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.
Dehne, T.; Lindahl, A.; Brittberg, M.; Pruss, A.; Ringe, J.; Sittinger, M.; Karlsson, C.
2012-01-01
Objective: It is well known that expression of markers for WNT signaling is dysregulated in osteoarthritic (OA) bone. However, it is still not fully known if the expression of these markers also is affected in OA cartilage. The aim of this study was therefore to examine this issue. Methods: Human cartilage biopsies from OA and control donors were subjected to genome-wide oligonucleotide microarrays. Genes involved in WNT signaling were selected using the BioRetis database, KEGG pathway analysis was searched using DAVID software tools, and cluster analysis was performed using Genesis software. Results from the microarray analysis were verified using quantitative real-time PCR and immunohistochemistry. In order to study the impact of cytokines for the dysregulated WNT signaling, OA and control chondrocytes were stimulated with interleukin-1 and analyzed with real-time PCR for their expression of WNT-related genes. Results: Several WNT markers displayed a significantly altered expression in OA compared to normal cartilage. Interestingly, inhibitors of the canonical and planar cell polarity WNT signaling pathways displayed significantly increased expression in OA cartilage, while the Ca2+/WNT signaling pathway was activated. Both real-time PCR and immunohistochemistry verified the microarray results. Real-time PCR analysis demonstrated that interleukin-1 upregulated expression of important WNT markers. Conclusions: WNT signaling is significantly affected in OA cartilage. The result suggests that both the canonical and planar cell polarity WNT signaling pathways were partly inhibited while the Ca2+/WNT pathway was activated in OA cartilage. PMID:26069618
Large-scale analysis of gene expression using cDNA microarrays promises the
rapid detection of the mode of toxicity for drugs and other chemicals. cDNA
microarrays were used to examine chemically-induced alterations of gene
expression in HepG2 cells exposed to oxidative ...
Autoregressive-model-based missing value estimation for DNA microarray time series data.
Choong, Miew Keen; Charbit, Maurice; Yan, Hong
2009-01-01
Missing value estimation is important in DNA microarray data analysis. A number of algorithms have been developed to solve this problem, but they have several limitations. Most existing algorithms are not able to deal with the situation where a particular time point (column) of the data is missing entirely. In this paper, we present an autoregressive-model-based missing value estimation method (ARLSimpute) that takes into account the dynamic property of microarray temporal data and the local similarity structures in the data. ARLSimpute is especially effective for the situation where a particular time point contains many missing values or where the entire time point is missing. Experiment results suggest that our proposed algorithm is an accurate missing value estimator in comparison with other imputation methods on simulated as well as real microarray time series datasets.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Gentry, T.; Schadt, C.; Zhou, J.
Microarray technology has the unparalleled potential tosimultaneously determine the dynamics and/or activities of most, if notall, of the microbial populations in complex environments such as soilsand sediments. Researchers have developed several types of arrays thatcharacterize the microbial populations in these samples based on theirphylogenetic relatedness or functional genomic content. Several recentstudies have used these microarrays to investigate ecological issues;however, most have only analyzed a limited number of samples withrelatively few experiments utilizing the full high-throughput potentialof microarray analysis. This is due in part to the unique analyticalchallenges that these samples present with regard to sensitivity,specificity, quantitation, and data analysis. Thismore » review discussesspecific applications of microarrays to microbial ecology research alongwith some of the latest studies addressing the difficulties encounteredduring analysis of complex microbial communities within environmentalsamples. With continued development, microarray technology may ultimatelyachieve its potential for comprehensive, high-throughput characterizationof microbial populations in near real-time.« less
Prediction of regulatory gene pairs using dynamic time warping and gene ontology.
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.
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.
Muguruma, Masako; Nishimura, Jihei; Jin, Meilan; Kashida, Yoko; Moto, Mitsuyoshi; Takahashi, Miwa; Yokouchi, Yusuke; Mitsumori, Kunitoshi
2006-12-07
Piperonyl butoxide (PBO), alpha-[2-(2-butoxyethoxy)ethoxy]-4,5-methylene-dioxy-2-propyltoluene, is widely used as a synergist for pyrethrins. In order to clarify the possible mechanism of non-genotoxic hepatocarcinogenesis induced by PBO, molecular pathological analyses consisting of low-density microarray analysis and real-time reverse transcriptase (RT)-PCR were performed in male ICR mice fed a basal powdered diet containing 6000 or 0 ppm PBO for 1, 4, or 8 weeks. The animals were sacrificed at weeks 1, 4, and 8, and the livers were histopathologically examined and analyzed for gene expression using the microarray at weeks 1 and 4 followed by real-time RT-PCR at each time point. Reactive oxygen species (ROS) products were also measured using liver microsomes. At each time point, the hepatocytes of PBO-treated mice showed centrilobular hypertrophy and increased lipofuscin deposition in Schmorl staining. The ROS products were significantly increased in the liver microsomes of PBO-treated mice. In the microarray analysis, the expression of oxidative and metabolic stress-related genes--cytochrome P450 (Cyp) 1A1, Cyp2A5 (week 1 only), Cyp2B9, Cyp2B10, and NADPH-cytochrome P450 oxidoreductase (Por) was over-expressed in mice given PBO at weeks 1 and 4. Fluctuations of these genes were confirmed by real-time RT-PCR in PBO-treated mice at each time point. In additional real-time RT-PCR, the expression of Cyclin D1 gene, key regulator of cell-cycle progression, and Xrcc5 gene, DNA damage repair-related gene, was significantly increased at each time point and at week 8, respectively. These results suggest the possibility that PBO has the potential to generate ROS via the metabolic pathway and to induce oxidative stress, including oxidative DNA damage, resulting in the induction of hepatocellular tumors in mice.
Ito, Yoshinori; Shibata-Watanabe, Yukiko; Ushijima, Yoko; Kawada, Jun-Ichi; Nishiyama, Yukihiro; Kojima, Seiji; Kimura, Hiroshi
2008-03-01
Chronic active Epstein-Barr virus infection (CAEBV) is characterized by recurrent infectious mononucleosis-like symptoms and has high mortality and morbidity. To clarify the mechanisms of CAEBV, the gene-expression profiles of peripheral blood obtained from patients with CAEBV were investigated. Twenty genes were differentially expressed in 4 patients with CAEBV. This microarray result was verified using a real-time reverse-transcriptase polymerase chain reaction assay in a larger group of patients with CAEBV. Eventually, 3 genes were found to be significantly upregulated: guanylate binding protein 1, tumor necrosis factor-induced protein 6, and guanylate binding protein 5. These genes may be associated with the inflammatory reaction or with cell proliferation.
Microarray-based identification of differentially expressed genes in extramammary Paget’s disease
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
NAIMA as a solution for future GMO diagnostics challenges.
Dobnik, David; Morisset, Dany; Gruden, Kristina
2010-03-01
In the field of genetically modified organism (GMO) diagnostics, real-time PCR has been the method of choice for target detection and quantification in most laboratories. Despite its numerous advantages, however, the lack of a true multiplexing option may render real-time PCR less practical in the face of future GMO detection challenges such as the multiplicity and increasing complexity of new transgenic events, as well as the repeated occurrence of unauthorized GMOs on the market. In this context, we recently reported the development of a novel multiplex quantitative DNA-based target amplification method, named NASBA implemented microarray analysis (NAIMA), which is suitable for sensitive, specific and quantitative detection of GMOs on a microarray. In this article, the performance of NAIMA is compared with that of real-time PCR, the focus being their performances in view of the upcoming challenge to detect/quantify an increasing number of possible GMOs at a sustainable cost and affordable staff effort. Finally, we present our conclusions concerning the applicability of NAIMA for future use in GMO diagnostics.
2010-01-01
Background Recent developments in high-throughput methods of analyzing transcriptomic profiles are promising for many areas of biology, including ecophysiology. However, although commercial microarrays are available for most common laboratory models, transcriptome analysis in non-traditional model species still remains a challenge. Indeed, the signal resulting from heterologous hybridization is low and difficult to interpret because of the weak complementarity between probe and target sequences, especially when no microarray dedicated to a genetically close species is available. Results We show here that transcriptome analysis in a species genetically distant from laboratory models is made possible by using MAXRS, a new method of analyzing heterologous hybridization on microarrays. This method takes advantage of the design of several commercial microarrays, with different probes targeting the same transcript. To illustrate and test this method, we analyzed the transcriptome of king penguin pectoralis muscle hybridized to Affymetrix chicken microarrays, two organisms separated by an evolutionary distance of approximately 100 million years. The differential gene expression observed between different physiological situations computed by MAXRS was confirmed by real-time PCR on 10 genes out of 11 tested. Conclusions MAXRS appears to be an appropriate method for gene expression analysis under heterologous hybridization conditions. PMID:20509979
Mining microarrays for metabolic meaning: nutritional regulation of hypothalamic gene expression.
Mobbs, Charles V; Yen, Kelvin; Mastaitis, Jason; Nguyen, Ha; Watson, Elizabeth; Wurmbach, Elisa; Sealfon, Stuart C; Brooks, Andrew; Salton, Stephen R J
2004-06-01
DNA microarray analysis has been used to investigate relative changes in the level of gene expression in the CNS, including changes that are associated with disease, injury, psychiatric disorders, drug exposure or withdrawal, and memory formation. We have used oligonucleotide microarrays to identify hypothalamic genes that respond to nutritional manipulation. In addition to commonly used microarray analysis based on criteria such as fold-regulation, we have also found that simply carrying out multiple t tests then sorting by P value constitutes a highly reliable method to detect true regulation, as assessed by real-time polymerase chain reaction (PCR), even for relatively low abundance genes or relatively low magnitude of regulation. Such analyses directly suggested novel mechanisms that mediate effects of nutritional state on neuroendocrine function and are being used to identify regulated gene products that may elucidate the metabolic pathology of obese ob/ob, lean Vgf-/Vgf-, and other models with profound metabolic impairments.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Franke-Whittle, Ingrid H., E-mail: ingrid.whittle@uibk.ac.at; Walter, Andreas; Ebner, Christian
Highlights: • Different methanogenic communities in mesophilic and thermophilic reactors. • High VFA levels do not cause major changes in archaeal communities. • Real-time PCR indicated greater diversity than ANAEROCHIP microarray. - Abstract: A study was conducted to determine whether differences in the levels of volatile fatty acids (VFAs) in anaerobic digester plants could result in variations in the indigenous methanogenic communities. Two digesters (one operated under mesophilic conditions, the other under thermophilic conditions) were monitored, and sampled at points where VFA levels were high, as well as when VFA levels were low. Physical and chemical parameters were measured, andmore » the methanogenic diversity was screened using the phylogenetic microarray ANAEROCHIP. In addition, real-time PCR was used to quantify the presence of the different methanogenic genera in the sludge samples. Array results indicated that the archaeal communities in the different reactors were stable, and that changes in the VFA levels of the anaerobic digesters did not greatly alter the dominating methanogenic organisms. In contrast, the two digesters were found to harbour different dominating methanogenic communities, which appeared to remain stable over time. Real-time PCR results were inline with those of microarray analysis indicating only minimal changes in methanogen numbers during periods of high VFAs, however, revealed a greater diversity in methanogens than found with the array.« less
A PCR primer bank for quantitative gene expression analysis.
Wang, Xiaowei; Seed, Brian
2003-12-15
Although gene expression profiling by microarray analysis is a useful tool for assessing global levels of transcriptional activity, variability associated with the data sets usually requires that observed differences be validated by some other method, such as real-time quantitative polymerase chain reaction (real-time PCR). However, non-specific amplification of non-target genes is frequently observed in the latter, confounding the analysis in approximately 40% of real-time PCR attempts when primer-specific labels are not used. Here we present an experimentally validated algorithm for the identification of transcript-specific PCR primers on a genomic scale that can be applied to real-time PCR with sequence-independent detection methods. An online database, PrimerBank, has been created for researchers to retrieve primer information for their genes of interest. PrimerBank currently contains 147 404 primers encompassing most known human and mouse genes. The primer design algorithm has been tested by conventional and real-time PCR for a subset of 112 primer pairs with a success rate of 98.2%.
Estimating differential expression from multiple indicators
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
Bisphenol A exposure leads to specific microRNA alterations in placental cells.
Avissar-Whiting, Michele; Veiga, Keila R; Uhl, Kristen M; Maccani, Matthew A; Gagne, Luc A; Moen, Erika L; Marsit, Carmen J
2010-07-01
Exposure to bisphenol A (BPA) has been observed to alter developmental pathways and cell processes, at least in part, through epigenetic mechanisms. This study sought to investigate the effect of BPA on microRNAs (miRNAs) in human placental cells. miRNA microarray was performed following BPA treatment in three immortalized cytotrophoblast cell lines and the results validated using quantitative real-time PCR. For functional analysis, overexpression constructs were stably transfected into cells that were then assayed for changes in proliferation and response to toxicants. Microarray analysis revealed several miRNAs to be significantly altered in response to BPA treatment in two cell lines. Real-time PCR results confirmed that miR-146a was particularly strongly induced and its overexpression in cells led to slower proliferation as well as higher sensitivity to the DNA damaging agent, bleomycin. Overall, these results suggest that BPA can alter miRNA expression in placental cells, a potentially novel mode of BPA toxicity.
Bisphenol A Exposure Leads to Specific MicroRNA Alterations in Placental Cells
Avissar-Whiting, Michele; Veiga, Keila; Uhl, Kristen; Maccani, Matthew; Gagne, Luc; Moen, Erika; Marsit, Carmen J.
2010-01-01
Exposure to bisphenol-A (BPA) has been observed to alter developmental pathways and cell processes, at least in part, through epigenetic mechanisms. This study sought to investigate the effect of BPA on microRNAs (miRNAs) in human placental cells. miRNA microarray was performed following BPA treatment in three immortalized cytotrophoblast cell lines and the results validated using quantitative real-time PCR. For functional analysis, overexpression constructs were stably transfected into cells that were then assayed for changes in proliferation and response to toxicants. Microarray analysis revealed several miRNAs to be significantly altered in response to BPA treatment in two cell lines. Real-time PCR results confirmed that miR-146a was particularly strongly induced and its overexpression in cells led to slower proliferation as well as higher sensitivity to the DNA damaging agent, bleomycin. Overall, these results suggest that BPA can alter miRNA expression in placental cells, a potentially novel mode of BPA toxicity. PMID:20417706
BATS: a Bayesian user-friendly software for analyzing time series microarray experiments.
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.
MIGS-GPU: Microarray Image Gridding and Segmentation on the GPU.
Katsigiannis, Stamos; Zacharia, Eleni; Maroulis, Dimitris
2017-05-01
Complementary DNA (cDNA) microarray is a powerful tool for simultaneously studying the expression level of thousands of genes. Nevertheless, the analysis of microarray images remains an arduous and challenging task due to the poor quality of the images that often suffer from noise, artifacts, and uneven background. In this study, the MIGS-GPU [Microarray Image Gridding and Segmentation on Graphics Processing Unit (GPU)] software for gridding and segmenting microarray images is presented. MIGS-GPU's computations are performed on the GPU by means of the compute unified device architecture (CUDA) in order to achieve fast performance and increase the utilization of available system resources. Evaluation on both real and synthetic cDNA microarray images showed that MIGS-GPU provides better performance than state-of-the-art alternatives, while the proposed GPU implementation achieves significantly lower computational times compared to the respective CPU approaches. Consequently, MIGS-GPU can be an advantageous and useful tool for biomedical laboratories, offering a user-friendly interface that requires minimum input in order to run.
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
2010-01-01
Background The development of DNA microarrays has facilitated the generation of hundreds of thousands of transcriptomic datasets. The use of a common reference microarray design allows existing transcriptomic data to be readily compared and re-analysed in the light of new data, and the combination of this design with large datasets is ideal for 'systems'-level analyses. One issue is that these datasets are typically collected over many years and may be heterogeneous in nature, containing different microarray file formats and gene array layouts, dye-swaps, and showing varying scales of log2- ratios of expression between microarrays. Excellent software exists for the normalisation and analysis of microarray data but many data have yet to be analysed as existing methods struggle with heterogeneous datasets; options include normalising microarrays on an individual or experimental group basis. Our solution was to develop the Batch Anti-Banana Algorithm in R (BABAR) algorithm and software package which uses cyclic loess to normalise across the complete dataset. We have already used BABAR to analyse the function of Salmonella genes involved in the process of infection of mammalian cells. Results The only input required by BABAR is unprocessed GenePix or BlueFuse microarray data files. BABAR provides a combination of 'within' and 'between' microarray normalisation steps and diagnostic boxplots. When applied to a real heterogeneous dataset, BABAR normalised the dataset to produce a comparable scaling between the microarrays, with the microarray data in excellent agreement with RT-PCR analysis. When applied to a real non-heterogeneous dataset and a simulated dataset, BABAR's performance in identifying differentially expressed genes showed some benefits over standard techniques. Conclusions BABAR is an easy-to-use software tool, simplifying the simultaneous normalisation of heterogeneous two-colour common reference design cDNA microarray-based transcriptomic datasets. We show BABAR transforms real and simulated datasets to allow for the correct interpretation of these data, and is the ideal tool to facilitate the identification of differentially expressed genes or network inference analysis from transcriptomic datasets. PMID:20128918
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.
The ability of infectious oocyst forms of Toxoplasma gondii and Cryptosporidium spp. to resist disinfection treatments and cause disease may have significant public health implications. Currently, little is known about oocyst-specific factors involved during host cell invasion p...
Microarray analysis of gene expression in West Nile virus–infected human retinal pigment epithelium
Munoz-Erazo, Luis; Natoli, Ricardo; Provis, Jan Marie; Madigan, Michelle Catherine
2012-01-01
Purpose To identify key genes differentially expressed in the human retinal pigment epithelium (hRPE) following low-level West Nile virus (WNV) infection. Methods Primary hRPE and retinal pigment epithelium cell line (ARPE-19) cells were infected with WNV (multiplicity of infection 1). RNA extracted from mock-infected and WNV-infected cells was assessed for differential expression of genes using Affymetrix microarray. Quantitative real-time PCR analysis of 23 genes was used to validate the microarray results. Results Functional annotation clustering of the microarray data showed that gene clusters involved in immune and antiviral responses ranked highly, involving genes such as chemokine (C-C motif) ligand 2 (CCL2), chemokine (C-C motif) ligand 5 (CCL5), chemokine (C-X-C motif) ligand 10 (CXCL10), and toll like receptor 3 (TLR3). In conjunction with the quantitative real-time PCR analysis, other novel genes regulated by WNV infection included indoleamine 2,3-dioxygenase (IDO1), genes involved in the transforming growth factor–β pathway (bone morphogenetic protein and activin membrane-bound inhibitor homolog [BAMBI] and activating transcription factor 3 [ATF3]), and genes involved in apoptosis (tumor necrosis factor receptor superfamily, member 10d [TNFRSF10D]). WNV-infected RPE did not produce any interferon-γ, suggesting that IDO1 is induced by other soluble factors, by the virus alone, or both. Conclusions Low-level WNV infection of hRPE cells induced expression of genes that are typically associated with the host cell response to virus infection. We also identified other genes, including IDO1 and BAMBI, that may influence the RPE and therefore outer blood-retinal barrier integrity during ocular infection and inflammation, or are associated with degeneration, as seen for example in aging. PMID:22509103
2012-01-01
Background Thalidomide is an anti-inflammatory and anti-angiogenic drug currently used for the treatment of several diseases, including erythema nodosum leprosum, which occurs in patients with lepromatous leprosy. In this research, we use DNA microarray analysis to identify the impact of thalidomide on gene expression responses in human cells after lipopolysaccharide (LPS) stimulation. We employed a two-stage framework. Initially, we identified 1584 altered genes in response to LPS. Modulation of this set of genes was then analyzed in the LPS stimulated cells treated with thalidomide. Results We identified 64 genes with altered expression induced by thalidomide using the rank product method. In addition, the lists of up-regulated and down-regulated genes were investigated by means of bioinformatics functional analysis, which allowed for the identification of biological processes affected by thalidomide. Confirmatory analysis was done in five of the identified genes using real time PCR. Conclusions The results showed some genes that can further our understanding of the biological mechanisms in the action of thalidomide. Of the five genes evaluated with real time PCR, three were down regulated and two were up regulated confirming the initial results of the microarray analysis. PMID:22695124
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.
Gene Expression Analyses of Subchondral Bone in Early Experimental Osteoarthritis by Microarray
Chen, YuXian; Shen, Jun; Lu, HuaDing; Zeng, Chun; Ren, JianHua; Zeng, Hua; Li, ZhiFu; Chen, ShaoMing; Cai, DaoZhang; Zhao, Qing
2012-01-01
Osteoarthritis (OA) is a degenerative joint disease that affects both cartilage and bone. A better understanding of the early molecular changes in subchondral bone may help elucidate the pathogenesis of OA. We used microarray technology to investigate the time course of molecular changes in the subchondral bone in the early stages of experimental osteoarthritis in a rat model. We identified 2,234 differentially expressed (DE) genes at 1 week, 1,944 at 2 weeks and 1,517 at 4 weeks post-surgery. Further analyses of the dysregulated genes indicated that the events underlying subchondral bone remodeling occurred sequentially and in a time-dependent manner at the gene expression level. Some of the identified dysregulated genes that were identified have suspected roles in bone development or remodeling; these genes include Alp, Igf1, Tgf β1, Postn, Mmp3, Tnfsf11, Acp5, Bmp5, Aspn and Ihh. The differences in the expression of these genes were confirmed by real-time PCR, and the results indicated that our microarray data accurately reflected gene expression patterns characteristic of early OA. To validate the results of our microarray analysis at the protein level, immunohistochemistry staining was used to investigate the expression of Mmp3 and Aspn protein in tissue sections. These analyses indicate that Mmp3 protein expression completely matched the results of both the microarray and real-time PCR analyses; however, Aspn protein expression was not observed to differ at any time. In summary, our study demonstrated a simple method of separation of subchondral bone sample from the knee joint of rat, which can effectively avoid bone RNA degradation. These findings also revealed the gene expression profiles of subchondral bone in the rat OA model at multiple time points post-surgery and identified important DE genes with known or suspected roles in bone development or remodeling. These genes may be novel diagnostic markers or therapeutic targets for OA. PMID:22384228
Pap, Domonkos; Sziksz, Erna; Kiss, Zoltán; Rokonay, Réka; Veres-Székely, Apor; Lippai, Rita; Takács, István Márton; Kis, Éva; Fekete, Andrea; Reusz, György; Szabó, Attila J; Vannay, Adam
2017-01-01
Congenital obstructive nephropathy (CON) is the main cause of pediatric chronic kidney diseases leading to renal fibrosis. High morbidity and limited treatment opportunities of CON urge the better understanding of the underlying molecular mechanisms. To identify the differentially expressed genes, microarray analysis was performed on the kidney samples of neonatal rats underwent unilateral ureteral obstruction (UUO). Microarray results were then validated by real-time RT-PCR and bioinformatics analysis was carried out to identify the relevant genes, functional groups and pathways involved in the pathomechanism of CON. Renal expression of matrix metalloproteinase (MMP)-12 and interleukin (IL)-24 were evaluated by real-time RT-PCR, flow cytometry and immunohistochemical analysis. Effect of the main profibrotic factors on the expression of MMP-12 and IL-24 was investigated on HK-2 and HEK-293 cell lines. Finally, the effect of IL-24 treatment on the expression of pro-inflammatory cytokines and MMPs were tested in vitro. Microarray analysis revealed 880 transcripts showing >2.0-fold change following UUO, enriched mainly in immune response related processes. The most up-regulated genes were MMPs and members of IL-20 cytokine subfamily, including MMP-3, MMP-7, MMP-12, IL-19 and IL-24. We found that while TGF-β treatment inhibits the expression of MMP-12 and IL-24, H2O2 or PDGF-B treatment induce the epithelial expression of MMP-12. We demonstrated that IL-24 treatment decreases the expression of IL-6 and MMP-3 in the renal epithelial cells. This study provides an extensive view of UUO induced changes in the gene expression profile of the developing kidney and describes novel molecules, which may play significant role in the pathomechanism of CON. © 2017 The Author(s)Published by S. Karger AG, Basel.
Ma, Jianping; Wang, Jufang; Liu, Yanfen; Wang, Changyi; Duan, Donghui; Lu, Nanjia; Wang, Kaiyue; Zhang, Lu; Gu, Kaibo; Chen, Sihan; Zhang, Tao; You, Dingyun; Han, Liyuan
2017-02-01
The aim of this study was to compare the expression levels of serum miRNAs in diabetic retinopathy and type 2 diabetes mellitus. Serum miRNA expression profiles from diabetic retinopathy cases (type 2 diabetes mellitus patients with diabetic retinopathy) and type 2 diabetes mellitus controls (type 2 diabetes mellitus patients without diabetic retinopathy) were examined by miRNA-specific microarray analysis. Quantitative real-time polymerase chain reaction was used to validate the significantly differentially expressed serum miRNAs from the microarray analysis of 45 diabetic retinopathy cases and 45 age-, sex-, body mass index- and duration-of-diabetes-matched type 2 diabetes mellitus controls. The relative changes in serum miRNA expression levels were analyzed using the 2-ΔΔCt method. A total of 5 diabetic retinopathy cases and 5 type 2 diabetes mellitus controls were included in the miRNA-specific microarray analysis. The serum levels of miR-3939 and miR-1910-3p differed significantly between the two groups in the screening stage; however, quantitative real-time polymerase chain reaction did not reveal significant differences in miRNA expression for 45 diabetic retinopathy cases and their matched type 2 diabetes mellitus controls. Our findings indicate that miR-3939 and miR-1910-3p may not play important roles in the development of diabetic retinopathy; however, studies with a larger sample size are needed to confirm our findings.
Microarray characterization of gene expression changes in blood during acute ethanol exposure
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
DigOut: viewing differential expression genes as outliers.
Yu, Hui; Tu, Kang; Xie, Lu; Li, Yuan-Yuan
2010-12-01
With regards to well-replicated two-conditional microarray datasets, the selection of differentially expressed (DE) genes is a well-studied computational topic, but for multi-conditional microarray datasets with limited or no replication, the same task is not properly addressed by previous studies. This paper adopts multivariate outlier analysis to analyze replication-lacking multi-conditional microarray datasets, finding that it performs significantly better than the widely used limit fold change (LFC) model in a simulated comparative experiment. Compared with the LFC model, the multivariate outlier analysis also demonstrates improved stability against sample variations in a series of manipulated real expression datasets. The reanalysis of a real non-replicated multi-conditional expression dataset series leads to satisfactory results. In conclusion, a multivariate outlier analysis algorithm, like DigOut, is particularly useful for selecting DE genes from non-replicated multi-conditional gene expression dataset.
The genome-wide expression profile of Curcuma longa-treated cisplatin-stimulated HEK293 cells
Sohn, Sung-Hwa; Ko, Eunjung; Chung, Hwan-Suck; Lee, Eun-Young; Kim, Sung-Hoon; Shin, Minkyu; Hong, Moochang; Bae, Hyunsu
2010-01-01
AIM The rhizome of turmeric, Curcuma longa (CL), is a herbal medicine used in many traditional prescriptions. It has previously been shown that CL treatment showed greater than 47% recovery from cisplatin-induced cell damage in human kidney HEK 293 cells. This study was conducted to evaluate the recovery mechanisms of CL that occur during cisplatin induced nephrotoxicity by examining the genome wide mRNA expression profiles of HEK 293 -cells. METHOD Recovery mechanisms of CL that occur during cisplatin-induced nephrotoxicity were determined by microarray, real-time PCR, immunofluorescent confocal microscopy and Western blot analysis. RESULTS The results of microarray analysis and real-time PCR revealed that NFκB pathway-related genes and apoptosis-related genes were down-regulated in CL-treated HEK 293 cells. In addition, immunofluorescent confocal microscopy and Western blot analysis revealed that NFκB p65 nuclear translocation was inhibited in CL-treated HEK 293 cells. Therefore, the mechanism responsible for the effects of CL on HEK 293 cells is closely associated with regulation of the NFκB pathway. CONCLUSION CL possesses novel therapeutic agents that can be used for the prevention or treatment of cisplatin-induced renal disorders. PMID:20840446
Deficits in serum amyloid A contribute to increased neonatal mortality during murine listeriosis.
Hawkins, J Seth; Wu, Qingqing; Wang, Yanxia; Lu, Christopher Y
2013-12-01
To understand the increased susceptibility of preterm neonates to infection. A murine listeriosis model using immunohistochemistry, microarray technology, and real-time polymerase chain reaction (PCR). We report that recombinant serum amyloid A (SAA) administered prophylactically 18 h before intraperitoneal (i.p.) inoculation with Listeria monocytogenes conferred a dramatic survival benefit compared with administration of only vehicle in neonatal mice. Neonates that received the recombinant SAA protein had significantly fewer Listeria colony counts on plating of infected liver and showed significantly more activated macrophages, but SAA did not affect postnatal growth. Real-time PCR was used to confirm the microarray findings that gene expression levels for the SAA proteins 1 (Saa1) and 2 (Saa2), in addition to that for orosomucoid-2 (Orm2), were strikingly elevated in the adult compared with those in the neonate. Real-time PCR analysis showed that of the acute phase cytokines, tumor necrosis factor (TNF) gene expression increased exponentially with time in the infected adult, whereas neonates did not show similar increases. The increased susceptibility of neonatal mice to listeriosis is in part mediated by a deficiency in the acute phase response, specifically expression of SAA, and that prophylactic SAA protein before neonatal murine listeriosis results in more macrophage activation, lower Listeria counts, and greater survival.
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.
Microarray Analysis of Differential Gene Expression Profile Between Human Fetal and Adult Heart.
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.
Robust gene selection methods using weighting schemes for microarray data analysis.
Kang, Suyeon; Song, Jongwoo
2017-09-02
A common task in microarray data analysis is to identify informative genes that are differentially expressed between two different states. Owing to the high-dimensional nature of microarray data, identification of significant genes has been essential in analyzing the data. However, the performances of many gene selection techniques are highly dependent on the experimental conditions, such as the presence of measurement error or a limited number of sample replicates. We have proposed new filter-based gene selection techniques, by applying a simple modification to significance analysis of microarrays (SAM). To prove the effectiveness of the proposed method, we considered a series of synthetic datasets with different noise levels and sample sizes along with two real datasets. The following findings were made. First, our proposed methods outperform conventional methods for all simulation set-ups. In particular, our methods are much better when the given data are noisy and sample size is small. They showed relatively robust performance regardless of noise level and sample size, whereas the performance of SAM became significantly worse as the noise level became high or sample size decreased. When sufficient sample replicates were available, SAM and our methods showed similar performance. Finally, our proposed methods are competitive with traditional methods in classification tasks for microarrays. The results of simulation study and real data analysis have demonstrated that our proposed methods are effective for detecting significant genes and classification tasks, especially when the given data are noisy or have few sample replicates. By employing weighting schemes, we can obtain robust and reliable results for microarray data analysis.
Yu, Shihui; Kielt, Matthew; Stegner, Andrew L; Kibiryeva, Nataliya; Bittel, Douglas C; Cooley, Linda D
2009-12-01
The American College of Medical Genetics guidelines for microarray analysis for constitutional cytogenetic abnormalities require abnormal or ambiguous results from microarray-based comparative genomic hybridization (aCGH) analysis be confirmed by an alternative method. We employed quantitative real-time polymerase chain reaction (qPCR) technology using SYBR Green I reagents for confirmation of 93 abnormal aCGH results (50 deletions and 43 duplications) and 54 parental samples. A novel qPCR protocol using DNA sequences coding for X-linked lethal diseases in males for designing reference primers was established. Of the 81 sets of test primers used for confirmation of 93 abnormal copy number variants (CNVs) in 80 patients, 71 sets worked after the initial primer design (88%), 9 sets were redesigned once, and 1 set twice because of poor amplification. Fifty-four parental samples were tested using 33 sets of test primers to follow up 34 CNVs in 30 patients. Nineteen CNVs were confirmed as inherited, 13 were negative in both parents, and 2 were inconclusive due to a negative result in a single parent. The qPCR assessment clarified aCGH results in two cases and corrected a fluorescence in situ hybridization result in one case. Our data illustrate that qPCR methodology using SYBR Green I reagents is accurate, highly sensitive, specific, rapid, and cost-effective for verification of chromosomal imbalances detected by aCGH in the clinical setting.
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.
Is this the real time for genomics?
Guarnaccia, Maria; Gentile, Giulia; Alessi, Enrico; Schneider, Claudio; Petralia, Salvatore; Cavallaro, Sebastiano
2014-01-01
In the last decades, molecular biology has moved from gene-by-gene analysis to more complex studies using a genome-wide scale. Thanks to high-throughput genomic technologies, such as microarrays and next-generation sequencing, a huge amount of information has been generated, expanding our knowledge on the genetic basis of various diseases. Although some of this information could be transferred to clinical diagnostics, the technologies available are not suitable for this purpose. In this review, we will discuss the drawbacks associated with the use of traditional DNA microarrays in diagnostics, pointing out emerging platforms that could overcome these obstacles and offer a more reproducible, qualitative and quantitative multigenic analysis. New miniaturized and automated devices, called Lab-on-Chip, begin to integrate PCR and microarray on the same platform, offering integrated sample-to-result systems. The introduction of this kind of innovative devices may facilitate the transition of genome-based tests into clinical routine. Copyright © 2014. Published by Elsevier Inc.
Kameue, Chiyoko; Tsukahara, Takamitsu; Ushida, Kazunari
2006-03-01
Butyrate induces apoptosis of various cancer cell lines in a p53-independent manner and inhibits the proliferation of cancer cells. In a previous report, we reported a significant reduction in tumor incidence in rat colon as a result of dietary sodium gluconate (GNA). The stimulation of apoptosis through enhanced butyrate production in the large intestine was involved in the antitumorigenic effect of GNA. In the present study, a cDNA microarray analysis was performed to investigate the particular mechanism involved in the antitumorigenic effect of GNA. Some up-regulated genes suggested by microarray analysis were further evaluated using real-time PCR. A microarray revealed that GNA regulates the expression of retinoic acid receptor (RAR) and retinoid X receptor (RXR), and several genes known as the target of retinoids in cancer cells. In other words, the antitumorigenic effect of GNA may involve the regulation of the retinoid signaling pathway by butyrate in a retinoid-independent manner.
Ma, Y; Dai, X; Hong, T; Munk, G B; Libera, M
2016-12-19
Despite their many advantages and successes, molecular beacon (MB) hybridization probes have not been extensively used in microarray formats because of the complicating probe-substrate interactions that increase the background intensity. We have previously shown that tethering to surface-patterned microgels is an effective means for localizing MB probes to specific surface locations in a microarray format while simultaneously maintaining them in as water-like an environment as possible and minimizing probe-surface interactions. Here we extend this approach to include both real-time detection together with integrated NASBA amplification. We fabricate small (∼250 μm × 250 μm) simplex, duplex, and five-plex assays with microarray spots of controllable size (∼20 μm diameter), position, and shape to detect bacteria and fungi in a bloodstream-infection model. The targets, primers, and microgel-tethered probes can be combined in a single isothermal reaction chamber with no post-amplification labelling. We extract total RNA from clinical blood samples and differentiate between Gram-positive and Gram-negative bloodstream infection in a duplex assay to detect RNA- amplicons. The sensitivity based on our current protocols in a simplex assay to detect specific ribosomal RNA sequences within total RNA extracted from S. aureus and E. coli cultures corresponds to tens of bacteria per ml. We furthermore show that the platform can detect RNA- amplicons from synthetic target DNA with 1 fM sensitivity in sample volumes that contain about 12 000 DNA molecules. These experiments demonstrate an alternative approach that can enable rapid and real-time microarray-based molecular diagnostics.
In-vitro analysis of Quantum Molecular Resonance effects on human mesenchymal stromal cells
Sella, Sabrina; Adami, Valentina; Amati, Eliana; Bernardi, Martina; Chieregato, Katia; Gatto, Pamela; Menarin, Martina; Pozzato, Alessandro; Pozzato, Gianantonio; Astori, Giuseppe
2018-01-01
Electromagnetic fields play an essential role in cellular functions interfering with cellular pathways and tissue physiology. In this context, Quantum Molecular Resonance (QMR) produces waves with a specific form at high-frequencies (4–64 MHz) and low intensity through electric fields. We evaluated the effects of QMR stimulation on bone marrow derived mesenchymal stromal cells (MSC). MSC were treated with QMR for 10 minutes for 4 consecutive days for 2 weeks at different nominal powers. Cell morphology, phenotype, multilineage differentiation, viability and proliferation were investigated. QMR effects were further investigated by cDNA microarray validated by real-time PCR. After 1 and 2 weeks of QMR treatment morphology, phenotype and multilineage differentiation were maintained and no alteration of cellular viability and proliferation were observed between treated MSC samples and controls. cDNA microarray analysis evidenced more transcriptional changes on cells treated at 40 nominal power than 80 ones. The main enrichment lists belonged to development processes, regulation of phosphorylation, regulation of cellular pathways including metabolism, kinase activity and cellular organization. Real-time PCR confirmed significant increased expression of MMP1, PLAT and ARHGAP22 genes while A2M gene showed decreased expression in treated cells compared to controls. Interestingly, differentially regulated MMP1, PLAT and A2M genes are involved in the extracellular matrix (ECM) remodelling through the fibrinolytic system that is also implicated in embryogenesis, wound healing and angiogenesis. In our model QMR-treated MSC maintained unaltered cell phenotype, viability, proliferation and the ability to differentiate into bone, cartilage and adipose tissue. Microarray analysis may suggest an involvement of QMR treatment in angiogenesis and in tissue regeneration probably through ECM remodelling. PMID:29293552
Cell cycle arrest and gene expression profiling of testis in mice exposed to fluoride.
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.
Bruns, Helge; Heil, Jan; Schultze, Daniel; Al Saeedi, Mohammed; Schemmer, Peter
2015-06-01
In patients with end-stage liver disease, liver transplantation is the only available curative treatment. Although the outcome and quality of life in the patients have improved over the past decades, primary dys- or nonfunction (PDF/PNF) can occur. Early detection of PDF and PNF is crucial and could lead to individual therapies. This study was designed to identify early markers of reperfusion injury and PDF in liver biopsies taken during the first hour after reperfusion. Biopsies from donor livers were prospectively taken as a routine during the first hour after reperfusion. Recipient data, transaminases and outcome were routinely monitored. In total, 10 biopsy specimens taken from patients with 90-day mortality and PDF, and patients with long-term survival but without PDF were used for DNA microarrays. Markers that were significantly up- or down-regulated in the microarray were verified using quantitative real-time PCR. Age, indications and labMELD score were similar in both groups. Peak-transaminases during the first week after transplantation were significantly different in the two groups. In total, 20 differentially regulated markers that correlated to PDF were identified using microarray analysis and verified with quantitative real-time PCR. The markers identified in this study could predict PDF at a very early time point and might point to interventions that ameliorate reperfusion injury and thus prevent PDF. Identification of patients and organs at risk might lead to individualized therapies and could ultimately improve outcome.
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.
Severgnini, Marco; Bicciato, Silvio; Mangano, Eleonora; Scarlatti, Francesca; Mezzelani, Alessandra; Mattioli, Michela; Ghidoni, Riccardo; Peano, Clelia; Bonnal, Raoul; Viti, Federica; Milanesi, Luciano; De Bellis, Gianluca; Battaglia, Cristina
2006-06-01
Meta-analysis of microarray data is increasingly important, considering both the availability of multiple platforms using disparate technologies and the accumulation in public repositories of data sets from different laboratories. We addressed the issue of comparing gene expression profiles from two microarray platforms by devising a standardized investigative strategy. We tested this procedure by studying MDA-MB-231 cells, which undergo apoptosis on treatment with resveratrol. Gene expression profiles were obtained using high-density, short-oligonucleotide, single-color microarray platforms: GeneChip (Affymetrix) and CodeLink (Amersham). Interplatform analyses were carried out on 8414 common transcripts represented on both platforms, as identified by LocusLink ID, representing 70.8% and 88.6% of annotated GeneChip and CodeLink features, respectively. We identified 105 differentially expressed genes (DEGs) on CodeLink and 42 DEGs on GeneChip. Among them, only 9 DEGs were commonly identified by both platforms. Multiple analyses (BLAST alignment of probes with target sequences, gene ontology, literature mining, and quantitative real-time PCR) permitted us to investigate the factors contributing to the generation of platform-dependent results in single-color microarray experiments. An effective approach to cross-platform comparison involves microarrays of similar technologies, samples prepared by identical methods, and a standardized battery of bioinformatic and statistical analyses.
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
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.
Chung, Sook Hee; Park, Young Sook; Kim, Ok Soon; Kim, Ja Hyun; Baik, Haing Woon; Hong, Young Ok; Kim, Sang Su; Shin, Jae-Ho; Jun, Jin-Hyun; Jo, Yunju; Ahn, Sang Bong; Jo, Young Kwan; Son, Byoung Kwan; Kim, Seong Hwan
2014-06-01
Inflammatory bowel disease is a chronic inflammatory condition of the gastrointestinal tract. It can be aggravated by stress, like sleep deprivation, and improved by anti-inflammatory agents, like melatonin. We aimed to investigate the effects of sleep deprivation and melatonin on inflammation. We also investigated genes regulated by sleep deprivation and melatonin. In the 2% DSS induced colitis mice model, sleep deprivation was induced using modified multiple platform water bath. Melatonin was injected after induction of colitis and colitis with sleep deprivation. Also mRNA was isolated from the colon of mice and analyzed via microarray and real-time PCR. Sleep deprivation induced reduction of body weight, and it was difficult for half of the mice to survive. Sleep deprivation aggravated, and melatonin attenuated the severity of colitis. In microarrays and real-time PCR of mice colon tissues, mRNA of adiponectin and aquaporin 8 were downregulated by sleep deprivation and upregulated by melatonin. However, mRNA of E2F transcription factor (E2F2) and histocompatibility class II antigen A, beta 1 (H2-Ab1) were upregulated by sleep deprivation and downregulated by melatonin. Melatonin improves and sleep deprivation aggravates inflammation of colitis in mice. Adiponectin, aquaporin 8, E2F2 and H2-Ab1 may be involved in the inflammatory change aggravated by sleep deprivation and attenuated by melatonin.
Lin, Yii-Lih; Huang, Yen-Jun; Teerapanich, Pattamon; Leïchlé, Thierry
2016-01-01
Nanofluidic devices promise high reaction efficiency and fast kinetic responses due to the spatial constriction of transported biomolecules with confined molecular diffusion. However, parallel detection of multiple biomolecules, particularly proteins, in highly confined space remains challenging. This study integrates extended nanofluidics with embedded protein microarray to achieve multiplexed real-time biosensing and kinetics monitoring. Implementation of embedded standard-sized antibody microarray is attained by epoxy-silane surface modification and a room-temperature low-aspect-ratio bonding technique. An effective sample transport is achieved by electrokinetic pumping via electroosmotic flow. Through the nanoslit-based spatial confinement, the antigen-antibody binding reaction is enhanced with ∼100% efficiency and may be directly observed with fluorescence microscopy without the requirement of intermediate washing steps. The image-based data provide numerous spatially distributed reaction kinetic curves and are collectively modeled using a simple one-dimensional convection-reaction model. This study represents an integrated nanofluidic solution for real-time multiplexed immunosensing and kinetics monitoring, starting from device fabrication, protein immobilization, device bonding, sample transport, to data analysis at Péclet number less than 1. PMID:27375819
Odbayar, Tseye-Oidov; Kimura, Toshinori; Tsushida, Tojiro; Ide, Takashi
2009-05-01
The impact of quercetin on the mRNA expression of hepatic enzymes involved in drug metabolism was evaluated with a DNA microarray and real-time PCR. Male Sprague-Dawley rats were fed an experimental diet containing either 0, 2.5, 5, 10, or 20 g/kg of quercetin for 15 days. The DNA microarray analysis of the gene expression profile in pooled RNA samples from rats fed diets containing 0, 5, and 20 g/kg of quercetin revealed genes of some isoenzymes of glutathione transferase (Gst) and aldo-keto reductase (Akr) to be activated by this flavonoid. Real-time PCR conducted with RNA samples from individual rats fed varying amounts of quercetin together with the microarray analysis showed that quercetin caused marked dose-dependent increases in the mRNA expression of Gsta3, Gstp1, and Gstt3. Some moderate increases were also noted in the mRNA expression of isoenzymes belonging to the Gstm class. Quercetin also dose-dependently increased the mRNA expression of Akr1b8 and Akr7a3. However, it did not affect the parameters of the other Gst and Akr isoenzymes. It is apparent that quercetin increases the mRNA expression of Gst and Akr involved in drug metabolism in an isoenzyme-specific manner. Inasmuch as Gst and Akr isoenzymes up-regulated in their gene expression are involved in the prevention and attenuation of cancer development, this consequence may account for the chemopreventive propensity of quercetin.
Tanaka, Yohei; Nakayama, Jun
2018-05-01
Water-filtered broad-spectrum near-infrared irradiation can induce various biological effects, as our previous clinical, histological, and biochemical investigations have shown. However, few studies that examined the changes thus induced in gene expression. The aim was to investigate the changes in gene expression in a 3-dimensional reconstructed epidermal tissue culture exposed to water-filtered broad-spectrum near-infrared irradiation. DNA microarray and quantitative real-time polymerase chain reaction (PCR) analysis was used to assess gene expression levels in a 3-dimensional reconstructed epidermal model composed of normal human epidermal cells exposed to water-filtered broad-spectrum near-infrared irradiation. The water filter allowed 1000-1800 nm wavelengths and excluded 1400-1500 nm wavelengths, and cells were exposed to 5 or 10 rounds of near-infrared irradiation at 10 J/cm 2 . A DNA microarray with over 50 000 different probes showed 18 genes that were upregulated or downregulated by at least twofold after irradiation. Quantitative real-time PCR revealed that, relative to control cells, the gene encoding La ribonucleoprotein domain family member 6 (LARP6), which regulates collagen expression, was significantly and dose-dependently upregulated (P < 0.05) by water-filtered broad-spectrum near-infrared exposure. Gene encoding transcripts of collagen type I were significantly upregulated compared with controls (P < 0.05). This study demonstrates the ability of water-filtered broad-spectrum near-infrared irradiation to stimulate the production of type I collagen. © 2017 The Australasian College of Dermatologists.
Biomarkers of the Hedgehog/Smoothened pathway in healthy volunteers
Kadam, Sunil K; Patel, Bharvin K R; Jones, Emma; Nguyen, Tuan S; Verma, Lalit K; Landschulz, Katherine T; Stepaniants, Sergey; Li, Bin; Brandt, John T; Brail, Leslie H
2012-01-01
The Hedgehog (Hh) pathway is involved in oncogenic transformation and tumor maintenance. The primary objective of this study was to select surrogate tissue to measure messenger ribonucleic acid (mRNA) levels of Hh pathway genes for measurement of pharmacodynamic effect. Expression of Hh pathway specific genes was measured by quantitative real time polymerase chain reaction (qRT-PCR) and global gene expression using Affymetrix U133 microarrays. Correlations were made between the expression of specific genes determined by qRT-PCR and normalized microarray data. Gene ontology analysis using microarray data for a broader set of Hh pathway genes was performed to identify additional Hh pathway-related markers in the surrogate tissue. RNA extracted from blood, hair follicle, and skin obtained from healthy subjects was analyzed by qRT-PCR for 31 genes, whereas 8 samples were analyzed for a 7-gene subset. Twelve sample sets, each with ≤500 ng total RNA derived from hair, skin, and blood, were analyzed using Affymetrix U133 microarrays. Transcripts for several Hh pathway genes were undetectable in blood using qRT-PCR. Skin was the most desirable matrix, followed by hair follicle. Whether processed by robust multiarray average or microarray suite 5 (MAS5), expression patterns of individual samples showed co-clustered signals; both normalization methods were equally effective for unsupervised analysis. The MAS5- normalized probe sets appeared better suited for supervised analysis. This work provides the basis for selection of a surrogate tissue and an expression analysis-based approach to evaluate pathway-related genes as markers of pharmacodynamic effect with novel inhibitors of the Hh pathway. PMID:22611475
Franke-Whittle, Ingrid H.; Walter, Andreas; Ebner, Christian; Insam, Heribert
2014-01-01
A study was conducted to determine whether differences in the levels of volatile fatty acids (VFAs) in anaerobic digester plants could result in variations in the indigenous methanogenic communities. Two digesters (one operated under mesophilic conditions, the other under thermophilic conditions) were monitored, and sampled at points where VFA levels were high, as well as when VFA levels were low. Physical and chemical parameters were measured, and the methanogenic diversity was screened using the phylogenetic microarray ANAEROCHIP. In addition, real-time PCR was used to quantify the presence of the different methanogenic genera in the sludge samples. Array results indicated that the archaeal communities in the different reactors were stable, and that changes in the VFA levels of the anaerobic digesters did not greatly alter the dominating methanogenic organisms. In contrast, the two digesters were found to harbour different dominating methanogenic communities, which appeared to remain stable over time. Real-time PCR results were inline with those of microarray analysis indicating only minimal changes in methanogen numbers during periods of high VFAs, however, revealed a greater diversity in methanogens than found with the array. PMID:25164858
Chemiluminescence microarrays in analytical chemistry: a critical review.
Seidel, Michael; Niessner, Reinhard
2014-09-01
Multi-analyte immunoassays on microarrays and on multiplex DNA microarrays have been described for quantitative analysis of small organic molecules (e.g., antibiotics, drugs of abuse, small molecule toxins), proteins (e.g., antibodies or protein toxins), and microorganisms, viruses, and eukaryotic cells. In analytical chemistry, multi-analyte detection by use of analytical microarrays has become an innovative research topic because of the possibility of generating several sets of quantitative data for different analyte classes in a short time. Chemiluminescence (CL) microarrays are powerful tools for rapid multiplex analysis of complex matrices. A wide range of applications for CL microarrays is described in the literature dealing with analytical microarrays. The motivation for this review is to summarize the current state of CL-based analytical microarrays. Combining analysis of different compound classes on CL microarrays reduces analysis time, cost of reagents, and use of laboratory space. Applications are discussed, with examples from food safety, water safety, environmental monitoring, diagnostics, forensics, toxicology, and biosecurity. The potential and limitations of research on multiplex analysis by use of CL microarrays are discussed in this review.
Complementary techniques: validation of gene expression data by quantitative real time PCR.
Provenzano, Maurizio; Mocellin, Simone
2007-01-01
Microarray technology can be considered the most powerful tool for screening gene expression profiles of biological samples. After data mining, results need to be validated with highly reliable biotechniques allowing for precise quantitation of transcriptional abundance of identified genes. Quantitative real time PCR (qrt-PCR) technology has recently reached a level of sensitivity, accuracy and practical ease that support its use as a routine bioinstrumentation for gene level measurement. Currently, qrt-PCR is considered by most experts the most appropriate method to confirm or confute microarray-generated data. The knowledge of the biochemical principles underlying qrt-PCR as well as some related technical issues must be beard in mind when using this biotechnology.
An efficient pseudomedian filter for tiling microrrays.
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
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
In vitro study of the effects of ELF electric fields on gene expression in human epidermal cells.
Collard, Jean-Francois; Mertens, Benjamin; Hinsenkamp, Maurice
2011-01-01
An acceleration of differentiation, at the expense of proliferation, is observed after exposure of various biological models to low frequency and low amplitude electric and electromagnetic fields. Following these results showing significant modifications, we try to identify the biological mechanism involved at the cell level through microarray screening. For this study, we use epidermis cultures harvested from human abdominoplasty. Two platinum electrodes are used to apply the electric signal. The gene expressions of 38,500 well-characterized human genes are analyzed using Affymetrix(®) microarray U133 Plus 2.0 chips. The protocol is repeated on three different patients. After three periods of exposure, a total of 24 chips have been processed. After the application of ELF electric fields, the microarray analysis confirms a modification of the gene expression of epidermis cells. Particularly, four up-regulated genes (DKK1, TXNRD1, ATF3, and MME) and one down-regulated gene (MACF1) are involved in the regulation of proliferation and differentiation. Expression of these five genes was also confirmed by real-time rtPCR in all samples used for microarray analysis. These results corroborate an acceleration of cell differentiation at the expense of cell proliferation. © 2010 Wiley-Liss, Inc.
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.
Park, Seungman; Kang, Youjin; Kim, Dong Geun; Kim, Eui-Chong; Park, Sung Sup; Seong, Moon-Woo
2013-08-01
The detection of high-risk (HR) HPV in cervical cancer screening is important for early diagnosis of cervical cancer or pre-cancerous lesions. We evaluated the analytical and clinical performances of 3 HR HPV assays in Gynecology patients. A total of 991 specimens were included in this study: 787 specimens for use with a Hybrid Capture 2 (HC2) and 204 specimens for a HPV DNA microarray (DNA Chip). All specimens were tested using an Abbott RealTime High Risk HPV assay (Real-time HR), PGMY PCR, and sequence analysis. Clinical sensitivities for severe abnormal cytology (severe than high-grade squamous intraepithelial lesion) were 81.8% for Real-time HR, 77.3% for HC2, and 66.7% for DNA Chip, and clinical sensitivities for severe abnormal histology (cervical intraepithelial neoplasia grade 2+) were 91.7% for HC2, 87.5% for Real-time HR, and 73.3% for DNA Chip. As compared to results of the sequence analysis, HC2, Real-time HR, and DNA Chip showed concordance rates of 94.3% (115/122), 90.0% (117/130), and 61.5% (16/26), respectively. The HC2 assay and Real-time HR assay showed comparable results to each other in both clinical and analytical performances, while the DNA Chip assay showed poor clinical and analytical performances. The Real-time HR assay can be a good alternative option for HR HPV testing with advantages of allowing full automation and simultaneous genotyping of HR types 16 and 18. Copyright © 2013 Elsevier Inc. All rights reserved.
Gene expression profiling in respond to TBT exposure in small abalone Haliotis diversicolor.
Jia, Xiwei; Zou, Zhihua; Wang, Guodong; Wang, Shuhong; Wang, Yilei; Zhang, Ziping
2011-10-01
In this study, we investigated the gene expression profiling of small abalone, Haliotis diversicolor by tributyltin (TBT) exposure using a cDNA microarray containing 2473 unique transcripts. Totally, 107 up-regulated genes and 41 down-regulated genes were found. For further investigation of candidate genes from microarray data and EST analysis, quantitative real-time PCR was performed at 6 h, 24 h, 48 h, 96 h and 192 h TBT exposure. 26 genes were found to be significantly differentially expressed in different time course, 3 of them were unknown. Some gene homologues like cellulose, endo-beta-1,4-glucanase, ferritin subunit 1 and thiolester containing protein II CG7052-PB might be the good biomarker candidate for TBT monitor. The identification of stress response genes and their expression profiles will permit detailed investigation of the defense responses of small abalone genes. Published by Elsevier Ltd.
NASA Astrophysics Data System (ADS)
Hsiu, Feng-Ming; Chen, Shean-Jen; Tsai, Chien-Hung; Tsou, Chia-Yuan; Su, Y.-D.; Lin, G.-Y.; Huang, K.-T.; Chyou, Jin-Jung; Ku, Wei-Chih; Chiu, S.-K.; Tzeng, C.-M.
2002-09-01
Surface plasmon resonance (SPR) imaging system is presented as a novel technique based on modified Mach-Zehnder phase-shifting interferometry (PSI) for biomolecular interaction analysis (BIA), which measures the spatial phase variation of a resonantly reflected light in biomolecular interaction. In this technique, the micro-array SPR biosensors with over a thousand probe NDA spots can be detected simultaneously. Owing to the feasible and swift measurements, the micro-array SPR biosensors can be extensively applied to the nonspecific adsorption of protein, the membrane/protein interactions, and DNA hybridization. The detection sensitivity of the SPR PSI imaging system is improved to about 1 pg/mm2 for each spot over the conventional SPR imaging systems. The SPR PSI imaging system and its SPR sensors have been successfully used to observe slightly index change in consequence of argon gas flow through the nitrogen in real time, with high sensitivity, and at high-throughout screening rates.
Ethical issues raised by genetic testing with oligonucleotide microarrays.
Grody, Wayne W
2003-02-01
Because genes and alterations within them determine the identity, characteristics, and inheritance of every individual, the application of genetic science to humans has long been surrounded by apprehension, controversy, and real or perceived potential for abuse. Crude eugenics practices of the past now find a theoretical rebirth and transformation through the use of modern molecular genetic technologies for mutation detection, predictive and prenatal diagnosis, and, ultimately, gene replacement. The advent of oligonucleotide microarray analysis, in which hundreds or thousands of genes and mutations can be tested in parallel, offers tremendous promise for more accurate, sensitive, and efficient genetic testing. At the same time, however, this powerful technology dramatically increases the number and scope of ethical concerns accompanying each individual test request. This article considers the evolution and implications of these concerns, from the initial ordering of a microarray test by the physician to such issues as informed consent, privacy, confidentiality, clinical utility, discrimination, stigmatization, ethnic and population impact, and reimbursement.
Tighe, S.; Holbrook, J.; Nadella, V.; Carmical, R.; Sol-Church, K.; Yueng, A.T.; Chittur, S.
2011-01-01
The Nucleic Acid Research Group (NARG) has previously conducted studies evaluating the impact of RNA integrity and priming strategies on cDNA synthesis and real-time RT-qPCR. The results of last year's field study as it relates to degraded RNA will be presented. In continuation of the RNA integrity theme, this year's study was designed to evaluate the impact of RNA integrity on the analysis of miRNA expression using real-time RT-qPCR. Target section was based on data obtained by the Microarray Research Group (MARG) and other published data from next gen sequencing. These 9 miRNAs represent three groups of miRNA that are expressed at low, medium or high levels in the First Choice human brain reference RNA sample. Two popular RT priming strategies tested in this study include the Megaplex miRNA TaqMan assay (ABI) and the RT2 miRNA qPCR assay (Qiagen/SA Biosciences). The basis for the ABI assay design is a target-specific stem-loop structure and reverse-transcription primer, while the Qiagen design combines poly(A) tailing and a universal reverse transcription in one cDNA synthesis reaction. For this study, the human brain reference RNA was subject to controlled degradation using RNase A to RIN (RNA Integrity Number) values of 7 (good), 4 (moderately degraded), and 2 (severely degraded).These templates were then used to assess both RT methods. In addition to this real-time RT-qPCR data, the same RNA templates were further analyzed using universal poly(A) tailing and hybridization to Affymetrix miRNA GeneChips. This talk will provide insights into RT priming strategies for miRNA and contrast the qPCR results obtained using different technologies.
Influence of 2 cryopreservation methods to induce CCL-13 from dental pulp cells.
Ahn, Su-Jin; Jang, Ji-Hyun; Seo, Ji-Sung; Cho, Kyu Min; Jung, Su-Hee; Lee, Hyeon-Woo; Kim, Eun-Cheol; Park, Sang Hyuk
2013-12-01
Cryopreservation preserves periodontal ligament cells but has a lower success rate with dental pulp cells (DPCs) because it causes inflammation. There are 2 well-known cryopreservation methods that reduce inflammation, slow freezing and rapid freezing, but the effects of the 2 methods on inflammation are not well-established. The purpose of this study was to compare the effects of the 2 different cryopreservation methods on CCL-13 induction from DPCs by using microarrays, real-time polymerase chain reaction (PCR), Western blotting, enzyme-linked immunosorbent assay, and confocal laser scanning microscopy (CLSM). In this study, the concentration of cryoprotectant was fixed, and the methods compared differed with respect to freezing speed. Initially we screened the DPCs of cryopreserved teeth with expression microarrays, and CCL-13 was identified as a differentially expressed gene involved in generalized inflammation. We then compared the expression of CCL-13 after exposing teeth to the 2 cryopreservation methods by using real-time PCR, Western blot, enzyme-linked immunosorbent assay, and CLSM. Expression of CCL-13 was up-regulated significantly only in the rapid freezing group, except in measurements made by real-time PCR. CLSM analysis also confirmed this up-regulation visually. Rapid freezing increased the expression of CCL-13 in DPCs compared with slow freezing. Understanding the inflammatory effect of cryopreservation should help to establish an optimal cryoprofile to minimize inflammation of DPCs and reduce the need for endodontic treatment. Copyright © 2013 American Association of Endodontists. Published by Elsevier Inc. All rights reserved.
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.
Microarray analysis of gene expression profiles in ripening pineapple fruits.
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
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
Nowrousian, Minou; Ringelberg, Carol; Dunlap, Jay C; Loros, Jennifer J; Kück, Ulrich
2005-04-01
The filamentous fungus Sordaria macrospora forms complex three-dimensional fruiting bodies that protect the developing ascospores and ensure their proper discharge. Several regulatory genes essential for fruiting body development were previously isolated by complementation of the sterile mutants pro1, pro11 and pro22. To establish the genetic relationships between these genes and to identify downstream targets, we have conducted cross-species microarray hybridizations using cDNA arrays derived from the closely related fungus Neurospora crassa and RNA probes prepared from wild-type S. macrospora and the three developmental mutants. Of the 1,420 genes which gave a signal with the probes from all the strains used, 172 (12%) were regulated differently in at least one of the three mutants compared to the wild type, and 17 (1.2%) were regulated differently in all three mutant strains. Microarray data were verified by Northern analysis or quantitative real time PCR. Among the genes that are up- or down-regulated in the mutant strains are genes encoding the pheromone precursors, enzymes involved in melanin biosynthesis and a lectin-like protein. Analysis of gene expression in double mutants revealed a complex network of interaction between the pro gene products.
Reddy, Sreekanth P; Britto, Ramona; Vinnakota, Katyayni; Aparna, Hebbar; Sreepathi, Hari Kishore; Thota, Balaram; Kumari, Arpana; Shilpa, B M; Vrinda, M; Umesh, Srikantha; Samuel, Cini; Shetty, Mitesh; Tandon, Ashwani; Pandey, Paritosh; Hegde, Sridevi; Hegde, A S; Balasubramaniam, Anandh; Chandramouli, B A; Santosh, Vani; Kondaiah, Paturu; Somasundaram, Kumaravel; Rao, M R Satyanarayana
2008-05-15
Current methods of classification of astrocytoma based on histopathologic methods are often subjective and less accurate. Although patients with glioblastoma have grave prognosis, significant variability in patient outcome is observed. Therefore, the aim of this study was to identify glioblastoma diagnostic and prognostic markers through microarray analysis. We carried out transcriptome analysis of 25 diffusely infiltrating astrocytoma samples [WHO grade II--diffuse astrocytoma, grade III--anaplastic astrocytoma, and grade IV--glioblastoma (GBM)] using cDNA microarrays containing 18,981 genes. Several of the markers identified were also validated by real-time reverse transcription quantitative PCR and immunohistochemical analysis on an independent set of tumor samples (n = 100). Survival analysis was carried out for two markers on another independent set of retrospective cases (n = 51). We identified several differentially regulated grade-specific genes. Independent validation by real-time reverse transcription quantitative PCR analysis found growth arrest and DNA-damage-inducible alpha (GADD45alpha) and follistatin-like 1 (FSTL1) to be up-regulated in most GBMs (both primary and secondary), whereas superoxide dismutase 2 and adipocyte enhancer binding protein 1 were up-regulated in the majority of primary GBM. Further, identification of the grade-specific expression of GADD45alpha and FSTL1 by immunohistochemical staining reinforced our findings. Analysis of retrospective GBM cases with known survival data revealed that cytoplasmic overexpression of GADD45alpha conferred better survival while the coexpression of FSTL1 with p53 was associated with poor survival. Our study reveals that GADD45alpha and FSTLI are GBM-specific whereas superoxide dismutase 2 and adipocyte enhancer binding protein 1 are primary GBM-specific diagnostic markers. Whereas GADD45alpha overexpression confers a favorable prognosis, FSTL1 overexpression is a hallmark of poor prognosis in GBM patients.
Burgos, Carmen Mesas; Uggla, Andreas Ringman; Fagerström-Billai, Fredrik; Eklöf, Ann-Christine; Frenckner, Björn; Nord, Magnus
2010-07-01
Pulmonary hypoplasia and persistent pulmonary hypertension are the main causes of mortality and morbidity in newborns with congenital diaphragmatic hernia (CDH). Nitrofen is well known to induce CDH and lung hypoplasia in a rat model, but the mechanism remains unknown. To increase the understanding of the underlying pathogenesis of CDH, we performed a global gene expression analysis using microarray technology. Pregnant rats were given 100 mg nitrofen on gestational day 9.5 to create CDH. On day 21, fetuses after nitrofen administration and control fetuses were removed; and lungs were harvested. Global gene expression analysis was performed using Affymetrix Platform and the RAE 230 set arrays. For validation of microarray data, we performed real-time polymerase chain reaction and Western blot analysis. Significantly decreased genes after nitrofen administration included several growth factors and growth factors receptors involved in lung development, transcription factors, water and ion channels, and genes involved in angiogenesis and extracellular matrix. These results could be confirmed with real-time polymerase chain reaction and protein expression studies. The pathogenesis of lung hypoplasia and CDH in the nitrofen model includes alteration at a molecular level of several pathways involved in lung development. The complexity of the nitrofen mechanism of action reminds of human CDH; and the picture is consistent with lung hypoplasia and vascular disease, both important contributors to the high mortality and morbidity in CDH. Increased understanding of the molecular mechanisms that control lung growth may be the key to develop novel therapeutic techniques to stimulate pre- and postnatal lung growth. Copyright 2010 Elsevier Inc. All rights reserved.
A robust two-way semi-linear model for normalization of cDNA microarray data
Wang, Deli; Huang, Jian; Xie, Hehuang; Manzella, Liliana; Soares, Marcelo Bento
2005-01-01
Background Normalization is a basic step in microarray data analysis. A proper normalization procedure ensures that the intensity ratios provide meaningful measures of relative expression values. Methods We propose a robust semiparametric method in a two-way semi-linear model (TW-SLM) for normalization of cDNA microarray data. This method does not make the usual assumptions underlying some of the existing methods. For example, it does not assume that: (i) the percentage of differentially expressed genes is small; or (ii) the numbers of up- and down-regulated genes are about the same, as required in the LOWESS normalization method. We conduct simulation studies to evaluate the proposed method and use a real data set from a specially designed microarray experiment to compare the performance of the proposed method with that of the LOWESS normalization approach. Results The simulation results show that the proposed method performs better than the LOWESS normalization method in terms of mean square errors for estimated gene effects. The results of analysis of the real data set also show that the proposed method yields more consistent results between the direct and the indirect comparisons and also can detect more differentially expressed genes than the LOWESS method. Conclusions Our simulation studies and the real data example indicate that the proposed robust TW-SLM method works at least as well as the LOWESS method and works better when the underlying assumptions for the LOWESS method are not satisfied. Therefore, it is a powerful alternative to the existing normalization methods. PMID:15663789
Manuel, Gerald; Lupták, Andrej; Corn, Robert M.
2017-01-01
A two-step templated, ribosomal biosynthesis/printing method for the fabrication of protein microarrays for surface plasmon resonance imaging (SPRI) measurements is demonstrated. In the first step, a sixteen component microarray of proteins is created in microwells by cell free on chip protein synthesis; each microwell contains both an in vitro transcription and translation (IVTT) solution and 350 femtomoles of a specific DNA template sequence that together are used to create approximately 40 picomoles of a specific hexahistidine-tagged protein. In the second step, the protein microwell array is used to contact print one or more protein microarrays onto nitrilotriacetic acid (NTA)-functionalized gold thin film SPRI chips for real-time SPRI surface bioaffinity adsorption measurements. Even though each microwell array element only contains approximately 40 picomoles of protein, the concentration is sufficiently high for the efficient bioaffinity adsorption and capture of the approximately 100 femtomoles of hexahistidine-tagged protein required to create each SPRI microarray element. As a first example, the protein biosynthesis process is verified with fluorescence imaging measurements of a microwell array containing His-tagged green fluorescent protein (GFP), yellow fluorescent protein (YFP) and mCherry (RFP), and then the fidelity of SPRI chips printed from this protein microwell array is ascertained by measuring the real-time adsorption of various antibodies specific to these three structurally related proteins. This greatly simplified two-step synthesis/printing fabrication methodology eliminates most of the handling, purification and processing steps normally required in the synthesis of multiple protein probes, and enables the rapid fabrication of SPRI protein microarrays from DNA templates for the study of protein-protein bioaffinity interactions. PMID:28706572
Generalized Correlation Coefficient for Non-Parametric Analysis of Microarray Time-Course Data.
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.
Mullin, Anne E; Soukatcheva, Galina; Verchere, C Bruce; Chantler, Janet K
2006-05-01
A technique to isolate high-quality intact RNA from murine pancreas is described. This technique involves in situ ductal perfusion of the pancreas with an RNase inhibitor prior to removal of the organ for RNA extraction. In this way, the pancreatic RNases are inhibited in situ allowing good yields of intact RNA, suitable for studies on pancreatic gene transcription by real-time PCR or microarray analysis, to be obtained in a reliable way.
Okomo-Adhiambo, Margaret; Beattie, Craig; Rink, Anette
2006-01-01
Toxoplasma gondii induces the expression of proinflammatory cytokines, reorganizes organelles, scavenges nutrients, and inhibits apoptosis in infected host cells. We used a cDNA microarray of 420 annotated porcine expressed sequence tags to analyze the molecular basis of these changes at eight time points over a 72-hour period in porcine kidney epithelial (PK13) cells infected with T. gondii. A total of 401 genes with Cy3 and Cy5 spot intensities of ≥500 were selected for analysis, of which 263 (65.6%) were induced ≥2-fold (expression ratio, ≥2.0; P ≤ 0.05 [t test]) over at least one time point and 48 (12%) were significantly down-regulated. At least 12 functional categories of genes were modulated (up- or down-regulated) by T. gondii. The majority of induced genes were clustered as transcription, signal transduction, host immune response, nutrient metabolism, and apoptosis related. The expression of selected genes altered by T. gondii was validated by quantitative real-time reverse transcription-PCR. These results suggest that significant changes in gene expression occur in response to T. gondii infection in PK13 cells, facilitating further analysis of host-pathogen interactions in toxoplasmosis in a secondary host. PMID:16790800
Hou, Mei-Ling; Chang, Li-Wen; Lin, Chi-Hung; Lin, Lie-Chwen; Tsai, Tung-Hu
2014-09-11
Rhein is a pharmacological active component found in Rheum palmatum L. that is the major herb of the San-Huang-Xie-Xin-Tang (SHXXT), a medicinal herbal product used as a remedy for constipation. Here we have investigated the comparative pharmacokinetics of rhein in normal and constipated rats. Microarray analysis was used to explore whether drug-metabolizing genes will be altered after SHXXT treatment. The comparative pharmacokinetics of rhein in normal and loperamide-induced constipated rats was studied by liquid chromatography with electrospray ionization tandem mass spectrometry (LC-MS/MS). Gene expression profiling in drug-metabolizing genes after SHXXT treatment was investigated by microarray analysis and real-time polymerase chain reaction (RT-PCR). A validated LC-MS/MS method was applied to investigate the comparative pharmacokinetics of rhein in normal and loperamide-induced constipated rats. The pharmacokinetic results demonstrate that the loperamide-induced constipation reduced the absorption of rhein. Cmax significantly reduced by 2.5-fold, the AUC decreased by 27.8%; however, the elimination half-life (t1/2) was prolonged by 1.6-fold. Tmax and mean residence time (MRT) were significantly prolonged by 2.8-fold, and 1.7-fold, respectively. The volume of distribution (Vss) increased by 2.2-fold. The data of microarray analysis on gene expression indicate that five drug-metabolizing genes, including Cyp7a1, Cyp2c6, Ces2e, Atp1b1, and Slc7a2 were significantly altered by the SHXXT (0.5 g/kg) treatment. The loperamide-induced constipation reduced the absorption of rhein. Since among the 25,338 genes analyzed, there were five genes significantly altered by SHXXT treatment. Thus, information on minor drug-metabolizing genes altered by SHXXT treatment indicates that SHXXT is relatively safe for clinical application. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.
Kumar, Mukesh; Rath, Nitish Kumar; Rath, Santanu Kumar
2016-04-01
Microarray-based gene expression profiling has emerged as an efficient technique for classification, prognosis, diagnosis, and treatment of cancer. Frequent changes in the behavior of this disease generates an enormous volume of data. Microarray data satisfies both the veracity and velocity properties of big data, as it keeps changing with time. Therefore, the analysis of microarray datasets in a small amount of time is essential. They often contain a large amount of expression, but only a fraction of it comprises genes that are significantly expressed. The precise identification of genes of interest that are responsible for causing cancer are imperative in microarray data analysis. Most existing schemes employ a two-phase process such as feature selection/extraction followed by classification. In this paper, various statistical methods (tests) based on MapReduce are proposed for selecting relevant features. After feature selection, a MapReduce-based K-nearest neighbor (mrKNN) classifier is also employed to classify microarray data. These algorithms are successfully implemented in a Hadoop framework. A comparative analysis is done on these MapReduce-based models using microarray datasets of various dimensions. From the obtained results, it is observed that these models consume much less execution time than conventional models in processing big data. Copyright © 2016 Elsevier Inc. All rights reserved.
Cytokine-related genes and oxidation-related genes detected in preeclamptic placentas.
Lee, Gui Se Ra; Joe, Yoon Seong; Kim, Sa Jin; Shin, Jong Chul
2010-10-01
To investigate cytokine- and oxidation-related genes for preeclampsia using DNA microarray analysis. Placentas were collected from 13 normal pregnancies and 13 patients with preeclampsia. Gene expression was studied using DNA microarray. Among significantly expressed genes, we focused on genes associated with cytokines and oxidation, and the results were confirmed using quantitative real time-polymerase chain reaction (QRT-PCR). 415 genes out of 30,940 genes were altered by > or =2-fold in the microarray analysis. 121 up-regulated genes and 294 down-regulated genes were found to be in preeclamptic placenta. Six cytokine-related genes and 5 oxidation-related genes were found from among the 121 up-regulated genes. The cytokine-related genes studied included oncostatin M (OSM), fms-related tyrosine kinase (FLT1) and vascular endothelial growth factor A (VEGFA), and the oxidation-related genes studied included spermine oxidase (SMOX), l cytochrome P450, family 26, subfamily A, polypeptide 1 (CYP26A1), acetate dehydrogenase A (LDHA). These six genes were also significantly higher in placentas from patients with preeclampsia than in those from women with normal pregnancies. The placental tissue of patients with preeclampsia showed significantly higher mRNA expression of these six genes than the normal group, using QRT-PCR. DNA microarray analysis is one of the great methods for simultaneously detecting the functionally associated genes of preeclampsia. The cytokine-related genes such as OSM, FLT1 and VEGFA, and the oxidation-related genes such as LDHA, CYP26A1 and SMOX might prove to be the starting point in the elucidation of the pathogenesis of preeclampsia.
