Microarray analysis of gene expression profiles in ripening pineapple fruits.

PubMed

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 ripening and non-climacteric fruit ripening in general.

Microarray analysis of gene expression profiles in ripening pineapple fruits

PubMed Central

2012-01-01

Background 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. Results 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. Conclusions 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 ripening and non-climacteric fruit ripening in general. PMID:23245313

Use of principal components analysis and protein microarray to explore the association of HIV-1-specific IgG responses with disease progression.

PubMed

Gerns Storey, Helen L; Richardson, Barbra A; Singa, Benson; Naulikha, Jackie; Prindle, Vivian C; Diaz-Ochoa, Vladimir E; Felgner, Phil L; Camerini, David; Horton, Helen; John-Stewart, Grace; Walson, Judd L

2014-01-01

The role of HIV-1-specific antibody responses in HIV disease progression is complex and would benefit from analysis techniques that examine clusterings of responses. Protein microarray platforms facilitate the simultaneous evaluation of numerous protein-specific antibody responses, though excessive data are cumbersome in analyses. Principal components analysis (PCA) reduces data dimensionality by generating fewer composite variables that maximally account for variance in a dataset. To identify clusters of antibody responses involved in disease control, we investigated the association of HIV-1-specific antibody responses by protein microarray, and assessed their association with disease progression using PCA in a nested cohort design. Associations observed among collections of antibody responses paralleled protein-specific responses. At baseline, greater antibody responses to the transmembrane glycoprotein (TM) and reverse transcriptase (RT) were associated with higher viral loads, while responses to the surface glycoprotein (SU), capsid (CA), matrix (MA), and integrase (IN) proteins were associated with lower viral loads. Over 12 months greater antibody responses were associated with smaller decreases in CD4 count (CA, MA, IN), and reduced likelihood of disease progression (CA, IN). PCA and protein microarray analyses highlighted a collection of HIV-specific antibody responses that together were associated with reduced disease progression, and may not have been identified by examining individual antibody responses. This technique may be useful to explore multifaceted host-disease interactions, such as HIV coinfections.

SYMBIOmatics: synergies in Medical Informatics and Bioinformatics--exploring current scientific literature for emerging topics.

PubMed

Rebholz-Schuhman, Dietrich; Cameron, Graham; Clark, Dominic; van Mulligen, Erik; Coatrieux, Jean-Louis; Del Hoyo Barbolla, Eva; Martin-Sanchez, Fernando; Milanesi, Luciano; Porro, Ivan; Beltrame, Francesco; Tollis, Ioannis; Van der Lei, Johan

2007-03-08

The SYMBIOmatics Specific Support Action (SSA) is "an information gathering and dissemination activity" that seeks "to identify synergies between the bioinformatics and the medical informatics" domain to improve collaborative progress between both domains (ref. to http://www.symbiomatics.org). As part of the project experts in both research fields will be identified and approached through a survey. To provide input to the survey, the scientific literature was analysed to extract topics relevant to both medical informatics and bioinformatics. This paper presents results of a systematic analysis of the scientific literature from medical informatics research and bioinformatics research. In the analysis pairs of words (bigrams) from the leading bioinformatics and medical informatics journals have been used as indication of existing and emerging technologies and topics over the period 2000-2005 ("recent") and 1990-1990 ("past"). We identified emerging topics that were equally important to bioinformatics and medical informatics in recent years such as microarray experiments, ontologies, open source, text mining and support vector machines. Emerging topics that evolved only in bioinformatics were system biology, protein interaction networks and statistical methods for microarray analyses, whereas emerging topics in medical informatics were grid technology and tissue microarrays. We conclude that although both fields have their own specific domains of interest, they share common technological developments that tend to be initiated by new developments in biotechnology and computer science.

SYMBIOmatics: Synergies in Medical Informatics and Bioinformatics – exploring current scientific literature for emerging topics

PubMed Central

Rebholz-Schuhman, Dietrich; Cameron, Graham; Clark, Dominic; van Mulligen, Erik; Coatrieux, Jean-Louis; Del Hoyo Barbolla, Eva; Martin-Sanchez, Fernando; Milanesi, Luciano; Porro, Ivan; Beltrame, Francesco; Tollis, Ioannis; Van der Lei, Johan

2007-01-01

Background The SYMBIOmatics Specific Support Action (SSA) is "an information gathering and dissemination activity" that seeks "to identify synergies between the bioinformatics and the medical informatics" domain to improve collaborative progress between both domains (ref. to ). As part of the project experts in both research fields will be identified and approached through a survey. To provide input to the survey, the scientific literature was analysed to extract topics relevant to both medical informatics and bioinformatics. Results This paper presents results of a systematic analysis of the scientific literature from medical informatics research and bioinformatics research. In the analysis pairs of words (bigrams) from the leading bioinformatics and medical informatics journals have been used as indication of existing and emerging technologies and topics over the period 2000–2005 ("recent") and 1990–1990 ("past"). We identified emerging topics that were equally important to bioinformatics and medical informatics in recent years such as microarray experiments, ontologies, open source, text mining and support vector machines. Emerging topics that evolved only in bioinformatics were system biology, protein interaction networks and statistical methods for microarray analyses, whereas emerging topics in medical informatics were grid technology and tissue microarrays. Conclusion We conclude that although both fields have their own specific domains of interest, they share common technological developments that tend to be initiated by new developments in biotechnology and computer science. PMID:17430562

Identification of differentially expressed genes and false discovery rate in microarray studies.

PubMed

Gusnanto, Arief; Calza, Stefano; Pawitan, Yudi

2007-04-01

To highlight the development in microarray data analysis for the identification of differentially expressed genes, particularly via control of false discovery rate. The emergence of high-throughput technology such as microarrays raises two fundamental statistical issues: multiplicity and sensitivity. We focus on the biological problem of identifying differentially expressed genes. First, multiplicity arises due to testing tens of thousands of hypotheses, rendering the standard P value meaningless. Second, known optimal single-test procedures such as the t-test perform poorly in the context of highly multiple tests. The standard approach of dealing with multiplicity is too conservative in the microarray context. The false discovery rate concept is fast becoming the key statistical assessment tool replacing the P value. We review the false discovery rate approach and argue that it is more sensible for microarray data. We also discuss some methods to take into account additional information from the microarrays to improve the false discovery rate. There is growing consensus on how to analyse microarray data using the false discovery rate framework in place of the classical P value. Further research is needed on the preprocessing of the raw data, such as the normalization step and filtering, and on finding the most sensitive test procedure.

An efficient method to identify differentially expressed genes in microarray experiments

PubMed Central

Qin, Huaizhen; Feng, Tao; Harding, Scott A.; Tsai, Chung-Jui; Zhang, Shuanglin

2013-01-01

Motivation Microarray experiments typically analyze thousands to tens of thousands of genes from small numbers of biological replicates. The fact that genes are normally expressed in functionally relevant patterns suggests that gene-expression data can be stratified and clustered into relatively homogenous groups. Cluster-wise dimensionality reduction should make it feasible to improve screening power while minimizing information loss. Results We propose a powerful and computationally simple method for finding differentially expressed genes in small microarray experiments. The method incorporates a novel stratification-based tight clustering algorithm, principal component analysis and information pooling. Comprehensive simulations show that our method is substantially more powerful than the popular SAM and eBayes approaches. We applied the method to three real microarray datasets: one from a Populus nitrogen stress experiment with 3 biological replicates; and two from public microarray datasets of human cancers with 10 to 40 biological replicates. In all three analyses, our method proved more robust than the popular alternatives for identification of differentially expressed genes. Availability The C++ code to implement the proposed method is available upon request for academic use. PMID:18453554

Addressable droplet microarrays for single cell protein analysis.

PubMed

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.

Ischemic and Nephrotoxic Acute Renal Failure are Distinguished by their Broad Transcriptomic Responses (102/160 char)

PubMed Central

Yuen, Peter S.T.; Jo, Sang-Kyung; Holly, Mikaela K.; Hu, Xuzhen; Star, Robert A.

2006-01-01

Acute renal failure (ARF) has a high morbidity and mortality. In animal ARF models, effective treatments must be administered before or shortly after the insult, limiting their clinical potential. We used microarrays to identify early biomarkers that distinguish ischemic from nephrotoxic ARF, or biomarkers that detect both injury types. We compared rat kidney transcriptomes 2 and 8 hours after ischemia/reperfusion and after mercuric chloride. Quality control and statistical analyses were necessary to normalize microarrays from different lots, eliminate outliers, and exclude unaltered genes. Principal component analysis revealed distinct ischemic and nephrotoxic trajectories, and clear array groupings. Therefore, we used supervised analysis, t-tests and fold changes, to compile gene lists for each group, exclusive or non-exclusive, alone or in combination. There was little network connectivity, even in the largest group. Some microarray-identified genes were validated by TaqMan assay, ruling out artifacts. Western blotting confirmed that HO-1 and ATF3 proteins were upregulated; however, unexpectedly, their localization changed within the kidney. HO-1 staining shifted from cortical (early) to outer stripe of the outer medulla (late), primarily in detaching cells, after mercuric chloride, but not ischemia/reperfusion. ATF3 staining was similar, but with additional early transient expression in the outer stripe after ischemia/reperfusion. We conclude that microarray-identified genes must be evaluated not only for protein levels, but also for anatomical distribution among different zones, nephron segments, or cell types. Although protein detection reagents are limited, microarray data lay a rich foundation to explore biomarkers, therapeutics, and pathophysiology of ARF. PMID:16507785

Molecular classification of benign prostatic hyperplasia: A gene expression profiling study in a rat model.

PubMed

Hata, Junya; Satoh, Yuichi; Akaihata, Hidenori; Hiraki, Hiroyuki; Ogawa, Soichiro; Haga, Nobuhiro; Ishibashi, Kei; Aikawa, Ken; Kojima, Yoshiyuki

2016-07-01

To characterize the molecular features of benign prostatic hyperplasia by carrying out a gene expression profiling analysis in a rat model. Fetal urogenital sinus isolated from 20-day-old male rat embryo was implanted into a pubertal male rat ventral prostate. The implanted urogenital sinus grew time-dependently, and the pathological findings at 3 weeks after implantation showed epithelial hyperplasia as well as stromal hyperplasia. Whole-genome oligonucleotide microarray analysis utilizing approximately 30 000 oligonucleotide probes was carried out using prostate specimens during the prostate growth process (3 weeks after implantation). Microarray analyses showed 926 upregulated (>2-fold change, P < 0.01) and 3217 downregulated genes (<0.5-fold change, P < 0.01) in benign prostatic hyperplasia specimens compared with normal prostate. Gene ontology analyses of upregulated genes showed predominant genetic themes of involvement in development (162 genes, P = 2.01 × 10(-4) ), response to stimulus (163 genes, P = 7.37 × 10(-13) ) and growth (32 genes, P = 1.93 × 10(-5) ). When we used both normal prostate and non-transplanted urogenital sinuses as controls to identify benign prostatic hyperplasia-specific genes, 507 and 406 genes were upregulated and downregulated, respectively. Functional network and pathway analyses showed that genes associated with apoptosis modulation by heat shock protein 70, interleukin-1, interleukin-2 and interleukin-5 signaling pathways, KIT signaling pathway, and secretin-like G-protein-coupled receptors, class B, were relatively activated during the growth process in the benign prostatic hyperplasia specimens. In contrast, genes associated with cholesterol biosynthesis were relatively inactivated. Our microarray analyses of the benign prostatic hyperplasia model rat might aid in clarifying the molecular mechanism of benign prostatic hyperplasia progression, and identifying molecular targets for benign prostatic hyperplasia treatment. © 2016 The Japanese Urological Association.

Microarray Analysis of Differential Gene Expression Profile Between Human Fetal and Adult Heart.

PubMed

Geng, Zhimin; Wang, Jue; Pan, Lulu; Li, Ming; Zhang, Jitai; Cai, Xueli; Chu, Maoping

2017-04-01

Although many changes have been discovered during heart maturation, the genetic mechanisms involved in the changes between immature and mature myocardium have only been partially elucidated. Here, gene expression profile changed between the human fetal and adult heart was characterized. A human microarray was applied to define the gene expression signatures of the fetal (13-17 weeks of gestation, n = 4) and adult hearts (30-40 years old, n = 4). Gene ontology analyses, pathway analyses, gene set enrichment analyses, and signal transduction network were performed to predict the function of the differentially expressed genes. Ten mRNAs were confirmed by quantificational real-time polymerase chain reaction. 5547 mRNAs were found to be significantly differentially expressed. "Cell cycle" was the most enriched pathway in the down-regulated genes. EFGR, IGF1R, and ITGB1 play a central role in the regulation of heart development. EGFR, IGF1R, and FGFR2 were the core genes regulating cardiac cell proliferation. The quantificational real-time polymerase chain reaction results were concordant with the microarray data. Our data identified the transcriptional regulation of heart development in the second trimester and the potential regulators that play a prominent role in the regulation of heart development and cardiac cells proliferation.

Building gene co-expression networks using transcriptomics data for systems biology investigations: Comparison of methods using microarray data

PubMed Central

Kadarmideen, Haja N; Watson-haigh, Nathan S

2012-01-01

Gene co-expression networks (GCN), built using high-throughput gene expression data are fundamental aspects of systems biology. The main aims of this study were to compare two popular approaches to building and analysing GCN. We use real ovine microarray transcriptomics datasets representing four different treatments with Metyrapone, an inhibitor of cortisol biosynthesis. We conducted several microarray quality control checks before applying GCN methods to filtered datasets. Then we compared the outputs of two methods using connectivity as a criterion, as it measures how well a node (gene) is connected within a network. The two GCN construction methods used were, Weighted Gene Co-expression Network Analysis (WGCNA) and Partial Correlation and Information Theory (PCIT) methods. Nodes were ranked based on their connectivity measures in each of the four different networks created by WGCNA and PCIT and node ranks in two methods were compared to identify those nodes which are highly differentially ranked (HDR). A total of 1,017 HDR nodes were identified across one or more of four networks. We investigated HDR nodes by gene enrichment analyses in relation to their biological relevance to phenotypes. We observed that, in contrast to WGCNA method, PCIT algorithm removes many of the edges of the most highly interconnected nodes. Removal of edges of most highly connected nodes or hub genes will have consequences for downstream analyses and biological interpretations. In general, for large GCN construction (with > 20000 genes) access to large computer clusters, particularly those with larger amounts of shared memory is recommended. PMID:23144540

mRNA-Based Parallel Detection of Active Methanotroph Populations by Use of a Diagnostic Microarray

PubMed Central

Bodrossy, Levente; Stralis-Pavese, Nancy; Konrad-Köszler, Marianne; Weilharter, Alexandra; Reichenauer, Thomas G.; Schöfer, David; Sessitsch, Angela

2006-01-01

A method was developed for the mRNA-based application of microbial diagnostic microarrays to detect active microbial populations. DNA- and mRNA-based analyses of environmental samples were compared and confirmed via quantitative PCR. Results indicated that mRNA-based microarray analyses may provide additional information on the composition and functioning of microbial communities. PMID:16461725

The Glycan Microarray Story from Construction to Applications.

PubMed

Hyun, Ji Young; Pai, Jaeyoung; Shin, Injae

2017-04-18

Not only are glycan-mediated binding processes in cells and organisms essential for a wide range of physiological processes, but they are also implicated in various pathological processes. As a result, elucidation of glycan-associated biomolecular interactions and their consequences is of great importance in basic biological research and biomedical applications. In 2002, we and others were the first to utilize glycan microarrays in efforts aimed at the rapid analysis of glycan-associated recognition events. Because they contain a number of glycans immobilized in a dense and orderly manner on a solid surface, glycan microarrays enable multiple parallel analyses of glycan-protein binding events while utilizing only small amounts of glycan samples. Therefore, this microarray technology has become a leading edge tool in studies aimed at elucidating roles played by glycans and glycan binding proteins in biological systems. In this Account, we summarize our efforts on the construction of glycan microarrays and their applications in studies of glycan-associated interactions. Immobilization strategies of functionalized and unmodified glycans on derivatized glass surfaces are described. Although others have developed immobilization techniques, our efforts have focused on improving the efficiencies and operational simplicity of microarray construction. The microarray-based technology has been most extensively used for rapid analysis of the glycan binding properties of proteins. In addition, glycan microarrays have been employed to determine glycan-protein interactions quantitatively, detect pathogens, and rapidly assess substrate specificities of carbohydrate-processing enzymes. More recently, the microarrays have been employed to identify functional glycans that elicit cell surface lectin-mediated cellular responses. Owing to these efforts, it is now possible to use glycan microarrays to expand the understanding of roles played by glycans and glycan binding proteins in biological systems.

Comprehensive analysis of differentially expressed profiles of lncRNAs and construction of miR-133b mediated ceRNA network in colorectal cancer.

PubMed

Wu, Hao; Wu, Runliu; Chen, Miao; Li, Daojiang; Dai, Jing; Zhang, Yi; Gao, Kai; Yu, Jun; Hu, Gui; Guo, Yihang; Lin, Changwei; Li, Xiaorong

2017-03-28

Growing evidence suggests that long non-coding RNAs (lncRNAs) play a key role in tumorigenesis. However, the mechanism remains largely unknown. Thousands of significantly dysregulated lncRNAs and mRNAs were identified by microarray. Furthermore, a miR-133b-meditated lncRNA-mRNA ceRNA network was revealed, a subset of which was validated in 14 paired CRC patient tumor/non-tumor samples. Gene set enrichment analysis (GSEA) results demonstrated that lncRNAs ENST00000520055 and ENST00000535511 shared KEGG pathways with miR-133b target genes. We used microarrays to survey the lncRNA and mRNA expression profiles of colorectal cancer and para-cancer tissues. Gene Ontology (GO) and KEGG pathway enrichment analyses were performed to explore the functions of the significantly dysregulated genes. An innovate method was employed that combined analyses of two microarray data sets to construct a miR-133b-mediated lncRNA-mRNA competing endogenous RNAs (ceRNA) network. Quantitative RT-PCR analysis was used to validate part of this network. GSEA was used to predict the potential functions of these lncRNAs. This study identifies and validates a new method to investigate the miR-133b-mediated lncRNA-mRNA ceRNA network and lays the foundation for future investigation into the role of lncRNAs in colorectal cancer.

Evaluation of microarray data normalization procedures using spike-in experiments

PubMed Central

Rydén, Patrik; Andersson, Henrik; Landfors, Mattias; Näslund, Linda; Hartmanová, Blanka; Noppa, Laila; Sjöstedt, Anders

2006-01-01

Background Recently, a large number of methods for the analysis of microarray data have been proposed but there are few comparisons of their relative performances. By using so-called spike-in experiments, it is possible to characterize the analyzed data and thereby enable comparisons of different analysis methods. Results A spike-in experiment using eight in-house produced arrays was used to evaluate established and novel methods for filtration, background adjustment, scanning, channel adjustment, and censoring. The S-plus package EDMA, a stand-alone tool providing characterization of analyzed cDNA-microarray data obtained from spike-in experiments, was developed and used to evaluate 252 normalization methods. For all analyses, the sensitivities at low false positive rates were observed together with estimates of the overall bias and the standard deviation. In general, there was a trade-off between the ability of the analyses to identify differentially expressed genes (i.e. the analyses' sensitivities) and their ability to provide unbiased estimators of the desired ratios. Virtually all analysis underestimated the magnitude of the regulations; often less than 50% of the true regulations were observed. Moreover, the bias depended on the underlying mRNA-concentration; low concentration resulted in high bias. Many of the analyses had relatively low sensitivities, but analyses that used either the constrained model (i.e. a procedure that combines data from several scans) or partial filtration (a novel method for treating data from so-called not-found spots) had with few exceptions high sensitivities. These methods gave considerable higher sensitivities than some commonly used analysis methods. Conclusion The use of spike-in experiments is a powerful approach for evaluating microarray preprocessing procedures. Analyzed data are characterized by properties of the observed log-ratios and the analysis' ability to detect differentially expressed genes. If bias is not a major problem; we recommend the use of either the CM-procedure or partial filtration. PMID:16774679

Identification of novel and known oocyte-specific genes using complementary DNA subtraction and microarray analysis in three different species.

PubMed

Vallée, Maud; Gravel, Catherine; Palin, Marie-France; Reghenas, Hélène; Stothard, Paul; Wishart, David S; Sirard, Marc-André

2005-07-01

The main objective of the present study was to identify novel oocyte-specific genes in three different species: bovine, mouse, and Xenopus laevis. To achieve this goal, two powerful technologies were combined: a polymerase chain reaction (PCR)-based cDNA subtraction, and cDNA microarrays. Three subtractive libraries consisting of 3456 clones were established and enriched for oocyte-specific transcripts. Sequencing analysis of the positive insert-containing clones resulted in the following classification: 53% of the clones corresponded to known cDNAs, 26% were classified as uncharacterized cDNAs, and a final 9% were classified as novel sequences. All these clones were used for cDNA microarray preparation. Results from these microarray analyses revealed that in addition to already known oocyte-specific genes, such as GDF9, BMP15, and ZP, known genes with unknown function in the oocyte were identified, such as a MLF1-interacting protein (MLF1IP), B-cell translocation gene 4 (BTG4), and phosphotyrosine-binding protein (xPTB). Furthermore, 15 novel oocyte-specific genes were validated by reverse transcription-PCR to confirm their preferential expression in the oocyte compared to somatic tissues. The results obtained in the present study confirmed that microarray analysis is a robust technique to identify true positives from the suppressive subtractive hybridization experiment. Furthermore, obtaining oocyte-specific genes from three species simultaneously allowed us to look at important genes that are conserved across species. Further characterization of these novel oocyte-specific genes will lead to a better understanding of the molecular mechanisms related to the unique functions found in the oocyte.

The low-abundance transcriptome reveals novel biomarkers, specific intracellular pathways and targetable genes associated with advanced gastric cancer.

PubMed

Bizama, Carolina; Benavente, Felipe; Salvatierra, Edgardo; Gutiérrez-Moraga, Ana; Espinoza, Jaime A; Fernández, Elmer A; Roa, Iván; Mazzolini, Guillermo; Sagredo, Eduardo A; Gidekel, Manuel; Podhajcer, Osvaldo L

2014-02-15

Studies on the low-abundance transcriptome are of paramount importance for identifying the intimate mechanisms of tumor progression that can lead to novel therapies. The aim of the present study was to identify novel markers and targetable genes and pathways in advanced human gastric cancer through analyses of the low-abundance transcriptome. The procedure involved an initial subtractive hybridization step, followed by global gene expression analysis using microarrays. We observed profound differences, both at the single gene and gene ontology levels, between the low-abundance transcriptome and the whole transcriptome. Analysis of the low-abundance transcriptome led to the identification and validation by tissue microarrays of novel biomarkers, such as LAMA3 and TTN; moreover, we identified cancer type-specific intracellular pathways and targetable genes, such as IRS2, IL17, IFNγ, VEGF-C, WISP1, FZD5 and CTBP1 that were not detectable by whole transcriptome analyses. We also demonstrated that knocking down the expression of CTBP1 sensitized gastric cancer cells to mainstay chemotherapeutic drugs. We conclude that the analysis of the low-abundance transcriptome provides useful insights into the molecular basis and treatment of cancer. © 2013 UICC.

A Model-Based Joint Identification of Differentially Expressed Genes and Phenotype-Associated Genes

PubMed Central

Seo, Minseok; Shin, Su-kyung; Kwon, Eun-Young; Kim, Sung-Eun; Bae, Yun-Jung; Lee, Seungyeoun; Sung, Mi-Kyung; Choi, Myung-Sook; Park, Taesung

2016-01-01

Over the last decade, many analytical methods and tools have been developed for microarray data. The detection of differentially expressed genes (DEGs) among different treatment groups is often a primary purpose of microarray data analysis. In addition, association studies investigating the relationship between genes and a phenotype of interest such as survival time are also popular in microarray data analysis. Phenotype association analysis provides a list of phenotype-associated genes (PAGs). However, it is sometimes necessary to identify genes that are both DEGs and PAGs. We consider the joint identification of DEGs and PAGs in microarray data analyses. The first approach we used was a naïve approach that detects DEGs and PAGs separately and then identifies the genes in an intersection of the list of PAGs and DEGs. The second approach we considered was a hierarchical approach that detects DEGs first and then chooses PAGs from among the DEGs or vice versa. In this study, we propose a new model-based approach for the joint identification of DEGs and PAGs. Unlike the previous two-step approaches, the proposed method identifies genes simultaneously that are DEGs and PAGs. This method uses standard regression models but adopts different null hypothesis from ordinary regression models, which allows us to perform joint identification in one-step. The proposed model-based methods were evaluated using experimental data and simulation studies. The proposed methods were used to analyze a microarray experiment in which the main interest lies in detecting genes that are both DEGs and PAGs, where DEGs are identified between two diet groups and PAGs are associated with four phenotypes reflecting the expression of leptin, adiponectin, insulin-like growth factor 1, and insulin. Model-based approaches provided a larger number of genes, which are both DEGs and PAGs, than other methods. Simulation studies showed that they have more power than other methods. Through analysis of data from experimental microarrays and simulation studies, the proposed model-based approach was shown to provide a more powerful result than the naïve approach and the hierarchical approach. Since our approach is model-based, it is very flexible and can easily handle different types of covariates. PMID:26964035

Microarray and growth analyses identify differences and similarities of early corn response to weeds, shade, and nitrogen stress

USDA-ARS?s Scientific Manuscript database

Weed interference with crop growth is often attributed to water, nutrient, or light competition; however, specific physiological responses to these stresses are not well described. This study’s objective was to compare growth, yield, and gene expression responses of corn to nitrogen (N), low light (...

Transcriptome profiling and expression analyses of genes critical to wheat adaptation to low temperature

USDA-ARS?s Scientific Manuscript database

Background: To identify the genes involved in the development of low temperature (LT) tolerance in hexaploid wheat, we examined the global changes in expression in response to cold of the 55,052 potentially unique genes represented in the Affymetrix Wheat Genome microarray. We compared the expressi...

Performing statistical analyses on quantitative data in Taverna workflows: an example using R and maxdBrowse to identify differentially-expressed genes from microarray data.

PubMed

Li, Peter; Castrillo, Juan I; Velarde, Giles; Wassink, Ingo; Soiland-Reyes, Stian; Owen, Stuart; Withers, David; Oinn, Tom; Pocock, Matthew R; Goble, Carole A; Oliver, Stephen G; Kell, Douglas B

2008-08-07

There has been a dramatic increase in the amount of quantitative data derived from the measurement of changes at different levels of biological complexity during the post-genomic era. However, there are a number of issues associated with the use of computational tools employed for the analysis of such data. For example, computational tools such as R and MATLAB require prior knowledge of their programming languages in order to implement statistical analyses on data. Combining two or more tools in an analysis may also be problematic since data may have to be manually copied and pasted between separate user interfaces for each tool. Furthermore, this transfer of data may require a reconciliation step in order for there to be interoperability between computational tools. Developments in the Taverna workflow system have enabled pipelines to be constructed and enacted for generic and ad hoc analyses of quantitative data. Here, we present an example of such a workflow involving the statistical identification of differentially-expressed genes from microarray data followed by the annotation of their relationships to cellular processes. This workflow makes use of customised maxdBrowse web services, a system that allows Taverna to query and retrieve gene expression data from the maxdLoad2 microarray database. These data are then analysed by R to identify differentially-expressed genes using the Taverna RShell processor which has been developed for invoking this tool when it has been deployed as a service using the RServe library. In addition, the workflow uses Beanshell scripts to reconcile mismatches of data between services as well as to implement a form of user interaction for selecting subsets of microarray data for analysis as part of the workflow execution. A new plugin system in the Taverna software architecture is demonstrated by the use of renderers for displaying PDF files and CSV formatted data within the Taverna workbench. Taverna can be used by data analysis experts as a generic tool for composing ad hoc analyses of quantitative data by combining the use of scripts written in the R programming language with tools exposed as services in workflows. When these workflows are shared with colleagues and the wider scientific community, they provide an approach for other scientists wanting to use tools such as R without having to learn the corresponding programming language to analyse their own data.

Performing statistical analyses on quantitative data in Taverna workflows: An example using R and maxdBrowse to identify differentially-expressed genes from microarray data

PubMed Central

Li, Peter; Castrillo, Juan I; Velarde, Giles; Wassink, Ingo; Soiland-Reyes, Stian; Owen, Stuart; Withers, David; Oinn, Tom; Pocock, Matthew R; Goble, Carole A; Oliver, Stephen G; Kell, Douglas B

2008-01-01

Background There has been a dramatic increase in the amount of quantitative data derived from the measurement of changes at different levels of biological complexity during the post-genomic era. However, there are a number of issues associated with the use of computational tools employed for the analysis of such data. For example, computational tools such as R and MATLAB require prior knowledge of their programming languages in order to implement statistical analyses on data. Combining two or more tools in an analysis may also be problematic since data may have to be manually copied and pasted between separate user interfaces for each tool. Furthermore, this transfer of data may require a reconciliation step in order for there to be interoperability between computational tools. Results Developments in the Taverna workflow system have enabled pipelines to be constructed and enacted for generic and ad hoc analyses of quantitative data. Here, we present an example of such a workflow involving the statistical identification of differentially-expressed genes from microarray data followed by the annotation of their relationships to cellular processes. This workflow makes use of customised maxdBrowse web services, a system that allows Taverna to query and retrieve gene expression data from the maxdLoad2 microarray database. These data are then analysed by R to identify differentially-expressed genes using the Taverna RShell processor which has been developed for invoking this tool when it has been deployed as a service using the RServe library. In addition, the workflow uses Beanshell scripts to reconcile mismatches of data between services as well as to implement a form of user interaction for selecting subsets of microarray data for analysis as part of the workflow execution. A new plugin system in the Taverna software architecture is demonstrated by the use of renderers for displaying PDF files and CSV formatted data within the Taverna workbench. Conclusion Taverna can be used by data analysis experts as a generic tool for composing ad hoc analyses of quantitative data by combining the use of scripts written in the R programming language with tools exposed as services in workflows. When these workflows are shared with colleagues and the wider scientific community, they provide an approach for other scientists wanting to use tools such as R without having to learn the corresponding programming language to analyse their own data. PMID:18687127

Validation of MIMGO: a method to identify differentially expressed GO terms in a microarray dataset

PubMed Central

2012-01-01

Background We previously proposed an algorithm for the identification of GO terms that commonly annotate genes whose expression is upregulated or downregulated in some microarray data compared with in other microarray data. We call these “differentially expressed GO terms” and have named the algorithm “matrix-assisted identification method of differentially expressed GO terms” (MIMGO). MIMGO can also identify microarray data in which genes annotated with a differentially expressed GO term are upregulated or downregulated. However, MIMGO has not yet been validated on a real microarray dataset using all available GO terms. Findings We combined Gene Set Enrichment Analysis (GSEA) with MIMGO to identify differentially expressed GO terms in a yeast cell cycle microarray dataset. GSEA followed by MIMGO (GSEA + MIMGO) correctly identified (p < 0.05) microarray data in which genes annotated to differentially expressed GO terms are upregulated. We found that GSEA + MIMGO was slightly less effective than, or comparable to, GSEA (Pearson), a method that uses Pearson’s correlation as a metric, at detecting true differentially expressed GO terms. However, unlike other methods including GSEA (Pearson), GSEA + MIMGO can comprehensively identify the microarray data in which genes annotated with a differentially expressed GO term are upregulated or downregulated. Conclusions MIMGO is a reliable method to identify differentially expressed GO terms comprehensively. PMID:23232071

Shrinkage regression-based methods for microarray missing value imputation.

PubMed

Wang, Hsiuying; Chiu, Chia-Chun; Wu, Yi-Ching; Wu, Wei-Sheng

2013-01-01

Missing values commonly occur in the microarray data, which usually contain more than 5% missing values with up to 90% of genes affected. Inaccurate missing value estimation results in reducing the power of downstream microarray data analyses. Many types of methods have been developed to estimate missing values. Among them, the regression-based methods are very popular and have been shown to perform better than the other types of methods in many testing microarray datasets. To further improve the performances of the regression-based methods, we propose shrinkage regression-based methods. Our methods take the advantage of the correlation structure in the microarray data and select similar genes for the target gene by Pearson correlation coefficients. Besides, our methods incorporate the least squares principle, utilize a shrinkage estimation approach to adjust the coefficients of the regression model, and then use the new coefficients to estimate missing values. Simulation results show that the proposed methods provide more accurate missing value estimation in six testing microarray datasets than the existing regression-based methods do. Imputation of missing values is a very important aspect of microarray data analyses because most of the downstream analyses require a complete dataset. Therefore, exploring accurate and efficient methods for estimating missing values has become an essential issue. Since our proposed shrinkage regression-based methods can provide accurate missing value estimation, they are competitive alternatives to the existing regression-based methods.

RNA transcriptional biosignature analysis for identifying febrile infants with serious bacterial infections in the emergency department: a feasibility study.

PubMed

Mahajan, Prashant; Kuppermann, Nathan; Suarez, Nicolas; Mejias, Asuncion; Casper, Charlie; Dean, J Michael; Ramilo, Octavio

2015-01-01

To develop the infrastructure and demonstrate the feasibility of conducting microarray-based RNA transcriptional profile analyses for the diagnosis of serious bacterial infections in febrile infants 60 days and younger in a multicenter pediatric emergency research network. We designed a prospective multicenter cohort study with the aim of enrolling more than 4000 febrile infants 60 days and younger. To ensure success of conducting complex genomic studies in emergency department (ED) settings, we established an infrastructure within the Pediatric Emergency Care Applied Research Network, including 21 sites, to evaluate RNA transcriptional profiles in young febrile infants. We developed a comprehensive manual of operations and trained site investigators to obtain and process blood samples for RNA extraction and genomic analyses. We created standard operating procedures for blood sample collection, processing, storage, shipping, and analyses. We planned to prospectively identify, enroll, and collect 1 mL blood samples for genomic analyses from eligible patients to identify logistical issues with study procedures. Finally, we planned to batch blood samples and determined RNA quantity and quality at the central microarray laboratory and organized data analysis with the Pediatric Emergency Care Applied Research Network data coordinating center. Below we report on establishment of the infrastructure and the feasibility success in the first year based on the enrollment of a limited number of patients. We successfully established the infrastructure at 21 EDs. Over the first 5 months we enrolled 79% (74 of 94) of eligible febrile infants. We were able to obtain and ship 1 mL of blood from 74% (55 of 74) of enrolled participants, with at least 1 sample per participating ED. The 55 samples were shipped and evaluated at the microarray laboratory, and 95% (52 of 55) of blood samples were of adequate quality and contained sufficient RNA for expression analysis. It is possible to create a robust infrastructure to conduct genomic studies in young febrile infants in the context of a multicenter pediatric ED research setting. The sufficient quantity and high quality of RNA obtained suggests that whole blood transcriptional profile analysis for the diagnostic evaluation of young febrile infants can be successfully performed in this setting.

Discrimination of Influenza Infection (A/2009 H1N1) from Prior Exposure by Antibody Protein Microarray Analysis

PubMed Central

te Beest, Dennis; de Bruin, Erwin; Imholz, Sandra; Wallinga, Jacco; Teunis, Peter; Koopmans, Marion; van Boven, Michiel

2014-01-01

Reliable discrimination of recent influenza A infection from previous exposure using hemagglutination inhibition (HI) or virus neutralization tests is currently not feasible. This is due to low sensitivity of the tests and the interference of antibody responses generated by previous infections. Here we investigate the diagnostic characteristics of a newly developed antibody (HA1) protein microarray using data from cross-sectional serological studies carried out before and after the pandemic of 2009. The data are analysed by mixture models, providing a probabilistic classification of sera (susceptible, prior-exposed, recently infected). Estimated sensitivity and specificity for identifying A/2009 infections are low using HI (66% and 51%), and high when using A/2009 microarray data alone or together with A/1918 microarray data (96% and 95%). As a heuristic, a high A/2009 to A/1918 antibody ratio (>1.05) is indicative of recent infection, while a low ratio is indicative of a pre-existing response, even if the A/2009 titer is high. We conclude that highly sensitive and specific classification of individual sera is possible using the protein microarray, thereby enabling precise estimation of age-specific infection attack rates in the population even if sample sizes are small. PMID:25405997

Vaginal microbial flora analysis by next generation sequencing and microarrays; can microbes indicate vaginal origin in a forensic context?

PubMed

Benschop, Corina C G; Quaak, Frederike C A; Boon, Mathilde E; Sijen, Titia; Kuiper, Irene

2012-03-01

Forensic analysis of biological traces generally encompasses the investigation of both the person who contributed to the trace and the body site(s) from which the trace originates. For instance, for sexual assault cases, it can be beneficial to distinguish vaginal samples from skin or saliva samples. In this study, we explored the use of microbial flora to indicate vaginal origin. First, we explored the vaginal microbiome for a large set of clinical vaginal samples (n = 240) by next generation sequencing (n = 338,184 sequence reads) and found 1,619 different sequences. Next, we selected 389 candidate probes targeting genera or species and designed a microarray, with which we analysed a diverse set of samples; 43 DNA extracts from vaginal samples and 25 DNA extracts from samples from other body sites, including sites in close proximity of or in contact with the vagina. Finally, we used the microarray results and next generation sequencing dataset to assess the potential for a future approach that uses microbial markers to indicate vaginal origin. Since no candidate genera/species were found to positively identify all vaginal DNA extracts on their own, while excluding all non-vaginal DNA extracts, we deduce that a reliable statement about the cellular origin of a biological trace should be based on the detection of multiple species within various genera. Microarray analysis of a sample will then render a microbial flora pattern that is probably best analysed in a probabilistic approach.

Microarray Analyses and Comparisons of Upper or Lower Flanks of Rice Shoot Base Preceding Gravitropic Bending

PubMed Central

Zang, Aiping; Chen, Haiying; Dou, Xianying; Jin, Jing; Cai, Weiming

2013-01-01

Gravitropism is a complex process involving a series of physiological pathways. Despite ongoing research, gravitropism sensing and response mechanisms are not well understood. To identify the key transcripts and corresponding pathways in gravitropism, a whole-genome microarray approach was used to analyze transcript abundance in the shoot base of rice (Oryza sativa sp. japonica) at 0.5 h and 6 h after gravistimulation by horizontal reorientation. Between upper and lower flanks of the shoot base, 167 transcripts at 0.5 h and 1202 transcripts at 6 h were discovered to be significantly different in abundance by 2-fold. Among these transcripts, 48 were found to be changed both at 0.5 h and 6 h, while 119 transcripts were only changed at 0.5 h and 1154 transcripts were changed at 6 h in association with gravitropism. MapMan and PageMan analyses were used to identify transcripts significantly changed in abundance. The asymmetric regulation of transcripts related to phytohormones, signaling, RNA transcription, metabolism and cell wall-related categories between upper and lower flanks were demonstrated. Potential roles of the identified transcripts in gravitropism are discussed. Our results suggest that the induction of asymmetrical transcription, likely as a consequence of gravitropic reorientation, precedes gravitropic bending in the rice shoot base. PMID:24040303

Defining the interaction of human soluble lectin ZG16p and mycobacterial phosphatidylinositol mannosides

PubMed Central

Ikeda, Akemi; Kojima-Aikawa, Kyoko; Taniguchi, Naoyuki; Varón Silva, Daniel; Feizi, Ten; Seeberger, Peter H.; Yamaguchi, Yoshiki

2018-01-01

ZG16p is a soluble mammalian lectin that interacts with mannose and heparan sulfate. Here we describe detailed analyses of the interactions of human ZG16p with mycobacterial phosphatidylinositol mannosides (PIMs), using glycan microarray and NMR. Pathogen-related glycan microarray analysis identified phosphatidylinositol mono- and di-mannosides (PIM1 and PIM2) as novel ligand candidates of ZG16p. Saturation Transfer Difference (STD) NMR and transferred NOE experiments with chemically synthesized PIM glycans indicate that PIMs preferentially interacts with ZG16p using the mannose residues. Binding site of PIMs is identified by chemical shift perturbation experiments using uniformly 15N-labeled ZG16p. NMR results with docking simulations suggest a binding mode of ZG16p and PIM glycan, which would help to consider the physiological role of ZG16p. PMID:25919894

The Development of Protein Microarrays and Their Applications in DNA-Protein and Protein-Protein Interaction Analyses of Arabidopsis Transcription Factors

PubMed Central

Gong, Wei; He, Kun; Covington, Mike; Dinesh-Kumar, S. P.; Snyder, Michael; Harmer, Stacey L.; Zhu, Yu-Xian; Deng, Xing Wang

2009-01-01

We used our collection of Arabidopsis transcription factor (TF) ORFeome clones to construct protein microarrays containing as many as 802 TF proteins. These protein microarrays were used for both protein-DNA and protein-protein interaction analyses. For protein-DNA interaction studies, we examined AP2/ERF family TFs and their cognate cis-elements. By careful comparison of the DNA-binding specificity of 13 TFs on the protein microarray with previous non-microarray data, we showed that protein microarrays provide an efficient and high throughput tool for genome-wide analysis of TF-DNA interactions. This microarray protein-DNA interaction analysis allowed us to derive a comprehensive view of DNA-binding profiles of AP2/ERF family proteins in Arabidopsis. It also revealed four TFs that bound the EE (evening element) and had the expected phased gene expression under clock-regulation, thus providing a basis for further functional analysis of their roles in clock regulation of gene expression. We also developed procedures for detecting protein interactions using this TF protein microarray and discovered four novel partners that interact with HY5, which can be validated by yeast two-hybrid assays. Thus, plant TF protein microarrays offer an attractive high-throughput alternative to traditional techniques for TF functional characterization on a global scale. PMID:19802365

Expression profiling and pathway analysis of Krüppel-like factor 4 in mouse embryonic fibroblasts

PubMed Central

Hagos, Engda G; Ghaleb, Amr M; Kumar, Amrita; Neish, Andrew S; Yang, Vincent W

2011-01-01

Background: Krüppel-like factor 4 (KLF4) is a zinc-finger transcription factor with diverse regulatory functions in proliferation, differentiation, and development. KLF4 also plays a role in inflammation, tumorigenesis, and reprogramming of somatic cells to induced pluripotent stem (iPS) cells. To gain insight into the mechanisms by which KLF4 regulates these processes, we conducted DNA microarray analyses to identify differentially expressed genes in mouse embryonic fibroblasts (MEFs) wild type and null for Klf4. Methods: Expression profiles of fibroblasts isolated from mouse embryos wild type or null for the Klf4 alleles were examined by DNA microarrays. Differentially expressed genes were subjected to the Database for Annotation, Visualization and Integrated Discovery (DAVID). The microarray data were also interrogated with the Ingenuity Pathway Analysis (IPA) and Gene Set Enrichment Analysis (GSEA) for pathway identification. Results obtained from the microarray analysis were confirmed by Western blotting for select genes with biological relevance to determine the correlation between mRNA and protein levels. Results: One hundred and sixty three up-regulated and 88 down-regulated genes were identified that demonstrated a fold-change of at least 1.5 and a P-value < 0.05 in Klf4-null MEFs compared to wild type MEFs. Many of the up-regulated genes in Klf4-null MEFs encode proto-oncogenes, growth factors, extracellular matrix, and cell cycle activators. In contrast, genes encoding tumor suppressors and those involved in JAK-STAT signaling pathways are down-regulated in Klf4-null MEFs. IPA and GSEA also identified various pathways that are regulated by KLF4. Lastly, Western blotting of select target genes confirmed the changes revealed by microarray data. Conclusions: These data are not only consistent with previous functional studies of KLF4's role in tumor suppression and somatic cell reprogramming, but also revealed novel target genes that mediate KLF4's functions. PMID:21892412

Gene-expression profiling using suppression-subtractive hybridization and cDNA microarray in rat mononuclear cells in response to welding-fume exposure.

PubMed

Rim, Kyung Taek; Park, Kun Koo; Sung, Jae Hyuck; Chung, Yong Hyun; Han, Jeong Hee; Cho, Key Seung; Kim, Kwang Jong; Yu, Il Je

2004-06-01

Welders with radiographic pneumoconiosis abnormalities have shown a gradual clearing of the X-ray identified effects following removal from exposure. In some cases, the pulmonary fibrosis associated with welding fumes appears in a more severe form in welders. Accordingly, for the early detection of welding-fume-exposure-induced pulmonary fibrosis, the gene expression profiles of peripheral mononuclear cells from rats exposed to welding fumes were studied using suppression-subtractive hybridization (SSH) and a cDNA microarray. As such, Sprague-Dawley rats were exposed to a stainless steel arc welding fume for 2 h/day in an inhalation chamber with a 1107.5 +/- 2.6 mg/m3 concentration of total suspended particulate (TSP) for 30 days. Thereafter, the total RNA was extracted from the peripheral blood mononuclear cells, the cDNA synthesized from the total RNA using the SMART PCR cDNA method, and SSH performed to select the welding-fume-exposure-regulated genes. The cDNAs identified by the SSH were then cloned into a plasmid miniprep, sequenced and the sequences analysed using the NCBI BLAST programme. In the SSH cloned cDNA microarray analysis, five genes were found to increase their expression by 1.9-fold or more, including Rgs 14, which plays an important function in cellular signal transduction pathways; meanwhile 36 genes remained the same and 30 genes decreased their expression by more than 59%, including genes associated with the immune response, transcription factors and tyrosine kinases. Among the 5200 genes analysed, 256 genes (5.1%) were found to increase their gene expression, while 742 genes (15%) decreased their gene expression in response to the welding-fume exposure when tested using a commercial 5.0k DNA microarray. Therefore, unlike exposure to other toxic substances, prolonged welding-fume exposure was found to substantially downregulate many genes.

ArrayPitope: Automated Analysis of Amino Acid Substitutions for Peptide Microarray-Based Antibody Epitope Mapping.

PubMed

Hansen, Christian Skjødt; Østerbye, Thomas; Marcatili, Paolo; Lund, Ole; Buus, Søren; Nielsen, Morten

2017-01-01

Identification of epitopes targeted by antibodies (B cell epitopes) is of critical importance for the development of many diagnostic and therapeutic tools. For clinical usage, such epitopes must be extensively characterized in order to validate specificity and to document potential cross-reactivity. B cell epitopes are typically classified as either linear epitopes, i.e. short consecutive segments from the protein sequence or conformational epitopes adapted through native protein folding. Recent advances in high-density peptide microarrays enable high-throughput, high-resolution identification and characterization of linear B cell epitopes. Using exhaustive amino acid substitution analysis of peptides originating from target antigens, these microarrays can be used to address the specificity of polyclonal antibodies raised against such antigens containing hundreds of epitopes. However, the interpretation of the data provided in such large-scale screenings is far from trivial and in most cases it requires advanced computational and statistical skills. Here, we present an online application for automated identification of linear B cell epitopes, allowing the non-expert user to analyse peptide microarray data. The application takes as input quantitative peptide data of fully or partially substituted overlapping peptides from a given antigen sequence and identifies epitope residues (residues that are significantly affected by substitutions) and visualize the selectivity towards each residue by sequence logo plots. Demonstrating utility, the application was used to identify and address the antibody specificity of 18 linear epitope regions in Human Serum Albumin (HSA), using peptide microarray data consisting of fully substituted peptides spanning the entire sequence of HSA and incubated with polyclonal rabbit anti-HSA (and mouse anti-rabbit-Cy3). The application is made available at: www.cbs.dtu.dk/services/ArrayPitope.

ArrayPitope: Automated Analysis of Amino Acid Substitutions for Peptide Microarray-Based Antibody Epitope Mapping

PubMed Central

Hansen, Christian Skjødt; Østerbye, Thomas; Marcatili, Paolo; Lund, Ole; Buus, Søren

2017-01-01

Identification of epitopes targeted by antibodies (B cell epitopes) is of critical importance for the development of many diagnostic and therapeutic tools. For clinical usage, such epitopes must be extensively characterized in order to validate specificity and to document potential cross-reactivity. B cell epitopes are typically classified as either linear epitopes, i.e. short consecutive segments from the protein sequence or conformational epitopes adapted through native protein folding. Recent advances in high-density peptide microarrays enable high-throughput, high-resolution identification and characterization of linear B cell epitopes. Using exhaustive amino acid substitution analysis of peptides originating from target antigens, these microarrays can be used to address the specificity of polyclonal antibodies raised against such antigens containing hundreds of epitopes. However, the interpretation of the data provided in such large-scale screenings is far from trivial and in most cases it requires advanced computational and statistical skills. Here, we present an online application for automated identification of linear B cell epitopes, allowing the non-expert user to analyse peptide microarray data. The application takes as input quantitative peptide data of fully or partially substituted overlapping peptides from a given antigen sequence and identifies epitope residues (residues that are significantly affected by substitutions) and visualize the selectivity towards each residue by sequence logo plots. Demonstrating utility, the application was used to identify and address the antibody specificity of 18 linear epitope regions in Human Serum Albumin (HSA), using peptide microarray data consisting of fully substituted peptides spanning the entire sequence of HSA and incubated with polyclonal rabbit anti-HSA (and mouse anti-rabbit-Cy3). The application is made available at: www.cbs.dtu.dk/services/ArrayPitope. PMID:28095436

A comparative study of RNA-Seq and microarray data analysis on the two examples of rectal-cancer patients and Burkitt Lymphoma cells.

PubMed

Wolff, Alexander; Bayerlová, Michaela; Gaedcke, Jochen; Kube, Dieter; Beißbarth, Tim

2018-01-01

Pipeline comparisons for gene expression data are highly valuable for applied real data analyses, as they enable the selection of suitable analysis strategies for the dataset at hand. Such pipelines for RNA-Seq data should include mapping of reads, counting and differential gene expression analysis or preprocessing, normalization and differential gene expression in case of microarray analysis, in order to give a global insight into pipeline performances. Four commonly used RNA-Seq pipelines (STAR/HTSeq-Count/edgeR, STAR/RSEM/edgeR, Sailfish/edgeR, TopHat2/Cufflinks/CuffDiff)) were investigated on multiple levels (alignment and counting) and cross-compared with the microarray counterpart on the level of gene expression and gene ontology enrichment. For these comparisons we generated two matched microarray and RNA-Seq datasets: Burkitt Lymphoma cell line data and rectal cancer patient data. The overall mapping rate of STAR was 98.98% for the cell line dataset and 98.49% for the patient dataset. Tophat's overall mapping rate was 97.02% and 96.73%, respectively, while Sailfish had only an overall mapping rate of 84.81% and 54.44%. The correlation of gene expression in microarray and RNA-Seq data was moderately worse for the patient dataset (ρ = 0.67-0.69) than for the cell line dataset (ρ = 0.87-0.88). An exception were the correlation results of Cufflinks, which were substantially lower (ρ = 0.21-0.29 and 0.34-0.53). For both datasets we identified very low numbers of differentially expressed genes using the microarray platform. For RNA-Seq we checked the agreement of differentially expressed genes identified in the different pipelines and of GO-term enrichment results. In conclusion the combination of STAR aligner with HTSeq-Count followed by STAR aligner with RSEM and Sailfish generated differentially expressed genes best suited for the dataset at hand and in agreement with most of the other transcriptomics pipelines.

Dual-color Proteomic Profiling of Complex Samples with a Microarray of 810 Cancer-related Antibodies*

PubMed Central

Schröder, Christoph; Jacob, Anette; Tonack, Sarah; Radon, Tomasz P.; Sill, Martin; Zucknick, Manuela; Rüffer, Sven; Costello, Eithne; Neoptolemos, John P.; Crnogorac-Jurcevic, Tatjana; Bauer, Andrea; Fellenberg, Kurt; Hoheisel, Jörg D.

2010-01-01

Antibody microarrays have the potential to enable comprehensive proteomic analysis of small amounts of sample material. Here, protocols are presented for the production, quality assessment, and reproducible application of antibody microarrays in a two-color mode with an array of 1,800 features, representing 810 antibodies that were directed at 741 cancer-related proteins. In addition to measures of array quality, we implemented indicators for the accuracy and significance of dual-color detection. Dual-color measurements outperform a single-color approach concerning assay reproducibility and discriminative power. In the analysis of serum samples, depletion of high-abundance proteins did not improve technical assay quality. On the contrary, depletion introduced a strong bias in protein representation. In an initial study, we demonstrated the applicability of the protocols to proteins derived from urine samples. We identified differences between urine samples from pancreatic cancer patients and healthy subjects and between sexes. This study demonstrates that biomedically relevant data can be produced. As demonstrated by the thorough quality analysis, the dual-color antibody array approach proved to be competitive with other proteomic techniques and comparable in performance to transcriptional microarray analyses. PMID:20164060

High density DNA microarrays: algorithms and biomedical applications.

PubMed

Liu, Wei-Min

2004-08-01

DNA microarrays are devices capable of detecting the identity and abundance of numerous DNA or RNA segments in samples. They are used for analyzing gene expressions, identifying genetic markers and detecting mutations on a genomic scale. The fundamental chemical mechanism of DNA microarrays is the hybridization between probes and targets due to the hydrogen bonds of nucleotide base pairing. Since the cross hybridization is inevitable, and probes or targets may form undesirable secondary or tertiary structures, the microarray data contain noise and depend on experimental conditions. It is crucial to apply proper statistical algorithms to obtain useful signals from noisy data. After we obtained the signals of a large amount of probes, we need to derive the biomedical information such as the existence of a transcript in a cell, the difference of expression levels of a gene in multiple samples, and the type of a genetic marker. Furthermore, after the expression levels of thousands of genes or the genotypes of thousands of single nucleotide polymorphisms are determined, it is usually important to find a small number of genes or markers that are related to a disease, individual reactions to drugs, or other phenotypes. All these applications need careful data analyses and reliable algorithms.

EMAAS: An extensible grid-based Rich Internet Application for microarray data analysis and management

PubMed Central

Barton, G; Abbott, J; Chiba, N; Huang, DW; Huang, Y; Krznaric, M; Mack-Smith, J; Saleem, A; Sherman, BT; Tiwari, B; Tomlinson, C; Aitman, T; Darlington, J; Game, L; Sternberg, MJE; Butcher, SA

2008-01-01

Background Microarray experimentation requires the application of complex analysis methods as well as the use of non-trivial computer technologies to manage the resultant large data sets. This, together with the proliferation of tools and techniques for microarray data analysis, makes it very challenging for a laboratory scientist to keep up-to-date with the latest developments in this field. Our aim was to develop a distributed e-support system for microarray data analysis and management. Results EMAAS (Extensible MicroArray Analysis System) is a multi-user rich internet application (RIA) providing simple, robust access to up-to-date resources for microarray data storage and analysis, combined with integrated tools to optimise real time user support and training. The system leverages the power of distributed computing to perform microarray analyses, and provides seamless access to resources located at various remote facilities. The EMAAS framework allows users to import microarray data from several sources to an underlying database, to pre-process, quality assess and analyse the data, to perform functional analyses, and to track data analysis steps, all through a single easy to use web portal. This interface offers distance support to users both in the form of video tutorials and via live screen feeds using the web conferencing tool EVO. A number of analysis packages, including R-Bioconductor and Affymetrix Power Tools have been integrated on the server side and are available programmatically through the Postgres-PLR library or on grid compute clusters. Integrated distributed resources include the functional annotation tool DAVID, GeneCards and the microarray data repositories GEO, CELSIUS and MiMiR. EMAAS currently supports analysis of Affymetrix 3' and Exon expression arrays, and the system is extensible to cater for other microarray and transcriptomic platforms. Conclusion EMAAS enables users to track and perform microarray data management and analysis tasks through a single easy-to-use web application. The system architecture is flexible and scalable to allow new array types, analysis algorithms and tools to be added with relative ease and to cope with large increases in data volume. PMID:19032776

Identification of genes related to high royal jelly production in the honey bee (Apis mellifera) using microarray analysis

PubMed Central

Nie, Hongyi; Liu, Xiaoyan; Pan, Jiao; Li, Wenfeng; Li, Zhiguo; Zhang, Shaowu; Chen, Shenglu; Miao, Xiaoqing; Zheng, Nenggan; Su, Songkun

2017-01-01

Abstract China is the largest royal jelly producer and exporter in the world, and high royal jelly-yielding strains have been bred in the country for approximately three decades. However, information on the molecular mechanism underlying high royal jelly production is scarce. Here, a cDNA microarray was used to screen and identify differentially expressed genes (DEGs) to obtain an overview on the changes in gene expression levels between high and low royal jelly producing bees. We developed a honey bee gene chip that covered 11,689 genes, and this chip was hybridised with cDNA generated from RNA isolated from heads of nursing bees. A total of 369 DEGs were identified between high and low royal jelly producing bees. Amongst these DEGs, 201 (54.47%) genes were up-regulated, whereas 168 (45.53%) were down-regulated in high royal jelly-yielding bees. Gene ontology (GO) analyses showed that they are mainly involved in four key biological processes, and pathway analyses revealed that they belong to a total of 46 biological pathways. These results provide a genetic basis for further studies on the molecular mechanisms involved in high royal jelly production. PMID:28981563

Identification of genes related to high royal jelly production in the honey bee (Apis mellifera) using microarray analysis.

PubMed

Nie, Hongyi; Liu, Xiaoyan; Pan, Jiao; Li, Wenfeng; Li, Zhiguo; Zhang, Shaowu; Chen, Shenglu; Miao, Xiaoqing; Zheng, Nenggan; Su, Songkun

2017-01-01

China is the largest royal jelly producer and exporter in the world, and high royal jelly-yielding strains have been bred in the country for approximately three decades. However, information on the molecular mechanism underlying high royal jelly production is scarce. Here, a cDNA microarray was used to screen and identify differentially expressed genes (DEGs) to obtain an overview on the changes in gene expression levels between high and low royal jelly producing bees. We developed a honey bee gene chip that covered 11,689 genes, and this chip was hybridised with cDNA generated from RNA isolated from heads of nursing bees. A total of 369 DEGs were identified between high and low royal jelly producing bees. Amongst these DEGs, 201 (54.47%) genes were up-regulated, whereas 168 (45.53%) were down-regulated in high royal jelly-yielding bees. Gene ontology (GO) analyses showed that they are mainly involved in four key biological processes, and pathway analyses revealed that they belong to a total of 46 biological pathways. These results provide a genetic basis for further studies on the molecular mechanisms involved in high royal jelly production.

Microarray analyses reveal distinct roles for Rel proteins in the Drosophila immune response

PubMed Central

Pal, Subhamoy; Wu, Junlin; Wu, Louisa P.

2007-01-01

The NF-κB group of transcription factors play an important role in mediating immune responses in organisms as diverse as insects and mammals. The fruit fly Drosophila melanogaster express three closely related NF-κB-like transcription factors: Dorsal, Dif, and Relish. To study their roles in vivo, we used microarrays to determine the effect of null mutations in individual Rel transcription factors on larval immune gene expression. Of the 188 genes that were significantly up-regulated in wildtype larvae upon bacterial challenge, overlapping but distinct groups of genes were affected in the Rel mutants. We also ectopically expressed Dorsal or Dif and used cDNA microarrays to determine the genes that were up-regulated in the presence of these transcription factors. This expression was sufficient to drive expression of some immune genes, suggesting redundancy in the regulation of these genes. Combining this data, we also identified novel genes that may be specific targets of Dif. PMID:17537510

MALDI-TOF mass spectrometry for quantitative gene expression analysis of acid responses in Staphylococcus aureus.

PubMed

Rode, Tone Mari; Berget, Ingunn; Langsrud, Solveig; Møretrø, Trond; Holck, Askild

2009-07-01

Microorganisms are constantly exposed to new and altered growth conditions, and respond by changing gene expression patterns. Several methods for studying gene expression exist. During the last decade, the analysis of microarrays has been one of the most common approaches applied for large scale gene expression studies. A relatively new method for gene expression analysis is MassARRAY, which combines real competitive-PCR and MALDI-TOF (matrix-assisted laser desorption/ionization time-of-flight) mass spectrometry. In contrast to microarray methods, MassARRAY technology is suitable for analysing a larger number of samples, though for a smaller set of genes. In this study we compare the results from MassARRAY with microarrays on gene expression responses of Staphylococcus aureus exposed to acid stress at pH 4.5. RNA isolated from the same stress experiments was analysed using both the MassARRAY and the microarray methods. The MassARRAY and microarray methods showed good correlation. Both MassARRAY and microarray estimated somewhat lower fold changes compared with quantitative real-time PCR (qRT-PCR). The results confirmed the up-regulation of the urease genes in acidic environments, and also indicated the importance of metal ion regulation. This study shows that the MassARRAY technology is suitable for gene expression analysis in prokaryotes, and has advantages when a set of genes is being analysed for an organism exposed to many different environmental conditions.

Systematic evaluation of RNA quality, microarray data reliability and pathway analysis in fresh, fresh frozen and formalin-fixed paraffin-embedded tissue samples.

PubMed

Wimmer, Isabella; Tröscher, Anna R; Brunner, Florian; Rubino, Stephen J; Bien, Christian G; Weiner, Howard L; Lassmann, Hans; Bauer, Jan

2018-04-20

Formalin-fixed paraffin-embedded (FFPE) tissues are valuable resources commonly used in pathology. However, formalin fixation modifies nucleic acids challenging the isolation of high-quality RNA for genetic profiling. Here, we assessed feasibility and reliability of microarray studies analysing transcriptome data from fresh, fresh-frozen (FF) and FFPE tissues. We show that reproducible microarray data can be generated from only 2 ng FFPE-derived RNA. For RNA quality assessment, fragment size distribution (DV200) and qPCR proved most suitable. During RNA isolation, extending tissue lysis time to 10 hours reduced high-molecular-weight species, while additional incubation at 70 °C markedly increased RNA yields. Since FF- and FFPE-derived microarrays constitute different data entities, we used indirect measures to investigate gene signal variation and relative gene expression. Whole-genome analyses revealed high concordance rates, while reviewing on single-genes basis showed higher data variation in FFPE than FF arrays. Using an experimental model, gene set enrichment analysis (GSEA) of FFPE-derived microarrays and fresh tissue-derived RNA-Seq datasets yielded similarly affected pathways confirming the applicability of FFPE tissue in global gene expression analysis. Our study provides a workflow comprising RNA isolation, quality assessment and microarray profiling using minimal RNA input, thus enabling hypothesis-generating pathway analyses from limited amounts of precious, pathologically significant FFPE tissues.

Contributions to Statistical Problems Related to Microarray Data

ERIC Educational Resources Information Center

Hong, Feng

2009-01-01

Microarray is a high throughput technology to measure the gene expression. Analysis of microarray data brings many interesting and challenging problems. This thesis consists three studies related to microarray data. First, we propose a Bayesian model for microarray data and use Bayes Factors to identify differentially expressed genes. Second, we…

Recurrent pregnancy loss evaluation combined with 24-chromosome microarray of miscarriage tissue provides a probable or definite cause of pregnancy loss in over 90% of patients.

PubMed

Popescu, F; Jaslow, C R; Kutteh, W H

2018-04-01

Will the addition of 24-chromosome microarray analysis on miscarriage tissue combined with the standard American Society for Reproductive Medicine (ASRM) evaluation for recurrent miscarriage explain most losses? Over 90% of patients with recurrent pregnancy loss (RPL) will have a probable or definitive cause identified when combining genetic testing on miscarriage tissue with the standard ASRM evaluation for recurrent miscarriage. RPL is estimated to occur in 2-4% of reproductive age couples. A probable cause can be identified in approximately 50% of patients after an ASRM recommended workup including an evaluation for parental chromosomal abnormalities, congenital and acquired uterine anomalies, endocrine imbalances and autoimmune factors including antiphospholipid syndrome. Single-center, prospective cohort study that included 100 patients seen in a private RPL clinic from 2014 to 2017. All 100 women had two or more pregnancy losses, a complete evaluation for RPL as defined by the ASRM, and miscarriage tissue evaluated by 24-chromosome microarray analysis after their second or subsequent miscarriage. Frequencies of abnormal results for evidence-based diagnostic tests considered definite or probable causes of RPL (karyotyping for parental chromosomal abnormalities, and 24-chromosome microarray evaluation for products of conception (POC); pelvic sonohysterography, hysterosalpingogram, or hysteroscopy for uterine anomalies; immunological tests for lupus anticoagulant and anticardiolipin antibodies; and blood tests for thyroid stimulating hormone (TSH), prolactin and hemoglobin A1c) were evaluated. We excluded cases where there was maternal cell contamination of the miscarriage tissue or if the ASRM evaluation was incomplete. A cost analysis for the evaluation of RPL was conducted to determine whether a proposed procedure of 24-chromome microarray evaluation followed by an ASRM RPL workup (for those RPL patients who had a normal 24-chromosome microarray evaluation) was more cost-efficient than conducting ASRM RPL workups on RPL patients followed by 24-chromosome microarray analysis (for those RPL patients who had a normal RPL workup). A definite or probable cause of pregnancy loss was identified in the vast majority (95/100; 95%) of RPL patients when a 24-chromosome pair microarray evaluation of POC testing is combined with the standard ASRM RPL workup evaluation at the time of the second or subsequent loss. The ASRM RPL workup identified an abnormality and a probable explanation for pregnancy loss in only 45/100 or 45% of all patients. A definite abnormality was identified in 67/100 patients or 67% when initial testing was performed using 24-chromosome microarray analyses on the miscarriage tissue. Only 5/100 (5%) patients, who had a euploid loss and a normal ASRM RPL workup, had a pregnancy loss without a probable or definitive cause identified. All other losses were explained by an abnormal 24-chromosome microarray analysis of the miscarriage tissue, an abnormal finding of the RPL workup, or a combination of both. Results from the cost analysis indicated that an initial approach of using a 24-chromosome microarray analysis on miscarriage tissue resulted in a 50% savings in cost to the health care system and to the patient. This is a single-center study on a small group of well-characterized women with RPL. There was an incomplete follow-up on subsequent pregnancy outcomes after evaluation, however this should not affect our principal results. The maternal age of patients varied from 26 to 45 years old. More aneuploid pregnancy losses would be expected in older women, particularly over the age of 35 years old. Evaluation of POC using 24-chromosome microarray analysis adds significantly to the ASRM recommended evaluation of RPL. Genetic evaluation on miscarriage tissue obtained at the time of the second and subsequent pregnancy losses should be offered to all couples with two or more consecutive pregnancy losses. The combination of a genetic evaluation on miscarriage tissue with an evidence-based evaluation for RPL will identify a probable or definitive cause in over 90% of miscarriages. No funding was received for this study and there are no conflicts of interest to declare. Not applicable.

Overcoming bias and systematic errors in next generation sequencing data.

PubMed

Taub, Margaret A; Corrada Bravo, Hector; Irizarry, Rafael A

2010-12-10

Considerable time and effort has been spent in developing analysis and quality assessment methods to allow the use of microarrays in a clinical setting. As is the case for microarrays and other high-throughput technologies, data from new high-throughput sequencing technologies are subject to technological and biological biases and systematic errors that can impact downstream analyses. Only when these issues can be readily identified and reliably adjusted for will clinical applications of these new technologies be feasible. Although much work remains to be done in this area, we describe consistently observed biases that should be taken into account when analyzing high-throughput sequencing data. In this article, we review current knowledge about these biases, discuss their impact on analysis results, and propose solutions.

A DNA microarray-based methylation-sensitive (MS)-AFLP hybridization method for genetic and epigenetic analyses.

PubMed

Yamamoto, F; Yamamoto, M

2004-07-01

We previously developed a PCR-based DNA fingerprinting technique named the Methylation Sensitive (MS)-AFLP method, which permits comparative genome-wide scanning of methylation status with a manageable number of fingerprinting experiments. The technique uses the methylation sensitive restriction enzyme NotI in the context of the existing Amplified Fragment Length Polymorphism (AFLP) method. Here we report the successful conversion of this gel electrophoresis-based DNA fingerprinting technique into a DNA microarray hybridization technique (DNA Microarray MS-AFLP). By performing a total of 30 (15 x 2 reciprocal labeling) DNA Microarray MS-AFLP hybridization experiments on genomic DNA from two breast and three prostate cancer cell lines in all pairwise combinations, and Southern hybridization experiments using more than 100 different probes, we have demonstrated that the DNA Microarray MS-AFLP is a reliable method for genetic and epigenetic analyses. No statistically significant differences were observed in the number of differences between the breast-prostate hybridization experiments and the breast-breast or prostate-prostate comparisons.

Screening for Intellectual Disability Using High-Resolution CMA Technology in a Retrospective Cohort from Central Brazil

PubMed Central

Pereira, Rodrigo Roncato; Pinto, Irene Plaza; Minasi, Lysa Bernardes; de Melo, Aldaires Vieira; da Cruz e Cunha, Damiana Mirian; Cruz, Alex Silva; Ribeiro, Cristiano Luiz; da Silva, Cláudio Carlos; de Melo e Silva, Daniela; da Cruz, Aparecido Divino

2014-01-01

Intellectual disability is a complex, variable, and heterogeneous disorder, representing a disabling condition diagnosed worldwide, and the etiologies are multiple and highly heterogeneous. Microscopic chromosomal abnormalities and well-characterized genetic conditions are the most common causes of intellectual disability. Chromosomal Microarray Analysis analyses have made it possible to identify putatively pathogenic copy number variation that could explain the molecular etiology of intellectual disability. The aim of the current study was to identify possible submicroscopic genomic alterations using a high-density chromosomal microarray in a retrospective cohort of patients with otherwise undiagnosable intellectual disabilities referred by doctors from the public health system in Central Brazil. The CytoScan HD technology was used to detect changes in the genome copy number variation of patients who had intellectual disability and a normal karyotype. The analysis detected 18 CNVs in 60% of patients. Pathogenic CNVs represented about 22%, so it was possible to propose the etiology of intellectual disability for these patients. Likely pathogenic and unknown clinical significance CNVs represented 28% and 50%, respectively. Inherited and de novo CNVs were equally distributed. We report the nature of CNVs in patients from Central Brazil, representing a population not yet screened by microarray technologies. PMID:25061755

Chromosomal Microarray versus Karyotyping for Prenatal Diagnosis

PubMed Central

Wapner, Ronald J.; Martin, Christa Lese; Levy, Brynn; Ballif, Blake C.; Eng, Christine M.; Zachary, Julia M.; Savage, Melissa; Platt, Lawrence D.; Saltzman, Daniel; Grobman, William A.; Klugman, Susan; Scholl, Thomas; Simpson, Joe Leigh; McCall, Kimberly; Aggarwal, Vimla S.; Bunke, Brian; Nahum, Odelia; Patel, Ankita; Lamb, Allen N.; Thom, Elizabeth A.; Beaudet, Arthur L.; Ledbetter, David H.; Shaffer, Lisa G.; Jackson, Laird

2013-01-01

Background Chromosomal microarray analysis has emerged as a primary diagnostic tool for the evaluation of developmental delay and structural malformations in children. We aimed to evaluate the accuracy, efficacy, and incremental yield of chromosomal microarray analysis as compared with karyotyping for routine prenatal diagnosis. Methods Samples from women undergoing prenatal diagnosis at 29 centers were sent to a central karyotyping laboratory. Each sample was split in two; standard karyotyping was performed on one portion and the other was sent to one of four laboratories for chromosomal microarray. Results We enrolled a total of 4406 women. Indications for prenatal diagnosis were advanced maternal age (46.6%), abnormal result on Down’s syndrome screening (18.8%), structural anomalies on ultrasonography (25.2%), and other indications (9.4%). In 4340 (98.8%) of the fetal samples, microarray analysis was successful; 87.9% of samples could be used without tissue culture. Microarray analysis of the 4282 nonmosaic samples identified all the aneuploidies and unbalanced rearrangements identified on karyotyping but did not identify balanced translocations and fetal triploidy. In samples with a normal karyotype, microarray analysis revealed clinically relevant deletions or duplications in 6.0% with a structural anomaly and in 1.7% of those whose indications were advanced maternal age or positive screening results. Conclusions In the context of prenatal diagnostic testing, chromosomal microarray analysis identified additional, clinically significant cytogenetic information as compared with karyotyping and was equally efficacious in identifying aneuploidies and unbalanced rearrangements but did not identify balanced translocations and triploidies. (Funded by the Eunice Kennedy Shriver National Institute of Child Health and Human Development and others; ClinicalTrials.gov number, NCT01279733.) PMID:23215555

A 15-gene signature for prediction of colon cancer recurrence and prognosis based on SVM.

PubMed

Xu, Guangru; Zhang, Minghui; Zhu, Hongxing; Xu, Jinhua

2017-03-10

To screen the gene signature for distinguishing patients with high risks from those with low-risks for colon cancer recurrence and predicting their prognosis. Five microarray datasets of colon cancer samples were collected from Gene Expression Omnibus database and one was obtained from The Cancer Genome Atlas (TCGA). After preprocessing, data in GSE17537 were analyzed using the Linear Models for Microarray data (LIMMA) method to identify the differentially expressed genes (DEGs). The DEGs further underwent PPI network-based neighborhood scoring and support vector machine (SVM) analyses to screen the feature genes associated with recurrence and prognosis, which were then validated by four datasets GSE38832, GSE17538, GSE28814 and TCGA using SVM and Cox regression analyses. A total of 1207 genes were identified as DEGs between recurrence and no-recurrence samples, including 726 downregulated and 481 upregulated genes. Using SVM analysis and five gene expression profile data confirmation, a 15-gene signature (HES5, ZNF417, GLRA2, OR8D2, HOXA7, FABP6, MUSK, HTR6, GRIP2, KLRK1, VEGFA, AKAP12, RHEB, NCRNA00152 and PMEPA1) were identified as a predictor of recurrence risk and prognosis for colon cancer patients. Our identified 15-gene signature may be useful to classify colon cancer patients with different prognosis and some genes in this signature may represent new therapeutic targets. Copyright © 2016. Published by Elsevier B.V.

Genomics of the Effect of Spinal Cord Stimulation on an Animal Model of Neuropathic Pain.

PubMed

Vallejo, Ricardo; Tilley, Dana M; Cedeño, David L; Kelley, Courtney A; DeMaegd, Margaret; Benyamin, Ramsin

2016-08-01

Few studies have evaluated single-gene changes modulated by spinal cord stimulation (SCS), providing a narrow understanding of molecular changes. Genomics allows for a robust analysis of holistic gene changes in response to stimulation. Rats were randomized into six groups to determine the effect of continuous SCS in uninjured and spared-nerve injury (SNI) animals. After behavioral assessment, tissues from the dorsal quadrant of the spinal cord (SC) and dorsal root ganglion (DRG) underwent full-genome microarray analyses. Weighted Gene Correlation Network Analysis (WGCNA), and Gene Ontology (GO) analysis identified similar expression patterns, molecular functions and biological processes for significant genes. Microarray analyses reported 20,985 gene probes in SC and 19,104 in DRG. WGCNA sorted 7449 SC and 4275 DRG gene probes into 29 and 9 modules, respectively. WGCNA provided significant modules from paired comparisons of experimental groups. GO analyses reported significant biological processes influenced by injury, as well as the presence of an electric field. The genes Tlr2, Cxcl16, and Cd68 were used to further validate the microarray based on significant response to SCS in SNI animals. They were up-regulated in the SC while both Tlr2 and Cd68 were up-regulated in the DRG. The process described provides highly significant interconnected genes and pathways responsive to injury and/or electric field in the SC and DRG. Genes in the SC respond significantly to the SCS in both injured and uninjured animals, while those in the DRG significantly responded to injury, and SCS in injured animals. © 2016 International Neuromodulation Society.

Genetic Mapping and Exome Sequencing Identify Variants Associated with Five Novel Diseases

PubMed Central

Puffenberger, Erik G.; Jinks, Robert N.; Sougnez, Carrie; Cibulskis, Kristian; Willert, Rebecca A.; Achilly, Nathan P.; Cassidy, Ryan P.; Fiorentini, Christopher J.; Heiken, Kory F.; Lawrence, Johnny J.; Mahoney, Molly H.; Miller, Christopher J.; Nair, Devika T.; Politi, Kristin A.; Worcester, Kimberly N.; Setton, Roni A.; DiPiazza, Rosa; Sherman, Eric A.; Eastman, James T.; Francklyn, Christopher; Robey-Bond, Susan; Rider, Nicholas L.; Gabriel, Stacey; Morton, D. Holmes; Strauss, Kevin A.

2012-01-01

The Clinic for Special Children (CSC) has integrated biochemical and molecular methods into a rural pediatric practice serving Old Order Amish and Mennonite (Plain) children. Among the Plain people, we have used single nucleotide polymorphism (SNP) microarrays to genetically map recessive disorders to large autozygous haplotype blocks (mean = 4.4 Mb) that contain many genes (mean = 79). For some, uninformative mapping or large gene lists preclude disease-gene identification by Sanger sequencing. Seven such conditions were selected for exome sequencing at the Broad Institute; all had been previously mapped at the CSC using low density SNP microarrays coupled with autozygosity and linkage analyses. Using between 1 and 5 patient samples per disorder, we identified sequence variants in the known disease-causing genes SLC6A3 and FLVCR1, and present evidence to strongly support the pathogenicity of variants identified in TUBGCP6, BRAT1, SNIP1, CRADD, and HARS. Our results reveal the power of coupling new genotyping technologies to population-specific genetic knowledge and robust clinical data. PMID:22279524

MiR-141-3p is upregulated in esophageal squamous cell carcinoma and targets pleckstrin homology domain leucine-rich repeat protein phosphatase-2, a negative regulator of the PI3K/AKT pathway.

PubMed

Ishibashi, Osamu; Akagi, Ichiro; Ogawa, Yota; Inui, Takashi

2018-05-11

The phosphatidylinositol-3-kinase (PI3K)/AKT pathway is frequently activated in various human cancers and plays essential roles in their development and progression. Accumulating evidence suggests that dysregulated expression of microRNAs (miRNAs) is closely associated with cancer progression and metastasis. Here, we focused on miRNAs that could regulate genes related to the PI3K/AKT pathway in esophageal squamous cell carcinoma (ESCC). To identify upregulated miRNAs and their possible target genes in ESCC, we performed microarray-based integrative analyses of miRNA and mRNA expression levels in three human ESCC cell lines and a normal esophageal epithelial cell line. The miRNA microarray analysis revealed that miR-31-5p, miR-141-3p, miR-200b-3p, miR-200c-3p, and miR-205-5p were expressed at higher levels in the ESCC cell lines than the normal esophageal epithelial cell line. Bioinformatical analyses of mRNA microarray data identified several AKT/PI3K pathway-related genes as candidate targets of these miRNAs, which include tumor suppressors such as DNA-damage-inducible transcript 4 and pleckstrin homology domain leucine-rich repeat protein phosphatase-2 (PHLPP2). To validate the targets of relevant miRNAs experimentally, synthetic mimics of the miRNAs were transfected into the esophageal epithelial cell line. Here, we report that miR-141-3p suppress the expression of PHLPP2, a negative regulators of the AKT/PI3K pathway, as a target in ESCC. Copyright © 2018 Elsevier Inc. All rights reserved.

Fungal Morphology, Iron Homeostasis, and Lipid Metabolism Regulated by a GATA Transcription Factor in Blastomyces dermatitidis

PubMed Central

Marty, Amber J.; Broman, Aimee T.; Zarnowski, Robert; Dwyer, Teigan G.; Bond, Laura M.; Lounes-Hadj Sahraoui, Anissa; Fontaine, Joël; Ntambi, James M.; Keleş, Sündüz; Kendziorski, Christina; Gauthier, Gregory M.

2015-01-01

In response to temperature, Blastomyces dermatitidis converts between yeast and mold forms. Knowledge of the mechanism(s) underlying this response to temperature remains limited. In B. dermatitidis, we identified a GATA transcription factor, SREB, important for the transition to mold. Null mutants (SREBΔ) fail to fully complete the conversion to mold and cannot properly regulate siderophore biosynthesis. To capture the transcriptional response regulated by SREB early in the phase transition (0–48 hours), gene expression microarrays were used to compare SREB∆ to an isogenic wild type isolate. Analysis of the time course microarray data demonstrated SREB functioned as a transcriptional regulator at 37°C and 22°C. Bioinformatic and biochemical analyses indicated SREB was involved in diverse biological processes including iron homeostasis, biosynthesis of triacylglycerol and ergosterol, and lipid droplet formation. Integration of microarray data, bioinformatics, and chromatin immunoprecipitation identified a subset of genes directly bound and regulated by SREB in vivo in yeast (37°C) and during the phase transition to mold (22°C). This included genes involved with siderophore biosynthesis and uptake, iron homeostasis, and genes unrelated to iron assimilation. Functional analysis suggested that lipid droplets were actively metabolized during the phase transition and lipid metabolism may contribute to filamentous growth at 22°C. Chromatin immunoprecipitation, RNA interference, and overexpression analyses suggested that SREB was in a negative regulatory circuit with the bZIP transcription factor encoded by HAPX. Both SREB and HAPX affected morphogenesis at 22°C; however, large changes in transcript abundance by gene deletion for SREB or strong overexpression for HAPX were required to alter the phase transition. PMID:26114571

Diversity Arrays Technology (DArT) for Pan-Genomic Evolutionary Studies of Non-Model Organisms

PubMed Central

James, Karen E.; Schneider, Harald; Ansell, Stephen W.; Evers, Margaret; Robba, Lavinia; Uszynski, Grzegorz; Pedersen, Niklas; Newton, Angela E.; Russell, Stephen J.; Vogel, Johannes C.; Kilian, Andrzej

2008-01-01

Background High-throughput tools for pan-genomic study, especially the DNA microarray platform, have sparked a remarkable increase in data production and enabled a shift in the scale at which biological investigation is possible. The use of microarrays to examine evolutionary relationships and processes, however, is predominantly restricted to model or near-model organisms. Methodology/Principal Findings This study explores the utility of Diversity Arrays Technology (DArT) in evolutionary studies of non-model organisms. DArT is a hybridization-based genotyping method that uses microarray technology to identify and type DNA polymorphism. Theoretically applicable to any organism (even one for which no prior genetic data are available), DArT has not yet been explored in exclusively wild sample sets, nor extensively examined in a phylogenetic framework. DArT recovered 1349 markers of largely low copy-number loci in two lineages of seed-free land plants: the diploid fern Asplenium viride and the haploid moss Garovaglia elegans. Direct sequencing of 148 of these DArT markers identified 30 putative loci including four routinely sequenced for evolutionary studies in plants. Phylogenetic analyses of DArT genotypes reveal phylogeographic and substrate specificity patterns in A. viride, a lack of phylogeographic pattern in Australian G. elegans, and additive variation in hybrid or mixed samples. Conclusions/Significance These results enable methodological recommendations including procedures for detecting and analysing DArT markers tailored specifically to evolutionary investigations and practical factors informing the decision to use DArT, and raise evolutionary hypotheses concerning substrate specificity and biogeographic patterns. Thus DArT is a demonstrably valuable addition to the set of existing molecular approaches used to infer biological phenomena such as adaptive radiations, population dynamics, hybridization, introgression, ecological differentiation and phylogeography. PMID:18301759

Seasonal dynamics of freshwater pathogens as measured by microarray at Lake Sapanca, a drinking water source in the north-eastern part of Turkey.

PubMed

Akçaalan, Reyhan; Albay, Meric; Koker, Latife; Baudart, Julia; Guillebault, Delphine; Fischer, Sabine; Weigel, Wilfried; Medlin, Linda K

2017-12-22

Monitoring drinking water quality is an important public health issue. Two objectives from the 4 years, six nations, EU Project μAqua were to develop hierarchically specific probes to detect and quantify pathogens in drinking water using a PCR-free microarray platform and to design a standardised water sampling program from different sources in Europe to obtain sufficient material for downstream analysis. Our phylochip contains barcodes (probes) that specifically identify freshwater pathogens that are human health risks in a taxonomic hierarchical fashion such that if species is present, the entire taxonomic hierarchy (genus, family, order, phylum, kingdom) leading to it must also be present, which avoids false positives. Molecular tools are more rapid, accurate and reliable than traditional methods, which means faster mitigation strategies with less harm to humans and the community. We present microarray results for the presence of freshwater pathogens from a Turkish lake used drinking water and inferred cyanobacterial cell equivalents from samples concentrated from 40 into 1 L in 45 min using hollow fibre filters. In two companion studies from the same samples, cyanobacterial toxins were analysed using chemical methods and those dates with highest toxin values also had highest cell equivalents as inferred from this microarray study.

GENE EXPRESSION IN THE TESTES OF NORMOSPERMIC VERSUS TERATOSPERMIC DOMESTIC CATS USING HUMAN CDNA MICROARRAY ANALYSES

EPA Science Inventory

GENE EXPRESSION IN THE TESTES OF NORMOSPERMIC VERSUS TERATOSPERMIC DOMESTIC CATS USING HUMAN cDNA MICROARRAY ANALYSES

B.S. Pukazhenthi1, J. C. Rockett2, M. Ouyang3, D.J. Dix2, J.G. Howard1, P. Georgopoulos4, W.J. J. Welsh3 and D. E. Wildt1

1Department of Reproductiv...

permGPU: Using graphics processing units in RNA microarray association studies.

