Microarray expression analysis of meiosis and microsporogenesis in hexaploid bread wheat

    Directory of Open Access Journals (Sweden)

    Langridge Peter

    2006-10-01

    Full Text Available Abstract Background Our understanding of the mechanisms that govern the cellular process of meiosis is limited in higher plants with polyploid genomes. Bread wheat is an allohexaploid that behaves as a diploid during meiosis. Chromosome pairing is restricted to homologous chromosomes despite the presence of homoeologues in the nucleus. The importance of wheat as a crop and the extensive use of wild wheat relatives in breeding programs has prompted many years of cytogenetic and genetic research to develop an understanding of the control of chromosome pairing and recombination. The rapid advance of biochemical and molecular information on meiosis in model organisms such as yeast provides new opportunities to investigate the molecular basis of chromosome pairing control in wheat. However, building the link between the model and wheat requires points of data contact. Results We report here a large-scale transcriptomics study using the Affymetrix wheat GeneChip® aimed at providing this link between wheat and model systems and at identifying early meiotic genes. Analysis of the microarray data identified 1,350 transcripts temporally-regulated during the early stages of meiosis. Expression profiles with annotated transcript functions including chromatin condensation, synaptonemal complex formation, recombination and fertility were identified. From the 1,350 transcripts, 30 displayed at least an eight-fold expression change between and including pre-meiosis and telophase II, with more than 50% of these having no similarities to known sequences in NCBI and TIGR databases. Conclusion This resource is now available to support research into the molecular basis of pairing and recombination control in the complex polyploid, wheat.

  6. Filtering for increased power for microarray data analysis

    Directory of Open Access Journals (Sweden)

    Hess Ann M

    2009-01-01

    Full Text Available Abstract Background Due to the large number of hypothesis tests performed during the process of routine analysis of microarray data, a multiple testing adjustment is certainly warranted. However, when the number of tests is very large and the proportion of differentially expressed genes is relatively low, the use of a multiple testing adjustment can result in very low power to detect those genes which are truly differentially expressed. Filtering allows for a reduction in the number of tests and a corresponding increase in power. Common filtering methods include filtering by variance, average signal or MAS detection call (for Affymetrix arrays. We study the effects of filtering in combination with the Benjamini-Hochberg method for false discovery rate control and q-value for false discovery rate estimation. Results Three case studies are used to compare three different filtering methods in combination with the two false discovery rate methods and three different preprocessing methods. For the case studies considered, filtering by detection call and variance (on the original scale consistently led to an increase in the number of differentially expressed genes identified. On the other hand, filtering by variance on the log2 scale had a detrimental effect when paired with MAS5 or PLIER preprocessing methods, even when the testing was done on the log2 scale. A simulation study was done to further examine the effect of filtering by variance. We find that filtering by variance leads to higher power, often with a decrease in false discovery rate, when paired with either of the false discovery rate methods considered. This holds regardless of the proportion of genes which are differentially expressed or whether we assume dependence or independence among genes. Conclusion The case studies show that both detection call and variance filtering are viable methods of filtering which can increase the number of differentially expressed genes identified. The

  7. Xylella fastidiosa gene expression analysis by DNA microarrays

    OpenAIRE

    Travensolo,Regiane F.; Carareto-Alves,Lucia M.; Costa,Maria V.C.G.; Lopes,Tiago J.S.; Carrilho,Emanuel; Lemos,Eliana G.M.

    2009-01-01

    Xylella fastidiosa genome sequencing has generated valuable data by identifying genes acting either on metabolic pathways or in associated pathogenicity and virulence. Based on available information on these genes, new strategies for studying their expression patterns, such as microarray technology, were employed. A total of 2,600 primer pairs were synthesized and then used to generate fragments using the PCR technique. The arrays were hybridized against cDNAs labeled during reverse transcrip...

  8. Toxicogenomic markers for corticosteroid treatment in beef cattle: integrated analysis of transcriptomic data.

    Science.gov (United States)

    Pegolo, Sara; Di Camillo, Barbara; Montesissa, Clara; Cannizzo, Francesca Tiziana; Biolatti, Bartolomeo; Bargelloni, Luca

    2015-03-01

    In the present work, an integrated analysis was performed on DNA-microarray data of bovine muscle samples belonging to controls, animals treated with various growth promoters (GPs) and unknown commercial samples. The aim was identify a robust gene expression signature of corticosteroid treatment for the classification of commercial samples, despite the effects of biological variation and other confounding factors. DNA-Microarray data from 5 different batches of bovine skeletal muscle samples were analyzed (146 samples). After preprocessing, expression data from animals treated with corticosteroids and controls from the different batches (89 samples) were used to train a Support Vector Machines (SVMs) classifier. The optimal number of gene probes chosen by our classification framework was 73. The SVMs with linear kernel built on these 73 biomarker genes was predicted to perform on novel samples with a high classification accuracy (Matthew's correlation coefficient equal to 0.77) and an average percentage of false positive and false negative equal to 5% and 6%, respectively. Concluding, a relatively small set of genes was able to discriminate between controls and corticosteroid-treated animals, despite different breeds, animal ages, and combination of GPs. The results are extremely promising, suggesting that integrated analysis provides robust transcriptomic signatures for GP abuse. Copyright © 2014 Elsevier Ltd. All rights reserved.

  9. Transcriptomic meta-analysis identifies gene expression characteristics in various samples of HIV-infected patients with nonprogressive disease.

    Science.gov (United States)

    Zhang, Le-Le; Zhang, Zi-Ning; Wu, Xian; Jiang, Yong-Jun; Fu, Ya-Jing; Shang, Hong

    2017-09-12

    A small proportion of HIV-infected patients remain clinically and/or immunologically stable for years, including elite controllers (ECs) who have undetectable viremia (10 years). However, the mechanism of nonprogression needs to be further resolved. In this study, a transcriptome meta-analysis was performed on nonprogressor and progressor microarray data to identify differential transcriptome pathways and potential biomarkers. Using the INMEX (integrative meta-analysis of expression data) program, we performed the meta-analysis to identify consistently differentially expressed genes (DEGs) in nonprogressors and further performed functional interpretation (gene ontology analysis and pathway analysis) of the DEGs identified in the meta-analysis. Five microarray datasets (81 cases and 98 controls in total), including whole blood, CD4 + and CD8 + T cells, were collected for meta-analysis. We determined that nonprogressors have reduced expression of important interferon-stimulated genes (ISGs), CD38, lymphocyte activation gene 3 (LAG-3) in whole blood, CD4 + and CD8 + T cells. Gene ontology (GO) analysis showed a significant enrichment in DEGs that function in the type I interferon signaling pathway. Upregulated pathways, including the PI3K-Akt signaling pathway in whole blood, cytokine-cytokine receptor interaction in CD4 + T cells and the MAPK signaling pathway in CD8 + T cells, were identified in nonprogressors compared with progressors. In each metabolic functional category, the number of downregulated DEGs was more than the upregulated DEGs, and almost all genes were downregulated DEGs in the oxidative phosphorylation (OXPHOS) and tricarboxylic acid (TCA) cycle in the three types of samples. Our transcriptomic meta-analysis provides a comprehensive evaluation of the gene expression profiles in major blood types of nonprogressors, providing new insights in the understanding of HIV pathogenesis and developing strategies to delay HIV disease progression.

  10. Analysis of a human brain transcriptome map

    Directory of Open Access Journals (Sweden)

    Greene Jonathan R

    2002-04-01

    Full Text Available Abstract Background Genome wide transcriptome maps can provide tools to identify candidate genes that are over-expressed or silenced in certain disease tissue and increase our understanding of the structure and organization of the genome. Expressed Sequence Tags (ESTs from the public dbEST and proprietary Incyte LifeSeq databases were used to derive a transcript map in conjunction with the working draft assembly of the human genome sequence. Results Examination of ESTs derived from brain tissues (excluding brain tumor tissues suggests that these genes are distributed on chromosomes in a non-random fashion. Some regions on the genome are dense with brain-enriched genes while some regions lack brain-enriched genes, suggesting a significant correlation between distribution of genes along the chromosome and tissue type. ESTs from brain tumor tissues have also been mapped to the human genome working draft. We reveal that some regions enriched in brain genes show a significant decrease in gene expression in brain tumors, and, conversely that some regions lacking in brain genes show an increased level of gene expression in brain tumors. Conclusions This report demonstrates a novel approach for tissue specific transcriptome mapping using EST-based quantitative assessment.

  11. Comparative analysis of the transcriptome responses of zebrafish embryos after exposure to low concentrations of cadmium, cobalt and copper.

    Science.gov (United States)

    Sonnack, Laura; Klawonn, Thorsten; Kriehuber, Ralf; Hollert, Henner; Schäfers, Christoph; Fenske, Martina

    2018-03-01

    Metal toxicity is a global environmental challenge. Fish are particularly prone to metal exposure, which can be lethal or cause sublethal physiological impairments. The objective of this study was to investigate how adverse effects of chronic exposure to non-toxic levels of essential and non-essential metals in early life stage zebrafish may be explained by changes in the transcriptome. We therefore studied the effects of three different metals at low concentrations in zebrafish embryos by transcriptomics analysis. The study design compared exposure effects caused by different metals at different developmental stages (pre-hatch and post-hatch). Wild-type embryos were exposed to solutions of low concentrations of copper (CuSO 4 ), cadmium (CdCl 2 ) and cobalt (CoSO 4 ) until 96h post-fertilization (hpf) and microarray experiments were carried out to determine transcriptome profiles at 48 and 96hpf. We found that the toxic metal cadmium affected the expression of more genes at 96hpf than 48hpf. The opposite effect was observed for the essential metals cobalt and copper, which also showed enrichment of different GO terms. Genes involved in neuromast and motor neuron development were significantly enriched, agreeing with our previous results showing motor neuron and neuromast damage in the embryos. Our data provide evidence that the response of the transcriptome of fish embryos to metal exposure differs for essential and non-essential metals. Copyright © 2017 Elsevier Inc. All rights reserved.

  12. Genome-wide binding and transcriptome analysis of human farnesoid X receptor in primary human hepatocytes.

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    Le Zhan

    Full Text Available Farnesoid X receptor (FXR, NR1H4 is a ligand-activated transcription factor, belonging to the nuclear receptor superfamily. FXR is highly expressed in the liver and is essential in regulating bile acid homeostasis. FXR deficiency is implicated in numerous liver diseases and mice with modulation of FXR have been used as animal models to study liver physiology and pathology. We have reported genome-wide binding of FXR in mice by chromatin immunoprecipitation - deep sequencing (ChIP-seq, with results indicating that FXR may be involved in regulating diverse pathways in liver. However, limited information exists for the functions of human FXR and the suitability of using murine models to study human FXR functions.In the current study, we performed ChIP-seq in primary human hepatocytes (PHHs treated with a synthetic FXR agonist, GW4064 or DMSO control. In parallel, RNA deep sequencing (RNA-seq and RNA microarray were performed for GW4064 or control treated PHHs and wild type mouse livers, respectively.ChIP-seq showed similar profiles of genome-wide FXR binding in humans and mice in terms of motif analysis and pathway prediction. However, RNA-seq and microarray showed more different transcriptome profiles between PHHs and mouse livers upon GW4064 treatment.In summary, we have established genome-wide human FXR binding and transcriptome profiles. These results will aid in determining the human FXR functions, as well as judging to what level the mouse models could be used to study human FXR functions.

  13. Improved elucidation of biological processes linked to diabetic nephropathy by single probe-based microarray data analysis.

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    Clemens D Cohen

    Full Text Available BACKGROUND: Diabetic nephropathy (DN is a complex and chronic metabolic disease that evolves into a progressive fibrosing renal disorder. Effective transcriptomic profiling of slowly evolving disease processes such as DN can be problematic. The changes that occur are often subtle and can escape detection by conventional oligonucleotide DNA array analyses. METHODOLOGY/PRINCIPAL FINDINGS: We examined microdissected human renal tissue with or without DN using Affymetrix oligonucleotide microarrays (HG-U133A by standard Robust Multi-array Analysis (RMA. Subsequent gene ontology analysis by Database for Annotation, Visualization and Integrated Discovery (DAVID showed limited detection of biological processes previously identified as central mechanisms in the development of DN (e.g. inflammation and angiogenesis. This apparent lack of sensitivity may be associated with the gene-oriented averaging of oligonucleotide probe signals, as this includes signals from cross-hybridizing probes and gene annotation that is based on out of date genomic data. We then examined the same CEL file data using a different methodology to determine how well it could correlate transcriptomic data with observed biology. ChipInspector (CI is based on single probe analysis and de novo gene annotation that bypasses probe set definitions. Both methods, RMA and CI, used at default settings yielded comparable numbers of differentially regulated genes. However, when verified by RT-PCR, the single probe based analysis demonstrated reduced background noise with enhanced sensitivity and fewer false positives. CONCLUSIONS/SIGNIFICANCE: Using a single probe based analysis approach with de novo gene annotation allowed an improved representation of the biological processes linked to the development and progression of DN. The improved analysis was exemplified by the detection of Wnt signaling pathway activation in DN, a process not previously reported to be involved in this disease.

  14. Application of Microarray technology in research and diagnostics

    DEFF Research Database (Denmark)

    Helweg-Larsen, Rehannah Borup

    The overall purpose of this thesis is to evaluate the use of microarray analysis to investigate the transcriptome of human cancers and human follicular cells and define the correlation between expression of human genes and specific cancer types as well as the developmental competence of the oocyte...

  15. BASE - 2nd generation software for microarray data management and analysis

    Directory of Open Access Journals (Sweden)

    Nordborg Nicklas

    2009-10-01

    Full Text Available Abstract Background Microarray experiments are increasing in size and samples are collected asynchronously over long time. Available data are re-analysed as more samples are hybridized. Systematic use of collected data requires tracking of biomaterials, array information, raw data, and assembly of annotations. To meet the information tracking and data analysis challenges in microarray experiments we reimplemented and improved BASE version 1.2. Results The new BASE presented in this report is a comprehensive annotable local microarray data repository and analysis application providing researchers with an efficient information management and analysis tool. The information management system tracks all material from biosource, via sample and through extraction and labelling to raw data and analysis. All items in BASE can be annotated and the annotations can be used as experimental factors in downstream analysis. BASE stores all microarray experiment related data regardless if analysis tools for specific techniques or data formats are readily available. The BASE team is committed to continue improving and extending BASE to make it usable for even more experimental setups and techniques, and we encourage other groups to target their specific needs leveraging on the infrastructure provided by BASE. Conclusion BASE is a comprehensive management application for information, data, and analysis of microarray experiments, available as free open source software at http://base.thep.lu.se under the terms of the GPLv3 license.

  16. BASE--2nd generation software for microarray data management and analysis.

    Science.gov (United States)

    Vallon-Christersson, Johan; Nordborg, Nicklas; Svensson, Martin; Häkkinen, Jari

    2009-10-12

    Microarray experiments are increasing in size and samples are collected asynchronously over long time. Available data are re-analysed as more samples are hybridized. Systematic use of collected data requires tracking of biomaterials, array information, raw data, and assembly of annotations. To meet the information tracking and data analysis challenges in microarray experiments we reimplemented and improved BASE version 1.2. The new BASE presented in this report is a comprehensive annotable local microarray data repository and analysis application providing researchers with an efficient information management and analysis tool. The information management system tracks all material from biosource, via sample and through extraction and labelling to raw data and analysis. All items in BASE can be annotated and the annotations can be used as experimental factors in downstream analysis. BASE stores all microarray experiment related data regardless if analysis tools for specific techniques or data formats are readily available. The BASE team is committed to continue improving and extending BASE to make it usable for even more experimental setups and techniques, and we encourage other groups to target their specific needs leveraging on the infrastructure provided by BASE. BASE is a comprehensive management application for information, data, and analysis of microarray experiments, available as free open source software at http://base.thep.lu.se under the terms of the GPLv3 license.

  17. A microarray analysis of two distinct lymphatic endothelial cell populations

    Directory of Open Access Journals (Sweden)

    Bernhard Schweighofer

    2015-06-01

    Full Text Available We have recently identified lymphatic endothelial cells (LECs to form two morphologically different populations, exhibiting significantly different surface protein expression levels of podoplanin, a major surface marker for this cell type. In vitro shockwave treatment (IVSWT of LECs resulted in enrichment of the podoplaninhigh cell population and was accompanied by markedly increased cell proliferation, as well as 2D and 3D migration. Gene expression profiles of these distinct populations were established using Affymetrix microarray analyses. Here we provide additional details about our dataset (NCBI GEO accession number GSE62510 and describe how we analyzed the data to identify differently expressed genes in these two LEC populations.

  18. Versatile High Throughput Microarray Analysis for Marine Glycobiology

    DEFF Research Database (Denmark)

    Asunción Salmeán, Armando

    to concept proof that is possible to use the Comprehensive Microarray Polymer Profiling (CoMPP) as a tool for other extracellular matrixes such as marine animals and not only for algal or plant cell walls. Thus, we discovered fucoidan and cellulose epitopes in several tissues of various marine animals from...... in cell development. Another part of this work focused in the development of a novel methodology for the discovery of unknown algal polysaccharides and characterization of carbohydrate binding proteins. Based on the coevolution between alga and marine saprophytic microorganisms, which use the algal...

  19. Prediction of Pectin Yield and Quality by FTIR and Carbohydrate Microarray Analysis

    DEFF Research Database (Denmark)

    Baum, Andreas; Dominiak, Malgorzata Maria; Vidal-Melgosa, Silvia

    2017-01-01

    and carbohydrate microarray analysis were performed directly on the crude lime peel extracts during the time course of the extractions. Multivariate analysis of the data was carried out to predict final pectin yields. Fourier transform infrared spectroscopy (FTIR) was found applicable for determining the optimal...... extraction time for the enzymatic and acidic extraction processes, respectively. The combined results of FTIR and carbohydrate microarray analysis suggested major differences in the crude pectin extracts obtained by enzymatic and acid extraction, respectively. Enzymatically extracted pectin, thus, showed......, and that FTIR and carbohydrate microarray analysis have potential to be developed into online process analysis tools for prediction of pectin extraction yields and pectin features from measurements on crude pectin extracts....

  20. Variance estimation in the analysis of microarray data

    KAUST Repository

    Wang, Yuedong

    2009-04-01

    Microarrays are one of the most widely used high throughput technologies. One of the main problems in the area is that conventional estimates of the variances that are required in the t-statistic and other statistics are unreliable owing to the small number of replications. Various methods have been proposed in the literature to overcome this lack of degrees of freedom problem. In this context, it is commonly observed that the variance increases proportionally with the intensity level, which has led many researchers to assume that the variance is a function of the mean. Here we concentrate on estimation of the variance as a function of an unknown mean in two models: the constant coefficient of variation model and the quadratic variance-mean model. Because the means are unknown and estimated with few degrees of freedom, naive methods that use the sample mean in place of the true mean are generally biased because of the errors-in-variables phenomenon. We propose three methods for overcoming this bias. The first two are variations on the theme of the so-called heteroscedastic simulation-extrapolation estimator, modified to estimate the variance function consistently. The third class of estimators is entirely different, being based on semiparametric information calculations. Simulations show the power of our methods and their lack of bias compared with the naive method that ignores the measurement error. The methodology is illustrated by using microarray data from leukaemia patients.

  1. Transcriptome-wide analysis supports environmental adaptations of two Pinus pinaster populations from contrasting habitats.

    Science.gov (United States)

    Cañas, Rafael A; Feito, Isabel; Fuente-Maqueda, José Francisco; Ávila, Concepción; Majada, Juan; Cánovas, Francisco M

    2015-11-06

    Maritime pine (Pinus pinaster Aiton) grows in a range of different climates in the southwestern Mediterranean region and the existence of a variety of latitudinal ecotypes or provenances is well established. In this study, we have conducted a deep analysis of the transcriptome in needles from two P. pinaster provenances, Leiria (Portugal) and Tamrabta (Morocco), which were grown in northern Spain under the same conditions. An oligonucleotide microarray (PINARRAY3) and RNA-Seq were used for whole-transcriptome analyses, and we found that 90.95% of the data were concordant between the two platforms. Furthermore, the two methods identified very similar percentages of differentially expressed genes with values of 5.5% for PINARRAY3 and 5.7% for RNA-Seq. In total, 6,023 transcripts were shared and 88 differentially expressed genes overlapped in the two platforms. Among the differentially expressed genes, all transport related genes except aquaporins were expressed at higher levels in Tamrabta than in Leiria. In contrast, genes involved in secondary metabolism were expressed at higher levels in Tamrabta, and photosynthesis-related genes were expressed more highly in Leiria. The genes involved in light sensing in plants were well represented in the differentially expressed groups of genes. In addition, increased levels of hormones such as abscisic acid, gibberellins, jasmonic and salicylic acid were observed in Leiria. Both transcriptome platforms have proven to be useful resources, showing complementary and reliable results. The results presented here highlight the different abilities of the two maritime pine populations to sense environmental conditions and reveal one type of regulation that can be ascribed to different genetic and epigenetic backgrounds.

  2. Transcriptomic and proteomic analysis of Oenococcus oeni adaptation to wine stress conditions

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    Mar Margalef-Català

    2016-09-01

    Full Text Available Oenococcus oeni, the main lactic acid bacteria responsible for malolactic fermentation in wine, has to adapt to stressful conditions, such as low pH and high ethanol content. In this study, the changes in the transcriptome and the proteome of O. oeni PSU-1 during the adaptation period before MLF start have been studied. DNA microarrays were used for the transcriptomic analysis and two complementary proteomic techniques, 2-D DIGE and iTRAQ labeling were used to analyze the proteomic response. One of the most influenced functions in PSU-1 due to inoculation into wine-like medium (WLM was translation, showing the over-expression of certain ribosomal genes and the corresponding proteins. Amino acid metabolism and transport was also altered and several peptidases were up regulated both at gene and protein level. Certain proteins involved in glutamine and glutamate metabolism showed an increased abundance revealing the key role of nitrogen uptake under stressful conditions. A strong transcriptional inhibition of carbohydrate metabolism related genes was observed. On the other hand, the transcriptional up-regulation of malate transport and citrate consumption was indicative of the use of L-malate and citrate associated to stress response and as an alternative energy source to sugar metabolism. Regarding the stress mechanisms, our results support the relevance of the thioredoxin and glutathione systems in the adaptation of O. oeni to wine related stress. Genes and proteins related to cell wall showed also significant changes indicating the relevance of the cell envelop as protective barrier to environmental stress. The differences found between transcriptomic and proteomic data suggested the relevance of post-transcriptional mechanisms and the complexity of the stress response in O. oeni adaptation. Further research should deepen into the metabolisms mostly altered due to wine conditions to elucidate the role of each mechanism in the O. oeni ability to

  3. Transcriptomic analysis of Salmonella desiccation resistance.

    Science.gov (United States)

    Li, Haiping; Bhaskara, Anuhya; Megalis, Christina; Tortorello, Mary Lou

    2012-12-01

    The survival of Salmonella in low moisture foods and processing environments remains a great challenge for the food industry and public health. To explore the mechanisms of Salmonella desiccation resistance, we studied the transcriptomic responses in Salmonella Tennessee (Tennessee), using Salmonella Typhimurium LT2 (LT2), a strain weakly resistant to desiccation, as a reference strain. In response to 2 h of air-drying at 11% equilibrated relative humidity, approximately one-fourth of the open reading frames (ORFs) in the Tennessee genome and one-fifth in LT2 were differentially expressed (>2-fold). Among all differentially expressed functional groups (>5-fold) in both strains, the expression fold change associated with fatty acid metabolism was the highest, and constituted 51% and 35% of the total expression fold change in Tennessee and LT2, respectively. Tennessee showed greater changes in expression of genes associated with stress response and envelope modification than LT2, while showing lesser changes in protein biosynthesis expression. Expression of flagella genes was significantly more inhibited in stationary phase cells of Tennessee than LT2 both before and after desiccation. The accumulation of the osmolyte trehalose was significantly induced by desiccation in Tennessee, but no increase was detectable in LT2, which is consistent with the expression patterns of the entire trehalose biosynthesis and degradation pathways in both strains. Results from this study present a global view of the dynamic desiccation responses in Salmonella, which will guide future research efforts to control Salmonella in low moisture environments.

  4. Genome-scale cluster analysis of replicated microarrays using shrinkage correlation coefficient.

    Science.gov (United States)

    Yao, Jianchao; Chang, Chunqi; Salmi, Mari L; Hung, Yeung Sam; Loraine, Ann; Roux, Stanley J

    2008-06-18

    Currently, clustering with some form of correlation coefficient as the gene similarity metric has become a popular method for profiling genomic data. The Pearson correlation coefficient and the standard deviation (SD)-weighted correlation coefficient are the two most widely-used correlations as the similarity metrics in clustering microarray data. However, these two correlations are not optimal for analyzing replicated microarray data generated by most laboratories. An effective correlation coefficient is needed to provide statistically sufficient analysis of replicated microarray data. In this study, we describe a novel correlation coefficient, shrinkage correlation coefficient (SCC), that fully exploits the similarity between the replicated microarray experimental samples. The methodology considers both the number of replicates and the variance within each experimental group in clustering expression data, and provides a robust statistical estimation of the error of replicated microarray data. The value of SCC is revealed by its comparison with two other correlation coefficients that are currently the most widely-used (Pearson correlation coefficient and SD-weighted correlation coefficient) using statistical measures on both synthetic expression data as well as real gene expression data from Saccharomyces cerevisiae. Two leading clustering methods, hierarchical and k-means clustering were applied for the comparison. The comparison indicated that using SCC achieves better clustering performance. Applying SCC-based hierarchical clustering to the replicated microarray data obtained from germinating spores of the fern Ceratopteris richardii, we discovered two clusters of genes with shared expression patterns during spore germination. Functional analysis suggested that some of the genetic mechanisms that control germination in such diverse plant lineages as mosses and angiosperms are also conserved among ferns. This study shows that SCC is an alternative to the Pearson

  5. Transcriptome analysis of the model protozoan, Tetrahymena thermophila, using Deep RNA sequencing.

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    Jie Xiong

    Full Text Available BACKGROUND: The ciliated protozoan Tetrahymena thermophila is a well-studied single-celled eukaryote model organism for cellular and molecular biology. However, the lack of extensive T. thermophila cDNA libraries or a large expressed sequence tag (EST database limited the quality of the original genome annotation. METHODOLOGY/PRINCIPAL FINDINGS: This RNA-seq study describes the first deep sequencing analysis of the T. thermophila transcriptome during the three major stages of the life cycle: growth, starvation and conjugation. Uniquely mapped reads covered more than 96% of the 24,725 predicted gene models in the somatic genome. More than 1,000 new transcribed regions were identified. The great dynamic range of RNA-seq allowed detection of a nearly six order-of-magnitude range of measurable gene expression orchestrated by this cell. RNA-seq also allowed the first prediction of transcript untranslated regions (UTRs and an updated (larger size estimate of the T. thermophila transcriptome: 57 Mb, or about 55% of the somatic genome. Our study identified nearly 1,500 alternative splicing (AS events distributed over 5.2% of T. thermophila genes. This percentage represents a two order-of-magnitude increase over previous EST-based estimates in Tetrahymena. Evidence of stage-specific regulation of alternative splicing was also obtained. Finally, our study allowed us to completely confirm about 26.8% of the genes originally predicted by the gene finder, to correct coding sequence boundaries and intron-exon junctions for about a third, and to reassign microarray probes and correct earlier microarray data. CONCLUSIONS/SIGNIFICANCE: RNA-seq data significantly improve the genome annotation and provide a fully comprehensive view of the global transcriptome of T. thermophila. To our knowledge, 5.2% of T. thermophila genes with AS is the highest percentage of genes showing AS reported in a unicellular eukaryote. Tetrahymena thus becomes an excellent unicellular

  6. Microarray analysis of thioacetamide-treated type 1 diabetic rats

    International Nuclear Information System (INIS)

    Devi, Sachin S.; Mehendale, Harihara M.

    2006-01-01

    It is well known that diabetes imparts high sensitivity to numerous hepatotoxicants. Previously, we have shown that a normally non-lethal dose of thioacetamide (TA, 300 mg/kg) causes 90% mortality in type 1 diabetic (DB) rats due to inhibited tissue repair allowing progression of liver injury. On the other hand, DB rats exposed to 30 mg TA/kg exhibit delayed tissue repair and delayed recovery from injury. The objective of this study was to investigate the mechanism of impaired tissue repair and progression of liver injury in TA-treated DB rats by using cDNA microarray. Gene expression pattern was examined at 0, 6, and 12 h after TA challenge, and selected mechanistic leads from microarray experiments were confirmed by real-time RT-PCR and further investigated at protein level over the time course of 0 to 36 h after TA treatment. Diabetic condition itself increased gene expression of proteases and decreased gene expression of protease inhibitors. Administration of 300 mg TA/kg to DB rats further elevated gene expression of proteases and suppressed gene expression of protease inhibitors, explaining progression of liver injury in DB rats after TA treatment. Inhibited expression of genes involved in cell division cycle (cyclin D1, IGFBP-1, ras, E2F) was observed after exposure of DB rats to 300 mg TA/kg, explaining inhibited tissue repair in these rats. On the other hand, DB rats receiving 30 mg TA/kg exhibit delayed expression of genes involved in cell division cycle, explaining delayed tissue repair in these rats. In conclusion, impaired cyclin D1 signaling along with increased proteases and decreased protease inhibitors may explain impaired tissue repair that leads to progression of liver injury initiated by TA in DB rats

  7. Transcriptome Analysis of Mycobacteria-Specific CD4+ T Cells Identified by Activation-Induced Expression of CD154.

    Science.gov (United States)

    Kunnath-Velayudhan, Shajo; Goldberg, Michael F; Saini, Neeraj K; Johndrow, Christopher T; Ng, Tony W; Johnson, Alison J; Xu, Jiayong; Chan, John; Jacobs, William R; Porcelli, Steven A

    2017-10-01

    Analysis of Ag-specific CD4 + T cells in mycobacterial infections at the transcriptome level is informative but technically challenging. Although several methods exist for identifying Ag-specific T cells, including intracellular cytokine staining, cell surface cytokine-capture assays, and staining with peptide:MHC class II multimers, all of these have significant technical constraints that limit their usefulness. Measurement of activation-induced expression of CD154 has been reported to detect live Ag-specific CD4 + T cells, but this approach remains underexplored and, to our knowledge, has not previously been applied in mycobacteria-infected animals. In this article, we show that CD154 expression identifies adoptively transferred or endogenous Ag-specific CD4 + T cells induced by Mycobacterium bovis bacillus Calmette-Guérin vaccination. We confirmed that Ag-specific cytokine production was positively correlated with CD154 expression by CD4 + T cells from bacillus Calmette-Guérin-vaccinated mice and show that high-quality microarrays can be performed from RNA isolated from CD154 + cells purified by cell sorting. Analysis of microarray data demonstrated that the transcriptome of CD4 + CD154 + cells was distinct from that of CD154 - cells and showed major enrichment of transcripts encoding multiple cytokines and pathways of cellular activation. One notable finding was the identification of a previously unrecognized subset of mycobacteria-specific CD4 + T cells that is characterized by the production of IL-3. Our results support the use of CD154 expression as a practical and reliable method to isolate live Ag-specific CD4 + T cells for transcriptomic analysis and potentially for a range of other studies in infected or previously immunized hosts. Copyright © 2017 by The American Association of Immunologists, Inc.

  8. Automating dChip: toward reproducible sharing of microarray data analysis

    Directory of Open Access Journals (Sweden)

    Li Cheng

    2008-05-01

    Full Text Available Abstract Background During the past decade, many software packages have been developed for analysis and visualization of various types of microarrays. We have developed and maintained the widely used dChip as a microarray analysis software package accessible to both biologist and data analysts. However, challenges arise when dChip users want to analyze large number of arrays automatically and share data analysis procedures and parameters. Improvement is also needed when the dChip user support team tries to identify the causes of reported analysis errors or bugs from users. Results We report here implementation and application of the dChip automation module. Through this module, dChip automation files can be created to include menu steps, parameters, and data viewpoints to run automatically. A data-packaging function allows convenient transfer from one user to another of the dChip software, microarray data, and analysis procedures, so that the second user can reproduce the entire analysis session of the first user. An analysis report file can also be generated during an automated run, including analysis logs, user comments, and viewpoint screenshots. Conclusion The dChip automation module is a step toward reproducible research, and it can prompt a more convenient and reproducible mechanism for sharing microarray software, data, and analysis procedures and results. Automation data packages can also be used as publication supplements. Similar automation mechanisms could be valuable to the research community if implemented in other genomics and bioinformatics software packages.

  9. De Novo Deep Transcriptome Analysis of Medicinal Plants for Gene Discovery in Biosynthesis of Plant Natural Products.

    Science.gov (United States)

    Han, R; Rai, A; Nakamura, M; Suzuki, H; Takahashi, H; Yamazaki, M; Saito, K

    2016-01-01

    Study on transcriptome, the entire pool of transcripts in an organism or single cells at certain physiological or pathological stage, is indispensable in unraveling the connection and regulation between DNA and protein. Before the advent of deep sequencing, microarray was the main approach to handle transcripts. Despite obvious shortcomings, including limited dynamic range and difficulties to compare the results from distinct experiments, microarray was widely applied. During the past decade, next-generation sequencing (NGS) has revolutionized our understanding of genomics in a fast, high-throughput, cost-effective, and tractable manner. By adopting NGS, efficiency and fruitful outcomes concerning the efforts to elucidate genes responsible for producing active compounds in medicinal plants were profoundly enhanced. The whole process involves steps, from the plant material sampling, to cDNA library preparation, to deep sequencing, and then bioinformatics takes over to assemble enormous-yet fragmentary-data from which to comb and extract information. The unprecedentedly rapid development of such technologies provides so many choices to facilitate the task, which can cause confusion when choosing the suitable methodology for specific purposes. Here, we review the general approaches for deep transcriptome analysis and then focus on their application in discovering biosynthetic pathways of medicinal plants that produce important secondary metabolites. © 2016 Elsevier Inc. All rights reserved.

  10. Generalized Correlation Coefficient for Non-Parametric Analysis of Microarray Time-Course Data.

    Science.gov (United States)

    Tan, Qihua; Thomassen, Mads; Burton, Mark; Mose, Kristian Fredløv; Andersen, Klaus Ejner; Hjelmborg, Jacob; Kruse, Torben

    2017-06-06

    Modeling complex time-course patterns is a challenging issue in microarray study due to complex gene expression patterns in response to the time-course experiment. We introduce the generalized correlation coefficient and propose a combinatory approach for detecting, testing and clustering the heterogeneous time-course gene expression patterns. Application of the method identified nonlinear time-course patterns in high agreement with parametric analysis. We conclude that the non-parametric nature in the generalized correlation analysis could be an useful and efficient tool for analyzing microarray time-course data and for exploring the complex relationships in the omics data for studying their association with disease and health.

  11. Extended analysis of benchmark datasets for Agilent two-color microarrays

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    Kerr Kathleen F

    2007-10-01

    Full Text Available Abstract Background As part of its broad and ambitious mission, the MicroArray Quality Control (MAQC project reported the results of experiments using External RNA Controls (ERCs on five microarray platforms. For most platforms, several different methods of data processing were considered. However, there was no similar consideration of different methods for processing the data from the Agilent two-color platform. While this omission is understandable given the scale of the project, it can create the false impression that there is consensus about the best way to process Agilent two-color data. It is also important to consider whether ERCs are representative of all the probes on a microarray. Results A comparison of different methods of processing Agilent two-color data shows substantial differences among methods for low-intensity genes. The sensitivity and specificity for detecting differentially expressed genes varies substantially for different methods. Analysis also reveals that the ERCs in the MAQC data only span the upper half of the intensity range, and therefore cannot be representative of all genes on the microarray. Conclusion Although ERCs demonstrate good agreement between observed and expected log-ratios on the Agilent two-color platform, such an analysis is incomplete. Simple loess normalization outperformed data processing with Agilent's Feature Extraction software for accurate identification of differentially expressed genes. Results from studies using ERCs should not be over-generalized when ERCs are not representative of all probes on a microarray.

  12. Support vector machine and principal component analysis for microarray data classification

    Science.gov (United States)

    Astuti, Widi; Adiwijaya

    2018-03-01

    Cancer is a leading cause of death worldwide although a significant proportion of it can be cured if it is detected early. In recent decades, technology called microarray takes an important role in the diagnosis of cancer. By using data mining technique, microarray data classification can be performed to improve the accuracy of cancer diagnosis compared to traditional techniques. The characteristic of microarray data is small sample but it has huge dimension. Since that, there is a challenge for researcher to provide solutions for microarray data classification with high performance in both accuracy and running time. This research proposed the usage of Principal Component Analysis (PCA) as a dimension reduction method along with Support Vector Method (SVM) optimized by kernel functions as a classifier for microarray data classification. The proposed scheme was applied on seven data sets using 5-fold cross validation and then evaluation and analysis conducted on term of both accuracy and running time. The result showed that the scheme can obtained 100% accuracy for Ovarian and Lung Cancer data when Linear and Cubic kernel functions are used. In term of running time, PCA greatly reduced the running time for every data sets.

  13. Histological and Transcriptomic Analysis during Bulbil Formation in Lilium lancifolium

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    Panpan Yang

    2017-08-01

    Full Text Available Aerial bulbils are an important propagative organ, playing an important role in population expansion. However, the detailed gene regulatory patterns and molecular mechanism underlying bulbil formation remain unclear. Triploid Lilium lancifolium, which develops many aerial bulbils on the leaf axils of middle-upper stem, is a useful species for investigating bulbil formation. To investigate the mechanism of bulbil formation in triploid L. lancifolium, we performed histological and transcriptomic analyses using samples of leaf axils located in the upper and lower stem of triploid L. lancifolium during bulbil formation. Histological results indicated that the bulbils of triploid L. lancifolium are derived from axillary meristems that initiate de novo from cells on the adaxial side of the petiole base. Transcriptomic analysis generated ~650 million high-quality reads and 11,871 differentially expressed genes (DEGs. Functional analysis showed that the DEGs were significantly enriched in starch and sucrose metabolism and plant hormone signal transduction. Starch synthesis and accumulation likely promoted the initiation of upper bulbils in triploid L. lancifolium. Hormone-associated pathways exhibited distinct patterns of change in each sample. Auxin likely promoted the initiation of bulbils and then inhibited further bulbil formation. High biosynthesis and low degradation of cytokinin might have led to bulbil formation in the upper leaf axil. The present study achieved a global transcriptomic analysis focused on gene expression changes and pathways' enrichment during upper bulbil formation in triploid L. lancifolium, laying a solid foundation for future molecular studies on bulbil formation.

  14. Utility of RNA Sequencing for Analysis of Maize Reproductive Transcriptomes

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    Rebecca M. Davidson

    2011-11-01

    Full Text Available Transcriptome sequencing is a powerful method for studying global expression patterns in large, complex genomes. Evaluation of sequence-based expression profiles during reproductive development would provide functional annotation to genes underlying agronomic traits. We generated transcriptome profiles for 12 diverse maize ( L. reproductive tissues representing male, female, developing seed, and leaf tissues using high throughput transcriptome sequencing. Overall, ∼80% of annotated genes were expressed. Comparative analysis between sequence and hybridization-based methods demonstrated the utility of ribonucleic acid sequencing (RNA-seq for expression determination and differentiation of paralagous genes (∼85% of maize genes. Analysis of 4975 gene families across reproductive tissues revealed expression divergence is proportional to family size. In all pairwise comparisons between tissues, 7 (pre- vs. postemergence cobs to 48% (pollen vs. ovule of genes were differentially expressed. Genes with expression restricted to a single tissue within this study were identified with the highest numbers observed in leaves, endosperm, and pollen. Coexpression network analysis identified 17 gene modules with complex and shared expression patterns containing many previously described maize genes. The data and analyses in this study provide valuable tools through improved gene annotation, gene family characterization, and a core set of candidate genes to further characterize maize reproductive development and improve grain yield potential.

  15. The Use of Atomic Force Microscopy for 3D Analysis of Nucleic Acid Hybridization on Microarrays.

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    Dubrovin, E V; Presnova, G V; Rubtsova, M Yu; Egorov, A M; Grigorenko, V G; Yaminsky, I V

    2015-01-01

    Oligonucleotide microarrays are considered today to be one of the most efficient methods of gene diagnostics. The capability of atomic force microscopy (AFM) to characterize the three-dimensional morphology of single molecules on a surface allows one to use it as an effective tool for the 3D analysis of a microarray for the detection of nucleic acids. The high resolution of AFM offers ways to decrease the detection threshold of target DNA and increase the signal-to-noise ratio. In this work, we suggest an approach to the evaluation of the results of hybridization of gold nanoparticle-labeled nucleic acids on silicon microarrays based on an AFM analysis of the surface both in air and in liquid which takes into account of their three-dimensional structure. We suggest a quantitative measure of the hybridization results which is based on the fraction of the surface area occupied by the nanoparticles.

  16. Global transcriptome analysis of developing chickpea (Cicer arietinum L.) seeds.

    Science.gov (United States)

    Pradhan, Seema; Bandhiwal, Nitesh; Shah, Niraj; Kant, Chandra; Gaur, Rashmi; Bhatia, Sabhyata

    2014-01-01

    Understanding developmental processes, especially in non-model crop plants, is extremely important in order to unravel unique mechanisms regulating development. Chickpea (C. arietinum L.) seeds are especially valued for their high carbohydrate and protein content. Therefore, in order to elucidate the mechanisms underlying seed development in chickpea, deep sequencing of transcriptomes from four developmental stages was undertaken. In this study, next generation sequencing platform was utilized to sequence the transcriptome of four distinct stages of seed development in chickpea. About 1.3 million reads were generated which were assembled into 51,099 unigenes by merging the de novo and reference assemblies. Functional annotation of the unigenes was carried out using the Uniprot, COG and KEGG databases. RPKM based digital expression analysis revealed specific gene activities at different stages of development which was validated using Real time PCR analysis. More than 90% of the unigenes were found to be expressed in at least one of the four seed tissues. DEGseq was used to determine differentially expressing genes which revealed that only 6.75% of the unigenes were differentially expressed at various stages. Homology based comparison revealed 17.5% of the unigenes to be putatively seed specific. Transcription factors were predicted based on HMM profiles built using TF sequences from five legume plants and analyzed for their differential expression during progression of seed development. Expression analysis of genes involved in biosynthesis of important secondary metabolites suggested that chickpea seeds can serve as a good source of antioxidants. Since transcriptomes are a valuable source of molecular markers like simple sequence repeats (SSRs), about 12,000 SSRs were mined in chickpea seed transcriptome and few of them were validated. In conclusion, this study will serve as a valuable resource for improved chickpea breeding.

  17. Global transcriptome analysis of developing chickpea (Cicer arietinum L. seeds

    Directory of Open Access Journals (Sweden)

    Seema ePradhan

    2014-12-01

    Full Text Available Understanding developmental processes, especially in non-model crop plants, is extremely important in order to unravel unique mechanisms regulating development. Chickpea (C. arietinum L. seeds are especially valued for their high carbohydrate and protein content. Therefore, in order to elucidate the mechanisms underlying seed development in chickpea, deep sequencing of transcriptomes from four developmental stages was undertaken. In this study, next generation sequencing platform was utilised to sequence the transcriptome of four distinct stages of seed development in chickpea. About 1.3 million reads were generated which were assembled into 51,099 unigenes by merging the de novo and reference assemblies. Functional annotation of the unigenes was carried out using the Uniprot, COG and KEGG databases. RPKM based digital expression analysis revealed specific gene activities at different stages of development which was validated using Real time PCR analysis. More than 90% of the unigenes were found to be expressed in at least one of the four seed tissues. DEGseq was used to determine differentially expressing genes which revealed that only 6.75% of the unigenes were differentially expressed at various stages. Homology based comparison revealed 17.5% of the unigenes to be putatively seed specific. Transcription factors were predicted based on HMM profiles built using TF sequences from five legume plants and analysed for their differential expression during progression of seed development. Expression analysis of genes involved in biosynthesis of important secondary metabolites suggested that chickpea seeds can serve as a good source of antioxidants. Since transcriptomes are a valuable source of molecular markers like simple sequence repeats (SSRs, about 12,000 SSRs were mined in chickpea seed transcriptome and few of them were validated. In conclusion, this study will serve as a valuable resource for improved chickpea breeding.

  18. Immunohistochemistry - Microarray Analysis of Patients with Peritoneal Metastases of Appendiceal or Colorectal Origin

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    Danielle E Green

    2015-01-01

    Full Text Available BackgroundThe value of immunohistochemistry (IHC-microarray analysis of pathological specimens in the management of patients is controversial although preliminary data suggests potential benefit. We describe the characteristics of patients undergoing a commercially available IHC-microarray method in patients with peritoneal metastases (PM and the feasibility of this technique in this population.MethodsWe retrospectively analyzed consecutive patients with pathologically confirmed PM from appendiceal or colorectal primary who underwent Caris Molecular IntelligenceTM testing. IHC, microarray, FISH and mutational analysis were included and stratified by PCI score, histology and treatment characteristics. Statistical analysis was performed using non-parametric tests.ResultsOur study included 5 patients with appendiceal and 11 with colorectal PM. The median age of patients was 51 (IQR 39-65 years, with 11(68% female. The median PCI score of the patients was 17(IQR 10-25. Hyperthermic intra-peritoneal chemoperfusion (HIPEC was performed in 4 (80% patients with appendiceal primary tumors and 4 (36% with colorectal primary. KRAS mutations were encountered in 40% of appendiceal vs. 30% colorectal tumors, while BRAF mutations were seen in 40% of colorectal PM and none of the patients with appendiceal PM (p=0.06. IHC biomarker expression was not significantly different between the two primaries. Sufficient tumor for microarray analysis was found in 44% (n=7 patients, which was not associated with previous use of chemotherapy (p>0.20 for 5-FU/LV, Irinotecan and Oxaliplatin.ConclusionsIn a small sample of patients with peritoneal metastases, the feasibility and results of IHC-microarray staining based on a commercially available test is reported. The apparent high incidence of the BRAF mutation in patients with PM may potentially offer opportunities for novel therapeutics and suggest that IHC-microarray is a method that can be used in this population.

  19. Global transcriptome analysis of spore formation in Myxococcus xanthus reveals a locus necessary for cell differentiation

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    Treuner-Lange Anke

    2010-04-01

    Full Text Available Abstract Background Myxococcus xanthus is a Gram negative bacterium that can differentiate into metabolically quiescent, environmentally resistant spores. Little is known about the mechanisms involved in differentiation in part because sporulation is normally initiated at the culmination of a complex starvation-induced developmental program and only inside multicellular fruiting bodies. To obtain a broad overview of the sporulation process and to identify novel genes necessary for differentiation, we instead performed global transcriptome analysis of an artificial chemically-induced sporulation process in which addition of glycerol to vegetatively growing liquid cultures of M. xanthus leads to rapid and synchronized differentiation of nearly all cells into myxospore-like entities. Results Our analyses identified 1 486 genes whose expression was significantly regulated at least two-fold within four hours of chemical-induced differentiation. Most of the previously identified sporulation marker genes were significantly upregulated. In contrast, most genes that are required to build starvation-induced multicellular fruiting bodies, but which are not required for sporulation per se, were not significantly regulated in our analysis. Analysis of functional gene categories significantly over-represented in the regulated genes, suggested large rearrangements in core metabolic pathways, and in genes involved in protein synthesis and fate. We used the microarray data to identify a novel operon of eight genes that, when mutated, rendered cells unable to produce viable chemical- or starvation-induced spores. Importantly, these mutants displayed no defects in building fruiting bodies, suggesting these genes are necessary for the core sporulation process. Furthermore, during the starvation-induced developmental program, these genes were expressed in fruiting bodies but not in peripheral rods, a subpopulation of developing cells which do not sporulate

  20. Microarray mRNA expression analysis of Fanconi anemia fibroblasts.

    Science.gov (United States)

    Galetzka, D; Weis, E; Rittner, G; Schindler, D; Haaf, T

    2008-01-01

    Fanconi anemia (FA) cells are generally hypersensitive to DNA cross-linking agents, implying that mutations in the different FANC genes cause a similar DNA repair defect(s). By using a customized cDNA microarray chip for DNA repair- and cell cycle-associated genes, we identified three genes, cathepsin B (CTSB), glutaredoxin (GLRX), and polo-like kinase 2 (PLK2), that were misregulated in untreated primary fibroblasts from three unrelated FA-D2 patients, compared to six controls. Quantitative real-time RT PCR was used to validate these results and to study possible molecular links between FA-D2 and other FA subtypes. GLRX was misregulated to opposite directions in a variety of different FA subtypes. Increased CTSB and decreased PLK2 expression was found in all or almost all of the analyzed complementation groups and, therefore, may be related to the defective FA pathway. Transcriptional upregulation of the CTSB proteinase appears to be a secondary phenomenon due to proliferation differences between FA and normal fibroblast cultures. In contrast, PLK2 is known to play a pivotal role in processes that are linked to FA defects and may contribute in multiple ways to the FA phenotype: PLK2 is a target gene for TP53, is likely to function as a tumor suppressor gene in hematologic neoplasia, and Plk2(-/-) mice are small because of defective embryonal development. (c) 2008 S. Karger AG, Basel.

  1. A probabilistic framework for microarray data analysis: fundamental probability models and statistical inference.

    Science.gov (United States)

    Ogunnaike, Babatunde A; Gelmi, Claudio A; Edwards, Jeremy S

    2010-05-21

    Gene expression studies generate large quantities of data with the defining characteristic that the number of genes (whose expression profiles are to be determined) exceed the number of available replicates by several orders of magnitude. Standard spot-by-spot analysis still seeks to extract useful information for each gene on the basis of the number of available replicates, and thus plays to the weakness of microarrays. On the other hand, because of the data volume, treating the entire data set as an ensemble, and developing theoretical distributions for these ensembles provides a framework that plays instead to the strength of microarrays. We present theoretical results that under reasonable assumptions, the distribution of microarray intensities follows the Gamma model, with the biological interpretations of the model parameters emerging naturally. We subsequently establish that for each microarray data set, the fractional intensities can be represented as a mixture of Beta densities, and develop a procedure for using these results to draw statistical inference regarding differential gene expression. We illustrate the results with experimental data from gene expression studies on Deinococcus radiodurans following DNA damage using cDNA microarrays. Copyright (c) 2010 Elsevier Ltd. All rights reserved.

  2. Analysis of the salivary gland transcriptome of Frankliniella occidentalis.

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    Candice A Stafford-Banks

    Full Text Available Saliva is known to play a crucial role in insect feeding behavior and virus transmission. Currently, little is known about the salivary glands and saliva of thrips, despite the fact that Frankliniella occidentalis (Pergande (the western flower thrips is a serious pest due to its destructive feeding, wide host range, and transmission of tospoviruses. As a first step towards characterizing thrips salivary gland functions, we sequenced the transcriptome of the primary salivary glands of F. occidentalis using short read sequencing (Illumina technology. A de novo-assembled transcriptome revealed 31,392 high quality contigs with an average size of 605 bp. A total of 12,166 contigs had significant BLASTx or tBLASTx hits (E≤1.0E-6 to known proteins, whereas a high percentage (61.24% of contigs had no apparent protein or nucleotide hits. Comparison of the F. occidentalis salivary gland transcriptome (sialotranscriptome against a published F. occidentalis full body transcriptome assembled from Roche-454 reads revealed several contigs with putative annotations associated with salivary gland functions. KEGG pathway analysis of the sialotranscriptome revealed that the majority (18 out of the top 20 predicted KEGG pathways of the salivary gland contig sequences match proteins involved in metabolism. We identified several genes likely to be involved in detoxification and inhibition of plant defense responses including aldehyde dehydrogenase, metalloprotease, glucose oxidase, glucose dehydrogenase, and regucalcin. We also identified several genes that may play a role in the extra-oral digestion of plant structural tissues including β-glucosidase and pectin lyase; and the extra-oral digestion of sugars, including α-amylase, maltase, sucrase, and α-glucosidase. This is the first analysis of a sialotranscriptome for any Thysanopteran species and it provides a foundational tool to further our understanding of how thrips interact with their plant hosts and the

  3. Evaluation of a gene information summarization system by users during the analysis process of microarray datasets

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    Cohen Aaron

    2009-02-01

    Full Text Available Abstract Background Summarization of gene information in the literature has the potential to help genomics researchers translate basic research into clinical benefits. Gene expression microarrays have been used to study biomarkers for disease and discover novel types of therapeutics and the task of finding information in journal articles on sets of genes is common for translational researchers working with microarray data. However, manually searching and scanning the literature references returned from PubMed is a time-consuming task for scientists. We built and evaluated an automatic summarizer of information on genes studied in microarray experiments. The Gene Information Clustering and Summarization System (GICSS is a system that integrates two related steps of the microarray data analysis process: functional gene clustering and gene information gathering. The system evaluation was conducted during the process of genomic researchers analyzing their own experimental microarray datasets. Results The clusters generated by GICSS were validated by scientists during their microarray analysis process. In addition, presenting sentences in the abstract provided significantly more important information to the users than just showing the title in the default PubMed format. Conclusion The evaluation results suggest that GICSS can be useful for researchers in genomic area. In addition, the hybrid evaluation method, partway between intrinsic and extrinsic system evaluation, may enable researchers to gauge the true usefulness of the tool for the scientists in their natural analysis workflow and also elicit suggestions for future enhancements. Availability GICSS can be accessed online at: http://ir.ohsu.edu/jianji/index.html

  4. Deep analysis of cellular transcriptomes – LongSAGE versus classic MPSS

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    Davis Simon J

    2007-09-01

    Full Text Available Abstract Background Deep transcriptome analysis will underpin a large fraction of post-genomic biology. 'Closed' technologies, such as microarray analysis, only detect the set of transcripts chosen for analysis, whereas 'open' e.g. tag-based technologies are capable of identifying all possible transcripts, including those that were previously uncharacterized. Although new technologies are now emerging, at present the major resources for open-type analysis are the many publicly available SAGE (serial analysis of gene expression and MPSS (massively parallel signature sequencing libraries. These technologies have never been compared for their utility in the context of deep transcriptome mining. Results We used a single LongSAGE library of 503,431 tags and a "classic" MPSS library of 1,744,173 tags, both prepared from the same T cell-derived RNA sample, to compare the ability of each method to probe, at considerable depth, a human cellular transcriptome. We show that even though LongSAGE is more error-prone than MPSS, our LongSAGE library nevertheless generated 6.3-fold more genome-matching (and therefore likely error-free tags than the MPSS library. An analysis of a set of 8,132 known genes detectable by both methods, and for which there is no ambiguity about tag matching, shows that MPSS detects only half (54% the number of transcripts identified by SAGE (3,617 versus 1,955. Analysis of two additional MPSS libraries shows that each library samples a different subset of transcripts, and that in combination the three MPSS libraries (4,274,992 tags in total still only detect 73% of the genes identified in our test set using SAGE. The fraction of transcripts detected by MPSS is likely to be even lower for uncharacterized transcripts, which tend to be more weakly expressed. The source of the loss of complexity in MPSS libraries compared to SAGE is unclear, but its effects become more severe with each sequencing cycle (i.e. as MPSS tag length increases

  5. Gene ARMADA: an integrated multi-analysis platform for microarray data implemented in MATLAB.

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    Chatziioannou, Aristotelis; Moulos, Panagiotis; Kolisis, Fragiskos N

    2009-10-27

    The microarray data analysis realm is ever growing through the development of various tools, open source and commercial. However there is absence of predefined rational algorithmic analysis workflows or batch standardized processing to incorporate all steps, from raw data import up to the derivation of significantly differentially expressed gene lists. This absence obfuscates the analytical procedure and obstructs the massive comparative processing of genomic microarray datasets. Moreover, the solutions provided, heavily depend on the programming skills of the user, whereas in the case of GUI embedded solutions, they do not provide direct support of various raw image analysis formats or a versatile and simultaneously flexible combination of signal processing methods. We describe here Gene ARMADA (Automated Robust MicroArray Data Analysis), a MATLAB implemented platform with a Graphical User Interface. This suite integrates all steps of microarray data analysis including automated data import, noise correction and filtering, normalization, statistical selection of differentially expressed genes, clustering, classification and annotation. In its current version, Gene ARMADA fully supports 2 coloured cDNA and Affymetrix oligonucleotide arrays, plus custom arrays for which experimental details are given in tabular form (Excel spreadsheet, comma separated values, tab-delimited text formats). It also supports the analysis of already processed results through its versatile import editor. Besides being fully automated, Gene ARMADA incorporates numerous functionalities of the Statistics and Bioinformatics Toolboxes of MATLAB. In addition, it provides numerous visualization and exploration tools plus customizable export data formats for seamless integration by other analysis tools or MATLAB, for further processing. Gene ARMADA requires MATLAB 7.4 (R2007a) or higher and is also distributed as a stand-alone application with MATLAB Component Runtime. Gene ARMADA provides a

  6. Immunohistochemical analysis of breast tissue microarray images using contextual classifiers

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    Stephen J McKenna

    2013-01-01

    Full Text Available Background: Tissue microarrays (TMAs are an important tool in translational research for examining multiple cancers for molecular and protein markers. Automatic immunohistochemical (IHC scoring of breast TMA images remains a challenging problem. Methods: A two-stage approach that involves localization of regions of invasive and in-situ carcinoma followed by ordinal IHC scoring of nuclei in these regions is proposed. The localization stage classifies locations on a grid as tumor or non-tumor based on local image features. These classifications are then refined using an auto-context algorithm called spin-context. Spin-context uses a series of classifiers to integrate image feature information with spatial context information in the form of estimated class probabilities. This is achieved in a rotationally-invariant manner. The second stage estimates ordinal IHC scores in terms of the strength of staining and the proportion of nuclei stained. These estimates take the form of posterior probabilities, enabling images with uncertain scores to be referred for pathologist review. Results: The method was validated against manual pathologist scoring on two nuclear markers, progesterone receptor (PR and estrogen receptor (ER. Errors for PR data were consistently lower than those achieved with ER data. Scoring was in terms of estimated proportion of cells that were positively stained (scored on an ordinal scale of 0-6 and perceived strength of staining (scored on an ordinal scale of 0-3. Average absolute differences between predicted scores and pathologist-assigned scores were 0.74 for proportion of cells and 0.35 for strength of staining (PR. Conclusions: The use of context information via spin-context improved the precision and recall of tumor localization. The combination of the spin-context localization method with the automated scoring method resulted in reduced IHC scoring errors.

