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Sample records for microarray analyses identified

  1. Identifying Fishes through DNA Barcodes and Microarrays.

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    Marc Kochzius

    2010-09-01

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

  2. Analyses of Aloe polysaccharides using carbohydrate microarray profiling

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

    2018-01-01

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

  3. Genome-wide transcription analyses in rice using tiling microarrays

    DEFF Research Database (Denmark)

    Li, Lei; Wang, Xiangfeng; Stolc, Viktor

    2006-01-01

    . We report here a full-genome transcription analysis of the indica rice subspecies using high-density oligonucleotide tiling microarrays. Our results provided expression data support for the existence of 35,970 (81.9%) annotated gene models and identified 5,464 unique transcribed intergenic regions...... that share similar compositional properties with the annotated exons and have significant homology to other plant proteins. Elucidating and mapping of all transcribed regions revealed an association between global transcription and cytological chromosome features, and an overall similarity of transcriptional......Sequencing and computational annotation revealed several features, including high gene numbers, unusual composition of the predicted genes and a large number of genes lacking homology to known genes, that distinguish the rice (Oryza sativa) genome from that of other fully sequenced model species...

  4. Application of four dyes in gene expression analyses by microarrays

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    van Schooten Frederik J

    2005-07-01

    Full Text Available Abstract Background DNA microarrays are widely used in gene expression analyses. To increase throughput and minimize costs without reducing gene expression data obtained, we investigated whether four mRNA samples can be analyzed simultaneously by applying four different fluorescent dyes. Results Following tests for cross-talk of fluorescence signals, Alexa 488, Alexa 594, Cyanine 3 and Cyanine 5 were selected for hybridizations. For self-hybridizations, a single RNA sample was labelled with all dyes and hybridized on commercial cDNA arrays or on in-house spotted oligonucleotide arrays. Correlation coefficients for all combinations of dyes were above 0.9 on the cDNA array. On the oligonucleotide array they were above 0.8, except combinations with Alexa 488, which were approximately 0.5. Standard deviation of expression differences for replicate spots were similar on the cDNA array for all dye combinations, but on the oligonucleotide array combinations with Alexa 488 showed a higher variation. Conclusion In conclusion, the four dyes can be used simultaneously for gene expression experiments on the tested cDNA array, but only three dyes can be used on the tested oligonucleotide array. This was confirmed by hybridizations of control with test samples, as all combinations returned similar numbers of differentially expressed genes with comparable effects on gene expression.

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

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    Yamada, Yoichi; Sawada, Hiroki; Hirotani, Ken-ichi; Oshima, Masanobu; Satou, Kenji

    2012-01-01

    Abstract 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...

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

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    Yamada Yoichi

    2012-12-01

    Full Text Available Abstract 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 Conclusions MIMGO is a reliable method to identify differentially expressed GO terms comprehensively.

  7. Amygdala-enriched genes identified by microarray technology are restricted to specific amygdaloid subnuclei

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    Zirlinger, M.; Kreiman, Gabriel; Anderson, D. J.

    2001-01-01

    Microarray technology represents a potentially powerful method for identifying cell type- and regionally restricted genes expressed in the brain. Here we have combined a microarray analysis of differential gene expression among five selected brain regions, including the amygdala, cerebellum, hippocampus, olfactory bulb, and periaqueductal gray, with in situ hybridization. On average, 0.3% of the 34,000 genes interrogated were highly enriched in each of the five regions...

  8. Microarray analyses of glucocorticoid and vitamin D3 target genes in differentiating cultured human podocytes.

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    Xiwen Cheng

    Full Text Available Glomerular podocytes are highly differentiated epithelial cells that are key components of the kidney filtration units. Podocyte damage or loss is the hallmark of nephritic diseases characterized by severe proteinuria. Recent studies implicate that hormones including glucocorticoids (ligand for glucocorticoid receptor and vitamin D3 (ligand for vitamin D receptor protect or promote repair of podocytes from injury. In order to elucidate the mechanisms underlying hormone-mediated podocyte-protecting activity from injury, we carried out microarray gene expression studies to identify the target genes and corresponding pathways in response to these hormones during podocyte differentiation. We used immortalized human cultured podocytes (HPCs as a model system and carried out in vitro differentiation assays followed by dexamethasone (Dex or vitamin D3 (VD3 treatment. Upon the induction of differentiation, multiple functional categories including cell cycle, organelle dynamics, mitochondrion, apoptosis and cytoskeleton organization were among the most significantly affected. Interestingly, while Dex and VD3 are capable of protecting podocytes from injury, they only share limited target genes and affected pathways. Compared to VD3 treatment, Dex had a broader and greater impact on gene expression profiles. In-depth analyses of Dex altered genes indicate that Dex crosstalks with a broad spectrum of signaling pathways, of which inflammatory responses, cell migration, angiogenesis, NF-κB and TGFβ pathways are predominantly altered. Together, our study provides new information and identifies several new avenues for future investigation of hormone signaling in podocytes.

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

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    Gerosolimo Germano

    2008-06-01

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

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

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    Puccinia striiformis f. sp. tritici (Pst) causes stripe rust, one of the most important diseases of wheat worldwide. To identify Pst genes involved in infection and sporulation, a custom oligonucleotide Genechip was made using sequences of 442 genes selected from Pst cDNA libraries. Microarray analy...

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

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    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.

  12. Consistent Differential Expression Pattern (CDEP) on microarray to identify genes related to metastatic behavior.

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    Tsoi, Lam C; Qin, Tingting; Slate, Elizabeth H; Zheng, W Jim

    2011-11-11

    To utilize the large volume of gene expression information generated from different microarray experiments, several meta-analysis techniques have been developed. Despite these efforts, there remain significant challenges to effectively increasing the statistical power and decreasing the Type I error rate while pooling the heterogeneous datasets from public resources. The objective of this study is to develop a novel meta-analysis approach, Consistent Differential Expression Pattern (CDEP), to identify genes with common differential expression patterns across different datasets. We combined False Discovery Rate (FDR) estimation and the non-parametric RankProd approach to estimate the Type I error rate in each microarray dataset of the meta-analysis. These Type I error rates from all datasets were then used to identify genes with common differential expression patterns. Our simulation study showed that CDEP achieved higher statistical power and maintained low Type I error rate when compared with two recently proposed meta-analysis approaches. We applied CDEP to analyze microarray data from different laboratories that compared transcription profiles between metastatic and primary cancer of different types. Many genes identified as differentially expressed consistently across different cancer types are in pathways related to metastatic behavior, such as ECM-receptor interaction, focal adhesion, and blood vessel development. We also identified novel genes such as AMIGO2, Gem, and CXCL11 that have not been shown to associate with, but may play roles in, metastasis. CDEP is a flexible approach that borrows information from each dataset in a meta-analysis in order to identify genes being differentially expressed consistently. We have shown that CDEP can gain higher statistical power than other existing approaches under a variety of settings considered in the simulation study, suggesting its robustness and insensitivity to data variation commonly associated with microarray

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

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

    2014-06-01

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

  14. Anti-schistosomal intervention targets identified by lifecycle transcriptomic analyses.

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    Jennifer M Fitzpatrick

    2009-11-01

    Full Text Available Novel methods to identify anthelmintic drug and vaccine targets are urgently needed, especially for those parasite species currently being controlled by singular, often limited strategies. A clearer understanding of the transcriptional components underpinning helminth development will enable identification of exploitable molecules essential for successful parasite/host interactions. Towards this end, we present a combinatorial, bioinformatics-led approach, employing both statistical and network analyses of transcriptomic data, for identifying new immunoprophylactic and therapeutic lead targets to combat schistosomiasis.Utilisation of a Schistosoma mansoni oligonucleotide DNA microarray consisting of 37,632 elements enabled gene expression profiling from 15 distinct parasite lifecycle stages, spanning three unique ecological niches. Statistical approaches of data analysis revealed differential expression of 973 gene products that minimally describe the three major characteristics of schistosome development: asexual processes within intermediate snail hosts, sexual maturation within definitive vertebrate hosts and sexual dimorphism amongst adult male and female worms. Furthermore, we identified a group of 338 constitutively expressed schistosome gene products (including 41 transcripts sharing no sequence similarity outside the Platyhelminthes, which are likely to be essential for schistosome lifecycle progression. While highly informative, statistics-led bioinformatics mining of the transcriptional dataset has limitations, including the inability to identify higher order relationships between differentially expressed transcripts and lifecycle stages. Network analysis, coupled to Gene Ontology enrichment investigations, facilitated a re-examination of the dataset and identified 387 clusters (containing 12,132 gene products displaying novel examples of developmentally regulated classes (including 294 schistosomula and/or adult transcripts with no

  15. Identification of molecular mechanisms of radiation-induced vascular damage in normal tissues using microarray analyses

    International Nuclear Information System (INIS)

    Kruse, J.J.C.M.; Te Poele, J.A.M.; Russell, N.S.; Boersma, L.J.; Stewart, F.A.

    2003-01-01

    Radiation-induced telangiectasia, characterized by thin-walled dilated blood vessels, can be a serious late complication in patients that have been previously treated for cancer. It might cause cosmetic problems when occurring in the skin, and excessive bleeding requiring surgery when occurring in rectal mucosa. The mechanisms underlying the development of radiation-induced telangiectasia are unclear. The aim of the present study is to determine whether microarrays are useful for studying mechanisms of radiation-induced telangiectasia. The second aim is to test the hypotheses that telangiectasia is characterized by a final common pathway in different tissues. Microarray experiments were performed using amplified RNA from (sham)irradiated mouse tissues (kidney, rectum) at different intervals (1-30 weeks) after irradiation. After normalization procedures, the differentially expressed genes were identified. Control/repeat experiments were done to confirm that the observations were not artifacts of the array procedure. The mouse kidney experiments showed significant upregulation of 31 and 42 genes and downregulation of 9 and 4 genes at 10 and 20 weeks after irradiation, respectively. Irradiated mouse rectum has 278 upregulated and 537 downregulated genes at 10 weeks and 86 upregulated and 29 downregulated genes at 20 weeks. During the development of telangiectasia, 19 upregulated genes and 5 downregulated genes were common to both tissues. Upregulation of Jagged-1, known to play a role in angiogenesis, is particularly interesting in the context of radiation-induced telangiectasia. Microarrays are affective discovery tools to identify novel genes of interest, which may be involved in radiation-induced normal tissue injury. Using information from control arrays (particularly straight color, color reverse and self-self experiments) allowed for a more accurate and reproducible identification of differentially expressed genes than the selection of an arbitrary 2-fold change

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

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    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.

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

    International Nuclear Information System (INIS)

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

    2003-01-01

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

  18. Microarray data analyses of yeast RNA Pol I subunit RPA12 deletion strain

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    Kamlesh Kumar Yadav

    2016-06-01

    Full Text Available The ribosomal RNA (rRNA biosynthesis is the most energy consuming process in all living cells and the majority of total transcription activity is dedicated for synthesizing rRNA. The cells may adjust the synthesis of rRNA with the availability of resources. rRNA is mainly synthesized by RNA polymerase I that is composed of 14 subunits. Deletion of RPA12, 14, 39 and 49 are viable. RPA12 is a very small protein (13.6 kDa, and the amount of protein in the cells is very high (12,000 molecules per cell, but the role of this protein is unknown in other cellular metabolic processes (Kulak et al., 2014 [1]. RPA12 consists of two zinc-binding domains and it is required for the termination of rRNA synthesis (Mullem et al., 2002 [2]. Deletions of RPA12 in Saccharomyces cerevisiae and Schizosaccharomyces pombe cause a conditional growth defect (Nogi et al., 1993 [3]. In S. pombe, C-terminal deletion behaves like wild-type (Imazawa et al., 2001 [4]. This prompted us to investigate in detail the physiological role of RPA12 in S. cerevisiae, we performed the microarray of rpa12∆ strain and deposited into Gene Expression Omnibus under GSE68731. The analysis of microarray data revealed that the expression of major cellular metabolism genes is high. The amino acid biosynthesis, nonpolar lipid biosynthesis and glucose metabolic genes are highly expressed. The analyses also revealed that the rpa12∆ cells have an uncontrolled synthesis of cell metabolites, so RPA12 could be a master regulator for whole cellular metabolism.

  19. PreP+07: improvements of a user friendly tool to preprocess and analyse microarray data

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    Claros M Gonzalo

    2009-01-01

    Full Text Available Abstract Background Nowadays, microarray gene expression analysis is a widely used technology that scientists handle but whose final interpretation usually requires the participation of a specialist. The need for this participation is due to the requirement of some background in statistics that most users lack or have a very vague notion of. Moreover, programming skills could also be essential to analyse these data. An interactive, easy to use application seems therefore necessary to help researchers to extract full information from data and analyse them in a simple, powerful and confident way. Results PreP+07 is a standalone Windows XP application that presents a friendly interface for spot filtration, inter- and intra-slide normalization, duplicate resolution, dye-swapping, error removal and statistical analyses. Additionally, it contains two unique implementation of the procedures – double scan and Supervised Lowess-, a complete set of graphical representations – MA plot, RG plot, QQ plot, PP plot, PN plot – and can deal with many data formats, such as tabulated text, GenePix GPR and ArrayPRO. PreP+07 performance has been compared with the equivalent functions in Bioconductor using a tomato chip with 13056 spots. The number of differentially expressed genes considering p-values coming from the PreP+07 and Bioconductor Limma packages were statistically identical when the data set was only normalized; however, a slight variability was appreciated when the data was both normalized and scaled. Conclusion PreP+07 implementation provides a high degree of freedom in selecting and organizing a small set of widely used data processing protocols, and can handle many data formats. Its reliability has been proven so that a laboratory researcher can afford a statistical pre-processing of his/her microarray results and obtain a list of differentially expressed genes using PreP+07 without any programming skills. All of this gives support to scientists

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

    International Nuclear Information System (INIS)

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

    2011-01-01

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

  1. Cross-species microarray hybridization to identify developmentally regulated genes in the filamentous fungus Sordaria macrospora.

    Science.gov (United States)

    Nowrousian, Minou; Ringelberg, Carol; Dunlap, Jay C; Loros, Jennifer J; Kück, Ulrich

    2005-04-01

    The filamentous fungus Sordaria macrospora forms complex three-dimensional fruiting bodies that protect the developing ascospores and ensure their proper discharge. Several regulatory genes essential for fruiting body development were previously isolated by complementation of the sterile mutants pro1, pro11 and pro22. To establish the genetic relationships between these genes and to identify downstream targets, we have conducted cross-species microarray hybridizations using cDNA arrays derived from the closely related fungus Neurospora crassa and RNA probes prepared from wild-type S. macrospora and the three developmental mutants. Of the 1,420 genes which gave a signal with the probes from all the strains used, 172 (12%) were regulated differently in at least one of the three mutants compared to the wild type, and 17 (1.2%) were regulated differently in all three mutant strains. Microarray data were verified by Northern analysis or quantitative real time PCR. Among the genes that are up- or down-regulated in the mutant strains are genes encoding the pheromone precursors, enzymes involved in melanin biosynthesis and a lectin-like protein. Analysis of gene expression in double mutants revealed a complex network of interaction between the pro gene products.

  2. Microarray and bioinformatic analyses suggest models for carbon metabolism in the autotroph Acidithiobacillus ferrooxidans

    Energy Technology Data Exchange (ETDEWEB)

    C. Appia-ayme; R. Quatrini; Y. Denis; F. Denizot; S. Silver; F. Roberto; F. Veloso; J. Valdes; J. P. Cardenas; M. Esparza; O. Orellana; E. Jedlicki; V. Bonnefoy; D. Holmes

    2006-09-01

    Acidithiobacillus ferrooxidans is a chemolithoautotrophic bacterium that uses iron or sulfur as an energy and electron source. Bioinformatic analysis was used to identify putative genes and potential metabolic pathways involved in CO2 fixation, 2P-glycolate detoxification, carboxysome formation and glycogen utilization in At. ferrooxidans. Microarray transcript profiling was carried out to compare the relative expression of the predicted genes of these pathways when the microorganism was grown in the presence of iron versus sulfur. Several gene expression patterns were confirmed by real-time PCR. Genes for each of the above predicted pathways were found to be organized into discrete clusters. Clusters exhibited differential gene expression depending on the presence of iron or sulfur in the medium. Concordance of gene expression within each cluster, suggested that they are operons Most notably, clusters of genes predicted to be involved in CO2 fixation, carboxysome formation, 2P-glycolate detoxification and glycogen biosynthesis were up-regulated in sulfur medium, whereas genes involved in glycogen utilization were preferentially expressed in iron medium. These results can be explained in terms of models of gene regulation that suggest how A. ferrooxidans can adjust its central carbon management to respond to changing environmental conditions.

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

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    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

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

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    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

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

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    Yamamoto, F; Yamamoto, M

    2004-07-01

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

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

    Science.gov (United States)

    GENE EXPRESSION IN THE TESTES OF NORMOSPERMIC VERSUS TERATOSPERMIC DOMESTIC CATS USING HUMAN cDNA MICROARRAY ANALYSESB.S. Pukazhenthi1, J. C. Rockett2, M. Ouyang3, D.J. Dix2, J.G. Howard1, P. Georgopoulos4, W.J. J. Welsh3 and D. E. Wildt11Department of Reproductiv...

  7. Identifying significant temporal variation in time course microarray data without replicates

    Directory of Open Access Journals (Sweden)

    Porter Weston

    2009-03-01

    Full Text Available Abstract Background An important component of time course microarray studies is the identification of genes that demonstrate significant time-dependent variation in their expression levels. Until recently, available methods for performing such significance tests required replicates of individual time points. This paper describes a replicate-free method that was developed as part of a study of the estrous cycle in the rat mammary gland in which no replicate data was collected. Results A temporal test statistic is proposed that is based on the degree to which data are smoothed when fit by a spline function. An algorithm is presented that uses this test statistic together with a false discovery rate method to identify genes whose expression profiles exhibit significant temporal variation. The algorithm is tested on simulated data, and is compared with another recently published replicate-free method. The simulated data consists both of genes with known temporal dependencies, and genes from a null distribution. The proposed algorithm identifies a larger percentage of the time-dependent genes for a given false discovery rate. Use of the algorithm in a study of the estrous cycle in the rat mammary gland resulted in the identification of genes exhibiting distinct circadian variation. These results were confirmed in follow-up laboratory experiments. Conclusion The proposed algorithm provides a new approach for identifying expression profiles with significant temporal variation without relying on replicates. When compared with a recently published algorithm on simulated data, the proposed algorithm appears to identify a larger percentage of time-dependent genes for a given false discovery rate. The development of the algorithm was instrumental in revealing the presence of circadian variation in the virgin rat mammary gland during the estrous cycle.

  8. GTI: a novel algorithm for identifying outlier gene expression profiles from integrated microarray datasets.

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    John Patrick Mpindi

    Full Text Available BACKGROUND: Meta-analysis of gene expression microarray datasets presents significant challenges for statistical analysis. We developed and validated a new bioinformatic method for the identification of genes upregulated in subsets of samples of a given tumour type ('outlier genes', a hallmark of potential oncogenes. METHODOLOGY: A new statistical method (the gene tissue index, GTI was developed by modifying and adapting algorithms originally developed for statistical problems in economics. We compared the potential of the GTI to detect outlier genes in meta-datasets with four previously defined statistical methods, COPA, the OS statistic, the t-test and ORT, using simulated data. We demonstrated that the GTI performed equally well to existing methods in a single study simulation. Next, we evaluated the performance of the GTI in the analysis of combined Affymetrix gene expression data from several published studies covering 392 normal samples of tissue from the central nervous system, 74 astrocytomas, and 353 glioblastomas. According to the results, the GTI was better able than most of the previous methods to identify known oncogenic outlier genes. In addition, the GTI identified 29 novel outlier genes in glioblastomas, including TYMS and CDKN2A. The over-expression of these genes was validated in vivo by immunohistochemical staining data from clinical glioblastoma samples. Immunohistochemical data were available for 65% (19 of 29 of these genes, and 17 of these 19 genes (90% showed a typical outlier staining pattern. Furthermore, raltitrexed, a specific inhibitor of TYMS used in the therapy of tumour types other than glioblastoma, also effectively blocked cell proliferation in glioblastoma cell lines, thus highlighting this outlier gene candidate as a potential therapeutic target. CONCLUSIONS/SIGNIFICANCE: Taken together, these results support the GTI as a novel approach to identify potential oncogene outliers and drug targets. The algorithm is

  9. Antibody Microarray Analyses of Signal Transduction Protein Expression and Phosphorylation during Porcine Oocyte Maturation

    Czech Academy of Sciences Publication Activity Database

    Pelech, S.; Jelínková, Lucie; Šušor, Andrej; Zhang, H.; Shi, X.; Pavlok, Antonín; Kubelka, Michal; Kovářová, Hana

    2008-01-01

    Roč. 7, č. 7 (2008), s. 2860-2871 ISSN 1535-3893 R&D Projects: GA ČR GA204/06/1297 Grant - others:GA AV ČR(CZ) 1QS500450568 Program:1Q Institutional research plan: CEZ:AV0Z50450515 Keywords : antibody microarray * pig * frog Subject RIV: EB - Genetics ; Molecular Biology Impact factor: 5.684, year: 2008

  10. Meta-analysis of Drosophila circadian microarray studies identifies a novel set of rhythmically expressed genes.

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    Kevin P Keegan

    2007-11-01

    Full Text Available Five independent groups have reported microarray studies that identify dozens of rhythmically expressed genes in the fruit fly Drosophila melanogaster. Limited overlap among the lists of discovered genes makes it difficult to determine which, if any, exhibit truly rhythmic patterns of expression. We reanalyzed data from all five reports and found two sources for the observed discrepancies, the use of different expression pattern detection algorithms and underlying variation among the datasets. To improve upon the methods originally employed, we developed a new analysis that involves compilation of all existing data, application of identical transformation and standardization procedures followed by ANOVA-based statistical prescreening, and three separate classes of post hoc analysis: cross-correlation to various cycling waveforms, autocorrelation, and a previously described fast Fourier transform-based technique. Permutation-based statistical tests were used to derive significance measures for all post hoc tests. We find application of our method, most significantly the ANOVA prescreening procedure, significantly reduces the false discovery rate relative to that observed among the results of the original five reports while maintaining desirable statistical power. We identify a set of 81 cycling transcripts previously found in one or more of the original reports as well as a novel set of 133 transcripts not found in any of the original studies. We introduce a novel analysis method that compensates for variability observed among the original five Drosophila circadian array reports. Based on the statistical fidelity of our meta-analysis results, and the results of our initial validation experiments (quantitative RT-PCR, we predict many of our newly found genes to be bona fide cyclers, and suggest that they may lead to new insights into the pathways through which clock mechanisms regulate behavioral rhythms.

  11. Usefulness of the SNP microarray technology to identify rare mutations in the case of perinatal death

    DEFF Research Database (Denmark)

    Hoeffding, L. K.; Kock, K. F.; Johnsen, Iben Birgit Gade

    2015-01-01

    The single nucleotide polymorphism (SNP) microarray technology has emerged as a powerful tool to screen the whole genome for sub-microscopic duplications and deletions that are not detectable by traditional cytogenetic analysis. Case: We report a case of a female twin born at 27th week of gestation...

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

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    Nolwenn M Dheilly

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

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

    Science.gov (United States)

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

    2009-01-01

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

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

    Science.gov (United States)

    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.

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

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    Rolf I. Skotheim

    2003-09-01

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

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

    Energy Technology Data Exchange (ETDEWEB)

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

    2009-03-01

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

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

    Science.gov (United States)

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

    2016-06-01

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

  18. Multi-platform whole-genome microarray analyses refine the epigenetic signature of breast cancer metastasis with gene expression and copy number.

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    Joseph Andrews

    2010-01-01

    Full Text Available We have previously identified genome-wide DNA methylation changes in a cell line model of breast cancer metastasis. These complex epigenetic changes that we observed, along with concurrent karyotype analyses, have led us to hypothesize that complex genomic alterations in cancer cells (deletions, translocations and ploidy are superimposed over promoter-specific methylation events that are responsible for gene-specific expression changes observed in breast cancer metastasis.We undertook simultaneous high-resolution, whole-genome analyses of MDA-MB-468GFP and MDA-MB-468GFP-LN human breast cancer cell lines (an isogenic, paired lymphatic metastasis cell line model using Affymetrix gene expression (U133, promoter (1.0R, and SNP/CNV (SNP 6.0 microarray platforms to correlate data from gene expression, epigenetic (DNA methylation, and combination copy number variant/single nucleotide polymorphism microarrays. Using Partek Software and Ingenuity Pathway Analysis we integrated datasets from these three platforms and detected multiple hypomethylation and hypermethylation events. Many of these epigenetic alterations correlated with gene expression changes. In addition, gene dosage events correlated with the karyotypic differences observed between the cell lines and were reflected in specific promoter methylation patterns. Gene subsets were identified that correlated hyper (and hypo methylation with the loss (or gain of gene expression and in parallel, with gene dosage losses and gains, respectively. Individual gene targets from these subsets were also validated for their methylation, expression and copy number status, and susceptible gene pathways were identified that may indicate how selective advantage drives the processes of tumourigenesis and metastasis.Our approach allows more precisely profiling of functionally relevant epigenetic signatures that are associated with cancer progression and metastasis.

  19. Biological data warehousing system for identifying transcriptional regulatory sites from gene expressions of microarray data.

    Science.gov (United States)

    Tsou, Ann-Ping; Sun, Yi-Ming; Liu, Chia-Lin; Huang, Hsien-Da; Horng, Jorng-Tzong; Tsai, Meng-Feng; Liu, Baw-Juine

    2006-07-01

    Identification of transcriptional regulatory sites plays an important role in the investigation of gene regulation. For this propose, we designed and implemented a data warehouse to integrate multiple heterogeneous biological data sources with data types such as text-file, XML, image, MySQL database model, and Oracle database model. The utility of the biological data warehouse in predicting transcriptional regulatory sites of coregulated genes was explored using a synexpression group derived from a microarray study. Both of the binding sites of known transcription factors and predicted over-represented (OR) oligonucleotides were demonstrated for the gene group. The potential biological roles of both known nucleotides and one OR nucleotide were demonstrated using bioassays. Therefore, the results from the wet-lab experiments reinforce the power and utility of the data warehouse as an approach to the genome-wide search for important transcription regulatory elements that are the key to many complex biological systems.

  20. Identifying significant genetic regulatory networks in the prostate cancer from microarray data based on transcription factor analysis and conditional independency

    Directory of Open Access Journals (Sweden)

    Yeh Cheng-Yu

    2009-12-01

    Full Text Available Abstract Background Prostate cancer is a world wide leading cancer and it is characterized by its aggressive metastasis. According to the clinical heterogeneity, prostate cancer displays different stages and grades related to the aggressive metastasis disease. Although numerous studies used microarray analysis and traditional clustering method to identify the individual genes during the disease processes, the important gene regulations remain unclear. We present a computational method for inferring genetic regulatory networks from micorarray data automatically with transcription factor analysis and conditional independence testing to explore the potential significant gene regulatory networks that are correlated with cancer, tumor grade and stage in the prostate cancer. Results To deal with missing values in microarray data, we used a K-nearest-neighbors (KNN algorithm to determine the precise expression values. We applied web services technology to wrap the bioinformatics toolkits and databases to automatically extract the promoter regions of DNA sequences and predicted the transcription factors that regulate the gene expressions. We adopt the microarray datasets consists of 62 primary tumors, 41 normal prostate tissues from Stanford Microarray Database (SMD as a target dataset to evaluate our method. The predicted results showed that the possible biomarker genes related to cancer and denoted the androgen functions and processes may be in the development of the prostate cancer and promote the cell death in cell cycle. Our predicted results showed that sub-networks of genes SREBF1, STAT6 and PBX1 are strongly related to a high extent while ETS transcription factors ELK1, JUN and EGR2 are related to a low extent. Gene SLC22A3 may explain clinically the differentiation associated with the high grade cancer compared with low grade cancer. Enhancer of Zeste Homolg 2 (EZH2 regulated by RUNX1 and STAT3 is correlated to the pathological stage

  1. Identifying significant genetic regulatory networks in the prostate cancer from microarray data based on transcription factor analysis and conditional independency.

    Science.gov (United States)

    Yeh, Hsiang-Yuan; Cheng, Shih-Wu; Lin, Yu-Chun; Yeh, Cheng-Yu; Lin, Shih-Fang; Soo, Von-Wun

    2009-12-21

    Prostate cancer is a world wide leading cancer and it is characterized by its aggressive metastasis. According to the clinical heterogeneity, prostate cancer displays different stages and grades related to the aggressive metastasis disease. Although numerous studies used microarray analysis and traditional clustering method to identify the individual genes during the disease processes, the important gene regulations remain unclear. We present a computational method for inferring genetic regulatory networks from micorarray data automatically with transcription factor analysis and conditional independence testing to explore the potential significant gene regulatory networks that are correlated with cancer, tumor grade and stage in the prostate cancer. To deal with missing values in microarray data, we used a K-nearest-neighbors (KNN) algorithm to determine the precise expression values. We applied web services technology to wrap the bioinformatics toolkits and databases to automatically extract the promoter regions of DNA sequences and predicted the transcription factors that regulate the gene expressions. We adopt the microarray datasets consists of 62 primary tumors, 41 normal prostate tissues from Stanford Microarray Database (SMD) as a target dataset to evaluate our method. The predicted results showed that the possible biomarker genes related to cancer and denoted the androgen functions and processes may be in the development of the prostate cancer and promote the cell death in cell cycle. Our predicted results showed that sub-networks of genes SREBF1, STAT6 and PBX1 are strongly related to a high extent while ETS transcription factors ELK1, JUN and EGR2 are related to a low extent. Gene SLC22A3 may explain clinically the differentiation associated with the high grade cancer compared with low grade cancer. Enhancer of Zeste Homolg 2 (EZH2) regulated by RUNX1 and STAT3 is correlated to the pathological stage. We provide a computational framework to reconstruct

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

    Science.gov (United States)

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

    2009-07-16

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

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

    DEFF Research Database (Denmark)

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

    2002-01-01

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

  4. Differential and correlation analyses of microarray gene expression data in the CEPH Utah families

    DEFF Research Database (Denmark)

    Tan, Qihua; Zhao, Jinghua; Li, Shuxia

    2008-01-01

    -regulated genes identifies cell-cell signaling as an important functional category implicated in human aging. Sex-dependent gene expression is characterized by genes that may escape X-inactivation and, most interestingly, such a pattern is not affected by the aging process. Analysis on sibship correlation on gene...... expression revealed a large number of significant genes suggesting the importance of a genetic mechanism in regulating transcriptional activities. In addition, we observe an interesting pattern of sibship correlation on gene expression that increases exponentially with the mean of gene expression reflecting...

  5. Microarray profiling of mononuclear peripheral blood cells identifies novel candidate genes related to chemoradiation response in rectal cancer.

    Directory of Open Access Journals (Sweden)

    Pablo Palma

    Full Text Available Preoperative chemoradiation significantly improves oncological outcome in locally advanced rectal cancer. However there is no effective method of predicting tumor response to chemoradiation in these patients. Peripheral blood mononuclear cells have emerged recently as pathology markers of cancer and other diseases, making possible their use as therapy predictors. Furthermore, the importance of the immune response in radiosensivity of solid organs led us to hypothesized that microarray gene expression profiling of peripheral blood mononuclear cells could identify patients with response to chemoradiation in rectal cancer. Thirty five 35 patients with locally advanced rectal cancer were recruited initially to perform the study. Peripheral blood samples were obtained before neaodjuvant treatment. RNA was extracted and purified to obtain cDNA and cRNA for hybridization of microarrays included in Human WG CodeLink bioarrays. Quantitative real time PCR was used to validate microarray experiment data. Results were correlated with pathological response, according to Mandard´s criteria and final UICC Stage (patients with tumor regression grade 1-2 and downstaging being defined as responders and patients with grade 3-5 and no downstaging as non-responders. Twenty seven out of 35 patients were finally included in the study. We performed a multiple t-test using Significance Analysis of Microarrays, to find those genes differing significantly in expression, between responders (n = 11 and non-responders (n = 16 to CRT. The differently expressed genes were: BC 035656.1, CIR, PRDM2, CAPG, FALZ, HLA-DPB2, NUPL2, and ZFP36. The measurement of FALZ (p = 0.029 gene expression level determined by qRT-PCR, showed statistically significant differences between the two groups. Gene expression profiling reveals novel genes in peripheral blood samples of mononuclear cells that could predict responders and non-responders to chemoradiation in patients with

  6. Extracting gene expression patterns and identifying co-expressed genes from microarray data reveals biologically responsive processes

    Directory of Open Access Journals (Sweden)

    Paules Richard S

    2007-11-01

    Full Text Available Abstract Background A common observation in the analysis of gene expression data is that many genes display similarity in their expression patterns and therefore appear to be co-regulated. However, the variation associated with microarray data and the complexity of the experimental designs make the acquisition of co-expressed genes a challenge. We developed a novel method for Extracting microarray gene expression Patterns and Identifying co-expressed Genes, designated as EPIG. The approach utilizes the underlying structure of gene expression data to extract patterns and identify co-expressed genes that are responsive to experimental conditions. Results Through evaluation of the correlations among profiles, the magnitude of variation in gene expression profiles, and profile signal-to-noise ratio's, EPIG extracts a set of patterns representing co-expressed genes. The method is shown to work well with a simulated data set and microarray data obtained from time-series studies of dauer recovery and L1 starvation in C. elegans and after ultraviolet (UV or ionizing radiation (IR-induced DNA damage in diploid human fibroblasts. With the simulated data set, EPIG extracted the appropriate number of patterns which were more stable and homogeneous than the set of patterns that were determined using the CLICK or CAST clustering algorithms. However, CLICK performed better than EPIG and CAST with respect to the average correlation between clusters/patterns of the simulated data. With real biological data, EPIG extracted more dauer-specific patterns than CLICK. Furthermore, analysis of the IR/UV data revealed 18 unique patterns and 2661 genes out of approximately 17,000 that were identified as significantly expressed and categorized to the patterns by EPIG. The time-dependent patterns displayed similar and dissimilar responses between IR and UV treatments. Gene Ontology analysis applied to each pattern-related subset of co-expressed genes revealed underlying

  7. SVD identifies transcript length distribution functions from DNA microarray data and reveals evolutionary forces globally affecting GBM metabolism.

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    Nicolas M Bertagnolli

    Full Text Available To search for evolutionary forces that might act upon transcript length, we use the singular value decomposition (SVD to identify the length distribution functions of sets and subsets of human and yeast transcripts from profiles of mRNA abundance levels across gel electrophoresis migration distances that were previously measured by DNA microarrays. We show that the SVD identifies the transcript length distribution functions as "asymmetric generalized coherent states" from the DNA microarray data and with no a-priori assumptions. Comparing subsets of human and yeast transcripts of the same gene ontology annotations, we find that in both disparate eukaryotes, transcripts involved in protein synthesis or mitochondrial metabolism are significantly shorter than typical, and in particular, significantly shorter than those involved in glucose metabolism. Comparing the subsets of human transcripts that are overexpressed in glioblastoma multiforme (GBM or normal brain tissue samples from The Cancer Genome Atlas, we find that GBM maintains normal brain overexpression of significantly short transcripts, enriched in transcripts that are involved in protein synthesis or mitochondrial metabolism, but suppresses normal overexpression of significantly longer transcripts, enriched in transcripts that are involved in glucose metabolism and brain activity. These global relations among transcript length, cellular metabolism and tumor development suggest a previously unrecognized physical mode for tumor and normal cells to differentially regulate metabolism in a transcript length-dependent manner. The identified distribution functions support a previous hypothesis from mathematical modeling of evolutionary forces that act upon transcript length in the manner of the restoring force of the harmonic oscillator.

  8. Identifying molecular subtypes in human colon cancer using gene expression and DNA methylation microarray data

    OpenAIRE

    REN, ZHONGLU; WANG, WENHUI; LI, JINMING

    2015-01-01

    Identifying colon cancer subtypes based on molecular signatures may allow for a more rational, patient-specific approach to therapy in the future. Classifications using gene expression data have been attempted before with little concordance between the different studies carried out. In this study we aimed to uncover subtypes of colon cancer that have distinct biological characteristics and identify a set of novel biomarkers which could best reflect the clinical and/or biological characteristi...

  9. Differential gene expression from genome-wide microarray analyses distinguishes Lohmann Selected Leghorn and Lohmann Brown layers.

    Directory of Open Access Journals (Sweden)

    Christin Habig

    Full Text Available The Lohmann Selected Leghorn (LSL and Lohmann Brown (LB layer lines have been selected for high egg production since more than 50 years and belong to the worldwide leading commercial layer lines. The objectives of the present study were to characterize the molecular processes that are different among these two layer lines using whole genome RNA expression profiles. The hens were kept in the newly developed small group housing system Eurovent German with two different group sizes. Differential expression was observed for 6,276 microarray probes (FDR adjusted P-value <0.05 among the two layer lines LSL and LB. A 2-fold or greater change in gene expression was identified on 151 probe sets. In LSL, 72 of the 151 probe sets were up- and 79 of them were down-regulated. Gene ontology (GO enrichment analysis accounting for biological processes evinced 18 GO-terms for the 72 probe sets with higher expression in LSL, especially those taking part in immune system processes and membrane organization. A total of 32 enriched GO-terms were determined among the 79 down-regulated probe sets of LSL. Particularly, these terms included phosphorus metabolic processes and signaling pathways. In conclusion, the phenotypic differences among the two layer lines LSL and LB are clearly reflected in their gene expression profiles of the cerebrum. These novel findings provide clues for genes involved in economically important line characteristics of commercial laying hens.

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

    Directory of Open Access Journals (Sweden)

    Nupur Dasgupta

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

  11. Expression microarray identifies the unliganded glucocorticoid receptor as a regulator of gene expression in mammary epithelial cells

    International Nuclear Information System (INIS)

    Ritter, Heather D; Mueller, Christopher R

    2014-01-01

    While glucocorticoids and the liganded glucocorticoid receptor (GR) have a well-established role in the maintenance of differentiation and suppression of apoptosis in breast tissue, the involvement of unliganded GR in cellular processes is less clear. Our previous studies implicated unliganded GR as a positive regulator of the BRCA1 tumour suppressor gene in the absence of glucocorticoid hormone, which suggested it could play a similar role in the regulation of other genes. An shRNA vector directed against GR was used to create mouse mammary cell lines with depleted endogenous levels of this receptor in order to further characterize the role of GR in breast cells. An expression microarray screen for targets of unliganded GR was performed using our GR-depleted cell lines maintained in the absence of glucocorticoids. Candidate genes positively regulated by unliganded GR were identified, classified by Gene Ontology and Ingenuity Pathway Analysis, and validated using quantitative real-time reverse transcriptase PCR. Chromatin immunoprecipitation and dual luciferase expression assays were conducted to further investigate the mechanism through which unliganded GR regulates these genes. Expression microarray analysis revealed 260 targets negatively regulated and 343 targets positively regulated by unliganded GR. A number of the positively regulated targets were involved in pro-apoptotic networks, possibly opposing the activity of liganded GR targets. Validation and further analysis of five candidates from the microarray indicated that two of these, Hsd11b1 and Ch25h, were regulated by unliganded GR in a manner similar to Brca1 during glucocorticoid treatment. Furthermore, GR was shown to interact directly with and upregulate the Ch25h promoter in the absence, but not the presence, of hydrocortisone (HC), confirming our previously described model of gene regulation by unliganded GR. This work presents the first identification of targets of unliganded GR. We propose that

  12. Identifying molecular subtypes in human colon cancer using gene expression and DNA methylation microarray data.

    Science.gov (United States)

    Ren, Zhonglu; Wang, Wenhui; Li, Jinming

    2016-02-01

    Identifying colon cancer subtypes based on molecular signatures may allow for a more rational, patient-specific approach to therapy in the future. Classifications using gene expression data have been attempted before with little concordance between the different studies carried out. In this study we aimed to uncover subtypes of colon cancer that have distinct biological characteristics and identify a set of novel biomarkers which could best reflect the clinical and/or biological characteristics of each subtype. Clustering analysis and discriminant analysis were utilized to discover the subtypes in two different molecular levels on 153 colon cancer samples from The Cancer Genome Atlas (TCGA) Data Portal. At gene expression level, we identified two major subtypes, ECL1 (expression cluster 1) and ECL2 (expression cluster 2) and a list of signature genes. Due to the heterogeneity of colon cancer, the subtype ECL1 can be further subdivided into three nested subclasses, and HOTAIR were found upregulated in subclass 2. At DNA methylation level, we uncovered three major subtypes, MCL1 (methylation cluster 1), MCL2 (methylation cluster 2) and MCL3 (methylation cluster 3). We found only three subtypes of CpG island methylator phenotype (CIMP) in colon cancer instead of the four subtypes in the previous reports, and we found no sufficient evidence to subdivide MCL3 into two distinct subgroups.

  13. Microarray analysis identifies keratin loci as sensitive biomarkers for thyroid hormone disruption in the salamander Ambystoma mexicanum.

    Science.gov (United States)

    Page, Robert B; Monaghan, James R; Samuels, Amy K; Smith, Jeramiah J; Beachy, Christopher K; Voss, S Randal

    2007-02-01

    Ambystomatid salamanders offer several advantages for endocrine disruption research, including genomic and bioinformatics resources, an accessible laboratory model (Ambystoma mexicanum), and natural lineages that are broadly distributed among North American habitats. We used microarray analysis to measure the relative abundance of transcripts isolated from A. mexicanum epidermis (skin) after exogenous application of thyroid hormone (TH). Only one gene had a >2-fold change in transcript abundance after 2 days of TH treatment. However, hundreds of genes showed significantly different transcript levels at days 12 and 28 in comparison to day 0. A list of 123 TH-responsive genes was identified using statistical, BLAST, and fold level criteria. Cluster analysis identified two groups of genes with similar transcription patterns: up-regulated versus down-regulated. Most notably, several keratins exhibited dramatic (1000 fold) increases or decreases in transcript abundance. Keratin gene expression changes coincided with morphological remodeling of epithelial tissues. This suggests that keratin loci can be developed as sensitive biomarkers to assay temporal disruptions of larval-to-adult gene expression programs. Our study has identified the first collection of loci that are regulated during TH-induced metamorphosis in a salamander, thus setting the stage for future investigations of TH disruption in the Mexican axolotl and other salamanders of the genus Ambystoma.

  14. Integrated microarray and ChIP analysis identifies multiple Foxa2 dependent target genes in the notochord.

    Science.gov (United States)

    Tamplin, Owen J; Cox, Brian J; Rossant, Janet

    2011-12-15

    The node and notochord are key tissues required for patterning of the vertebrate body plan. Understanding the gene regulatory network that drives their formation and function is therefore important. Foxa2 is a key transcription factor at the top of this genetic hierarchy and finding its targets will help us to better understand node and notochord development. We performed an extensive microarray-based gene expression screen using sorted embryonic notochord cells to identify early notochord-enriched genes. We validated their specificity to the node and notochord by whole mount in situ hybridization. This provides the largest available resource of notochord-expressed genes, and therefore candidate Foxa2 target genes in the notochord. Using existing Foxa2 ChIP-seq data from adult liver, we were able to identify a set of genes expressed in the notochord that had associated regions of Foxa2-bound chromatin. Given that Foxa2 is a pioneer transcription factor, we reasoned that these sites might represent notochord-specific enhancers. Candidate Foxa2-bound regions were tested for notochord specific enhancer function in a zebrafish reporter assay and 7 novel notochord enhancers were identified. Importantly, sequence conservation or predictive models could not have readily identified these regions. Mutation of putative Foxa2 binding elements in two of these novel enhancers abrogated reporter expression and confirmed their Foxa2 dependence. The combination of highly specific gene expression profiling and genome-wide ChIP analysis is a powerful means of understanding developmental pathways, even for small cell populations such as the notochord. Copyright © 2011 Elsevier Inc. All rights reserved.

  15. A reverse-phase protein microarray-based screen identifies host signaling dynamics upon Burkholderia spp. infection

    Directory of Open Access Journals (Sweden)

    Chih-Yuan eChiang

    2015-07-01

    Full Text Available Burkholderia is a diverse genus of Gram-negative bacteria that cause high mortality rate in humans and cattle. The lack of effective therapeutic treatments poses serious public health threats. Insights toward host-Burkholderia spp. interaction are critical in understanding the pathogenesis of the infection as well as identifying therapeutic targets for drug development. Reverse-phase protein microarray (RPMA technology was previously proven to characterize novel biomarkers and molecular signatures associated with infectious diseases and cancers. In the present study, this technology was utilized to interrogate changes in host protein expression and post-translational phosphorylation events in macrophages infected with a collection of geographically diverse strains of Burkholderia spp. The expression or phosphorylation state of 25 proteins was altered during Burkholderia spp. infections and of which eight proteins were selected for further validation by immunoblotting. Kinetic expression patterns of phosphorylated AMPK-α1, Src, and GSK3β suggested the importance of their roles in regulating Burkholderia spp. mediated innate immune responses. Modulating inflammatory responses by perturbing AMPK-α1, Src, and GSK3β activities may provide novel therapeutic targets for future treatments.