2012-01-01
Background The use of growth-promoters in beef cattle, despite the EU ban, remains a frequent practice. The use of transcriptomic markers has already proposed to identify indirect evidence of anabolic hormone treatment. So far, such approach has been tested in experimentally treated animals. Here, for the first time commercial samples were analyzed. Results Quantitative determination of Dexamethasone (DEX) residues in the urine collected at the slaughterhouse was performed by Liquid Chromatography-Mass Spectrometry (LC-MS). DNA-microarray technology was used to obtain transcriptomic profiles of skeletal muscle in commercial samples and negative controls. LC-MS confirmed the presence of low level of DEX residues in the urine of the commercial samples suspect for histological classification. Principal Component Analysis (PCA) on microarray data identified two clusters of samples. One cluster included negative controls and a subset of commercial samples, while a second cluster included part of the specimens collected at the slaughterhouse together with positives for corticosteroid treatment based on thymus histology and LC-MS. Functional analysis of the differentially expressed genes (3961) between the two groups provided further evidence that animals clustering with positive samples might have been treated with corticosteroids. These suspect samples could be reliably classified with a specific classification tool (Prediction Analysis of Microarray) using just two genes. Conclusions Despite broad variation observed in gene expression profiles, the present study showed that DNA-microarrays can be used to find transcriptomic signatures of putative anabolic treatments and that gene expression markers could represent a useful screening tool. PMID:23110699
Transfection microarray and the applications.
Miyake, Masato; Yoshikawa, Tomohiro; Fujita, Satoshi; Miyake, Jun
2009-05-01
Microarray transfection has been extensively studied for high-throughput functional analysis of mammalian cells. However, control of efficiency and reproducibility are the critical issues for practical use. By using solid-phase transfection accelerators and nano-scaffold, we provide a highly efficient and reproducible microarray-transfection device, "transfection microarray". The device would be applied to the limited number of available primary cells and stem cells not only for large-scale functional analysis but also reporter-based time-lapse cellular event analysis.
A cluster merging method for time series microarray with production values.
Chira, Camelia; Sedano, Javier; Camara, Monica; Prieto, Carlos; Villar, Jose R; Corchado, Emilio
2014-09-01
A challenging task in time-course microarray data analysis is to cluster genes meaningfully combining the information provided by multiple replicates covering the same key time points. This paper proposes a novel cluster merging method to accomplish this goal obtaining groups with highly correlated genes. The main idea behind the proposed method is to generate a clustering starting from groups created based on individual temporal series (representing different biological replicates measured in the same time points) and merging them by taking into account the frequency by which two genes are assembled together in each clustering. The gene groups at the level of individual time series are generated using several shape-based clustering methods. This study is focused on a real-world time series microarray task with the aim to find co-expressed genes related to the production and growth of a certain bacteria. The shape-based clustering methods used at the level of individual time series rely on identifying similar gene expression patterns over time which, in some models, are further matched to the pattern of production/growth. The proposed cluster merging method is able to produce meaningful gene groups which can be naturally ranked by the level of agreement on the clustering among individual time series. The list of clusters and genes is further sorted based on the information correlation coefficient and new problem-specific relevant measures. Computational experiments and results of the cluster merging method are analyzed from a biological perspective and further compared with the clustering generated based on the mean value of time series and the same shape-based algorithm.
Iwanabe, Yujiro; Masaki, Chihiro; Tamura, Akiko; Tsuka, Shintaro; Mukaibo, Taro; Kondo, Yusuke; Hosokawa, Ryuji
2016-10-01
Low-intensity pulsed ultrasound (LIPUS) is widely used in medical fields because it shortens the time required for biologic wound healing in fracture treatment. Also, in dental fields, LIPUS should be effectively employed for implant treatment. However, most of the relevant reports have been published on its effects on bone formation around implants, and the effects of LIPUS on soft tissue healing remain unclear. In the present study, we examined the effects of LIPUS on soft tissue healing using gingival epithelial cells. Gingival epithelial cells were cultured on a dish, followed by LIPUS exposure at a frequency of 3MHz for 15min. The cells were counted with a hemocytometer, and a scratch assay was conducted by measuring the closing area of the scratch wound using a microscope. Following LIPUS exposure, total RNA was collected for microarray analysis. In addition, real-time PCR was performed to examine the mRNA expression level of integrin α6β4. Furthermore, total protein was collected to examine the protein expression level of integrin α6β4 by western blotting. The cell count and scratch assay demonstrated that LIPUS exposure promoted cell proliferation and scratch-wound closure. Microarray analysis demonstrated the increased expression levels of adhesion-related genes, including integrin. Real-time PCR analysis demonstrated that LIPUS exposure significantly up-regulated the mRNA expression level of integrin α6β4. Western blotting showed intense staining of integrin α6β4. LIPUS exposure promotes wound closure in the scratch assay and up-regulates the expression level of integrin α6β4 as compared with the control. Copyright © 2016 Japan Prosthodontic Society. Published by Elsevier Ltd. All rights reserved.
Analysis of Altered Micro RNA Expression Profiles in Focal Cortical Dysplasia IIB.
Li, Lin; Liu, Chang-Qing; Li, Tian-Fu; Guan, Yu-Guang; Zhou, Jian; Qi, Xue-Ling; Yang, Yu-Tao; Deng, Jia-Hui; Xu, Zhi-Qing David; Luan, Guo-Ming
2016-04-01
Focal cortical dysplasia type IIB is a commonly encountered subtype of developmental malformation of the cerebral cortex and is often associated with pharmacoresistant epilepsy. In this study, to investigate the molecular etiology of focal cortical dysplasia type IIB, the authors performed micro ribonucleic acid (RNA) microarray on surgical specimens from 5 children (2 female and 3 male, mean age was 73.4 months, range 50-112 months) diagnosed of focal cortical dysplasia type IIB and matched normal tissue adjacent to the lesion. In all, 24 micro RNAs were differentially expressed in focal cortical dysplasia type IIB, and the microarray results were validated using quantitative real-time polymerase chain reaction (PCR). Then the putative target genes of the differentially expressed micro RNAs were identified by bioinformatics analysis. Moreover, biological significance of the target genes was evaluated by investigating the pathways in which the genes were enriched, and the Hippo signaling pathway was proposed to be highly related with the pathogenesis of focal cortical dysplasia type IIB. © The Author(s) 2015.
Support vector machine and principal component analysis for microarray data classification
NASA Astrophysics Data System (ADS)
Astuti, Widi; Adiwijaya
2018-03-01
Cancer is a leading cause of death worldwide although a significant proportion of it can be cured if it is detected early. In recent decades, technology called microarray takes an important role in the diagnosis of cancer. By using data mining technique, microarray data classification can be performed to improve the accuracy of cancer diagnosis compared to traditional techniques. The characteristic of microarray data is small sample but it has huge dimension. Since that, there is a challenge for researcher to provide solutions for microarray data classification with high performance in both accuracy and running time. This research proposed the usage of Principal Component Analysis (PCA) as a dimension reduction method along with Support Vector Method (SVM) optimized by kernel functions as a classifier for microarray data classification. The proposed scheme was applied on seven data sets using 5-fold cross validation and then evaluation and analysis conducted on term of both accuracy and running time. The result showed that the scheme can obtained 100% accuracy for Ovarian and Lung Cancer data when Linear and Cubic kernel functions are used. In term of running time, PCA greatly reduced the running time for every data sets.
Weighted analysis of paired microarray experiments.
Kristiansson, Erik; Sjögren, Anders; Rudemo, Mats; Nerman, Olle
2005-01-01
In microarray experiments quality often varies, for example between samples and between arrays. The need for quality control is therefore strong. A statistical model and a corresponding analysis method is suggested for experiments with pairing, including designs with individuals observed before and after treatment and many experiments with two-colour spotted arrays. The model is of mixed type with some parameters estimated by an empirical Bayes method. Differences in quality are modelled by individual variances and correlations between repetitions. The method is applied to three real and several simulated datasets. Two of the real datasets are of Affymetrix type with patients profiled before and after treatment, and the third dataset is of two-colour spotted cDNA type. In all cases, the patients or arrays had different estimated variances, leading to distinctly unequal weights in the analysis. We suggest also plots which illustrate the variances and correlations that affect the weights computed by our analysis method. For simulated data the improvement relative to previously published methods without weighting is shown to be substantial.
Cheng, Xiao-Rui; Zhou, Wen-Xia; Zhang, Yong-Xiang
2006-05-01
Alzheimer' s disease (AD) is the most common form of dementia in the elderly. AD is an invariably fatal neurodegenerative disorder with no effective treatment. Senescence-accelerated mouse prone 8 (SAMP8) is a model for studying age-related cognitive impairments and also is a good model to study brain aging and one of mouse model of AD. The technique of cDNA microarray can monitor the expression levels of thousands of genes simultaneously and can be used to study AD with the character of multi-mechanism, multi-targets and multi-pathway. In order to disclose the mechanism of AD and find the drug targets of AD, cDNA microarray containing 3136 cDNAs amplified from the suppression subtracted cDNA library of hippocampus of SAMP8 and SAMR1 was prepared with 16 blocks and 14 x 14 pins, the housekeeping gene beta-actin and G3PDH as inner conference. The background of this microarray was low and unanimous, and dots divided evenly. The conditions of hybridization and washing were optimized during the hybridization of probe and target molecule. After the data of hybridization analysis, the differential expressed cDNAs were sequenced and analyzed by the bioinformatics, and some of genes were quantified by the real time RT-PCR and the reliability of this cDNA microarray were validated. This cDNA microarray may be the good means to select the differential expressed genes and disclose the molecular mechanism of SAMP8's brain aging and AD.
Inamura, Kentaro; Togashi, Yuki; Ninomiya, Hironori; Shimoji, Takashi; Noda, Tetsuo; Ishikawa, Yuichi
2008-01-01
Previously, using microarray and real-time RT-PCR analysis, we established that HOXB2 is an adverse prognostic indicator for Stage I lung adenocarcinomas. HOXB2 is one of the homeobox master development-controlling genes regulating morphogenesis and cell differentiation. The molecular functions of HOXB2 were analyzed with a small interfering RNA (siRNA) approach in HOP-62 human non-small cell lung cancer (NSCLC) cells featuring high HOXB2 expression. Matrigel invasion assays and microarray gene expression analysis were compared between the HOXB2-siRNA cells and the control cells. The Matrigel invasion assays showed attenuation of HOXB2 expression by siRNA to result in a significant decrease of invasiveness compared to the control cells (p = 0.0013, paired t-test). On microarray gene expression analysis, up-regulation of many metastasis-related genes and others correlating with HOXB2 expression was observed in the control case. With attenuation of HOXB2 expression, downregulation was noted for laminins alpha 4 and 5, involved in enriched signaling, and for Mac-2BP (Mac-2 binding protein) and integrin beta 4 amongst the genes having an enriched glycoprotein ontology. HOXB2 promotes invasion of lung cancer cells through the regulation of metastasis-related genes.
Ban, Susumu; Kondo, Tomoko; Ishizuka, Mayumi; Sasaki, Seiko; Konishi, Kanae; Washino, Noriaki; Fujita, Syoichi; Kishi, Reiko
2007-05-01
The field of molecular biology currently faces the need for a comprehensive method of evaluating individual differences derived from genetic variation in the form of single nucleotide polymorphisms (SNPs). SNPs in human genes are generally considered to be very useful in determining inherited genetic disorders, susceptibility to certain diseases, and cancer predisposition. Quick and accurate discrimination of SNPs is the key characteristic of technology used in DNA diagnostics. For this study, we first developed a DNA microarray and then evaluated its efficacy by determining the detection ability and validity of this method. Using DNA obtained from 380 pregnant Japanese women, we examined 13 polymorphisms of 9 genes, which are associated with the metabolism of environmental chemical compounds found in high frequency among Japanese populations. The ability to detect CYP1A1 I462V, CYP1B1 L432V, GSTP1 I105V and AhR R554K gene polymorphisms was above 98%, and agreement rates when compared with real time PCR analysis methods (kappa values) showed high validity: 0.98 (0.96), 0.97 (0.93), 0.90 (0.81), 0.90 (0.91), respectively. While this DNA microarray analysis should prove important as a method for initial screening, it is still necessary that we find better methods for improving the detection of other gene polymorphisms not part of this study.
Go, Yoon Young; Park, Moo Kyun; Kwon, Jee Young; Seo, Young Rok; Chae, Sung-Won; Song, Jae-Jun
2015-12-01
The primary aim of this study is to evaluate the gene expression profile of Asian sand dust (ASD)-treated human middle ear epithelial cell (HMEEC) using microarray analysis. The HMEEC was treated with ASD (400 µg/mL) and total RNA was extracted for microarray analysis. Molecular pathways among differentially expressed genes were further analyzed. For selected genes, the changes in gene expression were confirmed by real-time polymerase chain reaction. A total of 1,274 genes were differentially expressed by ASD. Among them, 1,138 genes were 2 folds up-regulated, whereas 136 genes were 2 folds down-regulated. Up-regulated genes were mainly involved in cellular processes, including apoptosis, cell differentiation, and cell proliferation. Down-regulated genes affected cellular processes, including apoptosis, cell cycle, cell differentiation, and cell proliferation. The 10 genes including ADM, CCL5, EDN1, EGR1, FOS, GHRL, JUN, SOCS3, TNF, and TNFSF10 were identified as main modulators in up-regulated genes. A total of 11 genes including CSF3, DKK1, FOSL1, FST, TERT, MMP13, PTHLH, SPRY2, TGFBR2, THBS1, and TIMP1 acted as main components of pathway associated with 2-fold down regulated genes. We identified the differentially expressed genes in ASD-treated HMEEC. Our work indicates that air pollutant like ASD, may play an important role in the pathogenesis of otitis media.
Bikel, Shirley; Jacobo-Albavera, Leonor; Sánchez-Muñoz, Fausto; Cornejo-Granados, Fernanda; Canizales-Quinteros, Samuel; Soberón, Xavier; Sotelo-Mundo, Rogerio R; Del Río-Navarro, Blanca E; Mendoza-Vargas, Alfredo; Sánchez, Filiberto; Ochoa-Leyva, Adrian
2017-01-01
In spite of the emergence of RNA sequencing (RNA-seq), microarrays remain in widespread use for gene expression analysis in the clinic. There are over 767,000 RNA microarrays from human samples in public repositories, which are an invaluable resource for biomedical research and personalized medicine. The absolute gene expression analysis allows the transcriptome profiling of all expressed genes under a specific biological condition without the need of a reference sample. However, the background fluorescence represents a challenge to determine the absolute gene expression in microarrays. Given that the Y chromosome is absent in female subjects, we used it as a new approach for absolute gene expression analysis in which the fluorescence of the Y chromosome genes of female subjects was used as the background fluorescence for all the probes in the microarray. This fluorescence was used to establish an absolute gene expression threshold, allowing the differentiation between expressed and non-expressed genes in microarrays. We extracted the RNA from 16 children leukocyte samples (nine males and seven females, ages 6-10 years). An Affymetrix Gene Chip Human Gene 1.0 ST Array was carried out for each sample and the fluorescence of 124 genes of the Y chromosome was used to calculate the absolute gene expression threshold. After that, several expressed and non-expressed genes according to our absolute gene expression threshold were compared against the expression obtained using real-time quantitative polymerase chain reaction (RT-qPCR). From the 124 genes of the Y chromosome, three genes (DDX3Y, TXLNG2P and EIF1AY) that displayed significant differences between sexes were used to calculate the absolute gene expression threshold. Using this threshold, we selected 13 expressed and non-expressed genes and confirmed their expression level by RT-qPCR. Then, we selected the top 5% most expressed genes and found that several KEGG pathways were significantly enriched. Interestingly, these pathways were related to the typical functions of leukocytes cells, such as antigen processing and presentation and natural killer cell mediated cytotoxicity. We also applied this method to obtain the absolute gene expression threshold in already published microarray data of liver cells, where the top 5% expressed genes showed an enrichment of typical KEGG pathways for liver cells. Our results suggest that the three selected genes of the Y chromosome can be used to calculate an absolute gene expression threshold, allowing a transcriptome profiling of microarray data without the need of an additional reference experiment. Our approach based on the establishment of a threshold for absolute gene expression analysis will allow a new way to analyze thousands of microarrays from public databases. This allows the study of different human diseases without the need of having additional samples for relative expression experiments.
Sato, Motoya; Ohguro, Hiroshi; Ohguro, Ikuyo; Mamiya, Kazuhisa; Takano, Yoshiko; Yamazaki, Hitoshi; Metoki, Tomomi; Miyagawa, Yasuhiro; Ishikawa, Fotoshi; Nakazawa, Mitsuru
2003-07-11
In our recent study, we found that the Ca(2+) antagonist, nilvadipine caused significant preservation of photoreceptor cells in The Royal College of Surgeons (RCS) rats [Invest. Ophthalmol. Vis. Sci. 43 (2002) 919]. Here, to elucidate the mechanisms of nilvadipine-induced effects we analyzed altered gene expression of 1101 genes commonly expressed in rodent by DNA microarray analysis in the retinas of nilvadipine-treated and untreated RCS rats and SD rat. In the total number of genes, the expression of 30 genes was altered upon administration of nilvadipine to RCS rats, including several genes related to the apoptotic pathway and other mechanisms. Remarkably, neurotrophic factors, FGF-2 and Arc, known to suppress the apoptosis in the central nervous system, were up-regulated. These changes were also confirmed by real-time quantitative (Taqman) RT-PCR and Western blot analysis. Therefore, our present data suggested that administration of nilvadipine to RCS rats increases the expression of endogenous FGF-2 and Arc in retina, and potentially has a protective effect against retinal degeneration.
Fully Automated Complementary DNA Microarray Segmentation using a Novel Fuzzy-based Algorithm.
Saberkari, Hamidreza; Bahrami, Sheyda; Shamsi, Mousa; Amoshahy, Mohammad Javad; Ghavifekr, Habib Badri; Sedaaghi, Mohammad Hossein
2015-01-01
DNA microarray is a powerful approach to study simultaneously, the expression of 1000 of genes in a single experiment. The average value of the fluorescent intensity could be calculated in a microarray experiment. The calculated intensity values are very close in amount to the levels of expression of a particular gene. However, determining the appropriate position of every spot in microarray images is a main challenge, which leads to the accurate classification of normal and abnormal (cancer) cells. In this paper, first a preprocessing approach is performed to eliminate the noise and artifacts available in microarray cells using the nonlinear anisotropic diffusion filtering method. Then, the coordinate center of each spot is positioned utilizing the mathematical morphology operations. Finally, the position of each spot is exactly determined through applying a novel hybrid model based on the principle component analysis and the spatial fuzzy c-means clustering (SFCM) algorithm. Using a Gaussian kernel in SFCM algorithm will lead to improving the quality in complementary DNA microarray segmentation. The performance of the proposed algorithm has been evaluated on the real microarray images, which is available in Stanford Microarray Databases. Results illustrate that the accuracy of microarray cells segmentation in the proposed algorithm reaches to 100% and 98% for noiseless/noisy cells, respectively.
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.
Time Series Expression Analyses Using RNA-seq: A Statistical Approach
Oh, Sunghee; Song, Seongho; Grabowski, Gregory; Zhao, Hongyu; Noonan, James P.
2013-01-01
RNA-seq is becoming the de facto standard approach for transcriptome analysis with ever-reducing cost. It has considerable advantages over conventional technologies (microarrays) because it allows for direct identification and quantification of transcripts. Many time series RNA-seq datasets have been collected to study the dynamic regulations of transcripts. However, statistically rigorous and computationally efficient methods are needed to explore the time-dependent changes of gene expression in biological systems. These methods should explicitly account for the dependencies of expression patterns across time points. Here, we discuss several methods that can be applied to model timecourse RNA-seq data, including statistical evolutionary trajectory index (SETI), autoregressive time-lagged regression (AR(1)), and hidden Markov model (HMM) approaches. We use three real datasets and simulation studies to demonstrate the utility of these dynamic methods in temporal analysis. PMID:23586021
Time series expression analyses using RNA-seq: a statistical approach.
Oh, Sunghee; Song, Seongho; Grabowski, Gregory; Zhao, Hongyu; Noonan, James P
2013-01-01
RNA-seq is becoming the de facto standard approach for transcriptome analysis with ever-reducing cost. It has considerable advantages over conventional technologies (microarrays) because it allows for direct identification and quantification of transcripts. Many time series RNA-seq datasets have been collected to study the dynamic regulations of transcripts. However, statistically rigorous and computationally efficient methods are needed to explore the time-dependent changes of gene expression in biological systems. These methods should explicitly account for the dependencies of expression patterns across time points. Here, we discuss several methods that can be applied to model timecourse RNA-seq data, including statistical evolutionary trajectory index (SETI), autoregressive time-lagged regression (AR(1)), and hidden Markov model (HMM) approaches. We use three real datasets and simulation studies to demonstrate the utility of these dynamic methods in temporal analysis.
Casel, Pierrot; Moreews, François; Lagarrigue, Sandrine; Klopp, Christophe
2009-07-16
Microarray is a powerful technology enabling to monitor tens of thousands of genes in a single experiment. Most microarrays are now using oligo-sets. The design of the oligo-nucleotides is time consuming and error prone. Genome wide microarray oligo-sets are designed using as large a set of transcripts as possible in order to monitor as many genes as possible. Depending on the genome sequencing state and on the assembly state the knowledge of the existing transcripts can be very different. This knowledge evolves with the different genome builds and gene builds. Once the design is done the microarrays are often used for several years. The biologists working in EADGENE expressed the need of up-to-dated annotation files for the oligo-sets they share including information about the orthologous genes of model species, the Gene Ontology, the corresponding pathways and the chromosomal location. The results of SigReannot on a chicken micro-array used in the EADGENE project compared to the initial annotations show that 23% of the oligo-nucleotide gene annotations were not confirmed, 2% were modified and 1% were added. The interest of this up-to-date annotation procedure is demonstrated through the analysis of real data previously published. SigReannot uses the oligo-nucleotide design procedure criteria to validate the probe-gene link and the Ensembl transcripts as reference for annotation. It therefore produces a high quality annotation based on reference gene sets.
Characterization of circulating microRNA expression in patients with a ventricular septal defect.
Li, Dong; Ji, Long; Liu, Lianbo; Liu, Yizhi; Hou, Haifeng; Yu, Kunkun; Sun, Qiang; Zhao, Zhongtang
2014-01-01
Ventricular septal defect (VSD), one of the most common types of congenital heart disease (CHD), results from a combination of environmental and genetic factors. Recent studies demonstrated that microRNAs (miRNAs) are involved in development of CHD. This study was to characterize the expression of miRNAs that might be involved in the development or reflect the consequences of VSD. MiRNA microarray analysis and reverse transcription-polymerase chain reaction (RT-PCR) were employed to determine the miRNA expression profile from 3 patients with VSD and 3 VSD-free controls. 3 target gene databases were employed to predict the target genes of differentially expressed miRNAs. miRNAs that were generally consensus across the three databases were selected and then independently validated using real time PCR in plasma samples from 20 VSD patients and 15 VSD-free controls. Target genes of validated 8 miRNAs were predicted using bioinformatic methods. 36 differentially expressed miRNAs were found in the patients with VSD and the VSD-free controls. Compared with VSD-free controls, expression of 15 miRNAs were up-regulated and 21 miRNAs were downregulated in the VSD group. 15 miRNAs were selected based on database analysis results and expression levels of 8 miRNAs were validated. The results of the real time PCR were consistent with those of the microarray analysis. Gene ontology analysis indicated that the top target genes were mainly related to cardiac right ventricle morphogenesis. NOTCH1, HAND1, ZFPM2, and GATA3 were predicted as targets of hsa-let-7e-5p, hsa-miR-222-3p and hsa-miR-433. We report for the first time the circulating miRNA profile for patients with VSD and showed that 7 miRNAs were downregulated and 1 upregulated when matched to VSD-free controls. Analysis revealed target genes involved in cardiac development were probably regulated by these miRNAs.
Miyamoto, Yutaka; Kanzaki, Hiroyuki; Wada, Satoshi; Tsuruoka, Sari; Itohiya, Kanako; Kumagai, Kenichi; Hamada, Yoshiki; Nakamura, Yoshiki
2017-12-01
Mandibular condylar cartilage (MCC) exhibits dual roles both articular cartilage and growth center. Of many growth factors, TGF-β has been implicated in the growth of articular cartilage including MCC. Recently, Asporin, decoy to TGF-β, was discovered and it blocks TGF-β signaling. Asporin is expressed in a variety of tissues including osteoarthritic articular cartilage, though there was no report of Asporin expression in MCC. In the present study, we investigated the temporal and spatial expression of Asporin in MCC. Gene expression profile of MCC and epiphyseal cartilage in tibia of 5 weeks old ICR mice were firstly compared with microarray analysis using the laser capture microdissected samples. Variance of gene expression was further confirmed by real-time RT-PCR and immunohistochemical staining at 1,3,10, and 20 weeks old. TGF-β and its signaling molecule, phosphorylated Smad-2/3 (p-Smad2/3), were also examined by immunohistochemical staining. Microarray analysis revealed that Asporin was highly expressed in MCC. Real-time RT-PCR analysis confirmed that the fibrous layer of MCC exhibited stable higher Asporin expression at any time points as compared to epiphyseal cartilage. This was also observed in immunohistochemical staining. Deeper layer in MCC augmented Asporin expression with age. Whereas, TGF-β was stably highly observed in the layer. The fibrous layer of MCC exhibited weak staining of p-Smad2/3, though the proliferating layer of MCC was strongly stained as compared to epiphyseal cartilage of tibia at early time point. Consistent with the increase of Asporin expression in the deeper layer of MCC, the intensity of p-Smad-2/3 staining was decreased with age. In conclusion, we discovered that Asporin was stably expressed at the fibrous layer of MCC, which makes it possible to manage both articular cartilage and growth center at the same time.
Direct multiplexed measurement of gene expression with color-coded probe pairs.
Geiss, Gary K; Bumgarner, Roger E; Birditt, Brian; Dahl, Timothy; Dowidar, Naeem; Dunaway, Dwayne L; Fell, H Perry; Ferree, Sean; George, Renee D; Grogan, Tammy; James, Jeffrey J; Maysuria, Malini; Mitton, Jeffrey D; Oliveri, Paola; Osborn, Jennifer L; Peng, Tao; Ratcliffe, Amber L; Webster, Philippa J; Davidson, Eric H; Hood, Leroy; Dimitrov, Krassen
2008-03-01
We describe a technology, the NanoString nCounter gene expression system, which captures and counts individual mRNA transcripts. Advantages over existing platforms include direct measurement of mRNA expression levels without enzymatic reactions or bias, sensitivity coupled with high multiplex capability, and digital readout. Experiments performed on 509 human genes yielded a replicate correlation coefficient of 0.999, a detection limit between 0.1 fM and 0.5 fM, and a linear dynamic range of over 500-fold. Comparison of the NanoString nCounter gene expression system with microarrays and TaqMan PCR demonstrated that the nCounter system is more sensitive than microarrays and similar in sensitivity to real-time PCR. Finally, a comparison of transcript levels for 21 genes across seven samples measured by the nCounter system and SYBR Green real-time PCR demonstrated similar patterns of gene expression at all transcript levels.
Screening circular RNA related to chemotherapeutic resistance in breast cancer.
Gao, Danfeng; Zhang, Xiufen; Liu, Beibei; Meng, Dong; Fang, Kai; Guo, Zijian; Li, Lihua
2017-09-01
We aimed to identify circular RNAs (circRNAs) associated with breast cancer chemoresistance. CircRNA microarray expression profiles were obtained from Adriamycin (ADM) resistant MCF-7 breast cancer cells (MCF-7/ADM) and parental MCF-7 cells and were validated using quantitative real-time reverse transcription PCR. The expression data were analyzed bioinformatically. We detected 3093 circRNAs and identified 18 circRNAs that are differentially expressed between MCF-7/ADM and MCF-7 cells; after validating by quantitative real-time reverse transcription PCR, we predicted the possible miRNAs and potential target genes of the seven upregulated circRNAs using TargetScan and miRanda. The bioinformatics analysis revealed several target genes related to cancer-related signaling pathways. Additionally, we discovered a regulatory role of the circ_0006528-miR-7-5p-Raf1 axis in ADM-resistant breast cancer. These results revealed that circRNAs may play a role in breast cancer chemoresistance and that hsa_circ_0006528 might be a promising candidate for further functional analysis.
Suh, Yeunsu; Davis, Michael E.; Lee, Kichoon
2013-01-01
Understanding the tissue-specific pattern of gene expression is critical in elucidating the molecular mechanisms of tissue development, gene function, and transcriptional regulations of biological processes. Although tissue-specific gene expression information is available in several databases, follow-up strategies to integrate and use these data are limited. The objective of the current study was to identify and evaluate novel tissue-specific genes in human and mouse tissues by performing comparative microarray database analysis and semi-quantitative PCR analysis. We developed a powerful approach to predict tissue-specific genes by analyzing existing microarray data from the NCBI′s Gene Expression Omnibus (GEO) public repository. We investigated and confirmed tissue-specific gene expression in the human and mouse kidney, liver, lung, heart, muscle, and adipose tissue. Applying our novel comparative microarray approach, we confirmed 10 kidney, 11 liver, 11 lung, 11 heart, 8 muscle, and 8 adipose specific genes. The accuracy of this approach was further verified by employing semi-quantitative PCR reaction and by searching for gene function information in existing publications. Three novel tissue-specific genes were discovered by this approach including AMDHD1 (amidohydrolase domain containing 1) in the liver, PRUNE2 (prune homolog 2) in the heart, and ACVR1C (activin A receptor, type IC) in adipose tissue. We further confirmed the tissue-specific expression of these 3 novel genes by real-time PCR. Among them, ACVR1C is adipose tissue-specific and adipocyte-specific in adipose tissue, and can be used as an adipocyte developmental marker. From GEO profiles, we predicted the processes in which AMDHD1 and PRUNE2 may participate. Our approach provides a novel way to identify new sets of tissue-specific genes and to predict functions in which they may be involved. PMID:23741331
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.
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.
Lengger, Sandra; Otto, Johannes; Elsässer, Dennis; Schneider, Oliver; Tiehm, Andreas; Fleischer, Jens; Niessner, Reinhard; Seidel, Michael
2014-05-01
Pathogenic viruses are emerging contaminants in water which should be analyzed for water safety to preserve public health. A strategy was developed to quantify RNA and DNA viruses in parallel on chemiluminescence flow-through oligonucleotide microarrays. In order to show the proof of principle, bacteriophage MS2, ΦX174, and the human pathogenic adenovirus type 2 (hAdV2) were analyzed in spiked tap water samples on the analysis platform MCR 3. The chemiluminescence microarray imaging unit was equipped with a Peltier heater for a controlled heating of the flow cell. The efficiency and selectivity of DNA hybridization could be increased resulting in higher signal intensities and lower cross-reactivities of polymerase chain reaction (PCR) products from other viruses. The total analysis time for DNA/RNA extraction, cDNA synthesis for RNA viruses, polymerase chain reaction, single-strand separation, and oligonucleotide microarray analysis was performed in 4-4.5 h. The parallel quantification was possible in a concentration range of 9.6 × 10(5)-1.4 × 10(10) genomic units (GU)/mL for bacteriophage MS2, 1.4 × 10(5)-3.7 × 10(8) GU/mL for bacteriophage ΦX174, and 6.5 × 10(3)-1.2 × 10(5) for hAdV2, respectively, by using a measuring temperature of 40 °C. Detection limits could be calculated to 6.6 × 10(5) GU/mL for MS2, 5.3 × 10(3) GU/mL for ΦX174, and 1.5 × 10(2) GU/mL for hAdV2, respectively. Real samples of surface water and treated wastewater were tested. Generally, found concentrations of hAdV2, bacteriophage MS2, and ΦX174 were at the detection limit. Nevertheless, bacteriophages could be identified with similar results by means of quantitative PCR and oligonucleotide microarray analysis on the MCR 3.
Validation of MIMGO: a method to identify differentially expressed GO terms in a microarray dataset
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
Transcriptomic profile of host response in mouse brain after exposure to plant toxin abrin.
Bhaskar, A S Bala; Gupta, Nimesh; Rao, P V Lakshmana
2012-09-04
Abrin toxin is a plant glycoprotein, which is similar in structure and properties to ricin and is obtained from the seeds of Abrus precatorius (jequirity bean). Abrin is highly toxic, with an estimated human fatal dose of 0.1-1 μg/kg, and has caused death after accidental and intentional poisoning. Abrin is a potent biological toxin warfare agent. There are no chemical antidotes available against the toxin. Neurological symptoms like delirium, hallucinations, reduced consciousness and generalized seizures were reported in human poisoning cases. Death of a patient with symptoms of acute demyelinating encephalopathy with gastrointestinal bleeding due to ingestion of abrin seeds was reported in India. The aim of this study was to examine both dose and time-dependent transcriptional responses induced by abrin in the adult mouse brain. Mice (n=6) were exposed to 1 and 2 LD50 (2.83 and 5.66 μg/kg respectively) dose of abrin by intraperitoneal route and observed over 3 days. A subset of animals (n=3) were sacrificed at 1 and 2 day intervals for microarray and histopathology analysis. None of the 2 LD50 exposed animals survived till 3 days. The histopathological analysis showed the severe damage in brain and the infiltration of inflammatory cells in a dose and time dependent manner. The abrin exposure resulted in the induction of rapid immune and inflammatory response in brain. Clinical biochemistry parameters like lactate dehydrogenase, aspartate aminotransferase, urea and creatinine showed significant increase at 2-day 2 LD50 exposure. The whole genome microarray data revealed the significant regulation of various pathways like MAPK pathway, cytokine-cytokine receptor interaction, calcium signaling pathway, Jak-STAT signaling pathway and natural killer cell mediated toxicity. The comparison of differential gene expression at both the doses showed dose dependent effects of abrin toxicity. The real-time qRT-PCR analysis of selected genes supported the microarray data. This is the first report on host-gene response using whole genome microarray in an animal model after abrin exposure. The data generated provides leads for developing suitable medical counter measures against abrin poisoning. Copyright © 2012 Elsevier Ireland Ltd. All rights reserved.
2013-01-01
Background As high-throughput genomic technologies become accurate and affordable, an increasing number of data sets have been accumulated in the public domain and genomic information integration and meta-analysis have become routine in biomedical research. In this paper, we focus on microarray meta-analysis, where multiple microarray studies with relevant biological hypotheses are combined in order to improve candidate marker detection. Many methods have been developed and applied in the literature, but their performance and properties have only been minimally investigated. There is currently no clear conclusion or guideline as to the proper choice of a meta-analysis method given an application; the decision essentially requires both statistical and biological considerations. Results We performed 12 microarray meta-analysis methods for combining multiple simulated expression profiles, and such methods can be categorized for different hypothesis setting purposes: (1) HS A : DE genes with non-zero effect sizes in all studies, (2) HS B : DE genes with non-zero effect sizes in one or more studies and (3) HS r : DE gene with non-zero effect in "majority" of studies. We then performed a comprehensive comparative analysis through six large-scale real applications using four quantitative statistical evaluation criteria: detection capability, biological association, stability and robustness. We elucidated hypothesis settings behind the methods and further apply multi-dimensional scaling (MDS) and an entropy measure to characterize the meta-analysis methods and data structure, respectively. Conclusions The aggregated results from the simulation study categorized the 12 methods into three hypothesis settings (HS A , HS B , and HS r ). Evaluation in real data and results from MDS and entropy analyses provided an insightful and practical guideline to the choice of the most suitable method in a given application. All source files for simulation and real data are available on the author’s publication website. PMID:24359104
Chang, Lun-Ching; Lin, Hui-Min; Sibille, Etienne; Tseng, George C
2013-12-21
As high-throughput genomic technologies become accurate and affordable, an increasing number of data sets have been accumulated in the public domain and genomic information integration and meta-analysis have become routine in biomedical research. In this paper, we focus on microarray meta-analysis, where multiple microarray studies with relevant biological hypotheses are combined in order to improve candidate marker detection. Many methods have been developed and applied in the literature, but their performance and properties have only been minimally investigated. There is currently no clear conclusion or guideline as to the proper choice of a meta-analysis method given an application; the decision essentially requires both statistical and biological considerations. We performed 12 microarray meta-analysis methods for combining multiple simulated expression profiles, and such methods can be categorized for different hypothesis setting purposes: (1) HS(A): DE genes with non-zero effect sizes in all studies, (2) HS(B): DE genes with non-zero effect sizes in one or more studies and (3) HS(r): DE gene with non-zero effect in "majority" of studies. We then performed a comprehensive comparative analysis through six large-scale real applications using four quantitative statistical evaluation criteria: detection capability, biological association, stability and robustness. We elucidated hypothesis settings behind the methods and further apply multi-dimensional scaling (MDS) and an entropy measure to characterize the meta-analysis methods and data structure, respectively. The aggregated results from the simulation study categorized the 12 methods into three hypothesis settings (HS(A), HS(B), and HS(r)). Evaluation in real data and results from MDS and entropy analyses provided an insightful and practical guideline to the choice of the most suitable method in a given application. All source files for simulation and real data are available on the author's publication website.
Evaluation of artificial time series microarray data for dynamic gene regulatory network inference.
Xenitidis, P; Seimenis, I; Kakolyris, S; Adamopoulos, A
2017-08-07
High-throughput technology like microarrays is widely used in the inference of gene regulatory networks (GRNs). We focused on time series data since we are interested in the dynamics of GRNs and the identification of dynamic networks. We evaluated the amount of information that exists in artificial time series microarray data and the ability of an inference process to produce accurate models based on them. We used dynamic artificial gene regulatory networks in order to create artificial microarray data. Key features that characterize microarray data such as the time separation of directly triggered genes, the percentage of directly triggered genes and the triggering function type were altered in order to reveal the limits that are imposed by the nature of microarray data on the inference process. We examined the effect of various factors on the inference performance such as the network size, the presence of noise in microarray data, and the network sparseness. We used a system theory approach and examined the relationship between the pole placement of the inferred system and the inference performance. We examined the relationship between the inference performance in the time domain and the true system parameter identification. Simulation results indicated that time separation and the percentage of directly triggered genes are crucial factors. Also, network sparseness, the triggering function type and noise in input data affect the inference performance. When two factors were simultaneously varied, it was found that variation of one parameter significantly affects the dynamic response of the other. Crucial factors were also examined using a real GRN and acquired results confirmed simulation findings with artificial data. Different initial conditions were also used as an alternative triggering approach. Relevant results confirmed that the number of datasets constitutes the most significant parameter with regard to the inference performance. Copyright © 2017 Elsevier Ltd. All rights reserved.
Ku, Yu-Fu; Huang, Long-Sun; Yen, Yi-Kuang
2018-02-28
Here, we provide a method and apparatus for real-time compensation of the thermal effect of single free-standing piezoresistive microcantilever-based biosensors. The sensor chip contained an on-chip fixed piezoresistor that served as a temperature sensor, and a multilayer microcantilever with an embedded piezoresistor served as a biomolecular sensor. This method employed the calibrated relationship between the resistance and the temperature of piezoresistors to eliminate the thermal effect on the sensor, including the temperature coefficient of resistance (TCR) and bimorph effect. From experimental results, the method was verified to reduce the signal of thermal effect from 25.6 μV/°C to 0.3 μV/°C, which was approximately two orders of magnitude less than that before the processing of the thermal elimination method. Furthermore, the proposed approach and system successfully demonstrated its effective real-time thermal self-elimination on biomolecular detection without any thermostat device to control the environmental temperature. This method realizes the miniaturization of an overall measurement system of the sensor, which can be used to develop portable medical devices and microarray analysis platforms.
Genome-scale cluster analysis of replicated microarrays using shrinkage correlation coefficient.
Yao, Jianchao; Chang, Chunqi; Salmi, Mari L; Hung, Yeung Sam; Loraine, Ann; Roux, Stanley J
2008-06-18
Currently, clustering with some form of correlation coefficient as the gene similarity metric has become a popular method for profiling genomic data. The Pearson correlation coefficient and the standard deviation (SD)-weighted correlation coefficient are the two most widely-used correlations as the similarity metrics in clustering microarray data. However, these two correlations are not optimal for analyzing replicated microarray data generated by most laboratories. An effective correlation coefficient is needed to provide statistically sufficient analysis of replicated microarray data. In this study, we describe a novel correlation coefficient, shrinkage correlation coefficient (SCC), that fully exploits the similarity between the replicated microarray experimental samples. The methodology considers both the number of replicates and the variance within each experimental group in clustering expression data, and provides a robust statistical estimation of the error of replicated microarray data. The value of SCC is revealed by its comparison with two other correlation coefficients that are currently the most widely-used (Pearson correlation coefficient and SD-weighted correlation coefficient) using statistical measures on both synthetic expression data as well as real gene expression data from Saccharomyces cerevisiae. Two leading clustering methods, hierarchical and k-means clustering were applied for the comparison. The comparison indicated that using SCC achieves better clustering performance. Applying SCC-based hierarchical clustering to the replicated microarray data obtained from germinating spores of the fern Ceratopteris richardii, we discovered two clusters of genes with shared expression patterns during spore germination. Functional analysis suggested that some of the genetic mechanisms that control germination in such diverse plant lineages as mosses and angiosperms are also conserved among ferns. This study shows that SCC is an alternative to the Pearson correlation coefficient and the SD-weighted correlation coefficient, and is particularly useful for clustering replicated microarray data. This computational approach should be generally useful for proteomic data or other high-throughput analysis methodology.
Levine, Peter M; Gong, Ping; Levicky, Rastislav; Shepard, Kenneth L
2009-03-15
Optical biosensing based on fluorescence detection has arguably become the standard technique for quantifying extents of hybridization between surface-immobilized probes and fluorophore-labeled analyte targets in DNA microarrays. However, electrochemical detection techniques are emerging which could eliminate the need for physically bulky optical instrumentation, enabling the design of portable devices for point-of-care applications. Unlike fluorescence detection, which can function well using a passive substrate (one without integrated electronics), multiplexed electrochemical detection requires an electronically active substrate to analyze each array site and benefits from the addition of integrated electronic instrumentation to further reduce platform size and eliminate the electromagnetic interference that can result from bringing non-amplified signals off chip. We report on an active electrochemical biosensor array, constructed with a standard complementary metal-oxide-semiconductor (CMOS) technology, to perform quantitative DNA hybridization detection on chip using targets conjugated with ferrocene redox labels. A 4 x 4 array of gold working electrodes and integrated potentiostat electronics, consisting of control amplifiers and current-input analog-to-digital converters, on a custom-designed 5 mm x 3 mm CMOS chip drive redox reactions using cyclic voltammetry, sense DNA binding, and transmit digital data off chip for analysis. We demonstrate multiplexed and specific detection of DNA targets as well as real-time monitoring of hybridization, a task that is difficult, if not impossible, with traditional fluorescence-based microarrays.
NAIMA: target amplification strategy allowing quantitative on-chip detection of GMOs.
Morisset, Dany; Dobnik, David; Hamels, Sandrine; Zel, Jana; Gruden, Kristina
2008-10-01
We have developed a novel multiplex quantitative DNA-based target amplification method suitable for sensitive, specific and quantitative detection on microarray. This new method named NASBA Implemented Microarray Analysis (NAIMA) was applied to GMO detection in food and feed, but its application can be extended to all fields of biology requiring simultaneous detection of low copy number DNA targets. In a first step, the use of tailed primers allows the multiplex synthesis of template DNAs in a primer extension reaction. A second step of the procedure consists of transcription-based amplification using universal primers. The cRNA product is further on directly ligated to fluorescent dyes labelled 3DNA dendrimers allowing signal amplification and hybridized without further purification on an oligonucleotide probe-based microarray for multiplex detection. Two triplex systems have been applied to test maize samples containing several transgenic lines, and NAIMA has shown to be sensitive down to two target copies and to provide quantitative data on the transgenic contents in a range of 0.1-25%. Performances of NAIMA are comparable to singleplex quantitative real-time PCR. In addition, NAIMA amplification is faster since 20 min are sufficient to achieve full amplification.
NAIMA: target amplification strategy allowing quantitative on-chip detection of GMOs
Morisset, Dany; Dobnik, David; Hamels, Sandrine; Žel, Jana; Gruden, Kristina
2008-01-01
We have developed a novel multiplex quantitative DNA-based target amplification method suitable for sensitive, specific and quantitative detection on microarray. This new method named NASBA Implemented Microarray Analysis (NAIMA) was applied to GMO detection in food and feed, but its application can be extended to all fields of biology requiring simultaneous detection of low copy number DNA targets. In a first step, the use of tailed primers allows the multiplex synthesis of template DNAs in a primer extension reaction. A second step of the procedure consists of transcription-based amplification using universal primers. The cRNA product is further on directly ligated to fluorescent dyes labelled 3DNA dendrimers allowing signal amplification and hybridized without further purification on an oligonucleotide probe-based microarray for multiplex detection. Two triplex systems have been applied to test maize samples containing several transgenic lines, and NAIMA has shown to be sensitive down to two target copies and to provide quantitative data on the transgenic contents in a range of 0.1–25%. Performances of NAIMA are comparable to singleplex quantitative real-time PCR. In addition, NAIMA amplification is faster since 20 min are sufficient to achieve full amplification. PMID:18710880
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 (...
Gene expression in developing watermelon fruit
Wechter, W Patrick; Levi, Amnon; Harris, Karen R; Davis, Angela R; Fei, Zhangjun; Katzir, Nurit; Giovannoni, James J; Salman-Minkov, Ayelet; Hernandez, Alvaro; Thimmapuram, Jyothi; Tadmor, Yaakov; Portnoy, Vitaly; Trebitsh, Tova
2008-01-01
Background Cultivated watermelon form large fruits that are highly variable in size, shape, color, and content, yet have extremely narrow genetic diversity. Whereas a plethora of genes involved in cell wall metabolism, ethylene biosynthesis, fruit softening, and secondary metabolism during fruit development and ripening have been identified in other plant species, little is known of the genes involved in these processes in watermelon. A microarray and quantitative Real-Time PCR-based study was conducted in watermelon [Citrullus lanatus (Thunb.) Matsum. & Nakai var. lanatus] in order to elucidate the flow of events associated with fruit development and ripening in this species. RNA from three different maturation stages of watermelon fruits, as well as leaf, were collected from field grown plants during three consecutive years, and analyzed for gene expression using high-density photolithography microarrays and quantitative PCR. Results High-density photolithography arrays, composed of probes of 832 EST-unigenes from a subtracted, fruit development, cDNA library of watermelon were utilized to examine gene expression at three distinct time-points in watermelon fruit development. Analysis was performed with field-grown fruits over three consecutive growing seasons. Microarray analysis identified three hundred and thirty-five unique ESTs that are differentially regulated by at least two-fold in watermelon fruits during the early, ripening, or mature stage when compared to leaf. Of the 335 ESTs identified, 211 share significant homology with known gene products and 96 had no significant matches with any database accession. Of the modulated watermelon ESTs related to annotated genes, a significant number were found to be associated with or involved in the vascular system, carotenoid biosynthesis, transcriptional regulation, pathogen and stress response, and ethylene biosynthesis. Ethylene bioassays, performed with a closely related watermelon genotype with a similar phenotype, i.e. seeded, bright red flesh, dark green rind, etc., determined that ethylene levels were highest during the green fruit stage followed by a decrease during the white and pink fruit stages. Additionally, quantitative Real-Time PCR was used to validate modulation of 127 ESTs that were differentially expressed in developing and ripening fruits based on array analysis. Conclusion This study identified numerous ESTs with putative involvement in the watermelon fruit developmental and ripening process, in particular the involvement of the vascular system and ethylene. The production of ethylene during fruit development in watermelon gives further support to the role of ethylene in fruit development in non-climacteric fruits. PMID:18534026
Radiation Fibrosis of the Vocal Fold: From Man to Mouse
Johns, Michael M.; Kolachala, Vasantha; Berg, Eric; Muller, Susan; Creighton, Frances X.; Branski, Ryan C.
2013-01-01
Objectives To characterize fundamental late tissue effects in the human vocal fold following radiation therapy. To develop a murine model of radiation fibrosis to ultimately develop both treatment and prevention paradigms. Design Translational study using archived human and fresh murine irradiated vocal fold tissue. Methods 1) Irradiated vocal fold tissue from patients undergoing laryngectomy for loss of function from radiation fibrosis were identified from pathology archives. Histomorphometry, immunohistochemistry, and whole-genome microarray as well as real-time transcriptional analyses was performed. 2) Focused radiation to the head and neck was delivered to mice in a survival fashion. One month following radiation, vocal fold tissue was analyzed with histomorphometry, immunohistochemistry, and real-time PCR transcriptional analysis for selected markers of fibrosis. Results Human irradiated vocal folds demonstrated increased collagen transcription with increased deposition and disorganization of collagen in both the thyroarytenoid muscle and the superficial lamina propria. Fibronectin were increased in the superficial lamina propria. Laminin decreased in the thyroarytenoid muscle. Whole genome microarray analysis demonstrated increased transcription of markers for fibrosis, oxidative stress, inflammation, glycosaminoglycan production and apoptosis. Irradiated murine vocal folds demonstrated increases in collagen and fibronectin transcription and deposition in the lamina propria. Transforming growth factor (TGF)-β increased in the lamina propria. Conclusion Human irradiated vocal folds demonstrate molecular changes leading to fibrosis that underlie loss of vocal fold pliability that occurs in patients following laryngeal irradiation. Irradiated murine tissue demonstrates similar findings, and this mouse model may have utility in creating prevention and treatment strategies for vocal fold radiation fibrosis. PMID:23242839
NAGATOMO, T; OHGA, S; TAKADA, H; NOMURA, A; HIKINO, S; IMURA, M; OHSHIMA, K; HARA, T
2004-01-01
To continue the search for immunological roles of breast milk, cDNA microarray analysis on cytokines and growth factors was performed for human milk cells. Among the 240 cytokine-related genes, osteopontin (OPN) gene ranked top of the expression. Real-time PCR revealed that the OPN mRNA levels in colostrum cells were approximately 100 times higher than those in PHA-stimulated peripheral blood mononuclear cells (PBMNCs), and 10 000 times higher than those in PB CD14+ cells. The median levels of OPN mRNA in early milk or mature milk cells were more than three times higher than those in colostrum cells. Western blot analysis of human milk showed appreciable expression of full-length and short form proteins of OPN. The concentrations of full-length OPN in early milk or mature milk whey continued to be higher than those in colostrum whey and plasma as assessed by ELISA. The early milk (3–7 days postpartum) contained the highest concentrations of OPN protein, while the late mature milk cells (1 years postpartum) had the highest expression of OPN mRNA of all the lactating periods. The results of immunohistochemical and immunocytochemical staining indicated that OPN-producing epithelial cells and macrophages are found in actively lactating mammary glands. These results suggest that the persistently and extraordinarily high expression of OPN in human milk cells plays a potential role in the immunological development of breast-fed infants. PMID:15373904
Quality control of inkjet technology for DNA microarray fabrication.
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.
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.
The genes Scgb1a1, Lpo and Gbp2 characteristically expressed in peri-implant epithelium of rats.
Mori, Gentaro; Sasaki, Hodaka; Makabe, Yasushi; Yoshinari, Masao; Yajima, Yasutomo
2016-12-01
The peri-implant epithelium (PIE) plays an important role in the prevention against initial stage of inflammation. To minimize the risk of peri-implantitis, it is necessary to understand the biological characteristics of the PIE. The aim of this study was to investigate the characteristic gene expression profile of PIE as compared to junctional epithelium (JE) using laser microdissection and microarray analysis. Left upper first molars of 4-week-old rat were extracted, and titanium alloy implants were placed. Four weeks after surgery, samples were harvested by laser microdissection, and total RNA samples were isolated. Comprehensive analyses of genes expressed in the JE and PIE were performed using microarray analysis. Confirmation of the differential expression of selected genes was performed by quantitative real-time polymerase chain reaction and immunohistochemistry. The microarray analysis showed that 712 genes were more than twofold change upregulated in the PIE compared with the JE. Genes Scgb1a1 were significantly upregulated more than 19.1-fold, Lpo more than 19.0-fold, and Gbp2 more than 8.9-fold, in the PIE (P < 0.01). Immunohistochemical localization of SCGB1A1, LPO, and GBP2 was observed in PIE. The present results suggested that genes Scgb1a1, Lpo, and Gbp2 are characteristically expressed in the PIE. © 2015 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.
Bikel, Shirley; Jacobo-Albavera, Leonor; Sánchez-Muñoz, Fausto; Cornejo-Granados, Fernanda; Canizales-Quinteros, Samuel; Soberón, Xavier; Sotelo-Mundo, Rogerio R.; del Río-Navarro, Blanca E.; Mendoza-Vargas, Alfredo; Sánchez, Filiberto
2017-01-01
Background In spite of the emergence of RNA sequencing (RNA-seq), microarrays remain in widespread use for gene expression analysis in the clinic. There are over 767,000 RNA microarrays from human samples in public repositories, which are an invaluable resource for biomedical research and personalized medicine. The absolute gene expression analysis allows the transcriptome profiling of all expressed genes under a specific biological condition without the need of a reference sample. However, the background fluorescence represents a challenge to determine the absolute gene expression in microarrays. Given that the Y chromosome is absent in female subjects, we used it as a new approach for absolute gene expression analysis in which the fluorescence of the Y chromosome genes of female subjects was used as the background fluorescence for all the probes in the microarray. This fluorescence was used to establish an absolute gene expression threshold, allowing the differentiation between expressed and non-expressed genes in microarrays. Methods We extracted the RNA from 16 children leukocyte samples (nine males and seven females, ages 6–10 years). An Affymetrix Gene Chip Human Gene 1.0 ST Array was carried out for each sample and the fluorescence of 124 genes of the Y chromosome was used to calculate the absolute gene expression threshold. After that, several expressed and non-expressed genes according to our absolute gene expression threshold were compared against the expression obtained using real-time quantitative polymerase chain reaction (RT-qPCR). Results From the 124 genes of the Y chromosome, three genes (DDX3Y, TXLNG2P and EIF1AY) that displayed significant differences between sexes were used to calculate the absolute gene expression threshold. Using this threshold, we selected 13 expressed and non-expressed genes and confirmed their expression level by RT-qPCR. Then, we selected the top 5% most expressed genes and found that several KEGG pathways were significantly enriched. Interestingly, these pathways were related to the typical functions of leukocytes cells, such as antigen processing and presentation and natural killer cell mediated cytotoxicity. We also applied this method to obtain the absolute gene expression threshold in already published microarray data of liver cells, where the top 5% expressed genes showed an enrichment of typical KEGG pathways for liver cells. Our results suggest that the three selected genes of the Y chromosome can be used to calculate an absolute gene expression threshold, allowing a transcriptome profiling of microarray data without the need of an additional reference experiment. Discussion Our approach based on the establishment of a threshold for absolute gene expression analysis will allow a new way to analyze thousands of microarrays from public databases. This allows the study of different human diseases without the need of having additional samples for relative expression experiments. PMID:29230367
Trio, Phoebe Zapanta; Fujisaki, Satoru; Tanigawa, Shunsuke; Hisanaga, Ayami; Sakao, Kozue; Hou, De-Xing
2016-01-01
6-(Methylsulfinyl)hexyl isothiocyanate (6-MSITC), 6-(methylthio)hexyl isothiocyanate (6-MTITC), and 4-(methylsulfinyl)butyl isothiocyanate (4-MSITC) are isothiocyanate (ITC) bioactive compounds from Japanese Wasabi. Previous in vivo studies highlighted the neuroprotective potential of ITCs since ITCs enhance the production of antioxidant-related enzymes. Thus, in this present study, a genome-wide DNA microarray analysis was designed to profile gene expression changes in a neuron cell line, IMR-32, stimulated by these ITCs. Among these ITCs, 6-MSITC caused the expression changes of most genes (263), of which 100 genes were upregulated and 163 genes were downregulated. Gene categorization showed that most of the differentially expressed genes are involved in oxidative stress response, and pathway analysis further revealed that Nrf2-mediated oxidative stress pathway is the top of the ITC-modulated signaling pathway. Finally, real-time polymerase chain reaction (PCR) and Western blotting confirmed the gene expression and protein products of the major targets by ITCs. Taken together, Wasabi-derived ITCs might target the Nrf2-mediated oxidative stress pathway to exert neuroprotective effects. PMID:27547033
Trio, Phoebe Zapanta; Fujisaki, Satoru; Tanigawa, Shunsuke; Hisanaga, Ayami; Sakao, Kozue; Hou, De-Xing
2016-01-01
6-(Methylsulfinyl)hexyl isothiocyanate (6-MSITC), 6-(methylthio)hexyl isothiocyanate (6-MTITC), and 4-(methylsulfinyl)butyl isothiocyanate (4-MSITC) are isothiocyanate (ITC) bioactive compounds from Japanese Wasabi. Previous in vivo studies highlighted the neuroprotective potential of ITCs since ITCs enhance the production of antioxidant-related enzymes. Thus, in this present study, a genome-wide DNA microarray analysis was designed to profile gene expression changes in a neuron cell line, IMR-32, stimulated by these ITCs. Among these ITCs, 6-MSITC caused the expression changes of most genes (263), of which 100 genes were upregulated and 163 genes were downregulated. Gene categorization showed that most of the differentially expressed genes are involved in oxidative stress response, and pathway analysis further revealed that Nrf2-mediated oxidative stress pathway is the top of the ITC-modulated signaling pathway. Finally, real-time polymerase chain reaction (PCR) and Western blotting confirmed the gene expression and protein products of the major targets by ITCs. Taken together, Wasabi-derived ITCs might target the Nrf2-mediated oxidative stress pathway to exert neuroprotective effects.
Hokanson, R; Fudge, R; Chowdhary, R; Busbee, D
2007-09-01
Gene expression is altered in mammalian cells (MCF-7 cells), by exposure to a variety of chemicals that mimic steroid hormones or interact with endocrine receptors or their co-factors. Among those populations chronically exposed to these endocrine disruptive chemicals are persons, and their families, who are employed in agriculture or horticulture, or who use agricultural/horticultural chemicals. Among the chemicals most commonly used, both commercially and in the home, is the herbicide glyphosate. Although glyphosate is commonly considered to be relatively non-toxic, we utilized in vitro DNA microarray analysis of this chemical to evaluate its capacity to alter the expression of a variety of genes in human cells. We selected a group of genes, determined by DNA microarray analysis to be dysregulated, and used quantitative real-time PCR to corroborate their altered states of expression. We discussed the reported function of those genes, with emphasis on altered physiological states that are capable of initiating adverse health effects that might be anticipated if gene expression were significantly altered in either adults or embryos exposed in utero.
Statistical methodology for the analysis of dye-switch microarray experiments
Mary-Huard, Tristan; Aubert, Julie; Mansouri-Attia, Nadera; Sandra, Olivier; Daudin, Jean-Jacques
2008-01-01
Background In individually dye-balanced microarray designs, each biological sample is hybridized on two different slides, once with Cy3 and once with Cy5. While this strategy ensures an automatic correction of the gene-specific labelling bias, it also induces dependencies between log-ratio measurements that must be taken into account in the statistical analysis. Results We present two original statistical procedures for the statistical analysis of individually balanced designs. These procedures are compared with the usual ML and REML mixed model procedures proposed in most statistical toolboxes, on both simulated and real data. Conclusion The UP procedure we propose as an alternative to usual mixed model procedures is more efficient and significantly faster to compute. This result provides some useful guidelines for the analysis of complex designs. PMID:18271965
Nanotechnology: moving from microarrays toward nanoarrays.
Chen, Hua; Li, Jun
2007-01-01
Microarrays are important tools for high-throughput analysis of biomolecules. The use of microarrays for parallel screening of nucleic acid and protein profiles has become an industry standard. A few limitations of microarrays are the requirement for relatively large sample volumes and elongated incubation time, as well as the limit of detection. In addition, traditional microarrays make use of bulky instrumentation for the detection, and sample amplification and labeling are quite laborious, which increase analysis cost and delays the time for obtaining results. These problems limit microarray techniques from point-of-care and field applications. One strategy for overcoming these problems is to develop nanoarrays, particularly electronics-based nanoarrays. With further miniaturization, higher sensitivity, and simplified sample preparation, nanoarrays could potentially be employed for biomolecular analysis in personal healthcare and monitoring of trace pathogens. In this chapter, it is intended to introduce the concept and advantage of nanotechnology and then describe current methods and protocols for novel nanoarrays in three aspects: (1) label-free nucleic acids analysis using nanoarrays, (2) nanoarrays for protein detection by conventional optical fluorescence microscopy as well as by novel label-free methods such as atomic force microscopy, and (3) nanoarray for enzymatic-based assay. These nanoarrays will have significant applications in drug discovery, medical diagnosis, genetic testing, environmental monitoring, and food safety inspection.
An efficient method to identify differentially expressed genes in microarray experiments
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
Im, Hyungsoon; Lesuffleur, Antoine; Lindquist, Nathan C.; Oh, Sang-Hyun
2009-01-01
We present nanohole arrays in a gold film integrated with a 6-channel microfluidic chip for parallel measurements of molecular binding kinetics. Surface plasmon resonance effects in the nanohole arrays enable real-time label-free measurements of molecular binding events in each channel, while adjacent negative reference channels can record measurement artifacts such as bulk solution index changes, temperature variations, or changing light absorption in the liquid. Using this platform, streptavidin-biotin specific binding kinetics are measured at various concentrations with negative controls. A high-density microarray of 252 biosensing pixels is also demonstrated with a packing density of 106 sensing elements/cm2, which can potentially be coupled with a massively parallel array of microfluidic channels for protein microarray applications. PMID:19284776
Taki, Kenji; Fukushima, Tamio; Ise, Ryota; Horii, Ikuo; Yoshida, Takemi
2013-02-01
MicroRNAs (miRNAs) are small single-stranded RNAs of 19-25 nucleotides and are important in posttranscriptional regulation of genes. Recently, the role of miRNAs in toxicity incidence is reported to be a regulator of key-stopper of gene expression, however the detailed mechanism of miRNAs is not well known yet. 6-Mercaptopurine (6-MP), the anti-leukemic and immunosuppressive drug, produced teratogenicity and pregnancy loss. We focused on the placenta to evaluate toxicity in embryo/fetal development produced by 6-MP treatment. MiRNA expression in the placenta was analyzed by miRNA microarray. Fifteen miRNAs were upregulated on GD13 and 5 miRNAs were downregulated on GD15 in 6-MP treatment rat placentas. Some miRNAs may have functions in apoptosis (miR-195, miR-21, miR-29c and miR-34a), inflammation (miR-146b), and ischemia (miR-144 and miR-451). In the maternal plasma, expression of miR-144 was significantly reduced by 6-MP treatment when examined by real-time RT-PCR. We determined toxicity-related gene expression in the rat placenta. Gene expression analysis was carried out by DNA oligo microarray using rat placenta total RNAs. Compared between predicted targets of miRNAs and microarray data in 6-MP-treated rat placenta, expressions of hormone receptor genes (estrogen receptor 1; Esr1, progesterone receptor; Pgr, and prolactin receptor; Prlr), xanthine oxidase (Xdh), Slc38a5 and Phlda2 genes were changed. The histopathologically found increase in trophoblastic giant cells and reduced placental growth by 6-MP treatment were well correlated to these gene expressions. These data suggest that some miRNAs may link to toxicological reactions in 6-MP-induced placental toxicity.
Paraboschi, Elvezia Maria; Cardamone, Giulia; Rimoldi, Valeria; Gemmati, Donato; Spreafico, Marta; Duga, Stefano; Soldà, Giulia; Asselta, Rosanna
2015-09-30
Abnormalities in RNA metabolism and alternative splicing (AS) are emerging as important players in complex disease phenotypes. In particular, accumulating evidence suggests the existence of pathogenic links between multiple sclerosis (MS) and altered AS, including functional studies showing that an imbalance in alternatively-spliced isoforms may contribute to disease etiology. Here, we tested whether the altered expression of AS-related genes represents a MS-specific signature. A comprehensive comparative analysis of gene expression profiles of publicly-available microarray datasets (190 MS cases, 182 controls), followed by gene-ontology enrichment analysis, highlighted a significant enrichment for differentially-expressed genes involved in RNA metabolism/AS. In detail, a total of 17 genes were found to be differentially expressed in MS in multiple datasets, with CELF1 being dysregulated in five out of seven studies. We confirmed CELF1 downregulation in MS (p=0.0015) by real-time RT-PCRs on RNA extracted from blood cells of 30 cases and 30 controls. As a proof of concept, we experimentally verified the unbalance in alternatively-spliced isoforms in MS of the NFAT5 gene, a putative CELF1 target. In conclusion, for the first time we provide evidence of a consistent dysregulation of splicing-related genes in MS and we discuss its possible implications in modulating specific AS events in MS susceptibility genes.
Detection of foodborne pathogens using microarray technology
USDA-ARS?s Scientific Manuscript database
Assays based on the polymerase chain reaction (PCR) are now accepted methods for rapidly confirming the presence or absence of specific pathogens in foods and other types of samples. Conventional PCR requires the use of agarose gel electrophoresis to detect the PCR product; whereas, real-time PCR c...
Pandey, Mamta; Singh, Dheer; Onteru, Suneel K
2018-06-01
Transcript analysis is usually performed by costly, time-consuming, and expertise intensive methods, like real time-PCR, microarray, etc. However, they are not much feasible in low-input laboratories. Therefore, we implemented the reverse transcription loop-mediated isothermal amplification (RT-LAMP) as a means of mammalian transcript analysis. Particularly, RT-LAMP was developed for buffalo aromatase cytochrome P450 (CYP19) transcript, to study its expression in 3D-cultured buffalo granulosa cells, which were exposed to lipopolysaccharide (LPS). The CYP19-RT-LAMP assay rapidly identified the LPS-induced downregulation of the CYP19 gene within 30 min at 63°C in a water bath. The assay was visualized via unaided eye by observing the change in turbidity and fluorescence, which were decreased by increasing the LPS exposure time to granulosa cells. Overall, the developed CYP19-RT-LAMP assay provided a hope on the application of RT-LAMP for mammalian transcript analysis in low-input laboratories. © 2017 Wiley Periodicals, Inc.
Identification and characterization of nuclear genes involved in photosynthesis in Populus
2014-01-01
Background The gap between the real and potential photosynthetic rate under field conditions suggests that photosynthesis could potentially be improved. Nuclear genes provide possible targets for improving photosynthetic efficiency. Hence, genome-wide identification and characterization of the nuclear genes affecting photosynthetic traits in woody plants would provide key insights on genetic regulation of photosynthesis and identify candidate processes for improvement of photosynthesis. Results Using microarray and bulked segregant analysis strategies, we identified differentially expressed nuclear genes for photosynthesis traits in a segregating population of poplar. We identified 515 differentially expressed genes in this population (FC ≥ 2 or FC ≤ 0.5, P < 0.05), 163 up-regulated and 352 down-regulated. Real-time PCR expression analysis confirmed the microarray data. Singular Enrichment Analysis identified 48 significantly enriched GO terms for molecular functions (28), biological processes (18) and cell components (2). Furthermore, we selected six candidate genes for functional examination by a single-marker association approach, which demonstrated that 20 SNPs in five candidate genes significantly associated with photosynthetic traits, and the phenotypic variance explained by each SNP ranged from 2.3% to 12.6%. This revealed that regulation of photosynthesis by the nuclear genome mainly involves transport, metabolism and response to stimulus functions. Conclusions This study provides new genome-scale strategies for the discovery of potential candidate genes affecting photosynthesis in Populus, and for identification of the functions of genes involved in regulation of photosynthesis. This work also suggests that improving photosynthetic efficiency under field conditions will require the consideration of multiple factors, such as stress responses. PMID:24673936
Microarray expression profiling in adhesion and normal peritoneal tissues.
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.
Smoking induces transcription of the heat shock protein system in the joints.
Ospelt, Caroline; Camici, Giovanni G; Engler, Anna; Kolling, Christoph; Vogetseder, Alexander; Gay, Renate E; Michel, Beat A; Gay, Steffen
2014-07-01
Smoking increases the risk of developing rheumatoid arthritis (RA) and worsens the course of the disease. In the current study we analysed whether smoking can affect gene expression directly in the joints. Synovial fibroblasts were incubated with 5% cigarette smoke extract and changes in gene expression were detected using whole genome microarrays and verified with real-time PCR. Synovial tissues were obtained from smoking and non-smoking patients with RA undergoing joint replacement surgery and from mice exposed to cigarette smoke or ambient air in a whole body exposure chamber for 3 weeks. Microarray and real-time PCR analysis showed a significant upregulation of the heat shock proteins DnaJA4, DnaJB4, DnaJC6, HspB8 and Hsp70 after stimulation of synovial fibroblasts with 5% cigarette smoke extract. Similarly, in synovial tissues of smokers with RA the expression of DnaJB4, DnaJC6, HspB8 and Hsp70 was significantly higher compared with non-smokers with RA. Upregulation of DnaJB4 and DnaJC6 in joints by smoking was also confirmed in mice exposed to cigarette smoke. Our data clearly show that smoking can change gene expression in the joints, which can lead to the activation of signalling pathways that promote development of autoimmunity and chronic joint inflammation. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions.
Lo, Kai-Yin; Sun, Yung-Shin; Landry, James P.; Zhu, Xiangdong; Deng, Wenbin
2012-01-01
Conventional fluorescent microscopy is routinely used to detect cell surface markers through fluorophore-conjugated antibodies. However, fluorophore-conjugation of antibodies alters binding properties such as strength and specificity of the antibody in ways often uncharacterized. The binding between antibody and antigen might not be in the native situation after such conjugation. Here, we present an oblique-incidence reflectivity difference (OI-RD) microscope as an effective method for label-free, real-time detection of cell surface markers and apply such a technique to analysis of Stage-Specific Embryonic Antigen 1 (SSEA1) on stem cells. Mouse stem cells express SSEA1 on their surfaces and the level of SSEA1 decreases when the cells start to differentiate. In this study, we immobilized mouse stem cells and non-stem cells (control) on a glass surface as a microarray and reacted the cell microarray with unlabeled SSEA1 antibodies. By monitoring the reaction with an OI-RD microscope in real time, we confirmed that the SSEA1 antibodies only bind to the surface of the stem cells while not to the surface of non-stem cells. From the binding curves, we determined the equilibrium dissociation constant (Kd) of the antibody with the SSEA1 markers on the stem cell surface. The results concluded that OI-RD microscope can be used to detect binding affinities between cell surface markers and unlabeled antibodies bound to the cells. The information could be another indicator to determine the cell stages. PMID:21781038
Ku, Yu-Fu; Huang, Long-Sun
2018-01-01
Here, we provide a method and apparatus for real-time compensation of the thermal effect of single free-standing piezoresistive microcantilever-based biosensors. The sensor chip contained an on-chip fixed piezoresistor that served as a temperature sensor, and a multilayer microcantilever with an embedded piezoresistor served as a biomolecular sensor. This method employed the calibrated relationship between the resistance and the temperature of piezoresistors to eliminate the thermal effect on the sensor, including the temperature coefficient of resistance (TCR) and bimorph effect. From experimental results, the method was verified to reduce the signal of thermal effect from 25.6 μV/°C to 0.3 μV/°C, which was approximately two orders of magnitude less than that before the processing of the thermal elimination method. Furthermore, the proposed approach and system successfully demonstrated its effective real-time thermal self-elimination on biomolecular detection without any thermostat device to control the environmental temperature. This method realizes the miniaturization of an overall measurement system of the sensor, which can be used to develop portable medical devices and microarray analysis platforms. PMID:29495574
Microarray analysis of potential genes in the pathogenesis of recurrent oral ulcer.
Han, Jingying; He, Zhiwei; Li, Kun; Hou, Lu
2015-01-01
Recurrent oral ulcer seriously threatens patients' daily life and health. This study investigated potential genes and pathways that participate in the pathogenesis of recurrent oral ulcer by high throughput bioinformatic analysis. RT-PCR and Western blot were applied to further verify screened interleukins effect. Recurrent oral ulcer related genes were collected from websites and papers, and further found out from Human Genome 280 6.0 microarray data. Each pathway of recurrent oral ulcer related genes were got through chip hybridization. RT-PCR was applied to test four recurrent oral ulcer related genes to verify the microarray data. Data transformation, scatter plot, clustering analysis, and expression pattern analysis were used to analyze recurrent oral ulcer related gene expression changes. Recurrent oral ulcer gene microarray was successfully established. Microarray showed that 551 genes involved in recurrent oral ulcer activity and 196 genes were recurrent oral ulcer related genes. Of them, 76 genes up-regulated, 62 genes down-regulated, and 58 genes up-/down-regulated. Total expression level up-regulated 752 times (60%) and down-regulated 485 times (40%). IL-2 plays an important role in the occurrence, development and recurrence of recurrent oral ulcer on the mRNA and protein levels. Gene microarray can be used to analyze potential genes and pathways in recurrent oral ulcer. IL-2 may be involved in the pathogenesis of recurrent oral ulcer.
Kim, Yong-June; Yoon, Hyung-Yoon; Kim, Seon-Kyu; Kim, Young-Won; Kim, Eun-Jung; Kim, Isaac Yi; Kim, Wun-Jae
2011-07-01
Abnormal DNA methylation is associated with many human cancers. The aim of the present study was to identify novel methylation markers in prostate cancer (PCa) by microarray analysis and to test whether these markers could discriminate normal and PCa cells. Microarray-based DNA methylation and gene expression profiling was carried out using a panel of PCa cell lines and a control normal prostate cell line. The methylation status of candidate genes in prostate cell lines was confirmed by real-time reverse transcriptase-PCR, bisulfite sequencing analysis, and treatment with a demethylation agent. DNA methylation and gene expression analysis in 203 human prostate specimens, including 106 PCa and 97 benign prostate hyperplasia (BPH), were carried out. Further validation using microarray gene expression data from the Gene Expression Omnibus (GEO) was carried out. Epidermal growth factor-containing fibulin-like extracellular matrix protein 1 (EFEMP1) was identified as a lead candidate methylation marker for PCa. The gene expression level of EFEMP1 was significantly higher in tissue samples from patients with BPH than in those with PCa (P < 0.001). The sensitivity and specificity of EFEMP1 methylation status in discriminating between PCa and BPH reached 95.3% (101 of 106) and 86.6% (84 of 97), respectively. From the GEO data set, we confirmed that the expression level of EFEMP1 was significantly different between PCa and BPH. Genome-wide characterization of DNA methylation profiles enabled the identification of EFEMP1 aberrant methylation patterns in PCa. EFEMP1 might be a useful indicator for the detection of PCa.
The ability of infectious oocyst forms of Toxoplasma gondii and Cryptosporidium spp. to resist disinfection treatments and cause disease may have significant public health implications. Currently, little is known about oocyst-specific factors involved during host cell invasion pr...
Lim, Hye-Sun; Ha, Hyekyung; Shin, Hyeun-Kyoo; Jeong, Soo-Jin
2015-09-01
Saussurea lappa has been reported to possess anti-atopic properties. In this study, we have confirmed the S. lappa's anti-atopic properties in Nc/Nga mice and investigated the candidate gene related with its properties using microarray. We determined the target gene using real time PCR in in vitro experiment. S. lappa showed the significant reduction in atopic dermatitis (AD) score and immunoglobulin E compared with the AD induced Nc/Nga mice. In the results of microarray using back skin obtained from animals, we found that S. lappa's properties are closely associated with cytokine-cytokine receptor interaction and the JAK-STAT signaling pathway. Consistent with the microarray data, real-time RT-PCR confirmed these modulation at the mRNA level in skin tissues from S. lappa-treated mice. Among these genes, PI3Kca and IL20Rβ were significantly downregulated by S. lappa treatment in Nc/Nga mouse model. In in vitro experiment using HaCaT cells, we found that the S. lappa components, including alantolactone, caryophyllene, costic acid, costunolide and dehydrocostus lactone significantly decreased the expression of PI3Kca but not IL20Rβ in vitro. Therefore, our study suggests that PI3Kca-related signaling is closely related with the protective effects of S. lappa against the development of atopic-dermatitis.