  7. [SSR loci information analysis in transcriptome of Andrographis paniculata].

    Science.gov (United States)

    Li, Jun-Ren; Chen, Xiu-Zhen; Tang, Xiao-Ting; He, Rui; Zhan, Ruo-Ting

    2018-06-01

    To study the SSR loci information and develop molecular markers, a total of 43 683 Unigenes in transcriptome of Andrographis paniculata were used to explore SSR. The distribution frequency of SSR and the basic characteristics of repeat motifs were analyzed using MicroSAtellite software, SSR primers were designed by Primer 3.0 software and then validated by PCR. Moreover, the gene function analysis of SSR Unigene was obtained by Blast. The results showed that 14 135 SSR loci were found in the transcriptome of A. paniculata, which distributed in 9 973 Unigenes with a distribution frequency of 32.36%. Di-nucleotide and Tri-nucleotide repeat were the main types, accounted for 75.54% of all SSRs. The repeat motifs of AT/AT and CCG/CGG were the predominant repeat types of Di-nucleotide and Tri-nucleotide, respectively. A total of 4 740 pairs of SSR primers with the potential to produce polymorphism were designed for maker development. Ten pairs of primers in 20 pairs of randomly picked primers produced fragments with expected molecular size. The gene function of Unigenes containing SSR were mostly related to the basic metabolism function of A. paniculata. The SSR markers in transcriptome of A. paniculata show rich type, strong specificity and high potential of polymorphism, which will benefit the candidate gene mining and marker-assisted breeding. Copyright© by the Chinese Pharmaceutical Association.

  8. Transcriptome analysis of the Asian honey bee Apis cerana cerana.

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    Zi Long Wang

    Full Text Available BACKGROUND: The Eastern hive honey bee, Apis cerana cerana is a native and widely bred honey bee species in China. Molecular biology research about this honey bee species is scarce, and genomic information for A. c. cerana is not currently available. Transcriptome and expression profiling data for this species are therefore important resources needed to better understand the biological mechanisms of A. c. cerana. In this study, we obtained the transcriptome information of A. c. cerana by RNA-sequencing and compared gene expression differences between queens and workers of A. c. cerana by digital gene expression (DGE analysis. RESULTS: Using high-throughput Illumina RNA sequencing we obtained 51,581,510 clean reads corresponding to 4.64 Gb total nucleotides from a single run. These reads were assembled into 46,999 unigenes with a mean length of 676 bp. Based on a sequence similarity search against the five public databases (NR, Swissport, GO, COG, KEGG with a cut-off E-value of 10(-5 using BLASTX, a total of 24,630 unigenes were annotated with gene descriptions, gene ontology terms, or metabolic pathways. Using these transcriptome data as references we analyzed the gene expression differences between the queens and workers of A. c. cerana using a tag-based digital gene expression method. We obtained 5.96 and 5.66 million clean tags from the queen and worker samples, respectively. A total of 414 genes were differentially expressed between them, with 189 up-regulated and 225 down-regulated in queens. CONCLUSIONS: Our transcriptome data provide a comprehensive sequence resource for future A. c. cerana study, establishing an important public information platform for functional genomic studies in A. c. cerana. Furthermore, the DGE data provide comprehensive gene expression information for the queens and workers, which will facilitate our understanding of the molecular mechanisms of the different physiological aspects of the two castes.

  9. Transcriptome and proteomic analysis of mango (Mangifera indica Linn) fruits.

    Science.gov (United States)

    Wu, Hong-xia; Jia, Hui-min; Ma, Xiao-wei; Wang, Song-biao; Yao, Quan-sheng; Xu, Wen-tian; Zhou, Yi-gang; Gao, Zhong-shan; Zhan, Ru-lin

    2014-06-13

    Here we used Illumina RNA-seq technology for transcriptome sequencing of a mixed fruit sample from 'Zill' mango (Mangifera indica Linn) fruit pericarp and pulp during the development and ripening stages. RNA-seq generated 68,419,722 sequence reads that were assembled into 54,207 transcripts with a mean length of 858bp, including 26,413 clusters and 27,794 singletons. A total of 42,515(78.43%) transcripts were annotated using public protein databases, with a cut-off E-value above 10(-5), of which 35,198 and 14,619 transcripts were assigned to gene ontology terms and clusters of orthologous groups respectively. Functional annotation against the Kyoto Encyclopedia of Genes and Genomes database identified 23,741(43.79%) transcripts which were mapped to 128 pathways. These pathways revealed many previously unknown transcripts. We also applied mass spectrometry-based transcriptome data to characterize the proteome of ripe fruit. LC-MS/MS analysis of the mango fruit proteome was using tandem mass spectrometry (MS/MS) in an LTQ Orbitrap Velos (Thermo) coupled online to the HPLC. This approach enabled the identification of 7536 peptides that matched 2754 proteins. Our study provides a comprehensive sequence for a systemic view of transcriptome during mango fruit development and the most comprehensive fruit proteome to date, which are useful for further genomics research and proteomic studies. Our study provides a comprehensive sequence for a systemic view of both the transcriptome and proteome of mango fruit, and a valuable reference for further research on gene expression and protein identification. This article is part of a Special Issue entitled: Proteomics of non-model organisms. Copyright © 2014 Elsevier B.V. All rights reserved.

  10. Microarray analysis of gender- and parasite-specific gene transcription in Strongyloides ratti

    NARCIS (Netherlands)

    Evans, Helen; Mello, Luciane V.; Fang, Yongxiang; Wit, Ernst; Thompson, Fiona J.; Viney, Mark E.; Paterson, Steve

    2008-01-01

    The molecular mechanisms by which parasitic nematodes reproduce and have adapted to life within a host are unclear. In the present study, microarray analysis was used to explore differential transcription among the different stages and sexes of Strongyloides ratti, a parasitic nematode of brown

  11. Diagnostic Yield of Chromosomal Microarray Analysis in an Autism Primary Care Practice: Which Guidelines to Implement?

    Science.gov (United States)

    McGrew, Susan G.; Peters, Brittany R.; Crittendon, Julie A.; Veenstra-VanderWeele, Jeremy

    2012-01-01

    Genetic testing is recommended for patients with ASD; however specific recommendations vary by specialty. American Academy of Pediatrics and American Academy of Neurology guidelines recommend G-banded karyotype and Fragile X DNA. The American College of Medical Genetics recommends Chromosomal Microarray Analysis (CMA). We determined the yield of…

  12. The Utility of Chromosomal Microarray Analysis in Developmental and Behavioral Pediatrics

    Science.gov (United States)

    Beaudet, Arthur L.

    2013-01-01

    Chromosomal microarray analysis (CMA) has emerged as a powerful new tool to identify genomic abnormalities associated with a wide range of developmental disabilities including congenital malformations, cognitive impairment, and behavioral abnormalities. CMA includes array comparative genomic hybridization (CGH) and single nucleotide polymorphism…

  13. Enhancing Interdisciplinary Mathematics and Biology Education: A Microarray Data Analysis Course Bridging These Disciplines

    Science.gov (United States)

    Tra, Yolande V.; Evans, Irene M.

    2010-01-01

    "BIO2010" put forth the goal of improving the mathematical educational background of biology students. The analysis and interpretation of microarray high-dimensional data can be very challenging and is best done by a statistician and a biologist working and teaching in a collaborative manner. We set up such a collaboration and designed a course on…

  14. CoryneCenter – An online resource for the integrated analysis of corynebacterial genome and transcriptome data

    Directory of Open Access Journals (Sweden)

    Hüser Andrea T

    2007-11-01

    Full Text Available Abstract Background The introduction of high-throughput genome sequencing and post-genome analysis technologies, e.g. DNA microarray approaches, has created the potential to unravel and scrutinize complex gene-regulatory networks on a large scale. The discovery of transcriptional regulatory interactions has become a major topic in modern functional genomics. Results To facilitate the analysis of gene-regulatory networks, we have developed CoryneCenter, a web-based resource for the systematic integration and analysis of genome, transcriptome, and gene regulatory information for prokaryotes, especially corynebacteria. For this purpose, we extended and combined the following systems into a common platform: (1 GenDB, an open source genome annotation system, (2 EMMA, a MAGE compliant application for high-throughput transcriptome data storage and analysis, and (3 CoryneRegNet, an ontology-based data warehouse designed to facilitate the reconstruction and analysis of gene regulatory interactions. We demonstrate the potential of CoryneCenter by means of an application example. Using microarray hybridization data, we compare the gene expression of Corynebacterium glutamicum under acetate and glucose feeding conditions: Known regulatory networks are confirmed, but moreover CoryneCenter points out additional regulatory interactions. Conclusion CoryneCenter provides more than the sum of its parts. Its novel analysis and visualization features significantly simplify the process of obtaining new biological insights into complex regulatory systems. Although the platform currently focusses on corynebacteria, the integrated tools are by no means restricted to these species, and the presented approach offers a general strategy for the analysis and verification of gene regulatory networks. CoryneCenter provides freely accessible projects with the underlying genome annotation, gene expression, and gene regulation data. The system is publicly available at http://www.CoryneCenter.de.

  15. Transcriptome analysis of adiposity in domestic ducks by transcriptomic comparison with their wild counterparts.

    Science.gov (United States)

    Chen, L; Luo, J; Li, J X; Li, J J; Wang, D Q; Tian, Y; Lu, L Z

    2015-06-01

    Excessive adiposity is a major problem in the duck industry, but its molecular mechanisms remain unknown. Genetic comparisons between domestic and wild animals have contributed to the exploration of genetic mechanisms responsible for many phenotypic traits. Significant differences in body fat mass have been detected between domestic and wild ducks. In this study, we used the Peking duck and Anas platyrhynchos as the domestic breed and wild counterpart respectively and performed a transcriptomic comparison of abdominal fat between the two breeds to comprehensively analyze the transcriptome basis of adiposity in ducks. We obtained approximately 350 million clean reads; assembled 61 250 transcripts, including 23 699 novel ones; and identified alternative 5' splice sites, alternative 3' splice sites, skipped exons and retained intron as the main alternative splicing events. A differential expression analysis between the two breeds showed that 753 genes exhibited differential expression. In Peking ducks, some lipid metabolism-related genes (IGF2, FABP5, BMP7, etc.) and oncogenes (RRM2, AURKA, CYR61, etc.) were upregulated, whereas genes related to tumor suppression and immunity (TNFRSF19, TNFAIP6, IGSF21, NCF1, etc.) were downregulated, suggesting adiposity might closely associate with tumorigenesis in ducks. Furthermore, 280 576 single-nucleotide variations were found differentiated between the two breeds, including 8641 non-synonymous ones, and some of the non-synonymous ones were found enriched in genes involved in lipid-associated and immune-associated pathways, suggesting abdominal fat of the duck undertakes both a metabolic function and immune-related function. These datasets enlarge our genetic information of ducks and provide valuable resources for analyzing mechanisms underlying adiposity in ducks. © 2015 Stichting International Foundation for Animal Genetics.

  16. Robust gene selection methods using weighting schemes for microarray data analysis.

    Science.gov (United States)

    Kang, Suyeon; Song, Jongwoo

    2017-09-02

    A common task in microarray data analysis is to identify informative genes that are differentially expressed between two different states. Owing to the high-dimensional nature of microarray data, identification of significant genes has been essential in analyzing the data. However, the performances of many gene selection techniques are highly dependent on the experimental conditions, such as the presence of measurement error or a limited number of sample replicates. We have proposed new filter-based gene selection techniques, by applying a simple modification to significance analysis of microarrays (SAM). To prove the effectiveness of the proposed method, we considered a series of synthetic datasets with different noise levels and sample sizes along with two real datasets. The following findings were made. First, our proposed methods outperform conventional methods for all simulation set-ups. In particular, our methods are much better when the given data are noisy and sample size is small. They showed relatively robust performance regardless of noise level and sample size, whereas the performance of SAM became significantly worse as the noise level became high or sample size decreased. When sufficient sample replicates were available, SAM and our methods showed similar performance. Finally, our proposed methods are competitive with traditional methods in classification tasks for microarrays. The results of simulation study and real data analysis have demonstrated that our proposed methods are effective for detecting significant genes and classification tasks, especially when the given data are noisy or have few sample replicates. By employing weighting schemes, we can obtain robust and reliable results for microarray data analysis.

  17. NMD Microarray Analysis for Rapid Genome-Wide Screen of Mutated Genes in Cancer

    Directory of Open Access Journals (Sweden)

    Maija Wolf

    2005-01-01

    Full Text Available Gene mutations play a critical role in cancer development and progression, and their identification offers possibilities for accurate diagnostics and therapeutic targeting. Finding genes undergoing mutations is challenging and slow, even in the post-genomic era. A new approach was recently developed by Noensie and Dietz to prioritize and focus the search, making use of nonsense-mediated mRNA decay (NMD inhibition and microarray analysis (NMD microarrays in the identification of transcripts containing nonsense mutations. We combined NMD microarrays with array-based CGH (comparative genomic hybridization in order to identify inactivation of tumor suppressor genes in cancer. Such a “mutatomics” screening of prostate cancer cell lines led to the identification of inactivating mutations in the EPHB2 gene. Up to 8% of metastatic uncultured prostate cancers also showed mutations of this gene whose loss of function may confer loss of tissue architecture. NMD microarray analysis could turn out to be a powerful research method to identify novel mutated genes in cancer cell lines, providing targets that could then be further investigated for their clinical relevance and therapeutic potential.

  18. Goober: A fully integrated and user-friendly microarray data management and analysis solution for core labs and bench biologists

    Directory of Open Access Journals (Sweden)

    Luo Wen

    2009-03-01

    Full Text Available Despite the large number of software tools developed to address different areas of microarray data analysis, very few offer an all-in-one solution with little learning curve. For microarray core labs, there are even fewer software packages available to help with their routine but critical tasks, such as data quality control (QC and inventory management. We have developed a simple-to-use web portal to allow bench biologists to analyze and query complicated microarray data and related biological pathways without prior training. Both experiment-based and gene-based analysis can be easily performed, even for the first-time user, through the intuitive multi-layer design and interactive graphic links. While being friendly to inexperienced users, most parameters in Goober can be easily adjusted via drop-down menus to allow advanced users to tailor their needs and perform more complicated analysis. Moreover, we have integrated graphic pathway analysis into the website to help users examine microarray data within the relevant biological content. Goober also contains features that cover most of the common tasks in microarray core labs, such as real time array QC, data loading, array usage and inventory tracking. Overall, Goober is a complete microarray solution to help biologists instantly discover valuable information from a microarray experiment and enhance the quality and productivity of microarray core labs. The whole package is freely available at http://sourceforge.net/projects/goober. A demo web server is available at http://www.goober-array.org.

  19. Exploratory transcriptomic analysis in muscle tissue of broilers fed a phytase-supplemented diet.

    Science.gov (United States)

    Schmeisser, J; Séon, A-A; Aureli, R; Friedel, A; Guggenbuhl, P; Duval, S; Cowieson, A J; Fru-Nji, F

    2017-06-01

    The effect of phytase on phosphorus retention, broiler (Gallus gallus) performance and bone mineralization in diets with reduced inorganic phosphate concentration is well documented. Furthermore, so-called 'extra-phosphoric' effects of phytase have been described in the literature that may be associated with changes in mineral and amino acid partitioning and requirements per se. In particular, the role of myo-inositol in phytase responses is implied but not well elucidated. It was the purpose of the experiment reported herein to explore the effect of phytase on broiler growth, nutrient digestibility, blood biochemistry and gene expression. A 5-week broiler floor pen trial was conducted to evaluate the effect of supplementation of a moderately phosphorus-deficient diet with 1000 U/kg of a 6-microbial phytase. Parameters measured were growth performance, phosphorus (P), calcium (Ca) and myo-inositol plasma concentrations, apparent ileal P digestibility, bone mineralization, breast meat weight and Pectoralis major muscle transcriptome. Supplementation of the diet with phytase improved weight gain during the starter period (18%) and the whole period (24%) compared with animals that received the control diet (p phytase. The transcriptomic analysis revealed that some differentially expressed genes (DEG) in broilers, receiving phytase in comparison with animals fed reduced phosphorus diet without phytase, were part of pathways involved in muscle development, via calmodulin/calcineurin and insulin-like growth factor. Microarray data confirmation was performed on six genes by quantitative PCR (qPCR): PI3K regulatory and catalytic subunit, Phospholipase C beta, Myocyte Enhancer Factors 2A and 2C, and calcineurin A. The results suggested that dietary supplementation with this phytase could generate low molecular weight phytate esters and indirectly myo-inositol, and could help us to understand how muscle metabolism may be affected at a gene level. Journal of Animal

  20. Comparative analysis of gene expression by microarray analysis of male and female flowers of Asparagus officinalis.

    Science.gov (United States)

    Gao, Wu-Jun; Li, Shu-Fen; Zhang, Guo-Jun; Wang, Ning-Na; Deng, Chuan-Liang; Lu, Long-Dou

    2013-01-01

    To identify rapidly a number of genes probably involved in sex determination and differentiation of the dioecious plant Asparagus officinalis, gene expression profiles in early flower development for male and female plants were investigated by microarray assay with 8,665 probes. In total, 638 male-biased and 543 female-biased genes were identified. These genes with biased-expression for male and female were involved in a variety of processes associated with molecular functions, cellular components, and biological processes, suggesting that a complex mechanism underlies the sex development of asparagus. Among the differentially expressed genes involved in the reproductive process, a number of genes associated with floral development were identified. Reverse transcription-PCR was performed for validation, and the results were largely consistent with those obtained by microarray analysis. The findings of this study might contribute to understanding of the molecular mechanisms of sex determination and differentiation in dioecious asparagus and provide a foundation for further studies of this plant.

  1. A non-parametric meta-analysis approach for combining independent microarray datasets: application using two microarray datasets pertaining to chronic allograft nephropathy

    Directory of Open Access Journals (Sweden)

    Archer Kellie J

    2008-02-01

    Full Text Available Abstract Background With the popularity of DNA microarray technology, multiple groups of researchers have studied the gene expression of similar biological conditions. Different methods have been developed to integrate the results from various microarray studies, though most of them rely on distributional assumptions, such as the t-statistic based, mixed-effects model, or Bayesian model methods. However, often the sample size for each individual microarray experiment is small. Therefore, in this paper we present a non-parametric meta-analysis approach for combining data from independent microarray studies, and illustrate its application on two independent Affymetrix GeneChip studies that compared the gene expression of biopsies from kidney transplant recipients with chronic allograft nephropathy (CAN to those with normal functioning allograft. Results The simulation study comparing the non-parametric meta-analysis approach to a commonly used t-statistic based approach shows that the non-parametric approach has better sensitivity and specificity. For the application on the two CAN studies, we identified 309 distinct genes that expressed differently in CAN. By applying Fisher's exact test to identify enriched KEGG pathways among those genes called differentially expressed, we found 6 KEGG pathways to be over-represented among the identified genes. We used the expression measurements of the identified genes as predictors to predict the class labels for 6 additional biopsy samples, and the predicted results all conformed to their pathologist diagnosed class labels. Conclusion We present a new approach for combining data from multiple independent microarray studies. This approach is non-parametric and does not rely on any distributional assumptions. The rationale behind the approach is logically intuitive and can be easily understood by researchers not having advanced training in statistics. Some of the identified genes and pathways have been

  2. Knowledge-based analysis of microarrays for the discovery of transcriptional regulation relationships.

    Science.gov (United States)

    Seok, Junhee; Kaushal, Amit; Davis, Ronald W; Xiao, Wenzhong

    2010-01-18

    The large amount of high-throughput genomic data has facilitated the discovery of the regulatory relationships between transcription factors and their target genes. While early methods for discovery of transcriptional regulation relationships from microarray data often focused on the high-throughput experimental data alone, more recent approaches have explored the integration of external knowledge bases of gene interactions. In this work, we develop an algorithm that provides improved performance in the prediction of transcriptional regulatory relationships by supplementing the analysis of microarray data with a new method of integrating information from an existing knowledge base. Using a well-known dataset of yeast microarrays and the Yeast Proteome Database, a comprehensive collection of known information of yeast genes, we show that knowledge-based predictions demonstrate better sensitivity and specificity in inferring new transcriptional interactions than predictions from microarray data alone. We also show that comprehensive, direct and high-quality knowledge bases provide better prediction performance. Comparison of our results with ChIP-chip data and growth fitness data suggests that our predicted genome-wide regulatory pairs in yeast are reasonable candidates for follow-up biological verification. High quality, comprehensive, and direct knowledge bases, when combined with appropriate bioinformatic algorithms, can significantly improve the discovery of gene regulatory relationships from high throughput gene expression data.

  3. Generalized Correlation Coefficient for Non-Parametric Analysis of Microarray Time-Course Data

    DEFF Research Database (Denmark)

    Tan, Qihua; Thomassen, Mads; Burton, Mark

    2017-01-01

    the heterogeneous time-course gene expression patterns. Application of the method identified nonlinear time-course patterns in high agreement with parametric analysis. We conclude that the non-parametric nature in the generalized correlation analysis could be an useful and efficient tool for analyzing microarray...... time-course data and for exploring the complex relationships in the omics data for studying their association with disease and health....

  4. A comprehensive sensitivity analysis of microarray breast cancer classification under feature variability

    Directory of Open Access Journals (Sweden)

    Reinders Marcel JT

    2009-11-01

    Full Text Available Abstract Background Large discrepancies in signature composition and outcome concordance have been observed between different microarray breast cancer expression profiling studies. This is often ascribed to differences in array platform as well as biological variability. We conjecture that other reasons for the observed discrepancies are the measurement error associated with each feature and the choice of preprocessing method. Microarray data are known to be subject to technical variation and the confidence intervals around individual point estimates of expression levels can be wide. Furthermore, the estimated expression values also vary depending on the selected preprocessing scheme. In microarray breast cancer classification studies, however, these two forms of feature variability are almost always ignored and hence their exact role is unclear. Results We have performed a comprehensive sensitivity analysis of microarray breast cancer classification under the two types of feature variability mentioned above. We used data from six state of the art preprocessing methods, using a compendium consisting of eight diferent datasets, involving 1131 hybridizations, containing data from both one and two-color array technology. For a wide range of classifiers, we performed a joint study on performance, concordance and stability. In the stability analysis we explicitly tested classifiers for their noise tolerance by using perturbed expression profiles that are based on uncertainty information directly related to the preprocessing methods. Our results indicate that signature composition is strongly influenced by feature variability, even if the array platform and the stratification of patient samples are identical. In addition, we show that there is often a high level of discordance between individual class assignments for signatures constructed on data coming from different preprocessing schemes, even if the actual signature composition is identical

  5. Transcriptome and proteome analysis of Eucalyptus infected with Calonectria pseudoreteaudii.

    Science.gov (United States)

    Chen, Quanzhu; Guo, Wenshuo; Feng, Lizhen; Ye, Xiaozhen; Xie, Wanfeng; Huang, Xiuping; Liu, Jinyan

    2015-02-06

    Cylindrocladium leaf blight is one of the most severe diseases in Eucalyptus plantations and nurseries. There are Eucalyptus cultivars with resistance to the disease. However, little is known about the defense mechanism of resistant cultivars. Here, we investigated the transcriptome and proteome of Eucalyptus leaves (E. urophylla×E. tereticornis M1), infected or not with Calonectria pseudoreteaudii. A total of 8585 differentially expressed genes (|log2 ratio| ≥1, FDR ≤0.001) at 12 and 24hours post-inoculation were detected using RNA-seq. Transcriptional changes for five genes were further confirmed by qRT-PCR. A total of 3680 proteins at the two time points were identified using iTRAQ technique.The combined transcriptome and proteome analysis revealed that the shikimate/phenylpropanoid pathway, terpenoid biosynthesis, signalling pathway (jasmonic acid and sugar) were activated. The data also showed that some proteins (WRKY33 and PR proteins) which have been reported to involve in plant defense response were up-regulated. However, photosynthesis, nucleic acid metabolism and protein metabolism were impaired by the infection of C. pseudoreteaudii. This work will facilitate the identification of defense related genes and provide insights into Eucalyptus defense responses to Cylindrocladium leaf blight. In this study, a total of 130 proteins and genes involved in the shikimate/phenylpropanoid pathway, terpenoid biosynthesis, signalling pathway, cell transport, carbohydrate and energy metabolism, nucleic acid metabolism and protein metabolism in Eucalyptus leaves after infected with C. pseudoreteaudii were identified. This is the first report of a comprehensive transcriptomic and proteomic analysis of Eucalyptus in response to Calonectria sp. Copyright © 2014 Elsevier B.V. All rights reserved.

  6. Transcriptomic analysis of flower development in wintersweet (Chimonanthus praecox).

    Science.gov (United States)

    Liu, Daofeng; Sui, Shunzhao; Ma, Jing; Li, Zhineng; Guo, Yulong; Luo, Dengpan; Yang, Jianfeng; Li, Mingyang

    2014-01-01

    Wintersweet (Chimonanthus praecox) is familiar as a garden plant and woody ornamental flower. On account of its unique flowering time and strong fragrance, it has a high ornamental and economic value. Despite a long history of human cultivation, our understanding of wintersweet genetics and molecular biology remains scant, reflecting a lack of basic genomic and transcriptomic data. In this study, we assembled three cDNA libraries, from three successive stages in flower development, designated as the flower bud with displayed petal, open flower and senescing flower stages. Using the Illumina RNA-Seq method, we obtained 21,412,928, 26,950,404, 24,912,954 qualified Illumina reads, respectively, for the three successive stages. The pooled reads from all three libraries were then assembled into 106,995 transcripts, 51,793 of which were annotated in the NCBI non-redundant protein database. Of these annotated sequences, 32,649 and 21,893 transcripts were assigned to gene ontology categories and clusters of orthologous groups, respectively. We could map 15,587 transcripts onto 312 pathways using the Kyoto Encyclopedia of Genes and Genomes pathway database. Based on these transcriptomic data, we obtained a large number of candidate genes that were differentially expressed at the open flower and senescing flower stages. An analysis of differentially expressed genes involved in plant hormone signal transduction pathways indicated that although flower opening and senescence may be independent of the ethylene signaling pathway in wintersweet, salicylic acid may be involved in the regulation of flower senescence. We also succeeded in isolating key genes of floral scent biosynthesis and proposed a biosynthetic pathway for monoterpenes and sesquiterpenes in wintersweet flowers, based on the annotated sequences. This comprehensive transcriptomic analysis presents fundamental information on the genes and pathways which are involved in flower development in wintersweet. And our data

  7. Leading edge analysis of transcriptomic changes during pseudorabies virus infection

    Directory of Open Access Journals (Sweden)

    Damarius S. Fleming

    2016-12-01

    Full Text Available Eight RNA samples taken from the tracheobronchial lymph nodes (TBLN of pigs that were either infected or non-infected with a feral isolate of porcine pseudorabies virus (PRV were used to investigate changes in gene expression related to the pathogen. The RNA was processed into fastq files for each library prior to being analyzed using Illumina Digital Gene Expression Tag Profiling sequences (DGETP which were used as the downstream measure of differential expression. Analyzed tags consisted of 21 base pair sequences taken from time points 1, 3, 6, and 14 days' post infection (dpi that generated 1,927,547 unique tag sequences. Tag sequences were analyzed for differential transcript expression and gene set enrichment analysis (GSEA to uncover transcriptomic changes related to PRV pathology progression. In conjunction with the DGETP and GSEA, the study also incorporated use of leading edge analysis to help link the TBLN transcriptome data to clinical progression of PRV at each of the sampled time points. The purpose of this manuscript is to provide useful background on applying the leading edge analysis to GSEA and expression data to help identify genes considered to be of high biological interest. The data in the form of fastq files has been uploaded to the NCBI Gene Expression Omnibus (GEO (GSE74473 database.

  8. Leading edge analysis of transcriptomic changes during pseudorabies virus infection.

    Science.gov (United States)

    Fleming, Damarius S; Miller, Laura C

    2016-12-01

    Eight RNA samples taken from the tracheobronchial lymph nodes (TBLN) of pigs that were either infected or non-infected with a feral isolate of porcine pseudorabies virus (PRV) were used to investigate changes in gene expression related to the pathogen. The RNA was processed into fastq files for each library prior to being analyzed using Illumina Digital Gene Expression Tag Profiling sequences (DGETP) which were used as the downstream measure of differential expression. Analyzed tags consisted of 21 base pair sequences taken from time points 1, 3, 6, and 14 days' post infection (dpi) that generated 1,927,547 unique tag sequences. Tag sequences were analyzed for differential transcript expression and gene set enrichment analysis (GSEA) to uncover transcriptomic changes related to PRV pathology progression. In conjunction with the DGETP and GSEA, the study also incorporated use of leading edge analysis to help link the TBLN transcriptome data to clinical progression of PRV at each of the sampled time points. The purpose of this manuscript is to provide useful background on applying the leading edge analysis to GSEA and expression data to help identify genes considered to be of high biological interest. The data in the form of fastq files has been uploaded to the NCBI Gene Expression Omnibus (GEO) (GSE74473) database.

  9. GEPAS, a web-based tool for microarray data analysis and interpretation

    Science.gov (United States)

    Tárraga, Joaquín; Medina, Ignacio; Carbonell, José; Huerta-Cepas, Jaime; Minguez, Pablo; Alloza, Eva; Al-Shahrour, Fátima; Vegas-Azcárate, Susana; Goetz, Stefan; Escobar, Pablo; Garcia-Garcia, Francisco; Conesa, Ana; Montaner, David; Dopazo, Joaquín

    2008-01-01

    Gene Expression Profile Analysis Suite (GEPAS) is one of the most complete and extensively used web-based packages for microarray data analysis. During its more than 5 years of activity it has continuously been updated to keep pace with the state-of-the-art in the changing microarray data analysis arena. GEPAS offers diverse analysis options that include well established as well as novel algorithms for normalization, gene selection, class prediction, clustering and functional profiling of the experiment. New options for time-course (or dose-response) experiments, microarray-based class prediction, new clustering methods and new tests for differential expression have been included. The new pipeliner module allows automating the execution of sequential analysis steps by means of a simple but powerful graphic interface. An extensive re-engineering of GEPAS has been carried out which includes the use of web services and Web 2.0 technology features, a new user interface with persistent sessions and a new extended database of gene identifiers. GEPAS is nowadays the most quoted web tool in its field and it is extensively used by researchers of many countries and its records indicate an average usage rate of 500 experiments per day. GEPAS, is available at http://www.gepas.org. PMID:18508806

  10. Domain-enhanced analysis of microarray data using GO annotations.

    Science.gov (United States)

    Liu, Jiajun; Hughes-Oliver, Jacqueline M; Menius, J Alan

    2007-05-15

    New biological systems technologies give scientists the ability to measure thousands of bio-molecules including genes, proteins, lipids and metabolites. We use domain knowledge, e.g. the Gene Ontology, to guide analysis of such data. By focusing on domain-aggregated results at, say the molecular function level, increased interpretability is available to biological scientists beyond what is possible if results are presented at the gene level. We use a 'top-down' approach to perform domain aggregation by first combining gene expressions before testing for differentially expressed patterns. This is in contrast to the more standard 'bottom-up' approach, where genes are first tested individually then aggregated by domain knowledge. The benefits are greater sensitivity for detecting signals. Our method, domain-enhanced analysis (DEA) is assessed and compared to other methods using simulation studies and analysis of two publicly available leukemia data sets. Our DEA method uses functions available in R (http://www.r-project.org/) and SAS (http://www.sas.com/). The two experimental data sets used in our analysis are available in R as Bioconductor packages, 'ALL' and 'golubEsets' (http://www.bioconductor.org/). Supplementary data are available at Bioinformatics online.

  11. SEURAT: visual analytics for the integrated analysis of microarray data.

    Science.gov (United States)

    Gribov, Alexander; Sill, Martin; Lück, Sonja; Rücker, Frank; Döhner, Konstanze; Bullinger, Lars; Benner, Axel; Unwin, Antony

    2010-06-03

    In translational cancer research, gene expression data is collected together with clinical data and genomic data arising from other chip based high throughput technologies. Software tools for the joint analysis of such high dimensional data sets together with clinical data are required. We have developed an open source software tool which provides interactive visualization capability for the integrated analysis of high-dimensional gene expression data together with associated clinical data, array CGH data and SNP array data. The different data types are organized by a comprehensive data manager. Interactive tools are provided for all graphics: heatmaps, dendrograms, barcharts, histograms, eventcharts and a chromosome browser, which displays genetic variations along the genome. All graphics are dynamic and fully linked so that any object selected in a graphic will be highlighted in all other graphics. For exploratory data analysis the software provides unsupervised data analytics like clustering, seriation algorithms and biclustering algorithms. The SEURAT software meets the growing needs of researchers to perform joint analysis of gene expression, genomical and clinical data.

  12. SEURAT: Visual analytics for the integrated analysis of microarray data

    Directory of Open Access Journals (Sweden)

    Bullinger Lars

    2010-06-01

    Full Text Available Abstract Background In translational cancer research, gene expression data is collected together with clinical data and genomic data arising from other chip based high throughput technologies. Software tools for the joint analysis of such high dimensional data sets together with clinical data are required. Results We have developed an open source software tool which provides interactive visualization capability for the integrated analysis of high-dimensional gene expression data together with associated clinical data, array CGH data and SNP array data. The different data types are organized by a comprehensive data manager. Interactive tools are provided for all graphics: heatmaps, dendrograms, barcharts, histograms, eventcharts and a chromosome browser, which displays genetic variations along the genome. All graphics are dynamic and fully linked so that any object selected in a graphic will be highlighted in all other graphics. For exploratory data analysis the software provides unsupervised data analytics like clustering, seriation algorithms and biclustering algorithms. Conclusions The SEURAT software meets the growing needs of researchers to perform joint analysis of gene expression, genomical and clinical data.

  13. A flexible representation of omic knowledge for thorough analysis of microarray data

    Directory of Open Access Journals (Sweden)

    Demura Taku

    2006-03-01

    Full Text Available Abstract Background In order to understand microarray data reasonably in the context of other existing biological knowledge, it is necessary to conduct a thorough examination of the data utilizing every aspect of available omic knowledge libraries. So far, a number of bioinformatics tools have been developed. However, each of them is restricted to deal with one type of omic knowledge, e.g., pathways, interactions or gene ontology. Now that the varieties of omic knowledge are expanding, analysis tools need a way to deal with any type of omic knowledge. Hence, we have designed the Omic Space Markup Language (OSML that can represent a wide range of omic knowledge, and also, we have developed a tool named GSCope3, which can statistically analyze microarray data in comparison with the OSML-formatted omic knowledge data. Results In order to test the applicability of OSML to represent a variety of omic knowledge specifically useful for analysis of Arabidopsis thaliana microarray data, we have constructed a Biological Knowledge Library (BiKLi by converting eight different types of omic knowledge into OSML-formatted datasets. We applied GSCope3 and BiKLi to previously reported A. thaliana microarray data, so as to extract any additional insights from the data. As a result, we have discovered a new insight that lignin formation resists drought stress and activates transcription of many water channel genes to oppose drought stress; and most of the 20S proteasome subunit genes show similar expression profiles under drought stress. In addition to this novel discovery, similar findings previously reported were also quickly confirmed using GSCope3 and BiKLi. Conclusion GSCope3 can statistically analyze microarray data in the context of any OSML-represented omic knowledge. OSML is not restricted to a specific data type structure, but it can represent a wide range of omic knowledge. It allows us to convert new types of omic knowledge into datasets that can be

  14. [Diagnosis of a case with Williams-Beuren syndrome with nephrocalcinosis using chromosome microarray analysis].

    Science.gov (United States)

    Jin, S J; Liu, M; Long, W J; Luo, X P

    2016-12-02

    Objective: To explore the clinical phenotypes and the genetic cause for a boy with unexplained growth retardation, nephrocalcinosis, auditory anomalies and multi-organ/system developmental disorders. Method: Routine G-banding and chromosome microarray analysis were applied to a child with unexplained growth retardation, nephrocalcinosis, auditory anomalies and multi-organ/system developmental disorders treated in the Department of Pediatrics of Tongji Hospital Affiliated to Tongji Medical College of Huazhong University of Science and Technology in September 2015 and his parents to conduct the chromosomal karyotype analysis and the whole genome scanning. Deleted genes were searched in the Decipher and NCBI databases, and their relationships with the clinical phenotypes were analyzed. Result: A six-month-old boy was refered to us because of unexplained growth retardation and feeding intolerance.The affected child presented with abnormal manifestation such as special face, umbilical hernia, growth retardation, hypothyroidism, congenital heart disease, right ear sensorineural deafness, hypercalcemia and nephrocalcinosis. The child's karyotype was 46, XY, 16qh + , and his parents' karyotypes were normal. Chromosome microarray analysis revealed a 1 436 kb deletion on the 7q11.23(72701098_74136633) region of the child. This region included 23 protein-coding genes, which were reported to be corresponding to Williams-Beuren syndrome and its certain clinical phenotypes. His parents' results of chromosome microarray analysis were normal. Conclusion: A boy with characteristic manifestation of Williams-Beuren syndrome and rare nephrocalcinosis was diagnosed using chromosome microarray analysis. The deletion on the 7q11.23 might be related to the clinical phenotypes of Williams-Beuren syndrome, yet further studies are needed.

  15. Genes involved in immunity and apoptosis are associated with human presbycusis based on microarray analysis.

    Science.gov (United States)

    Dong, Yang; Li, Ming; Liu, Puzhao; Song, Haiyan; Zhao, Yuping; Shi, Jianrong

    2014-06-01

    Genes involved in immunity and apoptosis were associated with human presbycusis. CCR3 and GILZ played an important role in the pathogenesis of presbycusis, probably through regulating chemokine receptor, T-cell apoptosis, or T-cell activation pathways. To identify genes associated with human presbycusis and explore the molecular mechanism of presbycusis. Hearing function was tested by pure-tone audiometry. Microarray analysis was performed to identify presbycusis-correlated genes by Illumina Human-6 BeadChip using the peripheral blood samples of subjects. To identify biological process categories and pathways associated with presbycusis-correlated genes, bioinformatics analysis was carried out by Gene Ontology Tree Machine (GOTM) and database for annotation, visualization, and integrated discovery (DAVID). Quantitative RT-PCR (qRT-PCR) was used to validate the microarray data. Microarray analysis identified 469 up-regulated genes and 323 down-regulated genes. Both the dominant biological processes by Gene Ontology (GO) analysis and the enriched pathways by Kyoto encyclopedia of genes and genomes (KEGG) and BIOCARTA showed that genes involved in immunity and apoptosis were associated with presbycusis. In addition, CCR3, GILZ, CXCL10, and CX3CR1 genes showed consistent difference between groups for both the gene chip and qRT-PCR data. The differences of CCR3 and GILZ between presbycusis patients and controls were statistically significant (p < 0.05).

  16. Transcriptome Analysis Uncovers a Growth-Promoting Activity of Orosomucoid-1 on Hepatocytes

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    Xian-Yang Qin

    2017-10-01

    Full Text Available The acute phase protein orosomucoid-1 (Orm1 is mainly expressed by hepatocytes (HPCs under stress conditions. However, its specific function is not fully understood. Here, we report a role of Orm1 as an executer of HPC proliferation. Increases in serum levels of Orm1 were observed in patients after surgical resection for liver cancer and in mice undergone partial hepatectomy (PH. Transcriptome study showed that Orm1 became the most abundant in HPCs isolated from regenerating mouse liver tissues after PH. Both in vitro and in vivo siRNA-induced knockdown of Orm1 suppressed proliferation of mouse regenerating HPCs and human hepatic cells. Microarray analysis in regenerating mouse livers revealed that the signaling pathways controlling chromatin replication, especially the minichromosome maintenance protein complex genes were uniformly down-regulated following Orm1 knockdown. These data suggest that Orm1 is induced in response to hepatic injury and executes liver regeneration by activating cell cycle progression in HPCs.

  17. Carbohydrate microarrays

    DEFF Research Database (Denmark)

    Park, Sungjin; Gildersleeve, Jeffrey C; Blixt, Klas Ola

    2012-01-01

    In the last decade, carbohydrate microarrays have been core technologies for analyzing carbohydrate-mediated recognition events in a high-throughput fashion. A number of methods have been exploited for immobilizing glycans on the solid surface in a microarray format. This microarray...... of substrate specificities of glycosyltransferases. This review covers the construction of carbohydrate microarrays, detection methods of carbohydrate microarrays and their applications in biological and biomedical research....

  18. Microarray analysis and scale-free gene networks identify candidate regulators in drought-stressed roots of loblolly pine (P. taeda L.

    Directory of Open Access Journals (Sweden)

    Bordeaux John M

    2011-05-01

    Full Text Available Abstract Background Global transcriptional analysis of loblolly pine (Pinus taeda L. is challenging due to limited molecular tools. PtGen2, a 26,496 feature cDNA microarray, was fabricated and used to assess drought-induced gene expression in loblolly pine propagule roots. Statistical analysis of differential expression and weighted gene correlation network analysis were used to identify drought-responsive genes and further characterize the molecular basis of drought tolerance in loblolly pine. Results Microarrays were used to interrogate root cDNA populations obtained from 12 genotype × treatment combinations (four genotypes, three watering regimes. Comparison of drought-stressed roots with roots from the control treatment identified 2445 genes displaying at least a 1.5-fold expression difference (false discovery rate = 0.01. Genes commonly associated with drought response in pine and other plant species, as well as a number of abiotic and biotic stress-related genes, were up-regulated in drought-stressed roots. Only 76 genes were identified as differentially expressed in drought-recovered roots, indicating that the transcript population can return to the pre-drought state within 48 hours. Gene correlation analysis predicts a scale-free network topology and identifies eleven co-expression modules that ranged in size from 34 to 938 members. Network topological parameters identified a number of central nodes (hubs including those with significant homology (E-values ≤ 2 × 10-30 to 9-cis-epoxycarotenoid dioxygenase, zeatin O-glucosyltransferase, and ABA-responsive protein. Identified hubs also include genes that have been associated previously with osmotic stress, phytohormones, enzymes that detoxify reactive oxygen species, and several genes of unknown function. Conclusion PtGen2 was used to evaluate transcriptome responses in loblolly pine and was leveraged to identify 2445 differentially expressed genes responding to severe drought stress in

  19. Microarray analysis and scale-free gene networks identify candidate regulators in drought-stressed roots of loblolly pine (P. taeda L.)

    Science.gov (United States)

    2011-01-01

    Background Global transcriptional analysis of loblolly pine (Pinus taeda L.) is challenging due to limited molecular tools. PtGen2, a 26,496 feature cDNA microarray, was fabricated and used to assess drought-induced gene expression in loblolly pine propagule roots. Statistical analysis of differential expression and weighted gene correlation network analysis were used to identify drought-responsive genes and further characterize the molecular basis of drought tolerance in loblolly pine. Results Microarrays were used to interrogate root cDNA populations obtained from 12 genotype × treatment combinations (four genotypes, three watering regimes). Comparison of drought-stressed roots with roots from the control treatment identified 2445 genes displaying at least a 1.5-fold expression difference (false discovery rate = 0.01). Genes commonly associated with drought response in pine and other plant species, as well as a number of abiotic and biotic stress-related genes, were up-regulated in drought-stressed roots. Only 76 genes were identified as differentially expressed in drought-recovered roots, indicating that the transcript population can return to the pre-drought state within 48 hours. Gene correlation analysis predicts a scale-free network topology and identifies eleven co-expression modules that ranged in size from 34 to 938 members. Network topological parameters identified a number of central nodes (hubs) including those with significant homology (E-values ≤ 2 × 10-30) to 9-cis-epoxycarotenoid dioxygenase, zeatin O-glucosyltransferase, and ABA-responsive protein. Identified hubs also include genes that have been associated previously with osmotic stress, phytohormones, enzymes that detoxify reactive oxygen species, and several genes of unknown function. Conclusion PtGen2 was used to evaluate transcriptome responses in loblolly pine and was leveraged to identify 2445 differentially expressed genes responding to severe drought stress in roots. Many of the

  20. Comprehensive Transcriptome Analysis Unravels the Existence of Crucial Genes Regulating Primary Metabolism during Adventitious Root Formation in Petunia hybrida

    Science.gov (United States)

    Ahkami, Amirhossein; Scholz, Uwe; Steuernagel, Burkhard; Strickert, Marc; Haensch, Klaus-Thomas; Druege, Uwe; Reinhardt, Didier; Nouri, Eva; von Wirén, Nicolaus; Franken, Philipp; Hajirezaei, Mohammad-Reza

    2014-01-01

    To identify specific genes determining the initiation and formation of adventitious roots (AR), a microarray-based transcriptome analysis in the stem base of the cuttings of Petunia hybrida (line W115) was conducted. A microarray carrying 24,816 unique, non-redundant annotated sequences was hybridized to probes derived from different stages of AR formation. After exclusion of wound-responsive and root-regulated genes, 1,354 of them were identified which were significantly and specifically induced during various phases of AR formation. Based on a recent physiological model distinguishing three metabolic phases in AR formation, the present paper focuses on the response of genes related to particular metabolic pathways. Key genes involved in primary carbohydrate metabolism such as those mediating apoplastic sucrose unloading were induced at the early sink establishment phase of AR formation. Transcriptome changes also pointed to a possible role of trehalose metabolism and SnRK1 (sucrose non-fermenting 1- related protein kinase) in sugar sensing during this early step of AR formation. Symplastic sucrose unloading and nucleotide biosynthesis were the major processes induced during the later recovery and maintenance phases. Moreover, transcripts involved in peroxisomal beta-oxidation were up-regulated during different phases of AR formation. In addition to metabolic pathways, the analysis revealed the activation of cell division at the two later phases and in particular the induction of G1-specific genes in the maintenance phase. Furthermore, results point towards a specific demand for certain mineral nutrients starting in the recovery phase. PMID:24978694

  1. Comprehensive transcriptome analysis unravels the existence of crucial genes regulating primary metabolism during adventitious root formation in Petunia hybrida.

    Science.gov (United States)

    Ahkami, Amirhossein; Scholz, Uwe; Steuernagel, Burkhard; Strickert, Marc; Haensch, Klaus-Thomas; Druege, Uwe; Reinhardt, Didier; Nouri, Eva; von Wirén, Nicolaus; Franken, Philipp; Hajirezaei, Mohammad-Reza

    2014-01-01

    To identify specific genes determining the initiation and formation of adventitious roots (AR), a microarray-based transcriptome analysis in the stem base of the cuttings of Petunia hybrida (line W115) was conducted. A microarray carrying 24,816 unique, non-redundant annotated sequences was hybridized to probes derived from different stages of AR formation. After exclusion of wound-responsive and root-regulated genes, 1,354 of them were identified which were significantly and specifically induced during various phases of AR formation. Based on a recent physiological model distinguishing three metabolic phases in AR formation, the present paper focuses on the response of genes related to particular metabolic pathways. Key genes involved in primary carbohydrate metabolism such as those mediating apoplastic sucrose unloading were induced at the early sink establishment phase of AR formation. Transcriptome changes also pointed to a possible role of trehalose metabolism and SnRK1 (sucrose non-fermenting 1- related protein kinase) in sugar sensing during this early step of AR formation. Symplastic sucrose unloading and nucleotide biosynthesis were the major processes induced during the later recovery and maintenance phases. Moreover, transcripts involved in peroxisomal beta-oxidation were up-regulated during different phases of AR formation. In addition to metabolic pathways, the analysis revealed the activation of cell division at the two later phases and in particular the induction of G1-specific genes in the maintenance phase. Furthermore, results point towards a specific demand for certain mineral nutrients starting in the recovery phase.

  2. Comprehensive transcriptome analysis unravels the existence of crucial genes regulating primary metabolism during adventitious root formation in Petunia hybrida.

    Directory of Open Access Journals (Sweden)

    Amirhossein Ahkami

    Full Text Available To identify specific genes determining the initiation and formation of adventitious roots (AR, a microarray-based transcriptome analysis in the stem base of the cuttings of Petunia hybrida (line W115 was conducted. A microarray carrying 24,816 unique, non-redundant annotated sequences was hybridized to probes derived from different stages of AR formation. After exclusion of wound-responsive and root-regulated genes, 1,354 of them were identified which were significantly and specifically induced during various phases of AR formation. Based on a recent physiological model distinguishing three metabolic phases in AR formation, the present paper focuses on the response of genes related to particular metabolic pathways. Key genes involved in primary carbohydrate metabolism such as those mediating apoplastic sucrose unloading were induced at the early sink establishment phase of AR formation. Transcriptome changes also pointed to a possible role of trehalose metabolism and SnRK1 (sucrose non-fermenting 1- related protein kinase in sugar sensing during this early step of AR formation. Symplastic sucrose unloading and nucleotide biosynthesis were the major processes induced during the later recovery and maintenance phases. Moreover, transcripts involved in peroxisomal beta-oxidation were up-regulated during different phases of AR formation. In addition to metabolic pathways, the analysis revealed the activation of cell division at the two later phases and in particular the induction of G1-specific genes in the maintenance phase. Furthermore, results point towards a specific demand for certain mineral nutrients starting in the recovery phase.

  3. Transcriptomics and comparative analysis of three antarctic notothenioid fishes.

    Directory of Open Access Journals (Sweden)

    Seung Chul Shin

    Full Text Available For the past 10 to 13 million years, Antarctic notothenioid fish have undergone extraordinary periods of evolution and have adapted to a cold and highly oxygenated Antarctic marine environment. While these species are considered an attractive model with which to study physiology and evolutionary adaptation, they are poorly characterized at the molecular level, and sequence information is lacking. The transcriptomes of the Antarctic fishes Notothenia coriiceps, Chaenocephalus aceratus, and Pleuragramma antarcticum were obtained by 454 FLX Titanium sequencing of a normalized cDNA library. More than 1,900,000 reads were assembled in a total of 71,539 contigs. Overall, 40% of the contigs were annotated based on similarity to known protein or nucleotide sequences, and more than 50% of the predicted transcripts were validated as full-length or putative full-length cDNAs. These three Antarctic fishes shared 663 genes expressed in the brain and 1,557 genes expressed in the liver. In addition, these cold-adapted fish expressed more Ub-conjugated proteins compared to temperate fish; Ub-conjugated proteins are involved in maintaining proteins in their native state in the cold and thermally stable Antarctic environments. Our transcriptome analysis of Antarctic notothenioid fish provides an archive for future studies in molecular mechanisms of fundamental genetic questions, and can be used in evolution studies comparing other fish.

  4. Transcriptome analysis of Haloquadratum walsbyi: vanity is but the surface.

    Science.gov (United States)

    Bolhuis, Henk; Martín-Cuadrado, Ana Belén; Rosselli, Riccardo; Pašić, Lejla; Rodriguez-Valera, Francisco

    2017-07-03

    Haloquadratum walsbyi dominates saturated thalassic lakes worldwide where they can constitute up to 80-90% of the total prokaryotic community. Despite the abundance of the enigmatic square-flattened cells, only 7 isolates are currently known with 2 genomes fully sequenced and annotated due to difficulties to grow them under laboratory conditions. We have performed a transcriptomic analysis of one of these isolates, the Spanish strain HBSQ001 in order to investigate gene transcription under light and dark conditions. Despite a potential advantage for light as additional source of energy, no significant differences were found between light and dark expressed genes. Constitutive high gene expression was observed in genes encoding surface glycoproteins, light mediated proton pumping by bacteriorhodopsin, several nutrient uptake systems, buoyancy and storage of excess carbon. Two low expressed regions of the genome were characterized by a lower codon adaptation index, low GC content and high incidence of hypothetical genes. Under the extant cultivation conditions, the square hyperhalophile devoted most of its transcriptome towards processes maintaining cell integrity and exploiting solar energy. Surface glycoproteins are essential for maintaining the large surface to volume ratio that facilitates light and organic nutrient harvesting whereas constitutive expression of bacteriorhodopsin warrants an immediate source of energy when light becomes available.

