A panel of prognostic protein markers for progression in non-muscle invasive bladder cancer - a multicenter tissue microarray validation study

DEFF Research Database (Denmark)

Fristrup, Niels; Birkenkamp-Demtröder, Karin; Ulhøi, Benedicte Parm

2012-01-01

cohort of 283 patients with long-term follow-up. For validation of the results we used three independent patient cohorts with long-term follow-up from Sweden, Spain, and Taiwan. In total 649 primary NMIBC tissue-microarray specimens from patients with long-term follow-up were used. Protein expression......Bladder cancer is the fifth most common cancer in the Western world. The histopathological parameters used in the clinic cannot precisely predict the individual disease course. Bladder cancer patients are therefore monitored thoroughly for disease recurrence and progression by urine and cystoscopy...... Ta and T1 urothelial carcinomas. Transcripts from the five genes encoding these proteins were previously included in gene expression signatures for outcome prediction for non-muscle invasive bladder cancer (NMIBC). As a training-set, we used primary NMIBC tissue-microarray specimens from a Danish...

The clinicopathologic association of c-MET overexpression in Iranian gastric carcinomas; an immunohistochemical study of tissue microarrays.

Science.gov (United States)

Sotoudeh, Kambiz; Hashemi, Forough; Madjd, Zahra; Sadeghipour, Alireza; Molanaei, Saadat; Kalantary, Elham

2012-05-28

c-MET is an oncogene protein that plays important role in gastric carcinogenesis and has been introduced as a prognostic marker and potential therapeutic target. The aim of this study was to evaluate the frequency of c-MET overexpression and its relationship with clinicopathological variables in gastric cancer of Iranian population using tissue microarray. In a cross sectional study, representative paraffin blocks of 130 patients with gastric carcinoma treated by curative gastrectomy during a 2 years period of 2008-2009 in two university hospitals in Tehran-Iran were collected in tissue microarray and c-MET expression was studied by immunohistochemical staining. Finally 124 cases were evaluated, constituted of 99 male and 25 female with the average age of 61.5 years. In 71% (88/124) of tumors, c-MET high expression was found. c-MET high expression was more associated with intestinal than diffuse tumor type (P = 0.04), deeper tumor invasion, pT3 and pT4 versus pT1 and pT2 (P = 0.014), neural invasion (P = 0.002) and advanced TNM staging, stage 3 and 4 versus stage 1 and2 (P = 0.044). The c-MET high expression was not associated with age, sex, tumor location, differentiation grade and distant metastasis, but relative associations with lymph node metastasis (P = 0.065) and vascular invasion (P = 0.078) were observed. c-MET oncogene protein was frequently overexpressed in Iranian gastric carcinomas and it was related to clinicopathological characteristics such as tumor type, depth of invasion, neural invasion and TNM staging. It can also support the idea that c-MET is a potential marker for target therapy in Iranian gastric cancer. The virtual slide(s) for this article can be found here: http://www.diagnosticpathology.diagnomx.eu/vs/9744598757151429.

Immunohistochemical localization of steroid receptor coactivators in chondrosarcoma: an in vivo tissue microarray study.

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Li, Wei; Fu, Jingshu; Bian, Chen; Zhang, Jiqiang; Xie, Zhao

2014-12-01

Chondrosarcoma is the second most common type of primary bone malignancy following up osteosarcoma, characterized by resistance to conventional chemotherapeutic agents and radiation regimens. The p160 family members steroid receptor coactivator-1 and -3 (SRC-1 and SRC-3) have been implied in the regulation of cancer growth, migration, invasion, metastasis and chemotherapeutic resistance; but we still lack detailed information about the levels of SRCs in chondrosarcoma. In this study, expression of SRC-1 and SRC-3 in chondrosarcoma was examined by immunohistochemistry with tissue microarrays; the four score system (0, 1, 2 and 3) was used to evaluate the staining. The results showed that there were no gender-, site- or age-differences regarding the expression of SRC-1 or SRC-3 (p>0.05); organ (bone or cartilage) -differences were only detected for SRC-1 but not SRC-3 (pchondrosarcoma, may be novel targets for the prognosis and/or treatment of chondrosarcoma, would have opened a new avenue and established foundation for studying chondrosarcoma. Copyright © 2014 Elsevier GmbH. All rights reserved.

Tissue Microarray TechnologyA Brief Review

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Ramya S Vokuda

2018-01-01

Full Text Available In this era of modern revolutionisation in the field of medical laboratory technology, everyone is aiming at taking the innovations from laboratory to bed side. One such technique that is most relevant to the pathologic community is Tissue Microarray (TMA technology. This is becoming quite popular amongst all the members of this family, right from laboratory scientists to clinicians and residents to technologists. The reason for this technique to gain popularity is attributed to its cost effectiveness and time saving protocols. Though, every technique is accompanied by disadvantages, the benefits out number them. This technique is very versatile as many downstream molecular assays such as immunohistochemistry, cytogenetic studies, Fluorescent In situ-Hybridisation (FISH etc., can be carried out on a single slide with multiple numbers of samples. It is a very practical approach that aids effectively to identify novel biomarkers in cancer diagnostics and therapeutics. It helps in assessing the molecular markers on a large scale very quickly. Also, the quality assurance protocols in pathological laboratory has exploited TMA to a great extent. However, the application of TMA technology is beyond oncology. This review shall focus on the different aspects of this technology such as construction of TMA, instrumentation, types, advantages and disadvantages and utilisation of the technique in various disease conditions.

Feasibility of using tissue microarray cores of paraffin-embedded breast cancer tissue for measurement of gene expression: a proof-of-concept study.

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Drury, Suzanne; Salter, Janine; Baehner, Frederick L; Shak, Steven; Dowsett, Mitch

2010-06-01

To determine whether 0.6 mm cores of formalin-fixed paraffin-embedded (FFPE) tissue, as commonly used to construct immunohistochemical tissue microarrays, may be a valid alternative to tissue sections as source material for quantitative real-time PCR-based transcriptional profiling of breast cancer. Four matched 0.6 mm cores of invasive breast tumour and two 10 microm whole sections were taken from eight FFPE blocks. RNA was extracted and reverse transcribed, and TaqMan assays were performed on the 21 genes of the Oncotype DX Breast Cancer assay. Expression of the 16 recurrence-related genes was normalised to the set of five reference genes, and the recurrence score (RS) was calculated. RNA yield was lower from 0.6 mm cores than from 10 microm whole sections, but was still more than sufficient to perform the assay. RS and single gene data from cores were highly comparable with those from whole sections (RS p=0.005). Greater variability was seen between cores than between sections. FFPE sections are preferable to 0.6 mm cores for RNA profiling in order to maximise RNA yield and to allow for standard histopathological assessment. However, 0.6 mm cores are sufficient and would be appropriate to use for large cohort studies.

Application of TMA (Tissue micro-array) in the observation of apoptotic cascade in postradiation damage in avian medicine

International Nuclear Information System (INIS)

Fridman, E.; Skarda, J.; Skardova, I.

2006-01-01

The study of apoptotic cascade by the use of relatively new technique in avian medicine: TMA may help in early detection and prevention of acquired immunodeficiency caused by the influence of a variety of pathogenic and non-pathogenic environmental factors, which may result in severe economical losses in conditions of intensive poultry farming. There has not been any report of applying this method in veterinary medicine. Tissue micro-array (TMA) technology allows rapid visualization of molecular targets in thousands of tissue specimens at a time, either at the DNA, RNA or protein level. The technique facilitates rapid translation of molecular discoveries to clinical applications. This technology has a number of advantages compared with conventional techniques: speed and high throughput, standardization and experimental uniformity, ease of use, all histochemical and molecular detection techniques can be used, decreased assay volume, preservation of original block, and conservation of valuable tissue etc. The aim of the present work were the study of immunosuppression and apoptotic cascade and possibilities of application of tissue micro-array in chicken in experimental condition and diagnostics in avian medicine in general. The selection of samples from avian primary immune organs: thymus and Bursa Fabric was done after gamma irradiation and infectious bursal virus infection (IBDV). (authors)

The clinicopathologic association of c-MET overexpression in Iranian gastric carcinomas; an immunohistochemical study of tissue microarrays

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Sotoudeh Kambiz

2012-05-01

Full Text Available Abstract Background c-MET is an oncogene protein that plays important role in gastric carcinogenesis and has been introduced as a prognostic marker and potential therapeutic target. The aim of this study was to evaluate the frequency of c-MET overexpression and its relationship with clinicopathological variables in gastric cancer of Iranian population using tissue microarray. Methods In a cross sectional study, representative paraffin blocks of 130 patients with gastric carcinoma treated by curative gastrectomy during a 2 years period of 2008–2009 in two university hospitals in Tehran-Iran were collected in tissue microarray and c-MET expression was studied by immunohistochemical staining. Results Finally 124 cases were evaluated, constituted of 99 male and 25 female with the average age of 61.5 years. In 71% (88/124 of tumors, c-MET high expression was found. c-MET high expression was more associated with intestinal than diffuse tumor type (P = 0.04, deeper tumor invasion, pT3 and pT4 versus pT1 and pT2 (P = 0.014, neural invasion (P = 0.002 and advanced TNM staging, stage 3 and 4 versus stage 1 and2 (P = 0.044. The c-MET high expression was not associated with age, sex, tumor location, differentiation grade and distant metastasis, but relative associations with lymph node metastasis (P = 0.065 and vascular invasion (P = 0.078 were observed. Conclusions c-MET oncogene protein was frequently overexpressed in Iranian gastric carcinomas and it was related to clinicopathological characteristics such as tumor type, depth of invasion, neural invasion and TNM staging. It can also support the idea that c-MET is a potential marker for target therapy in Iranian gastric cancer. Virtual slides The virtual slide(s for this article can be found here: http://www.diagnosticpathology.diagnomx.eu/vs/9744598757151429

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

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

2018-04-19

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

Genome-wide prediction and analysis of human tissue-selective genes using microarray expression data

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Teng Shaolei

2013-01-01

Full Text Available Abstract Background Understanding how genes are expressed specifically in particular tissues is a fundamental question in developmental biology. Many tissue-specific genes are involved in the pathogenesis of complex human diseases. However, experimental identification of tissue-specific genes is time consuming and difficult. The accurate predictions of tissue-specific gene targets could provide useful information for biomarker development and drug target identification. Results In this study, we have developed a machine learning approach for predicting the human tissue-specific genes using microarray expression data. The lists of known tissue-specific genes for different tissues were collected from UniProt database, and the expression data retrieved from the previously compiled dataset according to the lists were used for input vector encoding. Random Forests (RFs and Support Vector Machines (SVMs were used to construct accurate classifiers. The RF classifiers were found to outperform SVM models for tissue-specific gene prediction. The results suggest that the candidate genes for brain or liver specific expression can provide valuable information for further experimental studies. Our approach was also applied for identifying tissue-selective gene targets for different types of tissues. Conclusions A machine learning approach has been developed for accurately identifying the candidate genes for tissue specific/selective expression. The approach provides an efficient way to select some interesting genes for developing new biomedical markers and improve our knowledge of tissue-specific expression.

O arranjo em matriz de amostras teciduais (tissue microarray: larga escala e baixo custo ao alcance do patologista Tissue microarrays: high throughput and low cost avaiable for pathologists

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Victor Piana de Andrade

2007-02-01

Full Text Available O arranjo em matriz de amostras teciduais, ou tissue microarray (TMA, é uma técnica descrita em 1998 por Kononen et al. com ampla aceitação pela literatura mundial. Com um conceito extremamente simples, trata-se de agrupar um grande número de amostras teciduais em um único bloco de parafina, permitindo o estudo de expressão de marcadores moleculares em larga escala com grande aproveitamento do material arquivado, do tempo e dos custos. Discutimos as vantagens e limitações do método, as estratégias e técnica de construção, as aplicações e dificuldades encontradas para a patologia investigativa nos últimos cinco anos de uso no Hospital do Câncer A. C. Camargo.Tissue microarrays (TMA is a worldwide well accepted technique described in 1998 by Kononen et al. It uses an extremely simple concept of ordering hundreds of samples in just one paraffin block to evaluate protein expression in large cohorts with great advantages on costs, time and sample saving. We discuss the technique, its advantages and limitations, strategies to construct the receptor block, its usefulness and difficulties experienced in the last five years at Hospital do Cancer A.C. Camargo.

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

Science.gov (United States)

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.

Tissue Microarray Analysis Applied to Bone Diagenesis.

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

2017-01-04

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

Increased Inhibitor of Differentiation 4 (Id4 Expression in Glioblastoma: A Tissue Microarray Study

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Weifin Zeng, Elisabeth J. Rushing, Daniel P. Hartmann, Norio Azumi

2010-01-01

Full Text Available Background: The inhibitor of differentiation/DNA binding protein family (Id1-4 is involved in cell cycle control, tumorigenesis and angiogenesis through the negative regulation of helix-loop-helix transcription factors. Of these proteins, Id4 is known to play an important role in neural stem cell differentiation, and deregulation has been implicated in glial neoplasia. However, the expression and significance of Id4 in astrocytomas has not been fully addressed. Herein we report the differential expression of Id4 in astrocytomas of various grades using tissue microarrays (TMA and immunohistochemistry (IHC. Design: The GBM TMA was constructed from 53 archival cases at Georgetown University Hospital and a TMA with normal brain controls and grades II-III astrocytoma was obtained from Cybrdi (Rockville, MD. TMA sections were stained with Id4 antibody and the slides were scored according to the percentage of staining astrocytic nuclei (<9% -, 10-50% +, >51% ++. The Fisher Exact test was used to test for statistical significance. Results: Nuclear staining for Id4 was seen in 73.58% GBMs, 25% grade III, and 12.5% grade II astrocytomas; staining was absent in normal brain tissue. There was a statistically significant difference between GBM and grades II, III astrocytoma (p <0.01. Significant Id4 expression was not detected in normal brain. Conclusions: Our study confirms the frequent upregulation of Id4 expression in GBM, which lends support to its role in tumorigenesis, possibly in the transformation of low to high-grade astrocytoma (i.e. GBM. Further studies are warranted to determine the precise role of Id4 in glial neoplasia and its potential use in targeted therapy for GBM.

Quantitative multiplex quantum dot in-situ hybridisation based gene expression profiling in tissue microarrays identifies prognostic genes in acute myeloid leukaemia

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Tholouli, Eleni [Department of Haematology, Manchester Royal Infirmary, Oxford Road, Manchester, M13 9WL (United Kingdom); MacDermott, Sarah [The Medical School, The University of Manchester, Oxford Road, M13 9PT Manchester (United Kingdom); Hoyland, Judith [School of Biomedicine, Faculty of Medical and Human Sciences, The University of Manchester, Oxford Road, M13 9PT Manchester (United Kingdom); Yin, John Liu [Department of Haematology, Manchester Royal Infirmary, Oxford Road, Manchester, M13 9WL (United Kingdom); Byers, Richard, E-mail: richard.byers@cmft.nhs.uk [School of Cancer and Enabling Sciences, Faculty of Medical and Human Sciences, The University of Manchester, Stopford Building, Oxford Road, M13 9PT Manchester (United Kingdom)

2012-08-24

Highlights: Black-Right-Pointing-Pointer Development of a quantitative high throughput in situ expression profiling method. Black-Right-Pointing-Pointer Application to a tissue microarray of 242 AML bone marrow samples. Black-Right-Pointing-Pointer Identification of HOXA4, HOXA9, Meis1 and DNMT3A as prognostic markers in AML. -- Abstract: Measurement and validation of microarray gene signatures in routine clinical samples is problematic and a rate limiting step in translational research. In order to facilitate measurement of microarray identified gene signatures in routine clinical tissue a novel method combining quantum dot based oligonucleotide in situ hybridisation (QD-ISH) and post-hybridisation spectral image analysis was used for multiplex in-situ transcript detection in archival bone marrow trephine samples from patients with acute myeloid leukaemia (AML). Tissue-microarrays were prepared into which white cell pellets were spiked as a standard. Tissue microarrays were made using routinely processed bone marrow trephines from 242 patients with AML. QD-ISH was performed for six candidate prognostic genes using triplex QD-ISH for DNMT1, DNMT3A, DNMT3B, and for HOXA4, HOXA9, Meis1. Scrambled oligonucleotides were used to correct for background staining followed by normalisation of expression against the expression values for the white cell pellet standard. Survival analysis demonstrated that low expression of HOXA4 was associated with poorer overall survival (p = 0.009), whilst high expression of HOXA9 (p < 0.0001), Meis1 (p = 0.005) and DNMT3A (p = 0.04) were associated with early treatment failure. These results demonstrate application of a standardised, quantitative multiplex QD-ISH method for identification of prognostic markers in formalin-fixed paraffin-embedded clinical samples, facilitating measurement of gene expression signatures in routine clinical samples.

High-throughput immunophenotyping of 43 ferret lymphomas using tissue microarray technology

DEFF Research Database (Denmark)

Hammer, Anne Sofie; Williams, B.; Dietz, H.H.

2007-01-01

To validate the use of the tissue microarray (TMA) method for immunophenotyping of ferret lymphomas, a TMA was constructed containing duplicate 1-mm cores sampled from 112 paraffin-embedded lymphoma tissue specimens obtained from 43 ferret lymphoma cases. Immunohistochemical (IHC) expression of CD3......, CD79 alpha, and Ki-67 (MIB-1) was determined by TMA and whole mount (WM) staining of each individual case for result comparison. There was a high correlation between CD79 alpha and CD3 results comparing ferret TMA and WM sections (kappa statistic 0.71-0.73 for single-core TMA and 0.......79-0.95 for duplicate-core TMA) and between continuous data from Ki-67 staining of ferret TMA sections and WM sections (concordance correlation coefficients 0.77 for single cores and 0.87 for duplicate cores). Subsequently, a panel of commercially available antibodies was applied to the TMA for the analysis...

A prototype for unsupervised analysis of tissue microarrays for cancer research and diagnostics.

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Chen, Wenjin; Reiss, Michael; Foran, David J

2004-06-01

The tissue microarray (TMA) technique enables researchers to extract small cylinders of tissue from histological sections and arrange them in a matrix configuration on a recipient paraffin block such that hundreds can be analyzed simultaneously. TMA offers several advantages over traditional specimen preparation by maximizing limited tissue resources and providing a highly efficient means for visualizing molecular targets. By enabling researchers to reliably determine the protein expression profile for specific types of cancer, it may be possible to elucidate the mechanism by which healthy tissues are transformed into malignancies. Currently, the primary methods used to evaluate arrays involve the interactive review of TMA samples while they are viewed under a microscope, subjectively evaluated, and scored by a technician. This process is extremely slow, tedious, and prone to error. In order to facilitate large-scale, multi-institutional studies, a more automated and reliable means for analyzing TMAs is needed. We report here a web-based prototype which features automated imaging, registration, and distributed archiving of TMAs in multiuser network environments. The system utilizes a principal color decomposition approach to identify and characterize the predominant staining signatures of specimens in color space. This strategy was shown to be reliable for detecting and quantifying the immunohistochemical expression levels for TMAs.

Radioactive cDNA microarray in neurospsychiatry

International Nuclear Information System (INIS)

Choe, Jae Gol; Shin, Kyung Ho; Lee, Min Soo; Kim, Meyoung Kon

2003-01-01

Microarray technology allows the simultaneous analysis of gene expression patterns of thousands of genes, in a systematic fashion, under a similar set of experimental conditions, thus making the data highly comparable. In some cases arrays are used simply as a primary screen leading to downstream molecular characterization of individual gene candidates. In other cases, the goal of expression profiling is to begin to identify complex regulatory networks underlying developmental processes and disease states. Microarrays were originally used with cell lines or other simple model systems. More recently, microarrays have been used in the analysis of more complex biological tissues including neural systems and the brain. The application of cDNA arrays in neuropsychiatry has lagged behind other fields for a number of reasons. These include a requirement for a large amount of input probe RNA in fluorescent-glass based array systems and the cellular complexity introduced by multicellular brain and neural tissues. An additional factor that impacts the general use of microarrays in neuropsychiatry is the lack of availability of sequenced clone sets from model systems. While human cDNA clones have been widely available, high quality rat, mouse, and drosophilae, among others are just becoming widely available. A final factor in the application of cDNA microarrays in neuropsychiatry is cost of commercial arrays. As academic microarray facilitates become more commonplace custom made arrays will become more widely available at a lower cost allowing more widespread applications. In summary, microarray technology is rapidly having an impact on many areas of biomedical research. Radioisotope-nylon based microarrays offer alternatives that may in some cases be more sensitive, flexible, inexpensive, and universal as compared to other array formats, such as fluorescent-glass arrays. In some situations of limited RNA or exotic species, radioactive membrane microarrays may be the most

Radioactive cDNA microarray in neurospsychiatry

Energy Technology Data Exchange (ETDEWEB)

Choe, Jae Gol; Shin, Kyung Ho; Lee, Min Soo; Kim, Meyoung Kon [Korea University Medical School, Seoul (Korea, Republic of)

2003-02-01

Microarray technology allows the simultaneous analysis of gene expression patterns of thousands of genes, in a systematic fashion, under a similar set of experimental conditions, thus making the data highly comparable. In some cases arrays are used simply as a primary screen leading to downstream molecular characterization of individual gene candidates. In other cases, the goal of expression profiling is to begin to identify complex regulatory networks underlying developmental processes and disease states. Microarrays were originally used with cell lines or other simple model systems. More recently, microarrays have been used in the analysis of more complex biological tissues including neural systems and the brain. The application of cDNA arrays in neuropsychiatry has lagged behind other fields for a number of reasons. These include a requirement for a large amount of input probe RNA in fluorescent-glass based array systems and the cellular complexity introduced by multicellular brain and neural tissues. An additional factor that impacts the general use of microarrays in neuropsychiatry is the lack of availability of sequenced clone sets from model systems. While human cDNA clones have been widely available, high quality rat, mouse, and drosophilae, among others are just becoming widely available. A final factor in the application of cDNA microarrays in neuropsychiatry is cost of commercial arrays. As academic microarray facilitates become more commonplace custom made arrays will become more widely available at a lower cost allowing more widespread applications. In summary, microarray technology is rapidly having an impact on many areas of biomedical research. Radioisotope-nylon based microarrays offer alternatives that may in some cases be more sensitive, flexible, inexpensive, and universal as compared to other array formats, such as fluorescent-glass arrays. In some situations of limited RNA or exotic species, radioactive membrane microarrays may be the most

Comparison of Nanostring nCounter® Data on FFPE Colon Cancer Samples and Affymetrix Microarray Data on Matched Frozen Tissues.

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Xi Chen

Full Text Available The prognosis of colorectal cancer (CRC stage II and III patients remains a challenge due to the difficulties of finding robust biomarkers suitable for testing clinical samples. The majority of published gene signatures of CRC have been generated on fresh frozen colorectal tissues. Because collection of frozen tissue is not practical for routine surgical pathology practice, a clinical test that improves prognostic capabilities beyond standard pathological staging of colon cancer will need to be designed for formalin-fixed paraffin-embedded (FFPE tissues. The NanoString nCounter® platform is a gene expression analysis tool developed for use with FFPE-derived samples. We designed a custom nCounter® codeset based on elements from multiple published fresh frozen tissue microarray-based prognostic gene signatures for colon cancer, and we used this platform to systematically compare gene expression data from FFPE with matched microarray array data from frozen tissues. Our results show moderate correlation of gene expression between two platforms and discovery of a small subset of genes as candidate biomarkers for colon cancer prognosis that are detectable and quantifiable in FFPE tissue sections.

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

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

2014-08-01

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

3D Biomaterial Microarrays for Regenerative Medicine

DEFF Research Database (Denmark)

Gaharwar, Akhilesh K.; Arpanaei, Ayyoob; Andresen, Thomas Lars

2015-01-01

Three dimensional (3D) biomaterial microarrays hold enormous promise for regenerative medicine because of their ability to accelerate the design and fabrication of biomimetic materials. Such tissue-like biomaterials can provide an appropriate microenvironment for stimulating and controlling stem...... for tissue engineering and drug screening applications....... cell differentiation into tissue-specifi c lineages. The use of 3D biomaterial microarrays can, if optimized correctly, result in a more than 1000-fold reduction in biomaterials and cells consumption when engineering optimal materials combinations, which makes these miniaturized systems very attractive...

Support vector machine classification and validation of cancer tissue samples using microarray expression data.

Science.gov (United States)

Furey, T S; Cristianini, N; Duffy, N; Bednarski, D W; Schummer, M; Haussler, D

2000-10-01

DNA microarray experiments generating thousands of gene expression measurements, are being used to gather information from tissue and cell samples regarding gene expression differences that will be useful in diagnosing disease. We have developed a new method to analyse this kind of data using support vector machines (SVMs). This analysis consists of both classification of the tissue samples, and an exploration of the data for mis-labeled or questionable tissue results. We demonstrate the method in detail on samples consisting of ovarian cancer tissues, normal ovarian tissues, and other normal tissues. The dataset consists of expression experiment results for 97,802 cDNAs for each tissue. As a result of computational analysis, a tissue sample is discovered and confirmed to be wrongly labeled. Upon correction of this mistake and the removal of an outlier, perfect classification of tissues is achieved, but not with high confidence. We identify and analyse a subset of genes from the ovarian dataset whose expression is highly differentiated between the types of tissues. To show robustness of the SVM method, two previously published datasets from other types of tissues or cells are analysed. The results are comparable to those previously obtained. We show that other machine learning methods also perform comparably to the SVM on many of those datasets. The SVM software is available at http://www.cs. columbia.edu/ approximately bgrundy/svm.

The tissue microarray data exchange specification: Extending TMA DES to provide flexible scoring and incorporate virtual slides

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Alexander Wright

2011-01-01

Full Text Available Background: Tissue MicroArrays (TMAs are a high throughput technology for rapid analysis of protein expression across hundreds of patient samples. Often, data relating to TMAs is specific to the clinical trial or experiment it is being used for, and not interoperable. The Tissue Microarray Data Exchange Specification (TMA DES is a set of eXtensible Markup Language (XML-based protocols for storing and sharing digitized Tissue Microarray data. XML data are enclosed by named tags which serve as identifiers. These tag names can be Common Data Elements (CDEs, which have a predefined meaning or semantics. By using this specification in a laboratory setting with increasing demands for digital pathology integration, we found that the data structure lacked the ability to cope with digital slide imaging in respect to web-enabled digital pathology systems and advanced scoring techniques. Materials and Methods: By employing user centric design, and observing behavior in relation to TMA scoring and associated data, the TMA DES format was extended to accommodate the current limitations. This was done with specific focus on developing a generic tool for handling any given scoring system, and utilizing data for multiple observations and observers. Results: DTDs were created to validate the extensions of the TMA DES protocol, and a test set of data containing scores for 6,708 TMA core images was generated. The XML was then read into an image processing algorithm to utilize the digital pathology data extensions, and scoring results were easily stored alongside the existing multiple pathologist scores. Conclusions: By extending the TMA DES format to include digital pathology data and customizable scoring systems for TMAs, the new system facilitates the collaboration between pathologists and organizations, and can be used in automatic or manual data analysis. This allows complying systems to effectively communicate complex and varied scoring data.

Classification across gene expression microarray studies

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Kuner Ruprecht

2009-12-01

Full Text Available Abstract Background The increasing number of gene expression microarray studies represents an important resource in biomedical research. As a result, gene expression based diagnosis has entered clinical practice for patient stratification in breast cancer. However, the integration and combined analysis of microarray studies remains still a challenge. We assessed the potential benefit of data integration on the classification accuracy and systematically evaluated the generalization performance of selected methods on four breast cancer studies comprising almost 1000 independent samples. To this end, we introduced an evaluation framework which aims to establish good statistical practice and a graphical way to monitor differences. The classification goal was to correctly predict estrogen receptor status (negative/positive and histological grade (low/high of each tumor sample in an independent study which was not used for the training. For the classification we chose support vector machines (SVM, predictive analysis of microarrays (PAM, random forest (RF and k-top scoring pairs (kTSP. Guided by considerations relevant for classification across studies we developed a generalization of kTSP which we evaluated in addition. Our derived version (DV aims to improve the robustness of the intrinsic invariance of kTSP with respect to technologies and preprocessing. Results For each individual study the generalization error was benchmarked via complete cross-validation and was found to be similar for all classification methods. The misclassification rates were substantially higher in classification across studies, when each single study was used as an independent test set while all remaining studies were combined for the training of the classifier. However, with increasing number of independent microarray studies used in the training, the overall classification performance improved. DV performed better than the average and showed slightly less variance. In

Comparing transformation methods for DNA microarray data

NARCIS (Netherlands)

Thygesen, Helene H.; Zwinderman, Aeilko H.

2004-01-01

Background: When DNA microarray data are used for gene clustering, genotype/phenotype correlation studies, or tissue classification the signal intensities are usually transformed and normalized in several steps in order to improve comparability and signal/noise ratio. These steps may include

Comparison of microarray platforms for measuring differential microRNA expression in paired normal/cancer colon tissues.

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Maurizio Callari

Full Text Available BACKGROUND: Microarray technology applied to microRNA (miRNA profiling is a promising tool in many research fields; nevertheless, independent studies characterizing the same pathology have often reported poorly overlapping results. miRNA analysis methods have only recently been systematically compared but only in few cases using clinical samples. METHODOLOGY/PRINCIPAL FINDINGS: We investigated the inter-platform reproducibility of four miRNA microarray platforms (Agilent, Exiqon, Illumina, and Miltenyi, comparing nine paired tumor/normal colon tissues. The most concordant and selected discordant miRNAs were further studied by quantitative RT-PCR. Globally, a poor overlap among differentially expressed miRNAs identified by each platform was found. Nevertheless, for eight miRNAs high agreement in differential expression among the four platforms and comparability to qRT-PCR was observed. Furthermore, most of the miRNA sets identified by each platform are coherently enriched in data from the other platforms and the great majority of colon cancer associated miRNA sets derived from the literature were validated in our data, independently from the platform. Computational integration of miRNA and gene expression profiles suggested that anti-correlated predicted target genes of differentially expressed miRNAs are commonly enriched in cancer-related pathways and in genes involved in glycolysis and nutrient transport. CONCLUSIONS: Technical and analytical challenges in measuring miRNAs still remain and further research is required in order to increase consistency between different microarray-based methodologies. However, a better inter-platform agreement was found by looking at miRNA sets instead of single miRNAs and through a miRNAs - gene expression integration approach.

Fascin and EMMPRIN expression in primary mucinous tumors of ovary: a tissue microarray study.

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Alici, Omer; Kefeli, Mehmet; Yildiz, Levent; Baris, Sancar; Karagoz, Filiz; Kandemir, Bedri

2014-12-01

The aim of this study was to compare the expressions of fascin and EMMPRIN in primary malignant, borderline and benign mucinous ovarian tumors, and to investigate the relationship of these markers with tumor progression and their applicability to differential diagnosis. An immunohistochemical study was performed for fascin and EMMPRIN using the tissue microarray technique. Eighty-one cases were included in the study; there were 37 benign, 25 borderline and 19 malignant primary mucinous ovarian tumors. For each case, a total staining score was determined, consisting of scores for extent of staining and intensity of staining. The cases were allocated to negative, weakly positive and strongly positive staining categories, according to the total staining score. Both of the markers were significantly negative in benign tumors as compared with borderline and malignant tumors. There was no significant difference between borderline and malignant groups for both markers. Sixty-eight percent of malignant tumors were stained positive by fascin, while this rate was 40% for borderline mucinous tumors. All malignant tumors were strongly stained positive for EMMPRIN, while this rate was 92% for borderline mucinous tumors. The rest of the cases stained weakly positive. No significant difference in staining score was found between fascin and EMMPRIN expression. In ovarian primary mucinous tumors, fascin and EMMPRIN may play an important role in tumor progression from benign tumor to carcinoma. In that context, EMMPRIN and fascin expression may have potential application in the differential diagnosis of some diagnostically problematic mucinous ovarian tumors. However, the differential diagnostic applicability of EMMPRIN appears to be more limited than that of fascin due to its wide spectrum of staining in mucinous ovarian tumors. Copyright © 2014 Elsevier GmbH. All rights reserved.

No-cost manual method for preparation of tissue microarrays having high quality comparable to semiautomated methods.

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Foda, Abd Al-Rahman Mohammad

2013-05-01

Manual tissue microarray (TMA) construction had been introduced to avoid the high cost of automated and semiautomated techniques. The cheapest and simplest technique for constructing manual TMA was that of using mechanical pencil tips. This study was carried out to modify this method, aiming to raise its quality to reach that of expensive ones. Some modifications were introduced to Shebl's technique. Two conventional mechanical pencil tips of different diameters were used to construct the recipient blocks. A source of mild heat was used, and blocks were incubated at 38°C overnight. With our modifications, 3 high-density TMA blocks were constructed. We successfully performed immunostaining without substantial tissue loss. Our modifications increased the number of cores per block and improved the stability of the cores within the paraffin block. This new, modified technique is a good alternative for expensive machines in many laboratories.

Tissue Microarray Assessment of Novel Prostate Cancer Biomarkers AMACR and EZH2 and Immunologic Response to Them in African-American and Caucasian Men

National Research Council Canada - National Science Library

Mehra, Rohit

2007-01-01

.... We constructed 5 tissue microarrays representing 40 African-American and 159 Caucasian prostate cancer patients and performed immunohistochemistry on these arrays using antibody to AMACR and EZH2...

Tissue Microarray Assessment of Novel Prostate Cancer Biomarkers AMACR and EZH2 and Immunologic Response to them in African-American and Caucasian Men

National Research Council Canada - National Science Library

Mehra, Rohit

2006-01-01

.... We constructed 5 tissue microarrays representing 40 African-American and 159 Caucasian prostate cancer patients and performed immunohistochemistry on these arrays using antibodies to AMACR and EZH2...

The prognostic implication of the expression of EGFR, p53, cyclin D1, Bcl-2 and p16 in primary locally advanced oral squamous cell carcinoma cases: a tissue microarray study.

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Solomon, Monica Charlotte; Vidyasagar, M S; Fernandes, Donald; Guddattu, Vasudev; Mathew, Mary; Shergill, Ankur Kaur; Carnelio, Sunitha; Chandrashekar, Chetana

2016-12-01

Oral squamous cell carcinomas comprise a heterogeneous tumor cell population with varied molecular characteristics, which makes prognostication of these tumors a complex and challenging issue. Thus, molecular profiling of these tumors is advantageous for an accurate prognostication and treatment planning. This is a retrospective study on a cohort of primary locally advanced oral squamous cell carcinomas (n = 178) of an Indian rural population. The expression of EGFR, p53, cyclin D1, Bcl-2 and p16 in a cohort of primary locally advanced oral squamous cell carcinomas was evaluated. A potential biomarker that can predict the tumor response to treatment was identified. Formalin-fixed paraffin-embedded tumor blocks of (n = 178) of histopathologically diagnosed cases of locally advanced oral squamous cell carcinomas were selected. Tissue microarray blocks were constructed with 2 cores of 2 mm diameter from each tumor block. Four-micron-thick sections were cut from these tissue microarray blocks. These tissue microarray sections were immunohistochemically stained for EGFR, p53, Bcl-2, cyclin D1 and p16. In this cohort, EGFR was the most frequently expressed 150/178 (84%) biomarker of the cases. Kaplan-Meier analysis showed a significant association (p = 0.038) between expression of p53 and a poor prognosis. A Poisson regression analysis showed that tumors that expressed p53 had a two times greater chance of recurrence (unadjusted IRR-95% CI 2.08 (1.03, 4.5), adjusted IRR-2.29 (1.08, 4.8) compared with the tumors that did not express this biomarker. Molecular profiling of oral squamous cell carcinomas will enable us to categorize our patients into more realistic risk groups. With biologically guided tumor characterization, personalized treatment protocols can be designed for individual patients, which will improve the quality of life of these patients.

Protein microarray: sensitive and effective immunodetection for drug residues

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Zer Cindy

2010-02-01

Full Text Available Abstract Background Veterinary drugs such as clenbuterol (CL and sulfamethazine (SM2 are low molecular weight ( Results The artificial antigens were spotted on microarray slides. Standard concentrations of the compounds were added to compete with the spotted antigens for binding to the antisera to determine the IC50. Our microarray assay showed the IC50 were 39.6 ng/ml for CL and 48.8 ng/ml for SM2, while the traditional competitive indirect-ELISA (ci-ELISA showed the IC50 were 190.7 ng/ml for CL and 156.7 ng/ml for SM2. We further validated the two methods with CL fortified chicken muscle tissues, and the protein microarray assay showed 90% recovery while the ci-ELISA had 76% recovery rate. When tested with CL-fed chicken muscle tissues, the protein microarray assay had higher sensitivity (0.9 ng/g than the ci-ELISA (0.1 ng/g for detection of CL residues. Conclusions The protein microarrays showed 4.5 and 3.5 times lower IC50 than the ci-ELISA detection for CL and SM2, respectively, suggesting that immunodetection of small molecules with protein microarray is a better approach than the traditional ELISA technique.

Production of tissue microarrays, immunohistochemistry staining and digitalization within the human protein atlas.

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Kampf, Caroline; Olsson, Ingmarie; Ryberg, Urban; Sjöstedt, Evelina; Pontén, Fredrik

2012-05-31

The tissue microarray (TMA) technology provides the means for high-throughput analysis of multiple tissues and cells. The technique is used within the Human Protein Atlas project for global analysis of protein expression patterns in normal human tissues, cancer and cell lines. Here we present the assembly of 1 mm cores, retrieved from microscopically selected representative tissues, into a single recipient TMA block. The number and size of cores in a TMA block can be varied from approximately forty 2 mm cores to hundreds of 0.6 mm cores. The advantage of using TMA technology is that large amount of data can rapidly be obtained using a single immunostaining protocol to avoid experimental variability. Importantly, only limited amount of scarce tissue is needed, which allows for the analysis of large patient cohorts (1 2). Approximately 250 consecutive sections (4 μm thick) can be cut from a TMA block and used for immunohistochemical staining to determine specific protein expression patterns for 250 different antibodies. In the Human Protein Atlas project, antibodies are generated towards all human proteins and used to acquire corresponding protein profiles in both normal human tissues from 144 individuals and cancer tissues from 216 different patients, representing the 20 most common forms of human cancer. Immunohistochemically stained TMA sections on glass slides are scanned to create high-resolution images from which pathologists can interpret and annotate the outcome of immunohistochemistry. Images together with corresponding pathology-based annotation data are made publically available for the research community through the Human Protein Atlas portal (www.proteinatlas.org) (Figure 1) (3 4). The Human Protein Atlas provides a map showing the distribution and relative abundance of proteins in the human body. The current version contains over 11 million images with protein expression data for 12.238 unique proteins, corresponding to more than 61% of all proteins

The tissue microarray data exchange specification: A document type definition to validate and enhance XML data

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Nohle, David G; Ayers, Leona W

2005-01-01

Background The Association for Pathology Informatics (API) Extensible Mark-up Language (XML) TMA Data Exchange Specification (TMA DES) proposed in April 2003 provides a community-based, open source tool for sharing tissue microarray (TMA) data in a common format. Each tissue core within an array has separate data including digital images; therefore an organized, common approach to produce, navigate and publish such data facilitates viewing, sharing and merging TMA data from different laboratories. The AIDS and Cancer Specimen Resource (ACSR) is a HIV/AIDS tissue bank consortium sponsored by the National Cancer Institute (NCI) Division of Cancer Treatment and Diagnosis (DCTD). The ACSR offers HIV-related malignancies and uninfected control tissues in microarrays (TMA) accompanied by de-identified clinical data to approved researchers. Exporting our TMA data into the proposed API specified format offers an opportunity to evaluate the API specification in an applied setting and to explore its usefulness. Results A document type definition (DTD) that governs the allowed common data elements (CDE) in TMA DES export XML files was written, tested and evolved and is in routine use by the ACSR. This DTD defines TMA DES CDEs which are implemented in an external file that can be supplemented by internal DTD extensions for locally defined TMA data elements (LDE). Conclusion ACSR implementation of the TMA DES demonstrated the utility of the specification and allowed application of a DTD to validate the language of the API specified XML elements and to identify possible enhancements within our TMA data management application. Improvements to the specification have additionally been suggested by our experience in importing other institution's exported TMA data. Enhancements to TMA DES to remove ambiguous situations and clarify the data should be considered. Better specified identifiers and hierarchical relationships will make automatic use of the data possible. Our tool can be

Re-Punching Tissue Microarrays Is Possible: Why Can This Be Useful and How to Do It

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Aurélien Lacombe

2015-05-01

Full Text Available Tissue microarray (TMA methodology allows the concomitant analysis of hundreds of tissue specimens arrayed in the same manner on a recipient block. Subsequently, all samples can be processed under identical conditions, such as antigen retrieval procedure, reagent concentrations, incubation times with antibodies/probes, and escaping the inter-assays variability. Therefore, the use of TMA has revolutionized histopathology translational research projects and has become a tool very often used for putative biomarker investigations. TMAs are particularly relevant for large scale analysis of a defined disease entity. In the course of these exploratory studies, rare subpopulations can be discovered or identified. This can refer to subsets of patients with more particular phenotypic or genotypic disease with low incidence or to patients receiving a particular treatment. Such rare cohorts should be collected for more specific investigations at a later time, when, possibly, more samples of a rare identity will be available as well as more knowledge derived from concomitant, e.g., genetic, investigations will have been acquired. In this article we analyze for the first time the limits and opportunities to construct new TMA blocks using tissues from older available arrays and supplementary donor blocks. In summary, we describe the reasons and technical details for the construction of rare disease entities arrays.

Expression of the G protein-coupled estrogen receptor (GPER in endometriosis: a tissue microarray study

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Samartzis Nicolas

2012-04-01

Full Text Available Abstract Background The G protein-coupled estrogen receptor (GPER is thought to be involved in non-genomic estrogen responses as well as processes such as cell proliferation and migration. In this study, we analyzed GPER expression patterns from endometriosis samples and normal endometrial tissue samples and compared these expression profiles to those of the classical sex hormone receptors. Methods A tissue microarray, which included 74 samples from different types of endometriosis (27 ovarian, 19 peritoneal and 28 deep-infiltrating and 30 samples from normal endometrial tissue, was used to compare the expression levels of the GPER, estrogen receptor (ER-alpha, ER-beta and progesterone receptor (PR. The immunoreactive score (IRS was calculated separately for epithelium and stroma as the product of the staining intensity and the percentage of positive cells. The expression levels of the hormonal receptors were dichotomized into low (IRS  =6 expression groups. Results The mean epithelial IRS (+/−standard deviation, range of cytoplasmic GPER expression was 1.2 (+/−1.7, 0–4 in normal endometrium and 5.1 (+/−3.5, 0–12 in endometriosis (p p = 0.71, of ER-alpha 10.6 (+/−2.4, 3–12 and 9.8 (+/−3.0, 2–12; p = 0.26, of ER-beta 2.4 (+/−2.2; 0–8 and 5.6 (+/−2.6; 0–10; p p p p = 0.001, of ER-beta 1.8 (+/−2.0; 0–8 and 5.4 (+/−2.5; 0–10; p p���= 0.044, respectively. Cytoplasmic GPER expression was not detectable in the stroma of endometrium and endometriosis. The observed frequency of high epithelial cytoplasmic GPER expression levels was 50% (n = 30/60 in the endometriosis and none (0/30 in the normal endometrium samples (p p = 0.01, as compared to peritoneal (9/18, 50% or deep-infiltrating endometriotic lesions (7/22, 31.8%. The frequency of high stromal nuclear GPER expression levels was 100% (n = 74/74 in endometriosis and 76.7% (n = 23/30 in normal endometrium (p�

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

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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.

Microarrays in brain research: the good, the bad and the ugly.

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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

How the RNA isolation method can affect microRNA microarray results

DEFF Research Database (Denmark)

Podolska, Agnieszka; Kaczkowski, Bogumil; Litman, Thomas

2011-01-01

RNA microarray analysis on porcine brain tissue. One method is a phenol-guanidine isothiocyanate-based procedure that permits isolation of total RNA. The second method, miRVana™ microRNA isolation, is column based and recovers the small RNA fraction alone. We found that microarray analyses give different results...... that depend on the RNA fraction used, in particular because some microRNAs appear very sensitive to the RNA isolation method. We conclude that precautions need to be taken when comparing microarray studies based on RNA isolated with different methods.......The quality of RNA is crucial in gene expression experiments. RNA degradation interferes in the measurement of gene expression, and in this context, microRNA quantification can lead to an incorrect estimation. In the present study, two different RNA isolation methods were used to perform micro...

A texture based pattern recognition approach to distinguish melanoma from non-melanoma cells in histopathological tissue microarray sections.

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Elton Rexhepaj

Full Text Available AIMS: Immunohistochemistry is a routine practice in clinical cancer diagnostics and also an established technology for tissue-based research regarding biomarker discovery efforts. Tedious manual assessment of immunohistochemically stained tissue needs to be fully automated to take full advantage of the potential for high throughput analyses enabled by tissue microarrays and digital pathology. Such automated tools also need to be reproducible for different experimental conditions and biomarker targets. In this study we present a novel supervised melanoma specific pattern recognition approach that is fully automated and quantitative. METHODS AND RESULTS: Melanoma samples were immunostained for the melanocyte specific target, Melan-A. Images representing immunostained melanoma tissue were then digitally processed to segment regions of interest, highlighting Melan-A positive and negative areas. Color deconvolution was applied to each region of interest to separate the channel containing the immunohistochemistry signal from the hematoxylin counterstaining channel. A support vector machine melanoma classification model was learned from a discovery melanoma patient cohort (n = 264 and subsequently validated on an independent cohort of melanoma patient tissue sample images (n = 157. CONCLUSION: Here we propose a novel method that takes advantage of utilizing an immuhistochemical marker highlighting melanocytes to fully automate the learning of a general melanoma cell classification model. The presented method can be applied on any protein of interest and thus provides a tool for quantification of immunohistochemistry-based protein expression in melanoma.

Carbohydrate microarrays

DEFF Research Database (Denmark)

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

2012-01-01

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

Candidate Genes for Testicular Cancer Evaluated by In Situ Protein Expression Analyses on Tissue Microarrays

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Rolf I. Skotheim

2003-09-01

Full Text Available By the use of high-throughput molecular technologies, the number of genes and proteins potentially relevant to testicular germ cell tumor (TGCT and other diseases will increase rapidly. In a recent transcriptional profiling, we demonstrated the overexpression of GRB7 and JUP in TGCTs, confirmed the reported overexpression of CCND2. We also have recent evidences for frequent genetic alterations of FHIT and epigenetic alterations of MGMT. To evaluate whether the expression of these genes is related to any clinicopathological variables, we constructed a tissue microarray with 510 testicular tissue cores from 279 patients diagnosed with TGCT, covering various histological subgroups and clinical stages. By immunohistochemistry, we found that JUP, GRB7, CCND2 proteins were rarely present in normal testis, but frequently expressed at high levels in TGCT. Additionally, all premalignant intratubular germ cell neoplasias were JUP-immunopositive. MGMT and FHIT were expressed by normal testicular tissues, but at significantly lower frequencies in TGCT. Except for CCND2, the expressions of all markers were significantly associated with various TGCT subtypes. In summary, we have developed a high-throughput tool for the evaluation of TGCT markers, utilized this to validate five candidate genes whose protein expressions were indeed deregulated in TGCT.

Microarray Data Processing Techniques for Genome-Scale Network Inference from Large Public Repositories.

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Chockalingam, Sriram; Aluru, Maneesha; Aluru, Srinivas

2016-09-19

Pre-processing of microarray data is a well-studied problem. Furthermore, all popular platforms come with their own recommended best practices for differential analysis of genes. However, for genome-scale network inference using microarray data collected from large public repositories, these methods filter out a considerable number of genes. This is primarily due to the effects of aggregating a diverse array of experiments with different technical and biological scenarios. Here we introduce a pre-processing pipeline suitable for inferring genome-scale gene networks from large microarray datasets. We show that partitioning of the available microarray datasets according to biological relevance into tissue- and process-specific categories significantly extends the limits of downstream network construction. We demonstrate the effectiveness of our pre-processing pipeline by inferring genome-scale networks for the model plant Arabidopsis thaliana using two different construction methods and a collection of 11,760 Affymetrix ATH1 microarray chips. Our pre-processing pipeline and the datasets used in this paper are made available at http://alurulab.cc.gatech.edu/microarray-pp.

Microarray evaluation of age-related changes in human dental pulp.

Science.gov (United States)

Tranasi, Michelangelo; Sberna, Maria Teresa; Zizzari, Vincenzo; D'Apolito, Giuseppe; Mastrangelo, Filiberto; Salini, Luisa; Stuppia, Liborio; Tetè, Stefano

2009-09-01

The dental pulp undergoes age-related changes that could be ascribed to physiological, defensive, or pathological irritant-induced changes. These changes are regulated by pulp cell activity and by a variety of extracellular matrix (ECM) macromolecules, playing important roles in growth regulation, tissue differentiation and organization, formation of calcified tissue, and defense mechanisms and reactions to inflammatory stimuli. The aim of this research was to better understand the genetic changes that underlie the histological modification of the dental pulp in aging. The gene expression profile of the human dental pulp in young and older subjects was compared by RNA microarray analysis that allowed to simultaneously analyze the expression levels of thousands of genes. Data were statistically analyzed by Significance Analysis of Microarrays (SAM) Ingenuity Pathway Analysis (IPA) software. Semiquantitative and real-time reverse-transcriptase polymerase chain reaction analyses were performed to confirm the results. Microarray analysis revealed several differentially expressed genes that were categorized in growth factors, transcription regulators, apoptosis regulators, and genes of the ECM. The comparison analysis showed a high expression level of the biological functions of cell and tissue differentiation, development, and proliferation and of the immune, lymphatic, and hematologic system in young dental pulp, whereas the pathway of apoptosis was highly expressed in older dental pulp. Expression profile analyses of human dental pulp represent a sensible and useful tool for the study of mechanisms involved in differentiation, growth and aging of human dental pulp in physiological and pathological conditions.

Altered metabolism of growth hormone receptor mutant mice: a combined NMR metabonomics and microarray study.

