Development and application of a 6.5 million feature Affymetrix Genechip® for massively parallel discovery of single position polymorphisms in lettuce (Lactuca spp.)

PubMed Central

2012-01-01

Background High-resolution genetic maps are needed in many crops to help characterize the genetic diversity that determines agriculturally important traits. Hybridization to microarrays to detect single feature polymorphisms is a powerful technique for marker discovery and genotyping because of its highly parallel nature. However, microarrays designed for gene expression analysis rarely provide sufficient gene coverage for optimal detection of nucleotide polymorphisms, which limits utility in species with low rates of polymorphism such as lettuce (Lactuca sativa). Results We developed a 6.5 million feature Affymetrix GeneChip® for efficient polymorphism discovery and genotyping, as well as for analysis of gene expression in lettuce. Probes on the microarray were designed from 26,809 unigenes from cultivated lettuce and an additional 8,819 unigenes from four related species (L. serriola, L. saligna, L. virosa and L. perennis). Where possible, probes were tiled with a 2 bp stagger, alternating on each DNA strand; providing an average of 187 probes covering approximately 600 bp for each of over 35,000 unigenes; resulting in up to 13 fold redundancy in coverage per nucleotide. We developed protocols for hybridization of genomic DNA to the GeneChip® and refined custom algorithms that utilized coverage from multiple, high quality probes to detect single position polymorphisms in 2 bp sliding windows across each unigene. This allowed us to detect greater than 18,000 polymorphisms between the parental lines of our core mapping population, as well as numerous polymorphisms between cultivated lettuce and wild species in the lettuce genepool. Using marker data from our diversity panel comprised of 52 accessions from the five species listed above, we were able to separate accessions by species using both phylogenetic and principal component analyses. Additionally, we estimated the diversity between different types of cultivated lettuce and distinguished morphological types

Development and application of a 6.5 million feature Affymetrix Genechip® for massively parallel discovery of single position polymorphisms in lettuce (Lactuca spp.).

PubMed

Stoffel, Kevin; van Leeuwen, Hans; Kozik, Alexander; Caldwell, David; Ashrafi, Hamid; Cui, Xinping; Tan, Xiaoping; Hill, Theresa; Reyes-Chin-Wo, Sebastian; Truco, Maria-Jose; Michelmore, Richard W; Van Deynze, Allen

2012-05-14

High-resolution genetic maps are needed in many crops to help characterize the genetic diversity that determines agriculturally important traits. Hybridization to microarrays to detect single feature polymorphisms is a powerful technique for marker discovery and genotyping because of its highly parallel nature. However, microarrays designed for gene expression analysis rarely provide sufficient gene coverage for optimal detection of nucleotide polymorphisms, which limits utility in species with low rates of polymorphism such as lettuce (Lactuca sativa). We developed a 6.5 million feature Affymetrix GeneChip® for efficient polymorphism discovery and genotyping, as well as for analysis of gene expression in lettuce. Probes on the microarray were designed from 26,809 unigenes from cultivated lettuce and an additional 8,819 unigenes from four related species (L. serriola, L. saligna, L. virosa and L. perennis). Where possible, probes were tiled with a 2 bp stagger, alternating on each DNA strand; providing an average of 187 probes covering approximately 600 bp for each of over 35,000 unigenes; resulting in up to 13 fold redundancy in coverage per nucleotide. We developed protocols for hybridization of genomic DNA to the GeneChip® and refined custom algorithms that utilized coverage from multiple, high quality probes to detect single position polymorphisms in 2 bp sliding windows across each unigene. This allowed us to detect greater than 18,000 polymorphisms between the parental lines of our core mapping population, as well as numerous polymorphisms between cultivated lettuce and wild species in the lettuce genepool. Using marker data from our diversity panel comprised of 52 accessions from the five species listed above, we were able to separate accessions by species using both phylogenetic and principal component analyses. Additionally, we estimated the diversity between different types of cultivated lettuce and distinguished morphological types. By hybridizing

ArrayWiki: an enabling technology for sharing public microarray data repositories and meta-analyses

PubMed Central

Stokes, Todd H; Torrance, JT; Li, Henry; Wang, May D

2008-01-01

Background A survey of microarray databases reveals that most of the repository contents and data models are heterogeneous (i.e., data obtained from different chip manufacturers), and that the repositories provide only basic biological keywords linking to PubMed. As a result, it is difficult to find datasets using research context or analysis parameters information beyond a few keywords. For example, to reduce the "curse-of-dimension" problem in microarray analysis, the number of samples is often increased by merging array data from different datasets. Knowing chip data parameters such as pre-processing steps (e.g., normalization, artefact removal, etc), and knowing any previous biological validation of the dataset is essential due to the heterogeneity of the data. However, most of the microarray repositories do not have meta-data information in the first place, and do not have a a mechanism to add or insert this information. Thus, there is a critical need to create "intelligent" microarray repositories that (1) enable update of meta-data with the raw array data, and (2) provide standardized archiving protocols to minimize bias from the raw data sources. Results To address the problems discussed, we have developed a community maintained system called ArrayWiki that unites disparate meta-data of microarray meta-experiments from multiple primary sources with four key features. First, ArrayWiki provides a user-friendly knowledge management interface in addition to a programmable interface using standards developed by Wikipedia. Second, ArrayWiki includes automated quality control processes (caCORRECT) and novel visualization methods (BioPNG, Gel Plots), which provide extra information about data quality unavailable in other microarray repositories. Third, it provides a user-curation capability through the familiar Wiki interface. Fourth, ArrayWiki provides users with simple text-based searches across all experiment meta-data, and exposes data to search engine crawlers

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

PubMed

Jain, K K

2001-02-01

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

Response of sweet orange (Citrus sinensis) to 'Candidatus Liberibacter asiaticus' infection: microscopy and microarray analyses.

PubMed

Kim, Jeong-Soon; Sagaram, Uma Shankar; Burns, Jacqueline K; Li, Jian-Liang; Wang, Nian

2009-01-01

Citrus greening or huanglongbing (HLB) is a devastating disease of citrus. HLB is associated with the phloem-limited fastidious prokaryotic alpha-proteobacterium 'Candidatus Liberibacter spp.' In this report, we used sweet orange (Citrus sinensis) leaf tissue infected with 'Ca. Liberibacter asiaticus' and compared this with healthy controls. Investigation of the host response was examined with citrus microarray hybridization based on 33,879 expressed sequence tag sequences from several citrus species and hybrids. The microarray analysis indicated that HLB infection significantly affected expression of 624 genes whose encoded proteins were categorized according to function. The categories included genes associated with sugar metabolism, plant defense, phytohormone, and cell wall metabolism, as well as 14 other gene categories. The anatomical analyses indicated that HLB bacterium infection caused phloem disruption, sucrose accumulation, and plugged sieve pores. The up-regulation of three key starch biosynthetic genes including ADP-glucose pyrophosphorylase, starch synthase, granule-bound starch synthase and starch debranching enzyme likely contributed to accumulation of starch in HLB-affected leaves. The HLB-associated phloem blockage resulted from the plugged sieve pores rather than the HLB bacterial aggregates since 'Ca. Liberibacter asiaticus' does not form aggregate in citrus. The up-regulation of pp2 gene is related to callose deposition to plug the sieve pores in HLB-affected plants.

Shrinkage regression-based methods for microarray missing value imputation.

PubMed

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

2013-01-01

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

APPLICATION OF DNA MICROARRAYS TO REPRODUCTIVE TOXICOLOGY AND THE DEVELOPMENT OF A TESTIS ARRAY

EPA Science Inventory

With the advent of sequence information for entire mammalian genomes, it is now possible to analyze gene expression and gene polymorphisms on a genomic scale. The primary tool for analysis of gene expression is the DNA microarray. We have used commercially available cDNA micro...

Single-feature polymorphism discovery in the barley transcriptome

PubMed Central

Rostoks, Nils; Borevitz, Justin O; Hedley, Peter E; Russell, Joanne; Mudie, Sharon; Morris, Jenny; Cardle, Linda; Marshall, David F; Waugh, Robbie

2005-01-01

A probe-level model for analysis of GeneChip gene-expression data is presented which identified more than 10,000 single-feature polymorphisms (SFP) between two barley genotypes. The method has good sensitivity, as 67% of known single-nucleotide polymorphisms (SNP) were called as SFPs. This method is applicable to all oligonucleotide microarray data, accounts for SNP effects in gene-expression data and represents an efficient and versatile approach for highly parallel marker identification in large genomes. PMID:15960806

Meta-analyses of the 5-HTTLPR polymorphisms and post-traumatic stress disorder.

PubMed

Navarro-Mateu, Fernando; Escámez, Teresa; Koenen, Karestan C; Alonso, Jordi; Sánchez-Meca, Julio

2013-01-01

To conduct a meta-analysis of all published genetic association studies of 5-HTTLPR polymorphisms performed in PTSD cases. Potential studies were identified through PubMed/MEDLINE, EMBASE, Web of Science databases (Web of Knowledge, WoK), PsychINFO, PsychArticles and HuGeNet (Human Genome Epidemiology Network) up until December 2011. Published observational studies reporting genotype or allele frequencies of this genetic factor in PTSD cases and in non-PTSD controls were all considered eligible for inclusion in this systematic review. Two reviewers selected studies for possible inclusion and extracted data independently following a standardized protocol. A biallelic and a triallelic meta-analysis, including the total S and S' frequencies, the dominant (S+/LL and S'+/L'L') and the recessive model (SS/L+ and S'S'/L'+), was performed with a random-effect model to calculate the pooled OR and its corresponding 95% CI. Forest plots and Cochran's Q-Statistic and I(2) index were calculated to check for heterogeneity. Subgroup analyses and meta-regression were carried out to analyze potential moderators. Publication bias and quality of reporting were also analyzed. 13 studies met our inclusion criteria, providing a total sample of 1874 patients with PTSD and 7785 controls in the biallelic meta-analyses and 627 and 3524, respectively, in the triallelic. None of the meta-analyses showed evidence of an association between 5-HTTLPR and PTSD but several characteristics (exposure to the same principal stressor for PTSD cases and controls, adjustment for potential confounding variables, blind assessment, study design, type of PTSD, ethnic distribution and Total Quality Score) influenced the results in subgroup analyses and meta-regression. There was no evidence of potential publication bias. Current evidence does not support a direct effect of 5-HTTLPR polymorphisms on PTSD. Further analyses of gene-environment interactions, epigenetic modulation and new studies with large samples

C677T (RS1801133 ) MTHFR gene polymorphism frequency in a colombian population.

PubMed

Romero-Sánchez, Consuelo; Gómez-Gutierrez, Alberto; Gómez, Piedad Elena; Casas-Gomez, Maria Consuelo; Briceño, Ignacio

2015-01-01

Abnormal levels of the enzyme methylenetetrahydrofolate reductase (MTHFR) are associated with an increased risk of both cardiovascular and cerebrovascular disease and higher concentrations of homocysteine. Abnormal levels are also related to birth defects, pregnancy complications, cancer and toxicity to methotrexate (MTX). Polymorphisms of MTHFR affect the activity of the enzyme. Genetic associations have been related to treatment efficacy. To establish the frequency of the C> T polymorphism at nucleotide 677 of the MTHFR gene in a group of Colombian individuals. Data from pharmacogenetic microarrays that include MTX sensibility-associated polymorphisms were retrospectively collected (Pathway Genomics(®)). The frequency of the C> T MTHFR rs1801133 marker polymorphism was analyzed. Microarray data from 68 men and 84 women were analyzed. Comparisons of genotype C/C vs. C/T and T/T were statistically significantly different (p= 0.00, p= 0.026, respectively), as were C/T and T / T (p= 0.0001). Results for the C/C and C/T genotypes in a Colombian population are similar to other previously studied groups of healthy subjects. Subjects from our population might be at risk of developing diseases associated with MTHFR polymorphisms and might present toxicity and adverse effects if treated with MTX, which suggests the need to evaluate therapeutic alternatives based on individual pharmacogenetic studies.

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

PubMed

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

2013-01-01

Microarrays are widely used for examining differential gene expression, identifying single nucleotide polymorphisms, and detecting methylation loci. Multiple testing methods in microarray data analysis aim at controlling both Type I and Type II error rates; however, real microarray data do not always fit their distribution assumptions. Smyth's ubiquitous parametric method, for example, inadequately accommodates violations of normality assumptions, resulting in inflated Type I error rates. The Significance Analysis of Microarrays, another widely used microarray data analysis method, is based on a permutation test and is robust to non-normally distributed data; however, the Significance Analysis of Microarrays method fold change criteria are problematic, and can critically alter the conclusion of a study, as a result of compositional changes of the control data set in the analysis. We propose a novel approach, combining resampling with empirical Bayes methods: the Resampling-based empirical Bayes Methods. This approach not only reduces false discovery rates for non-normally distributed microarray data, but it is also impervious to fold change threshold since no control data set selection is needed. Through simulation studies, sensitivities, specificities, total rejections, and false discovery rates are compared across the Smyth's parametric method, the Significance Analysis of Microarrays, and the Resampling-based empirical Bayes Methods. Differences in false discovery rates controls between each approach are illustrated through a preterm delivery methylation study. The results show that the Resampling-based empirical Bayes Methods offer significantly higher specificity and lower false discovery rates compared to Smyth's parametric method when data are not normally distributed. The Resampling-based empirical Bayes Methods also offers higher statistical power than the Significance Analysis of Microarrays method when the proportion of significantly differentially

A high-density transcript linkage map with 1,845 expressed genes positioned by microarray-based Single Feature Polymorphisms (SFP) in Eucalyptus

PubMed Central

2011-01-01

Background Technological advances are progressively increasing the application of genomics to a wider array of economically and ecologically important species. High-density maps enriched for transcribed genes facilitate the discovery of connections between genes and phenotypes. We report the construction of a high-density linkage map of expressed genes for the heterozygous genome of Eucalyptus using Single Feature Polymorphism (SFP) markers. Results SFP discovery and mapping was achieved using pseudo-testcross screening and selective mapping to simultaneously optimize linkage mapping and microarray costs. SFP genotyping was carried out by hybridizing complementary RNA prepared from 4.5 year-old trees xylem to an SFP array containing 103,000 25-mer oligonucleotide probes representing 20,726 unigenes derived from a modest size expressed sequence tags collection. An SFP-mapping microarray with 43,777 selected candidate SFP probes representing 15,698 genes was subsequently designed and used to genotype SFPs in a larger subset of the segregating population drawn by selective mapping. A total of 1,845 genes were mapped, with 884 of them ordered with high likelihood support on a framework map anchored to 180 microsatellites with average density of 1.2 cM. Using more probes per unigene increased by two-fold the likelihood of detecting segregating SFPs eventually resulting in more genes mapped. In silico validation showed that 87% of the SFPs map to the expected location on the 4.5X draft sequence of the Eucalyptus grandis genome. Conclusions The Eucalyptus 1,845 gene map is the most highly enriched map for transcriptional information for any forest tree species to date. It represents a major improvement on the number of genes previously positioned on Eucalyptus maps and provides an initial glimpse at the gene space for this global tree genome. A general protocol is proposed to build high-density transcript linkage maps in less characterized plant species by SFP genotyping

Determination of genotoxic effects of boron and zinc on Zea mays using protein and random amplification of polymorphic DNA analyses.

PubMed

Erturk, Filiz Aygun; Nardemir, Gokce; Hilal, A Y; Arslan, Esra; Agar, Guleray

2015-11-01

In this research, we aimed to determine genotoxic effects of boron (B) and zinc (Zn) on Zea mays by using total soluble protein content and random amplification of polymorphic DNA (RAPD) analyses. For the RAPD analysis, 16 RAPD primers were found to produce unique polymorphic band profiles on treated maize seedlings. With increased Zn and B concentrations, increased polymorphism rate was observed, while genomic template stability and total soluble protein content decreased. The treatment with Zn was more effective than that of B groups on the levels of total proteins. The obtained results from this study revealed that the total soluble protein levels and RAPD profiles were performed as endpoints of genotoxicity and these analyses can offer useful biomarker assays for the evaluation of genotoxic effects on Zn and B polluted plants. © The Author(s) 2013.

Methylenetetrahydrofolate reductase gene polymorphisms contribute to acute myeloid leukemia and chronic myeloid leukemia susceptibilities: evidence from meta-analyses.

PubMed

He, Hairong; He, Gonghao; Wang, Taotao; Cai, Jiangxia; Wang, Yan; Zheng, Xiaowei; Dong, Yalin; Lu, Jun

2014-10-01

The expression of methylenetetrahydrofolate reductase (MTHFR) is associated with acute myeloid leukemia (AML) and chronic myeloid leukemia (CML). Most studies have linked the common functional C677T and A1298C polymorphisms of the MTHFR gene and susceptibility to AML and CML, but the results were not consistent. The aim of the present study was to derive a more precise estimation of the relationship. Meta-analyses assessing the association of MTHFR C677T and A1298C variations with AML and CML were conducted. Eligible articles were identified from the PubMed and EMBASE databases. All statistical analyses were conducted using Review Manager Software. 10 and 10 studies were included in the meta-analysis about the role of C677T polymorphism on the AML and CML risks, respectively; 6 and 4 studies were included about the role of A1298C polymorphism on the AML and CML risks, respectively. Overall, both the C677T and A1298C polymorphisms were significantly associated with CML risk under the recessive model (P=0.04, OR=1.35, 95% CI=1.02-1.79 for C677T and P=0.003, OR=2.17, 95% CI=1.29-3.63 for A1298C). In addition, the risk of CML was higher in 1298CC genotype carriers than in 1298AA genotype carriers (P=0.004, OR=2.17, 95%=1.28-3.69). Conversely, the overall data failed to indicate a significant association of C677T or A1298C polymorphisms with AML risk under any model. The findings provide evidence that C677T and A1298C polymorphisms are risk factors for CML risk. Copyright © 2014 Elsevier Ltd. All rights reserved.

Bioinformatic analyses to select phenotype affecting polymorphisms in HTR2C gene.

PubMed

Piva, Francesco; Giulietti, Matteo; Baldelli, Luisa; Nardi, Bernardo; Bellantuono, Cesario; Armeni, Tatiana; Saccucci, Franca; Principato, Giovanni

2011-08-01

Single nucleotide polymorphisms (SNPs) in serotonin related genes influence mental disorders, responses to pharmacological and psychotherapeutic treatments. In planning association studies, researchers that want to investigate new SNPs have to select some among a large number of candidates. Our aim is to guide researchers in the selection of the most likely phenotype affecting polymorphisms. Here, we studied serotonin receptor 2C (HTR2C) SNPs because, till now, only relatively few of about 2000 are investigated. We used the most updated and assessed bioinformatic tools to predict which variations can give rise to biological effects among 2450 HTR2C SNPs. We suggest 48 SNPs that are worth considering in future association studies in the field of psychiatry, psychology and pharmacogenomics. Moreover, our analyses point out the biological level probably affected, such as transcription, splicing, miRNA regulation and protein structure, thus allowing to suggest future molecular investigations. Although few association studies are available in literature, their results are in agreement with our predictions, showing that our selection methods can help to guide future association studies. Copyright © 2011 John Wiley & Sons, Ltd.

C677T (RS1801133 ) MTHFR gene polymorphism frequency in a colombian population

PubMed Central

Gómez-Gutierrez, Alberto; Gómez, Piedad Elena; Casas-Gomez, Maria Consuelo; Briceño, Ignacio

2015-01-01

Introduction: Abnormal levels of the enzyme methylenetetrahydrofolate reductase (MTHFR) are associated with an increased risk of both cardiovascular and cerebrovascular disease and higher concentrations of homocysteine. Abnormal levels are also related to birth defects, pregnancy complications, cancer and toxicity to methotrexate (MTX). Polymorphisms of MTHFR affect the activity of the enzyme. Genetic associations have been related to treatment efficacy. Objective: To establish the frequency of the C> T polymorphism at nucleotide 677 of the MTHFR gene in a group of Colombian individuals. Methods: Data from pharmacogenetic microarrays that include MTX sensibility-associated polymorphisms were retrospectively collected (Pathway Genomics®). The frequency of the C> T MTHFR rs1801133 marker polymorphism was analyzed. Results: Microarray data from 68 men and 84 women were analyzed. Comparisons of genotype C/C vs. C/T and T/T were statistically significantly different (p= 0.00, p= 0.026, respectively), as were C/T and T / T (p= 0.0001). Conclusions: Results for the C/C and C/T genotypes in a Colombian population are similar to other previously studied groups of healthy subjects. Subjects from our population might be at risk of developing diseases associated with MTHFR polymorphisms and might present toxicity and adverse effects if treated with MTX, which suggests the need to evaluate therapeutic alternatives based on individual pharmacogenetic studies. PMID:26309343

BABAR: an R package to simplify the normalisation of common reference design microarray-based transcriptomic datasets

PubMed Central

2010-01-01

Background The development of DNA microarrays has facilitated the generation of hundreds of thousands of transcriptomic datasets. The use of a common reference microarray design allows existing transcriptomic data to be readily compared and re-analysed in the light of new data, and the combination of this design with large datasets is ideal for 'systems'-level analyses. One issue is that these datasets are typically collected over many years and may be heterogeneous in nature, containing different microarray file formats and gene array layouts, dye-swaps, and showing varying scales of log2- ratios of expression between microarrays. Excellent software exists for the normalisation and analysis of microarray data but many data have yet to be analysed as existing methods struggle with heterogeneous datasets; options include normalising microarrays on an individual or experimental group basis. Our solution was to develop the Batch Anti-Banana Algorithm in R (BABAR) algorithm and software package which uses cyclic loess to normalise across the complete dataset. We have already used BABAR to analyse the function of Salmonella genes involved in the process of infection of mammalian cells. Results The only input required by BABAR is unprocessed GenePix or BlueFuse microarray data files. BABAR provides a combination of 'within' and 'between' microarray normalisation steps and diagnostic boxplots. When applied to a real heterogeneous dataset, BABAR normalised the dataset to produce a comparable scaling between the microarrays, with the microarray data in excellent agreement with RT-PCR analysis. When applied to a real non-heterogeneous dataset and a simulated dataset, BABAR's performance in identifying differentially expressed genes showed some benefits over standard techniques. Conclusions BABAR is an easy-to-use software tool, simplifying the simultaneous normalisation of heterogeneous two-colour common reference design cDNA microarray-based transcriptomic datasets. We show

Selective recognition of DNA from olive leaves and olive oil by PNA and modified-PNA microarrays

PubMed Central

Rossi, Stefano; Calabretta, Alessandro; Tedeschi, Tullia; Sforza, Stefano; Arcioni, Sergio; Baldoni, Luciana; Corradini, Roberto; Marchelli, Rosangela

2012-01-01

PNA probes for the specific detection of DNA from olive oil samples by microarray technology were developed. The presence of as low as 5% refined hazelnut (Corylus avellana) oil in extra-virgin olive oil (Olea europaea L.) could be detected by using a PNA microarray. A set of two single nucleotide polymorphisms (SNPs) from the Actin gene of Olive was chosen as a model for evaluating the ability of PNA probes for discriminating olive cultivars. Both unmodified and C2-modified PNAs bearing an arginine side-chain were used, the latter showing higher sequence specificity. DNA extracted from leaves of three different cultivars (Ogliarola leccese, Canino and Frantoio) could be easily discriminated using a microarray with unmodified PNA probes, whereas discrimination of DNA from oil samples was more challenging, and could be obtained only by using chiral PNA probes. PMID:22772038

Manufacturing of microarrays.

PubMed

Petersen, David W; Kawasaki, Ernest S

2007-01-01

DNA microarray technology has become a powerful tool in the arsenal of the molecular biologist. Capitalizing on high precision robotics and the wealth of DNA sequences annotated from the genomes of a large number of organisms, the manufacture of microarrays is now possible for the average academic laboratory with the funds and motivation. Microarray production requires attention to both biological and physical resources, including DNA libraries, robotics, and qualified personnel. While the fabrication of microarrays is a very labor-intensive process, production of quality microarrays individually tailored on a project-by-project basis will help researchers shed light on future scientific questions.

The Glycan Microarray Story from Construction to Applications.

PubMed

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

2017-04-18

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

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

PubMed Central

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

2013-01-01

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

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

PubMed Central

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

2007-01-01

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

Microarrays

ERIC Educational Resources Information Center

Plomin, Robert; Schalkwyk, Leonard C.

2007-01-01

Microarrays are revolutionizing genetics by making it possible to genotype hundreds of thousands of DNA markers and to assess the expression (RNA transcripts) of all of the genes in the genome. Microarrays are slides the size of a postage stamp that contain millions of DNA sequences to which single-stranded DNA or RNA can hybridize. This…

A microarray-based genotyping and genetic mapping approach for highly heterozygous outcrossing species enables localization of a large fraction of the unassembled Populus trichocarpa genome sequence.

PubMed

Drost, Derek R; Novaes, Evandro; Boaventura-Novaes, Carolina; Benedict, Catherine I; Brown, Ryan S; Yin, Tongming; Tuskan, Gerald A; Kirst, Matias

2009-06-01

Microarrays have demonstrated significant power for genome-wide analyses of gene expression, and recently have also revolutionized the genetic analysis of segregating populations by genotyping thousands of loci in a single assay. Although microarray-based genotyping approaches have been successfully applied in yeast and several inbred plant species, their power has not been proven in an outcrossing species with extensive genetic diversity. Here we have developed methods for high-throughput microarray-based genotyping in such species using a pseudo-backcross progeny of 154 individuals of Populus trichocarpa and P. deltoides analyzed with long-oligonucleotide in situ-synthesized microarray probes. Our analysis resulted in high-confidence genotypes for 719 single-feature polymorphism (SFP) and 1014 gene expression marker (GEM) candidates. Using these genotypes and an established microsatellite (SSR) framework map, we produced a high-density genetic map comprising over 600 SFPs, GEMs and SSRs. The abundance of gene-based markers allowed us to localize over 35 million base pairs of previously unplaced whole-genome shotgun (WGS) scaffold sequence to putative locations in the genome of P. trichocarpa. A high proportion of sampled scaffolds could be verified for their placement with independently mapped SSRs, demonstrating the previously un-utilized power that high-density genotyping can provide in the context of map-based WGS sequence reassembly. Our results provide a substantial contribution to the continued improvement of the Populus genome assembly, while demonstrating the feasibility of microarray-based genotyping in a highly heterozygous population. The strategies presented are applicable to genetic mapping efforts in all plant species with similarly high levels of genetic diversity.

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

PubMed Central

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

2006-01-01

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

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

PubMed

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

2008-08-07

There has been a dramatic increase in the amount of quantitative data derived from the measurement of changes at different levels of biological complexity during the post-genomic era. However, there are a number of issues associated with the use of computational tools employed for the analysis of such data. For example, computational tools such as R and MATLAB require prior knowledge of their programming languages in order to implement statistical analyses on data. Combining two or more tools in an analysis may also be problematic since data may have to be manually copied and pasted between separate user interfaces for each tool. Furthermore, this transfer of data may require a reconciliation step in order for there to be interoperability between computational tools. Developments in the Taverna workflow system have enabled pipelines to be constructed and enacted for generic and ad hoc analyses of quantitative data. Here, we present an example of such a workflow involving the statistical identification of differentially-expressed genes from microarray data followed by the annotation of their relationships to cellular processes. This workflow makes use of customised maxdBrowse web services, a system that allows Taverna to query and retrieve gene expression data from the maxdLoad2 microarray database. These data are then analysed by R to identify differentially-expressed genes using the Taverna RShell processor which has been developed for invoking this tool when it has been deployed as a service using the RServe library. In addition, the workflow uses Beanshell scripts to reconcile mismatches of data between services as well as to implement a form of user interaction for selecting subsets of microarray data for analysis as part of the workflow execution. A new plugin system in the Taverna software architecture is demonstrated by the use of renderers for displaying PDF files and CSV formatted data within the Taverna workbench. Taverna can be used by data analysis

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

PubMed Central

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

2008-01-01

Background There has been a dramatic increase in the amount of quantitative data derived from the measurement of changes at different levels of biological complexity during the post-genomic era. However, there are a number of issues associated with the use of computational tools employed for the analysis of such data. For example, computational tools such as R and MATLAB require prior knowledge of their programming languages in order to implement statistical analyses on data. Combining two or more tools in an analysis may also be problematic since data may have to be manually copied and pasted between separate user interfaces for each tool. Furthermore, this transfer of data may require a reconciliation step in order for there to be interoperability between computational tools. Results Developments in the Taverna workflow system have enabled pipelines to be constructed and enacted for generic and ad hoc analyses of quantitative data. Here, we present an example of such a workflow involving the statistical identification of differentially-expressed genes from microarray data followed by the annotation of their relationships to cellular processes. This workflow makes use of customised maxdBrowse web services, a system that allows Taverna to query and retrieve gene expression data from the maxdLoad2 microarray database. These data are then analysed by R to identify differentially-expressed genes using the Taverna RShell processor which has been developed for invoking this tool when it has been deployed as a service using the RServe library. In addition, the workflow uses Beanshell scripts to reconcile mismatches of data between services as well as to implement a form of user interaction for selecting subsets of microarray data for analysis as part of the workflow execution. A new plugin system in the Taverna software architecture is demonstrated by the use of renderers for displaying PDF files and CSV formatted data within the Taverna workbench. Conclusion Taverna can

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

PubMed

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

2010-06-16

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

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

PubMed

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

2003-09-22

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

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

PubMed Central

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

2008-01-01

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

2008 Microarray Research Group (MARG Survey): Sensing the State of Microarray Technology

EPA Science Inventory

Over the past several years, the field of microarrays has grown and evolved drastically. In its continued efforts to track this evolution and transformation, the ABRF-MARG has once again conducted a survey of international microarray facilities and individual microarray users. Th...

Validation of the Swine Protein-Annotated Oligonucleotide Microarray

USDA-ARS?s Scientific Manuscript database

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

Development of a DNA microarray for species identification of quarantine aphids.

PubMed

Lee, Won Sun; Choi, Hwalran; Kang, Jinseok; Kim, Ji-Hoon; Lee, Si Hyeock; Lee, Seunghwan; Hwang, Seung Yong

2013-12-01

Aphid pests are being brought into Korea as a result of increased crop trading. Aphids exist on growth areas of plants, and thus plant growth is seriously affected by aphid pests. However, aphids are very small and have several sexual morphs and life stages, so it is difficult to identify species on the basis of morphological features. This problem was approached using DNA microarray technology. DNA targets of the cytochrome c oxidase subunit I gene were generated with a fluorescent dye-labelled primer and were hybridised onto a DNA microarray consisting of specific probes. After analysing the signal intensity of the specific probes, the unique patterns from the DNA microarray, consisting of 47 species-specific probes, were obtained to identify 23 aphid species. To confirm the accuracy of the developed DNA microarray, ten individual blind samples were used in blind trials, and the identifications were completely consistent with the sequencing data of all individual blind samples. A microarray has been developed to distinguish aphid species. DNA microarray technology provides a rapid, easy, cost-effective and accurate method for identifying aphid species for pest control management. © 2013 Society of Chemical Industry.

The relationship between methylenetetrahydrofolate reductase polymorphism and hematological malignancy.

PubMed

Jiang, Ni; Zhu, Xishan; Zhang, Hongmei; Wang, Xiaoli; Zhou, Xinna; Gu, Jiezhun; Chen, Baoan; Ren, Jun

2014-01-01

Methylenetetrahydrofolate reductase (MTHFR) is the key enzyme for folate metabolism. Previous studies suggest a relationship between its single nucleotide polymorphisms (SNP) of C677T and A1298C with a variety of tumor susceptibility including hematological malignancy. SNP frequency distribution in different ethnic populations might lead to differences in disease susceptibility. There has been little research in Chinese people on the MTHFR SNP with the susceptibility of the hematological malignancy. Therefore, this study investigated the relationship between MTHFR SNPs and hematological malignancy in Jiangsu province in China. Gene microarray was used to detect MTHFR C677T and A1298C single nucleotide polymorphism loci on 157 healthy controls and 127 patients from Jiangsu province with hematological malignancies (30 with multiple myeloma, 28 with non-Hodgkin's lymphoma, 22 with acute lymphoblastic leukemia, 40 with acute myeloid leukemia, and seven with chronic myeloid leukemia). The allele frequency of 677T was 41.3% in patients and 33.1% in controls, showed significant difference (chi2 = 4.08, p = 0.043); 677TT genotype with a high susceptibility to hematological malignancy (OR 1.96, 95% CI 1.01 - 4.45, p = 0.041). In subgroup analyses, the genotypes 677TT and 1298CC were associated with significantly increased multiple myeloma risk (TT vs. CC: OR 8.92, 95% CI 1.06 - 75.24, p = 0.006; CC vs. AA: OR = 4.80, 95% CI 1.56 - 14.73, p = 0.044). No associations were found between polymorphisms and susceptibilities to acute lymphoblastic leukemia, acute myeloid leukemia, or non-Hodgkin's lymphoma. MTHFRC677T polymorphisms influence the risk of hematological malignancy among the population in Jiangsu province. Both MTHFR 677TT and MTHFR 1298CC genotypes increase susceptibility to myeloid leukemia.

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

PubMed

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

2007-11-22

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

A Versatile Microarray Platform for Capturing Rare Cells

NASA Astrophysics Data System (ADS)

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

2015-10-01

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

Strategies for comparing gene expression profiles from different microarray platforms: application to a case-control experiment.

PubMed

Severgnini, Marco; Bicciato, Silvio; Mangano, Eleonora; Scarlatti, Francesca; Mezzelani, Alessandra; Mattioli, Michela; Ghidoni, Riccardo; Peano, Clelia; Bonnal, Raoul; Viti, Federica; Milanesi, Luciano; De Bellis, Gianluca; Battaglia, Cristina

2006-06-01

Meta-analysis of microarray data is increasingly important, considering both the availability of multiple platforms using disparate technologies and the accumulation in public repositories of data sets from different laboratories. We addressed the issue of comparing gene expression profiles from two microarray platforms by devising a standardized investigative strategy. We tested this procedure by studying MDA-MB-231 cells, which undergo apoptosis on treatment with resveratrol. Gene expression profiles were obtained using high-density, short-oligonucleotide, single-color microarray platforms: GeneChip (Affymetrix) and CodeLink (Amersham). Interplatform analyses were carried out on 8414 common transcripts represented on both platforms, as identified by LocusLink ID, representing 70.8% and 88.6% of annotated GeneChip and CodeLink features, respectively. We identified 105 differentially expressed genes (DEGs) on CodeLink and 42 DEGs on GeneChip. Among them, only 9 DEGs were commonly identified by both platforms. Multiple analyses (BLAST alignment of probes with target sequences, gene ontology, literature mining, and quantitative real-time PCR) permitted us to investigate the factors contributing to the generation of platform-dependent results in single-color microarray experiments. An effective approach to cross-platform comparison involves microarrays of similar technologies, samples prepared by identical methods, and a standardized battery of bioinformatic and statistical analyses.

Comparison of dkgB-linked intergenic sequence ribotyping to DNA microarray hybridization for assigning serotype to Salmonella enterica

PubMed Central

Guard, Jean; Sanchez-Ingunza, Roxana; Morales, Cesar; Stewart, Tod; Liljebjelke, Karen; Kessel, JoAnn; Ingram, Kim; Jones, Deana; Jackson, Charlene; Fedorka-Cray, Paula; Frye, Jonathan; Gast, Richard; Hinton, Arthur

2012-01-01

Two DNA-based methods were compared for the ability to assign serotype to 139 isolates of Salmonella enterica ssp. I. Intergenic sequence ribotyping (ISR) evaluated single nucleotide polymorphisms occurring in a 5S ribosomal gene region and flanking sequences bordering the gene dkgB. A DNA microarray hybridization method that assessed the presence and the absence of sets of genes was the second method. Serotype was assigned for 128 (92.1%) of submissions by the two DNA methods. ISR detected mixtures of serotypes within single colonies and it cost substantially less than Kauffmann–White serotyping and DNA microarray hybridization. Decreasing the cost of serotyping S. enterica while maintaining reliability may encourage routine testing and research. PMID:22998607

THE ABRF-MARG MICROARRAY SURVEY 2004: TAKING THE PULSE OF THE MICROARRAY FIELD

EPA Science Inventory

Over the past several years, the field of microarrays has grown and evolved drastically. In its continued efforts to track this evolution, the ABRF-MARG has once again conducted a survey of international microarray facilities and individual microarray users. The goal of the surve...

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

PubMed Central

Rouse, Richard JD; Field, Katrine; Lapira, Jennifer; Lee, Allen; Wick, Ivan; Eckhardt, Colleen; Bhasker, C Ramana; Soverchia, Laura; Hardiman, Gary

2008-01-01

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. PMID:18710498

AccuTyping: new algorithms for automated analysis of data from high-throughput genotyping with oligonucleotide microarrays

PubMed Central

Hu, Guohong; Wang, Hui-Yun; Greenawalt, Danielle M.; Azaro, Marco A.; Luo, Minjie; Tereshchenko, Irina V.; Cui, Xiangfeng; Yang, Qifeng; Gao, Richeng; Shen, Li; Li, Honghua

2006-01-01

Microarray-based analysis of single nucleotide polymorphisms (SNPs) has many applications in large-scale genetic studies. To minimize the influence of experimental variation, microarray data usually need to be processed in different aspects including background subtraction, normalization and low-signal filtering before genotype determination. Although many algorithms are sophisticated for these purposes, biases are still present. In the present paper, new algorithms for SNP microarray data analysis and the software, AccuTyping, developed based on these algorithms are described. The algorithms take advantage of a large number of SNPs included in each assay, and the fact that the top and bottom 20% of SNPs can be safely treated as homozygous after sorting based on their ratios between the signal intensities. These SNPs are then used as controls for color channel normalization and background subtraction. Genotype calls are made based on the logarithms of signal intensity ratios using two cutoff values, which were determined after training the program with a dataset of ∼160 000 genotypes and validated by non-microarray methods. AccuTyping was used to determine >300 000 genotypes of DNA and sperm samples. The accuracy was shown to be >99%. AccuTyping can be downloaded from . PMID:16982644

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.

PubMed

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.

A meta-data based method for DNA microarray imputation.

PubMed

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

2007-03-29

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

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

PubMed

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

2003-10-01

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

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

PubMed

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

2013-01-01

Microarray data are usually peppered with missing values due to various reasons. However, most of the downstream analyses for microarray data require complete datasets. Therefore, accurate algorithms for missing value estimation are needed for improving the performance of microarray data analyses. Although many algorithms have been developed, there are many debates on the selection of the optimal algorithm. The studies about the performance comparison of different algorithms are still incomprehensive, especially in the number of benchmark datasets used, the number of algorithms compared, the rounds of simulation conducted, and the performance measures used. In this paper, we performed a comprehensive comparison by using (I) thirteen datasets, (II) nine algorithms, (III) 110 independent runs of simulation, and (IV) three types of measures to evaluate the performance of each imputation algorithm fairly. First, the effects of different types of microarray datasets on the performance of each imputation algorithm were evaluated. Second, we discussed whether the datasets from different species have different impact on the performance of different algorithms. To assess the performance of each algorithm fairly, all evaluations were performed using three types of measures. Our results indicate that the performance of an imputation algorithm mainly depends on the type of a dataset but not on the species where the samples come from. In addition to the statistical measure, two other measures with biological meanings are useful to reflect the impact of missing value imputation on the downstream data analyses. Our study suggests that local-least-squares-based methods are good choices to handle missing values for most of the microarray datasets. In this work, we carried out a comprehensive comparison of the algorithms for microarray missing value imputation. Based on such a comprehensive comparison, researchers could choose the optimal algorithm for their datasets easily

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

PubMed Central

2013-01-01

Background Microarray data are usually peppered with missing values due to various reasons. However, most of the downstream analyses for microarray data require complete datasets. Therefore, accurate algorithms for missing value estimation are needed for improving the performance of microarray data analyses. Although many algorithms have been developed, there are many debates on the selection of the optimal algorithm. The studies about the performance comparison of different algorithms are still incomprehensive, especially in the number of benchmark datasets used, the number of algorithms compared, the rounds of simulation conducted, and the performance measures used. Results In this paper, we performed a comprehensive comparison by using (I) thirteen datasets, (II) nine algorithms, (III) 110 independent runs of simulation, and (IV) three types of measures to evaluate the performance of each imputation algorithm fairly. First, the effects of different types of microarray datasets on the performance of each imputation algorithm were evaluated. Second, we discussed whether the datasets from different species have different impact on the performance of different algorithms. To assess the performance of each algorithm fairly, all evaluations were performed using three types of measures. Our results indicate that the performance of an imputation algorithm mainly depends on the type of a dataset but not on the species where the samples come from. In addition to the statistical measure, two other measures with biological meanings are useful to reflect the impact of missing value imputation on the downstream data analyses. Our study suggests that local-least-squares-based methods are good choices to handle missing values for most of the microarray datasets. Conclusions In this work, we carried out a comprehensive comparison of the algorithms for microarray missing value imputation. Based on such a comprehensive comparison, researchers could choose the optimal algorithm for

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

PubMed

Gusnanto, Arief; Calza, Stefano; Pawitan, Yudi

2007-04-01

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

Fibre optic microarrays.

PubMed

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 platform for omics analysis

NASA Astrophysics Data System (ADS)

Mecklenburg, Michael; Xie, Bin

2001-09-01

Microarray technology has revolutionized genetic analysis. However, limitations in genome analysis has lead to renewed interest in establishing 'omic' strategies. As we enter the post-genomic era, new microarray technologies are needed to address these new classes of 'omic' targets, such as proteins, as well as lipids and carbohydrates. We have developed a microarray platform that combines self- assembling monolayers with the biotin-streptavidin system to provide a robust, versatile immobilization scheme. A hydrophobic film is patterned on the surface creating an array of tension wells that eliminates evaporation effects thereby reducing the shear stress to which biomolecules are exposed to during immobilization. The streptavidin linker layer makes it possible to adapt and/or develop microarray based assays using virtually any class of biomolecules including: carbohydrates, peptides, antibodies, receptors, as well as them ore traditional DNA based arrays. Our microarray technology is designed to furnish seamless compatibility across the various 'omic' platforms by providing a common blueprint for fabricating and analyzing arrays. The prototype microarray uses a microscope slide footprint patterned with 2 by 96 flat wells. Data on the microarray platform will be presented.

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

PubMed

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

2014-08-04

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

An efficient method to identify differentially expressed genes in microarray experiments

PubMed Central

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

2013-01-01

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

Microarray-integrated optoelectrofluidic immunoassay system

PubMed Central

Han, Dongsik

2016-01-01

A microarray-based analytical platform has been utilized as a powerful tool in biological assay fields. However, an analyte depletion problem due to the slow mass transport based on molecular diffusion causes low reaction efficiency, resulting in a limitation for practical applications. This paper presents a novel method to improve the efficiency of microarray-based immunoassay via an optically induced electrokinetic phenomenon by integrating an optoelectrofluidic device with a conventional glass slide-based microarray format. A sample droplet was loaded between the microarray slide and the optoelectrofluidic device on which a photoconductive layer was deposited. Under the application of an AC voltage, optically induced AC electroosmotic flows caused by a microarray-patterned light actively enhanced the mass transport of target molecules at the multiple assay spots of the microarray simultaneously, which reduced tedious reaction time from more than 30 min to 10 min. Based on this enhancing effect, a heterogeneous immunoassay with a tiny volume of sample (5 μl) was successfully performed in the microarray-integrated optoelectrofluidic system using immunoglobulin G (IgG) and anti-IgG, resulting in improved efficiency compared to the static environment. Furthermore, the application of multiplex assays was also demonstrated by multiple protein detection. PMID:27190571

Microarray-integrated optoelectrofluidic immunoassay system.

PubMed

Han, Dongsik; Park, Je-Kyun

2016-05-01

A microarray-based analytical platform has been utilized as a powerful tool in biological assay fields. However, an analyte depletion problem due to the slow mass transport based on molecular diffusion causes low reaction efficiency, resulting in a limitation for practical applications. This paper presents a novel method to improve the efficiency of microarray-based immunoassay via an optically induced electrokinetic phenomenon by integrating an optoelectrofluidic device with a conventional glass slide-based microarray format. A sample droplet was loaded between the microarray slide and the optoelectrofluidic device on which a photoconductive layer was deposited. Under the application of an AC voltage, optically induced AC electroosmotic flows caused by a microarray-patterned light actively enhanced the mass transport of target molecules at the multiple assay spots of the microarray simultaneously, which reduced tedious reaction time from more than 30 min to 10 min. Based on this enhancing effect, a heterogeneous immunoassay with a tiny volume of sample (5 μl) was successfully performed in the microarray-integrated optoelectrofluidic system using immunoglobulin G (IgG) and anti-IgG, resulting in improved efficiency compared to the static environment. Furthermore, the application of multiplex assays was also demonstrated by multiple protein detection.

Isolation of Microarray-Grade Total RNA, MicroRNA, and DNA from a Single PAXgene Blood RNA Tube

PubMed Central

Kruhøffer, Mogens; Dyrskjøt, Lars; Voss, Thorsten; Lindberg, Raija L.P.; Wyrich, Ralf; Thykjaer, Thomas; Orntoft, Torben F.

2007-01-01

We have developed a procedure for isolation of microRNA and genomic DNA in addition to total RNA from whole blood stabilized in PAXgene Blood RNA tubes. The procedure is based on automatic extraction on a BioRobot MDx and includes isolation of DNA from a fraction of the stabilized blood and recovery of small RNA species that are otherwise lost. The procedure presented here is suitable for large-scale experiments and is amenable to further automation. Procured total RNA and DNA was tested using Affymetrix Expression and single-nucleotide polymorphism GeneChips, respectively, and isolated microRNA was tested using spotted locked nucleic acid-based microarrays. We conclude that the yield and quality of total RNA, microRNA, and DNA from a single PAXgene blood RNA tube is sufficient for downstream microarray analysis. PMID:17690207

Dynamic variable selection in SNP genotype autocalling from APEX microarray data.

PubMed

Podder, Mohua; Welch, William J; Zamar, Ruben H; Tebbutt, Scott J

2006-11-30

Single nucleotide polymorphisms (SNPs) are DNA sequence variations, occurring when a single nucleotide--adenine (A), thymine (T), cytosine (C) or guanine (G)--is altered. Arguably, SNPs account for more than 90% of human genetic variation. Our laboratory has developed a highly redundant SNP genotyping assay consisting of multiple probes with signals from multiple channels for a single SNP, based on arrayed primer extension (APEX). This mini-sequencing method is a powerful combination of a highly parallel microarray with distinctive Sanger-based dideoxy terminator sequencing chemistry. Using this microarray platform, our current genotype calling system (known as SNP Chart) is capable of calling single SNP genotypes by manual inspection of the APEX data, which is time-consuming and exposed to user subjectivity bias. Using a set of 32 Coriell DNA samples plus three negative PCR controls as a training data set, we have developed a fully-automated genotyping algorithm based on simple linear discriminant analysis (LDA) using dynamic variable selection. The algorithm combines separate analyses based on the multiple probe sets to give a final posterior probability for each candidate genotype. We have tested our algorithm on a completely independent data set of 270 DNA samples, with validated genotypes, from patients admitted to the intensive care unit (ICU) of St. Paul's Hospital (plus one negative PCR control sample). Our method achieves a concordance rate of 98.9% with a 99.6% call rate for a set of 96 SNPs. By adjusting the threshold value for the final posterior probability of the called genotype, the call rate reduces to 94.9% with a higher concordance rate of 99.6%. We also reversed the two independent data sets in their training and testing roles, achieving a concordance rate up to 99.8%. The strength of this APEX chemistry-based platform is its unique redundancy having multiple probes for a single SNP. Our model-based genotype calling algorithm captures the

Application of HLA-DRB1 genotyping by oligonucleotide micro-array technology in forensic medicine.

PubMed

Jiang, Bin; Li, Yao; Wu, Hai; He, Xianmin; Li, Chengtao; Li, Li; Tang, Rong; Xie, Yi; Mao, Yumin

2006-10-16

The human leukocyte antigen (HLA) system is known to be the most complex polymorphic system in the human genome. Among all of the HLA loci, HLA-DRB1 has the second largest number of alleles. The purpose of this study is to develop an oligonucleotide micro-array based HLA-DRB1 typing system for use in forensic identification, anthropology, tissue transplantation, and other genetic research fields. The system was developed by analyzing the HLA-DRB1 (DRB1) genotypes in 1198 unrelated healthy Chinese Han individuals originating from various parts of China and residing in Shanghai, China. Polymerase chain reaction (PCR) coupled with the oligonucleotide micro-array technology was used to detect and type HLA-DRB1 alleles of the sample individuals. The reliability, sensitivity, consistency and specificity were evaluated for use in forensic identification. Furthermore, a meta-analysis was carried out by comparing the allele frequencies of the HLA-DRB1 locus with those of other Chinese Han groups, Chinese minorities and other ethnic populations. All the DNA samples yielded a 273 bp amplification product, with no other amplification products in this length range. The minimum quantity of DNA detected by this method is 15 ng in a PCR reaction system of 25 microl. The population studied appeared to be not in Hardy-Weinberg equilibrium. Observed heterozygosity (Ho), expected heterozygosity (He), expected probability of exclusion (PE), polymorphic information content (PIC), and discrimination power (DP) of the HLA-DRB1 locus from the Shanghai Han ethnic group were evaluated to be 0.8022, 0.8870, 0.7741, 0.8771, 0.9750, respectively. A total of 25 HLA-DRB1 alleles were identified. HLA-DRB1*09XX, *04XX, *12XX and *15XX were the most frequent DRB1 alleles, which were observed in 58.76% of the sample. One hundred and sixteen genotypes were found. The five most frequent genotypes were: *04XX/*04XX (0.0626), *09XX/*09XX (0.0593), *04XX/*09XX (0.0551), *09XX/*15XX (0.0384) and *08XX/*12

Evaluation of microarray data normalization procedures using spike-in experiments

PubMed Central

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

2006-01-01

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

A proposed metric for assessing the measurement quality of individual microarrays

PubMed Central

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

2006-01-01

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

THE ABRF MARG MICROARRAY SURVEY 2005: TAKING THE PULSE ON THE MICROARRAY FIELD

EPA Science Inventory

Over the past several years microarray technology has evolved into a critical component of any discovery based program. Since 1999, the Association of Biomolecular Resource Facilities (ABRF) Microarray Research Group (MARG) has conducted biennial surveys designed to generate a pr...