  16. Carbohydrate microarrays

    DEFF Research Database (Denmark)

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

    2012-01-01

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

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

    Science.gov (United States)

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

    2015-12-01

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

  18. Chromosomal microarray testing identifies a 4p terminal region associated with seizures in Wolf–Hirschhorn syndrome

    Science.gov (United States)

    South, Sarah T; Lortz, Amanda; Hensel, Charles H; Sdano, Mallory R; Vanzo, Rena J; Martin, Megan M; Peiffer, Andreas; Lambert, Christophe G; Calhoun, Amy; Carey, John C; Battaglia, Agatino

    2016-01-01

    Background Wolf–Hirschhorn syndrome (WHS) is a contiguous gene deletion syndrome involving variable size deletions of the 4p16.3 region. Seizures are frequently, but not always, associated with WHS. We hypothesised that the size and location of the deleted region may correlate with seizure presentation. Methods Using chromosomal microarray analysis, we finely mapped the breakpoints of copy number variants (CNVs) in 48 individuals with WHS. Seizure phenotype data were collected through parent-reported answers to a comprehensive questionnaire and supplemented with available medical records. Results We observed a significant correlation between the presence of an interstitial 4p deletion and lack of a seizure phenotype (Fisher's exact test p=3.59e-6). In our cohort, there were five individuals with interstitial deletions with a distal breakpoint at least 751 kbp proximal to the 4p terminus. Four of these individuals have never had an observable seizure, and the fifth individual had a single febrile seizure at the age of 1.5 years. All other individuals in our cohort whose deletions encompass the terminal 751 kbp region report having seizures typical of WHS. Additional examples from the literature corroborate these observations and further refine the candidate seizure susceptibility region to a region 197 kbp in size, starting 368 kbp from the terminus of chromosome 4. Conclusions We identify a small terminal region of chromosome 4p that represents a seizure susceptibility region. Deletion of this region in the context of WHS is sufficient for seizure occurrence. PMID:26747863

  19. Chromosomal microarray testing identifies a 4p terminal region associated with seizures in Wolf-Hirschhorn syndrome.

    Science.gov (United States)

    Ho, Karen S; South, Sarah T; Lortz, Amanda; Hensel, Charles H; Sdano, Mallory R; Vanzo, Rena J; Martin, Megan M; Peiffer, Andreas; Lambert, Christophe G; Calhoun, Amy; Carey, John C; Battaglia, Agatino

    2016-04-01

    Wolf-Hirschhorn syndrome (WHS) is a contiguous gene deletion syndrome involving variable size deletions of the 4p16.3 region. Seizures are frequently, but not always, associated with WHS. We hypothesised that the size and location of the deleted region may correlate with seizure presentation. Using chromosomal microarray analysis, we finely mapped the breakpoints of copy number variants (CNVs) in 48 individuals with WHS. Seizure phenotype data were collected through parent-reported answers to a comprehensive questionnaire and supplemented with available medical records. We observed a significant correlation between the presence of an interstitial 4p deletion and lack of a seizure phenotype (Fisher's exact test p=3.59e-6). In our cohort, there were five individuals with interstitial deletions with a distal breakpoint at least 751 kbp proximal to the 4p terminus. Four of these individuals have never had an observable seizure, and the fifth individual had a single febrile seizure at the age of 1.5 years. All other individuals in our cohort whose deletions encompass the terminal 751 kbp region report having seizures typical of WHS. Additional examples from the literature corroborate these observations and further refine the candidate seizure susceptibility region to a region 197 kbp in size, starting 368 kbp from the terminus of chromosome 4. We identify a small terminal region of chromosome 4p that represents a seizure susceptibility region. Deletion of this region in the context of WHS is sufficient for seizure occurrence. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/

  20. Identifying null meta-analyses that are ripe for updating

    Directory of Open Access Journals (Sweden)

    Fang Manchun

    2003-07-01

    Full Text Available Abstract Background As an increasingly large number of meta-analyses are published, quantitative methods are needed to help clinicians and systematic review teams determine when meta-analyses are not up to date. Methods We propose new methods for determining when non-significant meta-analytic results might be overturned, based on a prediction of the number of participants required in new studies. To guide decision making, we introduce the "new participant ratio", the ratio of the actual number of participants in new studies to the predicted number required to obtain statistical significance. A simulation study was conducted to study the performance of our methods and a real meta-analysis provides further evidence. Results In our three simulation configurations, our diagnostic test for determining whether a meta-analysis is out of date had sensitivity of 55%, 62%, and 49% with corresponding specificity of 85%, 80%, and 90% respectively. Conclusions Simulations suggest that our methods are able to detect out-of-date meta-analyses. These quick and approximate methods show promise for use by systematic review teams to help decide whether to commit the considerable resources required to update a meta-analysis. Further investigation and evaluation of the methods is required before they can be recommended for general use.

  1. Timecourse microarray analyses reveal global changes in gene expression of susceptible Glycine max (soybean) roots during infection by Heterodera glycines (soybean cyst nematode).

    Science.gov (United States)

    Alkharouf, Nadim W; Klink, Vincent P; Chouikha, Imed B; Beard, Hunter S; MacDonald, Margaret H; Meyer, Susan; Knap, Halina T; Khan, Rana; Matthews, Benjamin F

    2006-09-01

    Changes in gene expression within roots of Glycine max (soybean), cv. Kent, susceptible to infection by Heterodera glycines (the soybean cyst nematode [SCN]), at 6, 12, and 24 h, and 2, 4, 6, and 8 days post-inoculation were monitored using microarrays containing more than 6,000 cDNA inserts. Replicate, independent biological samples were examined at each time point. Gene expression was analyzed statistically using T-tests, ANOVA, clustering algorithms, and online analytical processing (OLAP). These analyses allow the user to query the data in several ways without importing the data into third-party software. RT-PCR confirmed that WRKY6 transcription factor, trehalose phosphate synthase, EIF4a, Skp1, and CLB1 were differentially induced across most time-points. Other genes induced across most timepoints included lipoxygenase, calmodulin, phospholipase C, metallothionein-like protein, and chalcone reductase. RT-PCR demonstrated enhanced expression during the first 12 h of infection for Kunitz trypsin inhibitor and sucrose synthase. The stress-related gene, SAM-22, phospholipase D and 12-oxophytodienoate reductase were also induced at the early time-points. At 6 and 8 dpi there was an abundance of transcripts expressed that encoded genes involved in transcription and protein synthesis. Some of those genes included ribosomal proteins, and initiation and elongation factors. Several genes involved in carbon metabolism and transport were also more abundant. Those genes included glyceraldehyde 3-phosphate dehydrogenase, fructose-bisphosphate aldolase and sucrose synthase. These results identified specific changes in gene transcript levels triggered by infection of susceptible soybean roots by SCN.

  2. Genomic analyses identify molecular subtypes of pancreatic cancer.

    Science.gov (United States)

    Bailey, Peter; Chang, David K; Nones, Katia; Johns, Amber L; Patch, Ann-Marie; Gingras, Marie-Claude; Miller, David K; Christ, Angelika N; Bruxner, Tim J C; Quinn, Michael C; Nourse, Craig; Murtaugh, L Charles; Harliwong, Ivon; Idrisoglu, Senel; Manning, Suzanne; Nourbakhsh, Ehsan; Wani, Shivangi; Fink, Lynn; Holmes, Oliver; Chin, Venessa; Anderson, Matthew J; Kazakoff, Stephen; Leonard, Conrad; Newell, Felicity; Waddell, Nick; Wood, Scott; Xu, Qinying; Wilson, Peter J; Cloonan, Nicole; Kassahn, Karin S; Taylor, Darrin; Quek, Kelly; Robertson, Alan; Pantano, Lorena; Mincarelli, Laura; Sanchez, Luis N; Evers, Lisa; Wu, Jianmin; Pinese, Mark; Cowley, Mark J; Jones, Marc D; Colvin, Emily K; Nagrial, Adnan M; Humphrey, Emily S; Chantrill, Lorraine A; Mawson, Amanda; Humphris, Jeremy; Chou, Angela; Pajic, Marina; Scarlett, Christopher J; Pinho, Andreia V; Giry-Laterriere, Marc; Rooman, Ilse; Samra, Jaswinder S; Kench, James G; Lovell, Jessica A; Merrett, Neil D; Toon, Christopher W; Epari, Krishna; Nguyen, Nam Q; Barbour, Andrew; Zeps, Nikolajs; Moran-Jones, Kim; Jamieson, Nigel B; Graham, Janet S; Duthie, Fraser; Oien, Karin; Hair, Jane; Grützmann, Robert; Maitra, Anirban; Iacobuzio-Donahue, Christine A; Wolfgang, Christopher L; Morgan, Richard A; Lawlor, Rita T; Corbo, Vincenzo; Bassi, Claudio; Rusev, Borislav; Capelli, Paola; Salvia, Roberto; Tortora, Giampaolo; Mukhopadhyay, Debabrata; Petersen, Gloria M; Munzy, Donna M; Fisher, William E; Karim, Saadia A; Eshleman, James R; Hruban, Ralph H; Pilarsky, Christian; Morton, Jennifer P; Sansom, Owen J; Scarpa, Aldo; Musgrove, Elizabeth A; Bailey, Ulla-Maja Hagbo; Hofmann, Oliver; Sutherland, Robert L; Wheeler, David A; Gill, Anthony J; Gibbs, Richard A; Pearson, John V; Waddell, Nicola; Biankin, Andrew V; Grimmond, Sean M

    2016-03-03

    Integrated genomic analysis of 456 pancreatic ductal adenocarcinomas identified 32 recurrently mutated genes that aggregate into 10 pathways: KRAS, TGF-β, WNT, NOTCH, ROBO/SLIT signalling, G1/S transition, SWI-SNF, chromatin modification, DNA repair and RNA processing. Expression analysis defined 4 subtypes: (1) squamous; (2) pancreatic progenitor; (3) immunogenic; and (4) aberrantly differentiated endocrine exocrine (ADEX) that correlate with histopathological characteristics. Squamous tumours are enriched for TP53 and KDM6A mutations, upregulation of the TP63∆N transcriptional network, hypermethylation of pancreatic endodermal cell-fate determining genes and have a poor prognosis. Pancreatic progenitor tumours preferentially express genes involved in early pancreatic development (FOXA2/3, PDX1 and MNX1). ADEX tumours displayed upregulation of genes that regulate networks involved in KRAS activation, exocrine (NR5A2 and RBPJL), and endocrine differentiation (NEUROD1 and NKX2-2). Immunogenic tumours contained upregulated immune networks including pathways involved in acquired immune suppression. These data infer differences in the molecular evolution of pancreatic cancer subtypes and identify opportunities for therapeutic development.

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

    Energy Technology Data Exchange (ETDEWEB)

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

    2012-08-24

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

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

    Science.gov (United States)

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

    2012-01-01

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

  5. Microarray analysis to identify the similarities and differences of pathogenesis between aortic occlusive disease and abdominal aortic aneurysm.

    Science.gov (United States)

    Wang, Guofu; Bi, Lechang; Wang, Gaofeng; Huang, Feilai; Lu, Mingjing; Zhu, Kai

    2018-06-01

    Objectives Expression profile of GSE57691 was analyzed to identify the similarities and differences between aortic occlusive disease and abdominal aortic aneurysm. Methods The expression profile of GSE57691 was downloaded from Gene Expression Omnibus database, including 20 small abdominal aortic aneurysm samples, 29 large abdominal aortic aneurysm samples, 9 aortic occlusive disease samples, and 10 control samples. Using the limma package in R, the differentially expressed genes were screened. Followed by enrichment analysis was performed for the differentially expressed genes using database for annotation, visualization, and integrated discovery online tool. Based on string online tool and Cytoscape software, protein-protein interaction network and module analyses were carried out. Moreover, integrated TF platform database and Cytoscape software were used for constructing transcriptional regulatory networks. Results As a result, 1757, 354, and 396 differentially expressed genes separately were identified in aortic occlusive disease, large abdominal aortic aneurysm, and small abdominal aortic aneurysm samples. UBB was significantly enriched in proteolysis related pathways with a high degree in three groups. SPARCL1 was another gene shared by these groups and regulated by NFIA, which had a high degree in transcriptional regulatory network. ACTB, a significant upregulated gene in abdominal aortic aneurysm samples, could be regulated by CLIC4, which was significantly enriched in cell motions. ACLY and NFIB were separately identified in aortic occlusive disease and small abdominal aortic aneurysm samples, and separately enriched in lipid metabolism and negative regulation of cell proliferation. Conclusions The downregulated UBB, NFIA, and SPARCL1 might play key roles in both aortic occlusive disease and abdominal aortic aneurysm, while the upregulated ACTB might only involve in abdominal aortic aneurysm. ACLY and NFIB were specifically involved in aortic occlusive

  6. Microarray-based approach identifies microRNAs and their target functional patterns in polycystic kidney disease

    Directory of Open Access Journals (Sweden)

    Boehn Susanne NE

    2008-12-01

    Full Text Available Abstract Background MicroRNAs (miRNAs play key roles in mammalian gene expression and several cellular processes, including differentiation, development, apoptosis and cancer pathomechanisms. Recently the biological importance of primary cilia has been recognized in a number of human genetic diseases. Numerous disorders are related to cilia dysfunction, including polycystic kidney disease (PKD. Although involvement of certain genes and transcriptional networks in PKD development has been shown, not much is known how they are regulated molecularly. Results Given the emerging role of miRNAs in gene expression, we explored the possibilities of miRNA-based regulations in PKD. Here, we analyzed the simultaneous expression changes of miRNAs and mRNAs by microarrays. 935 genes, classified into 24 functional categories, were differentially regulated between PKD and control animals. In parallel, 30 miRNAs were differentially regulated in PKD rats: our results suggest that several miRNAs might be involved in regulating genetic switches in PKD. Furthermore, we describe some newly detected miRNAs, miR-31 and miR-217, in the kidney which have not been reported previously. We determine functionally related gene sets, or pathways to reveal the functional correlation between differentially expressed mRNAs and miRNAs. Conclusion We find that the functional patterns of predicted miRNA targets and differentially expressed mRNAs are similar. Our results suggest an important role of miRNAs in specific pathways underlying PKD.

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

    Science.gov (United States)

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

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

    Directory of Open Access Journals (Sweden)

    Bordeaux John M

    2011-05-01

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

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

    Science.gov (United States)

    2011-01-01

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

  10. Microarray Analyses of Genes Differentially Expressed by Diet (Black Beans and Soy Flour) during Azoxymethane-Induced Colon Carcinogenesis in Rats.

    Science.gov (United States)

    Rondini, Elizabeth A; Bennink, Maurice R

    2012-01-01

    We previously demonstrated that black bean (BB) and soy flour (SF)-based diets inhibit azoxymethane (AOM)-induced colon cancer. The objective of this study was to identify genes altered by carcinogen treatment in normal-appearing colonic mucosa and those attenuated by bean feeding. Ninety-five male F344 rats were fed control (AIN) diets upon arrival. At 4 and 5 weeks, rats were injected with AOM (15 mg/kg) or saline and one week later administered an AIN, BB-, or SF-based diet. Rats were sacrificed after 31 weeks, and microarrays were conducted on RNA isolated from the distal colonic mucosa. AOM treatment induced a number of genes involved in immunity, including several MHC II-associated antigens and innate defense genes (RatNP-3, Lyz2, Pla2g2a). BB- and SF-fed rats exhibited a higher expression of genes involved in energy metabolism and water and sodium absorption and lower expression of innate (RatNP-3, Pla2g2a, Tlr4, Dmbt1) and cell cycle-associated (Cdc2, Ccnb1, Top2a) genes. Genes involved in the extracellular matrix (Col1a1, Fn1) and innate immunity (RatNP-3, Pla2g2a) were induced by AOM in all diets, but to a lower extent in bean-fed animals. This profile suggests beans inhibit colon carcinogenesis by modulating cellular kinetics and reducing inflammation, potentially by preserving mucosal barrier function.

  11. Molecular characterization of NRXN1 deletions from 19,263 clinical microarray cases identifies exons important for neurodevelopmental disease expression

    Science.gov (United States)

    Lowther, Chelsea; Speevak, Marsha; Armour, Christine M.; Goh, Elaine S.; Graham, Gail E.; Li, Chumei; Zeesman, Susan; Nowaczyk, Malgorzata J.M.; Schultz, Lee-Anne; Morra, Antonella; Nicolson, Rob; Bikangaga, Peter; Samdup, Dawa; Zaazou, Mostafa; Boyd, Kerry; Jung, Jack H.; Siu, Victoria; Rajguru, Manjulata; Goobie, Sharan; Tarnopolsky, Mark A.; Prasad, Chitra; Dick, Paul T.; Hussain, Asmaa S.; Walinga, Margreet; Reijenga, Renske G.; Gazzellone, Matthew; Lionel, Anath C.; Marshall, Christian R.; Scherer, Stephen W.; Stavropoulos, Dimitri J.; McCready, Elizabeth; Bassett, Anne S.

    2016-01-01

    Purpose The purpose of the current study was to assess the penetrance of NRXN1 deletions. Methods We compared the prevalence and genomic extent of NRXN1 deletions identified among 19,263 clinically referred cases to that of 15,264 controls. The burden of additional clinically relevant CNVs was used as a proxy to estimate the relative penetrance of NRXN1 deletions. Results We identified 41 (0.21%) previously unreported exonic NRXN1 deletions ascertained for developmental delay/intellectual disability, significantly greater than in controls [OR=8.14 (95% CI 2.91–22.72), p< 0.0001)]. Ten (22.7%) of these had a second clinically relevant CNV. Subjects with a deletion near the 3′ end of NRXN1 were significantly more likely to have a second rare CNV than subjects with a 5′ NRXN1 deletion [OR=7.47 (95% CI 2.36–23.61), p=0.0006]. The prevalence of intronic NRXN1 deletions was not statistically different between cases and controls (p=0.618). The majority (63.2%) of intronic NRXN1 deletion cases had a second rare CNV, a two-fold greater prevalence than for exonic NRXN1 deletion cases (p=0.0035). Conclusions The results support the importance of exons near the 5′ end of NRXN1 in the expression of neurodevelopmental disorders. Intronic NRXN1 deletions do not appear to substantially increase the risk for clinical phenotypes. PMID:27195815

  12. New Blood Pressure-Associated Loci Identified in Meta-Analyses of 475 000 Individuals

    DEFF Research Database (Denmark)

    Kraja, Aldi T.; Cook, James P.; Warren, Helen R.

    2017-01-01

    Background - Genome-wide association studies have recently identified >400 loci that harbor DNA sequence variants that influence blood pressure (BP). Our earlier studies identified and validated 56 single nucleotide variants (SNVs) associated with BP from meta-analyses of exome chip genotype data...

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

    International Nuclear Information System (INIS)

    Fukunaga, Satoki; Kakehashi, Anna; Sumida, Kayo; Kushida, Masahiko; Asano, Hiroyuki; Gi, Min; Wanibuchi, Hideki

    2015-01-01

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

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

    Energy Technology Data Exchange (ETDEWEB)

    Fukunaga, Satoki [Department of Molecular Pathology, Osaka City University Graduate School of Medicine, 1-4-3 Asahi-machi, Abeno-ku, Osaka 545-8585 (Japan); Environmental Health Science Laboratory, Sumitomo Chemical Co., Ltd., 3-1-98 Kasugade-Naka, Konohana-ku, Osaka 554-8558 (Japan); Kakehashi, Anna [Department of Molecular Pathology, Osaka City University Graduate School of Medicine, 1-4-3 Asahi-machi, Abeno-ku, Osaka 545-8585 (Japan); Sumida, Kayo; Kushida, Masahiko; Asano, Hiroyuki [Environmental Health Science Laboratory, Sumitomo Chemical Co., Ltd., 3-1-98 Kasugade-Naka, Konohana-ku, Osaka 554-8558 (Japan); Gi, Min [Department of Molecular Pathology, Osaka City University Graduate School of Medicine, 1-4-3 Asahi-machi, Abeno-ku, Osaka 545-8585 (Japan); Wanibuchi, Hideki, E-mail: wani@med.osaka-cu.ac.jp [Department of Molecular Pathology, Osaka City University Graduate School of Medicine, 1-4-3 Asahi-machi, Abeno-ku, Osaka 545-8585 (Japan)

    2015-08-01

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

  15. Expression microarray meta-analysis identifies genes associated with Ras/MAPK and related pathways in progression of muscle-invasive bladder transition cell carcinoma.

    Directory of Open Access Journals (Sweden)

    Jonathan A Ewald

    Full Text Available The effective detection and management of muscle-invasive bladder Transition Cell Carcinoma (TCC continues to be an urgent clinical challenge. While some differences of gene expression and function in papillary (Ta, superficial (T1 and muscle-invasive (≥T2 bladder cancers have been investigated, the understanding of mechanisms involved in the progression of bladder tumors remains incomplete. Statistical methods of pathway-enrichment, cluster analysis and text-mining can extract and help interpret functional information about gene expression patterns in large sets of genomic data. The public availability of patient-derived expression microarray data allows open access and analysis of large amounts of clinical data. Using these resources, we investigated gene expression differences associated with tumor progression and muscle-invasive TCC. Gene expression was calculated relative to Ta tumors to assess progression-associated differences, revealing a network of genes related to Ras/MAPK and PI3K signaling pathways with increased expression. Further, we identified genes within this network that are similarly expressed in superficial Ta and T1 stages but altered in muscle-invasive T2 tumors, finding 7 genes (COL3A1, COL5A1, COL11A1, FN1, ErbB3, MAPK10 and CDC25C whose expression patterns in muscle-invasive tumors are consistent in 5 to 7 independent outside microarray studies. Further, we found increased expression of the fibrillar collagen proteins COL3A1 and COL5A1 in muscle-invasive tumor samples and metastatic T24 cells. Our results suggest that increased expression of genes involved in mitogenic signaling may support the progression of muscle-invasive bladder tumors that generally lack activating mutations in these pathways, while expression changes of fibrillar collagens, fibronectin and specific signaling proteins are associated with muscle-invasive disease. These results identify potential biomarkers and targets for TCC treatments, and

  16. Microarray Analysis in a Cell Death Resistant Glioma Cell Line to Identify Signaling Pathways and Novel Genes Controlling Resistance and Malignancy

    Energy Technology Data Exchange (ETDEWEB)

    Seznec, Janina; Naumann, Ulrike, E-mail: ulrike.naumann@uni-tuebingen.de [Laboratory of Molecular Neuro-Oncology, Department of General Neurology, Hertie-Institute for Clinical Brain Research and Center Neurology, University of Tuebingen, Otfried-Mueller-Str. 27, Tuebingen 72076 (Germany)

    2011-06-27

    Glioblastoma multiforme (GBM) is a lethal type of cancer mainly resistant to radio- and chemotherapy. Since the tumor suppressor p53 functions as a transcription factor regulating the expression of genes involved in growth inhibition, DNA repair and apoptosis, we previously assessed whether specific differences in the modulation of gene expression are responsible for the anti-tumor properties of a dominant positive p53, chimeric tumor suppressor (CTS)-1. CTS-1 is based on the sequence of p53 and designed to resist various mechanisms of inactivation which limit the activity of p53. To identify CTS-1-regulated cell death-inducing genes, we generated a CTS-1-resistant glioma cell line (229R). We used Affymetrix whole-genome microarray expression analysis to analyze alterations in gene expression and identified a variety of CTS-1 regulated genes involved in cancer-linked processes. 313 genes were differentially expressed in Adeno-CTS-1 (Ad-CTS-1)-infected and 700 genes in uninfected 229R cells compared to matching parental cells. Ingenuity Pathway Analysis (IPA) determined a variety of differentially expressed genes in Ad-CTS-1-infected cells that were members of the intracellular networks with central tumor-involved players such as nuclear factor kappa B (NF-κB), protein kinase B (PKB/AKT) or transforming growth factor beta (TGF-β). Differentially regulated genes include secreted factors as well as intracellular proteins and transcription factors regulating not only cell death, but also processes such as tumor cell motility and immunity. This work gives an overview of the pathways differentially regulated in the resistant versus parental glioma cells and might be helpful to identify candidate genes which could serve as targets to develop novel glioma specific therapy strategies.

  17. Microarray Analysis in a Cell Death Resistant Glioma Cell Line to Identify Signaling Pathways and Novel Genes Controlling Resistance and Malignancy

    International Nuclear Information System (INIS)

    Seznec, Janina; Naumann, Ulrike

    2011-01-01

    Glioblastoma multiforme (GBM) is a lethal type of cancer mainly resistant to radio- and chemotherapy. Since the tumor suppressor p53 functions as a transcription factor regulating the expression of genes involved in growth inhibition, DNA repair and apoptosis, we previously assessed whether specific differences in the modulation of gene expression are responsible for the anti-tumor properties of a dominant positive p53, chimeric tumor suppressor (CTS)-1. CTS-1 is based on the sequence of p53 and designed to resist various mechanisms of inactivation which limit the activity of p53. To identify CTS-1-regulated cell death-inducing genes, we generated a CTS-1-resistant glioma cell line (229R). We used Affymetrix whole-genome microarray expression analysis to analyze alterations in gene expression and identified a variety of CTS-1 regulated genes involved in cancer-linked processes. 313 genes were differentially expressed in Adeno-CTS-1 (Ad-CTS-1)-infected and 700 genes in uninfected 229R cells compared to matching parental cells. Ingenuity Pathway Analysis (IPA) determined a variety of differentially expressed genes in Ad-CTS-1-infected cells that were members of the intracellular networks with central tumor-involved players such as nuclear factor kappa B (NF-κB), protein kinase B (PKB/AKT) or transforming growth factor beta (TGF-β). Differentially regulated genes include secreted factors as well as intracellular proteins and transcription factors regulating not only cell death, but also processes such as tumor cell motility and immunity. This work gives an overview of the pathways differentially regulated in the resistant versus parental glioma cells and might be helpful to identify candidate genes which could serve as targets to develop novel glioma specific therapy strategies

  18. "Harshlighting" small blemishes on microarrays

    Directory of Open Access Journals (Sweden)

    Wittkowski Knut M

    2005-03-01

    Full Text Available Abstract Background Microscopists are familiar with many blemishes that fluorescence images can have due to dust and debris, glass flaws, uneven distribution of fluids or surface coatings, etc. Microarray scans show similar artefacts, which affect the analysis, particularly when one tries to detect subtle changes. However, most blemishes are hard to find by the unaided eye, particularly in high-density oligonucleotide arrays (HDONAs. Results We present a method that harnesses the statistical power provided by having several HDONAs available, which are obtained under similar conditions except for the experimental factor. This method "harshlights" blemishes and renders them evident. We find empirically that about 25% of our chips are blemished, and we analyze the impact of masking them on screening for differentially expressed genes. Conclusion Experiments attempting to assess subtle expression changes should be carefully screened for blemishes on the chips. The proposed method provides investigators with a novel robust approach to improve the sensitivity of microarray analyses. By utilizing topological information to identify and mask blemishes prior to model based analyses, the method prevents artefacts from confounding the process of background correction, normalization, and summarization.

  19. Microarray Expression Analyses of Arabidopsis Guard Cells and Isolation of a Recessive Abscisic Acid Hypersensitive Protein Phosphatase 2C MutantW⃞

    Science.gov (United States)

    Leonhardt, Nathalie; Kwak, June M.; Robert, Nadia; Waner, David; Leonhardt, Guillaume; Schroeder, Julian I.

    2004-01-01

    Oligomer-based DNA Affymetrix GeneChips representing about one-third of Arabidopsis (Arabidopsis thaliana) genes were used to profile global gene expression in a single cell type, guard cells, identifying 1309 guard cell–expressed genes. Highly pure preparations of guard cells and mesophyll cells were isolated in the presence of transcription inhibitors that prevented induction of stress-inducible genes during cell isolation procedures. Guard cell expression profiles were compared with those of mesophyll cells, resulting in identification of 64 transcripts expressed preferentially in guard cells. Many large gene families and gene duplications are known to exist in the Arabidopsis genome, giving rise to redundancies that greatly hamper conventional genetic and functional genomic analyses. The presented genomic scale analysis identifies redundant expression of specific isoforms belonging to large gene families at the single cell level, which provides a powerful tool for functional genomic characterization of the many signaling pathways that function in guard cells. Reverse transcription–PCR of 29 genes confirmed the reliability of GeneChip results. Statistical analyses of promoter regions of abscisic acid (ABA)–regulated genes reveal an overrepresented ABA responsive motif, which is the known ABA response element. Interestingly, expression profiling reveals ABA modulation of many known guard cell ABA signaling components at the transcript level. We further identified a highly ABA-induced protein phosphatase 2C transcript, AtP2C-HA, in guard cells. A T-DNA disruption mutation in AtP2C-HA confers ABA-hypersensitive regulation of stomatal closing and seed germination. The presented data provide a basis for cell type–specific genomic scale analyses of gene function. PMID:14973164

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

    Science.gov (United States)

    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.

  1. Direct calibration of PICKY-designed microarrays

    Directory of Open Access Journals (Sweden)

    Ronald Pamela C

    2009-10-01

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

  2. Structural identifiability analyses of candidate models for in vitro Pitavastatin hepatic uptake.

    Science.gov (United States)

    Grandjean, Thomas R B; Chappell, Michael J; Yates, James W T; Evans, Neil D

    2014-05-01

    In this paper a review of the application of four different techniques (a version of the similarity transformation approach for autonomous uncontrolled systems, a non-differential input/output observable normal form approach, the characteristic set differential algebra and a recent algebraic input/output relationship approach) to determine the structural identifiability of certain in vitro nonlinear pharmacokinetic models is provided. The Organic Anion Transporting Polypeptide (OATP) substrate, Pitavastatin, is used as a probe on freshly isolated animal and human hepatocytes. Candidate pharmacokinetic non-linear compartmental models have been derived to characterise the uptake process of Pitavastatin. As a prerequisite to parameter estimation, structural identifiability analyses are performed to establish that all unknown parameters can be identified from the experimental observations available. Copyright © 2013. Published by Elsevier Ireland Ltd.

  3. DNA Microarrays in Comparative Genomics and Transcriptomics

    DEFF Research Database (Denmark)

    Willenbrock, Hanni

    2007-01-01

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

  4. Statistical Analyses of Scatterplots to Identify Important Factors in Large-Scale Simulations

    Energy Technology Data Exchange (ETDEWEB)

    Kleijnen, J.P.C.; Helton, J.C.

    1999-04-01

    The robustness of procedures for identifying patterns in scatterplots generated in Monte Carlo sensitivity analyses is investigated. These procedures are based on attempts to detect increasingly complex patterns in the scatterplots under consideration and involve the identification of (1) linear relationships with correlation coefficients, (2) monotonic relationships with rank correlation coefficients, (3) trends in central tendency as defined by means, medians and the Kruskal-Wallis statistic, (4) trends in variability as defined by variances and interquartile ranges, and (5) deviations from randomness as defined by the chi-square statistic. The following two topics related to the robustness of these procedures are considered for a sequence of example analyses with a large model for two-phase fluid flow: the presence of Type I and Type II errors, and the stability of results obtained with independent Latin hypercube samples. Observations from analysis include: (1) Type I errors are unavoidable, (2) Type II errors can occur when inappropriate analysis procedures are used, (3) physical explanations should always be sought for why statistical procedures identify variables as being important, and (4) the identification of important variables tends to be stable for independent Latin hypercube samples.

  5. Phosphinothricin Acetyltransferases Identified Using In Vivo, In Vitro, and Bioinformatic Analyses

    Science.gov (United States)

    VanDrisse, Chelsey M.; Hentchel, Kristy L.

    2016-01-01

    ABSTRACT Acetylation of small molecules is widespread in nature, and in some cases, cells use this process to detoxify harmful chemicals. Streptomyces species utilize a Gcn5 N-acetyltransferase (GNAT), known as Bar, to acetylate and detoxify a self-produced toxin, phosphinothricin (PPT), a glutamate analogue. Bar homologues, such as MddA from Salmonella enterica, acetylate methionine analogues such as methionine sulfoximine (MSX) and methionine sulfone (MSO), but not PPT, even though Bar homologues are annotated as PPT acetyltransferases. S. enterica was used as a heterologous host to determine whether or not putative PPT acetyltransferases from various sources could acetylate PPT, MSX, and MSO. In vitro and in vivo analyses identified substrates acetylated by putative PPT acetyltransferases from Deinococcus radiodurans (DR_1057 and DR_1182) and Geobacillus kaustophilus (GK0593 and GK2920). In vivo, synthesis of DR_1182, GK0593, and GK2920 blocked the inhibitory effects of PPT, MSX, and MSO. In contrast, DR_1057 did not detoxify any of the above substrates. Results of in vitro studies were consistent with the in vivo results. In addition, phylogenetic analyses were used to predict the functionality of annotated PPT acetyltransferases in Burkholderia xenovorans, Bacillus subtilis, Staphylococcus aureus, Acinetobacter baylyi, and Escherichia coli. IMPORTANCE The work reported here provides an example of the use of a heterologous system for the identification of enzyme function. Many members of this superfamily of proteins do not have a known function, or it has been annotated solely on the basis of sequence homology to previously characterized enzymes. The critical role of Gcn5 N-acetyltransferases (GNATs) in the modulation of central metabolic processes, and in controlling metabolic stress, necessitates approaches that can reveal their physiological role. The combination of in vivo, in vitro, and bioinformatics approaches reported here identified GNATs that can

  6. The EADGENE Microarray Data Analysis Workshop

    DEFF Research Database (Denmark)

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

    2007-01-01

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

  7. Two novel antimicrobial defensins from rice identified by gene coexpression network analyses.

    Science.gov (United States)

    Tantong, Supaluk; Pringsulaka, Onanong; Weerawanich, Kamonwan; Meeprasert, Arthitaya; Rungrotmongkol, Thanyada; Sarnthima, Rakrudee; Roytrakul, Sittiruk; Sirikantaramas, Supaart

    2016-10-01

    Defensins form an antimicrobial peptides (AMP) family, and have been widely studied in various plants because of their considerable inhibitory functions. However, their roles in rice (Oryza sativa L.) have not been characterized, even though rice is one of the most important staple crops that is susceptible to damaging infections. Additionally, a previous study identified 598 rice genes encoding cysteine-rich peptides, suggesting there are several uncharacterized AMPs in rice. We performed in silico gene expression and coexpression network analyses of all genes encoding defensin and defensin-like peptides, and determined that OsDEF7 and OsDEF8 are coexpressed with pathogen-responsive genes. Recombinant OsDEF7 and OsDEF8 could form homodimers. They inhibited the growth of the bacteria Xanthomonas oryzae pv. oryzae, X. oryzae pv. oryzicola, and Erwinia carotovora subsp. atroseptica with minimum inhibitory concentration (MIC) ranging from 0.6 to 63μg/mL. However, these OsDEFs are weakly active against the phytopathogenic fungi Helminthosporium oryzae and Fusarium oxysporum f.sp. cubense. This study describes a useful method for identifying potential plant AMPs with biological activities. Copyright © 2016 Elsevier Inc. All rights reserved.

  8. Attribute analyses of gpr data for detecting and identifying heavy minerals

    Science.gov (United States)

    Catakli, Aycan

    Attribute analyses have been used successfully in seismic applications for many years. In this study, the application of the attribute analyses to Ground Penetrating Radar (GPR) data has been proposed to detect and identify heavy minerals within the Moon soil (regolith). Lunar samples are mostly composed of heavy minerals such as ilmenite, plagioclase, olivine and pyroxene, a characteristic that makes lunar soil a source for elements such as titanium, oxygen and iron. The main goal of this study is to demonstrate the use of GPR method for detecting and mapping heavy minerals concentrations. The attribute analyses used in this study are Attenuation Analysis (AA), Complex Trace Analysis (CTA), Texture Analysis (TA) and Center Frequency Destitution (CFD). Attribute analysis was applied to both synthetic models and prototype laboratory measurements to study its application to GPR data. The results indicate that the attribute analyses of GPR data can be useful to provide valuable subsurface information. The findings of AA show that attenuation values are function of mineralogy of the subsurface. This could be applicable to Moon and Mars in addition to Earth environment to explore their near-surface soils. CTA can successfully estimate the location of heavy mineral samples embedded inside host medium through the variation of reflected energy around buried sample and sharpen the reflecting interface. Results indicate that as the amount of the buried heavy minerals increases, the value of CTA parameters (Normal distribution of amplitude spectra `NDoAS' and tau-parameter) proportionally increase. TA measures combined can be used as an enhanced interpretation tool. The texture results show that heavy mineral concentrations can be identified by the high contrast, entropy, autocorrelation, correlation, cluster, dissimilarity, standard deviation, variance and low energy, maximum probability, and homogeneity. The measures also help in highlighting the edge of the buried samples

  9. TF-finder: A software package for identifying transcription factors involved in biological processes using microarray data and existing knowledge base

    Directory of Open Access Journals (Sweden)

    Cui Xiaoqi

    2010-08-01

    Full Text Available Abstract Background Identification of transcription factors (TFs involved in a biological process is the first step towards a better understanding of the underlying regulatory mechanisms. However, due to the involvement of a large number of genes and complicated interactions in a gene regulatory network (GRN, identification of the TFs involved in a biology process remains to be very challenging. In reality, the recognition of TFs for a given a biological process can be further complicated by the fact that most eukaryotic genomes encode thousands of TFs, which are organized in gene families of various sizes and in many cases with poor sequence conservation except for small conserved domains. This poses a significant challenge for identification of the exact TFs involved or ranking the importance of a set of TFs to a process of interest. Therefore, new methods for recognizing novel TFs are desperately needed. Although a plethora of methods have been developed to infer regulatory genes using microarray data, it is still rare to find the methods that use existing knowledge base in particular the validated genes known to be involved in a process to bait/guide discovery of novel TFs. Such methods can replace the sometimes-arbitrary process of selection of candidate genes for experimental validation and significantly advance our knowledge and understanding of the regulation of a process. Results We developed an automated software package called TF-finder for recognizing TFs involved in a biological process using microarray data and existing knowledge base. TF-finder contains two components, adaptive sparse canonical correlation analysis (ASCCA and enrichment test, for TF recognition. ASCCA uses positive target genes to bait TFS from gene expression data while enrichment test examines the presence of positive TFs in the outcomes from ASCCA. Using microarray data from salt and water stress experiments, we showed TF-finder is very efficient in recognizing

  10. Multiple gene analyses identify distinct “bois noir” phytoplasma genotypes in the Republic of Macedonia

    Directory of Open Access Journals (Sweden)

    Emilija KOSTADINOVSKA

    2015-01-01

    Full Text Available “Bois noir” (BN is a grapevine yellows disease, associated with phytoplasma strains related to ‘Candidatus Phytoplasma solani’, that causes severe losses to viticulture in the Euro-Mediterranean basin. Due to the complex ecological cycle of its etiological agent, BN epidemiology is only partially known, and no effective control strategies have been developed. Numerous studies have focused on molecular characterization of BN phytoplasma strains, to identify molecular markers useful to accurately describe their genetic diversity, geographic distribution and host range. In the present study, a multiple gene analysess were carried out on 16S rRNA, tuf, vmp1, and stamp genes to study the genetic variability among 18 BN phytoplasma strains detected in diverse regions of the Republic of Macedonia. Restriction fragment length polymorphism (RFLP assays showed the presence of one 16S rRNA (16SrXII-A, two tuf (tuf-type a, tuf-type b, five vmp1 (V2-TA, V3, V4, V14, V18, and three stamp (S1, S2, S3 gene patterns among the examined strains. Based on the collective RFLP patterns, seven genotypes (Mac1 to Mac7 were described as evidence for genetic heterogeneity, and highlighting their prevalence and distribution in the investigated regions. Phylogenetic analyses on vmp1 and stamp genes underlined the affiliation of Macedonian BN phytoplasma strains to clusters associated with distinct ecologies.

  11. Microarray analysis of Arabidopsis under gold exposure to identify putative genes involved in the synthesis of gold nanoparticles (AuNPs).

    Science.gov (United States)

    Shukla, Devesh; Krishnamurthy, Sneha; Sahi, Shivendra V

    2015-03-01

    Very little is known about the genes responsible for Au uptake, reduction and detoxification in plants, which indeed essential to understand the complex trait of AuNP biosynthesis. We designed a targeted experiment to elucidate the response of plant at transcriptional level under Au exposure, and a microarray was performed on root tissue treated with AuCl4 (-) in the absence of nutrient media to record specific gene expression signature. Here, we describe the experimental procedures and data analysis in detail to reproduce the results (available at GEO database under GSE55436) published by Shukla et al. (2014) [1] in the Frontiers in Plant Sciences. The data produced from this study provide significant information of genes which may be used to enhance the AuNP biosynthesis.

  12. Genome-wide meta-analyses identify multiple loci associated with smoking behavior.

    LENUS (Irish Health Repository)

    2010-05-01

    Consistent but indirect evidence has implicated genetic factors in smoking behavior. We report meta-analyses of several smoking phenotypes within cohorts of the Tobacco and Genetics Consortium (n = 74,053). We also partnered with the European Network of Genetic and Genomic Epidemiology (ENGAGE) and Oxford-GlaxoSmithKline (Ox-GSK) consortia to follow up the 15 most significant regions (n > 140,000). We identified three loci associated with number of cigarettes smoked per day. The strongest association was a synonymous 15q25 SNP in the nicotinic receptor gene CHRNA3 (rs1051730[A], beta = 1.03, standard error (s.e.) = 0.053, P = 2.8 x 10(-73)). Two 10q25 SNPs (rs1329650[G], beta = 0.367, s.e. = 0.059, P = 5.7 x 10(-10); and rs1028936[A], beta = 0.446, s.e. = 0.074, P = 1.3 x 10(-9)) and one 9q13 SNP in EGLN2 (rs3733829[G], beta = 0.333, s.e. = 0.058, P = 1.0 x 10(-8)) also exceeded genome-wide significance for cigarettes per day. For smoking initiation, eight SNPs exceeded genome-wide significance, with the strongest association at a nonsynonymous SNP in BDNF on chromosome 11 (rs6265[C], odds ratio (OR) = 1.06, 95% confidence interval (Cl) 1.04-1.08, P = 1.8 x 10(-8)). One SNP located near DBH on chromosome 9 (rs3025343[G], OR = 1.12, 95% Cl 1.08-1.18, P = 3.6 x 10(-8)) was significantly associated with smoking cessation.

  13. Polyadenylation state microarray (PASTA) analysis.

    Science.gov (United States)

    Beilharz, Traude H; Preiss, Thomas

    2011-01-01

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

  14. Nonmosaic tetrasomy 15q25.2 → qter identified with SNP microarray in a patient with characteristic facial appearance and review of the literature.

    Science.gov (United States)

    Xu, Huihui; Xiao, Bing; Ji, Xing; Hu, Qin; Chen, Yingwei; Qiu, Wenjuan

    2014-07-01

    Tetrasomy for the distal chromosome 15q is rare, and only 22 patients (including 6 cases without detailed information) have been described to date in the literature. Here we report on another patient with nonmosaic tetrasomy 15q25.2-qter resulted from an inverted duplication of distal chromosome 15. This patient presents with features of development delay, arachnodactyly, joint contractures and typical facial dysmorphism including frontal bossing, short palpebral fissures, long philtrum, low-set ears, high-arched palate and retrognathia. Unlike most of the related patients, abdominal ultrasound test and brain MRI showed normal. Karyotyping analysis revealed a supernumerary marker chromosome presented in all metaphase cells examined. Parental karyotyping analysis was normal, indicating a de novo chromosome aberration of the patient. SNP microarray analysis found a two copy gain of 17.7 Mb from the distal long arm of chromosome 15 (15q25.2-qter). Further FISH analysis using SureFISH 15q26.3 IGF1R probe proved an inverted duplication of distal long arm of chromosome 15. The segmental duplications which lie in the hotspots of 15q24-26 might increase the susceptibility of chromosome rearrangement. Compared with the George-Abraham' study [2012], ADAMTSL3 might be more related to the cardiac disorders in tetrasomy 15q patients. Considering all patients reported in the literature, different mosaic degrees and segmental sizes don't correlate to the severity of phenotypes. A clear delineation on tetrasomy for distal chromosome 15q could still be investigated. Copyright © 2014 Elsevier Masson SAS. All rights reserved.

  15. Integrative ChIP-seq/microarray analysis identifies a CTNNB1 target signature enriched in intestinal stem cells and colon cancer.

    Science.gov (United States)

    Watanabe, Kazuhide; Biesinger, Jacob; Salmans, Michael L; Roberts, Brian S; Arthur, William T; Cleary, Michele; Andersen, Bogi; Xie, Xiaohui; Dai, Xing

    2014-01-01

    Deregulation of canonical Wnt/CTNNB1 (beta-catenin) pathway is one of the earliest events in the pathogenesis of colon cancer. Mutations in APC or CTNNB1 are highly frequent in colon cancer and cause aberrant stabilization of CTNNB1, which activates the transcription of Wnt target genes by binding to chromatin via the TCF/LEF transcription factors. Here we report an integrative analysis of genome-wide chromatin occupancy of CTNNB1 by chromatin immunoprecipitation coupled with high-throughput sequencing (ChIP-seq) and gene expression profiling by microarray analysis upon RNAi-mediated knockdown of CTNNB1 in colon cancer cells. We observed 3629 CTNNB1 binding peaks across the genome and a significant correlation between CTNNB1 binding and knockdown-induced gene expression change. Our integrative analysis led to the discovery of a direct Wnt target signature composed of 162 genes. Gene ontology analysis of this signature revealed a significant enrichment of Wnt pathway genes, suggesting multiple feedback regulations of the pathway. We provide evidence that this gene signature partially overlaps with the Lgr5+ intestinal stem cell signature, and is significantly enriched in normal intestinal stem cells as well as in clinical colorectal cancer samples. Interestingly, while the expression of the CTNNB1 target gene set does not correlate with survival, elevated expression of negative feedback regulators within the signature predicts better prognosis. Our data provide a genome-wide view of chromatin occupancy and gene regulation of Wnt/CTNNB1 signaling in colon cancer cells.

  16. Integrative ChIP-seq/microarray analysis identifies a CTNNB1 target signature enriched in intestinal stem cells and colon cancer.

    Directory of Open Access Journals (Sweden)

    Kazuhide Watanabe

    Full Text Available Deregulation of canonical Wnt/CTNNB1 (beta-catenin pathway is one of the earliest events in the pathogenesis of colon cancer. Mutations in APC or CTNNB1 are highly frequent in colon cancer and cause aberrant stabilization of CTNNB1, which activates the transcription of Wnt target genes by binding to chromatin via the TCF/LEF transcription factors. Here we report an integrative analysis of genome-wide chromatin occupancy of CTNNB1 by chromatin immunoprecipitation coupled with high-throughput sequencing (ChIP-seq and gene expression profiling by microarray analysis upon RNAi-mediated knockdown of CTNNB1 in colon cancer cells.We observed 3629 CTNNB1 binding peaks across the genome and a significant correlation between CTNNB1 binding and knockdown-induced gene expression change. Our integrative analysis led to the discovery of a direct Wnt target signature composed of 162 genes. Gene ontology analysis of this signature revealed a significant enrichment of Wnt pathway genes, suggesting multiple feedback regulations of the pathway. We provide evidence that this gene signature partially overlaps with the Lgr5+ intestinal stem cell signature, and is significantly enriched in normal intestinal stem cells as well as in clinical colorectal cancer samples. Interestingly, while the expression of the CTNNB1 target gene set does not correlate with survival, elevated expression of negative feedback regulators within the signature predicts better prognosis.Our data provide a genome-wide view of chromatin occupancy and gene regulation of Wnt/CTNNB1 signaling in colon cancer cells.