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Horst Joachim Schirra

Full Text Available BACKGROUND: Growth hormone is an important regulator of post-natal growth and metabolism. We have investigated the metabolic consequences of altered growth hormone signalling in mutant mice that have truncations at position 569 and 391 of the intracellular domain of the growth hormone receptor, and thus exhibit either low (around 30% maximum or no growth hormone-dependent STAT5 signalling respectively. These mutations result in altered liver metabolism, obesity and insulin resistance. METHODOLOGY/PRINCIPAL FINDINGS: The analysis of metabolic changes was performed using microarray analysis of liver tissue and NMR metabonomics of urine and liver tissue. Data were analyzed using multivariate statistics and Gene Ontology tools. The metabolic profiles characteristic for each of the two mutant groups and wild-type mice were identified with NMR metabonomics. We found decreased urinary levels of taurine, citrate and 2-oxoglutarate, and increased levels of trimethylamine, creatine and creatinine when compared to wild-type mice. These results indicate significant changes in lipid and choline metabolism, and were coupled with increased fat deposition, leading to obesity. The microarray analysis identified changes in expression of metabolic enzymes correlating with alterations in metabolite concentration both in urine and liver. Similarity of mutant 569 to the wild-type was seen in young mice, but the pattern of metabolites shifted to that of the 391 mutant as the 569 mice became obese after six months age. CONCLUSIONS/SIGNIFICANCE: The metabonomic observations were consistent with the parallel analysis of gene expression and pathway mapping using microarray data, identifying metabolites and gene transcripts involved in hepatic metabolism, especially for taurine, choline and creatinine metabolism. The systems biology approach applied in this study provides a coherent picture of metabolic changes resulting from impaired STAT5 signalling by the growth hormone

Identification of New Players in Hepatocarcinogenesis: Limits and Opportunities of Using Tissue Microarray (TMA

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Luca Quagliata

2014-04-01

Full Text Available Liver tumours are among the leading causes of cancer-related death worldwide and hepatocellular carcinoma (HCC accounts for the vast majority of liver tumours. When detected at an early stage of disease, patients might still be eligible for surgical-based curative treatments. However, currently only small portion of HCC affected patients are diagnosed at an early stage. For late stage HCC no treatment option exists beside the multi-tyrosine kinase inhibitor Sorafenib. Thus new molecular targets and treatment options for HCC are urgently needed. Nevertheless, despite some improvements in diagnosis and patient management, the biology of liver tumour remains inadequately understood, mainly because these tumours have shown to harbour a highly complex genomic landscape. In addition, one major obstacle delaying the identification of new molecular targets in biomedical research is the necessity to validate them using a large collection of tissue specimens. Tissue microarray (TMA technology allows the prompt molecular profiling of multiple tissue specimens and is therefore ideal to analyze presumptive candidate biomarkers in a fast an effective manner. The use of TMA has substantial benefits over standard techniques and represents a significant advancement in molecular pathology. For example, TMA technology reduces laboratory work, offers a high level of experimental uniformity and provides a judicious use of precious tissue. On the other hand, one potential limitation of using TMA is that the small cores sampled may not be representative of whole tumors. This issue is very critical in particularly heterogeneous cancers such as HCC. For liver focused studies, it is ideal to evaluate the staining patters of a determined marker over the structure of an entire acinus and to define staining in as many as possible anatomical regions. In this review we analyze the limits and opportunities offered by the usage of TMA technology in HCC research. In summary, TMA

Identification of New Players in Hepatocarcinogenesis: Limits and Opportunities of Using Tissue Microarray (TMA).

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Quagliata, Luca; Schlageter, Manuel; Quintavalle, Cristina; Tornillo, Luigi; Terracciano, Luigi M

2014-04-15

Liver tumours are among the leading causes of cancer-related death worldwide and hepatocellular carcinoma (HCC) accounts for the vast majority of liver tumours. When detected at an early stage of disease, patients might still be eligible for surgical-based curative treatments. However, currently only small portion of HCC affected patients are diagnosed at an early stage. For late stage HCC no treatment option exists beside the multi-tyrosine kinase inhibitor Sorafenib. Thus new molecular targets and treatment options for HCC are urgently needed. Nevertheless, despite some improvements in diagnosis and patient management, the biology of liver tumour remains inadequately understood, mainly because these tumours have shown to harbour a highly complex genomic landscape. In addition, one major obstacle delaying the identification of new molecular targets in biomedical research is the necessity to validate them using a large collection of tissue specimens. Tissue microarray (TMA) technology allows the prompt molecular profiling of multiple tissue specimens and is therefore ideal to analyze presumptive candidate biomarkers in a fast an effective manner. The use of TMA has substantial benefits over standard techniques and represents a significant advancement in molecular pathology. For example, TMA technology reduces laboratory work, offers a high level of experimental uniformity and provides a judicious use of precious tissue. On the other hand, one potential limitation of using TMA is that the small cores sampled may not be representative of whole tumors. This issue is very critical in particularly heterogeneous cancers such as HCC. For liver focused studies, it is ideal to evaluate the staining patters of a determined marker over the structure of an entire acinus and to define staining in as many as possible anatomical regions. In this review we analyze the limits and opportunities offered by the usage of TMA technology in HCC research. In summary, TMA has

Universal Reference RNA as a standard for microarray experiments

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Fero Michael

2004-03-01

Full Text Available Abstract Background Obtaining reliable and reproducible two-color microarray gene expression data is critically important for understanding the biological significance of perturbations made on a cellular system. Microarray design, RNA preparation and labeling, hybridization conditions and data acquisition and analysis are variables difficult to simultaneously control. A useful tool for monitoring and controlling intra- and inter-experimental variation is Universal Reference RNA (URR, developed with the goal of providing hybridization signal at each microarray probe location (spot. Measuring signal at each spot as the ratio of experimental RNA to reference RNA targets, rather than relying on absolute signal intensity, decreases variability by normalizing signal output in any two-color hybridization experiment. Results Human, mouse and rat URR (UHRR, UMRR and URRR, respectively were prepared from pools of RNA derived from individual cell lines representing different tissues. A variety of microarrays were used to determine percentage of spots hybridizing with URR and producing signal above a user defined threshold (microarray coverage. Microarray coverage was consistently greater than 80% for all arrays tested. We confirmed that individual cell lines contribute their own unique set of genes to URR, arguing for a pool of RNA from several cell lines as a better configuration for URR as opposed to a single cell line source for URR. Microarray coverage comparing two separately prepared batches each of UHRR, UMRR and URRR were highly correlated (Pearson's correlation coefficients of 0.97. Conclusion Results of this study demonstrate that large quantities of pooled RNA from individual cell lines are reproducibly prepared and possess diverse gene representation. This type of reference provides a standard for reducing variation in microarray experiments and allows more reliable comparison of gene expression data within and between experiments and

Avaliação de combinações de técnicas alternativas de construção e montagem de blocos de tissue microarray Evaluation of alternative technique combinations of building and preparation of tissue microarrays blocks

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Ivan Tiburtino dos Santos Junior

2010-02-01

Full Text Available INTRODUÇÃO E OBJETIVOS: O objetivo deste estudo foi pesquisar diferentes métodos alternativos de tissue microarray (TMA à técnica original e conduzir adaptações desses, combinando diferentes métodos de punção das amostras teciduais e de montagem dos blocos de TMA, de modo a introduzir no Laboratório de Patologia Bucal da Faculdade de Odontologia de Pernambuco da Universidade de Pernambuco (LPBFOP/UPE técnicas de TMA facilmente operáveis, reproduzíveis e de baixo custo. RESULTADOS: Foram reproduzidas quatro técnicas de punção dos blocos doadores e duas de montagem dos blocos de TMA, resultando em oito combinações possíveis. Para cada combinação, foram confeccionados três blocos de TMA, contendo nove, 16 e 32 amostras, respectivamente, e avaliadas quanto a perda de amostras, custo, tempo de confecção e dificuldade. Para blocos com nove amostras, a combinação 2 mostrou-se a mais adequada; para blocos com 16, a combinação 6 foi constatada como a mais eficiente; e para blocos com 32, a combinação 1 apresentou o melhor custo-benefício. CONCLUSÃO: Foi concluído que a escolha da combinação a ser utilizada depende do número de amostras a serem colocadas nos blocos de TMA.INTRODUCTION AND OBJECTIVES: The aim of this study was to investigate different alternative tissue microarray (TMA techniques and to make adaptations, combining different tissue punch and TMA block construction techniques in order to introduce easily reproducible, operational and cost effective TMA techniques in the Oral Pathology Laboratory of Pernambuco College of Dentistry, State University of Pernambuco. METHODS: Four donor punch techniques and two TMA block construction techniques were performed, resulting in a total of eight possible combinations. For each combination three TMA blocks were made, containing 9, 16 and 32 samples, respectively. They were evaluated as to sample loss, cost effectiveness, construction time and difficulty. RESULTS: For

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

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Song Joon J

2007-03-01

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

Microarray Expression Profile of Circular RNAs in Heart Tissue of Mice with Myocardial Infarction-Induced Heart Failure

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Hong-Jin Wu

2016-06-01

Full Text Available Background/Aims: Myocardial infarction (MI is a serious complication of atherosclerosis associated with increasing mortality attributable to heart failure. This study is aimed to assess the global changes in and characteristics of the transcriptome of circular RNAs (circRNAs in heart tissue during MI induced heart failure (HF. Methods: Using a post-myocardial infarction (MI model of HF in mice, we applied microarray assay to examine the transcriptome of circRNAs deregulated in the heart during HF. We confirmed the changes in circRNAs by quantitative PCR. Results: We revealed and confirmed a number of circRNAs that were deregulated during HF, which suggests a potential role of circRNAs in HF. Conclusions: The distinct expression patterns of circulatory circRNAs during HF indicate that circRNAs may actively respond to stress and thus serve as biomarkers of HF diagnosis and treatment.

Generalization of DNA microarray dispersion properties: microarray equivalent of t-distribution

DEFF Research Database (Denmark)

Novak, Jaroslav P; Kim, Seon-Young; Xu, Jun

2006-01-01

BACKGROUND: DNA microarrays are a powerful technology that can provide a wealth of gene expression data for disease studies, drug development, and a wide scope of other investigations. Because of the large volume and inherent variability of DNA microarray data, many new statistical methods have...

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

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Hu, Wenchao; Liu, Yuting; Yan, Jun

2014-01-01

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

Discovery of distinctive gene expression profiles in rheumatoid synovium using cDNA microarray technology: evidence for the existence of multiple pathways of tissue destruction and repair.

NARCIS (Netherlands)

Kraan, TC van der Pouw; Gaalen, van FA; Huizinga, T.W.; Pieterman, E; Breedveld, F.C.; Verweij, C.L.

2003-01-01

Rheumatoid arthritis (RA) is a heterogeneous disease. We used cDNA microarray technology to subclassify RA patients and disclose disease pathways in rheumatoid synovium. Hierarchical clustering of gene expression data identified two main groups of tissues (RA-I and RA-II). A total of 121 genes were

Detection of EGFR and COX-2 Expression by Immunohistochemical Method on a Tissue Microarray Section in Lung Cancer and Biological Significance

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Xinyun WANG

2010-02-01

Full Text Available Background and objective Epidermal growth factor receptor (EGFR and cyclooxygenase-2 (COX-2, which can regulate growth, invasion and metastasis of tumor through relevant signaling pathway, have been detected in a variety of solid tumors. The aim of this study is to investigate the biological significance of EGFR and COX-2 expression in lung cancer and the relationship between them. Methods The expression of EGFR and COX-2 was detected in 89 primary lung cancer tissues, 12 premaliganant lesions, 12 lymph node metastases, and 10 normal lung tissues as the control by immunohistochemical method on a tissue microarray section. Results EGFR protein was detectable in 59.6%, 41.7%, and 66.7% of primary lung cancer tissues, premalignant lesions and lymph node metastases, respectively; COX-2 protein was detectable in 52.8%, 41.7%, and 66.7% of primary lung cancer tissues, premalignant lesions and lymph node metastases, respectively, which were significantly higher than those of the control (P 0.05. COX-2 expression was related to gross type (P < 0.05. A highly positive correlation was observed between EGFR and COX-2 expression (P < 0.01. Conclusion Overexpression of EGFR and COX-2 may play an important role in the tumorgenesis, progression and malignancy of lung cancer. Detection of EGFR and COX-2 expression might be helpful to diagnosis and prognosis of lung cancer.

Strategies for cell manipulation and skeletal tissue engineering using high-throughput polymer blend formulation and microarray techniques.

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Khan, Ferdous; Tare, Rahul S; Kanczler, Janos M; Oreffo, Richard O C; Bradley, Mark

2010-03-01

A combination of high-throughput material formulation and microarray techniques were synergistically applied for the efficient analysis of the biological functionality of 135 binary polymer blends. This allowed the identification of cell-compatible biopolymers permissive for human skeletal stem cell growth in both in vitro and in vivo applications. The blended polymeric materials were developed from commercially available, inexpensive and well characterised biodegradable polymers, which on their own lacked both the structural requirements of a scaffold material and, critically, the ability to facilitate cell growth. Blends identified here proved excellent templates for cell attachment, and in addition, a number of blends displayed remarkable bone-like architecture and facilitated bone regeneration by providing 3D biomimetic scaffolds for skeletal cell growth and osteogenic differentiation. This study demonstrates a unique strategy to generate and identify innovative materials with widespread application in cell biology as well as offering a new reparative platform strategy applicable to skeletal tissues. Copyright (c) 2009 Elsevier Ltd. All rights reserved.

DNA Microarrays: a Powerful Genomic Tool for Biomedical and Clinical Research

OpenAIRE

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 to 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, they reveal differences in genetic makeup, regulat...

Construction of a tissue microarray with two millimeters cores of endometrioid endometrial cancer: factors affecting the quality of the recipient block.

Science.gov (United States)

Gottwald, L; Sęk, P; Piekarski, J; Pasz-Walczak, G; Kubiak, R; Szwalski, J; Spych, M; Suzin, J; Tyliński, W; Topczewska-Tylinska, K; Jeziorski, A

2012-11-01

The tissue microarray (TMA) method currently is not used to render a primary diagnosis of cancer, but its scientific value has been proved in studies of various cancer types. TMA technology still is not used often for uterine tumors, however. We investigated the repeatability of histological diagnosis of endometrioid endometrial cancer (EEC) using conventional histology and TMA using 2 mm cores. We examined EEC tissues from 171 patients. Formalin fixed, paraffin embedded tissue donor blocks from EEC specimens were selected and examined histologically. Duplicate 2 mm tissue cores were inserted into a TMA recipient block. EEC tissues were examined as hematoxylin-eosin stained sections from the TMAs. EEC tissue was identified in the TMAs in 158 cases (92.4%) and not found in 13 cases (7.6%). On the TMA slides, both EEC positive cores were identified in 129 cases (75.4%), but only one core in 29 cases (17.0%). Among 342 biopsies of the donor blocks (each case in duplicate), EEC was found in 287 cases (83.9%) using the TMA: 124/146 (84.9%) with superficial infiltration, 153/178 (86.0%) with deep myometrial infiltration, and 10/18 (55.6%) without myometrial infiltration. We concluded that two 2 mm tissue cores from a biopsy of a donor block inserted into a TMA recipient block were sufficient to diagnose EEC in more than 90% of cases. EEC was identified in the TMAs with similar frequency with respect to superficial and deep myometrial infiltration. Cases without myometrial infiltration were identified less often.

Speckle-type POZ (pox virus and zinc finger protein) protein gene deletion in ovarian cancer: Fluorescence in situ hybridization analysis of a tissue microarray.

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Hu, Xiaoyu; Yang, Zhu; Zeng, Manman; Liu, Y I; Yang, Xiaotao; Li, Yanan; Li, X U; Yu, Qiubo

2016-07-01

The aim of the present study was to investigate the status of speckle-type POZ (pox virus and zinc finger protein) protein (SPOP) gene located on chromosome 17q21 in ovarian cancer (OC). The present study evaluated a tissue microarray, which contained 90 samples of ovarian cancer and 10 samples of normal ovarian tissue, using fluorescence in situ hybridization (FISH). FISH is a method where a SPOP-specific DNA red fluorescence probe was used for the experimental group and a centromere-specific DNA green fluorescence probe for chromosome 17 was used for the control group. The present study demonstrated that a deletion of the SPOP gene was observed in 52.27% (46/88) of the ovarian cancer tissues, but was not identified in normal ovarian tissues. Simultaneously, monosomy 17 was frequently identified in the ovarian cancer tissues, but not in the normal ovarian tissues. Furthermore, the present data revealed that the ovarian cancer histological subtype and grade were significantly associated with a deletion of the SPOP gene, which was assessed by the appearance of monosomy 17 in the ovarian cancer samples; the deletion of the SPOP gene was observed in a large proportion of serous epithelial ovarian cancer (41/61; 67.21%), particularly in grade 3 (31/37; 83.78%). In conclusion, deletion of the SPOP gene on chromosome 17 in ovarian cancer samples, which results from monosomy 17, indicates that the SPOP gene may serve as a tumor suppressor gene in ovarian cancer.

Fibre optic microarrays.

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Walt, David R

2010-01-01

This tutorial review describes how fibre optic microarrays can be used to create a variety of sensing and measurement systems. This review covers the basics of optical fibres and arrays, the different microarray architectures, and describes a multitude of applications. Such arrays enable multiplexed sensing for a variety of analytes including nucleic acids, vapours, and biomolecules. Polymer-coated fibre arrays can be used for measuring microscopic chemical phenomena, such as corrosion and localized release of biochemicals from cells. In addition, these microarrays can serve as a substrate for fundamental studies of single molecules and single cells. The review covers topics of interest to chemists, biologists, materials scientists, and engineers.

Microarray analysis of thioacetamide-treated type 1 diabetic rats

International Nuclear Information System (INIS)

Devi, Sachin S.; Mehendale, Harihara M.

2006-01-01

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

NM23 protein expression in colorectal carcinoma using TMA (tissue microarray: association with metastases and survival

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Levindo Alves de Oliveira

2010-12-01

Full Text Available CONTEXT: NM23, a metastasis suppressor gene, may be associated with prognosis in patients with colorectal carcinoma. OBJECTIVE: To analyze NM23 expression and its association with the presence of lymph node and liver metastases and survival in patients operated on for colorectal carcinoma. METHODS: One hundred thirty patients operated on for colorectal carcinoma were investigated. Tissue microarray blocks containing neoplastic tissue and tumor-adjacent non-neoplastic mucosa were obtained and analyzed by immunohistochemical staining using a monoclonal anti-NM23 antibody. Immunohistochemical expression was assessed using a semiquantitative scoring method, counting the percentage of stained cells. The results were compared regarding morphological and histological characteristics of the colorectal carcinoma, presence of lymph node and liver metastases, tumor staging, and patient survival. Statistical analysis was performed using the Mann-Whitney test, the Kruskal-Wallis test and Fisher's exact test. Survival analysis was performed using the Kaplan-Meier method and the log-rank test. RESULTS: NM23 expression was higher in colorectal carcinoma tissue than in adjacent non-neoplastic mucosa (P<0.0001. NM23 protein expression did not correlate with degree of cell differentiation (P = 0.57, vascular invasion (P = 0.85, lymphatic invasion (P = 0.41, perineural infiltration (P = 0.46, staging (P = 0.19, lymph node metastases (P = 0.08, or liver metastases (P = 0.59. Disease-free survival showed significant association (P = 0.01 with the intensity of NM23 protein immunohistochemical expression in colorectal carcinoma tissue, whereas overall survival showed no association with NM23 protein expression (P = 0.13. CONCLUSIONS: NM23 protein expression was higher in neoplastic colorectal carcinoma tissue than in adjacent non-neoplastic mucosa, showing no correlation with morphological aspects, presence of lymph node or liver metastases, colorectal carcinoma

Development and validation of a flax (Linum usitatissimum L.) gene expression oligo microarray.

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Fenart, Stéphane; Ndong, Yves-Placide Assoumou; Duarte, Jorge; Rivière, Nathalie; Wilmer, Jeroen; van Wuytswinkel, Olivier; Lucau, Anca; Cariou, Emmanuelle; Neutelings, Godfrey; Gutierrez, Laurent; Chabbert, Brigitte; Guillot, Xavier; Tavernier, Reynald; Hawkins, Simon; Thomasset, Brigitte

2010-10-21

Flax (Linum usitatissimum L.) has been cultivated for around 9,000 years and is therefore one of the oldest cultivated species. Today, flax is still grown for its oil (oil-flax or linseed cultivars) and its cellulose-rich fibres (fibre-flax cultivars) used for high-value linen garments and composite materials. Despite the wide industrial use of flax-derived products, and our actual understanding of the regulation of both wood fibre production and oil biosynthesis more information must be acquired in both domains. Recent advances in genomics are now providing opportunities to improve our fundamental knowledge of these complex processes. In this paper we report the development and validation of a high-density oligo microarray platform dedicated to gene expression analyses in flax. Nine different RNA samples obtained from flax inner- and outer-stems, seeds, leaves and roots were used to generate a collection of 1,066,481 ESTs by massive parallel pyrosequencing. Sequences were assembled into 59,626 unigenes and 48,021 sequences were selected for oligo design and high-density microarray (Nimblegen 385K) fabrication with eight, non-overlapping 25-mers oligos per unigene. 18 independent experiments were used to evaluate the hybridization quality, precision, specificity and accuracy and all results confirmed the high technical quality of our microarray platform. Cross-validation of microarray data was carried out using quantitative qRT-PCR. Nine target genes were selected on the basis of microarray results and reflected the whole range of fold change (both up-regulated and down-regulated genes in different samples). A statistically significant positive correlation was obtained comparing expression levels for each target gene across all biological replicates both in qRT-PCR and microarray results. Further experiments illustrated the capacity of our arrays to detect differential gene expression in a variety of flax tissues as well as between two contrasted flax varieties

Development and validation of a flax (Linum usitatissimum L. gene expression oligo microarray

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Gutierrez Laurent

2010-10-01

Full Text Available Abstract Background Flax (Linum usitatissimum L. has been cultivated for around 9,000 years and is therefore one of the oldest cultivated species. Today, flax is still grown for its oil (oil-flax or linseed cultivars and its cellulose-rich fibres (fibre-flax cultivars used for high-value linen garments and composite materials. Despite the wide industrial use of flax-derived products, and our actual understanding of the regulation of both wood fibre production and oil biosynthesis more information must be acquired in both domains. Recent advances in genomics are now providing opportunities to improve our fundamental knowledge of these complex processes. In this paper we report the development and validation of a high-density oligo microarray platform dedicated to gene expression analyses in flax. Results Nine different RNA samples obtained from flax inner- and outer-stems, seeds, leaves and roots were used to generate a collection of 1,066,481 ESTs by massive parallel pyrosequencing. Sequences were assembled into 59,626 unigenes and 48,021 sequences were selected for oligo design and high-density microarray (Nimblegen 385K fabrication with eight, non-overlapping 25-mers oligos per unigene. 18 independent experiments were used to evaluate the hybridization quality, precision, specificity and accuracy and all results confirmed the high technical quality of our microarray platform. Cross-validation of microarray data was carried out using quantitative qRT-PCR. Nine target genes were selected on the basis of microarray results and reflected the whole range of fold change (both up-regulated and down-regulated genes in different samples. A statistically significant positive correlation was obtained comparing expression levels for each target gene across all biological replicates both in qRT-PCR and microarray results. Further experiments illustrated the capacity of our arrays to detect differential gene expression in a variety of flax tissues as well

permGPU: Using graphics processing units in RNA microarray association studies

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George Stephen L

2010-06-01

Full Text Available Abstract Background 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. Results 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. Conclusions 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.

Microarray expression profiling of human dental pulp from single subject.

Science.gov (United States)

Tete, Stefano; Mastrangelo, Filiberto; Scioletti, Anna Paola; Tranasi, Michelangelo; Raicu, Florina; Paolantonio, Michele; Stuppia, Liborio; Vinci, Raffaele; Gherlone, Enrico; Ciampoli, Cristian; Sberna, Maria Teresa; Conti, Pio

2008-01-01

Microarray is a recently developed simultaneous analysis of expression patterns of thousand of genes. The aim of this research was to evaluate the expression profile of human healthy dental pulp in order to find the presence of genes activated and encoding for proteins involved in the physiological process of human dental pulp. We report data obtained by analyzing expression profiles of human tooth pulp from single subjects, using an approach based on the amplification of the total RNA. Experiments were performed on a high-density array able to analyse about 21,000 oligonucleotide sequences of about 70 bases in duplicate, using an approach based on the amplification of the total RNA from the pulp of a single tooth. Obtained data were analyzed using the S.A.M. system (Significance Analysis of Microarray) and genes were merged according to their molecular functions and biological process by the Onto-Express software. The microarray analysis revealed 362 genes with specific pulp expression. Genes showing significant high expression were classified in genes involved in tooth development, protoncogenes, genes of collagen, DNAse, Metallopeptidases and Growth factors. We report a microarray analysis, carried out by extraction of total RNA from specimens of healthy human dental pulp tissue. This approach represents a powerful tool in the study of human normal and pathological pulp, allowing minimization of the genetic variability due to the pooling of samples from different individuals.

Evaluation of Zinc-alpha-2-Glycoprotein and Proteasome Subunit beta-Type 6 Expression in Prostate Cancer Using Tissue Microarray Technology.

LENUS (Irish Health Repository)

2010-07-23

Prostate cancer (CaP) is a significant cause of illness and death in males. Current detection strategies do not reliably detect the disease at an early stage and cannot distinguish aggressive versus nonaggressive CaP leading to potential overtreatment of the disease and associated morbidity. Zinc-alpha-2-glycoprotein (ZAG) and proteasome subunit beta-Type 6 (PSMB-6) were found to be up-regulated in the serum of CaP patients with higher grade tumors after 2-dimensional difference gel electrophoresis analysis. The aim of this study was to investigate if ZAG and PSMB-6 were also overexpressed in prostatic tumor tissue of CaP patients. Immunohistochemical analysis was performed on CaP tissue microarrays with samples from 199 patients. Confirmatory gene expression profiling for ZAG and PSMB-6 were performed on 4 cases using Laser Capture Microdissection and TaqMan real-time polymerase chain reaction. ZAG expression in CaP epithelial cells was inversely associated with Gleason grade (benign prostatic hyperplasia>G3>G4\\/G5). PSMB-6 was not expressed in either tumor or benign epithelium. However, strong PSMB-6 expression was noted in stromal and inflammatory cells. Our results indicate ZAG as a possible predictive marker of Gleason grade. The inverse association between grade and tissue expression with a rising serum protein level is similar to that seen with prostate-specific antigen. In addition, the results for both ZAG and PSMB-6 highlight the challenges in trying to associate the protein levels in serum with tissue expression.

Graph Based Study of Allergen Cross-Reactivity of Plant Lipid Transfer Proteins (LTPs) Using Microarray in a Multicenter Study

Science.gov (United States)

Palacín, Arantxa; Gómez-Casado, Cristina; Rivas, Luis A.; Aguirre, Jacobo; Tordesillas, Leticia; Bartra, Joan; Blanco, Carlos; Carrillo, Teresa; Cuesta-Herranz, Javier; de Frutos, Consolación; Álvarez-Eire, Genoveva García; Fernández, Francisco J.; Gamboa, Pedro; Muñoz, Rosa; Sánchez-Monge, Rosa; Sirvent, Sofía; Torres, María J.; Varela-Losada, Susana; Rodríguez, Rosalía; Parro, Victor; Blanca, Miguel; Salcedo, Gabriel; Díaz-Perales, Araceli

2012-01-01

The study of cross-reactivity in allergy is key to both understanding. the allergic response of many patients and providing them with a rational treatment In the present study, protein microarrays and a co-sensitization graph approach were used in conjunction with an allergen microarray immunoassay. This enabled us to include a wide number of proteins and a large number of patients, and to study sensitization profiles among members of the LTP family. Fourteen LTPs from the most frequent plant food-induced allergies in the geographical area studied were printed into a microarray specifically designed for this research. 212 patients with fruit allergy and 117 food-tolerant pollen allergic subjects were recruited from seven regions of Spain with different pollen profiles, and their sera were tested with allergen microarray. This approach has proven itself to be a good tool to study cross-reactivity between members of LTP family, and could become a useful strategy to analyze other families of allergens. PMID:23272072

Graph based study of allergen cross-reactivity of plant lipid transfer proteins (LTPs using microarray in a multicenter study.

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Arantxa Palacín

Full Text Available The study of cross-reactivity in allergy is key to both understanding. the allergic response of many patients and providing them with a rational treatment In the present study, protein microarrays and a co-sensitization graph approach were used in conjunction with an allergen microarray immunoassay. This enabled us to include a wide number of proteins and a large number of patients, and to study sensitization profiles among members of the LTP family. Fourteen LTPs from the most frequent plant food-induced allergies in the geographical area studied were printed into a microarray specifically designed for this research. 212 patients with fruit allergy and 117 food-tolerant pollen allergic subjects were recruited from seven regions of Spain with different pollen profiles, and their sera were tested with allergen microarray. This approach has proven itself to be a good tool to study cross-reactivity between members of LTP family, and could become a useful strategy to analyze other families of allergens.

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

Science.gov (United States)

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

2009-07-16

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

Characterization of the effect of sample quality on high density oligonucleotide microarray data using progressively degraded rat liver RNA

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Rosenzweig Barry A

2007-09-01

Full Text Available Abstract Background The interpretability of microarray data can be affected by sample quality. To systematically explore how RNA quality affects microarray assay performance, a set of rat liver RNA samples with a progressive change in RNA integrity was generated by thawing frozen tissue or by ex vivo incubation of fresh tissue over a time course. Results Incubation of tissue at 37°C for several hours had little effect on RNA integrity, but did induce changes in the transcript levels of stress response genes and immune cell markers. In contrast, thawing of tissue led to a rapid loss of RNA integrity. Probe sets identified as most sensitive to RNA degradation tended to be located more than 1000 nucleotides upstream of their transcription termini, similar to the positioning of control probe sets used to assess sample quality on Affymetrix GeneChip® arrays. Samples with RNA integrity numbers less than or equal to 7 showed a significant increase in false positives relative to undegraded liver RNA and a reduction in the detection of true positives among probe sets most sensitive to sample integrity for in silico modeled changes of 1.5-, 2-, and 4-fold. Conclusion Although moderate levels of RNA degradation are tolerated by microarrays with 3'-biased probe selection designs, in this study we identify a threshold beyond which decreased specificity and sensitivity can be observed that closely correlates with average target length. These results highlight the value of annotating microarray data with metrics that capture important aspects of sample quality.

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

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H.C. Cunningham

2018-02-01

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

Immunohistochemical analysis of breast tissue microarray images using contextual classifiers

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Stephen J McKenna

2013-01-01

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

Hormonal receptors and vascular endothelial growth factor in juvenile nasopharyngeal angiofibroma: immunohistochemical and tissue microarray analysis.

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Liu, Zhuofu; Wang, Jingjing; Wang, Huan; Wang, Dehui; Hu, Li; Liu, Quan; Sun, Xicai

2015-01-01

This work demonstrated that juvenile nasopharyngeal angiofibromas (JNAs) express high levels of hormone receptors and vascular endothelial growth factor (VEGF) compared with normal nasal mucosa. The interaction between hormone receptors and VEGF may be involved in the initiation and growth of JNA. JNA is a rare benign tumor that occurs almost exclusively in male adolescents. Although generally regarded as a hormone-dependent tumor, this has not been proven in previous studies. The aim of this study was to investigate the role of hormone receptors in JNA and the relationship with clinical characteristics. Standard immunohistochemical microarray analysis was performed on 70 JNA samples and 10 turbinate tissue samples. Specific antibodies for androgen receptor (AR), estrogen receptor-α (ER-α), estrogen receptor-β (ER-β), progesterone receptor (PR), and VEGF were examined, and the relationships of receptor expression with age, tumor stage, and bleeding were evaluated. RESULTS showed that JNA expressed ER-α (92.9%), ER-β (91.4%), AR (65.7%), PR (12.8%), and VEGF (95.7%) at different levels. High level of VEGF was linked to elevated ER-α and ER-β. There was no significant relationship between hormonal receptors and age at diagnosis, tumor stage or bleeding. However, overexpression of ER-α was found to be an indicator of poor prognosis (p = 0.031).

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

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

2007-01-01

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

Differentiation of the seven major lyssavirus species by oligonucleotide microarray.

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Xi, Jin; Guo, Huancheng; Feng, Ye; Xu, Yunbin; Shao, Mingfu; Su, Nan; Wan, Jiayu; Li, Jiping; Tu, Changchun

2012-03-01

An oligonucleotide microarray, LyssaChip, has been developed and verified as a highly specific diagnostic tool for differentiation of the 7 major lyssavirus species. As with conventional typing microarray methods, the LyssaChip relies on sequence differences in the 371-nucleotide region coding for the nucleoprotein. This region was amplified using nested reverse transcription-PCR primers that bind to the 7 major lyssaviruses. The LyssaChip includes 57 pairs of species typing and corresponding control oligonucleotide probes (oligoprobes) immobilized on glass slides, and it can analyze 12 samples on a single slide within 8 h. Analysis of 111 clinical brain specimens (65 from animals with suspected rabies submitted to the laboratory and 46 of butchered dog brain tissues collected from restaurants) showed that the chip method was 100% sensitive and highly consistent with the "gold standard," a fluorescent antibody test (FAT). The chip method could detect rabies virus in highly decayed brain tissues, whereas the FAT did not, and therefore the chip test may be more applicable to highly decayed brain tissues than the FAT. LyssaChip may provide a convenient and inexpensive alternative for diagnosis and differentiation of rabies and rabies-related diseases.

Toxicity of Doxorubicin on Pig Liver After Chemoembolization with Doxorubicin-loaded Microspheres: A Pilot DNA-microarrays and Histology Study

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Verret, Valentin, E-mail: valentin.verret@archimmed.com; Namur, Julien; Ghegediban, Saieda Homayra [ArchimMed (France); Wassef, Michel [University of Paris 7-Denis Diderot, Department of Pathology, Faculty of Medicine, AP-HP Hopital Lariboisiere (France); Moine, Laurence [Universite Paris Sud, Faculte de Pharmacie, UMR CNRS 8612, IFR 141-ITFM (France); Bonneau, Michel [AP-HP/INRA, Centre de Recherche En Imagerie Interventionnelle (France); Pelage, Jean-Pierre [AP-HP Hopital Ambroise Pare, Department of Interventional Radiology (France); Laurent, Alexandre [AP-HP/INRA, Centre de Recherche En Imagerie Interventionnelle (France)

2013-02-15

The potential mechanisms accounting for the hepatotoxicity of doxorubicin-loaded microspheres in chemoembolization were examined by combining histology and DNA-microarray techniques.The left hepatic arteries of two pigs were embolized with 1 mL of doxorubicin-loaded (25 mg; (DoxMS)) or non-loaded (BlandMS) microspheres. The histopathological effects of the embolization were analyzed at 1 week. RNAs extracted from both the embolized and control liver areas were hybridized onto Agilent porcine microarrays. Genes showing significantly different expression (p < 0.01; fold-change > 2) between two groups were classified by biological process. At 1 week after embolization, DoxMS caused arterial and parenchymal necrosis in 51 and 38 % of embolized vessels, respectively. By contrast, BlandMS did not cause any tissue damage. Up-regulated genes following embolization with DoxMS (vs. BlandMS, n = 353) were mainly involved in cell death, apoptosis, and metabolism of doxorubicin. Down-regulated genes (n = 120) were mainly related to hepatic functions, including enzymes of lipid and carbohydrate metabolisms. Up-regulated genes included genes related to cell proliferation (growth factors and transcription factors), tissue remodeling (MMPs and several collagen types), inflammatory reaction (interleukins and chemokines), and angiogenesis (angiogenic factors and HIF1a pathway), all of which play an important role in liver healing and regeneration. DoxMS caused lesions to the liver, provoked cell death, and disturbed liver metabolism. An inflammatory repair process with cell proliferation, tissue remodeling, and angiogenesis was rapidly initiated during the first week after chemoembolization. This pilot study provides a comprehensive method to compare different types of DoxMS in healthy animals or tumor models.

Cross-platform comparison of SYBR® Green real-time PCR with TaqMan PCR, microarrays and other gene expression measurement technologies evaluated in the MicroArray Quality Control (MAQC study

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Dial Stacey L

2008-07-01

Full Text Available Abstract Background The MicroArray Quality Control (MAQC project evaluated the inter- and intra-platform reproducibility of seven microarray platforms and three quantitative gene expression assays in profiling the expression of two commercially available Reference RNA samples (Nat Biotechnol 24:1115-22, 2006. The tested microarrays were the platforms from Affymetrix, Agilent Technologies, Applied Biosystems, GE Healthcare, Illumina, Eppendorf and the National Cancer Institute, and quantitative gene expression assays included TaqMan® Gene Expression PCR Assay, Standardized (Sta RT-PCR™ and QuantiGene®. The data showed great consistency in gene expression measurements across different microarray platforms, different technologies and test sites. However, SYBR® Green real-time PCR, another common technique utilized by half of all real-time PCR users for gene expression measurement, was not addressed in the MAQC study. In the present study, we compared the performance of SYBR Green PCR with TaqMan PCR, microarrays and other quantitative technologies using the same two Reference RNA samples as the MAQC project. We assessed SYBR Green real-time PCR using commercially available RT2 Profiler™ PCR Arrays from SuperArray, containing primer pairs that have been experimentally validated to ensure gene-specificity and high amplification efficiency. Results The SYBR Green PCR Arrays exhibit good reproducibility among different users, PCR instruments and test sites. In addition, the SYBR Green PCR Arrays have the highest concordance with TaqMan PCR, and a high level of concordance with other quantitative methods and microarrays that were evaluated in this study in terms of fold-change correlation and overlap of lists of differentially expressed genes. Conclusion These data demonstrate that SYBR Green real-time PCR delivers highly comparable results in gene expression measurement with TaqMan PCR and other high-density microarrays.

Development and application of a microarray meter tool to optimize microarray experiments

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Rouse Richard JD

2008-07-01

Full Text Available Abstract Background Successful microarray experimentation requires a complex interplay between the slide chemistry, the printing pins, the nucleic acid probes and targets, and the hybridization milieu. Optimization of these parameters and a careful evaluation of emerging slide chemistries are a prerequisite to any large scale array fabrication effort. We have developed a 'microarray meter' tool which assesses the inherent variations associated with microarray measurement prior to embarking on large scale projects. Findings The microarray meter consists of nucleic acid targets (reference and dynamic range control and probe components. Different plate designs containing identical probe material were formulated to accommodate different robotic and pin designs. We examined the variability in probe quality and quantity (as judged by the amount of DNA printed and remaining post-hybridization using three robots equipped with capillary printing pins. Discussion The generation of microarray data with minimal variation requires consistent quality control of the (DNA microarray manufacturing and experimental processes. Spot reproducibility is a measure primarily of the variations associated with printing. The microarray meter assesses array quality by measuring the DNA content for every feature. It provides a post-hybridization analysis of array quality by scoring probe performance using three metrics, a a measure of variability in the signal intensities, b a measure of the signal dynamic range and c a measure of variability of the spot morphologies.

DNA Microarray Technology; TOPICAL

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WERNER-WASHBURNE, MARGARET; DAVIDSON, GEORGE S.

2002-01-01

Collaboration between Sandia National Laboratories and the University of New Mexico Biology Department resulted in the capability to train students in microarray techniques and the interpretation of data from microarray experiments. These studies provide for a better understanding of the role of stationary phase and the gene regulation involved in exit from stationary phase, which may eventually have important clinical implications. Importantly, this research trained numerous students and is the basis for three new Ph.D. projects

A study of metaheuristic algorithms for high dimensional feature selection on microarray data

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Dankolo, Muhammad Nasiru; Radzi, Nor Haizan Mohamed; Sallehuddin, Roselina; Mustaffa, Noorfa Haszlinna

2017-11-01

Microarray systems enable experts to examine gene profile at molecular level using machine learning algorithms. It increases the potentials of classification and diagnosis of many diseases at gene expression level. Though, numerous difficulties may affect the efficiency of machine learning algorithms which includes vast number of genes features comprised in the original data. Many of these features may be unrelated to the intended analysis. Therefore, feature selection is necessary to be performed in the data pre-processing. Many feature selection algorithms are developed and applied on microarray which including the metaheuristic optimization algorithms. This paper discusses the application of the metaheuristics algorithms for feature selection in microarray dataset. This study reveals that, the algorithms have yield an interesting result with limited resources thereby saving computational expenses of machine learning algorithms.

Recommendations for the use of microarrays in prenatal diagnosis.

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Suela, Javier; López-Expósito, Isabel; Querejeta, María Eugenia; Martorell, Rosa; Cuatrecasas, Esther; Armengol, Lluis; Antolín, Eugenia; Domínguez Garrido, Elena; Trujillo-Tiebas, María José; Rosell, Jordi; García Planells, Javier; Cigudosa, Juan Cruz

2017-04-07

Microarray technology, recently implemented in international prenatal diagnosis systems, has become one of the main techniques in this field in terms of detection rate and objectivity of the results. This guideline attempts to provide background information on this technology, including technical and diagnostic aspects to be considered. Specifically, this guideline defines: the different prenatal sample types to be used, as well as their characteristics (chorionic villi samples, amniotic fluid, fetal cord blood or miscarriage tissue material); variant reporting policies (including variants of uncertain significance) to be considered in informed consents and prenatal microarray reports; microarray limitations inherent to the technique and which must be taken into account when recommending microarray testing for diagnosis; a detailed clinical algorithm recommending the use of microarray testing and its introduction into routine clinical practice within the context of other genetic tests, including pregnancies in families with a genetic history or specific syndrome suspicion, first trimester increased nuchal translucency or second trimester heart malformation and ultrasound findings not related to a known or specific syndrome. This guideline has been coordinated by the Spanish Association for Prenatal Diagnosis (AEDP, «Asociación Española de Diagnóstico Prenatal»), the Spanish Human Genetics Association (AEGH, «Asociación Española de Genética Humana») and the Spanish Society of Clinical Genetics and Dysmorphology (SEGCyD, «Sociedad Española de Genética Clínica y Dismorfología»). Copyright © 2017 Elsevier España, S.L.U. All rights reserved.

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

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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.

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

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Jianping Hua

2004-01-01

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

The tissue micro-array data exchange specification: a web based experience browsing imported data

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Nohle, David G; Hackman, Barbara A; Ayers, Leona W

2005-01-01

Background The AIDS and Cancer Specimen Resource (ACSR) is an HIV/AIDS tissue bank consortium sponsored by the National Cancer Institute (NCI) Division of Cancer Treatment and Diagnosis (DCTD). The ACSR offers to approved researchers HIV infected biologic samples and uninfected control tissues including tissue cores in micro-arrays (TMA) accompanied by de-identified clinical data. Researchers interested in the type and quality of TMA tissue cores and the associated clinical data need an efficient method for viewing available TMA materials. Because each of the tissue samples within a TMA has separate data including a core tissue digital image and clinical data, an organized, standard approach to producing, navigating and publishing such data is necessary. The Association for Pathology Informatics (API) extensible mark-up language (XML) TMA data exchange specification (TMA DES) proposed in April 2003 provides a common format for TMA data. Exporting TMA data into the proposed format offers an opportunity to implement the API TMA DES. Using our public BrowseTMA tool, we created a web site that organizes and cross references TMA lists, digital "virtual slide" images, TMA DES export data, linked legends and clinical details for researchers. Microsoft Excel® and Microsoft Word® are used to convert tabular clinical data and produce an XML file in the TMA DES format. The BrowseTMA tool contains Extensible Stylesheet Language Transformation (XSLT) scripts that convert XML data into Hyper-Text Mark-up Language (HTML) web pages with hyperlinks automatically added to allow rapid navigation. Results Block lists, virtual slide images, legends, clinical details and exports have been placed on the ACSR web site for 14 blocks with 1623 cores of 2.0, 1.0 and 0.6 mm sizes. Our virtual microscope can be used to view and annotate these TMA images. Researchers can readily navigate from TMA block lists to TMA legends and to clinical details for a selected tissue core. Exports for 11

A Lateral Flow Protein Microarray for Rapid and Sensitive Antibody Assays

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Helene Andersson-Svahn

2011-11-01

Full Text Available Protein microarrays are useful tools for highly multiplexed determination of presence or levels of clinically relevant biomarkers in human tissues and biofluids. However, such tools have thus far been restricted to laboratory environments. Here, we present a novel 384-plexed easy to use lateral flow protein microarray device capable of sensitive (< 30 ng/mL determination of antigen-specific antibodies in ten minutes of total assay time. Results were developed with gold nanobeads and could be recorded by a cell-phone camera or table top scanner. Excellent accuracy with an area under curve (AUC of 98% was achieved in comparison with an established glass microarray assay for 26 antigen-specific antibodies. We propose that the presented framework could find use in convenient and cost-efficient quality control of antibody production, as well as in providing a platform for multiplexed affinity-based assays in low-resource or mobile settings.

Direct calibration of PICKY-designed microarrays

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Ronald Pamela C

2009-10-01

Full Text Available Abstract Background Few microarrays have been quantitatively calibrated to identify optimal hybridization conditions because it is difficult to precisely determine the hybridization characteristics of a microarray using biologically variable cDNA samples. Results Using synthesized samples with known concentrations of specific oligonucleotides, a series of microarray experiments was conducted to evaluate microarrays designed by PICKY, an oligo microarray design software tool, and to test a direct microarray calibration method based on the PICKY-predicted, thermodynamically closest nontarget information. The complete set of microarray experiment results is archived in the GEO database with series accession number GSE14717. Additional data files and Perl programs described in this paper can be obtained from the website http://www.complex.iastate.edu under the PICKY Download area. Conclusion PICKY-designed microarray probes are highly reliable over a wide range of hybridization temperatures and sample concentrations. The microarray calibration method reported here allows researchers to experimentally optimize their hybridization conditions. Because this method is straightforward, uses existing microarrays and relatively inexpensive synthesized samples, it can be used by any lab that uses microarrays designed by PICKY. In addition, other microarrays can be reanalyzed by PICKY to obtain the thermodynamically closest nontarget information for calibration.

Empirical Bayes ranking and selection methods via semiparametric hierarchical mixture models in microarray studies.

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Noma, Hisashi; Matsui, Shigeyuki

2013-05-20

The main purpose of microarray studies is screening of differentially expressed genes as candidates for further investigation. Because of limited resources in this stage, prioritizing genes are relevant statistical tasks in microarray studies. For effective gene selections, parametric empirical Bayes methods for ranking and selection of genes with largest effect sizes have been proposed (Noma et al., 2010; Biostatistics 11: 281-289). The hierarchical mixture model incorporates the differential and non-differential components and allows information borrowing across differential genes with separation from nuisance, non-differential genes. In this article, we develop empirical Bayes ranking methods via a semiparametric hierarchical mixture model. A nonparametric prior distribution, rather than parametric prior distributions, for effect sizes is specified and estimated using the "smoothing by roughening" approach of Laird and Louis (1991; Computational statistics and data analysis 12: 27-37). We present applications to childhood and infant leukemia clinical studies with microarrays for exploring genes related to prognosis or disease progression. Copyright © 2012 John Wiley & Sons, Ltd.

Methodological Challenges in Protein Microarray and Immunohistochemistry for the Discovery of Novel Autoantibodies in Paediatric Acute Disseminated Encephalomyelitis

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Peschl, Patrick; Ramberger, Melanie; Höftberger, Romana; Jöhrer, Karin; Baumann, Matthias; Rostásy, Kevin; Reindl, Markus

2017-01-01

Acute disseminated encephalomyelitis (ADEM) is a rare autoimmune-mediated demyelinating disease affecting mainly children and young adults. Differentiation to multiple sclerosis is not always possible, due to overlapping clinical symptoms and recurrent and multiphasic forms. Until now, immunoglobulins reactive to myelin oligodendrocyte glycoprotein (MOG antibodies) have been found in a subset of patients with ADEM. However, there are still patients lacking autoantibodies, necessitating the identification of new autoantibodies as biomarkers in those patients. Therefore, we aimed to identify novel autoantibody targets in ADEM patients. Sixteen ADEM patients (11 seronegative, 5 seropositive for MOG antibodies) were analysed for potential new biomarkers, using a protein microarray and immunohistochemistry on rat brain tissue to identify antibodies against intracellular and surface neuronal and glial antigens. Nine candidate antigens were identified in the protein microarray analysis in at least two patients per group. Immunohistochemistry on rat brain tissue did not reveal new target antigens. Although no new autoantibody targets could be found here, future studies should aim to identify new biomarkers for therapeutic and prognostic purposes. The microarray analysis and immunohistochemistry methods used here have several limitations, which should be considered in future searches for biomarkers. PMID:28327523

Metric learning for DNA microarray data analysis

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Takeuchi, Ichiro; Nakagawa, Masao; Seto, Masao

2009-01-01

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

Numerical and structural genomic aberrations are reliably detectable in tissue microarrays of formalin-fixed paraffin-embedded tumor samples by fluorescence in-situ hybridization.

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Heike Horn

Full Text Available Few data are available regarding the reliability of fluorescence in-situ hybridization (FISH, especially for chromosomal deletions, in high-throughput settings using tissue microarrays (TMAs. We performed a comprehensive FISH study for the detection of chromosomal translocations and deletions in formalin-fixed and paraffin-embedded (FFPE tumor specimens arranged in TMA format. We analyzed 46 B-cell lymphoma (B-NHL specimens with known karyotypes for translocations of IGH-, BCL2-, BCL6- and MYC-genes. Locus-specific DNA probes were used for the detection of deletions in chromosome bands 6q21 and 9p21 in 62 follicular lymphomas (FL and six malignant mesothelioma (MM samples, respectively. To test for aberrant signals generated by truncation of nuclei following sectioning of FFPE tissue samples, cell line dilutions with 9p21-deletions were embedded into paraffin blocks. The overall TMA hybridization efficiency was 94%. FISH results regarding translocations matched karyotyping data in 93%. As for chromosomal deletions, sectioning artefacts occurred in 17% to 25% of cells, suggesting that the proportion of cells showing deletions should exceed 25% to be reliably detectable. In conclusion, FISH represents a robust tool for the detection of structural as well as numerical aberrations in FFPE tissue samples in a TMA-based high-throughput setting, when rigorous cut-off values and appropriate controls are maintained, and, of note, was superior to quantitative PCR approaches.

MARS: Microarray analysis, retrieval, and storage system

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Scheideler Marcel

2005-04-01

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

Comparing transformation methods for DNA microarray data

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Zwinderman Aeilko H

2004-06-01

Full Text Available Abstract Background When DNA microarray data are used for gene clustering, genotype/phenotype correlation studies, or tissue classification the signal intensities are usually transformed and normalized in several steps in order to improve comparability and signal/noise ratio. These steps may include subtraction of an estimated background signal, subtracting the reference signal, smoothing (to account for nonlinear measurement effects, and more. Different authors use different approaches, and it is generally not clear to users which method they should prefer. Results We used the ratio between biological variance and measurement variance (which is an F-like statistic as a quality measure for transformation methods, and we demonstrate a method for maximizing that variance ratio on real data. We explore a number of transformations issues, including Box-Cox transformation, baseline shift, partial subtraction of the log-reference signal and smoothing. It appears that the optimal choice of parameters for the transformation methods depends on the data. Further, the behavior of the variance ratio, under the null hypothesis of zero biological variance, appears to depend on the choice of parameters. Conclusions The use of replicates in microarray experiments is important. Adjustment for the null-hypothesis behavior of the variance ratio is critical to the selection of transformation method.

Microarray-based DNA methylation study of Ewing's sarcoma of the bone.

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Park, Hye-Rim; Jung, Woon-Won; Kim, Hyun-Sook; Park, Yong-Koo

2014-10-01

Alterations in DNA methylation patterns are a hallmark of malignancy. However, the majority of epigenetic studies of Ewing's sarcoma have focused on the analysis of only a few candidate genes. Comprehensive studies are thus lacking and are required. The aim of the present study was to identify novel methylation markers in Ewing's sarcoma using microarray analysis. The current study reports the microarray-based DNA methylation study of 1,505 CpG sites of 807 cancer-related genes from 69 Ewing's sarcoma samples. The Illumina GoldenGate Methylation Cancer Panel I microarray was used, and with the appropriate controls (n=14), a total of 92 hypermethylated genes were identified in the Ewing's sarcoma samples. The majority of the hypermethylated genes were associated with cell adhesion, cell regulation, development and signal transduction. The overall methylation mean values were compared between patients who survived and those that did not. The overall methylation mean was significantly higher in the patients who did not survive (0.25±0.03) than in those who did (0.22±0.05) (P=0.0322). However, the overall methylation mean was not found to significantly correlate with age, gender or tumor location. GDF10 , OSM , APC and HOXA11 were the most significant differentially-methylated genes, however, their methylation levels were not found to significantly correlate with the survival rate. The DNA methylation profile of Ewing's sarcoma was characterized and 92 genes that were significantly hypermethylated were detected. A trend towards a more aggressive behavior was identified in the methylated group. The results of this study indicated that methylation may be significant in the development of Ewing's sarcoma.