Bennet, Jaison; Ganaprakasam, Chilambuchelvan Arul; Arputharaj, Kannan
2014-01-01
Cancer classification by doctors and radiologists was based on morphological and clinical features and had limited diagnostic ability in olden days. The recent arrival of DNA microarray technology has led to the concurrent monitoring of thousands of gene expressions in a single chip which stimulates the progress in cancer classification. In this paper, we have proposed a hybrid approach for microarray data classification based on nearest neighbor (KNN), naive Bayes, and support vector machine (SVM). Feature selection prior to classification plays a vital role and a feature selection technique which combines discrete wavelet transform (DWT) and moving window technique (MWT) is used. The performance of the proposed method is compared with the conventional classifiers like support vector machine, nearest neighbor, and naive Bayes. Experiments have been conducted on both real and benchmark datasets and the results indicate that the ensemble approach produces higher classification accuracy than conventional classifiers. This paper serves as an automated system for the classification of cancer and can be applied by doctors in real cases which serve as a boon to the medical community. This work further reduces the misclassification of cancers which is highly not allowed in cancer detection.
The Effect of Gestational Age on Angiogenic Gene Expression in the Rat Placenta
Vaswani, Kanchan; Hum, Melissa Wen-Ching; Chan, Hsiu-Wen; Ryan, Jennifer; Wood-Bradley, Ryan J.; Nitert, Marloes Dekker; Mitchell, Murray D.; Armitage, James A.; Rice, Gregory E.
2013-01-01
The placenta plays a central role in determining the outcome of pregnancy. It undergoes changes during gestation as the fetus develops and as demands for energy substrate transfer and gas exchange increase. The molecular mechanisms that coordinate these changes have yet to be fully elucidated. The study performed a large scale screen of the transcriptome of the rat placenta throughout mid-late gestation (E14.25–E20) with emphasis on characterizing gestational age associated changes in the expression of genes invoved in angiogenic pathways. Sprague Dawley dams were sacrificed at E14.25, E15.25, E17.25 and E20 (n = 6 per group) and RNA was isolated from one placenta per dam. Changes in placental gene expression were identifed using Illumina Rat Ref-12 Expression BeadChip Microarrays. Differentially expressed genes (>2-fold change, <1% false discovery rate, FDR) were functionally categorised by gene ontology pathway analysis. A subset of differentially expressed genes identified by microarrays were confirmed using Real-Time qPCR. The expression of thirty one genes involved in the angiogenic pathway was shown to change over time, using microarray analysis (22 genes displayed increased and 9 gene decreased expression). Five genes (4 up regulated: Cd36, Mmp14, Rhob and Angpt4 and 1 down regulated: Foxm1) involved in angiogenesis and blood vessel morphogenesis were subjected to further validation. qPCR confirmed late gestational increased expression of Cd36, Mmp14, Rhob and Angpt4 and a decrease in expression of Foxm1 before labour onset (P<0.0001). The observed acute, pre-labour changes in the expression of the 31 genes during gestation warrant further investigation to elucidate their role in pregnancy. PMID:24391823
Shao, Ning; Jiang, Shi-Meng; Zhang, Miao; Wang, Jing; Guo, Shu-Juan; Li, Yang; Jiang, He-Wei; Liu, Cheng-Xi; Zhang, Da-Bing; Yang, Li-Tao; Tao, Sheng-Ce
2014-01-21
The monitoring of genetically modified organisms (GMOs) is a primary step of GMO regulation. However, there is presently a lack of effective and high-throughput methodologies for specifically and sensitively monitoring most of the commercialized GMOs. Herein, we developed a multiplex amplification on a chip with readout on an oligo microarray (MACRO) system specifically for convenient GMO monitoring. This system is composed of a microchip for multiplex amplification and an oligo microarray for the readout of multiple amplicons, containing a total of 91 targets (18 universal elements, 20 exogenous genes, 45 events, and 8 endogenous reference genes) that covers 97.1% of all GM events that have been commercialized up to 2012. We demonstrate that the specificity of MACRO is ~100%, with a limit of detection (LOD) that is suitable for real-world applications. Moreover, the results obtained of simulated complex samples and blind samples with MACRO were 100% consistent with expectations and the results of independently performed real-time PCRs, respectively. Thus, we believe MACRO is the first system that can be applied for effectively monitoring the majority of the commercialized GMOs in a single test.
Jo, Kyuri; Kwon, Hawk-Bin; Kim, Sun
2014-06-01
Measuring expression levels of genes at the whole genome level can be useful for many purposes, especially for revealing biological pathways underlying specific phenotype conditions. When gene expression is measured over a time period, we have opportunities to understand how organisms react to stress conditions over time. Thus many biologists routinely measure whole genome level gene expressions at multiple time points. However, there are several technical difficulties for analyzing such whole genome expression data. In addition, these days gene expression data is often measured by using RNA-sequencing rather than microarray technologies and then analysis of expression data is much more complicated since the analysis process should start with mapping short reads and produce differentially activated pathways and also possibly interactions among pathways. In addition, many useful tools for analyzing microarray gene expression data are not applicable for the RNA-seq data. Thus a comprehensive package for analyzing time series transcriptome data is much needed. In this article, we present a comprehensive package, Time-series RNA-seq Analysis Package (TRAP), integrating all necessary tasks such as mapping short reads, measuring gene expression levels, finding differentially expressed genes (DEGs), clustering and pathway analysis for time-series data in a single environment. In addition to implementing useful algorithms that are not available for RNA-seq data, we extended existing pathway analysis methods, ORA and SPIA, for time series analysis and estimates statistical values for combined dataset by an advanced metric. TRAP also produces visual summary of pathway interactions. Gene expression change labeling, a practical clustering method used in TRAP, enables more accurate interpretation of the data when combined with pathway analysis. We applied our methods on a real dataset for the analysis of rice (Oryza sativa L. Japonica nipponbare) upon drought stress. The result showed that TRAP was able to detect pathways more accurately than several existing methods. TRAP is available at http://biohealth.snu.ac.kr/software/TRAP/. Copyright © 2014 Elsevier Inc. All rights reserved.
MAAMD: a workflow to standardize meta-analyses and comparison of affymetrix microarray data
2014-01-01
Background Mandatory deposit of raw microarray data files for public access, prior to study publication, provides significant opportunities to conduct new bioinformatics analyses within and across multiple datasets. Analysis of raw microarray data files (e.g. Affymetrix CEL files) can be time consuming, complex, and requires fundamental computational and bioinformatics skills. The development of analytical workflows to automate these tasks simplifies the processing of, improves the efficiency of, and serves to standardize multiple and sequential analyses. Once installed, workflows facilitate the tedious steps required to run rapid intra- and inter-dataset comparisons. Results We developed a workflow to facilitate and standardize Meta-Analysis of Affymetrix Microarray Data analysis (MAAMD) in Kepler. Two freely available stand-alone software tools, R and AltAnalyze were embedded in MAAMD. The inputs of MAAMD are user-editable csv files, which contain sample information and parameters describing the locations of input files and required tools. MAAMD was tested by analyzing 4 different GEO datasets from mice and drosophila. MAAMD automates data downloading, data organization, data quality control assesment, differential gene expression analysis, clustering analysis, pathway visualization, gene-set enrichment analysis, and cross-species orthologous-gene comparisons. MAAMD was utilized to identify gene orthologues responding to hypoxia or hyperoxia in both mice and drosophila. The entire set of analyses for 4 datasets (34 total microarrays) finished in ~ one hour. Conclusions MAAMD saves time, minimizes the required computer skills, and offers a standardized procedure for users to analyze microarray datasets and make new intra- and inter-dataset comparisons. PMID:24621103
Chen, Jihua; Uto, Takuhiro; Tanigawa, Shunsuke; Yamada-Kato, Tomeo; Fujii, Makoto; Hou, DE-Xing
2010-01-01
6-(Methylsulfinyl)hexyl isothiocyanate (6-MSITC) is a bioactive ingredient of wasabi [Wasabia japonica (Miq.) Matsumura], which is a popular pungent spice of Japan. To evaluate the anti-inflammatory function and underlying genes targeted by 6-MSITC, gene expression profiling through DNA microarray was performed in mouse macrophages. Among 22,050 oligonucleotides, the expression levels of 406 genes were increased by ≥3-fold in lipopolysaccharide (LPS)-activated RAW264 cells, 238 gene signals of which were attenuated by 6-MSITC (≥2-fold). Expression levels of 717 genes were decreased by ≥3-fold in LPS-activated cells, of which 336 gene signals were restored by 6-MSITC (≥2-fold). Utilizing group analysis, 206 genes affected by 6-MSITC with a ≥2-fold change were classified into 35 categories relating to biological processes (81), molecular functions (108) and signaling pathways (17). The genes were further categorized as 'defense, inflammatory response, cytokine activities and receptor activities' and some were confirmed by real-time polymerase chain reaction. Ingenuity pathway analysis further revealed that wasabi 6-MSITC regulated the relevant networks of chemokines, interleukins and interferons to exert its anti-inflammatory function.
CHEN, JIHUA; UTO, TAKUHIRO; TANIGAWA, SHUNSUKE; YAMADA-KATO, TOMEO; FUJII, MAKOTO; HOU, DE-XING
2010-01-01
6-(Methylsulfinyl)hexyl isothiocyanate (6-MSITC) is a bioactive ingredient of wasabi [Wasabia japonica (Miq.) Matsumura], which is a popular pungent spice of Japan. To evaluate the anti-inflammatory function and underlying genes targeted by 6-MSITC, gene expression profiling through DNA microarray was performed in mouse macrophages. Among 22,050 oligonucleotides, the expression levels of 406 genes were increased by ≥3-fold in lipopolysaccharide (LPS)-activated RAW264 cells, 238 gene signals of which were attenuated by 6-MSITC (≥2-fold). Expression levels of 717 genes were decreased by ≥3-fold in LPS-activated cells, of which 336 gene signals were restored by 6-MSITC (≥2-fold). Utilizing group analysis, 206 genes affected by 6-MSITC with a ≥2-fold change were classified into 35 categories relating to biological processes (81), molecular functions (108) and signaling pathways (17). The genes were further categorized as ‘defense, inflammatory response, cytokine activities and receptor activities’ and some were confirmed by real-time polymerase chain reaction. Ingenuity pathway analysis further revealed that wasabi 6-MSITC regulated the relevant networks of chemokines, interleukins and interferons to exert its anti-inflammatory function. PMID:23136589
NASA Astrophysics Data System (ADS)
Kardous, F.; El Fissi, L.; Friedt, J.-M.; Bastien, F.; Boireau, W.; Yahiaoui, R.; Manceau, J.-F.; Ballandras, S.
2011-05-01
The development of lab-on-chip devices is expected to dramatically change biochemical analyses, allowing for a notable increase of processing quality and throughput, provided the induced chemical reactions are well controlled. In this work, we investigate the impact of local acoustic mixing to promote or accelerate such biochemical reactions, such as antibody grafting on activated surfaces. During microarray building, the spotting mode leads to low efficiency in the ligand grafting and heterogeneities which limits its performances. To improve the transfer rate, we induce a hydrodynamic flow in the spotted droplet to disrupt the steady state during antibody grafting. To prove that acoustic mixing increases the antibody transfer rate to the biochip surface, we have used a Love-wave sensor allowing for real-time monitoring of the biological reaction for different operating conditions (with or without mixing). An analysis of the impact of the proposed mixing on grafting kinetics is proposed and finally checked in the case of antibody-antigen combination.
Genome-wide transcription analysis of histidine-related cataract in Atlantic salmon (Salmo salar L)
Waagbø, Rune; Breck, Olav; Stavrum, Anne-Kristin; Petersen, Kjell; Olsvik, Pål A.
2009-01-01
Purpose Elevated levels of dietary histidine have previously been shown to prevent or mitigate cataract formation in farmed Atlantic salmon (Salmo salar L). The aim of this study was to shed light on the mechanisms by which histidine acts. Applying microarray analysis to the lens transcriptome, we screened for differentially expressed genes in search for a model explaining cataract development in Atlantic salmon and possible markers for early cataract diagnosis. Methods Adult Atlantic salmon (1.7 kg) were fed three standard commercial salmon diets only differing in the histidine content (9, 13, and 17 g histidine/kg diet) for four months. Individual cataract scores for both eyes were assessed by slit-lamp biomicroscopy. Lens N-acetyl histidine contents were measured by high performance liquid chromatography (HPLC). Total RNA extracted from whole lenses was analyzed using the GRASP 16K salmonid microarray. The microarray data were analyzed using J-Express Pro 2.7 and validated by quantitative real-time polymerase chain reaction (qRT–PCR). Results Fish developed cataracts with different severity in response to dietary histidine levels. Lens N-acetyl histidine contents reflected the dietary histidine levels and were negatively correlated to cataract scores. Significance analysis of microarrays (SAM) revealed 248 significantly up-regulated transcripts and 266 significantly down-regulated transcripts in fish that were fed a low level of histidine compared to fish fed a higher histidine level. Among the differentially expressed transcripts were metallothionein A and B as well as transcripts involved in lipid metabolism, carbohydrate metabolism, regulation of ion homeostasis, and protein degradation. Hierarchical clustering and correspondence analysis plot confirmed differences in gene expression between the feeding groups. The differentially expressed genes could be categorized as “early” and “late” responsive according to their expression pattern relative to progression in cataract formation. Conclusions Dietary histidine regimes affected cataract formation and lens gene expression in adult Atlantic salmon. Regulated transcripts selected from the results of this genome-wide transcription analysis might be used as possible biological markers for cataract development in Atlantic salmon. PMID:19597568
Gene set analysis approaches for RNA-seq data: performance evaluation and application guideline
Rahmatallah, Yasir; Emmert-Streib, Frank
2016-01-01
Transcriptome sequencing (RNA-seq) is gradually replacing microarrays for high-throughput studies of gene expression. The main challenge of analyzing microarray data is not in finding differentially expressed genes, but in gaining insights into the biological processes underlying phenotypic differences. To interpret experimental results from microarrays, gene set analysis (GSA) has become the method of choice, in particular because it incorporates pre-existing biological knowledge (in a form of functionally related gene sets) into the analysis. Here we provide a brief review of several statistically different GSA approaches (competitive and self-contained) that can be adapted from microarrays practice as well as those specifically designed for RNA-seq. We evaluate their performance (in terms of Type I error rate, power, robustness to the sample size and heterogeneity, as well as the sensitivity to different types of selection biases) on simulated and real RNA-seq data. Not surprisingly, the performance of various GSA approaches depends only on the statistical hypothesis they test and does not depend on whether the test was developed for microarrays or RNA-seq data. Interestingly, we found that competitive methods have lower power as well as robustness to the samples heterogeneity than self-contained methods, leading to poor results reproducibility. We also found that the power of unsupervised competitive methods depends on the balance between up- and down-regulated genes in tested gene sets. These properties of competitive methods have been overlooked before. Our evaluation provides a concise guideline for selecting GSA approaches, best performing under particular experimental settings in the context of RNA-seq. PMID:26342128
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.
Pollen is the primary means of gene flow between plants and plant populations and plays a critical role in seed production. Pollen fitness can be defined as the ability of a particular pollen grain to outcompete other pollen present on the stigma and complete fertilization, thus ...
Usadel, Björn; Nagel, Axel; Steinhauser, Dirk; Gibon, Yves; Bläsing, Oliver E; Redestig, Henning; Sreenivasulu, Nese; Krall, Leonard; Hannah, Matthew A; Poree, Fabien; Fernie, Alisdair R; Stitt, Mark
2006-12-18
Microarray technology has become a widely accepted and standardized tool in biology. The first microarray data analysis programs were developed to support pair-wise comparison. However, as microarray experiments have become more routine, large scale experiments have become more common, which investigate multiple time points or sets of mutants or transgenics. To extract biological information from such high-throughput expression data, it is necessary to develop efficient analytical platforms, which combine manually curated gene ontologies with efficient visualization and navigation tools. Currently, most tools focus on a few limited biological aspects, rather than offering a holistic, integrated analysis. Here we introduce PageMan, a multiplatform, user-friendly, and stand-alone software tool that annotates, investigates, and condenses high-throughput microarray data in the context of functional ontologies. It includes a GUI tool to transform different ontologies into a suitable format, enabling the user to compare and choose between different ontologies. It is equipped with several statistical modules for data analysis, including over-representation analysis and Wilcoxon statistical testing. Results are exported in a graphical format for direct use, or for further editing in graphics programs.PageMan provides a fast overview of single treatments, allows genome-level responses to be compared across several microarray experiments covering, for example, stress responses at multiple time points. This aids in searching for trait-specific changes in pathways using mutants or transgenics, analyzing development time-courses, and comparison between species. In a case study, we analyze the results of publicly available microarrays of multiple cold stress experiments using PageMan, and compare the results to a previously published meta-analysis.PageMan offers a complete user's guide, a web-based over-representation analysis as well as a tutorial, and is freely available at http://mapman.mpimp-golm.mpg.de/pageman/. PageMan allows multiple microarray experiments to be efficiently condensed into a single page graphical display. The flexible interface allows data to be quickly and easily visualized, facilitating comparisons within experiments and to published experiments, thus enabling researchers to gain a rapid overview of the biological responses in the experiments.
Bobe, Julien; Montfort, Jerôme; Nguyen, Thaovi; Fostier, Alexis
2006-01-01
Background The hormonal control of oocyte maturation and ovulation as well as the molecular mechanisms of nuclear maturation have been thoroughly studied in fish. In contrast, the other molecular events occurring in the ovary during post-vitellogenesis have received far less attention. Methods Nylon microarrays displaying 9152 rainbow trout cDNAs were hybridized using RNA samples originating from ovarian tissue collected during late vitellogenesis, post-vitellogenesis and oocyte maturation. Differentially expressed genes were identified using a statistical analysis. A supervised clustering analysis was performed using only differentially expressed genes in order to identify gene clusters exhibiting similar expression profiles. In addition, specific genes were selected and their preovulatory ovarian expression was analyzed using real-time PCR. Results From the statistical analysis, 310 differentially expressed genes were identified. Among those genes, 90 were up-regulated at the time of oocyte maturation while 220 exhibited an opposite pattern. After clustering analysis, 90 clones belonging to 3 gene clusters exhibiting the most remarkable expression patterns were kept for further analysis. Using real-time PCR analysis, we observed a strong up-regulation of ion and water transport genes such as aquaporin 4 (aqp4) and pendrin (slc26). In addition, a dramatic up-regulation of vasotocin (avt) gene was observed. Furthermore, angiotensin-converting-enzyme 2 (ace2), coagulation factor V (cf5), adam 22, and the chemokine cxcl14 genes exhibited a sharp up-regulation at the time of oocyte maturation. Finally, ovarian aromatase (cyp19a1) exhibited a dramatic down-regulation over the post-vitellogenic period while a down-regulation of Cytidine monophosphate-N-acetylneuraminic acid hydroxylase (cmah) was observed at the time of oocyte maturation. Conclusion We showed the over or under expression of more that 300 genes, most of them being previously unstudied or unknown in the fish preovulatory ovary. Our data confirmed the down-regulation of estrogen synthesis genes during the preovulatory period. In addition, the strong up-regulation of aqp4 and slc26 genes prior to ovulation suggests their participation in the oocyte hydration process occurring at that time. Furthermore, among the most up-regulated clones, several genes such as cxcl14, ace2, adam22, cf5 have pro-inflammatory, vasodilatory, proteolytics and coagulatory functions. The identity and expression patterns of those genes support the theory comparing ovulation to an inflammatory-like reaction. PMID:16872517
Similarities and Differences between Porcine Mandibular and Limb Bone Marrow Mesenchymal Stem Cells
Lloyd, Brandon; Tee, Boon Ching; Headley, Colwyn; Emam, Hany; Mallery, Susan; Sun, Zongyang
2017-01-01
Objective Research has shown promise of using bone marrow mesenchymal stem cells (BMSCs) for craniofacial bone regeneration; yet little is known about the differences of BMSCs from limb and craniofacial bones. This study compared pig mandibular and tibia BMSCs for their in vitro proliferation, osteogenic differentiation properties and gene expression. Design Bone marrow was aspirated from the tibia and mandible of 3–4 month-old pigs (n=4), followed by BMSC isolation, culture-expansion and characterization by flow cytometry. Proliferation rates were assessed using population doubling times. Osteogenic differentiation was evaluated by alkaline phosphatase activity. Affymetrix porcine microarray was used to compare gene expressions of tibial and mandibular BMSCs, followed by real-time RT-PCR evaluation of certain genes. Results Our results showed that BMSCs from both locations expressed MSC markers but not hematopoietic markers. The proliferation and osteogenic differentiation potential of mandibular BMSCs were significantly stronger than those of tibial BMSCs. Microarray analysis identified 404 highly abundant genes, out of which 334 genes were matched between the two locations and annotated into the same functional groups including osteogenesis and angiogenesis, while 70 genes were mismatched and annotated into different functional groups. In addition, 48 genes were differentially expressed by at least 1.5-fold difference between the two locations, including higher expression of cranial neural crest-related gene BMP-4 in mandibular BMSCs, which was confirmed by real-time RT-PCR. Conclusions Altogether, these data indicate that despite strong similarities in gene expression between mandibular and tibial BMSCs, mandibular BMSCs express some genes differently than tibial BMSCs and have a phenotypic profile that may make them advantageous for craniofacial bone regeneration. PMID:28135571
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.
Nonell, Lara; Puigdecanet, Eulàlia; Astier, Laura; Solé, Francesc; Bayes-Genis, Antoni
2013-01-01
Molecular mechanisms associated with pathophysiological changes in ventricular remodelling due to myocardial infarction (MI) remain poorly understood. We analyzed changes in gene expression by microarray technology in porcine myocardial tissue at 1, 4, and 6 weeks post-MI. MI was induced by coronary artery ligation in 9 female pigs (30–40 kg). Animals were randomly sacrificed at 1, 4, or 6 weeks post-MI (n = 3 per group) and 3 healthy animals were also included as control group. Total RNA from myocardial samples was hybridized to GeneChip® Porcine Genome Arrays. Functional analysis was obtained with the Ingenuity Pathway Analysis (IPA) online tool. Validation of microarray data was performed by quantitative real-time PCR (qRT-PCR). More than 8,000 different probe sets showed altered expression in the remodelling myocardium at 1, 4, or 6 weeks post-MI. Ninety-seven percent of altered transcripts were detected in the infarct core and 255 probe sets were differentially expressed in the remote myocardium. Functional analysis revealed 28 genes de-regulated in the remote myocardial region in at least one of the three temporal analyzed stages, including genes associated with heart failure (HF), systemic sclerosis and coronary artery disease. In the infarct core tissue, eight major time-dependent gene expression patterns were recognized among 4,221 probe sets commonly altered over time. Altered gene expression of ACVR2B, BID, BMP2, BMPR1A, LMNA, NFKBIA, SMAD1, TGFB3, TNFRSF1A, and TP53 were further validated. The clustering of similar expression patterns for gene products with related function revealed molecular footprints, some of them described for the first time, which elucidate changes in biological processes at different stages after MI. PMID:23372767
A proposed metric for assessing the measurement quality of individual microarrays
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
Baker, Valerie A; Harries, Helen M; Waring, Jeff F; Duggan, Colette M; Ni, Hong A; Jolly, Robert A; Yoon, Lawrence W; De Souza, Angus T; Schmid, Judith E; Brown, Roger H; Ulrich, Roger G; Rockett, John C
2004-01-01
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 reliability and interlaboratory reproducibility. As part of a series of studies conducted by the International Life Sciences Institute Health and Environmental Science Institute Technical Committee on the Application of Genomics to Mechanism-Based Risk Assessment, the biological response in rats to the hepatotoxin clofibrate was investigated. Animals were treated with high (250 mg/kg/day) or low (25 mg/kg/day) doses for 1, 3, or 7 days in two laboratories. Clinical chemistry parameters were measured, livers removed for histopathological assessment, and gene expression analysis was conducted using cDNA arrays. Expression changes in genes involved in fatty acid metabolism (e.g., acyl-CoA oxidase), cell proliferation (e.g., topoisomerase II-Alpha), and fatty acid oxidation (e.g., cytochrome P450 4A1), consistent with the mechanism of clofibrate hepatotoxicity, were detected. Observed differences in gene expression levels correlated with the level of biological response induced in the two in vivo studies. Generally, there was a high level of concordance between the gene expression profiles generated from pooled and individual RNA samples. Quantitative real-time polymerase chain reaction was used to confirm modulations for a number of peroxisome proliferator marker genes. Though the results indicate some variability in the quantitative nature of the microarray data, this appears due largely to differences in experimental and data analysis procedures used within each laboratory. In summary, this study demonstrates the potential for gene expression profiling to identify toxic hazards by the identification of mechanistically relevant markers of toxicity. PMID:15033592
The Changes of Gene Expression on Human Hair during Long-Spaceflight
NASA Astrophysics Data System (ADS)
Terada, Masahiro; Mukai, Chiaki; Ishioka, Noriaki; Majima, Hideyuki J.; Yamada, Shin; Seki, Masaya; Takahashi, Rika; Higashibata, Akira; Ohshima, Hiroshi; Sudoh, Masamichi; Minamisawa, Susumu
Hair has many advantages as the experimental sample. In a hair follicle, hair matrix cells actively divide and these active changes sensitively reflect physical condition on human body. The hair shaft records the metabolic conditions of mineral elements in our body. From human hairs, we can detect physiological informations about the human health. Therefore, we focused on using hair root analysis to understand the effects of spaceflight on astronauts. In 2009, we started a research program focusing on the analysis of astronauts’ hairs to examine the effects of long-term spaceflight on the gene expression in the human body. We want to get basic information to invent the effectivly diagnostic methods to detect the health situations of astronauts during space flight by analyzing human hair. We extracted RNA form the collected samples. Then, these extracted RNA was amplified. Amplified RNA was processed and hybridized to the Whole Human Genome (4×44K) Oligo Microarray (Agilent Technologies) according to the manufacturer’s protocol. Slide scanning was performed using the Agilent DNA Microarray Scanner. Scanning data were normalized with Agilent’s Feature Extraction software. Data preprocessing and analysis were performed using GeneSpring software 11.0.1. Next, Synthesis of cDNA (1 mg) was carried out using the PrimeScript RT reagent Kit (TaKaRa Bio) following the manufacturer’s instructions. The qRT-PCR experiment was performed with SYBR Premix Ex Taq (TaKaRa Bio) using the 7500 Real-Time PCR system (Applied Biosystems). We detected the changes of some gene expressions during spaceflight from both microarray and qRT-PCR data. These genes seems to be related with the hair proliferation. We believe that these results will lead to the discovery of the important factor effected during space flight on the hair.
Principles of gene microarray data analysis.
Mocellin, Simone; Rossi, Carlo Riccardo
2007-01-01
The development of several gene expression profiling methods, such as comparative genomic hybridization (CGH), differential display, serial analysis of gene expression (SAGE), and gene microarray, together with the sequencing of the human genome, has provided an opportunity to monitor and investigate the complex cascade of molecular events leading to tumor development and progression. The availability of such large amounts of information has shifted the attention of scientists towards a nonreductionist approach to biological phenomena. High throughput technologies can be used to follow changing patterns of gene expression over time. Among them, gene microarray has become prominent because it is easier to use, does not require large-scale DNA sequencing, and allows for the parallel quantification of thousands of genes from multiple samples. Gene microarray technology is rapidly spreading worldwide and has the potential to drastically change the therapeutic approach to patients affected with tumor. Therefore, it is of paramount importance for both researchers and clinicians to know the principles underlying the analysis of the huge amount of data generated with microarray technology.
Global transcriptional responses of Bacillus subtilis to xenocoumacin 1.
Zhou, T; Zeng, H; Qiu, D; Yang, X; Wang, B; Chen, M; Guo, L; Wang, S
2011-09-01
To determine the global transcriptional response of Bacillus subtilis to an antimicrobial agent, xenocoumacin 1 (Xcn1). Subinhibitory concentration of Xcn1 applied to B. subtilis was measured according to Hutter's method for determining optimal concentrations. cDNA microarray technology was used to study the global transcriptional response of B. subtilis to Xcn1. Real-time RT-PCR was employed to verify alterations in the transcript levels of six genes. The subinhibitory concentration was determined to be 1 μg ml(-1). The microarray data demonstrated that Xcn1 treatment of B. subtilis led to more than a 2.0-fold up-regulation of 480 genes and more than a 2.0-fold down-regulation of 479 genes (q ≤ 0.05). The transcriptional responses of B. subtilis to Xcn1 were determined, and several processes were affected by Xcn1. Additionally, cluster analysis of gene expression profiles after treatment with Xcn1 or 37 previously studied antibiotics indicated that Xcn1 has similar mechanisms of action to protein synthesis inhibitors. These microarray data showed alterations of gene expression in B. subtilis after exposure to Xcn1. From the results, we identified various processes affected by Xcn1. This study provides a whole-genome perspective to elucidate the action of Xcn1 as a potential antimicrobial agent. © 2011 The Authors. Journal of Applied Microbiology © 2011 The Society for Applied Microbiology.
Optimization of cDNA microarrays procedures using criteria that do not rely on external standards.
Bruland, Torunn; Anderssen, Endre; Doseth, Berit; Bergum, Hallgeir; Beisvag, Vidar; Laegreid, Astrid
2007-10-18
The measurement of gene expression using microarray technology is a complicated process in which a large number of factors can be varied. Due to the lack of standard calibration samples such as are used in traditional chemical analysis it may be a problem to evaluate whether changes done to the microarray procedure actually improve the identification of truly differentially expressed genes. The purpose of the present work is to report the optimization of several steps in the microarray process both in laboratory practices and in data processing using criteria that do not rely on external standards. We performed a cDNA microarry experiment including RNA from samples with high expected differential gene expression termed "high contrasts" (rat cell lines AR42J and NRK52E) compared to self-self hybridization, and optimized a pipeline to maximize the number of genes found to be differentially expressed in the "high contrasts" RNA samples by estimating the false discovery rate (FDR) using a null distribution obtained from the self-self experiment. The proposed high-contrast versus self-self method (HCSSM) requires only four microarrays per evaluation. The effects of blocking reagent dose, filtering, and background corrections methodologies were investigated. In our experiments a dose of 250 ng LNA (locked nucleic acid) dT blocker, no background correction and weight based filtering gave the largest number of differentially expressed genes. The choice of background correction method had a stronger impact on the estimated number of differentially expressed genes than the choice of filtering method. Cross platform microarray (Illumina) analysis was used to validate that the increase in the number of differentially expressed genes found by HCSSM was real. The results show that HCSSM can be a useful and simple approach to optimize microarray procedures without including external standards. Our optimizing method is highly applicable to both long oligo-probe microarrays which have become commonly used for well characterized organisms such as man, mouse and rat, as well as to cDNA microarrays which are still of importance for organisms with incomplete genome sequence information such as many bacteria, plants and fish.
Optimization of cDNA microarrays procedures using criteria that do not rely on external standards
Bruland, Torunn; Anderssen, Endre; Doseth, Berit; Bergum, Hallgeir; Beisvag, Vidar; Lægreid, Astrid
2007-01-01
Background The measurement of gene expression using microarray technology is a complicated process in which a large number of factors can be varied. Due to the lack of standard calibration samples such as are used in traditional chemical analysis it may be a problem to evaluate whether changes done to the microarray procedure actually improve the identification of truly differentially expressed genes. The purpose of the present work is to report the optimization of several steps in the microarray process both in laboratory practices and in data processing using criteria that do not rely on external standards. Results We performed a cDNA microarry experiment including RNA from samples with high expected differential gene expression termed "high contrasts" (rat cell lines AR42J and NRK52E) compared to self-self hybridization, and optimized a pipeline to maximize the number of genes found to be differentially expressed in the "high contrasts" RNA samples by estimating the false discovery rate (FDR) using a null distribution obtained from the self-self experiment. The proposed high-contrast versus self-self method (HCSSM) requires only four microarrays per evaluation. The effects of blocking reagent dose, filtering, and background corrections methodologies were investigated. In our experiments a dose of 250 ng LNA (locked nucleic acid) dT blocker, no background correction and weight based filtering gave the largest number of differentially expressed genes. The choice of background correction method had a stronger impact on the estimated number of differentially expressed genes than the choice of filtering method. Cross platform microarray (Illumina) analysis was used to validate that the increase in the number of differentially expressed genes found by HCSSM was real. Conclusion The results show that HCSSM can be a useful and simple approach to optimize microarray procedures without including external standards. Our optimizing method is highly applicable to both long oligo-probe microarrays which have become commonly used for well characterized organisms such as man, mouse and rat, as well as to cDNA microarrays which are still of importance for organisms with incomplete genome sequence information such as many bacteria, plants and fish. PMID:17949480
A New Modified Histogram Matching Normalization for Time Series Microarray Analysis.
Astola, Laura; Molenaar, Jaap
2014-07-01
Microarray data is often utilized in inferring regulatory networks. Quantile normalization (QN) is a popular method to reduce array-to-array variation. We show that in the context of time series measurements QN may not be the best choice for this task, especially not if the inference is based on continuous time ODE model. We propose an alternative normalization method that is better suited for network inference from time series data.
Form-Deprivation Myopia in Chick Induces Limited Changes in Retinal Gene Expression
McGlinn, Alice M.; Baldwin, Donald A.; Tobias, John W.; Budak, Murat T.; Khurana, Tejvir S.; Stone, Richard A.
2007-01-01
Purpose Evidence has implicated the retina as a principal controller of refractive development. In the present study, the retinal transcriptome was analyzed to identify alterations in gene expression and potential signaling pathways involved in form-deprivation myopia of the chick. Methods One-week-old white Leghorn chicks wore a unilateral image-degrading goggle for 6 hours or 3 days (n = 6 at each time). Total RNA from the retina/(retinal pigment epithelium) was used for expression profiling with chicken gene microarrays (Chicken GeneChips; Affymetrix, Santa Clara, CA). To identify gene expression level differences between goggled and contralateral nongoggled eyes, normalized microarray signal intensities were analyzed by the significance analysis of microarrays (SAM) approach. Differentially expressed genes were validated by real-time quantitative reverse transcription–polymerase chain reaction (qPCR) in independent biological replicates. Results Small changes were detected in differentially expressed genes in form-deprived eyes. In chickens that had 6 hours of goggle wear, downregulation of bone morphogenetic protein 2 and connective tissue growth factor was validated. In those with 3 days of goggle wear, downregulation of bone morphogenetic protein 2, vasoactive intestinal peptide, preopro-urotensin II–related peptide and mitogen-activated protein kinase phosphatase 2 was validated, and upregulation of endothelin receptor type B and interleukin-18 was validated. Conclusions Form-deprivation myopia, in its early stages, is associated with only minimal changes in retinal gene expression at the level of the transcriptome. While the list of validated genes is short, each merits further study for potential involvement in the signaling cascade mediating myopia development. PMID:17652709
Meade, Kieran G; Gormley, Eamonn; Park, Stephen D E; Fitzsimons, Tara; Rosa, Guilherme J M; Costello, Eamon; Keane, Joseph; Coussens, Paul M; MacHugh, David E
2006-09-15
Microarray analysis of messenger RNA (mRNA) abundance was used to investigate the gene expression program of peripheral blood mononuclear cells (PBMC) from cattle infected with Mycobacterium bovis, the causative agent of bovine tuberculosis. An immunospecific bovine microarray platform (BOTL-4) with spot features representing 1336 genes was used for transcriptional profiling of PBMC from six M. bovis-infected cattle stimulated in vitro with bovine purified protein derivative of tuberculin (PPD-bovine). Cells were harvested at four time points (3 h, 6 h, 12 h and 24 h post-stimulation) and a split-plot design with pooled samples was used for the microarray experiment to compare gene expression between PPD-bovine stimulated PBMC and unstimulated controls for each time point. Statistical analyses of these data revealed 224 genes (approximately 17% of transcripts on the array) differentially expressed between stimulated and unstimulated PBMC across the 24 h time course (P<0.05). Of the 224 genes, 87 genes were significantly upregulated and 137 genes were significantly downregulated in M. bovis-infected PBMC stimulated with PPD-bovine across the 24 h time course. However, perturbation of the PBMC transcriptome was most apparent at time points 3 h and 12 h post-stimulation, with 81 and 84 genes differentially expressed, respectively. In addition, a more stringent statistical threshold (P<0.01) revealed 35 genes (approximately 3%) that were differentially expressed across the time course. Real-time quantitative reverse transcription PCR (qRT-PCR) of selected genes validated the microarray results and demonstrated a wide range of differentially expressed genes in PPD-bovine-, PPD-avian- and Concanavalin A (ConA) stimulated PBMC, including the interferon-gamma gene (IFNG), which was upregulated in PBMC stimulated with PPD-bovine (40-fold), PPD-avian (10-fold) and ConA (8-fold) after in vitro culture for 12 h. The pattern of expression of these genes in PPD-bovine stimulated PBMC provides the first description of an M. bovis-specific signature of infection that may provide insights into the molecular basis of the host response to infection. Although the present study was carried out with mixed PBMC cell populations, it will guide future studies to dissect immune cell-specific gene expression patterns in response to M. bovis infection.
Bermudo, R; Abia, D; Mozos, A; García-Cruz, E; Alcaraz, A; Ortiz, Á R; Thomson, T M; Fernández, P L
2011-01-01
Introduction: Currently, final diagnosis of prostate cancer (PCa) is based on histopathological analysis of needle biopsies, but this process often bears uncertainties due to small sample size, tumour focality and pathologist's subjective assessment. Methods: Prostate cancer diagnostic signatures were generated by applying linear discriminant analysis to microarray and real-time RT–PCR (qRT–PCR) data from normal and tumoural prostate tissue samples. Additionally, after removal of biopsy tissues, material washed off from transrectal biopsy needles was used for molecular profiling and discriminant analysis. Results: Linear discriminant analysis applied to microarray data for a set of 318 genes differentially expressed between non-tumoural and tumoural prostate samples produced 26 gene signatures, which classified the 84 samples used with 100% accuracy. To identify signatures potentially useful for the diagnosis of prostate biopsies, surplus material washed off from routine biopsy needles from 53 patients was used to generate qRT–PCR data for a subset of 11 genes. This analysis identified a six-gene signature that correctly assigned the biopsies as benign or tumoural in 92.6% of the cases, with 88.8% sensitivity and 96.1% specificity. Conclusion: Surplus material from prostate needle biopsies can be used for minimal-size gene signature analysis for sensitive and accurate discrimination between non-tumoural and tumoural prostates, without interference with current diagnostic procedures. This approach could be a useful adjunct to current procedures in PCa diagnosis. PMID:22009027
Sayanthooran, Saravanabavan; Gunerathne, Lishanthe; Abeysekera, Tilak D J; Magana-Arachchi, Dhammika N
2018-05-28
Chronic kidney disease of unknown etiology (CKDu), having epidemic characteristics, is being diagnosed increasingly in certain tropical regions of the world, mainly Latin America and Sri Lanka. They have been observed primarily in farming communities and current hypotheses point toward many environmental and occupational triggers. CKDu does not have common etiologies of chronic kidney disease (CKD) such as hypertension, diabetes, or autoimmune disease. We aimed to understand the molecular processes underlying CKDu in Sri Lanka using transcriptome analysis. RNA extracted from whole blood was reverse transcribed and used for microarray analysis using the Human HT-12 v.4 array (Illumina). Pathway analysis was carried out using ingenuity pathway analysis (IPA-Qiagen). Microarray results were validated using real-time PCR of five selected genes. Pathways related to innate immune response, including interferon signaling, inflammasome signaling and TREM1 signaling had the most significant positive activation z scores, where as EIF2 signaling and mTOR signaling had the most significant negative activation z scores. Pathways previously linked to fluoride toxicity; G-protein activation, Cdc42 signaling, Rac signaling and RhoA signaling were activated in CKDu patients. The most significantly activated biological functions were cell death, cell movement and antimicrobial response. Significant toxicological functions were mitochondrial dysfunction, oxidative stress and apoptosis. Based on the molecular pathway analysis in CKDu patients and review of literature, viral infections and fluoride toxicity appear to be contributing to the molecular mechanisms underlying CKDu.
Fully automated analysis of multi-resolution four-channel micro-array genotyping data
NASA Astrophysics Data System (ADS)
Abbaspour, Mohsen; Abugharbieh, Rafeef; Podder, Mohua; Tebbutt, Scott J.
2006-03-01
We present a fully-automated and robust microarray image analysis system for handling multi-resolution images (down to 3-micron with sizes up to 80 MBs per channel). The system is developed to provide rapid and accurate data extraction for our recently developed microarray analysis and quality control tool (SNP Chart). Currently available commercial microarray image analysis applications are inefficient, due to the considerable user interaction typically required. Four-channel DNA microarray technology is a robust and accurate tool for determining genotypes of multiple genetic markers in individuals. It plays an important role in the state of the art trend where traditional medical treatments are to be replaced by personalized genetic medicine, i.e. individualized therapy based on the patient's genetic heritage. However, fast, robust, and precise image processing tools are required for the prospective practical use of microarray-based genetic testing for predicting disease susceptibilities and drug effects in clinical practice, which require a turn-around timeline compatible with clinical decision-making. In this paper we have developed a fully-automated image analysis platform for the rapid investigation of hundreds of genetic variations across multiple genes. Validation tests indicate very high accuracy levels for genotyping results. Our method achieves a significant reduction in analysis time, from several hours to just a few minutes, and is completely automated requiring no manual interaction or guidance.
Parallel processing of genomics data
NASA Astrophysics Data System (ADS)
Agapito, Giuseppe; Guzzi, Pietro Hiram; Cannataro, Mario
2016-10-01
The availability of high-throughput experimental platforms for the analysis of biological samples, such as mass spectrometry, microarrays and Next Generation Sequencing, have made possible to analyze a whole genome in a single experiment. Such platforms produce an enormous volume of data per single experiment, thus the analysis of this enormous flow of data poses several challenges in term of data storage, preprocessing, and analysis. To face those issues, efficient, possibly parallel, bioinformatics software needs to be used to preprocess and analyze data, for instance to highlight genetic variation associated with complex diseases. In this paper we present a parallel algorithm for the parallel preprocessing and statistical analysis of genomics data, able to face high dimension of data and resulting in good response time. The proposed system is able to find statistically significant biological markers able to discriminate classes of patients that respond to drugs in different ways. Experiments performed on real and synthetic genomic datasets show good speed-up and scalability.
Molecular methods for septicemia diagnosis.
Marco, Francesc
2017-11-01
Septicemia remains a major cause of hospital mortality. Blood culture remains the best approach to identify the etiological microorganisms when a bloodstream infection is suspected but it takes long time because it relies on bacterial or fungal growth. The introduction in clinical microbiology laboratories of the matrix-assisted laser desorption ionization time-of-flight mass spectrometry technology, DNA hybridization, microarrays or rapid PCR-based test significantly reduce the time to results. Tests for direct detection in whole blood samples are highly desirable because of their potential to identify bloodstream pathogens without waiting for blood cultures to become positive. Nonetheless, limitations of current molecular diagnostic methods are substantial. This article reviews these new molecular approaches (LightCycler SeptiFast, Magicplex sepsis real time, Septitest, VYOO, PCR/ESI-MS analysis, T2Candida). Copyright © 2017 Elsevier España, S.L.U. and Sociedad Española de Enfermedades Infecciosas y Microbiología Clínica. All rights reserved.
A New Modified Histogram Matching Normalization for Time Series Microarray Analysis
Astola, Laura; Molenaar, Jaap
2014-01-01
Microarray data is often utilized in inferring regulatory networks. Quantile normalization (QN) is a popular method to reduce array-to-array variation. We show that in the context of time series measurements QN may not be the best choice for this task, especially not if the inference is based on continuous time ODE model. We propose an alternative normalization method that is better suited for network inference from time series data. PMID:27600344
Hidayat, M F H; Milne, T; Cullinan, M P; Seymour, G J
2018-06-01
The salivary transcriptome may present as a readily available and non-invasive source of potential biomarkers. The development of chronic periodontitis is determined by individual patient susceptibility; hence, the aim of this study was to determine the potential of the salivary transcriptome as a biomarker of disease susceptibility using chronic periodontitis as an example. Using an Oragene ® RNA kit, the total RNA was purified from the saliva of 10 patients with chronic periodontitis and 10 patients without chronic periodontitis. The quantity and quality of the total RNA was determined, and a measure of gene expression via cDNA was undertaken using the Affymetrix microarray system. The microarray profiling result was further validated by real-time quantitative polymerase chain reaction. Spectrophotometric analysis showed the total RNA purified from each participant ranged from 0.92 μg/500 μL to 62.85 μg/500 μL. There was great variability in the quantity of total RNA obtained from the 2 groups in the study with a mean of 10.21 ± 12.71 μg/500 μL for the periodontitis group and 15.97 ± 23.47 μg/500 μL for the control group. Further the RNA purity (based on the A 260 /A 280 ratio) for the majority of participants (9 periodontitis and 6 controls) were within the acceptable limits for downstream analysis (2.0 ± 0.1). The study samples, showed 2 distinct bands at 23S (3800 bp) and 16S (1500 bp) characteristic of bacterial rRNA. Preliminary microarray analysis was performed for 4 samples (P2, P6, H5 and H9). The percentage of genes present in each of the 4 samples was not consistent with about 1.8%-18.7% of genes being detected. Quantitative real-time polymerase chain reaction confirmed that the total RNA purified from each sample was mainly bacterial RNA (Uni 16S) with minimal human mRNA. This study showed that minimal amounts of human RNA were able to be isolated from the saliva of patients with periodontitis as well as controls. Further work is required to enhance the extraction process of human mRNA from saliva if the salivary transcriptome is to be used in determining individual patient susceptibility. © 2017 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.
Gallou, Adrien; Declerck, Stéphane; Cranenbrouck, Sylvie
2012-03-01
The establishment of arbuscular mycorrhizal associations causes major changes in plant roots and affects significantly the host in term of plant nutrition and resistance against biotic and abiotic stresses. As a consequence, major changes in root transcriptome, especially in plant genes related to biotic stresses, are expected. Potato microarray analysis, followed by real-time quantitative PCR, was performed to detect the wide transcriptome changes induced during the pre-, early and late stages of potato root colonization by Glomus sp. MUCL 41833. The microarray analysis revealed 526 up-regulated and 132 down-regulated genes during the pre-stage, 272 up-regulated and 109 down-regulated genes during the early stage and 734 up-regulated and 122 down-regulated genes during the late stage of root colonization. The most important class of regulated genes was associated to plant stress and in particular to the WRKY transcription factors genes during the pre-stage of root colonization. The expression profiling clearly demonstrated a wide transcriptional change during the pre-, early and late stages of root colonization. It further suggested that the WRKY transcription factor genes are involved in the mechanisms controlling the arbuscular mycorrhizal establishment by the regulation of plant defence genes.
Altered Expression of Diabetes-Related Genes in Alzheimer's Disease Brains: The Hisayama Study
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
Identification of the Key Genes and Pathways in Esophageal Carcinoma.
Su, Peng; Wen, Shiwang; Zhang, Yuefeng; Li, Yong; Xu, Yanzhao; Zhu, Yonggang; Lv, Huilai; Zhang, Fan; Wang, Mingbo; Tian, Ziqiang
2016-01-01
Objective . Esophageal carcinoma (EC) is a frequently common malignancy of gastrointestinal cancer in the world. This study aims to screen key genes and pathways in EC and elucidate the mechanism of it. Methods . 5 microarray datasets of EC were downloaded from Gene Expression Omnibus. Differentially expressed genes (DEGs) were screened by bioinformatics analysis. Gene Ontology (GO) enrichment, Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment, and protein-protein interaction (PPI) network construction were performed to obtain the biological roles of DEGs in EC. Quantitative real-time polymerase chain reaction (qRT-PCR) was used to verify the expression level of DEGs in EC. Results . A total of 1955 genes were filtered as DEGs in EC. The upregulated genes were significantly enriched in cell cycle and the downregulated genes significantly enriched in Endocytosis. PPI network displayed CDK4 and CCT3 were hub proteins in the network. The expression level of 8 dysregulated DEGs including CDK4, CCT3, THSD4, SIM2, MYBL2, CENPF, CDCA3, and CDKN3 was validated in EC compared to adjacent nontumor tissues and the results were matched with the microarray analysis. Conclusion . The significantly DEGs including CDK4, CCT3, THSD4, and SIM2 may play key roles in tumorigenesis and development of EC involved in cell cycle and Endocytosis.
Long noncoding RNA OR3A4 promotes metastasis and tumorigenicity in gastric cancer
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
Bökenkamp, Regina; van Brempt, Ronald; van Munsteren, Jacoba Cornelia; van den Wijngaert, Ilse; de Hoogt, Ronald; Finos, Livio; Goeman, Jelle; Groot, Adriana Cornelia Gittenberger-de; Poelmann, Robert Eugen; Blom, Nicolaas Andreas; DeRuiter, Marcus Cornelis
2014-01-01
Closure of the ductus arteriosus (DA) is a crucial step in the transition from fetal to postnatal life. Patent DA is one of the most common cardiovascular anomalies in children with significant clinical consequences especially in premature infants. We aimed to identify genes that specify the DA in the fetus and differentiate it from the aorta. Comparative microarray analysis of laser-captured microdissected endothelial (ECs) and vascular smooth muscle cells (SMCs) from the DA and aorta of fetal rats (embryonic day 18 and 21) identified vessel-specific transcriptional profiles. We found a strong age-dependency of gene expression. Among the genes that were upregulated in the DA the regulator of the G-protein coupled receptor 5 (Rgs5) and the transcription factor distal-less homeobox 1 (Dlx1) exhibited the highest and most significant level of differential expression. The aorta showed a significant preferential expression of the Purkinje cell protein 4 (Pcp4) gene. The results of the microarray analysis were validated by real-time quantitative PCR and immunohistochemistry. Our study confirms vessel-specific transcriptional profiles in ECs and SMCs of rat DA and aorta. Rgs5 and Dlx1 represent novel molecular targets for the regulation of DA maturation and closure. PMID:24489801
NASA Astrophysics Data System (ADS)
Vukanti, R. V.; Mintz, E. M.; Leff, L. G.
2005-05-01
Bacterial responses to environmental signals are multifactorial and are coupled to changes in gene expression. An understanding of bacterial responses to environmental conditions is possible using microarray expression analysis. In this study, the utility of microarrays for examining changes in gene expression in Escherichia coli under different environmental conditions was assessed. RNA was isolated, hybridized to Affymetrix E. coli Genome 2.0 chips and analyzed using Affymetrix GCOS and Genespring software. Major limiting factors were obtaining enough quality RNA (107-108 cells to get 10μg RNA)and accounting for differences in growth rates under different conditions. Stabilization of RNA prior to isolation and taking extreme precautions while handling RNA were crucial. In addition, use of this method in ecological studies is limited by availability and cost of commercial arrays; choice of primers for cDNA synthesis, reproducibility, complexity of results generated and need to validate findings. This method may be more widely applicable with the development of better approaches for RNA recovery from environmental samples and increased number of available strain-specific arrays. Diligent experimental design and verification of results with real-time PCR or northern blots is needed. Overall, there is a great potential for use of this technology to discover mechanisms underlying organisms' responses to environmental conditions.
A close examination of double filtering with fold change and t test in microarray analysis
2009-01-01
Background Many researchers use the double filtering procedure with fold change and t test to identify differentially expressed genes, in the hope that the double filtering will provide extra confidence in the results. Due to its simplicity, the double filtering procedure has been popular with applied researchers despite the development of more sophisticated methods. Results This paper, for the first time to our knowledge, provides theoretical insight on the drawback of the double filtering procedure. We show that fold change assumes all genes to have a common variance while t statistic assumes gene-specific variances. The two statistics are based on contradicting assumptions. Under the assumption that gene variances arise from a mixture of a common variance and gene-specific variances, we develop the theoretically most powerful likelihood ratio test statistic. We further demonstrate that the posterior inference based on a Bayesian mixture model and the widely used significance analysis of microarrays (SAM) statistic are better approximations to the likelihood ratio test than the double filtering procedure. Conclusion We demonstrate through hypothesis testing theory, simulation studies and real data examples, that well constructed shrinkage testing methods, which can be united under the mixture gene variance assumption, can considerably outperform the double filtering procedure. PMID:19995439
Different responses to oxidized low-density lipoproteins in human polarized macrophages
2011-01-01
Background Oxidized low-density lipoprotein (oxLDL) uptake by macrophages plays an important role in foam cell formation. It has been suggested the presence of heterogeneous subsets of macrophage, such as M1 and M2, in human atherosclerotic lesions. To evaluate which types of macrophages contribute to atherogenesis, we performed cDNA microarray analysis to determine oxLDL-induced transcriptional alterations of each subset of macrophages. Results Human monocyte-derived macrophages were polarized toward the M1 or M2 subset, followed by treatment with oxLDL. Then gene expression levels during oxLDL treatment in each subset of macrophages were evaluated by cDNA microarray analysis and quantitative real-time RT-PCR. In terms of high-ranking upregulated genes and functional ontologies, the alterations during oxLDL treatment in M2 macrophages were similar to those in nonpolarized macrophages (M0). Molecular network analysis showed that most of the molecules in the oxLDL-induced highest scoring molecular network of M1 macrophages were directly or indirectly related to transforming growth factor (TGF)-β1. Hierarchical cluster analysis revealed commonly upregulated genes in all subset of macrophages, some of which contained antioxidant response elements (ARE) in their promoter regions. A cluster of genes that were specifically upregulated in M1 macrophages included those encoding molecules related to nuclear factor of kappa light polypeptide gene enhancer in B-cells (NF-κB) signaling pathway. Quantitative real-time RT-PCR showed that the gene expression of interleukin (IL)-8 after oxLDL treatment in M2 macrophages was markedly lower than those in M0 and M1 cells. HMOX1 gene expression levels were almost the same in all 3 subsets of macrophages even after oxLDL treatment. Conclusions The present study demonstrated transcriptional alterations in polarized macrophages during oxLDL treatment. The data suggested that oxLDL uptake may affect TGF-β1- and NF-κB-mediated functions of M1 macrophages, but not those of M0 or M2 macrophages. It is likely that M1 macrophages characteristically respond to oxLDL. PMID:21199582
Discovery of error-tolerant biclusters from noisy gene expression data.
Gupta, Rohit; Rao, Navneet; Kumar, Vipin
2011-11-24
An important analysis performed on microarray gene-expression data is to discover biclusters, which denote groups of genes that are coherently expressed for a subset of conditions. Various biclustering algorithms have been proposed to find different types of biclusters from these real-valued gene-expression data sets. However, these algorithms suffer from several limitations such as inability to explicitly handle errors/noise in the data; difficulty in discovering small bicliusters due to their top-down approach; inability of some of the approaches to find overlapping biclusters, which is crucial as many genes participate in multiple biological processes. Association pattern mining also produce biclusters as their result and can naturally address some of these limitations. However, traditional association mining only finds exact biclusters, which limits its applicability in real-life data sets where the biclusters may be fragmented due to random noise/errors. Moreover, as they only work with binary or boolean attributes, their application on gene-expression data require transforming real-valued attributes to binary attributes, which often results in loss of information. Many past approaches have tried to address the issue of noise and handling real-valued attributes independently but there is no systematic approach that addresses both of these issues together. In this paper, we first propose a novel error-tolerant biclustering model, 'ET-bicluster', and then propose a bottom-up heuristic-based mining algorithm to sequentially discover error-tolerant biclusters directly from real-valued gene-expression data. The efficacy of our proposed approach is illustrated by comparing it with a recent approach RAP in the context of two biological problems: discovery of functional modules and discovery of biomarkers. For the first problem, two real-valued S.Cerevisiae microarray gene-expression data sets are used to demonstrate that the biclusters obtained from ET-bicluster approach not only recover larger set of genes as compared to those obtained from RAP approach but also have higher functional coherence as evaluated using the GO-based functional enrichment analysis. The statistical significance of the discovered error-tolerant biclusters as estimated by using two randomization tests, reveal that they are indeed biologically meaningful and statistically significant. For the second problem of biomarker discovery, we used four real-valued Breast Cancer microarray gene-expression data sets and evaluate the biomarkers obtained using MSigDB gene sets. The results obtained for both the problems: functional module discovery and biomarkers discovery, clearly signifies the usefulness of the proposed ET-bicluster approach and illustrate the importance of explicitly incorporating noise/errors in discovering coherent groups of genes from gene-expression data.
Microarray analysis of pancreatic gene expression during biotin repletion in biotin-deficient rats.
Dakshinamurti, Krishnamurti; Bagchi, Rushita A; Abrenica, Bernard; Czubryt, Michael P
2015-12-01
Biotin is a B vitamin involved in multiple metabolic pathways. In humans, biotin deficiency is relatively rare but can cause dermatitis, alopecia, and perosis. Low biotin levels occur in individuals with type-2 diabetes, and supplementation with biotin plus chromium may improve blood sugar control. The acute effect on pancreatic gene expression of biotin repletion following chronic deficiency is unclear, therefore we induced biotin deficiency in adult male rats by feeding them a 20% raw egg white diet for 6 weeks. Animals were then randomized into 2 groups: one group received a single biotin supplement and returned to normal chow lacking egg white, while the second group remained on the depletion diet. After 1 week, pancreata were removed from biotin-deficient (BD) and biotin-repleted (BR) animals and RNA was isolated for microarray analysis. Biotin depletion altered gene expression in a manner indicative of inflammation, fibrosis, and defective pancreatic function. Conversely, biotin repletion activated numerous repair and anti-inflammatory pathways, reduced fibrotic gene expression, and induced multiple genes involved in pancreatic endocrine and exocrine function. A subset of the results was confirmed by quantitative real-time PCR analysis, as well as by treatment of pancreatic AR42J cells with biotin. The results indicate that biotin repletion, even after lengthy deficiency, results in the rapid induction of repair processes in the pancreas.
FH535, a β-catenin pathway inhibitor, represses pancreatic cancer xenograft growth and angiogenesis
Gong, Fei-Ran; Zhou, Binhua P.; Lian, Lian; Shen, Bairong; Chen, Kai; Duan, Weiming; Wu, Meng-Yao; Tao, Min; Li, Wei
2016-01-01
The WNT/β-catenin pathway plays an important role in pancreatic cancer carcinogenesis. We evaluated the correlation between aberrant β-catenin pathway activation and the prognosis pancreatic cancer, and the potential of applying the β-catenin pathway inhibitor FH535 to pancreatic cancer treatment. Meta-analysis and immunohistochemistry showed that abnormal β-catenin pathway activation was associated with unfavorable outcome. FH535 repressed pancreatic cancer xenograft growth in vivo. Gene Ontology (GO) analysis of microarray data indicated that target genes responding to FH535 participated in stemness maintenance. Real-time PCR and flow cytometry confirmed that FH535 downregulated CD24 and CD44, pancreatic cancer stem cell (CSC) markers, suggesting FH535 impairs pancreatic CSC stemness. GO analysis of β-catenin chromatin immunoprecipitation sequencing data identified angiogenesis-related gene regulation. Immunohistochemistry showed that higher microvessel density correlated with elevated nuclear β-catenin expression and unfavorable outcome. FH535 repressed the secretion of the proangiogenic cytokines vascular endothelial growth factor (VEGF), interleukin (IL)-6, IL-8, and tumor necrosis factor-α, and also inhibited angiogenesis in vitro and in vivo. Protein and mRNA microarrays revealed that FH535 downregulated the proangiogenic genes ANGPT2, VEGFR3, IFN-γ, PLAUR, THPO, TIMP1, and VEGF. FH535 not only represses pancreatic CSC stemness in vitro, but also remodels the tumor microenvironment by repressing angiogenesis, warranting further clinical investigation. PMID:27323403
Quinn, Patrick; Bowers, Robert M; Zhang, Xiaoyu; Wahlund, Thomas M; Fanelli, Michael A; Olszova, Daniela; Read, Betsy A
2006-08-01
Marine unicellular coccolithophore algae produce species-specific calcite scales otherwise known as coccoliths. While the coccoliths and their elaborate architecture have attracted the attention of investigators from various scientific disciplines, our knowledge of the underpinnings of the process of biomineralization in this alga is still in its infancy. The processes of calcification and coccolithogenesis are highly regulated and likely to be complex, requiring coordinated expression of many genes and pathways. In this study, we have employed cDNA microarrays to investigate changes in gene expression associated with biomineralization in the most abundant coccolithophorid, Emiliania huxleyi. Expression profiling of cultures grown under calcifying and noncalcifying conditions has been carried out using cDNA microarrays corresponding to approximately 2,300 expressed sequence tags. A total of 127 significantly up- or down-regulated transcripts were identified using a P value of 0.01 and a change of >2.0-fold. Real-time reverse transcriptase PCR was used to test the overall validity of the microarray data, as well as the relevance of many of the proteins predicted to be associated with biomineralization, including a novel gamma-class carbonic anhydrase (A. R. Soto, H. Zheng, D. Shoemaker, J. Rodriguez, B. A. Read, and T. M. Wahlund, Appl. Environ. Microbiol. 72:5500-5511, 2006). Differentially regulated genes include those related to cellular metabolism, ion channels, transport proteins, vesicular trafficking, and cell signaling. The putative function of the vast majority of candidate transcripts could not be defined. Nonetheless, the data described herein represent profiles of the transcription changes associated with biomineralization-related pathways in E. huxleyi and have identified novel and potentially useful targets for more detailed analysis.
Quinn, Patrick; Bowers, Robert M.; Zhang, Xiaoyu; Wahlund, Thomas M.; Fanelli, Michael A.; Olszova, Daniela; Read, Betsy A.
2006-01-01
Marine unicellular coccolithophore algae produce species-specific calcite scales otherwise known as coccoliths. While the coccoliths and their elaborate architecture have attracted the attention of investigators from various scientific disciplines, our knowledge of the underpinnings of the process of biomineralization in this alga is still in its infancy. The processes of calcification and coccolithogenesis are highly regulated and likely to be complex, requiring coordinated expression of many genes and pathways. In this study, we have employed cDNA microarrays to investigate changes in gene expression associated with biomineralization in the most abundant coccolithophorid, Emiliania huxleyi. Expression profiling of cultures grown under calcifying and noncalcifying conditions has been carried out using cDNA microarrays corresponding to approximately 2,300 expressed sequence tags. A total of 127 significantly up- or down-regulated transcripts were identified using a P value of 0.01 and a change of >2.0-fold. Real-time reverse transcriptase PCR was used to test the overall validity of the microarray data, as well as the relevance of many of the proteins predicted to be associated with biomineralization, including a novel gamma-class carbonic anhydrase (A. R. Soto, H. Zheng, D. Shoemaker, J. Rodriguez, B. A. Read, and T. M. Wahlund, Appl. Environ. Microbiol. 72:5500-5511, 2006). Differentially regulated genes include those related to cellular metabolism, ion channels, transport proteins, vesicular trafficking, and cell signaling. The putative function of the vast majority of candidate transcripts could not be defined. Nonetheless, the data described herein represent profiles of the transcription changes associated with biomineralization-related pathways in E. huxleyi and have identified novel and potentially useful targets for more detailed analysis. PMID:16885305
Dai, Yilin; Guo, Ling; Li, Meng; Chen, Yi-Bu
2012-06-08
Microarray data analysis presents a significant challenge to researchers who are unable to use the powerful Bioconductor and its numerous tools due to their lack of knowledge of R language. Among the few existing software programs that offer a graphic user interface to Bioconductor packages, none have implemented a comprehensive strategy to address the accuracy and reliability issue of microarray data analysis due to the well known probe design problems associated with many widely used microarray chips. There is also a lack of tools that would expedite the functional analysis of microarray results. We present Microarray Я US, an R-based graphical user interface that implements over a dozen popular Bioconductor packages to offer researchers a streamlined workflow for routine differential microarray expression data analysis without the need to learn R language. In order to enable a more accurate analysis and interpretation of microarray data, we incorporated the latest custom probe re-definition and re-annotation for Affymetrix and Illumina chips. A versatile microarray results output utility tool was also implemented for easy and fast generation of input files for over 20 of the most widely used functional analysis software programs. Coupled with a well-designed user interface, Microarray Я US leverages cutting edge Bioconductor packages for researchers with no knowledge in R language. It also enables a more reliable and accurate microarray data analysis and expedites downstream functional analysis of microarray results.
Implementation of mutual information and bayes theorem for classification microarray data
NASA Astrophysics Data System (ADS)
Dwifebri Purbolaksono, Mahendra; Widiastuti, Kurnia C.; Syahrul Mubarok, Mohamad; Adiwijaya; Aminy Ma’ruf, Firda
2018-03-01
Microarray Technology is one of technology which able to read the structure of gen. The analysis is important for this technology. It is for deciding which attribute is more important than the others. Microarray technology is able to get cancer information to diagnose a person’s gen. Preparation of microarray data is a huge problem and takes a long time. That is because microarray data contains high number of insignificant and irrelevant attributes. So, it needs a method to reduce the dimension of microarray data without eliminating important information in every attribute. This research uses Mutual Information to reduce dimension. System is built with Machine Learning approach specifically Bayes Theorem. This theorem uses a statistical and probability approach. By combining both methods, it will be powerful for Microarray Data Classification. The experiment results show that system is good to classify Microarray data with highest F1-score using Bayesian Network by 91.06%, and Naïve Bayes by 88.85%.
Sun, Yung-Shin; Zhu, Xiangdong
2016-10-01
Microarrays provide a platform for high-throughput characterization of biomolecular interactions. To increase the sensitivity and specificity of microarrays, surface blocking is required to minimize the nonspecific interactions between analytes and unprinted yet functionalized surfaces. To block amine- or epoxy-functionalized substrates, bovine serum albumin (BSA) is one of the most commonly used blocking reagents because it is cheap and easy to use. Based on standard protocols from microarray manufactories, a BSA concentration of 1% (10 mg/mL or 200 μM) and reaction time of at least 30 min are required to efficiently block epoxy-coated slides. In this paper, we used both fluorescent and label-free methods to characterize the BSA blocking efficiency on epoxy-functionalized substrates. The blocking efficiency of BSA was characterized using a fluorescent scanner and a label-free oblique-incidence reflectivity difference (OI-RD) microscope. We found that (1) a BSA concentration of 0.05% (0.5 mg/mL or 10 μM) could give a blocking efficiency of 98%, and (2) the BSA blocking step took only about 5 min to be complete. Also, from real-time and in situ measurements, we were able to calculate the conformational properties (thickness, mass density, and number density) of BSA molecules deposited on the epoxy surface. © 2015 Society for Laboratory Automation and Screening.
Molecular diagnostics of periodontitis.
Korona-Głowniak, Izabela; Siwiec, Radosław; Berger, Marcin; Malm, Anna; Szymańska, Jolanta
2017-01-28
The microorganisms that form dental plaque are the main cause of periodontitis. Their identification and the understanding of the complex relationships and interactions that involve these microorganisms, environmental factors and the host's health status enable improvement in diagnostics and targeted therapy in patients with periodontitis. To this end, molecular diagnostics techniques (both techniques based on the polymerase chain reaction and those involving nucleic acid analysis via hybridization) come increasingly into use. On the basis of a literature review, the following methods are presented: polymerase chain reaction (PCR), real-time polymerase chain reaction (real-time PCR), 16S rRNA-encoding gene sequencing, checkerboard and reverse-capture checkerboard hybridization, microarrays, denaturing gradient gel electrophoresis (DGGE), temperature gradient gel electrophoresis (TGGE), as well as terminal restriction fragment length polymorphism (TRFLP) and next generation sequencing (NGS). The advantages and drawbacks of each method in the examination of periopathogens are indicated. The techniques listed above allow fast detection of even small quantities of pathogen present in diagnostic material and prove particularly useful to detect microorganisms that are difficult or impossible to grow in a laboratory.
Ide, Takashi
2014-08-14
In the present study, the mRNA levels of hepatic proteins involved in the drug metabolism of rats fed α-lipoic acid were evaluated by DNA microarray and real-time PCR analyses. Experimental diets containing 0, 0·1, 0·25 and 0·5 % (w/w) α-lipoic acid were fed to four groups of rats consisting of seven animals each for 21 d. DNA microarray analysis revealed that the diet containing 0·5 % α-lipoic acid significantly (P< 0·05) increased the mRNA levels of various phase I drug-metabolising enzymes up to 15-fold and phase II enzymes up to 52-fold in an isoenzyme-specific manner. α-Lipoic acid also up-regulated the mRNA levels of some members of the ATP-binding cassette transporter superfamily, presumed to be involved in the exportation of xenobiotics, up to 6·6-fold. In addition, we observed that α-lipoic acid increased the mRNA levels of many proteins involved in antioxidation, such as members of the thiol redox system (up to 5·5-fold), metallothioneins (up to 12-fold) and haeme oxygenase 1 (1·5-fold). These results were confirmed using real-time PCR analysis, and α-lipoic acid dose dependently increased the mRNA levels of various proteins involved in drug metabolism and antioxidation. Consistent with these observations, α-lipoic acid dose dependently increased the hepatic concentration of glutathione and the activities of glutathione reductase and glutathione transferase measured using 1-chloro-2,4-dinitrobenzene and 1,2-dichloro-4-nitrobenzene as substrates, but decreased the hepatic and serum concentrations of malondialdehyde. In conclusion, the present study unequivocally demonstrated that α-lipoic acid increases the mRNA expression of proteins involved in drug metabolism and antioxidation in the liver.
Tanaka, Yohei; Nakayama, Jun
2016-01-01
Humans are increasingly exposed to near-infrared (NIR) radiation from both natural (eg, solar) and artificial (eg, electrical appliances) sources. Although the biological effects of sun and ultraviolet (UV) exposure have been extensively investigated, the biological effect of NIR radiation is still unclear. We previously reported that NIR as well as UV induces photoaging and standard UV-blocking materials, such as sunglasses, do not sufficiently block NIR. The objective of this study was to investigate changes in gene expression in three-dimensional reconstructed corneal epithelial tissue culture exposed to broad-spectrum NIR irradiation to simulate solar NIR radiation that reaches human tissues. DNA microarray and quantitative real-time polymerase chain reaction analysis were used to assess gene expression levels in a three-dimensional reconstructed corneal epithelial model composed of normal human corneal epithelial cells exposed to water-filtered broad-spectrum NIR irradiation with a contact cooling (20°C). The water-filter allowed 1,000-1,800 nm wavelengths and excluded 1,400-1,500 nm wavelengths. A DNA microarray with >62,000 different probes showed 25 and 150 genes that were up- or downregulated by at least fourfold and twofold, respectively, after NIR irradiation. In particular, epidermal growth factor receptor (EGFR) was upregulated by 19.4-fold relative to control cells. Quantitative real-time polymerase chain reaction analysis revealed that two variants of EGFR in human corneal epithelial tissue were also significantly upregulated after five rounds of 10 J/cm(2) irradiation (P<0.05). We found that NIR irradiation induced the upregulated expression of EGFR in human corneal cells. Since over half of the solar energy reaching the Earth is in the NIR region, which cannot be adequately blocked by eyewear and thus can induce eye damage with intensive or long-term exposure, protection from both UV and NIR radiation may prevent changes in gene expression and in turn eye damage.
Madanecki, Piotr; Bałut, Magdalena; Buckley, Patrick G; Ochocka, J Renata; Bartoszewski, Rafał; Crossman, David K; Messiaen, Ludwine M; Piotrowski, Arkadiusz
2018-01-01
High-throughput technologies generate considerable amount of data which often requires bioinformatic expertise to analyze. Here we present High-Throughput Tabular Data Processor (HTDP), a platform independent Java program. HTDP works on any character-delimited column data (e.g. BED, GFF, GTF, PSL, WIG, VCF) from multiple text files and supports merging, filtering and converting of data that is produced in the course of high-throughput experiments. HTDP can also utilize itemized sets of conditions from external files for complex or repetitive filtering/merging tasks. The program is intended to aid global, real-time processing of large data sets using a graphical user interface (GUI). Therefore, no prior expertise in programming, regular expression, or command line usage is required of the user. Additionally, no a priori assumptions are imposed on the internal file composition. We demonstrate the flexibility and potential of HTDP in real-life research tasks including microarray and massively parallel sequencing, i.e. identification of disease predisposing variants in the next generation sequencing data as well as comprehensive concurrent analysis of microarray and sequencing results. We also show the utility of HTDP in technical tasks including data merge, reduction and filtering with external criteria files. HTDP was developed to address functionality that is missing or rudimentary in other GUI software for processing character-delimited column data from high-throughput technologies. Flexibility, in terms of input file handling, provides long term potential functionality in high-throughput analysis pipelines, as the program is not limited by the currently existing applications and data formats. HTDP is available as the Open Source software (https://github.com/pmadanecki/htdp).
Bałut, Magdalena; Buckley, Patrick G.; Ochocka, J. Renata; Bartoszewski, Rafał; Crossman, David K.; Messiaen, Ludwine M.; Piotrowski, Arkadiusz
2018-01-01
High-throughput technologies generate considerable amount of data which often requires bioinformatic expertise to analyze. Here we present High-Throughput Tabular Data Processor (HTDP), a platform independent Java program. HTDP works on any character-delimited column data (e.g. BED, GFF, GTF, PSL, WIG, VCF) from multiple text files and supports merging, filtering and converting of data that is produced in the course of high-throughput experiments. HTDP can also utilize itemized sets of conditions from external files for complex or repetitive filtering/merging tasks. The program is intended to aid global, real-time processing of large data sets using a graphical user interface (GUI). Therefore, no prior expertise in programming, regular expression, or command line usage is required of the user. Additionally, no a priori assumptions are imposed on the internal file composition. We demonstrate the flexibility and potential of HTDP in real-life research tasks including microarray and massively parallel sequencing, i.e. identification of disease predisposing variants in the next generation sequencing data as well as comprehensive concurrent analysis of microarray and sequencing results. We also show the utility of HTDP in technical tasks including data merge, reduction and filtering with external criteria files. HTDP was developed to address functionality that is missing or rudimentary in other GUI software for processing character-delimited column data from high-throughput technologies. Flexibility, in terms of input file handling, provides long term potential functionality in high-throughput analysis pipelines, as the program is not limited by the currently existing applications and data formats. HTDP is available as the Open Source software (https://github.com/pmadanecki/htdp). PMID:29432475
A phenotypic comparison of intervertebral disc and articular cartilage cells in the rat
Lee, Cynthia R.; Sakai, Daisuke; Nakai, Tomoko; Toyama, Kanae; Mochida, Joji; Alini, Mauro
2007-01-01
The basic molecular characteristics of intervertebral disc cells are still poorly defined. This study compared the phenotypes of nucleus pulposus (NP), annulus fibrosus (AF) and articular cartilage (AC) cells using rat coccygeal discs and AC from both young and aged animals and a combination of microarray, real-time RT-PCR and immunohistochemistry. Microarray analysis identified 63 genes with at least a fivefold difference in fluorescence intensity between the NP and AF cells and 41 genes with a fivefold or greater difference comparing NP cells and articular chondrocytes. In young rats, the relative mRNA levels, assessed by real-time RT-PCR, of annexin A3, glypican 3 (gpc3), keratin 19 (k19) and pleiotrophin (ptn) were significantly higher in NP compared to AF and AC samples. Furthermore, vimentin (vim) mRNA was higher in NP versus AC, and expression levels of cartilage oligomeric matrix protein (comp) and matrix gla protein (mgp) were lower in NP versus AC. Higher NP levels of comp and mgp mRNA and higher AF levels of gpc3, k19, mgp and ptn mRNA were found in aged compared to young tissue. However, the large differences between NP and AC expression of gpc3 and k19 were obvious even in the aged animals. Furthermore, the differences in expression levels of gpc3 and k19 were also evident at the protein level, with intense immunostaining for both proteins in NP and non-existent immunoreaction in AF and AC. Future studies using different species are required to evaluate whether the expression of these molecules can be used to characterize NP cells and distinguish them from other chondrocyte-like cells. PMID:17786487
English, Sangeeta B.; Shih, Shou-Ching; Ramoni, Marco F.; Smith, Lois E.; Butte, Atul J.
