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Sample records for genomic microarray analysis

  1. Digital microarray analysis for digital artifact genomics

    Science.gov (United States)

    Jaenisch, Holger; Handley, James; Williams, Deborah

    2013-06-01

    We implement a Spatial Voting (SV) based analogy of microarray analysis for digital gene marker identification in malware code sections. We examine a famous set of malware formally analyzed by Mandiant and code named Advanced Persistent Threat (APT1). APT1 is a Chinese organization formed with specific intent to infiltrate and exploit US resources. Manidant provided a detailed behavior and sting analysis report for the 288 malware samples available. We performed an independent analysis using a new alternative to the traditional dynamic analysis and static analysis we call Spatial Analysis (SA). We perform unsupervised SA on the APT1 originating malware code sections and report our findings. We also show the results of SA performed on some members of the families associated by Manidant. We conclude that SV based SA is a practical fast alternative to dynamics analysis and static analysis.

  2. Comparative analysis of genomic signal processing for microarray data clustering.

    Science.gov (United States)

    Istepanian, Robert S H; Sungoor, Ala; Nebel, Jean-Christophe

    2011-12-01

    Genomic signal processing is a new area of research that combines advanced digital signal processing methodologies for enhanced genetic data analysis. It has many promising applications in bioinformatics and next generation of healthcare systems, in particular, in the field of microarray data clustering. In this paper we present a comparative performance analysis of enhanced digital spectral analysis methods for robust clustering of gene expression across multiple microarray data samples. Three digital signal processing methods: linear predictive coding, wavelet decomposition, and fractal dimension are studied to provide a comparative evaluation of the clustering performance of these methods on several microarray datasets. The results of this study show that the fractal approach provides the best clustering accuracy compared to other digital signal processing and well known statistical methods.

  3. Whole genome microarray analysis, from neonatal blood cards

    Directory of Open Access Journals (Sweden)

    Hogan Michael E

    2009-07-01

    Full Text Available Abstract Background Neonatal blood, obtained from a heel stick and stored dry on paper cards, has been the standard for birth defects screening for 50 years. Such dried blood samples are used, primarily, for analysis of small-molecule analytes. More recently, the DNA complement of such dried blood cards has been used for targeted genetic testing, such as for single nucleotide polymorphism in cystic fibrosis. Expansion of such testing to include polygenic traits, and perhaps whole genome scanning, has been discussed as a formal possibility. However, until now the amount of DNA that might be obtained from such dried blood cards has been limiting, due to inefficient DNA recovery technology. Results A new technology is employed for efficient DNA release from a standard neonatal blood card. Using standard Guthrie cards, stored an average of ten years post-collection, about 1/40th of the air-dried neonatal blood specimen (two 3 mm punches was processed to obtain DNA that was sufficient in mass and quality for direct use in microarray-based whole genome scanning. Using that same DNA release technology, it is also shown that approximately 1/250th of the original purified DNA (about 1 ng could be subjected to whole genome amplification, thus yielding an additional microgram of amplified DNA product. That amplified DNA product was then used in microarray analysis and yielded statistical concordance of 99% or greater to the primary, unamplified DNA sample. Conclusion Together, these data suggest that DNA obtained from less than 10% of a standard neonatal blood specimen, stored dry for several years on a Guthrie card, can support a program of genome-wide neonatal genetic testing.

  4. A process for analysis of microarray comparative genomics hybridisation studies for bacterial genomes

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    Woodward Martin J

    2008-01-01

    Full Text Available Abstract Background Microarray based comparative genomic hybridisation (CGH experiments have been used to study numerous biological problems including understanding genome plasticity in pathogenic bacteria. Typically such experiments produce large data sets that are difficult for biologists to handle. Although there are some programmes available for interpretation of bacterial transcriptomics data and CGH microarray data for looking at genetic stability in oncogenes, there are none specifically to understand the mosaic nature of bacterial genomes. Consequently a bottle neck still persists in accurate processing and mathematical analysis of these data. To address this shortfall we have produced a simple and robust CGH microarray data analysis process that may be automated in the future to understand bacterial genomic diversity. Results The process involves five steps: cleaning, normalisation, estimating gene presence and absence or divergence, validation, and analysis of data from test against three reference strains simultaneously. Each stage of the process is described and we have compared a number of methods available for characterising bacterial genomic diversity, for calculating the cut-off between gene presence and absence or divergence, and shown that a simple dynamic approach using a kernel density estimator performed better than both established, as well as a more sophisticated mixture modelling technique. We have also shown that current methods commonly used for CGH microarray analysis in tumour and cancer cell lines are not appropriate for analysing our data. Conclusion After carrying out the analysis and validation for three sequenced Escherichia coli strains, CGH microarray data from 19 E. coli O157 pathogenic test strains were used to demonstrate the benefits of applying this simple and robust process to CGH microarray studies using bacterial genomes.

  5. Picky: oligo microarray design for large genomes

    National Research Council Canada - National Science Library

    Chou, Hui-Hsien; Hsia, An-Ping; Mooney, Denise L; Schnable, Patrick S

    2004-01-01

    Many large genomes are getting sequenced nowadays. Biologists are eager to start microarray analysis taking advantage of all known genes of a species, but existing microarray design tools were very inefficient for large genomes...

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

    Science.gov (United States)

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

    2008-07-03

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

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

    Directory of Open Access Journals (Sweden)

    Gadea Jose

    2008-07-01

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

  8. Microarray comparative genomic hybridisation analysis incorporating genomic organisation, and application to enterobacterial plant pathogens.

    Directory of Open Access Journals (Sweden)

    Leighton Pritchard

    2009-08-01

    Full Text Available Microarray comparative genomic hybridisation (aCGH provides an estimate of the relative abundance of genomic DNA (gDNA taken from comparator and reference organisms by hybridisation to a microarray containing probes that represent sequences from the reference organism. The experimental method is used in a number of biological applications, including the detection of human chromosomal aberrations, and in comparative genomic analysis of bacterial strains, but optimisation of the analysis is desirable in each problem domain.We present a method for analysis of bacterial aCGH data that encodes spatial information from the reference genome in a hidden Markov model. This technique is the first such method to be validated in comparisons of sequenced bacteria that diverge at the strain and at the genus level: Pectobacterium atrosepticum SCRI1043 (Pba1043 and Dickeya dadantii 3937 (Dda3937; and Lactococcus lactis subsp. lactis IL1403 and L. lactis subsp. cremoris MG1363. In all cases our method is found to outperform common and widely used aCGH analysis methods that do not incorporate spatial information. This analysis is applied to comparisons between commercially important plant pathogenic soft-rotting enterobacteria (SRE Pba1043, P. atrosepticum SCRI1039, P. carotovorum 193, and Dda3937.Our analysis indicates that it should not be assumed that hybridisation strength is a reliable proxy for sequence identity in aCGH experiments, and robustly extends the applicability of aCGH to bacterial comparisons at the genus level. Our results in the SRE further provide evidence for a dynamic, plastic 'accessory' genome, revealing major genomic islands encoding gene products that provide insight into, and may play a direct role in determining, variation amongst the SRE in terms of their environmental survival, host range and aetiology, such as phytotoxin synthesis, multidrug resistance, and nitrogen fixation.

  9. SIGMA: A System for Integrative Genomic Microarray Analysis of Cancer Genomes

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    Davies Jonathan J

    2006-12-01

    Full Text Available Abstract Background The prevalence of high resolution profiling of genomes has created a need for the integrative analysis of information generated from multiple methodologies and platforms. Although the majority of data in the public domain are gene expression profiles, and expression analysis software are available, the increase of array CGH studies has enabled integration of high throughput genomic and gene expression datasets. However, tools for direct mining and analysis of array CGH data are limited. Hence, there is a great need for analytical and display software tailored to cross platform integrative analysis of cancer genomes. Results We have created a user-friendly java application to facilitate sophisticated visualization and analysis such as cross-tumor and cross-platform comparisons. To demonstrate the utility of this software, we assembled array CGH data representing Affymetrix SNP chip, Stanford cDNA arrays and whole genome tiling path array platforms for cross comparison. This cancer genome database contains 267 profiles from commonly used cancer cell lines representing 14 different tissue types. Conclusion In this study we have developed an application for the visualization and analysis of data from high resolution array CGH platforms that can be adapted for analysis of multiple types of high throughput genomic datasets. Furthermore, we invite researchers using array CGH technology to deposit both their raw and processed data, as this will be a continually expanding database of cancer genomes. This publicly available resource, the System for Integrative Genomic Microarray Analysis (SIGMA of cancer genomes, can be accessed at http://sigma.bccrc.ca.

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

    OpenAIRE

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

    2008-01-01

    Abstract Background Understanding of genetic elements that contribute to key aspects of citrus biology will impact future improvements in this economically important crop. Global gene expression analysis demands microarray platforms with a high genome coverage. In the last years, genome-wide EST collections have been generated in citrus, opening the possibility to create new tools for functional genomics in this crop plant. Results We have designed and constructed a publicly available genome-...

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

    OpenAIRE

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

    2008-01-01

    Background Understanding of genetic elements that contribute to key aspects of citrus biology will impact future improvements in this economically important crop. Global gene expression analysis demands microarray platforms with a high genome coverage. In the last years, genome-wide EST collections have been generated in citrus, opening the possibility to create new tools for functional genomics in this crop plant. Results We have designed and constructed a publicly available genome-wide cDNA...

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

    OpenAIRE

    Martínez-Godoy, M. Ángeles; Mauri, Nuria; Juárez, José; Marqués, M. Carmen; Santiago, Julia; Forment, Javier; Gadea Vacas, José

    2008-01-01

    Background: Understanding of genetic elements that contribute to key aspects of citrus biology will impact future improvements in this economically important crop. Global gene expression analysis demands microarray platforms with a high genome coverage. In the last years, genomewide EST collections have been generated in citrus, opening the possibility to create new tools for functional genomics in this crop plant. Results: We have designed and constructed a publicly available ...

  13. Genomic Imbalances in Neonates With Birth Defects: High Detection Rates by Using Chromosomal Microarray Analysis

    Science.gov (United States)

    Lu, Xin-Yan; Phung, Mai T.; Shaw, Chad A.; Pham, Kim; Neil, Sarah E.; Patel, Ankita; Sahoo, Trilochan; Bacino, Carlos A.; Stankiewicz, Pawel; Lee Kang, Sung-Hae; Lalani, Seema; Chinault, A. Craig; Lupski, James R.; Cheung, Sau W.; Beaudet, Arthur L.

    2009-01-01

    OBJECTIVES Our aim was to determine the frequency of genomic imbalances in neonates with birth defects by using targeted array-based comparative genomic hybridization, also known as chromosomal microarray analysis. METHODS Between March 2006 and September 2007, 638 neonates with various birth defects were referred for chromosomal microarray analysis. Three consecutive chromosomal microarray analysis versions were used: bacterial artificial chromosome-based versions V5 and V6 and bacterial artificial chromosome emulated oligonucleotide-based version V6 Oligo. Each version had targeted but increasingly extensive genomic coverage and interrogated >150 disease loci with enhanced coverage in genomic rearrangement-prone pericentromeric and subtelomeric regions. RESULTS Overall, 109 (17.1%) patients were identified with clinically significant abnormalities with detection rates of 13.7%, 16.6%, and 19.9% on V5, V6, and V6 Oligo, respectively. The majority of these abnormalities would not be defined by using karyotype analysis. The clinically significant detection rates by use of chromosomal microarray analysis for various clinical indications were 66.7% for “possible chromosomal abnormality” ± “others” (other clinical indications), 33.3% for ambiguous genitalia ± others, 27.1% for dysmorphic features + multiple congenital anomalies ± others, 24.6% for dysmorphic features ± others, 21.8% for congenital heart disease ± others, 17.9% for multiple congenital anomalies ± others, and 9.5% for the patients referred for others that were different from the groups defined. In all, 16 (2.5%) patients had chromosomal aneuploidies, and 81 (12.7%) patients had segmental aneusomies including common microdeletion or microduplication syndromes and other genomic disorders. Chromosomal mosaicism was found in 12 (1.9%) neonates. CONCLUSIONS Chromosomal microarray analysis is a valuable clinical diagnostic tool that allows precise and rapid identification of genomic imbalances

  14. High resolution microarray comparative genomic hybridisation analysis using spotted oligonucleotides.

    NARCIS (Netherlands)

    Carvalho, B; Ouwerkerk, E; Meijer, G.A.; Ylstra, B.

    2004-01-01

    BACKGROUND: Currently, comparative genomic hybridisation array (array CGH) is the method of choice for studying genome wide DNA copy number changes. To date, either amplified representations of bacterial artificial chromosomes (BACs)/phage artificial chromosomes (PACs) or cDNAs have been spotted as

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

    Science.gov (United States)

    Yao, Jianchao; Chang, Chunqi; Salmi, Mari L; Hung, Yeung Sam; Loraine, Ann; Roux, Stanley J

    2008-06-18

    Currently, clustering with some form of correlation coefficient as the gene similarity metric has become a popular method for profiling genomic data. The Pearson correlation coefficient and the standard deviation (SD)-weighted correlation coefficient are the two most widely-used correlations as the similarity metrics in clustering microarray data. However, these two correlations are not optimal for analyzing replicated microarray data generated by most laboratories. An effective correlation coefficient is needed to provide statistically sufficient analysis of replicated microarray data. In this study, we describe a novel correlation coefficient, shrinkage correlation coefficient (SCC), that fully exploits the similarity between the replicated microarray experimental samples. The methodology considers both the number of replicates and the variance within each experimental group in clustering expression data, and provides a robust statistical estimation of the error of replicated microarray data. The value of SCC is revealed by its comparison with two other correlation coefficients that are currently the most widely-used (Pearson correlation coefficient and SD-weighted correlation coefficient) using statistical measures on both synthetic expression data as well as real gene expression data from Saccharomyces cerevisiae. Two leading clustering methods, hierarchical and k-means clustering were applied for the comparison. The comparison indicated that using SCC achieves better clustering performance. Applying SCC-based hierarchical clustering to the replicated microarray data obtained from germinating spores of the fern Ceratopteris richardii, we discovered two clusters of genes with shared expression patterns during spore germination. Functional analysis suggested that some of the genetic mechanisms that control germination in such diverse plant lineages as mosses and angiosperms are also conserved among ferns. This study shows that SCC is an alternative to the Pearson

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

    Directory of Open Access Journals (Sweden)

    Loraine Ann

    2008-06-01

    Full Text Available Abstract Background Currently, clustering with some form of correlation coefficient as the gene similarity metric has become a popular method for profiling genomic data. The Pearson correlation coefficient and the standard deviation (SD-weighted correlation coefficient are the two most widely-used correlations as the similarity metrics in clustering microarray data. However, these two correlations are not optimal for analyzing replicated microarray data generated by most laboratories. An effective correlation coefficient is needed to provide statistically sufficient analysis of replicated microarray data. Results In this study, we describe a novel correlation coefficient, shrinkage correlation coefficient (SCC, that fully exploits the similarity between the replicated microarray experimental samples. The methodology considers both the number of replicates and the variance within each experimental group in clustering expression data, and provides a robust statistical estimation of the error of replicated microarray data. The value of SCC is revealed by its comparison with two other correlation coefficients that are currently the most widely-used (Pearson correlation coefficient and SD-weighted correlation coefficient using statistical measures on both synthetic expression data as well as real gene expression data from Saccharomyces cerevisiae. Two leading clustering methods, hierarchical and k-means clustering were applied for the comparison. The comparison indicated that using SCC achieves better clustering performance. Applying SCC-based hierarchical clustering to the replicated microarray data obtained from germinating spores of the fern Ceratopteris richardii, we discovered two clusters of genes with shared expression patterns during spore germination. Functional analysis suggested that some of the genetic mechanisms that control germination in such diverse plant lineages as mosses and angiosperms are also conserved among ferns. Conclusion

  17. arrayCGHbase: an analysis platform for comparative genomic hybridization microarrays

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    Moreau Yves

    2005-05-01

    Full Text Available Abstract Background The availability of the human genome sequence as well as the large number of physically accessible oligonucleotides, cDNA, and BAC clones across the entire genome has triggered and accelerated the use of several platforms for analysis of DNA copy number changes, amongst others microarray comparative genomic hybridization (arrayCGH. One of the challenges inherent to this new technology is the management and analysis of large numbers of data points generated in each individual experiment. Results We have developed arrayCGHbase, a comprehensive analysis platform for arrayCGH experiments consisting of a MIAME (Minimal Information About a Microarray Experiment supportive database using MySQL underlying a data mining web tool, to store, analyze, interpret, compare, and visualize arrayCGH results in a uniform and user-friendly format. Following its flexible design, arrayCGHbase is compatible with all existing and forthcoming arrayCGH platforms. Data can be exported in a multitude of formats, including BED files to map copy number information on the genome using the Ensembl or UCSC genome browser. Conclusion ArrayCGHbase is a web based and platform independent arrayCGH data analysis tool, that allows users to access the analysis suite through the internet or a local intranet after installation on a private server. ArrayCGHbase is available at http://medgen.ugent.be/arrayCGHbase/.