PubMed

Shterev, Ivo D; Jung, Sin-Ho; George, Stephen L; Owzar, Kouros

2010-06-16

Many analyses of microarray association studies involve permutation, bootstrap resampling and cross-validation, that are ideally formulated as embarrassingly parallel computing problems. Given that these analyses are computationally intensive, scalable approaches that can take advantage of multi-core processor systems need to be developed. We have developed a CUDA based implementation, permGPU, that employs graphics processing units in microarray association studies. We illustrate the performance and applicability of permGPU within the context of permutation resampling for a number of test statistics. An extensive simulation study demonstrates a dramatic increase in performance when using permGPU on an NVIDIA GTX 280 card compared to an optimized C/C++ solution running on a conventional Linux server. permGPU is available as an open-source stand-alone application and as an extension package for the R statistical environment. It provides a dramatic increase in performance for permutation resampling analysis in the context of microarray association studies. The current version offers six test statistics for carrying out permutation resampling analyses for binary, quantitative and censored time-to-event traits.

Identifying gene networks underlying the neurobiology of ethanol and alcoholism.

PubMed

Wolen, Aaron R; Miles, Michael F

2012-01-01

For complex disorders such as alcoholism, identifying the genes linked to these diseases and their specific roles is difficult. Traditional genetic approaches, such as genetic association studies (including genome-wide association studies) and analyses of quantitative trait loci (QTLs) in both humans and laboratory animals already have helped identify some candidate genes. However, because of technical obstacles, such as the small impact of any individual gene, these approaches only have limited effectiveness in identifying specific genes that contribute to complex diseases. The emerging field of systems biology, which allows for analyses of entire gene networks, may help researchers better elucidate the genetic basis of alcoholism, both in humans and in animal models. Such networks can be identified using approaches such as high-throughput molecular profiling (e.g., through microarray-based gene expression analyses) or strategies referred to as genetical genomics, such as the mapping of expression QTLs (eQTLs). Characterization of gene networks can shed light on the biological pathways underlying complex traits and provide the functional context for identifying those genes that contribute to disease development.

Investigating the Genome Diversity of B. cereus and Evolutionary Aspects of B. anthracis Emergence

PubMed Central

Papazisi, Leka; Rasko, David A.; Ratnayake, Shashikala; Bock, Geoff R.; Remortel, Brian G.; Appalla, Lakshmi; Liu, Jia; Dracheva, Tatiana; Braisted, John C.; Shallom, Shamira; Jarrahi, Benham; Snesrud, Erik; Ahn, Susie; Sun, Qiang; Rilstone, Jenifer; Økstad, Ole Andreas; Kolstø, Anne-Brit; Fleischmann, Robert D.; Peterson, Scott N.

2011-01-01

Here we report the use of a multi-genome DNA microarray to investigate the genome diversity of Bacillus cereus group members and elucidate the events associated with the emergence of B. anthracis the causative agent of anthrax–a lethal zoonotic disease. We initially performed directed genome sequencing of seven diverse B. cereus strains to identify novel sequences encoded in those genomes. The novel genes identified, combined with those publicly available, allowed the design of a “species” DNA microarray. Comparative genomic hybridization analyses of 41 strains indicates that substantial heterogeneity exists with respect to the genes comprising functional role categories. While the acquisition of the plasmid-encoded pathogenicity island (pXO1) and capsule genes (pXO2) represent a crucial landmark dictating the emergence of B. anthracis, the evolution of this species and its close relatives was associated with an overall a shift in the fraction of genes devoted to energy metabolism, cellular processes, transport, as well as virulence. PMID:21447378

Fast gene ontology based clustering for microarray experiments.

PubMed

Ovaska, Kristian; Laakso, Marko; Hautaniemi, Sampsa

2008-11-21

Analysis of a microarray experiment often results in a list of hundreds of disease-associated genes. In order to suggest common biological processes and functions for these genes, Gene Ontology annotations with statistical testing are widely used. However, these analyses can produce a very large number of significantly altered biological processes. Thus, it is often challenging to interpret GO results and identify novel testable biological hypotheses. We present fast software for advanced gene annotation using semantic similarity for Gene Ontology terms combined with clustering and heat map visualisation. The methodology allows rapid identification of genes sharing the same Gene Ontology cluster. Our R based semantic similarity open-source package has a speed advantage of over 2000-fold compared to existing implementations. From the resulting hierarchical clustering dendrogram genes sharing a GO term can be identified, and their differences in the gene expression patterns can be seen from the heat map. These methods facilitate advanced annotation of genes resulting from data analysis.

Identification of candidate genes involved in neuroblastoma progression by combining genomic and expression microarrays with survival data.

PubMed

Łastowska, M; Viprey, V; Santibanez-Koref, M; Wappler, I; Peters, H; Cullinane, C; Roberts, P; Hall, A G; Tweddle, D A; Pearson, A D J; Lewis, I; Burchill, S A; Jackson, M S

2007-11-22

Identifying genes, whose expression is consistently altered by chromosomal gains or losses, is an important step in defining genes of biological relevance in a wide variety of tumour types. However, additional criteria are needed to discriminate further among the large number of candidate genes identified. This is particularly true for neuroblastoma, where multiple genomic copy number changes of proven prognostic value exist. We have used Affymetrix microarrays and a combination of fluorescent in situ hybridization and single nucleotide polymorphism (SNP) microarrays to establish expression profiles and delineate copy number alterations in 30 primary neuroblastomas. Correlation of microarray data with patient survival and analysis of expression within rodent neuroblastoma cell lines were then used to define further genes likely to be involved in the disease process. Using this approach, we identify >1000 genes within eight recurrent genomic alterations (loss of 1p, 3p, 4p, 10q and 11q, 2p gain, 17q gain, and the MYCN amplicon) whose expression is consistently altered by copy number change. Of these, 84 correlate with patient survival, with the minimal regions of 17q gain and 4p loss being enriched significantly for such genes. These include genes involved in RNA and DNA metabolism, and apoptosis. Orthologues of all but one of these genes on 17q are overexpressed in rodent neuroblastoma cell lines. A significant excess of SNPs whose copy number correlates with survival is also observed on proximal 4p in stage 4 tumours, and we find that deletion of 4p is associated with improved outcome in an extended cohort of tumours. These results define the major impact of genomic copy number alterations upon transcription within neuroblastoma, and highlight genes on distal 17q and proximal 4p for downstream analyses. They also suggest that integration of discriminators, such as survival and comparative gene expression, with microarray data may be useful in the identification of critical genes within regions of loss or gain in many human cancers.

Circular RNA Expression Profile of Pancreatic Ductal Adenocarcinoma Revealed by Microarray.

PubMed

Li, Haimin; Hao, Xiaokun; Wang, Huimin; Liu, Zhengcai; He, Yong; Pu, Meng; Zhang, Hongtao; Yu, Hengchao; Duan, Juanli; Qu, Shibin

2016-01-01

Circular RNAs (circRNAs) are a special novel type of a stable, diverse and conserved noncoding RNA in mammalian cells. Particularly in cancer, circRNAs have been reported to be widely involved in the physiological/pathological process of life. However, it is unclear whether circRNAs are specifically involved in pancreatic ductal adenocarcinoma (PDAC). We investigated the expression profile of circRNAs in six PDAC cancer samples and paired adjacent normal tissues using microarray. A high-throughput circRNA microarray was used to identify dysregulated circular RNAs in six PDAC patients. Bioinformatic analyses were applied to study these differentially expressed circRNAs. Furthermore, quantitative reverse transcription polymerase chain reaction (qRT-PCR) was performed to confirm these results. We revealed and confirmed that a number of circRNAs were dysregulated, which suggests a potential role in pancreatic cancer. this study demonstrates that clusters of circRNAs are aberrantly expressed in PDAC compared with normal samples and provides new potential targets for the future treatment of PDAC and novel insights into PDAC biology. © 2016 The Author(s) Published by S. Karger AG, Basel.

Integrative analyses of miRNA and proteomics identify potential biological pathways associated with onset of pulmonary fibrosis in the bleomycin rat model

DOE Office of Scientific and Technical Information (OSTI.GOV)

Fukunaga, Satoki; Environmental Health Science Laboratory, Sumitomo Chemical Co., Ltd., 3-1-98 Kasugade-Naka, Konohana-ku, Osaka 554-8558; Kakehashi, Anna

To determine miRNAs and their predicted target proteins regulatory networks which are potentially involved in onset of pulmonary fibrosis in the bleomycin rat model, we conducted integrative miRNA microarray and iTRAQ-coupled LC-MS/MS proteomic analyses, and evaluated the significance of altered biological functions and pathways. We observed that alterations of miRNAs and proteins are associated with the early phase of bleomycin-induced pulmonary fibrosis, and identified potential target pairs by using ingenuity pathway analysis. Using the data set of these alterations, it was demonstrated that those miRNAs, in association with their predicted target proteins, are potentially involved in canonical pathways reflective ofmore » initial epithelial injury and fibrogenic processes, and biofunctions related to induction of cellular development, movement, growth, and proliferation. Prediction of activated functions suggested that lung cells acquire proliferative, migratory, and invasive capabilities, and resistance to cell death especially in the very early phase of bleomycin-induced pulmonary fibrosis. The present study will provide new insights for understanding the molecular pathogenesis of idiopathic pulmonary fibrosis. - Highlights: • We analyzed bleomycin-induced pulmonary fibrosis in the rat. • Integrative analyses of miRNA microarray and proteomics were conducted. • We determined the alterations of miRNAs and their potential target proteins. • The alterations may control biological functions and pathways in pulmonary fibrosis. • Our result may provide new insights of pulmonary fibrosis.« less

An international standardization programme towards the application of gene expression profiling in routine leukaemia diagnostics: the Microarray Innovations in LEukemia study prephase

PubMed Central

Kohlmann, Alexander; Kipps, Thomas J; Rassenti, Laura Z; Downing, James R; Shurtleff, Sheila A; Mills, Ken I; Gilkes, Amanda F; Hofmann, Wolf-Karsten; Basso, Giuseppe; Dell’Orto, Marta Campo; Foà, Robin; Chiaretti, Sabina; De Vos, John; Rauhut, Sonja; Papenhausen, Peter R; Hernández, Jesus M; Lumbreras, Eva; Yeoh, Allen E; Koay, Evelyn S; Li, Rachel; Liu, Wei-min; Williams, Paul M; Wieczorek, Lothar; Haferlach, Torsten

2008-01-01

Gene expression profiling has the potential to enhance current methods for the diagnosis of haematological malignancies. Here, we present data on 204 analyses from an international standardization programme that was conducted in 11 laboratories as a prephase to the Microarray Innovations in LEukemia (MILE) study. Each laboratory prepared two cell line samples, together with three replicate leukaemia patient lysates in two distinct stages: (i) a 5-d course of protocol training, and (ii) independent proficiency testing. Unsupervised, supervised, and r2 correlation analyses demonstrated that microarray analysis can be performed with remarkably high intra-laboratory reproducibility and with comparable quality and reliability. PMID:18573112

Missing value imputation for microarray data: a comprehensive comparison study and a web tool.

PubMed

Chiu, Chia-Chun; Chan, Shih-Yao; Wang, Chung-Ching; Wu, Wei-Sheng

2013-01-01

Microarray data are usually peppered with missing values due to various reasons. However, most of the downstream analyses for microarray data require complete datasets. Therefore, accurate algorithms for missing value estimation are needed for improving the performance of microarray data analyses. Although many algorithms have been developed, there are many debates on the selection of the optimal algorithm. The studies about the performance comparison of different algorithms are still incomprehensive, especially in the number of benchmark datasets used, the number of algorithms compared, the rounds of simulation conducted, and the performance measures used. In this paper, we performed a comprehensive comparison by using (I) thirteen datasets, (II) nine algorithms, (III) 110 independent runs of simulation, and (IV) three types of measures to evaluate the performance of each imputation algorithm fairly. First, the effects of different types of microarray datasets on the performance of each imputation algorithm were evaluated. Second, we discussed whether the datasets from different species have different impact on the performance of different algorithms. To assess the performance of each algorithm fairly, all evaluations were performed using three types of measures. Our results indicate that the performance of an imputation algorithm mainly depends on the type of a dataset but not on the species where the samples come from. In addition to the statistical measure, two other measures with biological meanings are useful to reflect the impact of missing value imputation on the downstream data analyses. Our study suggests that local-least-squares-based methods are good choices to handle missing values for most of the microarray datasets. In this work, we carried out a comprehensive comparison of the algorithms for microarray missing value imputation. Based on such a comprehensive comparison, researchers could choose the optimal algorithm for their datasets easily. Moreover, new imputation algorithms could be compared with the existing algorithms using this comparison strategy as a standard protocol. In addition, to assist researchers in dealing with missing values easily, we built a web-based and easy-to-use imputation tool, MissVIA (http://cosbi.ee.ncku.edu.tw/MissVIA), which supports many imputation algorithms. Once users upload a real microarray dataset and choose the imputation algorithms, MissVIA will determine the optimal algorithm for the users' data through a series of simulations, and then the imputed results can be downloaded for the downstream data analyses.

Use of DNA Microarrays to Identify Diagnostic Signature Transcription Profiles for Host Responses to Infectious Agents

DTIC Science & Technology

2004-10-01

informative in this regard. Key signature genes will serve as the basis for rapid diagnostic approaches that could be accessed when an outbreak is suspected...AD Award Number: DAMD17-01-1-0787 TITLE: Use of DNA Microarrays to Identify Diagnostic Signature Transcription Profiles for Host Responses to...Sep 2004) 4. TITLE AND SUBTITLE 5. FUNDING NUMBERS Use of DNA Microarrays to Identify Diagnostic Signature DAMD17-01-1-0787 Transcription Profiles for

Controlling false-negative errors in microarray differential expression analysis: a PRIM approach.

PubMed

Cole, Steve W; Galic, Zoran; Zack, Jerome A

2003-09-22

Theoretical considerations suggest that current microarray screening algorithms may fail to detect many true differences in gene expression (Type II analytic errors). We assessed 'false negative' error rates in differential expression analyses by conventional linear statistical models (e.g. t-test), microarray-adapted variants (e.g. SAM, Cyber-T), and a novel strategy based on hold-out cross-validation. The latter approach employs the machine-learning algorithm Patient Rule Induction Method (PRIM) to infer minimum thresholds for reliable change in gene expression from Boolean conjunctions of fold-induction and raw fluorescence measurements. Monte Carlo analyses based on four empirical data sets show that conventional statistical models and their microarray-adapted variants overlook more than 50% of genes showing significant up-regulation. Conjoint PRIM prediction rules recover approximately twice as many differentially expressed transcripts while maintaining strong control over false-positive (Type I) errors. As a result, experimental replication rates increase and total analytic error rates decline. RT-PCR studies confirm that gene inductions detected by PRIM but overlooked by other methods represent true changes in mRNA levels. PRIM-based conjoint inference rules thus represent an improved strategy for high-sensitivity screening of DNA microarrays. Freestanding JAVA application at http://microarray.crump.ucla.edu/focus

Mitochondrial electron transport chain identified as a novel molecular target of SPIO nanoparticles mediated cancer-specific cytotoxicity.

PubMed

He, Chengyong; Jiang, Shengwei; Jin, Haijing; Chen, Shuzhen; Lin, Gan; Yao, Huan; Wang, Xiaoyong; Mi, Peng; Ji, Zhiliang; Lin, Yuchun; Lin, Zhongning; Liu, Gang

2016-03-01

Superparamagnetic iron oxide nanoparticles (SPIONs) are highly cytotoxic and target cancer cells with high specificity; however, the mechanism by which SPIONs induce cancer cell-specific cytotoxicity remains unclear. Herein, the molecular mechanism of SPION-induced cancer cell-specific cytotoxicity to cancer cells is clarified through DNA microarray and bioinformatics analyses. SPIONs can interference with the mitochondrial electron transport chain (METC) in cancer cells, which further affects the production of ATP, mitochondrial membrane potential, and microdistribution of calcium, and induces cell apoptosis. Additionally, SPIONs induce the formation of reactive oxygen species in mitochondria; these reactive oxygen species trigger cancer-specific cytotoxicity due to the lower antioxidative capacity of cancer cells. Moreover, the DNA microarray and gene ontology analyses revealed that SPIONs elevate the expression of metallothioneins in both normal and cancer cells but decrease the expression of METC genes in cancer cells. Overall, these results suggest that SPIONs induce cancer cell death by targeting the METC, which is helpful for designing anti-cancer nanotheranostics and evaluating the safety of future nanomedicines. Copyright © 2016 Elsevier Ltd. All rights reserved.

IDENTIFYING AND MONITORING ENVIRONMENTAL TOXICITY USING CERIODAPHNIA MICROARRAYS - PHASE I

EPA Science Inventory

The current U.S. Environmental Protection Agency (EPA) SBIR solicitation states that “technology is needed to better identify and monitor sources of pollution and protect water quality.” Microarrays may be particularly well suited to identifying environmental toxic...

Validation of the Swine Protein-Annotated Oligonucleotide Microarray

USDA-ARS?s Scientific Manuscript database

The specificity and utility of the Swine Protein-Annotated Oligonucleotide Microarray, or Pigoligoarray (www.pigoligoarray.org), has been evaluated by profiling the expression of transcripts from four porcine tissues. Tools for comparative analyses of expression on the Pigoligoarray were developed i...

Identification of genes modulated in rheumatoid arthritis using complementary DNA microarray analysis of lymphoblastoid B cell lines from disease-discordant monozygotic twins.

PubMed

Haas, Christian S; Creighton, Chad J; Pi, Xiujun; Maine, Ira; Koch, Alisa E; Haines, G Kenneth; Ling, Song; Chinnaiyan, Arul M; Holoshitz, Joseph

2006-07-01

To identify disease-specific gene expression profiles in patients with rheumatoid arthritis (RA), using complementary DNA (cDNA) microarray analyses on lymphoblastoid B cell lines (LCLs) derived from RA-discordant monozygotic (MZ) twins. The cDNA was prepared from LCLs derived from the peripheral blood of 11 pairs of RA-discordant MZ twins. The RA twin cDNA was labeled with cy5 fluorescent dye, and the cDNA of the healthy co-twin was labeled with cy3. To determine relative expression profiles, cDNA from each twin pair was combined and hybridized on 20,000-element microarray chips. Immunohistochemistry and real-time polymerase chain reaction were used to detect the expression of selected gene products in synovial tissue from patients with RA compared with patients with osteoarthritis and normal healthy controls. In RA twin LCLs compared with healthy co-twin LCLs, 1,163 transcripts were significantly differentially expressed. Of these, 747 were overexpressed and 416 were underexpressed. Gene ontology analysis revealed many genes known to play a role in apoptosis, angiogenesis, proteolysis, and signaling. The 3 most significantly overexpressed genes were laeverin (a novel enzyme with sequence homology to CD13), 11beta-hydroxysteroid dehydrogenase type 2 (a steroid pathway enzyme), and cysteine-rich, angiogenic inducer 61 (a known angiogenic factor). The products of these genes, heretofore uncharacterized in RA, were all abundantly expressed in RA synovial tissues. Microarray cDNA analysis of peripheral blood-derived LCLs from well-controlled patient populations is a useful tool to detect RA-relevant genes and could help in identifying novel therapeutic targets.

Systematic Omics Analysis Review (SOAR) Tool to Support Risk Assessment

PubMed Central

McConnell, Emma R.; Bell, Shannon M.; Cote, Ila; Wang, Rong-Lin; Perkins, Edward J.; Garcia-Reyero, Natàlia; Gong, Ping; Burgoon, Lyle D.

2014-01-01

Environmental health risk assessors are challenged to understand and incorporate new data streams as the field of toxicology continues to adopt new molecular and systems biology technologies. Systematic screening reviews can help risk assessors and assessment teams determine which studies to consider for inclusion in a human health assessment. A tool for systematic reviews should be standardized and transparent in order to consistently determine which studies meet minimum quality criteria prior to performing in-depth analyses of the data. The Systematic Omics Analysis Review (SOAR) tool is focused on assisting risk assessment support teams in performing systematic reviews of transcriptomic studies. SOAR is a spreadsheet tool of 35 objective questions developed by domain experts, focused on transcriptomic microarray studies, and including four main topics: test system, test substance, experimental design, and microarray data. The tool will be used as a guide to identify studies that meet basic published quality criteria, such as those defined by the Minimum Information About a Microarray Experiment standard and the Toxicological Data Reliability Assessment Tool. Seven scientists were recruited to test the tool by using it to independently rate 15 published manuscripts that study chemical exposures with microarrays. Using their feedback, questions were weighted based on importance of the information and a suitability cutoff was set for each of the four topic sections. The final validation resulted in 100% agreement between the users on four separate manuscripts, showing that the SOAR tool may be used to facilitate the standardized and transparent screening of microarray literature for environmental human health risk assessment. PMID:25531884

IMPROVING THE RELIABILITY OF MICROARRAYS FOR TOXICOLOGY RESEARCH: A COLLABORATIVE APPROACH

EPA Science Inventory

Microarray-based gene expression profiling is a critical tool to identify molecular biomarkers of specific chemical stressors. Although current microarray technologies have progressed from their infancy, biological and technical repeatability and reliability are often still limit...

Functional genomics annotation of a statistical epistasis network associated with bladder cancer susceptibility.

PubMed

Hu, Ting; Pan, Qinxin; Andrew, Angeline S; Langer, Jillian M; Cole, Michael D; Tomlinson, Craig R; Karagas, Margaret R; Moore, Jason H

2014-04-11

Several different genetic and environmental factors have been identified as independent risk factors for bladder cancer in population-based studies. Recent studies have turned to understanding the role of gene-gene and gene-environment interactions in determining risk. We previously developed the bioinformatics framework of statistical epistasis networks (SEN) to characterize the global structure of interacting genetic factors associated with a particular disease or clinical outcome. By applying SEN to a population-based study of bladder cancer among Caucasians in New Hampshire, we were able to identify a set of connected genetic factors with strong and significant interaction effects on bladder cancer susceptibility. To support our statistical findings using networks, in the present study, we performed pathway enrichment analyses on the set of genes identified using SEN, and found that they are associated with the carcinogen benzo[a]pyrene, a component of tobacco smoke. We further carried out an mRNA expression microarray experiment to validate statistical genetic interactions, and to determine if the set of genes identified in the SEN were differentially expressed in a normal bladder cell line and a bladder cancer cell line in the presence or absence of benzo[a]pyrene. Significant nonrandom sets of genes from the SEN were found to be differentially expressed in response to benzo[a]pyrene in both the normal bladder cells and the bladder cancer cells. In addition, the patterns of gene expression were significantly different between these two cell types. The enrichment analyses and the gene expression microarray results support the idea that SEN analysis of bladder in population-based studies is able to identify biologically meaningful statistical patterns. These results bring us a step closer to a systems genetic approach to understanding cancer susceptibility that integrates population and laboratory-based studies.

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

PubMed

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.

LS-CAP: an algorithm for identifying cytogenetic aberrations in hepatocellular carcinoma using microarray data.

PubMed

He, Xianmin; Wei, Qing; Sun, Meiqian; Fu, Xuping; Fan, Sichang; Li, Yao

2006-05-01

Biological techniques such as Array-Comparative genomic hybridization (CGH), fluorescent in situ hybridization (FISH) and affymetrix single nucleotide pleomorphism (SNP) array have been used to detect cytogenetic aberrations. However, on genomic scale, these techniques are labor intensive and time consuming. Comparative genomic microarray analysis (CGMA) has been used to identify cytogenetic changes in hepatocellular carcinoma (HCC) using gene expression microarray data. However, CGMA algorithm can not give precise localization of aberrations, fails to identify small cytogenetic changes, and exhibits false negatives and positives. Locally un-weighted smoothing cytogenetic aberrations prediction (LS-CAP) based on local smoothing and binomial distribution can be expected to address these problems. LS-CAP algorithm was built and used on HCC microarray profiles. Eighteen cytogenetic abnormalities were identified, among them 5 were reported previously, and 12 were proven by CGH studies. LS-CAP effectively reduced the false negatives and positives, and precisely located small fragments with cytogenetic aberrations.

Differential gene expression of wheat progeny with contrasting levels of transpiration efficiency.

PubMed

Xue, Gang-Ping; McIntyre, C Lynne; Chapman, Scott; Bower, Neil I; Way, Heather; Reverter, Antonio; Clarke, Bryan; Shorter, Ray

2006-08-01

High water use efficiency or transpiration efficiency (TE) in wheat is a desirable physiological trait for increasing grain yield under water-limited environments. The identification of genes associated with this trait would facilitate the selection for genotypes with higher TE using molecular markers. We performed an expression profiling (microarray) analysis of approximately 16,000 unique wheat ESTs to identify genes that were differentially expressed between wheat progeny lines with contrasting TE levels from a cross between Quarrion (high TE) and Genaro 81 (low TE). We also conducted a second microarray analysis to identify genes responsive to drought stress in wheat leaves. Ninety-three genes that were differentially expressed between high and low TE progeny lines were identified. One fifth of these genes were markedly responsive to drought stress. Several potential growth-related regulatory genes, which were down-regulated by drought, were expressed at a higher level in the high TE lines than the low TE lines and are potentially associated with a biomass production component of the Quarrion-derived high TE trait. Eighteen of the TE differentially expressed genes were further analysed using quantitative RT-PCR on a separate set of plant samples from those used for microarray analysis. The expression levels of 11 of the 18 genes were positively correlated with the high TE trait, measured as carbon isotope discrimination (Delta(13)C). These data indicate that some of these TE differentially expressed genes are candidates for investigating processes that underlie the high TE trait or for use as expression quantitative trait loci (eQTLs) for TE.

DOE Office of Scientific and Technical Information (OSTI.GOV)

White, Amanda M.; Daly, Don S.; Willse, Alan R.

The Automated Microarray Image Analysis (AMIA) Toolbox for MATLAB is a flexible, open-source microarray image analysis tool that allows the user to customize analysis of sets of microarray images. This tool provides several methods of identifying and quantify spot statistics, as well as extensive diagnostic statistics and images to identify poor data quality or processing. The open nature of this software allows researchers to understand the algorithms used to provide intensity estimates and to modify them easily if desired.

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

PubMed Central

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

Microarray-based screening of heat shock protein inhibitors.

PubMed

Schax, Emilia; Walter, Johanna-Gabriela; Märzhäuser, Helene; Stahl, Frank; Scheper, Thomas; Agard, David A; Eichner, Simone; Kirschning, Andreas; Zeilinger, Carsten

2014-06-20

Based on the importance of heat shock proteins (HSPs) in diseases such as cancer, Alzheimer's disease or malaria, inhibitors of these chaperons are needed. Today's state-of-the-art techniques to identify HSP inhibitors are performed in microplate format, requiring large amounts of proteins and potential inhibitors. In contrast, we have developed a miniaturized protein microarray-based assay to identify novel inhibitors, allowing analysis with 300 pmol of protein. The assay is based on competitive binding of fluorescence-labeled ATP and potential inhibitors to the ATP-binding site of HSP. Therefore, the developed microarray enables the parallel analysis of different ATP-binding proteins on a single microarray. We have demonstrated the possibility of multiplexing by immobilizing full-length human HSP90α and HtpG of Helicobacter pylori on microarrays. Fluorescence-labeled ATP was competed by novel geldanamycin/reblastatin derivatives with IC50 values in the range of 0.5 nM to 4 μM and Z(*)-factors between 0.60 and 0.96. Our results demonstrate the potential of a target-oriented multiplexed protein microarray to identify novel inhibitors for different members of the HSP90 family. Copyright © 2014 Elsevier B.V. All rights reserved.

The Importance of Normalization on Large and Heterogeneous Microarray Datasets

EPA Science Inventory

DNA microarray technology is a powerful functional genomics tool increasingly used for investigating global gene expression in environmental studies. Microarrays can also be used in identifying biological networks, as they give insight on the complex gene-to-gene interactions, ne...

RECOVERING FILTER-BASED MICROARRAY DATA FOR PATHWAYS ANALYSIS USING A MULTIPOINT ALIGNMENT STRATEGY

EPA Science Inventory

The use of commercial microarrays are rapidly becoming the method of choice for profiling gene expression and assessing various disease states. Research Genetics has provided a series of well defined biological and software tools to the research community for these analyses. Th...

Image-guided genomic analysis of tissue response to laser-induced thermal stress

NASA Astrophysics Data System (ADS)

Mackanos, Mark A.; Helms, Mike; Kalish, Flora; Contag, Christopher H.

2011-05-01

The cytoprotective response to thermal injury is characterized by transcriptional activation of ``heat shock proteins'' (hsp) and proinflammatory proteins. Expression of these proteins may predict cellular survival. Microarray analyses were performed to identify spatially distinct gene expression patterns responding to thermal injury. Laser injury zones were identified by expression of a transgene reporter comprised of the 70 kD hsp gene and the firefly luciferase coding sequence. Zones included the laser spot, the surrounding region where hsp70-luc expression was increased, and a region adjacent to the surrounding region. A total of 145 genes were up-regulated in the laser irradiated region, while 69 were up-regulated in the adjacent region. At 7 hours the chemokine Cxcl3 was the highest expressed gene in the laser spot (24 fold) and adjacent region (32 fold). Chemokines were the most common up-regulated genes identified. Microarray gene expression was successfully validated using qRT- polymerase chain reaction for selected genes of interest. The early response genes are likely involved in cytoprotection and initiation of the healing response. Their regulatory elements will benefit creating the next generation reporter mice and controlling expression of therapeutic proteins. The identified genes serve as drug development targets that may prevent acute tissue damage and accelerate healing.

Missing value imputation for microarray data: a comprehensive comparison study and a web tool

PubMed Central

2013-01-01

Background Microarray data are usually peppered with missing values due to various reasons. However, most of the downstream analyses for microarray data require complete datasets. Therefore, accurate algorithms for missing value estimation are needed for improving the performance of microarray data analyses. Although many algorithms have been developed, there are many debates on the selection of the optimal algorithm. The studies about the performance comparison of different algorithms are still incomprehensive, especially in the number of benchmark datasets used, the number of algorithms compared, the rounds of simulation conducted, and the performance measures used. Results In this paper, we performed a comprehensive comparison by using (I) thirteen datasets, (II) nine algorithms, (III) 110 independent runs of simulation, and (IV) three types of measures to evaluate the performance of each imputation algorithm fairly. First, the effects of different types of microarray datasets on the performance of each imputation algorithm were evaluated. Second, we discussed whether the datasets from different species have different impact on the performance of different algorithms. To assess the performance of each algorithm fairly, all evaluations were performed using three types of measures. Our results indicate that the performance of an imputation algorithm mainly depends on the type of a dataset but not on the species where the samples come from. In addition to the statistical measure, two other measures with biological meanings are useful to reflect the impact of missing value imputation on the downstream data analyses. Our study suggests that local-least-squares-based methods are good choices to handle missing values for most of the microarray datasets. Conclusions In this work, we carried out a comprehensive comparison of the algorithms for microarray missing value imputation. Based on such a comprehensive comparison, researchers could choose the optimal algorithm for their datasets easily. Moreover, new imputation algorithms could be compared with the existing algorithms using this comparison strategy as a standard protocol. In addition, to assist researchers in dealing with missing values easily, we built a web-based and easy-to-use imputation tool, MissVIA (http://cosbi.ee.ncku.edu.tw/MissVIA), which supports many imputation algorithms. Once users upload a real microarray dataset and choose the imputation algorithms, MissVIA will determine the optimal algorithm for the users' data through a series of simulations, and then the imputed results can be downloaded for the downstream data analyses. PMID:24565220

Evaluation of a Field-Portable DNA Microarray Platform and Nucleic Acid Amplification Strategies for the Detection of Arboviruses, Arthropods, and Bloodmeals

PubMed Central

Grubaugh, Nathan D.; Petz, Lawrence N.; Melanson, Vanessa R.; McMenamy, Scott S.; Turell, Michael J.; Long, Lewis S.; Pisarcik, Sarah E.; Kengluecha, Ampornpan; Jaichapor, Boonsong; O'Guinn, Monica L.; Lee, John S.

2013-01-01

Highly multiplexed assays, such as microarrays, can benefit arbovirus surveillance by allowing researchers to screen for hundreds of targets at once. We evaluated amplification strategies and the practicality of a portable DNA microarray platform to analyze virus-infected mosquitoes. The prototype microarray design used here targeted the non-structural protein 5, ribosomal RNA, and cytochrome b genes for the detection of flaviviruses, mosquitoes, and bloodmeals, respectively. We identified 13 of 14 flaviviruses from virus inoculated mosquitoes and cultured cells. Additionally, we differentiated between four mosquito genera and eight whole blood samples. The microarray platform was field evaluated in Thailand and successfully identified flaviviruses (Culex flavivirus, dengue-3, and Japanese encephalitis viruses), differentiated between mosquito genera (Aedes, Armigeres, Culex, and Mansonia), and detected mammalian bloodmeals (human and dog). We showed that the microarray platform and amplification strategies described here can be used to discern specific information on a wide variety of viruses and their vectors. PMID:23249687

mRNA expression profiling of laser microbeam microdissected cells from slender embryonic structures.

PubMed

Scheidl, Stefan J; Nilsson, Sven; Kalén, Mattias; Hellström, Mats; Takemoto, Minoru; Håkansson, Joakim; Lindahl, Per

2002-03-01

Microarray hybridization has rapidly evolved as an important tool for genomic studies and studies of gene regulation at the transcriptome level. Expression profiles from homogenous samples such as yeast and mammalian cell cultures are currently extending our understanding of biology, whereas analyses of multicellular organisms are more difficult because of tissue complexity. The combination of laser microdissection, RNA amplification, and microarray hybridization has the potential to provide expression profiles from selected populations of cells in vivo. In this article, we present and evaluate an experimental procedure for global gene expression analysis of slender embryonic structures using laser microbeam microdissection and laser pressure catapulting. As a proof of principle, expression profiles from 1000 cells in the mouse embryonic (E9.5) dorsal aorta were generated and compared with profiles for captured mesenchymal cells located one cell diameter further away from the aortic lumen. A number of genes were overexpressed in the aorta, including 11 previously known markers for blood vessels. Among the blood vessel markers were endoglin, tie-2, PDGFB, and integrin-beta1, that are important regulators of blood vessel formation. This demonstrates that microarray analysis of laser microbeam micro-dissected cells is sufficiently sensitive for identifying genes with regulative functions.

Recursive feature selection with significant variables of support vectors.

PubMed

Tsai, Chen-An; Huang, Chien-Hsun; Chang, Ching-Wei; Chen, Chun-Houh

2012-01-01

The development of DNA microarray makes researchers screen thousands of genes simultaneously and it also helps determine high- and low-expression level genes in normal and disease tissues. Selecting relevant genes for cancer classification is an important issue. Most of the gene selection methods use univariate ranking criteria and arbitrarily choose a threshold to choose genes. However, the parameter setting may not be compatible to the selected classification algorithms. In this paper, we propose a new gene selection method (SVM-t) based on the use of t-statistics embedded in support vector machine. We compared the performance to two similar SVM-based methods: SVM recursive feature elimination (SVMRFE) and recursive support vector machine (RSVM). The three methods were compared based on extensive simulation experiments and analyses of two published microarray datasets. In the simulation experiments, we found that the proposed method is more robust in selecting informative genes than SVMRFE and RSVM and capable to attain good classification performance when the variations of informative and noninformative genes are different. In the analysis of two microarray datasets, the proposed method yields better performance in identifying fewer genes with good prediction accuracy, compared to SVMRFE and RSVM.

Hybrid microarray based on double biomolecular markers of DNA and carbohydrate for simultaneous genotypic and phenotypic detection of cholera toxin-producing Vibrio cholerae.

PubMed

Shin, Hwa Hui; Seo, Jeong Hyun; Kim, Chang Sup; Hwang, Byeong Hee; Cha, Hyung Joon

2016-05-15

Life-threatening diarrheal cholera is usually caused by water or food contaminated with cholera toxin-producing Vibrio cholerae. For the prevention and surveillance of cholera, it is crucial to rapidly and precisely detect and identify the etiological causes, such as V. cholerae and/or its toxin. In the present work, we propose the use of a hybrid double biomolecular marker (DBM) microarray containing 16S rRNA-based DNA capture probe to genotypically identify V. cholerae and GM1 pentasaccharide capture probe to phenotypically detect cholera toxin. We employed a simple sample preparation method to directly obtain genomic DNA and secreted cholera toxin as target materials from bacterial cells. By utilizing the constructed DBM microarray and prepared samples, V. cholerae and cholera toxin were detected successfully, selectively, and simultaneously; the DBM microarray was able to analyze the pathogenicity of the identified V. cholerae regardless of whether the bacteria produces toxin. Therefore, our proposed DBM microarray is a new effective platform for identifying bacteria and analyzing bacterial pathogenicity simultaneously. Copyright © 2015 Elsevier B.V. All rights reserved.

Derivation of Tissue-specific Functional Gene Sets to Aid Transcriptomic Analysis of Chemical Impacts on the Teleost Reproductive Axis.

EPA Science Inventory

Oligonucleotide microarrays are a powerful tool for unsupervised analysis of chemical impacts on biological systems. However, the lack of well annotated biological pathways for many aquatic organisms, including fish, and the poor power of microarray-based analyses to detect diffe...

Microarray characterization of gene expression changes in blood during acute ethanol exposure

PubMed Central

2013-01-01

Background As part of the civil aviation safety program to define the adverse effects of ethanol on flying performance, we performed a DNA microarray analysis of human whole blood samples from a five-time point study of subjects administered ethanol orally, followed by breathalyzer analysis, to monitor blood alcohol concentration (BAC) to discover significant gene expression changes in response to the ethanol exposure. Methods Subjects were administered either orange juice or orange juice with ethanol. Blood samples were taken based on BAC and total RNA was isolated from PaxGene™ blood tubes. The amplified cDNA was used in microarray and quantitative real-time polymerase chain reaction (RT-qPCR) analyses to evaluate differential gene expression. Microarray data was analyzed in a pipeline fashion to summarize and normalize and the results evaluated for relative expression across time points with multiple methods. Candidate genes showing distinctive expression patterns in response to ethanol were clustered by pattern and further analyzed for related function, pathway membership and common transcription factor binding within and across clusters. RT-qPCR was used with representative genes to confirm relative transcript levels across time to those detected in microarrays. Results Microarray analysis of samples representing 0%, 0.04%, 0.08%, return to 0.04%, and 0.02% wt/vol BAC showed that changes in gene expression could be detected across the time course. The expression changes were verified by qRT-PCR. The candidate genes of interest (GOI) identified from the microarray analysis and clustered by expression pattern across the five BAC points showed seven coordinately expressed groups. Analysis showed function-based networks, shared transcription factor binding sites and signaling pathways for members of the clusters. These include hematological functions, innate immunity and inflammation functions, metabolic functions expected of ethanol metabolism, and pancreatic and hepatic function. Five of the seven clusters showed links to the p38 MAPK pathway. Conclusions The results of this study provide a first look at changing gene expression patterns in human blood during an acute rise in blood ethanol concentration and its depletion because of metabolism and excretion, and demonstrate that it is possible to detect changes in gene expression using total RNA isolated from whole blood. The analysis approach for this study serves as a workflow to investigate the biology linked to expression changes across a time course and from these changes, to identify target genes that could serve as biomarkers linked to pilot performance. PMID:23883607

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.

PubMed

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 expression in S. aurata with an emphasis upon immunity and the immune response.

Quantitative Proteomic and Microarray Analysis of the Archaeon Methanosarcina Acetivorans Grown with Acetate Versus Methanol*

PubMed Central

Li, Lingyun; Li, Qingbo; Rohlin, Lars; Kim, UnMi; Salmon, Kirsty; Rejtar, Tomas; Gunsalus, Robert P.; Karger, Barry L.; Ferry, James G.

2008-01-01

Summary Methanosarcina acetivorans strain C2A is an acetate- and methanol-utilizing methane-producing organism for which the genome, the largest yet sequenced among the Archaea, reveals extensive physiological diversity. LC linear ion trap-FTICR mass spectrometry was employed to analyze acetate- vs. methanol-grown cells metabolically labeled with 14N vs. 15N, respectively, to obtain quantitative protein abundance ratios. DNA microarray analyses of acetate- vs. methanol-grown cells was also performed to determine gene expression ratios. The combined approaches were highly complementary, extending the physiological understanding of growth and methanogenesis. Of the 1081 proteins detected, 255 were ≥ 3-fold differentially abundant. DNA microarray analysis revealed 410 genes that were ≥ 2.5-fold differentially expressed of 1972 genes with detected expression. The ratios of differentially abundant proteins were in good agreement with expression ratios of the encoding genes. Taken together, the results suggest several novel roles for electron transport components specific to acetate-grown cells, including two flavodoxins each specific for growth on acetate or methanol. Protein abundance ratios indicated that duplicate CO dehydrogenase/acetyl-CoA complexes function in the conversion of acetate to methane. Surprisingly, the protein abundance and gene expression ratios indicated a general stress response in acetate- vs. methanol-grown cells that included enzymes specific for polyphosphate accumulation and oxidative stress. The microarray analysis identified transcripts of several genes encoding regulatory proteins with identity to the PhoU, MarR, GlnK, and TetR families commonly found in the Bacteria domain. An analysis of neighboring genes suggested roles in controlling phosphate metabolism (PhoU), ammonia assimilation (GlnK), and molybdopterin cofactor biosynthesis (TetR). Finally, the proteomic and microarray results suggested roles for two-component regulatory systems specific for each growth substrate. PMID:17269732

Differential binding of calmodulin-related proteins to their targets revealed through high-density Arabidopsis protein microarrays

PubMed Central

Popescu, Sorina C.; Popescu, George V.; Bachan, Shawn; Zhang, Zimei; Seay, Montrell; Gerstein, Mark; Snyder, Michael; Dinesh-Kumar, S. P.

2007-01-01

Calmodulins (CaMs) are the most ubiquitous calcium sensors in eukaryotes. A number of CaM-binding proteins have been identified through classical methods, and many proteins have been predicted to bind CaMs based on their structural homology with known targets. However, multicellular organisms typically contain many CaM-like (CML) proteins, and a global identification of their targets and specificity of interaction is lacking. In an effort to develop a platform for large-scale analysis of proteins in plants we have developed a protein microarray and used it to study the global analysis of CaM/CML interactions. An Arabidopsis thaliana expression collection containing 1,133 ORFs was generated and used to produce proteins with an optimized medium-throughput plant-based expression system. Protein microarrays were prepared and screened with several CaMs/CMLs. A large number of previously known and novel CaM/CML targets were identified, including transcription factors, receptor and intracellular protein kinases, F-box proteins, RNA-binding proteins, and proteins of unknown function. Multiple CaM/CML proteins bound many binding partners, but the majority of targets were specific to one or a few CaMs/CMLs indicating that different CaM family members function through different targets. Based on our analyses, the emergent CaM/CML interactome is more extensive than previously predicted. Our results suggest that calcium functions through distinct CaM/CML proteins to regulate a wide range of targets and cellular activities. PMID:17360592

The Use of Signal-Transduction and Metabolic Pathways to Predict Human Disease Targets from Electric and Magnetic Fields Using in vitro Data in Human Cell Lines

PubMed Central

Parham, Fred; Portier, Christopher J.; Chang, Xiaoqing; Mevissen, Meike

2016-01-01

Using in vitro data in human cell lines, several research groups have investigated changes in gene expression in cellular systems following exposure to extremely low frequency (ELF) and radiofrequency (RF) electromagnetic fields (EMF). For ELF EMF, we obtained five studies with complete microarray data and three studies with only lists of significantly altered genes. Likewise, for RF EMF, we obtained 13 complete microarray datasets and 5 limited datasets. Plausible linkages between exposure to ELF and RF EMF and human diseases were identified using a three-step process: (a) linking genes associated with classes of human diseases to molecular pathways, (b) linking pathways to ELF and RF EMF microarray data, and (c) identifying associations between human disease and EMF exposures where the pathways are significantly similar. A total of 60 pathways were associated with human diseases, mostly focused on basic cellular functions like JAK–STAT signaling or metabolic functions like xenobiotic metabolism by cytochrome P450 enzymes. ELF EMF datasets were sporadically linked to human diseases, but no clear pattern emerged. Individual datasets showed some linkage to cancer, chemical dependency, metabolic disorders, and neurological disorders. RF EMF datasets were not strongly linked to any disorders but strongly linked to changes in several pathways. Based on these analyses, the most promising area for further research would be to focus on EMF and neurological function and disorders. PMID:27656641

Identification of Differentially Expressed IGFBP5-Related Genes in Breast Cancer Tumor Tissues Using cDNA Microarray Experiments.

PubMed

Akkiprik, Mustafa; Peker, İrem; Özmen, Tolga; Amuran, Gökçe Güllü; Güllüoğlu, Bahadır M; Kaya, Handan; Özer, Ayşe

2015-11-10

IGFBP5 is an important regulatory protein in breast cancer progression. We tried to identify differentially expressed genes (DEGs) between breast tumor tissues with IGFBP5 overexpression and their adjacent normal tissues. In this study, thirty-eight breast cancer and adjacent normal breast tissue samples were used to determine IGFBP5 expression by qPCR. cDNA microarrays were applied to the highest IGFBP5 overexpressed tumor samples compared to their adjacent normal breast tissue. Microarray analysis revealed that a total of 186 genes were differentially expressed in breast cancer compared with normal breast tissues. Of the 186 genes, 169 genes were downregulated and 17 genes were upregulated in the tumor samples. KEGG pathway analyses showed that protein digestion and absorption, focal adhesion, salivary secretion, drug metabolism-cytochrome P450, and phenylalanine metabolism pathways are involved. Among these DEGs, the prominent top two genes (MMP11 and COL1A1) which potentially correlated with IGFBP5 were selected for validation using real time RT-qPCR. Only COL1A1 expression showed a consistent upregulation with IGFBP5 expression and COL1A1 and MMP11 were significantly positively correlated. We concluded that the discovery of coordinately expressed genes related with IGFBP5 might contribute to understanding of the molecular mechanism of the function of IGFBP5 in breast cancer. Further functional studies on DEGs and association with IGFBP5 may identify novel biomarkers for clinical applications in breast cancer.

Use of Microarray to Analyze Gene Expression Profiles of Acute Effects of Prochloraz on Fathead Minnows Pimephales promelas

EPA Science Inventory

Microarray technology is a powerful tool to investigate the gene expression profiles for thousands of genes simultaneously. In recent years, microarrays have been used to characterize environmental pollutants and identify molecular mode(s) of action of chemicals including endocri...

Clustering approaches to identifying gene expression patterns from DNA microarray data.

PubMed

Do, Jin Hwan; Choi, Dong-Kug

2008-04-30

The analysis of microarray data is essential for large amounts of gene expression data. In this review we focus on clustering techniques. The biological rationale for this approach is the fact that many co-expressed genes are co-regulated, and identifying co-expressed genes could aid in functional annotation of novel genes, de novo identification of transcription factor binding sites and elucidation of complex biological pathways. Co-expressed genes are usually identified in microarray experiments by clustering techniques. There are many such methods, and the results obtained even for the same datasets may vary considerably depending on the algorithms and metrics for dissimilarity measures used, as well as on user-selectable parameters such as desired number of clusters and initial values. Therefore, biologists who want to interpret microarray data should be aware of the weakness and strengths of the clustering methods used. In this review, we survey the basic principles of clustering of DNA microarray data from crisp clustering algorithms such as hierarchical clustering, K-means and self-organizing maps, to complex clustering algorithms like fuzzy clustering.

Development and application of a fluorescence protein microarray for detecting serum alpha-fetoprotein in patients with hepatocellular carcinoma.

PubMed

Zhang, Aiying; Yin, Chengzeng; Wang, Zhenshun; Zhang, Yonghong; Zhao, Yuanshun; Li, Ang; Sun, Huanqin; Lin, Dongdong; Li, Ning

2016-12-01

Objective To develop a simple, effective, time-saving and low-cost fluorescence protein microarray method for detecting serum alpha-fetoprotein (AFP) in patients with hepatocellular carcinoma (HCC). Method Non-contact piezoelectric print techniques were applied to fluorescence protein microarray to reduce the cost of prey antibody. Serum samples from patients with HCC and healthy control subjects were collected and evaluated for the presence of AFP using a novel fluorescence protein microarray. To validate the fluorescence protein microarray, serum samples were tested for AFP using an enzyme-linked immunosorbent assay (ELISA). Results A total of 110 serum samples from patients with HCC ( n = 65) and healthy control subjects ( n = 45) were analysed. When the AFP cut-off value was set at 20 ng/ml, the fluorescence protein microarray had a sensitivity of 91.67% and a specificity of 93.24% for detecting serum AFP. Serum AFP quantified via fluorescence protein microarray had a similar diagnostic performance compared with ELISA in distinguishing patients with HCC from healthy control subjects (area under receiver operating characteristic curve: 0.906 for fluorescence protein microarray; 0.880 for ELISA). Conclusion A fluorescence protein microarray method was developed for detecting serum AFP in patients with HCC.

Development and application of a fluorescence protein microarray for detecting serum alpha-fetoprotein in patients with hepatocellular carcinoma

PubMed Central

Zhang, Aiying; Yin, Chengzeng; Wang, Zhenshun; Zhang, Yonghong; Zhao, Yuanshun; Li, Ang; Sun, Huanqin; Lin, Dongdong

2016-01-01

Objective To develop a simple, effective, time-saving and low-cost fluorescence protein microarray method for detecting serum alpha-fetoprotein (AFP) in patients with hepatocellular carcinoma (HCC). Method Non-contact piezoelectric print techniques were applied to fluorescence protein microarray to reduce the cost of prey antibody. Serum samples from patients with HCC and healthy control subjects were collected and evaluated for the presence of AFP using a novel fluorescence protein microarray. To validate the fluorescence protein microarray, serum samples were tested for AFP using an enzyme-linked immunosorbent assay (ELISA). Results A total of 110 serum samples from patients with HCC (n = 65) and healthy control subjects (n = 45) were analysed. When the AFP cut-off value was set at 20 ng/ml, the fluorescence protein microarray had a sensitivity of 91.67% and a specificity of 93.24% for detecting serum AFP. Serum AFP quantified via fluorescence protein microarray had a similar diagnostic performance compared with ELISA in distinguishing patients with HCC from healthy control subjects (area under receiver operating characteristic curve: 0.906 for fluorescence protein microarray; 0.880 for ELISA). Conclusion A fluorescence protein microarray method was developed for detecting serum AFP in patients with HCC. PMID:27885040

A Java-based tool for the design of classification microarrays.

PubMed

Meng, Da; Broschat, Shira L; Call, Douglas R

2008-08-04

Classification microarrays are used for purposes such as identifying strains of bacteria and determining genetic relationships to understand the epidemiology of an infectious disease. For these cases, mixed microarrays, which are composed of DNA from more than one organism, are more effective than conventional microarrays composed of DNA from a single organism. Selection of probes is a key factor in designing successful mixed microarrays because redundant sequences are inefficient and limited representation of diversity can restrict application of the microarray. We have developed a Java-based software tool, called PLASMID, for use in selecting the minimum set of probe sequences needed to classify different groups of plasmids or bacteria. The software program was successfully applied to several different sets of data. The utility of PLASMID was illustrated using existing mixed-plasmid microarray data as well as data from a virtual mixed-genome microarray constructed from different strains of Streptococcus. Moreover, use of data from expression microarray experiments demonstrated the generality of PLASMID. In this paper we describe a new software tool for selecting a set of probes for a classification microarray. While the tool was developed for the design of mixed microarrays-and mixed-plasmid microarrays in particular-it can also be used to design expression arrays. The user can choose from several clustering methods (including hierarchical, non-hierarchical, and a model-based genetic algorithm), several probe ranking methods, and several different display methods. A novel approach is used for probe redundancy reduction, and probe selection is accomplished via stepwise discriminant analysis. Data can be entered in different formats (including Excel and comma-delimited text), and dendrogram, heat map, and scatter plot images can be saved in several different formats (including jpeg and tiff). Weights generated using stepwise discriminant analysis can be stored for analysis of subsequent experimental data. Additionally, PLASMID can be used to construct virtual microarrays with genomes from public databases, which can then be used to identify an optimal set of probes.

Novel statistical framework to identify differentially expressed genes allowing transcriptomic background differences.

PubMed

Ling, Zhi-Qiang; Wang, Yi; Mukaisho, Kenichi; Hattori, Takanori; Tatsuta, Takeshi; Ge, Ming-Hua; Jin, Li; Mao, Wei-Min; Sugihara, Hiroyuki

2010-06-01

Tests of differentially expressed genes (DEGs) from microarray experiments are based on the null hypothesis that genes that are irrelevant to the phenotype/stimulus are expressed equally in the target and control samples. However, this strict hypothesis is not always true, as there can be several transcriptomic background differences between target and control samples, including different cell/tissue types, different cell cycle stages and different biological donors. These differences lead to increased false positives, which have little biological/medical significance. In this article, we propose a statistical framework to identify DEGs between target and control samples from expression microarray data allowing transcriptomic background differences between these samples by introducing a modified null hypothesis that the gene expression background difference is normally distributed. We use an iterative procedure to perform robust estimation of the null hypothesis and identify DEGs as outliers. We evaluated our method using our own triplicate microarray experiment, followed by validations with reverse transcription-polymerase chain reaction (RT-PCR) and on the MicroArray Quality Control dataset. The evaluations suggest that our technique (i) results in less false positive and false negative results, as measured by the degree of agreement with RT-PCR of the same samples, (ii) can be applied to different microarray platforms and results in better reproducibility as measured by the degree of DEG identification concordance both intra- and inter-platforms and (iii) can be applied efficiently with only a few microarray replicates. Based on these evaluations, we propose that this method not only identifies more reliable and biologically/medically significant DEG, but also reduces the power-cost tradeoff problem in the microarray field. Source code and binaries freely available for download at http://comonca.org.cn/fdca/resources/softwares/deg.zip.

Microarray analysis of peripheral blood lymphocytes from ALS patients and the SAFE detection of the KEGG ALS pathway

PubMed Central

2011-01-01

Background Sporadic amyotrophic lateral sclerosis (sALS) is a motor neuron disease with poorly understood etiology. Results of gene expression profiling studies of whole blood from ALS patients have not been validated and are difficult to relate to ALS pathogenesis because gene expression profiles depend on the relative abundance of the different cell types present in whole blood. We conducted microarray analyses using Agilent Human Whole Genome 4 × 44k Arrays on a more homogeneous cell population, namely purified peripheral blood lymphocytes (PBLs), from ALS patients and healthy controls to identify molecular signatures possibly relevant to ALS pathogenesis. Methods Differentially expressed genes were determined by LIMMA (Linear Models for MicroArray) and SAM (Significance Analysis of Microarrays) analyses. The SAFE (Significance Analysis of Function and Expression) procedure was used to identify molecular pathway perturbations. Proteasome inhibition assays were conducted on cultured peripheral blood mononuclear cells (PBMCs) from ALS patients to confirm alteration of the Ubiquitin/Proteasome System (UPS). Results For the first time, using SAFE in a global gene ontology analysis (gene set size 5-100), we show significant perturbation of the KEGG (Kyoto Encyclopedia of Genes and Genomes) ALS pathway of motor neuron degeneration in PBLs from ALS patients. This was the only KEGG disease pathway significantly upregulated among 25, and contributing genes, including SOD1, represented 54% of the encoded proteins or protein complexes of the KEGG ALS pathway. Further SAFE analysis, including gene set sizes >100, showed that only neurodegenerative diseases (4 out of 34 disease pathways) including ALS were significantly upregulated. Changes in UBR2 expression correlated inversely with time since onset of disease and directly with ALSFRS-R, implying that UBR2 was increased early in the course of ALS. Cultured PBMCs from ALS patients accumulated more ubiquitinated proteins than PBMCs from healthy controls in a serum-dependent manner confirming changes in this pathway. Conclusions Our study indicates that PBLs from sALS patients are strong responders to systemic signals or local signals acquired by cell trafficking, representing changes in gene expression similar to those present in brain and spinal cord of sALS patients. PBLs may provide a useful means to study ALS pathogenesis. PMID:22027401

Comprehensive Census of Bacteria in Clean Rooms by Using DNA Microarray and Cloning Methods▿ †

PubMed Central

La Duc, Myron T.; Osman, Shariff; Vaishampayan, Parag; Piceno, Yvette; Andersen, Gary; Spry, J. A.; Venkateswaran, Kasthuri

2009-01-01

A census of clean room surface-associated bacterial populations was derived from the results of both the cloning and sequencing of 16S rRNA genes and DNA microarray (PhyloChip) analyses. Samples from the Lockheed Martin Aeronautics Multiple Testing Facility (LMA-MTF), the Kennedy Space Center Payload Hazard and Servicing Facility (KSC-PHSF), and the Jet Propulsion Laboratory Spacecraft Assembly Facility (JPL-SAF) clean rooms were collected during the various assembly phases of the Phoenix and Mars Science Laboratory (MSL) spacecraft. Clone library-derived analyses detected a larger bacterial diversity prior to the arrival of spacecraft hardware in these clean room facilities. PhyloChip results were in agreement with this trend but also unveiled the presence of anywhere from 9- to 70-fold more bacterial taxa than cloning approaches. Among the facilities sampled, the JPL-SAF (MSL mission) housed a significantly less diverse bacterial population than either the LMA-MTF or KSC-PHSF (Phoenix mission). Bacterial taxa known to thrive in arid conditions were frequently detected in MSL-associated JPL-SAF samples, whereas proteobacterial lineages dominated Phoenix-associated KSC-PHSF samples. Comprehensive bacterial censuses, such as that reported here, will help space-faring nations preemptively identify contaminant biomatter that may compromise extraterrestrial life detection experiments. The robust nature and high sensitivity of DNA microarray technologies should prove beneficial to a wide range of scientific, electronic, homeland security, medical, and pharmaceutical applications and to any other ventures with a vested interest in monitoring and controlling contamination in exceptionally clean environments. PMID:19700540

Comprehensive census of bacteria in clean rooms by using DNA microarray and cloning methods.

PubMed

La Duc, Myron T; Osman, Shariff; Vaishampayan, Parag; Piceno, Yvette; Andersen, Gary; Spry, J A; Venkateswaran, Kasthuri

2009-10-01

A census of clean room surface-associated bacterial populations was derived from the results of both the cloning and sequencing of 16S rRNA genes and DNA microarray (PhyloChip) analyses. Samples from the Lockheed Martin Aeronautics Multiple Testing Facility (LMA-MTF), the Kennedy Space Center Payload Hazard and Servicing Facility (KSC-PHSF), and the Jet Propulsion Laboratory Spacecraft Assembly Facility (JPL-SAF) clean rooms were collected during the various assembly phases of the Phoenix and Mars Science Laboratory (MSL) spacecraft. Clone library-derived analyses detected a larger bacterial diversity prior to the arrival of spacecraft hardware in these clean room facilities. PhyloChip results were in agreement with this trend but also unveiled the presence of anywhere from 9- to 70-fold more bacterial taxa than cloning approaches. Among the facilities sampled, the JPL-SAF (MSL mission) housed a significantly less diverse bacterial population than either the LMA-MTF or KSC-PHSF (Phoenix mission). Bacterial taxa known to thrive in arid conditions were frequently detected in MSL-associated JPL-SAF samples, whereas proteobacterial lineages dominated Phoenix-associated KSC-PHSF samples. Comprehensive bacterial censuses, such as that reported here, will help space-faring nations preemptively identify contaminant biomatter that may compromise extraterrestrial life detection experiments. The robust nature and high sensitivity of DNA microarray technologies should prove beneficial to a wide range of scientific, electronic, homeland security, medical, and pharmaceutical applications and to any other ventures with a vested interest in monitoring and controlling contamination in exceptionally clean environments.

A general framework for optimization of probes for gene expression microarray and its application to the fungus Podospora anserina.

PubMed

Bidard, Frédérique; Imbeaud, Sandrine; Reymond, Nancie; Lespinet, Olivier; Silar, Philippe; Clavé, Corinne; Delacroix, Hervé; Berteaux-Lecellier, Véronique; Debuchy, Robert

2010-06-18

The development of new microarray technologies makes custom long oligonucleotide arrays affordable for many experimental applications, notably gene expression analyses. Reliable results depend on probe design quality and selection. Probe design strategy should cope with the limited accuracy of de novo gene prediction programs, and annotation up-dating. We present a novel in silico procedure which addresses these issues and includes experimental screening, as an empirical approach is the best strategy to identify optimal probes in the in silico outcome. We used four criteria for in silico probe selection: cross-hybridization, hairpin stability, probe location relative to coding sequence end and intron position. This latter criterion is critical when exon-intron gene structure predictions for intron-rich genes are inaccurate. For each coding sequence (CDS), we selected a sub-set of four probes. These probes were included in a test microarray, which was used to evaluate the hybridization behavior of each probe. The best probe for each CDS was selected according to three experimental criteria: signal-to-noise ratio, signal reproducibility, and representative signal intensities. This procedure was applied for the development of a gene expression Agilent platform for the filamentous fungus Podospora anserina and the selection of a single 60-mer probe for each of the 10,556 P. anserina CDS. A reliable gene expression microarray version based on the Agilent 44K platform was developed with four spot replicates of each probe to increase statistical significance of analysis.

Multi-membership gene regulation in pathway based microarray analysis

PubMed Central

2011-01-01

Background Gene expression analysis has been intensively researched for more than a decade. Recently, there has been elevated interest in the integration of microarray data analysis with other types of biological knowledge in a holistic analytical approach. We propose a methodology that can be facilitated for pathway based microarray data analysis, based on the observation that a substantial proportion of genes present in biochemical pathway databases are members of a number of distinct pathways. Our methodology aims towards establishing the state of individual pathways, by identifying those truly affected by the experimental conditions based on the behaviour of such genes. For that purpose it considers all the pathways in which a gene participates and the general census of gene expression per pathway. Results We utilise hill climbing, simulated annealing and a genetic algorithm to analyse the consistency of the produced results, through the application of fuzzy adjusted rand indexes and hamming distance. All algorithms produce highly consistent genes to pathways allocations, revealing the contribution of genes to pathway functionality, in agreement with current pathway state visualisation techniques, with the simulated annealing search proving slightly superior in terms of efficiency. Conclusions We show that the expression values of genes, which are members of a number of biochemical pathways or modules, are the net effect of the contribution of each gene to these biochemical processes. We show that by manipulating the pathway and module contribution of such genes to follow underlying trends we can interpret microarray results centred on the behaviour of these genes. PMID:21939531

Multi-membership gene regulation in pathway based microarray analysis.

PubMed

Pavlidis, Stelios P; Payne, Annette M; Swift, Stephen M

2011-09-22

Gene expression analysis has been intensively researched for more than a decade. Recently, there has been elevated interest in the integration of microarray data analysis with other types of biological knowledge in a holistic analytical approach. We propose a methodology that can be facilitated for pathway based microarray data analysis, based on the observation that a substantial proportion of genes present in biochemical pathway databases are members of a number of distinct pathways. Our methodology aims towards establishing the state of individual pathways, by identifying those truly affected by the experimental conditions based on the behaviour of such genes. For that purpose it considers all the pathways in which a gene participates and the general census of gene expression per pathway. We utilise hill climbing, simulated annealing and a genetic algorithm to analyse the consistency of the produced results, through the application of fuzzy adjusted rand indexes and hamming distance. All algorithms produce highly consistent genes to pathways allocations, revealing the contribution of genes to pathway functionality, in agreement with current pathway state visualisation techniques, with the simulated annealing search proving slightly superior in terms of efficiency. We show that the expression values of genes, which are members of a number of biochemical pathways or modules, are the net effect of the contribution of each gene to these biochemical processes. We show that by manipulating the pathway and module contribution of such genes to follow underlying trends we can interpret microarray results centred on the behaviour of these genes.

MOLECULAR METHODS (E.G., MICROARRAYS) APPLIED TO PLANT GENOMES FOR ASSESSING GENETIC CHANGE AND ENVIRONMENTAL STRESS

EPA Science Inventory

This is a technical document that presents a detailed sample standard operating procedure (S.O.P.) for preparing plant nucleic acid samples for microarray analyses using commercial ¿chips¿ such as those sold by Affymetrix. It also presents the application of a commercially availa...

Cross-species transcriptomic approach reveals genes in hamster implantation sites.

PubMed

Lei, Wei; Herington, Jennifer; Galindo, Cristi L; Ding, Tianbing; Brown, Naoko; Reese, Jeff; Paria, Bibhash C

2014-12-01

The mouse model has greatly contributed to understanding molecular mechanisms involved in the regulation of progesterone (P4) plus estrogen (E)-dependent blastocyst implantation process. However, little is known about contributory molecular mechanisms of the P4-only-dependent blastocyst implantation process that occurs in species such as hamsters, guineapigs, rabbits, pigs, rhesus monkeys, and perhaps humans. We used the hamster as a model of P4-only-dependent blastocyst implantation and carried out cross-species microarray (CSM) analyses to reveal differentially expressed genes at the blastocyst implantation site (BIS), in order to advance the understanding of molecular mechanisms of implantation. Upregulation of 112 genes and downregulation of 77 genes at the BIS were identified using a mouse microarray platform, while use of the human microarray revealed 62 up- and 38 down-regulated genes at the BIS. Excitingly, a sizable number of genes (30 up- and 11 down-regulated genes) were identified as a shared pool by both CSMs. Real-time RT-PCR and in situ hybridization validated the expression patterns of several up- and down-regulated genes identified by both CSMs at the hamster and mouse BIS to demonstrate the merit of CSM findings across species, in addition to revealing genes specific to hamsters. Functional annotation analysis found that genes involved in the spliceosome, proteasome, and ubiquination pathways are enriched at the hamster BIS, while genes associated with tight junction, SAPK/JNK signaling, and PPARα/RXRα signalings are repressed at the BIS. Overall, this study provides a pool of genes and evidence of their participation in up- and down-regulated cellular functions/pathways at the hamster BIS. © 2014 Society for Reproduction and Fertility.

Microarray Analysis of LTR Retrotransposon Silencing Identifies Hdac1 as a Regulator of Retrotransposon Expression in Mouse Embryonic Stem Cells

PubMed Central

Madej, Monika J.; Taggart, Mary; Gautier, Philippe; Garcia-Perez, Jose Luis; Meehan, Richard R.; Adams, Ian R.

2012-01-01

Retrotransposons are highly prevalent in mammalian genomes due to their ability to amplify in pluripotent cells or developing germ cells. Host mechanisms that silence retrotransposons in germ cells and pluripotent cells are important for limiting the accumulation of the repetitive elements in the genome during evolution. However, although silencing of selected individual retrotransposons can be relatively well-studied, many mammalian retrotransposons are seldom analysed and their silencing in germ cells, pluripotent cells or somatic cells remains poorly understood. Here we show, and experimentally verify, that cryptic repetitive element probes present in Illumina and Affymetrix gene expression microarray platforms can accurately and sensitively monitor repetitive element expression data. This computational approach to genome-wide retrotransposon expression has allowed us to identify the histone deacetylase Hdac1 as a component of the retrotransposon silencing machinery in mouse embryonic stem cells, and to determine the retrotransposon targets of Hdac1 in these cells. We also identify retrotransposons that are targets of other retrotransposon silencing mechanisms such as DNA methylation, Eset-mediated histone modification, and Ring1B/Eed-containing polycomb repressive complexes in mouse embryonic stem cells. Furthermore, our computational analysis of retrotransposon silencing suggests that multiple silencing mechanisms are independently targeted to retrotransposons in embryonic stem cells, that different genomic copies of the same retrotransposon can be differentially sensitive to these silencing mechanisms, and helps define retrotransposon sequence elements that are targeted by silencing machineries. Thus repeat annotation of gene expression microarray data suggests that a complex interplay between silencing mechanisms represses retrotransposon loci in germ cells and embryonic stem cells. PMID:22570599

DEVELOPMENT AND VALIDATION OF A 2,000 GENE MICROARRAY FOR THE FATHEAD MINNOW, PIMEPHALES PROMELAS

EPA Science Inventory

The development of the gene microarray has provided the field of ecotoxicology a new tool to identify modes of action (MOA) of chemicals and chemical mixtures. Herein we describe the development and application of a 2,000 gene oligonucleotide microarray for the fathead minnow (P...

Molecular Microbial Analyses of the Mars Exploration Rovers Assembly Facility

NASA Technical Reports Server (NTRS)

Venkateswaran, Kasthuri; LaDuc, Myron T.; Newcombe, David; Kempf, Michael J.; Koke, John. A.; Smoot, James C.; Smoot, Laura M.; Stahl, David A.

2004-01-01

During space exploration, the control of terrestrial microbes associated with robotic space vehicles intended to land on extraterrestrial solar system bodies is necessary to prevent forward contamination and maintain scientific integrity during the search for life. Microorganisms associated with the spacecraft assembly environment can be a source of contamination for the spacecraft. In this study, we have monitored the microbial burden of air samples of the Mars Exploration Rovers' assembly facility at the Kennedy Space Center utilizing complementary diagnostic tools. To estimate the microbial burden and identify potential contaminants in the assembly facility, several microbiological techniques were used including culturing, cloning and sequencing of 16S rRNA genes, DNA microarray analysis, and ATP assays to assess viable microorganisms. Culturing severely underestimated types and amounts of contamination since many of the microbes implicated by molecular analyses were not cultivable. In addition to the cultivation of Agrobacterium, Burkholderia and Bacillus species, the cloning approach retrieved 16s rDNA sequences of oligotrophs, symbionts, and y-proteobacteria members. DNA microarray analysis based on rational probe design and dissociation curves complemented existing molecular techniques and produced a highly parallel, high resolution analysis of contaminating microbial populations. For instance, strong hybridization signals to probes targeting the Bacillus species indicated that members of this species were present in the assembly area samples; however, differences in dissociation curves between perfect-match and air sample sequences showed that these samples harbored nucleotide polymorphisms. Vegetative cells of several isolates were resistant when subjected to treatments of UVC (254 nm) and vapor H202 (4 mg/L). This study further validates the significance of non-cultivable microbes in association with spacecraft assembly facilities, as our analyses have identified several non-cultivable microbes likely to contaminate the surfaces of spacecraft hardware.

Differential Network Analyses of Alzheimer’s Disease Identify Early Events in Alzheimer’s Disease Pathology

DOE Office of Scientific and Technical Information (OSTI.GOV)

Xia, Jing; Rocke, David M.; Perry, George

In late-onset Alzheimer’s disease (AD), multiple brain regions are not affected simultaneously. Comparing the gene expression of the affected regions to identify the differences in the biological processes perturbed can lead to greater insight into AD pathogenesis and early characteristics. We identified differentially expressed (DE) genes from single cell microarray data of four AD affected brain regions: entorhinal cortex (EC), hippocampus (HIP), posterior cingulate cortex (PCC), and middle temporal gyrus (MTG). We organized the DE genes in the four brain regions into region-specific gene coexpression networks. Differential neighborhood analyses in the coexpression networks were performed to identify genes with lowmore » topological overlap (TO) of their direct neighbors. The low TO genes were used to characterize the biological differences between two regions. Our analyses show that increased oxidative stress, along with alterations in lipid metabolism in neurons, may be some of the very early events occurring in AD pathology. Cellular defense mechanisms try to intervene but fail, finally resulting in AD pathology as the disease progresses. Furthermore, disease annotation of the low TO genes in two independent protein interaction networks has resulted in association between cancer, diabetes, renal diseases, and cardiovascular diseases.« less

Differential Network Analyses of Alzheimer’s Disease Identify Early Events in Alzheimer’s Disease Pathology

DOE PAGES

Xia, Jing; Rocke, David M.; Perry, George; ...

2014-01-01

In late-onset Alzheimer’s disease (AD), multiple brain regions are not affected simultaneously. Comparing the gene expression of the affected regions to identify the differences in the biological processes perturbed can lead to greater insight into AD pathogenesis and early characteristics. We identified differentially expressed (DE) genes from single cell microarray data of four AD affected brain regions: entorhinal cortex (EC), hippocampus (HIP), posterior cingulate cortex (PCC), and middle temporal gyrus (MTG). We organized the DE genes in the four brain regions into region-specific gene coexpression networks. Differential neighborhood analyses in the coexpression networks were performed to identify genes with lowmore » topological overlap (TO) of their direct neighbors. The low TO genes were used to characterize the biological differences between two regions. Our analyses show that increased oxidative stress, along with alterations in lipid metabolism in neurons, may be some of the very early events occurring in AD pathology. Cellular defense mechanisms try to intervene but fail, finally resulting in AD pathology as the disease progresses. Furthermore, disease annotation of the low TO genes in two independent protein interaction networks has resulted in association between cancer, diabetes, renal diseases, and cardiovascular diseases.« less

Construction of a cDNA microarray derived from the ascidian Ciona intestinalis.

PubMed

Azumi, Kaoru; Takahashi, Hiroki; Miki, Yasufumi; Fujie, Manabu; Usami, Takeshi; Ishikawa, Hisayoshi; Kitayama, Atsusi; Satou, Yutaka; Ueno, Naoto; Satoh, Nori

2003-10-01

A cDNA microarray was constructed from a basal chordate, the ascidian Ciona intestinalis. The draft genome of Ciona has been read and inferred to contain approximately 16,000 protein-coding genes, and cDNAs for transcripts of 13,464 genes have been characterized and compiled as the "Ciona intestinalis Gene Collection Release I". In the present study, we constructed a cDNA microarray of these 13,464 Ciona genes. A preliminary experiment with Cy3- and Cy5-labeled probes showed extensive differential gene expression between fertilized eggs and larvae. In addition, there was a good correlation between results obtained by the present microarray analysis and those from previous EST analyses. This first microarray of a large collection of Ciona intestinalis cDNA clones should facilitate the analysis of global gene expression and gene networks during the embryogenesis of basal chordates.

Risk of type 1 diabetes progression in islet autoantibody-positive children can be further stratified using expression patterns of multiple genes implicated in peripheral blood lymphocyte activation and function.

PubMed

Jin, Yulan; Sharma, Ashok; Bai, Shan; Davis, Colleen; Liu, Haitao; Hopkins, Diane; Barriga, Kathy; Rewers, Marian; She, Jin-Xiong

2014-07-01

There is tremendous scientific and clinical value to further improving the predictive power of autoantibodies because autoantibody-positive (AbP) children have heterogeneous rates of progression to clinical diabetes. This study explored the potential of gene expression profiles as biomarkers for risk stratification among 104 AbP subjects from the Diabetes Autoimmunity Study in the Young (DAISY) using a discovery data set based on microarray and a validation data set based on real-time RT-PCR. The microarray data identified 454 candidate genes with expression levels associated with various type 1 diabetes (T1D) progression rates. RT-PCR analyses of the top-27 candidate genes confirmed 5 genes (BACH2, IGLL3, EIF3A, CDC20, and TXNDC5) associated with differential progression and implicated in lymphocyte activation and function. Multivariate analyses of these five genes in the discovery and validation data sets identified and confirmed four multigene models (BI, ICE, BICE, and BITE, with each letter representing a gene) that consistently stratify high- and low-risk subsets of AbP subjects with hazard ratios >6 (P < 0.01). The results suggest that these genes may be involved in T1D pathogenesis and potentially serve as excellent gene expression biomarkers to predict the risk of progression to clinical diabetes for AbP subjects. © 2014 by the American Diabetes Association.

Bioinformatics analysis of differentially expressed gene profiles associated with systemic lupus erythematosus

PubMed Central

Wu, Chengjiang; Zhao, Yangjing; Lin, Yu; Yang, Xinxin; Yan, Meina; Min, Yujiao; Pan, Zihui; Xia, Sheng; Shao, Qixiang

2018-01-01

DNA microarray and high-throughput sequencing have been widely used to identify the differentially expressed genes (DEGs) in systemic lupus erythematosus (SLE). However, the big data from gene microarrays are also challenging to work with in terms of analysis and processing. The presents study combined data from the microarray expression profile (GSE65391) and bioinformatics analysis to identify the key genes and cellular pathways in SLE. Gene ontology (GO) and cellular pathway enrichment analyses of DEGs were performed to investigate significantly enriched pathways. A protein-protein interaction network was constructed to determine the key genes in the occurrence and development of SLE. A total of 310 DEGs were identified in SLE, including 193 upregulated genes and 117 downregulated genes. GO analysis revealed that the most significant biological process of DEGs was immune system process. Kyoto Encyclopedia of Genes and Genome pathway analysis showed that these DEGs were enriched in signaling pathways associated with the immune system, including the RIG-I-like receptor signaling pathway, intestinal immune network for IgA production, antigen processing and presentation and the toll-like receptor signaling pathway. The current study screened the top 10 genes with higher degrees as hub genes, which included 2′-5′-oligoadenylate synthetase 1, MX dynamin like GTPase 2, interferon induced protein with tetratricopeptide repeats 1, interferon regulatory factor 7, interferon induced with helicase C domain 1, signal transducer and activator of transcription 1, ISG15 ubiquitin-like modifier, DExD/H-box helicase 58, interferon induced protein with tetratricopeptide repeats 3 and 2′-5′-oligoadenylate synthetase 2. Module analysis revealed that these hub genes were also involved in the RIG-I-like receptor signaling, cytosolic DNA-sensing, toll-like receptor signaling and ribosome biogenesis pathways. In addition, these hub genes, from different probe sets, exhibited significant co-expressed tendency in multi-experiment microarray datasets (P<0.01). In conclusion, these key genes and cellular pathways may improve the current understanding of the underlying mechanism of development of SLE. These key genes may be potential biomarkers of diagnosis, therapy and prognosis for SLE. PMID:29257335

Self-Directed Student Research through Analysis of Microarray Datasets: A Computer-Based Functional Genomics Practical Class for Masters-Level Students

ERIC Educational Resources Information Center

Grenville-Briggs, Laura J.; Stansfield, Ian

2011-01-01

This report describes a linked series of Masters-level computer practical workshops. They comprise an advanced functional genomics investigation, based upon analysis of a microarray dataset probing yeast DNA damage responses. The workshops require the students to analyse highly complex transcriptomics datasets, and were designed to stimulate…

Quantifying protein-protein interactions in high throughput using protein domain microarrays.

PubMed

Kaushansky, Alexis; Allen, John E; Gordus, Andrew; Stiffler, Michael A; Karp, Ethan S; Chang, Bryan H; MacBeath, Gavin

2010-04-01

Protein microarrays provide an efficient way to identify and quantify protein-protein interactions in high throughput. One drawback of this technique is that proteins show a broad range of physicochemical properties and are often difficult to produce recombinantly. To circumvent these problems, we have focused on families of protein interaction domains. Here we provide protocols for constructing microarrays of protein interaction domains in individual wells of 96-well microtiter plates, and for quantifying domain-peptide interactions in high throughput using fluorescently labeled synthetic peptides. As specific examples, we will describe the construction of microarrays of virtually every human Src homology 2 (SH2) and phosphotyrosine binding (PTB) domain, as well as microarrays of mouse PDZ domains, all produced recombinantly in Escherichia coli. For domains that mediate high-affinity interactions, such as SH2 and PTB domains, equilibrium dissociation constants (K(D)s) for their peptide ligands can be measured directly on arrays by obtaining saturation binding curves. For weaker binding domains, such as PDZ domains, arrays are best used to identify candidate interactions, which are then retested and quantified by fluorescence polarization. Overall, protein domain microarrays provide the ability to rapidly identify and quantify protein-ligand interactions with minimal sample consumption. Because entire domain families can be interrogated simultaneously, they provide a powerful way to assess binding selectivity on a proteome-wide scale and provide an unbiased perspective on the connectivity of protein-protein interaction networks.

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

PubMed

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.

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

PubMed Central

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

Moving Toward Integrating Gene Expression Profiling into High-throughput Testing:A Gene Expression Biomarker Accurately Predicts Estrogen Receptor α Modulation in a Microarray Compendium

EPA Science Inventory

Microarray profiling of chemical-induced effects is being increasingly used in medium and high-throughput formats. In this study, we describe computational methods to identify molecular targets from whole-genome microarray data using as an example the estrogen receptor α (ERα), ...

Identification of new autoantigens for primary biliary cirrhosis using human proteome microarrays.

PubMed

Hu, Chao-Jun; Song, Guang; Huang, Wei; Liu, Guo-Zhen; Deng, Chui-Wen; Zeng, Hai-Pan; Wang, Li; Zhang, Feng-Chun; Zhang, Xuan; Jeong, Jun Seop; Blackshaw, Seth; Jiang, Li-Zhi; Zhu, Heng; Wu, Lin; Li, Yong-Zhe

2012-09-01

Primary biliary cirrhosis (PBC) is a chronic cholestatic liver disease of unknown etiology and is considered to be an autoimmune disease. Autoantibodies are important tools for accurate diagnosis of PBC. Here, we employed serum profiling analysis using a human proteome microarray composed of about 17,000 full-length unique proteins and identified 23 proteins that correlated with PBC. To validate these results, we fabricated a PBC-focused microarray with 21 of these newly identified candidates and nine additional known PBC antigens. By screening the PBC microarrays with additional cohorts of 191 PBC patients and 321 controls (43 autoimmune hepatitis, 55 hepatitis B virus, 31 hepatitis C virus, 48 rheumatoid arthritis, 45 systematic lupus erythematosus, 49 systemic sclerosis, and 50 healthy), six proteins were confirmed as novel PBC autoantigens with high sensitivities and specificities, including hexokinase-1 (isoforms I and II), Kelch-like protein 7, Kelch-like protein 12, zinc finger and BTB domain-containing protein 2, and eukaryotic translation initiation factor 2C, subunit 1. To facilitate clinical diagnosis, we developed ELISA for Kelch-like protein 12 and zinc finger and BTB domain-containing protein 2 and tested large cohorts (297 PBC and 637 control sera) to confirm the sensitivities and specificities observed in the microarray-based assays. In conclusion, our research showed that a strategy using high content protein microarray combined with a smaller but more focused protein microarray can effectively identify and validate novel PBC-specific autoantigens and has the capacity to be translated to clinical diagnosis by means of an ELISA-based method.

Automatic Identification and Quantification of Extra-Well Fluorescence in Microarray Images.

PubMed

Rivera, Robert; Wang, Jie; Yu, Xiaobo; Demirkan, Gokhan; Hopper, Marika; Bian, Xiaofang; Tahsin, Tasnia; Magee, D Mitchell; Qiu, Ji; LaBaer, Joshua; Wallstrom, Garrick

2017-11-03

In recent studies involving NAPPA microarrays, extra-well fluorescence is used as a key measure for identifying disease biomarkers because there is evidence to support that it is better correlated with strong antibody responses than statistical analysis involving intraspot intensity. Because this feature is not well quantified by traditional image analysis software, identification and quantification of extra-well fluorescence is performed manually, which is both time-consuming and highly susceptible to variation between raters. A system that could automate this task efficiently and effectively would greatly improve the process of data acquisition in microarray studies, thereby accelerating the discovery of disease biomarkers. In this study, we experimented with different machine learning methods, as well as novel heuristics, for identifying spots exhibiting extra-well fluorescence (rings) in microarray images and assigning each ring a grade of 1-5 based on its intensity and morphology. The sensitivity of our final system for identifying rings was found to be 72% at 99% specificity and 98% at 92% specificity. Our system performs this task significantly faster than a human, while maintaining high performance, and therefore represents a valuable tool for microarray image analysis.

Prenatal metformin exposure in mice programs the metabolic phenotype of the offspring during a high fat diet at adulthood.

PubMed

Salomäki, Henriikka; Vähätalo, Laura H; Laurila, Kirsti; Jäppinen, Norma T; Penttinen, Anna-Maija; Ailanen, Liisa; Ilyasizadeh, Juan; Pesonen, Ullamari; Koulu, Markku

2013-01-01

The antidiabetic drug metformin is currently used prior and during pregnancy for polycystic ovary syndrome, as well as during gestational diabetes mellitus. We investigated the effects of prenatal metformin exposure on the metabolic phenotype of the offspring during adulthood in mice. Metformin (300 mg/kg) or vehicle was administered orally to dams on regular diet from the embryonic day E0.5 to E17.5. Gene expression profiles in liver and brain were analysed from 4-day old offspring by microarray. Body weight development and several metabolic parameters of offspring were monitored both during regular diet (RD-phase) and high fat diet (HFD-phase). At the end of the study, two doses of metformin or vehicle were given acutely to mice at the age of 20 weeks, and Insig-1 and GLUT4 mRNA expressions in liver and fat tissue were analysed using qRT-PCR. Metformin exposed fetuses were lighter at E18.5. There was no effect of metformin on the maternal body weight development or food intake. Metformin exposed offspring gained more body weight and mesenteric fat during the HFD-phase. The male offspring also had impaired glucose tolerance and elevated fasting glucose during the HFD-phase. Moreover, the expression of GLUT4 mRNA was down-regulated in epididymal fat in male offspring prenatally exposed to metformin. Based on the microarray and subsequent qRT-PCR analyses, the expression of Insig-1 was changed in the liver of neonatal mice exposed to metformin prenatally. Furthermore, metformin up-regulated the expression of Insig-1 later in development. Gene set enrichment analysis based on preliminary microarray data identified several differentially enriched pathways both in control and metformin exposed mice. The present study shows that prenatal metformin exposure causes long-term programming effects on the metabolic phenotype during high fat diet in mice. This should be taken into consideration when using metformin as a therapeutic agent during pregnancy.