Can intrinsic human tissue radiosensitivity be correlated with late responding gene RNA expression in white blood cells using a 96 gene micro-array?

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Schmidt, D.; Streeter, O.; Dagliyan, G.; Hill, C.K.; Williams-Hill, D.M.

2003-01-01

Radiation is widely used in the treatment of cancers. It is generally believed there is a sigmoid relationship between radiation dose and probability of cure. There is also a sigmoid relationship between radiation dose and normal tissue response. Generally total radiation dose to a tumor is limited by normal tissue tolerance. It has been postulated that up to 70% of inter-individual differences in radiosensitivity may be due to genetic predisposition (Tureson I. Et al, IJROBP, 1996;36:1065). However, to date, clinicians have no way of estimating or predicting an individual's normal tissue response to radiation exposure. Thus the prescribed dose cannot be tailored to an individuals actual expected response but is an empirically derived compromise based on experience. Although a number of studies using cellular techniques have shown that human cell radiosensitivity can be measured, none of these can be performed quick enough to be used in the clinic. In this study we are looking at gene expression that occurs some 24 hours after an exposure compared to expression before any exposure in peripheral white blood cells from patients undergoing radiotherapy for various tumors. The patients will be followed for overt radiation sensitivity by standard criteria by clinicians in the Department. The main aims are: does RNA expression level in a 96 gene micro-array vary before and after radiation and do these changes in RNA expression correlate with the objective measurements of acute radiation response observed by the clinicians in the patients. The USC IRB recently approved the protocol and human consent for this study to enter 50 patients in the next 12 months using mostly head and neck and endometrial cancer patients where we can get a normal tissue sample to examine as well as the blood sample. We will present the rationale, protocol, methods and early results in detail

Endoglin (CD105) expression on microvessel endothelial cells in juvenile nasopharyngeal angiofibroma: tissue microarray analysis and association with prognostic significance.

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Wang, Jing-Jing; Sun, Xi-Cai; Hu, Li; Liu, Zhuo-Fu; Yu, Hua-Peng; Li, Han; Wang, Shu-Yi; Wang, De-Hui

2013-12-01

The purpose of this study was to examine endoglin (CD105) expression on microvessel endothelial cells (ECs) in juvenile nasopharyngeal angiofibroma (JNA) and its relationship with recurrence. Immunohistochemistry was performed to detect CD105 expression in a tissue microarray from 70 patients with JNA. Correlation between CD105 expression on microvessel ECs and clinicopathological features, as well as tumor recurrence, were analyzed. Immunohistochemistry revealed CD105 expression on ECs but not in stroma of patients with JNA. Chi-square analysis indicated CD105-based microvessel density (MVD) was correlated with JNA recurrence (p = .013). Univariate and multivariate analyses determined that MVD was a significant predictor of time to recurrence (p = .009). The CD105-based MVD was better for predicting disease recurrence (AUROC: 0.673; p = .036) than other clinicopathological features. MVD is a useful predictor for poor prognosis of patients with JNA after curative resection. Angiogenesis, which may play an important role in the occurrence and development of JNA, is therefore a potential therapeutic target for JNA. Copyright © 2013 Wiley Periodicals, Inc., A Wiley Company.

Systematic gene microarray analysis of the lncRNA expression profiles in human uterine cervix carcinoma.

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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.

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

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Maija Wolf

2005-01-01

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

A salmonid EST genomic study: genes, duplications, phylogeny and microarrays

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Brahmbhatt Sonal

2008-11-01

Full Text Available Abstract Background Salmonids are of interest because of their relatively recent genome duplication, and their extensive use in wild fisheries and aquaculture. A comprehensive gene list and a comparison of genes in some of the different species provide valuable genomic information for one of the most widely studied groups of fish. Results 298,304 expressed sequence tags (ESTs from Atlantic salmon (69% of the total, 11,664 chinook, 10,813 sockeye, 10,051 brook trout, 10,975 grayling, 8,630 lake whitefish, and 3,624 northern pike ESTs were obtained in this study and have been deposited into the public databases. Contigs were built and putative full-length Atlantic salmon clones have been identified. A database containing ESTs, assemblies, consensus sequences, open reading frames, gene predictions and putative annotation is available. The overall similarity between Atlantic salmon ESTs and those of rainbow trout, chinook, sockeye, brook trout, grayling, lake whitefish, northern pike and rainbow smelt is 93.4, 94.2, 94.6, 94.4, 92.5, 91.7, 89.6, and 86.2% respectively. An analysis of 78 transcript sets show Salmo as a sister group to Oncorhynchus and Salvelinus within Salmoninae, and Thymallinae as a sister group to Salmoninae and Coregoninae within Salmonidae. Extensive gene duplication is consistent with a genome duplication in the common ancestor of salmonids. Using all of the available EST data, a new expanded salmonid cDNA microarray of 32,000 features was created. Cross-species hybridizations to this cDNA microarray indicate that this resource will be useful for studies of all 68 salmonid species. Conclusion An extensive collection and analysis of salmonid RNA putative transcripts indicate that Pacific salmon, Atlantic salmon and charr are 94–96% similar while the more distant whitefish, grayling, pike and smelt are 93, 92, 89 and 86% similar to salmon. The salmonid transcriptome reveals a complex history of gene duplication that is

Microarray analysis in the zebrafish (Danio rerio) liver and telencephalon after exposure to low concentration of 17alpha-ethinylestradiol

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Martyniuk, Christopher J. [Centre for Advanced Research in Environmental Genomics, 30 Marie Curie, Department of Biology, University of Ottawa, Ottawa, Ontario, K1N 6N5 (Canada); Gerrie, Emily R. [Centre for Advanced Research in Environmental Genomics, 30 Marie Curie, Department of Biology, University of Ottawa, Ottawa, Ontario, K1N 6N5 (Canada); Popesku, Jason T. [Centre for Advanced Research in Environmental Genomics, 30 Marie Curie, Department of Biology, University of Ottawa, Ottawa, Ontario, K1N 6N5 (Canada); Ekker, Marc [Centre for Advanced Research in Environmental Genomics, 30 Marie Curie, Department of Biology, University of Ottawa, Ottawa, Ontario, K1N 6N5 (Canada); Trudeau, Vance L. [Centre for Advanced Research in Environmental Genomics, 30 Marie Curie, Department of Biology, University of Ottawa, Ottawa, Ontario, K1N 6N5 (Canada)]. E-mail: trudeauv@uottawa.ca

2007-08-15

17alpha-ethinylestradiol (EE2) is detected in sewage effluent at concentrations that can disrupt normal reproductive function in fish. The objectives of this study were to identify novel genomic responses to EE2 exposure using microarray and real-time RT-PCR analysis in the liver and telencephalon of male zebrafish. Zebrafish were exposed to an environmentally relevant nominal concentration of 10 ng/L EE2 for a 21-day period. In the liver, common biomarkers for estrogenic exposure such as vitellogenin 1 and 3 (vtg1; vtg3), estrogen receptor alpha (esr1), and apolipoprotein A1 (apoA1) mRNA were identified by microarray analysis as being differentially regulated. Real-time RT-PCR confirmed that vtg1 was induced {approx}700-fold, vtg3 was induced {approx}100-fold and esr1 was induced {approx}20-fold. As determined by microarray analysis, ATPase Na+/K+ alpha 1a.4 (atp1a1a.4) and ATPase Na+/K+ beta 1a (atp1b1a) mRNA were down-regulated in the liver. Gene ontology (GO) analysis revealed that there were common biological processes and molecular functions regulated by EE2 in both tissues (e.g. electron transport and cell communication) but there were tissue specific changes in gene categories. For example, genes involved in protein metabolism, carbohydrate metabolism were down-regulated in the liver but were induced in the telencephalon. This study demonstrates that (1) tissues exhibit different gene responses to low EE2 exposure; (2) there are pronounced genomic effects in the liver and (3) multi-tissue gene profiling is needed to improve understanding of the effects of human pharmaceuticals on aquatic organisms.

Potential upstream regulators of cannabinoid receptor 1 signaling in prostate cancer: a Bayesian network analysis of data from a tissue microarray.

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Häggström, Jenny; Cipriano, Mariateresa; Forshell, Linus Plym; Persson, Emma; Hammarsten, Peter; Stella, Nephi; Fowler, Christopher J

2014-08-01

The endocannabinoid system regulates cancer cell proliferation, and in prostate cancer a high cannabinoid CB1 receptor expression is associated with a poor prognosis. Down-stream mediators of CB1 receptor signaling in prostate cancer are known, but information on potential upstream regulators is lacking. Data from a well-characterized tumor tissue microarray were used for a Bayesian network analysis using the max-min hill-climbing method. In non-malignant tissue samples, a directionality of pEGFR (the phosphorylated form of the epidermal growth factor receptor) → CB1 receptors were found regardless as to whether the endocannabinoid metabolizing enzyme fatty acid amide hydrolase (FAAH) was included as a parameter. A similar result was found in the tumor tissue, but only when FAAH was included in the analysis. A second regulatory pathway, from the growth factor receptor ErbB2 → FAAH was also identified in the tumor samples. Transfection of AT1 prostate cancer cells with CB1 receptors induced a sensitivity to the growth-inhibiting effects of the CB receptor agonist CP55,940. The sensitivity was not dependent upon the level of receptor expression. Thus a high CB1 receptor expression alone does not drive the cells towards a survival phenotype in the presence of a CB receptor agonist. The data identify two potential regulators of the endocannabinoid system in prostate cancer and allow the construction of a model of a dysregulated endocannabinoid signaling network in this tumor. Further studies should be designed to test the veracity of the predictions of the network analysis in prostate cancer and other solid tumors. © 2014 The Authors. The Prostate published by Wiley Periodicals, Inc.

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

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

2008-01-01

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

Microarrays in ecological research: A case study of a cDNA microarray for plant-herbivore interactions

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Gase Klaus

2004-09-01

Full Text Available Abstract Background Microarray technology allows researchers to simultaneously monitor changes in the expression ratios (ERs of hundreds of genes and has thereby revolutionized most of biology. Although this technique has the potential of elucidating early stages in an organism's phenotypic response to complex ecological interactions, to date, it has not been fully incorporated into ecological research. This is partially due to a lack of simple procedures of handling and analyzing the expression ratio (ER data produced from microarrays. Results We describe an analysis of the sources of variation in ERs from 73 hybridized cDNA microarrays, each with 234 herbivory-elicited genes from the model ecological expression system, Nicotiana attenuata, using procedures that are commonly used in ecologic research. Each gene is represented by two independently labeled PCR products and each product was arrayed in quadruplicate. We present a robust method of normalizing and analyzing ERs based on arbitrary thresholds and statistical criteria, and characterize a "norm of reaction" of ERs for 6 genes (4 of known function, 2 of unknown with different ERs as determined across all analyzed arrays to provide a biologically-informed alternative to the use of arbitrary expression ratios in determining significance of expression. These gene-specific ERs and their variance (gene CV were used to calculate array-based variances (array CV, which, in turn, were used to study the effects of array age, probe cDNA quantity and quality, and quality of spotted PCR products as estimates of technical variation. Cluster analysis and a Principal Component Analysis (PCA were used to reveal associations among the transcriptional "imprints" of arrays hybridized with cDNA probes derived from mRNA from N. attenuata plants variously elicited and attacked by different herbivore species and from three congeners: N. quadrivalis, N. longiflora and N. clevelandii. Additionally, the PCA

Manual evaluation of tissue microarrays in a high-throughput research project: The contribution of Indian surgical pathology to the Human Protein Atlas (HPA) project.

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Navani, Sanjay

2016-04-01

The Human Protein Atlas (HPA) program (www.proteinatlas.org) is an international program that has been set up to allow for a systematic exploration of the human proteome using antibody-based proteomics. This is accomplished by combining high-throughput generation of affinity-purified (mono-specific) antibodies with protein profiling in a multitude of tissues/cell types assembled in tissue microarrays. Twenty-six surgical pathologists over a seven-and-half year period have annotated and curated approximately sixteen million tissue images derived from immunostaining of normal and cancer tissues by approximately 23 000 antibodies. Web-based annotation software that allows for a basic and rapid evaluation of immunoreactivity in tissues has been utilized. Intensity, fraction of immunoreactive cells and subcellular localization were recorded for each given cell population. A text comment summarizing the characteristics for each antibody was added. The methods used and the challenges encountered for this exercise, the largest effort ever by a single group of surgical pathologists, are discussed. Manual annotation of digital images is an important tool that may be successfully utilized in high-throughput research projects. This is the first time an Indian private pathology laboratory has been associated with cutting-edge research internationally providing a classic example of developed and emerging nation collaboration. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

APPLICATION OF CDNA MICROARRAY TO THE STUDY OF ARSENIC TOXICOLOGY AND CARCINOGENESIS

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Arsenic (As) is a common environmental toxicant and known human carcinogen. Epidemiological studies link As exposure to various disorders and cancers. However, the molecular mechanisms for As toxicity and carcinogenicity are not completely known. The cDNA microarray, a high-th...

Association of adipocyte genes with ASP expression: a microarray analysis of subcutaneous and omental adipose tissue in morbidly obese subjects

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Lu HuiLing

2010-01-01

Full Text Available Abstract Background Prevalence of obesity is increasing to pandemic proportions. However, obese subjects differ in insulin resistance, adipokine production and co-morbidities. Based on fasting plasma analysis, obese subjects were grouped as Low Acylation Stimulating protein (ASP and Triglyceride (TG (LAT vs High ASP and TG (HAT. Subcutaneous (SC and omental (OM adipose tissues (n = 21 were analysed by microarray, and biologic pathways in lipid metabolism and inflammation were specifically examined. Methods LAT and HAT groups were matched in age, obesity, insulin, and glucose, and had similar expression of insulin-related genes (InsR, IRS-1. ASP related genes tended to be increased in the HAT group and were correlated (factor B, adipsin, complement C3, p Results HAT adipose tissue demonstrated increased lipid related genes for storage (CD36, DGAT1, DGAT2, SCD1, FASN, and LPL, lipolysis (HSL, CES1, perilipin, fatty acid binding proteins (FABP1, FABP3 and adipocyte differentiation markers (CEBPα, CEBPβ, PPARγ. By contrast, oxidation related genes were decreased (AMPK, UCP1, CPT1, FABP7. HAT subjects had increased anti-inflammatory genes TGFB1, TIMP1, TIMP3, and TIMP4 while proinflammatory PIG7 and MMP2 were also significantly increased; all genes, p Conclusion Taken together, the profile of C5L2 receptor, ASP gene expression and metabolic factors in adipose tissue from morbidly obese HAT subjects suggests a compensatory response associated with the increased plasma ASP and TG.

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

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Primmer Craig R

2009-09-01

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

Transcriptional profiling of endocrine cerebro-osteodysplasia using microarray and next-generation sequencing.

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Piya Lahiry

Full Text Available BACKGROUND: Transcriptome profiling of patterns of RNA expression is a powerful approach to identify networks of genes that play a role in disease. To date, most mRNA profiling of tissues has been accomplished using microarrays, but next-generation sequencing can offer a richer and more comprehensive picture. METHODOLOGY/PRINCIPAL FINDINGS: ECO is a rare multi-system developmental disorder caused by a homozygous mutation in ICK encoding intestinal cell kinase. We performed gene expression profiling using both cDNA microarrays and next-generation mRNA sequencing (mRNA-seq of skin fibroblasts from ECO-affected subjects. We then validated a subset of differentially expressed transcripts identified by each method using quantitative reverse transcription-polymerase chain reaction (qRT-PCR. Finally, we used gene ontology (GO to identify critical pathways and processes that were abnormal according to each technical platform. Methodologically, mRNA-seq identifies a much larger number of differentially expressed genes with much better correlation to qRT-PCR results than the microarray (r² = 0.794 and 0.137, respectively. Biologically, cDNA microarray identified functional pathways focused on anatomical structure and development, while the mRNA-seq platform identified a higher proportion of genes involved in cell division and DNA replication pathways. CONCLUSIONS/SIGNIFICANCE: Transcriptome profiling with mRNA-seq had greater sensitivity, range and accuracy than the microarray. The two platforms generated different but complementary hypotheses for further evaluation.

Extended -Regular Sequence for Automated Analysis of Microarray Images

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Jin Hee-Jeong

2006-01-01

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

Brachyury, SOX-9, and Podoplanin, New Markers in the Skull Base Chordoma Vs Chondrosarcoma Differential: A Tissue Microarray Based Comparative Analysis

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Oakley, GJ; Fuhrer, K; Seethala, RR

2014-01-01

The distinction between chondrosarcoma and chordoma of the skull base/head and neck is prognostically important; however, both have sufficient morphologic overlap to make distinction difficult. As a result of gene expression studies, additional candidate markers have been proposed to help in this distinction. Hence, we sought to evaluate the performance of new markers: brachyury, SOX-9, and podoplanin alongside the more traditional markers glial fibrillary acid protein, carcinoembryonic antigen, CD24 and epithelial membrane antigen. Paraffin blocks from 103 skull base/head and neck chondroid tumors from 70 patients were retrieved (1969-2007). Diagnoses were made based on morphology and/or whole section immunohistochemistry for cytokeratin and S100 protein yielding 79 chordomas (comprising 45 chondroid chordomas and 34 conventional chordomas), and 24 chondrosarcomas. A tissue microarray containing 0.6 mm cores of each tumor in triplicate was constructed using a manual array (MTA-1, Beecher Instruments). For visualization of staining, the ImmPRESS detection system (Vector Laboratories) with 2 - diaminobenzidine substrate was used. Sensitivities and specificities were calculated for each marker. Core loss from the microarray ranged from 25-29% yielding 66-78 viable cases per stain. The classic marker, cytokeratin, still has the best performance characteristics. When combined with brachyury, accuracy improves slightly (sensitivity and specificity for detection of chordoma 98% and 100%, respectively). Positivity for both epithelial membrane antigen and AE1/AE3 had a sensitivity of 90% and a specificity of 100% for detecting chordoma in this study. SOX-9 is apparently common to both notochordal and cartilaginous differentiation, and is not useful in the chordoma-chondrosarcoma differential diagnosis. Glial fibrillary acid protein, carcinoembryonic antigen, CD24, and epithelial membrane antigen did not outperform other markers, and are less useful in the diagnosis of

A comparative analysis of DNA barcode microarray feature size

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Smith Andrew M

2009-10-01

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

Implementation of plaid model biclustering method on microarray of carcinoma and adenoma tumor gene expression data

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Ardaneswari, Gianinna; Bustamam, Alhadi; Sarwinda, Devvi

2017-10-01

A Tumor is an abnormal growth of cells that serves no purpose. Carcinoma is a tumor that grows from the top of the cell membrane and the organ adenoma is a benign tumor of the gland-like cells or epithelial tissue. In the field of molecular biology, the development of microarray technology is used in the data store of disease genetic expression. For each of microarray gene, an amount of information is stored for each trait or condition. In gene expression data clustering can be done with a bicluster algorithm, thats clustering method which not only the objects to be clustered, but also the properties or condition of the object. This research proposed Plaid Model Biclustering as one of biclustering method. In this study, we discuss the implementation of Plaid Model Biclustering Method on microarray of Carcinoma and Adenoma tumor gene expression data. From the experimental results, we found three biclusters are formed by Carcinoma gene expression data and four biclusters are formed by Adenoma gene expression data.

Identification and target prediction of miRNAs specifically expressed in rat neural tissue

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Tu Kang

2009-05-01

Full Text Available Abstract Background MicroRNAs (miRNAs are a large group of RNAs that play important roles in regulating gene expression and protein translation. Several studies have indicated that some miRNAs are specifically expressed in human, mouse and zebrafish tissues. For example, miR-1 and miR-133 are specifically expressed in muscles. Tissue-specific miRNAs may have particular functions. Although previous studies have reported the presence of human, mouse and zebrafish tissue-specific miRNAs, there have been no detailed reports of rat tissue-specific miRNAs. In this study, Home-made rat miRNA microarrays which established in our previous study were used to investigate rat neural tissue-specific miRNAs, and mapped their target genes in rat tissues. This study will provide information for the functional analysis of these miRNAs. Results In order to obtain as complete a picture of specific miRNA expression in rat neural tissues as possible, customized miRNA microarrays with 152 selected miRNAs from miRBase were used to detect miRNA expression in 14 rat tissues. After a general clustering analysis, 14 rat tissues could be clearly classified into neural and non-neural tissues based on the obtained expression profiles with p values Conclusion Our work provides a global view of rat neural tissue-specific miRNA profiles and a target map of miRNAs, which is expected to contribute to future investigations of miRNA regulatory mechanisms in neural systems.

Evaluation of toxicity of the mycotoxin citrinin using yeast ORF DNA microarray and Oligo DNA microarray

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Nobumasa Hitoshi

2007-04-01

Full Text Available Abstract Background Mycotoxins are fungal secondary metabolites commonly present in feed and food, and are widely regarded as hazardous contaminants. Citrinin, one of the very well known mycotoxins that was first isolated from Penicillium citrinum, is produced by more than 10 kinds of fungi, and is possibly spread all over the world. However, the information on the action mechanism of the toxin is limited. Thus, we investigated the citrinin-induced genomic response for evaluating its toxicity. Results Citrinin inhibited growth of yeast cells at a concentration higher than 100 ppm. We monitored the citrinin-induced mRNA expression profiles in yeast using the ORF DNA microarray and Oligo DNA microarray, and the expression profiles were compared with those of the other stress-inducing agents. Results obtained from both microarray experiments clustered together, but were different from those of the mycotoxin patulin. The oxidative stress response genes – AADs, FLR1, OYE3, GRE2, and MET17 – were significantly induced. In the functional category, expression of genes involved in "metabolism", "cell rescue, defense and virulence", and "energy" were significantly activated. In the category of "metabolism", genes involved in the glutathione synthesis pathway were activated, and in the category of "cell rescue, defense and virulence", the ABC transporter genes were induced. To alleviate the induced stress, these cells might pump out the citrinin after modification with glutathione. While, the citrinin treatment did not induce the genes involved in the DNA repair. Conclusion Results from both microarray studies suggest that citrinin treatment induced oxidative stress in yeast cells. The genotoxicity was less severe than the patulin, suggesting that citrinin is less toxic than patulin. The reproducibility of the expression profiles was much better with the Oligo DNA microarray. However, the Oligo DNA microarray did not completely overcome cross

Identification of listeria species isolated in Tunisia by Microarray based assay : results of a preliminary study

International Nuclear Information System (INIS)

Hmaied, Fatma; Helel, Salma; Barkallah, Insaf; Leberre, V.; Francois, J.M.; Kechrid, A.

2008-01-01

Microarray-based assay is a new molecular approach for genetic screening and identification of microorganisms. We have developed a rapid microarray-based assay for the reliable detection and discrimination of Listeria spp. in food and clinical isolates from Tunisia. The method used in the present study is based on the PCR amplification of a virulence factor gene (iap gene). the PCR mixture contained cyanine Cy5labeled dCTP. Therefore, The PCR products were fluorescently labeled. The presence of multiple species-specific sequences within the iap gene enabled us to design different oligoprobes per species. The species-specific sequences of the iap gene used in this study were obtained from genBank and then aligned for phylogenetic analysis in order to identify and retrieve the sequences of homologues of the amplified iap gene analysed. 20 probes were used for detection and identification of 22 food isolates and clinical isolates of Listeria spp (L. monocytogenes, L. ivanovi), L. welshimeri, L. seeligeri, and L. grayi). Each bacterial gene was identified by hybridization to oligoprobes specific for each Listeria species and immobilized on a glass surface. The microarray analysis showed that 5 clinical isolates and 2 food isolates were identified listeria monocytogenes. Concerning the remaining 15 food isolates; 13 were identified listeria innocua and 2 isolates could not be identified by microarray based assay. Further phylogenetic and molecular analysis are required to design more species-specific probes for the identification of Listeria spp. Microarray-based assay is a simple and rapid method used for Listeria species discrimination

Cell-cycle and suppressor proteins expression in uterine cervix in HIV/HPV co-infection: comparative study by tissue micro-array (TMA)

International Nuclear Information System (INIS)

Nicol, Alcina F; Pirmez, Claude; Pires, Andréa Rodrigues Cordovil; Souza, Simone R de; Nuovo, Gerard J; Grinsztejn, Beatriz; Tristão, Aparecida; Russomano, Fabio B; Velasque, Luciane; Silva, José R Lapa e

2008-01-01

The oncoproteins of human papillomavirus (HPVs) directly effect cell-cycle control. We hypothesize that regulatory and cell cycle protein expression might be additionally modified in the cervix of HIV/HPV co-infected women. We analyzed the expression of Rb, p27, VEGF and Elf-1 transcriptor factor by immunohistochemistry in 163 paraffin-embeded cervical samples using Tissue Micro-Array (TMA) and correlated this to HIV-1 and HPV infection. HIV/HPV co-infection was associated with a significant increase in expression (p < 0.001) of VEGF and p27 in both low and high grade CIN when compared to the cervices of women infected by HPV alone. Decreased Rb expression was evident with increased CIN grade in the cervices of women infected with HPV alone (p = 0.003 average of cells/mm 2 in CIN I: 17.9, CIN II/III: 4.8, and tumor 3.9). Rb expression increased 3-fold for both low and high grade CIN with HPV/HIV-1 co-infection compared to HPV infection alone but did not reach statistical significance. There was a significant increase in Elf-1 expression in HPV+/HIV- women with CIN II/III and tumor (average of cells/mm 2 in CIN I: 63.8; CIN II/III: 115.7 and tumor: 112.0, p = 0.005), in comparison to controls. Co-infection of HPV and HIV leads to significant increase in the VEGF and p27 expression when compared to HPV+/HIV-negative infection that could facilitate viral persistence and invasive tumor development

Cell-cycle and suppressor proteins expression in uterine cervix in HIV/HPV co-infection: comparative study by tissue micro-array (TMA).

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Nicol, Alcina F; Pires, Andréa Rodrigues Cordovil; de Souza, Simone R; Nuovo, Gerard J; Grinsztejn, Beatriz; Tristão, Aparecida; Russomano, Fabio B; Velasque, Luciane; Lapa e Silva, José R; Pirmez, Claude

2008-10-07

The oncoproteins of human papillomavirus (HPVs) directly effect cell-cycle control. We hypothesize that regulatory and cell cycle protein expression might be additionally modified in the cervix of HIV/HPV co-infected women. We analyzed the expression of Rb, p27, VEGF and Elf-1 transcriptor factor by immunohistochemistry in 163 paraffin-embeded cervical samples using Tissue Micro-Array (TMA) and correlated this to HIV-1 and HPV infection. HIV/HPV co-infection was associated with a significant increase in expression (p < 0.001) of VEGF and p27 in both low and high grade CIN when compared to the cervices of women infected by HPV alone. Decreased Rb expression was evident with increased CIN grade in the cervices of women infected with HPV alone (p = 0.003 average of cells/mm2 in CIN I: 17.9, CIN II/III: 4.8, and tumor 3.9). Rb expression increased 3-fold for both low and high grade CIN with HPV/HIV-1 co-infection compared to HPV infection alone but did not reach statistical significance. There was a significant increase in Elf-1 expression in HPV+/HIV- women with CIN II/III and tumor (average of cells/mm2 in CIN I: 63.8; CIN II/III: 115.7 and tumor: 112.0, p = 0.005), in comparison to controls. Co-infection of HPV and HIV leads to significant increase in the VEGF and p27 expression when compared to HPV+/HIV-negative infection that could facilitate viral persistence and invasive tumor development.

ArrayMining: a modular web-application for microarray analysis combining ensemble and consensus methods with cross-study normalization

Directory of Open Access Journals (Sweden)

Krasnogor Natalio

2009-10-01

Full Text Available Abstract Background Statistical analysis of DNA microarray data provides a valuable diagnostic tool for the investigation of genetic components of diseases. To take advantage of the multitude of available data sets and analysis methods, it is desirable to combine both different algorithms and data from different studies. Applying ensemble learning, consensus clustering and cross-study normalization methods for this purpose in an almost fully automated process and linking different analysis modules together under a single interface would simplify many microarray analysis tasks. Results We present ArrayMining.net, a web-application for microarray analysis that provides easy access to a wide choice of feature selection, clustering, prediction, gene set analysis and cross-study normalization methods. In contrast to other microarray-related web-tools, multiple algorithms and data sets for an analysis task can be combined using ensemble feature selection, ensemble prediction, consensus clustering and cross-platform data integration. By interlinking different analysis tools in a modular fashion, new exploratory routes become available, e.g. ensemble sample classification using features obtained from a gene set analysis and data from multiple studies. The analysis is further simplified by automatic parameter selection mechanisms and linkage to web tools and databases for functional annotation and literature mining. Conclusion ArrayMining.net is a free web-application for microarray analysis combining a broad choice of algorithms based on ensemble and consensus methods, using automatic parameter selection and integration with annotation databases.

Identification of differentially expressed genes in cutaneous squamous cell carcinoma by microarray expression profiling

Directory of Open Access Journals (Sweden)

Sterry Wolfram

2006-08-01

Full Text Available Abstract Background Carcinogenesis is a multi-step process indicated by several genes up- or down-regulated during tumor progression. This study examined and identified differentially expressed genes in cutaneous squamous cell carcinoma (SCC. Results Three different biopsies of 5 immunosuppressed organ-transplanted recipients each normal skin (all were pooled, actinic keratosis (AK (two were pooled, and invasive SCC and additionally 5 normal skin tissues from immunocompetent patients were analyzed. Thus, total RNA of 15 specimens were used for hybridization with Affymetrix HG-U133A microarray technology containing 22,283 genes. Data analyses were performed by prediction analysis of microarrays using nearest shrunken centroids with the threshold 3.5 and ANOVA analysis was independently performed in order to identify differentially expressed genes (p vs. AK and SCC were observed for 118 genes. Conclusion The majority of identified differentially expressed genes in cutaneous SCC were previously not described.

Versatile High Throughput Microarray Analysis for Marine Glycobiology

DEFF Research Database (Denmark)

Asunción Salmeán, Armando

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

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

Directory of Open Access Journals (Sweden)

M J Pont

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

A Combinatory Approach for Selecting Prognostic Genes in Microarray Studies of Tumour Survivals

Directory of Open Access Journals (Sweden)

Qihua Tan

2009-01-01

Full Text Available Different from significant gene expression analysis which looks for genes that are differentially regulated, feature selection in the microarray-based prognostic gene expression analysis aims at finding a subset of marker genes that are not only differentially expressed but also informative for prediction. Unfortunately feature selection in literature of microarray study is predominated by the simple heuristic univariate gene filter paradigm that selects differentially expressed genes according to their statistical significances. We introduce a combinatory feature selection strategy that integrates differential gene expression analysis with the Gram-Schmidt process to identify prognostic genes that are both statistically significant and highly informative for predicting tumour survival outcomes. Empirical application to leukemia and ovarian cancer survival data through-within- and cross-study validations shows that the feature space can be largely reduced while achieving improved testing performances.

The EADGENE Microarray Data Analysis Workshop

DEFF Research Database (Denmark)

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

2007-01-01

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

Computational biology of genome expression and regulation--a review of microarray bioinformatics.

Science.gov (United States)

Wang, Junbai

2008-01-01

Microarray technology is being used widely in various biomedical research areas; the corresponding microarray data analysis is an essential step toward the best utilizing of array technologies. Here we review two components of the microarray data analysis: a low level of microarray data analysis that emphasizes the designing, the quality control, and the preprocessing of microarray experiments, then a high level of microarray data analysis that focuses on the domain-specific microarray applications such as tumor classification, biomarker prediction, analyzing array CGH experiments, and reverse engineering of gene expression networks. Additionally, we will review the recent development of building a predictive model in genome expression and regulation studies. This review may help biologists grasp a basic knowledge of microarray bioinformatics as well as its potential impact on the future evolvement of biomedical research fields.

Facilitating functional annotation of chicken microarray data

Directory of Open Access Journals (Sweden)

Gresham Cathy R

2009-10-01

Full Text Available Abstract Background Modeling results from chicken microarray studies is challenging for researchers due to little functional annotation associated with these arrays. The Affymetrix GenChip chicken genome array, one of the biggest arrays that serve as a key research tool for the study of chicken functional genomics, is among the few arrays that link gene products to Gene Ontology (GO. However the GO annotation data presented by Affymetrix is incomplete, for example, they do not show references linked to manually annotated functions. In addition, there is no tool that facilitates microarray researchers to directly retrieve functional annotations for their datasets from the annotated arrays. This costs researchers amount of time in searching multiple GO databases for functional information. Results We have improved the breadth of functional annotations of the gene products associated with probesets on the Affymetrix chicken genome array by 45% and the quality of annotation by 14%. We have also identified the most significant diseases and disorders, different types of genes, and known drug targets represented on Affymetrix chicken genome array. To facilitate functional annotation of other arrays and microarray experimental datasets we developed an Array GO Mapper (AGOM tool to help researchers to quickly retrieve corresponding functional information for their dataset. Conclusion Results from this study will directly facilitate annotation of other chicken arrays and microarray experimental datasets. Researchers will be able to quickly model their microarray dataset into more reliable biological functional information by using AGOM tool. The disease, disorders, gene types and drug targets revealed in the study will allow researchers to learn more about how genes function in complex biological systems and may lead to new drug discovery and development of therapies. The GO annotation data generated will be available for public use via AgBase website and

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

Science.gov (United States)

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

2015-10-01

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

Generation of EST and Microarray Resources for Functional Genomic Studies on Chicken Intestinal Health

NARCIS (Netherlands)

Hemert, van S.; Ebbelaar, B.H.; Smits, M.A.; Rebel, J.M.J.

2003-01-01

Expressed sequenced tags (ESTs) and microarray resources have a great impact on the ability to study host response in mice and humans. Unfortunately, these resources are not yet available for domestic farm animals. The aim of this study was to provide genomic resources to study chicken intestinal

Examination of gene expression in mice exposed to low dose radiation using affymetrix cDNA microarrays

Energy Technology Data Exchange (ETDEWEB)

Morris, D.; Knox, D.; Lavoie, J.; Lemon, J.; Boreham, D. [McMaster Univ., Hamilton, Ontario (Canada)

2005-07-01

'Full text:' Gamma radiation acts via the indirect effect to damage cells by producing reactive oxygen species (ROS). These ROS are capable damaging macromolecules and, altering signal pathways and gene transcription. Cells have evolved enzymes and mechanisms to scavenge ROS and repair oxidative damage. Microarrays allow the survey of the gene transcription activity of thousands of genes simultaneously. Messenger RNA is extracted from cells, hybridized with the complementary DNA (cDNA) of a microarray chip, and examined with a chip reader. Affymetrix microarray chips have been produced by the CSCHAH in Winnipeg containing 26000 murine genes. Groups of female mice have been exposed to low dose whole body chronic gamma radiation exposures of 0,50,100, and 120 mGy, corresponding to 15,30,60, and 75 weeks, respectively. MRNA from mice brain tissue has been extracted, isolated, converted to cDNA and labeled. Gene expression in each irradiated mouse was compared to the pooled expression of the control mice. Analysis of gene expression levels are performed with microarray analytical software, Array Pro by Media Cybernetics, and powerful statistical software, BRB microarray tools. Differences in gene expressions, focusing on genes for cytokines, DNA repair mechanisms, immuno-modulators, apoptosis pathways, and enzymatic anti-oxidant systems, are being examined and will be reported. (author)

The application of DNA microarrays in gene expression analysis

NARCIS (Netherlands)

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

2000-01-01

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

Emerging use of gene expression microarrays in plant physiology.

Science.gov (United States)

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 were 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.

Overview on Techniques to Construct Tissue Arrays with Special Emphasis on Tissue Microarrays

Science.gov (United States)

Vogel, Ulrich

2014-01-01

With the advent of new histopathological staining techniques (histochemistry, immunohistochemistry, in situ hybridization) and the discovery of thousands of new genes, mRNA, and proteins by molecular biology, the need grew for a technique to compare many different cells or tissues on one slide in a cost effective manner and with the possibility to easily track the identity of each specimen: the tissue array (TA). Basically, a TA consists of at least two different specimens per slide. TAs differ in the kind of specimens, the number of specimens installed, the dimension of the specimens, the arrangement of the specimens, the embedding medium, the technique to prepare the specimens to be installed, and the technique to construct the TA itself. A TA can be constructed by arranging the tissue specimens in a mold and subsequently pouring the mold with the embedding medium of choice. In contrast, preformed so-called recipient blocks consisting of the embedding medium of choice have punched, drilled, or poured holes of different diameters and distances in which the cells or tissue biopsies will be deployed manually, semi-automatically, or automatically. The costs of constructing a TA differ from a few to thousands of Euros depending on the technique/equipment used. Remarkably high quality TAs can be also achieved by low cost techniques. PMID:27600339

The application of DNA microarrays in gene expression analysis.

Science.gov (United States)

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

2000-03-31

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

DNA microarrays : a molecular cloning manual

National Research Council Canada - National Science Library

Sambrook, Joseph; Bowtell, David

2002-01-01

.... DNA Microarrays provides authoritative, detailed instruction on the design, construction, and applications of microarrays, as well as comprehensive descriptions of the software tools and strategies...

Effects of ingested turmeric oleoresin on glucose and lipid metabolisms in obese diabetic mice: a DNA microarray study.

Science.gov (United States)

Honda, Shinichi; Aoki, Fumiki; Tanaka, Hozumi; Kishida, Hideyuki; Nishiyama, Tozo; Okada, Shinji; Matsumoto, Ichiro; Abe, Keiko; Mae, Tatsumasa

2006-11-29

Turmeric, the rhizome of Curcuma longa L., has a wide range of effects on human health. Turmeric oleoresin, an extract of turmeric, is often used for flavoring and coloring. Curcuminoids and turmeric essential oil are both contained in turmeric oleoresin, and both of these fractions have hypoglycemic effects. In the present study, we comprehensively assessed the effect of turmeric oleoresin on hepatic gene expression in obese diabetic KK-Ay mice using DNA microarray analysis and quantitative real-time polymerase chain reaction (PCR). Female KK-Ay mice aged 6 weeks (n = 6/group) were fed a high-fat diet containing turmeric oleoresin, curcuminoids, and essential oil for 5 weeks. The same diet without any of these fractions was used as a control diet. Ingestion of turmeric oleoresin and essential oil inhibited the development of increased blood glucose and abdominal fat mass, while curcuminoids only inhibited the increase in blood glucose. DNA microarray analysis indicated that turmeric oleoresin ingestion up-regulated the expression of genes related to glycolysis, beta-oxidation, and cholesterol metabolism in the liver of KK-Ay mice, while expression of gluconeogenesis-related genes was down-regulated. Real-time PCR analysis was conducted to assess the contribution of the curcuminoids and essential oil in turmeric oleoresin to the changes in expression of representative genes selected by DNA microarray analysis. This analysis suggested that curcuminoids regulated turmeric oleoresin ingestion-induced expression of glycolysis-related genes and also that curcuminoids and turmeric essential oil acted synergistically to regulate the peroxisomal beta-oxidation-related gene expression induced by turmeric oleoresin ingestion. These changes in gene expression were considered to be the mechanism by which the turmeric oleoresin affected the control of both blood glucose levels and abdominal adipose tissue masses. All of these results suggest that the use of whole turmeric

Current Knowledge on Microarray Technology - An Overview

African Journals Online (AJOL)

Erah

This paper reviews basics and updates of each microarray technology and serves to .... through protein microarrays. Protein microarrays also known as protein chips are nothing but grids that ... conditioned media, patient sera, plasma and urine. Clontech ... based antibody arrays) is similar to membrane-based antibody ...

Diagnostic and analytical applications of protein microarrays

DEFF Research Database (Denmark)

Dufva, Hans Martin; Christensen, C.B.V.

2005-01-01

DNA microarrays have changed the field of biomedical sciences over the past 10 years. For several reasons, antibody and other protein microarrays have not developed at the same rate. However, protein and antibody arrays have emerged as a powerful tool to complement DNA microarrays during the post...

Emerging Use of Gene Expression Microarrays in Plant Physiology

Directory of Open Access Journals (Sweden)

Stephen P. Difazio

2006-04-01

Full Text Available 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 were 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.

Annotating breast cancer microarray samples using ontologies

Science.gov (United States)

Liu, Hongfang; Li, Xin; Yoon, Victoria; Clarke, Robert

2008-01-01

As the most common cancer among women, breast cancer results from the accumulation of mutations in essential genes. Recent advance in high-throughput gene expression microarray technology has inspired researchers to use the technology to assist breast cancer diagnosis, prognosis, and treatment prediction. However, the high dimensionality of microarray experiments and public access of data from many experiments have caused inconsistencies which initiated the development of controlled terminologies and ontologies for annotating microarray experiments, such as the standard microarray Gene Expression Data (MGED) ontology (MO). In this paper, we developed BCM-CO, an ontology tailored specifically for indexing clinical annotations of breast cancer microarray samples from the NCI Thesaurus. Our research showed that the coverage of NCI Thesaurus is very limited with respect to i) terms used by researchers to describe breast cancer histology (covering 22 out of 48 histology terms); ii) breast cancer cell lines (covering one out of 12 cell lines); and iii) classes corresponding to the breast cancer grading and staging. By incorporating a wider range of those terms into BCM-CO, we were able to indexed breast cancer microarray samples from GEO using BCM-CO and MGED ontology and developed a prototype system with web interface that allows the retrieval of microarray data based on the ontology annotations. PMID:18999108

Prognostic implication of p27Kip1, Skp2 and Cks1 expression in renal cell carcinoma: a tissue microarray study

Directory of Open Access Journals (Sweden)

Wang Facheng

2008-10-01

Full Text Available Abstract Background p27Kip1 plays a major role as a negative regulator of the cell cycle. The regulation of p27Kip1 degradation is mediated by its specific ubiquitin ligase subunits S-phase kinase protein (Skp 2 and cyclin-dependent kinase subunit (Cks 1. However, little is known regarding the prognostic utility of p27Kip1, Skp2 and Cks1 expression in renal cell carcinoma. Methods Immunohistochemistry was performed for p27Kip1, Skp2 and Cks1 in tissue microarrays of 482 renal cell carcinomas with follow-up. The data were correlated with clinicopathological features. The univariate and multivariate survival analyses were also performed to determine their prognostic significance. Results Immunoreactivity of p27Kip1, Skp2 and Cks1 was noted in 357, 71 and 82 patients, respectively. Skp2 and Cks1 expression were not noted in chromophobe cancers. A strong correlation was found between Skp2 and Cks1 expression (P Kip1 levels (P = 0.006 and P Kip1 expression and Skp2 expression were correlated with larger tumor size and higher stage, as well as tumor necrosis. Cks1 expression was only correlated with tumor size. In univariate analysis, low p27Kip1 expression, Skp2 and Cks1 expression were all associated with a poor prognosis, while in multivariate analysis, only low p27Kip1 expression were independent prognostic factors for both cancer specific survival and recurrence-free survival in patients with RCC. Conclusion Our results suggest that immunohistochemical expression levels of p27Kip1, Skp2 and Cks1 may serve as markers with prognostic value in renal cell carcinoma.

The Importance of Normalization on Large and Heterogeneous Microarray Datasets

Science.gov (United States)

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

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

Directory of Open Access Journals (Sweden)

van Ommen Gert-Jan B

2008-06-01

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

Cross-species hybridization of woodchuck hepatitis virus-induced hepatocellular carcinoma using human oligonucleotide microarrays

Institute of Scientific and Technical Information of China (English)

Paul W Anderson; Bud C Tennant; Zhenghong Lee

2006-01-01

AIM: To demonstrate the feasibility of using woodchuck samples on human microarrays, to provide insight into pathways involving positron emission tomography (PET) imaging tracers and to identify genes that could be potential molecular imaging targets for woodchuck hepatocellular carcinoma.METHODS: Labeled cRNA from woodchuck tissue samples were hybridized to Affymetrix U133 plus 2.0 GeneChips(R). Ten genes were selected for validation using quantitative RT-PCR and literature review was made.RESULTS: Testis enhanced gene transcript (BAX Inhibitor 1), alpha-fetoprotein, isocitrate dehydrogenase 3 (NAD+) beta, acetyl-CoA synthetase 2, carnitine palmitoyltransferase 2, and N-myc2 were up-regulated and spermidine/spermine N1-acetyltransferase was down-regulated in the woodchuck HCC. We also found previously published results supporting 8 of the 10 most up-regulated genes and all 10 of the 10 most downregulated genes.CONCLUSION: Many of our microarray results were validated using RT-PCR or literature search. Hence, we believe that woodchuck HCC and non-cancerous liver samples can be used on human microarrays to yield meaningful results.

The tissue-engineered human cornea as a model to study expression of matrix metalloproteinases during corneal wound healing.

Science.gov (United States)

Couture, Camille; Zaniolo, Karine; Carrier, Patrick; Lake, Jennifer; Patenaude, Julien; Germain, Lucie; Guérin, Sylvain L

2016-02-01

Corneal injuries remain a major cause of consultation in the ophthalmology clinics worldwide. Repair of corneal wounds is a complex mechanism that involves cell death, migration, proliferation, differentiation, and extracellular matrix (ECM) remodeling. In the present study, we used a tissue-engineered, two-layers (epithelium and stroma) human cornea as a biomaterial to study both the cellular and molecular mechanisms of wound healing. Gene profiling on microarrays revealed important alterations in the pattern of genes expressed by tissue-engineered corneas in response to wound healing. Expression of many MMPs-encoding genes was shown by microarray and qPCR analyses to increase in the migrating epithelium of wounded corneas. Many of these enzymes were converted into their enzymatically active form as wound closure proceeded. In addition, expression of MMPs by human corneal epithelial cells (HCECs) was affected both by the stromal fibroblasts and the collagen-enriched ECM they produce. Most of all, results from mass spectrometry analyses provided evidence that a fully stratified epithelium is required for proper synthesis and organization of the ECM on which the epithelial cells adhere. In conclusion, and because of the many characteristics it shares with the native cornea, this human two layers corneal substitute may prove particularly useful to decipher the mechanistic details of corneal wound healing. Copyright © 2015 Elsevier Ltd. All rights reserved.

Identification of potential biomarkers from microarray experiments using multiple criteria optimization

International Nuclear Information System (INIS)

Sánchez-Peña, Matilde L; Isaza, Clara E; Pérez-Morales, Jaileene; Rodríguez-Padilla, Cristina; Castro, José M; Cabrera-Ríos, Mauricio

2013-01-01

Microarray experiments are capable of determining the relative expression of tens of thousands of genes simultaneously, thus resulting in very large databases. The analysis of these databases and the extraction of biologically relevant knowledge from them are challenging tasks. The identification of potential cancer biomarker genes is one of the most important aims for microarray analysis and, as such, has been widely targeted in the literature. However, identifying a set of these genes consistently across different experiments, researches, microarray platforms, or cancer types is still an elusive endeavor. Besides the inherent difficulty of the large and nonconstant variability in these experiments and the incommensurability between different microarray technologies, there is the issue of the users having to adjust a series of parameters that significantly affect the outcome of the analyses and that do not have a biological or medical meaning. In this study, the identification of potential cancer biomarkers from microarray data is casted as a multiple criteria optimization (MCO) problem. The efficient solutions to this problem, found here through data envelopment analysis (DEA), are associated to genes that are proposed as potential cancer biomarkers. The method does not require any parameter adjustment by the user, and thus fosters repeatability. The approach also allows the analysis of different microarray experiments, microarray platforms, and cancer types simultaneously. The results include the analysis of three publicly available microarray databases related to cervix cancer. This study points to the feasibility of modeling the selection of potential cancer biomarkers from microarray data as an MCO problem and solve it using DEA. Using MCO entails a new optic to the identification of potential cancer biomarkers as it does not require the definition of a threshold value to establish significance for a particular gene and the selection of a normalization

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

Directory of Open Access Journals (Sweden)

Archer Kellie J

2008-02-01

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

PERBANDINGAN ANALISIS LEAST ABSOLUTE SHRINKAGE AND SELECTION OPERATOR DAN PARTIAL LEAST SQUARES (Studi Kasus: Data Microarray

Directory of Open Access Journals (Sweden)

KADEK DWI FARMANI

2012-09-01

Full Text Available Linear regression analysis is one of the parametric statistical methods which utilize the relationship between two or more quantitative variables. In linear regression analysis, there are several assumptions that must be met that is normal distribution of errors, there is no correlation between the error and error variance is constant and homogent. There are some constraints that caused the assumption can not be met, for example, the correlation between independent variables (multicollinearity, constraints on the number of data and independent variables are obtained. When the number of samples obtained less than the number of independent variables, then the data is called the microarray data. Least Absolute shrinkage and Selection Operator (LASSO and Partial Least Squares (PLS is a statistical method that can be used to overcome the microarray, overfitting, and multicollinearity. From the above description, it is necessary to study with the intention of comparing LASSO and PLS method. This study uses coronary heart and stroke patients data which is a microarray data and contain multicollinearity. With these two characteristics of the data that most have a weak correlation between independent variables, LASSO method produces a better model than PLS seen from the large RMSEP.

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

Energy Technology Data Exchange (ETDEWEB)

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

2010-01-27

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

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

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Eils Roland

2005-11-01

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

Comparative study of discretization methods of microarray data for inferring transcriptional regulatory networks

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Ji Wei

2010-10-01

Full Text Available Abstract Background Microarray data discretization is a basic preprocess for many algorithms of gene regulatory network inference. Some common discretization methods in informatics are used to discretize microarray data. Selection of the discretization method is often arbitrary and no systematic comparison of different discretization has been conducted, in the context of gene regulatory network inference from time series gene expression data. Results In this study, we propose a new discretization method "bikmeans", and compare its performance with four other widely-used discretization methods using different datasets, modeling algorithms and number of intervals. Sensitivities, specificities and total accuracies were calculated and statistical analysis was carried out. Bikmeans method always gave high total accuracies. Conclusions Our results indicate that proper discretization methods can consistently improve gene regulatory network inference independent of network modeling algorithms and datasets. Our new method, bikmeans, resulted in significant better total accuracies than other methods.

Simulation of microarray data with realistic characteristics

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Lehmussola Antti

2006-07-01

Full Text Available Abstract Background Microarray technologies have become common tools in biological research. As a result, a need for effective computational methods for data analysis has emerged. Numerous different algorithms have been proposed for analyzing the data. However, an objective evaluation of the proposed algorithms is not possible due to the lack of biological ground truth information. To overcome this fundamental problem, the use of simulated microarray data for algorithm validation has been proposed. Results We present a microarray simulation model which can be used to validate different kinds of data analysis algorithms. The proposed model is unique in the sense that it includes all the steps that affect the quality of real microarray data. These steps include the simulation of biological ground truth data, applying biological and measurement technology specific error models, and finally simulating the microarray slide manufacturing and hybridization. After all these steps are taken into account, the simulated data has realistic biological and statistical characteristics. The applicability of the proposed model is demonstrated by several examples. Conclusion The proposed microarray simulation model is modular and can be used in different kinds of applications. It includes several error models that have been proposed earlier and it can be used with different types of input data. The model can be used to simulate both spotted two-channel and oligonucleotide based single-channel microarrays. All this makes the model a valuable tool for example in validation of data analysis algorithms.