  18. 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.

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

    Directory of Open Access Journals (Sweden)

    Fowler Katie E

    2009-08-01

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

  20. Analysis of the genome content of Lactococcus garvieae by genomic interspecies microarray hybridization

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    Gibello Alicia

    2010-03-01

    Full Text Available Abstract Background Lactococcus garvieae is a bacterial pathogen that affects different animal species in addition to humans. Despite the widespread distribution and emerging clinical significance of L. garvieae in both veterinary and human medicine, there is almost a complete lack of knowledge about the genetic content of this microorganism. In the present study, the genomic content of L. garvieae CECT 4531 was analysed using bioinformatics tools and microarray-based comparative genomic hybridization (CGH experiments. Lactococcus lactis subsp. lactis IL1403 and Streptococcus pneumoniae TIGR4 were used as reference microorganisms. Results The combination and integration of in silico analyses and in vitro CGH experiments, performed in comparison with the reference microorganisms, allowed establishment of an inter-species hybridization framework with a detection threshold based on a sequence similarity of ≥ 70%. With this threshold value, 267 genes were identified as having an analogue in L. garvieae, most of which (n = 258 have been documented for the first time in this pathogen. Most of the genes are related to ribosomal, sugar metabolism or energy conversion systems. Some of the identified genes, such as als and mycA, could be involved in the pathogenesis of L. garvieae infections. Conclusions In this study, we identified 267 genes that were potentially present in L. garvieae CECT 4531. Some of the identified genes could be involved in the pathogenesis of L. garvieae infections. These results provide the first insight into the genome content of L. garvieae.

  1. Experimental analysis of oligonucleotide microarray design criteria to detect deletions by comparative genomic hybridization

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    Moerman Donald G

    2008-10-01

    Full Text Available Abstract Background Microarray comparative genomic hybridization (CGH is currently one of the most powerful techniques to measure DNA copy number in large genomes. In humans, microarray CGH is widely used to assess copy number variants in healthy individuals and copy number aberrations associated with various diseases, syndromes and disease susceptibility. In model organisms such as Caenorhabditis elegans (C. elegans the technique has been applied to detect mutations, primarily deletions, in strains of interest. Although various constraints on oligonucleotide properties have been suggested to minimize non-specific hybridization and improve the data quality, there have been few experimental validations for CGH experiments. For genomic regions where strict design filters would limit the coverage it would also be useful to quantify the expected loss in data quality associated with relaxed design criteria. Results We have quantified the effects of filtering various oligonucleotide properties by measuring the resolving power for detecting deletions in the human and C. elegans genomes using NimbleGen microarrays. Approximately twice as many oligonucleotides are typically required to be affected by a deletion in human DNA samples in order to achieve the same statistical confidence as one would observe for a deletion in C. elegans. Surprisingly, the ability to detect deletions strongly depends on the oligonucleotide 15-mer count, which is defined as the sum of the genomic frequency of all the constituent 15-mers within the oligonucleotide. A similarity level above 80% to non-target sequences over the length of the probe produces significant cross-hybridization. We recommend the use of a fairly large melting temperature window of up to 10°C, the elimination of repeat sequences, the elimination of homopolymers longer than 5 nucleotides, and a threshold of -1 kcal/mol on the oligonucleotide self-folding energy. We observed very little difference in data

  2. Comprehensive Analysis of Prokaryotes in Environmental Water Using DNA Microarray Analysis and Whole Genome Amplification

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    Norihisa Ishii

    2013-10-01

    Full Text Available The microflora in environmental water consists of a high density and diversity of bacterial species that form the foundation of the water ecosystem. Because the majority of these species cannot be cultured in vitro, a different approach is needed to identify prokaryotes in environmental water. A novel DNA microarray was developed as a simplified detection protocol. Multiple DNA probes were designed against each of the 97,927 sequences in the DNA Data Bank of Japan and mounted on a glass chip in duplicate. Evaluation of the microarray was performed using the DNA extracted from one liter of environmental water samples collected from seven sites in Japan. The extracted DNA was uniformly amplified using whole genome amplification (WGA, labeled with Cy3-conjugated 16S rRNA specific primers and hybridized to the microarray. The microarray successfully identified soil bacteria and environment-specific bacteria clusters. The DNA microarray described herein can be a useful tool in evaluating the diversity of prokaryotes and assessing environmental changes such as global warming.

  3. Application of functional genomics to the chimeric mouse model of HCV infection: optimization of microarray protocols and genomics analysis

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    Smith Maria W

    2006-05-01

    Full Text Available Abstract Background Many model systems of human viral disease involve human-mouse chimeric tissue. One such system is the recently developed SCID-beige/Alb-uPA mouse model of hepatitis C virus (HCV infection which involves a human-mouse chimeric liver. The use of functional genomics to study HCV infection in these chimeric tissues is complicated by the potential cross-hybridization of mouse mRNA on human oligonucleotide microarrays. To identify genes affected by mouse liver mRNA hybridization, mRNA from identical human liver samples labeled with either Cy3 or Cy5 was compared in the presence and absence of known amounts of mouse liver mRNA labeled in only one dye. Results The results indicate that hybridization of mouse mRNA to the corresponding human gene probe on Agilent Human 22 K oligonucleotide microarray does occur. The number of genes affected by such cross-hybridization was subsequently reduced to approximately 300 genes both by increasing the hybridization temperature and using liver samples which contain at least 80% human tissue. In addition, Real Time quantitative RT-PCR using human specific probes was shown to be a valid method to verify the expression level in human cells of known cross-hybridizing genes. Conclusion The identification of genes affected by cross-hybridization of mouse liver RNA on human oligonucleotide microarrays makes it feasible to use functional genomics approaches to study the chimeric SCID-beige/Alb-uPA mouse model of HCV infection. This approach used to study cross-species hybridization on oligonucleotide microarrays can be adapted to other chimeric systems of viral disease to facilitate selective analysis of human gene expression.

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

    NARCIS (Netherlands)

    Skinner, M.; Robertson, L.B.; Tempest, H.G.; Langley, E.J.; Ioannou, D.; Fowler, K.E.; Crooijmans, R.P.M.A.

    2009-01-01

    Background: The availability of the complete chicken (Gallus gallus) genome sequence as well as a large number of chicken probes for fluorescent in-situ hybridization (FISH) and microarray resources facilitate comparative genomic studies between chicken and other bird species. In a previous study, w

  5. Genome-wide microarray expression and genomic alterations by array-CGH analysis in neuroblastoma stem-like cells.

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    Raquel Ordóñez

    Full Text Available Neuroblastoma has a very diverse clinical behaviour: from spontaneous regression to a very aggressive malignant progression and resistance to chemotherapy. This heterogeneous clinical behaviour might be due to the existence of Cancer Stem Cells (CSC, a subpopulation within the tumor with stem-like cell properties: a significant proliferation capacity, a unique self-renewal capacity, and therefore, a higher ability to form new tumors. We enriched the CSC-like cell population content of two commercial neuroblastoma cell lines by the use of conditioned cell culture media for neurospheres, and compared genomic gains and losses and genome expression by array-CGH and microarray analysis, respectively (in CSC-like versus standard tumor cells culture. Despite the array-CGH did not show significant differences between standard and CSC-like in both analyzed cell lines, the microarray expression analysis highlighted some of the most relevant biological processes and molecular functions that might be responsible for the CSC-like phenotype. Some signalling pathways detected seem to be involved in self-renewal of normal tissues (Wnt, Notch, Hh and TGF-β and contribute to CSC phenotype. We focused on the aberrant activation of TGF-β and Hh signalling pathways, confirming the inhibition of repressors of TGF-β pathway, as SMAD6 and SMAD7 by RT-qPCR. The analysis of the Sonic Hedgehog pathway showed overexpression of PTCH1, GLI1 and SMO. We found overexpression of CD133 and CD15 in SIMA neurospheres, confirming that this cell line was particularly enriched in stem-like cells. This work shows a cross-talk among different pathways in neuroblastoma and its importance in CSC-like cells.

  6. Microarray Genomic Systems Development

    Science.gov (United States)

    2008-06-01

    D Canada Contract Report DRDC Suffield CR 2009-145 June 2008 V. Lam, M. Crichton , T. Dickinson Laing, and D.C. Mah Canada West Biosciences Inc...Genomic Systems Development V. Lam, M. Crichton , T. Dickinson Laing, and D.C. Mah Canada West Biosciences Inc. Canada West Biosciences Inc. 5429... Crichton , M.; Dickinson Laing, T.; Mah, D.C.; DRDC Suffield CR 2009- 145; Defence R&D Canada – Suffield; June 2008. Introduction: Conventional

  7. Surface ligation-based resonance light scattering analysis of methylated genomic DNA on a microarray platform.

    Science.gov (United States)

    Ma, Lan; Lei, Zhen; Liu, Xia; Liu, Dianjun; Wang, Zhenxin

    2016-05-10

    DNA methylation is a crucial epigenetic modification and is closely related to tumorigenesis. Herein, a surface ligation-based high throughput method combined with bisulfite treatment is developed for analysis of methylated genomic DNA. In this method, a DNA microarray is employed as a reaction platform, and resonance light scattering (RLS) of nanoparticles is used as the detection principle. The specificity stems from allele-specific ligation of Taq DNA ligase, which is further enhanced by improving the fidelity of Taq DNA ligase in a heterogeneous reaction. Two amplification techniques, rolling circle amplification (RCA) and silver enhancement, are employed after the ligation reaction and a gold nanoparticle (GNP) labeling procedure is used to amplify the signal. As little as 0.01% methylated DNA (i.e. 2 pmol L(-1)) can be distinguished from the cocktail of methylated and unmethylated DNA by the proposed method. More importantly, this method shows good accuracy and sensitivity in profiling the methylation level of genomic DNA of three selected colonic cancer cell lines. This strategy provides a high throughput alternative with reasonable sensitivity and resolution for cancer study and diagnosis.

  8. An analysis of the use of genomic DNA as a universal reference in two channel DNA microarrays

    Directory of Open Access Journals (Sweden)

    Kapur Vivek

    2005-05-01

    Full Text Available Abstract Background DNA microarray is an invaluable tool for gene expression explorations. In the two-dye microarray, fluorescence intensities of two samples, each labeled with a different dye, are compared after hybridization. To compare a large number of samples, the 'reference design' is widely used, in which all RNA samples are hybridized to a common reference. Genomic DNA is an attractive candidate for use as a universal reference, especially for bacterial systems with a low percentage of non-coding sequences. However, genomic DNA, comprising of both the sense and anti-sense strands, is unlike the single stranded cDNA usually used in microarray hybridizations. The presence of the antisense strand in the 'reference' leads to reactions between complementary labeled strands in solution and may cause the assay result to deviate from true values. Results We have developed a mathematical model to predict the validity of using genomic DNA as a reference in the microarray assay. The model predicts that the assay can accurately estimate relative concentrations for a wide range of initial cDNA concentrations. Experimental results of DNA microarray assay using genomic DNA as a reference correlated well to those obtained by a direct hybridization between two cDNA samples. The model predicts that the initial concentrations of labeled genomic DNA strands and immobilized strands, and the hybridization time do not significantly affect the assay performance. At low values of the rate constant for hybridization between immobilized and mobile strands, the assay performance varies with the hybridization time and initial cDNA concentrations. For the case where a microarray with immobilized single strands is used, results from hybridizations using genomic DNA as a reference will correspond to true ratios under all conditions. Conclusion Simulation using the mathematical model, and the experimental study presented here show the potential utility of microarray

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

    Science.gov (United States)

    Oikawa, Masahiro; Yoshiura, Koh-ichiro; Kondo, Hisayoshi; Miura, Shiro; Nagayasu, Takeshi; Nakashima, Masahiro

    2011-12-07

    It has been postulated that ionizing radiation induces breast cancers among atomic bomb (A-bomb) survivors. We have reported a higher incidence of HER2 and C-MYC oncogene amplification in breast cancers from A-bomb survivors. The purpose of this study was to clarify the effect of A-bomb radiation exposure on genomic instability (GIN), which is an important hallmark of carcinogenesis, in archival formalin-fixed paraffin-embedded (FFPE) tissues of breast cancer by using microarray-comparative genomic hybridization (aCGH). Tumor DNA was extracted from FFPE tissues of invasive ductal cancers from 15 survivors who were exposed at 1.5 km or less from the hypocenter and 13 calendar year-matched non-exposed patients followed by aCGH analysis using a high-density oligonucleotide microarray. The total length of copy number aberrations (CNA) was used as an indicator of GIN, and correlation with clinicopathological factors were statistically tested. The mean of the derivative log ratio spread (DLRSpread), which estimates the noise by calculating the spread of log ratio differences between consecutive probes for all chromosomes, was 0.54 (range, 0.26 to 1.05). The concordance of results between aCGH and fluorescence in situ hybridization (FISH) for HER2 gene amplification was 88%. The incidence of HER2 amplification and histological grade was significantly higher in the A-bomb survivors than control group (P = 0.04, respectively). The total length of CNA tended to be larger in the A-bomb survivors (P = 0.15). Correlation analysis of CNA and clinicopathological factors revealed that DLRSpread was negatively correlated with that significantly (P = 0.034, r = -0.40). Multivariate analysis with covariance revealed that the exposure to A-bomb was a significant (P = 0.005) independent factor which was associated with larger total length of CNA of breast cancers. Thus, archival FFPE tissues from A-bomb survivors are useful for genome-wide aCGH analysis. Our results suggested that A

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

    Directory of Open Access Journals (Sweden)

    Oikawa Masahiro

    2011-12-01

    Full Text Available Abstract Background It has been postulated that ionizing radiation induces breast cancers among atomic bomb (A-bomb survivors. We have reported a higher incidence of HER2 and C-MYC oncogene amplification in breast cancers from A-bomb survivors. The purpose of this study was to clarify the effect of A-bomb radiation exposure on genomic instability (GIN, which is an important hallmark of carcinogenesis, in archival formalin-fixed paraffin-embedded (FFPE tissues of breast cancer by using microarray-comparative genomic hybridization (aCGH. Methods Tumor DNA was extracted from FFPE tissues of invasive ductal cancers from 15 survivors who were exposed at 1.5 km or less from the hypocenter and 13 calendar year-matched non-exposed patients followed by aCGH analysis using a high-density oligonucleotide microarray. The total length of copy number aberrations (CNA was used as an indicator of GIN, and correlation with clinicopathological factors were statistically tested. Results The mean of the derivative log ratio spread (DLRSpread, which estimates the noise by calculating the spread of log ratio differences between consecutive probes for all chromosomes, was 0.54 (range, 0.26 to 1.05. The concordance of results between aCGH and fluorescence in situ hybridization (FISH for HER2 gene amplification was 88%. The incidence of HER2 amplification and histological grade was significantly higher in the A-bomb survivors than control group (P = 0.04, respectively. The total length of CNA tended to be larger in the A-bomb survivors (P = 0.15. Correlation analysis of CNA and clinicopathological factors revealed that DLRSpread was negatively correlated with that significantly (P = 0.034, r = -0.40. Multivariate analysis with covariance revealed that the exposure to A-bomb was a significant (P = 0.005 independent factor which was associated with larger total length of CNA of breast cancers. Conclusions Thus, archival FFPE tissues from A-bomb survivors are useful for

  11. Analysis Method of Citrus Genome Microarray%浅谈柑橘基因组芯片分析方法

    Institute of Scientific and Technical Information of China (English)

    杨雪莲; 贝学军; 朱友娟

    2012-01-01

    cDNA microarray and oligonucleotide microarray are currently used for analysing citrus gene expression profile.The data analysis of genome microarray include data preprocessing,screening differential expression genes,and further analysing the differential expression genes.Through data analysis and integration of biological information,this paper studies the plant physiological changes.%指出了cDNA芯片和寡核苷酸芯片是目前用于柑橘基因表达谱分析的方法,基因组芯片数据分析主要包括数据预处理,筛选差异基因,差异基因再进一步分析。通过数据分析及整合样点的生物学信息,研究了植物生理变化。

  12. Comparative genomic analysis of Acidithiobacillus ferrooxidans strains using the A. ferrooxidans ATCC 23270 whole-genome oligonucleotide microarray.