COLD-PCR and microarray: two independent highly sensitive approaches allowing the identification of fetal paternally inherited mutations in maternal plasma.

PubMed

Galbiati, Silvia; Monguzzi, Alessandra; Damin, Francesco; Soriani, Nadia; Passiu, Marianna; Castellani, Carlo; Natacci, Federica; Curcio, Cristina; Seia, Manuela; Lalatta, Faustina; Chiari, Marcella; Ferrari, Maurizio; Cremonesi, Laura

2016-07-01

Until now, non-invasive prenatal diagnosis of genetic diseases found only limited routine applications. In autosomal recessive diseases, it can be used to determine the carrier status of the fetus through the detection of a paternally inherited disease allele in cases where maternal and paternal mutated alleles differ. Conditions for non-invasive identification of fetal paternally inherited mutations in maternal plasma were developed by two independent approaches: coamplification at lower denaturation temperature-PCR (COLD-PCR) and highly sensitive microarrays. Assays were designed for identifying 14 mutations, 7 causing β-thalassaemia and 7 cystic fibrosis. In total, 87 non-invasive prenatal diagnoses were performed by COLD-PCR in 75 couples at risk for β-thalassaemia and 12 for cystic fibrosis. First, to identify the more appropriate methodology for the analysis of minority mutated fetal alleles in maternal plasma, both fast and full COLD-PCR protocols were developed for the most common Italian β-thalassaemia Cd39 and IVSI.110 mutations. In 5 out of 31 samples, no enrichment was obtained with the fast protocol, while full COLD-PCR provided the correct fetal genotypes. Thus, full COLD-PCR protocols were developed for all the remaining mutations and all analyses confirmed the fetal genotypes obtained by invasive prenatal diagnosis. Microarray analysis was performed on 40 samples from 28 couples at risk for β-thalassaemia and 12 for cystic fibrosis. Results were in complete concordance with those obtained by both COLD-PCR and invasive procedures. COLD-PCR and microarray approaches are not expensive, simple to handle, fast and can be easily set up in specialised clinical laboratories where prenatal diagnosis is routinely performed. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/

A novel strategy of integrated microarray analysis identifies CENPA, CDK1 and CDC20 as a cluster of diagnostic biomarkers in lung adenocarcinoma.

PubMed

Liu, Wan-Ting; Wang, Yang; Zhang, Jing; Ye, Fei; Huang, Xiao-Hui; Li, Bin; He, Qing-Yu

2018-07-01

Lung adenocarcinoma (LAC) is the most lethal cancer and the leading cause of cancer-related death worldwide. The identification of meaningful clusters of co-expressed genes or representative biomarkers may help improve the accuracy of LAC diagnoses. Public databases, such as the Gene Expression Omnibus (GEO), provide rich resources of valuable information for clinics, however, the integration of multiple microarray datasets from various platforms and institutes remained a challenge. To determine potential indicators of LAC, we performed genome-wide relative significance (GWRS), genome-wide global significance (GWGS) and support vector machine (SVM) analyses progressively to identify robust gene biomarker signatures from 5 different microarray datasets that included 330 samples. The top 200 genes with robust signatures were selected for integrative analysis according to "guilt-by-association" methods, including protein-protein interaction (PPI) analysis and gene co-expression analysis. Of these 200 genes, only 10 genes showed both intensive PPI network and high gene co-expression correlation (r > 0.8). IPA analysis of this regulatory networks suggested that the cell cycle process is a crucial determinant of LAC. CENPA, as well as two linked hub genes CDK1 and CDC20, are determined to be potential indicators of LAC. Immunohistochemical staining showed that CENPA, CDK1 and CDC20 were highly expressed in LAC cancer tissue with co-expression patterns. A Cox regression model indicated that LAC patients with CENPA + /CDK1 + and CENPA + /CDC20 + were high-risk groups in terms of overall survival. In conclusion, our integrated microarray analysis demonstrated that CENPA, CDK1 and CDC20 might serve as novel cluster of prognostic biomarkers for LAC, and the cooperative unit of three genes provides a technically simple approach for identification of LAC patients. Copyright © 2018 Elsevier B.V. All rights reserved.

Noncoding RNAs in human intervertebral disc degeneration: An integrated microarray study.

PubMed

Liu, Xu; Che, Lu; Xie, Yan-Ke; Hu, Qing-Jie; Ma, Chi-Jiao; Pei, Yan-Jun; Wu, Zhi-Gang; Liu, Zhi-Heng; Fan, Li-Ying; Wang, Hai-Qiang

2015-09-01

Accumulating evidence indicates that noncoding RNAs play important roles in a multitude of biological processes. The striking findings of miRNAs (microRNAs) and lncRNAs (long noncoding RNAs) as members of noncoding RNAs open up an exciting era in the studies of gene regulation. More recently, the reports of circRNAs (circular RNAs) add fuel to the noncoding RNAs research. Human intervertebral disc degeneration (IDD) is a main cause of low back pain as a disabling spinal disease. We have addressed the expression profiles if miRNAs, lncRNAs and mRNAs in IDD (Wang et al., J Pathology, 2011 and Wan et al., Arthritis Res Ther, 2014). Furthermore, we thoroughly analysed noncoding RNAs, including miRNAs, lncRNAs and circRNAs in IDD using the very same samples. Here we delineate in detail the contents of the aforementioned microarray analyses. Microarray and sample annotation data were deposited in GEO under accession number GSE67567 as SuperSeries. The integrated analyses of these noncoding RNAs will shed a novel light on coding-noncoding regulatory machinery.

Microarray analysis identified Puccinia striiformis f. sp. tritici genes involved in infection and sporulation.

USDA-ARS?s Scientific Manuscript database

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...

mRNA Expression Profiling of Laser Microbeam Microdissected Cells from Slender Embryonic Structures

PubMed Central

Scheidl, Stefan J.; Nilsson, Sven; Kalén, Mattias; Hellström, Mats; Takemoto, Minoru; Håkansson, Joakim; Lindahl, Per

2002-01-01

Microarray hybridization has rapidly evolved as an important tool for genomic studies and studies of gene regulation at the transcriptome level. Expression profiles from homogenous samples such as yeast and mammalian cell cultures are currently extending our understanding of biology, whereas analyses of multicellular organisms are more difficult because of tissue complexity. The combination of laser microdissection, RNA amplification, and microarray hybridization has the potential to provide expression profiles from selected populations of cells in vivo. In this article, we present and evaluate an experimental procedure for global gene expression analysis of slender embryonic structures using laser microbeam microdissection and laser pressure catapulting. As a proof of principle, expression profiles from 1000 cells in the mouse embryonic (E9.5) dorsal aorta were generated and compared with profiles for captured mesenchymal cells located one cell diameter further away from the aortic lumen. A number of genes were overexpressed in the aorta, including 11 previously known markers for blood vessels. Among the blood vessel markers were endoglin, tie-2, PDGFB, and integrin-β1, that are important regulators of blood vessel formation. This demonstrates that microarray analysis of laser microbeam micro-dissected cells is sufficiently sensitive for identifying genes with regulative functions. PMID:11891179

Methods to study legionella transcriptome in vitro and in vivo.

PubMed

Faucher, Sebastien P; Shuman, Howard A

2013-01-01

The study of transcriptome responses can provide insight into the regulatory pathways and genetic factors that contribute to a specific phenotype. For bacterial pathogens, it can identify putative new virulence systems and shed light on the mechanisms underlying the regulation of virulence factors. Microarrays have been previously used to study gene regulation in Legionella pneumophila. In the past few years a sharp reduction of the costs associated with microarray experiments together with the availability of relatively inexpensive custom-designed commercial microarrays has made microarray technology an accessible tool for the majority of researchers. Here we describe the methodologies to conduct microarray experiments from in vitro and in vivo samples.

Functional Genomic Analysis of the Impact of Camelina (Camelina sativa) Meal on Atlantic Salmon (Salmo salar) Distal Intestine Gene Expression and Physiology.

PubMed

Brown, Tyler D; Hori, Tiago S; Xue, Xi; Ye, Chang Lin; Anderson, Derek M; Rise, Matthew L

2016-06-01

The inclusion of plant meals in diets of farmed Atlantic salmon can elicit inflammatory responses in the distal intestine (DI). For the present work, fish were fed a standard fish meal (FM) diet or a diet with partial replacement of FM with solvent-extracted camelina meal (CM) (8, 16, or 24 % CM inclusion) during a 16-week feeding trial. A significant decrease in growth performance was seen in fish fed all CM inclusion diets (Hixson et al. in Aquacult Nutr 22:615-630, 2016). A 4x44K oligonucleotide microarray experiment was carried out and significance analysis of microarrays (SAM) and rank products (RP) methods were used to identify differentially expressed genes between the DIs of fish fed the 24 % CM diet and those fed the FM diet. Twelve features representing six known transcripts and two unknowns were identified as CM responsive by both SAM and RP. The six known transcripts (including thioredoxin and ependymin), in addition to tgfb, mmp13, and GILT, were studied using qPCR with RNA templates from all four experimental diet groups. All six microarray-identified genes were confirmed to be CM responsive, as was tgfb and mmp13. Histopathological analyses identified signs of inflammation in the DI of salmon fed CM-containing diets, including lamina propria and sub-epithelial mucosa thickening, infiltration of eosinophilic granule cells, increased goblet cells and decreased enterocyte vacuolization. All of these were significantly altered in 24 % CM compared to all other diets, with the latter two also altered in 16 % CM compared with 8 % CM and control diet groups. Significant correlation was seen between histological parameters as well as between five of the qPCR analyzed genes and histological parameters. These molecular biomarkers of inflammation arising from long-term dietary CM exposure will be useful in the development of CM-containing diets that do not have deleterious effects on salmon growth or physiology.

Fidelity and enhanced sensitivity of differential transcription profiles following linear amplification of nanogram amounts of endothelial mRNA

NASA Technical Reports Server (NTRS)

Polacek, Denise C.; Passerini, Anthony G.; Shi, Congzhu; Francesco, Nadeene M.; Manduchi, Elisabetta; Grant, Gregory R.; Powell, Steven; Bischof, Helen; Winkler, Hans; Stoeckert, Christian J Jr;

GOTree Machine (GOTM): a web-based platform for interpreting sets of interesting genes using Gene Ontology hierarchies

PubMed Central

Zhang, Bing; Schmoyer, Denise; Kirov, Stefan; Snoddy, Jay

2004-01-01

Background Microarray and other high-throughput technologies are producing large sets of interesting genes that are difficult to analyze directly. Bioinformatics tools are needed to interpret the functional information in the gene sets. Results We have created a web-based tool for data analysis and data visualization for sets of genes called GOTree Machine (GOTM). This tool was originally intended to analyze sets of co-regulated genes identified from microarray analysis but is adaptable for use with other gene sets from other high-throughput analyses. GOTree Machine generates a GOTree, a tree-like structure to navigate the Gene Ontology Directed Acyclic Graph for input gene sets. This system provides user friendly data navigation and visualization. Statistical analysis helps users to identify the most important Gene Ontology categories for the input gene sets and suggests biological areas that warrant further study. GOTree Machine is available online at . Conclusion GOTree Machine has a broad application in functional genomic, proteomic and other high-throughput methods that generate large sets of interesting genes; its primary purpose is to help users sort for interesting patterns in gene sets. PMID:14975175

Multiplex giant magnetoresistive biosensor microarrays identify interferon-associated autoantibodies in systemic lupus erythematosus

NASA Astrophysics Data System (ADS)

Lee, Jung-Rok; Haddon, D. James; Wand, Hannah E.; Price, Jordan V.; Diep, Vivian K.; Hall, Drew A.; Petri, Michelle; Baechler, Emily C.; Balboni, Imelda M.; Utz, Paul J.; Wang, Shan X.

2016-06-01

High titer, class-switched autoantibodies are a hallmark of systemic lupus erythematosus (SLE). Dysregulation of the interferon (IFN) pathway is observed in individuals with active SLE, although the association of specific autoantibodies with chemokine score, a combined measurement of three IFN-regulated chemokines, is not known. To identify autoantibodies associated with chemokine score, we developed giant magnetoresistive (GMR) biosensor microarrays, which allow the parallel measurement of multiple serum antibodies to autoantigens and peptides. We used the microarrays to analyze serum samples from SLE patients and found individuals with high chemokine scores had significantly greater reactivity to 13 autoantigens than individuals with low chemokine scores. Our findings demonstrate that multiple autoantibodies, including antibodies to U1-70K and modified histone H2B tails, are associated with IFN dysregulation in SLE. Further, they show the microarrays are capable of identifying autoantibodies associated with relevant clinical manifestations of SLE, with potential for use as biomarkers in clinical practice.

Interim report on updated microarray probes for the LLNL Burkholderia pseudomallei SNP array

DOE Office of Scientific and Technical Information (OSTI.GOV)

Gardner, S; Jaing, C

2012-03-27

The overall goal of this project is to forensically characterize 100 unknown Burkholderia isolates in the US-Australia collaboration. We will identify genome-wide single nucleotide polymorphisms (SNPs) from B. pseudomallei and near neighbor species including B. mallei, B. thailandensis and B. oklahomensis. We will design microarray probes to detect these SNP markers and analyze 100 Burkholderia genomic DNAs extracted from environmental, clinical and near neighbor isolates from Australian collaborators on the Burkholderia SNP microarray. We will analyze the microarray genotyping results to characterize the genetic diversity of these new isolates and triage the samples for whole genome sequencing. In this interimmore » report, we described the SNP analysis and the microarray probe design for the Burkholderia SNP microarray.« less

A general framework for optimization of probes for gene expression microarray and its application to the fungus Podospora anserina

PubMed Central

2010-01-01

Background The development of new microarray technologies makes custom long oligonucleotide arrays affordable for many experimental applications, notably gene expression analyses. Reliable results depend on probe design quality and selection. Probe design strategy should cope with the limited accuracy of de novo gene prediction programs, and annotation up-dating. We present a novel in silico procedure which addresses these issues and includes experimental screening, as an empirical approach is the best strategy to identify optimal probes in the in silico outcome. Findings We used four criteria for in silico probe selection: cross-hybridization, hairpin stability, probe location relative to coding sequence end and intron position. This latter criterion is critical when exon-intron gene structure predictions for intron-rich genes are inaccurate. For each coding sequence (CDS), we selected a sub-set of four probes. These probes were included in a test microarray, which was used to evaluate the hybridization behavior of each probe. The best probe for each CDS was selected according to three experimental criteria: signal-to-noise ratio, signal reproducibility, and representative signal intensities. This procedure was applied for the development of a gene expression Agilent platform for the filamentous fungus Podospora anserina and the selection of a single 60-mer probe for each of the 10,556 P. anserina CDS. Conclusions A reliable gene expression microarray version based on the Agilent 44K platform was developed with four spot replicates of each probe to increase statistical significance of analysis. PMID:20565839

Prevalence, identification by a DNA microarray-based assay of human and food isolates Listeria spp. from Tunisia.

PubMed

Hmaïed, F; Helel, S; Le Berre, V; François, J-M; Leclercq, A; Lecuit, M; Smaoui, H; Kechrid, A; Boudabous, A; Barkallah, I

2014-02-01

We aimed at evaluating the prevalence of Listeria species isolated from food samples and characterizing food and human cases isolates. Between 2005 and 2007, one hundred food samples collected in the markets of Tunis were analysed in our study. Five strains of Listeria monocytogenes responsible for human listeriosis isolated in hospital of Tunis were included. Multiplex PCR serogrouping and pulsed field gel electrophoresis (PFGE) applying the enzyme AscI and ApaI were used for the characterization of isolates of L. monocytogenes. We have developed a rapid microarray-based assay to a reliable discrimination of species within the Listeria genus. The prevalence of Listeria spp. in food samples was estimated at 14% by using classical biochemical identification. Two samples were assigned to L. monocytogenes and 12 to L. innocua. DNA microarray allowed unambiguous identification of Listeria species. Our results obtained by microarray-based assay were in accordance with the biochemical identification. The two food L. monocytogenes isolates were assigned to the PCR serogroup IIa (serovar 1/2a). Whereas human L. monocytogenes isolates were of PCR serogroup IVb, (serovars 4b). These isolates present a high similarity in PFGE. Food L. monocytogenes isolates were classified into two different pulsotypes. These pulsotypes were different from that of the five strains responsible for the human cases. We confirmed the presence of Listeria spp. in variety of food samples in Tunis. Increased food and clinical surveillance must be taken into consideration in Tunisia to identify putative infections sources. Copyright © 2013 Elsevier Masson SAS. All rights reserved.

Immune and inflammatory gene signature in rat cerebrum in subarachnoid hemorrhage with microarray analysis.

PubMed

Lee, Chu-I; Chou, An-Kuo; Lin, Ching-Chih; Chou, Chia-Hua; Loh, Joon-Khim; Lieu, Ann-Shung; Wang, Chih-Jen; Huang, Chi-Ying F; Howng, Shen-Long; Hong, Yi-Ren

2012-01-01

Cerebral vasospasm following subarachnoid hemorrhage (SAH) has been studied in terms of a contraction of the major cerebral arteries, but the effect of cerebrum tissue in SAH is not yet well understood. To gain insight into the biology of SAH-expressing cerebrum, we employed oligonucleotide microarrays to characterize the gene expression profiles of cerebrum tissue at the early stage of SAH. Functional gene expression in the cerebrum was analyzed 2 h following stage 1-hemorrhage in Sprague-Dawley rats. mRNA was investigated by performing microarray and quantitative real-time PCR analyses, and protein expression was determined by Western blot analysis. In this study, 18 upregulated and 18 downregulated genes displayed at least a 1.5-fold change. Five genes were verified by real-time PCR, including three upregulated genes [prostaglandin E synthase (PGES), CD14 antigen, and tissue inhibitor of metalloproteinase 1 (TIMP1)] as well as two downregulated genes [KRAB-zinc finger protein-2 (KZF-2) and γ-aminobutyric acid B receptor 1 (GABA B receptor)]. Notably, there were functional implications for the three upregulated genes involved in the inflammatory SAH process. However, the mechanisms leading to decreased KZF-2 and GABA B receptor expression in SAH have never been characterized. We conclude that oligonucleotide microarrays have the potential for use as a method to identify candidate genes associated with SAH and to provide novel investigational targets, including genes involved in the immune and inflammatory response. Furthermore, understanding the regulation of MMP9/TIMP1 during the early stages of SAH may elucidate the pathophysiological mechanisms in SAH rats.

Differential transcriptomic profiles effected by oil palm phenolics indicate novel health outcomes

PubMed Central

2011-01-01

Background Plant phenolics are important nutritional antioxidants which could aid in overcoming chronic diseases such as cardiovascular disease and cancer, two leading causes of death in the world. The oil palm (Elaeis guineensis) is a rich source of water-soluble phenolics which have high antioxidant activities. This study aimed to identify the in vivo effects and molecular mechanisms involved in the biological activities of oil palm phenolics (OPP) during healthy states via microarray gene expression profiling, using mice supplemented with a normal diet as biological models. Results Having confirmed via histology, haematology and clinical biochemistry analyses that OPP is not toxic to mice, we further explored the gene expression changes caused by OPP through statistical and functional analyses using Illumina microarrays. OPP showed numerous biological activities in three major organs of mice, the liver, spleen and heart. In livers of mice given OPP, four lipid catabolism genes were up-regulated while five cholesterol biosynthesis genes were down-regulated, suggesting that OPP may play a role in reducing cardiovascular disease. OPP also up-regulated eighteen blood coagulation genes in spleens of mice. OPP elicited gene expression changes similar to the effects of caloric restriction in the hearts of mice supplemented with OPP. Microarray gene expression fold changes for six target genes in the three major organs tested were validated with real-time quantitative reverse transcription-polymerase chain reaction (qRT-PCR), and the correlation of fold changes obtained with these two techniques was high (R2 = 0.9653). Conclusions OPP showed non-toxicity and various pleiotropic effects in mice. This study implies the potential application of OPP as a valuable source of wellness nutraceuticals, and further suggests the molecular mechanisms as to how dietary phenolics work in vivo. PMID:21864415

Differential transcriptomic profiles effected by oil palm phenolics indicate novel health outcomes.

PubMed

Leow, Soon-Sen; Sekaran, Shamala Devi; Sundram, Kalyana; Tan, YewAi; Sambanthamurthi, Ravigadevi

2011-08-25

Plant phenolics are important nutritional antioxidants which could aid in overcoming chronic diseases such as cardiovascular disease and cancer, two leading causes of death in the world. The oil palm (Elaeis guineensis) is a rich source of water-soluble phenolics which have high antioxidant activities. This study aimed to identify the in vivo effects and molecular mechanisms involved in the biological activities of oil palm phenolics (OPP) during healthy states via microarray gene expression profiling, using mice supplemented with a normal diet as biological models. Having confirmed via histology, haematology and clinical biochemistry analyses that OPP is not toxic to mice, we further explored the gene expression changes caused by OPP through statistical and functional analyses using Illumina microarrays. OPP showed numerous biological activities in three major organs of mice, the liver, spleen and heart. In livers of mice given OPP, four lipid catabolism genes were up-regulated while five cholesterol biosynthesis genes were down-regulated, suggesting that OPP may play a role in reducing cardiovascular disease. OPP also up-regulated eighteen blood coagulation genes in spleens of mice. OPP elicited gene expression changes similar to the effects of caloric restriction in the hearts of mice supplemented with OPP. Microarray gene expression fold changes for six target genes in the three major organs tested were validated with real-time quantitative reverse transcription-polymerase chain reaction (qRT-PCR), and the correlation of fold changes obtained with these two techniques was high (R2 = 0.9653). OPP showed non-toxicity and various pleiotropic effects in mice. This study implies the potential application of OPP as a valuable source of wellness nutraceuticals, and further suggests the molecular mechanisms as to how dietary phenolics work in vivo.

Construct and Compare Gene Coexpression Networks with DAPfinder and DAPview.

PubMed

Skinner, Jeff; Kotliarov, Yuri; Varma, Sudhir; Mine, Karina L; Yambartsev, Anatoly; Simon, Richard; Huyen, Yentram; Morgun, Andrey

2011-07-14

DAPfinder and DAPview are novel BRB-ArrayTools plug-ins to construct gene coexpression networks and identify significant differences in pairwise gene-gene coexpression between two phenotypes. Each significant difference in gene-gene association represents a Differentially Associated Pair (DAP). Our tools include several choices of filtering methods, gene-gene association metrics, statistical testing methods and multiple comparison adjustments. Network results are easily displayed in Cytoscape. Analyses of glioma experiments and microarray simulations demonstrate the utility of these tools. DAPfinder is a new friendly-user tool for reconstruction and comparison of biological networks.

Microarray analyses reveal novel targets of exercise-induced stress resistance in the dorsal raphe nucleus

PubMed Central

Loughridge, Alice B.; Greenwood, Benjamin N.; Day, Heidi E. W.; McQueen, Matthew B.; Fleshner, Monika

2013-01-01

Serotonin (5-HT) is implicated in the development of stress-related mood disorders in humans. Physical activity reduces the risk of developing stress-related mood disorders, such as depression and anxiety. In rats, 6 weeks of wheel running protects against stress-induced behaviors thought to resemble symptoms of human anxiety and depression. The mechanisms by which exercise confers protection against stress-induced behaviors, however, remain unknown. One way by which exercise could generate stress resistance is by producing plastic changes in gene expression in the dorsal raphe nucleus (DRN). The DRN has a high concentration of 5-HT neurons and is implicated in stress-related mood disorders. The goal of the current experiment was to identify changes in the expression of genes that could be novel targets of exercise-induced stress resistance in the DRN. Adult, male F344 rats were allowed voluntary access to running wheels for 6 weeks; exposed to inescapable stress or no stress; and sacrificed immediately and 2 h after stressor termination. Laser capture micro dissection selectively sampled the DRN. mRNA expression was measured using the whole genome Affymetrix microarray. Comprehensive data analyses of gene expression included differential gene expression, log fold change (LFC) contrast analyses with False Discovery Rate correction, KEGG and Wiki Web Gestalt pathway enrichment analyses, and Weighted Gene Correlational Network Analysis (WGCNA). Our results suggest that physically active rats exposed to stress modulate expression of twice the number of genes, and display a more rapid and strongly coordinated response, than sedentary rats. Bioinformatics analyses revealed several potential targets of stress resistance including genes that are related to immune processes, tryptophan metabolism, and circadian/diurnal rhythms. PMID:23717271

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

PubMed

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.

A Synthetic Glycan Microarray Enables Epitope Mapping of Plant Cell Wall Glycan-Directed Antibodies.

PubMed

Ruprecht, Colin; Bartetzko, Max P; Senf, Deborah; Dallabernadina, Pietro; Boos, Irene; Andersen, Mathias C F; Kotake, Toshihisa; Knox, J Paul; Hahn, Michael G; Clausen, Mads H; Pfrengle, Fabian

2017-11-01

In the last three decades, more than 200 monoclonal antibodies have been raised against most classes of plant cell wall polysaccharides by different laboratories worldwide. These antibodies are widely used to identify differences in plant cell wall components in mutants, organ and tissue types, and developmental stages. Despite their importance and broad use, the precise binding epitope has been determined for only a few of these antibodies. Here, we use a plant glycan microarray equipped with 88 synthetic oligosaccharides to comprehensively map the epitopes of plant cell wall glycan-directed antibodies. Our results reveal the binding epitopes for 78 arabinogalactan-, rhamnogalacturonan-, xylan-, and xyloglucan-directed antibodies. We demonstrate that, with knowledge of the exact epitopes recognized by individual antibodies, specific glycosyl hydrolases can be implemented into immunological cell wall analyses, providing a framework to obtain structural information on plant cell wall glycans with unprecedented molecular precision. © 2017 American Society of Plant Biologists. All Rights Reserved.

Microarray analyses of Xylella fastidiosa provide evidence of coordinated transcription control of laterally transferred elements.

PubMed

Nunes, Luiz R; Rosato, Yoko B; Muto, Nair H; Yanai, Giane M; da Silva, Vivian S; Leite, Daniela B; Gonçalves, Edmilson R; de Souza, Alessandra A; Coletta-Filho, Helvécio D; Machado, Marcos A; Lopes, Silvio A; de Oliveira, Regina Costa

2003-04-01

Genetically distinct strains of the plant bacterium Xylella fastidiosa (Xf) are responsible for a variety of plant diseases, accounting for severe economic damage throughout the world. Using as a reference the genome of Xf 9a5c strain, associated with citrus variegated chlorosis (CVC), we developed a microarray-based comparison involving 12 Xf isolates, providing a thorough assessment of the variation in genomic composition across the group. Our results demonstrate that Xf displays one of the largest flexible gene pools characterized to date, with several horizontally acquired elements, such as prophages, plasmids, and genomic islands (GIs), which contribute up to 18% of the final genome. Transcriptome analysis of bacteria grown under different conditions shows that most of these elements are transcriptionally active, and their expression can be influenced in a coordinated manner by environmental stimuli. Finally, evaluation of the genetic composition of these laterally transferred elements identified differences that may help to explain the adaptability of Xf strains to infect such a wide range of plant species.

Direct labeling of serum proteins by fluorescent dye for antibody microarray.

PubMed

Klimushina, M V; Gumanova, N G; Metelskaya, V A

2017-05-06

Analysis of serum proteome by antibody microarray is used to identify novel biomarkers and to study signaling pathways including protein phosphorylation and protein-protein interactions. Labeling of serum proteins is important for optimal performance of the antibody microarray. Proper choice of fluorescent label and optimal concentration of protein loaded on the microarray ensure good quality of imaging that can be reliably scanned and processed by the software. We have optimized direct serum protein labeling using fluorescent dye Arrayit Green 540 (Arrayit Corporation, USA) for antibody microarray. Optimized procedure produces high quality images that can be readily scanned and used for statistical analysis of protein composition of the serum. Copyright © 2017 Elsevier Inc. All rights reserved.

DNA microarrays and their use in dermatology.

PubMed

Mlakar, Vid; Glavac, Damjan

2007-03-01

Multiple different DNA microarray technologies are available on the market today. They can be used for studying either DNA or RNA with the purpose of identifying and explaining the role of genes involved in different processes. This paper reviews different DNA microarray platforms available for such studies and their usage in cases of malignant melanomas, psoriasis, and exposure of keratinocytes and melanocytes to UV illumination.

Gene expression profiling in gill tissues of White spot syndrome virus infected black tiger shrimp Penaeus monodon by DNA microarray.

PubMed

Shekhar, M S; Gomathi, A; Gopikrishna, G; Ponniah, A G

2015-06-01

White spot syndrome virus (WSSV) continues to be the most devastating viral pathogen infecting penaeid shrimp the world over. The genome of WSSV has been deciphered and characterized from three geographical isolates and significant progress has been made in developing various molecular diagnostic methods to detect the virus. However, the information on host immune gene response to WSSV pathogenesis is limited. Microarray analysis was carried out as an approach to analyse the gene expression in black tiger shrimp Penaeus monodon in response to WSSV infection. Gill tissues collected from the WSSV infected shrimp at 6, 24, 48 h and moribund stage were analysed for differential gene expression. Shrimp cDNAs of 40,059 unique sequences were considered for designing the microarray chip. The Cy3-labeled cRNA derived from healthy and WSSV-infected shrimp was subjected to hybridization with all the DNA spots in the microarray which revealed 8,633 and 11,147 as up- and down-regulated genes respectively at different time intervals post infection. The altered expression of these numerous genes represented diverse functions such as immune response, osmoregulation, apoptosis, nucleic acid binding, energy and metabolism, signal transduction, stress response and molting. The changes in gene expression profiles observed by microarray analysis provides molecular insights and framework of genes which are up- and down-regulated at different time intervals during WSSV infection in shrimp. The microarray data was validated by Real Time analysis of four differentially expressed genes involved in apoptosis (translationally controlled tumor protein, inhibitor of apoptosis protein, ubiquitin conjugated enzyme E2 and caspase) for gene expression levels. The role of apoptosis related genes in WSSV infected shrimp is discussed herein.

Improvement of experimental testing and network training conditions with genome-wide microarrays for more accurate predictions of drug gene targets

PubMed Central

2014-01-01

Background Genome-wide microarrays have been useful for predicting chemical-genetic interactions at the gene level. However, interpreting genome-wide microarray results can be overwhelming due to the vast output of gene expression data combined with off-target transcriptional responses many times induced by a drug treatment. This study demonstrates how experimental and computational methods can interact with each other, to arrive at more accurate predictions of drug-induced perturbations. We present a two-stage strategy that links microarray experimental testing and network training conditions to predict gene perturbations for a drug with a known mechanism of action in a well-studied organism. Results S. cerevisiae cells were treated with the antifungal, fluconazole, and expression profiling was conducted under different biological conditions using Affymetrix genome-wide microarrays. Transcripts were filtered with a formal network-based method, sparse simultaneous equation models and Lasso regression (SSEM-Lasso), under different network training conditions. Gene expression results were evaluated using both gene set and single gene target analyses, and the drug’s transcriptional effects were narrowed first by pathway and then by individual genes. Variables included: (i) Testing conditions – exposure time and concentration and (ii) Network training conditions – training compendium modifications. Two analyses of SSEM-Lasso output – gene set and single gene – were conducted to gain a better understanding of how SSEM-Lasso predicts perturbation targets. Conclusions This study demonstrates that genome-wide microarrays can be optimized using a two-stage strategy for a more in-depth understanding of how a cell manifests biological reactions to a drug treatment at the transcription level. Additionally, a more detailed understanding of how the statistical model, SSEM-Lasso, propagates perturbations through a network of gene regulatory interactions is achieved. PMID:24444313

Genome image programs: visualization and interpretation of Escherichia coli microarray experiments.

PubMed

Zimmer, Daniel P; Paliy, Oleg; Thomas, Brian; Gyaneshwar, Prasad; Kustu, Sydney

2004-08-01

We have developed programs to facilitate analysis of microarray data in Escherichia coli. They fall into two categories: manipulation of microarray images and identification of known biological relationships among lists of genes. A program in the first category arranges spots from glass-slide DNA microarrays according to their position in the E. coli genome and displays them compactly in genome order. The resulting genome image is presented in a web browser with an image map that allows the user to identify genes in the reordered image. Another program in the first category aligns genome images from two or more experiments. These images assist in visualizing regions of the genome with common transcriptional control. Such regions include multigene operons and clusters of operons, which are easily identified as strings of adjacent, similarly colored spots. The images are also useful for assessing the overall quality of experiments. The second category of programs includes a database and a number of tools for displaying biological information about many E. coli genes simultaneously rather than one gene at a time, which facilitates identifying relationships among them. These programs have accelerated and enhanced our interpretation of results from E. coli DNA microarray experiments. Examples are given. Copyright 2004 Genetics Society of America

Comparison of DNA Microarray, Loop-Mediated Isothermal Amplification (LAMP) and Real-Time PCR with DNA Sequencing for Identification of Fusarium spp. Obtained from Patients with Hematologic Malignancies.

PubMed

de Souza, Marcela; Matsuzawa, Tetsuhiro; Sakai, Kanae; Muraosa, Yasunori; Lyra, Luzia; Busso-Lopes, Ariane Fidelis; Levin, Anna Sara Shafferman; Schreiber, Angélica Zaninelli; Mikami, Yuzuru; Gonoi, Tohoru; Kamei, Katsuhiko; Moretti, Maria Luiza; Trabasso, Plínio

2017-08-01

The performance of three molecular biology techniques, i.e., DNA microarray, loop-mediated isothermal amplification (LAMP), and real-time PCR were compared with DNA sequencing for properly identification of 20 isolates of Fusarium spp. obtained from blood stream as etiologic agent of invasive infections in patients with hematologic malignancies. DNA microarray, LAMP and real-time PCR identified 16 (80%) out of 20 samples as Fusarium solani species complex (FSSC) and four (20%) as Fusarium spp. The agreement among the techniques was 100%. LAMP exhibited 100% specificity, while DNA microarray, LAMP and real-time PCR showed 100% sensitivity. The three techniques had 100% agreement with DNA sequencing. Sixteen isolates were identified as FSSC by sequencing, being five Fusarium keratoplasticum, nine Fusarium petroliphilum and two Fusarium solani. On the other hand, sequencing identified four isolates as Fusarium non-solani species complex (FNSSC), being three isolates as Fusarium napiforme and one isolate as Fusarium oxysporum. Finally, LAMP proved to be faster and more accessible than DNA microarray and real-time PCR, since it does not require a thermocycler. Therefore, LAMP signalizes as emerging and promising methodology to be used in routine identification of Fusarium spp. among cases of invasive fungal infections.

DNA Microarray Detection of 18 Important Human Blood Protozoan Species

PubMed Central

Chen, Jun-Hu; Feng, Xin-Yu; Chen, Shao-Hong; Cai, Yu-Chun; Lu, Yan; Zhou, Xiao-Nong; Chen, Jia-Xu; Hu, Wei

2016-01-01

Background Accurate detection of blood protozoa from clinical samples is important for diagnosis, treatment and control of related diseases. In this preliminary study, a novel DNA microarray system was assessed for the detection of Plasmodium, Leishmania, Trypanosoma, Toxoplasma gondii and Babesia in humans, animals, and vectors, in comparison with microscopy and PCR data. Developing a rapid, simple, and convenient detection method for protozoan detection is an urgent need. Methodology/Principal Findings The microarray assay simultaneously identified 18 species of common blood protozoa based on the differences in respective target genes. A total of 20 specific primer pairs and 107 microarray probes were selected according to conserved regions which were designed to identify 18 species in 5 blood protozoan genera. The positive detection rate of the microarray assay was 91.78% (402/438). Sensitivity and specificity for blood protozoan detection ranged from 82.4% (95%CI: 65.9% ~ 98.8%) to 100.0% and 95.1% (95%CI: 93.2% ~ 97.0%) to 100.0%, respectively. Positive predictive value (PPV) and negative predictive value (NPV) ranged from 20.0% (95%CI: 2.5% ~ 37.5%) to 100.0% and 96.8% (95%CI: 95.0% ~ 98.6%) to 100.0%, respectively. Youden index varied from 0.82 to 0.98. The detection limit of the DNA microarrays ranged from 200 to 500 copies/reaction, similar to PCR findings. The concordance rate between microarray data and DNA sequencing results was 100%. Conclusions/Significance Overall, the newly developed microarray platform provides a convenient, highly accurate, and reliable clinical assay for the determination of blood protozoan species. PMID:27911895

Two-Dimensional VO2 Mesoporous Microarrays for High-Performance Supercapacitor

NASA Astrophysics Data System (ADS)

Fan, Yuqi; Ouyang, Delong; Li, Bao-Wen; Dang, Feng; Ren, Zongming

2018-05-01

Two-dimensional (2D) mesoporous VO2 microarrays have been prepared using an organic-inorganic liquid interface. The units of microarrays consist of needle-like VO2 particles with a mesoporous structure, in which crack-like pores with a pore size of about 2 nm and depth of 20-100 nm are distributed on the particle surface. The liquid interface acts as a template for the formation of the 2D microarrays, as identified from the kinetic observation. Due to the mesoporous structure of the units and high conductivity of the microarray, such 2D VO2 microarrays exhibit a high specific capacitance of 265 F/g at 1 A/g and excellent rate capability (182 F/g at 10 A/g) and cycling stability, suggesting the effect of unique microstructure for improving the electrochemical performance.

Clustering of self-organizing map identifies five distinct medulloblastoma subgroups.

PubMed

Cao, Changjun; Wang, Wei; Jiang, Pucha

2016-01-01

Medulloblastoma is one the most malignant paediatric brain tumours. Molecular subgrouping these medulloblastomas will not only help identify specific cohorts for certain treatment but also improve confidence in prognostic prediction. Currently, there is a consensus of the existences of four distinct subtypes of medulloblastoma. We proposed a novel bioinformatics method, clustering of self-organizing map, to determine the subgroups and their molecular diversity. Microarray expression profiles of 46 medulloblastoma samples were analysed and five clusters with distinct demographics, clinical outcome and transcriptional profiles were identified. The previously reported Wnt subgroup was identified as expected. Three other novel subgroups were proposed for later investigation. Our findings underscore the value of SOM clustering for discovering the medulloblastoma subgroups. When the suggested subdivision has been confirmed in large cohorts, this method should serve as a part of routine classification of clinical samples.

Design and evaluation of Actichip, a thematic microarray for the study of the actin cytoskeleton

PubMed Central

Muller, Jean; Mehlen, André; Vetter, Guillaume; Yatskou, Mikalai; Muller, Arnaud; Chalmel, Frédéric; Poch, Olivier; Friederich, Evelyne; Vallar, Laurent

2007-01-01

Background The actin cytoskeleton plays a crucial role in supporting and regulating numerous cellular processes. Mutations or alterations in the expression levels affecting the actin cytoskeleton system or related regulatory mechanisms are often associated with complex diseases such as cancer. Understanding how qualitative or quantitative changes in expression of the set of actin cytoskeleton genes are integrated to control actin dynamics and organisation is currently a challenge and should provide insights in identifying potential targets for drug discovery. Here we report the development of a dedicated microarray, the Actichip, containing 60-mer oligonucleotide probes for 327 genes selected for transcriptome analysis of the human actin cytoskeleton. Results Genomic data and sequence analysis features were retrieved from GenBank and stored in an integrative database called Actinome. From these data, probes were designed using a home-made program (CADO4MI) allowing sequence refinement and improved probe specificity by combining the complementary information recovered from the UniGene and RefSeq databases. Actichip performance was analysed by hybridisation with RNAs extracted from epithelial MCF-7 cells and human skeletal muscle. Using thoroughly standardised procedures, we obtained microarray images with excellent quality resulting in high data reproducibility. Actichip displayed a large dynamic range extending over three logs with a limit of sensitivity between one and ten copies of transcript per cell. The array allowed accurate detection of small changes in gene expression and reliable classification of samples based on the expression profiles of tissue-specific genes. When compared to two other oligonucleotide microarray platforms, Actichip showed similar sensitivity and concordant expression ratios. Moreover, Actichip was able to discriminate the highly similar actin isoforms whereas the two other platforms did not. Conclusion Our data demonstrate that Actichip is a powerful alternative to commercial high density microarrays for cytoskeleton gene profiling in normal or pathological samples. Actichip is available upon request. PMID:17727702

Microarray analysis of genes associated with cell surface NIS protein levels in breast cancer.

PubMed

Beyer, Sasha J; Zhang, Xiaoli; Jimenez, Rafael E; Lee, Mei-Ling T; Richardson, Andrea L; Huang, Kun; Jhiang, Sissy M

2011-10-11

Na+/I- symporter (NIS)-mediated iodide uptake allows radioiodine therapy for thyroid cancer. NIS is also expressed in breast tumors, raising potential for radionuclide therapy of breast cancer. However, NIS expression in most breast cancers is low and may not be sufficient for radionuclide therapy. We aimed to identify biomarkers associated with NIS expression such that mechanisms underlying NIS modulation in human breast tumors may be elucidated. Published oligonucleotide microarray data within the National Center for Biotechnology Information Gene Expression Omnibus database were analyzed to identify gene expression tightly correlated with NIS mRNA level among human breast tumors. NIS immunostaining was performed in a tissue microarray composed of 28 human breast tumors which had corresponding oligonucleotide microarray data available for each tumor such that gene expression associated with cell surface NIS protein level could be identified. NIS mRNA levels do not vary among breast tumors or when compared to normal breast tissues when detected by Affymetrix oligonucleotide microarray platforms. Cell surface NIS protein levels are much more variable than their corresponding NIS mRNA levels. Despite a limited number of breast tumors examined, our analysis identified cysteinyl-tRNA synthetase as a biomarker that is highly associated with cell surface NIS protein levels in the ER-positive breast cancer subtype. Further investigation on genes associated with cell surface NIS protein levels within each breast cancer molecular subtype may lead to novel targets for selectively increasing NIS expression/function in a subset of breast cancers patients.

Thermodynamically optimal whole-genome tiling microarray design and validation.

PubMed

Cho, Hyejin; Chou, Hui-Hsien

2016-06-13

Microarray is an efficient apparatus to interrogate the whole transcriptome of species. Microarray can be designed according to annotated gene sets, but the resulted microarrays cannot be used to identify novel transcripts and this design method is not applicable to unannotated species. Alternatively, a whole-genome tiling microarray can be designed using only genomic sequences without gene annotations, and it can be used to detect novel RNA transcripts as well as known genes. The difficulty with tiling microarray design lies in the tradeoff between probe-specificity and coverage of the genome. Sequence comparison methods based on BLAST or similar software are commonly employed in microarray design, but they cannot precisely determine the subtle thermodynamic competition between probe targets and partially matched probe nontargets during hybridizations. Using the whole-genome thermodynamic analysis software PICKY to design tiling microarrays, we can achieve maximum whole-genome coverage allowable under the thermodynamic constraints of each target genome. The resulted tiling microarrays are thermodynamically optimal in the sense that all selected probes share the same melting temperature separation range between their targets and closest nontargets, and no additional probes can be added without violating the specificity of the microarray to the target genome. This new design method was used to create two whole-genome tiling microarrays for Escherichia coli MG1655 and Agrobacterium tumefaciens C58 and the experiment results validated the design.

Transcriptional profile of isoproterenol-induced cardiomyopathy and comparison to exercise-induced cardiac hypertrophy and human cardiac failure

PubMed Central

2009-01-01

Background Isoproterenol-induced cardiac hypertrophy in mice has been used in a number of studies to model human cardiac disease. In this study, we compared the transcriptional response of the heart in this model to other animal models of heart failure, as well as to the transcriptional response of human hearts suffering heart failure. Results We performed microarray analyses on RNA from mice with isoproterenol-induced cardiac hypertrophy and mice with exercise-induced physiological hypertrophy and identified 865 and 2,534 genes that were significantly altered in pathological and physiological cardiac hypertrophy models, respectively. We compared our results to 18 different microarray data sets (318 individual arrays) representing various other animal models and four human cardiac diseases and identified a canonical set of 64 genes that are generally altered in failing hearts. We also produced a pairwise similarity matrix to illustrate relatedness of animal models with human heart disease and identified ischemia as the human condition that most resembles isoproterenol treatment. Conclusion The overall patterns of gene expression are consistent with observed structural and molecular differences between normal and maladaptive cardiac hypertrophy and support a role for the immune system (or immune cell infiltration) in the pathology of stress-induced hypertrophy. Cross-study comparisons such as the results presented here provide targets for further research of cardiac disease that might generally apply to maladaptive cardiac stresses and are also a means of identifying which animal models best recapitulate human disease at the transcriptional level. PMID:20003209

[Oligonucleotide microarray for subtyping avian influenza virus].

PubMed

Xueqing, Han; Xiangmei, Lin; Yihong, Hou; Shaoqiang, Wu; Jian, Liu; Lin, Mei; Guangle, Jia; Zexiao, Yang

2008-09-01

Avian influenza viruses are important human and animal respiratory pathogens and rapid diagnosis of novel emerging avian influenza viruses is vital for effective global influenza surveillance. We developed an oligonucleotide microarray-based method for subtyping all avian influenza virus (16 HA and 9 NA subtypes). In total 25 pairs of primers specific for different subtypes and 1 pair of universal primers were carefully designed based on the genomic sequences of influenza A viruses retrieved from GenBank database. Several multiplex RT-PCR methods were then developed, and the target cDNAs of 25 subtype viruses were amplified by RT-PCR or overlapping PCR for evaluating the microarray. Further 52 oligonucleotide probes specific for all 25 subtype viruses were designed according to published gene sequences of avian influenza viruses in amplified target cDNAs domains, and a microarray for subtyping influenza A virus was developed. Then its specificity and sensitivity were validated by using different subtype strains and 2653 samples from 49 different areas. The results showed that all the subtypes of influenza virus could be identified simultaneously on this microarray with high sensitivity, which could reach to 2.47 pfu/mL virus or 2.5 ng target DNA. Furthermore, there was no cross reaction with other avian respiratory virus. An oligonucleotide microarray-based strategy for detection of avian influenza viruses has been developed. Such a diagnostic microarray will be useful in discovering and identifying all subtypes of avian influenza virus.

Analysis of ripening-related gene expression in papaya using an Arabidopsis-based microarray

PubMed Central

2012-01-01

Background Papaya (Carica papaya L.) is a commercially important crop that produces climacteric fruits with a soft and sweet pulp that contain a wide range of health promoting phytochemicals. Despite its importance, little is known about transcriptional modifications during papaya fruit ripening and their control. In this study we report the analysis of ripe papaya transcriptome by using a cross-species (XSpecies) microarray technique based on the phylogenetic proximity between papaya and Arabidopsis thaliana. Results Papaya transcriptome analyses resulted in the identification of 414 ripening-related genes with some having their expression validated by qPCR. The transcription profile was compared with that from ripening tomato and grape. There were many similarities between papaya and tomato especially with respect to the expression of genes encoding proteins involved in primary metabolism, regulation of transcription, biotic and abiotic stress and cell wall metabolism. XSpecies microarray data indicated that transcription factors (TFs) of the MADS-box, NAC and AP2/ERF gene families were involved in the control of papaya ripening and revealed that cell wall-related gene expression in papaya had similarities to the expression profiles seen in Arabidopsis during hypocotyl development. Conclusion The cross-species array experiment identified a ripening-related set of genes in papaya allowing the comparison of transcription control between papaya and other fruit bearing taxa during the ripening process. PMID:23256600

Transcriptomic responses to wounding: meta-analysis of gene expression microarray data.

PubMed

Sass, Piotr Andrzej; Dąbrowski, Michał; Charzyńska, Agata; Sachadyn, Paweł

2017-11-07

A vast amount of microarray data on transcriptomic response to injury has been collected so far. We designed the analysis in order to identify the genes displaying significant changes in expression after wounding in different organisms and tissues. This meta-analysis is the first study to compare gene expression profiles in response to wounding in as different tissues as heart, liver, skin, bones, and spinal cord, and species, including rat, mouse and human. We collected available microarray transcriptomic profiles obtained from different tissue injury experiments and selected the genes showing a minimum twofold change in expression in response to wounding in prevailing number of experiments for each of five wound healing stages we distinguished: haemostasis & early inflammation, inflammation, early repair, late repair and remodelling. During the initial phases after wounding, haemostasis & early inflammation and inflammation, the transcriptomic responses showed little consistency between different tissues and experiments. For the later phases, wound repair and remodelling, we identified a number of genes displaying similar transcriptional responses in all examined tissues. As revealed by ontological analyses, activation of certain pathways was rather specific for selected phases of wound healing, such as e.g. responses to vitamin D pronounced during inflammation. Conversely, we observed induction of genes encoding inflammatory agents and extracellular matrix proteins in all wound healing phases. Further, we selected several genes differentially upregulated throughout different stages of wound response, including established factors of wound healing in addition to those previously unreported  in this context such as PTPRC and AQP4. We found that transcriptomic responses to wounding showed similar traits in a diverse selection of tissues including skin, muscles, internal organs and nervous system. Notably, we distinguished transcriptional induction of inflammatory genes not only in the initial response to wounding, but also later, during wound repair and tissue remodelling.

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

PubMed Central

Müller, Christian; Schillert, Arne; Röthemeier, Caroline; Trégouët, David-Alexandre; Proust, Carole; Binder, Harald; Pfeiffer, Norbert; Beutel, Manfred; Lackner, Karl J.; Schnabel, Renate B.; Tiret, Laurence; Wild, Philipp S.; Blankenberg, Stefan

2016-01-01

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. PMID:27272489

Expression Profile of Long Noncoding RNAs in Peripheral Blood Mononuclear Cells from Multiple Sclerosis Patients.

PubMed

Zhang, Fang; Gao, Chao; Ma, Xiao-Feng; Peng, Xiao-Lin; Zhang, Rong-Xin; Kong, De-Xin; Simard, Alain R; Hao, Jun-Wei

2016-04-01

Long noncoding RNAs (lncRNAs) play a key role in regulating immunological functions. Their impact on the chronic inflammatory disease multiple sclerosis (MS), however, remains unknown. We investigated the expression of lncRNAs in peripheral blood mononuclear cells (PBMCs) of patients with MS and attempt to explain their possible role in the process of MS. For this study, we recruited 26 patients with MS according to the revised McDonald criteria. Then, we randomly chose 6 patients for microarray analysis. Microarray assays identified outstanding differences in lncRNA expression, which were verified through real-time PCR. LncRNA functions were annotated for target genes using Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses, and regulatory relationships between lncRNAs and target genes were analyzed using the "cis" and "trans" model. There were 2353 upregulated lncRNAs, 389 downregulated lncRNAs, 1037 upregulated mRNAs, and 279 downregulated mRNAs in patients with MS compared to healthy control subjects (fold change >2.0). Real-time PCR results of six aberrant lncRNAs were consistent with the microarray data. The coexpression network comprised 864 lncRNAs and 628 mRNAs. Among differentially expressed lncRNAs, 10 lncRNAs were predicted to have 10 cis-regulated target genes, and 33 lncRNAs might regulate their trans target genes. We identified a subset of dysregulated lncRNAs and mRNAs. The differentially expressed lncRNAs may be important in the process of MS. However, the specific molecular mechanisms and biological functions of these lncRNAs in the pathogenesis of MS need further study. © 2016 The Authors. CNS Neuroscience & Therapeutics published by John Wiley & Sons Ltd.

GEOquery: a bridge between the Gene Expression Omnibus (GEO) and BioConductor.

PubMed

Davis, Sean; Meltzer, Paul S

2007-07-15

Microarray technology has become a standard molecular biology tool. Experimental data have been generated on a huge number of organisms, tissue types, treatment conditions and disease states. The Gene Expression Omnibus (Barrett et al., 2005), developed by the National Center for Bioinformatics (NCBI) at the National Institutes of Health is a repository of nearly 140,000 gene expression experiments. The BioConductor project (Gentleman et al., 2004) is an open-source and open-development software project built in the R statistical programming environment (R Development core Team, 2005) for the analysis and comprehension of genomic data. The tools contained in the BioConductor project represent many state-of-the-art methods for the analysis of microarray and genomics data. We have developed a software tool that allows access to the wealth of information within GEO directly from BioConductor, eliminating many the formatting and parsing problems that have made such analyses labor-intensive in the past. The software, called GEOquery, effectively establishes a bridge between GEO and BioConductor. Easy access to GEO data from BioConductor will likely lead to new analyses of GEO data using novel and rigorous statistical and bioinformatic tools. Facilitating analyses and meta-analyses of microarray data will increase the efficiency with which biologically important conclusions can be drawn from published genomic data. GEOquery is available as part of the BioConductor project.

Exploratory Visual Analysis of Statistical Results from Microarray Experiments Comparing High and Low Grade Glioma

PubMed Central

Reif, David M.; Israel, Mark A.; Moore, Jason H.

2007-01-01

The biological interpretation of gene expression microarray results is a daunting challenge. For complex diseases such as cancer, wherein the body of published research is extensive, the incorporation of expert knowledge provides a useful analytical framework. We have previously developed the Exploratory Visual Analysis (EVA) software for exploring data analysis results in the context of annotation information about each gene, as well as biologically relevant groups of genes. We present EVA as a flexible combination of statistics and biological annotation that provides a straightforward visual interface for the interpretation of microarray analyses of gene expression in the most commonly occuring class of brain tumors, glioma. We demonstrate the utility of EVA for the biological interpretation of statistical results by analyzing publicly available gene expression profiles of two important glial tumors. The results of a statistical comparison between 21 malignant, high-grade glioblastoma multiforme (GBM) tumors and 19 indolent, low-grade pilocytic astrocytomas were analyzed using EVA. By using EVA to examine the results of a relatively simple statistical analysis, we were able to identify tumor class-specific gene expression patterns having both statistical and biological significance. Our interactive analysis highlighted the potential importance of genes involved in cell cycle progression, proliferation, signaling, adhesion, migration, motility, and structure, as well as candidate gene loci on a region of Chromosome 7 that has been implicated in glioma. Because EVA does not require statistical or computational expertise and has the flexibility to accommodate any type of statistical analysis, we anticipate EVA will prove a useful addition to the repertoire of computational methods used for microarray data analysis. EVA is available at no charge to academic users and can be found at http://www.epistasis.org. PMID:19390666

Transcriptome-Wide Mega-Analyses Reveal Joint Dysregulation of Immunologic Genes and Transcription Regulators in Brain and Blood in Schizophrenia

PubMed Central

Hess, Jonathan L.; Tylee, Daniel S.; Barve, Rahul; de Jong, Simone; Ophoff, Roel A.; Kumarasinghe, Nishantha; Tooney, Paul; Schall, Ulrich; Gardiner, Erin; Beveridge, Natalie Jane; Scott, Rodney J.; Yasawardene, Surangi; Perera, Antionette; Mendis, Jayan; Carr, Vaughan; Kelly, Brian; Cairns, Murray; Tsuang, Ming T.; Glatt, Stephen J.

2016-01-01

The application of microarray technology in schizophrenia research was heralded as paradigm-shifting, as it allowed for high-throughput assessment of cell and tissue function. This technology was widely adopted, initially in studies of postmortem brain tissue, and later in studies of peripheral blood. The collective body of schizophrenia microarray literature contains apparent inconsistencies between studies, with failures to replicate top hits, in part due to small sample sizes, cohort-specific effects, differences in array types, and other confounders. In an attempt to summarize existing studies of schizophrenia cases and non-related comparison subjects, we performed two mega-analyses of a combined set of microarray data from postmortem prefrontal cortices (n = 315) and from ex-vivo blood tissues (n = 578). We adjusted regression models per gene to remove non-significant covariates, providing best-estimates of transcripts dysregulated in schizophrenia. We also examined dysregulation of functionally related gene sets and gene co-expression modules, and assessed enrichment of cell types and genetic risk factors. The identities of the most significantly dysregulated genes were largely distinct for each tissue, but the findings indicated common emergent biological functions (e.g. immunity) and regulatory factors (e.g., predicted targets of transcription factors and miRNA species across tissues). Our network-based analyses converged upon similar patterns of heightened innate immune gene expression in both brain and blood in schizophrenia. We also constructed generalizable machine-learning classifiers using the blood-based microarray data. Our study provides an informative atlas for future pathophysiologic and biomarker studies of schizophrenia. PMID:27450777

Transcriptome-wide mega-analyses reveal joint dysregulation of immunologic genes and transcription regulators in brain and blood in schizophrenia.

PubMed

Hess, Jonathan L; Tylee, Daniel S; Barve, Rahul; de Jong, Simone; Ophoff, Roel A; Kumarasinghe, Nishantha; Tooney, Paul; Schall, Ulrich; Gardiner, Erin; Beveridge, Natalie Jane; Scott, Rodney J; Yasawardene, Surangi; Perera, Antionette; Mendis, Jayan; Carr, Vaughan; Kelly, Brian; Cairns, Murray; Tsuang, Ming T; Glatt, Stephen J

2016-10-01

The application of microarray technology in schizophrenia research was heralded as paradigm-shifting, as it allowed for high-throughput assessment of cell and tissue function. This technology was widely adopted, initially in studies of postmortem brain tissue, and later in studies of peripheral blood. The collective body of schizophrenia microarray literature contains apparent inconsistencies between studies, with failures to replicate top hits, in part due to small sample sizes, cohort-specific effects, differences in array types, and other confounders. In an attempt to summarize existing studies of schizophrenia cases and non-related comparison subjects, we performed two mega-analyses of a combined set of microarray data from postmortem prefrontal cortices (n=315) and from ex-vivo blood tissues (n=578). We adjusted regression models per gene to remove non-significant covariates, providing best-estimates of transcripts dysregulated in schizophrenia. We also examined dysregulation of functionally related gene sets and gene co-expression modules, and assessed enrichment of cell types and genetic risk factors. The identities of the most significantly dysregulated genes were largely distinct for each tissue, but the findings indicated common emergent biological functions (e.g. immunity) and regulatory factors (e.g., predicted targets of transcription factors and miRNA species across tissues). Our network-based analyses converged upon similar patterns of heightened innate immune gene expression in both brain and blood in schizophrenia. We also constructed generalizable machine-learning classifiers using the blood-based microarray data. Our study provides an informative atlas for future pathophysiologic and biomarker studies of schizophrenia. Published by Elsevier B.V.

Integrating microarray analysis and the soybean genome to understand the soybeans iron deficiency response

PubMed Central

2009-01-01

Background Soybeans grown in the upper Midwestern United States often suffer from iron deficiency chlorosis, which results in yield loss at the end of the season. To better understand the effect of iron availability on soybean yield, we identified genes in two near isogenic lines with changes in expression patterns when plants were grown in iron sufficient and iron deficient conditions. Results Transcriptional profiles of soybean (Glycine max, L. Merr) near isogenic lines Clark (PI548553, iron efficient) and IsoClark (PI547430, iron inefficient) grown under Fe-sufficient and Fe-limited conditions were analyzed and compared using the Affymetrix® GeneChip® Soybean Genome Array. There were 835 candidate genes in the Clark (PI548553) genotype and 200 candidate genes in the IsoClark (PI547430) genotype putatively involved in soybean's iron stress response. Of these candidate genes, fifty-eight genes in the Clark genotype were identified with a genetic location within known iron efficiency QTL and 21 in the IsoClark genotype. The arrays also identified 170 single feature polymorphisms (SFPs) specific to either Clark or IsoClark. A sliding window analysis of the microarray data and the 7X genome assembly coupled with an iterative model of the data showed the candidate genes are clustered in the genome. An analysis of 5' untranslated regions in the promoter of candidate genes identified 11 conserved motifs in 248 differentially expressed genes, all from the Clark genotype, representing 129 clusters identified earlier, confirming the cluster analysis results. Conclusion These analyses have identified the first genes with expression patterns that are affected by iron stress and are located within QTL specific to iron deficiency stress. The genetic location and promoter motif analysis results support the hypothesis that the differentially expressed genes are co-regulated. The combined results of all analyses lead us to postulate iron inefficiency in soybean is a result of a mutation in a transcription factor(s), which controls the expression of genes required in inducing an iron stress response. PMID:19678937

Substrate analysis of the Pneumocystis carinii protein kinases PcCbk1 and PcSte20 using yeast proteome microarrays provides a novel method for Pneumocystis signalling biology.

PubMed

Kottom, Theodore J; Limper, Andrew H

2011-10-01

Pneumocystis carinii (Pc) undergoes morphological transitions between cysts and trophic forms. We have previously described two Pc serine/threonine kinases, termed PcCbk1 and PcSte20, with PcSte20 belonging to a family of kinases involved in yeast mating, while PcCbk1 is a member of a group of protein kinases involved in regulation of cell cycle, shape, and proliferation. As Pc remains genetically intractable, knowledge on specific substrates phosphorylated by these kinases remains limited. Utilizing the phylogenetic relatedness of Pc to Saccharomyces cerevisiae, we interrogated a yeast proteome microarray containing >4000 purified protein based peptides, leading to the identification of 18 potential PcCbk1 and 15 PcSte20 substrates (Z-score > 3.0). A number of these potential protein substrates are involved in bud site selection, polarized growth, and response to mating α factor and pseudohyphal and invasive growth. Full-length open reading frames suggested by the PcCbk1 and PcSte20 protoarrays were amplified and expressed. These five proteins were used as substrates for PcCbk1 or PcSte20, with each being highly phosphorylated by the respective kinase. Finally, to demonstrate the utility of this method to identify novel PcCbk1 and PcSte20 substrates, we analysed DNA sequence data from the partially complete Pc genome database and detected partial sequence information of potential PcCbk1 kinase substrates PcPxl1 and PcInt1. We additionally identified the potential PcSte20 kinase substrate PcBdf2. Full-length Pc substrates were cloned and expressed in yeast, and shown to be phosphorylated by the respective Pc kinases. In conclusion, the yeast protein microarray represents a novel crossover technique for identifying unique potential Pc kinase substrates. Copyright © 2011 John Wiley & Sons, Ltd.

Probing the Xenopus laevis inner ear transcriptome for biological function

PubMed Central

2012-01-01

Background The senses of hearing and balance depend upon mechanoreception, a process that originates in the inner ear and shares features across species. Amphibians have been widely used for physiological studies of mechanotransduction by sensory hair cells. In contrast, much less is known of the genetic basis of auditory and vestibular function in this class of animals. Among amphibians, the genus Xenopus is a well-characterized genetic and developmental model that offers unique opportunities for inner ear research because of the amphibian capacity for tissue and organ regeneration. For these reasons, we implemented a functional genomics approach as a means to undertake a large-scale analysis of the Xenopus laevis inner ear transcriptome through microarray analysis. Results Microarray analysis uncovered genes within the X. laevis inner ear transcriptome associated with inner ear function and impairment in other organisms, thereby supporting the inclusion of Xenopus in cross-species genetic studies of the inner ear. The use of gene categories (inner ear tissue; deafness; ion channels; ion transporters; transcription factors) facilitated the assignment of functional significance to probe set identifiers. We enhanced the biological relevance of our microarray data by using a variety of curation approaches to increase the annotation of the Affymetrix GeneChip® Xenopus laevis Genome array. In addition, annotation analysis revealed the prevalence of inner ear transcripts represented by probe set identifiers that lack functional characterization. Conclusions We identified an abundance of targets for genetic analysis of auditory and vestibular function. The orthologues to human genes with known inner ear function and the highly expressed transcripts that lack annotation are particularly interesting candidates for future analyses. We used informatics approaches to impart biologically relevant information to the Xenopus inner ear transcriptome, thereby addressing the impediment imposed by insufficient gene annotation. These findings heighten the relevance of Xenopus as a model organism for genetic investigations of inner ear organogenesis, morphogenesis, and regeneration. PMID:22676585

A Versatile Microarray Platform for Capturing Rare Cells

NASA Astrophysics Data System (ADS)

Brinkmann, Falko; Hirtz, Michael; Haller, Anna; Gorges, Tobias M.; Vellekoop, Michael J.; Riethdorf, Sabine; Müller, Volkmar; Pantel, Klaus; Fuchs, Harald

2015-10-01

Analyses of rare events occurring at extremely low frequencies in body fluids are still challenging. We established a versatile microarray-based platform able to capture single target cells from large background populations. As use case we chose the challenging application of detecting circulating tumor cells (CTCs) - about one cell in a billion normal blood cells. After incubation with an antibody cocktail, targeted cells are extracted on a microarray in a microfluidic chip. The accessibility of our platform allows for subsequent recovery of targets for further analysis. The microarray facilitates exclusion of false positive capture events by co-localization allowing for detection without fluorescent labelling. Analyzing blood samples from cancer patients with our platform reached and partly outreached gold standard performance, demonstrating feasibility for clinical application. Clinical researchers free choice of antibody cocktail without need for altered chip manufacturing or incubation protocol, allows virtual arbitrary targeting of capture species and therefore wide spread applications in biomedical sciences.

Genome-Wide Gene Expression in relation to Age in Large Laboratory Cohorts of Drosophila melanogaster

PubMed Central

Carlson, Kimberly A.; Gardner, Kylee; Pashaj, Anjeza; Carlson, Darby J.; Yu, Fang; Eudy, James D.; Zhang, Chi; Harshman, Lawrence G.

2015-01-01

Aging is a complex process characterized by a steady decline in an organism's ability to perform life-sustaining tasks. In the present study, two cages of approximately 12,000 mated Drosophila melanogaster females were used as a source of RNA from individuals sampled frequently as a function of age. A linear model for microarray data method was used for the microarray analysis to adjust for the box effect; it identified 1,581 candidate aging genes. Cluster analyses using a self-organizing map algorithm on the 1,581 significant genes identified gene expression patterns across different ages. Genes involved in immune system function and regulation, chorion assembly and function, and metabolism were all significantly differentially expressed as a function of age. The temporal pattern of data indicated that gene expression related to aging is affected relatively early in life span. In addition, the temporal variance in gene expression in immune function genes was compared to a random set of genes. There was an increase in the variance of gene expression within each cohort, which was not observed in the set of random genes. This observation is compatible with the hypothesis that D. melanogaster immune function genes lose control of gene expression as flies age. PMID:26090231

Chromosomal aneuploidies and copy number variations in posterior fossa abnormalities diagnosed by prenatal ultrasonography.

PubMed

Lei, Ting; Feng, Jie-Ling; Xie, Ying-Jun; Xie, Hong-Ning; Zheng, Ju; Lin, Mei-Fang

2017-11-01

To explore the genetic aetiology of fetal posterior fossa abnormalities (PFAs). This study involved cases of PFAs that were identified by prenatal ultrasonographic screening and confirmed postnatally between January 2012 and January 2016. Conventional cytogenetic analyses and chromosomal microarray analysis were performed, and chromosomal aneuploidies and copy number variations (CNVs) were identified. Among 74 cases included in this study, 8 were of Blake's pouch cyst; 7, Dandy-Walker malformation; 11, vermian hypoplasia; 32, enlarged cisterna magna; and 16, cerebellar hypoplasia. The rates of nonbenign chromosomal aberrations (including chromosomal aneuploidies, pathogenic CNVs, and variants of unknown significance) were 2/8 (25.0%), 2/7 (28.5%), 8/11 (72.7%), 7/32 (21.9%), and 6/16 (37.5%), respectively. Cases were also classified as isolated PFAs (30/74), PFAs with other central nervous system (CNS) abnormalities (13/74), or PFAs with extra-CNS structural abnormalities (31/74). No fetuses with isolated PFAs or PFAs accompanied by other CNS abnormalities exhibited chromosomal aneuploidies or pathogenic CNVs. The rate of pathogenic chromosomal aberrations in the remaining fetuses was 17/31 (22.9%). The combined use of chromosomal microarray analysis and karyotype analysis might assist the prenatal diagnosis and management of PFAs, with extra-CNS structural abnormalities being detected by ultrasonography. © 2017 John Wiley & Sons, Ltd.

Ecology and genomics of Bacillus subtilis.

PubMed

Earl, Ashlee M; Losick, Richard; Kolter, Roberto

2008-06-01

Bacillus subtilis is a remarkably diverse bacterial species that is capable of growth within many environments. Recent microarray-based comparative genomic analyses have revealed that members of this species also exhibit considerable genomic diversity. The identification of strain-specific genes might explain how B. subtilis has become so broadly adapted. The goal of identifying ecologically adaptive genes could soon be realized with the imminent release of several new B. subtilis genome sequences. As we embark upon this exciting new era of B. subtilis comparative genomics we review what is currently known about the ecology and evolution of this species.

Advantages of RNA-seq compared to RNA microarrays for transcriptome profiling of anterior cruciate ligament tears.

PubMed

Rai, Muhammad Farooq; Tycksen, Eric D; Sandell, Linda J; Brophy, Robert H

2018-01-01

Microarrays and RNA-seq are at the forefront of high throughput transcriptome analyses. Since these methodologies are based on different principles, there are concerns about the concordance of data between the two techniques. The concordance of RNA-seq and microarrays for genome-wide analysis of differential gene expression has not been rigorously assessed in clinically derived ligament tissues. To demonstrate the concordance between RNA-seq and microarrays and to assess potential benefits of RNA-seq over microarrays, we assessed differences in transcript expression in anterior cruciate ligament (ACL) tissues based on time-from-injury. ACL remnants were collected from patients with an ACL tear at the time of ACL reconstruction. RNA prepared from torn ACL remnants was subjected to Agilent microarrays (N = 24) and RNA-seq (N = 8). The correlation of biological replicates in RNA-seq and microarrays data was similar (0.98 vs. 0.97), demonstrating that each platform has high internal reproducibility. Correlations between the RNA-seq data and the individual microarrays were low, but correlations between the RNA-seq values and the geometric mean of the microarrays values were moderate. The cross-platform concordance for differentially expressed transcripts or enriched pathways was linearly correlated (r = 0.64). RNA-Seq was superior in detecting low abundance transcripts and differentiating biologically critical isoforms. Additional independent validation of transcript expression was undertaken using microfluidic PCR for selected genes. PCR data showed 100% concordance (in expression pattern) with RNA-seq and microarrays data. These findings demonstrate that RNA-seq has advantages over microarrays for transcriptome profiling of ligament tissues when available and affordable. Furthermore, these findings are likely transferable to other musculoskeletal tissues where tissue collection is challenging and cells are in low abundance. © 2017 Orthopaedic Research Society. Published by Wiley Periodicals, Inc. J Orthop Res 36:484-497, 2018. © 2017 Orthopaedic Research Society. Published by Wiley Periodicals, Inc.

MVIAeval: a web tool for comprehensively evaluating the performance of a new missing value imputation algorithm.

PubMed

Wu, Wei-Sheng; Jhou, Meng-Jhun

2017-01-13

Missing value imputation is important for microarray data analyses because microarray data with missing values would significantly degrade the performance of the downstream analyses. Although many microarray missing value imputation algorithms have been developed, an objective and comprehensive performance comparison framework is still lacking. To solve this problem, we previously proposed a framework which can perform a comprehensive performance comparison of different existing algorithms. Also the performance of a new algorithm can be evaluated by our performance comparison framework. However, constructing our framework is not an easy task for the interested researchers. To save researchers' time and efforts, here we present an easy-to-use web tool named MVIAeval (Missing Value Imputation Algorithm evaluator) which implements our performance comparison framework. MVIAeval provides a user-friendly interface allowing users to upload the R code of their new algorithm and select (i) the test datasets among 20 benchmark microarray (time series and non-time series) datasets, (ii) the compared algorithms among 12 existing algorithms, (iii) the performance indices from three existing ones, (iv) the comprehensive performance scores from two possible choices, and (v) the number of simulation runs. The comprehensive performance comparison results are then generated and shown as both figures and tables. MVIAeval is a useful tool for researchers to easily conduct a comprehensive and objective performance evaluation of their newly developed missing value imputation algorithm for microarray data or any data which can be represented as a matrix form (e.g. NGS data or proteomics data). Thus, MVIAeval will greatly expedite the progress in the research of missing value imputation algorithms.

Extraction and labeling methods for microarrays using small amounts of plant tissue.

PubMed

Stimpson, Alexander J; Pereira, Rhea S; Kiss, John Z; Correll, Melanie J

2009-03-01

Procedures were developed to maximize the yield of high-quality RNA from small amounts of plant biomass for microarrays. Two disruption techniques (bead milling and pestle and mortar) were compared for the yield and the quality of RNA extracted from 1-week-old Arabidopsis thaliana seedlings (approximately 0.5-30 mg total biomass). The pestle and mortar method of extraction showed enhanced RNA quality at the smaller biomass samples compared with the bead milling technique, although the quality in the bead milling could be improved with additional cooling steps. The RNA extracted from the pestle and mortar technique was further tested to determine if the small quantity of RNA (500 ng-7 microg) was appropriate for microarray analyses. A new method of low-quantity RNA labeling for microarrays (NuGEN Technologies, Inc.) was used on five 7-day-old seedlings (approximately 2.5 mg fresh weight total) of Arabidopsis that were grown in the dark and exposed to 1 h of red light or continued dark. Microarray analyses were performed on a small plant sample (five seedlings; approximately 2.5 mg) using these methods and compared with extractions performed with larger biomass samples (approximately 500 roots). Many well-known light-regulated genes between the small plant samples and the larger biomass samples overlapped in expression changes, and the relative expression levels of selected genes were confirmed with quantitative real-time polymerase chain reaction, suggesting that these methods can be used for plant experiments where the biomass is extremely limited (i.e. spaceflight studies).

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

PubMed

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.

Applying Multivariate Adaptive Splines to Identify Genes With Expressions Varying After Diagnosis in Microarray Experiments.

PubMed

Duan, Fenghai; Xu, Ye

2017-01-01

To analyze a microarray experiment to identify the genes with expressions varying after the diagnosis of breast cancer. A total of 44 928 probe sets in an Affymetrix microarray data publicly available on Gene Expression Omnibus from 249 patients with breast cancer were analyzed by the nonparametric multivariate adaptive splines. Then, the identified genes with turning points were grouped by K-means clustering, and their network relationship was subsequently analyzed by the Ingenuity Pathway Analysis. In total, 1640 probe sets (genes) were reliably identified to have turning points along with the age at diagnosis in their expression profiling, of which 927 expressed lower after turning points and 713 expressed higher after the turning points. K-means clustered them into 3 groups with turning points centering at 54, 62.5, and 72, respectively. The pathway analysis showed that the identified genes were actively involved in various cancer-related functions or networks. In this article, we applied the nonparametric multivariate adaptive splines method to a publicly available gene expression data and successfully identified genes with expressions varying before and after breast cancer diagnosis.

THE MAQC (MICROARRAY QUALITY CONTROL) PROJECT: CALIBRATED RNA SAMPLES, REFERENCE DATASETS, AND QC METRICS AND THRESHOLDS

EPA Science Inventory

FDAs Critical Path Initiative identifies pharmacogenomics and toxicogenomics as key opportunities in advancing medical product development and personalized medicine, and the Guidance for Industry: Pharmacogenomic Data Submissions has been released. Microarrays represent a co...

Assessment of data processing to improve reliability of microarray experiments using genomic DNA reference.

PubMed

Yang, Yunfeng; Zhu, Mengxia; Wu, Liyou; Zhou, Jizhong

2008-09-16

Using genomic DNA as common reference in microarray experiments has recently been tested by different laboratories. Conflicting results have been reported with regard to the reliability of microarray results using this method. To explain it, we hypothesize that data processing is a critical element that impacts the data quality. Microarray experiments were performed in a gamma-proteobacterium Shewanella oneidensis. Pair-wise comparison of three experimental conditions was obtained either with two labeled cDNA samples co-hybridized to the same array, or by employing Shewanella genomic DNA as a standard reference. Various data processing techniques were exploited to reduce the amount of inconsistency between both methods and the results were assessed. We discovered that data quality was significantly improved by imposing the constraint of minimal number of replicates, logarithmic transformation and random error analyses. These findings demonstrate that data processing significantly influences data quality, which provides an explanation for the conflicting evaluation in the literature. This work could serve as a guideline for microarray data analysis using genomic DNA as a standard reference.

Rapid Detection of Rare Deleterious Variants by Next Generation Sequencing with Optional Microarray SNP Genotype Data

PubMed Central

Watson, Christopher M.; Crinnion, Laura A.; Gurgel‐Gianetti, Juliana; Harrison, Sally M.; Daly, Catherine; Antanavicuite, Agne; Lascelles, Carolina; Markham, Alexander F.; Pena, Sergio D. J.; Bonthron, David T.

2015-01-01

ABSTRACT Autozygosity mapping is a powerful technique for the identification of rare, autosomal recessive, disease‐causing genes. The ease with which this category of disease gene can be identified has greatly increased through the availability of genome‐wide SNP genotyping microarrays and subsequently of exome sequencing. Although these methods have simplified the generation of experimental data, its analysis, particularly when disparate data types must be integrated, remains time consuming. Moreover, the huge volume of sequence variant data generated from next generation sequencing experiments opens up the possibility of using these data instead of microarray genotype data to identify disease loci. To allow these two types of data to be used in an integrated fashion, we have developed AgileVCFMapper, a program that performs both the mapping of disease loci by SNP genotyping and the analysis of potentially deleterious variants using exome sequence variant data, in a single step. This method does not require microarray SNP genotype data, although analysis with a combination of microarray and exome genotype data enables more precise delineation of disease loci, due to superior marker density and distribution. PMID:26037133

Transcriptome analysis of salinity stress responses in common wheat using a 22k oligo-DNA microarray.

PubMed

Kawaura, Kanako; Mochida, Keiichi; Yamazaki, Yukiko; Ogihara, Yasunari

2006-04-01

In this study, we constructed a 22k wheat oligo-DNA microarray. A total of 148,676 expressed sequence tags of common wheat were collected from the database of the Wheat Genomics Consortium of Japan. These were grouped into 34,064 contigs, which were then used to design an oligonucleotide DNA microarray. Following a multistep selection of the sense strand, 21,939 60-mer oligo-DNA probes were selected for attachment on the microarray slide. This 22k oligo-DNA microarray was used to examine the transcriptional response of wheat to salt stress. More than 95% of the probes gave reproducible hybridization signals when targeted with RNAs extracted from salt-treated wheat shoots and roots. With the microarray, we identified 1,811 genes whose expressions changed more than 2-fold in response to salt. These included genes known to mediate response to salt, as well as unknown genes, and they were classified into 12 major groups by hierarchical clustering. These gene expression patterns were also confirmed by real-time reverse transcription-PCR. Many of the genes with unknown function were clustered together with genes known to be involved in response to salt stress. Thus, analysis of gene expression patterns combined with gene ontology should help identify the function of the unknown genes. Also, functional analysis of these wheat genes should provide new insight into the response to salt stress. Finally, these results indicate that the 22k oligo-DNA microarray is a reliable method for monitoring global gene expression patterns in wheat.

Gene response profiles for Daphnia pulex exposed to the environmental stressor cadmium reveals novel crustacean metallothioneins.

PubMed

Shaw, Joseph R; Colbourne, John K; Davey, Jennifer C; Glaholt, Stephen P; Hampton, Thomas H; Chen, Celia Y; Folt, Carol L; Hamilton, Joshua W

2007-12-21

Genomic research tools such as microarrays are proving to be important resources to study the complex regulation of genes that respond to environmental perturbations. A first generation cDNA microarray was developed for the environmental indicator species Daphnia pulex, to identify genes whose regulation is modulated following exposure to the metal stressor cadmium. Our experiments revealed interesting changes in gene transcription that suggest their biological roles and their potentially toxicological features in responding to this important environmental contaminant. Our microarray identified genes reported in the literature to be regulated in response to cadmium exposure, suggested functional attributes for genes that share no sequence similarity to proteins in the public databases, and pointed to genes that are likely members of expanded gene families in the Daphnia genome. Genes identified on the microarray also were associated with cadmium induced phenotypes and population-level outcomes that we experimentally determined. A subset of genes regulated in response to cadmium exposure was independently validated using quantitative-realtime (Q-RT)-PCR. These microarray studies led to the discovery of three genes coding for the metal detoxication protein metallothionein (MT). The gene structures and predicted translated sequences of D. pulex MTs clearly place them in this gene family. Yet, they share little homology with previously characterized MTs. The genomic information obtained from this study represents an important first step in characterizing microarray patterns that may be diagnostic to specific environmental contaminants and give insights into their toxicological mechanisms, while also providing a practical tool for evolutionary, ecological, and toxicological functional gene discovery studies. Advances in Daphnia genomics will enable the further development of this species as a model organism for the environmental sciences.

Gene response profiles for Daphnia pulex exposed to the environmental stressor cadmium reveals novel crustacean metallothioneins

PubMed Central

Shaw, Joseph R; Colbourne, John K; Davey, Jennifer C; Glaholt, Stephen P; Hampton, Thomas H; Chen, Celia Y; Folt, Carol L; Hamilton, Joshua W

2007-01-01

Background Genomic research tools such as microarrays are proving to be important resources to study the complex regulation of genes that respond to environmental perturbations. A first generation cDNA microarray was developed for the environmental indicator species Daphnia pulex, to identify genes whose regulation is modulated following exposure to the metal stressor cadmium. Our experiments revealed interesting changes in gene transcription that suggest their biological roles and their potentially toxicological features in responding to this important environmental contaminant. Results Our microarray identified genes reported in the literature to be regulated in response to cadmium exposure, suggested functional attributes for genes that share no sequence similarity to proteins in the public databases, and pointed to genes that are likely members of expanded gene families in the Daphnia genome. Genes identified on the microarray also were associated with cadmium induced phenotypes and population-level outcomes that we experimentally determined. A subset of genes regulated in response to cadmium exposure was independently validated using quantitative-realtime (Q-RT)-PCR. These microarray studies led to the discovery of three genes coding for the metal detoxication protein metallothionein (MT). The gene structures and predicted translated sequences of D. pulex MTs clearly place them in this gene family. Yet, they share little homology with previously characterized MTs. Conclusion The genomic information obtained from this study represents an important first step in characterizing microarray patterns that may be diagnostic to specific environmental contaminants and give insights into their toxicological mechanisms, while also providing a practical tool for evolutionary, ecological, and toxicological functional gene discovery studies. Advances in Daphnia genomics will enable the further development of this species as a model organism for the environmental sciences. PMID:18154678

Identification of differentially-expressed genes potentially implicated in drought response in pitaya (Hylocereus undatus) by suppression subtractive hybridization and cDNA microarray analysis.

PubMed

Fan, Qing-Jie; Yan, Feng-Xia; Qiao, Guang; Zhang, Bing-Xue; Wen, Xiao-Peng

2014-01-01

Drought is one of the most severe threats to the growth, development and yield of plant. In order to unravel the molecular basis underlying the high tolerance of pitaya (Hylocereus undatus) to drought stress, suppression subtractive hybridization (SSH) and cDNA microarray approaches were firstly combined to identify the potential important or novel genes involved in the plant responses to drought stress. The forward (drought over drought-free) and reverse (drought-free over drought) suppression subtractive cDNA libraries were constructed using in vitro shoots of cultivar 'Zihonglong' exposed to drought stress and drought-free (control). A total of 2112 clones, among which half were from either forward or reverse SSH library, were randomly picked up to construct a pitaya cDNA microarray. Microarray analysis was carried out to verify the expression fluctuations of this set of clones upon drought treatment compared with the controls. A total of 309 expressed sequence tags (ESTs), 153 from forward library and 156 from reverse library, were obtained, and 138 unique ESTs were identified after sequencing by clustering and blast analyses, which included genes that had been previously reported as responsive to water stress as well as some functionally unknown genes. Thirty six genes were mapped to 47 KEGG pathways, including carbohydrate metabolism, lipid metabolism, energy metabolism, nucleotide metabolism, and amino acid metabolism of pitaya. Expression analysis of the selected ESTs by reverse transcriptase polymerase chain reaction (RT-PCR) corroborated the results of differential screening. Moreover, time-course expression patterns of these selected ESTs further confirmed that they were closely responsive to drought treatment. Among the differentially expressed genes (DEGs), many are related to stress tolerances including drought tolerance. Thereby, the mechanism of drought tolerance of this pitaya genotype is a very complex physiological and biochemical process, in which multiple metabolism pathways and many genes were implicated. The data gained herein provide an insight into the mechanism underlying the drought stress tolerance of pitaya, as well as may facilitate the screening of candidate genes for drought tolerance. © 2013 Elsevier B.V. All rights reserved.