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

PubMed

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

2015-09-01

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

Microarray analysis of gene expression profiles in ripening pineapple fruits.

PubMed

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

2012-12-18

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

Microarray analysis of gene expression profiles in ripening pineapple fruits

PubMed Central

2012-01-01

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

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

PubMed

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 < 0.1). mRNAs related to ribosomal biogenesis, mRNA processing, and translation were upregulated during overnight nutrition; particularly anabolic signaling S6K1 (P < 0.01-0.1). Transcripts of genes associated with lysosomal degradation showed consistently lower expression during TPN while mRNAs for ubiquitin-mediated degradation of proteins as well as transcripts related to intracellular signaling pathways, PI3 kinase/MAPkinase, were either increased or decreased. In conclusion, muscle mRNA alterations during overnight standard TPN infusions at constant rate altered mRNAs associated with mTOR signaling; increased initiation of protein translation; and suppressed autophagy/lysosomal degradation of proteins. This indicates that overnight preoperative 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

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

PubMed Central

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

2013-01-01

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

Rivastigmine hydrogen tartrate polymorphs: Solid-state characterisation of transition and polymorphic conversion via milling

NASA Astrophysics Data System (ADS)

Amaro, Maria Inês; Simon, Alice; Cabral, Lúcio Mendes; de Sousa, Valéria Pereira; Healy, Anne Marie

2015-11-01

Rivastigmine (RHT) is an active pharmaceutical ingredient that is used for the treatment of mild to moderately severe dementia in Alzheimer's disease, and is known to present two polymorphic forms and to amorphise upon granulation. To date there is no information in the scientific or patent literature on polymorphic transition and stability. Hence, the aim of the current study was to gain a fundamental understanding of the polymorphic forms by (1) evaluating RHT thermodynamic stability (monotropy or enantiotropy) and (2) investigating the potential for polymorphic transformation upon milling. The two polymorphic and amorphous forms were characterised using X-ray powder diffractometry, thermal analyses, infra-red spectroscopy and water sorption analysis. The polymorphic transition was found to be spontaneous (ΔG0 < 0) and exothermic (ΔH0 < 0), indicative of a monotropic polymorph pair. The kinetic studies showed a fast initial polymorphic transition characterised by a heterogeneous nucleation, followed by a slow crystal growth. Ball milling can be used to promote the polymorphic transition and for the production of RHT amorphous form.

Analysis of High-Throughput ELISA Microarray Data

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

White, Amanda M.; Daly, Don S.; Zangar, Richard C.

Our research group develops analytical methods and software for the high-throughput analysis of quantitative enzyme-linked immunosorbent assay (ELISA) microarrays. ELISA microarrays differ from DNA microarrays in several fundamental aspects and most algorithms for analysis of DNA microarray data are not applicable to ELISA microarrays. In this review, we provide an overview of the steps involved in ELISA microarray data analysis and how the statistically sound algorithms we have developed provide an integrated software suite to address the needs of each data-processing step. The algorithms discussed are available in a set of open-source software tools (http://www.pnl.gov/statistics/ProMAT).

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

PubMed

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

2008-09-18

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

Direct Detection and Genotyping of Klebsiella pneumoniae Carbapenemases from Urine by Use of a New DNA Microarray Test

PubMed Central

Peter, Harald; Berggrav, Kathrine; Thomas, Peter; Pfeifer, Yvonne; Witte, Wolfgang; Templeton, Kate

2012-01-01

Klebsiella pneumoniae carbapenemases (KPCs) are considered a serious threat to antibiotic therapy, as they confer resistance to carbapenems, which are used to treat extended-spectrum beta-lactamase (ESBL)-producing bacteria. Here, we describe the development and evaluation of a DNA microarray for the detection and genotyping of KPC genes (blaKPC) within a 5-h period. To test the whole assay procedure (DNA extraction plus a DNA microarray assay) directly from clinical specimens, we compared two commercial DNA extraction kits (the QIAprep Spin miniprep kit [Qiagen] and the urine bacterial DNA isolation kit [Norgen]) for the direct DNA extraction from urine samples (dilution series spiked in human urine). Reliable single nucleotide polymorphism (SNP) typing was demonstrated using 1 × 105 CFU/ml urine for Escherichia coli (Qiagen and Norgen) and 80 CFU/ml urine, on average, for K. pneumoniae (Norgen). This study presents, for the first time, the combination of a new KPC microarray with commercial sample preparation for detecting and genotyping microbial pathogens directly from clinical specimens; this paves the way toward tests providing epidemiological and diagnostic data, enabling better antimicrobial stewardship. PMID:23035190

Molecular Microbial Analyses of the Mars Exploration Rovers Assembly Facility

NASA Technical Reports Server (NTRS)

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

2004-01-01

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

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

PubMed

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

2009-03-01

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

Mining microarrays for metabolic meaning: nutritional regulation of hypothalamic gene expression.

PubMed

Mobbs, Charles V; Yen, Kelvin; Mastaitis, Jason; Nguyen, Ha; Watson, Elizabeth; Wurmbach, Elisa; Sealfon, Stuart C; Brooks, Andrew; Salton, Stephen R J

2004-06-01

DNA microarray analysis has been used to investigate relative changes in the level of gene expression in the CNS, including changes that are associated with disease, injury, psychiatric disorders, drug exposure or withdrawal, and memory formation. We have used oligonucleotide microarrays to identify hypothalamic genes that respond to nutritional manipulation. In addition to commonly used microarray analysis based on criteria such as fold-regulation, we have also found that simply carrying out multiple t tests then sorting by P value constitutes a highly reliable method to detect true regulation, as assessed by real-time polymerase chain reaction (PCR), even for relatively low abundance genes or relatively low magnitude of regulation. Such analyses directly suggested novel mechanisms that mediate effects of nutritional state on neuroendocrine function and are being used to identify regulated gene products that may elucidate the metabolic pathology of obese ob/ob, lean Vgf-/Vgf-, and other models with profound metabolic impairments.

Living Cell Microarrays: An Overview of Concepts

PubMed Central

Jonczyk, Rebecca; Kurth, Tracy; Lavrentieva, Antonina; Walter, Johanna-Gabriela; Scheper, Thomas; Stahl, Frank

2016-01-01

Living cell microarrays are a highly efficient cellular screening system. Due to the low number of cells required per spot, cell microarrays enable the use of primary and stem cells and provide resolution close to the single-cell level. Apart from a variety of conventional static designs, microfluidic microarray systems have also been established. An alternative format is a microarray consisting of three-dimensional cell constructs ranging from cell spheroids to cells encapsulated in hydrogel. These systems provide an in vivo-like microenvironment and are preferably used for the investigation of cellular physiology, cytotoxicity, and drug screening. Thus, many different high-tech microarray platforms are currently available. Disadvantages of many systems include their high cost, the requirement of specialized equipment for their manufacture, and the poor comparability of results between different platforms. In this article, we provide an overview of static, microfluidic, and 3D cell microarrays. In addition, we describe a simple method for the printing of living cell microarrays on modified microscope glass slides using standard DNA microarray equipment available in most laboratories. Applications in research and diagnostics are discussed, e.g., the selective and sensitive detection of biomarkers. Finally, we highlight current limitations and the future prospects of living cell microarrays. PMID:27600077

Microarray Analyses Reveal Marked Differences in Growth Factor and Receptor Expression Between 8-Cell Human Embryos and Pluripotent Stem Cells

PubMed Central

Vlismas, Antonis; Bletsa, Ritsa; Mavrogianni, Despina; Mamali, Georgina; Pergamali, Maria; Dinopoulou, Vasiliki; Partsinevelos, George; Drakakis, Peter; Loutradis, Dimitris

2016-01-01

Previous microarray analyses of RNAs from 8-cell (8C) human embryos revealed a lack of cell cycle checkpoints and overexpression of core circadian oscillators and cell cycle drivers relative to pluripotent human stem cells [human embryonic stem cells/induced pluripotent stem (hES/iPS)] and fibroblasts, suggesting growth factor independence during early cleavage stages. To explore this possibility, we queried our combined microarray database for expression of 487 growth factors and receptors. Fifty-one gene elements were overdetected on the 8C arrays relative to hES/iPS cells, including 14 detected at least 80-fold higher, which annotated to multiple pathways: six cytokine family (CSF1R, IL2RG, IL3RA, IL4, IL17B, IL23R), four transforming growth factor beta (TGFB) family (BMP6, BMP15, GDF9, ENG), one fibroblast growth factor (FGF) family [FGF14(FH4)], one epidermal growth factor member (GAB1), plus CD36, and CLEC10A. 8C-specific gene elements were enriched (73%) for reported circadian-controlled genes in mouse tissues. High-level detection of CSF1R, ENG, IL23R, and IL3RA specifically on the 8C arrays suggests the embryo plays an active role in blocking immune rejection and is poised for trophectoderm development; robust detection of NRG1, GAB1, -2, GRB7, and FGF14(FHF4) indicates novel roles in early development in addition to their known roles in later development. Forty-four gene elements were underdetected on the 8C arrays, including 11 at least 80-fold under the pluripotent cells: two cytokines (IFITM1, TNFRSF8), five TGFBs (BMP7, LEFTY1, LEFTY2, TDGF1, TDGF3), two FGFs (FGF2, FGF receptor 1), plus ING5, and WNT6. The microarray detection patterns suggest that hES/iPS cells exhibit suppressed circadian competence, underexpression of early differentiation markers, and more robust expression of generic pluripotency genes, in keeping with an artificial state of continual uncommitted cell division. In contrast, gene expression patterns of the 8C embryo suggest that

Genetic Interrelatedness among Clover Proliferation Mycoplasmalike Organisms (MLOs) and Other MLOs Investigated by Nucleic Acid Hybridization and Restriction Fragment Length Polymorphism Analyses

PubMed Central

Lee, Ing-Ming; Davis, Robert E.; Hiruki, Chuji

1991-01-01

DNA was isolated from clover proliferation (CP) mycoplasmalike organism (MLO)-diseased periwinkle plants (Catharanthus roseus (L.) G. Don.) and cloned into pSP6 plasmid vectors. CP MLO-specific recombinant DNA clones were biotin labeled and used as probes in dot hybridization and restriction fragment length polymorphism analyses to study the genetic interrelatedness among CP MLO and other MLOs, including potato witches'-broom (PWB) MLO. Results from dot hybridization analyses indicated that both a Maryland strain of aster yellows and a California strain of aster yellows are distantly related to CP MLO. Elm yellows, paulownia witches'-broom, peanut witches'-broom, loofah witches'-broom, and sweet potato witches'-broom may be very distantly related, if at all, to CP MLO. A new Jersey strain of aster yellows MLO, tomato big bud MLO, clover phyllody MLO, beet leafhopper-transmitted virescence MLO, and ash yellows MLO are related to CP MLO, but PWB MLO is the most closely related. Similarity coefficients derived from restriction fragment length polymorphism analyses revealed that PWB and CP MLOs are closely related strains and thus provided direct evidence of their relatedness in contrast to reliance solely on biological characterization. Images PMID:16348604

The Microarray Revolution: Perspectives from Educators

ERIC Educational Resources Information Center

Brewster, Jay L.; Beason, K. Beth; Eckdahl, Todd T.; Evans, Irene M.

2004-01-01

In recent years, microarray analysis has become a key experimental tool, enabling the analysis of genome-wide patterns of gene expression. This review approaches the microarray revolution with a focus upon four topics: 1) the early development of this technology and its application to cancer diagnostics; 2) a primer of microarray research,…

Direct Detection of Drug-Resistant Hepatitis B Virus in Serum Using a Dendron-Modified Microarray

PubMed Central

Kim, Doo Hyun; Kang, Hong Seok; Hur, Seong-Suk; Sim, Seobo; Ahn, Sung Hyun; Park, Yong Kwang; Park, Eun-Sook; Lee, Ah Ram; Park, Soree; Kwon, So Young; Lee, Jeong-Hoon

2018-01-01

Background/Aims Direct sequencing is the gold standard for the detection of drug-resistance mutations in hepatitis B virus (HBV); however, this procedure is time-consuming, labor-intensive, and difficult to adapt to high-throughput screening. In this study, we aimed to develop a dendron-modified DNA microarray for the detection of genotypic resistance mutations and evaluate its efficiency. Methods The specificity, sensitivity, and selectivity of dendron-modified slides for the detection of representative drug-resistance mutations were evaluated and compared to those of conventional slides. The diagnostic accuracy was validated using sera obtained from 13 patients who developed viral breakthrough during lamivudine, adefovir, or entecavir therapy and compared with the accuracy of restriction fragment mass polymorphism and direct sequencing data. Results The dendron-modified slides significantly outperformed the conventional microarray slides and were able to detect HBV DNA at a very low level (1 copy/μL). Notably, HBV mutants could be detected in the chronic hepatitis B patient sera without virus purification. The validation of our data revealed that this technique is fully compatible with sequencing data of drug-resistant HBV. Conclusions We developed a novel diagnostic technique for the simultaneous detection of several drug-resistance mutations using a dendron-modified DNA microarray. This technique can be directly applied to sera from chronic hepatitis B patients who show resistance to several nucleos(t)ide analogues. PMID:29271185

Bridging the Gap Between Large-scale Data Sets and Analyses: Semi-automated Methods to Facilitate Length Polymorphism Scoring and Data Analyses.

EPA Science Inventory

Amplified fragment length polymorphism (AFLP) markers can be developed more quickly and at a lower cost than microsatellite and single nucleotide polymorphism markers, which makes them ideal markers for large-scale studies of understudied taxa — such as species at risk. However,...

Transfection microarray and the applications.

PubMed

Miyake, Masato; Yoshikawa, Tomohiro; Fujita, Satoshi; Miyake, Jun

2009-05-01

Microarray transfection has been extensively studied for high-throughput functional analysis of mammalian cells. However, control of efficiency and reproducibility are the critical issues for practical use. By using solid-phase transfection accelerators and nano-scaffold, we provide a highly efficient and reproducible microarray-transfection device, "transfection microarray". The device would be applied to the limited number of available primary cells and stem cells not only for large-scale functional analysis but also reporter-based time-lapse cellular event analysis.

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

PubMed Central

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

2014-01-01

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

[Microarray CGH: principle and use for constitutional disorders].

PubMed

Sanlaville, D; Lapierre, J M; Coquin, A; Turleau, C; Vermeesch, J; Colleaux, L; Borck, G; Vekemans, M; Aurias, A; Romana, S P

2005-10-01

Chips technology has allowed to miniaturize process making possible to realize in one step and using the same device a lot of chemical reactions. The application of this technology to molecular cytogenetics resulted in the development of comparative genomic hybridization (CGH) on microarrays technique. Using this technique it is possible to detect very small genetic imbalances anywhere in the genome. Its usefulness has been well documented in cancer and more recently in constitutional disorders. In particular it has been used to detect interstitial and subtelomeric submicroscopic imbalances, to characterize their size at the molecular level or to define the breakpoints of translocation. The challenge today is to transfer this technology in laboratory medicine. Nevertheless this technology remains expensive and the existence of numerous sequence polymorphisms makes its interpretation difficult. Finally its is unlikely that it will make karyotyping obsolete as it does not allow to detect balanced rearrangements which after meiotic segregation might result in genome imbalance in the progeny.

Chemiluminescence microarrays in analytical chemistry: a critical review.

PubMed

Seidel, Michael; Niessner, Reinhard

2014-09-01

Multi-analyte immunoassays on microarrays and on multiplex DNA microarrays have been described for quantitative analysis of small organic molecules (e.g., antibiotics, drugs of abuse, small molecule toxins), proteins (e.g., antibodies or protein toxins), and microorganisms, viruses, and eukaryotic cells. In analytical chemistry, multi-analyte detection by use of analytical microarrays has become an innovative research topic because of the possibility of generating several sets of quantitative data for different analyte classes in a short time. Chemiluminescence (CL) microarrays are powerful tools for rapid multiplex analysis of complex matrices. A wide range of applications for CL microarrays is described in the literature dealing with analytical microarrays. The motivation for this review is to summarize the current state of CL-based analytical microarrays. Combining analysis of different compound classes on CL microarrays reduces analysis time, cost of reagents, and use of laboratory space. Applications are discussed, with examples from food safety, water safety, environmental monitoring, diagnostics, forensics, toxicology, and biosecurity. The potential and limitations of research on multiplex analysis by use of CL microarrays are discussed in this review.

cDNA microarray analyses reveal candidate marker genes for the detection of ascidian disease in Korea.

PubMed

Azumi, Kaoru; Usami, Takeshi; Kamimura, Akiko; Sabau, Sorin V; Miki, Yasufumi; Fujie, Manabu; Jung, Sung-Ju; Kitamura, Shin-Ichi; Suzuki, Satoru; Yokosawa, Hideyoshi

2007-12-01

A serious disease of the ascidian Halocynthia roretzi has been spread extensively among Korean aquaculture sites. To reveal the cause of the disease and establish a monitoring system for it, we constructed a cDNA microarray spotted with 2,688 cDNAs derived from H. roretzi hemocyte cDNA libraries to detect genes differentially expressed in hemocytes between diseased and non-diseased ascidians. We detected 21 genes showing increased expression and 16 genes showing decreased expression in hemocytes from diseased ascidians compared with those from non-diseased ascidians. RT-PCR analyses confirmed that the expression levels of genes encoding astacin, lysozyme, ribosomal protein PO, and ubiquitin-ribosomal protein L40e fusion protein were increased in hemocytes from diseased ascidians, while those of genes encoding HSP40, HSP70, fibronectin, carboxypeptidase and lactate dehydrogenase were decreased. These genes were expressed not only in hemocytes but also in various other tissues in ascidians. Furthermore, the expression of glutathione-S transferase omega, which is known to be up-regulated in H. roretzi hemocytes during inflammatory responses, was strongly increased in hemocytes from diseased ascidians. These gene expression profiles suggest that immune and inflammatory reactions occur in the hemocytes of diseased ascidians. These genes will be good markers for detecting and monitoring this disease of ascidians in Korean aquaculture sites.

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

PubMed

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

2016-12-01

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

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

PubMed Central

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

2016-01-01

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

Contributions to Statistical Problems Related to Microarray Data

ERIC Educational Resources Information Center

Hong, Feng

2009-01-01

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

Discovery and mapping of single feature polymorphisms in wheat using Affymetrix arrays

PubMed Central

Bernardo, Amy N; Bradbury, Peter J; Ma, Hongxiang; Hu, Shengwa; Bowden, Robert L; Buckler, Edward S; Bai, Guihua

2009-01-01

Background Wheat (Triticum aestivum L.) is a staple food crop worldwide. The wheat genome has not yet been sequenced due to its huge genome size (~17,000 Mb) and high levels of repetitive sequences; the whole genome sequence may not be expected in the near future. Available linkage maps have low marker density due to limitation in available markers; therefore new technologies that detect genome-wide polymorphisms are still needed to discover a large number of new markers for construction of high-resolution maps. A high-resolution map is a critical tool for gene isolation, molecular breeding and genomic research. Single feature polymorphism (SFP) is a new microarray-based type of marker that is detected by hybridization of DNA or cRNA to oligonucleotide probes. This study was conducted to explore the feasibility of using the Affymetrix GeneChip to discover and map SFPs in the large hexaploid wheat genome. Results Six wheat varieties of diverse origins (Ning 7840, Clark, Jagger, Encruzilhada, Chinese Spring, and Opata 85) were analyzed for significant probe by variety interactions and 396 probe sets with SFPs were identified. A subset of 164 unigenes was sequenced and 54% showed polymorphism within probes. Microarray analysis of 71 recombinant inbred lines from the cross Ning 7840/Clark identified 955 SFPs and 877 of them were mapped together with 269 simple sequence repeat markers. The SFPs were randomly distributed within a chromosome but were unevenly distributed among different genomes. The B genome had the most SFPs, and the D genome had the least. Map positions of a selected set of SFPs were validated by mapping single nucleotide polymorphism using SNaPshot and comparing with expressed sequence tags mapping data. Conclusion The Affymetrix array is a cost-effective platform for SFP discovery and SFP mapping in wheat. The new high-density map constructed in this study will be a useful tool for genetic and genomic research in wheat. PMID:19480702

Switching benchmarks in cancer of unknown primary: from autopsy to microarray.

PubMed

Pentheroudakis, George; Golfinopoulos, Vassilios; Pavlidis, Nicholas

2007-09-01

Cancer of unknown primary (CUP) is associated with unknown biology and dismal prognosis. Information on the primary site of origin is scant and has never been analysed. We systematically reviewed all published evidence on the CUP primary site identified by two different approaches, either autopsy or microarray gene expression profiling. Published reports on identification of CUP primary site by autopsy or microarray-based multigene expression platforms were retrieved and analysed for year of publication, primary site, patient age, gender, histology, rate of primary identification, manifestations and metastatic deposits, microarray chip technology, training and validation sets, mathematical modelling, classification accuracy and number of classifying genes. From 1944 to 2000, a total of 884 CUP patients (66% males) underwent autopsy in 12 studies after presenting with metastatic or systemic symptoms and succumbing to their disease. A primary was identified in 644 (73%) of them, mostly in the lung (27%), pancreas (24%), hepatobiliary tree (8%), kidneys (8%), bowel, genital system and stomach, as a small focus of adenocarcinoma or poorly differentiated carcinoma. An unpredictable systemic dissemination was evident with high frequency of lung (46%), nodal (35%), bone (17%), brain (16%) and uncommon (18%) deposits. Between the 1944-1980 and the 1980-2000 series, female representation increased, 'undetermined neoplasm' diagnosis became rarer, pancreatic primaries were found less often while colonic ones were identified more frequently. Four studies using microarray technology profiled more than 500 CUP cases using classifier set of genes (ranging from 10 to 495) and reported strikingly dissimilar frequencies of assigned primary sites (lung 11.5%, pancreas 12.5%, bowel 12%, breast 15%, hepatobiliary tree 8%, kidneys 6%, genital system 9%, bladder 5%) in 75-90% of the cases. Evolution in medical imaging technology, diet and lifestyle habits probably account for changing

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

PubMed Central

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

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

PubMed

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

2008-09-16

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

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

PubMed

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

2018-04-20

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

An overview of the Progenika ID CORE XT: an automated genotyping platform based on a fluidic microarray system.

PubMed

Goldman, Mindy; Núria, Núria; Castilho, Lilian M

2015-01-01

Automated testing platforms facilitate the introduction of red cell genotyping of patients and blood donors. Fluidic microarray systems, such as Luminex XMAP (Austin, TX), are used in many clinical applications, including HLA and HPA typing. The Progenika ID CORE XT (Progenika Biopharma-Grifols, Bizkaia, Spain) uses this platform to analyze 29 polymorphisms determining 37 antigens in 10 blood group systems. Once DNA has been extracted, processing time is approximately 4 hours. The system is highly automated and includes integrated analysis software that produces a file and a report with genotype and predicted phenotype results.

Importing MAGE-ML format microarray data into BioConductor.

PubMed

Durinck, Steffen; Allemeersch, Joke; Carey, Vincent J; Moreau, Yves; De Moor, Bart

2004-12-12

The microarray gene expression markup language (MAGE-ML) is a widely used XML (eXtensible Markup Language) standard for describing and exchanging information about microarray experiments. It can describe microarray designs, microarray experiment designs, gene expression data and data analysis results. We describe RMAGEML, a new Bioconductor package that provides a link between cDNA microarray data stored in MAGE-ML format and the Bioconductor framework for preprocessing, visualization and analysis of microarray experiments. http://www.bioconductor.org. Open Source.

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

EPA Science Inventory

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

Three reversible polymorphic copper(I) complexes triggered by ligand conformation: insights into polymorphic crystal habit and luminescent properties.

PubMed

Chai, Wenxiang; Hong, Mingwei; Song, Li; Jia, Guohua; Shi, Hongsheng; Guo, Jiayu; Shu, Kangying; Guo, Bing; Zhang, Yicheng; You, Wenwu; Chen, Xueyuan

2015-05-04

Three luminescent polymorphs based on a new copper(I) complex Cu(2-QBO)(PPh3)PF6 (1, PPh3 = triphenylphosphine, 2-QBO = 2-(2'-quinolyl)benzoxazole) have been synthesized and characterized by FT-IR, UV-vis, elemental analyses, and single-crystal X-ray diffraction analyses. Each polymorph can reversibly convert from one to another through appropriate procedures. Interestingly, such interconversion can be distinguished by their intrinsic crystal morphologies and colors (namely α, dark yellow plate, β, orange block, γ, light yellow needle) as well as photoluminescent (PL) properties. X-ray crystal structure analyses of these three polymorphs show three different supramolecular structures from 1D to 3D, which are expected to be responsible for the formation of three different crystal morphologies such as needle, plate, and block. Combination of the experimental data with DFT calculations on these three polymorphs reveals that the polymorphic interconversion is triggered by the conformation isomerization of the 2-QBO ligand and can be successfully controlled by the polarity of the process solvents (affecting the molecular dipole moment) and thermodynamics (affecting the molecular total energy). It is also found that the different crystal colors of polymorphs and their PL properties are derived from different θ values (dihedral angle between benzoxazolyl and quinolyl group of the 2-QBO ligand) and P-Cu-P angles based on TD-DFT calculations. Moreover, an interesting phase interconversion between γ and β has also been found under different temperature, and this result is consistent with the DFT calculations in which the total energy of β is larger than that of γ. This polymorphism provides a good model to study the relationship between the structure and the physical properties in luminescent copper(I) complexes as well as some profound insights into their PL properties.

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

PubMed

Smyth, Gordon K; Altman, Naomi S

2013-05-26

Two-channel (or two-color) microarrays are cost-effective platforms for comparative analysis of gene expression. They are traditionally analysed in terms of the log-ratios (M-values) of the two channel intensities at each spot, but this analysis does not use all the information available in the separate channel observations. Mixed models have been proposed to analyse intensities from the two channels as separate observations, but such models can be complex to use and the gain in efficiency over the log-ratio analysis is difficult to quantify. Mixed models yield test statistics for the null distributions can be specified only approximately, and some approaches do not borrow strength between genes. This article reformulates the mixed model to clarify the relationship with the traditional log-ratio analysis, to facilitate information borrowing between genes, and to obtain an exact distributional theory for the resulting test statistics. The mixed model is transformed to operate on the M-values and A-values (average log-expression for each spot) instead of on the log-expression values. The log-ratio analysis is shown to ignore information contained in the A-values. The relative efficiency of the log-ratio analysis is shown to depend on the size of the intraspot correlation. A new separate channel analysis method is proposed that assumes a constant intra-spot correlation coefficient across all genes. This approach permits the mixed model to be transformed into an ordinary linear model, allowing the data analysis to use a well-understood empirical Bayes analysis pipeline for linear modeling of microarray data. This yields statistically powerful test statistics that have an exact distributional theory. The log-ratio, mixed model and common correlation methods are compared using three case studies. The results show that separate channel analyses that borrow strength between genes are more powerful than log-ratio analyses. The common correlation analysis is the most

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

PubMed Central

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

2008-01-01

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

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

PubMed Central

Kesherwani, Varun; Shahshahan, Hamid R.

2017-01-01

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

Macrophage Gene Expression Associated with Remodeling of the Prepartum Rat Cervix: Microarray and Pathway Analyses

PubMed Central

Dobyns, Abigail E.; Goyal, Ravi; Carpenter, Lauren Grisham; Freeman, Tom C.; Longo, Lawrence D.; Yellon, Steven M.

2015-01-01

As the critical gatekeeper for birth, prepartum remodeling of the cervix is associated with increased resident macrophages (Mφ), proinflammatory processes, and extracellular matrix degradation. This study tested the hypothesis that expression of genes unique to Mφs characterizes the prepartum from unremodeled nonpregnant cervix. Perfused cervix from prepartum day 21 postbreeding (D21) or nonpregnant (NP) rats, with or without Mφs, had RNA extracted and whole genome microarray analysis performed. By subtractive analyses, expression of 194 and 120 genes related to Mφs in the cervix from D21 rats were increased and decreased, respectively. In both D21 and NP groups, 158 and 57 Mφ genes were also more or less up- or down-regulated, respectively. Mφ gene expression patterns were most strongly correlated within groups and in 5 major clustering patterns. In the cervix from D21 rats, functional categories and canonical pathways of increased expression by Mφ gene related to extracellular matrix, cell proliferation, differentiation, as well as cell signaling. Pathways were characteristic of inflammation and wound healing, e.g., CD163, CD206, and CCR2. Signatures of only inflammation pathways, e.g., CSF1R, EMR1, and MMP12 were common to both D21 and NP groups. Thus, a novel and complex balance of Mφ genes and clusters differentiated the degraded extracellular matrix and cellular genomic activities in the cervix before birth from the unremodeled state. Predicted Mφ activities, pathways, and networks raise the possibility that expression patterns of specific genes characterize and promote prepartum remodeling of the cervix for parturition at term and with preterm labor. PMID:25811906

Microfluidic microarray systems and methods thereof

DOEpatents

West, Jay A. A. [Castro Valley, CA; Hukari, Kyle W [San Ramon, CA; Hux, Gary A [Tracy, CA

2009-04-28

Disclosed are systems that include a manifold in fluid communication with a microfluidic chip having a microarray, an illuminator, and a detector in optical communication with the microarray. Methods for using these systems for biological detection are also disclosed.

Oligo Design: a computer program for development of probes for oligonucleotide microarrays.

PubMed

Herold, Keith E; Rasooly, Avraham

2003-12-01

Oligonucleotide microarrays have demonstrated potential for the analysis of gene expression, genotyping, and mutational analysis. Our work focuses primarily on the detection and identification of bacteria based on known short sequences of DNA. Oligo Design, the software described here, automates several design aspects that enable the improved selection of oligonucleotides for use with microarrays for these applications. Two major features of the program are: (i) a tiling algorithm for the design of short overlapping temperature-matched oligonucleotides of variable length, which are useful for the analysis of single nucleotide polymorphisms and (ii) a set of tools for the analysis of multiple alignments of gene families and related short DNA sequences, which allow for the identification of conserved DNA sequences for PCR primer selection and variable DNA sequences for the selection of unique probes for identification. Note that the program does not address the full genome perspective but, instead, is focused on the genetic analysis of short segments of DNA. The program is Internet-enabled and includes a built-in browser and the automated ability to download sequences from GenBank by specifying the GI number. The program also includes several utilities, including audio recital of a DNA sequence (useful for verifying sequences against a written document), a random sequence generator that provides insight into the relationship between melting temperature and GC content, and a PCR calculator.

Thermodynamically optimal whole-genome tiling microarray design and validation.

PubMed

Cho, Hyejin; Chou, Hui-Hsien

2016-06-13

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

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

PubMed

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

2018-01-01

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

Improved prediction of biochemical recurrence after radical prostatectomy by genetic polymorphisms.

PubMed

Morote, Juan; Del Amo, Jokin; Borque, Angel; Ars, Elisabet; Hernández, Carlos; Herranz, Felipe; Arruza, Antonio; Llarena, Roberto; Planas, Jacques; Viso, María J; Palou, Joan; Raventós, Carles X; Tejedor, Diego; Artieda, Marta; Simón, Laureano; Martínez, Antonio; Rioja, Luis A

2010-08-01

Single nucleotide polymorphisms are inherited genetic variations that can predispose or protect individuals against clinical events. We hypothesized that single nucleotide polymorphism profiling may improve the prediction of biochemical recurrence after radical prostatectomy. We performed a retrospective, multi-institutional study of 703 patients treated with radical prostatectomy for clinically localized prostate cancer who had at least 5 years of followup after surgery. All patients were genotyped for 83 prostate cancer related single nucleotide polymorphisms using a low density oligonucleotide microarray. Baseline clinicopathological variables and single nucleotide polymorphisms were analyzed to predict biochemical recurrence within 5 years using stepwise logistic regression. Discrimination was measured by ROC curve AUC, specificity, sensitivity, predictive values, net reclassification improvement and integrated discrimination index. The overall biochemical recurrence rate was 35%. The model with the best fit combined 8 covariates, including the 5 clinicopathological variables prostate specific antigen, Gleason score, pathological stage, lymph node involvement and margin status, and 3 single nucleotide polymorphisms at the KLK2, SULT1A1 and TLR4 genes. Model predictive power was defined by 80% positive predictive value, 74% negative predictive value and an AUC of 0.78. The model based on clinicopathological variables plus single nucleotide polymorphisms showed significant improvement over the model without single nucleotide polymorphisms, as indicated by 23.3% net reclassification improvement (p = 0.003), integrated discrimination index (p <0.001) and likelihood ratio test (p <0.001). Internal validation proved model robustness (bootstrap corrected AUC 0.78, range 0.74 to 0.82). The calibration plot showed close agreement between biochemical recurrence observed and predicted probabilities. Predicting biochemical recurrence after radical prostatectomy based on

cDNA Microarray Screening in Food Safety

PubMed Central

ROY, SASHWATI; SEN, CHANDAN K

2009-01-01

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. PMID:16466843

Polyadenylation state microarray (PASTA) analysis.

PubMed

Beilharz, Traude H; Preiss, Thomas

2011-01-01

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

Development of a Digital Microarray with Interferometric Reflectance Imaging

NASA Astrophysics Data System (ADS)

Sevenler, Derin

This dissertation describes a new type of molecular assay for nucleic acids and proteins. We call this technique a digital microarray since it is conceptually similar to conventional fluorescence microarrays, yet it performs enumerative ('digital') counting of the number captured molecules. Digital microarrays are approximately 10,000-fold more sensitive than fluorescence microarrays, yet maintain all of the strengths of the platform including low cost and high multiplexing (i.e., many different tests on the same sample simultaneously). Digital microarrays use gold nanorods to label the captured target molecules. Each gold nanorod on the array is individually detected based on its light scattering, with an interferometric microscopy technique called SP-IRIS. Our optimized high-throughput version of SP-IRIS is able to scan a typical array of 500 spots in less than 10 minutes. Digital DNA microarrays may have utility in applications where sequencing is prohibitively expensive or slow. As an example, we describe a digital microarray assay for gene expression markers of bacterial drug resistance.

Single-base-pair discrimination of terminal mismatches by using oligonucleotide microarrays and neural network analyses

NASA Technical Reports Server (NTRS)

Urakawa, Hidetoshi; Noble, Peter A.; El Fantroussi, Said; Kelly, John J.; Stahl, David A.

2002-01-01

The effects of single-base-pair near-terminal and terminal mismatches on the dissociation temperature (T(d)) and signal intensity of short DNA duplexes were determined by using oligonucleotide microarrays and neural network (NN) analyses. Two perfect-match probes and 29 probes having a single-base-pair mismatch at positions 1 to 5 from the 5' terminus of the probe were designed to target one of two short sequences representing 16S rRNA. Nonequilibrium dissociation rates (i.e., melting profiles) of all probe-target duplexes were determined simultaneously. Analysis of variance revealed that position of the mismatch, type of mismatch, and formamide concentration significantly affected the T(d) and signal intensity. Increasing the concentration of formamide in the washing buffer decreased the T(d) and signal intensity, and it decreased the variability of the signal. Although T(d)s of probe-target duplexes with mismatches in the first or second position were not significantly different from one another, duplexes with mismatches in the third to fifth positions had significantly lower T(d)s than those with mismatches in the first or second position. The trained NNs predicted the T(d) with high accuracies (R(2) = 0.93). However, the NNs predicted the signal intensity only moderately accurately (R(2) = 0.67), presumably due to increased noise in the signal intensity at low formamide concentrations. Sensitivity analysis revealed that the concentration of formamide explained most (75%) of the variability in T(d)s, followed by position of the mismatch (19%) and type of mismatch (6%). The results suggest that position of the mismatch at or near the 5' terminus plays a greater role in determining the T(d) and signal intensity of duplexes than the type of mismatch.

Korean, Japanese, and Chinese populations featured similar genes encoding drug-metabolizing enzymes and transporters: a DMET Plus microarray assessment.

PubMed

Yi, SoJeong; An, Hyungmi; Lee, Howard; Lee, Sangin; Ieiri, Ichiro; Lee, Youngjo; Cho, Joo-Youn; Hirota, Takeshi; Fukae, Masato; Yoshida, Kenji; Nagatsuka, Shinichiro; Kimura, Miyuki; Irie, Shin; Sugiyama, Yuichi; Shin, Dong Wan; Lim, Kyoung Soo; Chung, Jae-Yong; Yu, Kyung-Sang; Jang, In-Jin

2014-10-01

Interethnic differences in genetic polymorphism in genes encoding drug-metabolizing enzymes and transporters are one of the major factors that cause ethnic differences in drug response. This study aimed to investigate genetic polymorphisms in genes involved in drug metabolism, transport, and excretion among Korean, Japanese, and Chinese populations, the three major East Asian ethnic groups. The frequencies of 1936 variants representing 225 genes encoding drug-metabolizing enzymes and transporters were determined from 786 healthy participants (448 Korean, 208 Japanese, and 130 Chinese) using the Affymetrix Drug-Metabolizing Enzymes and Transporters Plus microarray. To compare allele or genotype frequencies in the high-dimensional data among the three East Asian ethnic groups, multiple testing, principal component analysis (PCA), and regularized multinomial logit model through least absolute shrinkage and selection operator were used. On microarray analysis, 1071 of 1936 variants (>50% of markers) were found to be monomorphic. In a large number of genetic variants, the fixation index and Pearson's correlation coefficient of minor allele frequencies were less than 0.034 and greater than 0.95, respectively, among the three ethnic groups. PCA identified 47 genetic variants with multiple testing, but was unable to discriminate ethnic groups by the first three components. Multinomial least absolute shrinkage and selection operator analysis identified 269 genetic variants that showed different frequencies among the three ethnic groups. However, none of those variants distinguished between the three ethnic groups during subsequent PCA. Korean, Japanese, and Chinese populations are not pharmacogenetically distant from one another, at least with regard to drug disposition, metabolism, and elimination.

Fabrication of Carbohydrate Microarrays by Boronate Formation.

PubMed

Adak, Avijit K; Lin, Ting-Wei; Li, Ben-Yuan; Lin, Chun-Cheng

2017-01-01

The interactions between soluble carbohydrates and/or surface displayed glycans and protein receptors are essential to many biological processes and cellular recognition events. Carbohydrate microarrays provide opportunities for high-throughput quantitative analysis of carbohydrate-protein interactions. Over the past decade, various techniques have been implemented for immobilizing glycans on solid surfaces in a microarray format. Herein, we describe a detailed protocol for fabricating carbohydrate microarrays that capitalizes on the intrinsic reactivity of boronic acid toward carbohydrates to form stable boronate diesters. A large variety of unprotected carbohydrates ranging in structure from simple disaccharides and trisaccharides to considerably more complex human milk and blood group (oligo)saccharides have been covalently immobilized in a single step on glass slides, which were derivatized with high-affinity boronic acid ligands. The immobilized ligands in these microarrays maintain the receptor-binding activities including those of lectins and antibodies according to the structures of their pendant carbohydrates for rapid analysis of a number of carbohydrate-recognition events within 30 h. This method facilitates the direct construction of otherwise difficult to obtain carbohydrate microarrays from underivatized glycans.

Plant-pathogen interactions: what microarray tells about it?

PubMed

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.

Chromosomal Microarray versus Karyotyping for Prenatal Diagnosis

PubMed Central

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

2013-01-01

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

Nanotechnology: moving from microarrays toward nanoarrays.

PubMed

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

MedlinePlus

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 ...

Microarray gene expression profiling analysis combined with bioinformatics in multiple sclerosis.

PubMed

Liu, Mingyuan; Hou, Xiaojun; Zhang, Ping; Hao, Yong; Yang, Yiting; Wu, Xiongfeng; Zhu, Desheng; Guan, Yangtai

2013-05-01

Multiple sclerosis (MS) is the most prevalent demyelinating disease and the principal cause of neurological disability in young adults. Recent microarray gene expression profiling studies have identified several genetic variants contributing to the complex pathogenesis of MS, however, expressional and functional studies are still required to further understand its molecular mechanism. The present study aimed to analyze the molecular mechanism of MS using microarray analysis combined with bioinformatics techniques. We downloaded the gene expression profile of MS from Gene Expression Omnibus (GEO) and analysed the microarray data using the differentially coexpressed genes (DCGs) and links package in R and Database for Annotation, Visualization and Integrated Discovery. The regulatory impact factor (RIF) algorithm was used to measure the impact factor of transcription factor. A total of 1,297 DCGs between MS patients and healthy controls were identified. Functional annotation indicated that these DCGs were associated with immune and neurological functions. Furthermore, the RIF result suggested that IKZF1, BACH1, CEBPB, EGR1, FOS may play central regulatory roles in controlling gene expression in the pathogenesis of MS. Our findings confirm the presence of multiple molecular alterations in MS and indicate the possibility for identifying prognostic factors associated with MS pathogenesis.

Carbohydrate Microarray Technology Applied to High-Throughput Mapping of Plant Cell Wall Glycans Using Comprehensive Microarray Polymer Profiling (CoMPP).

PubMed

Kračun, Stjepan Krešimir; Fangel, Jonatan Ulrik; Rydahl, Maja Gro; Pedersen, Henriette Lodberg; Vidal-Melgosa, Silvia; Willats, William George Tycho

2017-01-01

Cell walls are an important feature of plant cells and a major component of the plant glycome. They have both structural and physiological functions and are critical for plant growth and development. The diversity and complexity of these structures demand advanced high-throughput techniques to answer questions about their structure, functions and roles in both fundamental and applied scientific fields. Microarray technology provides both the high-throughput and the feasibility aspects required to meet that demand. In this chapter, some of the most recent microarray-based techniques relating to plant cell walls are described together with an overview of related contemporary techniques applied to carbohydrate microarrays and their general potential in glycoscience. A detailed experimental procedure for high-throughput mapping of plant cell wall glycans using the comprehensive microarray polymer profiling (CoMPP) technique is included in the chapter and provides a good example of both the robust and high-throughput nature of microarrays as well as their applicability to plant glycomics.

Serotyping of Streptococcus pneumoniae Based on Capsular Genes Polymorphisms

PubMed Central

Raymond, Frédéric; Boucher, Nancy; Allary, Robin; Robitaille, Lynda; Lefebvre, Brigitte; Tremblay, Cécile

2013-01-01

Streptococcus pneumoniae serotype epidemiology is essential since serotype replacement is a concern when introducing new polysaccharide-conjugate vaccines. A novel PCR-based automated microarray assay was developed to assist in the tracking of the serotypes. Autolysin, pneumolysin and eight genes located in the capsular operon were amplified using multiplex PCR. This step was followed by a tagged fluorescent primer extension step targeting serotype-specific polymorphisms. The tagged primers were then hybridized to a microarray. Results were exported to an expert system to identify capsular serotypes. The assay was validated on 166 cultured S. pneumoniae samples from 63 different serotypes as determined by the Quellung method. We show that typing only 12 polymorphisms located in the capsular operon allows the identification at the serotype level of 22 serotypes and the assignation of 24 other serotypes to a subgroup of serotypes. Overall, 126 samples (75.9%) were correctly serotyped, 14 were assigned to a member of the same serogroup, 8 rare serotypes were erroneously serotyped, and 18 gave negative serotyping results. Most of the discrepancies involved rare serotypes or serotypes that are difficult to discriminate using a DNA-based approach, for example 6A and 6B. The assay was also tested on clinical specimens including 43 cerebrospinal fluid samples from patients with meningitis and 59 nasopharyngeal aspirates from bacterial pneumonia patients. Overall, 89% of specimens positive for pneumolysin were serotyped, demonstrating that this method does not require culture to serotype clinical specimens. The assay showed no cross-reactivity for 24 relevant bacterial species found in these types of samples. The limit of detection for serotyping and S. pneumoniae detection was 100 genome equivalent per reaction. This automated assay is amenable to clinical testing and does not require any culturing of the samples. The assay will be useful for the evaluation of serotype

Principles of gene microarray data analysis.

PubMed

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.

The Diversity of REcent and Ancient huMan (DREAM): A New Microarray for Genetic Anthropology and Genealogy, Forensics, and Personalized Medicine

PubMed Central

Yusuf, Leeban; Anderson, Ainan I J; Pirooznia, Mehdi; Arnellos, Dimitrios; Vilshansky, Gregory; Ercal, Gunes; Lu, Yontao; Webster, Teresa; Baird, Michael L; Esposito, Umberto

2017-01-01

Abstract The human population displays wide variety in demographic history, ancestry, content of DNA derived from hominins or ancient populations, adaptation, traits, copy number variation, drug response, and more. These polymorphisms are of broad interest to population geneticists, forensics investigators, and medical professionals. Historically, much of that knowledge was gained from population survey projects. Although many commercial arrays exist for genome-wide single-nucleotide polymorphism genotyping, their design specifications are limited and they do not allow a full exploration of biodiversity. We thereby aimed to design the Diversity of REcent and Ancient huMan (DREAM)—an all-inclusive microarray that would allow both identification of known associations and exploration of standing questions in genetic anthropology, forensics, and personalized medicine. DREAM includes probes to interrogate ancestry informative markers obtained from over 450 human populations, over 200 ancient genomes, and 10 archaic hominins. DREAM can identify 94% and 61% of all known Y and mitochondrial haplogroups, respectively, and was vetted to avoid interrogation of clinically relevant markers. To demonstrate its capabilities, we compared its FST distributions with those of the 1000 Genomes Project and commercial arrays. Although all arrays yielded similarly shaped (inverse J) FST distributions, DREAM’s autosomal and X-chromosomal distributions had the highest mean FST, attesting to its ability to discern subpopulations. DREAM performances are further illustrated in biogeographical, identical by descent, and copy number variation analyses. In summary, with approximately 800,000 markers spanning nearly 2,000 genes, DREAM is a useful tool for genetic anthropology, forensic, and personalized medicine studies. PMID:29165562

[Oligonucleotide microarray for subtyping avian influenza virus].

PubMed

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

2008-09-01

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

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

PubMed

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

2017-04-01

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

Recent progress in making protein microarray through BioLP

NASA Astrophysics Data System (ADS)

Yang, Rusong; Wei, Lian; Feng, Ying; Li, Xiujian; Zhou, Quan

2017-02-01

Biological laser printing (BioLP) is a promising biomaterial printing technique. It has the advantage of high resolution, high bioactivity, high printing frequency and small transported liquid amount. In this paper, a set of BioLP device is design and made, and protein microarrays are printed by this device. It's found that both laser intensity and fluid layer thickness have an influence on the microarrays acquired. Besides, two kinds of the fluid layer coating methods are compared, and the results show that blade coating method is better than well-coating method in BioLP. A microarray of 0.76pL protein microarray and a "NUDT" patterned microarray are printed to testify the printing ability of BioLP.

Cell-Based Microarrays for In Vitro Toxicology

NASA Astrophysics Data System (ADS)

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.

Microbial forensics: fiber optic microarray subtyping of Bacillus anthracis

NASA Astrophysics Data System (ADS)

Shepard, Jason R. E.

2009-05-01

The past decade has seen increased development and subsequent adoption of rapid molecular techniques involving DNA analysis for detection of pathogenic microorganisms, also termed microbial forensics. The continued accumulation of microbial sequence information in genomic databases now better positions the field of high-throughput DNA analysis to proceed in a more manageable fashion. The potential to build off of these databases exists as technology continues to develop, which will enable more rapid, cost effective analyses. This wealth of genetic information, along with new technologies, has the potential to better address some of the current problems and solve the key issues involved in DNA analysis of pathogenic microorganisms. To this end, a high density fiber optic microarray has been employed, housing numerous DNA sequences simultaneously for detection of various pathogenic microorganisms, including Bacillus anthracis, among others. Each organism is analyzed with multiple sequences and can be sub-typed against other closely related organisms. For public health labs, real-time PCR methods have been developed as an initial preliminary screen, but culture and growth are still considered the gold standard. Technologies employing higher throughput than these standard methods are better suited to capitalize on the limitless potential garnered from the sequence information. Microarray analyses are one such format positioned to exploit this potential, and our array platform is reusable, allowing repetitive tests on a single array, providing an increase in throughput and decrease in cost, along with a certainty of detection, down to the individual strain level.