    Science.gov (United States)

    Luo, Hailang; Shen, Li; Yin, Huaqun; Li, Qian; Chen, Qijiong; Luo, Yanjie; Liao, Liqin; Qiu, Guanzhou; Liu, Xueduan

    2009-05-01

    Acidithiobacillus ferrooxidans is an important microorganism used in biomining operations for metal recovery. Whole-genomic diversity analysis based on the oligonucleotide microarray was used to analyze the gene content of 12 strains of A. ferrooxidans purified from various mining areas in China. Among the 3100 open reading frames (ORFs) on the slides, 1235 ORFs were absent in at least 1 strain of bacteria and 1385 ORFs were conserved in all strains. The hybridization results showed that these strains were highly diverse from a genomic perspective. The hybridization results of 4 major functional gene categories, namely electron transport, carbon metabolism, extracellular polysaccharides, and detoxification, were analyzed. Based on the hybridization signals obtained, a phylogenetic tree was built to analyze the evolution of the 12 tested strains, which indicated that the geographic distribution was the main factor influencing the strain diversity of these strains. Based on the hybridization signals of genes associated with bioleaching, another phylogenetic tree showed an evolutionary relationship from which the co-relation between the clustering of specific genes and geochemistry could be observed. The results revealed that the main factor was geochemistry, among which the following 6 factors were the most important: pH, Mg, Cu, S, Fe, and Al.

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

    Directory of Open Access Journals (Sweden)

    Cannon Steven

    2009-08-01

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

  14. Combining microarrays and genetic analysis

    NARCIS (Netherlands)

    Alberts, Rudi; Fu, Jingyuan; Swertz, Morris A.; Lubbers, L. Alrik; Albers, Casper J.; Jansen, Ritsert C.

    2005-01-01

    Gene expression can be studied at a genome-wide scale with the aid of modern microarray technologies. Expression profiling of tens to hundreds of individuals in a genetic population can reveal the consequences of genetic variation. In this paper it is argued that the design and analysis of such a

  15. Combining microarrays and genetic analysis

    NARCIS (Netherlands)

    Alberts, Rudi; Fu, Jingyuan; Swertz, Morris A.; Lubbers, L. Alrik; Albers, Casper J.; Jansen, Ritsert C.

    2005-01-01

    Gene expression can be studied at a genome-wide scale with the aid of modern microarray technologies. Expression profiling of tens to hundreds of individuals in a genetic population can reveal the consequences of genetic variation. In this paper it is argued that the design and analysis of such a st

  16. Microarray Analysis in Glioblastomas

    Science.gov (United States)

    Bhawe, Kaumudi M.; Aghi, Manish K.

    2016-01-01

    Microarray analysis in glioblastomas is done using either cell lines or patient samples as starting material. A survey of the current literature points to transcript-based microarrays and immunohistochemistry (IHC)-based tissue microarrays as being the preferred methods of choice in cancers of neurological origin. Microarray analysis may be carried out for various purposes including the following: To correlate gene expression signatures of glioblastoma cell lines or tumors with response to chemotherapy (DeLay et al., Clin Cancer Res 18(10):2930–2942, 2012)To correlate gene expression patterns with biological features like proliferation or invasiveness of the glioblastoma cells (Jiang et al., PLoS One 8(6):e66008, 2013)To discover new tumor classificatory systems based on gene expression signature, and to correlate therapeutic response and prognosis with these signatures (Huse et al., Annu Rev Med 64(1):59–70, 2013; Verhaak et al., Cancer Cell 17(1):98–110, 2010) While investigators can sometimes use archived tumor gene expression data available from repositories such as the NCBI Gene Expression Omnibus to answer their questions, new arrays must often be run to adequately answer specific questions. Here, we provide a detailed description of microarray methodologies, how to select the appropriate methodology for a given question, and analytical strategies that can be used. Experimental methodology for protein microarrays is outside the scope of this chapter, but basic sample preparation techniques for transcript-based microarrays are included here. PMID:26113463

  17. Microarray data integration for genome-wide analysis of human tissue-selective gene expression

    OpenAIRE

    Wang, Liangjiang; Srivastava, Anand K; Schwartz, Charles E

    2010-01-01

    Background Microarray gene expression data are accumulating in public databases. The expression profiles contain valuable information for understanding human gene expression patterns. However, the effective use of public microarray data requires integrating the expression profiles from heterogeneous sources. Results In this study, we have compiled a compendium of microarray expression profiles of various human tissue samples. The microarray raw data generated in different research laboratorie...

  18. Microarray-bioinformatics analysis of altered genomic expression profiles between human fetal and infant myocardium

    Institute of Scientific and Technical Information of China (English)

    KONG Bo; LIU Ying-long; L(U) Xiao-dong

    2008-01-01

    Background The physiological differences between fetal and postnatal heart have been well characterized at the cellular level. However, the genetic mechanisms governing and regulating these differences have only been partially elucidated. Elucidation of the differentially expressed genes profile before and after birth has never been systematically proposed and analyzed.Methods The human oligonuclectide microarray and bioinformatics analysis approaches were applied to isolate and classify the differentially expressed genes between fetal and infant cardiac tissue samples. Quantitative real-time PCR was used to confirm the results from the microarray.Results Two hundred and forty-two differentially expressed genes were discovered and classified into 13 categories, including genes related to energy metabolism, myocyte hyperplasia, development, muscle contraction, protein synthesis and degradation, extraceUular matrix components, transcription factors, apoptosis, signal pathway molecules, organelle organization and several other biological processes. Moreover, 95 genes were identified which had not previously been reported to be expressed in the heart.Conclusions The study systematically analyzed the alteration of the gene expression profile between the human fetal and infant myocardium. A number of genes were discovered which had not been reported to be expressed in the heart. The data provided insight into the physical development mechanisms of the heart before and after birth.KONG Bo and LU Xiao-dong contributed equally to this study.

  19. Construction of Whole Genome Microarrays, and Expression Analysis of Desulfovibrio vulgaris cells in Metal-Reducing Conditions (Uranium and Chromium)

    Energy Technology Data Exchange (ETDEWEB)

    Fields, Matthew W.

    2005-06-01

    One of the major goals of the project is to construct whole-genome microarrays for Desulfovibrio vulgaris. Previous whole-genome microarrays constructed at ORNL have been PCR-amplimer based, and we wanted to re-evaluate the type of microarrays being built because oligonucleotide probes have several advantages. Microarrays have been generally constructed with two types of probes, PCR-generated probes that typically range in size between 200 and 2000 bp, and oligonucleotide probes with typical size of 20-70 nt. Producing PCR product-based DNA arrays can be a time-consuming procedure that includes PCR primer design, amplification, size verification, product purification, and product quantification. Also, some ORFs are difficult to amplify and thus the construction of comprehensive arrays can be a challenge. Recently, to alleviate some of the problems associated with PCR product-based microarrays, oligonucleotide microarrays that contain probes longer than 40 nt have been evaluated and used for whole genome expression studies. These microarrays should have higher specificity and are easy to construct, and can thus provide an important alternative approach to monitor gene expression. However, due to the smaller probe size, it is expected that the detection sensitivity of oligonucleotide arrays will be lower than PCR product-based probes.

  20. The EADGENE Microarray Data Analysis Workshop

    NARCIS (Netherlands)

    Koning, de D.J.; Jaffrezic, F.; Lund, M.S.; Watson, M.; Channing, C.; Hulsegge, B.; Pool, M.H.; Buitenhuis, B.; Hedegaard, J.; Hornshoj, H.; Sorensen, P.; Marot, G.; Delmas, C.; Lê Cao, K.A.; San Cristobal, M.; Baron, M.D.; Malinverni, R.; Stella, A.; Brunner, R.M.; Seyfert, H.M.; Jensen, K.; Mouzaki, D.; Waddington, D.; Jiménez-Marín, A.; Perez-Alegre, M.; Perez-Reinado, E.; Closset, R.; Detilleux, J.C.; Dovc, P.; Lavric, M.; Nie, H.; Janss, L.

    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

  1. Genome-wide microarray analysis of human fibroblasts in response to γ radiation and the radiation-induced bystander effect.

    Science.gov (United States)

    Kalanxhi, Erta; Dahle, Jostein

    2012-01-01

    Radiation-induced bystander effects have been studied extensively due to their potential implications for cancer therapy and radiation protection; however, a complete understanding of the molecular mechanisms remains to be elucidated. In this study, we monitored transcriptional responses to γ radiation in irradiated and bystander fibroblasts simultaneously employing a genome-wide microarray approach to determine factors that may be modulated in the generation or propagation of the bystander effect. For the microarray data we employed analysis at both the single-gene and gene-set level to place the findings in a biological context. Unirradiated bystander fibroblasts that were recipients of growth medium harvested from irradiated cultures 2 h after exposure to 2 Gy displayed transient enrichment in gene sets belonging to ribosome, oxidative phosphorylation and neurodegenerative disease pathways associated with mitochondrial dysfunctions. The response to direct irradiation was characterized by induction of signaling and apoptosis genes and the gradual formation of a cellular immune response. A set of 14 genes, many of which were regulated by p53, were found to be induced early after irradiation (prior to medium transfer) and may be important in the generation or propagation of the bystander effect.

  2. A genome assembly-integrated dog 1 Mb BAC microarray: a cytogenetic resource for canine cancer studies and comparative genomic analysis.

    Science.gov (United States)

    Thomas, R; Duke, S E; Karlsson, E K; Evans, A; Ellis, P; Lindblad-Toh, K; Langford, C F; Breen, M

    2008-01-01

    Molecular cytogenetic studies have been instrumental in defining the nature of numerical and structural chromosome changes in human cancers, but their significance remains to be fully understood. The emergence of high quality genome assemblies for several model organisms provides exciting opportunities to develop novel genome-integrated molecular cytogenetic resources that now permit a comparative approach to evaluating the relevance of tumor-associated chromosome aberrations, both within and between species. We have used the dog genome sequence assembly to identify a framework panel of 2,097 bacterial artificial chromosome (BAC) clones, selected at intervals of approximately one megabase. Each clone has been evaluated by multicolor fluorescence in situ hybridization (FISH) to confirm its unique cytogenetic location in concordance with its reported position in the genome assembly, providing new information on the organization of the dog genome. This panel of BAC clones also represents a powerful cytogenetic resource with numerous potential applications. We have used the clone set to develop a genome-wide microarray for comparative genomic hybridization (aCGH) analysis, and demonstrate its application in detection of tumor-associated DNA copy number aberrations (CNAs) including single copy deletions and amplifications, regional aneuploidy and whole chromosome aneuploidy. We also show how individual clones selected from the BAC panel can be used as FISH probes in direct evaluation of tumor karyotypes, to verify and explore CNAs detected using aCGH analysis. This cytogenetically validated, genome integrated BAC clone panel has enormous potential for aiding gene discovery through a comparative approach to molecular oncology.

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

    Science.gov (United States)

    Grenville-Briggs, Laura J.; Stansfield, Ian

    2011-01-01

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

  4. American College of Medical Genetics and Genomics technical standards and guidelines: microarray analysis for chromosome abnormalities in neoplastic disorders.

    Science.gov (United States)

    Cooley, Linda D; Lebo, Matthew; Li, Marilyn M; Slovak, Marilyn L; Wolff, Daynna J

    2013-06-01

    Microarray methodologies, to include array comparative genomic hybridization and single-nucleotide polymorphism-based arrays, are innovative methods that provide genomic data. These data should be correlated with the results from the standard methods, chromosome and/or fluorescence in situ hybridization, to ascertain and characterize the genomic aberrations of neoplastic disorders, both liquid and solid tumors. Over the past several decades, standard methods have led to an accumulation of genetic information specific to many neoplasms. This specificity is now used for the diagnosis and classification of neoplasms. Cooperative studies have revealed numerous correlations between particular genetic aberrations and therapeutic outcomes. Molecular investigation of chromosomal abnormalities identified by standard methods has led to discovery of genes, and gene function and dysfunction. This knowledge has led to improved therapeutics and, in some disorders, targeted therapies. Data gained from the higher-resolution microarray methodologies will enhance our knowledge of the genomics of specific disorders, leading to more effective therapeutic strategies. To assist clinical laboratories in validation of the methods, their consistent use, and interpretation and reporting of results from these microarray methodologies, the American College of Medical Genetics and Genomics has developed the following professional standard and guidelines.

  5. Genome-wide mapping of protein-DNA interaction by chromatin immunoprecipitation and DNA microarray hybridization (ChIP-chip). Part B: ChIP-chip data analysis.

    Science.gov (United States)

    Göbel, Ulrike; Reimer, Julia; Turck, Franziska

    2010-01-01

    Genome-wide targets of chromatin-associated factors can be identified by a combination of chromatin-immunoprecipitation and oligonucleotide microarray hybridization. Genome-wide mircoarray data analysis represents a major challenge for the experimental biologist. This chapter introduces ChIPR, a package written in the R statistical programming language that facilitates the analysis of two-color microarrays from Roche-Nimblegen. The workflow of ChIPR is illustrated with sample data from Arabidopsis thaliana. However, ChIPR supports ChIP-chip data preprocessing, target identification, and cross-annotation of any species for which genome annotation data is available in GFF format. This chapter describes how to use ChIPR as a software tool without the requirement for programming skills in the R language.

  6. 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.

  7. Genome-wide microarray analysis of tomato roots showed defined responses to iron deficiency

    Directory of Open Access Journals (Sweden)

    Zamboni Anita

    2012-03-01

    Full Text Available Abstract Background Plants react to iron deficiency stress adopting different kind of adaptive responses. Tomato, a Strategy I plant, improves iron uptake through acidification of rhizosphere, reduction of Fe3+ to Fe2+ and transport of Fe2+ into the cells. Large-scale transcriptional analyses of roots under iron deficiency are only available for a very limited number of plant species with particular emphasis for Arabidopsis thaliana. Regarding tomato, an interesting model species for Strategy I plants and an economically important crop, physiological responses to Fe-deficiency have been thoroughly described and molecular analyses have provided evidence for genes involved in iron uptake mechanisms and their regulation. However, no detailed transcriptome analysis has been described so far. Results A genome-wide transcriptional analysis, performed with a chip that allows to monitor the expression of more than 25,000 tomato transcripts, identified 97 differentially expressed transcripts by comparing roots of Fe-deficient and Fe-sufficient tomato plants. These transcripts are related to the physiological responses of tomato roots to the nutrient stress resulting in an improved iron uptake, including regulatory aspects, translocation, root morphological modification and adaptation in primary metabolic pathways, such as glycolysis and TCA cycle. Other genes play a role in flavonoid biosynthesis and hormonal metabolism. Conclusions The transcriptional characterization confirmed the presence of the previously described mechanisms to adapt to iron starvation in tomato, but also allowed to identify other genes potentially playing a role in this process, thus opening new research perspectives to improve the knowledge on the tomato root response to the nutrient deficiency.