  17. Genome-wide meta-analyses identify multiple loci associated with smoking behavior

    NARCIS (Netherlands)

    H. Furberg (Helena); Y. Kim (Yunjung); J. Dackor (Jennifer); E.A. Boerwinkle (Eric); N. Franceschini (Nora); D. Ardissino (Diego); L. Bernardinelli (Luisa); P.M. Mannucci (Pier); F. Mauri (Francesco); P.A. Merlini (Piera); D. Absher (Devin); T.L. Assimes (Themistocles); S.P. Fortmann (Stephen); C. Iribarren (Carlos); J.W. Knowles (Joshua); T. Quertermous (Thomas); L. Ferrucci (Luigi); T. Tanaka (Toshiko); J.C. Bis (Joshua); T. Haritunians (Talin); B. McKnight (Barbara); B.M. Psaty (Bruce); K.D. Taylor (Kent); E.L. Thacker (Evan); P. Almgren (Peter); L. Groop (Leif); C. Ladenvall (Claes); M. Boehnke (Michael); A.U. Jackson (Anne); K.L. Mohlke (Karen); H.M. Stringham (Heather); J. Tuomilehto (Jaakko); E.J. Benjamin (Emelia); S.J. Hwang; D. Levy (Daniel); S.R. Preis; R.S. Vasan (Ramachandran Srini); J. Duan (Jubao); P.V. Gejman (Pablo); D.F. Levinson (Douglas); A.R. Sanders (Alan); J. Shi (Jianxin); E.H. Lips (Esther); J.D. McKay (James); A. Agudo (Antonio); L. Barzan (Luigi); V. Bencko (Vladimir); S. Benhamou (Simone); X. Castellsagué (Xavier); C. Canova (Cristina); D.I. Conway (David); E. Fabianova (Eleonora); L. Foretova (Lenka); V. Janout (Vladimir); C.M. Healy (Claire); I. Holcátová (Ivana); K. Kjaerheim (Kristina); P. Lagiou; J. Lissowska (Jolanta); R. Lowry (Ray); T.V. MacFarlane (Tatiana); D. Mates (Dana); L. Richiardi (Lorenzo); P. Rudnai (Peter); N. Szeszenia-Dabrowska (Neonilia); D. Zaridze; A. Znaor (Ariana); M. Lathrop (Mark); P. Brennan (Paul); S. Bandinelli (Stefania); T.M. Frayling (Timothy); J.M. Guralnik (Jack); Y. Milaneschi (Yuri); J.R.B. Perry (John); D. Altshuler (David); R. Elosua (Roberto); S. Kathiresan (Sekar); G. Lucas (Gavin); O. Melander (Olle); V. Salomaa (Veikko); S.M. Schwartz (Stephen); B.F. Voight (Benjamin); B.W.J.H. Penninx (Brenda); J.H. Smit (Johannes); N. Vogelzangs (Nicole); D.I. Boomsma (Dorret); E.J.C. de Geus (Eco); J.M. Vink (Jacqueline); G.A.H.M. Willemsen (Gonneke); S.J. Chanock (Stephen); F. Gu (Fangyi); S.E. Hankinson (Susan); D. Hunter (David); A. Hofman (Albert); H.W. Tiemeier (Henning); A.G. Uitterlinden (André); P. Tikka-Kleemola (Päivi); S. Walter (Stefan); D.I. Chasman (Daniel); B.M. Everett (Brendan); G. Pare (Guillaume); P.M. Ridker (Paul); M.D. Li (Ming); H.H. Maes (Hermine); J. Audrain-Mcgovern (Janet); D. Posthuma (Danielle); L.M. Thornton (Laura); C. Lerman (Caryn); J. Kaprio (Jaakko); J.E. Rose (Jed); J.P.A. Ioannidis (John); P. Kraft (Peter); D.Y. Lin (Dan); P.F. Sullivan (Patrick); C.J. O'Donnell (Christopher)

    2010-01-01

    textabstractConsistent but indirect evidence has implicated genetic factors in smoking behavior. We report meta-analyses of several smoking phenotypes within cohorts of the Tobacco and Genetics Consortium (n = 74,053). We also partnered with the European Network of Genetic and Genomic Epidemiology

  18. Attempts to identify and analyse prospects and challenges of tourism marketing in Bangladesh.

    OpenAIRE

    Redwan, Md

    2017-01-01

    Master's thesis in International hotel and tourism management The research has been done to analyse the tourism position of the country Bangladesh. Bangladesh is country of huge potential and the country can do well its present assets related to the tourism. The natural resources of the country and the foreign exchange inflow in the country can make the country economically sound. The research aims to understand the present scenario of the tourism industry of Bangladesh and the challenges ...

  19. Identification of potential biomarkers from microarray experiments using multiple criteria optimization

    International Nuclear Information System (INIS)

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

    2013-01-01

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

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

    International Nuclear Information System (INIS)

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

    2010-01-01

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

  1. Genome-wide Analyses Identify KIF5A as a Novel ALS Gene

    NARCIS (Netherlands)

    Nicolas, Aude; Kenna, Kevin P.; Renton, Alan E.; Ticozzi, Nicola; Faghri, Faraz; Chia, Ruth; Dominov, Janice A.; Kenna, Brendan J.; Nalls, Mike A.; Keagle, Pamela; Rivera, Alberto M.; van Rheenen, Wouter; Murphy, Natalie A.; van Vugt, Joke J.F.A.; Geiger, Joshua T.; van der Spek, Rick; Pliner, Hannah A.; Smith, Bradley N.; Marangi, Giuseppe; Topp, Simon D.; Abramzon, Yevgeniya; Gkazi, Athina Soragia; Eicher, John D.; Kenna, Aoife; Logullo, Francesco O.; Simone, Isabella L.; Logroscino, Giancarlo; Salvi, Fabrizio; Bartolomei, Ilaria; Borghero, Giuseppe; Murru, Maria Rita; Costantino, Emanuela; Pani, Carla; Puddu, Roberta; Caredda, Carla; Piras, Valeria; Tranquilli, Stefania; Cuccu, Stefania; Corongiu, Daniela; Melis, Maurizio; Milia, Antonio; Marrosu, Francesco; Marrosu, Maria Giovanna; Floris, Gianluca; Cannas, Antonino; Capasso, Margherita; Caponnetto, Claudia; Mancardi, Gianluigi; Origone, Paola; Mandich, Paola; Conforti, Francesca L.; Cavallaro, Sebastiano; Mora, Gabriele; Marinou, Kalliopi; Sideri, Riccardo; Penco, Silvana; Mosca, Lorena; Lunetta, Christian; Pinter, Giuseppe Lauria; Corbo, Massimo; Riva, Nilo; Carrera, Paola; Volanti, Paolo; Mandrioli, Jessica; Fini, Nicola; Fasano, Antonio; Tremolizzo, Lucio; Arosio, Alessandro; Ferrarese, Carlo; Trojsi, Francesca; Tedeschi, Gioacchino; Monsurrò, Maria Rosaria; Piccirillo, Giovanni; Femiano, Cinzia; Ticca, Anna; Ortu, Enzo; La Bella, Vincenzo; Spataro, Rossella; Colletti, Tiziana; Sabatelli, Mario; Zollino, Marcella; Conte, Amelia; Luigetti, Marco; Lattante, Serena; Marangi, Giuseppe; Santarelli, Marialuisa; Petrucci, Antonio; Pugliatti, Maura; Pirisi, Angelo; Parish, Leslie D.; Occhineri, Patrizia; Giannini, Fabio; Battistini, Stefania; Ricci, Claudia; Benigni, Michele; Cau, Tea B.; Loi, Daniela; Calvo, Andrea; Moglia, Cristina; Brunetti, Maura; Barberis, Marco; Restagno, Gabriella; Casale, Federico; Marrali, Giuseppe; Fuda, Giuseppe; Ossola, Irene; Cammarosano, Stefania; Canosa, Antonio; Ilardi, Antonio; Manera, Umberto; Grassano, Maurizio; Tanel, Raffaella; Pisano, Fabrizio; Mora, Gabriele; Calvo, Andrea; Mazzini, Letizia; Riva, Nilo; Mandrioli, Jessica; Caponnetto, Claudia; Battistini, Stefania; Volanti, Paolo; La Bella, Vincenzo; Conforti, Francesca L.; Borghero, Giuseppe; Messina, Sonia; Simone, Isabella L.; Trojsi, Francesca; Salvi, Fabrizio; Logullo, Francesco O.; D'Alfonso, Sandra; Corrado, Lucia; Capasso, Margherita; Ferrucci, Luigi; Harms, Matthew B.; Goldstein, David B.; Shneider, Neil A.; Goutman, Stephen A.; Simmons, Zachary; Miller, Timothy M.; Chandran, Siddharthan; Pal, Suvankar; Manousakis, George; Appel, Stanley H.; Simpson, Ericka; Wang, Leo; Baloh, Robert H.; Gibson, Summer B.; Bedlack, Richard; Lacomis, David; Sareen, Dhruv; Sherman, Alexander; Bruijn, Lucie; Penny, Michelle; Moreno, Cristiane de Araujo Martins; Kamalakaran, Sitharthan; Goldstein, David B.; Allen, Andrew S.; Appel, Stanley; Baloh, Robert H.; Bedlack, Richard S.; Boone, Braden E.; Brown, Robert; Carulli, John P.; Chesi, Alessandra; Chung, Wendy K.; Cirulli, Elizabeth T.; Cooper, Gregory M.; Couthouis, Julien; Day-Williams, Aaron G.; Dion, Patrick A.; Gibson, Summer B.; Gitler, Aaron D.; Glass, Jonathan D.; Goldstein, David B.; Han, Yujun; Harms, Matthew B.; Harris, Tim; Hayes, Sebastian D.; Jones, Angela L.; Keebler, Jonathan; Krueger, Brian J.; Lasseigne, Brittany N.; Levy, Shawn E.; Lu, Yi Fan; Maniatis, Tom; McKenna-Yasek, Diane; Miller, Timothy M.; Myers, Richard M.; Petrovski, Slavé; Pulst, Stefan M.; Raphael, Alya R.; Ravits, John M.; Ren, Zhong; Rouleau, Guy A.; Sapp, Peter C.; Shneider, Neil A.; Simpson, Ericka; Sims, Katherine B.; Staropoli, John F.; Waite, Lindsay L.; Wang, Quanli; Wimbish, Jack R.; Xin, Winnie W.; Gitler, Aaron D.; Harris, Tim; Myers, Richard M.; Phatnani, Hemali; Kwan, Justin; Sareen, Dhruv; Broach, James R.; Simmons, Zachary; Arcila-Londono, Ximena; Lee, Edward B.; Van Deerlin, Vivianna M.; Shneider, Neil A.; Fraenkel, Ernest; Ostrow, Lyle W.; Baas, Frank; Zaitlen, Noah; Berry, James D.; Malaspina, Andrea; Fratta, Pietro; Cox, Gregory A.; Thompson, Leslie M.; Finkbeiner, Steve; Dardiotis, Efthimios; Miller, Timothy M.; Chandran, Siddharthan; Pal, Suvankar; Hornstein, Eran; MacGowan, Daniel J.L.; Heiman-Patterson, Terry D.; Hammell, Molly G.; Patsopoulos, Nikolaos A.; Dubnau, Joshua; Nath, Avindra; Phatnani, Hemali; Musunuri, Rajeeva Lochan; Evani, Uday Shankar; Abhyankar, Avinash; Zody, Michael C.; Kaye, Julia; Finkbeiner, Steven; Wyman, Stacia K.; LeNail, Alexander; Lima, Leandro; Fraenkel, Ernest; Rothstein, Jeffrey D.; Svendsen, Clive N.; Thompson, Leslie M.; Van Eyk, Jenny; Maragakis, Nicholas J.; Berry, James D.; Glass, Jonathan D.; Miller, Timothy M.; Kolb, Stephen J.; Baloh, Robert H.; Cudkowicz, Merit; Baxi, Emily; Kaye, Julia; Finkbeiner, Steven; Wyman, Stacia K.; Finkbeiner, Steven; LeNail, Alex; Lima, Leandro; Fraenkel, Ernest; Fraenkel, Ernest; Svendsen, Clive N.; Svendsen, Clive N.; Thompson, Leslie M.; Thompson, Leslie M.; Van Eyk, Jennifer E.; Berry, James D.; Berry, James D.; Miller, Timothy M.; Kolb, Stephen J.; Cudkowicz, Merit; Cudkowicz, Merit; Baxi, Emily; Benatar, Michael; Taylor, J. Paul; Wu, Gang; Rampersaud, Evadnie; Wuu, Joanne; Rademakers, Rosa; Züchner, Stephan; Schule, Rebecca; McCauley, Jacob; Hussain, Sumaira; Cooley, Anne; Wallace, Marielle; Clayman, Christine; Barohn, Richard; Statland, Jeffrey; Ravits, John M.; Swenson, Andrea; Jackson, Carlayne; Trivedi, Jaya; Khan, Shaida; Katz, Jonathan; Jenkins, Liberty; Burns, Ted; Gwathmey, Kelly; Caress, James; McMillan, Corey; Elman, Lauren; Pioro, Erik P.; Heckmann, Jeannine; So, Yuen; Walk, David; Maiser, Samuel; Zhang, Jinghui; Benatar, Michael; Taylor, J. Paul; Taylor, J. Paul; Rampersaud, Evadnie; Wu, Gang; Wuu, Joanne; Silani, Vincenzo; Ticozzi, Nicola; Gellera, Cinzia; Ratti, Antonia; Taroni, Franco; Lauria, Giuseppe; Verde, Federico; Fogh, Isabella; Tiloca, Cinzia; Comi, Giacomo P.; Sorarù, Gianni; Cereda, Cristina; D'Alfonso, Sandra; Corrado, Lucia; De Marchi, Fabiola; Corti, Stefania; Ceroni, Mauro; Mazzini, Letizia; Siciliano, Gabriele; Filosto, Massimiliano; Inghilleri, Maurizio; Peverelli, Silvia; Colombrita, Claudia; Poletti, Barbara; Maderna, Luca; Del Bo, Roberto; Gagliardi, Stella; Querin, Giorgia; Bertolin, Cinzia; Pensato, Viviana; Castellotti, Barbara; Lauria, Giuseppe; Verde, Federico; Fogh, Isabella; Tiloca, Cinzia; Fogh, Isabella; Comi, Giacomo P.; Sorarù, Gianni; Cereda, Cristina; Camu, William; Mouzat, Kevin; Lumbroso, Serge; Corcia, Philippe; Meininger, Vincent; Besson, Gérard; Lagrange, Emmeline; Clavelou, Pierre; Guy, Nathalie; Couratier, Philippe; Vourch, Patrick; Danel, Véronique; Bernard, Emilien; Lemasson, Gwendal; Corcia, Philippe; Laaksovirta, Hannu; Myllykangas, Liisa; Jansson, Lilja; Valori, Miko; Ealing, John; Hamdalla, Hisham; Rollinson, Sara; Pickering-Brown, Stuart; Orrell, Richard W.; Sidle, Katie C.; Malaspina, Andrea; Hardy, John; Singleton, Andrew B.; Johnson, Janel O.; Arepalli, Sampath; Sapp, Peter C.; McKenna-Yasek, Diane; Polak, Meraida; Asress, Seneshaw; Al-Sarraj, Safa; King, Andrew; Troakes, Claire; Vance, Caroline; de Belleroche, Jacqueline; Baas, Frank; ten Asbroek, Anneloor L.M.A.; Muñoz-Blanco, José Luis; Hernandez, Dena G.; Ding, Jinhui; Gibbs, J. Raphael; Scholz, Sonja W.; Scholz, Sonja W.; Floeter, Mary Kay; Campbell, Roy H.; Landi, Francesco; Bowser, Robert; Pulst, Stefan M.; Ravits, John M.; MacGowan, Daniel J.L.; Kirby, Janine; Pioro, Erik P.; Pamphlett, Roger; Broach, James; Gerhard, Glenn; Dunckley, Travis L.; Brady, Christopher B.; Brady, Christopher B.; Kowall, Neil W.; Troncoso, Juan C.; Le Ber, Isabelle; Mouzat, Kevin; Lumbroso, Serge; Mouzat, Kevin; Lumbroso, Serge; Heiman-Patterson, Terry D.; Heiman-Patterson, Terry D.; Kamel, Freya; Van Den Bosch, Ludo; Van Den Bosch, Ludo; Baloh, Robert H.; Strom, Tim M.; Meitinger, Thomas; Strom, Tim M.; Shatunov, Aleksey; Van Eijk, Kristel R.; de Carvalho, Mamede; de Carvalho, Mamede; Kooyman, Maarten; Middelkoop, Bas; Moisse, Matthieu; McLaughlin, Russell; Van Es, Michael A.; Weber, Markus; Boylan, Kevin B.; Van Blitterswijk, Marka; Rademakers, Rosa; Morrison, Karen; Basak, A. Nazli; Mora, Jesús S.; Drory, Vivian; Shaw, Pamela; Turner, Martin R.; Talbot, Kevin; Hardiman, Orla; Williams, Kelly L.; Fifita, Jennifer A.; Nicholson, Garth A.; Blair, Ian P.; Nicholson, Garth A.; Rouleau, Guy A.; Esteban-Pérez, Jesús; García-Redondo, Alberto; Al-Chalabi, Ammar; Al Kheifat, Ahmad; Al-Chalabi, Ammar; Andersen, Peter M.; Basak, A. Nazli; Blair, Ian P.; Chio, Adriano; Cooper-Knock, Jonathan; Corcia, Philippe; Couratier, Philippe; de Carvalho, Mamede; Dekker, Annelot; Drory, Vivian; Redondo, Alberto Garcia; Gotkine, Marc; Hardiman, Orla; Hide, Winston; Iacoangeli, Alfredo; Glass, Jonathan D.; Kenna, Kevin P.; Kiernan, Matthew; Kooyman, Maarten; Landers, John E.; McLaughlin, Russell; Middelkoop, Bas; Mill, Jonathan; Neto, Miguel Mitne; Moisse, Matthieu; Pardina, Jesus Mora; Morrison, Karen; Newhouse, Stephen; Pinto, Susana; Pulit, Sara; Robberecht, Wim; Shatunov, Aleksey; Shaw, Pamela; Shaw, Chris; Silani, Vincenzo; Sproviero, William; Tazelaar, Gijs; Ticozzi, Nicola; Van Damme, Philip; van den Berg, Leonard; van der Spek, Rick; Van Eijk, Kristel R.; Van Es, Michael A.; van Rheenen, Wouter; van Vugt, Joke J.F.A.; Veldink, Jan H.; Weber, Markus; Williams, Kelly L.; Van Damme, Philip; Robberecht, Wim; Zatz, Mayana; Robberecht, Wim; Bauer, Denis C.; Twine, Natalie A.; Rogaeva, Ekaterina; Zinman, Lorne; Ostrow, Lyle W.; Maragakis, Nicholas J.; Rothstein, Jeffrey D.; Simmons, Zachary; Cooper-Knock, Johnathan; Brice, Alexis; Goutman, Stephen A.; Feldman, Eva L.; Gibson, Summer B.; Taroni, Franco; Ratti, Antonia; Ratti, Antonia; Gellera, Cinzia; Van Damme, Philip; Robberecht, Wim; Fratta, Pietro; Sabatelli, Mario; Lunetta, Christian; Ludolph, Albert C.; Andersen, Peter M.; Weishaupt, Jochen H.; Camu, William; Trojanowski, John Q.; Van Deerlin, Vivianna M.; Brown, Robert H.; van den Berg, Leonard; Veldink, Jan H.; Harms, Matthew B.; Glass, Jonathan D.; Stone, David J.; Tienari, Pentti; Silani, Vincenzo; Silani, Vincenzo; Chiò, Adriano; Shaw, Christopher E.; Chiò, Adriano; Traynor, Bryan J.; Landers, John E.; Traynor, Bryan J.

    2018-01-01

    To identify novel genes associated with ALS, we undertook two lines of investigation. We carried out a genome-wide association study comparing 20,806 ALS cases and 59,804 controls. Independently, we performed a rare variant burden analysis comparing 1,138 index familial ALS cases and 19,494

  2. Genome-wide association analyses identify 18 new loci associated with serum urate concentrations

    NARCIS (Netherlands)

    Kottgen, A.; Albrecht, E.; Teumer, A.; Vitart, V.; Krumsiek, J.; Hundertmark, C.; Pistis, G.; Ruggiero, D.; O'Seaghdha, C.M.; Haller, T.; Yang, Q.; Johnson, A.D.; Kutalik, Z.; Smith, A.V.; Shi, J.L.; Struchalin, M.; Middelberg, R.P.S.; Brown, M.J.; Gaffo, A.L.; Pirastu, N.; Li, G.; Hayward, C.; Zemunik, T.; Huffman, J.; Yengo, L.; Zhao, J.H.; Demirkan, A.; Feitosa, M.F.; Liu, X.; Malerba, G.; Lopez, L.M.; van der Harst, P.; Li, X.Z.; Kleber, M.E.; Hicks, A.A.; Nolte, I.M.; Johansson, A.; Murgia, F.; Wild, S.H.; Bakker, S.J.L.; Peden, J.F.; Dehghan, A.; Steri, M.; Tenesa, A.; Lagou, V.; Salo, P.; Mangino, M.; Rose, L.M.; Lehtimaki, T.; Woodward, O.M.; Okada, Y.; Tin, A.; Muller, C.; Oldmeadow, C.; Putku, M.; Czamara, D.; Kraft, P.; Frogheri, L.; Thun, G.A.; Grotevendt, A.; Gislason, G.K.; Harris, T.B.; Launer, L.J.; McArdle, P.; Shuldiner, A.R.; Boerwinkle, E.; Coresh, J.; Schmidt, H.; Schallert, M.; Martin, N.G.; Montgomery, G.W.; Kubo, M.; Nakamura, Y.; Tanaka, T.; Munroe, P.B.; Samani, N.J.; Jacobs, D.R.; Liu, K.; d'Adamo, P.; Ulivi, S.; Rotter, J.I.; Psaty, B.M.; Vollenweider, P.; Waeber, G.; Campbell, S.; Devuyst, O.; Navarro, P.; Kolcic, I.; Hastie, N.; Balkau, B.; Froguel, P.; Esko, T.; Salumets, A.; Khaw, K.T.; Langenberg, C.; Wareham, N.J.; Isaacs, A.; Kraja, A.; Zhang, Q.Y.; Penninx, B.W.J.H.; Smit, J.H.; Bochud, M.; Gieger, C.

    2013-01-01

    Elevated serum urate concentrations can cause gout, a prevalent and painful inflammatory arthritis. By combining data from >140,000 individuals of European ancestry within the Global Urate Genetics Consortium (GUGC), we identified and replicated 28 genome-wide significant loci in association with

  3. Genome-wide association analyses identify 18 new loci associated with serum urate concentrations

    NARCIS (Netherlands)

    Köttgen, Anna; Albrecht, Eva; Teumer, Alexander; Vitart, Veronique; Krumsiek, Jan; Hundertmark, Claudia; Pistis, Giorgio; Ruggiero, Daniela; O'Seaghdha, Conall M; Haller, Toomas; Yang, Qiong; Tanaka, Toshiko; Johnson, Andrew D; Kutalik, Zoltán; Smith, Albert V; Shi, Julia; Struchalin, Maksim; Middelberg, Rita P S; Brown, Morris J; Gaffo, Angelo L; Pirastu, Nicola; Li, Guo; Hayward, Caroline; Zemunik, Tatijana; Huffman, Jennifer; Yengo, Loic; Zhao, Jing Hua; Demirkan, Ayse; Feitosa, Mary F; Liu, Xuan; Malerba, Giovanni; Lopez, Lorna M; van der Harst, Pim; Li, Xinzhong; Kleber, Marcus E; Hicks, Andrew A; Nolte, Ilja M; Johansson, Asa; Murgia, Federico; Bakker, Stephan J L; Lagou, Vasiliki; Bruinenberg, Marcel; Stolk, Ronald P; Penninx, Brenda W; Mateo Leach, Irene; van Gilst, Wiek H; Hillege, Hans L; Wolffenbuttel, Bruce H R; Snieder, Harold; Navis, Gerjan

    Elevated serum urate concentrations can cause gout, a prevalent and painful inflammatory arthritis. By combining data from >140,000 individuals of European ancestry within the Global Urate Genetics Consortium (GUGC), we identified and replicated 28 genome-wide significant loci in association with

  4. Integrating genetic, transcriptional, and functional analyses to identify 5 novel genes for atrial fibrillation

    DEFF Research Database (Denmark)

    Sinner, Moritz F; Tucker, Nathan R; Lunetta, Kathryn L

    2014-01-01

    BACKGROUND: Atrial fibrillation (AF) affects >30 million individuals worldwide and is associated with an increased risk of stroke, heart failure, and death. AF is highly heritable, yet the genetic basis for the arrhythmia remains incompletely understood. METHODS AND RESULTS: To identify new AF-re...

  5. Comparative analyses identified species-specific functional roles in oral microbial genomes

    Science.gov (United States)

    Chen, Tsute; Gajare, Prasad; Olsen, Ingar; Dewhirst, Floyd E.

    2017-01-01

    ABSTRACT The advent of next generation sequencing is producing more genomic sequences for various strains of many human oral microbial species and allows for insightful functional comparisons at both intra- and inter-species levels. This study performed in-silico functional comparisons for currently available genomic sequences of major species associated with periodontitis including Aggregatibacter actinomycetemcomitans (AA), Porphyromonas gingivalis (PG), Treponema denticola (TD), and Tannerella forsythia (TF), as well as several cariogenic and commensal streptococcal species. Complete or draft sequences were annotated with the RAST to infer structured functional subsystems for each genome. The subsystems profiles were clustered to groups of functions with similar patterns. Functional enrichment and depletion were evaluated based on hypergeometric distribution to identify subsystems that are unique or missing between two groups of genomes. Unique or missing metabolic pathways and biological functions were identified in different species. For example, components involved in flagellar motility were found only in the motile species TD, as expected, with few exceptions scattered in several streptococcal species, likely associated with chemotaxis. Transposable elements were only found in the two Bacteroidales species PG and TF, and half of the AA genomes. Genes involved in CRISPR were prevalent in most oral species. Furthermore, prophage related subsystems were also commonly found in most species except for PG and Streptococcus mutans, in which very few genomes contain prophage components. Comparisons between pathogenic (P) and nonpathogenic (NP) genomes also identified genes potentially important for virulence. Two such comparisons were performed between AA (P) and several A. aphrophilus (NP) strains, and between S. mutans + S. sobrinus (P) and other oral streptococcal species (NP). This comparative genomics approach can be readily used to identify functions unique to

  6. Identifying Breeding Priorities for Blueberry Flavor Using Biochemical, Sensory, and Genotype by Environment Analyses

    Science.gov (United States)

    Gilbert, Jessica L.; Guthart, Matthew J.; Gezan, Salvador A.; Pisaroglo de Carvalho, Melissa; Schwieterman, Michael L.; Colquhoun, Thomas A.; Bartoshuk, Linda M.; Sims, Charles A.; Clark, David G.; Olmstead, James W.

    2015-01-01

    Breeding for a subjective goal such as flavor is challenging, as many blueberry cultivars are grown worldwide, and identifying breeding targets relating to blueberry flavor biochemistry that have a high degree of genetic control and low environmental variability are priorities. A variety of biochemical compounds and physical characters induce the sensory responses of taste, olfaction, and somatosensation, all of which interact to create what is perceived flavor. The goal of this study was to identify the flavor compounds with a larger genetic versus environmental component regulating their expression over an array of cultivars, locations, and years. Over the course of three years, consumer panelists rated overall liking, texture, sweetness, sourness, and flavor intensity of 19 southern highbush blueberry (Vaccinium corymbosum hybrids) genotypes in 30 sensory panels. Significant positive correlations to overall liking of blueberry fruit (Panalysis was used to identify sugars, acids, and volatile compounds contributing to liking and sensory intensities, and revealed strong effects of fructose, pH, and several volatile compounds upon all sensory parameters measured. To assess the feasibility of breeding for flavor components, a three year study was conducted to compare genetic and environmental influences on flavor biochemistry. Panelists could discern genotypic variation in blueberry sensory components, and many of the compounds affecting consumer favor of blueberries, such as fructose, pH, β-caryophyllene oxide and 2-heptanone, were sufficiently genetically controlled that allocating resources for their breeding is worthwhile. PMID:26378911

  7. Identifying Breeding Priorities for Blueberry Flavor Using Biochemical, Sensory, and Genotype by Environment Analyses.

    Directory of Open Access Journals (Sweden)

    Jessica L Gilbert

    Full Text Available Breeding for a subjective goal such as flavor is challenging, as many blueberry cultivars are grown worldwide, and identifying breeding targets relating to blueberry flavor biochemistry that have a high degree of genetic control and low environmental variability are priorities. A variety of biochemical compounds and physical characters induce the sensory responses of taste, olfaction, and somatosensation, all of which interact to create what is perceived flavor. The goal of this study was to identify the flavor compounds with a larger genetic versus environmental component regulating their expression over an array of cultivars, locations, and years. Over the course of three years, consumer panelists rated overall liking, texture, sweetness, sourness, and flavor intensity of 19 southern highbush blueberry (Vaccinium corymbosum hybrids genotypes in 30 sensory panels. Significant positive correlations to overall liking of blueberry fruit (P<0.001 were found with sweetness (R2 = 0.70, texture (R2 = 0.68, and flavor (R2 = 0.63. Sourness had a significantly negative relationship with overall liking (R2 = 0.55. The relationship between flavor and texture liking was also linear (R2 = 0.73, P<0.0001 demonstrating interaction between olfaction and somatosensation. Partial least squares analysis was used to identify sugars, acids, and volatile compounds contributing to liking and sensory intensities, and revealed strong effects of fructose, pH, and several volatile compounds upon all sensory parameters measured. To assess the feasibility of breeding for flavor components, a three year study was conducted to compare genetic and environmental influences on flavor biochemistry. Panelists could discern genotypic variation in blueberry sensory components, and many of the compounds affecting consumer favor of blueberries, such as fructose, pH, β-caryophyllene oxide and 2-heptanone, were sufficiently genetically controlled that allocating resources for their

  8. Differential proteomic and tissue expression analyses identify valuable diagnostic biomarkers of hepatocellular differentiation and hepatoid adenocarcinomas.

    Science.gov (United States)

    Reis, Henning; Padden, Juliet; Ahrens, Maike; Pütter, Carolin; Bertram, Stefanie; Pott, Leona L; Reis, Anna-Carinna; Weber, Frank; Juntermanns, Benjamin; Hoffmann, Andreas-C; Eisenacher, Martin; Schlaak, Joörg F; Canbay, Ali; Meyer, Helmut E; Sitek, Barbara; Baba, Hideo A

    2015-10-01

    The exact discrimination of lesions with true hepatocellular differentiation from secondary tumours and neoplasms with hepatocellular histomorphology like hepatoid adenocarcinomas (HAC) is crucial. Therefore, we aimed to identify ancillary protein biomarkers by using complementary proteomic techniques (2D-DIGE, label-free MS). The identified candidates were immunohistochemically validated in 14 paired samples of hepatocellular carcinoma (HCC) and non-tumourous liver tissue (NT). The candidates and HepPar1/Arginase1 were afterwards tested for consistency in a large cohort of hepatocellular lesions and NT (n = 290), non-hepatocellular malignancies (n = 383) and HAC (n = 13). Eight non-redundant, differentially expressed proteins were suitable for further immunohistochemical validation and four (ABAT, BHMT, FABP1, HAOX1) for further evaluation. Sensitivity and specificity rates for HCC/HAC were as follows: HepPar1 80.2%, 94.3% / 80.2%, 46.2%; Arginase1 82%, 99.4% / 82%, 69.2%; BHMT 61.4%, 93.8% / 61.4%, 100%; ABAT 84.4%, 33.7% / 84.4%, 30.8%; FABP1 87.2%, 95% / 87.2%, 69.2%; HAOX1 95.5%, 36.3% / 95.5%, 46.2%. The best 2×/3× biomarker panels for the diagnosis of HCC consisted of Arginase1/HAOX1 and BHMT/Arginase1/HAOX1 and for HAC consisted of Arginase1/FABP1 and BHMT/Arginase1/FABP1. In summary, we successfully identified, validated and benchmarked protein biomarker candidates of hepatocellular differentiation. BHMT in particular exhibited superior diagnostic characteristics in hepatocellular lesions and specifically in HAC. BHMT is therefore a promising (panel based) biomarker candidate in the differential diagnostic process of lesions with hepatocellular aspect.

  9. Comparative analyses of Legionella species identifies genetic features of strains causing Legionnaires' disease.

    Science.gov (United States)

    Gomez-Valero, Laura; Rusniok, Christophe; Rolando, Monica; Neou, Mario; Dervins-Ravault, Delphine; Demirtas, Jasmin; Rouy, Zoe; Moore, Robert J; Chen, Honglei; Petty, Nicola K; Jarraud, Sophie; Etienne, Jerome; Steinert, Michael; Heuner, Klaus; Gribaldo, Simonetta; Médigue, Claudine; Glöckner, Gernot; Hartland, Elizabeth L; Buchrieser, Carmen

    2014-01-01

    The genus Legionella comprises over 60 species. However, L. pneumophila and L. longbeachae alone cause over 95% of Legionnaires’ disease. To identify the genetic bases underlying the different capacities to cause disease we sequenced and compared the genomes of L. micdadei, L. hackeliae and L. fallonii (LLAP10), which are all rarely isolated from humans. We show that these Legionella species possess different virulence capacities in amoeba and macrophages, correlating with their occurrence in humans. Our comparative analysis of 11 Legionella genomes belonging to five species reveals highly heterogeneous genome content with over 60% representing species-specific genes; these comprise a complete prophage in L. micdadei, the first ever identified in a Legionella genome. Mobile elements are abundant in Legionella genomes; many encode type IV secretion systems for conjugative transfer, pointing to their importance for adaptation of the genus. The Dot/Icm secretion system is conserved, although the core set of substrates is small, as only 24 out of over 300 described Dot/Icm effector genes are present in all Legionella species. We also identified new eukaryotic motifs including thaumatin, synaptobrevin or clathrin/coatomer adaptine like domains. Legionella genomes are highly dynamic due to a large mobilome mainly comprising type IV secretion systems, while a minority of core substrates is shared among the diverse species. Eukaryotic like proteins and motifs remain a hallmark of the genus Legionella. Key factors such as proteins involved in oxygen binding, iron storage, host membrane transport and certain Dot/Icm substrates are specific features of disease-related strains.

  10. Genome-wide Analyses Identify KIF5A as a Novel ALS Gene.

    Science.gov (United States)

    Nicolas, Aude; Kenna, Kevin P; Renton, Alan E; Ticozzi, Nicola; Faghri, Faraz; Chia, Ruth; Dominov, Janice A; Kenna, Brendan J; Nalls, Mike A; Keagle, Pamela; Rivera, Alberto M; van Rheenen, Wouter; Murphy, Natalie A; van Vugt, Joke J F A; Geiger, Joshua T; Van der Spek, Rick A; Pliner, Hannah A; Shankaracharya; Smith, Bradley N; Marangi, Giuseppe; Topp, Simon D; Abramzon, Yevgeniya; Gkazi, Athina Soragia; Eicher, John D; Kenna, Aoife; Mora, Gabriele; Calvo, Andrea; Mazzini, Letizia; Riva, Nilo; Mandrioli, Jessica; Caponnetto, Claudia; Battistini, Stefania; Volanti, Paolo; La Bella, Vincenzo; Conforti, Francesca L; Borghero, Giuseppe; Messina, Sonia; Simone, Isabella L; Trojsi, Francesca; Salvi, Fabrizio; Logullo, Francesco O; D'Alfonso, Sandra; Corrado, Lucia; Capasso, Margherita; Ferrucci, Luigi; Moreno, Cristiane de Araujo Martins; Kamalakaran, Sitharthan; Goldstein, David B; Gitler, Aaron D; Harris, Tim; Myers, Richard M; Phatnani, Hemali; Musunuri, Rajeeva Lochan; Evani, Uday Shankar; Abhyankar, Avinash; Zody, Michael C; Kaye, Julia; Finkbeiner, Steven; Wyman, Stacia K; LeNail, Alex; Lima, Leandro; Fraenkel, Ernest; Svendsen, Clive N; Thompson, Leslie M; Van Eyk, Jennifer E; Berry, James D; Miller, Timothy M; Kolb, Stephen J; Cudkowicz, Merit; Baxi, Emily; Benatar, Michael; Taylor, J Paul; Rampersaud, Evadnie; Wu, Gang; Wuu, Joanne; Lauria, Giuseppe; Verde, Federico; Fogh, Isabella; Tiloca, Cinzia; Comi, Giacomo P; Sorarù, Gianni; Cereda, Cristina; Corcia, Philippe; Laaksovirta, Hannu; Myllykangas, Liisa; Jansson, Lilja; Valori, Miko; Ealing, John; Hamdalla, Hisham; Rollinson, Sara; Pickering-Brown, Stuart; Orrell, Richard W; Sidle, Katie C; Malaspina, Andrea; Hardy, John; Singleton, Andrew B; Johnson, Janel O; Arepalli, Sampath; Sapp, Peter C; McKenna-Yasek, Diane; Polak, Meraida; Asress, Seneshaw; Al-Sarraj, Safa; King, Andrew; Troakes, Claire; Vance, Caroline; de Belleroche, Jacqueline; Baas, Frank; Ten Asbroek, Anneloor L M A; Muñoz-Blanco, José Luis; Hernandez, Dena G; Ding, Jinhui; Gibbs, J Raphael; Scholz, Sonja W; Floeter, Mary Kay; Campbell, Roy H; Landi, Francesco; Bowser, Robert; Pulst, Stefan M; Ravits, John M; MacGowan, Daniel J L; Kirby, Janine; Pioro, Erik P; Pamphlett, Roger; Broach, James; Gerhard, Glenn; Dunckley, Travis L; Brady, Christopher B; Kowall, Neil W; Troncoso, Juan C; Le Ber, Isabelle; Mouzat, Kevin; Lumbroso, Serge; Heiman-Patterson, Terry D; Kamel, Freya; Van Den Bosch, Ludo; Baloh, Robert H; Strom, Tim M; Meitinger, Thomas; Shatunov, Aleksey; Van Eijk, Kristel R; de Carvalho, Mamede; Kooyman, Maarten; Middelkoop, Bas; Moisse, Matthieu; McLaughlin, Russell L; Van Es, Michael A; Weber, Markus; Boylan, Kevin B; Van Blitterswijk, Marka; Rademakers, Rosa; Morrison, Karen E; Basak, A Nazli; Mora, Jesús S; Drory, Vivian E; Shaw, Pamela J; Turner, Martin R; Talbot, Kevin; Hardiman, Orla; Williams, Kelly L; Fifita, Jennifer A; Nicholson, Garth A; Blair, Ian P; Rouleau, Guy A; Esteban-Pérez, Jesús; García-Redondo, Alberto; Al-Chalabi, Ammar; Rogaeva, Ekaterina; Zinman, Lorne; Ostrow, Lyle W; Maragakis, Nicholas J; Rothstein, Jeffrey D; Simmons, Zachary; Cooper-Knock, Johnathan; Brice, Alexis; Goutman, Stephen A; Feldman, Eva L; Gibson, Summer B; Taroni, Franco; Ratti, Antonia; Gellera, Cinzia; Van Damme, Philip; Robberecht, Wim; Fratta, Pietro; Sabatelli, Mario; Lunetta, Christian; Ludolph, Albert C; Andersen, Peter M; Weishaupt, Jochen H; Camu, William; Trojanowski, John Q; Van Deerlin, Vivianna M; Brown, Robert H; van den Berg, Leonard H; Veldink, Jan H; Harms, Matthew B; Glass, Jonathan D; Stone, David J; Tienari, Pentti; Silani, Vincenzo; Chiò, Adriano; Shaw, Christopher E; Traynor, Bryan J; Landers, John E

    2018-03-21

    To identify novel genes associated with ALS, we undertook two lines of investigation. We carried out a genome-wide association study comparing 20,806 ALS cases and 59,804 controls. Independently, we performed a rare variant burden analysis comparing 1,138 index familial ALS cases and 19,494 controls. Through both approaches, we identified kinesin family member 5A (KIF5A) as a novel gene associated with ALS. Interestingly, mutations predominantly in the N-terminal motor domain of KIF5A are causative for two neurodegenerative diseases: hereditary spastic paraplegia (SPG10) and Charcot-Marie-Tooth type 2 (CMT2). In contrast, ALS-associated mutations are primarily located at the C-terminal cargo-binding tail domain and patients harboring loss-of-function mutations displayed an extended survival relative to typical ALS cases. Taken together, these results broaden the phenotype spectrum resulting from mutations in KIF5A and strengthen the role of cytoskeletal defects in the pathogenesis of ALS. Copyright © 2018 Elsevier Inc. All rights reserved.

  11. Identifying Breeding Priorities for Blueberry Flavor Using Biochemical, Sensory, and Genotype by Environment Analyses.

    Science.gov (United States)

    Gilbert, Jessica L; Guthart, Matthew J; Gezan, Salvador A; Pisaroglo de Carvalho, Melissa; Schwieterman, Michael L; Colquhoun, Thomas A; Bartoshuk, Linda M; Sims, Charles A; Clark, David G; Olmstead, James W

    2015-01-01

    Breeding for a subjective goal such as flavor is challenging, as many blueberry cultivars are grown worldwide, and identifying breeding targets relating to blueberry flavor biochemistry that have a high degree of genetic control and low environmental variability are priorities. A variety of biochemical compounds and physical characters induce the sensory responses of taste, olfaction, and somatosensation, all of which interact to create what is perceived flavor. The goal of this study was to identify the flavor compounds with a larger genetic versus environmental component regulating their expression over an array of cultivars, locations, and years. Over the course of three years, consumer panelists rated overall liking, texture, sweetness, sourness, and flavor intensity of 19 southern highbush blueberry (Vaccinium corymbosum hybrids) genotypes in 30 sensory panels. Significant positive correlations to overall liking of blueberry fruit (Pblueberry sensory components, and many of the compounds affecting consumer favor of blueberries, such as fructose, pH, β-caryophyllene oxide and 2-heptanone, were sufficiently genetically controlled that allocating resources for their breeding is worthwhile.

  12. Single-cell analyses identify bioengineered niches for enhanced maintenance of hematopoietic stem cells.

    Science.gov (United States)

    Roch, Aline; Giger, Sonja; Girotra, Mukul; Campos, Vasco; Vannini, Nicola; Naveiras, Olaia; Gobaa, Samy; Lutolf, Matthias P

    2017-08-09

    The in vitro expansion of long-term hematopoietic stem cells (HSCs) remains a substantial challenge, largely because of our limited understanding of the mechanisms that control HSC fate choices. Using single-cell multigene expression analysis and time-lapse microscopy, here we define gene expression signatures and cell cycle hallmarks of murine HSCs and the earliest multipotent progenitors (MPPs), and analyze systematically single HSC fate choices in culture. Our analysis revealed twelve differentially expressed genes marking the quiescent HSC state, including four genes encoding cell-cell interaction signals in the niche. Under basal culture conditions, most HSCs rapidly commit to become early MPPs. In contrast, when we present ligands of the identified niche components such as JamC or Esam within artificial niches, HSC cycling is reduced and long-term multipotency in vivo is maintained. Our approach to bioengineer artificial niches should be useful in other stem cell systems.Haematopoietic stem cell (HSC) self-renewal is not sufficiently understood to recapitulate in vitro. Here, the authors generate gene signature and cell cycle hallmarks of single murine HSCs, and use identified endothelial receptors Esam and JamC as substrates to enhance HSC growth in engineered niches.

  13. Stable isotope analyses of feather amino acids identify penguin migration strategies at ocean basin scales.

    Science.gov (United States)

    Polito, Michael J; Hinke, Jefferson T; Hart, Tom; Santos, Mercedes; Houghton, Leah A; Thorrold, Simon R

    2017-08-01

    Identifying the at-sea distribution of wide-ranging marine predators is critical to understanding their ecology. Advances in electronic tracking devices and intrinsic biogeochemical markers have greatly improved our ability to track animal movements on ocean-wide scales. Here, we show that, in combination with direct tracking, stable carbon isotope analysis of essential amino acids in tail feathers provides the ability to track the movement patterns of two, wide-ranging penguin species over ocean basin scales. In addition, we use this isotopic approach across multiple breeding colonies in the Scotia Arc to evaluate migration trends at a regional scale that would be logistically challenging using direct tracking alone. © 2017 The Author(s).

  14. Comprehensive analyses of ventricular myocyte models identify targets exhibiting favorable rate dependence.

    Directory of Open Access Journals (Sweden)

    Megan A Cummins

    2014-03-01

    Full Text Available Reverse rate dependence is a problematic property of antiarrhythmic drugs that prolong the cardiac action potential (AP. The prolongation caused by reverse rate dependent agents is greater at slow heart rates, resulting in both reduced arrhythmia suppression at fast rates and increased arrhythmia risk at slow rates. The opposite property, forward rate dependence, would theoretically overcome these parallel problems, yet forward rate dependent (FRD antiarrhythmics remain elusive. Moreover, there is evidence that reverse rate dependence is an intrinsic property of perturbations to the AP. We have addressed the possibility of forward rate dependence by performing a comprehensive analysis of 13 ventricular myocyte models. By simulating populations of myocytes with varying properties and analyzing population results statistically, we simultaneously predicted the rate-dependent effects of changes in multiple model parameters. An average of 40 parameters were tested in each model, and effects on AP duration were assessed at slow (0.2 Hz and fast (2 Hz rates. The analysis identified a variety of FRD ionic current perturbations and generated specific predictions regarding their mechanisms. For instance, an increase in L-type calcium current is FRD when this is accompanied by indirect, rate-dependent changes in slow delayed rectifier potassium current. A comparison of predictions across models identified inward rectifier potassium current and the sodium-potassium pump as the two targets most likely to produce FRD AP prolongation. Finally, a statistical analysis of results from the 13 models demonstrated that models displaying minimal rate-dependent changes in AP shape have little capacity for FRD perturbations, whereas models with large shape changes have considerable FRD potential. This can explain differences between species and between ventricular cell types. Overall, this study provides new insights, both specific and general, into the determinants of

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

    Science.gov (United States)

    van Huet, Ramon A. C.; Pierrache, Laurence H.M.; Meester-Smoor, Magda A.; Klaver, Caroline C.W.; van den Born, L. Ingeborgh; Hoyng, Carel B.; de Wijs, Ilse J.; Collin, Rob W. J.; Hoefsloot, Lies H.

    2015-01-01

    Purpose To determine the efficacy of multiple versions of a commercially available arrayed primer extension (APEX) microarray chip for autosomal recessive retinitis pigmentosa (arRP). Methods We included 250 probands suspected of arRP who were genetically analyzed with the APEX microarray between January 2008 and November 2013. The mode of inheritance had to be autosomal recessive according to the pedigree (including isolated cases). If the microarray identified a heterozygous mutation, we performed Sanger sequencing of exons and exon–intron boundaries of that specific gene. The efficacy of this microarray chip with the additional Sanger sequencing approach was determined by the percentage of patients that received a molecular diagnosis. We also collected data from genetic tests other than the APEX analysis for arRP to provide a detailed description of the molecular diagnoses in our study cohort. Results The APEX microarray chip for arRP identified the molecular diagnosis in 21 (8.5%) of the patients in our cohort. Additional Sanger sequencing yielded a second mutation in 17 patients (6.8%), thereby establishing the molecular diagnosis. In total, 38 patients (15.2%) received a molecular diagnosis after analysis using the microarray and additional Sanger sequencing approach. Further genetic analyses after a negative result of the arRP microarray (n = 107) resulted in a molecular diagnosis of arRP (n = 23), autosomal dominant RP (n = 5), X-linked RP (n = 2), and choroideremia (n = 1). Conclusions The efficacy of the commercially available APEX microarray chips for arRP appears to be low, most likely caused by the limitations of this technique and the genetic and allelic heterogeneity of RP. Diagnostic yields up to 40% have been reported for next-generation sequencing (NGS) techniques that, as expected, thereby outperform targeted APEX analysis. PMID:25999674

  16. Comparative and bioinformatics analyses of pathogenic bacterial secretomes identified by mass spectrometry in Burkholderia species.