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

PubMed Central

2010-01-01

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

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

PubMed

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

2010-10-21

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

A High-Density Genetic Map with Array-Based Markers Facilitates Structural and Quantitative Trait Locus Analyses of the Common Wheat Genome

PubMed Central

Iehisa, Julio Cesar Masaru; Ohno, Ryoko; Kimura, Tatsuro; Enoki, Hiroyuki; Nishimura, Satoru; Okamoto, Yuki; Nasuda, Shuhei; Takumi, Shigeo

2014-01-01

The large genome and allohexaploidy of common wheat have complicated construction of a high-density genetic map. Although improvements in the throughput of next-generation sequencing (NGS) technologies have made it possible to obtain a large amount of genotyping data for an entire mapping population by direct sequencing, including hexaploid wheat, a significant number of missing data points are often apparent due to the low coverage of sequencing. In the present study, a microarray-based polymorphism detection system was developed using NGS data obtained from complexity-reduced genomic DNA of two common wheat cultivars, Chinese Spring (CS) and Mironovskaya 808. After design and selection of polymorphic probes, 13,056 new markers were added to the linkage map of a recombinant inbred mapping population between CS and Mironovskaya 808. On average, 2.49 missing data points per marker were observed in the 201 recombinant inbred lines, with a maximum of 42. Around 40% of the new markers were derived from genic regions and 11% from repetitive regions. The low number of retroelements indicated that the new polymorphic markers were mainly derived from the less repetitive region of the wheat genome. Around 25% of the mapped sequences were useful for alignment with the physical map of barley. Quantitative trait locus (QTL) analyses of 14 agronomically important traits related to flowering, spikes, and seeds demonstrated that the new high-density map showed improved QTL detection, resolution, and accuracy over the original simple sequence repeat map. PMID:24972598

Evaluating concentration estimation errors in ELISA microarray experiments

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

Daly, Don S.; White, Amanda M.; Varnum, Susan M.

Enzyme-linked immunosorbent assay (ELISA) is a standard immunoassay to predict a protein concentration in a sample. Deploying ELISA in a microarray format permits simultaneous prediction of the concentrations of numerous proteins in a small sample. These predictions, however, are uncertain due to processing error and biological variability. Evaluating prediction error is critical to interpreting biological significance and improving the ELISA microarray process. Evaluating prediction error must be automated to realize a reliable high-throughput ELISA microarray system. Methods: In this paper, we present a statistical method based on propagation of error to evaluate prediction errors in the ELISA microarray process. Althoughmore » propagation of error is central to this method, it is effective only when comparable data are available. Therefore, we briefly discuss the roles of experimental design, data screening, normalization and statistical diagnostics when evaluating ELISA microarray prediction errors. We use an ELISA microarray investigation of breast cancer biomarkers to illustrate the evaluation of prediction errors. The illustration begins with a description of the design and resulting data, followed by a brief discussion of data screening and normalization. In our illustration, we fit a standard curve to the screened and normalized data, review the modeling diagnostics, and apply propagation of error.« less

Multi-membership gene regulation in pathway based microarray analysis

PubMed Central

2011-01-01

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

Multi-membership gene regulation in pathway based microarray analysis.

PubMed

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

2011-09-22

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

Micro-Analyzer: automatic preprocessing of Affymetrix microarray data.

PubMed

Guzzi, Pietro Hiram; Cannataro, Mario

2013-08-01

A current trend in genomics is the investigation of the cell mechanism using different technologies, in order to explain the relationship among genes, molecular processes and diseases. For instance, the combined use of gene-expression arrays and genomic arrays has been demonstrated as an effective instrument in clinical practice. Consequently, in a single experiment different kind of microarrays may be used, resulting in the production of different types of binary data (images and textual raw data). The analysis of microarray data requires an initial preprocessing phase, that makes raw data suitable for use on existing analysis platforms, such as the TIGR M4 (TM4) Suite. An additional challenge to be faced by emerging data analysis platforms is the ability to treat in a combined way those different microarray formats coupled with clinical data. In fact, resulting integrated data may include both numerical and symbolic data (e.g. gene expression and SNPs regarding molecular data), as well as temporal data (e.g. the response to a drug, time to progression and survival rate), regarding clinical data. Raw data preprocessing is a crucial step in analysis but is often performed in a manual and error prone way using different software tools. Thus novel, platform independent, and possibly open source tools enabling the semi-automatic preprocessing and annotation of different microarray data are needed. The paper presents Micro-Analyzer (Microarray Analyzer), a cross-platform tool for the automatic normalization, summarization and annotation of Affymetrix gene expression and SNP binary data. It represents the evolution of the μ-CS tool, extending the preprocessing to SNP arrays that were not allowed in μ-CS. The Micro-Analyzer is provided as a Java standalone tool and enables users to read, preprocess and analyse binary microarray data (gene expression and SNPs) by invoking TM4 platform. It avoids: (i) the manual invocation of external tools (e.g. the Affymetrix Power

Analysis and modelling of septic shock microarray data using Singular Value Decomposition.

PubMed

Allanki, Srinivas; Dixit, Madhulika; Thangaraj, Paul; Sinha, Nandan Kumar

2017-06-01

Being a high throughput technique, enormous amounts of microarray data has been generated and there arises a need for more efficient techniques of analysis, in terms of speed and accuracy. Finding the differentially expressed genes based on just fold change and p-value might not extract all the vital biological signals that occur at a lower gene expression level. Besides this, numerous mathematical models have been generated to predict the clinical outcome from microarray data, while very few, if not none, aim at predicting the vital genes that are important in a disease progression. Such models help a basic researcher narrow down and concentrate on a promising set of genes which leads to the discovery of gene-based therapies. In this article, as a first objective, we have used the lesser known and used Singular Value Decomposition (SVD) technique to build a microarray data analysis tool that works with gene expression patterns and intrinsic structure of the data in an unsupervised manner. We have re-analysed a microarray data over the clinical course of Septic shock from Cazalis et al. (2014) and have shown that our proposed analysis provides additional information compared to the conventional method. As a second objective, we developed a novel mathematical model that predicts a set of vital genes in the disease progression that works by generating samples in the continuum between health and disease, using a simple normal-distribution-based random number generator. We also verify that most of the predicted genes are indeed related to septic shock. Copyright © 2017 Elsevier Inc. All rights reserved.

Enhancing Results of Microarray Hybridizations Through Microagitation

PubMed Central

Toegl, Andreas; Kirchner, Roland; Gauer, Christoph; Wixforth, Achim

2003-01-01

Protein and DNA microarrays have become a standard tool in proteomics/genomics research. In order to guarantee fast and reproducible hybridization results, the diffusion limit must be overcome. Surface acoustic wave (SAW) micro-agitation chips efficiently agitate the smallest sample volumes (down to 10 μL and below) without introducing any dead volume. The advantages are reduced reaction time, increased signal-to-noise ratio, improved homogeneity across the microarray, and better slide-to-slide reproducibility. The SAW micromixer chips are the heart of the Advalytix ArrayBooster, which is compatible with all microarrays based on the microscope slide format. PMID:13678150

Progress in the application of DNA microarrays.

PubMed Central

Lobenhofer, E K; Bushel, P R; Afshari, C A; Hamadeh, H K

2001-01-01

Microarray technology has been applied to a variety of different fields to address fundamental research questions. The use of microarrays, or DNA chips, to study the gene expression profiles of biologic samples began in 1995. Since that time, the fundamental concepts behind the chip, the technology required for making and using these chips, and the multitude of statistical tools for analyzing the data have been extensively reviewed. For this reason, the focus of this review will be not on the technology itself but on the application of microarrays as a research tool and the future challenges of the field. PMID:11673116

Microintaglio Printing for Soft Lithography-Based in Situ Microarrays

PubMed Central

Biyani, Manish; Ichiki, Takanori

2015-01-01

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. PMID:27600226

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

PubMed

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

2008-08-04

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

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

PubMed

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 < .0001) or intrauterine growth retardation group (50.0% vs 14.3%, P = .044) was significantly higher than that in isolated 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 < .0001). No significant difference was observed in the detection rates between 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

Restriction Site Tiling Analysis: accurate discovery and quantitative genotyping of genome-wide polymorphisms using nucleotide arrays

PubMed Central

2010-01-01

High-throughput genotype data can be used to identify genes important for local adaptation in wild populations, phenotypes in lab stocks, or disease-related traits in human medicine. Here we advance microarray-based genotyping for population genomics with Restriction Site Tiling Analysis. The approach simultaneously discovers polymorphisms and provides quantitative genotype data at 10,000s of loci. It is highly accurate and free from ascertainment bias. We apply the approach to uncover genomic differentiation in the purple sea urchin. PMID:20403197

EDGE3: A web-based solution for management and analysis of Agilent two color microarray experiments

PubMed Central

Vollrath, Aaron L; Smith, Adam A; Craven, Mark; Bradfield, Christopher A

2009-01-01

Background The ability to generate transcriptional data on the scale of entire genomes has been a boon both in the improvement of biological understanding and in the amount of data generated. The latter, the amount of data generated, has implications when it comes to effective storage, analysis and sharing of these data. A number of software tools have been developed to store, analyze, and share microarray data. However, a majority of these tools do not offer all of these features nor do they specifically target the commonly used two color Agilent DNA microarray platform. Thus, the motivating factor for the development of EDGE3 was to incorporate the storage, analysis and sharing of microarray data in a manner that would provide a means for research groups to collaborate on Agilent-based microarray experiments without a large investment in software-related expenditures or extensive training of end-users. Results EDGE3 has been developed with two major functions in mind. The first function is to provide a workflow process for the generation of microarray data by a research laboratory or a microarray facility. The second is to store, analyze, and share microarray data in a manner that doesn't require complicated software. To satisfy the first function, EDGE3 has been developed as a means to establish a well defined experimental workflow and information system for microarray generation. To satisfy the second function, the software application utilized as the user interface of EDGE3 is a web browser. Within the web browser, a user is able to access the entire functionality, including, but not limited to, the ability to perform a number of bioinformatics based analyses, collaborate between research groups through a user-based security model, and access to the raw data files and quality control files generated by the software used to extract the signals from an array image. Conclusion Here, we present EDGE3, an open-source, web-based application that allows for the

EDGE(3): a web-based solution for management and analysis of Agilent two color microarray experiments.

PubMed

Vollrath, Aaron L; Smith, Adam A; Craven, Mark; Bradfield, Christopher A

2009-09-04

The ability to generate transcriptional data on the scale of entire genomes has been a boon both in the improvement of biological understanding and in the amount of data generated. The latter, the amount of data generated, has implications when it comes to effective storage, analysis and sharing of these data. A number of software tools have been developed to store, analyze, and share microarray data. However, a majority of these tools do not offer all of these features nor do they specifically target the commonly used two color Agilent DNA microarray platform. Thus, the motivating factor for the development of EDGE(3) was to incorporate the storage, analysis and sharing of microarray data in a manner that would provide a means for research groups to collaborate on Agilent-based microarray experiments without a large investment in software-related expenditures or extensive training of end-users. EDGE(3) has been developed with two major functions in mind. The first function is to provide a workflow process for the generation of microarray data by a research laboratory or a microarray facility. The second is to store, analyze, and share microarray data in a manner that doesn't require complicated software. To satisfy the first function, EDGE3 has been developed as a means to establish a well defined experimental workflow and information system for microarray generation. To satisfy the second function, the software application utilized as the user interface of EDGE(3) is a web browser. Within the web browser, a user is able to access the entire functionality, including, but not limited to, the ability to perform a number of bioinformatics based analyses, collaborate between research groups through a user-based security model, and access to the raw data files and quality control files generated by the software used to extract the signals from an array image. Here, we present EDGE(3), an open-source, web-based application that allows for the storage, analysis, and

On-Chip Synthesis of Protein Microarrays from DNA Microarrays Via Coupled In Vitro Transcription and Translation for Surface Plasmon Resonance Imaging Biosensor Applications

PubMed Central

Seefeld, Ting H.; Halpern, Aaron R.; Corn, Robert M.

2012-01-01

Protein microarrays are fabricated from double-stranded DNA (dsDNA) microarrays by a one-step, multiplexed enzymatic synthesis in an on-chip microfluidic format and then employed for antibody biosensing measurements with surface plasmon resonance imaging (SPRI). A microarray of dsDNA elements (denoted as generator elements) that encode either a His-tagged green fluorescent protein (GFP) or a His-tagged luciferase protein is utilized to create multiple copies of messenger RNA (mRNA) in a surface RNA polymerase reaction; the mRNA transcripts are then translated into proteins by cell-free protein synthesis in a microfluidic format. The His-tagged proteins diffuse to adjacent Cu(II)-NTA microarray elements (denoted as detector elements) and are specifically adsorbed. The net result is the on-chip, cell-free synthesis of a protein microarray that can be used immediately for SPRI protein biosensing. The dual element format greatly reduces any interference from the nonspecific adsorption of enzyme or proteins. SPRI measurements for the detection of the antibodies anti-GFP and anti-luciferase were used to verify the formation of the protein microarray. This convenient on-chip protein microarray fabrication method can be implemented for multiplexed SPRI biosensing measurements in both clinical and research applications. PMID:22793370

cDNA microarray analysis of esophageal cancer: discoveries and prospects.

PubMed

Shimada, Yutaka; Sato, Fumiaki; Shimizu, Kazuharu; Tsujimoto, Gozoh; Tsukada, Kazuhiro

2009-07-01

Recent progress in molecular biology has revealed many genetic and epigenetic alterations that are involved in the development and progression of esophageal cancer. Microarray analysis has also revealed several genetic networks that are involved in esophageal cancer. However, clinical application of microarray techniques and use of microarray data have not yet occurred. In this review, we focus on the recent developments and problems with microarray analysis of esophageal cancer.

A perspective on DNA microarray technology in food and nutritional science.

PubMed

Kato, Hisanori; Saito, Kenji; Kimura, Takeshi

2005-09-01

The functions of nutrients and other foods have been revealed at the level of gene regulation. The advent of DNA microarray technology has enabled us to analyze the body's response to these factors in a much more holistic manner than before. This review is intended to overview the present status of this DNA microarray technology, hoping to provide food and nutrition scientists, especially those who are planning to introduce this technology, with hints and suggestions. The number of papers examining transcriptomics analysis in food and nutrition science has expanded over the last few years. The effects of some dietary conditions and administration of specific nutrients or food factors are studied in various animal models and cultured cells. The target food components range from macronutrients and micronutrients to other functional food factors. Such studies have already yielded fruitful results, which include discovery of novel functions of a food, uncovering hitherto unknown mechanisms of action, and analyses of food safety. The potency of DNA microarray technology in food and nutrition science is broadly recognized. This technique will surely continue to provide researchers and the public with valuable information on the beneficial and adverse effects of food factors. It should also be acknowledged, however, that there remain problems such as standardization of the data and sharing of the results among researchers in this field.

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

EPA Science Inventory

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

Development of a DNA Microarray-Based Assay for the Detection of Sugar Beet Root Rot Pathogens.

PubMed

Liebe, Sebastian; Christ, Daniela S; Ehricht, Ralf; Varrelmann, Mark

2016-01-01

Sugar beet root rot diseases that occur during the cropping season or in storage are accompanied by high yield losses and a severe reduction of processing quality. The vast diversity of microorganism species involved in rot development requires molecular tools allowing simultaneous identification of many different targets. Therefore, a new microarray technology (ArrayTube) was applied in this study to improve diagnosis of sugar beet root rot diseases. Based on three marker genes (internal transcribed spacer, translation elongation factor 1 alpha, and 16S ribosomal DNA), 42 well-performing probes enabled the identification of prevalent field pathogens (e.g., Aphanomyces cochlioides), storage pathogens (e.g., Botrytis cinerea), and ubiquitous spoilage fungi (e.g., Penicillium expansum). All probes were proven for specificity with pure cultures from 73 microorganism species as well as for in planta detection of their target species using inoculated sugar beet tissue. Microarray-based identification of root rot pathogens in diseased field beets was successfully confirmed by classical detection methods. The high discriminatory potential was proven by Fusarium species differentiation based on a single nucleotide polymorphism. The results demonstrate that the ArrayTube constitute an innovative tool allowing a rapid and reliable detection of plant pathogens particularly when multiple microorganism species are present.

Genome-wide divergence and linkage disequilibrium analyses for Capsicum baccatum revealed by genome-anchored single nucleotide polymorphisms

USDA-ARS?s Scientific Manuscript database

Principal component analysis (PCA) with 36,621 polymorphic genome-anchored single nucleotide polymorphisms (SNPs) identified collectively for Capsicum annuum and Capsicum baccatum was used to show the distribution of these 2 important incompatible cultivated pepper species. Estimated mean nucleotide...

Massive Collection of Full-Length Complementary DNA Clones and Microarray Analyses:. Keys to Rice Transcriptome Analysis

NASA Astrophysics Data System (ADS)

Kikuchi, Shoshi

2009-02-01

Completion of the high-precision genome sequence analysis of rice led to the collection of about 35,000 full-length cDNA clones and the determination of their complete sequences. Mapping of these full-length cDNA sequences has given us information on (1) the number of genes expressed in the rice genome; (2) the start and end positions and exon-intron structures of rice genes; (3) alternative transcripts; (4) possible encoded proteins; (5) non-protein-coding (np) RNAs; (6) the density of gene localization on the chromosome; (7) setting the parameters of gene prediction programs; and (8) the construction of a microarray system that monitors global gene expression. Manual curation for rice gene annotation by using mapping information on full-length cDNA and EST assemblies has revealed about 32,000 expressed genes in the rice genome. Analysis of major gene families, such as those encoding membrane transport proteins (pumps, ion channels, and secondary transporters), along with the evolution from bacteria to higher animals and plants, reveals how gene numbers have increased through adaptation to circumstances. Family-based gene annotation also gives us a new way of comparing organisms. Massive amounts of data on gene expression under many kinds of physiological conditions are being accumulated in rice oligoarrays (22K and 44K) based on full-length cDNA sequences. Cluster analyses of genes that have the same promoter cis-elements, that have similar expression profiles, or that encode enzymes in the same metabolic pathways or signal transduction cascades give us clues to understanding the networks of gene expression in rice. As a tool for that purpose, we recently developed "RiCES", a tool for searching for cis-elements in the promoter regions of clustered genes.

Flow-pattern Guided Fabrication of High-density Barcode Antibody Microarray

PubMed Central

Ramirez, Lisa S.; Wang, Jun

2016-01-01

Antibody microarray as a well-developed technology is currently challenged by a few other established or emerging high-throughput technologies. In this report, we renovate the antibody microarray technology by using a novel approach for manufacturing and by introducing new features. The fabrication of our high-density antibody microarray is accomplished through perpendicularly oriented flow-patterning of single stranded DNAs and subsequent conversion mediated by DNA-antibody conjugates. This protocol outlines the critical steps in flow-patterning DNA, producing and purifying DNA-antibody conjugates, and assessing the quality of the fabricated microarray. The uniformity and sensitivity are comparable with conventional microarrays, while our microarray fabrication does not require the assistance of an array printer and can be performed in most research laboratories. The other major advantage is that the size of our microarray units is 10 times smaller than that of printed arrays, offering the unique capability of analyzing functional proteins from single cells when interfacing with generic microchip designs. This barcode technology can be widely employed in biomarker detection, cell signaling studies, tissue engineering, and a variety of clinical applications. PMID:26780370

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

PubMed Central

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

2008-01-01

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

Microarrays Made Simple: "DNA Chips" Paper Activity

ERIC Educational Resources Information Center

Barnard, Betsy

2006-01-01

DNA microarray technology is revolutionizing biological science. DNA microarrays (also called DNA chips) allow simultaneous screening of many genes for changes in expression between different cells. Now researchers can obtain information about genes in days or weeks that used to take months or years. The paper activity described in this article…

Integrative missing value estimation for microarray data.

PubMed

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.

Emerging Use of Gene Expression Microarrays in Plant Physiology

DOE PAGES

Wullschleger, Stan D.; Difazio, Stephen P.

2003-01-01

Microarrays have become an important technology for the global analysis of gene expression in humans, animals, plants, and microbes. Implemented in the context of a well-designed experiment, cDNA and oligonucleotide arrays can provide highthroughput, simultaneous analysis of transcript abundance for hundreds, if not thousands, of genes. However, despite widespread acceptance, the use of microarrays as a tool to better understand processes of interest to the plant physiologist is still being explored. To help illustrate current uses of microarrays in the plant sciences, several case studies that we believe demonstrate the emerging application of gene expression arrays in plant physiology weremore » selected from among the many posters and presentations at the 2003 Plant and Animal Genome XI Conference. Based on this survey, microarrays are being used to assess gene expression in plants exposed to the experimental manipulation of air temperature, soil water content and aluminium concentration in the root zone. Analysis often includes characterizing transcript profiles for multiple post-treatment sampling periods and categorizing genes with common patterns of response using hierarchical clustering techniques. In addition, microarrays are also providing insights into developmental changes in gene expression associated with fibre and root elongation in cotton and maize, respectively. Technical and analytical limitations of microarrays are discussed and projects attempting to advance areas of microarray design and data analysis are highlighted. Finally, although much work remains, we conclude that microarrays are a valuable tool for the plant physiologist interested in the characterization and identification of individual genes and gene families with potential application in the fields of agriculture, horticulture and forestry.« less

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

PubMed

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

2015-06-01

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

Microarray-based screening of heat shock protein inhibitors.

PubMed

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

2014-06-20

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

A Human Lectin Microarray for Sperm Surface Glycosylation Analysis *

PubMed Central

Sun, Yangyang; Cheng, Li; Gu, Yihua; Xin, Aijie; Wu, Bin; Zhou, Shumin; Guo, Shujuan; Liu, Yin; Diao, Hua; Shi, Huijuan; Wang, Guangyu; Tao, Sheng-ce

2016-01-01

Glycosylation is one of the most abundant and functionally important protein post-translational modifications. As such, technology for efficient glycosylation analysis is in high demand. Lectin microarrays are a powerful tool for such investigations and have been successfully applied for a variety of glycobiological studies. However, most of the current lectin microarrays are primarily constructed from plant lectins, which are not well suited for studies of human glycosylation because of the extreme complexity of human glycans. Herein, we constructed a human lectin microarray with 60 human lectin and lectin-like proteins. All of the lectins and lectin-like proteins were purified from yeast, and most showed binding to human glycans. To demonstrate the applicability of the human lectin microarray, human sperm were probed on the microarray and strong bindings were observed for several lectins, including galectin-1, 7, 8, GalNAc-T6, and ERGIC-53 (LMAN1). These bindings were validated by flow cytometry and fluorescence immunostaining. Further, mass spectrometry analysis showed that galectin-1 binds several membrane-associated proteins including heat shock protein 90. Finally, functional assays showed that binding of galectin-8 could significantly enhance the acrosome reaction within human sperms. To our knowledge, this is the first construction of a human lectin microarray, and we anticipate it will find wide use for a range of human or mammalian studies, alone or in combination with plant lectin microarrays. PMID:27364157

Evolutionary Determinants of Morphological Polymorphism in Colonial Animals.

PubMed

Simpson, Carl; Jackson, Jeremy B C; Herrera-Cubilla, Amalia

2017-07-01

Colonial animals commonly exhibit morphologically polymorphic modular units that are phenotypically distinct and specialize in specific functional tasks. But how and why these polymorphic modules have evolved is poorly understood. Across colonial invertebrates, there is wide variation in the degree of polymorphism, from none in colonial ascidians to extreme polymorphism in siphonophores, such as the Portuguese man-of-war. Bryozoa are a phylum of exclusively colonial invertebrates that uniquely exhibit almost the entire range of polymorphism, from monomorphic species to others that rival siphonophores in their polymorphic complexity. Previous approaches to understanding the evolution of polymorphism have been based on analyses of (1) the functional role of polymorphs or (2) presumed evolutionary costs and benefits based on evolutionary theory that postulates polymorphism should be evolutionarily sustainable only in more stable environments because polymorphism commonly leads to the loss of feeding and sexual competence. Here we use bryozoans from opposite shores of the Isthmus of Panama to revisit the environmental hypothesis by comparison of faunas from distinct oceanographic provinces that differ greatly in environmental variability, and we then examine the correlations between the extent of polymorphism in relation to patterns of ecological succession and variation in life histories. We find no support for the environmental hypothesis. Distributions of the incidence of polymorphism in the oceanographically unstable Eastern Pacific are indistinguishable from those in the more stable Caribbean. In contrast, the temporal position of species in a successional sequence is collinear with the degree of polymorphism because species with fewer types of polymorphs are competitively replaced by species with higher numbers of polymorphs on the same substrata. Competitively dominant species also exhibit patterns of growth that increase their competitive ability. The

The Diversity of REcent and Ancient huMan (DREAM): A New Microarray for Genetic Anthropology and Genealogy, Forensics, and Personalized Medicine.

PubMed

Elhaik, Eran; Yusuf, Leeban; Anderson, Ainan I J; Pirooznia, Mehdi; Arnellos, Dimitrios; Vilshansky, Gregory; Ercal, Gunes; Lu, Yontao; Webster, Teresa; Baird, Michael L; Esposito, Umberto

2017-12-01

The human population displays wide variety in demographic history, ancestry, content of DNA derived from hominins or ancient populations, adaptation, traits, copy number variation, drug response, and more. These polymorphisms are of broad interest to population geneticists, forensics investigators, and medical professionals. Historically, much of that knowledge was gained from population survey projects. Although many commercial arrays exist for genome-wide single-nucleotide polymorphism genotyping, their design specifications are limited and they do not allow a full exploration of biodiversity. We thereby aimed to design the Diversity of REcent and Ancient huMan (DREAM)-an all-inclusive microarray that would allow both identification of known associations and exploration of standing questions in genetic anthropology, forensics, and personalized medicine. DREAM includes probes to interrogate ancestry informative markers obtained from over 450 human populations, over 200 ancient genomes, and 10 archaic hominins. DREAM can identify 94% and 61% of all known Y and mitochondrial haplogroups, respectively, and was vetted to avoid interrogation of clinically relevant markers. To demonstrate its capabilities, we compared its FST distributions with those of the 1000 Genomes Project and commercial arrays. Although all arrays yielded similarly shaped (inverse J) FST distributions, DREAM's autosomal and X-chromosomal distributions had the highest mean FST, attesting to its ability to discern subpopulations. DREAM performances are further illustrated in biogeographical, identical by descent, and copy number variation analyses. In summary, with approximately 800,000 markers spanning nearly 2,000 genes, DREAM is a useful tool for genetic anthropology, forensic, and personalized medicine studies. © The Author(s) 2017. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution.

Spot detection and image segmentation in DNA microarray data.

PubMed

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

2005-01-01

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

Implementation of mutual information and bayes theorem for classification microarray data

NASA Astrophysics Data System (ADS)

Dwifebri Purbolaksono, Mahendra; Widiastuti, Kurnia C.; Syahrul Mubarok, Mohamad; Adiwijaya; Aminy Ma’ruf, Firda

2018-03-01

Microarray Technology is one of technology which able to read the structure of gen. The analysis is important for this technology. It is for deciding which attribute is more important than the others. Microarray technology is able to get cancer information to diagnose a person’s gen. Preparation of microarray data is a huge problem and takes a long time. That is because microarray data contains high number of insignificant and irrelevant attributes. So, it needs a method to reduce the dimension of microarray data without eliminating important information in every attribute. This research uses Mutual Information to reduce dimension. System is built with Machine Learning approach specifically Bayes Theorem. This theorem uses a statistical and probability approach. By combining both methods, it will be powerful for Microarray Data Classification. The experiment results show that system is good to classify Microarray data with highest F1-score using Bayesian Network by 91.06%, and Naïve Bayes by 88.85%.

Clustering-based spot segmentation of cDNA microarray images.

PubMed

Uslan, Volkan; Bucak, Ihsan Ömür

2010-01-01

Microarrays are utilized as that they provide useful information about thousands of gene expressions simultaneously. In this study segmentation step of microarray image processing has been implemented. Clustering-based methods, fuzzy c-means and k-means, have been applied for the segmentation step that separates the spots from the background. The experiments show that fuzzy c-means have segmented spots of the microarray image more accurately than the k-means.

Using Kepler for Tool Integration in Microarray Analysis Workflows.

PubMed

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

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

The MicroArray Quality Control (MAQC)-II study of common practices for the development and validation of microarray-based predictive models

EPA Science Inventory

The second phase of the MicroArray Quality Control (MAQC-II) project evaluated common practices for developing and validating microarray-based models aimed at predicting toxicological and clinical endpoints. Thirty-six teams developed classifiers for 13 endpoints - some easy, som...

DFP: a Bioconductor package for fuzzy profile identification and gene reduction of microarray data

PubMed Central

Glez-Peña, Daniel; Álvarez, Rodrigo; Díaz, Fernando; Fdez-Riverola, Florentino

2009-01-01

Background Expression profiling assays done by using DNA microarray technology generate enormous data sets that are not amenable to simple analysis. The greatest challenge in maximizing the use of this huge amount of data is to develop algorithms to interpret and interconnect results from different genes under different conditions. In this context, fuzzy logic can provide a systematic and unbiased way to both (i) find biologically significant insights relating to meaningful genes, thereby removing the need for expert knowledge in preliminary steps of microarray data analyses and (ii) reduce the cost and complexity of later applied machine learning techniques being able to achieve interpretable models. Results DFP is a new Bioconductor R package that implements a method for discretizing and selecting differentially expressed genes based on the application of fuzzy logic. DFP takes advantage of fuzzy membership functions to assign linguistic labels to gene expression levels. The technique builds a reduced set of relevant genes (FP, Fuzzy Pattern) able to summarize and represent each underlying class (pathology). A last step constructs a biased set of genes (DFP, Discriminant Fuzzy Pattern) by intersecting existing fuzzy patterns in order to detect discriminative elements. In addition, the software provides new functions and visualisation tools that summarize achieved results and aid in the interpretation of differentially expressed genes from multiple microarray experiments. Conclusion DFP integrates with other packages of the Bioconductor project, uses common data structures and is accompanied by ample documentation. It has the advantage that its parameters are highly configurable, facilitating the discovery of biologically relevant connections between sets of genes belonging to different pathologies. This information makes it possible to automatically filter irrelevant genes thereby reducing the large volume of data supplied by microarray experiments. Based on

DFP: a Bioconductor package for fuzzy profile identification and gene reduction of microarray data.

PubMed

Glez-Peña, Daniel; Alvarez, Rodrigo; Díaz, Fernando; Fdez-Riverola, Florentino

2009-01-29

Expression profiling assays done by using DNA microarray technology generate enormous data sets that are not amenable to simple analysis. The greatest challenge in maximizing the use of this huge amount of data is to develop algorithms to interpret and interconnect results from different genes under different conditions. In this context, fuzzy logic can provide a systematic and unbiased way to both (i) find biologically significant insights relating to meaningful genes, thereby removing the need for expert knowledge in preliminary steps of microarray data analyses and (ii) reduce the cost and complexity of later applied machine learning techniques being able to achieve interpretable models. DFP is a new Bioconductor R package that implements a method for discretizing and selecting differentially expressed genes based on the application of fuzzy logic. DFP takes advantage of fuzzy membership functions to assign linguistic labels to gene expression levels. The technique builds a reduced set of relevant genes (FP, Fuzzy Pattern) able to summarize and represent each underlying class (pathology). A last step constructs a biased set of genes (DFP, Discriminant Fuzzy Pattern) by intersecting existing fuzzy patterns in order to detect discriminative elements. In addition, the software provides new functions and visualisation tools that summarize achieved results and aid in the interpretation of differentially expressed genes from multiple microarray experiments. DFP integrates with other packages of the Bioconductor project, uses common data structures and is accompanied by ample documentation. It has the advantage that its parameters are highly configurable, facilitating the discovery of biologically relevant connections between sets of genes belonging to different pathologies. This information makes it possible to automatically filter irrelevant genes thereby reducing the large volume of data supplied by microarray experiments. Based on these contributions GENECBR, a

A perspective on microarrays: current applications, pitfalls, and potential uses

PubMed Central

Jaluria, Pratik; Konstantopoulos, Konstantinos; Betenbaugh, Michael; Shiloach, Joseph

2007-01-01

With advances in robotics, computational capabilities, and the fabrication of high quality glass slides coinciding with increased genomic information being available on public databases, microarray technology is increasingly being used in laboratories around the world. In fact, fields as varied as: toxicology, evolutionary biology, drug development and production, disease characterization, diagnostics development, cellular physiology and stress responses, and forensics have benefiting from its use. However, for many researchers not familiar with microarrays, current articles and reviews often address neither the fundamental principles behind the technology nor the proper designing of experiments. Although, microarray technology is relatively simple, conceptually, its practice does require careful planning and detailed understanding of the limitations inherently present. Without these considerations, it can be exceedingly difficult to ascertain valuable information from microarray data. Therefore, this text aims to outline key features in microarray technology, paying particular attention to current applications as outlined in recent publications, experimental design, statistical methods, and potential uses. Furthermore, this review is not meant to be comprehensive, but rather substantive; highlighting important concepts and detailing steps necessary to conduct and interpret microarray experiments. Collectively, the information included in this text will highlight the versatility of microarray technology and provide a glimpse of what the future may hold. PMID:17254338

Detection of clonal evolution in hematopoietic malignancies by combining comparative genomic hybridization and single nucleotide polymorphism arrays.

PubMed

Hartmann, Luise; Stephenson, Christine F; Verkamp, Stephanie R; Johnson, Krystal R; Burnworth, Bettina; Hammock, Kelle; Brodersen, Lisa Eidenschink; de Baca, Monica E; Wells, Denise A; Loken, Michael R; Zehentner, Barbara K

2014-12-01

Array comparative genomic hybridization (aCGH) has become a powerful tool for analyzing hematopoietic neoplasms and identifying genome-wide copy number changes in a single assay. aCGH also has superior resolution compared with fluorescence in situ hybridization (FISH) or conventional cytogenetics. Integration of single nucleotide polymorphism (SNP) probes with microarray analysis allows additional identification of acquired uniparental disomy, a copy neutral aberration with known potential to contribute to tumor pathogenesis. However, a limitation of microarray analysis has been the inability to detect clonal heterogeneity in a sample. This study comprised 16 samples (acute myeloid leukemia, myelodysplastic syndrome, chronic lymphocytic leukemia, plasma cell neoplasm) with complex cytogenetic features and evidence of clonal evolution. We used an integrated manual peak reassignment approach combining analysis of aCGH and SNP microarray data for characterization of subclonal abnormalities. We compared array findings with results obtained from conventional cytogenetic and FISH studies. Clonal heterogeneity was detected in 13 of 16 samples by microarray on the basis of log2 values. Use of the manual peak reassignment analysis approach improved resolution of the sample's clonal composition and genetic heterogeneity in 10 of 13 (77%) patients. Moreover, in 3 patients, clonal disease progression was revealed by array analysis that was not evident by cytogenetic or FISH studies. Genetic abnormalities originating from separate clonal subpopulations can be identified and further characterized by combining aCGH and SNP hybridization results from 1 integrated microarray chip by use of the manual peak reassignment technique. Its clinical utility in comparison to conventional cytogenetic or FISH studies is demonstrated. © 2014 American Association for Clinical Chemistry.

Tissue microarray immunohistochemical detection of brachyury is not a prognostic indicator in chordoma.

PubMed

Zhang, Linlin; Guo, Shang; Schwab, Joseph H; Nielsen, G Petur; Choy, Edwin; Ye, Shunan; Zhang, Zhan; Mankin, Henry; Hornicek, Francis J; Duan, Zhenfeng

2013-01-01

Brachyury is a marker for notochord-derived tissues and neoplasms, such as chordoma. However, the prognostic relevance of brachyury expression in chordoma is still unknown. The improvement of tissue microarray technology has provided the opportunity to perform analyses of tumor tissues on a large scale in a uniform and consistent manner. This study was designed with the use of tissue microarray to determine the expression of brachyury. Brachyury expression in chordoma tissues from 78 chordoma patients was analyzed by immunohistochemical staining of tissue microarray. The clinicopathologic parameters, including gender, age, location of tumor and metastatic status were evaluated. Fifty-nine of 78 (75.64%) tumors showed nuclear staining for brachyury, and among them, 29 tumors (49.15%) showed 1+ (<30% positive cells) staining, 15 tumors (25.42%) had 2+ (31% to 60% positive cells) staining, and 15 tumors (25.42%) demonstrated 3+ (61% to 100% positive cells) staining. Brachyury nuclear staining was detected more frequently in sacral chordomas than in chordomas of the mobile spine. However, there was no significant relationship between brachyury expression and other clinical variables. By Kaplan-Meier analysis, brachyury expression failed to produce any significant relationship with the overall survival rate. In conclusion, brachyury expression is not a prognostic indicator in chordoma.

A high-density genetic map with array-based markers facilitates structural and quantitative trait locus analyses of the common wheat genome.

PubMed

Iehisa, Julio Cesar Masaru; Ohno, Ryoko; Kimura, Tatsuro; Enoki, Hiroyuki; Nishimura, Satoru; Okamoto, Yuki; Nasuda, Shuhei; Takumi, Shigeo

2014-10-01

The large genome and allohexaploidy of common wheat have complicated construction of a high-density genetic map. Although improvements in the throughput of next-generation sequencing (NGS) technologies have made it possible to obtain a large amount of genotyping data for an entire mapping population by direct sequencing, including hexaploid wheat, a significant number of missing data points are often apparent due to the low coverage of sequencing. In the present study, a microarray-based polymorphism detection system was developed using NGS data obtained from complexity-reduced genomic DNA of two common wheat cultivars, Chinese Spring (CS) and Mironovskaya 808. After design and selection of polymorphic probes, 13,056 new markers were added to the linkage map of a recombinant inbred mapping population between CS and Mironovskaya 808. On average, 2.49 missing data points per marker were observed in the 201 recombinant inbred lines, with a maximum of 42. Around 40% of the new markers were derived from genic regions and 11% from repetitive regions. The low number of retroelements indicated that the new polymorphic markers were mainly derived from the less repetitive region of the wheat genome. Around 25% of the mapped sequences were useful for alignment with the physical map of barley. Quantitative trait locus (QTL) analyses of 14 agronomically important traits related to flowering, spikes, and seeds demonstrated that the new high-density map showed improved QTL detection, resolution, and accuracy over the original simple sequence repeat map. © The Author 2014. Published by Oxford University Press on behalf of Kazusa DNA Research Institute.

Experimental Approaches to Microarray Analysis of Tumor Samples

ERIC Educational Resources Information Center

Furge, Laura Lowe; Winter, Michael B.; Meyers, Jacob I.; Furge, Kyle A.

2008-01-01

Comprehensive measurement of gene expression using high-density nucleic acid arrays (i.e. microarrays) has become an important tool for investigating the molecular differences in clinical and research samples. Consequently, inclusion of discussion in biochemistry, molecular biology, or other appropriate courses of microarray technologies has…

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

PubMed Central

2013-01-01

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

Design of microarray experiments for genetical genomics studies.

PubMed

Bueno Filho, Júlio S S; Gilmour, Steven G; Rosa, Guilherme J M

2006-10-01

Microarray experiments have been used recently in genetical genomics studies, as an additional tool to understand the genetic mechanisms governing variation in complex traits, such as for estimating heritabilities of mRNA transcript abundances, for mapping expression quantitative trait loci, and for inferring regulatory networks controlling gene expression. Several articles on the design of microarray experiments discuss situations in which treatment effects are assumed fixed and without any structure. In the case of two-color microarray platforms, several authors have studied reference and circular designs. Here, we discuss the optimal design of microarray experiments whose goals refer to specific genetic questions. Some examples are used to illustrate the choice of a design for comparing fixed, structured treatments, such as genotypic groups. Experiments targeting single genes or chromosomic regions (such as with transgene research) or multiple epistatic loci (such as within a selective phenotyping context) are discussed. In addition, microarray experiments in which treatments refer to families or to subjects (within family structures or complex pedigrees) are presented. In these cases treatments are more appropriately considered to be random effects, with specific covariance structures, in which the genetic goals relate to the estimation of genetic variances and the heritability of transcriptional abundances.

Intra-Platform Repeatability and Inter-Platform Comparability of MicroRNA Microarray Technology

PubMed Central

Sato, Fumiaki; Tsuchiya, Soken; Terasawa, Kazuya; Tsujimoto, Gozoh

2009-01-01

Over the last decade, DNA microarray technology has provided a great contribution to the life sciences. The MicroArray Quality Control (MAQC) project demonstrated the way to analyze the expression microarray. Recently, microarray technology has been utilized to analyze a comprehensive microRNA expression profiling. Currently, several platforms of microRNA microarray chips are commercially available. Thus, we compared repeatability and comparability of five different microRNA microarray platforms (Agilent, Ambion, Exiqon, Invitrogen and Toray) using 309 microRNAs probes, and the Taqman microRNA system using 142 microRNA probes. This study demonstrated that microRNA microarray has high intra-platform repeatability and comparability to quantitative RT-PCR of microRNA. Among the five platforms, Agilent and Toray array showed relatively better performances than the others. However, the current lineup of commercially available microRNA microarray systems fails to show good inter-platform concordance, probably because of lack of an adequate normalization method and severe divergence in stringency of detection call criteria between different platforms. This study provided the basic information about the performance and the problems specific to the current microRNA microarray systems. PMID:19436744

A meta-analysis of eNOS and ACE gene polymorphisms and risk of pre-eclampsia in women.

PubMed

Shaik, A P; Sultana, A; Bammidi, V K; Sampathirao, K; Jamil, K

2011-10-01

A meta-analyses of endothelial nitric oxide synthase (eNOS) and angiotensin-converting enzyme (ACE) gene polymorphisms in pre-eclampsia was performed. We shortlisted 33 studies (17 for ACE; 16 for eNOS gene polymorphisms), of which 29 articles (16 for ACE and 15 for eNOS) were analysed. Overall, 1,620 cases with pre-eclampsia and 2,158 controls were analysed for intron 16 insertion-deletion polymorphism in ACE gene. A total of 1,610 subjects with pre-eclampsia and 2,875 controls were analysed for the Glu298Asp in eNOS gene. Overall, the random-effects odds ratio (OR) with Glu298Asp in eNOS gene was 0.958 (95% confidence intervals, CI 0.747-1.228, p > 0.05), and for the insertion-deletion/ACE polymorphism was 0.987 (95% CI 0.698-1.395, p > 0.05). Significant heterogeneity was observed in the studies that evaluated polymorphisms in ACE (Q value = 55.6; I(2) = 73; p value = 0.000); and eNOS (Q value = 37.2; I(2) = 62.4; p value = 0.001) polymorphisms. No significant risk of pre-eclampsia was observed in both eNOS and ACE genes with these polymorphisms.

Profiling In Situ Microbial Community Structure with an Amplification Microarray

PubMed Central

Knickerbocker, Christopher; Bryant, Lexi; Golova, Julia; Wiles, Cory; Williams, Kenneth H.; Peacock, Aaron D.; Long, Philip E.

2013-01-01

The objectives of this study were to unify amplification, labeling, and microarray hybridization chemistries within a single, closed microfluidic chamber (an amplification microarray) and verify technology performance on a series of groundwater samples from an in situ field experiment designed to compare U(VI) mobility under conditions of various alkalinities (as HCO3−) during stimulated microbial activity accompanying acetate amendment. Analytical limits of detection were between 2 and 200 cell equivalents of purified DNA. Amplification microarray signatures were well correlated with 16S rRNA-targeted quantitative PCR results and hybridization microarray signatures. The succession of the microbial community was evident with and consistent between the two microarray platforms. Amplification microarray analysis of acetate-treated groundwater showed elevated levels of iron-reducing bacteria (Flexibacter, Geobacter, Rhodoferax, and Shewanella) relative to the average background profile, as expected. Identical molecular signatures were evident in the transect treated with acetate plus NaHCO3, but at much lower signal intensities and with a much more rapid decline (to nondetection). Azoarcus, Thaurea, and Methylobacterium were responsive in the acetate-only transect but not in the presence of bicarbonate. Observed differences in microbial community composition or response to bicarbonate amendment likely had an effect on measured rates of U reduction, with higher rates probable in the part of the field experiment that was amended with bicarbonate. The simplification in microarray-based work flow is a significant technological advance toward entirely closed-amplicon microarray-based tests and is generally extensible to any number of environmental monitoring applications. PMID:23160129

Polymorphic DNA microsatellite markers for forensic individual identification and parentage analyses of seven threatened species of parrots (family Psittacidae)

PubMed Central

Jan, Catherine

2016-01-01

The parrot family represents one of the bird group with the largest number of endangered species, as a result of habitat destruction and illegal trade. This illicit traffic involves the smuggling of eggs and animals, and the laundering through captive breeding facilities of wild-caught animals. Despite the huge potential of wildlife DNA forensics to determine with conclusive evidence illegal trade, current usage of DNA profiling approaches in parrots has been limited by the lack of suitable molecular markers specifically developed for the focal species and by low cross-species polymorphism. In this study, we isolated DNA microsatellite markers in seven parrot species threatened with extinction (Amazona brasiliensis, A. oratrix, A. pretrei, A. rhodocorytha, Anodorhynchus leari, Ara rubrogenys and Primolius couloni). From an enriched genomic library followed by 454 pyrosequencing, we characterized a total of 106 polymorphic microsatellite markers (mostly tetranucleotides) in the seven species and tested them across an average number of 19 individuals per species. The mean number of alleles per species and across loci varied from 6.4 to 8.3, with the mean observed heterozygosities ranging from 0.65 to 0.84. Identity and parentage exclusion probabilities were highly discriminatory. The high variability displayed by these microsatellite loci demonstrates their potential utility to perform individual genotyping and parentage analyses, in order to develop a DNA testing framework to determine illegal traffic in these threatened species. PMID:27688959

Polymorphic DNA microsatellite markers for forensic individual identification and parentage analyses of seven threatened species of parrots (family Psittacidae).

PubMed

Jan, Catherine; Fumagalli, Luca

2016-01-01

The parrot family represents one of the bird group with the largest number of endangered species, as a result of habitat destruction and illegal trade. This illicit traffic involves the smuggling of eggs and animals, and the laundering through captive breeding facilities of wild-caught animals. Despite the huge potential of wildlife DNA forensics to determine with conclusive evidence illegal trade, current usage of DNA profiling approaches in parrots has been limited by the lack of suitable molecular markers specifically developed for the focal species and by low cross-species polymorphism. In this study, we isolated DNA microsatellite markers in seven parrot species threatened with extinction (Amazona brasiliensis, A. oratrix, A. pretrei, A. rhodocorytha, Anodorhynchus leari, Ara rubrogenys and Primolius couloni). From an enriched genomic library followed by 454 pyrosequencing, we characterized a total of 106 polymorphic microsatellite markers (mostly tetranucleotides) in the seven species and tested them across an average number of 19 individuals per species. The mean number of alleles per species and across loci varied from 6.4 to 8.3, with the mean observed heterozygosities ranging from 0.65 to 0.84. Identity and parentage exclusion probabilities were highly discriminatory. The high variability displayed by these microsatellite loci demonstrates their potential utility to perform individual genotyping and parentage analyses, in order to develop a DNA testing framework to determine illegal traffic in these threatened species.

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

PubMed Central

2014-01-01

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

Women's experiences receiving abnormal prenatal chromosomal microarray testing results.

PubMed

Bernhardt, Barbara A; Soucier, Danielle; Hanson, Karen; Savage, Melissa S; Jackson, Laird; Wapner, Ronald J

2013-02-01

Genomic microarrays can detect copy-number variants not detectable by conventional cytogenetics. This technology is diffusing rapidly into prenatal settings even though the clinical implications of many copy-number variants are currently unknown. We conducted a qualitative pilot study to explore the experiences of women receiving abnormal results from prenatal microarray testing performed in a research setting. Participants were a subset of women participating in a multicenter prospective study "Prenatal Cytogenetic Diagnosis by Array-based Copy Number Analysis." Telephone interviews were conducted with 23 women receiving abnormal prenatal microarray results. We found that five key elements dominated the experiences of women who had received abnormal prenatal microarray results: an offer too good to pass up, blindsided by the results, uncertainty and unquantifiable risks, need for support, and toxic knowledge. As prenatal microarray testing is increasingly used, uncertain findings will be common, resulting in greater need for careful pre- and posttest counseling, and more education of and resources for providers so they can adequately support the women who are undergoing testing.

Two-Dimensional VO2 Mesoporous Microarrays for High-Performance Supercapacitor

NASA Astrophysics Data System (ADS)

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

2018-05-01

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

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

PubMed

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

2016-01-01

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

Peptidoglycan microarray as a novel tool to explore protein-ligand recognition.

PubMed

Wang, Ning; Hirata, Akiyoshi; Nokihara, Kiyoshi; Fukase, Koichi; Fujimoto, Yukari

2016-11-04

Peptidoglycan is a giant bag-shaped molecule essential for bacterial cell shape and resistance to osmotic stresses. The activity of a large number of bacterial surface proteins involved in cell growth and division requires binding to this macromolecule. Recognition of peptidoglycan by immune effectors is also crucial for the establishment of the immune response against pathogens. The availability of pure and chemically defined peptidoglycan fragments is a major technical bottleneck that has precluded systematic studies of the mechanisms underpinning protein-mediated peptidoglycan recognition. Here, we report a microarray strategy suitable to carry out comprehensive studies to characterize proteins-peptidoglycan interactions. We describe a method to introduce a functional group on peptidoglycan fragments allowing their stable immobilization on amorphous carbon chip plates to minimize nonspecific binding. Such peptidoglycan microarrays were used with a model peptidoglycan binding protein-the human peptidoglycan recognition protein-S (hPGRP-S). We propose that this strategy could be implemented to carry out high-throughput analyses to study peptidoglycan binding proteins. © 2016 Wiley Periodicals, Inc. Biopolymers (Pept Sci) 106: 422-429, 2016. © 2016 Wiley Periodicals, Inc.