  8. A predictive factor of the quality of microarray comparative genomic hybridization analysis for formalin-fixed paraffin-embedded archival tissue.

    Science.gov (United States)

    Nakao, Kenjiro; Oikawa, Masahiro; Arai, Junichi; Mussazhanova, Zhanna; Kondo, Hisayoshi; Shichijo, Kazuko; Nakashima, Masahiro; Hayashi, Tomayoshi; Yoshiura, Koh-Ichiro; Hatachi, Toshiko; Nagayasu, Takeshi

    2013-09-01

    Utilizing formalin-fixed paraffin-embedded (FFPE) archival tissue, the most common form of tissue preservation in routine practice, for cytogenetic analysis using microarray comparative genomic hybridization (aCGH) remains challenging. We searched for a predictive factor of the performance of FFPE DNA in aCGH analysis. DNA was extracted from 63 FFPE archival tissue samples of various tissue types (31 breast cancers, 24 lung cancers, and 8 thyroid tumors), followed by aCGH analysis using high-density oligonucleotide microarrays. Tumor DNA from matched frozen samples and from FFPE samples after whole-genome amplification were also analyzed in 2 and 4 case, respectively. The derivative log ratio spread (DLRSpread) was used to assess the overall quality of each aCGH result. The DLRSpread correlated significantly with the double-stranded DNA ratio of tumor DNA, storage time, and the degree of labeling with Cy5 (Parchival tissue samples can be utilized for aCGH analysis.

  9. 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...

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

    Science.gov (United States)

    Teng, Shaolei; Yang, Jack Y; Wang, Liangjiang

    2013-01-01

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

  11. Exploring host-pathogen interactions through genome wide protein microarray analysis.

    Science.gov (United States)

    Scietti, Luigi; Sampieri, Katia; Pinzuti, Irene; Bartolini, Erika; Benucci, Barbara; Liguori, Alessia; Haag, Andreas F; Lo Surdo, Paola; Pansegrau, Werner; Nardi-Dei, Vincenzo; Santini, Laura; Arora, Seguinde; Leber, Xavier; Rindi, Simonetta; Savino, Silvana; Costantino, Paolo; Maione, Domenico; Merola, Marcello; Speziale, Pietro; Bottomley, Matthew J; Bagnoli, Fabio; Masignani, Vega; Pizza, Mariagrazia; Scharenberg, Meike; Schlaeppi, Jean-Marc; Nissum, Mikkel; Liberatori, Sabrina

    2016-06-15

    During bacterial pathogenesis extensive contacts between the human and the bacterial extracellular proteomes take place. The identification of novel host-pathogen interactions by standard methods using a case-by-case approach is laborious and time consuming. To overcome this limitation, we took advantage of large libraries of human and bacterial recombinant proteins. We applied a large-scale protein microarray-based screening on two important human pathogens using two different approaches: (I) 75 human extracellular proteins were tested on 159 spotted Staphylococcus aureus recombinant proteins and (II) Neisseria meningitidis adhesin (NadA), an important vaccine component against serogroup B meningococcus, was screened against ≈2300 spotted human recombinant proteins. The approach presented here allowed the identification of the interaction between the S. aureus immune evasion protein FLIPr (formyl-peptide receptor like-1 inhibitory protein) and the human complement component C1q, key players of the offense-defense fighting; and of the interaction between meningococcal NadA and human LOX-1 (low-density oxidized lipoprotein receptor), an endothelial receptor. The novel interactions between bacterial and human extracellular proteins here presented might provide a better understanding of the molecular events underlying S. aureus and N. meningitidis pathogenesis.

  12. Exploring host-pathogen interactions through genome wide protein microarray analysis

    Science.gov (United States)

    Scietti, Luigi; Sampieri, Katia; Pinzuti, Irene; Bartolini, Erika; Benucci, Barbara; Liguori, Alessia; Haag, Andreas F.; Lo Surdo, Paola; Pansegrau, Werner; Nardi-Dei, Vincenzo; Santini, Laura; Arora, Seguinde; Leber, Xavier; Rindi, Simonetta; Savino, Silvana; Costantino, Paolo; Maione, Domenico; Merola, Marcello; Speziale, Pietro; Bottomley, Matthew J.; Bagnoli, Fabio; Masignani, Vega; Pizza, Mariagrazia; Scharenberg, Meike; Schlaeppi, Jean-Marc; Nissum, Mikkel; Liberatori, Sabrina

    2016-01-01

    During bacterial pathogenesis extensive contacts between the human and the bacterial extracellular proteomes take place. The identification of novel host-pathogen interactions by standard methods using a case-by-case approach is laborious and time consuming. To overcome this limitation, we took advantage of large libraries of human and bacterial recombinant proteins. We applied a large-scale protein microarray-based screening on two important human pathogens using two different approaches: (I) 75 human extracellular proteins were tested on 159 spotted Staphylococcus aureus recombinant proteins and (II) Neisseria meningitidis adhesin (NadA), an important vaccine component against serogroup B meningococcus, was screened against ≈2300 spotted human recombinant proteins. The approach presented here allowed the identification of the interaction between the S. aureus immune evasion protein FLIPr (formyl-peptide receptor like-1 inhibitory protein) and the human complement component C1q, key players of the offense-defense fighting; and of the interaction between meningococcal NadA and human LOX-1 (low-density oxidized lipoprotein receptor), an endothelial receptor. The novel interactions between bacterial and human extracellular proteins here presented might provide a better understanding of the molecular events underlying S. aureus and N. meningitidis pathogenesis. PMID:27302108

  13. Preliminary report for analysis of genome wide mutations from four ciprofloxacin resistant B. anthracis Sterne isolates generated by Illumina, 454 sequencing and microarrays for DHS

    Energy Technology Data Exchange (ETDEWEB)

    Jaing, Crystal [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Vergez, Lisa [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Hinckley, Aubree [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Thissen, James [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Gardner, Shea [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); McLoughlin, Kevin [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Jackson, Paul [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Ellingson, Sally [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Hauser, Loren [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Brettin, Tom [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Fofanov, Viacheslav [Eureka Genomics, Hercules, CA (United States); Koshinsky, Heather [Eureka Genomics, Hercules, CA (United States); Fofanov, Yuriy [Univ. of Houston, TX (United States)

    2011-06-21

    The objective of this project is to provide DHS a comprehensive evaluation of the current genomic technologies including genotyping, Taqman PCR, multiple locus variable tandem repeat analysis (MLVA), microarray and high-throughput DNA sequencing in the analysis of biothreat agents from complex environmental samples. As the result of a different DHS project, we have selected for and isolated a large number of ciprofloxacin resistant B. anthracis Sterne isolates. These isolates vary in the concentrations of ciprofloxacin that they can tolerate, suggesting multiple mutations in the samples. In collaboration with University of Houston, Eureka Genomics and Oak Ridge National Laboratory, we analyzed the ciprofloxacin resistant B. anthracis Sterne isolates by microarray hybridization, Illumina and Roche 454 sequencing to understand the error rates and sensitivity of the different methods. The report provides an assessment of the results and a complete set of all protocols used and all data generated along with information to interpret the protocols and data sets.

  14. In silico enhanced restriction enzyme based methylation analysis of the human glioblastoma genome using Agilent 244K CpG Island microarrays

    Directory of Open Access Journals (Sweden)

    Anh Tran

    2010-01-01

    Full Text Available Genome wide methylation profiling of gliomas is likely to provide important clues to improving treatment outcomes. Restriction enzyme based approaches have been widely utilized for methylation profiling of cancer genomes and will continue to have importance in combination with higher density microarrays. With the availability of the human genome sequence and microarray probe sequences, these approaches can be readily characterized and optimized via in silico modeling. We adapted the previously described HpaII/MspI based Methylation Sensitive Restriction Enzyme (MSRE assay for use with two-color Agilent 244K CpG island microarrays. In this assay, fragmented genomic DNA is digested in separate reactions with isoschizomeric HpaII (methylation-sensitive and MspI (methylation-insensitive restriction enzymes. Using in silico hybridization, we found that genomic fragmentation with BfaI was superior to MseI, providing a maximum effective coverage of 22,362 CpG islands in the human genome. In addition, we confirmed the presence of an internal control group of fragments lacking HpaII/MspI sites which enable separation of methylated and unmethylated fragments. We used this method on genomic DNA isolated from normal brain, U87MG cells, and a glioblastoma patient tumor sample and confirmed selected differentially methylated CpG islands using bisulfite sequencing. Along with additional validation points, we performed a receiver operating characteristics (ROC analysis to determine the optimal threshold (p ≤ 0.001. Based on this threshold, we identified ~2400 CpG islands common to all three samples and 145 CpG islands unique to glioblastoma. These data provide more general guidance to individuals seeking to maximize effective coverage using restriction enzyme based methylation profiling approaches.

  15. Differential Gene Expression Analysis of Placentas with Increased Vascular Resistance and Pre-Eclampsia Using Whole-Genome Microarrays

    Directory of Open Access Journals (Sweden)

    M. Centlow

    2011-01-01

    Full Text Available Pre-eclampsia is a pregnancy complication characterized by hypertension and proteinuria. There are several factors associated with an increased risk of developing pre-eclampsia, one of which is increased uterine artery resistance, referred to as “notching”. However, some women do not progress into pre-eclampsia whereas others may have a higher risk of doing so. The placenta, central in pre-eclampsia pathology, may express genes associated with either protection or progression into pre-eclampsia. In order to search for genes associated with protection or progression, whole-genome profiling was performed. Placental tissue from 15 controls, 10 pre-eclamptic, 5 pre-eclampsia with notching, and 5 with notching only were analyzed using microarray and antibody microarrays to study some of the same gene product and functionally related ones. The microarray showed 148 genes to be significantly altered between the four groups. In the preeclamptic group compared to notch only, there was increased expression of genes related to chemotaxis and the NF-kappa B pathway and decreased expression of genes related to antigen processing and presentation, such as human leukocyte antigen B. Our results indicate that progression of pre-eclampsia from notching may involve the development of inflammation. Increased expression of antigen-presenting genes, as seen in the notch-only placenta, may prevent this inflammatory response and, thereby, protect the patient from developing pre-eclampsia.

  16. 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...

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

    Science.gov (United States)

    Wang, Junbai

    2008-01-01

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

  18. Two recombinant human interferon-beta 1a pharmaceutical preparations produce a similar transcriptional response determined using whole genome microarray analysis.

    Science.gov (United States)

    Prync, A E Sterin; Yankilevich, P; Barrero, P R; Bello, R; Marangunich, L; Vidal, A; Criscuolo, M; Benasayag, L; Famulari, A L; Domínguez, R O; Kauffman, M A; Diez, R A

    2008-02-01

    Recombinant human interferon-beta (IFN-b) is a well-established treatment for multiple sclerosis (MS). The regulatory process for marketing authorization of biosimilars is currently under debate in certain countries. In the EU, EMEA has clearly defined the process including overarching and product-specific guidelines, which includes clinical testing. Biosimilarity needs to be based on comparability criteria, including at least molecular characterization, biological activity relevant for the therapeutic effect and relative bioavailability ("bioequivalence"). In the case of such complex diseases as MS, where the effect of treatment is not so directly measurable, in vitro tools can provide additional data to support comparability. Genomic microarrays assays might be useful to compare multisource biopharmaceuticals. The aim of the present study was to compare the pharmacodynamic genomic effects (in terms of transcriptional regulation) of two recombinant human IFN-I(2)1a preparations on lymphocytes of multiple sclerosis patients using a whole genome microarray assay. We performed an ex vivo whole genome expression profiling of the effect of two preparations of IFN-I(2)1a on non-adherent mononuclears from five relapsing-remitting MS patients analyzing microarrays (CodeLink Human Whole Genome). Patients blood was drawn, PBMCs isolated and cultured in three different conditions: culture medium (control), 1,000 U/ml of IFN-I(2)1a (BLA- (STOFERON, Bio Sidus) and 1,000 U/ml of IFN-I(2)1a (REBIF, Serono) RNA was purified from non-adherent cells (mostly lymphocytes), amplified and hybridized. Raw data were generated by CodeLink proprietary software. Data normalization, quality control and analysis of differential gene expression between treatments were done using linear model for microarray data. Functional annotation analysis of IFN-I(2)1a MS treatment transcription was done using DAVID. Out of the approximately 45,000 human sequences examined, no evidence of differential

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

    DEFF Research Database (Denmark)

    Li, Lei; Wang, Xiangfeng; Stolc, Viktor;

    2006-01-01

    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....... 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...... activity between duplicated segments of the genome. Collectively, our results provide the first whole-genome transcription map useful for further understanding the rice genome. Udgivelsesdato: 2006-Jan...

  20. Genome-wide expression profiling of the response to terbinafine in Candida albicans using a cDNA microarray analysis

    Institute of Scientific and Technical Information of China (English)

    ZENG Yue-bin; QIAN Yuan-shu; MA Lian; GU Hong-ni

    2007-01-01

    Background Candida albicans is the most frequently seen opportunistic human fungal pathogen. Terbinafine is an allylamine antifungal agent that has been proven to have high clinical efficacy in the therapy of fungal infections, the mechanism of action of terbinafine involves the specific inhibition of fungal squalene epoxidase, resulting in ergosterol deficiency and accumulation of intracellular squalene. We used cDNA microarray analysis technology to monitor global expression profile changes of Candida albicans genes in response to terbinafine treatment, and we anticipated a panoramic view of the responses of Candida albicans cells to the representatives of allylamine antifungal agents at the molecular level in an effort to identify drug class-specific and mechanism-independent changes in gene expression.Methods Candida albicans strain ATCC 90028 was exposed to either medium alone or terbinafine at a concentration equivalent to the 1/2 minimal inhibitory concentrations (MICs, 4 mg/L) for 90 minutes. RNA was isolated and gene expression profiles were compared to identify the changes in the gene expression profile using a cDNA microarray analysis. Differential expression of 10 select genes detected by cDNA microarray analysis was confirmed by semi-quantitative reverse transcription-polymerase chain reaction (RT-PCR).Results A total of 222 genes were found to be responsive to terbinafine, including 121 up-regulated genes and 101 down-regulated genes. These included genes encoding membrane transport proteins belonging to the members of the ATP-binding cassette (ABC) or major facilitator superfamily (MFS; CDR1, AGP2, GAP6, PHO84, HOL3, FCY23, VCX1),genes involved in stress response and detoxification (CDR1, AGP2, HOL3), and gene involved in the ergosterol biosynthesis pathway (ERG12). The results of semi-quantitative RT-PCR were consistent with that of the cDNA microarray analysis.Conclusions The up-regulation of the gene encoding the multidrug resistance efflux pump

  1. Different responsiveness to a high-fat/cholesterol diet in two inbred mice and underlying genetic factors: a whole genome microarray analysis

    Directory of Open Access Journals (Sweden)

    Jin Gang

    2009-10-01

    Full Text Available Abstract Background To investigate different responses to a high-fat/cholesterol diet and uncover their underlying genetic factors between C57BL/6J (B6 and DBA/2J (D2 inbred mice. Methods B6 and D2 mice were fed a high-fat/cholesterol diet for a series of time-points. Serum and bile lipid profiles, bile acid yields, hepatic apoptosis, gallstones and atherosclerosis formation were measured. Furthermore, a whole genome microarray was performed to screen hepatic genes expression profile. Quantitative real-time PCR, western blot and TUNEL assay were conducted to validate microarray data. Results After fed the high-fat/cholesterol diet, serum and bile total cholesterol, serum cholesterol esters, HDL cholesterol and Non-HDL cholesterol levels were altered in B6 but not significantly changed in D2; meanwhile, biliary bile acid was decreased in B6 but increased in D2. At the same time, hepatic apoptosis, gallstones and atherosclerotic lesions occurred in B6 but not in D2. The hepatic microarray analysis revealed distinctly different genes expression patterns between B6 and D2 mice. Their functional pathway groups included lipid metabolism, oxidative stress, immune/inflammation response and apoptosis. Quantitative real time PCR, TUNEL assay and western-blot results were consistent with microarray analysis. Conclusion Different genes expression patterns between B6 and D2 mice might provide a genetic basis for their distinctive responses to a high-fat/cholesterol diet, and give us an opportunity to identify novel pharmaceutical targets in related diseases in the future.