Tissue microarrays and their use for preparation of reference slides ...

African Journals Online (AJOL)

Use of Tissue array was first applied in 1998, and has received a significant amount of attention from the research community ever since. In this technique, a large number (up to 1000) of cylindrical tissue core extracted from \\"donor\\" paraffin block are deposited into \\"recipient\\" block. The aim was modification of the ...

Study of hepatitis B virus gene mutations with enzymatic colorimetry-based DNA microarray.

Science.gov (United States)

Mao, Hailei; Wang, Huimin; Zhang, Donglei; Mao, Hongju; Zhao, Jianlong; Shi, Jian; Cui, Zhichu

2006-01-01

To establish a modified microarray method for detecting HBV gene mutations in the clinic. Site-specific oligonucleotide probes were immobilized to microarray slides and hybridized to biotin-labeled HBV gene fragments amplified from two-step PCR. Hybridized targets were transferred to nitrocellulose membranes, followed by intensity measurement using BCIP/NBT colorimetry. HBV genes from 99 Hepatitis B patients and 40 healthy blood donors were analyzed. Mutation frequencies of HBV pre-core/core and basic core promoter (BCP) regions were found to be significantly higher in the patient group (42%, 40% versus 2.5%, 5%, P colorimetry method exhibited the same level of sensitivity and reproducibility. An enzymatic colorimetry-based DNA microarray assay was successfully established to monitor HBV mutations. Pre-core/core and BCP mutations of HBV genes could be major causes of HBV infection in HBeAg-negative patients and could also be relevant to chronicity and aggravation of hepatitis B.

cDNA microarray screening in food safety

International Nuclear Information System (INIS)

Roy, Sashwati; Sen, Chandan K.

2006-01-01

The cDNA microarray technology and related bioinformatics tools presents a wide range of novel application opportunities. The technology may be productively applied to address food safety. In this mini-review article, we present an update highlighting the late breaking discoveries that demonstrate the vitality of cDNA microarray technology as a tool to analyze food safety with reference to microbial pathogens and genetically modified foods. In order to bring the microarray technology to mainstream food safety, it is important to develop robust user-friendly tools that may be applied in a field setting. In addition, there needs to be a standardized process for regulatory agencies to interpret and act upon microarray-based data. The cDNA microarray approach is an emergent technology in diagnostics. Its values lie in being able to provide complimentary molecular insight when employed in addition to traditional tests for food safety, as part of a more comprehensive battery of tests

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

International Nuclear Information System (INIS)

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

2003-01-01

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

Genomic expression patterns of cardiac tissues from dogs with dilated cardiomyopathy.

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Oyama, Mark A; Chittur, Sridar

2005-07-01

To evaluate global genome expression patterns of left ventricular tissues from dogs with dilated cardiomyopathy (DCM). Tissues obtained from the left ventricle of 2 Doberman Pinschers with end-stage DCM and 5 healthy control dogs. Transcriptional activities of 23,851 canine DNA sequences were determined by use of an oligonucleotide microarray. Genome expression patterns of DCM tissue were evaluated by measuring the relative amount of complementary RNA hybridization to the microarray probes and comparing it with gene expression for tissues from 5 healthy control dogs. 478 transcripts were differentially expressed (> or = 2.5-fold change). In DCM tissue, expression of 173 transcripts was upregulated and expression of 305 transcripts was downregulated, compared with expression for control tissues. Of the 478 transcripts, 167 genes could be specifically identified. These genes were grouped into 1 of 8 categories on the basis of their primary physiologic function. Grouping revealed that pathways involving cellular energy production, signaling and communication, and cell structure were generally downregulated, whereas pathways involving cellular defense and stress responses were upregulated. Many previously unreported genes that may contribute to the pathophysiologic aspects of heart disease were identified. Evaluation of global expression patterns provides a molecular portrait of heart failure, yields insights into the pathophysiologic aspects of DCM, and identifies intriguing genes and pathways for further study.

Design of an Enterobacteriaceae Pan-genome Microarray Chip

DEFF Research Database (Denmark)

Lukjancenko, Oksana; Ussery, David

2010-01-01

-density microarray chip has been designed, using 116 Enterobacteriaceae genome sequences, taking into account the enteric pan-genome. Probes for the microarray were checked in silico and performance of the chip, based on experimental strains from four different genera, demonstrate a relatively high ability...... to distinguish those strains on genus, species, and pathotype/serovar levels. Additionally, the microarray performed well when investigating which genes were found in a given strain of interest. The Enterobacteriaceae pan-genome microarray, based on 116 genomes, provides a valuable tool for determination...

Assessing Bacterial Interactions Using Carbohydrate-Based Microarrays

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Andrea Flannery

2015-12-01

Full Text Available Carbohydrates play a crucial role in host-microorganism interactions and many host glycoconjugates are receptors or co-receptors for microbial binding. Host glycosylation varies with species and location in the body, and this contributes to species specificity and tropism of commensal and pathogenic bacteria. Additionally, bacterial glycosylation is often the first bacterial molecular species encountered and responded to by the host system. Accordingly, characterising and identifying the exact structures involved in these critical interactions is an important priority in deciphering microbial pathogenesis. Carbohydrate-based microarray platforms have been an underused tool for screening bacterial interactions with specific carbohydrate structures, but they are growing in popularity in recent years. In this review, we discuss carbohydrate-based microarrays that have been profiled with whole bacteria, recombinantly expressed adhesins or serum antibodies. Three main types of carbohydrate-based microarray platform are considered; (i conventional carbohydrate or glycan microarrays; (ii whole mucin microarrays; and (iii microarrays constructed from bacterial polysaccharides or their components. Determining the nature of the interactions between bacteria and host can help clarify the molecular mechanisms of carbohydrate-mediated interactions in microbial pathogenesis, infectious disease and host immune response and may lead to new strategies to boost therapeutic treatments.

Microarray of DNA probes on carboxylate functional beads surface

Institute of Scientific and Technical Information of China (English)

黄承志; 李原芳; 黄新华; 范美坤

2000-01-01

The microarray of DNA probes with 5’ -NH2 and 5’ -Tex/3’ -NH2 modified terminus on 10 um carboxylate functional beads surface in the presence of 1-ethyl-3-(3-dimethylaminopropyl)-carbodiimide (EDC) is characterized in the preseni paper. it was found that the microarray capacity of DNA probes on the beads surface depends on the pH of the aqueous solution, the concentra-tion of DNA probe and the total surface area of the beads. On optimal conditions, the minimum distance of 20 mer single-stranded DNA probe microarrayed on beads surface is about 14 nm, while that of 20 mer double-stranded DNA probes is about 27 nm. If the probe length increases from 20 mer to 35 mer, its microarray density decreases correspondingly. Mechanism study shows that the binding mode of DNA probes on the beads surface is nearly parallel to the beads surface.

Microarray of DNA probes on carboxylate functional beads surface

Institute of Scientific and Technical Information of China (English)

无

2000-01-01

The microarray of DNA probes with 5′-NH2 and 5′-Tex/3′-NH2 modified terminus on 10 m m carboxylate functional beads surface in the presence of 1-ethyl-3-(3-dimethylaminopropyl)- carbodiimide (EDC) is characterized in the present paper. It was found that the microarray capacity of DNA probes on the beads surface depends on the pH of the aqueous solution, the concentration of DNA probe and the total surface area of the beads. On optimal conditions, the minimum distance of 20 mer single-stranded DNA probe microarrayed on beads surface is about 14 nm, while that of 20 mer double-stranded DNA probes is about 27 nm. If the probe length increases from 20 mer to 35 mer, its microarray density decreases correspondingly. Mechanism study shows that the binding mode of DNA probes on the beads surface is nearly parallel to the beads surface.

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

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Daniel L Roden

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

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

DEFF Research Database (Denmark)

Stolc, Viktor; Li, Lei; Wang, Xiangfeng

2005-01-01

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

Association Study between BDNF Gene Polymorphisms and Autism by Three-Dimensional Gel-Based Microarray

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Zuhong Lu

2009-06-01

Full Text Available Single nucleotide polymorphisms (SNPs are important markers which can be used in association studies searching for susceptible genes of complex diseases. High-throughput methods are needed for SNP genotyping in a large number of samples. In this study, we applied polyacrylamide gel-based microarray combined with dual-color hybridization for association study of four BDNF polymorphisms with autism. All the SNPs in both patients and controls could be analyzed quickly and correctly. Among four SNPs, only C270T polymorphism showed significant differences in the frequency of the allele (χ2 = 7.809, p = 0.005 and genotype (χ2 = 7.800, p = 0.020. In the haplotype association analysis, there was significant difference in global haplotype distribution between the groups (χ2 = 28.19，p = 3.44e-005. We suggest that BDNF has a possible role in the pathogenesis of autism. The study also show that the polyacrylamide gel-based microarray combined with dual-color hybridization is a rapid, simple and high-throughput method for SNPs genotyping, and can be used for association study of susceptible gene with disorders in large samples.

Polyadenylation state microarray (PASTA) analysis.

Science.gov (United States)

Beilharz, Traude H; Preiss, Thomas

2011-01-01

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

Bright-field in situ hybridization for HER2 gene amplification in breast cancer using tissue microarrays: correlation between chromogenic (CISH) and automated silver-enhanced (SISH) methods with patient outcome.

Science.gov (United States)

Francis, Glenn D; Jones, Mark A; Beadle, Geoffrey F; Stein, Sandra R

2009-06-01

HER2 gene amplification or overexpression occurs in 15% to 25% of breast cancers and has implications for treatment and prognosis. The most commonly used methods for HER2 testing are fluorescence in situ hybridization (FISH) and immunohistochemistry. FISH is considered to be the reference standard and more accurately predicts response to trastuzumab, but is technically demanding, expensive, and requires specialized equipment. In situ hybridization is required to be eligible for adjuvant treatment with trastuzumab in Australia. Bright-field in situ hybridization is an alternative to FISH and uses a combination of in situ methodology and a peroxidase-mediated chromogenic substrate such as diaminobenzidine [chromogenic in situ hybridization (CISH)] or multimer technology coupled with enzyme metallography [silver-enhanced in situ hybridization (SISH)] to create a marker visible under bright-field microscopy. CISH was introduced into diagnostic testing in Australia in October 2006. SISH methodology is a more recent introduction into the testing repertoire. An evaluation of CISH and SISH performance to assess patient outcome were performed using tissue microarrays. Tissue microarrays were constructed in duplicate using material from 593 patients with invasive breast carcinoma and assessed using CISH and SISH. Gene amplification was assessed using the American Society of Clinical Oncology/College of American Pathologists guideline and Australian HER2 Advisory Board criteria (single probe: diploid, 1 to 2.5 copies/nucleus; polysomy >2.5 to 4 copies/nucleus; equivocal, >4 to 6 copies/nucleus; low-level amplification, >6 to 10 copies/nucleus and high-level amplification >10 copies/nucleus; dual probe HER2/CHR17 ratio: nonamplified 2.2). Results were informative for 337 tissue cores comprising 230 patient samples. Concordance rates were 96% for HER2 single probe CISH and SISH and 95.5% for single probe CISH and dual probe HER2/CHR17 SISH. Both bright-field methods correlated

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

Science.gov (United States)

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

2016-01-01

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

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

Directory of Open Access Journals (Sweden)

Sunwoo Chun

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

A regression-based differential expression detection algorithm for microarray studies with ultra-low sample size.

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Daniel Vasiliu

Full Text Available Global gene expression analysis using microarrays and, more recently, RNA-seq, has allowed investigators to understand biological processes at a system level. However, the identification of differentially expressed genes in experiments with small sample size, high dimensionality, and high variance remains challenging, limiting the usability of these tens of thousands of publicly available, and possibly many more unpublished, gene expression datasets. We propose a novel variable selection algorithm for ultra-low-n microarray studies using generalized linear model-based variable selection with a penalized binomial regression algorithm called penalized Euclidean distance (PED. Our method uses PED to build a classifier on the experimental data to rank genes by importance. In place of cross-validation, which is required by most similar methods but not reliable for experiments with small sample size, we use a simulation-based approach to additively build a list of differentially expressed genes from the rank-ordered list. Our simulation-based approach maintains a low false discovery rate while maximizing the number of differentially expressed genes identified, a feature critical for downstream pathway analysis. We apply our method to microarray data from an experiment perturbing the Notch signaling pathway in Xenopus laevis embryos. This dataset was chosen because it showed very little differential expression according to limma, a powerful and widely-used method for microarray analysis. Our method was able to detect a significant number of differentially expressed genes in this dataset and suggest future directions for investigation. Our method is easily adaptable for analysis of data from RNA-seq and other global expression experiments with low sample size and high dimensionality.

Advanced microarray technologies for clinical diagnostics

NARCIS (Netherlands)

Pierik, Anke

2011-01-01

DNA microarrays become increasingly important in the field of clinical diagnostics. These microarrays, also called DNA chips, are small solid substrates, typically having a maximum surface area of a few cm2, onto which many spots are arrayed in a pre-determined pattern. Each of these spots contains

Using Ambystoma mexicanum (Mexican axolotl) embryos, chemical genetics, and microarray analysis to identify signaling pathways associated with tissue regeneration.

Science.gov (United States)

Ponomareva, Larissa V; Athippozhy, Antony; Thorson, Jon S; Voss, S Randal

2015-12-01

Amphibian vertebrates are important models in regenerative biology because they present exceptional regenerative capabilities throughout life. However, it takes considerable effort to rear amphibians to juvenile and adult stages for regeneration studies, and the relatively large sizes that frogs and salamanders achieve during development make them difficult to use in chemical screens. Here, we introduce a new tail regeneration model using late stage Mexican axolotl embryos. We show that axolotl embryos completely regenerate amputated tails in 7days before they exhaust their yolk supply and begin to feed. Further, we show that axolotl embryos can be efficiently reared in microtiter plates to achieve moderate throughput screening of soluble chemicals to investigate toxicity and identify molecules that alter regenerative outcome. As proof of principle, we identified integration 1 / wingless (Wnt), transforming growth factor beta (Tgf-β), and fibroblast growth factor (Fgf) pathway antagonists that completely block tail regeneration and additional chemicals that significantly affected tail outgrowth. Furthermore, we used microarray analysis to show that inhibition of Wnt signaling broadly affects transcription of genes associated with Wnt, Fgf, Tgf-β, epidermal growth factor (Egf), Notch, nerve growth factor (Ngf), homeotic gene (Hox), rat sarcoma/mitogen-activated protein kinase (Ras/Mapk), myelocytomatosis viral oncogene (Myc), tumor protein 53 (p53), and retinoic acid (RA) pathways. Punctuated changes in the expression of genes known to regulate vertebrate development were observed; this suggests the tail regeneration transcriptional program is hierarchically structured and temporally ordered. Our study establishes the axolotl as a chemical screening model to investigate signaling pathways associated with tissue regeneration. Copyright © 2015 Elsevier Inc. All rights reserved.

Advanced Data Mining of Leukemia Cells Micro-Arrays

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Richard S. Segall

2009-12-01

Full Text Available This paper provides continuation and extensions of previous research by Segall and Pierce (2009a that discussed data mining for micro-array databases of Leukemia cells for primarily self-organized maps (SOM. As Segall and Pierce (2009a and Segall and Pierce (2009b the results of applying data mining are shown and discussed for the data categories of microarray databases of HL60, Jurkat, NB4 and U937 Leukemia cells that are also described in this article. First, a background section is provided on the work of others pertaining to the applications of data mining to micro-array databases of Leukemia cells and micro-array databases in general. As noted in predecessor article by Segall and Pierce (2009a, micro-array databases are one of the most popular functional genomics tools in use today. This research in this paper is intended to use advanced data mining technologies for better interpretations and knowledge discovery as generated by the patterns of gene expressions of HL60, Jurkat, NB4 and U937 Leukemia cells. The advanced data mining performed entailed using other data mining tools such as cubic clustering criterion, variable importance rankings, decision trees, and more detailed examinations of data mining statistics and study of other self-organized maps (SOM clustering regions of workspace as generated by SAS Enterprise Miner version 4. Conclusions and future directions of the research are also presented.

Serious limitations of the QTL/Microarray approach for QTL gene discovery

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Warden Craig H

2010-07-01

Full Text Available Abstract Background It has been proposed that the use of gene expression microarrays in nonrecombinant parental or congenic strains can accelerate the process of isolating individual genes underlying quantitative trait loci (QTL. However, the effectiveness of this approach has not been assessed. Results Thirty-seven studies that have implemented the QTL/microarray approach in rodents were reviewed. About 30% of studies showed enrichment for QTL candidates, mostly in comparisons between congenic and background strains. Three studies led to the identification of an underlying QTL gene. To complement the literature results, a microarray experiment was performed using three mouse congenic strains isolating the effects of at least 25 biometric QTL. Results show that genes in the congenic donor regions were preferentially selected. However, within donor regions, the distribution of differentially expressed genes was homogeneous once gene density was accounted for. Genes within identical-by-descent (IBD regions were less likely to be differentially expressed in chromosome 2, but not in chromosomes 11 and 17. Furthermore, expression of QTL regulated in cis (cis eQTL showed higher expression in the background genotype, which was partially explained by the presence of single nucleotide polymorphisms (SNP. Conclusions The literature shows limited successes from the QTL/microarray approach to identify QTL genes. Our own results from microarray profiling of three congenic strains revealed a strong tendency to select cis-eQTL over trans-eQTL. IBD regions had little effect on rate of differential expression, and we provide several reasons why IBD should not be used to discard eQTL candidates. In addition, mismatch probes produced false cis-eQTL that could not be completely removed with the current strains genotypes and low probe density microarrays. The reviewed studies did not account for lack of coverage from the platforms used and therefore removed genes

Chromosomal microarrays testing in children with developmental disabilities and congenital anomalies

Directory of Open Access Journals (Sweden)

Guillermo Lay-Son

2015-04-01

Full Text Available OBJECTIVES: Clinical use of microarray-based techniques for the analysis of many developmental disorders has emerged during the last decade. Thus, chromosomal microarray has been positioned as a first-tier test. This study reports the first experience in a Chilean cohort. METHODS: Chilean patients with developmental disabilities and congenital anomalies were studied with a high-density microarray (CytoScan(tm HD Array, Affymetrix, Inc., Santa Clara, CA, USA. Patients had previous cytogenetic studies with either a normal result or a poorly characterized anomaly. RESULTS: This study tested 40 patients selected by two or more criteria, including: major congenital anomalies, facial dysmorphism, developmental delay, and intellectual disability. Copy number variants (CNVs were found in 72.5% of patients, while a pathogenic CNV was found in 25% of patients and a CNV of uncertain clinical significance was found in 2.5% of patients. CONCLUSION: Chromosomal microarray analysis is a useful and powerful tool for diagnosis of developmental diseases, by allowing accurate diagnosis, improving the diagnosis rate, and discovering new etiologies. The higher cost is a limitation for widespread use in this setting.

Translating microarray data for diagnostic testing in childhood leukaemia

International Nuclear Information System (INIS)

Hoffmann, Katrin; Firth, Martin J; Beesley, Alex H; Klerk, Nicholas H de; Kees, Ursula R

2006-01-01

Recent findings from microarray studies have raised the prospect of a standardized diagnostic gene expression platform to enhance accurate diagnosis and risk stratification in paediatric acute lymphoblastic leukaemia (ALL). However, the robustness as well as the format for such a diagnostic test remains to be determined. As a step towards clinical application of these findings, we have systematically analyzed a published ALL microarray data set using Robust Multi-array Analysis (RMA) and Random Forest (RF). We examined published microarray data from 104 ALL patients specimens, that represent six different subgroups defined by cytogenetic features and immunophenotypes. Using the decision-tree based supervised learning algorithm Random Forest (RF), we determined a small set of genes for optimal subgroup distinction and subsequently validated their predictive power in an independent patient cohort. We achieved very high overall ALL subgroup prediction accuracies of about 98%, and were able to verify the robustness of these genes in an independent panel of 68 specimens obtained from a different institution and processed in a different laboratory. Our study established that the selection of discriminating genes is strongly dependent on the analysis method. This may have profound implications for clinical use, particularly when the classifier is reduced to a small set of genes. We have demonstrated that as few as 26 genes yield accurate class prediction and importantly, almost 70% of these genes have not been previously identified as essential for class distinction of the six ALL subgroups. Our finding supports the feasibility of qRT-PCR technology for standardized diagnostic testing in paediatric ALL and should, in conjunction with conventional cytogenetics lead to a more accurate classification of the disease. In addition, we have demonstrated that microarray findings from one study can be confirmed in an independent study, using an entirely independent patient cohort

Plant-pathogen interactions: what microarray tells about it?

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Lodha, T D; Basak, J

2012-01-01

Plant defense responses are mediated by elementary regulatory proteins that affect expression of thousands of genes. Over the last decade, microarray technology has played a key role in deciphering the underlying networks of gene regulation in plants that lead to a wide variety of defence responses. Microarray is an important tool to quantify and profile the expression of thousands of genes simultaneously, with two main aims: (1) gene discovery and (2) global expression profiling. Several microarray technologies are currently in use; most include a glass slide platform with spotted cDNA or oligonucleotides. Till date, microarray technology has been used in the identification of regulatory genes, end-point defence genes, to understand the signal transduction processes underlying disease resistance and its intimate links to other physiological pathways. Microarray technology can be used for in-depth, simultaneous profiling of host/pathogen genes as the disease progresses from infection to resistance/susceptibility at different developmental stages of the host, which can be done in different environments, for clearer understanding of the processes involved. A thorough knowledge of plant disease resistance using successful combination of microarray and other high throughput techniques, as well as biochemical, genetic, and cell biological experiments is needed for practical application to secure and stabilize yield of many crop plants. This review starts with a brief introduction to microarray technology, followed by the basics of plant-pathogen interaction, the use of DNA microarrays over the last decade to unravel the mysteries of plant-pathogen interaction, and ends with the future prospects of this technology.

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

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Nupur Dasgupta

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

Nanotechnology: moving from microarrays toward nanoarrays.

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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.

DNA Microarray Technology

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Skip to main content DNA Microarray Technology Enter Search Term(s): Español Research Funding An Overview Bioinformatics Current Grants Education and Training Funding Extramural Research News Features Funding Divisions Funding ...

Testing an aflatoxin B1 gene signature in rat archival tissues.

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Merrick, B Alex; Auerbach, Scott S; Stockton, Patricia S; Foley, Julie F; Malarkey, David E; Sills, Robert C; Irwin, Richard D; Tice, Raymond R

2012-05-21

Archival tissues from laboratory studies represent a unique opportunity to explore the relationship between genomic changes and agent-induced disease. In this study, we evaluated the applicability of qPCR for detecting genomic changes in formalin-fixed, paraffin-embedded (FFPE) tissues by determining if a subset of 14 genes from a 90-gene signature derived from microarray data and associated with eventual tumor development could be detected in archival liver, kidney, and lung of rats exposed to aflatoxin B1 (AFB1) for 90 days in feed at 1 ppm. These tissues originated from the same rats used in the microarray study. The 14 genes evaluated were Adam8, Cdh13, Ddit4l, Mybl2, Akr7a3, Akr7a2, Fhit, Wwox, Abcb1b, Abcc3, Cxcl1, Gsta5, Grin2c, and the C8orf46 homologue. The qPCR FFPE liver results were compared to the original liver microarray data and to qPCR results using RNA from fresh frozen liver. Archival liver paraffin blocks yielded 30 to 50 μg of degraded RNA that ranged in size from 0.1 to 4 kB. qPCR results from FFPE and fresh frozen liver samples were positively correlated (p ≤ 0.05) by regression analysis and showed good agreement in direction and proportion of change with microarray data for 11 of 14 genes. All 14 transcripts could be amplified from FFPE kidney RNA except the glutamate receptor gene Grin2c; however, only Abcb1b was significantly upregulated from control. Abundant constitutive transcripts, S18 and β-actin, could be amplified from lung FFPE samples, but the narrow RNA size range (25-500 bp length) prevented consistent detection of target transcripts. Overall, a discrete gene signature derived from prior transcript profiling and representing cell cycle progression, DNA damage response, and xenosensor and detoxication pathways was successfully applied to archival liver and kidney by qPCR and indicated that gene expression changes in response to subchronic AFB1 exposure occurred predominantly in the liver, the primary target for AFB1-induced

Uropathogenic Escherichia coli virulence genes: invaluable approaches for designing DNA microarray probes.

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Jahandeh, Nadia; Ranjbar, Reza; Behzadi, Payam; Behzadi, Elham

2015-01-01

The pathotypes of uropathogenic Escherichia coli (UPEC) cause different types of urinary tract infections (UTIs). The presence of a wide range of virulence genes in UPEC enables us to design appropriate DNA microarray probes. These probes, which are used in DNA microarray technology, provide us with an accurate and rapid diagnosis and definitive treatment in association with UTIs caused by UPEC pathotypes. The main goal of this article is to introduce the UPEC virulence genes as invaluable approaches for designing DNA microarray probes. Main search engines such as Google Scholar and databases like NCBI were searched to find and study several original pieces of literature, review articles, and DNA gene sequences. In parallel with in silico studies, the experiences of the authors were helpful for selecting appropriate sources and writing this review article. There is a significant variety of virulence genes among UPEC strains. The DNA sequences of virulence genes are fabulous patterns for designing microarray probes. The location of virulence genes and their sequence lengths influence the quality of probes. The use of selected virulence genes for designing microarray probes gives us a wide range of choices from which the best probe candidates can be chosen. DNA microarray technology provides us with an accurate, rapid, cost-effective, sensitive, and specific molecular diagnostic method which is facilitated by designing microarray probes. Via these tools, we are able to have an accurate diagnosis and a definitive treatment regarding UTIs caused by UPEC pathotypes.

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

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

2015-06-25

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

Multi-tissue computational modeling analyzes pathophysiology of type 2 diabetes in MKR mice.

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Amit Kumar

Full Text Available Computational models using metabolic reconstructions for in silico simulation of metabolic disorders such as type 2 diabetes mellitus (T2DM can provide a better understanding of disease pathophysiology and avoid high experimentation costs. There is a limited amount of computational work, using metabolic reconstructions, performed in this field for the better understanding of T2DM. In this study, a new algorithm for generating tissue-specific metabolic models is presented, along with the resulting multi-confidence level (MCL multi-tissue model. The effect of T2DM on liver, muscle, and fat in MKR mice was first studied by microarray analysis and subsequently the changes in gene expression of frank T2DM MKR mice versus healthy mice were applied to the multi-tissue model to test the effect. Using the first multi-tissue genome-scale model of all metabolic pathways in T2DM, we found out that branched-chain amino acids' degradation and fatty acids oxidation pathway is downregulated in T2DM MKR mice. Microarray data showed low expression of genes in MKR mice versus healthy mice in the degradation of branched-chain amino acids and fatty-acid oxidation pathways. In addition, the flux balance analysis using the MCL multi-tissue model showed that the degradation pathways of branched-chain amino acid and fatty acid oxidation were significantly downregulated in MKR mice versus healthy mice. Validation of the model was performed using data derived from the literature regarding T2DM. Microarray data was used in conjunction with the model to predict fluxes of various other metabolic pathways in the T2DM mouse model and alterations in a number of pathways were detected. The Type 2 Diabetes MCL multi-tissue model may explain the high level of branched-chain amino acids and free fatty acids in plasma of Type 2 Diabetic subjects from a metabolic fluxes perspective.

HER2 evaluation using the novel rabbit monoclonal antibody SP3 and CISH in tissue microarrays of invasive breast carcinomas.

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Ricardo, Sara Alexandra Vinhas; Milanezi, Fernanda; Carvalho, Sílvia Teresa; Leitão, Dina Raquel Aguilera; Schmitt, Fernando Carlos Lander

2007-09-01

Laboratory methods for HER2 assessment currently include immunohistochemical (IHC) methods (measuring protein overexpression) and fluorescence in situ hybridisation (FISH) (measuring gene amplification). The measure of HER2 protein by IHC is usually assessed by the mouse monoclonal antibody CB11, and polyclonal antibodies (Herceptest) directed against the internal portion of the receptor. Recently, chromogenic in situ hybridisation (CISH), in which HER2 is detected by a peroxidase reaction and the gene amplification can be determined by regular bright-field microscopy, has emerged as an alternative to FISH. To evaluate the status of HER2 in tissue microarrays (TMAs) of invasive breast cancer using the novel rabbit monoclonal antibody SP3 directed against the external portion of HER2, and correlate the results with CB11 and CISH. IHC was performed with two antibodies (CB11 and SP3) and CISH for HER2 in 10 TMA blocks with 190 formalin-fixed paraffin-embedded cases of invasive breast carcinomas. The correlation between SP3 and CB11 was significant (pCISH (pCISH, shows that this novel antibody is a reliable candidate to evaluate the expression of HER2 in breast cancer.

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

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Wu Xiaogang

2012-06-01

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

A Microarray Study of Middle Cerebral Occlusion Rat Brain with Acupuncture Intervention

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Chao Zhang

2015-01-01

Full Text Available Microarray analysis was used to investigate the changes of gene expression of ischemic stroke and acupuncture intervention in middle cerebral artery occlusion (MCAo rat brain. Results showed that acupuncture intervention had a remarkable improvement in neural deficit score, cerebral blood flow, and cerebral infarction volume of MCAo rats. Microarray analysis showed that a total of 627 different expression genes were regulated in ischemic stroke. 417 genes were upregulated and 210 genes were downregulated. A total of 361 different expression genes were regulated after acupuncture intervention. Three genes were upregulated and 358 genes were downregulated. The expression of novel genes after acupuncture intervention, including Tph1 and Olr883, was further analyzed by Real-Time Quantitative Polymerase Chain Reaction (RT-PCR. Upregulation of Tph1 and downregulation of Olr883 indicated that the therapeutic effect of acupuncture for ischemic stroke may be closely related to the suppression of poststroke depression and regulation of olfactory transduction. In conclusion, the present study may enrich our understanding of the multiple pathological process of ischemic brain injury and indicate possible mechanisms of acupuncture on ischemic stroke.

A cell spot microarray method for production of high density siRNA transfection microarrays

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Mpindi John-Patrick

2011-03-01

Full Text Available Abstract Background High-throughput RNAi screening is widely applied in biological research, but remains expensive, infrastructure-intensive and conversion of many assays to HTS applications in microplate format is not feasible. Results Here, we describe the optimization of a miniaturized cell spot microarray (CSMA method, which facilitates utilization of the transfection microarray technique for disparate RNAi analyses. To promote rapid adaptation of the method, the concept has been tested with a panel of 92 adherent cell types, including primary human cells. We demonstrate the method in the systematic screening of 492 GPCR coding genes for impact on growth and survival of cultured human prostate cancer cells. Conclusions The CSMA method facilitates reproducible preparation of highly parallel cell microarrays for large-scale gene knockdown analyses. This will be critical towards expanding the cell based functional genetic screens to include more RNAi constructs, allow combinatorial RNAi analyses, multi-parametric phenotypic readouts or comparative analysis of many different cell types.

Identifying Fishes through DNA Barcodes and Microarrays.

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Marc Kochzius

2010-09-01

Full Text Available International fish trade reached an import value of 62.8 billion Euro in 2006, of which 44.6% are covered by the European Union. Species identification is a key problem throughout the life cycle of fishes: from eggs and larvae to adults in fisheries research and control, as well as processed fish products in consumer protection.This study aims to evaluate the applicability of the three mitochondrial genes 16S rRNA (16S, cytochrome b (cyt b, and cytochrome oxidase subunit I (COI for the identification of 50 European marine fish species by combining techniques of "DNA barcoding" and microarrays. In a DNA barcoding approach, neighbour Joining (NJ phylogenetic trees of 369 16S, 212 cyt b, and 447 COI sequences indicated that cyt b and COI are suitable for unambiguous identification, whereas 16S failed to discriminate closely related flatfish and gurnard species. In course of probe design for DNA microarray development, each of the markers yielded a high number of potentially species-specific probes in silico, although many of them were rejected based on microarray hybridisation experiments. None of the markers provided probes to discriminate the sibling flatfish and gurnard species. However, since 16S-probes were less negatively influenced by the "position of label" effect and showed the lowest rejection rate and the highest mean signal intensity, 16S is more suitable for DNA microarray probe design than cty b and COI. The large portion of rejected COI-probes after hybridisation experiments (>90% renders the DNA barcoding marker as rather unsuitable for this high-throughput technology.Based on these data, a DNA microarray containing 64 functional oligonucleotide probes for the identification of 30 out of the 50 fish species investigated was developed. It represents the next step towards an automated and easy-to-handle method to identify fish, ichthyoplankton, and fish products.

Identification of rat lung-specific microRNAs by microRNA microarray: valuable discoveries for the facilitation of lung research

OpenAIRE

Chintagari Narendranath; Chen Zhongming; Gou Deming; Weng Tingting; Wang Yang; Liu Lin

2007-01-01

Abstract Background An important mechanism for gene regulation utilizes small non-coding RNAs called microRNAs (miRNAs). These small RNAs play important roles in tissue development, cell differentiation and proliferation, lipid and fat metabolism, stem cells, exocytosis, diseases and cancers. To date, relatively little is known about functions of miRNAs in the lung except lung cancer. Results In this study, we utilized a rat miRNA microarray containing 216 miRNA probes, printed in-house, to d...

Discovering biological progression underlying microarray samples.

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Peng Qiu

2011-04-01

Full Text Available In biological systems that undergo processes such as differentiation, a clear concept of progression exists. We present a novel computational approach, called Sample Progression Discovery (SPD, to discover patterns of biological progression underlying microarray gene expression data. SPD assumes that individual samples of a microarray dataset are related by an unknown biological process (i.e., differentiation, development, cell cycle, disease progression, and that each sample represents one unknown point along the progression of that process. SPD aims to organize the samples in a manner that reveals the underlying progression and to simultaneously identify subsets of genes that are responsible for that progression. We demonstrate the performance of SPD on a variety of microarray datasets that were generated by sampling a biological process at different points along its progression, without providing SPD any information of the underlying process. When applied to a cell cycle time series microarray dataset, SPD was not provided any prior knowledge of samples' time order or of which genes are cell-cycle regulated, yet SPD recovered the correct time order and identified many genes that have been associated with the cell cycle. When applied to B-cell differentiation data, SPD recovered the correct order of stages of normal B-cell differentiation and the linkage between preB-ALL tumor cells with their cell origin preB. When applied to mouse embryonic stem cell differentiation data, SPD uncovered a landscape of ESC differentiation into various lineages and genes that represent both generic and lineage specific processes. When applied to a prostate cancer microarray dataset, SPD identified gene modules that reflect a progression consistent with disease stages. SPD may be best viewed as a novel tool for synthesizing biological hypotheses because it provides a likely biological progression underlying a microarray dataset and, perhaps more importantly, the

Principles of gene microarray data analysis.

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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.

Leptospiral outer membrane protein microarray, a novel approach to identification of host ligand-binding proteins.

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Pinne, Marija; Matsunaga, James; Haake, David A

2012-11-01

Leptospirosis is a zoonosis with worldwide distribution caused by pathogenic spirochetes belonging to the genus Leptospira. The leptospiral life cycle involves transmission via freshwater and colonization of the renal tubules of their reservoir hosts. Infection requires adherence to cell surfaces and extracellular matrix components of host tissues. These host-pathogen interactions involve outer membrane proteins (OMPs) expressed on the bacterial surface. In this study, we developed an Leptospira interrogans serovar Copenhageni strain Fiocruz L1-130 OMP microarray containing all predicted lipoproteins and transmembrane OMPs. A total of 401 leptospiral genes or their fragments were transcribed and translated in vitro and printed on nitrocellulose-coated glass slides. We investigated the potential of this protein microarray to screen for interactions between leptospiral OMPs and fibronectin (Fn). This approach resulted in the identification of the recently described fibronectin-binding protein, LIC10258 (MFn8, Lsa66), and 14 novel Fn-binding proteins, denoted Microarray Fn-binding proteins (MFns). We confirmed Fn binding of purified recombinant LIC11612 (MFn1), LIC10714 (MFn2), LIC11051 (MFn6), LIC11436 (MFn7), LIC10258 (MFn8, Lsa66), and LIC10537 (MFn9) by far-Western blot assays. Moreover, we obtained specific antibodies to MFn1, MFn7, MFn8 (Lsa66), and MFn9 and demonstrated that MFn1, MFn7, and MFn9 are expressed and surface exposed under in vitro growth conditions. Further, we demonstrated that MFn1, MFn4 (LIC12631, Sph2), and MFn7 enable leptospires to bind fibronectin when expressed in the saprophyte, Leptospira biflexa. Protein microarrays are valuable tools for high-throughput identification of novel host ligand-binding proteins that have the potential to play key roles in the virulence mechanisms of pathogens.

Cell-Based Microarrays for In Vitro Toxicology

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Wegener, Joachim

2015-07-01

DNA/RNA and protein microarrays have proven their outstanding bioanalytical performance throughout the past decades, given the unprecedented level of parallelization by which molecular recognition assays can be performed and analyzed. Cell microarrays (CMAs) make use of similar construction principles. They are applied to profile a given cell population with respect to the expression of specific molecular markers and also to measure functional cell responses to drugs and chemicals. This review focuses on the use of cell-based microarrays for assessing the cytotoxicity of drugs, toxins, or chemicals in general. It also summarizes CMA construction principles with respect to the cell types that are used for such microarrays, the readout parameters to assess toxicity, and the various formats that have been established and applied. The review ends with a critical comparison of CMAs and well-established microtiter plate (MTP) approaches.

SLIMarray: Lightweight software for microarray facility management

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Marzolf Bruz

2006-10-01

Full Text Available Abstract Background Microarray core facilities are commonplace in biological research organizations, and need systems for accurately tracking various logistical aspects of their operation. Although these different needs could be handled separately, an integrated management system provides benefits in organization, automation and reduction in errors. Results We present SLIMarray (System for Lab Information Management of Microarrays, an open source, modular database web application capable of managing microarray inventories, sample processing and usage charges. The software allows modular configuration and is well suited for further development, providing users the flexibility to adapt it to their needs. SLIMarray Lite, a version of the software that is especially easy to install and run, is also available. Conclusion SLIMarray addresses the previously unmet need for free and open source software for managing the logistics of a microarray core facility.

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

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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

The detection and differentiation of canine respiratory pathogens using oligonucleotide microarrays.

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Wang, Lih-Chiann; Kuo, Ya-Ting; Chueh, Ling-Ling; Huang, Dean; Lin, Jiunn-Horng

2017-05-01

Canine respiratory diseases are commonly seen in dogs along with co-infections with multiple respiratory pathogens, including viruses and bacteria. Virus infections in even vaccinated dogs were also reported. The clinical signs caused by different respiratory etiological agents are similar, which makes differential diagnosis imperative. An oligonucleotide microarray system was developed in this study. The wild type and vaccine strains of canine distemper virus (CDV), influenza virus, canine herpesvirus (CHV), Bordetella bronchiseptica and Mycoplasma cynos were detected and differentiated simultaneously on a microarray chip. The detection limit is 10, 10, 100, 50 and 50 copy numbers for CDV, influenza virus, CHV, B. bronchiseptica and M. cynos, respectively. The clinical test results of nasal swab samples showed that the microarray had remarkably better efficacy than the multiplex PCR-agarose gel method. The positive detection rate of microarray and agarose gel was 59.0% (n=33) and 41.1% (n=23) among the 56 samples, respectively. CDV vaccine strain and pathogen co-infections were further demonstrated by the microarray but not by the multiplex PCR-agarose gel. The oligonucleotide microarray provides a highly efficient diagnosis alternative that could be applied to clinical usage, greatly assisting in disease therapy and control. Copyright © 2017 Elsevier B.V. All rights reserved.

Probe Selection for DNA Microarrays using OligoWiz

DEFF Research Database (Denmark)

Wernersson, Rasmus; Juncker, Agnieszka; Nielsen, Henrik Bjørn

2007-01-01

Nucleotide abundance measurements using DNA microarray technology are possible only if appropriate probes complementary to the target nucleotides can be identified. Here we present a protocol for selecting DNA probes for microarrays using the OligoWiz application. OligoWiz is a client-server appl......Nucleotide abundance measurements using DNA microarray technology are possible only if appropriate probes complementary to the target nucleotides can be identified. Here we present a protocol for selecting DNA probes for microarrays using the OligoWiz application. OligoWiz is a client......-server application that offers a detailed graphical interface and real-time user interaction on the client side, and massive computer power and a large collection of species databases (400, summer 2007) on the server side. Probes are selected according to five weighted scores: cross-hybridization, deltaT(m), folding...... computer skills and can be executed from any Internet-connected computer. The probe selection procedure for a standard microarray design targeting all yeast transcripts can be completed in 1 h....

Employing image processing techniques for cancer detection using microarray images.

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Dehghan Khalilabad, Nastaran; Hassanpour, Hamid

2017-02-01

Microarray technology is a powerful genomic tool for simultaneously studying and analyzing the behavior of thousands of genes. The analysis of images obtained from this technology plays a critical role in the detection and treatment of diseases. The aim of the current study is to develop an automated system for analyzing data from microarray images in order to detect cancerous cases. The proposed system consists of three main phases, namely image processing, data mining, and the detection of the disease. The image processing phase performs operations such as refining image rotation, gridding (locating genes) and extracting raw data from images the data mining includes normalizing the extracted data and selecting the more effective genes. Finally, via the extracted data, cancerous cell is recognized. To evaluate the performance of the proposed system, microarray database is employed which includes Breast cancer, Myeloid Leukemia and Lymphomas from the Stanford Microarray Database. The results indicate that the proposed system is able to identify the type of cancer from the data set with an accuracy of 95.45%, 94.11%, and 100%, respectively. Copyright © 2017 Elsevier Ltd. All rights reserved.

Microarray-based method for the parallel analysis of genotypes and expression profiles of wood-forming tissues in Eucalyptus grandis

CSIR Research Space (South Africa)

Barros, E

2009-05-01

Full Text Available of Eucalyptus grandis planting stock that exhibit preferred wood qualities is thus a priority of the South African forestry industry. The researchers used microarray-based DNA-amplified fragment length polymorphism (AFLP) analysis in combination with expression...

MicroRNA expression in melanocytic nevi: the usefulness of formalin-fixed, paraffin-embedded material for miRNA microarray profiling.

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Glud, Martin; Klausen, Mikkel; Gniadecki, Robert; Rossing, Maria; Hastrup, Nina; Nielsen, Finn C; Drzewiecki, Krzysztof T

2009-05-01

MicroRNAs (miRNAs) are small, noncoding RNA molecules that regulate cellular differentiation, proliferation, and apoptosis. MiRNAs are expressed in a developmentally regulated and tissue-specific manner. Aberrant expression may contribute to pathological processes such as cancer, and miRNA may therefore serve as biomarkers that may be useful in a clinical environment for diagnosis of various diseases. Most miRNA profiling studies have used fresh tissue samples. However, in some types of cancer, including malignant melanoma, fresh material is difficult to obtain from primary tumors, and most surgical specimens are formalin fixed and paraffin embedded (FFPE). To explore whether FFPE material would be suitable for miRNA profiling in melanocytic lesions, we compared miRNA expression patterns in FFPE versus fresh frozen samples, obtained from 15 human melanocytic nevi. Out of microarray data, we identified 84 miRNAs that were expressed in both types of samples and represented an miRNA profile of melanocytic nevi. Our results showed a high correlation in miRNA expression (Spearman r-value of 0.80) between paired FFPE and fresh frozen material. The data were further validated by quantitative RT-PCR. In conclusion, FFPE specimens of melanocytic lesions are suitable as a source for miRNA microarray profiling.

Microintaglio Printing for Soft Lithography-Based in Situ Microarrays

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Manish Biyani

2015-07-01

Full Text Available Advances in lithographic approaches to fabricating bio-microarrays have been extensively explored over the last two decades. However, the need for pattern flexibility, a high density, a high resolution, affordability and on-demand fabrication is promoting the development of unconventional routes for microarray fabrication. This review highlights the development and uses of a new molecular lithography approach, called “microintaglio printing technology”, for large-scale bio-microarray fabrication using a microreactor array (µRA-based chip consisting of uniformly-arranged, femtoliter-size µRA molds. In this method, a single-molecule-amplified DNA microarray pattern is self-assembled onto a µRA mold and subsequently converted into a messenger RNA or protein microarray pattern by simultaneously producing and transferring (immobilizing a messenger RNA or a protein from a µRA mold to a glass surface. Microintaglio printing allows the self-assembly and patterning of in situ-synthesized biomolecules into high-density (kilo-giga-density, ordered arrays on a chip surface with µm-order precision. This holistic aim, which is difficult to achieve using conventional printing and microarray approaches, is expected to revolutionize and reshape proteomics. This review is not written comprehensively, but rather substantively, highlighting the versatility of microintaglio printing for developing a prerequisite platform for microarray technology for the postgenomic era.

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

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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

Uso de microarrays na busca de perfis de expressão gênica: aplicação no estudo de fenótipos complexos Use of microarrays in the search of gene expression patterns: application to the study of complex phenotypes

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Camila Guindalini

2007-12-01

. By the simultaneous determination of the expression levels of thousands of genes, microarrays allow researchers to compare the molecular behaviour of different types of cells lines or specific tissues that have been exposed to pathological or experimental conditions. The method may provide insights into physiological processes and facilitate the identification of novel biological markers for diagnostic, prognostic and pharmacological treatments for a number of diseases. In this article, we present theoretical and methodological concepts underlying the microarray technology, as well as an overview of its advantages, perspectives and future scientific directions. In an attempt to demonstrate the applicability and efficiency of the method in the study of complex phenotypes, initial results on gene expression studies in post mortem brain samples of psychiatric patients and on the molecular and functional consequences of sleep disturbances, which is strongly associated with psychiatric illness, will be described and discussed.

DNA microarray-based PCR ribotyping of Clostridium difficile.

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Schneeberg, Alexander; Ehricht, Ralf; Slickers, Peter; Baier, Vico; Neubauer, Heinrich; Zimmermann, Stefan; Rabold, Denise; Lübke-Becker, Antina; Seyboldt, Christian

2015-02-01

This study presents a DNA microarray-based assay for fast and simple PCR ribotyping of Clostridium difficile strains. Hybridization probes were designed to query the modularly structured intergenic spacer region (ISR), which is also the template for conventional and PCR ribotyping with subsequent capillary gel electrophoresis (seq-PCR) ribotyping. The probes were derived from sequences available in GenBank as well as from theoretical ISR module combinations. A database of reference hybridization patterns was set up from a collection of 142 well-characterized C. difficile isolates representing 48 seq-PCR ribotypes. The reference hybridization patterns calculated by the arithmetic mean were compared using a similarity matrix analysis. The 48 investigated seq-PCR ribotypes revealed 27 array profiles that were clearly distinguishable. The most frequent human-pathogenic ribotypes 001, 014/020, 027, and 078/126 were discriminated by the microarray. C. difficile strains related to 078/126 (033, 045/FLI01, 078, 126, 126/FLI01, 413, 413/FLI01, 598, 620, 652, and 660) and 014/020 (014, 020, and 449) showed similar hybridization patterns, confirming their genetic relatedness, which was previously reported. A panel of 50 C. difficile field isolates was tested by seq-PCR ribotyping and the DNA microarray-based assay in parallel. Taking into account that the current version of the microarray does not discriminate some closely related seq-PCR ribotypes, all isolates were typed correctly. Moreover, seq-PCR ribotypes without reference profiles available in the database (ribotype 009 and 5 new types) were correctly recognized as new ribotypes, confirming the performance and expansion potential of the microarray. Copyright © 2015, American Society for Microbiology. All Rights Reserved.

Integrated olfactory receptor and microarray gene expression databases

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Crasto Chiquito J

2007-06-01

Full Text Available Abstract Background Gene expression patterns of olfactory receptors (ORs are an important component of the signal encoding mechanism in the olfactory system since they determine the interactions between odorant ligands and sensory neurons. We have developed the Olfactory Receptor Microarray Database (ORMD to house OR gene expression data. ORMD is integrated with the Olfactory Receptor Database (ORDB, which is a key repository of OR gene information. Both databases aim to aid experimental research related to olfaction. Description ORMD is a Web-accessible database that provides a secure data repository for OR microarray experiments. It contains both publicly available and private data; accessing the latter requires authenticated login. The ORMD is designed to allow users to not only deposit gene expression data but also manage their projects/experiments. For example, contributors can choose whether to make their datasets public. For each experiment, users can download the raw data files and view and export the gene expression data. For each OR gene being probed in a microarray experiment, a hyperlink to that gene in ORDB provides access to genomic and proteomic information related to the corresponding olfactory receptor. Individual ORs archived in ORDB are also linked to ORMD, allowing users access to the related microarray gene expression data. Conclusion ORMD serves as a data repository and project management system. It facilitates the study of microarray experiments of gene expression in the olfactory system. In conjunction with ORDB, ORMD integrates gene expression data with the genomic and functional data of ORs, and is thus a useful resource for both olfactory researchers and the public.

Fabrication of Biomolecule Microarrays for Cell Immobilization Using Automated Microcontact Printing.

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Foncy, Julie; Estève, Aurore; Degache, Amélie; Colin, Camille; Cau, Jean Christophe; Malaquin, Laurent; Vieu, Christophe; Trévisiol, Emmanuelle

2018-01-01

Biomolecule microarrays are generally produced by conventional microarrayer, i.e., by contact or inkjet printing. Microcontact printing represents an alternative way of deposition of biomolecules on solid supports but even if various biomolecules have been successfully microcontact printed, the production of biomolecule microarrays in routine by microcontact printing remains a challenging task and needs an effective, fast, robust, and low-cost automation process. Here, we describe the production of biomolecule microarrays composed of extracellular matrix protein for the fabrication of cell microarrays by using an automated microcontact printing device. Large scale cell microarrays can be reproducibly obtained by this method.

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

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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.

See what you eat--broad GMO screening with microarrays.

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von Götz, Franz

2010-03-01

Despite the controversy of whether genetically modified organisms (GMOs) are beneficial or harmful for humans, animals, and/or ecosystems, the number of cultivated GMOs is increasing every year. Many countries and federations have implemented safety and surveillance systems for GMOs. Potent testing technologies need to be developed and implemented to monitor the increasing number of GMOs. First, these GMO tests need to be comprehensive, i.e., should detect all, or at least the most important, GMOs on the market. This type of GMO screening requires a high degree of parallel tests or multiplexing. To date, DNA microarrays have the highest number of multiplexing capabilities when nucleic acids are analyzed. This trend article focuses on the evolution of DNA microarrays for GMO testing. Over the last 7 years, combinations of multiplex PCR detection and microarray detection have been developed to qualitatively assess the presence of GMOs. One example is the commercially available DualChip GMO (Eppendorf, Germany; http://www.eppendorf-biochip.com), which is the only GMO screening system successfully validated in a multicenter study. With use of innovative amplification techniques, promising steps have recently been taken to make GMO detection with microarrays quantitative.