Heterologous oligonucleotide microarrays for transcriptomics in a non-model species; a proof-of-concept study of drought stress in Musa

PubMed Central

Davey, Mark W; Graham, Neil S; Vanholme, Bartel; Swennen, Rony; May, Sean T; Keulemans, Johan

2009-01-01

Background 'Systems-wide' approaches such as microarray RNA-profiling are ideally suited to the study of the complex overlapping responses of plants to biotic and abiotic stresses. However, commercial microarrays are only available for a limited number of plant species and development costs are so substantial as to be prohibitive for most research groups. Here we evaluate the use of cross-hybridisation to Affymetrix oligonucleotide GeneChip® microarrays to profile the response of the banana (Musa spp.) leaf transcriptome to drought stress using a genomic DNA (gDNA)-based probe-selection strategy to improve the efficiency of detection of differentially expressed Musa transcripts. Results Following cross-hybridisation of Musa gDNA to the Rice GeneChip® Genome Array, ~33,700 gene-specific probe-sets had a sufficiently high degree of homology to be retained for transcriptomic analyses. In a proof-of-concept approach, pooled RNA representing a single biological replicate of control and drought stressed leaves of the Musa cultivar 'Cachaco' were hybridised to the Affymetrix Rice Genome Array. A total of 2,910 Musa gene homologues with a >2-fold difference in expression levels were subsequently identified. These drought-responsive transcripts included many functional classes associated with plant biotic and abiotic stress responses, as well as a range of regulatory genes known to be involved in coordinating abiotic stress responses. This latter group included members of the ERF, DREB, MYB, bZIP and bHLH transcription factor families. Fifty-two of these drought-sensitive Musa transcripts were homologous to genes underlying QTLs for drought and cold tolerance in rice, including in 2 instances QTLs associated with a single underlying gene. The list of drought-responsive transcripts also included genes identified in publicly-available comparative transcriptomics experiments. Conclusion Our results demonstrate that despite the general paucity of nucleotide sequence data in Musa and only distant phylogenetic relations to rice, gDNA probe-based cross-hybridisation to the Rice GeneChip® is a highly promising strategy to study complex biological responses and illustrates the potential of such strategies for gene discovery in non-model species. PMID:19758430

Meta-analyses of microarrays of Arabidopsis asymmetric leaves1 (as1), as2 and their modifying mutants reveal a critical role for the ETT pathway in stabilization of adaxial-abaxial patterning and cell division during leaf development.

PubMed

Takahashi, Hiro; Iwakawa, Hidekazu; Ishibashi, Nanako; Kojima, Shoko; Matsumura, Yoko; Prananingrum, Pratiwi; Iwasaki, Mayumi; Takahashi, Anna; Ikezaki, Masaya; Luo, Lilan; Kobayashi, Takeshi; Machida, Yasunori; Machida, Chiyoko

2013-03-01

It is necessary to use algorithms to analyze gene expression data from DNA microarrays, such as in clustering and machine learning. Previously, we developed the knowledge-based fuzzy adaptive resonance theory (KB-FuzzyART), a clustering algorithm suitable for analyzing gene expression data, to find clues for identifying gene networks. Leaf primordia form around the shoot apical meristem (SAM), which consists of indeterminate stem cells. Upon initiation of leaf development, adaxial-abaxial patterning is crucial for lateral expansion, via cellular proliferation, and the formation of flat symmetric leaves. Many regulatory genes that specify such patterning have been identified. Analysis by the KB-FuzzyART and subsequent molecular and genetic analyses previously showed that ASYMMETRIC LEAVES1 (AS1) and AS2 repress the expression of some abaxial-determinant genes, such as AUXIN RESPONSE FACTOR3 (ARF3)/ETTIN (ETT) and ARF4, which are responsible for defects in leaf adaxial-abaxial polarity in as1 and as2. In the present study, genetic analysis revealed that ARF3/ETT and ARF4 were regulated by modifier genes, BOBBER1 (BOB1) and ELONGATA3 (ELO3), together with AS1-AS2. We analyzed expression arrays with as2 elo3 and as2 bob1, and extracted genes downstream of ARF3/ETT by using KB-FuzzyART and molecular analyses. The results showed that expression of Kip-related protein (KRP) (for inhibitors of cyclin-dependent protein kinases) and Isopentenyltransferase (IPT) (for biosynthesis of cytokinin) genes were controlled by AS1-AS2 through ARF3/ETT and ARF4 functions, which suggests that the AS1-AS2-ETT pathway plays a critical role in controlling the cell division cycle and the biosynthesis of cytokinin around SAM to stabilize leaf development in Arabidopsis thaliana.

MiMiR – an integrated platform for microarray data sharing, mining and analysis

PubMed Central

Tomlinson, Chris; Thimma, Manjula; Alexandrakis, Stelios; Castillo, Tito; Dennis, Jayne L; Brooks, Anthony; Bradley, Thomas; Turnbull, Carly; Blaveri, Ekaterini; Barton, Geraint; Chiba, Norie; Maratou, Klio; Soutter, Pat; Aitman, Tim; Game, Laurence

2008-01-01

Background Despite considerable efforts within the microarray community for standardising data format, content and description, microarray technologies present major challenges in managing, sharing, analysing and re-using the large amount of data generated locally or internationally. Additionally, it is recognised that inconsistent and low quality experimental annotation in public data repositories significantly compromises the re-use of microarray data for meta-analysis. MiMiR, the Microarray data Mining Resource was designed to tackle some of these limitations and challenges. Here we present new software components and enhancements to the original infrastructure that increase accessibility, utility and opportunities for large scale mining of experimental and clinical data. Results A user friendly Online Annotation Tool allows researchers to submit detailed experimental information via the web at the time of data generation rather than at the time of publication. This ensures the easy access and high accuracy of meta-data collected. Experiments are programmatically built in the MiMiR database from the submitted information and details are systematically curated and further annotated by a team of trained annotators using a new Curation and Annotation Tool. Clinical information can be annotated and coded with a clinical Data Mapping Tool within an appropriate ethical framework. Users can visualise experimental annotation, assess data quality, download and share data via a web-based experiment browser called MiMiR Online. All requests to access data in MiMiR are routed through a sophisticated middleware security layer thereby allowing secure data access and sharing amongst MiMiR registered users prior to publication. Data in MiMiR can be mined and analysed using the integrated EMAAS open source analysis web portal or via export of data and meta-data into Rosetta Resolver data analysis package. Conclusion The new MiMiR suite of software enables systematic and effective capture of extensive experimental and clinical information with the highest MIAME score, and secure data sharing prior to publication. MiMiR currently contains more than 150 experiments corresponding to over 3000 hybridisations and supports the Microarray Centre's large microarray user community and two international consortia. The MiMiR flexible and scalable hardware and software architecture enables secure warehousing of thousands of datasets, including clinical studies, from microarray and potentially other -omics technologies. PMID:18801157

MiMiR--an integrated platform for microarray data sharing, mining and analysis.

PubMed

Tomlinson, Chris; Thimma, Manjula; Alexandrakis, Stelios; Castillo, Tito; Dennis, Jayne L; Brooks, Anthony; Bradley, Thomas; Turnbull, Carly; Blaveri, Ekaterini; Barton, Geraint; Chiba, Norie; Maratou, Klio; Soutter, Pat; Aitman, Tim; Game, Laurence

2008-09-18

Despite considerable efforts within the microarray community for standardising data format, content and description, microarray technologies present major challenges in managing, sharing, analysing and re-using the large amount of data generated locally or internationally. Additionally, it is recognised that inconsistent and low quality experimental annotation in public data repositories significantly compromises the re-use of microarray data for meta-analysis. MiMiR, the Microarray data Mining Resource was designed to tackle some of these limitations and challenges. Here we present new software components and enhancements to the original infrastructure that increase accessibility, utility and opportunities for large scale mining of experimental and clinical data. A user friendly Online Annotation Tool allows researchers to submit detailed experimental information via the web at the time of data generation rather than at the time of publication. This ensures the easy access and high accuracy of meta-data collected. Experiments are programmatically built in the MiMiR database from the submitted information and details are systematically curated and further annotated by a team of trained annotators using a new Curation and Annotation Tool. Clinical information can be annotated and coded with a clinical Data Mapping Tool within an appropriate ethical framework. Users can visualise experimental annotation, assess data quality, download and share data via a web-based experiment browser called MiMiR Online. All requests to access data in MiMiR are routed through a sophisticated middleware security layer thereby allowing secure data access and sharing amongst MiMiR registered users prior to publication. Data in MiMiR can be mined and analysed using the integrated EMAAS open source analysis web portal or via export of data and meta-data into Rosetta Resolver data analysis package. The new MiMiR suite of software enables systematic and effective capture of extensive experimental and clinical information with the highest MIAME score, and secure data sharing prior to publication. MiMiR currently contains more than 150 experiments corresponding to over 3000 hybridisations and supports the Microarray Centre's large microarray user community and two international consortia. The MiMiR flexible and scalable hardware and software architecture enables secure warehousing of thousands of datasets, including clinical studies, from microarray and potentially other -omics technologies.

Tyrosine pathway regulation is host-mediated in the pea aphid symbiosis during late embryonic and early larval development.

PubMed

Rabatel, Andréane; Febvay, Gérard; Gaget, Karen; Duport, Gabrielle; Baa-Puyoulet, Patrice; Sapountzis, Panagiotis; Bendridi, Nadia; Rey, Marjolaine; Rahbé, Yvan; Charles, Hubert; Calevro, Federica; Colella, Stefano

2013-04-10

Nutritional symbioses play a central role in insects' adaptation to specialized diets and in their evolutionary success. The obligatory symbiosis between the pea aphid, Acyrthosiphon pisum, and the bacterium, Buchnera aphidicola, is no exception as it enables this important agricultural pest insect to develop on a diet exclusively based on plant phloem sap. The symbiotic bacteria provide the host with essential amino acids lacking in its diet but necessary for the rapid embryonic growth seen in the parthenogenetic viviparous reproduction of aphids. The aphid furnishes, in exchange, non-essential amino acids and other important metabolites. Understanding the regulations acting on this integrated metabolic system during the development of this insect is essential in elucidating aphid biology. We used a microarray-based approach to analyse gene expression in the late embryonic and the early larval stages of the pea aphid, characterizing, for the first time, the transcriptional profiles in these developmental phases. Our analyses allowed us to identify key genes in the phenylalanine, tyrosine and dopamine pathways and we identified ACYPI004243, one of the four genes encoding for the aspartate transaminase (E.C. 2.6.1.1), as specifically regulated during development. Indeed, the tyrosine biosynthetic pathway is crucial for the symbiotic metabolism as it is shared between the two partners, all the precursors being produced by B. aphidicola. Our microarray data are supported by HPLC amino acid analyses demonstrating an accumulation of tyrosine at the same developmental stages, with an up-regulation of the tyrosine biosynthetic genes. Tyrosine is also essential for the synthesis of cuticular proteins and it is an important precursor for cuticle maturation: together with the up-regulation of tyrosine biosynthesis, we observed an up-regulation of cuticular genes expression. We were also able to identify some amino acid transporter genes which are essential for the switch over to the late embryonic stages in pea aphid development. Our data show that, in the development of A. pisum, a specific host gene set regulates the biosynthetic pathways of amino acids, demonstrating how the regulation of gene expression enables an insect to control the production of metabolites crucial for its own development and symbiotic metabolism.

A system biology approach for understanding the miRNA regulatory network in colon rectal cancer.

PubMed

Pradhan, Meeta; Nagulapalli, Kshithija; Ledford, Lakenvia; Pandit, Yogesh; Palakal, Mathew

2015-01-01

In this paper we present a systems biology approach to the understanding of the miRNA-regulatory network in colon rectal cancer. An initial set of significant genes in Colon Rectal Cancer (CRC) were obtained by mining relevant literature. An initial set of cancer-related miRNAs were obtained from three databases: miRBase, miRWalk, Targetscan and GEO microarray experiment. First principle methods were then used to generate the global miRNA-gene network. Significant miRNAs and associated transcription factors in the global miRNA-gene network were identified using topological and sub-graph analyses. Eleven novel miRNAs were identified and three of the novel miRNAs, hsa-miR-630, hsa-miR-100 and hsa-miR-99a, were further analysed to elucidate their role in CRC. The proposed methodology effectively made use of literature data and was able to show novel, significant miRNA-transcription associations in CRC.

Systems biology of cancer biomarker detection.

PubMed

Mitra, Sanga; Das, Smarajit; Chakrabarti, Jayprokas

2013-01-01

Cancer systems-biology is an ever-growing area of research due to explosion of data; how to mine these data and extract useful information is the problem. To have an insight on carcinogenesis one need to systematically mine several resources, such as databases, microarray and next-generation sequences. This review encompasses management and analysis of cancer data, databases construction and data deposition, whole transcriptome and genome comparison, analysing results from high throughput experiments to uncover cellular pathways and molecular interactions, and the design of effective algorithms to identify potential biomarkers. Recent technical advances such as ChIP-on-chip, ChIP-seq and RNA-seq can be applied to get epigenetic information transformed into a high-throughput endeavour to which systems biology and bioinformatics are making significant inroads. The data from ENCODE and GENCODE projects available through UCSC genome browser can be considered as benchmark for comparison and meta-analysis. A pipeline for integrating next generation sequencing data, microarray data, and putting them together with the existing database is discussed. The understanding of cancer genomics is changing the way we approach cancer diagnosis and treatment. To give a better understanding of utilizing available resources' we have chosen oral cancer to show how and what kind of analysis can be done. This review is a computational genomic primer that provides a bird's eye view of computational and bioinformatics' tools currently available to perform integrated genomic and system biology analyses of several carcinoma.

The Utility of Chromosomal Microarray Analysis in Developmental and Behavioral Pediatrics

ERIC Educational Resources Information Center

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…

Tissue microarrays and quantitative tissue-based image analysis as a tool for oncology biomarker and diagnostic development.

PubMed

Dolled-Filhart, Marisa P; Gustavson, Mark D

2012-11-01

Translational oncology has been improved by using tissue microarrays (TMAs), which facilitate biomarker analysis of large cohorts on a single slide. This has allowed for rapid analysis and validation of potential biomarkers for prognostic and predictive value, as well as for evaluation of biomarker prevalence. Coupled with quantitative analysis of immunohistochemical (IHC) staining, objective and standardized biomarker data from tumor samples can further advance companion diagnostic approaches for the identification of drug-responsive or resistant patient subpopulations. This review covers the advantages, disadvantages and applications of TMAs for biomarker research. Research literature and reviews of TMAs and quantitative image analysis methodology have been surveyed for this review (with an AQUA® analysis focus). Applications such as multi-marker diagnostic development and pathway-based biomarker subpopulation analyses are described. Tissue microarrays are a useful tool for biomarker analyses including prevalence surveys, disease progression assessment and addressing potential prognostic or predictive value. By combining quantitative image analysis with TMAs, analyses will be more objective and reproducible, allowing for more robust IHC-based diagnostic test development. Quantitative multi-biomarker IHC diagnostic tests that can predict drug response will allow for greater success of clinical trials for targeted therapies and provide more personalized clinical decision making.

Self-directed student research through analysis of microarray datasets: a computer-based functional genomics practical class for masters-level students.

PubMed

Grenville-Briggs, Laura J; Stansfield, Ian

2011-01-01

This report describes a linked series of Masters-level computer practical workshops. They comprise an advanced functional genomics investigation, based upon analysis of a microarray dataset probing yeast DNA damage responses. The workshops require the students to analyse highly complex transcriptomics datasets, and were designed to stimulate active learning through experience of current research methods in bioinformatics and functional genomics. They seek to closely mimic a realistic research environment, and require the students first to propose research hypotheses, then test those hypotheses using specific sections of the microarray dataset. The complexity of the microarray data provides students with the freedom to propose their own unique hypotheses, tested using appropriate sections of the microarray data. This research latitude was highly regarded by students and is a strength of this practical. In addition, the focus on DNA damage by radiation and mutagenic chemicals allows them to place their results in a human medical context, and successfully sparks broad interest in the subject material. In evaluation, 79% of students scored the practical workshops on a five-point scale as 4 or 5 (totally effective) for student learning. More broadly, the general use of microarray data as a "student research playground" is also discussed. Copyright © 2011 Wiley Periodicals, Inc.

Inference of sigma factor controlled networks by using numerical modeling applied to microarray time series data of the germinating prokaryote.

PubMed

Strakova, Eva; Zikova, Alice; Vohradsky, Jiri

2014-01-01

A computational model of gene expression was applied to a novel test set of microarray time series measurements to reveal regulatory interactions between transcriptional regulators represented by 45 sigma factors and the genes expressed during germination of a prokaryote Streptomyces coelicolor. Using microarrays, the first 5.5 h of the process was recorded in 13 time points, which provided a database of gene expression time series on genome-wide scale. The computational modeling of the kinetic relations between the sigma factors, individual genes and genes clustered according to the similarity of their expression kinetics identified kinetically plausible sigma factor-controlled networks. Using genome sequence annotations, functional groups of genes that were predominantly controlled by specific sigma factors were identified. Using external binding data complementing the modeling approach, specific genes involved in the control of the studied process were identified and their function suggested.

Printing Proteins as Microarrays for High-Throughput Function Determination

NASA Astrophysics Data System (ADS)

MacBeath, Gavin; Schreiber, Stuart L.

2000-09-01

Systematic efforts are currently under way to construct defined sets of cloned genes for high-throughput expression and purification of recombinant proteins. To facilitate subsequent studies of protein function, we have developed miniaturized assays that accommodate extremely low sample volumes and enable the rapid, simultaneous processing of thousands of proteins. A high-precision robot designed to manufacture complementary DNA microarrays was used to spot proteins onto chemically derivatized glass slides at extremely high spatial densities. The proteins attached covalently to the slide surface yet retained their ability to interact specifically with other proteins, or with small molecules, in solution. Three applications for protein microarrays were demonstrated: screening for protein-protein interactions, identifying the substrates of protein kinases, and identifying the protein targets of small molecules.

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

PubMed

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.

Spot detection and image segmentation in DNA microarray data.

PubMed

Qin, Li; Rueda, Luis; Ali, Adnan; Ngom, Alioune

2005-01-01

Following the invention of microarrays in 1994, the development and applications of this technology have grown exponentially. The numerous applications of microarray technology include clinical diagnosis and treatment, drug design and discovery, tumour detection, and environmental health research. One of the key issues in the experimental approaches utilising microarrays is to extract quantitative information from the spots, which represent genes in a given experiment. For this process, the initial stages are important and they influence future steps in the analysis. Identifying the spots and separating the background from the foreground is a fundamental problem in DNA microarray data analysis. In this review, we present an overview of state-of-the-art methods for microarray image segmentation. We discuss the foundations of the circle-shaped approach, adaptive shape segmentation, histogram-based methods and the recently introduced clustering-based techniques. We analytically show that clustering-based techniques are equivalent to the one-dimensional, standard k-means clustering algorithm that utilises the Euclidean distance.

Caryoscope: An Open Source Java application for viewing microarray data in a genomic context

PubMed Central

Awad, Ihab AB; Rees, Christian A; Hernandez-Boussard, Tina; Ball, Catherine A; Sherlock, Gavin

2004-01-01

Background Microarray-based comparative genome hybridization experiments generate data that can be mapped onto the genome. These data are interpreted more easily when represented graphically in a genomic context. Results We have developed Caryoscope, which is an open source Java application for visualizing microarray data from array comparative genome hybridization experiments in a genomic context. Caryoscope can read General Feature Format files (GFF files), as well as comma- and tab-delimited files, that define the genomic positions of the microarray reporters for which data are obtained. The microarray data can be browsed using an interactive, zoomable interface, which helps users identify regions of chromosomal deletion or amplification. The graphical representation of the data can be exported in a number of graphic formats, including publication-quality formats such as PostScript. Conclusion Caryoscope is a useful tool that can aid in the visualization, exploration and interpretation of microarray data in a genomic context. PMID:15488149

The MicroArray Quality Control (MAQC) project shows inter- and intraplatform reproducibility of gene expression measurements

PubMed Central

2012-01-01

Over the last decade, the introduction of microarray technology has had a profound impact on gene expression research. The publication of studies with dissimilar or altogether contradictory results, obtained using different microarray platforms to analyze identical RNA samples, has raised concerns about the reliability of this technology. The MicroArray Quality Control (MAQC) project was initiated to address these concerns, as well as other performance and data analysis issues. Expression data on four titration pools from two distinct reference RNA samples were generated at multiple test sites using a variety of microarray-based and alternative technology platforms. Here we describe the experimental design and probe mapping efforts behind the MAQC project. We show intraplatform consistency across test sites as well as a high level of interplatform concordance in terms of genes identified as differentially expressed. This study provides a resource that represents an important first step toward establishing a framework for the use of microarrays in clinical and regulatory settings. PMID:16964229

Split-plot microarray experiments: issues of design, power and sample size.

PubMed

Tsai, Pi-Wen; Lee, Mei-Ling Ting

2005-01-01

This article focuses on microarray experiments with two or more factors in which treatment combinations of the factors corresponding to the samples paired together onto arrays are not completely random. A main effect of one (or more) factor(s) is confounded with arrays (the experimental blocks). This is called a split-plot microarray experiment. We utilise an analysis of variance (ANOVA) model to assess differentially expressed genes for between-array and within-array comparisons that are generic under a split-plot microarray experiment. Instead of standard t- or F-test statistics that rely on mean square errors of the ANOVA model, we use a robust method, referred to as 'a pooled percentile estimator', to identify genes that are differentially expressed across different treatment conditions. We illustrate the design and analysis of split-plot microarray experiments based on a case application described by Jin et al. A brief discussion of power and sample size for split-plot microarray experiments is also presented.

Cardiac transcriptome profiling of diabetic Akita mice using microarray and next generation sequencing

PubMed Central

Kesherwani, Varun; Shahshahan, Hamid R.

2017-01-01

Although diabetes mellitus (DM) causes cardiomyopathy and exacerbates heart failure, the underlying molecular mechanisms for diabetic cardiomyopathy/heart failure are poorly understood. Insulin2 mutant (Ins2+/-) Akita is a mouse model of T1DM, which manifests cardiac dysfunction. However, molecular changes at cardiac transcriptome level that lead to cardiomyopathy remain unclear. To understand the molecular changes in the heart of diabetic Akita mice, we profiled cardiac transcriptome of Ins2+/- Akita and Ins2+/+ control mice using next generation sequencing (NGS) and microarray, and determined the implications of differentially expressed genes on various heart failure signaling pathways using Ingenuity pathway (IPA) analysis. First, we validated hyperglycemia, increased cardiac fibrosis, and cardiac dysfunction in twelve-week male diabetic Akita. Then, we analyzed the transcriptome levels in the heart. NGS analyses on Akita heart revealed 137 differentially expressed transcripts, where Bone Morphogenic Protein-10 (BMP10) was the most upregulated and hairy and enhancer of split-related (HELT) was the most downregulated gene. Moreover, twelve long non-coding RNAs (lncRNAs) were upregulated. The microarray analyses on Akita heart showed 351 differentially expressed transcripts, where vomeronasal-1 receptor-180 (Vmn1r180) was the most upregulated and WD Repeat Domain 83 Opposite Strand (WDR83OS) was the most downregulated gene. Further, miR-101c and H19 lncRNA were upregulated but Neat1 lncRNA was downregulated in Akita heart. Eleven common genes were upregulated in Akita heart in both NGS and microarray analyses. IPA analyses revealed the role of these differentially expressed genes in key signaling pathways involved in diabetic cardiomyopathy. Our results provide a platform to initiate focused future studies by targeting these genes and/or non-coding RNAs, which are differentially expressed in Akita hearts and are involved in diabetic cardiomyopathy. PMID:28837672

Meta-analysis of studies using suppression subtractive hybridization and microarrays to investigate the effects of environmental stress on gene transcription in oysters.

PubMed

Anderson, Kelli; Taylor, Daisy A; Thompson, Emma L; Melwani, Aroon R; Nair, Sham V; Raftos, David A

2015-01-01

Many microarray and suppression subtractive hybridization (SSH) studies have analyzed the effects of environmental stress on gene transcription in marine species. However, there have been no unifying analyses of these data to identify common stress response pathways. To address this shortfall, we conducted a meta-analysis of 14 studies that investigated the effects of different environmental stressors on gene expression in oysters. The stressors tested included chemical contamination, hypoxia and infection, as well as extremes of temperature, pH and turbidity. We found that the expression of over 400 genes in a range of oyster species changed significantly after exposure to environmental stress. A repeating pattern was evident in these transcriptional responses, regardless of the type of stress applied. Many of the genes that responded to environmental stress encoded proteins involved in translation and protein processing (including molecular chaperones), the mitochondrial electron transport chain, anti-oxidant activity and the cytoskeleton. In light of these findings, we put forward a consensus model of sub-cellular stress responses in oysters.

Gene expression analysis of hypersensitivity to mosquito bite, chronic active EBV infection and NK/T-lymphoma/leukemia.

PubMed

Washio, Kana; Oka, Takashi; Abdalkader, Lamia; Muraoka, Michiko; Shimada, Akira; Oda, Megumi; Sato, Hiaki; Takata, Katsuyoshi; Kagami, Yoshitoyo; Shimizu, Norio; Kato, Seiichi; Kimura, Hiroshi; Nishizaki, Kazunori; Yoshino, Tadashi; Tsukahara, Hirokazu

2017-11-01

The human herpes virus, Epstein-Barr virus (EBV), is a known oncogenic virus and plays important roles in life-threatening T/NK-cell lymphoproliferative disorders (T/NK-cell LPD) such as hypersensitivity to mosquito bite (HMB), chronic active EBV infection (CAEBV), and NK/T-cell lymphoma/leukemia. During the clinical courses of HMB and CAEBV, patients frequently develop malignant lymphomas and the diseases passively progress sequentially. In the present study, gene expression of CD16 (-) CD56 (+) -, EBV (+) HMB, CAEBV, NK-lymphoma, and NK-leukemia cell lines, which were established from patients, was analyzed using oligonucleotide microarrays and compared to that of CD56 bright CD16 dim/- NK cells from healthy donors. Principal components analysis showed that CAEBV and NK-lymphoma cells were relatively closely located, indicating that they had similar expression profiles. Unsupervised hierarchal clustering analyses of microarray data and gene ontology analysis revealed specific gene clusters and identified several candidate genes responsible for disease that can be used to discriminate each category of NK-LPD and NK-cell lymphoma/leukemia.

Genome-wide RNA profiling of long-lasting stem cell-like memory CD8 T cells induced by Yellow Fever vaccination in humans.

PubMed

Fuertes Marraco, Silvia A; Soneson, Charlotte; Delorenzi, Mauro; Speiser, Daniel E

2015-09-01

The live-attenuated Yellow Fever (YF) vaccine YF-17D induces a broad and polyfunctional CD8 T cell response in humans. Recently, we identified a population of stem cell-like memory CD8 T cells induced by YF-17D that persists at stable frequency for at least 25 years after vaccination. The YF-17D is thus a model system of human CD8 T cell biology that furthermore allows to track and study long-lasting and antigen-specific human memory CD8 T cells. Here, we describe in detail the sample characteristics and preparation of a microarray dataset acquired for genome-wide gene expression profiling of long-lasting YF-specific stem cell-like memory CD8 T cells, compared to the reference CD8 T cell differentiation subsets from total CD8 T cells. We also describe the quality controls, annotations and exploratory analyses of the dataset. The microarray data is available from the Gene Expression Omnibus (GEO) public repository with accession number GSE65804.

Meta-Analysis of Studies Using Suppression Subtractive Hybridization and Microarrays to Investigate the Effects of Environmental Stress on Gene Transcription in Oysters

PubMed Central

Thompson, Emma L.; Melwani, Aroon R.; Nair, Sham V.; Raftos, David A.

2015-01-01

Many microarray and suppression subtractive hybridization (SSH) studies have analyzed the effects of environmental stress on gene transcription in marine species. However, there have been no unifying analyses of these data to identify common stress response pathways. To address this shortfall, we conducted a meta-analysis of 14 studies that investigated the effects of different environmental stressors on gene expression in oysters. The stressors tested included chemical contamination, hypoxia and infection, as well as extremes of temperature, pH and turbidity. We found that the expression of over 400 genes in a range of oyster species changed significantly after exposure to environmental stress. A repeating pattern was evident in these transcriptional responses, regardless of the type of stress applied. Many of the genes that responded to environmental stress encoded proteins involved in translation and protein processing (including molecular chaperones), the mitochondrial electron transport chain, anti-oxidant activity and the cytoskeleton. In light of these findings, we put forward a consensus model of sub-cellular stress responses in oysters. PMID:25768438

TIPMaP: a web server to establish transcript isoform profiles from reliable microarray probes.

PubMed

Chitturi, Neelima; Balagannavar, Govindkumar; Chandrashekar, Darshan S; Abinaya, Sadashivam; Srini, Vasan S; Acharya, Kshitish K

2013-12-27

Standard 3' Affymetrix gene expression arrays have contributed a significantly higher volume of existing gene expression data than other microarray platforms. These arrays were designed to identify differentially expressed genes, but not their alternatively spliced transcript forms. No resource can currently identify expression pattern of specific mRNA forms using these microarray data, even though it is possible to do this. We report a web server for expression profiling of alternatively spliced transcripts using microarray data sets from 31 standard 3' Affymetrix arrays for human, mouse and rat species. The tool has been experimentally validated for mRNAs transcribed or not-detected in a human disease condition (non-obstructive azoospermia, a male infertility condition). About 4000 gene expression datasets were downloaded from a public repository. 'Good probes' with complete coverage and identity to latest reference transcript sequences were first identified. Using them, 'Transcript specific probe-clusters' were derived for each platform and used to identify expression status of possible transcripts. The web server can lead the user to datasets corresponding to specific tissues, conditions via identifiers of the microarray studies or hybridizations, keywords, official gene symbols or reference transcript identifiers. It can identify, in the tissues and conditions of interest, about 40% of known transcripts as 'transcribed', 'not-detected' or 'differentially regulated'. Corresponding additional information for probes, genes, transcripts and proteins can be viewed too. We identified the expression of transcripts in a specific clinical condition and validated a few of these transcripts by experiments (using reverse transcription followed by polymerase chain reaction). The experimental observations indicated higher agreements with the web server results, than contradictions. The tool is accessible at http://resource.ibab.ac.in/TIPMaP. The newly developed online tool forms a reliable means for identification of alternatively spliced transcript-isoforms that may be differentially expressed in various tissues, cell types or physiological conditions. Thus, by making better use of existing data, TIPMaP avoids the dependence on precious tissue-samples, in experiments with a goal to establish expression profiles of alternative splice forms--at least in some cases.

Differentially co-expressed interacting protein pairs discriminate samples under distinct stages of HIV type 1 infection.

PubMed

Yoon, Dukyong; Kim, Hyosil; Suh-Kim, Haeyoung; Park, Rae Woong; Lee, KiYoung

2011-01-01

Microarray analyses based on differentially expressed genes (DEGs) have been widely used to distinguish samples across different cellular conditions. However, studies based on DEGs have not been able to clearly determine significant differences between samples of pathophysiologically similar HIV-1 stages, e.g., between acute and chronic progressive (or AIDS) or between uninfected and clinically latent stages. We here suggest a novel approach to allow such discrimination based on stage-specific genetic features of HIV-1 infection. Our approach is based on co-expression changes of genes known to interact. The method can identify a genetic signature for a single sample as contrasted with existing protein-protein-based analyses with correlational designs. Our approach distinguishes each sample using differentially co-expressed interacting protein pairs (DEPs) based on co-expression scores of individual interacting pairs within a sample. The co-expression score has positive value if two genes in a sample are simultaneously up-regulated or down-regulated. And the score has higher absolute value if expression-changing ratios are similar between the two genes. We compared characteristics of DEPs with that of DEGs by evaluating their usefulness in separation of HIV-1 stage. And we identified DEP-based network-modules and their gene-ontology enrichment to find out the HIV-1 stage-specific gene signature. Based on the DEP approach, we observed clear separation among samples from distinct HIV-1 stages using clustering and principal component analyses. Moreover, the discrimination power of DEPs on the samples (70-100% accuracy) was much higher than that of DEGs (35-45%) using several well-known classifiers. DEP-based network analysis also revealed the HIV-1 stage-specific network modules; the main biological processes were related to "translation," "RNA splicing," "mRNA, RNA, and nucleic acid transport," and "DNA metabolism." Through the HIV-1 stage-related modules, changing stage-specific patterns of protein interactions could be observed. DEP-based method discriminated the HIV-1 infection stages clearly, and revealed a HIV-1 stage-specific gene signature. The proposed DEP-based method might complement existing DEG-based approaches in various microarray expression analyses.

Structure and transcriptional regulation of the major intrinsic protein gene family in grapevine.

PubMed

Wong, Darren Chern Jan; Zhang, Li; Merlin, Isabelle; Castellarin, Simone D; Gambetta, Gregory A

2018-04-11

The major intrinsic protein (MIP) family is a family of proteins, including aquaporins, which facilitate water and small molecule transport across plasma membranes. In plants, MIPs function in a huge variety of processes including water transport, growth, stress response, and fruit development. In this study, we characterize the structure and transcriptional regulation of the MIP family in grapevine, describing the putative genome duplication events leading to the family structure and characterizing the family's tissue and developmental specific expression patterns across numerous preexisting microarray and RNAseq datasets. Gene co-expression network (GCN) analyses were carried out across these datasets and the promoters of each family member were analyzed for cis-regulatory element structure in order to provide insight into their transcriptional regulation. A total of 29 Vitis vinifera MIP family members (excluding putative pseudogenes) were identified of which all but two were mapped onto Vitis vinifera chromosomes. In this study, segmental duplication events were identified for five plasma membrane intrinsic protein (PIP) and four tonoplast intrinsic protein (TIP) genes, contributing to the expansion of PIPs and TIPs in grapevine. Grapevine MIP family members have distinct tissue and developmental expression patterns and hierarchical clustering revealed two primary groups regardless of the datasets analyzed. Composite microarray and RNA-seq gene co-expression networks (GCNs) highlighted the relationships between MIP genes and functional categories involved in cell wall modification and transport, as well as with other MIPs revealing a strong co-regulation within the family itself. Some duplicated MIP family members have undergone sub-functionalization and exhibit distinct expression patterns and GCNs. Cis-regulatory element (CRE) analyses of the MIP promoters and their associated GCN members revealed enrichment for numerous CREs including AP2/ERFs and NACs. Combining phylogenetic analyses, gene expression profiling, gene co-expression network analyses, and cis-regulatory element enrichment, this study provides a comprehensive overview of the structure and transcriptional regulation of the grapevine MIP family. The study highlights the duplication and sub-functionalization of the family, its strong coordinated expression with genes involved in growth and transport, and the putative classes of TFs responsible for its regulation.

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

NASA Astrophysics Data System (ADS)

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.

Estimation of gene induction enables a relevance-based ranking of gene sets.

PubMed

Bartholomé, Kilian; Kreutz, Clemens; Timmer, Jens

2009-07-01

In order to handle and interpret the vast amounts of data produced by microarray experiments, the analysis of sets of genes with a common biological functionality has been shown to be advantageous compared to single gene analyses. Some statistical methods have been proposed to analyse the differential gene expression of gene sets in microarray experiments. However, most of these methods either require threshhold values to be chosen for the analysis, or they need some reference set for the determination of significance. We present a method that estimates the number of differentially expressed genes in a gene set without requiring a threshold value for significance of genes. The method is self-contained (i.e., it does not require a reference set for comparison). In contrast to other methods which are focused on significance, our approach emphasizes the relevance of the regulation of gene sets. The presented method measures the degree of regulation of a gene set and is a useful tool to compare the induction of different gene sets and place the results of microarray experiments into the biological context. An R-package is available.

Transfer of chromosome 3 fragments suppresses tumorigenicity of an ovarian cancer cell line monoallelic for chromosome 3p.

PubMed

Cody, N A L; Ouellet, V; Manderson, E N; Quinn, M C J; Filali-Mouhim, A; Tellis, P; Zietarska, M; Provencher, D M; Mes-Masson, A-M; Chevrette, M; Tonin, P N

2007-01-25

Multiple chromosome 3p tumor suppressor genes (TSG) have been proposed in the pathogenesis of ovarian cancer based on complex patterns of 3p loss. To attain functional evidence in support of TSGs and identify candidate regions, we applied a chromosome transfer method involving cell fusions of the tumorigenic OV90 human ovarian cancer cell line, monoallelic for 3p and an irradiated mouse cell line containing a human chromosome 3 in order to derive OV90 hybrids containing normal 3p fragments. The resulting hybrids showed complete or incomplete suppression of tumorigenicity in nude mouse xenograft assays, and varied in their ability to form colonies in soft agarose and three-dimensional spheroids in a manner consistent with alteration of their in vivo tumorigenic phenotypes. Expression microarray analysis identified a set of common differentially expressed genes, such as SPARC, DAB2 and VEGF, some of which have been shown implicated in ovarian cancer. Genotyping assays revealed that they harbored normal 3p fragments, some of which overlapped candidate TSG regions (3p25-p26, 3p24 and 3p14-pcen) identified previously in loss of heterozygosity analyses of ovarian cancers. However, only the 3p12-pcen region was acquired in common by all hybrids where expression microarray analysis identified differentially expressed genes. The correlation of 3p12-pcen transfer and tumor suppression with a concerted re-programming of the cellular transcriptome suggest that the putative TSG may have affected key underlying events in ovarian cancer.

Genome-wide analyses of LINE–LINE-mediated nonallelic homologous recombination

PubMed Central

Startek, Michał; Szafranski, Przemyslaw; Gambin, Tomasz; Campbell, Ian M.; Hixson, Patricia; Shaw, Chad A.; Stankiewicz, Paweł; Gambin, Anna

2015-01-01

Nonallelic homologous recombination (NAHR), occurring between low-copy repeats (LCRs) >10 kb in size and sharing >97% DNA sequence identity, is responsible for the majority of recurrent genomic rearrangements in the human genome. Recent studies have shown that transposable elements (TEs) can also mediate recurrent deletions and translocations, indicating the features of substrates that mediate NAHR may be significantly less stringent than previously believed. Using >4 kb length and >95% sequence identity criteria, we analyzed of the genome-wide distribution of long interspersed element (LINE) retrotransposon and their potential to mediate NAHR. We identified 17 005 directly oriented LINE pairs located <10 Mbp from each other as potential NAHR substrates, placing 82.8% of the human genome at risk of LINE–LINE-mediated instability. Cross-referencing these regions with CNVs in the Baylor College of Medicine clinical chromosomal microarray database of 36 285 patients, we identified 516 CNVs potentially mediated by LINEs. Using long-range PCR of five different genomic regions in a total of 44 patients, we confirmed that the CNV breakpoints in each patient map within the LINE elements. To additionally assess the scale of LINE–LINE/NAHR phenomenon in the human genome, we tested DNA samples from six healthy individuals on a custom aCGH microarray targeting LINE elements predicted to mediate CNVs and identified 25 LINE–LINE rearrangements. Our data indicate that LINE–LINE-mediated NAHR is widespread and under-recognized, and is an important mechanism of structural rearrangement contributing to human genomic variability. PMID:25613453

Separate-channel analysis of two-channel microarrays: recovering inter-spot information.

PubMed

Smyth, Gordon K; Altman, Naomi S

2013-05-26

Two-channel (or two-color) microarrays are cost-effective platforms for comparative analysis of gene expression. They are traditionally analysed in terms of the log-ratios (M-values) of the two channel intensities at each spot, but this analysis does not use all the information available in the separate channel observations. Mixed models have been proposed to analyse intensities from the two channels as separate observations, but such models can be complex to use and the gain in efficiency over the log-ratio analysis is difficult to quantify. Mixed models yield test statistics for the null distributions can be specified only approximately, and some approaches do not borrow strength between genes. This article reformulates the mixed model to clarify the relationship with the traditional log-ratio analysis, to facilitate information borrowing between genes, and to obtain an exact distributional theory for the resulting test statistics. The mixed model is transformed to operate on the M-values and A-values (average log-expression for each spot) instead of on the log-expression values. The log-ratio analysis is shown to ignore information contained in the A-values. The relative efficiency of the log-ratio analysis is shown to depend on the size of the intraspot correlation. A new separate channel analysis method is proposed that assumes a constant intra-spot correlation coefficient across all genes. This approach permits the mixed model to be transformed into an ordinary linear model, allowing the data analysis to use a well-understood empirical Bayes analysis pipeline for linear modeling of microarray data. This yields statistically powerful test statistics that have an exact distributional theory. The log-ratio, mixed model and common correlation methods are compared using three case studies. The results show that separate channel analyses that borrow strength between genes are more powerful than log-ratio analyses. The common correlation analysis is the most powerful of all. The common correlation method proposed in this article for separate-channel analysis of two-channel microarray data is no more difficult to apply in practice than the traditional log-ratio analysis. It provides an intuitive and powerful means to conduct analyses and make comparisons that might otherwise not be possible.

Development of a Schistosoma mansoni shotgun O-glycan microarray and application to the discovery of new antigenic schistosome glycan motifs.

PubMed

van Diepen, Angela; van der Plas, Arend-Jan; Kozak, Radoslaw P; Royle, Louise; Dunne, David W; Hokke, Cornelis H

2015-06-01

Upon infection with Schistosoma, antibody responses are mounted that are largely directed against glycans. Over the last few years significant progress has been made in characterising the antigenic properties of N-glycans of Schistosoma mansoni. Despite also being abundantly expressed by schistosomes, much less is understood about O-glycans and antibody responses to these have not yet been systematically analysed. Antibody binding to schistosome glycans can be analysed efficiently and quantitatively using glycan microarrays, but O-glycan array construction and exploration is lagging behind because no universal O-glycanase is available, and release of O-glycans has been dependent on chemical methods. Recently, a modified hydrazinolysis method has been developed that allows the release of O-glycans with free reducing termini and limited degradation, and we applied this method to obtain O-glycans from different S. mansoni life stages. Two-dimensional HPLC separation of 2-aminobenzoic acid-labelled O-glycans generated 362 O-glycan-containing fractions that were printed on an epoxide-modified glass slide, thereby generating the first shotgun O-glycan microarray containing naturally occurring schistosome O-glycans. Monoclonal antibodies and mass spectrometry showed that the O-glycan microarray contains well-known antigenic glycan motifs as well as numerous other, potentially novel, antibody targets. Incubations of the microarrays with sera from Schistosoma-infected humans showed substantial antibody responses to O-glycans in addition to those observed to the previously investigated N- and glycosphingolipid glycans. This underlines the importance of the inclusion of these often schistosome-specific O-glycans in glycan antigen studies and indicates that O-glycans contain novel antigenic motifs that have potential for use in diagnostic methods and studies aiming at the discovery of vaccine targets. Copyright © 2015 The Authors. Published by Elsevier Ltd.. All rights reserved.

Fish and chips: Various methodologies demonstrate utility of a 16,006-gene salmonid microarray

PubMed Central

von Schalburg, Kristian R; Rise, Matthew L; Cooper, Glenn A; Brown, Gordon D; Gibbs, A Ross; Nelson, Colleen C; Davidson, William S; Koop, Ben F

2005-01-01

Background We have developed and fabricated a salmonid microarray containing cDNAs representing 16,006 genes. The genes spotted on the array have been stringently selected from Atlantic salmon and rainbow trout expressed sequence tag (EST) databases. The EST databases presently contain over 300,000 sequences from over 175 salmonid cDNA libraries derived from a wide variety of tissues and different developmental stages. In order to evaluate the utility of the microarray, a number of hybridization techniques and screening methods have been developed and tested. Results We have analyzed and evaluated the utility of a microarray containing 16,006 (16K) salmonid cDNAs in a variety of potential experimental settings. We quantified the amount of transcriptome binding that occurred in cross-species, organ complexity and intraspecific variation hybridization studies. We also developed a methodology to rapidly identify and confirm the contents of a bacterial artificial chromosome (BAC) library containing Atlantic salmon genomic DNA. Conclusion We validate and demonstrate the usefulness of the 16K microarray over a wide range of teleosts, even for transcriptome targets from species distantly related to salmonids. We show the potential of the use of the microarray in a variety of experimental settings through hybridization studies that examine the binding of targets derived from different organs and tissues. Intraspecific variation in transcriptome expression is evaluated and discussed. Finally, BAC hybridizations are demonstrated as a rapid and accurate means to identify gene content. PMID:16164747

High-density polymer microarrays: identifying synthetic polymers that control human embryonic stem cell growth.

PubMed

Hansen, Anne; Mjoseng, Heidi K; Zhang, Rong; Kalloudis, Michail; Koutsos, Vasileios; de Sousa, Paul A; Bradley, Mark

2014-06-01

The fabrication of high-density polymer microarray is described, allowing the simultaneous and efficient evaluation of more than 7000 different polymers in a single-cellular-based screen. These high-density polymer arrays are applied in the search for synthetic substrates for hESCs culture. Up-scaling of the identified hit polymers enables long-term cellular cultivation and promoted successful stem-cell maintenance. © 2013 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

CLOFIBRATE-INDUCED GENE EXPRESSION CHANGES IN RAT LIVER: A CROSS-LABORATORY ANALYSIS USING MEMBRANE CDNA ARRAYS

EPA Science Inventory

Microarrays have the potential to significantly impact our ability to identify toxic hazards by the identification of mechanistically-relevant markers of toxicity. To be useful for risk assessment however, microarray data must be challenged to determine its reliability and inter...

IDENTIFICATION OF BIOLOGICALLY RELEVANT GENES USING A DATABASE OF RAT LIVER AND KIDNEY BASELINE GENE EXPRESSION

EPA Science Inventory

Microarray data from independent labs and studies can be compared to potentially identify toxicologically and biologically relevant genes. The Baseline Animal Database working group of HESI was formed to assess baseline gene expression from microarray data derived from control or...

Comparative Profiling of Primary Colorectal Carcinomas and Liver Metastases Identifies LEF1 as a Prognostic Biomarker

PubMed Central

Lin, Albert Y.; Chua, Mei-Sze; Choi, Yoon-La; Yeh, William; Kim, Young H.; Azzi, Raymond; Adams, Gregg A.; Sainani, Kristin; van de Rijn, Matt; So, Samuel K.; Pollack, Jonathan R.

2011-01-01

Purpose We sought to identify genes of clinical significance to predict survival and the risk for colorectal liver metastasis (CLM), the most common site of metastasis from colorectal cancer (CRC). Patients and Methods We profiled gene expression in 31 specimens from primary CRC and 32 unmatched specimens of CLM, and performed Significance Analysis of Microarrays (SAM) to identify genes differentially expressed between these two groups. To characterize the clinical relevance of two highly-ranked differentially-expressed genes, we analyzed the expression of secreted phosphoprotein 1 (SPP1 or osteopontin) and lymphoid enhancer factor-1 (LEF1) by immunohistochemistry using a tissue microarray (TMA) representing an independent set of 154 patients with primary CRC. Results Supervised analysis using SAM identified 963 genes with significantly higher expression in CLM compared to primary CRC, with a false discovery rate of <0.5%. TMA analysis showed SPP1 and LEF1 protein overexpression in 60% and 44% of CRC cases, respectively. Subsequent occurrence of CLM was significantly correlated with the overexpression of LEF1 (chi-square p = 0.042), but not SPP1 (p = 0.14). Kaplan Meier analysis revealed significantly worse survival in patients with overexpression of LEF1 (p<0.01), but not SPP1 (p = 0.11). Both univariate and multivariate analyses identified stage (p<0.0001) and LEF1 overexpression (p<0.05) as important prognostic markers, but not tumor grade or SPP1. Conclusion Among genes differentially expressed between CLM and primary CRC, we demonstrate overexpression of LEF1 in primary CRC to be a prognostic factor for poor survival and increased risk for liver metastasis. PMID:21383983

Comparative genome analysis of a large Dutch Legionella pneumophila strain collection identifies five markers highly correlated with clinical strains

PubMed Central

2010-01-01

Background Discrimination between clinical and environmental strains within many bacterial species is currently underexplored. Genomic analyses have clearly shown the enormous variability in genome composition between different strains of a bacterial species. In this study we have used Legionella pneumophila, the causative agent of Legionnaire's disease, to search for genomic markers related to pathogenicity. During a large surveillance study in The Netherlands well-characterized patient-derived strains and environmental strains were collected. We have used a mixed-genome microarray to perform comparative-genome analysis of 257 strains from this collection. Results Microarray analysis indicated that 480 DNA markers (out of in total 3360 markers) showed clear variation in presence between individual strains and these were therefore selected for further analysis. Unsupervised statistical analysis of these markers showed the enormous genomic variation within the species but did not show any correlation with a pathogenic phenotype. We therefore used supervised statistical analysis to identify discriminating markers. Genetic programming was used both to identify predictive markers and to define their interrelationships. A model consisting of five markers was developed that together correctly predicted 100% of the clinical strains and 69% of the environmental strains. Conclusions A novel approach for identifying predictive markers enabling discrimination between clinical and environmental isolates of L. pneumophila is presented. Out of over 3000 possible markers, five were selected that together enabled correct prediction of all the clinical strains included in this study. This novel approach for identifying predictive markers can be applied to all bacterial species, allowing for better discrimination between strains well equipped to cause human disease and relatively harmless strains. PMID:20630115

Single-Nucleotide Polymorphism-Microarray Ploidy Analysis of Paraffin-Embedded Products of Conception in Recurrent Pregnancy Loss Evaluations.

PubMed

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 cytogenetic results. Recommended recurrent pregnancy loss screening was unnecessary in almost half the patients in our study. II.

Identifying molecular features for prostate cancer with Gleason 7 based on microarray gene expression profiles.

PubMed

Bălăcescu, Loredana; Bălăcescu, O; Crişan, N; Fetica, B; Petruţ, B; Bungărdean, Cătălina; Rus, Meda; Tudoran, Oana; Meurice, G; Irimie, Al; Dragoş, N; Berindan-Neagoe, Ioana

2011-01-01

Prostate cancer represents the first leading cause of cancer among western male population, with different clinical behavior ranging from indolent to metastatic disease. Although many molecules and deregulated pathways are known, the molecular mechanisms involved in the development of prostate cancer are not fully understood. The aim of this study was to explore the molecular variation underlying the prostate cancer, based on microarray analysis and bioinformatics approaches. Normal and prostate cancer tissues were collected by macrodissection from prostatectomy pieces. All prostate cancer specimens used in our study were Gleason score 7. Gene expression microarray (Agilent Technologies) was used for Whole Human Genome evaluation. The bioinformatics and functional analysis were based on Limma and Ingenuity software. The microarray analysis identified 1119 differentially expressed genes between prostate cancer and normal prostate, which were up- or down-regulated at least 2-fold. P-values were adjusted for multiple testing using Benjamini-Hochberg method with a false discovery rate of 0.01. These genes were analyzed with Ingenuity Pathway Analysis software and were established 23 genetic networks. Our microarray results provide new information regarding the molecular networks in prostate cancer stratified as Gleason 7. These data highlighted gene expression profiles for better understanding of prostate cancer progression.

Analysis of host response to bacterial infection using error model based gene expression microarray experiments

PubMed Central

Stekel, Dov J.; Sarti, Donatella; Trevino, Victor; Zhang, Lihong; Salmon, Mike; Buckley, Chris D.; Stevens, Mark; Pallen, Mark J.; Penn, Charles; Falciani, Francesco

2005-01-01

A key step in the analysis of microarray data is the selection of genes that are differentially expressed. Ideally, such experiments should be properly replicated in order to infer both technical and biological variability, and the data should be subjected to rigorous hypothesis tests to identify the differentially expressed genes. However, in microarray experiments involving the analysis of very large numbers of biological samples, replication is not always practical. Therefore, there is a need for a method to select differentially expressed genes in a rational way from insufficiently replicated data. In this paper, we describe a simple method that uses bootstrapping to generate an error model from a replicated pilot study that can be used to identify differentially expressed genes in subsequent large-scale studies on the same platform, but in which there may be no replicated arrays. The method builds a stratified error model that includes array-to-array variability, feature-to-feature variability and the dependence of error on signal intensity. We apply this model to the characterization of the host response in a model of bacterial infection of human intestinal epithelial cells. We demonstrate the effectiveness of error model based microarray experiments and propose this as a general strategy for a microarray-based screening of large collections of biological samples. PMID:15800204

Microarray-based identification of differentially expressed genes in extramammary Paget’s disease

PubMed Central

Lin, Jin-Ran; Liang, Jun; Zhang, Qiao-An; Huang, Qiong; Wang, Shang-Shang; Qin, Hai-Hong; Chen, Lian-Jun; Xu, Jin-Hua

2015-01-01

Extramammary Paget’s disease (EMPD) is a rare cutaneous malignancy accounting for approximately 1-2% of vulvar cancers. The rarity of this disease has caused difficulties in characterization and the molecular mechanism underlying EMPD development remains largely unclear. Here we used microarray analysis to identify differentially expressed genes in EMPD of the scrotum comparing with normal epithelium from healthy donors. Agilent single-channel microarray was used to compare the gene expression between 6 EMPD specimens and 6 normal scrotum epithelium samples. A total of 799 up-regulated genes and 723 down-regulated genes were identified in EMPD tissues. Real-time PCR was conducted to verify the differential expression of some representative genes, including ERBB4, TCF3, PAPSS2, PIK3R3, PRLR, SULT1A1, TCF7L1, and CREB3L4. Generally, the real-time PCR results were consistent with microarray data, and the expression of ERBB4, PRLR, TCF3, PIK3R3, SULT1A1, and TCF7L1 was significantly overexpressed in EMPD (P<0.05). Moreover, the overexpression of PRLR in EMPD, a receptor for the anterior pituitary hormone prolactin (PRL), was confirmed by immunohistochemistry. These data demonstrate that the differentially expressed genes from the microarray-based identification are tightly associated with EMPD occurrence. PMID:26221264

Performance evaluation of DNA copy number segmentation methods.

PubMed

Pierre-Jean, Morgane; Rigaill, Guillem; Neuvial, Pierre

2015-07-01

A number of bioinformatic or biostatistical methods are available for analyzing DNA copy number profiles measured from microarray or sequencing technologies. In the absence of rich enough gold standard data sets, the performance of these methods is generally assessed using unrealistic simulation studies, or based on small real data analyses. To make an objective and reproducible performance assessment, we have designed and implemented a framework to generate realistic DNA copy number profiles of cancer samples with known truth. These profiles are generated by resampling publicly available SNP microarray data from genomic regions with known copy-number state. The original data have been extracted from dilutions series of tumor cell lines with matched blood samples at several concentrations. Therefore, the signal-to-noise ratio of the generated profiles can be controlled through the (known) percentage of tumor cells in the sample. This article describes this framework and its application to a comparison study between methods for segmenting DNA copy number profiles from SNP microarrays. This study indicates that no single method is uniformly better than all others. It also helps identifying pros and cons of the compared methods as a function of biologically informative parameters, such as the fraction of tumor cells in the sample and the proportion of heterozygous markers. This comparison study may be reproduced using the open source and cross-platform R package jointseg, which implements the proposed data generation and evaluation framework: http://r-forge.r-project.org/R/?group_id=1562. © The Author 2014. Published by Oxford University Press.

Comparison of gene expression responses to hypoxia in viviparous (Xiphophorus) and oviparous (Oryzias) fishes using a medaka microarray.

PubMed

Boswell, Mikki G; Wells, Melissa C; Kirk, Lyndsey M; Ju, Zhenlin; Zhang, Ziping; Booth, Rachell E; Walter, Ronald B

2009-03-01

Gene expression profiling using DNA microarray technology is a useful tool for assessing gene transcript level responses after an organism is exposed to environmental stress. Herein, we detail results from studies using an 8 k medaka (Oryzias latipes) microarray to assess modulated gene expression patterns upon hypoxia exposure of the live-bearing aquaria fish, Xiphophorus maculatus. To assess the reproducibility and reliability of using the medaka array in cross-genus hybridization, a two-factor ANOVA analysis of gene expression was employed. The data show the tissue source of the RNA used for array hybridization contributed more to the observed response of modulated gene targets than did the species source of the RNA. In addition, hierarchical clustering via heat map analyses of groupings of tissues and species (Xiphophorus and medaka) suggests that hypoxia induced similar responses in the same tissues from these two diverse aquatic model organisms. Our Xiphophorus results indicate 206 brain, 37 liver, and 925 gill gene targets exhibit hypoxia induced expression changes. Analysis of the Xiphophorus data to determine those features exhibiting a significant (p<0.05)+/-3 fold change produced only two gene targets within brain tissue and 80 features within gill tissue. Of these 82 characterized features, 39 were identified via homology searching (cut-off E-value of 1 x 10(-5)) and placed into one or more biological process gene ontology groups. Among these 39 genes, metabolic energy changes and manipulation was the most affected biological pathway (13 genes).

Microarray analysis identifies Salmonella genes belonging to the low-shear modeled microgravity regulon

NASA Technical Reports Server (NTRS)

Wilson, James W.; Ramamurthy, Rajee; Porwollik, Steffen; McClelland, Michael; Hammond, Timothy; Allen, Pat; Ott, C. Mark; Pierson, Duane L.; Nickerson, Cheryl A.

2002-01-01

The low-shear environment of optimized rotation suspension culture allows both eukaryotic and prokaryotic cells to assume physiologically relevant phenotypes that have led to significant advances in fundamental investigations of medical and biological importance. This culture environment has also been used to model microgravity for ground-based studies regarding the impact of space flight on eukaryotic and prokaryotic physiology. We have previously demonstrated that low-shear modeled microgravity (LSMMG) under optimized rotation suspension culture is a novel environmental signal that regulates the virulence, stress resistance, and protein expression levels of Salmonella enterica serovar Typhimurium. However, the mechanisms used by the cells of any species, including Salmonella, to sense and respond to LSMMG and identities of the genes involved are unknown. In this study, we used DNA microarrays to elucidate the global transcriptional response of Salmonella to LSMMG. When compared with identical growth conditions under normal gravity (1 x g), LSMMG differentially regulated the expression of 163 genes distributed throughout the chromosome, representing functionally diverse groups including transcriptional regulators, virulence factors, lipopolysaccharide biosynthetic enzymes, iron-utilization enzymes, and proteins of unknown function. Many of the LSMMG-regulated genes were organized in clusters or operons. The microarray results were further validated by RT-PCR and phenotypic analyses, and they indicate that the ferric uptake regulator is involved in the LSMMG response. The results provide important insight about the Salmonella LSMMG response and could provide clues for the functioning of known Salmonella virulence systems or the identification of uncharacterized bacterial virulence strategies.

Prediction of regulatory gene pairs using dynamic time warping and gene ontology.

PubMed

Yang, Andy C; Hsu, Hui-Huang; Lu, Ming-Da; Tseng, Vincent S; Shih, Timothy K

2014-01-01

Selecting informative genes is the most important task for data analysis on microarray gene expression data. In this work, we aim at identifying regulatory gene pairs from microarray gene expression data. However, microarray data often contain multiple missing expression values. Missing value imputation is thus needed before further processing for regulatory gene pairs becomes possible. We develop a novel approach to first impute missing values in microarray time series data by combining k-Nearest Neighbour (KNN), Dynamic Time Warping (DTW) and Gene Ontology (GO). After missing values are imputed, we then perform gene regulation prediction based on our proposed DTW-GO distance measurement of gene pairs. Experimental results show that our approach is more accurate when compared with existing missing value imputation methods on real microarray data sets. Furthermore, our approach can also discover more regulatory gene pairs that are known in the literature than other methods.

Mistaken Identifiers: Gene name errors can be introduced inadvertently when using Excel in bioinformatics

PubMed Central

Zeeberg, Barry R; Riss, Joseph; Kane, David W; Bussey, Kimberly J; Uchio, Edward; Linehan, W Marston; Barrett, J Carl; Weinstein, John N

2004-01-01

Background When processing microarray data sets, we recently noticed that some gene names were being changed inadvertently to non-gene names. Results A little detective work traced the problem to default date format conversions and floating-point format conversions in the very useful Excel program package. The date conversions affect at least 30 gene names; the floating-point conversions affect at least 2,000 if Riken identifiers are included. These conversions are irreversible; the original gene names cannot be recovered. Conclusions Users of Excel for analyses involving gene names should be aware of this problem, which can cause genes, including medically important ones, to be lost from view and which has contaminated even carefully curated public databases. We provide work-arounds and scripts for circumventing the problem. PMID:15214961

Modular organization of the white spruce (Picea glauca) transcriptome reveals functional organization and evolutionary signatures.

PubMed

Raherison, Elie S M; Giguère, Isabelle; Caron, Sébastien; Lamara, Mebarek; MacKay, John J

2015-07-01

Transcript profiling has shown the molecular bases of several biological processes in plants but few studies have developed an understanding of overall transcriptome variation. We investigated transcriptome structure in white spruce (Picea glauca), aiming to delineate its modular organization and associated functional and evolutionary attributes. Microarray analyses were used to: identify and functionally characterize groups of co-expressed genes; investigate expressional and functional diversity of vascular tissue preferential genes which were conserved among Picea species, and identify expression networks underlying wood formation. We classified 22 857 genes as variable (79%; 22 coexpression groups) or invariant (21%) by profiling across several vegetative tissues. Modular organization and complex transcriptome restructuring among vascular tissue preferential genes was revealed by their assignment to coexpression groups with partially overlapping profiles and partially distinct functions. Integrated analyses of tissue-based and temporally variable profiles identified secondary xylem gene networks, showed their remodelling over a growing season and identified PgNAC-7 (no apical meristerm (NAM), Arabidopsis transcription activation factor (ATAF) and cup-shaped cotyledon (CUC) transcription factor 007 in Picea glauca) as a major hub gene specific to earlywood formation. Reference profiling identified comprehensive, statistically robust coexpressed groups, revealing that modular organization underpins the evolutionary conservation of the transcriptome structure. © 2015 The Authors. New Phytologist © 2015 New Phytologist Trust.

Microarray Meta-Analysis Identifies Acute Lung Injury Biomarkers in Donor Lungs That Predict Development of Primary Graft Failure in Recipients

PubMed Central

Haitsma, Jack J.; Furmli, Suleiman; Masoom, Hussain; Liu, Mingyao; Imai, Yumiko; Slutsky, Arthur S.; Beyene, Joseph; Greenwood, Celia M. T.; dos Santos, Claudia

2012-01-01

Objectives To perform a meta-analysis of gene expression microarray data from animal studies of lung injury, and to identify an injury-specific gene expression signature capable of predicting the development of lung injury in humans. Methods We performed a microarray meta-analysis using 77 microarray chips across six platforms, two species and different animal lung injury models exposed to lung injury with or/and without mechanical ventilation. Individual gene chips were classified and grouped based on the strategy used to induce lung injury. Effect size (change in gene expression) was calculated between non-injurious and injurious conditions comparing two main strategies to pool chips: (1) one-hit and (2) two-hit lung injury models. A random effects model was used to integrate individual effect sizes calculated from each experiment. Classification models were built using the gene expression signatures generated by the meta-analysis to predict the development of lung injury in human lung transplant recipients. Results Two injury-specific lists of differentially expressed genes generated from our meta-analysis of lung injury models were validated using external data sets and prospective data from animal models of ventilator-induced lung injury (VILI). Pathway analysis of gene sets revealed that both new and previously implicated VILI-related pathways are enriched with differentially regulated genes. Classification model based on gene expression signatures identified in animal models of lung injury predicted development of primary graft failure (PGF) in lung transplant recipients with larger than 80% accuracy based upon injury profiles from transplant donors. We also found that better classifier performance can be achieved by using meta-analysis to identify differentially-expressed genes than using single study-based differential analysis. Conclusion Taken together, our data suggests that microarray analysis of gene expression data allows for the detection of “injury" gene predictors that can classify lung injury samples and identify patients at risk for clinically relevant lung injury complications. PMID:23071521

MicroArray Facility: a laboratory information management system with extended support for Nylon based technologies.

PubMed

Honoré, Paul; Granjeaud, Samuel; Tagett, Rebecca; Deraco, Stéphane; Beaudoing, Emmanuel; Rougemont, Jacques; Debono, Stéphane; Hingamp, Pascal

2006-09-20

High throughput gene expression profiling (GEP) is becoming a routine technique in life science laboratories. With experimental designs that repeatedly span thousands of genes and hundreds of samples, relying on a dedicated database infrastructure is no longer an option.GEP technology is a fast moving target, with new approaches constantly broadening the field diversity. This technology heterogeneity, compounded by the informatics complexity of GEP databases, means that software developments have so far focused on mainstream techniques, leaving less typical yet established techniques such as Nylon microarrays at best partially supported. MAF (MicroArray Facility) is the laboratory database system we have developed for managing the design, production and hybridization of spotted microarrays. Although it can support the widely used glass microarrays and oligo-chips, MAF was designed with the specific idiosyncrasies of Nylon based microarrays in mind. Notably single channel radioactive probes, microarray stripping and reuse, vector control hybridizations and spike-in controls are all natively supported by the software suite. MicroArray Facility is MIAME supportive and dynamically provides feedback on missing annotations to help users estimate effective MIAME compliance. Genomic data such as clone identifiers and gene symbols are also directly annotated by MAF software using standard public resources. The MAGE-ML data format is implemented for full data export. Journalized database operations (audit tracking), data anonymization, material traceability and user/project level confidentiality policies are also managed by MAF. MicroArray Facility is a complete data management system for microarray producers and end-users. Particular care has been devoted to adequately model Nylon based microarrays. The MAF system, developed and implemented in both private and academic environments, has proved a robust solution for shared facilities and industry service providers alike.

MicroArray Facility: a laboratory information management system with extended support for Nylon based technologies

PubMed Central

Honoré, Paul; Granjeaud, Samuel; Tagett, Rebecca; Deraco, Stéphane; Beaudoing, Emmanuel; Rougemont, Jacques; Debono, Stéphane; Hingamp, Pascal

2006-01-01

Background High throughput gene expression profiling (GEP) is becoming a routine technique in life science laboratories. With experimental designs that repeatedly span thousands of genes and hundreds of samples, relying on a dedicated database infrastructure is no longer an option. GEP technology is a fast moving target, with new approaches constantly broadening the field diversity. This technology heterogeneity, compounded by the informatics complexity of GEP databases, means that software developments have so far focused on mainstream techniques, leaving less typical yet established techniques such as Nylon microarrays at best partially supported. Results MAF (MicroArray Facility) is the laboratory database system we have developed for managing the design, production and hybridization of spotted microarrays. Although it can support the widely used glass microarrays and oligo-chips, MAF was designed with the specific idiosyncrasies of Nylon based microarrays in mind. Notably single channel radioactive probes, microarray stripping and reuse, vector control hybridizations and spike-in controls are all natively supported by the software suite. MicroArray Facility is MIAME supportive and dynamically provides feedback on missing annotations to help users estimate effective MIAME compliance. Genomic data such as clone identifiers and gene symbols are also directly annotated by MAF software using standard public resources. The MAGE-ML data format is implemented for full data export. Journalized database operations (audit tracking), data anonymization, material traceability and user/project level confidentiality policies are also managed by MAF. Conclusion MicroArray Facility is a complete data management system for microarray producers and end-users. Particular care has been devoted to adequately model Nylon based microarrays. The MAF system, developed and implemented in both private and academic environments, has proved a robust solution for shared facilities and industry service providers alike. PMID:16987406

A meta-data based method for DNA microarray imputation.

PubMed

Jörnsten, Rebecka; Ouyang, Ming; Wang, Hui-Yu

2007-03-29

DNA microarray experiments are conducted in logical sets, such as time course profiling after a treatment is applied to the samples, or comparisons of the samples under two or more conditions. Due to cost and design constraints of spotted cDNA microarray experiments, each logical set commonly includes only a small number of replicates per condition. Despite the vast improvement of the microarray technology in recent years, missing values are prevalent. Intuitively, imputation of missing values is best done using many replicates within the same logical set. In practice, there are few replicates and thus reliable imputation within logical sets is difficult. However, it is in the case of few replicates that the presence of missing values, and how they are imputed, can have the most profound impact on the outcome of downstream analyses (e.g. significance analysis and clustering). This study explores the feasibility of imputation across logical sets, using the vast amount of publicly available microarray data to improve imputation reliability in the small sample size setting. We download all cDNA microarray data of Saccharomyces cerevisiae, Arabidopsis thaliana, and Caenorhabditis elegans from the Stanford Microarray Database. Through cross-validation and simulation, we find that, for all three species, our proposed imputation using data from public databases is far superior to imputation within a logical set, sometimes to an astonishing degree. Furthermore, the imputation root mean square error for significant genes is generally a lot less than that of non-significant ones. Since downstream analysis of significant genes, such as clustering and network analysis, can be very sensitive to small perturbations of estimated gene effects, it is highly recommended that researchers apply reliable data imputation prior to further analysis. Our method can also be applied to cDNA microarray experiments from other species, provided good reference data are available.

DNA Microarray for Rapid Detection and Identification of Food and Water Borne Bacteria: From Dry to Wet Lab.

PubMed

Ranjbar, Reza; Behzadi, Payam; Najafi, Ali; Roudi, Raheleh

2017-01-01

A rapid, accurate, flexible and reliable diagnostic method may significantly decrease the costs of diagnosis and treatment. Designing an appropriate microarray chip reduces noises and probable biases in the final result. The aim of this study was to design and construct a DNA Microarray Chip for a rapid detection and identification of 10 important bacterial agents. In the present survey, 10 unique genomic regions relating to 10 pathogenic bacterial agents including Escherichia coli (E.coli), Shigella boydii, Sh.dysenteriae, Sh.flexneri, Sh.sonnei, Salmonella typhi, S.typhimurium, Brucella sp., Legionella pneumophila, and Vibrio cholera were selected for designing specific long oligo microarray probes. For this reason, the in-silico operations including utilization of the NCBI RefSeq database, Servers of PanSeq and Gview, AlleleID 7.7 and Oligo Analyzer 3.1 was done. On the other hand, the in-vitro part of the study comprised stages of robotic microarray chip probe spotting, bacterial DNAs extraction and DNA labeling, hybridization and microarray chip scanning. In wet lab section, different tools and apparatus such as Nexterion® Slide E, Qarray mini spotter, NimbleGen kit, TrayMix TM S4, and Innoscan 710 were used. A DNA microarray chip including 10 long oligo microarray probes was designed and constructed for detection and identification of 10 pathogenic bacteria. The DNA microarray chip was capable to identify all 10 bacterial agents tested simultaneously. The presence of a professional bioinformatician as a probe designer is needed to design appropriate multifunctional microarray probes to increase the accuracy of the outcomes.

Comparison of gene expression microarray data with count-based RNA measurements informs microarray interpretation.

PubMed

Richard, Arianne C; Lyons, Paul A; Peters, James E; Biasci, Daniele; Flint, Shaun M; Lee, James C; McKinney, Eoin F; Siegel, Richard M; Smith, Kenneth G C

2014-08-04

Although numerous investigations have compared gene expression microarray platforms, preprocessing methods and batch correction algorithms using constructed spike-in or dilution datasets, there remains a paucity of studies examining the properties of microarray data using diverse biological samples. Most microarray experiments seek to identify subtle differences between samples with variable background noise, a scenario poorly represented by constructed datasets. Thus, microarray users lack important information regarding the complexities introduced in real-world experimental settings. The recent development of a multiplexed, digital technology for nucleic acid measurement enables counting of individual RNA molecules without amplification and, for the first time, permits such a study. Using a set of human leukocyte subset RNA samples, we compared previously acquired microarray expression values with RNA molecule counts determined by the nCounter Analysis System (NanoString Technologies) in selected genes. We found that gene measurements across samples correlated well between the two platforms, particularly for high-variance genes, while genes deemed unexpressed by the nCounter generally had both low expression and low variance on the microarray. Confirming previous findings from spike-in and dilution datasets, this "gold-standard" comparison demonstrated signal compression that varied dramatically by expression level and, to a lesser extent, by dataset. Most importantly, examination of three different cell types revealed that noise levels differed across tissues. Microarray measurements generally correlate with relative RNA molecule counts within optimal ranges but suffer from expression-dependent accuracy bias and precision that varies across datasets. We urge microarray users to consider expression-level effects in signal interpretation and to evaluate noise properties in each dataset independently.

Polyadenylation state microarray (PASTA) analysis.

PubMed

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.

Lecithin:retinol acyltransferase in ARPE-19

DTIC Science & Technology

2005-04-05

analyses. (A) Microarray analysis was performed on RNA extracted from ARPE 19. Both LRAT (white), and housekeeping gene G3PDH (shaded) were detected...about one third of the house keeping gene glyceraldehydes-3-phosphate dehydrogenase ( G3PDH ) 663G66. Western analyses with tLRAT antibody showed that LRAT

Role of the Chemokine MCP-1 in Sensitization of PKC-Mediated Apoptosis in Prostate Cancer Cells

DTIC Science & Technology

2010-02-01

component. As phorbol esters are strong inducers of gene expression, we analyzed changes in gene expression using Affymetrix microarrays. These studies...were carried out at the UPenn Microarray Facility. We studied the dynamics of changes in gene expression by PMA at different times between 0 and 24 h...after PMA treatment. We identified ~ 5,000 PMA- genes up- or down-regulated by PMA (> 2-fold change), identified early and late genes , and classified

Clinical application of chromosomal microarray analysis for the prenatal diagnosis of chromosomal abnormalities and copy number variations in fetuses with congenital heart disease.

PubMed

Xia, Yu; Yang, Yongchao; Huang, Shufang; Wu, Yueheng; Li, Ping; Zhuang, Jian

2018-03-24

This study aimed to determine chromosomal abnormalities and copy number variations (CNVs) in fetuses with congenital heart disease (CHD) by chromosomal microarray analysis (CMA). One hundred and ten cases with CHD detected by prenatal echocardiography were enrolled in the study; 27 cases were simple CHDs, and 83 were complex CHDs. Chromosomal microarray analysis was performed on the Affymetrix CytoScan HD platform. All annotated CNVs were validated by quantitative PCR. Chromosomal microarray analysis identified 6 cases with chromosomal abnormalities, including 2 cases with trisomy 21, 2 cases with trisomy 18, 1 case with trisomy 13, and 1 unusual case of mosaic trisomy 21. Pathogenic CNVs were detected in 15.5% (17/110) of the fetuses with CHDs, including 13 cases with CHD-associated CNVs. We further identified 10 genes as likely novel CHD candidate genes through gene functional enrichment analysis. We also found that pathogenic CMA results impacted the rate of pregnancy termination. This study shows that CMA is particularly effective for identifying chromosomal abnormalities and CNVs in fetuses with CHDs as well as having an effect on obstetrical outcomes. The elucidation of the genetic basis of CHDs will continue to expand our understanding of the etiology of CHDs. © 2018 John Wiley & Sons, Ltd.

A proposed metric for assessing the measurement quality of individual microarrays

PubMed Central

Kim, Kyoungmi; Page, Grier P; Beasley, T Mark; Barnes, Stephen; Scheirer, Katherine E; Allison, David B

2006-01-01

Background High-density microarray technology is increasingly applied to study gene expression levels on a large scale. Microarray experiments rely on several critical steps that may introduce error and uncertainty in analyses. These steps include mRNA sample extraction, amplification and labeling, hybridization, and scanning. In some cases this may be manifested as systematic spatial variation on the surface of microarray in which expression measurements within an individual array may vary as a function of geographic position on the array surface. Results We hypothesized that an index of the degree of spatiality of gene expression measurements associated with their physical geographic locations on an array could indicate the summary of the physical reliability of the microarray. We introduced a novel way to formulate this index using a statistical analysis tool. Our approach regressed gene expression intensity measurements on a polynomial response surface of the microarray's Cartesian coordinates. We demonstrated this method using a fixed model and presented results from real and simulated datasets. Conclusion We demonstrated the potential of such a quantitative metric for assessing the reliability of individual arrays. Moreover, we showed that this procedure can be incorporated into laboratory practice as a means to set quality control specifications and as a tool to determine whether an array has sufficient quality to be retained in terms of spatial correlation of gene expression measurements. PMID:16430768

Microarray Analysis of Long Noncoding RNAs in Female Diabetic Peripheral Neuropathy Patients.

PubMed

Luo, Lin; Ji, Lin-Dan; Cai, Jiang-Jia; Feng, Mei; Zhou, Mi; Hu, Su-Pei; Xu, Jin; Zhou, Wen-Hua

2018-01-01

Diabetic peripheral neuropathy (DPN) is the most common complication of diabetes mellitus (DM). Because of its controversial pathogenesis, DPN is still not diagnosed or managed properly in most patients. In this study, human lncRNA microarrays were used to identify the differentially expressed lncRNAs in DM and DPN patients, and some of the discovered lncRNAs were further validated in additional 78 samples by quantitative realtime PCR (qRT-PCR). The microarray analysis identified 446 and 1327 differentially expressed lncRNAs in DM and DPN, respectively. The KEGG pathway analysis further revealed that the differentially expressed lncRNA-coexpressed mRNAs between DPN and DM groups were significantly enriched in the MAPK signaling pathway. The lncRNA/mRNA coexpression network indicated that BDNF and TRAF2 correlated with 6 lncRNAs. The qRT-PCR confirmed the initial microarray results. These findings demonstrated that the interplay between lncRNAs and mRNA may be involved in the pathogenesis of DPN, especially the neurotrophin-MAPK signaling pathway, thus providing relevant information for future studies. © 2018 The Author(s). Published by S. Karger AG, Basel.

Cell cycle arrest and gene expression profiling of testis in mice exposed to fluoride.

PubMed

Su, Kai; Sun, Zilong; Niu, Ruiyan; Lei, Ying; Cheng, Jing; Wang, Jundong

2017-05-01

Exposure to fluoride results in low reproductive capacity; however, the mechanism underlying the impact of fluoride on male productive system still remains obscure. To assess the potential toxicity in testis of mice administrated with fluoride, global genome microarray and real-time PCR were performed to detect and identify the altered transcriptions. The results revealed that 763 differentially expressed genes were identified, including 330 up-regulated and 433 down-regulated genes, which were involved in spermatogenesis, apoptosis, DNA damage, DNA replication, and cell differentiation. Twelve differential expressed genes were selected to confirm the microarray results using real-time PCR, and the result kept the same tendency with that of microarray. Furthermore, compared with the control group, more apoptotic spermatogenic cells were observed in the fluoride group, and the spermatogonium were markedly increased in S phase and decreased in G2/M phase by fluoride. Our findings suggested global genome microarray provides an insight into the reproductive toxicity induced by fluoride, and several important biological clues for further investigations. © 2016 Wiley Periodicals, Inc. Environ Toxicol 32: 1558-1565, 2017. © 2016 Wiley Periodicals, Inc.

Simplified Microarray Technique for Identifying mRNA in Rare Samples

NASA Technical Reports Server (NTRS)

Almeida, Eduardo; Kadambi, Geeta

2007-01-01

Two simplified methods of identifying messenger ribonucleic acid (mRNA), and compact, low-power apparatuses to implement the methods, are at the proof-of-concept stage of development. These methods are related to traditional methods based on hybridization of nucleic acid, but whereas the traditional methods must be practiced in laboratory settings, these methods could be practiced in field settings. Hybridization of nucleic acid is a powerful technique for detection of specific complementary nucleic acid sequences, and is increasingly being used for detection of changes in gene expression in microarrays containing thousands of gene probes. A traditional microarray study entails at least the following six steps: 1. Purification of cellular RNA, 2. Amplification of complementary deoxyribonucleic acid [cDNA] by polymerase chain reaction (PCR), 3. Labeling of cDNA with fluorophores of Cy3 (a green cyanine dye) and Cy5 (a red cyanine dye), 4. Hybridization to a microarray chip, 5. Fluorescence scanning the array(s) with dual excitation wavelengths, and 6. Analysis of the resulting images. This six-step procedure must be performed in a laboratory because it requires bulky equipment.

A Unique Procedure to Identify Cell Surface Markers Through a Spherical Self-Organizing Map Applied to DNA Microarray Analysis.

PubMed

Sugii, Yuh; Kasai, Tomonari; Ikeda, Masashi; Vaidyanath, Arun; Kumon, Kazuki; Mizutani, Akifumi; Seno, Akimasa; Tokutaka, Heizo; Kudoh, Takayuki; Seno, Masaharu

2016-01-01

To identify cell-specific markers, we designed a DNA microarray platform with oligonucleotide probes for human membrane-anchored proteins. Human glioma cell lines were analyzed using microarray and compared with normal and fetal brain tissues. For the microarray analysis, we employed a spherical self-organizing map, which is a clustering method suitable for the conversion of multidimensional data into two-dimensional data and displays the relationship on a spherical surface. Based on the gene expression profile, the cell surface characteristics were successfully mirrored onto the spherical surface, thereby distinguishing normal brain tissue from the disease model based on the strength of gene expression. The clustered glioma-specific genes were further analyzed by polymerase chain reaction procedure and immunocytochemical staining of glioma cells. Our platform and the following procedure were successfully demonstrated to categorize the genes coding for cell surface proteins that are specific to glioma cells. Our assessment demonstrates that a spherical self-organizing map is a valuable tool for distinguishing cell surface markers and can be employed in marker discovery studies for the treatment of cancer.

MASQOT: a method for cDNA microarray spot quality control

PubMed Central

Bylesjö, Max; Eriksson, Daniel; Sjödin, Andreas; Sjöström, Michael; Jansson, Stefan; Antti, Henrik; Trygg, Johan

2005-01-01

Background cDNA microarray technology has emerged as a major player in the parallel detection of biomolecules, but still suffers from fundamental technical problems. Identifying and removing unreliable data is crucial to prevent the risk of receiving illusive analysis results. Visual assessment of spot quality is still a common procedure, despite the time-consuming work of manually inspecting spots in the range of hundreds of thousands or more. Results A novel methodology for cDNA microarray spot quality control is outlined. Multivariate discriminant analysis was used to assess spot quality based on existing and novel descriptors. The presented methodology displays high reproducibility and was found superior in identifying unreliable data compared to other evaluated methodologies. Conclusion The proposed methodology for cDNA microarray spot quality control generates non-discrete values of spot quality which can be utilized as weights in subsequent analysis procedures as well as to discard spots of undesired quality using the suggested threshold values. The MASQOT approach provides a consistent assessment of spot quality and can be considered an alternative to the labor-intensive manual quality assessment process. PMID:16223442

A DNA microarray for identification of selected Korean birds based on mitochondrial cytochrome c oxidase I gene sequences.

PubMed

Chung, In-Hyuk; Yoo, Hye Sook; Eah, Jae-Yong; Yoon, Hyun-Kyu; Jung, Jin-Wook; Hwang, Seung Yong; Kim, Chang-Bae

2010-10-01

DNA barcoding with the gene encoding cytochrome c oxidase I (COI) in the mitochondrial genome has been proposed as a standard marker to identify and discover animal species. Some migratory wild birds are suspected of transmitting avian influenza and pose a threat to aircraft safety because of bird strikes. We have previously reported the COI gene sequences of 92 Korean bird species. In the present study, we developed a DNA microarray to identify 17 selected bird species on the basis of nucleotide diversity. We designed and synthesized 19 specific oligonucleotide probes; these probes were arrayed on a silylated glass slide. The length of the probes was 19-24 bps. The COI sequences amplified from the tissues of the selected birds were labeled with a fluorescent probe for microarray hybridization, and unique hybridization patterns were detected for each selected species. These patterns may be considered diagnostic patterns for species identification. This microarray system will provide a sensitive and a high-throughput method for identification of Korean birds.

MYCN-non-amplified metastatic neuroblastoma with good prognosis and spontaneous regression: a molecular portrait of stage 4S.

PubMed

Bénard, Jean; Raguénez, Gilda; Kauffmann, Audrey; Valent, Alexander; Ripoche, Hugues; Joulin, Virginie; Job, Bastien; Danglot, Gisèle; Cantais, Sabrina; Robert, Thomas; Terrier-Lacombe, Marie-José; Chassevent, Agnès; Koscielny, Serge; Fischer, Matthias; Berthold, Frank; Lipinski, Marc; Tursz, Thomas; Dessen, Philippe; Lazar, Vladimir; Valteau-Couanet, Dominique

2008-10-01

Stage 4 neuroblastoma (NB) are heterogeneous regarding their clinical presentations and behavior. Indeed infants (stage 4S and non-stage 4S of age <365days at diagnosis) show regression contrasting with progression in children (>365days). Our study aimed at: (i) identifying age-based genomic and gene expression profiles of stage 4 NB supporting this clinical stratification; and (ii) finding a stage 4S NB signature. Differential genome and transcriptome analyses of a learning set of MYCN-non amplified stage 4 NB tumors at diagnosis (n=29 tumors including 12 stage 4S) were performed using 1Mb BAC microarrays and Agilent 22K probes oligo-microarrays. mRNA chips data following filtering yielded informative genes before supervised hierarchical clustering to identify relationship among tumor samples. After confirmation by quantitative RT-PCR, a stage 4S NB's gene cluster was obtained and submitted to a validation set (n=22 tumors). Genomic abnormalities of infant's tumors (whole chromosomes gains or loss) differ radically from that of children (intra-chromosomal rearrangements) but could not discriminate infants with 4S from those without this presentation. In contrast, differential gene expression by looking at both individual genes and whole biological pathways leads to a molecular stage 4S NB portrait which provides new biological clues about this fascinating entity.

Transcriptome remodeling associated with chronological aging in the dinoflagellate, Karenia brevis.