  2. Final Report Construction of Whole Genome Microarrays, and Expression Analysis of Desulfovibrio vulgaris cells in Metal-Reducing Conditions

    Energy Technology Data Exchange (ETDEWEB)

    M.W. Fields; J.D. Wall; J. Keasling; J. Zhou

    2008-05-15

    We continue to utilize the oligonucleotide microarrays that were constructed through funding with this project to characterize growth responses of Desulfovibrio vulgaris relevant to metal-reducing conditions. To effectively immobilize heavy metals and radionuclides via sulfate-reduction, it is important to understand the cellular responses to adverse factors observed at contaminated subsurface environments (e.g., nutrients, pH, contaminants, growth requirements and products). One of the major goals of the project is to construct whole-genome microarrays for Desulfovibrio vulgaris. First, in order to experimentally establish the criteria for designing gene-specific oligonucleotide probes, an oligonucleotide array was constructed that contained perfect match (PM) and mismatch (MM) probes (50mers and 70mers) based upon 4 genes. The effects of probe-target identity, continuous stretch, mismatch position, and hybridization free energy on specificity were examined. Little hybridization was observed at a probe-target identity of <85% for both 50mer and 70mer probes. 33 to 48% of the PM signal intensities were detected at a probe-target identity of 94% for 50mer oligonucleotides, and 43 to 55% for 70mer probes at a probe-target identity of 96%. When the effects of sequence identity and continuous stretch were considered independently, a stretch probe (>15 bases) contributed an additional 9% of the PM signal intensity compared to a non-stretch probe (< 15 bases) at the same identity level. Cross-hybridization increased as the length of continuous stretch increased. A 35-base stretch for 50mer probes or a 50-base stretch for 70mer probes had approximately 55% of the PM signal. Mismatches should be as close to the middle position of an oligonucleotide probe as possible to minimize cross-hybridization. Little cross-hybridization was observed for probes with a minimal binding free energy greater than -30 kcal/mol for 50mer probes or -40 kcal/mol for 70mer probes. Based on the

  3. DNA Microarrays in Comparative Genomics and Transcriptomics

    DEFF Research Database (Denmark)

    Willenbrock, Hanni

    2007-01-01

    of each method’s ability to analyze DNA copy number data. Moreover, our study shows that analysis methods developed for cancer research may also successfully be applied to DNA copy number profiles from bacterial genomes. However, here the purpose is to characterize variations in the gene content...... to verify predictions of highly expressed genes. Moreover, the codon bias of microbial genomes was found to constitute an environmental signature. For example, soil bacteria have very similar codon bias....

  4. Human genomics and microarrays: implications for the plastic surgeon.

    Science.gov (United States)

    Cole, Jana; Isik, Frank

    2002-09-01

    The Human Genome Project was launched in 1989 in an effort to sequence the entire span of human DNA. Although coding sequences are important in identifying mutations, the static order of DNA does not explain how a cell or organism may respond to normal and abnormal biological processes. By examining the mRNA content of a cell, researchers can determine which genes are being activated in response to a stimulus. Traditional methods in molecular biology generally work on a "one gene: one experiment" basis, which means that the throughput is very limited and the "whole picture" of gene function is hard to obtain. To study each of the 60,000 to 80,000 genes in the human genome under each biological circumstance is not practical. Recently, microarrays (also known as gene or DNA chips) have emerged; these allow for the simultaneous determination of expression for thousands of genes and analysis of genome-wide mRNA expression. The purpose of this article is twofold: first, to provide the clinical plastic surgeon with a working knowledge and understanding of the fields of genomics, microarrays, and bioinformatics and second, to present a case to illustrate how these technologies can be applied in the study of wound healing.

  5. Use of genomic DNA control features and predicted operon structure in microarray data analysis: ArrayLeaRNA – a Bayesian approach

    Directory of Open Access Journals (Sweden)

    Pin Carmen

    2007-11-01

    Full Text Available Abstract Background Microarrays are widely used for the study of gene expression; however deciding on whether observed differences in expression are significant remains a challenge. Results A computing tool (ArrayLeaRNA has been developed for gene expression analysis. It implements a Bayesian approach which is based on the Gumbel distribution and uses printed genomic DNA control features for normalization and for estimation of the parameters of the Bayesian model and prior knowledge from predicted operon structure. The method is compared with two other approaches: the classical LOWESS normalization followed by a two fold cut-off criterion and the OpWise method (Price, et al. 2006. BMC Bioinformatics. 7, 19, a published Bayesian approach also using predicted operon structure. The three methods were compared on experimental datasets with prior knowledge of gene expression. With ArrayLeaRNA, data normalization is carried out according to the genomic features which reflect the results of equally transcribed genes; also the statistical significance of the difference in expression is based on the variability of the equally transcribed genes. The operon information helps the classification of genes with low confidence measurements. ArrayLeaRNA is implemented in Visual Basic and freely available as an Excel add-in at http://www.ifr.ac.uk/safety/ArrayLeaRNA/ Conclusion We have introduced a novel Bayesian model and demonstrated that it is a robust method for analysing microarray expression profiles. ArrayLeaRNA showed a considerable improvement in data normalization, in the estimation of the experimental variability intrinsic to each hybridization and in the establishment of a clear boundary between non-changing and differentially expressed genes. The method is applicable to data derived from hybridizations of labelled cDNA samples as well as from hybridizations of labelled cDNA with genomic DNA and can be used for the analysis of datasets where

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

    Directory of Open Access Journals (Sweden)

    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.

  7. 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

  8. A comparative genomic study in schizophrenic and in bipolar disorder patients, based on microarray expression profiling meta-analysis.

    Science.gov (United States)

    Logotheti, Marianthi; Papadodima, Olga; Venizelos, Nikolaos; Chatziioannou, Aristotelis; Kolisis, Fragiskos

    2013-01-01

    Schizophrenia affecting almost 1% and bipolar disorder affecting almost 3%-5% of the global population constitute two severe mental disorders. The catecholaminergic and the serotonergic pathways have been proved to play an important role in the development of schizophrenia, bipolar disorder, and other related psychiatric disorders. The aim of the study was to perform and interpret the results of a comparative genomic profiling study in schizophrenic patients as well as in healthy controls and in patients with bipolar disorder and try to relate and integrate our results with an aberrant amino acid transport through cell membranes. In particular we have focused on genes and mechanisms involved in amino acid transport through cell membranes from whole genome expression profiling data. We performed bioinformatic analysis on raw data derived from four different published studies. In two studies postmortem samples from prefrontal cortices, derived from patients with bipolar disorder, schizophrenia, and control subjects, have been used. In another study we used samples from postmortem orbitofrontal cortex of bipolar subjects while the final study was performed based on raw data from a gene expression profiling dataset in the postmortem superior temporal cortex of schizophrenics. The data were downloaded from NCBI's GEO datasets.

  9. A Comparative Genomic Study in Schizophrenic and in Bipolar Disorder Patients, Based on Microarray Expression Profiling Meta-Analysis

    Directory of Open Access Journals (Sweden)

    Marianthi Logotheti

    2013-01-01

    Full Text Available Schizophrenia affecting almost 1% and bipolar disorder affecting almost 3%–5% of the global population constitute two severe mental disorders. The catecholaminergic and the serotonergic pathways have been proved to play an important role in the development of schizophrenia, bipolar disorder, and other related psychiatric disorders. The aim of the study was to perform and interpret the results of a comparative genomic profiling study in schizophrenic patients as well as in healthy controls and in patients with bipolar disorder and try to relate and integrate our results with an aberrant amino acid transport through cell membranes. In particular we have focused on genes and mechanisms involved in amino acid transport through cell membranes from whole genome expression profiling data. We performed bioinformatic analysis on raw data derived from four different published studies. In two studies postmortem samples from prefrontal cortices, derived from patients with bipolar disorder, schizophrenia, and control subjects, have been used. In another study we used samples from postmortem orbitofrontal cortex of bipolar subjects while the final study was performed based on raw data from a gene expression profiling dataset in the postmortem superior temporal cortex of schizophrenics. The data were downloaded from NCBI's GEO datasets.

  10. Experimental genomics: The application of DNA microarrays in cellular and molecular biology studies

    Institute of Scientific and Technical Information of China (English)

    2002-01-01

    The genome sequence information in combination with DNA microarrays promises to revolutionize the way of cellular and molecular biological research by allowing complex mixtures of RNA and DNA to interrogated in a parallel and quant itative fashion. DNA microarrays can be used to measure levels of gene expressio n for tens of thousands of gene simultaneously and take advantage of all availab le sequence information for experimental design and data interpretation in pursu it of biological understanding. Recent progress in experimental genomics allows DNA microarrays not simply to provide a catalogue of all the genes and informati on about their function, but to understand how the components work together to comprise functioning cells and organisms. This brief review gives a survey of DNA microarrays technology and its applications in genome and gene function analysis, gene expression studies, biological signal and defense system, cell cyclereg ulation, mechanism of transcriptional regulation, proteomics, and the functional ity of food component.

  11. Cytotoxicity and genome-wide microarray analysis of intestinal smooth muscle cells in response to hexavalent chromium induction

    Institute of Scientific and Technical Information of China (English)

    Li-Fang JIN; Yuan-Yuan WANG; Zi-Dong ZHANG; Yi-Meng YUAN; Yi-Rui HU; Yang-Feng WEI; Jian NI

    2013-01-01

    Chronic ingestion of high concentrations of hexavalent chromium [Cr(Ⅵ)] in drinking water induces intestinal tumors in mice; however,information on its toxicity on intestinal smooth muscle cells is limited.The present study aimed to assess the in vitro and in vivo toxicological effects of Cr(Ⅵ) on intestinal smooth muscle cells.Human intestinal smooth muscle cells (HISM cells) were cultured with different concentrations of Cr(Ⅵ) to evaluate effects on cell proliferation ability,oxidative stress levels,and antioxidant system.Furthermore,tissue sections in Cr(Ⅵ) exposed rabbits were analyzed to evaluate toxicity on intestinal muscle cells in vivo.Gene chips were utilized to assess differential gene expression profiles at the genome-wide level in 1 μmol/L Cr(Ⅵ) treated cells.Intestinal tissue biopsy results showed that Cr(Ⅵ) increased the incidences of diffuse epithelial hyperplasia in intestinal jejunum but caused no obvious damage to the structure of the muscularis.Cell proliferation analysis revealed that high concentrations (≥64 μmol/L) but not low concentrations of Cr(Ⅵ) (≤16 μmol/L) significantly inhibited the growth of HISM cells.For oxidative stress levels,the expression of reactive oxygen species (ROS) and nitric oxide (NO) was elevated at high concentrations (≥64 μmol/L) but not at low concentrations of Cr(Ⅵ) (≤ 16 μmol/L).In addition,dose-dependent increases in the activity of oxidized glutathione (GSSH)/total-glutathione (T-GSH) were also observed.Gene chip screened 491 differentially expressed genes including genes associated with cell apoptosis,oxidations,and cytoskeletons.Some of these differentially expressed genes may be unique to smooth muscle cells in response to Cr(Ⅵ) induction.

  12. Analysis of pigmented villonodular synovitis with genome-wide complementary DNA microarray and tissue array technology reveals insight into potential novel therapeutic approaches.

    Science.gov (United States)

    Finis, Katharina; Sültmann, Holger; Ruschhaupt, Markus; Buness, Andreas; Helmchen, Birgit; Kuner, Ruprecht; Gross, Marie-Luise; Fink, Bernd; Schirmacher, Peter; Poustka, Annemarie; Berger, Irina

    2006-03-01

    To characterize the gene expression profile and determine potential diagnostic markers and therapeutic targets in pigmented villonodular synovitis (PVNS). Gene expression patterns in 11 patients with PVNS, 18 patients with rheumatoid arthritis (RA), and 19 patients with osteoarthritis (OA) were investigated using genome-wide complementary DNA microarrays. Validation of differentially expressed genes was performed by real-time quantitative polymerase chain reaction and immunohistochemical analysis on tissue arrays (80 patients with PVNS, 51 patients with RA, and 20 patients with OA). The gene expression profile in PVNS was clearly distinct from those in RA and OA. One hundred forty-one up-regulated genes and 47 down-regulated genes were found in PVNS compared with RA, and 153 up-regulated genes and 89 down-regulated genes were found in PVNS compared with OA (fold change > or = 1.5; Q PVNS were involved in apoptosis regulation, matrix degradation, and inflammation (ALOX5AP, ATP6V1B2, CD53, CHI3L1, CTSL, CXCR4, HSPA8, HSPCA, LAPTM5, MMP9, MOAP1, and SPP1). The gene expression signature in PVNS is similar to that of activated macrophages and is consistent with the local destructive course of the disease. The gene and protein expression patterns suggest that the ongoing proliferation in PVNS is sustained by apoptosis resistance. This result suggests the possibility of a potential novel therapeutic intervention against PVNS.

  13. Pineal function: impact of microarray analysis

    DEFF Research Database (Denmark)

    Klein, David C; Bailey, Michael J; Carter, David A

    2009-01-01

    Microarray analysis has provided a new understanding of pineal function by identifying genes that are highly expressed in this tissue relative to other tissues and also by identifying over 600 genes that are expressed on a 24-h schedule. This effort has highlighted surprising similarity...... foundation that microarray analysis has provided will broadly support future research on pineal function....

  14. The EADGENE Microarray Data Analysis Workshop (Open Access publication

    Directory of Open Access Journals (Sweden)

    Jiménez-Marín Ángeles

    2007-11-01

    Full Text Available Abstract 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 from a direct comparison of two treatments (dye-balanced. While there was broader agreement with regards to methods of microarray normalisation and significance testing, there were major differences with regards to quality control. The quality control approaches varied from none, through using 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 in facilitating interaction between scientists with a diverse background but a common interest in microarray analyses.

  15. Kernel Based Nonlinear Dimensionality Reduction and Classification for Genomic Microarray

    Directory of Open Access Journals (Sweden)

    Lan Shu

    2008-07-01

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

  16. Bioinformatics/biostatistics: microarray analysis.

    Science.gov (United States)

    Eichler, Gabriel S

    2012-01-01

    The quantity and complexity of the molecular-level data generated in both research and clinical settings require the use of sophisticated, powerful computational interpretation techniques. It is for this reason that bioinformatic analysis of complex molecular profiling data has become a fundamental technology in the development of personalized medicine. This chapter provides a high-level overview of the field of bioinformatics and outlines several, classic bioinformatic approaches. The highlighted approaches can be aptly applied to nearly any sort of high-dimensional genomic, proteomic, or metabolomic experiments. Reviewed technologies in this chapter include traditional clustering analysis, the Gene Expression Dynamics Inspector (GEDI), GoMiner (GoMiner), Gene Set Enrichment Analysis (GSEA), and the Learner of Functional Enrichment (LeFE).

  17. Genomic analysis of a sexually-selected character: EST sequencing and microarray analysis of eye-antennal imaginal discs in the stalk-eyed fly Teleopsis dalmanni (Diopsidae

    Directory of Open Access Journals (Sweden)

    Wang Xianhui

    2009-08-01

    framework for a comprehensive examination of the genetic basis of eye-stalk variation. Several candidate genes, such as crooked legs, cdc2, CG31917 and CG11577, emerge from the analysis of gene duplication, protein evolution and microarray gene expression. Additional comparisons of expression profiles between, for example, males and females, and species that differ in eye-stalk sexual dimorphism, are now enabled by these resources.