  5. Differential Transcriptome Analysis between Paulownia fortunei and Its Synthesized Autopolyploid

    Directory of Open Access Journals (Sweden)

    Xiaoshen Zhang

    2014-03-01

    Full Text Available Paulownia fortunei is an ecologically and economically important tree species that is widely used as timber and chemical pulp. Its autotetraploid, which carries a number of valuable traits, was successfully induced with colchicine. To identify differences in gene expression between P. fortunei and its synthesized autotetraploid, we performed transcriptome sequencing using an Illumina Genome Analyzer IIx (GAIIx. About 94.8 million reads were generated and assembled into 383,056 transcripts, including 18,984 transcripts with a complete open reading frame. A conducted Basic Local Alignment Search Tool (BLAST search indicated that 16,004 complete transcripts had significant hits in the National Center for Biotechnology Information (NCBI non-redundant database. The complete transcripts were given functional assignments using three public protein databases. One thousand one hundred fifty eight differentially expressed complete transcripts were screened through a digital abundance analysis, including transcripts involved in energy metabolism and epigenetic regulation. Finally, the expression levels of several transcripts were confirmed by quantitative real-time PCR. Our results suggested that polyploidization caused epigenetic-related changes, which subsequently resulted in gene expression variation between diploid and autotetraploid P. fortunei. This might be the main mechanism affected by the polyploidization. Our results represent an extensive survey of the P. fortunei transcriptome and will facilitate subsequent functional genomics research in P. fortunei. Moreover, the gene expression profiles of P. fortunei and its autopolyploid will provide a valuable resource for the study of polyploidization.

  6. The pathogenesis shared between abdominal aortic aneurysms and intracranial aneurysms: a microarray analysis.

    Science.gov (United States)

    Wang, Wen; Li, Hao; Zhao, Zheng; Wang, Haoyuan; Zhang, Dong; Zhang, Yan; Lan, Qing; Wang, Jiangfei; Cao, Yong; Zhao, Jizong

    2018-04-01

    Abdominal aortic aneurysms (AAAs) and intracranial saccular aneurysms (IAs) are the most common types of aneurysms. This study was to investigate the common pathogenesis shared between these two kinds of aneurysms. We collected 12 IAs samples and 12 control arteries from the Beijing Tiantan Hospital and performed microarray analysis. In addition, we utilized the microarray datasets of IAs and AAAs from the Gene Expression Omnibus (GEO), in combination with our microarray results, to generate messenger RNA expression profiles for both AAAs and IAs in our study. Functional exploration and protein-protein interaction (PPI) analysis were performed. A total of 727 common genes were differentially expressed (404 was upregulated; 323 was downregulated) for both AAAs and IAs. The GO and pathway analyses showed that the common dysregulated genes were mainly enriched in vascular smooth muscle contraction, muscle contraction, immune response, defense response, cell activation, IL-6 signaling and chemokine signaling pathways, etc. The further protein-protein analysis identified 35 hub nodes, including TNF, IL6, MAPK13, and CCL5. These hub node genes were enriched in inflammatory response, positive regulation of IL-6 production, chemokine signaling pathway, and T/B cell receptor signaling pathway. Our study will gain new insight into the molecular mechanisms for the pathogenesis of both types of aneurysms and provide new therapeutic targets for the patients harboring AAAs and IAs.

  7. The IronChip evaluation package: a package of perl modules for robust analysis of custom microarrays

    Directory of Open Access Journals (Sweden)

    Brazma Alvis

    2010-03-01

    Full Text Available Abstract Background Gene expression studies greatly contribute to our understanding of complex relationships in gene regulatory networks. However, the complexity of array design, production and manipulations are limiting factors, affecting data quality. The use of customized DNA microarrays improves overall data quality in many situations, however, only if for these specifically designed microarrays analysis tools are available. Results The IronChip Evaluation Package (ICEP is a collection of Perl utilities and an easy to use data evaluation pipeline for the analysis of microarray data with a focus on data quality of custom-designed microarrays. The package has been developed for the statistical and bioinformatical analysis of the custom cDNA microarray IronChip but can be easily adapted for other cDNA or oligonucleotide-based designed microarray platforms. ICEP uses decision tree-based algorithms to assign quality flags and performs robust analysis based on chip design properties regarding multiple repetitions, ratio cut-off, background and negative controls. Conclusions ICEP is a stand-alone Windows application to obtain optimal data quality from custom-designed microarrays and is freely available here (see "Additional Files" section and at: http://www.alice-dsl.net/evgeniy.vainshtein/ICEP/

  8. Outcome-Driven Cluster Analysis with Application to Microarray Data.

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    Jessie J Hsu

    Full Text Available One goal of cluster analysis is to sort characteristics into groups (clusters so that those in the same group are more highly correlated to each other than they are to those in other groups. An example is the search for groups of genes whose expression of RNA is correlated in a population of patients. These genes would be of greater interest if their common level of RNA expression were additionally predictive of the clinical outcome. This issue arose in the context of a study of trauma patients on whom RNA samples were available. The question of interest was whether there were groups of genes that were behaving similarly, and whether each gene in the cluster would have a similar effect on who would recover. For this, we develop an algorithm to simultaneously assign characteristics (genes into groups of highly correlated genes that have the same effect on the outcome (recovery. We propose a random effects model where the genes within each group (cluster equal the sum of a random effect, specific to the observation and cluster, and an independent error term. The outcome variable is a linear combination of the random effects of each cluster. To fit the model, we implement a Markov chain Monte Carlo algorithm based on the likelihood of the observed data. We evaluate the effect of including outcome in the model through simulation studies and describe a strategy for prediction. These methods are applied to trauma data from the Inflammation and Host Response to Injury research program, revealing a clustering of the genes that are informed by the recovery outcome.

  9. Bayesian meta-analysis models for microarray data: a comparative study

    Directory of Open Access Journals (Sweden)

    Song Joon J

    2007-03-01

    Full Text Available Abstract Background With the growing abundance of microarray data, statistical methods are increasingly needed to integrate results across studies. Two common approaches for meta-analysis of microarrays include either combining gene expression measures across studies or combining summaries such as p-values, probabilities or ranks. Here, we compare two Bayesian meta-analysis models that are analogous to these methods. Results Two Bayesian meta-analysis models for microarray data have recently been introduced. The first model combines standardized gene expression measures across studies into an overall mean, accounting for inter-study variability, while the second combines probabilities of differential expression without combining expression values. Both models produce the gene-specific posterior probability of differential expression, which is the basis for inference. Since the standardized expression integration model includes inter-study variability, it may improve accuracy of results versus the probability integration model. However, due to the small number of studies typical in microarray meta-analyses, the variability between studies is challenging to estimate. The probability integration model eliminates the need to model variability between studies, and thus its implementation is more straightforward. We found in simulations of two and five studies that combining probabilities outperformed combining standardized gene expression measures for three comparison values: the percent of true discovered genes in meta-analysis versus individual studies; the percent of true genes omitted in meta-analysis versus separate studies, and the number of true discovered genes for fixed levels of Bayesian false discovery. We identified similar results when pooling two independent studies of Bacillus subtilis. We assumed that each study was produced from the same microarray platform with only two conditions: a treatment and control, and that the data sets

  10. Microarray gene expression profiling and analysis in renal cell carcinoma

    Directory of Open Access Journals (Sweden)

    Sadhukhan Provash

    2004-06-01

    Full Text Available Abstract Background Renal cell carcinoma (RCC is the most common cancer in adult kidney. The accuracy of current diagnosis and prognosis of the disease and the effectiveness of the treatment for the disease are limited by the poor understanding of the disease at the molecular level. To better understand the genetics and biology of RCC, we profiled the expression of 7,129 genes in both clear cell RCC tissue and cell lines using oligonucleotide arrays. Methods Total RNAs isolated from renal cell tumors, adjacent normal tissue and metastatic RCC cell lines were hybridized to affymatrix HuFL oligonucleotide arrays. Genes were categorized into different functional groups based on the description of the Gene Ontology Consortium and analyzed based on the gene expression levels. Gene expression profiles of the tissue and cell line samples were visualized and classified by singular value decomposition. Reverse transcription polymerase chain reaction was performed to confirm the expression alterations of selected genes in RCC. Results Selected genes were annotated based on biological processes and clustered into functional groups. The expression levels of genes in each group were also analyzed. Seventy-four commonly differentially expressed genes with more than five-fold changes in RCC tissues were identified. The expression alterations of selected genes from these seventy-four genes were further verified using reverse transcription polymerase chain reaction (RT-PCR. Detailed comparison of gene expression patterns in RCC tissue and RCC cell lines shows significant differences between the two types of samples, but many important expression patterns were preserved. Conclusions This is one of the initial studies that examine the functional ontology of a large number of genes in RCC. Extensive annotation, clustering and analysis of a large number of genes based on the gene functional ontology revealed many interesting gene expression patterns in RCC. Most

  11. A pilot study of transcription unit analysis in rice using oligonucleotide tiling-path microarray

    DEFF Research Database (Denmark)

    Stolc, Viktor; Li, Lei; Wang, Xiangfeng

    2005-01-01

    As the international efforts to sequence the rice genome are completed, an immediate challenge and opportunity is to comprehensively and accurately define all transcription units in the rice genome. Here we describe a strategy of using high-density oligonucleotide tiling-path microarrays to map...... transcription of the japonica rice genome. In a pilot experiment to test this approach, one array representing the reverse strand of the last 11.2 Mb sequence of chromosome 10 was analyzed in detail based on a mathematical model developed in this study. Analysis of the array data detected 77% of the reference...... gene models in a mixture of four RNA populations. Moreover, significant transcriptional activities were found in many of the previously annotated intergenic regions. These preliminary results demonstrate the utility of genome tiling microarrays in evaluating annotated rice gene models...

  12. Gene targeting associated with the radiation sensitivity in squamous cell carcinoma by using microarray analysis

    International Nuclear Information System (INIS)

    Nimura, Yoshinori; Kumagai, Ken; Kouzu, Yoshinao; Higo, Morihiro; Kato, Yoshikuni; Seki, Naohiko; Yamada, Shigeru

    2005-01-01

    In order to identify a set of genes related to radiation sensitivity of squamous cell carcinoma (SCC) and establish a predictive method, we compared expression profiles of radio-sensitive/radio-resistant SCC cell lines, using the in-house cDNA microarray consisting of 2,201 human genes derived from full-length enriched SCC cDNA libraries and the Human oligo chip 30 K (Hitachi Software Engineering). Surviving fractions (SF) after irradiation of heavy iron were calculated by colony formation assay. Three pairs (TE2-TE13, YES5-YES6, and HSC3-HSC2), sensitive (SF1 0.6), were selected for the microarray analysis. The results of cDNA microarray analysis showed that 20 genes in resistant cell lines and 5 genes in sensitive cell lines were up regulated more than 1.5-fold compared with sensitive and resistant cell lines respectively. Fourteen out of 25 genes were confirmed the gene expression profiles by real-time polymerase chain reaction (PCR). Twenty-seven genes identified by Human oligo chip 30 K are candidate for the markers to distinguish radio-sensitive from radio-resistant. These results suggest that the isolated 27 genes are the candidates that might be used as specific molecular markers to predict radiation sensitivity. (author)

  13. Mutation analysis of 272 Spanish families affected by autosomal recessive retinitis pigmentosa using a genotyping microarray.

    Science.gov (United States)

    Ávila-Fernández, Almudena; Cantalapiedra, Diego; Aller, Elena; Vallespín, Elena; Aguirre-Lambán, Jana; Blanco-Kelly, Fiona; Corton, M; Riveiro-Álvarez, Rosa; Allikmets, Rando; Trujillo-Tiebas, María José; Millán, José M; Cremers, Frans P M; Ayuso, Carmen

    2010-12-03

    Retinitis pigmentosa (RP) is a genetically heterogeneous disorder characterized by progressive loss of vision. The aim of this study was to identify the causative mutations in 272 Spanish families using a genotyping microarray. 272 unrelated Spanish families, 107 with autosomal recessive RP (arRP) and 165 with sporadic RP (sRP), were studied using the APEX genotyping microarray. The families were also classified by clinical criteria: 86 juveniles and 186 typical RP families. Haplotype and sequence analysis were performed to identify the second mutated allele. At least one-gene variant was found in 14% and 16% of the juvenile and typical RP groups respectively. Further study identified four new mutations, providing both causative changes in 11% of the families. Retinol Dehydrogenase 12 (RDH12) was the most frequently mutated gene in the juvenile RP group, and Usher Syndrome 2A (USH2A) and Ceramide Kinase-Like (CERKL) were the most frequently mutated genes in the typical RP group. The only variant found in CERKL was p.Arg257Stop, the most frequent mutation. The genotyping microarray combined with segregation and sequence analysis allowed us to identify the causative mutations in 11% of the families. Due to the low number of characterized families, this approach should be used in tandem with other techniques.

  14. A Transcriptome Meta-Analysis Proposes Novel Biological Roles for the Antifungal Protein AnAFP in Aspergillus niger.

    Directory of Open Access Journals (Sweden)

    Norman Paege

    Full Text Available Understanding the genetic, molecular and evolutionary basis of cysteine-stabilized antifungal proteins (AFPs from fungi is important for understanding whether their function is mainly defensive or associated with fungal growth and development. In the current study, a transcriptome meta-analysis of the Aspergillus niger γ-core protein AnAFP was performed to explore co-expressed genes and pathways, based on independent expression profiling microarrays covering 155 distinct cultivation conditions. This analysis uncovered that anafp displays a highly coordinated temporal and spatial transcriptional profile which is concomitant with key nutritional and developmental processes. Its expression profile coincides with early starvation response and parallels with genes involved in nutrient mobilization and autophagy. Using fluorescence- and luciferase reporter strains we demonstrated that the anafp promoter is active in highly vacuolated compartments and foraging hyphal cells during carbon starvation with CreA and FlbA, but not BrlA, as most likely regulators of anafp. A co-expression network analysis supported by luciferase-based reporter assays uncovered that anafp expression is embedded in several cellular processes including allorecognition, osmotic and oxidative stress survival, development, secondary metabolism and autophagy, and predicted StuA and VelC as additional regulators. The transcriptomic resources available for A. niger provide unparalleled resources to investigate the function of proteins. Our work illustrates how transcriptomic meta-analyses can lead to hypotheses regarding protein function and predict a role for AnAFP during slow growth, allorecognition, asexual development and nutrient recycling of A. niger and propose that it interacts with the autophagic machinery to enable these processes.

  15. A Transcriptome Meta-Analysis Proposes Novel Biological Roles for the Antifungal Protein AnAFP in Aspergillus niger.

    Science.gov (United States)

    Paege, Norman; Jung, Sascha; Schäpe, Paul; Müller-Hagen, Dirk; Ouedraogo, Jean-Paul; Heiderich, Caroline; Jedamzick, Johanna; Nitsche, Benjamin M; van den Hondel, Cees A; Ram, Arthur F; Meyer, Vera

    2016-01-01

    Understanding the genetic, molecular and evolutionary basis of cysteine-stabilized antifungal proteins (AFPs) from fungi is important for understanding whether their function is mainly defensive or associated with fungal growth and development. In the current study, a transcriptome meta-analysis of the Aspergillus niger γ-core protein AnAFP was performed to explore co-expressed genes and pathways, based on independent expression profiling microarrays covering 155 distinct cultivation conditions. This analysis uncovered that anafp displays a highly coordinated temporal and spatial transcriptional profile which is concomitant with key nutritional and developmental processes. Its expression profile coincides with early starvation response and parallels with genes involved in nutrient mobilization and autophagy. Using fluorescence- and luciferase reporter strains we demonstrated that the anafp promoter is active in highly vacuolated compartments and foraging hyphal cells during carbon starvation with CreA and FlbA, but not BrlA, as most likely regulators of anafp. A co-expression network analysis supported by luciferase-based reporter assays uncovered that anafp expression is embedded in several cellular processes including allorecognition, osmotic and oxidative stress survival, development, secondary metabolism and autophagy, and predicted StuA and VelC as additional regulators. The transcriptomic resources available for A. niger provide unparalleled resources to investigate the function of proteins. Our work illustrates how transcriptomic meta-analyses can lead to hypotheses regarding protein function and predict a role for AnAFP during slow growth, allorecognition, asexual development and nutrient recycling of A. niger and propose that it interacts with the autophagic machinery to enable these processes.

  16. CDNA Microarray Based Comparative Gene Expression Analysis of Primary Breast Tumors Versus In Vitro Transformed Neoplastic Breast Epithelium

    National Research Council Canada - National Science Library

    Szallasi, Zoltan

    2001-01-01

    .... The first group of clones is being sorted by their ability to form tumors. We are currently performing cDNA microarray analysis quantifying the expression level of about 15,000 genes in these cell lines...

  17. Integration of microarray analysis into the clinical diagnosis of hematological malignancies: How much can we improve cytogenetic testing?

    Science.gov (United States)

    Peterson, Jess F.; Aggarwal, Nidhi; Smith, Clayton A.; Gollin, Susanne M.; Surti, Urvashi; Rajkovic, Aleksandar; Swerdlow, Steven H.; Yatsenko, Svetlana A.

    2015-01-01

    Purpose To evaluate the clinical utility, diagnostic yield and rationale of integrating microarray analysis in the clinical diagnosis of hematological malignancies in comparison with classical chromosome karyotyping/fluorescence in situ hybridization (FISH). Methods G-banded chromosome analysis, FISH and microarray studies using customized CGH and CGH+SNP designs were performed on 27 samples from patients with hematological malignancies. A comprehensive comparison of the results obtained by three methods was conducted to evaluate benefits and limitations of these techniques for clinical diagnosis. Results Overall, 89.7% of chromosomal abnormalities identified by karyotyping/FISH studies were also detectable by microarray. Among 183 acquired copy number alterations (CNAs) identified by microarray, 94 were additional findings revealed in 14 cases (52%), and at least 30% of CNAs were in genomic regions of diagnostic/prognostic significance. Approximately 30% of novel alterations detected by microarray were >20 Mb in size. Balanced abnormalities were not detected by microarray; however, of the 19 apparently “balanced” rearrangements, 55% (6/11) of recurrent and 13% (1/8) of non-recurrent translocations had alterations at the breakpoints discovered by microarray. Conclusion Microarray technology enables accurate, cost-effective and time-efficient whole-genome analysis at a resolution significantly higher than that of conventional karyotyping and FISH. Array-CGH showed advantage in identification of cryptic imbalances and detection of clonal aberrations in population of non-dividing cancer cells and samples with poor chromosome morphology. The integration of microarray analysis into the cytogenetic diagnosis of hematologic malignancies has the potential to improve patient management by providing clinicians with additional disease specific and potentially clinically actionable genomic alterations. PMID:26299921

  18. Transcriptomic analysis highlights epigenetic and transcriptional regulation during zygotic embryo development of Pinus pinaster.

    Science.gov (United States)

    de Vega-Bartol, José J; Simões, Marta; Lorenz, W Walter; Rodrigues, Andreia S; Alba, Rob; Dean, Jeffrey F D; Miguel, Célia M

    2013-08-30

    It is during embryogenesis that the plant body plan is established and the meristems responsible for all post-embryonic growth are specified. The molecular mechanisms governing conifer embryogenesis are still largely unknown. Their elucidation may contribute valuable information to clarify if the distinct features of embryo development in angiosperms and gymnosperms result from differential gene regulation. To address this issue, we have performed the first transcriptomic analysis of zygotic embryo development in a conifer species (Pinus pinaster) focusing our study in particular on regulatory genes playing important roles during plant embryo development, namely epigenetic regulators and transcription factors. Microarray analysis of P. pinaster zygotic embryogenesis was performed at five periods of embryo development from early developing to mature embryos. Our results show that most changes in transcript levels occurred in the first and the last embryo stage-to-stage transitions, namely early to pre-cotyledonary embryo and cotyledonary to mature embryo. An analysis of functional categories for genes that were differentially expressed through embryogenesis highlighted several epigenetic regulation mechanisms. While putative orthologs of transcripts associated with mechanisms that target transposable elements and repetitive sequences were strongly expressed in early embryogenesis, PRC2-mediated repression of genes seemed more relevant during late embryogenesis. On the other hand, functions related to sRNA pathways appeared differentially regulated across all stages of embryo development with a prevalence of miRNA functions in mid to late embryogenesis. Identification of putative transcription factor genes differentially regulated between consecutive embryo stages was strongly suggestive of the relevance of auxin responses and regulation of auxin carriers during early embryogenesis. Such responses could be involved in establishing embryo patterning. Later in

  19. Preliminary analysis of Psoroptes ovis transcriptome in different developmental stages

    Directory of Open Access Journals (Sweden)

    Man-Li He

    2016-11-01

    Full Text Available Abstract Background Psoroptic mange is a chronic, refractory, contagious and infectious disease mainly caused by the mange mite Psoroptes ovis, which can infect horses, sheep, buffaloes, rabbits, other domestic animals, deer, wild camels, foxes, minks, lemurs, alpacas, elks and other wild animals. Features of the disease include intense pruritus and dermatitis, depilation and hyperkeratosis, which ultimately result in emaciation or death caused by secondary bacterial infections. The infestation is usually transmitted by close contact between animals. Psoroptic mange is widespread in the world. In this paper, the transcriptome of P. ovis is described following sequencing and analysis of transcripts from samples of larvae (i.e. the Pso_L group and nymphs and adults (i.e. the Pso_N_A group. The study describes differentially expressed genes (DEGs and genes encoding allergens, which help understanding the biology of P. ovis and lay foundations for the development of vaccine antigens and drug target screening. Methods The transcriptome of P. ovis was assembled and analyzed using bioinformatic tools. The unigenes of P. ovis from each developmental stage and the unigenes differentially between developmental stages were compared with allergen protein sequences contained in the allergen database website to predict potential allergens. Results We identified 38,836 unigenes, whose mean length was 825 bp. On the basis of sequence similarity with seven databases, a total of 17,366 unigenes were annotated. A total of 1,316 DEGs were identified, including 496 upregulated and 820 downregulated in the Pso_L group compared with the Pso_N_A group. We predicted 205 allergens genes in the two developmental stages similar to genes from other mites and ticks, of these, 14 were among the upregulated DEGs and 26 among the downregulated DEGs. Conclusion This study provides a reference transcriptome of P. ovis in absence of a reference genome. The analysis of DEGs and

  20. Gene expression analysis of the biocontrol fungus Trichoderma harzianum in the presence of tomato plants, chitin, or glucose using a high-density oligonucleotide microarray.

    Science.gov (United States)

    Samolski, Ilanit; de Luis, Alberto; Vizcaíno, Juan Antonio; Monte, Enrique; Suárez, M Belén

    2009-10-13

    It has recently been shown that the Trichoderma fungal species used for biocontrol of plant diseases are capable of interacting with plant roots directly, behaving as symbiotic microorganisms. With a view to providing further information at transcriptomic level about the early response of Trichoderma to a host plant, we developed a high-density oligonucleotide (HDO) microarray encompassing 14,081 Expressed Sequence Tag (EST)-based transcripts from eight Trichoderma spp. and 9,121 genome-derived transcripts of T. reesei, and we have used this microarray to examine the gene expression of T. harzianum either alone or in the presence of tomato plants, chitin, or glucose. Global microarray analysis revealed 1,617 probe sets showing differential expression in T. harzianum mycelia under at least one of the culture conditions tested as compared with one another. Hierarchical clustering and heat map representation showed that the expression patterns obtained in glucose medium clustered separately from the expression patterns observed in the presence of tomato plants and chitin. Annotations using the Blast2GO suite identified 85 of the 257 transcripts whose probe sets afforded up-regulated expression in response to tomato plants. Some of these transcripts were predicted to encode proteins related to Trichoderma-host (fungus or plant) associations, such as Sm1/Elp1 protein, proteases P6281 and PRA1, enchochitinase CHIT42, or QID74 protein, although previously uncharacterized genes were also identified, including those responsible for the possible biosynthesis of nitric oxide, xenobiotic detoxification, mycelium development, or those related to the formation of infection structures in plant tissues. The effectiveness of the Trichoderma HDO microarray to detect different gene responses under different growth conditions in the fungus T. harzianum strongly indicates that this tool should be useful for further assays that include different stages of plant colonization, as well as

  1. Microarray Meta-Analysis of RNA-Binding Protein Functions in Alternative Polyadenylation

    Science.gov (United States)

    Hu, Wenchao; Liu, Yuting; Yan, Jun

    2014-01-01

    Alternative polyadenylation (APA) is a post-transcriptional mechanism to generate diverse mRNA transcripts with different 3′UTRs from the same gene. In this study, we systematically searched for the APA events with differential expression in public mouse microarray data. Hundreds of genes with over-represented differential APA events and the corresponding experiments were identified. We further revealed that global APA differential expression occurred prevalently in tissues such as brain comparing to peripheral tissues, and biological processes such as development, differentiation and immune responses. Interestingly, we also observed widespread differential APA events in RNA-binding protein (RBP) genes such as Rbm3, Eif4e2 and Elavl1. Given the fact that RBPs are considered as the main regulators of differential APA expression, we constructed a co-expression network between APAs and RBPs using the microarray data. Further incorporation of CLIP-seq data of selected RBPs showed that Nova2 represses and Mbnl1 promotes the polyadenylation of closest poly(A) sites respectively. Altogether, our study is the first microarray meta-analysis in a mammal on the regulation of APA by RBPs that integrated massive mRNA expression data under a wide-range of biological conditions. Finally, we present our results as a comprehensive resource in an online website for the research community. PMID:24622240

  2. ZODET: software for the identification, analysis and visualisation of outlier genes in microarray expression data.

    Directory of Open Access Journals (Sweden)

    Daniel L Roden

    Full Text Available Complex human diseases can show significant heterogeneity between patients with the same phenotypic disorder. An outlier detection strategy was developed to identify variants at the level of gene transcription that are of potential biological and phenotypic importance. Here we describe a graphical software package (z-score outlier detection (ZODET that enables identification and visualisation of gross abnormalities in gene expression (outliers in individuals, using whole genome microarray data. Mean and standard deviation of expression in a healthy control cohort is used to detect both over and under-expressed probes in individual test subjects. We compared the potential of ZODET to detect outlier genes in gene expression datasets with a previously described statistical method, gene tissue index (GTI, using a simulated expression dataset and a publicly available monocyte-derived macrophage microarray dataset. Taken together, these results support ZODET as a novel approach to identify outlier genes of potential pathogenic relevance in complex human diseases. The algorithm is implemented using R packages and Java.The software is freely available from http://www.ucl.ac.uk/medicine/molecular-medicine/publications/microarray-outlier-analysis.

  3. Flow cytometric purification of Colletotrichum higginsianum biotrophic hyphae from Arabidopsis leaves for stage-specific transcriptome analysis.

    Science.gov (United States)

    Takahara, Hiroyuki; Dolf, Andreas; Endl, Elmar; O'Connell, Richard

    2009-08-01

    Generation of stage-specific cDNA libraries is a powerful approach to identify pathogen genes that are differentially expressed during plant infection. Biotrophic pathogens develop specialized infection structures inside living plant cells, but sampling the transcriptome of these structures is problematic due to the low ratio of fungal to plant RNA, and the lack of efficient methods to isolate them from infected plants. Here we established a method, based on fluorescence-activated cell sorting (FACS), to purify the intracellular biotrophic hyphae of Colletotrichum higginsianum from homogenates of infected Arabidopsis leaves. Specific selection of viable hyphae using a fluorescent vital marker provided intact RNA for cDNA library construction. Pilot-scale sequencing showed that the library was enriched with plant-induced and pathogenicity-related fungal genes, including some encoding small, soluble secreted proteins that represent candidate fungal effectors. The high purity of the hyphae (94%) prevented contamination of the library by sequences derived from host cells or other fungal cell types. RT-PCR confirmed that genes identified in the FACS-purified hyphae were also expressed in planta. The method has wide applicability for isolating the infection structures of other plant pathogens, and will facilitate cell-specific transcriptome analysis via deep sequencing and microarray hybridization, as well as proteomic analyses.

  4. Factorial microarray analysis of zebra mussel (Dreissena polymorpha: Dreissenidae, Bivalvia adhesion

    Directory of Open Access Journals (Sweden)

    Faisal Mohamed

    2010-05-01

    Full Text Available Abstract Background The zebra mussel (Dreissena polymorpha has been well known for its expertise in attaching to substances under the water. Studies in past decades on this underwater adhesion focused on the adhesive protein isolated from the byssogenesis apparatus of the zebra mussel. However, the mechanism of the initiation, maintenance, and determination of the attachment process remains largely unknown. Results In this study, we used a zebra mussel cDNA microarray previously developed in our lab and a factorial analysis to identify the genes that were involved in response to the changes of four factors: temperature (Factor A, current velocity (Factor B, dissolved oxygen (Factor C, and byssogenesis status (Factor D. Twenty probes in the microarray were found to be modified by one of the factors. The transcription products of four selected genes, DPFP-BG20_A01, EGP-BG97/192_B06, EGP-BG13_G05, and NH-BG17_C09 were unique to the zebra mussel foot based on the results of quantitative reverse transcription PCR (qRT-PCR. The expression profiles of these four genes under the attachment and non-attachment were also confirmed by qRT-PCR and the result is accordant to that from microarray assay. The in situ hybridization with the RNA probes of two identified genes DPFP-BG20_A01 and EGP-BG97/192_B06 indicated that both of them were expressed by a type of exocrine gland cell located in the middle part of the zebra mussel foot. Conclusions The results of this study suggested that the changes of D. polymorpha byssogenesis status and the environmental factors can dramatically affect the expression profiles of the genes unique to the foot. It turns out that the factorial design and analysis of the microarray experiment is a reliable method to identify the influence of multiple factors on the expression profiles of the probesets in the microarray; therein it provides a powerful tool to reveal the mechanism of zebra mussel underwater attachment.

  5. Development of a novel multiplex DNA microarray for Fusarium graminearum and analysis of azole fungicide responses

    Directory of Open Access Journals (Sweden)

    Deising Holger B

    2011-01-01

    Full Text Available Abstract Background The toxigenic fungal plant pathogen Fusarium graminearum compromises wheat production worldwide. Azole fungicides play a prominent role in controlling this pathogen. Sequencing of its genome stimulated the development of high-throughput technologies to study mechanisms of coping with fungicide stress and adaptation to fungicides at a previously unprecedented precision. DNA-microarrays have been used to analyze genome-wide gene expression patterns and uncovered complex transcriptional responses. A recently developed one-color multiplex array format allowed flexible, effective, and parallel examinations of eight RNA samples. Results We took advantage of the 8 × 15 k Agilent format to design, evaluate, and apply a novel microarray covering the whole F. graminearum genome to analyze transcriptional responses to azole fungicide treatment. Comparative statistical analysis of expression profiles uncovered 1058 genes that were significantly differentially expressed after azole-treatment. Quantitative RT-PCR analysis for 31 selected genes indicated high conformity to results from the microarray hybridization. Among the 596 genes with significantly increased transcript levels, analyses using GeneOntology and FunCat annotations detected the ergosterol-biosynthesis pathway genes as the category most significantly responding, confirming the mode-of-action of azole fungicides. Cyp51A, which is one of the three F. graminearum paralogs of Cyp51 encoding the target of azoles, was the most consistently differentially expressed gene of the entire study. A molecular phylogeny analyzing the relationships of the three CYP51 proteins in the context of 38 fungal genomes belonging to the Pezizomycotina indicated that CYP51C (FGSG_11024 groups with a new clade of CYP51 proteins. The transcriptional profiles for genes encoding ABC transporters and transcription factors suggested several involved in mechanisms alleviating the impact of the fungicide

  6. Factorial microarray analysis of zebra mussel (Dreissena polymorpha: Dreissenidae, Bivalvia) adhesion.

    Science.gov (United States)

    Xu, Wei; Faisal, Mohamed

    2010-05-28

    The zebra mussel (Dreissena polymorpha) has been well known for its expertise in attaching to substances under the water. Studies in past decades on this underwater adhesion focused on the adhesive protein isolated from the byssogenesis apparatus of the zebra mussel. However, the mechanism of the initiation, maintenance, and determination of the attachment process remains largely unknown. In this study, we used a zebra mussel cDNA microarray previously developed in our lab and a factorial analysis to identify the genes that were involved in response to the changes of four factors: temperature (Factor A), current velocity (Factor B), dissolved oxygen (Factor C), and byssogenesis status (Factor D). Twenty probes in the microarray were found to be modified by one of the factors. The transcription products of four selected genes, DPFP-BG20_A01, EGP-BG97/192_B06, EGP-BG13_G05, and NH-BG17_C09 were unique to the zebra mussel foot based on the results of quantitative reverse transcription PCR (qRT-PCR). The expression profiles of these four genes under the attachment and non-attachment were also confirmed by qRT-PCR and the result is accordant to that from microarray assay. The in situ hybridization with the RNA probes of two identified genes DPFP-BG20_A01 and EGP-BG97/192_B06 indicated that both of them were expressed by a type of exocrine gland cell located in the middle part of the zebra mussel foot. The results of this study suggested that the changes of D. polymorpha byssogenesis status and the environmental factors can dramatically affect the expression profiles of the genes unique to the foot. It turns out that the factorial design and analysis of the microarray experiment is a reliable method to identify the influence of multiple factors on the expression profiles of the probesets in the microarray; therein it provides a powerful tool to reveal the mechanism of zebra mussel underwater attachment.

  7. PIIKA 2: an expanded, web-based platform for analysis of kinome microarray data.

    Directory of Open Access Journals (Sweden)

    Brett Trost

    Full Text Available Kinome microarrays are comprised of peptides that act as phosphorylation targets for protein kinases. This platform is growing in popularity due to its ability to measure phosphorylation-mediated cellular signaling in a high-throughput manner. While software for analyzing data from DNA microarrays has also been used for kinome arrays, differences between the two technologies and associated biologies previously led us to develop Platform for Intelligent, Integrated Kinome Analysis (PIIKA, a software tool customized for the analysis of data from kinome arrays. Here, we report the development of PIIKA 2, a significantly improved version with new features and improvements in the areas of clustering, statistical analysis, and data visualization. Among other additions to the original PIIKA, PIIKA 2 now allows the user to: evaluate statistically how well groups of samples cluster together; identify sets of peptides that have consistent phosphorylation patterns among groups of samples; perform hierarchical clustering analysis with bootstrapping; view false negative probabilities and positive and negative predictive values for t-tests between pairs of samples; easily assess experimental reproducibility; and visualize the data using volcano plots, scatterplots, and interactive three-dimensional principal component analyses. Also new in PIIKA 2 is a web-based interface, which allows users unfamiliar with command-line tools to easily provide input and download the results. Collectively, the additions and improvements described here enhance both the breadth and depth of analyses available, simplify the user interface, and make the software an even more valuable tool for the analysis of kinome microarray data. Both the web-based and stand-alone versions of PIIKA 2 can be accessed via http://saphire.usask.ca.

  8. PIIKA 2: an expanded, web-based platform for analysis of kinome microarray data.

    Science.gov (United States)

    Trost, Brett; Kindrachuk, Jason; Määttänen, Pekka; Napper, Scott; Kusalik, Anthony

    2013-01-01

    Kinome microarrays are comprised of peptides that act as phosphorylation targets for protein kinases. This platform is growing in popularity due to its ability to measure phosphorylation-mediated cellular signaling in a high-throughput manner. While software for analyzing data from DNA microarrays has also been used for kinome arrays, differences between the two technologies and associated biologies previously led us to develop Platform for Intelligent, Integrated Kinome Analysis (PIIKA), a software tool customized for the analysis of data from kinome arrays. Here, we report the development of PIIKA 2, a significantly improved version with new features and improvements in the areas of clustering, statistical analysis, and data visualization. Among other additions to the original PIIKA, PIIKA 2 now allows the user to: evaluate statistically how well groups of samples cluster together; identify sets of peptides that have consistent phosphorylation patterns among groups of samples; perform hierarchical clustering analysis with bootstrapping; view false negative probabilities and positive and negative predictive values for t-tests between pairs of samples; easily assess experimental reproducibility; and visualize the data using volcano plots, scatterplots, and interactive three-dimensional principal component analyses. Also new in PIIKA 2 is a web-based interface, which allows users unfamiliar with command-line tools to easily provide input and download the results. Collectively, the additions and improvements described here enhance both the breadth and depth of analyses available, simplify the user interface, and make the software an even more valuable tool for the analysis of kinome microarray data. Both the web-based and stand-alone versions of PIIKA 2 can be accessed via http://saphire.usask.ca.

  9. A High Phosphorus Diet Affects Lipid Metabolism in Rat Liver: A DNA Microarray Analysis

    Science.gov (United States)

    Chun, Sunwoo; Bamba, Takeshi; Suyama, Tatsuya; Ishijima, Tomoko; Fukusaki, Eiichiro; Abe, Keiko; Nakai, Yuji

    2016-01-01

    A high phosphorus (HP) diet causes disorders of renal function, bone metabolism, and vascular function. We previously demonstrated that DNA microarray analysis is an appropriate method to comprehensively evaluate the effects of a HP diet on kidney dysfunction such as calcification, fibrillization, and inflammation. We reported that type IIb sodium-dependent phosphate transporter is significantly up-regulated in this context. In the present study, we performed DNA microarray analysis to investigate the effects of a HP diet on the liver, which plays a pivotal role in energy metabolism. DNA microarray analysis was performed with total RNA isolated from the livers of rats fed a control diet (containing 0.3% phosphorus) or a HP diet (containing 1.2% phosphorus). Gene Ontology analysis of differentially expressed genes (DEGs) revealed that the HP diet induced down-regulation of genes involved in hepatic amino acid catabolism and lipogenesis, while genes related to fatty acid β-oxidation process were up-regulated. Although genes related to fatty acid biosynthesis were down-regulated in HP diet-fed rats, genes important for the elongation and desaturation reactions of omega-3 and -6 fatty acids were up-regulated. Concentrations of hepatic arachidonic acid and eicosapentaenoic acid were increased in HP diet-fed rats. These essential fatty acids activate peroxisome proliferator-activated receptor alpha (PPARα), a transcription factor for fatty acid β-oxidation. Evaluation of the upstream regulators of DEGs using Ingenuity Pathway Analysis indicated that PPARα was activated in the livers of HP diet-fed rats. Furthermore, the serum concentration of fibroblast growth factor 21, a hormone secreted from the liver that promotes fatty acid utilization in adipose tissue as a PPARα target gene, was higher (p = 0.054) in HP diet-fed rats than in control diet-fed rats. These data suggest that a HP diet enhances energy expenditure through the utilization of free fatty acids

  10. Global transcriptome analysis of the heat shock response ofshewanella oneidensis

    Energy Technology Data Exchange (ETDEWEB)

    Gao, Haichun; Wang, Sarah; Liu, Xueduan; Yan, Tinfeng; Wu, Liyou; Alm, Eric; Arkin, Adam P.; Thompson, Dorothea K.; Zhou, Jizhong

    2004-04-30

    Shewanella oneidensis is an important model organism for bioremediation studies because of its diverse respiratory capabilities. However, the genetic basis and regulatory mechanisms underlying the ability of S. oneidensis to survive and adapt to various environmentally relevant stresses is poorly understood. To define this organism's molecular response to elevated growth temperatures, temporal gene expression profiles were examined in cells subjected to heat stress using whole-genome DNA microarrays for S. oneidensis MR-1. Approximately 15 percent (711) of the predicted S. oneidensis genes represented on the microarray were significantly up- or down-regulated (P < 0.05) over a 25-min period following shift to the heat shock temperature (42 C). As expected, the majority of S. oneidensis genes exhibiting homology to known chaperones and heat shock proteins (Hsps) were highly and transiently induced. In addition, a number of predicted genes encoding enzymes in glycolys is and the pentose cycle, [NiFe] dehydrogenase, serine proteases, transcriptional regulators (MerR, LysR, and TetR families), histidine kinases, and hypothetical proteins were induced in response to heat stress. Genes encoding membrane proteins were differentially expressed, suggesting that cells possibly alter their membrane composition or structure in response to variations in growth temperature. A substantial number of the genes encoding ribosomal proteins displayed down-regulated co-expression patterns in response to heat stress, as did genes encoding prophage and flagellar proteins. Finally, based on computational comparative analysis of the upstream promoter regions of S.oneidensis heat-inducible genes, a putative regulatory motif, showing high conservation to the Escherichia coli sigma 32-binding consensus sequence, was identified.

  11. Biofilm formation and transcriptome analysis of Streptococcus gallolyticus subsp. gallolyticus in response to lysozyme.

    Directory of Open Access Journals (Sweden)

    Imke Grimm

    Full Text Available Streptococcus gallolyticus subsp. gallolyticus is a commensal bacterium of the human gastrointestinal tract, and a pathogen causing infective endocarditis and other biofilm-associated infections via exposed collagen. This study focuses on the characterization of the biofilm formation and collagen adhesion of S. gallolyticus subsp. gallolyticus under different conditions. In this study, it has been observed that the isolate UCN 34 is resistant to 20 mg/ml lysozyme in BHI medium, whereas the strain BAA-2069 builds more biofilm in the presence of lysozyme compared to in a control of BHI without lysozyme. A transcriptome analysis with whole genome microarrays of these two isolates in BHI medium with lysozyme compared to control without lysozyme revealed changes in gene expression levels. In the isolate BAA-2069, 67 genes showed increased expression in the presence of lysozyme, while in the isolate UCN 34, 165 genes showed increased expression and 30 genes showed decreased expression through lysozyme treatment. Products of genes which were higher expressed are in involved in transcription and translation, in cell-wall modification, in hydrogen peroxide resistance and in bacterial immunity. Furthermore, the adhesion ability of different strains of S. gallolyticus subsp. gallolyticus to collagen type I and IV was analyzed. Thereby, we compared the adhesion of 46 human isolates with 23 isolates from animals. It was shown that the adhesion ability depends significantly on whether the isolate was isolated from human or animal. For example, high adhesion ability was observed for strain UCN 34 isolated from an infective endocarditis patient, whereas strain DSM 16831 isolated from koala feces adhered only marginally to collagen. Full genome microarray analysis of these two strains revealed strain-dependent gene expression due to adhesion. The expression of 25 genes of a transposon and 15 genes of a phage region in strain DSM 16831 were increased, which

  12. Meta-Transcriptomic Analysis of a Chromate-Reducing Aquifer Microbial Community

    Science.gov (United States)

    Beller, H. R.; Brodie, E. L.; Han, R.; Karaoz, U.

    2010-12-01

    A major challenge for microbial ecology that has become more tractable in the advent of new molecular techniques is characterizing gene expression in complex microbial communities. We are using meta-transcriptomic analysis to characterize functional changes in an aquifer-derived, chromate-reducing microbial community as it transitions through various electron-accepting conditions. We inoculated anaerobic microcosms with groundwater from the Cr-contaminated Hanford 100H site and supplemented them with lactate and electron acceptors present at the site, namely, nitrate, sulfate, and Fe(III). The microcosms progressed successively through various electron-accepting conditions (e.g., denitrifying, sulfate-reducing, and ferric iron-reducing conditions, as well as nitrate-dependent, chemolithotrophic Fe(II)-oxidizing conditions). Cr(VI) was rapidly reduced initially and again upon further Cr(VI) amendments. Extensive geochemical sampling and analysis (e.g., lactate, acetate, chloride, nitrate, nitrite, sulfate, dissolved Cr(VI), total Fe(II)), RNA/DNA harvesting, and PhyloChip analyses were conducted. Methods were developed for removal of rRNA from total RNA in preparation for meta-transcriptome sequencing. To date, samples representing denitrifying and fermentative/sulfate-reducing conditions have been sequenced using 454 Titanium technology. Of the non-rRNA related reads for the denitrifying sample (which was also actively reducing chromate), ca. 8% were associated with denitrification and ca. 0.9% were associated with chromate resistance/transport, in contrast to the fermentative/sulfate-reducing sample (in which chromate had already been reduced), which had zero reads associated with either of these categories but many predicted proteins associated with sulfate-reducing bacteria. We observed sequences for key functional transcripts that were unique at the nucleotide level compared to the GenBank non-redundant database [such as L-lactate dehydrogenase (iron

  13. arrayCGHbase: an analysis platform for comparative genomic hybridization microarrays

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    Moreau Yves

    2005-05-01

    Full Text Available Abstract Background The availability of the human genome sequence as well as the large number of physically accessible oligonucleotides, cDNA, and BAC clones across the entire genome has triggered and accelerated the use of several platforms for analysis of DNA copy number changes, amongst others microarray comparative genomic hybridization (arrayCGH. One of the challenges inherent to this new technology is the management and analysis of large numbers of data points generated in each individual experiment. Results We have developed arrayCGHbase, a comprehensive analysis platform for arrayCGH experiments consisting of a MIAME (Minimal Information About a Microarray Experiment supportive database using MySQL underlying a data mining web tool, to store, analyze, interpret, compare, and visualize arrayCGH results in a uniform and user-friendly format. Following its flexible design, arrayCGHbase is compatible with all existing and forthcoming arrayCGH platforms. Data can be exported in a multitude of formats, including BED files to map copy number information on the genome using the Ensembl or UCSC genome browser. Conclusion ArrayCGHbase is a web based and platform independent arrayCGH data analysis tool, that allows users to access the analysis suite through the internet or a local intranet after installation on a private server. ArrayCGHbase is available at http://medgen.ugent.be/arrayCGHbase/.

  14. Transcriptomic data analysis and differential gene expression of antioxidant pathways in king penguin juveniles (Aptenodytes patagonicus) before and after acclimatization to marine life.

    Science.gov (United States)

    Rey, Benjamin; Dégletagne, Cyril; Duchamp, Claude

    2016-12-01

    In this article, we present differentially expressed gene profiles in the pectoralis muscle of wild juvenile king penguins that were either naturally acclimated to cold marine environment or experimentally immersed in cold water as compared with penguin juveniles that never experienced cold water immersion. Transcriptomic data were obtained by hybridizing penguins total cDNA on Affymetrix GeneChip Chicken Genome arrays and analyzed using maxRS algorithm , " Transcriptome analysis in non-model species: a new method for the analysis of heterologous hybridization on microarrays " (Dégletagne et al., 2010) [1] . We focused on genes involved in multiple antioxidant pathways. For better clarity, these differentially expressed genes were clustered into six functional groups according to their role in controlling redox homeostasis. The data are related to a comprehensive research study on the ontogeny of antioxidant functions in king penguins, "Hormetic response triggers multifaceted anti-oxidant strategies in immature king penguins (Aptenodytes patagonicus)" (Rey et al., 2016) [2] . The raw microarray dataset supporting the present analyses has been deposited at the Gene Expression Omnibus (GEO) repository under accessions GEO: GSE17725 and GEO: GSE82344.

  15. Sequencing and analysis of the Mediterranean amphioxus (Branchiostoma lanceolatum transcriptome.

    Directory of Open Access Journals (Sweden)

    Silvan Oulion

    Full Text Available BACKGROUND: The basally divergent phylogenetic position of amphioxus (Cephalochordata, as well as its conserved morphology, development and genetics, make it the best proxy for the chordate ancestor. Particularly, studies using the amphioxus model help our understanding of vertebrate evolution and development. Thus, interest for the amphioxus model led to the characterization of both the transcriptome and complete genome sequence of the American species, Branchiostoma floridae. However, recent technical improvements allowing induction of spawning in the laboratory during the breeding season on a daily basis with the Mediterranean species Branchiostoma lanceolatum have encouraged European Evo-Devo researchers to adopt this species as a model even though no genomic or transcriptomic data have been available. To fill this need we used the pyrosequencing method to characterize the B. lanceolatum transcriptome and then compared our results with the published transcriptome of B. floridae. RESULTS: Starting with total RNA from nine different developmental stages of B. lanceolatum, a normalized cDNA library was constructed and sequenced on Roche GS FLX (Titanium mode. Around 1.4 million of reads were produced and assembled into 70,530 contigs (average length of 490 bp. Overall 37% of the assembled sequences were annotated by BlastX and their Gene Ontology terms were determined. These results were then compared to genomic and transcriptomic data of B. floridae to assess similarities and specificities of each species. CONCLUSION: We obtained a high-quality amphioxus (B. lanceolatum reference transcriptome using a high throughput sequencing approach. We found that 83% of the predicted genes in the B. floridae complete genome sequence are also found in the B. lanceolatum transcriptome, while only 41% were found in the B. floridae transcriptome obtained with traditional Sanger based sequencing. Therefore, given the high degree of sequence conservation

  16. Nonlinear matching measure for the analysis of on-off type DNA microarray images

    Science.gov (United States)

    Kim, Jong D.; Park, Misun; Kim, Jongwon

    2003-07-01

    In this paper, we propose a new nonlinear matching measure for automatic analysis of the on-off type DNA microarray images in which the hybridized spots are detected by the template matching method. The targeting spots of HPV DNA chips are designed for genotyping the human papilloma virus(HPV). The proposed measure is obtained by binarythresholding over the whole template region and taking the number of white pixels inside the spotted area. This measure is evaluated in terms of the accuracy of the estimated marker location to show better performance than the normalized covariance.

  17. Transcriptome analysis of cytoplasmic male sterility and restoration in CMS-D8 cotton.

    Science.gov (United States)

    Suzuki, Hideaki; Rodriguez-Uribe, Laura; Xu, Jiannong; Zhang, Jinfa

    2013-10-01

    A global view of differential expression of genes in CMS-D8 of cotton was presented in this study which will facilitate the understanding of cytoplasmic male sterility in cotton. Cytoplasmic male sterility (CMS) is a maternally inherited trait in higher plants which is incapable of producing functional pollen. However, the male fertility can be restored by one or more nuclear-encoded restorer genes. A genome-wide transcriptome analysis of CMS and restoration in cotton is currently lacking. In this study, Affymetrix GeneChips© Cotton Genome Array containing 24,132 transcripts was used to compare differentially expressed (DE) genes of flower buds at the meiosis stage between CMS and its restorer cotton plants conditioned by the D8 cytoplasm. A total of 458 (1.9 %) of DE genes including 127 up-regulated and 331 down-regulated ones were identified in the CMS-D8 line. Quantitative RT-PCR was used to validate 10 DE genes selected from seven functional categories. The most frequent DE gene group was found to encode putative proteins involved in cell wall expansion, such as pectinesterase, pectate lyase, pectin methylesterase, glyoxal oxidase, polygalacturonase, indole-3-acetic acid-amino synthetase, and xyloglucan endo-transglycosylase. Genes in cytoskeleton category including actin, which plays a key role in cell wall expansion, cell elongation and cell division, were also highly differentially expressed between the fertile and CMS plants. This work represents the first study in utilizing microarray to identify CMS-related genes by comparing overall DE genes between fertile and CMS plants in cotton. The results provide evidence that many CMS-associated genes are mainly involved in cell wall expansion. Further analysis will be required to elucidate the molecular mechanisms of male sterility which will facilitate the development of new hybrid cultivars in cotton.

  18. Identification of estrogen target genes during zebrafish embryonic development through transcriptomic analysis.

    Directory of Open Access Journals (Sweden)

    Ruixin Hao

    Full Text Available Estrogen signaling is important for vertebrate embryonic development. Here we have used zebrafish (Danio rerio as a vertebrate model to analyze estrogen signaling during development. Zebrafish embryos were exposed to 1 µM 17β-estradiol (E2 or vehicle from 3 hours to 4 days post fertilization (dpf, harvested at 1, 2, 3 and 4 dpf, and subjected to RNA extraction for transcriptome analysis using microarrays. Differentially expressed genes by E2-treatment were analyzed with hierarchical clustering followed by biological process and tissue enrichment analysis. Markedly distinct sets of genes were up and down-regulated by E2 at the four different time points. Among these genes, only the well-known estrogenic marker vtg1 was co-regulated at all time points. Despite this, the biological functional categories targeted by E2 were relatively similar throughout zebrafish development. According to knowledge-based tissue enrichment, estrogen responsive genes were clustered mainly in the liver, pancreas and brain. This was in line with the developmental dynamics of estrogen-target tissues that were visualized using transgenic zebrafish containing estrogen responsive elements driving the expression of GFP (Tg(5xERE:GFP. Finally, the identified embryonic estrogen-responsive genes were compared to already published estrogen-responsive genes identified in male adult zebrafish (Gene Expression Omnibus database. The expressions of a few genes were co-regulated by E2 in both embryonic and adult zebrafish. These could potentially be used as estrogenic biomarkers for exposure to estrogens or estrogenic endocrine disruptors in zebrafish. In conclusion, our data suggests that estrogen effects on early embryonic zebrafish development are stage- and tissue- specific.

  19. In Silico Analysis of Microarray-Based Gene Expression Profiles Predicts Tumor Cell Response to Withanolides

    Directory of Open Access Journals (Sweden)

    Thomas Efferth

    2012-05-01

    Full Text Available Withania somnifera (L. Dunal (Indian ginseng, winter cherry, Solanaceae is widely used in traditional medicine. Roots are either chewed or used to prepare beverages (aqueous decocts. The major secondary metabolites of Withania somnifera are the withanolides, which are C-28-steroidal lactone triterpenoids. Withania somnifera extracts exert chemopreventive and anticancer activities in vitro and in vivo. The aims of the present in silico study were, firstly, to investigate whether tumor cells develop cross-resistance between standard anticancer drugs and withanolides and, secondly, to elucidate the molecular determinants of sensitivity and resistance of tumor cells towards withanolides. Using IC50 concentrations of eight different withanolides (withaferin A, withaferin A diacetate, 3-azerininylwithaferin A, withafastuosin D diacetate, 4-B-hydroxy-withanolide E, isowithanololide E, withafastuosin E, and withaperuvin and 19 established anticancer drugs, we analyzed the cross-resistance profile of 60 tumor cell lines. The cell lines revealed cross-resistance between the eight withanolides. Consistent cross-resistance between withanolides and nitrosoureas (carmustin, lomustin, and semimustin was also observed. Then, we performed transcriptomic microarray-based COMPARE and hierarchical cluster analyses of mRNA expression to identify mRNA expression profiles predicting sensitivity or resistance towards withanolides. Genes from diverse functional groups were significantly associated with response of tumor cells to withaferin A diacetate, e.g. genes functioning in DNA damage and repair, stress response, cell growth regulation, extracellular matrix components, cell adhesion and cell migration, constituents of the ribosome, cytoskeletal organization and regulation, signal transduction, transcription factors, and others.

  20. Transcriptome analysis of female and male flower buds of Idesia polycarpa Maxim. var. vestita Diels

    Directory of Open Access Journals (Sweden)

    Lanju Mei

    2017-09-01

    Conclusion: This work provides the first detailed transcriptome analysis of female and male flower of I. polycarpa and lays foundations for future studies on the molecular mechanisms underlying flower bud development of I. polycarpa.

  1. Improvement of Lactobacillus plantarum aerobic growth as directed by comprehensive transcriptome analysis

    NARCIS (Netherlands)

    Stevens, Marc J. A.; Wiersma, Anne; de Vos, Willern M.; Kuipers, Oscar P.; Smid, Eddy J.; Molenaar, Douwe; Kleerebezem, Michiel; Vos, Willem M. de

    An aerobic Lactobacillus plantarum culture displayed growth stagnation during early growth. Transcriptome analysis revealed that resumption of growth after stagnation correlated with activation of CO(2)-producing pathways, suggesting that a limiting CO(2) concentration induced the stagnation.