    Science.gov (United States)

    Nguyen, Thao Thi; Chon, Tae-Soo; Kim, Jaehan; Seo, Young-Su; Heo, Muyoung

    2017-07-01

    Secreted proteins (secretomes) play crucial roles during bacterial pathogenesis in both plant and human hosts. The identification and characterization of secretomes in the two plant pathogens Burkholderia glumae BGR1 and B. gladioli BSR3, which cause diseases in rice such as seedling blight, panicle blight, and grain rot, are important steps to not only understand the disease-causing mechanisms but also find remedies for the diseases. Here, we identified two datasets of secretomes in B. glumae BGR1 and B. gladioli BSR3, which consist of 118 and 111 proteins, respectively, using mass spectrometry approach and literature curation. Next, we characterized the functional properties, potential secretion pathways and sequence information properties of secretomes of two plant pathogens in a comparative analysis by various computational approaches. The ratio of potential non-classically secreted proteins (NCSPs) to classically secreted proteins (CSPs) in B. glumae BGR1 was greater than that in B. gladioli BSR3. For CSPs, the putative hydrophobic regions (PHRs) which are essential for secretion process of CSPs were screened in detail at their N-terminal sequences using hidden Markov model (HMM)-based method. Total 31 pairs of homologous proteins in two bacterial secretomes were indicated based on the global alignment (identity ≥ 70%). Our results may facilitate the understanding of the species-specific features of secretomes in two plant pathogenic Burkholderia species.

  17. Statistical analyses of scatterplots to identify important factors in large-scale simulations, 1: Review and comparison of techniques

    International Nuclear Information System (INIS)

    Kleijnen, J.P.C.; Helton, J.C.

    1999-01-01

    Procedures for identifying patterns in scatterplots generated in Monte Carlo sensitivity analyses are described and illustrated. These procedures attempt to detect increasingly complex patterns in scatterplots and involve the identification of (i) linear relationships with correlation coefficients, (ii) monotonic relationships with rank correlation coefficients, (iii) trends in central tendency as defined by means, medians and the Kruskal-Wallis statistic, (iv) trends in variability as defined by variances and interquartile ranges, and (v) deviations from randomness as defined by the chi-square statistic. A sequence of example analyses with a large model for two-phase fluid flow illustrates how the individual procedures can differ in the variables that they identify as having effects on particular model outcomes. The example analyses indicate that the use of a sequence of procedures is a good analysis strategy and provides some assurance that an important effect is not overlooked

  18. Application of Microarrays and qPCR to Identify Phylogenetic and Functional Biomarkers Diagnostic of Microbial Communities that Biodegrade Chlorinated Solvents to Ethene

    Science.gov (United States)

    2012-01-01

    appropriate and cost - effective biomarkers to assess, monitor, and optimize performance. Commonly, biomarker development has focused on identifying...field sites. Firmicutes (Mostly Clostridium spp.), Bacteroidetes (Mostly Bacteroides spp.), as well as Proteobacteria (Mostly sulfate-reducer, i.e...continuous-flow chemostat, and environmental samples from contaminated field sites. Firmicutes (Mostly Clostridium spp.), Bacteroidetes (Mostly

  19. Gene Network Construction from Microarray Data Identifies a Key Network Module and Several Candidate Hub Genes in Age-Associated Spatial Learning Impairment.

    Science.gov (United States)

    Uddin, Raihan; Singh, Shiva M

    2017-01-01

    As humans age many suffer from a decrease in normal brain functions including spatial learning impairments. This study aimed to better understand the molecular mechanisms in age-associated spatial learning impairment (ASLI). We used a mathematical modeling approach implemented in Weighted Gene Co-expression Network Analysis (WGCNA) to create and compare gene network models of young (learning unimpaired) and aged (predominantly learning impaired) brains from a set of exploratory datasets in rats in the context of ASLI. The major goal was to overcome some of the limitations previously observed in the traditional meta- and pathway analysis using these data, and identify novel ASLI related genes and their networks based on co-expression relationship of genes. This analysis identified a set of network modules in the young, each of which is highly enriched with genes functioning in broad but distinct GO functional categories or biological pathways. Interestingly, the analysis pointed to a single module that was highly enriched with genes functioning in "learning and memory" related functions and pathways. Subsequent differential network analysis of this "learning and memory" module in the aged (predominantly learning impaired) rats compared to the young learning unimpaired rats allowed us to identify a set of novel ASLI candidate hub genes. Some of these genes show significant repeatability in networks generated from independent young and aged validation datasets. These hub genes are highly co-expressed with other genes in the network, which not only show differential expression but also differential co-expression and differential connectivity across age and learning impairment. The known function of these hub genes indicate that they play key roles in critical pathways, including kinase and phosphatase signaling, in functions related to various ion channels, and in maintaining neuronal integrity relating to synaptic plasticity and memory formation. Taken together, they

  20. Fibre optic microarrays.

    Science.gov (United States)

    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.

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

    Directory of Open Access Journals (Sweden)

    Bernhard Schweighofer

    2015-06-01

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

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

    Directory of Open Access Journals (Sweden)

    Paula Fernandez

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

  3. Radioactive cDNA microarray in neurospsychiatry

    International Nuclear Information System (INIS)

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

    2003-01-01

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

  4. Radioactive cDNA microarray in neurospsychiatry

    Energy Technology Data Exchange (ETDEWEB)

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

    2003-02-01

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

  5. DNA Microarray Technology

    Science.gov (United States)

    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 ...

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

    Science.gov (United States)

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

    2012-12-18

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

  7. DNA Microarray Technology; TOPICAL

    International Nuclear Information System (INIS)

    WERNER-WASHBURNE, MARGARET; DAVIDSON, GEORGE S.

    2002-01-01

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

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

    Science.gov (United States)

    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.

  9. Large-scale association analyses identify new loci influencing glycemic traits and provide insight into the underlying biological pathways

    Science.gov (United States)

    Scott, Robert A; Lagou, Vasiliki; Welch, Ryan P; Wheeler, Eleanor; Montasser, May E; Luan, Jian’an; Mägi, Reedik; Strawbridge, Rona J; Rehnberg, Emil; Gustafsson, Stefan; Kanoni, Stavroula; Rasmussen-Torvik, Laura J; Yengo, Loïc; Lecoeur, Cecile; Shungin, Dmitry; Sanna, Serena; Sidore, Carlo; Johnson, Paul C D; Jukema, J Wouter; Johnson, Toby; Mahajan, Anubha; Verweij, Niek; Thorleifsson, Gudmar; Hottenga, Jouke-Jan; Shah, Sonia; Smith, Albert V; Sennblad, Bengt; Gieger, Christian; Salo, Perttu; Perola, Markus; Timpson, Nicholas J; Evans, David M; Pourcain, Beate St; Wu, Ying; Andrews, Jeanette S; Hui, Jennie; Bielak, Lawrence F; Zhao, Wei; Horikoshi, Momoko; Navarro, Pau; Isaacs, Aaron; O’Connell, Jeffrey R; Stirrups, Kathleen; Vitart, Veronique; Hayward, Caroline; Esko, Tönu; Mihailov, Evelin; Fraser, Ross M; Fall, Tove; Voight, Benjamin F; Raychaudhuri, Soumya; Chen, Han; Lindgren, Cecilia M; Morris, Andrew P; Rayner, Nigel W; Robertson, Neil; Rybin, Denis; Liu, Ching-Ti; Beckmann, Jacques S; Willems, Sara M; Chines, Peter S; Jackson, Anne U; Kang, Hyun Min; Stringham, Heather M; Song, Kijoung; Tanaka, Toshiko; Peden, John F; Goel, Anuj; Hicks, Andrew A; An, Ping; Müller-Nurasyid, Martina; Franco-Cereceda, Anders; Folkersen, Lasse; Marullo, Letizia; Jansen, Hanneke; Oldehinkel, Albertine J; Bruinenberg, Marcel; Pankow, James S; North, Kari E; Forouhi, Nita G; Loos, Ruth J F; Edkins, Sarah; Varga, Tibor V; Hallmans, Göran; Oksa, Heikki; Antonella, Mulas; Nagaraja, Ramaiah; Trompet, Stella; Ford, Ian; Bakker, Stephan J L; Kong, Augustine; Kumari, Meena; Gigante, Bruna; Herder, Christian; Munroe, Patricia B; Caulfield, Mark; Antti, Jula; Mangino, Massimo; Small, Kerrin; Miljkovic, Iva; Liu, Yongmei; Atalay, Mustafa; Kiess, Wieland; James, Alan L; Rivadeneira, Fernando; Uitterlinden, Andre G; Palmer, Colin N A; Doney, Alex S F; Willemsen, Gonneke; Smit, Johannes H; Campbell, Susan; Polasek, Ozren; Bonnycastle, Lori L; Hercberg, Serge; Dimitriou, Maria; Bolton, Jennifer L; Fowkes, Gerard R; Kovacs, Peter; Lindström, Jaana; Zemunik, Tatijana; Bandinelli, Stefania; Wild, Sarah H; Basart, Hanneke V; Rathmann, Wolfgang; Grallert, Harald; Maerz, Winfried; Kleber, Marcus E; Boehm, Bernhard O; Peters, Annette; Pramstaller, Peter P; Province, Michael A; Borecki, Ingrid B; Hastie, Nicholas D; Rudan, Igor; Campbell, Harry; Watkins, Hugh; Farrall, Martin; Stumvoll, Michael; Ferrucci, Luigi; Waterworth, Dawn M; Bergman, Richard N; Collins, Francis S; Tuomilehto, Jaakko; Watanabe, Richard M; de Geus, Eco J C; Penninx, Brenda W; Hofman, Albert; Oostra, Ben A; Psaty, Bruce M; Vollenweider, Peter; Wilson, James F; Wright, Alan F; Hovingh, G Kees; Metspalu, Andres; Uusitupa, Matti; Magnusson, Patrik K E; Kyvik, Kirsten O; Kaprio, Jaakko; Price, Jackie F; Dedoussis, George V; Deloukas, Panos; Meneton, Pierre; Lind, Lars; Boehnke, Michael; Shuldiner, Alan R; van Duijn, Cornelia M; Morris, Andrew D; Toenjes, Anke; Peyser, Patricia A; Beilby, John P; Körner, Antje; Kuusisto, Johanna; Laakso, Markku; Bornstein, Stefan R; Schwarz, Peter E H; Lakka, Timo A; Rauramaa, Rainer; Adair, Linda S; Smith, George Davey; Spector, Tim D; Illig, Thomas; de Faire, Ulf; Hamsten, Anders; Gudnason, Vilmundur; Kivimaki, Mika; Hingorani, Aroon; Keinanen-Kiukaanniemi, Sirkka M; Saaristo, Timo E; Boomsma, Dorret I; Stefansson, Kari; van der Harst, Pim; Dupuis, Josée; Pedersen, Nancy L; Sattar, Naveed; Harris, Tamara B; Cucca, Francesco; Ripatti, Samuli; Salomaa, Veikko; Mohlke, Karen L; Balkau, Beverley; Froguel, Philippe; Pouta, Anneli; Jarvelin, Marjo-Riitta; Wareham, Nicholas J; Bouatia-Naji, Nabila; McCarthy, Mark I; Franks, Paul W; Meigs, James B; Teslovich, Tanya M; Florez, Jose C; Langenberg, Claudia; Ingelsson, Erik; Prokopenko, Inga; Barroso, Inês

    2012-01-01

    Through genome-wide association meta-analyses of up to 133,010 individuals of European ancestry without diabetes, including individuals newly genotyped using the Metabochip, we have raised the number of confirmed loci influencing glycemic traits to 53, of which 33 also increase type 2 diabetes risk (q fasting insulin showed association with lipid levels and fat distribution, suggesting impact on insulin resistance. Gene-based analyses identified further biologically plausible loci, suggesting that additional loci beyond those reaching genome-wide significance are likely to represent real associations. This conclusion is supported by an excess of directionally consistent and nominally significant signals between discovery and follow-up studies. Functional follow-up of these newly discovered loci will further improve our understanding of glycemic control. PMID:22885924

  10. Genetic variants associated with subjective well-being, depressive symptoms and neuroticism identified through genome-wide analyses

    Science.gov (United States)

    Derringer, Jaime; Gratten, Jacob; Lee, James J; Liu, Jimmy Z; de Vlaming, Ronald; Ahluwalia, Tarunveer S; Buchwald, Jadwiga; Cavadino, Alana; Frazier-Wood, Alexis C; Davies, Gail; Furlotte, Nicholas A; Garfield, Victoria; Geisel, Marie Henrike; Gonzalez, Juan R; Haitjema, Saskia; Karlsson, Robert; van der Laan, Sander W; Ladwig, Karl-Heinz; Lahti, Jari; van der Lee, Sven J; Miller, Michael B; Lind, Penelope A; Liu, Tian; Matteson, Lindsay; Mihailov, Evelin; Minica, Camelia C; Nolte, Ilja M; Mook-Kanamori, Dennis O; van der Most, Peter J; Oldmeadow, Christopher; Qian, Yong; Raitakari, Olli; Rawal, Rajesh; Realo, Anu; Rueedi, Rico; Schmidt, Börge; Smith, Albert V; Stergiakouli, Evie; Tanaka, Toshiko; Taylor, Kent; Thorleifsson, Gudmar; Wedenoja, Juho; Wellmann, Juergen; Westra, Harm-Jan; Willems, Sara M; Zhao, Wei; Amin, Najaf; Bakshi, Andrew; Bergmann, Sven; Bjornsdottir, Gyda; Boyle, Patricia A; Cherney, Samantha; Cox, Simon R; Davis, Oliver S P; Ding, Jun; Direk, Nese; Eibich, Peter; Emeny, Rebecca T; Fatemifar, Ghazaleh; Faul, Jessica D; Ferrucci, Luigi; Forstner, Andreas J; Gieger, Christian; Gupta, Richa; Harris, Tamara B; Harris, Juliette M; Holliday, Elizabeth G; Hottenga, Jouke-Jan; De Jager, Philip L; Kaakinen, Marika A; Kajantie, Eero; Karhunen, Ville; Kolcic, Ivana; Kumari, Meena; Launer, Lenore J; Franke, Lude; Li-Gao, Ruifang; Liewald, David C; Koini, Marisa; Loukola, Anu; Marques-Vidal, Pedro; Montgomery, Grant W; Mosing, Miriam A; Paternoster, Lavinia; Pattie, Alison; Petrovic, Katja E; Pulkki-Råback, Laura; Quaye, Lydia; Räikkönen, Katri; Rudan, Igor; Scott, Rodney J; Smith, Jennifer A; Sutin, Angelina R; Trzaskowski, Maciej; Vinkhuyzen, Anna E; Yu, Lei; Zabaneh, Delilah; Attia, John R; Bennett, David A; Berger, Klaus; Bertram, Lars; Boomsma, Dorret I; Snieder, Harold; Chang, Shun-Chiao; Cucca, Francesco; Deary, Ian J; van Duijn, Cornelia M; Eriksson, Johan G; Bültmann, Ute; de Geus, Eco J C; Groenen, Patrick J F; Gudnason, Vilmundur; Hansen, Torben; Hartman, Catharine A; Haworth, Claire M A; Hayward, Caroline; Heath, Andrew C; Hinds, David A; Hyppönen, Elina; Iacono, William G; Järvelin, Marjo-Riitta; Jöckel, Karl-Heinz; Kaprio, Jaakko; Kardia, Sharon L R; Keltikangas-Järvinen, Liisa; Kraft, Peter; Kubzansky, Laura D; Lehtimäki, Terho; Magnusson, Patrik K E; Martin, Nicholas G; McGue, Matt; Metspalu, Andres; Mills, Melinda; de Mutsert, Renée; Oldehinkel, Albertine J; Pasterkamp, Gerard; Pedersen, Nancy L; Plomin, Robert; Polasek, Ozren; Power, Christine; Rich, Stephen S; Rosendaal, Frits R; den Ruijter, Hester M; Schlessinger, David; Schmidt, Helena; Svento, Rauli; Schmidt, Reinhold; Alizadeh, Behrooz Z; Sørensen, Thorkild I A; Spector, Tim D; Starr, John M; Stefansson, Kari; Steptoe, Andrew; Terracciano, Antonio; Thorsteinsdottir, Unnur; Thurik, A Roy; Timpson, Nicholas J; Tiemeier, Henning; Uitterlinden, André G; Vollenweider, Peter; Wagner, Gert G; Weir, David R; Yang, Jian; Conley, Dalton C; Smith, George Davey; Hofman, Albert; Johannesson, Magnus; Laibson, David I; Medland, Sarah E; Meyer, Michelle N; Pickrell, Joseph K; Esko, Tõnu; Krueger, Robert F; Beauchamp, Jonathan P; Koellinger, Philipp D; Benjamin, Daniel J; Bartels, Meike; Cesarini, David

    2016-01-01

    We conducted genome-wide association studies of three phenotypes: subjective well-being (N = 298,420), depressive symptoms (N = 161,460), and neuroticism (N = 170,910). We identified three variants associated with subjective well-being, two with depressive symptoms, and eleven with neuroticism, including two inversion polymorphisms. The two depressive symptoms loci replicate in an independent depression sample. Joint analyses that exploit the high genetic correlations between the phenotypes (|ρ^| ≈ 0.8) strengthen the overall credibility of the findings, and allow us to identify additional variants. Across our phenotypes, loci regulating expression in central nervous system and adrenal/pancreas tissues are strongly enriched for association. PMID:27089181

  11. Statistical analyses of scatterplots to identify important factors in large-scale simulations, 2: robustness of techniques

    International Nuclear Information System (INIS)

    Kleijnen, J.P.C.; Helton, J.C.

    1999-01-01

    The robustness of procedures for identifying patterns in scatterplots generated in Monte Carlo sensitivity analyses is investigated. These procedures are based on attempts to detect increasingly complex patterns in the scatterplots under consideration and involve the identification of (i) linear relationships with correlation coefficients, (ii) monotonic relationships with rank correlation coefficients, (iii) trends in central tendency as defined by means, medians and the Kruskal-Wallis statistic, (iv) trends in variability as defined by variances and interquartile ranges, and (v) deviations from randomness as defined by the chi-square statistic. The following two topics related to the robustness of these procedures are considered for a sequence of example analyses with a large model for two-phase fluid flow: the presence of Type I and Type II errors, and the stability of results obtained with independent Latin hypercube samples. Observations from analysis include: (i) Type I errors are unavoidable, (ii) Type II errors can occur when inappropriate analysis procedures are used, (iii) physical explanations should always be sought for why statistical procedures identify variables as being important, and (iv) the identification of important variables tends to be stable for independent Latin hypercube samples

  12. Addressable droplet microarrays for single cell protein analysis.

    Science.gov (United States)

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

    2014-11-07

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

  13. Global metabolic analyses identify key differences in metabolite levels between polymyxin-susceptible and polymyxin-resistant Acinetobacter baumannii.

    Science.gov (United States)

    Maifiah, Mohd Hafidz Mahamad; Cheah, Soon-Ee; Johnson, Matthew D; Han, Mei-Ling; Boyce, John D; Thamlikitkul, Visanu; Forrest, Alan; Kaye, Keith S; Hertzog, Paul; Purcell, Anthony W; Song, Jiangning; Velkov, Tony; Creek, Darren J; Li, Jian

    2016-02-29

    Multidrug-resistant Acinetobacter baumannii presents a global medical crisis and polymyxins are used as the last-line therapy. This study aimed to identify metabolic differences between polymyxin-susceptible and polymyxin-resistant A. baumannii using untargeted metabolomics. The metabolome of each A. baumannii strain was measured using liquid chromatography-mass spectrometry. Multivariate and univariate statistics and pathway analyses were employed to elucidate metabolic differences between the polymyxin-susceptible and -resistant A. baumannii strains. Significant differences were identified between the metabolic profiles of the polymyxin-susceptible and -resistant A. baumannii strains. The lipopolysaccharide (LPS) deficient, polymyxin-resistant 19606R showed perturbation in specific amino acid and carbohydrate metabolites, particularly pentose phosphate pathway (PPP) and tricarboxylic acid (TCA) cycle intermediates. Levels of nucleotides were lower in the LPS-deficient 19606R. Furthermore, 19606R exhibited a shift in its glycerophospholipid profile towards increased abundance of short-chain lipids compared to the parent polymyxin-susceptible ATCC 19606. In contrast, in a pair of clinical isolates 03-149.1 (polymyxin-susceptible) and 03-149.2 (polymyxin-resistant, due to modification of lipid A), minor metabolic differences were identified. Notably, peptidoglycan biosynthesis metabolites were significantly depleted in both of the aforementioned polymyxin-resistant strains. This is the first comparative untargeted metabolomics study to show substantial differences in the metabolic profiles of the polymyxin-susceptible and -resistant A. baumannii.

  14. Using multivariate analyses and GIS to identify pollutants and their spatial patterns in urban soils in Galway, Ireland

    International Nuclear Information System (INIS)

    Zhang Chaosheng

    2006-01-01

    Galway is a small but rapidly growing tourism city in western Ireland. To evaluate its environmental quality, a total of 166 surface soil samples (0-10 cm depth) were collected from parks and grasslands at the density of 1 sample per 0.25 km 2 at the end of 2004. All samples were analysed using ICP-AES for the near-total concentrations of 26 chemical elements. Multivariate statistics and GIS techniques were applied to classify the elements and to identify elements influenced by human activities. Cluster analysis (Canada) and principal component analysis (PCA) classified the elements into two groups: the first group predominantly derived from natural sources, the second being influenced by human activities. GIS mapping is a powerful tool in identifying the possible sources of pollutants. Relatively high concentrations of Cu, Pb and Zn were found in the city centre, old residential areas, and along major traffic routes, showing significant effects of traffic pollution. The element As is enriched in soils of the old built-up areas, which can be attributed to coal and peat combustion for home heating. Such significant spatial patterns of pollutants displayed by urban soils may imply potential health threat to residents of the contaminated areas of the city. - Multivariate statistics and GIS are useful tools to identify pollutants in urban soils

  15. Genome-wide linkage, exome sequencing and functional analyses identify ABCB6 as the pathogenic gene of dyschromatosis universalis hereditaria.

    Directory of Open Access Journals (Sweden)

    Hong Liu

    Full Text Available As a genetic disorder of abnormal pigmentation, the molecular basis of dyschromatosis universalis hereditaria (DUH had remained unclear until recently when ABCB6 was reported as a causative gene of DUH.We performed genome-wide linkage scan using Illumina Human 660W-Quad BeadChip and exome sequencing analyses using Agilent SureSelect Human All Exon Kits in a multiplex Chinese DUH family to identify the pathogenic mutations and verified the candidate mutations using Sanger sequencing. Quantitative RT-PCR and Immunohistochemistry was performed to verify the expression of the pathogenic gene, Zebrafish was also used to confirm the functional role of ABCB6 in melanocytes and pigmentation.Genome-wide linkage (assuming autosomal dominant inheritance mode and exome sequencing analyses identified ABCB6 as the disease candidate gene by discovering a coding mutation (c.1358C>T; p.Ala453Val that co-segregates with the disease phenotype. Further mutation analysis of ABCB6 in four other DUH families and two sporadic cases by Sanger sequencing confirmed the mutation (c.1358C>T; p.Ala453Val and discovered a second, co-segregating coding mutation (c.964A>C; p.Ser322Lys in one of the four families. Both mutations were heterozygous in DUH patients and not present in the 1000 Genome Project and dbSNP database as well as 1,516 unrelated Chinese healthy controls. Expression analysis in human skin and mutagenesis interrogation in zebrafish confirmed the functional role of ABCB6 in melanocytes and pigmentation. Given the involvement of ABCB6 mutations in coloboma, we performed ophthalmological examination of the DUH carriers of ABCB6 mutations and found ocular abnormalities in them.Our study has advanced our understanding of DUH pathogenesis and revealed the shared pathological mechanism between pigmentary DUH and ocular coloboma.

  16. DNA microarray technique for detecting food-borne pathogens

    Directory of Open Access Journals (Sweden)

    Xing GAO

    2012-08-01

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

  17. The Importance of Normalization on Large and Heterogeneous Microarray Datasets

    Science.gov (United States)

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

  18. Novel Protein Microarray Technology to Examine Men with Prostate Cancer

    National Research Council Canada - National Science Library

    Lilja, Hans

    2005-01-01

    The authors developed a novel macro and nanoporous silicon surface for protein microarrays to facilitate high-throughput biomarker discovery, and high-density protein-chip array analyses of complex biological samples...

  19. Discovering biological progression underlying microarray samples.

    Directory of Open Access Journals (Sweden)

    Peng Qiu

    2011-04-01

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

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

    International Nuclear Information System (INIS)

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

    2008-01-01

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

  1. Evaluation of bentonite alteration due to interactions with iron. Sensitivity analyses to identify the important factors for the bentonite alteration

    International Nuclear Information System (INIS)

    Sasamoto, Hiroshi; Wilson, James; Sato, Tsutomu

    2013-01-01

    Performance assessment of geological disposal systems for high-level radioactive waste requires a consideration of long-term systems behaviour. It is possible that the alteration of swelling clay present in bentonite buffers might have an impact on buffer functions. In the present study, iron (as a candidate overpack material)-bentonite (I-B) interactions were evaluated as the main buffer alteration scenario. Existing knowledge on alteration of bentonite during I-B interactions was first reviewed, then the evaluation methodology was developed considering modeling techniques previously used overseas. A conceptual model for smectite alteration during I-B interactions was produced. The following reactions and processes were selected: 1) release of Fe 2+ due to overpack corrosion; 2) diffusion of Fe 2+ in compacted bentonite; 3) sorption of Fe 2+ on smectite edge and ion exchange in interlayers; 4) dissolution of primary phases and formation of alteration products. Sensitivity analyses were performed to identify the most important factors for the alteration of bentonite by I-B interactions. (author)

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

    Directory of Open Access Journals (Sweden)

    Sterry Wolfram

    2006-08-01

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

  3. Shared probe design and existing microarray reanalysis using PICKY

    Directory of Open Access Journals (Sweden)

    Chou Hui-Hsien

    2010-04-01

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

  4. The use of microarrays in microbial ecology

    Energy Technology Data Exchange (ETDEWEB)

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

    2009-09-15

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

  5. Genome-Wide Association Analyses in 128,266 Individuals Identifies New Morningness and Sleep Duration Loci.

    Directory of Open Access Journals (Sweden)

    Samuel E Jones

    2016-08-01

    Full Text Available Disrupted circadian rhythms and reduced sleep duration are associated with several human diseases, particularly obesity and type 2 diabetes, but until recently, little was known about the genetic factors influencing these heritable traits. We performed genome-wide association studies of self-reported chronotype (morning/evening person and self-reported sleep duration in 128,266 white British individuals from the UK Biobank study. Sixteen variants were associated with chronotype (P<5x10-8, including variants near the known circadian rhythm genes RGS16 (1.21 odds of morningness, 95% CI [1.15, 1.27], P = 3x10-12 and PER2 (1.09 odds of morningness, 95% CI [1.06, 1.12], P = 4x10-10. The PER2 signal has previously been associated with iris function. We sought replication using self-reported data from 89,283 23andMe participants; thirteen of the chronotype signals remained associated at P<5x10-8 on meta-analysis and eleven of these reached P<0.05 in the same direction in the 23andMe study. We also replicated 9 additional variants identified when the 23andMe study was used as a discovery GWAS of chronotype (all P<0.05 and meta-analysis P<5x10-8. For sleep duration, we replicated one known signal in PAX8 (2.6 minutes per allele, 95% CI [1.9, 3.2], P = 5.7x10-16 and identified and replicated two novel associations at VRK2 (2.0 minutes per allele, 95% CI [1.3, 2.7], P = 1.2x10-9; and 1.6 minutes per allele, 95% CI [1.1, 2.2], P = 7.6x10-9. Although we found genetic correlation between chronotype and BMI (rG = 0.056, P = 0.05; undersleeping and BMI (rG = 0.147, P = 1x10-5 and oversleeping and BMI (rG = 0.097, P = 0.04, Mendelian Randomisation analyses, with limited power, provided no consistent evidence of causal associations between BMI or type 2 diabetes and chronotype or sleep duration. Our study brings the total number of loci associated with chronotype to 22 and with sleep duration to three, and provides new insights into the biology of sleep and

  6. Molecular and functional analyses of a maize autoactive NB-LRR protein identify precise structural requirements for activity.

    Directory of Open Access Journals (Sweden)

    Guan-Feng Wang

    2015-02-01

    Full Text Available Plant disease resistance is often mediated by nucleotide binding-leucine rich repeat (NLR proteins which remain auto-inhibited until recognition of specific pathogen-derived molecules causes their activation, triggering a rapid, localized cell death called a hypersensitive response (HR. Three domains are recognized in one of the major classes of NLR proteins: a coiled-coil (CC, a nucleotide binding (NB-ARC and a leucine rich repeat (LRR domains. The maize NLR gene Rp1-D21 derives from an intergenic recombination event between two NLR genes, Rp1-D and Rp1-dp2 and confers an autoactive HR. We report systematic structural and functional analyses of Rp1 proteins in maize and N. benthamiana to characterize the molecular mechanism of NLR activation/auto-inhibition. We derive a model comprising the following three main features: Rp1 proteins appear to self-associate to become competent for activity. The CC domain is signaling-competent and is sufficient to induce HR. This can be suppressed by the NB-ARC domain through direct interaction. In autoactive proteins, the interaction of the LRR domain with the NB-ARC domain causes de-repression and thus disrupts the inhibition of HR. Further, we identify specific amino acids and combinations thereof that are important for the auto-inhibition/activity of Rp1 proteins. We also provide evidence for the function of MHD2, a previously uncharacterized, though widely conserved NLR motif. This work reports several novel insights into the precise structural requirement for NLR function and informs efforts towards utilizing these proteins for engineering disease resistance.

  7. Molecular and functional analyses of a maize autoactive NB-LRR protein identify precise structural requirements for activity.

    Science.gov (United States)

    Wang, Guan-Feng; Ji, Jiabing; El-Kasmi, Farid; Dangl, Jeffery L; Johal, Guri; Balint-Kurti, Peter J

    2015-02-01

    Plant disease resistance is often mediated by nucleotide binding-leucine rich repeat (NLR) proteins which remain auto-inhibited until recognition of specific pathogen-derived molecules causes their activation, triggering a rapid, localized cell death called a hypersensitive response (HR). Three domains are recognized in one of the major classes of NLR proteins: a coiled-coil (CC), a nucleotide binding (NB-ARC) and a leucine rich repeat (LRR) domains. The maize NLR gene Rp1-D21 derives from an intergenic recombination event between two NLR genes, Rp1-D and Rp1-dp2 and confers an autoactive HR. We report systematic structural and functional analyses of Rp1 proteins in maize and N. benthamiana to characterize the molecular mechanism of NLR activation/auto-inhibition. We derive a model comprising the following three main features: Rp1 proteins appear to self-associate to become competent for activity. The CC domain is signaling-competent and is sufficient to induce HR. This can be suppressed by the NB-ARC domain through direct interaction. In autoactive proteins, the interaction of the LRR domain with the NB-ARC domain causes de-repression and thus disrupts the inhibition of HR. Further, we identify specific amino acids and combinations thereof that are important for the auto-inhibition/activity of Rp1 proteins. We also provide evidence for the function of MHD2, a previously uncharacterized, though widely conserved NLR motif. This work reports several novel insights into the precise structural requirement for NLR function and informs efforts towards utilizing these proteins for engineering disease resistance.

  8. New markers of pancreatic cancer identified through differential gene expression analyses: claudin 18 and annexin A8.

    Science.gov (United States)

    Karanjawala, Zarir E; Illei, Peter B; Ashfaq, Raheela; Infante, Jeffrey R; Murphy, Kathleen; Pandey, Akhilesh; Schulick, Richard; Winter, Jordan; Sharma, Rajni; Maitra, Anirban; Goggins, Michael; Hruban, Ralph H

    2008-02-01

    New markers to distinguish benign reactive glands from infiltrating ductal adenocarcinoma of the pancreas are needed. The gene expression patterns of 24 surgically resected primary infiltrating ductal adenocarcinomas of the pancreas were compared with 18 non-neoplastic samples using the Affymetrix U133 Plus 2.0 Arrays and the Gene Logic GeneExpress Software System. Gene fragments from 4 genes (annexin A8, claudin 18, CXCL5, and S100 A2) were selected from the fragments found to be highly expressed in infiltrating adenocarcinomas when compared with normal tissues. The protein expression of these genes was examined using immunohistochemical labeling of tissue microarrays. Claudin 18 labeled infiltrating carcinomas in a membranous pattern. When compared with normal and reactive ducts, claudin 18 was overexpressed, at least focally, in 159 of 166 evaluable carcinomas (96%). Strong and diffuse claudin 18 overexpression was most often seen in well-differentiated carcinomas (P=0.02). Claudin 18 was overexpressed in 51 of 52 cases (98%) of pancreatic intraepithelial neoplasia. Annexin A8 was at least focally overexpressed in 149 of 154 evaluable infiltrating carcinomas (97%). S100 A2 was at least focally overexpressed in 118 of 154 evaluable infiltrating carcinomas (77%). Non-neoplastic glands also frequently expressed S100 A2 diminishing its potential diagnostic utility. Immunolabeling with antibodies directed against CXCL5 did not reveal any significant differences in protein expression between infiltrating adenocarcinomas and normal pancreatic ducts. Claudin 18 and annexin A8 are frequently highly overexpressed in infiltrating ductal adenocarcinomas when compared with normal reactive ducts, suggesting a role for these molecules in pancreatic ductal adenocarcinomas. Furthermore, these may serve as diagnostic markers, as screening tests and as therapeutic targets.

  9. Identifying the Research Process to Analyse the Adoption of the International Baccalaureate's Diploma Programme in England

    Science.gov (United States)

    Outhwaite, Deborah

    2018-01-01

    This article analyses the flow-line around the methodology used inside an educational research process that was originally established to examine the expansion of the International Baccalaureate's Diploma Programme (IBDP) in England. This article analyses the research question, then assesses the research focus, aims and objectives. The article…

  10. Elimination of heparin interference during microarray processing of fresh and biobank-archived blood samples.

    Science.gov (United States)

    Hebels, Dennie G A J; van Herwijnen, Marcel H M; Brauers, Karen J J; de Kok, Theo M C M; Chalkiadaki, Georgia; Kyrtopoulos, Soterios A; Kleinjans, Jos C S

    2014-07-01

    In the context of environmental health research, biobank blood samples have recently been identified as suitable for high-throughput omics analyses enabling the identification of new biomarkers of exposure and disease. However, blood samples containing the anti-coagulant heparin could complicate transcriptomic analysis because heparin may inhibit RNA polymerase causing inefficient cRNA synthesis and fluorophore labelling. We investigated the inhibitory effect of heparin and the influence of storage conditions (0 or 3 hr bench times, storage at room temperature or -80°C) on fluorophore labelling in heparinized fresh human buffy coat and whole blood biobank samples during the mRNA work-up protocol for microarray analysis. Subsequently, we removed heparin by lithium chloride (LiCl) treatment and performed a quality control analysis of LiCl-treated biobank sample microarrays to prove their suitability for downstream data analysis. Both fresh and biobank samples experienced varying degrees of heparin-induced inhibition of fluorophore labelling, making most samples unusable for microarray analysis. RNA derived from EDTA and citrate blood was not inhibited. No effect of bench time was observed but room temperature storage gave slightly better results. Strong correlations were observed between original blood sample RNA yield and the amount of synthesized cRNA. LiCl treatment restored sample quality to normal standards in both fresh and biobank samples and the previously identified correlations disappeared. Microarrays hybridized with LiCl-treated biobank samples were of excellent quality with no identifiable influence of heparin. We conclude that, to obtain high quality results, in most cases heparin removal is essential in blood-derived RNA samples intended for microarray analysis. Copyright © 2014 Wiley Periodicals, Inc.

  11. Fast gene ontology based clustering for microarray experiments.

    Science.gov (United States)

    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.

  12. Genome-wide meta-analyses of multiancestry cohorts identify multiple new susceptibility loci for refractive error and myopia

    NARCIS (Netherlands)

    Verhoeven, Virginie J. M.; Hysi, Pirro G.; Wojciechowski, Robert; Fan, Qiao; Guggenheim, Jeremy A.; Höhn, René; Macgregor, Stuart; Hewitt, Alex W.; Nag, Abhishek; Cheng, Ching-Yu; Yonova-Doing, Ekaterina; Zhou, Xin; Ikram, M. Kamran; Buitendijk, Gabriëlle H. S.; McMahon, George; Kemp, John P.; Pourcain, Beate St; Simpson, Claire L.; Mäkelä, Kari-Matti; Lehtimäki, Terho; Kähönen, Mika; Paterson, Andrew D.; Hosseini, S. Mohsen; Wong, Hoi Suen; Xu, Liang; Jonas, Jost B.; Pärssinen, Olavi; Wedenoja, Juho; Yip, Shea Ping; Ho, Daniel W. H.; Pang, Chi Pui; Chen, Li Jia; Burdon, Kathryn P.; Craig, Jamie E.; Klein, Barbara E. K.; Klein, Ronald; Haller, Toomas; Metspalu, Andres; Khor, Chiea-Chuen; Tai, E.-Shyong; Aung, Tin; Vithana, Eranga; Tay, Wan-Ting; Barathi, Veluchamy A.; Chen, Peng; Li, Ruoying; Liao, Jiemin; Zheng, Yingfeng; Bergen, Arthur A. B.; Chen, Wei

    2013-01-01

    Refractive error is the most common eye disorder worldwide and is a prominent cause of blindness. Myopia affects over 30% of Western populations and up to 80% of Asians. The CREAM consortium conducted genome-wide meta-analyses, including 37,382 individuals from 27 studies of European ancestry and

  13. Large-scale association analyses identify new loci influencing glycemic traits and provide insight into the underlying biological pathways

    DEFF Research Database (Denmark)

    Scott, Robert A; Lagou, Vasiliki; Welch, Ryan P

    2012-01-01

    Through genome-wide association meta-analyses of up to 133,010 individuals of European ancestry without diabetes, including individuals newly genotyped using the Metabochip, we have increased the number of confirmed loci influencing glycemic traits to 53, of which 33 also increase type 2 diabetes...

  14. Large-scale association analyses identify new loci influencing glycemic traits and provide insight into the underlying biological pathways

    NARCIS (Netherlands)

    Scott, Robert A.; Lagou, Vasiliki; Welch, Ryan P.; Wheeler, Eleanor; Montasser, May E.; Luan, Jian'an; Mägi, Reedik; Strawbridge, Rona J.; Rehnberg, Emil; Gustafsson, Stefan; Kanoni, Stavroula; Rasmussen-Torvik, Laura J.; Yengo, Loïc; Lecoeur, Cecile; Shungin, Dmitry; Sanna, Serena; Sidore, Carlo; Johnson, Paul C. D.; Jukema, J. Wouter; Johnson, Toby; Mahajan, Anubha; Verweij, Niek; Thorleifsson, Gudmar; Hottenga, Jouke-Jan; Shah, Sonia; Smith, Albert V.; Sennblad, Bengt; Gieger, Christian; Salo, Perttu; Perola, Markus; Timpson, Nicholas J.; Evans, David M.; Pourcain, Beate St; Wu, Ying; Andrews, Jeanette S.; Hui, Jennie; Bielak, Lawrence F.; Zhao, Wei; Horikoshi, Momoko; Navarro, Pau; Isaacs, Aaron; O'Connell, Jeffrey R.; Stirrups, Kathleen; Vitart, Veronique; Hayward, Caroline; Esko, Tõnu; Mihailov, Evelin; Fraser, Ross M.; Fall, Tove; Voight, Benjamin F.; Raychaudhuri, Soumya; Chen, Han; Lindgren, Cecilia M.; Morris, Andrew P.; Rayner, Nigel W.; Robertson, Neil; Rybin, Denis; Liu, Ching-Ti; Beckmann, Jacques S.; Willems, Sara M.; Chines, Peter S.; Jackson, Anne U.; Kang, Hyun Min; Stringham, Heather M.; Song, Kijoung; Tanaka, Toshiko; Peden, John F.; Goel, Anuj; Hicks, Andrew A.; An, Ping; Müller-Nurasyid, Martina; Franco-Cereceda, Anders; Folkersen, Lasse; Marullo, Letizia; Jansen, Hanneke; Oldehinkel, Albertine J.; Bruinenberg, Marcel; Pankow, James S.; North, Kari E.; Forouhi, Nita G.; Loos, Ruth J. F.; Edkins, Sarah; Varga, Tibor V.; Hallmans, Göran; Oksa, Heikki; Antonella, Mulas; Nagaraja, Ramaiah; Trompet, Stella; Ford, Ian; Bakker, Stephan J. L.; Kong, Augustine; Kumari, Meena; Gigante, Bruna; Herder, Christian; Munroe, Patricia B.; Caulfield, Mark; Antti, Jula; Mangino, Massimo; Small, Kerrin; Miljkovic, Iva; Liu, Yongmei; Atalay, Mustafa; Kiess, Wieland; James, Alan L.; Rivadeneira, Fernando; Uitterlinden, Andre G.; Palmer, Colin N. A.; Doney, Alex S. F.; Willemsen, Gonneke; Smit, Johannes H.; Campbell, Susan; Polasek, Ozren; Bonnycastle, Lori L.; Hercberg, Serge; Dimitriou, Maria; Bolton, Jennifer L.; Fowkes, Gerard R.; Kovacs, Peter; Lindström, Jaana; Zemunik, Tatijana; Bandinelli, Stefania; Wild, Sarah H.; Basart, Hanneke V.; Rathmann, Wolfgang; Grallert, Harald; Maerz, Winfried; Kleber, Marcus E.; Boehm, Bernhard O.; Peters, Annette; Pramstaller, Peter P.; Province, Michael A.; Borecki, Ingrid B.; Hastie, Nicholas D.; Rudan, Igor; Campbell, Harry; Watkins, Hugh; Farrall, Martin; Stumvoll, Michael; Ferrucci, Luigi; Waterworth, Dawn M.; Bergman, Richard N.; Collins, Francis S.; Tuomilehto, Jaakko; Watanabe, Richard M.; de Geus, Eco J. C.; Penninx, Brenda W.; Hofman, Albert; Oostra, Ben A.; Psaty, Bruce M.; Vollenweider, Peter; Wilson, James F.; Wright, Alan F.; Hovingh, G. Kees; Metspalu, Andres; Uusitupa, Matti; Magnusson, Patrik K. E.; Kyvik, Kirsten O.; Kaprio, Jaakko; Price, Jackie F.; Dedoussis, George V.; Deloukas, Panos; Meneton, Pierre; Lind, Lars; Boehnke, Michael; Shuldiner, Alan R.; van Duijn, Cornelia M.; Morris, Andrew D.; Toenjes, Anke; Peyser, Patricia A.; Beilby, John P.; Körner, Antje; Kuusisto, Johanna; Laakso, Markku; Bornstein, Stefan R.; Schwarz, Peter E. H.; Lakka, Timo A.; Rauramaa, Rainer; Adair, Linda S.; Smith, George Davey; Spector, Tim D.; Illig, Thomas; de Faire, Ulf; Hamsten, Anders; Gudnason, Vilmundur; Kivimaki, Mika; Hingorani, Aroon; Keinanen-Kiukaanniemi, Sirkka M.; Saaristo, Timo E.; Boomsma, Dorret I.; Stefansson, Kari; van der Harst, Pim; Dupuis, Josée; Pedersen, Nancy L.; Sattar, Naveed; Harris, Tamara B.; Cucca, Francesco; Ripatti, Samuli; Salomaa, Veikko; Mohlke, Karen L.; Balkau, Beverley; Froguel, Philippe; Pouta, Anneli; Jarvelin, Marjo-Riitta; Wareham, Nicholas J.; Bouatia-Naji, Nabila; McCarthy, Mark I.; Franks, Paul W.; Meigs, James B.; Teslovich, Tanya M.; Florez, Jose C.; Langenberg, Claudia; Ingelsson, Erik; Prokopenko, Inga; Barroso, Inês

    2012-01-01

    Through genome-wide association meta-analyses of up to 133,010 individuals of European ancestry without diabetes, including individuals newly genotyped using the Metabochip, we have increased the number of confirmed loci influencing glycemic traits to 53, of which 33 also increase type 2 diabetes

  15. Significance of functional disease-causal/susceptible variants identified by whole-genome analyses for the understanding of human diseases.

    Science.gov (United States)

    Hitomi, Yuki; Tokunaga, Katsushi

    2017-01-01

    Human genome variation may cause differences in traits and disease risks. Disease-causal/susceptible genes and variants for both common and rare diseases can be detected by comprehensive whole-genome analyses, such as whole-genome sequencing (WGS), using next-generation sequencing (NGS) technology and genome-wide association studies (GWAS). Here, in addition to the application of an NGS as a whole-genome analysis method, we summarize approaches for the identification of functional disease-causal/susceptible variants from abundant genetic variants in the human genome and methods for evaluating their functional effects in human diseases, using an NGS and in silico and in vitro functional analyses. We also discuss the clinical applications of the functional disease causal/susceptible variants to personalized medicine.

  16. Facilitating functional annotation of chicken microarray data

    Directory of Open Access Journals (Sweden)

    Gresham Cathy R

    2009-10-01

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

  17. DNA microarrays : a molecular cloning manual

    National Research Council Canada - National Science Library

    Sambrook, Joseph; Bowtell, David

    2002-01-01

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

  18. Prevalence of mutations and functional analyses of melanocortin 4 receptor variants identified among 750 men with juvenile-onset obesity

    DEFF Research Database (Denmark)

    Larsen, Lesli H; Echwald, Søren Morgenthaler; Sørensen, Thorkild I A

    2005-01-01

    )) for mutations in MC4R. A total of 14 different mutations were identified of which two, Ala219Val and Leu325Phe, were novel variants. The variant receptor, Leu325Phe, was unable to bind [Nle4,d-Phe7]-alphaMSH, whereas the Ala219Val variant showed a significantly impaired melanotan II induction of cAMP, compared...

  19. Root Cause Analyses of Suicides of Mental Health Clients: Identifying Systematic Processes and Service-Level Prevention Strategies.

    Science.gov (United States)

    Gillies, Donna; Chicop, David; O'Halloran, Paul

    2015-01-01

    The ability to predict imminent risk of suicide is limited, particularly among mental health clients. Root cause analysis (RCA) can be used by health services to identify service-wide approaches to suicide prevention. To (a) develop a standardized taxonomy for RCAs; (b) to quantitate service-related factors associated with suicides; and (c) to identify service-related suicide prevention strategies. The RCAs of all people who died by suicide within 1 week of contact with the mental health service over 5 years were thematically analyzed using a data collection tool. Data were derived from RCAs of all 64 people who died by suicide between 2008 and 2012. Major themes were categorized as individual, situational, and care-related factors. The most common factor was that clients had recently denied suicidality. Reliance on carers, recent changes in medication, communication problems, and problems in follow-through were also commonly identified. Given the difficulty in predicting suicide in people whose expressions of suicidal ideation change so rapidly, services may consider the use of strategies aimed at improving the individual, stressor, support, and care factors identified in this study.

  20. Identifying consumer segments in health services markets: an application of conjoint and cluster analyses to the ambulatory care pharmacy market.