DNA microarrays and their use in dermatology.

PubMed

Mlakar, Vid; Glavac, Damjan

2007-03-01

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

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

PubMed Central

Jupiter, Daniel; Chen, Hailin; VanBuren, Vincent

2009-01-01

Background Although expression microarrays have become a standard tool used by biologists, analysis of data produced by microarray experiments may still present challenges. Comparison of data from different platforms, organisms, and labs may involve complicated data processing, and inferring relationships between genes remains difficult. Results STARNET 2 is a new web-based tool that allows post hoc visual analysis of correlations that are derived from expression microarray data. STARNET 2 facilitates user discovery of putative gene regulatory networks in a variety of species (human, rat, mouse, chicken, zebrafish, Drosophila, C. elegans, S. cerevisiae, Arabidopsis and rice) by graphing networks of genes that are closely co-expressed across a large heterogeneous set of preselected microarray experiments. For each of the represented organisms, raw microarray data were retrieved from NCBI's Gene Expression Omnibus for a selected Affymetrix platform. All pairwise Pearson correlation coefficients were computed for expression profiles measured on each platform, respectively. These precompiled results were stored in a MySQL database, and supplemented by additional data retrieved from NCBI. A web-based tool allows user-specified queries of the database, centered at a gene of interest. The result of a query includes graphs of correlation networks, graphs of known interactions involving genes and gene products that are present in the correlation networks, and initial statistical analyses. Two analyses may be performed in parallel to compare networks, which is facilitated by the new HEATSEEKER module. Conclusion STARNET 2 is a useful tool for developing new hypotheses about regulatory relationships between genes and gene products, and has coverage for 10 species. Interpretation of the correlation networks is supported with a database of previously documented interactions, a test for enrichment of Gene Ontology terms, and heat maps of correlation distances that may be used to

Quantitative comparison of microarray experiments with published leukemia related gene expression signatures.

PubMed

Klein, Hans-Ulrich; Ruckert, Christian; Kohlmann, Alexander; Bullinger, Lars; Thiede, Christian; Haferlach, Torsten; Dugas, Martin

2009-12-15

Multiple gene expression signatures derived from microarray experiments have been published in the field of leukemia research. A comparison of these signatures with results from new experiments is useful for verification as well as for interpretation of the results obtained. Currently, the percentage of overlapping genes is frequently used to compare published gene signatures against a signature derived from a new experiment. However, it has been shown that the percentage of overlapping genes is of limited use for comparing two experiments due to the variability of gene signatures caused by different array platforms or assay-specific influencing parameters. Here, we present a robust approach for a systematic and quantitative comparison of published gene expression signatures with an exemplary query dataset. A database storing 138 leukemia-related published gene signatures was designed. Each gene signature was manually annotated with terms according to a leukemia-specific taxonomy. Two analysis steps are implemented to compare a new microarray dataset with the results from previous experiments stored and curated in the database. First, the global test method is applied to assess gene signatures and to constitute a ranking among them. In a subsequent analysis step, the focus is shifted from single gene signatures to chromosomal aberrations or molecular mutations as modeled in the taxonomy. Potentially interesting disease characteristics are detected based on the ranking of gene signatures associated with these aberrations stored in the database. Two example analyses are presented. An implementation of the approach is freely available as web-based application. The presented approach helps researchers to systematically integrate the knowledge derived from numerous microarray experiments into the analysis of a new dataset. By means of example leukemia datasets we demonstrate that this approach detects related experiments as well as related molecular mutations and may

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

PubMed

Grenville-Briggs, Laura J; Stansfield, Ian

2011-01-01

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

Survey and analysis of crystal polymorphism in organic structures

PubMed Central

Kaur, Ramanpreet

2018-01-01

With the intention of producing the most comprehensive treatment of the prevalence of crystal polymorphism among structurally characterized materials, all polymorphic compounds flagged as such within the Cambridge Structural Database (CSD) are analysed and a list of crystallographically characterized organic polymorphic compounds is assembled. Classifying these structures into subclasses of anhydrates, salts, hydrates, non-hydrated solvates and cocrystals reveals that there are significant variations in polymorphism prevalence as a function of crystal type, a fact which has not previously been recognized in the literature. It is also shown that, as a percentage, polymorphic entries are decreasing temporally within the CSD, with the notable exception of cocrystals, which continue to rise at a rate that is a constant fraction of the overall entries. Some phenomena identified that require additional scrutiny include the relative prevalence of temperature-induced phase transitions among organic salts and the paucity of polymorphism in crystals with three or more chemical components. PMID:29765601

A genome-wide 20 K citrus microarray for gene expression analysis

PubMed Central

Martinez-Godoy, M Angeles; Mauri, Nuria; Juarez, Jose; Marques, M Carmen; Santiago, Julia; Forment, Javier; Gadea, Jose

2008-01-01

Background Understanding of genetic elements that contribute to key aspects of citrus biology will impact future improvements in this economically important crop. Global gene expression analysis demands microarray platforms with a high genome coverage. In the last years, genome-wide EST collections have been generated in citrus, opening the possibility to create new tools for functional genomics in this crop plant. Results We have designed and constructed a publicly available genome-wide cDNA microarray that include 21,081 putative unigenes of citrus. As a functional companion to the microarray, a web-browsable database [1] was created and populated with information about the unigenes represented in the microarray, including cDNA libraries, isolated clones, raw and processed nucleotide and protein sequences, and results of all the structural and functional annotation of the unigenes, like general description, BLAST hits, putative Arabidopsis orthologs, microsatellites, putative SNPs, GO classification and PFAM domains. We have performed a Gene Ontology comparison with the full set of Arabidopsis proteins to estimate the genome coverage of the microarray. We have also performed microarray hybridizations to check its usability. Conclusion This new cDNA microarray replaces the first 7K microarray generated two years ago and allows gene expression analysis at a more global scale. We have followed a rational design to minimize cross-hybridization while maintaining its utility for different citrus species. Furthermore, we also provide access to a website with full structural and functional annotation of the unigenes represented in the microarray, along with the ability to use this site to directly perform gene expression analysis using standard tools at different publicly available servers. Furthermore, we show how this microarray offers a good representation of the citrus genome and present the usefulness of this genomic tool for global studies in citrus by using it to

High-Resolution SNP/CGH Microarrays Reveal the Accumulation of Loss of Heterozygosity in Commonly Used Candida albicans Strains

PubMed Central

Abbey, Darren; Hickman, Meleah; Gresham, David; Berman, Judith

2011-01-01

Phenotypic diversity can arise rapidly through loss of heterozygosity (LOH) or by the acquisition of copy number variations (CNV) spanning whole chromosomes or shorter contiguous chromosome segments. In Candida albicans, a heterozygous diploid yeast pathogen with no known meiotic cycle, homozygosis and aneuploidy alter clinical characteristics, including drug resistance. Here, we developed a high-resolution microarray that simultaneously detects ∼39,000 single nucleotide polymorphism (SNP) alleles and ∼20,000 copy number variation loci across the C. albicans genome. An important feature of the array analysis is a computational pipeline that determines SNP allele ratios based upon chromosome copy number. Using the array and analysis tools, we constructed a haplotype map (hapmap) of strain SC5314 to assign SNP alleles to specific homologs, and we used it to follow the acquisition of loss of heterozygosity (LOH) and copy number changes in a series of derived laboratory strains. This high-resolution SNP/CGH microarray and the associated hapmap facilitated the phasing of alleles in lab strains and revealed detrimental genome changes that arose frequently during molecular manipulations of laboratory strains. Furthermore, it provided a useful tool for rapid, high-resolution, and cost-effective characterization of changes in allele diversity as well as changes in chromosome copy number in new C. albicans isolates. PMID:22384363

Plastic Polymers for Efficient DNA Microarray Hybridization: Application to Microbiological Diagnostics▿

PubMed Central

Zhao, Zhengshan; Peytavi, Régis; Diaz-Quijada, Gerardo A.; Picard, Francois J.; Huletsky, Ann; Leblanc, Éric; Frenette, Johanne; Boivin, Guy; Veres, Teodor; Dumoulin, Michel M.; Bergeron, Michel G.

2008-01-01

Fabrication of microarray devices using traditional glass slides is not easily adaptable to integration into microfluidic systems. There is thus a need for the development of polymeric materials showing a high hybridization signal-to-background ratio, enabling sensitive detection of microbial pathogens. We have developed such plastic supports suitable for highly sensitive DNA microarray hybridizations. The proof of concept of this microarray technology was done through the detection of four human respiratory viruses that were amplified and labeled with a fluorescent dye via a sensitive reverse transcriptase PCR (RT-PCR) assay. The performance of the microarray hybridization with plastic supports made of PMMA [poly(methylmethacrylate)]-VSUVT or Zeonor 1060R was compared to that with high-quality glass slide microarrays by using both passive and microfluidic hybridization systems. Specific hybridization signal-to-background ratios comparable to that obtained with high-quality commercial glass slides were achieved with both polymeric substrates. Microarray hybridizations demonstrated an analytical sensitivity equivalent to approximately 100 viral genome copies per RT-PCR, which is at least 100-fold higher than the sensitivities of previously reported DNA hybridizations on plastic supports. Testing of these plastic polymers using a microfluidic microarray hybridization platform also showed results that were comparable to those with glass supports. In conclusion, PMMA-VSUVT and Zeonor 1060R are both suitable for highly sensitive microarray hybridizations. PMID:18784318

Detection of cryptic pathogenic copy number variations and constitutional loss of heterozygosity using high resolution SNP microarray analysis in 117 patients referred for cytogenetic analysis and impact on clinical practice.

PubMed

Bruno, D L; Ganesamoorthy, D; Schoumans, J; Bankier, A; Coman, D; Delatycki, M; Gardner, R J M; Hunter, M; James, P A; Kannu, P; McGillivray, G; Pachter, N; Peters, H; Rieubland, C; Savarirayan, R; Scheffer, I E; Sheffield, L; Tan, T; White, S M; Yeung, A; Bowman, Z; Ngo, C; Choy, K W; Cacheux, V; Wong, L; Amor, D J; Slater, H R

2009-02-01

Microarray genome analysis is realising its promise for improving detection of genetic abnormalities in individuals with mental retardation and congenital abnormality. Copy number variations (CNVs) are now readily detectable using a variety of platforms and a major challenge is the distinction of pathogenic from ubiquitous, benign polymorphic CNVs. The aim of this study was to investigate replacement of time consuming, locus specific testing for specific microdeletion and microduplication syndromes with microarray analysis, which theoretically should detect all known syndromes with CNV aetiologies as well as new ones. Genome wide copy number analysis was performed on 117 patients using Affymetrix 250K microarrays. 434 CNVs (195 losses and 239 gains) were found, including 18 pathogenic CNVs and 9 identified as "potentially pathogenic". Almost all pathogenic CNVs were larger than 500 kb, significantly larger than the median size of all CNVs detected. Segmental regions of loss of heterozygosity larger than 5 Mb were found in 5 patients. Genome microarray analysis has improved diagnostic success in this group of patients. Several examples of recently discovered "new syndromes" were found suggesting they are more common than previously suspected and collectively are likely to be a major cause of mental retardation. The findings have several implications for clinical practice. The study revealed the potential to make genetic diagnoses that were not evident in the clinical presentation, with implications for pretest counselling and the consent process. The importance of contributing novel CNVs to high quality databases for genotype-phenotype analysis and review of guidelines for selection of individuals for microarray analysis is emphasised.

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

PubMed Central

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

2010-01-01

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

HOTAIR gene polymorphisms contribute to increased neuroblastoma susceptibility in Chinese children.

PubMed

Yang, Xu; He, Jing; Chang, Yitian; Luo, Annie; Luo, Ailing; Zhang, Jiao; Zhang, Ruizhong; Xia, Huimin; Xu, Ling

2018-06-15

Neuroblastoma is the most frequently diagnosed extracranial solid tumor in children. Previous studies have shown that single-nucleotide polymorphisms in some genes are associated with the risk of multiple cancers, including neuroblastoma. Although Hox transcript antisense intergenic RNA (HOTAIR) gene polymorphisms have been investigated in a variety of cancers, to the authors' knowledge the relationships between HOTAIR gene polymorphisms and neuroblastoma susceptibility have not been reported to date. The objective of the current study was to evaluate the correlation between HOTAIR gene polymorphisms and neuroblastoma risk in Chinese children. The authors genotyped 6 polymorphisms (rs920778 A>G, rs12826786 C>T, rs4759314 A>G, rs7958904 G>C, rs874945 C>T, and rs1899663 C>A) of the HOTAIR gene in 2 Chinese populations including 393 neuroblastoma cases and 812 healthy controls. The strength of the associations was evaluated using odds ratios and 95% confidence intervals. Further stratification analyses were conducted to explore the association between the HOTAIR gene polymorphisms rs12826786 C>T, rs874945 C>T, and rs1899663 C>A with neuroblastoma susceptibility in terms of age, sex, clinical stage of disease, and sites of origin. The authors found that the rs12826786 C>T (P =.013), rs874945 C>T (P =.020), and rs1899663 C>A (P =.029) polymorphisms were significantly associated with increased neuroblastoma risk. In stratification analyses, these associations were more predominant in females and among patients with tumor in the retroperitoneal region or mediastinum. The remaining 3 polymorphisms were not found to be related to neuroblastoma susceptibility. The results of the current study verified that HOTAIR gene polymorphisms are associated with increased neuroblastoma risk and suggest that HOTAIR gene polymorphisms might be a potential biomarker for neuroblastoma susceptibility. Cancer 2018;124:2599-606. © 2018 American Cancer Society. © 2018 American Cancer Society.

The application of DNA microarrays in gene expression analysis.

PubMed

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.

Comparative Analyses of Single-Nucleotide Polymorphisms in the TNF Promoter Region Provide Further Validation for the Vervet Monkey Model of Obesity

PubMed Central

Gray, Stanton B; Howard, Timothy D; Langefeld, Carl D; Hawkins, Gregory A; Diallo, Abdoulaye F; Wagner, Janice D

2009-01-01

Tumor necrosis factor is a cytokine that plays critical roles in inflammation, the innate immune response, and a variety of other physiologic and pathophysiologic processes. In addition, TNF has recently been shown to mediate an intersection of chronic, low-grade inflammation and concurrent metabolic dysregulation associated with obesity and its comorbidities. As part of an ongoing initiative to further characterize vervet monkeys originating from St Kitts as an animal model of obesity and inflammation, we sequenced and genotyped the human ortholog vervet TNF gene and approximately 1 kb of the flanking 3′ and 5′ regions from 265 monkeys in a closed, pedigreed colony. This process revealed a total of 11 single-nucleotide polymorphisms (SNPs) and a single 4-bp insertion–deletion, with minor allele frequencies of 0.08 to 0.39. Many of these polymorphisms were in strong or complete linkage disequilibrium with each other, and all but 1 were contained within a single haplotype block, comprising 5 haplotypes with frequencies of 0.075 to 0.298. Using sequences from humans, chimpanzees, vervets, baboons, and rhesus macaques, phylogenetic shadowing of the TNF promoter region revealed that vervet SNPs, like the SNPs in related species, were clustered nonrandomly and nonuniformly around conserved transcription factor binding sites. These data, combined with previously defined heritable phenotypes, permit future association analyses in this nonhuman primate model and have great potential to help dissect the genetic and nongenetic contributions to complex diseases like obesity. More broadly, the sequence data and comparative analyses reported herein facilitates study of the evolution of regulatory sequences of inflammatory and immune-related genes. PMID:20034434

Microarray data mining using Bioconductor packages.

PubMed

Nie, Haisheng; Neerincx, Pieter B T; van der Poel, Jan; Ferrari, Francesco; Bicciato, Silvio; Leunissen, Jack A M; Groenen, Martien A M

2009-07-16

This paper describes the results of a Gene Ontology (GO) term enrichment analysis of chicken microarray data using the Bioconductor packages. By checking the enriched GO terms in three contrasts, MM8-PM8, MM8-MA8, and MM8-MM24, of the provided microarray data during this workshop, this analysis aimed to investigate the host reactions in chickens occurring shortly after a secondary challenge with either a homologous or heterologous species of Eimeria. The results of GO enrichment analysis using GO terms annotated to chicken genes and GO terms annotated to chicken-human orthologous genes were also compared. Furthermore, a locally adaptive statistical procedure (LAP) was performed to test differentially expressed chromosomal regions, rather than individual genes, in the chicken genome after Eimeria challenge. GO enrichment analysis identified significant (raw p-value < 0.05) GO terms for all three contrasts included in the analysis. Some of the GO terms linked to, generally, primary immune responses or secondary immune responses indicating the GO enrichment analysis is a useful approach to analyze microarray data. The comparisons of GO enrichment results using chicken gene information and chicken-human orthologous gene information showed more refined GO terms related to immune responses when using chicken-human orthologous gene information, this suggests that using chicken-human orthologous gene information has higher power to detect significant GO terms with more refined functionality. Furthermore, three chromosome regions were identified to be significantly up-regulated in contrast MM8-PM8 (q-value < 0.01). Overall, this paper describes a practical approach to analyze microarray data in farm animals where the genome information is still incomplete. For farm animals, such as chicken, with currently limited gene annotation, borrowing gene annotation information from orthologous genes in well-annotated species, such as human, will help improve the pathway analysis

Protein microarray with horseradish peroxidase chemiluminescence for quantification of serum α-fetoprotein.

PubMed

Zhao, Yuanshun; Zhang, Yonghong; Lin, Dongdong; Li, Kang; Yin, Chengzeng; Liu, Xiuhong; Jin, Boxun; Sun, Libo; Liu, Jinhua; Zhang, Aiying; Li, Ning

2015-10-01

To develop and evaluate a protein microarray assay with horseradish peroxidase (HRP) chemiluminescence for quantification of α-fetoprotein (AFP) in serum from patients with hepatocellular carcinoma (HCC). A protein microarray assay for AFP was developed. Serum was collected from patients with HCC and healthy control subjects. AFP was quantified using protein microarray and enzyme-linked immunosorbent assay (ELISA). Serum AFP concentrations determined via protein microarray were positively correlated (r = 0.973) with those determined via ELISA in patients with HCC (n = 60) and healthy control subjects (n = 30). Protein microarray showed 80% sensitivity and 100% specificity for HCC diagnosis. ELISA had 83.3% sensitivity and 100% specificity. Protein microarray effectively distinguished between patients with HCC and healthy control subjects (area under ROC curve 0.974; 95% CI 0.000, 1.000). Protein microarray is a rapid, simple and low-cost alternative to ELISA for detecting AFP in human serum. © The Author(s) 2015.

Analytical Protein Microarrays: Advancements Towards Clinical Applications

PubMed Central

Sauer, Ursula

2017-01-01

Protein microarrays represent a powerful technology with the potential to serve as tools for the detection of a broad range of analytes in numerous applications such as diagnostics, drug development, food safety, and environmental monitoring. Key features of analytical protein microarrays include high throughput and relatively low costs due to minimal reagent consumption, multiplexing, fast kinetics and hence measurements, and the possibility of functional integration. So far, especially fundamental studies in molecular and cell biology have been conducted using protein microarrays, while the potential for clinical, notably point-of-care applications is not yet fully utilized. The question arises what features have to be implemented and what improvements have to be made in order to fully exploit the technology. In the past we have identified various obstacles that have to be overcome in order to promote protein microarray technology in the diagnostic field. Issues that need significant improvement to make the technology more attractive for the diagnostic market are for instance: too low sensitivity and deficiency in reproducibility, inadequate analysis time, lack of high-quality antibodies and validated reagents, lack of automation and portable instruments, and cost of instruments necessary for chip production and read-out. The scope of the paper at hand is to review approaches to solve these problems. PMID:28146048

WebArray: an online platform for microarray data analysis

PubMed Central

Xia, Xiaoqin; McClelland, Michael; Wang, Yipeng

2005-01-01

Background Many cutting-edge microarray analysis tools and algorithms, including commonly used limma and affy packages in Bioconductor, need sophisticated knowledge of mathematics, statistics and computer skills for implementation. Commercially available software can provide a user-friendly interface at considerable cost. To facilitate the use of these tools for microarray data analysis on an open platform we developed an online microarray data analysis platform, WebArray, for bench biologists to utilize these tools to explore data from single/dual color microarray experiments. Results The currently implemented functions were based on limma and affy package from Bioconductor, the spacings LOESS histogram (SPLOSH) method, PCA-assisted normalization method and genome mapping method. WebArray incorporates these packages and provides a user-friendly interface for accessing a wide range of key functions of limma and others, such as spot quality weight, background correction, graphical plotting, normalization, linear modeling, empirical bayes statistical analysis, false discovery rate (FDR) estimation, chromosomal mapping for genome comparison. Conclusion WebArray offers a convenient platform for bench biologists to access several cutting-edge microarray data analysis tools. The website is freely available at . It runs on a Linux server with Apache and MySQL. PMID:16371165

Polymorphisms in GSTM1, GSTT1, GSTP1, and GSTM3 genes and breast cancer risk in northeastern Mexico.

PubMed

Jaramillo-Rangel, G; Ortega-Martínez, M; Cerda-Flores, R M; Barrera-Saldaña, H A

2015-06-11

Glutathione S-transferases (GSTs) are a family of phase II metabolizing enzymes involved in carcinogen detoxification and the metabolism of various bioactive compounds. Several genes that code for these enzymes are polymorphic in an ethnicity-dependent manner, with particular genotypes previously associated with an increased risk of breast cancer. The purpose of this study was to determine the frequencies of polymorphisms in the genes GSTM1, GSTT1, GSTP1, and GSTM3 and to investigate whether an association exists between these genes and breast cancer risk in subjects from northeastern Mexico. Genotypes were determined for 243 women with histologically confirmed breast cancer and 118 control subjects. Gene polymorphisms were analyzed using a DNA microarray. We found an increased breast cancer risk associated with the GSTM1 gene deletion polymorphism (OR = 2.19; 95%CI = 1.50-3.21; P = 0.001). No associations between the GSTT1, GSTP1, and GSTM3 genotypes and neoplasia risk were observed. In conclusion, we determined the genotype distribution of GST polymorphisms in control subjects and breast cancer patients from northeastern Mexico. The GSTM1 null genotype was associated with breast cancer risk. Our findings may be used to individualize breast cancer screening and therapeutic intervention in our population, which displays ethnic characteristics that differentiate it from other populations in Mexico.

Signal amplification by rolling circle amplification on DNA microarrays

PubMed Central

Nallur, Girish; Luo, Chenghua; Fang, Linhua; Cooley, Stephanie; Dave, Varshal; Lambert, Jeremy; Kukanskis, Kari; Kingsmore, Stephen; Lasken, Roger; Schweitzer, Barry

2001-01-01

While microarrays hold considerable promise in large-scale biology on account of their massively parallel analytical nature, there is a need for compatible signal amplification procedures to increase sensitivity without loss of multiplexing. Rolling circle amplification (RCA) is a molecular amplification method with the unique property of product localization. This report describes the application of RCA signal amplification for multiplexed, direct detection and quantitation of nucleic acid targets on planar glass and gel-coated microarrays. As few as 150 molecules bound to the surface of microarrays can be detected using RCA. Because of the linear kinetics of RCA, nucleic acid target molecules may be measured with a dynamic range of four orders of magnitude. Consequently, RCA is a promising technology for the direct measurement of nucleic acids on microarrays without the need for a potentially biasing preamplification step. PMID:11726701

Parallel, confocal, and complete spectrum imager for fluorescent detection of high-density microarray

NASA Astrophysics Data System (ADS)

Bogdanov, Valery L.; Boyce-Jacino, Michael

1999-05-01

Confined arrays of biochemical probes deposited on a solid support surface (analytical microarray or 'chip') provide an opportunity to analysis multiple reactions simultaneously. Microarrays are increasingly used in genetics, medicine and environment scanning as research and analytical instruments. A power of microarray technology comes from its parallelism which grows with array miniaturization, minimization of reagent volume per reaction site and reaction multiplexing. An optical detector of microarray signals should combine high sensitivity, spatial and spectral resolution. Additionally, low-cost and a high processing rate are needed to transfer microarray technology into biomedical practice. We designed an imager that provides confocal and complete spectrum detection of entire fluorescently-labeled microarray in parallel. Imager uses microlens array, non-slit spectral decomposer, and high- sensitive detector (cooled CCD). Two imaging channels provide a simultaneous detection of localization, integrated and spectral intensities for each reaction site in microarray. A dimensional matching between microarray and imager's optics eliminates all in moving parts in instrumentation, enabling highly informative, fast and low-cost microarray detection. We report theory of confocal hyperspectral imaging with microlenses array and experimental data for implementation of developed imager to detect fluorescently labeled microarray with a density approximately 103 sites per cm2.

Impact of hepatitis C virus polymorphisms on direct-acting antiviral treatment efficacy: Regulatory analyses and perspectives.

PubMed

Harrington, Patrick R; Komatsu, Takashi E; Deming, Damon J; Donaldson, Eric F; O'Rear, Julian J; Naeger, Lisa K

2018-06-01

Several highly effective, interferon-free, direct-acting antiviral (DAA)-based regimens are available for the treatment of chronic hepatitis C virus (HCV) infection. Despite impressive efficacy overall, a small proportion of patients in registrational trials experienced treatment failure, which in some cases was associated with the detection of HCV resistance-associated substitutions (RASs) at baseline. In this article, we describe methods and key findings from independent regulatory analyses investigating the impact of baseline nonstructural (NS) 3 Q80K and NS5A RASs on the efficacy of current United States Food and Drug Administration (FDA)-approved regimens for patients with HCV genotype (GT) 1 or GT3 infection. These analyses focused on clinical trials that included patients who were previously naïve to the DAA class(es) in their investigational regimen and characterized the impact of baseline RASs that were enriched in the viral population as natural or transmitted polymorphisms (i.e., not drug-selected RASs). We used a consistent approach to optimize comparability of results across different DAA regimens and patient populations, including the use of a 15% sensitivity cutoff for next-generation sequencing results and standardized lists of NS5A RASs. These analyses confirmed that detection of NS3 Q80K or NS5A baseline RASs was associated with reduced treatment efficacy for multiple DAA regimens, but their impact was often minimized with the use of an intensified treatment regimen, such as a longer treatment duration and/or addition of ribavirin. We discuss the drug resistance-related considerations that contributed to pretreatment resistance testing and treatment recommendations in drug labeling for FDA-approved DAA regimens. Independent regulatory analyses confirmed that baseline HCV RASs can reduce the efficacy of certain DAA-based regimens in selected patient groups. However, highly effective treatment options are available for patients with or without

Systematic validation and atomic force microscopy of non-covalent short oligonucleotide barcode microarrays.

PubMed

Cook, Michael A; Chan, Chi-Kin; Jorgensen, Paul; Ketela, Troy; So, Daniel; Tyers, Mike; Ho, Chi-Yip

2008-02-06

Molecular barcode arrays provide a powerful means to analyze cellular phenotypes in parallel through detection of short (20-60 base) unique sequence tags, or "barcodes", associated with each strain or clone in a collection. However, costs of current methods for microarray construction, whether by in situ oligonucleotide synthesis or ex situ coupling of modified oligonucleotides to the slide surface are often prohibitive to large-scale analyses. Here we demonstrate that unmodified 20mer oligonucleotide probes printed on conventional surfaces show comparable hybridization signals to covalently linked 5'-amino-modified probes. As a test case, we undertook systematic cell size analysis of the budding yeast Saccharomyces cerevisiae genome-wide deletion collection by size separation of the deletion pool followed by determination of strain abundance in size fractions by barcode arrays. We demonstrate that the properties of a 13K unique feature spotted 20 mer oligonucleotide barcode microarray compare favorably with an analogous covalently-linked oligonucleotide array. Further, cell size profiles obtained with the size selection/barcode array approach recapitulate previous cell size measurements of individual deletion strains. Finally, through atomic force microscopy (AFM), we characterize the mechanism of hybridization to unmodified barcode probes on the slide surface. These studies push the lower limit of probe size in genome-scale unmodified oligonucleotide microarray construction and demonstrate a versatile, cost-effective and reliable method for molecular barcode analysis.

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

PubMed

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

2018-04-01

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

Best practices for hybridization design in two-colour microarray analysis.

PubMed

Knapen, Dries; Vergauwen, Lucia; Laukens, Kris; Blust, Ronny

2009-07-01

Two-colour microarrays are a popular platform of choice in gene expression studies. Because two different samples are hybridized on a single microarray, and several microarrays are usually needed in a given experiment, there are many possible ways to combine samples on different microarrays. The actual combination employed is commonly referred to as the 'hybridization design'. Different types of hybridization designs have been developed, all aimed at optimizing the experimental setup for the detection of differentially expressed genes while coping with technical noise. Here, we first provide an overview of the different classes of hybridization designs, discussing their advantages and limitations, and then we illustrate the current trends in the use of different hybridization design types in contemporary research.

Metabolic Capacity of Sinorhizobium (Ensifer) meliloti Strains as Determined by Phenotype MicroArray Analysis▿ †

PubMed Central

Biondi, Emanuele G.; Tatti, Enrico; Comparini, Diego; Giuntini, Elisa; Mocali, Stefano; Giovannetti, Luciana; Bazzicalupo, Marco; Mengoni, Alessio; Viti, Carlo

2009-01-01

Sinorhizobium meliloti is a soil bacterium that fixes atmospheric nitrogen in plant roots. The high genetic diversity of its natural populations has been the subject of extensive analysis. Recent genomic studies of several isolates revealed a high content of variable genes, suggesting a correspondingly large phenotypic differentiation among strains of S. meliloti. Here, using the Phenotype MicroArray (PM) system, hundreds of different growth conditions were tested in order to compare the metabolic capabilities of the laboratory reference strain Rm1021 with those of four natural S. meliloti isolates previously analyzed by comparative genomic hybridization (CGH). The results of PM analysis showed that most phenotypic differences involved carbon source utilization and tolerance to osmolytes and pH, while fewer differences were scored for nitrogen, phosphorus, and sulfur source utilization. Only the variability of the tested strain in tolerance to sodium nitrite and ammonium sulfate of pH 8 was hypothesized to be associated with the genetic polymorphisms detected by CGH analysis. Colony and cell morphologies and the ability to nodulate Medicago truncatula plants were also compared, revealing further phenotypic diversity. Overall, our results suggest that the study of functional (phenotypic) variability of S. meliloti populations is an important and complementary step in the investigation of genetic polymorphism of rhizobia and may help to elucidate rhizobial evolutionary dynamics, including adaptation to diverse environments. PMID:19561177

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

PubMed

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

Waveguide-excited fluorescence microarray

NASA Astrophysics Data System (ADS)

Sagarzazu, Gabriel; Bedu, Mélanie; Martinelli, Lucio; Ha, Khoi-Nguyen; Pelletier, Nicolas; Safarov, Viatcheslav I.; Weisbuch, Claude; Gacoin, Thierry; Benisty, Henri

2008-04-01

Signal-to-noise ratio is a crucial issue in microarray fluorescence read-out. Several strategies are proposed for its improvement. First, light collection in conventional microarrays scanners is quite limited. It was recently shown that almost full collection can be achieved in an integrated lens-free biosensor, with labelled species hybridizing practically on the surface of a sensitive silicon detector [L. Martinelli et al. Appl. Phys. Lett. 91, 083901 (2007)]. However, even with such an improvement, the ultimate goal of real-time measurements during hybridization is challenging: the detector is dazzled by the large fluorescence of labelled species in the solution. In the present paper we show that this unwanted signal can effectively be reduced if the excitation light is confined in a waveguide. Moreover, the concentration of excitation light in a waveguide results in a huge signal gain. In our experiment we realized a structure consisting of a high index sol-gel waveguide deposited on a low-index substrate. The fluorescent molecules deposited on the surface of the waveguide were excited by the evanescent part of a wave travelling in the guide. The comparison with free-space excitation schemes confirms a huge gain (by several orders of magnitude) in favour of waveguide-based excitation. An optical guide deposited onto an integrated biosensor thus combines both advantages of ideal light collection and enhanced surface localized excitation without compromising the imaging properties. Modelling predicts a negligible penalty from spatial cross-talk in practical applications. We believe that such a system would bring microarrays to hitherto unattained sensitivities.

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

PubMed Central

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

2014-01-01

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

Diversity and relationships of Crocus sativus and its relatives analysed by inter-retroelement amplified polymorphism (IRAP)

PubMed Central

Alsayied, Nouf Fakieh; Fernández, José Antonio; Schwarzacher, Trude; Heslop-Harrison, J. S.

2015-01-01

Background and Aims: Saffron (Crocus sativus) is a sterile triploid (2n = 3x = 24) cultivated species, of unknown origin from other diploid and polyploid species in the genus Crocus (Iridaceae). Species in the genus have high morphological diversity, with no clear phylogenetic patterns below the level of section Crocus series Crocus. Using DNA markers, this study aimed to examine the diversity and relationships within and between species of Crocus series Crocus. Methods: Eleven inter-retroelement amplified polymorphism (IRAP) primers were used in 63 different combinations with 35 single-plant accessions of C. sativus and related Crocus species in order to determine genetic variability and to conduct phylogenetic analysis. Key Results: A total of 4521 distinct polymorphic bands from 100 bp to approx. 4 kb were amplified; no fragment specific to all accessions of a single species was amplified. The polymorphic information content (PIC) values varied from approx. 0·37 to approx. 0·05 (mean 0·17 ± 0·1) and the major allele frequency had a mean of 0·87. High levels of polymorphism were identified between accessions of the six species of Crocus series Crocus related to C. sativus, with further variation between the species. In contrast, no polymorphisms were seen among 17 C. sativus accessions obtained in the region from Kashmir through Iran to Spain. Conclusions In contrast to the intraspecific variability seen in other Crocus species, C. sativus has minimal genetic variation, and it is concluded that the triploid hybrid species has most probably arisen only once. The data show that saffron is an allotriploid species, with the IRAP analysis indicating that the most likely ancestors are C. cartwrightianus and C. pallasii subsp. pallasii (or close relatives). The results may facilitate resynthesizing saffron with improved characteristics, and show the need for conservation and collection of wild Crocus. PMID:26138822

Fully Automated Complementary DNA Microarray Segmentation using a Novel Fuzzy-based Algorithm.

PubMed

Saberkari, Hamidreza; Bahrami, Sheyda; Shamsi, Mousa; Amoshahy, Mohammad Javad; Ghavifekr, Habib Badri; Sedaaghi, Mohammad Hossein

2015-01-01

DNA microarray is a powerful approach to study simultaneously, the expression of 1000 of genes in a single experiment. The average value of the fluorescent intensity could be calculated in a microarray experiment. The calculated intensity values are very close in amount to the levels of expression of a particular gene. However, determining the appropriate position of every spot in microarray images is a main challenge, which leads to the accurate classification of normal and abnormal (cancer) cells. In this paper, first a preprocessing approach is performed to eliminate the noise and artifacts available in microarray cells using the nonlinear anisotropic diffusion filtering method. Then, the coordinate center of each spot is positioned utilizing the mathematical morphology operations. Finally, the position of each spot is exactly determined through applying a novel hybrid model based on the principle component analysis and the spatial fuzzy c-means clustering (SFCM) algorithm. Using a Gaussian kernel in SFCM algorithm will lead to improving the quality in complementary DNA microarray segmentation. The performance of the proposed algorithm has been evaluated on the real microarray images, which is available in Stanford Microarray Databases. Results illustrate that the accuracy of microarray cells segmentation in the proposed algorithm reaches to 100% and 98% for noiseless/noisy cells, respectively.

Glycan microarray screening assay for glycosyltransferase specificities.

PubMed

Peng, Wenjie; Nycholat, Corwin M; Razi, Nahid

2013-01-01

Glycan microarrays represent a high-throughput approach to determining the specificity of glycan-binding proteins against a large set of glycans in a single format. This chapter describes the use of a glycan microarray platform for evaluating the activity and substrate specificity of glycosyltransferases (GTs). The methodology allows simultaneous screening of hundreds of immobilized glycan acceptor substrates by in situ incubation of a GT and its appropriate donor substrate on the microarray surface. Using biotin-conjugated donor substrate enables direct detection of the incorporated sugar residues on acceptor substrates on the array. In addition, the feasibility of the method has been validated using label-free donor substrate combined with lectin-based detection of product to assess enzyme activity. Here, we describe the application of both procedures to assess the specificity of a recombinant human α2-6 sialyltransferase. This technique is readily adaptable to studying other glycosyltransferases.

Identifying Fishes through DNA Barcodes and Microarrays.

PubMed

Kochzius, Marc; Seidel, Christian; Antoniou, Aglaia; Botla, Sandeep Kumar; Campo, Daniel; Cariani, Alessia; Vazquez, Eva Garcia; Hauschild, Janet; Hervet, Caroline; Hjörleifsdottir, Sigridur; Hreggvidsson, Gudmundur; Kappel, Kristina; Landi, Monica; Magoulas, Antonios; Marteinsson, Viggo; Nölte, Manfred; Planes, Serge; Tinti, Fausto; Turan, Cemal; Venugopal, Moleyur N; Weber, Hannes; Blohm, Dietmar

2010-09-07

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

Microarray analysis of genes differentially expressed in HepG2 cells cultured in simulated microgravity: preliminary report

NASA Technical Reports Server (NTRS)

Khaoustov, V. I.; Risin, D.; Pellis, N. R.; Yoffe, B.; McIntire, L. V. (Principal Investigator)

2001-01-01

Developed at NASA, the rotary cell culture system (RCCS) allows the creation of unique microgravity environment of low shear force, high-mass transfer, and enables three-dimensional (3D) cell culture of dissimilar cell types. Recently we demonstrated that a simulated microgravity is conducive for maintaining long-term cultures of functional hepatocytes and promote 3D cell assembly. Using deoxyribonucleic acid (DNA) microarray technology, it is now possible to measure the levels of thousands of different messenger ribonucleic acids (mRNAs) in a single hybridization step. This technique is particularly powerful for comparing gene expression in the same tissue under different environmental conditions. The aim of this research was to analyze gene expression of hepatoblastoma cell line (HepG2) during early stage of 3D-cell assembly in simulated microgravity. For this, mRNA from HepG2 cultured in the RCCS was analyzed by deoxyribonucleic acid microarray. Analyses of HepG2 mRNA by using 6K glass DNA microarray revealed changes in expression of 95 genes (overexpression of 85 genes and downregulation of 10 genes). Our preliminary results indicated that simulated microgravity modifies the expression of several genes and that microarray technology may provide new understanding of the fundamental biological questions of how gravity affects the development and function of individual cells.

Deciphering the glycosaminoglycan code with the help of microarrays.

PubMed

de Paz, Jose L; Seeberger, Peter H

2008-07-01

Carbohydrate microarrays have become a powerful tool to elucidate the biological role of complex sugars. Microarrays are particularly useful for the study of glycosaminoglycans (GAGs), a key class of carbohydrates. The high-throughput chip format enables rapid screening of large numbers of potential GAG sequences produced via a complex biosynthesis while consuming very little sample. Here, we briefly highlight the most recent advances involving GAG microarrays built with synthetic or naturally derived oligosaccharides. These chips are powerful tools for characterizing GAG-protein interactions and determining structure-activity relationships for specific sequences. Thereby, they contribute to decoding the information contained in specific GAG sequences.

AFM 4.0: a toolbox for DNA microarray analysis

PubMed Central

Breitkreutz, Bobby-Joe; Jorgensen, Paul; Breitkreutz, Ashton; Tyers, Mike

2001-01-01

We have developed a series of programs, collectively packaged as Array File Maker 4.0 (AFM), that manipulate and manage DNA microarray data. AFM 4.0 is simple to use, applicable to any organism or microarray, and operates within the familiar confines of Microsoft Excel. Given a database of expression ratios, AFM 4.0 generates input files for clustering, helps prepare colored figures and Venn diagrams, and can uncover aneuploidy in yeast microarray data. AFM 4.0 should be especially useful to laboratories that do not have access to specialized commercial or in-house software. PMID:11532221

Applications of microarray technology in breast cancer research

PubMed Central

Cooper, Colin S

2001-01-01

Microarrays provide a versatile platform for utilizing information from the Human Genome Project to benefit human health. This article reviews the ways in which microarray technology may be used in breast cancer research. Its diverse applications include monitoring chromosome gains and losses, tumour classification, drug discovery and development, DNA resequencing, mutation detection and investigating the mechanism of tumour development. PMID:11305951

Development and characterization of a disposable plastic microarray printhead.

PubMed

Griessner, Matthias; Hartig, Dave; Christmann, Alexander; Pohl, Carsten; Schellhase, Michaela; Ehrentreich-Förster, Eva

2011-06-01

During the last decade microarrays have become a powerful analytical tool. Commonly microarrays are produced in a non-contact manner using silicone printheads. However, silicone printheads are expensive and not able to be used as a disposable. Here, we show the development and functional characterization of 8-channel plastic microarray printheads that overcome both disadvantages of their conventional silicone counterparts. A combination of injection-molding and laser processing allows us to produce a high quantity of cheap, customizable and disposable microarray printheads. The use of plastics (e.g., polystyrene) minimizes the need for surface modifications required previously for proper printing results. Time-consuming regeneration processes, cleaning procedures and contaminations caused by residual samples are avoided. The utilization of plastic printheads for viscous liquids, such as cell suspensions or whole blood, is possible. Furthermore, functional parts within the plastic printhead (e.g., particle filters) can be included. Our printhead is compatible with commercially available TopSpot devices but provides additional economic and technical benefits as compared to conventional TopSpot printheads, while fulfilling all requirements demanded on the latter. All in all, this work describes how the field of traditional microarray spotting can be extended significantly by low cost plastic printheads.

[Typing and subtyping avian influenza virus using DNA microarrays].

PubMed

Yang, Zhongping; Wang, Xiurong; Tian, Lina; Wang, Yu; Chen, Hualan

2008-07-01

Outbreaks of highly pathogenic avian influenza (HPAI) virus has caused great economic loss to the poultry industry and resulted in human deaths in Thailand and Vietnam since 2004. Rapid typing and subtyping of viruses, especially HPAI from clinical specimens, are desirable for taking prompt control measures to prevent spreading of the disease. We described a simultaneous approach using microarray to detect and subtype avian influenza virus (AIV). We designed primers of probe genes and used reverse transcriptase PCR to prepare cDNAs of AIV M gene, H5, H7, H9 subtypes haemagglutinin genes and N1, N2 subtypes neuraminidase genes. They were cloned, sequenced, reamplified and spotted to form a glass-bound microarrays. We labeled samples using Cy3-dUTP by RT-PCR, hybridized and scanned the microarrays to typing and subtyping AIV. The hybridization pattern agreed perfectly with the known grid location of each probe, no cross hybridization could be detected. Examinating of HA subtypes 1 through 15, 30 infected samples and 21 field samples revealed the DNA microarray assay was more sensitive and specific than RT-PCR test and chicken embryo inoculation. It can simultaneously detect and differentiate the main epidemic AIV. The results show that DNA microarray technology is a useful diagnostic method.

Statistical issues in signal extraction from microarrays

NASA Astrophysics Data System (ADS)

Bergemann, Tracy; Quiaoit, Filemon; Delrow, Jeffrey J.; Zhao, Lue Ping

2001-06-01

Microarray technologies are increasingly used in biomedical research to study genome-wide expression profiles in the post genomic era. Their popularity is largely due to their high throughput and economical affordability. For example, microarrays have been applied to studies of cell cycle, regulatory circuitry, cancer cell lines, tumor tissues, and drug discoveries. One obstacle facing the continued success of applying microarray technologies, however, is the random variaton present on microarrays: within signal spots, between spots and among chips. In addition, signals extracted by available software packages seem to vary significantly. Despite a variety of software packages, it appears that there are two major approaches to signal extraction. One approach is to focus on the identification of signal regions and hence estimation of signal levels above background levels. The other approach is to use the distribution of intensity values as a way of identifying relevant signals. Building upon both approaches, the objective of our work is to develop a method that is statistically rigorous and also efficient and robust. Statistical issues to be considered here include: (1) how to refine grid alignment so that the overall variation is minimized, (2) how to estimate the signal levels relative to the local background levels as well as the variance of this estimate, and (3) how to integrate red and green channel signals so that the ratio of interest is stable, simultaneously relaxing distributional assumptions.

ELISA-BASE: An Integrated Bioinformatics Tool for Analyzing and Tracking ELISA Microarray Data

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

White, Amanda M.; Collett, James L.; Seurynck-Servoss, Shannon L.

ELISA-BASE is an open-source database for capturing, organizing and analyzing protein enzyme-linked immunosorbent assay (ELISA) microarray data. ELISA-BASE is an extension of the BioArray Soft-ware Environment (BASE) database system, which was developed for DNA microarrays. In order to make BASE suitable for protein microarray experiments, we developed several plugins for importing and analyzing quantitative ELISA microarray data. Most notably, our Protein Microarray Analysis Tool (ProMAT) for processing quantita-tive ELISA data is now available as a plugin to the database.

MIGS-GPU: Microarray Image Gridding and Segmentation on the GPU.

PubMed

Katsigiannis, Stamos; Zacharia, Eleni; Maroulis, Dimitris

2017-05-01

Complementary DNA (cDNA) microarray is a powerful tool for simultaneously studying the expression level of thousands of genes. Nevertheless, the analysis of microarray images remains an arduous and challenging task due to the poor quality of the images that often suffer from noise, artifacts, and uneven background. In this study, the MIGS-GPU [Microarray Image Gridding and Segmentation on Graphics Processing Unit (GPU)] software for gridding and segmenting microarray images is presented. MIGS-GPU's computations are performed on the GPU by means of the compute unified device architecture (CUDA) in order to achieve fast performance and increase the utilization of available system resources. Evaluation on both real and synthetic cDNA microarray images showed that MIGS-GPU provides better performance than state-of-the-art alternatives, while the proposed GPU implementation achieves significantly lower computational times compared to the respective CPU approaches. Consequently, MIGS-GPU can be an advantageous and useful tool for biomedical laboratories, offering a user-friendly interface that requires minimum input in order to run.

A Novel Plasmid-Based Microarray Screen Identifies Suppressors of rrp6Δ in Saccharomyces cerevisiae▿†

PubMed Central

Abruzzi, Katharine; Denome, Sylvia; Olsen, Jens Raabjerg; Assenholt, Jannie; Haaning, Line Lindegaard; Jensen, Torben Heick; Rosbash, Michael

2007-01-01

Genetic screens in Saccharomyces cerevisiae provide novel information about interacting genes and pathways. We screened for high-copy-number suppressors of a strain with the gene encoding the nuclear exosome component Rrp6p deleted, with either a traditional plate screen for suppressors of rrp6Δ temperature sensitivity or a novel microarray enhancer/suppressor screening (MES) strategy. MES combines DNA microarray technology with high-copy-number plasmid expression in liquid media. The plate screen and MES identified overlapping, but also different, suppressor genes. Only MES identified the novel mRNP protein Nab6p and the tRNA transporter Los1p, which could not have been identified in a traditional plate screen; both genes are toxic when overexpressed in rrp6Δ strains at 37°C. Nab6p binds poly(A)+ RNA, and the functions of Nab6p and Los1p suggest that mRNA metabolism and/or protein synthesis are growth rate limiting in rrp6Δ strains. Microarray analyses of gene expression in rrp6Δ strains and a number of suppressor strains support this hypothesis. PMID:17101774

Impact of genomic polymorphisms on the repertoire of human MHC class I-associated peptides

PubMed Central

Granados, Diana Paola; Sriranganadane, Dev; Daouda, Tariq; Zieger, Antoine; Laumont, Céline M.; Caron-Lizotte, Olivier; Boucher, Geneviève; Hardy, Marie-Pierre; Gendron, Patrick; Côté, Caroline; Lemieux, Sébastien; Thibault, Pierre; Perreault, Claude

2014-01-01

For decades, the global impact of genomic polymorphisms on the repertoire of peptides presented by major histocompatibility complex (MHC) has remained a matter of speculation. Here we present a novel approach that enables high-throughput discovery of polymorphic MHC class I-associated peptides (MIPs), which play a major role in allorecognition. On the basis of comprehensive analyses of the genomic landscape of MIPs eluted from B lymphoblasts of two MHC-identical siblings, we show that 0.5% of non-synonymous single nucleotide variations are represented in the MIP repertoire. The 34 polymorphic MIPs found in our subjects are encoded by bi-allelic loci with dominant and recessive alleles. Our analyses show that, at the population level, 12% of the MIP-coding exome is polymorphic. Our method provides fundamental insights into the relationship between the genomic self and the immune self and accelerates the discovery of polymorphic MIPs (also known as minor histocompatibility antigens). PMID:24714562

Genotyping microarray: Mutation screening in Spanish families with autosomal dominant retinitis pigmentosa

PubMed Central

García-Hoyos, María; Cortón, Marta; Ávila-Fernández, Almudena; Riveiro-Álvarez, Rosa; Giménez, Ascensión; Hernan, Inma; Carballo, Miguel; Ayuso, Carmen

2012-01-01

Purpose Presently, 22 genes have been described in association with autosomal dominant retinitis pigmentosa (adRP); however, they explain only 50% of all cases, making genetic diagnosis of this disease difficult and costly. The aim of this study was to evaluate a specific genotyping microarray for its application to the molecular diagnosis of adRP in Spanish patients. Methods We analyzed 139 unrelated Spanish families with adRP. Samples were studied by using a genotyping microarray (adRP). All mutations found were further confirmed with automatic sequencing. Rhodopsin (RHO) sequencing was performed in all negative samples for the genotyping microarray. Results The adRP genotyping microarray detected the mutation associated with the disease in 20 of the 139 families with adRP. As in other populations, RHO was found to be the most frequently mutated gene in these families (7.9% of the microarray genotyped families). The rate of false positives (microarray results not confirmed with sequencing) and false negatives (mutations in RHO detected with sequencing but not with the genotyping microarray) were established, and high levels of analytical sensitivity (95%) and specificity (100%) were found. Diagnostic accuracy was 15.1%. Conclusions The adRP genotyping microarray is a quick, cost-efficient first step in the molecular diagnosis of Spanish patients with adRP. PMID:22736939

DNA Microarray Detection of 18 Important Human Blood Protozoan Species

PubMed Central

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

2016-01-01

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

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

PubMed

Dolled-Filhart, Marisa P; Gustavson, Mark D

2012-11-01

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

Linking microarray reporters with protein functions.