Cross-platform comparison of microarray data using order restricted inference

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Klinglmueller, Florian; Tuechler, Thomas; Posch, Martin

2013-01-01

Motivation Titration experiments measuring the gene expression from two different tissues, along with total RNA mixtures of the pure samples, are frequently used for quality evaluation of microarray technologies. Such a design implies that the true mRNA expression of each gene, is either constant or follows a monotonic trend between the mixtures, applying itself to the use of order restricted inference procedures. Exploiting only the postulated monotonicity of titration designs, we propose three statistical analysis methods for the validation of high-throughput genetic data and corresponding preprocessing techniques. Results Our methods allow for inference of accuracy, repeatability and cross-platform agreement, with minimal required assumptions regarding the underlying data generating process. Therefore, they are readily applicable to all sorts of genetic high-throughput data independent of the degree of preprocessing. An application to the EMERALD dataset was used to demonstrate how our methods provide a rich spectrum of easily interpretable quality metrics and allow the comparison of different microarray technologies and normalization methods. The results are on par with previous work, but provide additional new insights that cast doubt on the utility of popular preprocessing techniques, specifically concerning the EMERALD projects dataset. Availability All datasets are available on EBI’s ArrayExpress web site (http://www.ebi.ac.uk/microarray-as/ae/) under accession numbers E-TABM-536, E-TABM-554 and E-TABM-555. Source code implemented in C and R is available at: http://statistics.msi.meduniwien.ac.at/float/cross_platform/. Methods for testing and variance decomposition have been made available in the R-package orQA, which can be downloaded and installed from CRAN http://cran.r-project.org. PMID:21317143

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

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Bihoreau Marie-Thérèse

2009-02-01

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

Shared probe design and existing microarray reanalysis using PICKY

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Chou Hui-Hsien

2010-04-01

Full Text Available Abstract Background Large genomes contain families of highly similar genes that cannot be individually identified by microarray probes. This limitation is due to thermodynamic restrictions and cannot be resolved by any computational method. Since gene annotations are updated more frequently than microarrays, another common issue facing microarray users is that existing microarrays must be routinely reanalyzed to determine probes that are still useful with respect to the updated annotations. Results PICKY 2.0 can design shared probes for sets of genes that cannot be individually identified using unique probes. PICKY 2.0 uses novel algorithms to track sharable regions among genes and to strictly distinguish them from other highly similar but nontarget regions during thermodynamic comparisons. Therefore, PICKY does not sacrifice the quality of shared probes when choosing them. The latest PICKY 2.1 includes the new capability to reanalyze existing microarray probes against updated gene sets to determine probes that are still valid to use. In addition, more precise nonlinear salt effect estimates and other improvements are added, making PICKY 2.1 more versatile to microarray users. Conclusions Shared probes allow expressed gene family members to be detected; this capability is generally more desirable than not knowing anything about these genes. Shared probes also enable the design of cross-genome microarrays, which facilitate multiple species identification in environmental samples. The new nonlinear salt effect calculation significantly increases the precision of probes at a lower buffer salt concentration, and the probe reanalysis function improves existing microarray result interpretations.

An algorithm for finding biologically significant features in microarray data based on a priori manifold learning.

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Zena M Hira

Full Text Available Microarray databases are a large source of genetic data, which, upon proper analysis, could enhance our understanding of biology and medicine. Many microarray experiments have been designed to investigate the genetic mechanisms of cancer, and analytical approaches have been applied in order to classify different types of cancer or distinguish between cancerous and non-cancerous tissue. However, microarrays are high-dimensional datasets with high levels of noise and this causes problems when using machine learning methods. A popular approach to this problem is to search for a set of features that will simplify the structure and to some degree remove the noise from the data. The most widely used approach to feature extraction is principal component analysis (PCA which assumes a multivariate Gaussian model of the data. More recently, non-linear methods have been investigated. Among these, manifold learning algorithms, for example Isomap, aim to project the data from a higher dimensional space onto a lower dimension one. We have proposed a priori manifold learning for finding a manifold in which a representative set of microarray data is fused with relevant data taken from the KEGG pathway database. Once the manifold has been constructed the raw microarray data is projected onto it and clustering and classification can take place. In contrast to earlier fusion based methods, the prior knowledge from the KEGG databases is not used in, and does not bias the classification process--it merely acts as an aid to find the best space in which to search the data. In our experiments we have found that using our new manifold method gives better classification results than using either PCA or conventional Isomap.

Detecting imbalanced expression of SNP alleles by minisequencing on microarrays

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Dahlgren Andreas

2004-10-01

Full Text Available Abstract Background Each of the human genes or transcriptional units is likely to contain single nucleotide polymorphisms that may give rise to sequence variation between individuals and tissues on the level of RNA. Based on recent studies, differential expression of the two alleles of heterozygous coding single nucleotide polymorphisms (SNPs may be frequent for human genes. Methods with high accuracy to be used in a high throughput setting are needed for systematic surveys of expressed sequence variation. In this study we evaluated two formats of multiplexed, microarray based minisequencing for quantitative detection of imbalanced expression of SNP alleles. We used a panel of ten SNPs located in five genes known to be expressed in two endothelial cell lines as our model system. Results The accuracy and sensitivity of quantitative detection of allelic imbalance was assessed for each SNP by constructing regression lines using a dilution series of mixed samples from individuals of different genotype. Accurate quantification of SNP alleles by both assay formats was evidenced for by R2 values > 0.95 for the majority of the regression lines. According to a two sample t-test, we were able to distinguish 1–9% of a minority SNP allele from a homozygous genotype, with larger variation between SNPs than between assay formats. Six of the SNPs, heterozygous in either of the two cell lines, were genotyped in RNA extracted from the endothelial cells. The coefficient of variation between the fluorescent signals from five parallel reactions was similar for cDNA and genomic DNA. The fluorescence signal intensity ratios measured in the cDNA samples were compared to those in genomic DNA to determine the relative expression levels of the two alleles of each SNP. Four of the six SNPs tested displayed a higher than 1.4-fold difference in allelic ratios between cDNA and genomic DNA. The results were verified by allele-specific oligonucleotide hybridisation and

Washing scaling of GeneChip microarray expression

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Krohn Knut

2010-05-01

Full Text Available Abstract Background Post-hybridization washing is an essential part of microarray experiments. Both the quality of the experimental washing protocol and adequate consideration of washing in intensity calibration ultimately affect the quality of the expression estimates extracted from the microarray intensities. Results We conducted experiments on GeneChip microarrays with altered protocols for washing, scanning and staining to study the probe-level intensity changes as a function of the number of washing cycles. For calibration and analysis of the intensity data we make use of the 'hook' method which allows intensity contributions due to non-specific and specific hybridization of perfect match (PM and mismatch (MM probes to be disentangled in a sequence specific manner. On average, washing according to the standard protocol removes about 90% of the non-specific background and about 30-50% and less than 10% of the specific targets from the MM and PM, respectively. Analysis of the washing kinetics shows that the signal-to-noise ratio doubles roughly every ten stringent washing cycles. Washing can be characterized by time-dependent rate constants which reflect the heterogeneous character of target binding to microarray probes. We propose an empirical washing function which estimates the survival of probe bound targets. It depends on the intensity contribution due to specific and non-specific hybridization per probe which can be estimated for each probe using existing methods. The washing function allows probe intensities to be calibrated for the effect of washing. On a relative scale, proper calibration for washing markedly increases expression measures, especially in the limit of small and large values. Conclusions Washing is among the factors which potentially distort expression measures. The proposed first-order correction method allows direct implementation in existing calibration algorithms for microarray data. We provide an experimental

Development, characterization and experimental validation of a cultivated sunflower (Helianthus annuus L.) gene expression oligonucleotide microarray.

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Fernandez, Paula; Soria, Marcelo; Blesa, David; DiRienzo, Julio; Moschen, Sebastian; Rivarola, Maximo; Clavijo, Bernardo Jose; Gonzalez, Sergio; Peluffo, Lucila; Príncipi, Dario; Dosio, Guillermo; Aguirrezabal, Luis; García-García, Francisco; Conesa, Ana; Hopp, Esteban; Dopazo, Joaquín; Heinz, Ruth Amelia; Paniego, Norma

2012-01-01

Oligonucleotide-based microarrays with accurate gene coverage represent a key strategy for transcriptional studies in orphan species such as sunflower, H. annuus L., which lacks full genome sequences. The goal of this study was the development and functional annotation of a comprehensive sunflower unigene collection and the design and validation of a custom sunflower oligonucleotide-based microarray. A large scale EST (>130,000 ESTs) curation, assembly and sequence annotation was performed using Blast2GO (www.blast2go.de). The EST assembly comprises 41,013 putative transcripts (12,924 contigs and 28,089 singletons). The resulting Sunflower Unigen Resource (SUR version 1.0) was used to design an oligonucleotide-based Agilent microarray for cultivated sunflower. This microarray includes a total of 42,326 features: 1,417 Agilent controls, 74 control probes for sunflower replicated 10 times (740 controls) and 40,169 different non-control probes. Microarray performance was validated using a model experiment examining the induction of senescence by water deficit. Pre-processing and differential expression analysis of Agilent microarrays was performed using the Bioconductor limma package. The analyses based on p-values calculated by eBayes (psunflower unigene collection, and a custom, validated sunflower oligonucleotide-based microarray using Agilent technology. Both the curated unigene collection and the validated oligonucleotide microarray provide key resources for sunflower genome analysis, transcriptional studies, and molecular breeding for crop improvement.

The use of microarrays in microbial ecology

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Andersen, G.L.; He, Z.; DeSantis, T.Z.; Brodie, E.L.; Zhou, J.

2009-09-15

Microarrays have proven to be a useful and high-throughput method to provide targeted DNA sequence information for up to many thousands of specific genetic regions in a single test. A microarray consists of multiple DNA oligonucleotide probes that, under high stringency conditions, hybridize only to specific complementary nucleic acid sequences (targets). A fluorescent signal indicates the presence and, in many cases, the abundance of genetic regions of interest. In this chapter we will look at how microarrays are used in microbial ecology, especially with the recent increase in microbial community DNA sequence data. Of particular interest to microbial ecologists, phylogenetic microarrays are used for the analysis of phylotypes in a community and functional gene arrays are used for the analysis of functional genes, and, by inference, phylotypes in environmental samples. A phylogenetic microarray that has been developed by the Andersen laboratory, the PhyloChip, will be discussed as an example of a microarray that targets the known diversity within the 16S rRNA gene to determine microbial community composition. Using multiple, confirmatory probes to increase the confidence of detection and a mismatch probe for every perfect match probe to minimize the effect of cross-hybridization by non-target regions, the PhyloChip is able to simultaneously identify any of thousands of taxa present in an environmental sample. The PhyloChip is shown to reveal greater diversity within a community than rRNA gene sequencing due to the placement of the entire gene product on the microarray compared with the analysis of up to thousands of individual molecules by traditional sequencing methods. A functional gene array that has been developed by the Zhou laboratory, the GeoChip, will be discussed as an example of a microarray that dynamically identifies functional activities of multiple members within a community. The recent version of GeoChip contains more than 24,000 50mer

Integrative proteomics and tissue microarray profiling indicate the association between overexpressed serum proteins and non-small cell lung cancer.

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Yansheng Liu

Full Text Available Lung cancer is the leading cause of cancer deaths worldwide. Clinically, the treatment of non-small cell lung cancer (NSCLC can be improved by the early detection and risk screening among population. To meet this need, here we describe the application of extensive peptide level fractionation coupled with label free quantitative proteomics for the discovery of potential serum biomarkers for lung cancer, and the usage of Tissue microarray analysis (TMA and Multiple reaction monitoring (MRM assays for the following up validations in the verification phase. Using these state-of-art, currently available clinical proteomic approaches, in the discovery phase we confidently identified 647 serum proteins, and 101 proteins showed a statistically significant association with NSCLC in our 18 discovery samples. This serum proteomic dataset allowed us to discern the differential patterns and abnormal biological processes in the lung cancer blood. Of these proteins, Alpha-1B-glycoprotein (A1BG and Leucine-rich alpha-2-glycoprotein (LRG1, two plasma glycoproteins with previously unknown function were selected as examples for which TMA and MRM verification were performed in a large sample set consisting about 100 patients. We revealed that A1BG and LRG1 were overexpressed in both the blood level and tumor sections, which can be referred to separate lung cancer patients from healthy cases.

Integrative missing value estimation for microarray data.

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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.

A Java-based tool for the design of classification microarrays

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Broschat Shira L

2008-08-01

Full Text Available Abstract Background 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. Results 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. Conclusion 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

Identification of rat lung-specific microRNAs by microRNA microarray: valuable discoveries for the facilitation of lung research

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Chintagari Narendranath

2007-01-01

Full Text Available Abstract Background An important mechanism for gene regulation utilizes small non-coding RNAs called microRNAs (miRNAs. These small RNAs play important roles in tissue development, cell differentiation and proliferation, lipid and fat metabolism, stem cells, exocytosis, diseases and cancers. To date, relatively little is known about functions of miRNAs in the lung except lung cancer. Results In this study, we utilized a rat miRNA microarray containing 216 miRNA probes, printed in-house, to detect the expression of miRNAs in the rat lung compared to the rat heart, brain, liver, kidney and spleen. Statistical analysis using Significant Analysis of Microarray (SAM and Tukey Honestly Significant Difference (HSD revealed 2 miRNAs (miR-195 and miR-200c expressed specifically in the lung and 9 miRNAs co-expressed in the lung and another organ. 12 selected miRNAs were verified by Northern blot analysis. Conclusion The identified lung-specific miRNAs from this work will facilitate functional studies of miRNAs during normal physiological and pathophysiological processes of the lung.

Identification of rat lung-specific microRNAs by micoRNA microarray: valuable discoveries for the facilitation of lung research.

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Wang, Yang; Weng, Tingting; Gou, Deming; Chen, Zhongming; Chintagari, Narendranath Reddy; Liu, Lin

2007-01-24

An important mechanism for gene regulation utilizes small non-coding RNAs called microRNAs (miRNAs). These small RNAs play important roles in tissue development, cell differentiation and proliferation, lipid and fat metabolism, stem cells, exocytosis, diseases and cancers. To date, relatively little is known about functions of miRNAs in the lung except lung cancer. In this study, we utilized a rat miRNA microarray containing 216 miRNA probes, printed in-house, to detect the expression of miRNAs in the rat lung compared to the rat heart, brain, liver, kidney and spleen. Statistical analysis using Significant Analysis of Microarray (SAM) and Tukey Honestly Significant Difference (HSD) revealed 2 miRNAs (miR-195 and miR-200c) expressed specifically in the lung and 9 miRNAs co-expressed in the lung and another organ. 12 selected miRNAs were verified by Northern blot analysis. The identified lung-specific miRNAs from this work will facilitate functional studies of miRNAs during normal physiological and pathophysiological processes of the lung.

Deciphering cellular morphology and biocompatibility using polymer microarrays

International Nuclear Information System (INIS)

Pernagallo, Salvatore; Unciti-Broceta, Asier; DIaz-Mochon, Juan Jose; Bradley, Mark

2008-01-01

A quantitative and qualitative analysis of cellular adhesion, morphology and viability is essential in understanding and designing biomaterials such as those involved in implant surfaces or as tissue-engineering scaffolds. As a means to simultaneously perform these studies in a high-throughput (HT) manner, we report a normalized protocol which allows the rapid analysis of a large number of potential cell binding substrates using polymer microarrays and high-content fluorescence microscopy. The method was successfully applied to the discovery of optimal polymer substrates from a 214-member polyurethane library with mouse fibroblast cells (L929), as well as simultaneous evaluation of cell viability and cellular morphology. Analysis demonstrated high biocompatibility of the binding polymers and permitted the identification of several different cellular morphologies, showing that specific polymer interactions may provoke changes in cell shape. In addition, SAR studies showed a clear correspondence between cellular adhesion and polymer structure. The approach can be utilized to perform multiple experiments (up to 1024 single experiments per slide) in a highly reproducible manner, leading to the generation of vast amounts of data in a short time period (48-72 h) while reducing dramatically the quantities of polymers, reagents and cells used

Comparison of gene coverage of mouse oligonucleotide microarray platforms

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Medrano Juan F

2006-03-01

Full Text Available Abstract Background The increasing use of DNA microarrays for genetical genomics studies generates a need for platforms with complete coverage of the genome. We have compared the effective gene coverage in the mouse genome of different commercial and noncommercial oligonucleotide microarray platforms by performing an in-house gene annotation of probes. We only used information about probes that is available from vendors and followed a process that any researcher may take to find the gene targeted by a given probe. In order to make consistent comparisons between platforms, probes in each microarray were annotated with an Entrez Gene id and the chromosomal position for each gene was obtained from the UCSC Genome Browser Database. Gene coverage was estimated as the percentage of Entrez Genes with a unique position in the UCSC Genome database that is tested by a given microarray platform. Results A MySQL relational database was created to store the mapping information for 25,416 mouse genes and for the probes in five microarray platforms (gene coverage level in parenthesis: Affymetrix430 2.0 (75.6%, ABI Genome Survey (81.24%, Agilent (79.33%, Codelink (78.09%, Sentrix (90.47%; and four array-ready oligosets: Sigma (47.95%, Operon v.3 (69.89%, Operon v.4 (84.03%, and MEEBO (84.03%. The differences in coverage between platforms were highly conserved across chromosomes. Differences in the number of redundant and unspecific probes were also found among arrays. The database can be queried to compare specific genomic regions using a web interface. The software used to create, update and query the database is freely available as a toolbox named ArrayGene. Conclusion The software developed here allows researchers to create updated custom databases by using public or proprietary information on genes for any organisms. ArrayGene allows easy comparisons of gene coverage between microarray platforms for any region of the genome. The comparison presented here

Molecular characterisation of the early response in pigs to experimental infection with Actinobacillus pleuropneumoniae using cDNA microarrays

DEFF Research Database (Denmark)

Hedegaard, Jakob; Skovgaard, Kerstin; Mortensen, Shila

2007-01-01

Background: The bacterium Actinobacillus pleuropneumoniae is responsible for porcine pleuropneumonia, a widespread, highly contagious and often fatal respiratory disease of pigs. The general porcine innate immune response after A. pleuropneumoniae infection is still not clarified. The objective...... lymph node tissue were hybridised to an expanded version of the porcine microarray with 26879 unique PCR products. Results: A total of 357 genes differed significantly in expression between infected and non-infected lung tissue, 713 genes differed in expression in liver tissue from infected versus non-infected...... animals and 130 genes differed in expression in tracheobronchial lymph node tissue from infected versus non-infected animals. Among these genes, several have previously been described to be part of a general host response to infections encoding immune response related proteins. In inflamed lung tissue...

Pathway-specific differences between tumor cell lines and normal and tumor tissue cells

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Tozeren Aydin

2006-11-01

Full Text Available Abstract Background Cell lines are used in experimental investigation of cancer but their capacity to represent tumor cells has yet to be quantified. The aim of the study was to identify significant alterations in pathway usage in cell lines in comparison with normal and tumor tissue. Methods This study utilized a pathway-specific enrichment analysis of publicly accessible microarray data and quantified the gene expression differences between cell lines, tumor, and normal tissue cells for six different tissue types. KEGG pathways that are significantly different between cell lines and tumors, cell lines and normal tissues and tumor and normal tissue were identified through enrichment tests on gene lists obtained using Significance Analysis of Microarrays (SAM. Results Cellular pathways that were significantly upregulated in cell lines compared to tumor cells and normal cells of the same tissue type included ATP synthesis, cell communication, cell cycle, oxidative phosphorylation, purine, pyrimidine and pyruvate metabolism, and proteasome. Results on metabolic pathways suggested an increase in the velocity nucleotide metabolism and RNA production. Pathways that were downregulated in cell lines compared to tumor and normal tissue included cell communication, cell adhesion molecules (CAMs, and ECM-receptor interaction. Only a fraction of the significantly altered genes in tumor-to-normal comparison had similar expressions in cancer cell lines and tumor cells. These genes were tissue-specific and were distributed sparsely among multiple pathways. Conclusion Significantly altered genes in tumors compared to normal tissue were largely tissue specific. Among these genes downregulation was a major trend. In contrast, cell lines contained large sets of significantly upregulated genes that were common to multiple tissue types. Pathway upregulation in cell lines was most pronounced over metabolic pathways including cell nucleotide metabolism and oxidative

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

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2012-01-01

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

Combined gene expression analysis of whole-tissue and microdissected pancreatic ductal adenocarcinoma identifies genes specifically overexpressed in tumor epithelia.

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Badea, Liviu; Herlea, Vlad; Dima, Simona Olimpia; Dumitrascu, Traian; Popescu, Irinel

2008-01-01

The precise details of pancreatic ductal adenocarcinoma (PDAC) pathogenesis are still insufficiently known, requiring the use of high-throughput methods. However, PDAC is especially difficult to study using microarrays due to its strong desmoplastic reaction, which involves a hyperproliferating stroma that effectively "masks" the contribution of the minoritary neoplastic epithelial cells. Thus it is not clear which of the genes that have been found differentially expressed between normal and whole tumor tissues are due to the tumor epithelia and which simply reflect the differences in cellular composition. To address this problem, laser microdissection studies have been performed, but these have to deal with much smaller tissue sample quantities and therefore have significantly higher experimental noise. In this paper we combine our own large sample whole-tissue study with a previously published smaller sample microdissection study by Grützmann et al. to identify the genes that are specifically overexpressed in PDAC tumor epithelia. The overlap of this list of genes with other microarray studies of pancreatic cancer as well as with the published literature is impressive. Moreover, we find a number of genes whose over-expression appears to be inversely correlated with patient survival: keratin 7, laminin gamma 2, stratifin, platelet phosphofructokinase, annexin A2, MAP4K4 and OACT2 (MBOAT2), which are all specifically upregulated in the neoplastic epithelia, rather than the tumor stroma. We improve on other microarray studies of PDAC by putting together the higher statistical power due to a larger number of samples with information about cell-type specific expression and patient survival.

Microarray-based screening of heat shock protein inhibitors.

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

2014-06-20

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

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

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E. V. Thomas

2009-01-01

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

Microarrays for global expression constructed with a low redundancy set of 27,500 sequenced cDNAs representing an array of developmental stages and physiological conditions of the soybean plant

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Retzel Ernest

2004-09-01

Full Text Available Abstract Background Microarrays are an important tool with which to examine coordinated gene expression. Soybean (Glycine max is one of the most economically valuable crop species in the world food supply. In order to accelerate both gene discovery as well as hypothesis-driven research in soybean, global expression resources needed to be developed. The applications of microarray for determining patterns of expression in different tissues or during conditional treatments by dual labeling of the mRNAs are unlimited. In addition, discovery of the molecular basis of traits through examination of naturally occurring variation in hundreds of mutant lines could be enhanced by the construction and use of soybean cDNA microarrays. Results We report the construction and analysis of a low redundancy 'unigene' set of 27,513 clones that represent a variety of soybean cDNA libraries made from a wide array of source tissue and organ systems, developmental stages, and stress or pathogen-challenged plants. The set was assembled from the 5' sequence data of the cDNA clones using cluster analysis programs. The selected clones were then physically reracked and sequenced at the 3' end. In order to increase gene discovery from immature cotyledon libraries that contain abundant mRNAs representing storage protein gene families, we utilized a high density filter normalization approach to preferentially select more weakly expressed cDNAs. All 27,513 cDNA inserts were amplified by polymerase chain reaction. The amplified products, along with some repetitively spotted control or 'choice' clones, were used to produce three 9,728-element microarrays that have been used to examine tissue specific gene expression and global expression in mutant isolines. Conclusions Global expression studies will be greatly aided by the availability of the sequence-validated and low redundancy cDNA sets described in this report. These cDNAs and ESTs represent a wide array of developmental

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

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

2010-05-21

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

Spot detection and image segmentation in DNA microarray data.

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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.

Implementation of mutual information and bayes theorem for classification microarray data

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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%.

Comparing independent microarray studies: the case of human embryonic stem cells

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Hemmati-Brivanlou Ali

2005-07-01

Full Text Available Abstract Background Microarray studies of the same phenomenon in different labs often appear at variance because the published lists of regulated transcripts have disproportionately small intersections. We demonstrate that comparing studies by intersecting lists in this manner is methodologically flawed by reanalyzing three studies of the molecular signature of "stemness" in human embryonic stem cells. There are only 7 genes common to all three published lists, suggesting disagreement. Results Carefully reanalyzing all three together from the raw data we detect 111 genes upregulated and 95 downregulated in all three studies. The upregulated list was subject to rtRTPCR analysis and 75% of the genes were confirmed. Conclusion Our findings show that the three studies have a substantial core of common genes, which is missed if only the published lists are examined. Combined analysis of multiple experiments can be a powerful way to distil coherent conclusions.

Epigenetics-related genes in prostate cancer: expression profile in prostate cancer tissues, androgen-sensitive and -insensitive cell lines.

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Shaikhibrahim, Zaki; Lindstrot, Andreas; Ochsenfahrt, Jacqueline; Fuchs, Kerstin; Wernert, Nicolas

2013-01-01

Epigenetic changes have been suggested to drive prostate cancer (PCa) development and progression. Therefore, in this study, we aimed to identify novel epigenetics-related genes in PCa tissues, and to examine their expression in metastatic PCa cell lines. We analyzed the expression of epigenetics-related genes via a clustering analysis based on gene function in moderately and poorly differentiated PCa glands compared to normal glands of the peripheral zone (prostate proper) from PCa patients using Whole Human Genome Oligo Microarrays. Our analysis identified 12 epigenetics-related genes with a more than 2-fold increase or decrease in expression and a p-value epigenetics-related genes that we identified in primary PCa tissues may provide further insight into the role that epigenetic changes play in PCa. Moreover, some of the genes that we identified may play important roles in primary PCa and metastasis, in primary PCa only, or in metastasis only. Follow-up studies are required to investigate the functional role and the role that the expression of these genes play in the outcome and progression of PCa using tissue microarrays.

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

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

2003-10-01

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

Integrative missing value estimation for microarray data

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Zhou Xianghong

2006-10-01

Full Text Available Abstract Background 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. Results 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. Conclusion 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.

CONFIRMING MICROARRAY DATA--IS IT REALLY NECESSARY?

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The generation of corroborative data has become a commonly used approach for ensuring the veracity of microarray data. Indeed, the need to conduct corroborative studies has now become official editorial policy for at least two journals, and several more are considering introducin...

Analyses of Aloe polysaccharides using carbohydrate microarray profiling

DEFF Research Database (Denmark)

Isager Ahl, Louise; Grace, Olwen M; Pedersen, Henriette Lodberg

2018-01-01

As the popularity of Aloe vera extracts continues to rise, a desire to fully understand the individual polymer components of the leaf mesophyll, their relation to one another and the effects they have on the human body are increasing. Polysaccharides present in the leaf mesophyll have been...... identified as the components responsible for the biological activities of Aloe vera, and they have been widely studied in the past decades. However, the commonly used methods do not provide the desired platform to conduct large comparative studies of polysaccharide compositions as most of them require...... a complete or near-complete fractionation of the polymers. The objective for this study was to assess whether carbohydrate microarrays could be used for the high-throughput analysis of cell wall polysaccharides in Aloe leaf mesophyll. The method we chose is known as Comprehensive Microarray Polymer Profiling...

DNA microarray data and contextual analysis of correlation graphs

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Hingamp Pascal

2003-04-01

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

Extended analysis of benchmark datasets for Agilent two-color microarrays

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Kerr Kathleen F

2007-10-01

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

Improved microarray-based decision support with graph encoded interactome data.

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Anneleen Daemen

Full Text Available In the past, microarray studies have been criticized due to noise and the limited overlap between gene signatures. Prior biological knowledge should therefore be incorporated as side information in models based on gene expression data to improve the accuracy of diagnosis and prognosis in cancer. As prior knowledge, we investigated interaction and pathway information from the human interactome on different aspects of biological systems. By exploiting the properties of kernel methods, relations between genes with similar functions but active in alternative pathways could be incorporated in a support vector machine classifier based on spectral graph theory. Using 10 microarray data sets, we first reduced the number of data sources relevant for multiple cancer types and outcomes. Three sources on metabolic pathway information (KEGG, protein-protein interactions (OPHID and miRNA-gene targeting (microRNA.org outperformed the other sources with regard to the considered class of models. Both fixed and adaptive approaches were subsequently considered to combine the three corresponding classifiers. Averaging the predictions of these classifiers performed best and was significantly better than the model based on microarray data only. These results were confirmed on 6 validation microarray sets, with a significantly improved performance in 4 of them. Integrating interactome data thus improves classification of cancer outcome for the investigated microarray technologies and cancer types. Moreover, this strategy can be incorporated in any kernel method or non-linear version of a non-kernel method.

Testing a Microarray to Detect and Monitor Toxic Microalgae in Arcachon Bay in France

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Linda K. Medlin

2013-03-01

Full Text Available Harmful algal blooms (HABs occur worldwide, causing health problems and economic damages to fisheries and tourism. Monitoring agencies are therefore essential, yet monitoring is based only on time-consuming light microscopy, a level at which a correct identification can be limited by insufficient morphological characters. The project MIDTAL (Microarray Detection of Toxic Algae—an FP7-funded EU project—used rRNA genes (SSU and LSU as a target on microarrays to identify toxic species. Furthermore, toxins were detected with a newly developed multiplex optical Surface Plasmon Resonance biosensor (Multi SPR and compared with an enzyme-linked immunosorbent assay (ELISA. In this study, we demonstrate the latest generation of MIDTAL microarrays (version 3 and show the correlation between cell counts, detected toxin and microarray signals from field samples taken in Arcachon Bay in France in 2011. The MIDTAL microarray always detected more potentially toxic species than those detected by microscopic counts. The toxin detection was even more sensitive than both methods. Because of the universal nature of both toxin and species microarrays, they can be used to detect invasive species. Nevertheless, the MIDTAL microarray is not completely universal: first, because not all toxic species are on the chip, and second, because invasive species, such as Ostreopsis, already influence European coasts.

Mining meiosis and gametogenesis with DNA microarrays.

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Schlecht, Ulrich; Primig, Michael

2003-04-01

Gametogenesis is a key developmental process that involves complex transcriptional regulation of numerous genes including many that are conserved between unicellular eukaryotes and mammals. Recent expression-profiling experiments using microarrays have provided insight into the co-ordinated transcription of several hundred genes during mitotic growth and meiotic development in budding and fission yeast. Furthermore, microarray-based studies have identified numerous loci that are regulated during the cell cycle or expressed in a germ-cell specific manner in eukaryotic model systems like Caenorhabditis elegans, Mus musculus as well as Homo sapiens. The unprecedented amount of information produced by post-genome biology has spawned novel approaches to organizing biological knowledge using currently available information technology. This review outlines experiments that contribute to an emerging comprehensive picture of the molecular machinery governing sexual reproduction in eukaryotes.

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

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

2018-02-01

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

Microarray analysis in the archaeon Halobacterium salinarum strain R1.

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Jens Twellmeyer

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

Biobanking for cancer research: Preservation of tissue integrity - Some technical considerations

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S K Shankar

2012-01-01

Full Text Available Biobanking and biomarker discovery have become an integral part of neuro-oncology research. Towards achieving this end, the essential requirement is optimizing methods of tissue preservation of human tissues removed at surgery for diagnostic purposes and banking them for subserving future research. Owing to recent advances in molecular diagnostic tools, this clinical material has become a precious source for proteomic and genomic studies. The advent of biotechnological tools such as microarray, proteomics, and genomics has made it essential to preserve not just morphology but also the quality of nucleic acids and proteins, changing the traditional workflow of a pathology laboratory. It is therefore essential to develop simple technologies for tissue fixation and storage ensure that receptor and molecular integrity is reasonably maintained. Knowledge of the basic chemistry of tissue fixatives, the biochemical changes that take place in biological material by utilizing different techniques of fixation is essential while undertaking molecular, genomic, and proteomic studies on fresh and archival tissues.

Microarrays: Molecular allergology and nanotechnology for personalised medicine (II).

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Lucas, J M

2010-01-01

Progress in nanotechnology and DNA recombination techniques have produced tools for the diagnosis and investigation of allergy at molecular level. The most advanced examples of such progress are the microarray techniques, which have been expanded not only in research in the field of proteomics but also in application to the clinical setting. Microarrays of allergic components offer results relating to hundreds of allergenic components in a single test, and using a small amount of serum which can be obtained from capillary blood. The availability of new molecules will allow the development of panels including new allergenic components and sources, which will require evaluation for clinical use. Their application opens the door to component-based diagnosis, to the holistic perception of sensitisation as represented by molecular allergy, and to patient-centred medical practice by allowing great diagnostic accuracy and the definition of individualised immunotherapy for each patient. The present article reviews the application of allergenic component microarrays to allergology for diagnosis, management in the form of specific immunotherapy, and epidemiological studies. A review is also made of the use of protein and gene microarray techniques in basic research and in allergological diseases. Lastly, an evaluation is made of the challenges we face in introducing such techniques to clinical practice, and of the future perspectives of this new technology. Copyright 2010 SEICAP. Published by Elsevier Espana. All rights reserved.

Expression profiling of microRNAs in human bone tissue from postmenopausal women.

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De-Ugarte, Laura; Serra-Vinardell, Jenny; Nonell, Lara; Balcells, Susana; Arnal, Magdalena; Nogues, Xavier; Mellibovsky, Leonardo; Grinberg, Daniel; Diez-Perez, Adolfo; Garcia-Giralt, Natalia

2018-01-01

Bone tissue is composed of several cell types, which express their own microRNAs (miRNAs) that will play a role in cell function. The set of total miRNAs expressed in all cell types configures the specific signature of the bone tissue in one physiological condition. The aim of this study was to explore the miRNA expression profile of bone tissue from postmenopausal women. Tissue was obtained from trabecular bone and was analyzed in fresh conditions (n = 6). Primary osteoblasts were also obtained from trabecular bone (n = 4) and human osteoclasts were obtained from monocyte precursors after in vitro differentiation (n = 5). MicroRNA expression profiling was obtained for each sample by microarray and a global miRNA analysis was performed combining the data acquired in all the microarray experiments. From the 641 miRNAs detected in bone tissue samples, 346 (54%) were present in osteoblasts and/or osteoclasts. The other 46% were not identified in any of the bone cells analyzed. Intersection of osteoblast and osteoclast arrays identified 101 miRNAs shared by both cell types, which accounts for 30-40% of miRNAs detected in these cells. In osteoblasts, 266 miRNAs were detected, of which 243 (91%) were also present in the total bone array, representing 38% of all bone miRNAs. In osteoclasts, 340 miRNAs were detected, of which 196 (58%) were also present in the bone tissue array, representing 31% of all miRNAs detected in total bone. These analyses provide an overview of miRNAs expressed in bone tissue, broadening our knowledge in the microRNA field.

Design issues in toxicogenomics using DNA microarray experiment

International Nuclear Information System (INIS)

Lee, Kyoung-Mu; Kim, Ju-Han; Kang, Daehee

2005-01-01

The methods of toxicogenomics might be classified into omics study (e.g., genomics, proteomics, and metabolomics) and population study focusing on risk assessment and gene-environment interaction. In omics study, microarray is the most popular approach. Genes falling into several categories (e.g., xenobiotics metabolism, cell cycle control, DNA repair etc.) can be selected up to 20,000 according to a priori hypothesis. The appropriate type of samples and species should be selected in advance. Multiple doses and varied exposure durations are suggested to identify those genes clearly linked to toxic response. Microarray experiments can be affected by numerous nuisance variables including experimental designs, sample extraction, type of scanners, etc. The number of slides might be determined from the magnitude and variance of expression change, false-positive rate, and desired power. Instead, pooling samples is an alternative. Online databases on chemicals with known exposure-disease outcomes and genetic information can aid the interpretation of the normalized results. Gene function can be inferred from microarray data analyzed by bioinformatics methods such as cluster analysis. The population study often adopts hospital-based or nested case-control design. Biases in subject selection and exposure assessment should be minimized, and confounding bias should also be controlled for in stratified or multiple regression analysis. Optimal sample sizes are dependent on the statistical test for gene-to-environment or gene-to-gene interaction. The design issues addressed in this mini-review are crucial in conducting toxicogenomics study. In addition, integrative approach of exposure assessment, epidemiology, and clinical trial is required

Advanced spot quality analysis in two-colour microarray experiments

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Vetter Guillaume

2008-09-01

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

Senescent vs. non-senescent cells in the human annulus in vivo: Cell harvest with laser capture microdissection and gene expression studies with microarray analysis

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Ingram Jane A

2010-01-01

Full Text Available Abstract Background Senescent cells are well-recognized in the aging/degenerating human disc. Senescent cells are viable, cannot divide, remain metabolically active and accumulate within the disc over time. Molecular analysis of senescent cells in tissue offers a special challenge since there are no cell surface markers for senescence which would let one use fluorescence-activated cell sorting as a method for separating out senescent cells. Methods We employed a novel laser capture microdissection (LCM design to selectively harvest senescent and non-senescent annulus cells in paraffin-embedded tissue, and compared their gene expression with microarray analysis. LCM was used to separately harvest senescent and non-senescent cells from 11 human annulus specimens. Results Microarray analysis revealed significant differences in expression levels in senescent cells vs non-senescent cells: 292 genes were upregulated, and 321 downregulated. Genes with established relationships to senescence were found to be significantly upregulated in senescent cells vs. non-senescent cells: p38 (MPAK14, RB-Associated KRAB zinc finger, Discoidin, CUB and LCCL domain, growth arrest and DNA-damage inducible beta, p28ING5, sphingosine-1-phosphate receptor 2 and somatostatin receptor 3; cyclin-dependent kinase 8 showed significant downregulation in senescent cells. Nitric oxidase synthase 1, and heat shock 70 kDa protein 6, both of which were significantly down-regulated in senescent cells, also showed significant changes. Additional genes related to cytokines, cell proliferation, and other processes were also identified. Conclusions Our LCM-microarray analyses identified a set of genes associated with senescence which were significantly upregulated in senescent vs non-senescent cells in the human annulus. These genes include p38 MAP kinase, discoidin, inhibitor of growth family member 5, and growth arrest and DNA-damage-inducible beta. Other genes, including genes

Aberrant Expression of miRNA and mRNAs in Lesioned Tissues of Graves' Disease

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Qiu Qin

2015-03-01

Full Text Available Background and Aims: Abnormal microRNA (miRNA expression is found in many diseases including autoimmune diseases. However, little is known about the role of miRNA regulation in Graves' disease (GD. Here, we simultaneously detected different expressions of miRNA and mRNAs in thyroid tissues via a high-throughput transcriptomics approach, known as microarray, in order to reveal the relationship between aberrant expression of miRNAs and mRNAs spectrum and GD. Methods: Totally 7 specimens of thyroid tissue from 4 GD patients and 3 controls were obtained by surgery for microarray analysis. Then, 30 thyroid specimens (18 GD and 12 controls were also collected for further validation by quantitative real-time PCR ( qRT-PCR . Results: Statistical analysis showed that the expressions of 5 specific miRNA were increased significantly while those of other 18 miRNA were decreased in thyroid tissue of GD patients (FC≥1.3 or≤0.77 and pConclusion: Our study highlights the possibility that miRNA-target gene network may be involved in the pathogenesis of GD and could provide new insights into understanding the pathophysiological mechanisms of GD.

Analysis of Temporal-spatial Co-variation within Gene Expression Microarray Data in an Organogenesis Model

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Ehler, Martin; Rajapakse, Vinodh; Zeeberg, Barry; Brooks, Brian; Brown, Jacob; Czaja, Wojciech; Bonner, Robert F.

The gene networks underlying closure of the optic fissure during vertebrate eye development are poorly understood. We used a novel clustering method based on Laplacian Eigenmaps, a nonlinear dimension reduction method, to analyze microarray data from laser capture microdissected (LCM) cells at the site and developmental stages (days 10.5 to 12.5) of optic fissure closure. Our new method provided greater biological specificity than classical clustering algorithms in terms of identifying more biological processes and functions related to eye development as defined by Gene Ontology at lower false discovery rates. This new methodology builds on the advantages of LCM to isolate pure phenotypic populations within complex tissues and allows improved ability to identify critical gene products expressed at lower copy number. The combination of LCM of embryonic organs, gene expression microarrays, and extracting spatial and temporal co-variations appear to be a powerful approach to understanding the gene regulatory networks that specify mammalian organogenesis.

Tissue-specific mRNA expression profiling in grape berry tissues

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Grimplet, Jerome; Deluc, Laurent G; Tillett, Richard L; Wheatley, Matthew D; Schlauch, Karen A; Cramer, Grant R; Cushman, John C

2007-01-01

Background Berries of grape (Vitis vinifera) contain three major tissue types (skin, pulp and seed) all of which contribute to the aroma, color, and flavor characters of wine. The pericarp, which is composed of the exocarp (skin) and mesocarp (pulp), not only functions to protect and feed the developing seed, but also to assist in the dispersal of the mature seed by avian and mammalian vectors. The skin provides volatile and nonvolatile aroma and color compounds, the pulp contributes organic acids and sugars, and the seeds provide condensed tannins, all of which are important to the formation of organoleptic characteristics of wine. In order to understand the transcriptional network responsible for controlling tissue-specific mRNA expression patterns, mRNA expression profiling was conducted on each tissue of mature berries of V. vinifera Cabernet Sauvignon using the Affymetrix GeneChip® Vitis oligonucleotide microarray ver. 1.0. In order to monitor the influence of water-deficit stress on tissue-specific expression patterns, mRNA expression profiles were also compared from mature berries harvested from vines subjected to well-watered or water-deficit conditions. Results Overall, berry tissues were found to express approximately 76% of genes represented on the Vitis microarray. Approximately 60% of these genes exhibited significant differential expression in one or more of the three major tissue types with more than 28% of genes showing pronounced (2-fold or greater) differences in mRNA expression. The largest difference in tissue-specific expression was observed between the seed and pulp/skin. Exocarp tissue, which is involved in pathogen defense and pigment production, showed higher mRNA abundance relative to other berry tissues for genes involved with flavonoid biosynthesis, pathogen resistance, and cell wall modification. Mesocarp tissue, which is considered a nutritive tissue, exhibited a higher mRNA abundance of genes involved in cell wall function and

Tissue-specific mRNA expression profiling in grape berry tissues

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Cramer Grant R

2007-06-01

Full Text Available Abstract Background Berries of grape (Vitis vinifera contain three major tissue types (skin, pulp and seed all of which contribute to the aroma, color, and flavor characters of wine. The pericarp, which is composed of the exocarp (skin and mesocarp (pulp, not only functions to protect and feed the developing seed, but also to assist in the dispersal of the mature seed by avian and mammalian vectors. The skin provides volatile and nonvolatile aroma and color compounds, the pulp contributes organic acids and sugars, and the seeds provide condensed tannins, all of which are important to the formation of organoleptic characteristics of wine. In order to understand the transcriptional network responsible for controlling tissue-specific mRNA expression patterns, mRNA expression profiling was conducted on each tissue of mature berries of V. vinifera Cabernet Sauvignon using the Affymetrix GeneChip® Vitis oligonucleotide microarray ver. 1.0. In order to monitor the influence of water-deficit stress on tissue-specific expression patterns, mRNA expression profiles were also compared from mature berries harvested from vines subjected to well-watered or water-deficit conditions. Results Overall, berry tissues were found to express approximately 76% of genes represented on the Vitis microarray. Approximately 60% of these genes exhibited significant differential expression in one or more of the three major tissue types with more than 28% of genes showing pronounced (2-fold or greater differences in mRNA expression. The largest difference in tissue-specific expression was observed between the seed and pulp/skin. Exocarp tissue, which is involved in pathogen defense and pigment production, showed higher mRNA abundance relative to other berry tissues for genes involved with flavonoid biosynthesis, pathogen resistance, and cell wall modification. Mesocarp tissue, which is considered a nutritive tissue, exhibited a higher mRNA abundance of genes involved in cell

An Overview of DNA Microarray Grid Alignment and Foreground Separation Approaches

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Bajcsy Peter

2006-01-01

Full Text Available This paper overviews DNA microarray grid alignment and foreground separation approaches. Microarray grid alignment and foreground separation are the basic processing steps of DNA microarray images that affect the quality of gene expression information, and hence impact our confidence in any data-derived biological conclusions. Thus, understanding microarray data processing steps becomes critical for performing optimal microarray data analysis. In the past, the grid alignment and foreground separation steps have not been covered extensively in the survey literature. We present several classifications of existing algorithms, and describe the fundamental principles of these algorithms. Challenges related to automation and reliability of processed image data are outlined at the end of this overview paper.

Development, characterization and experimental validation of a cultivated sunflower (Helianthus annuus L. gene expression oligonucleotide microarray.

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Paula Fernandez

Full Text Available Oligonucleotide-based microarrays with accurate gene coverage represent a key strategy for transcriptional studies in orphan species such as sunflower, H. annuus L., which lacks full genome sequences. The goal of this study was the development and functional annotation of a comprehensive sunflower unigene collection and the design and validation of a custom sunflower oligonucleotide-based microarray. A large scale EST (>130,000 ESTs curation, assembly and sequence annotation was performed using Blast2GO (www.blast2go.de. The EST assembly comprises 41,013 putative transcripts (12,924 contigs and 28,089 singletons. The resulting Sunflower Unigen Resource (SUR version 1.0 was used to design an oligonucleotide-based Agilent microarray for cultivated sunflower. This microarray includes a total of 42,326 features: 1,417 Agilent controls, 74 control probes for sunflower replicated 10 times (740 controls and 40,169 different non-control probes. Microarray performance was validated using a model experiment examining the induction of senescence by water deficit. Pre-processing and differential expression analysis of Agilent microarrays was performed using the Bioconductor limma package. The analyses based on p-values calculated by eBayes (p<0.01 allowed the detection of 558 differentially expressed genes between water stress and control conditions; from these, ten genes were further validated by qPCR. Over-represented ontologies were identified using FatiScan in the Babelomics suite. This work generated a curated and trustable sunflower unigene collection, and a custom, validated sunflower oligonucleotide-based microarray using Agilent technology. Both the curated unigene collection and the validated oligonucleotide microarray provide key resources for sunflower genome analysis, transcriptional studies, and molecular breeding for crop improvement.

Patterns of gene expression in carp liver after exposure to a mixture of waterborne and dietary cadmium using a custom-made microarray

International Nuclear Information System (INIS)

Reynders, Hans; Ven, Karlijn van der; Moens, Lotte N.; Remortel, Piet van; De Coen, Wim M.; Blust, Ronny

2006-01-01

Gene expression changes in carp liver tissue were studied after acute (3 and 24 h) and subchronic (7 and 28 days) exposure to a mixture of waterborne (9, 105 and 480 μg/l) and dietary (9.5, 122 and 144 μg/g) cadmium, using a custom-made microarray. Suppression subtractive hybridization-PCR (SSH-PCR) was applied to isolate a set of 643 liver genes, involved in multiple biological pathways, such as energy metabolism (e.g. glucokinase), immune response (e.g. complement C3) and stress and detoxification (e.g. cytochrome P450 2F2, glutathione-S-transferase pi). These genes were subsequently spotted on glass-slides for the construction of a custom-made microarray. Resulting microarray hybridizations indicated a highly dynamic response to cadmium exposure. At low exposure concentrations (9 μg/l through water and 9.5 μg/g dry weight through food) mostly energy-related genes (e.g. glucokinase, elastase) were influenced, while a general stress response was obvious through induction of several stress-related genes, including hemopexin and cytochrome P450 2F2, at high cadmium concentrations. In addition, fish exposed to the highest cadmium concentrations showed liver damage after 7 days of exposure, as measured by elevated alanine transaminase activity in plasma and increased liver water content (wet-to-dry weight ratio). Moreover, decreased hematocrit and growth were found at the end of the experiment. Altogether this study clearly demonstrated the importance of varying exposure conditions for the characterization of the molecular impact of cadmium and showed that microarray results can provide important information, required to unravel the molecular events and responses related to cadmium exposure

Seeded Bayesian Networks: Constructing genetic networks from microarray data

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Quackenbush John

2008-07-01

Full Text Available Abstract Background DNA microarrays and other genomics-inspired technologies provide large datasets that often include hidden patterns of correlation between genes reflecting the complex processes that underlie cellular metabolism and physiology. The challenge in analyzing large-scale expression data has been to extract biologically meaningful inferences regarding these processes – often represented as networks – in an environment where the datasets are often imperfect and biological noise can obscure the actual signal. Although many techniques have been developed in an attempt to address these issues, to date their ability to extract meaningful and predictive network relationships has been limited. Here we describe a method that draws on prior information about gene-gene interactions to infer biologically relevant pathways from microarray data. Our approach consists of using preliminary networks derived from the literature and/or protein-protein interaction data as seeds for a Bayesian network analysis of microarray results. Results Through a bootstrap analysis of gene expression data derived from a number of leukemia studies, we demonstrate that seeded Bayesian Networks have the ability to identify high-confidence gene-gene interactions which can then be validated by comparison to other sources of pathway data. Conclusion The use of network seeds greatly improves the ability of Bayesian Network analysis to learn gene interaction networks from gene expression data. We demonstrate that the use of seeds derived from the biomedical literature or high-throughput protein-protein interaction data, or the combination, provides improvement over a standard Bayesian Network analysis, allowing networks involving dynamic processes to be deduced from the static snapshots of biological systems that represent the most common source of microarray data. Software implementing these methods has been included in the widely used TM4 microarray analysis package.

Comparison of in situ hybridization methods for the assessment of HER-2/neu gene amplification status in breast cancer using a tissue microarray.

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Malicka-Durczak, Anna; Korski, Konstanty; Ibbs, Matthew

2012-01-01

This project compared HER-2/neu gene status in breast cancers, as demonstrated by FISH (fluorescent in situ hybridization) and CISH (chromogenic in situ hybridization) and using a tissue microarray (TMA). The study also aimed to show whether the TMA technique could be used in clinical diagnostics, rather than remain a scientific tool. A TMA was constructed using 121 breast cancer specimens, 6 cores from each specimen. Demonstration and assessment of HER-2/neu gene status was by FISH (Vysis Path) and CISH (DAKO Duo CISH). The 121 breast cancer specimens were divided into 3 groups by HER-2 status, as determined by immunohistochemistry. In the HER-2 negative group no amplification was observed in 36 out of 40 cases. 3 cases showed amplification by both methods and one by CISH alone. The equivocal HER-2 group showed no amplification in 30 out of 41 cases and amplification in 9 cases. One case was FISH negative CISH positive and one was discarded. In the HER-2 positive group, amplification was confirmed in 37 of the 40 cases by both methods. 3 cases were unsuitable for assessment. This study indicated that CISH is a sensitive alternative to FISH in detecting HER2 gene amplification and may replace FISH in HER2 testing. Good agreement was observed between methods (98.5% - 119 out of 121 cases). Furthermore, as only 4 out of 121 cases were unsuitable for assessment (no signal or missing TMA cores) - it may be feasible to use TMA in diagnostics.