2014-01-01
Though genome-wide technologies, such as microarrays, are widely used, data from these methods are considered noisy; there is still varied success in downstream biological validation. We report a method that increases the likelihood of successfully validating microarray findings using real time RT-PCR, including genes at low expression levels and with small differences. We use a Bayesian network to identify the most relevant sources of noise based on the successes and failures in validation for an initial set of selected genes, and then improve our subsequent selection of genes for validation based on eliminating these sources of noise. The network displays the significant sources of noise in an experiment, and scores the likelihood of validation for every gene. We show how the method can significantly increase validation success rates. In conclusion, in this study, we have successfully added a new automated step to determine the contributory sources of noise that determine successful or unsuccessful downstream biological validation. PMID:18790084
A meta-data based method for DNA microarray imputation.
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.
Melendez, Roberto I.; McGinty, Jacqueline F.; Kalivas, Peter W.; Becker, Howard C.
2014-01-01
Neuroadaptations that participate in the ontogeny of alcohol dependence are likely a result of altered gene expression in various brain regions. The present study investigated brain region-specific changes in the pattern and magnitude of gene expression immediately following chronic intermittent ethanol (CIE) exposure and 8 hours following final ethanol exposure [i.e. early withdrawal (EWD)]. High-density oligonucleotide microarrays (Affymetrix 430A 2.0, Affymetrix, Santa Clara, CA, USA) and bioinformatics analysis were used to characterize gene expression and function in the prefrontal cortex (PFC), hippocampus (HPC) and nucleus accumbens (NAc) of C57BL/6J mice (Jackson Laboratories, Bar Harbor, ME, USA). Gene expression levels were determined using gene chip robust multi-array average followed by statistical analysis of microarrays and validated by quantitative real-time reverse transcription polymerase chain reaction and Western blot analysis. Results indicated that immediately following CIE exposure, changes in gene expression were strikingly greater in the PFC (284 genes) compared with the HPC (16 genes) and NAc (32 genes). Bioinformatics analysis revealed that most of the transcriptionally responsive genes in the PFC were involved in Ras/MAPK signaling, notch signaling or ubiquitination. In contrast, during EWD, changes in gene expression were greatest in the HPC (139 genes) compared with the PFC (four genes) and NAc (eight genes). The most transcriptionally responsive genes in the HPC were involved in mRNA processing or actin dynamics. Of the few genes detected in the NAc, the most representatives were involved in circadian rhythms. Overall, these findings indicate that brain region-specific and time-dependent neuroadaptive alterations in gene expression play an integral role in the development of alcohol dependence and withdrawal. PMID:21812870
Li, Xuejie; Zhao, Zhenzhou; Jian, Dongdong; Li, Wentao; Tang, Haiyu; Li, Muwei
2017-11-01
The purpose of this study was to identify the expression characteristics of circular RNAs in the peripheral blood of coronary artery disease patients and type 2 diabetes mellitus patients. Circular RNA in the peripheral blood from 6 control individuals, 6 coronary artery disease patients, 6 type 2 diabetes mellitus patients and 6 coronary artery disease combined with type 2 diabetes mellitus patients was collected for microarray analysis, and a further independent cohort consisting of 20 normal individuals, 20 type 2 diabetes mellitus subjects and 20 coronary artery disease subjects was used to verify the expression of five circular RNAs chosen for further analysis. The findings were then tested in a third cohort using quantitative real-time polymerase chain reaction. In total, 40 circular RNAs differentially expressed between the three experimental groups and the control group were identified by microarray analysis: 13 were upregulated in the experimental groups, while 27 were downregulated. Of the five circular RNAs chosen for further analysis, three were significantly downregulated in the experimental groups. The crude odds ratios and adjusted odds ratios of hsa-circRNA11783-2 showed significant differences in both the coronary artery disease group and type 2 diabetes mellitus group. We then verified hsa-circRNA11783-2 in the third cohort, and it remained closely related to both coronary artery disease and type 2 diabetes mellitus. Hsa-circRNA11783-2 is closely related to both coronary artery disease and type 2 diabetes mellitus.
Holliday, Jason A; Ralph, Steven G; White, Richard; Bohlmann, Jörg; Aitken, Sally N
2008-01-01
Cold acclimation in conifers is a complex process, the timing and extent of which reflects local adaptation and varies widely along latitudinal gradients for many temperate and boreal tree species. Despite their ecological and economic importance, little is known about the global changes in gene expression that accompany autumn cold acclimation in conifers. Using three populations of Sitka spruce (Picea sitchensis) spanning the species range, and a Picea cDNA microarray with 21,840 unique elements, within- and among-population gene expression was monitored during the autumn. Microarray data were validated for selected genes using real-time PCR. Similar numbers of genes were significantly twofold upregulated (1257) and downregulated (967) between late summer and early winter. Among those upregulated were dehydrins, pathogenesis-related/antifreeze genes, carbohydrate and lipid metabolism genes, and genes involved in signal transduction and transcriptional regulation. Among-population microarray hybridizations at early and late autumn time points revealed substantial variation in the autumn transcriptome, some of which may reflect local adaptation. These results demonstrate the complexity of cold acclimation in conifers, highlight similarities and differences to cold tolerance in annual plants, and provide a solid foundation for functional and genetic studies of this important adaptive process.
Mlakar, Vid; Strazisar, Mojca; Sok, Mihael; Glavac, Damjan
2010-06-01
The purpose of this study was to find novel gene(s) involved in the development of lung adenocarcinoma (AD). Using DNA microarrays, we identified 31 up-regulated and 8 downregulated genes in 12 AD. Real time PCR was used to measure expression of VIPR1 and SPP1 mRNA and possible losses or gains of genes in 32 AD. We describe significant upregulation of the SPP1 gene, downregulation of VIPR1, and losses of the VIPR1 gene. Our findings complement a proposed VIPR1 tumor suppressor role, in which deletions in the 3p22 chromosome region are an important mechanism leading to loss of the VIPR1 gene.
NASA Technical Reports Server (NTRS)
Patel, Mamta J.; Liu, Wenbin; Sykes, Michelle C.; Ward, Nancy E.; Risin, Semyon A.; Risin, Diana; Hanjoong, Jo
2007-01-01
Microgravity of spaceflight induces bone loss due in part to decreased bone formation by osteoblasts. We have previously examined the microgravity-induced changes in gene expression profiles in 2T3 preosteoblasts using the Random Positioning Machine (RPM) to simulate microgravity conditions. Here, we hypothesized that exposure of preosteoblasts to an independent microgravity simulator, the Rotating Wall Vessel (RWV), induces similar changes in differentiation and gene transcript profiles, resulting in a more confined list of gravi-sensitive genes that may play a role in bone formation. In comparison to static 1g controls, exposure of 2T3 cells to RWV for 3 days inhibited alkaline phosphatase activity, a marker of differentiation, and downregulated 61 genes and upregulated 45 genes by more than two-fold as shown by microarray analysis. The microarray results were confirmed with real time PCR for downregulated genes osteomodulin, bone morphogenic protein 4 (BMP4), runx2, and parathyroid hormone receptor 1. Western blot analysis validated the expression of three downregulated genes, BMP4, peroxiredoxin IV, and osteoglycin, and one upregulated gene peroxiredoxin I. Comparison of the microarrays from the RPM and the RWV studies identified 14 gravi-sensitive genes that changed in the same direction in both systems. Further comparison of our results to a published database showing gene transcript profiles of mechanically loaded mouse tibiae revealed 16 genes upregulated by the loading that were shown to be downregulated by RWV and RPM. These mechanosensitive genes identified by the comparative studies may provide novel insights into understanding the mechanisms regulating bone formation and potential targets of countermeasure against decreased bone formation both in astronauts and in general patients with musculoskeletal disorders.
Guerra, Susana; López-Fernández, Luis A.; Conde, Raquel; Pascual-Montano, Alberto; Harshman, Keith; Esteban, Mariano
2004-01-01
The potential use of the modified vaccinia virus Ankara (MVA) strain as a live recombinant vector to deliver antigens and elicit protective immune responses against infectious diseases demands a comprehensive understanding of the effect of MVA infection on human host gene expression. We used microarrays containing more than 15,000 human cDNAs to identify gene expression changes in human HeLa cell cultures at 2, 6, and 16 h postinfection. Clustering of the 410 differentially regulated genes identified 11 discrete gene clusters with altered expression patterns after MVA infection. Clusters 1 and 2 (accounting for 16.59% [68 of 410] of the genes) contained 68 transcripts showing a robust induction pattern that was maintained during the course of infection. Changes in cellular gene transcription detected by microarrays after MVA infection were confirmed for selected genes by Northern blot analysis and by real-time reverse transcription-PCR. Upregulated transcripts in clusters 1 and 2 included 20 genes implicated in immune responses, including interleukin 1A (IL-1A), IL-6, IL-7, IL-8, and IL-15 genes. MVA infection also stimulated the expression of NF-κB and components of the NF-κB signal transduction pathway, including p50 and TRAF-interacting protein. A marked increase in the expression of histone family members was also induced during MVA infection. Expression of the Wiskott-Aldrich syndrome family members WAS, WASF1, and the small GTP-binding protein RAC-1, which are involved in actin cytoskeleton reorganization, was enhanced after MVA infection. This study demonstrates that MVA infection triggered the induction of groups of genes, some of which may be involved in host resistance and immune modulation during virus infection. PMID:15140980
Kim, Joseph; Mori, Takuji; Chen, Steven L.; Amersi, Farin F.; Martinez, Steve R.; Kuo, Christine; Turner, Roderick R.; Ye, Xing; Bilchik, Anton J.; Morton, Donald L.; Hoon, Dave S. B.
2006-01-01
Objective: To determine the role of chemokine receptor (CR) expression in patients with melanoma and colorectal cancer (CRC) liver metastases. Summary Background Data: Murine and in vitro models have identified CR as potential factors in organ-specific metastasis of multiple cancers. Chemokines via their respective receptors have been shown to promote cell migration to distant organs. Methods: Patients who underwent hepatic surgery for melanoma or CRC liver metastases were assessed. Screening cDNA microarrays of melanoma/CRC cell lines and tumor specimens were analyzed to identify CR. Microarray data were validated by quantitative real-time RT-PCR (qRT) in paraffin-embedded liver metastases. Migration assays and immunohistochemistry were performed to verify CR function and confirm CR expression, respectively. Results: Microarray analysis identified CXCR4 as the most common CR expressed by both cancers. qRT demonstrated CXCR4 expression in 24 of 27 (89%) melanoma and 28 of 29 (97%) CRC liver metastases. In vitro treatment of melanoma or CRC cells with CXCL12, the ligand for CXCR4, significantly increased cell migration (P < 0.001). Low versus high CXCR4 expression in CRC liver metastases correlated with a significant difference in overall survival (median 27 months vs. 10 months, respectively; P = 0.036). In melanoma, low versus high CXCR4 expression in liver metastases demonstrated no difference in overall survival (median 11 months vs. 8 months, respectively; P = not significant). Conclusions: CXCR4 is expressed and functional on melanoma and CRC cells. The ligand for CXCR4 is highly expressed in liver and may specifically attract melanoma and CRC CXCR4 (+) cells. Quantitative analysis of CXCR4 gene expression in patients with liver metastases has prognostic significance for disease outcome. PMID:16794396
DOE Office of Scientific and Technical Information (OSTI.GOV)
Wu, Yongyan; Key Laboratory of Animal Biotechnology, Ministry of Agriculture, Northwest A and F University, Yangling 712100, Shaanxi; Ai, Zhiying
2013-10-15
Embryonic stem cells (ESCs) can proliferate indefinitely in vitro and differentiate into cells of all three germ layers. These unique properties make them exceptionally valuable for drug discovery and regenerative medicine. However, the practical application of ESCs is limited because it is difficult to derive and culture ESCs. It has been demonstrated that CHIR99021 (CHIR) promotes self-renewal and enhances the derivation efficiency of mouse (m)ESCs. However, the downstream targets of CHIR are not fully understood. In this study, we identified CHIR-regulated genes in mESCs using microarray analysis. Our microarray data demonstrated that CHIR not only influenced the Wnt/β-catenin pathway bymore » stabilizing β-catenin, but also modulated several other pluripotency-related signaling pathways such as TGF-β, Notch and MAPK signaling pathways. More detailed analysis demonstrated that CHIR inhibited Nodal signaling, while activating bone morphogenetic protein signaling in mESCs. In addition, we found that pluripotency-maintaining transcription factors were up-regulated by CHIR, while several developmental-related genes were down-regulated. Furthermore, we found that CHIR altered the expression of epigenetic regulatory genes and long intergenic non-coding RNAs. Quantitative real-time PCR results were consistent with microarray data, suggesting that CHIR alters the expression pattern of protein-encoding genes (especially transcription factors), epigenetic regulatory genes and non-coding RNAs to establish a relatively stable pluripotency-maintaining network. - Highlights: • Combined use of CHIR with LIF promotes self-renewal of J1 mESCs. • CHIR-regulated genes are involved in multiple pathways. • CHIR inhibits Nodal signaling and promotes Bmp4 expression to activate BMP signaling. • Expression of epigenetic regulatory genes and lincRNAs is altered by CHIR.« less
Pentadecapeptide BPC 157 enhances the growth hormone receptor expression in tendon fibroblasts.
Chang, Chung-Hsun; Tsai, Wen-Chung; Hsu, Ya-Hui; Pang, Jong-Hwei Su
2014-11-19
BPC 157, a pentadecapeptide derived from human gastric juice, has been demonstrated to promote the healing of different tissues, including skin, muscle, bone, ligament and tendon in many animal studies. However, the underlying mechanism has not been fully clarified. The present study aimed to explore the effect of BPC 157 on tendon fibroblasts isolated from Achilles tendon of male Sprague-Dawley rat. From the result of cDNA microarray analysis, growth hormone receptor was revealed as one of the most abundantly up-regulated genes in tendon fibroblasts by BPC 157. BPC 157 dose- and time-dependently increased the expression of growth hormone receptor in tendon fibroblasts at both the mRNA and protein levels as measured by RT/real-time PCR and Western blot, respectively. The addition of growth hormone to BPC 157-treated tendon fibroblasts dose- and time-dependently increased the cell proliferation as determined by MTT assay and PCNA expression by RT/real-time PCR. Janus kinase 2, the downstream signal pathway of growth hormone receptor, was activated time-dependently by stimulating the BPC 157-treated tendon fibroblasts with growth hormone. In conclusion, the BPC 157-induced increase of growth hormone receptor in tendon fibroblasts may potentiate the proliferation-promoting effect of growth hormone and contribute to the healing of tendon.
MULTI-K: accurate classification of microarray subtypes using ensemble k-means clustering
Kim, Eun-Youn; Kim, Seon-Young; Ashlock, Daniel; Nam, Dougu
2009-01-01
Background Uncovering subtypes of disease from microarray samples has important clinical implications such as survival time and sensitivity of individual patients to specific therapies. Unsupervised clustering methods have been used to classify this type of data. However, most existing methods focus on clusters with compact shapes and do not reflect the geometric complexity of the high dimensional microarray clusters, which limits their performance. Results We present a cluster-number-based ensemble clustering algorithm, called MULTI-K, for microarray sample classification, which demonstrates remarkable accuracy. The method amalgamates multiple k-means runs by varying the number of clusters and identifies clusters that manifest the most robust co-memberships of elements. In addition to the original algorithm, we newly devised the entropy-plot to control the separation of singletons or small clusters. MULTI-K, unlike the simple k-means or other widely used methods, was able to capture clusters with complex and high-dimensional structures accurately. MULTI-K outperformed other methods including a recently developed ensemble clustering algorithm in tests with five simulated and eight real gene-expression data sets. Conclusion The geometric complexity of clusters should be taken into account for accurate classification of microarray data, and ensemble clustering applied to the number of clusters tackles the problem very well. The C++ code and the data sets tested are available from the authors. PMID:19698124
Oil palm phenolics confer neuroprotective effects involving cognitive and motor functions in mice
Leow, Soon-Sen; Sekaran, Shamala Devi; Tan, YewAi; Sundram, Kalyana; Sambanthamurthi, Ravigadevi
2013-01-01
Objectives Phenolics are important phytochemicals which have positive effects on chronic diseases, including neurodegenerative ailments. The oil palm (Elaeis guineensis) is a rich source of water-soluble phenolics. This study was carried out to discover the effects of administering oil palm phenolics (OPP) to mice, with the aim of identifying whether these compounds possess significant neuroprotective properties. Methods OPP was given to BALB/c mice on a normal diet as fluids for 6 weeks while the controls were given distilled water. These animals were tested in a water maze and on a rotarod weekly to assess the effects of OPP on cognitive and motor functions, respectively. Using Illumina microarrays, we further explored the brain gene expression changes caused by OPP in order to determine the molecular mechanisms involved. Real-time quantitative reverse transcription-polymerase chain reaction experiments were then carried out to validate the microarray data. Results We found that mice given OPP showed better cognitive function and spatial learning when tested in a water maze, and their performance also improved when tested on a rotarod, possibly due to better motor function and balance. Microarray gene expression analysis showed that these compounds up-regulated genes involved in brain development and activity, such as those under the regulation of the brain-derived neurotrophic factor. OPP also down-regulated genes involved in inflammation. Discussion These results suggest that the improvement of mouse cognitive and motor functions by OPP is caused by the neuroprotective and anti-inflammatory effects of the extract. PMID:23433062
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.
Vidyasagar, Mathukumalli
2015-01-01
This article reviews several techniques from machine learning that can be used to study the problem of identifying a small number of features, from among tens of thousands of measured features, that can accurately predict a drug response. Prediction problems are divided into two categories: sparse classification and sparse regression. In classification, the clinical parameter to be predicted is binary, whereas in regression, the parameter is a real number. Well-known methods for both classes of problems are briefly discussed. These include the SVM (support vector machine) for classification and various algorithms such as ridge regression, LASSO (least absolute shrinkage and selection operator), and EN (elastic net) for regression. In addition, several well-established methods that do not directly fall into machine learning theory are also reviewed, including neural networks, PAM (pattern analysis for microarrays), SAM (significance analysis for microarrays), GSEA (gene set enrichment analysis), and k-means clustering. Several references indicative of the application of these methods to cancer biology are discussed.
2012-01-01
Background Along the root axis of Arabidopsis thaliana, cells pass through different developmental stages. In the apical meristem repeated cycles of division increase the numbers of cells. Upon leaving the meristem, these cells pass the transition zone where they are physiologically and mechanically prepared to undergo subsequent rapid elongation. During the process of elongation epidermal cells increase their length by 300% in a couple of hours. When elongation ceases, the cells acquire their final size, shape and functions (in the differentiation zone). Ethylene administered as its precursor 1-aminocyclopropane-1-carboxylic acid (ACC) is capable of inhibiting elongation in a concentration-dependent way. Using a microarray analysis, genes and/or processes involved in this elongation arrest are identified. Results Using a CATMA-microarray analysis performed on control and 3h ACC-treated roots, 240 differentially expressed genes were identified. Quantitative Real-Time RT-PCR analysis of the 10 most up and down regulated genes combined with literature search confirmed the accurateness of the analysis. This revealed that inhibition of cell elongation is, at least partly, caused by restricting the events that under normal growth conditions initiate elongation and by increasing the processes that normally stop cellular elongation at the end of the elongation/onset of differentiation zone. Conclusions ACC interferes with cell elongation in the Arabidopsis thaliana roots by inhibiting cells from entering the elongation process and by immediately stimulating the formation of cross-links in cell wall components, diminishing the remaining elongation capacity. From the analysis of the differentially expressed genes, it becomes clear that many genes identified in this response, are also involved in several other kind of stress responses. This suggests that many responses originate from individual elicitors, but that somewhere in the downstream signaling cascade, these are converged to a ’common pathway’. Furthermore, several potential keyplayers, such as transcription factors and auxin-responsive genes, were identified by the microarray analysis. They await further analysis to reveal their exact role in the control of cell elongation. PMID:23134674
Bruno, D L; Ganesamoorthy, D; Schoumans, J; Bankier, A; Coman, D; Delatycki, M; Gardner, R J M; Hunter, M; James, P A; Kannu, P; McGillivray, G; Pachter, N; Peters, H; Rieubland, C; Savarirayan, R; Scheffer, I E; Sheffield, L; Tan, T; White, S M; Yeung, A; Bowman, Z; Ngo, C; Choy, K W; Cacheux, V; Wong, L; Amor, D J; Slater, H R
2009-02-01
Microarray genome analysis is realising its promise for improving detection of genetic abnormalities in individuals with mental retardation and congenital abnormality. Copy number variations (CNVs) are now readily detectable using a variety of platforms and a major challenge is the distinction of pathogenic from ubiquitous, benign polymorphic CNVs. The aim of this study was to investigate replacement of time consuming, locus specific testing for specific microdeletion and microduplication syndromes with microarray analysis, which theoretically should detect all known syndromes with CNV aetiologies as well as new ones. Genome wide copy number analysis was performed on 117 patients using Affymetrix 250K microarrays. 434 CNVs (195 losses and 239 gains) were found, including 18 pathogenic CNVs and 9 identified as "potentially pathogenic". Almost all pathogenic CNVs were larger than 500 kb, significantly larger than the median size of all CNVs detected. Segmental regions of loss of heterozygosity larger than 5 Mb were found in 5 patients. Genome microarray analysis has improved diagnostic success in this group of patients. Several examples of recently discovered "new syndromes" were found suggesting they are more common than previously suspected and collectively are likely to be a major cause of mental retardation. The findings have several implications for clinical practice. The study revealed the potential to make genetic diagnoses that were not evident in the clinical presentation, with implications for pretest counselling and the consent process. The importance of contributing novel CNVs to high quality databases for genotype-phenotype analysis and review of guidelines for selection of individuals for microarray analysis is emphasised.
Gene expression in the rectus abdominus muscle of patients with and without pelvic organ prolapse.
Hundley, Andrew F; Yuan, Lingwen; Visco, Anthony G
2008-02-01
The objective of the study was to compare gene expression in a group of actin and myosin-related proteins in the rectus muscle of 15 patients with pelvic organ prolapse and 13 controls. Six genes previously identified by microarray GeneChip analysis were examined using real-time quantitative reverse transcriptase-polymerase chain reaction analysis, including 2 genes showing differential expression in pubococcygeus muscle. Samples and controls were run in triplicate in multiplexed wells, and levels of gene expression were analyzed using the comparative critical threshold method. One gene, MYH3, was 3.2 times overexpressed in patients with prolapse (P = .032), but no significant differences in expression were seen for the other genes examined. An age-matched subset of 9 patients and controls showed that MYH3 gene expression was no longer significantly different (P = .058). Differential messenger ribonucleic acid levels of actin and myosin-related genes in patients with pelvic organ prolapse and controls may be limited to skeletal muscle from the pelvic floor.
RHEB expression in fibroadenomas of the breast.
Eom, Minseob; Han, Airi; Yi, Sang Yeop; Shin, John Junghun; Cui, Ying; Park, Kwang Hwa
2008-04-01
Although fibroadenoma is one of the most common types of benign breast tumor, genes specific to the tumor have not been identified. Microarrays were used to identify differentially expressed genes between fibroadenoma and infiltrating ductal carcinoma. The comparative expression of one of the identified genes, RAS homolog enriched in the brain (RHEB), was further explored using reverse transcriptase-polymerase chain reaction (RT-PCR). Microarray analysis was performed on tissue samples from five patients with fibroadenoma. In the fibroadenoma samples, the genes HDAC1, ROS1, TNFRSF10A, WASP2, TYRP1, WEE1, and RHEB were expressed at levels more than twofold higher than in the normal tissues. RT-PCR for RHEB indicated increased expression of RHEB in fibroadenoma compared to breast cancer. When studied with real-time PCR, the average RHEB/beta-actin ratio in fibroadenoma samples was 1.99, 2.46-fold greater than the average RHEB/beta-actin ratio in breast carcinoma of 0.81 (P < 0.01). Immunohistochemistry and PCR followed by microdissection shows increased expression of RHEB in epithelial cells compared to the stromal cells of fibroadenoma. Therefore, RHEB could be used cytopathologically to distinguish fibroadenoma from malignant breast carcinomas as a secondary diagnostic tool.
Kaur, Surleen; Archer, Kellie J; Devi, M Gouri; Kriplani, Alka; Strauss, Jerome F; Singh, Rita
2012-10-01
Polycystic ovary syndrome (PCOS) is a heterogeneous, genetically complex, endocrine disorder of uncertain etiology in women. Our aim was to compare the gene expression profiles in stimulated granulosa cells of PCOS women with and without insulin resistance vs. matched controls. This study included 12 normal ovulatory women (controls), 12 women with PCOS without evidence for insulin resistance (PCOS non-IR), and 16 women with insulin resistance (PCOS-IR) undergoing in vitro fertilization. Granulosa cell gene expression profiling was accomplished using Affymetrix Human Genome-U133 arrays. Differentially expressed genes were classified according to gene ontology using ingenuity pathway analysis tools. Microarray results for selected genes were confirmed by real-time quantitative PCR. A total of 211 genes were differentially expressed in PCOS non-IR and PCOS-IR granulosa cells (fold change≥1.5; P≤0.001) vs. matched controls. Diabetes mellitus and inflammation genes were significantly increased in PCOS-IR patients. Real-time quantitative PCR confirmed higher expression of NCF2 (2.13-fold), TCF7L2 (1.92-fold), and SERPINA1 (5.35-fold). Increased expression of inflammation genes ITGAX (3.68-fold) and TAB2 (1.86-fold) was confirmed in PCOS non-IR. Different cardiometabolic disease genes were differentially expressed in the two groups. Decreased expression of CAV1 (-3.58-fold) in PCOS non-IR and SPARC (-1.88-fold) in PCOS-IR was confirmed. Differential expression of genes involved in TGF-β signaling (IGF2R, increased; and HAS2, decreased), and oxidative stress (TXNIP, increased) was confirmed in both groups. Microarray analysis demonstrated differential expression of genes linked to diabetes mellitus, inflammation, cardiovascular diseases, and infertility in the granulosa cells of PCOS women with and without insulin resistance. Because these dysregulated genes are also involved in oxidative stress, lipid metabolism, and insulin signaling, we hypothesize that these genes may be involved in follicular growth arrest and metabolic disorders associated with the different phenotypes of PCOS.
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
Automatic Identification and Quantification of Extra-Well Fluorescence in Microarray Images.
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.
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.
Identification of the soybean HyPRP family and specific gene response to Asian soybean rust disease.
Neto, Lauro Bücker; de Oliveira, Rafael Rodrigues; Wiebke-Strohm, Beatriz; Bencke, Marta; Weber, Ricardo Luís Mayer; Cabreira, Caroline; Abdelnoor, Ricardo Vilela; Marcelino, Francismar Correa; Zanettini, Maria Helena Bodanese; Passaglia, Luciane Maria Pereira
2013-07-01
Soybean [Glycine max (L.) Merril], one of the most important crop species in the world, is very susceptible to abiotic and biotic stress. Soybean plants have developed a variety of molecular mechanisms that help them survive stressful conditions. Hybrid proline-rich proteins (HyPRPs) constitute a family of cell-wall proteins with a variable N-terminal domain and conserved C-terminal domain that is phylogenetically related to non-specific lipid transfer proteins. Members of the HyPRP family are involved in basic cellular processes and their expression and activity are modulated by environmental factors. In this study, microarray analysis and real time RT-qPCR were used to identify putative HyPRP genes in the soybean genome and to assess their expression in different plant tissues. Some of the genes were also analyzed by time-course real time RT-qPCR in response to infection by Phakopsora pachyrhizi, the causal agent of Asian soybean rust disease. Our findings indicate that the time of induction of a defense pathway is crucial in triggering the soybean resistance response to P. pachyrhizi. This is the first study to identify the soybean HyPRP group B family and to analyze disease-responsive GmHyPRP during infection by P. pachyrhizi.
Analysis of High-Throughput ELISA Microarray Data
DOE Office of Scientific and Technical Information (OSTI.GOV)
White, Amanda M.; Daly, Don S.; Zangar, Richard C.
Our research group develops analytical methods and software for the high-throughput analysis of quantitative enzyme-linked immunosorbent assay (ELISA) microarrays. ELISA microarrays differ from DNA microarrays in several fundamental aspects and most algorithms for analysis of DNA microarray data are not applicable to ELISA microarrays. In this review, we provide an overview of the steps involved in ELISA microarray data analysis and how the statistically sound algorithms we have developed provide an integrated software suite to address the needs of each data-processing step. The algorithms discussed are available in a set of open-source software tools (http://www.pnl.gov/statistics/ProMAT).
Zhu, Yuerong; Zhu, Yuelin; Xu, Wei
2008-01-01
Background Though microarray experiments are very popular in life science research, managing and analyzing microarray data are still challenging tasks for many biologists. Most microarray programs require users to have sophisticated knowledge of mathematics, statistics and computer skills for usage. With accumulating microarray data deposited in public databases, easy-to-use programs to re-analyze previously published microarray data are in high demand. Results EzArray is a web-based Affymetrix expression array data management and analysis system for researchers who need to organize microarray data efficiently and get data analyzed instantly. EzArray organizes microarray data into projects that can be analyzed online with predefined or custom procedures. EzArray performs data preprocessing and detection of differentially expressed genes with statistical methods. All analysis procedures are optimized and highly automated so that even novice users with limited pre-knowledge of microarray data analysis can complete initial analysis quickly. Since all input files, analysis parameters, and executed scripts can be downloaded, EzArray provides maximum reproducibility for each analysis. In addition, EzArray integrates with Gene Expression Omnibus (GEO) and allows instantaneous re-analysis of published array data. Conclusion EzArray is a novel Affymetrix expression array data analysis and sharing system. EzArray provides easy-to-use tools for re-analyzing published microarray data and will help both novice and experienced users perform initial analysis of their microarray data from the location of data storage. We believe EzArray will be a useful system for facilities with microarray services and laboratories with multiple members involved in microarray data analysis. EzArray is freely available from . PMID:18218103
2016-01-01
Abstract Microarray gene expression data sets are jointly analyzed to increase statistical power. They could either be merged together or analyzed by meta-analysis. For a given ensemble of data sets, it cannot be foreseen which of these paradigms, merging or meta-analysis, works better. In this article, three joint analysis methods, Z -score normalization, ComBat and the inverse normal method (meta-analysis) were selected for survival prognosis and risk assessment of breast cancer patients. The methods were applied to eight microarray gene expression data sets, totaling 1324 patients with two clinical endpoints, overall survival and relapse-free survival. The performance derived from the joint analysis methods was evaluated using Cox regression for survival analysis and independent validation used as bias estimation. Overall, Z -score normalization had a better performance than ComBat and meta-analysis. Higher Area Under the Receiver Operating Characteristic curve and hazard ratio were also obtained when independent validation was used as bias estimation. With a lower time and memory complexity, Z -score normalization is a simple method for joint analysis of microarray gene expression data sets. The derived findings suggest further assessment of this method in future survival prediction and cancer classification applications. PMID:26504096
Sule, Preeti; Horne, Shelley M.; Logue, Catherine M.; Prüß, Birgit M.
2011-01-01
To understand the continuous problems that Escherichia coli O157:H7 causes as food pathogen, this study assessed global gene regulation in bacteria growing on meat. Since FlhD/FlhC of E. coli K-12 laboratory strains was previously established as a major control point in transducing signals from the environment to several cellular processes, this study compared the expression pattern of an E. coli O157:H7 parent strain to that of its isogenic flhC mutant. This was done with bacteria that had been grown on meat. Microarray experiments revealed 287 putative targets of FlhC. Real-time PCR was performed as an alternative estimate of transcription and confirmed microarray data for 13 out of 15 genes tested (87%). The confirmed genes are representative of cellular functions, such as central metabolism, cell division, biofilm formation, and pathogenicity. An additional 13 genes from the same cellular functions that had not been hypothesized as being regulated by FlhC by the microarray experiment were tested with real-time PCR and also exhibited higher expression levels in the flhC mutant than in the parent strain. Physiological experiments were performed and confirmed that FlhC reduced the cell division rate, the amount of biofilm biomass, and pathogenicity in a chicken embryo lethality model. Altogether, this study provides valuable insight into the complex regulatory network of the pathogen that enables its survival under various environmental conditions. This information may be used to develop strategies that could be used to reduce the number of cells or pathogenicity of E. coli O157:H7 on meat by interfering with the signal transduction pathways. PMID:21498760
Characterization and simulation of cDNA microarray spots using a novel mathematical model
Kim, Hye Young; Lee, Seo Eun; Kim, Min Jung; Han, Jin Il; Kim, Bo Kyung; Lee, Yong Sung; Lee, Young Seek; Kim, Jin Hyuk
2007-01-01
Background The quality of cDNA microarray data is crucial for expanding its application to other research areas, such as the study of gene regulatory networks. Despite the fact that a number of algorithms have been suggested to increase the accuracy of microarray gene expression data, it is necessary to obtain reliable microarray images by improving wet-lab experiments. As the first step of a cDNA microarray experiment, spotting cDNA probes is critical to determining the quality of spot images. Results We developed a governing equation of cDNA deposition during evaporation of a drop in the microarray spotting process. The governing equation included four parameters: the surface site density on the support, the extrapolated equilibrium constant for the binding of cDNA molecules with surface sites on glass slides, the macromolecular interaction factor, and the volume constant of a drop of cDNA solution. We simulated cDNA deposition from the single model equation by varying the value of the parameters. The morphology of the resulting cDNA deposit can be classified into three types: a doughnut shape, a peak shape, and a volcano shape. The spot morphology can be changed into a flat shape by varying the experimental conditions while considering the parameters of the governing equation of cDNA deposition. The four parameters were estimated by fitting the governing equation to the real microarray images. With the results of the simulation and the parameter estimation, the phenomenon of the formation of cDNA deposits in each type was investigated. Conclusion This study explains how various spot shapes can exist and suggests which parameters are to be adjusted for obtaining a good spot. This system is able to explore the cDNA microarray spotting process in a predictable, manageable and descriptive manner. We hope it can provide a way to predict the incidents that can occur during a real cDNA microarray experiment, and produce useful data for several research applications involving cDNA microarrays. PMID:18096047
Microarray analysis of retinal gene expression in Egr-1 knockout mice
Schippert, Ruth; Schaeffel, Frank
2009-01-01
Purpose We found earlier that 42 day-old Egr-1 knockout mice had longer eyes and a more myopic refractive error compared to their wild-types. To identify genes that could be responsible for the temporarily enhanced axial eye growth, a microarray analysis was performed in knockout and wild-type mice at the postnatal ages of 30 and 42 days. Methods The retinas of homozygous and wild-type Egr-1 knockout mice (Taconic, Ry, Denmark) were prepared for RNA isolation (RNeasy Mini Kit, Qiagen) at the age of 30 or 42 days, respectively (n=12 each). Three retinas were pooled and labeled cRNA was made. The samples were hybridized to Affymetrix GeneChip Mouse Genome 430 2.0 Arrays. Hybridization signals were calculated using GC-RMA normalization. Genes were identified as differentially expressed if they showed a fold-change (FC) of at least 1.5 and a p-value <0.05. A false-discovery rate of 5% was applied. Ten genes with potential biologic relevance were examined further with semiquantitative real-time RT–PCR. Results Comparing mRNA expression levels between wild-type and homozygous Egr-1 knockout mice, we found 73 differentially expressed genes at the age of 30 days and 135 genes at the age of 42 days. Testing for differences in gene expression between the two ages (30 versus 42 days), 54 genes were differently expressed in wild-type mice and 215 genes in homozygous animals. Based on three networks proposed by Ingenuity pathway analysis software, nine differently expressed genes in the homozygous Egr-1 knockout mice were chosen for further validation by real-time RT–PCR, three genes in each network. In addition, the gene that was most prominently regulated in the knockout mice, compared to wild-type, at both 30 days and 42 days of age (protocadherin beta-9 [Pcdhb9]), was tested with real-time RT–PCR. Changes in four of the ten genes could be confirmed by real-time RT–PCR: nuclear prelamin A recognition factor (Narf), oxoglutarate dehydrogenase (Ogdh), selenium binding protein 1 (Selenbp1), and Pcdhb9. Except for Pcdhb9, the genes whose mRNA expression levels were validated were listed in one of the networks proposed by Ingenuity pathway analysis software. In addition to these genes, the software proposed several key-regulators which did not change in our study: retinoic acid, vascular endothelial growth factor A (VEGF-A), FBJ murine osteosarcoma viral oncogene homolog (cFos), and others. Conclusions Identification of genes that are differentially regulated during the development period between postnatal day 30 (when both homozygous and wild-type mice still have the same axial length) and day 42 (where the difference in eye length is apparent) could improve the understanding of mechanisms for the control of axial eye growth and may lead to potential targets for pharmacological intervention. With the aid of pathway-analysis software, a coarse picture of possible biochemical pathways could be generated. Although the mRNA expression levels of proteins proposed by the software, like VEGF, FOS, retinoic acid (RA) receptors, or cellular RA binding protein, did not show any changes in our experiment, these molecules have previously been implicated in the signaling cascades controlling axial eye growth. According to the pathway-analysis software, they represent links between several proteins whose mRNA expression was changed in our study. PMID:20019881
Microarray analysis of retinal gene expression in Egr-1 knockout mice.
Schippert, Ruth; Schaeffel, Frank; Feldkaemper, Marita Pauline
2009-12-10
We found earlier that 42 day-old Egr-1 knockout mice had longer eyes and a more myopic refractive error compared to their wild-types. To identify genes that could be responsible for the temporarily enhanced axial eye growth, a microarray analysis was performed in knockout and wild-type mice at the postnatal ages of 30 and 42 days. The retinas of homozygous and wild-type Egr-1 knockout mice (Taconic, Ry, Denmark) were prepared for RNA isolation (RNeasy Mini Kit, Qiagen) at the age of 30 or 42 days, respectively (n=12 each). Three retinas were pooled and labeled cRNA was made. The samples were hybridized to Affymetrix GeneChip Mouse Genome 430 2.0 Arrays. Hybridization signals were calculated using GC-RMA normalization. Genes were identified as differentially expressed if they showed a fold-change (FC) of at least 1.5 and a p-value <0.05. A false-discovery rate of 5% was applied. Ten genes with potential biologic relevance were examined further with semiquantitative real-time RT-PCR. Comparing mRNA expression levels between wild-type and homozygous Egr-1 knockout mice, we found 73 differentially expressed genes at the age of 30 days and 135 genes at the age of 42 days. Testing for differences in gene expression between the two ages (30 versus 42 days), 54 genes were differently expressed in wild-type mice and 215 genes in homozygous animals. Based on three networks proposed by Ingenuity pathway analysis software, nine differently expressed genes in the homozygous Egr-1 knockout mice were chosen for further validation by real-time RT-PCR, three genes in each network. In addition, the gene that was most prominently regulated in the knockout mice, compared to wild-type, at both 30 days and 42 days of age (protocadherin beta-9 [Pcdhb9]), was tested with real-time RT-PCR. Changes in four of the ten genes could be confirmed by real-time RT-PCR: nuclear prelamin A recognition factor (Narf), oxoglutarate dehydrogenase (Ogdh), selenium binding protein 1 (Selenbp1), and Pcdhb9. Except for Pcdhb9, the genes whose mRNA expression levels were validated were listed in one of the networks proposed by Ingenuity pathway analysis software. In addition to these genes, the software proposed several key-regulators which did not change in our study: retinoic acid, vascular endothelial growth factor A (VEGF-A), FBJ murine osteosarcoma viral oncogene homolog (cFos), and others. Identification of genes that are differentially regulated during the development period between postnatal day 30 (when both homozygous and wild-type mice still have the same axial length) and day 42 (where the difference in eye length is apparent) could improve the understanding of mechanisms for the control of axial eye growth and may lead to potential targets for pharmacological intervention. With the aid of pathway-analysis software, a coarse picture of possible biochemical pathways could be generated. Although the mRNA expression levels of proteins proposed by the software, like VEGF, FOS, retinoic acid (RA) receptors, or cellular RA binding protein, did not show any changes in our experiment, these molecules have previously been implicated in the signaling cascades controlling axial eye growth. According to the pathway-analysis software, they represent links between several proteins whose mRNA expression was changed in our study.
The Regulation of Non-Coding RNA Expression in the Liver of Mice Fed DDC
Oliva, Joan; Bardag-Gorce, Fawzia; French, Barbara A; Li, Jun; French, Samuel W
2010-01-01
Mallory-Denk bodies (MDBs) are found in the liver of patients with alcoholic and chronic nonalcoholic liver disease, and hepatocellular carcinoma (HCC). Diethyl 1,4-dihydro-2,4,6,-trimethyl-3,5-pyridinedicarboxylate (DDC) is used as a model to induce the formation of MDBs in mouse liver. Previous studies in this laboratory showed that DDC induced epigenetic modifications in DNA and histones. The combination of these modifications changes the phenotype of the MDB forming hepatocytes, as indicated by the marker FAT10. These epigenetic modifications are partially prevented by adding to the diet S-adenosylmethionine (SAMe) or betaine, both methyl donors. The expression of three imprinted ncRNA genes was found to change in MDB forming hepatocytes, which is the subject of this report. NcRNA expression was quantitated by Real-Time PCR and RNA FISH in liver sections. Microarray analysis showed that the expression of three ncRNAs was regulated by DDC: up regulation of H19, antisense Igf2r (AIR), and down regulation of GTL2 (also called MEG3). S-adenosylmethionine (SAMe) feeding prevented these changes. Betaine, another methyl group donor, prevented only H19 and AIR up regulation induced by DDC, on microarrays. The results of the SAMe and betaine groups were confirmed by Real-Time PCR, except for AIR expression. After 1 month of drug withdrawal, the expression of the three ncRNAs tended toward control levels of expression. Liver tumors that developed also showed up regulation of H19 and AIR. The RNA FISH approach showed that the MDB forming cells’ phenotype changed the level of expression of AIR, H19 and GTL2, compared to the surrounding cells. Furthermore, over expression of H19 and AIR was demonstrated in tumors formed in mice withdrawn for 9 months. The disregulation of ncRNA in MDB forming liver cells has been observed for the first time in drug primed mice associated with liver preneoplastic foci and tumors. PMID:19362547
The regulation of non-coding RNA expression in the liver of mice fed DDC.
Oliva, Joan; Bardag-Gorce, Fawzia; French, Barbara A; Li, Jun; French, Samuel W
2009-08-01
Mallory-Denk bodies (MDBs) are found in the liver of patients with alcoholic and chronic nonalcoholic liver disease, and hepatocellular carcinoma (HCC). Diethyl 1,4-dihydro-2,4,6,-trimethyl-3,5-pyridinedicarboxylate (DDC) is used as a model to induce the formation of MDBs in mouse liver. Previous studies in this laboratory showed that DDC induced epigenetic modifications in DNA and histones. The combination of these modifications changes the phenotype of the MDB forming hepatocytes, as indicated by the marker FAT10. These epigenetic modifications are partially prevented by adding to the diet S-adenosylmethionine (SAMe) or betaine, both methyl donors. The expression of three imprinted ncRNA genes was found to change in MDB forming hepatocytes, which is the subject of this report. NcRNA expression was quantitated by real-time PCR and RNA FISH in liver sections. Microarray analysis showed that the expression of three ncRNAs was regulated by DDC: up regulation of H19, antisense Igf2r (AIR), and down regulation of GTL2 (also called MEG3). S-adenosylmethionine (SAMe) feeding prevented these changes. Betaine, another methyl group donor, prevented only H19 and AIR up regulation induced by DDC, on microarrays. The results of the SAMe and betaine groups were confirmed by real-time PCR, except for AIR expression. After 1 month of drug withdrawal, the expression of the three ncRNAs tended toward control levels of expression. Liver tumors that developed also showed up regulation of H19 and AIR. The RNA FISH approach showed that the MDB forming cells' phenotype changed the level of expression of AIR, H19 and GTL2, compared to the surrounding cells. Furthermore, over expression of H19 and AIR was demonstrated in tumors formed in mice withdrawn for 9 months. The dysregulation of ncRNA in MDB forming liver cells has been observed for the first time in drug-primed mice associated with liver preneoplastic foci and tumors.
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.
Neuner, Elizabeth A; Pallotta, Andrea M; Lam, Simon W; Stowe, David; Gordon, Steven M; Procop, Gary W; Richter, Sandra S
2016-11-01
OBJECTIVE To describe the impact of rapid diagnostic microarray technology and antimicrobial stewardship for patients with Gram-positive blood cultures. DESIGN Retrospective pre-intervention/post-intervention study. SETTING A 1,200-bed academic medical center. PATIENTS Inpatients with blood cultures positive for Staphylococcus aureus, Enterococcus faecalis, E. faecium, Streptococcus pneumoniae, S. pyogenes, S. agalactiae, S. anginosus, Streptococcus spp., and Listeria monocytogenes during the 6 months before and after implementation of Verigene Gram-positive blood culture microarray (BC-GP) with an antimicrobial stewardship intervention. METHODS Before the intervention, no rapid diagnostic technology was used or antimicrobial stewardship intervention was undertaken, except for the use of peptide nucleic acid fluorescent in situ hybridization and MRSA agar to identify staphylococcal isolates. After the intervention, all Gram-positive blood cultures underwent BC-GP microarray and the antimicrobial stewardship intervention consisting of real-time notification and pharmacist review. RESULTS In total, 513 patients with bacteremia were included in this study: 280 patients with S. aureus, 150 patients with enterococci, 82 patients with stretococci, and 1 patient with L. monocytogenes. The number of antimicrobial switches was similar in the pre-BC-GP (52%; 155 of 300) and post-BC-GP (50%; 107 of 213) periods. The time to antimicrobial switch was significantly shorter in the post-BC-GP group than in the pre-BC-GP group: 48±41 hours versus 75±46 hours, respectively (P<.001). The most common antimicrobial switch was de-escalation and time to de-escalation, was significantly shorter in the post-BC-GP group than in the pre-BC-GP group: 53±41 hours versus 82±48 hours, respectively (P<.001). There was no difference in mortality or hospital length of stay as a result of the intervention. CONCLUSIONS The combination of a rapid microarray diagnostic test with an antimicrobial stewardship intervention improved time to antimicrobial switch, especially time to de-escalation to optimal therapy, in patients with Gram-positive blood cultures. Infect Control Hosp Epidemiol 2016;1-6.
Korashy, Hesham M; Attafi, Ibraheem M; Famulski, Konrad S; Bakheet, Saleh A; Hafez, Mohammed M; Alsaad, Abdulaziz M S; Al-Ghadeer, Abdul Rahman M
2017-02-01
Heavy metals are the most commonly encountered toxic substances that increase susceptibility to various diseases after prolonged exposure. We have previously shown that healthy volunteers living near a mining area had significant contamination with heavy metals associated with significant changes in the expression of some detoxifying genes, xenobiotic metabolizing enzymes, and DNA repair genes. However, alterations of most of the molecular target genes associated with diseases are still unknown. Thus, the aims of this study were to (a) evaluate the gene expression profile and (b) identify the toxicities and potentially relevant human disease outcomes associated with long-term human exposure to environmental heavy metals in mining area using microarray analysis. For this purpose, 40 healthy male volunteers who were residents of a heavy metal-polluted area (Mahd Al-Dhahab city, Saudi Arabia) and 20 healthy male volunteers who were residents of a non-heavy metal-polluted area were included in the study. Total RNA was isolated from whole blood using PAXgene Blood RNA tubes and then reversed transcribed and hybridized to the gene array using the Affymetrix U219 GeneChip. Microarray analysis showed about 2129 genes were identified and differentially altered, among which a shared set of 425 genes was differentially expressed in the heavy metal-exposed groups. Ingenuity pathway analysis revealed that the most altered gene-regulated diseases in heavy metal-exposed groups included hematological and developmental disorders and mostly renal and urological diseases. Quantitative real-time polymerase chain reaction closely matched the microarray data for some genes tested. Importantly, changes in gene-related diseases were attributed to alterations in the genes encoded for protein synthesis. Renal and urological diseases were the diseases that were most frequently associated with the heavy metal-exposed group. Therefore, there is a need for further studies to validate these genes, which could be used as early biomarkers to prevent renal injury. Copyright © 2016 Elsevier Ltd. All rights reserved.
Jiang, Lei; Dong, Zhao; Li, Fengpeng; Liu, Ruozhuo; Qiu, Enchao; Wang, Xiaolin; Yu, Shengyuan
2014-01-01
The molecular and cellular origins of migraine headache are among the most complex problems in contemporary neurology. Up to now the pathogenesis of migraine still remains unclearly defined. The objective of this study was to explore new factors that may be related to the mechanism of migraine. The present study performed a comprehensive analysis of gene expression in the trigeminal nucleus caudalis induced by electrical stimulation of dura mater surrounding the superior sagittal sinus in conscious rats using microarray analysis followed by quantitative real-time reverse-transcribed polymerase chain reaction (qRT-PCR) verification. Student's two sample t-test was employed when two groups were compared. A P value <0.05 was considered to be statistically significant. Comparing the placebo and the electrical stimulation groups, 40 genes were determined to be significantly differentially expressed. These significantly differentially expressed genes were involved in many pathways, including transporter activity, tryptophan metabolism, G protein signaling, kinase activity, actin binding, signal transducer activity, anion transport, protein folding, enzyme inhibitor activity, coenzyme metabolism, binding, ion transport, cell adhesion, metal ion transport, oxidoreductase activity, mitochondrion function, and others. Most of the genes were involved in more than 2 pathways. Of particular interest is the up-regulation of Phactr3 and Akap5 and the down-regulation of Kdr. These findings may provide important clues for a better understanding of the molecular mechanism of migraine.
Molecular and genomic basis of volatile-mediated indirect defense against insects in rice.
Yuan, Joshua S; Köllner, Tobias G; Wiggins, Greg; Grant, Jerome; Degenhardt, Jörg; Chen, Feng
2008-08-01
Rice plants fed on by fall armyworm (Spodoptera frugiperda, FAW) caterpillars emit a blend of volatiles dominated by terpenoids. These volatiles were highly attractive to females of the parasitoid Cotesia marginiventris. Microarray analysis identified 196 rice genes whose expression was significantly upregulated by FAW feeding, 18 of which encode metabolic enzymes potentially involved in volatile biosynthesis. Significant induction of expression of seven of the 11 terpene synthase (TPS) genes identified through the microarray experiments was confirmd using real-time RT-PCR. Enzymes encoded by three TPS genes, Os02g02930, Os08g07100 and Os08g04500, were biochemically characterized. Os02g02930 was found to encode a monoterpene synthase producing the single product S-linalool, which is the most abundant volatile emitted from FAW-damaged rice plants. Both Os08g07100 and Os08g04500 were found to encode sesquiterpene synthases, each producing multiple products. These three enzymes are responsible for production of the majority of the terpenes released from FAW-damaged rice plants. In addition to TPS genes, several key genes in the upstream terpenoid pathways were also found to be upregulated by FAW feeding. This paper provides a comprehensive analysis of FAW-induced volatiles and the corresponding volatile biosynthetic genes potentially involved in indirect defense in rice. Evolution of the genetic basis governing volatile terpenoid biosynthesis for indirect defense is discussed.
Estep, J Michael; O'Reilly, Linda; Grant, Geraldine; Piper, James; Jonsson, Johann; Afendy, Arian; Chandhoke, Vikas; Younossi, Zobair M
2010-02-01
Hepatic stellate cells (HSC) are involved in hepatic fibrogenesis. Cell signaling associated with an insult to the liver affects an HSC transdifferentiation to fibrogenic myofibroblast-like cells. To investigate the transcriptional expression distinguishing HSC and myofibroblast-like cells between livers with and without cirrhosis. Tissue from ten cirrhotic livers (undergoing transplant) and four non-cirrhotic livers from the National Disease Research Interchange underwent cell separation to extract HSC and myofibroblast-like cell populations. Separated cell types as well as LI-90 cells were subjected to microarray analysis. Selected microarray results were verified by quantitative real-time PCR. Differential expression of some genes, such as IL-1beta, IL-1alpha, and IL-6, was associated with both transdifferentiation and disease. Other genes, such as fatty acid 2-hydroxylase only show differential expression in association with disease. Functional analysis supported these findings, indicating some signal transduction pathways (IL-6) are involved in disease and activation, whereas retinoid X receptor signaling in HSC from cirrhotic and non-cirrhotic livers varies in scope and quality. These findings indicate distinct phenotypes for HSC from cirrhotic and non-cirrhotic livers. Furthermore, coordinated differential expression between genes involved in the same signal transduction pathways provides some insight into the mechanisms that may control the balance between fibrogenesis and fibrolysis.
c-Kit modifies the inflammatory status of smooth muscle cells
Song, Lei; Martinez, Laisel; Zigmond, Zachary M.; Hernandez, Diana R.; Lassance-Soares, Roberta M.; Selman, Guillermo
2017-01-01
Background c-Kit is a receptor tyrosine kinase present in multiple cell types, including vascular smooth muscle cells (SMC). However, little is known about how c-Kit influences SMC biology and vascular pathogenesis. Methods High-throughput microarray assays and in silico pathway analysis were used to identify differentially expressed genes between primary c-Kit deficient (KitW/W–v) and control (Kit+/+) SMC. Quantitative real-time RT-PCR and functional assays further confirmed the differences in gene expression and pro-inflammatory pathway regulation between both SMC populations. Results The microarray analysis revealed elevated NF-κB gene expression secondary to the loss of c-Kit that affects both the canonical and alternative NF-κB pathways. Upon stimulation with an oxidized phospholipid as pro-inflammatory agent, c-Kit deficient SMC displayed enhanced NF-κB transcriptional activity, higher phosphorylated/total p65 ratio, and increased protein expression of NF-κB regulated pro-inflammatory mediators with respect to cells from control mice. The pro-inflammatory phenotype of mutant cells was ameliorated after restoring c-Kit activity using lentiviral transduction. Functional assays further demonstrated that c-Kit suppresses NF-κB activity in SMC in a TGFβ-activated kinase 1 (TAK1) and Nemo-like kinase (NLK) dependent manner. Discussion Our study suggests a novel mechanism by which c-Kit suppresses NF-κB regulated pathways in SMC to prevent their pro-inflammatory transformation. PMID:28626608
c-Kit modifies the inflammatory status of smooth muscle cells.
Song, Lei; Martinez, Laisel; Zigmond, Zachary M; Hernandez, Diana R; Lassance-Soares, Roberta M; Selman, Guillermo; Vazquez-Padron, Roberto I
2017-01-01
c-Kit is a receptor tyrosine kinase present in multiple cell types, including vascular smooth muscle cells (SMC). However, little is known about how c-Kit influences SMC biology and vascular pathogenesis. High-throughput microarray assays and in silico pathway analysis were used to identify differentially expressed genes between primary c-Kit deficient (Kit W/W-v ) and control (Kit +/+ ) SMC. Quantitative real-time RT-PCR and functional assays further confirmed the differences in gene expression and pro-inflammatory pathway regulation between both SMC populations. The microarray analysis revealed elevated NF-κB gene expression secondary to the loss of c-Kit that affects both the canonical and alternative NF-κB pathways. Upon stimulation with an oxidized phospholipid as pro-inflammatory agent, c-Kit deficient SMC displayed enhanced NF-κB transcriptional activity, higher phosphorylated/total p65 ratio, and increased protein expression of NF-κB regulated pro-inflammatory mediators with respect to cells from control mice. The pro-inflammatory phenotype of mutant cells was ameliorated after restoring c-Kit activity using lentiviral transduction. Functional assays further demonstrated that c-Kit suppresses NF-κB activity in SMC in a TGFβ-activated kinase 1 (TAK1) and Nemo-like kinase (NLK) dependent manner. Our study suggests a novel mechanism by which c-Kit suppresses NF-κB regulated pathways in SMC to prevent their pro-inflammatory transformation.
Klix, V; Nowrousian, M; Ringelberg, C; Loros, J J; Dunlap, J C; Pöggeler, S
2010-06-01
Mating-type genes in fungi encode regulators of mating and sexual development. Heterothallic ascomycete species require different sets of mating-type genes to control nonself-recognition and mating of compatible partners of different mating types. Homothallic (self-fertile) species also carry mating-type genes in their genome that are essential for sexual development. To analyze the molecular basis of homothallism and the role of mating-type genes during fruiting-body development, we deleted each of the three genes, SmtA-1 (MAT1-1-1), SmtA-2 (MAT1-1-2), and SmtA-3 (MAT1-1-3), contained in the MAT1-1 part of the mating-type locus of the homothallic ascomycete species Sordaria macrospora. Phenotypic analysis of deletion mutants revealed that the PPF domain protein-encoding gene SmtA-2 is essential for sexual reproduction, whereas the alpha domain protein-encoding genes SmtA-1 and SmtA-3 play no role in fruiting-body development. By means of cross-species microarray analysis using Neurospora crassa oligonucleotide microarrays hybridized with S. macrospora targets and quantitative real-time PCR, we identified genes expressed under the control of SmtA-1 and SmtA-2. Both genes are involved in the regulation of gene expression, including that of pheromone genes.
Klix, V.; Nowrousian, M.; Ringelberg, C.; Loros, J. J.; Dunlap, J. C.; Pöggeler, S.
2010-01-01
Mating-type genes in fungi encode regulators of mating and sexual development. Heterothallic ascomycete species require different sets of mating-type genes to control nonself-recognition and mating of compatible partners of different mating types. Homothallic (self-fertile) species also carry mating-type genes in their genome that are essential for sexual development. To analyze the molecular basis of homothallism and the role of mating-type genes during fruiting-body development, we deleted each of the three genes, SmtA-1 (MAT1-1-1), SmtA-2 (MAT1-1-2), and SmtA-3 (MAT1-1-3), contained in the MAT1-1 part of the mating-type locus of the homothallic ascomycete species Sordaria macrospora. Phenotypic analysis of deletion mutants revealed that the PPF domain protein-encoding gene SmtA-2 is essential for sexual reproduction, whereas the α domain protein-encoding genes SmtA-1 and SmtA-3 play no role in fruiting-body development. By means of cross-species microarray analysis using Neurospora crassa oligonucleotide microarrays hybridized with S. macrospora targets and quantitative real-time PCR, we identified genes expressed under the control of SmtA-1 and SmtA-2. Both genes are involved in the regulation of gene expression, including that of pheromone genes. PMID:20435701
NASA Astrophysics Data System (ADS)
Liu, Robin H.; Lodes, Mike; Fuji, H. Sho; Danley, David; McShea, Andrew
Microarray assays typically involve multistage sample processing and fluidic handling, which are generally labor-intensive and time-consuming. Automation of these processes would improve robustness, reduce run-to-run and operator-to-operator variation, and reduce costs. In this chapter, a fully integrated and self-contained microfluidic biochip device that has been developed to automate the fluidic handling steps for microarray-based gene expression or genotyping analysis is presented. The device consists of a semiconductor-based CustomArray® chip with 12,000 features and a microfluidic cartridge. The CustomArray was manufactured using a semiconductor-based in situ synthesis technology. The micro-fluidic cartridge consists of microfluidic pumps, mixers, valves, fluid channels, and reagent storage chambers. Microarray hybridization and subsequent fluidic handling and reactions (including a number of washing and labeling steps) were performed in this fully automated and miniature device before fluorescent image scanning of the microarray chip. Electrochemical micropumps were integrated in the cartridge to provide pumping of liquid solutions. A micromixing technique based on gas bubbling generated by electrochemical micropumps was developed. Low-cost check valves were implemented in the cartridge to prevent cross-talk of the stored reagents. Gene expression study of the human leukemia cell line (K562) and genotyping detection and sequencing of influenza A subtypes have been demonstrated using this integrated biochip platform. For gene expression assays, the microfluidic CustomArray device detected sample RNAs with a concentration as low as 0.375 pM. Detection was quantitative over more than three orders of magnitude. Experiment also showed that chip-to-chip variability was low indicating that the integrated microfluidic devices eliminate manual fluidic handling steps that can be a significant source of variability in genomic analysis. The genotyping results showed that the device identified influenza A hemagglutinin and neuraminidase subtypes and sequenced portions of both genes, demonstrating the potential of integrated microfluidic and microarray technology for multiple virus detection. The device provides a cost-effective solution to eliminate labor-intensive and time-consuming fluidic handling steps and allows microarray-based DNA analysis in a rapid and automated fashion.
Classification of Microarray Data Using Kernel Fuzzy Inference System
Kumar Rath, Santanu
2014-01-01
The DNA microarray classification technique has gained more popularity in both research and practice. In real data analysis, such as microarray data, the dataset contains a huge number of insignificant and irrelevant features that tend to lose useful information. Classes with high relevance and feature sets with high significance are generally referred for the selected features, which determine the samples classification into their respective classes. In this paper, kernel fuzzy inference system (K-FIS) algorithm is applied to classify the microarray data (leukemia) using t-test as a feature selection method. Kernel functions are used to map original data points into a higher-dimensional (possibly infinite-dimensional) feature space defined by a (usually nonlinear) function ϕ through a mathematical process called the kernel trick. This paper also presents a comparative study for classification using K-FIS along with support vector machine (SVM) for different set of features (genes). Performance parameters available in the literature such as precision, recall, specificity, F-measure, ROC curve, and accuracy are considered to analyze the efficiency of the classification model. From the proposed approach, it is apparent that K-FIS model obtains similar results when compared with SVM model. This is an indication that the proposed approach relies on kernel function. PMID:27433543
MiMiR – an integrated platform for microarray data sharing, mining and analysis
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.
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.
miRNA 206 and miRNA 574-5p are highly expression in coronary artery disease
Zhou, Jianqing; Shao, Guofeng; Chen, Xiaoliang; Yang, Xi; Huang, Xiaoyan; Peng, Ping; Ba, Yanna; Zhang, Lin; Jehangir, Tashina; Bu, Shizhong; Liu, Ningsheng; Lian, Jiangfang
2015-01-01
Coronary artery disease (CAD) is the leading cause of human morbidity and mortality worldwide. Innovative diagnostic biomarkers are a pressing need for this disease. miRNAs profiling is an innovative method of identifying biomarkers for many diseases and could be proven as a powerful tool in the diagnosis and treatment of CAD. We performed miRNA microarray analysis from the plasma of three CAD patients and three healthy controls. Subsequently, we performed quantitative real-time PCR (qRT-PCR) analysis of miRNA expression in plasma of another 67 CAD patients and 67 healthy controls. We identified two miRNAs (miR-206 and miR-574-5p) that were significantly up-regulated in CAD patients as compared with healthy controls (P<0.05). The receiver operating characteristic (ROC) curves indicated these two miRNAs had great potential to provide sensitive and specific diagnostic value for CAD. PMID:26685009
Expression Comparison of Oil Biosynthesis Genes in Oil Palm Mesocarp Tissue Using Custom Array
Wong, Yick Ching; Kwong, Qi Bin; Lee, Heng Leng; Ong, Chuang Kee; Mayes, Sean; Chew, Fook Tim; Appleton, David R.; Kulaveerasingam, Harikrishna
2014-01-01
Gene expression changes that occur during mesocarp development are a major research focus in oil palm research due to the economic importance of this tissue and the relatively rapid increase in lipid content to very high levels at fruit ripeness. Here, we report the development of a transcriptome-based 105,000-probe oil palm mesocarp microarray. The expression of genes involved in fatty acid (FA) and triacylglycerol (TAG) assembly, along with the tricarboxylic acid cycle (TCA) and glycolysis pathway at 16 Weeks After Anthesis (WAA) exhibited significantly higher signals compared to those obtained from a cross-species hybridization to the Arabidopsis (p-value < 0.01), and rice (p-value < 0.01) arrays. The oil palm microarray data also showed comparable correlation of expression (r2 = 0.569, p < 0.01) throughout mesocarp development to transcriptome (RNA sequencing) data, and improved correlation over quantitative real-time PCR (qPCR) (r2 = 0.721, p < 0.01) of the same RNA samples. The results confirm the advantage of the custom microarray over commercially available arrays derived from model species. We demonstrate the utility of this custom microarray to gain a better understanding of gene expression patterns in the oil palm mesocarp that may lead to increasing future oil yield. PMID:27600348
Expression Comparison of Oil Biosynthesis Genes in Oil Palm Mesocarp Tissue Using Custom Array.
Wong, Yick Ching; Kwong, Qi Bin; Lee, Heng Leng; Ong, Chuang Kee; Mayes, Sean; Chew, Fook Tim; Appleton, David R; Kulaveerasingam, Harikrishna
2014-11-13
Gene expression changes that occur during mesocarp development are a major research focus in oil palm research due to the economic importance of this tissue and the relatively rapid increase in lipid content to very high levels at fruit ripeness. Here, we report the development of a transcriptome-based 105,000-probe oil palm mesocarp microarray. The expression of genes involved in fatty acid (FA) and triacylglycerol (TAG) assembly, along with the tricarboxylic acid cycle (TCA) and glycolysis pathway at 16 Weeks After Anthesis (WAA) exhibited significantly higher signals compared to those obtained from a cross-species hybridization to the Arabidopsis (p-value < 0.01), and rice (p-value < 0.01) arrays. The oil palm microarray data also showed comparable correlation of expression (r² = 0.569, p < 0.01) throughout mesocarp development to transcriptome (RNA sequencing) data, and improved correlation over quantitative real-time PCR (qPCR) (r² = 0.721, p < 0.01) of the same RNA samples. The results confirm the advantage of the custom microarray over commercially available arrays derived from model species. We demonstrate the utility of this custom microarray to gain a better understanding of gene expression patterns in the oil palm mesocarp that may lead to increasing future oil yield.
Gupta, Sanjay K.; Dahiya, Saurabh; Lundy, Robert F.; Kumar, Ashok
2010-01-01
Background Skeletal muscle wasting is a debilitating consequence of large number of disease states and conditions. Tumor necrosis factor-α (TNF-α) is one of the most important muscle-wasting cytokine, elevated levels of which cause significant muscular abnormalities. However, the underpinning molecular mechanisms by which TNF-α causes skeletal muscle wasting are less well-understood. Methodology/Principal Findings We have used microarray, quantitative real-time PCR (QRT-PCR), Western blot, and bioinformatics tools to study the effects of TNF-α on various molecular pathways and gene networks in C2C12 cells (a mouse myoblastic cell line). Microarray analyses of C2C12 myotubes treated with TNF-α (10 ng/ml) for 18h showed differential expression of a number of genes involved in distinct molecular pathways. The genes involved in nuclear factor-kappa B (NF-kappaB) signaling, 26s proteasome pathway, Notch1 signaling, and chemokine networks are the most important ones affected by TNF-α. The expression of some of the genes in microarray dataset showed good correlation in independent QRT-PCR and Western blot assays. Analysis of TNF-treated myotubes showed that TNF-α augments the activity of both canonical and alternative NF-κB signaling pathways in myotubes. Bioinformatics analyses of microarray dataset revealed that TNF-α affects the activity of several important pathways including those involved in oxidative stress, hepatic fibrosis, mitochondrial dysfunction, cholesterol biosynthesis, and TGF-β signaling. Furthermore, TNF-α was found to affect the gene networks related to drug metabolism, cell cycle, cancer, neurological disease, organismal injury, and abnormalities in myotubes. Conclusions TNF-α regulates the expression of multiple genes involved in various toxic pathways which may be responsible for TNF-induced muscle loss in catabolic conditions. Our study suggests that TNF-α activates both canonical and alternative NF-κB signaling pathways in a time-dependent manner in skeletal muscle cells. The study provides novel insight into the mechanisms of action of TNF-α in skeletal muscle cells. PMID:20967264
SoFoCles: feature filtering for microarray classification based on gene ontology.
Papachristoudis, Georgios; Diplaris, Sotiris; Mitkas, Pericles A
2010-02-01
Marker gene selection has been an important research topic in the classification analysis of gene expression data. Current methods try to reduce the "curse of dimensionality" by using statistical intra-feature set calculations, or classifiers that are based on the given dataset. In this paper, we present SoFoCles, an interactive tool that enables semantic feature filtering in microarray classification problems with the use of external, well-defined knowledge retrieved from the Gene Ontology. The notion of semantic similarity is used to derive genes that are involved in the same biological path during the microarray experiment, by enriching a feature set that has been initially produced with legacy methods. Among its other functionalities, SoFoCles offers a large repository of semantic similarity methods that are used in order to derive feature sets and marker genes. The structure and functionality of the tool are discussed in detail, as well as its ability to improve classification accuracy. Through experimental evaluation, SoFoCles is shown to outperform other classification schemes in terms of classification accuracy in two real datasets using different semantic similarity computation approaches.
Microarray profiling of diaphyseal bone of rats suffering from hypervitaminosis A.
Lind, Thomas; Hu, Lijuan; Lind, P Monica; Sugars, Rachael; Andersson, Göran; Jacobson, Annica; Melhus, Håkan
2012-03-01
Vitamin A is the only known compound that produces spontaneous fractures in rats. In an effort to resolve the molecular mechanism behind this effect, we fed young male rats high doses of vitamin A and performed microarray analysis of diaphyseal bone with and without marrow after 1 week, i.e., just before the first fractures appeared. Of the differentially expressed genes in cortical bone, including marrow, 98% were upregulated. In contrast, hypervitaminotic cortical bone without marrow showed reduced expression of 37% of differentially expressed genes. Gene ontology (GO) analysis revealed that only samples containing bone marrow were associated with a GO term, which principally represented extracellular matrix. This is consistent with the histological findings of increased endosteal/marrow osteoblast number. Fourteen genes, including Cyp26b1, which is known to be upregulated by vitamin A, were selected and verified by real-time PCR. In addition, immunohistochemical staining of bone sections confirmed that the bone-specific molecule osteoadherin was upregulated. Further analysis of the major gene-expression changes revealed apparent augmented Wnt signaling in the sample containing bone marrow but reduced Wnt signaling in cortical bone. Moreover, induced expression of hypoxia-associated genes was found only in samples containing bone marrow. Together, these results highlight the importance of compartment-specific analysis of bone and corroborate previous observations of compartment-specific effects of vitamin A, with reduced activity in cortical bone but increased activity in the endosteal/marrow compartment. We specifically identify potential key osteoblast-, Wnt signaling-, and hypoxia-associated genes in the processes leading to spontaneous fractures.
Ishiwata, Ryosuke R; Morioka, Masaki S; Ogishima, Soichi; Tanaka, Hiroshi
2009-02-15
BioCichlid is a 3D visualization system of time-course microarray data on molecular networks, aiming at interpretation of gene expression data by transcriptional relationships based on the central dogma with physical and genetic interactions. BioCichlid visualizes both physical (protein) and genetic (regulatory) network layers, and provides animation of time-course gene expression data on the genetic network layer. Transcriptional regulations are represented to bridge the physical network (transcription factors) and genetic network (regulated genes) layers, thus integrating promoter analysis into the pathway mapping. BioCichlid enhances the interpretation of microarray data and allows for revealing the underlying mechanisms causing differential gene expressions. BioCichlid is freely available and can be accessed at http://newton.tmd.ac.jp/. Source codes for both biocichlid server and client are also available.
cDNA microarray analysis of esophageal cancer: discoveries and prospects.
Shimada, Yutaka; Sato, Fumiaki; Shimizu, Kazuharu; Tsujimoto, Gozoh; Tsukada, Kazuhiro
2009-07-01
Recent progress in molecular biology has revealed many genetic and epigenetic alterations that are involved in the development and progression of esophageal cancer. Microarray analysis has also revealed several genetic networks that are involved in esophageal cancer. However, clinical application of microarray techniques and use of microarray data have not yet occurred. In this review, we focus on the recent developments and problems with microarray analysis of esophageal cancer.
Apparently low reproducibility of true differential expression discoveries in microarray studies.
Zhang, Min; Yao, Chen; Guo, Zheng; Zou, Jinfeng; Zhang, Lin; Xiao, Hui; Wang, Dong; Yang, Da; Gong, Xue; Zhu, Jing; Li, Yanhui; Li, Xia
2008-09-15
Differentially expressed gene (DEG) lists detected from different microarray studies for a same disease are often highly inconsistent. Even in technical replicate tests using identical samples, DEG detection still shows very low reproducibility. It is often believed that current small microarray studies will largely introduce false discoveries. Based on a statistical model, we show that even in technical replicate tests using identical samples, it is highly likely that the selected DEG lists will be very inconsistent in the presence of small measurement variations. Therefore, the apparently low reproducibility of DEG detection from current technical replicate tests does not indicate low quality of microarray technology. We also demonstrate that heterogeneous biological variations existing in real cancer data will further reduce the overall reproducibility of DEG detection. Nevertheless, in small subsamples from both simulated and real data, the actual false discovery rate (FDR) for each DEG list tends to be low, suggesting that each separately determined list may comprise mostly true DEGs. Rather than simply counting the overlaps of the discovery lists from different studies for a complex disease, novel metrics are needed for evaluating the reproducibility of discoveries characterized with correlated molecular changes. Supplementaty information: Supplementary data are available at Bioinformatics online.
Klempan, Timothy A; Ernst, Carl; Deleva, Vesselina; Labonte, Benoit; Turecki, Gustavo
2009-11-01
A number of studies have suggested deficits in myelination and glial gene expression in different psychiatric disorders. We examined the brain expression and genetic/epigenetic regulation of QKI, an oligodendrocyte-specific RNA binding protein important for cell development and myelination. The microarray-based expression of QKI was evaluated in cortical and subcortical brain regions from suicide victims with a diagnosis of major depression (n = 16) and control subjects (n = 13). These findings were also assessed with a real-time (quantitative polymerase chain reaction [qPCR]) approach, with QKI protein levels evaluated through immunoblotting. Identification of a QKI promoter sequence was then used to examine genetic and epigenetic variation at the QKI locus. The messenger RNA (mRNA) levels of multiple transcripts of QKI were evaluated on Affymetrix microarrays, revealing significant reductions in 11 cortical regions and the hippocampus and amygdala of suicide victims compared with control subjects. Microarray findings were confirmed by qPCR, and reduced expression of QKI protein was identified in orbitofrontal cortex. Analysis of promoter variation and methylation state in a subset of individuals did not identify differences at the genetic or epigenetic level between depressed suicide victims and control subjects. The observation of consistent reductions in multiple isoforms of QKI mRNA in depressed suicide victims supports the growing body of evidence for a role of myelination-related deficits in the etiology of psychiatric disorders. A specific role of QKI in this process is implied by its reduced expression and known interactions with genes involved in oligodendrocyte determination; however, QKI gene variation responsible for these changes remains to be identified.