    Science.gov (United States)

    Carrol, N V; Gagon, J P

    1983-01-01

    Because of increasing competition, it is becoming more important that health care providers pursue consumer-based market segmentation strategies. This paper presents a methodology for identifying and describing consumer segments in health service markets, and demonstrates the use of the methodology by presenting a study of consumer segments in the ambulatory care pharmacy market.

  1. High-resolution linkage analyses to identify genes that influence Varroa sensitive hygiene behavior in honey bees.

    Science.gov (United States)

    Tsuruda, Jennifer M; Harris, Jeffrey W; Bourgeois, Lanie; Danka, Robert G; Hunt, Greg J

    2012-01-01

    Varroa mites (V. destructor) are a major threat to honey bees (Apis melilfera) and beekeeping worldwide and likely lead to colony decline if colonies are not treated. Most treatments involve chemical control of the mites; however, Varroa has evolved resistance to many of these miticides, leaving beekeepers with a limited number of alternatives. A non-chemical control method is highly desirable for numerous reasons including lack of chemical residues and decreased likelihood of resistance. Varroa sensitive hygiene behavior is one of two behaviors identified that are most important for controlling the growth of Varroa populations in bee hives. To identify genes influencing this trait, a study was conducted to map quantitative trait loci (QTL). Individual workers of a backcross family were observed and evaluated for their VSH behavior in a mite-infested observation hive. Bees that uncapped or removed pupae were identified. The genotypes for 1,340 informative single nucleotide polymorphisms were used to construct a high-resolution genetic map and interval mapping was used to analyze the association of the genotypes with the performance of Varroa sensitive hygiene. We identified one major QTL on chromosome 9 (LOD score = 3.21) and a suggestive QTL on chromosome 1 (LOD = 1.95). The QTL confidence interval on chromosome 9 contains the gene 'no receptor potential A' and a dopamine receptor. 'No receptor potential A' is involved in vision and olfaction in Drosophila, and dopamine signaling has been previously shown to be required for aversive olfactory learning in honey bees, which is probably necessary for identifying mites within brood cells. Further studies on these candidate genes may allow for breeding bees with this trait using marker-assisted selection.

  2. High-resolution linkage analyses to identify genes that influence Varroa sensitive hygiene behavior in honey bees.

    Directory of Open Access Journals (Sweden)

    Jennifer M Tsuruda

    Full Text Available Varroa mites (V. destructor are a major threat to honey bees (Apis melilfera and beekeeping worldwide and likely lead to colony decline if colonies are not treated. Most treatments involve chemical control of the mites; however, Varroa has evolved resistance to many of these miticides, leaving beekeepers with a limited number of alternatives. A non-chemical control method is highly desirable for numerous reasons including lack of chemical residues and decreased likelihood of resistance. Varroa sensitive hygiene behavior is one of two behaviors identified that are most important for controlling the growth of Varroa populations in bee hives. To identify genes influencing this trait, a study was conducted to map quantitative trait loci (QTL. Individual workers of a backcross family were observed and evaluated for their VSH behavior in a mite-infested observation hive. Bees that uncapped or removed pupae were identified. The genotypes for 1,340 informative single nucleotide polymorphisms were used to construct a high-resolution genetic map and interval mapping was used to analyze the association of the genotypes with the performance of Varroa sensitive hygiene. We identified one major QTL on chromosome 9 (LOD score = 3.21 and a suggestive QTL on chromosome 1 (LOD = 1.95. The QTL confidence interval on chromosome 9 contains the gene 'no receptor potential A' and a dopamine receptor. 'No receptor potential A' is involved in vision and olfaction in Drosophila, and dopamine signaling has been previously shown to be required for aversive olfactory learning in honey bees, which is probably necessary for identifying mites within brood cells. Further studies on these candidate genes may allow for breeding bees with this trait using marker-assisted selection.

  3. Genetic variants associated with subjective well-being, depressive symptoms, and neuroticism identified through genome-wide analyses

    OpenAIRE

    Okbay, Aysu; Baselmans, B.M.L. (Bart M.L.); Neve, Jan-Emmanuel; Turley, Patrick; Nivard, Michel; Fontana, M.A. (Mark Alan); Meddens, S.F.W. (S. Fleur W.); Linnér, R.K. (Richard Karlsson); Rietveld, C.A. (Cornelius A); Derringer, J.; Gratten, Jacob; Lee, James J.; Liu, J.Z. (Jimmy Z); Vlaming, Ronald; SAhluwalia, T. (Tarunveer)

    2016-01-01

    textabstractVery few genetic variants have been associated with depression and neuroticism, likely because of limitations on sample size in previous studies. Subjective well-being, a phenotype that is genetically correlated with both of these traits, has not yet been studied with genome-wide data. We conducted genome-wide association studies of three phenotypes: subjective well-being (n = 298,420), depressive symptoms (n = 161,460), and neuroticism (n = 170,911). We identify 3 variants associ...

  4. Signature of Nonstationarity in Precipitation Extremes over Urbanizing Regions in India Identified through a Multivariate Frequency Analyses

    Science.gov (United States)

    Singh, Jitendra; Hari, Vittal; Sharma, Tarul; Karmakar, Subhankar; Ghosh, Subimal

    2016-04-01

    The statistical assumption of stationarity in hydrologic extreme time/event series has been relied heavily in frequency analysis. However, due to the analytically perceivable impacts of climate change, urbanization and concomitant land use pattern, assumption of stationarity in hydrologic time series will draw erroneous results, which in turn may affect the policy and decision-making. Past studies provided sufficient evidences on changes in the characteristics of Indian monsoon precipitation extremes and further it has been attributed to climate change and urbanization, which shows need of nonstationary analysis on the Indian monsoon extremes. Therefore, a comprehensive multivariate nonstationary frequency analysis has been conducted for the entire India to identify the precipitation characteristics (intensity, duration and depth) responsible for significant nonstationarity in the Indian monsoon. We use 1o resolution of precipitation data for a period of 1901-2004, in a Generalized Additive Model for Location, Scale and Shape (GAMLSS) framework. A cluster of GAMLSS models has been developed by considering nonstationarity in different combinations of distribution parameters through different regression techniques, and the best-fit model is further applied for bivariate analysis. A population density data has been utilized to identify the urban, urbanizing and rural regions. The results showed significant differences in the stationary and nonstationary bivariate return periods for the urbanizing grids, when compared to urbanized and rural grids. A comprehensive multivariate analysis has also been conducted to identify the precipitation characteristics particularly responsible for imprinting signature of nonstationarity.

  5. Genome-Wide Search Identifies 1.9 Mb from the Polar Bear Y Chromosome for Evolutionary Analyses.

    Science.gov (United States)

    Bidon, Tobias; Schreck, Nancy; Hailer, Frank; Nilsson, Maria A; Janke, Axel

    2015-05-27

    The male-inherited Y chromosome is the major haploid fraction of the mammalian genome, rendering Y-linked sequences an indispensable resource for evolutionary research. However, despite recent large-scale genome sequencing approaches, only a handful of Y chromosome sequences have been characterized to date, mainly in model organisms. Using polar bear (Ursus maritimus) genomes, we compare two different in silico approaches to identify Y-linked sequences: 1) Similarity to known Y-linked genes and 2) difference in the average read depth of autosomal versus sex chromosomal scaffolds. Specifically, we mapped available genomic sequencing short reads from a male and a female polar bear against the reference genome and identify 112 Y-chromosomal scaffolds with a combined length of 1.9 Mb. We verified the in silico findings for the longer polar bear scaffolds by male-specific in vitro amplification, demonstrating the reliability of the average read depth approach. The obtained Y chromosome sequences contain protein-coding sequences, single nucleotide polymorphisms, microsatellites, and transposable elements that are useful for evolutionary studies. A high-resolution phylogeny of the polar bear patriline shows two highly divergent Y chromosome lineages, obtained from analysis of the identified Y scaffolds in 12 previously published male polar bear genomes. Moreover, we find evidence of gene conversion among ZFX and ZFY sequences in the giant panda lineage and in the ancestor of ursine and tremarctine bears. Thus, the identification of Y-linked scaffold sequences from unordered genome sequences yields valuable data to infer phylogenomic and population-genomic patterns in bears. © The Author(s) 2015. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution.

  6. Genome-Wide Search Identifies 1.9 Mb from the Polar Bear Y Chromosome for Evolutionary Analyses

    Science.gov (United States)

    Bidon, Tobias; Schreck, Nancy; Hailer, Frank; Nilsson, Maria A.; Janke, Axel

    2015-01-01

    The male-inherited Y chromosome is the major haploid fraction of the mammalian genome, rendering Y-linked sequences an indispensable resource for evolutionary research. However, despite recent large-scale genome sequencing approaches, only a handful of Y chromosome sequences have been characterized to date, mainly in model organisms. Using polar bear (Ursus maritimus) genomes, we compare two different in silico approaches to identify Y-linked sequences: 1) Similarity to known Y-linked genes and 2) difference in the average read depth of autosomal versus sex chromosomal scaffolds. Specifically, we mapped available genomic sequencing short reads from a male and a female polar bear against the reference genome and identify 112 Y-chromosomal scaffolds with a combined length of 1.9 Mb. We verified the in silico findings for the longer polar bear scaffolds by male-specific in vitro amplification, demonstrating the reliability of the average read depth approach. The obtained Y chromosome sequences contain protein-coding sequences, single nucleotide polymorphisms, microsatellites, and transposable elements that are useful for evolutionary studies. A high-resolution phylogeny of the polar bear patriline shows two highly divergent Y chromosome lineages, obtained from analysis of the identified Y scaffolds in 12 previously published male polar bear genomes. Moreover, we find evidence of gene conversion among ZFX and ZFY sequences in the giant panda lineage and in the ancestor of ursine and tremarctine bears. Thus, the identification of Y-linked scaffold sequences from unordered genome sequences yields valuable data to infer phylogenomic and population-genomic patterns in bears. PMID:26019166

  7. RNAseq Analyses Identify Tumor Necrosis Factor-Mediated Inflammation as a Major Abnormality in ALS Spinal Cord.

    Directory of Open Access Journals (Sweden)

    David G Brohawn

    Full Text Available ALS is a rapidly progressive, devastating neurodegenerative illness of adults that produces disabling weakness and spasticity arising from death of lower and upper motor neurons. No meaningful therapies exist to slow ALS progression, and molecular insights into pathogenesis and progression are sorely needed. In that context, we used high-depth, next generation RNA sequencing (RNAseq, Illumina to define gene network abnormalities in RNA samples depleted of rRNA and isolated from cervical spinal cord sections of 7 ALS and 8 CTL samples. We aligned >50 million 2X150 bp paired-end sequences/sample to the hg19 human genome and applied three different algorithms (Cuffdiff2, DEseq2, EdgeR for identification of differentially expressed genes (DEG's. Ingenuity Pathways Analysis (IPA and Weighted Gene Co-expression Network Analysis (WGCNA identified inflammatory processes as significantly elevated in our ALS samples, with tumor necrosis factor (TNF found to be a major pathway regulator (IPA and TNFα-induced protein 2 (TNFAIP2 as a major network "hub" gene (WGCNA. Using the oPOSSUM algorithm, we analyzed transcription factors (TF controlling expression of the nine DEG/hub genes in the ALS samples and identified TF's involved in inflammation (NFkB, REL, NFkB1 and macrophage function (NR1H2::RXRA heterodimer. Transient expression in human iPSC-derived motor neurons of TNFAIP2 (also a DEG identified by all three algorithms reduced cell viability and induced caspase 3/7 activation. Using high-density RNAseq, multiple algorithms for DEG identification, and an unsupervised gene co-expression network approach, we identified significant elevation of inflammatory processes in ALS spinal cord with TNF as a major regulatory molecule. Overexpression of the DEG TNFAIP2 in human motor neurons, the population most vulnerable to die in ALS, increased cell death and caspase 3/7 activation. We propose that therapies targeted to reduce inflammatory TNFα signaling may be

  8. Transcriptome analyses identify five transcription factors differentially expressed in the hypothalamus of post- versus prepubertal Brahman heifers.

    Science.gov (United States)

    Fortes, M R S; Nguyen, L T; Weller, M M D C A; Cánovas, A; Islas-Trejo, A; Porto-Neto, L R; Reverter, A; Lehnert, S A; Boe-Hansen, G B; Thomas, M G; Medrano, J F; Moore, S S

    2016-09-01

    Puberty onset is a developmental process influenced by genetic determinants, environment, and nutrition. Mutations and regulatory gene networks constitute the molecular basis for the genetic determinants of puberty onset. The emerging knowledge of these genetic determinants presents opportunities for innovation in the breeding of early pubertal cattle. This paper presents new data on hypothalamic gene expression related to puberty in (Brahman) in age- and weight-matched heifers. Six postpubertal heifers were compared with 6 prepubertal heifers using whole-genome RNA sequencing methodology for quantification of global gene expression in the hypothalamus. Five transcription factors (TF) with potential regulatory roles in the hypothalamus were identified in this experiment: , , , , and . These TF genes were significantly differentially expressed in the hypothalamus of postpubertal versus prepubertal heifers and were also identified as significant according to the applied regulatory impact factor metric ( cancer and developmental processes. Mutations in were associated with puberty in humans. Mutations in these TF, together with other genetic determinants previously discovered, could be used in genomic selection to predict the genetic merit of cattle (i.e., the likelihood of the offspring presenting earlier than average puberty for Brahman). Knowledge of key mutations involved in genetic traits is an advantage for genomic prediction because it can increase its accuracy.

  9. Mining meiosis and gametogenesis with DNA microarrays.

    Science.gov (United States)

    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.

  10. Facilitating RNA structure prediction with microarrays.

    Science.gov (United States)

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

    2006-01-17

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

  11. Identifying Virulence-Associated Genes Using Transcriptomic and Proteomic Association Analyses of the Plant Parasitic Nematode Bursaphelenchus mucronatus

    Directory of Open Access Journals (Sweden)

    Lifeng Zhou

    2016-09-01

    Full Text Available Bursaphelenchus mucronatus (B. mucronatus isolates that originate from different regions may vary in their virulence, but their virulence-associated genes and proteins are poorly understood. Thus, we conducted an integrated study coupling RNA-Seq and isobaric tags for relative and absolute quantitation (iTRAQ to analyse transcriptomic and proteomic data of highly and weakly virulent B. mucronatus isolates during the pathogenic processes. Approximately 40,000 annotated unigenes and 5000 proteins were gained from the isolates. When we matched all of the proteins with their detected transcripts, a low correlation coefficient of r = 0.138 was found, indicating probable post-transcriptional gene regulation involved in the pathogenic processes. A functional analysis showed that five differentially expressed proteins which were all highly expressed in the highly virulent isolate were involved in the pathogenic processes of nematodes. Peroxiredoxin, fatty acid- and retinol-binding protein, and glutathione peroxidase relate to resistance against plant defence responses, while β-1,4-endoglucanase and expansin are associated with the breakdown of plant cell walls. Thus, the pathogenesis of B. mucronatus depends on its successful survival in host plants. Our work adds to the understanding of B. mucronatus’ pathogenesis, and will aid in controlling B. mucronatus and other pinewood nematode species complexes in the future.

  12. Multivariate Analyses and Classification of Inertial Sensor Data to Identify Aging Effects on the Timed-Up-and-Go Test.

    Directory of Open Access Journals (Sweden)

    Danique Vervoort

    Full Text Available Many tests can crudely quantify age-related mobility decrease but instrumented versions of mobility tests could increase their specificity and sensitivity. The Timed-up-and-Go (TUG test includes several elements that people use in daily life. The test has different transition phases: rise from a chair, walk, 180° turn, walk back, turn, and sit-down on a chair. For this reason the TUG is an often used test to evaluate in a standardized way possible decline in balance and walking ability due to age and or pathology. Using inertial sensors, qualitative information about the performance of the sub-phases can provide more specific information about a decline in balance and walking ability. The first aim of our study was to identify variables extracted from the instrumented timed-up-and-go (iTUG that most effectively distinguished performance differences across age (age 18-75. Second, we determined the discriminative ability of those identified variables to classify a younger (age 18-45 and older age group (age 46-75. From healthy adults (n = 59, trunk accelerations and angular velocities were recorded during iTUG performance. iTUG phases were detected with wavelet-analysis. Using a Partial Least Square (PLS model, from the 72-iTUG variables calculated across phases, those that explained most of the covariance between variables and age were extracted. Subsequently, a PLS-discriminant analysis (DA assessed classification power of the identified iTUG variables to discriminate the age groups. 27 variables, related to turning, walking and the stand-to-sit movement explained 71% of the variation in age. The PLS-DA with these 27 variables showed a sensitivity and specificity of 90% and 85%. Based on this model, the iTUG can accurately distinguish young and older adults. Such data can serve as a reference for pathological aging with respect to a widely used mobility test. Mobility tests like the TUG supplemented with smart technology could be used in

  13. Genome-wide association analyses identify 44 risk variants and refine the genetic architecture of major depression.

    Science.gov (United States)

    Wray, Naomi R; Ripke, Stephan; Mattheisen, Manuel; Trzaskowski, Maciej; Byrne, Enda M; Abdellaoui, Abdel; Adams, Mark J; Agerbo, Esben; Air, Tracy M; Andlauer, Till M F; Bacanu, Silviu-Alin; Bækvad-Hansen, Marie; Beekman, Aartjan F T; Bigdeli, Tim B; Binder, Elisabeth B; Blackwood, Douglas R H; Bryois, Julien; Buttenschøn, Henriette N; Bybjerg-Grauholm, Jonas; Cai, Na; Castelao, Enrique; Christensen, Jane Hvarregaard; Clarke, Toni-Kim; Coleman, Jonathan I R; Colodro-Conde, Lucía; Couvy-Duchesne, Baptiste; Craddock, Nick; Crawford, Gregory E; Crowley, Cheynna A; Dashti, Hassan S; Davies, Gail; Deary, Ian J; Degenhardt, Franziska; Derks, Eske M; Direk, Nese; Dolan, Conor V; Dunn, Erin C; Eley, Thalia C; Eriksson, Nicholas; Escott-Price, Valentina; Kiadeh, Farnush Hassan Farhadi; Finucane, Hilary K; Forstner, Andreas J; Frank, Josef; Gaspar, Héléna A; Gill, Michael; Giusti-Rodríguez, Paola; Goes, Fernando S; Gordon, Scott D; Grove, Jakob; Hall, Lynsey S; Hannon, Eilis; Hansen, Christine Søholm; Hansen, Thomas F; Herms, Stefan; Hickie, Ian B; Hoffmann, Per; Homuth, Georg; Horn, Carsten; Hottenga, Jouke-Jan; Hougaard, David M; Hu, Ming; Hyde, Craig L; Ising, Marcus; Jansen, Rick; Jin, Fulai; Jorgenson, Eric; Knowles, James A; Kohane, Isaac S; Kraft, Julia; Kretzschmar, Warren W; Krogh, Jesper; Kutalik, Zoltán; Lane, Jacqueline M; Li, Yihan; Li, Yun; Lind, Penelope A; Liu, Xiaoxiao; Lu, Leina; MacIntyre, Donald J; MacKinnon, Dean F; Maier, Robert M; Maier, Wolfgang; Marchini, Jonathan; Mbarek, Hamdi; McGrath, Patrick; McGuffin, Peter; Medland, Sarah E; Mehta, Divya; Middeldorp, Christel M; Mihailov, Evelin; Milaneschi, Yuri; Milani, Lili; Mill, Jonathan; Mondimore, Francis M; Montgomery, Grant W; Mostafavi, Sara; Mullins, Niamh; Nauck, Matthias; Ng, Bernard; Nivard, Michel G; Nyholt, Dale R; O'Reilly, Paul F; Oskarsson, Hogni; Owen, Michael J; Painter, Jodie N; Pedersen, Carsten Bøcker; Pedersen, Marianne Giørtz; Peterson, Roseann E; Pettersson, Erik; Peyrot, Wouter J; Pistis, Giorgio; Posthuma, Danielle; Purcell, Shaun M; Quiroz, Jorge A; Qvist, Per; Rice, John P; Riley, Brien P; Rivera, Margarita; Saeed Mirza, Saira; Saxena, Richa; Schoevers, Robert; Schulte, Eva C; Shen, Ling; Shi, Jianxin; Shyn, Stanley I; Sigurdsson, Engilbert; Sinnamon, Grant B C; Smit, Johannes H; Smith, Daniel J; Stefansson, Hreinn; Steinberg, Stacy; Stockmeier, Craig A; Streit, Fabian; Strohmaier, Jana; Tansey, Katherine E; Teismann, Henning; Teumer, Alexander; Thompson, Wesley; Thomson, Pippa A; Thorgeirsson, Thorgeir E; Tian, Chao; Traylor, Matthew; Treutlein, Jens; Trubetskoy, Vassily; Uitterlinden, André G; Umbricht, Daniel; Van der Auwera, Sandra; van Hemert, Albert M; Viktorin, Alexander; Visscher, Peter M; Wang, Yunpeng; Webb, Bradley T; Weinsheimer, Shantel Marie; Wellmann, Jürgen; Willemsen, Gonneke; Witt, Stephanie H; Wu, Yang; Xi, Hualin S; Yang, Jian; Zhang, Futao; Arolt, Volker; Baune, Bernhard T; Berger, Klaus; Boomsma, Dorret I; Cichon, Sven; Dannlowski, Udo; de Geus, E C J; DePaulo, J Raymond; Domenici, Enrico; Domschke, Katharina; Esko, Tõnu; Grabe, Hans J; Hamilton, Steven P; Hayward, Caroline; Heath, Andrew C; Hinds, David A; Kendler, Kenneth S; Kloiber, Stefan; Lewis, Glyn; Li, Qingqin S; Lucae, Susanne; Madden, Pamela F A; Magnusson, Patrik K; Martin, Nicholas G; McIntosh, Andrew M; Metspalu, Andres; Mors, Ole; Mortensen, Preben Bo; Müller-Myhsok, Bertram; Nordentoft, Merete; Nöthen, Markus M; O'Donovan, Michael C; Paciga, Sara A; Pedersen, Nancy L; Penninx, Brenda W J H; Perlis, Roy H; Porteous, David J; Potash, James B; Preisig, Martin; Rietschel, Marcella; Schaefer, Catherine; Schulze, Thomas G; Smoller, Jordan W; Stefansson, Kari; Tiemeier, Henning; Uher, Rudolf; Völzke, Henry; Weissman, Myrna M; Werge, Thomas; Winslow, Ashley R; Lewis, Cathryn M; Levinson, Douglas F; Breen, Gerome; Børglum, Anders D; Sullivan, Patrick F

    2018-05-01

    Major depressive disorder (MDD) is a common illness accompanied by considerable morbidity, mortality, costs, and heightened risk of suicide. We conducted a genome-wide association meta-analysis based in 135,458 cases and 344,901 controls and identified 44 independent and significant loci. The genetic findings were associated with clinical features of major depression and implicated brain regions exhibiting anatomical differences in cases. Targets of antidepressant medications and genes involved in gene splicing were enriched for smaller association signal. We found important relationships of genetic risk for major depression with educational attainment, body mass, and schizophrenia: lower educational attainment and higher body mass were putatively causal, whereas major depression and schizophrenia reflected a partly shared biological etiology. All humans carry lesser or greater numbers of genetic risk factors for major depression. These findings help refine the basis of major depression and imply that a continuous measure of risk underlies the clinical phenotype.

  14. Using Watershed Models and Human Behavioral Analyses to identify Management Options to Reduce Lake Erie's Harmful Algal Blooms

    Science.gov (United States)

    Martin, J.; Wilson, R. S.; Aloysius, N.; Kalcic, M. M.; Roe, B.; Howard, G.; Irwin, E.; Zhang, W.; Liu, H.

    2017-12-01

    In early 2016, the United States and Canada formally agreed to reduce phosphorus inputs to Lake Erie by 40% to reduce the severity of annual Harmful Algal Blooms (HABs). These blooms have become more severe, with record events occurring in 2011 and 2015, and have compromised public safety, shut down drinking water supplies, and negatively impacted the economy of the western Lake Erie basin. Now, a key question is what management options should be pursued to reach the 40% reduction. This presentation will highlight interdisciplinary research to compare the amount and types of practices needed for this reduction to the current and projected levels of adoption. Multiple models of the Maumee watershed identified management plans and adoption rates needed to reach the reduction targets. For example, one successful scenario estimated necessary adoption rates of 50% for subsurface application of fertilizer on row crops, 58% for cover crops, and 78% for buffer strips. Current adoption is below these levels, but future projections based on farmer surveys shows these levels are possible. This information was then used to guide another round of watershed modeling analysis to evaluate scenarios that represented more realistic scenarios based on potential levels of management adoption. In general, these results show that accelerated adoption of management plans is needed compared to past adoption rates, and that some of these greater adoption levels are possible based on likely adoption rates. Increasing the perceived efficacy of the practices is one method that will support greater voluntary rates of adoption.

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

    Directory of Open Access Journals (Sweden)

    Mpindi John-Patrick

    2011-03-01

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

  16. Combining the Power of Statistical Analyses and Community Interviews to Identify Adoption Barriers for Stormwater Best-Management Practices

    Science.gov (United States)

    Hoover, F. A.; Bowling, L. C.; Prokopy, L. S.

    2015-12-01

    Urban stormwater is an on-going management concern in municipalities of all sizes. In both combined or separated sewer systems, pollutants from stormwater runoff enter the natural waterway system during heavy rain events. Urban flooding during frequent and more intense storms are also a growing concern. Therefore, stormwater best-management practices (BMPs) are being implemented in efforts to reduce and manage stormwater pollution and overflow. The majority of BMP water quality studies focus on the small-scale, individual effects of the BMP, and the change in water quality directly from the runoff of these infrastructures. At the watershed scale, it is difficult to establish statistically whether or not these BMPs are making a difference in water quality, given that watershed scale monitoring is often costly and time consuming, relying on significant sources of funds, which a city may not have. Hence, there is a need to quantify the level of sampling needed to detect the water quality impact of BMPs at the watershed scale. In this study, a power analysis was performed on data from an urban watershed in Lafayette, Indiana, to determine the frequency of sampling required to detect a significant change in water quality measurements. Using the R platform, results indicate that detecting a significant change in watershed level water quality would require hundreds of weekly measurements, even when improvement is present. The second part of this study investigates whether the difficulty in demonstrating water quality change represents a barrier to adoption of stormwater BMPs. Semi-structured interviews of community residents and organizations in Chicago, IL are being used to investigate residents understanding of water quality and best management practices and identify their attitudes and perceptions towards stormwater BMPs. Second round interviews will examine how information on uncertainty in water quality improvements influences their BMP attitudes and perceptions.

  17. Single-trait and multi-trait genome-wide association analyses identify novel loci for blood pressure in African-ancestry populations.

    Directory of Open Access Journals (Sweden)

    Jingjing Liang

    2017-05-01

    Full Text Available Hypertension is a leading cause of global disease, mortality, and disability. While individuals of African descent suffer a disproportionate burden of hypertension and its complications, they have been underrepresented in genetic studies. To identify novel susceptibility loci for blood pressure and hypertension in people of African ancestry, we performed both single and multiple-trait genome-wide association analyses. We analyzed 21 genome-wide association studies comprised of 31,968 individuals of African ancestry, and validated our results with additional 54,395 individuals from multi-ethnic studies. These analyses identified nine loci with eleven independent variants which reached genome-wide significance (P < 1.25×10-8 for either systolic and diastolic blood pressure, hypertension, or for combined traits. Single-trait analyses identified two loci (TARID/TCF21 and LLPH/TMBIM4 and multiple-trait analyses identified one novel locus (FRMD3 for blood pressure. At these three loci, as well as at GRP20/CDH17, associated variants had alleles common only in African-ancestry populations. Functional annotation showed enrichment for genes expressed in immune and kidney cells, as well as in heart and vascular cells/tissues. Experiments driven by these findings and using angiotensin-II induced hypertension in mice showed altered kidney mRNA expression of six genes, suggesting their potential role in hypertension. Our study provides new evidence for genes related to hypertension susceptibility, and the need to study African-ancestry populations in order to identify biologic factors contributing to hypertension.

  18. A comparative analysis of DNA barcode microarray feature size

    Directory of Open Access Journals (Sweden)

    Smith Andrew M

    2009-10-01

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

  19. Assessing Bacterial Interactions Using Carbohydrate-Based Microarrays

    Directory of Open Access Journals (Sweden)

    Andrea Flannery

    2015-12-01

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

  20. Can hospital audit teams identify case management problems, analyse their causes, identify and implement improvements? A cross-sectional process evaluation of obstetric near-miss case reviews in Benin

    Directory of Open Access Journals (Sweden)

    Borchert Matthias

    2012-10-01

    Full Text Available Abstract Background Obstetric near-miss case reviews are being promoted as a quality assurance intervention suitable for hospitals in low income countries. We introduced such reviews in five district, regional and national hospitals in Benin, West Africa. In a cross-sectional study we analysed the extent to which the hospital audit teams were able to identify case management problems (CMPs, analyse their causes, agree on solutions and put these solutions into practice. Methods We analysed case summaries, women’s interview transcripts and audit minutes produced by the audit teams for 67 meetings concerning one woman with near-miss complications each. We compared the proportion of CMPs identified by an external assessment team to the number found by the audit teams. For the latter, we described the CMP causes identified, solutions proposed and implemented by the audit teams. Results Audit meetings were conducted regularly and were well attended. Audit teams identified half of the 714 CMPs; they were more likely to find managerial ones (71% than the ones relating to treatment (30%. Most identified CMPs were valid. Almost all causes of CMPs were plausible, but often too superficial to be of great value for directing remedial action. Audit teams suggested solutions, most of them promising ones, for 38% of the CMPs they had identified, but recorded their implementation only for a minority (8.5%. Conclusions The importance of following-up and documenting the implementation of solutions should be stressed in future audit interventions. Tools facilitating the follow-up should be made available. Near-miss case reviews hold promise, but their effectiveness to improve the quality of care sustainably and on a large scale still needs to be established.

  1. Can hospital audit teams identify case management problems, analyse their causes, identify and implement improvements? A cross-sectional process evaluation of obstetric near-miss case reviews in Benin

    Science.gov (United States)

    2012-01-01

    Background Obstetric near-miss case reviews are being promoted as a quality assurance intervention suitable for hospitals in low income countries. We introduced such reviews in five district, regional and national hospitals in Benin, West Africa. In a cross-sectional study we analysed the extent to which the hospital audit teams were able to identify case management problems (CMPs), analyse their causes, agree on solutions and put these solutions into practice. Methods We analysed case summaries, women’s interview transcripts and audit minutes produced by the audit teams for 67 meetings concerning one woman with near-miss complications each. We compared the proportion of CMPs identified by an external assessment team to the number found by the audit teams. For the latter, we described the CMP causes identified, solutions proposed and implemented by the audit teams. Results Audit meetings were conducted regularly and were well attended. Audit teams identified half of the 714 CMPs; they were more likely to find managerial ones (71%) than the ones relating to treatment (30%). Most identified CMPs were valid. Almost all causes of CMPs were plausible, but often too superficial to be of great value for directing remedial action. Audit teams suggested solutions, most of them promising ones, for 38% of the CMPs they had identified, but recorded their implementation only for a minority (8.5%). Conclusions The importance of following-up and documenting the implementation of solutions should be stressed in future audit interventions. Tools facilitating the follow-up should be made available. Near-miss case reviews hold promise, but their effectiveness to improve the quality of care sustainably and on a large scale still needs to be established. PMID:23057707

  2. Single-trait and multi-trait genome-wide association analyses identify novel loci for blood pressure in African-ancestry populations

    OpenAIRE

    Liang, Jingjing; Le, Thu H.; Edwards, Digna R. Velez; Tayo, Bamidele O.; Gaulton, Kyle J.; Smith, Jennifer A.; Lu, Yingchang; Jensen, Richard A.; Chen, Guanjie; Yanek, Lisa R.; Schwander, Karen; Tajuddin, Salman M.; Sofer, Tamar; Kim, Wonji; Kayima, James

    2017-01-01

    © 2017 Public Library of Science. All Rights Reserved. Hypertension is a leading cause of global disease, mortality, and disability. While individuals of African descent suffer a disproportionate burden of hypertension and its complications, they have been underrepresented in genetic studies. To identify novel susceptibility loci for blood pressure and hypertension in people of African ancestry, we performed both single and multiple-trait genome-wide association analyses. We analyzed 21 genom...

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

    Directory of Open Access Journals (Sweden)

    Datta Somnath

    2010-02-01

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

  4. Microarray-based screening of heat shock protein inhibitors.

    Science.gov (United States)

    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.

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

    Science.gov (United States)

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

    2018-04-01

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

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

    Directory of Open Access Journals (Sweden)

    Deising Holger B

    2011-01-01

    . Comparative analyses with published microarray experiments obtained from two different nutritional stress conditions identified subsets of genes responding to different types of stress. Some of the genes that responded only to tebuconazole treatment appeared to be unique to the F. graminearum genome. Conclusions The novel F. graminearum 8 × 15 k microarray is a reliable and efficient high-throughput tool for genome-wide expression profiling experiments in fungicide research, and beyond, as shown by our data obtained for azole responses. The array data contribute to understanding mechanisms of fungicide resistance and allow identifying fungicide targets.

  7. A Versatile Microarray Platform for Capturing Rare Cells

    Science.gov (United States)

    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.

  8. Probe Selection for DNA Microarrays using OligoWiz

    DEFF Research Database (Denmark)

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

    2007-01-01

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

  9. Significance analysis of lexical bias in microarray data

    Directory of Open Access Journals (Sweden)

    Falkow Stanley

    2003-04-01

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

  10. A novel multifunctional oligonucleotide microarray for Toxoplasma gondii

    Directory of Open Access Journals (Sweden)

    Chen Feng

    2010-10-01

    Full Text Available Abstract Background Microarrays are invaluable tools for genome interrogation, SNP detection, and expression analysis, among other applications. Such broad capabilities would be of value to many pathogen research communities, although the development and use of genome-scale microarrays is often a costly undertaking. Therefore, effective methods for reducing unnecessary probes while maintaining or expanding functionality would be relevant to many investigators. Results Taking advantage of available genome sequences and annotation for Toxoplasma gondii (a pathogenic parasite responsible for illness in immunocompromised individuals and Plasmodium falciparum (a related parasite responsible for severe human malaria, we designed a single oligonucleotide microarray capable of supporting a wide range of applications at relatively low cost, including genome-wide expression profiling for Toxoplasma, and single-nucleotide polymorphism (SNP-based genotyping of both T. gondii and P. falciparum. Expression profiling of the three clonotypic lineages dominating T. gondii populations in North America and Europe provides a first comprehensive view of the parasite transcriptome, revealing that ~49% of all annotated genes are expressed in parasite tachyzoites (the acutely lytic stage responsible for pathogenesis and 26% of genes are differentially expressed among strains. A novel design utilizing few probes provided high confidence genotyping, used here to resolve recombination points in the clonal progeny of sexual crosses. Recent sequencing of additional T. gondii isolates identifies >620 K new SNPs, including ~11 K that intersect with expression profiling probes, yielding additional markers for genotyping studies, and further validating the utility of a combined expression profiling/genotyping array design. Additional applications facilitating SNP and transcript discovery, alternative statistical methods for quantifying gene expression, etc. are also pursued at

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

    Science.gov (United States)

    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

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

    Science.gov (United States)

    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

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

    Science.gov (United States)

    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

  14. Current Knowledge on Microarray Technology - An Overview

    African Journals Online (AJOL)

    Erah

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

  15. Diagnostic and analytical applications of protein microarrays

    DEFF Research Database (Denmark)

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

    2005-01-01

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

  16. Genomic analyses identify hundreds of variants associated with age at menarche and support a role for puberty timing in cancer risk

    DEFF Research Database (Denmark)

    Day, Felix R; Thompson, Deborah J; Helgason, Hannes

    2017-01-01

    The timing of puberty is a highly polygenic childhood trait that is epidemiologically associated with various adult diseases. Using 1000 Genomes Project-imputed genotype data in up to ∼370,000 women, we identify 389 independent signals (P ... pubertal development. In Icelandic data, these signals explain ∼7.4% of the population variance in age at menarche, corresponding to ∼25% of the estimated heritability. We implicate ∼250 genes via coding variation or associated expression, demonstrating significant enrichment in neural tissues. Rare...... variants near the imprinted genes MKRN3 and DLK1 were identified, exhibiting large effects when paternally inherited. Mendelian randomization analyses suggest causal inverse associations, independent of body mass index (BMI), between puberty timing and risks for breast and endometrial cancers in women...

  17. Analyses of germline variants associated with ovarian cancer survival identify functional candidates at the 1q22 and 19p12 outcome loci

    DEFF Research Database (Denmark)

    Glubb, Dylan M; Johnatty, Sharon E; Quinn, Michael C J

    2017-01-01

    We previously identified associations with ovarian cancer outcome at five genetic loci. To identify putatively causal genetic variants and target genes, we prioritized two ovarian outcome loci (1q22 and 19p12) for further study. Bioinformatic and functional genetic analyses indicated that MEF2D...... and ZNF100 are targets of candidate outcome variants at 1q22 and 19p12, respectively. At 19p12, the chromatin interaction of a putative regulatory element with the ZNF100 promoter region correlated with candidate outcome variants. At 1q22, putative regulatory elements enhanced MEF2D promoter activity...... and haplotypes containing candidate outcome variants modulated these effects. In a public dataset, MEF2D and ZNF100 expression were both associated with ovarian cancer progression-free or overall survival time. In an extended set of 6,162 epithelial ovarian cancer patients, we found that functional candidates...

  18. Genome-Wide Association Meta-Analyses to Identify Common Genetic Variants Associated with Hallux Valgus in Caucasian and African Americans

    Science.gov (United States)

    Hsu, Yi-Hsiang; Liu, Youfang; Hannan, Marian T.; Maixner, William; Smith, Shad B.; Diatchenko, Luda; Golightly, Yvonne M.; Menz, Hylton B.; Kraus, Virginia B.; Doherty, Michael; Wilson, A.G.; Jordan, Joanne M.

    2016-01-01

    Objective Hallux valgus (HV) affects ~36% of Caucasian adults. Although considered highly heritable, the underlying genetic determinants are unclear. We conducted the first genome-wide association study (GWAS) aimed to identify genetic variants associated with HV. Methods HV was assessed in 3 Caucasian cohorts (n=2,263, n=915, and n=1,231 participants, respectively). In each cohort, a GWAS was conducted using 2.5M imputed single nucleotide polymorphisms (SNPs). Mixed-effect regression with the additive genetic model adjusted for age, sex, weight and within-family correlations was used for both sex-specific and combined analyses. To combine GWAS results across cohorts, fixed-effect inverse-variance meta-analyses were used. Following meta-analyses, top-associated findings were also examined in an African American cohort (n=327). Results The proportion of HV variance explained by genome-wide genotyped SNPs was 50% in men and 48% in women. A higher proportion of genetic determinants of HV was sex-specific. The most significantly associated SNP in men was rs9675316 located on chr17q23-a24 near the AXIN2 gene (p=5.46×10−7); the most significantly associated SNP in women was rs7996797 located on chr13q14.1-q14.2 near the ESD gene (p=7.21×10−7). Genome-wide significant SNP-by-sex interaction was found for SNP rs1563374 located on chr11p15.1 near the MRGPRX3 gene (interaction p-value =4.1×10−9). The association signals diminished when combining men and women. Conclusion Findings suggest that the potential pathophysiological mechanisms of HV are complex and strongly underlined by sex-specific interactions. The identified genetic variants imply contribution of biological pathways observed in osteoarthritis as well as new pathways, influencing skeletal development and inflammation. PMID:26337638

  19. Spot detection and image segmentation in DNA microarray data.

    Science.gov (United States)

    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.

  20. Density based pruning for identification of differentially expressed genes from microarray data

    Directory of Open Access Journals (Sweden)

    Xu Jia

    2010-11-01

    Full Text Available Abstract Motivation Identification of differentially expressed genes from microarray datasets is one of the most important analyses for microarray data mining. Popular algorithms such as statistical t-test rank genes based on a single statistics. The false positive rate of these methods can be improved by considering other features of differentially expressed genes. Results We proposed a pattern recognition strategy for identifying differentially expressed genes. Genes are mapped to a two dimension feature space composed of average difference of gene expression and average expression levels. A density based pruning algorithm (DB Pruning is developed to screen out potential differentially expressed genes usually located in the sparse boundary region. Biases of popular algorithms for identifying differentially expressed genes are visually characterized. Experiments on 17 datasets from Gene Omnibus Database (GEO with experimentally verified differentially expressed genes showed that DB pruning can significantly improve the prediction accuracy of popular identification algorithms such as t-test, rank product, and fold change. Conclusions Density based pruning of non-differentially expressed genes is an effective method for enhancing statistical testing based algorithms for identifying differentially expressed genes. It improves t-test, rank product, and fold change by 11% to 50% in the numbers of identified true differentially expressed genes. The source code of DB pruning is freely available on our website http://mleg.cse.sc.edu/degprune

  1. Microarray-Based Identification of Transcription Factor Target Genes

    NARCIS (Netherlands)

    Gorte, M.; Horstman, A.; Page, R.B.; Heidstra, R.; Stromberg, A.; Boutilier, K.A.

    2011-01-01

    Microarray analysis is widely used to identify transcriptional changes associated with genetic perturbation or signaling events. Here we describe its application in the identification of plant transcription factor target genes with emphasis on the design of suitable DNA constructs for controlling TF

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

    Directory of Open Access Journals (Sweden)

    Song Joon J

    2007-03-01

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

  3. Fast Gene Ontology based clustering for microarray experiments

    Directory of Open Access Journals (Sweden)

    Ovaska Kristian

    2008-11-01

    Full Text Available Abstract Background 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. Results 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. Conclusion 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.

  4. Uses of Dendrimers for DNA Microarrays

    Directory of Open Access Journals (Sweden)

    Jean-Pierre Majoral

    2006-08-01

    Full Text Available Biosensors such as DNA microarrays and microchips are gaining an increasingimportance in medicinal, forensic, and environmental analyses. Such devices are based onthe detection of supramolecular interactions called hybridizations that occur betweencomplementary oligonucleotides, one linked to a solid surface (the probe, and the other oneto be analyzed (the target. This paper focuses on the improvements that hyperbranched andperfectly defined nanomolecules called dendrimers can provide to this methodology. Twomain uses of dendrimers for such purpose have been described up to now; either thedendrimer is used as linker between the solid surface and the probe oligonucleotide, or thedendrimer is used as a multilabeled entity linked to the target oligonucleotide. In the firstcase the dendrimer generally induces a higher loading of probes and an easier hybridization,due to moving away the solid phase. In the second case the high number of localized labels(generally fluorescent induces an increased sensitivity, allowing the detection of smallquantities of biological entities.

  5. HPLC-MS and GC-MS analyses combined with orthogonal partial least squares to identify cytotoxic constituents from turmeric (Curcuma longa L.).

    Science.gov (United States)

    Jiang, Jianlan; Zhang, Huan; Li, Zidan; Zhang, Xiaohang; Su, Xin; Li, Yan; Qiao, Bin; Yuan, Yingjin

    2013-08-01

    We investigated the fingerprints of 48 batches of turmeric total extracts (TTE) by HPLC-MS-MS and GC-MS analyses and 43 characteristic peaks (22 constituents from HPLC-MS-MS; 21 from GC-MS) were analyzed qualitatively and quantitatively. An MTT {3-(4,5-dimethylthiazol-2-yl)- 2,5-diphenyltetrazolium bromide} assay was implemented to measure the cytotoxicity of the TTE against HeLa cells. Then we utilized orthogonal partial least squares analysis, which correlated the chemical composition of the TTE to its cytotoxic activity, to identify potential cytotoxic constituents from turmeric. The result showed that 19 constituents contributed significantly to the cytotoxicity. The obtained result was verified by canonical correlation analysis. Comparison with previous reports also indicated some interaction between the curcuminoids and sesquiterpenoids in turmeric.

  6. Analyses of Tissue Culture Adaptation of Human Herpesvirus-6A by Whole Genome Deep Sequencing Redefines the Reference Sequence and Identifies Virus Entry Complex Changes.

    Science.gov (United States)

    Tweedy, Joshua G; Escriva, Eric; Topf, Maya; Gompels, Ursula A

    2017-12-31

    Tissue-culture adaptation of viruses can modulate infection. Laboratory passage and bacterial artificial chromosome (BAC)mid cloning of human cytomegalovirus, HCMV, resulted in genomic deletions and rearrangements altering genes encoding the virus entry complex, which affected cellular tropism, virulence, and vaccine development. Here, we analyse these effects on the reference genome for related betaherpesviruses, Roseolovirus, human herpesvirus 6A (HHV-6A) strain U1102. This virus is also naturally "cloned" by germline subtelomeric chromosomal-integration in approximately 1% of human populations, and accurate references are key to understanding pathological relationships between exogenous and endogenous virus. Using whole genome next-generation deep-sequencing Illumina-based methods, we compared the original isolate to tissue-culture passaged and the BACmid-cloned virus. This re-defined the reference genome showing 32 corrections and 5 polymorphisms. Furthermore, minor variant analyses of passaged and BACmid virus identified emerging populations of a further 32 single nucleotide polymorphisms (SNPs) in 10 loci, half non-synonymous indicating cell-culture selection. Analyses of the BAC-virus genome showed deletion of the BAC cassette via loxP recombination removing green fluorescent protein (GFP)-based selection. As shown for HCMV culture effects, select HHV-6A SNPs mapped to genes encoding mediators of virus cellular entry, including virus envelope glycoprotein genes gB and the gH/gL complex. Comparative models suggest stabilisation of the post-fusion conformation. These SNPs are essential to consider in vaccine-design, antimicrobial-resistance, and pathogenesis.

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

    Science.gov (United States)

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

    2012-01-01

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

  8. The Immunome of Colon Cancer: Functional In Silico Analysis of Antigenic Proteins Deduced from IgG Microarray Profiling

    Directory of Open Access Journals (Sweden)

    Johana A. Luna Coronell

    2018-02-01

    Full Text Available Characterization of the colon cancer immunome and its autoantibody signature from differentially-reactive antigens (DIRAGs could provide insights into aberrant cellular mechanisms or enriched networks associated with diseases. The purpose of this study was to characterize the antibody profile of plasma samples from 32 colorectal cancer (CRC patients and 32 controls using proteins isolated from 15,417 human cDNA expression clones on microarrays. 671 unique DIRAGs were identified and 632 were more highly reactive in CRC samples. Bioinformatics analyses reveal that compared to control samples, the immunoproteomic IgG profiling of CRC samples is mainly associated with cell death, survival, and proliferation pathways, especially proteins involved in EIF2 and mTOR signaling. Ribosomal proteins (e.g., RPL7, RPL22, and RPL27A and CRC-related genes such as APC, AXIN1, E2F4, MSH2, PMS2, and TP53 were highly enriched. In addition, differential pathways were observed between the CRC and control samples. Furthermore, 103 DIRAGs were reported in the SEREX antigen database, demonstrating our ability to identify known and new reactive antigens. We also found an overlap of 7 antigens with 48 “CRC genes.” These data indicate that immunomics profiling on protein microarrays is able to reveal the complexity of immune responses in cancerous diseases and faithfully reflects the underlying pathology. Keywords: Autoantibody tumor biomarker, Cancer immunology, Colorectal cancer, Immunomics, Protein microarray

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

    Directory of Open Access Journals (Sweden)

    Brett Trost

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

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

    Science.gov (United States)

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

    2013-01-01

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

  11. Visual Analysis of DNA Microarray Data for Accurate Molecular Identification of Non-albicans Candida Isolates from Patients with Candidemia Episodes

    OpenAIRE

    De Luca Ferrari, Michela; Ribeiro Resende, Mariângela; Sakai, Kanae; Muraosa, Yasunori; Lyra, Luzia; Gonoi, Tohru; Mikami, Yuzuru; Tominaga, Kenichiro; Kamei, Katsuhiko; Zaninelli Schreiber, Angelica; Trabasso, Plinio; Moretti, Maria Luiza

    2013-01-01

    The performance of a visual slide-based DNA microarray for the identification of non-albicans Candida spp. was evaluated. Among 167 isolates that had previously been identified by Vitek 2, the agreement between DNA microarray and sequencing results was 97.6%. This DNA microarray platform showed excellent performance.