PubMed

Johnson, Jillian G; Morey, Jeanine S; Neely, Marion G; Ryan, James C; Van Dolah, Frances M

2012-03-01

The toxic dinoflagellate, Karenia brevis, forms dense blooms in the Gulf of Mexico that persist for many months in coastal waters, where they can cause extensive marine animal mortalities and human health impacts. The mechanisms that enable cell survival in high density, low growth blooms, and the mechanisms leading to often rapid bloom demise are not well understood. To gain an understanding of processes that underlie chronological aging in this dinoflagellate, a microarray study was carried out to identify changes in the global transcriptome that accompany the entry and maintenance of stationary phase up to the onset of cell death. The transcriptome of K. brevis was assayed using a custom 10,263 feature oligonucleotide microarray from mid-logarithmic growth to the onset of culture demise. A total of 2958 (29%) features were differentially expressed, with the mid-stationary phase timepoint demonstrating peak changes in expression. Gene ontology enrichment analyses identified a significant shift in transcripts involved in energy acquisition, ribosome biogenesis, gene expression, stress adaptation, calcium signaling, and putative brevetoxin biosynthesis. The extensive remodeling of the transcriptome observed in the transition into a quiescent non-dividing phase appears to be indicative of a global shift in the metabolic and signaling requirements and provides the basis from which to understand the process of chronological aging in a dinoflagellate. Published by Elsevier B.V.

Genes misregulated in C. elegans deficient in Dicer, RDE-4, or RDE-1 are enriched for innate immunity genes.

PubMed

Welker, Noah C; Habig, Jeffrey W; Bass, Brenda L

2007-07-01

We describe the first microarray analysis of a whole animal containing a mutation in the Dicer gene. We used adult Caenorhabditis elegans and, to distinguish among different roles of Dicer, we also performed microarray analyses of animals with mutations in rde-4 and rde-1, which are involved in silencing by siRNA, but not miRNA. Surprisingly, we find that the X chromosome is greatly enriched for genes regulated by Dicer. Comparison of all three microarray data sets indicates the majority of Dicer-regulated genes are not dependent on RDE-4 or RDE-1, including the X-linked genes. However, all three data sets are enriched in genes important for innate immunity and, specifically, show increased expression of innate immunity genes.

Genes misregulated in C. elegans deficient in Dicer, RDE-4, or RDE-1 are enriched for innate immunity genes

PubMed Central

Welker, Noah C.; Habig, Jeffrey W.; Bass, Brenda L.

2007-01-01

We describe the first microarray analysis of a whole animal containing a mutation in the Dicer gene. We used adult Caenorhabditis elegans and, to distinguish among different roles of Dicer, we also performed microarray analyses of animals with mutations in rde-4 and rde-1, which are involved in silencing by siRNA, but not miRNA. Surprisingly, we find that the X chromosome is greatly enriched for genes regulated by Dicer. Comparison of all three microarray data sets indicates the majority of Dicer-regulated genes are not dependent on RDE-4 or RDE-1, including the X-linked genes. However, all three data sets are enriched in genes important for innate immunity and, specifically, show increased expression of innate immunity genes. PMID:17526642

Identifying pathogenic processes by integrating microarray data with prior knowledge

PubMed Central

2014-01-01

Background It is of great importance to identify molecular processes and pathways that are involved in disease etiology. Although there has been an extensive use of various high-throughput methods for this task, pathogenic pathways are still not completely understood. Often the set of genes or proteins identified as altered in genome-wide screens show a poor overlap with canonical disease pathways. These findings are difficult to interpret, yet crucial in order to improve the understanding of the molecular processes underlying the disease progression. We present a novel method for identifying groups of connected molecules from a set of differentially expressed genes. These groups represent functional modules sharing common cellular function and involve signaling and regulatory events. Specifically, our method makes use of Bayesian statistics to identify groups of co-regulated genes based on the microarray data, where external information about molecular interactions and connections are used as priors in the group assignments. Markov chain Monte Carlo sampling is used to search for the most reliable grouping. Results Simulation results showed that the method improved the ability of identifying correct groups compared to traditional clustering, especially for small sample sizes. Applied to a microarray heart failure dataset the method found one large cluster with several genes important for the structure of the extracellular matrix and a smaller group with many genes involved in carbohydrate metabolism. The method was also applied to a microarray dataset on melanoma cancer patients with or without metastasis, where the main cluster was dominated by genes related to keratinocyte differentiation. Conclusion Our method found clusters overlapping with known pathogenic processes, but also pointed to new connections extending beyond the classical pathways. PMID:24758699

Uncovering the cellular and molecular changes in tendon stem/progenitor cells attributed to tendon aging and degeneration.

PubMed

Kohler, Julia; Popov, Cvetan; Klotz, Barbara; Alberton, Paolo; Prall, Wolf Christian; Haasters, Florian; Müller-Deubert, Sigrid; Ebert, Regina; Klein-Hitpass, Ludger; Jakob, Franz; Schieker, Matthias; Docheva, Denitsa

2013-12-01

Although the link between altered stem cell properties and tissue aging has been recognized, the molecular and cellular processes of tendon aging have not been elucidated. As tendons contain stem/progenitor cells (TSPC), we investigated whether the molecular and cellular attributes of TSPC alter during tendon aging and degeneration. Comparing TSPC derived from young/healthy (Y-TSPC) and aged/degenerated human Achilles tendon biopsies (A-TSPC), we observed that A-TSPC exhibit a profound self-renewal and clonogenic deficits, while their multipotency was still retained. Senescence analysis showed a premature entry into senescence of the A-TSPC, a finding accompanied by an upregulation of p16(INK4A). To identify age-related molecular factors, we performed microarray and gene ontology analyses. These analyses revealed an intriguing transcriptomal shift in A-TSPC, where the most differentially expressed probesets encode for genes regulating cell adhesion, migration, and actin cytoskeleton. Time-lapse analysis showed that A-TSPC exhibit decelerated motion and delayed wound closure concomitant to a higher actin stress fiber content and a slower turnover of actin filaments. Lastly, based on the expression analyses of microarray candidates, we suggest that dysregulated cell-matrix interactions and the ROCK kinase pathway might be key players in TSPC aging. Taken together, we propose that during tendon aging and degeneration, the TSPC pool is becoming exhausted in terms of size and functional fitness. Thus, our study provides the first fundamental basis for further exploration into the molecular mechanisms behind tendon aging and degeneration as well as for the selection of novel tendon-specific therapeutical targets. © 2013 The Authors. Aging Cell published by the Anatomical Society and John Wiley & Sons Ltd.

Developing an Efficient and General Strategy for Immobilization of Small Molecules onto Microarrays Using Isocyanate Chemistry.

PubMed

Zhu, Chenggang; Zhu, Xiangdong; Landry, James P; Cui, Zhaomeng; Li, Quanfu; Dang, Yongjun; Mi, Lan; Zheng, Fengyun; Fei, Yiyan

2016-03-16

Small-molecule microarray (SMM) is an effective platform for identifying lead compounds from large collections of small molecules in drug discovery, and efficient immobilization of molecular compounds is a pre-requisite for the success of such a platform. On an isocyanate functionalized surface, we studied the dependence of immobilization efficiency on chemical residues on molecular compounds, terminal residues on isocyanate functionalized surface, lengths of spacer molecules, and post-printing treatment conditions, and we identified a set of optimized conditions that enable us to immobilize small molecules with significantly improved efficiencies, particularly for those molecules with carboxylic acid residues that are known to have low isocyanate reactivity. We fabricated microarrays of 3375 bioactive compounds on isocyanate functionalized glass slides under these optimized conditions and confirmed that immobilization percentage is over 73%.

Systematic analysis of microarray datasets to identify Parkinson's disease‑associated pathways and genes.

PubMed

Feng, Yinling; Wang, Xuefeng

2017-03-01

In order to investigate commonly disturbed genes and pathways in various brain regions of patients with Parkinson's disease (PD), microarray datasets from previous studies were collected and systematically analyzed. Different normalization methods were applied to microarray datasets from different platforms. A strategy combining gene co‑expression networks and clinical information was adopted, using weighted gene co‑expression network analysis (WGCNA) to screen for commonly disturbed genes in different brain regions of patients with PD. Functional enrichment analysis of commonly disturbed genes was performed using the Database for Annotation, Visualization, and Integrated Discovery (DAVID). Co‑pathway relationships were identified with Pearson's correlation coefficient tests and a hypergeometric distribution‑based test. Common genes in pathway pairs were selected out and regarded as risk genes. A total of 17 microarray datasets from 7 platforms were retained for further analysis. Five gene coexpression modules were identified, containing 9,745, 736, 233, 101 and 93 genes, respectively. One module was significantly correlated with PD samples and thus the 736 genes it contained were considered to be candidate PD‑associated genes. Functional enrichment analysis demonstrated that these genes were implicated in oxidative phosphorylation and PD. A total of 44 pathway pairs and 52 risk genes were revealed, and a risk gene pathway relationship network was constructed. Eight modules were identified and were revealed to be associated with PD, cancers and metabolism. A number of disturbed pathways and risk genes were unveiled in PD, and these findings may help advance understanding of PD pathogenesis.

Differential Expression and Functional Analysis of High-Throughput -Omics Data Using Open Source Tools.

PubMed

Kebschull, Moritz; Fittler, Melanie Julia; Demmer, Ryan T; Papapanou, Panos N

2017-01-01

Today, -omics analyses, including the systematic cataloging of messenger RNA and microRNA sequences or DNA methylation patterns in a cell population, organ, or tissue sample, allow for an unbiased, comprehensive genome-level analysis of complex diseases, offering a large advantage over earlier "candidate" gene or pathway analyses. A primary goal in the analysis of these high-throughput assays is the detection of those features among several thousand that differ between different groups of samples. In the context of oral biology, our group has successfully utilized -omics technology to identify key molecules and pathways in different diagnostic entities of periodontal disease.A major issue when inferring biological information from high-throughput -omics studies is the fact that the sheer volume of high-dimensional data generated by contemporary technology is not appropriately analyzed using common statistical methods employed in the biomedical sciences.In this chapter, we outline a robust and well-accepted bioinformatics workflow for the initial analysis of -omics data generated using microarrays or next-generation sequencing technology using open-source tools. Starting with quality control measures and necessary preprocessing steps for data originating from different -omics technologies, we next outline a differential expression analysis pipeline that can be used for data from both microarray and sequencing experiments, and offers the possibility to account for random or fixed effects. Finally, we present an overview of the possibilities for a functional analysis of the obtained data.

Comparative genomics in chicken and Pekin duck using FISH mapping and microarray analysis

PubMed Central

2009-01-01

Background The availability of the complete chicken (Gallus gallus) genome sequence as well as a large number of chicken probes for fluorescent in-situ hybridization (FISH) and microarray resources facilitate comparative genomic studies between chicken and other bird species. In a previous study, we provided a comprehensive cytogenetic map for the turkey (Meleagris gallopavo) and the first analysis of copy number variants (CNVs) in birds. Here, we extend this approach to the Pekin duck (Anas platyrhynchos), an obvious target for comparative genomic studies due to its agricultural importance and resistance to avian flu. Results We provide a detailed molecular cytogenetic map of the duck genome through FISH assignment of 155 chicken clones. We identified one inter- and six intrachromosomal rearrangements between chicken and duck macrochromosomes and demonstrated conserved synteny among all microchromosomes analysed. Array comparative genomic hybridisation revealed 32 CNVs, of which 5 overlap previously designated "hotspot" regions between chicken and turkey. Conclusion Our results suggest extensive conservation of avian genomes across 90 million years of evolution in both macro- and microchromosomes. The data on CNVs between chicken and duck extends previous analyses in chicken and turkey and supports the hypotheses that avian genomes contain fewer CNVs than mammalian genomes and that genomes of evolutionarily distant species share regions of copy number variation ("CNV hotspots"). Our results will expedite duck genomics, assist marker development and highlight areas of interest for future evolutionary and functional studies. PMID:19656363

Surviving the cold: molecular analyses of insect cryoprotective dehydration in the Arctic springtail Megaphorura arctica (Tullberg)

PubMed Central

Clark, Melody S; Thorne, Michael AS; Purać, Jelena; Burns, Gavin; Hillyard, Guy; Popović, Željko D; Grubor-Lajšić, Gordana; Worland, M Roger

2009-01-01

Background Insects provide tractable models for enhancing our understanding of the physiological and cellular processes that enable survival at extreme low temperatures. They possess three main strategies to survive the cold: freeze tolerance, freeze avoidance or cryoprotective dehydration, of which the latter method is exploited by our model species, the Arctic springtail Megaphorura arctica, formerly Onychiurus arcticus (Tullberg 1876). The physiological mechanisms underlying cryoprotective dehydration have been well characterised in M. arctica and to date this process has been described in only a few other species: the Antarctic nematode Panagrolaimus davidi, an enchytraied worm, the larvae of the Antarctic midge Belgica antarctica and the cocoons of the earthworm Dendrobaena octaedra. There are no in-depth molecular studies on the underlying cold survival mechanisms in any species. Results A cDNA microarray was generated using 6,912 M. arctica clones printed in duplicate. Analysis of clones up-regulated during dehydration procedures (using both cold- and salt-induced dehydration) has identified a number of significant cellular processes, namely the production and mobilisation of trehalose, protection of cellular systems via small heat shock proteins and tissue/cellular remodelling during the dehydration process. Energy production, initiation of protein translation and cell division, plus potential tissue repair processes dominate genes identified during recovery. Heat map analysis identified a duplication of the trehalose-6-phosphate synthase (TPS) gene in M. arctica and also 53 clones co-regulated with TPS, including a number of membrane associated and cell signalling proteins. Q-PCR on selected candidate genes has also contributed to our understanding with glutathione-S-transferase identified as the major antioxdidant enzyme protecting the cells during these stressful procedures, and a number of protein kinase signalling molecules involved in recovery. Conclusion Microarray analysis has proved to be a powerful technique for understanding the processes and genes involved in cryoprotective dehydration, beyond the few candidate genes identified in the current literature. Dehydration is associated with the mobilisation of trehalose, cell protection and tissue remodelling. Energy production, leading to protein production, and cell division characterise the recovery process. Novel membrane proteins, along with aquaporins and desaturases, have been identified as promising candidates for future functional analyses to better understand membrane remodelling during cellular dehydration. PMID:19622137

Systematic spatial bias in DNA microarray hybridization is caused by probe spot position-dependent variability in lateral diffusion.

PubMed

Steger, Doris; Berry, David; Haider, Susanne; Horn, Matthias; Wagner, Michael; Stocker, Roman; Loy, Alexander

2011-01-01

The hybridization of nucleic acid targets with surface-immobilized probes is a widely used assay for the parallel detection of multiple targets in medical and biological research. Despite its widespread application, DNA microarray technology still suffers from several biases and lack of reproducibility, stemming in part from an incomplete understanding of the processes governing surface hybridization. In particular, non-random spatial variations within individual microarray hybridizations are often observed, but the mechanisms underpinning this positional bias remain incompletely explained. This study identifies and rationalizes a systematic spatial bias in the intensity of surface hybridization, characterized by markedly increased signal intensity of spots located at the boundaries of the spotted areas of the microarray slide. Combining observations from a simplified single-probe block array format with predictions from a mathematical model, the mechanism responsible for this bias is found to be a position-dependent variation in lateral diffusion of target molecules. Numerical simulations reveal a strong influence of microarray well geometry on the spatial bias. Reciprocal adjustment of the size of the microarray hybridization chamber to the area of surface-bound probes is a simple and effective measure to minimize or eliminate the diffusion-based bias, resulting in increased uniformity and accuracy of quantitative DNA microarray hybridization.

Systematic Spatial Bias in DNA Microarray Hybridization Is Caused by Probe Spot Position-Dependent Variability in Lateral Diffusion

PubMed Central

Haider, Susanne; Horn, Matthias; Wagner, Michael; Stocker, Roman; Loy, Alexander

2011-01-01

Background The hybridization of nucleic acid targets with surface-immobilized probes is a widely used assay for the parallel detection of multiple targets in medical and biological research. Despite its widespread application, DNA microarray technology still suffers from several biases and lack of reproducibility, stemming in part from an incomplete understanding of the processes governing surface hybridization. In particular, non-random spatial variations within individual microarray hybridizations are often observed, but the mechanisms underpinning this positional bias remain incompletely explained. Methodology/Principal Findings This study identifies and rationalizes a systematic spatial bias in the intensity of surface hybridization, characterized by markedly increased signal intensity of spots located at the boundaries of the spotted areas of the microarray slide. Combining observations from a simplified single-probe block array format with predictions from a mathematical model, the mechanism responsible for this bias is found to be a position-dependent variation in lateral diffusion of target molecules. Numerical simulations reveal a strong influence of microarray well geometry on the spatial bias. Conclusions Reciprocal adjustment of the size of the microarray hybridization chamber to the area of surface-bound probes is a simple and effective measure to minimize or eliminate the diffusion-based bias, resulting in increased uniformity and accuracy of quantitative DNA microarray hybridization. PMID:21858215

Crossword: A Fully Automated Algorithm for the Segmentation and Quality Control of Protein Microarray Images

PubMed Central

2015-01-01

Biological assays formatted as microarrays have become a critical tool for the generation of the comprehensive data sets required for systems-level understanding of biological processes. Manual annotation of data extracted from images of microarrays, however, remains a significant bottleneck, particularly for protein microarrays due to the sensitivity of this technology to weak artifact signal. In order to automate the extraction and curation of data from protein microarrays, we describe an algorithm called Crossword that logically combines information from multiple approaches to fully automate microarray segmentation. Automated artifact removal is also accomplished by segregating structured pixels from the background noise using iterative clustering and pixel connectivity. Correlation of the location of structured pixels across image channels is used to identify and remove artifact pixels from the image prior to data extraction. This component improves the accuracy of data sets while reducing the requirement for time-consuming visual inspection of the data. Crossword enables a fully automated protocol that is robust to significant spatial and intensity aberrations. Overall, the average amount of user intervention is reduced by an order of magnitude and the data quality is increased through artifact removal and reduced user variability. The increase in throughput should aid the further implementation of microarray technologies in clinical studies. PMID:24417579

A DNA microarray-based assay to detect dual infection with two dengue virus serotypes.

PubMed

Díaz-Badillo, Alvaro; Muñoz, María de Lourdes; Perez-Ramirez, Gerardo; Altuzar, Victor; Burgueño, Juan; Mendoza-Alvarez, Julio G; Martínez-Muñoz, Jorge P; Cisneros, Alejandro; Navarrete-Espinosa, Joel; Sanchez-Sinencio, Feliciano

2014-04-25

Here; we have described and tested a microarray based-method for the screening of dengue virus (DENV) serotypes. This DNA microarray assay is specific and sensitive and can detect dual infections with two dengue virus serotypes and single-serotype infections. Other methodologies may underestimate samples containing more than one serotype. This technology can be used to discriminate between the four DENV serotypes. Single-stranded DNA targets were covalently attached to glass slides and hybridised with specific labelled probes. DENV isolates and dengue samples were used to evaluate microarray performance. Our results demonstrate that the probes hybridized specifically to DENV serotypes; with no detection of unspecific signals. This finding provides evidence that specific probes can effectively identify single and double infections in DENV samples.

A DNA Microarray-Based Assay to Detect Dual Infection with Two Dengue Virus Serotypes

PubMed Central

Díaz-Badillo, Alvaro; de Lourdes Muñoz, María; Perez-Ramirez, Gerardo; Altuzar, Victor; Burgueño, Juan; Mendoza-Alvarez, Julio G.; Martínez-Muñoz, Jorge P.; Cisneros, Alejandro; Navarrete-Espinosa, Joel; Sanchez-Sinencio, Feliciano

2014-01-01

Here; we have described and tested a microarray based-method for the screening of dengue virus (DENV) serotypes. This DNA microarray assay is specific and sensitive and can detect dual infections with two dengue virus serotypes and single-serotype infections. Other methodologies may underestimate samples containing more than one serotype. This technology can be used to discriminate between the four DENV serotypes. Single-stranded DNA targets were covalently attached to glass slides and hybridised with specific labelled probes. DENV isolates and dengue samples were used to evaluate microarray performance. Our results demonstrate that the probes hybridized specifically to DENV serotypes; with no detection of unspecific signals. This finding provides evidence that specific probes can effectively identify single and double infections in DENV samples. PMID:24776933

STARNET 2: a web-based tool for accelerating discovery of gene regulatory networks using microarray co-expression data

PubMed Central

Jupiter, Daniel; Chen, Hailin; VanBuren, Vincent

2009-01-01

Background Although expression microarrays have become a standard tool used by biologists, analysis of data produced by microarray experiments may still present challenges. Comparison of data from different platforms, organisms, and labs may involve complicated data processing, and inferring relationships between genes remains difficult. Results STARNET 2 is a new web-based tool that allows post hoc visual analysis of correlations that are derived from expression microarray data. STARNET 2 facilitates user discovery of putative gene regulatory networks in a variety of species (human, rat, mouse, chicken, zebrafish, Drosophila, C. elegans, S. cerevisiae, Arabidopsis and rice) by graphing networks of genes that are closely co-expressed across a large heterogeneous set of preselected microarray experiments. For each of the represented organisms, raw microarray data were retrieved from NCBI's Gene Expression Omnibus for a selected Affymetrix platform. All pairwise Pearson correlation coefficients were computed for expression profiles measured on each platform, respectively. These precompiled results were stored in a MySQL database, and supplemented by additional data retrieved from NCBI. A web-based tool allows user-specified queries of the database, centered at a gene of interest. The result of a query includes graphs of correlation networks, graphs of known interactions involving genes and gene products that are present in the correlation networks, and initial statistical analyses. Two analyses may be performed in parallel to compare networks, which is facilitated by the new HEATSEEKER module. Conclusion STARNET 2 is a useful tool for developing new hypotheses about regulatory relationships between genes and gene products, and has coverage for 10 species. Interpretation of the correlation networks is supported with a database of previously documented interactions, a test for enrichment of Gene Ontology terms, and heat maps of correlation distances that may be used to compare two networks. The list of genes in a STARNET network may be useful in developing a list of candidate genes to use for the inference of causal networks. The tool is freely available at , and does not require user registration. PMID:19828039

Differences of RNA Expression in the Tendon According to Anatomic Outcomes in Rotator Cuff Repair.

PubMed

Ahn, Jin-Ok; Chung, Jin-Young; Kim, Do Hoon; Im, Wooseok; Kim, Sae Hoon

2017-11-01

Despite increased understanding of the pathophysiology of rotator cuff tears and the evolution of rotator cuff repair, healing failure remains a substantial problem. The critical roles played by biological factors have been emphasized, but little is known of the implications of gene expression profile differences at the time of repair. To document the relationship between the perioperative gene expression of healed and unhealed rotator cuffs by RNA microarray analysis. Case-control study; Level of evidence, 3. Superior (supraspinatus involvement) and posterosuperior (supraspinatus and infraspinatus involvement) tears were included in the study. Samples of rotator cuff tendons were prospectively collected during rotator cuff surgery. Three samples were harvested at the tendon ends of tears from the anterior, middle (apex), and posterior parts using an arthroscopic punch. Seven patients with an unhealed rotator cuff were matched one-to-one with patients with a healed rotator cuff by sex, age, tear size, and fatty degeneration of rotator cuff muscles. mRNA microarray analysis was used to identify genetic differences between healed and unhealed rotator cuff tendons. Gene ontology and gene association files were obtained from the Gene Ontology Consortium, and the Gene Ontology system in DAVID was used to identify enhanced biological processes. Microarray analyses identified 262 genes that were differentially expressed by at least 1.5-fold between the healed and unhealed groups. Overall, in the healed group, 103 genes were significantly downregulated, and 159 were significantly upregulated. DAVID Functional Annotation Cluster analysis showed that in the healed group, the genes most upregulated were related to the G protein-coupled receptor protein signaling pathway and to the neurological system. On the other hand, the genes most downregulated were related to immune and inflammatory responses. BMP5 was the gene most upregulated in the healed group, and the majority of downregulated genes were involved in the immune/inflammatory response. The downregulation of inflammatory response genes and the upregulation of cell differentiation genes in torn rotator cuffs at the time of surgery are related to rotator cuff healing. These results provide useful baseline information for future biological studies on rotator cuff healing.

Microarray-based screening of differentially expressed genes in glucocorticoid-induced avascular necrosis

PubMed Central

Huang, Gangyong; Wei, Yibing; Zhao, Guanglei; Xia, Jun; Wang, Siqun; Wu, Jianguo; Chen, Feiyan; Chen, Jie; Shi, Jingshen

2017-01-01

The underlying mechanisms of glucocorticoid (GC)-induced avascular necrosis of the femoral head (ANFH) have yet to be fully understood, in particular the mechanisms associated with the change of gene expression pattern. The present study aimed to identify key genes with a differential expression pattern in GC-induced ANFH. E-MEXP-2751 microarray data were downloaded from the ArrayExpress database. Differentially expressed genes (DEGs) were identified in 5 femoral head samples of steroid-induced ANFH rats compared with 5 placebo-treated rat samples. Gene Ontology (GO) and pathway enrichment analyses were performed upon these DEGs. A total 93 DEGs (46 upregulated and 47 downregulated genes) were identified in GC-induced ANFH samples. These DEGs were enriched in different GO terms and pathways, including chondrocyte differentiation and detection of chemical stimuli. The enrichment map revealed that skeletal system development was interconnected with several other GO terms by gene overlap. The literature mined network analysis revealed that 5 upregulated genes were associated with femoral necrosis, including parathyroid hormone receptor 1 (PTHR1), vitamin D (1,25-Dihydroxyvitamin D3) receptor (VDR), collagen, type II, α1, proprotein convertase subtilisin/kexin type 6 and zinc finger protein 354C (ZFP354C). In addition, ZFP354C and VDR were identified to transcription factors. Furthermore, PTHR1 was revealed to interact with VDR, and α-2-macroglobulin (A2M) interacted with fibronectin 1 (FN1) in the PPI network. PTHR1 may be involved in GC-induced ANFH via interacting with VDR. A2M may also be involved in the development of GC-induced ANFH through interacting with FN1. An improved understanding of the molecular mechanisms underlying GC-induced ANFH may provide novel targets for diagnostics and therapeutic treatment. PMID:28393228

From genomes to vaccines: Leishmania as a model.

PubMed Central

Almeida, Renata; Norrish, Alan; Levick, Mark; Vetrie, David; Freeman, Tom; Vilo, Jaak; Ivens, Alasdair; Lange, Uta; Stober, Carmel; McCann, Sharon; Blackwell, Jenefer M

2002-01-01

The 35 Mb genome of Leishmania should be sequenced by late 2002. It contains approximately 8500 genes that will probably translate into more than 10 000 proteins. In the laboratory we have been piloting strategies to try to harness the power of the genome-proteome for rapid screening of new vaccine candidate. To this end, microarray analysis of 1094 unique genes identified using an EST analysis of 2091 cDNA clones from spliced leader libraries prepared from different developmental stages of Leishmania has been employed. The plan was to identify amastigote-expressed genes that could be used in high-throughput DNA-vaccine screens to identify potential new vaccine candidates. Despite the lack of transcriptional regulation that polycistronic transcription in Leishmania dictates, the data provide evidence for a high level of post-transcriptional regulation of RNA abundance during the developmental cycle of promastigotes in culture and in lesion-derived amastigotes of Leishmania major. This has provided 147 candidates from the 1094 unique genes that are specifically upregulated in amastigotes and are being used in vaccine studies. Using DNA vaccination, it was demonstrated that pooling strategies can work to identify protective vaccines, but it was found that some potentially protective antigens are masked by other disease-exacerbatory antigens in the pool. A total of 100 new vaccine candidates are currently being tested separately and in pools to extend this analysis, and to facilitate retrospective bioinformatic analysis to develop predictive algorithms for sequences that constitute potentially protective antigens. We are also working with other members of the Leishmania Genome Network to determine whether RNA expression determined by microarray analyses parallels expression at the protein level. We believe we are making good progress in developing strategies that will allow rapid translation of the sequence of Leishmania into potential interventions for disease control in humans. PMID:11839176

Vaccine-associated varicella and rubella infections in severe combined immunodeficiency with isolated CD4 lymphocytopenia and mutations in IL7R detected by tandem whole exome sequencing and chromosomal microarray

PubMed Central

Bayer, D K; Martinez, C A; Sorte, H S; Forbes, L R; Demmler-Harrison, G J; Hanson, I C; Pearson, N M; Noroski, L M; Zaki, S R; Bellini, W J; Leduc, M S; Yang, Y; Eng, C M; Patel, A; Rodningen, O K; Muzny, D M; Gibbs, R A; Campbell, I M; Shaw, C A; Baker, M W; Zhang, V; Lupski, J R; Orange, J S; Seeborg, F O; Stray-Pedersen, A

2014-01-01

In areas without newborn screening for severe combined immunodeficiency (SCID), disease-defining infections may lead to diagnosis, and in some cases, may not be identified prior to the first year of life. We describe a female infant who presented with disseminated vaccine-acquired varicella (VZV) and vaccine-acquired rubella infections at 13 months of age. Immunological evaluations demonstrated neutropenia, isolated CD4 lymphocytopenia, the presence of CD8+ T cells, poor lymphocyte proliferation, hypergammaglobulinaemia and poor specific antibody production to VZV infection and routine immunizations. A combination of whole exome sequencing and custom-designed chromosomal microarray with exon coverage of primary immunodeficiency genes detected compound heterozygous mutations (one single nucleotide variant and one intragenic copy number variant involving one exon) within the IL7R gene. Mosaicism for wild-type allele (20–30%) was detected in pretransplant blood and buccal DNA and maternal engraftment (5–10%) demonstrated in pretransplant blood DNA. This may be responsible for the patient's unusual immunological phenotype compared to classical interleukin (IL)-7Rα deficiency. Disseminated VZV was controlled with anti-viral and immune-based therapy, and umbilical cord blood stem cell transplantation was successful. Retrospectively performed T cell receptor excision circle (TREC) analyses completed on neonatal Guthrie cards identified absent TREC. This case emphasizes the danger of live viral vaccination in severe combined immunodeficiency (SCID) patients and the importance of newborn screening to identify patients prior to high-risk exposures. It also illustrates the value of aggressive pathogen identification and treatment, the influence newborn screening can have on morbidity and mortality and the significant impact of newer genomic diagnostic tools in identifying the underlying genetic aetiology for SCID patients. PMID:25046553

Unique Chemokine Profiles of Lung Tissues Distinguish Post-chemotherapeutic Persistent and Chronic Tuberculosis in a Mouse Model.

PubMed

Park, Soomin; Baek, Seung-Hun; Cho, Sang-Nae; Jang, Young-Saeng; Kim, Ahreum; Choi, In-Hong

2017-01-01

There is a substantial need for biomarkers to distinguish latent stage from active Mycobacterium tuberculosis infections, for predicting disease progression. To induce the reactivation of tuberculosis, we present a new experimental animal model modified based on the previous model established by our group. In the new model, the reactivation of tuberculosis is induced without administration of immunosuppressive agents, which might disturb immune responses. To identify the immunological status of the persistent and chronic stages, we analyzed immunological genes in lung tissues from mice infected with M. tuberculosis . Gene expression was screened using cDNA microarray analysis and confirmed by quantitative RT-PCR. Based on the cDNA microarray results, 11 candidate cytokines genes, which were obviously up-regulated during the chronic stage compared with those during the persistent stage, were selected and clustered into three groups: (1) chemokine genes, except those of monocyte chemoattractant proteins (MCPs; CXCL9, CXCL10, CXCL11, CCL5, CCL19); (2) MCP genes (CCL2, CCL7, CCL8, CCL12); and (3) TNF and IFN-γ genes. Results from the cDNA microarray and quantitative RT-PCR analyses revealed that the mRNA expression of the selected cytokine genes was significantly higher in lung tissues of the chronic stage than of the persistent stage. Three chemokines (CCL5, CCL19, and CXCL9) and three MCPs (CCL7, CCL2, and CCL12) were noticeably increased in the chronic stage compared with the persistent stage by cDNA microarray ( p < 0.01, except CCL12) or RT-PCR ( p < 0.01). Therefore, these six significantly increased cytokines in lung tissue from the mouse tuberculosis model might be candidates for biomarkers to distinguish the two disease stages. This information can be combined with already reported potential biomarkers to construct a network of more efficient tuberculosis markers.

Plasma long noncoding RNA expression profile identified by microarray in patients with Crohn's disease.

PubMed

Chen, Dong; Liu, Jiang; Zhao, Hui-Ying; Chen, Yi-Peng; Xiang, Zun; Jin, Xi

2016-05-21

To investigate the expression pattern of plasma long noncoding RNAs (lncRNAs) in Chrohn's disease (CD) patients. Microarray screening and qRT-PCR verification of lncRNAs and mRNAs were performed in CD and control subjects, followed by hierarchy clustering, GO and KEGG pathway analyses. Significantly dysregulated lncRNAs were categorized into subgroups of antisense lncRNAs, enhancer lncRNAs and lincRNAs. To predict the regulatory effect of lncRNAs on mRNAs, a CNC network analysis was performed and cross linked with significantly changed lncRNAs. The overlapping lncRNAs were randomly selected and verified by qRT-PCR in a larger cohort. Initially, there were 1211 up-regulated and 777 down-regulated lncRNAs as well as 1020 up-regulated and 953 down-regulated mRNAs after microarray analysis; a heat map based on these results showed good categorization into the CD and control groups. GUSBP2 and AF113016 had the highest fold change of the up- and down-regulated lncRNAs, whereas TBC1D17 and CCL3L3 had the highest fold change of the up- and down-regulated mRNAs. Six (SNX1, CYFIP2, CD6, CMTM8, STAT4 and IGFBP7) of 10 mRNAs and 8 (NR_033913, NR_038218, NR_036512, NR_049759, NR_033951, NR_045408, NR_038377 and NR_039976) of 14 lncRNAs showed the same change trends on the microarray and qRT-PCR results with statistical significance. Based on the qRT-PCR verified mRNAs, 1358 potential lncRNAs with 2697 positive correlations and 2287 negative correlations were predicted by the CNC network. The plasma lncRNAs profiles provide preliminary data for the non-invasive diagnosis of CD and a resource for further specific lncRNA-mRNA pathway exploration.

Using microarrays to identify positional candidate genes for QTL: the case study of ACTH response in pigs.

PubMed

Jouffe, Vincent; Rowe, Suzanne; Liaubet, Laurence; Buitenhuis, Bart; Hornshøj, Henrik; SanCristobal, Magali; Mormède, Pierre; de Koning, D J

2009-07-16

Microarray studies can supplement QTL studies by suggesting potential candidate genes in the QTL regions, which by themselves are too large to provide a limited selection of candidate genes. Here we provide a case study where we explore ways to integrate QTL data and microarray data for the pig, which has only a partial genome sequence. We outline various procedures to localize differentially expressed genes on the pig genome and link this with information on published QTL. The starting point is a set of 237 differentially expressed cDNA clones in adrenal tissue from two pig breeds, before and after treatment with adrenocorticotropic hormone (ACTH). Different approaches to localize the differentially expressed (DE) genes to the pig genome showed different levels of success and a clear lack of concordance for some genes between the various approaches. For a focused analysis on 12 genes, overlapping QTL from the public domain were presented. Also, differentially expressed genes underlying QTL for ACTH response were described. Using the latest version of the draft sequence, the differentially expressed genes were mapped to the pig genome. This enabled co-location of DE genes and previously studied QTL regions, but the draft genome sequence is still incomplete and will contain many errors. A further step to explore links between DE genes and QTL at the pathway level was largely unsuccessful due to the lack of annotation of the pig genome. This could be improved by further comparative mapping analyses but this would be time consuming. This paper provides a case study for the integration of QTL data and microarray data for a species with limited genome sequence information and annotation. The results illustrate the challenges that must be addressed but also provide a roadmap for future work that is applicable to other non-model species.

LncRNA-FEZF1-AS1 promotes tumor proliferation and metastasis in colorectal cancer by regulating PKM2 signaling.

PubMed

Bian, Zehua; Zhang, Jiwei; Li, Min; Feng, Yuyang; Wang, Xue; Zhang, Jia; Yao, Surui; Jin, Guoying; Du, Jun; Han, Weifeng; Yin, Yuan; Huang, Shenglin; Fei, Bojian; Zou, Jian; Huang, Zhaohui

2018-06-18

Long non-coding RNAs (lncRNAs) play key roles in human cancers. Here, FEZF1-AS1, a highly overexpressed lncRNA in colorectal cancer (CRC), was identified by lncRNA microarrays. We aimed to explore the roles and possible molecular mechanisms of FEZF1-AS1 in CRC. LncRNA expression in CRC tissues was measured by lncRNA microarray and qRT-PCR. The functional roles of FEZF1-AS1 in CRC were demonstrated by a series of in vitro and in vivo experiments. RNA pull-down, RNA immunoprecipitation and luciferase analyses were used to demonstrate the potential mechanisms of FEZF1-AS1. We identified a series of differentially expressed lncRNAs in CRC using lncRNA microarrays, and revealed that FEZF1-AS1 is one of the most overexpressed. Further validation in two expanded CRC cohorts confirmed the upregulation of FEZF1-AS1 in CRC, and revealed that increased FEZF1-AS1 expression is associated with poor survival. Functional assays revealed that FEZF1-AS1 promotes CRC cell proliferation and metastasis. Mechanistically, FEZF1-AS1 could bind and increase the stability of the pyruvate kinase 2 (PKM2) protein, resulting in increased cytoplasmic and nuclear PKM2 levels. Increased cytoplasmic PKM2 promoted pyruvate kinase activity and lactate production (aerobic glycolysis), whereas FEZF1-AS1-induced nuclear PKM2 upregulation further activated STAT3 signaling. In addition, PKM2 was upregulated in CRC tissues and correlated with FEZF1-AS1 expression and patient survival. Together, these data provide mechanistic insights into the regulation of FEZF1-AS1 on both STAT3 signaling and glycolysis by binding PKM2 and increasing its stability. Copyright ©2018, American Association for Cancer Research.

A western-style diet, with and without chronic androgen treatment, alters the number, structure and function of small antral follicles in ovaries of young adult monkeys

PubMed Central

Bishop, Cecily V.; Xu, Fuhua; Xu, Jing; Ting, Alison Y.; Galbreath, Etienne; McGee, Whitney K.; Zelinski, Mary B.; Hennebold, Jon D.; Cameron, Judy L.; Stouffer, Richard L.

2015-01-01

Objective To examine the small antral follicle (SAF) cohort in ovaries of adult rhesus monkeys following consumption of a western-style diet (WSD), with or without chronically elevated androgen levels since before puberty. Design Cholesterol or testosterone (T; n=6/group) implants were placed subcutaneously in female rhesus macaques beginning at 1 yr of age (pre-pubertal), with addition of a WSD (high fat/fructose) at 5.5 yrs (menarche ~2.6 yrs). Ovaries were collected at 7 yrs of age. One ovary/female was embedded in paraffin for morphological and immunohistochemical analyses. The SAFs (<2.5mm) were dissected from the other ovary obtained at/near menses in a subgroup of females (n=3/group), and processed for microarray analyses of the SAF transcriptome. Ovaries of adult monkeys consuming a standard macaque diet (low in fats and sugars) were obtained at similar stages of the menstrual cycle and used as controls for all analyses. Setting National primate research center Animals Adult, female rhesus monkeys (Macaca mulatta) Interventions None Main outcome measures Histological analyses, SAF counts and morphology, protein localization and abundance in SAFs, transcriptome in SAFs (mRNAs) Results Compared to controls, consumption of a WSD, with and without T treatment, increased the numbers of SAFs per ovary, due to the presence of more atretic follicles. Numbers of granulosa cells expressing cellular proliferation markers (pRb and pH3) was greater in healthy SAFs, while numbers of cells expressing the cell cycle inhibitor (p21) was higher in atretic SAFs. Intense CYP17A1 staining was observed in the theca cells of SAFs from WSD+/− T groups, compared to controls. Microarray analyses of the transcriptome in SAFs isolated from WSD and WSD+T treated females and controls consuming a standard diet, identified 1944 genes whose mRNA levels changed ≥2-fold among the three groups. Further analyses identified several gene pathways altered by WSD and/or WSD+T associated with steroid, carbohydrate and lipid metabolism, plus ovarian processes. Alterations in levels of several SAF mRNAs are similar to those observed in follicular cells from women with polycystic ovary syndrome (PCOS). Conclusion These data indicate that consumption of a WSD high in fats and sugars in the presence and absence of chronically elevated T alters the structure and function of SAFs within primate ovaries. PMID:26718060

Transcription Factor Binding Site Enrichment Analysis in Co-Expression Modules in Celiac Disease

PubMed Central

Romero-Garmendia, Irati; Jauregi-Miguel, Amaia; Plaza-Izurieta, Leticia; Cros, Marie-Pierre; Legarda, Maria; Irastorza, Iñaki; Herceg, Zdenko; Fernandez-Jimenez, Nora

2018-01-01

The aim of this study was to construct celiac co-expression patterns at a whole genome level and to identify transcription factors (TFs) that could drive the gliadin-related changes in coordination of gene expression observed in celiac disease (CD). Differential co-expression modules were identified in the acute and chronic responses to gliadin using expression data from a previous microarray study in duodenal biopsies. Transcription factor binding site (TFBS) and Gene Ontology (GO) annotation enrichment analyses were performed in differentially co-expressed genes (DCGs) and selection of candidate regulators was performed. Expression of candidates was measured in clinical samples and the activation of the TFs was further characterized in C2BBe1 cells upon gliadin challenge. Enrichment analyses of the DCGs identified 10 TFs and five were selected for further investigation. Expression changes related to active CD were detected in four TFs, as well as in several of their in silico predicted targets. The activation of TFs was further characterized in C2BBe1 cells upon gliadin challenge, and an increase in nuclear translocation of CAMP Responsive Element Binding Protein 1 (CREB1) and IFN regulatory factor-1 (IRF1) in response to gliadin was observed. Using transcriptome-wide co-expression analyses we are able to propose novel genes involved in CD pathogenesis that respond upon gliadin stimulation, also in non-celiac models. PMID:29748492

Transcription Factor Binding Site Enrichment Analysis in Co-Expression Modules in Celiac Disease.

PubMed

Romero-Garmendia, Irati; Garcia-Etxebarria, Koldo; Hernandez-Vargas, Hector; Santin, Izortze; Jauregi-Miguel, Amaia; Plaza-Izurieta, Leticia; Cros, Marie-Pierre; Legarda, Maria; Irastorza, Iñaki; Herceg, Zdenko; Fernandez-Jimenez, Nora; Bilbao, Jose Ramon

2018-05-10

The aim of this study was to construct celiac co-expression patterns at a whole genome level and to identify transcription factors (TFs) that could drive the gliadin-related changes in coordination of gene expression observed in celiac disease (CD). Differential co-expression modules were identified in the acute and chronic responses to gliadin using expression data from a previous microarray study in duodenal biopsies. Transcription factor binding site (TFBS) and Gene Ontology (GO) annotation enrichment analyses were performed in differentially co-expressed genes (DCGs) and selection of candidate regulators was performed. Expression of candidates was measured in clinical samples and the activation of the TFs was further characterized in C2BBe1 cells upon gliadin challenge. Enrichment analyses of the DCGs identified 10 TFs and five were selected for further investigation. Expression changes related to active CD were detected in four TFs, as well as in several of their in silico predicted targets. The activation of TFs was further characterized in C2BBe1 cells upon gliadin challenge, and an increase in nuclear translocation of CAMP Responsive Element Binding Protein 1 (CREB1) and IFN regulatory factor-1 (IRF1) in response to gliadin was observed. Using transcriptome-wide co-expression analyses we are able to propose novel genes involved in CD pathogenesis that respond upon gliadin stimulation, also in non-celiac models.

Characterization of microRNA profile in mammary tissue of dairy and beef breed heifers.

PubMed

Wicik, Z; Gajewska, M; Majewska, A; Walkiewicz, D; Osińska, E; Motyl, T

2016-02-01

MicroRNAs (miRNAs) are small non-coding RNAs that participate in the regulation of gene expression. Their role during mammary gland development is still largely unknown. In this study, we performed a microarray analysis to identify miRNAs associated with high mammogenic potential of the bovine mammary gland. We identified 54 significantly differentially expressed miRNAs between the mammary tissue of dairy (Holstein-Friesian, HF) and beef (Limousin, LM) postpubertal heifers. Fifty-two miRNAs had higher expression in the mammary tissue of LM heifers. The expression of the top candidate miRNAs (bta-miR-10b, bta-miR-29b, bta-miR-101, bta-miR-375, bta-miR-2285t, bta-miR-146b, bta-let7b, bta-miR-107, bta-miR-1434-3p) identified in the microarray experiment was additionally evaluated by qPCR. Enrichment analyses for targeted genes revealed that the major differences between miRNA expression in the mammary gland of HF versus LM were associated with the regulation of signalling pathways that are crucial for mammary gland development, such as TGF-beta, insulin, WNT and inflammatory pathways. Moreover, a number of genes potentially targeted by significantly differentially expressed miRNAs were associated with the activity of mammary stem cells. These data indicate that the high developmental potential of the mammary gland in dairy cattle, leading to high milk productivity, depends also on a specific miRNA expression pattern. © 2015 Blackwell Verlag GmbH.

Application of chromosome microarray analysis in patients with unexplained developmental delay/intellectual disability in South China.

PubMed

Wang, Rongyue; Lei, Tingying; Fu, Fang; Li, Ru; Jing, Xiangyi; Yang, Xin; Liu, Juan; Li, Dongzhi; Liao, Can

2018-03-26

Chromosome microarray analysis (CMA) is currently the first-tier diagnostic assay for the evaluation of developmental delay (DD) and intellectual disability (ID) with unknown etiology. Here, we present our clinical experience in implementing whole-genome high-resolution single nucleotide polymorphism (SNP) arrays to investigate 489 patients with unexplained DD/ID in whom standard karyotyping analyses showed normal karyotypes. This study aimed to assess the usefulness of CMA for clinical diagnostic testing in the Chinese population. A total of 489 children were classified into three groups: isolated DD/ID (n = 358), DD/ID with epilepsy (n = 49), and DD/ID with other structural anomalies (n = 82). We identified 126 cases (25.8%, 126/489) of pathogenic copy number variants (CNVs) by CMA, including 89 (24.9%, 89/358) with isolated DD/ID, 13 (26.5%, 13/49) with DD/ID with epilepsy, and 24 (29.3%, 24/82) with DD/ID with other structural anomalies. Among the 126 cases of pathogenic CNVs, 79 cases were identified as microdeletion/microduplication syndromes, among which 76 cases were classified as common syndromes, and 3 cases were classified as rare syndromes, including 15q24 microdeletion syndrome, Xq28 microduplication syndrome and Lowe syndrome. Additionally, there were forty-seven cases of non-syndromic pathogenic CNVs. The ABAT, FTSJ1, DYNC1H1, and SETBP1 genes were identified as DD/ID candidate genes. Our findings suggest the necessity of CMA as a routine diagnostic test for unexplained DD/ID in South China. Copyright © 2018. Published by Elsevier B.V.

Alterations in the developing testis transcriptome following embryonic vinclozolin exposure.

PubMed

Clement, Tracy M; Savenkova, Marina I; Settles, Matthew; Anway, Matthew D; Skinner, Michael K

2010-11-01

The current study investigates the direct effects of in utero vinclozolin exposure on the developing F1 generation rat testis transcriptome. Previous studies have demonstrated that exposure to vinclozolin during embryonic gonadal sex determination induces epigenetic modifications of the germ line and transgenerational adult onset disease states. Microarray analyses were performed to compare control and vinclozolin treated testis transcriptomes at embryonic days 13, 14 and 16. A total of 576 differentially expressed genes were identified and the major cellular functions and pathways associated with these altered transcripts were examined. The sets of regulated genes at the different development periods were found to be transiently altered and distinct. Categorization by major known functions of altered genes was performed. Specific cellular process and pathway analyses suggest the involvement of Wnt and calcium signaling, vascular development and epigenetic mechanisms as potential mediators of the direct F1 generation actions of vinclozolin. Copyright © 2010 Elsevier Inc. All rights reserved.

ALTERATIONS IN THE DEVELOPING TESTIS TRANSCRIPTOME FOLLOWING EMBRYONIC VINCLOZOLIN EXPOSURE

PubMed Central

Clement, Tracy M.; Savenkova, Marina I.; Settles, Matthew; Anway, Matthew D.; Skinner, Michael K.

2010-01-01

The current study investigates the direct effects of in utero vinclozolin exposure on the developing F1 generation rat testis transcriptome. Previous studies have demonstrated that exposure to vinclozolin during embryonic gonadal sex determination induces epigenetic modifications of the germ line and transgenerational adult onset disease states. Microarray analyses were performed to compare control and vinclozolin treated testis transcriptomes at embryonic day 13, 14 and 16. A total of 576 differentially expressed genes were identified and the major cellular functions and pathways associated with these altered transcripts were examined. The sets of regulated genes at the different development periods were found to be transiently altered and distinct. Categorization by major known functions of altered genes was performed. Specific cellular process and pathway analyses suggest the involvement of Wnt and calcium signaling, vascular development and epigenetic mechanisms as potential mediators of the direct F1 generation actions of vinclozolin. PMID:20566332

Separate enrichment analysis of pathways for up- and downregulated genes.

PubMed

Hong, Guini; Zhang, Wenjing; Li, Hongdong; Shen, Xiaopei; Guo, Zheng

2014-03-06

Two strategies are often adopted for enrichment analysis of pathways: the analysis of all differentially expressed (DE) genes together or the analysis of up- and downregulated genes separately. However, few studies have examined the rationales of these enrichment analysis strategies. Using both microarray and RNA-seq data, we show that gene pairs with functional links in pathways tended to have positively correlated expression levels, which could result in an imbalance between the up- and downregulated genes in particular pathways. We then show that the imbalance could greatly reduce the statistical power for finding disease-associated pathways through the analysis of all-DE genes. Further, using gene expression profiles from five types of tumours, we illustrate that the separate analysis of up- and downregulated genes could identify more pathways that are really pertinent to phenotypic difference. In conclusion, analysing up- and downregulated genes separately is more powerful than analysing all of the DE genes together.

Cambridge Healthtech Institute's Third Annual Conference on Lab-on-a-Chip and Microarrays. 22-24 January 2001, Zurich, Switzerland.

PubMed

Jain, K K

2001-02-01

Cambridge Healthtech Institute's Third Annual Conference on Lab-on-a-Chip and Microarray technology covered the latest advances in this technology and applications in life sciences. Highlights of the meetings are reported briefly with emphasis on applications in genomics, drug discovery and molecular diagnostics. There was an emphasis on microfluidics because of the wide applications in laboratory and drug discovery. The lab-on-a-chip provides the facilities of a complete laboratory in a hand-held miniature device. Several microarray systems have been used for hybridisation and detection techniques. Oligonucleotide scanning arrays provide a versatile tool for the analysis of nucleic acid interactions and provide a platform for improving the array-based methods for investigation of antisense therapeutics. A method for analysing combinatorial DNA arrays using oligonucleotide-modified gold nanoparticle probes and a conventional scanner has considerable potential in molecular diagnostics. Various applications of microarray technology for high-throughput screening in drug discovery and single nucleotide polymorphisms (SNP) analysis were discussed. Protein chips have important applications in proteomics. With the considerable amount of data generated by the different technologies using microarrays, it is obvious that the reading of the information and its interpretation and management through the use of bioinformatics is essential. Various techniques for data analysis were presented. Biochip and microarray technology has an essential role to play in the evolving trends in healthcare, which integrate diagnosis with prevention/treatment and emphasise personalised medicines.

ArraySolver: an algorithm for colour-coded graphical display and Wilcoxon signed-rank statistics for comparing microarray gene expression data.

PubMed

Khan, Haseeb Ahmad

2004-01-01

The massive surge in the production of microarray data poses a great challenge for proper analysis and interpretation. In recent years numerous computational tools have been developed to extract meaningful interpretation of microarray gene expression data. However, a convenient tool for two-groups comparison of microarray data is still lacking and users have to rely on commercial statistical packages that might be costly and require special skills, in addition to extra time and effort for transferring data from one platform to other. Various statistical methods, including the t-test, analysis of variance, Pearson test and Mann-Whitney U test, have been reported for comparing microarray data, whereas the utilization of the Wilcoxon signed-rank test, which is an appropriate test for two-groups comparison of gene expression data, has largely been neglected in microarray studies. The aim of this investigation was to build an integrated tool, ArraySolver, for colour-coded graphical display and comparison of gene expression data using the Wilcoxon signed-rank test. The results of software validation showed similar outputs with ArraySolver and SPSS for large datasets. Whereas the former program appeared to be more accurate for 25 or fewer pairs (n < or = 25), suggesting its potential application in analysing molecular signatures that usually contain small numbers of genes. The main advantages of ArraySolver are easy data selection, convenient report format, accurate statistics and the familiar Excel platform.

ArraySolver: An Algorithm for Colour-Coded Graphical Display and Wilcoxon Signed-Rank Statistics for Comparing Microarray Gene Expression Data

PubMed Central

2004-01-01

The massive surge in the production of microarray data poses a great challenge for proper analysis and interpretation. In recent years numerous computational tools have been developed to extract meaningful interpretation of microarray gene expression data. However, a convenient tool for two-groups comparison of microarray data is still lacking and users have to rely on commercial statistical packages that might be costly and require special skills, in addition to extra time and effort for transferring data from one platform to other. Various statistical methods, including the t-test, analysis of variance, Pearson test and Mann–Whitney U test, have been reported for comparing microarray data, whereas the utilization of the Wilcoxon signed-rank test, which is an appropriate test for two-groups comparison of gene expression data, has largely been neglected in microarray studies. The aim of this investigation was to build an integrated tool, ArraySolver, for colour-coded graphical display and comparison of gene expression data using the Wilcoxon signed-rank test. The results of software validation showed similar outputs with ArraySolver and SPSS for large datasets. Whereas the former program appeared to be more accurate for 25 or fewer pairs (n ≤ 25), suggesting its potential application in analysing molecular signatures that usually contain small numbers of genes. The main advantages of ArraySolver are easy data selection, convenient report format, accurate statistics and the familiar Excel platform. PMID:18629036

Stress Sensors and Signal Transducers in Cyanobacteria

PubMed Central

Los, Dmitry A.; Zorina, Anna; Sinetova, Maria; Kryazhov, Sergey; Mironov, Kirill; Zinchenko, Vladislav V.

2010-01-01

In living cells, the perception of environmental stress and the subsequent transduction of stress signals are primary events in the acclimation to changes in the environment. Some molecular sensors and transducers of environmental stress cannot be identified by traditional and conventional methods. Based on genomic information, a systematic approach has been applied to the solution of this problem in cyanobacteria, involving mutagenesis of potential sensors and signal transducers in combination with DNA microarray analyses for the genome-wide expression of genes. Forty-five genes for the histidine kinases (Hiks), 12 genes for serine-threonine protein kinases (Spks), 42 genes for response regulators (Rres), seven genes for RNA polymerase sigma factors, and nearly 70 genes for transcription factors have been successfully inactivated by targeted mutagenesis in the unicellular cyanobacterium Synechocystis sp. PCC 6803. Screening of mutant libraries by genome-wide DNA microarray analysis under various stress and non-stress conditions has allowed identification of proteins that perceive and transduce signals of environmental stress. Here we summarize recent progress in the identification of sensory and regulatory systems, including Hiks, Rres, Spks, sigma factors, transcription factors, and the role of genomic DNA supercoiling in the regulation of the responses of cyanobacterial cells to various types of stress. PMID:22294932

Expression Profile of Long Noncoding RNAs in Human Earlobe Keloids: A Microarray Analysis

PubMed Central

Guo, Liang; Xu, Kai; Yan, Hongbo; Feng, Haifeng

2016-01-01

Background. Long noncoding RNAs (lncRNAs) play key roles in a wide range of biological processes and their deregulation results in human disease, including keloids. Earlobe keloid is a type of pathological skin scar, and the molecular pathogenesis of this disease remains largely unknown. Methods. In this study, microarray analysis was used to determine the expression profiles of lncRNAs and mRNAs between 3 pairs of earlobe keloid and normal specimens. Gene Ontology (GO) categories and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were performed to identify the main functions of the differentially expressed genes and earlobe keloid-related pathways. Results. A total of 2068 lncRNAs and 1511 mRNAs were differentially expressed between earlobe keloid and normal tissues. Among them, 1290 lncRNAs and 1092 mRNAs were upregulated, and 778 lncRNAs and 419 mRNAs were downregulated. Pathway analysis revealed that 24 pathways were correlated to the upregulated transcripts, while 11 pathways were associated with the downregulated transcripts. Conclusion. We characterized the expression profiles of lncRNA and mRNA in earlobe keloids and suggest that lncRNAs may serve as diagnostic biomarkers for the therapy of earlobe keloid. PMID:28101509

Equalizer reduces SNP bias in Affymetrix microarrays.

PubMed

Quigley, David

2015-07-30

Gene expression microarrays measure the levels of messenger ribonucleic acid (mRNA) in a sample using probe sequences that hybridize with transcribed regions. These probe sequences are designed using a reference genome for the relevant species. However, most model organisms and all humans have genomes that deviate from their reference. These variations, which include single nucleotide polymorphisms, insertions of additional nucleotides, and nucleotide deletions, can affect the microarray's performance. Genetic experiments comparing individuals bearing different population-associated single nucleotide polymorphisms that intersect microarray probes are therefore subject to systemic bias, as the reduction in binding efficiency due to a technical artifact is confounded with genetic differences between parental strains. This problem has been recognized for some time, and earlier methods of compensation have attempted to identify probes affected by genome variants using statistical models. These methods may require replicate microarray measurement of gene expression in the relevant tissue in inbred parental samples, which are not always available in model organisms and are never available in humans. By using sequence information for the genomes of organisms under investigation, potentially problematic probes can now be identified a priori. However, there is no published software tool that makes it easy to eliminate these probes from an annotation. I present equalizer, a software package that uses genome variant data to modify annotation files for the commonly used Affymetrix IVT and Gene/Exon platforms. These files can be used by any microarray normalization method for subsequent analysis. I demonstrate how use of equalizer on experiments mapping germline influence on gene expression in a genetic cross between two divergent mouse species and in human samples significantly reduces probe hybridization-induced bias, reducing false positive and false negative findings. The equalizer package reduces probe hybridization bias from experiments performed on the Affymetrix microarray platform, allowing accurate assessment of germline influence on gene expression.

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

PubMed Central

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 contrast, popular normalization approaches like quantile, LOWESS, Peng's method and VSN normalization alter the data distributions of regulation microarrays to such an extent that using these approaches will impact the reliability of the downstream analysis substantially. PMID:22276688

Mapping the affinity landscape of Thrombin-binding aptamers on 2΄F-ANA/DNA chimeric G-Quadruplex microarrays

PubMed Central

Abou Assi, Hala; Gómez-Pinto, Irene; González, Carlos

2017-01-01

Abstract In situ fabricated nucleic acids microarrays are versatile and very high-throughput platforms for aptamer optimization and discovery, but the chemical space that can be probed against a given target has largely been confined to DNA, while RNA and non-natural nucleic acid microarrays are still an essentially uncharted territory. 2΄-Fluoroarabinonucleic acid (2΄F-ANA) is a prime candidate for such use in microarrays. Indeed, 2΄F-ANA chemistry is readily amenable to photolithographic microarray synthesis and its potential in high affinity aptamers has been recently discovered. We thus synthesized the first microarrays containing 2΄F-ANA and 2΄F-ANA/DNA chimeric sequences to fully map the binding affinity landscape of the TBA1 thrombin-binding G-quadruplex aptamer containing all 32 768 possible DNA-to-2΄F-ANA mutations. The resulting microarray was screened against thrombin to identify a series of promising 2΄F-ANA-modified aptamer candidates with Kds significantly lower than that of the unmodified control and which were found to adopt highly stable, antiparallel-folded G-quadruplex structures. The solution structure of the TBA1 aptamer modified with 2΄F-ANA at position T3 shows that fluorine substitution preorganizes the dinucleotide loop into the proper conformation for interaction with thrombin. Overall, our work strengthens the potential of 2΄F-ANA in aptamer research and further expands non-genomic applications of nucleic acids microarrays. PMID:28100695

Development of a rapid microarray-based DNA subtyping assay for the alleles of Shiga toxins 1 and 2 of Escherichia coli.

PubMed

Geue, Lutz; Stieber, Bettina; Monecke, Stefan; Engelmann, Ines; Gunzer, Florian; Slickers, Peter; Braun, Sascha D; Ehricht, Ralf

2014-08-01

In this study, we developed a new rapid, economic, and automated microarray-based genotyping test for the standardized subtyping of Shiga toxins 1 and 2 of Escherichia coli. The microarrays from Alere Technologies can be used in two different formats, the ArrayTube and the ArrayStrip (which enables high-throughput testing in a 96-well format). One microarray chip harbors all the gene sequences necessary to distinguish between all Stx subtypes, facilitating the identification of single and multiple subtypes within a single isolate in one experiment. Specific software was developed to automatically analyze all data obtained from the microarray. The assay was validated with 21 Shiga toxin-producing E. coli (STEC) reference strains that were previously tested by the complete set of conventional subtyping PCRs. The microarray results showed 100% concordance with the PCR results. Essentially identical results were detected when the standard DNA extraction method was replaced by a time-saving heat lysis protocol. For further validation of the microarray, we identified the Stx subtypes or combinations of the subtypes in 446 STEC field isolates of human and animal origin. In summary, this oligonucleotide array represents an excellent diagnostic tool that provides some advantages over standard PCR-based subtyping. The number of the spotted probes on the microarrays can be increased by additional probes, such as for novel alleles, species markers, or resistance genes, should the need arise. Copyright © 2014, American Society for Microbiology. All Rights Reserved.

Microarray analysis identifies Salmonella genes belonging to the low-shear modeled microgravity regulon

PubMed Central

Wilson, James W.; Ramamurthy, Rajee; Porwollik, Steffen; McClelland, Michael; Hammond, Timothy; Allen, Pat; Ott, C. Mark; Pierson, Duane L.; Nickerson, Cheryl A.

2002-01-01

The low-shear environment of optimized rotation suspension culture allows both eukaryotic and prokaryotic cells to assume physiologically relevant phenotypes that have led to significant advances in fundamental investigations of medical and biological importance. This culture environment has also been used to model microgravity for ground-based studies regarding the impact of space flight on eukaryotic and prokaryotic physiology. We have previously demonstrated that low-shear modeled microgravity (LSMMG) under optimized rotation suspension culture is a novel environmental signal that regulates the virulence, stress resistance, and protein expression levels of Salmonella enterica serovar Typhimurium. However, the mechanisms used by the cells of any species, including Salmonella, to sense and respond to LSMMG and identities of the genes involved are unknown. In this study, we used DNA microarrays to elucidate the global transcriptional response of Salmonella to LSMMG. When compared with identical growth conditions under normal gravity (1 × g), LSMMG differentially regulated the expression of 163 genes distributed throughout the chromosome, representing functionally diverse groups including transcriptional regulators, virulence factors, lipopolysaccharide biosynthetic enzymes, iron-utilization enzymes, and proteins of unknown function. Many of the LSMMG-regulated genes were organized in clusters or operons. The microarray results were further validated by RT-PCR and phenotypic analyses, and they indicate that the ferric uptake regulator is involved in the LSMMG response. The results provide important insight about the Salmonella LSMMG response and could provide clues for the functioning of known Salmonella virulence systems or the identification of uncharacterized bacterial virulence strategies. PMID:12370447

Artificial intelligence in hematology.

PubMed

Zini, Gina

2005-10-01

Artificial intelligence (AI) is a computer based science which aims to simulate human brain faculties using a computational system. A brief history of this new science goes from the creation of the first artificial neuron in 1943 to the first artificial neural network application to genetic algorithms. The potential for a similar technology in medicine has immediately been identified by scientists and researchers. The possibility to store and process all medical knowledge has made this technology very attractive to assist or even surpass clinicians in reaching a diagnosis. Applications of AI in medicine include devices applied to clinical diagnosis in neurology and cardiopulmonary diseases, as well as the use of expert or knowledge-based systems in routine clinical use for diagnosis, therapeutic management and for prognostic evaluation. Biological applications include genome sequencing or DNA gene expression microarrays, modeling gene networks, analysis and clustering of gene expression data, pattern recognition in DNA and proteins, protein structure prediction. In the field of hematology the first devices based on AI have been applied to the routine laboratory data management. New tools concern the differential diagnosis in specific diseases such as anemias, thalassemias and leukemias, based on neural networks trained with data from peripheral blood analysis. A revolution in cancer diagnosis, including the diagnosis of hematological malignancies, has been the introduction of the first microarray based and bioinformatic approach for molecular diagnosis: a systematic approach based on the monitoring of simultaneous expression of thousands of genes using DNA microarray, independently of previous biological knowledge, analysed using AI devices. Using gene profiling, the traditional diagnostic pathways move from clinical to molecular based diagnostic systems.

EST resources and establishment and validation of a 16k cDNA microarray from Atlantic cod (Gadus morhua).

PubMed

Edvardsen, Rolf B; Malde, Ketil; Mittelholzer, Christian; Taranger, Geir Lasse; Nilsen, Frank

2011-03-01

The Atlantic cod, Gadus morhua, is an important species both for traditional fishery and increasingly also in fish farming. The Atlantic cod is also under potential threat from various environmental changes such as pollution and climate change, but the biological impact of such changes are not well known, in particular when it comes to sublethal effects that can be difficult to assert. Modern molecular and genomic approaches have revolutionized biological research during the last decade, and offer new avenues to study biological functions and e.g. the impact of anthropogenic activities at different life-stages for a given organism. In order to develop genomic data and genomic tools for Atlantic cod we conducted a program were we constructed 20 cDNA libraries, and produced and analyzed 44006 expressed sequence tags (ESTs) from these. Several tissues are represented in the multiple cDNA libraries, that differ in either sexual maturation or immulogical stimulation. This approach allowed us to identify genes that are expressed in particular tissues, life-stages or in response to specific stimuli, and also gives us information about potential functions of the transcripts. The ESTs were used to construct a 16k cDNA microarray to further investigate the cod transcriptome. Microarray analyses were preformed on pylorus, pituitary gland, spleen and testis of sexually maturing male cod. The four different tissues displayed tissue specific transcriptomes demonstrating that the cDNA array is working as expected and will prove to be a powerful tool in further experiments. Copyright © 2010 Elsevier Inc. All rights reserved.

16S rRNA gene-based phylogenetic microarray for simultaneous identification of members of the genus Burkholderia.

PubMed

Schönmann, Susan; Loy, Alexander; Wimmersberger, Céline; Sobek, Jens; Aquino, Catharine; Vandamme, Peter; Frey, Beat; Rehrauer, Hubert; Eberl, Leo

2009-04-01

For cultivation-independent and highly parallel analysis of members of the genus Burkholderia, an oligonucleotide microarray (phylochip) consisting of 131 hierarchically nested 16S rRNA gene-targeted oligonucleotide probes was developed. A novel primer pair was designed for selective amplification of a 1.3 kb 16S rRNA gene fragment of Burkholderia species prior to microarray analysis. The diagnostic performance of the microarray for identification and differentiation of Burkholderia species was tested with 44 reference strains of the genera Burkholderia, Pandoraea, Ralstonia and Limnobacter. Hybridization patterns based on presence/absence of probe signals were interpreted semi-automatically using the novel likelihood-based strategy of the web-tool Phylo- Detect. Eighty-eight per cent of the reference strains were correctly identified at the species level. The evaluated microarray was applied to investigate shifts in the Burkholderia community structure in acidic forest soil upon addition of cadmium, a condition that selected for Burkholderia species. The microarray results were in agreement with those obtained from phylogenetic analysis of Burkholderia 16S rRNA gene sequences recovered from the same cadmiumcontaminated soil, demonstrating the value of the Burkholderia phylochip for determinative and environmental studies.

Detection and identification of intestinal pathogenic bacteria by hybridization to oligonucleotide microarrays

PubMed Central

Jin, Lian-Qun; Li, Jun-Wen; Wang, Sheng-Qi; Chao, Fu-Huan; Wang, Xin-Wei; Yuan, Zheng-Quan

2005-01-01

AIM: To detect the common intestinal pathogenic bacteria quickly and accurately. METHODS: A rapid (<3 h) experimental procedure was set up based upon the gene chip technology. Target genes were amplified and hybridized by oligonucleotide microarrays. RESULTS: One hundred and seventy strains of bacteria in pure culture belonging to 11 genera were successfully discriminated under comparatively same conditions, and a series of specific hybridization maps corresponding to each kind of bacteria were obtained. When this method was applied to 26 divided cultures, 25 (96.2%) were identified. CONCLUSION: Salmonella sp., Escherichia coli, Shigella sp., Listeria monocytogenes, Vibrio parahaemolyticus, Staphylococcus aureus, Proteus sp., Bacillus cereus, Vibrio cholerae, Enterococcus faecalis, Yersinia enterocolitica, and Campylobacter jejuni can be detected and identified by our microarrays. The accuracy, range, and discrimination power of this assay can be continually improved by adding further oligonucleotides to the arrays without any significant increase of complexity or cost. PMID:16437687

Protein-protein interactions: an application of Tus-Ter mediated protein microarray system.

PubMed

Sitaraman, Kalavathy; Chatterjee, Deb K

2011-01-01

In this chapter, we present a novel, cost-effective microarray strategy that utilizes expression-ready plasmid DNAs to generate protein arrays on-demand and its use to validate protein-protein interactions. These expression plasmids were constructed in such a way so as to serve a dual purpose of synthesizing the protein of interest as well as capturing the synthesized protein. The microarray system is based on the high affinity binding of Escherichia coli "Tus" protein to "Ter," a 20 bp DNA sequence involved in the regulation of DNA replication. The protein expression is carried out in a cell-free protein synthesis system, with rabbit reticulocyte lysates, and the target proteins are detected either by labeled incorporated tag specific or by gene-specific antibodies. This microarray system has been successfully used for the detection of protein-protein interaction because both the target protein and the query protein can be transcribed and translated simultaneously in the microarray slides. The utility of this system for detecting protein-protein interaction is demonstrated by a few well-known examples: Jun/Fos, FRB/FKBP12, p53/MDM2, and CDK4/p16. In all these cases, the presence of protein complexes resulted in the localization of fluorophores at the specific sites of the immobilized target plasmids. Interestingly, during our interactions studies we also detected a previously unknown interaction between CDK2 and p16. Thus, this Tus-Ter based system of protein microarray can be used for the validation of known protein interactions as well as for identifying new protein-protein interactions. In addition, it can be used to examine and identify targets of nucleic acid-protein, ligand-receptor, enzyme-substrate, and drug-protein interactions.

Immunological Targeting of Tumor Initiating Prostate Cancer Cells

DTIC Science & Technology

2014-10-01

clinically using well-accepted immuno-competent animal models. 2) Keywords: Prostate Cancer, Lymphocyte, Vaccine, Antibody 3) Overall Project Summary...castrate animals . Task 1: Identify and verify antigenic targets from CAstrate Resistant Luminal Epithelial Cells (CRLEC) (months 1-16... animals per group will be processed to derive sufficient RNA for microarray analysis; the experiment will be repeated x 3. Microarray analysis will

Discovering ligands for a microRNA precursor with peptoid microarrays

PubMed Central

Chirayil, Sara; Chirayil, Rachel; Luebke, Kevin J.

2009-01-01

We have screened peptoid microarrays to identify specific ligands for the RNA hairpin precursor of miR-21, a microRNA involved in cancer and heart disease. Microarrays were printed by spotting a library of 7680 N-substituted oligoglycines (peptoids) onto glass slides. Two compounds on the array specifically bind RNA having the sequence and predicted secondary structure of the miR-21 precursor hairpin and have specific affinity for the target in solution. Their binding induces a conformational change around the hairpin loop, and the most specific compound recognizes the loop sequence and a bulged uridine in the proximal duplex. Functional groups contributing affinity and specificity were identified, and by varying a critical methylpyridine group, a compound with a dissociation constant of 1.9 μM for the miR-21 precursor hairpin and a 20-fold discrimination against a closely-related hairpin was created. This work describes a systematic approach to discovery of ligands for specific pre-defined novel RNA structures. It demonstrates discovery of new ligands for an RNA for which no specific lead compounds were previously known by screening a microarray of small molecules. PMID:19561197

Estimating differential expression from multiple indicators

PubMed Central

Ilmjärv, Sten; Hundahl, Christian Ansgar; Reimets, Riin; Niitsoo, Margus; Kolde, Raivo; Vilo, Jaak; Vasar, Eero; Luuk, Hendrik

2014-01-01

Regardless of the advent of high-throughput sequencing, microarrays remain central in current biomedical research. Conventional microarray analysis pipelines apply data reduction before the estimation of differential expression, which is likely to render the estimates susceptible to noise from signal summarization and reduce statistical power. We present a probe-level framework, which capitalizes on the high number of concurrent measurements to provide more robust differential expression estimates. The framework naturally extends to various experimental designs and target categories (e.g. transcripts, genes, genomic regions) as well as small sample sizes. Benchmarking in relation to popular microarray and RNA-sequencing data-analysis pipelines indicated high and stable performance on the Microarray Quality Control dataset and in a cell-culture model of hypoxia. Experimental-data-exhibiting long-range epigenetic silencing of gene expression was used to demonstrate the efficacy of detecting differential expression of genomic regions, a level of analysis not embraced by conventional workflows. Finally, we designed and conducted an experiment to identify hypothermia-responsive genes in terms of monotonic time-response. As a novel insight, hypothermia-dependent up-regulation of multiple genes of two major antioxidant pathways was identified and verified by quantitative real-time PCR. PMID:24586062

Using Kepler for Tool Integration in Microarray Analysis Workflows.

PubMed

Gan, Zhuohui; Stowe, Jennifer C; Altintas, Ilkay; McCulloch, Andrew D; Zambon, Alexander C

Increasing numbers of genomic technologies are leading to massive amounts of genomic data, all of which requires complex analysis. More and more bioinformatics analysis tools are being developed by scientist to simplify these analyses. However, different pipelines have been developed using different software environments. This makes integrations of these diverse bioinformatics tools difficult. Kepler provides an open source environment to integrate these disparate packages. Using Kepler, we integrated several external tools including Bioconductor packages, AltAnalyze, a python-based open source tool, and R-based comparison tool to build an automated workflow to meta-analyze both online and local microarray data. The automated workflow connects the integrated tools seamlessly, delivers data flow between the tools smoothly, and hence improves efficiency and accuracy of complex data analyses. Our workflow exemplifies the usage of Kepler as a scientific workflow platform for bioinformatics pipelines.

An efficient pseudomedian filter for tiling microrrays.

PubMed

Royce, Thomas E; Carriero, Nicholas J; Gerstein, Mark B

2007-06-07

Tiling microarrays are becoming an essential technology in the functional genomics toolbox. They have been applied to the tasks of novel transcript identification, elucidation of transcription factor binding sites, detection of methylated DNA and several other applications in several model organisms. These experiments are being conducted at increasingly finer resolutions as the microarray technology enjoys increasingly greater feature densities. The increased densities naturally lead to increased data analysis requirements. Specifically, the most widely employed algorithm for tiling array analysis involves smoothing observed signals by computing pseudomedians within sliding windows, a O(n2logn) calculation in each window. This poor time complexity is an issue for tiling array analysis and could prove to be a real bottleneck as tiling microarray experiments become grander in scope and finer in resolution. We therefore implemented Monahan's HLQEST algorithm that reduces the runtime complexity for computing the pseudomedian of n numbers to O(nlogn) from O(n2logn). For a representative tiling microarray dataset, this modification reduced the smoothing procedure's runtime by nearly 90%. We then leveraged the fact that elements within sliding windows remain largely unchanged in overlapping windows (as one slides across genomic space) to further reduce computation by an additional 43%. This was achieved by the application of skip lists to maintaining a sorted list of values from window to window. This sorted list could be maintained with simple O(log n) inserts and deletes. We illustrate the favorable scaling properties of our algorithms with both time complexity analysis and benchmarking on synthetic datasets. Tiling microarray analyses that rely upon a sliding window pseudomedian calculation can require many hours of computation. We have eased this requirement significantly by implementing efficient algorithms that scale well with genomic feature density. This result not only speeds the current standard analyses, but also makes possible ones where many iterations of the filter may be required, such as might be required in a bootstrap or parameter estimation setting. Source code and executables are available at http://tiling.gersteinlab.org/pseudomedian/.

An efficient pseudomedian filter for tiling microrrays

PubMed Central

Royce, Thomas E; Carriero, Nicholas J; Gerstein, Mark B

2007-01-01

Background Tiling microarrays are becoming an essential technology in the functional genomics toolbox. They have been applied to the tasks of novel transcript identification, elucidation of transcription factor binding sites, detection of methylated DNA and several other applications in several model organisms. These experiments are being conducted at increasingly finer resolutions as the microarray technology enjoys increasingly greater feature densities. The increased densities naturally lead to increased data analysis requirements. Specifically, the most widely employed algorithm for tiling array analysis involves smoothing observed signals by computing pseudomedians within sliding windows, a O(n2logn) calculation in each window. This poor time complexity is an issue for tiling array analysis and could prove to be a real bottleneck as tiling microarray experiments become grander in scope and finer in resolution. Results We therefore implemented Monahan's HLQEST algorithm that reduces the runtime complexity for computing the pseudomedian of n numbers to O(nlogn) from O(n2logn). For a representative tiling microarray dataset, this modification reduced the smoothing procedure's runtime by nearly 90%. We then leveraged the fact that elements within sliding windows remain largely unchanged in overlapping windows (as one slides across genomic space) to further reduce computation by an additional 43%. This was achieved by the application of skip lists to maintaining a sorted list of values from window to window. This sorted list could be maintained with simple O(log n) inserts and deletes. We illustrate the favorable scaling properties of our algorithms with both time complexity analysis and benchmarking on synthetic datasets. Conclusion Tiling microarray analyses that rely upon a sliding window pseudomedian calculation can require many hours of computation. We have eased this requirement significantly by implementing efficient algorithms that scale well with genomic feature density. This result not only speeds the current standard analyses, but also makes possible ones where many iterations of the filter may be required, such as might be required in a bootstrap or parameter estimation setting. Source code and executables are available at . PMID:17555595

Gene Expression Profiling of Gastric Cancer

PubMed Central

Marimuthu, Arivusudar; Jacob, Harrys K.C.; Jakharia, Aniruddha; Subbannayya, Yashwanth; Keerthikumar, Shivakumar; Kashyap, Manoj Kumar; Goel, Renu; Balakrishnan, Lavanya; Dwivedi, Sutopa; Pathare, Swapnali; Dikshit, Jyoti Bajpai; Maharudraiah, Jagadeesha; Singh, Sujay; Sameer Kumar, Ghantasala S; Vijayakumar, M.; Veerendra Kumar, Kariyanakatte Veeraiah; Premalatha, Chennagiri Shrinivasamurthy; Tata, Pramila; Hariharan, Ramesh; Roa, Juan Carlos; Prasad, T.S.K; Chaerkady, Raghothama; Kumar, Rekha Vijay; Pandey, Akhilesh

2015-01-01

Gastric cancer is the second leading cause of cancer death worldwide, both in men and women. A genomewide gene expression analysis was carried out to identify differentially expressed genes in gastric adenocarcinoma tissues as compared to adjacent normal tissues. We used Agilent’s whole human genome oligonucleotide microarray platform representing ~41,000 genes to carry out gene expression analysis. Two-color microarray analysis was employed to directly compare the expression of genes between tumor and normal tissues. Through this approach, we identified several previously known candidate genes along with a number of novel candidate genes in gastric cancer. Testican-1 (SPOCK1) was one of the novel molecules that was 10-fold upregulated in tumors. Using tissue microarrays, we validated the expression of testican-1 by immunohistochemical staining. It was overexpressed in 56% (160/282) of the cases tested. Pathway analysis led to the identification of several networks in which SPOCK1 was among the topmost networks of interacting genes. By gene enrichment analysis, we identified several genes involved in cell adhesion and cell proliferation to be significantly upregulated while those corresponding to metabolic pathways were significantly downregulated. The differentially expressed genes identified in this study are candidate biomarkers for gastric adenoacarcinoma. PMID:27030788

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

PubMed

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.

Integration of Genome-Wide Computation DRE Search, AhR ChIP-chip and Gene Expression Analyses of TCDD-Elicited Responses in the Mouse Liver

PubMed Central

2011-01-01

Background The aryl hydrocarbon receptor (AhR) is a ligand-activated transcription factor (TF) that mediates responses to 2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD). Integration of TCDD-induced genome-wide AhR enrichment, differential gene expression and computational dioxin response element (DRE) analyses further elucidate the hepatic AhR regulatory network. Results Global ChIP-chip and gene expression analyses were performed on hepatic tissue from immature ovariectomized mice orally gavaged with 30 μg/kg TCDD. ChIP-chip analysis identified 14,446 and 974 AhR enriched regions (1% false discovery rate) at 2 and 24 hrs, respectively. Enrichment density was greatest in the proximal promoter, and more specifically, within ± 1.5 kb of a transcriptional start site (TSS). AhR enrichment also occurred distal to a TSS (e.g. intergenic DNA and 3' UTR), extending the potential gene expression regulatory roles of the AhR. Although TF binding site analyses identified over-represented DRE sequences within enriched regions, approximately 50% of all AhR enriched regions lacked a DRE core (5'-GCGTG-3'). Microarray analysis identified 1,896 number of TCDD-responsive genes (|fold change| ≥ 1.5, P1(t) > 0.999). Integrating this gene expression data with our ChIP-chip and DRE analyses only identified 625 differentially expressed genes that involved an AhR interaction at a DRE. Functional annotation analysis of differentially regulated genes associated with AhR enrichment identified overrepresented processes related to fatty acid and lipid metabolism and transport, and xenobiotic metabolism, which are consistent with TCDD-elicited steatosis in the mouse liver. Conclusions Details of the AhR regulatory network have been expanded to include AhR-DNA interactions within intragenic and intergenic genomic regions. Moreover, the AhR can interact with DNA independent of a DRE core suggesting there are alternative mechanisms of AhR-mediated gene regulation. PMID:21762485

Maternal Pre-Pregnancy Obesity Is Associated with Altered Placental Transcriptome.

PubMed

Altmäe, Signe; Segura, Maria Teresa; Esteban, Francisco J; Bartel, Sabine; Brandi, Pilar; Irmler, Martin; Beckers, Johannes; Demmelmair, Hans; López-Sabater, Carmen; Koletzko, Berthold; Krauss-Etschmann, Susanne; Campoy, Cristina

2017-01-01

Maternal obesity has a major impact on pregnancy outcomes. There is growing evidence that maternal obesity has a negative influence on placental development and function, thereby adversely influencing offspring programming and health outcomes. However, the molecular mechanisms underlying these processes are poorly understood. We analysed ten term placenta's whole transcriptomes in obese (n = 5) and normal weight women (n = 5), using the Affymetrix microarray platform. Analyses of expression data were carried out using non-parametric methods. Hierarchical clustering and principal component analysis showed a clear distinction in placental transcriptome between obese and normal weight women. We identified 72 differentially regulated genes, with most being down-regulated in obesity (n = 61). Functional analyses of the targets using DAVID and IPA confirm the dysregulation of previously identified processes and pathways in the placenta from obese women, including inflammation and immune responses, lipid metabolism, cancer pathways, and angiogenesis. In addition, we detected new molecular aspects of obesity-derived effects on the placenta, involving the glucocorticoid receptor signalling pathway and dysregulation of several genes including CCL2, FSTL3, IGFBP1, MMP12, PRG2, PRL, QSOX1, SERPINE2 and TAC3. Our global gene expression profiling approach demonstrates that maternal obesity creates a unique in utero environment that impairs the placental transcriptome.

Questioning the utility of pooling samples in microarray experiments with cell lines.

PubMed

Lusa, L; Cappelletti, V; Gariboldi, M; Ferrario, C; De Cecco, L; Reid, J F; Toffanin, S; Gallus, G; McShane, L M; Daidone, M G; Pierotti, M A

2006-01-01

We describe a microarray experiment using the MCF-7 breast cancer cell line in two different experimental conditions for which the same number of independent pools as the number of individual samples was hybridized on Affymetrix GeneChips. Unexpectedly, when using individual samples, the number of probe sets found to be differentially expressed between treated and untreated cells was about three times greater than that found using pools. These findings indicate that pooling samples in microarray experiments where the biological variability is expected to be small might not be helpful and could even decrease one's ability to identify differentially expressed genes.

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

PubMed

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.