PubMed

Gaj, Stan; van Erk, Arie; van Haaften, Rachel I M; Evelo, Chris T A

2007-09-26

The analysis of microarray experiments requires accurate and up-to-date functional annotation of the microarray reporters to optimize the interpretation of the biological processes involved. Pathway visualization tools are used to connect gene expression data with existing biological pathways by using specific database identifiers that link reporters with elements in the pathways. This paper proposes a novel method that aims to improve microarray reporter annotation by BLASTing the original reporter sequences against a species-specific EMBL subset, that was derived from and crosslinked back to the highly curated UniProt database. The resulting alignments were filtered using high quality alignment criteria and further compared with the outcome of a more traditional approach, where reporter sequences were BLASTed against EnsEMBL followed by locating the corresponding protein (UniProt) entry for the high quality hits. Combining the results of both methods resulted in successful annotation of > 58% of all reporter sequences with UniProt IDs on two commercial array platforms, increasing the amount of Incyte reporters that could be coupled to Gene Ontology terms from 32.7% to 58.3% and to a local GenMAPP pathway from 9.6% to 16.7%. For Agilent, 35.3% of the total reporters are now linked towards GO nodes and 7.1% on local pathways. Our methods increased the annotation quality of microarray reporter sequences and allowed us to visualize more reporters using pathway visualization tools. Even in cases where the original reporter annotation showed the correct description the new identifiers often allowed improved pathway and Gene Ontology linking. These methods are freely available at http://www.bigcat.unimaas.nl/public/publications/Gaj_Annotation/.

Linking microarray reporters with protein functions

PubMed Central

Gaj, Stan; van Erk, Arie; van Haaften, Rachel IM; Evelo, Chris TA

2007-01-01

Background The analysis of microarray experiments requires accurate and up-to-date functional annotation of the microarray reporters to optimize the interpretation of the biological processes involved. Pathway visualization tools are used to connect gene expression data with existing biological pathways by using specific database identifiers that link reporters with elements in the pathways. Results This paper proposes a novel method that aims to improve microarray reporter annotation by BLASTing the original reporter sequences against a species-specific EMBL subset, that was derived from and crosslinked back to the highly curated UniProt database. The resulting alignments were filtered using high quality alignment criteria and further compared with the outcome of a more traditional approach, where reporter sequences were BLASTed against EnsEMBL followed by locating the corresponding protein (UniProt) entry for the high quality hits. Combining the results of both methods resulted in successful annotation of > 58% of all reporter sequences with UniProt IDs on two commercial array platforms, increasing the amount of Incyte reporters that could be coupled to Gene Ontology terms from 32.7% to 58.3% and to a local GenMAPP pathway from 9.6% to 16.7%. For Agilent, 35.3% of the total reporters are now linked towards GO nodes and 7.1% on local pathways. Conclusion Our methods increased the annotation quality of microarray reporter sequences and allowed us to visualize more reporters using pathway visualization tools. Even in cases where the original reporter annotation showed the correct description the new identifiers often allowed improved pathway and Gene Ontology linking. These methods are freely available at http://www.bigcat.unimaas.nl/public/publications/Gaj_Annotation/. PMID:17897448

Data-adaptive test statistics for microarray data.

PubMed

Mukherjee, Sach; Roberts, Stephen J; van der Laan, Mark J

2005-09-01

An important task in microarray data analysis is the selection of genes that are differentially expressed between different tissue samples, such as healthy and diseased. However, microarray data contain an enormous number of dimensions (genes) and very few samples (arrays), a mismatch which poses fundamental statistical problems for the selection process that have defied easy resolution. In this paper, we present a novel approach to the selection of differentially expressed genes in which test statistics are learned from data using a simple notion of reproducibility in selection results as the learning criterion. Reproducibility, as we define it, can be computed without any knowledge of the 'ground-truth', but takes advantage of certain properties of microarray data to provide an asymptotically valid guide to expected loss under the true data-generating distribution. We are therefore able to indirectly minimize expected loss, and obtain results substantially more robust than conventional methods. We apply our method to simulated and oligonucleotide array data. By request to the corresponding author.

Plasminogen activator inhibitor-1 4G/5G promoter polymorphism and coagulation factor VII Arg353-->Gln polymorphism in Korean patients with coronary artery disease.

PubMed Central

Song, J.; Yoon, Y. M.; Jung, H. J.; Hong, S. H.; Park, H.; Kim, J. Q.

2000-01-01

An increased risk for arterial thrombosis is associated with high plasma levels of coagulation and fibrinolytic factors such as PAI-1 and FVII. In this study, the 4G/5G polymorphism in the promoter of PAI-1 gene and Arg353-->Gln polymorphism in the FVII gene were analysed in 139 normal adults and 158 patients with coronary artery disease (CAD), and their association with plasma lipid traits was investigated. There were no significant differences in the allele frequencies of PAI-1 and FVII polymorphisms between control and patient groups. The allelic distributions of both polymorphisms in Koreans were similar to those in Japanese but significantly different from those in Caucasians. In the CAD group, the 4G homozygotes of PAI-1 polymorphism showed significantly higher levels of total (p=0.0250) and LDL cholesterol (p=0.0335) with individuals having other genotypes. However, FVII polymorphism showed no association with lipid levels. In conclusion, the 4G/5G PAI-1 promoter polymorphism and Arg353-->Gln FVII polymorphism are not major genetic risk factors for CAD in Koreans. However, 4G allele of PAI-1 polymorphism revealed to be associated with the levels of cholesterol, especially LDL cholesterol levels in CAD patients. PMID:10803689

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

PubMed

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

2003-04-01

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

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

PubMed Central

2009-01-01

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

puma: a Bioconductor package for propagating uncertainty in microarray analysis.

PubMed

Pearson, Richard D; Liu, Xuejun; Sanguinetti, Guido; Milo, Marta; Lawrence, Neil D; Rattray, Magnus

2009-07-09

Most analyses of microarray data are based on point estimates of expression levels and ignore the uncertainty of such estimates. By determining uncertainties from Affymetrix GeneChip data and propagating these uncertainties to downstream analyses it has been shown that we can improve results of differential expression detection, principal component analysis and clustering. Previously, implementations of these uncertainty propagation methods have only been available as separate packages, written in different languages. Previous implementations have also suffered from being very costly to compute, and in the case of differential expression detection, have been limited in the experimental designs to which they can be applied. puma is a Bioconductor package incorporating a suite of analysis methods for use on Affymetrix GeneChip data. puma extends the differential expression detection methods of previous work from the 2-class case to the multi-factorial case. puma can be used to automatically create design and contrast matrices for typical experimental designs, which can be used both within the package itself but also in other Bioconductor packages. The implementation of differential expression detection methods has been parallelised leading to significant decreases in processing time on a range of computer architectures. puma incorporates the first R implementation of an uncertainty propagation version of principal component analysis, and an implementation of a clustering method based on uncertainty propagation. All of these techniques are brought together in a single, easy-to-use package with clear, task-based documentation. For the first time, the puma package makes a suite of uncertainty propagation methods available to a general audience. These methods can be used to improve results from more traditional analyses of microarray data. puma also offers improvements in terms of scope and speed of execution over previously available methods. puma is recommended for

Association between IL-1β polymorphisms and gastritis risk

PubMed Central

Sun, Xiaoming; Cai, Hongxing; Li, Zhouru; Li, Shanshan; Yin, Wenjiang; Dong, Guokai; Kuai, Jinxia; He, Yihui; Jia, Jing

2017-01-01

Abstract Background: Helicobacter pylori (H. pylori) infection of the human stomach regularly leads to chronic gastric inflammation. The cytokine gene interleukin (IL)-1β has been implicated in influencing the pathology of inflammation induced by H. pylori infection. Currently, several studies have been carried out to investigate the association of IL-1β-511 (rs16944) and IL-1β-31 (rs1143627) polymorphisms with gastritis risk; however, the results are inconsistent and inconclusive. To assess the effect of IL-1β polymorphisms on gastritis susceptibility, we conducted a meta-analysis. Methods: Up to March 15, 2016, 2205 cases and 2289 controls were collected from 12 published case–control studies. Summarized odds ratios and corresponding 95% confidence intervals (CIs) for IL-1β-511 and IL-1β-31 polymorphisms and gastritis risk were estimated using fixed- or random-effects models when appropriate. Heterogeneity was assessed by chi-squared-based Q-statistic test, and the sources of heterogeneity were explored by subgroup analyses and logistic meta-regression analyses. Publication bias was evaluated by Begg funnel plot and Egger test. Sensitivity analyses were also performed. Results: The results provided evidences that the single nucleotide polymorphisms (SNPs) in IL-1β-31 might be associated with the gastritis risk, especially in the Caucasian population, while SNPs in the IL-1β-511 might not be. Conclusion: Our studies may be helpful in supplementing the disease monitoring of gastritis in the future, and additional studies to determine the exact molecular mechanisms might inspire interventions to protect the susceptible subgroups. PMID:28151895

Genomic resources for Myzus persicae: EST sequencing, SNP identification, and microarray design

PubMed Central

Ramsey, John S; Wilson, Alex CC; de Vos, Martin; Sun, Qi; Tamborindeguy, Cecilia; Winfield, Agnese; Malloch, Gaynor; Smith, Dawn M; Fenton, Brian; Gray, Stewart M; Jander, Georg

2007-01-01

Background The green peach aphid, Myzus persicae (Sulzer), is a world-wide insect pest capable of infesting more than 40 plant families, including many crop species. However, despite the significant damage inflicted by M. persicae in agricultural systems through direct feeding damage and by its ability to transmit plant viruses, limited genomic information is available for this species. Results Sequencing of 16 M. persicae cDNA libraries generated 26,669 expressed sequence tags (ESTs). Aphids for library construction were raised on Arabidopsis thaliana, Nicotiana benthamiana, Brassica oleracea, B. napus, and Physalis floridana (with and without Potato leafroll virus infection). The M. persicae cDNA libraries include ones made from sexual and asexual whole aphids, guts, heads, and salivary glands. In silico comparison of cDNA libraries identified aphid genes with tissue-specific expression patterns, and gene expression that is induced by feeding on Nicotiana benthamiana. Furthermore, 2423 genes that are novel to science and potentially aphid-specific were identified. Comparison of cDNA data from three aphid lineages identified single nucleotide polymorphisms that can be used as genetic markers and, in some cases, may represent functional differences in the protein products. In particular, non-conservative amino acid substitutions in a highly expressed gut protease may be of adaptive significance for M. persicae feeding on different host plants. The Agilent eArray platform was used to design an M. persicae oligonucleotide microarray representing over 10,000 unique genes. Conclusion New genomic resources have been developed for M. persicae, an agriculturally important insect pest. These include previously unknown sequence data, a collection of expressed genes, molecular markers, and a DNA microarray that can be used to study aphid gene expression. These resources will help elucidate the adaptations that allow M. persicae to develop compatible interactions with its

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

PubMed

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.

eSensor: an electrochemical detection-based DNA microarray technology enabling sample-to-answer molecular diagnostics

NASA Astrophysics Data System (ADS)

Liu, Robin H.; Longiaru, Mathew

2009-05-01

DNA microarrays are becoming a widespread tool used in life science and drug screening due to its many benefits of miniaturization and integration. Microarrays permit a highly multiplexed DNA analysis. Recently, the development of new detection methods and simplified methodologies has rapidly expanded the use of microarray technologies from predominantly gene expression analysis into the arena of diagnostics. Osmetech's eSensor® is an electrochemical detection platform based on a low-to- medium density DNA hybridization array on a cost-effective printed circuit board substrate. eSensor® has been cleared by FDA for Warfarin sensitivity test and Cystic Fibrosis Carrier Detection. Other genetic-based diagnostic and infectious disease detection tests are under development. The eSensor® platform eliminates the need for an expensive laser-based optical system and fluorescent reagents. It allows one to perform hybridization and detection in a single and small instrument without any fluidic processing and handling. Furthermore, the eSensor® platform is readily adaptable to on-chip sample-to-answer genetic analyses using microfluidics technology. The eSensor® platform provides a cost-effective solution to direct sample-to-answer genetic analysis, and thus have a potential impact in the fields of point-of-care genetic analysis, environmental testing, and biological warfare agent detection.

Normal uniform mixture differential gene expression detection for cDNA microarrays

PubMed Central

Dean, Nema; Raftery, Adrian E

2005-01-01

Background One of the primary tasks in analysing gene expression data is finding genes that are differentially expressed in different samples. Multiple testing issues due to the thousands of tests run make some of the more popular methods for doing this problematic. Results We propose a simple method, Normal Uniform Differential Gene Expression (NUDGE) detection for finding differentially expressed genes in cDNA microarrays. The method uses a simple univariate normal-uniform mixture model, in combination with new normalization methods for spread as well as mean that extend the lowess normalization of Dudoit, Yang, Callow and Speed (2002) [1]. It takes account of multiple testing, and gives probabilities of differential expression as part of its output. It can be applied to either single-slide or replicated experiments, and it is very fast. Three datasets are analyzed using NUDGE, and the results are compared to those given by other popular methods: unadjusted and Bonferroni-adjusted t tests, Significance Analysis of Microarrays (SAM), and Empirical Bayes for microarrays (EBarrays) with both Gamma-Gamma and Lognormal-Normal models. Conclusion The method gives a high probability of differential expression to genes known/suspected a priori to be differentially expressed and a low probability to the others. In terms of known false positives and false negatives, the method outperforms all multiple-replicate methods except for the Gamma-Gamma EBarrays method to which it offers comparable results with the added advantages of greater simplicity, speed, fewer assumptions and applicability to the single replicate case. An R package called nudge to implement the methods in this paper will be made available soon at . PMID:16011807

PRACTICAL STRATEGIES FOR PROCESSING AND ANALYZING SPOTTED OLIGONUCLEOTIDE MICROARRAY DATA

EPA Science Inventory

Thoughtful data analysis is as important as experimental design, biological sample quality, and appropriate experimental procedures for making microarrays a useful supplement to traditional toxicology. In the present study, spotted oligonucleotide microarrays were used to profile...

DNA microarray analyses reveal a post-irradiation differential time-dependent gene expression profile in yeast cells exposed to X-rays and gamma-rays.

PubMed

Kimura, Shinzo; Ishidou, Emi; Kurita, Sakiko; Suzuki, Yoshiteru; Shibato, Junko; Rakwal, Randeep; Iwahashi, Hitoshi

2006-07-21

Ionizing radiation (IR) is the most enigmatic of genotoxic stress inducers in our environment that has been around from the eons of time. IR is generally considered harmful, and has been the subject of numerous studies, mostly looking at the DNA damaging effects in cells and the repair mechanisms therein. Moreover, few studies have focused on large-scale identification of cellular responses to IR, and to this end, we describe here an initial study on the transcriptional responses of the unicellular genome model, yeast (Saccharomyces cerevisiae strain S288C), by cDNA microarray. The effect of two different IR, X-rays, and gamma (gamma)-rays, was investigated by irradiating the yeast cells cultured in YPD medium with 50 Gy doses of X- and gamma-rays, followed by resuspension of the cells in YPD for time-course experiments. The samples were collected for microarray analysis at 20, 40, and 80 min after irradiation. Microarray analysis revealed a time-course transcriptional profile of changed gene expressions. Up-regulated genes belonged to the functional categories mainly related to cell cycle and DNA processing, cell rescue defense and virulence, protein and cell fate, and metabolism (X- and gamma-rays). Similarly, for X- and gamma-rays, the down-regulated genes belonged to mostly transcription and protein synthesis, cell cycle and DNA processing, control of cellular organization, cell fate, and C-compound and carbohydrate metabolism categories, respectively. This study provides for the first time a snapshot of the genome-wide mRNA expression profiles in X- and gamma-ray post-irradiated yeast cells and comparatively interprets/discusses the changed gene functional categories as effects of these two radiations vis-à-vis their energy levels.

A fisheye viewer for microarray-based gene expression data

PubMed Central

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

2006-01-01

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 . 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. PMID:17038193

Efficient SNP Discovery by Combining Microarray and Lab-on-a-Chip Data for Animal Breeding and Selection

PubMed Central

Huang, Chao-Wei; Lin, Yu-Tsung; Ding, Shih-Torng; Lo, Ling-Ling; Wang, Pei-Hwa; Lin, En-Chung; Liu, Fang-Wei; Lu, Yen-Wen

2015-01-01

The genetic markers associated with economic traits have been widely explored for animal breeding. Among these markers, single-nucleotide polymorphism (SNPs) are gradually becoming a prevalent and effective evaluation tool. Since SNPs only focus on the genetic sequences of interest, it thereby reduces the evaluation time and cost. Compared to traditional approaches, SNP genotyping techniques incorporate informative genetic background, improve the breeding prediction accuracy and acquiesce breeding quality on the farm. This article therefore reviews the typical procedures of animal breeding using SNPs and the current status of related techniques. The associated SNP information and genotyping techniques, including microarray and Lab-on-a-Chip based platforms, along with their potential are highlighted. Examples in pig and poultry with different SNP loci linked to high economic trait values are given. The recommendations for utilizing SNP genotyping in nimal breeding are summarized. PMID:27600241

Where statistics and molecular microarray experiments biology meet.

PubMed

Kelmansky, Diana M

2013-01-01

This review chapter presents a statistical point of view to microarray experiments with the purpose of understanding the apparent contradictions that often appear in relation to their results. We give a brief introduction of molecular biology for nonspecialists. We describe microarray experiments from their construction and the biological principles the experiments rely on, to data acquisition and analysis. The role of epidemiological approaches and sample size considerations are also discussed.

Systematic Validation and Atomic Force Microscopy of Non-Covalent Short Oligonucleotide Barcode Microarrays

PubMed Central

Cook, Michael A.; Chan, Chi-Kin; Jorgensen, Paul; Ketela, Troy; So, Daniel; Tyers, Mike; Ho, Chi-Yip

2008-01-01

Background Molecular barcode arrays provide a powerful means to analyze cellular phenotypes in parallel through detection of short (20–60 base) unique sequence tags, or “barcodes”, associated with each strain or clone in a collection. However, costs of current methods for microarray construction, whether by in situ oligonucleotide synthesis or ex situ coupling of modified oligonucleotides to the slide surface are often prohibitive to large-scale analyses. Methodology/Principal Findings Here we demonstrate that unmodified 20mer oligonucleotide probes printed on conventional surfaces show comparable hybridization signals to covalently linked 5′-amino-modified probes. As a test case, we undertook systematic cell size analysis of the budding yeast Saccharomyces cerevisiae genome-wide deletion collection by size separation of the deletion pool followed by determination of strain abundance in size fractions by barcode arrays. We demonstrate that the properties of a 13K unique feature spotted 20 mer oligonucleotide barcode microarray compare favorably with an analogous covalently-linked oligonucleotide array. Further, cell size profiles obtained with the size selection/barcode array approach recapitulate previous cell size measurements of individual deletion strains. Finally, through atomic force microscopy (AFM), we characterize the mechanism of hybridization to unmodified barcode probes on the slide surface. Conclusions/Significance These studies push the lower limit of probe size in genome-scale unmodified oligonucleotide microarray construction and demonstrate a versatile, cost-effective and reliable method for molecular barcode analysis. PMID:18253494

Computational synchronization of microarray data with application to Plasmodium falciparum.

PubMed

Zhao, Wei; Dauwels, Justin; Niles, Jacquin C; Cao, Jianshu

2012-06-21

Microarrays are widely used to investigate the blood stage of Plasmodium falciparum infection. Starting with synchronized cells, gene expression levels are continually measured over the 48-hour intra-erythrocytic cycle (IDC). However, the cell population gradually loses synchrony during the experiment. As a result, the microarray measurements are blurred. In this paper, we propose a generalized deconvolution approach to reconstruct the intrinsic expression pattern, and apply it to P. falciparum IDC microarray data. We develop a statistical model for the decay of synchrony among cells, and reconstruct the expression pattern through statistical inference. The proposed method can handle microarray measurements with noise and missing data. The original gene expression patterns become more apparent in the reconstructed profiles, making it easier to analyze and interpret the data. We hypothesize that reconstructed gene expression patterns represent better temporally resolved expression profiles that can be probabilistically modeled to match changes in expression level to IDC transitions. In particular, we identify transcriptionally regulated protein kinases putatively involved in regulating the P. falciparum IDC. By analyzing publicly available microarray data sets for the P. falciparum IDC, protein kinases are ranked in terms of their likelihood to be involved in regulating transitions between the ring, trophozoite and schizont developmental stages of the P. falciparum IDC. In our theoretical framework, a few protein kinases have high probability rankings, and could potentially be involved in regulating these developmental transitions. This study proposes a new methodology for extracting intrinsic expression patterns from microarray data. By applying this method to P. falciparum microarray data, several protein kinases are predicted to play a significant role in the P. falciparum IDC. Earlier experiments have indeed confirmed that several of these kinases are involved

Microarrays for Undergraduate Classes

ERIC Educational Resources Information Center

Hancock, Dale; Nguyen, Lisa L.; Denyer, Gareth S.; Johnston, Jill M.

2006-01-01

A microarray experiment is presented that, in six laboratory sessions, takes undergraduate students from the tissue sample right through to data analysis. The model chosen, the murine erythroleukemia cell line, can be easily cultured in sufficient quantities for class use. Large changes in gene expression can be induced in these cells by…

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

PubMed

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

2005-01-01

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

A Perspective on DNA Microarrays in Pathology Research and Practice

PubMed Central

Pollack, Jonathan R.

2007-01-01

DNA microarray technology matured in the mid-1990s, and the past decade has witnessed a tremendous growth in its application. DNA microarrays have provided powerful tools for pathology researchers seeking to describe, classify, and understand human disease. There has also been great expectation that the technology would advance the practice of pathology. This review highlights some of the key contributions of DNA microarrays to experimental pathology, focusing in the area of cancer research. Also discussed are some of the current challenges in translating utility to clinical practice. PMID:17600117

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

PubMed

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

2017-05-06

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

DNA microarray-based PCR ribotyping of Clostridium difficile.

PubMed

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.

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

PubMed

Khan, Haseeb Ahmad

2004-01-01

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

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

PubMed Central

2004-01-01

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

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

PubMed

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.

The Importance of Normalization on Large and Heterogeneous Microarray Datasets

EPA Science Inventory

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

Microarray slide hybridization using fluorescently labeled cDNA.

PubMed

Ares, Manuel

2014-01-01

Microarray hybridization is used to determine the amount and genomic origins of RNA molecules in an experimental sample. Unlabeled probe sequences for each gene or gene region are printed in an array on the surface of a slide, and fluorescently labeled cDNA derived from the RNA target is hybridized to it. This protocol describes a blocking and hybridization protocol for microarray slides. The blocking step is particular to the chemistry of "CodeLink" slides, but it serves to remind us that almost every kind of microarray has a treatment step that occurs after printing but before hybridization. We recommend making sure of the precise treatment necessary for the particular chemistry used in the slides to be hybridized because the attachment chemistries differ significantly. Hybridization is similar to northern or Southern blots, but on a much smaller scale.

The effect of column purification on cDNA indirect labelling for microarrays

PubMed Central

Molas, M Lia; Kiss, John Z

2007-01-01

Background The success of the microarray reproducibility is dependent upon the performance of standardized procedures. Since the introduction of microarray technology for the analysis of global gene expression, reproducibility of results among different laboratories has been a major problem. Two of the main contributors to this variability are the use of different microarray platforms and different laboratory practices. In this paper, we address the latter question in terms of how variation in one of the steps of a labelling procedure affects the cDNA product prior to microarray hybridization. Results We used a standard procedure to label cDNA for microarray hybridization and employed different types of column chromatography for cDNA purification. After purifying labelled cDNA, we used the Agilent 2100 Bioanalyzer and agarose gel electrophoresis to assess the quality of the labelled cDNA before its hybridization onto a microarray platform. There were major differences in the cDNA profile (i.e. cDNA fragment lengths and abundance) as a result of using four different columns for purification. In addition, different columns have different efficiencies to remove rRNA contamination. This study indicates that the appropriate column to use in this type of protocol has to be experimentally determined. Finally, we present new evidence establishing the importance of testing the method of purification used during an indirect labelling procedure. Our results confirm the importance of assessing the quality of the sample in the labelling procedure prior to hybridization onto a microarray platform. Conclusion Standardization of column purification systems to be used in labelling procedures will improve the reproducibility of microarray results among different laboratories. In addition, implementation of a quality control check point of the labelled samples prior to microarray hybridization will prevent hybridizing a poor quality sample to expensive micorarrays. PMID:17597522

The effect of column purification on cDNA indirect labelling for microarrays.

PubMed

Molas, M Lia; Kiss, John Z

2007-06-27

The success of the microarray reproducibility is dependent upon the performance of standardized procedures. Since the introduction of microarray technology for the analysis of global gene expression, reproducibility of results among different laboratories has been a major problem. Two of the main contributors to this variability are the use of different microarray platforms and different laboratory practices. In this paper, we address the latter question in terms of how variation in one of the steps of a labelling procedure affects the cDNA product prior to microarray hybridization. We used a standard procedure to label cDNA for microarray hybridization and employed different types of column chromatography for cDNA purification. After purifying labelled cDNA, we used the Agilent 2100 Bioanalyzer and agarose gel electrophoresis to assess the quality of the labelled cDNA before its hybridization onto a microarray platform. There were major differences in the cDNA profile (i.e. cDNA fragment lengths and abundance) as a result of using four different columns for purification. In addition, different columns have different efficiencies to remove rRNA contamination. This study indicates that the appropriate column to use in this type of protocol has to be experimentally determined. Finally, we present new evidence establishing the importance of testing the method of purification used during an indirect labelling procedure. Our results confirm the importance of assessing the quality of the sample in the labelling procedure prior to hybridization onto a microarray platform. Standardization of column purification systems to be used in labelling procedures will improve the reproducibility of microarray results among different laboratories. In addition, implementation of a quality control check point of the labelled samples prior to microarray hybridization will prevent hybridizing a poor quality sample to expensive micorarrays.

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

PubMed

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

2018-03-26

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

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

ERIC Educational Resources Information Center

Grenville-Briggs, Laura J.; Stansfield, Ian

2011-01-01

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

GeneXplorer: an interactive web application for microarray data visualization and analysis.

PubMed

Rees, Christian A; Demeter, Janos; Matese, John C; Botstein, David; Sherlock, Gavin

2004-10-01

When publishing large-scale microarray datasets, it is of great value to create supplemental websites where either the full data, or selected subsets corresponding to figures within the paper, can be browsed. We set out to create a CGI application containing many of the features of some of the existing standalone software for the visualization of clustered microarray data. We present GeneXplorer, a web application for interactive microarray data visualization and analysis in a web environment. GeneXplorer allows users to browse a microarray dataset in an intuitive fashion. It provides simple access to microarray data over the Internet and uses only HTML and JavaScript to display graphic and annotation information. It provides radar and zoom views of the data, allows display of the nearest neighbors to a gene expression vector based on their Pearson correlations and provides the ability to search gene annotation fields. The software is released under the permissive MIT Open Source license, and the complete documentation and the entire source code are freely available for download from CPAN http://search.cpan.org/dist/Microarray-GeneXplorer/.

Workflows for microarray data processing in the Kepler environment.

PubMed

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

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

PubMed

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

2017-01-01

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

Contact printing of protein microarrays.

PubMed

Austin, John; Holway, Antonia H

2011-01-01

A review is provided of contact-printing technologies for the fabrication of planar protein microarrays. The key printing performance parameters for creating protein arrays are reviewed. Solid pin and quill pin technologies are described and their strengths and weaknesses compared.

Customizing microarrays for neuroscience drug discovery.

PubMed

Girgenti, Matthew J; Newton, Samuel S

2007-08-01

Microarray-based gene profiling has become the centerpiece of gene expression studies in the biological sciences. The ability to now interrogate the entire genome using a single chip demonstrates the progress in technology and instrumentation that has been made over the last two decades. Although this unbiased approach provides researchers with an immense quantity of data, obtaining meaningful insight is not possible without intensive data analysis and processing. Custom developed arrays have emerged as a viable and attractive alternative that can take advantage of this robust technology and tailor it to suit the needs and requirements of individual investigations. The ability to simplify data analysis, reduce noise and carefully optimize experimental conditions makes it a suitable tool that can be effectively utilized in neuroscience drug discovery efforts. Furthermore, incorporating recent advancements in fine focusing gene profiling to include specific cellular phenotypes can help resolve the complex cellular heterogeneity of the brain. This review surveys the use of microarray technology in neuroscience paying special attention to customized arrays and their potential in drug discovery. Novel applications of microarrays and ancillary techniques, such as laser microdissection, FAC sorting and RNA amplification, have also been discussed. The notion that a hypothesis-driven approach can be integrated into drug development programs is highlighted.

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

PubMed

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

2011-12-01

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

Metadata management and semantics in microarray repositories.

PubMed

Kocabaş, F; Can, T; Baykal, N

2011-12-01

The number of microarray and other high-throughput experiments on primary repositories keeps increasing as do the size and complexity of the results in response to biomedical investigations. Initiatives have been started on standardization of content, object model, exchange format and ontology. However, there are backlogs and inability to exchange data between microarray repositories, which indicate that there is a great need for a standard format and data management. We have introduced a metadata framework that includes a metadata card and semantic nets that make experimental results visible, understandable and usable. These are encoded in syntax encoding schemes and represented in RDF (Resource Description Frame-word), can be integrated with other metadata cards and semantic nets, and can be exchanged, shared and queried. We demonstrated the performance and potential benefits through a case study on a selected microarray repository. We concluded that the backlogs can be reduced and that exchange of information and asking of knowledge discovery questions can become possible with the use of this metadata framework.

Cross species analysis of microarray expression data

PubMed Central

Lu, Yong; Huggins, Peter; Bar-Joseph, Ziv

2009-01-01

Motivation: Many biological systems operate in a similar manner across a large number of species or conditions. Cross-species analysis of sequence and interaction data is often applied to determine the function of new genes. In contrast to these static measurements, microarrays measure the dynamic, condition-specific response of complex biological systems. The recent exponential growth in microarray expression datasets allows researchers to combine expression experiments from multiple species to identify genes that are not only conserved in sequence but also operated in a similar way in the different species studied. Results: In this review we discuss the computational and technical challenges associated with these studies, the approaches that have been developed to address these challenges and the advantages of cross-species analysis of microarray data. We show how successful application of these methods lead to insights that cannot be obtained when analyzing data from a single species. We also highlight current open problems and discuss possible ways to address them. Contact: zivbj@cs.cmu.edu PMID:19357096

The emergence and diffusion of DNA microarray technology.

PubMed

Lenoir, Tim; Giannella, Eric

2006-08-22

The network model of innovation widely adopted among researchers in the economics of science and technology posits relatively porous boundaries between firms and academic research programs and a bi-directional flow of inventions, personnel, and tacit knowledge between sites of university and industry innovation. Moreover, the model suggests that these bi-directional flows should be considered as mutual stimulation of research and invention in both industry and academe, operating as a positive feedback loop. One side of this bi-directional flow--namely; the flow of inventions into industry through the licensing of university-based technologies--has been well studied; but the reverse phenomenon of the stimulation of university research through the absorption of new directions emanating from industry has yet to be investigated in much detail. We discuss the role of federal funding of academic research in the microarray field, and the multiple pathways through which federally supported development of commercial microarray technologies have transformed core academic research fields. Our study confirms the picture put forward by several scholars that the open character of networked economies is what makes them truly innovative. In an open system innovations emerge from the network. The emergence and diffusion of microarray technologies we have traced here provides an excellent example of an open system of innovation in action. Whether they originated in a startup company environment that operated like a think-tank, such as Affymax, the research labs of a large firm, such as Agilent, or within a research university, the inventors we have followed drew heavily on knowledge resources from all parts of the network in bringing microarray platforms to light. Federal funding for high-tech startups and new industrial development was important at several phases in the early history of microarrays, and federal funding of academic researchers using microarrays was fundamental to

The emergence and diffusion of DNA microarray technology

PubMed Central

Lenoir, Tim; Giannella, Eric

2006-01-01

The network model of innovation widely adopted among researchers in the economics of science and technology posits relatively porous boundaries between firms and academic research programs and a bi-directional flow of inventions, personnel, and tacit knowledge between sites of university and industry innovation. Moreover, the model suggests that these bi-directional flows should be considered as mutual stimulation of research and invention in both industry and academe, operating as a positive feedback loop. One side of this bi-directional flow – namely; the flow of inventions into industry through the licensing of university-based technologies – has been well studied; but the reverse phenomenon of the stimulation of university research through the absorption of new directions emanating from industry has yet to be investigated in much detail. We discuss the role of federal funding of academic research in the microarray field, and the multiple pathways through which federally supported development of commercial microarray technologies have transformed core academic research fields. Our study confirms the picture put forward by several scholars that the open character of networked economies is what makes them truly innovative. In an open system innovations emerge from the network. The emergence and diffusion of microarray technologies we have traced here provides an excellent example of an open system of innovation in action. Whether they originated in a startup company environment that operated like a think-tank, such as Affymax, the research labs of a large firm, such as Agilent, or within a research university, the inventors we have followed drew heavily on knowledge resources from all parts of the network in bringing microarray platforms to light. Federal funding for high-tech startups and new industrial development was important at several phases in the early history of microarrays, and federal funding of academic researchers using microarrays was fundamental

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

PubMed

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

2012-03-01

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

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

PubMed

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

2015-06-01

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

Generation and analyses of human synthetic antibody libraries and their application for protein microarrays.

PubMed

Säll, Anna; Walle, Maria; Wingren, Christer; Müller, Susanne; Nyman, Tomas; Vala, Andrea; Ohlin, Mats; Borrebaeck, Carl A K; Persson, Helena

2016-10-01

Antibody-based proteomics offers distinct advantages in the analysis of complex samples for discovery and validation of biomarkers associated with disease. However, its large-scale implementation requires tools and technologies that allow development of suitable antibody or antibody fragments in a high-throughput manner. To address this we designed and constructed two human synthetic antibody fragment (scFv) libraries denoted HelL-11 and HelL-13. By the use of phage display technology, in total 466 unique scFv antibodies specific for 114 different antigens were generated. The specificities of these antibodies were analyzed in a variety of immunochemical assays and a subset was further evaluated for functionality in protein microarray applications. This high-throughput approach demonstrates the ability to rapidly generate a wealth of reagents not only for proteome research, but potentially also for diagnostics and therapeutics. In addition, this work provides a great example on how a synthetic approach can be used to optimize library designs. By having precise control of the diversity introduced into the antigen-binding sites, synthetic libraries offer increased understanding of how different diversity contributes to antibody binding reactivity and stability, thereby providing the key to future library optimization. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

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

PubMed

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

2015-06-25

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

MAPPI-DAT: data management and analysis for protein-protein interaction data from the high-throughput MAPPIT cell microarray platform.

PubMed

Gupta, Surya; De Puysseleyr, Veronic; Van der Heyden, José; Maddelein, Davy; Lemmens, Irma; Lievens, Sam; Degroeve, Sven; Tavernier, Jan; Martens, Lennart

2017-05-01

Protein-protein interaction (PPI) studies have dramatically expanded our knowledge about cellular behaviour and development in different conditions. A multitude of high-throughput PPI techniques have been developed to achieve proteome-scale coverage for PPI studies, including the microarray based Mammalian Protein-Protein Interaction Trap (MAPPIT) system. Because such high-throughput techniques typically report thousands of interactions, managing and analysing the large amounts of acquired data is a challenge. We have therefore built the MAPPIT cell microArray Protein Protein Interaction-Data management & Analysis Tool (MAPPI-DAT) as an automated data management and analysis tool for MAPPIT cell microarray experiments. MAPPI-DAT stores the experimental data and metadata in a systematic and structured way, automates data analysis and interpretation, and enables the meta-analysis of MAPPIT cell microarray data across all stored experiments. MAPPI-DAT is developed in Python, using R for data analysis and MySQL as data management system. MAPPI-DAT is cross-platform and can be ran on Microsoft Windows, Linux and OS X/macOS. The source code and a Microsoft Windows executable are freely available under the permissive Apache2 open source license at https://github.com/compomics/MAPPI-DAT. jan.tavernier@vib-ugent.be or lennart.martens@vib-ugent.be. Supplementary data are available at Bioinformatics online. © The Author 2017. Published by Oxford University Press.

A Customized DNA Microarray for Microbial Source Tracking ...

EPA Pesticide Factsheets

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

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

PubMed

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.

The application of artificial intelligence to microarray data: identification of a novel gene signature to identify bladder cancer progression.

PubMed

Catto, James W F; Abbod, Maysam F; Wild, Peter J; Linkens, Derek A; Pilarsky, Christian; Rehman, Ishtiaq; Rosario, Derek J; Denzinger, Stefan; Burger, Maximilian; Stoehr, Robert; Knuechel, Ruth; Hartmann, Arndt; Hamdy, Freddie C

2010-03-01

New methods for identifying bladder cancer (BCa) progression are required. Gene expression microarrays can reveal insights into disease biology and identify novel biomarkers. However, these experiments produce large datasets that are difficult to interpret. To develop a novel method of microarray analysis combining two forms of artificial intelligence (AI): neurofuzzy modelling (NFM) and artificial neural networks (ANN) and validate it in a BCa cohort. We used AI and statistical analyses to identify progression-related genes in a microarray dataset (n=66 tumours, n=2800 genes). The AI-selected genes were then investigated in a second cohort (n=262 tumours) using immunohistochemistry. We compared the accuracy of AI and statistical approaches to identify tumour progression. AI identified 11 progression-associated genes (odds ratio [OR]: 0.70; 95% confidence interval [CI], 0.56-0.87; p=0.0004), and these were more discriminate than genes chosen using statistical analyses (OR: 1.24; 95% CI, 0.96-1.60; p=0.09). The expression of six AI-selected genes (LIG3, FAS, KRT18, ICAM1, DSG2, and BRCA2) was determined using commercial antibodies and successfully identified tumour progression (concordance index: 0.66; log-rank test: p=0.01). AI-selected genes were more discriminate than pathologic criteria at determining progression (Cox multivariate analysis: p=0.01). Limitations include the use of statistical correlation to identify 200 genes for AI analysis and that we did not compare regression identified genes with immunohistochemistry. AI and statistical analyses use different techniques of inference to determine gene-phenotype associations and identify distinct prognostic gene signatures that are equally valid. We have identified a prognostic gene signature whose members reflect a variety of carcinogenic pathways that could identify progression in non-muscle-invasive BCa. 2009 European Association of Urology. Published by Elsevier B.V. All rights reserved.

MADGE: scalable distributed data management software for cDNA microarrays.

PubMed

McIndoe, Richard A; Lanzen, Aaron; Hurtz, Kimberly

2003-01-01

The human genome project and the development of new high-throughput technologies have created unparalleled opportunities to study the mechanism of diseases, monitor the disease progression and evaluate effective therapies. Gene expression profiling is a critical tool to accomplish these goals. The use of nucleic acid microarrays to assess the gene expression of thousands of genes simultaneously has seen phenomenal growth over the past five years. Although commercial sources of microarrays exist, investigators wanting more flexibility in the genes represented on the array will turn to in-house production. The creation and use of cDNA microarrays is a complicated process that generates an enormous amount of information. Effective data management of this information is essential to efficiently access, analyze, troubleshoot and evaluate the microarray experiments. We have developed a distributable software package designed to track and store the various pieces of data generated by a cDNA microarray facility. This includes the clone collection storage data, annotation data, workflow queues, microarray data, data repositories, sample submission information, and project/investigator information. This application was designed using a 3-tier client server model. The data access layer (1st tier) contains the relational database system tuned to support a large number of transactions. The data services layer (2nd tier) is a distributed COM server with full database transaction support. The application layer (3rd tier) is an internet based user interface that contains both client and server side code for dynamic interactions with the user. This software is freely available to academic institutions and non-profit organizations at http://www.genomics.mcg.edu/niddkbtc.

Recommendations for the use of microarrays in prenatal diagnosis.

PubMed

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.

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

EPA Science Inventory

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

Reverse phase protein microarrays: fluorometric and colorimetric detection.

PubMed

Gallagher, Rosa I; Silvestri, Alessandra; Petricoin, Emanuel F; Liotta, Lance A; Espina, Virginia

2011-01-01

The Reverse Phase Protein Microarray (RPMA) is an array platform used to quantitate proteins and their posttranslationally modified forms. RPMAs are applicable for profiling key cellular signaling pathways and protein networks, allowing direct comparison of the activation state of proteins from multiple samples within the same array. The RPMA format consists of proteins immobilized directly on a nitrocellulose substratum. The analyte is subsequently probed with a primary antibody and a series of reagents for signal amplification and detection. Due to the diversity, low concentration, and large dynamic range of protein analytes, RPMAs require stringent signal amplification methods, high quality image acquisition, and software capable of precisely analyzing spot intensities on an array. Microarray detection strategies can be either fluorescent or colorimetric. The choice of a detection system depends on (a) the expected analyte concentration, (b) type of microarray imaging system, and (c) type of sample. The focus of this chapter is to describe RPMA detection and imaging using fluorescent and colorimetric (diaminobenzidine (DAB)) methods.

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

PubMed Central

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

Cytokine gene polymorphisms in Italian preterm infants: association between interleukin-10 -1082 G/A polymorphism and respiratory distress syndrome.

PubMed

Capasso, Mario; Avvisati, Rosa Anna; Piscopo, Carmelo; Laforgia, Nicola; Raimondi, Francesco; de Angelis, Filomena; Iolascon, Achille

2007-03-01

In this study, we determined the genotype frequencies of polymorphisms of cytokine genes and investigated their association with the risk of respiratory distress syndrome (RDS) in preterm infants. Genetic polymorphisms in the cytokines interleukin (IL)-10, IL-8, and tumor necrosis factor (TNF) alpha, were studied in 342 white Italian newborns (112 without RDS, 66 prematurely born with RDS, and 164 infants born at term who were included as healthy controls). The polymorphisms were analyzed by polymerase chain reaction (PCR) restriction fragment length polymorphism (RFLP). The IL-10 mRNA levels were analyzed according to genotype by quantitative real-time PCR (QRT-PCR) in Epstein-Barr virus-transformed lymphoblastoid cell lines (EBV-LCLs) of 42 full-term healthy infants. Logistic regression analysis demonstrated the risk of RDS to be significantly lower in preterm infants with an IL-10 -1082 GG/GA genotype than in those with an AA genotype [odds ratio (OR) = 0.48, 95% confidence interval (CI): 0.24-0.95, p = 0.03]. QRT-PCR analyses showed that the IL-10 mRNA levels were significantly higher in 27 IL-10 -1082 GG/GA carriers compared with 15 IL-10 -1082 AA carriers (p = 0.03). We conclude that the IL-10 -1082 GG/GA polymorphism may have a role in RDS development in premature infants.

CEM-designer: design of custom expression microarrays in the post-ENCODE Era.

PubMed

Arnold, Christian; Externbrink, Fabian; Hackermüller, Jörg; Reiche, Kristin

2014-11-10

Microarrays are widely used in gene expression studies, and custom expression microarrays are popular to monitor expression changes of a customer-defined set of genes. However, the complexity of transcriptomes uncovered recently make custom expression microarray design a non-trivial task. Pervasive transcription and alternative processing of transcripts generate a wealth of interweaved transcripts that requires well-considered probe design strategies and is largely neglected in existing approaches. We developed the web server CEM-Designer that facilitates microarray platform independent design of custom expression microarrays for complex transcriptomes. CEM-Designer covers (i) the collection and generation of a set of unique target sequences from different sources and (ii) the selection of a set of sensitive and specific probes that optimally represents the target sequences. Probe design itself is left to third party software to ensure that probes meet provider-specific constraints. CEM-Designer is available at http://designpipeline.bioinf.uni-leipzig.de. Copyright © 2014 Elsevier B.V. All rights reserved.

DNA Microarray for Detection of Gastrointestinal Viruses

PubMed Central

Martínez, Miguel A.; Soto-del Río, María de los Dolores; Gutiérrez, Rosa María; Chiu, Charles Y.; Greninger, Alexander L.; Contreras, Juan Francisco; López, Susana; Arias, Carlos F.

2014-01-01

Gastroenteritis is a clinical illness of humans and other animals that is characterized by vomiting and diarrhea and caused by a variety of pathogens, including viruses. An increasing number of viral species have been associated with gastroenteritis or have been found in stool samples as new molecular tools have been developed. In this work, a DNA microarray capable in theory of parallel detection of more than 100 viral species was developed and tested. Initial validation was done with 10 different virus species, and an additional 5 species were validated using clinical samples. Detection limits of 1 × 103 virus particles of Human adenovirus C (HAdV), Human astrovirus (HAstV), and group A Rotavirus (RV-A) were established. Furthermore, when exogenous RNA was added, the limit for RV-A detection decreased by one log. In a small group of clinical samples from children with gastroenteritis (n = 76), the microarray detected at least one viral species in 92% of the samples. Single infection was identified in 63 samples (83%), and coinfection with more than one virus was identified in 7 samples (9%). The most abundant virus species were RV-A (58%), followed by Anellovirus (15.8%), HAstV (6.6%), HAdV (5.3%), Norwalk virus (6.6%), Human enterovirus (HEV) (9.2%), Human parechovirus (1.3%), Sapporo virus (1.3%), and Human bocavirus (1.3%). To further test the specificity and sensitivity of the microarray, the results were verified by reverse transcription-PCR (RT-PCR) detection of 5 gastrointestinal viruses. The RT-PCR assay detected a virus in 59 samples (78%). The microarray showed good performance for detection of RV-A, HAstV, and calicivirus, while the sensitivity for HAdV and HEV was low. Furthermore, some discrepancies in detection of mixed infections were observed and were addressed by reverse transcription-quantitative PCR (RT-qPCR) of the viruses involved. It was observed that differences in the amount of genetic material favored the detection of the most abundant

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

PubMed

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

A New Distribution Family for Microarray Data.

PubMed

Kelmansky, Diana Mabel; Ricci, Lila

2017-02-10

The traditional approach with microarray data has been to apply transformations that approximately normalize them, with the drawback of losing the original scale. The alternative stand point taken here is to search for models that fit the data, characterized by the presence of negative values, preserving their scale; one advantage of this strategy is that it facilitates a direct interpretation of the results. A new family of distributions named gpower-normal indexed by p∈R is introduced and it is proven that these variables become normal or truncated normal when a suitable gpower transformation is applied. Expressions are given for moments and quantiles, in terms of the truncated normal density. This new family can be used to model asymmetric data that include non-positive values, as required for microarray analysis. Moreover, it has been proven that the gpower-normal family is a special case of pseudo-dispersion models, inheriting all the good properties of these models, such as asymptotic normality for small variances. A combined maximum likelihood method is proposed to estimate the model parameters, and it is applied to microarray and contamination data. Rcodes are available from the authors upon request.

Geiger mode avalanche photodiodes for microarray systems

NASA Astrophysics Data System (ADS)

Phelan, Don; Jackson, Carl; Redfern, R. Michael; Morrison, Alan P.; Mathewson, Alan

2002-06-01

New Geiger Mode Avalanche Photodiodes (GM-APD) have been designed and characterized specifically for use in microarray systems. Critical parameters such as excess reverse bias voltage, hold-off time and optimum operating temperature have been experimentally determined for these photon-counting devices. The photon detection probability, dark count rate and afterpulsing probability have been measured under different operating conditions. An active- quench circuit (AQC) is presented for operating these GM- APDs. This circuit is relatively simple, robust and has such benefits as reducing average power dissipation and afterpulsing. Arrays of these GM-APDs have already been designed and together with AQCs open up the possibility of having a solid-state microarray detector that enables parallel analysis on a single chip. Another advantage of these GM-APDs over current technology is their low voltage CMOS compatibility which could allow for the fabrication of an AQC on the same device. Small are detectors have already been employed in the time-resolved detection of fluorescence from labeled proteins. It is envisaged that operating these new GM-APDs with this active-quench circuit will have numerous applications for the detection of fluorescence in microarray systems.

Support vector machine and principal component analysis for microarray data classification

NASA Astrophysics Data System (ADS)

Astuti, Widi; Adiwijaya

2018-03-01

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

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

PubMed Central

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

2017-01-01

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

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

PubMed Central

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

2008-01-01

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

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

PubMed Central

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

2007-01-01

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

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

PubMed

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.