Chen, Jie; Fu, Ziyi; Ji, Chenbo; Gu, Pingqing; Xu, Pengfei; Yu, Ningzhu; Kan, Yansheng; Wu, Xiaowei; Shen, Rong; Shen, Yan
2015-05-01
The human uterine cervix carcinoma is one of the most well-known malignancy reproductive system cancers, which threatens women health globally. However, the mechanisms of the oncogenesis and development process of cervix carcinoma are not yet fully understood. Long non-coding RNAs (lncRNAs) have been proved to play key roles in various biological processes, especially development of cancer. The function and mechanism of lncRNAs on cervix carcinoma is still rarely reported. We selected 3 cervix cancer and normal cervix tissues separately, then performed lncRNA microarray to detect the differentially expressed lncRNAs. Subsequently, we explored the potential function of these dysregulated lncRNAs through online bioinformatics databases. Finally, quantity real-time PCR was carried out to confirm the expression levels of these dysregulated lncRNAs in cervix cancer and normal tissues. We uncovered the profiles of differentially expressed lncRNAs between normal and cervix carcinoma tissues by using the microarray techniques, and found 1622 upregulated and 3026 downregulated lncRNAs (fold-change>2.0) in cervix carcinoma compared to the normal cervical tissue. Furthermore, we found HOXA11-AS might participate in cervix carcinogenesis by regulating HOXA11, which is involved in regulating biological processes of cervix cancer. This study afforded expression profiles of lncRNAs between cervix carcinoma tissue and normal cervical tissue, which could provide database for further research about the function and mechanism of key-lncRNAs in cervix carcinoma, and might be helpful to explore potential diagnosis factors and therapeutic targets for cervix carcinoma. Copyright © 2015 Elsevier Masson SAS. All rights reserved.
Qian, Airong; Di, Shengmeng; Gao, Xiang; Zhang, Wei; Tian, Zongcheng; Li, Jingbao; Hu, Lifang; Yang, Pengfei; Yin, Dachuan; Shang, Peng
2009-07-01
The diamagnetic levitation as a novel ground-based model for simulating a reduced gravity environment has been widely applied in many fields. In this study, a special designed superconducting magnet, which can produce three apparent gravity levels (0, 1, and 2 g), namely high magneto-gravitational environment (HMGE), was used to simulate space gravity environment. The effects of HMGE on osteoblast gene expression profile were investigated by microarray. Genes sensitive to diamagnetic levitation environment (0 g), gravity changes, and high magnetic field changes were sorted on the basis of typical cell functions. Cytoskeleton, as an intracellular load-bearing structure, plays an important role in gravity perception. Therefore, 13 cytoskeleton-related genes were chosen according to the results of microarray analysis, and the expressions of these genes were found to be altered under HMGE by real-time PCR. Based on the PCR results, the expressions of WASF2 (WAS protein family, member 2), WIPF1 (WAS/WASL interacting protein family, member 1), paxillin, and talin 1 were further identified by western blot assay. Results indicated that WASF2 and WIPF1 were more sensitive to altered gravity levels, and talin 1 and paxillin were sensitive to both magnetic field and gravity changes. Our findings demonstrated that HMGE can affect osteoblast gene expression profile and cytoskeleton-related genes expression. The identification of mechanosensitive genes may enhance our understandings to the mechanism of bone loss induced by microgravity and may provide some potential targets for preventing and treating bone loss or osteoporosis.
Importing MAGE-ML format microarray data into BioConductor.
Durinck, Steffen; Allemeersch, Joke; Carey, Vincent J; Moreau, Yves; De Moor, Bart
2004-12-12
The microarray gene expression markup language (MAGE-ML) is a widely used XML (eXtensible Markup Language) standard for describing and exchanging information about microarray experiments. It can describe microarray designs, microarray experiment designs, gene expression data and data analysis results. We describe RMAGEML, a new Bioconductor package that provides a link between cDNA microarray data stored in MAGE-ML format and the Bioconductor framework for preprocessing, visualization and analysis of microarray experiments. http://www.bioconductor.org. Open Source.
MASQOT: a method for cDNA microarray spot quality control
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
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.
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
Alvarez, Hector; Corvalan, Alejandro; Roa, Juan C; Argani, Pedram; Murillo, Francisco; Edwards, Jennifer; Beaty, Robert; Feldmann, Georg; Hong, Seung-Mo; Mullendore, Michael; Roa, Ivan; Ibañez, Luis; Pimentel, Fernando; Diaz, Alfonso; Riggins, Gregory J; Maitra, Anirban
2008-05-01
Gallbladder cancer (GBC) is an uncommon neoplasm in the United States, but one with high mortality rates. This malignancy remains largely understudied at the molecular level such that few targeted therapies or predictive biomarkers exist. We built the first series of serial analysis of gene expression (SAGE) libraries from GBC and nonneoplastic gallbladder mucosa, composed of 21-bp long-SAGE tags. SAGE libraries were generated from three stage-matched GBC patients (representing Hispanic/Latino, Native American, and Caucasian ethnicities, respectively) and one histologically alithiasic gallbladder. Real-time quantitative PCR was done on microdissected epithelium from five matched GBC and corresponding nonneoplastic gallbladder mucosa. Immunohistochemical analysis was done on a panel of 182 archival GBC in high-throughput tissue microarray format. SAGE tags corresponding to connective tissue growth factor (CTGF) transcripts were identified as differentially overexpressed in all pairwise comparisons of GBC (P < 0.001). Real-time quantitative PCR confirmed significant overexpression of CTGF transcripts in microdissected primary GBC (P < 0.05), but not in metastatic GBC, compared with nonneoplastic gallbladder epithelium. By immunohistochemistry, 66 of 182 (36%) GBC had high CTGF antigen labeling, which was significantly associated with better survival on univariate analysis (P = 0.0069, log-rank test). An unbiased analysis of the GBC transcriptome by SAGE has identified CTGF expression as a predictive biomarker of favorable prognosis in this malignancy. The SAGE libraries from GBC and nonneoplastic gallbladder mucosa are publicly available at the Cancer Genome Anatomy Project web site and should facilitate much needed research into this lethal neoplasm.
Tomato Expression Database (TED): a suite of data presentation and analysis tools
Fei, Zhangjun; Tang, Xuemei; Alba, Rob; Giovannoni, James
2006-01-01
The Tomato Expression Database (TED) includes three integrated components. The Tomato Microarray Data Warehouse serves as a central repository for raw gene expression data derived from the public tomato cDNA microarray. In addition to expression data, TED stores experimental design and array information in compliance with the MIAME guidelines and provides web interfaces for researchers to retrieve data for their own analysis and use. The Tomato Microarray Expression Database contains normalized and processed microarray data for ten time points with nine pair-wise comparisons during fruit development and ripening in a normal tomato variety and nearly isogenic single gene mutants impacting fruit development and ripening. Finally, the Tomato Digital Expression Database contains raw and normalized digital expression (EST abundance) data derived from analysis of the complete public tomato EST collection containing >150 000 ESTs derived from 27 different non-normalized EST libraries. This last component also includes tools for the comparison of tomato and Arabidopsis digital expression data. A set of query interfaces and analysis, and visualization tools have been developed and incorporated into TED, which aid users in identifying and deciphering biologically important information from our datasets. TED can be accessed at . PMID:16381976
Tomato Expression Database (TED): a suite of data presentation and analysis tools.
Fei, Zhangjun; Tang, Xuemei; Alba, Rob; Giovannoni, James
2006-01-01
The Tomato Expression Database (TED) includes three integrated components. The Tomato Microarray Data Warehouse serves as a central repository for raw gene expression data derived from the public tomato cDNA microarray. In addition to expression data, TED stores experimental design and array information in compliance with the MIAME guidelines and provides web interfaces for researchers to retrieve data for their own analysis and use. The Tomato Microarray Expression Database contains normalized and processed microarray data for ten time points with nine pair-wise comparisons during fruit development and ripening in a normal tomato variety and nearly isogenic single gene mutants impacting fruit development and ripening. Finally, the Tomato Digital Expression Database contains raw and normalized digital expression (EST abundance) data derived from analysis of the complete public tomato EST collection containing >150,000 ESTs derived from 27 different non-normalized EST libraries. This last component also includes tools for the comparison of tomato and Arabidopsis digital expression data. A set of query interfaces and analysis, and visualization tools have been developed and incorporated into TED, which aid users in identifying and deciphering biologically important information from our datasets. TED can be accessed at http://ted.bti.cornell.edu.
Droplet Microarray Based on Superhydrophobic-Superhydrophilic Patterns for Single Cell Analysis.
Jogia, Gabriella E; Tronser, Tina; Popova, Anna A; Levkin, Pavel A
2016-12-09
Single-cell analysis provides fundamental information on individual cell response to different environmental cues and is a growing interest in cancer and stem cell research. However, current existing methods are still facing challenges in performing such analysis in a high-throughput manner whilst being cost-effective. Here we established the Droplet Microarray (DMA) as a miniaturized screening platform for high-throughput single-cell analysis. Using the method of limited dilution and varying cell density and seeding time, we optimized the distribution of single cells on the DMA. We established culturing conditions for single cells in individual droplets on DMA obtaining the survival of nearly 100% of single cells and doubling time of single cells comparable with that of cells cultured in bulk cell population using conventional methods. Our results demonstrate that the DMA is a suitable platform for single-cell analysis, which carries a number of advantages compared with existing technologies allowing for treatment, staining and spot-to-spot analysis of single cells over time using conventional analysis methods such as microscopy.
Flexible hemispheric microarrays of highly pressure-sensitive sensors based on breath figure method.
Wang, Zhihui; Zhang, Ling; Liu, Jin; Jiang, Hao; Li, Chunzhong
2018-05-30
Recently, flexible pressure sensors featuring high sensitivity, broad sensing range and real-time detection have aroused great attention owing to their crucial role in the development of artificial intelligent devices and healthcare systems. Herein, highly sensitive pressure sensors based on hemisphere-microarray flexible substrates are fabricated via inversely templating honeycomb structures deriving from a facile and static breath figure process. The interlocked and subtle microstructures greatly improve the sensing characteristics and compressibility of the as-prepared pressure sensor, endowing it a sensitivity as high as 196 kPa-1 and a wide pressure sensing range (0-100 kPa), as well as other superior performance, including a lower detection limit of 0.5 Pa, fast response time (<26 ms) and high reversibility (>10 000 cycles). Based on the outstanding sensing performance, the potential capability of our pressure sensor in capturing physiological information and recognizing speech signals has been demonstrated, indicating promising application in wearable and intelligent electronics.
Molecular insights into the progression of crystalline silica-induced pulmonary toxicity in rats.
Sellamuthu, Rajendran; Umbright, Christina; Roberts, Jenny R; Cumpston, Amy; McKinney, Walter; Chen, Bean T; Frazer, David; Li, Shengqiao; Kashon, Michael; Joseph, Pius
2013-04-01
Identification of molecular target(s) and mechanism(s) of silica-induced pulmonary toxicity is important for the intervention and/or prevention of diseases associated with exposure to silica. Rats were exposed to crystalline silica by inhalation (15 mg m(-3), 6 h per day, 5 days) and global gene expression profile was determined in the lungs by microarray analysis at 1, 2, 4, 8 and 16 weeks following termination of silica exposure. The number of significantly differentially expressed genes (>1.5-fold change and <0.01 false discovery rate P-value) detected in the lungs during the post-exposure time intervals analyzed exhibited a steady increase in parallel with the progression of silica-induced pulmonary toxicity noticed in the rats. Quantitative real-time PCR analysis of a representative set of 10 genes confirmed the microarray findings. The number of biological functions, canonical pathways and molecular networks significantly affected by silica exposure, as identified by the bioinformatics analysis of the significantly differentially expressed genes detected during the post-exposure time intervals, also exhibited a steady increase similar to the silica-induced pulmonary toxicity. Genes involved in oxidative stress, inflammation, respiratory diseases, cancer, and tissue remodeling and fibrosis were significantly differentially expressed in the rat lungs; however, unresolved inflammation was the single most significant biological response to pulmonary exposure to silica. Excessive mucus production, as implicated by significant overexpression of the pendrin coding gene, SLC26A4, was identified as a potential novel mechanism for silica-induced pulmonary toxicity. Collectively, the findings of our study provided insights into the molecular mechanisms underlying the progression of crystalline silica-induced pulmonary toxicity in the rat. Published 2012. This article is a US Government work and is in the public domain in the USA. Published 2012. This article is a US Government work and is in the public domain in the USA.
Killion, Patrick J; Sherlock, Gavin; Iyer, Vishwanath R
2003-01-01
Background The power of microarray analysis can be realized only if data is systematically archived and linked to biological annotations as well as analysis algorithms. Description The Longhorn Array Database (LAD) is a MIAME compliant microarray database that operates on PostgreSQL and Linux. It is a fully open source version of the Stanford Microarray Database (SMD), one of the largest microarray databases. LAD is available at Conclusions Our development of LAD provides a simple, free, open, reliable and proven solution for storage and analysis of two-color microarray data. PMID:12930545
Unsupervised Bayesian linear unmixing of gene expression microarrays.
Bazot, Cécile; Dobigeon, Nicolas; Tourneret, Jean-Yves; Zaas, Aimee K; Ginsburg, Geoffrey S; Hero, Alfred O
2013-03-19
This paper introduces a new constrained model and the corresponding algorithm, called unsupervised Bayesian linear unmixing (uBLU), to identify biological signatures from high dimensional assays like gene expression microarrays. The basis for uBLU is a Bayesian model for the data samples which are represented as an additive mixture of random positive gene signatures, called factors, with random positive mixing coefficients, called factor scores, that specify the relative contribution of each signature to a specific sample. The particularity of the proposed method is that uBLU constrains the factor loadings to be non-negative and the factor scores to be probability distributions over the factors. Furthermore, it also provides estimates of the number of factors. A Gibbs sampling strategy is adopted here to generate random samples according to the posterior distribution of the factors, factor scores, and number of factors. These samples are then used to estimate all the unknown parameters. Firstly, the proposed uBLU method is applied to several simulated datasets with known ground truth and compared with previous factor decomposition methods, such as principal component analysis (PCA), non negative matrix factorization (NMF), Bayesian factor regression modeling (BFRM), and the gradient-based algorithm for general matrix factorization (GB-GMF). Secondly, we illustrate the application of uBLU on a real time-evolving gene expression dataset from a recent viral challenge study in which individuals have been inoculated with influenza A/H3N2/Wisconsin. We show that the uBLU method significantly outperforms the other methods on the simulated and real data sets considered here. The results obtained on synthetic and real data illustrate the accuracy of the proposed uBLU method when compared to other factor decomposition methods from the literature (PCA, NMF, BFRM, and GB-GMF). The uBLU method identifies an inflammatory component closely associated with clinical symptom scores collected during the study. Using a constrained model allows recovery of all the inflammatory genes in a single factor.
Wang, Shih-Han; Cheng, Chuen-Yu; Tang, Pin-Chi; Chen, Chih-Feng; Chen, Hsin-Hsin; Lee, Yen-Pai; Huang, San-Yuan
2013-01-15
Acute heat stress affects genes involved in spermatogenesis in mammals. However, there is apparently no elaborate research on the effects of acute heat stress on gene expression in avian testes. The purpose of this study was to investigate global gene expression in testes of the L2 strain of Taiwan country chicken after acute heat stress. Twelve roosters, 45 weeks old, were allocated into four groups, including control roosters kept at 25 °C, roosters subjected to 38 °C acute heat stress for 4 hours without recovery, with 2-hour recovery, and with 6-hour recovery, respectively. Testis samples were collected for RNA isolation and microarray analysis. Based on gene expression profiles, 169 genes were upregulated and 140 genes were downregulated after heat stress using a cutoff value of twofold or greater change. Based on gene ontology analysis, differentially expressed genes were mainly related to response to stress, transport, signal transduction, and metabolism. A functional network analysis displayed that heat shock protein genes and related chaperones were the major upregulated groups in chicken testes after acute heat stress. A quantitative real-time polymerase chain reaction analysis of mRNA expressions of HSP70, HSP90AA1, BAG3, SERPINB2, HSP25, DNAJA4, CYP3A80, CIRBP, and TAGLN confirmed the results of the microarray analysis. Because the HSP genes (HSP25, HSP70, and HSP90AA1) and the antiapoptotic BAG3 gene were dramatically altered in heat-stressed chicken testes, we concluded that these genes were important factors in the avian testes under acute heat stress. Whether these genes could be candidate genes for thermotolerance in roosters requires further investigation. Copyright © 2013 Elsevier Inc. All rights reserved.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Daly, Don S.; Anderson, Kevin K.; White, Amanda M.
Background: A microarray of enzyme-linked immunosorbent assays, or ELISA microarray, predicts simultaneously the concentrations of numerous proteins in a small sample. These predictions, however, are uncertain due to processing error and biological variability. Making sound biological inferences as well as improving the ELISA microarray process require require both concentration predictions and creditable estimates of their errors. Methods: We present a statistical method based on monotonic spline statistical models, penalized constrained least squares fitting (PCLS) and Monte Carlo simulation (MC) to predict concentrations and estimate prediction errors in ELISA microarray. PCLS restrains the flexible spline to a fit of assay intensitymore » that is a monotone function of protein concentration. With MC, both modeling and measurement errors are combined to estimate prediction error. The spline/PCLS/MC method is compared to a common method using simulated and real ELISA microarray data sets. Results: In contrast to the rigid logistic model, the flexible spline model gave credible fits in almost all test cases including troublesome cases with left and/or right censoring, or other asymmetries. For the real data sets, 61% of the spline predictions were more accurate than their comparable logistic predictions; especially the spline predictions at the extremes of the prediction curve. The relative errors of 50% of comparable spline and logistic predictions differed by less than 20%. Monte Carlo simulation rendered acceptable asymmetric prediction intervals for both spline and logistic models while propagation of error produced symmetric intervals that diverged unrealistically as the standard curves approached horizontal asymptotes. Conclusions: The spline/PCLS/MC method is a flexible, robust alternative to a logistic/NLS/propagation-of-error method to reliably predict protein concentrations and estimate their errors. The spline method simplifies model selection and fitting, and reliably estimates believable prediction errors. For the 50% of the real data sets fit well by both methods, spline and logistic predictions are practically indistinguishable, varying in accuracy by less than 15%. The spline method may be useful when automated prediction across simultaneous assays of numerous proteins must be applied routinely with minimal user intervention.« less
Effect of storage time on gene expression data acquired from unfrozen archived newborn blood spots.
Ho, Nhan T; Busik, Julia V; Resau, James H; Paneth, Nigel; Khoo, Sok Kean
2016-11-01
Unfrozen archived newborn blood spots (NBS) have been shown to retain sufficient messenger RNA (mRNA) for gene expression profiling. However, the effect of storage time at ambient temperature for NBS samples in relation to the quality of gene expression data is relatively unknown. Here, we evaluated mRNA expression from quantitative real-time PCR (qRT-PCR) and microarray data obtained from NBS samples stored at ambient temperature to determine the effect of storage time on the quality of gene expression. These data were generated in a previous case-control study examining NBS in 53 children with cerebral palsy (CP) and 53 matched controls. NBS sample storage period ranged from 3 to 16years at ambient temperature. We found persistently low RNA integrity numbers (RIN=2.3±0.71) and 28S/18S rRNA ratios (~0) across NBS samples for all storage periods. In both qRT-PCR and microarray data, the expression of three common housekeeping genes-beta cytoskeletal actin (ACTB), glyceraldehyde 3-phosphate dehydrogenase (GAPDH), and peptidylprolyl isomerase A (PPIA)-decreased with increased storage time. Median values of each microarray probe intensity at log 2 scale also decreased over time. After eight years of storage, probe intensity values were largely reduced to background intensity levels. Of 21,500 genes tested, 89% significantly decreased in signal intensity, with 13,551, 10,730, and 9925 genes detected within 5years, > 5 to <10years, and >10years of storage, respectively. We also examined the expression of two gender-specific genes (X inactivation-specific transcript, XIST and lysine-specific demethylase 5D, KDM5D) and seven gene sets representing the inflammatory, hypoxic, coagulative, and thyroidal pathways hypothesized to be related to CP risk to determine the effect of storage time on the detection of these biologically relevant genes. We found the gender-specific genes and CP-related gene sets detectable in all storage periods, but exhibited differential expression (between male vs. female or CP vs. control) only within the first six years of storage. We concluded that gene expression data quality deteriorates in unfrozen archived NBS over time and that differential gene expression profiling and analysis is recommended for those NBS samples collected and stored within six years at ambient temperature. Copyright © 2016 Elsevier Inc. All rights reserved.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Jenny, Matthew J.; Department of Biological Sciences, University of Alabama, Tuscaloosa, AL 35487; Aluru, Neelakanteswar
Although many drugs and environmental chemicals are teratogenic, the mechanisms by which most toxicants disrupt embryonic development are not well understood. MicroRNAs, single-stranded RNA molecules of ∼ 22 nt that regulate protein expression by inhibiting mRNA translation and promoting mRNA sequestration or degradation, are important regulators of a variety of cellular processes including embryonic development and cellular differentiation. Recent studies have demonstrated that exposure to xenobiotics can alter microRNA expression and contribute to the mechanisms by which environmental chemicals disrupt embryonic development. In this study we tested the hypothesis that developmental exposure to 2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD), a well-known teratogen, alters microRNAmore » expression during zebrafish development. We exposed zebrafish embryos to DMSO (0.1%) or TCDD (5 nM) for 1 h at 30 hours post fertilization (hpf) and measured microRNA expression using several methods at 36 and 60 hpf. TCDD caused strong induction of CYP1A at 36 hpf (62-fold) and 60 hpf (135-fold) as determined by real-time RT-PCR, verifying the effectiveness of the exposure. MicroRNA expression profiles were determined using microarrays (Agilent and Exiqon), next-generation sequencing (SOLiD), and real-time RT-PCR. The two microarray platforms yielded results that were similar but not identical; both showed significant changes in expression of miR-451, 23a, 23b, 24 and 27e at 60 hpf. Multiple analyses were performed on the SOLiD sequences yielding a total of 16 microRNAs as differentially expressed by TCDD in zebrafish embryos. However, miR-27e was the only microRNA to be identified as differentially expressed by all three methods (both microarrays, SOLiD sequencing, and real-time RT-PCR). These results suggest that TCDD exposure causes modest changes in expression of microRNAs, including some (miR-451, 23a, 23b, 24 and 27e) that are critical for hematopoiesis and cardiovascular development. -- Highlights: ► Zebrafish embryos were exposed to TCDD at two different developmental timepoints. ► Compared different methods in detecting global changes in microRNA expression. ► TCDD caused significant changes in microRNA expression in zebrafish embryos. ► Differentially expressed microRNAs have roles related to TCDD-induced phenotypes.« less
Tanaka, Yohei; Nakayama, Jun
2016-01-01
Background and objective Humans are increasingly exposed to near-infrared (NIR) radiation from both natural (eg, solar) and artificial (eg, electrical appliances) sources. Although the biological effects of sun and ultraviolet (UV) exposure have been extensively investigated, the biological effect of NIR radiation is still unclear. We previously reported that NIR as well as UV induces photoaging and standard UV-blocking materials, such as sunglasses, do not sufficiently block NIR. The objective of this study was to investigate changes in gene expression in three-dimensional reconstructed corneal epithelial tissue culture exposed to broad-spectrum NIR irradiation to simulate solar NIR radiation that reaches human tissues. Materials and methods DNA microarray and quantitative real-time polymerase chain reaction analysis were used to assess gene expression levels in a three-dimensional reconstructed corneal epithelial model composed of normal human corneal epithelial cells exposed to water-filtered broad-spectrum NIR irradiation with a contact cooling (20°C). The water-filter allowed 1,000–1,800 nm wavelengths and excluded 1,400–1,500 nm wavelengths. Results A DNA microarray with >62,000 different probes showed 25 and 150 genes that were up- or downregulated by at least fourfold and twofold, respectively, after NIR irradiation. In particular, epidermal growth factor receptor (EGFR) was upregulated by 19.4-fold relative to control cells. Quantitative real-time polymerase chain reaction analysis revealed that two variants of EGFR in human corneal epithelial tissue were also significantly upregulated after five rounds of 10 J/cm2 irradiation (P<0.05). Conclusion We found that NIR irradiation induced the upregulated expression of EGFR in human corneal cells. Since over half of the solar energy reaching the Earth is in the NIR region, which cannot be adequately blocked by eyewear and thus can induce eye damage with intensive or long-term exposure, protection from both UV and NIR radiation may prevent changes in gene expression and in turn eye damage. PMID:27536083
Serum miRNAs Signature Plays an Important Role in Keloid Disease.
Luan, Y; Liu, Y; Liu, C; Lin, Q; He, F; Dong, X; Xiao, Z
2016-01-01
The molecular mechanism underlying the pathogenesis of keloid is largely unknown. MicroRNA (miRNA) is a class of small regulatory RNA that has emerged as a group of posttranscriptional gene repressors, participating in diverse pathophysiological processes of skin diseases. We investigated the expression profiles of miRNAs in the sera of patients to decipher the complicated factors involved in the development of keloid disease. MiRNA expression profiling in the sera from 9 keloid patients and 7 normal controls were characterized using a miRNA microarray containing established human mature and precursor miRNA sequences. Quantitative real-time PCR was performed to confirm the expression of miRNAs. The putative targets of differentially expressed miRNAs were functionally annotated by bioinformatics. MiRNA microarray analysis identified 37 differentially expressed miRNAs (17 upregulated and 20 downregulated) in keloid patients, compared to the healthy controls. Functional annotations revealed that the targets of those differentially expressed miRNAs were enriched in signaling pathways essential for scar formation and wound healing. The expression profiling of miRNAs is altered in the keloid, providing a clue for the molecular mechanisms underlying its initiation and progression. MiRNAs may partly contribute to the etiology of keloids by affecting the critical signaling pathways relevant to keloid pathogenesis.
Mirski, Tomasz; Bartoszcze, Michał; Bielawska-Drózd, Agata; Gryko, Romuald; Kocik, Janusz; Niemcewicz, Marcin; Chomiczewski, Krzysztof
2016-01-01
Both the known biological agents that cause infectious diseases, as well as modified (ABF-Advanced Biological Factors) or new, emerging agents pose a significant diagnostic problem using previously applied methods, both classical, as well as based on molecular biology methods. The latter, such as PCR and real-time PCR, have significant limitations, both quantitative (low capacity), and qualitative (limited number of targets). The article discusses the results of studies on using the microarray method for the identification of viruses (e.g. Orthopoxvirus group, noroviruses, influenza A and B viruses, rhino- and enteroviruses responsible for the FRI (Febrile Respiratory Illness), European bunyaviruses, and SARS-causing viruses), and bacteria (Mycobacterium spp., Yersinia spp., Campylobacter spp., Streptococcus pneumoniae, Salmonella typhi, Salmonella enterica, Staphylococcus aureus, Neisseria meningitidis, Clostridium difficile , Helicobacter pylori), including multiple antibiotic-resistant strains. The method allows for the serotyping and genotyping of bacteria, and is useful in the diagnosis of genetically modified agents. It allows the testing of thousands of genes in one experiment. In addition to diagnosis, it is applicable for gene expression studies, analysis of the function of genes, microorganisms virulence, and allows the detection of even single mutations. The possibility of its operational application in epidemiological surveillance, and in the detection of disease outbreak agents is demonstrated.
Motakis, E S; Nason, G P; Fryzlewicz, P; Rutter, G A
2006-10-15
Many standard statistical techniques are effective on data that are normally distributed with constant variance. Microarray data typically violate these assumptions since they come from non-Gaussian distributions with a non-trivial mean-variance relationship. Several methods have been proposed that transform microarray data to stabilize variance and draw its distribution towards the Gaussian. Some methods, such as log or generalized log, rely on an underlying model for the data. Others, such as the spread-versus-level plot, do not. We propose an alternative data-driven multiscale approach, called the Data-Driven Haar-Fisz for microarrays (DDHFm) with replicates. DDHFm has the advantage of being 'distribution-free' in the sense that no parametric model for the underlying microarray data is required to be specified or estimated; hence, DDHFm can be applied very generally, not just to microarray data. DDHFm achieves very good variance stabilization of microarray data with replicates and produces transformed intensities that are approximately normally distributed. Simulation studies show that it performs better than other existing methods. Application of DDHFm to real one-color cDNA data validates these results. The R package of the Data-Driven Haar-Fisz transform (DDHFm) for microarrays is available in Bioconductor and CRAN.
NASA Astrophysics Data System (ADS)
Leski, T. A.; Ansumana, R.; Jimmy, D. H.; Bangura, U.; Malanoski, A. P.; Lin, B.; Stenger, D. A.
2011-06-01
Multiplexed microbial diagnostic assays are a promising method for detection and identification of pathogens causing syndromes characterized by nonspecific symptoms in which traditional differential diagnosis is difficult. Also such assays can play an important role in outbreak investigations and environmental screening for intentional or accidental release of biothreat agents, which requires simultaneous testing for hundreds of potential pathogens. The resequencing pathogen microarray (RPM) is an emerging technological platform, relying on a combination of massively multiplex PCR and high-density DNA microarrays for rapid detection and high-resolution identification of hundreds of infectious agents simultaneously. The RPM diagnostic system was deployed in Sierra Leone, West Africa in collaboration with Njala University and Mercy Hospital Research Laboratory located in Bo. We used the RPM-Flu microarray designed for broad-range detection of human respiratory pathogens, to investigate a suspected outbreak of avian influenza in a number of poultry farms in which significant mortality of chickens was observed. The microarray results were additionally confirmed by influenza specific real-time PCR. The results of the study excluded the possibility that the outbreak was caused by influenza, but implicated Klebsiella pneumoniae as a possible pathogen. The outcome of this feasibility study confirms that application of broad-spectrum detection platforms for outbreak investigation in low-resource locations is possible and allows for rapid discovery of the responsible agents, even in cases when different agents are suspected. This strategy enables quick and cost effective detection of low probability events such as outbreak of a rare disease or intentional release of a biothreat agent.
Extraction and labeling methods for microarrays using small amounts of plant tissue.
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).
Chipster: user-friendly analysis software for microarray and other high-throughput data.
Kallio, M Aleksi; Tuimala, Jarno T; Hupponen, Taavi; Klemelä, Petri; Gentile, Massimiliano; Scheinin, Ilari; Koski, Mikko; Käki, Janne; Korpelainen, Eija I
2011-10-14
The growth of high-throughput technologies such as microarrays and next generation sequencing has been accompanied by active research in data analysis methodology, producing new analysis methods at a rapid pace. While most of the newly developed methods are freely available, their use requires substantial computational skills. In order to enable non-programming biologists to benefit from the method development in a timely manner, we have created the Chipster software. Chipster (http://chipster.csc.fi/) brings a powerful collection of data analysis methods within the reach of bioscientists via its intuitive graphical user interface. Users can analyze and integrate different data types such as gene expression, miRNA and aCGH. The analysis functionality is complemented with rich interactive visualizations, allowing users to select datapoints and create new gene lists based on these selections. Importantly, users can save the performed analysis steps as reusable, automatic workflows, which can also be shared with other users. Being a versatile and easily extendable platform, Chipster can be used for microarray, proteomics and sequencing data. In this article we describe its comprehensive collection of analysis and visualization tools for microarray data using three case studies. Chipster is a user-friendly analysis software for high-throughput data. Its intuitive graphical user interface enables biologists to access a powerful collection of data analysis and integration tools, and to visualize data interactively. Users can collaborate by sharing analysis sessions and workflows. Chipster is open source, and the server installation package is freely available.
Chipster: user-friendly analysis software for microarray and other high-throughput data
2011-01-01
Background The growth of high-throughput technologies such as microarrays and next generation sequencing has been accompanied by active research in data analysis methodology, producing new analysis methods at a rapid pace. While most of the newly developed methods are freely available, their use requires substantial computational skills. In order to enable non-programming biologists to benefit from the method development in a timely manner, we have created the Chipster software. Results Chipster (http://chipster.csc.fi/) brings a powerful collection of data analysis methods within the reach of bioscientists via its intuitive graphical user interface. Users can analyze and integrate different data types such as gene expression, miRNA and aCGH. The analysis functionality is complemented with rich interactive visualizations, allowing users to select datapoints and create new gene lists based on these selections. Importantly, users can save the performed analysis steps as reusable, automatic workflows, which can also be shared with other users. Being a versatile and easily extendable platform, Chipster can be used for microarray, proteomics and sequencing data. In this article we describe its comprehensive collection of analysis and visualization tools for microarray data using three case studies. Conclusions Chipster is a user-friendly analysis software for high-throughput data. Its intuitive graphical user interface enables biologists to access a powerful collection of data analysis and integration tools, and to visualize data interactively. Users can collaborate by sharing analysis sessions and workflows. Chipster is open source, and the server installation package is freely available. PMID:21999641
Wang, H B; Zan, L S; Zhang, Y Y
2014-01-01
Of all the mammals of the world, the yak lives at the highest altitude area of more than 3000 m. Comparison between yak and cattle of the low-altitude areas will be informative in studying animal adaptation to higher altitudes. To investigate the molecular mechanism involved in meat quality differences between the two Chinese special varieties Qinghai yak and Qinchuan cattle, 12 chemical-physical characteristics of the longissimus dorsi muscle related to meat quality were compared at the age of 36 months, and the gene expression profiles were constructed by utilizing the bovine genome array. Significant analysis of microarrays was used to identify the differentially expressed genes. Gene ontology and pathway analysis were performed by a free Web-based Molecular Annotation System 2.0. The results reveal ~11 000 probes representing about 10 000 genes that were detected in both the Qinghai yak and Qinchuan cattle. A total of 1922 genes were shown to be differentially expressed, 633 probes were upregulated and 1259 probes were downregulated in the muscle tissue of Qinghai yak that were mainly involved in ubiquitin-mediated proteolysis, muscle growth regulation, glucose metabolism, immune response and so on. Quantitative real-time PCR (qRT-PCR) was performed to validate some differentially expressed genes identified by microarray. Further analysis implied that animals living at a high altitude may supply energy by more active protein catabolism and glycolysis compared with those living in the plain areas. Our results establish the groundwork for further studies on yaks' meat quality and will be beneficial in improving the yaks' breeding by molecular biotechnology.
Tang, Yao; Ji, Hongjing; Liu, Haiyan; Gu, Weirong; Li, Xiaotian; Peng, Ting
2015-01-01
Spontaneous preterm labor is an important complication in perinatology characterized by early onset myometrium contractions leading to labor at preterm. However, the exact mechanism that maintain uterine quiescence and promote increased uterine contractility during labor were incompletely defined. MicroRNAs is a class of short non-coding RNAs that regulate gene expression at the post-transcriptional level by binding the 3’ untranslated region of target mRNAs and play an important role in biological process and cellular functions. We hypothesized we could find differentially expressed microRNAs in the myometrium of women in spontaneous preterm labor. Thus, a microarray analysis of miRNAs of preterm myometrium was performed. 18 out of the 2006 detected microRNAs were found to be significantly dysregulated in myometrium in labor verse not in labor at preterm. Biological validation by quantitative real-time polymerase chain reaction confirms us a consistence rate of 83.3% (5 out of 6) with microarray analysis. The target genes for validated microRNAs were predicted by three algorithms (PicTar, TargetScan, and miRanda). Most of the potential targets of the miRNAs were relevant to positive regulation of cardiac muscle hypertrophy, reduction of cytosolic calcium ion concentration and relaxation of cardiac muscle as well as prostate cancer, adherents junction, regulation of actin cytoskeleton and regulation and other factor-regulated calcium reabsorption. Our result illustrates a characteristic microRNA profile in myometrium tissues and provides a new understanding of the process involved in spontaneous preterm labor. PMID:26722471
Gene expression profiling for nitric oxide prodrug JS-K to kill HL-60 myeloid leukemia cells.
Liu, Jie; Malavya, Swati; Wang, Xueqian; Saavedra, Joseph E; Keefer, Larry K; Tokar, Erik; Qu, Wei; Waalkes, Michael P; Shami, Paul J
2009-07-01
The nitric oxide (NO) prodrug JS-K is shown to have anticancer activity. To profile the molecular events associated with the anticancer effects of JS-K, HL-60 leukemia cells were treated with JS-K and subjected to microarray and real-time RT-PCR analysis. JS-K induced concentration- and time-dependent gene expression changes in HL-60 cells corresponding to the cytolethality effects. The apoptotic genes (caspases, Bax, and TNF-alpha) were induced, and differentiation-related genes (CD14, ITGAM, and VIM) were increased. For acute phase protein genes, some were increased (TP53, JUN) while others were suppressed (c-myc, cyclin E). The expression of anti-angiogenesis genes THBS1 and CD36 and genes involved in tumor cell migration such as tissue inhibitors of metalloproteinases, were also increased by JS-K. Confocal analysis confirmed key gene changes at the protein levels. Thus, multiple molecular events are associated with JS-K effects in killing HL-60, which could be molecular targets for this novel anticancer NO prodrug.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Ovacik, Meric A.; Sen, Banalata; Euling, Susan Y.
Pathway activity level analysis, the approach pursued in this study, focuses on all genes that are known to be members of metabolic and signaling pathways as defined by the KEGG database. The pathway activity level analysis entails singular value decomposition (SVD) of the expression data of the genes constituting a given pathway. We explore an extension of the pathway activity methodology for application to time-course microarray data. We show that pathway analysis enhances our ability to detect biologically relevant changes in pathway activity using synthetic data. As a case study, we apply the pathway activity level formulation coupled with significancemore » analysis to microarray data from two different rat testes exposed in utero to Dibutyl Phthalate (DBP). In utero DBP exposure in the rat results in developmental toxicity of a number of male reproductive organs, including the testes. One well-characterized mode of action for DBP and the male reproductive developmental effects is the repression of expression of genes involved in cholesterol transport, steroid biosynthesis and testosterone synthesis that lead to a decreased fetal testicular testosterone. Previous analyses of DBP testes microarray data focused on either individual gene expression changes or changes in the expression of specific genes that are hypothesized, or known, to be important in testicular development and testosterone synthesis. However, a pathway analysis may inform whether there are additional affected pathways that could inform additional modes of action linked to DBP developmental toxicity. We show that Pathway activity analysis may be considered for a more comprehensive analysis of microarray data.« less
Kato, Yoko; Li, Xiangping; Amarnath, Dasari; Ushizawa, Koichi; Hashizume, Kazuyoshi; Tokunaga, Tomoyuki; Taniguchi, Masanori; Tsunoda, Yukio
2007-01-01
Placental abnormalities are the main factor in the high incidence of somatic cell clone abnormalities. The expression of several trophoblast cell-specific molecules is enhanced during gestational days 7 to 14. To determine the possible genes whose expression patterns might reflect calf normality, we first compared the gene expression profiles on day 15 between in vitro-fertilized (IVF) embryos and two types of somatic cell nuclear-transferred embryos with either a high (FNT) or low (CNT) incidence of neonatal abnormalities using a cDNA microarray containing 16 of 21 placenta-specific genes developed from tissues collected across gestation. To identify significant genes from the screening of day 15 embryos, genes with a less than two-fold difference in expression between IVF and CNT embryos, and those with a greater than two-fold difference between IVF and FNT and between CNT and FNT were considered to contribute to clone abnormalities. These two comparisons revealed 18 down-regulated and 18 upregulated genes of the 1722 genes examined. We then examined the expression levels of 10 genes with known functions in eight-cell and blastocyst-stage embryos by real-time PCR. The mRNA expression pattern of interferon (IFN)-tau, a trophectoderm-related gene, differed between IVF, CNT, and FNT eight-cell embryos; few or none of the IVF or CNT eight-cell embryos expressed IFN-tau mRNA, but all eight-cell FNT embryos expressed IFN-tau. IFN-tau mRNA expression was significantly higher in IVF blastocysts, however, than in nuclear-transferred blastocysts. Average IFN-tau mRNA expression in FNT blastocysts was not different from that in CNT blastocysts, due to one CNT blastocyst with high expression. The precise relation between early expression of IFN-tau mRNA and inferior developmental potential in cloned embryos should be examined further.
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
Changes in Global Transcriptional Profiling of Women Following Obesity Surgery Bypass.
Pinhel, Marcela Augusta de Souza; Noronha, Natalia Yumi; Nicoletti, Carolina Ferreira; de Oliveira, Bruno Affonso Parente; Cortes-Oliveira, Cristiana; Pinhanelli, Vitor Caressato; Salgado Junior, Wilson; Machry, Ana Julia; da Silva Junior, Wilson Araújo; Souza, Dorotéia Rossi Silva; Marchini, Júlio Sérgio; Nonino, Carla Barbosa
2018-01-01
Differential gene expression in peripheral blood mononuclear cells (PBMCs) after Roux-en-Y gastric bypass (RYGB) is poorly characterized. Markers of these processes may provide a deeper understanding of the mechanisms that underlie these events. The main goal of this study was to identify changes in PBMC gene expression in women with obesity before and 6 months after RYGB-induced weight loss. The ribonucleic acid (RNA) of PBMCs from 13 obese women was analyzed before and 6 months after RYGB; the RNA of PBMCs from nine healthy women served as control. The gene expression levels were determined by microarray analysis. Significant differences in gene expression were validated by real-time quantitative polymerase chain reaction (RT-qPCR). Microarray analysis for comparison of the pre- and postoperative periods showed that 1366 genes were differentially expressed genes (DEGs). The main pathways were related to gene transcription; lipid, energy, and glycide metabolism; inflammatory and immunological response; cell differentiation; oxidative stress regulation; response to endogenous and exogenous stimuli; substrate oxidation; mTOR signaling pathway; interferon signaling; mitogen-activated protein kinases (MAPK), cAMP response element binding protein (CREB1), heat shock factor 1 (HSF1), and sterol regulatory element binding protein 1c (SREBP-1c) gene expression; adipocyte differentiation; and methylation. Six months after bariatric surgery and significant weight loss, many molecular pathways involved in obesity and metabolic diseases change. These findings are an important tool to identify potential targets for therapeutic intervention and clinical practice of nutritional genomics in obesity.
Differences in the developmental origins of the periosteum may influence bone healing.
Ichikawa, Y; Watahiki, J; Nampo, T; Nose, K; Yamamoto, G; Irie, T; Mishima, K; Maki, K
2015-08-01
The jaw bone, unlike most other bones, is derived from neural crest stem cells, so we hypothesized that it may have different characteristics to bones from other parts of the body, especially in the nature of its periosteum. The periosteum exhibits osteogenic potential and has received considerable attention as a grafting material for the repair of bone and joint defects. Gene expression profiles of jaw bone and periosteum were evaluated by DNA microarray and real-time polymerase chain reaction. Furthermore, we perforated an area 2 mm in diameter on mouse frontal and parietal bones. Bone regeneration of these calvarial defects was evaluated using microcomputed tomography and histological analysis. The DNA microarray data revealed close homology between the gene expression profiles within the ilium and femur. The gene expression of Wnt-1, SOX10, nestin, and musashi-1 were significantly higher in the jaw bone than in other locations. Microcomputed tomography and histological analysis revealed that the jaw bone had superior bone regenerative abilities than other bones. Jaw bone periosteum exhibits a unique gene expression profile that is associated with neural crest cells and has a positive influence on bone regeneration when used as a graft material to repair bone defects. A full investigation of the biological and mechanical properties of jaw bone as an alternative graft material for jaw reconstructive surgery is recommended. © 2014 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.
Jiang, Qian-Tao; Liu, Tao; Ma, Jian; Wei, Yu-Ming; Lu, Zhen-Xiang; Lan, Xiu-Jin; Dai, Shou-Fen; Zheng, You-Liang
2011-10-01
The pre-mRNA processing (Prp1) gene encodes a spliceosomal protein. It was firstly identified in fission yeast and plays a regular role during spliceosome activation and cell cycle. Plant Prp1 genes have only been identified from rice, Sorghum and Arabidopsis thaliana. In this study, we reported the identification and isolation of a novel Prp1 gene from barley, and further explored its expressional pattern by using real-time quantitative RTPCR, promoter prediction and analysis of microarray data. The putative barley Prp1 protein has a similar primary structure features to those of other known Prp1 protein in this family. The results of amino acid comparison indicated that Prp1 protein of barley and other plant species has a highly conserved 30 termnal region while their 50 sequences greatly varied. The results of expressional analysis revealed that the expression level of barley Prp1 gene is always stable in different vegetative tissues, except it is up-regulated at the mid- and late stages of seed development or under the condition of cold stress. This kind of expressional pattern for barley Prp1 is also supported by our results of comparison of microarray data from barley, rice and Arabidopsis. For the molecular mechanism of its expressional pattern, we conclude that the expression of Prp1 gene may be up-regulated by the increase of pre-mRNAs and not be constitutive or ubiquitous.
Single cell gene expression profiling in Alzheimer's disease.
Ginsberg, Stephen D; Che, Shaoli; Counts, Scott E; Mufson, Elliott J
2006-07-01
Development and implementation of microarray techniques to quantify expression levels of dozens to hundreds to thousands of transcripts simultaneously within select tissue samples from normal control subjects and neurodegenerative diseased brains has enabled scientists to create molecular fingerprints of vulnerable neuronal populations in Alzheimer's disease (AD) and related disorders. A goal is to sample gene expression from homogeneous cell types within a defined region without potential contamination by expression profiles of adjacent neuronal subpopulations and nonneuronal cells. The precise resolution afforded by single cell and population cell RNA analysis in combination with microarrays and real-time quantitative polymerase chain reaction (qPCR)-based analyses allows for relative gene expression level comparisons across cell types under different experimental conditions and disease progression. The ability to analyze single cells is an important distinction from global and regional assessments of mRNA expression and can be applied to optimally prepared tissues from animal models of neurodegeneration as well as postmortem human brain tissues. Gene expression analysis in postmortem AD brain regions including the hippocampal formation and neocortex reveals selectively vulnerable cell types share putative pathogenetic alterations in common classes of transcripts, for example, markers of glutamatergic neurotransmission, synaptic-related markers, protein phosphatases and kinases, and neurotrophins/neurotrophin receptors. Expression profiles of vulnerable regions and neurons may reveal important clues toward the understanding of the molecular pathogenesis of various neurological diseases and aid in identifying rational targets toward pharmacotherapeutic interventions for progressive, late-onset neurodegenerative disorders such as mild cognitive impairment (MCI) and AD.
Szmolka, Ama; Wiener, Zoltán; Matulova, Marta Elsheimer; Varmuzova, Karolina; Rychlik, Ivan
2015-01-01
The response of chicken to non-typhoidal Salmonella infection is becoming well characterised but the role of particular cell types in this response is still far from being understood. Therefore, in this study we characterised the response of chicken embryo fibroblasts (CEFs) to infection with two different S. Enteritidis strains by microarray analysis. The expression of chicken genes identified as significantly up- or down-regulated (≥3-fold) by microarray analysis was verified by real-time PCR followed by functional classification of the genes and prediction of interactions between the proteins using Gene Ontology and STRING Database. Finally the expression of the newly identified genes was tested in HD11 macrophages and in vivo in chickens. Altogether 19 genes were induced in CEFs after S. Enteritidis infection. Twelve of them were also induced in HD11 macrophages and thirteen in the caecum of orally infected chickens. The majority of these genes were assigned different functions in the immune response, however five of them (LOC101750351, K123, BU460569, MOBKL2C and G0S2) have not been associated with the response of chicken to Salmonella infection so far. K123 and G0S2 were the only ’non-immune’ genes inducible by S. Enteritidis in fibroblasts, HD11 macrophages and in the caecum after oral infection. The function of K123 is unknown but G0S2 is involved in lipid metabolism and in β-oxidation of fatty acids in mitochondria. PMID:26046914
Szmolka, Ama; Wiener, Zoltán; Matulova, Marta Elsheimer; Varmuzova, Karolina; Rychlik, Ivan
2015-01-01
The response of chicken to non-typhoidal Salmonella infection is becoming well characterised but the role of particular cell types in this response is still far from being understood. Therefore, in this study we characterised the response of chicken embryo fibroblasts (CEFs) to infection with two different S. Enteritidis strains by microarray analysis. The expression of chicken genes identified as significantly up- or down-regulated (≥3-fold) by microarray analysis was verified by real-time PCR followed by functional classification of the genes and prediction of interactions between the proteins using Gene Ontology and STRING Database. Finally the expression of the newly identified genes was tested in HD11 macrophages and in vivo in chickens. Altogether 19 genes were induced in CEFs after S. Enteritidis infection. Twelve of them were also induced in HD11 macrophages and thirteen in the caecum of orally infected chickens. The majority of these genes were assigned different functions in the immune response, however five of them (LOC101750351, K123, BU460569, MOBKL2C and G0S2) have not been associated with the response of chicken to Salmonella infection so far. K123 and G0S2 were the only 'non-immune' genes inducible by S. Enteritidis in fibroblasts, HD11 macrophages and in the caecum after oral infection. The function of K123 is unknown but G0S2 is involved in lipid metabolism and in β-oxidation of fatty acids in mitochondria.
Current-Controlled Electrical Point-Source Stimulation of Embryonic Stem Cells
Chen, Michael Q.; Xie, Xiaoyan; Wilson, Kitchener D.; Sun, Ning; Wu, Joseph C.; Giovangrandi, Laurent; Kovacs, Gregory T. A.
2010-01-01
Stem cell therapy is emerging as a promising clinical approach for myocardial repair. However, the interactions between the graft and host, resulting in inconsistent levels of integration, remain largely unknown. In particular, the influence of electrical activity of the surrounding host tissue on graft differentiation and integration is poorly understood. In order to study this influence under controlled conditions, an in vitro system was developed. Electrical pacing of differentiating murine embryonic stem (ES) cells was performed at physiologically relevant levels through direct contact with microelectrodes, simulating the local activation resulting from contact with surrounding electroactive tissue. Cells stimulated with a charged balanced voltage-controlled current source for up to 4 days were analyzed for cardiac and ES cell gene expression using real-time PCR, immunofluorescent imaging, and genome microarray analysis. Results varied between ES cells from three progressive differentiation stages and stimulation amplitudes (nine conditions), indicating a high sensitivity to electrical pacing. Conditions that maximally encouraged cardiomyocyte differentiation were found with Day 7 EBs stimulated at 30 µA. The resulting gene expression included a sixfold increase in troponin-T and a twofold increase in β-MHCwithout increasing ES cell proliferation marker Nanog. Subsequent genome microarray analysis revealed broad transcriptome changes after pacing. Concurrent to upregulation of mature gene programs including cardiovascular, neurological, and musculoskeletal systems is the apparent downregulation of important self-renewal and pluripotency genes. Overall, a robust system capable of long-term stimulation of ES cells is demonstrated, and specific conditions are outlined that most encourage cardiomyocyte differentiation. PMID:20652088
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.
Ning, Tongbo; Cui, Hao; Sun, Feng; Zou, Jidian
2017-09-05
Glioblastoma represents one of the most aggressive malignant brain tumors with high morbidity and motility. Demethylation drugs have been developed for its treatment with little efficacy has been observed. The purpose of this study was to screen therapeutic targets of demethylation drugs or bioactive molecules for glioblastoma through systemic bioinformatics analysis. We firstly downloaded genome-wide expression profiles from the Gene Expression Omnibus (GEO) and conducted the primary analysis through R software, mainly including preprocessing of raw microarray data, transformation between probe ID and gene symbol and identification of differential expression genes (DEGs). Secondly, functional enrichment analysis was conducted via the Database for Annotation, Visualization and Integrated Discovery (DAVID) to explore biological processes involved in the development of glioblastoma. Thirdly, we constructed protein-protein interaction (PPI) network of interested genes and conducted cross analysis for multi datasets to obtain potential therapeutic targets for glioblastoma. Finally, we further confirmed the therapeutic targets through real-time RT-PCR. As a result, biological processes that related to cancer development, amino metabolism, immune response and etc. were found to be significantly enriched in genes that differential expression in glioblastoma and regulated by 5'aza-dC. Besides, network and cross analysis identified ACAT2, UFC1 and CYB5R1 as novel therapeutic targets of demethylation drugs which also confirmed by real time RT-PCR. In conclusions, our study identified several biological processes and genes that involved in the development of glioblastoma and regulated by 5'aza-dC, which would be helpful for the treatment of glioblastoma. Copyright © 2017 Elsevier B.V. All rights reserved.
Musser, Richard O.; Hum-Musser, Sue M.; Gallucci, Matthew; DesRochers, Brittany; Brown, Judith K.
2014-01-01
Abstract Plants are routinely exposed to biotic and abiotic stresses to which they have evolved by synthesizing constitutive and induced defense compounds. Induced defense compounds are usually made, initially, at low levels; however, following further stimulation by specific kinds of biotic and abiotic stresses, they can be synthesized in relatively large amounts to abate the particular stress. cDNA microarray hybridization was used to identify an array of genes that were differentially expressed in tomato plants 15 d after they were exposed to feeding by nonviruliferous whiteflies or by viruliferous whiteflies carrying Pepper golden mosaic virus (PepGMV) ( Begomovirus, Geminiviridae ). Tomato plants inoculated by viruliferous whiteflies developed symptoms characteristic of PepGMV, whereas plants exposed to nonviruliferous whitefly feeding or nonwounded (negative) control plants exhibited no disease symptoms. The microarray analysis yielded over 290 spotted probes, with significantly altered expression of 161 putative annotated gene targets, and 129 spotted probes of unknown identities. The majority of the differentially regulated “known” genes were associated with the plants exposed to viruliferous compared with nonviruliferous whitefly feeding. Overall, significant differences in gene expression were represented by major physiological functions including defense-, pathogen-, photosynthesis-, and signaling-related responses and were similar to genes identified for other insect–plant systems. Viruliferous whitefly-stimulated gene expression was validated by real-time quantitative polymerase chain reaction of selected, representative candidate genes (messenger RNA): arginase, dehydrin, pathogenesis-related proteins 1 and -4, polyphenol oxidase, and several protease inhibitors. This is the first comparative profiling of the expression of tomato plants portraying different responses to biotic stress induced by viruliferous whitefly feeding (with resultant virus infection) compared with whitefly feeding only and negative control nonwounded plants exposed to neither. These results may be applicable to many other plant–insect–pathogen system interactions. PMID:25525099
Singh, Virendra; Singh, Laishram C; Singh, Avninder P; Sharma, Jagannath; Borthakur, Bibhuti B; Debnath, Arundhati; Rai, Avdhesh K; Phukan, Rup K; Mahanta, Jagadish; Kataki, Amal C; Kapur, Sujala; Saxena, Sunita
2015-01-01
Esophageal cancer incidence is reported in high frequency in northeast India. The etiology is different from other population at India due to wide variations in dietary habits or nutritional factors, tobacco/betel quid chewing and alcohol habits. Since DNA methylation, histone modification and miRNA-mediated epigenetic processes alter the gene expression, the involvement of these processes might be useful to find out epigenetic markers of esophageal cancer risk in northeast Indian population. The present investigation was aimed to carryout differential expression profiling of chromatin modification enzymes in tumor and normal tissue collected from esophageal squamous cell carcinoma (ESCC) patients. Differential mRNA expression profiling and their validation was done by quantitative real time PCR and tissue microarray respectively. Univariate and multiple logistic regression analysis were used to analyze the epidemiological data. mRNA expression data was analyzed by Student t-test. Fisher exact test was used for tissue microarray data analysis. Higher expression of enzymes regulating methylation (DOT1L and PRMT1) and acetylation (KAT7, KAT8, KAT2A and KAT6A) of histone was found associated with ESCC risk. Tissue microarray done in independent cohort of 75 patients revealed higher nuclear protein expression of KAT8 and PRMT1 in tumor similar to mRNA expression. Expression status of PRMT1 and KAT8 was found declined as we move from low grade to high grade tumor. Betel nut chewing, alcohol drinking and dried fish intake were significantly associated with increased risk of esophageal cancer among the study subject. Study suggests the association of PRMT1 and KAT8 with esophageal cancer risk and its involvement in the transition process of low to high grade tumor formation. The study exposes the differential status of chromatin modification enzymes between tumor and normal tissue and points out that relaxed state of chromatin facilitates more transcriptionally active genome in esophageal carcinogenesis.
Mining microarray data at NCBI's Gene Expression Omnibus (GEO)*.
Barrett, Tanya; Edgar, Ron
2006-01-01
The Gene Expression Omnibus (GEO) at the National Center for Biotechnology Information (NCBI) has emerged as the leading fully public repository for gene expression data. This chapter describes how to use Web-based interfaces, applications, and graphics to effectively explore, visualize, and interpret the hundreds of microarray studies and millions of gene expression patterns stored in GEO. Data can be examined from both experiment-centric and gene-centric perspectives using user-friendly tools that do not require specialized expertise in microarray analysis or time-consuming download of massive data sets. The GEO database is publicly accessible through the World Wide Web at http://www.ncbi.nlm.nih.gov/geo.
Advances in analytical methodologies to guide bioprocess engineering for bio-therapeutics.
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.
The Microarray Revolution: Perspectives from Educators
ERIC Educational Resources Information Center
Brewster, Jay L.; Beason, K. Beth; Eckdahl, Todd T.; Evans, Irene M.
2004-01-01
In recent years, microarray analysis has become a key experimental tool, enabling the analysis of genome-wide patterns of gene expression. This review approaches the microarray revolution with a focus upon four topics: 1) the early development of this technology and its application to cancer diagnostics; 2) a primer of microarray research,…
Effects of spaceflight on murine skeletal muscle gene expression
Allen, David L.; Bandstra, Eric R.; Harrison, Brooke C.; Thorng, Seiha; Stodieck, Louis S.; Kostenuik, Paul J.; Morony, Sean; Lacey, David L.; Hammond, Timothy G.; Leinwand, Leslie L.; Argraves, W. Scott; Bateman, Ted A.; Barth, Jeremy L.
2009-01-01
Spaceflight results in a number of adaptations to skeletal muscle, including atrophy and shifts toward faster muscle fiber types. To identify changes in gene expression that may underlie these adaptations, we used both microarray expression analysis and real-time polymerase chain reaction to quantify shifts in mRNA levels in the gastrocnemius from mice flown on the 11-day, 19-h STS-108 shuttle flight and from normal gravity controls. Spaceflight data also were compared with the ground-based unloading model of hindlimb suspension, with one group of pure suspension and one of suspension followed by 3.5 h of reloading to mimic the time between landing and euthanization of the spaceflight mice. Analysis of microarray data revealed that 272 mRNAs were significantly altered by spaceflight, the majority of which displayed similar responses to hindlimb suspension, whereas reloading tended to counteract these responses. Several mRNAs altered by spaceflight were associated with muscle growth, including the phosphatidylinositol 3-kinase regulatory subunit p85α, insulin response substrate-1, the forkhead box O1 transcription factor, and MAFbx/atrogin1. Moreover, myostatin mRNA expression tended to increase, whereas mRNA levels of the myostatin inhibitor FSTL3 tended to decrease, in response to spaceflight. In addition, mRNA levels of the slow oxidative fiber-associated transcriptional coactivator peroxisome proliferator-associated receptor (PPAR)-γ coactivator-1α and the transcription factor PPAR-α were significantly decreased in spaceflight gastrocnemius. Finally, spaceflight resulted in a significant decrease in levels of the microRNA miR-206. Together these data demonstrate that spaceflight induces significant changes in mRNA expression of genes associated with muscle growth and fiber type. PMID:19074574
Hu, Pingsha; Maiti, Tapabrata
2011-01-01
Microarray is a powerful tool for genome-wide gene expression analysis. In microarray expression data, often mean and variance have certain relationships. We present a non-parametric mean-variance smoothing method (NPMVS) to analyze differentially expressed genes. In this method, a nonlinear smoothing curve is fitted to estimate the relationship between mean and variance. Inference is then made upon shrinkage estimation of posterior means assuming variances are known. Different methods have been applied to simulated datasets, in which a variety of mean and variance relationships were imposed. The simulation study showed that NPMVS outperformed the other two popular shrinkage estimation methods in some mean-variance relationships; and NPMVS was competitive with the two methods in other relationships. A real biological dataset, in which a cold stress transcription factor gene, CBF2, was overexpressed, has also been analyzed with the three methods. Gene ontology and cis-element analysis showed that NPMVS identified more cold and stress responsive genes than the other two methods did. The good performance of NPMVS is mainly due to its shrinkage estimation for both means and variances. In addition, NPMVS exploits a non-parametric regression between mean and variance, instead of assuming a specific parametric relationship between mean and variance. The source code written in R is available from the authors on request.
Hu, Pingsha; Maiti, Tapabrata
2011-01-01
Microarray is a powerful tool for genome-wide gene expression analysis. In microarray expression data, often mean and variance have certain relationships. We present a non-parametric mean-variance smoothing method (NPMVS) to analyze differentially expressed genes. In this method, a nonlinear smoothing curve is fitted to estimate the relationship between mean and variance. Inference is then made upon shrinkage estimation of posterior means assuming variances are known. Different methods have been applied to simulated datasets, in which a variety of mean and variance relationships were imposed. The simulation study showed that NPMVS outperformed the other two popular shrinkage estimation methods in some mean-variance relationships; and NPMVS was competitive with the two methods in other relationships. A real biological dataset, in which a cold stress transcription factor gene, CBF2, was overexpressed, has also been analyzed with the three methods. Gene ontology and cis-element analysis showed that NPMVS identified more cold and stress responsive genes than the other two methods did. The good performance of NPMVS is mainly due to its shrinkage estimation for both means and variances. In addition, NPMVS exploits a non-parametric regression between mean and variance, instead of assuming a specific parametric relationship between mean and variance. The source code written in R is available from the authors on request. PMID:21611181
Gene expression profiling in melasma in Korean women.
Chung, Bo Young; Noh, Tai Kyung; Yang, Sang Hwa; Kim, Il Hwan; Lee, Mi Woo; Yoon, Tae Jin; Chang, Sung Eun
2014-01-01
There has been a paucity of data about the difference in gene expression between melasma lesional skin and normal adjacent one. Our aim was to identify novel genes involved in the pathogenesis of melasma. We performed a microarray analysis and confirmed the results on quantitative real-time polymerase chain reaction (qRT-PCR) in Korean women with melasma. There were 334 genes whose degree of expression showed a significant difference between melasma lesional skin and normal adjacent one. Of these, five were confirmed on qRT-PCR. In melasma lesional skin, there were down-regulation of genes involved in the PPAR signaling pathway and up-regulation of genes involved in neuronal component and the functions of stratum corneum barrier. This result suggests that the pathogenesis of melasma might be associated with novel genes involved in the above signaling pathway in Korean women.
Molecular diagnosis of bloodstream infections: planning to (physically) reach the bedside.
Leggieri, N; Rida, A; François, P; Schrenzel, Jacques
2010-08-01
Faster identification of infecting microorganisms and treatment options is a first-ranking priority in the infectious disease area, in order to prevent inappropriate treatment and overuse of broad-spectrum antibiotics. Standard bacterial identification is intrinsically time-consuming, and very recently there has been a burst in the number of commercially available nonphenotype-based techniques and in the documentation of a possible clinical impact of these techniques. Matrix-assisted laser desorption ionization time-of-flight mass spectrometry (MALDI-TOF MS) is now a standard diagnostic procedure on cultures and hold promises on spiked blood. Meanwhile, commercial PCR-based techniques have improved with the use of bacterial DNA enrichment methods, the diversity of amplicon analysis techniques (melting curve analysis, microarrays, gel electrophoresis, sequencing and analysis by mass spectrometry) leading to the ability to challenge bacterial culture as the gold standard for providing earlier diagnosis with a better 'clinical' sensitivity and additional prognostic information. Laboratory practice has already changed with MALDI-TOF MS, but a change in clinical practice, driven by emergent nucleic acid-based techniques, will need the demonstration of real-life applicability as well as robust clinical-impact-oriented studies.
An Introduction to MAMA (Meta-Analysis of MicroArray data) System.
Zhang, Zhe; Fenstermacher, David
2005-01-01
Analyzing microarray data across multiple experiments has been proven advantageous. To support this kind of analysis, we are developing a software system called MAMA (Meta-Analysis of MicroArray data). MAMA utilizes a client-server architecture with a relational database on the server-side for the storage of microarray datasets collected from various resources. The client-side is an application running on the end user's computer that allows the user to manipulate microarray data and analytical results locally. MAMA implementation will integrate several analytical methods, including meta-analysis within an open-source framework offering other developers the flexibility to plug in additional statistical algorithms.
ELISA microarray technology as a high-throughput system for cancer biomarker validation
DOE Office of Scientific and Technical Information (OSTI.GOV)
Zangar, Richard C.; Daly, Don S.; White, Amanda M.
A large gap currently exists between the ability to discover potential biomarkers and the ability to assess the real value of these proteins for cancer screening. One major challenge in biomarker validation is the inherent variability in biomarker levels. This variability stems from the diversity across the human population and the considerable molecular heterogeneity between individual tumors, even those that originate from a single tissue. Another major challenge with cancer screening is that most cancers are rare in the general population, meaning that the specificity of an assay must be very high if the number of false positive is notmore » going to be much greater than the number of true positives. Because of these challenges with biomarker validation, it is necessary to analysis of thousands of samples before a clear idea of the utility of a screening assay can be determined. Enzyme-linked immunosorbent assay (ELISA) microarray technology can simultaneously quantify levels of multiple proteins and has the potential to accelerate biomarker validation. In this review, we discuss current ELISA microarray technology and the enabling advances needed to achieve the reproducibility and throughput that are required to evaluate cancer biomarkers.« less
Reproducibility-optimized test statistic for ranking genes in microarray studies.
Elo, Laura L; Filén, Sanna; Lahesmaa, Riitta; Aittokallio, Tero
2008-01-01
A principal goal of microarray studies is to identify the genes showing differential expression under distinct conditions. In such studies, the selection of an optimal test statistic is a crucial challenge, which depends on the type and amount of data under analysis. While previous studies on simulated or spike-in datasets do not provide practical guidance on how to choose the best method for a given real dataset, we introduce an enhanced reproducibility-optimization procedure, which enables the selection of a suitable gene- anking statistic directly from the data. In comparison with existing ranking methods, the reproducibilityoptimized statistic shows good performance consistently under various simulated conditions and on Affymetrix spike-in dataset. Further, the feasibility of the novel statistic is confirmed in a practical research setting using data from an in-house cDNA microarray study of asthma-related gene expression changes. These results suggest that the procedure facilitates the selection of an appropriate test statistic for a given dataset without relying on a priori assumptions, which may bias the findings and their interpretation. Moreover, the general reproducibilityoptimization procedure is not limited to detecting differential expression only but could be extended to a wide range of other applications as well.
A 256 pixel magnetoresistive biosensor microarray in 0.18μm CMOS
Hall, Drew A.; Gaster, Richard S.; Makinwa, Kofi; Wang, Shan X.; Murmann, Boris
2014-01-01
Magnetic nanotechnologies have shown significant potential in several areas of nanomedicine such as imaging, therapeutics, and early disease detection. Giant magnetoresistive spin-valve (GMR SV) sensors coupled with magnetic nanotags (MNTs) possess great promise as ultra-sensitive biosensors for diagnostics. We report an integrated sensor interface for an array of 256 GMR SV biosensors designed in 0.18 μm CMOS. Arranged like an imager, each of the 16 column level readout channels contains an analog front- end and a compact ΣΔ modulator (0.054 mm2) with 84 dB of dynamic range and an input referred noise of 49 nT/√Hz. Performance is demonstrated through detection of an ovarian cancer biomarker, secretory leukocyte peptidase inhibitor (SLPI), spiked at concentrations as low as 10 fM. This system is designed as a replacement for optical protein microarrays while also providing real-time kinetics monitoring. PMID:24761029
Cross-species transcriptomic approach reveals genes in hamster implantation sites.
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.
A new functional membrane protein microarray based on tethered phospholipid bilayers.
Chadli, Meriem; Maniti, Ofelia; Marquette, Christophe; Tillier, Bruno; Cortès, Sandra; Girard-Egrot, Agnès
2018-04-30
A new prototype of a membrane protein biochip is presented in this article. This biochip was created by the combination of novel technologies of peptide-tethered bilayer lipid membrane (pep-tBLM) formation and solid support micropatterning. Pep-tBLMs integrating a membrane protein were obtained in the form of microarrays on a gold chip. The formation of the microspots was visualized in real-time by surface plasmon resonance imaging (SPRi) and the functionality of a GPCR (CXCR4), reinserted locally into microwells, was assessed by ligand binding studies. In brief, to achieve micropatterning, P19-4H, a 4 histidine-possessing peptide spacer, was spotted inside microwells obtained on polystyrene-coated gold, and Ni-chelating proteoliposomes were injected into the reaction chamber. Proteoliposome binding to the peptide was based on metal-chelate interaction. The peptide-tethered lipid bilayer was finally obtained by addition of a fusogenic peptide (AH peptide) to promote proteoliposome fusion. The CXCR4 pep-tBLM microarray was characterized by surface plasmon resonance imaging (SPRi) throughout the building-up process. This new generation of membrane protein biochip represents a promising method of developing a screening tool for drug discovery.
NASA Astrophysics Data System (ADS)
Li, Qiang; Huang, Guoliang; Gan, Wupeng; Chen, Shengyi
2009-08-01
Biomolecular interactions can be detected by many established technologies such as fluorescence imaging, surface plasmon resonance (SPR)[1-4], interferometry and radioactive labeling of the analyte. In this study, we have designed and constructed a label-free, real-time sensing platform and its operating imaging instrument that detects interactions using optical phase differences from the accumulation of biological material on solid substrates. This system allows us to monitor biomolecular interactions in real time and quantify concentration changes during micro-mixing processes by measuring the changes of the optical path length (OPD). This simple interferometric technology monitors the optical phase difference resulting from accumulated biomolecular mass. A label-free protein chip that forms a 4×4 probe array was designed and fabricated using a commercial microarray robot spotter on solid substrates. Two positive control probe lines of BSA (Bovine Serum Albumin) and two experimental human IgG and goat IgG was used. The binding of multiple protein targets was performed and continuously detected by using this label-free and real-time sensing platform.
Kimura, Shinzo; Ishidou, Emi; Kurita, Sakiko; Suzuki, Yoshiteru; Shibato, Junko; Rakwal, Randeep; Iwahashi, Hitoshi
2006-07-21
Ionizing radiation (IR) is the most enigmatic of genotoxic stress inducers in our environment that has been around from the eons of time. IR is generally considered harmful, and has been the subject of numerous studies, mostly looking at the DNA damaging effects in cells and the repair mechanisms therein. Moreover, few studies have focused on large-scale identification of cellular responses to IR, and to this end, we describe here an initial study on the transcriptional responses of the unicellular genome model, yeast (Saccharomyces cerevisiae strain S288C), by cDNA microarray. The effect of two different IR, X-rays, and gamma (gamma)-rays, was investigated by irradiating the yeast cells cultured in YPD medium with 50 Gy doses of X- and gamma-rays, followed by resuspension of the cells in YPD for time-course experiments. The samples were collected for microarray analysis at 20, 40, and 80 min after irradiation. Microarray analysis revealed a time-course transcriptional profile of changed gene expressions. Up-regulated genes belonged to the functional categories mainly related to cell cycle and DNA processing, cell rescue defense and virulence, protein and cell fate, and metabolism (X- and gamma-rays). Similarly, for X- and gamma-rays, the down-regulated genes belonged to mostly transcription and protein synthesis, cell cycle and DNA processing, control of cellular organization, cell fate, and C-compound and carbohydrate metabolism categories, respectively. This study provides for the first time a snapshot of the genome-wide mRNA expression profiles in X- and gamma-ray post-irradiated yeast cells and comparatively interprets/discusses the changed gene functional categories as effects of these two radiations vis-à-vis their energy levels.
Geiger mode avalanche photodiodes for microarray systems
NASA Astrophysics Data System (ADS)
Phelan, Don; Jackson, Carl; Redfern, R. Michael; Morrison, Alan P.; Mathewson, Alan
2002-06-01
New Geiger Mode Avalanche Photodiodes (GM-APD) have been designed and characterized specifically for use in microarray systems. Critical parameters such as excess reverse bias voltage, hold-off time and optimum operating temperature have been experimentally determined for these photon-counting devices. The photon detection probability, dark count rate and afterpulsing probability have been measured under different operating conditions. An active- quench circuit (AQC) is presented for operating these GM- APDs. This circuit is relatively simple, robust and has such benefits as reducing average power dissipation and afterpulsing. Arrays of these GM-APDs have already been designed and together with AQCs open up the possibility of having a solid-state microarray detector that enables parallel analysis on a single chip. Another advantage of these GM-APDs over current technology is their low voltage CMOS compatibility which could allow for the fabrication of an AQC on the same device. Small are detectors have already been employed in the time-resolved detection of fluorescence from labeled proteins. It is envisaged that operating these new GM-APDs with this active-quench circuit will have numerous applications for the detection of fluorescence in microarray systems.
[Differential expression genes of bone tissues surrounding implants in diabetic rats by gene chip].
Wang, Xin-xin; Ma, Yue; Li, Qing; Jiang, Bao-qi; Lan, Jing
2012-10-01
To compare mRNA expression profiles of bone tissues surrounding implants between normal rats and rats with diabetes using microarray technology. Six Wistar rats were randomly selected and divided into normal model group and diabetic group. Diabetic model condition was established by injecting Streptozotocin into peritoneal space. Titanium implants were implanted into the epiphyseal end of the rats' tibia. Bone tissues surrounding implant were harvested and sampled after 3 months to perform comprehensive RNA gene expression profiling, including 17983 for genome-wide association study.GO analysis was used to compare different gene expression and real-time PCR was used to confirm the results on core samples. The results indicated that there were 1084 differential gene expression. In the diabetic model, there were 352 enhanced expression genes, 732 suppressed expression genes. GO analysis involved 1154 different functional type. Osteoblast related gene expressions in bone tissue samples of diabetic rats were decreased, and lipid metabolism pathway related gene expression was increased.
Zhou, Xiaobo; Qiu, Weiliang; Sathirapongsasuti, J. Fah.; Cho, Michael H.; Mancini, John D.; Lao, Taotao; Thibault, Derek M.; Litonjua, Gus; Bakke, Per S.; Gulsvik, Amund; Lomas, David A.; Beaty, Terri H.; Hersh, Craig P.; Anderson, Christopher; Geigenmuller, Ute; Raby, Benjamin A.; Rennard, Stephen I.; Perrella, Mark A.; Choi, Augustine M.K.; Quackenbush, John; Silverman, Edwin K.
2013-01-01
Hedgehog Interacting Protein (HHIP) was implicated in chronic obstructive pulmonary disease (COPD) by genome-wide association studies (GWAS). However, it remains unclear how HHIP contributes to COPD pathogenesis. To identify genes regulated by HHIP, we performed gene expression microarray analysis in a human bronchial epithelial cell line (Beas-2B) stably infected with HHIP shRNAs. HHIP silencing led to differential expression of 296 genes; enrichment for variants nominally associated with COPD was found. Eighteen of the differentially expressed genes were validated by real-time PCR in Beas-2B cells. Seven of 11 validated genes tested in human COPD and control lung tissues demonstrated significant gene expression differences. Functional annotation indicated enrichment for extracellular matrix and cell growth genes. Network modeling demonstrated that the extracellular matrix and cell proliferation genes influenced by HHIP tended to be interconnected. Thus, we identified potential HHIP targets in human bronchial epithelial cells that may contribute to COPD pathogenesis. PMID:23459001
DOE Office of Scientific and Technical Information (OSTI.GOV)
Zhou, J.; Wu, L.; Gentry, T.