  2. Investigating the effect of paralogs on microarray gene-set analysis

    LENUS (Irish Health Repository)

    Faure, Andre J

    2011-01-24

    Abstract Background In order to interpret the results obtained from a microarray experiment, researchers often shift focus from analysis of individual differentially expressed genes to analyses of sets of genes. These gene-set analysis (GSA) methods use previously accumulated biological knowledge to group genes into sets and then aim to rank these gene sets in a way that reflects their relative importance in the experimental situation in question. We suspect that the presence of paralogs affects the ability of GSA methods to accurately identify the most important sets of genes for subsequent research. Results We show that paralogs, which typically have high sequence identity and similar molecular functions, also exhibit high correlation in their expression patterns. We investigate this correlation as a potential confounding factor common to current GSA methods using Indygene http:\\/\\/www.cbio.uct.ac.za\\/indygene, a web tool that reduces a supplied list of genes so that it includes no pairwise paralogy relationships above a specified sequence similarity threshold. We use the tool to reanalyse previously published microarray datasets and determine the potential utility of accounting for the presence of paralogs. Conclusions The Indygene tool efficiently removes paralogy relationships from a given dataset and we found that such a reduction, performed prior to GSA, has the ability to generate significantly different results that often represent novel and plausible biological hypotheses. This was demonstrated for three different GSA approaches when applied to the reanalysis of previously published microarray datasets and suggests that the redundancy and non-independence of paralogs is an important consideration when dealing with GSA methodologies.

  3. Automated detection of regions of interest for tissue microarray experiments: an image texture analysis

    International Nuclear Information System (INIS)

    Karaçali, Bilge; Tözeren, Aydin

    2007-01-01

    Recent research with tissue microarrays led to a rapid progress toward quantifying the expressions of large sets of biomarkers in normal and diseased tissue. However, standard procedures for sampling tissue for molecular profiling have not yet been established. This study presents a high throughput analysis of texture heterogeneity on breast tissue images for the purpose of identifying regions of interest in the tissue for molecular profiling via tissue microarray technology. Image texture of breast histology slides was described in terms of three parameters: the percentage of area occupied in an image block by chromatin (B), percentage occupied by stroma-like regions (P), and a statistical heterogeneity index H commonly used in image analysis. Texture parameters were defined and computed for each of the thousands of image blocks in our dataset using both the gray scale and color segmentation. The image blocks were then classified into three categories using the texture feature parameters in a novel statistical learning algorithm. These categories are as follows: image blocks specific to normal breast tissue, blocks specific to cancerous tissue, and those image blocks that are non-specific to normal and disease states. Gray scale and color segmentation techniques led to identification of same regions in histology slides as cancer-specific. Moreover the image blocks identified as cancer-specific belonged to those cell crowded regions in whole section image slides that were marked by two pathologists as regions of interest for further histological studies. These results indicate the high efficiency of our automated method for identifying pathologic regions of interest on histology slides. Automation of critical region identification will help minimize the inter-rater variability among different raters (pathologists) as hundreds of tumors that are used to develop an array have typically been evaluated (graded) by different pathologists. The region of interest

  4. Prenatal chromosomal microarray analysis in fetuses with congenital heart disease: a prospective cohort study.

    Science.gov (United States)

    Wang, Yan; Cao, Li; Liang, Dong; Meng, Lulu; Wu, Yun; Qiao, Fengchang; Ji, Xiuqing; Luo, Chunyu; Zhang, Jingjing; Xu, Tianhui; Yu, Bin; Wang, Leilei; Wang, Ting; Pan, Qiong; Ma, Dingyuan; Hu, Ping; Xu, Zhengfeng

    2018-02-01

    Currently, chromosomal microarray analysis is considered the first-tier test in pediatric care and prenatal diagnosis. However, the diagnostic yield of chromosomal microarray analysis for prenatal diagnosis of congenital heart disease has not been evaluated based on a large cohort. Our aim was to evaluate the clinical utility of chromosomal microarray as the first-tier test for chromosomal abnormalities in fetuses with congenital heart disease. In this prospective study, 602 prenatal cases of congenital heart disease were investigated using single nucleotide polymorphism array over a 5-year period. Overall, pathogenic chromosomal abnormalities were identified in 125 (20.8%) of 602 prenatal cases of congenital heart disease, with 52.0% of them being numerical chromosomal abnormalities. The detection rates of likely pathogenic copy number variations and variants of uncertain significance were 1.3% and 6.0%, respectively. The detection rate of pathogenic chromosomal abnormalities in congenital heart disease plus additional structural anomalies (48.9% vs 14.3%, P congenital heart disease group. Additionally, the detection rate in congenital heart disease with additional structural anomalies group was significantly higher than that in congenital heart disease with soft markers group (48.9% vs 19.8%, P congenital heart disease with additional structural anomalies and congenital heart disease with intrauterine growth retardation groups (48.9% vs 50.0%), congenital heart disease with soft markers and congenital heart disease with intrauterine growth retardation groups (19.8% vs 50.0%), or congenital heart disease with soft markers and isolated congenital heart disease groups (19.8% vs 14.3%). The detection rate in fetuses with congenital heart disease plus mild ventriculomegaly was significantly higher than in those with other types of soft markers (50.0% vs 15.6%, P congenital heart disease in clinical practice. Copyright © 2017 Elsevier Inc. All rights reserved.

  5. Previously unidentified changes in renal cell carcinoma gene expression identified by parametric analysis of microarray data

    International Nuclear Information System (INIS)

    Lenburg, Marc E; Liou, Louis S; Gerry, Norman P; Frampton, Garrett M; Cohen, Herbert T; Christman, Michael F

    2003-01-01

    Renal cell carcinoma is a common malignancy that often presents as a metastatic-disease for which there are no effective treatments. To gain insights into the mechanism of renal cell carcinogenesis, a number of genome-wide expression profiling studies have been performed. Surprisingly, there is very poor agreement among these studies as to which genes are differentially regulated. To better understand this lack of agreement we profiled renal cell tumor gene expression using genome-wide microarrays (45,000 probe sets) and compare our analysis to previous microarray studies. We hybridized total RNA isolated from renal cell tumors and adjacent normal tissue to Affymetrix U133A and U133B arrays. We removed samples with technical defects and removed probesets that failed to exhibit sequence-specific hybridization in any of the samples. We detected differential gene expression in the resulting dataset with parametric methods and identified keywords that are overrepresented in the differentially expressed genes with the Fisher-exact test. We identify 1,234 genes that are more than three-fold changed in renal tumors by t-test, 800 of which have not been previously reported to be altered in renal cell tumors. Of the only 37 genes that have been identified as being differentially expressed in three or more of five previous microarray studies of renal tumor gene expression, our analysis finds 33 of these genes (89%). A key to the sensitivity and power of our analysis is filtering out defective samples and genes that are not reliably detected. The widespread use of sample-wise voting schemes for detecting differential expression that do not control for false positives likely account for the poor overlap among previous studies. Among the many genes we identified using parametric methods that were not previously reported as being differentially expressed in renal cell tumors are several oncogenes and tumor suppressor genes that likely play important roles in renal cell

  6. BioconductorBuntu: a Linux distribution that implements a web-based DNA microarray analysis server.

    Science.gov (United States)

    Geeleher, Paul; Morris, Dermot; Hinde, John P; Golden, Aaron

    2009-06-01

    BioconductorBuntu is a custom distribution of Ubuntu Linux that automatically installs a server-side microarray processing environment, providing a user-friendly web-based GUI to many of the tools developed by the Bioconductor Project, accessible locally or across a network. System installation is via booting off a CD image or by using a Debian package provided to upgrade an existing Ubuntu installation. In its current version, several microarray analysis pipelines are supported including oligonucleotide, dual-or single-dye experiments, including post-processing with Gene Set Enrichment Analysis. BioconductorBuntu is designed to be extensible, by server-side integration of further relevant Bioconductor modules as required, facilitated by its straightforward underlying Python-based infrastructure. BioconductorBuntu offers an ideal environment for the development of processing procedures to facilitate the analysis of next-generation sequencing datasets. BioconductorBuntu is available for download under a creative commons license along with additional documentation and a tutorial from (http://bioinf.nuigalway.ie).

  7. A benchmark for statistical microarray data analysis that preserves actual biological and technical variance.

    Science.gov (United States)

    De Hertogh, Benoît; De Meulder, Bertrand; Berger, Fabrice; Pierre, Michael; Bareke, Eric; Gaigneaux, Anthoula; Depiereux, Eric

    2010-01-11

    Recent reanalysis of spike-in datasets underscored the need for new and more accurate benchmark datasets for statistical microarray analysis. We present here a fresh method using biologically-relevant data to evaluate the performance of statistical methods. Our novel method ranks the probesets from a dataset composed of publicly-available biological microarray data and extracts subset matrices with precise information/noise ratios. Our method can be used to determine the capability of different methods to better estimate variance for a given number of replicates. The mean-variance and mean-fold change relationships of the matrices revealed a closer approximation of biological reality. Performance analysis refined the results from benchmarks published previously.We show that the Shrinkage t test (close to Limma) was the best of the methods tested, except when two replicates were examined, where the Regularized t test and the Window t test performed slightly better. The R scripts used for the analysis are available at http://urbm-cluster.urbm.fundp.ac.be/~bdemeulder/.

  8. Illumina–based de novo transcriptome sequencing and analysis of ...

    Indian Academy of Sciences (India)

    Administrator

    2017-10-25

    Oct 25, 2017 ... (Shanghai, China) following manufacturer's protocols (Illumina, San .... suggests that pathways involved in musk production are expressed at a ..... Strickler S. R., Aureliano B. and Mueller L. A. 2012 Designing a transcriptome.

  9. Transcriptome analysis of Pinus massoniana Lamb. microstrobili during sexual reversal

    Directory of Open Access Journals (Sweden)

    Feng Xiao

    2018-04-01

    Full Text Available The normal megastrobilli and microstrobilli before and after the sexual reversal in Pinus massoniana Lamb. were studied and classified using a transcriptomic approach. In the analysis, a total of 190,023 unigenes were obtained with an average length of 595 bp. The annotated unigenes were divided into 56 functional groups and 130 metabolic pathways involved in the physiological and biochemical processes related to ribosome biogenesis, carbon metabolism, and amino acid biosynthesis. Analysis revealed 4,758 differentially expressed genes (DEGs between the mega- and microstrobili from the polycone twig. The DEGs between the mega- and microstrobili from the normal twig were 5,550. In the polycone twig, 1,188 DEGs were identified between the microstrobili and the sexually reversed megastrobili. Concerning plant hormone signal transduction pathways, the DEGs from both the normal and polycone twigs displayed distinct male or female associated expression patterns. There were 36 common hormone-related DEGs from the two types of twigs of P. massoniana. Interestingly, expression of these DEGs was up-regulated in the bisexual strobili, which underwent the sexual reversal. A portion of MADS-box genes in the bisexual strobili were up-regulated relative to expression in microstrobili.

  10. Transcriptome sequencing and positive selected genes analysis of Bombyx mandarina.

    Directory of Open Access Journals (Sweden)

    Tingcai Cheng

    Full Text Available The wild silkworm Bombyx mandarina is widely believed to be an ancestor of the domesticated silkworm, Bombyx mori. Silkworms are often used as a model for studying the mechanism of species domestication. Here, we performed transcriptome sequencing of the wild silkworm using an Illumina HiSeq2000 platform. We produced 100,004,078 high-quality reads and assembled them into 50,773 contigs with an N50 length of 1764 bp and a mean length of 941.62 bp. A total of 33,759 unigenes were identified, with 12,805 annotated in the Nr database, 8273 in the Pfam database, and 9093 in the Swiss-Prot database. Expression profile analysis found significant differential expression of 1308 unigenes between the middle silk gland (MSG and posterior silk gland (PSG. Three sericin genes (sericin 1, sericin 2, and sericin 3 were expressed specifically in the MSG and three fibroin genes (fibroin-H, fibroin-L, and fibroin/P25 were expressed specifically in the PSG. In addition, 32,297 Single-nucleotide polymorphisms (SNPs and 361 insertion-deletions (INDELs were detected. Comparison with the domesticated silkworm p50/Dazao identified 5,295 orthologous genes, among which 400 might have experienced or to be experiencing positive selection by Ka/Ks analysis. These data and analyses presented here provide insights into silkworm domestication and an invaluable resource for wild silkworm genomics research.

  11. Chicken hepatic response to chronic heat stress using integrated transcriptome and metabolome analysis.

    Directory of Open Access Journals (Sweden)

    Sara F Jastrebski

    Full Text Available The liver plays a central role in metabolism and is important in maintaining homeostasis throughout the body. This study integrated transcriptomic and metabolomic data to understand how the liver responds under chronic heat stress. Chickens from a rapidly growing broiler line were heat stressed for 8 hours per day for one week and liver samples were collected at 28 days post hatch. Transcriptome analysis reveals changes in genes responsible for cell cycle regulation, DNA replication, and DNA repair along with immune function. Integrating the metabolome and transcriptome data highlighted multiple pathways affected by heat stress including glucose, amino acid, and lipid metabolism along with glutathione production and beta-oxidation.

  12. Incorporation of gene-specific variability improves expression analysis using high-density DNA microarrays

    Directory of Open Access Journals (Sweden)

    Spitznagel Edward

    2003-11-01

    Full Text Available Abstract Background The assessment of data reproducibility is essential for application of microarray technology to exploration of biological pathways and disease states. Technical variability in data analysis largely depends on signal intensity. Within that context, the reproducibility of individual probe sets has not been hitherto addressed. Results We used an extraordinarily large replicate data set derived from human placental trophoblast to analyze probe-specific contribution to variability of gene expression. We found that signal variability, in addition to being signal-intensity dependant, is probe set-specific. Importantly, we developed a novel method to quantify the contribution of this probe set-specific variability. Furthermore, we devised a formula that incorporates a priori-computed, replicate-based information on probe set- and intensity-specific variability in determination of expression changes even without technical replicates. Conclusion The strategy of incorporating probe set-specific variability is superior to analysis based on arbitrary fold-change thresholds. We recommend its incorporation to any computation of gene expression changes using high-density DNA microarrays. A Java application implementing our T-score is available at http://www.sadovsky.wustl.edu/tscore.html.

  13. Segment and fit thresholding: a new method for image analysis applied to microarray and immunofluorescence data.

    Science.gov (United States)

    Ensink, Elliot; Sinha, Jessica; Sinha, Arkadeep; Tang, Huiyuan; Calderone, Heather M; Hostetter, Galen; Winter, Jordan; Cherba, David; Brand, Randall E; Allen, Peter J; Sempere, Lorenzo F; Haab, Brian B

    2015-10-06

    Experiments involving the high-throughput quantification of image data require algorithms for automation. A challenge in the development of such algorithms is to properly interpret signals over a broad range of image characteristics, without the need for manual adjustment of parameters. Here we present a new approach for locating signals in image data, called Segment and Fit Thresholding (SFT). The method assesses statistical characteristics of small segments of the image and determines the best-fit trends between the statistics. Based on the relationships, SFT identifies segments belonging to background regions; analyzes the background to determine optimal thresholds; and analyzes all segments to identify signal pixels. We optimized the initial settings for locating background and signal in antibody microarray and immunofluorescence data and found that SFT performed well over multiple, diverse image characteristics without readjustment of settings. When used for the automated analysis of multicolor, tissue-microarray images, SFT correctly found the overlap of markers with known subcellular localization, and it performed better than a fixed threshold and Otsu's method for selected images. SFT promises to advance the goal of full automation in image analysis.

  14. Large scale aggregate microarray analysis reveals three distinct molecular subclasses of human preeclampsia.

    Science.gov (United States)

    Leavey, Katherine; Bainbridge, Shannon A; Cox, Brian J

    2015-01-01

    Preeclampsia (PE) is a life-threatening hypertensive pathology of pregnancy affecting 3-5% of all pregnancies. To date, PE has no cure, early detection markers, or effective treatments short of the removal of what is thought to be the causative organ, the placenta, which may necessitate a preterm delivery. Additionally, numerous small placental microarray studies attempting to identify "PE-specific" genes have yielded inconsistent results. We therefore hypothesize that preeclampsia is a multifactorial disease encompassing several pathology subclasses, and that large cohort placental gene expression analysis will reveal these groups. To address our hypothesis, we utilized known bioinformatic methods to aggregate 7 microarray data sets across multiple platforms in order to generate a large data set of 173 patient samples, including 77 with preeclampsia. Unsupervised clustering of these patient samples revealed three distinct molecular subclasses of PE. This included a "canonical" PE subclass demonstrating elevated expression of known PE markers and genes associated with poor oxygenation and increased secretion, as well as two other subclasses potentially representing a poor maternal response to pregnancy and an immunological presentation of preeclampsia. Our analysis sheds new light on the heterogeneity of PE patients, and offers up additional avenues for future investigation. Hopefully, our subclassification of preeclampsia based on molecular diversity will finally lead to the development of robust diagnostics and patient-based treatments for this disorder.

  15. Prognostic value of matrix metalloproteinase 9 expression in patients with juvenile nasopharyngeal angiofibroma: tissue microarray analysis.

    Science.gov (United States)

    Sun, Xicai; Guo, Limin; Wang, Jingjing; Wang, Huan; Liu, Zhuofu; Liu, Juan; Yu, Huapeng; Hu, Li; Li, Han; Wang, Dehui

    2014-08-01

    Although JNA is a benign neoplasm histopathologically, it has a propensity for locally destructive growth and remains a higher postoperative recurrence rate. The aim of this study was to analyze the expression and localization of MMP-9 in JNA using tissue microarray to elucidate its correlation with clinicopathological features and recurrence. The expression of MMP-9 was assessed by immunohistochemistry in a tissue microarray from 70 patients with JNA and 10 control subjects. Correlation between the levels of MMP-9 expression and clinicopathologic variables, as well as tumor recurrence, were analyzed. MMP-9 was detected in perivascular and extravascular less differentiated cells and stromal cells of patients with JNA but not in the matured vascular endothelial cells of these patients. The presence of MMP-9 expression in JNA was correlated with patient's age (p=0.001). Spearman correlation analysis suggested that high expression of MMP-9 in JNA had negative correlation with patient's age (r=-0.412, p<0.001). The recurrence rate in JNA patients with high MMP-9 expression was significantly higher than those with low MMP-9 expression (p=0.002). In multivariate and ROC curve analysis, MMP-9 was a good prognostic factor for tumor recurrence of JNA. Higher MMP-9 expression is a poor prognostic factor for patients with JNA who have been surgically treated. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

  16. Evaluation of Different Normalization and Analysis Procedures for Illumina Gene Expression Microarray Data Involving Small Changes

    Science.gov (United States)

    Johnstone, Daniel M.; Riveros, Carlos; Heidari, Moones; Graham, Ross M.; Trinder, Debbie; Berretta, Regina; Olynyk, John K.; Scott, Rodney J.; Moscato, Pablo; Milward, Elizabeth A.

    2013-01-01

    While Illumina microarrays can be used successfully for detecting small gene expression changes due to their high degree of technical replicability, there is little information on how different normalization and differential expression analysis strategies affect outcomes. To evaluate this, we assessed concordance across gene lists generated by applying different combinations of normalization strategy and analytical approach to two Illumina datasets with modest expression changes. In addition to using traditional statistical approaches, we also tested an approach based on combinatorial optimization. We found that the choice of both normalization strategy and analytical approach considerably affected outcomes, in some cases leading to substantial differences in gene lists and subsequent pathway analysis results. Our findings suggest that important biological phenomena may be overlooked when there is a routine practice of using only one approach to investigate all microarray datasets. Analytical artefacts of this kind are likely to be especially relevant for datasets involving small fold changes, where inherent technical variation—if not adequately minimized by effective normalization—may overshadow true biological variation. This report provides some basic guidelines for optimizing outcomes when working with Illumina datasets involving small expression changes. PMID:27605185

  17. Comparison of RNA-seq and microarray-based models for clinical endpoint prediction.

    Science.gov (United States)

    Zhang, Wenqian; Yu, Ying; Hertwig, Falk; Thierry-Mieg, Jean; Zhang, Wenwei; Thierry-Mieg, Danielle; Wang, Jian; Furlanello, Cesare; Devanarayan, Viswanath; Cheng, Jie; Deng, Youping; Hero, Barbara; Hong, Huixiao; Jia, Meiwen; Li, Li; Lin, Simon M; Nikolsky, Yuri; Oberthuer, André; Qing, Tao; Su, Zhenqiang; Volland, Ruth; Wang, Charles; Wang, May D; Ai, Junmei; Albanese, Davide; Asgharzadeh, Shahab; Avigad, Smadar; Bao, Wenjun; Bessarabova, Marina; Brilliant, Murray H; Brors, Benedikt; Chierici, Marco; Chu, Tzu-Ming; Zhang, Jibin; Grundy, Richard G; He, Min Max; Hebbring, Scott; Kaufman, Howard L; Lababidi, Samir; Lancashire, Lee J; Li, Yan; Lu, Xin X; Luo, Heng; Ma, Xiwen; Ning, Baitang; Noguera, Rosa; Peifer, Martin; Phan, John H; Roels, Frederik; Rosswog, Carolina; Shao, Susan; Shen, Jie; Theissen, Jessica; Tonini, Gian Paolo; Vandesompele, Jo; Wu, Po-Yen; Xiao, Wenzhong; Xu, Joshua; Xu, Weihong; Xuan, Jiekun; Yang, Yong; Ye, Zhan; Dong, Zirui; Zhang, Ke K; Yin, Ye; Zhao, Chen; Zheng, Yuanting; Wolfinger, Russell D; Shi, Tieliu; Malkas, Linda H; Berthold, Frank; Wang, Jun; Tong, Weida; Shi, Leming; Peng, Zhiyu; Fischer, Matthias

    2015-06-25

    Gene expression profiling is being widely applied in cancer research to identify biomarkers for clinical endpoint prediction. Since RNA-seq provides a powerful tool for transcriptome-based applications beyond the limitations of microarrays, we sought to systematically evaluate the performance of RNA-seq-based and microarray-based classifiers in this MAQC-III/SEQC study for clinical endpoint prediction using neuroblastoma as a model. We generate gene expression profiles from 498 primary neuroblastomas using both RNA-seq and 44 k microarrays. Characterization of the neuroblastoma transcriptome by RNA-seq reveals that more than 48,000 genes and 200,000 transcripts are being expressed in this malignancy. We also find that RNA-seq provides much more detailed information on specific transcript expression patterns in clinico-genetic neuroblastoma subgroups than microarrays. To systematically compare the power of RNA-seq and microarray-based models in predicting clinical endpoints, we divide the cohort randomly into training and validation sets and develop 360 predictive models on six clinical endpoints of varying predictability. Evaluation of factors potentially affecting model performances reveals that prediction accuracies are most strongly influenced by the nature of the clinical endpoint, whereas technological platforms (RNA-seq vs. microarrays), RNA-seq data analysis pipelines, and feature levels (gene vs. transcript vs. exon-junction level) do not significantly affect performances of the models. We demonstrate that RNA-seq outperforms microarrays in determining the transcriptomic characteristics of cancer, while RNA-seq and microarray-based models perform similarly in clinical endpoint prediction. Our findings may be valuable to guide future studies on the development of gene expression-based predictive models and their implementation in clinical practice.

  18. Integrative systems analysis of diet-induced obesity identified a critical transition in the transcriptomes of the murine liver and epididymal white adipose tissue.

    Science.gov (United States)

    Kim, J; Kwon, E-Y; Park, S; Kim, J-R; Choi, S-W; Choi, M-S; Kim, S-J

    2016-02-01

    It is well known that high-fat diet (HFD) can cause immune system-related pathological alterations after a significant body weight gain. The mechanisms of the delayed pathological alterations during the development of diet-induced obesity (DIO) are not fully understood. To elucidate the mechanisms underlying DIO development, we analyzed time-course microarray data obtained from a previous study. First, differentially expressed genes (DEGs) were identified at each time point by comparing the hepatic transcriptome of mice fed HFD with that of mice fed normal diet. Next, we clustered the union of DEGs and identified annotations related to each cluster. Finally, we constructed an 'integrated obesity-associated gene regulatory network (GRN) in murine liver'. We analyzed the epididymal white adipose tissue (eWAT) transcriptome usig the same procedure. Based on time-course microarray data, we found that the genes associated with immune responses were upregulated with an oscillating expression pattern between weeks 2 and 8, relatively downregulated between weeks 12 and 16, and eventually upregulated after week 20 in the liver of the mice fed HFD. The genes associated with immune responses were also upregulated at late stage, in the eWAT of the mice fed HFD. These results suggested that a critical transition occurred in the immune system-related transcriptomes of the liver and eWAT around week 16 of the DIO development, and this may be associated with the delayed pathological alterations. The GRN analysis suggested that Maff may be a key transcription factor for the immune system-related critical transition thatoccurred at week 16. We found that transcription factors associated with immune responses were centrally located in the integrated obesity-associated GRN in the liver. In this study, systems analysis identified regulatory network modules underlying the delayed immune system-related pathological changes during the development of DIO and could suggest possible

  19. DATE analysis: A general theory of biological change applied to microarray data.

    Science.gov (United States)

    Rasnick, David

    2009-01-01

    In contrast to conventional data mining, which searches for specific subsets of genes (extensive variables) to correlate with specific phenotypes, DATE analysis correlates intensive state variables calculated from the same datasets. At the heart of DATE analysis are two biological equations of state not dependent on genetic pathways. This result distinguishes DATE analysis from other bioinformatics approaches. The dimensionless state variable F quantifies the relative overall cellular activity of test cells compared to well-chosen reference cells. The variable pi(i) is the fold-change in the expression of the ith gene of test cells relative to reference. It is the fraction phi of the genome undergoing differential expression-not the magnitude pi-that controls biological change. The state variable phi is equivalent to the control strength of metabolic control analysis. For tractability, DATE analysis assumes a linear system of enzyme-connected networks and exploits the small average contribution of each cellular component. This approach was validated by reproducible values of the state variables F, RNA index, and phi calculated from random subsets of transcript microarray data. Using published microarray data, F, RNA index, and phi were correlated with: (1) the blood-feeding cycle of the malaria parasite, (2) embryonic development of the fruit fly, (3) temperature adaptation of Killifish, (4) exponential growth of cultured S. pneumoniae, and (5) human cancers. DATE analysis was applied to aCGH data from the great apes. A good example of the power of DATE analysis is its application to genomically unstable cancers, which have been refractory to data mining strategies. 2009 American Institute of Chemical Engineers Biotechnol.

  20. Performance analysis of clustering techniques over microarray data: A case study

    Science.gov (United States)

    Dash, Rasmita; Misra, Bijan Bihari

    2018-03-01

    Handling big data is one of the major issues in the field of statistical data analysis. In such investigation cluster analysis plays a vital role to deal with the large scale data. There are many clustering techniques with different cluster analysis approach. But which approach suits a particular dataset is difficult to predict. To deal with this problem a grading approach is introduced over many clustering techniques to identify a stable technique. But the grading approach depends on the characteristic of dataset as well as on the validity indices. So a two stage grading approach is implemented. In this study the grading approach is implemented over five clustering techniques like hybrid swarm based clustering (HSC), k-means, partitioning around medoids (PAM), vector quantization (VQ) and agglomerative nesting (AGNES). The experimentation is conducted over five microarray datasets with seven validity indices. The finding of grading approach that a cluster technique is significant is also established by Nemenyi post-hoc hypothetical test.

  1. Sex Change in Clownfish: Molecular Insights from Transcriptome Analysis

    KAUST Repository

    Casas, Laura

    2016-10-17

    Sequential hermaphroditism is a unique reproductive strategy among teleosts that is displayed mainly in fish species living in the coral reef environment. The reproductive biology of hermaphrodites has long been intriguing; however, very little is known about the molecular pathways underlying their sex change. Here, we provide the first de novo transcriptome analyses of a hermaphrodite teleost´s undergoing sex change in its natural environment. Our study has examined relative gene expression across multiple groups—rather than just two contrasting conditions— and has allowed us to explore the differential expression patterns throughout the whole process. Our analysis has highlighted the rapid and complex genomic response of the brain associated with sex change, which is subsequently transmitted to the gonads, identifying a large number of candidate genes, some well-known and some novel, involved in the process. The present study provides strong evidence of the importance of the sex steroidogenic machinery during sex change in clownfish, with the aromatase gene playing a central role, both in the brain and the gonad. This work constitutes the first genome-wide study in a social sex-changing species and provides insights into the genetic mechanism governing social sex change and gonadal restructuring in protandrous hermaphrodites.

  2. Chromosomal Microarray Analysis of Consecutive Individuals with Autism Spectrum Disorders Using an Ultra-High Resolution Chromosomal Microarray Optimized for Neurodevelopmental Disorders

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    Karen S. Ho

    2016-12-01

    Full Text Available Copy number variants (CNVs detected by chromosomal microarray analysis (CMA significantly contribute to understanding the etiology of autism spectrum disorder (ASD and other related conditions. In recognition of the value of CMA testing and its impact on medical management, CMA is in medical guidelines as a first-tier test in the evaluation of children with these disorders. As CMA becomes adopted into routine care for these patients, it becomes increasingly important to report these clinical findings. This study summarizes the results of over 4 years of CMA testing by a CLIA-certified clinical testing laboratory. Using a 2.8 million probe microarray optimized for the detection of CNVs associated with neurodevelopmental disorders, we report an overall CNV detection rate of 28.1% in 10,351 consecutive patients, which rises to nearly 33% in cases without ASD, with only developmental delay/intellectual disability (DD/ID and/or multiple congenital anomalies (MCA. The overall detection rate for individuals with ASD is also significant at 24.4%. The detection rate and pathogenic yield of CMA vary significantly with the indications for testing, age, and gender, as well as the specialty of the ordering doctor. We note discrete differences in the most common recurrent CNVs found in individuals with or without a diagnosis of ASD.

  3. SegMine workflows for semantic microarray data analysis in Orange4WS

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    Kulovesi Kimmo

    2011-10-01

    Full Text Available Abstract Background In experimental data analysis, bioinformatics researchers increasingly rely on tools that enable the composition and reuse of scientific workflows. The utility of current bioinformatics workflow environments can be significantly increased by offering advanced data mining services as workflow components. Such services can support, for instance, knowledge discovery from diverse distributed data and knowledge sources (such as GO, KEGG, PubMed, and experimental databases. Specifically, cutting-edge data analysis approaches, such as semantic data mining, link discovery, and visualization, have not yet been made available to researchers investigating complex biological datasets. Results We present a new methodology, SegMine, for semantic analysis of microarray data by exploiting general biological knowledge, and a new workflow environment, Orange4WS, with integrated support for web services in which the SegMine methodology is implemented. The SegMine methodology consists of two main steps. First, the semantic subgroup discovery algorithm is used to construct elaborate rules that identify enriched gene sets. Then, a link discovery service is used for the creation and visualization of new biological hypotheses. The utility of SegMine, implemented as a set of workflows in Orange4WS, is demonstrated in two microarray data analysis applications. In the analysis of senescence in human stem cells, the use of SegMine resulted in three novel research hypotheses that could improve understanding of the underlying mechanisms of senescence and identification of candidate marker genes. Conclusions Compared to the available data analysis systems, SegMine offers improved hypothesis generation and data interpretation for bioinformatics in an easy-to-use integrated workflow environment.

  4. Age-Specific Gene Expression Profiles of Rhesus Monkey Ovaries Detected by Microarray Analysis

    Directory of Open Access Journals (Sweden)

    Hengxi Wei

    2015-01-01

    Full Text Available The biological function of human ovaries declines with age. To identify the potential molecular changes in ovarian aging, we performed genome-wide gene expression analysis by microarray of ovaries from young, middle-aged, and old rhesus monkeys. Microarray data was validated by quantitative real-time PCR. Results showed that a total of 503 (60 upregulated, 443 downregulated and 84 (downregulated genes were differentially expressed in old ovaries compared to young and middle-aged groups, respectively. No difference in gene expression was found between middle-aged and young groups. Differentially expressed genes were mainly enriched in cell and organelle, cellular and physiological process, binding, and catalytic activity. These genes were primarily associated with KEGG pathways of cell cycle, DNA replication and repair, oocyte meiosis and maturation, MAPK, TGF-beta, and p53 signaling pathway. Genes upregulated were involved in aging, defense response, oxidation reduction, and negative regulation of cellular process; genes downregulated have functions in reproduction, cell cycle, DNA and RNA process, macromolecular complex assembly, and positive regulation of macromolecule metabolic process. These findings show that monkey ovary undergoes substantial change in global transcription with age. Gene expression profiles are useful in understanding the mechanisms underlying ovarian aging and age-associated infertility in primates.

  5. cDNA Microarray Analysis of Serially Sampled Cervical Cancer Specimens From Patients Treated With Thermochemoradiotherapy

    International Nuclear Information System (INIS)

    Borkamo, Erling Dahl; Schem, Baard-Christian; Fluge, Oystein; Bruland, Ove; Dahl, Olav; Mella, Olav

    2009-01-01

    Purpose: To elucidate changes in gene expression after treatment with regional thermochemoradiotherapy in locally advanced squamous cell cervical cancer. Methods and Materials: Tru-Cut biopsy specimens were serially collected from 16 patients. Microarray gene expression levels before and 24 h after the first and second trimodality treatment sessions were compared. Pathway and network analyses were conducted by use of Ingenuity Pathways Analysis (IPA; Ingenuity Systems, Redwood City, CA). Single gene expressions were analyzed by quantitative real-time reverse transcription-polymerase chain reaction. Results: We detected 53 annotated genes that were differentially expressed after trimodality treatment. Central in the three top networks detected by IPA were interferon alfa, interferon beta, and interferon gamma receptor; nuclear factor κB; and tumor necrosis factor, respectively. These genes encode proteins that are important in regulation cell signaling, proliferation, gene expression, and immune stimulation. Biological processes over-represented among the 53 genes were fibrosis, tumorigenesis, and immune response. Conclusions: Microarrays showed minor changes in gene expression after thermochemoradiotherapy in locally advanced cervical cancer. We detected 53 differentially expressed genes, mainly involved in fibrosis, tumorigenesis, and immune response. A limitation with the use of serial biopsy specimens was low quality of ribonucleic acid from tumors that respond to highly effective therapy. Another 'key limitation' is timing of the post-treatment biopsy, because 24 h may be too late to adequately assess the impact of hyperthermia on gene expression.

  6. Statistical Analysis of Microarray Data with Replicated Spots: A Case Study with Synechococcus WH8102

    Directory of Open Access Journals (Sweden)

    E. V. Thomas

    2009-01-01

    Full Text Available Until recently microarray experiments often involved relatively few arrays with only a single representation of each gene on each array. A complete genome microarray with multiple spots per gene (spread out spatially across the array was developed in order to compare the gene expression of a marine cyanobacterium and a knockout mutant strain in a defined artificial seawater medium. Statistical methods were developed for analysis in the special situation of this case study where there is gene replication within an array and where relatively few arrays are used, which can be the case with current array technology. Due in part to the replication within an array, it was possible to detect very small changes in the levels of expression between the wild type and mutant strains. One interesting biological outcome of this experiment is the indication of the extent to which the phosphorus regulatory system of this cyanobacterium affects the expression of multiple genes beyond those strictly involved in phosphorus acquisition.

  7. A High Phosphorus Diet Affects Lipid Metabolism in Rat Liver: A DNA Microarray Analysis.

    Directory of Open Access Journals (Sweden)

    Sunwoo Chun

    Full Text Available A high phosphorus (HP diet causes disorders of renal function, bone metabolism, and vascular function. We previously demonstrated that DNA microarray analysis is an appropriate method to comprehensively evaluate the effects of a HP diet on kidney dysfunction such as calcification, fibrillization, and inflammation. We reported that type IIb sodium-dependent phosphate transporter is significantly up-regulated in this context. In the present study, we performed DNA microarray analysis to investigate the effects of a HP diet on the liver, which plays a pivotal role in energy metabolism. DNA microarray analysis was performed with total RNA isolated from the livers of rats fed a control diet (containing 0.3% phosphorus or a HP diet (containing 1.2% phosphorus. Gene Ontology analysis of differentially expressed genes (DEGs revealed that the HP diet induced down-regulation of genes involved in hepatic amino acid catabolism and lipogenesis, while genes related to fatty acid β-oxidation process were up-regulated. Although genes related to fatty acid biosynthesis were down-regulated in HP diet-fed rats, genes important for the elongation and desaturation reactions of omega-3 and -6 fatty acids were up-regulated. Concentrations of hepatic arachidonic acid and eicosapentaenoic acid were increased in HP diet-fed rats. These essential fatty acids activate peroxisome proliferator-activated receptor alpha (PPARα, a transcription factor for fatty acid β-oxidation. Evaluation of the upstream regulators of DEGs using Ingenuity Pathway Analysis indicated that PPARα was activated in the livers of HP diet-fed rats. Furthermore, the serum concentration of fibroblast growth factor 21, a hormone secreted from the liver that promotes fatty acid utilization in adipose tissue as a PPARα target gene, was higher (p = 0.054 in HP diet-fed rats than in control diet-fed rats. These data suggest that a HP diet enhances energy expenditure through the utilization of free fatty

  8. Transcriptomic responses to biotic stresses in Malus x domestica: a meta-analysis study

    OpenAIRE

    Balan, Bipin; Marra, Francesco Paolo; Caruso, Tiziano; Martinelli, Federico

    2018-01-01

    RNA-Seq analysis is a strong tool to gain insight into the molecular responses to biotic stresses in plants. The objective of this work is to identify specific and common molecular responses between different transcriptomic data related to fungi, virus and bacteria attacks in Malus x domestica. We analyzed seven transcriptomic datasets in Malus x domestica divided in responses to fungal pathogens, virus (Apple Stem Grooving Virus) and bacteria (Erwinia amylovora). Data were dissected using an...

  9. Transcriptomic analysis of the entomopathogenic nematode Heterorhabditis bacteriophora TTO1

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    Spieth John

    2009-04-01

    Full Text Available Abstract Background The entomopathogenic nematode Heterorhabditis bacteriophora and its symbiotic bacterium, Photorhabdus luminescens, are important biological control agents of insect pests. This nematode-bacterium-insect association represents an emerging tripartite model for research on mutualistic and parasitic symbioses. Elucidation of mechanisms underlying these biological processes may serve as a foundation for improving the biological control potential of the nematode-bacterium complex. This large-scale expressed sequence tag (EST analysis effort enables gene discovery and development of microsatellite markers. These ESTs will also aid in the annotation of the upcoming complete genome sequence of H. bacteriophora. Results A total of 31,485 high quality ESTs were generated from cDNA libraries of the adult H. bacteriophora TTO1 strain. Cluster analysis revealed the presence of 3,051 contigs and 7,835 singletons, representing 10,886 distinct EST sequences. About 72% of the distinct EST sequences had significant matches (E value H. bacteriophora, among which are those encoding F-box-like/WD-repeat protein theromacin, Bax inhibitor-1-like protein, and PAZ domain containing protein. Gene Ontology terms were assigned to 6,685 of the 10,886 ESTs. A total of 168 microsatellite loci were identified with primers designable for 141 loci. Conclusion A total of 10,886 distinct EST sequences were identified from adult H. bacteriophora cDNA libraries. BLAST searches revealed ESTs potentially involved in parasitism, RNA interference, defense responses, stress responses, and dauer-related processes. The putative microsatellite markers identified in H. bacteriophora ESTs will enable genetic mapping and population genetic studies. These genomic resources provide the material base necessary for genome annotation, microarray development, and in-depth gene functional analysis.

  10. [Integrating obtained knowledge from transcriptome data by a new framework for data analysis].

    Science.gov (United States)

    Konishi, Tomokazu

    2006-01-01

    Microarray analyses facilitate the investigation of quantitative information coded in the genome by measuring transcriptome, which records the decoded information from the genome. The state of a cell and differences from other states can be studied through genome information, by comparing one set of transcriptome data to other sets. Clearly, those data should be shared and compared with researchers, and the knowledge should be integrated. Unfortunately, at present data comparisons in microarray analyses are quite difficult; the accuracy as well as the reproducibility is low. The difficulties are originated from data analyses methods. Data comparison requires an intelligent framework, such as that discussed by philosopher Sir Karl R Popper. Frameworks for microarray analyses have been developed by many efforts of bioinformatitians. The frameworks currently used are being inspected and critically discussed. By checking the mathematical models that form the practical frameworks, arbitrariness such as the lack of falsifiability has been pointed out. The paradigm in this field of analyses is also criticized by disagreement with the scientific standard, and it is shown as the origin of errors in analyses. The excessive numbers of frameworks produced in an ad hoc manner has also been criticized, since the existence of so many allows researchers to select different frameworks, discussions beyond frameworks are always difficult. A new framework that uses a parametric model is introduced with an explanation of the bases of the framework and the process of testing. Additionally, differences of obtained results by these frameworks are presented using GeneChip data, in stability of log-ratio measurements and reproducibility of analyses. The possibility of artificial decoding of genome information by an extended framework is also discussed.

  11. Meta-analysis of cancer transcriptomes: A new approach to uncover molecular pathological events in different cancer tissues

    Directory of Open Access Journals (Sweden)

    Sundus Iqbal

    2014-03-01

    Full Text Available To explore secrets of metastatic cancers, individual expression of true sets of respective genes must spread across the tissue. In this study, meta-analysis for transcriptional profiles of oncogenes was carried out to hunt critical genes or networks helping in metastasizing cancers. For this, transcriptomic analysis of different cancerous tissues causing leukemia, lung, liver, spleen, colorectal, colon, breast, bladder, and kidney cancers was performed by extracting microarray expression data from online resource; Gene Expression Omnibus. A newly developed bioinformatics technique; Dynamic Impact Approach (DIA was applied for enrichment analysis of transcriptional profiles using Database for Annotation Visualization and Integrated Discovery (DAVID. Furthermore, oPOSSUM (v. 2.0 and Cytoscape (v. 2.8.2 were used for in-depth analysis of transcription factors and regulatory gene networks respectively. DAVID analysis uncovered the most significantly enriched pathways in molecular functions that were 'Ubiquitin thiolesterase activity' up regulated in blood, breast, bladder, colorectal, lung, spleen, prostrate cancer. 'Transforming growth factor beta receptor activity' was inhibited in all cancers except leukemia, colon and liver cancer. oPOSSUM further revealed highly over-represented Transcription Factors (TFs; Broad-complex_3, Broad-complex_4, and Foxd3 except for leukemia and bladder cancer. From these findings, it is possible to target genes and networks, play a crucial role in the development of cancer. In the future, these transcription factors can serve as potential candidates for the therapeutic drug targets which can impede the deadly spread.

  12. Clonal diversity analysis using SNP microarray: a new prognostic tool for chronic lymphocytic leukemia.

    Science.gov (United States)

    Zhang, Linsheng; Znoyko, Iya; Costa, Luciano J; Conlin, Laura K; Daber, Robert D; Self, Sally E; Wolff, Daynna J

    2011-12-01

    Chronic lymphocytic leukemia (CLL) is a clinically heterogeneous disease. The methods currently used for monitoring CLL and determining conditions for treatment are limited in their ability to predict disease progression, patient survival, and response to therapy. Although clonal diversity and the acquisition of new chromosomal abnormalities during the disease course (clonal evolution) have been associated with disease progression, their prognostic potential has been underappreciated because cytogenetic and fluorescence in situ hybridization (FISH) studies have a restricted ability to detect genomic abnormalities and clonal evolution. We hypothesized that whole genome analysis using high resolution single nucleotide polymorphism (SNP) microarrays would be useful to detect diversity and infer clonal evolution to offer prognostic information. In this study, we used the Infinium Omni1 BeadChip (Illumina, San Diego, CA) array for the analysis of genetic variation and percent mosaicism in 25 non-selected CLL patients to explore the prognostic value of the assessment of clonal diversity in patients with CLL. We calculated the percentage of mosaicism for each abnormality by applying a mathematical algorithm to the genotype frequency data and by manual determination using the Simulated DNA Copy Number (SiDCoN) tool, which was developed from a computer model of mosaicism. At least one genetic abnormality was identified in each case, and the SNP data was 98% concordant with FISH results. Clonal diversity, defined as the presence of two or more genetic abnormalities with differing percentages of mosaicism, was observed in 12 patients (48%), and the diversity correlated with the disease stage. Clonal diversity was present in most cases of advanced disease (Rai stages III and IV) or those with previous treatment, whereas 9 of 13 patients without detected clonal diversity were asymptomatic or clinically stable. In conclusion, SNP microarray studies with simultaneous evaluation

  13. Identification of Novel STAT6-Regulated Proteins in Mouse B Cells by Comparative Transcriptome and Proteome Analysis.

    Science.gov (United States)

    Mokada-Gopal, Lavanya; Boeser, Alexander; Lehmann, Christian H K; Drepper, Friedel; Dudziak, Diana; Warscheid, Bettina; Voehringer, David

    2017-05-01

    The transcription factor STAT6 plays a key role in mediating signaling downstream of the receptors for IL-4 and IL-13. In B cells, STAT6 is required for class switch recombination to IgE and for germinal center formation during type 2 immune responses directed against allergens or helminths. In this study, we compared the transcriptomes and proteomes of primary mouse B cells from wild-type and STAT6-deficient mice cultured for 4 d in the presence or absence of IL-4. Microarray analysis revealed that 214 mRNAs were upregulated and 149 were downregulated >3-fold by IL-4 in a STAT6-dependent manner. Across all samples, ∼5000 proteins were identified by label-free quantitative liquid chromatography/mass spectrometry. A total of 149 proteins was found to be differentially expressed >3-fold between IL-4-stimulated wild-type and STAT6 -/- B cells (75 upregulated and 74 downregulated). Comparative analysis of the proteome and transcriptome revealed that expression of these proteins was mainly regulated at the transcriptional level, which argues against a major role for posttranscriptional mechanisms that modulate the STAT6-dependent proteome. Nine proteins were selected for confirmation by flow cytometry or Western blot. We show that CD30, CD79b, SLP-76, DEC205, IL-5Rα, STAT5, and Thy1 are induced by IL-4 in a STAT6-dependent manner. In contrast, Syk and Fc receptor-like 1 were downregulated. This dataset provides a framework for further functional analysis of newly identified IL-4-regulated proteins in B cells that may contribute to germinal center formation and IgE switching in type 2 immunity. Copyright © 2017 by The American Association of Immunologists, Inc.

  14. Integrated Analysis of the Transcriptome and Metabolome of Corynebacterium glutamicum during Penicillin-Induced Glutamic Acid Production.

    Science.gov (United States)

    Hirasawa, Takashi; Saito, Masaki; Yoshikawa, Katsunori; Furusawa, Chikara; Shmizu, Hiroshi

    2018-05-01

    Corynebacterium glutamicum is known for its ability to produce glutamic acid and has been utilized for the fermentative production of various amino acids. Glutamic acid production in C. glutamicum is induced by penicillin. In this study, the transcriptome and metabolome of C. glutamicum is analyzed to understand the mechanism of penicillin-induced glutamic acid production. Transcriptomic analysis with DNA microarray revealed that expression of some glycolysis- and TCA cycle-related genes, which include those encoding the enzymes involved in conversion of glucose to 2-oxoglutaric acid, is upregulated after penicillin addition. Meanwhile, expression of some TCA cycle-related genes, encoding the enzymes for conversion of 2-oxoglutaric acid to oxaloacetic acid, and the anaplerotic reactions decreased. In addition, expression of NCgl1221 and odhI, encoding proteins involved in glutamic acid excretion and inhibition of the 2-oxoglutarate dehydrogenase, respectively, is upregulated. Functional category enrichment analysis of genes upregulated and downregulated after penicillin addition revealed that genes for signal transduction systems are enriched among upregulated genes, whereas those for energy production and carbohydrate and amino acid metabolisms are enriched among the downregulated genes. As for the metabolomic analysis using capillary electrophoresis time-of-flight mass spectrometry, the intracellular content of most metabolites of the glycolysis and the TCA cycle decreased dramatically after penicillin addition. Overall, these results indicate that the cellular metabolism and glutamic acid excretion are mainly optimized at the transcription level during penicillin-induced glutamic acid production by C. glutamicum. © 2018 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  15. Phytoremediation potential of Arabidopsis with reference to acrylamide and microarray analysis of acrylamide-response genes.

    Science.gov (United States)

    Gao, Jian-Jie; Peng, Ri-He; Zhu, Bo; Wang, Bo; Wang, Li-Juan; Xu, Jing; Sun, Miao; Yao, Quan-Hong

    2015-10-01

    Acrylamide (ACR) is a widely used industrial chemical. However, it is a dangerous compound because it showed neurotoxic effects in humans and act as reproductive toxicant and carcinogen in many animal species. In the environment, acrylamide has high soil mobility and may travel via groundwater. Phytoremediation is an effective method to remove the environmental pollutants, but the mechanism of plant response to acrylamide remains unknown. With the purpose of assessing remediation potentials of plants for acrylamide, we have examined acrylamide uptake by the model plant Arabidopsis grown on contaminated substrates with high performance liquid chromatography (HPLC) analysis. The result revealed that acrylamide could be absorbed and degraded by Arabidopsis. Further microarray analysis showed that 527 transcripts were up-regulated within 2-days under acrylamide exposure condition. We have found many potential acrylamide-induced genes playing a major role in plant metabolism and phytoremediation. Copyright © 2015 Elsevier Inc. All rights reserved.

  16. Comparative Transcriptome Analysis of Two Ascophyllum nodosum Extract Biostimulants: Same Seaweed but Different.

    Science.gov (United States)

    Goñi, Oscar; Fort, Antoine; Quille, Patrick; McKeown, Peter C; Spillane, Charles; O'Connell, Shane

    2016-04-13

    Biostimulants for crop management are gaining increased attention with continued demand for increased crop yields. Seaweed extracts represent one category of biostimulant, with Ascophyllum nodosum extracts (ANE) widely used for yield and quality enhancement. This study investigated how the composition of two ANE biostimulants (ANE A and ANE B) affects plant mRNA transcriptomes, using the model plant Arabidopsis thaliana. Using Affymetrix Ath1 microarrays, significant heterogeneity was detected between the ANE biostimulants in terms of their impacts on the mRNA transcriptome of A. thaliana plants, which accumulated significantly more biomass than untreated controls. Genes dysregulated by the ANE biostimulants are associated with a wide array of predicted biological processes, molecular functions, and subcellular distributions. ANE A dysregulated 4.47% of the transcriptome, whereas ANE B dysregulated 0.87%. The compositions of both ANEs were significantly different, with a 4-fold difference in polyphenol levels, the largest observed. The standardization of the composition of ANE biostimulants represents a challenge for providing consistent effects on plant gene expression and biostimulation.

  17. Adaptation of a Bioinformatics Microarray Analysis Workflow for a Toxicogenomic Study in Rainbow Trout.

    Directory of Open Access Journals (Sweden)

    Sophie Depiereux

    Full Text Available Sex steroids play a key role in triggering sex differentiation in fish, the use of exogenous hormone treatment leading to partial or complete sex reversal. This phenomenon has attracted attention since the discovery that even low environmental doses of exogenous steroids can adversely affect gonad morphology (ovotestis development and induce reproductive failure. Modern genomic-based technologies have enhanced opportunities to find out mechanisms of actions (MOA and identify biomarkers related to the toxic action of a compound. However, high throughput data interpretation relies on statistical analysis, species genomic resources, and bioinformatics tools. The goals of this study are to improve the knowledge of feminisation in fish, by the analysis of molecular responses in the gonads of rainbow trout fry after chronic exposure to several doses (0.01, 0.1, 1 and 10 μg/L of ethynylestradiol (EE2 and to offer target genes as potential biomarkers of ovotestis development. We successfully adapted a bioinformatics microarray analysis workflow elaborated on human data to a toxicogenomic study using rainbow trout, a fish species lacking accurate functional annotation and genomic resources. The workflow allowed to obtain lists of genes supposed to be enriched in true positive differentially expressed genes (DEGs, which were subjected to over-representation analysis methods (ORA. Several pathways and ontologies, mostly related to cell division and metabolism, sexual reproduction and steroid production, were found significantly enriched in our analyses. Moreover, two sets of potential ovotestis biomarkers were selected using several criteria. The first group displayed specific potential biomarkers belonging to pathways/ontologies highlighted in the experiment. Among them, the early ovarian differentiation gene foxl2a was overexpressed. The second group, which was highly sensitive but not specific, included the DEGs presenting the highest fold change and

  18. Porous Silicon Antibody Microarrays for Quantitative Analysis: Measurement of Free and Total PSA in Clinical Plasma Samples

    Science.gov (United States)

    Tojo, Axel; Malm, Johan; Marko-Varga, György; Lilja, Hans; Laurell, Thomas

    2014-01-01

    The antibody microarrays have become widespread, but their use for quantitative analyses in clinical samples has not yet been established. We investigated an immunoassay based on nanoporous silicon antibody microarrays for quantification of total prostate-specific-antigen (PSA) in 80 clinical plasma samples, and provide quantitative data from a duplex microarray assay that simultaneously quantifies free and total PSA in plasma. To further develop the assay the porous silicon chips was placed into a standard 96-well microtiter plate for higher throughput analysis. The samples analyzed by this quantitative microarray were 80 plasma samples obtained from men undergoing clinical PSA testing (dynamic range: 0.14-44ng/ml, LOD: 0.14ng/ml). The second dataset, measuring free PSA (dynamic range: 0.40-74.9ng/ml, LOD: 0.47ng/ml) and total PSA (dynamic range: 0.87-295ng/ml, LOD: 0.76ng/ml), was also obtained from the clinical routine. The reference for the quantification was a commercially available assay, the ProStatus PSA Free/Total DELFIA. In an analysis of 80 plasma samples the microarray platform performs well across the range of total PSA levels. This assay might have the potential to substitute for the large-scale microtiter plate format in diagnostic applications. The duplex assay paves the way for a future quantitative multiplex assay, which analyses several prostate cancer biomarkers simultaneously. PMID:22921878

  19. Mercury-induced hepatotoxicity in zebrafish: in vivo mechanistic insights from transcriptome analysis, phenotype anchoring and targeted gene expression validation

    Directory of Open Access Journals (Sweden)

    Mathavan Sinnakaruppan

    2010-03-01

    Full Text Available Abstract Background Mercury is a prominent environmental contaminant that causes detrimental effects to human health. Although the liver has been known to be a main target organ, there is limited information on in vivo molecular mechanism of mercury-induced toxicity in the liver. By using transcriptome analysis, phenotypic anchoring and validation of targeted gene expression in zebrafish, mercury-induced hepatotoxicity was investigated and a number of perturbed cellular processes were identified and compared with those captured in the in vitro human cell line studies. Results Hepato-transcriptome analysis of mercury-exposed zebrafish revealed that the earliest deregulated genes were associated with electron transport chain, mitochondrial fatty acid beta-oxidation, nuclear receptor signaling and apoptotic pathway, followed by complement system and proteasome pathway, and thereafter DNA damage, hypoxia, Wnt signaling, fatty acid synthesis, gluconeogenesis, cell cycle and motility. Comparative meta-analysis of microarray data between zebrafish liver and human HepG2 cells exposed to mercury identified some common toxicological effects of mercury-induced hepatotoxicity in both models. Histological analyses of liver from mercury-exposed fish revealed morphological changes of liver parenchyma, decreased nucleated cell count, increased lipid vesicles, glycogen and apoptotic bodies, thus providing phenotypic evidence for anchoring of the transcriptome analysis. Validation of targeted gene expression confirmed deregulated gene-pathways from enrichment analysis. Some of these genes responding to low concentrations of mercury may serve as toxicogenomic-based markers for detection and health risk assessment of environmental mercury contaminations. Conclusion Mercury-induced hepatotoxicity was triggered by oxidative stresses, intrinsic apoptotic pathway, deregulation of nuclear receptor and kinase activities including Gsk3 that deregulates Wnt signaling

  20. Identification of Putative Ortholog Gene Blocks Involved in Gestant and Lactating Mammary Gland Development: A Rodent Cross-Species Microarray Transcriptomics Approach

    Science.gov (United States)

    Rodríguez-Cruz, Maricela; Coral-Vázquez, Ramón M.; Hernández-Stengele, Gabriel; Sánchez, Raúl; Salazar, Emmanuel; Sanchez-Muñoz, Fausto; Encarnación-Guevara, Sergio; Ramírez-Salcedo, Jorge

    2013-01-01

    The mammary gland (MG) undergoes functional and metabolic changes during the transition from pregnancy to lactation, possibly by regulation of conserved genes. The objective was to elucidate orthologous genes, chromosome clusters and putative conserved transcriptional modules during MG development. We analyzed expression of 22,000 transcripts using murine microarrays and RNA samples of MG from virgin, pregnant, and lactating rats by cross-species hybridization. We identified 521 transcripts differentially expressed; upregulated in early (78%) and midpregnancy (89%) and early lactation (64%), but downregulated in mid-lactation (61%). Putative orthologous genes were identified. We mapped the altered genes to orthologous chromosomal locations in human and mouse. Eighteen sets of conserved genes associated with key cellular functions were revealed and conserved transcription factor binding site search entailed possible coregulation among all eight block sets of genes. This study demonstrates that the use of heterologous array hybridization for screening of orthologous gene expression from rat revealed sets of conserved genes arranged in chromosomal order implicated in signaling pathways and functional ontology. Results demonstrate the utilization power of comparative genomics and prove the feasibility of using rodent microarrays to identification of putative coexpressed orthologous genes involved in the control of human mammary gland development. PMID:24288657

  1. Microarray-based analysis of differential gene expression between infective and noninfective larvae of Strongyloides stercoralis.