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

International Nuclear Information System (INIS)

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

2004-01-01

DNA microarray profiling performed on clinical tissue specimens can potentially provide significant information regarding human cancer biology. Biopsy cores, the typical source of human tumor tissue, however, generally provide very small amounts of RNA (0.3–15 μg). RNA amplification is a common method used to increase the amount of material available for hybridization experiments. Using human xenograft tissue, we sought to address the following three questions: 1) is amplified RNA representative of the original RNA profile? 2) what is the minimum amount of total RNA required to perform a representative amplification? 3) are the direct and indirect methods of labeling the hybridization probe equivalent? Total RNA was extracted from human xenograft tissue and amplified using a linear amplification process. RNA was labeled and hybridized, and the resulting images yielded data that was extracted into two categories using the mAdb system: 'all genes' and 'outliers'. Scatter plots were generated for each slide and Pearson Coefficients of correlation were obtained. Results show that the amplification of 5 μg of total RNA yields a Pearson Correlation Coefficient of 0.752 (N = 6,987 genes) between the amplified and total RNA samples. We subsequently determined that amplification of 0.5 μg of total RNA generated a similar Pearson Correlation Coefficient as compared to the corresponding original RNA sample. Similarly, sixty-nine percent of total RNA outliers were detected with 5 μg of amplified starting RNA, and 55% of outliers were detected with 0.5 μg of starting RNA. However, amplification of 0.05 μg of starting RNA resulted in a loss of fidelity (Pearson Coefficient 0.669 between amplified and original samples, 44% outlier concordance). In these studies the direct or indirect methods of probe labeling yielded similar results. Finally, we examined whether RNA obtained from needle core biopsies of human tumor xenografts, amplified and indirectly

Synovial tissue heterogeneity in rheumatoid arthritis in relation to disease activity and biomarkers in peripheral blood

NARCIS (Netherlands)

van Baarsen, Lisa G. M.; Wijbrandts, Carla A.; Timmer, Trieneke C. G.; van der Pouw Kraan, Tineke C. T. M.; Tak, Paul P.; Verweij, Cornelis L.

2010-01-01

OBJECTIVE: To investigate the clinical relevance of synovial tissue subtypes in rheumatoid arthritis (RA) and to search for peripheral blood (PB) markers that may serve as biomarkers for tissue subtypes. METHODS: Gene expression analysis using complementary DNA microarrays was applied on paired

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

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Mo Qianxing

2009-12-01

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

Improvement in the amine glass platform by bubbling method for a DNA microarray.

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Jee, Seung Hyun; Kim, Jong Won; Lee, Ji Hyeong; Yoon, Young Soo

2015-01-01

A glass platform with high sensitivity for sexually transmitted diseases microarray is described here. An amino-silane-based self-assembled monolayer was coated on the surface of a glass platform using a novel bubbling method. The optimized surface of the glass platform had highly uniform surface modifications using this method, as well as improved hybridization properties with capture probes in the DNA microarray. On the basis of these results, the improved glass platform serves as a highly reliable and optimal material for the DNA microarray. Moreover, in this study, we demonstrated that our glass platform, manufactured by utilizing the bubbling method, had higher uniformity, shorter processing time, lower background signal, and higher spot signal than the platforms manufactured by the general dipping method. The DNA microarray manufactured with a glass platform prepared using bubbling method can be used as a clinical diagnostic tool.

Microarray Analysis of microRNA Expression during Axolotl Limb Regeneration

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Holman, Edna C.; Campbell, Leah J.; Hines, John; Crews, Craig M.

2012-01-01

Among vertebrates, salamanders stand out for their remarkable capacity to quickly regrow a myriad of tissues and organs after injury or amputation. The limb regeneration process in axolotls (Ambystoma mexicanum) has been well studied for decades at the cell-tissue level. While several developmental genes are known to be reactivated during this epimorphic process, less is known about the role of microRNAs in urodele amphibian limb regeneration. Given the compelling evidence that many microRNAs tightly regulate cell fate and morphogenetic processes through development and adulthood by modulating the expression (or re-expression) of developmental genes, we investigated the possibility that microRNA levels change during limb regeneration. Using two different microarray platforms to compare the axolotl microRNA expression between mid-bud limb regenerating blastemas and non-regenerating stump tissues, we found that miR-21 was overexpressed in mid-bud blastemas compared to stump tissue. Mature A. mexicanum (“Amex”) miR-21 was detected in axolotl RNA by Northern blot and differential expression of Amex-miR-21 in blastema versus stump was confirmed by quantitative RT-PCR. We identified the Amex Jagged1 as a putative target gene for miR-21 during salamander limb regeneration. We cloned the full length 3′UTR of Amex-Jag1, and our in vitro assays demonstrated that its single miR-21 target recognition site is functional and essential for the response of the Jagged1 gene to miR-21 levels. Our findings pave the road for advanced in vivo functional assays aimed to clarify how microRNAs such as miR-21, often linked to pathogenic cell growth, might be modulating the redeployment of developmental genes such as Jagged1 during regenerative processes. PMID:23028429

Microarray analysis of microRNA expression during axolotl limb regeneration.

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Edna C Holman

Full Text Available Among vertebrates, salamanders stand out for their remarkable capacity to quickly regrow a myriad of tissues and organs after injury or amputation. The limb regeneration process in axolotls (Ambystoma mexicanum has been well studied for decades at the cell-tissue level. While several developmental genes are known to be reactivated during this epimorphic process, less is known about the role of microRNAs in urodele amphibian limb regeneration. Given the compelling evidence that many microRNAs tightly regulate cell fate and morphogenetic processes through development and adulthood by modulating the expression (or re-expression of developmental genes, we investigated the possibility that microRNA levels change during limb regeneration. Using two different microarray platforms to compare the axolotl microRNA expression between mid-bud limb regenerating blastemas and non-regenerating stump tissues, we found that miR-21 was overexpressed in mid-bud blastemas compared to stump tissue. Mature A. mexicanum ("Amex" miR-21 was detected in axolotl RNA by Northern blot and differential expression of Amex-miR-21 in blastema versus stump was confirmed by quantitative RT-PCR. We identified the Amex Jagged1 as a putative target gene for miR-21 during salamander limb regeneration. We cloned the full length 3'UTR of Amex-Jag1, and our in vitro assays demonstrated that its single miR-21 target recognition site is functional and essential for the response of the Jagged1 gene to miR-21 levels. Our findings pave the road for advanced in vivo functional assays aimed to clarify how microRNAs such as miR-21, often linked to pathogenic cell growth, might be modulating the redeployment of developmental genes such as Jagged1 during regenerative processes.

Layered signaling regulatory networks analysis of gene expression involved in malignant tumorigenesis of non-resolving ulcerative colitis via integration of cross-study microarray profiles.

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Fan, Shengjun; Pan, Zhenyu; Geng, Qiang; Li, Xin; Wang, Yefan; An, Yu; Xu, Yan; Tie, Lu; Pan, Yan; Li, Xuejun

2013-01-01

Ulcerative colitis (UC) was the most frequently diagnosed inflammatory bowel disease (IBD) and closely linked to colorectal carcinogenesis. By far, the underlying mechanisms associated with the disease are still unclear. With the increasing accumulation of microarray gene expression profiles, it is profitable to gain a systematic perspective based on gene regulatory networks to better elucidate the roles of genes associated with disorders. However, a major challenge for microarray data analysis is the integration of multiple-studies generated by different groups. In this study, firstly, we modeled a signaling regulatory network associated with colorectal cancer (CRC) initiation via integration of cross-study microarray expression data sets using Empirical Bayes (EB) algorithm. Secondly, a manually curated human cancer signaling map was established via comprehensive retrieval of the publicly available repositories. Finally, the co-differently-expressed genes were manually curated to portray the layered signaling regulatory networks. Overall, the remodeled signaling regulatory networks were separated into four major layers including extracellular, membrane, cytoplasm and nucleus, which led to the identification of five core biological processes and four signaling pathways associated with colorectal carcinogenesis. As a result, our biological interpretation highlighted the importance of EGF/EGFR signaling pathway, EPO signaling pathway, T cell signal transduction and members of the BCR signaling pathway, which were responsible for the malignant transition of CRC from the benign UC to the aggressive one. The present study illustrated a standardized normalization approach for cross-study microarray expression data sets. Our model for signaling networks construction was based on the experimentally-supported interaction and microarray co-expression modeling. Pathway-based signaling regulatory networks analysis sketched a directive insight into colorectal carcinogenesis

Assessing the Clinical Utility of SNP Microarray for Prader-Willi Syndrome due to Uniparental Disomy.

Science.gov (United States)

Santoro, Stephanie L; Hashimoto, Sayaka; McKinney, Aimee; Mihalic Mosher, Theresa; Pyatt, Robert; Reshmi, Shalini C; Astbury, Caroline; Hickey, Scott E

2017-01-01

Maternal uniparental disomy (UPD) 15 is one of the molecular causes of Prader-Willi syndrome (PWS), a multisystem disorder which presents with neonatal hypotonia and feeding difficulty. Current diagnostic algorithms differ regarding the use of SNP microarray to detect PWS. We retrospectively examined the frequency with which SNP microarray could identify regions of homozygosity (ROH) in patients with PWS. We determined that 7/12 (58%) patients with previously confirmed PWS by methylation analysis and microsatellite-positive UPD studies had ROH (>10 Mb) by SNP microarray. Additional assessment of 5,000 clinical microarrays, performed from 2013 to present, determined that only a single case of ROH for chromosome 15 was not caused by an imprinting disorder or identity by descent. We observed that ROH for chromosome 15 is rarely incidental and strongly associated with hypotonic infants having features of PWS. Although UPD microsatellite studies remain essential to definitively establish the presence of UPD, SNP microarray has important utility in the timely diagnostic algorithm for PWS. © 2017 S. Karger AG, Basel.

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

DEFF Research Database (Denmark)

Skov, Vibe

2007-01-01

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

DNA Microarray Technologies: A Novel Approach to Geonomic Research

Energy Technology Data Exchange (ETDEWEB)

Hinman, R.; Thrall, B.; Wong, K,

2002-01-01

A cDNA microarray allows biologists to examine the expression of thousands of genes simultaneously. Researchers may analyze the complete transcriptional program of an organism in response to specific physiological or developmental conditions. By design, a cDNA microarray is an experiment with many variables and few controls. One question that inevitably arises when working with a cDNA microarray is data reproducibility. How easy is it to confirm mRNA expression patterns? In this paper, a case study involving the treatment of a murine macrophage RAW 264.7 cell line with tumor necrosis factor alpha (TNF) was used to obtain a rough estimate of data reproducibility. Two trials were examined and a list of genes displaying either a > 2-fold or > 4-fold increase in gene expression was compiled. Variations in signal mean ratios between the two slides were observed. We can assume that erring in reproducibility may be compensated by greater inductive levels of similar genes. Steps taken to obtain results included serum starvation of cells before treatment, tests of mRNA for quality/consistency, and data normalization.

Report on emerging technologies for translational bioinformatics: a symposium on gene expression profiling for archival tissues

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Waldron Levi

2012-03-01

Full Text Available Abstract Background With over 20 million formalin-fixed, paraffin-embedded (FFPE tissue samples archived each year in the United States alone, archival tissues remain a vast and under-utilized resource in the genomic study of cancer. Technologies have recently been introduced for whole-transcriptome amplification and microarray analysis of degraded mRNA fragments from FFPE samples, and studies of these platforms have only recently begun to enter the published literature. Results The Emerging Technologies for Translational Bioinformatics symposium on gene expression profiling for archival tissues featured presentations of two large-scale FFPE expression profiling studies (each involving over 1,000 samples, overviews of several smaller studies, and representatives from three leading companies in the field (Illumina, Affymetrix, and NuGEN. The meeting highlighted challenges in the analysis of expression data from archival tissues and strategies being developed to overcome them. In particular, speakers reported higher rates of clinical sample failure (from 10% to 70% than are typical for fresh-frozen tissues, as well as more frequent probe failure for individual samples. The symposium program is available at http://www.hsph.harvard.edu/ffpe. Conclusions Multiple solutions now exist for whole-genome expression profiling of FFPE tissues, including both microarray- and sequencing-based platforms. Several studies have reported their successful application, but substantial challenges and risks still exist. Symposium speakers presented novel methodology for analysis of FFPE expression data and suggestions for improving data recovery and quality assessment in pre-analytical stages. Research presentations emphasized the need for careful study design, including the use of pilot studies, replication, and randomization of samples among batches, as well as careful attention to data quality control. Regardless of any limitations in quantitave transcriptomics for

Microarray Expression Profile and Functional Analysis of Circular RNAs in Osteosarcoma

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Weihai Liu

2017-09-01

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

Dynamic, electronically switchable surfaces for membrane protein microarrays.

Science.gov (United States)

Tang, C S; Dusseiller, M; Makohliso, S; Heuschkel, M; Sharma, S; Keller, B; Vörös, J

2006-02-01

Microarray technology is a powerful tool that provides a high throughput of bioanalytical information within a single experiment. These miniaturized and parallelized binding assays are highly sensitive and have found widespread popularity especially during the genomic era. However, as drug diagnostics studies are often targeted at membrane proteins, the current arraying technologies are ill-equipped to handle the fragile nature of the protein molecules. In addition, to understand the complex structure and functions of proteins, different strategies to immobilize the probe molecules selectively onto a platform for protein microarray are required. We propose a novel approach to create a (membrane) protein microarray by using an indium tin oxide (ITO) microelectrode array with an electronic multiplexing capability. A polycationic, protein- and vesicle-resistant copolymer, poly(l-lysine)-grafted-poly(ethylene glycol) (PLL-g-PEG), is exposed to and adsorbed uniformly onto the microelectrode array, as a passivating adlayer. An electronic stimulation is then applied onto the individual ITO microelectrodes resulting in the localized release of the polymer thus revealing a bare ITO surface. Different polymer and biological moieties are specifically immobilized onto the activated ITO microelectrodes while the other regions remain protein-resistant as they are unaffected by the induced electrical potential. The desorption process of the PLL-g-PEG is observed to be highly selective, rapid, and reversible without compromising on the integrity and performance of the conductive ITO microelectrodes. As such, we have successfully created a stable and heterogeneous microarray of biomolecules by using selective electronic addressing on ITO microelectrodes. Both pharmaceutical diagnostics and biomedical technology are expected to benefit directly from this unique method.

Significance analysis of lexical bias in microarray data

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Falkow Stanley

2003-04-01

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

On the classification techniques in data mining for microarray data classification

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Aydadenta, Husna; Adiwijaya

2018-03-01

Cancer is one of the deadly diseases, according to data from WHO by 2015 there are 8.8 million more deaths caused by cancer, and this will increase every year if not resolved earlier. Microarray data has become one of the most popular cancer-identification studies in the field of health, since microarray data can be used to look at levels of gene expression in certain cell samples that serve to analyze thousands of genes simultaneously. By using data mining technique, we can classify the sample of microarray data thus it can be identified with cancer or not. In this paper we will discuss some research using some data mining techniques using microarray data, such as Support Vector Machine (SVM), Artificial Neural Network (ANN), Naive Bayes, k-Nearest Neighbor (kNN), and C4.5, and simulation of Random Forest algorithm with technique of reduction dimension using Relief. The result of this paper show performance measure (accuracy) from classification algorithm (SVM, ANN, Naive Bayes, kNN, C4.5, and Random Forets).The results in this paper show the accuracy of Random Forest algorithm higher than other classification algorithms (Support Vector Machine (SVM), Artificial Neural Network (ANN), Naive Bayes, k-Nearest Neighbor (kNN), and C4.5). It is hoped that this paper can provide some information about the speed, accuracy, performance and computational cost generated from each Data Mining Classification Technique based on microarray data.

Position dependent mismatch discrimination on DNA microarrays – experiments and model

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Michel Wolfgang

2008-12-01

Full Text Available Abstract Background The propensity of oligonucleotide strands to form stable duplexes with complementary sequences is fundamental to a variety of biological and biotechnological processes as various as microRNA signalling, microarray hybridization and PCR. Yet our understanding of oligonucleotide hybridization, in particular in presence of surfaces, is rather limited. Here we use oligonucleotide microarrays made in-house by optically controlled DNA synthesis to produce probe sets comprising all possible single base mismatches and base bulges for each of 20 sequence motifs under study. Results We observe that mismatch discrimination is mostly determined by the defect position (relative to the duplex ends as well as by the sequence context. We investigate the thermodynamics of the oligonucleotide duplexes on the basis of double-ended molecular zipper. Theoretical predictions of defect positional influence as well as long range sequence influence agree well with the experimental results. Conclusion Molecular zipping at thermodynamic equilibrium explains the binding affinity of mismatched DNA duplexes on microarrays well. The position dependent nearest neighbor model (PDNN can be inferred from it. Quantitative understanding of microarray experiments from first principles is in reach.

Genetic response in masseter muscle after orthognathic surgery in comparison with healthy controls - A Microarray study.

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Marewski, Maya; Petto, Carola; Schneider, Matthias; Harzer, Winfried

2017-04-01

One third of adult patients with orthognathic surgery of a prognathic or retrognathic mandible show relapse. The sagittal split osteotomy of the mandible leads to a displacement of both parts up to 10 mm without any changes of muscle attachment. Changed mandible length needs adaptation of muscle capacity because of changed force to moment ratio. The aim of this Microarray study was to analyze the general genetic response of masseter muscle in patients with retrognathism or prognathism of the mandible six months after surgery in comparison with healthy untreated controls. We found in tissue samples from masseter muscle a reduction of different entities between patients and controls but less in retrognathic than in prognathic patients (274/429). The different entities to controls in prognathia were reduced from 1862 to 1749 but increased in retrognathia from 1070 to 1563. We have to consider that the total amount of different entities to the controls is higher in patients with prognathic mandible (7364) because of their strong genetic controlled development compared with that in patients with retrognathic mandible (4126), which is more environmentally influenced. It can be concluded that function follows form after surgical change with high inheritance. In retrognathic patients the adaptation could be delayed or the capacity of regeneration potential is not sufficient. Copyright © 2017 European Association for Cranio-Maxillo-Facial Surgery. Published by Elsevier Ltd. All rights reserved.

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

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Brazma Alvis

2010-03-01

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

Versatile High Resolution Oligosaccharide Microarrays for Plant Glycobiology and Cell Wall Research

DEFF Research Database (Denmark)

Pedersen, Henriette Lodberg; Fangel, Jonatan Ulrik; McCleary, Barry

2012-01-01

Microarrays are powerful tools for high throughput analysis, and hundreds or thousands of molecular interactions can be assessed simultaneously using very small amounts of analytes. Nucleotide microarrays are well established in plant research, but carbohydrate microarrays are much less establish...

Universal ligation-detection-reaction microarray applied for compost microbes

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Romantschuk Martin

2008-12-01

Full Text Available Abstract Background Composting is one of the methods utilised in recycling organic communal waste. The composting process is dependent on aerobic microbial activity and proceeds through a succession of different phases each dominated by certain microorganisms. In this study, a ligation-detection-reaction (LDR based microarray method was adapted for species-level detection of compost microbes characteristic of each stage of the composting process. LDR utilises the specificity of the ligase enzyme to covalently join two adjacently hybridised probes. A zip-oligo is attached to the 3'-end of one probe and fluorescent label to the 5'-end of the other probe. Upon ligation, the probes are combined in the same molecule and can be detected in a specific location on a universal microarray with complementary zip-oligos enabling equivalent hybridisation conditions for all probes. The method was applied to samples from Nordic composting facilities after testing and optimisation with fungal pure cultures and environmental clones. Results Probes targeted for fungi were able to detect 0.1 fmol of target ribosomal PCR product in an artificial reaction mixture containing 100 ng competing fungal ribosomal internal transcribed spacer (ITS area or herring sperm DNA. The detection level was therefore approximately 0.04% of total DNA. Clone libraries were constructed from eight compost samples. The LDR microarray results were in concordance with the clone library sequencing results. In addition a control probe was used to monitor the per-spot hybridisation efficiency on the array. Conclusion This study demonstrates that the LDR microarray method is capable of sensitive and accurate species-level detection from a complex microbial community. The method can detect key species from compost samples, making it a basis for a tool for compost process monitoring in industrial facilities.

Nanomedicine, microarrays and their applications in clinical microbiology

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Özcan Deveci

2010-12-01

Full Text Available Growing interest in the future medical applications of nanotechnology is leading to the emergence of a new scientific field that called as “nanomedicine”. Nanomedicine may be defined as the investigating, treating, reconstructing and controlling human biology and health at the molecular level, using engineered nanodevices and nanostructures. Microarray technology is a revolutionary tool for elucidating roles of genes in infectious diseases, shifting from traditional methods of research to integrated approaches. This technology has great potential to provide medical diagnosis, monitor treatment and help in the development of new tools for infectious disease prevention and/or management. The aim of this paper is to provide an overview of the current application of microarray platforms and nanomedicine in the study of experimental microbiology and the impact of this technology in clinical settings.

Multiplex RT-PCR and Automated Microarray for Detection of Eight Bovine Viruses.

Science.gov (United States)

Lung, O; Furukawa-Stoffer, T; Burton Hughes, K; Pasick, J; King, D P; Hodko, D

2017-12-01

Microarrays can be a useful tool for pathogen detection as it allow for simultaneous interrogation of the presence of a large number of genetic sequences in a sample. However, conventional microarrays require extensive manual handling and multiple pieces of equipment for printing probes, hybridization, washing and signal detection. In this study, a reverse transcription (RT)-PCR with an accompanying novel automated microarray for simultaneous detection of eight viruses that affect cattle [vesicular stomatitis virus (VSV), bovine viral diarrhoea virus type 1 and type 2, bovine herpesvirus 1, bluetongue virus, malignant catarrhal fever virus, rinderpest virus (RPV) and parapox viruses] is described. The assay accurately identified a panel of 37 strains of the target viruses and identified a mixed infection. No non-specific reactions were observed with a panel of 23 non-target viruses associated with livestock. Vesicular stomatitis virus was detected as early as 2 days post-inoculation in oral swabs from experimentally infected animals. The limit of detection of the microarray assay was as low as 1 TCID 50 /ml for RPV. The novel microarray platform automates the entire post-PCR steps of the assay and integrates electrophoretic-driven capture probe printing in a single user-friendly instrument that allows array layout and assay configuration to be user-customized on-site. © 2016 Her Majesty the Queen in Right of Canada.

A cDNA microarray, UniShrimpChip, for identification of genes relevant to testicular development in the black tiger shrimp (Penaeus monodon

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Klinbunga Sirawut

2011-04-01

Full Text Available Abstract Background Poor reproductive maturation in captive male broodstock of the black tiger shrimp (Penaeus monodon is one of the serious problems to the farming industries. Without genome sequence, EST libraries of P. monodon were previously constructed to identify transcripts with important biological functions. In this study, a new version of cDNA microarray, UniShrimpChip, was constructed from the Peneaus monodon EST libraries of 12 tissues, containing 5,568 non-redundant cDNA clones from 10,536 unique cDNA in the P. monodon EST database. UniShrimpChip was used to study testicular development by comparing gene expression levels of wild brooders from the West and East coasts of Thailand and domesticated brooders with different ages (10-, 14-, 18-month-old. Results The overall gene expression patterns from the microarray experiments revealed distinct transcriptomic patterns between the wild and domesticated groups. Moreover, differentially expressed genes from the microarray comparisons were identified, and the expression patterns of eight selected transcripts were subsequently confirmed by reverse-transcriptase quantitative PCR (RT-qPCR. Among these, expression levels of six subunits (CSN2, 4, 5, 6, 7a, and 8 of the COP9 signalosome (CSN gene family in wild and different ages of domesticated brooders were examined by RT-qPCR. Among the six subunits, CSN5 and CSN6 were most highly expressed in wild brooders and least expressed in the 18-month-old domesticated group; therefore, their full-length cDNA sequences were characterized. Conclusions This study is the first report to employ cDNA microarray to study testicular development in the black tiger shrimp. We show that there are obvious differences between the wild and domesticated shrimp at the transcriptomic level. Furthermore, our study is the first to investigate the feasibility that the CSN gene family might have involved in reproduction and development of this economically important

SCK-CEN Genomic Platform: the microarray technology

International Nuclear Information System (INIS)

Benotmane, R.

2006-01-01

The human body contains approximately 10 14 cells, wherein each one is a nucleus. The nucleus contains 2x23 chromosomes, or two complete sets of the human genome, one set coming from the mother and the other from the father. In principle each set includes 30.000-40.000 genes. If the genome was a book, it would be twenty-three chapters, called chromosomes,each chapter with several thousand stories, called genes. Each story made up of paragraphs, called exons and introns. Each paragraph made up of 3 letter words, called codons. Each word is written with letters called bases (AGCT). But the whole is written in a single very long sentence, which is the DNA molecule or deoxy nucleic acid. The usual state of DNA is two complementary strands intertwined forming a double helix. In the cell, DNA is duplicated during each cell division to ensure the transmission of the genome to the daughter cells. For expression, the DNA is transcribed to messenger RNA. The RNA is edited and finally translated to a protein, each three bases coding for one amino acid. When the whole message is translated, the chain of amino acids folds itself up into a distinctive shape that depends on its sequence. Proteins are the effectors of the genes, and are responsible for all metabolic, hormonal and enzymatic reactions in the cells. The expressed RNA determines the amount of proteins to be produced and subsequently the desired effect (strong or weak) in the cell. The microarray technology aims at quantifying the amount of RNA present in the cell from each expressed gene, and at evaluating the changes of these amounts after exposure of the cell to toxic chemicals, ionising radiation or other stress components. The global picture of expressed genes helps to understand the affected genetic pathways in the cell at the molecular level. The microarray technology is used in the Radiobiology and Microbiology topics to study the effect of ionising radiation on human cells and mouse tissue, as well as the

Microarrays for Universal Detection and Identification of Phytoplasmas

DEFF Research Database (Denmark)

Nicolaisen, Mogens; Nyskjold, Henriette; Bertaccini, Assunta

2013-01-01

Detection and identification of phytoplasmas is a laborious process often involving nested PCR followed by restriction enzyme analysis and fine-resolution gel electrophoresis. To improve throughput, other methods are needed. Microarray technology offers a generic assay that can potentially detect...... and differentiate all types of phytoplasmas in one assay. The present protocol describes a microarray-based method for identification of phytoplasmas to 16Sr group level....

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

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Faisal Mohamed

2010-05-01

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

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

Science.gov (United States)

Xu, Wei; Faisal, Mohamed

2010-05-28

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

Parallel scan hyperspectral fluorescence imaging system and biomedical application for microarrays

International Nuclear Information System (INIS)

Liu Zhiyi; Ma Suihua; Liu Le; Guo Jihua; He Yonghong; Ji Yanhong

2011-01-01

Microarray research offers great potential for analysis of gene expression profile and leads to greatly improved experimental throughput. A number of instruments have been reported for microarray detection, such as chemiluminescence, surface plasmon resonance, and fluorescence markers. Fluorescence imaging is popular for the readout of microarrays. In this paper we develop a quasi-confocal, multichannel parallel scan hyperspectral fluorescence imaging system for microarray research. Hyperspectral imaging records the entire emission spectrum for every voxel within the imaged area in contrast to recording only fluorescence intensities of filter-based scanners. Coupled with data analysis, the recorded spectral information allows for quantitative identification of the contributions of multiple, spectrally overlapping fluorescent dyes and elimination of unwanted artifacts. The mechanism of quasi-confocal imaging provides a high signal-to-noise ratio, and parallel scan makes this approach a high throughput technique for microarray analysis. This system is improved with a specifically designed spectrometer which can offer a spectral resolution of 0.2 nm, and operates with spatial resolutions ranging from 2 to 30 μm . Finally, the application of the system is demonstrated by reading out microarrays for identification of bacteria.

[Study of generational risk in deafness inflicted couples using deafness gene microarray technique].

Science.gov (United States)

Wang, Ping; Zhao, Jia; Yu, Shu-yuan; Jin, Peng; Zhu, Wei; DU, Bo

2011-06-01

To explored the significance of screening the gene mutations of deafness related in deaf-mute (deaf & dumb) family using DNA microarray. Total of 52 couples of deaf-mute were recruited from Changchun deaf-mute community. With an average age of (58.3 ± 6.7) years old (x(-) ± s). Blood samples were obtained with informed consent. Their genomic DNA was extracted from peripheral blood and PCR was performed. Nine of hot spot mutations in four most common deafness pathologic gene were examined with the DNA microarray, including GJB2, GJB3, PDS and mtDNA 12S rRNA genes. At the same time, the results were verified with the traditional methods of sequencing. Fifty of normal people served as a control group. All patients were diagnosed non-syndromic sensorineural hearing loss by subjective pure tone audiometry. Thirty-two of 104 cases appeared GJB2 gene mutation (30.7%), the mutation sites included 35delG, 176del16, 235delC and 299delAT. Eighteen of 32 cases of GJB2 mutations were 235delC (59.1%). Seven of 104 cases appeared SLC26A4 gene IVS7-2 A > G mutation. Questionnaire survey and gene diagnosis revealed that four of 52 families have deaf offspring (7.6%). When a couple carries the same gene mutation, the risk of their children deafness was 100%. The results were confirmed with the traditional methods of sequencing. There is a high risk of deafness if a deaf-mute family is planning to have a new baby. It is very important and helpful to avoid deaf newborns again in deaf-mute family by DNA microarray.

The PowerAtlas: a power and sample size atlas for microarray experimental design and research

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Wang Jelai

2006-02-01

Full Text Available Abstract Background Microarrays permit biologists to simultaneously measure the mRNA abundance of thousands of genes. An important issue facing investigators planning microarray experiments is how to estimate the sample size required for good statistical power. What is the projected sample size or number of replicate chips needed to address the multiple hypotheses with acceptable accuracy? Statistical methods exist for calculating power based upon a single hypothesis, using estimates of the variability in data from pilot studies. There is, however, a need for methods to estimate power and/or required sample sizes in situations where multiple hypotheses are being tested, such as in microarray experiments. In addition, investigators frequently do not have pilot data to estimate the sample sizes required for microarray studies. Results To address this challenge, we have developed a Microrarray PowerAtlas 1. The atlas enables estimation of statistical power by allowing investigators to appropriately plan studies by building upon previous studies that have similar experimental characteristics. Currently, there are sample sizes and power estimates based on 632 experiments from Gene Expression Omnibus (GEO. The PowerAtlas also permits investigators to upload their own pilot data and derive power and sample size estimates from these data. This resource will be updated regularly with new datasets from GEO and other databases such as The Nottingham Arabidopsis Stock Center (NASC. Conclusion This resource provides a valuable tool for investigators who are planning efficient microarray studies and estimating required sample sizes.

DNA microarray technique for detecting food-borne pathogens

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Xing GAO

2012-08-01

Full Text Available Objective To study the application of DNA microarray technique for screening and identifying multiple food-borne pathogens. Methods The oligonucleotide probes were designed by Clustal X and Oligo 6.0 at the conserved regions of specific genes of multiple food-borne pathogens, and then were validated by bioinformatic analyses. The 5' end of each probe was modified by amino-group and 10 Poly-T, and the optimized probes were synthesized and spotted on aldehyde-coated slides. The bacteria DNA template incubated with Klenow enzyme was amplified by arbitrarily primed PCR, and PCR products incorporated into Aminoallyl-dUTP were coupled with fluorescent dye. After hybridization of the purified PCR products with DNA microarray, the hybridization image and fluorescence intensity analysis was acquired by ScanArray and GenePix Pro 5.1 software. A series of detection conditions such as arbitrarily primed PCR and microarray hybridization were optimized. The specificity of this approach was evaluated by 16 different bacteria DNA, and the sensitivity and reproducibility were verified by 4 food-borne pathogens DNA. The samples of multiple bacteria DNA and simulated water samples of Shigella dysenteriae were detected. Results Nine different food-borne bacteria were successfully discriminated under the same condition. The sensitivity of genomic DNA was 102 －103pg/ μl, and the coefficient of variation (CV of the reproducibility of assay was less than 15%. The corresponding specific hybridization maps of the multiple bacteria DNA samples were obtained, and the detection limit of simulated water sample of Shigella dysenteriae was 3.54×105cfu/ml. Conclusions The DNA microarray detection system based on arbitrarily primed PCR can be employed for effective detection of multiple food-borne pathogens, and this assay may offer a new method for high-throughput platform for detecting bacteria.

Microengineering methods for cell-based microarrays and high-throughput drug-screening applications

International Nuclear Information System (INIS)

Xu Feng; Wu Jinhui; Wang Shuqi; Gurkan, Umut Atakan; Demirci, Utkan; Durmus, Naside Gozde

2011-01-01

Screening for effective therapeutic agents from millions of drug candidates is costly, time consuming, and often faces concerns due to the extensive use of animals. To improve cost effectiveness, and to minimize animal testing in pharmaceutical research, in vitro monolayer cell microarrays with multiwell plate assays have been developed. Integration of cell microarrays with microfluidic systems has facilitated automated and controlled component loading, significantly reducing the consumption of the candidate compounds and the target cells. Even though these methods significantly increased the throughput compared to conventional in vitro testing systems and in vivo animal models, the cost associated with these platforms remains prohibitively high. Besides, there is a need for three-dimensional (3D) cell-based drug-screening models which can mimic the in vivo microenvironment and the functionality of the native tissues. Here, we present the state-of-the-art microengineering approaches that can be used to develop 3D cell-based drug-screening assays. We highlight the 3D in vitro cell culture systems with live cell-based arrays, microfluidic cell culture systems, and their application to high-throughput drug screening. We conclude that among the emerging microengineering approaches, bioprinting holds great potential to provide repeatable 3D cell-based constructs with high temporal, spatial control and versatility.

Microengineering methods for cell-based microarrays and high-throughput drug-screening applications

Energy Technology Data Exchange (ETDEWEB)

Xu Feng; Wu Jinhui; Wang Shuqi; Gurkan, Umut Atakan; Demirci, Utkan [Department of Medicine, Demirci Bio-Acoustic-MEMS in Medicine (BAMM) Laboratory, Center for Biomedical Engineering, Brigham and Women' s Hospital, Harvard Medical School, Boston, MA (United States); Durmus, Naside Gozde, E-mail: udemirci@rics.bwh.harvard.edu [School of Engineering and Division of Biology and Medicine, Brown University, Providence, RI (United States)

2011-09-15

Screening for effective therapeutic agents from millions of drug candidates is costly, time consuming, and often faces concerns due to the extensive use of animals. To improve cost effectiveness, and to minimize animal testing in pharmaceutical research, in vitro monolayer cell microarrays with multiwell plate assays have been developed. Integration of cell microarrays with microfluidic systems has facilitated automated and controlled component loading, significantly reducing the consumption of the candidate compounds and the target cells. Even though these methods significantly increased the throughput compared to conventional in vitro testing systems and in vivo animal models, the cost associated with these platforms remains prohibitively high. Besides, there is a need for three-dimensional (3D) cell-based drug-screening models which can mimic the in vivo microenvironment and the functionality of the native tissues. Here, we present the state-of-the-art microengineering approaches that can be used to develop 3D cell-based drug-screening assays. We highlight the 3D in vitro cell culture systems with live cell-based arrays, microfluidic cell culture systems, and their application to high-throughput drug screening. We conclude that among the emerging microengineering approaches, bioprinting holds great potential to provide repeatable 3D cell-based constructs with high temporal, spatial control and versatility.

High throughput screening of starch structures using carbohydrate microarrays

DEFF Research Database (Denmark)

Tanackovic, Vanja; Rydahl, Maja Gro; Pedersen, Henriette Lodberg

2016-01-01

In this study we introduce the starch-recognising carbohydrate binding module family 20 (CBM20) from Aspergillus niger for screening biological variations in starch molecular structure using high throughput carbohydrate microarray technology. Defined linear, branched and phosphorylated...

The efficacy of microarray screening for autosomal recessive retinitis pigmentosa in routine clinical practice

Science.gov (United States)

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

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

Science.gov (United States)

Zhang, Zhe; Fenstermacher, David

2005-01-01

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

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

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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.

Microarray analysis of gene expression profiles in ripening pineapple fruits.

Science.gov (United States)

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

2012-12-18

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

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

Science.gov (United States)

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

2008-08-25

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

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

Science.gov (United States)

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

2008-01-01

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

Phase II Study of Neoadjuvant Bevacizumab and Radiotherapy for Resectable Soft Tissue Sarcomas

International Nuclear Information System (INIS)

Yoon, Sam S.; Duda, Dan G.; Karl, Daniel L.; Kim, Tae-Min; Kambadakone, Avinash R.; Chen, Yen-Lin; Rothrock, Courtney; Rosenberg, Andrew E.; Nielsen, G. Petur; Kirsch, David G.; Choy, Edwin; Harmon, David C.; Hornicek, Francis J.; Dreyfuss, Jonathan; Ancukiewicz, Marek

2011-01-01

Purpose: Numerous preclinical studies have demonstrated that angiogenesis inhibitors can increase the efficacy of radiotherapy (RT). We sought to examine the safety and efficacy of bevacizumab (BV) and RT in soft tissue sarcomas and explore biomarkers to help determine the treatment response. Methods and Materials: Patients with ≥5 cm, intermediate- or high-grade soft tissue sarcomas at significant risk of local recurrence received neoadjuvant BV alone followed by BV plus RT before surgical resection. Correlative science studies included analysis of the serial blood and tumor samples and serial perfusion computed tomography scans. Results: The 20 patients had a median tumor size of 8.25 cm, with 13 extremity, 1 trunk, and 6 retroperitoneal/pelvis tumors. The neoadjuvant treatment was well tolerated, with only 4 patients having Grade 3 toxicities (hypertension, liver function test elevation). BV plus RT resulted in ≥80% pathologic necrosis in 9 (45%) of 20 tumors, more than double the historical rate seen with RT alone. Three patients had a complete pathologic response. The median microvessel density decreased 53% after BV alone (p <.05). After combination therapy, the median tumor cell proliferation decreased by 73%, apoptosis increased 10.4-fold, and the blood flow, blood volume, and permeability surface area decreased by 62–72% (p <.05). Analysis of gene expression microarrays of untreated tumors identified a 24-gene signature for treatment response. The microvessel density and circulating progenitor cells at baseline and the reduction in microvessel density and plasma soluble c-KIT with BV therapy also correlated with a good pathologic response (p <.05). After a median follow-up of 20 months, only 1 patient had developed local recurrence. Conclusions: The results from the present exploratory study indicated that BV increases the efficacy of RT against soft tissue sarcomas and might reduce the incidence of local recurrence. Thus, this regimen warrants

Improvement in the amine glass platform by bubbling method for a DNA microarray

Directory of Open Access Journals (Sweden)

Jee SH

2015-10-01

Full Text Available Seung Hyun Jee,1 Jong Won Kim,2 Ji Hyeong Lee,2 Young Soo Yoon11Department of Chemical and Biological Engineering, Gachon University, Seongnam, Gyeonggi, Republic of Korea; 2Genomics Clinical Research Institute, LabGenomics Co., Ltd., Bundang-gu, Seongnam-si, Gyeonggi-do, Republic of KoreaAbstract: A glass platform with high sensitivity for sexually transmitted diseases microarray is described here. An amino-silane-based self-assembled monolayer was coated on the surface of a glass platform using a novel bubbling method. The optimized surface of the glass platform had highly uniform surface modifications using this method, as well as improved hybridization properties with capture probes in the DNA microarray. On the basis of these results, the improved glass platform serves as a highly reliable and optimal material for the DNA microarray. Moreover, in this study, we demonstrated that our glass platform, manufactured by utilizing the bubbling method, had higher uniformity, shorter processing time, lower background signal, and higher spot signal than the platforms manufactured by the general dipping method. The DNA microarray manufactured with a glass platform prepared using bubbling method can be used as a clinical diagnostic tool. Keywords: DNA microarray, glass platform, bubbling method, self-assambled monolayer

A Fisheye Viewer for microarray-based gene expression data.

Science.gov (United States)

Wu, Min; Thao, Cheng; Mu, Xiangming; Munson, Ethan V

2006-10-13

Microarray has been widely used to measure the relative amounts of every mRNA transcript from the genome in a single scan. Biologists have been accustomed to reading their experimental data directly from tables. However, microarray data are quite large and are stored in a series of files in a machine-readable format, so direct reading of the full data set is not feasible. The challenge is to design a user interface that allows biologists to usefully view large tables of raw microarray-based gene expression data. This paper presents one such interface--an electronic table (E-table) that uses fisheye distortion technology. The Fisheye Viewer for microarray-based gene expression data has been successfully developed to view MIAME data stored in the MAGE-ML format. The viewer can be downloaded from the project web site http://polaris.imt.uwm.edu:7777/fisheye/. The fisheye viewer was implemented in Java so that it could run on multiple platforms. We implemented the E-table by adapting JTable, a default table implementation in the Java Swing user interface library. Fisheye views use variable magnification to balance magnification for easy viewing and compression for maximizing the amount of data on the screen. This Fisheye Viewer is a lightweight but useful tool for biologists to quickly overview the raw microarray-based gene expression data in an E-table.

Sensitivity and fidelity of DNA microarray improved with integration of Amplified Differential Gene Expression (ADGE

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Ile Kristina E

2003-07-01

Full Text Available Abstract Background The ADGE technique is a method designed to magnify the ratios of gene expression before detection. It improves the detection sensitivity to small change of gene expression and requires small amount of starting material. However, the throughput of ADGE is low. We integrated ADGE with DNA microarray (ADGE microarray and compared it with regular microarray. Results When ADGE was integrated with DNA microarray, a quantitative relationship of a power function between detected and input ratios was found. Because of ratio magnification, ADGE microarray was better able to detect small changes in gene expression in a drug resistant model cell line system. The PCR amplification of templates and efficient labeling reduced the requirement of starting material to as little as 125 ng of total RNA for one slide hybridization and enhanced the signal intensity. Integration of ratio magnification, template amplification and efficient labeling in ADGE microarray reduced artifacts in microarray data and improved detection fidelity. The results of ADGE microarray were less variable and more reproducible than those of regular microarray. A gene expression profile generated with ADGE microarray characterized the drug resistant phenotype, particularly with reference to glutathione, proliferation and kinase pathways. Conclusion ADGE microarray magnified the ratios of differential gene expression in a power function, improved the detection sensitivity and fidelity and reduced the requirement for starting material while maintaining high throughput. ADGE microarray generated a more informative expression pattern than regular microarray.

A microarray study of gene and protein regulation in human and rat brain following middle cerebral artery occlusion

Science.gov (United States)

Mitsios, Nick; Saka, Mohamad; Krupinski, Jerzy; Pennucci, Roberta; Sanfeliu, Coral; Wang, Qiuyu; Rubio, Francisco; Gaffney, John; Kumar, Pat; Kumar, Shant; Sullivan, Matthew; Slevin, Mark

2007-01-01

Background Altered gene expression is an important feature of ischemic cerebral injury and affects proteins of many functional classes. We have used microarrays to investigate the changes in gene expression at various times after middle cerebral artery occlusion in human and rat brain. Results Our results demonstrated a significant difference in the number of genes affected and the time-course of expression between the two cases. The total number of deregulated genes in the rat was 335 versus 126 in the human, while, of 393 overlapping genes between the two array sets, 184 were changed only in the rat and 36 in the human with a total of 41 genes deregulated in both cases. Interestingly, the mean fold changes were much higher in the human. The expression of novel genes, including p21-activated kinase 1 (PAK1), matrix metalloproteinase 11 (MMP11) and integrase interactor 1, was further analyzed by RT-PCR, Western blotting and immunohistochemistry. Strong neuronal staining was seen for PAK1 and MMP11. Conclusion Our findings confirmed previous studies reporting that gene expression screening can detect known and unknown transcriptional features of stroke and highlight the importance of research using human brain tissue in the search for novel therapeutic agents. PMID:17997827

Immunohistochemical expression study of proapoptotic BH3-only protein bad in canine nonneoplastic tissues and canine lymphomas.

Science.gov (United States)

Dettwiler, M; Croci, M; Vaughan, L; Guscetti, F

2013-09-01

The BH3-only protein Bad is a proapoptotic Bcl-2 family member that acts as a sensitizer in intrinsic apoptosis by inactivating antiapoptotic members through heterodimer formation. Bad has been shown to contribute to tumorigenesis, including lymphoma formation in humans and mice, through alteration in expression or functional status. Here, its immunohistochemical expression was analyzed in canine nonneoplastic and lymphoma tissues using tissue microarrays. Bad was expressed in the cytoplasm of a wide range of nonneoplastic tissues, especially epithelial cells. Nonneoplastic lymph nodes displayed weak immunostaining in the follicular germinal centers only. Immunoblotting supported these observations but also revealed presence of nonspecific labeling in some organs. Of 81 lymphomas, 29 (35.8%) displayed moderate to strong immunohistochemical Bad labeling, and a significant expression increase was found in lymphomas (especially B cell and double negative) compared to nonneoplastic lymph nodes. These findings warrant further investigations of the functional status, the involvement of partner proteins, and a possible impact of Bad on prognosis in canine lymphoma.

Adipose tissue transcriptome changes during obesity development in female dogs.

Science.gov (United States)

Grant, Ryan W; Vester Boler, Brittany M; Ridge, Tonya K; Graves, Thomas K; Swanson, Kelly S

2011-03-29

During the development of obesity, adipose tissue undergoes major expansion and remodeling, but the biological processes involved in this transition are not well understood. The objective of this study was to analyze global gene expression profiles of adipose tissue in dogs, fed a high-fat diet, during the transition from a lean to obese phenotype. Nine female beagles (4.09 ± 0.64 yr; 8.48 ± 0.35 kg) were randomized to ad libitum feeding or body weight maintenance. Subcutaneous adipose tissue biopsy, blood, and dual x-ray absorptiometry measurements were collected at 0, 4, 8, 12, and 24 wk of feeding. Serum was analyzed for glucose, insulin, fructosamine, triglycerides, free fatty acids, adiponectin, and leptin. Formalin-fixed adipose tissue was used for determination of adipocyte size. Adipose RNA samples were hybridized to Affymetrix Canine 2.0 microarrays. Statistical analysis, using repeated-measures ANOVA, showed ad libitum feeding increased (P obesity development.

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

Science.gov (United States)

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

2015-01-01

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

The unique genomic properties of sex-biased genes: Insights from avian microarray data

Directory of Open Access Journals (Sweden)

Webster Matthew T

2008-03-01

Full Text Available Abstract Background In order to develop a framework for the analysis of sex-biased genes, we present a characterization of microarray data comparing male and female gene expression in 18 day chicken embryos for brain, gonad, and heart tissue. Results From the 15982 significantly expressed coding regions that have been assigned to either the autosomes or the Z chromosome (12979 in brain, 13301 in gonad, and 12372 in heart, roughly 18% were significantly sex-biased in any one tissue, though only 4 gene targets were biased in all tissues. The gonad was the most sex-biased tissue, followed by the brain. Sex-biased autosomal genes tended to be expressed at lower levels and in fewer tissues than unbiased gene targets, and autosomal somatic sex-biased genes had more expression noise than similar unbiased genes. Sex-biased genes linked to the Z-chromosome showed reduced expression in females, but not in males, when compared to unbiased Z-linked genes, and sex-biased Z-linked genes were also expressed in fewer tissues than unbiased Z coding regions. Third position GC content, and codon usage bias showed some sex-biased effects, primarily for autosomal genes expressed in the gonad. Finally, there were several over-represented Gene Ontology terms in the sex-biased gene sets. Conclusion On the whole, this analysis suggests that sex-biased genes have unique genomic and organismal properties that delineate them from genes that are expressed equally in males and females.

Dimension reduction methods for microarray data: a review

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Rabia Aziz

2017-03-01

Full Text Available Dimension reduction has become inevitable for pre-processing of high dimensional data. “Gene expression microarray data” is an instance of such high dimensional data. Gene expression microarray data displays the maximum number of genes (features simultaneously at a molecular level with a very small number of samples. The copious numbers of genes are usually provided to a learning algorithm for producing a complete characterization of the classification task. However, most of the times the majority of the genes are irrelevant or redundant to the learning task. It will deteriorate the learning accuracy and training speed as well as lead to the problem of overfitting. Thus, dimension reduction of microarray data is a crucial preprocessing step for prediction and classification of disease. Various feature selection and feature extraction techniques have been proposed in the literature to identify the genes, that have direct impact on the various machine learning algorithms for classification and eliminate the remaining ones. This paper describes the taxonomy of dimension reduction methods with their characteristics, evaluation criteria, advantages and disadvantages. It also presents a review of numerous dimension reduction approaches for microarray data, mainly those methods that have been proposed over the past few years.

The 'PUCE CAFE' Project: the first 15K coffee microarray, a new tool for discovering candidate genes correlated to agronomic and quality traits.

Science.gov (United States)

Privat, Isabelle; Bardil, Amélie; Gomez, Aureliano Bombarely; Severac, Dany; Dantec, Christelle; Fuentes, Ivanna; Mueller, Lukas; Joët, Thierry; Pot, David; Foucrier, Séverine; Dussert, Stéphane; Leroy, Thierry; Journot, Laurent; de Kochko, Alexandre; Campa, Claudine; Combes, Marie-Christine; Lashermes, Philippe; Bertrand, Benoit

2011-01-05

Understanding the genetic elements that contribute to key aspects of coffee biology will have an impact on future agronomical improvements for this economically important tree. During the past years, EST collections were generated in Coffee, opening the possibility to create new tools for functional genomics. The "PUCE CAFE" Project, organized by the scientific consortium NESTLE/IRD/CIRAD, has developed an oligo-based microarray using 15,721 unigenes derived from published coffee EST sequences mostly obtained from different stages of fruit development and leaves in Coffea Canephora (Robusta). Hybridizations for two independent experiments served to compare global gene expression profiles in three types of tissue matter (mature beans, leaves and flowers) in C. canephora as well as in the leaves of three different coffee species (C. canephora, C. eugenoides and C. arabica). Microarray construction, statistical analyses and validation by Q-PCR analysis are presented in this study. We have generated the first 15 K coffee array during this PUCE CAFE project, granted by Génoplante (the French consortium for plant genomics). This new tool will help study functional genomics in a wide range of experiments on various plant tissues, such as analyzing bean maturation or resistance to pathogens or drought. Furthermore, the use of this array has proven to be valid in different coffee species (diploid or tetraploid), drastically enlarging its impact for high-throughput gene expression in the community of coffee research.

The 'PUCE CAFE' Project: the First 15K Coffee Microarray, a New Tool for Discovering Candidate Genes correlated to Agronomic and Quality Traits

Directory of Open Access Journals (Sweden)

Leroy Thierry

2011-01-01

Full Text Available Abstract Background Understanding the genetic elements that contribute to key aspects of coffee biology will have an impact on future agronomical improvements for this economically important tree. During the past years, EST collections were generated in Coffee, opening the possibility to create new tools for functional genomics. Results The "PUCE CAFE" Project, organized by the scientific consortium NESTLE/IRD/CIRAD, has developed an oligo-based microarray using 15,721 unigenes derived from published coffee EST sequences mostly obtained from different stages of fruit development and leaves in Coffea Canephora (Robusta. Hybridizations for two independent experiments served to compare global gene expression profiles in three types of tissue matter (mature beans, leaves and flowers in C. canephora as well as in the leaves of three different coffee species (C. canephora, C. eugenoides and C. arabica. Microarray construction, statistical analyses and validation by Q-PCR analysis are presented in this study. Conclusion We have generated the first 15 K coffee array during this PUCE CAFE project, granted by Génoplante (the French consortium for plant genomics. This new tool will help study functional genomics in a wide range of experiments on various plant tissues, such as analyzing bean maturation or resistance to pathogens or drought. Furthermore, the use of this array has proven to be valid in different coffee species (diploid or tetraploid, drastically enlarging its impact for high-throughput gene expression in the community of coffee research.