2006-04-05
To effectively monitor microbial populations involved in various important processes, a 50-mer-based oligonucleotide microarray was developed based on known genes and pathways involved in: biodegradation, metal resistance and reduction, denitrification, nitrification, nitrogen fixation, methane oxidation, methanogenesis, carbon polymer decomposition, and sulfate reduction. This array contains approximately 2000 unique and group-specific probes with <85% similarity to their non-target sequences. Based on artificial probes, our results showed that at hybridization conditions of 50 C and 50% formamide, the 50-mer microarray hybridization can differentiate sequences having <88% similarity. Specificity tests with representative pure cultures indicated that the designed probes on the arrays appearedmore » to be specific to their corresponding target genes. Detection limits were about 5-10ng genomic DNA in the absence of background DNA, and 50-100ng ({approx}1.3{sup o} 10{sup 7} cells) in the presence background DNA. Strong linear relationships between signal intensity and target DNA and RNA concentration were observed (r{sup 2} = 0.95-0.99). Application of this microarray to naphthalene-amended enrichments and soil microcosms demonstrated that composition of the microflora varied depending on incubation conditions. While the naphthalene-degrading genes from Rhodococcus-type microorganisms were dominant in enrichments, the genes involved in naphthalene degradation from Gram-negative microorganisms such as Ralstonia, Comamonas, and Burkholderia were most abundant in the soil microcosms (as well as those for polyaromatic hydrocarbon and nitrotoluene degradation). Although naphthalene degradation is widely known and studied in Pseudomonas, Pseudomonas genes were not detected in either system. Real-time PCR analysis of 4 representative genes was consistent with microarray-based quantification (r{sup 2} = 0.95). Currently, we are also applying this microarray to the study of several different microbial communities and processes at the NABIR-FRC in Oak Ridge, TN. One project involves the monitoring of the development and dynamics of the microbial community of a fluidized bed reactor (FBR) used for reducing nitrate and the other project monitors microbial community responses to stimulation of uranium reducing populations via ethanol donor additions in situ and in a model system. Additionally, we are developing novel strategies for increasing microarray hybridization sensitivity. Finally, great improvements to our methods of probe design were made by the development of a new computer program, CommOligo. CommOligo designs unique and group-specific oligo probes for whole-genomes, metagenomes, and groups of environmental sequences and uses a new global alignment algorithm to design single or multiple probes for each gene or group. We are now using this program to design a more comprehensive functional gene array for environmental studies. Overall, our results indicate that the 50mer-based microarray technology has potential as a specific and quantitative tool to reveal the composition of microbial communities and their dynamics important to processes within contaminated environments.« less
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.
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.
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
Mining Microarray Data at NCBI’s Gene Expression Omnibus (GEO)*
Barrett, Tanya; Edgar, Ron
2006-01-01
Summary The Gene Expression Omnibus (GEO) at the National Center for Biotechnology Information (NCBI) has emerged as the leading fully public repository for gene expression data. This chapter describes how to use Web-based interfaces, applications, and graphics to effectively explore, visualize, and interpret the hundreds of microarray studies and millions of gene expression patterns stored in GEO. Data can be examined from both experiment-centric and gene-centric perspectives using user-friendly tools that do not require specialized expertise in microarray analysis or time-consuming download of massive data sets. The GEO database is publicly accessible through the World Wide Web at http://www.ncbi.nlm.nih.gov/geo. PMID:16888359
Reuse of imputed data in microarray analysis increases imputation efficiency
Kim, Ki-Yeol; Kim, Byoung-Jin; Yi, Gwan-Su
2004-01-01
Background The imputation of missing values is necessary for the efficient use of DNA microarray data, because many clustering algorithms and some statistical analysis require a complete data set. A few imputation methods for DNA microarray data have been introduced, but the efficiency of the methods was low and the validity of imputed values in these methods had not been fully checked. Results We developed a new cluster-based imputation method called sequential K-nearest neighbor (SKNN) method. This imputes the missing values sequentially from the gene having least missing values, and uses the imputed values for the later imputation. Although it uses the imputed values, the efficiency of this new method is greatly improved in its accuracy and computational complexity over the conventional KNN-based method and other methods based on maximum likelihood estimation. The performance of SKNN was in particular higher than other imputation methods for the data with high missing rates and large number of experiments. Application of Expectation Maximization (EM) to the SKNN method improved the accuracy, but increased computational time proportional to the number of iterations. The Multiple Imputation (MI) method, which is well known but not applied previously to microarray data, showed a similarly high accuracy as the SKNN method, with slightly higher dependency on the types of data sets. Conclusions Sequential reuse of imputed data in KNN-based imputation greatly increases the efficiency of imputation. The SKNN method should be practically useful to save the data of some microarray experiments which have high amounts of missing entries. The SKNN method generates reliable imputed values which can be used for further cluster-based analysis of microarray data. PMID:15504240
Nguewa, Paul A; Agorreta, Jackeline; Blanco, David; Lozano, Maria Dolores; Gomez-Roman, Javier; Sanchez, Blas A; Valles, Iñaki; Pajares, Maria J; Pio, Ruben; Rodriguez, Maria Jose; Montuenga, Luis M; Calvo, Alfonso
2008-01-01
Background The accurate normalization of differentially expressed genes in lung cancer is essential for the identification of novel therapeutic targets and biomarkers by real time RT-PCR and microarrays. Although classical "housekeeping" genes, such as GAPDH, HPRT1, and beta-actin have been widely used in the past, their accuracy as reference genes for lung tissues has not been proven. Results We have conducted a thorough analysis of a panel of 16 candidate reference genes for lung specimens and lung cell lines. Gene expression was measured by quantitative real time RT-PCR and expression stability was analyzed with the softwares GeNorm and NormFinder, mean of |ΔCt| (= |Ct Normal-Ct tumor|) ± SEM, and correlation coefficients among genes. Systematic comparison between candidates led us to the identification of a subset of suitable reference genes for clinical samples: IPO8, ACTB, POLR2A, 18S, and PPIA. Further analysis showed that IPO8 had a very low mean of |ΔCt| (0.70 ± 0.09), with no statistically significant differences between normal and malignant samples and with excellent expression stability. Conclusion Our data show that IPO8 is the most accurate reference gene for clinical lung specimens. In addition, we demonstrate that the commonly used genes GAPDH and HPRT1 are inappropriate to normalize data derived from lung biopsies, although they are suitable as reference genes for lung cell lines. We thus propose IPO8 as a novel reference gene for lung cancer samples. PMID:19014639
Pettit, Ashley P.; Brooks, Andrew; Laumbach, Robert; Fiedler, Nancy; Wang, Qi; Strickland, Pamela Ohman; Madura, Kiran; Zhang, Junfeng; Kipen, Howard M.
2013-01-01
Context Epidemiologic associations between acutely increased cardiorespiratory morbidity and mortality and particulate air pollution are well established, but the effects of acute pollution exposure on human gene expression changes are not well understood. Objective In order to identify potential mechanisms underlying epidemiologic associations between air pollution and morbidity, we explored changes in gene expression in humans following inhalation of fresh diesel exhaust (DE), a model for particulate air pollution. Materials and methods Fourteen ethnically homogeneous (white males), young, healthy subjects underwent 60-min inhalation exposures on 2 separate days with clean filtered air (CA) or freshly generated and diluted DE at a concentration of 300 μg/m3 PM2.5. Prior to and 24 h following each session, whole blood was sampled and fractionated for peripheral blood mononuclear cell (PBMC) isolation, RNA extraction, and generation of cDNA, followed by hybridization with Agilent Whole Human Genome (4X44K) arrays. Results Oxidative stress and the ubiquitin proteasome pathway, as well as the coagulation system, were among hypothesized pathways identified by analysis of differentially expressed genes. Nine genes from these pathways were validated using real-time polymerase chain reaction (PCR) to compare fold change in expression between DE exposed and CA days. Quantitative gene fold changes generated by real-time PCR were directionally consistent with the fold changes from the microarray analysis. Discussion and conclusion Changes in gene expression connected with key oxidative stress, protein degradation, and coagulation pathways are likely to underlie observed physiologic and clinical outcomes and suggest specific avenues and sensitive time points for further physiologic exploration. PMID:22369193
Zhang, Zhaowei; Li, Peiwu; Hu, Xiaofeng; Zhang, Qi; Ding, Xiaoxia; Zhang, Wen
2012-01-01
Chemical contaminants in food have caused serious health issues in both humans and animals. Microarray technology is an advanced technique suitable for the analysis of chemical contaminates. In particular, immuno-microarray approach is one of the most promising methods for chemical contaminants analysis. The use of microarrays for the analysis of chemical contaminants is the subject of this review. Fabrication strategies and detection methods for chemical contaminants are discussed in detail. Application to the analysis of mycotoxins, biotoxins, pesticide residues, and pharmaceutical residues is also described. Finally, future challenges and opportunities are discussed.
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.
A new measure for gene expression biclustering based on non-parametric correlation.
Flores, Jose L; Inza, Iñaki; Larrañaga, Pedro; Calvo, Borja
2013-12-01
One of the emerging techniques for performing the analysis of the DNA microarray data known as biclustering is the search of subsets of genes and conditions which are coherently expressed. These subgroups provide clues about the main biological processes. Until now, different approaches to this problem have been proposed. Most of them use the mean squared residue as quality measure but relevant and interesting patterns can not be detected such as shifting, or scaling patterns. Furthermore, recent papers show that there exist new coherence patterns involved in different kinds of cancer and tumors such as inverse relationships between genes which can not be captured. The proposed measure is called Spearman's biclustering measure (SBM) which performs an estimation of the quality of a bicluster based on the non-linear correlation among genes and conditions simultaneously. The search of biclusters is performed by using a evolutionary technique called estimation of distribution algorithms which uses the SBM measure as fitness function. This approach has been examined from different points of view by using artificial and real microarrays. The assessment process has involved the use of quality indexes, a set of bicluster patterns of reference including new patterns and a set of statistical tests. It has been also examined the performance using real microarrays and comparing to different algorithmic approaches such as Bimax, CC, OPSM, Plaid and xMotifs. SBM shows several advantages such as the ability to recognize more complex coherence patterns such as shifting, scaling and inversion and the capability to selectively marginalize genes and conditions depending on the statistical significance. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.
Waveguide-excited fluorescence microarray
NASA Astrophysics Data System (ADS)
Sagarzazu, Gabriel; Bedu, Mélanie; Martinelli, Lucio; Ha, Khoi-Nguyen; Pelletier, Nicolas; Safarov, Viatcheslav I.; Weisbuch, Claude; Gacoin, Thierry; Benisty, Henri
2008-04-01
Signal-to-noise ratio is a crucial issue in microarray fluorescence read-out. Several strategies are proposed for its improvement. First, light collection in conventional microarrays scanners is quite limited. It was recently shown that almost full collection can be achieved in an integrated lens-free biosensor, with labelled species hybridizing practically on the surface of a sensitive silicon detector [L. Martinelli et al. Appl. Phys. Lett. 91, 083901 (2007)]. However, even with such an improvement, the ultimate goal of real-time measurements during hybridization is challenging: the detector is dazzled by the large fluorescence of labelled species in the solution. In the present paper we show that this unwanted signal can effectively be reduced if the excitation light is confined in a waveguide. Moreover, the concentration of excitation light in a waveguide results in a huge signal gain. In our experiment we realized a structure consisting of a high index sol-gel waveguide deposited on a low-index substrate. The fluorescent molecules deposited on the surface of the waveguide were excited by the evanescent part of a wave travelling in the guide. The comparison with free-space excitation schemes confirms a huge gain (by several orders of magnitude) in favour of waveguide-based excitation. An optical guide deposited onto an integrated biosensor thus combines both advantages of ideal light collection and enhanced surface localized excitation without compromising the imaging properties. Modelling predicts a negligible penalty from spatial cross-talk in practical applications. We believe that such a system would bring microarrays to hitherto unattained sensitivities.
Sehgal, Muhammad Shoaib B; Gondal, Iqbal; Dooley, Laurence S
2005-05-15
Microarray data are used in a range of application areas in biology, although often it contains considerable numbers of missing values. These missing values can significantly affect subsequent statistical analysis and machine learning algorithms so there is a strong motivation to estimate these values as accurately as possible before using these algorithms. While many imputation algorithms have been proposed, more robust techniques need to be developed so that further analysis of biological data can be accurately undertaken. In this paper, an innovative missing value imputation algorithm called collateral missing value estimation (CMVE) is presented which uses multiple covariance-based imputation matrices for the final prediction of missing values. The matrices are computed and optimized using least square regression and linear programming methods. The new CMVE algorithm has been compared with existing estimation techniques including Bayesian principal component analysis imputation (BPCA), least square impute (LSImpute) and K-nearest neighbour (KNN). All these methods were rigorously tested to estimate missing values in three separate non-time series (ovarian cancer based) and one time series (yeast sporulation) dataset. Each method was quantitatively analyzed using the normalized root mean square (NRMS) error measure, covering a wide range of randomly introduced missing value probabilities from 0.01 to 0.2. Experiments were also undertaken on the yeast dataset, which comprised 1.7% actual missing values, to test the hypothesis that CMVE performed better not only for randomly occurring but also for a real distribution of missing values. The results confirmed that CMVE consistently demonstrated superior and robust estimation capability of missing values compared with other methods for both series types of data, for the same order of computational complexity. A concise theoretical framework has also been formulated to validate the improved performance of the CMVE algorithm. The CMVE software is available upon request from the authors.
DNA microarrays: a powerful genomic tool for biomedical and clinical research
Trevino, Victor; Falciani, Francesco; Barrera-Saldaña, Hugo A.
2007-01-01
Among the many benefits of the Human Genome Project are new and powerful tools such as the genome-wide hybridization devices referred as microarrays. Initially designed to measure gene transcriptional levels, microarray technologies are now used for comparing other genome features among individuals and their tissues and cells. Results provide valuable information on disease subcategories, disease prognosis, and treatment outcome. Likewise, reveal differences in genetic makeup, regulatory mechanisms and subtle variations are approaching the era of personalized medicine. To understand this powerful tool, its versatility and how it is dramatically changing the molecular approach to biomedical and clinical research, this review describes the technology, its applications, a didactic step-by-step review of a typical microarray protocol, and a real experiment. Finally, it calls the attention of the medical community to integrate multidisciplinary teams, to take advantage of this technology and its expanding applications that in a slide reveals our genetic inheritance and destiny. PMID:17660860
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…
DOE Office of Scientific and Technical Information (OSTI.GOV)
Kim, Yongbaek; Thai-Vu Ton; De Angelo, Anthony B.
2006-07-15
This study was performed to characterize the gene expression profile and to identify the major carcinogenic pathways involved in rat peritoneal mesothelioma (RPM) formation following treatment of Fischer 344 rats with o-nitrotoluene (o-NT) or bromochloracetic acid (BCA). Oligo arrays, with over 20,000 target genes, were used to evaluate o-NT- and BCA-induced RPMs, when compared to a non-transformed mesothelial cell line (Fred-PE). Analysis using Ingenuity Pathway Analysis software revealed 169 cancer-related genes that were categorized into binding activity, growth and proliferation, cell cycle progression, apoptosis, and invasion and metastasis. The microarray data were validated by positive correlation with quantitative real-time RT-PCRmore » on 16 selected genes including igf1, tgfb3 and nov. Important carcinogenic pathways involved in RPM formation included insulin-like growth factor 1 (IGF-1), p38 MAPkinase, Wnt/{beta}-catenin and integrin signaling pathways. This study demonstrated that mesotheliomas in rats exposed to o-NT- and BCA were similar to mesotheliomas in humans, at least at the cellular and molecular level.« less
Preparation of Formalin-fixed Paraffin-embedded Tissue Cores for both RNA and DNA Extraction.
Patel, Palak G; Selvarajah, Shamini; Boursalie, Suzanne; How, Nathan E; Ejdelman, Joshua; Guerard, Karl-Philippe; Bartlett, John M; Lapointe, Jacques; Park, Paul C; Okello, John B A; Berman, David M
2016-08-21
Formalin-fixed paraffin embedded tissue (FFPET) represents a valuable, well-annotated substrate for molecular investigations. The utility of FFPET in molecular analysis is complicated both by heterogeneous tissue composition and low yields when extracting nucleic acids. A literature search revealed a paucity of protocols addressing these issues, and none that showed a validated method for simultaneous extraction of RNA and DNA from regions of interest in FFPET. This method addresses both issues. Tissue specificity was achieved by mapping cancer areas of interest on microscope slides and transferring annotations onto FFPET blocks. Tissue cores were harvested from areas of interest using 0.6 mm microarray punches. Nucleic acid extraction was performed using a commercial FFPET extraction system, with modifications to homogenization, deparaffinization, and Proteinase K digestion steps to improve tissue digestion and increase nucleic acid yields. The modified protocol yields sufficient quantity and quality of nucleic acids for use in a number of downstream analyses, including a multi-analyte gene expression platform, as well as reverse transcriptase coupled real time PCR analysis of mRNA expression, and methylation-specific PCR (MSP) analysis of DNA methylation.
Zhao, Jie
2010-01-01
Arabinogalactan proteins (AGPs) comprise a family of hydroxyproline-rich glycoproteins that are implicated in plant growth and development. In this study, 69 AGPs are identified from the rice genome, including 13 classical AGPs, 15 arabinogalactan (AG) peptides, three non-classical AGPs, three early nodulin-like AGPs (eNod-like AGPs), eight non-specific lipid transfer protein-like AGPs (nsLTP-like AGPs), and 27 fasciclin-like AGPs (FLAs). The results from expressed sequence tags, microarrays, and massively parallel signature sequencing tags are used to analyse the expression of AGP-encoding genes, which is confirmed by real-time PCR. The results reveal that several rice AGP-encoding genes are predominantly expressed in anthers and display differential expression patterns in response to abscisic acid, gibberellic acid, and abiotic stresses. Based on the results obtained from this analysis, an attempt has been made to link the protein structures and expression patterns of rice AGP-encoding genes to their functions. Taken together, the genome-wide identification and expression analysis of the rice AGP gene family might facilitate further functional studies of rice AGPs. PMID:20423940
Microarray platform for omics analysis
NASA Astrophysics Data System (ADS)
Mecklenburg, Michael; Xie, Bin
2001-09-01
Microarray technology has revolutionized genetic analysis. However, limitations in genome analysis has lead to renewed interest in establishing 'omic' strategies. As we enter the post-genomic era, new microarray technologies are needed to address these new classes of 'omic' targets, such as proteins, as well as lipids and carbohydrates. We have developed a microarray platform that combines self- assembling monolayers with the biotin-streptavidin system to provide a robust, versatile immobilization scheme. A hydrophobic film is patterned on the surface creating an array of tension wells that eliminates evaporation effects thereby reducing the shear stress to which biomolecules are exposed to during immobilization. The streptavidin linker layer makes it possible to adapt and/or develop microarray based assays using virtually any class of biomolecules including: carbohydrates, peptides, antibodies, receptors, as well as them ore traditional DNA based arrays. Our microarray technology is designed to furnish seamless compatibility across the various 'omic' platforms by providing a common blueprint for fabricating and analyzing arrays. The prototype microarray uses a microscope slide footprint patterned with 2 by 96 flat wells. Data on the microarray platform will be presented.
Su, Huafang; Lin, Fuqiang; Deng, Xia; Shen, Lanxiao; Fang, Ya; Fei, Zhenghua; Zhao, Lihao; Zhang, Xuebang; Pan, Huanle; Xie, Deyao; Jin, Xiance; Xie, Congying
2016-07-28
Acquired radioresistance during radiotherapy is considered as the most important reason for local tumor recurrence or treatment failure. Circular RNAs (circRNAs) have recently been identified as microRNA sponges and involve in various biological processes. The purpose of this study is to investigate the role of circRNAs in the radioresistance of esophageal cancer. Total RNA was isolated from human parental cell line KYSE-150 and self-established radioresistant esophageal cancer cell line KYSE-150R, and hybridized to Arraystar Human circRNA Array. Quantitative real-time PCR was used to confirm the circRNA expression profiles obtained from the microarray data. Bioinformatic tools including gene ontology (GO) analysis, KEGG pathway analysis and network analysis were done for further assessment. Among the detected candidate 3752 circRNA genes, significant upregulation of 57 circRNAs and downregulation of 17 circRNAs in human radioresistant esophageal cancer cell line KYSE-150R were observed compared with the parental cell line KYSE-150 (fold change ≥2.0 and P < 0.05). There were 9 out of these candidate circRNAs were validated by real-time PCR. GO analysis revealed that numerous target genes, including most microRNAs were involved in the biological processes. There were more than 400 target genes enrichment on Wnt signaling pathway. CircRNA_001059 and circRNA_000167 were the two largest nodes in circRNA/microRNA co-expression network. Our study revealed a comprehensive expression and functional profile of differentially expressed circRNAs in radioresistant esophageal cancer cells, indicating possible involvement of these dysregulated circRNAs in the development of radiation resistance.
Genome-wide identification of WRKY family genes and their response to cold stress in Vitis vinifera
2014-01-01
Background WRKY transcription factors are one of the largest families of transcriptional regulators in plants. WRKY genes are not only found to play significant roles in biotic and abiotic stress response, but also regulate growth and development. Grapevine (Vitis vinifera) production is largely limited by stressful climate conditions such as cold stress and the role of WRKY genes in the survival of grapevine under these conditions remains unknown. Results We identified a total of 59 VvWRKYs from the V. vinifera genome, belonging to four subgroups according to conserved WRKY domains and zinc-finger structure. The majority of VvWRKYs were expressed in more than one tissue among the 7 tissues examined which included young leaves, mature leaves, tendril, stem apex, root, young fruits and ripe fruits. Publicly available microarray data suggested that a subset of VvWRKYs was activated in response to diverse stresses. Quantitative real-time PCR (qRT-PCR) results demonstrated that the expression levels of 36 VvWRKYs are changed following cold exposure. Comparative analysis was performed on data from publicly available microarray experiments, previous global transcriptome analysis studies, and qRT-PCR. We identified 15 VvWRKYs in at least two of these databases which may relate to cold stress. Among them, the transcription of three genes can be induced by exogenous ABA application, suggesting that they can be involved in an ABA-dependent signaling pathway in response to cold stress. Conclusions We identified 59 VvWRKYs from the V. vinifera genome and 15 of them showed cold stress-induced expression patterns. These genes represented candidate genes for future functional analysis of VvWRKYs involved in the low temperature-related signal pathways in grape. PMID:24755338
Moreb, Jan S; Baker, Henry V; Chang, Lung-Ji; Amaya, Maria; Lopez, M Cecilia; Ostmark, Blanca; Chou, Wayne
2008-11-24
Aldehyde dehydrogenase isozymes ALDH1A1 and ALDH3A1 are highly expressed in non small cell lung cancer. Neither the mechanisms nor the biologic significance for such over expression have been studied. We have employed oligonucleotide microarrays to analyze changes in gene profiles in A549 lung cancer cell line in which ALDH activity was reduced by up to 95% using lentiviral mediated expression of siRNA against both isozymes (Lenti 1+3). Stringent analysis methods were used to identify gene expression patterns that are specific to the knock down of ALDH activity and significantly different in comparison to wild type A549 cells (WT) or cells similarly transduced with green fluorescent protein (GFP) siRNA. We confirmed significant and specific down regulation of ALDH1A1 and ALDH3A1 in Lenti 1+3 cells and in comparison to 12 other ALDH genes detected. The results of the microarray analysis were validated by real time RT-PCR on RNA obtained from Lenti 1+3 or WT cells treated with ALDH activity inhibitors. Detailed functional analysis was performed on 101 genes that were significantly different (P < 0.001) and their expression changed by > or = 2 folds in the Lenti 1+3 group versus the control groups. There were 75 down regulated and 26 up regulated genes. Protein binding, organ development, signal transduction, transcription, lipid metabolism, and cell migration and adhesion were among the most affected pathways. These molecular effects of the ALDH knock-down are associated with in vitro functional changes in the proliferation and motility of these cells and demonstrate the significance of ALDH enzymes in cell homeostasis with a potentially significant impact on the treatment of lung cancer.
microRNA-206 in Rat Medial Prefrontal Cortex Regulates BDNF Expression and Alcohol Drinking
Barbier, Estelle; Flanigan, Meghan; Solomon, Matthew; Pincus, Alexandra; Pilling, Andrew; Sun, Hui; Schank, Jesse R.; King, Courtney; Heilig, Markus
2014-01-01
Escalation of voluntary alcohol consumption is a hallmark of alcoholism, but its neural substrates remain unknown. In rats, escalation occurs following prolonged exposure to cycles of alcohol intoxication, and is associated with persistent, wide-ranging changes in gene expression within the medial prefrontal cortex (mPFC). Here, we examined whether induction of microRNA (miR) 206 in mPFC contributes to escalated alcohol consumption. Following up on a microarray screen, quantitative real-time reverse transcription PCR (qPCR) confirmed that a history of dependence results in persistent (>3weeks) up-regulation of miR-206 expression in the mPFC, but not in the ventral tegmental area, amygdala, or nucleus accumbens. Viral-mediated overexpression of miR-206 in the mPFC of nondependent rats reproduced the escalation of alcohol self-administration seen following a history of dependence and significantly inhibited BDNF expression. Bioinformatic analysis identified three conserved target sites for miR-206 in the 3′-UTR of the rat BDNF transcript. Accordingly, BDNF was downregulated in post-dependent rats on microarray analysis, and this was confirmed by qPCR. In vitro, BDNF expression was repressed by miR-206 but not miR-9 in a 3′-UTR reporter assay, confirming BDNF as a functional target of miR-206. Mutation analysis showed that repression was dependent on the presence of all three miR-206 target sites in the BDNF 3′-UTR. Inhibition of miR-206 expression in differentiated rat cortical primary neurons significantly increased secreted levels of BDNF. In conclusion, recruitment of miR-206 in the mPFC contributes to escalated alcohol consumption following a history of dependence, with BDNF as a possible mediator of its action. PMID:24672003
Tsunoda, Fumiyoshi; Lamon-Fava, Stefania; Asztalos, Bela F; Iyer, Lakshmanan K; Richardson, Kris; Schaefer, Ernst J
2015-08-01
Eicosapentaenoic acid (EPA) and docosahexaenoic acid (DHA) have beneficial effects on inflammation and cardiovascular disease (CVD). Our aim was to assess the effect of a six-week supplementation with either olive oil, EPA, or DHA on gene expression in peripheral blood mononuclear cells (PBMC). Subjects were sampled at baseline and six weeks after receiving either: olive oil 6.0 g/day (n = 16), EPA 1.8 g/day (n = 16), or DHA 1.8 g/day (n = 18). PBMC were subjected to gene expression analysis by microarray with key findings confirmed by quantitative real-time polymerase chain reaction (Q-PCR). Plasma phospholipid EPA increased 3 fold in the EPA group, and DHA increased 63% in the DHA group (both p < 0.01), while no effects were observed in the olive oil group. Microarray analysis indicated that EPA but not DHA or olive oil significantly affected the gene expression in the following pathways: 1) interferon signaling, 2) receptor recognition of bacteria and viruses, 3) G protein signaling, glycolysis and glycolytic shunting, 4) S-adenosyl-l-methionine biosynthesis, and 5) cAMP-mediated signaling including cAMP responsive element protein 1 (CREB1), as well as many other individual genes including hypoxia inducible factor 1, α subunit (HIF1A). The findings for CREB1 and HIF1A were confirmed by Q-PCR analysis. Our data indicate that EPA supplementation was associated with significant effects on gene expression involving the interferon pathway as well as down-regulation of CREB1 and HIF1A, which may relate to its beneficial effect on CVD risk reduction. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.
microRNA-206 in rat medial prefrontal cortex regulates BDNF expression and alcohol drinking.
Tapocik, Jenica D; Barbier, Estelle; Flanigan, Meghan; Solomon, Matthew; Pincus, Alexandra; Pilling, Andrew; Sun, Hui; Schank, Jesse R; King, Courtney; Heilig, Markus
2014-03-26
Escalation of voluntary alcohol consumption is a hallmark of alcoholism, but its neural substrates remain unknown. In rats, escalation occurs following prolonged exposure to cycles of alcohol intoxication, and is associated with persistent, wide-ranging changes in gene expression within the medial prefrontal cortex (mPFC). Here, we examined whether induction of microRNA (miR) 206 in mPFC contributes to escalated alcohol consumption. Following up on a microarray screen, quantitative real-time reverse transcription PCR (qPCR) confirmed that a history of dependence results in persistent (>3weeks) up-regulation of miR-206 expression in the mPFC, but not in the ventral tegmental area, amygdala, or nucleus accumbens. Viral-mediated overexpression of miR-206 in the mPFC of nondependent rats reproduced the escalation of alcohol self-administration seen following a history of dependence and significantly inhibited BDNF expression. Bioinformatic analysis identified three conserved target sites for miR-206 in the 3'-UTR of the rat BDNF transcript. Accordingly, BDNF was downregulated in post-dependent rats on microarray analysis, and this was confirmed by qPCR. In vitro, BDNF expression was repressed by miR-206 but not miR-9 in a 3'-UTR reporter assay, confirming BDNF as a functional target of miR-206. Mutation analysis showed that repression was dependent on the presence of all three miR-206 target sites in the BDNF 3'-UTR. Inhibition of miR-206 expression in differentiated rat cortical primary neurons significantly increased secreted levels of BDNF. In conclusion, recruitment of miR-206 in the mPFC contributes to escalated alcohol consumption following a history of dependence, with BDNF as a possible mediator of its action.
Expanding frontiers in plant transcriptomics in aid of functional genomics and molecular breeding.
Agarwal, Pinky; Parida, Swarup K; Mahto, Arunima; Das, Sweta; Mathew, Iny Elizebeth; Malik, Naveen; Tyagi, Akhilesh K
2014-12-01
The transcript pool of a plant part, under any given condition, is a collection of mRNAs that will pave the way for a biochemical reaction of the plant to stimuli. Over the past decades, transcriptome study has advanced from Northern blotting to RNA sequencing (RNA-seq), through other techniques, of which real-time quantitative polymerase chain reaction (PCR) and microarray are the most significant ones. The questions being addressed by such studies have also matured from a solitary process to expression atlas and marker-assisted genetic enhancement. Not only genes and their networks involved in various developmental processes of plant parts have been elucidated, but also stress tolerant genes have been highlighted. The transcriptome of a plant with altered expression of a target gene has given information about the downstream genes. Marker information has been used for breeding improved varieties. Fortunately, the data generated by transcriptome analysis has been made freely available for ample utilization and comparison. The review discusses this wide variety of transcriptome data being generated in plants, which includes developmental stages, abiotic and biotic stress, effect of altered gene expression, as well as comparative transcriptomics, with a special emphasis on microarray and RNA-seq. Such data can be used to determine the regulatory gene networks, which can subsequently be utilized for generating improved plant varieties. Copyright © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.
Microarray mRNA expression analysis of Fanconi anemia fibroblasts.
Galetzka, D; Weis, E; Rittner, G; Schindler, D; Haaf, T
2008-01-01
Fanconi anemia (FA) cells are generally hypersensitive to DNA cross-linking agents, implying that mutations in the different FANC genes cause a similar DNA repair defect(s). By using a customized cDNA microarray chip for DNA repair- and cell cycle-associated genes, we identified three genes, cathepsin B (CTSB), glutaredoxin (GLRX), and polo-like kinase 2 (PLK2), that were misregulated in untreated primary fibroblasts from three unrelated FA-D2 patients, compared to six controls. Quantitative real-time RT PCR was used to validate these results and to study possible molecular links between FA-D2 and other FA subtypes. GLRX was misregulated to opposite directions in a variety of different FA subtypes. Increased CTSB and decreased PLK2 expression was found in all or almost all of the analyzed complementation groups and, therefore, may be related to the defective FA pathway. Transcriptional upregulation of the CTSB proteinase appears to be a secondary phenomenon due to proliferation differences between FA and normal fibroblast cultures. In contrast, PLK2 is known to play a pivotal role in processes that are linked to FA defects and may contribute in multiple ways to the FA phenotype: PLK2 is a target gene for TP53, is likely to function as a tumor suppressor gene in hematologic neoplasia, and Plk2(-/-) mice are small because of defective embryonal development. (c) 2008 S. Karger AG, Basel.
Rüegg, S R; Regenscheit, N; Origgi, F C; Kaiser, C; Borel, N
2015-09-01
In a collection of 58 snakes comprising predominantly Eurasian vipers in Switzerland, five snakes died unexpectedly during hibernation from 2009 to 2012. In one snake, organisms resembling chlamydiae were detected by immunohistochemistry in multiple histiocytic granulomas. Real-time quantitative PCR and microarray analysis were used to determine the presence of Chlamydia pneumoniae in tissue samples and cloacal/choanal swabs from snakes in the collection; 8/53 (15.1%) of the remaining snakes were positive. Although one infected snake had suppurative periglossitis, infection with C. pneumoniae did not appear to be associated with specific clinical signs in snakes. Of seven snakes treated with 5 mg/kg marbofloxacin IM once daily, five became PCR negative for C. pneumoniae following treatment, whereas one animal remained positive and one snake was lost to follow-up. Copyright © 2015 Elsevier Ltd. All rights reserved.
Zoonotic Chlamydiaceae Species Associated with Trachoma, Nepal
Rothschild, James; Ruettger, Anke; Kandel, Ram Prasad; Sachse, Konrad
2013-01-01
Trachoma is the leading cause of preventable blindness. Commercial assays do not discriminate among all Chlamydiaceae species that might be involved in trachoma. We investigated whether a commercial Micro-ArrayTube could discriminate Chlamydiaceae species in DNA extracted directly from conjunctival samples from 101 trachoma patients in Nepal. To evaluate organism viability, we extracted RNA, reverse transcribed it, and subjected it to quantitative real-time PCR. We found that 71 (70.3%) villagers were infected. ArrayTube sensitivity was 91.7% and specificity was 100% compared with that of real-time PCR. Concordance between genotypes detected by microarray and ompA genotyping was 100%. Species distribution included 54 (76%) single infections with Chlamydia trachomatis, C. psittaci, C. suis, or C. pecorum, and 17 (24%) mixed infections that includied C. pneumoniae. Ocular infections were caused by 5 Chlamydiaceae species. Additional studies of trachoma pathogenesis involving Chlamydiaceae species other than C. trachomatis and their zoonotic origins are needed. PMID:24274654
Microarrays in brain research: the good, the bad and the ugly.
Mirnics, K
2001-06-01
Making sense of microarray data is a complex process, in which the interpretation of findings will depend on the overall experimental design and judgement of the investigator performing the analysis. As a result, differences in tissue harvesting, microarray types, sample labelling and data analysis procedures make post hoc sharing of microarray data a great challenge. To ensure rapid and meaningful data exchange, we need to create some order out of the existing chaos. In these ground-breaking microarray standardization and data sharing efforts, NIH agencies should take a leading role
Weniger, Markus; Engelmann, Julia C; Schultz, Jörg
2007-01-01
Background Regulation of gene expression is relevant to many areas of biology and medicine, in the study of treatments, diseases, and developmental stages. Microarrays can be used to measure the expression level of thousands of mRNAs at the same time, allowing insight into or comparison of different cellular conditions. The data derived out of microarray experiments is highly dimensional and often noisy, and interpretation of the results can get intricate. Although programs for the statistical analysis of microarray data exist, most of them lack an integration of analysis results and biological interpretation. Results We have developed GEPAT, Genome Expression Pathway Analysis Tool, offering an analysis of gene expression data under genomic, proteomic and metabolic context. We provide an integration of statistical methods for data import and data analysis together with a biological interpretation for subsets of probes or single probes on the chip. GEPAT imports various types of oligonucleotide and cDNA array data formats. Different normalization methods can be applied to the data, afterwards data annotation is performed. After import, GEPAT offers various statistical data analysis methods, as hierarchical, k-means and PCA clustering, a linear model based t-test or chromosomal profile comparison. The results of the analysis can be interpreted by enrichment of biological terms, pathway analysis or interaction networks. Different biological databases are included, to give various information for each probe on the chip. GEPAT offers no linear work flow, but allows the usage of any subset of probes and samples as a start for a new data analysis. GEPAT relies on established data analysis packages, offers a modular approach for an easy extension, and can be run on a computer grid to allow a large number of users. It is freely available under the LGPL open source license for academic and commercial users at . Conclusion GEPAT is a modular, scalable and professional-grade software integrating analysis and interpretation of microarray gene expression data. An installation available for academic users can be found at . PMID:17543125
Li, Huiyan; Leulmi, Rym Feriel; Juncker, David
2011-02-07
Antibody microarrays are a powerful tool for rapid, multiplexed profiling of proteins. 3D microarray substrates have been developed to improve binding capacity, assay sensitivity, and mass transport, however, they often rely on photopolymers which are difficult to manufacture and have a small pore size that limits mass transport and demands long incubation time. Here, we present a novel 3D antibody microarray format based on the entrapment of antibody-coated microbeads within alginate droplets that were spotted onto a glass slide using an inkjet. Owing to the low concentration of alginate used, the gels were highly porous to proteins, and together with the 3D architecture helped enhance mass transport during the assays. The spotting parameters were optimized for the attachment of the alginate to the substrate. Beads with 0.2 µm, 0.5 µm and 1 µm diameter were tested and 1 µm beads were selected based on their superior retention within the hydrogel. The beads were found to be distributed within the entire volume of the gel droplet using confocal microscopy. The assay time and the concentration of beads in the gels were investigated for maximal binding signal using one-step immunoassays. As a proof of concept, six proteins including cytokines (TNFα, IL-8 and MIP/CCL4), breast cancer biomarkers (CEA and HER2) and one cancer-related protein (ENG) were profiled in multiplex using sandwich assays down to pg mL(-1) concentrations with 1 h incubation without agitation in both buffer solutions and 10% serum. These results illustrate the potential of beads-in-gel microarrays for highly sensitive and multiplexed protein analysis.
Trivedi, Prinal; Edwards, Jode W; Wang, Jelai; Gadbury, Gary L; Srinivasasainagendra, Vinodh; Zakharkin, Stanislav O; Kim, Kyoungmi; Mehta, Tapan; Brand, Jacob P L; Patki, Amit; Page, Grier P; Allison, David B
2005-04-06
Many efforts in microarray data analysis are focused on providing tools and methods for the qualitative analysis of microarray data. HDBStat! (High-Dimensional Biology-Statistics) is a software package designed for analysis of high dimensional biology data such as microarray data. It was initially developed for the analysis of microarray gene expression data, but it can also be used for some applications in proteomics and other aspects of genomics. HDBStat! provides statisticians and biologists a flexible and easy-to-use interface to analyze complex microarray data using a variety of methods for data preprocessing, quality control analysis and hypothesis testing. Results generated from data preprocessing methods, quality control analysis and hypothesis testing methods are output in the form of Excel CSV tables, graphs and an Html report summarizing data analysis. HDBStat! is a platform-independent software that is freely available to academic institutions and non-profit organizations. It can be downloaded from our website http://www.soph.uab.edu/ssg_content.asp?id=1164.
Circular RNA profiles in mouse lung tissue induced by radon.
Pei, Weiwei; Tao, Lijing; Zhang, Leshuai W; Zhang, Shuyu; Cao, Jianping; Jiao, Yang; Tong, Jian; Nie, Jihua
2017-04-07
Radon is a known human lung carcinogen, whose underlying carcinogenic mechanism remains unclear. Recently, circular RNA (circRNA), a class of endogenous non-protein coding RNAs that contain a circular loop, was found to exhibit multiple biological effects. In this study, circRNA profiles in mouse lung tissues between control and radon exposure were analyzed. Six mice were exposed to radon at concentration of 100,000 Bq/m 3 , 12 h/d, for up to cumulative doses of 60 working level months (WLM). H&E staining and immunohistochemistry of caspase-3 were used to detect the damages in lung tissue. The lung tissue of control and exposed group were selected for circRNA microarray study. The circRNA/microRNA interaction was analyzed by starBase prediction software. 5 highest expressing circRNAs were selected by real-time PCR to validate the consistency in mouse lung tissue exposed to radon. Inflammatory reaction was found in mouse lung tissue exposed to radon, and caspase-3 expression was significantly increased. Microarray screening revealed 107 up-regulated and 83 down-regulated circRNAs, among which top 30 circRNAs with the highest fold changes were chosen for further analysis, with 5 microRNAs binding sites listed for each circRNA. Consistency of the top 5 circRNAs with the highest expressions were confirmed in mice exposed with 60WLM of radon. Mouse lung tissue was severely injured when exposed to radon through pathological diagnosis and immunohistochemical analysis. A series of differentially expressed circRNAs demonstrated that they may play an important role in pulmonary toxicity induced by radon.
Monticone, Massimiliano; Daga, Antonio; Candiani, Simona; Romeo, Francesco; Mirisola, Valentina; Viaggi, Silvia; Melloni, Ilaria; Pedemonte, Simona; Zona, Gianluigi; Giaretti, Walter; Pfeffer, Ulrich; Castagnola, Patrizio
2012-08-17
Most patients affected by Glioblastoma multiforme (GBM, grade IV glioma) experience a recurrence of the disease because of the spreading of tumor cells beyond surgical boundaries. Unveiling mechanisms causing this process is a logic goal to impair the killing capacity of GBM cells by molecular targeting.We noticed that our long-term GBM cultures, established from different patients, may display two categories/types of growth behavior in an orthotopic xenograft model: expansion of the tumor mass and formation of tumor branches/nodules (nodular like, NL-type) or highly diffuse single tumor cell infiltration (HD-type). We determined by DNA microarrays the gene expression profiles of three NL-type and three HD-type long-term GBM cultures. Subsequently, individual genes with different expression levels between the two groups were identified using Significance Analysis of Microarrays (SAM). Real time RT-PCR, immunofluorescence and immunoblot analyses, were performed for a selected subgroup of regulated gene products to confirm the results obtained by the expression analysis. Here, we report the identification of a set of 34 differentially expressed genes in the two types of GBM cultures. Twenty-three of these genes encode for proteins localized to the plasma membrane and 9 of these for proteins are involved in the process of cell adhesion. This study suggests the participation in the diffuse infiltrative/invasive process of GBM cells within the CNS of a novel set of genes coding for membrane-associated proteins, which should be thus susceptible to an inhibition strategy by specific targeting.Massimiliano Monticone and Antonio Daga contributed equally to this work.
Gastroesophageal reflux activates the NF-κB pathway and impairs esophageal barrier function in mice
Fang, Yu; Chen, Hao; Hu, Yuhui; Djukic, Zorka; Tevebaugh, Whitney; Shaheen, Nicholas J.; Orlando, Roy C.; Hu, Jianguo
2013-01-01
The barrier function of the esophageal epithelium is a major defense against gastroesophageal reflux disease. Previous studies have shown that reflux damage is reflected in a decrease in transepithelial electrical resistance associated with tight junction alterations in the esophageal epithelium. To develop novel therapies, it is critical to understand the molecular mechanisms whereby contact with a refluxate impairs esophageal barrier function. In this study, surgical models of duodenal and mixed reflux were developed in mice. Mouse esophageal epithelium was analyzed by gene microarray. Gene set enrichment analysis showed upregulation of inflammation-related gene sets and the NF-κB pathway due to reflux. Significance analysis of microarrays revealed upregulation of NF-κB target genes. Overexpression of NF-κB subunits (p50 and p65) and NF-κB target genes (matrix metalloproteinases-3 and -9, IL-1β, IL-6, and IL-8) confirmed activation of the NF-κB pathway in the esophageal epithelium. In addition, real-time PCR, Western blotting, and immunohistochemical staining also showed downregulation and mislocalization of claudins-1 and -4. In a second animal experiment, treatment with an NF-κB inhibitor, BAY 11-7085 (20 mg·kg−1·day−1 ip for 10 days), counteracted the effects of duodenal and mixed reflux on epithelial resistance and NF-κB-regulated cytokines. We conclude that gastroesophageal reflux activates the NF-κB pathway and impairs esophageal barrier function in mice and that targeting the NF-κB pathway may strengthen esophageal barrier function against reflux. PMID:23639809
Prognostic significance of TRIM24/TIF-1α gene expression in breast cancer.
Chambon, Monique; Orsetti, Béatrice; Berthe, Marie-Laurence; Bascoul-Mollevi, Caroline; Rodriguez, Carmen; Duong, Vanessa; Gleizes, Michel; Thénot, Sandrine; Bibeau, Frédéric; Theillet, Charles; Cavaillès, Vincent
2011-04-01
In this study, we have analyzed the expression of TRIM24/TIF-1α, a negative regulator of various transcription factors (including nuclear receptors and p53) at the genomic, mRNA, and protein levels in human breast tumors. In breast cancer biopsy specimens, TRIM24/TIF-1α mRNA levels (assessed by Real-Time Quantitative PCR or microarray expression profiling) were increased as compared to normal breast tissues. At the genomic level, array comparative genomic hybridization analysis showed that the TRIM24/TIF-1α locus (7q34) exhibited both gains and losses that correlated with mRNA levels. By re-analyzing a series of 238 tumors, high levels of TRIM24/TIF-1α mRNA significantly correlated with various markers of poor prognosis (such as the molecular subtype) and were associated with worse overall survival. By using a rabbit polyclonal antibody for immunochemistry, the TRIM24/TIF-1α protein was detected in nuclei of normal luminal epithelial breast cells, but not in myoepithelial cells. Tissue microarray analysis confirmed that its expression was increased in epithelial cells from normal to breast infiltrating duct carcinoma and correlated with worse overall survival. Altogether, this work is the first study that shows that overexpression of the TRIM24/TIF-1α gene in breast cancer is associated with poor prognosis and worse survival, and it suggests that this transcription coregulator may play a role in mammary carcinogenesis and represent a novel prognostic marker. Copyright © 2011 American Society for Investigative Pathology. Published by Elsevier Inc. All rights reserved.
Barbolina, Maria V; Adley, Brian P; Kelly, David L; Shepard, Jaclyn; Fought, Angela J; Scholtens, Denise; Penzes, Peter; Shea, Lonnie D; Stack, M Sharon
2009-08-15
Epithelial ovarian carcinoma (EOC) is a leading cause of death from gynecologic malignancies, due mainly to the prevalence of undetected metastatic disease. The process of cell invasion during intraperitoneal anchoring of metastatic lesions requires concerted regulation of many processes, including modulation of adhesion to the extracellular matrix and localized invasion. Exploratory cDNA microarray analysis of early response genes (altered after 4 hr of 3D collagen culture) coupled with confirmatory real-time reverse-transcriptase polymerase chain reaction, multiple 3D cell culture matrices, Western blot, immunostaining, adhesion, migration and invasion assays were used to identify modulators of adhesion pertinent to EOC progression and metastasis. cDNA microarray analysis indicated a dramatic downregulation of connective tissue growth factor (CTGF) in EOC cells placed in invasion- mimicking conditions (3D Type I collagen). Examination of human EOC specimens revealed that CTGF expression was absent in 46% of the tested samples (n = 41), but was present in 100% of normal ovarian epithelium samples (n = 7). Reduced CTGF expression occurs in many types of cells and may be a general phenomenon displayed by cells encountering a 3D environment. CTGF levels were inversely correlated with invasion such that downregulation of CTGF increased, while its upregulation reduced collagen invasion. Cells adhered preferentially to a surface comprised of both collagen I and CTGF relative to either component alone using alpha6beta1 and alpha3beta1 integrins. Together these data suggest that downregulation of CTGF in EOC cells may be important for cell invasion through modulation of cell-matrix adhesion.
Barbolina, Maria V.; Adley, Brian P.; Kelly, David L.; Shepard, Jaclyn; Fought, Angela J.; Scholtens, Denise; Penzes, Peter; Shea, Lonnie D.; Sharon Stack, M
2010-01-01
Epithelial ovarian carcinoma (EOC) is a leading cause of death from gynecologic malignancy, due mainly to the prevalence of undetected metastatic disease. The process of cell invasion during intra-peritoneal anchoring of metastatic lesions requires concerted regulation of many processes, including modulation of adhesion to the extracellular matrix and localized invasion. Exploratory cDNA microarray analysis of early response genes (altered after 4 hours of 3-dimensional collagen culture) coupled with confirmatory real-time RT-PCR, multiple three-dimensional cell culture matrices, Western blot, immunostaining, adhesion, migration, and invasion assays were used to identify modulators of adhesion pertinent to EOC progression and metastasis. cDNA microarray analysis indicated a dramatic downregulation of connective tissue growth factor (CTGF) in EOC cells placed in invasion-mimicking conditions (3-dimensional type I collagen). Examination of human EOC specimens revealed that CTGF expression was absent in 46% of the tested samples (n=41), but was present in 100% of normal ovarian epithelium samples (n=7). Reduced CTGF expression occurs in many types of cells and may be a general phenomenon displayed by cells encountering a 3D environment. CTGF levels were inversely correlated with invasion such that downregulation of CTGF increased, while its upregulation reduced, collagen invasion. Cells adhered preferentially to a surface comprised of both collagen I and CTGF relative to either component alone using α6β1 and α3β1 integrins. Together these data suggest that downregulation of CTGF in EOC cells may be important for cell invasion through modulation of cell-matrix adhesion. PMID:19382180
MSL: A Measure to Evaluate Three-dimensional Patterns in Gene Expression Data
Gutiérrez-Avilés, David; Rubio-Escudero, Cristina
2015-01-01
Microarray technology is highly used in biological research environments due to its ability to monitor the RNA concentration levels. The analysis of the data generated represents a computational challenge due to the characteristics of these data. Clustering techniques are widely applied to create groups of genes that exhibit a similar behavior. Biclustering relaxes the constraints for grouping, allowing genes to be evaluated only under a subset of the conditions. Triclustering appears for the analysis of longitudinal experiments in which the genes are evaluated under certain conditions at several time points. These triclusters provide hidden information in the form of behavior patterns from temporal experiments with microarrays relating subsets of genes, experimental conditions, and time points. We present an evaluation measure for triclusters called Multi Slope Measure, based on the similarity among the angles of the slopes formed by each profile formed by the genes, conditions, and times of the tricluster. PMID:26124630
Szcześniak, Katarzyna A; Ciecierska, Anna; Ostaszewski, Piotr; Sadkowski, Tomasz
2016-10-01
β-Hydroxy-β-methylbutyrate (HMB) is a popular ergogenic aid used by human athletes and as a supplement to sport horses, because of its ability to aid muscle recovery, improve performance and body composition. Recent findings suggest that HMB may stimulate satellite cells and affect expressions of genes regulating skeletal muscle cell growth. Despite the scientific data showing benefits of HMB supplementation in horses, no previous study has explained the mechanism of action of HMB in this species. The aim of this study was to reveal the molecular background of HMB action on equine skeletal muscle by investigating the transcriptomic profile changes induced by HMB in equine satellite cells in vitro. Upon isolation from the semitendinosus muscle, equine satellite cells were cultured until the 2nd day of differentiation. Differentiating cells were incubated with HMB for 24 h. Total cellular RNA was isolated, amplified, labelled and hybridised to microarray slides. Microarray data validation was performed with real-time quantitative PCR. HMB induced differential expressions of 361 genes. Functional analysis revealed that the main biological processes influenced by HMB in equine satellite cells were related to muscle organ development, protein metabolism, energy homoeostasis and lipid metabolism. In conclusion, this study demonstrated for the first time that HMB has the potential to influence equine satellite cells by controlling global gene expression. Genes and biological processes targeted by HMB in equine satellite cells may support HMB utility in improving growth and regeneration of equine skeletal muscle; however, the overall role of HMB in horses remains equivocal and requires further proteomic, biochemical and pharmacokinetic studies.
Nie, Zhiyi; Kang, Guijuan; Duan, Cuifang; Li, Yu; Dai, Longjun; Zeng, Rizhong
2016-01-01
Ethylene is commonly used as a latex stimulant of Hevea brasiliensis by application of ethephon (chloro-2-ethylphosphonic acid); however, the molecular mechanism by which ethylene increases latex production is not clear. To better understand the effects of ethylene stimulation on the laticiferous cells of rubber trees, a latex expressed sequence tag (EST)-based complementary DNA microarray containing 2,973 unique genes (probes) was first developed and used to analyze the gene expression changes in the latex of the mature virgin rubber trees after ethephon treatment at three different time-points: 8, 24 and 48 h. Transcript levels of 163 genes were significantly altered with fold-change values ≥ 2 or ≤ –2 (q-value < 0.05) in ethephon-treated rubber trees compared with control trees. Of the 163 genes, 92 were up-regulated and 71 down-regulated. The microarray results were further confirmed using real-time quantitative reverse transcript-PCR for 20 selected genes. The 163 ethylene-responsive genes were involved in several biological processes including organic substance metabolism, cellular metabolism, primary metabolism, biosynthetic process, cellular response to stimulus and stress. The presented data suggest that the laticifer water circulation, production and scavenging of reactive oxygen species, sugar metabolism, and assembly and depolymerization of the latex actin cytoskeleton might play important roles in ethylene-induced increase of latex production. The results may provide useful insights into understanding the molecular mechanism underlying the effect of ethylene on latex metabolism of H. brasiliensis. PMID:26985821
Genomic Approach to Study Floral Development Genes in Rosa sp.
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
Constitutional downregulation of SEMA5A expression in autism.
Melin, M; Carlsson, B; Anckarsater, H; Rastam, M; Betancur, C; Isaksson, A; Gillberg, C; Dahl, N
2006-01-01
There is strong evidence for the importance of genetic factors in idiopathic autism. The results from independent twin and family studies suggest that the disorder is caused by the action of several genes, possibly acting epistatically. We have used cDNA microarray technology for the identification of constitutional changes in the gene expression profile associated with idiopathic autism. Samples were obtained and analyzed from 6 affected subjects belonging to multiplex autism families and from 6 healthy controls. We assessed the expression levels for approximately 7,700 genes by cDNA microarrays using mRNA derived from Epstein-Barr virus-transformed B lymphocytes. The microarray data were analyzed in order to identify up- or downregulation of specific genes. A common pattern with nine downregulated genes was identified among samples derived from individuals with autism when compared to controls. Four of these nine genes encode proteins involved in biological processes associated with brain function or the immune system, and are consequently considered as candidates for genes associated with autism. Quantitative real-time PCR confirms the downregulation of the gene encoding SEMA5A, a protein involved in axonal guidance. Epstein-Barr virus should be considered as a possible source for altered expression, but our consistent results make us suggest SEMA5A as a candidate gene in the etiology of idiopathic autism.
ArrayNinja: An Open Source Platform for Unified Planning and Analysis of Microarray Experiments.
Dickson, B M; Cornett, E M; Ramjan, Z; Rothbart, S B
2016-01-01
Microarray-based proteomic platforms have emerged as valuable tools for studying various aspects of protein function, particularly in the field of chromatin biochemistry. Microarray technology itself is largely unrestricted in regard to printable material and platform design, and efficient multidimensional optimization of assay parameters requires fluidity in the design and analysis of custom print layouts. This motivates the need for streamlined software infrastructure that facilitates the combined planning and analysis of custom microarray experiments. To this end, we have developed ArrayNinja as a portable, open source, and interactive application that unifies the planning and visualization of microarray experiments and provides maximum flexibility to end users. Array experiments can be planned, stored to a private database, and merged with the imaged results for a level of data interaction and centralization that is not currently attainable with available microarray informatics tools. © 2016 Elsevier Inc. All rights reserved.
WebArray: an online platform for microarray data analysis
Xia, Xiaoqin; McClelland, Michael; Wang, Yipeng
2005-01-01
Background Many cutting-edge microarray analysis tools and algorithms, including commonly used limma and affy packages in Bioconductor, need sophisticated knowledge of mathematics, statistics and computer skills for implementation. Commercially available software can provide a user-friendly interface at considerable cost. To facilitate the use of these tools for microarray data analysis on an open platform we developed an online microarray data analysis platform, WebArray, for bench biologists to utilize these tools to explore data from single/dual color microarray experiments. Results The currently implemented functions were based on limma and affy package from Bioconductor, the spacings LOESS histogram (SPLOSH) method, PCA-assisted normalization method and genome mapping method. WebArray incorporates these packages and provides a user-friendly interface for accessing a wide range of key functions of limma and others, such as spot quality weight, background correction, graphical plotting, normalization, linear modeling, empirical bayes statistical analysis, false discovery rate (FDR) estimation, chromosomal mapping for genome comparison. Conclusion WebArray offers a convenient platform for bench biologists to access several cutting-edge microarray data analysis tools. The website is freely available at . It runs on a Linux server with Apache and MySQL. PMID:16371165
Teste, Marie-Ange; Duquenne, Manon; François, Jean M; Parrou, Jean-Luc
2009-01-01
Background Real-time RT-PCR is the recommended method for quantitative gene expression analysis. A compulsory step is the selection of good reference genes for normalization. A few genes often referred to as HouseKeeping Genes (HSK), such as ACT1, RDN18 or PDA1 are among the most commonly used, as their expression is assumed to remain unchanged over a wide range of conditions. Since this assumption is very unlikely, a geometric averaging of multiple, carefully selected internal control genes is now strongly recommended for normalization to avoid this problem of expression variation of single reference genes. The aim of this work was to search for a set of reference genes for reliable gene expression analysis in Saccharomyces cerevisiae. Results From public microarray datasets, we selected potential reference genes whose expression remained apparently invariable during long-term growth on glucose. Using the algorithm geNorm, ALG9, TAF10, TFC1 and UBC6 turned out to be genes whose expression remained stable, independent of the growth conditions and the strain backgrounds tested in this study. We then showed that the geometric averaging of any subset of three genes among the six most stable genes resulted in very similar normalized data, which contrasted with inconsistent results among various biological samples when the normalization was performed with ACT1. Normalization with multiple selected genes was therefore applied to transcriptional analysis of genes involved in glycogen metabolism. We determined an induction ratio of 100-fold for GPH1 and 20-fold for GSY2 between the exponential phase and the diauxic shift on glucose. There was no induction of these two genes at this transition phase on galactose, although in both cases, the kinetics of glycogen accumulation was similar. In contrast, SGA1 expression was independent of the carbon source and increased by 3-fold in stationary phase. Conclusion In this work, we provided a set of genes that are suitable reference genes for quantitative gene expression analysis by real-time RT-PCR in yeast biological samples covering a large panel of physiological states. In contrast, we invalidated and discourage the use of ACT1 as well as other commonly used reference genes (PDA1, TDH3, RDN18, etc) as internal controls for quantitative gene expression analysis in yeast. PMID:19874630
Teste, Marie-Ange; Duquenne, Manon; François, Jean M; Parrou, Jean-Luc
2009-10-30
Real-time RT-PCR is the recommended method for quantitative gene expression analysis. A compulsory step is the selection of good reference genes for normalization. A few genes often referred to as HouseKeeping Genes (HSK), such as ACT1, RDN18 or PDA1 are among the most commonly used, as their expression is assumed to remain unchanged over a wide range of conditions. Since this assumption is very unlikely, a geometric averaging of multiple, carefully selected internal control genes is now strongly recommended for normalization to avoid this problem of expression variation of single reference genes. The aim of this work was to search for a set of reference genes for reliable gene expression analysis in Saccharomyces cerevisiae. From public microarray datasets, we selected potential reference genes whose expression remained apparently invariable during long-term growth on glucose. Using the algorithm geNorm, ALG9, TAF10, TFC1 and UBC6 turned out to be genes whose expression remained stable, independent of the growth conditions and the strain backgrounds tested in this study. We then showed that the geometric averaging of any subset of three genes among the six most stable genes resulted in very similar normalized data, which contrasted with inconsistent results among various biological samples when the normalization was performed with ACT1. Normalization with multiple selected genes was therefore applied to transcriptional analysis of genes involved in glycogen metabolism. We determined an induction ratio of 100-fold for GPH1 and 20-fold for GSY2 between the exponential phase and the diauxic shift on glucose. There was no induction of these two genes at this transition phase on galactose, although in both cases, the kinetics of glycogen accumulation was similar. In contrast, SGA1 expression was independent of the carbon source and increased by 3-fold in stationary phase. In this work, we provided a set of genes that are suitable reference genes for quantitative gene expression analysis by real-time RT-PCR in yeast biological samples covering a large panel of physiological states. In contrast, we invalidated and discourage the use of ACT1 as well as other commonly used reference genes (PDA1, TDH3, RDN18, etc) as internal controls for quantitative gene expression analysis in yeast.
Flechner, Stuart M.; Kurian, Sunil M.; Head, Steven R.; Sharp, Starlette M.; Whisenant, Thomas C.; Zhang, Jie; Chismar, Jeffrey D.; Horvath, Steve; Mondala, Tony; Gilmartin, Timothy; Cook, Daniel J.; Kay, Steven A.; Walker, John R.; Salomon, Daniel R.
2007-01-01
A major challenge for kidney transplantation is balancing the need for immunosuppression to prevent rejection, while minimizing drug-induced toxicities. We used DNA microarrays (HG-U95Av2 GeneChips, Affymetrix) to determine gene expression profiles for kidney biopsies and peripheral blood lymphocytes (PBLs) in transplant patients including normal donor kidneys, well-functioning transplants without rejection, kidneys undergoing acute rejection, and transplants with renal dysfunction without rejection. We developed a data analysis schema based on expression signal determination, class comparison and prediction, hierarchical clustering, statistical power analysis and real-time quantitative PCR validation. We identified distinct gene expression signatures for both biopsies and PBLs that correlated significantly with each of the different classes of transplant patients. This is the most complete report to date using commercial arrays to identify unique expression signatures in transplant biopsies distinguishing acute rejection, acute dysfunction without rejection and well-functioning transplants with no rejection history. We demonstrate for the first time the successful application of high density DNA chip analysis of PBL as a diagnostic tool for transplantation. The significance of these results, if validated in a multicenter prospective trial, would be the establishment of a metric based on gene expression signatures for monitoring the immune status and immunosuppression of transplanted patients. PMID:15307835
Huang, Jinguang; Zheng, Chengchao
2013-01-01
RNA helicases are enzymes that are thought to unwind double-stranded RNA molecules in an energy-dependent fashion through the hydrolysis of NTP. RNA helicases are associated with all processes involving RNA molecules, including nuclear transcription, editing, splicing, ribosome biogenesis, RNA export, and organelle gene expression. The involvement of RNA helicase in response to stress and in plant growth and development has been reported previously. While their importance in Arabidopsis and Oryza sativa has been partially studied, the function of RNA helicase proteins is poorly understood in Zea mays and Glycine max. In this study, we identified a total of RNA helicase genes in Arabidopsis and other crop species genome by genome-wide comparative in silico analysis. We classified the RNA helicase genes into three subfamilies according to the structural features of the motif II region, such as DEAD-box, DEAH-box and DExD/H-box, and different species showed different patterns of alternative splicing. Secondly, chromosome location analysis showed that the RNA helicase protein genes were distributed across all chromosomes with different densities in the four species. Thirdly, phylogenetic tree analyses identified the relevant homologs of DEAD-box, DEAH-box and DExD/H-box RNA helicase proteins in each of the four species. Fourthly, microarray expression data showed that many of these predicted RNA helicase genes were expressed in different developmental stages and different tissues under normal growth conditions. Finally, real-time quantitative PCR analysis showed that the expression levels of 10 genes in Arabidopsis and 13 genes in Zea mays were in close agreement with the microarray expression data. To our knowledge, this is the first report of a comparative genome-wide analysis of the RNA helicase gene family in Arabidopsis, Oryza sativa, Zea mays and Glycine max. This study provides valuable information for understanding the classification and putative functions of the RNA helicase gene family in crop growth and development. PMID:24265739
Xu, Ruirui; Zhang, Shizhong; Huang, Jinguang; Zheng, Chengchao
2013-01-01
RNA helicases are enzymes that are thought to unwind double-stranded RNA molecules in an energy-dependent fashion through the hydrolysis of NTP. RNA helicases are associated with all processes involving RNA molecules, including nuclear transcription, editing, splicing, ribosome biogenesis, RNA export, and organelle gene expression. The involvement of RNA helicase in response to stress and in plant growth and development has been reported previously. While their importance in Arabidopsis and Oryza sativa has been partially studied, the function of RNA helicase proteins is poorly understood in Zea mays and Glycine max. In this study, we identified a total of RNA helicase genes in Arabidopsis and other crop species genome by genome-wide comparative in silico analysis. We classified the RNA helicase genes into three subfamilies according to the structural features of the motif II region, such as DEAD-box, DEAH-box and DExD/H-box, and different species showed different patterns of alternative splicing. Secondly, chromosome location analysis showed that the RNA helicase protein genes were distributed across all chromosomes with different densities in the four species. Thirdly, phylogenetic tree analyses identified the relevant homologs of DEAD-box, DEAH-box and DExD/H-box RNA helicase proteins in each of the four species. Fourthly, microarray expression data showed that many of these predicted RNA helicase genes were expressed in different developmental stages and different tissues under normal growth conditions. Finally, real-time quantitative PCR analysis showed that the expression levels of 10 genes in Arabidopsis and 13 genes in Zea mays were in close agreement with the microarray expression data. To our knowledge, this is the first report of a comparative genome-wide analysis of the RNA helicase gene family in Arabidopsis, Oryza sativa, Zea mays and Glycine max. This study provides valuable information for understanding the classification and putative functions of the RNA helicase gene family in crop growth and development.
DNA Microarray Data Analysis: A Novel Biclustering Algorithm Approach
NASA Astrophysics Data System (ADS)
Tchagang, Alain B.; Tewfik, Ahmed H.
2006-12-01
Biclustering algorithms refer to a distinct class of clustering algorithms that perform simultaneous row-column clustering. Biclustering problems arise in DNA microarray data analysis, collaborative filtering, market research, information retrieval, text mining, electoral trends, exchange analysis, and so forth. When dealing with DNA microarray experimental data for example, the goal of biclustering algorithms is to find submatrices, that is, subgroups of genes and subgroups of conditions, where the genes exhibit highly correlated activities for every condition. In this study, we develop novel biclustering algorithms using basic linear algebra and arithmetic tools. The proposed biclustering algorithms can be used to search for all biclusters with constant values, biclusters with constant values on rows, biclusters with constant values on columns, and biclusters with coherent values from a set of data in a timely manner and without solving any optimization problem. We also show how one of the proposed biclustering algorithms can be adapted to identify biclusters with coherent evolution. The algorithms developed in this study discover all valid biclusters of each type, while almost all previous biclustering approaches will miss some.
Luan, Enxiao; Zheng, Zhaozhu; Li, Xinyu; Gu, Hongxi; Liu, Shaoqin
2016-04-15
We present a facile fabrication of layer-by-layer (LbL) microarrays of quantum dots (QDs) and acetylcholinesterase enzyme (AChE). The resulting arrays had several unique properties, such as low cost, high integration and excellent flexibility and time-saving. The presence of organophosphorous pesticides (OPs) can inhibit the AChE activity and thus changes the fluorescent intensity of QDs/AChE microscopic dot arrays. Therefore, the QDs/AChE microscopic dot arrays were used for the sensitive visual detection of OPs. Linear calibration for parathion and paraoxon was obtained in the range of 5-100 μg L(-1) under the optimized conditions with the limit of detection (LOD) of 10 μg L(-1). The arrays have been successfully used for detection of OPs in fruits and water real samples. The new array was validated by comparison with conventional high performance liquid chromatography-mass spectrometry (HPLC-MS). Copyright © 2016 Elsevier B.V. All rights reserved.
Denou, Emmanuel; Pridmore, Raymond David; Berger, Bernard; Panoff, Jean-Michel; Arigoni, Fabrizio; Brüssow, Harald
2008-05-01
Lactobacillus johnsonii strains NCC533 and ATCC 33200 (the type strain of this species) differed significantly in gut residence time (12 versus 5 days) after oral feeding to mice. Genes affecting the long gut residence time of the probiotic strain NCC533 were targeted for analysis. We hypothesized that genes specific for this strain, which are expressed during passage of the bacterium through the gut, affect the phenotype. When the DNA of the type strain was hybridized against a microarray of the sequenced NCC533 strain, we identified 233 genes that were specific for the long-gut-persistence isolate. Whole-genome transcription analysis of the NCC533 strain using the microarray format identified 174 genes that were strongly and consistently expressed in the jejunum of mice monocolonized with this strain. Fusion of the two microarray data sets identified three gene loci that were both expressed in vivo and specific to the long-gut-persistence isolate. The identified genes included LJ1027 and LJ1028, two glycosyltransferase genes in the exopolysaccharide synthesis operon; LJ1654 to LJ1656, encoding a sugar phosphotransferase system (PTS) transporter annotated as mannose PTS; and LJ1680, whose product shares 30% amino acid identity with immunoglobulin A proteases from pathogenic bacteria. Knockout mutants were tested in vivo. The experiments revealed that deletion of LJ1654 to LJ1656 and LJ1680 decreased the gut residence time, while a mutant with a deleted exopolysaccharide biosynthesis cluster had a slightly increased residence time.
Gardiner, Erin J; Cairns, Murray J; Liu, Bing; Beveridge, Natalie J; Carr, Vaughan; Kelly, Brian; Scott, Rodney J; Tooney, Paul A
2013-04-01
Peripheral blood mononuclear cells (PBMCs) represent an accessible tissue source for gene expression profiling in schizophrenia that could provide insight into the molecular basis of the disorder. This study used the Illumina HT_12 microarray platform and quantitative real time PCR (QPCR) to perform mRNA expression profiling on 114 patients with schizophrenia or schizoaffective disorder and 80 non-psychiatric controls from the Australian Schizophrenia Research Bank (ASRB). Differential expression analysis revealed altered expression of 164 genes (59 up-regulated and 105 down-regulated) in the PBMCs from patients with schizophrenia compared to controls. Bioinformatic analysis indicated significant enrichment of differentially expressed genes known to be involved or associated with immune function and regulating the immune response. The differential expression of 6 genes, EIF2C2 (Ago 2), MEF2D, EVL, PI3, S100A12 and DEFA4 was confirmed by QPCR. Genome-wide expression analysis of PBMCs from individuals with schizophrenia was characterized by the alteration of genes with immune system function, supporting the hypothesis that the disorder has a significant immunological component in its etiology. Copyright © 2012 Elsevier Ltd. All rights reserved.
Choi, Bosung; Ghosh, Ritesh; Gururani, Mayank Anand; Shanmugam, Gnanendra; Jeon, Junhyun; Kim, Jonggeun; Park, Soo-Chul; Jeong, Mi-Jeong; Han, Kyung-Hwan; Bae, Dong-Won; Bae, Hanhong
2017-05-30
Sound vibration (SV), a mechanical stimulus, can trigger various molecular and physiological changes in plants like gene expression, hormonal modulation, induced antioxidant activity and calcium spiking. It also alters the seed germination and growth of plants. In this study, we investigated the effects of SV on the resistance of Arabidopsis thaliana against Botrytis cinerea infection. The microarray analysis was performed on infected Arabidopsis plants pre-exposed to SV of 1000 Hertz with 100 decibels. Broadly, the transcriptomic analysis revealed up-regulation of several defense and SA-responsive and/or signaling genes. Quantitative real-time PCR (qRT-PCR) analysis of selected genes also validated the induction of SA-mediated response in the infected Arabidopsis plants pre-exposed to SV. Corroboratively, hormonal analysis identified the increased concentration of salicylic acid (SA) in the SV-treated plants after pathogen inoculation. In contrast, jasmonic acid (JA) level in the SV-treated plants remained stable but lower than control plants during the infection. Based on these findings, we propose that SV treatment invigorates the plant defense system by regulating the SA-mediated priming effect, consequently promoting the SV-induced resistance in Arabidopsis against B. cinerea.
USDA-ARS?s Scientific Manuscript database
RNA expression analysis was performed on the corpus luteum tissue at five time points after prostaglandin F2 alpha treatment of midcycle cows using an Affymetrix Bovine Gene v1 Array. The normalized linear microarray data was uploaded to the NCBI GEO repository (GSE94069). Subsequent statistical ana...
Issues in the analysis of oligonucleotide tiling microarrays for transcript mapping
NASA Technical Reports Server (NTRS)
Royce, Thomas E.; Rozowsky, Joel S.; Bertone, Paul; Samanta, Manoj; Stolc, Viktor; Weissman, Sherman; Snyder, Michael; Gerstein, Mark
2005-01-01
Traditional microarrays use probes complementary to known genes to quantitate the differential gene expression between two or more conditions. Genomic tiling microarray experiments differ in that probes that span a genomic region at regular intervals are used to detect the presence or absence of transcription. This difference means the same sets of biases and the methods for addressing them are unlikely to be relevant to both types of experiment. We introduce the informatics challenges arising in the analysis of tiling microarray experiments as open problems to the scientific community and present initial approaches for the analysis of this nascent technology.
Hinchliffe, Doug J; Meredith, William R; Yeater, Kathleen M; Kim, Hee Jin; Woodward, Andrew W; Chen, Z Jeffrey; Triplett, Barbara A
2010-05-01
Gene expression profiles of developing cotton (Gossypium hirsutum L.) fibers from two near-isogenic lines (NILs) that differ in fiber-bundle strength, short-fiber content, and in fewer than two genetic loci were compared using an oligonucleotide microarray. Fiber gene expression was compared at five time points spanning fiber elongation and secondary cell wall (SCW) biosynthesis. Fiber samples were collected from field plots in a randomized, complete block design, with three spatially distinct biological replications for each NIL at each time point. Microarray hybridizations were performed in a loop experimental design that allowed comparisons of fiber gene expression profiles as a function of time between the two NILs. Overall, developmental expression patterns revealed by the microarray experiment agreed with previously reported cotton fiber gene expression patterns for specific genes. Additionally, genes expressed coordinately with the onset of SCW biosynthesis in cotton fiber correlated with gene expression patterns of other SCW-producing plant tissues. Functional classification and enrichment analysis of differentially expressed genes between the two NILs revealed that genes associated with SCW biosynthesis were significantly up-regulated in fibers of the high-fiber quality line at the transition stage of cotton fiber development. For independent corroboration of the microarray results, 15 genes were selected for quantitative reverse transcription PCR analysis of fiber gene expression. These analyses, conducted over multiple field years, confirmed the temporal difference in fiber gene expression between the two NILs. We hypothesize that the loci conferring temporal differences in fiber gene expression between the NILs are important regulatory sequences that offer the potential for more targeted manipulation of cotton fiber quality.
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
Karyotype versus microarray testing for genetic abnormalities after stillbirth.