    Directory of Open Access Journals (Sweden)

    Roshan Ramanathan

    2011-05-01

    Full Text Available Differences between noninfective first-stage (L1 and infective third-stage (L3i larvae of parasitic nematode Strongyloides stercoralis at the molecular level are relatively uncharacterized. DNA microarrays were developed and utilized for this purpose.Oligonucleotide hybridization probes for the array were designed to bind 3,571 putative mRNA transcripts predicted by analysis of 11,335 expressed sequence tags (ESTs obtained as part of the Nematode EST project. RNA obtained from S. stercoralis L3i and L1 was co-hybridized to each array after labeling the individual samples with different fluorescent tags. Bioinformatic predictions of gene function were developed using a novel cDNA Annotation System software. We identified 935 differentially expressed genes (469 L3i-biased; 466 L1-biased having two-fold expression differences or greater and microarray signals with a p value<0.01. Based on a functional analysis, L1 larvae have a larger number of genes putatively involved in transcription (p = 0.004, and L3i larvae have biased expression of putative heat shock proteins (such as hsp-90. Genes with products known to be immunoreactive in S. stercoralis-infected humans (such as SsIR and NIE had L3i biased expression. Abundantly expressed L3i contigs of interest included S. stercoralis orthologs of cytochrome oxidase ucr 2.1 and hsp-90, which may be potential chemotherapeutic targets. The S. stercoralis ortholog of fatty acid and retinol binding protein-1, successfully used in a vaccine against Ancylostoma ceylanicum, was identified among the 25 most highly expressed L3i genes. The sperm-containing glycoprotein domain, utilized in a vaccine against the nematode Cooperia punctata, was exclusively found in L3i biased genes and may be a valuable S. stercoralis target of interest.A new DNA microarray tool for the examination of S. stercoralis biology has been developed and provides new and valuable insights regarding differences between infective and

  2. Microarray analysis identifies a common set of cellular genes modulated by different HCV replicon clones

    Directory of Open Access Journals (Sweden)

    Gerosolimo Germano

    2008-06-01

    Full Text Available Abstract Background Hepatitis C virus (HCV RNA synthesis and protein expression affect cell homeostasis by modulation of gene expression. The impact of HCV replication on global cell transcription has not been fully evaluated. Thus, we analysed the expression profiles of different clones of human hepatoma-derived Huh-7 cells carrying a self-replicating HCV RNA which express all viral proteins (HCV replicon system. Results First, we compared the expression profile of HCV replicon clone 21-5 with both the Huh-7 parental cells and the 21-5 cured (21-5c cells. In these latter, the HCV RNA has been eliminated by IFN-α treatment. To confirm data, we also analyzed microarray results from both the 21-5 and two other HCV replicon clones, 22-6 and 21-7, compared to the Huh-7 cells. The study was carried out by using the Applied Biosystems (AB Human Genome Survey Microarray v1.0 which provides 31,700 probes that correspond to 27,868 human genes. Microarray analysis revealed a specific transcriptional program induced by HCV in replicon cells respect to both IFN-α-cured and Huh-7 cells. From the original datasets of differentially expressed genes, we selected by Venn diagrams a final list of 38 genes modulated by HCV in all clones. Most of the 38 genes have never been described before and showed high fold-change associated with significant p-value, strongly supporting data reliability. Classification of the 38 genes by Panther System identified functional categories that were significantly enriched in this gene set, such as histones and ribosomal proteins as well as extracellular matrix and intracellular protein traffic. The dataset also included new genes involved in lipid metabolism, extracellular matrix and cytoskeletal network, which may be critical for HCV replication and pathogenesis. Conclusion Our data provide a comprehensive analysis of alterations in gene expression induced by HCV replication and reveal modulation of new genes potentially useful

  3. Analysis of Saprolegnia parasitica Transcriptome following Treatment with Copper Sulfate.

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    Kun Hu

    Full Text Available Massive infection caused by oomycete fungus Saprolegnia parasitica is detrimental to freshwater fish. Recently, we showed that copper sulfate demonstrated good efficacy for controlling S. parasitica infection in grass carp. In this study, we investigated the mechanism of inhibition of S. parasitica growth by copper sulfate by analyzing the transcriptome of copper sulfate-treated S. parasitica. To examine the mechanism of copper sulfate inhibiting S. parasitica, we utilized RNA-seq technology to compare differential gene expression in S. parasitica treated with or without copper sulfate.The total mapped rates of the reads with the reference genome were 90.50% in the control group and 73.50% in the experimental group. In the control group, annotated splice junctions, partial novel splice junctions and complete novel splice junctions were about 83%, 3% and 14%, respectively. In the treatment group, the corresponding values were about 75%, 6% and 19%. Following copper sulfate treatment, a total 310 genes were markedly upregulated and 556 genes were markedly downregulated in S. parasitica. Material metabolism related GO terms including cofactor binding (33 genes, 1,3-beta-D-glucan synthase complex (4 genes, carboxylic acid metabolic process (40 genes were the most significantly enriched. KEGG pathway analysis also determined that the metabolism-related biological pathways were significantly enriched, including the metabolic pathways (98 genes, biosynthesis of secondary metabolites pathways (42 genes, fatty acid metabolism (13 genes, phenylalanine metabolism (7 genes, starch and sucrose metabolism pathway (12 genes. The qRT-PCR results were largely consistent with the RNA-Seq results.Our results indicate that copper sulfate inhibits S. parasitica growth by affecting multiple biological functions, including protein synthesis, energy biogenesis, and metabolism.

  4. Microarray Analysis on Gene Regulation by Estrogen, Progesterone and Tamoxifen in Human Endometrial Stromal Cells

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    Chun-E Ren

    2015-03-01

    Full Text Available Epithelial stromal cells represent a major cellular component of human uterine endometrium that is subject to tight hormonal regulation. Through cell-cell contacts and/or paracrine mechanisms, stromal cells play a significant role in the malignant transformation of epithelial cells. We isolated stromal cells from normal human endometrium and investigated the morphological and transcriptional changes induced by estrogen, progesterone and tamoxifen. We demonstrated that stromal cells express appreciable levels of estrogen and progesterone receptors and undergo different morphological changes upon hormonal stimulation. Microarray analysis indicated that both estrogen and progesterone induced dramatic alterations in a variety of genes associated with cell structure, transcription, cell cycle, and signaling. However, divergent patterns of changes, and in some genes opposite effects, were observed for the two hormones. A large number of genes are identified as novel targets for hormonal regulation. These hormone-responsive genes may be involved in normal uterine function and the development of endometrial malignancies.

  5. Antimicrobial resistance determinant microarray for analysis of multi-drug resistant isolates

    Science.gov (United States)

    Taitt, Chris Rowe; Leski, Tomasz; Stenger, David; Vora, Gary J.; House, Brent; Nicklasson, Matilda; Pimentel, Guillermo; Zurawski, Daniel V.; Kirkup, Benjamin C.; Craft, David; Waterman, Paige E.; Lesho, Emil P.; Bangurae, Umaru; Ansumana, Rashid

    2012-06-01

    The prevalence of multidrug-resistant infections in personnel wounded in Iraq and Afghanistan has made it challenging for physicians to choose effective therapeutics in a timely fashion. To address the challenge of identifying the potential for drug resistance, we have developed the Antimicrobial Resistance Determinant Microarray (ARDM) to provide DNAbased analysis for over 250 resistance genes covering 12 classes of antibiotics. Over 70 drug-resistant bacteria from different geographic regions have been analyzed on ARDM, with significant differences in patterns of resistance identified: genes for resistance to sulfonamides, trimethoprim, chloramphenicol, rifampin, and macrolide-lincosamidesulfonamide drugs were more frequently identified in isolates from sources in Iraq/Afghanistan. Of particular concern was the presence of genes responsible for resistance to many of the last-resort antibiotics used to treat war traumaassociated infections.

  6. PAX3 gene deletion detected by microarray analysis in a girl with hearing loss.

    Science.gov (United States)

    Drozniewska, Malgorzata; Haus, Olga

    2014-01-01

    Deletions of the PAX3 gene have been rarely reported in the literature. Mutations of this gene are a common cause of Waardenburg syndrome type 1 and 3. We report a 16 year old female presenting hearing loss and normal intellectual development, without major features of Waardenburg syndrome type 1, and without family history of the syndrome. Her phenotype, however, overlaps with features of craniofacial-deafness-hand syndrome. Microarray analysis showed ~862 kb de novo deletion at 2q36.1 including PAX3. The above findings suggest that the rearrangement found in our patient appeared de novo and with high probability is a cause of her phenotype.

  7. A new locally weighted K-means for cancer-aided microarray data analysis.

    Science.gov (United States)

    Iam-On, Natthakan; Boongoen, Tossapon

    2012-11-01

    Cancer has been identified as the leading cause of death. It is predicted that around 20-26 million people will be diagnosed with cancer by 2020. With this alarming rate, there is an urgent need for a more effective methodology to understand, prevent and cure cancer. Microarray technology provides a useful basis of achieving this goal, with cluster analysis of gene expression data leading to the discrimination of patients, identification of possible tumor subtypes and individualized treatment. Amongst clustering techniques, k-means is normally chosen for its simplicity and efficiency. However, it does not account for the different importance of data attributes. This paper presents a new locally weighted extension of k-means, which has proven more accurate across many published datasets than the original and other extensions found in the literature.

  8. Gene expression microarray analysis encompassing metamorphosis and the onset of calcification in the scleractinian coral Montastraea faveolata.

    Science.gov (United States)

    Reyes-Bermudez, Alejandro; Desalvo, Michael K; Voolstra, Christian R; Sunagawa, Shinichi; Szmant, Alina M; Iglesias-Prieto, Roberto; Medina, Mónica

    2009-01-01

    Similar to many marine invertebrates, scleractinian corals experience a dramatic morphological transformation, as well as a habitat switch, upon settlement and metamorphosis. At this time, planula larvae transform from non-calcifying, demersal, motile organisms into sessile, calcifying, benthic juvenile polyps. We performed gene expression microarray analyses between planulae, aposymbiotic primary polyps, and symbiotic adult tissue to elucidate the molecular mechanisms underlying coral metamorphosis and early stages of calcification in the Robust/Short clade scleractinian coral Montastraea faveolata. Among the annotated genes, the most abundant upregulated transcripts in the planula stage are involved in protein synthesis, chromatin assembly and mitochondrial metabolism; the polyp stage, morphogenesis, protein catabolism and organic matrix synthesis; and the adult stage, sexual reproduction, stress response and symbiosis. We also present evidence showing that the planula and adult transcriptomes are more similar to each other than to the polyp transcriptome. Our results also point to a large number of uncharacterized adult coral-specific genes likely involved in coral-specific functions such as symbiosis and calcification.

  9. Microarray analysis of kiwifruit (Actinidia chinensis bark following challenge by the sucking insect Hemiberlesia lataniae (Hemiptera: Diaspididae

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    M. Garry Hill

    2016-03-01

    Full Text Available Both commercial and experimental genotypes of kiwifruit (Actinidia spp. exhibit large differences in response to insect pests. An understanding of the vine's physiological response to insect feeding and its genetic basis will be important in assisting the development of varieties with acceptable levels of pest resistance. This experiment describes transcriptome changes observed in the bark of kiwifruit 2 and 7 days after the commencement of feeding by the armored scale insect pest, Hemiberlesia lataniae. Using a cDNA microarray consisting of 17,512 unigenes, we measured transcriptome changes and analyzed these into functional ontology categories using MapMan. Results are available in the GEO database GSE73922 and are described fully in Ref. Hill et al. (2015 [1]. After 7 days, transcripts associated with photosynthesis were down-regulated and secondary metabolism was up-regulated. Differential expression of transcripts associated with stress response was consistent with a defense response involving both effector and herbivore-triggered immunities, with predominant involvement of the salicylic acid phytohormonal pathway. This hypothesis was supported by the results of two laboratory experiments. The methods described here could be further adapted and applied to the study of plant responses to a wide range of sessile sucking pests.

  10. Analysis of human HPRT- deletion mutants by the microarray-CGH (comparative genomic hybridization)

    International Nuclear Information System (INIS)

    Kodaira, M.; Sasaki, K.; Tagawa, H.; Omine, H.; Kushiro, J.; Takahashi, N.; Katayama, H.

    2003-01-01

    We are trying to evaluate genetic effects of radiation on human using mutation frequency as an indicator. For the efficient detection of mutations, it is important to understand the mechanism and the characteristics of radiation-induced mutations. We have started the analysis of hypoxanthine-guanine phosphoribosyl transferase (HPRT) mutants induced by X-ray in order to clarify the deletion size and the mutation-distribution. We analyzed 39 human X-ray induced HPRT-deletion mutants by using the microarray-CGH. The array for this analysis contains 57 BAC clones covering as much as possible of the 4Mb of the 5' side and 10Mb of the 3' side of the HPRT gene based on the NCBI genome database. DNA from parent strain and each HPRT-mutant strain are labeled with Cy5 and Cy3 respectively, and were mixed and hybridized on the array. Fluorescent intensity ratio of the obtained spots was analyzed using software we developed to identify clones corresponding to the deletion region. The deletion in these strains ranged up to 3.5 Mb on the 5' side and 6 Mb on the 3' side of the HPRT gene. Deletions in 13 strains ended around BAC clones located at about 3 Mb on the 5' side. On the 3' side, deletions extended up to the specific clones located at 1.5 Mb in 11 strains. The mutations seem to be complex on the 3' end of deletion; some accompanied duplications with deletions and others could not be explained by one mutation event. We need to confirm these results, taking into account the experimental reproducibility and the accuracy of the published genetic map. The results of the research using the microarray-CGH help us to search the regions where deletions are easily induced and to identify the factors affecting the range of deletions

  11. Microarray and cDNA sequence analysis of transcription during nerve-dependent limb regeneration

    Directory of Open Access Journals (Sweden)

    Bryant Susan V

    2009-01-01

    Full Text Available Abstract Background Microarray analysis and 454 cDNA sequencing were used to investigate a centuries-old problem in regenerative biology: the basis of nerve-dependent limb regeneration in salamanders. Innervated (NR and denervated (DL forelimbs of Mexican axolotls were amputated and transcripts were sampled after 0, 5, and 14 days of regeneration. Results Considerable similarity was observed between NR and DL transcriptional programs at 5 and 14 days post amputation (dpa. Genes with extracellular functions that are critical to wound healing were upregulated while muscle-specific genes were downregulated. Thus, many processes that are regulated during early limb regeneration do not depend upon nerve-derived factors. The majority of the transcriptional differences between NR and DL limbs were correlated with blastema formation; cell numbers increased in NR limbs after 5 dpa and this yielded distinct transcriptional signatures of cell proliferation in NR limbs at 14 dpa. These transcriptional signatures were not observed in DL limbs. Instead, gene expression changes within DL limbs suggest more diverse and protracted wound-healing responses. 454 cDNA sequencing complemented the microarray analysis by providing deeper sampling of transcriptional programs and associated biological processes. Assembly of new 454 cDNA sequences with existing expressed sequence tag (EST contigs from the Ambystoma EST database more than doubled (3935 to 9411 the number of non-redundant human-A. mexicanum orthologous sequences. Conclusion Many new candidate gene sequences were discovered for the first time and these will greatly enable future studies of wound healing, epigenetics, genome stability, and nerve-dependent blastema formation and outgrowth using the axolotl model.

  12. Microarray meta-analysis to explore abiotic stress-specific gene expression patterns in Arabidopsis.

    Science.gov (United States)

    Shen, Po-Chih; Hour, Ai-Ling; Liu, Li-Yu Daisy

    2017-12-01

    Abiotic stresses are the major limiting factors that affect plant growth, development, yield and final quality. Deciphering the underlying mechanisms of plants' adaptations to stresses using few datasets might overlook the different aspects of stress tolerance in plants, which might be simultaneously and consequently operated in the system. Fortunately, the accumulated microarray expression data offer an opportunity to infer abiotic stress-specific gene expression patterns through meta-analysis. In this study, we propose to combine microarray gene expression data under control, cold, drought, heat, and salt conditions and determined modules (gene sets) of genes highly associated with each other according to the observed expression data. By analyzing the expression variations of the Eigen genes from different conditions, we had identified two, three, and five gene modules as cold-, heat-, and salt-specific modules, respectively. Most of the cold- or heat-specific modules were differentially expressed to a particular degree in shoot samples, while most of the salt-specific modules were differentially expressed to a particular degree in root samples. A gene ontology (GO) analysis on the stress-specific modules suggested that the gene modules exclusively enriched stress-related GO terms and that different genes under the same GO terms may be alternatively disturbed in different conditions. The gene regulatory events for two genes, DREB1A and DEAR1, in the cold-specific gene module had also been validated, as evidenced through the literature search. Our protocols study the specificity of the gene modules that were specifically activated under a particular type of abiotic stress. The biplot can also assist to visualize the stress-specific gene modules. In conclusion, our approach has the potential to further elucidate mechanisms in plants and beneficial for future experiments design under different abiotic stresses.

  13. Transcriptome and genome size analysis of the venus flytrap

    DEFF Research Database (Denmark)

    Jensen, Michael Krogh; Vogt, Josef Korbinian; Bressendorff, Simon

    2015-01-01

    . muscipula flowers and traps. Using the Oases transcriptome assembler 79,165,657 quality trimmed reads were assembled into 80,806 cDNA contigs, with an average length of 679 bp and an N50 length of 1,051 bp. A total of 17,047 unique proteins were identified, and assigned to Gene Ontology (GO) and classified...

  14. Illumina-based de novo transcriptome sequencing and analysis

    Indian Academy of Sciences (India)

    In the present study, we used Illumina HiSeq technology to perform de novo assembly of heart and musk gland transcriptomes from the Chinese forest musk deer. A total of 239,383 transcripts and 176,450 unigenes were obtained, of which 37,329 unigenes were matched to known sequences in the NCBI nonredundant ...

  15. Combined analysis of DNA methylome and transcriptome reveal novel candidate genes with susceptibility to bovine Staphylococcus aureus subclinical mastitis.

    Science.gov (United States)

    Song, Minyan; He, Yanghua; Zhou, Huangkai; Zhang, Yi; Li, Xizhi; Yu, Ying

    2016-07-14

    Subclinical mastitis is a widely spread disease of lactating cows. Its major pathogen is Staphylococcus aureus (S. aureus). In this study, we performed genome-wide integrative analysis of DNA methylation and transcriptional expression to identify candidate genes and pathways relevant to bovine S. aureus subclinical mastitis. The genome-scale DNA methylation profiles of peripheral blood lymphocytes in cows with S. aureus subclinical mastitis (SA group) and healthy controls (CK) were generated by methylated DNA immunoprecipitation combined with microarrays. We identified 1078 differentially methylated genes in SA cows compared with the controls. By integrating DNA methylation and transcriptome data, 58 differentially methylated genes were shared with differently expressed genes, in which 20.7% distinctly hypermethylated genes showed down-regulated expression in SA versus CK, whereas 14.3% dramatically hypomethylated genes showed up-regulated expression. Integrated pathway analysis suggested that these genes were related to inflammation, ErbB signalling pathway and mismatch repair. Further functional analysis revealed that three genes, NRG1, MST1 and NAT9, were strongly correlated with the progression of S. aureus subclinical mastitis and could be used as powerful biomarkers for the improvement of bovine mastitis resistance. Our studies lay the groundwork for epigenetic modification and mechanistic studies on susceptibility of bovine mastitis.

  16. Identification of cytokinin-responsive genes using microarray meta-analysis and RNA-Seq in Arabidopsis.

    Science.gov (United States)

    Bhargava, Apurva; Clabaugh, Ivory; To, Jenn P; Maxwell, Bridey B; Chiang, Yi-Hsuan; Schaller, G Eric; Loraine, Ann; Kieber, Joseph J

    2013-05-01

    Cytokinins are N(6)-substituted adenine derivatives that play diverse roles in plant growth and development. We sought to define a robust set of genes regulated by cytokinin as well as to query the response of genes not represented on microarrays. To this end, we performed a meta-analysis of microarray data from a variety of cytokinin-treated samples and used RNA-seq to examine cytokinin-regulated gene expression in Arabidopsis (Arabidopsis thaliana). Microarray meta-analysis using 13 microarray experiments combined with empirically defined filtering criteria identified a set of 226 genes differentially regulated by cytokinin, a subset of which has previously been validated by other methods. RNA-seq validated about 73% of the up-regulated genes identified by this meta-analysis. In silico promoter analysis indicated an overrepresentation of type-B Arabidopsis response regulator binding elements, consistent with the role of type-B Arabidopsis response regulators as primary mediators of cytokinin-responsive gene expression. RNA-seq analysis identified 73 cytokinin-regulated genes that were not represented on the ATH1 microarray. Representative genes were verified using quantitative reverse transcription-polymerase chain reaction and NanoString analysis. Analysis of the genes identified reveals a substantial effect of cytokinin on genes encoding proteins involved in secondary metabolism, particularly those acting in flavonoid and phenylpropanoid biosynthesis, as well as in the regulation of redox state of the cell, particularly a set of glutaredoxin genes. Novel splicing events were found in members of some gene families that are known to play a role in cytokinin signaling or metabolism. The genes identified in this analysis represent a robust set of cytokinin-responsive genes that are useful in the analysis of cytokinin function in plants.

  17. Analysis of gene expression in resynthesized Brassica napus Allopolyploids using arabidopsis 70mer oligo microarrays.

    Directory of Open Access Journals (Sweden)

    Robert T Gaeta

    . Furthermore, our microarray analysis did not provide strong evidence that homoeologous rearrangements were a determinant of genome-wide nonadditive gene expression. In light of the inherent limitations of the Arabidopsis microarray to measure gene expression in polyploid Brassicas, further studies are warranted.

  18. Transcriptomic and bioinformatics analysis of the early time-course of the response to prostaglandin F2 alpha in the bovine corpus luteum

    Directory of Open Access Journals (Sweden)

    Heather Talbott

    2017-10-01

    Full Text Available RNA expression analysis was performed on the corpus luteum tissue at five time points after prostaglandin F2 alpha treatment of midcycle cows using an Affymetrix Bovine Gene v1 Array. The normalized linear microarray data was uploaded to the NCBI GEO repository (GSE94069. Subsequent statistical analysis determined differentially expressed transcripts ± 1.5-fold change from saline control with P ≤ 0.05. Gene ontology of differentially expressed transcripts was annotated by DAVID and Panther. Physiological characteristics of the study animals are presented in a figure. Bioinformatic analysis by Ingenuity Pathway Analysis was curated, compiled, and presented in tables. A dataset comparison with similar microarray analyses was performed and bioinformatics analysis by Ingenuity Pathway Analysis, DAVID, Panther, and String of differentially expressed genes from each dataset as well as the differentially expressed genes common to all three datasets were curated, compiled, and presented in tables. Finally, a table comparing four bioinformatics tools’ predictions of functions associated with genes common to all three datasets is presented. These data have been further analyzed and interpreted in the companion article “Early transcriptome responses of the bovine mid-cycle corpus luteum to prostaglandin F2 alpha includes cytokine signaling” [1].

  19. Integrated analysis of whole genome and transcriptome sequencing reveals diverse transcriptomic aberrations driven by somatic genomic changes in liver cancers.

    Directory of Open Access Journals (Sweden)

    Yuichi Shiraishi

    Full Text Available Recent studies applying high-throughput sequencing technologies have identified several recurrently mutated genes and pathways in multiple cancer genomes. However, transcriptional consequences from these genomic alterations in cancer genome remain unclear. In this study, we performed integrated and comparative analyses of whole genomes and transcriptomes of 22 hepatitis B virus (HBV-related hepatocellular carcinomas (HCCs and their matched controls. Comparison of whole genome sequence (WGS and RNA-Seq revealed much evidence that various types of genomic mutations triggered diverse transcriptional changes. Not only splice-site mutations, but also silent mutations in coding regions, deep intronic mutations and structural changes caused splicing aberrations. HBV integrations generated diverse patterns of virus-human fusion transcripts depending on affected gene, such as TERT, CDK15, FN1 and MLL4. Structural variations could drive over-expression of genes such as WNT ligands, with/without creating gene fusions. Furthermore, by taking account of genomic mutations causing transcriptional aberrations, we could improve the sensitivity of deleterious mutation detection in known cancer driver genes (TP53, AXIN1, ARID2, RPS6KA3, and identified recurrent disruptions in putative cancer driver genes such as HNF4A, CPS1, TSC1 and THRAP3 in HCCs. These findings indicate genomic alterations in cancer genome have diverse transcriptomic effects, and integrated analysis of WGS and RNA-Seq can facilitate the interpretation of a large number of genomic alterations detected in cancer genome.

  20. Global pathway analysis using DNA microarrays in skeletal muscle of women with polycystic ovary syndrome

    DEFF Research Database (Denmark)

    Skov, Vibe

    2007-01-01

    (study 1), to investigate whether pioglitazone therapy could reverse abnormalities in the transcriptional profile of muscle associated with insulin resistance in skeletal muscle of obese PCOS patients (study 2), and to develop a microarray platform for global gene expression profiling (study 3). In study...... comparable to other commercial and custom made microarrays and is a cost-effective alternative especially in larger epidemiological studies....

  1. Multiplexed Analysis of Serum Breast and Ovarian Cancer Markers by Means of Suspension Bead-quantum Dot Microarrays

    Science.gov (United States)

    Brazhnik, Kristina; Sokolova, Zinaida; Baryshnikova, Maria; Bilan, Regina; Nabiev, Igor; Sukhanova, Alyona

    Multiplexed analysis of cancer markers is crucial for early tumor diagnosis and screening. We have designed lab-on-a-bead microarray for quantitative detection of three breast cancer markers in human serum. Quantum dots were used as bead-bound fluorescent tags for identifying each marker by means of flow cytometry. Antigen-specific beads reliably detected CA 15-3, CEA, and CA 125 in serum samples, providing clear discrimination between the samples with respect to the antigen levels. The novel microarray is advantageous over the routine single-analyte ones due to the simultaneous detection of various markers. Therefore the developed microarray is a promising tool for serum tumor marker profiling.

  2. From microarray to biology: an integrated experimental, statistical and in silico analysis of how the extracellular matrix modulates the phenotype of cancer cells

    OpenAIRE

    Centola Michael B; Dozmorov Igor; Buethe David D; Saban Ricardo; Hauser Paul J; Kyker Kimberly D; Dozmorov Mikhail G; Culkin Daniel J; Hurst Robert E

    2008-01-01

    Abstract A statistically robust and biologically-based approach for analysis of microarray data is described that integrates independent biological knowledge and data with a global F-test for finding genes of interest that minimizes the need for replicates when used for hypothesis generation. First, each microarray is normalized to its noise level around zero. The microarray dataset is then globally adjusted by robust linear regression. Second, genes of interest that capture significant respo...

  3. Potential physiological effects of pharmaceutical compounds in Atlantic salmon (Salmo salar) implied by transcriptomic analysis.

    Science.gov (United States)

    Hampel, Miriam; Alonso, Esteban; Aparicio, Irene; Bron, James E; Santos, Juan Luis; Taggart, John B; Leaver, Michael J

    2010-05-01

    Pharmaceuticals are emerging pollutants widely used in everyday urban activities which can be detected in surface, ground, and drinking waters. Their presence is derived from consumption of medicines, disposal of expired medications, release of treated and untreated urban effluents, and from the pharmaceutical industry. Their growing use has become an alarming environmental problem which potentially will become dangerous in the future. However, there is still a lack of knowledge about long-term effects in non-target organisms as well as for human health. Toxicity testing has indicated a relatively low acute toxicity to fish species, but no information is available on possible sublethal effects. This study provides data on the physiological pathways involved in the exposure of Atlantic salmon as representative test species to three pharmaceutical compounds found in ground, surface, and drinking waters based on the evaluation of the xenobiotic-induced impairment resulting in the activation and silencing of specific genes. Individuals of Atlantic salmon (Salmo salar) parr were exposed during 5 days to environmentally relevant concentrations of three representative pharmaceutical compounds with high consumption rates: the analgesic acetaminophen (54.77+/-34.67 microg L(-1)), the anticonvulsant carbamazepine (7.85+/-0.13 microg L(-1)), and the beta-blocker atenolol (11.08+/-7.98 microg L(-1)). Five immature males were selected for transcriptome analysis in brain tissues by means of a 17k salmon cDNA microarray. For this purpose, mRNA was isolated and reverse-transcribed into cDNA which was labeled with fluorescent dyes and hybridized against a common pool to the arrays. Lists of significantly up- and down-regulated candidate genes were submitted to KEGG (Kyoto Encyclopedia of Genes and Genomes) in order to analyze for induced pathways and to evaluate the usefulness of this method in cases of not completely annotated test organisms. Exposure during 5 days to

  4. A stratified transcriptomics analysis of polygenic fat and lean mouse adipose tissues identifies novel candidate obesity genes.

    Directory of Open Access Journals (Sweden)

    Nicholas M Morton

    Full Text Available Obesity and metabolic syndrome results from a complex interaction between genetic and environmental factors. In addition to brain-regulated processes, recent genome wide association studies have indicated that genes highly expressed in adipose tissue affect the distribution and function of fat and thus contribute to obesity. Using a stratified transcriptome gene enrichment approach we attempted to identify adipose tissue-specific obesity genes in the unique polygenic Fat (F mouse strain generated by selective breeding over 60 generations for divergent adiposity from a comparator Lean (L strain.To enrich for adipose tissue obesity genes a 'snap-shot' pooled-sample transcriptome comparison of key fat depots and non adipose tissues (muscle, liver, kidney was performed. Known obesity quantitative trait loci (QTL information for the model allowed us to further filter genes for increased likelihood of being causal or secondary for obesity. This successfully identified several genes previously linked to obesity (C1qr1, and Np3r as positional QTL candidate genes elevated specifically in F line adipose tissue. A number of novel obesity candidate genes were also identified (Thbs1, Ppp1r3d, Tmepai, Trp53inp2, Ttc7b, Tuba1a, Fgf13, Fmr that have inferred roles in fat cell function. Quantitative microarray analysis was then applied to the most phenotypically divergent adipose depot after exaggerating F and L strain differences with chronic high fat feeding which revealed a distinct gene expression profile of line, fat depot and diet-responsive inflammatory, angiogenic and metabolic pathways. Selected candidate genes Npr3 and Thbs1, as well as Gys2, a non-QTL gene that otherwise passed our enrichment criteria were characterised, revealing novel functional effects consistent with a contribution to obesity.A focussed candidate gene enrichment strategy in the unique F and L model has identified novel adipose tissue-enriched genes contributing to obesity.

  5. A meta-analysis of human embryonic stem cells transcriptome integrated into a web-based expression atlas.

    Science.gov (United States)

    Assou, Said; Le Carrour, Tanguy; Tondeur, Sylvie; Ström, Susanne; Gabelle, Audrey; Marty, Sophie; Nadal, Laure; Pantesco, Véronique; Réme, Thierry; Hugnot, Jean-Philippe; Gasca, Stéphan; Hovatta, Outi; Hamamah, Samir; Klein, Bernard; De Vos, John

    2007-04-01

    Microarray technology provides a unique opportunity to examine gene expression patterns in human embryonic stem cells (hESCs). We performed a meta-analysis of 38 original studies reporting on the transcriptome of hESCs. We determined that 1,076 genes were found to be overexpressed in hESCs by at least three studies when compared to differentiated cell types, thus composing a "consensus hESC gene list." Only one gene was reported by all studies: the homeodomain transcription factor POU5F1/OCT3/4. The list comprised other genes critical for pluripotency such as the transcription factors NANOG and SOX2, and the growth factors TDGF1/CRIPTO and Galanin. We show that CD24 and SEMA6A, two cell surface protein-coding genes from the top of the consensus hESC gene list, display a strong and specific membrane protein expression on hESCs. Moreover, CD24 labeling permits the purification by flow cytometry of hESCs cocultured on human fibroblasts. The consensus hESC gene list also included the FZD7 WNT receptor, the G protein-coupled receptor GPR19, and the HELLS helicase, which could play an important role in hESCs biology. Conversely, we identified 783 genes downregulated in hESCs and reported in at least three studies. This "consensus differentiation gene list" included the IL6ST/GP130 LIF receptor. We created an online hESC expression atlas, http://amazonia.montp.inserm.fr, to provide an easy access to this public transcriptome dataset. Expression histograms comparing hESCs to a broad collection of fetal and adult tissues can be retrieved with this web tool for more than 15,000 genes.

  6. Global microarray analysis of carbohydrate use in alkaliphilic hemicellulolytic bacterium Bacillus sp. N16-5.

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    Yajian Song

    Full Text Available The alkaliphilic hemicellulolytic bacterium Bacillus sp. N16-5 has a broad substrate spectrum and exhibits the capacity to utilize complex carbohydrates such as galactomannan, xylan, and pectin. In the monosaccharide mixture, sequential utilization by Bacillus sp. N16-5 was observed. Glucose appeared to be its preferential monosaccharide, followed by fructose, mannose, arabinose, xylose, and galactose. Global transcription profiles of the strain were determined separately for growth on six monosaccharides (glucose, fructose, mannose, galactose, arabinose, and xylose and four polysaccharides (galactomannan, xylan, pectin, and sodium carboxymethylcellulose using one-color microarrays. Numerous genes potentially related to polysaccharide degradation, sugar transport, and monosaccharide metabolism were found to respond to a specific substrate. Putative gene clusters for different carbohydrates were identified according to transcriptional patterns and genome annotation. Identification and analysis of these gene clusters contributed to pathway reconstruction for carbohydrate utilization in Bacillus sp. N16-5. Several genes encoding putative sugar transporters were highly expressed during growth on specific sugars, suggesting their functional roles. Two phosphoenolpyruvate-dependent phosphotransferase systems were identified as candidate transporters for mannose and fructose, and a major facilitator superfamily transporter was identified as a candidate transporter for arabinose and xylose. Five carbohydrate uptake transporter 1 family ATP-binding cassette transporters were predicted to participate in the uptake of hemicellulose and pectin degradation products. Collectively, microarray data improved the pathway reconstruction involved in carbohydrate utilization of Bacillus sp. N16-5 and revealed that the organism precisely regulates gene transcription in response to fluctuations in energy resources.

  7. Global Microarray Analysis of Carbohydrate Use in Alkaliphilic Hemicellulolytic Bacterium Bacillus sp. N16-5

    Science.gov (United States)

    Song, Yajian; Xue, Yanfen; Ma, Yanhe

    2013-01-01

    The alkaliphilic hemicellulolytic bacterium Bacillus sp. N16-5 has a broad substrate spectrum and exhibits the capacity to utilize complex carbohydrates such as galactomannan, xylan, and pectin. In the monosaccharide mixture, sequential utilization by Bacillus sp. N16-5 was observed. Glucose appeared to be its preferential monosaccharide, followed by fructose, mannose, arabinose, xylose, and galactose. Global transcription profiles of the strain were determined separately for growth on six monosaccharides (glucose, fructose, mannose, galactose, arabinose, and xylose) and four polysaccharides (galactomannan, xylan, pectin, and sodium carboxymethylcellulose) using one-color microarrays. Numerous genes potentially related to polysaccharide degradation, sugar transport, and monosaccharide metabolism were found to respond to a specific substrate. Putative gene clusters for different carbohydrates were identified according to transcriptional patterns and genome annotation. Identification and analysis of these gene clusters contributed to pathway reconstruction for carbohydrate utilization in Bacillus sp. N16-5. Several genes encoding putative sugar transporters were highly expressed during growth on specific sugars, suggesting their functional roles. Two phosphoenolpyruvate-dependent phosphotransferase systems were identified as candidate transporters for mannose and fructose, and a major facilitator superfamily transporter was identified as a candidate transporter for arabinose and xylose. Five carbohydrate uptake transporter 1 family ATP-binding cassette transporters were predicted to participate in the uptake of hemicellulose and pectin degradation products. Collectively, microarray data improved the pathway reconstruction involved in carbohydrate utilization of Bacillus sp. N16-5 and revealed that the organism precisely regulates gene transcription in response to fluctuations in energy resources. PMID:23326578

  8. Early Gene Expression in Wounded Human Keratinocytes Revealed by DNA Microarray Analysis

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    Pascal Barbry

    2006-04-01

    Full Text Available Wound healing involves several steps: spreading of the cells, migration and proliferation. We have profiled gene expression during the early events of wound healing in normal human keratinocytes with a home-made DNA microarray containing about 1000 relevant human probes. An original wounding machine was used, that allows the wounding of up to 40% of the surface of a confluent monolayer of cultured cells grown on a Petri dish (compared with 5% with a classical ‘scratch’ method. The two aims of the present study were: (a to validate a limited number of genes by comparing the expression levels obtained with this technique with those found in the literature; (b to combine the use of the wounding machine with DNA microarray analysis for large-scale detection of the molecular events triggered during the early stages of the wound-healing process. The time-courses of RNA expression observed at 0.5, 1.5, 3, 6 and 15 h after wounding for genes such as c-Fos, c-Jun, Egr1, the plasminogen activator PLAU (uPA and the signal transducer and transcription activator STAT3, were consistent with previously published data. This suggests that our methodologies are able to perform quantitative measurement of gene expression. Transcripts encoding two zinc finger proteins, ZFP36 and ZNF161, and the tumour necrosis factor α-induced protein TNFAIP3, were also overexpressed after wounding. The role of the p38 mitogen-activated protein kinase (p38MAPK in wound healing was shown after the inhibition of p38 by SB203580, but our results also suggest the existence of surrogate activating pathways.

  9. Using microarray analysis as a prognostic and predictive tool in oncology: focus on breast cancer and normal tissue toxicity

    NARCIS (Netherlands)

    Nuyten, Dimitry S. A.; van de Vijver, Marc J.

    2008-01-01

    Microarray analysis makes it possible to study the expression levels of tens of thousands of genes in one single experiment and is widely available for research purposes. Gene expression profiling is currently being used in many research projects aimed at identifying gene expression signatures in

  10. Comparative analysis of proteome and transcriptome variation in mouse.

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    Anatole Ghazalpour

    2011-06-01

    Full Text Available The relationships between the levels of transcripts and the levels of the proteins they encode have not been examined comprehensively in mammals, although previous work in plants and yeast suggest a surprisingly modest correlation. We have examined this issue using a genetic approach in which natural variations were used to perturb both transcript levels and protein levels among inbred strains of mice. We quantified over 5,000 peptides and over 22,000 transcripts in livers of 97 inbred and recombinant inbred strains and focused on the 7,185 most heritable transcripts and 486 most reliable proteins. The transcript levels were quantified by microarray analysis in three replicates and the proteins were quantified by Liquid Chromatography-Mass Spectrometry using O(18-reference-based isotope labeling approach. We show that the levels of transcripts and proteins correlate significantly for only about half of the genes tested, with an average correlation of 0.27, and the correlations of transcripts and proteins varied depending on the cellular location and biological function of the gene. We examined technical and biological factors that could contribute to the modest correlation. For example, differential splicing clearly affects the analyses for certain genes; but, based on deep sequencing, this does not substantially contribute to the overall estimate of the correlation. We also employed genome-wide association analyses to map loci controlling both transcript and protein levels. Surprisingly, little overlap was observed between the protein- and transcript-mapped loci. We have typed numerous clinically relevant traits among the strains, including adiposity, lipoprotein levels, and tissue parameters. Using correlation analysis, we found that a low number of clinical trait relationships are preserved between the protein and mRNA gene products and that the majority of such relationships are specific to either the protein levels or transcript levels

  11. Transcriptome analysis of the ependymal barrier during murine neurocysticercosis

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    Mishra Pramod

    2012-06-01

    Full Text Available Abstract Background Central nervous system (CNS barriers play a pivotal role in the protection and homeostasis of the CNS by enabling the exchange of metabolites while restricting the entry of xenobiotics, blood cells and blood-borne macromolecules. While the blood–brain barrier and blood-cerebrospinal fluid barrier (CSF control the interface between the blood and CNS, the ependyma acts as a barrier between the CSF and parenchyma, and regulates hydrocephalic pressure and metabolic toxicity. Neurocysticercosis (NCC is an infection of the CNS caused by the metacestode (larva of Taenia solium and a major cause of acquired epilepsy worldwide. The common clinical manifestations of NCC are seizures, hydrocephalus and symptoms due to increased intracranial pressure. The majority of the associated pathogenesis is attributed to the immune response against the parasite. The properties of the CNS barriers, including the ependyma, are affected during infection, resulting in disrupted homeostasis and infiltration of leukocytes, which correlates with the pathology and disease symptoms of NCC patients. Results In order to characterize the role of the ependymal barrier in the immunopathogenesis of NCC, we isolated ependymal cells using laser capture microdissection from mice infected or mock-infected with the closely related parasite Mesocestoides corti, and analyzed the genes that were differentially expressed using microarray analysis. The expression of 382 genes was altered. Immune response-related genes were verified by real-time RT-PCR. Ingenuity Pathway Analysis (IPA software was used to analyze the biological significance of the differentially expressed genes, and revealed that genes known to participate in innate immune responses, antigen presentation and leukocyte infiltration were affected along with the genes involved in carbohydrate, lipid and small molecule biochemistry. Further, MHC class II molecules and chemokines, including CCL12, were found

  12. Assessment of chitosan-affected metabolic response by peroxisome proliferator-activated receptor bioluminescent imaging-guided transcriptomic analysis.

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    Chia-Hung Kao

    Full Text Available Chitosan has been widely used in food industry as a weight-loss aid and a cholesterol-lowering agent. Previous studies have shown that chitosan affects metabolic responses and contributes to anti-diabetic, hypocholesteremic, and blood glucose-lowering effects; however, the in vivo targeting sites and mechanisms of chitosan remain to be clarified. In this study, we constructed transgenic mice, which carried the luciferase genes driven by peroxisome proliferator-activated receptor (PPAR, a key regulator of fatty acid and glucose metabolism. Bioluminescent imaging of PPAR transgenic mice was applied to report the organs that chitosan acted on, and gene expression profiles of chitosan-targeted organs were further analyzed to elucidate the mechanisms of chitosan. Bioluminescent imaging showed that constitutive PPAR activities were detected in brain and gastrointestinal tract. Administration of chitosan significantly activated the PPAR activities in brain and stomach. Microarray analysis of brain and stomach showed that several pathways involved in lipid and glucose metabolism were regulated by chitosan. Moreover, the expression levels of metabolism-associated genes like apolipoprotein B (apoB and ghrelin genes were down-regulated by chitosan. In conclusion, these findings suggested the feasibility of PPAR bioluminescent imaging-guided transcriptomic analysis on the evaluation of chitosan-affected metabolic responses in vivo. Moreover, we newly identified that downregulated expression of apoB and ghrelin genes were novel mechanisms for chitosan-affected metabolic responses in vivo.

  13. Transcriptomic Analysis of Induced Pluripotent Stem Cells Derived from Patients with Bipolar Disorder from an Old Order Amish Pedigree.

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    Kwi Hye Kim

    Full Text Available Fibroblasts from patients with Type I bipolar disorder (BPD and their unaffected siblings were obtained from an Old Order Amish pedigree with a high incidence of BPD and reprogrammed to induced pluripotent stem cells (iPSCs. Established iPSCs were subsequently differentiated into neuroprogenitors (NPs and then to neurons. Transcriptomic microarray analysis was conducted on RNA samples from iPSCs, NPs and neurons matured in culture for either 2 weeks (termed early neurons, E or 4 weeks (termed late neurons, L. Global RNA profiling indicated that BPD and control iPSCs differentiated into NPs and neurons at a similar rate, enabling studies of differentially expressed genes in neurons from controls and BPD cases. Significant disease-associated differences in gene expression were observed only in L neurons. Specifically, 328 genes were differentially expressed between BPD and control L neurons including GAD1, glutamate decarboxylase 1 (2.5 fold and SCN4B, the voltage gated type IV sodium channel beta subunit (-14.6 fold. Quantitative RT-PCR confirmed the up-regulation of GAD1 in BPD compared to control L neurons. Gene Ontology, GeneGo and Ingenuity Pathway Analysis of differentially regulated genes in L neurons suggest that alterations in RNA biosynthesis and metabolism, protein trafficking as well as receptor signaling pathways may play an important role in the pathophysiology of BPD.

  14. Comprehensive evaluation of gene expression signatures in response to electroacupuncture stimulation at Zusanli (ST36) acupoint by transcriptomic analysis.

    Science.gov (United States)

    Wu, Jing-Shan; Lo, Hsin-Yi; Li, Chia-Cheng; Chen, Feng-Yuan; Hsiang, Chien-Yun; Ho, Tin-Yun

    2017-08-15

    Electroacupuncture (EA) has been applied to treat and prevent diseases for years. However, molecular events happened in both the acupunctured site and the internal organs after EA stimulation have not been clarified. Here we applied transcriptomic analysis to explore the gene expression signatures after EA stimulation. Mice were applied EA stimulation at ST36 for 15 min and nine tissues were collected three hours later for microarray analysis. We found that EA affected the expression of genes not only in the acupunctured site but also in the internal organs. EA commonly affected biological networks involved in cytoskeleton and cell adhesion, and also regulated unique process networks in specific organs, such as γ-aminobutyric acid-ergic neurotransmission in brain and inflammation process in lung. In addition, EA affected the expression of genes related to various diseases, such as neurodegenerative diseases in brain and obstructive pulmonary diseases in lung. This report applied, for the first time, a global comprehensive genome-wide approach to analyze the gene expression profiling of acupunctured site and internal organs after EA stimulation. The connection between gene expression signatures, biological processes, and diseases might provide a basis for prediction and explanation on the therapeutic potentials of acupuncture in organs.

  15. Comparative gene expression analysis of two mouse models of autism:transcriptome profiling of the BTBR and En2-/- hippocampus

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    Giovanni Provenzano

    2016-08-01

    Full Text Available Autism spectrum disorders (ASD are characterized by a high degree of genetic heterogeneity. Genomic studies identified common pathological processes underlying the heterogeneous clinical manifestations of ASD, and transcriptome analyses revealed that gene networks involved in synapse development, neuronal activity and immune function are deregulated in ASD. Mouse models provide unique tools to investigate the neurobiological basis of ASD; however, a comprehensive approach to identify transcriptional abnormalities in different ASD models has never been performed. Here we used two well-recognized ASD mouse models, BTBR T+ Itpr3tf/J (BTBR and Engrailed-2 knockout (En2-/-, to identify conserved ASD-related molecular signatures. En2-/- mice bear a mutation within the EN2 transcription factor homeobox, while BTBR is an inbred strain with unknown genetic defects. Hippocampal RNA samples from BTBR, En2-/- and respective control (C57Bl/6J and En2+/+ adult mice were assessed for differential gene expression using microarrays. A total of 153 genes were similarly deregulated in the BTBR and En2-/- hippocampus. Mouse phenotype and gene ontology enrichment analyses were performed on BTBR and En2-/- hippocampal differentially expressed genes (DEGs. Pathways represented in both BTBR and En2-/- hippocampal DEGs included abnormal behavioral response and chemokine/MAP kinase signaling. Genes involved in abnormal function of the immune system and abnormal synaptic transmission/seizures were significantly represented among BTBR and En2-/- DEGs, respectively. Interestingly, both BTBR and En2-/- hippocampal DEGs showed a significant enrichment of ASD and schizophrenia (SCZ-associated genes. Specific gene sets were enriched in the two models: microglial genes were significantly enriched among BTBR DEGs, whereas GABAergic/glutamatergic postsynaptic genes, FMRP-interacting genes and epilepsy-related genes were significantly enriched among En2-/- DEGs. Weighted

  16. Transcriptome tomography for brain analysis in the web-accessible anatomical space.

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    Yuko Okamura-Oho

    Full Text Available Increased information on the encoded mammalian genome is expected to facilitate an integrated understanding of complex anatomical structure and function based on the knowledge of gene products. Determination of gene expression-anatomy associations is crucial for this understanding. To elicit the association in the three-dimensional (3D space, we introduce a novel technique for comprehensive mapping of endogenous gene expression into a web-accessible standard space: Transcriptome Tomography. The technique is based on conjugation of sequential tissue-block sectioning, all fractions of which are used for molecular measurements of gene expression densities, and the block- face imaging, which are used for 3D reconstruction of the fractions. To generate a 3D map, tissues are serially sectioned in each of three orthogonal planes and the expression density data are mapped using a tomographic technique. This rapid and unbiased mapping technique using a relatively small number of original data points allows researchers to create their own expression maps in the broad anatomical context of the space. In the first instance we generated a dataset of 36,000 maps, reconstructed from data of 61 fractions measured with microarray, covering the whole mouse brain (ViBrism: http://vibrism.riken.jp/3dviewer/ex/index.html in one month. After computational estimation of the mapping accuracy we validated the dataset against existing data with respect to the expression location and density. To demonstrate the relevance of the framework, we showed disease related expression of Huntington's disease gene and Bdnf. Our tomographic approach is applicable to analysis of any biological molecules derived from frozen tissues, organs and whole embryos, and the maps are spatially isotropic and well suited to the analysis in the standard space (e.g. Waxholm Space for brain-atlas databases. This will facilitate research creating and using open-standards for a molecular

  17. Establishment and analysis of a reference transcriptome for Spodoptera frugiperda.

    Science.gov (United States)

    Legeai, Fabrice; Gimenez, Sylvie; Duvic, Bernard; Escoubas, Jean-Michel; Gosselin Grenet, Anne-Sophie; Blanc, Florence; Cousserans, François; Séninet, Imène; Bretaudeau, Anthony; Mutuel, Doriane; Girard, Pierre-Alain; Monsempes, Christelle; Magdelenat, Ghislaine; Hilliou, Frédérique; Feyereisen, René; Ogliastro, Mylène; Volkoff, Anne-Nathalie; Jacquin-Joly, Emmanuelle; d'Alençon, Emmanuelle; Nègre, Nicolas; Fournier, Philippe

    2014-08-23

    Spodoptera frugiperda (Noctuidae) is a major agricultural pest throughout the American continent. The highly polyphagous larvae are frequently devastating crops of importance such as corn, sorghum, cotton and grass. In addition, the Sf9 cell line, widely used in biochemistry for in vitro protein production, is derived from S. frugiperda tissues. Many research groups are using S. frugiperda as a model organism to investigate questions such as plant adaptation, pest behavior or resistance to pesticides. In this study, we constructed a reference transcriptome assembly (Sf_TR2012b) of RNA sequences obtained from more than 35 S. frugiperda developmental time-points and tissue samples. We assessed the quality of this reference transcriptome by annotating a ubiquitous gene family--ribosomal proteins--as well as gene families that have a more constrained spatio-temporal expression and are involved in development, immunity and olfaction. We also provide a time-course of expression that we used to characterize the transcriptional regulation of the gene families studied. We conclude that the Sf_TR2012b transcriptome is a valid reference transcriptome. While its reliability decreases for the detection and annotation of genes under strong transcriptional constraint we still recover a fair percentage of tissue-specific transcripts. That allowed us to explore the spatial and temporal expression of genes and to observe that some olfactory receptors are expressed in antennae and palps but also in other non related tissues such as fat bodies. Similarly, we observed an interesting interplay of gene families involved in immunity between fat bodies and antennae.

  18. Transcriptome Analysis of the Response of Burmese Python to Digestion

    OpenAIRE

    Duan, Jinjie; Sanggaard, Kristian Wejse; Schauser, Leif; Lauridsen, Sanne Enok; Enghild, Jan J.; Schierup, Mikkel Heide; Wang, Tobias

    2017-01-01

    Abstract Exceptional and extreme feeding behaviour makes the Burmese python (Python bivittatus) an interesting model to study physiological remodelling and metabolic adaptation in response to refeeding after prolonged starvation. In this study, we used transcriptome sequencing of 5 visceral organs during fasting as well as 24 hours and 48 hours after ingestion of a large meal to unravel the postprandial changes in Burmese pythons. We first used the pooled data to perform a de novo assembly of...

  19. Transcriptome analysis of the response of Burmese python to digestion.

    Science.gov (United States)

    Duan, Jinjie; Sanggaard, Kristian Wejse; Schauser, Leif; Lauridsen, Sanne Enok; Enghild, Jan J; Schierup, Mikkel Heide; Wang, Tobias

    2017-08-01

    Exceptional and extreme feeding behaviour makes the Burmese python (Python bivittatus) an interesting model to study physiological remodelling and metabolic adaptation in response to refeeding after prolonged starvation. In this study, we used transcriptome sequencing of 5 visceral organs during fasting as well as 24 hours and 48 hours after ingestion of a large meal to unravel the postprandial changes in Burmese pythons. We first used the pooled data to perform a de novo assembly of the transcriptome and supplemented this with a proteomic survey of enzymes in the plasma and gastric fluid. We constructed a high-quality transcriptome with 34 423 transcripts, of which 19 713 (57%) were annotated. Among highly expressed genes (fragments per kilo base per million sequenced reads > 100 in 1 tissue), we found that the transition from fasting to digestion was associated with differential expression of 43 genes in the heart, 206 genes in the liver, 114 genes in the stomach, 89 genes in the pancreas, and 158 genes in the intestine. We interrogated the function of these genes to test previous hypotheses on the response to feeding. We also used the transcriptome to identify 314 secreted proteins in the gastric fluid of the python. Digestion was associated with an upregulation of genes related to metabolic processes, and translational changes therefore appear to support the postprandial rise in metabolism. We identify stomach-related proteins from a digesting individual and demonstrate that the sensitivity of modern liquid chromatography/tandem mass spectrometry equipment allows the identification of gastric juice proteins that are present during digestion. © The Authors 2017. Published by Oxford University Press.