Tumour auto-antibody screening: performance of protein microarrays using SEREX derived antigens

International Nuclear Information System (INIS)

Stempfer, René; Weinhäusel, Andreas; Syed, Parvez; Vierlinger, Klemens; Pichler, Rudolf; Meese, Eckart; Leidinger, Petra; Ludwig, Nicole; Kriegner, Albert; Nöhammer, Christa

2010-01-01

The simplicity and potential of minimal invasive testing using serum from patients make auto-antibody based biomarkers a very promising tool for use in diagnostics of cancer and auto-immune disease. Although several methods exist for elucidating candidate-protein markers, immobilizing these onto membranes and generating so called macroarrays is of limited use for marker validation. Especially when several hundred samples have to be analysed, microarrays could serve as a good alternative since processing macro membranes is cumbersome and reproducibility of results is moderate. Candidate markers identified by SEREX (serological identification of antigens by recombinant expression cloning) screenings of brain and lung tumour were used for macroarray and microarray production. For microarray production recombinant proteins were expressed in E. coli by autoinduction and purified His-tag (histidine-tagged) proteins were then used for the production of protein microarrays. Protein arrays were hybridized with the serum samples from brain and lung tumour patients. Methods for the generation of microarrays were successfully established when using antigens derived from membrane-based selection. Signal patterns obtained by microarrays analysis of brain and lung tumour patients' sera were highly reproducible (R = 0.92-0.96). This provides the technical foundation for diagnostic applications on the basis of auto-antibody patterns. In this limited test set, the assay provided high reproducibility and a broad dynamic range to classify all brain and lung samples correctly. Protein microarray is an efficient means for auto-antibody-based detection when using SEREX-derived clones expressing antigenic proteins. Protein microarrays are preferred to macroarrays due to the easier handling and the high reproducibility of auto-antibody testing. Especially when using only a few microliters of patient samples protein microarrays are ideally suited for validation of auto

Clinical relevance of DNA microarray analyses using archival formalin-fixed paraffin-embedded breast cancer specimens

International Nuclear Information System (INIS)

Sadi, Al Muktafi; Wang, Dong-Yu; Youngson, Bruce J; Miller, Naomi; Boerner, Scott; Done, Susan J; Leong, Wey L

2011-01-01

The ability of gene profiling to predict treatment response and prognosis in breast cancers has been demonstrated in many studies using DNA microarray analyses on RNA from fresh frozen tumor specimens. In certain clinical and research situations, performing such analyses on archival formalin fixed paraffin-embedded (FFPE) surgical specimens would be advantageous as large libraries of such specimens with long-term follow-up data are widely available. However, FFPE tissue processing can cause fragmentation and chemical modifications of the RNA. A number of recent technical advances have been reported to overcome these issues. Our current study evaluates whether or not the technology is ready for clinical applications. A modified RNA extraction method and a recent DNA microarray technique, cDNA-mediated annealing, selection, extension and ligation (DASL, Illumina Inc) were evaluated. The gene profiles generated from FFPE specimens were compared to those obtained from paired fresh fine needle aspiration biopsies (FNAB) of 25 breast cancers of different clinical subtypes (based on ER and Her2/neu status). Selected RNA levels were validated using RT-qPCR, and two public databases were used to demonstrate the prognostic significance of the gene profiles generated from FFPE specimens. Compared to FNAB, RNA isolated from FFPE samples was relatively more degraded, nonetheless, over 80% of the RNA samples were deemed suitable for subsequent DASL assay. Despite a higher noise level, a set of genes from FFPE specimens correlated very well with the gene profiles obtained from FNAB, and could differentiate breast cancer subtypes. Expression levels of these genes were validated using RT-qPCR. Finally, for the first time we correlated gene expression profiles from FFPE samples to survival using two independent microarray databases. Specifically, over-expression of ANLN and KIF2C, and under-expression of MAPT strongly correlated with poor outcomes in breast cancer patients. We

Preoperative overnight parenteral nutrition (TPN) improves skeletal muscle protein metabolism indicated by microarray algorithm analyses in a randomized trial.

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Iresjö, Britt-Marie; Engström, Cecilia; Lundholm, Kent

2016-06-01

Loss of muscle mass is associated with increased risk of morbidity and mortality in hospitalized patients. Uncertainties of treatment efficiency by short-term artificial nutrition remain, specifically improvement of protein balance in skeletal muscles. In this study, algorithmic microarray analysis was applied to map cellular changes related to muscle protein metabolism in human skeletal muscle tissue during provision of overnight preoperative total parenteral nutrition (TPN). Twenty-two patients (11/group) scheduled for upper GI surgery due to malignant or benign disease received a continuous peripheral all-in-one TPN infusion (30 kcal/kg/day, 0.16 gN/kg/day) or saline infusion for 12 h prior operation. Biopsies from the rectus abdominis muscle were taken at the start of operation for isolation of muscle RNA RNA expression microarray analyses were performed with Agilent Sureprint G3, 8 × 60K arrays using one-color labeling. 447 mRNAs were differently expressed between study and control patients (P nutrition; particularly anabolic signaling S6K1 (P parenteral nutrition is effective to promote muscle protein metabolism. © 2016 The Authors. Physiological Reports published by Wiley Periodicals, Inc. on behalf of the American Physiological Society and The Physiological Society.

Printing Proteins as Microarrays for High-Throughput Function Determination

Science.gov (United States)

MacBeath, Gavin; Schreiber, Stuart L.

2000-09-01

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

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

NARCIS (Netherlands)

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

2007-01-01

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

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

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Pląder Wojciech

2011-09-01

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

Workflows for microarray data processing in the Kepler environment

Science.gov (United States)

2012-01-01

Background Microarray data analysis has been the subject of extensive and ongoing pipeline development due to its complexity, the availability of several options at each analysis step, and the development of new analysis demands, including integration with new data sources. Bioinformatics pipelines are usually custom built for different applications, making them typically difficult to modify, extend and repurpose. Scientific workflow systems are intended to address these issues by providing general-purpose frameworks in which to develop and execute such pipelines. The Kepler workflow environment is a well-established system under continual development that is employed in several areas of scientific research. Kepler provides a flexible graphical interface, featuring clear display of parameter values, for design and modification of workflows. It has capabilities for developing novel computational components in the R, Python, and Java programming languages, all of which are widely used for bioinformatics algorithm development, along with capabilities for invoking external applications and using web services. Results We developed a series of fully functional bioinformatics pipelines addressing common tasks in microarray processing in the Kepler workflow environment. These pipelines consist of a set of tools for GFF file processing of NimbleGen chromatin immunoprecipitation on microarray (ChIP-chip) datasets and more comprehensive workflows for Affymetrix gene expression microarray bioinformatics and basic primer design for PCR experiments, which are often used to validate microarray results. Although functional in themselves, these workflows can be easily customized, extended, or repurposed to match the needs of specific projects and are designed to be a toolkit and starting point for specific applications. These workflows illustrate a workflow programming paradigm focusing on local resources (programs and data) and therefore are close to traditional shell scripting or

Workflows for microarray data processing in the Kepler environment

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Stropp Thomas

2012-05-01

Full Text Available Abstract Background Microarray data analysis has been the subject of extensive and ongoing pipeline development due to its complexity, the availability of several options at each analysis step, and the development of new analysis demands, including integration with new data sources. Bioinformatics pipelines are usually custom built for different applications, making them typically difficult to modify, extend and repurpose. Scientific workflow systems are intended to address these issues by providing general-purpose frameworks in which to develop and execute such pipelines. The Kepler workflow environment is a well-established system under continual development that is employed in several areas of scientific research. Kepler provides a flexible graphical interface, featuring clear display of parameter values, for design and modification of workflows. It has capabilities for developing novel computational components in the R, Python, and Java programming languages, all of which are widely used for bioinformatics algorithm development, along with capabilities for invoking external applications and using web services. Results We developed a series of fully functional bioinformatics pipelines addressing common tasks in microarray processing in the Kepler workflow environment. These pipelines consist of a set of tools for GFF file processing of NimbleGen chromatin immunoprecipitation on microarray (ChIP-chip datasets and more comprehensive workflows for Affymetrix gene expression microarray bioinformatics and basic primer design for PCR experiments, which are often used to validate microarray results. Although functional in themselves, these workflows can be easily customized, extended, or repurposed to match the needs of specific projects and are designed to be a toolkit and starting point for specific applications. These workflows illustrate a workflow programming paradigm focusing on local resources (programs and data and therefore are close to

Workflows for microarray data processing in the Kepler environment.

Science.gov (United States)

Stropp, Thomas; McPhillips, Timothy; Ludäscher, Bertram; Bieda, Mark

2012-05-17

Microarray data analysis has been the subject of extensive and ongoing pipeline development due to its complexity, the availability of several options at each analysis step, and the development of new analysis demands, including integration with new data sources. Bioinformatics pipelines are usually custom built for different applications, making them typically difficult to modify, extend and repurpose. Scientific workflow systems are intended to address these issues by providing general-purpose frameworks in which to develop and execute such pipelines. The Kepler workflow environment is a well-established system under continual development that is employed in several areas of scientific research. Kepler provides a flexible graphical interface, featuring clear display of parameter values, for design and modification of workflows. It has capabilities for developing novel computational components in the R, Python, and Java programming languages, all of which are widely used for bioinformatics algorithm development, along with capabilities for invoking external applications and using web services. We developed a series of fully functional bioinformatics pipelines addressing common tasks in microarray processing in the Kepler workflow environment. These pipelines consist of a set of tools for GFF file processing of NimbleGen chromatin immunoprecipitation on microarray (ChIP-chip) datasets and more comprehensive workflows for Affymetrix gene expression microarray bioinformatics and basic primer design for PCR experiments, which are often used to validate microarray results. Although functional in themselves, these workflows can be easily customized, extended, or repurposed to match the needs of specific projects and are designed to be a toolkit and starting point for specific applications. These workflows illustrate a workflow programming paradigm focusing on local resources (programs and data) and therefore are close to traditional shell scripting or R

Microarray-based genotyping of Salmonella: Inter-laboratory evaluation of reproducibility and standardization potential

DEFF Research Database (Denmark)

Grønlund, Hugo Ahlm; Riber, Leise; Vigre, Håkan

2011-01-01

Bacterial food-borne infections in humans caused by Salmonella spp. are considered a crucial food safety issue. Therefore, it is important for the risk assessments of Salmonella to consider the genomic variationamong different isolates in order to control pathogen-induced infections. Microarray...... critical methodology parameters that differed between the two labs were identified. These related to printing facilities, choice of hybridization buffer,wash buffers used following the hybridization and choice of procedure for purifying genomic DNA. Critical parameters were randomized in a four......DNA and different wash buffers. However, less agreement (Kappa=0.2–0.6) between microarray results were observed when using different hybridization buffers, indicating this parameter as being highly criticalwhen transferring a standard microarray assay between laboratories. In conclusion, this study indicates...

Fuzzy support vector machine for microarray imbalanced data classification

Science.gov (United States)

Ladayya, Faroh; Purnami, Santi Wulan; Irhamah

2017-11-01

DNA microarrays are data containing gene expression with small sample sizes and high number of features. Furthermore, imbalanced classes is a common problem in microarray data. This occurs when a dataset is dominated by a class which have significantly more instances than the other minority classes. Therefore, it is needed a classification method that solve the problem of high dimensional and imbalanced data. Support Vector Machine (SVM) is one of the classification methods that is capable of handling large or small samples, nonlinear, high dimensional, over learning and local minimum issues. SVM has been widely applied to DNA microarray data classification and it has been shown that SVM provides the best performance among other machine learning methods. However, imbalanced data will be a problem because SVM treats all samples in the same importance thus the results is bias for minority class. To overcome the imbalanced data, Fuzzy SVM (FSVM) is proposed. This method apply a fuzzy membership to each input point and reformulate the SVM such that different input points provide different contributions to the classifier. The minority classes have large fuzzy membership so FSVM can pay more attention to the samples with larger fuzzy membership. Given DNA microarray data is a high dimensional data with a very large number of features, it is necessary to do feature selection first using Fast Correlation based Filter (FCBF). In this study will be analyzed by SVM, FSVM and both methods by applying FCBF and get the classification performance of them. Based on the overall results, FSVM on selected features has the best classification performance compared to SVM.

A fisheye viewer for microarray-based gene expression data

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Munson Ethan V

2006-10-01

Full Text Available Abstract Background Microarray has been widely used to measure the relative amounts of every mRNA transcript from the genome in a single scan. Biologists have been accustomed to reading their experimental data directly from tables. However, microarray data are quite large and are stored in a series of files in a machine-readable format, so direct reading of the full data set is not feasible. The challenge is to design a user interface that allows biologists to usefully view large tables of raw microarray-based gene expression data. This paper presents one such interface – an electronic table (E-table that uses fisheye distortion technology. Results The Fisheye Viewer for microarray-based gene expression data has been successfully developed to view MIAME data stored in the MAGE-ML format. The viewer can be downloaded from the project web site http://polaris.imt.uwm.edu:7777/fisheye/. The fisheye viewer was implemented in Java so that it could run on multiple platforms. We implemented the E-table by adapting JTable, a default table implementation in the Java Swing user interface library. Fisheye views use variable magnification to balance magnification for easy viewing and compression for maximizing the amount of data on the screen. Conclusion This Fisheye Viewer is a lightweight but useful tool for biologists to quickly overview the raw microarray-based gene expression data in an E-table.

AMDA: an R package for the automated microarray data analysis

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Foti Maria

2006-07-01

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

A mixture model-based approach to the clustering of microarray expression data.

Science.gov (United States)

McLachlan, G J; Bean, R W; Peel, D

2002-03-01

This paper introduces the software EMMIX-GENE that has been developed for the specific purpose of a model-based approach to the clustering of microarray expression data, in particular, of tissue samples on a very large number of genes. The latter is a nonstandard problem in parametric cluster analysis because the dimension of the feature space (the number of genes) is typically much greater than the number of tissues. A feasible approach is provided by first selecting a subset of the genes relevant for the clustering of the tissue samples by fitting mixtures of t distributions to rank the genes in order of increasing size of the likelihood ratio statistic for the test of one versus two components in the mixture model. The imposition of a threshold on the likelihood ratio statistic used in conjunction with a threshold on the size of a cluster allows the selection of a relevant set of genes. However, even this reduced set of genes will usually be too large for a normal mixture model to be fitted directly to the tissues, and so the use of mixtures of factor analyzers is exploited to reduce effectively the dimension of the feature space of genes. The usefulness of the EMMIX-GENE approach for the clustering of tissue samples is demonstrated on two well-known data sets on colon and leukaemia tissues. For both data sets, relevant subsets of the genes are able to be selected that reveal interesting clusterings of the tissues that are either consistent with the external classification of the tissues or with background and biological knowledge of these sets. EMMIX-GENE is available at http://www.maths.uq.edu.au/~gjm/emmix-gene/

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

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Laura Kennedy

2008-01-01

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

Massively multiplexed microbial identification using resequencing DNA microarrays for outbreak investigation

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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.

Transcriptomic comparisons between cultured human adipose tissue-derived pericytes and mesenchymal stromal cells

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Lindolfo da Silva Meirelles

2016-03-01

Full Text Available Mesenchymal stromal cells (MSCs, sometimes called mesenchymal stem cells, are cultured cells able to give rise to mature mesenchymal cells such as adipocytes, osteoblasts, and chondrocytes, and to secrete a wide range of trophic and immunomodulatory molecules. Evidence indicates that pericytes, cells that surround and maintain physical connections with endothelial cells in blood vessels, can give rise to MSCs (da Silva Meirelles et al., 2008 [1]; Caplan and Correa, 2011 [2]. We have compared the transcriptomes of highly purified, human adipose tissue pericytes subjected to culture-expansion in pericyte medium or MSC medium, with that of human adipose tissue MSCs isolated with traditional methods to test the hypothesis that their transcriptomes are similar (da Silva Meirelles et al., 2015 [3]. Here, we provide further information and analyses of microarray data from three pericyte populations cultured in pericyte medium, three pericyte populations cultured in MSC medium, and three adipose tissue MSC populations deposited in the Gene Expression Omnibus under accession number GSE67747. Keywords: Mesenchymal stromal cells, Mesenchymal stem cells, Pericytes, Microarrays

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

Energy Technology Data Exchange (ETDEWEB)

Gardner, S; Jaing, C

2012-03-27

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

AN IMPROVED FUZZY CLUSTERING ALGORITHM FOR MICROARRAY IMAGE SPOTS SEGMENTATION

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V.G. Biju

2015-11-01

Full Text Available An automatic cDNA microarray image processing using an improved fuzzy clustering algorithm is presented in this paper. The spot segmentation algorithm proposed uses the gridding technique developed by the authors earlier, for finding the co-ordinates of each spot in an image. Automatic cropping of spots from microarray image is done using these co-ordinates. The present paper proposes an improved fuzzy clustering algorithm Possibility fuzzy local information c means (PFLICM to segment the spot foreground (FG from background (BG. The PFLICM improves fuzzy local information c means (FLICM algorithm by incorporating typicality of a pixel along with gray level information and local spatial information. The performance of the algorithm is validated using a set of simulated cDNA microarray images added with different levels of AWGN noise. The strength of the algorithm is tested by computing the parameters such as the Segmentation matching factor (SMF, Probability of error (pe, Discrepancy distance (D and Normal mean square error (NMSE. SMF value obtained for PFLICM algorithm shows an improvement of 0.9 % and 0.7 % for high noise and low noise microarray images respectively compared to FLICM algorithm. The PFLICM algorithm is also applied on real microarray images and gene expression values are computed.

Addressable droplet microarrays for single cell protein analysis.

Science.gov (United States)

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

2014-11-07

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

MICROARRAY IMAGE GRIDDING USING GRID LINE REFINEMENT TECHNIQUE

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V.G. Biju

2015-05-01

Full Text Available An important stage in microarray image analysis is gridding. Microarray image gridding is done to locate sub arrays in a microarray image and find co-ordinates of spots within each sub array. For accurate identification of spots, most of the proposed gridding methods require human intervention. In this paper a fully automatic gridding method which enhances spot intensity in the preprocessing step as per a histogram based threshold method is used. The gridding step finds co-ordinates of spots from horizontal and vertical profile of the image. To correct errors due to the grid line placement, a grid line refinement technique is proposed. The algorithm is applied on different image databases and results are compared based on spot detection accuracy and time. An average spot detection accuracy of 95.06% depicts the proposed method’s flexibility and accuracy in finding the spot co-ordinates for different database images.

Expression of BMI-1 and Mel-18 in breast tissue--a diagnostic marker in patients with breast cancer.

Science.gov (United States)

Riis, Margit L H; Lüders, Torben; Nesbakken, Anne-Jorunn; Vollan, Hilde S; Kristensen, Vessela; Bukholm, Ida R K

2010-12-16

Polycomb Group (PcG) proteins are epigenetic silencers involved in maintaining cellular identity, and their deregulation can result in cancer. Expression of Mel-18 and Bmi-1 has been studied in tumor tissue, but not in adjacent non-cancerous breast epithelium. Our study compares the expression of the two genes in normal breast epithelium of cancer patients and relates it to the level of expression in the corresponding tumors as well as in breast epithelium of healthy women. A total of 79 tumors, of which 71 malignant tumors of the breast, 6 fibroadenomas, and 2 DCIS were studied and compared to the reduction mammoplastic specimens of 11 healthy women. In addition there was available adjacent cancer free tissue for 23 of the malignant tumors. The tissue samples were stored in RNAlater, RNA was isolated to create expression microarray profile. These two genes were then studied more closely first on mRNA transcription level by microarrays (Agilent 44 K) and quantitative RT-PCR (TaqMan) and then on protein expression level using immunohistochemistry. Bmi-1 mRNA is significantly up-regulated in adjacent normal breast tissue in breast cancer patients compared to normal breast tissue from noncancerous patients. Conversely, mRNA transcription level of Mel-18 is lower in normal breast from patients operated for breast cancer compared to breast tissue from mammoplasty. When protein expression of these two genes was evaluated, we observed that most of the epithelial cells were positive for Bmi-1 in both groups of tissue samples, although the expression intensity was stronger in normal tissue from cancer patients compared to mammoplasty tissue samples. Protein expression of Mel-18 showed inversely stronger intensity in tissue samples from mammoplasty compared to normal breast tissue from patients operated for breast cancer. Bmi-1 mRNA level is consistently increased and Mel-18 mRNA level is consistently decreased in adjacent normal breast tissue of cancer patients as compared

Identification of a novel uromodulin-like gene related to predator-induced bulgy morph in anuran tadpoles by functional microarray analysis.

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Tsukasa Mori

2009-06-01

Full Text Available Tadpoles of the anuran species Rana pirica can undergo predator-specific morphological responses. Exposure to a predation threat by larvae of the salamander Hynobius retardatus results in formation of a bulgy body (bulgy morph with a higher tail. The tadpoles revert to a normal phenotype upon removal of the larval salamander threat. Although predator-induced phenotypic plasticity is of major interest to evolutionary ecologists, the molecular and physiological mechanisms that control this response have yet to be elucidated. In a previous study, we identified various genes that are expressed in the skin of the bulgy morph. However, it proved difficult to determine which of these were key genes in the control of gene expression associated with the bulgy phenotype. Here, we show that a novel gene plays an important role in the phenotypic plasticity producing the bulgy morph. A functional microarray analysis using facial tissue samples of control and bulgy morph tadpoles identified candidate functional genes for predator-specific morphological responses. A larger functional microarray was prepared than in the previous study and used to analyze mRNAs extracted from facial and brain tissues of tadpoles from induction-reversion experiments. We found that a novel uromodulin-like gene, which we name here pirica, was up-regulated and that keratin genes were down-regulated as the period of exposure to larval salamanders increased. Pirica consists of a 1296 bp open reading frame, which is putatively translated into a protein of 432 amino acids. The protein contains a zona pellucida domain similar to that of proteins that function to control water permeability. We found that the gene was expressed in the superficial epidermis of the tadpole skin.

NF2 tumor suppressor gene: a comprehensive and efficient detection of somatic mutations by denaturing HPLC and microarray-CGH.

Science.gov (United States)

Szijan, Irene; Rochefort, Daniel; Bruder, Carl; Surace, Ezequiel; Machiavelli, Gloria; Dalamon, Viviana; Cotignola, Javier; Ferreiro, Veronica; Campero, Alvaro; Basso, Armando; Dumanski, Jan P; Rouleau, Guy A

2003-01-01

The NF2 tumor suppressor gene, located in chromosome 22q12, is involved in the development of multiple tumors of the nervous system, either associated with neurofibromatosis 2 or sporadic ones, mainly schwannomas and meningiomas. In order to evaluate the role of the NF2 gene in sporadic central nervous system (CNS) tumors, we analyzed NF2 mutations in 26 specimens: 14 meningiomas, 4 schwannomas, 4 metastases, and 4 other histopathological types of neoplasms. Denaturing high performance liquid chromatography (denaturing HPLC) and comparative genomic hybridization on a DNA microarray (microarray- CGH) were used as scanning methods for small mutations and gross rearrangements respectively. Small mutations were identified in six out of seventeen meningiomas and schwannomas, one mutation was novel. Large deletions were detected in six meningiomas. All mutations were predicted to result in truncated protein or in the absence of a large protein domain. No NF2 mutations were found in other histopathological types of CNS tumors. These results provide additional evidence that mutations in the NF2 gene play an important role in the development of sporadic meningiomas and schwannomas. Denaturing HPLC analysis of small mutations and microarray-CGH of large deletions are complementary, fast, and efficient methods for the detection of mutations in tumor tissues.

Kernel Based Nonlinear Dimensionality Reduction and Classification for Genomic Microarray

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Lan Shu

2008-07-01

Full Text Available Genomic microarrays are powerful research tools in bioinformatics and modern medicinal research because they enable massively-parallel assays and simultaneous monitoring of thousands of gene expression of biological samples. However, a simple microarray experiment often leads to very high-dimensional data and a huge amount of information, the vast amount of data challenges researchers into extracting the important features and reducing the high dimensionality. In this paper, a nonlinear dimensionality reduction kernel method based locally linear embedding(LLE is proposed, and fuzzy K-nearest neighbors algorithm which denoises datasets will be introduced as a replacement to the classical LLE’s KNN algorithm. In addition, kernel method based support vector machine (SVM will be used to classify genomic microarray data sets in this paper. We demonstrate the application of the techniques to two published DNA microarray data sets. The experimental results confirm the superiority and high success rates of the presented method.

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

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Reinders Marcel JT

2009-11-01

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

Prognostic meta-signature of breast cancer developed by two-stage mixture modeling of microarray data

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Ghosh Debashis

2004-12-01

Full Text Available Abstract Background An increasing number of studies have profiled tumor specimens using distinct microarray platforms and analysis techniques. With the accumulating amount of microarray data, one of the most intriguing yet challenging tasks is to develop robust statistical models to integrate the findings. Results By applying a two-stage Bayesian mixture modeling strategy, we were able to assimilate and analyze four independent microarray studies to derive an inter-study validated "meta-signature" associated with breast cancer prognosis. Combining multiple studies (n = 305 samples on a common probability scale, we developed a 90-gene meta-signature, which strongly associated with survival in breast cancer patients. Given the set of independent studies using different microarray platforms which included spotted cDNAs, Affymetrix GeneChip, and inkjet oligonucleotides, the individually identified classifiers yielded gene sets predictive of survival in each study cohort. The study-specific gene signatures, however, had minimal overlap with each other, and performed poorly in pairwise cross-validation. The meta-signature, on the other hand, accommodated such heterogeneity and achieved comparable or better prognostic performance when compared with the individual signatures. Further by comparing to a global standardization method, the mixture model based data transformation demonstrated superior properties for data integration and provided solid basis for building classifiers at the second stage. Functional annotation revealed that genes involved in cell cycle and signal transduction activities were over-represented in the meta-signature. Conclusion The mixture modeling approach unifies disparate gene expression data on a common probability scale allowing for robust, inter-study validated prognostic signatures to be obtained. With the emerging utility of microarrays for cancer prognosis, it will be important to establish paradigms to meta

Facilitating RNA structure prediction with microarrays.

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Kierzek, Elzbieta; Kierzek, Ryszard; Turner, Douglas H; Catrina, Irina E

2006-01-17

Determining RNA secondary structure is important for understanding structure-function relationships and identifying potential drug targets. This paper reports the use of microarrays with heptamer 2'-O-methyl oligoribonucleotides to probe the secondary structure of an RNA and thereby improve the prediction of that secondary structure. When experimental constraints from hybridization results are added to a free-energy minimization algorithm, the prediction of the secondary structure of Escherichia coli 5S rRNA improves from 27 to 92% of the known canonical base pairs. Optimization of buffer conditions for hybridization and application of 2'-O-methyl-2-thiouridine to enhance binding and improve discrimination between AU and GU pairs are also described. The results suggest that probing RNA with oligonucleotide microarrays can facilitate determination of secondary structure.

A Customized DNA Microarray for Microbial Source Tracking ...

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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

Systematic interpretation of microarray data using experiment annotations

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Frohme Marcus

2006-12-01

Full Text Available Abstract Background Up to now, microarray data are mostly assessed in context with only one or few parameters characterizing the experimental conditions under study. More explicit experiment annotations, however, are highly useful for interpreting microarray data, when available in a statistically accessible format. Results We provide means to preprocess these additional data, and to extract relevant traits corresponding to the transcription patterns under study. We found correspondence analysis particularly well-suited for mapping such extracted traits. It visualizes associations both among and between the traits, the hereby annotated experiments, and the genes, revealing how they are all interrelated. Here, we apply our methods to the systematic interpretation of radioactive (single channel and two-channel data, stemming from model organisms such as yeast and drosophila up to complex human cancer samples. Inclusion of technical parameters allows for identification of artifacts and flaws in experimental design. Conclusion Biological and clinical traits can act as landmarks in transcription space, systematically mapping the variance of large datasets from the predominant changes down toward intricate details.

Application of a New Genetic Deafness Microarray for Detecting Mutations in the Deaf in China.

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Hong Wu

Full Text Available The aim of this study was to evaluate the GoldenGate microarray as a diagnostic tool and to elucidate the contribution of the genes on this array to the development of both nonsyndromic and syndromic sensorineural hearing loss in China.We developed a microarray to detect 240 mutations underlying syndromic and nonsyndromic sensorineural hearing loss. The microarray was then used for analysis of 382 patients with nonsyndromic sensorineural hearing loss (including 15 patients with enlarged vestibular aqueduct syndrome, 21 patients with Waardenburg syndrome, and 60 unrelated controls. Subsequently, we analyzed the sensitivity, specificity, and reproducibility of this new approach after Sanger sequencing-based verification, and also determined the contribution of the genes on this array to the development of distinct hearing disorders.The sensitivity and specificity of the microarray chip were 98.73% and 98.34%, respectively. Genetic defects were identified in 61.26% of the patients with nonsyndromic sensorineural hearing loss, and 9 causative genes were identified. The molecular etiology was confirmed in 19.05% and 46.67% of the patients with Waardenburg syndrome and enlarged vestibular aqueduct syndrome, respectively.Our new mutation-based microarray comprises an accurate and comprehensive genetic tool for the detection of sensorineural hearing loss. This microarray-based detection method could serve as a first-pass screening (before next-generation-sequencing screening for deafness-causing mutations in China.

Molecular aspects in inflammatory events of temporomandibular joint: Microarray-based identification of mediators

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Naomi Ogura

2015-02-01

Full Text Available Synovial inflammation (synovitis frequently accompanies intracapsular pathologic conditions of the temporomandibular joint (TMJ such as internal derangement (ID and/or osteoarthritis (OA, and is suggested to be associated with symptom severity. To identify the putative factors associated with synovitis, we investigated interleukin (IL-1β- and/or tumor necrosis factor (TNF-α-responsive genes of fibroblast-like synoviocytes (FLS from patients with ID and/or OA of TMJ using microarray analysis. In this review, we first summarize the FLS of TMJ and the signaling pathways of IL-1β and TNF-α. Next, we show the up-regulated genes in FLS after stimulation with IL-1β or TNF-α, and summarize the gene functions based on recent studies. Among the top 10 up-regulated factors, molecules such as IL-6 and cycrooxygense-2 have been well characterized and investigated in the inflammatory responses and tissue destruction associated with joint diseases such as RA and OA, but the roles of some molecules remain unclear. The FLS reaction can lead to the synthesis and release of a wide variety of inflammatory mediators. Some of these mediators are detected in joint tissues and synovial fluids under intracapsular pathologic conditions, and may represent potential targets for therapeutic interventions in ID and/or OA of TMJ.

A Critical Perspective On Microarray Breast Cancer Gene Expression Profiling

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Sontrop, H.M.J.

2015-01-01

Microarrays offer biologists an exciting tool that allows the simultaneous assessment of gene expression levels for thousands of genes at once. At the time of their inception, microarrays were hailed as the new dawn in cancer biology and oncology practice with the hope that within a decade diseases

Pathway modeling of microarray data: A case study of pathway activity changes in the testis following in utero exposure to dibutyl phthalate (DBP)

International Nuclear Information System (INIS)

Ovacik, Meric A.; Sen, Banalata; Euling, Susan Y.; Gaido, Kevin W.; Ierapetritou, Marianthi G.; Androulakis, Ioannis P.

2013-01-01

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 significance 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

Pathway modeling of microarray data: A case study of pathway activity changes in the testis following in utero exposure to dibutyl phthalate (DBP)

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Ovacik, Meric A. [Chemical and Biochemical Engineering Department, Rutgers University, Piscataway, NJ 08854 (United States); Sen, Banalata [National Center for Environmental Assessment, U.S. Environmental Protection Agency, Research Triangle Park, NC 27709 (United States); Euling, Susan Y. [National Center for Environmental Assessment, Office of Research and Development, U.S. Environmental Protection Agency, Washington, DC 20460 (United States); Gaido, Kevin W. [U.S. Food and Drug Administration, Center for Veterinary Medicine, Office of New Animal Drug Evaluation, Division of Human Food Safety, Rockville, MD 20855 (United States); Ierapetritou, Marianthi G. [Chemical and Biochemical Engineering Department, Rutgers University, Piscataway, NJ 08854 (United States); Androulakis, Ioannis P., E-mail: yannis@rci.rutgers.edu [Chemical and Biochemical Engineering Department, Rutgers University, Piscataway, NJ 08854 (United States); Biomedical Engineering Department, Rutgers University, NJ 08854 (United States)

2013-09-15

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 significance 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.

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

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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.

Profiling cellular protein complexes by proximity ligation with dual tag microarray readout.

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Hammond, Maria; Nong, Rachel Yuan; Ericsson, Olle; Pardali, Katerina; Landegren, Ulf

2012-01-01

Patterns of protein interactions provide important insights in basic biology, and their analysis plays an increasing role in drug development and diagnostics of disease. We have established a scalable technique to compare two biological samples for the levels of all pairwise interactions among a set of targeted protein molecules. The technique is a combination of the proximity ligation assay with readout via dual tag microarrays. In the proximity ligation assay protein identities are encoded as DNA sequences by attaching DNA oligonucleotides to antibodies directed against the proteins of interest. Upon binding by pairs of antibodies to proteins present in the same molecular complexes, ligation reactions give rise to reporter DNA molecules that contain the combined sequence information from the two DNA strands. The ligation reactions also serve to incorporate a sample barcode in the reporter molecules to allow for direct comparison between pairs of samples. The samples are evaluated using a dual tag microarray where information is decoded, revealing which pairs of tags that have become joined. As a proof-of-concept we demonstrate that this approach can be used to detect a set of five proteins and their pairwise interactions both in cellular lysates and in fixed tissue culture cells. This paper provides a general strategy to analyze the extent of any pairwise interactions in large sets of molecules by decoding reporter DNA strands that identify the interacting molecules.

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

KAUST Repository

Boopathi, Pon Arunachalam

2016-10-09

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

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

KAUST Repository

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

2016-01-01

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

A statistical model for investigating binding probabilities of DNA nucleotide sequences using microarrays.

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Lee, Mei-Ling Ting; Bulyk, Martha L; Whitmore, G A; Church, George M

2002-12-01

There is considerable scientific interest in knowing the probability that a site-specific transcription factor will bind to a given DNA sequence. Microarray methods provide an effective means for assessing the binding affinities of a large number of DNA sequences as demonstrated by Bulyk et al. (2001, Proceedings of the National Academy of Sciences, USA 98, 7158-7163) in their study of the DNA-binding specificities of Zif268 zinc fingers using microarray technology. In a follow-up investigation, Bulyk, Johnson, and Church (2002, Nucleic Acid Research 30, 1255-1261) studied the interdependence of nucleotides on the binding affinities of transcription proteins. Our article is motivated by this pair of studies. We present a general statistical methodology for analyzing microarray intensity measurements reflecting DNA-protein interactions. The log probability of a protein binding to a DNA sequence on an array is modeled using a linear ANOVA model. This model is convenient because it employs familiar statistical concepts and procedures and also because it is effective for investigating the probability structure of the binding mechanism.

In silico design and performance of peptide microarrays for breast cancer tumour-auto-antibody testing

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Andreas Weinhäusel

2012-06-01

Full Text Available The simplicity and potential of minimally invasive testing using sera from patients makes auto-antibody based biomarkers a very promising tool for use in cancer diagnostics. Protein microarrays have been used for the identification of such auto-antibody signatures. Because high throughput protein expression and purification is laborious, synthetic peptides might be a good alternative for microarray generation and multiplexed analyses. In this study, we designed 1185 antigenic peptides, deduced from proteins expressed by 642 cDNA expression clones found to be sero-reactive in both breast tumour patients and controls. The sero-reactive proteins and the corresponding peptides were used for the production of protein and peptide microarrays. Serum samples from females with benign and malignant breast tumours and healthy control sera (n=16 per group were then analysed. Correct classification of the serum samples on peptide microarrays were 78% for discrimination of ‘malignant versus healthy controls’, 72% for ‘benign versus malignant’ and 94% for ‘benign versus controls’. On protein arrays, correct classification for these contrasts was 69%, 59% and 59%, respectively. The over-representation analysis of the classifiers derived from class prediction showed enrichment of genes associated with ribosomes, spliceosomes, endocytosis and the pentose phosphate pathway. Sequence analyses of the peptides with the highest sero-reactivity demonstrated enrichment of the zinc-finger domain. Peptides’ sero-reactivities were found negatively correlated with hydrophobicity and positively correlated with positive charge, high inter-residue protein contact energies and a secondary structure propensity bias. This study hints at the possibility of using in silico designed antigenic peptide microarrays as an alternative to protein microarrays for the improvement of tumour auto-antibody based diagnostics.

A Versatile Microarray Platform for Capturing Rare Cells

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

2015-10-01

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

Fabrication of protein microarrays for alpha fetoprotein detection by using a rapid photo-immobilization process

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Sirasa Yodmongkol

2016-03-01

Full Text Available In this study, protein microarrays based on sandwich immunoassays are generated to quantify the amount of alpha fetoprotein (AFP in blood serum. For chip generation a mixture of capture antibody and a photoactive copolymer consisting of N,N-dimethylacrylamide (DMAA, methacryloyloxy benzophenone (MaBP, and Na-4-styrenesulfonate (SSNa was spotted onto unmodified polymethyl methacrylate (PMMA substrates. Subsequently to printing of the microarray, the polymer and protein were photochemically cross-linked and the forming, biofunctionalized hydrogels simultaneously bound to the chip surface by short UV- irradiation. The obtained biochip was incubated with AFP antigen, followed by biotinylated AFP antibody and streptavidin-Cy5 and the fluorescence signal read-out. The developed microarray biochip covers the range of AFP in serum samples such as maternal serum in the range of 5 and 100 ng/ml. The chip production process is based on a fast and simple immobilization process, which can be applied to conventional plastic surfaces. Therefore, this protein microarray production process is a promising method to fabricate biochips for AFP screening processes. Keywords: Photo-immobilization, Protein microarray, Alpha fetoprotein, Hydrogel, 3D surface, Down syndrome

Development and application of an oligonucleotide microarray and real-time quantitative PCR for detection of wastewater bacterial pathogens

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Lee, Dae-Young [National Water Research Institute, Environment Canada, 867 Lakeshore Road, Burlington, Ontario, L7R 4A6 (Canada)], E-mail: daeyoung.lee@ec.gc.ca; Lauder, Heather; Cruwys, Heather; Falletta, Patricia [National Water Research Institute, Environment Canada, 867 Lakeshore Road, Burlington, Ontario, L7R 4A6 (Canada); Beaudette, Lee A. [Environmental Science and Technology Centre, Environment Canada, 335 River Road South, Ottawa, Ontario, K1A 0H3 (Canada)], E-mail: lee.beaudette@ec.gc.ca

2008-07-15

Conventional microbial water quality test methods are well known for their technical limitations, such as lack of direct pathogen detection capacity and low throughput capability. The microarray assay has recently emerged as a promising alternative for environmental pathogen monitoring. In this study, bacterial pathogens were detected in municipal wastewater using a microarray equipped with short oligonucleotide probes targeting 16S rRNA sequences. To date, 62 probes have been designed against 38 species, 4 genera, and 1 family of pathogens. The detection sensitivity of the microarray for a waterborne pathogen Aeromonas hydrophila was determined to be approximately 1.0% of the total DNA, or approximately 10{sup 3}A. hydrophila cells per sample. The efficacy of the DNA microarray was verified in a parallel study where pathogen genes and E. coli cells were enumerated using real-time quantitative PCR (qPCR) and standard membrane filter techniques, respectively. The microarray and qPCR successfully detected multiple wastewater pathogen species at different stages of the disinfection process (i.e. secondary effluents vs. disinfected final effluents) and at two treatment plants employing different disinfection methods (i.e. chlorination vs. UV irradiation). This result demonstrates the effectiveness of the DNA microarray as a semi-quantitative, high throughput pathogen monitoring tool for municipal wastewater.

[Transciptome among Mexicans: a large scale methodology to analyze the genetics expression profile of simultaneous samples in muscle, adipose tissue and lymphocytes obtained from the same individual].

Science.gov (United States)

Bastarrachea, Raúl A; López-Alvarenga, Juan Carlos; Kent, Jack W; Laviada-Molina, Hugo A; Cerda-Flores, Ricardo M; Calderón-Garcidueñas, Ana Laura; Torres-Salazar, Amada; Torres-Salazar, Amanda; Nava-González, Edna J; Solis-Pérez, Elizabeth; Gallegos-Cabrales, Esther C; Cole, Shelley A; Comuzzie, Anthony G

2008-01-01

We describe the methodology used to analyze multiple transcripts using microarray techniques in simultaneous biopsies of muscle, adipose tissue and lymphocytes obtained from the same individual as part of the standard protocol of the Genetics of Metabolic Diseases in Mexico: GEMM Family Study. We recruited 4 healthy male subjects with BM1 20-41, who signed an informed consent letter. Subjects participated in a clinical examination that included anthropometric and body composition measurements, muscle biopsies (vastus lateralis) subcutaneous fat biopsies anda blood draw. All samples provided sufficient amplified RNA for microarray analysis. Total RNA was extracted from the biopsy samples and amplified for analysis. Of the 48,687 transcript targets queried, 39.4% were detectable in a least one of the studied tissues. Leptin was not detectable in lymphocytes, weakly expressed in muscle, but overexpressed and highly correlated with BMI in subcutaneous fat. Another example was GLUT4, which was detectable only in muscle and not correlated with BMI. Expression level concordance was 0.7 (p< 0.001) for the three tissues studied. We demonstrated the feasibility of carrying out simultaneous analysis of gene expression in multiple tissues, concordance of genetic expression in different tissues, and obtained confidence that this method corroborates the expected biological relationships among LEPand GLUT4. TheGEMM study will provide a broad and valuable overview on metabolic diseases, including obesity and type 2 diabetes.

High quality protein microarray using in situ protein purification

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Fleischmann Robert D

2009-08-01

Full Text Available Abstract Background In the postgenomic era, high throughput protein expression and protein microarray technologies have progressed markedly permitting screening of therapeutic reagents and discovery of novel protein functions. Hexa-histidine is one of the most commonly used fusion tags for protein expression due to its small size and convenient purification via immobilized metal ion affinity chromatography (IMAC. This purification process has been adapted to the protein microarray format, but the quality of in situ His-tagged protein purification on slides has not been systematically evaluated. We established methods to determine the level of purification of such proteins on metal chelate-modified slide surfaces. Optimized in situ purification of His-tagged recombinant proteins has the potential to become the new gold standard for cost-effective generation of high-quality and high-density protein microarrays. Results Two slide surfaces were examined, chelated Cu2+ slides suspended on a polyethylene glycol (PEG coating and chelated Ni2+ slides immobilized on a support without PEG coating. Using PEG-coated chelated Cu2+ slides, consistently higher purities of recombinant proteins were measured. An optimized wash buffer (PBST composed of 10 mM phosphate buffer, 2.7 mM KCl, 140 mM NaCl and 0.05% Tween 20, pH 7.4, further improved protein purity levels. Using Escherichia coli cell lysates expressing 90 recombinant Streptococcus pneumoniae proteins, 73 proteins were successfully immobilized, and 66 proteins were in situ purified with greater than 90% purity. We identified several antigens among the in situ-purified proteins via assays with anti-S. pneumoniae rabbit antibodies and a human patient antiserum, as a demonstration project of large scale microarray-based immunoproteomics profiling. The methodology is compatible with higher throughput formats of in vivo protein expression, eliminates the need for resin-based purification and circumvents

Utility of the pooling approach as applied to whole genome association scans with high-density Affymetrix microarrays

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Gray Joanna

2010-11-01

Full Text Available Abstract Background We report an attempt to extend the previously successful approach of combining SNP (single nucleotide polymorphism microarrays and DNA pooling (SNP-MaP employing high-density microarrays. Whereas earlier studies employed a range of Affymetrix SNP microarrays comprising from 10 K to 500 K SNPs, this most recent investigation used the 6.0 chip which displays 906,600 SNP probes and 946,000 probes for the interrogation of CNVs (copy number variations. The genotyping assay using the Affymetrix SNP 6.0 array is highly demanding on sample quality due to the small feature size, low redundancy, and lack of mismatch probes. Findings In the first study published so far using this microarray on pooled DNA, we found that pooled cheek swab DNA could not accurately predict real allele frequencies of the samples that comprised the pools. In contrast, the allele frequency estimates using blood DNA pools were reasonable, although inferior compared to those obtained with previously employed Affymetrix microarrays. However, it might be possible to improve performance by developing improved analysis methods. Conclusions Despite the decreasing costs of genome-wide individual genotyping, the pooling approach may have applications in very large-scale case-control association studies. In such cases, our study suggests that high-quality DNA preparations and lower density platforms should be preferred.

Geiger mode avalanche photodiodes for microarray systems

Science.gov (United States)

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.

Support vector machine and principal component analysis for microarray data classification

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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.

Mechanic effect of pulsed focused ultrasound in tumor and muscle tissue evaluated by MRI, histology, and microarray analysis

International Nuclear Information System (INIS)

Hundt, Walter; Yuh, Esther L.; Steinbach, Silke; Bednarski, Mark D.; Guccione, Samira

2010-01-01

The purpose of this study was to investigate the effect of pulsed high-intensity focused ultrasound (HIFU) to tumor and muscle tissue. Pulsed HIFU was applied to tumor and muscle tissue in C3H/Km mice. Three hours after HIFU treatment pre- and post-contrast T1-wt, T2-wt images and a diffusion-wt STEAM-sequence were obtained. After MR imaging, the animals were euthenized and the treated tumor and muscle was taken out for histology and functional genomic analysis. In the tumor tissue a slight increase of the diffusion coefficient could be found. In the muscle tissue T2 images showed increased signal intensity and post-contrast T1 showed a decreased contrast uptake in the center and a severe contrast uptake in the surrounding muscle tissue. A significant increase of the diffusion coefficient was found. Gene expression analysis revealed profound changes in the expression levels of 29 genes being up-regulated and 3 genes being down-regulated in the muscle tissue and 31 genes being up-regulated and 15 genes being down-regulated in the SCCVII tumor tissue. Seven genes were up-regulated in both tissue types. The highest up-regulated gene in the tumor and muscle tissue encoded for Mouse histone H2A.1 gene (FC = 13.2 ± 20.6) and Apolipoprotein E (FC = 12.8 ± 27.4) respectively MHC class III (FC = 83.7 ± 67.4) and hsp70 (FC = 75.3 ± 85.0). Immunoblot confirmed the presence of HSP70 protein in the muscle tissue. Pulsed HIFU treatment on tumor and muscle tissue results in dramatic changes in gene expression, indicating that the effect of pulsed HIFU is in some regard dependent and also independent of the tissue type.

Microarray studies on lager brewer's yeasts reveal cell status in the process of autolysis.

Science.gov (United States)

Xu, Weina; Wang, Jinjing; Li, Qi

2014-08-01

In this work, we performed DNA microarray studies on lager brewer's yeast Saccharomyces pastorianus to investigate changes in gene expression in the process of autolysis. The two strains we used were Qing2 and 5-2. Strain 5-2 is a mutant of Qing2 and autolyzes much more slowly than its parent strain. Four samples of these two strains during different autolysis stages (0% and 15%) were tested using DNA microarray containing > 10,000 yeast's genes. Analysis of genes with the same transcription pattern (up- or down-regulated in both strains) showed that the same 99 genes were up-regulated (transcription levels were increased), and the same 97 genes were down-regulated (transcription levels were decreased) by fivefold or more during autolysis. Genes involved in energy production/utilization, protein anabolism, and stress response were down-regulated. Genes related to cell wall organization and biogenesis, starvation response and DNA damage response were up-regulated. Analysis of genes with opposite transcription patterns (up-regulated in one strain and down-regulated in the other one) showed that 246 genes were up-regulated in 5-2 (autolyzes slowly) and down-regulated in Qing2 (autolyzes rapidly). Another 18 genes had opposite transcription levels, indicating that the strain which autolyzes slowly had better cell vitality despite the same autolysis stage. These findings might further promote the global understanding of autolysis in yeast. © 2014 Federation of European Microbiological Societies. Published by John Wiley & Sons Ltd. All rights reserved.

Advanced Data Mining of Leukemia Cells Micro-Arrays

OpenAIRE

Richard S. Segall; Ryan M. Pierce

2009-01-01

This paper provides continuation and extensions of previous research by Segall and Pierce (2009a) that discussed data mining for micro-array databases of Leukemia cells for primarily self-organized maps (SOM). As Segall and Pierce (2009a) and Segall and Pierce (2009b) the results of applying data mining are shown and discussed for the data categories of microarray databases of HL60, Jurkat, NB4 and U937 Leukemia cells that are also described in this article. First, a background section is pro...

Evaluation of HER2 Gene Amplification in Breast Cancer Using Nuclei Microarray in Situ Hybridization

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Xuefeng Zhang

2012-05-01

Full Text Available Fluorescence in situ hybridization (FISH assay is considered the “gold standard” in evaluating HER2/neu (HER2 gene status. However, FISH detection is costly and time consuming. Thus, we established nuclei microarray with extracted intact nuclei from paraffin embedded breast cancer tissues for FISH detection. The nuclei microarray FISH (NMFISH technology serves as a useful platform for analyzing HER2 gene/chromosome 17 centromere ratio. We examined HER2 gene status in 152 cases of invasive ductal carcinomas of the breast that were resected surgically with FISH and NMFISH. HER2 gene amplification status was classified according to the guidelines of the American Society of Clinical Oncology and College of American Pathologists (ASCO/CAP. Comparison of the cut-off values for HER2/chromosome 17 centromere copy number ratio obtained by NMFISH and FISH showed that there was almost perfect agreement between the two methods (κ coefficient 0.920. The results of the two methods were almost consistent for the evaluation of HER2 gene counts. The present study proved that NMFISH is comparable with FISH for evaluating HER2 gene status. The use of nuclei microarray technology is highly efficient, time and reagent conserving and inexpensive.

Investigation of archived formalin-fixed paraffin-embedded pancreatic tissue with whole-genome gene expression microarray

DEFF Research Database (Denmark)

Michelsen, Nete Vinstrup; Brusgaard, Klaus; Tan, Qihua

2011-01-01

The use of formalin-fixed, paraffin-embedded (FFPE) tissue overcomes the most prominent issues related to research on relatively rare diseases: limited sample size, availability of control tissue, and time frame. The use of FFPE pancreatic tissue in GEM may be especially challenging due to its very...

Can Archival Tissue Reveal Answers to Modern Research Questions?: Computer-Aided Histological Assessment of Neuroblastoma Tumours Collected over 60 Years

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Albert Chetcuti

2014-02-01

Full Text Available Despite neuroblastoma being the most common extracranial solid cancer in childhood, it is still a rare disease. Consequently, the unavailability of tissue for research limits the statistical power of studies. Pathology archives are possible sources of rare tissue, which, if proven to remain consistent over time, could prove useful to research of rare disease types. We applied immunohistochemistry to investigate whether long term storage caused any changes to antigens used diagnostically for neuroblastoma. We constructed and quantitatively assessed a tissue microarray containing neuroblastoma archival material dating between 1950 and 2007. A total of 119 neuroblastoma tissue cores were included spanning 6 decades. Fourteen antibodies were screened across the tissue microarray (TMA. These included seven positive neuroblastoma diagnosis markers (NB84, Chromogranin A, NSE, Ki-67, INI1, Neurofilament Protein, Synaptophysin, two anticipated to be negative (S100A, CD99, and five research antibodies (IL-7, IL-7R, JAK1, JAK3, STAT5. The staining of these antibodies was evaluated using Aperio ImageScope software along with novel pattern recognition and quantification algorithms. This analysis demonstrated that marker signal intensity did not decrease over time and that storage for 60 years had little effect on antigenicity. The construction and assessment of this neuroblastoma TMA has demonstrated the feasibility of using archival samples for research.