Supervised normalization of microarrays

PubMed Central

Mecham, Brigham H.; Nelson, Peter S.; Storey, John D.

2010-01-01

Motivation: A major challenge in utilizing microarray technologies to measure nucleic acid abundances is ‘normalization’, the goal of which is to separate biologically meaningful signal from other confounding sources of signal, often due to unavoidable technical factors. It is intuitively clear that true biological signal and confounding factors need to be simultaneously considered when performing normalization. However, the most popular normalization approaches do not utilize what is known about the study, both in terms of the biological variables of interest and the known technical factors in the study, such as batch or array processing date. Results: We show here that failing to include all study-specific biological and technical variables when performing normalization leads to biased downstream analyses. We propose a general normalization framework that fits a study-specific model employing every known variable that is relevant to the expression study. The proposed method is generally applicable to the full range of existing probe designs, as well as to both single-channel and dual-channel arrays. We show through real and simulated examples that the method has favorable operating characteristics in comparison to some of the most highly used normalization methods. Availability: An R package called snm implementing the methodology will be made available from Bioconductor (http://bioconductor.org). Contact: jstorey@princeton.edu Supplementary information: Supplementary data are available at Bioinformatics online. PMID:20363728

[Application of single nucleotide polymorphism-microarray and target gene sequencing in the study of genetic etiology of children with unexplained intellectual disability or developmental delay].

PubMed

Gao, Z J; Jiang, Q; Cheng, D Z; Yan, X X; Chen, Q; Xu, K M

2016-10-02

Objective: To evaluate the application of single nucleotide polymorphism (SNP)-microarray and target gene sequencing technology in the clinical molecular genetic diagnosis of unexplained intellectual disability(ID) or developmental delay (DD). Method: Patients with ID or DD were recruited in the Department of Neurology, Affiliated Children's Hospital of Capital Institute of Pediatrics between September 2015 and February 2016. The intellectual assessment of the patients was performed using 0-6-year-old pediatric examination table of neuropsychological development or Wechsler intelligence scale (>6 years). Patients with a DQ less than 49 or IQ less than 51 were included in this study. The patients were scanned by SNP-array for detection of genomic copy number variations (CNV), and the revealed genomic imbalance was confirmed by quantitative real time-PCR. Candidate gene mutation screening was carried out by target gene sequencing technology.Causal mutations or likely pathogenic variants were verified by polymerase chain reaction and direct sequencing. Result: There were 15 children with ID or DD enrolled, 9 males and 6 females. The age of these patients was 7 months-16 years and 9 months. SNP-array revealed that two of the 15 patients had genomic CNV. Both CNV were de novo micro deletions, one involved 11q24.1q25 and the other micro deletion located on 21q22.2q22.3. Both micro deletions were proved to have a clinical significance due to their association with ID, brain DD, unusual faces etc. by querying Decipher database. Thirteen patients with negative findings in SNP-array were consequently examined with target gene sequencing technology, genotype-phenotype correlation analysis and genetic analysis. Five patients were diagnosed with monogenic disorder, two were diagnosed with suspected genetic disorder and six were still negative. Conclusion: Sequential use of SNP-array and target gene sequencing technology can significantly increase the molecular genetic etiologic

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

PubMed

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.

Contrasting patterns of X/Y polymorphism distinguish Carica papaya from other sex chromosome systems.

PubMed

Weingartner, Laura A; Moore, Richard C

2012-12-01

The sex chromosomes of the tropical crop papaya (Carica papaya) are evolutionarily young and consequently allow for the examination of evolutionary mechanisms that drive early sex chromosome divergence. We conducted a molecular population genetic analysis of four X/Y gene pairs from a collection of 45 wild papaya accessions. These population genetic analyses reveal striking differences in the patterns of polymorphism between the X and Y chromosomes that distinguish them from other sex chromosome systems. In most sex chromosome systems, the Y chromosome displays significantly reduced polymorphism levels, whereas the X chromosome maintains a level of polymorphism that is comparable to autosomal loci. However, the four papaya sex-linked loci that we examined display diversity patterns that are opposite this trend: the papaya X alleles exhibit significantly reduced polymorphism levels, whereas the papaya Y alleles maintain greater than expected levels of diversity. Our analyses suggest that selective sweeps in the regions of the X have contributed to this pattern while also revealing geographically restricted haplogroups on the Y. We discuss the possible role sexual selection and/or genomic conflict have played in shaping the contrasting patterns of polymorphism found for the papaya X and Y chromosomes.

Polysaccharide Microarray Technology for the Detection of Burkholderia Pseudomallei and Burkholderia Mallei Antibodies

DTIC Science & Technology

2006-04-27

polysaccharide microarray platform was prepared by immobilizing Burkholderia pseudomallei and Burkholderia mallei polysaccharides . This... polysaccharide array was tested with success for detecting B. pseudomallei and B. mallei serum (human and animal) antibodies. The advantages of this microarray... Polysaccharide microarrays; Burkholderia pseudomallei; Burkholderia mallei; Glanders; Melioidosis1. Introduction There has been a great deal of emphasis on the

Digital Microarrays: Single-Molecule Readout with Interferometric Detection of Plasmonic Nanorod Labels.

PubMed

Sevenler, Derin; Daaboul, George G; Ekiz Kanik, Fulya; Ünlü, Neşe Lortlar; Ünlü, M Selim

2018-05-21

DNA and protein microarrays are a high-throughput technology that allow the simultaneous quantification of tens of thousands of different biomolecular species. The mediocre sensitivity and limited dynamic range of traditional fluorescence microarrays compared to other detection techniques have been the technology's Achilles' heel and prevented their adoption for many biomedical and clinical diagnostic applications. Previous work to enhance the sensitivity of microarray readout to the single-molecule ("digital") regime have either required signal amplifying chemistry or sacrificed throughput, nixing the platform's primary advantages. Here, we report the development of a digital microarray which extends both the sensitivity and dynamic range of microarrays by about 3 orders of magnitude. This technique uses functionalized gold nanorods as single-molecule labels and an interferometric scanner which can rapidly enumerate individual nanorods by imaging them with a 10× objective lens. This approach does not require any chemical signal enhancement such as silver deposition and scans arrays with a throughput similar to commercial fluorescence scanners. By combining single-nanoparticle enumeration and ensemble measurements of spots when the particles are very dense, this system achieves a dynamic range of about 6 orders of magnitude directly from a single scan. As a proof-of-concept digital protein microarray assay, we demonstrated detection of hepatitis B virus surface antigen in buffer with a limit of detection of 3.2 pg/mL. More broadly, the technique's simplicity and high-throughput nature make digital microarrays a flexible platform technology with a wide range of potential applications in biomedical research and clinical diagnostics.

Curation of microarray oligonucleotides and corresponding ESTs/cDNAs used for gene expression analysis in zebra finches.

PubMed

Lovell, Peter V; Huizinga, Nicole A; Getachew, Abel; Mees, Brianna; Friedrich, Samantha R; Wirthlin, Morgan; Mello, Claudio V

2018-05-18

Zebra finches are a major model organism for investigating mechanisms of vocal learning, a trait that enables spoken language in humans. The development of cDNA collections with expressed sequence tags (ESTs) and microarrays has allowed for extensive molecular characterizations of circuitry underlying vocal learning and production. However, poor database curation can lead to errors in transcriptome and bioinformatics analyses, limiting the impact of these resources. Here we used genomic alignments and synteny analysis for orthology verification to curate and reannotate ~ 35% of the oligonucleotides and corresponding ESTs/cDNAs that make-up Agilent microarrays for gene expression analysis in finches. We found that: (1) 5475 out of 43,084 oligos (a) failed to align to the zebra finch genome, (b) aligned to multiple loci, or (c) aligned to Chr_un only, and thus need to be flagged until a better genome assembly is available, or (d) reflect cloning artifacts; (2) Out of 9635 valid oligos examined further, 3120 were incorrectly named, including 1533 with no known orthologs; and (3) 2635 oligos required name update. The resulting curated dataset provides a reference for correcting gene identification errors in previous finch microarrays studies, and avoiding such errors in future studies.

Improved microarray methods for profiling the yeast knockout strain collection

PubMed Central

Yuan, Daniel S.; Pan, Xuewen; Ooi, Siew Loon; Peyser, Brian D.; Spencer, Forrest A.; Irizarry, Rafael A.; Boeke, Jef D.

2005-01-01

A remarkable feature of the Yeast Knockout strain collection is the presence of two unique 20mer TAG sequences in almost every strain. In principle, the relative abundances of strains in a complex mixture can be profiled swiftly and quantitatively by amplifying these sequences and hybridizing them to microarrays, but TAG microarrays have not been widely used. Here, we introduce a TAG microarray design with sophisticated controls and describe a robust method for hybridizing high concentrations of dye-labeled TAGs in single-stranded form. We also highlight the importance of avoiding PCR contamination and provide procedures for detection and eradication. Validation experiments using these methods yielded false positive (FP) and false negative (FN) rates for individual TAG detection of 3–6% and 15–18%, respectively. Analysis demonstrated that cross-hybridization was the chief source of FPs, while TAG amplification defects were the main cause of FNs. The materials, protocols, data and associated software described here comprise a suite of experimental resources that should facilitate the use of TAG microarrays for a wide variety of genetic screens. PMID:15994458

Cruella: developing a scalable tissue microarray data management system.

PubMed

Cowan, James D; Rimm, David L; Tuck, David P

2006-06-01

Compared with DNA microarray technology, relatively little information is available concerning the special requirements, design influences, and implementation strategies of data systems for tissue microarray technology. These issues include the requirement to accommodate new and different data elements for each new project as well as the need to interact with pre-existing models for clinical, biological, and specimen-related data. To design and implement a flexible, scalable tissue microarray data storage and management system that could accommodate information regarding different disease types and different clinical investigators, and different clinical investigation questions, all of which could potentially contribute unforeseen data types that require dynamic integration with existing data. The unpredictability of the data elements combined with the novelty of automated analysis algorithms and controlled vocabulary standards in this area require flexible designs and practical decisions. Our design includes a custom Java-based persistence layer to mediate and facilitate interaction with an object-relational database model and a novel database schema. User interaction is provided through a Java Servlet-based Web interface. Cruella has become an indispensable resource and is used by dozens of researchers every day. The system stores millions of experimental values covering more than 300 biological markers and more than 30 disease types. The experimental data are merged with clinical data that has been aggregated from multiple sources and is available to the researchers for management, analysis, and export. Cruella addresses many of the special considerations for managing tissue microarray experimental data and the associated clinical information. A metadata-driven approach provides a practical solution to many of the unique issues inherent in tissue microarray research, and allows relatively straightforward interoperability with and accommodation of new data models.

Emergent FDA biodefense issues for microarray technology: process analytical technology.

PubMed

Weinberg, Sandy

2004-11-01

A successful biodefense strategy relies upon any combination of four approaches. A nation can protect its troops and citizenry first by advanced mass vaccination, second, by responsive ring vaccination, and third, by post-exposure therapeutic treatment (including vaccine therapies). Finally, protection can be achieved by rapid detection followed by exposure limitation (suites and air filters) or immediate treatment (e.g., antibiotics, rapid vaccines and iodine pills). All of these strategies rely upon or are enhanced by microarray technologies. Microarrays can be used to screen, engineer and test vaccines. They are also used to construct early detection tools. While effective biodefense utilizes a variety of tactical tools, microarray technology is a valuable arrow in that quiver.

Implementation of GenePattern within the Stanford Microarray Database.

PubMed

Hubble, Jeremy; Demeter, Janos; Jin, Heng; Mao, Maria; Nitzberg, Michael; Reddy, T B K; Wymore, Farrell; Zachariah, Zachariah K; Sherlock, Gavin; Ball, Catherine A

2009-01-01

Hundreds of researchers across the world use the Stanford Microarray Database (SMD; http://smd.stanford.edu/) to store, annotate, view, analyze and share microarray data. In addition to providing registered users at Stanford access to their own data, SMD also provides access to public data, and tools with which to analyze those data, to any public user anywhere in the world. Previously, the addition of new microarray data analysis tools to SMD has been limited by available engineering resources, and in addition, the existing suite of tools did not provide a simple way to design, execute and share analysis pipelines, or to document such pipelines for the purposes of publication. To address this, we have incorporated the GenePattern software package directly into SMD, providing access to many new analysis tools, as well as a plug-in architecture that allows users to directly integrate and share additional tools through SMD. In this article, we describe our implementation of the GenePattern microarray analysis software package into the SMD code base. This extension is available with the SMD source code that is fully and freely available to others under an Open Source license, enabling other groups to create a local installation of SMD with an enriched data analysis capability.

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

PubMed

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

2014-01-01

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

Analyses of amplified fragment length polymorphisms (AFLP) indicate rapid radiation of Diospyros species (Ebenaceae) endemic to New Caledonia

PubMed Central

2013-01-01

Background Radiation in some plant groups has occurred on islands and due to the characteristic rapid pace of phenotypic evolution, standard molecular markers often provide insufficient variation for phylogenetic reconstruction. To resolve relationships within a clade of 21 closely related New Caledonian Diospyros species and evaluate species boundaries we analysed genome-wide DNA variation via amplified fragment length polymorphisms (AFLP). Results A neighbour-joining (NJ) dendrogram based on Dice distances shows all species except D. minimifolia, D. parviflora and D. vieillardii to form unique clusters of genetically similar accessions. However, there was little variation between these species clusters, resulting in unresolved species relationships and a star-like general NJ topology. Correspondingly, analyses of molecular variance showed more variation within species than between them. A Bayesian analysis with BEAST produced a similar result. Another Bayesian method, this time a clustering method, Structure, demonstrated the presence of two groups, highly congruent with those observed in a principal coordinate analysis (PCO). Molecular divergence between the two groups is low and does not correspond to any hypothesised taxonomic, ecological or geographical patterns. Conclusions We hypothesise that such a pattern could have been produced by rapid and complex evolution involving a widespread progenitor for which an initial split into two groups was followed by subsequent fragmentation into many diverging populations, which was followed by range expansion of then divergent entities. Overall, this process resulted in an opportunistic pattern of phenotypic diversification. The time since divergence was probably insufficient for some species to become genetically well-differentiated, resulting in progenitor/derivative relationships being exhibited in a few cases. In other cases, our analyses may have revealed evidence for the existence of cryptic species, for which

Polymorphs and polymorphic cocrystals of temozolomide.

PubMed

Babu, N Jagadeesh; Reddy, L Sreenivas; Aitipamula, Srinivasulu; Nangia, Ashwini

2008-07-07

Crystal polymorphism in the antitumor drug temozolomide (TMZ), cocrystals of TMZ with 4,4'-bipyridine-N,N'-dioxide (BPNO), and solid-state stability were studied. Apart from a known X-ray crystal structure of TMZ (form 1), two new crystalline modifications, forms 2 and 3, were obtained during attempted cocrystallization with carbamazepine and 3-hydroxypyridine-N-oxide. Conformers A and B of the drug molecule are stabilized by intramolecular amide N--HN(imidazole) and N--HN(tetrazine) interactions. The stable conformer A is present in forms 1 and 2, whereas both conformers crystallized in form 3. Preparation of polymorphic cocrystals I and II (TMZBPNO 1:0.5 and 2:1) were optimized by using solution crystallization and grinding methods. The metastable nature of polymorph 2 and cocrystal II is ascribed to unused hydrogen-bond donors/acceptors in the crystal structure. The intramolecularly bonded amide N-H donor in the less stable structure makes additional intermolecular bonds with the tetrazine C==O group and the imidazole N atom in stable polymorph 1 and cocrystal I, respectively. All available hydrogen-bond donors and acceptors are used to make intermolecular hydrogen bonds in the stable crystalline form. Synthon polymorphism and crystal stability are discussed in terms of hydrogen-bond reorganization.

Sandwich ELISA Microarrays: Generating Reliable and Reproducible Assays for High-Throughput Screens

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

Gonzalez, Rachel M.; Varnum, Susan M.; Zangar, Richard C.

The sandwich ELISA microarray is a powerful screening tool in biomarker discovery and validation due to its ability to simultaneously probe for multiple proteins in a miniaturized assay. The technical challenges of generating and processing the arrays are numerous. However, careful attention to possible pitfalls in the development of your antibody microarray assay can overcome these challenges. In this chapter, we describe in detail the steps that are involved in generating a reliable and reproducible sandwich ELISA microarray assay.

High-Throughput Nano-Biofilm Microarray for Antifungal Drug Discovery

DTIC Science & Technology

2013-06-25

High-Throughput Nano-Biofilm Microarray for Antifungal Drug Discovery Anand Srinivasan,a, c Kai P. Leung,d Jose L. Lopez-Ribot,b, c Anand K...Ramasubramaniana, c Departments of Biomedical Engineeringa and Biologyb and South Texas Center for Emerging Infectious Diseases, c The University of Texas at San...of the opportunistic fungal pathogen Candida albicans on a microarray platform. The mi- croarray consists of 1,200 individual cultures of 30 nl of C

[Association of XRCC1 genetic polymorphism with susceptibility to non-Hodgkin's lymphoma].

PubMed

Li, Su-Xia; Zhu, Hong-Li; Guo, Bo; Yang, Yang; Wang, Hong-Yan; Sun, Jing-Fen; Cao, Yong-Bin

2014-08-01

The purpose of this study was to explore the association between X-ray repair cross-complementing group 1 (XRCC1)gene polymorphism and non-Hodgkin's lymphoma risk. A total of 282 non-Hodgkin's lymphoma (NHL) patients and 231 normal controls were used to investigate the effect of three XRCC1 gene polymorphisms (rs25487, rs25489, rs1799782) on susceptibility to non-Hodgkin's lymphoma. Genotyping was performed by using SNaPshot method. All statistical analyses were done with R software. Genotype and allele frequencies of XRCC1 were compared between the patients and controls by using the chi-square test. Crude and adjusted odd ratios and 95% confidence intervals were calculated by using logistic regression on the basis of genetic different models. For four kinds of NHL, subgroup analyses were also conducted. Combined genotype analyses of the three XRCC1 polymorphisms were also done by using logistic regression. The results showed that the variant genotype frequency was not significantly different between the controls and NHL or NHL subtype cases. Combined genotype analyses of XRCC1 399-280-194 results showed that the combined genotype was not associated with risk of NHL overall, but the VT-WT-WT combined genotype was associated with the decreased risk of T-NHL (OR: 0.21; 95%CI (0.06-0.8); P = 0.022), and the WT-VT-WT combined genotype was associated with the increased risk of FL(OR:15.23; 95%CI (1.69-137.39); P = 0.015). It is concluded that any studied polymorphism (rs25487, rs25489, rs1799782) alone was not shown to be rela-ted with the risk of NHL or each histologic subtype of NHL. The combined genotype with mutation of three SNP of XRCC1 was not related to the risk of NHL. However, further large-scale studies would be needed to confirm the association of decreased or increased risk for T-NHL and FL with the risk 3 combined SNP mutants of XRCC1 polymorphism.

Protein Microarray Analysis in Patients With Asthma*

PubMed Central

Kim, Hyo-Bin; Kim, Chang-Keun; Iijima, Koji; Kobayashi, Takao; Kita, Hirohito

2010-01-01

Background Microarray technology offers a new opportunity to gain insight into global gene and protein expression profiles in asthma. To identify novel factors produced in the asthmatic airway, we analyzed sputum samples by using a membrane-based human cytokine microarray technology in patients with bronchial asthma (BA). Methods Induced sputum was obtained from 28 BA subjects, 20 nonasthmatic atopic control (AC) subjects, and 38 nonasthmatic nonatopic normal control (NC) subjects. The microarray samples of subjects were randomly selected from nine BA subjects, three AC subjects, and six NC subjects. Sputum supernatants were analyzed using a custom human cytokine array (RayBio Custom Human Cytokine Array; RayBiotech; Norcross, GA) designed to analyze 79 specific cytokines simultaneously. The levels of growth-regulated oncogene (GRO)-α, eotaxin-2, and pulmonary and activation-regulated chemokine (PARC)/CCL18 were measured by sandwich enzyme-linked immunosorbent assays (ELISAs), and eosinophil-derived neurotoxin (EDN) was measured by radioimmunoassay. Results By microarray, the signal intensities for GRO-α, eotaxin-2, and PARC were significantly higher in BA subjects than in AC and NC subjects (p = 0.036, p = 0.042, and p = 0.033, respectively). By ELISA, the sputum PARC protein levels were significantly higher in BA subjects than in AC and NC subjects (p < 0.0001). Furthermore, PARC levels correlated significantly with sputum eosinophil percentages (r = 0.570, p < 0.0001) and the levels of EDN(r = 0.633, p < 0.0001), the regulated upon activation, normal T cell expressed and secreted cytokine (r = 0.440, p < 0.001), interleukin-4 (r = 0.415, p < 0.01), and interferon-γ (r = 0.491, p < 0.001). Conclusions By a nonbiased screening approach, a chemokine, PARC, is elevated in sputum specimens from patients with asthma. PARC may play important roles in development of airway eosinophilic inflammation in asthma. PMID:19017877

Fuzzy support vector machine: an efficient rule-based classification technique for microarrays.

PubMed

Hajiloo, Mohsen; Rabiee, Hamid R; Anooshahpour, Mahdi

2013-01-01

The abundance of gene expression microarray data has led to the development of machine learning algorithms applicable for tackling disease diagnosis, disease prognosis, and treatment selection problems. However, these algorithms often produce classifiers with weaknesses in terms of accuracy, robustness, and interpretability. This paper introduces fuzzy support vector machine which is a learning algorithm based on combination of fuzzy classifiers and kernel machines for microarray classification. Experimental results on public leukemia, prostate, and colon cancer datasets show that fuzzy support vector machine applied in combination with filter or wrapper feature selection methods develops a robust model with higher accuracy than the conventional microarray classification models such as support vector machine, artificial neural network, decision trees, k nearest neighbors, and diagonal linear discriminant analysis. Furthermore, the interpretable rule-base inferred from fuzzy support vector machine helps extracting biological knowledge from microarray data. Fuzzy support vector machine as a new classification model with high generalization power, robustness, and good interpretability seems to be a promising tool for gene expression microarray classification.

Fluorescent microarray for multiplexed quantification of environmental contaminants in seawater samples

USDA-ARS?s Scientific Manuscript database

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...

Issues in the analysis of oligonucleotide tiling microarrays for transcript mapping

NASA Technical Reports Server (NTRS)

Royce, Thomas E.; Rozowsky, Joel S.; Bertone, Paul; Samanta, Manoj; Stolc, Viktor; Weissman, Sherman; Snyder, Michael; Gerstein, Mark

2005-01-01

Traditional microarrays use probes complementary to known genes to quantitate the differential gene expression between two or more conditions. Genomic tiling microarray experiments differ in that probes that span a genomic region at regular intervals are used to detect the presence or absence of transcription. This difference means the same sets of biases and the methods for addressing them are unlikely to be relevant to both types of experiment. We introduce the informatics challenges arising in the analysis of tiling microarray experiments as open problems to the scientific community and present initial approaches for the analysis of this nascent technology.

Dopamine D4 receptor gene polymorphism and personality traits in healthy volunteers.

PubMed

Persson, M L; Wasserman, D; Geijer, T; Frisch, A; Rockah, R; Michaelovsky, E; Apter, A; Weizman, A; Jönsson, E G; Bergman, H

2000-01-01

An association between long alleles of a variable number tandem repeat (VNTR) polymorphism in the dopamine receptor D4 gene and the extraversion related personality traits Excitement and Novelty Seeking has been reported in healthy subjects. In an attempt to replicate the previous findings, 256 healthy Caucasian volunteers were analysed for a potential relationship between the dopamine receptor D4 exon III VNTR polymorphism and Extraversion as assessed by the Revised Neo Personality Inventory (NEO PI-R). The present study did not yield evidence for an association between Extraversion and the dopamine receptor D4 polymorphism.

Microarray platform affords improved product analysis in mammalian cell growth studies

PubMed Central

Li, Lingyun; Migliore, Nicole; Schaefer, Eugene; Sharfstein, Susan T.; Dordick, Jonathan S.; Linhardt, Robert J.

2014-01-01

High throughput (HT) platforms serve as cost-efficient and rapid screening method for evaluating the effect of cell culture conditions and screening of chemicals. The aim of the current study was to develop a high-throughput cell-based microarray platform to assess the effect of culture conditions on Chinese hamster ovary (CHO) cells. Specifically, growth, transgene expression and metabolism of a GS/MSX CHO cell line, which produces a therapeutic monoclonal antibody, was examined using microarray system in conjunction with conventional shake flask platform in a non-proprietary medium. The microarray system consists of 60 nl spots of cells encapsulated in alginate and separated in groups via an 8-well chamber system attached to the chip. Results show the non-proprietary medium developed allows cell growth, production and normal glycosylation of recombinant antibody and metabolism of the recombinant CHO cells in both the microarray and shake flask platforms. In addition, 10.3 mM glutamate addition to the defined base media results in lactate metabolism shift in the recombinant GS/MSX CHO cells in the shake flask platform. Ultimately, the results demonstrate that the high-throughput microarray platform has the potential to be utilized for evaluating the impact of media additives on cellular processes, such as, cell growth, metabolism and productivity. PMID:24227746

Profiling protein function with small molecule microarrays

PubMed Central

Winssinger, Nicolas; Ficarro, Scott; Schultz, Peter G.; Harris, Jennifer L.

2002-01-01

The regulation of protein function through posttranslational modification, local environment, and protein–protein interaction is critical to cellular function. The ability to analyze on a genome-wide scale protein functional activity rather than changes in protein abundance or structure would provide important new insights into complex biological processes. Herein, we report the application of a spatially addressable small molecule microarray to an activity-based profile of proteases in crude cell lysates. The potential of this small molecule-based profiling technology is demonstrated by the detection of caspase activation upon induction of apoptosis, characterization of the activated caspase, and inhibition of the caspase-executed apoptotic phenotype using the small molecule inhibitor identified in the microarray-based profile. PMID:12167675

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

PubMed

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.

Sequencing ebola and marburg viruses genomes using microarrays.

PubMed

Hardick, Justin; Woelfel, Roman; Gardner, Warren; Ibrahim, Sofi

2016-08-01

Periodic outbreaks of Ebola and Marburg hemorrhagic fevers have occurred in Africa over the past four decades with case fatality rates reaching as high as 90%. The latest Ebola outbreak in West Africa in 2014 raised concerns that these infections can spread across continents and pose serious health risks. Early and accurate identification of the causative agents is necessary to contain outbreaks. In this report, we describe sequencing-by-hybridization (SBH) technique using high density microarrays to identify Ebola and Marburg viruses. The microarrays were designed to interrogate the sequences of entire viral genomes, and were evaluated with three species of Ebolavirus (Reston, Sudan, and Zaire), and three strains of Marburgvirus (Angola, Musoke, and Ravn). The results showed that the consensus sequences generated with four or more hybridizations had 92.1-98.9% accuracy over 95-99% of the genomes. Additionally, with SBH microarrays it was possible to distinguish between different strains of the Lake Victoria Marburgvirus. J. Med. Virol. 88:1303-1308, 2016. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

DNA Microarray-based Ecotoxicological Biomarker Discovery in a Small Fish Model Species

EPA Science Inventory

This paper addresses several issues critical to use of zebrafish oligonucleotide microarrays for computational toxicology research on endocrine disrupting chemicals using small fish models, and more generally, the use of microarrays in aquatic toxicology.

Number of blastocysts biopsied as a predictive indicator to obtain at least one normal/balanced embryo following preimplantation genetic diagnosis with single nucleotide polymorphism microarray in translocation cases.

PubMed

Wang, Yi-Zi; Ding, Chen-Hui; Wang, Jing; Zeng, Yan-Hong; Zhou, Wen; Li, Rong; Zhou, Can-Quan; Deng, Ming-Fen; Xu, Yan-Wen

2017-01-01

The aim of this study is to investigate the minimum number of blastocysts for biopsy to increase the likelihood of obtaining at least one normal/balanced embryo in preimplantation genetic diagnosis (PGD) for translocation carriers. This blinded retrospective study included 55 PGD cycles for Robertsonian translocation (RT) and 181 cycles for reciprocal translocation (rcp) to indicate when only one of the couples carried a translocation. Single-nucleotide polymorphism microarray after trophectoderm biopsy was performed. Reliable results were obtained for 355/379 (93.7 %) biopsied blastocysts in RT group and 986/1053 (93.6 %) in rcp group. Mean numbers of biopsied embryos per patient, normal/balanced embryos per patient, and mean normal/balanced embryo rate per patient were 7.4, 3.1, and 40.7 % in RT group and 8.0, 2.1, and 27.3 %, respectively, in rcp group. In a regression model, three factors significantly affected the number of genetically transferrable embryos: number of biopsied embryos (P = 0.001), basal FSH level (P = 0.040), and maternal age (P = 0.027). ROC analysis with a cutoff of 1.5 was calculated for the number of biopsied embryos required to obtain at least one normal/balanced embryo for RT carriers. For rcp carriers, the cutoff was 3.5. The clinical pregnancy rate per embryo transfer was 44.2 and 42.6 % in RT and rcp groups (P = 0.836). The minimum numbers of blastocysts to obtain at least one normal/balanced embryo for RT and rcp were 2 and 4 under the conditions of female age < 37 years with a basal FSH level < 11.4 IU/L.

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

PubMed

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.

Association study of interleukin-4 polymorphisms with paranoid schizophrenia in the Polish population: a critical approach.

PubMed

Fila-Danilow, Anna; Kucia, Krzysztof; Kowalczyk, Malgorzata; Owczarek, Aleksander; Paul-Samojedny, Monika; Borkowska, Paulina; Suchanek, Renata; Kowalski, Jan

2012-08-01

Changes in immunological system are one of dysfunctions reported in schizophrenia. Some changes based on an imbalance between Th1 and Th2 cytokines results from cytokine gene polymorphisms. Interleukin-4 gene (IL4) is considered as a potential candidate gene in schizophrenia association studies. The aim of the current case-control study was to examine whether the -590C/T (rs2243250) and -33C/T (rs2070874) IL4 gene polymorphisms are implicated in paranoid schizophrenia development in the Polish population. Genotyping of polymorphisms was performed by using PCR-RFLP technique. The genotypes and alleles distribution of both SNPs were analysed in patients (n = 182) and healthy individuals constituted the control group (n = 215). The connection between some clinical variables and studied polymorphisms has been examined as well. We did not revealed any association between the -590C/T and -33C/T polymorphisms and paranoid schizophrenia. In case of both SNPs the homozygous TT genotype was extremely rare. Both polymorphic sites of the IL4 gene were found to be in a very strong linkage disequilibrium. However we did not identify a haplotype predispose to paranoid schizophrenia. No associations were also observed between the clinical course and psychopathology of the disease and the genotypes of both analysed polymorphisms. Our results suggest that the polymorphisms -590C/T in IL4 gene promoter region and -33C/T in the 5'-UTR are not involved in the pathophysiology of paranoid schizophrenia in Polish residents.

Characterization and simulation of cDNA microarray spots using a novel mathematical model

PubMed Central

Kim, Hye Young; Lee, Seo Eun; Kim, Min Jung; Han, Jin Il; Kim, Bo Kyung; Lee, Yong Sung; Lee, Young Seek; Kim, Jin Hyuk

2007-01-01

Background The quality of cDNA microarray data is crucial for expanding its application to other research areas, such as the study of gene regulatory networks. Despite the fact that a number of algorithms have been suggested to increase the accuracy of microarray gene expression data, it is necessary to obtain reliable microarray images by improving wet-lab experiments. As the first step of a cDNA microarray experiment, spotting cDNA probes is critical to determining the quality of spot images. Results We developed a governing equation of cDNA deposition during evaporation of a drop in the microarray spotting process. The governing equation included four parameters: the surface site density on the support, the extrapolated equilibrium constant for the binding of cDNA molecules with surface sites on glass slides, the macromolecular interaction factor, and the volume constant of a drop of cDNA solution. We simulated cDNA deposition from the single model equation by varying the value of the parameters. The morphology of the resulting cDNA deposit can be classified into three types: a doughnut shape, a peak shape, and a volcano shape. The spot morphology can be changed into a flat shape by varying the experimental conditions while considering the parameters of the governing equation of cDNA deposition. The four parameters were estimated by fitting the governing equation to the real microarray images. With the results of the simulation and the parameter estimation, the phenomenon of the formation of cDNA deposits in each type was investigated. Conclusion This study explains how various spot shapes can exist and suggests which parameters are to be adjusted for obtaining a good spot. This system is able to explore the cDNA microarray spotting process in a predictable, manageable and descriptive manner. We hope it can provide a way to predict the incidents that can occur during a real cDNA microarray experiment, and produce useful data for several research applications

The future of microarray technology: networking the genome search.

PubMed

D'Ambrosio, C; Gatta, L; Bonini, S

2005-10-01

In recent years microarray technology has been increasingly used in both basic and clinical research, providing substantial information for a better understanding of genome-environment interactions responsible for diseases, as well as for their diagnosis and treatment. However, in genomic research using microarray technology there are several unresolved issues, including scientific, ethical and legal issues. Networks of excellence like GA(2)LEN may represent the best approach for teaching, cost reduction, data repositories, and functional studies implementation.

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

PubMed

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

2012-01-01

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

Comparison of Mediterranean Pistacia lentiscus genotypes by random amplified polymorphic DNA, chemical, and morphological analyses.

PubMed

Barazani, Oz; Dudai, Nativ; Golan-Goldhirsh, Avi

2003-08-01

Characterization of the genetic variability of Mediterranean Pistacia lentiscus genotypes by RAPD, composition of essential oils, and morphology is presented. High polymorphism in morphological parameters was found among accessions, with no significant differences in relation to geographical origin, or to gender. GC-MS analysis of leaves extracted by t-butyl methyl ether, showed 12 monoterpenes, seven sesquiterpenes, and one linear nonterpenic compound. Cluster analysis divided the accessions into two main groups according to the relative content of the major compounds, with no relation to their geographical origin. In contrast, a dendrogram based on RAPD analysis gave two main clusters according to their geographical origins. Low correlation was found between genetic and essential oil content matrices. High morphological and chemical variability on one hand, and genotypic polymorphism on the other, provide ecological advantages that might explain the distribution of Pistacia lentiscus over a wide range of habitats. The plants under study were grown together in the same climatic and environmental conditions, thus pointing to the plausible genetic basis of the observed phenotypic differences.

Exploiting fluorescence for multiplex immunoassays on protein microarrays

NASA Astrophysics Data System (ADS)

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

2014-09-01

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.

Evolution of the MIDTAL microarray: the adaption and testing of oligonucleotide 18S and 28S rDNA probes and evaluation of subsequent microarray generations with Prymnesium spp. cultures and field samples.

PubMed

McCoy, Gary R; Touzet, Nicolas; Fleming, Gerard T A; Raine, Robin

2015-07-01

The toxic microalgal species Prymnesium parvum and Prymnesium polylepis are responsible for numerous fish kills causing economic stress on the aquaculture industry and, through the consumption of contaminated shellfish, can potentially impact on human health. Monitoring of toxic phytoplankton is traditionally carried out by light microscopy. However, molecular methods of identification and quantification are becoming more common place. This study documents the optimisation of the novel Microarrays for the Detection of Toxic Algae (MIDTAL) microarray from its initial stages to the final commercial version now available from Microbia Environnement (France). Existing oligonucleotide probes used in whole-cell fluorescent in situ hybridisation (FISH) for Prymnesium species from higher group probes to species-level probes were adapted and tested on the first-generation microarray. The combination and interaction of numerous other probes specific for a whole range of phytoplankton taxa also spotted on the chip surface caused high cross reactivity, resulting in false-positive results on the microarray. The probe sequences were extended for the subsequent second-generation microarray, and further adaptations of the hybridisation protocol and incubation temperatures significantly reduced false-positive readings from the first to the second-generation chip, thereby increasing the specificity of the MIDTAL microarray. Additional refinement of the subsequent third-generation microarray protocols with the addition of a poly-T amino linker to the 5' end of each probe further enhanced the microarray performance but also highlighted the importance of optimising RNA labelling efficiency when testing with natural seawater samples from Killary Harbour, Ireland.

DISC-BASED IMMUNOASSAY MICROARRAYS. (R825433)

EPA Science Inventory

Microarray technology as applied to areas that include genomics, diagnostics, environmental, and drug discovery, is an interesting research topic for which different chip-based devices have been developed. As an alternative, we have explored the principle of compact disc-based...

Duffy blood group phenotype-genotype correlations using high-resolution melting analysis PCR and microarray reveal complex cases including a new null FY*A allele: the role for sequencing in genotyping algorithms.

PubMed

Lopez, G H; Morrison, J; Condon, J A; Wilson, B; Martin, J R; Liew, Y-W; Flower, R L; Hyland, C A

2015-10-01

Duffy blood group phenotypes can be predicted by genotyping for single nucleotide polymorphisms (SNPs) responsible for the Fy(a) /Fy(b) polymorphism, for weak Fy(b) antigen, and for the red cell null Fy(a-b-) phenotype. This study correlates Duffy phenotype predictions with serotyping to assess the most reliable procedure for typing. Samples, n = 155 (135 donors and 20 patients), were genotyped by high-resolution melt PCR and by microarray. Samples were in three serology groups: 1) Duffy patterns expected n = 79, 2) weak and equivocal Fy(b) patterns n = 29 and 3) Fy(a-b-) n = 47 (one with anti-Fy3 antibody). Discrepancies were observed for five samples. For two, SNP genotyping predicted weak Fy(b) expression discrepant with Fy(b-) (Group 1 and 3). For three, SNP genotyping predicted Fy(a) , discrepant with Fy(a-b-) (Group 3). DNA sequencing identified silencing mutations in these FY*A alleles. One was a novel FY*A 719delG. One, the sample with the anti-Fy3, was homozygous for a 14-bp deletion (FY*01N.02); a true null. Both the high-resolution melting analysis and SNP microarray assays were concordant and showed genotyping, as well as phenotyping, is essential to ensure 100% accuracy for Duffy blood group assignments. Sequencing is important to resolve phenotype/genotype conflicts which here identified alleles, one novel, that carry silencing mutations. The risk of alloimmunisation may be dependent on this zygosity status. © 2015 International Society of Blood Transfusion.

A Platform for Combined DNA and Protein Microarrays Based on Total Internal Reflection Fluorescence

PubMed Central

Asanov, Alexander; Zepeda, Angélica; Vaca, Luis

2012-01-01

We have developed a novel microarray technology based on total internal reflection fluorescence (TIRF) in combination with DNA and protein bioassays immobilized at the TIRF surface. Unlike conventional microarrays that exhibit reduced signal-to-background ratio, require several stages of incubation, rinsing and stringency control, and measure only end-point results, our TIRF microarray technology provides several orders of magnitude better signal-to-background ratio, performs analysis rapidly in one step, and measures the entire course of association and dissociation kinetics between target DNA and protein molecules and the bioassays. In many practical cases detection of only DNA or protein markers alone does not provide the necessary accuracy for diagnosing a disease or detecting a pathogen. Here we describe TIRF microarrays that detect DNA and protein markers simultaneously, which reduces the probabilities of false responses. Supersensitive and multiplexed TIRF DNA and protein microarray technology may provide a platform for accurate diagnosis or enhanced research studies. Our TIRF microarray system can be mounted on upright or inverted microscopes or interfaced directly with CCD cameras equipped with a single objective, facilitating the development of portable devices. As proof-of-concept we applied TIRF microarrays for detecting molecular markers from Bacillus anthracis, the pathogen responsible for anthrax. PMID:22438738

Employing image processing techniques for cancer detection using microarray images.

PubMed

Dehghan Khalilabad, Nastaran; Hassanpour, Hamid

2017-02-01

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

Microarray Analyses of Gene Expression during Adventitious Root Development in Pinus contorta1[w

PubMed Central

Brinker, Monika; van Zyl, Leonel; Liu, Wenbin; Craig, Deborah; Sederoff, Ronald R.; Clapham, David H.; von Arnold, Sara

2004-01-01

In order to investigate the gene expression pattern during adventitious root development, RNA of Pinus contorta hypocotyls, pulse-treated with the auxin indole-3-butyric acid and harvested at distinct developmental time points of root development, was hybridized to microarrays containing 2,178 cDNAs from Pinus taeda. Over the period of observation of root development, the transcript levels of 220 genes changed significantly. During the root initiation phase, genes involved in cell replication and cell wall weakening and a transcript encoding a PINHEAD/ZWILLE-like protein were up-regulated, while genes related to auxin transport, photosynthesis, and cell wall synthesis were down-regulated. In addition, there were changes in transcript abundance of genes related to water stress. During the root meristem formation phase the transcript abundances of genes involved in auxin transport, auxin responsive transcription, and cell wall synthesis, and of a gene encoding a B-box zinc finger-like protein, increased, while those encoding proteins involved in cell wall weakening decreased. Changes of transcript abundance of genes related to water stress during the root meristem formation and root formation phase indicate that the plant roots had become functional in water transport. Simultaneously, genes involved in auxin transport were up-regulated, while genes related to cell wall modification were down-regulated. Finally, during the root elongation phase down-regulation of transcripts encoding proteins involved in cell replication and stress occurred. Based on the observed changes in transcript abundances, we suggest hypotheses about the relative importance of various physiological processes during the auxin-induced development of roots in P. contorta. PMID:15247392

Broad spectrum microarray for fingerprint-based bacterial species identification

PubMed Central

2010-01-01

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. PMID:20163710

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

PubMed

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.

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

EPA Science Inventory

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...

Search for methylation-sensitive amplification polymorphisms in mutant figs.

PubMed

Rodrigues, M G F; Martins, A B G; Bertoni, B W; Figueira, A; Giuliatti, S

2013-07-08

Fig (Ficus carica) breeding programs that use conventional approaches to develop new cultivars are rare, owing to limited genetic variability and the difficulty in obtaining plants via gamete fusion. Cytosine methylation in plants leads to gene repression, thereby affecting transcription without changing the DNA sequence. Previous studies using random amplification of polymorphic DNA and amplified fragment length polymorphism markers revealed no polymorphisms among select fig mutants that originated from gamma-irradiated buds. Therefore, we conducted methylation-sensitive amplified polymorphism analysis to verify the existence of variability due to epigenetic DNA methylation among these mutant selections compared to the main cultivar 'Roxo-de-Valinhos'. Samples of genomic DNA were double-digested with either HpaII (methylation sensitive) or MspI (methylation insensitive) and with EcoRI. Fourteen primer combinations were tested, and on an average, non-methylated CCGG, symmetrically methylated CmCGG, and hemimethylated hmCCGG sites accounted for 87.9, 10.1, and 2.0%, respectively. MSAP analysis was effective in detecting differentially methylated sites in the genomic DNA of fig mutants, and methylation may be responsible for the phenotypic variation between treatments. Further analyses such as polymorphic DNA sequencing are necessary to validate these differences, standardize the regions of methylation, and analyze reads using bioinformatic tools.

Microarray expression technology: from start to finish.

PubMed

Elvidge, Gareth

2006-01-01

The recent introduction of new microarray expression technologies and the further development of established platforms ensure that the researcher is presented with a range of options for performing an experiment. Whilst this has opened up the possibilities for future applications, such as exon-specific arrays, increased sample throughput and 'chromatin immunoprecipitation (ChIP) on chip' experiments, the initial decision processes and experiment planning are made more difficult. This review will give an overview of the various technologies that are available to perform a microarray expression experiment, from the initial planning stages through to the final data analysis. Both practical aspects and data analysis options will be considered. The relative advantages and disadvantages will be discussed with insights provided for future directions of the technology.

Gaussian mixture clustering and imputation of microarray data.

PubMed

Ouyang, Ming; Welsh, William J; Georgopoulos, Panos

2004-04-12

In microarray experiments, missing entries arise from blemishes on the chips. In large-scale studies, virtually every chip contains some missing entries and more than 90% of the genes are affected. Many analysis methods require a full set of data. Either those genes with missing entries are excluded, or the missing entries are filled with estimates prior to the analyses. This study compares methods of missing value estimation. Two evaluation metrics of imputation accuracy are employed. First, the root mean squared error measures the difference between the true values and the imputed values. Second, the number of mis-clustered genes measures the difference between clustering with true values and that with imputed values; it examines the bias introduced by imputation to clustering. The Gaussian mixture clustering with model averaging imputation is superior to all other imputation methods, according to both evaluation metrics, on both time-series (correlated) and non-time series (uncorrelated) data sets.

Fast gene ontology based clustering for microarray experiments.

PubMed

Ovaska, Kristian; Laakso, Marko; Hautaniemi, Sampsa

2008-11-21

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

[Research progress of probe design software of oligonucleotide microarrays].

PubMed

Chen, Xi; Wu, Zaoquan; Liu, Zhengchun

2014-02-01

DNA microarray has become an essential medical genetic diagnostic tool for its high-throughput, miniaturization and automation. The design and selection of oligonucleotide probes are critical for preparing gene chips with high quality. Several sets of probe design software have been developed and are available to perform this work now. Every set of the software aims to different target sequences and shows different advantages and limitations. In this article, the research and development of these sets of software are reviewed in line with three main criteria, including specificity, sensitivity and melting temperature (Tm). In addition, based on the experimental results from literatures, these sets of software are classified according to their applications. This review will be helpful for users to choose an appropriate probe-design software. It will also reduce the costs of microarrays, improve the application efficiency of microarrays, and promote both the research and development (R&D) and commercialization of high-performance probe design software.

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

PubMed

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

2006-09-20

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

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

PubMed Central

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

2006-01-01

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

Reusable conductimetric array of interdigitated microelectrodes for the readout of low-density microarrays.

PubMed

Mallén, Maria; Díaz-González, María; Bonilla, Diana; Salvador, Juan P; Marco, María P; Baldi, Antoni; Fernández-Sánchez, César

2014-06-17

Low-density protein microarrays are emerging tools in diagnostics whose deployment could be primarily limited by the cost of fluorescence detection schemes. This paper describes an electrical readout system of microarrays comprising an array of gold interdigitated microelectrodes and an array of polydimethylsiloxane microwells, which enabled multiplexed detection of up to thirty six biological events on the same substrate. Similarly to fluorescent readout counterparts, the microarray can be developed on disposable glass slide substrates. However, unlike them, the presented approach is compact and requires a simple and inexpensive instrumentation. The system makes use of urease labeled affinity reagents for developing the microarrays and is based on detection of conductivity changes taking place when ionic species are generated in solution due to the catalytic hydrolysis of urea. The use of a polydimethylsiloxane microwell array facilitates the positioning of the measurement solution on every spot of the microarray. Also, it ensures the liquid tightness and isolation from the surrounding ones during the microarray readout process, thereby avoiding evaporation and chemical cross-talk effects that were shown to affect the sensitivity and reliability of the system. The performance of the system is demonstrated by carrying out the readout of a microarray for boldenone anabolic androgenic steroid hormone. Analytical results are comparable to those obtained by fluorescent scanner detection approaches. The estimated detection limit is 4.0 ng mL(-1), this being below the threshold value set by the World Anti-Doping Agency and the European Community. Copyright © 2014 Elsevier B.V. All rights reserved.

Association between IL-1β polymorphisms and gastritis risk: A meta-analysis.

PubMed

Sun, Xiaoming; Cai, Hongxing; Li, Zhouru; Li, Shanshan; Yin, Wenjiang; Dong, Guokai; Kuai, Jinxia; He, Yihui; Jia, Jing

2017-02-01

Helicobacter pylori (H. pylori) infection of the human stomach regularly leads to chronic gastric inflammation. The cytokine gene interleukin (IL)-1β has been implicated in influencing the pathology of inflammation induced by H. pylori infection. Currently, several studies have been carried out to investigate the association of IL-1β-511 (rs16944) and IL-1β-31 (rs1143627) polymorphisms with gastritis risk; however, the results are inconsistent and inconclusive. To assess the effect of IL-1β polymorphisms on gastritis susceptibility, we conducted a meta-analysis. Up to March 15, 2016, 2205 cases and 2289 controls were collected from 12 published case-control studies. Summarized odds ratios and corresponding 95% confidence intervals (CIs) for IL-1β-511 and IL-1β-31 polymorphisms and gastritis risk were estimated using fixed- or random-effects models when appropriate. Heterogeneity was assessed by chi-squared-based Q-statistic test, and the sources of heterogeneity were explored by subgroup analyses and logistic meta-regression analyses. Publication bias was evaluated by Begg funnel plot and Egger test. Sensitivity analyses were also performed. The results provided evidences that the single nucleotide polymorphisms (SNPs) in IL-1β-31 might be associated with the gastritis risk, especially in the Caucasian population, while SNPs in the IL-1β-511 might not be. Our studies may be helpful in supplementing the disease monitoring of gastritis in the future, and additional studies to determine the exact molecular mechanisms might inspire interventions to protect the susceptible subgroups.

Novel SNPs and INDEL polymorphisms in the 3'UTR of DGAT1 gene: in silico analyses and a possible association.