  20. Massively parallel sequencing and analysis of the Necator americanus transcriptome.

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    Cinzia Cantacessi

    2010-05-01

    Full Text Available The blood-feeding hookworm Necator americanus infects hundreds of millions of people worldwide. In order to elucidate fundamental molecular biological aspects of this hookworm, the transcriptome of the adult stage of Necator americanus was explored using next-generation sequencing and bioinformatic analyses.A total of 19,997 contigs were assembled from the sequence data; 6,771 of these contigs had known orthologues in the free-living nematode Caenorhabditis elegans, and most of them encoded proteins with WD40 repeats (10.6%, proteinase inhibitors (7.8% or calcium-binding EF-hand proteins (6.7%. Bioinformatic analyses inferred that the C. elegans homologues are involved mainly in biological pathways linked to ribosome biogenesis (70%, oxidative phosphorylation (63% and/or proteases (60%; most of these molecules were predicted to be involved in more than one biological pathway. Comparative analyses of the transcriptomes of N. americanus and the canine hookworm, Ancylostoma caninum, revealed qualitative and quantitative differences. For instance, proteinase inhibitors were inferred to be highly represented in the former species, whereas SCP/Tpx-1/Ag5/PR-1/Sc7 proteins ( = SCP/TAPS or Ancylostoma-secreted proteins were predominant in the latter. In N. americanus, essential molecules were predicted using a combination of orthology mapping and functional data available for C. elegans. Further analyses allowed the prioritization of 18 predicted drug targets which did not have homologues in the human host. These candidate targets were inferred to be linked to mitochondrial (e.g., processing proteins or amino acid metabolism (e.g., asparagine t-RNA synthetase.This study has provided detailed insights into the transcriptome of the adult stage of N. americanus and examines similarities and differences between this species and A. caninum. Future efforts should focus on comparative transcriptomic and proteomic investigations of the other predominant human

  1. Transcriptome analysis of the phytobacterium Xylella fastidiosa growing under xylem-based chemical conditions.

    Science.gov (United States)

    Ciraulo, Maristela Boaceff; Santos, Daiene Souza; Rodrigues, Ana Claudia de Freitas Oliveira; de Oliveira, Marcus Vinícius; Rodrigues, Tiago; de Oliveira, Regina Costa; Nunes, Luiz R

    2010-01-01

    Xylella fastidiosa is a xylem-limited bacterium responsible for important plant diseases, like citrus-variegated chlorosis (CVC) and grapevine Pierce's disease (PD). Interestingly, in vitro growth of X. fastidiosa in chemically defined media that resemble xylem fluid has been achieved, allowing studies of metabolic processes used by xylem-dwelling bacteria to thrive in such nutrient-poor conditions. Thus, we performed microarray hybridizations to compare transcriptomes of X. fastidiosa cells grown in 3G10-R, a medium that resembles grape sap, and in Periwinkle Wilt (PW), the complex medium traditionally used to cultivate X. fastidiosa. We identified 299 transcripts modulated in response to growth in these media. Some 3G10R-overexpressed genes have been shown to be upregulated in cells directly isolated from infected plants and may be involved in plant colonization, virulence and environmental competition. In contrast, cells cultivated in PW show a metabolic switch associated with increased aerobic respiration and enhanced bacterial growth rates.

  2. Microarray Expression Profile and Functional Analysis of Circular RNAs in Osteosarcoma

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    Weihai Liu

    2017-09-01

    Full Text Available Background/Aims: Osteosarcoma (OS is the most common primary malignant bone tumor in children and adolescents. However, the molecular mechanisms regulating osteosarcoma tumorigenesis and progression are still poorly understood. Circular RNAs (circRNAs have been identified as microRNA sponges and are involved in many important biological processes. This study aims to investigate the global changes in the expression pattern of circRNAs in osteosarcoma and provide a comprehensive understanding of differentially expressed circRNAs. Methods: Microarray based circRNA expression was determined in osteosarcoma cell lines and compared with hFOB1.19, which was used as the normal control. We confirmed the microarray data by real time-qPCR in both osteosarcoma cell lines and tissues. The circRNA/microRNA/mRNA interaction network was predicted using bioinformatics. Gene Ontology analysis and 4 annotation tools for pathway analysis (KEGG, Biocarta, PANTHER and Reactome were used to predict the functions of differentially expressed circRNAs. Results: We revealed a number of differentially expressed circRNAs and 12 of them were confirmed, which suggests a potential role of circRNAs in OS. Among these differentially expressed circRNAs, hsa_circRNA_103801 was up-regulated in both osteosarcoma cell lines and tissues, while hsa_circRNA_104980 was down-regulated. The most likely potential target miRNAs for hsa_circRNA_103801 include hsa-miR-370-3p, hsa-miR-338-3p and hsa-miR-877-3p, while the most potential target miRNAs of hsa_circRNA_104980 consist of hsa-miR-1298-3p and hsa-miR-660-3p. Functional analysis found that hsa_circRNA_103801 was involved in pathways in cancer, such as the HIF-1, VEGF and angiogenesis pathway, the Rap1 signaling pathway and the PI3K-Akt signaling pathway, while hsa_circRNA_104980 was related to some pathways such as the tight junction pathway. Conclusions: This study has identified the comprehensive expression profile of circRNAs in

  3. Transcriptome Analysis of Spartina pectinata in Response to Freezing Stress.

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    Gyoungju Nah

    Full Text Available Prairie cordgrass (Spartina pectinata, a perennial C4 grass native to the North American prairie, has several distinctive characteristics that potentially make it a model crop for production in stressful environments. However, little is known about the transcriptome dynamics of prairie cordgrass despite its unique freezing stress tolerance. Therefore, the purpose of this work was to explore the transcriptome dynamics of prairie cordgrass in response to freezing stress at -5°C for 5 min and 30 min. We used a RNA-sequencing method to assemble the S. pectinata leaf transcriptome and performed gene-expression profiling of the transcripts under freezing treatment. Six differentially expressed gene (DEG groups were categorized from the profiling. In addition, two major consecutive orders of gene expression were observed in response to freezing; the first being the acute up-regulation of genes involved in plasma membrane modification, calcium-mediated signaling, proteasome-related proteins, and transcription regulators (e.g., MYB and WRKY. The follow-up and second response was of genes involved in encoding the putative anti-freezing protein and the previously known DNA and cell-damage-repair proteins. Moreover, we identified the genes involved in epigenetic regulation and circadian-clock expression. Our results indicate that freezing response in S. pectinata reflects dynamic changes in rapid-time duration, as well as in metabolic, transcriptional, post-translational, and epigenetic regulation.

  4. [Application of chromosome microarray analysis for fetuses with multicystic dysplastic kidney].

    Science.gov (United States)

    Chen, Feifei; Lei, Tingying; Fu, Fang; Li, Ru; Zhang, Yongling; Jing, Xiangyi; Yang, Xin; Han, Jin; Zhen, Li; Pan, Min; Liao, Can

    2016-12-10

    To explore the genetic etiology of fetuses with multicystic dysplastic kidney (MCDK) by chromosome microarray analysis (CMA). Seventy-two fetuses with MCDK were analyzed with conventional cytogenetic technique, among which 30 fetuses with a normal karyotype were subjected to CMA analysis with Affymetrix CytoScan HD arrays by following the manufacturer's protocol. The data was analyzed with ChAS software. Conventional cytogenetic technique has revealed three fetuses (4.2%) with identifiable chromosomal aberrations. CMA analysis has detected pathogenic CNVs in 5 fetuses (16.7%), which included two well-known microdeletion or microduplication syndromes, i.e., 17q12 microdeletion syndrome and Williams-Beuren syndrome (WBS) and three submicroscopic imbalances at 4q35.2, 22q13.33, and 1p33. PEX26, FKBP6, TUBGCP6, ALG12, and CYP4A11 are likely the causative genes. CMA can identify the submicroscopic imbalances unidentifiable by conventional cytogenetic technique, and therefore has a significant role in prenatal diagnosis and genetic counseling. The detection rate of pathogenic CNVs in fetuses with MCDK was 16.7% by CMA. 17q12 microdeletion syndrome and WBS are associated with MCDK. Mutations of PEX26, FKBP6, TUBGCP6, ALG12, and CYP4A11 genes may be the causes for MCDK.

  5. SIGMA: A System for Integrative Genomic Microarray Analysis of Cancer Genomes

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    Davies Jonathan J

    2006-12-01

    Full Text Available Abstract Background The prevalence of high resolution profiling of genomes has created a need for the integrative analysis of information generated from multiple methodologies and platforms. Although the majority of data in the public domain are gene expression profiles, and expression analysis software are available, the increase of array CGH studies has enabled integration of high throughput genomic and gene expression datasets. However, tools for direct mining and analysis of array CGH data are limited. Hence, there is a great need for analytical and display software tailored to cross platform integrative analysis of cancer genomes. Results We have created a user-friendly java application to facilitate sophisticated visualization and analysis such as cross-tumor and cross-platform comparisons. To demonstrate the utility of this software, we assembled array CGH data representing Affymetrix SNP chip, Stanford cDNA arrays and whole genome tiling path array platforms for cross comparison. This cancer genome database contains 267 profiles from commonly used cancer cell lines representing 14 different tissue types. Conclusion In this study we have developed an application for the visualization and analysis of data from high resolution array CGH platforms that can be adapted for analysis of multiple types of high throughput genomic datasets. Furthermore, we invite researchers using array CGH technology to deposit both their raw and processed data, as this will be a continually expanding database of cancer genomes. This publicly available resource, the System for Integrative Genomic Microarray Analysis (SIGMA of cancer genomes, can be accessed at http://sigma.bccrc.ca.

  6. Transcriptomic network analysis of micronuclei-related genes: a case study

    DEFF Research Database (Denmark)

    van Leeuwen, D. M.; Pedersen, Marie; Knudsen, Lisbeth E.

    2011-01-01

    checkpoint and aneuploidy. The MN-related gene network was tested against a transcriptomics case study associated with MN measurements. In this case study, transcriptomic data from children and adults differentially exposed to ambient air pollution in the Czech Republic were analysed and visualised......Mechanistically relevant information on responses of humans to xenobiotic exposure in relation to chemically induced biological effects, such as micronuclei (MN) formation can be obtained through large-scale transcriptomics studies. Network analysis may enhance the analysis and visualisation...... of such data. Therefore, this study aimed to develop a 'MN formation' network based on a priori knowledge, by using the pathway tool MetaCore. The gene network contained 27 genes and three gene complexes that are related to processes involved in MN formation, e.g. spindle assembly checkpoint, cell cycle...

  7. An evaluation of two-channel ChIP-on-chip and DNA methylation microarray normalization strategies

    Science.gov (United States)

    2012-01-01

    Background The combination of chromatin immunoprecipitation with two-channel microarray technology enables genome-wide mapping of binding sites of DNA-interacting proteins (ChIP-on-chip) or sites with methylated CpG di-nucleotides (DNA methylation microarray). These powerful tools are the gateway to understanding gene transcription regulation. Since the goals of such studies, the sample preparation procedures, the microarray content and study design are all different from transcriptomics microarrays, the data pre-processing strategies traditionally applied to transcriptomics microarrays may not be appropriate. Particularly, the main challenge of the normalization of "regulation microarrays" is (i) to make the data of individual microarrays quantitatively comparable and (ii) to keep the signals of the enriched probes, representing DNA sequences from the precipitate, as distinguishable as possible from the signals of the un-enriched probes, representing DNA sequences largely absent from the precipitate. Results We compare several widely used normalization approaches (VSN, LOWESS, quantile, T-quantile, Tukey's biweight scaling, Peng's method) applied to a selection of regulation microarray datasets, ranging from DNA methylation to transcription factor binding and histone modification studies. Through comparison of the data distributions of control probes and gene promoter probes before and after normalization, and assessment of the power to identify known enriched genomic regions after normalization, we demonstrate that there are clear differences in performance between normalization procedures. Conclusion T-quantile normalization applied separately on the channels and Tukey's biweight scaling outperform other methods in terms of the conservation of enriched and un-enriched signal separation, as well as in identification of genomic regions known to be enriched. T-quantile normalization is preferable as it additionally improves comparability between microarrays. In

  8. A functional and transcriptomic analysis of NET1 bioactivity in gastric cancer

    LENUS (Irish Health Repository)

    Bennett, Gayle

    2011-02-01

    Abstract Background NET1, a RhoA guanine exchange factor, is up-regulated in gastric cancer (GC) tissue and drives the invasive phenotype of this disease. In this study, we aimed to determine the role of NET1 in GC by monitoring the proliferation, motility and invasion of GC cells in which NET1 has been stably knocked down. Additionally, we aimed to determine NET1-dependent transcriptomic events that occur in GC. Methods An in vitro model of stable knockdown of NET1 was achieved in AGS human gastric adenocarcinoma cells via lentiviral mediated transduction of short-hairpin (sh) RNA targeting NET1. Knockdown was assessed using quantitative PCR. Cell proliferation was assessed using an MTS assay and cell migration was assessed using a wound healing scratch assay. Cell invasion was assessed using a transwell matrigel invasion assay. Gene expression profiles were examined using affymetrix oligonucleotide U133A expression arrays. A student\\'s t test was used to determine changes of statistical significance. Results GC cells were transduced with NET1 shRNA resulting in a 97% reduction in NET1 mRNA (p < 0.0001). NET1 knockdown significantly reduced the invasion and migration of GC cells by 94% (p < 0.05) and 24% (p < 0.001) respectively, while cell proliferation was not significantly altered following NET1 knockdown. Microarray analysis was performed on non-target and knockdown cell lines, treated with and without 10 μM lysophosphatidic acid (LPA) allowing us to identify NET1-dependent, LPA-dependent and NET1-mediated LPA-induced gene transcription. Differential gene expression was confirmed by quantitative PCR. Shortlisted NET1-dependent genes included STAT1, TSPAN1, TGFBi and CCL5 all of which were downregulatd upon NET1 downregulation. Shortlisted LPA-dependent genes included EGFR and PPARD where EGFR was upregulated and PPARD was downregulated upon LPA stimulation. Shortlisted NET1 and LPA dependent genes included IGFR1 and PIP5K3. These LPA induced genes were

  9. Temporal transcriptomic analysis of Desulfovibrio vulgaris Hildenborough transition into stationary phase growth during electrondonor depletion

    Energy Technology Data Exchange (ETDEWEB)

    Clark, M.E.; He, Q.; He, Z.; Huang, K.H.; Alm, E.J.; Wan, X.-F.; Hazen, T.C.; Arkin, A.P.; Wall, J.D.; Zhou, J.-Z.; Fields, M.W.

    2006-08-01

    Desulfovibrio vulgaris was cultivated in a defined medium, and biomass was sampled for approximately 70 h to characterize the shifts in gene expression as cells transitioned from the exponential to the stationary phase during electron donor depletion. In addition to temporal transcriptomics, total protein, carbohydrate, lactate, acetate, and sulfate levels were measured. The microarray data were examined for statistically significant expression changes, hierarchical cluster analysis, and promoter element prediction and were validated by quantitative PCR. As the cells transitioned from the exponential phase to the stationary phase, a majority of the down-expressed genes were involved in translation and transcription, and this trend continued at the remaining times. There were general increases in relative expression for intracellular trafficking and secretion, ion transport, and coenzyme metabolism as the cells entered the stationary phase. As expected, the DNA replication machinery was down-expressed, and the expression of genes involved in DNA repair increased during the stationary phase. Genes involved in amino acid acquisition, carbohydrate metabolism, energy production, and cell envelope biogenesis did not exhibit uniform transcriptional responses. Interestingly, most phage-related genes were up-expressed at the onset of the stationary phase. This result suggested that nutrient depletion may affect community dynamics and DNA transfer mechanisms of sulfate-reducing bacteria via the phage cycle. The putative feoAB system (in addition to other presumptive iron metabolism genes) was significantly up-expressed, and this suggested the possible importance of Fe{sup 2+} acquisition under metal-reducing conditions. The expression of a large subset of carbohydrate-related genes was altered, and the total cellular carbohydrate levels declined during the growth phase transition. Interestingly, the D. vulgaris genome does not contain a putative rpoS gene, a common attribute

  10. A functional and transcriptomic analysis of NET1 bioactivity in gastric cancer

    International Nuclear Information System (INIS)

    Bennett, Gayle; Sadlier, Denise; Doran, Peter P; MacMathuna, Padraic; Murray, David W

    2011-01-01

    NET1, a RhoA guanine exchange factor, is up-regulated in gastric cancer (GC) tissue and drives the invasive phenotype of this disease. In this study, we aimed to determine the role of NET1 in GC by monitoring the proliferation, motility and invasion of GC cells in which NET1 has been stably knocked down. Additionally, we aimed to determine NET1-dependent transcriptomic events that occur in GC. An in vitro model of stable knockdown of NET1 was achieved in AGS human gastric adenocarcinoma cells via lentiviral mediated transduction of short-hairpin (sh) RNA targeting NET1. Knockdown was assessed using quantitative PCR. Cell proliferation was assessed using an MTS assay and cell migration was assessed using a wound healing scratch assay. Cell invasion was assessed using a transwell matrigel invasion assay. Gene expression profiles were examined using affymetrix oligonucleotide U133A expression arrays. A student's t test was used to determine changes of statistical significance. GC cells were transduced with NET1 shRNA resulting in a 97% reduction in NET1 mRNA (p < 0.0001). NET1 knockdown significantly reduced the invasion and migration of GC cells by 94% (p < 0.05) and 24% (p < 0.001) respectively, while cell proliferation was not significantly altered following NET1 knockdown. Microarray analysis was performed on non-target and knockdown cell lines, treated with and without 10 μM lysophosphatidic acid (LPA) allowing us to identify NET1-dependent, LPA-dependent and NET1-mediated LPA-induced gene transcription. Differential gene expression was confirmed by quantitative PCR. Shortlisted NET1-dependent genes included STAT1, TSPAN1, TGFBi and CCL5 all of which were downregulatd upon NET1 downregulation. Shortlisted LPA-dependent genes included EGFR and PPARD where EGFR was upregulated and PPARD was downregulated upon LPA stimulation. Shortlisted NET1 and LPA dependent genes included IGFR1 and PIP5K3. These LPA induced genes were downregulated in NET1 knockdown cells

  11. Transcriptomic Analysis of Ciguatoxin-Induced Changes in Gene Expression in Primary Cultures of Mice Cortical Neurons

    Directory of Open Access Journals (Sweden)

    Juan Andrés Rubiolo

    2018-05-01

    Full Text Available Ciguatoxins are polyether marine toxins that act as sodium channel activators. These toxins cause ciguatera, one of the most widespread nonbacterial forms of food poisoning, which presents several symptoms in humans including long-term neurological alterations. Earlier work has shown that both acute and chronic exposure of primary cortical neurons to synthetic ciguatoxin CTX3C have profound impacts on neuronal function. Thus, the present work aimed to identify relevant neuronal genes and metabolic pathways that could be altered by ciguatoxin exposure. To study the effect of ciguatoxins in primary neurons in culture, we performed a transcriptomic analysis using whole mouse genome microarrays, for primary cortical neurons exposed during 6, 24, or 72 h in culture to CTX3C. Here, we have shown that the effects of the toxin on gene expression differ with the exposure time. The results presented here have identified several relevant genes and pathways related to the effect of ciguatoxins on neurons and may assist in future research or even treatment of ciguatera. Moreover, we demonstrated that the effects of the toxin on gene expression were exclusively consequential of its action as a voltage-gated sodium channel activator, since all the effects of CTX3C were avoided by preincubation of the neurons with the sodium channel blocker tetrodotoxin.

  12. Root Transcriptomic Analysis Revealing the Importance of Energy Metabolism to the Development of Deep Roots in Rice (Oryza sativa L.

    Directory of Open Access Journals (Sweden)

    Qiaojun Lou

    2017-07-01

    Full Text Available Drought is the most serious abiotic stress limiting rice production, and deep root is the key contributor to drought avoidance. However, the genetic mechanism regulating the development of deep roots is largely unknown. In this study, the transcriptomes of 74 root samples from 37 rice varieties, representing the extreme genotypes of shallow or deep rooting, were surveyed by RNA-seq. The 13,242 differentially expressed genes (DEGs between deep rooting and shallow rooting varieties (H vs. L were enriched in the pathway of genetic information processing and metabolism, while the 1,052 DEGs between the deep roots and shallow roots from each of the plants (D vs. S were significantly enriched in metabolic pathways especially energy metabolism. Ten quantitative trait transcripts (QTTs were identified and some were involved in energy metabolism. Forty-nine candidate DEGs were confirmed by qRT-PCR and microarray. Through weighted gene co-expression network analysis (WGCNA, we found 18 hub genes. Surprisingly, all these hub genes expressed higher in deep roots than in shallow roots, furthermore half of them functioned in energy metabolism. We also estimated that the ATP production in the deep roots was faster than shallow roots. Our results provided a lot of reliable candidate genes to improve deep rooting, and firstly highlight the importance of energy metabolism to the development of deep roots.

  13. Root Transcriptomic Analysis Revealing the Importance of Energy Metabolism to the Development of Deep Roots in Rice (Oryza sativa L.).

    Science.gov (United States)

    Lou, Qiaojun; Chen, Liang; Mei, Hanwei; Xu, Kai; Wei, Haibin; Feng, Fangjun; Li, Tiemei; Pang, Xiaomeng; Shi, Caiping; Luo, Lijun; Zhong, Yang

    2017-01-01

    Drought is the most serious abiotic stress limiting rice production, and deep root is the key contributor to drought avoidance. However, the genetic mechanism regulating the development of deep roots is largely unknown. In this study, the transcriptomes of 74 root samples from 37 rice varieties, representing the extreme genotypes of shallow or deep rooting, were surveyed by RNA-seq. The 13,242 differentially expressed genes (DEGs) between deep rooting and shallow rooting varieties (H vs. L) were enriched in the pathway of genetic information processing and metabolism, while the 1,052 DEGs between the deep roots and shallow roots from each of the plants (D vs. S) were significantly enriched in metabolic pathways especially energy metabolism. Ten quantitative trait transcripts (QTTs) were identified and some were involved in energy metabolism. Forty-nine candidate DEGs were confirmed by qRT-PCR and microarray. Through weighted gene co-expression network analysis (WGCNA), we found 18 hub genes. Surprisingly, all these hub genes expressed higher in deep roots than in shallow roots, furthermore half of them functioned in energy metabolism. We also estimated that the ATP production in the deep roots was faster than shallow roots. Our results provided a lot of reliable candidate genes to improve deep rooting, and firstly highlight the importance of energy metabolism to the development of deep roots.

  14. A comprehensive sensitivity analysis of microarray breast cancer classification under feature variability

    NARCIS (Netherlands)

    Sontrop, H.M.J.; Moerland, P.D.; Van den Ham, R.; Reinders, M.J.T.; Verhaegh, W.F.J.

    2009-01-01

    Background: Large discrepancies in signature composition and outcome concordance have been observed between different microarray breast cancer expression profiling studies. This is often ascribed to differences in array platform as well as biological variability. We conjecture that other reasons for

  15. A comprehensive sensitivity analysis of microarray breast cancer classification under feature variability

    NARCIS (Netherlands)

    Sontrop, Herman M. J.; Moerland, Perry D.; van den Ham, René; Reinders, Marcel J. T.; Verhaegh, Wim F. J.

    2009-01-01

    Large discrepancies in signature composition and outcome concordance have been observed between different microarray breast cancer expression profiling studies. This is often ascribed to differences in array platform as well as biological variability. We conjecture that other reasons for the

  16. Microarray Gene Expression Analysis to Evaluate Cell Type Specific Expression of Targets Relevant for Immunotherapy of Hematological Malignancies.

    Directory of Open Access Journals (Sweden)

    M J Pont

    Full Text Available Cellular immunotherapy has proven to be effective in the treatment of hematological cancers by donor lymphocyte infusion after allogeneic hematopoietic stem cell transplantation and more recently by targeted therapy with chimeric antigen or T-cell receptor-engineered T cells. However, dependent on the tissue distribution of the antigens that are targeted, anti-tumor responses can be accompanied by undesired side effects. Therefore, detailed tissue distribution analysis is essential to estimate potential efficacy and toxicity of candidate targets for immunotherapy of hematological malignancies. We performed microarray gene expression analysis of hematological malignancies of different origins, healthy hematopoietic cells and various non-hematopoietic cell types from organs that are often targeted in detrimental immune responses after allogeneic stem cell transplantation leading to graft-versus-host disease. Non-hematopoietic cells were also cultured in the presence of IFN-γ to analyze gene expression under inflammatory circumstances. Gene expression was investigated by Illumina HT12.0 microarrays and quality control analysis was performed to confirm the cell-type origin and exclude contamination of non-hematopoietic cell samples with peripheral blood cells. Microarray data were validated by quantitative RT-PCR showing strong correlations between both platforms. Detailed gene expression profiles were generated for various minor histocompatibility antigens and B-cell surface antigens to illustrate the value of the microarray dataset to estimate efficacy and toxicity of candidate targets for immunotherapy. In conclusion, our microarray database provides a relevant platform to analyze and select candidate antigens with hematopoietic (lineage-restricted expression as potential targets for immunotherapy of hematological cancers.

  17. Comparative analysis of chrysanthemum transcriptome in response to three RNA viruses: Cucumber mosaic virus, Tomato spotted wilt virus and Potato virus X.

    Science.gov (United States)

    Choi, Hoseong; Jo, Yeonhwa; Lian, Sen; Jo, Kyoung-Min; Chu, Hyosub; Yoon, Ju-Yeon; Choi, Seung-Kook; Kim, Kook-Hyung; Cho, Won Kyong

    2015-06-01

    The chrysanthemum is one of popular flowers in the world and a host for several viruses. So far, molecular interaction studies between the chrysanthemum and viruses are limited. In this study, we carried out a transcriptome analysis of chrysanthemum in response to three different viruses including Cucumber mosaic virus (CMV), Tomato spotted wilt virus (TSWV) and Potato virus X (PVX). A chrysanthemum 135K microarray derived from expressed sequence tags was successfully applied for the expression profiles of the chrysanthemum at early stage of virus infection. Finally, we identified a total of 125, 70 and 124 differentially expressed genes (DEGs) for CMV, TSWV and PVX, respectively. Many DEGs were virus specific; however, 33 DEGs were commonly regulated by three viruses. Gene ontology (GO) enrichment analysis identified a total of 132 GO terms, and of them, six GO terms related stress response and MCM complex were commonly identified for three viruses. Several genes functioning in stress response such as chitin response and ethylene mediated signaling pathway were up-regulated indicating their involvement in establishment of host immune system. In particular, TSWV infection significantly down-regulated genes related to DNA metabolic process including DNA replication, chromatin organization, histone modification and cytokinesis, and they are mostly targeted to nucleosome and MCM complex. Taken together, our comparative transcriptome analysis revealed several genes related to hormone mediated viral stress response and DNA modification. The identified chrysanthemums genes could be good candidates for further functional study associated with resistant to various plant viruses.

  18. Single-cell multiple gene expression analysis based on single-molecule-detection microarray assay for multi-DNA determination

    Energy Technology Data Exchange (ETDEWEB)

    Li, Lu [School of Chemistry and Chemical Engineering, Shandong University, Jinan 250100 (China); Wang, Xianwei [School of Life Sciences, Shandong University, Jinan 250100 (China); Zhang, Xiaoli [School of Chemistry and Chemical Engineering, Shandong University, Jinan 250100 (China); Wang, Jinxing [School of Life Sciences, Shandong University, Jinan 250100 (China); Jin, Wenrui, E-mail: jwr@sdu.edu.cn [School of Chemistry and Chemical Engineering, Shandong University, Jinan 250100 (China)

    2015-01-07

    Highlights: • A single-molecule-detection (SMD) microarray for 10 samples is fabricated. • The based-SMD microarray assay (SMA) can determine 8 DNAs for each sample. • The limit of detection of SMA is as low as 1.3 × 10{sup −16} mol L{sup −1}. • The SMA can be applied in single-cell multiple gene expression analysis. - Abstract: We report a novel ultra-sensitive and high-selective single-molecule-detection microarray assay (SMA) for multiple DNA determination. In the SMA, a capture DNA (DNAc) microarray consisting of 10 subarrays with 9 spots for each subarray is fabricated on a silanized glass coverslip as the substrate. On the subarrays, the spot-to-spot spacing is 500 μm and each spot has a diameter of ∼300 μm. The sequence of the DNAcs on the 9 spots of a subarray is different, to determine 8 types of target DNAs (DNAts). Thus, 8 types of DNAts are captured to their complementary DNAcs at 8 spots of a subarray, respectively, and then labeled with quantum dots (QDs) attached to 8 types of detection DNAs (DNAds) with different sequences. The ninth spot is used to detect the blank value. In order to determine the same 8 types of DNAts in 10 samples, the 10 DNAc-modified subarrays on the microarray are identical. Fluorescence single-molecule images of the QD-labeled DNAts on each spot of the subarray are acquired using a home-made single-molecule microarray reader. The amounts of the DNAts are quantified by counting the bright dots from the QDs. For a microarray, 8 types of DNAts in 10 samples can be quantified in parallel. The limit of detection of the SMA for DNA determination is as low as 1.3 × 10{sup −16} mol L{sup −1}. The SMA for multi-DNA determination can also be applied in single-cell multiple gene expression analysis through quantification of complementary DNAs (cDNAs) corresponding to multiple messenger RNAs (mRNAs) in single cells. To do so, total RNA in single cells is extracted and reversely transcribed into their cDNAs. Three

  19. Microarray analysis in clinical oncology: pre-clinical optimization using needle core biopsies from xenograft tumors

    International Nuclear Information System (INIS)

    Goley, Elizabeth M; Anderson, Soni J; Ménard, Cynthia; Chuang, Eric; Lü, Xing; Tofilon, Philip J; Camphausen, Kevin

    2004-01-01

    labeled, would generate representative array profiles compared to larger excisional biopsy material. In this analysis correlation coefficients were obtained ranging from 0.750–0.834 between U251 biopsy cores and excised tumors, and 0.812–0.846 between DU145 biopsy cores and excised tumors. These data suggest that needle core biopsies can be used as reliable tissue samples for tumor microarray analysis after linear amplification and either indirect or direct labeling of the starting RNA

  20. ATMAD: robust image analysis for Automatic Tissue MicroArray De-arraying.

    Science.gov (United States)

    Nguyen, Hoai Nam; Paveau, Vincent; Cauchois, Cyril; Kervrann, Charles

    2018-04-19

    Over the last two decades, an innovative technology called Tissue Microarray (TMA), which combines multi-tissue and DNA microarray concepts, has been widely used in the field of histology. It consists of a collection of several (up to 1000 or more) tissue samples that are assembled onto a single support - typically a glass slide - according to a design grid (array) layout, in order to allow multiplex analysis by treating numerous samples under identical and standardized conditions. However, during the TMA manufacturing process, the sample positions can be highly distorted from the design grid due to the imprecision when assembling tissue samples and the deformation of the embedding waxes. Consequently, these distortions may lead to severe errors of (histological) assay results when the sample identities are mismatched between the design and its manufactured output. The development of a robust method for de-arraying TMA, which localizes and matches TMA samples with their design grid, is therefore crucial to overcome the bottleneck of this prominent technology. In this paper, we propose an Automatic, fast and robust TMA De-arraying (ATMAD) approach dedicated to images acquired with brightfield and fluorescence microscopes (or scanners). First, tissue samples are localized in the large image by applying a locally adaptive thresholding on the isotropic wavelet transform of the input TMA image. To reduce false detections, a parametric shape model is considered for segmenting ellipse-shaped objects at each detected position. Segmented objects that do not meet the size and the roundness criteria are discarded from the list of tissue samples before being matched with the design grid. Sample matching is performed by estimating the TMA grid deformation under the thin-plate model. Finally, thanks to the estimated deformation, the true tissue samples that were preliminary rejected in the early image processing step are recognized by running a second segmentation step. We

  1. Investigation of cellular signalling responses to non-ionising radiation in melanocytes by microarray analysis

    International Nuclear Information System (INIS)

    Boyle, G.M.; Pedley, J.; Martyn, A.C.; Fraser, L.M.; Banducci, K.J.; Parsons, P.G.; Breit, S.N.

    2003-01-01

    Melanoma is a highly aggressive cancer resulting from the abnormal proliferation and spread of specialised pigment cells in the skin, known as melanocytes. Extensive epidemiological and molecular evidence suggests that a major risk factor for melanoma formation is exposure to non-ionising radiation in the form of solar ultra-violet (UV) light. However, the exact role of solar UV in the development of melanoma is unclear. To elucidate the molecular events that occur in melanocytes following solar UV exposure and determine how they lead to melanoma development, cDNA microarray analysis was used to analyse the gene expression profile of normal melanocytes, melanocytes exposed to simulated solar UV and melanoma cells. The development of cDNA microarray technology has allowed gene expression profiling at the mRNA level to be conducted for many thousands of genes simultaneously by hybridising an array of known sequences with labelled cDNA reverse transcribed form the sample RNA. Gene expression analysis was performed for over 13,000 genes. More than 500 genes were identified as differentially expressed in melanocytes following a single UV exposure, although overall there was a general suppression of transcription. Genes that were up-regulated included oncogenes and cytoskeletal genes; in contrast, genes encoding protein tyrosine kinases and apoptosis effectors were down-regulated. Many of the genes identified as being differentially expressed represent novel UV-regulated targets. Repeated exposure to solar UV resulted in the elevation in expression of a novel member of the transforming growth factor-b (TGF-b) superfamily, the Macrophage Inhibitory Cytokine-1 (MIC-1). Our results have shown that MIC-1 is up-regulated by solar UV in melanocytes, and is highly expressed (>3 fold) in a number of metastatic melanoma cell lines (31/61) in comparison to primary melanocytes. Furthermore functional, dimerised MIC-1 was found to be secreted by melanocytes, and secreted levels were

  2. Mutation Analysis of Consanguineous Moroccan Patients with Parkinson’s Disease Combining Microarray and Gene Panel

    Directory of Open Access Journals (Sweden)

    Ahmed Bouhouche

    2017-10-01

    Full Text Available During the last two decades, 15 different genes have been reported to be responsible for the monogenic form of Parkinson’s disease (PD, representing a worldwide frequency of 5–10%. Among them, 10 genes have been associated with autosomal recessive PD, with PRKN and PINK1 being the most frequent. In a cohort of 145 unrelated Moroccan PD patients enrolled since 2013, 19 patients were born from a consanguineous marriage, of which 15 were isolated cases and 4 familial. One patient was homozygous for the common LRRK2 G2019S mutation and the 18 others who did not carry this mutation were screened for exon rearrangements in the PRKN gene using Affymetrix Cytoscan HD microarray. Two patients were determined homozygous for PRKN exon-deletions, while another patient presented with compound heterozygous inheritance (3/18, 17%. Two other patients showed a region of homozygosity covering the 1p36.12 locus and were sequenced for the candidate PINK1 gene, which revealed two homozygous point mutations: the known Q456X mutation in exon 7 and a novel L539F variation in exon 8. The 13 remaining patients were subjected to next-generation sequencing (NGS that targeted a panel of 22 PD-causing genes and overlapping phenotypes. NGS data showed that two unrelated consanguineous patients with juvenile-onset PD (12 and 13 years carried the same homozygous stop mutation W258X in the ATP13A2 gene, possibly resulting from a founder effect; and one patient with late onset (76 years carried a novel heterozygous frameshift mutation in SYNJ1. Clinical analysis showed that patients with the ATP13A2 mutation developed juvenile-onset PD with a severe phenotype, whereas patients having either PRKN or PINK1 mutations displayed early-onset PD with a relatively mild phenotype. By identifying pathogenic mutations in 45% (8/18 of our consanguineous Moroccan PD series, we demonstrate that the combination of chromosomal microarray analysis and NGS is a powerful approach to

  3. Microarray Data Analysis of Space Grown Arabidopsis Leaves for Genes Important in Vascular Patterning

    Science.gov (United States)

    Weitzeal, A. J.; Wyatt, S. E.; Parsons-Wingerter, P.

    2016-01-01

    Venation patterning in leaves is a major determinant of photosynthesis efficiency because of its dependency on vascular transport of photoassimilates, water, and minerals. Arabidopsis thaliana grown in microgravity show delayed growth and leaf maturation. Gene expression data from the roots, hypocotyl, and leaves of A. thaliana grown during spaceflight vs. ground control analyzed by Affymetrix microarray are available through NASAs GeneLab (GLDS-7). We analyzed the data for differential expression of genes in leaves resulting from the effects of spaceflight on vascular patterning. Two genes were found by preliminary analysis to be upregulated during spaceflight that may be related to vascular formation. The genes are responsible for coding an ARGOS like protein (potentially affecting cell elongation in the leaves), and an F-boxkelch-repeat protein (possibly contributing to protoxylem specification). Further analysis that will focus on raw data quality assessment and a moderated t-test may further confirm upregulation of the two genes and/or identify other gene candidates. Plants defective in these genes will then be assessed for phenotype by the mapping and quantification of leaf vascular patterning by NASAs VESsel GENeration (VESGEN) software to model specific vascular differences of plants grown in spaceflight.

  4. Meta-Analysis of Multiple Sclerosis Microarray Data Reveals Dysregulation in RNA Splicing Regulatory Genes

    Directory of Open Access Journals (Sweden)

    Elvezia Maria Paraboschi

    2015-09-01

    Full Text Available Abnormalities in RNA metabolism and alternative splicing (AS are emerging as important players in complex disease phenotypes. In particular, accumulating evidence suggests the existence of pathogenic links between multiple sclerosis (MS and altered AS, including functional studies showing that an imbalance in alternatively-spliced isoforms may contribute to disease etiology. Here, we tested whether the altered expression of AS-related genes represents a MS-specific signature. A comprehensive comparative analysis of gene expression profiles of publicly-available microarray datasets (190 MS cases, 182 controls, followed by gene-ontology enrichment analysis, highlighted a significant enrichment for differentially-expressed genes involved in RNA metabolism/AS. In detail, a total of 17 genes were found to be differentially expressed in MS in multiple datasets, with CELF1 being dysregulated in five out of seven studies. We confirmed CELF1 downregulation in MS (p = 0.0015 by real-time RT-PCRs on RNA extracted from blood cells of 30 cases and 30 controls. As a proof of concept, we experimentally verified the unbalance in alternatively-spliced isoforms in MS of the NFAT5 gene, a putative CELF1 target. In conclusion, for the first time we provide evidence of a consistent dysregulation of splicing-related genes in MS and we discuss its possible implications in modulating specific AS events in MS susceptibility genes.

  5. DNA microarray global gene expression analysis of influenza virus-infected chicken and duck cells

    Directory of Open Access Journals (Sweden)

    Suresh V. Kuchipudi

    2015-06-01

    Full Text Available The data described in this article pertain to the article by Kuchipudi et al. (2014 titled “Highly Pathogenic Avian Influenza Virus Infection in Chickens But Not Ducks Is Associated with Elevated Host Immune and Pro-inflammatory Responses” [1]. While infection of chickens with highly pathogenic avian influenza (HPAI H5N1 virus subtypes often leads to 100% mortality within 1 to 2 days, infection of ducks in contrast causes mild or no clinical signs. The rapid onset of fatal disease in chickens, but with no evidence of severe clinical symptoms in ducks, suggests underlying differences in their innate immune mechanisms. We used Chicken Genechip microarrays (Affymetrix to analyse the gene expression profiles of primary chicken and duck lung cells infected with a low pathogenic avian influenza (LPAI H2N3 virus and two HPAI H5N1 virus subtypes to understand the molecular basis of host susceptibility and resistance in chickens and ducks. Here, we described the experimental design, quality control and analysis that were performed on the data set. The data are publicly available through the Gene Expression Omnibus (GEOdatabase with accession number GSE33389, and the analysis and interpretation of these data are included in Kuchipudi et al. (2014 [1].

  6. Microarray analysis reveals genetic pathways modulated by tipifarnib in acute myeloid leukemia

    International Nuclear Information System (INIS)

    Raponi, Mitch; Belly, Robert T; Karp, Judith E; Lancet, Jeffrey E; Atkins, David; Wang, Yixin

    2004-01-01

    Farnesyl protein transferase inhibitors (FTIs) were originally developed to inhibit oncogenic ras, however it is now clear that there are several other potential targets for this drug class. The FTI tipifarnib (ZARNESTRA™, R115777) has recently demonstrated clinical responses in adults with refractory and relapsed acute leukemias. This study was conducted to identify genetic markers and pathways that are regulated by tipifarnib in acute myeloid leukemia (AML). Tipifarnib-mediated gene expression changes in 3 AML cell lines and bone marrow samples from two patients with AML were analyzed on a cDNA microarray containing approximately 7000 human genes. Pathways associated with these expression changes were identified using the Ingenuity Pathway Analysis tool. The expression analysis identified a common set of genes that were regulated by tipifarnib in three leukemic cell lines and in leukemic blast cells isolated from two patients who had been treated with tipifarnib. Association of modulated genes with biological functional groups identified several pathways affected by tipifarnib including cell signaling, cytoskeletal organization, immunity, and apoptosis. Gene expression changes were verified in a subset of genes using real time RT-PCR. Additionally, regulation of apoptotic genes was found to correlate with increased Annexin V staining in the THP-1 cell line but not in the HL-60 cell line. The genetic networks derived from these studies illuminate some of the biological pathways affected by FTI treatment while providing a proof of principle for identifying candidate genes that might be used as surrogate biomarkers of drug activity

  7. Microarray analysis of pancreatic gene expression during biotin repletion in biotin-deficient rats.

    Science.gov (United States)

    Dakshinamurti, Krishnamurti; Bagchi, Rushita A; Abrenica, Bernard; Czubryt, Michael P

    2015-12-01

    Biotin is a B vitamin involved in multiple metabolic pathways. In humans, biotin deficiency is relatively rare but can cause dermatitis, alopecia, and perosis. Low biotin levels occur in individuals with type-2 diabetes, and supplementation with biotin plus chromium may improve blood sugar control. The acute effect on pancreatic gene expression of biotin repletion following chronic deficiency is unclear, therefore we induced biotin deficiency in adult male rats by feeding them a 20% raw egg white diet for 6 weeks. Animals were then randomized into 2 groups: one group received a single biotin supplement and returned to normal chow lacking egg white, while the second group remained on the depletion diet. After 1 week, pancreata were removed from biotin-deficient (BD) and biotin-repleted (BR) animals and RNA was isolated for microarray analysis. Biotin depletion altered gene expression in a manner indicative of inflammation, fibrosis, and defective pancreatic function. Conversely, biotin repletion activated numerous repair and anti-inflammatory pathways, reduced fibrotic gene expression, and induced multiple genes involved in pancreatic endocrine and exocrine function. A subset of the results was confirmed by quantitative real-time PCR analysis, as well as by treatment of pancreatic AR42J cells with biotin. The results indicate that biotin repletion, even after lengthy deficiency, results in the rapid induction of repair processes in the pancreas.

  8. Cyclin D1 and Ewing's sarcoma/PNET: A microarray analysis.

    Science.gov (United States)

    Fagone, Paolo; Nicoletti, Ferdinando; Salvatorelli, Lucia; Musumeci, Giuseppe; Magro, Gaetano

    2015-10-01

    Recent immunohistochemical analyses have showed that cyclin D1 is expressed in soft tissue Ewing's sarcoma/peripheral neuroectodermal tumor (PNET) of childhood and adolescents, while it is undetectable in both embryonal and alveolar rhabdomyosarcoma. In the present paper, microarray analysis provided evidence of a significant upregulation of cyclin D1 in Ewing's sarcoma as compared to normal tissues. In addition, we confirmed our previous findings of a significant over-expression of cyclin D1 in Ewing sarcoma as compared to rhabdomyosarcoma. Bioinformatic analysis also allowed to identify some other genes, strongly correlated to cyclin D1, which, although not previously studied in pediatric tumors, could represent novel markers for the diagnosis and prognosis of Ewing's sarcoma/PNET. The data herein provided support not only the use of cyclin D1 as a diagnostic marker of Ewing sarcoma/PNET but also the possibility of using drugs targeting cyclin D1 as potential therapeutic strategies. Copyright © 2015 Elsevier GmbH. All rights reserved.

  9. The use of open source bioinformatics tools to dissect transcriptomic data.

    Science.gov (United States)

    Nitsche, Benjamin M; Ram, Arthur F J; Meyer, Vera

    2012-01-01

    Microarrays are a valuable technology to study fungal physiology on a transcriptomic level. Various microarray platforms are available comprising both single and two channel arrays. Despite different technologies, preprocessing of microarray data generally includes quality control, background correction, normalization, and summarization of probe level data. Subsequently, depending on the experimental design, diverse statistical analysis can be performed, including the identification of differentially expressed genes and the construction of gene coexpression networks.We describe how Bioconductor, a collection of open source and open development packages for the statistical programming language R, can be used for dissecting microarray data. We provide fundamental details that facilitate the process of getting started with R and Bioconductor. Using two publicly available microarray datasets from Aspergillus niger, we give detailed protocols on how to identify differentially expressed genes and how to construct gene coexpression networks.

  10. Analysis of Pigeon (Columba) Ovary Transcriptomes to Identify Genes Involved in Blue Light Regulation

    Science.gov (United States)

    Wang, Ying; Ding, Jia-tong; Yang, Hai-ming; Yan, Zheng-jie; Cao, Wei; Li, Yang-bai

    2015-01-01

    Monochromatic light is widely applied to promote poultry reproductive performance, yet little is currently known regarding the mechanism by which light wavelengths affect pigeon reproduction. Recently, high-throughput sequencing technologies have been used to provide genomic information for solving this problem. In this study, we employed Illumina Hiseq 2000 to identify differentially expressed genes in ovary tissue from pigeons under blue and white light conditions and de novo transcriptome assembly to construct a comprehensive sequence database containing information on the mechanisms of follicle development. A total of 157,774 unigenes (mean length: 790 bp) were obtained by the Trinity program, and 35.83% of these unigenes were matched to genes in a non-redundant protein database. Gene description, gene ontology, and the clustering of orthologous group terms were performed to annotate the transcriptome assembly. Differentially expressed genes between blue and white light conditions included those related to oocyte maturation, hormone biosynthesis, and circadian rhythm. Furthermore, 17,574 SSRs and 533,887 potential SNPs were identified in this transcriptome assembly. This work is the first transcriptome analysis of the Columba ovary using Illumina technology, and the resulting transcriptome and differentially expressed gene data can facilitate further investigations into the molecular mechanism of the effect of blue light on follicle development and reproduction in pigeons and other bird species. PMID:26599806

  11. Analysis of Pigeon (Columba Ovary Transcriptomes to Identify Genes Involved in Blue Light Regulation.

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    Ying Wang

    Full Text Available Monochromatic light is widely applied to promote poultry reproductive performance, yet little is currently known regarding the mechanism by which light wavelengths affect pigeon reproduction. Recently, high-throughput sequencing technologies have been used to provide genomic information for solving this problem. In this study, we employed Illumina Hiseq 2000 to identify differentially expressed genes in ovary tissue from pigeons under blue and white light conditions and de novo transcriptome assembly to construct a comprehensive sequence database containing information on the mechanisms of follicle development. A total of 157,774 unigenes (mean length: 790 bp were obtained by the Trinity program, and 35.83% of these unigenes were matched to genes in a non-redundant protein database. Gene description, gene ontology, and the clustering of orthologous group terms were performed to annotate the transcriptome assembly. Differentially expressed genes between blue and white light conditions included those related to oocyte maturation, hormone biosynthesis, and circadian rhythm. Furthermore, 17,574 SSRs and 533,887 potential SNPs were identified in this transcriptome assembly. This work is the first transcriptome analysis of the Columba ovary using Illumina technology, and the resulting transcriptome and differentially expressed gene data can facilitate further investigations into the molecular mechanism of the effect of blue light on follicle development and reproduction in pigeons and other bird species.

  12. Analysis of gene expression profile microarray data in complex regional pain syndrome.

    Science.gov (United States)

    Tan, Wulin; Song, Yiyan; Mo, Chengqiang; Jiang, Shuangjian; Wang, Zhongxing

    2017-09-01

    The aim of the present study was to predict key genes and proteins associated with complex regional pain syndrome (CRPS) using bioinformatics analysis. The gene expression profiling microarray data, GSE47603, which included peripheral blood samples from 4 patients with CRPS and 5 healthy controls, was obtained from the Gene Expression Omnibus (GEO) database. The differentially expressed genes (DEGs) in CRPS patients compared with healthy controls were identified using the GEO2R online tool. Functional enrichment analysis was then performed using The Database for Annotation Visualization and Integrated Discovery online tool. Protein‑protein interaction (PPI) network analysis was subsequently performed using Search Tool for the Retrieval of Interaction Genes database and analyzed with Cytoscape software. A total of 257 DEGs were identified, including 243 upregulated genes and 14 downregulated ones. Genes in the human leukocyte antigen (HLA) family were most significantly differentially expressed. Enrichment analysis demonstrated that signaling pathways, including immune response, cell motion, adhesion and angiogenesis were associated with CRPS. PPI network analysis revealed that key genes, including early region 1A binding protein p300 (EP300), CREB‑binding protein (CREBBP), signal transducer and activator of transcription (STAT)3, STAT5A and integrin α M were associated with CRPS. The results suggest that the immune response may therefore serve an important role in CRPS development. In addition, genes in the HLA family, such as HLA‑DQB1 and HLA‑DRB1, may present potential biomarkers for the diagnosis of CRPS. Furthermore, EP300, its paralog CREBBP, and the STAT family genes, STAT3 and STAT5 may be important in the development of CRPS.

  13. De novo Assembly and Analysis of the Chilean Pencil Catfish Trichomycterus areolatus Transcriptome

    Science.gov (United States)

    Schulze, Thomas T.; Ali, Jonathan M.; Bartlett, Maggie L.; McFarland, Madalyn M.; Clement, Emalie J.; Won, Harim I.; Sanford, Austin G.; Monzingo, Elyssa B.; Martens, Matthew C.; Hemsley, Ryan M.; Kumar, Sidharta; Gouin, Nicolas; Kolok, Alan S.; Davis, Paul H.

    2016-01-01

    Trichomycterus areolatus is an endemic species of pencil catfish that inhabits the riffles and rapids of many freshwater ecosystems of Chile. Despite its unique adaptation to Chile's high gradient watersheds and therefore potential application in the investigation of ecosystem integrity and environmental contamination, relatively little is known regarding the molecular biology of this environmental sentinel. Here, we detail the assembly of the Trichomycterus areolatus transcriptome, a molecular resource for the study of this organism and its molecular response to the environment. RNA-Seq reads were obtained by next-generation sequencing with an Illumina® platform and processed using PRINSEQ. The transcriptome assembly was performed using TRINITY assembler. Transcriptome validation was performed by functional characterization with KOG, KEGG, and GO analyses. Additionally, differential expression analysis highlights sex-specific expression patterns, and a list of endocrine and oxidative stress related transcripts are included. PMID:27672404

  14. Meta-analysis of Drosophila circadian microarray studies identifies a novel set of rhythmically expressed genes.

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    Kevin P Keegan

    2007-11-01

    Full Text Available Five independent groups have reported microarray studies that identify dozens of rhythmically expressed genes in the fruit fly Drosophila melanogaster. Limited overlap among the lists of discovered genes makes it difficult to determine which, if any, exhibit truly rhythmic patterns of expression. We reanalyzed data from all five reports and found two sources for the observed discrepancies, the use of different expression pattern detection algorithms and underlying variation among the datasets. To improve upon the methods originally employed, we developed a new analysis that involves compilation of all existing data, application of identical transformation and standardization procedures followed by ANOVA-based statistical prescreening, and three separate classes of post hoc analysis: cross-correlation to various cycling waveforms, autocorrelation, and a previously described fast Fourier transform-based technique. Permutation-based statistical tests were used to derive significance measures for all post hoc tests. We find application of our method, most significantly the ANOVA prescreening procedure, significantly reduces the false discovery rate relative to that observed among the results of the original five reports while maintaining desirable statistical power. We identify a set of 81 cycling transcripts previously found in one or more of the original reports as well as a novel set of 133 transcripts not found in any of the original studies. We introduce a novel analysis method that compensates for variability observed among the original five Drosophila circadian array reports. Based on the statistical fidelity of our meta-analysis results, and the results of our initial validation experiments (quantitative RT-PCR, we predict many of our newly found genes to be bona fide cyclers, and suggest that they may lead to new insights into the pathways through which clock mechanisms regulate behavioral rhythms.

  15. Identification of Cell Surface Targets through Meta-analysis of Microarray Data

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    Henry Haeberle

    2012-07-01

    Full Text Available High-resolution image guidance for resection of residual tumor cells would enable more precise and complete excision for more effective treatment of cancers, such as medulloblastoma, the most common pediatric brain cancer. Numerous studies have shown that brain tumor patient outcomes correlate with the precision of resection. To enable guided resection with molecular specificity and cellular resolution, molecular probes that effectively delineate brain tumor boundaries are essential. Therefore, we developed a bioinformatics approach to analyze micro-array datasets for the identification of transcripts that encode candidate cell surface biomarkers that are highly enriched in medulloblastoma. The results identified 380 genes with greater than a two-fold increase in the expression in the medulloblastoma compared with that in the normal cerebellum. To enrich for targets with accessibility for extracellular molecular probes, we further refined this list by filtering it with gene ontology to identify genes with protein localization on, or within, the plasma membrane. To validate this meta-analysis, the top 10 candidates were evaluated with immunohistochemistry. We identified two targets, fibrillin 2 and EphA3, which specifically stain medulloblastoma. These results demonstrate a novel bioinformatics approach that successfully identified cell surface and extracellular candidate markers enriched in medulloblastoma versus adjacent cerebellum. These two proteins are high-value targets for the development of tumor-specific probes in medulloblastoma. This bioinformatics method has broad utility for the identification of accessible molecular targets in a variety of cancers and will enable probe development for guided resection.

  16. Microarray Analysis of Transcriptional Responses to Abscisic Acid and Salt Stress in Arabidopsis thaliana

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    Yucheng Wang

    2013-05-01

    Full Text Available Abscisic acid (ABA plays a crucial role in plant responses to abiotic stress. To investigate differences in plant responses to salt and ABA stimulus, differences in gene expression in Arabidopsis in response to salt and ABA were compared using an Agilent oligo microarray. A total of 144 and 139 genes were significantly up- and downregulated, respectively, under NaCl stress, while 406 and 381 genes were significantly up- and downregulated, respectively, under ABA stress conditions. In addition, 31 genes were upregulated by both NaCl and ABA stresses, and 23 genes were downregulated by these stressors, suggesting that these genes may play similar roles in plant responses to salt and ABA stress. Gene ontology (GO analysis revealed four subgroups of genes, including genes in the GO categories “Molecular transducer activity”, “Growth”, “Biological adhesion” and “Pigmentation”, which were expressed in response to ABA stress but not NaCl stress. In addition, genes that play specific roles during salt or ABA stress were identified. Our results may help elucidate differences in the response of plants to salt and ABA stress.