Identifying circRNA-associated-ceRNA networks in the hippocampus of Aβ1-42-induced Alzheimer's disease-like rats using microarray analysis

PubMed Central

Wang, Zhe; Xu, Panpan; Chen, Biyue; Zhang, Zheyu; Zhang, Chunhu; Zhan, Qiong; Huang, Siqi; Xia, Zi-an

2018-01-01

Alzheimer’s disease (AD) is the most common form of dementia worldwide. Accumulating evidence indicates that non-coding RNAs are strongly implicated in AD-associated pathophysiology. However, the role of these ncRNAs remains largely unknown. In the present study, we used microarray analysis technology to characterize the expression patterns of circular RNAs (circRNAs), microRNAs (miRNAs), and mRNAs in hippocampal tissue from Aβ1-42-induced AD model rats, to integrate interaction data and thus provide novel insights into the mechanisms underlying AD. A total of 555 circRNAs, 183 miRNAs and 319 mRNAs were identified to be significantly dysregulated (fold-change ≥ 2.0 and p-value < 0.05) in the hippocampus of AD rats. Quantitative real-time polymerase chain reaction (qRT-PCR) was then used to validate the expression of randomly-selected circRNAs, miRNAs and mRNAs. Next, GO and KEGG pathway analyses were performed to further investigate ncRNAs biological functions and potential mechanisms. In addition, we constructed circRNA-miRNA and competitive endogenous RNA (ceRNA) regulatory networks to determine functional interactions between ncRNAs and mRNAs. Our results suggest the involvement of different ncRNA expression patterns in the pathogenesis of AD. Our findings provide a novel perspective for further research into AD pathogenesis and might facilitate the development of novel therapeutics targeting ncRNAs. PMID:29706607

An Integrative Framework for Bayesian Variable Selection with Informative Priors for Identifying Genes and Pathways

PubMed Central

Ander, Bradley P.; Zhang, Xiaoshuai; Xue, Fuzhong; Sharp, Frank R.; Yang, Xiaowei

2013-01-01

The discovery of genetic or genomic markers plays a central role in the development of personalized medicine. A notable challenge exists when dealing with the high dimensionality of the data sets, as thousands of genes or millions of genetic variants are collected on a relatively small number of subjects. Traditional gene-wise selection methods using univariate analyses face difficulty to incorporate correlational, structural, or functional structures amongst the molecular measures. For microarray gene expression data, we first summarize solutions in dealing with ‘large p, small n’ problems, and then propose an integrative Bayesian variable selection (iBVS) framework for simultaneously identifying causal or marker genes and regulatory pathways. A novel partial least squares (PLS) g-prior for iBVS is developed to allow the incorporation of prior knowledge on gene-gene interactions or functional relationships. From the point view of systems biology, iBVS enables user to directly target the joint effects of multiple genes and pathways in a hierarchical modeling diagram to predict disease status or phenotype. The estimated posterior selection probabilities offer probabilitic and biological interpretations. Both simulated data and a set of microarray data in predicting stroke status are used in validating the performance of iBVS in a Probit model with binary outcomes. iBVS offers a general framework for effective discovery of various molecular biomarkers by combining data-based statistics and knowledge-based priors. Guidelines on making posterior inferences, determining Bayesian significance levels, and improving computational efficiencies are also discussed. PMID:23844055

An integrative framework for Bayesian variable selection with informative priors for identifying genes and pathways.

PubMed

Peng, Bin; Zhu, Dianwen; Ander, Bradley P; Zhang, Xiaoshuai; Xue, Fuzhong; Sharp, Frank R; Yang, Xiaowei

2013-01-01

The discovery of genetic or genomic markers plays a central role in the development of personalized medicine. A notable challenge exists when dealing with the high dimensionality of the data sets, as thousands of genes or millions of genetic variants are collected on a relatively small number of subjects. Traditional gene-wise selection methods using univariate analyses face difficulty to incorporate correlational, structural, or functional structures amongst the molecular measures. For microarray gene expression data, we first summarize solutions in dealing with 'large p, small n' problems, and then propose an integrative Bayesian variable selection (iBVS) framework for simultaneously identifying causal or marker genes and regulatory pathways. A novel partial least squares (PLS) g-prior for iBVS is developed to allow the incorporation of prior knowledge on gene-gene interactions or functional relationships. From the point view of systems biology, iBVS enables user to directly target the joint effects of multiple genes and pathways in a hierarchical modeling diagram to predict disease status or phenotype. The estimated posterior selection probabilities offer probabilitic and biological interpretations. Both simulated data and a set of microarray data in predicting stroke status are used in validating the performance of iBVS in a Probit model with binary outcomes. iBVS offers a general framework for effective discovery of various molecular biomarkers by combining data-based statistics and knowledge-based priors. Guidelines on making posterior inferences, determining Bayesian significance levels, and improving computational efficiencies are also discussed.

The Long Non-Coding RNA Transcriptome Landscape in CHO Cells Under Batch and Fed-Batch Conditions.

PubMed

Vito, Davide; Smales, C Mark

2018-05-21

The role of non-coding RNAs in determining growth, productivity and recombinant product quality attributes in Chinese hamster ovary (CHO) cells has received much attention in recent years, exemplified by studies into microRNAs in particular. However, other classes of non-coding RNAs have received less attention. One such class are the non-coding RNAs known collectively as long non-coding RNAs (lncRNAs). We have undertaken the first landscape analysis of the lncRNA transcriptome in CHO using a mouse based microarray that also provided for the surveillance of the coding transcriptome. We report on those lncRNAs present in a model host CHO cell line under batch and fed-batch conditions on two different days and relate the expression of different lncRNAs to each other. We demonstrate that the mouse microarray was suitable for the detection and analysis of thousands of CHO lncRNAs and validated a number of these by qRT-PCR. We then further analysed the data to identify those lncRNAs whose expression changed the most between growth and stationary phases of culture or between batch and fed-batch culture to identify potential lncRNA targets for further functional studies with regard to their role in controlling growth of CHO cells. We discuss the implications for the publication of this rich dataset and how this may be used by the community. This article is protected by copyright. All rights reserved.

Identifying circRNA-associated-ceRNA networks in the hippocampus of Aβ1-42-induced Alzheimer's disease-like rats using microarray analysis.

PubMed

Wang, Zhe; Xu, Panpan; Chen, Biyue; Zhang, Zheyu; Zhang, Chunhu; Zhan, Qiong; Huang, Siqi; Xia, Zi-An; Peng, Weijun

2018-04-27

Alzheimer's disease (AD) is the most common form of dementia worldwide. Accumulating evidence indicates that non-coding RNAs are strongly implicated in AD-associated pathophysiology. However, the role of these ncRNAs remains largely unknown. In the present study, we used microarray analysis technology to characterize the expression patterns of circular RNAs (circRNAs), microRNAs (miRNAs), and mRNAs in hippocampal tissue from Aβ 1-42 -induced AD model rats, to integrate interaction data and thus provide novel insights into the mechanisms underlying AD. A total of 555 circRNAs, 183 miRNAs and 319 mRNAs were identified to be significantly dysregulated (fold-change ≥ 2.0 and p -value < 0.05) in the hippocampus of AD rats. Quantitative real-time polymerase chain reaction (qRT-PCR) was then used to validate the expression of randomly-selected circRNAs, miRNAs and mRNAs. Next, GO and KEGG pathway analyses were performed to further investigate ncRNAs biological functions and potential mechanisms. In addition, we constructed circRNA-miRNA and competitive endogenous RNA (ceRNA) regulatory networks to determine functional interactions between ncRNAs and mRNAs. Our results suggest the involvement of different ncRNA expression patterns in the pathogenesis of AD. Our findings provide a novel perspective for further research into AD pathogenesis and might facilitate the development of novel therapeutics targeting ncRNAs.

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

PubMed Central

2010-01-01

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. PMID:20509938

Biomphalaria glabrata transcriptome: cDNA microarray profiling identifies resistant- and susceptible-specific gene expression in haemocytes from snail strains exposed to Schistosoma mansoni

PubMed Central

Lockyer, Anne E; Spinks, Jenny; Kane, Richard A; Hoffmann, Karl F; Fitzpatrick, Jennifer M; Rollinson, David; Noble, Leslie R; Jones, Catherine S

2008-01-01

Background Biomphalaria glabrata is an intermediate snail host for Schistosoma mansoni, one of the important schistosomes infecting man. B. glabrata/S. mansoni provides a useful model system for investigating the intimate interactions between host and parasite. Examining differential gene expression between S. mansoni-exposed schistosome-resistant and susceptible snail lines will identify genes and pathways that may be involved in snail defences. Results We have developed a 2053 element cDNA microarray for B. glabrata containing clones from ORESTES (Open Reading frame ESTs) libraries, suppression subtractive hybridization (SSH) libraries and clones identified in previous expression studies. Snail haemocyte RNA, extracted from parasite-challenged resistant and susceptible snails, 2 to 24 h post-exposure to S. mansoni, was hybridized to the custom made cDNA microarray and 98 differentially expressed genes or gene clusters were identified, 94 resistant-associated and 4 susceptible-associated. Quantitative PCR analysis verified the cDNA microarray results for representative transcripts. Differentially expressed genes were annotated and clustered using gene ontology (GO) terminology and Kyoto Encyclopaedia of Genes and Genomes (KEGG) pathway analysis. 61% of the identified differentially expressed genes have no known function including the 4 susceptible strain-specific transcripts. Resistant strain-specific expression of genes implicated in innate immunity of invertebrates was identified, including hydrolytic enzymes such as cathepsin L, a cysteine proteinase involved in lysis of phagocytosed particles; metabolic enzymes such as ornithine decarboxylase, the rate-limiting enzyme in the production of polyamines, important in inflammation and infection processes, as well as scavenging damaging free radicals produced during production of reactive oxygen species; stress response genes such as HSP70; proteins involved in signalling, such as importin 7 and copine 1, cytoplasmic intermediate filament (IF) protein and transcription enzymes such as elongation factor 1α and EF-2. Conclusion Production of the first cDNA microarray for profiling gene expression in B. glabrata provides a foundation for expanding our understanding of pathways and genes involved in the snail internal defence system (IDS). We demonstrate resistant strain-specific expression of genes potentially associated with the snail IDS, ranging from signalling and inflammation responses through to lysis of proteinacous products (encapsulated sporocysts or phagocytosed parasite components) and processing/degradation of these targeted products by ubiquitination. PMID:19114004

Biomphalaria glabrata transcriptome: cDNA microarray profiling identifies resistant- and susceptible-specific gene expression in haemocytes from snail strains exposed to Schistosoma mansoni.

PubMed

Lockyer, Anne E; Spinks, Jenny; Kane, Richard A; Hoffmann, Karl F; Fitzpatrick, Jennifer M; Rollinson, David; Noble, Leslie R; Jones, Catherine S

2008-12-29

Biomphalaria glabrata is an intermediate snail host for Schistosoma mansoni, one of the important schistosomes infecting man. B. glabrata/S. mansoni provides a useful model system for investigating the intimate interactions between host and parasite. Examining differential gene expression between S. mansoni-exposed schistosome-resistant and susceptible snail lines will identify genes and pathways that may be involved in snail defences. We have developed a 2053 element cDNA microarray for B. glabrata containing clones from ORESTES (Open Reading frame ESTs) libraries, suppression subtractive hybridization (SSH) libraries and clones identified in previous expression studies. Snail haemocyte RNA, extracted from parasite-challenged resistant and susceptible snails, 2 to 24 h post-exposure to S. mansoni, was hybridized to the custom made cDNA microarray and 98 differentially expressed genes or gene clusters were identified, 94 resistant-associated and 4 susceptible-associated. Quantitative PCR analysis verified the cDNA microarray results for representative transcripts. Differentially expressed genes were annotated and clustered using gene ontology (GO) terminology and Kyoto Encyclopaedia of Genes and Genomes (KEGG) pathway analysis. 61% of the identified differentially expressed genes have no known function including the 4 susceptible strain-specific transcripts. Resistant strain-specific expression of genes implicated in innate immunity of invertebrates was identified, including hydrolytic enzymes such as cathepsin L, a cysteine proteinase involved in lysis of phagocytosed particles; metabolic enzymes such as ornithine decarboxylase, the rate-limiting enzyme in the production of polyamines, important in inflammation and infection processes, as well as scavenging damaging free radicals produced during production of reactive oxygen species; stress response genes such as HSP70; proteins involved in signalling, such as importin 7 and copine 1, cytoplasmic intermediate filament (IF) protein and transcription enzymes such as elongation factor 1alpha and EF-2. Production of the first cDNA microarray for profiling gene expression in B. glabrata provides a foundation for expanding our understanding of pathways and genes involved in the snail internal defence system (IDS). We demonstrate resistant strain-specific expression of genes potentially associated with the snail IDS, ranging from signalling and inflammation responses through to lysis of proteinacous products (encapsulated sporocysts or phagocytosed parasite components) and processing/degradation of these targeted products by ubiquitination.

Assessing differential expression in two-color microarrays: a resampling-based empirical Bayes approach.

PubMed

Li, Dongmei; Le Pape, Marc A; Parikh, Nisha I; Chen, Will X; Dye, Timothy D

2013-01-01

Microarrays are widely used for examining differential gene expression, identifying single nucleotide polymorphisms, and detecting methylation loci. Multiple testing methods in microarray data analysis aim at controlling both Type I and Type II error rates; however, real microarray data do not always fit their distribution assumptions. Smyth's ubiquitous parametric method, for example, inadequately accommodates violations of normality assumptions, resulting in inflated Type I error rates. The Significance Analysis of Microarrays, another widely used microarray data analysis method, is based on a permutation test and is robust to non-normally distributed data; however, the Significance Analysis of Microarrays method fold change criteria are problematic, and can critically alter the conclusion of a study, as a result of compositional changes of the control data set in the analysis. We propose a novel approach, combining resampling with empirical Bayes methods: the Resampling-based empirical Bayes Methods. This approach not only reduces false discovery rates for non-normally distributed microarray data, but it is also impervious to fold change threshold since no control data set selection is needed. Through simulation studies, sensitivities, specificities, total rejections, and false discovery rates are compared across the Smyth's parametric method, the Significance Analysis of Microarrays, and the Resampling-based empirical Bayes Methods. Differences in false discovery rates controls between each approach are illustrated through a preterm delivery methylation study. The results show that the Resampling-based empirical Bayes Methods offer significantly higher specificity and lower false discovery rates compared to Smyth's parametric method when data are not normally distributed. The Resampling-based empirical Bayes Methods also offers higher statistical power than the Significance Analysis of Microarrays method when the proportion of significantly differentially expressed genes is large for both normally and non-normally distributed data. Finally, the Resampling-based empirical Bayes Methods are generalizable to next generation sequencing RNA-seq data analysis.

Characterizing biomarkers in osteosarcoma metastasis based on an ego-network.

PubMed

Liu, Zhen; Song, Yan

2017-06-01

To characterize biomarkers that underlie osteosarcoma (OS) metastasis based on an ego-network. From the microarray data, we obtained 13,326 genes. By combining PPI data and microarray data, 10,520 shared genes were found and constructed into ego-networks. 17 significant ego-networks were identified with p < 0.05. In the pathway enrichment analysis, seven ego-networks were identified with the most significant pathway. These significant ego-modules were potential biomarkers that reveal the potential mechanisms in OS metastasis, which may contribute to understanding cancer prognoses and providing new perspectives in the treatment of cancer.

EDGE3: A web-based solution for management and analysis of Agilent two color microarray experiments

PubMed Central

Vollrath, Aaron L; Smith, Adam A; Craven, Mark; Bradfield, Christopher A

2009-01-01

Background The ability to generate transcriptional data on the scale of entire genomes has been a boon both in the improvement of biological understanding and in the amount of data generated. The latter, the amount of data generated, has implications when it comes to effective storage, analysis and sharing of these data. A number of software tools have been developed to store, analyze, and share microarray data. However, a majority of these tools do not offer all of these features nor do they specifically target the commonly used two color Agilent DNA microarray platform. Thus, the motivating factor for the development of EDGE3 was to incorporate the storage, analysis and sharing of microarray data in a manner that would provide a means for research groups to collaborate on Agilent-based microarray experiments without a large investment in software-related expenditures or extensive training of end-users. Results EDGE3 has been developed with two major functions in mind. The first function is to provide a workflow process for the generation of microarray data by a research laboratory or a microarray facility. The second is to store, analyze, and share microarray data in a manner that doesn't require complicated software. To satisfy the first function, EDGE3 has been developed as a means to establish a well defined experimental workflow and information system for microarray generation. To satisfy the second function, the software application utilized as the user interface of EDGE3 is a web browser. Within the web browser, a user is able to access the entire functionality, including, but not limited to, the ability to perform a number of bioinformatics based analyses, collaborate between research groups through a user-based security model, and access to the raw data files and quality control files generated by the software used to extract the signals from an array image. Conclusion Here, we present EDGE3, an open-source, web-based application that allows for the storage, analysis, and controlled sharing of transcription-based microarray data generated on the Agilent DNA platform. In addition, EDGE3 provides a means for managing RNA samples and arrays during the hybridization process. EDGE3 is freely available for download at . PMID:19732451

EDGE(3): a web-based solution for management and analysis of Agilent two color microarray experiments.

PubMed

Vollrath, Aaron L; Smith, Adam A; Craven, Mark; Bradfield, Christopher A

2009-09-04

The ability to generate transcriptional data on the scale of entire genomes has been a boon both in the improvement of biological understanding and in the amount of data generated. The latter, the amount of data generated, has implications when it comes to effective storage, analysis and sharing of these data. A number of software tools have been developed to store, analyze, and share microarray data. However, a majority of these tools do not offer all of these features nor do they specifically target the commonly used two color Agilent DNA microarray platform. Thus, the motivating factor for the development of EDGE(3) was to incorporate the storage, analysis and sharing of microarray data in a manner that would provide a means for research groups to collaborate on Agilent-based microarray experiments without a large investment in software-related expenditures or extensive training of end-users. EDGE(3) has been developed with two major functions in mind. The first function is to provide a workflow process for the generation of microarray data by a research laboratory or a microarray facility. The second is to store, analyze, and share microarray data in a manner that doesn't require complicated software. To satisfy the first function, EDGE3 has been developed as a means to establish a well defined experimental workflow and information system for microarray generation. To satisfy the second function, the software application utilized as the user interface of EDGE(3) is a web browser. Within the web browser, a user is able to access the entire functionality, including, but not limited to, the ability to perform a number of bioinformatics based analyses, collaborate between research groups through a user-based security model, and access to the raw data files and quality control files generated by the software used to extract the signals from an array image. Here, we present EDGE(3), an open-source, web-based application that allows for the storage, analysis, and controlled sharing of transcription-based microarray data generated on the Agilent DNA platform. In addition, EDGE(3) provides a means for managing RNA samples and arrays during the hybridization process. EDGE(3) is freely available for download at http://edge.oncology.wisc.edu/.

Identifying differentially expressed genes in cancer patients using a non-parameter Ising model.

PubMed

Li, Xumeng; Feltus, Frank A; Sun, Xiaoqian; Wang, James Z; Luo, Feng

2011-10-01

Identification of genes and pathways involved in diseases and physiological conditions is a major task in systems biology. In this study, we developed a novel non-parameter Ising model to integrate protein-protein interaction network and microarray data for identifying differentially expressed (DE) genes. We also proposed a simulated annealing algorithm to find the optimal configuration of the Ising model. The Ising model was applied to two breast cancer microarray data sets. The results showed that more cancer-related DE sub-networks and genes were identified by the Ising model than those by the Markov random field model. Furthermore, cross-validation experiments showed that DE genes identified by Ising model can improve classification performance compared with DE genes identified by Markov random field model. Copyright © 2011 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Employing image processing techniques for cancer detection using microarray images.

PubMed

Dehghan Khalilabad, Nastaran; Hassanpour, Hamid

2017-02-01

Microarray technology is a powerful genomic tool for simultaneously studying and analyzing the behavior of thousands of genes. The analysis of images obtained from this technology plays a critical role in the detection and treatment of diseases. The aim of the current study is to develop an automated system for analyzing data from microarray images in order to detect cancerous cases. The proposed system consists of three main phases, namely image processing, data mining, and the detection of the disease. The image processing phase performs operations such as refining image rotation, gridding (locating genes) and extracting raw data from images the data mining includes normalizing the extracted data and selecting the more effective genes. Finally, via the extracted data, cancerous cell is recognized. To evaluate the performance of the proposed system, microarray database is employed which includes Breast cancer, Myeloid Leukemia and Lymphomas from the Stanford Microarray Database. The results indicate that the proposed system is able to identify the type of cancer from the data set with an accuracy of 95.45%, 94.11%, and 100%, respectively. Copyright © 2017 Elsevier Ltd. All rights reserved.

Rapid and reliable detection and identification of GM events using multiplex PCR coupled with oligonucleotide microarray.

PubMed

Xu, Xiaodan; Li, Yingcong; Zhao, Heng; Wen, Si-yuan; Wang, Sheng-qi; Huang, Jian; Huang, Kun-lun; Luo, Yun-bo

2005-05-18

To devise a rapid and reliable method for the detection and identification of genetically modified (GM) events, we developed a multiplex polymerase chain reaction (PCR) coupled with a DNA microarray system simultaneously aiming at many targets in a single reaction. The system included probes for screening gene, species reference gene, specific gene, construct-specific gene, event-specific gene, and internal and negative control genes. 18S rRNA was combined with species reference genes as internal controls to assess the efficiency of all reactions and to eliminate false negatives. Two sets of the multiplex PCR system were used to amplify four and five targets, respectively. Eight different structure genes could be detected and identified simultaneously for Roundup Ready soybean in a single microarray. The microarray specificity was validated by its ability to discriminate two GM maizes Bt176 and Bt11. The advantages of this method are its high specificity and greatly reduced false-positives and -negatives. The multiplex PCR coupled with microarray technology presented here is a rapid and reliable tool for the simultaneous detection of GM organism ingredients.

Genomic Approach to Study Floral Development Genes in Rosa sp.

PubMed Central

Chauvet, Aurélie; Maene, Marion; Pécrix, Yann; Yang, Shu-Hua; Jeauffre, Julien; Thouroude, Tatiana; Boltz, Véronique; Martin-Magniette, Marie-Laure; Janczarski, Stéphane; Legeai, Fabrice; Renou, Jean-Pierre; Vergne, Philippe; Le Bris, Manuel; Foucher, Fabrice; Bendahmane, Mohammed

2011-01-01

Cultivated for centuries, the varieties of rose have been selected based on a number of flower traits. Understanding the genetic and molecular basis that contributes to these traits will impact on future improvements for this economically important ornamental plant. In this study, we used scanning electron microscopy and sections of meristems and flowers to establish a precise morphological calendar from early rose flower development stages to senescing flowers. Global gene expression was investigated from floral meristem initiation up to flower senescence in three rose genotypes exhibiting contrasted floral traits including continuous versus once flowering and simple versus double flower architecture, using a newly developed Affymetrix microarray (Rosa1_Affyarray) tool containing sequences representing 4765 unigenes expressed during flower development. Data analyses permitted the identification of genes associated with floral transition, floral organs initiation up to flower senescence. Quantitative real time PCR analyses validated the mRNA accumulation changes observed in microarray hybridizations for a selection of 24 genes expressed at either high or low levels. Our data describe the early flower development stages in Rosa sp, the production of a rose microarray and demonstrate its usefulness and reliability to study gene expression during extensive development phases, from the vegetative meristem to the senescent flower. PMID:22194838

Response of sweet orange (Citrus sinensis) to 'Candidatus Liberibacter asiaticus' infection: microscopy and microarray analyses.

PubMed

Kim, Jeong-Soon; Sagaram, Uma Shankar; Burns, Jacqueline K; Li, Jian-Liang; Wang, Nian

2009-01-01

Citrus greening or huanglongbing (HLB) is a devastating disease of citrus. HLB is associated with the phloem-limited fastidious prokaryotic alpha-proteobacterium 'Candidatus Liberibacter spp.' In this report, we used sweet orange (Citrus sinensis) leaf tissue infected with 'Ca. Liberibacter asiaticus' and compared this with healthy controls. Investigation of the host response was examined with citrus microarray hybridization based on 33,879 expressed sequence tag sequences from several citrus species and hybrids. The microarray analysis indicated that HLB infection significantly affected expression of 624 genes whose encoded proteins were categorized according to function. The categories included genes associated with sugar metabolism, plant defense, phytohormone, and cell wall metabolism, as well as 14 other gene categories. The anatomical analyses indicated that HLB bacterium infection caused phloem disruption, sucrose accumulation, and plugged sieve pores. The up-regulation of three key starch biosynthetic genes including ADP-glucose pyrophosphorylase, starch synthase, granule-bound starch synthase and starch debranching enzyme likely contributed to accumulation of starch in HLB-affected leaves. The HLB-associated phloem blockage resulted from the plugged sieve pores rather than the HLB bacterial aggregates since 'Ca. Liberibacter asiaticus' does not form aggregate in citrus. The up-regulation of pp2 gene is related to callose deposition to plug the sieve pores in HLB-affected plants.

Circadian Rhythm and Cartilage Extracellular Matrix Genes in Osseointegration: A Genome-Wide Screening of Implant Failure by Vitamin D Deficiency

PubMed Central

Mengatto, Cristiane Machado; Mussano, Federico; Honda, Yoshitomo; Colwell, Christopher S.; Nishimura, Ichiro

2011-01-01

Background Successful dental and orthopedic implants require the establishment of an intimate association with bone tissue; however, the mechanistic explanation of how biological systems accomplish osseointegration is still incomplete. We sought to identify critical gene networks involved in osseointegration by exploring the implant failure model under vitamin D deficiency. Methodology Adult male Sprague-Dawley rats were exposed to control or vitamin D-deficient diet prior to the osteotomy surgery in the femur bone and the placement of T-shaped Ti4Al6V implant. Two weeks after the osteotomy and implant placement, tissue formed at the osteotomy site or in the hollow chamber of T-shaped implant was harvested and total RNA was evaluated by whole genome microarray analyses. Principal Findings Two-way ANOVA of microarray data identified 103 genes that were significantly (>2 fold) modulated by the implant placement and vitamin D deficiency. Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses assigned the highest z-score to the circadian rhythm pathway including neuronal PAS domain 2 (NPAS2), and period homolog 2 (Per2). NPAS2 and Aryl hydrocarbon receptor nuclear translocator-like (ARNTL/Bmal 1) were upregulated around implant and diminished by vitamin D deficiency, whereas the expression pattern of Per2 was complementary. Hierarchical cluster analysis further revealed that NPAS2 was in a group predominantly composed of cartilage extracellular matrix (ECM) genes. Whereas the expression of bone ECM genes around implant was not significantly affected by vitamin D deficiency, cartilage ECM genes were modulated by the presence of the implant and vitamin D status. In a proof-of-concept in vitro study, the expression of cartilage type II and X collagens was found upregulated when mouse mesenchymal stem cells were cultured on implant disk with 1,25D supplementation. Conclusions This study suggests that the circadian rhythm system and cartilage extracellular matrix may be involved in the establishment of osseointegration under vitamin D regulation. PMID:21264318

Identification of intracellular proteins and signaling pathways in human endothelial cells regulated by angiotensin-(1-7).

PubMed

Meinert, Christian; Gembardt, Florian; Böhme, Ilka; Tetzner, Anja; Wieland, Thomas; Greenberg, Barry; Walther, Thomas

2016-01-01

The study aimed to identify proteins regulated by the cardiovascular protective peptide angiotensin-(1-7) and to determine potential intracellular signaling cascades. Human endothelial cells were stimulated with Ang-(1-7) for 1 h, 3 h, 6 h, and 9 h. Peptide effects on intracellular signaling were assessed via antibody microarray, containing antibodies against 725 proteins. Bioinformatics software was used to identify affected intracellular signaling pathways. Microarray data was verified exemplarily by Western blot, Real-Time RT-PCR, and immunohistochemical studies. The microarray identified 110 regulated proteins after 1 h, 119 after 3 h, 31 after 6 h, and 86 after 9 h Ang-(1-7) stimulation. Regulated proteins were associated with high significance to several metabolic pathways like “Molecular Mechanism of Cancer” and “p53 signaling” in a time dependent manner. Exemplarily, Western blots for the E3-type small ubiquitin-like modifier ligase PIAS2 confirmed the microarray data and displayed a decrease by more than 50% after Ang-(1-7) stimulation at 1 h and 3 h without affecting its mRNA. Immunohistochemical studies with PIAS2 in human endothelial cells showed a decrease in cytoplasmic PIAS2 after Ang-(1-7) treatment. The Ang-(1-7) mediated decrease of PIAS2 was reproduced in other endothelial cell types. The results suggest that angiotensin-(1-7) plays a role in metabolic pathways related to cell death and cell survival in human endothelial cells.

Microarray expression profiling in adhesion and normal peritoneal tissues.

PubMed

Ambler, Dana R; Golden, Alicia M; Gell, Jennifer S; Saed, Ghassan M; Carey, David J; Diamond, Michael P

2012-05-01

To identify molecular markers associated with adhesion and normal peritoneal tissue using microarray expression profiling. Comparative study. University hospital. Five premenopausal women. Adhesion and normal peritoneal tissue samples were obtained from premenopausal women. Ribonucleic acid was extracted using standard protocols and processed for hybridization to Affymetrix Whole Transcript Human Gene Expression Chips. Microarray data were obtained from five different patients, each with adhesion tissue and normal peritoneal samples. Real-time polymerase chain reaction was performed for confirmation using standard protocols. Gene expression in postoperative adhesion and normal peritoneal tissues. A total of 1,263 genes were differentially expressed between adhesion and normal tissues. One hundred seventy-three genes were found to be up-regulated and 56 genes were down-regulated in the adhesion tissues compared with normal peritoneal tissues. The genes were sorted into functional categories according to Gene Ontology annotations. Twenty-six up-regulated genes and 11 down-regulated genes were identified with functions potentially relevant to the pathophysiology of postoperative adhesions. We evaluated and confirmed expression of 12 of these specific genes via polymerase chain reaction. The pathogenesis, natural history, and optimal treatment of postoperative adhesive disease remains unanswered. Microarray analysis of adhesions identified specific genes with increased and decreased expression when compared with normal peritoneum. Knowledge of these genes and ontologic pathways with altered expression provide targets for new therapies to treat patients who have or are at risk for postoperative adhesions. Copyright © 2012 American Society for Reproductive Medicine. Published by Elsevier Inc. All rights reserved.

Microarray analysis of genes differentially expressed in HepG2 cells cultured in simulated microgravity: preliminary report

NASA Technical Reports Server (NTRS)

Khaoustov, V. I.; Risin, D.; Pellis, N. R.; Yoffe, B.; McIntire, L. V. (Principal Investigator)

2001-01-01

Developed at NASA, the rotary cell culture system (RCCS) allows the creation of unique microgravity environment of low shear force, high-mass transfer, and enables three-dimensional (3D) cell culture of dissimilar cell types. Recently we demonstrated that a simulated microgravity is conducive for maintaining long-term cultures of functional hepatocytes and promote 3D cell assembly. Using deoxyribonucleic acid (DNA) microarray technology, it is now possible to measure the levels of thousands of different messenger ribonucleic acids (mRNAs) in a single hybridization step. This technique is particularly powerful for comparing gene expression in the same tissue under different environmental conditions. The aim of this research was to analyze gene expression of hepatoblastoma cell line (HepG2) during early stage of 3D-cell assembly in simulated microgravity. For this, mRNA from HepG2 cultured in the RCCS was analyzed by deoxyribonucleic acid microarray. Analyses of HepG2 mRNA by using 6K glass DNA microarray revealed changes in expression of 95 genes (overexpression of 85 genes and downregulation of 10 genes). Our preliminary results indicated that simulated microgravity modifies the expression of several genes and that microarray technology may provide new understanding of the fundamental biological questions of how gravity affects the development and function of individual cells.

MAPPI-DAT: data management and analysis for protein-protein interaction data from the high-throughput MAPPIT cell microarray platform.

PubMed

Gupta, Surya; De Puysseleyr, Veronic; Van der Heyden, José; Maddelein, Davy; Lemmens, Irma; Lievens, Sam; Degroeve, Sven; Tavernier, Jan; Martens, Lennart

2017-05-01

Protein-protein interaction (PPI) studies have dramatically expanded our knowledge about cellular behaviour and development in different conditions. A multitude of high-throughput PPI techniques have been developed to achieve proteome-scale coverage for PPI studies, including the microarray based Mammalian Protein-Protein Interaction Trap (MAPPIT) system. Because such high-throughput techniques typically report thousands of interactions, managing and analysing the large amounts of acquired data is a challenge. We have therefore built the MAPPIT cell microArray Protein Protein Interaction-Data management & Analysis Tool (MAPPI-DAT) as an automated data management and analysis tool for MAPPIT cell microarray experiments. MAPPI-DAT stores the experimental data and metadata in a systematic and structured way, automates data analysis and interpretation, and enables the meta-analysis of MAPPIT cell microarray data across all stored experiments. MAPPI-DAT is developed in Python, using R for data analysis and MySQL as data management system. MAPPI-DAT is cross-platform and can be ran on Microsoft Windows, Linux and OS X/macOS. The source code and a Microsoft Windows executable are freely available under the permissive Apache2 open source license at https://github.com/compomics/MAPPI-DAT. jan.tavernier@vib-ugent.be or lennart.martens@vib-ugent.be. Supplementary data are available at Bioinformatics online. © The Author 2017. Published by Oxford University Press.

Genomic Analyses of Patients With Unexplained Early-Onset Scoliosis.

PubMed

Gao, Xiaochong; Gotway, Garrett; Rathjen, Karl; Johnston, Charles; Sparagana, Steven; Wise, Carol A

2014-09-01

To test for rare genetic mutations, a cohort of patients with unexplained early-onset scoliosis (EOS) was screened using high-density microarray genotyping. A cohort of patients with adolescent idiopathic scoliosis (AIS) was similarly screened and the results were compared. Patients with scoliosis in infancy or early childhood (EOS) are at high risk for progressive deformity and associated problems including respiratory compromise. Early-onset scoliosis is frequently associated with genetic disorders but many patients present with nonspecific clinical features and without an associated diagnosis. The authors hypothesized that EOS in these patients may be caused by rare genetic mutations detectable by next-generation genomic methods. The researchers identified 24 patients with unexplained EOS from pediatric orthopedic clinics. They genotyped them, along with 39 connecting family members, using the Illumina OmniExpress-12, version 1.0 beadchip. Resulting genotypes were analyzed for chromosomal changes, specifically copy number variation and absence of heterozygosity. They screened 482 adolescent idiopathic scoliosis (AIS) patients and 744 healthy controls, who were similarly genotyped with the same beadchip, for chromosomal changes identified in the EOS cohort. Copy number variation and absence of heterozygosity analyses revealed a genetic diagnosis of chromosome 15q24 microdeletion syndrome in 1 patient and maternal uniparental disomy of chromosome 14 in a second one. Prior genetic testing and clinical evaluations had been negative in both cases. A large novel chromosome 10 deletion was likely causal in a third EOS patient. These mutations identified in the EOS patients were absent in AIS patients and controls, and thus were not associated with AIS or found in asymptomatic individuals. These data underscore the usefulness of updated genetic evaluations including high-density microarray-based genotyping and other next-generation methods in patients with unexplained EOS, even when prior genetic studies were negative. These data also suggest the intriguing possibility that other mutations detectable by whole genome sequencing, as well as epigenetic effects, await discovery in the EOS population. Copyright © 2014 Scoliosis Research Society. Published by Elsevier Inc. All rights reserved.

Development and Comparison of Two Assay Formats for Parallel Detection of Four Biothreat Pathogens by Using Suspension Microarrays

PubMed Central

Janse, Ingmar; Bok, Jasper M.; Hamidjaja, Raditijo A.; Hodemaekers, Hennie M.; van Rotterdam, Bart J.

2012-01-01

Microarrays provide a powerful analytical tool for the simultaneous detection of multiple pathogens. We developed diagnostic suspension microarrays for sensitive and specific detection of the biothreat pathogens Bacillus anthracis, Yersinia pestis, Francisella tularensis and Coxiella burnetii. Two assay chemistries for amplification and labeling were developed, one method using direct hybridization and the other using target-specific primer extension, combined with hybridization to universal arrays. Asymmetric PCR products for both assay chemistries were produced by using a multiplex asymmetric PCR amplifying 16 DNA signatures (16-plex). The performances of both assay chemistries were compared and their advantages and disadvantages are discussed. The developed microarrays detected multiple signature sequences and an internal control which made it possible to confidently identify the targeted pathogens and assess their virulence potential. The microarrays were highly specific and detected various strains of the targeted pathogens. Detection limits for the different pathogen signatures were similar or slightly higher compared to real-time PCR. Probit analysis showed that even a few genomic copies could be detected with 95% confidence. The microarrays detected DNA from different pathogens mixed in different ratios and from spiked or naturally contaminated samples. The assays that were developed have a potential for application in surveillance and diagnostics. PMID:22355407

Development and comparison of two assay formats for parallel detection of four biothreat pathogens by using suspension microarrays.

PubMed

Janse, Ingmar; Bok, Jasper M; Hamidjaja, Raditijo A; Hodemaekers, Hennie M; van Rotterdam, Bart J

2012-01-01

Microarrays provide a powerful analytical tool for the simultaneous detection of multiple pathogens. We developed diagnostic suspension microarrays for sensitive and specific detection of the biothreat pathogens Bacillus anthracis, Yersinia pestis, Francisella tularensis and Coxiella burnetii. Two assay chemistries for amplification and labeling were developed, one method using direct hybridization and the other using target-specific primer extension, combined with hybridization to universal arrays. Asymmetric PCR products for both assay chemistries were produced by using a multiplex asymmetric PCR amplifying 16 DNA signatures (16-plex). The performances of both assay chemistries were compared and their advantages and disadvantages are discussed. The developed microarrays detected multiple signature sequences and an internal control which made it possible to confidently identify the targeted pathogens and assess their virulence potential. The microarrays were highly specific and detected various strains of the targeted pathogens. Detection limits for the different pathogen signatures were similar or slightly higher compared to real-time PCR. Probit analysis showed that even a few genomic copies could be detected with 95% confidence. The microarrays detected DNA from different pathogens mixed in different ratios and from spiked or naturally contaminated samples. The assays that were developed have a potential for application in surveillance and diagnostics.

Molecular Phylogenetic and Expression Analysis of the Complete WRKY Transcription Factor Family in Maize

PubMed Central

Wei, Kai-Fa; Chen, Juan; Chen, Yan-Feng; Wu, Ling-Juan; Xie, Dao-Xin

2012-01-01

The WRKY transcription factors function in plant growth and development, and response to the biotic and abiotic stresses. Although many studies have focused on the functional identification of the WRKY transcription factors, much less is known about molecular phylogenetic and global expression analysis of the complete WRKY family in maize. In this study, we identified 136 WRKY proteins coded by 119 genes in the B73 inbred line from the complete genome and named them in an orderly manner. Then, a comprehensive phylogenetic analysis of five species was performed to explore the origin and evolutionary patterns of these WRKY genes, and the result showed that gene duplication is the major driving force for the origin of new groups and subgroups and functional divergence during evolution. Chromosomal location analysis of maize WRKY genes indicated that 20 gene clusters are distributed unevenly in the genome. Microarray-based expression analysis has revealed that 131 WRKY transcripts encoded by 116 genes may participate in the regulation of maize growth and development. Among them, 102 transcripts are stably expressed with a coefficient of variation (CV) value of <15%. The remaining 29 transcripts produced by 25 WRKY genes with the CV value of >15% are further analysed to discover new organ- or tissue-specific genes. In addition, microarray analyses of transcriptional responses to drought stress and fungal infection showed that maize WRKY proteins are involved in stress responses. All these results contribute to a deep probing into the roles of WRKY transcription factors in maize growth and development and stress tolerance. PMID:22279089

Molecular phylogenetic and expression analysis of the complete WRKY transcription factor family in maize.

PubMed

Wei, Kai-Fa; Chen, Juan; Chen, Yan-Feng; Wu, Ling-Juan; Xie, Dao-Xin

2012-04-01

The WRKY transcription factors function in plant growth and development, and response to the biotic and abiotic stresses. Although many studies have focused on the functional identification of the WRKY transcription factors, much less is known about molecular phylogenetic and global expression analysis of the complete WRKY family in maize. In this study, we identified 136 WRKY proteins coded by 119 genes in the B73 inbred line from the complete genome and named them in an orderly manner. Then, a comprehensive phylogenetic analysis of five species was performed to explore the origin and evolutionary patterns of these WRKY genes, and the result showed that gene duplication is the major driving force for the origin of new groups and subgroups and functional divergence during evolution. Chromosomal location analysis of maize WRKY genes indicated that 20 gene clusters are distributed unevenly in the genome. Microarray-based expression analysis has revealed that 131 WRKY transcripts encoded by 116 genes may participate in the regulation of maize growth and development. Among them, 102 transcripts are stably expressed with a coefficient of variation (CV) value of <15%. The remaining 29 transcripts produced by 25 WRKY genes with the CV value of >15% are further analysed to discover new organ- or tissue-specific genes. In addition, microarray analyses of transcriptional responses to drought stress and fungal infection showed that maize WRKY proteins are involved in stress responses. All these results contribute to a deep probing into the roles of WRKY transcription factors in maize growth and development and stress tolerance.

Development of a promoter shutoff system in Aspergillus oryzae using a sorbitol-sensitive promoter.

PubMed

Oda, Ken; Terado, Shiho; Toyoura, Rieko; Fukuda, Hisashi; Kawauchi, Moriyuki; Iwashita, Kazuhiro

2016-09-01

Promoter shutoff is a general method for analyzing essential genes, but in the fungus Aspergillus oryzae, no tightly repressed promoters have been reported. To overcome the current limitations of conditional promoters, we examined sorbitol- and galactose-responsive genes using microarrays to identify regulatable genes with only minor physiological and genetic effects. We identified two sorbitol-induced genes (designated as sorA and sorB), cloned their promoters, and built a regulated egfp and brlA expression system. Growth medium-dependent enhanced green fluorescence protein (EGFP) fluorescence and conidiation were confirmed for egfp and brlA under the control of their respective promoters. We also used this shutoff system to regulate the essential rhoA, which demonstrated the expected growth inhibition under repressed growth conditions. Our new sorbitol promoter shutoff system developed can serve as a valuable new tool for essential gene analyses of filamentous fungi.

Transcriptional Profiling of Hypoxic Neural Stem Cells Identifies Calcineurin-NFATc4 Signaling as a Major Regulator of Neural Stem Cell Biology

PubMed Central

Moreno, Marta; Fernández, Virginia; Monllau, Josep M.; Borrell, Víctor; Lerin, Carles; de la Iglesia, Núria

2015-01-01

Summary Neural stem cells (NSCs) reside in a hypoxic microenvironment within the brain. However, the crucial transcription factors (TFs) that regulate NSC biology under physiologic hypoxia are poorly understood. Here we have performed gene set enrichment analysis (GSEA) of microarray datasets from hypoxic versus normoxic NSCs with the aim of identifying pathways and TFs that are activated under oxygen concentrations mimicking normal brain tissue microenvironment. Integration of TF target (TFT) and pathway enrichment analysis identified the calcium-regulated TF NFATc4 as a major candidate to regulate hypoxic NSC functions. Nfatc4 expression was coordinately upregulated by top hypoxia-activated TFs, while NFATc4 target genes were enriched in hypoxic NSCs. Loss-of-function analyses further revealed that the calcineurin-NFATc4 signaling axis acts as a major regulator of NSC self-renewal and proliferation in vitro and in vivo by promoting the expression of TFs, including Id2, that contribute to the maintenance of the NSC state. PMID:26235896

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

PubMed Central

2010-01-01

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. Conclusions These results suggest that microarray analysis of chemical-induced spore formation is an excellent system to specifically identify genes necessary for the core sporulation process of a Gram negative model organism for differentiation. PMID:20420673

Identification of a gene set to evaluate the potential effects of loud sounds from seismic surveys on the ears of fishes: a study with Salmo salar

PubMed Central

Andrews, C D; Payne, J F; Rise, M L

2014-01-01

Functional genomic studies were carried out on the inner ear of Atlantic salmon Salmo salar following exposure to a seismic airgun. Microarray analyses revealed 79 unique transcripts (passing background threshold), with 42 reproducibly up-regulated and 37 reproducibly down-regulated in exposed v. control fish. Regarding the potential effects on cellular energetics and cellular respiration, altered transcripts included those with roles in oxygen transport, the glycolytic pathway, the Krebs cycle and the electron transport chain. Of these, a number of transcripts encoding haemoglobins that are important in oxygen transport were up-regulated and among the most highly expressed. Up-regulation of transcripts encoding nicotinamide riboside kinase 2, which is also important in energy production and linked to nerve cell damage, points to evidence of neuronal damage in the ear following noise exposure. Transcripts related to protein modification or degradation also indicated potential damaging effects of sound on ear tissues. Notable in this regard were transcripts associated with the proteasome–ubiquitin pathway, which is involved in protein degradation, with the transcript encoding ubiquitin family domain-containing protein 1 displaying the highest response to exposure. The differential expression of transcripts observed for some immune responses could potentially be linked to the rupture of cell membranes. Meanwhile, the altered expression of transcripts for cytoskeletal proteins that contribute to the structural integrity of the inner ear could point to repair or regeneration of ear tissues including auditory hair cells. Regarding potential effects on hormones and vitamins, the protein carrier for thyroxine and retinol (vitamin A), namely transthyretin, was altered at the transcript expression level and it has been suggested from studies in mammalian systems that retinoic acid may play a role in the regeneration of damaged hair cells. The microarray experiment identified the transcript encoding growth hormone I as up-regulated by loud sound, supporting previous evidence linking growth hormone to hair cell regeneration in fishes. Quantitative (q) reverse transcription (RT) polymerase chain reaction (qRT-PCR) analyses confirmed dysregulation of some microarray-identified transcripts and in some cases revealed a high level of biological variability in the exposed group. These results support the potential utility of molecular biomarkers to evaluate the effect of seismic surveys on fishes with studies on the ears being placed in a priority category for development of exposure–response relationships. Knowledge of such relationships is necessary for addressing the question of potential size of injury zones. PMID:24814183

DOE Office of Scientific and Technical Information (OSTI.GOV)

Andersen, G.L.; He, Z.; DeSantis, T.Z.

Microarrays have proven to be a useful and high-throughput method to provide targeted DNA sequence information for up to many thousands of specific genetic regions in a single test. A microarray consists of multiple DNA oligonucleotide probes that, under high stringency conditions, hybridize only to specific complementary nucleic acid sequences (targets). A fluorescent signal indicates the presence and, in many cases, the abundance of genetic regions of interest. In this chapter we will look at how microarrays are used in microbial ecology, especially with the recent increase in microbial community DNA sequence data. Of particular interest to microbial ecologists, phylogeneticmore » microarrays are used for the analysis of phylotypes in a community and functional gene arrays are used for the analysis of functional genes, and, by inference, phylotypes in environmental samples. A phylogenetic microarray that has been developed by the Andersen laboratory, the PhyloChip, will be discussed as an example of a microarray that targets the known diversity within the 16S rRNA gene to determine microbial community composition. Using multiple, confirmatory probes to increase the confidence of detection and a mismatch probe for every perfect match probe to minimize the effect of cross-hybridization by non-target regions, the PhyloChip is able to simultaneously identify any of thousands of taxa present in an environmental sample. The PhyloChip is shown to reveal greater diversity within a community than rRNA gene sequencing due to the placement of the entire gene product on the microarray compared with the analysis of up to thousands of individual molecules by traditional sequencing methods. A functional gene array that has been developed by the Zhou laboratory, the GeoChip, will be discussed as an example of a microarray that dynamically identifies functional activities of multiple members within a community. The recent version of GeoChip contains more than 24,000 50mer oligonucleotide probes and covers more than 10,000 gene sequences in 150 gene categories involved in carbon, nitrogen, sulfur, and phosphorus cycling, metal resistance and reduction, and organic contaminant degradation. GeoChip can be used as a generic tool for microbial community analysis, and also link microbial community structure to ecosystem functioning. Examples of the application of both arrays in different environmental samples will be described in the two subsequent sections.« less

Gene expression patterns combined with network analysis identify hub genes associated with bladder cancer.

PubMed

Bi, Dongbin; Ning, Hao; Liu, Shuai; Que, Xinxiang; Ding, Kejia

2015-06-01

To explore molecular mechanisms of bladder cancer (BC), network strategy was used to find biomarkers for early detection and diagnosis. The differentially expressed genes (DEGs) between bladder carcinoma patients and normal subjects were screened using empirical Bayes method of the linear models for microarray data package. Co-expression networks were constructed by differentially co-expressed genes and links. Regulatory impact factors (RIF) metric was used to identify critical transcription factors (TFs). The protein-protein interaction (PPI) networks were constructed by the Search Tool for the Retrieval of Interacting Genes/Proteins (STRING) and clusters were obtained through molecular complex detection (MCODE) algorithm. Centralities analyses for complex networks were performed based on degree, stress and betweenness. Enrichment analyses were performed based on Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) databases. Co-expression networks and TFs (based on expression data of global DEGs and DEGs in different stages and grades) were identified. Hub genes of complex networks, such as UBE2C, ACTA2, FABP4, CKS2, FN1 and TOP2A, were also obtained according to analysis of degree. In gene enrichment analyses of global DEGs, cell adhesion, proteinaceous extracellular matrix and extracellular matrix structural constituent were top three GO terms. ECM-receptor interaction, focal adhesion, and cell cycle were significant pathways. Our results provide some potential underlying biomarkers of BC. However, further validation is required and deep studies are needed to elucidate the pathogenesis of BC. Copyright © 2015 Elsevier Ltd. All rights reserved.

Allogeneic T cell responses are regulated by a specific miRNA-mRNA network

PubMed Central

Sun, Yaping; Tawara, Isao; Zhao, Meng; Qin, Zhaohui S.; Toubai, Tomomi; Mathewson, Nathan; Tamaki, Hiroya; Nieves, Evelyn; Chinnaiyan, Arul M.; Reddy, Pavan

2013-01-01

Donor T cells that respond to host alloantigens following allogeneic bone marrow transplantation (BMT) induce graft-versus-host (GVH) responses, but their molecular landscape is not well understood. MicroRNAs (miRNAs) regulate gene (mRNA) expression and fine-tune the molecular responses of T cells. We stimulated naive T cells with either allogeneic or nonspecific stimuli and used argonaute cross-linked immunoprecipitation (CLIP) with subsequent ChIP microarray analyses to profile miR responses and their direct mRNA targets. We identified a unique expression pattern of miRs and mRNAs following the allostimulation of T cells and a high correlation between the expression of the identified miRs and a reduction of their mRNA targets. miRs and mRNAs that were predicted to be differentially regulated in allogeneic T cells compared with nonspecifically stimulated T cells were validated in vitro. These analyses identified wings apart-like homolog (Wapal) and synaptojanin 1 (Synj1) as potential regulators of allogeneic T cell responses. The expression of these molecular targets in vivo was confirmed in MHC-mismatched experimental BMT. Targeted silencing of either Wapal or Synj1 prevented the development of GVH response, confirming a role for these regulators in allogeneic T cell responses. Thus, this genome-wide analysis of miRNA-mRNA interactions identifies previously unrecognized molecular regulators of T cell responses. PMID:24216511

Profiling protein function with small molecule microarrays

PubMed Central

Winssinger, Nicolas; Ficarro, Scott; Schultz, Peter G.; Harris, Jennifer L.

2002-01-01

The regulation of protein function through posttranslational modification, local environment, and protein–protein interaction is critical to cellular function. The ability to analyze on a genome-wide scale protein functional activity rather than changes in protein abundance or structure would provide important new insights into complex biological processes. Herein, we report the application of a spatially addressable small molecule microarray to an activity-based profile of proteases in crude cell lysates. The potential of this small molecule-based profiling technology is demonstrated by the detection of caspase activation upon induction of apoptosis, characterization of the activated caspase, and inhibition of the caspase-executed apoptotic phenotype using the small molecule inhibitor identified in the microarray-based profile. PMID:12167675

BATS: a Bayesian user-friendly software for analyzing time series microarray experiments.

PubMed

Angelini, Claudia; Cutillo, Luisa; De Canditiis, Daniela; Mutarelli, Margherita; Pensky, Marianna

2008-10-06

Gene expression levels in a given cell can be influenced by different factors, namely pharmacological or medical treatments. The response to a given stimulus is usually different for different genes and may depend on time. One of the goals of modern molecular biology is the high-throughput identification of genes associated with a particular treatment or a biological process of interest. From methodological and computational point of view, analyzing high-dimensional time course microarray data requires very specific set of tools which are usually not included in standard software packages. Recently, the authors of this paper developed a fully Bayesian approach which allows one to identify differentially expressed genes in a 'one-sample' time-course microarray experiment, to rank them and to estimate their expression profiles. The method is based on explicit expressions for calculations and, hence, very computationally efficient. The software package BATS (Bayesian Analysis of Time Series) presented here implements the methodology described above. It allows an user to automatically identify and rank differentially expressed genes and to estimate their expression profiles when at least 5-6 time points are available. The package has a user-friendly interface. BATS successfully manages various technical difficulties which arise in time-course microarray experiments, such as a small number of observations, non-uniform sampling intervals and replicated or missing data. BATS is a free user-friendly software for the analysis of both simulated and real microarray time course experiments. The software, the user manual and a brief illustrative example are freely available online at the BATS website: http://www.na.iac.cnr.it/bats.

ARACNe-based inference, using curated microarray data, of Arabidopsis thaliana root transcriptional regulatory networks

PubMed Central

2014-01-01

Background Uncovering the complex transcriptional regulatory networks (TRNs) that underlie plant and animal development remains a challenge. However, a vast amount of data from public microarray experiments is available, which can be subject to inference algorithms in order to recover reliable TRN architectures. Results In this study we present a simple bioinformatics methodology that uses public, carefully curated microarray data and the mutual information algorithm ARACNe in order to obtain a database of transcriptional interactions. We used data from Arabidopsis thaliana root samples to show that the transcriptional regulatory networks derived from this database successfully recover previously identified root transcriptional modules and to propose new transcription factors for the SHORT ROOT/SCARECROW and PLETHORA pathways. We further show that these networks are a powerful tool to integrate and analyze high-throughput expression data, as exemplified by our analysis of a SHORT ROOT induction time-course microarray dataset, and are a reliable source for the prediction of novel root gene functions. In particular, we used our database to predict novel genes involved in root secondary cell-wall synthesis and identified the MADS-box TF XAL1/AGL12 as an unexpected participant in this process. Conclusions This study demonstrates that network inference using carefully curated microarray data yields reliable TRN architectures. In contrast to previous efforts to obtain root TRNs, that have focused on particular functional modules or tissues, our root transcriptional interactions provide an overview of the transcriptional pathways present in Arabidopsis thaliana roots and will likely yield a plethora of novel hypotheses to be tested experimentally. PMID:24739361

Linking microarray reporters with protein functions.

PubMed

Gaj, Stan; van Erk, Arie; van Haaften, Rachel I M; Evelo, Chris T A

2007-09-26

The analysis of microarray experiments requires accurate and up-to-date functional annotation of the microarray reporters to optimize the interpretation of the biological processes involved. Pathway visualization tools are used to connect gene expression data with existing biological pathways by using specific database identifiers that link reporters with elements in the pathways. This paper proposes a novel method that aims to improve microarray reporter annotation by BLASTing the original reporter sequences against a species-specific EMBL subset, that was derived from and crosslinked back to the highly curated UniProt database. The resulting alignments were filtered using high quality alignment criteria and further compared with the outcome of a more traditional approach, where reporter sequences were BLASTed against EnsEMBL followed by locating the corresponding protein (UniProt) entry for the high quality hits. Combining the results of both methods resulted in successful annotation of > 58% of all reporter sequences with UniProt IDs on two commercial array platforms, increasing the amount of Incyte reporters that could be coupled to Gene Ontology terms from 32.7% to 58.3% and to a local GenMAPP pathway from 9.6% to 16.7%. For Agilent, 35.3% of the total reporters are now linked towards GO nodes and 7.1% on local pathways. Our methods increased the annotation quality of microarray reporter sequences and allowed us to visualize more reporters using pathway visualization tools. Even in cases where the original reporter annotation showed the correct description the new identifiers often allowed improved pathway and Gene Ontology linking. These methods are freely available at http://www.bigcat.unimaas.nl/public/publications/Gaj_Annotation/.

Quantification of viable and non-viable Legionella spp. by heterogeneous asymmetric recombinase polymerase amplification (haRPA) on a flow-based chemiluminescence microarray.

PubMed

Kober, Catharina; Niessner, Reinhard; Seidel, Michael

2018-02-15

Increasing numbers of legionellosis outbreaks within the last years have shown that Legionella are a growing challenge for public health. Molecular biological detection methods capable of rapidly identifying viable Legionella are important for the control of engineered water systems. The current gold standard based on culture methods takes up to 10 days to show positive results. For this reason, a flow-based chemiluminescence (CL) DNA microarray was developed that is able to quantify viable and non-viable Legionella spp. as well as Legionella pneumophila in one hour. An isothermal heterogeneous asymmetric recombinase polymerase amplification (haRPA) was carried out on flow-based CL DNA microarrays. Detection limits of 87 genomic units (GU) µL -1 and 26GUµL -1 for Legionella spp. and Legionella pneumophila, respectively, were achieved. In this work, it was shown for the first time that the combination of a propidium monoazide (PMA) treatment with haRPA, the so-called viability haRPA, is able to identify viable Legionella on DNA microarrays. Different proportions of viable and non-viable Legionella, shown with the example of L. pneumophila, ranging in a total concentration between 10 1 to 10 5 GUµL -1 were analyzed on the microarray analysis platform MCR 3. Recovery values for viable Legionella spp. were found between 81% and 133%. With the combination of these two methods, there is a chance to replace culture-based methods in the future for the monitoring of engineered water systems like condensation recooling plants. Copyright © 2017 Elsevier B.V. All rights reserved.

Pro-oncogene Pokemon promotes breast cancer progression by upregulating survivin expression.

PubMed

Zu, Xuyu; Ma, Jun; Liu, Hongxia; Liu, Feng; Tan, Chunyan; Yu, Lingling; Wang, Jue; Xie, Zhenhua; Cao, Deliang; Jiang, Yuyang

2011-03-10

Pokemon is an oncogenic transcription factor involved in cell growth, differentiation and oncogenesis, but little is known about its role in human breast cancer. In this study, we aimed to reveal the role of Pokemon in breast cancer progression and patient survival and to understand its underlying mechanisms. Tissue microarray analysis of breast cancer tissues from patients with complete clinicopathological data and more than 20 years of follow-up were used to evaluate Pokemon expression and its correlation with the progression and prognosis of the disease. DNA microarray analysis of MCF-7 cells that overexpress Pokemon was used to identify Pokemon target genes. Chromatin immunoprecipitation (ChIP) and site-directed mutagenesis were utilized to determine how Pokemon regulates survivin expression, a target gene. Pokemon was found to be overexpressed in 158 (86.8%) of 182 breast cancer tissues, and its expression was correlated with tumor size (P = 0.0148) and lymph node metastasis (P = 0.0014). Pokemon expression led to worse overall (n = 175, P = 0.01) and disease-related (n = 79, P = 0.0134) patient survival. DNA microarray analyses revealed that in MCF-7 breast cancer cells, Pokemon regulates the expression of at least 121 genes involved in several signaling and metabolic pathways, including anti-apoptotic survivin. In clinical specimens, Pokemon and survivin expression were highly correlated (n = 49, r = 0.6799, P < 0.0001). ChIP and site-directed mutagenesis indicated that Pokemon induces survivin expression by binding to the GT boxes in its promoter. Pokemon promotes breast cancer progression by upregulating survivin expression and thus may be a potential target for the treatment of this malignancy.

Pro-oncogene Pokemon promotes breast cancer progression by upregulating survivin expression

PubMed Central

2011-01-01

Introduction Pokemon is an oncogenic transcription factor involved in cell growth, differentiation and oncogenesis, but little is known about its role in human breast cancer. In this study, we aimed to reveal the role of Pokemon in breast cancer progression and patient survival and to understand its underlying mechanisms. Methods Tissue microarray analysis of breast cancer tissues from patients with complete clinicopathological data and more than 20 years of follow-up were used to evaluate Pokemon expression and its correlation with the progression and prognosis of the disease. DNA microarray analysis of MCF-7 cells that overexpress Pokemon was used to identify Pokemon target genes. Chromatin immunoprecipitation (ChIP) and site-directed mutagenesis were utilized to determine how Pokemon regulates survivin expression, a target gene. Results Pokemon was found to be overexpressed in 158 (86.8%) of 182 breast cancer tissues, and its expression was correlated with tumor size (P = 0.0148) and lymph node metastasis (P = 0.0014). Pokemon expression led to worse overall (n = 175, P = 0.01) and disease-related (n = 79, P = 0.0134) patient survival. DNA microarray analyses revealed that in MCF-7 breast cancer cells, Pokemon regulates the expression of at least 121 genes involved in several signaling and metabolic pathways, including anti-apoptotic survivin. In clinical specimens, Pokemon and survivin expression were highly correlated (n = 49, r = 0.6799, P < 0.0001). ChIP and site-directed mutagenesis indicated that Pokemon induces survivin expression by binding to the GT boxes in its promoter. Conclusions Pokemon promotes breast cancer progression by upregulating survivin expression and thus may be a potential target for the treatment of this malignancy. PMID:21392388

Microarray analysis of long non-coding RNA expression profiles in monocytic myeloid-derived suppressor cells in Echinococcus granulosus-infected mice.

PubMed

Yu, Aiping; Wang, Ying; Yin, Jianhai; Zhang, Jing; Cao, Shengkui; Cao, Jianping; Shen, Yujuan

2018-05-30

Cystic echinococcosis is a worldwide chronic zoonotic disease caused by infection with the larval stage of Echinococcus granulosus. Previously, we found significant accumulation of myeloid-derived suppressor cells (MDSCs) in E. granulosus infection mouse models and that they play a key role in immunosuppressing T lymphocytes. Here, we compared the long non-coding RNA (lncRNA) and mRNA expression patterns between the splenic monocytic MDSCs (M-MDSCs) of E. granulosus protoscoleces-infected mice and normal mice using microarray analysis. LncRNA functions were predicted using Gene Ontology enrichment and the Kyoto Encyclopedia of Genes and Genomes pathway analysis. Cis- and trans-regulation analyses revealed potential relationships between the lncRNAs and their target genes or related transcription factors. We found that 649 lncRNAs were differentially expressed (fold change ≥ 2, P < 0.05): 582 lncRNAs were upregulated and 67 lncRNAs were downregulated; respectively, 28 upregulated mRNAs and 1043 downregulated mRNAs were differentially expressed. The microarray data was validated by quantitative reverse transcription-PCR. The results indicated that mRNAs co-expressed with the lncRNAs are mainly involved in regulating the actin cytoskeleton, Salmonella infection, leishmaniasis, and the vascular endothelial growth factor (VEGF) signaling pathway. The lncRNA NONMMUT021591 was predicted to cis-regulate the retinoblastoma gene (Rb1), whose expression is associated with abnormal M-MDSCs differentiation. We found that 372 lncRNAs were predicted to interact with 60 transcription factors; among these, C/EBPβ (CCAAT/enhancer binding protein beta) was previously demonstrated to be a transcription factor of MDSCs. Our study identified dysregulated lncRNAs in the M-MDSCs of E. granulosus infection mouse models; they might be involved in M-MDSC-derived immunosuppression in related diseases.

Characterization of a novel Lactobacillus species closely related to Lactobacillus johnsonii using a combination of molecular and comparative genomics methods.

PubMed

Sarmiento-Rubiano, Luz-Adriana; Berger, Bernard; Moine, Déborah; Zúñiga, Manuel; Pérez-Martínez, Gaspar; Yebra, María J

2010-09-17

Comparative genomic hybridization (CGH) constitutes a powerful tool for identification and characterization of bacterial strains. In this study we have applied this technique for the characterization of a number of Lactobacillus strains isolated from the intestinal content of rats fed with a diet supplemented with sorbitol. Phylogenetic analysis based on 16S rRNA gene, recA, pheS, pyrG and tuf sequences identified five bacterial strains isolated from the intestinal content of rats as belonging to the recently described Lactobacillus taiwanensis species. DNA-DNA hybridization experiments confirmed that these five strains are distinct but closely related to Lactobacillus johnsonii and Lactobacillus gasseri. A whole genome DNA microarray designed for the probiotic L. johnsonii strain NCC533 was used for CGH analysis of L. johnsonii ATCC 33200T, L. johnsonii BL261, L. gasseri ATCC 33323T and L. taiwanensis BL263. In these experiments, the fluorescence ratio distributions obtained with L. taiwanensis and L. gasseri showed characteristic inter-species profiles. The percentage of conserved L. johnsonii NCC533 genes was about 83% in the L. johnsonii strains comparisons and decreased to 51% and 47% for L. taiwanensis and L. gasseri, respectively. These results confirmed the separate status of L. taiwanensis from L. johnsonii at the level of species, and also that L. taiwanensis is closer to L. johnsonii than L. gasseri is to L. johnsonii. Conventional taxonomic analyses and microarray-based CGH analysis have been used for the identification and characterization of the newly species L. taiwanensis. The microarray-based CGH technology has been shown as a remarkable tool for the identification and fine discrimination between phylogenetically close species, and additionally provided insight into the adaptation of the strain L. taiwanensis BL263 to its ecological niche.

Integrated analysis of chromosome copy number variation and gene expression in cervical carcinoma

PubMed Central

Yan, Deng; Yi, Song; Chiu, Wang Chi; Qin, Liu Gui; Kin, Wong Hoi; Kwok Hung, Chung Tony; Linxiao, Han; Wai, Choy Kwong; Yi, Sui; Tao, Yang; Tao, Tang

2017-01-01

Objective This study was conducted to explore chromosomal copy number variations (CNV) and transcript expression and to examine pathways in cervical pathogenesis using genome-wide high resolution microarrays. Methods Genome-wide chromosomal CNVs were investigated in 6 cervical cancer cell lines by Human Genome CGH Microarray Kit (4x44K). Gene expression profiles in cervical cancer cell lines, primary cervical carcinoma and normal cervical epithelium tissues were also studied using the Whole Human Genome Microarray Kit (4x44K). Results Fifty common chromosomal CNVs were identified in the cervical cancer cell lines. Correlation analysis revealed that gene up-regulation or down-regulation is significantly correlated with genomic amplification (P=0.009) or deletion (P=0.006) events. Expression profiles were identified through cluster analysis. Gene annotation analysis pinpointed cell cycle pathways was significantly (P=1.15E-08) affected in cervical cancer. Common CNVs were associated with cervical cancer. Conclusion Chromosomal CNVs may contribute to their transcript expression in cervical cancer. PMID:29312578

Suppression subtractive hybridization as a tool to identify anthocyanin metabolism-related genes in apple skin.

PubMed

Ban, Yusuke; Moriguchi, Takaya

2010-01-01

The pigmentation of anthocyanins is one of the important determinants for consumer preference and marketability in horticultural crops such as fruits and flowers. To elucidate the mechanisms underlying the physiological process leading to the pigmentation of anthocyanins, identification of the genes differentially expressed in response to anthocyanin accumulation is a useful strategy. Currently, microarrays have been widely used to isolate differentially expressed genes. However, the use of microarrays is limited by its high cost of special apparatus and materials. Therefore, availability of microarrays is limited and does not come into common use at present. Suppression subtractive hybridization (SSH) is an alternative tool that has been widely used to identify differentially expressed genes due to its easy handling and relatively low cost. This chapter describes the procedures for SSH, including RNA extraction from polysaccharides and polyphenol-rich samples, poly(A)+ RNA purification, evaluation of subtraction efficiency, and differential screening using reverse northern in apple skin.

Integrated analysis of chromosome copy number variation and gene expression in cervical carcinoma.

PubMed

Yan, Deng; Yi, Song; Chiu, Wang Chi; Qin, Liu Gui; Kin, Wong Hoi; Kwok Hung, Chung Tony; Linxiao, Han; Wai, Choy Kwong; Yi, Sui; Tao, Yang; Tao, Tang

2017-12-12

This study was conducted to explore chromosomal copy number variations (CNV) and transcript expression and to examine pathways in cervical pathogenesis using genome-wide high resolution microarrays. Genome-wide chromosomal CNVs were investigated in 6 cervical cancer cell lines by Human Genome CGH Microarray Kit (4x44K). Gene expression profiles in cervical cancer cell lines, primary cervical carcinoma and normal cervical epithelium tissues were also studied using the Whole Human Genome Microarray Kit (4x44K). Fifty common chromosomal CNVs were identified in the cervical cancer cell lines. Correlation analysis revealed that gene up-regulation or down-regulation is significantly correlated with genomic amplification ( P =0.009) or deletion ( P =0.006) events. Expression profiles were identified through cluster analysis. Gene annotation analysis pinpointed cell cycle pathways was significantly ( P =1.15E-08) affected in cervical cancer. Common CNVs were associated with cervical cancer. Chromosomal CNVs may contribute to their transcript expression in cervical cancer.

Analysis of Temporal-spatial Co-variation within Gene Expression Microarray Data in an Organogenesis Model

NASA Astrophysics Data System (ADS)

Ehler, Martin; Rajapakse, Vinodh; Zeeberg, Barry; Brooks, Brian; Brown, Jacob; Czaja, Wojciech; Bonner, Robert F.

The gene networks underlying closure of the optic fissure during vertebrate eye development are poorly understood. We used a novel clustering method based on Laplacian Eigenmaps, a nonlinear dimension reduction method, to analyze microarray data from laser capture microdissected (LCM) cells at the site and developmental stages (days 10.5 to 12.5) of optic fissure closure. Our new method provided greater biological specificity than classical clustering algorithms in terms of identifying more biological processes and functions related to eye development as defined by Gene Ontology at lower false discovery rates. This new methodology builds on the advantages of LCM to isolate pure phenotypic populations within complex tissues and allows improved ability to identify critical gene products expressed at lower copy number. The combination of LCM of embryonic organs, gene expression microarrays, and extracting spatial and temporal co-variations appear to be a powerful approach to understanding the gene regulatory networks that specify mammalian organogenesis.

nuID: a universal naming scheme of oligonucleotides for Illumina, Affymetrix, and other microarrays

PubMed Central

Du, Pan; Kibbe, Warren A; Lin, Simon M

2007-01-01

Background Oligonucleotide probes that are sequence identical may have different identifiers between manufacturers and even between different versions of the same company's microarray; and sometimes the same identifier is reused and represents a completely different oligonucleotide, resulting in ambiguity and potentially mis-identification of the genes hybridizing to that probe. Results We have devised a unique, non-degenerate encoding scheme that can be used as a universal representation to identify an oligonucleotide across manufacturers. We have named the encoded representation 'nuID', for nucleotide universal identifier. Inspired by the fact that the raw sequence of the oligonucleotide is the true definition of identity for a probe, the encoding algorithm uniquely and non-degenerately transforms the sequence itself into a compact identifier (a lossless compression). In addition, we added a redundancy check (checksum) to validate the integrity of the identifier. These two steps, encoding plus checksum, result in an nuID, which is a unique, non-degenerate, permanent, robust and efficient representation of the probe sequence. For commercial applications that require the sequence identity to be confidential, we have an encryption schema for nuID. We demonstrate the utility of nuIDs for the annotation of Illumina microarrays, and we believe it has universal applicability as a source-independent naming convention for oligomers. Reviewers This article was reviewed by Itai Yanai, Rong Chen (nominated by Mark Gerstein), and Gregory Schuler (nominated by David Lipman). PMID:17540033

Transformation and model choice for RNA-seq co-expression analysis.

PubMed

Rau, Andrea; Maugis-Rabusseau, Cathy

2018-05-01

Although a large number of clustering algorithms have been proposed to identify groups of co-expressed genes from microarray data, the question of if and how such methods may be applied to RNA sequencing (RNA-seq) data remains unaddressed. In this work, we investigate the use of data transformations in conjunction with Gaussian mixture models for RNA-seq co-expression analyses, as well as a penalized model selection criterion to select both an appropriate transformation and number of clusters present in the data. This approach has the advantage of accounting for per-cluster correlation structures among samples, which can be strong in RNA-seq data. In addition, it provides a rigorous statistical framework for parameter estimation, an objective assessment of data transformations and number of clusters and the possibility of performing diagnostic checks on the quality and homogeneity of the identified clusters. We analyze four varied RNA-seq data sets to illustrate the use of transformations and model selection in conjunction with Gaussian mixture models. Finally, we propose a Bioconductor package coseq (co-expression of RNA-seq data) to facilitate implementation and visualization of the recommended RNA-seq co-expression analyses.

Performance of automated scoring of ER, PR, HER2, CK5/6 and EGFR in breast cancer tissue microarrays in the Breast Cancer Association Consortium

PubMed Central

Howat, William J; Blows, Fiona M; Provenzano, Elena; Brook, Mark N; Morris, Lorna; Gazinska, Patrycja; Johnson, Nicola; McDuffus, Leigh‐Anne; Miller, Jodi; Sawyer, Elinor J; Pinder, Sarah; van Deurzen, Carolien H M; Jones, Louise; Sironen, Reijo; Visscher, Daniel; Caldas, Carlos; Daley, Frances; Coulson, Penny; Broeks, Annegien; Sanders, Joyce; Wesseling, Jelle; Nevanlinna, Heli; Fagerholm, Rainer; Blomqvist, Carl; Heikkilä, Päivi; Ali, H Raza; Dawson, Sarah‐Jane; Figueroa, Jonine; Lissowska, Jolanta; Brinton, Louise; Mannermaa, Arto; Kataja, Vesa; Kosma, Veli‐Matti; Cox, Angela; Brock, Ian W; Cross, Simon S; Reed, Malcolm W; Couch, Fergus J; Olson, Janet E; Devillee, Peter; Mesker, Wilma E; Seyaneve, Caroline M; Hollestelle, Antoinette; Benitez, Javier; Perez, Jose Ignacio Arias; Menéndez, Primitiva; Bolla, Manjeet K; Easton, Douglas F; Schmidt, Marjanka K; Pharoah, Paul D; Sherman, Mark E

2014-01-01

Abstract Breast cancer risk factors and clinical outcomes vary by tumour marker expression. However, individual studies often lack the power required to assess these relationships, and large‐scale analyses are limited by the need for high throughput, standardized scoring methods. To address these limitations, we assessed whether automated image analysis of immunohistochemically stained tissue microarrays can permit rapid, standardized scoring of tumour markers from multiple studies. Tissue microarray sections prepared in nine studies containing 20 263 cores from 8267 breast cancers stained for two nuclear (oestrogen receptor, progesterone receptor), two membranous (human epidermal growth factor receptor 2 and epidermal growth factor receptor) and one cytoplasmic (cytokeratin 5/6) marker were scanned as digital images. Automated algorithms were used to score markers in tumour cells using the Ariol system. We compared automated scores against visual reads, and their associations with breast cancer survival. Approximately 65–70% of tissue microarray cores were satisfactory for scoring. Among satisfactory cores, agreement between dichotomous automated and visual scores was highest for oestrogen receptor (Kappa = 0.76), followed by human epidermal growth factor receptor 2 (Kappa = 0.69) and progesterone receptor (Kappa = 0.67). Automated quantitative scores for these markers were associated with hazard ratios for breast cancer mortality in a dose‐response manner. Considering visual scores of epidermal growth factor receptor or cytokeratin 5/6 as the reference, automated scoring achieved excellent negative predictive value (96–98%), but yielded many false positives (positive predictive value = 30–32%). For all markers, we observed substantial heterogeneity in automated scoring performance across tissue microarrays. Automated analysis is a potentially useful tool for large‐scale, quantitative scoring of immunohistochemically stained tissue microarrays available in consortia. However, continued optimization, rigorous marker‐specific quality control measures and standardization of tissue microarray designs, staining and scoring protocols is needed to enhance results. PMID:27499890

An integrated approach for identifying wrongly labelled samples when performing classification in microarray data.

PubMed

Leung, Yuk Yee; Chang, Chun Qi; Hung, Yeung Sam

2012-01-01

Using hybrid approach for gene selection and classification is common as results obtained are generally better than performing the two tasks independently. Yet, for some microarray datasets, both classification accuracy and stability of gene sets obtained still have rooms for improvement. This may be due to the presence of samples with wrong class labels (i.e. outliers). Outlier detection algorithms proposed so far are either not suitable for microarray data, or only solve the outlier detection problem on their own. We tackle the outlier detection problem based on a previously proposed Multiple-Filter-Multiple-Wrapper (MFMW) model, which was demonstrated to yield promising results when compared to other hybrid approaches (Leung and Hung, 2010). To incorporate outlier detection and overcome limitations of the existing MFMW model, three new features are introduced in our proposed MFMW-outlier approach: 1) an unbiased external Leave-One-Out Cross-Validation framework is developed to replace internal cross-validation in the previous MFMW model; 2) wrongly labeled samples are identified within the MFMW-outlier model; and 3) a stable set of genes is selected using an L1-norm SVM that removes any redundant genes present. Six binary-class microarray datasets were tested. Comparing with outlier detection studies on the same datasets, MFMW-outlier could detect all the outliers found in the original paper (for which the data was provided for analysis), and the genes selected after outlier removal were proven to have biological relevance. We also compared MFMW-outlier with PRAPIV (Zhang et al., 2006) based on same synthetic datasets. MFMW-outlier gave better average precision and recall values on three different settings. Lastly, artificially flipped microarray datasets were created by removing our detected outliers and flipping some of the remaining samples' labels. Almost all the 'wrong' (artificially flipped) samples were detected, suggesting that MFMW-outlier was sufficiently powerful to detect outliers in high-dimensional microarray datasets.

Identifying Fishes through DNA Barcodes and Microarrays.

PubMed

Kochzius, Marc; Seidel, Christian; Antoniou, Aglaia; Botla, Sandeep Kumar; Campo, Daniel; Cariani, Alessia; Vazquez, Eva Garcia; Hauschild, Janet; Hervet, Caroline; Hjörleifsdottir, Sigridur; Hreggvidsson, Gudmundur; Kappel, Kristina; Landi, Monica; Magoulas, Antonios; Marteinsson, Viggo; Nölte, Manfred; Planes, Serge; Tinti, Fausto; Turan, Cemal; Venugopal, Moleyur N; Weber, Hannes; Blohm, Dietmar

2010-09-07

International fish trade reached an import value of 62.8 billion Euro in 2006, of which 44.6% are covered by the European Union. Species identification is a key problem throughout the life cycle of fishes: from eggs and larvae to adults in fisheries research and control, as well as processed fish products in consumer protection. This study aims to evaluate the applicability of the three mitochondrial genes 16S rRNA (16S), cytochrome b (cyt b), and cytochrome oxidase subunit I (COI) for the identification of 50 European marine fish species by combining techniques of "DNA barcoding" and microarrays. In a DNA barcoding approach, neighbour Joining (NJ) phylogenetic trees of 369 16S, 212 cyt b, and 447 COI sequences indicated that cyt b and COI are suitable for unambiguous identification, whereas 16S failed to discriminate closely related flatfish and gurnard species. In course of probe design for DNA microarray development, each of the markers yielded a high number of potentially species-specific probes in silico, although many of them were rejected based on microarray hybridisation experiments. None of the markers provided probes to discriminate the sibling flatfish and gurnard species. However, since 16S-probes were less negatively influenced by the "position of label" effect and showed the lowest rejection rate and the highest mean signal intensity, 16S is more suitable for DNA microarray probe design than cty b and COI. The large portion of rejected COI-probes after hybridisation experiments (>90%) renders the DNA barcoding marker as rather unsuitable for this high-throughput technology. Based on these data, a DNA microarray containing 64 functional oligonucleotide probes for the identification of 30 out of the 50 fish species investigated was developed. It represents the next step towards an automated and easy-to-handle method to identify fish, ichthyoplankton, and fish products.

Quantitative multiplex quantum dot in-situ hybridisation based gene expression profiling in tissue microarrays identifies prognostic genes in acute myeloid leukaemia

DOE Office of Scientific and Technical Information (OSTI.GOV)

Tholouli, Eleni; MacDermott, Sarah; Hoyland, Judith

2012-08-24

Highlights: Black-Right-Pointing-Pointer Development of a quantitative high throughput in situ expression profiling method. Black-Right-Pointing-Pointer Application to a tissue microarray of 242 AML bone marrow samples. Black-Right-Pointing-Pointer Identification of HOXA4, HOXA9, Meis1 and DNMT3A as prognostic markers in AML. -- Abstract: Measurement and validation of microarray gene signatures in routine clinical samples is problematic and a rate limiting step in translational research. In order to facilitate measurement of microarray identified gene signatures in routine clinical tissue a novel method combining quantum dot based oligonucleotide in situ hybridisation (QD-ISH) and post-hybridisation spectral image analysis was used for multiplex in-situ transcript detection inmore » archival bone marrow trephine samples from patients with acute myeloid leukaemia (AML). Tissue-microarrays were prepared into which white cell pellets were spiked as a standard. Tissue microarrays were made using routinely processed bone marrow trephines from 242 patients with AML. QD-ISH was performed for six candidate prognostic genes using triplex QD-ISH for DNMT1, DNMT3A, DNMT3B, and for HOXA4, HOXA9, Meis1. Scrambled oligonucleotides were used to correct for background staining followed by normalisation of expression against the expression values for the white cell pellet standard. Survival analysis demonstrated that low expression of HOXA4 was associated with poorer overall survival (p = 0.009), whilst high expression of HOXA9 (p < 0.0001), Meis1 (p = 0.005) and DNMT3A (p = 0.04) were associated with early treatment failure. These results demonstrate application of a standardised, quantitative multiplex QD-ISH method for identification of prognostic markers in formalin-fixed paraffin-embedded clinical samples, facilitating measurement of gene expression signatures in routine clinical samples.« less

Open-target sparse sensing of biological agents using DNA microarray

PubMed Central

2011-01-01

Background Current biosensors are designed to target and react to specific nucleic acid sequences or structural epitopes. These 'target-specific' platforms require creation of new physical capture reagents when new organisms are targeted. An 'open-target' approach to DNA microarray biosensing is proposed and substantiated using laboratory generated data. The microarray consisted of 12,900 25 bp oligonucleotide capture probes derived from a statistical model trained on randomly selected genomic segments of pathogenic prokaryotic organisms. Open-target detection of organisms was accomplished using a reference library of hybridization patterns for three test organisms whose DNA sequences were not included in the design of the microarray probes. Results A multivariate mathematical model based on the partial least squares regression (PLSR) was developed to detect the presence of three test organisms in mixed samples. When all 12,900 probes were used, the model correctly detected the signature of three test organisms in all mixed samples (mean(R2)) = 0.76, CI = 0.95), with a 6% false positive rate. A sampling algorithm was then developed to sparsely sample the probe space for a minimal number of probes required to capture the hybridization imprints of the test organisms. The PLSR detection model was capable of correctly identifying the presence of the three test organisms in all mixed samples using only 47 probes (mean(R2)) = 0.77, CI = 0.95) with nearly 100% specificity. Conclusions We conceived an 'open-target' approach to biosensing, and hypothesized that a relatively small, non-specifically designed, DNA microarray is capable of identifying the presence of multiple organisms in mixed samples. Coupled with a mathematical model applied to laboratory generated data, and sparse sampling of capture probes, the prototype microarray platform was able to capture the signature of each organism in all mixed samples with high sensitivity and specificity. It was demonstrated that this new approach to biosensing closely follows the principles of sparse sensing. PMID:21801424

Identification of candidate genes in osteoporosis by integrated microarray analysis.

PubMed

Li, J J; Wang, B Q; Fei, Q; Yang, Y; Li, D

2016-12-01

In order to screen the altered gene expression profile in peripheral blood mononuclear cells of patients with osteoporosis, we performed an integrated analysis of the online microarray studies of osteoporosis. We searched the Gene Expression Omnibus (GEO) database for microarray studies of peripheral blood mononuclear cells in patients with osteoporosis. Subsequently, we integrated gene expression data sets from multiple microarray studies to obtain differentially expressed genes (DEGs) between patients with osteoporosis and normal controls. Gene function analysis was performed to uncover the functions of identified DEGs. A total of three microarray studies were selected for integrated analysis. In all, 1125 genes were found to be significantly differentially expressed between osteoporosis patients and normal controls, with 373 upregulated and 752 downregulated genes. Positive regulation of the cellular amino metabolic process (gene ontology (GO): 0033240, false discovery rate (FDR) = 1.00E + 00) was significantly enriched under the GO category for biological processes, while for molecular functions, flavin adenine dinucleotide binding (GO: 0050660, FDR = 3.66E-01) and androgen receptor binding (GO: 0050681, FDR = 6.35E-01) were significantly enriched. DEGs were enriched in many osteoporosis-related signalling pathways, including those of mitogen-activated protein kinase (MAPK) and calcium. Protein-protein interaction (PPI) network analysis showed that the significant hub proteins contained ubiquitin specific peptidase 9, X-linked (Degree = 99), ubiquitin specific peptidase 19 (Degree = 57) and ubiquitin conjugating enzyme E2 B (Degree = 57). Analysis of gene function of identified differentially expressed genes may expand our understanding of fundamental mechanisms leading to osteoporosis. Moreover, significantly enriched pathways, such as MAPK and calcium, may involve in osteoporosis through osteoblastic differentiation and bone formation.Cite this article: J. J. Li, B. Q. Wang, Q. Fei, Y. Yang, D. Li. Identification of candidate genes in osteoporosis by integrated microarray analysis. Bone Joint Res 2016;5:594-601. DOI: 10.1302/2046-3758.512.BJR-2016-0073.R1. © 2016 Fei et al.

Microarray data mining using Bioconductor packages.