  18. A 7872 cDNA microarray and its use in bovine functional genomics.

    Science.gov (United States)

    Everts, Robin E; Band, Mark R; Liu, Z Lewis; Kumar, Charu G; Liu, Lei; Loor, Juan J; Oliveira, Rosane; Lewin, Harris A

    2005-05-15

    The strategy used to create and annotate a 7872 cDNA microarray from cattle placenta and spleen cDNA sequences is described. This microarray contains approximately 6300 unique genes, as determined by BLASTN and TBLASTX similarity search against the human and mouse UniGene and draft human genome sequence databases (build 34). Sequences on the array were annotated with gene ontology (GO) terms, thereby facilitating data analysis and interpretation. A total of 3244 genes were annotated with GO terms. The array is rich in sequences encoding transcription factors, signal transducers and cell cycle regulators. Current research being conducted with this array is described, and an overview of planned improvements in our microarray platform for cattle functional genomics is presented.

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

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    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.

  20. Microarray analysis in the archaeon Halobacterium salinarum strain R1.

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    Jens Twellmeyer

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

  1. Ontology-Based Analysis of Microarray Data.

    Science.gov (United States)

    Giuseppe, Agapito; Milano, Marianna

    2016-01-01

    The importance of semantic-based methods and algorithms for the analysis and management of biological data is growing for two main reasons. From a biological side, knowledge contained in ontologies is more and more accurate and complete, from a computational side, recent algorithms are using in a valuable way such knowledge. Here we focus on semantic-based management and analysis of protein interaction networks referring to all the approaches of analysis of protein-protein interaction data that uses knowledge encoded into biological ontologies. Semantic approaches for studying high-throughput data have been largely used in the past to mine genomic and expression data. Recently, the emergence of network approaches for investigating molecular machineries has stimulated in a parallel way the introduction of semantic-based techniques for analysis and management of network data. The application of these computational approaches to the study of microarray data can broad the application scenario of them and simultaneously can help the understanding of disease development and progress.

  2. Advanced spot quality analysis in two-colour microarray experiments

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    Vetter Guillaume

    2008-09-01

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

  3. Sequencing ebola and marburg viruses genomes using microarrays.

    Science.gov (United States)

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

    2016-08-01

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

  4. Complete genome sequence and phenotype microarray analysis of Cronobacter sakazakii SP291: a persistent isolate cultured from a powdered infant formula production facility

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    Qiongqiong eYan

    2013-09-01

    Full Text Available Outbreaks of human infection linked to the powdered infant formula (PIF food chain and associated with the bacterium Cronobacter, are of concern to public health. These bacteria are regarded as opportunistic pathogens linked to life-threatening infections predominantly in neonates, with an under developed immune system. Monitoring the microbiological ecology of PIF production sites is an important step in attempting to limit the risk of contamination in the finished food product. Cronobacter species, like other microorganisms can adapt to the production environment. These organisms are known for their desiccation tolerance, a phenotype that can aid their survival in the production site and PIF itself. In evaluating the genome data currently available for Cronobacter species, no sequence information has been published describing a Cronobacter sakazakii isolate found to persist in a PIF production facility. Here we report on the complete genome sequence of one such isolate, Cronobacter sakazakii SP291 along with its phenotypic characteristics. The genome of C. sakazakii SP291 consists of a 4.3-Mb chromosome (56.9% GC and three plasmids, denoted as pSP291-1, [118.1-kb (57.2% GC], pSP291-2, [52.1-kb (49.2% GC] and pSP291-3, [4.4 -kb (54.0% GC]. When C. sakazakii SP291 was compared to the reference C. sakazakii ATCC BAA-894, which is also of PIF origin, the annotated genome data identified two interesting functional categories, comprising of genes related to the bacterial stress response and resistance to antimicrobial and toxic compounds. Using a phenotypic microarray (PM, we provided a full metabolic profile comparing C. sakazakii SP291 and the previously sequenced C. sakazakii ATCC BAA-894. These data extend our understanding of the genome of this important neonatal pathogen and provides further insights into the genotypes associated with features that can contribute to its persistence in the PIF environment.

  5. Complete genome sequence and phenotype microarray analysis of Cronobacter sakazakii SP291: a persistent isolate cultured from a powdered infant formula production facility.

    Science.gov (United States)

    Yan, Qiongqiong; Power, Karen A; Cooney, Shane; Fox, Edward; Gopinath, Gopal R; Grim, Christopher J; Tall, Ben D; McCusker, Matthew P; Fanning, Séamus

    2013-01-01

    Outbreaks of human infection linked to the powdered infant formula (PIF) food chain and associated with the bacterium Cronobacter, are of concern to public health. These bacteria are regarded as opportunistic pathogens linked to life-threatening infections predominantly in neonates, with an under developed immune system. Monitoring the microbiological ecology of PIF production sites is an important step in attempting to limit the risk of contamination in the finished food product. Cronobacter species, like other microorganisms can adapt to the production environment. These organisms are known for their desiccation tolerance, a phenotype that can aid their survival in the production site and PIF itself. In evaluating the genome data currently available for Cronobacter species, no sequence information has been published describing a Cronobacter sakazakii isolate found to persist in a PIF production facility. Here we report on the complete genome sequence of one such isolate, Cronobacter sakazakii SP291 along with its phenotypic characteristics. The genome of C. sakazakii SP291 consists of a 4.3-Mb chromosome (56.9% GC) and three plasmids, denoted as pSP291-1, [118.1-kb (57.2% GC)], pSP291-2, [52.1-kb (49.2% GC)], and pSP291-3, [4.4-kb (54.0% GC)]. When C. sakazakii SP291 was compared to the reference C. sakazakii ATCC BAA-894, which is also of PIF origin, the annotated genome data identified two interesting functional categories, comprising of genes related to the bacterial stress response and resistance to antimicrobial and toxic compounds. Using a phenotypic microarray (PM), we provided a full metabolic profile comparing C. sakazakii SP291 and the previously sequenced C. sakazakii ATCC BAA-894. These data extend our understanding of the genome of this important neonatal pathogen and provides further insights into the genotypes associated with features that can contribute to its persistence in the PIF environment.

  6. CGHScan: finding variable regions using high-density microarray comparative genomic hybridization data

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    Rajashekara Gireesh

    2006-04-01

    . Conclusion CGHScan is an effective tool for analyzing comparative genomic hybridization data from high-density microarrays. The algorithm is capable of accurately identifying known variable regions and is tolerant of high noise and varying methods of data preprocessing. Statistical analysis is used to define each variable region providing a robust and reliable method for rapid identification of genomic differences independent of annotated gene boundaries.

  7. The Impact of Photobleaching on Microarray Analysis

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    Marcel von der Haar

    2015-09-01

    Full Text Available DNA-Microarrays have become a potent technology for high-throughput analysis of genetic regulation. However, the wide dynamic range of signal intensities of fluorophore-based microarrays exceeds the dynamic range of a single array scan by far, thus limiting the key benefit of microarray technology: parallelization. The implementation of multi-scan techniques represents a promising approach to overcome these limitations. These techniques are, in turn, limited by the fluorophores’ susceptibility to photobleaching when exposed to the scanner’s laser light. In this paper the photobleaching characteristics of cyanine-3 and cyanine-5 as part of solid state DNA microarrays are studied. The effects of initial fluorophore intensity as well as laser scanner dependent variables such as the photomultiplier tube’s voltage on bleaching and imaging are investigated. The resulting data is used to develop a model capable of simulating the expected degree of signal intensity reduction caused by photobleaching for each fluorophore individually, allowing for the removal of photobleaching-induced, systematic bias in multi-scan procedures. Single-scan applications also benefit as they rely on pre-scans to determine the optimal scanner settings. These findings constitute a step towards standardization of microarray experiments and analysis and may help to increase the lab-to-lab comparability of microarray experiment results.

  8. Transcriptome analysis of zebrafish embryogenesis using microarrays.

    Directory of Open Access Journals (Sweden)

    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.

  9. 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.

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

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    Ball Catherine A

    2004-10-01

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

  11. Pineal function : Impact of microarray analysis

    NARCIS (Netherlands)

    Klein, David C.; Bailey, Michael J.; Carter, David A.; Kim, Jong-so; Shi, Qiong; Ho, Anthony K.; Chik, Constance L.; Gaildrat, Pascaline; Morin, Fabrice; Ganguly, Surajit; Rath, Martin F.; Moller, Morten; Sugden, David; Rangel, Zoila G.; Munson, Peter J.; Weller, Joan L.; Coon, Steven L.

    2010-01-01

    Microarray analysis has provided a new understanding of pineal function by identifying genes that are highly expressed in this tissue relative to other tissues and also by identifying over 600 genes that are expressed on a 24-h schedule. This effort has highlighted surprising similarity to the retin

  12. Assessing the significance of conserved genomic aberrations using high resolution genomic microarrays.

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    Mitchell Guttman

    2007-08-01

    Full Text Available Genomic aberrations recurrent in a particular cancer type can be important prognostic markers for tumor progression. Typically in early tumorigenesis, cells incur a breakdown of the DNA replication machinery that results in an accumulation of genomic aberrations in the form of duplications, deletions, translocations, and other genomic alterations. Microarray methods allow for finer mapping of these aberrations than has previously been possible; however, data processing and analysis methods have not taken full advantage of this higher resolution. Attention has primarily been given to analysis on the single sample level, where multiple adjacent probes are necessarily used as replicates for the local region containing their target sequences. However, regions of concordant aberration can be short enough to be detected by only one, or very few, array elements. We describe a method called Multiple Sample Analysis for assessing the significance of concordant genomic aberrations across multiple experiments that does not require a-priori definition of aberration calls for each sample. If there are multiple samples, representing a class, then by exploiting the replication across samples our method can detect concordant aberrations at much higher resolution than can be derived from current single sample approaches. Additionally, this method provides a meaningful approach to addressing population-based questions such as determining important regions for a cancer subtype of interest or determining regions of copy number variation in a population. Multiple Sample Analysis also provides single sample aberration calls in the locations of significant concordance, producing high resolution calls per sample, in concordant regions. The approach is demonstrated on a dataset representing a challenging but important resource: breast tumors that have been formalin-fixed, paraffin-embedded, archived, and subsequently UV-laser capture microdissected and hybridized to two

  13. Microarray Analysis of Serum mRNA in Patients with Head and Neck Squamous Cell Carcinoma at Whole-Genome Scale

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    Markéta Čapková

    2014-01-01

    Full Text Available With the increasing demand for noninvasive approaches in monitoring head and neck cancer, circulating nucleic acids have been shown to be a promising tool. We focused on the global transcriptome of serum samples of head and neck squamous cell carcinoma (HNSCC patients in comparison with healthy individuals. We compared gene expression patterns of 36 samples. Twenty-four participants including 16 HNSCC patients (from 12 patients we obtained blood samples 1 year posttreatment and 8 control subjects were recruited. The Illumina HumanWG-6 v3 Expression BeadChip was used to profile and identify the differences in serum mRNA transcriptomes. We found 159 genes to be significantly changed (Storey’s P value <0.05 between normal and cancer serum specimens regardless of factors including p53 and B-cell lymphoma family members (Bcl-2, Bcl-XL. In contrast, there was no difference in gene expression between samples obtained before and after surgery in cancer patients. We suggest that microarray analysis of serum cRNA in patients with HNSCC should be suitable for refinement of early stage diagnosis of disease that can be important for development of new personalized strategies in diagnosis and treatment of tumours but is not suitable for monitoring further development of disease.

  14. Expression profile analysis of the oxygen response in the nitrogen-fixing Pseudomonas stutzeri A1501 by genome-wide DNA microarray

    Institute of Scientific and Technical Information of China (English)

    DOU YueTan; YAN YongLiang; PING ShuZhen; LU Wei; CHEN Ming; ZHANG Wei; WANG YiPing; JIN Qi; LIN Min

    2008-01-01

    Pseudomonas stutzeri A1501, an associative nitrogen-fixing bacterium, was isolated from the rice paddy rhizosphere. This bacterium fixes nitrogen under microaerobic conditions. In this study, ge-nome-wide DNA microarrays were used to analyze the global transcription profile of A1501 under aerobic and microaerobic conditions. The expression of 135 genes was significantly altered by more than 2-fold in response to oxygen stress. Among these genes, 68 were down-regulated under aerobic conditions; these genes included those responsible for nitrogen fixation and denitrification. Sixty-seven genes were up-regulated under aerobic conditions; these genes included sodC, encoding a copper-zinc superoxide dismutase, PST2179, encoding an NAD(P)-dependent oxidoreductase, PST3584, encoding a 2OG-Fe(Ⅱ) oxygenase, and PST3602, encoding an NAD(P)H-flavin oxidoreductase. Addi-tionally, seven genes involved in capsular polysaccharide and antigen oligosaccharide biosynthesis together with 17 genes encoding proteins of unknown function were up-regulated under aerobic con-ditions. The overall analysis suggests that the genes we identified are involved in the protection of the bacterium from oxygen, but the mechanisms of their action remain to be elucidated.

  15. Chicken sperm transcriptome profiling by microarray analysis.

    Science.gov (United States)

    Singh, R P; Shafeeque, C M; Sharma, S K; Singh, R; Mohan, J; Sastry, K V H; Saxena, V K; Azeez, P A

    2016-03-01

    It has been confirmed that mammalian sperm contain thousands of functional RNAs, and some of them have vital roles in fertilization and early embryonic development. Therefore, we attempted to characterize transcriptome of the sperm of fertile chickens using microarray analysis. Spermatozoal RNA was pooled from 10 fertile males and used for RNA preparation. Prior to performing the microarray, RNA quality was assessed using a bioanalyzer, and gDNA and somatic cell RNA contamination was assessed by CD4 and PTPRC gene amplification. The chicken sperm transcriptome was cross-examined by analysing sperm and testes RNA on a 4 × 44K chicken array, and results were verified by RT-PCR. Microarray analysis identified 21,639 predominantly nuclear-encoded transcripts in chicken sperm. The majority (66.55%) of the sperm transcripts were shared with the testes, while surprisingly, 33.45% transcripts were detected (raw signal intensity greater than 50) only in the sperm and not in the testes. The greatest proportion of up-regulated transcripts were responsible for signal transduction (63.20%) followed by embryonic development (56.76%) and cell structure (56.25%). Of the 20 most abundant transcripts, 18 remain uncharacterized, whereas the least abundant genes were mostly associated with the ribosome. These findings lay a foundation for more detailed investigations on sperm RNAs in chickens to identify sperm-based biomarkers for fertility.

  16. 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…

  17. Analysis of tiling microarray data by learning vector quantization and relevance learning

    NARCIS (Netherlands)

    Biehl, Michael; Breitling, Rainer; Li, Yang; Yin, H; Tino, P; Corchado, E; Byrne, W; Yao,

    2007-01-01

    We apply learning vector quantization to the analysis of tiling microarray data. As an example we consider the classification of C. elegans genomic probes as intronic or exonic. Training is based on the current annotation of the genome. Relevance learning techniques are used to weight and select fea

  18. High throughput genetic analysis of congenital myasthenic syndromes using resequencing microarrays.

    Directory of Open Access Journals (Sweden)

    Lisa Denning

    Full Text Available BACKGROUND: The use of resequencing microarrays for screening multiple, candidate disease loci is a promising alternative to conventional capillary sequencing. We describe the performance of a custom resequencing microarray for mutational analysis of Congenital Myasthenic Syndromes (CMSs, a group of disorders in which the normal process of neuromuscular transmission is impaired. METHODOLOGY/PRINCIPAL FINDINGS: Our microarray was designed to assay the exons and flanking intronic regions of 8 genes linked to CMSs. A total of 31 microarrays were hybridized with genomic DNA from either individuals with known CMS mutations or from healthy controls. We estimated an overall microarray call rate of 93.61%, and we found the percentage agreement between the microarray and capillary sequencing techniques to be 99.95%. In addition, our microarray exhibited 100% specificity and 99.99% reproducibility. Finally, the microarray detected 22 out of the 23 known missense mutations, but it failed to detect all 7 known insertion and deletion (indels mutations, indicating an overall sensitivity of 73.33% and a sensitivity with respect to missense mutations of 95.65%. CONCLUSIONS/SIGNIFICANCE: Overall, our microarray prototype exhibited strong performance and proved highly efficient for screening genes associated with CMSs. Until indels can be efficiently assayed with this technology, however, we recommend using resequencing microarrays for screening CMS mutations after common indels have been first assayed by capillary sequencing.