  17. Microarray Analysis Reveals the Molecular Basis of Antiarthritic Activity of Huo-Luo-Xiao-Ling Dan

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    Hua Yu

    2013-01-01

    Full Text Available Rheumatoid arthritis (RA is a chronic inflammatory disease of autoimmune origin. Huo-luo-xiao-ling dan (HLXL is an herbal mixture that has been used in traditional Chinese medicine over several decades to treat chronic inflammatory diseases including RA. However, the mechanism of the anti-arthritic action of this herbal remedy is poorly understood at the molecular level. In this study, we determined by microarray analysis the effects of HLXL on the global gene expression profile of the draining lymph node cells (LNC in the rat adjuvant arthritis (AA model of human RA. In LNC restimulated in vitro with the disease-related antigen mycobacterial heat-shock protein 65 (Bhsp65, 84 differentially expressed genes (DEG (64 upregulated and 20 downregulated versus 120 DEG (94 upregulated and 26 downregulated were identified in HLXL-treated versus vehicle (Water-treated rats, respectively, and 62 DEG (45 upregulated and 17 downregulated were shared between the two groups. The most affected pathways in response to HLXL treatment included immune response, inflammation, cellular proliferation and apoptosis, and metabolic processes, many of which are directly relevant to arthritis pathogenesis. These results would advance our understanding of the mechanisms underlying the anti-arthritic activity of HLXL.

  18. Hormonal receptors and vascular endothelial growth factor in juvenile nasopharyngeal angiofibroma: immunohistochemical and tissue microarray analysis.

    Science.gov (United States)

    Liu, Zhuofu; Wang, Jingjing; Wang, Huan; Wang, Dehui; Hu, Li; Liu, Quan; Sun, Xicai

    2015-01-01

    This work demonstrated that juvenile nasopharyngeal angiofibromas (JNAs) express high levels of hormone receptors and vascular endothelial growth factor (VEGF) compared with normal nasal mucosa. The interaction between hormone receptors and VEGF may be involved in the initiation and growth of JNA. JNA is a rare benign tumor that occurs almost exclusively in male adolescents. Although generally regarded as a hormone-dependent tumor, this has not been proven in previous studies. The aim of this study was to investigate the role of hormone receptors in JNA and the relationship with clinical characteristics. Standard immunohistochemical microarray analysis was performed on 70 JNA samples and 10 turbinate tissue samples. Specific antibodies for androgen receptor (AR), estrogen receptor-α (ER-α), estrogen receptor-β (ER-β), progesterone receptor (PR), and VEGF were examined, and the relationships of receptor expression with age, tumor stage, and bleeding were evaluated. RESULTS showed that JNA expressed ER-α (92.9%), ER-β (91.4%), AR (65.7%), PR (12.8%), and VEGF (95.7%) at different levels. High level of VEGF was linked to elevated ER-α and ER-β. There was no significant relationship between hormonal receptors and age at diagnosis, tumor stage or bleeding. However, overexpression of ER-α was found to be an indicator of poor prognosis (p = 0.031).

  19. Protective Effect of Gwakhyangjeonggisan Herbal Acupuncture Solution in Glioblastoma Cells: Microarray Analysis of Gene Expression

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    Hong-Seok Lee

    2005-12-01

    Full Text Available Objectives : Neurological disorders have been one of main therapeutic targets of acupuncture. The present study investigated the protective effects of Gwakhyangjeonggisan herbal acupuncture solution (GHAS. Methods : We performed 3-(4,5-dimethylthiazol-2-yl-2,5-diphenyltetrazolium bromide (MTT assay in glioblastoma cells, and did microarray analysis with cells exposed to reactive oxigen species (ROS of hydrogen peroxide by 8.0 k Human cDNA, with cut-off level of 2-fold changes in gene expression. Results : MTT assay showed protective effect of GHAS on the glioblastoma cells exposed to hydrogen peroxide. When glioblastoma cells were exposed to hydrogen peroxide, 24 genes were downregulated. When the cells were pretreated with GHAS before exposure to hydrogen peroxide, 46 genes were downregulated. Many of the genes downregulated by hydrogen peroxide stimulation were decreased in the amount of downregulation or reversed to upregulation. Conclusions : The gene expression changes observed in the present study are supposed to be related to the protective molecular mechanism of GHAS in the glioblastoma cells exposed to ROS stress.

  20. Transcriptomic data analysis and differential gene expression of antioxidant pathways in king penguin juveniles (Aptenodytes patagonicus before and after acclimatization to marine life

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    Benjamin Rey

    2016-12-01

    Full Text Available In this article, we present differentially expressed gene profiles in the pectoralis muscle of wild juvenile king penguins that were either naturally acclimated to cold marine environment or experimentally immersed in cold water as compared with penguin juveniles that never experienced cold water immersion. Transcriptomic data were obtained by hybridizing penguins total cDNA on Affymetrix GeneChip Chicken Genome arrays and analyzed using maxRS algorithm, “Transcriptome analysis in non-model species: a new method for the analysis of heterologous hybridization on microarrays” (Dégletagne et al., 2010 [1]. We focused on genes involved in multiple antioxidant pathways. For better clarity, these differentially expressed genes were clustered into six functional groups according to their role in controlling redox homeostasis. The data are related to a comprehensive research study on the ontogeny of antioxidant functions in king penguins, “Hormetic response triggers multifaceted anti-oxidant strategies in immature king penguins (Aptenodytes patagonicus” (Rey et al., 2016 [2]. The raw microarray dataset supporting the present analyses has been deposited at the Gene Expression Omnibus (GEO repository under accessions GEO: GSE17725 and GEO: GSE82344.

  1. Transcriptome-Wide Identification of Differentially Expressed Genes in Solanum lycopersicon L. in Response to an Alfalfa-Protein Hydrolysate Using Microarrays

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    Andrea Ertani

    2017-07-01

    Full Text Available An alfalfa-based protein hydrolysate (EM has been tested in tomato (Solanum lycopersicon L. plants at two different concentrations (0.1 and 1 mL L-1 to get insight on its efficacy as biostimulant in this species and to unravel possible metabolic targets and molecular mechanisms that may shed light on its mode of action. EM was efficient in promoting the fresh biomass and content in chlorophyll and soluble sugars of tomato plants, especially when it was applied at the concentration of 1 mL L-1. This effect on plant productivity was likely related to the EM-dependent up-regulation of genes identified via microarray and involved in primary carbon and nitrogen metabolism, photosynthesis, nutrient uptake and developmental processes. EM also up-regulated a number of genes implied in the secondary metabolism that leads to the synthesis of compounds (phenols and terpenes functioning in plant development and interaction with the environment. Concomitantly, phenol content was enhanced in EM-treated plants. Several new genes have been identified in tomato as potential targets of EM action, like those involved in detoxification processes from reactive oxygen species and xenobiotic (particularly glutathione/ascorbate cycle-related and ABC transporters, and defense against abiotic and biotic stress. The model hypothesized is that elicitors present in the EM formulation like auxins, phenolics, and amino acids, may trigger a signal transduction pathway via modulation of the intracellular levels of the hormones ethylene, jasmonic acid and abscissic acid, which then further prompt the activation of a cascade events requiring the presence and activity of many kinases and transcription factors to activate stress-related genes. The genes identified suggest these kinases and transcription factors as players involved in a complex crosstalk between biotic and abiotic stress signaling pathways. We conclude that EM acts as a biostimulant in tomato due to its capacity to

  2. Transcriptomic Analysis of Young and Old Erythrocytes of Fish

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    Miriam Götting

    2017-12-01

    Full Text Available Understanding gene expression changes over the lifespan of cells is of fundamental interest and gives important insights into processes related to maturation and aging. This study was undertaken to understand the global transcriptome changes associated with aging in fish erythrocytes. Fish erythrocytes retain their nuclei throughout their lifetime and they are transcriptionally and translationally active. However, they lose important functions during their lifespan in the circulation. We separated rainbow trout (Oncorhynchus mykiss erythrocytes into young and old fractions using fixed angle-centrifugation and analyzed transcriptome changes using RNA sequencing (RNA-seq technology and quantitative real-time PCR. We found 930 differentially expressed between young and old erythrocyte fractions; 889 of these showed higher transcript levels in young, while only 34 protein-coding genes had higher transcript levels in old erythrocytes. In particular genes involved in ion binding, signal transduction, membrane transport, and those encoding various enzyme classes are affected in old erythrocytes. The transcripts with higher levels in old erythrocytes were associated with seven different GO terms within biological processes and nine within molecular functions and cellular components, respectively. Our study furthermore found several highly abundant transcripts as well as a number of differentially expressed genes (DEGs for which the protein products are currently not known revealing the gaps of knowledge in most non-mammalian vertebrates. Our data provide the first insight into changes involved in aging on the transcriptional level and thus opens new perspectives for the study of maturation processes in fish erythrocytes.

  3. Single-Nucleotide Polymorphism-Microarray Ploidy Analysis of Paraffin-Embedded Products of Conception in Recurrent Pregnancy Loss Evaluations.

    Science.gov (United States)

    Maslow, Bat-Sheva L; Budinetz, Tara; Sueldo, Carolina; Anspach, Erica; Engmann, Lawrence; Benadiva, Claudio; Nulsen, John C

    2015-07-01

    To compare the analysis of chromosome number from paraffin-embedded products of conception using single-nucleotide polymorphism (SNP) microarray with the recommended screening for the evaluation of couples presenting with recurrent pregnancy loss who do not have previous fetal cytogenetic data. We performed a retrospective cohort study including all women who presented for a new evaluation of recurrent pregnancy loss over a 2-year period (January 1, 2012, to December 31, 2013). All participants had at least two documented first-trimester losses and both the recommended screening tests and SNP microarray performed on at least one paraffin-embedded products of conception sample. Single-nucleotide polymorphism microarray identifies all 24 chromosomes (22 autosomes, X, and Y). Forty-two women with a total of 178 losses were included in the study. Paraffin-embedded products of conception from 62 losses were sent for SNP microarray. Single-nucleotide polymorphism microarray successfully diagnosed fetal chromosome number in 71% (44/62) of samples, of which 43% (19/44) were euploid and 57% (25/44) were noneuploid. Seven of 42 (17%) participants had abnormalities on recurrent pregnancy loss screening. The per-person detection rate for a cause of pregnancy loss was significantly higher in the SNP microarray (0.50; 95% confidence interval [CI] 0.36-0.64) compared with recurrent pregnancy loss evaluation (0.17; 95% CI 0.08-0.31) (P=.002). Participants with one or more euploid loss identified on paraffin-embedded products of conception were significantly more likely to have an abnormality on recurrent pregnancy loss screening than those with only noneuploid results (P=.028). The significance remained when controlling for age, number of losses, number of samples, and total pregnancies. These results suggest that SNP microarray testing of paraffin-embedded products of conception is a valuable tool for the evaluation of recurrent pregnancy loss in patients without prior fetal

  4. A microarray-based analysis of gametogenesis in two Portuguese populations of the European clam Ruditapes decussatus.

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    Joana Teixeira de Sousa

    Full Text Available The European clam, Ruditapes decussatus is a species with a high commercial importance in Portugal and other Southern European countries. Its production is almost exclusively based on natural recruitment, which is subject to high annual fluctuations. Increased knowledge of the natural reproductive cycle of R. decussatus and its molecular mechanisms would be particularly important in providing new highly valuable genomic information for better understanding the regulation of reproduction in this economically important aquaculture species. In this study, the transcriptomic bases of R. decussatus reproduction have been analysed using a custom oligonucleotide microarray representing 51,678 assembled contigs. Microarray analyses were performed in four gonadal maturation stages from two different Portuguese wild populations, characterized by different responses to spawning induction when used as progenitors in hatchery. A comparison between the two populations elucidated a specific pathway involved in the recognition signals and binding between the oocyte and components of the sperm plasma membrane. We suggest that this pathway can explain part of the differences in terms of spawning induction success between the two populations. In addition, sexes and reproductive stages were compared and a correlation between mRNA levels and gonadal area was investigated. The lists of differentially expressed genes revealed that sex explains most of the variance in gonadal gene expression. Additionally, genes like Foxl2, vitellogenin, condensing 2, mitotic apparatus protein p62, Cep57, sperm associated antigens 6, 16 and 17, motile sperm domain containing protein 2, sperm surface protein Sp17, sperm flagellar proteins 1 and 2 and dpy-30, were identified as being correlated with the gonad area and therefore supposedly with the number and/or the size of the gametes produced.

  5. Comparative transcriptome analysis of biofilm and planktonic cells of Bacillus cereus ATCC 14579

    NARCIS (Netherlands)

    Wijman, Janneke; Mols, M.; Tempelaars, Marcel; Abee, Tjakko

    2015-01-01

    Planktonic and biofilm cells of Bacillus cereus ATCC 14579 and ATCC 10987 were studied using microscopy and transcriptome analysis. By microscopy, clear differences could be observed between biofilm and planktonic cells as well as between the two strains. By using hierarchical clustering of the

  6. Comparative transcriptome analysis of biofilm and planktonic cells of Bacillus cereus ATCC 10987

    NARCIS (Netherlands)

    Wijman, Janneke; Mols, M.; Tempelaars, Marcel; Abee, Tjakko

    2015-01-01

    Planktonic and biofilm cells of Bacillus cereus ATCC 14579 and ATCC 10987 were studied using microscopy and transcriptome analysis. By microscopy, clear differences could be observed between biofilm and planktonic cells as well as between the two strains. By using hierarchical clustering of the

  7. Improving production of ?-lactam antibiotics by Penicillium chrysogenum : Metabolic engineering based on transcriptome analysis

    NARCIS (Netherlands)

    Veiga, T.

    2012-01-01

    In Chapters 2-5 of this thesis, the applicability of transcriptome analysis to guide metabolic engineering strategies in P. chrysogenum is explored by investigating four cellular processes that are of potential relevance for industrial production of ?-lactam antibiotics: - Regulation of secondary

  8. Comparative transcriptomic and metabolomic analysis of fenofibrate and fish oil treatments in mice

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    Lu, Y.; Boekschoten, M.V.; Wopereis, S.; Muller, M.R.; Kersten, A.H.

    2011-01-01

    Elevated circulating triglycerides, which are considered a risk factor for cardiovascular disease, can be targeted by treatment with fenofibrate or fish oil. To gain insight into underlying mechanisms, we carried out a comparative transcriptomics and metabolomics analysis of the effect of 2 wk

  9. Comparative transcriptomics and metabolomic analysis of fenofibrate and fish oil treatments in mice

    NARCIS (Netherlands)

    Lu Yingchang (Kevin), Y.; Boekschoten, Mark; Wopereis, Suzan; Muller, Michael; Kersten, Sander

    2011-01-01

    Elevated circulating triglycerides, which are considered a risk factor for cardiovascular disease, can be targeted by treatment with fenofibrate or fish oil. To gain insight into underlying mechanisms, we carried out a comparative transcriptomics and metabolomics analysis of the effect of 2 week

  10. Meta-Analysis of Microarray Data of Rainbow Trout Fry Gonad Differentiation Modulated by Ethynylestradiol.

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    Sophie Depiereux

    Full Text Available Sex differentiation in fish is a highly labile process easily reversed by the use of exogenous hormonal treatment and has led to environmental concerns since low doses of estrogenic molecules can adversely impact fish reproduction. The goal of this study was to identify pathways altered by treatment with ethynylestradiol (EE2 in developing fish and to find new target genes to be tested further for their possible role in male-to-female sex transdifferentiation. To this end, we have successfully adapted a previously developed bioinformatics workflow to a meta-analysis of two datasets studying sex reversal following exposure to EE2 in juvenile rainbow trout. The meta-analysis consisted of retrieving the intersection of the top gene lists generated for both datasets, performed at different levels of stringency. The intersecting gene lists, enriched in true positive differentially expressed genes (DEGs, were subjected to over-representation analysis (ORA which allowed identifying several statistically significant enriched pathways altered by EE2 treatment and several new candidate pathways, such as progesterone-mediated oocyte maturation and PPAR signalling. Moreover, several relevant key genes potentially implicated in the early transdifferentiation process were selected. Altogether, the results show that EE2 has a great effect on gene expression in juvenile rainbow trout. The feminization process seems to result from the altered transcription of genes implicated in normal female gonad differentiation, resulting in expression similar to that observed in normal females (i.e. the repression of key testicular markers cyp17a1, cyp11b, tbx1, as well as from other genes (including transcription factors that respond specifically to the EE2 treatment. The results also showed that the bioinformatics workflow can be applied to different types of microarray platforms and could be generalized to (ecotoxicogenomics studies for environmental risk assessment

  11. Comparative RNA-Seq and microarray analysis of gene expression changes in B-cell lymphomas of Canis familiaris.

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    Marie Mooney

    Full Text Available Comparative oncology is a developing research discipline that is being used to assist our understanding of human neoplastic diseases. Companion canines are a preferred animal oncology model due to spontaneous tumor development and similarity to human disease at the pathophysiological level. We use a paired RNA sequencing (RNA-Seq/microarray analysis of a set of four normal canine lymph nodes and ten canine lymphoma fine needle aspirates to identify technical biases and variation between the technologies and convergence on biological disease pathways. Surrogate Variable Analysis (SVA provides a formal multivariate analysis of the combined RNA-Seq/microarray data set. Applying SVA to the data allows us to decompose variation into contributions associated with transcript abundance, differences between the technology, and latent variation within each technology. A substantial and highly statistically significant component of the variation reflects transcript abundance, and RNA-Seq appeared more sensitive for detection of transcripts expressed at low levels. Latent random variation among RNA-Seq samples is also distinct in character from that impacting microarray samples. In particular, we observed variation between RNA-Seq samples that reflects transcript GC content. Platform-independent variable decomposition without a priori knowledge of the sources of variation using SVA represents a generalizable method for accomplishing cross-platform data analysis. We identified genes differentially expressed between normal lymph nodes of disease free dogs and a subset of the diseased dogs diagnosed with B-cell lymphoma using each technology. There is statistically significant overlap between the RNA-Seq and microarray sets of differentially expressed genes. Analysis of overlapping genes in the context of biological systems suggests elevated expression and activity of PI3K signaling in B-cell lymphoma biopsies compared with normal biopsies, consistent with

  12. Extending Immunological Profiling in the Gilthead Sea Bream, Sparus aurata, by Enriched cDNA Library Analysis, Microarray Design and Initial Studies upon the Inflammatory Response to PAMPs

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    Sebastian Boltaña

    2017-02-01

    Full Text Available This study describes the development and validation of an enriched oligonucleotide-microarray platform for Sparus aurata (SAQ to provide a platform for transcriptomic studies in this species. A transcriptome database was constructed by assembly of gilthead sea bream sequences derived from public repositories of mRNA together with reads from a large collection of expressed sequence tags (EST from two extensive targeted cDNA libraries characterizing mRNA transcripts regulated by both bacterial and viral challenge. The developed microarray was further validated by analysing monocyte/macrophage activation profiles after challenge with two Gram-negative bacterial pathogen-associated molecular patterns (PAMPs; lipopolysaccharide (LPS and peptidoglycan (PGN. Of the approximately 10,000 EST sequenced, we obtained a total of 6837 EST longer than 100 nt, with 3778 and 3059 EST obtained from the bacterial-primed and from the viral-primed cDNA libraries, respectively. Functional classification of contigs from the bacterial- and viral-primed cDNA libraries by Gene Ontology (GO showed that the top five represented categories were equally represented in the two libraries: metabolism (approximately 24% of the total number of contigs, carrier proteins/membrane transport (approximately 15%, effectors/modulators and cell communication (approximately 11%, nucleoside, nucleotide and nucleic acid metabolism (approximately 7.5% and intracellular transducers/signal transduction (approximately 5%. Transcriptome analyses using this enriched oligonucleotide platform identified differential shifts in the response to PGN and LPS in macrophage-like cells, highlighting responsive gene-cassettes tightly related to PAMP host recognition. As observed in other fish species, PGN is a powerful activator of the inflammatory response in S. aurata macrophage-like cells. We have developed and validated an oligonucleotide microarray (SAQ that provides a platform enriched for the study

  13. Extending Immunological Profiling in the Gilthead Sea Bream, Sparus aurata, by Enriched cDNA Library Analysis, Microarray Design and Initial Studies upon the Inflammatory Response to PAMPs.

    Science.gov (United States)

    Boltaña, Sebastian; Castellana, Barbara; Goetz, Giles; Tort, Lluis; Teles, Mariana; Mulero, Victor; Novoa, Beatriz; Figueras, Antonio; Goetz, Frederick W; Gallardo-Escarate, Cristian; Planas, Josep V; Mackenzie, Simon

    2017-02-03

    This study describes the development and validation of an enriched oligonucleotide-microarray platform for Sparus aurata (SAQ) to provide a platform for transcriptomic studies in this species. A transcriptome database was constructed by assembly of gilthead sea bream sequences derived from public repositories of mRNA together with reads from a large collection of expressed sequence tags (EST) from two extensive targeted cDNA libraries characterizing mRNA transcripts regulated by both bacterial and viral challenge. The developed microarray was further validated by analysing monocyte/macrophage activation profiles after challenge with two Gram-negative bacterial pathogen-associated molecular patterns (PAMPs; lipopolysaccharide (LPS) and peptidoglycan (PGN)). Of the approximately 10,000 EST sequenced, we obtained a total of 6837 EST longer than 100 nt, with 3778 and 3059 EST obtained from the bacterial-primed and from the viral-primed cDNA libraries, respectively. Functional classification of contigs from the bacterial- and viral-primed cDNA libraries by Gene Ontology (GO) showed that the top five represented categories were equally represented in the two libraries: metabolism (approximately 24% of the total number of contigs), carrier proteins/membrane transport (approximately 15%), effectors/modulators and cell communication (approximately 11%), nucleoside, nucleotide and nucleic acid metabolism (approximately 7.5%) and intracellular transducers/signal transduction (approximately 5%). Transcriptome analyses using this enriched oligonucleotide platform identified differential shifts in the response to PGN and LPS in macrophage-like cells, highlighting responsive gene-cassettes tightly related to PAMP host recognition. As observed in other fish species, PGN is a powerful activator of the inflammatory response in S. aurata macrophage-like cells. We have developed and validated an oligonucleotide microarray (SAQ) that provides a platform enriched for the study of gene

  14. Transcriptome analysis in cotton boll weevil (Anthonomus grandis and RNA interference in insect pests.

    Directory of Open Access Journals (Sweden)

    Alexandre Augusto Pereira Firmino

    Full Text Available Cotton plants are subjected to the attack of several insect pests. In Brazil, the cotton boll weevil, Anthonomus grandis, is the most important cotton pest. The use of insecticidal proteins and gene silencing by interference RNA (RNAi as techniques for insect control are promising strategies, which has been applied in the last few years. For this insect, there are not much available molecular information on databases. Using 454-pyrosequencing methodology, the transcriptome of all developmental stages of the insect pest, A. grandis, was analyzed. The A. grandis transcriptome analysis resulted in more than 500.000 reads and a data set of high quality 20,841 contigs. After sequence assembly and annotation, around 10,600 contigs had at least one BLAST hit against NCBI non-redundant protein database and 65.7% was similar to Tribolium castaneum sequences. A comparison of A. grandis, Drosophila melanogaster and Bombyx mori protein families' data showed higher similarity to dipteran than to lepidopteran sequences. Several contigs of genes encoding proteins involved in RNAi mechanism were found. PAZ Domains sequences extracted from the transcriptome showed high similarity and conservation for the most important functional and structural motifs when compared to PAZ Domains from 5 species. Two SID-like contigs were phylogenetically analyzed and grouped with T. castaneum SID-like proteins. No RdRP gene was found. A contig matching chitin synthase 1 was mined from the transcriptome. dsRNA microinjection of a chitin synthase gene to A. grandis female adults resulted in normal oviposition of unviable eggs and malformed alive larvae that were unable to develop in artificial diet. This is the first study that characterizes the transcriptome of the coleopteran, A. grandis. A new and representative transcriptome database for this insect pest is now available. All data support the state of the art of RNAi mechanism in insects.

  15. Transcriptome analysis in cotton boll weevil (Anthonomus grandis) and RNA interference in insect pests.

    Science.gov (United States)

    Firmino, Alexandre Augusto Pereira; Fonseca, Fernando Campos de Assis; de Macedo, Leonardo Lima Pepino; Coelho, Roberta Ramos; Antonino de Souza, José Dijair; Togawa, Roberto Coiti; Silva-Junior, Orzenil Bonfim; Pappas, Georgios Joannis; da Silva, Maria Cristina Mattar; Engler, Gilbert; Grossi-de-Sa, Maria Fatima

    2013-01-01

    Cotton plants are subjected to the attack of several insect pests. In Brazil, the cotton boll weevil, Anthonomus grandis, is the most important cotton pest. The use of insecticidal proteins and gene silencing by interference RNA (RNAi) as techniques for insect control are promising strategies, which has been applied in the last few years. For this insect, there are not much available molecular information on databases. Using 454-pyrosequencing methodology, the transcriptome of all developmental stages of the insect pest, A. grandis, was analyzed. The A. grandis transcriptome analysis resulted in more than 500.000 reads and a data set of high quality 20,841 contigs. After sequence assembly and annotation, around 10,600 contigs had at least one BLAST hit against NCBI non-redundant protein database and 65.7% was similar to Tribolium castaneum sequences. A comparison of A. grandis, Drosophila melanogaster and Bombyx mori protein families' data showed higher similarity to dipteran than to lepidopteran sequences. Several contigs of genes encoding proteins involved in RNAi mechanism were found. PAZ Domains sequences extracted from the transcriptome showed high similarity and conservation for the most important functional and structural motifs when compared to PAZ Domains from 5 species. Two SID-like contigs were phylogenetically analyzed and grouped with T. castaneum SID-like proteins. No RdRP gene was found. A contig matching chitin synthase 1 was mined from the transcriptome. dsRNA microinjection of a chitin synthase gene to A. grandis female adults resulted in normal oviposition of unviable eggs and malformed alive larvae that were unable to develop in artificial diet. This is the first study that characterizes the transcriptome of the coleopteran, A. grandis. A new and representative transcriptome database for this insect pest is now available. All data support the state of the art of RNAi mechanism in insects.

  16. Quantitative miRNA expression analysis: comparing microarrays with next-generation sequencing

    DEFF Research Database (Denmark)

    Willenbrock, Hanni; Salomon, Jesper; Søkilde, Rolf

    2009-01-01

    Recently, next-generation sequencing has been introduced as a promising, new platform for assessing the copy number of transcripts, while the existing microarray technology is considered less reliable for absolute, quantitative expression measurements. Nonetheless, so far, results from the two...... technologies have only been compared based on biological data, leading to the conclusion that, although they are somewhat correlated, expression values differ significantly. Here, we use synthetic RNA samples, resembling human microRNA samples, to find that microarray expression measures actually correlate...... better with sample RNA content than expression measures obtained from sequencing data. In addition, microarrays appear highly sensitive and perform equivalently to next-generation sequencing in terms of reproducibility and relative ratio quantification....

  17. Microarray analysis reveals key genes and pathways in Tetralogy of Fallot

    Science.gov (United States)

    He, Yue-E; Qiu, Hui-Xian; Jiang, Jian-Bing; Wu, Rong-Zhou; Xiang, Ru-Lian; Zhang, Yuan-Hai

    2017-01-01

    The aim of the present study was to identify key genes that may be involved in the pathogenesis of Tetralogy of Fallot (TOF) using bioinformatics methods. The GSE26125 microarray dataset, which includes cardiovascular tissue samples derived from 16 children with TOF and five healthy age-matched control infants, was downloaded from the Gene Expression Omnibus database. Differential expression analysis was performed between TOF and control samples to identify differentially expressed genes (DEGs) using Student's t-test, and the R/limma package, with a log2 fold-change of >2 and a false discovery rate of <0.01 set as thresholds. The biological functions of DEGs were analyzed using the ToppGene database. The ReactomeFIViz application was used to construct functional interaction (FI) networks, and the genes in each module were subjected to pathway enrichment analysis. The iRegulon plugin was used to identify transcription factors predicted to regulate the DEGs in the FI network, and the gene-transcription factor pairs were then visualized using Cytoscape software. A total of 878 DEGs were identified, including 848 upregulated genes and 30 downregulated genes. The gene FI network contained seven function modules, which were all comprised of upregulated genes. Genes enriched in Module 1 were enriched in the following three neurological disorder-associated signaling pathways: Parkinson's disease, Alzheimer's disease and Huntington's disease. Genes in Modules 0, 3 and 5 were dominantly enriched in pathways associated with ribosomes and protein translation. The Xbox binding protein 1 transcription factor was demonstrated to be involved in the regulation of genes encoding the subunits of cytoplasmic and mitochondrial ribosomes, as well as genes involved in neurodegenerative disorders. Therefore, dysfunction of genes involved in signaling pathways associated with neurodegenerative disorders, ribosome function and protein translation may contribute to the pathogenesis of TOF

  18. Comparative analysis of human conjunctival and corneal epithelial gene expression with oligonucleotide microarrays.

    Science.gov (United States)

    Turner, Helen C; Budak, Murat T; Akinci, M A Murat; Wolosin, J Mario

    2007-05-01

    To determine global mRNA expression levels in corneal and conjunctival epithelia and identify transcripts that exhibit preferential tissue expression. cDNA samples derived from human conjunctival and corneal epithelia were hybridized in three independent experiments to a commercial oligonucleotide array representing more than 22,000 transcripts. The resultant signal intensities and microarray software transcript present/absent calls were used in conjunction with the local pooled error (LPE) statistical method to identify transcripts that are preferentially or exclusively expressed in one of the two tissues at significant levels (expression >1% of the beta-actin level). EASE (Expression Analysis Systematic Explorer software) was used to identify biological systems comparatively overrepresented in either epithelium. Immuno-, and cytohistochemistry was performed to validate or expand on selected results of interest. The analysis identified 332 preferential and 93 exclusive significant corneal epithelial transcripts. The corresponding numbers of conjunctival epithelium transcripts were 592 and 211, respectively. The overrepresented biological processes in the cornea were related to cell adhesion and oxiredox equilibria and cytoprotection activities. In the conjunctiva, the biological processes that were most prominent were related to innate immunity and melanogenesis. Immunohistochemistry for antigen-presenting cells and melanocytes was consistent with these gene signatures. The transcript comparison identified a substantial number of genes that have either not been identified previously or are not known to be highly expressed in these two epithelia, including testican-1, ECM1, formin, CRTAC1, and NQO1 in the cornea and, in the conjunctiva, sPLA(2)-IIA, lipocalin 2, IGFBP3, multiple MCH class II proteins, and the Na-Pi cotransporter type IIb. Comparative gene expression profiling leads to the identification of many biological processes and previously unknown genes that

  19. Trait specific expression profiling of salt stress responsive genes in diverse rice genotypes as determined by modified Significance Analysis of Microarrays

    Directory of Open Access Journals (Sweden)

    Mohammad Rashed Hossain

    2016-05-01

    Full Text Available Stress responsive gene expression is commonly profiled in a comparative manner involving different stress conditions or genotypes with contrasting reputation of tolerance/resistance. In contrast, this research exploited a wide natural variation in terms of taxonomy, origin and salt sensitivity in eight genotypes of rice to identify the trait specific patterns of gene expression under salt stress. Genome wide transcptomic responses were interrogated by the weighted continuous morpho-physiological trait responses using modified Significance Analysis of Microarrays. More number of genes was found to be differentially expressed under salt stressed compared to that of under unstressed conditions. Higher numbers of genes were observed to be differentially expressed for the traits shoot Na+/K+, shoot Na+, root K+, biomass and shoot Cl-, respectively. The results identified around sixty genes to be involved in Na+, K+ and anion homeostasis, transport and transmembrane activity under stressed conditions. Gene Ontology (GO enrichment analysis identified 1.36% (578 genes of the entire transcriptome to be involved in the major molecular functions such as signal transduction (>150 genes, transcription factor (81 genes and translation factor activity (62 genes etc. under salt stress. Chromosomal mapping of the genes suggests that majority of the genes are located on chromosomes 1, 2, 3, 6 & 7. The gene network analysis showed that the transcription factors and translation initiation factors formed the major gene networks and are mostly active in nucleus, cytoplasm and mitochondria whereas the membrane and vesicle bound proteins formed a secondary network active in plasma membrane and vacuoles. The novel genes and the genes with unknown functions thus identified provide picture of a synergistic salinity response representing the potentially fundamental mechanisms that are active in the wide natural genetic background of rice and will be of greater use once

  20. Transcriptome Analysis and Comparison of Marmota monax and Marmota himalayana.

    Directory of Open Access Journals (Sweden)

    Yanan Liu

    Full Text Available The Eastern woodchuck (Marmota monax is a classical animal model for studying hepatitis B virus (HBV infection and hepatocellular carcinoma (HCC in humans. Recently, we found that Marmota himalayana, an Asian animal species closely related to Marmota monax, is susceptible to woodchuck hepatitis virus (WHV infection and can be used as a new mammalian model for HBV infection. However, the lack of genomic sequence information of both Marmota models strongly limited their application breadth and depth. To address this major obstacle of the Marmota models, we utilized Illumina RNA-Seq technology to sequence the cDNA libraries of liver and spleen samples of two Marmota monax and four Marmota himalayana. In total, over 13 billion nucleotide bases were sequenced and approximately 1.5 billion clean reads were obtained. Following assembly, 106,496 consensus sequences of Marmota monax and 78,483 consensus sequences of Marmota himalayana were detected. For functional annotation, in total 73,603 Unigenes of Marmota monax and 78,483 Unigenes of Marmota himalayana were identified using different databases (NR, NT, Swiss-Prot, KEGG, COG, GO. The Unigenes were aligned by blastx to protein databases to decide the coding DNA sequences (CDS and in total 41,247 CDS of Marmota monax and 34,033 CDS of Marmota himalayana were predicted. The single nucleotide polymorphisms (SNPs and the simple sequence repeats (SSRs were also analyzed for all Unigenes obtained. Moreover, a large-scale transcriptome comparison was performed and revealed a high similarity in transcriptome sequences between the two marmota species. Our study provides an extensive amount of novel sequence information for Marmota monax and Marmota himalayana. This information may serve as a valuable genomics resource for further molecular, developmental and comparative evolutionary studies, as well as for the identification and characterization of functional genes that are involved in WHV infection and HCC

  1. Comparative analysis of transcriptomic responses to repeated-dose exposure to 2-MCPD and 3-MCPD in rat kidney, liver and testis.

    Science.gov (United States)

    Buhrke, Thorsten; Schultrich, Katharina; Braeuning, Albert; Lampen, Alfonso

    2017-08-01

    3-Chloro-1,2-propanediol (3-MCPD) and its isomer 2-chloro-1,3-propanediol (2-MCPD) are heat-induced food contaminants present in oil- and fat-containing foodstuff. Kidney and testes are among the main target organs of 3-MCPD. Almost no data on 2-MCPD toxicity are available. Here, transcriptomic responses following repeated-dose exposure of rats to non-toxic doses of 10 mg/kg body weight per day 2-MCPD or 3-MCPD for 28 days were characterized by microarray analysis of kidney, liver, and testes. 3-MCPD exerted more pronounced effects than 2-MCPD in all organs. The limited overlap between the datasets indicates that 2-MCPD and 3-MCPD do not share the same molecular mechanisms of toxicity. By combining transcriptomic data with datasets on proteomic regulation by 3-MCPD, a comprehensive view on 3-MCPD-induced regulation of glucose utilization and oxidative stress response was developed. Bioinformatic analyses revealed that Nrf2 (nuclear factor (erythroid-derived 2)-like 2) signaling is likely to be involved in mediating the oxidative stress response to 3-MCPD. In summary, this study for the first time presents data on alterations in global gene expression by two important food contaminants, 2-MCPD and 3-MCPD. Data demonstrate profound differences between the effects of the two compounds and substantially broaden our knowledge on molecular details of 3-MCPD-induced disturbance of glucose utilization and redox balance. Copyright © 2017 Elsevier Ltd. All rights reserved.

  2. RNA Microarray Analysis of Macroscopically Normal Articular Cartilage from Knees Undergoing Partial Medial Meniscectomy: Potential Prediction of the Risk for Developing Osteoarthritis.

    Directory of Open Access Journals (Sweden)

    Muhammad Farooq Rai

    Full Text Available (i To provide baseline knowledge of gene expression in macroscopically normal articular cartilage, (ii to test the hypothesis that age, body-mass-index (BMI, and sex are associated with cartilage RNA transcriptome, and (iii to predict individuals at potential risk for developing "pre-osteoarthritis" (OA based on screening of genetic risk-alleles associated with OA and gene transcripts differentially expressed between normal and OA cartilage.Healthy-appearing cartilage was obtained from the medial femoral notch of 12 knees with a meniscus tear undergoing arthroscopic partial meniscectomy. Cartilage had no radiographic, magnetic-resonance-imaging or arthroscopic evidence for degeneration. RNA was subjected to Affymetrix microarrays followed by validation of selected transcripts by microfluidic digital polymerase-chain-reaction. The underlying biological processes were explored computationally. Transcriptome-wide gene expression was probed for association with known OA genetic risk-alleles assembled from published literature and for comparison with gene transcripts differentially expressed between healthy and OA cartilage from other studies.We generated a list of 27,641 gene transcripts in healthy cartilage. Several gene transcripts representing numerous biological processes were correlated with age and BMI and differentially expressed by sex. Based on disease-specific Ingenuity Pathways Analysis, gene transcripts associated with aging were enriched for bone/cartilage disease while the gene expression profile associated with BMI was enriched for growth-plate calcification and OA. When segregated by genetic risk-alleles, two clusters of study patients emerged, one cluster containing transcripts predicted by risk studies. When segregated by OA-associated gene transcripts, three clusters of study patients emerged, one of which is remarkably similar to gene expression pattern in OA.Our study provides a list of gene transcripts in healthy

  3. Aligning ontologies and integrating textual evidence for pathway analysis of microarray data

    Energy Technology Data Exchange (ETDEWEB)

    Gopalan, Banu; Posse, Christian; Sanfilippo, Antonio P.; Stenzel-Poore, Mary; Stevens, S.L.; Castano, Jose; Beagley, Nathaniel; Riensche, Roderick M.; Baddeley, Bob; Simon, R.P.; Pustejovsky, James

    2006-10-08

    Expression arrays are introducing a paradigmatic change in biology by shifting experimental approaches from single gene studies to genome-level analysis, monitoring the ex-pression levels of several thousands of genes in parallel. The massive amounts of data obtained from the microarray data needs to be integrated and interpreted to infer biological meaning within the context of information-rich pathways. In this paper, we present a methodology that integrates textual information with annotations from cross-referenced ontolo-gies to map genes to pathways in a semi-automated way. We illustrate this approach and compare it favorably to other tools by analyzing the gene expression changes underlying the biological phenomena related to stroke. Stroke is the third leading cause of death and a major disabler in the United States. Through years of study, researchers have amassed a significant knowledge base about stroke, and this knowledge, coupled with new technologies, is providing a wealth of new scientific opportunities. The potential for neu-roprotective stroke therapy is enormous. However, the roles of neurogenesis, angiogenesis, and other proliferative re-sponses in the recovery process following ischemia and the molecular mechanisms that lead to these processes still need to be uncovered. Improved annotation of genomic and pro-teomic data, including annotation of pathways in which genes and proteins are involved, is required to facilitate their interpretation and clinical application. While our approach is not aimed at replacing existing curated pathway databases, it reveals multiple hidden relationships that are not evident with the way these databases analyze functional groupings of genes from the Gene Ontology.

  4. Crowdsourcing for translational research: analysis of biomarker expression using cancer microarrays.

    Science.gov (United States)

    Lawson, Jonathan; Robinson-Vyas, Rupesh J; McQuillan, Janette P; Paterson, Andy; Christie, Sarah; Kidza-Griffiths, Matthew; McDuffus, Leigh-Anne; Moutasim, Karwan A; Shaw, Emily C; Kiltie, Anne E; Howat, William J; Hanby, Andrew M; Thomas, Gareth J; Smittenaar, Peter

    2017-01-17

    Academic pathology suffers from an acute and growing lack of workforce resource. This especially impacts on translational elements of clinical trials, which can require detailed analysis of thousands of tissue samples. We tested whether crowdsourcing - enlisting help from the public - is a sufficiently accurate method to score such samples. We developed a novel online interface to train and test lay participants on cancer detection and immunohistochemistry scoring in tissue microarrays. Lay participants initially performed cancer detection on lung cancer images stained for CD8, and we measured how extending a basic tutorial by annotated example images and feedback-based training affected cancer detection accuracy. We then applied this tutorial to additional cancer types and immunohistochemistry markers - bladder/ki67, lung/EGFR, and oesophageal/CD8 - to establish accuracy compared with experts. Using this optimised tutorial, we then tested lay participants' accuracy on immunohistochemistry scoring of lung/EGFR and bladder/p53 samples. We observed that for cancer detection, annotated example images and feedback-based training both improved accuracy compared with a basic tutorial only. Using this optimised tutorial, we demonstrate highly accurate (>0.90 area under curve) detection of cancer in samples stained with nuclear, cytoplasmic and membrane cell markers. We also observed high Spearman correlations between lay participants and experts for immunohistochemistry scoring (0.91 (0.78, 0.96) and 0.97 (0.91, 0.99) for lung/EGFR and bladder/p53 samples, respectively). These results establish crowdsourcing as a promising method to screen large data sets for biomarkers in cancer pathology research across a range of cancers and immunohistochemical stains.

  5. Grating coupled SPR microarray analysis of proteins and cells in blood from mice with breast cancer.

    Science.gov (United States)

    Mendoza, A; Torrisi, D M; Sell, S; Cady, N C; Lawrence, D A

    2016-01-21

    Biomarker discovery for early disease diagnosis is highly important. Of late, much effort has been made to analyze complex biological fluids in an effort to develop new markers specific for different cancer types. Recent advancements in label-free technologies such as surface plasmon resonance (SPR)-based biosensors have shown promise as a diagnostic tool since there is no need for labeling or separation of cells. Furthermore, SPR can provide rapid, real-time detection of antigens from biological samples since SPR is highly sensitive to changes in surface-associated molecular and cellular interactions. Herein, we report a lab-on-a-chip microarray biosensor that utilizes grating-coupled surface plasmon resonance (GCSPR) and grating-coupled surface plasmon coupled fluorescence (GCSPCF) imaging to detect circulating tumor cells (CTCs) from a mouse model (FVB-MMTV-PyVT). GCSPR and GCSPCF analysis was accomplished by spotting antibodies to surface cell markers, cytokines and stress proteins on a nanofabricated GCSPR microchip and screening blood samples from FVB control mice or FVB-MMTV-PyVT mice with developing mammary carcinomas. A transgenic MMTV-PyVT mouse derived cancer cell line was also analyzed. The analyses indicated that CD24, CD44, CD326, CD133 and CD49b were expressed in both cell lines and in blood from MMTV-PyVT mice. Furthermore, cytokines such as IL-6, IL-10 and TNF-α, along with heat shock proteins HSP60, HSP27, HSc70(HSP73), HSP90 total, HSP70/HSc70, HSP90, HSP70, HSP90 alpha, phosphotyrosine and HSF-1 were overexpressed in MMTV-PyVT mice.

  6. Microarray analysis of gene expression alteration in human middle ear epithelial cells induced by micro particle.

    Science.gov (United States)

    Song, Jae-Jun; Kwon, Jee Young; Park, Moo Kyun; Seo, Young Rok

    2013-10-01

    The primary aim of this study is to reveal the effect of particulate matter (PM) on the human middle ear epithelial cell (HMEEC). The HMEEC was treated with PM (300 μg/ml) for 24 h. Total RNA was extracted and used for microarray analysis. Molecular pathways among differentially expressed genes were further analyzed by using Pathway Studio 9.0 software. For selected genes, the changes in gene expression were confirmed by real-time PCR. A total of 611 genes were regulated by PM. Among them, 366 genes were up-regulated, whereas 245 genes were down-regulated. Up-regulated genes were mainly involved in cellular processes, including reactive oxygen species generation, cell proliferation, apoptosis, cell differentiation, inflammatory response and immune response. Down-regulated genes affected several cellular processes, including cell differentiation, cell cycle, proliferation, apoptosis and cell migration. A total of 21 genes were discovered as crucial components in potential signaling networks containing 2-fold up regulated genes. Four genes, VEGFA, IL1B, CSF2 and HMOX1 were revealed as key mediator genes among the up-regulated genes. A total of 25 genes were revealed as key modulators in the signaling pathway associated with 2-fold down regulated genes. Four genes, including IGF1R, TIMP1, IL6 and FN1, were identified as the main modulator genes. We identified the differentially expressed genes in PM-treated HMEEC, whose expression profile may provide a useful clue for the understanding of environmental pathophysiology of otitis media. Our work indicates that air pollution, like PM, plays an important role in the pathogenesis of otitis media. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

  7. Microarray Cluster Analysis of Irradiated Growth Plate Zones Following Laser Microdissection

    International Nuclear Information System (INIS)

    Damron, Timothy A.; Zhang Mingliang; Pritchard, Meredith R.; Middleton, Frank A.; Horton, Jason A.; Margulies, Bryan M.; Strauss, Judith A.; Farnum, Cornelia E.; Spadaro, Joseph A.

    2009-01-01

    Purpose: Genes and pathways involved in early growth plate chondrocyte recovery after fractionated irradiation were sought as potential targets for selective radiorecovery modulation. Materials and Methods: Three groups of six 5-week male Sprague-Dawley rats underwent fractionated irradiation to the right tibiae over 5 days, totaling 17.5 Gy, and then were killed at 7, 11, and 16 days after the first radiotherapy fraction. The growth plates were collected from the proximal tibiae bilaterally and subsequently underwent laser microdissection to separate reserve, perichondral, proliferative, and hypertrophic zones. Differential gene expression was analyzed between irradiated right and nonirradiated left tibia using RAE230 2.0 GeneChip microarray, compared between zones and time points and subjected to functional pathway cluster analysis with real-time polymerase chain reaction to confirm selected results. Results: Each zone had a number of pathways showing enrichment after the pattern of hypothesized importance to growth plate recovery, yet few met the strictest criteria. The proliferative and hypertrophic zones showed both the greatest number of genes with a 10-fold right/left change at 7 days after initiation of irradiation and enrichment of the most functional pathways involved in bone, cartilage, matrix, or skeletal development. Six genes confirmed by real-time polymerase chain reaction to have early upregulation included insulin-like growth factor 2, procollagen type I alpha 2, matrix metallopeptidase 9, parathyroid hormone receptor 1, fibromodulin, and aggrecan 1. Conclusions: Nine overlapping pathways in the proliferative and hypertrophic zones (skeletal development, ossification, bone remodeling, cartilage development, extracellular matrix structural constituent, proteinaceous extracellular matrix, collagen, extracellular matrix, and extracellular matrix part) may play key roles in early growth plate radiorecovery.

  8. Molecular sub-classification of renal epithelial tumors using meta-analysis of gene expression microarrays.

    Directory of Open Access Journals (Sweden)

    Thomas Sanford

    Full Text Available To evaluate the accuracy of the sub-classification of renal cortical neoplasms using molecular signatures.A search of publicly available databases was performed to identify microarray datasets with multiple histologic sub-types of renal cortical neoplasms. Meta-analytic techniques were utilized to identify differentially expressed genes for each histologic subtype. The lists of genes obtained from the meta-analysis were used to create predictive signatures through the use of a pair-based method. These signatures were organized into an algorithm to sub-classify renal neoplasms. The use of these signatures according to our algorithm was validated on several independent datasets.We identified three Gene Expression Omnibus datasets that fit our criteria to develop a training set. All of the datasets in our study utilized the Affymetrix platform. The final training dataset included 149 samples represented by the four most common histologic subtypes of renal cortical neoplasms: 69 clear cell, 41 papillary, 16 chromophobe, and 23 oncocytomas. When validation of our signatures was performed on external datasets, we were able to correctly classify 68 of the 72 samples (94%. The correct classification by subtype was 19/20 (95% for clear cell, 14/14 (100% for papillary, 17/19 (89% for chromophobe, 18/19 (95% for oncocytomas.Through the use of meta-analytic techniques, we were able to create an algorithm that sub-classified renal neoplasms on a molecular level with 94% accuracy across multiple independent datasets. This algorithm may aid in selecting molecular therapies and may improve the accuracy of subtyping of renal cortical tumors.

  9. Transcriptome Analysis of Barbarea vulgaris Infested with Diamondback Moth (Plutella xylostella) Larvae

    Science.gov (United States)

    Shen, Di; Wang, Haiping; Wu, Qingjun; Lu, Peng; Qiu, Yang; Song, Jiangping; Zhang, Youjun; Li, Xixiang

    2013-01-01

    Background The diamondback moth (DBM, Plutella xylostella) is a crucifer-specific pest that causes significant crop losses worldwide. Barbarea vulgaris (Brassicaceae) can resist DBM and other herbivorous insects by producing feeding-deterrent triterpenoid saponins. Plant breeders have long aimed to transfer this insect resistance to other crops. However, a lack of knowledge on the biosynthetic pathways and regulatory networks of these insecticidal saponins has hindered their practical application. A pyrosequencing-based transcriptome analysis of B. vulgaris during DBM larval feeding was performed to identify genes and gene networks responsible for saponin biosynthesis and its regulation at the genome level. Principal Findings Approximately 1.22, 1.19, 1.16, 1.23, 1.16, 1.20, and 2.39 giga base pairs of clean nucleotides were generated from B. vulgaris transcriptomes sampled 1, 4, 8, 12, 24, and 48 h after onset of P. xylostella feeding and from non-inoculated controls, respectively. De novo assembly using all data of the seven transcriptomes generated 39,531 unigenes. A total of 37,780 (95.57%) unigenes were annotated, 14,399 of which were assigned to one or more gene ontology terms and 19,620 of which were assigned to 126 known pathways. Expression profiles revealed 2,016–4,685 up-regulated and 557–5188 down-regulated transcripts. Secondary metabolic pathways, such as those of terpenoids, glucosinolates, and phenylpropanoids, and its related regulators were elevated. Candidate genes for the triterpene saponin pathway were found in the transcriptome. Orthological analysis of the transcriptome with four other crucifer transcriptomes identified 592 B. vulgaris-specific gene families with a P-value cutoff of 1e−5. Conclusion This study presents the first comprehensive transcriptome analysis of B. vulgaris subjected to a series of DBM feedings. The biosynthetic and regulatory pathways of triterpenoid saponins and other DBM deterrent metabolites in this plant were

  10. Sexual dimorphism and ageing in the human hyppocampus: Identification, validation and impact of differentially expressed genes by factorial microarray and network analysis

    Directory of Open Access Journals (Sweden)

    Daniel Victor Guebel

    2016-10-01

    Full Text Available Motivation: In the brain of elderly-healthy individuals, the effects of sexual dimorphism and those due to normal ageing appear overlapped. Discrimination of these two dimensions would powerfully contribute to a better understanding of the aetiology of some neurodegenerative diseases, such as sporadic Alzheimer. Methods: Following a system biology approach, top-down and bottom-up strategies were combined. First, public transcriptome data corresponding to the transition from adulthood to the ageing stage in normal, human hippocampus were analysed through an optimized microarray post-processing (Q-GDEMAR method together with a proper experimental design (full factorial analysis. Second, the identified genes were placed in context by building compatible networks. The subsequent ontology analyses carried out on these networks clarify the main functionalities involved. Results: Noticeably we could identify large sets of genes according to three groups: those that exclusively depend on the sex, those that exclusively depend on the age, and those that depend on the particular combinations of sex and age (interaction. The genes identified were validated against three independent sources (a proteomic study of ageing, a senescence database, and a mitochondrial genetic database. We arrived to several new inferences about the biological functions compromised during ageing in two ways: by taking into account the sex-independent effects of ageing, and considering the interaction between age and sex where pertinent. In particular, we discuss the impact of our findings on the functions of mitochondria, autophagy, mitophagia, and microRNAs.Conclusions: The evidence obtained herein supports the occurrence of significant neurobiological differences in the hippocampus, not only between adult and elderly individuals, but between old-healthy women and old-healthy men. Hence, to obtain realistic results in further analysis of the transition from the normal ageing to

  11. 16S rRNA based microarray analysis of ten periodontal bacteria in patients with different forms of periodontitis.

    Science.gov (United States)

    Topcuoglu, Nursen; Kulekci, Guven

    2015-10-01

    DNA microarray analysis is a computer based technology, that a reverse capture, which targets 10 periodontal bacteria (ParoCheck) is available for rapid semi-quantitative determination. The aim of this three-year retrospective study was to display the microarray analysis results for the subgingival biofilm samples taken from patient cases diagnosed with different forms of periodontitis. A total of 84 patients with generalized aggressive periodontitis (GAP,n:29), generalized chronic periodontitis (GCP, n:25), peri-implantitis (PI,n:14), localized aggressive periodontitis (LAP,n:8) and refractory chronic periodontitis (RP,n:8) were consecutively selected from the archives of the Oral Microbiological Diagnostic Laboratory. The subgingival biofilm samples were analyzed by the microarray-based identification of 10 selected species. All the tested species were detected in the samples. The red complex bacteria were the most prevalent with very high levels in all groups. Fusobacterium nucleatum was detected in all samples at high levels. The green and blue complex bacteria were less prevalent compared with red and orange complex, except Aggregatibacter actinomycetemcomitas was detected in all LAP group. Positive correlations were found within all the red complex bacteria and between red and orange complex bacteria especially in GCP and GAP groups. Parocheck enables to monitoring of periodontal pathogens in all forms of periodontal disease and can be alternative to other guiding and reliable microbiologic tests. Copyright © 2015 Elsevier Ltd. All rights reserved.

  12. Extending the scope of diagnostic chromosome analysis: detection of single gene defects using high-resolution SNP microarrays.

    Science.gov (United States)

    Bruno, Damien L; Stark, Zornitza; Amor, David J; Burgess, Trent; Butler, Kathy; Corrie, Sylvea; Francis, David; Ganesamoorthy, Devika; Hills, Louise; James, Paul A; O'Rielly, Darren; Oertel, Ralph; Savarirayan, Ravi; Prabhakara, Krishnamurthy; Salce, Nicholas; Slater, Howard R

    2011-12-01

    Microarray analysis has provided significant advances in the diagnosis of conditions resulting from submicroscopic chromosome abnormalities. It has been recommended that array testing should be a "first tier" test in the evaluation of individuals with intellectual disability, developmental delay, congenital anomalies, and autism. The availability of arrays with increasingly high probe coverage and resolution has increased the detection of decreasingly small copy number changes (CNCs) down to the intragenic or even exon level. Importantly, arrays that genotype SNPs also detect extended regions of homozygosity. We describe 14 examples of single gene disorders caused by intragenic changes from a consecutive set of 6,500 tests using high-resolution SNP microarrays. These cases illustrate the increased scope of cytogenetic testing beyond dominant chromosome rearrangements that typically contain many genes. Nine of the cases confirmed the clinical diagnosis, that is, followed a "phenotype to genotype" approach. Five were diagnosed by the laboratory analysis in the absence of a specific clinical diagnosis, that is, followed a "genotype to phenotype" approach. Two were clinically significant, incidental findings. The importance of astute clinical assessment and laboratory-clinician consultation is emphasized to optimize the value of microarrays in the diagnosis of disorders caused by single gene copy number and sequence mutations. © 2011 Wiley-Liss, Inc.