Reddy, Uma M; Page, Grier P; Saade, George R; Silver, Robert M; Thorsten, Vanessa R; Parker, Corette B; Pinar, Halit; Willinger, Marian; Stoll, Barbara J; Heim-Hall, Josefine; Varner, Michael W; Goldenberg, Robert L; Bukowski, Radek; Wapner, Ronald J; Drews-Botsch, Carolyn D; O'Brien, Barbara M; Dudley, Donald J; Levy, Brynn
2012-12-06
Genetic abnormalities have been associated with 6 to 13% of stillbirths, but the true prevalence may be higher. Unlike karyotype analysis, microarray analysis does not require live cells, and it detects small deletions and duplications called copy-number variants. The Stillbirth Collaborative Research Network conducted a population-based study of stillbirth in five geographic catchment areas. Standardized postmortem examinations and karyotype analyses were performed. A single-nucleotide polymorphism array was used to detect copy-number variants of at least 500 kb in placental or fetal tissue. Variants that were not identified in any of three databases of apparently unaffected persons were then classified into three groups: probably benign, clinical significance unknown, or pathogenic. We compared the results of karyotype and microarray analyses of samples obtained after delivery. In our analysis of samples from 532 stillbirths, microarray analysis yielded results more often than did karyotype analysis (87.4% vs. 70.5%, P<0.001) and provided better detection of genetic abnormalities (aneuploidy or pathogenic copy-number variants, 8.3% vs. 5.8%; P=0.007). Microarray analysis also identified more genetic abnormalities among 443 antepartum stillbirths (8.8% vs. 6.5%, P=0.02) and 67 stillbirths with congenital anomalies (29.9% vs. 19.4%, P=0.008). As compared with karyotype analysis, microarray analysis provided a relative increase in the diagnosis of genetic abnormalities of 41.9% in all stillbirths, 34.5% in antepartum stillbirths, and 53.8% in stillbirths with anomalies. Microarray analysis is more likely than karyotype analysis to provide a genetic diagnosis, primarily because of its success with nonviable tissue, and is especially valuable in analyses of stillbirths with congenital anomalies or in cases in which karyotype results cannot be obtained. (Funded by the Eunice Kennedy Shriver National Institute of Child Health and Human Development.).
Novel harmonic regularization approach for variable selection in Cox's proportional hazards model.
Chu, Ge-Jin; Liang, Yong; Wang, Jia-Xuan
2014-01-01
Variable selection is an important issue in regression and a number of variable selection methods have been proposed involving nonconvex penalty functions. In this paper, we investigate a novel harmonic regularization method, which can approximate nonconvex Lq (1/2 < q < 1) regularizations, to select key risk factors in the Cox's proportional hazards model using microarray gene expression data. The harmonic regularization method can be efficiently solved using our proposed direct path seeking approach, which can produce solutions that closely approximate those for the convex loss function and the nonconvex regularization. Simulation results based on the artificial datasets and four real microarray gene expression datasets, such as real diffuse large B-cell lymphoma (DCBCL), the lung cancer, and the AML datasets, show that the harmonic regularization method can be more accurate for variable selection than existing Lasso series methods.
Emerging Use of Gene Expression Microarrays in Plant Physiology
Wullschleger, Stan D.; Difazio, Stephen P.
2003-01-01
Microarrays have become an important technology for the global analysis of gene expression in humans, animals, plants, and microbes. Implemented in the context of a well-designed experiment, cDNA and oligonucleotide arrays can provide highthroughput, simultaneous analysis of transcript abundance for hundreds, if not thousands, of genes. However, despite widespread acceptance, the use of microarrays as a tool to better understand processes of interest to the plant physiologist is still being explored. To help illustrate current uses of microarrays in the plant sciences, several case studies that we believe demonstrate the emerging application of gene expression arrays in plant physiology weremore » selected from among the many posters and presentations at the 2003 Plant and Animal Genome XI Conference. Based on this survey, microarrays are being used to assess gene expression in plants exposed to the experimental manipulation of air temperature, soil water content and aluminium concentration in the root zone. Analysis often includes characterizing transcript profiles for multiple post-treatment sampling periods and categorizing genes with common patterns of response using hierarchical clustering techniques. In addition, microarrays are also providing insights into developmental changes in gene expression associated with fibre and root elongation in cotton and maize, respectively. Technical and analytical limitations of microarrays are discussed and projects attempting to advance areas of microarray design and data analysis are highlighted. Finally, although much work remains, we conclude that microarrays are a valuable tool for the plant physiologist interested in the characterization and identification of individual genes and gene families with potential application in the fields of agriculture, horticulture and forestry.« less
Li, Shicheng; Sun, Xiao; Miao, Shuncheng; Liu, Jia; Jiao, Wenjie
2017-11-01
Cigarette smoking is one of the greatest preventable risk factors for developing cancer, and most cases of lung squamous cell carcinoma (lung SCC) are associated with smoking. The pathogenesis mechanism of tumor progress is unclear. This study aimed to identify biomarkers in smoking-related lung cancer, including protein-coding gene, long noncoding RNA, and transcription factors. We selected and obtained messenger RNA microarray datasets and clinical data from the Gene Expression Omnibus database to identify gene expression altered by cigarette smoking. Integrated bioinformatic analysis was used to clarify biological functions of the identified genes, including Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway, the construction of a protein-protein interaction network, transcription factor, and statistical analyses. Subsequent quantitative real-time PCR was utilized to verify these bioinformatic analyses. Five hundred and ninety-eight differentially expressed genes and 21 long noncoding RNA were identified in smoking-related lung SCC. GO and KEGG pathway analysis showed that identified genes were enriched in the cancer-related functions and pathways. The protein-protein interaction network revealed seven hub genes identified in lung SCC. Several transcription factors and their binding sites were predicted. The results of real-time quantitative PCR revealed that AURKA and BIRC5 were significantly upregulated and LINC00094 was downregulated in the tumor tissues of smoking patients. Further statistical analysis indicated that dysregulation of AURKA, BIRC5, and LINC00094 indicated poor prognosis in lung SCC. Protein-coding genes AURKA, BIRC5, and LINC00094 could be biomarkers or therapeutic targets for smoking-related lung SCC. © 2017 The Authors. Thoracic Cancer published by China Lung Oncology Group and John Wiley & Sons Australia, Ltd.
Helicobacter pylori HP1512 Is a Nickel-Responsive NikR-Regulated Outer Membrane Protein▿
Davis, Gregg S.; Flannery, Erika L.; Mobley, Harry L. T.
2006-01-01
Helicobacter pylori is dependent upon the production of the highly abundant and active metalloenzyme urease for colonization of the human stomach. Thus, H. pylori has an absolute requirement for the transition metal nickel, a required cofactor for urease. To investigate the contribution of genes that are factors in this process, microarray analysis comparing the transcriptome of wild-type H. pylori 26695 cultured in brucella broth containing fetal calf serum (BBF) alone or supplemented with 100 μM NiCl2 suggested that HP1512 is repressed in the presence of 100 μM supplemental nickel. When measured by comparative real-time quantitative PCR (qPCR), HP1512 transcription was reduced 43-fold relative to the value for the wild type when cultured in BBF supplemented with 10 μM NiCl2. When grown in unsupplemented BBF, urease activity of an HP1512::cat mutant was significantly reduced compared to the wild type, 4.9 ± 0.5 μmol/min/mg of protein (n = 7) and 17.1 ± 4.9 μmol/min/mg of protein (n = 13), respectively (P < 0.0001). In silico analysis of the HP1511-HP1512 (HP1511-1512) intergenic region identified a putative NikR operator upstream of HP1512. Gel shift analysis with purified recombinant NikR verified nickel-dependent binding of H. pylori NikR to the HP1511-1512 intergenic region. Furthermore, comparative real-time qPCR of four nickel-related genes suggests that mutation of HP1512 results in reduced intracellular nickel concentration relative to wild-type H. pylori 26695. Taken together, these data suggest that HP1512 encodes a NikR-nickel-regulated outer membrane protein. PMID:17030579
NASA Astrophysics Data System (ADS)
Fengler, Svenja; Spirer, Ina; Neef, Maren; Ecke, Margret; Hauslage, Jens; Hampp, Rüdiger
2016-06-01
Cell cultures of the plant model organism Arabidopsis thaliana were exposed to partial- g forces during parabolic flight and clinostat experiments (0.16 g, 0.38 g and 0.5 g were tested). In order to investigate gravity-dependent alterations in gene expression, samples were metabolically quenched by the fixative RNA later Ⓡ to stabilize nucleic acids and used for whole-genome microarray analysis. An attempt to identify the potential threshold acceleration for the gravity-dependent response showed that the smaller the experienced g-force, the greater was the susceptibility of the cell cultures. Compared to short-term μ g during a parabolic flight, the number of differentially expressed genes under partial- g was lower. In addition, the effect on the alteration of amounts of transcripts decreased during partial- g parabolic flight due to the sequence of the different parabolas (0.38 g, 0.16 g and μ g). A time-dependent analysis under simulated 0.5 g indicates that adaptation occurs within minutes. Differentially expressed genes (at least 2-fold up- or down-regulated in expression) under real flight conditions were to some extent identical with those affected by clinorotation. The highest number of homologuous genes was detected within seconds of exposure to 0.38 g (both flight and clinorotation). To a considerable part, these genes deal with cell wall properties. Additionally, responses specific for clinorotation were observed.
Derivation of an artificial gene to improve classification accuracy upon gene selection.
Seo, Minseok; Oh, Sejong
2012-02-01
Classification analysis has been developed continuously since 1936. This research field has advanced as a result of development of classifiers such as KNN, ANN, and SVM, as well as through data preprocessing areas. Feature (gene) selection is required for very high dimensional data such as microarray before classification work. The goal of feature selection is to choose a subset of informative features that reduces processing time and provides higher classification accuracy. In this study, we devised a method of artificial gene making (AGM) for microarray data to improve classification accuracy. Our artificial gene was derived from a whole microarray dataset, and combined with a result of gene selection for classification analysis. We experimentally confirmed a clear improvement of classification accuracy after inserting artificial gene. Our artificial gene worked well for popular feature (gene) selection algorithms and classifiers. The proposed approach can be applied to any type of high dimensional dataset. Copyright © 2011 Elsevier Ltd. All rights reserved.
Lee, SangWook; Lee, Jong Hyun; Kwon, Hyuck Gi; Laurell, Thomas; Jeong, Ok Chan; Kim, Soyoun
2018-01-01
Here, we report a sol-gel integrated affinity microarray for on-chip matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF-MS) that enables capture and identification of prostate?specific antigen (PSA) in samples. An anti-PSA antibody (H117) was mixed with a sol?gel, and the mixture was spotted onto a porous silicon (pSi) surface without additional surface modifications. The antibody easily penetrates the sol-gel macropore fluidic network structure, making possible high affinities. To assess the capture affinity of the platform, we performed a direct assay using fluorescein isothiocyanate-labeled PSA. Pure PSA was subjected to on-chip MALDI-TOF-MS analysis, yielding three clear mass peptide peaks (m/z = 1272, 1407, and 1872). The sol-gel microarray platform enables dual readout of PSA both fluorometric and MALDI-TOF MS analysis in biological samples. Here we report a useful method for a means for discovery of biomarkers in complex body fluids.
A genome-wide 20 K citrus microarray for gene expression analysis
Martinez-Godoy, M Angeles; Mauri, Nuria; Juarez, Jose; Marques, M Carmen; Santiago, Julia; Forment, Javier; Gadea, Jose
2008-01-01
Background Understanding of genetic elements that contribute to key aspects of citrus biology will impact future improvements in this economically important crop. Global gene expression analysis demands microarray platforms with a high genome coverage. In the last years, genome-wide EST collections have been generated in citrus, opening the possibility to create new tools for functional genomics in this crop plant. Results We have designed and constructed a publicly available genome-wide cDNA microarray that include 21,081 putative unigenes of citrus. As a functional companion to the microarray, a web-browsable database [1] was created and populated with information about the unigenes represented in the microarray, including cDNA libraries, isolated clones, raw and processed nucleotide and protein sequences, and results of all the structural and functional annotation of the unigenes, like general description, BLAST hits, putative Arabidopsis orthologs, microsatellites, putative SNPs, GO classification and PFAM domains. We have performed a Gene Ontology comparison with the full set of Arabidopsis proteins to estimate the genome coverage of the microarray. We have also performed microarray hybridizations to check its usability. Conclusion This new cDNA microarray replaces the first 7K microarray generated two years ago and allows gene expression analysis at a more global scale. We have followed a rational design to minimize cross-hybridization while maintaining its utility for different citrus species. Furthermore, we also provide access to a website with full structural and functional annotation of the unigenes represented in the microarray, along with the ability to use this site to directly perform gene expression analysis using standard tools at different publicly available servers. Furthermore, we show how this microarray offers a good representation of the citrus genome and present the usefulness of this genomic tool for global studies in citrus by using it to catalogue genes expressed in citrus globular embryos. PMID:18598343
Chen, Josephine; Zhao, Po; Massaro, Donald; Clerch, Linda B; Almon, Richard R; DuBois, Debra C; Jusko, William J; Hoffman, Eric P
2004-01-01
Publicly accessible DNA databases (genome browsers) are rapidly accelerating post-genomic research (see http://www.genome.ucsc.edu/), with integrated genomic DNA, gene structure, EST/ splicing and cross-species ortholog data. DNA databases have relatively low dimensionality; the genome is a linear code that anchors all associated data. In contrast, RNA expression and protein databases need to be able to handle very high dimensional data, with time, tissue, cell type and genes, as interrelated variables. The high dimensionality of microarray expression profile data, and the lack of a standard experimental platform have complicated the development of web-accessible databases and analytical tools. We have designed and implemented a public resource of expression profile data containing 1024 human, mouse and rat Affymetrix GeneChip expression profiles, generated in the same laboratory, and subject to the same quality and procedural controls (Public Expression Profiling Resource; PEPR). Our Oracle-based PEPR data warehouse includes a novel time series query analysis tool (SGQT), enabling dynamic generation of graphs and spreadsheets showing the action of any transcript of interest over time. In this report, we demonstrate the utility of this tool using a 27 time point, in vivo muscle regeneration series. This data warehouse and associated analysis tools provides access to multidimensional microarray data through web-based interfaces, both for download of all types of raw data for independent analysis, and also for straightforward gene-based queries. Planned implementations of PEPR will include web-based remote entry of projects adhering to quality control and standard operating procedure (QC/SOP) criteria, and automated output of alternative probe set algorithms for each project (see http://microarray.cnmcresearch.org/pgadatatable.asp).
Chen, Josephine; Zhao, Po; Massaro, Donald; Clerch, Linda B.; Almon, Richard R.; DuBois, Debra C.; Jusko, William J.; Hoffman, Eric P.
2004-01-01
Publicly accessible DNA databases (genome browsers) are rapidly accelerating post-genomic research (see http://www.genome.ucsc.edu/), with integrated genomic DNA, gene structure, EST/ splicing and cross-species ortholog data. DNA databases have relatively low dimensionality; the genome is a linear code that anchors all associated data. In contrast, RNA expression and protein databases need to be able to handle very high dimensional data, with time, tissue, cell type and genes, as interrelated variables. The high dimensionality of microarray expression profile data, and the lack of a standard experimental platform have complicated the development of web-accessible databases and analytical tools. We have designed and implemented a public resource of expression profile data containing 1024 human, mouse and rat Affymetrix GeneChip expression profiles, generated in the same laboratory, and subject to the same quality and procedural controls (Public Expression Profiling Resource; PEPR). Our Oracle-based PEPR data warehouse includes a novel time series query analysis tool (SGQT), enabling dynamic generation of graphs and spreadsheets showing the action of any transcript of interest over time. In this report, we demonstrate the utility of this tool using a 27 time point, in vivo muscle regeneration series. This data warehouse and associated analysis tools provides access to multidimensional microarray data through web-based interfaces, both for download of all types of raw data for independent analysis, and also for straightforward gene-based queries. Planned implementations of PEPR will include web-based remote entry of projects adhering to quality control and standard operating procedure (QC/SOP) criteria, and automated output of alternative probe set algorithms for each project (see http://microarray.cnmcresearch.org/pgadatatable.asp). PMID:14681485
A Java-based tool for the design of classification microarrays.
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.
Tra, Yolande V; Evans, Irene M
2010-01-01
BIO2010 put forth the goal of improving the mathematical educational background of biology students. The analysis and interpretation of microarray high-dimensional data can be very challenging and is best done by a statistician and a biologist working and teaching in a collaborative manner. We set up such a collaboration and designed a course on microarray data analysis. We started using Genome Consortium for Active Teaching (GCAT) materials and Microarray Genome and Clustering Tool software and added R statistical software along with Bioconductor packages. In response to student feedback, one microarray data set was fully analyzed in class, starting from preprocessing to gene discovery to pathway analysis using the latter software. A class project was to conduct a similar analysis where students analyzed their own data or data from a published journal paper. This exercise showed the impact that filtering, preprocessing, and different normalization methods had on gene inclusion in the final data set. We conclude that this course achieved its goals to equip students with skills to analyze data from a microarray experiment. We offer our insight about collaborative teaching as well as how other faculty might design and implement a similar interdisciplinary course.
Evans, Irene M.
2010-01-01
BIO2010 put forth the goal of improving the mathematical educational background of biology students. The analysis and interpretation of microarray high-dimensional data can be very challenging and is best done by a statistician and a biologist working and teaching in a collaborative manner. We set up such a collaboration and designed a course on microarray data analysis. We started using Genome Consortium for Active Teaching (GCAT) materials and Microarray Genome and Clustering Tool software and added R statistical software along with Bioconductor packages. In response to student feedback, one microarray data set was fully analyzed in class, starting from preprocessing to gene discovery to pathway analysis using the latter software. A class project was to conduct a similar analysis where students analyzed their own data or data from a published journal paper. This exercise showed the impact that filtering, preprocessing, and different normalization methods had on gene inclusion in the final data set. We conclude that this course achieved its goals to equip students with skills to analyze data from a microarray experiment. We offer our insight about collaborative teaching as well as how other faculty might design and implement a similar interdisciplinary course. PMID:20810954
Tsimakouridze, Elena V; Straume, Marty; Podobed, Peter S; Chin, Heather; LaMarre, Jonathan; Johnson, Ron; Antenos, Monica; Kirby, Gordon M; Mackay, Allison; Huether, Patsy; Simpson, Jeremy A; Sole, Michael; Gadal, Gerard; Martino, Tami A
2012-08-01
There is critical demand in contemporary medicine for gene expression markers in all areas of human disease, for early detection of disease, classification, prognosis, and response to therapy. The integrity of circadian gene expression underlies cardiovascular health and disease; however time-of-day profiling in heart disease has never been examined. We hypothesized that a time-of-day chronomic approach using samples collected across 24-h cycles and analyzed by microarrays and bioinformatics advances contemporary approaches, because it includes sleep-time and/or wake-time molecular responses. As proof of concept, we demonstrate the value of this approach in cardiovascular disease using a murine Transverse Aortic Constriction (TAC) model of pressure overload-induced cardiac hypertrophy in mice. First, microarrays and a novel algorithm termed DeltaGene were used to identify time-of-day differences in gene expression in cardiac hypertrophy 8 wks post-TAC. The top 300 candidates were further analyzed using knowledge-based platforms, paring the list to 20 candidates, which were then validated by real-time polymerase chain reaction (RTPCR). Next, we tested whether the time-of-day gene expression profiles could be indicative of disease progression by comparing the 1- vs. 8-wk TAC. Lastly, since protein expression is functionally relevant, we monitored time-of-day cycling for the analogous cardiac proteins. This approach is generally applicable and can lead to new understanding of disease.
Glez-Peña, Daniel; Díaz, Fernando; Hernández, Jesús M; Corchado, Juan M; Fdez-Riverola, Florentino
2009-06-18
Bioinformatics and medical informatics are two research fields that serve the needs of different but related communities. Both domains share the common goal of providing new algorithms, methods and technological solutions to biomedical research, and contributing to the treatment and cure of diseases. Although different microarray techniques have been successfully used to investigate useful information for cancer diagnosis at the gene expression level, the true integration of existing methods into day-to-day clinical practice is still a long way off. Within this context, case-based reasoning emerges as a suitable paradigm specially intended for the development of biomedical informatics applications and decision support systems, given the support and collaboration involved in such a translational development. With the goals of removing barriers against multi-disciplinary collaboration and facilitating the dissemination and transfer of knowledge to real practice, case-based reasoning systems have the potential to be applied to translational research mainly because their computational reasoning paradigm is similar to the way clinicians gather, analyze and process information in their own practice of clinical medicine. In addressing the issue of bridging the existing gap between biomedical researchers and clinicians who work in the domain of cancer diagnosis, prognosis and treatment, we have developed and made accessible a common interactive framework. Our geneCBR system implements a freely available software tool that allows the use of combined techniques that can be applied to gene selection, clustering, knowledge extraction and prediction for aiding diagnosis in cancer research. For biomedical researches, geneCBR expert mode offers a core workbench for designing and testing new techniques and experiments. For pathologists or oncologists, geneCBR diagnostic mode implements an effective and reliable system that can diagnose cancer subtypes based on the analysis of microarray data using a CBR architecture. For programmers, geneCBR programming mode includes an advanced edition module for run-time modification of previous coded techniques. geneCBR is a new translational tool that can effectively support the integrative work of programmers, biomedical researches and clinicians working together in a common framework. The code is freely available under the GPL license and can be obtained at http://www.genecbr.org.
Chromosomal Microarray versus Karyotyping for Prenatal Diagnosis
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
Sundararajan, Vignesh; Civetta, Alberto
2011-01-01
Male sex genes have shown a pattern of rapid interspecies divergence at both the coding and gene expression level. A common outcome from crosses between closely-related species is hybrid male sterility. Phenotypic and genetic studies in Drosophila sterile hybrid males have shown that spermatogenesis arrest is postmeiotic with few exceptions, and that most misregulated genes are involved in late stages of spermatogenesis. Comparative studies of gene regulation in sterile hybrids and parental species have mainly used microarrays providing a whole genome representation of regulatory problems in sterile hybrids. Real-time PCR studies can reject or reveal differences not observed in microarray assays. Moreover, differences in gene expression between samples can be dependant on the source of RNA (e.g., whole body vs. tissue). Here we survey expression in D. simulans, D. mauritiana and both intra and interspecies hybrids using a real-time PCR approach for eight genes expressed at the four main stages of sperm development. We find that all genes show a trend toward under expression in the testes of sterile hybrids relative to parental species with only the two proliferation genes (bam and bgcn) and the two meiotic class genes (can and sa) showing significant down regulation. The observed pattern of down regulation for the genes tested can not fully explain hybrid male sterility. We discuss the down regulation of spermatogenesis genes in hybrids between closely-related species within the contest of rapid divergence experienced by the male genome, hybrid sterility and possible allometric changes due to subtle testes-specific developmental abnormalities.
High-density fiber-optic DNA random microsphere array.
Ferguson, J A; Steemers, F J; Walt, D R
2000-11-15
A high-density fiber-optic DNA microarray sensor was developed to monitor multiple DNA sequences in parallel. Microarrays were prepared by randomly distributing DNA probe-functionalized 3.1-microm-diameter microspheres in an array of wells etched in a 500-microm-diameter optical imaging fiber. Registration of the microspheres was performed using an optical encoding scheme and a custom-built imaging system. Hybridization was visualized using fluorescent-labeled DNA targets with a detection limit of 10 fM. Hybridization times of seconds are required for nanomolar target concentrations, and analysis is performed in minutes.
Soybean defense responses to the soybean aphid.
Li, Yan; Zou, Jijun; Li, Min; Bilgin, Damla D; Vodkin, Lila O; Hartman, Glen L; Clough, Steven J
2008-01-01
Transcript profiles in aphid (Aphis glycines)-resistant (cv. Dowling) and -susceptible (cv. Williams 82) soybean (Glycine max) cultivars using soybean cDNA microarrays were investigated. Large-scale soybean cDNA microarrays representing approx. 18 000 genes or c. 30% of the soybean genome were compared at 6 and 12 h post-application of aphids. In a separate experiment utilizing clip cages, expression of three defense-related genes were examined at 6, 12, 24, 48, and 72 h in both cultivars by quantitative real-time PCR. One hundred and forty genes showed specific responses for resistance; these included genes related to cell wall, defense, DNA/RNA, secondary metabolism, signaling and other processes. When an extended time period of sampling was investigated, earlier and greater induction of three defense-related genes was observed in the resistant cultivar; however, the induction declined after 24 or 48 h in the resistant cultivar but continued to increase in the susceptible cultivar after 24 h. Aphid-challenged resistant plants showed rapid differential gene expression patterns similar to the incompatible response induced by avirulent Pseudomonas syringae. Five genes were identified as differentially expressed between the two genotypes in the absence of aphids.
NASA Astrophysics Data System (ADS)
Liu, Hai-Tao; Wen, Zhi-Yu; Xu, Yi; Shang, Zheng-Guo; Peng, Jin-Lan; Tian, Peng
2017-09-01
In this paper, an integrated microfluidic analysis microsystems with bacterial capture enrichment and in-situ impedance detection was purposed based on microfluidic chips dielectrophoresis technique and electrochemical impedance detection principle. The microsystems include microfluidic chip, main control module, and drive and control module, and signal detection and processing modulet and result display unit. The main control module produce the work sequence of impedance detection system parts and achieve data communication functions, the drive and control circuit generate AC signal which amplitude and frequency adjustable, and it was applied on the foodborne pathogens impedance analysis microsystems to realize the capture enrichment and impedance detection. The signal detection and processing circuit translate the current signal into impendence of bacteria, and transfer to computer, the last detection result is displayed on the computer. The experiment sample was prepared by adding Escherichia coli standard sample into chicken sample solution, and the samples were tested on the dielectrophoresis chip capture enrichment and in-situ impedance detection microsystems with micro-array electrode microfluidic chips. The experiments show that the Escherichia coli detection limit of microsystems is 5 × 104 CFU/mL and the detection time is within 6 min in the optimization of voltage detection 10 V and detection frequency 500 KHz operating conditions. The integrated microfluidic analysis microsystems laid the solid foundation for rapid real-time in-situ detection of bacteria.
Guo, Chunguang; Zhang, Xiaodong; Fink, Stephen P; Platzer, Petra; Wilson, Keith; Willson, James K. V.; Wang, Zhenghe; Markowitz, Sanford D
2008-01-01
Expression microarrays identified a novel transcript, designated as Ugene, whose expression is absent in normal colon and colon adenomas, but that is commonly induced in malignant colon cancers. These findings were validated by real-time PCR and Northern blot analysis in an independent panel of colon cancer cases. In addition, Ugene expression was found to be elevated in many other common cancer types, including, breast, lung, uterus, and ovary. Immunofluorescence of V5-tagged Ugene revealed it to have a nuclear localization. In a pull-down assay, uracil DNA-glycosylase 2 (UNG2), an important enzyme in the base excision repair pathway, was identified as a partner protein that binds to Ugene. Co-immunoprecipitation and Western blot analysis confirmed the binding between the endogenous Ugene and UNG2 proteins. Using deletion constructs, we find that Ugene binds to the first 25 amino acids of the UNG2 NH2-terminus. We suggest Ugene induction in cancer may contribute to the cancer phenotype by interacting with the base excision repair pathway. PMID:18676834
A Model-Based Joint Identification of Differentially Expressed Genes and Phenotype-Associated Genes
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
Direct labeling of serum proteins by fluorescent dye for antibody microarray.
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.
Walter, Andreas; Knapp, Brigitte A.; Farbmacher, Theresa; Ebner, Christian; Insam, Heribert; Franke‐Whittle, Ingrid H.
2012-01-01
Summary To find links between the biotic characteristics and abiotic process parameters in anaerobic digestion systems, the microbial communities of nine full‐scale biogas plants in South Tyrol (Italy) and Vorarlberg (Austria) were investigated using molecular techniques and the physical and chemical properties were monitored. DNA from sludge samples was subjected to microarray hybridization with the ANAEROCHIP microarray and results indicated that sludge samples grouped into two main clusters, dominated either by Methanosarcina or by Methanosaeta, both aceticlastic methanogens. Hydrogenotrophic methanogens were hardly detected or if detected, gave low hybridization signals. Results obtained using denaturing gradient gel electrophoresis (DGGE) supported the findings of microarray hybridization. Real‐time PCR targeting Methanosarcina and Methanosaeta was conducted to provide quantitative data on the dominating methanogens. Correlation analysis to determine any links between the microbial communities found by microarray analysis, and the physicochemical parameters investigated was conducted. It was shown that the sludge samples dominated by the genus Methanosarcina were positively correlated with higher concentrations of acetate, whereas sludge samples dominated by representatives of the genus Methanosaeta had lower acetate concentrations. No other correlations between biotic characteristics and abiotic parameters were found. Methanogenic communities in each reactor were highly stable and resilient over the whole year. PMID:22950603
Development and Validation of Sandwich ELISA Microarrays with Minimal Assay Interference
DOE Office of Scientific and Technical Information (OSTI.GOV)
Gonzalez, Rachel M.; Servoss, Shannon; Crowley, Sheila A.
Sandwich enzyme-linked immunosorbent assay (ELISA) microarrays are emerging as a strong candidate platform for multiplex biomarker analysis because of the ELISA’s ability to quantitatively measure rare proteins in complex biological fluids. Advantages of this platform are high-throughput potential, assay sensitivity and stringency, and the similarity to the standard ELISA test, which facilitates assay transfer from a research setting to a clinical laboratory. However, a major concern with the multiplexing of ELISAs is maintaining high assay specificity. In this study, we systematically determine the amount of assay interference and noise contributed by individual components of the multiplexed 24-assay system. We findmore » that non-specific reagent cross-reactivity problems are relatively rare. We did identify the presence of contaminant antigens in a “purified antigen”. We tested the validated ELISA microarray chip using paired serum samples that had been collected from four women at a 6-month interval. This analysis demonstrated that protein levels typically vary much more between individuals then within an individual over time, a result which suggests that longitudinal studies may be useful in controlling for biomarker variability across a population. Overall, this research demonstrates the importance of a stringent screening protocol and the value of optimizing the antibody and antigen concentrations when designing chips for ELISA microarrays.« less
Integrative missing value estimation for microarray data.
Hu, Jianjun; Li, Haifeng; Waterman, Michael S; Zhou, Xianghong Jasmine
2006-10-12
Missing value estimation is an important preprocessing step in microarray analysis. Although several methods have been developed to solve this problem, their performance is unsatisfactory for datasets with high rates of missing data, high measurement noise, or limited numbers of samples. In fact, more than 80% of the time-series datasets in Stanford Microarray Database contain less than eight samples. We present the integrative Missing Value Estimation method (iMISS) by incorporating information from multiple reference microarray datasets to improve missing value estimation. For each gene with missing data, we derive a consistent neighbor-gene list by taking reference data sets into consideration. To determine whether the given reference data sets are sufficiently informative for integration, we use a submatrix imputation approach. Our experiments showed that iMISS can significantly and consistently improve the accuracy of the state-of-the-art Local Least Square (LLS) imputation algorithm by up to 15% improvement in our benchmark tests. We demonstrated that the order-statistics-based integrative imputation algorithms can achieve significant improvements over the state-of-the-art missing value estimation approaches such as LLS and is especially good for imputing microarray datasets with a limited number of samples, high rates of missing data, or very noisy measurements. With the rapid accumulation of microarray datasets, the performance of our approach can be further improved by incorporating larger and more appropriate reference datasets.
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.
Mansourian, Robert; Mutch, David M; Antille, Nicolas; Aubert, Jerome; Fogel, Paul; Le Goff, Jean-Marc; Moulin, Julie; Petrov, Anton; Rytz, Andreas; Voegel, Johannes J; Roberts, Matthew-Alan
2004-11-01
Microarray technology has become a powerful research tool in many fields of study; however, the cost of microarrays often results in the use of a low number of replicates (k). Under circumstances where k is low, it becomes difficult to perform standard statistical tests to extract the most biologically significant experimental results. Other more advanced statistical tests have been developed; however, their use and interpretation often remain difficult to implement in routine biological research. The present work outlines a method that achieves sufficient statistical power for selecting differentially expressed genes under conditions of low k, while remaining as an intuitive and computationally efficient procedure. The present study describes a Global Error Assessment (GEA) methodology to select differentially expressed genes in microarray datasets, and was developed using an in vitro experiment that compared control and interferon-gamma treated skin cells. In this experiment, up to nine replicates were used to confidently estimate error, thereby enabling methods of different statistical power to be compared. Gene expression results of a similar absolute expression are binned, so as to enable a highly accurate local estimate of the mean squared error within conditions. The model then relates variability of gene expression in each bin to absolute expression levels and uses this in a test derived from the classical ANOVA. The GEA selection method is compared with both the classical and permutational ANOVA tests, and demonstrates an increased stability, robustness and confidence in gene selection. A subset of the selected genes were validated by real-time reverse transcription-polymerase chain reaction (RT-PCR). All these results suggest that GEA methodology is (i) suitable for selection of differentially expressed genes in microarray data, (ii) intuitive and computationally efficient and (iii) especially advantageous under conditions of low k. The GEA code for R software is freely available upon request to authors.
Schmid, Patrick; Yao, Hui; Galdzicki, Michal; Berger, Bonnie; Wu, Erxi; Kohane, Isaac S.
2009-01-01
Background Although microarray technology has become the most common method for studying global gene expression, a plethora of technical factors across the experiment contribute to the variable of genome gene expression profiling using peripheral whole blood. A practical platform needs to be established in order to obtain reliable and reproducible data to meet clinical requirements for biomarker study. Methods and Findings We applied peripheral whole blood samples with globin reduction and performed genome-wide transcriptome analysis using Illumina BeadChips. Real-time PCR was subsequently used to evaluate the quality of array data and elucidate the mode in which hemoglobin interferes in gene expression profiling. We demonstrated that, when applied in the context of standard microarray processing procedures, globin reduction results in a consistent and significant increase in the quality of beadarray data. When compared to their pre-globin reduction counterparts, post-globin reduction samples show improved detection statistics, lowered variance and increased sensitivity. More importantly, gender gene separation is remarkably clearer in post-globin reduction samples than in pre-globin reduction samples. Our study suggests that the poor data obtained from pre-globin reduction samples is the result of the high concentration of hemoglobin derived from red blood cells either interfering with target mRNA binding or giving the pseudo binding background signal. Conclusion We therefore recommend the combination of performing globin mRNA reduction in peripheral whole blood samples and hybridizing on Illumina BeadChips as the practical approach for biomarker study. PMID:19381341
2013-01-01
Background Dilated cardiomyopathy (DCM) is the most common heart disease in Doberman Pinschers. MicroRNAs (miRNAs) are short non-coding RNAs playing important roles in gene regulation. Different miRNA expression patterns have been described for DCM in humans and might represent potential diagnostic markers. There are no studies investigating miRNA expression profiles in canine DCM. The aims of this study were to screen the miRNA expression profile of canine serum using miRNA microarray and to compare expression patterns of a group of Doberman Pinschers with DCM and healthy controls. Results Eight Doberman Pinschers were examined by echocardiography and 24-hour-ECG and classified as healthy (n = 4) or suffering from DCM (n = 4). Total RNA was extracted from serum and hybridized on a custom-designed 8x60k miRNA microarray (Agilent) containing probes for 1368 individual miRNAs. Although total RNA concentrations were very low in serum samples, 404 different miRNAs were detectable with sufficient signal intensity on miRNA microarray. 22 miRNAs were differentially expressed in the two groups (p < 0.05 and fold change (FC) > 1.5), but did not reach statistical significance after multiple testing correction (false discovery rate adjusted p > 0.05). Five miRNAs were selected for further analysis using quantitative Real-Time RT-PCR (qPCR) assays. No significant differences were found using specific miRNA qPCR assays (p > 0.05). Conclusions Numerous miRNAs can be detected in canine serum. Between healthy and DCM dogs, miRNA expression changes could be detected, but the results did not reach statistical significance most probably due to the small group size. miRNAs are potential new circulating biomarkers in veterinary medicine and should be investigated in larger patient groups and additional canine diseases. PMID:23327631
Steudemann, Carola; Bauersachs, Stefan; Weber, Karin; Wess, Gerhard
2013-01-17
Dilated cardiomyopathy (DCM) is the most common heart disease in Doberman Pinschers. MicroRNAs (miRNAs) are short non-coding RNAs playing important roles in gene regulation. Different miRNA expression patterns have been described for DCM in humans and might represent potential diagnostic markers. There are no studies investigating miRNA expression profiles in canine DCM. The aims of this study were to screen the miRNA expression profile of canine serum using miRNA microarray and to compare expression patterns of a group of Doberman Pinschers with DCM and healthy controls. Eight Doberman Pinschers were examined by echocardiography and 24-hour-ECG and classified as healthy (n=4) or suffering from DCM (n=4). Total RNA was extracted from serum and hybridized on a custom-designed 8x60k miRNA microarray (Agilent) containing probes for 1368 individual miRNAs. Although total RNA concentrations were very low in serum samples, 404 different miRNAs were detectable with sufficient signal intensity on miRNA microarray. 22 miRNAs were differentially expressed in the two groups (p<0.05 and fold change (FC)>1.5), but did not reach statistical significance after multiple testing correction (false discovery rate adjusted p>0.05). Five miRNAs were selected for further analysis using quantitative Real-Time RT-PCR (qPCR) assays. No significant differences were found using specific miRNA qPCR assays (p>0.05). Numerous miRNAs can be detected in canine serum. Between healthy and DCM dogs, miRNA expression changes could be detected, but the results did not reach statistical significance most probably due to the small group size. miRNAs are potential new circulating biomarkers in veterinary medicine and should be investigated in larger patient groups and additional canine diseases.
Reliable pre-eclampsia pathways based on multiple independent microarray data sets.
Kawasaki, Kaoru; Kondoh, Eiji; Chigusa, Yoshitsugu; Ujita, Mari; Murakami, Ryusuke; Mogami, Haruta; Brown, J B; Okuno, Yasushi; Konishi, Ikuo
2015-02-01
Pre-eclampsia is a multifactorial disorder characterized by heterogeneous clinical manifestations. Gene expression profiling of preeclamptic placenta have provided different and even opposite results, partly due to data compromised by various experimental artefacts. Here we aimed to identify reliable pre-eclampsia-specific pathways using multiple independent microarray data sets. Gene expression data of control and preeclamptic placentas were obtained from Gene Expression Omnibus. Single-sample gene-set enrichment analysis was performed to generate gene-set activation scores of 9707 pathways obtained from the Molecular Signatures Database. Candidate pathways were identified by t-test-based screening using data sets, GSE10588, GSE14722 and GSE25906. Additionally, recursive feature elimination was applied to arrive at a further reduced set of pathways. To assess the validity of the pre-eclampsia pathways, a statistically-validated protocol was executed using five data sets including two independent other validation data sets, GSE30186, GSE44711. Quantitative real-time PCR was performed for genes in a panel of potential pre-eclampsia pathways using placentas of 20 women with normal or severe preeclamptic singleton pregnancies (n = 10, respectively). A panel of ten pathways were found to discriminate women with pre-eclampsia from controls with high accuracy. Among these were pathways not previously associated with pre-eclampsia, such as the GABA receptor pathway, as well as pathways that have already been linked to pre-eclampsia, such as the glutathione and CDKN1C pathways. mRNA expression of GABRA3 (GABA receptor pathway), GCLC and GCLM (glutathione metabolic pathway), and CDKN1C was significantly reduced in the preeclamptic placentas. In conclusion, ten accurate and reliable pre-eclampsia pathways were identified based on multiple independent microarray data sets. A pathway-based classification may be a worthwhile approach to elucidate the pathogenesis of pre-eclampsia. © The Author 2014. Published by Oxford University Press on behalf of the European Society of Human Reproduction and Embryology. All rights reserved. For Permissions, please email: journals.permissions@oup.com.
ELISA-BASE: An Integrated Bioinformatics Tool for Analyzing and Tracking ELISA Microarray Data
DOE Office of Scientific and Technical Information (OSTI.GOV)
White, Amanda M.; Collett, James L.; Seurynck-Servoss, Shannon L.
ELISA-BASE is an open-source database for capturing, organizing and analyzing protein enzyme-linked immunosorbent assay (ELISA) microarray data. ELISA-BASE is an extension of the BioArray Soft-ware Environment (BASE) database system, which was developed for DNA microarrays. In order to make BASE suitable for protein microarray experiments, we developed several plugins for importing and analyzing quantitative ELISA microarray data. Most notably, our Protein Microarray Analysis Tool (ProMAT) for processing quantita-tive ELISA data is now available as a plugin to the database.
Ling, Jing; Wu, Xiaoli; Fu, Ziyi; Tan, Jie; Xu, Qing
2015-10-01
Our previous study showed that the expression of miR-197 in leiomyoma was down-regulated compared with myometrium. Further, miR-197 has been identified to affect uterine leiomyoma cell proliferation, apoptosis, and metastasis ability, though the responsible molecular mechanism has not been well elucidated. In this study, we sought to determine the expression patterns of miR-197 targeted genes and to explore their potential functions, participating Pathways and the networks that are involved in the biological behavior of human uterine leiomyoma. After transfection of human uterine leiomyoma cells with miR-197, we confirmed the expression level of miR-197 using quantitative real-time PCR (qRT-PCR), and we detected the gene expression profiles after miR-197 over-expression through DNA microarray analysis. Further, we performed GO and Pathway analysis. The dominantly dys-regulated genes, which were up- or down-regulated by more than 10-fold, compared with parental cells, were confirmed using qRT-PCR technology. Compared with the control group, miR-197 was up-regulated by 30-fold after miR-197 lentiviral transfection. The microarray data showed that 872 genes were dys-regulated by more than 2-fold in human uterine leiomyoma cells after miR-197 overexpression, including 537 up-regulated and 335 down-regulated genes. The GO analysis indicated that the dys-regulated genes were primarily involved in response to stimuli, multicellular organ processes, and the signaling of biological progression. Further, Pathway analysis data showed that these genes participated in regulating several signaling Pathways, including the JAK/STAT signaling Pathway, the Toll-like receptor signaling Pathway, and cytokine-cytokine receptor interaction. The qRT-PCR results confirmed that 17 of the 66 selected genes, which were up- or down-regulated more than 10-fold by miR-197, were consistent with the microarray results, including tumorigenesis-related genes, such as DRT7, SLC549, SFMBT2, FLJ37956, FBLN2, C10orf35, HOXD12, CACNG7, and LOC100134279. Our study explored gene expression patterns after miR-197 overexpression and confirmed 17 dominantly dys-regulated genes, which could expand the insights into the function of miR-197 and the molecular mechanisms during the development and progression of uterine leiomyomas. This study might afford new clues for understanding the pathogenesis of uterine leiomyomas, and it could likely provide a unique method for diagnosing or predicting prognosis in the clinical treatment of leiomyoma. Copyright © 2015 Elsevier Masson SAS. All rights reserved.
Adam, Rosalyn M; Eaton, Samuel H; Estrada, Carlos; Nimgaonkar, Ashish; Shih, Shu-Ching; Smith, Lois E H; Kohane, Isaac S; Bägli, Darius; Freeman, Michael R
2004-12-15
Application of mechanical stimuli has been shown to alter gene expression in bladder smooth muscle cells (SMC). To date, only a limited number of "stretch-responsive" genes in this cell type have been reported. We employed oligonucleotide arrays to identify stretch-sensitive genes in primary culture human bladder SMC subjected to repetitive mechanical stimulation for 4 h. Differential gene expression between stretched and nonstretched cells was assessed using Significance Analysis of Microarrays (SAM). Expression of 20 out of 11,731 expressed genes ( approximately 0.17%) was altered >2-fold following stretch, with 19 genes induced and one gene (FGF-9) repressed. Using real-time RT-PCR, we tested independently the responsiveness of 15 genes to stretch and to platelet-derived growth factor-BB (PDGF-BB), another hypertrophic stimulus for bladder SMC. In response to both stimuli, expression of 13 genes increased, 1 gene (FGF-9) decreased, and 1 gene was unchanged. Six transcripts (HB-EGF, BMP-2, COX-2, LIF, PAR-2, and FGF-9) were evaluated using an ex vivo rat model of bladder distension. HB-EGF, BMP-2, COX-2, LIF, and PAR-2 increased with bladder stretch ex vivo, whereas FGF-9 decreased, consistent with expression changes observed in vitro. In silico analysis of microarray data using the FIRED algorithm identified c-jun, AP-1, ATF-2, and neurofibromin-1 (NF-1) as potential transcriptional mediators of stretch signals. Furthermore, the promoters of 9 of 13 stretch-responsive genes contained AP-1 binding sites. These observations identify stretch as a highly selective regulator of gene expression in bladder SMC. Moreover, they suggest that mechanical and growth factor signals converge on common transcriptional regulators that include members of the AP-1 family.
Oh, Jung-Hwa; Yang, Mi-jin; Yang, Young-Su; Park, Han-Jin; Heo, Sun Hee; Lee, Eun-Hee; Song, Chang-Woo; Yoon, Seokjoo
2009-02-01
Repeated exposure to welding fumes promotes a reversible increase in pulmonary disease risk, but the molecular mechanisms by which welding fumes induce lung injury and how the lung recovers from such insults are unclear. In the present study, pulmonary function and gene-expression profiles in the lung were analyzed by Affymetrix GeneChip microarray after 30 days of consecutive exposure to manual metal arc welding combined with stainless-steel (MMA-SS) welding fumes, and again after 30 days of recovery from MMA-SS fume exposure. In total, 577 genes were identified as being either up-regulated or down-regulated (over twofold changes, p < 0.05) in the lungs of low-dose or high-dose groups. Differentially expressed genes were classified based on a k-means clustering algorithm and biological functions and molecular networks were further analyzed using Ingenuity Pathways Analysis. Among the genes affected by exposure to or recovery from MMA-SS fumes, the transcriptional changes of 13 genes that were highly altered by treatment were confirmed by quantitative real-time PCR. Notably, Mmp12, Cd5l, Ccl7, Cxcl5, and Spp1 related to the immune response were up-regulated only in the exposure group, whereas Trem2, IgG-2a, Igh-1a, and Igh were persistently up-regulated in both the exposure and recovery groups. In addition, several genes that might play a role in the repair process of the lung were up-regulated exclusively in the recovery group. Collectively, these data may help elucidate the molecular mechanism of the recovery process of the lung after welding fume exposure.
Loose, David S.; Gottipati, Koteswara R.; Natarajan, Kartiga; Mitchell, Courtney T.
2016-01-01
The intensification and concentration of animal production operations expose workers to high levels of organic dusts in the work environment. Exposure to organic dusts is a risk factor for the development of acute and chronic respiratory symptoms and diseases. Lung epithelium plays important roles in the control of immune and inflammatory responses to environmental agents to maintain lung health. To better understand the effects of organic dust on lung inflammatory responses, we characterized the gene expression profiles of A549 alveolar and Beas2B bronchial epithelial and THP-1 monocytic cells influenced by exposure to poultry dust extract by DNA microarray analysis using Illumina Human HT-12 v4 Expression BeadChip. We found that A549 alveolar and Beas2B bronchial epithelial and THP-1 cells responded with unique changes in the gene expression profiles with regulation of genes encoding inflammatory cytokines, chemokines, and other inflammatory proteins being common to all the three cells. Significantly induced genes included IL-8, IL-6, IL-1β, ICAM-1, CCL2, CCL5, TLR4, and PTGS2. Validation by real-time qRT-PCR, ELISA, Western immunoblotting, and immunohistochemical staining of lung sections from mice exposed to dust extract validated DNA microarray results. Pathway analysis indicated that dust extract induced changes in gene expression influenced functions related to cellular growth and proliferation, cell death and survival, and cellular development. These data show that a broad range of inflammatory mediators produced in response to poultry dust exposure can modulate lung immune and inflammatory responses. This is the first report on organic dust induced changes in expression profiles in lung epithelial and THP-1 monocytic cells. PMID:26884459
Grating coupled SPR microarray analysis of proteins and cells in blood from mice with breast cancer.
Mendoza, A; Torrisi, D M; Sell, S; Cady, N C; Lawrence, D A
2016-01-21
Biomarker discovery for early disease diagnosis is highly important. Of late, much effort has been made to analyze complex biological fluids in an effort to develop new markers specific for different cancer types. Recent advancements in label-free technologies such as surface plasmon resonance (SPR)-based biosensors have shown promise as a diagnostic tool since there is no need for labeling or separation of cells. Furthermore, SPR can provide rapid, real-time detection of antigens from biological samples since SPR is highly sensitive to changes in surface-associated molecular and cellular interactions. Herein, we report a lab-on-a-chip microarray biosensor that utilizes grating-coupled surface plasmon resonance (GCSPR) and grating-coupled surface plasmon coupled fluorescence (GCSPCF) imaging to detect circulating tumor cells (CTCs) from a mouse model (FVB-MMTV-PyVT). GCSPR and GCSPCF analysis was accomplished by spotting antibodies to surface cell markers, cytokines and stress proteins on a nanofabricated GCSPR microchip and screening blood samples from FVB control mice or FVB-MMTV-PyVT mice with developing mammary carcinomas. A transgenic MMTV-PyVT mouse derived cancer cell line was also analyzed. The analyses indicated that CD24, CD44, CD326, CD133 and CD49b were expressed in both cell lines and in blood from MMTV-PyVT mice. Furthermore, cytokines such as IL-6, IL-10 and TNF-α, along with heat shock proteins HSP60, HSP27, HSc70(HSP73), HSP90 total, HSP70/HSc70, HSP90, HSP70, HSP90 alpha, phosphotyrosine and HSF-1 were overexpressed in MMTV-PyVT mice.
Song, Jae-Jun; Kwon, Jee Young; Park, Moo Kyun; Seo, Young Rok
2013-10-01
The primary aim of this study is to reveal the effect of particulate matter (PM) on the human middle ear epithelial cell (HMEEC). The HMEEC was treated with PM (300 μg/ml) for 24 h. Total RNA was extracted and used for microarray analysis. Molecular pathways among differentially expressed genes were further analyzed by using Pathway Studio 9.0 software. For selected genes, the changes in gene expression were confirmed by real-time PCR. A total of 611 genes were regulated by PM. Among them, 366 genes were up-regulated, whereas 245 genes were down-regulated. Up-regulated genes were mainly involved in cellular processes, including reactive oxygen species generation, cell proliferation, apoptosis, cell differentiation, inflammatory response and immune response. Down-regulated genes affected several cellular processes, including cell differentiation, cell cycle, proliferation, apoptosis and cell migration. A total of 21 genes were discovered as crucial components in potential signaling networks containing 2-fold up regulated genes. Four genes, VEGFA, IL1B, CSF2 and HMOX1 were revealed as key mediator genes among the up-regulated genes. A total of 25 genes were revealed as key modulators in the signaling pathway associated with 2-fold down regulated genes. Four genes, including IGF1R, TIMP1, IL6 and FN1, were identified as the main modulator genes. We identified the differentially expressed genes in PM-treated HMEEC, whose expression profile may provide a useful clue for the understanding of environmental pathophysiology of otitis media. Our work indicates that air pollution, like PM, plays an important role in the pathogenesis of otitis media. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.
Soluble FLT-1 rules placental destiny.
Yamashita, Michiko; Kumasawa, Keiichi; Nakamura, Hitomi; Kimura, Tadashi
2018-02-19
Placenta previa is an abnormality in which the placenta covers the internal uterine os, and it can cause serious morbidity and mortality in both mother and fetus due to catastrophic hemorrhage. Some pregnant women recover from placenta previa due to a phenomenon called "migration." However, the mechanism of "migration" of the placenta has not been elucidated. Human placentas were collected from patients with placenta previa and those with no abnormal placentation (control). A microarray analysis was performed to detect the genes up- or down-regulated only in the caudal part in the previa group. Specific mRNA expression was evaluated using real-time quantitative reverse transcription PCR (qRT-PCR). Unilateral uterine artery ablation of 8.5 dpc mice was performed to reproduce the reduction of placental blood supply, and weights of the placentas and fetuses were evaluated in 18.5 dpc. Specific mRNA expression was also evaluated in mice placentas. According to the result of the microarray analysis, we focused on soluble fms-like tyrosine kinase-1 (sFLT-1) and hypoxia-inducible factor-1 (HIF-1) alpha. The sFLT-1 expression level is locally high in the caudal part of the human placenta in patients with placenta previa. In mice experiments, the weights of the placentas and fetuses were significantly smaller in the ablation side than those in the control side, and the sFlt-1 expression level was significantly higher in the ablation side than in the control side. Our study suggests that "migration" of the placenta is derived from placental degeneration at the caudal part of the placenta, and sFlt-1 plays a role in this placental degeneration. Copyright © 2018 Elsevier Inc. All rights reserved.
Ohse, Takamoto; Ota, Tatsuru; Kieran, Niamh; Godson, Catherine; Yamada, Koei; Tanaka, Tetsuhiro; Fujita, Toshiro; Nangaku, Masaomi
2004-04-01
Immune complex deposition is associated with the accumulation of neutrophils, which play an important role in the various immune-mediated diseases. A novel anti-inflammatory agent, the lipoxin A (LXA) analogue (15-epi-16-(FPhO)-LXA-Me)), a stable synthetic analogue of aspirin-triggered 15-epi-lipoxin A4 (ATLa), was used in experimental anti-glomerular basement membrane (GBM) antibody nephritis in mice. ATLa was administered before the induction of the disease, and 2 h later, the animals were killed. ATLa reduced the infiltrating neutrophils and nitrotyrosine staining in glomeruli. Subsequent changes of gene expression in the early phase were evaluated, and 5674 genes were present under the basal conditions in kidneys from normal mice; 54 upregulated genes and 25 downregulated genes were detected in anti-GBM nephritis. Eighteen of these upregulated genes were those induced by IFN-gamma. Real-time quantitative PCR analysis confirmed the results of the microarrays. To investigate a role of IFN-gamma in neutrophil infiltration, anti-GBM nephritis was induced in IFN-gamma knockout mice. The number of infiltrating neutrophils in these mice did not differ from those in wild-type mice. Also examined were CD11b expression on neutrophils from mice treated with ATLa by flow cytometry, but suppression of this adhesion molecule was not observed. Neutrophil infiltration was successfully inhibited by ATLa in the early phase of murine anti-GBM nephritis. Microarray analysis detected the change of mRNA expression in anti-GBM nephritis and demonstrated amelioration of various genes by ATLa, which may provide a clue to the development of novel therapeutic approaches in immune renal injury.
Planell, Núria; Masamunt, M Carme; Leal, Raquel Franco; Rodríguez, Lorena; Esteller, Miriam; Lozano, Juan J; Ramírez, Anna; Ayrizono, Maria de Lourdes Setsuko; Coy, Claudio Saddy Rodrigues; Alfaro, Ignacio; Ordás, Ingrid; Visvanathan, Sudha; Ricart, Elena; Guardiola, Jordi; Panés, Julián; Salas, Azucena
2017-10-27
Ulcerative colitis [UC] is a chronic inflammatory disease of the colon. Colonoscopy remains the gold standard for evaluating disease activity, as clinical symptoms are not sufficiently accurate. The aim of this study is to identify new accurate non-invasive biomarkers based on whole-blood transcriptomics that can predict mucosal lesions and response to treatment in UC patients. Whole-blood samples were collected for a total of 152 UC patients at endoscopy. Blood RNA from 25 UC individuals and 20 controls was analysed using microarrays. Genes that correlated with endoscopic activity were validated using real-time polymerase chain reaction in an independent group of 111 UC patients, and a prediction model for mucosal lesions was evaluated. Responsiveness to treatment was assessed in a longitudinal cohort of 16 UC patients who started anti-tumour necrosis factor [TNF] therapy and were followed up for 14 weeks. Microarray analysis identified 122 genes significantly altered in the blood of endoscopically active UC patients. A significant correlation with the degree of endoscopic activity was observed in several genes, including HP, CD177, GPR84, and S100A12. Using HP as a predictor of endoscopic disease activity, an accuracy of 67.3% was observed, compared with 52.4%, 45.2%, and 30.3% for C-reactive protein, erythrocyte sedimentation rate, and platelet count, respectively. Finally, at 14 weeks of treatment, response to anti-TNF therapy induced alterations in blood HP, CD177, GPR84, and S100A12 transcripts that correlated with changes in endoscopic activity. Transcriptional changes in UC patients are sensitive to endoscopic improvement and appear to be an effective tool to monitor patients over time. © European Crohn’s and Colitis Organisation (ECCO) 2017.
Planell, Núria; Masamunt, M Carme; Leal, Raquel Franco; Rodríguez, Lorena; Esteller, Miriam; Lozano, Juan J; Ramírez, Anna; Ayrizono, Maria de Lourdes Setsuko; Coy, Claudio Saddy Rodrigues; Alfaro, Ignacio; Ordás, Ingrid; Visvanathan, Sudha; Ricart, Elena; Guardiola, Jordi; Panés, Julián; Salas, Azucena
2017-01-01
Abstract Background and Aims Ulcerative colitis [UC] is a chronic inflammatory disease of the colon. Colonoscopy remains the gold standard for evaluating disease activity, as clinical symptoms are not sufficiently accurate. The aim of this study is to identify new accurate non-invasive biomarkers based on whole-blood transcriptomics that can predict mucosal lesions and response to treatment in UC patients. Methods Whole-blood samples were collected for a total of 152 UC patients at endoscopy. Blood RNA from 25 UC individuals and 20 controls was analysed using microarrays. Genes that correlated with endoscopic activity were validated using real-time polymerase chain reaction in an independent group of 111 UC patients, and a prediction model for mucosal lesions was evaluated. Responsiveness to treatment was assessed in a longitudinal cohort of 16 UC patients who started anti-tumour necrosis factor [TNF] therapy and were followed up for 14 weeks. Results Microarray analysis identified 122 genes significantly altered in the blood of endoscopically active UC patients. A significant correlation with the degree of endoscopic activity was observed in several genes, including HP, CD177, GPR84, and S100A12. Using HP as a predictor of endoscopic disease activity, an accuracy of 67.3% was observed, compared with 52.4%, 45.2%, and 30.3% for C-reactive protein, erythrocyte sedimentation rate, and platelet count, respectively. Finally, at 14 weeks of treatment, response to anti-TNF therapy induced alterations in blood HP, CD177, GPR84, and S100A12 transcripts that correlated with changes in endoscopic activity. Conclusions Transcriptional changes in UC patients are sensitive to endoscopic improvement and appear to be an effective tool to monitor patients over time. PMID:28981629
NASA Astrophysics Data System (ADS)
Meng, Xianhong; Shi, Xiaoli; Kong, Jie; Luan, Sheng; Luo, Kun; Cao, Baoxiang; Liu, Ning; Lu, Xia; Li, Xupeng; Deng, Kangyu; Cao, Jiawang; Zhang, Yingxue; Zhang, Hengheng
2017-10-01
To elucidate the molecular response of shrimp hepatopancreas to white spot syndrome virus (WSSV) infection, microarray was applied to investigate the differentially expressed genes in the hepatopancreas of `Huanghai No. 2' ( Fenneropenaeus chinensis). A total of 59137 unigenes were designed onto a custom-made 60K Agilent chip. After infection, the gene expression profiles in the hepatopancreas of the shrimp with a lower viral load at early (48-96 h), peak (168-192 h) and late (264-288 h) infection phases were analyzed. Of 18704 differentially expressed genes, 6412 were annotated. In total, 5453 differentially expressed genes (1916 annotated) expressed at all three phases, and most of the annotated were either up- or down-regulated continuously. These genes function diversely in, for example, immune response, cytoskeletal system, signal transduction, stress resistance, protein synthesis and processing, metabolism among others. Some of the immune-related genes, including antilipopolysaccharide factor, Kazal-type proteinase inhibitor, C-type lectin and serine protease encoding genes, were up-regulated after WSSV infection. These genes have been reported to be involved in the anti-WSSV responses. The expression of genes related to the cytoskeletal system, including β-actin and myosin but without tubulin genes, were down-regulated after WSSV infection. Astakine was found for the first time in the WSSV-infected F. chinensis. To further confirm the expression of differentially expressed genes, quantitative real-time PCR was performed to test the expression of eight randomly selected genes and verified the reliability and accuracy of the microarray expression analysis. The data will provide valuable information to understanding the immune mechanism of shrimp's response to WSSV.
Transcription Analysis of the Myometrium of Labouring and Non-Labouring Women
Hutchinson, James L.; Hibbert, Nanette; Freeman, Tom C.; Saunders, Philippa T. K.; Norman, Jane E.
2016-01-01
An incomplete understanding of the molecular mechanisms that initiate normal human labour at term seriously hampers the development of effective ways to predict, prevent and treat disorders such as preterm labour. Appropriate analysis of large microarray experiments that compare gene expression in non-labouring and labouring gestational tissues is necessary to help bridge these gaps in our knowledge. In this work, gene expression in 48 (22 labouring, 26 non-labouring) lower-segment myometrial samples collected at Caesarean section were analysed using Illumina HT-12 v4.0 BeadChips. Normalised data were compared between labouring and non-labouring groups using traditional statistical methods and a novel network graph approach. We sought technical validation with quantitative real-time PCR, and biological replication through inverse variance-weighted meta-analysis with published microarray data. We have extended the list of genes suggested to be associated with labour: Compared to non-labouring samples, labouring samples showed apparent higher expression at 960 probes (949 genes) and apparent lower expression at 801 probes (789 genes) (absolute fold change ≥1.2, rank product percentage of false positive value (RP-PFP) <0.05). Although half of the women in the labouring group had received pharmaceutical treatment to induce or augment labour, sensitivity analysis suggested that this did not confound our results. In agreement with previous studies, functional analysis suggested that labour was characterised by an increase in the expression of inflammatory genes and network analysis suggested a strong neutrophil signature. Our analysis also suggested that labour is characterised by a decrease in the expression of muscle-specific processes, which has not been explicitly discussed previously. We validated these findings through the first formal meta-analysis of raw data from previous experiments and we hypothesise that this represents a change in the composition of myometrial tissue at labour. Further work will be necessary to reveal whether these results are solely due to leukocyte infiltration into the myometrium as a mechanism initiating labour, or in addition whether they also represent gene changes in the myocytes themselves. We have made all our data available at www.ebi.ac.uk/arrayexpress/ (accession number E-MTAB-3136) to facilitate progression of this work. PMID:27176052
Novel Harmonic Regularization Approach for Variable Selection in Cox's Proportional Hazards Model
Chu, Ge-Jin; Liang, Yong; Wang, Jia-Xuan
2014-01-01
Variable selection is an important issue in regression and a number of variable selection methods have been proposed involving nonconvex penalty functions. In this paper, we investigate a novel harmonic regularization method, which can approximate nonconvex Lq (1/2 < q < 1) regularizations, to select key risk factors in the Cox's proportional hazards model using microarray gene expression data. The harmonic regularization method can be efficiently solved using our proposed direct path seeking approach, which can produce solutions that closely approximate those for the convex loss function and the nonconvex regularization. Simulation results based on the artificial datasets and four real microarray gene expression datasets, such as real diffuse large B-cell lymphoma (DCBCL), the lung cancer, and the AML datasets, show that the harmonic regularization method can be more accurate for variable selection than existing Lasso series methods. PMID:25506389
A Human Lectin Microarray for Sperm Surface Glycosylation Analysis *
Sun, Yangyang; Cheng, Li; Gu, Yihua; Xin, Aijie; Wu, Bin; Zhou, Shumin; Guo, Shujuan; Liu, Yin; Diao, Hua; Shi, Huijuan; Wang, Guangyu; Tao, Sheng-ce
2016-01-01
Glycosylation is one of the most abundant and functionally important protein post-translational modifications. As such, technology for efficient glycosylation analysis is in high demand. Lectin microarrays are a powerful tool for such investigations and have been successfully applied for a variety of glycobiological studies. However, most of the current lectin microarrays are primarily constructed from plant lectins, which are not well suited for studies of human glycosylation because of the extreme complexity of human glycans. Herein, we constructed a human lectin microarray with 60 human lectin and lectin-like proteins. All of the lectins and lectin-like proteins were purified from yeast, and most showed binding to human glycans. To demonstrate the applicability of the human lectin microarray, human sperm were probed on the microarray and strong bindings were observed for several lectins, including galectin-1, 7, 8, GalNAc-T6, and ERGIC-53 (LMAN1). These bindings were validated by flow cytometry and fluorescence immunostaining. Further, mass spectrometry analysis showed that galectin-1 binds several membrane-associated proteins including heat shock protein 90. Finally, functional assays showed that binding of galectin-8 could significantly enhance the acrosome reaction within human sperms. To our knowledge, this is the first construction of a human lectin microarray, and we anticipate it will find wide use for a range of human or mammalian studies, alone or in combination with plant lectin microarrays. PMID:27364157
Implementation of Quality Management in Core Service Laboratories
Creavalle, T.; Haque, K.; Raley, C.; Subleski, M.; Smith, M.W.; Hicks, B.
2010-01-01
CF-28 The Genetics and Genomics group of the Advanced Technology Program of SAIC-Frederick exists to bring innovative genomic expertise, tools and analysis to NCI and the scientific community. The Sequencing Facility (SF) provides next generation short read (Illumina) sequencing capacity to investigators using a streamlined production approach. The Laboratory of Molecular Technology (LMT) offers a wide range of genomics core services including microarray expression analysis, miRNA analysis, array comparative genome hybridization, long read (Roche) next generation sequencing, quantitative real time PCR, transgenic genotyping, Sanger sequencing, and clinical mutation detection services to investigators from across the NIH. As the technology supporting this genomic research becomes more complex, the need for basic quality processes within all aspects of the core service groups becomes critical. The Quality Management group works alongside members of these labs to establish or improve processes supporting operations control (equipment, reagent and materials management), process improvement (reengineering/optimization, automation, acceptance criteria for new technologies and tech transfer), and quality assurance and customer support (controlled documentation/SOPs, training, service deficiencies and continual improvement efforts). Implementation and expansion of quality programs within unregulated environments demonstrates SAIC-Frederick's dedication to providing the highest quality products and services to the NIH community.
Microarray analysis of retinal gene expression in chicks during imposed myopic defocus.
Schippert, Ruth; Schaeffel, Frank; Feldkaemper, Marita Pauline
2008-08-31
The retina plays an important regulatory role in ocular growth. To screen for new retinal candidate genes that could be involved in the inhibition of ocular growth, we used chick microarrays to analyze the changes in retinal mRNA expression after myopic defocus was imposed by positive lens wear. Four male white leghorn chicks, aged nine days, wore +6.9D spectacle lenses over both eyes for 24 h. Four untreated age-matched male chicks from the same batch served as controls. The chicks were euthanized, and retinas from both eyes of each chick were pooled. RNA was isolated and labeled cRNA was prepared. These samples were hybridized to Affymetrix GeneChip Chicken Genome arrays with more than 28,000 characterized genes. After comparison of multiple normalization methods, GC-RMA and a false-discovery rate of 6% was chosen for normalization of the data. The expression of 16 candidate genes was further studied, using semiquantitative real-time RT-PCR. In addition, the expression of the mRNA of some of these candidate genes was assessed in chicks that wore either +6.9D lenses for 4 h or -7D lenses for 24 h. 123 transcripts were found to be differentially expressed (p<0.05; at least 1.5-fold change in expression level), with an absolute mean fold-change of 1.97+/-1.16 (mean+/-standard deviation). Nine of the sixteen genes that were examined by real-time RT-PCR were validated. Regardless of whether positive or negative lenses were worn, six of these nine genes were regulated in the same direction after 24 h: arginyltransferase 1 (ATE1), E74-like factor 1 (ELF1), growth factor receptor-bound protein 2 (GRB2), SHQ1 homolog (S. cerevisiae) (SHQ1), spectrin, beta, non-erythrocytic 1 (SPTBN1), prepro-urotensin II-related peptide (pp-URP). Three genes responded differently to positive and negative lens treatment after 24 h: ATP-binding cassette, sub-family C, member 10 (ABCC10), CD226 molecule (CD226) and oxysterol binding protein 2 (OSBP2). The validated genes that were regulated only by myopic defocus may represent elements in a pathway generating a "stop-signal" for eye growth. Some of the genes identified in this study have so far not been described in the retina. Further investigation of their function may improve the understanding of the signaling cascades in emmetropization. More general, published microarray data are variable among different animal models (mouse, chick, monkeys), tissues (retina, retina/retinal pigment epithelium), treatments (diffusers, lenses, lid-suture), as well as different treatment durations (hours, days), and comparisons remain difficult. That only a small number of common genes were found emphasizes the need for careful normalization of the experimental parameters.
Classification of mislabelled microarrays using robust sparse logistic regression.
Bootkrajang, Jakramate; Kabán, Ata
2013-04-01
Previous studies reported that labelling errors are not uncommon in microarray datasets. In such cases, the training set may become misleading, and the ability of classifiers to make reliable inferences from the data is compromised. Yet, few methods are currently available in the bioinformatics literature to deal with this problem. The few existing methods focus on data cleansing alone, without reference to classification, and their performance crucially depends on some tuning parameters. In this article, we develop a new method to detect mislabelled arrays simultaneously with learning a sparse logistic regression classifier. Our method may be seen as a label-noise robust extension of the well-known and successful Bayesian logistic regression classifier. To account for possible mislabelling, we formulate a label-flipping process as part of the classifier. The regularization parameter is automatically set using Bayesian regularization, which not only saves the computation time that cross-validation would take, but also eliminates any unwanted effects of label noise when setting the regularization parameter. Extensive experiments with both synthetic data and real microarray datasets demonstrate that our approach is able to counter the bad effects of labelling errors in terms of predictive performance, it is effective at identifying marker genes and simultaneously it detects mislabelled arrays to high accuracy. The code is available from http://cs.bham.ac.uk/∼jxb008. Supplementary data are available at Bioinformatics online.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Hatazawa, Yukino; Research Fellow of Japan Society for the Promotion of Science, Tokyo; Minami, Kimiko
The expression of the transcriptional coactivator PGC1α is increased in skeletal muscles during exercise. Previously, we showed that increased PGC1α leads to prolonged exercise performance (the duration for which running can be continued) and, at the same time, increases the expression of branched-chain amino acid (BCAA) metabolism-related enzymes and genes that are involved in supplying substrates for the TCA cycle. We recently created mice with PGC1α knockout specifically in the skeletal muscles (PGC1α KO mice), which show decreased mitochondrial content. In this study, global gene expression (microarray) analysis was performed in the skeletal muscles of PGC1α KO mice compared withmore » that of wild-type control mice. As a result, decreased expression of genes involved in the TCA cycle, oxidative phosphorylation, and BCAA metabolism were observed. Compared with previously obtained microarray data on PGC1α-overexpressing transgenic mice, each gene showed the completely opposite direction of expression change. Bioinformatic analysis of the promoter region of genes with decreased expression in PGC1α KO mice predicted the involvement of several transcription factors, including a nuclear receptor, ERR, in their regulation. As PGC1α KO microarray data in this study show opposing findings to the PGC1α transgenic data, a loss-of-function experiment, as well as a gain-of-function experiment, revealed PGC1α’s function in the oxidative energy metabolism of skeletal muscles. - Highlights: • Microarray analysis was performed in the skeletal muscle of PGC1α KO mice. • Expression of genes in the oxidative energy metabolism was decreased. • Bioinformatic analysis of promoter region of the genes predicted involvement of ERR. • PGC1α KO microarray data in this study show the mirror image of transgenic data.« less
Transcriptomic Analysis and Meta-Analysis of Human Granulosa and Cumulus Cells
Burnik Papler, Tanja; Vrtacnik Bokal, Eda; Maver, Ales; Kopitar, Andreja Natasa; Lovrečić, Luca
2015-01-01
Specific gene expression in oocytes and its surrounding cumulus (CC) and granulosa (GC) cells is needed for successful folliculogenesis and oocyte maturation. The aim of the present study was to compare genome-wide gene expression and biological functions of human GC and CC. Individual GC and CC were derived from 37 women undergoing IVF procedures. Gene expression analysis was performed using microarrays, followed by a meta-analysis. Results were validated using quantitative real-time PCR. There were 6029 differentially expressed genes (q < 10−4); of which 650 genes had a log2 FC ≥ 2. After the meta-analysis there were 3156 genes differentially expressed. Among these there were genes that have previously not been reported in human somatic follicular cells, like prokineticin 2 (PROK2), higher expressed in GC, and pregnancy up-regulated nonubiquitous CaM kinase (PNCK), higher expressed in CC. Pathways like inflammatory response and angiogenesis were enriched in GC, whereas in CC, cell differentiation and multicellular organismal development were among enriched pathways. In conclusion, transcriptomes of GC and CC as well as biological functions, are distinctive for each cell subpopulation. By describing novel genes like PROK2 and PNCK, expressed in GC and CC, we upgraded the existing data on human follicular biology. PMID:26313571
Draghici, Sorin; Tarca, Adi L; Yu, Longfei; Ethier, Stephen; Romero, Roberto
2008-03-01
The BioArray Software Environment (BASE) is a very popular MIAME-compliant, web-based microarray data repository. However in BASE, like in most other microarray data repositories, the experiment annotation and raw data uploading can be very timeconsuming, especially for large microarray experiments. We developed KUTE (Karmanos Universal daTabase for microarray Experiments), as a plug-in for BASE 2.0 that addresses these issues. KUTE provides an automatic experiment annotation feature and a completely redesigned data work-flow that dramatically reduce the human-computer interaction time. For instance, in BASE 2.0 a typical Affymetrix experiment involving 100 arrays required 4 h 30 min of user interaction time forexperiment annotation, and 45 min for data upload/download. In contrast, for the same experiment, KUTE required only 28 min of user interaction time for experiment annotation, and 3.3 min for data upload/download. http://vortex.cs.wayne.edu/kute/index.html.
A multilevel Lab on chip platform for DNA analysis.
Marasso, Simone Luigi; Giuri, Eros; Canavese, Giancarlo; Castagna, Riccardo; Quaglio, Marzia; Ferrante, Ivan; Perrone, Denis; Cocuzza, Matteo
2011-02-01
Lab-on-chips (LOCs) are critical systems that have been introduced to speed up and reduce the cost of traditional, laborious and extensive analyses in biological and biomedical fields. These ambitious and challenging issues ask for multi-disciplinary competences that range from engineering to biology. Starting from the aim to integrate microarray technology and microfluidic devices, a complex multilevel analysis platform has been designed, fabricated and tested (All rights reserved-IT Patent number TO2009A000915). This LOC successfully manages to interface microfluidic channels with standard DNA microarray glass slides, in order to implement a complete biological protocol. Typical Micro Electro Mechanical Systems (MEMS) materials and process technologies were employed. A silicon/glass microfluidic chip and a Polydimethylsiloxane (PDMS) reaction chamber were fabricated and interfaced with a standard microarray glass slide. In order to have a high disposable system all micro-elements were passive and an external apparatus provided fluidic driving and thermal control. The major microfluidic and handling problems were investigated and innovative solutions were found. Finally, an entirely automated DNA hybridization protocol was successfully tested with a significant reduction in analysis time and reagent consumption with respect to a conventional protocol.
Overcoming bias and systematic errors in next generation sequencing data.
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.
PRACTICAL STRATEGIES FOR PROCESSING AND ANALYZING SPOTTED OLIGONUCLEOTIDE MICROARRAY DATA
Thoughtful data analysis is as important as experimental design, biological sample quality, and appropriate experimental procedures for making microarrays a useful supplement to traditional toxicology. In the present study, spotted oligonucleotide microarrays were used to profile...
permGPU: Using graphics processing units in RNA microarray association studies.
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.
Genome image programs: visualization and interpretation of Escherichia coli microarray experiments.
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
A Customized DNA Microarray for Microbial Source Tracking ...