  12. Genomic analyses identify hundreds of variants associated with age at menarche and support a role for puberty timing in cancer risk.

    Science.gov (United States)

    Day, Felix R; Thompson, Deborah J; Helgason, Hannes; Chasman, Daniel I; Finucane, Hilary; Sulem, Patrick; Ruth, Katherine S; Whalen, Sean; Sarkar, Abhishek K; Albrecht, Eva; Altmaier, Elisabeth; Amini, Marzyeh; Barbieri, Caterina M; Boutin, Thibaud; Campbell, Archie; Demerath, Ellen; Giri, Ayush; He, Chunyan; Hottenga, Jouke J; Karlsson, Robert; Kolcic, Ivana; Loh, Po-Ru; Lunetta, Kathryn L; Mangino, Massimo; Marco, Brumat; McMahon, George; Medland, Sarah E; Nolte, Ilja M; Noordam, Raymond; Nutile, Teresa; Paternoster, Lavinia; Perjakova, Natalia; Porcu, Eleonora; Rose, Lynda M; Schraut, Katharina E; Segrè, Ayellet V; Smith, Albert V; Stolk, Lisette; Teumer, Alexander; Andrulis, Irene L; Bandinelli, Stefania; Beckmann, Matthias W; Benitez, Javier; Bergmann, Sven; Bochud, Murielle; Boerwinkle, Eric; Bojesen, Stig E; Bolla, Manjeet K; Brand, Judith S; Brauch, Hiltrud; Brenner, Hermann; Broer, Linda; Brüning, Thomas; Buring, Julie E; Campbell, Harry; Catamo, Eulalia; Chanock, Stephen; Chenevix-Trench, Georgia; Corre, Tanguy; Couch, Fergus J; Cousminer, Diana L; Cox, Angela; Crisponi, Laura; Czene, Kamila; Davey Smith, George; de Geus, Eco J C N; de Mutsert, Renée; De Vivo, Immaculata; Dennis, Joe; Devilee, Peter; Dos-Santos-Silva, Isabel; Dunning, Alison M; Eriksson, Johan G; Fasching, Peter A; Fernández-Rhodes, Lindsay; Ferrucci, Luigi; Flesch-Janys, Dieter; Franke, Lude; Gabrielson, Marike; Gandin, Ilaria; Giles, Graham G; Grallert, Harald; Gudbjartsson, Daniel F; Guénel, Pascal; Hall, Per; Hallberg, Emily; Hamann, Ute; Harris, Tamara B; Hartman, Catharina A; Heiss, Gerardo; Hooning, Maartje J; Hopper, John L; Hu, Frank; Hunter, David J; Ikram, M Arfan; Im, Hae Kyung; Järvelin, Marjo-Riitta; Joshi, Peter K; Karasik, David; Kellis, Manolis; Kutalik, Zoltan; LaChance, Genevieve; Lambrechts, Diether; Langenberg, Claudia; Launer, Lenore J; Laven, Joop S E; Lenarduzzi, Stefania; Li, Jingmei; Lind, Penelope A; Lindstrom, Sara; Liu, YongMei; Luan, Jian'an; Mägi, Reedik; Mannermaa, Arto; Mbarek, Hamdi; McCarthy, Mark I; Meisinger, Christa; Meitinger, Thomas; Menni, Cristina; Metspalu, Andres; Michailidou, Kyriaki; Milani, Lili; Milne, Roger L; Montgomery, Grant W; Mulligan, Anna M; Nalls, Mike A; Navarro, Pau; Nevanlinna, Heli; Nyholt, Dale R; Oldehinkel, Albertine J; O'Mara, Tracy A; Padmanabhan, Sandosh; Palotie, Aarno; Pedersen, Nancy; Peters, Annette; Peto, Julian; Pharoah, Paul D P; Pouta, Anneli; Radice, Paolo; Rahman, Iffat; Ring, Susan M; Robino, Antonietta; Rosendaal, Frits R; Rudan, Igor; Rueedi, Rico; Ruggiero, Daniela; Sala, Cinzia F; Schmidt, Marjanka K; Scott, Robert A; Shah, Mitul; Sorice, Rossella; Southey, Melissa C; Sovio, Ulla; Stampfer, Meir; Steri, Maristella; Strauch, Konstantin; Tanaka, Toshiko; Tikkanen, Emmi; Timpson, Nicholas J; Traglia, Michela; Truong, Thérèse; Tyrer, Jonathan P; Uitterlinden, André G; Edwards, Digna R Velez; Vitart, Veronique; Völker, Uwe; Vollenweider, Peter; Wang, Qin; Widen, Elisabeth; van Dijk, Ko Willems; Willemsen, Gonneke; Winqvist, Robert; Wolffenbuttel, Bruce H R; Zhao, Jing Hua; Zoledziewska, Magdalena; Zygmunt, Marek; Alizadeh, Behrooz Z; Boomsma, Dorret I; Ciullo, Marina; Cucca, Francesco; Esko, Tõnu; Franceschini, Nora; Gieger, Christian; Gudnason, Vilmundur; Hayward, Caroline; Kraft, Peter; Lawlor, Debbie A; Magnusson, Patrik K E; Martin, Nicholas G; Mook-Kanamori, Dennis O; Nohr, Ellen A; Polasek, Ozren; Porteous, David; Price, Alkes L; Ridker, Paul M; Snieder, Harold; Spector, Tim D; Stöckl, Doris; Toniolo, Daniela; Ulivi, Sheila; Visser, Jenny A; Völzke, Henry; Wareham, Nicholas J; Wilson, James F; Spurdle, Amanda B; Thorsteindottir, Unnur; Pollard, Katherine S; Easton, Douglas F; Tung, Joyce Y; Chang-Claude, Jenny; Hinds, David; Murray, Anna; Murabito, Joanne M; Stefansson, Kari; Ong, Ken K; Perry, John R B

    2017-06-01

    The timing of puberty is a highly polygenic childhood trait that is epidemiologically associated with various adult diseases. Using 1000 Genomes Project-imputed genotype data in up to ∼370,000 women, we identify 389 independent signals (P < 5 × 10 -8 ) for age at menarche, a milestone in female pubertal development. In Icelandic data, these signals explain ∼7.4% of the population variance in age at menarche, corresponding to ∼25% of the estimated heritability. We implicate ∼250 genes via coding variation or associated expression, demonstrating significant enrichment in neural tissues. Rare variants near the imprinted genes MKRN3 and DLK1 were identified, exhibiting large effects when paternally inherited. Mendelian randomization analyses suggest causal inverse associations, independent of body mass index (BMI), between puberty timing and risks for breast and endometrial cancers in women and prostate cancer in men. In aggregate, our findings highlight the complexity of the genetic regulation of puberty timing and support causal links with cancer susceptibility.

  13. Microarray expression profiling of human dental pulp from single subject.

    Science.gov (United States)

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

    2008-01-01

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

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

    Energy Technology Data Exchange (ETDEWEB)

    Gardner, S; Jaing, C

    2012-03-27

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

  15. Fine-scaled human genetic structure revealed by SNP microarrays.

    Science.gov (United States)

    Xing, Jinchuan; Watkins, W Scott; Witherspoon, David J; Zhang, Yuhua; Guthery, Stephen L; Thara, Rangaswamy; Mowry, Bryan J; Bulayeva, Kazima; Weiss, Robert B; Jorde, Lynn B

    2009-05-01

    We report an analysis of more than 240,000 loci genotyped using the Affymetrix SNP microarray in 554 individuals from 27 worldwide populations in Africa, Asia, and Europe. To provide a more extensive and complete sampling of human genetic variation, we have included caste and tribal samples from two states in South India, Daghestanis from eastern Europe, and the Iban from Malaysia. Consistent with observations made by Charles Darwin, our results highlight shared variation among human populations and demonstrate that much genetic variation is geographically continuous. At the same time, principal components analyses reveal discernible genetic differentiation among almost all identified populations in our sample, and in most cases, individuals can be clearly assigned to defined populations on the basis of SNP genotypes. All individuals are accurately classified into continental groups using a model-based clustering algorithm, but between closely related populations, genetic and self-classifications conflict for some individuals. The 250K data permitted high-level resolution of genetic variation among Indian caste and tribal populations and between highland and lowland Daghestani populations. In particular, upper-caste individuals from Tamil Nadu and Andhra Pradesh form one defined group, lower-caste individuals from these two states form another, and the tribal Irula samples form a third. Our results emphasize the correlation of genetic and geographic distances and highlight other elements, including social factors that have contributed to population structure.

  16. Quantitative in vivo analyses reveal calcium-dependent phosphorylation sites and identifies a novel component of the Toxoplasma invasion motor complex.

    Directory of Open Access Journals (Sweden)

    Thomas Nebl

    2011-09-01

    Full Text Available Apicomplexan parasites depend on the invasion of host cells for survival and proliferation. Calcium-dependent signaling pathways appear to be essential for micronemal release and gliding motility, yet the target of activated kinases remains largely unknown. We have characterized calcium-dependent phosphorylation events during Toxoplasma host cell invasion. Stimulation of live tachyzoites with Ca²⁺-mobilizing drugs leads to phosphorylation of numerous parasite proteins, as shown by differential 2-DE display of ³²[P]-labeled protein extracts. Multi-dimensional Protein Identification Technology (MudPIT identified ∼546 phosphorylation sites on over 300 Toxoplasma proteins, including 10 sites on the actomyosin invasion motor. Using a Stable Isotope of Amino Acids in Culture (SILAC-based quantitative LC-MS/MS analyses we monitored changes in the abundance and phosphorylation of the invasion motor complex and defined Ca²⁺-dependent phosphorylation patterns on three of its components--GAP45, MLC1 and MyoA. Furthermore, calcium-dependent phosphorylation of six residues across GAP45, MLC1 and MyoA is correlated with invasion motor activity. By analyzing proteins that appear to associate more strongly with the invasion motor upon calcium stimulation we have also identified a novel 15-kDa Calmodulin-like protein that likely represents the MyoA Essential Light Chain of the Toxoplasma invasion motor. This suggests that invasion motor activity could be regulated not only by phosphorylation but also by the direct binding of calcium ions to this new component.

  17. Comprehensive multi-stage linkage analyses identify a locus for adult height on chromosome 3p in a healthy Caucasian population.

    Science.gov (United States)

    Ellis, Justine A; Scurrah, Katrina J; Duncan, Anna E; Lamantia, Angela; Byrnes, Graham B; Harrap, Stephen B

    2007-04-01

    There have been a number of genome-wide linkage studies for adult height in recent years. These studies have yielded few well-replicated loci, and none have been further confirmed by the identification of associated gene variants. The inconsistent results may be attributable to the fact that few studies have combined accurate phenotype measures with informative statistical modelling in healthy populations. We have performed a multi-stage genome-wide linkage analysis for height in 275 adult sibling pairs drawn randomly from the Victorian Family Heart Study (VFHS), a healthy population-based Caucasian cohort. Height was carefully measured in a standardised fashion on regularly calibrated equipment. Following genome-wide identification of a peak Z-score of 3.14 on chromosome 3 at 69 cM, we performed a fine-mapping analysis of this region in an extended sample of 392 two-generation families. We used a number of variance components models that incorporated assortative mating and shared environment effects, and we observed a peak LOD score of approximately 3.5 at 78 cM in four of the five models tested. We also demonstrated that the most prevalent model in the literature gave the worst fit, and the lowest LOD score (2.9) demonstrating the importance of appropriate modelling. The region identified in this study replicates the results of other genome-wide scans of height and bone-related phenotypes, strongly suggesting the presence of a gene important in bone growth on chromosome 3p. Association analyses of relevant candidate genes should identify the genetic variants responsible for the chromosome 3p linkage signal in our population.

  18. Microarray Beads for Identifying Blood Group Single Nucleotide Polymorphisms

    OpenAIRE

    Drago, Francesca; Karpasitou, Katerina; Poli, Francesca

    2009-01-01

    We have developed a high-throughput system for single nucleotide polymorphism (SNP) genotyping of alleles of diverse blood group systems exploiting Luminex technology. The method uses specific oligonucleotide probes coupled to a specific array of fluorescent microspheres and is designed for typing Jka/Jkb, Fya/Fyb, S/s, K/k, Kpa/Kpb, Jsa/Jsb, Coa/Cob and Lua/Lub alleles. Briefly, two multiplex PCR reactions (PCR I and PCR II) according to the laboratory specific needs are set up. PCR I amplif...

  19. Microarray Beads for Identifying Blood Group Single Nucleotide Polymorphisms.

    Science.gov (United States)

    Drago, Francesca; Karpasitou, Katerina; Poli, Francesca

    2009-01-01

    We have developed a high-throughput system for single nucleotide polymorphism (SNP) genotyping of alleles of diverse blood group systems exploiting Luminex technology. The method uses specific oligonucleotide probes coupled to a specific array of fluorescent microspheres and is designed for typing Jk(a)/Jk(b), Fy(a)/Fy(b), S/s, K/k, Kp(a)/Kp(b), Js(a)/Js(b), Co(a)/Co(b) and Lu(a)/Lu(b) alleles. Briefly, two multiplex PCR reactions (PCR I and PCR II) according to the laboratory specific needs are set up. PCR I amplifies the alleles tested routinely, namely Jk(a)/Jk(b), Fy(a)/Fy(b), S/s, and K/k. PCR II amplifies those alleles that are typed less frequently. Biotinylated PCR products are hybridized in a single multiplex assay with the corresponding probe mixture. After incubation with R-phycoerythrin-conjugated streptavidin, the emitted fluorescence is analyzed with Luminex 100. So far, we have typed more than 2,000 subjects, 493 of whom with multiplex assay, and there have been no discrepancies with the serology results other than null and/or weak phenotypes. The cost of consumables and reagents for typing a single biallelic pair per sample is less than EUR 3.-, not including DNA extraction costs. The capability to perform multiplexed reactions makes the method markedly suitable for mass screening of red blood cell alleles. This genotyping approach represents an important tool in transfusion medicine.

  20. Genome-wide Meta-analyses of Breast, Ovarian and Prostate Cancer Association Studies Identify Multiple New Susceptibility Loci Shared by At Least Two Cancer Types

    Science.gov (United States)

    Kar, Siddhartha P.; Beesley, Jonathan; Al Olama, Ali Amin; Michailidou, Kyriaki; Tyrer, Jonathan; Kote-Jarai, ZSofia; Lawrenson, Kate; Lindstrom, Sara; Ramus, Susan J.; Thompson, Deborah J.; Kibel, Adam S.; Dansonka-Mieszkowska, Agnieszka; Michael, Agnieszka; Dieffenbach, Aida K.; Gentry-Maharaj, Aleksandra; Whittemore, Alice S.; Wolk, Alicja; Monteiro, Alvaro; Peixoto, Ana; Kierzek, Andrzej; Cox, Angela; Rudolph, Anja; Gonzalez-Neira, Anna; Wu, Anna H.; Lindblom, Annika; Swerdlow, Anthony; Ziogas, Argyrios; Ekici, Arif B.; Burwinkel, Barbara; Karlan, Beth Y.; Nordestgaard, Børge G.; Blomqvist, Carl; Phelan, Catherine; McLean, Catriona; Pearce, Celeste Leigh; Vachon, Celine; Cybulski, Cezary; Slavov, Chavdar; Stegmaier, Christa; Maier, Christiane; Ambrosone, Christine B.; Høgdall, Claus K.; Teerlink, Craig C.; Kang, Daehee; Tessier, Daniel C.; Schaid, Daniel J.; Stram, Daniel O.; Cramer, Daniel W.; Neal, David E.; Eccles, Diana; Flesch-Janys, Dieter; Velez Edwards, Digna R.; Wokozorczyk, Dominika; Levine, Douglas A.; Yannoukakos, Drakoulis; Sawyer, Elinor J.; Bandera, Elisa V.; Poole, Elizabeth M.; Goode, Ellen L.; Khusnutdinova, Elza; Høgdall, Estrid; Song, Fengju; Bruinsma, Fiona; Heitz, Florian; Modugno, Francesmary; Hamdy, Freddie C.; Wiklund, Fredrik; Giles, Graham G.; Olsson, Håkan; Wildiers, Hans; Ulmer, Hans-Ulrich; Pandha, Hardev; Risch, Harvey A.; Darabi, Hatef; Salvesen, Helga B.; Nevanlinna, Heli; Gronberg, Henrik; Brenner, Hermann; Brauch, Hiltrud; Anton-Culver, Hoda; Song, Honglin; Lim, Hui-Yi; McNeish, Iain; Campbell, Ian; Vergote, Ignace; Gronwald, Jacek; Lubiński, Jan; Stanford, Janet L.; Benítez, Javier; Doherty, Jennifer A.; Permuth, Jennifer B.; Chang-Claude, Jenny; Donovan, Jenny L.; Dennis, Joe; Schildkraut, Joellen M.; Schleutker, Johanna; Hopper, John L.; Kupryjanczyk, Jolanta; Park, Jong Y.; Figueroa, Jonine; Clements, Judith A.; Knight, Julia A.; Peto, Julian; Cunningham, Julie M.; Pow-Sang, Julio; Batra, Jyotsna; Czene, Kamila; Lu, Karen H.; Herkommer, Kathleen; Khaw, Kay-Tee; Matsuo, Keitaro; Muir, Kenneth; Offitt, Kenneth; Chen, Kexin; Moysich, Kirsten B.; Aittomäki, Kristiina; Odunsi, Kunle; Kiemeney, Lambertus A.; Massuger, Leon F.A.G.; Fitzgerald, Liesel M.; Cook, Linda S.; Cannon-Albright, Lisa; Hooning, Maartje J.; Pike, Malcolm C.; Bolla, Manjeet K.; Luedeke, Manuel; Teixeira, Manuel R.; Goodman, Marc T.; Schmidt, Marjanka K.; Riggan, Marjorie; Aly, Markus; Rossing, Mary Anne; Beckmann, Matthias W.; Moisse, Matthieu; Sanderson, Maureen; Southey, Melissa C.; Jones, Michael; Lush, Michael; Hildebrandt, Michelle A. T.; Hou, Ming-Feng; Schoemaker, Minouk J.; Garcia-Closas, Montserrat; Bogdanova, Natalia; Rahman, Nazneen; Le, Nhu D.; Orr, Nick; Wentzensen, Nicolas; Pashayan, Nora; Peterlongo, Paolo; Guénel, Pascal; Brennan, Paul; Paulo, Paula; Webb, Penelope M.; Broberg, Per; Fasching, Peter A.; Devilee, Peter; Wang, Qin; Cai, Qiuyin; Li, Qiyuan; Kaneva, Radka; Butzow, Ralf; Kopperud, Reidun Kristin; Schmutzler, Rita K.; Stephenson, Robert A.; MacInnis, Robert J.; Hoover, Robert N.; Winqvist, Robert; Ness, Roberta; Milne, Roger L.; Travis, Ruth C.; Benlloch, Sara; Olson, Sara H.; McDonnell, Shannon K.; Tworoger, Shelley S.; Maia, Sofia; Berndt, Sonja; Lee, Soo Chin; Teo, Soo-Hwang; Thibodeau, Stephen N.; Bojesen, Stig E.; Gapstur, Susan M.; Kjær, Susanne Krüger; Pejovic, Tanja; Tammela, Teuvo L.J.; Dörk, Thilo; Brüning, Thomas; Wahlfors, Tiina; Key, Tim J.; Edwards, Todd L.; Menon, Usha; Hamann, Ute; Mitev, Vanio; Kosma, Veli-Matti; Setiawan, Veronica Wendy; Kristensen, Vessela; Arndt, Volker; Vogel, Walther; Zheng, Wei; Sieh, Weiva; Blot, William J.; Kluzniak, Wojciech; Shu, Xiao-Ou; Gao, Yu-Tang; Schumacher, Fredrick; Freedman, Matthew L.; Berchuck, Andrew; Dunning, Alison M.; Simard, Jacques; Haiman, Christopher A.; Spurdle, Amanda; Sellers, Thomas A.; Hunter, David J.; Henderson, Brian E.; Kraft, Peter; Chanock, Stephen J.; Couch, Fergus J.; Hall, Per; Gayther, Simon A.; Easton, Douglas F.; Chenevix-Trench, Georgia; Eeles, Rosalind; Pharoah, Paul D.P.; Lambrechts, Diether

    2016-01-01

    Breast, ovarian, and prostate cancers are hormone-related and may have a shared genetic basis but this has not been investigated systematically by genome-wide association (GWA) studies. Meta-analyses combining the largest GWA meta-analysis data sets for these cancers totaling 112,349 cases and 116,421 controls of European ancestry, all together and in pairs, identified at P cancer loci: three associated with susceptibility to all three cancers (rs17041869/2q13/BCL2L11; rs7937840/11q12/INCENP; rs1469713/19p13/GATAD2A), two breast and ovarian cancer risk loci (rs200182588/9q31/SMC2; rs8037137/15q26/RCCD1), and two breast and prostate cancer risk loci (rs5013329/1p34/NSUN4; rs9375701/6q23/L3MBTL3). Index variants in five additional regions previously associated with only one cancer also showed clear association with a second cancer type. Cell-type specific expression quantitative trait locus and enhancer-gene interaction annotations suggested target genes with potential cross-cancer roles at the new loci. Pathway analysis revealed significant enrichment of death receptor signaling genes near loci with P cancer meta-analysis. PMID:27432226

  1. The use of sterol distributions combined with compound specific isotope analyses as a tool to identify the origin of fecal contamination in rivers.

    Science.gov (United States)

    Biache, Coralie; Philp, R Paul

    2013-03-01

    The sterol distributions of 9 sediment samples from the Illinois River Basin (OK and AR, USA) were examined in order to identify the source of fecal contamination. The samples were extracted with organic solvent using sonication and the fractions containing the sterols were isolated and analyzed by gas chromatography-mass spectrometry. The sterol distributions of the Illinois River samples were dominated by phytosterols. They were compared to those of different animal feces and manures using a principal component analysis and correspondence appeared between the sediments and one group of chicken feces samples. Gas chromatography-isotope ratio mass spectrometry analyses were also performed to determine the δ(13)C values for the phytosterols and to get an indication of their origin based on the C(3)/C(4) plant signatures. The δ(13)C values obtained ranged from -30.6 ‰ to -17.4 ‰ (VPDB) corresponding to a mixed signature between C(3) and C(4) plants, indicating a C(4) plant contribution to the C(3) plant natural background. These observations indicate that a proportion of the phytosterols originated from chicken feces. Copyright © 2012 Elsevier Ltd. All rights reserved.

  2. Dimension reduction methods for microarray data: a review

    Directory of Open Access Journals (Sweden)

    Rabia Aziz

    2017-03-01

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

  3. Exploiting fluorescence for multiplex immunoassays on protein microarrays

    International Nuclear Information System (INIS)

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

    2014-01-01

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

  4. Bacterial identification and subtyping using DNA microarray and DNA sequencing.

    Science.gov (United States)

    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.

  5. Employing image processing techniques for cancer detection using microarray images.

    Science.gov (United States)

    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.

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

    Science.gov (United States)

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

    2010-06-18

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

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

    Directory of Open Access Journals (Sweden)

    Bidard Frédérique

    2010-06-01

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

  8. Bystander effect: Biological endpoints and microarray analysis

    Energy Technology Data Exchange (ETDEWEB)

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

    2006-05-11

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

  9. Bystander effect: Biological endpoints and microarray analysis

    International Nuclear Information System (INIS)

    Chaudhry, M. Ahmad

    2006-01-01

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

  10. Advanced microarray technologies for clinical diagnostics

    NARCIS (Netherlands)

    Pierik, Anke

    2011-01-01

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

  11. Carbohydrate Microarrays in Plant Science

    DEFF Research Database (Denmark)

    Fangel, Jonatan Ulrik; Pedersen, H.L.; Vidal-Melgosa, S.

    2012-01-01

    Almost all plant cells are surrounded by glycan-rich cell walls, which form much of the plant body and collectively are the largest source of biomass on earth. Plants use polysaccharides for support, defense, signaling, cell adhesion, and as energy storage, and many plant glycans are also important...... industrially and nutritionally. Understanding the biological roles of plant glycans and the effective exploitation of their useful properties requires a detailed understanding of their structures, occurrence, and molecular interactions. Microarray technology has revolutionized the massively high...... for plant research and can be used to map glycan populations across large numbers of samples to screen antibodies, carbohydrate binding proteins, and carbohydrate binding modules and to investigate enzyme activities....

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

    Directory of Open Access Journals (Sweden)

    Beaudoing Emmanuel

    2006-09-01

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

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

    LENUS (Irish Health Repository)

    Faure, Andre J

    2011-01-24

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

  14. Genome rearrangements detected by SNP microarrays in individuals with intellectual disability referred with possible Williams syndrome.

    Directory of Open Access Journals (Sweden)

    Ariel M Pani

    2010-08-01

    Full Text Available Intellectual disability (ID affects 2-3% of the population and may occur with or without multiple congenital anomalies (MCA or other medical conditions. Established genetic syndromes and visible chromosome abnormalities account for a substantial percentage of ID diagnoses, although for approximately 50% the molecular etiology is unknown. Individuals with features suggestive of various syndromes but lacking their associated genetic anomalies pose a formidable clinical challenge. With the advent of microarray techniques, submicroscopic genome alterations not associated with known syndromes are emerging as a significant cause of ID and MCA.High-density SNP microarrays were used to determine genome wide copy number in 42 individuals: 7 with confirmed alterations in the WS region but atypical clinical phenotypes, 31 with ID and/or MCA, and 4 controls. One individual from the first group had the most telomeric gene in the WS critical region deleted along with 2 Mb of flanking sequence. A second person had the classic WS deletion and a rearrangement on chromosome 5p within the Cri du Chat syndrome (OMIM:123450 region. Six individuals from the ID/MCA group had large rearrangements (3 deletions, 3 duplications, one of whom had a large inversion associated with a deletion that was not detected by the SNP arrays.Combining SNP microarray analyses and qPCR allowed us to clone and sequence 21 deletion breakpoints in individuals with atypical deletions in the WS region and/or ID or MCA. Comparison of these breakpoints to databases of genomic variation revealed that 52% occurred in regions harboring structural variants in the general population. For two probands the genomic alterations were flanked by segmental duplications, which frequently mediate recurrent genome rearrangements; these may represent new genomic disorders. While SNP arrays and related technologies can identify potentially pathogenic deletions and duplications, obtaining sequence information

  15. Spatiotemporal proteomic analyses during pancreas cancer progression identifies serine/threonine stress kinase 4 (STK4) as a novel candidate biomarker for early stage disease.

    Science.gov (United States)

    Mirus, Justin E; Zhang, Yuzheng; Hollingsworth, Michael A; Solan, Joell L; Lampe, Paul D; Hingorani, Sunil R

    2014-12-01

    Pancreas cancer, or pancreatic ductal adenocarcinoma, is the deadliest of solid tumors, with a five-year survival rate of pancreas cancer. Mouse models that accurately recapitulate the human condition allow disease tracking from inception to invasion and can therefore be useful for studying early disease stages in which surgical resection is possible. Using a highly faithful mouse model of pancreas cancer in conjunction with a high-density antibody microarray containing ∼2500 antibodies, we interrogated the pancreatic tissue proteome at preinvasive and invasive stages of disease. The goal was to discover early stage tissue markers of pancreas cancer and follow them through histologically defined stages of disease using cohorts of mice lacking overt clinical signs and symptoms and those with end-stage metastatic disease, respectively. A panel of seven up-regulated proteins distinguishing pancreas cancer from normal pancreas was validated, and their levels were assessed in tissues collected at preinvasive, early invasive, and moribund stages of disease. Six of the seven markers also differentiated pancreas cancer from an experimental model of chronic pancreatitis. The levels of serine/threonine stress kinase 4 (STK4) increased between preinvasive and invasive stages, suggesting its potential as a tissue biomarker, and perhaps its involvement in progression from precursor pancreatic intraepithelial neoplasia to pancreatic ductal adenocarcinoma. Immunohistochemistry of STK4 at different stages of disease revealed a dynamic expression pattern further implicating it in early tumorigenic events. Immunohistochemistry of a panel of human pancreas cancers confirmed that STK4 levels were increased in tumor epithelia relative to normal tissue. Overall, this integrated approach yielded several tissue markers that could serve as signatures of disease stage, including early (resectable), and therefore clinically meaningful, stages. © 2014 by The American Society for

  16. Printing Proteins as Microarrays for High-Throughput Function Determination

    Science.gov (United States)

    MacBeath, Gavin; Schreiber, Stuart L.

    2000-09-01

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

  17. High quality protein microarray using in situ protein purification

    Directory of Open Access Journals (Sweden)

    Fleischmann Robert D

    2009-08-01

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

  18. Translating microarray data for diagnostic testing in childhood leukaemia

    International Nuclear Information System (INIS)

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

    2006-01-01

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

  19. Seeded Bayesian Networks: Constructing genetic networks from microarray data

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    Quackenbush John

    2008-07-01

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

  20. Xylella fastidiosa gene expression analysis by DNA microarrays

    OpenAIRE

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

    2009-01-01

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

  1. Detection of perturbation phases and developmental stages in organisms from DNA microarray time series data.

    Directory of Open Access Journals (Sweden)

    Marianne Rooman

    Full Text Available Available DNA microarray time series that record gene expression along the developmental stages of multicellular eukaryotes, or in unicellular organisms subject to external perturbations such as stress and diauxie, are analyzed. By pairwise comparison of the gene expression profiles on the basis of a translation-invariant and scale-invariant distance measure corresponding to least-rectangle regression, it is shown that peaks in the average distance values are noticeable and are localized around specific time points. These points systematically coincide with the transition points between developmental phases or just follow the external perturbations. This approach can thus be used to identify automatically, from microarray time series alone, the presence of external perturbations or the succession of developmental stages in arbitrary cell systems. Moreover, our results show that there is a striking similarity between the gene expression responses to these a priori very different phenomena. In contrast, the cell cycle does not involve a perturbation-like phase, but rather continuous gene expression remodeling. Similar analyses were conducted using three other standard distance measures, showing that the one we introduced was superior. Based on these findings, we set up an adapted clustering method that uses this distance measure and classifies the genes on the basis of their expression profiles within each developmental stage or between perturbation phases.

  2. Identifying the sources of nitrate contamination of groundwater in an agricultural area (Haean basin, Korea) using isotope and microbial community analyses

    Energy Technology Data Exchange (ETDEWEB)

    Kim, Heejung [School of Earth and Environmental Sciences (BK21 SEES), Seoul National University, Seoul 151–747 (Korea, Republic of); Kaown, Dugin, E-mail: dugin1@snu.ac.kr [School of Earth and Environmental Sciences (BK21 SEES), Seoul National University, Seoul 151–747 (Korea, Republic of); Mayer, Bernhard [Department of Geoscience, University of Calgary, 2500 University Drive NW, Calgary T2N 1N4, Alberta (Canada); Lee, Jin-Yong [Department of Geology, Kangwon National University, Chuncheon 200–701 (Korea, Republic of); Hyun, Yunjung [Planning and Management Group, Korea Environment Institute, Sejong 339-007 (Korea, Republic of); Lee, Kang-Kun [School of Earth and Environmental Sciences (BK21 SEES), Seoul National University, Seoul 151–747 (Korea, Republic of)

    2015-11-15

    } and SO{sub 4}{sup 2−} in groundwater in areas with intensive agricultural land use. - Highlights: • Dual isotope analyses identified contaminant sources. • Aquifer contamination was affected by land use. • Microbial community in groundwater reflects land use. • Approach is promising for managing water quality in agricultural areas.

  3. Identifying the sources of nitrate contamination of groundwater in an agricultural area (Haean basin, Korea) using isotope and microbial community analyses

    International Nuclear Information System (INIS)

    Kim, Heejung; Kaown, Dugin; Mayer, Bernhard; Lee, Jin-Yong; Hyun, Yunjung; Lee, Kang-Kun

    2015-01-01

    An integrated study based on hydrogeochemical, microbiological and dual isotopic approaches for nitrate and sulfate was conducted to elucidate sources and biogeochemical reactions governing groundwater contaminants in different seasons and under different land use in a basin of Korea. The land use in the study area is comprised of forests (58.0%), vegetable fields (27.6%), rice paddy fields (11.4%) and others (3.0%). The concentrations of NO 3 –N and SO 4 2− in groundwater in vegetable fields were highest with 4.2–15.2 mg L −1 and 1.6–19.7 mg L −1 respectively, whereas under paddy fields NO 3 –N concentrations ranged from 0 to 10.7 mg L −1 and sulfate concentrations were ~ 15 mg L −1 . Groundwater with high NO 3 –N concentrations of > 10 mg L −1 had δ 15 N–NO 3 − values ranging from 5.2 to 5.9‰ and δ 18 O values of nitrate between 2.7 and 4.6‰ suggesting that the nitrate was mineralized from soil organic matter that was amended by fertilizer additions. Elevated concentrations of SO 4 2− with δ 34 S–SO 4 2− values between 1 and 6‰ in aquifers in vegetable fields indicated that a mixture of sulfate from atmospheric deposition, mineralization of soil organic matter and from synthetic fertilizers is the source of groundwater sulfate. Elevated δ 18 O–NO 3 − and δ 18 O–SO 4 2− values in samples collected from the paddy fields indicated that denitrification and bacterial sulfate reduction are actively occurring removing sulfate and nitrate from the groundwater. This was supported by high occurrences of denitrifying and sulfate reducing bacteria in groundwater of the paddy fields as evidenced by 16S rRNA pyrosequencing analysis. This study shows that dual isotope techniques combined with microbial data can be a powerful tool for identification of sources and microbial processes affecting NO 3 − and SO 4 2− in groundwater in areas with intensive agricultural land use. - Highlights: • Dual isotope analyses identified

  4. Foxtail millet NF-Y families: genome-wide survey and evolution analyses identified two functional genes important in abiotic stresses

    Directory of Open Access Journals (Sweden)

    Zhi-Juan eFeng

    2015-12-01

    Full Text Available It was reported that Nuclear Factor Y (NF-Y genes were involved in abiotic stress in plants. Foxtail millet (Setaria italica, an elite stress tolerant crop, provided an impetus for the investigation of the NF-Y families in abiotic responses. In the present study, a total of 39 NF-Y genes were identified in foxtail millet. Synteny analyses suggested that foxtail millet NF-Y genes had experienced rapid expansion and strong purifying selection during the process of plant evolution. De novo transcriptome assembly of foxtail millet revealed 11 drought up-regulated NF-Y genes. SiNF-YA1 and SiNF-YB8 were highly activated in leaves and/or roots by drought and salt stresses. Abscisic acid (ABA and H2O2 played positive roles in the induction of SiNF-YA1 and SiNF-YB8 under stress treatments. Transient luciferase (LUC expression assays revealed that SiNF-YA1 and SiNF-YB8 could activate the LUC gene driven by the tobacco (Nicotiana tobacam NtERD10, NtLEA5, NtCAT, NtSOD or NtPOD promoter under normal or stress conditions. Overexpression of SiNF-YA1 enhanced drought and salt tolerance by activating stress-related genes NtERD10 and NtCAT1 and by maintaining relatively stable relative water content (RWC and contents of chlorophyll, superoxide dismutase (SOD, peroxidase (POD, catalase (CAT and malondialdehyde (MDA in transgenic lines under stresses. SiNF-YB8 regulated expression of NtSOD, NtPOD, NtLEA5 and NtERD10 and conferred relatively high RWC and chlorophyll contents and low MDA content, resulting in drought and osmotic tolerance in transgenic lines under stresses. Therefore, SiNF-YA1 and SiNF-YB8 could activate stress-related genes and improve physiological traits, resulting in tolerance to abiotic stresses in plants. All these results will facilitate functional characterization of foxtail millet NF-Ys in future studies.

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

    Directory of Open Access Journals (Sweden)

    Scheideler Marcel

    2005-04-01

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

  6. Annotating breast cancer microarray samples using ontologies

    Science.gov (United States)

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

    2008-01-01

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

  7. Simulation of microarray data with realistic characteristics

    Directory of Open Access Journals (Sweden)

    Lehmussola Antti

    2006-07-01

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

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

    Science.gov (United States)

    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.

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

    Directory of Open Access Journals (Sweden)

    Linda K. Medlin

    2013-03-01

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

  10. Metric learning for DNA microarray data analysis

    International Nuclear Information System (INIS)

    Takeuchi, Ichiro; Nakagawa, Masao; Seto, Masao

    2009-01-01

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

  11. Correction of technical bias in clinical microarray data improves concordance with known biological information

    DEFF Research Database (Denmark)

    Eklund, Aron Charles; Szallasi, Zoltan Imre

    2008-01-01

    The performance of gene expression microarrays has been well characterized using controlled reference samples, but the performance on clinical samples remains less clear. We identified sources of technical bias affecting many genes in concert, thus causing spurious correlations in clinical data...... sets and false associations between genes and clinical variables. We developed a method to correct for technical bias in clinical microarray data, which increased concordance with known biological relationships in multiple data sets....

  12. DNA microarray revealed and RNAi plants confirmed key genes conferring low Cd accumulation in barley grains

    DEFF Research Database (Denmark)

    Sun, Hongyan; Chen, Zhong-Hua; Chen, Fei

    2015-01-01

    Background Understanding the mechanism of low Cd accumulation in crops is crucial for sustainable safe food production in Cd-contaminated soils. Results Confocal microscopy, atomic absorption spectrometry, gas exchange and chlorophyll fluorescence analyses revealed a distinct difference in Cd...... with a substantial difference between the two genotypes. Cd stress led to higher expression of genes involved in transport, carbohydrate metabolism and signal transduction in the low-grain-Cd-accumulating genotype. Novel transporter genes such as zinc transporter genes were identified as being associated with low Cd...... accumulation. Quantitative RT-PCR confirmed our microarray data. Furthermore, suppression of the zinc transporter genes HvZIP3 and HvZIP8 by RNAi silencing showed increased Cd accumulation and reduced Zn and Mn concentrations in barley grains. Thus, HvZIP3 and HvZIP8 could be candidate genes related to low...

  13. Gene Expression and Microarray Investigation of Dendrobium ...

    African Journals Online (AJOL)

    blood glucose > 16.7 mmol/L were used as the model group and treated with Dendrobium mixture. (DEN ... Keywords: Diabetes, Gene expression, Dendrobium mixture, Microarray testing ..... homeostasis in airway smooth muscle. Am J.

  14. SLIMarray: Lightweight software for microarray facility management

    Directory of Open Access Journals (Sweden)

    Marzolf Bruz

    2006-10-01

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

  15. Genotyping microarray (gene chip) for the ABCR (ABCA4) gene.

    Science.gov (United States)

    Jaakson, K; Zernant, J; Külm, M; Hutchinson, A; Tonisson, N; Glavac, D; Ravnik-Glavac, M; Hawlina, M; Meltzer, M R; Caruso, R C; Testa, F; Maugeri, A; Hoyng, C B; Gouras, P; Simonelli, F; Lewis, R A; Lupski, J R; Cremers, F P M; Allikmets, R

    2003-11-01

    Genetic variation in the ABCR (ABCA4) gene has been associated with five distinct retinal phenotypes, including Stargardt disease/fundus flavimaculatus (STGD/FFM), cone-rod dystrophy (CRD), and age-related macular degeneration (AMD). Comparative genetic analyses of ABCR variation and diagnostics have been complicated by substantial allelic heterogeneity and by differences in screening methods. To overcome these limitations, we designed a genotyping microarray (gene chip) for ABCR that includes all approximately 400 disease-associated and other variants currently described, enabling simultaneous detection of all known ABCR variants. The ABCR genotyping microarray (the ABCR400 chip) was constructed by the arrayed primer extension (APEX) technology. Each sequence change in ABCR was included on the chip by synthesis and application of sequence-specific oligonucleotides. We validated the chip by screening 136 confirmed STGD patients and 96 healthy controls, each of whom we had analyzed previously by single strand conformation polymorphism (SSCP) technology and/or heteroduplex analysis. The microarray was >98% effective in determining the existing genetic variation and was comparable to direct sequencing in that it yielded many sequence changes undetected by SSCP. In STGD patient cohorts, the efficiency of the array to detect disease-associated alleles was between 54% and 78%, depending on the ethnic composition and degree of clinical and molecular characterization of a cohort. In addition, chip analysis suggested a high carrier frequency (up to 1:10) of ABCR variants in the general population. The ABCR genotyping microarray is a robust, cost-effective, and comprehensive screening tool for variation in one gene in which mutations are responsible for a substantial fraction of retinal disease. The ABCR chip is a prototype for the next generation of screening and diagnostic tools in ophthalmic genetics, bridging clinical and scientific research. Copyright 2003 Wiley

  16. PATMA: parser of archival tissue microarray

    Directory of Open Access Journals (Sweden)

    Lukasz Roszkowiak

    2016-12-01

    Full Text Available Tissue microarrays are commonly used in modern pathology for cancer tissue evaluation, as it is a very potent technique. Tissue microarray slides are often scanned to perform computer-aided histopathological analysis of the tissue cores. For processing the image, splitting the whole virtual slide into images of individual cores is required. The only way to distinguish cores corresponding to specimens in the tissue microarray is through their arrangement. Unfortunately, distinguishing the correct order of cores is not a trivial task as they are not labelled directly on the slide. The main aim of this study was to create a procedure capable of automatically finding and extracting cores from archival images of the tissue microarrays. This software supports the work of scientists who want to perform further image processing on single cores. The proposed method is an efficient and fast procedure, working in fully automatic or semi-automatic mode. A total of 89% of punches were correctly extracted with automatic selection. With an addition of manual correction, it is possible to fully prepare the whole slide image for extraction in 2 min per tissue microarray. The proposed technique requires minimum skill and time to parse big array of cores from tissue microarray whole slide image into individual core images.

  17. Tissue Microarray TechnologyA Brief Review

    Directory of Open Access Journals (Sweden)

    Ramya S Vokuda

    2018-01-01

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

  18. Evaluation of gene expression data generated from expired Affymetrix GeneChip® microarrays using MAQC reference RNA samples

    Directory of Open Access Journals (Sweden)

    Tong Weida

    2010-10-01

    Full Text Available Abstract Background The Affymetrix GeneChip® system is a commonly used platform for microarray analysis but the technology is inherently expensive. Unfortunately, changes in experimental planning and execution, such as the unavailability of previously anticipated samples or a shift in research focus, may render significant numbers of pre-purchased GeneChip® microarrays unprocessed before their manufacturer’s expiration dates. Researchers and microarray core facilities wonder whether expired microarrays are still useful for gene expression analysis. In addition, it was not clear whether the two human reference RNA samples established by the MAQC project in 2005 still maintained their transcriptome integrity over a period of four years. Experiments were conducted to answer these questions. Results Microarray data were generated in 2009 in three replicates for each of the two MAQC samples with either expired Affymetrix U133A or unexpired U133Plus2 microarrays. These results were compared with data obtained in 2005 on the U133Plus2 microarray. The percentage of overlap between the lists of differentially expressed genes (DEGs from U133Plus2 microarray data generated in 2009 and in 2005 was 97.44%. While there was some degree of fold change compression in the expired U133A microarrays, the percentage of overlap between the lists of DEGs from the expired and unexpired microarrays was as high as 96.99%. Moreover, the microarray data generated using the expired U133A microarrays in 2009 were highly concordant with microarray and TaqMan® data generated by the MAQC project in 2005. Conclusions Our results demonstrated that microarray data generated using U133A microarrays, which were more than four years past the manufacturer’s expiration date, were highly specific and consistent with those from unexpired microarrays in identifying DEGs despite some appreciable fold change compression and decrease in sensitivity. Our data also suggested that the

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

    Directory of Open Access Journals (Sweden)

    Hong Wu

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

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

    Directory of Open Access Journals (Sweden)

    Wu Xiaogang

    2012-06-01

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

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

    Science.gov (United States)

    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.

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

    Science.gov (United States)

    Rehrauer, Hubert; Zoller, Stefan; Schlapbach, Ralph

    2007-07-01

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

  3. Genomic analyses identify hundreds of variants associated with age at menarche and support a role for puberty timing in cancer risk

    NARCIS (Netherlands)

    Day, Felix R; Thompson, Deborah J; Helgason, Hannes; Chasman, Daniel I; Finucane, Hilary; Sulem, Patrick; Ruth, Katherine S; Whalen, Sean; Sarkar, Abhishek K; Albrecht, Eva; Altmaier, Elisabeth; Amini, Marzyeh; Barbieri, Caterina M; Boutin, Thibaud; Campbell, Archie; Demerath, Ellen; Giri, Ayush; He, Chunyan; Hottenga, Jouke J; Karlsson, Robert; Kolcic, Ivana; Loh, Po-Ru; Lunetta, Kathryn L; Mangino, Massimo; Marco, Brumat; McMahon, George; Medland, Sarah E; Nolte, Ilja M; Noordam, Raymond; Nutile, Teresa; Paternoster, Lavinia; Perjakova, Natalia; Porcu, Eleonora; Rose, Lynda M; Schraut, Katharina E; Segrè, Ayellet V; Smith, Albert V; Stolk, Lisette; Teumer, Alexander; Andrulis, Irene L; Bandinelli, Stefania; Beckmann, Matthias W; Benitez, Javier; Bergmann, Sven; Bochud, Murielle; de Geus, Eco J C N; Mbarek, Hamdi; Willemsen, Gonneke; Boomsma, Dorret I; Visser, Jenny A

    2017-01-01

    The timing of puberty is a highly polygenic childhood trait that is epidemiologically associated with various adult diseases. Using 1000 Genomes Project-imputed genotype data in up to ∼370,000 women, we identify 389 independent signals (P < 5 × 10(-8)) for age at menarche, a milestone in female

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

    Directory of Open Access Journals (Sweden)

    Broschat Shira L

    2008-08-01

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

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

    DEFF Research Database (Denmark)

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

    2006-01-01

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

  6. Detecting Outlier Microarray Arrays by Correlation and Percentage of Outliers Spots

    Directory of Open Access Journals (Sweden)

    Song Yang

    2006-01-01

    Full Text Available We developed a quality assurance (QA tool, namely microarray outlier filter (MOF, and have applied it to our microarray datasets for the identification of problematic arrays. Our approach is based on the comparison of the arrays using the correlation coefficient and the number of outlier spots generated on each array to reveal outlier arrays. For a human universal reference (HUR dataset, which is used as a technical control in our standard hybridization procedure, 3 outlier arrays were identified out of 35 experiments. For a human blood dataset, 12 outlier arrays were identified from 185 experiments. In general, arrays from human blood samples displayed greater variation in their gene expression profiles than arrays from HUR samples. As a result, MOF identified two distinct patterns in the occurrence of outlier arrays. These results demonstrate that this methodology is a valuable QA practice to identify questionable microarray data prior to downstream analysis.