PubMed

Rosse, Izinara da Cruz; Steinberg, Raphael da Silva; Coimbra, Roney Santos; Peixoto, Maria Gabriela Campolina Diniz; Verneque, Rui Silva; Machado, Marco Antonio; Fonseca, Cleusa Graça; Carvalho, Maria Raquel Santos

2014-07-01

Diacylglycerol-O-acyltransferase (DGAT1) gene encodes the rate-limiting enzyme of triglyceride synthesis. A polymorphism in this gene, DGAT1 K232A, has been associated with milk production and composition in taurine breeds. However, this polymorphism is not a good tool for ascertaining the effects of this QTL in Bos indicus (Zebu), since the frequency of the DGAT1 232A allele is too low in these breeds. We sequenced the 3'-untranslated region of DGAT1 gene in a sample of bulls of the breeds Guzerá (Bos indicus) and Holstein (Bos taurus) and, using in silico analysis, we searched for genetic variation, evolutionary conservation, regulatory elements, and possible substitution effects. Six single nucleotide (SNPs) and one insertion-deletion (INDEL) polymorphisms were found in the Guzerá bulls. Additionally, we developed a preliminary association study, using this INDEL polymorphism as a genetic marker. A significant association was detected (P ≤ 0.05) between the INDEL (DGAT1 3'UTR INDEL) and the breeding values (BV) for protein, fat, and milk yields over a 305-day lactation period. The DGAT1 3' UTR INDEL genotype I/I (I, for insertion) was associated with lower BVs (-38.77 kg for milk, -1.86 kg for fat, and -1.48 kg for protein yields), when compared to the genotype I/D (D, for deletion). I/D genotype was lower D/D genotype (-34.98 kg milk, -1.73 kg fat, and -1.09 kg protein yields). This study reports the first polymorphism of DGAT1 3'UTR in the Guzerá breed, as well as its association with BV for milk protein, fat, and milk yields.

Dynamic, electronically switchable surfaces for membrane protein microarrays.

PubMed

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.

Autonomous system for Web-based microarray image analysis.

PubMed

Bozinov, Daniel

2003-12-01

Software-based feature extraction from DNA microarray images still requires human intervention on various levels. Manual adjustment of grid and metagrid parameters, precise alignment of superimposed grid templates and gene spots, or simply identification of large-scale artifacts have to be performed beforehand to reliably analyze DNA signals and correctly quantify their expression values. Ideally, a Web-based system with input solely confined to a single microarray image and a data table as output containing measurements for all gene spots would directly transform raw image data into abstracted gene expression tables. Sophisticated algorithms with advanced procedures for iterative correction function can overcome imminent challenges in image processing. Herein is introduced an integrated software system with a Java-based interface on the client side that allows for decentralized access and furthermore enables the scientist to instantly employ the most updated software version at any given time. This software tool is extended from PixClust as used in Extractiff incorporated with Java Web Start deployment technology. Ultimately, this setup is destined for high-throughput pipelines in genome-wide medical diagnostics labs or microarray core facilities aimed at providing fully automated service to its users.

A New Distribution Family for Microarray Data †

PubMed Central

Kelmansky, Diana Mabel; Ricci, Lila

2017-01-01

The traditional approach with microarray data has been to apply transformations that approximately normalize them, with the drawback of losing the original scale. The alternative standpoint taken here is to search for models that fit the data, characterized by the presence of negative values, preserving their scale; one advantage of this strategy is that it facilitates a direct interpretation of the results. A new family of distributions named gpower-normal indexed by p∈R is introduced and it is proven that these variables become normal or truncated normal when a suitable gpower transformation is applied. Expressions are given for moments and quantiles, in terms of the truncated normal density. This new family can be used to model asymmetric data that include non-positive values, as required for microarray analysis. Moreover, it has been proven that the gpower-normal family is a special case of pseudo-dispersion models, inheriting all the good properties of these models, such as asymptotic normality for small variances. A combined maximum likelihood method is proposed to estimate the model parameters, and it is applied to microarray and contamination data. R codes are available from the authors upon request. PMID:28208652

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

PubMed

Do, Jin Hwan; Choi, Dong-Kug

2008-04-30

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

Stochastic models for inferring genetic regulation from microarray gene expression data.

PubMed

Tian, Tianhai

2010-03-01

Microarray expression profiles are inherently noisy and many different sources of variation exist in microarray experiments. It is still a significant challenge to develop stochastic models to realize noise in microarray expression profiles, which has profound influence on the reverse engineering of genetic regulation. Using the target genes of the tumour suppressor gene p53 as the test problem, we developed stochastic differential equation models and established the relationship between the noise strength of stochastic models and parameters of an error model for describing the distribution of the microarray measurements. Numerical results indicate that the simulated variance from stochastic models with a stochastic degradation process can be represented by a monomial in terms of the hybridization intensity and the order of the monomial depends on the type of stochastic process. The developed stochastic models with multiple stochastic processes generated simulations whose variance is consistent with the prediction of the error model. This work also established a general method to develop stochastic models from experimental information. 2009 Elsevier Ireland Ltd. All rights reserved.

Microarray-based characterization of differential gene expression during vocal fold wound healing in rats

PubMed Central

Welham, Nathan V.; Ling, Changying; Dawson, John A.; Kendziorski, Christina; Thibeault, Susan L.; Yamashita, Masaru

2015-01-01

The vocal fold (VF) mucosa confers elegant biomechanical function for voice production but is susceptible to scar formation following injury. Current understanding of VF wound healing is hindered by a paucity of data and is therefore often generalized from research conducted in skin and other mucosal systems. Here, using a previously validated rat injury model, expression microarray technology and an empirical Bayes analysis approach, we generated a VF-specific transcriptome dataset to better capture the system-level complexity of wound healing in this specialized tissue. We measured differential gene expression at 3, 14 and 60 days post-injury compared to experimentally naïve controls, pursued functional enrichment analyses to refine and add greater biological definition to the previously proposed temporal phases of VF wound healing, and validated the expression and localization of a subset of previously unidentified repair- and regeneration-related genes at the protein level. Our microarray dataset is a resource for the wider research community and has the potential to stimulate new hypotheses and avenues of investigation, improve biological and mechanistic insight, and accelerate the identification of novel therapeutic targets. PMID:25592437

Applications of nanotechnology, next generation sequencing and microarrays in biomedical research.

PubMed

Elingaramil, Sauli; Li, Xiaolong; He, Nongyue

2013-07-01

Next-generation sequencing technologies, microarrays and advances in bio nanotechnology have had an enormous impact on research within a short time frame. This impact appears certain to increase further as many biomedical institutions are now acquiring these prevailing new technologies. Beyond conventional sampling of genome content, wide-ranging applications are rapidly evolving for next-generation sequencing, microarrays and nanotechnology. To date, these technologies have been applied in a variety of contexts, including whole-genome sequencing, targeted re sequencing and discovery of transcription factor binding sites, noncoding RNA expression profiling and molecular diagnostics. This paper thus discusses current applications of nanotechnology, next-generation sequencing technologies and microarrays in biomedical research and highlights the transforming potential these technologies offer.

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

PubMed

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

2005-07-01

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

Reuse of imputed data in microarray analysis increases imputation efficiency

PubMed Central

Kim, Ki-Yeol; Kim, Byoung-Jin; Yi, Gwan-Su

2004-01-01

Background The imputation of missing values is necessary for the efficient use of DNA microarray data, because many clustering algorithms and some statistical analysis require a complete data set. A few imputation methods for DNA microarray data have been introduced, but the efficiency of the methods was low and the validity of imputed values in these methods had not been fully checked. Results We developed a new cluster-based imputation method called sequential K-nearest neighbor (SKNN) method. This imputes the missing values sequentially from the gene having least missing values, and uses the imputed values for the later imputation. Although it uses the imputed values, the efficiency of this new method is greatly improved in its accuracy and computational complexity over the conventional KNN-based method and other methods based on maximum likelihood estimation. The performance of SKNN was in particular higher than other imputation methods for the data with high missing rates and large number of experiments. Application of Expectation Maximization (EM) to the SKNN method improved the accuracy, but increased computational time proportional to the number of iterations. The Multiple Imputation (MI) method, which is well known but not applied previously to microarray data, showed a similarly high accuracy as the SKNN method, with slightly higher dependency on the types of data sets. Conclusions Sequential reuse of imputed data in KNN-based imputation greatly increases the efficiency of imputation. The SKNN method should be practically useful to save the data of some microarray experiments which have high amounts of missing entries. The SKNN method generates reliable imputed values which can be used for further cluster-based analysis of microarray data. PMID:15504240

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

PubMed

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

2012-09-01

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

Microarray labeling extension values: laboratory signatures for Affymetrix GeneChips

PubMed Central

Lee, Yun-Shien; Chen, Chun-Houh; Tsai, Chi-Neu; Tsai, Chia-Lung; Chao, Angel; Wang, Tzu-Hao

2009-01-01

Interlaboratory comparison of microarray data, even when using the same platform, imposes several challenges to scientists. RNA quality, RNA labeling efficiency, hybridization procedures and data-mining tools can all contribute variations in each laboratory. In Affymetrix GeneChips, about 11–20 different 25-mer oligonucleotides are used to measure the level of each transcript. Here, we report that ‘labeling extension values (LEVs)’, which are correlation coefficients between probe intensities and probe positions, are highly correlated with the gene expression levels (GEVs) on eukayotic Affymetrix microarray data. By analyzing LEVs and GEVs in the publicly available 2414 cel files of 20 Affymetrix microarray types covering 13 species, we found that correlations between LEVs and GEVs only exist in eukaryotic RNAs, but not in prokaryotic ones. Surprisingly, Affymetrix results of the same specimens that were analyzed in different laboratories could be clearly differentiated only by LEVs, leading to the identification of ‘laboratory signatures’. In the examined dataset, GSE10797, filtering out high-LEV genes did not compromise the discovery of biological processes that are constructed by differentially expressed genes. In conclusion, LEVs provide a new filtering parameter for microarray analysis of gene expression and it may improve the inter- and intralaboratory comparability of Affymetrix GeneChips data. PMID:19295132

A microarray immunoassay for simultaneous detection of proteins and bacteria

NASA Technical Reports Server (NTRS)

Delehanty, James B.; Ligler, Frances S.

2002-01-01

We report the development and characterization of an antibody microarray biosensor for the rapid detection of both protein and bacterial analytes under flow conditions. Using a noncontact microarray printer, biotinylated capture antibodies were immobilized at discrete locations on the surface of an avidin-coated glass microscope slide. Preservation of capture antibody function during the deposition process was accomplished with the use of a low-salt buffer containing sucrose and bovine serum albumin. The slide was fitted with a six-channel flow module that conducted analyte-containing solutions over the array of capture antibody microspots. Detection of bound analyte was subsequently achieved using fluorescent tracer antibodies. The pattern of fluorescent complexes was interrogated using a scanning confocal microscope equipped with a 635-nm laser. This microarray system was employed to detect protein and bacterial analytes both individually and in samples containing mixtures of analytes. Assays were completed in 15 min, and detection of cholera toxin, staphylococcal enterotoxin B, ricin, and Bacillus globigii was demonstrated at levels as low as 8 ng/mL, 4 ng/mL, 10 ng/mL, and 6.2 x 10(4) cfu/mL, respectively. The assays presented here are very fast, as compared to previously published methods for measuring antibody-antigen interactions using microarrays (minutes versus hours).

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

PubMed

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

2009-10-01

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

ArrayNinja: An Open Source Platform for Unified Planning and Analysis of Microarray Experiments.

PubMed

Dickson, B M; Cornett, E M; Ramjan, Z; Rothbart, S B

2016-01-01

Microarray-based proteomic platforms have emerged as valuable tools for studying various aspects of protein function, particularly in the field of chromatin biochemistry. Microarray technology itself is largely unrestricted in regard to printable material and platform design, and efficient multidimensional optimization of assay parameters requires fluidity in the design and analysis of custom print layouts. This motivates the need for streamlined software infrastructure that facilitates the combined planning and analysis of custom microarray experiments. To this end, we have developed ArrayNinja as a portable, open source, and interactive application that unifies the planning and visualization of microarray experiments and provides maximum flexibility to end users. Array experiments can be planned, stored to a private database, and merged with the imaged results for a level of data interaction and centralization that is not currently attainable with available microarray informatics tools. © 2016 Elsevier Inc. All rights reserved.

TERT rs2736098 polymorphism and cancer risk: results of a meta-analysis.

PubMed

Qi, Hao-Yu; Zou, Peng; Zhao, Lin; Zhu, Jue; Gu, Ai-Hua

2012-01-01

Several studies have demonstrated associations between the TERT rs2736098 single nucleotide polymorphisms (SNPs) and susceptibility to cancer development. However, there are conflicting results. A systematic meta-analysis was therefore performed to establish the cancer risk associated with the polymorphism. In this meta-analysis, a total of 6 case-control studies, including 5,567 cases and 6,191 controls, were included. Crude odds ratios with 95% confidence intervals were used to assess the strength of associations in several genetic models. Our results showed no association reaching the level of statistical significance for overall risk. Interestingly, in the stratified analyses (subdivided by ethnicity), significantly increased risks were found in the Asian subgroup which indicates the TERT rs2736098 polymorphism may have controversial involvement in cancer susceptibility. Overall, this meta-analysis indicates that the TERT rs2736098 polymorphism may have little involvement in cancer susceptibility.

On the classification techniques in data mining for microarray data classification

NASA Astrophysics Data System (ADS)

Aydadenta, Husna; Adiwijaya

2018-03-01

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

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

PubMed

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

2010-04-01

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

BIOPHYSICAL PROPERTIES OF NUCLEIC ACIDS AT SURFACES RELEVANT TO MICROARRAY PERFORMANCE.

PubMed

Rao, Archana N; Grainger, David W

2014-04-01

Both clinical and analytical metrics produced by microarray-based assay technology have recognized problems in reproducibility, reliability and analytical sensitivity. These issues are often attributed to poor understanding and control of nucleic acid behaviors and properties at solid-liquid interfaces. Nucleic acid hybridization, central to DNA and RNA microarray formats, depends on the properties and behaviors of single strand (ss) nucleic acids (e.g., probe oligomeric DNA) bound to surfaces. ssDNA's persistence length, radius of gyration, electrostatics, conformations on different surfaces and under various assay conditions, its chain flexibility and curvature, charging effects in ionic solutions, and fluorescent labeling all influence its physical chemistry and hybridization under assay conditions. Nucleic acid (e.g., both RNA and DNA) target interactions with immobilized ssDNA strands are highly impacted by these biophysical states. Furthermore, the kinetics, thermodynamics, and enthalpic and entropic contributions to DNA hybridization reflect global probe/target structures and interaction dynamics. Here we review several biophysical issues relevant to oligomeric nucleic acid molecular behaviors at surfaces and their influences on duplex formation that influence microarray assay performance. Correlation of biophysical aspects of single and double-stranded nucleic acids with their complexes in bulk solution is common. Such analysis at surfaces is not commonly reported, despite its importance to microarray assays. We seek to provide further insight into nucleic acid-surface challenges facing microarray diagnostic formats that have hindered their clinical adoption and compromise their research quality and value as genomics tools.

BIOPHYSICAL PROPERTIES OF NUCLEIC ACIDS AT SURFACES RELEVANT TO MICROARRAY PERFORMANCE

PubMed Central

Rao, Archana N.; Grainger, David W.

2014-01-01

Both clinical and analytical metrics produced by microarray-based assay technology have recognized problems in reproducibility, reliability and analytical sensitivity. These issues are often attributed to poor understanding and control of nucleic acid behaviors and properties at solid-liquid interfaces. Nucleic acid hybridization, central to DNA and RNA microarray formats, depends on the properties and behaviors of single strand (ss) nucleic acids (e.g., probe oligomeric DNA) bound to surfaces. ssDNA’s persistence length, radius of gyration, electrostatics, conformations on different surfaces and under various assay conditions, its chain flexibility and curvature, charging effects in ionic solutions, and fluorescent labeling all influence its physical chemistry and hybridization under assay conditions. Nucleic acid (e.g., both RNA and DNA) target interactions with immobilized ssDNA strands are highly impacted by these biophysical states. Furthermore, the kinetics, thermodynamics, and enthalpic and entropic contributions to DNA hybridization reflect global probe/target structures and interaction dynamics. Here we review several biophysical issues relevant to oligomeric nucleic acid molecular behaviors at surfaces and their influences on duplex formation that influence microarray assay performance. Correlation of biophysical aspects of single and double-stranded nucleic acids with their complexes in bulk solution is common. Such analysis at surfaces is not commonly reported, despite its importance to microarray assays. We seek to provide further insight into nucleic acid-surface challenges facing microarray diagnostic formats that have hindered their clinical adoption and compromise their research quality and value as genomics tools. PMID:24765522

Mining meiosis and gametogenesis with DNA microarrays.

PubMed

Schlecht, Ulrich; Primig, Michael

2003-04-01

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

CNV-ROC: A cost effective, computer-aided analytical performance evaluator of chromosomal microarrays.

PubMed

Goodman, Corey W; Major, Heather J; Walls, William D; Sheffield, Val C; Casavant, Thomas L; Darbro, Benjamin W

2015-04-01

Chromosomal microarrays (CMAs) are routinely used in both research and clinical laboratories; yet, little attention has been given to the estimation of genome-wide true and false negatives during the assessment of these assays and how such information could be used to calibrate various algorithmic metrics to improve performance. Low-throughput, locus-specific methods such as fluorescence in situ hybridization (FISH), quantitative PCR (qPCR), or multiplex ligation-dependent probe amplification (MLPA) preclude rigorous calibration of various metrics used by copy number variant (CNV) detection algorithms. To aid this task, we have established a comparative methodology, CNV-ROC, which is capable of performing a high throughput, low cost, analysis of CMAs that takes into consideration genome-wide true and false negatives. CNV-ROC uses a higher resolution microarray to confirm calls from a lower resolution microarray and provides for a true measure of genome-wide performance metrics at the resolution offered by microarray testing. CNV-ROC also provides for a very precise comparison of CNV calls between two microarray platforms without the need to establish an arbitrary degree of overlap. Comparison of CNVs across microarrays is done on a per-probe basis and receiver operator characteristic (ROC) analysis is used to calibrate algorithmic metrics, such as log2 ratio threshold, to enhance CNV calling performance. CNV-ROC addresses a critical and consistently overlooked aspect of analytical assessments of genome-wide techniques like CMAs which is the measurement and use of genome-wide true and false negative data for the calculation of performance metrics and comparison of CNV profiles between different microarray experiments. Copyright © 2015 Elsevier Inc. All rights reserved.

CNV-ROC: A cost effective, computer-aided analytical performance evaluator of chromosomal microarrays

PubMed Central

Goodman, Corey W.; Major, Heather J.; Walls, William D.; Sheffield, Val C.; Casavant, Thomas L.; Darbro, Benjamin W.

2016-01-01

Chromosomal microarrays (CMAs) are routinely used in both research and clinical laboratories; yet, little attention has been given to the estimation of genome-wide true and false negatives during the assessment of these assays and how such information could be used to calibrate various algorithmic metrics to improve performance. Low-throughput, locus-specific methods such as fluorescence in situ hybridization (FISH), quantitative PCR (qPCR), or multiplex ligation-dependent probe amplification (MLPA) preclude rigorous calibration of various metrics used by copy number variant (CNV) detection algorithms. To aid this task, we have established a comparative methodology, CNV-ROC, which is capable of performing a high throughput, low cost, analysis of CMAs that takes into consideration genome-wide true and false negatives. CNV-ROC uses a higher resolution microarray to confirm calls from a lower resolution microarray and provides for a true measure of genome-wide performance metrics at the resolution offered by microarray testing. CNV-ROC also provides for a very precise comparison of CNV calls between two microarray platforms without the need to establish an arbitrary degree of overlap. Comparison of CNVs across microarrays is done on a per-probe basis and receiver operator characteristic (ROC) analysis is used to calibrate algorithmic metrics, such as log2 ratio threshold, to enhance CNV calling performance. CNV-ROC addresses a critical and consistently overlooked aspect of analytical assessments of genome-wide techniques like CMAs which is the measurement and use of genome-wide true and false negative data for the calculation of performance metrics and comparison of CNV profiles between different microarray experiments. PMID:25595567

An improved K-means clustering method for cDNA microarray image segmentation.

PubMed

Wang, T N; Li, T J; Shao, G F; Wu, S X

2015-07-14

Microarray technology is a powerful tool for human genetic research and other biomedical applications. Numerous improvements to the standard K-means algorithm have been carried out to complete the image segmentation step. However, most of the previous studies classify the image into two clusters. In this paper, we propose a novel K-means algorithm, which first classifies the image into three clusters, and then one of the three clusters is divided as the background region and the other two clusters, as the foreground region. The proposed method was evaluated on six different data sets. The analyses of accuracy, efficiency, expression values, special gene spots, and noise images demonstrate the effectiveness of our method in improving the segmentation quality.

Variance stabilization and normalization for one-color microarray data using a data-driven multiscale approach.

PubMed

Motakis, E S; Nason, G P; Fryzlewicz, P; Rutter, G A

2006-10-15

Many standard statistical techniques are effective on data that are normally distributed with constant variance. Microarray data typically violate these assumptions since they come from non-Gaussian distributions with a non-trivial mean-variance relationship. Several methods have been proposed that transform microarray data to stabilize variance and draw its distribution towards the Gaussian. Some methods, such as log or generalized log, rely on an underlying model for the data. Others, such as the spread-versus-level plot, do not. We propose an alternative data-driven multiscale approach, called the Data-Driven Haar-Fisz for microarrays (DDHFm) with replicates. DDHFm has the advantage of being 'distribution-free' in the sense that no parametric model for the underlying microarray data is required to be specified or estimated; hence, DDHFm can be applied very generally, not just to microarray data. DDHFm achieves very good variance stabilization of microarray data with replicates and produces transformed intensities that are approximately normally distributed. Simulation studies show that it performs better than other existing methods. Application of DDHFm to real one-color cDNA data validates these results. The R package of the Data-Driven Haar-Fisz transform (DDHFm) for microarrays is available in Bioconductor and CRAN.

Association of HMOX1 and NQO1 Polymorphisms with Metabolic Syndrome Components

PubMed Central

Martínez-Hernández, Angélica; Córdova, Emilio J.; Rosillo-Salazar, Oscar; García-Ortíz, Humberto; Contreras-Cubas, Cecilia; Islas-Andrade, Sergio; Revilla-Monsalve, Cristina; Salas-Labadía, Consuelo; Orozco, Lorena

2015-01-01

Metabolic syndrome (MetS) is among the most important public health problems worldwide, and is recognized as a major risk factor for various illnesses, including type 2 diabetes mellitus, obesity, and cardiovascular diseases. Recently, oxidative stress has been suggested as part of MetS aetiology. The heme oxygenase 1 (HMOX1) and NADH:quinone oxidoreductase 1 (NQO1) genes are crucial mediators of cellular defence against oxidative stress. In the present study, we analysed the associations of HMOX1 (GT)n and NQO1 C609T polymorphisms with MetS and its components. Our study population comprised 735 Mexican Mestizos unrelated volunteers recruited from different tertiary health institutions from Mexico City. In order to know the HMOX1 (GT)n and NQO1 C609T allele frequencies in Amerindians, we included a population of 241 Amerindian native speakers. Their clinical and demographic data were recorded. The HMOX1 (GT)n polymorphism was genotyped using PCR and fluorescence technology. NQO1 C609T polymorphism genotyping was performed using TaqMan probes. Short allele (<25 GT repeats) of the HMOX1 polymorphism was associated with high systolic and diastolic blood pressure, and the T allele of the NQO1 C609T polymorphism was associated with increased triglyceride levels and decreased HDL-c levels, but only in individuals with MetS. This is the first study to analyse the association between MetS and genes involved in oxidative stress among Mexican Mestizos. Our data suggest that polymorphisms of HMOX1 and NQO1 genes are associated with a high risk of metabolic disorders, including high systolic and diastolic blood pressure, hypertriglyceridemia, and low HDL-c levels in Mexican Mestizo individuals. PMID:25933176

Association of HMOX1 and NQO1 Polymorphisms with Metabolic Syndrome Components.

PubMed

Martínez-Hernández, Angélica; Córdova, Emilio J; Rosillo-Salazar, Oscar; García-Ortíz, Humberto; Contreras-Cubas, Cecilia; Islas-Andrade, Sergio; Revilla-Monsalve, Cristina; Salas-Labadía, Consuelo; Orozco, Lorena

2015-01-01

Metabolic syndrome (MetS) is among the most important public health problems worldwide, and is recognized as a major risk factor for various illnesses, including type 2 diabetes mellitus, obesity, and cardiovascular diseases. Recently, oxidative stress has been suggested as part of MetS aetiology. The heme oxygenase 1 (HMOX1) and NADH:quinone oxidoreductase 1 (NQO1) genes are crucial mediators of cellular defence against oxidative stress. In the present study, we analysed the associations of HMOX1 (GT)n and NQO1 C609T polymorphisms with MetS and its components. Our study population comprised 735 Mexican Mestizos unrelated volunteers recruited from different tertiary health institutions from Mexico City. In order to know the HMOX1 (GT)n and NQO1 C609T allele frequencies in Amerindians, we included a population of 241 Amerindian native speakers. Their clinical and demographic data were recorded. The HMOX1 (GT)n polymorphism was genotyped using PCR and fluorescence technology. NQO1 C609T polymorphism genotyping was performed using TaqMan probes. Short allele (<25 GT repeats) of the HMOX1 polymorphism was associated with high systolic and diastolic blood pressure, and the T allele of the NQO1 C609T polymorphism was associated with increased triglyceride levels and decreased HDL-c levels, but only in individuals with MetS. This is the first study to analyse the association between MetS and genes involved in oxidative stress among Mexican Mestizos. Our data suggest that polymorphisms of HMOX1 and NQO1 genes are associated with a high risk of metabolic disorders, including high systolic and diastolic blood pressure, hypertriglyceridemia, and low HDL-c levels in Mexican Mestizo individuals.

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

PubMed Central

2012-01-01

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

Single-fiber myosin heavy chain polymorphism during postnatal development: modulation by hypothyroidism

NASA Technical Reports Server (NTRS)

di Maso, N. A.; Caiozzo, V. J.; Baldwin, K. M.

2000-01-01

The primary objective of this study was to follow the developmental time course of myosin heavy chain (MHC) isoform transitions in single fibers of the rodent plantaris muscle. Hypothyroidism was used in conjunction with single-fiber analyses to better describe a possible linkage between the neonatal and fast type IIB MHC isoforms during development. In contrast to the general concept that developmental MHC isoform transitions give rise to muscle fibers that express only a single MHC isoform, the single-fiber analyses revealed a very high degree of MHC polymorphism throughout postnatal development. In the adult state, MHC polymorphism was so pervasive that the rodent plantaris muscles contained approximately 12-15 different pools of fibers (i.e., fiber types). The degree of polymorphism observed at the single-fiber level made it difficult to determine specific developmental schemes analogous to those observed previously for the rodent soleus muscle. However, hypothyroidism was useful in that it confirmed a possible link between the developmental regulation of the neonatal and fast type IIB MHC isoforms.

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

PubMed Central

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

2004-01-01

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

The Longhorn Array Database (LAD): An Open-Source, MIAME compliant implementation of the Stanford Microarray Database (SMD)

PubMed Central

Killion, Patrick J; Sherlock, Gavin; Iyer, Vishwanath R

2003-01-01

Background The power of microarray analysis can be realized only if data is systematically archived and linked to biological annotations as well as analysis algorithms. Description The Longhorn Array Database (LAD) is a MIAME compliant microarray database that operates on PostgreSQL and Linux. It is a fully open source version of the Stanford Microarray Database (SMD), one of the largest microarray databases. LAD is available at Conclusions Our development of LAD provides a simple, free, open, reliable and proven solution for storage and analysis of two-color microarray data. PMID:12930545

Solubility and conversion of carbamazepine polymorphs in supercritical carbon dioxide.

PubMed

Bettini, R; Bonassi, L; Castoro, V; Rossi, A; Zema, L; Gazzaniga, A; Giordano, F

2001-06-01

The aim of this work was to investigate whether mixtures of carbamazepine polymorphs could be processed in supercritical (SC) CO(2) in order to obtain the pure stable crystalline phase. To accomplish this goal the solubility of carbamazepine polymorphs I and III in supercritical CO(2) was first assessed using a low solvent flux dynamic method. Mixtures of Form I and Form III were processed in dynamic or static conditions in SC-CO(2). Differential scanning calorimetry, Fourier transformed infrared spectroscopy, and powder X-ray diffractometry were used to analyse solid samples in terms of polymorph composition. It was found that Form I and Form III of carbamazepine have different solubility in supercritical CO(2) at 55 degrees C above 300 bar. Due to the transformation of the metastable form, conversion of Form I into Form III can be carried out on a binary mixture of the two polymorphs by treating the mixture at 55 degrees C and 350 bar, under both static and dynamic conditions, via its solubilization in supercritical CO(2).

Screening Mammalian Cells on a Hydrogel: Functionalized Small Molecule Microarray.

PubMed

Zhu, Biwei; Jiang, Bo; Na, Zhenkun; Yao, Shao Q

2017-01-01

Mammalian cell-based microarray technology has gained wide attention, for its plethora of promising applications. The platform is able to provide simultaneous information on multiple parameters for a given target, or even multiple target proteins, in a complex biological system. Here we describe the preparation of mammalian cell-based microarrays using selectively captured of human prostate cancer cells (PC-3). This platform was then used in controlled drug release and measuring the associated drug effects on these cancer cells.

Potential of carrageenans to protect drugs from polymorphic transformation.

PubMed

Schmidt, Andrea G; Wartewig, Siegfried; Picker, Katharina M

2003-07-01

Carrageenans were analysed in mixture with polymorphic drugs to test their potential for minimising polymorphic or pseudopolymorphic transitions, which are induced by the tableting process. The kappa-carrageenans Gelcarin GP-812 NF and Gelcarin GP-911 NF and the iota-carrageenan Gelcarin GP-379 NF were tested in comparison to the well-known tableting excipients microcrystalline cellulose (MCC), hydroxypropyl methylcellulose (HPMC), and dicalcium phosphate dihydrate (DCPD). Amorphous indomethacin was chosen as model drug since its well-known recrystallisation behaviour can be mechanically stimulated. Further on, theophylline monohydrate was used. Its dehydration is induced by tableting. Pure materials and mixtures containing 20% (w/w) drug were compressed up to different maximum relative densities. The data obtained during tableting were analysed by three-dimensional (3D) modelling. Afterwards tablets were broken and examined by Fourier transform Raman spectroscopy in order to determine the degree of transformation inside the tablet. For quantitative interpretation, the intensities of representative bands were used. Thermal analysis was used additionally. Using 3D modelling a decrease of plastic deformation can be noticed in the order HPMC>MCC>carrageenans, whereas DCPD represents an exception because of brittle fracture. Best hindrance of polymorphic transformation showed the carrageenans, the hindrance was slightly worse for HPMC. MCC and DCPD could not hinder transformation. A complete protection of the amorphous form could not be achieved. For theophylline monohydrate, the results were similar.

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

PubMed

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

2017-11-03

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

Development of a low-cost detection method for miRNA microarray.

PubMed

Li, Wei; Zhao, Botao; Jin, Youxin; Ruan, Kangcheng

2010-04-01

MicroRNA (miRNA) microarray is a powerful tool to explore the expression profiling of miRNA. The current detection method used in miRNA microarray is mainly fluorescence based, which usually requires costly detection system such as laser confocal scanner of tens of thousands of dollars. Recently, we developed a low-cost yet sensitive detection method for miRNA microarray based on enzyme-linked assay. In this approach, the biotinylated miRNAs were captured by the corresponding oligonucleotide probes immobilized on microarray slide; and then the biotinylated miRNAs would capture streptavidin-conjugated alkaline phosphatase. A purple-black precipitation on each biotinylated miRNA spot was produced by the enzyme catalytic reaction. It could be easily detected by a charge-coupled device digital camera mounted on a microscope, which lowers the detection cost more than 100 fold compared with that of fluorescence method. Our data showed that signal intensity of the spot correlates well with the biotinylated miRNA concentration and the detection limit for miRNAs is at least 0.4 fmol and the detection dynamic range spans about 2.5 orders of magnitude, which is comparable to that of fluorescence method.

Fluorescent labeling of NASBA amplified tmRNA molecules for microarray applications

PubMed Central

Scheler, Ott; Glynn, Barry; Parkel, Sven; Palta, Priit; Toome, Kadri; Kaplinski, Lauris; Remm, Maido; Maher, Majella; Kurg, Ants

2009-01-01

Background Here we present a novel promising microbial diagnostic method that combines the sensitivity of Nucleic Acid Sequence Based Amplification (NASBA) with the high information content of microarray technology for the detection of bacterial tmRNA molecules. The NASBA protocol was modified to include aminoallyl-UTP (aaUTP) molecules that were incorporated into nascent RNA during the NASBA reaction. Post-amplification labeling with fluorescent dye was carried out subsequently and tmRNA hybridization signal intensities were measured using microarray technology. Significant optimization of the labeled NASBA protocol was required to maintain the required sensitivity of the reactions. Results Two different aaUTP salts were evaluated and optimum final concentrations were identified for both. The final 2 mM concentration of aaUTP Li-salt in NASBA reaction resulted in highest microarray signals overall, being twice as high as the strongest signals with 1 mM aaUTP Na-salt. Conclusion We have successfully demonstrated efficient combination of NASBA amplification technology with microarray based hybridization detection. The method is applicative for many different areas of microbial diagnostics including environmental monitoring, bio threat detection, industrial process monitoring and clinical microbiology. PMID:19445684

Cloning of polymorphisms (COP): enrichment of polymorphic sequences from complex genomes

PubMed Central

Li, Jingfeng; Wang, Fuli; Zabarovska, Veronika; Wahlestedt, Claes; Zabarovsky, Eugene R.

2000-01-01

Here we describe a new procedure (cloning of polymorphisms, COP) for enrichment of single nucleotide polymorphisms (SNPs) that represent restriction fragment length polymorphisms (RFLPs). COP would be applicable to the isolation of SNPs from particular regions of the genome, e.g. CpG islands, chromosomal bands, YACs or PAC contigs. A combination of digestion with restriction enzymes, treatment with uracil-DNA glycosylase and mung bean nuclease, PCR amplification and purification with streptavidin magnetic beads was used to isolate polymorphic sequences from the genomes of two human samples. After only two cycles of enrichment, 80% of the isolated clones were found to contain RFLPs. A simple method for the PCR detection of these polymorphisms was also developed. PMID:10606669

LRP5 gene polymorphism and cortical bone.

PubMed

Lauretani, Fulvio; Cepollaro, Chiara; Bandinelli, Stefania; Cherubini, Antonio; Gozzini, Alessia; Masi, Laura; Falchetti, Alberto; Del Monte, Francesca; Carbonell-Sala, Silvia; Marini, Francesca; Tanini, Annalisa; Corsi, Anna Maria; Ceda, Gian Paolo; Brandi, Maria Luisa; Ferrucci, Luigi

2010-08-01

There is evidence that distinct genetic polymorphisms of LRP5 are associated with low Bone Mineral Density (BMD) and the risk of fracture. However, relationships between LRP5 polymorphisms and micro- and macro architectural bone characteristics assessed by pQCT have not been studied. The aim of the present study was to investigate the association of Ala1330Val and Val667Met polymorphisms in LRP5 gene with volumetric BMD (vBMD) and macro-architectural bone parameters in a population-based sample of men and women. We studied 959 participants of the InCHIANTI study (451 men and 508 women, age range: 21-94 yrs). Trabecular vBMD (vBMDt, mg/cm3), cortical vBMD (vBMDc, mg/cm3), cortical bone area (CBA, mm2) and cortical thickness (Ct.Th, mm) at the level of the tibia were assessed by peripheral quantitative computed tomography (pQCT). Ala1330Val and Val667Met genotypes were determined on genomic DNA by polymerase chain reaction-restriction fragment length polymorphism (PCR-RFLP). In age-adjusted analyses both LRP 1330-valine and LRP 667-metionin variants were associated with lower vBMDt in men (p<0.05), and lower vBMDt (p<0.05), Ct.Th (p<0.05) and CBA (p<0.05) in women. After adjusting for multiple confounders, only the association of LRP5 1330-valine and 667-metionin with CBA remained statistically significant (p=0.04 and p=0.01, respectively) in women. These findings suggest that both Ala1330Val and Val667Met LRP5 polymorphisms may affect the determination of geometric bone parameters in women.

Arylamine N-acetyltransferase 2 gene polymorphism in an Algerian population.

PubMed

Chelouti, Hiba; Khelil, Malika

2017-09-01

The arylamine N-acetyltransferase 2 (NAT2) is a key enzyme in the biotransformation of xenobiotics. NAT2 gene polymorphisms have been associated with the risk of isoniazid hepatotoxicity and these polymorphisms change among different populations. The objective of this study is to investigate NAT2 polymorphisms in order to predict the prevalence of NAT2 phenotype in an Algerian population. Genotyping of NAT2 was done using a PCR-RFLP method. Haplotype was analysed using the software package PHASE, version 2.0. The major haplotypes were NAT2*5B (23.72%), NAT2*6 A (18.61%), NAT2*4 (14.60%) and NAT2*5 F (10%). The average of the expected slow acetylator phenotype was 53%. Our results suggest that the high frequency of slow acetylator phenotype requires investigation into its possible association with ATDH.

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

PubMed

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.

Optimal Control of Shock Wave Turbulent Boundary Layer Interactions Using Micro-Array Actuation

NASA Technical Reports Server (NTRS)

Anderson, Bernhard H.; Tinapple, Jon; Surber, Lewis

2006-01-01

The intent of this study on micro-array flow control is to demonstrate the viability and economy of Response Surface Methodology (RSM) to determine optimal designs of micro-array actuation for controlling the shock wave turbulent boundary layer interactions within supersonic inlets and compare these concepts to conventional bleed performance. The term micro-array refers to micro-actuator arrays which have heights of 25 to 40 percent of the undisturbed supersonic boundary layer thickness. This study covers optimal control of shock wave turbulent boundary layer interactions using standard micro-vane, tapered micro-vane, and standard micro-ramp arrays at a free stream Mach number of 2.0. The effectiveness of the three micro-array devices was tested using a shock pressure rise induced by the 10 shock generator, which was sufficiently strong as to separate the turbulent supersonic boundary layer. The overall design purpose of the micro-arrays was to alter the properties of the supersonic boundary layer by introducing a cascade of counter-rotating micro-vortices in the near wall region. In this manner, the impact of the shock wave boundary layer (SWBL) interaction on the main flow field was minimized without boundary bleed.

High-Density Droplet Microarray of Individually Addressable Electrochemical Cells.

PubMed

Zhang, Huijie; Oellers, Tobias; Feng, Wenqian; Abdulazim, Tarik; Saw, En Ning; Ludwig, Alfred; Levkin, Pavel A; Plumeré, Nicolas

2017-06-06

Microarray technology has shown great potential for various types of high-throughput screening applications. The main read-out methods of most microarray platforms, however, are based on optical techniques, limiting the scope of potential applications of such powerful screening technology. Electrochemical methods possess numerous complementary advantages over optical detection methods, including its label-free nature, capability of quantitative monitoring of various reporter molecules, and the ability to not only detect but also address compositions of individual compartments. However, application of electrochemical methods for the purpose of high-throughput screening remains very limited. In this work, we develop a high-density individually addressable electrochemical droplet microarray (eDMA). The eDMA allows for the detection of redox-active reporter molecules irrespective of their electrochemical reversibility in individual nanoliter-sized droplets. Orthogonal band microelectrodes are arranged to form at their intersections an array of three-electrode systems for precise control of the applied potential, which enables direct read-out of the current related to analyte detection. The band microelectrode array is covered with a layer of permeable porous polymethacrylate functionalized with a highly hydrophobic-hydrophilic pattern, forming spatially separated nanoliter-sized droplets on top of each electrochemical cell. Electrochemical characterization of single droplets demonstrates that the underlying electrode system is accessible to redox-active molecules through the hydrophilic polymeric pattern and that the nonwettable hydrophobic boundaries can spatially separate neighboring cells effectively. The eDMA technology opens the possibility to combine the high-throughput biochemical or living cell screenings using the droplet microarray platform with the sequential electrochemical read-out of individual droplets.

MAGMA: analysis of two-channel microarrays made easy.

PubMed

Rehrauer, Hubert; Zoller, Stefan; Schlapbach, Ralph

2007-07-01

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

Multiclassifier information fusion methods for microarray pattern recognition

NASA Astrophysics Data System (ADS)

Braun, Jerome J.; Glina, Yan; Judson, Nicholas; Herzig-Marx, Rachel

2004-04-01

This paper addresses automatic recognition of microarray patterns, a capability that could have a major significance for medical diagnostics, enabling development of diagnostic tools for automatic discrimination of specific diseases. The paper presents multiclassifier information fusion methods for microarray pattern recognition. The input space partitioning approach based on fitness measures that constitute an a-priori gauging of classification efficacy for each subspace is investigated. Methods for generation of fitness measures, generation of input subspaces and their use in the multiclassifier fusion architecture are presented. In particular, two-level quantification of fitness that accounts for the quality of each subspace as well as the quality of individual neighborhoods within the subspace is described. Individual-subspace classifiers are Support Vector Machine based. The decision fusion stage fuses the information from mulitple SVMs along with the multi-level fitness information. Final decision fusion stage techniques, including weighted fusion as well as Dempster-Shafer theory based fusion are investigated. It should be noted that while the above methods are discussed in the context of microarray pattern recognition, they are applicable to a broader range of discrimination problems, in particular to problems involving a large number of information sources irreducible to a low-dimensional feature space.

Patterns of genetic diversity in the polymorphic ground snake (Sonora semiannulata).

PubMed

Cox, Christian L; Chippindale, Paul T

2014-08-01

We evaluated the genetic diversity of a snake species with color polymorphism to understand the evolutionary processes that drive genetic structure across a large geographic region. Specifically, we analyzed genetic structure of the highly polymorphic ground snake, Sonora semiannulata, (1) among populations, (2) among color morphs (3) at regional and local spatial scales, using an amplified fragment length polymorphism dataset and multiple population genetic analyses, including FST-based and clustering analytical techniques. Based upon these methods, we found that there was moderate to low genetic structure among populations. However, this diversity was not associated with geographic locality at either spatial scale. Similarly, we found no evidence for genetic divergence among color morphs at either spatial scale. These results suggest that despite dramatic color polymorphism, this phenotypic diversity is not a major driver of genetic diversity within or among populations of ground snakes. We suggest that there are two mechanisms that could explain existing genetic diversity in ground snakes: recent range expansion from a genetically diverse founder population and current or recent gene flow among populations. Our findings have further implications for the types of color polymorphism that may generate genetic diversity in snakes.

An alternative method to amplify RNA without loss of signal conservation for expression analysis with a proteinase DNA microarray in the ArrayTube format.

PubMed

Schüler, Susann; Wenz, Ingrid; Wiederanders, B; Slickers, P; Ehricht, R

2006-06-12

alternative method for detecting even low expressed genes by microarray experiments in a highly reproducible and sensitive manner. Preservation of signal integrity is demonstrated out by QRT-PCR measurements. The little amounts of total RNA necessary for the analyses make this method applicable for investigations with limited material as in clinical samples from, for example, organ or tumour biopsies. Those are arguments in favour of the high potential of our assay compared to established procedures for amplification within the field of diagnostic expression profiling. Nevertheless, the screening character of microarray data must be mentioned, and independent methods should verify the results.

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

PubMed

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.

Functional Analyses of NSF1 in Wine Yeast Using Interconnected Correlation Clustering and Molecular Analyses

PubMed Central

Bessonov, Kyrylo; Walkey, Christopher J.; Shelp, Barry J.; van Vuuren, Hennie J. J.; Chiu, David; van der Merwe, George

2013-01-01

Analyzing time-course expression data captured in microarray datasets is a complex undertaking as the vast and complex data space is represented by a relatively low number of samples as compared to thousands of available genes. Here, we developed the Interdependent Correlation Clustering (ICC) method to analyze relationships that exist among genes conditioned on the expression of a specific target gene in microarray data. Based on Correlation Clustering, the ICC method analyzes a large set of correlation values related to gene expression profiles extracted from given microarray datasets. ICC can be applied to any microarray dataset and any target gene. We applied this method to microarray data generated from wine fermentations and selected NSF1, which encodes a C2H2 zinc finger-type transcription factor, as the target gene. The validity of the method was verified by accurate identifications of the previously known functional roles of NSF1. In addition, we identified and verified potential new functions for this gene; specifically, NSF1 is a negative regulator for the expression of sulfur metabolism genes, the nuclear localization of Nsf1 protein (Nsf1p) is controlled in a sulfur-dependent manner, and the transcription of NSF1 is regulated by Met4p, an important transcriptional activator of sulfur metabolism genes. The inter-disciplinary approach adopted here highlighted the accuracy and relevancy of the ICC method in mining for novel gene functions using complex microarray datasets with a limited number of samples. PMID:24130853

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

PubMed

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

PubMed

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

2012-01-01

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

Fully automated analysis of multi-resolution four-channel micro-array genotyping data

NASA Astrophysics Data System (ADS)

Abbaspour, Mohsen; Abugharbieh, Rafeef; Podder, Mohua; Tebbutt, Scott J.

2006-03-01

We present a fully-automated and robust microarray image analysis system for handling multi-resolution images (down to 3-micron with sizes up to 80 MBs per channel). The system is developed to provide rapid and accurate data extraction for our recently developed microarray analysis and quality control tool (SNP Chart). Currently available commercial microarray image analysis applications are inefficient, due to the considerable user interaction typically required. Four-channel DNA microarray technology is a robust and accurate tool for determining genotypes of multiple genetic markers in individuals. It plays an important role in the state of the art trend where traditional medical treatments are to be replaced by personalized genetic medicine, i.e. individualized therapy based on the patient's genetic heritage. However, fast, robust, and precise image processing tools are required for the prospective practical use of microarray-based genetic testing for predicting disease susceptibilities and drug effects in clinical practice, which require a turn-around timeline compatible with clinical decision-making. In this paper we have developed a fully-automated image analysis platform for the rapid investigation of hundreds of genetic variations across multiple genes. Validation tests indicate very high accuracy levels for genotyping results. Our method achieves a significant reduction in analysis time, from several hours to just a few minutes, and is completely automated requiring no manual interaction or guidance.

Microarray analysis of potential genes in the pathogenesis of recurrent oral ulcer.

PubMed

Han, Jingying; He, Zhiwei; Li, Kun; Hou, Lu

2015-01-01

Recurrent oral ulcer seriously threatens patients' daily life and health. This study investigated potential genes and pathways that participate in the pathogenesis of recurrent oral ulcer by high throughput bioinformatic analysis. RT-PCR and Western blot were applied to further verify screened interleukins effect. Recurrent oral ulcer related genes were collected from websites and papers, and further found out from Human Genome 280 6.0 microarray data. Each pathway of recurrent oral ulcer related genes were got through chip hybridization. RT-PCR was applied to test four recurrent oral ulcer related genes to verify the microarray data. Data transformation, scatter plot, clustering analysis, and expression pattern analysis were used to analyze recurrent oral ulcer related gene expression changes. Recurrent oral ulcer gene microarray was successfully established. Microarray showed that 551 genes involved in recurrent oral ulcer activity and 196 genes were recurrent oral ulcer related genes. Of them, 76 genes up-regulated, 62 genes down-regulated, and 58 genes up-/down-regulated. Total expression level up-regulated 752 times (60%) and down-regulated 485 times (40%). IL-2 plays an important role in the occurrence, development and recurrence of recurrent oral ulcer on the mRNA and protein levels. Gene microarray can be used to analyze potential genes and pathways in recurrent oral ulcer. IL-2 may be involved in the pathogenesis of recurrent oral ulcer.

MicroGen: a MIAME compliant web system for microarray experiment information and workflow management.

PubMed

Burgarella, Sarah; Cattaneo, Dario; Pinciroli, Francesco; Masseroli, Marco

2005-12-01

Improvements of bio-nano-technologies and biomolecular techniques have led to increasing production of high-throughput experimental data. Spotted cDNA microarray is one of the most diffuse technologies, used in single research laboratories and in biotechnology service facilities. Although they are routinely performed, spotted microarray experiments are complex procedures entailing several experimental steps and actors with different technical skills and roles. During an experiment, involved actors, who can also be located in a distance, need to access and share specific experiment information according to their roles. Furthermore, complete information describing all experimental steps must be orderly collected to allow subsequent correct interpretation of experimental results. We developed MicroGen, a web system for managing information and workflow in the production pipeline of spotted microarray experiments. It is constituted of a core multi-database system able to store all data completely characterizing different spotted microarray experiments according to the Minimum Information About Microarray Experiments (MIAME) standard, and of an intuitive and user-friendly web interface able to support the collaborative work required among multidisciplinary actors and roles involved in spotted microarray experiment production. MicroGen supports six types of user roles: the researcher who designs and requests the experiment, the spotting operator, the hybridisation operator, the image processing operator, the system administrator, and the generic public user who can access the unrestricted part of the system to get information about MicroGen services. MicroGen represents a MIAME compliant information system that enables managing workflow and supporting collaborative work in spotted microarray experiment production.

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

PubMed Central

2012-01-01

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

Challenges of microarray applications for microbial detection and gene expression profiling in food

USDA-ARS?s Scientific Manuscript database

Microarray technology represents one of the latest advances in molecular biology. The diverse types of microarrays have been applied to clinical and environmental microbiology, microbial ecology, and in human, veterinary, and plant diagnostics. Since multiple genes can be analyzed simultaneously, ...