PubMed

Nie, Haisheng; Neerincx, Pieter B T; van der Poel, Jan; Ferrari, Francesco; Bicciato, Silvio; Leunissen, Jack A M; Groenen, Martien A M

2009-07-16

This paper describes the results of a Gene Ontology (GO) term enrichment analysis of chicken microarray data using the Bioconductor packages. By checking the enriched GO terms in three contrasts, MM8-PM8, MM8-MA8, and MM8-MM24, of the provided microarray data during this workshop, this analysis aimed to investigate the host reactions in chickens occurring shortly after a secondary challenge with either a homologous or heterologous species of Eimeria. The results of GO enrichment analysis using GO terms annotated to chicken genes and GO terms annotated to chicken-human orthologous genes were also compared. Furthermore, a locally adaptive statistical procedure (LAP) was performed to test differentially expressed chromosomal regions, rather than individual genes, in the chicken genome after Eimeria challenge. GO enrichment analysis identified significant (raw p-value < 0.05) GO terms for all three contrasts included in the analysis. Some of the GO terms linked to, generally, primary immune responses or secondary immune responses indicating the GO enrichment analysis is a useful approach to analyze microarray data. The comparisons of GO enrichment results using chicken gene information and chicken-human orthologous gene information showed more refined GO terms related to immune responses when using chicken-human orthologous gene information, this suggests that using chicken-human orthologous gene information has higher power to detect significant GO terms with more refined functionality. Furthermore, three chromosome regions were identified to be significantly up-regulated in contrast MM8-PM8 (q-value < 0.01). Overall, this paper describes a practical approach to analyze microarray data in farm animals where the genome information is still incomplete. For farm animals, such as chicken, with currently limited gene annotation, borrowing gene annotation information from orthologous genes in well-annotated species, such as human, will help improve the pathway analysis results substantially. Furthermore, LAP analysis approach is a relatively new and very useful way to be applied in microarray analysis.

Altered Expression of Diabetes-Related Genes in Alzheimer's Disease Brains: The Hisayama Study

PubMed Central

Hokama, Masaaki; Oka, Sugako; Leon, Julio; Ninomiya, Toshiharu; Honda, Hiroyuki; Sasaki, Kensuke; Iwaki, Toru; Ohara, Tomoyuki; Sasaki, Tomio; LaFerla, Frank M.; Kiyohara, Yutaka; Nakabeppu, Yusaku

2014-01-01

Diabetes mellitus (DM) is considered to be a risk factor for dementia including Alzheimer's disease (AD). However, the molecular mechanism underlying this risk is not well understood. We examined gene expression profiles in postmortem human brains donated for the Hisayama study. Three-way analysis of variance of microarray data from frontal cortex, temporal cortex, and hippocampus was performed with the presence/absence of AD and vascular dementia, and sex, as factors. Comparative analyses of expression changes in the brains of AD patients and a mouse model of AD were also performed. Relevant changes in gene expression identified by microarray analysis were validated by quantitative real-time reverse-transcription polymerase chain reaction and western blotting. The hippocampi of AD brains showed the most significant alteration in gene expression profile. Genes involved in noninsulin-dependent DM and obesity were significantly altered in both AD brains and the AD mouse model, as were genes related to psychiatric disorders and AD. The alterations in the expression profiles of DM-related genes in AD brains were independent of peripheral DM-related abnormalities. These results indicate that altered expression of genes related to DM in AD brains is a result of AD pathology, which may thereby be exacerbated by peripheral insulin resistance or DM. PMID:23595620

A case report of two male siblings with autism and duplication of Xq13-q21, a region including three genes predisposing for autism.

PubMed

Wentz, Elisabet; Vujic, Mihailo; Kärrstedt, Ewa-Lotta; Erlandsson, Anna; Gillberg, Christopher

2014-05-01

Autism spectrum disorder, severe behaviour problems and duplication of the Xq12 to Xq13 region have recently been described in three male relatives. To describe the psychiatric comorbidity and dysmorphic features, including craniosynostosis, of two male siblings with autism and duplication of the Xq13 to Xq21 region, and attempt to narrow down the number of duplicated genes proposed to be leading to global developmental delay and autism. We performed DNA sequencing of certain exons of the TWIST1 gene, the FGFR2 gene and the FGFR3 gene. We also performed microarray analysis of the DNA. In addition to autism, the two male siblings exhibited severe learning disability, self-injurious behaviour, temper tantrums and hyperactivity, and had no communicative language. Chromosomal analyses were normal. Neither of the two siblings showed mutations of the sequenced exons known to produce craniosynostosis. The microarray analysis detected an extra copy of a region on the long arm of chromosome X, chromosome band Xq13.1-q21.1. Comparison of our two cases with previously described patients allowed us to identify three genes predisposing for autism in the duplicated chromosomal region. Sagittal craniosynostosis is also a new finding linked to the duplication.

Long noncoding RNA OR3A4 promotes metastasis and tumorigenicity in gastric cancer

PubMed Central

Guo, Xiaobo; Yang, Ziguo; Zhi, Qiaoming; Wang, Dan; Guo, Lei; Li, Guimei; Miao, Ruizhen; Shi, Yulong; Kuang, Yuting

2016-01-01

The contribution of long noncoding RNAs (lncRNAs) to metastasis of gastric cancer remains largely unknown. We used microarray analysis to identify lncRNAs differentially expressed between normal gastric tissues and gastric cancer tissues and validated these differences in quantitative real-time (qRT)-PCR experiments. The expression levels of lncRNA olfactory receptor, family 3, subfamily A, member 4 (OR3A4) were significantly associated with lymphatic metastasis, the depth of cancer invasion, and distal metastasis in 130 paired gastric cancer tissues. The effects of OR3A4 were assessed by overexpressing and silencing OR3A4 in gastric cancer cells. OR3A4 promoted cancer cell growth, angiogenesis, metastasis, and tumorigenesis in vitro and in vivo. Global microarray analysis combined with RT-PCR, RNA immunoprecipitation, and RNA pull-down analyses after OR3A4 transfection demonstrated that OR3A4 influenced biologic functions in gastric cancer cells via regulating the activation of PDLIM2, MACC1, NTN4, and GNB2L1. Our results reveal OR3A4 as an oncogenic lncRNA that promotes tumor progression, Therefore, lncRNAs might function as key regulatory hubs in gastric cancer progression. PMID:26863570

DNA Microarray Profiling Highlights Nrf2-Mediated Chemoprevention Targeted by Wasabi-Derived Isothiocyanates in HepG2 Cells.

PubMed

Trio, Phoebe Zapanta; Kawahara, Atsuyoshi; Tanigawa, Shunsuke; Sakao, Kozue; Hou, De-Xing

2017-01-01

6-MSITC and 6-MTITC are sulforaphane (SFN) analogs found in Japanese Wasabi. As we reported previously, Wasabi isothiocyanates (ITCs) are activators of Nrf2-antioxidant response element pathway, and also inhibitors of pro-inflammatory cyclooxygenase-2. This study is the first to assess the global changes in transcript levels by Wasabi ITCs, comparing with SFN, in HepG2 cells. We performed comparative gene expression profiling by treating HepG2 cells with ITCs, followed by DNA microarray analyses using HG-U133 plus 2.0 oligonucleotide array. Partial array data on selected gene products were confirmed by RT-PCR and Western blotting. Ingenuity Pathway Analysis (IPA) was used to identify functional subsets of genes and biologically significant network pathways. 6-MTITC showed the highest number of differentially altered (≥2 folds) gene expression, of which 114 genes were upregulated and 75 were downregulated. IPA revealed that Nrf2-mediated pathway, together with glutamate metabolism, is the common significantly modulated pathway across treatments. Interestingly, 6-MSITC exhibited the most potent effect toward Nrf2-mediated pathway. Our data suggest that 6-MSITC could exert chemopreventive role against cancer through its underlying antioxidant activity via the activation of Nrf2-mediated subsequent induction of cytoprotective genes.

The multidimensional perturbation value: a single metric to measure similarity and activity of treatments in high-throughput multidimensional screens.

PubMed

Hutz, Janna E; Nelson, Thomas; Wu, Hua; McAllister, Gregory; Moutsatsos, Ioannis; Jaeger, Savina A; Bandyopadhyay, Somnath; Nigsch, Florian; Cornett, Ben; Jenkins, Jeremy L; Selinger, Douglas W

2013-04-01

Screens using high-throughput, information-rich technologies such as microarrays, high-content screening (HCS), and next-generation sequencing (NGS) have become increasingly widespread. Compared with single-readout assays, these methods produce a more comprehensive picture of the effects of screened treatments. However, interpreting such multidimensional readouts is challenging. Univariate statistics such as t-tests and Z-factors cannot easily be applied to multidimensional profiles, leaving no obvious way to answer common screening questions such as "Is treatment X active in this assay?" and "Is treatment X different from (or equivalent to) treatment Y?" We have developed a simple, straightforward metric, the multidimensional perturbation value (mp-value), which can be used to answer these questions. Here, we demonstrate application of the mp-value to three data sets: a multiplexed gene expression screen of compounds and genomic reagents, a microarray-based gene expression screen of compounds, and an HCS compound screen. In all data sets, active treatments were successfully identified using the mp-value, and simulations and follow-up analyses supported the mp-value's statistical and biological validity. We believe the mp-value represents a promising way to simplify the analysis of multidimensional data while taking full advantage of its richness.

Estimation of low-dose radiation-responsive proteins in the absence of genomic instability in normal human fibroblast cells.

PubMed

Yim, Ji-Hye; Yun, Jung Mi; Kim, Ji Young; Nam, Seon Young; Kim, Cha Soon

2017-11-01

Low-dose radiation has various biological effects such as adaptive responses, low-dose hypersensitivity, as well as beneficial effects. However, little is known about the particular proteins involved in these effects. Here, we sought to identify low-dose radiation-responsive phosphoproteins in normal fibroblast cells. We assessed genomic instability and proliferation of fibroblast cells after γ-irradiation by γ-H2AX foci and micronucleus formation analyses and BrdU incorporation assay, respectively. We screened fibroblast cells 8 h after low-dose (0.05 Gy) γ-irradiation using Phospho Explorer Antibody Microarray and validated two differentially expressed phosphoproteins using Western blotting. Cell proliferation proceeded normally in the absence of genomic instability after low-dose γ-irradiation. Phospho antibody microarray analysis and Western blotting revealed increased expression of two phosphoproteins, phospho-NFκB (Ser536) and phospho-P70S6K (Ser418), 8 h after low-dose radiation. Our findings suggest that low-dose radiation of normal fibroblast cells activates the expression of phospho-NFκB (Ser536) and phospho-P70S6K (Ser418) in the absence of genomic instability. Therefore, these proteins may be involved in DNA damage repair processes.

A microarray-based genotyping and genetic mapping approach for highly heterozygous outcrossing species enables localization of a large fraction of the unassembled Populus trichocarpa genome sequence.

PubMed

Drost, Derek R; Novaes, Evandro; Boaventura-Novaes, Carolina; Benedict, Catherine I; Brown, Ryan S; Yin, Tongming; Tuskan, Gerald A; Kirst, Matias

2009-06-01

Microarrays have demonstrated significant power for genome-wide analyses of gene expression, and recently have also revolutionized the genetic analysis of segregating populations by genotyping thousands of loci in a single assay. Although microarray-based genotyping approaches have been successfully applied in yeast and several inbred plant species, their power has not been proven in an outcrossing species with extensive genetic diversity. Here we have developed methods for high-throughput microarray-based genotyping in such species using a pseudo-backcross progeny of 154 individuals of Populus trichocarpa and P. deltoides analyzed with long-oligonucleotide in situ-synthesized microarray probes. Our analysis resulted in high-confidence genotypes for 719 single-feature polymorphism (SFP) and 1014 gene expression marker (GEM) candidates. Using these genotypes and an established microsatellite (SSR) framework map, we produced a high-density genetic map comprising over 600 SFPs, GEMs and SSRs. The abundance of gene-based markers allowed us to localize over 35 million base pairs of previously unplaced whole-genome shotgun (WGS) scaffold sequence to putative locations in the genome of P. trichocarpa. A high proportion of sampled scaffolds could be verified for their placement with independently mapped SSRs, demonstrating the previously un-utilized power that high-density genotyping can provide in the context of map-based WGS sequence reassembly. Our results provide a substantial contribution to the continued improvement of the Populus genome assembly, while demonstrating the feasibility of microarray-based genotyping in a highly heterozygous population. The strategies presented are applicable to genetic mapping efforts in all plant species with similarly high levels of genetic diversity.

Bioinformatic analysis of the effects and mechanisms of decitabine and cytarabine on acute myeloid leukemia

PubMed Central

Zhou, Shiyong; Liu, Pengfei; Zhang, Huilai

2017-01-01

Acute myeloid leukemia (AML) is a frequently occurring malignant disease of the blood and may result from a variety of genetic disorders. The present study aimed to identify the underlying mechanisms associated with the therapeutic effects of decitabine and cytarabine on AML, using microarray analysis. The microarray datasets GSE40442 and GSE40870 were downloaded from the Gene Expression Omnibus database. Differentially expressed genes (DEGs) and differentially methylated sites were identified in AML cells treated with decitabine compared with those treated with cytarabine via the Linear Models for Microarray Data package, following data pre-processing. Gene Ontology (GO) analysis of DEGs was performed using the Database for Annotation, Visualization and Integrated Analysis Discovery. Genes corresponding to the differentially methylated sites were obtained using the annotation package of the methylation microarray platform. The overlapping genes were identified, which exhibited the opposite variation trend between gene expression and DNA methylation. Important transcription factor (TF)-gene pairs were screened out, and a regulated network subsequently constructed. A total of 190 DEGs and 540 differentially methylated sites were identified in AML cells treated with decitabine compared with those treated with cytarabine. A total of 36 GO terms of DEGs were enriched, including nucleosomes, protein-DNA complexes and the nucleosome assembly. The 540 differentially methylated sites were located on 240 genes, including the acid-repeat containing protein (ACRC) gene that was additionally differentially expressed. In addition, 60 TF pairs and overlapped methylated sites, and 140 TF-pairs and DEGs were screened out. The regulated network included 68 nodes and 140 TF-gene pairs. The present study identified various genes including ACRC and proliferating cell nuclear antigen, in addition to various TFs, including TATA-box binding protein associated factor 1 and CCCTC-binding factor, which may be potential therapeutic targets of AML. PMID:28498449

Bioinformatic analysis of the effects and mechanisms of decitabine and cytarabine on acute myeloid leukemia.

PubMed

Zhou, Shiyong; Liu, Pengfei; Zhang, Huilai

2017-07-01

Acute myeloid leukemia (AML) is a frequently occurring malignant disease of the blood and may result from a variety of genetic disorders. The present study aimed to identify the underlying mechanisms associated with the therapeutic effects of decitabine and cytarabine on AML, using microarray analysis. The microarray datasets GSE40442 and GSE40870 were downloaded from the Gene Expression Omnibus database. Differentially expressed genes (DEGs) and differentially methylated sites were identified in AML cells treated with decitabine compared with those treated with cytarabine via the Linear Models for Microarray Data package, following data pre‑processing. Gene Ontology (GO) analysis of DEGs was performed using the Database for Annotation, Visualization and Integrated Analysis Discovery. Genes corresponding to the differentially methylated sites were obtained using the annotation package of the methylation microarray platform. The overlapping genes were identified, which exhibited the opposite variation trend between gene expression and DNA methylation. Important transcription factor (TF)‑gene pairs were screened out, and a regulated network subsequently constructed. A total of 190 DEGs and 540 differentially methylated sites were identified in AML cells treated with decitabine compared with those treated with cytarabine. A total of 36 GO terms of DEGs were enriched, including nucleosomes, protein‑DNA complexes and the nucleosome assembly. The 540 differentially methylated sites were located on 240 genes, including the acid‑repeat containing protein (ACRC) gene that was additionally differentially expressed. In addition, 60 TF pairs and overlapped methylated sites, and 140 TF‑pairs and DEGs were screened out. The regulated network included 68 nodes and 140 TF‑gene pairs. The present study identified various genes including ACRC and proliferating cell nuclear antigen, in addition to various TFs, including TATA‑box binding protein associated factor 1 and CCCTC‑binding factor, which may be potential therapeutic targets of AML.

Archetypal analysis of diverse Pseudomonas aeruginosa transcriptomes reveals adaptation in cystic fibrosis airways

PubMed Central

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

Supervised group Lasso with applications to microarray data analysis

PubMed Central

Ma, Shuangge; Song, Xiao; Huang, Jian

2007-01-01

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. PMID:17316436

Evaluation of Four RNA Extraction Methods for Gene Expression Analyses of Cryptosporidium parvum and Toxoplasma gondii Oocys

EPA Science Inventory

Cryptosporidium spp. and Toxoplasma gondii are important coccidian parasites that have caused waterborne and foodborne disease outbreaks worldwide. Techniques like subtractive hybridization, microarrays, and quantitative reverse transcriptase real-time polymerase chain reaction (...

Development of a single nucleotide polymorphism DNA microarray for the detection and genotyping of the SARS coronavirus.

PubMed

Guo, Xi; Geng, Peng; Wang, Quan; Cao, Boyang; Liu, Bin

2014-10-01

Severe acute respiratory syndrome (SARS), a disease that spread widely in the world during late 2002 to 2004, severely threatened public health. Although there have been no reported infections since 2004, the extremely pathogenic SARS coronavirus (SARS-CoV), as the causative agent of SARS, has recently been identified in animals, showing the potential for the re-emergence of this disease. Previous studies showed that 27 single nucleotide polymorphism (SNP) mutations among the spike (S) gene of this virus are correlated closely with the SARS pathogenicity and epidemicity. We have developed a SNP DNA microarray in order to detect and genotype these SNPs, and to obtain related information on the pathogenicity and epidemicity of a given strain. The microarray was hybridized with PCR products amplified from cDNAs obtained from different SARS-CoV strains. We were able to detect 24 SNPs and determine the type of a given strain. The hybridization profile showed that 19 samples were detected and genotyped correctly by using our microarray, with 100% accuracy. Our microarray provides a novel method for the detection and epidemiological surveillance of SARS-CoV.

Fluorescent labeling of NASBA amplified tmRNA molecules for microarray applications

PubMed Central

Scheler, Ott; Glynn, Barry; Parkel, Sven; Palta, Priit; Toome, Kadri; Kaplinski, Lauris; Remm, Maido; Maher, Majella; Kurg, Ants

2009-01-01

Background Here we present a novel promising microbial diagnostic method that combines the sensitivity of Nucleic Acid Sequence Based Amplification (NASBA) with the high information content of microarray technology for the detection of bacterial tmRNA molecules. The NASBA protocol was modified to include aminoallyl-UTP (aaUTP) molecules that were incorporated into nascent RNA during the NASBA reaction. Post-amplification labeling with fluorescent dye was carried out subsequently and tmRNA hybridization signal intensities were measured using microarray technology. Significant optimization of the labeled NASBA protocol was required to maintain the required sensitivity of the reactions. Results Two different aaUTP salts were evaluated and optimum final concentrations were identified for both. The final 2 mM concentration of aaUTP Li-salt in NASBA reaction resulted in highest microarray signals overall, being twice as high as the strongest signals with 1 mM aaUTP Na-salt. Conclusion We have successfully demonstrated efficient combination of NASBA amplification technology with microarray based hybridization detection. The method is applicative for many different areas of microbial diagnostics including environmental monitoring, bio threat detection, industrial process monitoring and clinical microbiology. PMID:19445684

Bone health nutraceuticals alter microarray mRNA gene expression: A randomized, parallel, open-label clinical study.

PubMed

Lin, Yumei; Kazlova, Valentina; Ramakrishnan, Shyam; Murray, Mary A; Fast, David; Chandra, Amitabh; Gellenbeck, Kevin W

2016-01-15

Dietary intake of fruits and vegetables has been suggested to have a role in promoting bone health. More specifically, the polyphenols they contain have been linked to physiological effects related to bone mineral density and bone metabolism. In this research, we use standard microarray analyses of peripheral whole blood from post-menopausal women treated with two fixed combinations of plant extracts standardized to polyphenol content to identify differentially expressed genes relevant to bone health. In this 28-day open-label study, healthy post-menopausal women were randomized into three groups, each receiving one of three investigational fixed combinations of plant extracts: an anti-resorptive (AR) combination of pomegranate fruit (Punica granatum L.) and grape seed (Vitis vinifera L.) extracts; a bone formation (BF) combination of quercetin (Dimorphandra mollis Benth) and licorice (Glycyrrhiza glabra L.) extracts; and a fixed combination of all four plant extracts (AR plus BF). Standard microarray analysis was performed on peripheral whole blood samples taken before and after each treatment. Annotated genes were analyzed for their association to bone health by comparison to a gene library. The AR combination down-regulated a number of genes involved in reduction of bone resorption including cathepsin G (CTSG) and tachykinin receptor 1 (TACR1). The AR combination also up-regulated genes associated with formation of extracellular matrix including heparan sulfate proteoglycan 2 (HSPG2) and hyaluronoglucosaminidase 1 (HYAL1). In contrast, treatment with the BF combination resulted in up-regulation of bone morphogenetic protein 2 (BMP-2) and COL1A1 (collagen type I α1) genes which are linked to bone and collagen formation while down-regulating genes linked to osteoclastogenesis. Treatment with a combination of all four plant extracts had a distinctly different effect on gene expression than the results of the AR and BF combinations individually. These results could be due to multiple feedback systems balancing activities of osteoblasts and osteoclasts. In summary, this ex-vivo microarray study indicated that the pomegranate, grape seed, quercetin and licorice combinations of plant extracts modulated gene expression for both osteoclastic and osteogenic processes. Copyright © 2015 The Authors. Published by Elsevier GmbH.. All rights reserved.

An alternative method to amplify RNA without loss of signal conservation for expression analysis with a proteinase DNA microarray in the ArrayTube format.

PubMed

Schüler, Susann; Wenz, Ingrid; Wiederanders, B; Slickers, P; Ehricht, R

2006-06-12

Recent developments in DNA microarray technology led to a variety of open and closed devices and systems including high and low density microarrays for high-throughput screening applications as well as microarrays of lower density for specific diagnostic purposes. Beside predefined microarrays for specific applications manufacturers offer the production of custom-designed microarrays adapted to customers' wishes. Array based assays demand complex procedures including several steps for sample preparation (RNA extraction, amplification and sample labelling), hybridization and detection, thus leading to a high variability between several approaches and resulting in the necessity of extensive standardization and normalization procedures. In the present work a custom designed human proteinase DNA microarray of lower density in ArrayTube format was established. This highly economic open platform only requires standard laboratory equipment and allows the study of the molecular regulation of cell behaviour by proteinases. We established a procedure for sample preparation and hybridization and verified the array based gene expression profile by quantitative real-time PCR (QRT-PCR). Moreover, we compared the results with the well established Affymetrix microarray. By application of standard labelling procedures with e.g. Klenow fragment exo-, single primer amplification (SPA) or In Vitro Transcription (IVT) we noticed a loss of signal conservation for some genes. To overcome this problem we developed a protocol in accordance with the SPA protocol, in which we included target specific primers designed individually for each spotted oligomer. Here we present a complete array based assay in which only the specific transcripts of interest are amplified in parallel and in a linear manner. The array represents a proof of principle which can be adapted to other species as well. As the designed protocol for amplifying mRNA starts from as little as 100 ng total RNA, it presents an alternative method for detecting even low expressed genes by microarray experiments in a highly reproducible and sensitive manner. Preservation of signal integrity is demonstrated out by QRT-PCR measurements. The little amounts of total RNA necessary for the analyses make this method applicable for investigations with limited material as in clinical samples from, for example, organ or tumour biopsies. Those are arguments in favour of the high potential of our assay compared to established procedures for amplification within the field of diagnostic expression profiling. Nevertheless, the screening character of microarray data must be mentioned, and independent methods should verify the results.

Ultrafiltration and Microarray for Detection of Microbial Source Tracking Marker and Pathogen Genes in Riverine and Marine Systems

PubMed Central

Li, Xiang; Harwood, Valerie J.; Nayak, Bina

2016-01-01

Pathogen identification and microbial source tracking (MST) to identify sources of fecal pollution improve evaluation of water quality. They contribute to improved assessment of human health risks and remediation of pollution sources. An MST microarray was used to simultaneously detect genes for multiple pathogens and indicators of fecal pollution in freshwater, marine water, sewage-contaminated freshwater and marine water, and treated wastewater. Dead-end ultrafiltration (DEUF) was used to concentrate organisms from water samples, yielding a recovery efficiency of >95% for Escherichia coli and human polyomavirus. Whole-genome amplification (WGA) increased gene copies from ultrafiltered samples and increased the sensitivity of the microarray. Viruses (adenovirus, bocavirus, hepatitis A virus, and human polyomaviruses) were detected in sewage-contaminated samples. Pathogens such as Legionella pneumophila, Shigella flexneri, and Campylobacter fetus were detected along with genes conferring resistance to aminoglycosides, beta-lactams, and tetracycline. Nonmetric dimensional analysis of MST marker genes grouped sewage-spiked freshwater and marine samples with sewage and apart from other fecal sources. The sensitivity (percent true positives) of the microarray probes for gene targets anticipated in sewage was 51 to 57% and was lower than the specificity (percent true negatives; 79 to 81%). A linear relationship between gene copies determined by quantitative PCR and microarray fluorescence was found, indicating the semiquantitative nature of the MST microarray. These results indicate that ultrafiltration coupled with WGA provides sufficient nucleic acids for detection of viruses, bacteria, protozoa, and antibiotic resistance genes by the microarray in applications ranging from beach monitoring to risk assessment. PMID:26729716

Rice tolerance to suboptimal low temperatures relies on the maintenance of the photosynthetic capacity.

PubMed

Gazquez, Ayelén; Vilas, Juan Manuel; Colman Lerner, Jorge Esteban; Maiale, Santiago Javier; Calzadilla, Pablo Ignacio; Menéndez, Ana Bernardina; Rodríguez, Andrés Alberto

2018-06-01

The purpose of this research was to identify differences between two contrasting rice cultivars in their response to suboptimal low temperatures stress. A transcriptomic analysis of the seedlings was performed and results were complemented with biochemical and physiological analyses. The microarray analysis showed downregulation of many genes related with PSII and particularly with the oxygen evolving complex in the sensitive cultivar IR50. Complementary studies indicated that the PSII performance, the degree of oxygen evolving complex coupling with the PSII core and net photosynthetic rate diminished in this cultivar in response to the stress. However, the tolerant cultivar Koshihikari was able to maintain its energy equilibrium by sustaining the photosynthetic capacity. The increase of oleic acid in Koshihikari could be related with membrane remodelling of the chloroplasts and hence contribute to tolerance. Overall, these results work as a ground for future analyses that look forward to characterize possible mechanisms to tolerate this stress. Copyright © 2018 Elsevier Masson SAS. All rights reserved.

Screening hybridomas for anabolic androgenic steroids by steroid analog antigen microarray.

PubMed

Du, Hongwu; Chen, Guangyu; Bian, Yongzhong; Xing, Cenzan; Ding, Xue; Zhu, Mengliang; Xun, Yiping; Chen, Peng; Zhou, Yabin; Li, Shaoxu

2015-01-01

Currently, dozens of anabolic androgenic steroids (AAS) are forbidden in the World Anti-Doping Agency Prohibited List, however, despite extensive investigation, there are still lots of AAS without corresponding monoclonal antibodies. A steroid analog antigen microarray made up of ten AAS was fabricated to screen the hybridoma and it was found an original unsuccessful clone turned out to be a candidate anti-boldenone antibody, without any cross-reactions with endogenous AAS or 44 different AAS standard reference materials tested. Our findings suggested that steroid analog antigen microarray could be a promising tool to screen and characterize new applications of antibodies for structure analogs, and this also exhibits the potential to fast identify effective epitopes of hybridomas in a single assay.

Comparing microarrays and next-generation sequencing technologies for microbial ecology research.

PubMed

Roh, Seong Woon; Abell, Guy C J; Kim, Kyoung-Ho; Nam, Young-Do; Bae, Jin-Woo

2010-06-01

Recent advances in molecular biology have resulted in the application of DNA microarrays and next-generation sequencing (NGS) technologies to the field of microbial ecology. This review aims to examine the strengths and weaknesses of each of the methodologies, including depth and ease of analysis, throughput and cost-effectiveness. It also intends to highlight the optimal application of each of the individual technologies toward the study of a particular environment and identify potential synergies between the two main technologies, whereby both sample number and coverage can be maximized. We suggest that the efficient use of microarray and NGS technologies will allow researchers to advance the field of microbial ecology, and importantly, improve our understanding of the role of microorganisms in their various environments.

Cell Wall Modifications in Maize Pulvini in Response to Gravitational Stress1[W][OA

PubMed Central

Zhang, Qisen; Pettolino, Filomena A.; Dhugga, Kanwarpal S.; Rafalski, J. Antoni; Tingey, Scott; Taylor, Jillian; Shirley, Neil J.; Hayes, Kevin; Beatty, Mary; Abrams, Suzanne R.; Zaharia, L. Irina; Burton, Rachel A.; Bacic, Antony; Fincher, Geoffrey B.

2011-01-01

Changes in cell wall polysaccharides, transcript abundance, metabolite profiles, and hormone concentrations were monitored in the upper and lower regions of maize (Zea mays) pulvini in response to gravistimulation, during which maize plants placed in a horizontal position returned to the vertical orientation. Heteroxylan levels increased in the lower regions of the pulvini, together with lignin, but xyloglucans and heteromannan contents decreased. The degree of substitution of heteroxylan with arabinofuranosyl residues decreased in the lower pulvini, which exhibited increased mechanical strength as the plants returned to the vertical position. Few or no changes in noncellulosic wall polysaccharides could be detected on the upper side of the pulvinus, and crystalline cellulose content remained essentially constant in both the upper and lower pulvinus. Microarray analyses showed that spatial and temporal changes in transcript profiles were consistent with the changes in wall composition that were observed in the lower regions of the pulvinus. In addition, the microarray analyses indicated that metabolic pathways leading to the biosynthesis of phytohormones were differentially activated in the upper and lower regions of the pulvinus in response to gravistimulation. Metabolite profiles and measured hormone concentrations were consistent with the microarray data, insofar as auxin, physiologically active gibberellic acid, and metabolites potentially involved in lignin biosynthesis increased in the elongating cells of the lower pulvinus. PMID:21697508

Combined analysis of transcriptome and proteome data as a tool for the identification of candidate biomarkers in renal cell carcinoma

PubMed Central

Seliger, Barbara; Dressler, Sven P.; Wang, Ena; Kellner, Roland; Recktenwald, Christian V.; Lottspeich, Friedrich; Marincola, Francesco M.; Baumgärtner, Maja; Atkins, Derek; Lichtenfels, Rudolf

2012-01-01

Results obtained from expression profilings of renal cell carcinoma using different “ome”-based approaches and comprehensive data analysis demonstrated that proteome-based technologies and cDNA microarray analyses complement each other during the discovery phase for disease-related candidate biomarkers. The integration of the respective data revealed the uniqueness and complementarities of the different technologies. While comparative cDNA microarray analyses though restricted to upregulated targets largely revealed genes involved in controlling gene/protein expression (19%) and signal transduction processes (13%), proteomics/PROTEOMEX-defined candidate biomarkers include enzymes of the cellular metabolism (36%), transport proteins (12%) and cell motility/structural molecules (10%). Candidate biomarkers defined by proteomics and PROTEOMEX are frequently shared, whereas the sharing rate between cDNA microarray and proteome-based profilings is limited. Putative candidate biomarkers provide insights into their cellular (dys)function and their diagnostic/prognostic value but still warrant further validation in larger patient numbers. Based on the fact that merely 3 candidate biomarkers were shared by all applied technologies, namely annexin A4, tubulin alpha-1A chain and ubiquitin carboxyl-terminal hydrolase L1 the analysis at a single hierarchical level of biological regulation seems to provide only limited results thus emphasizing the importance and benefit of performing rather combinatorial screenings which can complement the standard clinical predictors. PMID:19235166

Reverse engineering biological networks :applications in immune responses to bio-toxins.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Martino, Anthony A.; Sinclair, Michael B.; Davidson, George S.

Our aim is to determine the network of events, or the regulatory network, that defines an immune response to a bio-toxin. As a model system, we are studying T cell regulatory network triggered through tyrosine kinase receptor activation using a combination of pathway stimulation and time-series microarray experiments. Our approach is composed of five steps (1) microarray experiments and data error analysis, (2) data clustering, (3) data smoothing and discretization, (4) network reverse engineering, and (5) network dynamics analysis and fingerprint identification. The technological outcome of this study is a suite of experimental protocols and computational tools that reverse engineermore » regulatory networks provided gene expression data. The practical biological outcome of this work is an immune response fingerprint in terms of gene expression levels. Inferring regulatory networks from microarray data is a new field of investigation that is no more than five years old. To the best of our knowledge, this work is the first attempt that integrates experiments, error analyses, data clustering, inference, and network analysis to solve a practical problem. Our systematic approach of counting, enumeration, and sampling networks matching experimental data is new to the field of network reverse engineering. The resulting mathematical analyses and computational tools lead to new results on their own and should be useful to others who analyze and infer networks.« less

The statistics of identifying differentially expressed genes in Expresso and TM4: a comparison

PubMed Central

Sioson, Allan A; Mane, Shrinivasrao P; Li, Pinghua; Sha, Wei; Heath, Lenwood S; Bohnert, Hans J; Grene, Ruth

2006-01-01

Background Analysis of DNA microarray data takes as input spot intensity measurements from scanner software and returns differential expression of genes between two conditions, together with a statistical significance assessment. This process typically consists of two steps: data normalization and identification of differentially expressed genes through statistical analysis. The Expresso microarray experiment management system implements these steps with a two-stage, log-linear ANOVA mixed model technique, tailored to individual experimental designs. The complement of tools in TM4, on the other hand, is based on a number of preset design choices that limit its flexibility. In the TM4 microarray analysis suite, normalization, filter, and analysis methods form an analysis pipeline. TM4 computes integrated intensity values (IIV) from the average intensities and spot pixel counts returned by the scanner software as input to its normalization steps. By contrast, Expresso can use either IIV data or median intensity values (MIV). Here, we compare Expresso and TM4 analysis of two experiments and assess the results against qRT-PCR data. Results The Expresso analysis using MIV data consistently identifies more genes as differentially expressed, when compared to Expresso analysis with IIV data. The typical TM4 normalization and filtering pipeline corrects systematic intensity-specific bias on a per microarray basis. Subsequent statistical analysis with Expresso or a TM4 t-test can effectively identify differentially expressed genes. The best agreement with qRT-PCR data is obtained through the use of Expresso analysis and MIV data. Conclusion The results of this research are of practical value to biologists who analyze microarray data sets. The TM4 normalization and filtering pipeline corrects microarray-specific systematic bias and complements the normalization stage in Expresso analysis. The results of Expresso using MIV data have the best agreement with qRT-PCR results. In one experiment, MIV is a better choice than IIV as input to data normalization and statistical analysis methods, as it yields as greater number of statistically significant differentially expressed genes; TM4 does not support the choice of MIV input data. Overall, the more flexible and extensive statistical models of Expresso achieve more accurate analytical results, when judged by the yardstick of qRT-PCR data, in the context of an experimental design of modest complexity. PMID:16626497

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

NASA Astrophysics Data System (ADS)

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.

Complex and dynamic landscape of RNA polyadenylation revealed by PAS-Seq

PubMed Central

Shepard, Peter J.; Choi, Eun-A; Lu, Jente; Flanagan, Lisa A.; Hertel, Klemens J.; Shi, Yongsheng

2011-01-01

Alternative polyadenylation (APA) of mRNAs has emerged as an important mechanism for post-transcriptional gene regulation in higher eukaryotes. Although microarrays have recently been used to characterize APA globally, they have a number of serious limitations that prevents comprehensive and highly quantitative analysis. To better characterize APA and its regulation, we have developed a deep sequencing-based method called Poly(A) Site Sequencing (PAS-Seq) for quantitatively profiling RNA polyadenylation at the transcriptome level. PAS-Seq not only accurately and comprehensively identifies poly(A) junctions in mRNAs and noncoding RNAs, but also provides quantitative information on the relative abundance of polyadenylated RNAs. PAS-Seq analyses of human and mouse transcriptomes showed that 40%–50% of all expressed genes produce alternatively polyadenylated mRNAs. Furthermore, our study detected evolutionarily conserved polyadenylation of histone mRNAs and revealed novel features of mitochondrial RNA polyadenylation. Finally, PAS-Seq analyses of mouse embryonic stem (ES) cells, neural stem/progenitor (NSP) cells, and neurons not only identified more poly(A) sites than what was found in the entire mouse EST database, but also detected significant changes in the global APA profile that lead to lengthening of 3′ untranslated regions (UTR) in many mRNAs during stem cell differentiation. Together, our PAS-Seq analyses revealed a complex landscape of RNA polyadenylation in mammalian cells and the dynamic regulation of APA during stem cell differentiation. PMID:21343387

Analysis of developmental gene conservation in the Actinomycetales using DNA/DNA microarray comparisons.

PubMed

Kirby, Ralph; Herron, Paul; Hoskisson, Paul

2011-02-01

Based on available genome sequences, Actinomycetales show significant gene synteny across a wide range of species and genera. In addition, many genera show varying degrees of complex morphological development. Using the presence of gene synteny as a basis, it is clear that an analysis of gene conservation across the Streptomyces and various other Actinomycetales will provide information on both the importance of genes and gene clusters and the evolution of morphogenesis in these bacteria. Genome sequencing, although becoming cheaper, is still relatively expensive for comparing large numbers of strains. Thus, a heterologous DNA/DNA microarray hybridization dataset based on a Streptomyces coelicolor microarray allows a cheaper and greater depth of analysis of gene conservation. This study, using both bioinformatical and microarray approaches, was able to classify genes previously identified as involved in morphogenesis in Streptomyces into various subgroups in terms of conservation across species and genera. This will allow the targeting of genes for further study based on their importance at the species level and at higher evolutionary levels.

Analysis of mutations in oral poliovirus vaccine by hybridization with generic oligonucleotide microchips.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Proudnikov, D.; Kirillov, E.; Chumakov, K.

2000-01-01

This paper describes use of a new technology of hybridization with a micro-array of immobilized oligonucleotides for detection and quantification of neurovirulent mutants in Oral Poliovirus Vaccine (OPV). We used a micro-array consisting of three-dimensional gel-elements containing all possible hexamers (total of 4096 probes). Hybridization of fluorescently labelled viral cDNA samples with such microchips resulted in a pattern of spots that was registered and quantified by a computer-linked CCD camera, so that the sequence of the original cDNA could be deduced. The method could reliably identify single point mutations, since each of them affected fluorescence intensity of 12 micro-array elements.more » Micro-array hybridization of DNA mixtures with varying contents of point mutants demonstrated that the method can detect as little as 10% of revertants in a population of vaccine virus. This new technology should be useful for quality control of live viral vaccines, as well as for other applications requiring identification and quantification of point mutations.« less

Sequencing ebola and marburg viruses genomes using microarrays.

PubMed

Hardick, Justin; Woelfel, Roman; Gardner, Warren; Ibrahim, Sofi

2016-08-01

Periodic outbreaks of Ebola and Marburg hemorrhagic fevers have occurred in Africa over the past four decades with case fatality rates reaching as high as 90%. The latest Ebola outbreak in West Africa in 2014 raised concerns that these infections can spread across continents and pose serious health risks. Early and accurate identification of the causative agents is necessary to contain outbreaks. In this report, we describe sequencing-by-hybridization (SBH) technique using high density microarrays to identify Ebola and Marburg viruses. The microarrays were designed to interrogate the sequences of entire viral genomes, and were evaluated with three species of Ebolavirus (Reston, Sudan, and Zaire), and three strains of Marburgvirus (Angola, Musoke, and Ravn). The results showed that the consensus sequences generated with four or more hybridizations had 92.1-98.9% accuracy over 95-99% of the genomes. Additionally, with SBH microarrays it was possible to distinguish between different strains of the Lake Victoria Marburgvirus. J. Med. Virol. 88:1303-1308, 2016. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

Cross species analysis of microarray expression data

PubMed Central

Lu, Yong; Huggins, Peter; Bar-Joseph, Ziv

2009-01-01

Motivation: Many biological systems operate in a similar manner across a large number of species or conditions. Cross-species analysis of sequence and interaction data is often applied to determine the function of new genes. In contrast to these static measurements, microarrays measure the dynamic, condition-specific response of complex biological systems. The recent exponential growth in microarray expression datasets allows researchers to combine expression experiments from multiple species to identify genes that are not only conserved in sequence but also operated in a similar way in the different species studied. Results: In this review we discuss the computational and technical challenges associated with these studies, the approaches that have been developed to address these challenges and the advantages of cross-species analysis of microarray data. We show how successful application of these methods lead to insights that cannot be obtained when analyzing data from a single species. We also highlight current open problems and discuss possible ways to address them. Contact: zivbj@cs.cmu.edu PMID:19357096

Evaluation of chronic lymphocytic leukemia by oligonucleotide-based microarray analysis uncovers novel aberrations not detected by FISH or cytogenetic analysis

PubMed Central

2011-01-01

Background Cytogenetic evaluation is a key component of the diagnosis and prognosis of chronic lymphocytic leukemia (CLL). We performed oligonucleotide-based comparative genomic hybridization microarray analysis on 34 samples with CLL and known abnormal karyotypes previously determined by cytogenetics and/or fluorescence in situ hybridization (FISH). Results Using a custom designed microarray that targets >1800 genes involved in hematologic disease and other malignancies, we identified additional cryptic aberrations and novel findings in 59% of cases. These included gains and losses of genes associated with cell cycle regulation, apoptosis and susceptibility loci on 3p21.31, 5q35.2q35.3, 10q23.31q23.33, 11q22.3, and 22q11.23. Conclusions Our results show that microarray analysis will detect known aberrations, including microscopic and cryptic alterations. In addition, novel genomic changes will be uncovered that may become important prognostic predictors or treatment targets for CLL in the future. PMID:22087757

Clustering gene expression data based on predicted differential effects of GV interaction.

PubMed

Pan, Hai-Yan; Zhu, Jun; Han, Dan-Fu

2005-02-01

Microarray has become a popular biotechnology in biological and medical research. However, systematic and stochastic variabilities in microarray data are expected and unavoidable, resulting in the problem that the raw measurements have inherent "noise" within microarray experiments. Currently, logarithmic ratios are usually analyzed by various clustering methods directly, which may introduce bias interpretation in identifying groups of genes or samples. In this paper, a statistical method based on mixed model approaches was proposed for microarray data cluster analysis. The underlying rationale of this method is to partition the observed total gene expression level into various variations caused by different factors using an ANOVA model, and to predict the differential effects of GV (gene by variety) interaction using the adjusted unbiased prediction (AUP) method. The predicted GV interaction effects can then be used as the inputs of cluster analysis. We illustrated the application of our method with a gene expression dataset and elucidated the utility of our approach using an external validation.

An in silico model for identification of small RNAs in whole bacterial genomes: characterization of antisense RNAs in pathogenic Escherichia coli and Streptococcus agalactiae strains.

PubMed

Pichon, Christophe; du Merle, Laurence; Caliot, Marie Elise; Trieu-Cuot, Patrick; Le Bouguénec, Chantal

2012-04-01

Characterization of small non-coding ribonucleic acids (sRNA) among the large volume of data generated by high-throughput RNA-seq or tiling microarray analyses remains a challenge. Thus, there is still a need for accurate in silico prediction methods to identify sRNAs within a given bacterial species. After years of effort, dedicated software were developed based on comparative genomic analyses or mathematical/statistical models. Although these genomic analyses enabled sRNAs in intergenic regions to be efficiently identified, they all failed to predict antisense sRNA genes (asRNA), i.e. RNA genes located on the DNA strand complementary to that which encodes the protein. The statistical models enabled any genomic region to be analyzed theorically but not efficiently. We present a new model for in silico identification of sRNA and asRNA candidates within an entire bacterial genome. This model was successfully used to analyze the Gram-negative Escherichia coli and Gram-positive Streptococcus agalactiae. In both bacteria, numerous asRNAs are transcribed from the complementary strand of genes located in pathogenicity islands, strongly suggesting that these asRNAs are regulators of the virulence expression. In particular, we characterized an asRNA that acted as an enhancer-like regulator of the type 1 fimbriae production involved in the virulence of extra-intestinal pathogenic E. coli.

An in silico model for identification of small RNAs in whole bacterial genomes: characterization of antisense RNAs in pathogenic Escherichia coli and Streptococcus agalactiae strains

PubMed Central

Pichon, Christophe; du Merle, Laurence; Caliot, Marie Elise; Trieu-Cuot, Patrick; Le Bouguénec, Chantal

2012-01-01

Characterization of small non-coding ribonucleic acids (sRNA) among the large volume of data generated by high-throughput RNA-seq or tiling microarray analyses remains a challenge. Thus, there is still a need for accurate in silico prediction methods to identify sRNAs within a given bacterial species. After years of effort, dedicated software were developed based on comparative genomic analyses or mathematical/statistical models. Although these genomic analyses enabled sRNAs in intergenic regions to be efficiently identified, they all failed to predict antisense sRNA genes (asRNA), i.e. RNA genes located on the DNA strand complementary to that which encodes the protein. The statistical models enabled any genomic region to be analyzed theorically but not efficiently. We present a new model for in silico identification of sRNA and asRNA candidates within an entire bacterial genome. This model was successfully used to analyze the Gram-negative Escherichia coli and Gram-positive Streptococcus agalactiae. In both bacteria, numerous asRNAs are transcribed from the complementary strand of genes located in pathogenicity islands, strongly suggesting that these asRNAs are regulators of the virulence expression. In particular, we characterized an asRNA that acted as an enhancer-like regulator of the type 1 fimbriae production involved in the virulence of extra-intestinal pathogenic E. coli. PMID:22139924

Genome-wide analysis of murine renal distal convoluted tubular cells for the target genes of mineralocorticoid receptor

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ueda, Kohei; Fujiki, Katsunori; Shirahige, Katsuhiko

Highlights: • We define a target gene of MR as that with MR-binding to the adjacent region of DNA. • We use ChIP-seq analysis in combination with microarray. • We, for the first time, explore the genome-wide binding profile of MR. • We reveal 5 genes as the direct target genes of MR in the renal epithelial cell-line. - Abstract: Background and objective: Mineralocorticoid receptor (MR) is a member of nuclear receptor family proteins and contributes to fluid homeostasis in the kidney. Although aldosterone-MR pathway induces several gene expressions in the kidney, it is often unclear whether the gene expressionsmore » are accompanied by direct regulations of MR through its binding to the regulatory region of each gene. The purpose of this study is to identify the direct target genes of MR in a murine distal convoluted tubular epithelial cell-line (mDCT). Methods: We analyzed the DNA samples of mDCT cells overexpressing 3xFLAG-hMR after treatment with 10{sup −7} M aldosterone for 1 h by chromatin immunoprecipitation with deep-sequence (ChIP-seq) and mRNA of the cell-line with treatment of 10{sup −7} M aldosterone for 3 h by microarray. Results: 3xFLAG-hMR overexpressed in mDCT cells accumulated in the nucleus in response to 10{sup −9} M aldosterone. Twenty-five genes were indicated as the candidate target genes of MR by ChIP-seq and microarray analyses. Five genes, Sgk1, Fkbp5, Rasl12, Tns1 and Tsc22d3 (Gilz), were validated as the direct target genes of MR by quantitative RT-qPCR and ChIP-qPCR. MR binding regions adjacent to Ctgf and Serpine1 were also validated. Conclusions: We, for the first time, captured the genome-wide distribution of MR in mDCT cells and, furthermore, identified five MR target genes in the cell-line. These results will contribute to further studies on the mechanisms of kidney diseases.« less

Comparative genomic characterization of citrus-associated Xylella fastidiosa strains.

PubMed

da Silva, Vivian S; Shida, Cláudio S; Rodrigues, Fabiana B; Ribeiro, Diógenes C D; de Souza, Alessandra A; Coletta-Filho, Helvécio D; Machado, Marcos A; Nunes, Luiz R; de Oliveira, Regina Costa

2007-12-21

The xylem-inhabiting bacterium Xylella fastidiosa (Xf) is the causal agent of Pierce's disease (PD) in vineyards and citrus variegated chlorosis (CVC) in orange trees. Both of these economically-devastating diseases are caused by distinct strains of this complex group of microorganisms, which has motivated researchers to conduct extensive genomic sequencing projects with Xf strains. This sequence information, along with other molecular tools, have been used to estimate the evolutionary history of the group and provide clues to understand the capacity of Xf to infect different hosts, causing a variety of symptoms. Nonetheless, although significant amounts of information have been generated from Xf strains, a large proportion of these efforts has concentrated on the study of North American strains, limiting our understanding about the genomic composition of South American strains - which is particularly important for CVC-associated strains. This paper describes the first genome-wide comparison among South American Xf strains, involving 6 distinct citrus-associated bacteria. Comparative analyses performed through a microarray-based approach allowed identification and characterization of large mobile genetic elements that seem to be exclusive to South American strains. Moreover, a large-scale sequencing effort, based on Suppressive Subtraction Hybridization (SSH), identified 290 new ORFs, distributed in 135 Groups of Orthologous Elements, throughout the genomes of these bacteria. Results from microarray-based comparisons provide further evidence concerning activity of horizontally transferred elements, reinforcing their importance as major mediators in the evolution of Xf. Moreover, the microarray-based genomic profiles showed similarity between Xf strains 9a5c and Fb7, which is unexpected, given the geographical and chronological differences associated with the isolation of these microorganisms. The newly identified ORFs, obtained by SSH, represent an approximately 10% increase in our current knowledge of the South American Xf gene pool and include new putative virulence factors, as well as novel potential markers for strain identification. Surprisingly, this list of novel elements include sequences previously believed to be unique to North American strains, pointing to the necessity of revising the list of specific markers that may be used for identification of distinct Xf strains.

Oncogene GAEC1 regulates CAPN10 expression which predicts survival in esophageal squamous cell carcinoma

PubMed Central

Chan, Dessy; Tsoi, Miriam Yuen-Tung; Liu, Christina Di; Chan, Sau-Hing; Law, Simon Ying-Kit; Chan, Kwok-Wah; Chan, Yuen-Piu; Gopalan, Vinod; Lam, Alfred King-Yin; Tang, Johnny Cheuk-On

2013-01-01

AIM: To identify the downstream regulated genes of GAEC1 oncogene in esophageal squamous cell carcinoma and their clinicopathological significance. METHODS: The anti-proliferative effect of knocking down the expression of GAEC1 oncogene was studied by using the RNA interference (RNAi) approach through transfecting the GAEC1-overexpressed esophageal carcinoma cell line KYSE150 with the pSilencer vector cloned with a GAEC1-targeted sequence, followed by MTS cell proliferation assay and cell cycle analysis using flow cytometry. RNA was then extracted from the parental, pSilencer-GAEC1-targeted sequence transfected and pSilencer negative control vector transfected KYSE150 cells for further analysis of different patterns in gene expression. Genes differentially expressed with suppressed GAEC1 expression were then determined using Human Genome U133 Plus 2.0 cDNA microarray analysis by comparing with the parental cells and normalized with the pSilencer negative control vector transfected cells. The most prominently regulated genes were then studied by immunohistochemical staining using tissue microarrays to determine their clinicopathological correlations in esophageal squamous cell carcinoma by statistical analyses. RESULTS: The RNAi approach of knocking down gene expression showed the effective suppression of GAEC1 expression in esophageal squamous cell carcinoma cell line KYSE150 that resulted in the inhibition of cell proliferation and increase of apoptotic population. cDNA microarray analysis for identifying differentially expressed genes detected the greatest levels of downregulation of calpain 10 (CAPN10) and upregulation of trinucleotide repeat containing 6C (TNRC6C) transcripts when GAEC1 expression was suppressed. At the tissue level, the high level expression of calpain 10 protein was significantly associated with longer patient survival (month) of esophageal squamous cell carcinoma compared to the patients with low level of calpain 10 expression (37.73 ± 16.33 vs 12.62 ± 12.44, P = 0.032). No significant correction was observed among the TNRC6C protein expression level and the clinocopathologcial features of esophageal squamous cell carcinoma. CONCLUSION: GAEC1 regulates the expression of CAPN10 and TNRC6C downstream. Calpain 10 expression is a potential prognostic marker in patients with esophageal squamous cell carcinoma. PMID:23687414

Molecular and physiological responses to titanium dioxide and cerium oxide nanoparticles in Arabidopsis

EPA Science Inventory

- Changes in tissue transcriptomes and productivity of Arabidopsis thaliana were investigated during exposure of plants to two widely-used engineered metal oxide nanoparticles, titanium dioxide (nano-titanium) and cerium dioxide (nano-cerium). Microarray analyses confirmed that e...

Advances in acute lymphoblastic leukemia.

PubMed

Randolph, Tim R

2004-01-01

Current literature. Acute lymphoblastic leukemia (ALL) is a stem cell disorder characterized by an overproduction of lymphoblasts in the bone marrow that eventually spill into circulation, producing lymphocytosis. As with the other acute leukemias, the most common symptoms experienced by patients include fatigue, bleeding, and recurrent infections resulting from the suppression of normal hematopoiesis in the bone marrow by the accumulating blasts. ALL primarily affects children and exhibits the best response to standard chemotherapy as compared to acute myeloblastic leukemias (AML). Further, remission rates are highest among ALL patients, many of whom are experiencing sustained remissions suggesting cure. In light of early treatment successes, researchers began to investigate modifications of standard treatment regimens to accommodate variability in weight, age, and response to therapy among children with ALL. Individualized treatment plans were implemented where some patients received a reduced intensity course of therapy to minimize drug toxicity while others received drug intensification to maximize response. More recently, research efforts have been directed at the elucidation of leukemogenic mechanisms implicated in ALL to identify specific protein mutants that can be used to design drugs tailored to interfere with the activity of these mutant protein targets. Identification of chimeric proteins produced from chromosomal translocations and gene expression profiles from microarray analyses are the primary techniques used to identify the potential therapeutic targets. Several reliable prognostic indicators have been identified and are being used to improve therapeutic planning and outcome prediction in ALL patients. Individualized treatment regimens have been developed based on the specific characteristics of each patient to minimize treatment related adverse events and maximize response. Through the use of cytogenetic, molecular, and microarray testing, ALL classification schemes have improved and potential therapeutic targets have been identified. It is anticipated that the next major advance in the treatment of ALL will involve the use of designer therapies developed to specifically interfere with particular molecular abnormalities producing the leukemogenic aberration to the normal signal transduction pathways.

Mucin-type O-glycans in Tears of Normal Subjects and Patients with Non-Sjögren’s Dry Eye

PubMed Central

Guzman-Aranguez, Ana; Mantelli, Flavio; Argüeso, Pablo

2009-01-01

Purpose O-linked carbohydrates (O-glycans) contribute to the hydrophilic character of mucins in mucosal tissues. This study aimed to identify the repertoire of O-glycans in the tear film, and the glycosyltransferases associated with their biosynthesis, in normal subjects and patients with non-Sjögren’s dry eye. Methods Human tear fluid was collected from the inferior conjunctival fornix. O-glycans were released by hydrazinolysis, labeled with 2-aminobenzamide, and analyzed by fluorometric, high-performance liquid chromatography (HPLC) coupled with exoglycosidase digestions. O-glycan structures identified in tears were related to potential biosynthetic pathways in human conjunctival epithelium using a glycogene microarray database. Lectin-binding analyses were performed using agglutinins from Arachis hypogaea, Maackia amurensis, and Sambucus nigra. Results The O-glycan profile of human tears consisted primarily of core 1 (Galβ1-3GalNAcα1-Ser/Thr)-based structures. Mono-sialyl O-glycans represented approximately 66% of the glycan pool, being α2-6-sialyl core 1 the predominant O-glycan structure in human tears (48%). Four families of glycosyltranferases potentially related to the biosynthesis of these structures were identified in human conjunctiva. These included thirteen polypeptide-GalNAc-transferases (GALNT), the core 1 β-3-galactosyltransferase (T-synthase), three α2-6-sialyltransferases (ST6GalNAc), and two α2-3-sialyltransferases (ST3Gal). No significant differences in total amount of O-glycans were detected between tears of normal subjects and dry eye patients, by HPLC and lectin blot. Likewise, no differences in glycosyltransferase expression were found by glycogene microarray. Conclusions This study identifies the most common mucin-type O-glycans in human tears and their expected biosynthetic pathways in ocular surface epithelia. Patients with non-Sjögren’s dry eye show no alterations in composition and amount of O-glycans in the tear fluid. PMID:19407012

Chicken interferome: avian interferon-stimulated genes identified by microarray and RNA-seq of primary chick embryo fibroblasts treated with a chicken type I interferon (IFN-α).

PubMed

Giotis, Efstathios S; Robey, Rebecca C; Skinner, Natalie G; Tomlinson, Christopher D; Goodbourn, Stephen; Skinner, Michael A

2016-08-05

Viruses that infect birds pose major threats-to the global supply of chicken, the major, universally-acceptable meat, and as zoonotic agents (e.g. avian influenza viruses H5N1 and H7N9). Controlling these viruses in birds as well as understanding their emergence into, and transmission amongst, humans will require considerable ingenuity and understanding of how different species defend themselves. The type I interferon-coordinated response constitutes the major antiviral innate defence. Although interferon was discovered in chicken cells, details of the response, particularly the identity of hundreds of stimulated genes, are far better described in mammals. Viruses induce interferon-stimulated genes but they also regulate the expression of many hundreds of cellular metabolic and structural genes to facilitate their replication. This study focusses on the potentially anti-viral genes by identifying those induced just by interferon in primary chick embryo fibroblasts. Three transcriptomic technologies were exploited: RNA-seq, a classical 3'-biased chicken microarray and a high density, "sense target", whole transcriptome chicken microarray, with each recognising 120-150 regulated genes (curated for duplication and incorrect assignment of some microarray probesets). Overall, the results are considered robust because 128 of the compiled, curated list of 193 regulated genes were detected by two, or more, of the technologies.

Oligonucleotide microarray for the identification of potential mycotoxigenic fungi

PubMed Central

2010-01-01

Background Mycotoxins are secondary metabolites which are produced by numerous fungi and pose a continuous challenge to the safety and quality of food commodities in South Africa. These toxins have toxicologically relevant effects on humans and animals that eat contaminated foods. In this study, a diagnostic DNA microarray was developed for the identification of the most common food-borne fungi, as well as the genes leading to toxin production. Results A total of 40 potentially mycotoxigenic fungi isolated from different food commodities, as well as the genes that are involved in the mycotoxin synthetic pathways, were analyzed. For fungal identification, oligonucleotide probes were designed by exploiting the sequence variations of the elongation factor 1-alpha (EF-1 α) coding regions and the internal transcribed spacer (ITS) regions of the rRNA gene cassette. For the detection of fungi able to produce mycotoxins, oligonucleotide probes directed towards genes leading to toxin production from different fungal strains were identified in data available in the public domain. The probes selected for fungal identification and the probes specific for toxin producing genes were spotted onto microarray slides. Conclusions The diagnostic microarray developed can be used to identify single pure strains or cultures of potentially mycotoxigenic fungi as well as genes leading to toxin production in both laboratory samples and maize-derived foods offering an interesting potential for microbiological laboratories. PMID:20307326

Detection of clonal evolution in hematopoietic malignancies by combining comparative genomic hybridization and single nucleotide polymorphism arrays.

PubMed

Hartmann, Luise; Stephenson, Christine F; Verkamp, Stephanie R; Johnson, Krystal R; Burnworth, Bettina; Hammock, Kelle; Brodersen, Lisa Eidenschink; de Baca, Monica E; Wells, Denise A; Loken, Michael R; Zehentner, Barbara K

2014-12-01

Array comparative genomic hybridization (aCGH) has become a powerful tool for analyzing hematopoietic neoplasms and identifying genome-wide copy number changes in a single assay. aCGH also has superior resolution compared with fluorescence in situ hybridization (FISH) or conventional cytogenetics. Integration of single nucleotide polymorphism (SNP) probes with microarray analysis allows additional identification of acquired uniparental disomy, a copy neutral aberration with known potential to contribute to tumor pathogenesis. However, a limitation of microarray analysis has been the inability to detect clonal heterogeneity in a sample. This study comprised 16 samples (acute myeloid leukemia, myelodysplastic syndrome, chronic lymphocytic leukemia, plasma cell neoplasm) with complex cytogenetic features and evidence of clonal evolution. We used an integrated manual peak reassignment approach combining analysis of aCGH and SNP microarray data for characterization of subclonal abnormalities. We compared array findings with results obtained from conventional cytogenetic and FISH studies. Clonal heterogeneity was detected in 13 of 16 samples by microarray on the basis of log2 values. Use of the manual peak reassignment analysis approach improved resolution of the sample's clonal composition and genetic heterogeneity in 10 of 13 (77%) patients. Moreover, in 3 patients, clonal disease progression was revealed by array analysis that was not evident by cytogenetic or FISH studies. Genetic abnormalities originating from separate clonal subpopulations can be identified and further characterized by combining aCGH and SNP hybridization results from 1 integrated microarray chip by use of the manual peak reassignment technique. Its clinical utility in comparison to conventional cytogenetic or FISH studies is demonstrated. © 2014 American Association for Clinical Chemistry.

A bioinformatics approach to identify patients with symptomatic peanut allergy using peptide microarray immunoassay

PubMed Central

Lin, Jing; Bruni, Francesca M.; Fu, Zhiyan; Maloney, Jennifer; Bardina, Ludmilla; Boner, Attilio L.; Gimenez, Gustavo; Sampson, Hugh A.

2013-01-01

Background Peanut allergy is relatively common, typically permanent, and often severe. Double-blind, placebo-controlled food challenge is considered the gold standard for the diagnosis of food allergy–related disorders. However, the complexity and potential of double-blind, placebo-controlled food challenge to cause life-threatening allergic reactions affects its clinical application. A laboratory test that could accurately diagnose symptomatic peanut allergy would greatly facilitate clinical practice. Objective We sought to develop an allergy diagnostic method that could correctly predict symptomatic peanut allergy by using peptide microarray immunoassays and bioinformatic methods. Methods Microarray immunoassays were performed by using the sera from 62 patients (31 with symptomatic peanut allergy and 31 who had outgrown their peanut allergy or were sensitized but were clinically tolerant to peanut). Specific IgE and IgG4 binding to 419 overlapping peptides (15 mers, 3 offset) covering the amino acid sequences of Ara h 1, Ara h 2, and Ara h 3 were measured by using a peptide microarray immunoassay. Bioinformatic methods were applied for data analysis. Results Individuals with peanut allergy showed significantly greater IgE binding and broader epitope diversity than did peanut-tolerant individuals. No significant difference in IgG4 binding was found between groups. By using machine learning methods, 4 peptide biomarkers were identified and prediction models that can predict the outcome of double-blind, placebo-controlled food challenges with high accuracy were developed by using a combination of the biomarkers. Conclusions In this study, we developed a novel diagnostic approach that can predict peanut allergy with high accuracy by combining the results of a peptide microarray immunoassay and bioinformatic methods. Further studies are needed to validate the efficacy of this assay in clinical practice. PMID:22444503

An unsupervised hierarchical dynamic self-organizing approach to cancer class discovery and marker gene identification in microarray data.

PubMed

Hsu, Arthur L; Tang, Sen-Lin; Halgamuge, Saman K

2003-11-01

Current Self-Organizing Maps (SOMs) approaches to gene expression pattern clustering require the user to predefine the number of clusters likely to be expected. Hierarchical clustering methods used in this area do not provide unique partitioning of data. We describe an unsupervised dynamic hierarchical self-organizing approach, which suggests an appropriate number of clusters, to perform class discovery and marker gene identification in microarray data. In the process of class discovery, the proposed algorithm identifies corresponding sets of predictor genes that best distinguish one class from other classes. The approach integrates merits of hierarchical clustering with robustness against noise known from self-organizing approaches. The proposed algorithm applied to DNA microarray data sets of two types of cancers has demonstrated its ability to produce the most suitable number of clusters. Further, the corresponding marker genes identified through the unsupervised algorithm also have a strong biological relationship to the specific cancer class. The algorithm tested on leukemia microarray data, which contains three leukemia types, was able to determine three major and one minor cluster. Prediction models built for the four clusters indicate that the prediction strength for the smaller cluster is generally low, therefore labelled as uncertain cluster. Further analysis shows that the uncertain cluster can be subdivided further, and the subdivisions are related to two of the original clusters. Another test performed using colon cancer microarray data has automatically derived two clusters, which is consistent with the number of classes in data (cancerous and normal). JAVA software of dynamic SOM tree algorithm is available upon request for academic use. A comparison of rectangular and hexagonal topologies for GSOM is available from http://www.mame.mu.oz.au/mechatronics/journalinfo/Hsu2003supp.pdf

Linking microarray reporters with protein functions

PubMed Central

Gaj, Stan; van Erk, Arie; van Haaften, Rachel IM; Evelo, Chris TA

2007-01-01

Background The analysis of microarray experiments requires accurate and up-to-date functional annotation of the microarray reporters to optimize the interpretation of the biological processes involved. Pathway visualization tools are used to connect gene expression data with existing biological pathways by using specific database identifiers that link reporters with elements in the pathways. Results This paper proposes a novel method that aims to improve microarray reporter annotation by BLASTing the original reporter sequences against a species-specific EMBL subset, that was derived from and crosslinked back to the highly curated UniProt database. The resulting alignments were filtered using high quality alignment criteria and further compared with the outcome of a more traditional approach, where reporter sequences were BLASTed against EnsEMBL followed by locating the corresponding protein (UniProt) entry for the high quality hits. Combining the results of both methods resulted in successful annotation of > 58% of all reporter sequences with UniProt IDs on two commercial array platforms, increasing the amount of Incyte reporters that could be coupled to Gene Ontology terms from 32.7% to 58.3% and to a local GenMAPP pathway from 9.6% to 16.7%. For Agilent, 35.3% of the total reporters are now linked towards GO nodes and 7.1% on local pathways. Conclusion Our methods increased the annotation quality of microarray reporter sequences and allowed us to visualize more reporters using pathway visualization tools. Even in cases where the original reporter annotation showed the correct description the new identifiers often allowed improved pathway and Gene Ontology linking. These methods are freely available at http://www.bigcat.unimaas.nl/public/publications/Gaj_Annotation/. PMID:17897448

Association of HADHA expression with the risk of breast cancer: targeted subset analysis and meta-analysis of microarray data

PubMed Central

2012-01-01

Background The role of n-3 fatty acids in prevention of breast cancer is well recognized, but the underlying molecular mechanisms are still unclear. In view of the growing need for early detection of breast cancer, Graham et al. (2010) studied the microarray gene expression in histologically normal epithelium of subjects with or without breast cancer. We conducted a secondary analysis of this dataset with a focus on the genes (n = 47) involved in fat and lipid metabolism. We used stepwise multivariate logistic regression analyses, volcano plots and false discovery rates for association analyses. We also conducted meta-analyses of other microarray studies using random effects models for three outcomes--risk of breast cancer (380 breast cancer patients and 240 normal subjects), risk of metastasis (430 metastatic compared to 1104 non-metastatic breast cancers) and risk of recurrence (484 recurring versus 890 non-recurring breast cancers). Results The HADHA gene [hydroxyacyl-CoA dehydrogenase/3-ketoacyl-CoA thiolase/enoyl-CoA hydratase (trifunctional protein), alpha subunit] was significantly under-expressed in breast cancer; more so in those with estrogen receptor-negative status. Our meta-analysis showed an 18.4%-26% reduction in HADHA expression in breast cancer. Also, there was an inconclusive but consistent under-expression of HADHA in subjects with metastatic and recurring breast cancers. Conclusions Involvement of mitochondria and the mitochondrial trifunctional protein (encoded by HADHA gene) in breast carcinogenesis is known. Our results lend additional support to the possibility of this involvement. Further, our results suggest that targeted subset analysis of large genome-based datasets can provide interesting association signals. PMID:22240105

Advances in analytical methodologies to guide bioprocess engineering for bio-therapeutics.

PubMed

Saldova, Radka; Kilcoyne, Michelle; Stöckmann, Henning; Millán Martín, Silvia; Lewis, Amanda M; Tuite, Catherine M E; Gerlach, Jared Q; Le Berre, Marie; Borys, Michael C; Li, Zheng Jian; Abu-Absi, Nicholas R; Leister, Kirk; Joshi, Lokesh; Rudd, Pauline M

2017-03-01

This study was performed to monitor the glycoform distribution of a recombinant antibody fusion protein expressed in CHO cells over the course of fed-batch bioreactor runs using high-throughput methods to accurately determine the glycosylation status of the cell culture and its product. Three different bioreactors running similar conditions were analysed at the same five time-points using the advanced methods described here. N-glycans from cell and secreted glycoproteins from CHO cells were analysed by HILIC-UPLC and MS, and the total glycosylation (both N- and O-linked glycans) secreted from the CHO cells were analysed by lectin microarrays. Cell glycoproteins contained mostly high mannose type N-linked glycans with some complex glycans; sialic acid was α-(2,3)-linked, galactose β-(1,4)-linked, with core fucose. Glycans attached to secreted glycoproteins were mostly complex with sialic acid α-(2,3)-linked, galactose β-(1,4)-linked, with mostly core fucose. There were no significant differences noted among the bioreactors in either the cell pellets or supernatants using the HILIC-UPLC method and only minor differences at the early time-points of days 1 and 3 by the lectin microarray method. In comparing different time-points, significant decreases in sialylation and branching with time were observed for glycans attached to both cell and secreted glycoproteins. Additionally, there was a significant decrease over time in high mannose type N-glycans from the cell glycoproteins. A combination of the complementary methods HILIC-UPLC and lectin microarrays could provide a powerful and rapid HTP profiling tool capable of yielding qualitative and quantitative data for a defined biopharmaceutical process, which would allow valuable near 'real-time' monitoring of the biopharmaceutical product. Copyright © 2016 Elsevier Inc. All rights reserved.

Identification of miR-15b as a transformation-related factor in mantle cell lymphoma.

PubMed

Arakawa, Fumiko; Kimura, Yoshizo; Yoshida, Noriaki; Miyoshi, Hiroaki; Doi, Atushi; Yasuda, Kaori; Nakajima, Kazutaka; Kiyasu, Junichi; Niino, Daisuke; Sugita, Yasuo; Tashiro, Kosuke; Kuhara, Satoru; Seto, Masao; Ohshima, Koichi

2016-02-01

Mantle cell lymphoma (MCL) is an aggressive B cell lymphoma with a poor prognosis. It is characterized by the t(11;14)(q13;q32) translocation, resulting in over-expression of CCND1. Morphologically, MCL is categorised into two types: classical MCL (cMCL) and aggressive MCL (aMCL), with a proportion of cMCL progressing to develop into aMCL. miRNAs are currently considered to be important regulators for cell behavior and are deregulated in many malignancies. Although several genetic alterations have been implicated in the transformation of cMCL to aMCL, the involvement of miRNAs in transformation is not known. In an effort to identify the miRNAs related to the transformation of MCL, miRNA microarray analyses were used for cMCL and aMCL cases. These analyses demonstrated significant differences in the expression of seven microRNAs based on a t-test (p-value <0.05); miR-15b was greatly upregulated in aMCL. Locked nucleic acid in situ hybridization showed increased staining of miR-15b in formalin-fixed paraffin-embedded sections of aMCL. These results correlated well with the microRNA microarray analysis. Although the molecular functions of miR-15b are largely unknown, it has been found to be associated with the cell cycle and apoptosis. However, the physiological significance of increased miR-15b in MCL is still unknown. Our present findings suggest that the upregulated expression of miR-15b is likely to play an important role in the trans-formation of cMCL to aMCL.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Balduino, Alex, E-mail: balduino@uva.edu.br; Mello-Coelho, Valeria; National Institute on Aging, National Institute of Health, Baltimore, MD

In the bone marrow cavity, hematopoietic stem cells (HSC) have been shown to reside in the endosteal and subendosteal perivascular niches, which play specific roles on HSC maintenance. Although cells with long-term ability to reconstitute full hematopoietic system can be isolated from both niches, several data support a heterogenous distribution regarding the cycling behavior of HSC. Whether this distinct behavior depends upon the role played by the stromal populations which distinctly create these two niches is a question that remains open. In the present report, we used our previously described in vivo assay to demonstrate that endosteal and subendosteal stromalmore » populations are very distinct regarding skeletal lineage differentiation potential. This was further supported by a microarray-based analysis, which also demonstrated that these two stromal populations play distinct, albeit complementary, roles in HSC niche. Both stromal populations were preferentially isolated from the trabecular region and behave distinctly in vitro, as previously reported. Even though these two niches are organized in a very close range, in vivo assays and molecular analyses allowed us to identify endosteal stroma (F-OST) cells as fully committed osteoblasts and subendosteal stroma (F-RET) cells as uncommitted mesenchymal cells mainly represented by perivascular reticular cells expressing high levels of chemokine ligand, CXCL12. Interestingly, a number of cytokines and growth factors including interleukin-6 (IL-6), IL-7, IL-15, Hepatocyte growth factor (HGF) and stem cell factor (SCF) matrix metalloproteases (MMPs) were also found to be differentially expressed by F-OST and F-RET cells. Further microarray analyses indicated important mechanisms used by the two stromal compartments in order to create and coordinate the 'quiescent' and 'proliferative' niches in which hematopoietic stem cells and progenitors reside.« less

The Development of Translational Biomarkers as a Tool for Improving the Understanding, Diagnosis and Treatment of Chronic Neuropathic Pain.

PubMed

Buckley, David A; Jennings, Elaine M; Burke, Nikita N; Roche, Michelle; McInerney, Veronica; Wren, Jonathan D; Finn, David P; McHugh, Patrick C

2018-03-01

Chronic neuropathic pain (CNP) is one of the most significant unmet clinical needs in modern medicine. Alongside the lack of effective treatments, there is a great deficit in the availability of objective diagnostic methods to reliably facilitate an accurate diagnosis. We therefore aimed to determine the feasibility of a simple diagnostic test by analysing differentially expressed genes in the blood of patients diagnosed with CNP of the lower back and compared to healthy human controls. Refinement of microarray expression data was performed using correlation analysis with 3900 human 2-colour microarray experiments. Selected genes were analysed in the dorsal horn of Sprague-Dawley rats after L5 spinal nerve ligation (SNL), using qRT-PCR and ddPCR, to determine possible associations with pathophysiological mechanisms underpinning CNP and whether they represent translational biomarkers of CNP. We found that of the 15 potential biomarkers identified, tissue inhibitor of matrix metalloproteinase-1 (TIMP1) gene expression was upregulated in chronic neuropathic lower back pain (CNBP) (p = 0.0049) which positively correlated (R = 0.68, p = ≤0.05) with increased plasma TIMP1 levels in this group (p = 0.0433). Moreover, plasma TIMP1 was also significantly upregulated in CNBP than chronic inflammatory lower back pain (p = 0.0272). In the SNL model, upregulation of the Timp1 gene was also observed (p = 0.0058) alongside a strong trend for the upregulation of melanocortin 1 receptor (p = 0.0847). Our data therefore highlights several genes that warrant further investigation, and of these, TIMP1 shows the greatest potential as an accessible and translational CNP biomarker.

Gene expression profiling in human skeletal muscle during recovery from eccentric exercise

PubMed Central

Mohoney, D. J.; Safdar, A.; Parise, G.; Melov, S.; Fu, Minghua; MacNeil, L.; Kaczor, J.; Payne, E. T.; Tarnopolsky, M. A.

2009-01-01

We used cDNA microarrays to screen for differentially expressed genes during recovery from exercise-induced muscle damage in humans. Male subjects (n = 4) performed 300 maximal eccentric contractions, and skeletal muscle biopsy samples were analyzed at 3 h and 48 h after exercise. In total, 113 genes increased 3 h postexercise, and 34 decreased. At 48 h postexercise, 59 genes increased and 29 decreased. On the basis of these data, we chose 19 gene changes and conducted secondary analyses using real-time RT-PCR from muscle biopsy samples taken from 11 additional subjects who performed an identical bout of exercise. Real-time RT-PCR analyses confirmed that exercise-induced muscle damage led to a rapid (3 h) increase in sterol response element binding protein 2 (SREBP-2), followed by a delayed (48 h) increase in the SREBP-2 gene targets Acyl CoA:cholesterol acyltransferase (ACAT)-2 and insulin-induced gene 1 (insig-1). The expression of the IL-1 receptor, a known regulator of SREBP-2, was also elevated after exercise. Taken together, these expression changes suggest a transcriptional program for increasing cholesterol and lipid synthesis and/or modification. Additionally, damaging exercise induced the expression of protein kinase H11, capping protein Z alpha (capZα), and modulatory calcineurin-interacting protein 1 (MCIP1), as well as cardiac ankryin repeat protein 1 (CARP1), DNAJB2, c-myc, and junD, each of which are likely involved in skeletal muscle growth, remodeling, and stress management. In summary, using DNA microarrays and RT-PCR, we have identified novel genes that respond to skeletal muscle damage, which, given the known biological functions, are likely involved in recovery from and/or adaptation to damaging exercise. PMID:18321953

BμG@Sbase—a microbial gene expression and comparative genomic database

PubMed Central

Witney, Adam A.; Waldron, Denise E.; Brooks, Lucy A.; Tyler, Richard H.; Withers, Michael; Stoker, Neil G.; Wren, Brendan W.; Butcher, Philip D.; Hinds, Jason

2012-01-01

The reducing cost of high-throughput functional genomic technologies is creating a deluge of high volume, complex data, placing the burden on bioinformatics resources and tool development. The Bacterial Microarray Group at St George's (BμG@S) has been at the forefront of bacterial microarray design and analysis for over a decade and while serving as a hub of a global network of microbial research groups has developed BμG@Sbase, a microbial gene expression and comparative genomic database. BμG@Sbase (http://bugs.sgul.ac.uk/bugsbase/) is a web-browsable, expertly curated, MIAME-compliant database that stores comprehensive experimental annotation and multiple raw and analysed data formats. Consistent annotation is enabled through a structured set of web forms, which guide the user through the process following a set of best practices and controlled vocabulary. The database currently contains 86 expertly curated publicly available data sets (with a further 124 not yet published) and full annotation information for 59 bacterial microarray designs. The data can be browsed and queried using an explorer-like interface; integrating intuitive tree diagrams to present complex experimental details clearly and concisely. Furthermore the modular design of the database will provide a robust platform for integrating other data types beyond microarrays into a more Systems analysis based future. PMID:21948792

BμG@Sbase--a microbial gene expression and comparative genomic database.

PubMed

Witney, Adam A; Waldron, Denise E; Brooks, Lucy A; Tyler, Richard H; Withers, Michael; Stoker, Neil G; Wren, Brendan W; Butcher, Philip D; Hinds, Jason

2012-01-01

The reducing cost of high-throughput functional genomic technologies is creating a deluge of high volume, complex data, placing the burden on bioinformatics resources and tool development. The Bacterial Microarray Group at St George's (BμG@S) has been at the forefront of bacterial microarray design and analysis for over a decade and while serving as a hub of a global network of microbial research groups has developed BμG@Sbase, a microbial gene expression and comparative genomic database. BμG@Sbase (http://bugs.sgul.ac.uk/bugsbase/) is a web-browsable, expertly curated, MIAME-compliant database that stores comprehensive experimental annotation and multiple raw and analysed data formats. Consistent annotation is enabled through a structured set of web forms, which guide the user through the process following a set of best practices and controlled vocabulary. The database currently contains 86 expertly curated publicly available data sets (with a further 124 not yet published) and full annotation information for 59 bacterial microarray designs. The data can be browsed and queried using an explorer-like interface; integrating intuitive tree diagrams to present complex experimental details clearly and concisely. Furthermore the modular design of the database will provide a robust platform for integrating other data types beyond microarrays into a more Systems analysis based future.

Tissue microarray immunohistochemical detection of brachyury is not a prognostic indicator in chordoma.

PubMed

Zhang, Linlin; Guo, Shang; Schwab, Joseph H; Nielsen, G Petur; Choy, Edwin; Ye, Shunan; Zhang, Zhan; Mankin, Henry; Hornicek, Francis J; Duan, Zhenfeng

2013-01-01

Brachyury is a marker for notochord-derived tissues and neoplasms, such as chordoma. However, the prognostic relevance of brachyury expression in chordoma is still unknown. The improvement of tissue microarray technology has provided the opportunity to perform analyses of tumor tissues on a large scale in a uniform and consistent manner. This study was designed with the use of tissue microarray to determine the expression of brachyury. Brachyury expression in chordoma tissues from 78 chordoma patients was analyzed by immunohistochemical staining of tissue microarray. The clinicopathologic parameters, including gender, age, location of tumor and metastatic status were evaluated. Fifty-nine of 78 (75.64%) tumors showed nuclear staining for brachyury, and among them, 29 tumors (49.15%) showed 1+ (<30% positive cells) staining, 15 tumors (25.42%) had 2+ (31% to 60% positive cells) staining, and 15 tumors (25.42%) demonstrated 3+ (61% to 100% positive cells) staining. Brachyury nuclear staining was detected more frequently in sacral chordomas than in chordomas of the mobile spine. However, there was no significant relationship between brachyury expression and other clinical variables. By Kaplan-Meier analysis, brachyury expression failed to produce any significant relationship with the overall survival rate. In conclusion, brachyury expression is not a prognostic indicator in chordoma.

eSensor: an electrochemical detection-based DNA microarray technology enabling sample-to-answer molecular diagnostics

NASA Astrophysics Data System (ADS)

Liu, Robin H.; Longiaru, Mathew

2009-05-01

DNA microarrays are becoming a widespread tool used in life science and drug screening due to its many benefits of miniaturization and integration. Microarrays permit a highly multiplexed DNA analysis. Recently, the development of new detection methods and simplified methodologies has rapidly expanded the use of microarray technologies from predominantly gene expression analysis into the arena of diagnostics. Osmetech's eSensor® is an electrochemical detection platform based on a low-to- medium density DNA hybridization array on a cost-effective printed circuit board substrate. eSensor® has been cleared by FDA for Warfarin sensitivity test and Cystic Fibrosis Carrier Detection. Other genetic-based diagnostic and infectious disease detection tests are under development. The eSensor® platform eliminates the need for an expensive laser-based optical system and fluorescent reagents. It allows one to perform hybridization and detection in a single and small instrument without any fluidic processing and handling. Furthermore, the eSensor® platform is readily adaptable to on-chip sample-to-answer genetic analyses using microfluidics technology. The eSensor® platform provides a cost-effective solution to direct sample-to-answer genetic analysis, and thus have a potential impact in the fields of point-of-care genetic analysis, environmental testing, and biological warfare agent detection.

Curation of microarray oligonucleotides and corresponding ESTs/cDNAs used for gene expression analysis in zebra finches.

PubMed

Lovell, Peter V; Huizinga, Nicole A; Getachew, Abel; Mees, Brianna; Friedrich, Samantha R; Wirthlin, Morgan; Mello, Claudio V

2018-05-18

Zebra finches are a major model organism for investigating mechanisms of vocal learning, a trait that enables spoken language in humans. The development of cDNA collections with expressed sequence tags (ESTs) and microarrays has allowed for extensive molecular characterizations of circuitry underlying vocal learning and production. However, poor database curation can lead to errors in transcriptome and bioinformatics analyses, limiting the impact of these resources. Here we used genomic alignments and synteny analysis for orthology verification to curate and reannotate ~ 35% of the oligonucleotides and corresponding ESTs/cDNAs that make-up Agilent microarrays for gene expression analysis in finches. We found that: (1) 5475 out of 43,084 oligos (a) failed to align to the zebra finch genome, (b) aligned to multiple loci, or (c) aligned to Chr_un only, and thus need to be flagged until a better genome assembly is available, or (d) reflect cloning artifacts; (2) Out of 9635 valid oligos examined further, 3120 were incorrectly named, including 1533 with no known orthologs; and (3) 2635 oligos required name update. The resulting curated dataset provides a reference for correcting gene identification errors in previous finch microarrays studies, and avoiding such errors in future studies.

Identification of novel genes potentially involved in somatic embryogenesis in chicory (Cichorium intybus L.)