  7. Gene Expression Responses to FUS, EWS, and TAF15 Reduction and Stress Granule Sequestration Analyses Identifies FET-Protein Non-Redundant Functions

    DEFF Research Database (Denmark)

    Blechingberg, Jenny; Luo, Yonglun; Bolund, Lars

    2012-01-01

    The FET family of proteins is composed of FUS/TLS, EWS/EWSR1, and TAF15 and possesses RNA- and DNA-binding capacities. The FET-proteins are involved in transcriptional regulation and RNA processing, and FET-gene deregulation is associated with development of cancer and protein granule formations...... in amyotrophic lateral sclerosis, frontotemporal lobar degeneration, and trinucleotide repeat expansion diseases. We here describe a comparative characterization of FET-protein localization and gene regulatory functions. We show that FUS and TAF15 locate to cellular stress granules to a larger extend than EWS....... FET-proteins have no major importance for stress granule formation and cellular stress responses, indicating that FET-protein stress granule association most likely is a downstream response to cellular stress. Gene expression analyses showed that the cellular response towards FUS and TAF15 reduction...

  8. Genome-Wide Meta-Analyses of Breast, Ovarian, and Prostate Cancer Association Studies Identify Multiple New Susceptibility Loci Shared by at Least Two Cancer Types

    DEFF Research Database (Denmark)

    Kar, Siddhartha P; Beesley, Jonathan; Amin Al Olama, Ali

    2016-01-01

    UNLABELLED: Breast, ovarian, and prostate cancers are hormone-related and may have a shared genetic basis, but this has not been investigated systematically by genome-wide association (GWA) studies. Meta-analyses combining the largest GWA meta-analysis data sets for these cancers totaling 112...... (rs200182588/9q31/SMC2; rs8037137/15q26/RCCD1), and two breast and prostate cancer risk loci (rs5013329/1p34/NSUN4; rs9375701/6q23/L3MBTL3). Index variants in five additional regions previously associated with only one cancer also showed clear association with a second cancer type. Cell......-type-specific expression quantitative trait locus and enhancer-gene interaction annotations suggested target genes with potential cross-cancer roles at the new loci. Pathway analysis revealed significant enrichment of death receptor signaling genes near loci with P cancer meta-analysis. SIGNIFICANCE...

  9. Nanotechnology: moving from microarrays toward nanoarrays.

    Science.gov (United States)

    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.

  10. Integrative missing value estimation for microarray data.

    Science.gov (United States)

    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.

  11. Integrative missing value estimation for microarray data

    Directory of Open Access Journals (Sweden)

    Zhou Xianghong

    2006-10-01

    Full Text Available Abstract Background Missing value estimation is an important preprocessing step in microarray analysis. Although several methods have been developed to solve this problem, their performance is unsatisfactory for datasets with high rates of missing data, high measurement noise, or limited numbers of samples. In fact, more than 80% of the time-series datasets in Stanford Microarray Database contain less than eight samples. Results We present the integrative Missing Value Estimation method (iMISS by incorporating information from multiple reference microarray datasets to improve missing value estimation. For each gene with missing data, we derive a consistent neighbor-gene list by taking reference data sets into consideration. To determine whether the given reference data sets are sufficiently informative for integration, we use a submatrix imputation approach. Our experiments showed that iMISS can significantly and consistently improve the accuracy of the state-of-the-art Local Least Square (LLS imputation algorithm by up to 15% improvement in our benchmark tests. Conclusion We demonstrated that the order-statistics-based integrative imputation algorithms can achieve significant improvements over the state-of-the-art missing value estimation approaches such as LLS and is especially good for imputing microarray datasets with a limited number of samples, high rates of missing data, or very noisy measurements. With the rapid accumulation of microarray datasets, the performance of our approach can be further improved by incorporating larger and more appropriate reference datasets.

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

    Science.gov (United States)

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

    2015-06-25

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

  13. Integrated genomic analyses identify KDM1A's role in cell proliferation via modulating E2F signaling activity and associate with poor clinical outcome in oral cancer.

    Science.gov (United States)

    Narayanan, Sathiya Pandi; Singh, Smriti; Gupta, Amit; Yadav, Sandhya; Singh, Shree Ram; Shukla, Sanjeev

    2015-10-28

    The histone demethylase KDM1A specifically demethylates lysine residues and its deregulation has been implicated in the initiation and progression of various cancers. However, KDM1A's molecular role and its pathological consequences, and prognostic significance in oral cancer remain less understood. In the present study, we sought to investigate the expression of KDM1A and its downstream role in oral cancer pathogenesis. By comparing mRNA expression profiles, we identified an elevated KDM1A expression in oral tumors when compared to normal oral tissues. In silico pathway prediction identified the association between KDM1A and E2F1 signaling in oral cancer. Pathway scanning, functional annotation analysis and In vitro assays showed the KDM1A's involvement in oral cancer cell proliferation and the cell cycle. Moreover, real time PCR and luciferase assays confirmed KDM1A's role in regulation of E2F1 signaling activity in oral cancer. Elevated KDM1A expression is associated with poor clinical outcome in oral cancer. Our data indicate that deregulated KDM1A expression is positively associated with proliferative phenotype of oral cancer and confers poor clinical outcome. These cumulative data suggest that KDM1A might be a potential diagnostic and therapeutic target for oral cancer. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

  14. Reduced Representation Libraries from DNA Pools Analysed with Next Generation Semiconductor Based-Sequencing to Identify SNPs in Extreme and Divergent Pigs for Back Fat Thickness

    Directory of Open Access Journals (Sweden)

    Samuele Bovo

    2015-01-01

    Full Text Available The aim of this study was to identify single nucleotide polymorphisms (SNPs that could be associated with back fat thickness (BFT in pigs. To achieve this goal, we evaluated the potential and limits of an experimental design that combined several methodologies. DNA samples from two groups of Italian Large White pigs with divergent estimating breeding value (EBV for BFT were separately pooled and sequenced, after preparation of reduced representation libraries (RRLs, on the Ion Torrent technology. Taking advantage from SNAPE for SNPs calling in sequenced DNA pools, 39,165 SNPs were identified; 1/4 of them were novel variants not reported in dbSNP. Combining sequencing data with Illumina PorcineSNP60 BeadChip genotyping results on the same animals, 661 genomic positions overlapped with a good approximation of minor allele frequency estimation. A total of 54 SNPs showing enriched alleles in one or in the other RRLs might be potential markers associated with BFT. Some of these SNPs were close to genes involved in obesity related phenotypes.

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

    Science.gov (United States)

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

    2015-11-10

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

  16. Integration of TP53, DREAM, MMB-FOXM1 and RB-E2F target gene analyses identifies cell cycle gene regulatory networks.

    Science.gov (United States)

    Fischer, Martin; Grossmann, Patrick; Padi, Megha; DeCaprio, James A

    2016-07-27

    Cell cycle (CC) and TP53 regulatory networks are frequently deregulated in cancer. While numerous genome-wide studies of TP53 and CC-regulated genes have been performed, significant variation between studies has made it difficult to assess regulation of any given gene of interest. To overcome the limitation of individual studies, we developed a meta-analysis approach to identify high confidence target genes that reflect their frequency of identification in independent datasets. Gene regulatory networks were generated by comparing differential expression of TP53 and CC-regulated genes with chromatin immunoprecipitation studies for TP53, RB1, E2F, DREAM, B-MYB, FOXM1 and MuvB. RNA-seq data from p21-null cells revealed that gene downregulation by TP53 generally requires p21 (CDKN1A). Genes downregulated by TP53 were also identified as CC genes bound by the DREAM complex. The transcription factors RB, E2F1 and E2F7 bind to a subset of DREAM target genes that function in G1/S of the CC while B-MYB, FOXM1 and MuvB control G2/M gene expression. Our approach yields high confidence ranked target gene maps for TP53, DREAM, MMB-FOXM1 and RB-E2F and enables prediction and distinction of CC regulation. A web-based atlas at www.targetgenereg.org enables assessing the regulation of any human gene of interest. © The Author(s) 2016. Published by Oxford University Press on behalf of Nucleic Acids Research.

  17. Quantitative and mixed analyses to identify factors that affect cervical cancer screening uptake among lesbian and bisexual women and transgender men.

    Science.gov (United States)

    Johnson, Michael J; Mueller, Martina; Eliason, Michele J; Stuart, Gail; Nemeth, Lynne S

    2016-12-01

    The purposes of this study were to measure the prevalence of, and identify factors associated with, cervical cancer screening among a sample of lesbian, bisexual and queer women, and transgender men. Past research has found that lesbian, bisexual and queer women underuse cervical screening service. Because deficient screening remains the most significant risk factor for cervical cancer, it is essential to understand the differences between routine and nonroutine screeners. A convergent-parallel mixed methods design. A convenience sample of 21- to 65-year-old lesbian and bisexual women and transgender men were recruited in the USA from August-December 2014. Quantitative data were collected via a 48-item Internet questionnaire (N = 226), and qualitative data were collected through in-depth telephone interviews (N = 20) and open-ended questions on the Internet questionnaire. Seventy-three per cent of the sample was routine cervical screeners. The results showed that a constellation of factors influence the use of cervical cancer screening among lesbian, bisexual and queer women. Some of those factors overlap with the general female population, whereas others are specific to the lesbian, bisexual or queer identity. Routine screeners reported feeling more welcome in the health care setting, while nonroutine screeners reported more discrimination related to their sexual orientation and gender expression. Routine screeners were also more likely to 'out' to their provider. The quantitative and qualitative factors were also compared and contrasted. Many of the factors identified in this study to influence cervical cancer screening relate to the health care environment and to interactions between the patient and provider. Nurses should be involved with creating welcoming environments for lesbian, bisexual and queer women and their partners. Moreover, nurses play a large role in patient education and should promote self-care behaviours among lesbian women and transgender

  18. Analyses of expressed sequence tags from the maize foliar pathogen Cercospora zeae-maydis identify novel genes expressed during vegetative, infectious, and reproductive growth

    Directory of Open Access Journals (Sweden)

    Kema Gert HJ

    2008-11-01

    Full Text Available Abstract Background The ascomycete fungus Cercospora zeae-maydis is an aggressive foliar pathogen of maize that causes substantial losses annually throughout the Western Hemisphere. Despite its impact on maize production, little is known about the regulation of pathogenesis in C. zeae-maydis at the molecular level. The objectives of this study were to generate a collection of expressed sequence tags (ESTs from C. zeae-maydis and evaluate their expression during vegetative, infectious, and reproductive growth. Results A total of 27,551 ESTs was obtained from five cDNA libraries constructed from vegetative and sporulating cultures of C. zeae-maydis. The ESTs, grouped into 4088 clusters and 531 singlets, represented 4619 putative unique genes. Of these, 36% encoded proteins similar (E value ≤ 10-05 to characterized or annotated proteins from the NCBI non-redundant database representing diverse molecular functions and biological processes based on Gene Ontology (GO classification. We identified numerous, previously undescribed genes with potential roles in photoreception, pathogenesis, and the regulation of development as well as Zephyr, a novel, actively transcribed transposable element. Differential expression of selected genes was demonstrated by real-time PCR, supporting their proposed roles in vegetative, infectious, and reproductive growth. Conclusion Novel genes that are potentially involved in regulating growth, development, and pathogenesis were identified in C. zeae-maydis, providing specific targets for characterization by molecular genetics and functional genomics. The EST data establish a foundation for future studies in evolutionary and comparative genomics among species of Cercospora and other groups of plant pathogenic fungi.

  19. Giant Galápagos tortoises; molecular genetic analyses identify a trans-island hybrid in a repatriation program of an endangered taxon

    Directory of Open Access Journals (Sweden)

    Caccone Adalgisa

    2007-02-01

    Full Text Available Abstract Background Giant Galápagos tortoises on the island of Española have been the focus of an intensive captive breeding-repatriation programme for over 35 years that saved the taxon from extinction. However, analysis of 118 samples from released individuals indicated that the bias sex ratio and large variance in reproductive success among the 15 breeders has severely reduced the effective population size (Ne. Results We report here that an analysis of an additional 473 captive-bred tortoises released back to the island reveals an individual (E1465 that exhibits nuclear microsatellite alleles not found in any of the 15 breeders. Statistical analyses incorporating genotypes of 304 field-sampled individuals from all populations on the major islands indicate that E1465 is most probably a hybrid between an Española female tortoise and a male from the island of Pinzón, likely present on Española due to human transport. Conclusion Removal of E1465 as well as its father and possible (half-siblings is warranted to prevent further contamination within this taxon of particular conservation significance. Despite this detected single contamination, it is highly noteworthy to emphasize the success of this repatriation program conducted over nearly 40 years and involving release of over 2000 captive-bred tortoises that now reproduce in situ. The incorporation of molecular genetic analysis of the program is providing guidance that will aid in monitoring the genetic integrity of this ambitious effort to restore a unique linage of a spectacular animal.

  20. Supervised group Lasso with applications to microarray data analysis

    Directory of Open Access Journals (Sweden)

    Huang Jian

    2007-02-01

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

  1. 3D Biomaterial Microarrays for Regenerative Medicine

    DEFF Research Database (Denmark)

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

    2015-01-01

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

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

    Directory of Open Access Journals (Sweden)

    Rouse Richard JD

    2008-07-01

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

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

    Directory of Open Access Journals (Sweden)

    Archer Kellie J

    2008-02-01

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

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

    Science.gov (United States)

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

    2000-10-01

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

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

    NARCIS (Netherlands)

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

    2009-01-01

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

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

    NARCIS (Netherlands)

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

    2017-01-01

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

  7. Post-genome wide association studies and functional analyses identify association of MPP7 gene variants with site-specific bone mineral density.

    Science.gov (United States)

    Xiao, Su-Mei; Kung, Annie Wai Chee; Gao, Yi; Lau, Kam-Shing; Ma, Alvin; Zhang, Zhen-Lin; Liu, Jian-Min; Xia, Wiebo; He, Jin-Wei; Zhao, Lin; Nie, Min; Fu, Wei-Zhen; Zhang, Min-Jia; Sun, Jing; Kwan, Johnny S H; Tso, Gloria Hoi Wan; Dai, Zhi-Jie; Cheung, Ching-Lung; Bow, Cora H; Leung, Anskar Yu Hung; Tan, Kathryn Choon Beng; Sham, Pak Chung

    2012-04-01

    Our previous genome-wide association study (GWAS) in a Hong Kong Southern Chinese population with extreme bone mineral density (BMD) scores revealed suggestive association with MPP7, which ranked second after JAG1 as a candidate gene for BMD. To follow-up this suggestive signal, we replicated the top single-nucleotide polymorphism rs4317882 of MPP7 in three additional independent Asian-descent samples (n= 2684). The association of rs4317882 reached the genome-wide significance in the meta-analysis of all available subjects (P(meta)= 4.58 × 10(-8), n= 4204). Site heterogeneity was observed, with a larger effect on spine than hip BMD. Further functional studies in a zebrafish model revealed that vertebral bone mass was lower in an mpp7 knock-down model compared with the wide-type (P= 9.64 × 10(-4), n= 21). In addition, MPP7 was found to have constitutive expression in human bone-derived cells during osteogenesis. Immunostaining of murine MC3T3-E1 cells revealed that the Mpp7 protein is localized in the plasma membrane and intracytoplasmic compartment of osteoblasts. In an assessment of the function of identified variants, an electrophoretic mobility shift assay demonstrated the binding of transcriptional factor GATA2 to the risk allele 'A' but not the 'G' allele of rs4317882. An mRNA expression study in human peripheral blood mononuclear cells confirmed that the low BMD-related allele 'A' of rs4317882 was associated with lower MPP7 expression (P= 9.07 × 10(-3), n= 135). Our data suggest a genetic and functional association of MPP7 with BMD variation.

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

    Directory of Open Access Journals (Sweden)

    Andreas Weinhäusel

    2012-06-01

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

  9. The tissue microarray OWL schema: An open-source tool for sharing tissue microarray data

    Directory of Open Access Journals (Sweden)

    Hyunseok P Kang

    2010-01-01

    Full Text Available Background: Tissue microarrays (TMAs are enormously useful tools for translational research, but incompatibilities in database systems between various researchers and institutions prevent the efficient sharing of data that could help realize their full potential. Resource Description Framework (RDF provides a flexible method to represent knowledge in triples, which take the form Subject- Predicate-Object. All data resources are described using Uniform Resource Identifiers (URIs, which are global in scope. We present an OWL (Web Ontology Language schema that expands upon the TMA data exchange specification to address this issue and assist in data sharing and integration. Methods: A minimal OWL schema was designed containing only concepts specific to TMA experiments. More general data elements were incorporated from predefined ontologies such as the NCI thesaurus. URIs were assigned using the Linked Data format. Results: We present examples of files utilizing the schema and conversion of XML data (similar to the TMA DES to OWL. Conclusion: By utilizing predefined ontologies and global unique identifiers, this OWL schema provides a solution to the limitations of XML, which represents concepts defined in a localized setting. This will help increase the utilization of tissue resources, facilitating collaborative translational research efforts.

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

    Science.gov (United States)

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

    2017-12-22

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

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

    Science.gov (United States)

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

    2012-06-08

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

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

    Science.gov (United States)

    2012-01-01

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

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

    Science.gov (United States)

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

    2014-02-01

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

  14. Development of a genotyping microarray for Usher syndrome.

    Science.gov (United States)

    Cremers, Frans P M; Kimberling, William J; Külm, Maigi; de Brouwer, Arjan P; van Wijk, Erwin; te Brinke, Heleen; Cremers, Cor W R J; Hoefsloot, Lies H; Banfi, Sandro; Simonelli, Francesca; Fleischhauer, Johannes C; Berger, Wolfgang; Kelley, Phil M; Haralambous, Elene; Bitner-Glindzicz, Maria; Webster, Andrew R; Saihan, Zubin; De Baere, Elfride; Leroy, Bart P; Silvestri, Giuliana; McKay, Gareth J; Koenekoop, Robert K; Millan, Jose M; Rosenberg, Thomas; Joensuu, Tarja; Sankila, Eeva-Marja; Weil, Dominique; Weston, Mike D; Wissinger, Bernd; Kremer, Hannie

    2007-02-01

    Usher syndrome, a combination of retinitis pigmentosa (RP) and sensorineural hearing loss with or without vestibular dysfunction, displays a high degree of clinical and genetic heterogeneity. Three clinical subtypes can be distinguished, based on the age of onset and severity of the hearing impairment, and the presence or absence of vestibular abnormalities. Thus far, eight genes have been implicated in the syndrome, together comprising 347 protein-coding exons. To improve DNA diagnostics for patients with Usher syndrome, we developed a genotyping microarray based on the arrayed primer extension (APEX) method. Allele-specific oligonucleotides corresponding to all 298 Usher syndrome-associated sequence variants known to date, 76 of which are novel, were arrayed. Approximately half of these variants were validated using original patient DNAs, which yielded an accuracy of >98%. The efficiency of the Usher genotyping microarray was tested using DNAs from 370 unrelated European and American patients with Usher syndrome. Sequence variants were identified in 64/140 (46%) patients with Usher syndrome type I, 45/189 (24%) patients with Usher syndrome type II, 6/21 (29%) patients with Usher syndrome type III and 6/20 (30%) patients with atypical Usher syndrome. The chip also identified two novel sequence variants, c.400C>T (p.R134X) in PCDH15 and c.1606T>C (p.C536S) in USH2A. The Usher genotyping microarray is a versatile and affordable screening tool for Usher syndrome. Its efficiency will improve with the addition of novel sequence variants with minimal extra costs, making it a very useful first-pass screening tool.

  15. Development of a genotyping microarray for Usher syndrome

    Science.gov (United States)

    Cremers, Frans P M; Kimberling, William J; Külm, Maigi; de Brouwer, Arjan P; van Wijk, Erwin; te Brinke, Heleen; Cremers, Cor W R J; Hoefsloot, Lies H; Banfi, Sandro; Simonelli, Francesca; Fleischhauer, Johannes C; Berger, Wolfgang; Kelley, Phil M; Haralambous, Elene; Bitner‐Glindzicz, Maria; Webster, Andrew R; Saihan, Zubin; De Baere, Elfride; Leroy, Bart P; Silvestri, Giuliana; McKay, Gareth J; Koenekoop, Robert K; Millan, Jose M; Rosenberg, Thomas; Joensuu, Tarja; Sankila, Eeva‐Marja; Weil, Dominique; Weston, Mike D; Wissinger, Bernd; Kremer, Hannie

    2007-01-01

    Background Usher syndrome, a combination of retinitis pigmentosa (RP) and sensorineural hearing loss with or without vestibular dysfunction, displays a high degree of clinical and genetic heterogeneity. Three clinical subtypes can be distinguished, based on the age of onset and severity of the hearing impairment, and the presence or absence of vestibular abnormalities. Thus far, eight genes have been implicated in the syndrome, together comprising 347 protein‐coding exons. Methods: To improve DNA diagnostics for patients with Usher syndrome, we developed a genotyping microarray based on the arrayed primer extension (APEX) method. Allele‐specific oligonucleotides corresponding to all 298 Usher syndrome‐associated sequence variants known to date, 76 of which are novel, were arrayed. Results Approximately half of these variants were validated using original patient DNAs, which yielded an accuracy of >98%. The efficiency of the Usher genotyping microarray was tested using DNAs from 370 unrelated European and American patients with Usher syndrome. Sequence variants were identified in 64/140 (46%) patients with Usher syndrome type I, 45/189 (24%) patients with Usher syndrome type II, 6/21 (29%) patients with Usher syndrome type III and 6/20 (30%) patients with atypical Usher syndrome. The chip also identified two novel sequence variants, c.400C>T (p.R134X) in PCDH15 and c.1606T>C (p.C536S) in USH2A. Conclusion The Usher genotyping microarray is a versatile and affordable screening tool for Usher syndrome. Its efficiency will improve with the addition of novel sequence variants with minimal extra costs, making it a very useful first‐pass screening tool. PMID:16963483

  16. Principles of gene microarray data analysis.

    Science.gov (United States)

    Mocellin, Simone; Rossi, Carlo Riccardo

    2007-01-01

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

  17. Detection of selected plant viruses by microarrays

    OpenAIRE

    HRABÁKOVÁ, Lenka

    2013-01-01

    The main aim of this master thesis was the simultaneous detection of four selected plant viruses ? Apple mosaic virus, Plum pox virus, Prunus necrotic ringspot virus and Prune harf virus, by microarrays. The intermediate step in the process of the detection was optimizing of multiplex polymerase chain reaction (PCR).

  18. LNA-modified isothermal oligonucleotide microarray for ...

    Indian Academy of Sciences (India)

    2014-10-20

    Oct 20, 2014 ... the advent of DNA microarray techniques (Lee et al. 2007). ... atoms of ribose to form a bicyclic ribosyl structure. It is the .... 532 nm and emission at 570 nm. The signal ..... sis and validation using real-time PCR. Nucleic Acids ...

  19. Gene Expression Analysis Using Agilent DNA Microarrays

    DEFF Research Database (Denmark)

    Stangegaard, Michael

    2009-01-01

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

  20. Microarrays (DNA Chips) for the Classroom Laboratory

    Science.gov (United States)

    Barnard, Betsy; Sussman, Michael; BonDurant, Sandra Splinter; Nienhuis, James; Krysan, Patrick

    2006-01-01

    We have developed and optimized the necessary laboratory materials to make DNA microarray technology accessible to all high school students at a fraction of both cost and data size. The primary component is a DNA chip/array that students "print" by hand and then analyze using research tools that have been adapted for classroom use. The…

  1. Comparing transformation methods for DNA microarray data

    NARCIS (Netherlands)

    Thygesen, Helene H.; Zwinderman, Aeilko H.

    2004-01-01

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

  2. Development of a cDNA microarray for the measurement of gene expression in the sheep scab mite Psoroptes ovis

    Directory of Open Access Journals (Sweden)

    Burgess Stewart TG

    2012-02-01

    Full Text Available Abstract Background Sheep scab is caused by the ectoparasitic mite Psoroptes ovis which initiates a profound cutaneous inflammatory response, leading to the development of the skin lesions which are characteristic of the disease. Existing control strategies rely upon injectable endectocides and acaricidal dips but concerns over residues, eco-toxicity and the development of acaricide resistance limit the sustainability of this approach. In order to identify alternative means of disease control, a deeper understanding of both the parasite and its interaction with the host are required. Methods Herein we describe the development and utilisation of an annotated P. ovis cDNA microarray containing 3,456 elements for the measurement of gene expression in this economically important ectoparasite. The array consists of 981 P. ovis EST sequences printed in triplicate along with 513 control elements. Array performance was validated through the analysis of gene expression differences between fed and starved P. ovis mites. Results Sequences represented on the array include homologues of major house dust mite allergens and tick salivary proteins, along with factors potentially involved in mite reproduction and xenobiotic metabolism. In order to validate the performance of this unique resource under biological conditions we used the array to analyse gene expression differences between fed and starved P. ovis mites. These analyses identified a number of house dust mite allergen homologues up-regulated in fed mites and P. ovis transcripts involved in stress responses, autophagy and chemosensory perception up-regulated in starved mites. Conclusion The P. ovis cDNA microarray described here has been shown to be both robust and reproducible and will enable future studies to analyse gene expression in this important ectoparasite.

  3. How the RNA isolation method can affect microRNA microarray results

    DEFF Research Database (Denmark)

    Podolska, Agnieszka; Kaczkowski, Bogumil; Litman, Thomas

    2011-01-01

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

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

    Science.gov (United States)

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

    2017-12-01

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

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

    Directory of Open Access Journals (Sweden)

    Nordborg Nicklas

    2009-10-01

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

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

    Science.gov (United States)

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

    2009-10-12

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

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

    Directory of Open Access Journals (Sweden)

    Sophie Depiereux

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

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

    Directory of Open Access Journals (Sweden)

    Jianping Hua

    2004-01-01

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

  9. Quantitative inference of dynamic regulatory pathways via microarray data

    Directory of Open Access Journals (Sweden)

    Chen Bor-Sen

    2005-03-01

    Full Text Available Abstract Background The cellular signaling pathway (network is one of the main topics of organismic investigations. The intracellular interactions between genes in a signaling pathway are considered as the foundation of functional genomics. Thus, what genes and how much they influence each other through transcriptional binding or physical interactions are essential problems. Under the synchronous measures of gene expression via a microarray chip, an amount of dynamic information is embedded and remains to be discovered. Using a systematically dynamic modeling approach, we explore the causal relationship among genes in cellular signaling pathways from the system biology approach. Results In this study, a second-order dynamic model is developed to describe the regulatory mechanism of a target gene from the upstream causality point of view. From the expression profile and dynamic model of a target gene, we can estimate its upstream regulatory function. According to this upstream regulatory function, we would deduce the upstream regulatory genes with their regulatory abilities and activation delays, and then link up a regulatory pathway. Iteratively, these regulatory genes are considered as target genes to trace back their upstream regulatory genes. Then we could construct the regulatory pathway (or network to the genome wide. In short, we can infer the genetic regulatory pathways from gene-expression profiles quantitatively, which can confirm some doubted paths or seek some unknown paths in a regulatory pathway (network. Finally, the proposed approach is validated by randomly reshuffling the time order of microarray data. Conclusion We focus our algorithm on the inference of regulatory abilities of the identified causal genes, and how much delay before they regulate the downstream genes. With this information, a regulatory pathway would be built up using microarray data. In the present study, two signaling pathways, i.e. circadian regulatory

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

    Science.gov (United States)

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

    2015-01-01

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

  11. Micro-Analyzer: automatic preprocessing of Affymetrix microarray data.

    Science.gov (United States)

    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

  12. Design issues in toxicogenomics using DNA microarray experiment

    International Nuclear Information System (INIS)

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

    2005-01-01

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

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

    Science.gov (United States)

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

  14. Development and evaluation of a high-throughput, low-cost genotyping platform based on oligonucleotide microarrays in rice

    Directory of Open Access Journals (Sweden)

    Liu Bin

    2008-05-01

    Full Text Available Abstract Background We report the development of a microarray platform for rapid and cost-effective genetic mapping, and its evaluation using rice as a model. In contrast to methods employing whole-genome tiling microarrays for genotyping, our method is based on low-cost spotted microarray production, focusing only on known polymorphic features. Results We have produced a genotyping microarray for rice, comprising 880 single feature polymorphism (SFP elements derived from insertions/deletions identified by aligning genomic sequences of the japonica cultivar Nipponbare and the indica cultivar 93-11. The SFPs were experimentally verified by hybridization with labeled genomic DNA prepared from the two cultivars. Using the genotyping microarrays, we found high levels of polymorphism across diverse rice accessions, and were able to classify all five subpopulations of rice with high bootstrap support. The microarrays were used for mapping of a gene conferring resistance to Magnaporthe grisea, the causative organism of rice blast disease, by quantitative genotyping of samples from a recombinant inbred line population pooled by phenotype. Conclusion We anticipate this microarray-based genotyping platform, based on its low cost-per-sample, to be particularly useful in applications requiring whole-genome molecular marker coverage across large numbers of individuals.

  15. Evaluation of an expanded microarray for detecting antibiotic resistance genes in a broad range of gram-negative bacterial pathogens.

    Science.gov (United States)

    Card, Roderick; Zhang, Jiancheng; Das, Priya; Cook, Charlotte; Woodford, Neil; Anjum, Muna F

    2013-01-01

    A microarray capable of detecting genes for resistance to 75 clinically relevant antibiotics encompassing 19 different antimicrobial classes was tested on 132 Gram-negative bacteria. Microarray-positive results correlated >91% with antimicrobial resistance phenotypes, assessed using British Society for Antimicrobial Chemotherapy clinical breakpoints; the overall test specificity was >83%. Microarray-positive results without a corresponding resistance phenotype matched 94% with PCR results, indicating accurate detection of genes present in the respective bacteria by microarray when expression was low or absent and, hence, undetectable by susceptibility testing. The low sensitivity and negative predictive values of the microarray results for identifying resistance to some antimicrobial resistance classes are likely due to the limited number of resistance genes present on the current microarray for those antimicrobial agents or to mutation-based resistance mechanisms. With regular updates, this microarray can be used for clinical diagnostics to help accurate therapeutic options to be taken following infection with multiple-antibiotic-resistant Gram-negative bacteria and prevent treatment failure.

  16. Detecting new microRNAs in human osteoarthritic chondrocytes identifies miR-3085 as a human, chondrocyte-selective, microRNA

    OpenAIRE

    Crowe, N.; Swingler, T.E.; Le, L.T.T.; Barter, M.J.; Wheeler, G.; Pais, H.; Donell, S.T.; Young, D.A.; Dalmay, T.; Clark, I.M.

    2016-01-01

    Summary Objective To use deep sequencing to identify novel microRNAs (miRNAs) in human osteoarthritic cartilage which have a functional role in chondrocyte phenotype or function. Design A small RNA library was prepared from human osteoarthritic primary chondrocytes using in-house adaptors and analysed by Illumina sequencing. Novel candidate miRNAs were validated by northern blot and qRT-PCR. Expression was measured in cartilage models. Targets of novel candidates were identified by microarray...

  17. An efficient algorithm for the stochastic simulation of the hybridization of DNA to microarrays

    Directory of Open Access Journals (Sweden)

    Laurenzi Ian J

    2009-12-01

    Full Text Available Abstract Background Although oligonucleotide microarray technology is ubiquitous in genomic research, reproducibility and standardization of expression measurements still concern many researchers. Cross-hybridization between microarray probes and non-target ssDNA has been implicated as a primary factor in sensitivity and selectivity loss. Since hybridization is a chemical process, it may be modeled at a population-level using a combination of material balance equations and thermodynamics. However, the hybridization reaction network may be exceptionally large for commercial arrays, which often possess at least one reporter per transcript. Quantification of the kinetics and equilibrium of exceptionally large chemical systems of this type is numerically infeasible with customary approaches. Results In this paper, we present a robust and computationally efficient algorithm for the simulation of hybridization processes underlying microarray assays. Our method may be utilized to identify the extent to which nucleic acid targets (e.g. cDNA will cross-hybridize with probes, and by extension, characterize probe robustnessusing the information specified by MAGE-TAB. Using this algorithm, we characterize cross-hybridization in a modified commercial microarray assay. Conclusions By integrating stochastic simulation with thermodynamic prediction tools for DNA hybridization, one may robustly and rapidly characterize of the selectivity of a proposed microarray design at the probe and "system" levels. Our code is available at http://www.laurenzi.net.

  18. On the classification techniques in data mining for microarray data classification

    Science.gov (United States)

    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.

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

    Science.gov (United States)

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

    2017-01-01

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

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

    Science.gov (United States)

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

    2017-06-06

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

  1. Immobilization Techniques for Microarray: Challenges and Applications

    Directory of Open Access Journals (Sweden)

    Satish Balasaheb Nimse

    2014-11-01

    Full Text Available The highly programmable positioning of molecules (biomolecules, nanoparticles, nanobeads, nanocomposites materials on surfaces has potential applications in the fields of biosensors, biomolecular electronics, and nanodevices. However, the conventional techniques including self-assembled monolayers fail to position the molecules on the nanometer scale to produce highly organized monolayers on the surface. The present article elaborates different techniques for the immobilization of the biomolecules on the surface to produce microarrays and their diagnostic applications. The advantages and the drawbacks of various methods are compared. This article also sheds light on the applications of the different technologies for the detection and discrimination of viral/bacterial genotypes and the detection of the biomarkers. A brief survey with 115 references covering the last 10 years on the biological applications of microarrays in various fields is also provided.

  2. Plasmonically amplified fluorescence bioassay with microarray format

    Science.gov (United States)

    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.

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

    Directory of Open Access Journals (Sweden)

    Alvaro Díaz-Badillo

    2014-04-01

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

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

    DEFF Research Database (Denmark)

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

    2011-01-01

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

  5. Tissue Microarray Analysis Applied to Bone Diagenesis

    OpenAIRE

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

    2017-01-01

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

  6. Chromosomal Localization of DNA Amplifications in Neuroblastoma Tumors Using cDNA Microarray Comparative Genomic Hybridization

    Directory of Open Access Journals (Sweden)

    Ben Beheshti

    2003-01-01

    Full Text Available Conventional comparative genomic hybridization (CGH profiling of neuroblastomas has identified many genomic aberrations, although the limited resolution has precluded a precise localization of sequences of interest within amplicons. To map high copy number genomic gains in clinically matched stage IV neuroblastomas, CGH analysis using a 19,200-feature cDNA microarray was used. A dedicated (freely available algorithm was developed for rapid in silico determination of chromosomal localizations of microarray cDNA targets, and for generation of an ideogram-type profile of copy number changes. Using these methodologies, novel gene amplifications undetectable by chromosome CGH were identified, and larger MYCN amplicon sizes (in one tumor up to 6 Mb than those previously reported in neuroblastoma were identified. The genes HPCAL1, LPIN1/KIAA0188, NAG, and NSE1/LOC151354 were found to be coamplified with MYCN. To determine whether stage IV primary tumors could be further subclassified based on their genomic copy number profiles, hierarchical clustering was performed. Cluster analysis of microarray CGH data identified three groups: 1 no amplifications evident, 2 a small MYCN amplicon as the only detectable imbalance, and 3 a large MYCN amplicon with additional gene amplifications. Application of CGH to cDNA microarray targets will help to determine both the variation of amplicon size and help better define amplification-dependent and independent pathways of progression in neuroblastoma.

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

    Science.gov (United States)

    Beaudet, Arthur L.

    2013-01-01

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

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

    NARCIS (Netherlands)

    Avila-Fernandez, A.; Cantalapiedra, D.; Aller, E.; Vallespin, E.; Aguirre-Lamban, J.; Blanco-Kelly, F.; Corton, M.; Riveiro-Alvarez, R.; Allikmets, R.; Trujillo-Tiebas, M.J.; Millan, J.M.; Cremers, F.P.M.; Ayuso, C.

    2010-01-01

    PURPOSE: Retinitis pigmentosa (RP) is a genetically heterogeneous disorder characterized by progressive loss of vision. The aim of this study was to identify the causative mutations in 272 Spanish families using a genotyping microarray. METHODS: 272 unrelated Spanish families, 107 with autosomal

  9. Transcription analysis of apple fruit development using cDNA microarrays

    NARCIS (Netherlands)

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

    2009-01-01

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

  10. Geiger mode avalanche photodiodes for microarray systems

    Science.gov (United States)

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

    2002-06-01

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

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

    Directory of Open Access Journals (Sweden)

    Piya Lahiry

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

  12. Screening for C3 deficiency in newborns using microarrays.

    Directory of Open Access Journals (Sweden)

    Magdalena Janzi

    Full Text Available BACKGROUND: Dried blood spot samples (DBSS from newborns are widely used in neonatal screening for selected metabolic diseases and diagnostic possibilities for additional disorders are continuously being evaluated. Primary immunodeficiency disorders comprise a group of more than one hundred diseases, several of which are fatal early in life. Yet, a majority of the patients are not diagnosed due to lack of high-throughput screening methods. METHODOLOGY/PRINCIPAL FINDINGS: We have previously developed a system using reverse phase protein microarrays for analysis of IgA levels in serum samples. In this study, we extended the applicability of the method to include determination of complement component C3 levels in eluates from DBSS collected at birth. Normal levels of C3 were readily detected in 269 DBSS from healthy newborns, while no C3 was detected in sera and DBSS from C3 deficient patients. CONCLUSIONS/SIGNIFICANCE: The findings suggest that patients with deficiencies of specific serum proteins can be identified by analysis of DBSS using reverse phase protein microarrays.

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

    Science.gov (United States)

    Kiiveri, Harri T

    2011-02-01

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

  14. Harshlight: a "corrective make-up" program for microarray chips

    Directory of Open Access Journals (Sweden)

    Wittkowski Knut M

    2005-12-01

    Full Text Available Abstract Background Microscopists are familiar with many blemishes that fluorescence images can have due to dust and debris, glass flaws, uneven distribution of fluids or surface coatings, etc. Microarray scans do show similar artifacts, which might affect subsequent analysis. Although all but the starkest blemishes are hard to find by the unaided eye, particularly in high-density oligonucleotide arrays (HDONAs, few tools are available to help with the detection of those defects. Results We develop a novel tool, Harshlight, for the automatic detection and masking of blemishes in HDONA microarray chips. Harshlight uses a combination of statistic and image processing methods to identify three different types of defects: localized blemishes affecting a few probes, diffuse defects affecting larger areas, and extended defects which may invalidate an entire chip. Conclusion We demonstrate the use of Harshlight can materially improve analysis of HDONA chips, especially for experiments with subtle changes between samples. For the widely used MAS5 algorithm, we show that compact blemishes cause an average of 8 gene expression values per chip to change by more than 50%, two of them by more than twofold; our masking algorithm restores about two thirds of this damage. Large-scale artifacts are successfully detected and eliminated.

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

    Directory of Open Access Journals (Sweden)

    Tewfik Ahmed H

    2006-01-01

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

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

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    Kiiveri Harri T

    2011-02-01

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

  17. Biocompatible Hydrogels for Microarray Cell Printing and Encapsulation

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    Akshata Datar

    2015-10-01

    Full Text Available Conventional drug screening processes are a time-consuming and expensive endeavor, but highly rewarding when they are successful. To identify promising lead compounds, millions of compounds are traditionally screened against therapeutic targets on human cells grown on the surface of 96-wells. These two-dimensional (2D cell monolayers are physiologically irrelevant, thus, often providing false-positive or false-negative results, when compared to cells grown in three-dimensional (3D structures such as hydrogel droplets. However, 3D cell culture systems are not easily amenable to high-throughput screening (HTS, thus inherently low throughput, and requiring relatively large volume for cell-based assays. In addition, it is difficult to control cellular microenvironments and hard to obtain reliable cell images due to focus position and transparency issues. To overcome these problems, miniaturized 3D cell cultures in hydrogels were developed via cell printing techniques where cell spots in hydrogels can be arrayed on the surface of glass slides or plastic chips by microarray spotters and cultured in growth media to form cells encapsulated 3D droplets for various cell-based assays. These approaches can dramatically reduce assay volume, provide accurate control over cellular microenvironments, and allow us to obtain clear 3D cell images for high-content imaging (HCI. In this review, several hydrogels that are compatible to microarray printing robots are discussed for miniaturized 3D cell cultures.

  18. Fuzzy C-means method for clustering microarray data.

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    Dembélé, Doulaye; Kastner, Philippe

    2003-05-22

    Clustering analysis of data from DNA microarray hybridization studies is essential for identifying biologically relevant groups of genes. Partitional clustering methods such as K-means or self-organizing maps assign each gene to a single cluster. However, these methods do not provide information about the influence of a given gene for the overall shape of clusters. Here we apply a fuzzy partitioning method, Fuzzy C-means (FCM), to attribute cluster membership values to genes. A major problem in applying the FCM method for clustering microarray data is the choice of the fuzziness parameter m. We show that the commonly used value m = 2 is not appropriate for some data sets, and that optimal values for m vary widely from one data set to another. We propose an empirical method, based on the distribution of distances between genes in a given data set, to determine an adequate value for m. By setting threshold levels for the membership values, genes which are tigthly associated to a given cluster can be selected. Using a yeast cell cycle data set as an example, we show that this selection increases the overall biological significance of the genes within the cluster. Supplementary text and Matlab functions are available at http://www-igbmc.u-strasbg.fr/fcm/

  19. Classification of mislabelled microarrays using robust sparse logistic regression.

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    Bootkrajang, Jakramate; Kabán, Ata

    2013-04-01

    Previous studies reported that labelling errors are not uncommon in microarray datasets. In such cases, the training set may become misleading, and the ability of classifiers to make reliable inferences from the data is compromised. Yet, few methods are currently available in the bioinformatics literature to deal with this problem. The few existing methods focus on data cleansing alone, without reference to classification, and their performance crucially depends on some tuning parameters. In this article, we develop a new method to detect mislabelled arrays simultaneously with learning a sparse logistic regression classifier. Our method may be seen as a label-noise robust extension of the well-known and successful Bayesian logistic regression classifier. To account for possible mislabelling, we formulate a label-flipping process as part of the classifier. The regularization parameter is automatically set using Bayesian regularization, which not only saves the computation time that cross-validation would take, but also eliminates any unwanted effects of label noise when setting the regularization parameter. Extensive experiments with both synthetic data and real microarray datasets demonstrate that our approach is able to counter the bad effects of labelling errors in terms of predictive performance, it is effective at identifying marker genes and simultaneously it detects mislabelled arrays to high accuracy. The code is available from http://cs.bham.ac.uk/∼jxb008. Supplementary data are available at Bioinformatics online.

  20. Gaussian mixture clustering and imputation of microarray data.

    Science.gov (United States)

    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.

  1. Classification across gene expression microarray studies

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    Kuner Ruprecht

    2009-12-01

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

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

    Science.gov (United States)

    2011-01-01

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

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

    Science.gov (United States)

    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.

  4. Immunochip analyses identify a novel risk locus for primary biliary cirrhosis at 13q14, multiple independent associations at four established risk loci and epistasis between 1p31 and 7q32 risk variants

    Science.gov (United States)

    Juran, Brian D.; Hirschfield, Gideon M.; Invernizzi, Pietro; Atkinson, Elizabeth J.; Li, Yafang; Xie, Gang; Kosoy, Roman; Ransom, Michael; Sun, Ye; Bianchi, Ilaria; Schlicht, Erik M.; Lleo, Ana; Coltescu, Catalina; Bernuzzi, Francesca; Podda, Mauro; Lammert, Craig; Shigeta, Russell; Chan, Landon L.; Balschun, Tobias; Marconi, Maurizio; Cusi, Daniele; Heathcote, E. Jenny; Mason, Andrew L.; Myers, Robert P.; Milkiewicz, Piotr; Odin, Joseph A.; Luketic, Velimir A.; Bacon, Bruce R.; Bodenheimer, Henry C.; Liakina, Valentina; Vincent, Catherine; Levy, Cynthia; Franke, Andre; Gregersen, Peter K.; Bossa, Fabrizio; Gershwin, M. Eric; deAndrade, Mariza; Amos, Christopher I.; Lazaridis, Konstantinos N.; Seldin, Michael F.; Siminovitch, Katherine A.

    2012-01-01

    To further characterize the genetic basis of primary biliary cirrhosis (PBC), we genotyped 2426 PBC patients and 5731 unaffected controls from three independent cohorts using a single nucleotide polymorphism (SNP) array (Immunochip) enriched for autoimmune disease risk loci. Meta-analysis of the genotype data sets identified a novel disease-associated locus near the TNFSF11 gene at 13q14, provided evidence for association at six additional immune-related loci not previously implicated in PBC and confirmed associations at 19 of 22 established risk loci. Results of conditional analyses also provided evidence for multiple independent association signals at four risk loci, with haplotype analyses suggesting independent SNP effects at the 2q32 and 16p13 loci, but complex haplotype driven effects at the 3q25 and 6p21 loci. By imputing classical HLA alleles from this data set, four class II alleles independently contributing to the association signal from this region were identified. Imputation of genotypes at the non-HLA loci also provided additional associations, but none with stronger effects than the genotyped variants. An epistatic interaction between the IL12RB2 risk locus at 1p31and the IRF5 risk locus at 7q32 was also identified and suggests a complementary effect of these loci in predisposing to disease. These data expand the repertoire of genes with potential roles in PBC pathogenesis that need to be explored by follow-up biological studies. PMID:22936693

  5. Development of a porcine skeletal muscle cDNA microarray: analysis of differential transcript expression in phenotypically distinct muscles

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    Stear Michael

    2003-03-01

    Full Text Available Abstract Background Microarray profiling has the potential to illuminate the molecular processes that govern the phenotypic characteristics of porcine skeletal muscles, such as hypertrophy or atrophy, and the expression of specific fibre types. This information is not only important for understanding basic muscle biology but also provides underpinning knowledge for enhancing the efficiency of livestock production. Results We report on the de novo development of a composite skeletal muscle cDNA microarray, comprising 5500 clones from two developmentally distinct cDNA libraries (longissimus dorsi of a 50-day porcine foetus and the gastrocnemius of a 3-day-old pig. Clones selected for the microarray assembly were of low to moderate abundance, as indicated by colony hybridisation. We profiled the differential expression of genes between the psoas (red muscle and the longissimus dorsi (white muscle, by co-hybridisation of Cy3 and Cy5 labelled cDNA derived from these two muscles. Results from seven microarray slides (replicates correctly identified genes that were expected to be differentially expressed, as well as a number of novel candidate regulatory genes. Quantitative real-time RT-PCR on selected genes was used to confirm the results from the microarray. Conclusion We have developed a porcine skeletal muscle cDNA microarray and have identified a number of candidate genes that could be involved in muscle phenotype determination, including several members of the casein kinase 2 signalling pathway.