  13. Archetypal analysis of diverse Pseudomonas aeruginosa transcriptomes reveals adaptation in cystic fibrosis airways

    DEFF Research Database (Denmark)

    Thøgersen, Juliane Charlotte; Mørup, Morten; Pedersen, Søren Damkiær

    2013-01-01

    is to introduce a method for DNA microarray analysis that provides an intuitive interpretation of data through dimension reduction and pattern recognition. We present the first “Archetypal Analysis” of global gene expression. The analysis is based on microarray data from five integrated studies of Pseudomonas...... aeruginosa isolated from the airways of cystic fibrosis patients. RESULTS: Our analysis clustered samples into distinct groups with comprehensible characteristics since the archetypes representing the individual groups are closely related to samples present in the data set. Significant changes in gene....... This suggests positive selection in the cystic fibrosis lung environment, and changes in gene expression for these isolates are therefore most likely related to adaptation of the bacteria. CONCLUSIONS: Archetypal analysis succeeded in identifying adaptive changes of P. aeruginosa. The combination of clustering...

  14. Microarray analysis identified Puccinia striiformis f. sp. tritici genes involved in infection and sporulation.

    Science.gov (United States)

    Puccinia striiformis f. sp. tritici (Pst) causes stripe rust, one of the most important diseases of wheat worldwide. To identify Pst genes involved in infection and sporulation, a custom oligonucleotide Genechip was made using sequences of 442 genes selected from Pst cDNA libraries. Microarray analy...

  15. A new modified histogram matching normalization for time series microarray analysis

    NARCIS (Netherlands)

    Astola, L.J.; Molenaar, J.

    2014-01-01

    Microarray data is often utilized in inferring regulatory networks. Quantile normalization (QN) is a popular method to reduce array-to-array variation. We show that in the context of time series measurements QN may not be the best choice for this task, especially not if the inference is based on

  16. Mutation analysis of 272 Spanish families affected by autosomal recessive retinitis pigmentosa using a genotyping microarray.

    NARCIS (Netherlands)

    Avila-Fernandez, A.; Cantalapiedra, D.; Aller, E.; Vallespin, E.; Aguirre-Lamban, J.; Blanco-Kelly, F.; Corton, M.; Riveiro-Alvarez, R.; Allikmets, R.; Trujillo-Tiebas, M.J.; Millan, J.M.; Cremers, F.P.M.; Ayuso, C.

    2010-01-01

    PURPOSE: Retinitis pigmentosa (RP) is a genetically heterogeneous disorder characterized by progressive loss of vision. The aim of this study was to identify the causative mutations in 272 Spanish families using a genotyping microarray. METHODS: 272 unrelated Spanish families, 107 with autosomal

  17. Functional microarray analysis of nitrogen and carbon cycling genes across an Antarctic latitudinal transect.

    NARCIS (Netherlands)

    Yergeau, E.; Kang, S.; He, Z.; Zhou, J.; Kowalchuk, G.A.

    2007-01-01

    Soil-borne microbial communities were examined via a functional gene microarray approach across a southern polar latitudinal gradient to gain insight into the environmental factors steering soil N- and C-cycling in terrestrial Antarctic ecosystems. The abundance and diversity of functional gene

  18. Transcription analysis of apple fruit development using cDNA microarrays

    NARCIS (Netherlands)

    Soglio, V.; Costa, F.; Molthoff, J.W.; Weemen-Hendriks, M.; Schouten, H.J.; Gianfranceschi, L.

    2009-01-01

    The knowledge of the molecular mechanisms underlying fruit quality traits is fundamental to devise efficient marker-assisted selection strategies and to improve apple breeding. In this study, cDNA microarray technology was used to identify genes whose expression changes during fruit development and

  19. Microarray analysis of serum mRNA in patients with head and neck squamous cell carcinoma at whole-genome scale

    Czech Academy of Sciences Publication Activity Database

    Čapková, M.; Šáchová, Jana; Strnad, Hynek; Kolář, Michal; Hroudová, Miluše; Chovanec, M.; Čada, Z.; Štefl, M.; Valach, J.; Kastner, J.; Smetana, K. Jr.; Plzák, J.

    -, April 23 (2014) ISSN 2314-6141 R&D Projects: GA MZd(CZ) NT13488 Institutional support: RVO:68378050 Keywords : Microarray Analysis * Head and Neck Squamous Cell Carcinoma * whole-genome scale Subject RIV: EB - Genetics ; Molecular Biology

  20. ValWorkBench: an open source Java library for cluster validation, with applications to microarray data analysis.

    Science.gov (United States)

    Giancarlo, R; Scaturro, D; Utro, F

    2015-02-01

    The prediction of the number of clusters in a dataset, in particular microarrays, is a fundamental task in biological data analysis, usually performed via validation measures. Unfortunately, it has received very little attention and in fact there is a growing need for software tools/libraries dedicated to it. Here we present ValWorkBench, a software library consisting of eleven well known validation measures, together with novel heuristic approximations for some of them. The main objective of this paper is to provide the interested researcher with the full software documentation of an open source cluster validation platform having the main features of being easily extendible in a homogeneous way and of offering software components that can be readily re-used. Consequently, the focus of the presentation is on the architecture of the library, since it provides an essential map that can be used to access the full software documentation, which is available at the supplementary material website [1]. The mentioned main features of ValWorkBench are also discussed and exemplified, with emphasis on software abstraction design and re-usability. A comparison with existing cluster validation software libraries, mainly in terms of the mentioned features, is also offered. It suggests that ValWorkBench is a much needed contribution to the microarray software development/algorithm engineering community. For completeness, it is important to mention that previous accurate algorithmic experimental analysis of the relative merits of each of the implemented measures [19,23,25], carried out specifically on microarray data, gives useful insights on the effectiveness of ValWorkBench for cluster validation to researchers in the microarray community interested in its use for the mentioned task. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

  1. RNA-Seq as an Emerging Tool for Marine Dinoflagellate Transcriptome Analysis: Process and Challenges

    Directory of Open Access Journals (Sweden)

    Muhamad Afiq Akbar

    2018-01-01

    Full Text Available Dinoflagellates are the large group of marine phytoplankton with primary studies interest regarding their symbiosis with coral reef and the abilities to form harmful algae blooms (HABs. Toxin produced by dinoflagellates during events of HABs cause severe negative impact both in the economy and health sector. However, attempts to understand the dinoflagellates genomic features are hindered by their complex genome organization. Transcriptomics have been employed to understand dinoflagellates genome structure, profile genes and gene expression. RNA-seq is one of the latest methods for transcriptomics study. This method is capable of profiling the dinoflagellates transcriptomes and has several advantages, including highly sensitive, cost effective and deeper sequence coverage. Thus, in this review paper, the current workflow of dinoflagellates RNA-seq starts with the extraction of high quality RNA and is followed by cDNA sequencing using the next-generation sequencing platform, dinoflagellates transcriptome assembly and computational analysis will be discussed. Certain consideration needs will be highlighted such as difficulty in dinoflagellates sequence annotation, post-transcriptional activity and the effect of RNA pooling when using RNA-seq.

  2. Comparative Transcriptome Analysis Identifies Putative Genes Involved in the Biosynthesis of Xanthanolides in Xanthium strumarium L.

    Science.gov (United States)

    Li, Yuanjun; Gou, Junbo; Chen, Fangfang; Li, Changfu; Zhang, Yansheng

    2016-01-01

    Xanthium strumarium L. is a traditional Chinese herb belonging to the Asteraceae family. The major bioactive components of this plant are sesquiterpene lactones (STLs), which include the xanthanolides. To date, the biogenesis of xanthanolides, especially their downstream pathway, remains largely unknown. In X. strumarium, xanthanolides primarily accumulate in its glandular trichomes. To identify putative gene candidates involved in the biosynthesis of xanthanolides, three X. strumarium transcriptomes, which were derived from the young leaves of two different cultivars and the purified glandular trichomes from one of the cultivars, were constructed in this study. In total, 157 million clean reads were generated and assembled into 91,861 unigenes, of which 59,858 unigenes were successfully annotated. All the genes coding for known enzymes in the upstream pathway to the biosynthesis of xanthanolides were present in the X. strumarium transcriptomes. From a comparative analysis of the X. strumarium transcriptomes, this study identified a number of gene candidates that are putatively involved in the downstream pathway to the synthesis of xanthanolides, such as four unigenes encoding CYP71 P450s, 50 unigenes for dehydrogenases, and 27 genes for acetyltransferases. The possible functions of these four CYP71 candidates are extensively discussed. In addition, 116 transcription factors that are highly expressed in X. strumarium glandular trichomes were also identified. Their possible regulatory roles in the biosynthesis of STLs are discussed. The global transcriptomic data for X. strumarium should provide a valuable resource for further research into the biosynthesis of xanthanolides.

  3. Comparative Transcriptome Analysis Identifies Putative Genes Involved in the Biosynthesis of Xanthanolides in Xanthium strumarium L.

    Directory of Open Access Journals (Sweden)

    Yuanjun Li

    2016-08-01

    Full Text Available Xanthium strumarium L. is a traditional Chinese herb belonging to the Asteraceae family. The major bioactive components of this plant are sesquiterpene lactones, which include the xanthanolides. To date, the biogenesis of xanthanolides, especiallytheir downstream pathway, remains largely unknown. In X. strumarium, xanthanolides primarily accumulate in its glandular trichomes. To identify putative gene candidates involved in the biosynthesis of xanthanolides, three X. strumarium transcriptomes, which were derived from the young leaves of two different cultivars and the purified glandular trichomes from one of the cultivars, were constructed in this study. In total, 157 million clean reads were generated and assembled into 91,861 unigenes, of which 59,858 unigenes were successfully annotated. All the genes coding for known enzymes in the upstream pathway to the biosynthesis of xanthanolides were present in the X. strumarium transcriptomes. From a comparative analysis of the X. strumarium transcriptomes, this study identified a number of gene candidates that are putatively involved in the downstream pathway to the synthesis of xanthanolides, such as four unigenes encoding CYP71 P450s, 50 unigenes for dehydrogenases, and 27 genes for acetyltransferases. The possible functions of these four CYP71 candidates are extensively discussed. In addition, 116 transcription factors that were highly expressed in X. strumarium glandular trichomes were also identified. Their possible regulatory roles in the biosynthesis of sesquiterpene lactones are discussed. The global transcriptomic data for X. strumarium should provide a valuable resource for further research into the biosynthesis of xanthanolides.

  4. De novo assembling and primary analysis of genome and transcriptome of gray whale Eschrichtius robustus.

    Science.gov (United States)

    Moskalev, Alexey А; Kudryavtseva, Anna V; Graphodatsky, Alexander S; Beklemisheva, Violetta R; Serdyukova, Natalya A; Krutovsky, Konstantin V; Sharov, Vadim V; Kulakovskiy, Ivan V; Lando, Andrey S; Kasianov, Artem S; Kuzmin, Dmitry A; Putintseva, Yuliya A; Feranchuk, Sergey I; Shaposhnikov, Mikhail V; Fraifeld, Vadim E; Toren, Dmitri; Snezhkina, Anastasia V; Sitnik, Vasily V

    2017-12-28

    Gray whale, Eschrichtius robustus (E. robustus), is a single member of the family Eschrichtiidae, which is considered to be the most primitive in the class Cetacea. Gray whale is often described as a "living fossil". It is adapted to extreme marine conditions and has a high life expectancy (77 years). The assembly of a gray whale genome and transcriptome will allow to carry out further studies of whale evolution, longevity, and resistance to extreme environment. In this work, we report the first de novo assembly and primary analysis of the E. robustus genome and transcriptome based on kidney and liver samples. The presented draft genome assembly is complete by 55% in terms of a total genome length, but only by 24% in terms of the BUSCO complete gene groups, although 10,895 genes were identified. Transcriptome annotation and comparison with other whale species revealed robust expression of DNA repair and hypoxia-response genes, which is expected for whales. This preliminary study of the gray whale genome and transcriptome provides new data to better understand the whale evolution and the mechanisms of their adaptation to the hypoxic conditions.

  5. Determining the optimal number of independent components for reproducible transcriptomic data analysis.

    Science.gov (United States)

    Kairov, Ulykbek; Cantini, Laura; Greco, Alessandro; Molkenov, Askhat; Czerwinska, Urszula; Barillot, Emmanuel; Zinovyev, Andrei

    2017-09-11

    Independent Component Analysis (ICA) is a method that models gene expression data as an action of a set of statistically independent hidden factors. The output of ICA depends on a fundamental parameter: the number of components (factors) to compute. The optimal choice of this parameter, related to determining the effective data dimension, remains an open question in the application of blind source separation techniques to transcriptomic data. Here we address the question of optimizing the number of statistically independent components in the analysis of transcriptomic data for reproducibility of the components in multiple runs of ICA (within the same or within varying effective dimensions) and in multiple independent datasets. To this end, we introduce ranking of independent components based on their stability in multiple ICA computation runs and define a distinguished number of components (Most Stable Transcriptome Dimension, MSTD) corresponding to the point of the qualitative change of the stability profile. Based on a large body of data, we demonstrate that a sufficient number of dimensions is required for biological interpretability of the ICA decomposition and that the most stable components with ranks below MSTD have more chances to be reproduced in independent studies compared to the less stable ones. At the same time, we show that a transcriptomics dataset can be reduced to a relatively high number of dimensions without losing the interpretability of ICA, even though higher dimensions give rise to components driven by small gene sets. We suggest a protocol of ICA application to transcriptomics data with a possibility of prioritizing components with respect to their reproducibility that strengthens the biological interpretation. Computing too few components (much less than MSTD) is not optimal for interpretability of the results. The components ranked within MSTD range have more chances to be reproduced in independent studies.

  6. De novo analysis of transcriptome dynamics in the migratory locust during the development of phase traits.

    Directory of Open Access Journals (Sweden)

    Shuang Chen

    Full Text Available Locusts exhibit remarkable density-dependent phenotype (phase changes from the solitary to the gregarious, making them one of the most destructive agricultural pests. This phenotype polyphenism arises from a single genome and diverse transcriptomes in different conditions. Here we report a de novo transcriptome for the migratory locust and a comprehensive, representative core gene set. We carried out assembly of 21.5 Gb Illumina reads, generated 72,977 transcripts with N50 2,275 bp and identified 11,490 locust protein-coding genes. Comparative genomics analysis with eight other sequenced insects was carried out to identify the genomic divergence between hemimetabolous and holometabolous insects for the first time and 18 genes relevant to development was found. We further utilized the quantitative feature of RNA-seq to measure and compare gene expression among libraries. We first discovered how divergence in gene expression between two phases progresses as locusts develop and identified 242 transcripts as candidates for phase marker genes. Together with the detailed analysis of deep sequencing data of the 4(th instar, we discovered a phase-dependent divergence of biological investment in the molecular level. Solitary locusts have higher activity in biosynthetic pathways while gregarious locusts show higher activity in environmental interaction, in which genes and pathways associated with regulation of neurotransmitter activities, such as neurotransmitter receptors, synthetase, transporters, and GPCR signaling pathways, are strongly involved. Our study, as the largest de novo transcriptome to date, with optimization of sequencing and assembly strategy, can further facilitate the application of de novo transcriptome. The locust transcriptome enriches genetic resources for hemimetabolous insects and our understanding of the origin of insect metamorphosis. Most importantly, we identified genes and pathways that might be involved in locust development

  7. An Integrated Transcriptome-Wide Analysis of Cave and Surface Dwelling Astyanax mexicanus

    Science.gov (United States)

    Gross, Joshua B.; Furterer, Allison; Carlson, Brian M.; Stahl, Bethany A.

    2013-01-01

    Numerous organisms around the globe have successfully adapted to subterranean environments. A powerful system in which to study cave adaptation is the freshwater characin fish, Astyanax mexicanus. Prior studies in this system have established a genetic basis for the evolution of numerous regressive traits, most notably vision and pigmentation reduction. However, identification of the precise genetic alterations that underlie these morphological changes has been delayed by limited genetic and genomic resources. To address this, we performed a transcriptome analysis of cave and surface dwelling Astyanax morphs using Roche/454 pyrosequencing technology. Through this approach, we obtained 576,197 Pachón cavefish-specific reads and 438,978 surface fish-specific reads. Using this dataset, we assembled transcriptomes of cave and surface fish separately, as well as an integrated transcriptome that combined 1,499,568 reads from both morphotypes. The integrated assembly was the most successful approach, yielding 22,596 high quality contiguous sequences comprising a total transcriptome length of 21,363,556 bp. Sequence identities were obtained through exhaustive blast searches, revealing an adult transcriptome represented by highly diverse Gene Ontology (GO) terms. Our dataset facilitated rapid identification of sequence polymorphisms between morphotypes. These data, along with positional information collected from the Danio rerio genome, revealed several syntenic regions between Astyanax and Danio. We demonstrated the utility of this positional information through a QTL analysis of albinism in a surface x Pachón cave F2 pedigree, using 65 polymorphic markers identified from our integrated assembly. We also adapted our dataset for an RNA-seq study, revealing many genes responsible for visual system maintenance in surface fish, whose expression was not detected in adult Pachón cavefish. Conversely, several metabolism-related genes expressed in cavefish were not detected in

  8. Archetypal analysis of diverse Pseudomonas aeruginosa transcriptomes reveals adaptation in cystic fibrosis airways

    Science.gov (United States)

    2013-01-01

    Background Analysis of global gene expression by DNA microarrays is widely used in experimental molecular biology. However, the complexity of such high-dimensional data sets makes it difficult to fully understand the underlying biological features present in the data. The aim of this study is to introduce a method for DNA microarray analysis that provides an intuitive interpretation of data through dimension reduction and pattern recognition. We present the first “Archetypal Analysis” of global gene expression. The analysis is based on microarray data from five integrated studies of Pseudomonas aeruginosa isolated from the airways of cystic fibrosis patients. Results Our analysis clustered samples into distinct groups with comprehensible characteristics since the archetypes representing the individual groups are closely related to samples present in the data set. Significant changes in gene expression between different groups identified adaptive changes of the bacteria residing in the cystic fibrosis lung. The analysis suggests a similar gene expression pattern between isolates with a high mutation rate (hypermutators) despite accumulation of different mutations for these isolates. This suggests positive selection in the cystic fibrosis lung environment, and changes in gene expression for these isolates are therefore most likely related to adaptation of the bacteria. Conclusions Archetypal analysis succeeded in identifying adaptive changes of P. aeruginosa. The combination of clustering and matrix factorization made it possible to reveal minor similarities among different groups of data, which other analytical methods failed to identify. We suggest that this analysis could be used to supplement current methods used to analyze DNA microarray data. PMID:24059747

  9. Transcriptomic responses to biotic stresses in Malus x domestica: a meta-analysis study.

    Science.gov (United States)

    Balan, Bipin; Marra, Francesco Paolo; Caruso, Tiziano; Martinelli, Federico

    2018-01-31

    RNA-Seq analysis is a strong tool to gain insight into the molecular responses to biotic stresses in plants. The objective of this work is to identify specific and common molecular responses between different transcriptomic data related to fungi, virus and bacteria attacks in Malus x domestica. We analyzed seven transcriptomic datasets in Malus x domestica divided in responses to fungal pathogens, virus (Apple Stem Grooving Virus) and bacteria (Erwinia amylovora). Data were dissected using an integrated approach of pathway- and gene- set enrichment analysis, Mapman visualization tool, gene ontology analysis and inferred protein-protein interaction network. Our meta-analysis revealed that the bacterial infection enhanced specifically genes involved in sugar alcohol metabolism. Brassinosteroids were upregulated by fungal pathogens while ethylene was highly affected by Erwinia amylovora. Gibberellins and jasmonates were strongly repressed by fungal and viral infections. The protein-protein interaction network highlighted the role of WRKYs in responses to the studied pathogens. In summary, our meta-analysis provides a better understanding of the Malus X domestica transcriptome responses to different biotic stress conditions; we anticipate that these insights will assist in the development of genetic resistance and acute therapeutic strategies. This work would be an example for next meta-analysis works aiming at identifying specific common molecular features linked with biotic stress responses in other specialty crops.

  10. GeNNet: an integrated platform for unifying scientific workflows and graph databases for transcriptome data analysis

    Directory of Open Access Journals (Sweden)

    Raquel L. Costa

    2017-07-01

    Full Text Available There are many steps in analyzing transcriptome data, from the acquisition of raw data to the selection of a subset of representative genes that explain a scientific hypothesis. The data produced can be represented as networks of interactions among genes and these may additionally be integrated with other biological databases, such as Protein-Protein Interactions, transcription factors and gene annotation. However, the results of these analyses remain fragmented, imposing difficulties, either for posterior inspection of results, or for meta-analysis by the incorporation of new related data. Integrating databases and tools into scientific workflows, orchestrating their execution, and managing the resulting data and its respective metadata are challenging tasks. Additionally, a great amount of effort is equally required to run in-silico experiments to structure and compose the information as needed for analysis. Different programs may need to be applied and different files are produced during the experiment cycle. In this context, the availability of a platform supporting experiment execution is paramount. We present GeNNet, an integrated transcriptome analysis platform that unifies scientific workflows with graph databases for selecting relevant genes according to the evaluated biological systems. It includes GeNNet-Wf, a scientific workflow that pre-loads biological data, pre-processes raw microarray data and conducts a series of analyses including normalization, differential expression inference, clusterization and gene set enrichment analysis. A user-friendly web interface, GeNNet-Web, allows for setting parameters, executing, and visualizing the results of GeNNet-Wf executions. To demonstrate the features of GeNNet, we performed case studies with data retrieved from GEO, particularly using a single-factor experiment in different analysis scenarios. As a result, we obtained differentially expressed genes for which biological functions were

  11. Transcriptome analysis elucidates key developmental components of bryozoan lophophore development

    KAUST Repository

    Wong, Yue Him

    2014-10-10

    The most recent phylogenomic study suggested that Bryozoa (Ectoprocta), Brachiopoda, and Phoronida are monophyletic, implying that the lophophore of bryozoans, phoronids and brachiopods is a synapomorphy. Understanding the molecular mechanisms of the lophophore development of the Lophophorata clade can therefore provide us a new insight into the formation of the diverse morphological traits in metazoans. In the present study, we profiled the transcriptome of the Bryozoan (Ectoproct) Bugula neritina during the swimming larval stage (SW) and the early (4 h) and late (24 h) metamorphic stages using the Illumina HiSeq2000 platform. Various genes that function in development, the immune response and neurogenesis showed differential expression levels during metamorphosis. In situ hybridization of 23 genes that participate in the Wnt, BMP, Notch, and Hedgehog signaling pathways revealed their regulatory roles in the development of the lophophore and the ancestrula digestive tract. Our findings support the hypothesis that developmental precursors of the lophophore and the ancestrula digestive tract are pre-patterned by the differential expression of key developmental genes according to their fate. This study provides a foundation to better understand the developmental divergence and/or convergence among developmental precursors of the lophophore of bryozoans, branchiopods and phoronids.

  12. TimesVector: a vectorized clustering approach to the analysis of time series transcriptome data from multiple phenotypes.

    Science.gov (United States)

    Jung, Inuk; Jo, Kyuri; Kang, Hyejin; Ahn, Hongryul; Yu, Youngjae; Kim, Sun

    2017-12-01

    Identifying biologically meaningful gene expression patterns from time series gene expression data is important to understand the underlying biological mechanisms. To identify significantly perturbed gene sets between different phenotypes, analysis of time series transcriptome data requires consideration of time and sample dimensions. Thus, the analysis of such time series data seeks to search gene sets that exhibit similar or different expression patterns between two or more sample conditions, constituting the three-dimensional data, i.e. gene-time-condition. Computational complexity for analyzing such data is very high, compared to the already difficult NP-hard two dimensional biclustering algorithms. Because of this challenge, traditional time series clustering algorithms are designed to capture co-expressed genes with similar expression pattern in two sample conditions. We present a triclustering algorithm, TimesVector, specifically designed for clustering three-dimensional time series data to capture distinctively similar or different gene expression patterns between two or more sample conditions. TimesVector identifies clusters with distinctive expression patterns in three steps: (i) dimension reduction and clustering of time-condition concatenated vectors, (ii) post-processing clusters for detecting similar and distinct expression patterns and (iii) rescuing genes from unclassified clusters. Using four sets of time series gene expression data, generated by both microarray and high throughput sequencing platforms, we demonstrated that TimesVector successfully detected biologically meaningful clusters of high quality. TimesVector improved the clustering quality compared to existing triclustering tools and only TimesVector detected clusters with differential expression patterns across conditions successfully. The TimesVector software is available at http://biohealth.snu.ac.kr/software/TimesVector/. sunkim.bioinfo@snu.ac.kr. Supplementary data are available at

  13. Evaluation of gene expression data generated from expired Affymetrix GeneChip® microarrays using MAQC reference RNA samples

    Directory of Open Access Journals (Sweden)

    Tong Weida

    2010-10-01

    Full Text Available Abstract Background The Affymetrix GeneChip® system is a commonly used platform for microarray analysis but the technology is inherently expensive. Unfortunately, changes in experimental planning and execution, such as the unavailability of previously anticipated samples or a shift in research focus, may render significant numbers of pre-purchased GeneChip® microarrays unprocessed before their manufacturer’s expiration dates. Researchers and microarray core facilities wonder whether expired microarrays are still useful for gene expression analysis. In addition, it was not clear whether the two human reference RNA samples established by the MAQC project in 2005 still maintained their transcriptome integrity over a period of four years. Experiments were conducted to answer these questions. Results Microarray data were generated in 2009 in three replicates for each of the two MAQC samples with either expired Affymetrix U133A or unexpired U133Plus2 microarrays. These results were compared with data obtained in 2005 on the U133Plus2 microarray. The percentage of overlap between the lists of differentially expressed genes (DEGs from U133Plus2 microarray data generated in 2009 and in 2005 was 97.44%. While there was some degree of fold change compression in the expired U133A microarrays, the percentage of overlap between the lists of DEGs from the expired and unexpired microarrays was as high as 96.99%. Moreover, the microarray data generated using the expired U133A microarrays in 2009 were highly concordant with microarray and TaqMan® data generated by the MAQC project in 2005. Conclusions Our results demonstrated that microarray data generated using U133A microarrays, which were more than four years past the manufacturer’s expiration date, were highly specific and consistent with those from unexpired microarrays in identifying DEGs despite some appreciable fold change compression and decrease in sensitivity. Our data also suggested that the

  14. Microarray analysis of a salamander hopeful monster reveals transcriptional signatures of paedomorphic brain development

    Science.gov (United States)

    2010-01-01

    Background The Mexican axolotl (Ambystoma mexicanum) is considered a hopeful monster because it exhibits an adaptive and derived mode of development - paedomorphosis - that has evolved rapidly and independently among tiger salamanders. Unlike related tiger salamanders that undergo metamorphosis, axolotls retain larval morphological traits into adulthood and thus present an adult body plan that differs dramatically from the ancestral (metamorphic) form. The basis of paedomorphic development was investigated by comparing temporal patterns of gene transcription between axolotl and tiger salamander larvae (Ambystoma tigrinum tigrinum) that typically undergo a metamorphosis. Results Transcript abundances from whole brain and pituitary were estimated via microarray analysis on four different days post hatching (42, 56, 70, 84 dph) and regression modeling was used to independently identify genes that were differentially expressed as a function of time in both species. Collectively, more differentially expressed genes (DEGs) were identified as unique to the axolotl (n = 76) and tiger salamander (n = 292) than were identified as shared (n = 108). All but two of the shared DEGs exhibited the same temporal pattern of expression and the unique genes tended to show greater changes later in the larval period when tiger salamander larvae were undergoing anatomical metamorphosis. A second, complementary analysis that directly compared the expression of 1320 genes between the species identified 409 genes that differed as a function of species or the interaction between time and species. Of these 409 DEGs, 84% exhibited higher abundances in tiger salamander larvae at all sampling times. Conclusions Many of the unique tiger salamander transcriptional responses are probably associated with metamorphic biological processes. However, the axolotl also showed unique patterns of transcription early in development. In particular, the axolotl showed a genome-wide reduction in mRNA abundance

  15. Microarray analysis of a salamander hopeful monster reveals transcriptional signatures of paedomorphic brain development

    Directory of Open Access Journals (Sweden)

    Putta Srikrishna

    2010-06-01

    Full Text Available Abstract Background The Mexican axolotl (Ambystoma mexicanum is considered a hopeful monster because it exhibits an adaptive and derived mode of development - paedomorphosis - that has evolved rapidly and independently among tiger salamanders. Unlike related tiger salamanders that undergo metamorphosis, axolotls retain larval morphological traits into adulthood and thus present an adult body plan that differs dramatically from the ancestral (metamorphic form. The basis of paedomorphic development was investigated by comparing temporal patterns of gene transcription between axolotl and tiger salamander larvae (Ambystoma tigrinum tigrinum that typically undergo a metamorphosis. Results Transcript abundances from whole brain and pituitary were estimated via microarray analysis on four different days post hatching (42, 56, 70, 84 dph and regression modeling was used to independently identify genes that were differentially expressed as a function of time in both species. Collectively, more differentially expressed genes (DEGs were identified as unique to the axolotl (n = 76 and tiger salamander (n = 292 than were identified as shared (n = 108. All but two of the shared DEGs exhibited the same temporal pattern of expression and the unique genes tended to show greater changes later in the larval period when tiger salamander larvae were undergoing anatomical metamorphosis. A second, complementary analysis that directly compared the expression of 1320 genes between the species identified 409 genes that differed as a function of species or the interaction between time and species. Of these 409 DEGs, 84% exhibited higher abundances in tiger salamander larvae at all sampling times. Conclusions Many of the unique tiger salamander transcriptional responses are probably associated with metamorphic biological processes. However, the axolotl also showed unique patterns of transcription early in development. In particular, the axolotl showed a genome

  16. Transcriptome analysis reveals novel patterning and pigmentation genes underlying Heliconius butterfly wing pattern variation

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    Hines Heather M

    2012-06-01

    Full Text Available Abstract Background Heliconius butterfly wing pattern diversity offers a unique opportunity to investigate how natural genetic variation can drive the evolution of complex adaptive phenotypes. Positional cloning and candidate gene studies have identified a handful of regulatory and pigmentation genes implicated in Heliconius wing pattern variation, but little is known about the greater developmental networks within which these genes interact to pattern a wing. Here we took a large-scale transcriptomic approach to identify the network of genes involved in Heliconius wing pattern development and variation. This included applying over 140 transcriptome microarrays to assay gene expression in dissected wing pattern elements across a range of developmental stages and wing pattern morphs of Heliconius erato. Results We identified a number of putative early prepattern genes with color-pattern related expression domains. We also identified 51 genes differentially expressed in association with natural color pattern variation. Of these, the previously identified color pattern “switch gene” optix was recovered as the first transcript to show color-specific differential expression. Most differentially expressed genes were transcribed late in pupal development and have roles in cuticle formation or pigment synthesis. These include previously undescribed transporter genes associated with ommochrome pigmentation. Furthermore, we observed upregulation of melanin-repressing genes such as ebony and Dat1 in non-melanic patterns. Conclusions This study identifies many new genes implicated in butterfly wing pattern development and provides a glimpse into the number and types of genes affected by variation in genes that drive color pattern evolution.

  17. Comparative de novo transcriptome analysis of male and female Sea buckthorn.

    Science.gov (United States)

    Bansal, Ankush; Salaria, Mehul; Sharma, Tashil; Stobdan, Tsering; Kant, Anil

    2018-02-01

    Sea buckthorn is a dioecious medicinal plant found at high altitude. The plant has both male and female reproductive organs in separate individuals. In this article, whole transcriptome de novo assemblies of male and female flower bud samples were carried out using Illumina NextSeq 500 platform to determine the role of the genes involved in sex determination. Moreover, genes with differential expression in male and female transcriptomes were identified to understand the underlying sex determination mechanism. The current study showed 63,904 and 62,272 coding sequences (CDS) in female and male transcriptome data sets, respectively. 16,831 common CDS were screened out from both transcriptomes, out of which 625 were upregulated and 491 were found to be downregulated. To understand the potential regulatory roles of differentially expressed genes in metabolic networks and biosynthetic pathways: KEGG mapping, gene ontology, and co-expression network analysis were performed. Comparison with Flowering Interactive Database (FLOR-ID) resulted in eight differentially expressed genes viz. CHD3-type chromatin-remodeling factor PICKLE ( PKL ), phytochrome-associated serine/threonine-protein phosphatase ( FYPP ), protein TOPLESS ( TPL ), sensitive to freezing 6 ( SFR6 ), lysine-specific histone demethylase 1 homolog 1 ( LDL1 ), pre-mRNA-processing-splicing factor 8A ( PRP8A ), sucrose synthase 4 ( SUS4 ), ubiquitin carboxyl-terminal hydrolase 12 ( UBP12 ), known to be broadly involved in flowering, photoperiodism, embryo development, and cold response pathways. Male and female flower bud transcriptome data of Sea buckthorn may provide comprehensive information at genomic level for the identification of genetic regulation involved in sex determination.

  18. Characterization of Liaoning cashmere goat transcriptome: sequencing, de novo assembly, functional annotation and comparative analysis.

    Directory of Open Access Journals (Sweden)

    Hongliang Liu

    Full Text Available Liaoning cashmere goat is a famous goat breed for cashmere wool. In order to increase the transcriptome data and accelerate genetic improvement for this breed, we performed de novo transcriptome sequencing to generate the first expressed sequence tag dataset for the Liaoning cashmere goat, using next-generation sequencing technology.Transcriptome sequencing of Liaoning cashmere goat on a Roche 454 platform yielded 804,601 high-quality reads. Clustering and assembly of these reads produced a non-redundant set of 117,854 unigenes, comprising 13,194 isotigs and 104,660 singletons. Based on similarity searches with known proteins, 17,356 unigenes were assigned to 6,700 GO categories, and the terms were summarized into three main GO categories and 59 sub-categories. 3,548 and 46,778 unigenes had significant similarity to existing sequences in the KEGG and COG databases, respectively. Comparative analysis revealed that 42,254 unigenes were aligned to 17,532 different sequences in NCBI non-redundant nucleotide databases. 97,236 (82.51% unigenes were mapped to the 30 goat chromosomes. 35,551 (30.17% unigenes were matched to 11,438 reported goat protein-coding genes. The remaining non-matched unigenes were further compared with cattle and human reference genes, 67 putative new goat genes were discovered. Additionally, 2,781 potential simple sequence repeats were initially identified from all unigenes.The transcriptome of Liaoning cashmere goat was deep sequenced, de novo assembled, and annotated, providing abundant data to better understand the Liaoning cashmere goat transcriptome. The potential simple sequence repeats provide a material basis for future genetic linkage and quantitative trait loci analyses.

  19. Identifying significant genetic regulatory networks in the prostate cancer from microarray data based on transcription factor analysis and conditional independency

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    Yeh Cheng-Yu

    2009-12-01

    Full Text Available Abstract Background Prostate cancer is a world wide leading cancer and it is characterized by its aggressive metastasis. According to the clinical heterogeneity, prostate cancer displays different stages and grades related to the aggressive metastasis disease. Although numerous studies used microarray analysis and traditional clustering method to identify the individual genes during the disease processes, the important gene regulations remain unclear. We present a computational method for inferring genetic regulatory networks from micorarray data automatically with transcription factor analysis and conditional independence testing to explore the potential significant gene regulatory networks that are correlated with cancer, tumor grade and stage in the prostate cancer. Results To deal with missing values in microarray data, we used a K-nearest-neighbors (KNN algorithm to determine the precise expression values. We applied web services technology to wrap the bioinformatics toolkits and databases to automatically extract the promoter regions of DNA sequences and predicted the transcription factors that regulate the gene expressions. We adopt the microarray datasets consists of 62 primary tumors, 41 normal prostate tissues from Stanford Microarray Database (SMD as a target dataset to evaluate our method. The predicted results showed that the possible biomarker genes related to cancer and denoted the androgen functions and processes may be in the development of the prostate cancer and promote the cell death in cell cycle. Our predicted results showed that sub-networks of genes SREBF1, STAT6 and PBX1 are strongly related to a high extent while ETS transcription factors ELK1, JUN and EGR2 are related to a low extent. Gene SLC22A3 may explain clinically the differentiation associated with the high grade cancer compared with low grade cancer. Enhancer of Zeste Homolg 2 (EZH2 regulated by RUNX1 and STAT3 is correlated to the pathological stage

  20. Identifying significant genetic regulatory networks in the prostate cancer from microarray data based on transcription factor analysis and conditional independency.

    Science.gov (United States)

    Yeh, Hsiang-Yuan; Cheng, Shih-Wu; Lin, Yu-Chun; Yeh, Cheng-Yu; Lin, Shih-Fang; Soo, Von-Wun

    2009-12-21

    Prostate cancer is a world wide leading cancer and it is characterized by its aggressive metastasis. According to the clinical heterogeneity, prostate cancer displays different stages and grades related to the aggressive metastasis disease. Although numerous studies used microarray analysis and traditional clustering method to identify the individual genes during the disease processes, the important gene regulations remain unclear. We present a computational method for inferring genetic regulatory networks from micorarray data automatically with transcription factor analysis and conditional independence testing to explore the potential significant gene regulatory networks that are correlated with cancer, tumor grade and stage in the prostate cancer. To deal with missing values in microarray data, we used a K-nearest-neighbors (KNN) algorithm to determine the precise expression values. We applied web services technology to wrap the bioinformatics toolkits and databases to automatically extract the promoter regions of DNA sequences and predicted the transcription factors that regulate the gene expressions. We adopt the microarray datasets consists of 62 primary tumors, 41 normal prostate tissues from Stanford Microarray Database (SMD) as a target dataset to evaluate our method. The predicted results showed that the possible biomarker genes related to cancer and denoted the androgen functions and processes may be in the development of the prostate cancer and promote the cell death in cell cycle. Our predicted results showed that sub-networks of genes SREBF1, STAT6 and PBX1 are strongly related to a high extent while ETS transcription factors ELK1, JUN and EGR2 are related to a low extent. Gene SLC22A3 may explain clinically the differentiation associated with the high grade cancer compared with low grade cancer. Enhancer of Zeste Homolg 2 (EZH2) regulated by RUNX1 and STAT3 is correlated to the pathological stage. We provide a computational framework to reconstruct

  1. HOXD-AS1 is a novel lncRNA encoded in HOXD cluster and a marker of neuroblastoma progression revealed via integrative analysis of noncoding transcriptome

    Science.gov (United States)

    2014-01-01

    Background Long noncoding RNAs (lncRNAs) constitute a major, but poorly characterized part of human transcriptome. Recent evidence indicates that many lncRNAs are involved in cancer and can be used as predictive and prognostic biomarkers. Significant fraction of lncRNAs is represented on widely used microarray platforms, however they have usually been ignored in cancer studies. Results We developed a computational pipeline to annotate lncRNAs on popular Affymetrix U133 microarrays, creating a resource allowing measurement of expression of 1581 lncRNAs. This resource can be utilized to interrogate existing microarray datasets for various lncRNA studies. We found that these lncRNAs fall into three distinct classes according to their statistical distribution by length. Remarkably, these three classes of lncRNAs were co-localized with protein coding genes exhibiting distinct gene ontology groups. This annotation was applied to microarray analysis which identified a 159 lncRNA signature that discriminates between localized and metastatic stages of neuroblastoma. Analysis of an independent patient cohort revealed that this signature differentiates also relapsing from non-relapsing primary tumors. This is the first example of the signature developed via the analysis of expression of lncRNAs solely. One of these lncRNAs, termed HOXD-AS1, is encoded in HOXD cluster. HOXD-AS1 is evolutionary conserved among hominids and has all bona fide features of a gene. Studying retinoid acid (RA) response of SH-SY5Y cell line, a model of human metastatic neuroblastoma, we found that HOXD-AS1 is a subject to morphogenic regulation, is activated by PI3K/Akt pathway and itself is involved in control of RA-induced cell differentiation. Knock-down experiments revealed that HOXD-AS1 controls expression levels of clinically significant protein-coding genes involved in angiogenesis and inflammation, the hallmarks of metastatic cancer. Conclusions Our findings greatly extend the number of

  2. Integrating Multiple Microarray Data for Cancer Pathway Analysis Using Bootstrapping K-S Test

    Directory of Open Access Journals (Sweden)

    Bing Han

    2009-01-01

    Full Text Available Previous applications of microarray technology for cancer research have mostly focused on identifying genes that are differentially expressed between a particular cancer and normal cells. In a biological system, genes perform different molecular functions and regulate various biological processes via interactions with other genes thus forming a variety of complex networks. Therefore, it is critical to understand the relationship (e.g., interactions between genes across different types of cancer in order to gain insights into the molecular mechanisms of cancer. Here we propose an integrative method based on the bootstrapping Kolmogorov-Smirnov test and a large set of microarray data produced with various types of cancer to discover common molecular changes in cells from normal state to cancerous state. We evaluate our method using three key pathways related to cancer and demonstrate that it is capable of finding meaningful alterations in gene relations.

  3. Energy metabolism in Desulfovibrio vulgaris Hildenborough: insights from transcriptome analysis

    Energy Technology Data Exchange (ETDEWEB)

    Pereira, Patricia M.; He, Qiang; Valente, Filipa M.A.; Xavier, Antonio V.; Zhou, Jizhong; Pereira, Ines A.C.; Louro, Ricardo O.

    2007-11-01

    Sulphate-reducing bacteria are important players in the global sulphur and carbon cycles, with considerable economical and ecological impact. However, the process of sulphate respiration is still incompletely understood. Several mechanisms of energy conservation have been proposed, but it is unclear how the different strategies contribute to the overall process. In order to obtain a deeper insight into the energy metabolism of sulphate-reducers whole-genome microarrays were used to compare the transcriptional response of Desulfovibrio vulgaris Hildenborough grown with hydrogen/sulphate, pyruvate/sulphate, pyruvate with limiting sulphate, and lactate/thiosulphate, relative to growth in lactate/sulphate. Growth with hydrogen/sulphate showed the largest number of differentially expressed genes and the largest changes in transcript levels. In this condition the most up-regulated energy metabolism genes were those coding for the periplasmic [NiFeSe]hydrogenase, followed by the Ech hydrogenase. The results also provide evidence for the involvement of formate cycling and the recently proposed ethanol pathway during growth in hydrogen. The pathway involving CO cycling is relevant during growth on lactate and pyruvate, but not during growth in hydrogen as the most down-regulated genes were those coding for the CO-induced hydrogenase. Growth on lactate/thiosulphate reveals a down-regulation of several energymetabolism genes similar to what was observed in the presence of nitrite. This study identifies the role of several proteins involved in the energy metabolism of D. vulgaris and highlights several novel genes related to this process, revealing a more complex bioenergetic metabolism than previously considered.

  4. Visual analysis of transcriptome data in the context of anatomical structures and biological networks

    Directory of Open Access Journals (Sweden)

    Astrid eJunker

    2012-11-01

    Full Text Available The complexity and temporal as well as spatial resolution of transcriptome datasets is constantly increasing due to extensive technological developments. Here we present methods for advanced visualization and intuitive exploration of transcriptomics data as necessary prerequisites in order to facilitate the gain of biological knowledge. Color-coding of structural images based on the expression level enables a fast visual data analysis in the background of the examined biological system. The network-based exploration of these visualizations allows for comparative analysis of genes with specific transcript patterns and supports the extraction of functional relationships even from large datasets. In order to illustrate the presented methods, the tool HIVE was applied for visualization and exploration of database-retrieved expression data for master regulators of Arabidopsis thaliana flower and seed development in the context of corresponding tissue-specific regulatory networks.

  5. Transcriptome analysis and metabolic profiling of green and red kale (Brassica oleracea var. acephala) seedlings.

    Science.gov (United States)

    Jeon, Jin; Kim, Jae Kwang; Kim, HyeRan; Kim, Yeon Jeong; Park, Yun Ji; Kim, Sun Ju; Kim, Changsoo; Park, Sang Un

    2018-02-15

    Kale (Brassica oleracea var. acephala) is a rich source of numerous health-benefiting compounds, including vitamins, glucosinolates, phenolic compounds, and carotenoids. However, the genetic resources for exploiting the phyto-nutritional traits of kales are limited. To acquire precise information on secondary metabolites in kales, we performed a comprehensive analysis of the transcriptome and metabolome of green and red kale seedlings. Kale transcriptome datasets revealed 37,149 annotated genes and several secondary metabolite biosynthetic genes. HPLC analysis revealed 14 glucosinolates, 20 anthocyanins, 3 phenylpropanoids, and 6 carotenoids in the kale seedlings that were examined. Red kale contained more glucosinolates, anthocyanins, and phenylpropanoids than green kale, whereas the carotenoid contents were much higher in green kale than in red kale. Ultimately, our data will be a valuable resource for future research on kale bio-engineering and will provide basic information to define gene-to-metabolite networks in kale. Copyright © 2017 Elsevier Ltd. All rights reserved.

  6. A New Modified Histogram Matching Normalization for Time Series Microarray Analysis.

    Science.gov (United States)

    Astola, Laura; Molenaar, Jaap

    2014-07-01

    Microarray data is often utilized in inferring regulatory networks. Quantile normalization (QN) is a popular method to reduce array-to-array variation. We show that in the context of time series measurements QN may not be the best choice for this task, especially not if the inference is based on continuous time ODE model. We propose an alternative normalization method that is better suited for network inference from time series data.

  7. A New Modified Histogram Matching Normalization for Time Series Microarray Analysis

    Directory of Open Access Journals (Sweden)

    Laura Astola

    2014-07-01

    Full Text Available Microarray data is often utilized in inferring regulatory networks. Quantile normalization (QN is a popular method to reduce array-to-array variation. We show that in the context of time series measurements QN may not be the best choice for this task, especially not if the inference is based on continuous time ODE model. We propose an alternative normalization method that is better suited for network inference from time series data.

  8. Production of DNA microarray and expression analysis of genes from Xylella fastidiosa in different culture media

    Directory of Open Access Journals (Sweden)

    Regiane de Fátima Travensolo

    2009-06-01

    Full Text Available DNA Microarray was developed to monitor the expression of many genes from Xylella fastidiosa, allowing the side by-side comparison of two situations in a single experiment. The experiments were performed using X. fastidiosa cells grown in two culture media: BCYE and XDM2. The primers were synthesized, spotted onto glass slides and the array was hybridized against fluorescently labeled cDNAs. The emitted signals were quantified, normalized and the data were statistically analyzed to verify the differentially expressed genes. According to the data, 104 genes were differentially expressed in XDM2 and 30 genes in BCYE media. The present study showed that DNA microarray technique efficiently differentiate the expressed genes under different conditions.DNA Microarray foi desenvolvida para monitorar a expressão de muitos genes de Xylella fastidiosa, permitindo a comparação de duas situações distintas em um único experimento. Os experimentos foram feitos utilizando células de X. fastidiosa cultivada em dois meios de cultura: BCYE e XDM2. Pares de oligonucleotídeos iniciadores foram sintetizados, depositados em lâminas de vidro e o arranjo foi hibridizado contra cDNAs marcados fluorescentemente. Os sinais emitidos foram quantificados, normalizados e os dados foram estatisticamente analisados para verificar os genes diferencialmente expressos. De acordo com nossos dados, 104 genes foram diferencialmente expressos para o meio de cultura XDM2 e 30 genes para o BCYE. No presente estudo, nós demonstramos que a técnica de DNA microarrays eficientemente diferencia genes expressos sob diferentes condições de cultivo.

  9. ArrayMining: a modular web-application for microarray analysis combining ensemble and consensus methods with cross-study normalization

    Directory of Open Access Journals (Sweden)

    Krasnogor Natalio

    2009-10-01

    Full Text Available Abstract Background Statistical analysis of DNA microarray data provides a valuable diagnostic tool for the investigation of genetic components of diseases. To take advantage of the multitude of available data sets and analysis methods, it is desirable to combine both different algorithms and data from different studies. Applying ensemble learning, consensus clustering and cross-study normalization methods for this purpose in an almost fully automated process and linking different analysis modules together under a single interface would simplify many microarray analysis tasks. Results We present ArrayMining.net, a web-application for microarray analysis that provides easy access to a wide choice of feature selection, clustering, prediction, gene set analysis and cross-study normalization methods. In contrast to other microarray-related web-tools, multiple algorithms and data sets for an analysis task can be combined using ensemble feature selection, ensemble prediction, consensus clustering and cross-platform data integration. By interlinking different analysis tools in a modular fashion, new exploratory routes become available, e.g. ensemble sample classification using features obtained from a gene set analysis and data from multiple studies. The analysis is further simplified by automatic parameter selection mechanisms and linkage to web tools and databases for functional annotation and literature mining. Conclusion ArrayMining.net is a free web-application for microarray analysis combining a broad choice of algorithms based on ensemble and consensus methods, using automatic parameter selection and integration with annotation databases.

  10. Evaluation of chronic lymphocytic leukemia by BAC-based microarray analysis

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    McDaniel Lisa D

    2011-02-01

    Full Text Available Abstract Background Chronic lymphocytic leukemia (CLL is a highly variable disease with life expectancies ranging from months to decades. Cytogenetic findings play an integral role in defining the prognostic significance and treatment for individual patients. Results We have evaluated 25 clinical cases from a tertiary cancer center that have an established diagnosis of CLL and for which there was prior cytogenetic and/or fluorescence in situ hybridization (FISH data. We performed microarray-based comparative genomic hybridization (aCGH using a bacterial artificial chromosome (BAC-based microarray designed for the detection of known constitutional genetic syndromes. In 15 of the 25 cases, aCGH detected all copy number imbalances identified by prior cytogenetic and/or FISH studies. For the majority of those not detected, the aberrations were present at low levels of mosaicism. Furthermore, for 15 of the 25 cases, additional abnormalities were detected. Four of those cases had deletions that mapped to intervals implicated in inherited predisposition to CLL. For most cases, aCGH was able to detect abnormalities present in as few as 10% of cells. Although changes in ploidy are not easily discernable by aCGH, results for two cases illustrate the detection of additional copy gains and losses present within a mosaic tetraploid cell population. Conclusions Our results illustrate the successful evaluation of CLL using a microarray optimized for the interrogation of inherited disorders and the identification of alterations with possible relevance to CLL susceptibility.

  11. Multiplexed fluorescent microarray for human salivary protein analysis using polymer microspheres and fiber-optic bundles.

    Science.gov (United States)

    Nie, Shuai; Benito-Peña, Elena; Zhang, Huaibin; Wu, Yue; Walt, David R

    2013-10-10

    Herein, we describe a protocol for simultaneously measuring six proteins in saliva using a fiber-optic microsphere-based antibody array. The immuno-array technology employed combines the advantages of microsphere-based suspension array fabrication with the use of fluorescence microscopy. As described in the video protocol, commercially available 4.5 μm polymer microspheres were encoded into seven different types, differentiated by the concentration of two fluorescent dyes physically trapped inside the microspheres. The encoded microspheres containing surface carboxyl groups were modified with monoclonal capture antibodies through EDC/NHS coupling chemistry. To assemble the protein microarray, the different types of encoded and functionalized microspheres were mixed and randomly deposited in 4.5 μm microwells, which were chemically etched at the proximal end of a fiber-optic bundle. The fiber-optic bundle was used as both a carrier and for imaging the microspheres. Once assembled, the microarray was used to capture proteins in the saliva supernatant collected from the clinic. The detection was based on a sandwich immunoassay using a mixture of biotinylated detection antibodies for different analytes with a streptavidin-conjugated fluorescent probe, R-phycoerythrin. The microarray was imaged by fluorescence microscopy in three different channels, two for microsphere registration and one for the assay signal. The fluorescence micrographs were then decoded and analyzed using a homemade algorithm in MATLAB.

  12. Profiling Humoral Immune Responses to Clostridium difficile-Specific Antigens by Protein Microarray Analysis.

    Science.gov (United States)

    Negm, Ola H; Hamed, Mohamed R; Dilnot, Elizabeth M; Shone, Clifford C; Marszalowska, Izabela; Lynch, Mark; Loscher, Christine E; Edwards, Laura J; Tighe, Patrick J; Wilcox, Mark H; Monaghan, Tanya M

    2015-09-01

    Clostridium difficile is an anaerobic, Gram-positive, and spore-forming bacterium that is the leading worldwide infective cause of hospital-acquired and antibiotic-associated diarrhea. Several studies have reported associations between humoral immunity and the clinical course of C. difficile infection (CDI). Host humoral immune responses are determined using conventional enzyme-linked immunosorbent assay (ELISA) techniques. Herein, we report the first use of a novel protein microarray assay to determine systemic IgG antibody responses against a panel of highly purified C. difficile-specific antigens, including native toxins A and B (TcdA and TcdB, respectively), recombinant fragments of toxins A and B (TxA4 and TxB4, respectively), ribotype-specific surface layer proteins (SLPs; 001, 002, 027), and control proteins (tetanus toxoid and Candida albicans). Microarrays were probed with sera from a total of 327 individuals with CDI, cystic fibrosis without diarrhea, and healthy controls. For all antigens, precision profiles demonstrated ELISA in the quantification of antitoxin A and antitoxin B IgG. These results indicate that microarray is a suitable assay for defining humoral immune responses to C. difficile protein antigens and may have potential advantages in throughput, convenience, and cost. Copyright © 2015, American Society for Microbiology. All Rights Reserved.

  13. Global analysis of transcriptome responses and gene expression profiles to cold stress of Jatropha curcas L.

    Science.gov (United States)

    Wang, Haibo; Zou, Zhurong; Wang, Shasha; Gong, Ming

    2013-01-01

    Jatropha curcas L., also called the Physic nut, is an oil-rich shrub with multiple uses, including biodiesel production, and is currently exploited as a renewable energy resource in many countries. Nevertheless, because of its origin from the tropical MidAmerican zone, J. curcas confers an inherent but undesirable characteristic (low cold resistance) that may seriously restrict its large-scale popularization. This adaptive flaw can be genetically improved by elucidating the mechanisms underlying plant tolerance to cold temperatures. The newly developed Illumina Hiseq™ 2000 RNA-seq and Digital Gene Expression (DGE) are deep high-throughput approaches for gene expression analysis at the transcriptome level, using which we carefully investigated the gene expression profiles in response to cold stress to gain insight into the molecular mechanisms of cold response in J. curcas. In total, 45,251 unigenes were obtained by assembly of clean data generated by RNA-seq analysis of the J. curcas transcriptome. A total of 33,363 and 912 complete or partial coding sequences (CDSs) were determined by protein database alignments and ESTScan prediction, respectively. Among these unigenes, more than 41.52% were involved in approximately 128 known metabolic or signaling pathways, and 4,185 were possibly associated with cold resistance. DGE analysis was used to assess the changes in gene expression when exposed to cold condition (12°C) for 12, 24, and 48 h. The results showed that 3,178 genes were significantly upregulated and 1,244 were downregulated under cold stress. These genes were then functionally annotated based on the transcriptome data from RNA-seq analysis. This study provides a global view of transcriptome response and gene expression profiling of J. curcas in response to cold stress. The results can help improve our current understanding of the mechanisms underlying plant cold resistance and favor the screening of crucial genes for genetically enhancing cold resistance

  14. Comparative transcriptome analysis of two contrasting watermelon genotypes during fruit development and ripening

    OpenAIRE

    Zhu, Qianglong; Gao, Peng; Liu, Shi; Zhu, Zicheng; Amanullah, Sikandar; Davis, Angela R.; Luan, Feishi

    2017-01-01

    Background Watermelon [Citrullus lanatus (Thunb.) Matsum. & Nakai] is an economically important crop with an attractive ripe fruit that has colorful flesh. Fruit ripening is a complex, genetically programmed process. Results In this study, a comparative transcriptome analysis was performed to identify the regulators and pathways that are in