PubMed Central

2010-01-01

Background In our laboratory we use cultured chicory (Cichorium intybus) explants as a model to investigate cell reactivation and somatic embryogenesis and have produced 2 chicory genotypes (K59, C15) sharing a similar genetic background. K59 is a responsive genotype (embryogenic) capable of undergoing complete cell reactivation i.e. cell de- and re-differentiation leading to somatic embryogenesis (SE), whereas C15 is a non-responsive genotype (non-embryogenic) and is unable to undergo SE. Previous studies [1] showed that the use of the β-D-glucosyl Yariv reagent (β-GlcY) that specifically binds arabinogalactan-proteins (AGPs) blocked somatic embryo production in chicory root explants. This observation indicates that β-GlcY is a useful tool for investigating somatic embryogenesis (SE) in chicory. In addition, a putative AGP (DT212818) encoding gene was previously found to be significantly up-regulated in the embryogenic K59 chicory genotype as compared to the non-embryogenic C15 genotype suggesting that this AGP could be involved in chicory re-differentiation [2]. In order to improve our understanding of the molecular and cellular regulation underlying SE in chicory, we undertook a detailed cytological study of cell reactivation events in K59 and C15 genotypes, and used microarray profiling to compare gene expression in these 2 genotypes. In addition we also used β-GlcY to block SE in order to identify genes potentially involved in this process. Results Microscopy confirmed that only the K59, but not the C15 genotype underwent complete cell reactivation leading to SE formation. β-GlcY-treatment of explants blocked in vitro SE induction, but not cell reactivation, and induced cell wall modifications. Microarray analyses revealed that 78 genes were differentially expressed between induced K59 and C15 genotypes. The expression profiles of 19 genes were modified by β-GlcY-treatment. Eight genes were both differentially expressed between K59 and C15 genotypes during SE induction and transcriptionally affected by β-GlcY-treatment: AGP (DT212818), 26 S proteasome AAA ATPase subunit 6 (RPT6), remorin (REM), metallothionein-1 (MT1), two non-specific lipid transfer proteins genes (SDI-9 and DEA1), 3-hydroxy-3-methylglutaryl-CoA reductase (HMG-CoA reductase), and snakin 2 (SN2). These results suggest that the 8 genes, including the previously-identified AGP gene (DT212818), could be involved in cell fate determination events leading to SE commitment in chicory. Conclusion The use of two different chicory genotypes differing in their responsiveness to SE induction, together with β-GlcY-treatment represented an efficient tool to discriminate cell reactivation from the SE morphogenetic pathway. Such an approach, together with microarray analyses, permitted us to identify several putative key genes related to the SE morphogenetic pathway in chicory. PMID:20565992

caCORRECT2: Improving the accuracy and reliability of microarray data in the presence of artifacts

PubMed Central

2011-01-01

Background In previous work, we reported the development of caCORRECT, a novel microarray quality control system built to identify and correct spatial artifacts commonly found on Affymetrix arrays. We have made recent improvements to caCORRECT, including the development of a model-based data-replacement strategy and integration with typical microarray workflows via caCORRECT's web portal and caBIG grid services. In this report, we demonstrate that caCORRECT improves the reproducibility and reliability of experimental results across several common Affymetrix microarray platforms. caCORRECT represents an advance over state-of-art quality control methods such as Harshlighting, and acts to improve gene expression calculation techniques such as PLIER, RMA and MAS5.0, because it incorporates spatial information into outlier detection as well as outlier information into probe normalization. The ability of caCORRECT to recover accurate gene expressions from low quality probe intensity data is assessed using a combination of real and synthetic artifacts with PCR follow-up confirmation and the affycomp spike in data. The caCORRECT tool can be accessed at the website: http://cacorrect.bme.gatech.edu. Results We demonstrate that (1) caCORRECT's artifact-aware normalization avoids the undesirable global data warping that happens when any damaged chips are processed without caCORRECT; (2) When used upstream of RMA, PLIER, or MAS5.0, the data imputation of caCORRECT generally improves the accuracy of microarray gene expression in the presence of artifacts more than using Harshlighting or not using any quality control; (3) Biomarkers selected from artifactual microarray data which have undergone the quality control procedures of caCORRECT are more likely to be reliable, as shown by both spike in and PCR validation experiments. Finally, we present a case study of the use of caCORRECT to reliably identify biomarkers for renal cell carcinoma, yielding two diagnostic biomarkers with potential clinical utility, PRKAB1 and NNMT. Conclusions caCORRECT is shown to improve the accuracy of gene expression, and the reproducibility of experimental results in clinical application. This study suggests that caCORRECT will be useful to clean up possible artifacts in new as well as archived microarray data. PMID:21957981

Towards the integration, annotation and association of historical microarray experiments with RNA-seq.

PubMed

Chavan, Shweta S; Bauer, Michael A; Peterson, Erich A; Heuck, Christoph J; Johann, Donald J

2013-01-01

Transcriptome analysis by microarrays has produced important advances in biomedicine. For instance in multiple myeloma (MM), microarray approaches led to the development of an effective disease subtyping via cluster assignment, and a 70 gene risk score. Both enabled an improved molecular understanding of MM, and have provided prognostic information for the purposes of clinical management. Many researchers are now transitioning to Next Generation Sequencing (NGS) approaches and RNA-seq in particular, due to its discovery-based nature, improved sensitivity, and dynamic range. Additionally, RNA-seq allows for the analysis of gene isoforms, splice variants, and novel gene fusions. Given the voluminous amounts of historical microarray data, there is now a need to associate and integrate microarray and RNA-seq data via advanced bioinformatic approaches. Custom software was developed following a model-view-controller (MVC) approach to integrate Affymetrix probe set-IDs, and gene annotation information from a variety of sources. The tool/approach employs an assortment of strategies to integrate, cross reference, and associate microarray and RNA-seq datasets. Output from a variety of transcriptome reconstruction and quantitation tools (e.g., Cufflinks) can be directly integrated, and/or associated with Affymetrix probe set data, as well as necessary gene identifiers and/or symbols from a diversity of sources. Strategies are employed to maximize the annotation and cross referencing process. Custom gene sets (e.g., MM 70 risk score (GEP-70)) can be specified, and the tool can be directly assimilated into an RNA-seq pipeline. A novel bioinformatic approach to aid in the facilitation of both annotation and association of historic microarray data, in conjunction with richer RNA-seq data, is now assisting with the study of MM cancer biology.

On the classification techniques in data mining for microarray data classification

NASA Astrophysics Data System (ADS)

Aydadenta, Husna; Adiwijaya

2018-03-01

Cancer is one of the deadly diseases, according to data from WHO by 2015 there are 8.8 million more deaths caused by cancer, and this will increase every year if not resolved earlier. Microarray data has become one of the most popular cancer-identification studies in the field of health, since microarray data can be used to look at levels of gene expression in certain cell samples that serve to analyze thousands of genes simultaneously. By using data mining technique, we can classify the sample of microarray data thus it can be identified with cancer or not. In this paper we will discuss some research using some data mining techniques using microarray data, such as Support Vector Machine (SVM), Artificial Neural Network (ANN), Naive Bayes, k-Nearest Neighbor (kNN), and C4.5, and simulation of Random Forest algorithm with technique of reduction dimension using Relief. The result of this paper show performance measure (accuracy) from classification algorithm (SVM, ANN, Naive Bayes, kNN, C4.5, and Random Forets).The results in this paper show the accuracy of Random Forest algorithm higher than other classification algorithms (Support Vector Machine (SVM), Artificial Neural Network (ANN), Naive Bayes, k-Nearest Neighbor (kNN), and C4.5). It is hoped that this paper can provide some information about the speed, accuracy, performance and computational cost generated from each Data Mining Classification Technique based on microarray data.

Cardiac mesenchymal progenitors from postmortem cardiac tissues retained cellular characterization.

PubMed

Kami, D; Kitani, T; Nakata, M; Gojo, S

2014-05-01

Currently, cells for transplantation in regenerative medicine are derived from either autologous or allogeneic tissue. The former has the drawbacks that the quality of donor cells may depend on the condition of the patient, while the quantity of the cells may also be limited. To solve these problems, we investigated the potential of allogeneic cardiac mesenchymal progenitors (CMPs) derived from postmortem hearts, which may be immunologically privileged similar to bone marrow-derived mesenchymal progenitors. We examined whether viable CMPs could be isolated from C57/B6 murine cardiac tissues harvested at 24 hours postmortem. After 2- to 3-week propagation with a high dose of basic fibroblast growth factor, we performed cellular characteristics analyses, which included proliferation and differentiation property flow cytometry and microarray analyses. Postmortem CMPs had a longer lag phase after seeding than CMPs obtained from living tissues, but otherwise had similar characteristics in all the analyses. In addition, global gene expression analysis by microarray showed that cells derived from postmortem and living tissues had similar characteristics. These results indicate that allogeneic postmortem CMPs have potential for cell transplantation because they circumvent the issue of both the quality and quantity of donor cells. Copyright © 2014 Elsevier Inc. All rights reserved.

Mitochondrial dysfunction, oxidative stress and apoptosis revealed by proteomic and transcriptomic analyses of the striata in two mouse models of Parkinson’s disease

DOE Office of Scientific and Technical Information (OSTI.GOV)

Chin, Mark H.; Qian, Weijun; Wang, Haixing

2008-02-10

The molecular mechanisms underlying the changes in the nigrostriatal pathway in Parkinson disease (PD) are not completely understood. Here we use mass spectrometry and microarrays to study the proteomic and transcriptomic changes in the striatum of two mouse models of PD, induced by the distinct neurotoxins 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP) and methamphetamine (METH). Proteomic analyses resulted in the identification and relative quantification of 912 proteins with two or more unique peptides and 85 proteins with significant abundance changes following neurotoxin treatment. Similarly, microarray analyses revealed 181 genes with significant changes in mRNA following neurotoxin treatment. The combined protein and gene list providesmore » a clearer picture of the potential mechanisms underlying neurodegeneration observed in PD. Functional analysis of this combined list revealed a number of significant categories, including mitochondrial dysfunction, oxidative stress response and apoptosis. Additionally, codon usage and miRNAs may play an important role in translational control in the striatum. These results constitute one of the largest datasets integrating protein and transcript changes for these neurotoxin models with many similar endpoint phenotypes but distinct mechanisms.« less

Gene expression profiling of pre-eclamptic placentae by RNA sequencing.

PubMed

Kaartokallio, Tea; Cervera, Alejandra; Kyllönen, Anjuska; Laivuori, Krista; Kere, Juha; Laivuori, Hannele

2015-09-21

Pre-eclampsia is a common and complex pregnancy disorder that often involves impaired placental development. In order to identify altered gene expression in pre-eclamptic placenta, we sequenced placental transcriptomes of nine pre-eclamptic and nine healthy pregnant women in pools of three. The differential gene expression was tested both by including all the pools in the analysis and by excluding some of the pools based on phenotypic characteristics. From these analyses, we identified altogether 53 differently expressed genes, a subset of which was validated by qPCR in 20 cases and 19 controls. Furthermore, we conducted pathway and functional analyses which revealed disturbed vascular function and immunological balance in pre-eclamptic placenta. Some of the genes identified in our study have been reported by numerous microarray studies (BHLHE40, FSTL3, HK2, HTRA4, LEP, PVRL4, SASH1, SIGLEC6), but many have been implicated in only few studies or have not previously been linked to pre-eclampsia (ARMS2, BTNL9, CCSAP, DIO2, FER1L4, HPSE, LOC100129345, LYN, MYO7B, NCMAP, NDRG1, NRIP1, PLIN2, SBSPON, SERPINB9, SH3BP5, TET3, TPBG, ZNF175). Several of the molecules produced by these genes may have a role in the pathogenesis of pre-eclampsia, and some could qualify as biomarkers for prediction or detection of this pregnancy complication.

Gene expression profiling of pre-eclamptic placentae by RNA sequencing

PubMed Central

Kaartokallio, Tea; Cervera, Alejandra; Kyllönen, Anjuska; Laivuori, Krista; Laivuori, Hannele; Heinonen, Seppo; Kajantie, Eero; Kere, Juha; Kivinen, Katja; Pouta, Anneli

2015-01-01

Pre-eclampsia is a common and complex pregnancy disorder that often involves impaired placental development. In order to identify altered gene expression in pre-eclamptic placenta, we sequenced placental transcriptomes of nine pre-eclamptic and nine healthy pregnant women in pools of three. The differential gene expression was tested both by including all the pools in the analysis and by excluding some of the pools based on phenotypic characteristics. From these analyses, we identified altogether 53 differently expressed genes, a subset of which was validated by qPCR in 20 cases and 19 controls. Furthermore, we conducted pathway and functional analyses which revealed disturbed vascular function and immunological balance in pre-eclamptic placenta. Some of the genes identified in our study have been reported by numerous microarray studies (BHLHE40, FSTL3, HK2, HTRA4, LEP, PVRL4, SASH1, SIGLEC6), but many have been implicated in only few studies or have not previously been linked to pre-eclampsia (ARMS2, BTNL9, CCSAP, DIO2, FER1L4, HPSE, LOC100129345, LYN, MYO7B, NCMAP, NDRG1, NRIP1, PLIN2, SBSPON, SERPINB9, SH3BP5, TET3, TPBG, ZNF175). Several of the molecules produced by these genes may have a role in the pathogenesis of pre-eclampsia, and some could qualify as biomarkers for prediction or detection of this pregnancy complication. PMID:26388242

Microarray-based DNA methylation study of Ewing's sarcoma of the bone.

PubMed

Park, Hye-Rim; Jung, Woon-Won; Kim, Hyun-Sook; Park, Yong-Koo

2014-10-01

Alterations in DNA methylation patterns are a hallmark of malignancy. However, the majority of epigenetic studies of Ewing's sarcoma have focused on the analysis of only a few candidate genes. Comprehensive studies are thus lacking and are required. The aim of the present study was to identify novel methylation markers in Ewing's sarcoma using microarray analysis. The current study reports the microarray-based DNA methylation study of 1,505 CpG sites of 807 cancer-related genes from 69 Ewing's sarcoma samples. The Illumina GoldenGate Methylation Cancer Panel I microarray was used, and with the appropriate controls (n=14), a total of 92 hypermethylated genes were identified in the Ewing's sarcoma samples. The majority of the hypermethylated genes were associated with cell adhesion, cell regulation, development and signal transduction. The overall methylation mean values were compared between patients who survived and those that did not. The overall methylation mean was significantly higher in the patients who did not survive (0.25±0.03) than in those who did (0.22±0.05) (P=0.0322). However, the overall methylation mean was not found to significantly correlate with age, gender or tumor location. GDF10 , OSM , APC and HOXA11 were the most significant differentially-methylated genes, however, their methylation levels were not found to significantly correlate with the survival rate. The DNA methylation profile of Ewing's sarcoma was characterized and 92 genes that were significantly hypermethylated were detected. A trend towards a more aggressive behavior was identified in the methylated group. The results of this study indicated that methylation may be significant in the development of Ewing's sarcoma.

Microarray-based DNA methylation study of Ewing’s sarcoma of the bone

PubMed Central

PARK, HYE-RIM; JUNG, WOON-WON; KIM, HYUN-SOOK; PARK, YONG-KOO

2014-01-01

Alterations in DNA methylation patterns are a hallmark of malignancy. However, the majority of epigenetic studies of Ewing’s sarcoma have focused on the analysis of only a few candidate genes. Comprehensive studies are thus lacking and are required. The aim of the present study was to identify novel methylation markers in Ewing’s sarcoma using microarray analysis. The current study reports the microarray-based DNA methylation study of 1,505 CpG sites of 807 cancer-related genes from 69 Ewing’s sarcoma samples. The Illumina GoldenGate Methylation Cancer Panel I microarray was used, and with the appropriate controls (n=14), a total of 92 hypermethylated genes were identified in the Ewing’s sarcoma samples. The majority of the hypermethylated genes were associated with cell adhesion, cell regulation, development and signal transduction. The overall methylation mean values were compared between patients who survived and those that did not. The overall methylation mean was significantly higher in the patients who did not survive (0.25±0.03) than in those who did (0.22±0.05) (P=0.0322). However, the overall methylation mean was not found to significantly correlate with age, gender or tumor location. GDF10, OSM, APC and HOXA11 were the most significant differentially-methylated genes, however, their methylation levels were not found to significantly correlate with the survival rate. The DNA methylation profile of Ewing’s sarcoma was characterized and 92 genes that were significantly hypermethylated were detected. A trend towards a more aggressive behavior was identified in the methylated group. The results of this study indicated that methylation may be significant in the development of Ewing’s sarcoma. PMID:25202378

Profiling the humoral immune response of acute and chronic Q fever by protein microarray.

PubMed

Vigil, Adam; Chen, Chen; Jain, Aarti; Nakajima-Sasaki, Rie; Jasinskas, Algimantas; Pablo, Jozelyn; Hendrix, Laura R; Samuel, James E; Felgner, Philip L

2011-10-01

Antigen profiling using comprehensive protein microarrays is a powerful tool for characterizing the humoral immune response to infectious pathogens. Coxiella burnetii is a CDC category B bioterrorist infectious agent with worldwide distribution. In order to assess the antibody repertoire of acute and chronic Q fever patients we have constructed a protein microarray containing 93% of the proteome of Coxiella burnetii, the causative agent of Q fever. Here we report the profile of the IgG and IgM seroreactivity in 25 acute Q fever patients in longitudinal samples. We found that both early and late time points of infection have a very consistent repertoire of IgM and IgG response, with a limited number of proteins undergoing increasing or decreasing seroreactivity. We also probed a large collection of acute and chronic Q fever patient samples and identified serological markers that can differentiate between the two disease states. In this comparative analysis we confirmed the identity of numerous IgG biomarkers of acute infection, identified novel IgG biomarkers for acute and chronic infections, and profiled for the first time the IgM antibody repertoire for both acute and chronic Q fever. Using these results we were able to devise a test that can distinguish acute from chronic Q fever. These results also provide a unique perspective on isotype switch and demonstrate the utility of protein microarrays for simultaneously examining the dynamic humoral immune response against thousands of proteins from a large number of patients. The results presented here identify novel seroreactive antigens for the development of recombinant protein-based diagnostics and subunit vaccines, and provide insight into the development of the antibody response.

Moving Toward Integrating Gene Expression Profiling Into High-Throughput Testing: A Gene Expression Biomarker Accurately Predicts Estrogen Receptor α Modulation in a Microarray Compendium

PubMed Central

Ryan, Natalia; Chorley, Brian; Tice, Raymond R.; Judson, Richard; Corton, J. Christopher

2016-01-01

Microarray profiling of chemical-induced effects is being increasingly used in medium- and high-throughput formats. Computational methods are described here to identify molecular targets from whole-genome microarray data using as an example the estrogen receptor α (ERα), often modulated by potential endocrine disrupting chemicals. ERα biomarker genes were identified by their consistent expression after exposure to 7 structurally diverse ERα agonists and 3 ERα antagonists in ERα-positive MCF-7 cells. Most of the biomarker genes were shown to be directly regulated by ERα as determined by ESR1 gene knockdown using siRNA as well as through chromatin immunoprecipitation coupled with DNA sequencing analysis of ERα-DNA interactions. The biomarker was evaluated as a predictive tool using the fold-change rank-based Running Fisher algorithm by comparison to annotated gene expression datasets from experiments using MCF-7 cells, including those evaluating the transcriptional effects of hormones and chemicals. Using 141 comparisons from chemical- and hormone-treated cells, the biomarker gave a balanced accuracy for prediction of ERα activation or suppression of 94% and 93%, respectively. The biomarker was able to correctly classify 18 out of 21 (86%) ER reference chemicals including “very weak” agonists. Importantly, the biomarker predictions accurately replicated predictions based on 18 in vitro high-throughput screening assays that queried different steps in ERα signaling. For 114 chemicals, the balanced accuracies were 95% and 98% for activation or suppression, respectively. These results demonstrate that the ERα gene expression biomarker can accurately identify ERα modulators in large collections of microarray data derived from MCF-7 cells. PMID:26865669

Retinal cell responses to elevated intraocular pressure: a gene array comparison between the whole retina and retinal ganglion cell layer.

PubMed

Guo, Ying; Cepurna, William O; Dyck, Jennifer A; Doser, Tom A; Johnson, Elaine C; Morrison, John C

2010-06-01

To determine and compare gene expression patterns in the whole retina and retinal ganglion cell layer (RGCL) in a rodent glaucoma model. IOP was unilaterally elevated in Brown Norway rats (N = 26) by injection of hypertonic saline and monitored for 5 weeks. A cDNA microarray was used on whole retinas from one group of eyes with extensive optic nerve injury and on RGCL isolated by laser capture microdissection (LCM) from another group with comparable injury, to determine the significantly up- or downregulated genes and gene categories in both groups. Expression changes of selected genes were examined by quantitative reverse transcription-PCR (qPCR) to verify microarray results. Microarray analysis of the whole retina identified 632 genes with significantly changed expression (335 up, 297 down), associated with 9 upregulated and 3 downregulated biological processes. In contrast, the RGCL microarray yielded 3726 genes with significantly changed expression (2003 up, 1723 down), including 60% of those found in whole retina. Thirteen distinct upregulated biological processes were identified in the RGCL, dominated by protein synthesis. Among 11 downregulated processes, axon extension and dendrite morphogenesis and generation of precursor metabolism and energy were uniquely identified in the RGCL. qPCR confirmed significant changes in 6 selected messages in whole retina and 11 in RGCL. Increased Atf3, the most upregulated gene in the RGCL, was confirmed by immunohistochemistry of RGCs. Isolation of RGCL by LCM allows a more refined detection of gene response to elevated pressure and improves the potential of determining cellular mechanisms in RGCs and their supporting cells that could be targets for enhancing RGC survival.

Microarray expression profiling identifies genes with altered expression in HDL-deficient mice

DOE Office of Scientific and Technical Information (OSTI.GOV)

Callow, Matthew J.; Dudoit, Sandrine; Gong, Elaine L.

2000-05-05

Based on the assumption that severe alterations in the expression of genes known to be involved in HDL metabolism may affect the expression of other genes we screened an array of over 5000 mouse expressed sequence tags (ESTs) for altered gene expression in the livers of two lines of mice with dramatic decreases in HDL plasma concentrations. Labeled cDNA from livers of apolipoprotein AI (apo AI) knockout mice, Scavenger Receptor BI (SR-BI) transgenic mice and control mice were co-hybridized to microarrays. Two-sample t-statistics were used to identify genes with altered expression levels in the knockout or transgenic mice compared withmore » the control mice. In the SR-BI group we found 9 array elements representing at least 5 genes to be significantly altered on the basis of an adjusted p value of less than 0.05. In the apo AI knockout group 8 array elements representing 4 genes were altered compared with the control group (p < 0.05). Several of the genes identified in the SR-BI transgenic suggest altered sterol metabolism and oxidative processes. These studies illustrate the use of multiple-testing methods for the identification of genes with altered expression in replicated microarray experiments of apo AI knockout and SR-BI transgenic mice.« less

Development of reversible jump Markov Chain Monte Carlo algorithm in the Bayesian mixture modeling for microarray data in Indonesia

NASA Astrophysics Data System (ADS)

Astuti, Ani Budi; Iriawan, Nur; Irhamah, Kuswanto, Heri

2017-12-01

In the Bayesian mixture modeling requires stages the identification number of the most appropriate mixture components thus obtained mixture models fit the data through data driven concept. Reversible Jump Markov Chain Monte Carlo (RJMCMC) is a combination of the reversible jump (RJ) concept and the Markov Chain Monte Carlo (MCMC) concept used by some researchers to solve the problem of identifying the number of mixture components which are not known with certainty number. In its application, RJMCMC using the concept of the birth/death and the split-merge with six types of movement, that are w updating, θ updating, z updating, hyperparameter β updating, split-merge for components and birth/death from blank components. The development of the RJMCMC algorithm needs to be done according to the observed case. The purpose of this study is to know the performance of RJMCMC algorithm development in identifying the number of mixture components which are not known with certainty number in the Bayesian mixture modeling for microarray data in Indonesia. The results of this study represent that the concept RJMCMC algorithm development able to properly identify the number of mixture components in the Bayesian normal mixture model wherein the component mixture in the case of microarray data in Indonesia is not known for certain number.

Finding gene clusters for a replicated time course study

PubMed Central

2014-01-01

Background Finding genes that share similar expression patterns across samples is an important question that is frequently asked in high-throughput microarray studies. Traditional clustering algorithms such as K-means clustering and hierarchical clustering base gene clustering directly on the observed measurements and do not take into account the specific experimental design under which the microarray data were collected. A new model-based clustering method, the clustering of regression models method, takes into account the specific design of the microarray study and bases the clustering on how genes are related to sample covariates. It can find useful gene clusters for studies from complicated study designs such as replicated time course studies. Findings In this paper, we applied the clustering of regression models method to data from a time course study of yeast on two genotypes, wild type and YOX1 mutant, each with two technical replicates, and compared the clustering results with K-means clustering. We identified gene clusters that have similar expression patterns in wild type yeast, two of which were missed by K-means clustering. We further identified gene clusters whose expression patterns were changed in YOX1 mutant yeast compared to wild type yeast. Conclusions The clustering of regression models method can be a valuable tool for identifying genes that are coordinately transcribed by a common mechanism. PMID:24460656

An integrated bioinformatics approach to improve two-color microarray quality-control: impact on biological conclusions.

PubMed

van Haaften, Rachel I M; Luceri, Cristina; van Erk, Arie; Evelo, Chris T A

2009-06-01

Omics technology used for large-scale measurements of gene expression is rapidly evolving. This work pointed out the need of an extensive bioinformatics analyses for array quality assessment before and after gene expression clustering and pathway analysis. A study focused on the effect of red wine polyphenols on rat colon mucosa was used to test the impact of quality control and normalisation steps on the biological conclusions. The integration of data visualization, pathway analysis and clustering revealed an artifact problem that was solved with an adapted normalisation. We propose a possible point to point standard analysis procedure, based on a combination of clustering and data visualization for the analysis of microarray data.

Identification of iron-regulated genes of Bifidobacterium breve UCC2003 as a basis for controlled gene expression

PubMed Central

Cronin, Michelle; Zomer, Aldert; Fitzgerald, Gerald; van Sinderen, Douwe

2012-01-01

Iron is an essential growth factor for virtually all organisms. However, iron is not readily available in most environments and microorganisms have evolved specialized mechanisms, such as the use of siderophores and high-affinity transport systems, to acquire iron when confronted with iron-limiting conditions. In general these systems are tightly regulated to prevent iron-induced toxicity and because they are quite costly to the microbe. Because of this tight regulation we chose to explore the response of Bifidobacterium breve UCC2003 to iron limitation. Through microarray and complementation analyses we identified and characterized a presumed ferrous iron uptake system, encoded by bfeUOB, from B. breve UCC2003 and exploited its regulated transcription to develop an inducible expression system for use in bifidobacteria. PMID:22179149

Computational synchronization of microarray data with application to Plasmodium falciparum.

PubMed

Zhao, Wei; Dauwels, Justin; Niles, Jacquin C; Cao, Jianshu

2012-06-21

Microarrays are widely used to investigate the blood stage of Plasmodium falciparum infection. Starting with synchronized cells, gene expression levels are continually measured over the 48-hour intra-erythrocytic cycle (IDC). However, the cell population gradually loses synchrony during the experiment. As a result, the microarray measurements are blurred. In this paper, we propose a generalized deconvolution approach to reconstruct the intrinsic expression pattern, and apply it to P. falciparum IDC microarray data. We develop a statistical model for the decay of synchrony among cells, and reconstruct the expression pattern through statistical inference. The proposed method can handle microarray measurements with noise and missing data. The original gene expression patterns become more apparent in the reconstructed profiles, making it easier to analyze and interpret the data. We hypothesize that reconstructed gene expression patterns represent better temporally resolved expression profiles that can be probabilistically modeled to match changes in expression level to IDC transitions. In particular, we identify transcriptionally regulated protein kinases putatively involved in regulating the P. falciparum IDC. By analyzing publicly available microarray data sets for the P. falciparum IDC, protein kinases are ranked in terms of their likelihood to be involved in regulating transitions between the ring, trophozoite and schizont developmental stages of the P. falciparum IDC. In our theoretical framework, a few protein kinases have high probability rankings, and could potentially be involved in regulating these developmental transitions. This study proposes a new methodology for extracting intrinsic expression patterns from microarray data. By applying this method to P. falciparum microarray data, several protein kinases are predicted to play a significant role in the P. falciparum IDC. Earlier experiments have indeed confirmed that several of these kinases are involved in this process. Overall, these results indicate that further functional analysis of these additional putative protein kinases may reveal new insights into how the P. falciparum IDC is regulated.

Mining meiosis and gametogenesis with DNA microarrays.

PubMed

Schlecht, Ulrich; Primig, Michael

2003-04-01

Gametogenesis is a key developmental process that involves complex transcriptional regulation of numerous genes including many that are conserved between unicellular eukaryotes and mammals. Recent expression-profiling experiments using microarrays have provided insight into the co-ordinated transcription of several hundred genes during mitotic growth and meiotic development in budding and fission yeast. Furthermore, microarray-based studies have identified numerous loci that are regulated during the cell cycle or expressed in a germ-cell specific manner in eukaryotic model systems like Caenorhabditis elegans, Mus musculus as well as Homo sapiens. The unprecedented amount of information produced by post-genome biology has spawned novel approaches to organizing biological knowledge using currently available information technology. This review outlines experiments that contribute to an emerging comprehensive picture of the molecular machinery governing sexual reproduction in eukaryotes.

Cross-platform method for identifying candidate network biomarkers for prostate cancer.

PubMed

Jin, G; Zhou, X; Cui, K; Zhang, X-S; Chen, L; Wong, S T C

2009-11-01

Discovering biomarkers using mass spectrometry (MS) and microarray expression profiles is a promising strategy in molecular diagnosis. Here, the authors proposed a new pipeline for biomarker discovery that integrates disease information for proteins and genes, expression profiles in both genomic and proteomic levels, and protein-protein interactions (PPIs) to discover high confidence network biomarkers. Using this pipeline, a total of 474 molecules (genes and proteins) related to prostate cancer were identified and a prostate-cancer-related network (PCRN) was derived from the integrative information. Thus, a set of candidate network biomarkers were identified from multiple expression profiles composed by eight microarray datasets and one proteomics dataset. The network biomarkers with PPIs can accurately distinguish the prostate patients from the normal ones, which potentially provide more reliable hits of biomarker candidates than conventional biomarker discovery methods.

Detection of Alicyclobacillus species in fruit juice using a random genomic DNA microarray chip.

PubMed

Jang, Jun Hyeong; Kim, Sun-Joong; Yoon, Bo Hyun; Ryu, Jee-Hoon; Gu, Man Bock; Chang, Hyo-Ihl

2011-06-01

This study describes a method using a DNA microarray chip to rapidly and simultaneously detect Alicyclobacillus species in orange juice based on the hybridization of genomic DNA with random probes. Three food spoilage bacteria were used in this study: Alicyclobacillus acidocaldarius, Alicyclobacillus acidoterrestris, and Alicyclobacillus cycloheptanicus. The three Alicyclobacillus species were adjusted to 2 × 10(3) CFU/ml and inoculated into pasteurized 100% pure orange juice. Cy5-dCTP labeling was used for reference signals, and Cy3-dCTP was labeled for target genomic DNA. The molar ratio of 1:1 of Cy3-dCTP and Cy5-dCTP was used. DNA microarray chips were fabricated using randomly fragmented DNA of Alicyclobacillus spp. and were hybridized with genomic DNA extracted from Bacillus spp. Genomic DNA extracted from Alicyclobacillus spp. showed a significantly higher hybridization rate compared with DNA of Bacillus spp., thereby distinguishing Alicyclobacillus spp. from Bacillus spp. The results showed that the microarray DNA chip containing randomly fragmented genomic DNA was specific and clearly identified specific food spoilage bacteria. This microarray system is a good tool for rapid and specific detection of thermophilic spoilage bacteria, mainly Alicyclobacillus spp., and is useful and applicable to the fruit juice industry.

Analytical Protein Microarrays: Advancements Towards Clinical Applications

PubMed Central

Sauer, Ursula

2017-01-01

Protein microarrays represent a powerful technology with the potential to serve as tools for the detection of a broad range of analytes in numerous applications such as diagnostics, drug development, food safety, and environmental monitoring. Key features of analytical protein microarrays include high throughput and relatively low costs due to minimal reagent consumption, multiplexing, fast kinetics and hence measurements, and the possibility of functional integration. So far, especially fundamental studies in molecular and cell biology have been conducted using protein microarrays, while the potential for clinical, notably point-of-care applications is not yet fully utilized. The question arises what features have to be implemented and what improvements have to be made in order to fully exploit the technology. In the past we have identified various obstacles that have to be overcome in order to promote protein microarray technology in the diagnostic field. Issues that need significant improvement to make the technology more attractive for the diagnostic market are for instance: too low sensitivity and deficiency in reproducibility, inadequate analysis time, lack of high-quality antibodies and validated reagents, lack of automation and portable instruments, and cost of instruments necessary for chip production and read-out. The scope of the paper at hand is to review approaches to solve these problems. PMID:28146048

Integrated in silico and biological validation of the blocking effect of Cot-1 DNA on Microarray-CGH.

PubMed

Kang, Seung-Hui; Park, Chan Hee; Jeung, Hei Cheul; Kim, Ki-Yeol; Rha, Sun Young; Chung, Hyun Cheol

2007-06-01

In array-CGH, various factors may act as variables influencing the result of experiments. Among them, Cot-1 DNA, which has been used as a repetitive sequence-blocking agent, may become an artifact-inducing factor in BAC array-CGH. To identify the effect of Cot-1 DNA on Microarray-CGH experiments, Cot-1 DNA was labeled directly and Microarray-CGH experiments were performed. The results confirmed that probes which hybridized more completely with Cot-1 DNA had a higher sequence similarity to the Alu element. Further, in the sex-mismatched Microarray-CGH experiments, the variation and intensity in the fluorescent signal were reduced in the high intensity probe group in which probes were better hybridized with Cot-1 DNA. Otherwise, those of the low intensity probe group showed no alterations regardless of Cot-1 DNA. These results confirmed by in silico methods that Cot-1 DNA could block repetitive sequences in gDNA and probes. In addition, it was confirmed biologically that the blocking effect of Cot-1 DNA could be presented via its repetitive sequences, especially Alu elements. Thus, in contrast to BAC-array CGH, the use of Cot-1 DNA is advantageous in controlling experimental variation in Microarray-CGH.

Comparative analysis of gene expression profiles of hip articular cartilage between non-traumatic necrosis and osteoarthritis.

PubMed

Wang, Wenyu; Liu, Yang; Hao, Jingcan; Zheng, Shuyu; Wen, Yan; Xiao, Xiao; He, Awen; Fan, Qianrui; Zhang, Feng; Liu, Ruiyu

2016-10-10

Hip cartilage destruction is consistently observed in the non-traumatic osteonecrosis of femoral head (NOFH) and accelerates its bone necrosis. The molecular mechanism underlying the cartilage damage of NOFH remains elusive. In this study, we conducted a systematically comparative study of gene expression profiles between NOFH and osteoarthritis (OA). Hip articular cartilage specimens were collected from 12 NOFH patients and 12 controls with traumatic femoral neck fracture for microarray (n=4) and quantitative real-time PCR validation experiments (n=8). Gene expression profiling of articular cartilage was performed using Agilent Human 4×44K Microarray chip. The accuracy of microarray experiment was further validated by qRT-PCR. Gene expression results of OA hip cartilage were derived from previously published study. Significance Analysis of Microarrays (SAM) software was applied for identifying differently expressed genes. Gene ontology (GO) and pathway enrichment analysis were conducted by Gene Set Enrichment Analysis software and DAVID tool, respectively. Totally, 27 differently expressed genes were identified for NOFH. Comparing the gene expression profiles of NOFH cartilage and OA cartilage detected 8 common differently expressed genes, including COL5A1, OGN, ANGPTL4, CRIP1, NFIL3, METRNL, ID2 and STEAP1. GO comparative analysis identified 10 common significant GO terms, mainly implicated in apoptosis and development process. Pathway comparative analysis observed that ECM-receptor interaction pathway and focal adhesion pathway were enriched in the differently expressed genes of both NOFH and hip OA. In conclusion, we identified a set of differently expressed genes, GO and pathways for NOFH articular destruction, some of which were also involved in the hip OA. Our study results may help to reveal the pathogenetic similarities and differences of cartilage damage of NOFH and hip OA. Copyright © 2016 Elsevier B.V. All rights reserved.

Generation of Antigen Microarrays to Screen for Autoantibodies in Heart Failure and Heart Transplantation.

PubMed

Chruscinski, Andrzej; Huang, Flora Y Y; Nguyen, Albert; Lioe, Jocelyn; Tumiati, Laura C; Kozuszko, Stella; Tinckam, Kathryn J; Rao, Vivek; Dunn, Shannon E; Persinger, Michael A; Levy, Gary A; Ross, Heather J

2016-01-01

Autoantibodies directed against endogenous proteins including contractile proteins and endothelial antigens are frequently detected in patients with heart failure and after heart transplantation. There is evidence that these autoantibodies contribute to cardiac dysfunction and correlate with clinical outcomes. Currently, autoantibodies are detected in patient sera using individual ELISA assays (one for each antigen). Thus, screening for many individual autoantibodies is laborious and consumes a large amount of patient sample. To better capture the broad-scale antibody reactivities that occur in heart failure and post-transplant, we developed a custom antigen microarray technique that can simultaneously measure IgM and IgG reactivities against 64 unique antigens using just five microliters of patient serum. We first demonstrated that our antigen microarray technique displayed enhanced sensitivity to detect autoantibodies compared to the traditional ELISA method. We then piloted this technique using two sets of samples that were obtained at our institution. In the first retrospective study, we profiled pre-transplant sera from 24 heart failure patients who subsequently received heart transplants. We identified 8 antibody reactivities that were higher in patients who developed cellular rejection (2 or more episodes of grade 2R rejection in first year after transplant as defined by revised criteria from the International Society for Heart and Lung Transplantation) compared with those who did have not have rejection episodes. In a second retrospective study with 31 patients, we identified 7 IgM reactivities that were higher in heart transplant recipients who developed antibody-mediated rejection (AMR) compared with control recipients, and in time course studies, these reactivities appeared prior to overt graft dysfunction. In conclusion, we demonstrated that the autoantibody microarray technique outperforms traditional ELISAs as it uses less patient sample, has increased sensitivity, and can detect autoantibodies in a multiplex fashion. Furthermore, our results suggest that this autoantibody array technology may help to identify patients at risk of rejection following heart transplantation and identify heart transplant recipients with AMR.

Generation of Antigen Microarrays to Screen for Autoantibodies in Heart Failure and Heart Transplantation

PubMed Central

Chruscinski, Andrzej; Huang, Flora Y. Y.; Nguyen, Albert; Lioe, Jocelyn; Tumiati, Laura C.; Kozuszko, Stella; Tinckam, Kathryn J.; Rao, Vivek; Dunn, Shannon E.; Persinger, Michael A.; Levy, Gary A.; Ross, Heather J.

2016-01-01

Autoantibodies directed against endogenous proteins including contractile proteins and endothelial antigens are frequently detected in patients with heart failure and after heart transplantation. There is evidence that these autoantibodies contribute to cardiac dysfunction and correlate with clinical outcomes. Currently, autoantibodies are detected in patient sera using individual ELISA assays (one for each antigen). Thus, screening for many individual autoantibodies is laborious and consumes a large amount of patient sample. To better capture the broad-scale antibody reactivities that occur in heart failure and post-transplant, we developed a custom antigen microarray technique that can simultaneously measure IgM and IgG reactivities against 64 unique antigens using just five microliters of patient serum. We first demonstrated that our antigen microarray technique displayed enhanced sensitivity to detect autoantibodies compared to the traditional ELISA method. We then piloted this technique using two sets of samples that were obtained at our institution. In the first retrospective study, we profiled pre-transplant sera from 24 heart failure patients who subsequently received heart transplants. We identified 8 antibody reactivities that were higher in patients who developed cellular rejection (2 or more episodes of grade 2R rejection in first year after transplant as defined by revised criteria from the International Society for Heart and Lung Transplantation) compared with those who did have not have rejection episodes. In a second retrospective study with 31 patients, we identified 7 IgM reactivities that were higher in heart transplant recipients who developed antibody-mediated rejection (AMR) compared with control recipients, and in time course studies, these reactivities appeared prior to overt graft dysfunction. In conclusion, we demonstrated that the autoantibody microarray technique outperforms traditional ELISAs as it uses less patient sample, has increased sensitivity, and can detect autoantibodies in a multiplex fashion. Furthermore, our results suggest that this autoantibody array technology may help to identify patients at risk of rejection following heart transplantation and identify heart transplant recipients with AMR. PMID:26967734

Combining suppressive subtractive hybridization and cDNA microarrays to identify dietary phosphorus-responsive genes of the rainbow trout (Oncorhynchus mykiss) kidney.

PubMed

Lake, Jennifer; Gravel, Catherine; Koko, Gabriel Koffi D; Robert, Claude; Vandenberg, Grant W

2010-03-01

Phosphorus (P)-responsive genes and how they regulate renal adaptation to phosphorous-deficient diets in animals, including fish, are not well understood. RNA abundance profiling using cDNA microarrays is an efficient approach to study nutrient-gene interactions and identify these dietary P-responsive genes. To test the hypothesis that dietary P-responsive genes are differentially expressed in fish fed varying P levels, rainbow trout were fed a practical high-P diet (R20: 0.96% P) or a low-P diet (R0: 0.38% P) for 7 weeks. The differentially-expressed genes between dietary groups were identified and compared from the kidney by combining suppressive subtractive hybridization (SSH) with cDNA microarray analysis. A number of genes were confirmed by real-time PCR, and correlated with plasma and bone P concentrations. Approximately 54 genes were identified as potential dietary P-responsive after 7 weeks on a diet deficient in P according to cDNA microarray analysis. Of 18 selected genes, 13 genes were confirmed to be P-responsive at 7 weeks by real-time PCR analysis, including: iNOS, cytochrome b, cytochrome c oxidase subunit II , alpha-globin I, beta-globin, ATP synthase, hyperosmotic protein 21, COL1A3, Nkef, NDPK, glucose phosphate isomerase 1, Na+/H+ exchange protein and GDP dissociation inhibitor 2. Many of these dietary P-responsive genes responded in a moderate way (R0/R20 ratio: <2-3 or >0.5) and in a transient manner to dietary P limitation. In summary, renal adaptation to dietary P deficiency in trout involves changes in the expression of several genes, suggesting a profile of metabolic stress, since many of these differentially-expressed candidates are associated with the cellular adaptative responses. Crown Copyright 2009. Published by Elsevier Inc. All rights reserved.

Analysis and modelling of septic shock microarray data using Singular Value Decomposition.

PubMed

Allanki, Srinivas; Dixit, Madhulika; Thangaraj, Paul; Sinha, Nandan Kumar

2017-06-01

Being a high throughput technique, enormous amounts of microarray data has been generated and there arises a need for more efficient techniques of analysis, in terms of speed and accuracy. Finding the differentially expressed genes based on just fold change and p-value might not extract all the vital biological signals that occur at a lower gene expression level. Besides this, numerous mathematical models have been generated to predict the clinical outcome from microarray data, while very few, if not none, aim at predicting the vital genes that are important in a disease progression. Such models help a basic researcher narrow down and concentrate on a promising set of genes which leads to the discovery of gene-based therapies. In this article, as a first objective, we have used the lesser known and used Singular Value Decomposition (SVD) technique to build a microarray data analysis tool that works with gene expression patterns and intrinsic structure of the data in an unsupervised manner. We have re-analysed a microarray data over the clinical course of Septic shock from Cazalis et al. (2014) and have shown that our proposed analysis provides additional information compared to the conventional method. As a second objective, we developed a novel mathematical model that predicts a set of vital genes in the disease progression that works by generating samples in the continuum between health and disease, using a simple normal-distribution-based random number generator. We also verify that most of the predicted genes are indeed related to septic shock. Copyright © 2017 Elsevier Inc. All rights reserved.

A multiplex reverse transcription PCR and automated electronic microarray assay for detection and differentiation of seven viruses affecting swine.

PubMed

Erickson, A; Fisher, M; Furukawa-Stoffer, T; Ambagala, A; Hodko, D; Pasick, J; King, D P; Nfon, C; Ortega Polo, R; Lung, O

2018-04-01

Microarray technology can be useful for pathogen detection as it allows simultaneous interrogation of the presence or absence of a large number of genetic signatures. However, most microarray assays are labour-intensive and time-consuming to perform. This study describes the development and initial evaluation of a multiplex reverse transcription (RT)-PCR and novel accompanying automated electronic microarray assay for simultaneous detection and differentiation of seven important viruses that affect swine (foot-and-mouth disease virus [FMDV], swine vesicular disease virus [SVDV], vesicular exanthema of swine virus [VESV], African swine fever virus [ASFV], classical swine fever virus [CSFV], porcine respiratory and reproductive syndrome virus [PRRSV] and porcine circovirus type 2 [PCV2]). The novel electronic microarray assay utilizes a single, user-friendly instrument that integrates and automates capture probe printing, hybridization, washing and reporting on a disposable electronic microarray cartridge with 400 features. This assay accurately detected and identified a total of 68 isolates of the seven targeted virus species including 23 samples of FMDV, representing all seven serotypes, and 10 CSFV strains, representing all three genotypes. The assay successfully detected viruses in clinical samples from the field, experimentally infected animals (as early as 1 day post-infection (dpi) for FMDV and SVDV, 4 dpi for ASFV, 5 dpi for CSFV), as well as in biological material that were spiked with target viruses. The limit of detection was 10 copies/μl for ASFV, PCV2 and PRRSV, 100 copies/μl for SVDV, CSFV, VESV and 1,000 copies/μl for FMDV. The electronic microarray component had reduced analytical sensitivity for several of the target viruses when compared with the multiplex RT-PCR. The integration of capture probe printing allows custom onsite array printing as needed, while electrophoretically driven hybridization generates results faster than conventional microarrays that rely on passive hybridization. With further refinement, this novel, rapid, highly automated microarray technology has potential applications in multipathogen surveillance of livestock diseases. © 2017 Her Majesty the Queen in Right of Canada • Transboundary and Emerging Diseases.

Engineered human skin substitutes undergo large-scale genomic reprogramming and normal skin-like maturation after transplantation to athymic mice.

PubMed

Klingenberg, Jennifer M; McFarland, Kevin L; Friedman, Aaron J; Boyce, Steven T; Aronow, Bruce J; Supp, Dorothy M

2010-02-01

Bioengineered skin substitutes can facilitate wound closure in severely burned patients, but deficiencies limit their outcomes compared with native skin autografts. To identify gene programs associated with their in vivo capabilities and limitations, we extended previous gene expression profile analyses to now compare engineered skin after in vivo grafting with both in vitro maturation and normal human skin. Cultured skin substitutes were grafted on full-thickness wounds in athymic mice, and biopsy samples for microarray analyses were collected at multiple in vitro and in vivo time points. Over 10,000 transcripts exhibited large-scale expression pattern differences during in vitro and in vivo maturation. Using hierarchical clustering, 11 different expression profile clusters were partitioned on the basis of differential sample type and temporal stage-specific activation or repression. Analyses show that the wound environment exerts a massive influence on gene expression in skin substitutes. For example, in vivo-healed skin substitutes gained the expression of many native skin-expressed genes, including those associated with epidermal barrier and multiple categories of cell-cell and cell-basement membrane adhesion. In contrast, immunological, trichogenic, and endothelial gene programs were largely lacking. These analyses suggest important areas for guiding further improvement of engineered skin for both increased homology with native skin and enhanced wound healing.

Challenges in projecting clustering results across gene expression-profiling datasets.

PubMed

Lusa, Lara; McShane, Lisa M; Reid, James F; De Cecco, Loris; Ambrogi, Federico; Biganzoli, Elia; Gariboldi, Manuela; Pierotti, Marco A

2007-11-21

Gene expression microarray studies for several types of cancer have been reported to identify previously unknown subtypes of tumors. For breast cancer, a molecular classification consisting of five subtypes based on gene expression microarray data has been proposed. These subtypes have been reported to exist across several breast cancer microarray studies, and they have demonstrated some association with clinical outcome. A classification rule based on the method of centroids has been proposed for identifying the subtypes in new collections of breast cancer samples; the method is based on the similarity of the new profiles to the mean expression profile of the previously identified subtypes. Previously identified centroids of five breast cancer subtypes were used to assign 99 breast cancer samples, including a subset of 65 estrogen receptor-positive (ER+) samples, to five breast cancer subtypes based on microarray data for the samples. The effect of mean centering the genes (i.e., transforming the expression of each gene so that its mean expression is equal to 0) on subtype assignment by method of centroids was assessed. Further studies of the effect of mean centering and of class prevalence in the test set on the accuracy of method of centroids classifications of ER status were carried out using training and test sets for which ER status had been independently determined by ligand-binding assay and for which the proportion of ER+ and ER- samples were systematically varied. When all 99 samples were considered, mean centering before application of the method of centroids appeared to be helpful for correctly assigning samples to subtypes, as evidenced by the expression of genes that had previously been used as markers to identify the subtypes. However, when only the 65 ER+ samples were considered for classification, many samples appeared to be misclassified, as evidenced by an unexpected distribution of ER+ samples among the resultant subtypes. When genes were mean centered before classification of samples for ER status, the accuracy of the ER subgroup assignments was highly dependent on the proportion of ER+ samples in the test set; this effect of subtype prevalence was not seen when gene expression data were not mean centered. Simple corrections such as mean centering of genes aimed at microarray platform or batch effect correction can have undesirable consequences because patient population effects can easily be confused with these assay-related effects. Careful thought should be given to the comparability of the patient populations before attempting to force data comparability for purposes of assigning subtypes to independent subjects.

ArrayWiki: an enabling technology for sharing public microarray data repositories and meta-analyses

PubMed Central

Stokes, Todd H; Torrance, JT; Li, Henry; Wang, May D

2008-01-01

Background A survey of microarray databases reveals that most of the repository contents and data models are heterogeneous (i.e., data obtained from different chip manufacturers), and that the repositories provide only basic biological keywords linking to PubMed. As a result, it is difficult to find datasets using research context or analysis parameters information beyond a few keywords. For example, to reduce the "curse-of-dimension" problem in microarray analysis, the number of samples is often increased by merging array data from different datasets. Knowing chip data parameters such as pre-processing steps (e.g., normalization, artefact removal, etc), and knowing any previous biological validation of the dataset is essential due to the heterogeneity of the data. However, most of the microarray repositories do not have meta-data information in the first place, and do not have a a mechanism to add or insert this information. Thus, there is a critical need to create "intelligent" microarray repositories that (1) enable update of meta-data with the raw array data, and (2) provide standardized archiving protocols to minimize bias from the raw data sources. Results To address the problems discussed, we have developed a community maintained system called ArrayWiki that unites disparate meta-data of microarray meta-experiments from multiple primary sources with four key features. First, ArrayWiki provides a user-friendly knowledge management interface in addition to a programmable interface using standards developed by Wikipedia. Second, ArrayWiki includes automated quality control processes (caCORRECT) and novel visualization methods (BioPNG, Gel Plots), which provide extra information about data quality unavailable in other microarray repositories. Third, it provides a user-curation capability through the familiar Wiki interface. Fourth, ArrayWiki provides users with simple text-based searches across all experiment meta-data, and exposes data to search engine crawlers (Semantic Agents) such as Google to further enhance data discovery. Conclusions Microarray data and meta information in ArrayWiki are distributed and visualized using a novel and compact data storage format, BioPNG. Also, they are open to the research community for curation, modification, and contribution. By making a small investment of time to learn the syntax and structure common to all sites running MediaWiki software, domain scientists and practioners can all contribute to make better use of microarray technologies in research and medical practices. ArrayWiki is available at . PMID:18541053

Development and validation of a flax (Linum usitatissimum L.) gene expression oligo microarray

PubMed Central

2010-01-01

Background Flax (Linum usitatissimum L.) has been cultivated for around 9,000 years and is therefore one of the oldest cultivated species. Today, flax is still grown for its oil (oil-flax or linseed cultivars) and its cellulose-rich fibres (fibre-flax cultivars) used for high-value linen garments and composite materials. Despite the wide industrial use of flax-derived products, and our actual understanding of the regulation of both wood fibre production and oil biosynthesis more information must be acquired in both domains. Recent advances in genomics are now providing opportunities to improve our fundamental knowledge of these complex processes. In this paper we report the development and validation of a high-density oligo microarray platform dedicated to gene expression analyses in flax. Results Nine different RNA samples obtained from flax inner- and outer-stems, seeds, leaves and roots were used to generate a collection of 1,066,481 ESTs by massive parallel pyrosequencing. Sequences were assembled into 59,626 unigenes and 48,021 sequences were selected for oligo design and high-density microarray (Nimblegen 385K) fabrication with eight, non-overlapping 25-mers oligos per unigene. 18 independent experiments were used to evaluate the hybridization quality, precision, specificity and accuracy and all results confirmed the high technical quality of our microarray platform. Cross-validation of microarray data was carried out using quantitative qRT-PCR. Nine target genes were selected on the basis of microarray results and reflected the whole range of fold change (both up-regulated and down-regulated genes in different samples). A statistically significant positive correlation was obtained comparing expression levels for each target gene across all biological replicates both in qRT-PCR and microarray results. Further experiments illustrated the capacity of our arrays to detect differential gene expression in a variety of flax tissues as well as between two contrasted flax varieties. Conclusion All results suggest that our high-density flax oligo-microarray platform can be used as a very sensitive tool for analyzing gene expression in a large variety of tissues as well as in different cultivars. Moreover, this highly reliable platform can also be used for the quantification of mRNA transcriptional profiling in different flax tissues. PMID:20964859

Development and validation of a flax (Linum usitatissimum L.) gene expression oligo microarray.

PubMed

Fenart, Stéphane; Ndong, Yves-Placide Assoumou; Duarte, Jorge; Rivière, Nathalie; Wilmer, Jeroen; van Wuytswinkel, Olivier; Lucau, Anca; Cariou, Emmanuelle; Neutelings, Godfrey; Gutierrez, Laurent; Chabbert, Brigitte; Guillot, Xavier; Tavernier, Reynald; Hawkins, Simon; Thomasset, Brigitte

2010-10-21

Flax (Linum usitatissimum L.) has been cultivated for around 9,000 years and is therefore one of the oldest cultivated species. Today, flax is still grown for its oil (oil-flax or linseed cultivars) and its cellulose-rich fibres (fibre-flax cultivars) used for high-value linen garments and composite materials. Despite the wide industrial use of flax-derived products, and our actual understanding of the regulation of both wood fibre production and oil biosynthesis more information must be acquired in both domains. Recent advances in genomics are now providing opportunities to improve our fundamental knowledge of these complex processes. In this paper we report the development and validation of a high-density oligo microarray platform dedicated to gene expression analyses in flax. Nine different RNA samples obtained from flax inner- and outer-stems, seeds, leaves and roots were used to generate a collection of 1,066,481 ESTs by massive parallel pyrosequencing. Sequences were assembled into 59,626 unigenes and 48,021 sequences were selected for oligo design and high-density microarray (Nimblegen 385K) fabrication with eight, non-overlapping 25-mers oligos per unigene. 18 independent experiments were used to evaluate the hybridization quality, precision, specificity and accuracy and all results confirmed the high technical quality of our microarray platform. Cross-validation of microarray data was carried out using quantitative qRT-PCR. Nine target genes were selected on the basis of microarray results and reflected the whole range of fold change (both up-regulated and down-regulated genes in different samples). A statistically significant positive correlation was obtained comparing expression levels for each target gene across all biological replicates both in qRT-PCR and microarray results. Further experiments illustrated the capacity of our arrays to detect differential gene expression in a variety of flax tissues as well as between two contrasted flax varieties. All results suggest that our high-density flax oligo-microarray platform can be used as a very sensitive tool for analyzing gene expression in a large variety of tissues as well as in different cultivars. Moreover, this highly reliable platform can also be used for the quantification of mRNA transcriptional profiling in different flax tissues.

DNA Microarray for Detection of Gastrointestinal Viruses

PubMed Central

Martínez, Miguel A.; Soto-del Río, María de los Dolores; Gutiérrez, Rosa María; Chiu, Charles Y.; Greninger, Alexander L.; Contreras, Juan Francisco; López, Susana; Arias, Carlos F.

2014-01-01

Gastroenteritis is a clinical illness of humans and other animals that is characterized by vomiting and diarrhea and caused by a variety of pathogens, including viruses. An increasing number of viral species have been associated with gastroenteritis or have been found in stool samples as new molecular tools have been developed. In this work, a DNA microarray capable in theory of parallel detection of more than 100 viral species was developed and tested. Initial validation was done with 10 different virus species, and an additional 5 species were validated using clinical samples. Detection limits of 1 × 103 virus particles of Human adenovirus C (HAdV), Human astrovirus (HAstV), and group A Rotavirus (RV-A) were established. Furthermore, when exogenous RNA was added, the limit for RV-A detection decreased by one log. In a small group of clinical samples from children with gastroenteritis (n = 76), the microarray detected at least one viral species in 92% of the samples. Single infection was identified in 63 samples (83%), and coinfection with more than one virus was identified in 7 samples (9%). The most abundant virus species were RV-A (58%), followed by Anellovirus (15.8%), HAstV (6.6%), HAdV (5.3%), Norwalk virus (6.6%), Human enterovirus (HEV) (9.2%), Human parechovirus (1.3%), Sapporo virus (1.3%), and Human bocavirus (1.3%). To further test the specificity and sensitivity of the microarray, the results were verified by reverse transcription-PCR (RT-PCR) detection of 5 gastrointestinal viruses. The RT-PCR assay detected a virus in 59 samples (78%). The microarray showed good performance for detection of RV-A, HAstV, and calicivirus, while the sensitivity for HAdV and HEV was low. Furthermore, some discrepancies in detection of mixed infections were observed and were addressed by reverse transcription-quantitative PCR (RT-qPCR) of the viruses involved. It was observed that differences in the amount of genetic material favored the detection of the most abundant virus. The microarray described in this work should help in understanding the etiology of gastroenteritis in humans and animals. PMID:25355758

Calibration and assessment of channel-specific biases in microarray data with extended dynamical range.

PubMed

Bengtsson, Henrik; Jönsson, Göran; Vallon-Christersson, Johan

2004-11-12

Non-linearities in observed log-ratios of gene expressions, also known as intensity dependent log-ratios, can often be accounted for by global biases in the two channels being compared. Any step in a microarray process may introduce such offsets and in this article we study the biases introduced by the microarray scanner and the image analysis software. By scanning the same spotted oligonucleotide microarray at different photomultiplier tube (PMT) gains, we have identified a channel-specific bias present in two-channel microarray data. For the scanners analyzed it was in the range of 15-25 (out of 65,535). The observed bias was very stable between subsequent scans of the same array although the PMT gain was greatly adjusted. This indicates that the bias does not originate from a step preceding the scanner detector parts. The bias varies slightly between arrays. When comparing estimates based on data from the same array, but from different scanners, we have found that different scanners introduce different amounts of bias. So do various image analysis methods. We propose a scanning protocol and a constrained affine model that allows us to identify and estimate the bias in each channel. Backward transformation removes the bias and brings the channels to the same scale. The result is that systematic effects such as intensity dependent log-ratios are removed, but also that signal densities become much more similar. The average scan, which has a larger dynamical range and greater signal-to-noise ratio than individual scans, can then be obtained. The study shows that microarray scanners may introduce a significant bias in each channel. Such biases have to be calibrated for, otherwise systematic effects such as intensity dependent log-ratios will be observed. The proposed scanning protocol and calibration method is simple to use and is useful for evaluating scanner biases or for obtaining calibrated measurements with extended dynamical range and better precision. The cross-platform R package aroma, which implements all described methods, is available for free from http://www.maths.lth.se/bioinformatics/.

Systems approach to the pharmacological actions of HDAC inhibitors reveals EP300 activities and convergent mechanisms of regulation in diabetes.

PubMed

Rafehi, Haloom; Kaspi, Antony; Ziemann, Mark; Okabe, Jun; Karagiannis, Tom C; El-Osta, Assam

2017-01-01

Given the skyrocketing costs to develop new drugs, repositioning of approved drugs, such as histone deacetylase (HDAC) inhibitors, may be a promising strategy to develop novel therapies. However, a gap exists in the understanding and advancement of these agents to meaningful translation for which new indications may emerge. To address this, we performed systems-level analyses of 33 independent HDAC inhibitor microarray studies. Based on network analysis, we identified enrichment for pathways implicated in metabolic syndrome and diabetes (insulin receptor signaling, lipid metabolism, immunity and trafficking). Integration with ENCODE ChIP-seq datasets identified suppression of EP300 target genes implicated in diabetes. Experimental validation indicates reversal of diabetes-associated EP300 target genes in primary vascular endothelial cells derived from a diabetic individual following inhibition of HDACs (by SAHA), EP300, or EP300 knockdown. Our computational systems biology approach provides an adaptable framework for the prediction of novel therapeutics for existing disease.

Inference of combinatorial Boolean rules of synergistic gene sets from cancer microarray datasets.

PubMed

Park, Inho; Lee, Kwang H; Lee, Doheon

2010-06-15

Gene set analysis has become an important tool for the functional interpretation of high-throughput gene expression datasets. Moreover, pattern analyses based on inferred gene set activities of individual samples have shown the ability to identify more robust disease signatures than individual gene-based pattern analyses. Although a number of approaches have been proposed for gene set-based pattern analysis, the combinatorial influence of deregulated gene sets on disease phenotype classification has not been studied sufficiently. We propose a new approach for inferring combinatorial Boolean rules of gene sets for a better understanding of cancer transcriptome and cancer classification. To reduce the search space of the possible Boolean rules, we identify small groups of gene sets that synergistically contribute to the classification of samples into their corresponding phenotypic groups (such as normal and cancer). We then measure the significance of the candidate Boolean rules derived from each group of gene sets; the level of significance is based on the class entropy of the samples selected in accordance with the rules. By applying the present approach to publicly available prostate cancer datasets, we identified 72 significant Boolean rules. Finally, we discuss several identified Boolean rules, such as the rule of glutathione metabolism (down) and prostaglandin synthesis regulation (down), which are consistent with known prostate cancer biology. Scripts written in Python and R are available at http://biosoft.kaist.ac.kr/~ihpark/. The refined gene sets and the full list of the identified Boolean rules are provided in the Supplementary Material. Supplementary data are available at Bioinformatics online.

Microbial forensics: fiber optic microarray subtyping of Bacillus anthracis

NASA Astrophysics Data System (ADS)

Shepard, Jason R. E.

2009-05-01

The past decade has seen increased development and subsequent adoption of rapid molecular techniques involving DNA analysis for detection of pathogenic microorganisms, also termed microbial forensics. The continued accumulation of microbial sequence information in genomic databases now better positions the field of high-throughput DNA analysis to proceed in a more manageable fashion. The potential to build off of these databases exists as technology continues to develop, which will enable more rapid, cost effective analyses. This wealth of genetic information, along with new technologies, has the potential to better address some of the current problems and solve the key issues involved in DNA analysis of pathogenic microorganisms. To this end, a high density fiber optic microarray has been employed, housing numerous DNA sequences simultaneously for detection of various pathogenic microorganisms, including Bacillus anthracis, among others. Each organism is analyzed with multiple sequences and can be sub-typed against other closely related organisms. For public health labs, real-time PCR methods have been developed as an initial preliminary screen, but culture and growth are still considered the gold standard. Technologies employing higher throughput than these standard methods are better suited to capitalize on the limitless potential garnered from the sequence information. Microarray analyses are one such format positioned to exploit this potential, and our array platform is reusable, allowing repetitive tests on a single array, providing an increase in throughput and decrease in cost, along with a certainty of detection, down to the individual strain level.

Genomic paradigms for food-borne enteric pathogen analysis at the USFDA: case studies highlighting method utility, integration and resolution.

PubMed

Elkins, C A; Kotewicz, M L; Jackson, S A; Lacher, D W; Abu-Ali, G S; Patel, I R

2013-01-01

Modern risk control and food safety practices involving food-borne bacterial pathogens are benefiting from new genomic technologies for rapid, yet highly specific, strain characterisations. Within the United States Food and Drug Administration (USFDA) Center for Food Safety and Applied Nutrition (CFSAN), optical genome mapping and DNA microarray genotyping have been used for several years to quickly assess genomic architecture and gene content, respectively, for outbreak strain subtyping and to enhance retrospective trace-back analyses. The application and relative utility of each method varies with outbreak scenario and the suspect pathogen, with comparative analytical power enhanced by database scale and depth. Integration of these two technologies allows high-resolution scrutiny of the genomic landscapes of enteric food-borne pathogens with notable examples including Shiga toxin-producing Escherichia coli (STEC) and Salmonella enterica serovars from a variety of food commodities. Moreover, the recent application of whole genome sequencing technologies to food-borne pathogen outbreaks and surveillance has enhanced resolution to the single nucleotide scale. This new wealth of sequence data will support more refined next-generation custom microarray designs, targeted re-sequencing and "genomic signature recognition" approaches involving a combination of genes and single nucleotide polymorphism detection to distil strain-specific fingerprinting to a minimised scale. This paper examines the utility of microarrays and optical mapping in analysing outbreaks, reviews best practices and the limits of these technologies for pathogen differentiation, and it considers future integration with whole genome sequencing efforts.

Microarray RNA expression analysis of cerebral white matter lesions reveals changes in multiple functional pathways.

PubMed

Simpson, Julie E; Hosny, Ola; Wharton, Stephen B; Heath, Paul R; Holden, Hazel; Fernando, Malee S; Matthews, Fiona; Forster, Gill; O'Brien, John T; Barber, Robert; Kalaria, Raj N; Brayne, Carol; Shaw, Pamela J; Lewis, Claire E; Ince, Paul G

2009-02-01

White matter lesions (WML) in brain aging are linked to dementia and depression. Ischemia contributes to their pathogenesis but other mechanisms may contribute. We used RNA microarray analysis with functional pathway grouping as an unbiased approach to investigate evidence for additional pathogenetic mechanisms. WML were identified by MRI and pathology in brains donated to the Medical Research Council Cognitive Function and Ageing Study Cognitive Function and Aging Study. RNA was extracted to compare WML with nonlesional white matter samples from cases with lesions (WM[L]), and from cases with no lesions (WM[C]) using RNA microarray and pathway analysis. Functional pathways were validated for selected genes by quantitative real-time polymerase chain reaction and immunocytochemistry. We identified 8 major pathways in which multiple genes showed altered RNA transcription (immune regulation, cell cycle, apoptosis, proteolysis, ion transport, cell structure, electron transport, metabolism) among 502 genes that were differentially expressed in WML compared to WM[C]. In WM[L], 409 genes were altered involving the same pathways. Genes selected to validate this microarray data all showed the expected changes in RNA levels and immunohistochemical expression of protein. WML represent areas with a complex molecular phenotype. From this and previous evidence, WML may arise through tissue ischemia but may also reflect the contribution of additional factors like blood-brain barrier dysfunction. Differential expression of genes in WM[L] compared to WM[C] indicate a "field effect" in the seemingly normal surrounding white matter.

RNAi targeting GPR4 influences HMEC-1 gene expression by microarray analysis

PubMed Central

Ren, Juan; Zhang, Yuelang; Cai, Hui; Ma, Hongbing; Zhao, Dongli; Zhang, Xiaozhi; Li, Zongfang; Wang, Shufeng; Wang, Jiangsheng; Liu, Rui; Li, Yi; Qian, Jiansheng; Wei, Hongxia; Niu, Liying; Liu, Yan; Xiao, Lisha; Ding, Muyang; Jiang, Shiwen

2014-01-01

G-protein coupled receptor 4 (GPR4) belongs to a protein family comprised of 3 closely related G protein-coupled receptors. Recent studies have shown that GPR4 plays important roles in angiogenesis, proton sensing, and regulating tumor cells as an oncogenic gene. How GPR4 conducts its functions? Rare has been known. In order to detect the genes related to GPR4, microarray technology was employed. GPR4 is highly expressed in human vascular endothelial cell HMEC-1. Small interfering RNA against GPR4 was used to knockdown GPR4 expression in HMEC-1. Then RNA from the GPR4 knockdown cells and control cells were analyzed through genome microarray. Microarray results shown that among the whole genes and expressed sequence tags, 447 differentially expressed genes were identified, containing 318 up-regulated genes and 129 down-regulated genes. These genes whose expression dramatically changed may be involved in the GPR4 functions. These genes were related to cell apoptosis, cytoskeleton and signal transduction, cell proliferation, differentiation and cell-cycle regulation, gene transcription and translation and cell material and energy metabolism. PMID:24753754

Prediction of Microbial Infection of Cultured Cells Using DNA Microarray Gene-Expression Profiles of Host Responses

PubMed Central

Park, Yu Rang; Chung, Tae Su; Lee, Young Joo; Song, Yeong Wook; Lee, Eun Young; Sohn, Yeo Won; Song, Sukgil; Park, Woong Yang

2012-01-01

Infection by microorganisms may cause fatally erroneous interpretations in the biologic researches based on cell culture. The contamination by microorganism in the cell culture is quite frequent (5% to 35%). However, current approaches to identify the presence of contamination have many limitations such as high cost of time and labor, and difficulty in interpreting the result. In this paper, we propose a model to predict cell infection, using a microarray technique which gives an overview of the whole genome profile. By analysis of 62 microarray expression profiles under various experimental conditions altering cell type, source of infection and collection time, we discovered 5 marker genes, NM_005298, NM_016408, NM_014588, S76389, and NM_001853. In addition, we discovered two of these genes, S76389, and NM_001853, are involved in a Mycolplasma-specific infection process. We also suggest models to predict the source of infection, cell type or time after infection. We implemented a web based prediction tool in microarray data, named Prediction of Microbial Infection (http://www.snubi.org/software/PMI). PMID:23091307

Quality control of inkjet technology for DNA microarray fabrication.

PubMed

Pierik, Anke; Dijksman, Frits; Raaijmakers, Adrie; Wismans, Ton; Stapert, Henk

2008-12-01

A robust manufacturing process is essential to make high-quality DNA microarrays, especially for use in diagnostic tests. We investigated different failure modes of the inkjet printing process used to manufacture low-density microarrays. A single nozzle inkjet spotter was provided with two optical imaging systems, monitoring in real time the flight path of every droplet. If a droplet emission failure is detected, the printing process is automatically stopped. We analyzed over 1.3 million droplets. This information was used to investigate the performance of the inkjet system and to obtain detailed insight into the frequency and causes of jetting failures. Of all the substrates investigated, 96.2% were produced without any system or jetting failures. In 1.6% of the substrates, droplet emission failed and was correctly identified. Appropriate measures could then be taken to get the process back on track. In 2.2%, the imaging systems failed while droplet emission occurred correctly. In 0.1% of the substrates, droplet emission failure that was not timely detected occurred. Thus, the overall yield of the microarray manufacturing process was 99.9%, which is highly acceptable for prototyping.

Transcriptomic Analysis Using Olive Varieties and Breeding Progenies Identifies Candidate Genes Involved in Plant Architecture.

PubMed

González-Plaza, Juan J; Ortiz-Martín, Inmaculada; Muñoz-Mérida, Antonio; García-López, Carmen; Sánchez-Sevilla, José F; Luque, Francisco; Trelles, Oswaldo; Bejarano, Eduardo R; De La Rosa, Raúl; Valpuesta, Victoriano; Beuzón, Carmen R

2016-01-01

Plant architecture is a critical trait in fruit crops that can significantly influence yield, pruning, planting density and harvesting. Little is known about how plant architecture is genetically determined in olive, were most of the existing varieties are traditional with an architecture poorly suited for modern growing and harvesting systems. In the present study, we have carried out microarray analysis of meristematic tissue to compare expression profiles of olive varieties displaying differences in architecture, as well as seedlings from their cross pooled on the basis of their sharing architecture-related phenotypes. The microarray used, previously developed by our group has already been applied to identify candidates genes involved in regulating juvenile to adult transition in the shoot apex of seedlings. Varieties with distinct architecture phenotypes and individuals from segregating progenies displaying opposite architecture features were used to link phenotype to expression. Here, we identify 2252 differentially expressed genes (DEGs) associated to differences in plant architecture. Microarray results were validated by quantitative RT-PCR carried out on genes with functional annotation likely related to plant architecture. Twelve of these genes were further analyzed in individual seedlings of the corresponding pool. We also examined Arabidopsis mutants in putative orthologs of these targeted candidate genes, finding altered architecture for most of them. This supports a functional conservation between species and potential biological relevance of the candidate genes identified. This study is the first to identify genes associated to plant architecture in olive, and the results obtained could be of great help in future programs aimed at selecting phenotypes adapted to modern cultivation practices in this species.

Protein profiles associated with survival in lung adenocarcinoma

PubMed Central

Chen, Guoan; Gharib, Tarek G; Wang, Hong; Huang, Chiang-Ching; Kuick, Rork; Thomas, Dafydd G.; Shedden, Kerby A.; Misek, David E.; Taylor, Jeremy M. G.; Giordano, Thomas J.; Kardia, Sharon L. R.; Iannettoni, Mark D.; Yee, John; Hogg, Philip J.; Orringer, Mark B.; Hanash, Samir M.; Beer, David G.

2003-01-01

Morphologic assessment of lung tumors is informative but insufficient to adequately predict patient outcome. We previously identified transcriptional profiles that predict patient survival, and here we identify proteins associated with patient survival in lung adenocarcinoma. A total of 682 individual protein spots were quantified in 90 lung adenocarcinomas by using quantitative two-dimensional polyacrylamide gel electrophoresis analysis. A leave-one-out cross-validation procedure using the top 20 survival-associated proteins identified by Cox modeling indicated that protein profiles as a whole can predict survival in stage I tumor patients (P = 0.01). Thirty-three of 46 survival-associated proteins were identified by using mass spectrometry. Expression of 12 candidate proteins was confirmed as tumor-derived with immunohistochemical analysis and tissue microarrays. Oligonucleotide microarray results from both the same tumors and from an independent study showed mRNAs associated with survival for 11 of 27 encoded genes. Combined analysis of protein and mRNA data revealed 11 components of the glycolysis pathway as associated with poor survival. Among these candidates, phosphoglycerate kinase 1 was associated with survival in the protein study, in both mRNA studies and in an independent validation set of 117 adenocarcinomas and squamous lung tumors using tissue microarrays. Elevated levels of phosphoglycerate kinase 1 in the serum were also significantly correlated with poor outcome in a validation set of 107 patients with lung adenocarcinomas using ELISA analysis. These studies identify new prognostic biomarkers and indicate that protein expression profiles can predict the outcome of patients with early-stage lung cancer. PMID:14573703

Discovery of prognostic biomarkers for predicting lung cancer metastasis using microarray and survival data.

PubMed

Huang, Hui-Ling; Wu, Yu-Chung; Su, Li-Jen; Huang, Yun-Ju; Charoenkwan, Phasit; Chen, Wen-Liang; Lee, Hua-Chin; Chu, William Cheng-Chung; Ho, Shinn-Ying

2015-02-21

Few studies have investigated prognostic biomarkers of distant metastases of lung cancer. One of the central difficulties in identifying biomarkers from microarray data is the availability of only a small number of samples, which results overtraining. Recently obtained evidence reveals that epithelial-mesenchymal transition (EMT) of tumor cells causes metastasis, which is detrimental to patients' survival. This work proposes a novel optimization approach to discovering EMT-related prognostic biomarkers to predict the distant metastasis of lung cancer using both microarray and survival data. This weighted objective function maximizes both the accuracy of prediction of distant metastasis and the area between the disease-free survival curves of the non-distant and distant metastases. Seventy-eight patients with lung cancer and a follow-up time of 120 months are used to identify a set of gene markers and an independent cohort of 26 patients is used to evaluate the identified biomarkers. The medical records of the 78 patients show a significant difference between the disease-free survival times of the 37 non-distant- and the 41 distant-metastasis patients. The experimental results thus obtained are as follows. 1) The use of disease-free survival curves can compensate for the shortcoming of insufficient samples and greatly increase the test accuracy by 11.10%; and 2) the support vector machine with a set of 17 transcripts, such as CCL16 and CDKN2AIP, can yield a leave-one-out cross-validation accuracy of 93.59%, a test accuracy of 76.92%, a large disease-free survival area of 74.81%, and a mean survival prediction error of 3.99 months. The identified putative biomarkers are examined using related studies and signaling pathways to reveal the potential effectiveness of the biomarkers in prospective confirmatory studies. The proposed new optimization approach to identifying prognostic biomarkers by combining multiple sources of data (microarray and survival) can facilitate the accurate selection of biomarkers that are most relevant to the disease while solving the problem of insufficient samples.

Impact of genotyping errors on statistical power of association tests in genomic analyses: A case study

PubMed Central

Hou, Lin; Sun, Ning; Mane, Shrikant; Sayward, Fred; Rajeevan, Nallakkandi; Cheung, Kei-Hoi; Cho, Kelly; Pyarajan, Saiju; Aslan, Mihaela; Miller, Perry; Harvey, Philip D.; Gaziano, J. Michael; Concato, John; Zhao, Hongyu

2017-01-01

A key step in genomic studies is to assess high throughput measurements across millions of markers for each participant’s DNA, either using microarrays or sequencing techniques. Accurate genotype calling is essential for downstream statistical analysis of genotype-phenotype associations, and next generation sequencing (NGS) has recently become a more common approach in genomic studies. How the accuracy of variant calling in NGS-based studies affects downstream association analysis has not, however, been studied using empirical data in which both microarrays and NGS were available. In this article, we investigate the impact of variant calling errors on the statistical power to identify associations between single nucleotides and disease, and on associations between multiple rare variants and disease. Both differential and nondifferential genotyping errors are considered. Our results show that the power of burden tests for rare variants is strongly influenced by the specificity in variant calling, but is rather robust with regard to sensitivity. By using the variant calling accuracies estimated from a substudy of a Cooperative Studies Program project conducted by the Department of Veterans Affairs, we show that the power of association tests is mostly retained with commonly adopted variant calling pipelines. An R package, GWAS.PC, is provided to accommodate power analysis that takes account of genotyping errors (http://zhaocenter.org/software/). PMID:28019059

A comparative cDNA microarray analysis reveals a spectrum of genes regulated by Pax6 in mouse lens

PubMed Central

Chauhan, Bharesh K.; Reed, Nathan A.; Yang, Ying; Čermák, Lukáš; Reneker, Lixing; Duncan, Melinda K.; Cvekl, Aleš

2007-01-01

Background Pax6 is a transcription factor that is required for induction, growth, and maintenance of the lens; however, few direct target genes of Pax6 are known. Results In this report, we describe the results of a cDNA microarray analysis of lens transcripts from transgenic mice over-expressing Pax6 in lens fibre cells in order to narrow the field of potential direct Pax6 target genes. This study revealed that the transcript levels were significantly altered for 508 of the 9700 genes analysed, including five genes encoding the cell adhesion molecules β1-integrin, JAM1, L1 CAM, NCAM-140 and neogenin. Notably, comparisons between the genes differentially expressed in Pax6 heterozygous and Pax6 over-expressing lenses identified 13 common genes, including paralemmin, GDIβ, ATF1, Hrp12 and Brg1. Immunohistochemistry and Western blotting demonstrated that Brg1 is expressed in the embryonic and neonatal (2-week-old) but not in 14-week adult lenses, and confirmed altered expression in transgenic lenses over-expressing Pax6. Furthermore, EMSA demonstrated that the BRG1 promoter contains Pax6 binding sites, further supporting the proposition that it is directly regulated by Pax6. Conclusions These results provide a list of genes with possible roles in lens biology and cataracts that are directly or indirectly regulated by Pax6. PMID:12485166

Staphylococcus aureus colonization related to severity of hand eczema.

PubMed

Mernelius, S; Carlsson, E; Henricson, J; Löfgren, S; Lindgren, P-E; Ehricht, R; Monecke, S; Matussek, A; Anderson, C D

2016-08-01

Knowledge on Staphylococcus aureus colonization rates and epidemiology in hand eczema is limited. The aim of this study was to clarify some of these issues. Samples were collected by the "glove juice" method from the hands of 59 patients with chronic hand eczema and 24 healthy individuals. Swab samples were taken from anterior nares and throat from 43 of the 59 patients and all healthy individuals. S. aureus were spa typed and analysed by DNA-microarray-based genotyping. The extent of the eczema was evaluated by the hand eczema extent score (HEES). The colonization rate was higher on the hands of hand eczema patients (69 %) compared to healthy individuals (21 %, p < 0.001). This was also seen for bacterial density (p = 0.002). Patients with severe hand eczema (HEES ≥ 13) had a significantly higher S. aureus density on their hands compared to those with milder eczema (HEES = 1 to 12, p = 0.004). There was no difference between patients and healthy individuals regarding colonization rates in anterior nares or throat. spa typing and DNA-microarray-based genotyping indicated certain types more prone to colonize eczematous skin. Simultaneous colonization, in one individual, with S. aureus of different types, was identified in 60-85 % of the study subjects. The colonization rate and density indicate a need for effective treatment of eczema and may have an impact on infection control in healthcare.

Revealing impaired pathways in the an11 mutant by high-throughput characterization of Petunia axillaris and Petunia inflata transcriptomes.

PubMed

Zenoni, Sara; D'Agostino, Nunzio; Tornielli, Giovanni B; Quattrocchio, Francesca; Chiusano, Maria L; Koes, Ronald; Zethof, Jan; Guzzo, Flavia; Delledonne, Massimo; Frusciante, Luigi; Gerats, Tom; Pezzotti, Mario

2011-10-01

Petunia is an excellent model system, especially for genetic, physiological and molecular studies. Thus far, however, genome-wide expression analysis has been applied rarely because of the lack of sequence information. We applied next-generation sequencing to generate, through de novo read assembly, a large catalogue of transcripts for Petunia axillaris and Petunia inflata. On the basis of both transcriptomes, comprehensive microarray chips for gene expression analysis were established and used for the analysis of global- and organ-specific gene expression in Petunia axillaris and Petunia inflata and to explore the molecular basis of the seed coat defects in a Petunia hybrida mutant, anthocyanin 11 (an11), lacking a WD40-repeat (WDR) transcription regulator. Among the transcripts differentially expressed in an11 seeds compared with wild type, many expected targets of AN11 were found but also several interesting new candidates that might play a role in morphogenesis of the seed coat. Our results validate the combination of next-generation sequencing with microarray analyses strategies to identify the transcriptome of two petunia species without previous knowledge of their genome, and to develop comprehensive chips as useful tools for the analysis of gene expression in P. axillaris, P. inflata and P. hybrida. © 2011 The Authors. The Plant Journal © 2011 Blackwell Publishing Ltd.

Analysis and Characterization of Proteins Associated with Outer Membrane Vesicles Secreted by Cronobacter spp.

PubMed Central

Kothary, Mahendra H.; Gopinath, Gopal R.; Gangiredla, Jayanthi; Rallabhandi, Prasad V.; Harrison, Lisa M.; Yan, Qiong Q.; Chase, Hannah R.; Lee, Boram; Park, Eunbi; Yoo, YeonJoo; Chung, Taejung; Finkelstein, Samantha B.; Negrete, Flavia J.; Patel, Isha R.; Carter, Laurenda; Sathyamoorthy, Venugopal; Fanning, Séamus; Tall, Ben D.

2017-01-01

Little is known about secretion of outer membrane vesicles (OMVs) by Cronobacter. In this study, OMVs isolated from Cronobacter sakazakii, Cronobacter turicensis, and Cronobacter malonaticus were examined by electron microscopy (EM) and their associated outer membrane proteins (OMP) and genes were analyzed by SDS-PAGE, protein sequencing, BLAST, PCR, and DNA microarray. EM of stained cells revealed that the OMVs are secreted as pleomorphic micro-vesicles which cascade from the cell's surface. SDS-PAGE analysis identified protein bands with molecular weights of 18 kDa to >100 kDa which had homologies to OMPs such as GroEL; OmpA, C, E, F, and X; MipA proteins; conjugative plasmid transfer protein; and an outer membrane auto-transporter protein (OMATP). PCR analyses showed that most of the OMP genes were present in all seven Cronobacter species while a few genes (OMATP gene, groEL, ompC, mipA, ctp, and ompX) were absent in some phylogenetically-related species. Microarray analysis demonstrated sequence divergence among the OMP genes that was not captured by PCR. These results support previous findings that OmpA and OmpX may be involved in virulence of Cronobacter, and are packaged within secreted OMVs. These results also suggest that other OMV-packaged OMPs may be involved in roles such as stress response, cell wall and plasmid maintenance, and extracellular transport. PMID:28232819

Differential expression of genes and proteins associated with wool follicle cycling.

PubMed

Liu, Nan; Li, Hegang; Liu, Kaidong; Yu, Juanjuan; Cheng, Ming; De, Wei; Liu, Jifeng; Shi, Shuyan; He, Yanghua; Zhao, Jinshan

2014-08-01

Sheep are valuable resources for the wool industry. Wool growth of Aohan fine wool sheep has cycled during different seasons in 1 year. Therefore, identifying genes that control wool growth cycling might lead to ways for improving the quality and yield of fine wool. In this study, we employed Agilent sheep gene expression microarray and proteomic technology to compare the gene expression patterns of the body side skins at August and December time points in Aohan fine wool sheep (a Chinese indigenous breed). Microarray study revealed that 2,223 transcripts were differentially expressed, including 1,162 up-regulated and 1,061 down-regulated transcripts, comparing body side skin at the August time point to the December one (A/D) in Aohan fine wool sheep. Then seven differentially expressed genes were selected to validated the reliability of the gene chip data. The majority of the genes possibly related to follicle development and wool growth could be assigned into the categories including regulation of receptor binding, extracellular region, protein binding and extracellular space. Proteomic study revealed that 84 protein spots showed significant differences in expression levels. Of the 84, 63 protein spots were upregulated and 21 were downregulated in A/D. Finally, 55 protein points were determined through MALDI-TOF/MS analyses. Furthermore, the regulation mechanism of hair follicle might resemble that of fetation.