Hybrid genetic algorithm-neural network: feature extraction for unpreprocessed microarray data.

PubMed

Tong, Dong Ling; Schierz, Amanda C

2011-09-01

Suitable techniques for microarray analysis have been widely researched, particularly for the study of marker genes expressed to a specific type of cancer. Most of the machine learning methods that have been applied to significant gene selection focus on the classification ability rather than the selection ability of the method. These methods also require the microarray data to be preprocessed before analysis takes place. The objective of this study is to develop a hybrid genetic algorithm-neural network (GANN) model that emphasises feature selection and can operate on unpreprocessed microarray data. The GANN is a hybrid model where the fitness value of the genetic algorithm (GA) is based upon the number of samples correctly labelled by a standard feedforward artificial neural network (ANN). The model is evaluated by using two benchmark microarray datasets with different array platforms and differing number of classes (a 2-class oligonucleotide microarray data for acute leukaemia and a 4-class complementary DNA (cDNA) microarray dataset for SRBCTs (small round blue cell tumours)). The underlying concept of the GANN algorithm is to select highly informative genes by co-evolving both the GA fitness function and the ANN weights at the same time. The novel GANN selected approximately 50% of the same genes as the original studies. This may indicate that these common genes are more biologically significant than other genes in the datasets. The remaining 50% of the significant genes identified were used to build predictive models and for both datasets, the models based on the set of genes extracted by the GANN method produced more accurate results. The results also suggest that the GANN method not only can detect genes that are exclusively associated with a single cancer type but can also explore the genes that are differentially expressed in multiple cancer types. The results show that the GANN model has successfully extracted statistically significant genes from the

Polymorphous computing fabric

DOEpatents

Wolinski, Christophe Czeslaw [Los Alamos, NM; Gokhale, Maya B [Los Alamos, NM; McCabe, Kevin Peter [Los Alamos, NM

2011-01-18

Fabric-based computing systems and methods are disclosed. A fabric-based computing system can include a polymorphous computing fabric that can be customized on a per application basis and a host processor in communication with said polymorphous computing fabric. The polymorphous computing fabric includes a cellular architecture that can be highly parameterized to enable a customized synthesis of fabric instances for a variety of enhanced application performances thereof. A global memory concept can also be included that provides the host processor random access to all variables and instructions associated with the polymorphous computing fabric.

Constructing Tissue Microarrays: Protocols and Methods Considering Potential Advantages and Disadvantages for Downstream Use.

PubMed

Bingle, Lynne; Fonseca, Felipe P; Farthing, Paula M

2017-01-01

Tissue microarrays were first constructed in the 1980s but were used by only a limited number of researchers for a considerable period of time. In the last 10 years there has been a dramatic increase in the number of publications describing the successful use of tissue microarrays in studies aimed at discovering and validating biomarkers. This, along with the increased availability of both manual and automated microarray builders on the market, has encouraged even greater use of this novel and powerful tool. This chapter describes the basic techniques required to build a tissue microarray using a manual method in order that the theory behind the practical steps can be fully explained. Guidance is given to ensure potential disadvantages of the technique are fully considered.

Catalog of MicroRNA Seed Polymorphisms in Vertebrates

PubMed Central

Calin, George Adrian; Horvat, Simon; Jiang, Zhihua; Dovc, Peter; Kunej, Tanja

2012-01-01

MicroRNAs (miRNAs) are a class of non-coding RNA that plays an important role in posttranscriptional regulation of mRNA. Evidence has shown that miRNA gene variability might interfere with its function resulting in phenotypic variation and disease susceptibility. A major role in miRNA target recognition is ascribed to complementarity with the miRNA seed region that can be affected by polymorphisms. In the present study, we developed an online tool for the detection of miRNA polymorphisms (miRNA SNiPer) in vertebrates (http://www.integratomics-time.com/miRNA-SNiPer) and generated a catalog of miRNA seed region polymorphisms (miR-seed-SNPs) consisting of 149 SNPs in six species. Although a majority of detected polymorphisms were due to point mutations, two consecutive nucleotide substitutions (double nucleotide polymorphisms, DNPs) were also identified in nine miRNAs. We determined that miR-SNPs are frequently located within the quantitative trait loci (QTL), chromosome fragile sites, and cancer susceptibility loci, indicating their potential role in the genetic control of various complex traits. To test this further, we performed an association analysis between the mmu-miR-717 seed SNP rs30372501, which is polymorphic in a large number of standard inbred strains, and all phenotypic traits in these strains deposited in the Mouse Phenome Database. Analysis showed a significant association between the mmu-miR-717 seed SNP and a diverse array of traits including behavior, blood-clinical chemistry, body weight size and growth, and immune system suggesting that seed SNPs can indeed have major pleiotropic effects. The bioinformatics analyses, data and tools developed in the present study can serve researchers as a starting point in testing more targeted hypotheses and designing experiments using optimal species or strains for further mechanistic studies. PMID:22303453

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

PubMed Central

Kadarmideen, Haja N; Watson-haigh, Nathan S

2012-01-01

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

Polymorphism and haplotype analyses of swine leukocyte antigen DQA exons 2, 3, 4, and their associations with piglet diarrhea in Chinese native pig.

PubMed

Huang, X Y; Yang, Q L; Yuan, J H; Gun, S B

2015-09-08

In this study, 290 Chinese native Yantai black pig piglets were investigated to identify gene polymorphisms, for haplotype reconstruction, and to determine the association between piglet diarrhea and swine leukocyte antigen (SLA) class II DQA exons 2, 3, and 4 by polymerase chain reaction-single stranded conformational polymorphism and cloning sequencing. The results showed that the 5, 8, and 7 genotypes were identified from SLA-DQA exon 2, 3, and 4, respectively, based on the single-stranded conformational polymorphism banding patterns and found a novel allele D in exon 2 and 2 novel mutational sites of allele C (c.4828T>C) and allele F (c.4617T>C) in exon 3. Polymorphism information content testing showed that exon 2 was moderately polymorphic and that exons-3 and -4 loci were highly polymorphic. The piglet diarrhea scores for genotypes AB (1.40 ± 0.14) and AC (1.54 ± 0.17) in exon 2, AA (1.22 ± 0.32), BC (1.72 ± 0.13), DD (1.67 ± 0.35), and CF (1.22 ± 0.45) in exon 3, and AD (2.35 ± 0.25) in exon 4 were significantly higher than those for the other genotypes (P ≤ 0.05) in DQA exons. There were 14 reconstructed haplotypes in the 3 exons from 290 individuals and Hap12 may be the diarrhea-resistant gene. Haplotype distribution was extremely uneven, and the SLA-DQA gene showed genetic linkage. In this study, we identified molecular genetic markers and provided a theoretical foundation for future pig anti-disease resistance breeding.

Associations between period 3 gene polymorphisms and sleep- /chronotype-related variables in patients with late-life insomnia.

PubMed

Mansour, Hader A; Wood, Joel; Chowdari, Kodavali V; Tumuluru, Divya; Bamne, Mikhil; Monk, Timothy H; Hall, Martica H; Buysse, Daniel J; Nimgaonkar, Vishwajit L

2017-01-01

A variable number tandem repeat polymorphism (VNTR) in the period 3 (PER3) gene has been associated with heritable sleep and circadian variables, including self-rated chronotypes, polysomnographic (PSG) variables, insomnia and circadian sleep-wake disorders. This report describes novel molecular and clinical analyses of PER3 VNTR polymorphisms to better define their functional consequences. As the PER3 VNTR is located in the exonic (protein coding) region of PER3, we initially investigated whether both alleles (variants) are transcribed into messenger RNA in human fibroblasts. The VNTR showed bi-allelic gene expression. We next investigated genetic associations in relation to clinical variables in 274 older adult Caucasian individuals. Independent variables included genotypes for the PER3 VNTR as well as a representative set of single nucleotide polymorphisms (SNPs) that tag common variants at the PER3 locus (linkage disequilibrium (LD) between genetic variants < 0.5). In order to comprehensively evaluate variables analyzed individually in prior analyses, dependent measures included PSG total sleep time and sleep latency, self-rated chronotype, estimated with the Composite Scale (CS), and lifestyle regularity, estimated using the social rhythm metric (SRM). Initially, genetic polymorphisms were individually analyzed in relation to each outcome variable using analysis of variance (ANOVA). Nominally significant associations were further tested using regression analyses that incorporated individual ANOVA-associated DNA variants as potential predictors and each of the selected sleep/circadian variables as outcomes. The covariates included age, gender, body mass index and an index of medical co-morbidity. Significant genetic associations with the VNTR were not detected with the sleep or circadian variables. Nominally significant associations were detected between SNP rs1012477 and CS scores (p = 0.003) and between rs10462021 and SRM (p = 0.047); rs11579477 and average

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

PubMed Central

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

2009-01-01

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

Association of Interleukin-10 gene promoter polymorphisms with obstructive sleep apnea.

PubMed

Özdaş, Sibel; Özdaş, Talih; Acar, Mustafa; Erbek, Selim S; Köseoğlu, Sabri; Göktürk, Gökhan; Izbirak, Afife

2016-05-01

Interleukin-10 (IL) is an anti-inflammatory cytokine that regulates normal sleep patterns, and recent studies have reported that it is a potential useful biomarker to identify presence and severity of sleep apnea syndrome (OSAS). Promoter polymorphisms of IL-10 gene have been associated with altered expression levels, which contributes to OSAS. The aim of this study was to determine the prevalence of -1082 G/A, -819 C/T, and -592 C/A promoter polymorphisms of IL-10 gene in individuals with OSAS and controls. An open-label study was performed in the Otorhinolaryngology and Sleep Disorders Outpatient Clinics. One hundred four cases with OSAS were included as the study group, and 78 individuals without OSAS were included as the controls. DNAs were extracted from peripheral blood leukocytes, and the sites that encompassed those polymorphisms were identified by DNA sequencing analyses. Data were analyzed with SNPStats and multifactor dimensionality reduction (MDR) software. The prevalence of OSAS was higher in males in the study group when compared to controls (P = 0.0003). The IL-10-1082 G/A, -819 C/T, and -592 C/A SNPs, and their minor alleles were associated with a significantly increased risk for OSAS compared to the controls (P ˂ 0.05 for all). Furthermore, ATA haplotype frequency was significantly higher in the study group compared to the control group, but the GCC haplotype frequency was lower (P = 0.0001 and P = 0.0001). As indicated in MDR analysis, combinations of IL-10 gene were associated with OSAS in single-, double-, and triple-locus analyses. The prevalences of the IL-10 gene promoter polymorphisms were different in OSAS patients and the controls in Turkish population. IL-10 gene polymorphisms may lead to altered inflammatory cascade, which might contribute to OSAS. Further studies on larger cohorts are needed to validate our findings.

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

PubMed Central

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. PMID:26468293

Identification of embryonic pancreatic genes using Xenopus DNA microarrays.

PubMed

Hayata, Tadayoshi; Blitz, Ira L; Iwata, Nahoko; Cho, Ken W Y

2009-06-01

The pancreas is both an exocrine and endocrine endodermal organ involved in digestion and glucose homeostasis. During embryogenesis, the anlagen of the pancreas arise from dorsal and ventral evaginations of the foregut that later fuse to form a single organ. To better understand the molecular genetics of early pancreas development, we sought to isolate markers that are uniquely expressed in this tissue. Microarray analysis was performed comparing dissected pancreatic buds, liver buds, and the stomach region of tadpole stage Xenopus embryos. A total of 912 genes were found to be differentially expressed between these organs during early stages of organogenesis. K-means clustering analysis predicted 120 of these genes to be specifically enriched in the pancreas. Of these, we report on the novel expression patterns of 24 genes. Our analyses implicate the involvement of previously unsuspected signaling pathways during early pancreas development. Developmental Dynamics 238:1455-1466, 2009. (c) 2009 Wiley-Liss, Inc.

A Protein Microarray ELISA for the Detection of Botulinum neurotoxin A

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

Varnum, Susan M.

An enzyme-linked immunosorbent assay (ELISA) microarray was developed for the specific and sensitive detection of botulinum neurotoxin A (BoNT/A), using high-affinity recombinant monoclonal antibodies against the receptor binding domain of the heavy chain of BoNT/A. The ELISA microarray assay, because of its sensitivity, offers a screening test with detection limits comparable to the mouse bioassay, with results available in hours instead of days.

Homogeneous versus heterogeneous probes for microbial ecological microarrays.

PubMed

Bae, Jin-Woo; Park, Yong-Ha

2006-07-01

Microbial ecological microarrays have been developed for investigating the composition and functions of microorganism communities in environmental niches. These arrays include microbial identification microarrays, which use oligonucleotides, gene fragments or microbial genomes as probes. In this article, the advantages and disadvantages of each type of probe are reviewed. Oligonucleotide probes are currently useful for probing uncultivated bacteria that are not amenable to gene fragment probing, whereas the functional gene fragments amplified randomly from microbial genomes require phylogenetic and hierarchical categorization before use as microbial identification probes, despite their high resolution for both specificity and sensitivity. Until more bacteria are sequenced and gene fragment probes are thoroughly validated, heterogeneous bacterial genome probes will provide a simple, sensitive and quantitative tool for exploring the ecosystem structure.

Preproghrelin Leu72Met polymorphism in patients with type 2 diabetes mellitus.

PubMed

Ukkola, O; Kesäniemi, Y A

2003-10-01

The association between the Leu72Met polymorphism of the preproghrelin gene and diabetic complications was examined in patients with type 2 diabetes mellitus. A total of 258 patients with type 2 diabetes mellitus and 522 control subjects were screened. Genotypes were determined by polymerase chain reaction technique. The diagnosis of coronary heart disease was based on clinical and ECG criteria. Laboratory analyses were carried out in the hospital laboratory. No differences in the genotype distributions and allele frequencies of the preproghrelin Leu72Met polymorphism were found between type 2 diabetes mellitus patients and controls. The polymorphism was not associated with macro- or micro-angiopathy or hypertension. However, Leu72Met polymorphism was associated with serum creatinine (P = 0.006) and lipoprotein(a) [Lp(a)] levels (P = 0.006) with Leu72Leu subjects showing the highest values. This association was observed only amongst diabetic group. The Leu72Met polymorphism of the preproghrelin gene was not related to cardiovascular disease in type 2 diabetes mellitus patients. Leu72Met polymorphism was, however, associated with serum creatinine and Lp(a) levels in diabetic patients. The mechanism might be associated with a possible change in ghrelin product and its somatotropic effect.

Genetic polymorphisms in ESR1 and ESR2 genes, and risk of hypospadias in a multiethnic study population.

PubMed

Choudhry, Shweta; Baskin, Laurence S; Lammer, Edward J; Witte, John S; Dasgupta, Sudeshna; Ma, Chen; Surampalli, Abhilasha; Shen, Joel; Shaw, Gary M; Carmichael, Suzan L

2015-05-01

Estrogenic endocrine disruptors acting via estrogen receptors α (ESR1) and β (ESR2) have been implicated in the etiology of hypospadias, a common congenital malformation of the male external genitalia. We determined the association of single nucleotide polymorphisms in ESR1 and ESR2 genes with hypospadias in a racially/ethnically diverse study population of California births. We investigated the relationship between hypospadias and 108 ESR1 and 36 ESR2 single nucleotide polymorphisms in 647 cases and 877 population based nonmalformed controls among infants born in selected California counties from 1990 to 2003. Subgroup analyses were performed by race/ethnicity (nonHispanic white and Hispanic subjects) and by hypospadias severity (mild to moderate and severe). Odds ratios for 33 of the 108 ESR1 single nucleotide polymorphisms had p values less than 0.05 (p = 0.05 to 0.007) for risk of hypospadias. However, none of the 36 ESR2 single nucleotide polymorphisms was significantly associated. In stratified analyses the association results were consistent by disease severity but different sets of single nucleotide polymorphisms were significantly associated with hypospadias in nonHispanic white and Hispanic subjects. Due to high linkage disequilibrium across the single nucleotide polymorphisms, haplotype analyses were conducted and identified 6 haplotype blocks in ESR1 gene that had haplotypes significantly associated with an increased risk of hypospadias (OR 1.3 to 1.8, p = 0.04 to 0.00001). Similar to single nucleotide polymorphism analysis, different ESR1 haplotypes were associated with risk of hypospadias in nonHispanic white and Hispanic subjects. No significant haplotype association was observed for ESR2. The data provide evidence that ESR1 single nucleotide polymorphisms and haplotypes influence the risk of hypospadias in white and Hispanic subjects, and warrant further examination in other study populations. Copyright © 2015 American Urological Association

Living-Cell Microarrays

PubMed Central

Yarmush, Martin L.; King, Kevin R.

2011-01-01

Living cells are remarkably complex. To unravel this complexity, living-cell assays have been developed that allow delivery of experimental stimuli and measurement of the resulting cellular responses. High-throughput adaptations of these assays, known as living-cell microarrays, which are based on microtiter plates, high-density spotting, microfabrication, and microfluidics technologies, are being developed for two general applications: (a) to screen large-scale chemical and genomic libraries and (b) to systematically investigate the local cellular microenvironment. These emerging experimental platforms offer exciting opportunities to rapidly identify genetic determinants of disease, to discover modulators of cellular function, and to probe the complex and dynamic relationships between cells and their local environment. PMID:19413510

Genetic polymorphisms for estimating risk of atrial fibrillation: a literature-based meta-analysis

PubMed Central

Smith, J. Gustav; Almgren, Peter; Engström, Gunnar; Hedblad, Bo; Platonov, Pyotr G.; Newton-Cheh, Christopher; Melander, Olle

2013-01-01

Objectives Genome-wide association studies have recently identified genetic polymorphisms associated with common, etiologically complex diseases, for which direct-to-consumer genetic testing with provision of absolute genetic risk estimates is marketed by commercial companies. Polymorphisms associated with atrial fibrillation (AF) have shown relatively large risk estimates but the robustness of such estimates across populations and study designs has not been studied. Design A systematic literature review with meta-analysis and assessment of between-study heterogeneity was performed for single nucleotide polymorphisms (SNPs) in the six genetic regions associated with AF in genome-wide or candidate gene studies. Results Data from 18 samples of European ancestry (n=12,100 cases; 115,702 controls) were identified for the SNP on chromosome 4q25 (rs220733), 16 samples (n=12,694 cases; 132,602 controls) for the SNP on 16q22 (rs2106261) and 4 samples (n=5,272 cases; 59,725 controls) for the SNP in KCNH2 (rs1805123). Only the discovery studies were identified for SNPs on 1q21 and in GJA5 and IL6R, why no meta-analyses were performed for those SNPs. In overall random-effects meta-analyses, association with AF was observed for both SNPs from genome-wide studies on 4q25 (OR 1.67, 95% CI=1.50–1.86, p=2×10−21) and 16q22 (OR 1.21, 95% CI=1.13–1.29, p=1×10−8), but not the SNP in KCNH2 from candidate gene studies (p=0.15). There was substantial effect heterogeneity across case-control and cross-sectional studies for both polymorphisms (I2=0.50–0.78, p<0.05), but not across prospective cohort studies (I2=0.39, p=0.15). Both polymorphisms were robustly associated with AF for each study design individually (p<0.05). Conclusions In meta-analyses including up to 150,000 individuals, polymorphisms in two genetic regions were robustly associated with AF across all study designs but with substantial context-dependency of risk estimates. PMID:22690879

CONFIRMING MICROARRAY DATA--IS IT REALLY NECESSARY?

EPA Science Inventory

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...

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

PubMed

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

2016-05-21

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

Gene Expression Browser: Large-Scale and Cross-Experiment Microarray Data Management, Search & Visualization

USDA-ARS?s Scientific Manuscript database

The amount of microarray gene expression data in public repositories has been increasing exponentially for the last couple of decades. High-throughput microarray data integration and analysis has become a critical step in exploring the large amount of expression data for biological discovery. Howeve...

Performance of automated scoring of ER, PR, HER2, CK5/6 and EGFR in breast cancer tissue microarrays in the Breast Cancer Association Consortium

PubMed Central

Howat, William J; Blows, Fiona M; Provenzano, Elena; Brook, Mark N; Morris, Lorna; Gazinska, Patrycja; Johnson, Nicola; McDuffus, Leigh‐Anne; Miller, Jodi; Sawyer, Elinor J; Pinder, Sarah; van Deurzen, Carolien H M; Jones, Louise; Sironen, Reijo; Visscher, Daniel; Caldas, Carlos; Daley, Frances; Coulson, Penny; Broeks, Annegien; Sanders, Joyce; Wesseling, Jelle; Nevanlinna, Heli; Fagerholm, Rainer; Blomqvist, Carl; Heikkilä, Päivi; Ali, H Raza; Dawson, Sarah‐Jane; Figueroa, Jonine; Lissowska, Jolanta; Brinton, Louise; Mannermaa, Arto; Kataja, Vesa; Kosma, Veli‐Matti; Cox, Angela; Brock, Ian W; Cross, Simon S; Reed, Malcolm W; Couch, Fergus J; Olson, Janet E; Devillee, Peter; Mesker, Wilma E; Seyaneve, Caroline M; Hollestelle, Antoinette; Benitez, Javier; Perez, Jose Ignacio Arias; Menéndez, Primitiva; Bolla, Manjeet K; Easton, Douglas F; Schmidt, Marjanka K; Pharoah, Paul D; Sherman, Mark E

2014-01-01

Abstract Breast cancer risk factors and clinical outcomes vary by tumour marker expression. However, individual studies often lack the power required to assess these relationships, and large‐scale analyses are limited by the need for high throughput, standardized scoring methods. To address these limitations, we assessed whether automated image analysis of immunohistochemically stained tissue microarrays can permit rapid, standardized scoring of tumour markers from multiple studies. Tissue microarray sections prepared in nine studies containing 20 263 cores from 8267 breast cancers stained for two nuclear (oestrogen receptor, progesterone receptor), two membranous (human epidermal growth factor receptor 2 and epidermal growth factor receptor) and one cytoplasmic (cytokeratin 5/6) marker were scanned as digital images. Automated algorithms were used to score markers in tumour cells using the Ariol system. We compared automated scores against visual reads, and their associations with breast cancer survival. Approximately 65–70% of tissue microarray cores were satisfactory for scoring. Among satisfactory cores, agreement between dichotomous automated and visual scores was highest for oestrogen receptor (Kappa = 0.76), followed by human epidermal growth factor receptor 2 (Kappa = 0.69) and progesterone receptor (Kappa = 0.67). Automated quantitative scores for these markers were associated with hazard ratios for breast cancer mortality in a dose‐response manner. Considering visual scores of epidermal growth factor receptor or cytokeratin 5/6 as the reference, automated scoring achieved excellent negative predictive value (96–98%), but yielded many false positives (positive predictive value = 30–32%). For all markers, we observed substantial heterogeneity in automated scoring performance across tissue microarrays. Automated analysis is a potentially useful tool for large‐scale, quantitative scoring of immunohistochemically stained tissue

Plasmonically amplified fluorescence bioassay with microarray format

NASA Astrophysics Data System (ADS)

Gogalic, S.; Hageneder, S.; Ctortecka, C.; Bauch, M.; Khan, I.; Preininger, Claudia; Sauer, U.; Dostalek, J.

2015-05-01

Plasmonic amplification of fluorescence signal in bioassays with microarray detection format is reported. A crossed relief diffraction grating was designed to couple an excitation laser beam to surface plasmons at the wavelength overlapping with the absorption and emission bands of fluorophore Dy647 that was used as a label. The surface of periodically corrugated sensor chip was coated with surface plasmon-supporting gold layer and a thin SU8 polymer film carrying epoxy groups. These groups were employed for the covalent immobilization of capture antibodies at arrays of spots. The plasmonic amplification of fluorescence signal on the developed microarray chip was tested by using interleukin 8 sandwich immunoassay. The readout was performed ex situ after drying the chip by using a commercial scanner with high numerical aperture collecting lens. Obtained results reveal the enhancement of fluorescence signal by a factor of 5 when compared to a regular glass chip.

Microarray Technology for the Diagnosis of Fetal Chromosomal Aberrations: Which Platform Should We Use?

PubMed Central

Karampetsou, Evangelia; Morrogh, Deborah; Chitty, Lyn

2014-01-01

The advantage of microarray (array) over conventional karyotype for the diagnosis of fetal pathogenic chromosomal anomalies has prompted the use of microarrays in prenatal diagnostics. In this review we compare the performance of different array platforms (BAC, oligonucleotide CGH, SNP) and designs (targeted, whole genome, whole genome, and targeted, custom) and discuss their advantages and disadvantages in relation to prenatal testing. We also discuss the factors to consider when implementing a microarray testing service for the diagnosis of fetal chromosomal aberrations. PMID:26237396

Pregnane X Receptor Polymorphisms and Risk of Inflammatory Bowel Disease: A Meta-Analysis.

PubMed

Guo, Xiaolan; Yan, Ming

2017-08-01

Pregnane X receptor (PXR) gene polymorphisms have been widely studied in terms of the association with inflammatory bowel disease (IBD), with inconsistent results. The present meta-analysis was performed to assess the association between PXR gene polymorphisms and the susceptibility of IBD, Crohn's disease (CD), and ulcerative colitis (UC). PubMed, Wanfang, and CNKI databases were searched for eligible studies before November 1, 2016. Pooled odds ratios (ORs) and 95% confidence intervals (95% CIs) were used to calculate the various genetic models using either a fixed-effect or a random-effect model. The heterogeneity of the included studies was examined with Cochran Q and I 2 statistics. Begg's rank correlation test and Egger's linear regression test were used to assess the publication bias. A total of six studies with 4248 cases and 3853 controls were included in this meta-analysis. Three PXR gene polymorphisms were evaluated: rs1523127, rs2276707, and rs6785049. Our analyses of rs1523127, rs2276707, and rs6785049 suggested that PXR gene polymorphism had no obvious influence on the risk of IBD in Caucasians. Subgroup analyses based on disease type showed similar results. Our meta-analysis revealed that PXR gene polymorphism may not be significantly associated with IBD susceptibility. However, the number of original studies was limited and further studies with large samples are needed to verify the results. PXR = pregnane X receptor, IBD = inflammatory bowel disease, CD = Crohn's disease, UC = ulcerative colitis, ORs = pooled odds ratios, 95% CIs = 95% confidence intervals, NOS = Newcastle-Ottawa scale, HWE = Hardy-Weinberg equilibrium.

Fuzzy support vector machine for microarray imbalanced data classification

NASA Astrophysics Data System (ADS)

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.

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

PubMed

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

2004-08-01

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

Protein microarray analysis reveals BAFF-binding autoantibodies in systemic lupus erythematosus

PubMed Central

Price, Jordan V.; Haddon, David J.; Kemmer, Dodge; Delepine, Guillaume; Mandelbaum, Gil; Jarrell, Justin A.; Gupta, Rohit; Balboni, Imelda; Chakravarty, Eliza F.; Sokolove, Jeremy; Shum, Anthony K.; Anderson, Mark S.; Cheng, Mickie H.; Robinson, William H.; Browne, Sarah K.; Holland, Steven M.; Baechler, Emily C.; Utz, Paul J.

2013-01-01

Autoantibodies against cytokines, chemokines, and growth factors inhibit normal immunity and are implicated in inflammatory autoimmune disease and diseases of immune deficiency. In an effort to evaluate serum from autoimmune and immunodeficient patients for Abs against cytokines, chemokines, and growth factors in a high-throughput and unbiased manner, we constructed a multiplex protein microarray for detection of serum factor–binding Abs and used the microarray to detect autoantibody targets in SLE. We designed a nitrocellulose-surface microarray containing human cytokines, chemokines, and other circulating proteins and demonstrated that the array permitted specific detection of serum factor–binding probes. We used the arrays to detect previously described autoantibodies against cytokines in samples from individuals with autoimmune polyendocrine syndrome type 1 and chronic mycobacterial infection. Serum profiling from individuals with SLE revealed that among several targets, elevated IgG autoantibody reactivity to B cell–activating factor (BAFF) was associated with SLE compared with control samples. BAFF reactivity correlated with the severity of disease-associated features, including IFN-α–driven SLE pathology. Our results showed that serum factor protein microarrays facilitate detection of autoantibody reactivity to serum factors in human samples and that BAFF-reactive autoantibodies may be associated with an elevated inflammatory disease state within the spectrum of SLE. PMID:24270423

Quality control of inkjet technology for DNA microarray fabrication.

PubMed

Pierik, Anke; Dijksman, Frits; Raaijmakers, Adrie; Wismans, Ton; Stapert, Henk

2008-12-01

A robust manufacturing process is essential to make high-quality DNA microarrays, especially for use in diagnostic tests. We investigated different failure modes of the inkjet printing process used to manufacture low-density microarrays. A single nozzle inkjet spotter was provided with two optical imaging systems, monitoring in real time the flight path of every droplet. If a droplet emission failure is detected, the printing process is automatically stopped. We analyzed over 1.3 million droplets. This information was used to investigate the performance of the inkjet system and to obtain detailed insight into the frequency and causes of jetting failures. Of all the substrates investigated, 96.2% were produced without any system or jetting failures. In 1.6% of the substrates, droplet emission failed and was correctly identified. Appropriate measures could then be taken to get the process back on track. In 2.2%, the imaging systems failed while droplet emission occurred correctly. In 0.1% of the substrates, droplet emission failure that was not timely detected occurred. Thus, the overall yield of the microarray manufacturing process was 99.9%, which is highly acceptable for prototyping.

Fiber-optic microarray for simultaneous detection of multiple harmful algal bloom species.

PubMed

Ahn, Soohyoun; Kulis, David M; Erdner, Deana L; Anderson, Donald M; Walt, David R

2006-09-01

Harmful algal blooms (HABs) are a serious threat to coastal resources, causing a variety of impacts on public health, regional economies, and ecosystems. Plankton analysis is a valuable component of many HAB monitoring and research programs, but the diversity of plankton poses a problem in discriminating toxic from nontoxic species using conventional detection methods. Here we describe a sensitive and specific sandwich hybridization assay that combines fiber-optic microarrays with oligonucleotide probes to detect and enumerate the HAB species Alexandrium fundyense, Alexandrium ostenfeldii, and Pseudo-nitzschia australis. Microarrays were prepared by loading oligonucleotide probe-coupled microspheres (diameter, 3 mum) onto the distal ends of chemically etched imaging fiber bundles. Hybridization of target rRNA from HAB cells to immobilized probes on the microspheres was visualized using Cy3-labeled secondary probes in a sandwich-type assay format. We applied these microarrays to the detection and enumeration of HAB cells in both cultured and field samples. Our study demonstrated a detection limit of approximately 5 cells for all three target organisms within 45 min, without a separate amplification step, in both sample types. We also developed a multiplexed microarray to detect the three HAB species simultaneously, which successfully detected the target organisms, alone and in combination, without cross-reactivity. Our study suggests that fiber-optic microarrays can be used for rapid and sensitive detection and potential enumeration of HAB species in the environment.

Bacterial identification and subtyping using DNA microarray and DNA sequencing.

PubMed

Al-Khaldi, Sufian F; Mossoba, Magdi M; Allard, Marc M; Lienau, E Kurt; Brown, Eric D

2012-01-01

The era of fast and accurate discovery of biological sequence motifs in prokaryotic and eukaryotic cells is here. The co-evolution of direct genome sequencing and DNA microarray strategies not only will identify, isotype, and serotype pathogenic bacteria, but also it will aid in the discovery of new gene functions by detecting gene expressions in different diseases and environmental conditions. Microarray bacterial identification has made great advances in working with pure and mixed bacterial samples. The technological advances have moved beyond bacterial gene expression to include bacterial identification and isotyping. Application of new tools such as mid-infrared chemical imaging improves detection of hybridization in DNA microarrays. The research in this field is promising and future work will reveal the potential of infrared technology in bacterial identification. On the other hand, DNA sequencing by using 454 pyrosequencing is so cost effective that the promise of $1,000 per bacterial genome sequence is becoming a reality. Pyrosequencing technology is a simple to use technique that can produce accurate and quantitative analysis of DNA sequences with a great speed. The deposition of massive amounts of bacterial genomic information in databanks is creating fingerprint phylogenetic analysis that will ultimately replace several technologies such as Pulsed Field Gel Electrophoresis. In this chapter, we will review (1) the use of DNA microarray using fluorescence and infrared imaging detection for identification of pathogenic bacteria, and (2) use of pyrosequencing in DNA cluster analysis to fingerprint bacterial phylogenetic trees.

Ontology-based, Tissue MicroArray oriented, image centered tissue bank

PubMed Central

Viti, Federica; Merelli, Ivan; Caprera, Andrea; Lazzari, Barbara; Stella, Alessandra; Milanesi, Luciano

2008-01-01

Background Tissue MicroArray technique is becoming increasingly important in pathology for the validation of experimental data from transcriptomic analysis. This approach produces many images which need to be properly managed, if possible with an infrastructure able to support tissue sharing between institutes. Moreover, the available frameworks oriented to Tissue MicroArray provide good storage for clinical patient, sample treatment and block construction information, but their utility is limited by the lack of data integration with biomolecular information. Results In this work we propose a Tissue MicroArray web oriented system to support researchers in managing bio-samples and, through the use of ontologies, enables tissue sharing aimed at the design of Tissue MicroArray experiments and results evaluation. Indeed, our system provides ontological description both for pre-analysis tissue images and for post-process analysis image results, which is crucial for information exchange. Moreover, working on well-defined terms it is then possible to query web resources for literature articles to integrate both pathology and bioinformatics data. Conclusions Using this system, users associate an ontology-based description to each image uploaded into the database and also integrate results with the ontological description of biosequences identified in every tissue. Moreover, it is possible to integrate the ontological description provided by the user with a full compliant gene ontology definition, enabling statistical studies about correlation between the analyzed pathology and the most commonly related biological processes. PMID:18460177

LRP5 gene polymorphism and cortical bone

PubMed Central

Lauretani, Fulvio; Cepollaro, Chiara; Bandinelli, Stefania; Cherubini, Antonio; Gozzini, Alessia; Masi, Laura; Falchetti, Alberto; Del Monte, Francesca; Carbonell-Sala, Silvia; Marini, Francesca; Tanini, Annalisa; Corsi, Anna Maria; Ceda, Gian Paolo; Brandi, Maria Luisa; Ferrucci, Luigi

2016-01-01

Background and aims There is evidence that distinct genetic polymorphisms of LRP5 are associated with low Bone Mineral Density (BMD) and the risk of fracture. However, relationships between LRP5 polymorphisms and micro- and macro-architectural bone characteristics assessed by pQCT have not been studied. The aim of the present study was to investigate the association of Ala1330Val and Val667Met polymorphisms in LRP5 gene with volumetric BMD (vBMD) and macro-architectural bone parameters in a population-based sample of men and women. Methods We studied 959 participants of the InCHIANTI study (451 men and 508 women, age range: 21–94 yrs). Trabecular vBMD (vBMDt, mg/cm3), cortical vBMD (vBMDc, mg/cm3), cortical bone area (CBA, mm2) and cortical thickness (Ct.Th, mm) at the level of the tibia were assessed by peripheral quantitative computed tomography (pQCT). Ala1330Val and Val667Met genotypes were determined on genomic DNA by polymerase chain reaction-restriction fragment length polymorphism (PCR-RFLP). Results In age-adjusted analyses both LRP 1330-valine and LRP 667-metionin variants were associated with lower vBMDt in men (p<0.05), and lower vBMDt (p<0.05), Ct.Th (p<0.05) and CBA (p<0.05) in women. After adjusting for multiple confounders, only the association of LRP5 1330-valine and 667-metionin with CBA remained statistically significant (p=0.04 and p=0.01, respectively) in women. Conclusion These findings suggest that both Ala1330Val and Val667Met LRP5 polymorphisms may affect the determination of geometric bone parameters in women. PMID:21116122

Mining microarray data at NCBI's Gene Expression Omnibus (GEO)*.

PubMed

Barrett, Tanya; Edgar, Ron

2006-01-01

The Gene Expression Omnibus (GEO) at the National Center for Biotechnology Information (NCBI) has emerged as the leading fully public repository for gene expression data. This chapter describes how to use Web-based interfaces, applications, and graphics to effectively explore, visualize, and interpret the hundreds of microarray studies and millions of gene expression patterns stored in GEO. Data can be examined from both experiment-centric and gene-centric perspectives using user-friendly tools that do not require specialized expertise in microarray analysis or time-consuming download of massive data sets. The GEO database is publicly accessible through the World Wide Web at http://www.ncbi.nlm.nih.gov/geo.

A Web-Based Multi-Database System Supporting Distributed Collaborative Management and Sharing of Microarray Experiment Information

PubMed Central

Burgarella, Sarah; Cattaneo, Dario; Masseroli, Marco

2006-01-01

We developed MicroGen, a multi-database Web based system for managing all the information characterizing spotted microarray experiments. It supports information gathering and storing according to the Minimum Information About Microarray Experiments (MIAME) standard. It also allows easy sharing of information and data among all multidisciplinary actors involved in spotted microarray experiments. PMID:17238488

VDR polymorphisms are associated with bone mineral density in post-menopausal Mayan-Mestizo women.

PubMed

Canto-Cetina, Thelma; Cetina Manzanilla, José Antonio; González Herrera, Lizbeth; Rojano-Mejía, David; Coral-Vázquez, Ramón Mauricio; Coronel, Agustín; Canto, Patricia

2015-01-01

Osteoporosis is characterized by low bone mineral density (BMD), which is determined by an interaction of genetic, metabolic and environmental factors. To analyse the association between two polymorphisms of VDR as well as their haplotypes with BMD in post-menopausal Maya-Mestizo women. This study comprised 600 post-menopausal Maya-Mestizo women. A structured questionnaire for risk factors was applied and BMD was assessed at the lumbar spine (LS) and total hip (TH) by dual-energy X-ray absorptiometry. DNA was extracted from blood leukocytes. Two single-nucleotide polymorphisms of VDR (rs731236 and rs2228570) were studied using real-time PCR allelic discrimination for genotyping. Differences between the means of the BMDs according to the genotype were analysed with covariance. Haplotype analysis was conducted. TT genotype of rs731236 of VDR had higher BMD at total hip and femoral neck (FN), and one haplotype formed by the two polymorphisms was associated with only TH-BMD variations. This difference was statistically significant after adjustment for confounders. The genotype of rs2228570 of VDR analysis showed no significant differences with BMD variations. The results showed that the TT genotype of rs731236 of VDR and one haplotype formed by rs731236 and rs2228570 polymorphisms were associated with higher BMD at TH and FN.

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

PubMed Central

2012-01-01

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

Microarray analysis in rat liver slices correctly predicts in vivo hepatotoxicity.

PubMed

Elferink, M G L; Olinga, P; Draaisma, A L; Merema, M T; Bauerschmidt, S; Polman, J; Schoonen, W G; Groothuis, G M M

2008-06-15

The microarray technology, developed for the simultaneous analysis of a large number of genes, may be useful for the detection of toxicity in an early stage of the development of new drugs. The effect of different hepatotoxins was analyzed at the gene expression level in the rat liver both in vivo and in vitro. As in vitro model system the precision-cut liver slice model was used, in which all liver cell types are present in their natural architecture. This is important since drug-induced toxicity often is a multi-cellular process involving not only hepatocytes but also other cell types such as Kupffer and stellate cells. As model toxic compounds lipopolysaccharide (LPS, inducing inflammation), paracetamol (necrosis), carbon tetrachloride (CCl(4), fibrosis and necrosis) and gliotoxin (apoptosis) were used. The aim of this study was to validate the rat liver slice system as in vitro model system for drug-induced toxicity studies. The results of the microarray studies show that the in vitro profiles of gene expression cluster per compound and incubation time, and when analyzed in a commercial gene expression database, can predict the toxicity and pathology observed in vivo. Each toxic compound induces a specific pattern of gene expression changes. In addition, some common genes were up- or down-regulated with all toxic compounds. These data show that the rat liver slice system can be an appropriate tool for the prediction of multi-cellular liver toxicity. The same experiments and analyses are currently performed for the prediction of human specific toxicity using human liver slices.

Microarray analysis in rat liver slices correctly predicts in vivo hepatotoxicity

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

Elferink, M.G.L.; Olinga, P.; Draaisma, A.L.

2008-06-15

The microarray technology, developed for the simultaneous analysis of a large number of genes, may be useful for the detection of toxicity in an early stage of the development of new drugs. The effect of different hepatotoxins was analyzed at the gene expression level in the rat liver both in vivo and in vitro. As in vitro model system the precision-cut liver slice model was used, in which all liver cell types are present in their natural architecture. This is important since drug-induced toxicity often is a multi-cellular process involving not only hepatocytes but also other cell types such asmore » Kupffer and stellate cells. As model toxic compounds lipopolysaccharide (LPS, inducing inflammation), paracetamol (necrosis), carbon tetrachloride (CCl{sub 4}, fibrosis and necrosis) and gliotoxin (apoptosis) were used. The aim of this study was to validate the rat liver slice system as in vitro model system for drug-induced toxicity studies. The results of the microarray studies show that the in vitro profiles of gene expression cluster per compound and incubation time, and when analyzed in a commercial gene expression database, can predict the toxicity and pathology observed in vivo. Each toxic compound induces a specific pattern of gene expression changes. In addition, some common genes were up- or down-regulated with all toxic compounds. These data show that the rat liver slice system can be an appropriate tool for the prediction of multi-cellular liver toxicity. The same experiments and analyses are currently performed for the prediction of human specific toxicity using human liver slices.« less

Association study of ghrelin receptor gene polymorphisms in rheumatoid arthritis.

PubMed

Robledo, G; Rueda, B; Gonzalez-Gay, M A; Fernández, B; Lamas, J R; Balsa, A; Pascual-Salcedo, D; García, A; Raya, E; Martín, J

2010-01-01

Ghrelin is a newly characterised growth hormone (GH) releasing peptide widely distributed that may play an important role in the regulation of metabolic balance in inflammatory diseases such as rheumatoid arthritis (RA) by decreasing the pro-inflammatory Th1 responses. In this study we investigated the possible contribution of several polymorphisms in the functional Ghrelin receptor to RA susceptibility. A screening of 3 single nucleotide polymorphisms (SNPs) was performed in a total of 950 RA patients and 990 healthy controls of Spanish Caucasian origin. Genotyping of all 3 SNPs was performed by real-time polymerase chain reaction technology, using the TaqMan 5'-allele discrimination assay. We observed no statistically significant deviation between RA patients and controls for the GHSR SNPs analysed. In addition, we performed a haplotype analysis that did not reveal an association with RA susceptibility. The stratification analysis for the presence of shared epitope (SE), rheumatoid factor (RF) or antibodies anti cyclic citrullinated peptide (anti-CCP) did not detect significant association of the GHSR polymorphisms with RA. These findings suggest that the GHSR gene polymorphisms do not appear to play a major role in RA genetic predisposition in our population.

DNA Microarray Wet Lab Simulation Brings Genomics into the High School Curriculum

ERIC Educational Resources Information Center

Campbell, A. Malcolm; Zanta, Carolyn A.; Heyer, Laurie J.; Kittinger, Ben; Gabric, Kathleen M.; Adler, Leslie

2006-01-01

We have developed a wet lab DNA microarray simulation as part of a complete DNA microarray module for high school students. The wet lab simulation has been field tested with high school students in Illinois and Maryland as well as in workshops with high school teachers from across the nation. Instead of using DNA, our simulation is based on pH…

Open-target sparse sensing of biological agents using DNA microarray

PubMed Central

2011-01-01

Background Current biosensors are designed to target and react to specific nucleic acid sequences or structural epitopes. These 'target-specific' platforms require creation of new physical capture reagents when new organisms are targeted. An 'open-target' approach to DNA microarray biosensing is proposed and substantiated using laboratory generated data. The microarray consisted of 12,900 25 bp oligonucleotide capture probes derived from a statistical model trained on randomly selected genomic segments of pathogenic prokaryotic organisms. Open-target detection of organisms was accomplished using a reference library of hybridization patterns for three test organisms whose DNA sequences were not included in the design of the microarray probes. Results A multivariate mathematical model based on the partial least squares regression (PLSR) was developed to detect the presence of three test organisms in mixed samples. When all 12,900 probes were used, the model correctly detected the signature of three test organisms in all mixed samples (mean(R2)) = 0.76, CI = 0.95), with a 6% false positive rate. A sampling algorithm was then developed to sparsely sample the probe space for a minimal number of probes required to capture the hybridization imprints of the test organisms. The PLSR detection model was capable of correctly identifying the presence of the three test organisms in all mixed samples using only 47 probes (mean(R2)) = 0.77, CI = 0.95) with nearly 100% specificity. Conclusions We conceived an 'open-target' approach to biosensing, and hypothesized that a relatively small, non-specifically designed, DNA microarray is capable of identifying the presence of multiple organisms in mixed samples. Coupled with a mathematical model applied to laboratory generated data, and sparse sampling of capture probes, the prototype microarray platform was able to capture the signature of each organism in all mixed samples with high sensitivity and specificity. It was demonstrated

Identification of candidate genes in osteoporosis by integrated microarray analysis.

PubMed

Li, J J; Wang, B Q; Fei, Q; Yang, Y; Li, D

2016-12-01

In order to screen the altered gene expression profile in peripheral blood mononuclear cells of patients with osteoporosis, we performed an integrated analysis of the online microarray studies of osteoporosis. We searched the Gene Expression Omnibus (GEO) database for microarray studies of peripheral blood mononuclear cells in patients with osteoporosis. Subsequently, we integrated gene expression data sets from multiple microarray studies to obtain differentially expressed genes (DEGs) between patients with osteoporosis and normal controls. Gene function analysis was performed to uncover the functions of identified DEGs. A total of three microarray studies were selected for integrated analysis. In all, 1125 genes were found to be significantly differentially expressed between osteoporosis patients and normal controls, with 373 upregulated and 752 downregulated genes. Positive regulation of the cellular amino metabolic process (gene ontology (GO): 0033240, false discovery rate (FDR) = 1.00E + 00) was significantly enriched under the GO category for biological processes, while for molecular functions, flavin adenine dinucleotide binding (GO: 0050660, FDR = 3.66E-01) and androgen receptor binding (GO: 0050681, FDR = 6.35E-01) were significantly enriched. DEGs were enriched in many osteoporosis-related signalling pathways, including those of mitogen-activated protein kinase (MAPK) and calcium. Protein-protein interaction (PPI) network analysis showed that the significant hub proteins contained ubiquitin specific peptidase 9, X-linked (Degree = 99), ubiquitin specific peptidase 19 (Degree = 57) and ubiquitin conjugating enzyme E2 B (Degree = 57). Analysis of gene function of identified differentially expressed genes may expand our understanding of fundamental mechanisms leading to osteoporosis. Moreover, significantly enriched pathways, such as MAPK and calcium, may involve in osteoporosis through osteoblastic differentiation and bone formation.Cite this article: J. J

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

PubMed Central

2015-01-01

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

Analysis of microarray leukemia data using an efficient MapReduce-based K-nearest-neighbor classifier.

PubMed

Kumar, Mukesh; Rath, Nitish Kumar; Rath, Santanu Kumar

2016-04-01

Microarray-based gene expression profiling has emerged as an efficient technique for classification, prognosis, diagnosis, and treatment of cancer. Frequent changes in the behavior of this disease generates an enormous volume of data. Microarray data satisfies both the veracity and velocity properties of big data, as it keeps changing with time. Therefore, the analysis of microarray datasets in a small amount of time is essential. They often contain a large amount of expression, but only a fraction of it comprises genes that are significantly expressed. The precise identification of genes of interest that are responsible for causing cancer are imperative in microarray data analysis. Most existing schemes employ a two-phase process such as feature selection/extraction followed by classification. In this paper, various statistical methods (tests) based on MapReduce are proposed for selecting relevant features. After feature selection, a MapReduce-based K-nearest neighbor (mrKNN) classifier is also employed to classify microarray data. These algorithms are successfully implemented in a Hadoop framework. A comparative analysis is done on these MapReduce-based models using microarray datasets of various dimensions. From the obtained results, it is observed that these models consume much less execution time than conventional models in processing big data. Copyright © 2016 Elsevier Inc. All rights reserved.

Paraoxonase-1 gene Q192R polymorphism and reactive oxygen metabolites.

PubMed

Kotani, K; Tsuzaki, K; Sakane, N

2012-01-01

Paraoxonase-1 (PON1) is a high-density lipoprotein-associated antioxidant enzyme. The Q192R polymorphism of the PON1 gene can protect against oxidative conditions, but the relationship between Q192R polymorphism and oxidative stress-related markers remains controversial. In this study, the diacron reactive oxygen metabolites (d-ROMs) test was used to investigate the relationship between Q192R polymorphism and oxidative stress-related markers in Japanese subjects. Patients without a history of overt cardiovascular disease who were not receiving antioxidant medication were enrolled in a cross-sectional clinic-based study. An allele-specific polymerase chain reaction method was used to assess the PON1 Q192R polymorphism and compare the level of d-ROMs between genotypes. A total of 103 subjects were analysed. The RR genotype was associated with a significantly lower level of d-ROMs than the RQ and QQ genotypes. After multivariate analysis the relationship between the genotypes and level of d-ROMs remained independently significant. The RR genotype may be protective against oxidative stress in cardiovascular diseasefree Japanese subjects. In addition, the d-ROMs test can be useful for examining the role of the PON1 Q192R polymorphism under oxidative conditions.