It is estimated that more than 160, 000 miles of rivers and streams in the United States are impaired due to the presence of waterborne pathogens. These pathogens typically originate from human and other animal fecal pollution sources; therefore, a rapid microbial source tracking (MST) method is needed to facilitate water quality assessment and impaired water remediation. We report a novel qualitative DNA microarray technology consisting of 453 probes for the detection of general fecal and host-associated bacteria, viruses, antibiotic resistance, and other environmentally relevant genetic indicators. A novel data normalization and reduction approach is also presented to help alleviate false positives often associated with high-density microarray applications. To evaluate the performance of the approach, DNA and cDNA was isolated from swine, cattle, duck, goose and gull fecal reference samples, as well as soiled poultry liter and raw municipal sewage. Based on nonmetric multidimensional scaling analysis of results, findings suggest that the novel microarray approach may be useful for pathogen detection and identification of fecal contamination in recreational waters. The ability to simultaneously detect a large collection of environmentally important genetic indicators in a single test has the potential to provide water quality managers with a wide range of information in a short period of time. Future research is warranted to measure microarray performance i
Analytical Protein Microarrays: Advancements Towards Clinical Applications
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
Arsenic exposure triggers a shift in microRNA expression.
Sturchio, Elena; Colombo, Teresa; Boccia, Priscilla; Carucci, Nicoletta; Meconi, Claudia; Minoia, Claudio; Macino, Giuseppe
2014-02-15
Exposure to inorganic Arsenic (iAs) through drinking water is a major public health problem affecting most countries. iAs has been classified by the International Agency for Research on Cancer as Group 1: "Carcinogenic to humans". Although numerous studies have shown the related adverse effects of iAs, sensitive appropriate biomarkers for studies of environmental epidemiology are still required. The present work aims at investigate the role of microRNAs (miRNAs), powerful negative regulators of gene expression, playing a key role in many physiological and pathological cellular processes, in iAs exposure. To this end, we analyzed miRNA changes in expression profile triggered by iAs exposure in Jurkat cell line. We used microarray technology to profile the expression of miRNAs following 2 μmol/L sodium arsenite treatment at different time points. Moreover, we performed phenotypic analysis of iAs treated cells. Real Time Polymerase Chain Reaction (RT-PCR) was used to validate miRNA microarray data and to assay expression modulation of selected relevant mRNAs. Finally, bioinformatics techniques were applied to reconstruct iAs-relevant molecular pathways and miRNA regulatory networks from the expression data. We report miRNAs modulated after iAs treatment in Jurkat cells. In particular, we highlight 36 miRNAs exhibiting consistent dysregulation and particularly a panel of 8 miRNAs which we also validated by RT-PCR analysis. Computational analysis of lists of putative target genes for these 8 miRNAs points to an involvement in arsenic-response pathways, for a subset of them, that were analyzed by RT-PCR. Furthermore, iAs exposure reveals induction of cell cycle progression and the failure of apoptosis, supporting the idea of iAs carcinogenic activity. Our study provides a list of miRNAs whose expression levels are affected by iAs treatment, corroborating the importance of proceeding with the hunt for specific subset of miRNAs, which can serve as potential biomarkers of iAs effects with useful diagnostic value. Copyright © 2013 Elsevier B.V. All rights reserved.
A cDNA microarray gene expression data classifier for clinical diagnostics based on graph theory.
Benso, Alfredo; Di Carlo, Stefano; Politano, Gianfranco
2011-01-01
Despite great advances in discovering cancer molecular profiles, the proper application of microarray technology to routine clinical diagnostics is still a challenge. Current practices in the classification of microarrays' data show two main limitations: the reliability of the training data sets used to build the classifiers, and the classifiers' performances, especially when the sample to be classified does not belong to any of the available classes. In this case, state-of-the-art algorithms usually produce a high rate of false positives that, in real diagnostic applications, are unacceptable. To address this problem, this paper presents a new cDNA microarray data classification algorithm based on graph theory and is able to overcome most of the limitations of known classification methodologies. The classifier works by analyzing gene expression data organized in an innovative data structure based on graphs, where vertices correspond to genes and edges to gene expression relationships. To demonstrate the novelty of the proposed approach, the authors present an experimental performance comparison between the proposed classifier and several state-of-the-art classification algorithms.
A common-path phase-shift interferometry surface plasmon imaging system
NASA Astrophysics Data System (ADS)
Su, Y.-T.; Chen, Shean-Jen; Yeh, T.-L.
2005-03-01
A biosensing imaging system is proposed based on the integration of surface plasmon resonance (SPR) and common-path phase-shift interferometry (PSI) techniques to measure the two-dimensional spatial phase variation caused by biomolecular interactions upon a sensing chip. The SPR phase imaging system can offer high resolution and high-throughout screening capabilities to analyze microarray biomolecular interaction without the need for additional labeling. With the long-term stability advantage of the common-path PSI technique even with external disturbances such as mechanical vibration, buffer flow noise, and laser unstable issue, the system can match the demand of real-time kinetic study for biomolecular interaction analysis (BIA). The SPR-PSI imaging system has achieved a detection limit of 2×10-7 refraction index change, a long-term phase stability of 2.5x10-4π rms over four hours, and a spatial phase resolution of 10-3 π with a lateral resolution of 100μm.
NASA Astrophysics Data System (ADS)
Babbick, Maren; Hampp, Rudiger
2005-08-01
Callus cultures of Arabidopsis thaliana (cv. Columbia) were used to screen for early changes in gene expression in response to altered gravitational fields. In a recent microarray study we found hyper- g dependent changes in gene expression which indicated the involvement of WRKY genes [Martzivanou M. and Hampp R., Physiol. Plant., 118, 221-231,2003]. WRKY genes code for a family of plant-specific regulators of gene expression. In this study we report on the exposure of Arabidopsis callus cultures to 8g for up to 30 min. Quantitative analysis by real time RT-PCR of the amount of transcripts of WRKYs 3, 6, 22, 46, 65 and 70 showed individual changes in expression. As far as their function is known, these WRKY proteins are mainly involved in stress responses. As most alterations in transcript amount occurred within 10 min of treatment, such genes can be used for the investigation of microgravity-related effects on gene expression under sounding rocket conditions (TEXUS, MAXUS).
Todorovic, Vesna; Sersa, Gregor; Mlakar, Vid; Glavac, Damjan; Cemazar, Maja
2012-01-01
Background Electrochemotherapy is a local treatment combining chemotherapy and electroporation and is highly effective treatment approach for subcutaneous tumours of various histologies. Contrary to surgery and radiation, the effect of electrochemotherapy on metastatic potential of tumour cells has not been extensively studied. The aim of the study was to evaluate the effect of electrochemotherapy with bleomycin on the metastatic potential of human melanoma cells in vitro. Materials and methods Viable cells 48 hours after electrochemotherapy were tested for their ability to migrate and invade through Matrigel coated porous membrane. In addition, microarray analysis and quantitative Real-Time PCR were used to detect changes in gene expression after electrochemotherapy. Results Cell migration and invasion were not changed in melanoma cells surviving electrochemotherapy. Interestingly, only a low number of tumourigenesis related genes was differentially expressed after electrochemotherapy. Conclusions Our data suggest that metastatic potential of human melanoma cells is not affected by electrochemotherapy with bleomycin, confirming safe role of electrochemotherapy in the clinics. PMID:22933978
Todorovic, Vesna; Sersa, Gregor; Mlakar, Vid; Glavac, Damjan; Cemazar, Maja
2012-03-01
Electrochemotherapy is a local treatment combining chemotherapy and electroporation and is highly effective treatment approach for subcutaneous tumours of various histologies. Contrary to surgery and radiation, the effect of electrochemotherapy on metastatic potential of tumour cells has not been extensively studied. The aim of the study was to evaluate the effect of electrochemotherapy with bleomycin on the metastatic potential of human melanoma cells in vitro. Viable cells 48 hours after electrochemotherapy were tested for their ability to migrate and invade through Matrigel coated porous membrane. In addition, microarray analysis and quantitative Real-Time PCR were used to detect changes in gene expression after electrochemotherapy. Cell migration and invasion were not changed in melanoma cells surviving electrochemotherapy. Interestingly, only a low number of tumourigenesis related genes was differentially expressed after electrochemotherapy. Our data suggest that metastatic potential of human melanoma cells is not affected by electrochemotherapy with bleomycin, confirming safe role of electrochemotherapy in the clinics.
RNA sequencing: current and prospective uses in metabolic research.
Vikman, Petter; Fadista, Joao; Oskolkov, Nikolay
2014-10-01
Previous global RNA analysis was restricted to known transcripts in species with a defined transcriptome. Next generation sequencing has transformed transcriptomics by making it possible to analyse expressed genes with an exon level resolution from any tissue in any species without any a priori knowledge of which genes that are being expressed, splice patterns or their nucleotide sequence. In addition, RNA sequencing is a more sensitive technique compared with microarrays with a larger dynamic range, and it also allows for investigation of imprinting and allele-specific expression. This can be done for a cost that is able to compete with that of a microarray, making RNA sequencing a technique available to most researchers. Therefore RNA sequencing has recently become the state of the art with regards to large-scale RNA investigations and has to a large extent replaced microarrays. The only drawback is the large data amounts produced, which together with the complexity of the data can make a researcher spend far more time on analysis than performing the actual experiment. © 2014 Society for Endocrinology.
Giancarlo, Raffaele; Scaturro, Davide; Utro, Filippo
2008-10-29
Inferring cluster structure in microarray datasets is a fundamental task for the so-called -omic sciences. It is also a fundamental question in Statistics, Data Analysis and Classification, in particular with regard to the prediction of the number of clusters in a dataset, usually established via internal validation measures. Despite the wealth of internal measures available in the literature, new ones have been recently proposed, some of them specifically for microarray data. We consider five such measures: Clest, Consensus (Consensus Clustering), FOM (Figure of Merit), Gap (Gap Statistics) and ME (Model Explorer), in addition to the classic WCSS (Within Cluster Sum-of-Squares) and KL (Krzanowski and Lai index). We perform extensive experiments on six benchmark microarray datasets, using both Hierarchical and K-means clustering algorithms, and we provide an analysis assessing both the intrinsic ability of a measure to predict the correct number of clusters in a dataset and its merit relative to the other measures. We pay particular attention both to precision and speed. Moreover, we also provide various fast approximation algorithms for the computation of Gap, FOM and WCSS. The main result is a hierarchy of those measures in terms of precision and speed, highlighting some of their merits and limitations not reported before in the literature. Based on our analysis, we draw several conclusions for the use of those internal measures on microarray data. We report the main ones. Consensus is by far the best performer in terms of predictive power and remarkably algorithm-independent. Unfortunately, on large datasets, it may be of no use because of its non-trivial computer time demand (weeks on a state of the art PC). FOM is the second best performer although, quite surprisingly, it may not be competitive in this scenario: it has essentially the same predictive power of WCSS but it is from 6 to 100 times slower in time, depending on the dataset. The approximation algorithms for the computation of FOM, Gap and WCSS perform very well, i.e., they are faster while still granting a very close approximation of FOM and WCSS. The approximation algorithm for the computation of Gap deserves to be singled-out since it has a predictive power far better than Gap, it is competitive with the other measures, but it is at least two order of magnitude faster in time with respect to Gap. Another important novel conclusion that can be drawn from our analysis is that all the measures we have considered show severe limitations on large datasets, either due to computational demand (Consensus, as already mentioned, Clest and Gap) or to lack of precision (all of the other measures, including their approximations). The software and datasets are available under the GNU GPL on the supplementary material web page.
GeneXplorer: an interactive web application for microarray data visualization and analysis.
Rees, Christian A; Demeter, Janos; Matese, John C; Botstein, David; Sherlock, Gavin
2004-10-01
When publishing large-scale microarray datasets, it is of great value to create supplemental websites where either the full data, or selected subsets corresponding to figures within the paper, can be browsed. We set out to create a CGI application containing many of the features of some of the existing standalone software for the visualization of clustered microarray data. We present GeneXplorer, a web application for interactive microarray data visualization and analysis in a web environment. GeneXplorer allows users to browse a microarray dataset in an intuitive fashion. It provides simple access to microarray data over the Internet and uses only HTML and JavaScript to display graphic and annotation information. It provides radar and zoom views of the data, allows display of the nearest neighbors to a gene expression vector based on their Pearson correlations and provides the ability to search gene annotation fields. The software is released under the permissive MIT Open Source license, and the complete documentation and the entire source code are freely available for download from CPAN http://search.cpan.org/dist/Microarray-GeneXplorer/.
Raymond, Frédéric; Carbonneau, Julie; Boucher, Nancy; Robitaille, Lynda; Boisvert, Sébastien; Wu, Whei-Kuo; De Serres, Gaston; Boivin, Guy; Corbeil, Jacques
2009-01-01
Respiratory virus infections are a major health concern and represent the primary cause of testing consultation and hospitalization for young children. We developed and compared two assays that allow the detection of up to 23 different respiratory viruses that frequently infect children. The first method consisted of single TaqMan quantitative real-time PCR assays in a 96-well-plate format. The second consisted of a multiplex PCR followed by primer extension and microarray hybridization in an integrated molecular diagnostic device, the Infiniti analyzer. Both of our assays can detect adenoviruses of groups A, B, C, and E; coronaviruses HKU1, 229E, NL63, and OC43; enteroviruses A, B, C, and D; rhinoviruses of genotypes A and B; influenza viruses A and B; human metapneumoviruses (HMPV) A and B, human respiratory syncytial viruses (HRSV) A and B; and parainfluenza viruses of types 1, 2, and 3. These tests were used to identify viruses in 221 nasopharyngeal aspirates obtained from children hospitalized for respiratory tract infections. Respiratory viruses were detected with at least one of the two methods in 81.4% of the 221 specimens: 10.0% were positive for HRSV A, 38.0% for HRSV B, 13.1% for influenzavirus A, 8.6% for any coronaviruses, 13.1% for rhinoviruses or enteroviruses, 7.2% for adenoviruses, 4.1% for HMPV, and 1.5% for parainfluenzaviruses. Multiple viral infections were found in 13.1% of the specimens. The two methods yielded concordant results for 94.1% of specimens. These tests allowed a thorough etiological assessment of respiratory viruses infecting children in hospital settings and would assist public health interventions. PMID:19158263
Raymond, Frédéric; Carbonneau, Julie; Boucher, Nancy; Robitaille, Lynda; Boisvert, Sébastien; Wu, Whei-Kuo; De Serres, Gaston; Boivin, Guy; Corbeil, Jacques
2009-03-01
Respiratory virus infections are a major health concern and represent the primary cause of testing consultation and hospitalization for young children. We developed and compared two assays that allow the detection of up to 23 different respiratory viruses that frequently infect children. The first method consisted of single TaqMan quantitative real-time PCR assays in a 96-well-plate format. The second consisted of a multiplex PCR followed by primer extension and microarray hybridization in an integrated molecular diagnostic device, the Infiniti analyzer. Both of our assays can detect adenoviruses of groups A, B, C, and E; coronaviruses HKU1, 229E, NL63, and OC43; enteroviruses A, B, C, and D; rhinoviruses of genotypes A and B; influenza viruses A and B; human metapneumoviruses (HMPV) A and B, human respiratory syncytial viruses (HRSV) A and B; and parainfluenza viruses of types 1, 2, and 3. These tests were used to identify viruses in 221 nasopharyngeal aspirates obtained from children hospitalized for respiratory tract infections. Respiratory viruses were detected with at least one of the two methods in 81.4% of the 221 specimens: 10.0% were positive for HRSV A, 38.0% for HRSV B, 13.1% for influenzavirus A, 8.6% for any coronaviruses, 13.1% for rhinoviruses or enteroviruses, 7.2% for adenoviruses, 4.1% for HMPV, and 1.5% for parainfluenzaviruses. Multiple viral infections were found in 13.1% of the specimens. The two methods yielded concordant results for 94.1% of specimens. These tests allowed a thorough etiological assessment of respiratory viruses infecting children in hospital settings and would assist public health interventions.
Ohtsuka, Yoshikazu; Ikegami, Takako; Izumi, Hirohisa; Namura, Mariko; Ikeda, Tomomi; Ikuse, Tamaki; Baba, Yosuke; Kudo, Takahiro; Suzuki, Ryuyo; Shimizu, Toshiaki
2012-01-01
To examine the immune-modulatory effects of probiotics during early infancy, Bifidobacterium breve M-16V (B. breve) was administered to rat pups during the newborn or weaning period, and the expression of inflammatory genes was investigated using a cDNA microarray and real-time PCR. After B. breve administration, significant increases in the numbers of Bifidobacterium in both the cecum and colon were confirmed during the newborn period. The numbers of upregulated and downregulated genes were greater during the weaning period than in the newborn period and were greatest in the colon, with fewer genes altered in the small intestine and the fewest in the spleen. The expression of inflammation-related genes, including lipoprotein lipase (Lpl), glutathione peroxidase 2 (Gpx2), and lipopolysaccharide-binding protein (Lbp), was significantly reduced in the colon during the newborn period. In weaning rat pups, the expression of CD3d, a cell surface receptor-linked signaling molecule, was significantly enhanced in the colon; however, the expression of co-stimulatory molecules was not enhanced. Our findings support a possible role for B. breve in mediating anti-inflammatory and antiallergic reactions by modulating the expression of inflammatory molecules during the newborn period and by regulating the expression of co-stimulatory molecules during the weaning period. Gene expression in the intestine was investigated after feeding 5 × 10(8) cfu of B. breve every day to the F344/Du rat from days 1 to 14 (newborn group) and from days 21 to 34 (weaning group). mRNA was extracted from intestine, and the expression of inflammatory gene was analyzed by microarray and real-time PCR.
Kobayashi, Kazuhiro; Hama, Takanori; Murakami, Kasumi; Ogawa, Rei
2016-01-01
Objective: In this study, we evaluated the effect of scalp massage on hair in Japanese males and the effect of stretching forces on human dermal papilla cells in vitro. Methods: Nine healthy men received 4 minutes of standardized scalp massage per day for 24 weeks using a scalp massage device. Total hair number, hair thickness, and hair growth rate were evaluated. The mechanical effect of scalp massage on subcutaneous tissue was analyzed using a finite element method. To evaluate the effect of mechanical forces, human dermal papilla cells were cultured using a 72-hour stretching cycle. Gene expression change was analyzed using DNA microarray analyses. In addition, expression of hair cycle-related genes including IL6, NOGGIN, BMP4, and SMAD4 were evaluated using real-time reverse transcription-polymerase chain reaction. Results: Standardized scalp massage resulted in increased hair thickness 24 weeks after initiation of massage (0.085 ± 0.003 mm vs 0.092 ± 0.001 mm). Finite element method showed that scalp massage caused z-direction displacement and von Mises stress on subcutaneous tissue. In vitro, DNA microarray showed gene expression change significantly compared with nonstretching human dermal papilla cells. A total of 2655 genes were upregulated and 2823 genes were downregulated. Real-time reverse transcription-polymerase chain reaction demonstrated increased expression of hair cycle–related genes such as NOGGIN, BMP4, SMAD4, and IL6ST and decrease in hair loss–related genes such as IL6. Conclusions: Stretching forces result in changes in gene expression in human dermal papilla cells. Standardized scalp massage is a way to transmit mechanical stress to human dermal papilla cells in subcutaneous tissue. Hair thickness was shown to increase with standardized scalp massage. PMID:26904154
Gene expression profiling in human skeletal muscle during recovery from eccentric exercise
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
Statistical design of quantitative mass spectrometry-based proteomic experiments.
Oberg, Ann L; Vitek, Olga
2009-05-01
We review the fundamental principles of statistical experimental design, and their application to quantitative mass spectrometry-based proteomics. We focus on class comparison using Analysis of Variance (ANOVA), and discuss how randomization, replication and blocking help avoid systematic biases due to the experimental procedure, and help optimize our ability to detect true quantitative changes between groups. We also discuss the issues of pooling multiple biological specimens for a single mass analysis, and calculation of the number of replicates in a future study. When applicable, we emphasize the parallels between designing quantitative proteomic experiments and experiments with gene expression microarrays, and give examples from that area of research. We illustrate the discussion using theoretical considerations, and using real-data examples of profiling of disease.
Hu, Ruibo; Chi, Xiaoyuan; Chai, Guohua; Kong, Yingzhen; He, Guo; Wang, Xiaoyu; Shi, Dachuan; Zhang, Dongyuan; Zhou, Gongke
2012-01-01
Background Homeodomain-leucine zipper (HD-ZIP) proteins are plant-specific transcriptional factors known to play crucial roles in plant development. Although sequence phylogeny analysis of Populus HD-ZIPs was carried out in a previous study, no systematic analysis incorporating genome organization, gene structure, and expression compendium has been conducted in model tree species Populus thus far. Principal Findings In this study, a comprehensive analysis of Populus HD-ZIP gene family was performed. Sixty-three full-length HD-ZIP genes were found in Populus genome. These Populus HD-ZIP genes were phylogenetically clustered into four distinct subfamilies (HD-ZIP I–IV) and predominately distributed across 17 linkage groups (LG). Fifty genes from 25 Populus paralogous pairs were located in the duplicated blocks of Populus genome and then preferentially retained during the sequential evolutionary courses. Genomic organization analyses indicated that purifying selection has played a pivotal role in the retention and maintenance of Populus HD-ZIP gene family. Microarray analysis has shown that 21 Populus paralogous pairs have been differentially expressed across different tissues and under various stresses, with five paralogous pairs showing nearly identical expression patterns, 13 paralogous pairs being partially redundant and three paralogous pairs diversifying significantly. Quantitative real-time RT-PCR (qRT-PCR) analysis performed on 16 selected Populus HD-ZIP genes in different tissues and under both drought and salinity stresses confirms their tissue-specific and stress-inducible expression patterns. Conclusions Genomic organizations indicated that segmental duplications contributed significantly to the expansion of Populus HD-ZIP gene family. Exon/intron organization and conserved motif composition of Populus HD-ZIPs are highly conservative in the same subfamily, suggesting the members in the same subfamilies may also have conservative functionalities. Microarray and qRT-PCR analyses showed that 89% (56 out of 63) of Populus HD-ZIPs were duplicate genes that might have been retained by substantial subfunctionalization. Taken together, these observations may lay the foundation for future functional analysis of Populus HD-ZIP genes to unravel their biological roles. PMID:22359569
SimArray: a user-friendly and user-configurable microarray design tool
Auburn, Richard P; Russell, Roslin R; Fischer, Bettina; Meadows, Lisa A; Sevillano Matilla, Santiago; Russell, Steven
2006-01-01
Background Microarrays were first developed to assess gene expression but are now also used to map protein-binding sites and to assess allelic variation between individuals. Regardless of the intended application, efficient production and appropriate array design are key determinants of experimental success. Inefficient production can make larger-scale studies prohibitively expensive, whereas poor array design makes normalisation and data analysis problematic. Results We have developed a user-friendly tool, SimArray, which generates a randomised spot layout, computes a maximum meta-grid area, and estimates the print time, in response to user-specified design decisions. Selected parameters include: the number of probes to be printed; the microtitre plate format; the printing pin configuration, and the achievable spot density. SimArray is compatible with all current robotic spotters that employ 96-, 384- or 1536-well microtitre plates, and can be configured to reflect most production environments. Print time and maximum meta-grid area estimates facilitate evaluation of each array design for its suitability. Randomisation of the spot layout facilitates correction of systematic biases by normalisation. Conclusion SimArray is intended to help both established researchers and those new to the microarray field to develop microarray designs with randomised spot layouts that are compatible with their specific production environment. SimArray is an open-source program and is available from . PMID:16509966
van Huet, Ramon A. C.; Pierrache, Laurence H.M.; Meester-Smoor, Magda A.; Klaver, Caroline C.W.; van den Born, L. Ingeborgh; Hoyng, Carel B.; de Wijs, Ilse J.; Collin, Rob W. J.; Hoefsloot, Lies H.
2015-01-01
Purpose To determine the efficacy of multiple versions of a commercially available arrayed primer extension (APEX) microarray chip for autosomal recessive retinitis pigmentosa (arRP). Methods We included 250 probands suspected of arRP who were genetically analyzed with the APEX microarray between January 2008 and November 2013. The mode of inheritance had to be autosomal recessive according to the pedigree (including isolated cases). If the microarray identified a heterozygous mutation, we performed Sanger sequencing of exons and exon–intron boundaries of that specific gene. The efficacy of this microarray chip with the additional Sanger sequencing approach was determined by the percentage of patients that received a molecular diagnosis. We also collected data from genetic tests other than the APEX analysis for arRP to provide a detailed description of the molecular diagnoses in our study cohort. Results The APEX microarray chip for arRP identified the molecular diagnosis in 21 (8.5%) of the patients in our cohort. Additional Sanger sequencing yielded a second mutation in 17 patients (6.8%), thereby establishing the molecular diagnosis. In total, 38 patients (15.2%) received a molecular diagnosis after analysis using the microarray and additional Sanger sequencing approach. Further genetic analyses after a negative result of the arRP microarray (n = 107) resulted in a molecular diagnosis of arRP (n = 23), autosomal dominant RP (n = 5), X-linked RP (n = 2), and choroideremia (n = 1). Conclusions The efficacy of the commercially available APEX microarray chips for arRP appears to be low, most likely caused by the limitations of this technique and the genetic and allelic heterogeneity of RP. Diagnostic yields up to 40% have been reported for next-generation sequencing (NGS) techniques that, as expected, thereby outperform targeted APEX analysis. PMID:25999674
Nowrousian, Minou
2009-04-01
During fungal fruiting body development, hyphae aggregate to form multicellular structures that protect and disperse the sexual spores. Analysis of microarray data revealed a gene cluster strongly upregulated during fruiting body development in the ascomycete Sordaria macrospora. Real time PCR analysis showed that the genes from the orthologous cluster in Neurospora crassa are also upregulated during development. The cluster encodes putative polyketide biosynthesis enzymes, including a reducing polyketide synthase. Analysis of knockout strains of a predicted dehydrogenase gene from the cluster showed that mutants in N. crassa and S. macrospora are delayed in fruiting body formation. In addition to the upregulated cluster, the N. crassa genome comprises another cluster containing a polyketide synthase gene, and five additional reducing polyketide synthase (rpks) genes that are not part of clusters. To study the role of these genes in sexual development, expression of the predicted rpks genes in S. macrospora (five genes) and N. crassa (six genes) was analyzed; all but one are upregulated during sexual development. Analysis of knockout strains for the N. crassa rpks genes showed that one of them is essential for fruiting body formation. These data indicate that polyketides produced by RPKSs are involved in sexual development in filamentous ascomycetes.
Wieghaus, Kristen A.; Gianchandani, Erwin P.; Neal, Rebekah A.; Paige, Mikell A.; Brown, Milton L.; Papin, Jason A.; Botchwey, Edward A.
2009-01-01
We are creating synthetic pharmaceuticals with angiogenic activity and potential to promote vascular invasion. We previously demonstrated that one of these molecules, phthalimide neovascular factor 1 (PNF1), significantly expands microvascular networks in vivo following sustained release from poly(lactic-co-glycolic acid) (PLAGA) films. In addition, to probe PNF1 mode-of-action, we recently applied a novel pathway-based compendium analysis to a multi-timepoint, controlled microarray dataset of PNF1-treated (versus control) human microvascular endothelial cells (HMVECs), and we identified induction of tumor necrosis factor-alpha (TNF-α) and, subsequently, transforming growth factor-beta (TGF-β) signaling networks by PNF1. Here we validate this microarray data-set with quantitative real-time polymerase chain reaction (RT-PCR) analysis. Subsequently, we probe this dataset and identify three specific TGF-β-induced genes with regulation by PNF1 conserved over multiple timepoints—amyloid beta (A4) precursor protein (APP), early growth response 1 (EGR-1), and matrix metalloproteinase 14 (MMP14 or MT1-MMP)—that are also implicated in angiogenesis. We further focus on MMP14 given its unique role in angiogenesis, and we validate MT1-MMP modulation by PNF1 with an in vitro fluorescence assay that demonstrates the direct effects that PNF1 exerts on functional metalloproteinase activity. We also utilize endothelial cord formation in collagen gels to show that PNF1-induced stimulation of endothelial cord network formation in vitro is in some way MT1-MMP-dependent. Ultimately, this new network analysis of our transcriptional footprint characterizing PNF1 activity 1–48 h post-supplementation in HMVECs coupled with corresponding validating experiments suggests a key set of a few specific targets that are involved in PNF1 mode-of-action and important for successful promotion of the neovascularization that we have observed by the drug in vivo. PMID:19326468
Wieghaus, Kristen A; Gianchandani, Erwin P; Neal, Rebekah A; Paige, Mikell A; Brown, Milton L; Papin, Jason A; Botchwey, Edward A
2009-07-01
We are creating synthetic pharmaceuticals with angiogenic activity and potential to promote vascular invasion. We previously demonstrated that one of these molecules, phthalimide neovascular factor 1 (PNF1), significantly expands microvascular networks in vivo following sustained release from poly(lactic-co-glycolic acid) (PLAGA) films. In addition, to probe PNF1 mode of action, we recently applied a novel pathway-based compendium analysis to a multi-timepoint, controlled microarray data set of PNF1-treated (vs. control) human microvascular endothelial cells (HMVECs), and we identified induction of tumor necrosis factor-alpha (TNF-alpha) and, subsequently, transforming growth factor-beta (TGF-beta) signaling networks by PNF1. Here we validate this microarray data set with quantitative real-time polymerase chain reaction (RT-PCR) analysis. Subsequently, we probe this data set and identify three specific TGF-beta-induced genes with regulation by PNF1 conserved over multiple timepoints-amyloid beta (A4) precursor protein (APP), early growth response 1 (EGR-1), and matrix metalloproteinase 14 (MMP14 or MT1-MMP)-that are also implicated in angiogenesis. We further focus on MMP14 given its unique role in angiogenesis, and we validate MT1-MMP modulation by PNF1 with an in vitro fluorescence assay that demonstrates the direct effects that PNF1 exerts on functional metalloproteinase activity. We also utilize endothelial cord formation in collagen gels to show that PNF1-induced stimulation of endothelial cord network formation in vitro is in some way MT1-MMP-dependent. Ultimately, this new network analysis of our transcriptional footprint characterizing PNF1 activity 1-48 h post-supplementation in HMVECs coupled with corresponding validating experiments suggests a key set of a few specific targets that are involved in PNF1 mode of action and important for successful promotion of the neovascularization that we have observed by the drug in vivo.
Host responses of Japanese flounder Paralichthys olivaceus with lymphocystis cell formation.
Iwakiri, Shogo; Song, Jun-Young; Nakayama, Kei; Oh, Myung-Joo; Ishida, Minoru; Kitamura, Shin-Ichi
2014-06-01
Lymphocystis disease virus (LCDV) is the causative agent of lymphocystis disease (LCD). In this study, we investigated the mechanisms of lymphocystis cell (LCC) formation from the viewpoint of gene expression changes in the infected fish. LCC occurrence and virus titers in the experimentally infected Japanese flounder, Paralichthys olivaceus were monitored by visual confirmation and real-time PCR, respectively. The gene expression changes in the fish fin were investigated by microarray experiments. LCCs firstly appeared in the fish at 21 days post infection (dpi). LCD incidence increased with time and reached 92.9% at 62 dpi. LCDV genome was firstly detected from dorsal fins at 14 dpi, and the relative amount of the genome gradually-increased until 56 dpi. Since the occurrence of LCC was approximately synchronized with increasing of the virus genome, virus replication might play important roles for LCC formation. The microarray detected a few gene expression changes until 28 dpi. However, the number of expression changed genes dramatically increased between 28 and 42 dpi in which LCCs formation was active. From the microarray data analyses, apoptosis and cell division related genes were down-regulated, whereas cell fusion and collagen related genes were up-regulated at 42 dpi. Together with the observation of morphological changes of LCCs in previous reports, it is suggested that the following steps are involved in LCC formation: the virus infected cells were (1) inhibited apoptotic death and (2) cell division before enlargement, (3) hypertrophied by cell fusion, and (4) surrounded by a hyaline capsule associated with the alteration of collagen fibers. Copyright © 2014 Elsevier Ltd. All rights reserved.
Blanchard, Raymond K.; Moore, J. Bernadette; Green, Calvert L.; Cousins, Robert J.
2001-01-01
Mammalian nutritional status affects the homeostatic balance of multiple physiological processes and their associated gene expression. Although DNA array analysis can monitor large numbers of genes, there are no reports of expression profiling of a micronutrient deficiency in an intact animal system. In this report, we have tested the feasibility of using cDNA arrays to compare the global changes in expression of genes of known function that occur in the early stages of rodent zinc deficiency. The gene-modulating effects of this deficiency were demonstrated by real-time quantitative PCR measurements of altered mRNA levels for metallothionein 1, zinc transporter 2, and uroguanylin, all of which have been previously documented as zinc-regulated genes. As a result of the low level of inherent noise within this model system and application of a recently reported statistical tool for statistical analysis of microarrays [Tusher, V.G., Tibshirani, R. & Chu, G. (2001) Proc. Natl. Acad. Sci. USA 98, 5116–5121], we demonstrate the ability to reproducibly identify the modest changes in mRNA abundance produced by this single micronutrient deficiency. Among the genes identified by this array profile are intestinal genes that influence signaling pathways, growth, transcription, redox, and energy utilization. Additionally, the influence of dietary zinc supply on the expression of some of these genes was confirmed by real-time quantitative PCR. Overall, these data support the effectiveness of cDNA array expression profiling to investigate the pleiotropic effects of specific nutrients and may provide an approach to establishing markers for assessment of nutritional status. PMID:11717422
Dual-mode acoustic wave biosensors microarrays
NASA Astrophysics Data System (ADS)
Auner, Gregory W.; Shreve, Gina; Ying, Hao; Newaz, Golam; Hughes, Chantelle; Xu, Jianzeng
2003-04-01
We have develop highly sensitive and selective acoustic wave biosensor arrays with signal analysis systems to provide a fingerprint for the real-time identification and quantification of a wide array of bacterial pathogens and environmental health hazards. We have developed an unique highly sensitive dual mode acoustic wave platform prototype that, when combined with phage based selective detection elements, form a durable bacteria sensor. Arrays of these new real-time biosensors are integrated to form a biosensor array on a chip. This research and development program optimizes advanced piezoelectric aluminum nitride wide bandgap semiconductors, novel micromachining processes, advanced device structures, selective phage displays development and immobilization techniques, and system integration and signal analysis technology to develop the biosensor arrays. The dual sensor platform can be programmed to sense in a gas, vapor or liquid environment by switching between acoustic wave resonate modes. Such a dual mode sensor has tremendous implications for applications involving monitoring of pathogenic microorganisms in the clinical setting due to their ability to detect airborne pathogens. This provides a number of applications including hospital settings such as intensive care or other in-patient wards for the reduction of nosocomial infections and maintenance of sterile environments in surgical suites. Monitoring for airborn pathogen transmission in public transportation areas such as airplanes may be useful for implementation of strategies for redution of airborn transmission routes. The ability to use the same sensor in the liquid sensing mode is important for tracing the source of airborn pathogens to local liquid sources. Sensing of pathogens in saliva will be useful for sensing oral pathogens and support of decision-making strategies regarding prevention of transmission and support of treatment strategies.
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.
Experimental Approaches to Microarray Analysis of Tumor Samples
ERIC Educational Resources Information Center
Furge, Laura Lowe; Winter, Michael B.; Meyers, Jacob I.; Furge, Kyle A.
2008-01-01
Comprehensive measurement of gene expression using high-density nucleic acid arrays (i.e. microarrays) has become an important tool for investigating the molecular differences in clinical and research samples. Consequently, inclusion of discussion in biochemistry, molecular biology, or other appropriate courses of microarray technologies has…
Multiplex cDNA quantification method that facilitates the standardization of gene expression data
Gotoh, Osamu; Murakami, Yasufumi; Suyama, Akira
2011-01-01
Microarray-based gene expression measurement is one of the major methods for transcriptome analysis. However, current microarray data are substantially affected by microarray platforms and RNA references because of the microarray method can provide merely the relative amounts of gene expression levels. Therefore, valid comparisons of the microarray data require standardized platforms, internal and/or external controls and complicated normalizations. These requirements impose limitations on the extensive comparison of gene expression data. Here, we report an effective approach to removing the unfavorable limitations by measuring the absolute amounts of gene expression levels on common DNA microarrays. We have developed a multiplex cDNA quantification method called GEP-DEAN (Gene expression profiling by DCN-encoding-based analysis). The method was validated by using chemically synthesized DNA strands of known quantities and cDNA samples prepared from mouse liver, demonstrating that the absolute amounts of cDNA strands were successfully measured with a sensitivity of 18 zmol in a highly multiplexed manner in 7 h. PMID:21415008
Spot detection and image segmentation in DNA microarray data.
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.
Split-plot microarray experiments: issues of design, power and sample size.
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.
Kilicoglu, Halil; Shin, Dongwook; Rindflesch, Thomas C.
2014-01-01
Gene regulatory networks are a crucial aspect of systems biology in describing molecular mechanisms of the cell. Various computational models rely on random gene selection to infer such networks from microarray data. While incorporation of prior knowledge into data analysis has been deemed important, in practice, it has generally been limited to referencing genes in probe sets and using curated knowledge bases. We investigate the impact of augmenting microarray data with semantic relations automatically extracted from the literature, with the view that relations encoding gene/protein interactions eliminate the need for random selection of components in non-exhaustive approaches, producing a more accurate model of cellular behavior. A genetic algorithm is then used to optimize the strength of interactions using microarray data and an artificial neural network fitness function. The result is a directed and weighted network providing the individual contribution of each gene to its target. For testing, we used invasive ductile carcinoma of the breast to query the literature and a microarray set containing gene expression changes in these cells over several time points. Our model demonstrates significantly better fitness than the state-of-the-art model, which relies on an initial random selection of genes. Comparison to the component pathways of the KEGG Pathways in Cancer map reveals that the resulting networks contain both known and novel relationships. The p53 pathway results were manually validated in the literature. 60% of non-KEGG relationships were supported (74% for highly weighted interactions). The method was then applied to yeast data and our model again outperformed the comparison model. Our results demonstrate the advantage of combining gene interactions extracted from the literature in the form of semantic relations with microarray analysis in generating contribution-weighted gene regulatory networks. This methodology can make a significant contribution to understanding the complex interactions involved in cellular behavior and molecular physiology. PMID:24921649
Chen, Guocai; Cairelli, Michael J; Kilicoglu, Halil; Shin, Dongwook; Rindflesch, Thomas C
2014-06-01
Gene regulatory networks are a crucial aspect of systems biology in describing molecular mechanisms of the cell. Various computational models rely on random gene selection to infer such networks from microarray data. While incorporation of prior knowledge into data analysis has been deemed important, in practice, it has generally been limited to referencing genes in probe sets and using curated knowledge bases. We investigate the impact of augmenting microarray data with semantic relations automatically extracted from the literature, with the view that relations encoding gene/protein interactions eliminate the need for random selection of components in non-exhaustive approaches, producing a more accurate model of cellular behavior. A genetic algorithm is then used to optimize the strength of interactions using microarray data and an artificial neural network fitness function. The result is a directed and weighted network providing the individual contribution of each gene to its target. For testing, we used invasive ductile carcinoma of the breast to query the literature and a microarray set containing gene expression changes in these cells over several time points. Our model demonstrates significantly better fitness than the state-of-the-art model, which relies on an initial random selection of genes. Comparison to the component pathways of the KEGG Pathways in Cancer map reveals that the resulting networks contain both known and novel relationships. The p53 pathway results were manually validated in the literature. 60% of non-KEGG relationships were supported (74% for highly weighted interactions). The method was then applied to yeast data and our model again outperformed the comparison model. Our results demonstrate the advantage of combining gene interactions extracted from the literature in the form of semantic relations with microarray analysis in generating contribution-weighted gene regulatory networks. This methodology can make a significant contribution to understanding the complex interactions involved in cellular behavior and molecular physiology.
Hybrid genetic algorithm-neural network: feature extraction for unpreprocessed microarray data.
Tong, Dong Ling; Schierz, Amanda C
2011-09-01
Suitable techniques for microarray analysis have been widely researched, particularly for the study of marker genes expressed to a specific type of cancer. Most of the machine learning methods that have been applied to significant gene selection focus on the classification ability rather than the selection ability of the method. These methods also require the microarray data to be preprocessed before analysis takes place. The objective of this study is to develop a hybrid genetic algorithm-neural network (GANN) model that emphasises feature selection and can operate on unpreprocessed microarray data. The GANN is a hybrid model where the fitness value of the genetic algorithm (GA) is based upon the number of samples correctly labelled by a standard feedforward artificial neural network (ANN). The model is evaluated by using two benchmark microarray datasets with different array platforms and differing number of classes (a 2-class oligonucleotide microarray data for acute leukaemia and a 4-class complementary DNA (cDNA) microarray dataset for SRBCTs (small round blue cell tumours)). The underlying concept of the GANN algorithm is to select highly informative genes by co-evolving both the GA fitness function and the ANN weights at the same time. The novel GANN selected approximately 50% of the same genes as the original studies. This may indicate that these common genes are more biologically significant than other genes in the datasets. The remaining 50% of the significant genes identified were used to build predictive models and for both datasets, the models based on the set of genes extracted by the GANN method produced more accurate results. The results also suggest that the GANN method not only can detect genes that are exclusively associated with a single cancer type but can also explore the genes that are differentially expressed in multiple cancer types. The results show that the GANN model has successfully extracted statistically significant genes from the unpreprocessed microarray data as well as extracting known biologically significant genes. We also show that assessing the biological significance of genes based on classification accuracy may be misleading and though the GANN's set of extra genes prove to be more statistically significant than those selected by other methods, a biological assessment of these genes is highly recommended to confirm their functionality. Copyright © 2011 Elsevier B.V. All rights reserved.
Meta-analysis of pathway enrichment: combining independent and dependent omics data sets.
Kaever, Alexander; Landesfeind, Manuel; Feussner, Kirstin; Morgenstern, Burkhard; Feussner, Ivo; Meinicke, Peter
2014-01-01
A major challenge in current systems biology is the combination and integrative analysis of large data sets obtained from different high-throughput omics platforms, such as mass spectrometry based Metabolomics and Proteomics or DNA microarray or RNA-seq-based Transcriptomics. Especially in the case of non-targeted Metabolomics experiments, where it is often impossible to unambiguously map ion features from mass spectrometry analysis to metabolites, the integration of more reliable omics technologies is highly desirable. A popular method for the knowledge-based interpretation of single data sets is the (Gene) Set Enrichment Analysis. In order to combine the results from different analyses, we introduce a methodical framework for the meta-analysis of p-values obtained from Pathway Enrichment Analysis (Set Enrichment Analysis based on pathways) of multiple dependent or independent data sets from different omics platforms. For dependent data sets, e.g. obtained from the same biological samples, the framework utilizes a covariance estimation procedure based on the nonsignificant pathways in single data set enrichment analysis. The framework is evaluated and applied in the joint analysis of Metabolomics mass spectrometry and Transcriptomics DNA microarray data in the context of plant wounding. In extensive studies of simulated data set dependence, the introduced correlation could be fully reconstructed by means of the covariance estimation based on pathway enrichment. By restricting the range of p-values of pathways considered in the estimation, the overestimation of correlation, which is introduced by the significant pathways, could be reduced. When applying the proposed methods to the real data sets, the meta-analysis was shown not only to be a powerful tool to investigate the correlation between different data sets and summarize the results of multiple analyses but also to distinguish experiment-specific key pathways.
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.
Is Ki67 prognostic for aggressive prostate cancer? A multicenter real-world study.
Fantony, Joseph J; Howard, Lauren E; Csizmadi, Ilona; Armstrong, Andrew J; Lark, Amy L; Galet, Colette; Aronson, William J; Freedland, Stephen J
2018-06-15
To test if Ki67 expression is prognostic for biochemical recurrence (BCR) after radical prostatectomy (RP). Ki67 immunohistochemistry was performed on tissue microarrays constructed from specimens obtained from 464 men undergoing RP at the Durham and West LA Veterans Affairs Hospitals. Hazard ratios (HR) for Ki67 expression and time to BCR were estimated using Cox regression. Ki67 was associated with more recent surgery year (p < 0.001), positive margins (p = 0.001) and extracapsular extension (p < 0.001). In center-stratified analyses, the adjusted HR for Ki67 expression and BCR approached statistical significance for west LA (HR: 1.54; p = 0.06), but not Durham (HR: 1.10; p = 0.74). This multi-institutional 'real-world' study provides limited evidence for the prognostic role of Ki67 in predicting outcome after RP.
Liu, Li-Zhi; Wu, Fang-Xiang; Zhang, Wen-Jun
2014-01-01
As an abstract mapping of the gene regulations in the cell, gene regulatory network is important to both biological research study and practical applications. The reverse engineering of gene regulatory networks from microarray gene expression data is a challenging research problem in systems biology. With the development of biological technologies, multiple time-course gene expression datasets might be collected for a specific gene network under different circumstances. The inference of a gene regulatory network can be improved by integrating these multiple datasets. It is also known that gene expression data may be contaminated with large errors or outliers, which may affect the inference results. A novel method, Huber group LASSO, is proposed to infer the same underlying network topology from multiple time-course gene expression datasets as well as to take the robustness to large error or outliers into account. To solve the optimization problem involved in the proposed method, an efficient algorithm which combines the ideas of auxiliary function minimization and block descent is developed. A stability selection method is adapted to our method to find a network topology consisting of edges with scores. The proposed method is applied to both simulation datasets and real experimental datasets. It shows that Huber group LASSO outperforms the group LASSO in terms of both areas under receiver operating characteristic curves and areas under the precision-recall curves. The convergence analysis of the algorithm theoretically shows that the sequence generated from the algorithm converges to the optimal solution of the problem. The simulation and real data examples demonstrate the effectiveness of the Huber group LASSO in integrating multiple time-course gene expression datasets and improving the resistance to large errors or outliers.
ArrayWiki: an enabling technology for sharing public microarray data repositories and meta-analyses
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
Resident training in microbiology.
Haller, Barbara L
2007-06-01
To meet the challenges of diagnosis and management of infectious diseases, clinical pathology residents must receive comprehensive training in microbiology, learn to think critically, develop problem-solving skills, and take active roles as laboratory consultants. Residents well trained in clinical microbiology become capable laboratory professionals, developing cost-effective testing strategies, decreasing risk for medical errors, and improving patient care. Newer methods for diagnosing infectious disease, such as real-time polymerase chain reaction, microarrays for pathogen detection, and rapid assays for antigen or antibody detection, have become standard. Knowledge of infectious disease principles, drug therapeutic options, and drug resistance is also important. Suggestions for training and for assessing resident competency in clinical microbiology are presented.
Hidden discriminative features extraction for supervised high-order time series modeling.
Nguyen, Ngoc Anh Thi; Yang, Hyung-Jeong; Kim, Sunhee
2016-11-01
In this paper, an orthogonal Tucker-decomposition-based extraction of high-order discriminative subspaces from a tensor-based time series data structure is presented, named as Tensor Discriminative Feature Extraction (TDFE). TDFE relies on the employment of category information for the maximization of the between-class scatter and the minimization of the within-class scatter to extract optimal hidden discriminative feature subspaces that are simultaneously spanned by every modality for supervised tensor modeling. In this context, the proposed tensor-decomposition method provides the following benefits: i) reduces dimensionality while robustly mining the underlying discriminative features, ii) results in effective interpretable features that lead to an improved classification and visualization, and iii) reduces the processing time during the training stage and the filtering of the projection by solving the generalized eigenvalue issue at each alternation step. Two real third-order tensor-structures of time series datasets (an epilepsy electroencephalogram (EEG) that is modeled as channel×frequency bin×time frame and a microarray data that is modeled as gene×sample×time) were used for the evaluation of the TDFE. The experiment results corroborate the advantages of the proposed method with averages of 98.26% and 89.63% for the classification accuracies of the epilepsy dataset and the microarray dataset, respectively. These performance averages represent an improvement on those of the matrix-based algorithms and recent tensor-based, discriminant-decomposition approaches; this is especially the case considering the small number of samples that are used in practice. Copyright © 2016 Elsevier Ltd. All rights reserved.
Goldman, Mindy; Núria, Núria; Castilho, Lilian M
2015-01-01
Automated testing platforms facilitate the introduction of red cell genotyping of patients and blood donors. Fluidic microarray systems, such as Luminex XMAP (Austin, TX), are used in many clinical applications, including HLA and HPA typing. The Progenika ID CORE XT (Progenika Biopharma-Grifols, Bizkaia, Spain) uses this platform to analyze 29 polymorphisms determining 37 antigens in 10 blood group systems. Once DNA has been extracted, processing time is approximately 4 hours. The system is highly automated and includes integrated analysis software that produces a file and a report with genotype and predicted phenotype results.
2010-01-01
Background Analysis of gene expression and gene mutation may add information to be different from ordinary pathological tissue diagnosis. Since samples obtained endoscopically are very small, it is desired that more sensitive technology is developed for gene analysis. We investigated whether gene expression and gene mutation analysis by newly developed ultra-sensitive three-dimensional (3D) microarray is possible using small amount samples from endoscopic ultrasound-guided fine-needle aspiration (EUS-FNA) specimens and pancreatic juices. Methods Small amount samples from 17 EUS-FNA specimens and 16 pancreatic juices were obtained. After nucleic acid extraction, the samples were amplified with labeling and analyzed by the 3D microarray. Results The analyzable rate with the microarray was 46% (6/13) in EUS-FNA specimens of RNAlater® storage, and RNA degradations were observed in all the samples of frozen storage. In pancreatic juices, the analyzable rate was 67% (4/6) in frozen storage samples and 20% (2/10) in RNAlater® storage. EUS-FNA specimens were classified into cancer and non-cancer by gene expression analysis and K-ras codon 12 mutations were also detected using the 3D microarray. Conclusions Gene analysis from small amount samples obtained endoscopically was possible by newly developed 3D microarray technology. High quality RNA from EUS-FNA samples were obtained and remained in good condition only using RNA stabilizer. In contrast, high quality RNA from pancreatic juice samples were obtained only in frozen storage without RNA stabilizer. PMID:20416107
Riis, Margit L H; Lüders, Torben; Markert, Elke K; Haakensen, Vilde D; Nesbakken, Anne-Jorun; Kristensen, Vessela N; Bukholm, Ida R K
2012-01-01
Gene expression studies on breast cancer have generally been performed on tissue obtained at the time of surgery. In this study, we have compared the gene expression profiles in preoperative tissue (core needle biopsies) while tumor is still in its normal milieu to postoperative tissue from the same tumor obtained during surgery. Thirteen patients were included of which eleven had undergone sentinel node diagnosis procedure before operation. Microarray gene expression analysis was performed using total RNA from all the samples. Paired significance analysis of microarrays revealed 228 differently expressed genes, including several early response stress-related genes such as members of the fos and jun families as well as genes of which the expression has previously been associated with cancer. The expression profiles found in the analyses of breast cancer tissue must be evaluated with caution. Different profiles may simply be the result of differences in the surgical trauma and timing of when samples are taken and not necessarily associated with tumor biology.
Riis, Margit L. H.; Lüders, Torben; Markert, Elke K.; Haakensen, Vilde D.; Nesbakken, Anne-Jorun; Kristensen, Vessela N.; Bukholm, Ida R. K.
2012-01-01
Gene expression studies on breast cancer have generally been performed on tissue obtained at the time of surgery. In this study, we have compared the gene expression profiles in preoperative tissue (core needle biopsies) while tumor is still in its normal milieu to postoperative tissue from the same tumor obtained during surgery. Thirteen patients were included of which eleven had undergone sentinel node diagnosis procedure before operation. Microarray gene expression analysis was performed using total RNA from all the samples. Paired significance analysis of microarrays revealed 228 differently expressed genes, including several early response stress-related genes such as members of the fos and jun families as well as genes of which the expression has previously been associated with cancer. The expression profiles found in the analyses of breast cancer tissue must be evaluated with caution. Different profiles may simply be the result of differences in the surgical trauma and timing of when samples are taken and not necessarily associated with tumor biology. PMID:23227362
USDA-ARS?s Scientific Manuscript database
The amount of microarray gene expression data in public repositories has been increasing exponentially for the last couple of decades. High-throughput microarray data integration and analysis has become a critical step in exploring the large amount of expression data for biological discovery. Howeve...
Lifeng, Zhao; Yan, Hong; Dayun, Yang; Xiaoying, Lü; Tingfei, Xi; Deyuan, Zhang; Ying, Hong; Jinfeng, Yuan
2011-04-01
TiN coating has been demonstrated to improve the biocompatibility of bare NiTi alloys; however, essential biocompatibility differences between NiTi alloys before and after TiN coating are not known so far. In this study, to explore the underlying biological mechanisms of biocompatibility differences between them, the changes of bare and TiN-coated NiTi alloys in surface chemical composition, morphology, hydrophilicity, Ni ions release, cytotoxicity, apoptosis, and gene expression profiles were compared using energy-dispersive spectroscopy, scanning electron microscopy, contact angle, surface energy, Ni ions release analysis, the methylthiazoltetrazolium (MTT) method, flow cytometry and microarray methods, respectively. Pathways binding to networks and real-time polymerase chain reaction (PCR) were employed to analyze and validate the microarray data, respectively. It was found that, compared with the bare NiTi alloys, TiN coating significantly decreased Ni ions content on the surfaces of the NiTi alloys and reduced the release of Ni ions from the alloys, attenuated the inhibition of Ni ions to the expression of genes associated with anti-inflammatory, and also suppressed the promotion of Ni ions to the expression of apoptosis-related genes. Moreover, TiN coating distinctly improved the hydrophilicity and uniformity of the surfaces of the NiTi alloys, and contributed to the expression of genes participating in cell adhesion and other physiological activities. These results indicate that the TiN-coated NiTi alloys will help overcome the shortcomings of NiTi alloys used in clinical application currently, and can be expected to be a replacement of biomaterials for a medical device field.
2013-01-01
Background Differential diagnosis between malignant follicular thyroid cancer (FTC) and benign follicular thyroid adenoma (FTA) is a great challenge for even an experienced pathologist and requires special effort. Molecular markers may potentially support a differential diagnosis between FTC and FTA in postoperative specimens. The purpose of this study was to derive molecular support for differential post-operative diagnosis, in the form of a simple multigene mRNA-based classifier that would differentiate between FTC and FTA tissue samples. Methods A molecular classifier was created based on a combined analysis of two microarray datasets (using 66 thyroid samples). The performance of the classifier was assessed using an independent dataset comprising 71 formalin-fixed paraffin-embedded (FFPE) samples (31 FTC and 40 FTA), which were analysed by quantitative real-time PCR (qPCR). In addition, three other microarray datasets (62 samples) were used to confirm the utility of the classifier. Results Five of 8 genes selected from training datasets (ELMO1, EMCN, ITIH5, KCNAB1, SLCO2A1) were amplified by qPCR in FFPE material from an independent sample set. Three other genes did not amplify in FFPE material, probably due to low abundance. All 5 analysed genes were downregulated in FTC compared to FTA. The sensitivity and specificity of the 5-gene classifier tested on the FFPE dataset were 71% and 72%, respectively. Conclusions The proposed approach could support histopathological examination: 5-gene classifier may aid in molecular discrimination between FTC and FTA in FFPE material. PMID:24099521
Song, Mingzhi; Wang, Yong
2017-01-01
Proteasome 26S subunit ATPase 2 (PSMC2) is a recently identified gene potentially associated with certain human carcinogenesis. However, the expressional correlation and functional importance of PSMC2 in osteosarcoma is still unclear. Current study was focused on elucidating the significance of PSMC2 on malignant behaviors in osteosarcoma including proliferation, apoptosis, colony formation, migration as well as invasion. The high protein levels of PSMC2 in osteosarcoma samples were identified by tissue microarrays analysis. Besides, its expression in the levels of mRNA and protein was also detected in four different osteosarcoma cell lines by real-time PCR and western blotting separately. Silencing PSMC2 by RNA interference in osteosarcoma cell lines (SaoS-2 and MG-63) would significantly suppress cell proliferation, enhance apoptosis, accelerate G2/M phase and/or S phase arrest, and decrease single cell colony formation. Similarly, pharmaceutical inhibition of proteasome with MG132 would mimic the PSMC2 depletion induced defects in cell cycle arrest, apoptosis and colonies formation. Silencing of PSMC2 was able to inhibit osteosarcoma cell motility, invasion as well as tumorigenicity in nude mice. Moreover, the gene microarray indicated knockdown of PSMC2 notably changed a number of genes, especially some cancer related genes including ITGA6, FN1, CCND1, CCNE2 and TGFβR2, and whose expression changes were further confirmed by western blotting. Our data suggested that PSMC2 may work as an oncogene for osteosarcoma and that inhibition of PSMC2 may be a therapeutic strategy for osteosarcoma treatment. PMID:27888613
Dorval, Véronique; Smith, Pascal Y; Delay, Charlotte; Calvo, Ezequiel; Planel, Emmanuel; Zommer, Nadège; Buée, Luc; Hébert, Sébastien S
2012-01-01
The small non-protein-coding microRNAs (miRNAs) have emerged as critical regulators of neuronal differentiation, identity and survival. To date, however, little is known about the genes and molecular networks regulated by neuronal miRNAs in vivo, particularly in the adult mammalian brain. We analyzed whole genome microarrays from mice lacking Dicer, the enzyme responsible for miRNA production, specifically in postnatal forebrain neurons. A total of 755 mRNA transcripts were significantly (P<0.05, FDR<0.25) misregulated in the conditional Dicer knockout mice. Ten genes, including Tnrc6c, Dnmt3a, and Limk1, were validated by real time quantitative RT-PCR. Upregulated transcripts were enriched in nonneuronal genes, which is consistent with previous studies in vitro. Microarray data mining showed that upregulated genes were enriched in biological processes related to gene expression regulation, while downregulated genes were associated with neuronal functions. Molecular pathways associated with neurological disorders, cellular organization and cellular maintenance were altered in the Dicer mutant mice. Numerous miRNA target sites were enriched in the 3'untranslated region (3'UTR) of upregulated genes, the most significant corresponding to the miR-124 seed sequence. Interestingly, our results suggest that, in addition to miR-124, a large fraction of the neuronal miRNome participates, by order of abundance, in coordinated gene expression regulation and neuronal maintenance. Taken together, these results provide new clues into the role of specific miRNA pathways in the regulation of brain identity and maintenance in adult mice.
Function of the tryptophan metabolite, L-kynurenine, in human corneal endothelial cells
Lahdou, Imad; Scheuerle, Alexander; Höftberger, Romana; Aboul-Enein, Fahmy
2009-01-01
Purpose Penetrating keratoplasty has been the mainstay for the treatment of blindness and is the most common form of tissue transplantation worldwide. Due to significant rates of rejection, treatment of immunological transplant reactions is of wide interest. Recently in a mouse model, the overexpression of indoeleamine 2,3 dioxigenase (IDO) was led to an extension in corneal allograft survival. L-kynurenine is a tryptophan metabolite, which may render activated T-cells apoptotic and therefore might modulate an allogenous transplant reaction. The function of L-kynurenine in the human cornea remains unclear. We analyzed the expression levels of IDO in human corneal endothelial cells (HCECs) and downstream tryptophan/kynurenine mechanisms in cell culture. Methods An immunological activation profile was determined in proliferation assays of monocytes from healthy donors. Reversed-phase high pressure liquid chromatography (HPLC), western blot, real time polymerase chain reaction (PCR), and microarray analyses were used. The expression of IDO and immunological infiltration of rejected human corneal allografts (n=12) were analyzed by immunohistochemistry. Results We found IDO and an associated tryptophan/kynurenine transporter protein exchange mechanism upregulated by inflammatory cytokines in HCECs. The inhibition of T-cell proliferation might depend on rapid delivery of the tryptophan metabolite, L-kynurenine, to the local corneal environment. Microarray analysis gives evidence that the large amino acid transporter 1 (LAT1) transporter protein is responsible for this mechanism. Conclusions Our data support that adequate levels of functional L-kynurenine might contribute to the maintenance of a relative immune privilege in the ocular anterior chamber, thereby contributing to the preservation of corneal allogeneic cells. PMID:19597571
Hammerschmid, Florian; Blum, Helmut; Krebs, Stefan; Redeker, Julia I.; Holzapfel, Boris M.; Jansson, Volkmar; Müller, Peter E.
2016-01-01
Introduction Low frequency electromagnetic fields (LF-EMF) and simulated microgravity (SMG) have been observed to affect chondrogenesis. A controlled bioreactor system was developed to apply LF-EMF and SMG singly or combined during chondrogenic differentiation of human mesenchymal stem cells (hMSCs) in 3D culture. Material and methods An external motor gear SMG bioreactor was combined with magnetic Helmholtz coils for EMF (5 mT; 15 Hz). Pellets of hMSCs (±TGF-β3) were cultured (P5) under SMG, LF-EMF, LF-EMF/SMG and control (1 g) conditions for 3 weeks. Sections were stained with safranin-O and collagen type II. Gene expression was evaluated by microarray and real-time polymerase chain reaction analysis. Results Simulated microgravity application significantly changed gene expression; specifically, COLXA1 but also COL2A1, which represents the chondrogenic potential, were reduced (p < 0.05). Low frequency electromagnetic fields application showed no gene expression changes on a microarray basis. LF-EMF/SMG application obtained significant different expression values from cultures obtained under SMG conditions with a re-increase of COL2A1, therefore rescuing the chondrogenic potential, which had been lowered by SMG. Conclusions Simulated microgravity lowered hypertrophy but also the chondrogenic potential of hMSCs. Combined LF-EMF/SMG provided a rescue effect of the chondrogenic potential of hMSCs although no LF-EMF effect was observed under optimal conditions. The study provides new insights into how LF-EMF and SMG affect chondrogenesis of hMSCs and how they generate interdependent effects. PMID:29765449
Smoot, L M; Smoot, J C; Graham, M R; Somerville, G A; Sturdevant, D E; Migliaccio, C A; Sylva, G L; Musser, J M
2001-08-28
Pathogens are exposed to different temperatures during an infection cycle and must regulate gene expression accordingly. However, the extent to which virulent bacteria alter gene expression in response to temperatures encountered in the host is unknown. Group A Streptococcus (GAS) is a human-specific pathogen that is responsible for illnesses ranging from superficial skin infections and pharyngitis to severe invasive infections such as necrotizing fasciitis and streptococcal toxic shock syndrome. GAS survives and multiplies at different temperatures during human infection. DNA microarray analysis was used to investigate the influence of temperature on global gene expression in a serotype M1 strain grown to exponential phase at 29 degrees C and 37 degrees C. Approximately 9% of genes were differentially expressed by at least 1.5-fold at 29 degrees C relative to 37 degrees C, including genes encoding transporter proteins, proteins involved in iron homeostasis, transcriptional regulators, phage-associated proteins, and proteins with no known homologue. Relatively few known virulence genes were differentially expressed at this threshold. However, transcription of 28 genes encoding proteins with predicted secretion signal sequences was altered, indicating that growth temperature substantially influences the extracellular proteome. TaqMan real-time reverse transcription-PCR assays confirmed the microarray data. We also discovered that transcription of genes encoding hemolysins, and proteins with inferred roles in iron regulation, transport, and homeostasis, was influenced by growth at 40 degrees C. Thus, GAS profoundly alters gene expression in response to temperature. The data delineate the spectrum of temperature-regulated gene expression in an important human pathogen and provide many unforeseen lines of pathogenesis investigation.
García, Normand; Salamanca, Fabio; Astudillo-de la Vega, Horacio; Curiel-Quesada, Everardo; Alvarado, Isabel; Peñaloza, Rosenda; Arenas, Diego
2005-01-01
Background Breast cancer is one of the most frequent causes of death in Mexican women over 35 years of age. At molecular level, changes in many genetic networks have been reported as associated with this neoplasia. To analyze these changes, we determined gene expression profiles of tumors from Mexican women with breast cancer at different stages and compared these with those of normal breast tissue samples. Methods 32P-radiolabeled cDNA was synthesized by reverse transcription of mRNA from fresh sporadic breast tumor biopsies, as well as normal breast tissue. cDNA probes were hybridized to microarrays and expression levels registered using a phosphorimager. Expression levels of some genes were validated by real time RT-PCR and immunohistochemical assays. Results We identified two subgroups of tumors according to their expression profiles, probably related with cancer progression. Ten genes, unexpressed in normal tissue, were turned on in some tumors. We found consistent high expression of Bik gene in 14/15 tumors with predominant cytoplasmic distribution. Conclusion Recently, the product of the Bik gene has been associated with tumoral reversion in different neoplasic cell lines, and was proposed as therapy to induce apoptosis in cancers, including breast tumors. Even though a relationship among genes, for example those from a particular pathway, can be observed through microarrays, this relationship might not be sufficient to assign a definitive role to Bik in development and progression of the neoplasia. The findings herein reported deserve further investigation. PMID:16060964
Nuzzolo, Eugenia R; Capodimonti, Sara; Martini, Maurizio; Iachininoto, Maria G; Bianchi, Maria; Cocomazzi, Alessandra; Zini, Gina; Leone, Giuseppe; Larocca, Luigi M; Teofili, Luciana
2014-01-01
Endothelial colony-forming cells (ECFC) are endowed with vascular regenerative ability in vivo and in vitro. In this study we compared the genotypic profile and the immunogenic potential of adult and cord blood ECFC, in order to explore the feasibility of using them as a cell therapy product. ECFC were obtained from cord blood samples not suitable for haematopoietic stem cell transplantation and from adult healthy blood donors after informed consent. Genotypes were analysed by commercially available microarray assays and results were confirmed by real-time polymerase chain reaction analysis. HLA antigen expression was evaluated by flow-cytometry. Immunogenic capacity was investigated by evaluating the activation of allogeneic lymphocytes and monocytes in co-cultures with ECFC. Microarray assays revealed that the genetic profile of cord blood and adult ECFC differed in about 20% of examined genes. We found that cord blood ECFC were characterised by lower pro-inflammatory and pro-thrombotic gene expression as compared to adult ECFC. Furthermore, whereas cord blood and adult ECFCs expressed similar amount of HLA molecules both at baseline and after incubation with γ-interferon, cord blood ECFC elicited a weaker expression of pro-inflammatory cytokine genes. Finally, we observed no differences in the amount of HLA antigens expressed among cord blood ECFC, adult ECFC and mesenchymal cells. Our observations suggest that cord blood ECFC have a lower pro-inflammatory and pro-thrombotic profile than adult ECFC. These preliminary data offer level-headed evidence to use cord blood ECFC as a cell therapy product in vascular diseases.
Microarray Analysis of Iris Gene Expression in Mice with Mutations Influencing Pigmentation
Trantow, Colleen M.; Cuffy, Tryphena L.; Fingert, John H.; Kuehn, Markus H.
2011-01-01
Purpose. Several ocular diseases involve the iris, notably including oculocutaneous albinism, pigment dispersion syndrome, and exfoliation syndrome. To screen for candidate genes that may contribute to the pathogenesis of these diseases, genome-wide iris gene expression patterns were comparatively analyzed from mouse models of these conditions. Methods. Iris samples from albino mice with a Tyr mutation, pigment dispersion–prone mice with Tyrp1 and Gpnmb mutations, and mice resembling exfoliation syndrome with a Lyst mutation were compared with samples from wild-type mice. All mice were strain (C57BL/6J), age (60 days old), and sex (female) matched. Microarrays were used to compare transcriptional profiles, and differentially expressed transcripts were described by functional annotation clustering using DAVID Bioinformatics Resources. Quantitative real-time PCR was performed to validate a subset of identified changes. Results. Compared with wild-type C57BL/6J mice, each disease context exhibited a large number of statistically significant changes in gene expression, including 685 transcripts differentially expressed in albino irides, 403 in pigment dispersion–prone irides, and 460 in exfoliative-like irides. Conclusions. Functional annotation clusterings were particularly striking among the overrepresented genes, with albino and pigment dispersion–prone irides both exhibiting overall evidence of crystallin-mediated stress responses. Exfoliative-like irides from mice with a Lyst mutation showed overall evidence of involvement of genes that influence immune system processes, lytic vacuoles, and lysosomes. These findings have several biologically relevant implications, particularly with respect to secondary forms of glaucoma, and represent a useful resource as a hypothesis-generating dataset. PMID:20739468
Bohannon, Meredith E; Porter, Tom E; Lavoie, Emma T; Ottinger, Mary Ann
2018-06-22
The upper Hudson River was contaminated with polychlorinated biphenyls (PCB) Aroclor mixtures from the 1940s until the late 1970s. Several well-established biomarkers, such as induction of hepatic cytochrome P450 monooxygenases, were used to measure exposure to PCBs and similar contaminants in birds. In the present study, Japanese quail eggs were injected with a PCB mixture based upon a congener profile found in spotted sandpiper eggs at the upper Hudson River and subsequently, RNA was extracted from hatchling liver tissue for hybridization to a customized chicken cDNA microarray. Nominal concentrations of the mixture used for microarray hybridization were 0, 6, 12, or 49 μg/g egg. Hepatic gene expression profiles were analyzed using cluster and pathway analyses. Results showed potentially useful biomarkers of both exposure and effect attributed to PCB mixture. Biorag and Ingenuity Pathway Analysis® analyses revealed differentially expressed genes including those involved in glycolysis, xenobiotic metabolism, replication, protein degradation, and tumor regulation. These genes included cytochrome P450 1A5 (CYP1A5), cytochrome b5 (CYB5), NADH-cytochrome b5 reductase, glutathione S-transferase (GSTA), fructose bisphosphate aldolase (ALDOB), glycogen phosphorylase, carbonic anhydrase, and DNA topoisomerase II. CYP1A5, CYB5, GSTA, and ALDOB were chosen for quantitative real-time polymerase chain reaction confirmation, as these genes exhibited a clear dose response on the array. Data demonstrated that an initial transcriptional profile associated with an environmentally relevant PCB mixture in Japanese quail occurred.
Kim, Sang Hwan; Hwang, Sue Yun; Yoon, Jong Taek
2014-01-01
The coat color of mammals is determined by the melanogenesis pathway, which is responsible for maintaining the balance between black-brown eumelanin and yellow-reddish pheomelanin. It is also believed that the color of the bovine muzzle is regulated in a similar manner; however, the molecular mechanism underlying pigment deposition in the dark-muzzle has yet to be elucidated. The aim of the present study was to identify melanogenesis-associated genes that are differentially expressed in the dark vs. light muzzle of native Korean cows. Using microarray clustering and real-time polymerase chain reaction techniques, we observed that the expression of genes involved in the mitogen-activated protein kinase (MAPK) and Wnt signaling pathways is distinctively regulated in the dark and light muzzle tissues. Differential expression of tyrosinase was also noticed, although the difference was not as distinct as those of MAPK and Wnt. We hypothesize that emphasis on the MAPK pathway in the dark-muzzle induces eumelanin synthesis through the activation of cAMP response element-binding protein and tyrosinase, while activation of Wnt signaling counteracts this process and raises the amount of pheomelanin in the light-muzzle. We also found 2 novel genes (GenBank No. NM-001076026 and XM-588439) with increase expression in the black nose, which may provide additional information about the mechanism of nose pigmentation. Regarding the increasing interest in the genetic diversity of cattle stocks, genes we identified for differential expression in the dark vs. light muzzle may serve as novel markers for genetic diversity among cows based on the muzzle color phenotype.
Chen, Muyan; Storey, Kenneth B
2014-02-01
The sea cucumber Apostichopus japonicus withstands high water temperatures in the summer by suppressing its metabolic rate and entering a state of aestivation. We hypothesized that changes in the expression of miRNAs could provide important post-transcriptional regulation of gene expression during hypometabolism via control over mRNA translation. The present study analyzed profiles of miRNA expression in the sea cucumber respiratory tree using Solexa deep sequencing technology. We identified 279 sea cucumber miRNAs, including 15 novel miRNAs specific to sea cucumber. Animals sampled during deep aestivation (DA; after at least 15 days of continuous torpor) were compared with animals from a non-aestivation (NA) state (animals that had passed through aestivation and returned to an active state). We identified 30 differentially expressed miRNAs ([RPM (reads per million) >10, |FC| (|fold change|)≥1, FDR (false discovery rate)<0.01]) during aestivation, which were validated by two other miRNA profiling methods: miRNA microarray and real-time PCR. Among the most prominent miRNA species, miR-124, miR-124-3p, miR-79, miR-9 and miR-2010 were significantly over-expressed during deep aestivation compared with non-aestivation animals, suggesting that these miRNAs may play important roles in metabolic rate suppression during aestivation. High-throughput sequencing data and microarray data have been submitted to the GEO database with accession number: 16902695. Copyright © 2014 Elsevier B.V. All rights reserved.
Real-time fMRI processing with physiological noise correction - Comparison with off-line analysis.
Misaki, Masaya; Barzigar, Nafise; Zotev, Vadim; Phillips, Raquel; Cheng, Samuel; Bodurka, Jerzy
2015-12-30
While applications of real-time functional magnetic resonance imaging (rtfMRI) are growing rapidly, there are still limitations in real-time data processing compared to off-line analysis. We developed a proof-of-concept real-time fMRI processing (rtfMRIp) system utilizing a personal computer (PC) with a dedicated graphic processing unit (GPU) to demonstrate that it is now possible to perform intensive whole-brain fMRI data processing in real-time. The rtfMRIp performs slice-timing correction, motion correction, spatial smoothing, signal scaling, and general linear model (GLM) analysis with multiple noise regressors including physiological noise modeled with cardiac (RETROICOR) and respiration volume per time (RVT). The whole-brain data analysis with more than 100,000voxels and more than 250volumes is completed in less than 300ms, much faster than the time required to acquire the fMRI volume. Real-time processing implementation cannot be identical to off-line analysis when time-course information is used, such as in slice-timing correction, signal scaling, and GLM. We verified that reduced slice-timing correction for real-time analysis had comparable output with off-line analysis. The real-time GLM analysis, however, showed over-fitting when the number of sampled volumes was small. Our system implemented real-time RETROICOR and RVT physiological noise corrections for the first time and it is capable of processing these steps on all available data at a given time, without need for recursive algorithms. Comprehensive data processing in rtfMRI is possible with a PC, while the number of samples should be considered in real-time GLM. Copyright © 2015 Elsevier B.V. All rights reserved.
NASA Astrophysics Data System (ADS)
Bogdanov, Valery L.; Boyce-Jacino, Michael
1999-05-01
Confined arrays of biochemical probes deposited on a solid support surface (analytical microarray or 'chip') provide an opportunity to analysis multiple reactions simultaneously. Microarrays are increasingly used in genetics, medicine and environment scanning as research and analytical instruments. A power of microarray technology comes from its parallelism which grows with array miniaturization, minimization of reagent volume per reaction site and reaction multiplexing. An optical detector of microarray signals should combine high sensitivity, spatial and spectral resolution. Additionally, low-cost and a high processing rate are needed to transfer microarray technology into biomedical practice. We designed an imager that provides confocal and complete spectrum detection of entire fluorescently-labeled microarray in parallel. Imager uses microlens array, non-slit spectral decomposer, and high- sensitive detector (cooled CCD). Two imaging channels provide a simultaneous detection of localization, integrated and spectral intensities for each reaction site in microarray. A dimensional matching between microarray and imager's optics eliminates all in moving parts in instrumentation, enabling highly informative, fast and low-cost microarray detection. We report theory of confocal hyperspectral imaging with microlenses array and experimental data for implementation of developed imager to detect fluorescently labeled microarray with a density approximately 103 sites per cm2.