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

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    Nobumasa Hitoshi

    2007-04-01

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

  7. Extending Immunological Profiling in the Gilthead Sea Bream, Sparus aurata, by Enriched cDNA Library Analysis, Microarray Design and Initial Studies upon the Inflammatory Response to PAMPs

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    Sebastian Boltaña

    2017-02-01

    Full Text Available This study describes the development and validation of an enriched oligonucleotide-microarray platform for Sparus aurata (SAQ to provide a platform for transcriptomic studies in this species. A transcriptome database was constructed by assembly of gilthead sea bream sequences derived from public repositories of mRNA together with reads from a large collection of expressed sequence tags (EST from two extensive targeted cDNA libraries characterizing mRNA transcripts regulated by both bacterial and viral challenge. The developed microarray was further validated by analysing monocyte/macrophage activation profiles after challenge with two Gram-negative bacterial pathogen-associated molecular patterns (PAMPs; lipopolysaccharide (LPS and peptidoglycan (PGN. Of the approximately 10,000 EST sequenced, we obtained a total of 6837 EST longer than 100 nt, with 3778 and 3059 EST obtained from the bacterial-primed and from the viral-primed cDNA libraries, respectively. Functional classification of contigs from the bacterial- and viral-primed cDNA libraries by Gene Ontology (GO showed that the top five represented categories were equally represented in the two libraries: metabolism (approximately 24% of the total number of contigs, carrier proteins/membrane transport (approximately 15%, effectors/modulators and cell communication (approximately 11%, nucleoside, nucleotide and nucleic acid metabolism (approximately 7.5% and intracellular transducers/signal transduction (approximately 5%. Transcriptome analyses using this enriched oligonucleotide platform identified differential shifts in the response to PGN and LPS in macrophage-like cells, highlighting responsive gene-cassettes tightly related to PAMP host recognition. As observed in other fish species, PGN is a powerful activator of the inflammatory response in S. aurata macrophage-like cells. We have developed and validated an oligonucleotide microarray (SAQ that provides a platform enriched for the study

  8. Extending Immunological Profiling in the Gilthead Sea Bream, Sparus aurata, by Enriched cDNA Library Analysis, Microarray Design and Initial Studies upon the Inflammatory Response to PAMPs.

    Science.gov (United States)

    Boltaña, Sebastian; Castellana, Barbara; Goetz, Giles; Tort, Lluis; Teles, Mariana; Mulero, Victor; Novoa, Beatriz; Figueras, Antonio; Goetz, Frederick W; Gallardo-Escarate, Cristian; Planas, Josep V; Mackenzie, Simon

    2017-02-03

    This study describes the development and validation of an enriched oligonucleotide-microarray platform for Sparus aurata (SAQ) to provide a platform for transcriptomic studies in this species. A transcriptome database was constructed by assembly of gilthead sea bream sequences derived from public repositories of mRNA together with reads from a large collection of expressed sequence tags (EST) from two extensive targeted cDNA libraries characterizing mRNA transcripts regulated by both bacterial and viral challenge. The developed microarray was further validated by analysing monocyte/macrophage activation profiles after challenge with two Gram-negative bacterial pathogen-associated molecular patterns (PAMPs; lipopolysaccharide (LPS) and peptidoglycan (PGN)). Of the approximately 10,000 EST sequenced, we obtained a total of 6837 EST longer than 100 nt, with 3778 and 3059 EST obtained from the bacterial-primed and from the viral-primed cDNA libraries, respectively. Functional classification of contigs from the bacterial- and viral-primed cDNA libraries by Gene Ontology (GO) showed that the top five represented categories were equally represented in the two libraries: metabolism (approximately 24% of the total number of contigs), carrier proteins/membrane transport (approximately 15%), effectors/modulators and cell communication (approximately 11%), nucleoside, nucleotide and nucleic acid metabolism (approximately 7.5%) and intracellular transducers/signal transduction (approximately 5%). Transcriptome analyses using this enriched oligonucleotide platform identified differential shifts in the response to PGN and LPS in macrophage-like cells, highlighting responsive gene-cassettes tightly related to PAMP host recognition. As observed in other fish species, PGN is a powerful activator of the inflammatory response in S. aurata macrophage-like cells. We have developed and validated an oligonucleotide microarray (SAQ) that provides a platform enriched for the study of gene

  9. Multi-gene detection and identification of mosquito-borne RNA viruses using an oligonucleotide microarray.

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    Nathan D Grubaugh

    Full Text Available BACKGROUND: Arthropod-borne viruses are important emerging pathogens world-wide. Viruses transmitted by mosquitoes, such as dengue, yellow fever, and Japanese encephalitis viruses, infect hundreds of millions of people and animals each year. Global surveillance of these viruses in mosquito vectors using molecular based assays is critical for prevention and control of the associated diseases. Here, we report an oligonucleotide DNA microarray design, termed ArboChip5.1, for multi-gene detection and identification of mosquito-borne RNA viruses from the genera Flavivirus (family Flaviviridae, Alphavirus (Togaviridae, Orthobunyavirus (Bunyaviridae, and Phlebovirus (Bunyaviridae. METHODOLOGY/PRINCIPAL FINDINGS: The assay utilizes targeted PCR amplification of three genes from each virus genus for electrochemical detection on a portable, field-tested microarray platform. Fifty-two viruses propagated in cell-culture were used to evaluate the specificity of the PCR primer sets and the ArboChip5.1 microarray capture probes. The microarray detected all of the tested viruses and differentiated between many closely related viruses such as members of the dengue, Japanese encephalitis, and Semliki Forest virus clades. Laboratory infected mosquitoes were used to simulate field samples and to determine the limits of detection. Additionally, we identified dengue virus type 3, Japanese encephalitis virus, Tembusu virus, Culex flavivirus, and a Quang Binh-like virus from mosquitoes collected in Thailand in 2011 and 2012. CONCLUSIONS/SIGNIFICANCE: We demonstrated that the described assay can be utilized in a comprehensive field surveillance program by the broad-range amplification and specific identification of arboviruses from infected mosquitoes. Furthermore, the microarray platform can be deployed in the field and viral RNA extraction to data analysis can occur in as little as 12 h. The information derived from the ArboChip5.1 microarray can help to establish

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

    Science.gov (United States)

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

    2013-01-01

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

  11. AffyMiner: mining differentially expressed genes and biological knowledge in GeneChip microarray data

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    Xia Yuannan

    2006-12-01

    Full Text Available Abstract Background DNA microarrays are a powerful tool for monitoring the expression of tens of thousands of genes simultaneously. With the advance of microarray technology, the challenge issue becomes how to analyze a large amount of microarray data and make biological sense of them. Affymetrix GeneChips are widely used microarrays, where a variety of statistical algorithms have been explored and used for detecting significant genes in the experiment. These methods rely solely on the quantitative data, i.e., signal intensity; however, qualitative data are also important parameters in detecting differentially expressed genes. Results AffyMiner is a tool developed for detecting differentially expressed genes in Affymetrix GeneChip microarray data and for associating gene annotation and gene ontology information with the genes detected. AffyMiner consists of the functional modules, GeneFinder for detecting significant genes in a treatment versus control experiment and GOTree for mapping genes of interest onto the Gene Ontology (GO space; and interfaces to run Cluster, a program for clustering analysis, and GenMAPP, a program for pathway analysis. AffyMiner has been used for analyzing the GeneChip data and the results were presented in several publications. Conclusion AffyMiner fills an important gap in finding differentially expressed genes in Affymetrix GeneChip microarray data. AffyMiner effectively deals with multiple replicates in the experiment and takes into account both quantitative and qualitative data in identifying significant genes. AffyMiner reduces the time and effort needed to compare data from multiple arrays and to interpret the possible biological implications associated with significant changes in a gene's expression.

  12. Normalization for triple-target microarray experiments

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    Magniette Frederic

    2008-04-01

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

  13. A microarray-based analysis of gametogenesis in two Portuguese populations of the European clam Ruditapes decussatus.

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    Joana Teixeira de Sousa

    Full Text Available The European clam, Ruditapes decussatus is a species with a high commercial importance in Portugal and other Southern European countries. Its production is almost exclusively based on natural recruitment, which is subject to high annual fluctuations. Increased knowledge of the natural reproductive cycle of R. decussatus and its molecular mechanisms would be particularly important in providing new highly valuable genomic information for better understanding the regulation of reproduction in this economically important aquaculture species. In this study, the transcriptomic bases of R. decussatus reproduction have been analysed using a custom oligonucleotide microarray representing 51,678 assembled contigs. Microarray analyses were performed in four gonadal maturation stages from two different Portuguese wild populations, characterized by different responses to spawning induction when used as progenitors in hatchery. A comparison between the two populations elucidated a specific pathway involved in the recognition signals and binding between the oocyte and components of the sperm plasma membrane. We suggest that this pathway can explain part of the differences in terms of spawning induction success between the two populations. In addition, sexes and reproductive stages were compared and a correlation between mRNA levels and gonadal area was investigated. The lists of differentially expressed genes revealed that sex explains most of the variance in gonadal gene expression. Additionally, genes like Foxl2, vitellogenin, condensing 2, mitotic apparatus protein p62, Cep57, sperm associated antigens 6, 16 and 17, motile sperm domain containing protein 2, sperm surface protein Sp17, sperm flagellar proteins 1 and 2 and dpy-30, were identified as being correlated with the gonad area and therefore supposedly with the number and/or the size of the gametes produced.

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

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    Jin Hee-Jeong

    2006-01-01

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

  15. Design of a covalently bonded glycosphingolipid microarray

    DEFF Research Database (Denmark)

    Arigi, Emma; Blixt, Klas Ola; Buschard, Karsten

    2012-01-01

    , the major classes of plant and fungal GSLs. In this work, a prototype "universal" GSL-based covalent microarray has been designed, and preliminary evaluation of its potential utility in assaying protein-GSL binding interactions investigated. An essential step in development involved the enzymatic release...... of the fatty acyl moiety of the ceramide aglycone of selected mammalian GSLs with sphingolipid N-deacylase (SCDase). Derivatization of the free amino group of a typical lyso-GSL, lyso-G(M1), with a prototype linker assembled from succinimidyl-[(N-maleimidopropionamido)-diethyleneglycol] ester and 2...

  16. Linking probe thermodynamics to microarray quantification

    International Nuclear Information System (INIS)

    Li, Shuzhao; Pozhitkov, Alexander; Brouwer, Marius

    2010-01-01

    Understanding the difference in probe properties holds the key to absolute quantification of DNA microarrays. So far, Langmuir-like models have failed to link sequence-specific properties to hybridization signals in the presence of a complex hybridization background. Data from washing experiments indicate that the post-hybridization washing has no major effect on the specifically bound targets, which give the final signals. Thus, the amount of specific targets bound to probes is likely determined before washing, by the competition against nonspecific binding. Our competitive hybridization model is a viable alternative to Langmuir-like models. (comment)

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

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    Maija Wolf

    2005-01-01

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

  18. Improving comparability between microarray probe signals by thermodynamic intensity correction

    DEFF Research Database (Denmark)

    Bruun, G. M.; Wernersson, Rasmus; Juncker, Agnieszka

    2007-01-01

    different probes. It is therefore of great interest to correct for the variation between probes. Much of this variation is sequence dependent. We demonstrate that a thermodynamic model for hybridization of either DNA or RNA to a DNA microarray, which takes the sequence-dependent probe affinities...... determination of transcription start sites for a subset of yeast genes. In another application, we identify present/absent calls for probes hybridized to the sequenced Escherichia coli strain O157:H7 EDL933. The model improves the correct calls from 85 to 95% relative to raw intensity measures. The model thus...... makes applications which depend on comparisons between probes aimed at different sections of the same target more reliable....

  19. Reverse phase protein microarray technology in traumatic brain injury.

    Science.gov (United States)

    Gyorgy, Andrea B; Walker, John; Wingo, Dan; Eidelman, Ofer; Pollard, Harvey B; Molnar, Andras; Agoston, Denes V

    2010-09-30

    Antibody based, high throughput proteomics technology represents an exciting new approach in understanding the pathobiologies of complex disorders such as cancer, stroke and traumatic brain injury. Reverse phase protein microarray (RPPA) can complement the classical methods based on mass spectrometry as a high throughput validation and quantification method. RPPA technology can address problematic issues, such as sample complexity, sensitivity, quantification, reproducibility and throughput, which are currently associated with mass spectrometry-based approaches. However, there are technical challenges, predominantly associated with the selection and use of antibodies, preparation and representation of samples and with analyzing and quantifying primary RPPA data. Here we present ways to identify and overcome some of the current issues associated with RPPA. We believe that using stringent quality controls, improved bioinformatics analysis and interpretation of primary RPPA data, this method will significantly contribute in generating new level of understanding about complex disorders at the level of systems biology. Published by Elsevier B.V.

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

    Directory of Open Access Journals (Sweden)

    Warden Craig H

    2010-07-01

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

  1. Design of an Enterobacteriaceae Pan-genome Microarray Chip

    DEFF Research Database (Denmark)

    Lukjancenko, Oksana; Ussery, David

    2010-01-01

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

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

    Science.gov (United States)

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

    2015-10-01

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

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

    Science.gov (United States)

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

    2017-01-01

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

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

    Science.gov (United States)

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

    2011-01-01

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

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

    International Nuclear Information System (INIS)

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

    2003-01-01

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

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

    Science.gov (United States)

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

    2014-01-01

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

  7. Comparing transformation methods for DNA microarray data

    Directory of Open Access Journals (Sweden)

    Zwinderman Aeilko H

    2004-06-01

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

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

    Science.gov (United States)

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

    2007-01-01

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

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

    Directory of Open Access Journals (Sweden)

    Christian Müller

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

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

    Directory of Open Access Journals (Sweden)

    George Stephen L

    2010-06-01

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

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

    Directory of Open Access Journals (Sweden)

    Brahmbhatt Sonal

    2008-11-01

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

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

    Science.gov (United States)

    Sitaraman, Kalavathy; Chatterjee, Deb K

    2011-01-01

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

  13. Rapid and reliable detection and identification of GM events using multiplex PCR coupled with oligonucleotide microarray.

    Science.gov (United States)

    Xu, Xiaodan; Li, Yingcong; Zhao, Heng; Wen, Si-yuan; Wang, Sheng-qi; Huang, Jian; Huang, Kun-lun; Luo, Yun-bo

    2005-05-18

    To devise a rapid and reliable method for the detection and identification of genetically modified (GM) events, we developed a multiplex polymerase chain reaction (PCR) coupled with a DNA microarray system simultaneously aiming at many targets in a single reaction. The system included probes for screening gene, species reference gene, specific gene, construct-specific gene, event-specific gene, and internal and negative control genes. 18S rRNA was combined with species reference genes as internal controls to assess the efficiency of all reactions and to eliminate false negatives. Two sets of the multiplex PCR system were used to amplify four and five targets, respectively. Eight different structure genes could be detected and identified simultaneously for Roundup Ready soybean in a single microarray. The microarray specificity was validated by its ability to discriminate two GM maizes Bt176 and Bt11. The advantages of this method are its high specificity and greatly reduced false-positives and -negatives. The multiplex PCR coupled with microarray technology presented here is a rapid and reliable tool for the simultaneous detection of GM organism ingredients.

  14. MULTI-K: accurate classification of microarray subtypes using ensemble k-means clustering

    Directory of Open Access Journals (Sweden)

    Ashlock Daniel

    2009-08-01

    Full Text Available Abstract Background Uncovering subtypes of disease from microarray samples has important clinical implications such as survival time and sensitivity of individual patients to specific therapies. Unsupervised clustering methods have been used to classify this type of data. However, most existing methods focus on clusters with compact shapes and do not reflect the geometric complexity of the high dimensional microarray clusters, which limits their performance. Results We present a cluster-number-based ensemble clustering algorithm, called MULTI-K, for microarray sample classification, which demonstrates remarkable accuracy. The method amalgamates multiple k-means runs by varying the number of clusters and identifies clusters that manifest the most robust co-memberships of elements. In addition to the original algorithm, we newly devised the entropy-plot to control the separation of singletons or small clusters. MULTI-K, unlike the simple k-means or other widely used methods, was able to capture clusters with complex and high-dimensional structures accurately. MULTI-K outperformed other methods including a recently developed ensemble clustering algorithm in tests with five simulated and eight real gene-expression data sets. Conclusion The geometric complexity of clusters should be taken into account for accurate classification of microarray data, and ensemble clustering applied to the number of clusters tackles the problem very well. The C++ code and the data sets tested are available from the authors.

  15. MULTI-K: accurate classification of microarray subtypes using ensemble k-means clustering.

    Science.gov (United States)

    Kim, Eun-Youn; Kim, Seon-Young; Ashlock, Daniel; Nam, Dougu

    2009-08-22

    Uncovering subtypes of disease from microarray samples has important clinical implications such as survival time and sensitivity of individual patients to specific therapies. Unsupervised clustering methods have been used to classify this type of data. However, most existing methods focus on clusters with compact shapes and do not reflect the geometric complexity of the high dimensional microarray clusters, which limits their performance. We present a cluster-number-based ensemble clustering algorithm, called MULTI-K, for microarray sample classification, which demonstrates remarkable accuracy. The method amalgamates multiple k-means runs by varying the number of clusters and identifies clusters that manifest the most robust co-memberships of elements. In addition to the original algorithm, we newly devised the entropy-plot to control the separation of singletons or small clusters. MULTI-K, unlike the simple k-means or other widely used methods, was able to capture clusters with complex and high-dimensional structures accurately. MULTI-K outperformed other methods including a recently developed ensemble clustering algorithm in tests with five simulated and eight real gene-expression data sets. The geometric complexity of clusters should be taken into account for accurate classification of microarray data, and ensemble clustering applied to the number of clusters tackles the problem very well. The C++ code and the data sets tested are available from the authors.

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

    Science.gov (United States)

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

    2011-06-01

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

  17. Fluorescent labeling of NASBA amplified tmRNA molecules for microarray applications

    Directory of Open Access Journals (Sweden)

    Kaplinski Lauris

    2009-05-01

    Full Text Available Abstract 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.

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

    Directory of Open Access Journals (Sweden)

    Li Cheng

    2008-05-01

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

  19. Ontology-based, Tissue MicroArray oriented, image centered tissue bank

    Directory of Open Access Journals (Sweden)

    Viti Federica

    2008-04-01

    Full Text Available Abstract 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.

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

    Science.gov (United States)

    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...

  1. Gene Expression Signature in Endemic Osteoarthritis by Microarray Analysis

    Directory of Open Access Journals (Sweden)

    Xi Wang

    2015-05-01

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

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

    Science.gov (United States)

    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

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

    Directory of Open Access Journals (Sweden)

    Gutierrez Laurent

    2010-10-01

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

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

    Science.gov (United States)

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

    2017-01-01

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

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

    Directory of Open Access Journals (Sweden)

    Hongyi Nie

    2017-10-01

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

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

    Science.gov (United States)

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

    2014-06-01

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

  7. A Critical Perspective On Microarray Breast Cancer Gene Expression Profiling

    NARCIS (Netherlands)

    Sontrop, H.M.J.

    2015-01-01

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

  8. The application of DNA microarrays in gene expression analysis

    NARCIS (Netherlands)

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

    2000-01-01

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

  9. Lipid Microarray Biosensor for Biotoxin Detection.

    Energy Technology Data Exchange (ETDEWEB)

    Singh, Anup K.; Throckmorton, Daniel J.; Moran-Mirabal, Jose C.; Edel, Joshua B.; Meyer, Grant D.; Craighead, Harold G.

    2006-05-01

    We present the use of micron-sized lipid domains, patterned onto planar substrates and within microfluidic channels, to assay the binding of bacterial toxins via total internal reflection fluorescence microscopy (TIRFM). The lipid domains were patterned using a polymer lift-off technique and consisted of ganglioside-populated DSPC:cholesterol supported lipid bilayers (SLBs). Lipid patterns were formed on the substrates by vesicle fusion followed by polymer lift-off, which revealed micron-sized SLBs containing either ganglioside GT1b or GM1. The ganglioside-populated SLB arrays were then exposed to either Cholera toxin subunit B (CTB) or Tetanus toxin fragment C (TTC). Binding was assayed on planar substrates by TIRFM down to 1 nM concentration for CTB and 100 nM for TTC. Apparent binding constants extracted from three different models applied to the binding curves suggest that binding of a protein to a lipid-based receptor is strongly affected by the lipid composition of the SLB and by the substrate on which the bilayer is formed. Patterning of SLBs inside microfluidic channels also allowed the preparation of lipid domains with different compositions on a single device. Arrays within microfluidic channels were used to achieve segregation and selective binding from a binary mixture of the toxin fragments in one device. The binding and segregation within the microfluidic channels was assayed with epifluorescence as proof of concept. We propose that the method used for patterning the lipid microarrays on planar substrates and within microfluidic channels can be easily adapted to proteins or nucleic acids and can be used for biosensor applications and cell stimulation assays under different flow conditions. KEYWORDS. Microarray, ganglioside, polymer lift-off, cholera toxin, tetanus toxin, TIRFM, binding constant.4

  10. cDNA microarray screening in food safety

    International Nuclear Information System (INIS)

    Roy, Sashwati; Sen, Chandan K.

    2006-01-01

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

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

    DEFF Research Database (Denmark)

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

    2012-01-01

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

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

    Science.gov (United States)

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

    2014-06-01

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

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

    Science.gov (United States)

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

    2010-12-03

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

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

    Science.gov (United States)

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

    2009-09-01

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

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

    Science.gov (United States)

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

    2005-01-01

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

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

    Science.gov (United States)

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

    2016-03-16

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

  17. Evaluation of gene importance in microarray data based upon probability of selection

    Directory of Open Access Journals (Sweden)

    Fu Li M

    2005-03-01

    Full Text Available Abstract Background Microarray devices permit a genome-scale evaluation of gene function. This technology has catalyzed biomedical research and development in recent years. As many important diseases can be traced down to the gene level, a long-standing research problem is to identify specific gene expression patterns linking to metabolic characteristics that contribute to disease development and progression. The microarray approach offers an expedited solution to this problem. However, it has posed a challenging issue to recognize disease-related genes expression patterns embedded in the microarray data. In selecting a small set of biologically significant genes for classifier design, the nature of high data dimensionality inherent in this problem creates substantial amount of uncertainty. Results Here we present a model for probability analysis of selected genes in order to determine their importance. Our contribution is that we show how to derive the P value of each selected gene in multiple gene selection trials based on different combinations of data samples and how to conduct a reliability analysis accordingly. The importance of a gene is indicated by its associated P value in that a smaller value implies higher information content from information theory. On the microarray data concerning the subtype classification of small round blue cell tumors, we demonstrate that the method is capable of finding the smallest set of genes (19 genes with optimal classification performance, compared with results reported in the literature. Conclusion In classifier design based on microarray data, the probability value derived from gene selection based on multiple combinations of data samples enables an effective mechanism for reducing the tendency of fitting local data particularities.

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

    Science.gov (United States)

    Kang, Suyeon; Song, Jongwoo

    2017-09-02

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

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

    Science.gov (United States)

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

    2016-01-15

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

  20. Microarray glycan profiling reveals algal fucoidan epitopes in diverse marine metazoans

    DEFF Research Database (Denmark)

    Asunción Salmeán, Armando; Hervé, Cécile; Jørgensen, Bodil

    2017-01-01

    Despite the biological importance and pharmacological potential of glycans from marine organisms, there are many unanswered questions regarding their distribution, function, and evolution. Here we describe microarray-based glycan profiling of a diverse selection of marine animals using antibodies...... raised against fucoidan isolated from a brown alga. We demonstrate the presence of two fucoidan epitopes in six animals belonging to three phyla including Porifera, Molusca, and Chordata. We studied the spatial distribution of these epitopes in Cliona celata ("boring sponge") and identified...

  1. Microarray-based genomic surveying of gene polymorphisms in Chlamydia trachomatis

    OpenAIRE

    Brunelle, Brian W; Nicholson, Tracy L; Stephens, Richard S

    2004-01-01

    By comparing two fully sequenced genomes of Chlamydia trachomatis using competitive hybridization on DNA microarrays, a logarithmic correlation was demonstrated between the signal ratio of the arrays and the 75-99% range of nucleotide identities of the genes. Variable genes within 14 uncharacterized strains of C. trachomatis were identified by array analysis and verified by DNA sequencing. These genes may be crucial for understanding chlamydial virulence and pathogenesis.

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

    DEFF Research Database (Denmark)

    Tan, Qihua; Thomassen, Mads; Burton, Mark

    2017-01-01

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

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

    Directory of Open Access Journals (Sweden)

    Gravelat Fabrice

    2010-09-01

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

  4. Transcriptomic analyses reveal novel genes with sexually dimorphic expression in the zebrafish gonad and brain.

    Directory of Open Access Journals (Sweden)

    Rajini Sreenivasan

    Full Text Available BACKGROUND: Our knowledge on zebrafish reproduction is very limited. We generated a gonad-derived cDNA microarray from zebrafish and used it to analyze large-scale gene expression profiles in adult gonads and other organs. METHODOLOGY/PRINCIPAL FINDINGS: We have identified 116638 gonad-derived zebrafish expressed sequence tags (ESTs, 21% of which were isolated in our lab. Following in silico normalization, we constructed a gonad-derived microarray comprising 6370 unique, full-length cDNAs from differentiating and adult gonads. Labeled targets from adult gonad, brain, kidney and 'rest-of-body' from both sexes were hybridized onto the microarray. Our analyses revealed 1366, 881 and 656 differentially expressed transcripts (34.7% novel that showed highest expression in ovary, testis and both gonads respectively. Hierarchical clustering showed correlation of the two gonadal transcriptomes and their similarities to those of the brains. In addition, we have identified 276 genes showing sexually dimorphic expression both between the brains and between the gonads. By in situ hybridization, we showed that the gonadal transcripts with the strongest array signal intensities were germline-expressed. We found that five members of the GTP-binding septin gene family, from which only one member (septin 4 has previously been implicated in reproduction in mice, were all strongly expressed in the gonads. CONCLUSIONS/SIGNIFICANCE: We have generated a gonad-derived zebrafish cDNA microarray and demonstrated its usefulness in identifying genes with sexually dimorphic co-expression in both the gonads and the brains. We have also provided the first evidence of large-scale differential gene expression between female and male brains of a teleost. Our microarray would be useful for studying gonad development, differentiation and function not only in zebrafish but also in related teleosts via cross-species hybridizations. Since several genes have been shown to play similar

  5. Array2BIO: from microarray expression data to functional annotation of co-regulated genes

    Directory of Open Access Journals (Sweden)

    Rasley Amy

    2006-06-01

    Full Text Available Abstract Background There are several isolated tools for partial analysis of microarray expression data. To provide an integrative, easy-to-use and automated toolkit for the analysis of Affymetrix microarray expression data we have developed Array2BIO, an application that couples several analytical methods into a single web based utility. Results Array2BIO converts raw intensities into probe expression values, automatically maps those to genes, and subsequently identifies groups of co-expressed genes using two complementary approaches: (1 comparative analysis of signal versus control and (2 clustering analysis of gene expression across different conditions. The identified genes are assigned to functional categories based on Gene Ontology classification and KEGG protein interaction pathways. Array2BIO reliably handles low-expressor genes and provides a set of statistical methods for quantifying expression levels, including Benjamini-Hochberg and Bonferroni multiple testing corrections. An automated interface with the ECR Browser provides evolutionary conservation analysis for the identified gene loci while the interconnection with Crème allows prediction of gene regulatory elements that underlie observed expression patterns. Conclusion We have developed Array2BIO – a web based tool for rapid comprehensive analysis of Affymetrix microarray expression data, which also allows users to link expression data to Dcode.org comparative genomics tools and integrates a system for translating co-expression data into mechanisms of gene co-regulation. Array2BIO is publicly available at http://array2bio.dcode.org.

  6. Microintaglio Printing for Soft Lithography-Based in Situ Microarrays

    Directory of Open Access Journals (Sweden)

    Manish Biyani

    2015-07-01

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

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

    Science.gov (United States)

    MacKinnon, Ruth N

    2018-01-01

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

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

    Science.gov (United States)

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

    2000-03-31

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

  9. Complete gene expression profiling of Saccharopolyspora erythraea using GeneChip DNA microarrays

    Directory of Open Access Journals (Sweden)

    Bordoni Roberta

    2007-11-01

    Full Text Available Abstract Background The Saccharopolyspora erythraea genome sequence, recently published, presents considerable divergence from those of streptomycetes in gene organization and function, confirming the remarkable potential of S. erythraea for producing many other secondary metabolites in addition to erythromycin. In order to investigate, at whole transcriptome level, how S. erythraea genes are modulated, a DNA microarray was specifically designed and constructed on the S. erythraea strain NRRL 2338 genome sequence, and the expression profiles of 6494 ORFs were monitored during growth in complex liquid medium. Results The transcriptional analysis identified a set of 404 genes, whose transcriptional signals vary during growth and characterize three distinct phases: a rapid growth until 32 h (Phase A; a growth slowdown until 52 h (Phase B; and another rapid growth phase from 56 h to 72 h (Phase C before the cells enter the stationary phase. A non-parametric statistical method, that identifies chromosomal regions with transcriptional imbalances, determined regional organization of transcription along the chromosome, highlighting differences between core and non-core regions, and strand specific patterns of expression. Microarray data were used to characterize the temporal behaviour of major functional classes and of all the gene clusters for secondary metabolism. The results confirmed that the ery cluster is up-regulated during Phase A and identified six additional clusters (for terpenes and non-ribosomal peptides that are clearly regulated in later phases. Conclusion The use of a S. erythraea DNA microarray improved specificity and sensitivity of gene expression analysis, allowing a global and at the same time detailed picture of how S. erythraea genes are modulated. This work underlines the importance of using DNA microarrays, coupled with an exhaustive statistical and bioinformatic analysis of the results, to understand the transcriptional

  10. Identification of a radiosensitivity signature using integrative metaanalysis of published microarray data for NCI-60 cancer cells

    Directory of Open Access Journals (Sweden)

    Kim Han

    2012-07-01

    Full Text Available Abstract Background In the postgenome era, a prediction of response to treatment could lead to better dose selection for patients in radiotherapy. To identify a radiosensitive gene signature and elucidate related signaling pathways, four different microarray experiments were reanalyzed before radiotherapy. Results Radiosensitivity profiling data using clonogenic assay and gene expression profiling data from four published microarray platforms applied to NCI-60 cancer cell panel were used. The survival fraction at 2 Gy (SF2, range from 0 to 1 was calculated as a measure of radiosensitivity and a linear regression model was applied to identify genes or a gene set with a correlation between expression and radiosensitivity (SF2. Radiosensitivity signature genes were identified using significant analysis of microarrays (SAM and gene set analysis was performed using a global test using linear regression model. Using the radiation-related signaling pathway and identified genes, a genetic network was generated. According to SAM, 31 genes were identified as common to all the microarray platforms and therefore a common radiosensitivity signature. In gene set analysis, functions in the cell cycle, DNA replication, and cell junction, including adherence and gap junctions were related to radiosensitivity. The integrin, VEGF, MAPK, p53, JAK-STAT and Wnt signaling pathways were overrepresented in radiosensitivity. Significant genes including ACTN1, CCND1, HCLS1, ITGB5, PFN2, PTPRC, RAB13, and WAS, which are adhesion-related molecules that were identified by both SAM and gene set analysis, and showed interaction in the genetic network with the integrin signaling pathway. Conclusions Integration of four different microarray experiments and gene selection using gene set analysis discovered possible target genes and pathways relevant to radiosensitivity. Our results suggested that the identified genes are candidates for radiosensitivity biomarkers and that

  11. 16S rRNA gene-based phylogenetic microarray for simultaneous identification of members of the genus Burkholderia.

    Science.gov (United States)

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

    2009-04-01

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

  12. Tissue Microarray Analysis Applied to Bone Diagenesis.

    Science.gov (United States)

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

    2017-01-04

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

  13. Transcriptome analysis of zebrafish embryogenesis using microarrays.

    Directory of Open Access Journals (Sweden)

    Sinnakaruppan Mathavan

    2005-08-01

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

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

    Science.gov (United States)

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

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

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

    NARCIS (Netherlands)

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

    2008-01-01

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

  16. Screening hybridomas for anabolic androgenic steroids by steroid analog antigen microarray.

    Science.gov (United States)

    Du, Hongwu; Chen, Guangyu; Bian, Yongzhong; Xing, Cenzan; Ding, Xue; Zhu, Mengliang; Xun, Yiping; Chen, Peng; Zhou, Yabin; Li, Shaoxu

    2015-01-01

    Currently, dozens of anabolic androgenic steroids (AAS) are forbidden in the World Anti-Doping Agency Prohibited List, however, despite extensive investigation, there are still lots of AAS without corresponding monoclonal antibodies. A steroid analog antigen microarray made up of ten AAS was fabricated to screen the hybridoma and it was found an original unsuccessful clone turned out to be a candidate anti-boldenone antibody, without any cross-reactions with endogenous AAS or 44 different AAS standard reference materials tested. Our findings suggested that steroid analog antigen microarray could be a promising tool to screen and characterize new applications of antibodies for structure analogs, and this also exhibits the potential to fast identify effective epitopes of hybridomas in a single assay.

  17. Comparing microarrays and next-generation sequencing technologies for microbial ecology research.

    Science.gov (United States)

    Roh, Seong Woon; Abell, Guy C J; Kim, Kyoung-Ho; Nam, Young-Do; Bae, Jin-Woo

    2010-06-01

    Recent advances in molecular biology have resulted in the application of DNA microarrays and next-generation sequencing (NGS) technologies to the field of microbial ecology. This review aims to examine the strengths and weaknesses of each of the methodologies, including depth and ease of analysis, throughput and cost-effectiveness. It also intends to highlight the optimal application of each of the individual technologies toward the study of a particular environment and identify potential synergies between the two main technologies, whereby both sample number and coverage can be maximized. We suggest that the efficient use of microarray and NGS technologies will allow researchers to advance the field of microbial ecology, and importantly, improve our understanding of the role of microorganisms in their various environments.

  18. Assessment of a direct hybridization microarray strategy for comprehensive monitoring of genetically modified organisms (GMOs).

    Science.gov (United States)

    Turkec, Aydin; Lucas, Stuart J; Karacanli, Burçin; Baykut, Aykut; Yuksel, Hakki

    2016-03-01

    Detection of GMO material in crop and food samples is the primary step in GMO monitoring and regulation, with the increasing number of GM events in the world market requiring detection solutions with high multiplexing capacity. In this study, we test the suitability of a high-density oligonucleotide microarray platform for direct, quantitative detection of GMOs found in the Turkish feed market. We tested 1830 different 60nt probes designed to cover the GM cassettes from 12 different GM cultivars (3 soya, 9 maize), as well as plant species-specific and contamination controls, and developed a data analysis method aiming to provide maximum throughput and sensitivity. The system was able specifically to identify each cultivar, and in 10/12 cases was sensitive enough to detect GMO DNA at concentrations of ⩽1%. These GMOs could also be quantified using the microarray, as their fluorescence signals increased linearly with GMO concentration. Copyright © 2015 Elsevier Ltd. All rights reserved.

  19. Integrating Multiple Microarray Data for Cancer Pathway Analysis Using Bootstrapping K-S Test

    Directory of Open Access Journals (Sweden)

    Bing Han

    2009-01-01

    Full Text Available Previous applications of microarray technology for cancer research have mostly focused on identifying genes that are differentially expressed between a particular cancer and normal cells. In a biological system, genes perform different molecular functions and regulate various biological processes via interactions with other genes thus forming a variety of complex networks. Therefore, it is critical to understand the relationship (e.g., interactions between genes across different types of cancer in order to gain insights into the molecular mechanisms of cancer. Here we propose an integrative method based on the bootstrapping Kolmogorov-Smirnov test and a large set of microarray data produced with various types of cancer to discover common molecular changes in cells from normal state to cancerous state. We evaluate our method using three key pathways related to cancer and demonstrate that it is capable of finding meaningful alterations in gene relations.

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

    Directory of Open Access Journals (Sweden)

    Qihua Tan

    2009-01-01

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

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

    International Nuclear Information System (INIS)

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

    2005-01-01

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

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

    Directory of Open Access Journals (Sweden)

    Daniel L Roden

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

  3. Gene selection and classification for cancer microarray data based on machine learning and similarity measures

    Directory of Open Access Journals (Sweden)

    Liu Qingzhong

    2011-12-01

    Full Text Available Abstract Background Microarray data have a high dimension of variables and a small sample size. In microarray data analyses, two important issues are how to choose genes, which provide reliable and good prediction for disease status, and how to determine the final gene set that is best for classification. Associations among genetic markers mean one can exploit information redundancy to potentially reduce classification cost in terms of time and money. Results To deal with redundant information and improve classification, we propose a gene selection method, Recursive Feature Addition, which combines supervised learning and statistical similarity measures. To determine the final optimal gene set for prediction and classification, we propose an algorithm, Lagging Prediction Peephole Optimization. By using six benchmark microarray gene expression data sets, we compared Recursive Feature Addition with recently developed gene selection methods: Support Vector Machine Recursive Feature Elimination, Leave-One-Out Calculation Sequential Forward Selection and several others. Conclusions On average, with the use of popular learning machines including Nearest Mean Scaled Classifier, Support Vector Machine, Naive Bayes Classifier and Random Forest, Recursive Feature Addition outperformed other methods. Our studies also showed that Lagging Prediction Peephole Optimization is superior to random strategy; Recursive Feature Addition with Lagging Prediction Peephole Optimization obtained better testing accuracies than the gene selection method varSelRF.

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

    Science.gov (United States)

    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+ (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.

  5. The effects of radiation on p53-mutated glioma cells using cDNA microarray technique

    International Nuclear Information System (INIS)

    Ngo, F.Q.H.; Hsiao, Y.-Y.H.

    2003-01-01

    Full text: In this study, we investigated the effects of 10-Gy irradiation on cell-cycle arrest, apoptosis and clonogenic death in the p53-mutated human U138MG (malignant glioblastoma) cell line. In order to evaluate time-dependent events in cellular responses to radiation, we did a time course study by incubating cells ranging from 0.5 to 48 hours after irradiation. Cell-cycle distribution and apoptosis were evaluated by flow cytometry using propidium iodide (PI) and annexin-V plus PI staining. Cell viability and proliferative capacity were studied by colony formation assay. Dual fluorescence cDNA microarray technique was used to examine the differential expression patterns of the irradiated cells. The cDNA microarray chips used contained DNA sequences corresponding to 12,814 human genes. From the flow cytometry data, it can be observed that radiation induced G2/M phase arrest and that late apoptosis was more evident following G2/M arrest. After 36 hours, some cells underwent senescence and the remains continued on with the cell cycle. Microarray analyses revealed changes in the expression of a small number of cell-cycle-related genes (p21, cyclin B1, etc.) and cell-death genes (tumor necrosis factors, DDB2, etc.) suggesting their involvement in radiation-induced cell-cycle arrest and apoptosis. In silico interpretations of the molecular mechanisms responsible for these radiation effects are in progress

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

    Directory of Open Access Journals (Sweden)

    Linlin Zhang

    Full Text Available 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.

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

    Directory of Open Access Journals (Sweden)

    Michael A Cook

    Full Text Available 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.

  8. Microarray MAPH: accurate array-based detection of relative copy number in genomic DNA.

    Science.gov (United States)

    Gibbons, Brian; Datta, Parikkhit; Wu, Ying; Chan, Alan; Al Armour, John

    2006-06-30

    Current methods for measurement of copy number do not combine all the desirable qualities of convenience, throughput, economy, accuracy and resolution. In this study, to improve the throughput associated with Multiplex Amplifiable Probe Hybridisation (MAPH) we aimed to develop a modification based on the 3-Dimensional, Flow-Through Microarray Platform from PamGene International. In this new method, electrophoretic analysis of amplified products is replaced with photometric analysis of a probed oligonucleotide array. Copy number analysis of hybridised probes is based on a dual-label approach by comparing the intensity of Cy3-labelled MAPH probes amplified from test samples co-hybridised with similarly amplified Cy5-labelled reference MAPH probes. The key feature of using a hybridisation-based end point with MAPH is that discrimination of amplified probes is based on sequence and not fragment length. In this study we showed that microarray MAPH measurement of PMP22 gene dosage correlates well with PMP22 gene dosage determined by capillary MAPH and that copy number was accurately reported in analyses of DNA from 38 individuals, 12 of which were known to have Charcot-Marie-Tooth disease type 1A (CMT1A). Measurement of microarray-based endpoints for MAPH appears to be of comparable accuracy to electrophoretic methods, and holds the prospect of fully exploiting the potential multiplicity of MAPH. The technology has the potential to simplify copy number assays for genes with a large number of exons, or of expanded sets of probes from dispersed genomic locations.

  9. Cell-Based Microarrays for In Vitro Toxicology

    Science.gov (United States)

    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.

  10. High throughput screening of starch structures using carbohydrate microarrays

    DEFF Research Database (Denmark)

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

    2016-01-01

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

  11. Microarray of DNA probes on carboxylate functional beads surface

    Institute of Scientific and Technical Information of China (English)

    黄承志; 李原芳; 黄新华; 范美坤

    2000-01-01

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

  12. Microarray of DNA probes on carboxylate functional beads surface

    Institute of Scientific and Technical Information of China (English)

    2000-01-01

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

  13. Rapid Diagnosis of Bacterial Meningitis Using a Microarray

    Directory of Open Access Journals (Sweden)

    Ren-Jy Ben

    2008-06-01

    Conclusion: The microarray method provides a more accurate and rapid diagnostic tool for bacterial meningitis compared to traditional culture methods. Clinical application of this new technique may reduce the potential risk of delay in treatment.

  14. Variance estimation in the analysis of microarray data

    KAUST Repository

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

    2009-01-01

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

  15. Oral tongue cancer gene expression profiling: Identification of novel potential prognosticators by oligonucleotide microarray analysis

    International Nuclear Information System (INIS)

    Estilo, Cherry L; Boyle, Jay O; Kraus, Dennis H; Patel, Snehal; Shaha, Ashok R; Wong, Richard J; Huryn, Joseph M; Shah, Jatin P; Singh, Bhuvanesh; O-charoenrat, Pornchai; Talbot, Simon; Socci, Nicholas D; Carlson, Diane L; Ghossein, Ronald; Williams, Tijaana; Yonekawa, Yoshihiro; Ramanathan, Yegnanarayana

    2009-01-01

    The present study is aimed at identifying potential candidate genes as prognostic markers in human oral tongue squamous cell carcinoma (SCC) by large scale gene expression profiling. The gene expression profile of patients (n=37) with oral tongue SCC were analyzed using Affymetrix HG-U95Av2 high-density oligonucleotide arrays. Patients (n=20) from which there were available tumor and matched normal mucosa were grouped into stage (early vs. late) and nodal disease (node positive vs. node negative) subgroups and genes differentially expressed in tumor vs. normal and between the subgroups were identified. Three genes, GLUT3, HSAL2, and PACE4, were selected for their potential biological significance in a larger cohort of 49 patients via quantitative real-time RT-PCR. Hierarchical clustering analyses failed to show significant segregation of patients. In patients (n=20) with available tumor and matched normal mucosa, 77 genes were found to be differentially expressed (P< 0.05) in the tongue tumor samples compared to their matched normal controls. Among the 45 over-expressed genes, MMP-1 encoding interstitial collagenase showed the highest level of increase (average: 34.18 folds). Using the criterion of two-fold or greater as overexpression, 30.6%, 24.5% and 26.5% of patients showed high levels of GLUT3, HSAL2 and PACE4, respectively. Univariate analyses demonstrated that GLUT3 over-expression correlated with depth of invasion (P<0.0001), tumor size (P=0.024), pathological stage (P=0.009) and recurrence (P=0.038). HSAL2 was positively associated with depth of invasion (P=0.015) and advanced T stage (P=0.047). In survival studies, only GLUT3 showed a prognostic value with disease-free (P=0.049), relapse-free (P=0.002) and overall survival (P=0.003). PACE4 mRNA expression failed to show correlation with any of the relevant parameters. The characterization of genes identified to be significant predictors of prognosis by oligonucleotide microarray and further validation by

  16. Can subtle changes in gene expression be consistently detected with different microarray platforms?

    Directory of Open Access Journals (Sweden)

    Kuiper Rowan

    2008-03-01

    Full Text Available Abstract Background The comparability of gene expression data generated with different microarray platforms is still a matter of concern. Here we address the performance and the overlap in the detection of differentially expressed genes for five different microarray platforms in a challenging biological context where differences in gene expression are few and subtle. Results Gene expression profiles in the hippocampus of five wild-type and five transgenic δC-doublecortin-like kinase mice were evaluated with five microarray platforms: Applied Biosystems, Affymetrix, Agilent, Illumina, LGTC home-spotted arrays. Using a fixed false discovery rate of 10% we detected surprising differences between the number of differentially expressed genes per platform. Four genes were selected by ABI, 130 by Affymetrix, 3,051 by Agilent, 54 by Illumina, and 13 by LGTC. Two genes were found significantly differentially expressed by all platforms and the four genes identified by the ABI platform were found by at least three other platforms. Quantitative RT-PCR analysis confirmed 20 out of 28 of the genes detected by two or more platforms and 8 out of 15 of the genes detected by Agilent only. We observed improved correlations between platforms when ranking the genes based on the significance level than with a fixed statistical cut-off. We demonstrate significant overlap in the affected gene sets identified by the different platforms, although biological processes were represented by only partially overlapping sets of genes. Aberrances in GABA-ergic signalling in the transgenic mice were consistently found by all platforms. Conclusion The different microarray platforms give partially complementary views on biological processes affected. Our data indicate that when analyzing samples with only subtle differences in gene expression the use of two different platforms might be more attractive than increasing the number of replicates. Commercial two-color platforms seem to

  17. Universal Reference RNA as a standard for microarray experiments

    Directory of Open Access Journals (Sweden)

    Fero Michael

    2004-03-01

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

  18. Microarrays for Universal Detection and Identification of Phytoplasmas

    DEFF Research Database (Denmark)

    Nicolaisen, Mogens; Nyskjold, Henriette; Bertaccini, Assunta

    2013-01-01

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

  19. Emerging use of gene expression microarrays in plant physiology.

    Science.gov (United States)

    Wullschleger, Stan D; Difazio, Stephen P

    2003-01-01

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

  20. Emerging Use of Gene Expression Microarrays in Plant Physiology

    Directory of Open Access Journals (Sweden)

    Stephen P. Difazio

    2006-04-01

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

  1. Plant-pathogen interactions: what microarray tells about it?

    Science.gov (United States)

    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,