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

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    Dai Yilin

    2012-06-01

    Full Text Available Abstract Background 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. Findings 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. Conclusion 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.

  20. Insights into genes involved in electricity generation in Geobacter sulfurreducens via whole genome microarray analysis of the OmcF-deficient mutant.

    Science.gov (United States)

    Kim, Byoung-Chan; Postier, Bradley L; Didonato, Raymond J; Chaudhuri, Swades K; Nevin, Kelly P; Lovley, Derek R

    2008-06-01

    Geobacter sulfurreducens effectively produces electricity in microbial fuel cells by oxidizing acetate with an electrode serving as the sole electron acceptor. Deletion of the gene encoding OmcF, a monoheme outer membrane c-type cytochrome, substantially decreased current production. Previous studies demonstrated that inhibition of Fe(III) reduction in the OmcF-deficient mutant could be attributed to poor transcription of the gene for OmcB, an outer membrane c-type cytochrome that is required for Fe(III) reduction. However, a mutant in which omcB was deleted produced electricity as well as wild type. Microarray analysis of the OmcF-deficient mutant versus the wild type revealed that many of the genes with the greatest decreases in transcript levels were genes whose expression was previously reported to be upregulated in cells grown with an electrode as the sole electron acceptor. These included genes with putative functions related to metal efflux and/or type I secretion and two hypothetical proteins. The outer membrane cytochromes, OmcS and OmcE, which previous studies have demonstrated are required for optimal current generation, were not detected on the outer surface of the OmcF-deficient mutant even though the omcS and omcE genes were still transcribed, suggesting that the putative secretion system could be involved in the export of outer membrane proteins necessary for electron transfer to the fuel cell anode. These results suggest that the requirement for OmcF for optimal current production is not because OmcF is directly involved in extracellular electron transfer but because OmcF is required for the appropriate transcription of other genes either directly or indirectly involved in electricity production.

  1. Genome-wide copy number profiling on high-density bacterial artificial chromosomes, single-nucleotide polymorphisms, and oligonucleotide microarrays: a platform comparison based on statistical power analysis.

    NARCIS (Netherlands)

    Hehir-Kwa, J.Y.; Egmont-Peterson, M.; Janssen, I.M.; Smeets, D.F.C.M.; Geurts van Kessel, A.H.M.; Veltman, J.A.

    2007-01-01

    Recently, comparative genomic hybridization onto bacterial artificial chromosome (BAC) arrays (array-based comparative genomic hybridization) has proved to be successful for the detection of submicroscopic DNA copy-number variations in health and disease. Technological improvements to achieve a

  2. Phylogenetic Analysis of Shewanella Strains by DNA Relatedness Derived from Whole Genome Microarray DNA-DNA Hybridization and Comparison with Other Methods

    Energy Technology Data Exchange (ETDEWEB)

    Wu, Liyou; Yi, T. Y.; Van Nostrand, Joy; Zhou, Jizhong

    2010-05-17

    Phylogenetic analyses were done for the Shewanella strains isolated from Baltic Sea (38 strains), US DOE Hanford Uranium bioremediation site [Hanford Reach of the Columbia River (HRCR), 11 strains], Pacific Ocean and Hawaiian sediments (8 strains), and strains from other resources (16 strains) with three out group strains, Rhodopseudomonas palustris, Clostridium cellulolyticum, and Thermoanaerobacter ethanolicus X514, using DNA relatedness derived from WCGA-based DNA-DNA hybridizations, sequence similarities of 16S rRNA gene and gyrB gene, and sequence similarities of 6 loci of Shewanella genome selected from a shared gene list of the Shewanella strains with whole genome sequenced based on the average nucleotide identity of them (ANI). The phylogenetic trees based on 16S rRNA and gyrB gene sequences, and DNA relatedness derived from WCGA hybridizations of the tested Shewanella strains share exactly the same sub-clusters with very few exceptions, in which the strains were basically grouped by species. However, the phylogenetic analysis based on DNA relatedness derived from WCGA hybridizations dramatically increased the differentiation resolution at species and strains level within Shewanella genus. When the tree based on DNA relatedness derived from WCGA hybridizations was compared to the tree based on the combined sequences of the selected functional genes (6 loci), we found that the resolutions of both methods are similar, but the clustering of the tree based on DNA relatedness derived from WMGA hybridizations was clearer. These results indicate that WCGA-based DNA-DNA hybridization is an idea alternative of conventional DNA-DNA hybridization methods and it is superior to the phylogenetics methods based on sequence similarities of single genes. Detailed analysis is being performed for the re-classification of the strains examined.

  3. Genomic and microarray analysis of aromatics degradation in Geobacter metallireducens and comparison to a Geobacter isolate from a contaminated field site

    Directory of Open Access Journals (Sweden)

    Zhou Jizhong

    2007-06-01

    Full Text Available Abstract Background Groundwater and subsurface environments contaminated with aromatic compounds can be remediated in situ by Geobacter species that couple oxidation of these compounds to reduction of Fe(III-oxides. Geobacter metallireducens metabolizes many aromatic compounds, but the enzymes involved are not well known. Results The complete G. metallireducens genome contained a 300 kb island predicted to encode enzymes for the degradation of phenol, p-cresol, 4-hydroxybenzaldehyde, 4-hydroxybenzoate, benzyl alcohol, benzaldehyde, and benzoate. Toluene degradation genes were encoded in a separate region. None of these genes was found in closely related species that cannot degrade aromatic compounds. Abundant transposons and phage-like genes in the island suggest mobility, but nucleotide composition and lack of synteny with other species do not suggest a recent transfer. The inferred degradation pathways are similar to those in species that anaerobically oxidize aromatic compounds with nitrate as an electron acceptor. In these pathways the aromatic compounds are converted to benzoyl-CoA and then to 3-hydroxypimelyl-CoA. However, in G. metallireducens there were no genes for the energetically-expensive dearomatizing enzyme. Whole-genome changes in transcript levels were identified in cells oxidizing benzoate. These supported the predicted pathway, identified induced fatty-acid oxidation genes, and identified an apparent shift in the TCA cycle to a putative ATP-yielding succinyl-CoA synthase. Paralogs to several genes in the pathway were also induced, as were several putative molybdo-proteins. Comparison of the aromatics degradation pathway genes to the genome of an isolate from a contaminated field site showed very similar content, and suggested this strain degrades many of the same compounds. This strain also lacked a classical dearomatizing enzyme, but contained two copies of an eight-gene cluster encoding redox proteins that was 30-fold

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

    Science.gov (United States)

    Yang, Jianji; Cohen, Aaron; Hersh, William

    2009-02-05

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

  5. Microarray analysis of p-anisaldehyde-induced transcriptome of Saccharomyces cerevisiae.

    Science.gov (United States)

    Yu, Lu; Guo, Na; Yang, Yi; Wu, Xiuping; Meng, Rizeng; Fan, Junwen; Ge, Fa; Wang, Xuelin; Liu, Jingbo; Deng, Xuming

    2010-03-01

    p-Anisaldehyde (4-methoxybenzaldehyde), an extract from Pimpinella anisum L. seeds, is a potential novel preservative. To reveal the possible action mechanism of p-anisaldehyde against microorganisms, yeast-based commercial oligonucleotide microarrays were used to analyze the genome-wide transcriptional changes in response to p-anisaldehyde. Quantitative real-time RT-PCR was performed for selected genes to verify the microarray results. We interpreted our microarray data with the clustering tool, T-profiler. Analysis of microarray data revealed that p-anisaldehyde induced the expression of genes related to sulphur assimilation, aromatic aldehydes metabolism, and secondary metabolism, which demonstrated that the addition of p-anisaldehyde may influence the normal metabolism of aromatic aldehydes. This genome-wide transcriptomics approach revealed first insights into the response of Saccharomyces cerevisiae (S. cerevisiae) to p-anisaldehyde challenge.

  6. Genome-wide copy number profiling on high-density bacterial artificial chromosomes, single-nucleotide polymorphisms, and oligonucleotide microarrays: a platform comparison based on statistical power analysis.

    NARCIS (Netherlands)

    Hehir-Kwa, J.Y.; Egmont-Peterson, M.; Janssen, I.M.; Smeets, D.F.C.M.; Geurts van Kessel, A.H.M.; Veltman, J.A.

    2007-01-01

    Recently, comparative genomic hybridization onto bacterial artificial chromosome (BAC) arrays (array-based comparative genomic hybridization) has proved to be successful for the detection of submicroscopic DNA copy-number variations in health and disease. Technological improvements to achieve a high

  7. Visualization methods for statistical analysis of microarray clusters

    Directory of Open Access Journals (Sweden)

    Li Kai

    2005-05-01

    Full Text Available Abstract Background The most common method of identifying groups of functionally related genes in microarray data is to apply a clustering algorithm. However, it is impossible to determine which clustering algorithm is most appropriate to apply, and it is difficult to verify the results of any algorithm due to the lack of a gold-standard. Appropriate data visualization tools can aid this analysis process, but existing visualization methods do not specifically address this issue. Results We present several visualization techniques that incorporate meaningful statistics that are noise-robust for the purpose of analyzing the results of clustering algorithms on microarray data. This includes a rank-based visualization method that is more robust to noise, a difference display method to aid assessments of cluster quality and detection of outliers, and a projection of high dimensional data into a three dimensional space in order to examine relationships between clusters. Our methods are interactive and are dynamically linked together for comprehensive analysis. Further, our approach applies to both protein and gene expression microarrays, and our architecture is scalable for use on both desktop/laptop screens and large-scale display devices. This methodology is implemented in GeneVAnD (Genomic Visual ANalysis of Datasets and is available at http://function.princeton.edu/GeneVAnD. Conclusion Incorporating relevant statistical information into data visualizations is key for analysis of large biological datasets, particularly because of high levels of noise and the lack of a gold-standard for comparisons. We developed several new visualization techniques and demonstrated their effectiveness for evaluating cluster quality and relationships between clusters.

  8. High-resolution genomic microarrays for X-linked mental retardation.

    NARCIS (Netherlands)

    Lugtenberg, D.; Veltman, J.A.; Bokhoven, J.H.L.M. van

    2007-01-01

    Developments in genomic microarray technology have revolutionized the study of human genomic copy number variation. This has significantly affected many areas in human genetics, including the field of X-linked mental retardation (XLMR). Chromosome X-specific bacterial artificial chromosomes

  9. High-resolution genomic microarrays for X-linked mental retardation.

    NARCIS (Netherlands)

    Lugtenberg, D.; Veltman, J.A.; Bokhoven, J.H.L.M. van

    2007-01-01

    Developments in genomic microarray technology have revolutionized the study of human genomic copy number variation. This has significantly affected many areas in human genetics, including the field of X-linked mental retardation (XLMR). Chromosome X-specific bacterial artificial chromosomes microarr

  10. Construction and Evaluation of Desulfovibrio vulgaris Whole-Genome Oligonucleotide Microarrays

    Energy Technology Data Exchange (ETDEWEB)

    Z. He; Q. He; L. Wu; M.E. Clark; J.D. Wall; Jizhong Zhou; Matthew W. Fields

    2004-03-17

    Desulfovibrio vulgaris Hildenborough has been the focus of biochemical and physiological studies in the laboratory, and the metabolic versatility of this organism has been largely recognized, particularly the reduction of sulfate, fumarate, iron, uranium and chromium. In addition, a Desulfovibrio sp. has been shown to utilize uranium as the sole electron acceptor. D. vulgaris is a d-Proteobacterium with a genome size of 3.6 Mb and 3584 ORFs. The whole-genome microarrays of D. vulgaris have been constructed using 70mer oligonucleotides. All ORFs in the genome were represented with 3471 (97.1%) unique probes and 103 (2.9%) non-specific probes that may have cross-hybridization with other ORFs. In preparation for use of the experimental microarrays, artificial probes and targets were designed to assess specificity and sensitivity and identify optimal hybridization conditions for oligonucleotide microarrays. The results indicated that for 50mer and 70mer oligonucleotide arrays, hybridization at 45 C to 50 C, washing at 37 C and a wash time of 2.5 to 5 minutes obtained specific and strong hybridization signals. In order to evaluate the performance of the experimental microarrays, growth conditions were selected that were expected to give significant hybridization differences for different sets of genes. The initial evaluations were performed using D. vulgaris cells grown at logarithmic and stationary phases. Transcriptional analysis of D. vulgaris cells sampled during logarithmic phase growth indicated that 25% of annotated ORFs were up-regulated and 3% of annotated ORFs were downregulated compared to stationary phase cells. The up-regulated genes included ORFs predicted to be involved with acyl chain biosynthesis, amino acid ABC transporter, translational initiation factors, and ribosomal proteins. In the stationary phase growth cells, the two most up-regulated ORFs (70-fold) were annotated as a carboxynorspermidine decarboxylase and a 2C-methyl-D-erythritol-2

  11. Identification of candidate genes in osteoporosis by integrated microarray analysis

    OpenAIRE

    Li, J J; Wang, B. Q.; Fei, Q.; Yang, Y; Li, D.

    2017-01-01

    Objectives In order to screen the altered gene expression profile in peripheral blood mononuclear cells of patients with osteoporosis, we performed an integrated analysis of the online microarray studies of osteoporosis. Methods We searched the Gene Expression Omnibus (GEO) database for microarray studies of peripheral blood mononuclear cells in patients with osteoporosis. Subsequently, we integrated gene expression data sets from multiple microarray studies to obtain differentially expressed...

  12. Analysis of antisense expression by whole genome tiling microarrays and siRNAs suggests mis-annotation of Arabidopsis orphan protein-coding genes.

    Directory of Open Access Journals (Sweden)

    Casey R Richardson

    Full Text Available BACKGROUND: MicroRNAs (miRNAs and trans-acting small-interfering RNAs (tasi-RNAs are small (20-22 nt long RNAs (smRNAs generated from hairpin secondary structures or antisense transcripts, respectively, that regulate gene expression by Watson-Crick pairing to a target mRNA and altering expression by mechanisms related to RNA interference. The high sequence homology of plant miRNAs to their targets has been the mainstay of miRNA prediction algorithms, which are limited in their predictive power for other kingdoms because miRNA complementarity is less conserved yet transitive processes (production of antisense smRNAs are active in eukaryotes. We hypothesize that antisense transcription and associated smRNAs are biomarkers which can be computationally modeled for gene discovery. PRINCIPAL FINDINGS: We explored rice (Oryza sativa sense and antisense gene expression in publicly available whole genome tiling array transcriptome data and sequenced smRNA libraries (as well as C. elegans and found evidence of transitivity of MIRNA genes similar to that found in Arabidopsis. Statistical analysis of antisense transcript abundances, presence of antisense ESTs, and association with smRNAs suggests several hundred Arabidopsis 'orphan' hypothetical genes are non-coding RNAs. Consistent with this hypothesis, we found novel Arabidopsis homologues of some MIRNA genes on the antisense strand of previously annotated protein-coding genes. A Support Vector Machine (SVM was applied using thermodynamic energy of binding plus novel expression features of sense/antisense transcription topology and siRNA abundances to build a prediction model of miRNA targets. The SVM when trained on targets could predict the "ancient" (deeply conserved class of validated Arabidopsis MIRNA genes with an accuracy of 84%, and 76% for "new" rapidly-evolving MIRNA genes. CONCLUSIONS: Antisense and smRNA expression features and computational methods may identify novel MIRNA genes and other non

  13. Microarray-based genomic profiling as a diagnostic tool in acute lymphoblastic leukemia.

    Science.gov (United States)

    Simons, Annet; Stevens-Kroef, Marian; El Idrissi-Zaynoun, Najat; van Gessel, Sabine; Weghuis, Daniel Olde; van den Berg, Eva; Waanders, Esmé; Hoogerbrugge, Peter; Kuiper, Roland; van Kessel, Ad Geurts

    2011-12-01

    In acute lymphoblastic leukemia (ALL) specific genomic abnormalities provide important clinical information. In most routine clinical diagnostic laboratories conventional karyotyping, in conjunction with targeted screens using e.g., fluorescence in situ hybridization (FISH), is currently considered as the gold standard to detect such aberrations. Conventional karyotyping, however, is limited in its resolution and yield, thus hampering the genetic diagnosis of ALL. We explored whether microarray-based genomic profiling would be feasible as an alternative strategy in a routine clinical diagnostic setting. To this end, we compared conventional karyotypes with microarray-deduced copy number aberration (CNA) karyotypes in 60 ALL cases. Microarray-based genomic profiling resulted in a CNA detection rate of 90%, whereas for conventional karyotyping this was 61%. In addition, many small (< 5 Mb) genetic lesions were encountered, frequently harboring clinically relevant ALL-related genes such as CDKN2A/B, ETV6, PAX5, and IKZF1. From our data we conclude that microarray-based genomic profiling serves as a robust tool in the genetic diagnosis of ALL, outreaching conventional karyotyping in CNA detection both in terms of sensitivity and specificity. We also propose a practical workflow for a comprehensive and objective interpretation of CNAs obtained through microarray-based genomic profiling, thereby facilitating its application in a routine clinical diagnostic setting.