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

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Danielle E Green

2015-01-01

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

Towards the integration, annotation and association of historical microarray experiments with RNA-seq.

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Chavan, Shweta S; Bauer, Michael A; Peterson, Erich A; Heuck, Christoph J; Johann, Donald J

2013-01-01

Transcriptome analysis by microarrays has produced important advances in biomedicine. For instance in multiple myeloma (MM), microarray approaches led to the development of an effective disease subtyping via cluster assignment, and a 70 gene risk score. Both enabled an improved molecular understanding of MM, and have provided prognostic information for the purposes of clinical management. Many researchers are now transitioning to Next Generation Sequencing (NGS) approaches and RNA-seq in particular, due to its discovery-based nature, improved sensitivity, and dynamic range. Additionally, RNA-seq allows for the analysis of gene isoforms, splice variants, and novel gene fusions. Given the voluminous amounts of historical microarray data, there is now a need to associate and integrate microarray and RNA-seq data via advanced bioinformatic approaches. Custom software was developed following a model-view-controller (MVC) approach to integrate Affymetrix probe set-IDs, and gene annotation information from a variety of sources. The tool/approach employs an assortment of strategies to integrate, cross reference, and associate microarray and RNA-seq datasets. Output from a variety of transcriptome reconstruction and quantitation tools (e.g., Cufflinks) can be directly integrated, and/or associated with Affymetrix probe set data, as well as necessary gene identifiers and/or symbols from a diversity of sources. Strategies are employed to maximize the annotation and cross referencing process. Custom gene sets (e.g., MM 70 risk score (GEP-70)) can be specified, and the tool can be directly assimilated into an RNA-seq pipeline. A novel bioinformatic approach to aid in the facilitation of both annotation and association of historic microarray data, in conjunction with richer RNA-seq data, is now assisting with the study of MM cancer biology.

Gene selection for microarray data classification via subspace learning and manifold regularization.

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Tang, Chang; Cao, Lijuan; Zheng, Xiao; Wang, Minhui

2017-12-19

With the rapid development of DNA microarray technology, large amount of genomic data has been generated. Classification of these microarray data is a challenge task since gene expression data are often with thousands of genes but a small number of samples. In this paper, an effective gene selection method is proposed to select the best subset of genes for microarray data with the irrelevant and redundant genes removed. Compared with original data, the selected gene subset can benefit the classification task. We formulate the gene selection task as a manifold regularized subspace learning problem. In detail, a projection matrix is used to project the original high dimensional microarray data into a lower dimensional subspace, with the constraint that the original genes can be well represented by the selected genes. Meanwhile, the local manifold structure of original data is preserved by a Laplacian graph regularization term on the low-dimensional data space. The projection matrix can serve as an importance indicator of different genes. An iterative update algorithm is developed for solving the problem. Experimental results on six publicly available microarray datasets and one clinical dataset demonstrate that the proposed method performs better when compared with other state-of-the-art methods in terms of microarray data classification. Graphical Abstract The graphical abstract of this work.

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

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Cohen Aaron

2009-02-01

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

Exploring the use of internal and externalcontrols for assessing microarray technical performance

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Game Laurence

2010-12-01

Full Text Available Abstract Background The maturing of gene expression microarray technology and interest in the use of microarray-based applications for clinical and diagnostic applications calls for quantitative measures of quality. This manuscript presents a retrospective study characterizing several approaches to assess technical performance of microarray data measured on the Affymetrix GeneChip platform, including whole-array metrics and information from a standard mixture of external spike-in and endogenous internal controls. Spike-in controls were found to carry the same information about technical performance as whole-array metrics and endogenous "housekeeping" genes. These results support the use of spike-in controls as general tools for performance assessment across time, experimenters and array batches, suggesting that they have potential for comparison of microarray data generated across species using different technologies. Results A layered PCA modeling methodology that uses data from a number of classes of controls (spike-in hybridization, spike-in polyA+, internal RNA degradation, endogenous or "housekeeping genes" was used for the assessment of microarray data quality. The controls provide information on multiple stages of the experimental protocol (e.g., hybridization, RNA amplification. External spike-in, hybridization and RNA labeling controls provide information related to both assay and hybridization performance whereas internal endogenous controls provide quality information on the biological sample. We find that the variance of the data generated from the external and internal controls carries critical information about technical performance; the PCA dissection of this variance is consistent with whole-array quality assessment based on a number of quality assurance/quality control (QA/QC metrics. Conclusions These results provide support for the use of both external and internal RNA control data to assess the technical quality of microarray

Carbonic Anhydrase IX is Not a Predictor of Outcomes in Non-Metastatic Clear Cell Renal Cell Carcinoma - A Digital Analysis of Tissue Microarray

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Marcelo Zerati

2013-07-01

Full Text Available Introduction The knowledge about the molecular biology of clear cell renal cell carcinoma (ccRCC is evolving, and Carbonic Anhydrase type IX (CA-IX has emerged as a potential prognostic marker in this challenging disease. However, most of the literature about CA-IX on ccRCC comes from series on metastatic cancer, with a lack of series on non-metastatic cancer. The objective is to evaluate the expression of CA-IX in a cohort of non-metastatic ccRCC, correlating with 1 overall survival, and 2 with established prognostic parameters (T stage, tumor size, Fuhrman nuclear grade, microvascular invasion and peri-renal fat invasion. Materials and Methods This is a retrospective cohort study. We evaluated 95 patients with non-metastatic clear cell renal cell carcinoma, as to the expression of CA-IX. The analyzed parameters where: overall survival (OS, TNM stage, tumor size (TS, Fuhrman nuclear grade (FNG, microvascular invasion (MVI, peri-renal fat invasion (PFI. We utilized a custom built tissue microarray, and the immunoexpression was digitally quantified using the Photoshop® software. Results: Th e mean follow-up time was 7.9 years (range 1.9 to 19.5 years. The analysis of CA-IX expression against the selected prognostic parameters showed no correlation. The results are as follows: Overall survival (p = 0.790; T stage (p = 0.179; tumor size (p = 0.143; grouped Fuhrman nuclear grade (p = 0.598; microvascular invasion (p = 0.685, and peri-renal fat invasion (p = 0.104. Conclusion Carbonic anhydrase type IX expression does not correlate with overall survival and conventional prognostic parameters in non-metastatic clear cell renal cell carcinoma.

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

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Dash, Rasmita; Misra, Bijan Bihari

2018-03-01

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

A Reliable and Distributed LIMS for Efficient Management of the Microarray Experiment Environment

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Jin Hee-Jeong

2007-03-01

Full Text Available A microarray is a principal technology in molecular biology. It generates thousands of expressions of genotypes at once. Typically, a microarray experiment contains many kinds of information, such as gene names, sequences, expression profiles, scanned images, and annotation. So, the organization and analysis of vast amounts of data are required. Microarray LIMS (Laboratory Information Management System provides data management, search, and basic analysis. Recently, microarray joint researches, such as the skeletal system disease and anti-cancer medicine have been widely conducted. This research requires data sharing among laboratories within the joint research group. In this paper, we introduce a web based microarray LIMS, SMILE (Small and solid MIcroarray Lims for Experimenters, especially for shared data management. The data sharing function of SMILE is based on Friend-to-Friend (F2F, which is based on anonymous P2P (Peer-to-Peer, in which people connect directly with their “friends”. It only allows its friends to exchange data directly using IP addresses or digital signatures you trust. In SMILE, there are two types of friends: “service provider”, which provides data, and “client”, which is provided with data. So, the service provider provides shared data only to its clients. SMILE provides useful functions for microarray experiments, such as variant data management, image analysis, normalization, system management, project schedule management, and shared data management. Moreover, it connections with two systems: ArrayMall for analyzing microarray images and GENAW for constructing a genetic network. SMILE is available on http://neobio.cs.pusan.ac.kr:8080/smile.

Development of DNA Microarrays for Metabolic Pathway and Bioprocess Monitoring

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Gregory Stephanopoulos

2004-07-31

Transcriptional profiling experiments utilizing DNA microarrays to study the intracellular accumulation of PHB in Synechocystis has proved difficult in large part because strains that show significant differences in PHB which would justify global analysis of gene expression have not been isolated.

Circadian clocks are resounding in peripheral tissues.

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Andrey A Ptitsyn

2006-03-01

Full Text Available Circadian rhythms are prevalent in most organisms. Even the smallest disturbances in the orchestration of circadian gene expression patterns among different tissues can result in functional asynchrony, at the organism level, and may to contribute to a wide range of physiologic disorders. It has been reported that as many as 5%-10% of transcribed genes in peripheral tissues follow a circadian expression pattern. We have conducted a comprehensive study of circadian gene expression on a large dataset representing three different peripheral tissues. The data have been produced in a large-scale microarray experiment covering replicate daily cycles in murine white and brown adipose tissues as well as in liver. We have applied three alternative algorithmic approaches to identify circadian oscillation in time series expression profiles. Analyses of our own data indicate that the expression of at least 7% to 21% of active genes in mouse liver, and in white and brown adipose tissues follow a daily oscillatory pattern. Indeed, analysis of data from other laboratories suggests that the percentage of genes with an oscillatory pattern may approach 50% in the liver. For the rest of the genes, oscillation appears to be obscured by stochastic noise. Our phase classification and computer simulation studies based on multiple datasets indicate no detectable boundary between oscillating and non-oscillating fractions of genes. We conclude that greater attention should be given to the potential influence of circadian mechanisms on any biological pathway related to metabolism and obesity.

Detection of Alicyclobacillus species in fruit juice using a random genomic DNA microarray chip.

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Jang, Jun Hyeong; Kim, Sun-Joong; Yoon, Bo Hyun; Ryu, Jee-Hoon; Gu, Man Bock; Chang, Hyo-Ihl

2011-06-01

This study describes a method using a DNA microarray chip to rapidly and simultaneously detect Alicyclobacillus species in orange juice based on the hybridization of genomic DNA with random probes. Three food spoilage bacteria were used in this study: Alicyclobacillus acidocaldarius, Alicyclobacillus acidoterrestris, and Alicyclobacillus cycloheptanicus. The three Alicyclobacillus species were adjusted to 2 × 10(3) CFU/ml and inoculated into pasteurized 100% pure orange juice. Cy5-dCTP labeling was used for reference signals, and Cy3-dCTP was labeled for target genomic DNA. The molar ratio of 1:1 of Cy3-dCTP and Cy5-dCTP was used. DNA microarray chips were fabricated using randomly fragmented DNA of Alicyclobacillus spp. and were hybridized with genomic DNA extracted from Bacillus spp. Genomic DNA extracted from Alicyclobacillus spp. showed a significantly higher hybridization rate compared with DNA of Bacillus spp., thereby distinguishing Alicyclobacillus spp. from Bacillus spp. The results showed that the microarray DNA chip containing randomly fragmented genomic DNA was specific and clearly identified specific food spoilage bacteria. This microarray system is a good tool for rapid and specific detection of thermophilic spoilage bacteria, mainly Alicyclobacillus spp., and is useful and applicable to the fruit juice industry.

Comparison of small n statistical tests of differential expression applied to microarrays

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Lee Anna Y

2009-02-01

Full Text Available Abstract Background DNA microarrays provide data for genome wide patterns of expression between observation classes. Microarray studies often have small samples sizes, however, due to cost constraints or specimen availability. This can lead to poor random error estimates and inaccurate statistical tests of differential expression. We compare the performance of the standard t-test, fold change, and four small n statistical test methods designed to circumvent these problems. We report results of various normalization methods for empirical microarray data and of various random error models for simulated data. Results Three Empirical Bayes methods (CyberT, BRB, and limma t-statistics were the most effective statistical tests across simulated and both 2-colour cDNA and Affymetrix experimental data. The CyberT regularized t-statistic in particular was able to maintain expected false positive rates with simulated data showing high variances at low gene intensities, although at the cost of low true positive rates. The Local Pooled Error (LPE test introduced a bias that lowered false positive rates below theoretically expected values and had lower power relative to the top performers. The standard two-sample t-test and fold change were also found to be sub-optimal for detecting differentially expressed genes. The generalized log transformation was shown to be beneficial in improving results with certain data sets, in particular high variance cDNA data. Conclusion Pre-processing of data influences performance and the proper combination of pre-processing and statistical testing is necessary for obtaining the best results. All three Empirical Bayes methods assessed in our study are good choices for statistical tests for small n microarray studies for both Affymetrix and cDNA data. Choice of method for a particular study will depend on software and normalization preferences.

Identification and prognostic value of anterior gradient protein 2 expression in breast cancer based on tissue microarray.

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Guo, Jilong; Gong, Guohua; Zhang, Bin

2017-07-01

Breast cancer has attracted substantial attention as one of the major cancers causing death in women. It is crucial to find potential biomarkers of prognostic value in breast cancer. In this study, the expression pattern of anterior gradient protein 2 in breast cancer was identified based on the main molecular subgroups. Through analysis of 69 samples from the Gene Expression Omnibus database, we found that anterior gradient protein 2 expression was significantly higher in non-triple-negative breast cancer tissues compared with normal tissues and triple-negative breast cancer tissues (p gradient protein 2 expression pattern. Furthermore, we performed immunohistochemical analysis. The quantification results revealed that anterior gradient protein 2 is highly expressed in non-triple-negative breast cancer (grade 3 excluded) and grade 1 + 2 (triple-negative breast cancer excluded) tumours compared with normal tissues. Anterior gradient protein 2 was significantly highly expressed in non-triple-negative breast cancer (grade 3 excluded) and non-triple-negative breast cancer tissues compared with triple-negative breast cancer tissues (p gradient protein 2 was significantly highly expressed in grade 1 + 2 (triple-negative breast cancer excluded) and grade 1 + 2 tissues compared with grade 3 tissues (p gradient protein 2 expression was significantly associated with histologic type, histological grade, oestrogen status and progesterone status. Univariate analysis of clinicopathological variables showed that anterior gradient protein 2 expression, tumour size and lymph node status were significantly correlated with overall survival in patients with grade 1 and 2 tumours. Cox multivariate analysis revealed anterior gradient protein 2 as a putative independent indicator of unfavourable outcomes (p = 0.031). All these data clearly showed that anterior gradient protein 2 is highly expressed in breast cancer and can be regarded as a putative biomarker for

Normalization for triple-target microarray experiments

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Magniette Frederic

2008-04-01

Full Text Available Abstract Background Most microarray studies are made using labelling with one or two dyes which allows the hybridization of one or two samples on the same slide. In such experiments, the most frequently used dyes are Cy3 and Cy5. Recent improvements in the technology (dye-labelling, scanner and, image analysis allow hybridization up to four samples simultaneously. The two additional dyes are Alexa488 and Alexa494. The triple-target or four-target technology is very promising, since it allows more flexibility in the design of experiments, an increase in the statistical power when comparing gene expressions induced by different conditions and a scaled down number of slides. However, there have been few methods proposed for statistical analysis of such data. Moreover the lowess correction of the global dye effect is available for only two-color experiments, and even if its application can be derived, it does not allow simultaneous correction of the raw data. Results We propose a two-step normalization procedure for triple-target experiments. First the dye bleeding is evaluated and corrected if necessary. Then the signal in each channel is normalized using a generalized lowess procedure to correct a global dye bias. The normalization procedure is validated using triple-self experiments and by comparing the results of triple-target and two-color experiments. Although the focus is on triple-target microarrays, the proposed method can be used to normalize p differently labelled targets co-hybridized on a same array, for any value of p greater than 2. Conclusion The proposed normalization procedure is effective: the technical biases are reduced, the number of false positives is under control in the analysis of differentially expressed genes, and the triple-target experiments are more powerful than the corresponding two-color experiments. There is room for improving the microarray experiments by simultaneously hybridizing more than two samples.

FiGS: a filter-based gene selection workbench for microarray data

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Yun Taegyun

2010-01-01

Full Text Available Abstract Background The selection of genes that discriminate disease classes from microarray data is widely used for the identification of diagnostic biomarkers. Although various gene selection methods are currently available and some of them have shown excellent performance, no single method can retain the best performance for all types of microarray datasets. It is desirable to use a comparative approach to find the best gene selection result after rigorous test of different methodological strategies for a given microarray dataset. Results FiGS is a web-based workbench that automatically compares various gene selection procedures and provides the optimal gene selection result for an input microarray dataset. FiGS builds up diverse gene selection procedures by aligning different feature selection techniques and classifiers. In addition to the highly reputed techniques, FiGS diversifies the gene selection procedures by incorporating gene clustering options in the feature selection step and different data pre-processing options in classifier training step. All candidate gene selection procedures are evaluated by the .632+ bootstrap errors and listed with their classification accuracies and selected gene sets. FiGS runs on parallelized computing nodes that capacitate heavy computations. FiGS is freely accessible at http://gexp.kaist.ac.kr/figs. Conclusion FiGS is an web-based application that automates an extensive search for the optimized gene selection analysis for a microarray dataset in a parallel computing environment. FiGS will provide both an efficient and comprehensive means of acquiring optimal gene sets that discriminate disease states from microarray datasets.

Carbohydrate Microarray on Glass: a Tool for Carbohydrate-Lectin Interactions

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Tetala, K.K.R.; Giesbers, M.; Visser, G.M.; Sudhölter, E.J.R.; Beek, van T.A.

2007-01-01

A simple method to immobilize carbohydrates on a glass surface to obtain a carbohydrate microarray is described. The array was used to study carbohydrate-lectin interactions. The glass surface was modified with aldehyde terminated linker groups of various chain lengths. Coupling of carbohydrates

Transcription analysis of apple fruit development using cDNA microarrays

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Soglio, V.; Costa, F.; Molthoff, J.W.; Weemen-Hendriks, M.; Schouten, H.J.; Gianfranceschi, L.

2009-01-01

The knowledge of the molecular mechanisms underlying fruit quality traits is fundamental to devise efficient marker-assisted selection strategies and to improve apple breeding. In this study, cDNA microarray technology was used to identify genes whose expression changes during fruit development and

Fluorescent microarray for multiplexed quantification of environmental contaminants in seawater samples

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The development of a fluorescent multiplexed microarray platform able to detect and quantify a wide variety of pollutants in seawater is reported. The microarray platform has been manufactured by spotting 6 different bioconjugate competitors and it uses a cocktail of 6 monoclonal and polyclonal anti...

Calling biomarkers in milk using a protein microarray on your smartphone

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Ludwig, S.K.J.; Tokarski, Christian; Lang, Stefan N.; Ginkel, Van L.A.; Zhu, Hongying; Ozcan, Aydogan; Nielen, M.W.F.

2015-01-01

Here we present the concept of a protein microarray-based fluorescence immunoassay for multiple biomarker detection in milk extracts by an ordinary smartphone. A multiplex immunoassay was designed on a microarray chip, having built-in positive and negative quality controls. After the immunoassay

Detecting variants with Metabolic Design, a new software tool to design probes for explorative functional DNA microarray development

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Gravelat Fabrice

2010-09-01

Full Text Available Abstract Background Microorganisms display vast diversity, and each one has its own set of genes, cell components and metabolic reactions. To assess their huge unexploited metabolic potential in different ecosystems, we need high throughput tools, such as functional microarrays, that allow the simultaneous analysis of thousands of genes. However, most classical functional microarrays use specific probes that monitor only known sequences, and so fail to cover the full microbial gene diversity present in complex environments. We have thus developed an algorithm, implemented in the user-friendly program Metabolic Design, to design efficient explorative probes. Results First we have validated our approach by studying eight enzymes involved in the degradation of polycyclic aromatic hydrocarbons from the model strain Sphingomonas paucimobilis sp. EPA505 using a designed microarray of 8,048 probes. As expected, microarray assays identified the targeted set of genes induced during biodegradation kinetics experiments with various pollutants. We have then confirmed the identity of these new genes by sequencing, and corroborated the quantitative discrimination of our microarray by quantitative real-time PCR. Finally, we have assessed metabolic capacities of microbial communities in soil contaminated with aromatic hydrocarbons. Results show that our probe design (sensitivity and explorative quality can be used to study a complex environment efficiently. Conclusions We successfully use our microarray to detect gene expression encoding enzymes involved in polycyclic aromatic hydrocarbon degradation for the model strain. In addition, DNA microarray experiments performed on soil polluted by organic pollutants without prior sequence assumptions demonstrate high specificity and sensitivity for gene detection. Metabolic Design is thus a powerful, efficient tool that can be used to design explorative probes and monitor metabolic pathways in complex environments

Bone health nutraceuticals alter microarray mRNA gene expression: A randomized, parallel, open-label clinical study.

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Lin, Yumei; Kazlova, Valentina; Ramakrishnan, Shyam; Murray, Mary A; Fast, David; Chandra, Amitabh; Gellenbeck, Kevin W

2016-01-15

Dietary intake of fruits and vegetables has been suggested to have a role in promoting bone health. More specifically, the polyphenols they contain have been linked to physiological effects related to bone mineral density and bone metabolism. In this research, we use standard microarray analyses of peripheral whole blood from post-menopausal women treated with two fixed combinations of plant extracts standardized to polyphenol content to identify differentially expressed genes relevant to bone health. In this 28-day open-label study, healthy post-menopausal women were randomized into three groups, each receiving one of three investigational fixed combinations of plant extracts: an anti-resorptive (AR) combination of pomegranate fruit (Punica granatum L.) and grape seed (Vitis vinifera L.) extracts; a bone formation (BF) combination of quercetin (Dimorphandra mollis Benth) and licorice (Glycyrrhiza glabra L.) extracts; and a fixed combination of all four plant extracts (AR plus BF). Standard microarray analysis was performed on peripheral whole blood samples taken before and after each treatment. Annotated genes were analyzed for their association to bone health by comparison to a gene library. The AR combination down-regulated a number of genes involved in reduction of bone resorption including cathepsin G (CTSG) and tachykinin receptor 1 (TACR1). The AR combination also up-regulated genes associated with formation of extracellular matrix including heparan sulfate proteoglycan 2 (HSPG2) and hyaluronoglucosaminidase 1 (HYAL1). In contrast, treatment with the BF combination resulted in up-regulation of bone morphogenetic protein 2 (BMP-2) and COL1A1 (collagen type I α1) genes which are linked to bone and collagen formation while down-regulating genes linked to osteoclastogenesis. Treatment with a combination of all four plant extracts had a distinctly different effect on gene expression than the results of the AR and BF combinations individually. These results could

Spatial changes in acid secretion from isolated stomach tissue using a pH-histamine sensing microarray.

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Bitziou, Eleni; O'Hare, Danny; Patel, Bhavik Anil

2010-03-01

The acid secretion mechanism can be studied by measuring a series of metabolic markers and neurotransmitters from in vitro isolated tissue. A microelectrode array was used to monitor proton concentration and histamine levels from isolated guinea pig stomach tissue. The device was partially modified using iridium oxide to form a series of pH sensors, whereas unmodified gold microelectrodes were used to measure the level of histamine in the gut. Real-time measurements in the presence of the H2-receptor antagonist ranitidine produced significant decreases in the overall Delta pH response, as expected. Also, a significant variation in the Delta pH response in between pH sensors was observed in the presence of pharmacological treatment due to structural features of the tissue. No significant differences in Delta i(H) were detected in the presence of ranitidine as expected. More significantly, clear variations in Delta pH responses between animals in control conditions and those in the presence of ranitidine was observed highlighting possible variation in parietal cell density and/or variations in tissue activity. These results identify great possibilities in applying these multi-sensing devices as a long-term stable personalised diagnostic tool for pharmacological screening and disease status.

Hybridization chain reaction amplification for highly sensitive fluorescence detection of DNA with dextran coated microarrays.

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Chao, Jie; Li, Zhenhua; Li, Jing; Peng, Hongzhen; Su, Shao; Li, Qian; Zhu, Changfeng; Zuo, Xiaolei; Song, Shiping; Wang, Lianhui; Wang, Lihua

2016-07-15

Microarrays of biomolecules hold great promise in the fields of genomics, proteomics, and clinical assays on account of their remarkably parallel and high-throughput assay capability. However, the fluorescence detection used in most conventional DNA microarrays is still limited by sensitivity. In this study, we have demonstrated a novel universal and highly sensitive platform for fluorescent detection of sequence specific DNA at the femtomolar level by combining dextran-coated microarrays with hybridization chain reaction (HCR) signal amplification. Three-dimensional dextran matrix was covalently coated on glass surface as the scaffold to immobilize DNA recognition probes to increase the surface binding capacity and accessibility. DNA nanowire tentacles were formed on the matrix surface for efficient signal amplification by capturing multiple fluorescent molecules in a highly ordered way. By quantifying microscopic fluorescent signals, the synergetic effects of dextran and HCR greatly improved sensitivity of DNA microarrays, with a detection limit of 10fM (1×10(5) molecules). This detection assay could recognize one-base mismatch with fluorescence signals dropped down to ~20%. This cost-effective microarray platform also worked well with samples in serum and thus shows great potential for clinical diagnosis. Copyright © 2016 Elsevier B.V. All rights reserved.

High-Dimensional Additive Hazards Regression for Oral Squamous Cell Carcinoma Using Microarray Data: A Comparative Study

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Omid Hamidi

2014-01-01

Full Text Available Microarray technology results in high-dimensional and low-sample size data sets. Therefore, fitting sparse models is substantial because only a small number of influential genes can reliably be identified. A number of variable selection approaches have been proposed for high-dimensional time-to-event data based on Cox proportional hazards where censoring is present. The present study applied three sparse variable selection techniques of Lasso, smoothly clipped absolute deviation and the smooth integration of counting, and absolute deviation for gene expression survival time data using the additive risk model which is adopted when the absolute effects of multiple predictors on the hazard function are of interest. The performances of used techniques were evaluated by time dependent ROC curve and bootstrap .632+ prediction error curves. The selected genes by all methods were highly significant (P<0.001. The Lasso showed maximum median of area under ROC curve over time (0.95 and smoothly clipped absolute deviation showed the lowest prediction error (0.105. It was observed that the selected genes by all methods improved the prediction of purely clinical model indicating the valuable information containing in the microarray features. So it was concluded that used approaches can satisfactorily predict survival based on selected gene expression measurements.

The MGED Ontology: a resource for semantics-based description of microarray experiments.

Science.gov (United States)

Whetzel, Patricia L; Parkinson, Helen; Causton, Helen C; Fan, Liju; Fostel, Jennifer; Fragoso, Gilberto; Game, Laurence; Heiskanen, Mervi; Morrison, Norman; Rocca-Serra, Philippe; Sansone, Susanna-Assunta; Taylor, Chris; White, Joseph; Stoeckert, Christian J

2006-04-01

The generation of large amounts of microarray data and the need to share these data bring challenges for both data management and annotation and highlights the need for standards. MIAME specifies the minimum information needed to describe a microarray experiment and the Microarray Gene Expression Object Model (MAGE-OM) and resulting MAGE-ML provide a mechanism to standardize data representation for data exchange, however a common terminology for data annotation is needed to support these standards. Here we describe the MGED Ontology (MO) developed by the Ontology Working Group of the Microarray Gene Expression Data (MGED) Society. The MO provides terms for annotating all aspects of a microarray experiment from the design of the experiment and array layout, through to the preparation of the biological sample and the protocols used to hybridize the RNA and analyze the data. The MO was developed to provide terms for annotating experiments in line with the MIAME guidelines, i.e. to provide the semantics to describe a microarray experiment according to the concepts specified in MIAME. The MO does not attempt to incorporate terms from existing ontologies, e.g. those that deal with anatomical parts or developmental stages terms, but provides a framework to reference terms in other ontologies and therefore facilitates the use of ontologies in microarray data annotation. The MGED Ontology version.1.2.0 is available as a file in both DAML and OWL formats at http://mged.sourceforge.net/ontologies/index.php. Release notes and annotation examples are provided. The MO is also provided via the NCICB's Enterprise Vocabulary System (http://nciterms.nci.nih.gov/NCIBrowser/Dictionary.do). Stoeckrt@pcbi.upenn.edu Supplementary data are available at Bioinformatics online.

Overexpression of arginine transporter CAT-1 is associated with accumulation of L-arginine and cell growth in human colorectal cancer tissue.

Directory of Open Access Journals (Sweden)

Ying Lu

Full Text Available We previously showed that L-arginine (Arg accumulates in colorectal cancer tissues. The aim of this study was to investigate the mechanism by which Arg accumulates and determine its biological significance. The concentration of Arg and Citrulline (Cit in sera and tumor tissues from colorectal cancer (CRC patients was analyzed by high-performance liquid chromatography (HPLC. The expression of Arg transporters was analyzed by quantitative reverse transcription polymerase chain reaction (qRT-PCR and immunohistochemical analysis of tissue microarray. We also transfected the colon cancer cell line HCT-116 with siRNA specific for the Arg transporter CAT-1 and measured the induction of apoptosis by flow cytometry and cell proliferation by MTT assay. Consistent with our previous results, serum Arg and Cit concentrations in colorectal cancer patients were significantly lower than those in normal volunteers, while Arg and Cit concentrations in colorectal cancer tissues were significantly higher than in matched adjacent normal colon tissues. Quantitative RT-PCR showed that the CAT-1 gene was highly overexpressed in 70.5% of colorectal cancer tissue samples relative to adjacent normal colon tissues in all 122 patients with colorectal cancer. Immunohistochemical analysis of tissue microarray confirmed that the expression of CAT-1 was higher in all 25 colorectal cancer tissues tested. CAT-1 siRNA significantly induced apoptosis of HCT-116 cells and subsequently inhibited cell growth by 20-50%. Our findings indicate that accumulation of L-Arg and Cit and cell growth in colorectal cancer tissues is associated with over-expression of the Arg transporter gene CAT-1. Our results may be useful for the development of molecular diagnostic tools and targeted therapy for colorectal cancer.

Multi-task feature selection in microarray data by binary integer programming.

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Lan, Liang; Vucetic, Slobodan

2013-12-20

A major challenge in microarray classification is that the number of features is typically orders of magnitude larger than the number of examples. In this paper, we propose a novel feature filter algorithm to select the feature subset with maximal discriminative power and minimal redundancy by solving a quadratic objective function with binary integer constraints. To improve the computational efficiency, the binary integer constraints are relaxed and a low-rank approximation to the quadratic term is applied. The proposed feature selection algorithm was extended to solve multi-task microarray classification problems. We compared the single-task version of the proposed feature selection algorithm with 9 existing feature selection methods on 4 benchmark microarray data sets. The empirical results show that the proposed method achieved the most accurate predictions overall. We also evaluated the multi-task version of the proposed algorithm on 8 multi-task microarray datasets. The multi-task feature selection algorithm resulted in significantly higher accuracy than when using the single-task feature selection methods.

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

Science.gov (United States)

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

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

Science.gov (United States)

Maslow, Bat-Sheva L; Budinetz, Tara; Sueldo, Carolina; Anspach, Erica; Engmann, Lawrence; Benadiva, Claudio; Nulsen, John C

2015-07-01

To compare the analysis of chromosome number from paraffin-embedded products of conception using single-nucleotide polymorphism (SNP) microarray with the recommended screening for the evaluation of couples presenting with recurrent pregnancy loss who do not have previous fetal cytogenetic data. We performed a retrospective cohort study including all women who presented for a new evaluation of recurrent pregnancy loss over a 2-year period (January 1, 2012, to December 31, 2013). All participants had at least two documented first-trimester losses and both the recommended screening tests and SNP microarray performed on at least one paraffin-embedded products of conception sample. Single-nucleotide polymorphism microarray identifies all 24 chromosomes (22 autosomes, X, and Y). Forty-two women with a total of 178 losses were included in the study. Paraffin-embedded products of conception from 62 losses were sent for SNP microarray. Single-nucleotide polymorphism microarray successfully diagnosed fetal chromosome number in 71% (44/62) of samples, of which 43% (19/44) were euploid and 57% (25/44) were noneuploid. Seven of 42 (17%) participants had abnormalities on recurrent pregnancy loss screening. The per-person detection rate for a cause of pregnancy loss was significantly higher in the SNP microarray (0.50; 95% confidence interval [CI] 0.36-0.64) compared with recurrent pregnancy loss evaluation (0.17; 95% CI 0.08-0.31) (P=.002). Participants with one or more euploid loss identified on paraffin-embedded products of conception were significantly more likely to have an abnormality on recurrent pregnancy loss screening than those with only noneuploid results (P=.028). The significance remained when controlling for age, number of losses, number of samples, and total pregnancies. These results suggest that SNP microarray testing of paraffin-embedded products of conception is a valuable tool for the evaluation of recurrent pregnancy loss in patients without prior fetal

Characteristic mTOR activity in Hodgkin-lymphomas offers a potential therapeutic target in high risk disease – a combined tissue microarray, in vitro and in vivo study

International Nuclear Information System (INIS)

Márk, Ágnes; Kopper, László; Sebestyén, Anna; Hajdu, Melinda; Váradi, Zsófia; Sticz, Tamás Béla; Nagy, Noémi; Csomor, Judit; Berczi, Lajos; Varga, Viktória; Csóka, Monika

2013-01-01

Targeting signaling pathways is an attractive approach in many malignancies. The PI3K/Akt/mTOR pathway is activated in a number of human neoplasms, accompanied by lower overall and/or disease free survival. mTOR kinase inhibitors have been introduced in the therapy of renal cell carcinoma and mantle cell lymphoma, and several trials are currently underway. However, the pathological characterization of mTOR activity in lymphomas is still incomplete. mTOR activity and the elements of mTOR complexes were investigated by immunohistochemistry on tissue microarrays representing different human non-Hodgkin-lymphomas (81 cases) and Hodgkin-lymphomas (87 cases). The expression of phospho-mTOR, phospho-4EBP1, phospho-p70S6K, phospho-S6, Rictor, Raptor and Bcl-2, Bcl-xL, Survivin and NF-kappaB-p50 were evaluated, and mTOR activity was statistically analyzed along with 5-year survival data. The in vitro and in vivo effect of the mTOR inhibitor rapamycin was also examined in human Hodgkin-lymphoma cell lines. The majority (>50%) of mantle cell lymphoma, Burkitt lymphoma, diffuse large B-cell lymphoma, anaplastic large-cell lymphoma and Hodgkin-lymphoma cases showed higher mTOR activity compared to normal lymphoid tissues. Hodgkin-lymphoma was characterized by high mTOR activity in 93% of the cases, and Bcl-xL and NF-kappaB expression correlated with this mTOR activity. High mTOR activity was observed in the case of both favorable and unfavorable clinical response. Low mTOR activity was accompanied by complete remission and at least 5-year disease free survival in Hodgkin-lymphoma patients. However, statistical analysis did not identify correlation beetween mTOR activity and different clinical data of HL patients, such as survival. We also found that Rictor (mTORC2) was not overexpressed in Hodgkin-lymphoma biopsies and cell lines. Rapamycin inhibited proliferation and induced apoptosis in Hodgkin-lymphoma cells both in vitro and in vivo, moreover, it increased the apoptotic

Exploiting fluorescence for multiplex immunoassays on protein microarrays

International Nuclear Information System (INIS)

Herbáth, Melinda; Balogh, Andrea; Matkó, János; Papp, Krisztián; Prechl, József

2014-01-01

Protein microarray technology is becoming the method of choice for identifying protein interaction partners, detecting specific proteins, carbohydrates and lipids, or for characterizing protein interactions and serum antibodies in a massively parallel manner. Availability of the well-established instrumentation of DNA arrays and development of new fluorescent detection instruments promoted the spread of this technique. Fluorescent detection has the advantage of high sensitivity, specificity, simplicity and wide dynamic range required by most measurements. Fluorescence through specifically designed probes and an increasing variety of detection modes offers an excellent tool for such microarray platforms. Measuring for example the level of antibodies, their isotypes and/or antigen specificity simultaneously can offer more complex and comprehensive information about the investigated biological phenomenon, especially if we take into consideration that hundreds of samples can be measured in a single assay. Not only body fluids, but also cell lysates, extracted cellular components, and intact living cells can be analyzed on protein arrays for monitoring functional responses to printed samples on the surface. As a rapidly evolving area, protein microarray technology offers a great bulk of information and new depth of knowledge. These are the features that endow protein arrays with wide applicability and robust sample analyzing capability. On the whole, protein arrays are emerging new tools not just in proteomics, but glycomics, lipidomics, and are also important for immunological research. In this review we attempt to summarize the technical aspects of planar fluorescent microarray technology along with the description of its main immunological applications. (topical review)

Ewing's Sarcoma: An Analysis of miRNA Expression Profiles and Target Genes in Paraffin-Embedded Primary Tumor Tissue.

Science.gov (United States)

Parafioriti, Antonina; Bason, Caterina; Armiraglio, Elisabetta; Calciano, Lucia; Daolio, Primo Andrea; Berardocco, Martina; Di Bernardo, Andrea; Colosimo, Alessia; Luksch, Roberto; Berardi, Anna C

2016-04-30

The molecular mechanism responsible for Ewing's Sarcoma (ES) remains largely unknown. MicroRNAs (miRNAs), a class of small non-coding RNAs able to regulate gene expression, are deregulated in tumors and may serve as a tool for diagnosis and prediction. However, the status of miRNAs in ES has not yet been thoroughly investigated. This study compared global miRNAs expression in paraffin-embedded tumor tissue samples from 20 ES patients, affected by primary untreated tumors, with miRNAs expressed in normal human mesenchymal stromal cells (MSCs) by microarray analysis. A miRTarBase database was used to identify the predicted target genes for differentially expressed miRNAs. The miRNAs microarray analysis revealed distinct patterns of miRNAs expression between ES samples and normal MSCs. 58 of the 954 analyzed miRNAs were significantly differentially expressed in ES samples compared to MSCs. Moreover, the qRT-PCR analysis carried out on three selected miRNAs showed that miR-181b, miR-1915 and miR-1275 were significantly aberrantly regulated, confirming the microarray results. Bio-database analysis identified BCL-2 as a bona fide target gene of the miR-21, miR-181a, miR-181b, miR-29a, miR-29b, miR-497, miR-195, miR-let-7a, miR-34a and miR-1915. Using paraffin-embedded tissues from ES patients, this study has identified several potential target miRNAs and one gene that might be considered a novel critical biomarker for ES pathogenesis.

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

Science.gov (United States)

Sitaraman, Kalavathy; Chatterjee, Deb K

2011-01-01

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

Hypoxia-Inducible Factor-1α (HIF-1α) Expression on Endothelial Cells in Juvenile Nasopharyngeal Angiofibroma: A Review of 70 cases and Tissue Microarray Analysis.

Science.gov (United States)

Song, Xiaole; Yang, Chenhe; Zhang, Huankang; Wang, Jingjing; Sun, Xicai; Hu, Li; Liu, Zhuofu; Wang, Dehui

2018-06-01

To examine the expression of hypoxia-inducible factor-1α (HIF-1α) and its related molecules (cellular repressor of E1A-stimulated genes [CREG], osteopontin [OPN], proto-oncogene tyrosine-protein kinase Src [c-Src], and vascular endothelial growth factor [VEGF]) in juvenile nasopharyngeal angiofibroma (JNA) and explore the correlation between clinical prognosis and HIF-1α expression. The study performed a retrospective review of the clinical records of patients with JNA treated between 2003 and 2007. Specimens were analyzed by immunohistochemistry for HIF-1α, CREG, OPN, c-Src, and VEGF expression, and microvessel density (MVD) was assessed by tissue microarray. The correlation between expression levels and clinicopathological features including age, tumor stage, intraoperative blood loss, and recurrence was analyzed. HIF-1α, CREG, OPN, c-Src, and VEGF were upregulated in endothelial cells (ECs) of patients with JNA, and strong correlations in the expression of these molecules were observed. HIF-1α expression was higher in young patients ( P = .032) and in recurrent cases ( P = .01). Survival analysis showed that low HIF-1α levels in ECs predicted longer time to recurrence (log rank test P = .006). Receiver operating characteristic curve analysis showed that HIF-1α was a prognostic factor for recurrence (area under the curve = 0.690, P = .019). No correlation was found between the expression of molecules and Radkowski stage or intraoperative blood loss. In cases of JNA treated surgically, HIF-1α expression in ECs is a useful prognostic factor for tumor recurrence.

Broad spectrum microarray for fingerprint-based bacterial species identification

Directory of Open Access Journals (Sweden)

Frey Jürg E

2010-02-01

Full Text Available Abstract Background Microarrays are powerful tools for DNA-based molecular diagnostics and identification of pathogens. Most target a limited range of organisms and are based on only one or a very few genes for specific identification. Such microarrays are limited to organisms for which specific probes are available, and often have difficulty discriminating closely related taxa. We have developed an alternative broad-spectrum microarray that employs hybridisation fingerprints generated by high-density anonymous markers distributed over the entire genome for identification based on comparison to a reference database. Results A high-density microarray carrying 95,000 unique 13-mer probes was designed. Optimized methods were developed to deliver reproducible hybridisation patterns that enabled confident discrimination of bacteria at the species, subspecies, and strain levels. High correlation coefficients were achieved between replicates. A sub-selection of 12,071 probes, determined by ANOVA and class prediction analysis, enabled the discrimination of all samples in our panel. Mismatch probe hybridisation was observed but was found to have no effect on the discriminatory capacity of our system. Conclusions These results indicate the potential of our genome chip for reliable identification of a wide range of bacterial taxa at the subspecies level without laborious prior sequencing and probe design. With its high resolution capacity, our proof-of-principle chip demonstrates great potential as a tool for molecular diagnostics of broad taxonomic groups.

DNA Microarray Data Analysis: A Novel Biclustering Algorithm Approach

Directory of Open Access Journals (Sweden)

Tewfik Ahmed H

2006-01-01

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

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

Science.gov (United States)

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

2015-10-06

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

THE MAQC PROJECT: ESTABLISHING QC METRICS AND THRESHOLDS FOR MICROARRAY QUALITY CONTROL

Science.gov (United States)

Microarrays represent a core technology in pharmacogenomics and toxicogenomics; however, before this technology can successfully and reliably be applied in clinical practice and regulatory decision-making, standards and quality measures need to be developed. The Microarray Qualit...

Significance of genomic instability in breast cancer in atomic bomb survivors: analysis of microarray-comparative genomic hybridization

Directory of Open Access Journals (Sweden)

Oikawa Masahiro

2011-12-01

Full Text Available Abstract Background It has been postulated that ionizing radiation induces breast cancers among atomic bomb (A-bomb survivors. We have reported a higher incidence of HER2 and C-MYC oncogene amplification in breast cancers from A-bomb survivors. The purpose of this study was to clarify the effect of A-bomb radiation exposure on genomic instability (GIN, which is an important hallmark of carcinogenesis, in archival formalin-fixed paraffin-embedded (FFPE tissues of breast cancer by using microarray-comparative genomic hybridization (aCGH. Methods Tumor DNA was extracted from FFPE tissues of invasive ductal cancers from 15 survivors who were exposed at 1.5 km or less from the hypocenter and 13 calendar year-matched non-exposed patients followed by aCGH analysis using a high-density oligonucleotide microarray. The total length of copy number aberrations (CNA was used as an indicator of GIN, and correlation with clinicopathological factors were statistically tested. Results The mean of the derivative log ratio spread (DLRSpread, which estimates the noise by calculating the spread of log ratio differences between consecutive probes for all chromosomes, was 0.54 (range, 0.26 to 1.05. The concordance of results between aCGH and fluorescence in situ hybridization (FISH for HER2 gene amplification was 88%. The incidence of HER2 amplification and histological grade was significantly higher in the A-bomb survivors than control group (P = 0.04, respectively. The total length of CNA tended to be larger in the A-bomb survivors (P = 0.15. Correlation analysis of CNA and clinicopathological factors revealed that DLRSpread was negatively correlated with that significantly (P = 0.034, r = -0.40. Multivariate analysis with covariance revealed that the exposure to A-bomb was a significant (P = 0.005 independent factor which was associated with larger total length of CNA of breast cancers. Conclusions Thus, archival FFPE tissues from A-bomb survivors are useful for

Significance of genomic instability in breast cancer in atomic bomb survivors: analysis of microarray-comparative genomic hybridization

International Nuclear Information System (INIS)

Oikawa, Masahiro; Yoshiura, Koh-ichiro; Kondo, Hisayoshi; Miura, Shiro; Nagayasu, Takeshi; Nakashima, Masahiro

2011-01-01

It has been postulated that ionizing radiation induces breast cancers among atomic bomb (A-bomb) survivors. We have reported a higher incidence of HER2 and C-MYC oncogene amplification in breast cancers from A-bomb survivors. The purpose of this study was to clarify the effect of A-bomb radiation exposure on genomic instability (GIN), which is an important hallmark of carcinogenesis, in archival formalin-fixed paraffin-embedded (FFPE) tissues of breast cancer by using microarray-comparative genomic hybridization (aCGH). Tumor DNA was extracted from FFPE tissues of invasive ductal cancers from 15 survivors who were exposed at 1.5 km or less from the hypocenter and 13 calendar year-matched non-exposed patients followed by aCGH analysis using a high-density oligonucleotide microarray. The total length of copy number aberrations (CNA) was used as an indicator of GIN, and correlation with clinicopathological factors were statistically tested. The mean of the derivative log ratio spread (DLRSpread), which estimates the noise by calculating the spread of log ratio differences between consecutive probes for all chromosomes, was 0.54 (range, 0.26 to 1.05). The concordance of results between aCGH and fluorescence in situ hybridization (FISH) for HER2 gene amplification was 88%. The incidence of HER2 amplification and histological grade was significantly higher in the A-bomb survivors than control group (P = 0.04, respectively). The total length of CNA tended to be larger in the A-bomb survivors (P = 0.15). Correlation analysis of CNA and clinicopathological factors revealed that DLRSpread was negatively correlated with that significantly (P = 0.034, r = -0.40). Multivariate analysis with covariance revealed that the exposure to A-bomb was a significant (P = 0.005) independent factor which was associated with larger total length of CNA of breast cancers. Thus, archival FFPE tissues from A-bomb survivors are useful for genome-wide aCGH analysis. Our results suggested that A

Significance of genomic instability in breast cancer in atomic bomb survivors: analysis of microarray-comparative genomic hybridization.

Science.gov (United States)

Oikawa, Masahiro; Yoshiura, Koh-ichiro; Kondo, Hisayoshi; Miura, Shiro; Nagayasu, Takeshi; Nakashima, Masahiro

2011-12-07

It has been postulated that ionizing radiation induces breast cancers among atomic bomb (A-bomb) survivors. We have reported a higher incidence of HER2 and C-MYC oncogene amplification in breast cancers from A-bomb survivors. The purpose of this study was to clarify the effect of A-bomb radiation exposure on genomic instability (GIN), which is an important hallmark of carcinogenesis, in archival formalin-fixed paraffin-embedded (FFPE) tissues of breast cancer by using microarray-comparative genomic hybridization (aCGH). Tumor DNA was extracted from FFPE tissues of invasive ductal cancers from 15 survivors who were exposed at 1.5 km or less from the hypocenter and 13 calendar year-matched non-exposed patients followed by aCGH analysis using a high-density oligonucleotide microarray. The total length of copy number aberrations (CNA) was used as an indicator of GIN, and correlation with clinicopathological factors were statistically tested. The mean of the derivative log ratio spread (DLRSpread), which estimates the noise by calculating the spread of log ratio differences between consecutive probes for all chromosomes, was 0.54 (range, 0.26 to 1.05). The concordance of results between aCGH and fluorescence in situ hybridization (FISH) for HER2 gene amplification was 88%. The incidence of HER2 amplification and histological grade was significantly higher in the A-bomb survivors than control group (P = 0.04, respectively). The total length of CNA tended to be larger in the A-bomb survivors (P = 0.15). Correlation analysis of CNA and clinicopathological factors revealed that DLRSpread was negatively correlated with that significantly (P = 0.034, r = -0.40). Multivariate analysis with covariance revealed that the exposure to A-bomb was a significant (P = 0.005) independent factor which was associated with larger total length of CNA of breast cancers. Thus, archival FFPE tissues from A-bomb survivors are useful for genome-wide aCGH analysis. Our results suggested that A

Sleep is not just for the brain: transcriptional responses to sleep in peripheral tissues

OpenAIRE

Anafi, Ron C; Pellegrino, Renata; Shockley, Keith R; Romer, Micah; Tufik, Sergio; Pack, Allan I

2013-01-01

Background Many have assumed that the primary function of sleep is for the brain. We evaluated the molecular consequences of sleep and sleep deprivation outside the brain, in heart and lung. Using microarrays we compared gene expression in tissue from sleeping and sleep deprived mice euthanized at the same diurnal times. Results In each tissue, nearly two thousand genes demonstrated statistically significant differential expression as a function of sleep/wake behavioral state. To mitigate the...

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

Directory of Open Access Journals (Sweden)

Nordborg Nicklas

2009-10-01

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

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

Science.gov (United States)

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

2009-10-12

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

Up-regulation of ALG-2 in hepatomas and lung cancer tissue

DEFF Research Database (Denmark)

la Cour, Jonas Marstrand; Mollerup, Jens; Winding, Pernille

2003-01-01

, a result confirmed by immunohistochemical analysis. Staining of four different lung cancer tissue microarrays including specimens of 263 patients showed that ALG-2 is mainly localized to epithelial cells and significantly up-regulated in small-cell lung cancers and in non-small-cell lung cancers. Our...... using Western blot analysis and immunohistochemistry. Western blot analysis of 15 different adult mouse tissues demonstrated that ALG-2 is ubiquitously expressed. We found that ALG-2 was more than threefold overexpressed in rat liver hepatoma compared to normal rat liver using Western blot analysis...

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

Directory of Open Access Journals (Sweden)

Beaudoing Emmanuel

2006-09-01

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

Mining microarray datasets in nutrition: expression of the GPR120 (n-3 fatty acid receptor/sensor) gene is down-regulated in human adipocytes by macrophage secretions.

Science.gov (United States)

Trayhurn, Paul; Denyer, Gareth

2012-01-01

Microarray datasets are a rich source of information in nutritional investigation. Targeted mining of microarray data following initial, non-biased bioinformatic analysis can provide key insight into specific genes and metabolic processes of interest. Microarrays from human adipocytes were examined to explore the effects of macrophage secretions on the expression of the G-protein-coupled receptor (GPR) genes that encode fatty acid receptors/sensors. Exposure of the adipocytes to macrophage-conditioned medium for 4 or 24 h had no effect on GPR40 and GPR43 expression, but there was a marked stimulation of GPR84 expression (receptor for medium-chain fatty acids), the mRNA level increasing 13·5-fold at 24 h relative to unconditioned medium. Importantly, expression of GPR120, which encodes an n-3 PUFA receptor/sensor, was strongly inhibited by the conditioned medium (15-fold decrease in mRNA at 24 h). Macrophage secretions have major effects on the expression of fatty acid receptor/sensor genes in human adipocytes, which may lead to an augmentation of the inflammatory response in adipose tissue in obesity.

LNA-modified isothermal oligonucleotide microarray for ...