  14. Microarray MAPH: accurate array-based detection of relative copy number in genomic DNA

    Directory of Open Access Journals (Sweden)

    Chan Alan

    2006-06-01

    Full Text Available Abstract Background 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. Results 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. Conclusion 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.

  15. 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.

  16. Comparison of three microarray probe annotation pipelines: differences in strategies and their effect on downstream analysis

    NARCIS (Netherlands)

    Neerincx, P.B.T.; Casel, P.; Prickett, D.; Nie, H.; Watson, M.; Leunissen, J.A.M.; Groenen, M.A.M.; Klopp, C.

    2009-01-01

    Background - Reliable annotation linking oligonucleotide probes to target genes is essential for functional biological analysis of microarray experiments. We used the IMAD, OligoRAP and sigReannot pipelines to update the annotation for the ARK-Genomics Chicken 20 K array as part of a joined EADGENE/

  17. Comparison of three microarray probe annotation pipelines: differences in strategies and their effect on downstream analysis

    NARCIS (Netherlands)

    Neerincx, P.B.T.; Casel, P.; Prickett, D.; Nie, H.; Watson, M.; Leunissen, J.A.M.; Groenen, M.A.M.; Klopp, C.

    2009-01-01

    Background - Reliable annotation linking oligonucleotide probes to target genes is essential for functional biological analysis of microarray experiments. We used the IMAD, OligoRAP and sigReannot pipelines to update the annotation for the ARK-Genomics Chicken 20 K array as part of a joined EADGENE/

  18. Microarrays--analysis of signaling pathways.

    Science.gov (United States)

    Ramachandran, Anassuya; Black, Michael A; Shelling, Andrew N; Love, Donald R

    2008-01-01

    Microarrays provide a powerful means of analyzing the expression level of multiple transcripts in two sample populations. In this study, we have used microarray technology to identify genes that are differentially regulated in response to activin-treated ovarian cancer cells. We find a number of biologically relevant genes that are involved in regulating activin signaling and genes potentially contributing to activin-mediated growth arrest appear to be differentially regulated. Thus, microarrays are an important tool for dissecting gene expression changes in normal physiological processes and disease.

  19. POLAR MODELLING AND SEGMENTATION OF GENOMIC MICROARRAY SPOTS USING MATHEMATICAL MORPHOLOGY

    Directory of Open Access Journals (Sweden)

    Jesús Angulo

    2011-05-01

    Full Text Available Robust image analysis of spots in microarrays (quality control + spot segmentation + quantification is a requirement for automated software which is of fundamental importance for a high-throughput analysis of genomics microarray-based data. This paper deals with the development of model-based image processing algorithms for qualifying/segmenting/quantifying adaptively each spot according to its morphology. A series of morphologicalmodels for spot intensities are introduced. The spot typologies representmost of the possible qualitative cases identified from a large database (different routines, techniques, etc.. Then, based on these spot models, a classification framework has been developed. The spot feature extraction and classification (without segmenting is based on converting the spot image to polar coordinates and, after computing the radial/angular projections, the calculation of granulometric curves and derived parameters from these projections. Spot contour segmentation can also be solved by working in polar coordinates, calculating the up/downminimal path, which is easily obtained with the generalized distance function. With this model-based technique, the segmentation can be regularised by controlling different elements of the algorithm. According to the spot typology (e.g., doughnut-like or egg-like spots, several minimal paths can be computed to obtain a multi-region segmentation. Moreover, this segmentation is more robust and sensible to weak spots, improving the previous approaches.

  20. Microarray-based whole-genome hybridization as a tool for determining procaryotic species relatedness

    Energy Technology Data Exchange (ETDEWEB)

    Wu, L.; Liu, X.; Fields, M.W.; Thompson, D.K.; Bagwell, C.E.; Tiedje, J. M.; Hazen, T.C.; Zhou, J.

    2008-01-15

    The definition and delineation of microbial species are of great importance and challenge due to the extent of evolution and diversity. Whole-genome DNA-DNA hybridization is the cornerstone for defining procaryotic species relatedness, but obtaining pairwise DNA-DNA reassociation values for a comprehensive phylogenetic analysis of procaryotes is tedious and time consuming. A previously described microarray format containing whole-genomic DNA (the community genome array or CGA) was rigorously evaluated as a high-throughput alternative to the traditional DNA-DNA reassociation approach for delineating procaryotic species relationships. DNA similarities for multiple bacterial strains obtained with the CGA-based hybridization were comparable to those obtained with various traditional whole-genome hybridization methods (r=0.87, P<0.01). Significant linear relationships were also observed between the CGA-based genome similarities and those derived from small subunit (SSU) rRNA gene sequences (r=0.79, P<0.0001), gyrB sequences (r=0.95, P<0.0001) or REP- and BOX-PCR fingerprinting profiles (r=0.82, P<0.0001). The CGA hybridization-revealed species relationships in several representative genera, including Pseudomonas, Azoarcus and Shewanella, were largely congruent with previous classifications based on various conventional whole-genome DNA-DNA reassociation, SSU rRNA and/or gyrB analyses. These results suggest that CGA-based DNA-DNA hybridization could serve as a powerful, high-throughput format for determining species relatedness among microorganisms.

  1. Genomewide expression analysis in amino acid-producing bacteria using DNA microarrays.

    Science.gov (United States)

    Polen, Tino; Wendisch, Volker F

    2004-01-01

    DNA microarray technology has become an important research tool for biotechnology and microbiology. It is now possible to characterize genetic diversity and gene expression in a genomewide manner. DNA microarrays have been applied extensively to study the biology of many bacteria including Escherichia coli, but only recently have they been developed for the Gram-positive Corynebacterium glutamicum. Both bacteria are widely used for biotechnological amino acid production. In this article, in addition to the design and generation of microarrays as well as their use in hybridization experiments and subsequent data analysis, we describe recent applications of DNA microarray technology regarding amino acid production in C. glutamicum and E. coli. We also discuss the impact of functional genomics studies on fundamental as well as applied aspects of amino acid production with C. glutamicum and E. coli.

  2. Rare copy number alterations and copy-neutral loss of heterozygosity revealed in ameloblastomas by high-density whole-genome microarray analysis

    DEFF Research Database (Denmark)

    Diniz, Marina Gonçalves; Duarte, Alessandra Pires; Villacis, Rolando A

    2017-01-01

    BACKGROUND: Ameloblastoma (unicystic, UA, or multicystic, MA) is a rare tumor associated with bone destruction and facial deformity. Its malignant counterpart is the ameloblastic carcinoma (AC). The BRAFV600E mutation is highly prevalent in all these tumors subtypes and cannot account for their d......BACKGROUND: Ameloblastoma (unicystic, UA, or multicystic, MA) is a rare tumor associated with bone destruction and facial deformity. Its malignant counterpart is the ameloblastic carcinoma (AC). The BRAFV600E mutation is highly prevalent in all these tumors subtypes and cannot account......, and PPP2R5A) covered by rare alterations, also including three MA and four normal oral tissues. RESULTS: Fifty-seven CNAs and cnLOH were observed in the ameloblastomas and six CNAs in the AC. Seven of the CNAs were rare (six in UA and one in MA), four of them encompassing genes (gains of 7q11.21, 1q32......: Ameloblastomas show rare CNAs and cnLOH, presenting a specific genomic profile with no overlapping of the rare alterations among UA, MA, and AC. These genomic changes might play a role in tumor evolution and in BRAFV600E-negative tumors....

  3. Automatic Spot Identification for High Throughput Microarray Analysis

    Science.gov (United States)

    Wu, Eunice; Su, Yan A.; Billings, Eric; Brooks, Bernard R.; Wu, Xiongwu

    2013-01-01

    High throughput microarray analysis has great potential in scientific research, disease diagnosis, and drug discovery. A major hurdle toward high throughput microarray analysis is the time and effort needed to accurately locate gene spots in microarray images. An automatic microarray image processor will allow accurate and efficient determination of spot locations and sizes so that gene expression information can be reliably extracted in a high throughput manner. Current microarray image processing tools require intensive manual operations in addition to the input of grid parameters to correctly and accurately identify gene spots. This work developed a method, herein called auto-spot, to automate the spot identification process. Through a series of correlation and convolution operations, as well as pixel manipulations, this method makes spot identification an automatic and accurate process. Testing with real microarray images has demonstrated that this method is capable of automatically extracting subgrids from microarray images and determining spot locations and sizes within each subgrid, regardless of variations in array patterns and background noises. With this method, we are one step closer to the goal of high throughput microarray analysis. PMID:24298393

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

    Directory of Open Access Journals (Sweden)

    Gray Joanna

    2010-11-01

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

  5. Enhancing interdisciplinary mathematics and biology education: a microarray data analysis course bridging these disciplines.

    Science.gov (United States)

    Tra, Yolande V; Evans, Irene M

    2010-01-01

    BIO2010 put forth the goal of improving the mathematical educational background of biology students. The analysis and interpretation of microarray high-dimensional data can be very challenging and is best done by a statistician and a biologist working and teaching in a collaborative manner. We set up such a collaboration and designed a course on microarray data analysis. We started using Genome Consortium for Active Teaching (GCAT) materials and Microarray Genome and Clustering Tool software and added R statistical software along with Bioconductor packages. In response to student feedback, one microarray data set was fully analyzed in class, starting from preprocessing to gene discovery to pathway analysis using the latter software. A class project was to conduct a similar analysis where students analyzed their own data or data from a published journal paper. This exercise showed the impact that filtering, preprocessing, and different normalization methods had on gene inclusion in the final data set. We conclude that this course achieved its goals to equip students with skills to analyze data from a microarray experiment. We offer our insight about collaborative teaching as well as how other faculty might design and implement a similar interdisciplinary course.

  6. Enhancing Interdisciplinary Mathematics and Biology Education: A Microarray Data Analysis Course Bridging These Disciplines

    Science.gov (United States)

    Evans, Irene M.

    2010-01-01

    BIO2010 put forth the goal of improving the mathematical educational background of biology students. The analysis and interpretation of microarray high-dimensional data can be very challenging and is best done by a statistician and a biologist working and teaching in a collaborative manner. We set up such a collaboration and designed a course on microarray data analysis. We started using Genome Consortium for Active Teaching (GCAT) materials and Microarray Genome and Clustering Tool software and added R statistical software along with Bioconductor packages. In response to student feedback, one microarray data set was fully analyzed in class, starting from preprocessing to gene discovery to pathway analysis using the latter software. A class project was to conduct a similar analysis where students analyzed their own data or data from a published journal paper. This exercise showed the impact that filtering, preprocessing, and different normalization methods had on gene inclusion in the final data set. We conclude that this course achieved its goals to equip students with skills to analyze data from a microarray experiment. We offer our insight about collaborative teaching as well as how other faculty might design and implement a similar interdisciplinary course. PMID:20810954

  7. Genome-wide microarray-based analysis of miRNAs expression in patients with acute-on-chronic liver failure

    Institute of Scientific and Technical Information of China (English)

    Wen Chen; Ze-Hui Yan; Yu-Ming Wang; Bao-Yan Xu; Guo-Hong Deng

    2014-01-01

    BACKGROUND: Acute-on-chronic liver failure (ACLF) is a severe clinical syndrome that may cause a high mortality. However, the mechanism is still not clear. Characterization of the microRNA (miRNA) proifles in ACLF patients may provide new clues to the pathogenesis and management of this syndrome. METHODS: Genome-wide  microarray  was  performed  to compare the different miRNA expression proifles in peripheral blood mononuclear cells of a pair of monozygotic twins, an ACLF patient and an HBV asymptomatic carrier (AsC). The case-control miRNA proifles were compared and conifrmed by quantitative reverse transcription-polymerase chain reaction in 104 ACLF patients and 96 AsCs. A combined computational prediction algorithm was used to predict the potential target genes. RESULTS: Forty-ifve miRNAs were increased and eight miRNAs were decreased in the ACLF group. The expressions of hsa-let-7a and hsa-miR-16 were increased by 8.58- and 8.63-fold in ACLF patients compared with that in AsCs, respectively (P CONCLUSIONS: Our  results  showed  that  there  is  a  close relationship  between  speciifc  miRNAs  of  peripheral  blood mononuclear cells and ACLF. hsa-miR-16 and hsa-let-7a may contribute to the development of ACLF.

  8. Bulk segregant analysis using single nucleotide polymorphism microarrays.

    Directory of Open Access Journals (Sweden)

    Anthony Becker

    Full Text Available Bulk segregant analysis (BSA using microarrays, and extreme array mapping (XAM have recently been used to rapidly identify genomic regions associated with phenotypes in multiple species. These experiments, however, require the identification of single feature polymorphisms (SFP between the cross parents for each new combination of genotypes, which raises the cost of experiments. The availability of the genomic polymorphism data in Arabidopsis thaliana, coupled with the efficient designs of Single Nucleotide Polymorphism (SNP genotyping arrays removes the requirement for SFP detection and lowers the per array cost, thereby lowering the overall cost per experiment. To demonstrate that these approaches would be functional on SNP arrays and determine confidence intervals, we analyzed hybridizations of natural accessions to the Arabidopsis ATSNPTILE array and simulated BSA or XAM given a variety of gene models, populations, and bulk selection parameters. Our results show a striking degree of correlation between the genotyping output of both methods, which suggests that the benefit of SFP genotyping in context of BSA can be had with the cheaper, more efficient SNP arrays. As a final proof of concept, we hybridized the DNA from bulks of an F2 mapping population of a Sulfur and Selenium ionomics mutant to both the Arabidopsis ATTILE1R and ATSNPTILE arrays, which produced almost identical results. We have produced R scripts that prompt the user for the required parameters and perform the BSA analysis using the ATSNPTILE1 array and have provided them as supplemental data files.

  9. Two heuristic approaches to describe periodicities in genomic microarrays

    Directory of Open Access Journals (Sweden)

    Jörg Aßmus

    2009-09-01

    Full Text Available In the first part we discuss the filtering of panels of time series based on singular value decomposition. The discussion is based on an approach where this filtering is used to normalize microarray data. We point out effects on the periodicity and phases for time series panels. In the second part we investigate time dependent periodic panels with different phases. We align the time series in the panel and discuss the periodogram of the aligned time series with the purpose of describing the periodic structure of the panel. The method is quite powerful assuming known phases in the model, but it deteriorates rapidly for noisy data.  

  10. Microarray Applications in Cancer Research

    Science.gov (United States)

    Kim, Il-Jin; Kang, Hio Chung

    2004-01-01

    DNA microarray technology permits simultaneous analysis of thousands of DNA sequences for genomic research and diagnostics applications. Microarray technology represents the most recent and exciting advance in the application of hybridization-based technology for biological sciences analysis. This review focuses on the classification (oligonucleotide vs. cDNA) and application (mutation-genotyping vs. gene expression) of microarrays. Oligonucleotide microarrays can be used both in mutation-genotyping and gene expression analysis, while cDNA microarrays can only be used in gene expression analysis. We review microarray mutation analysis, including examining the use of three oligonucleotide microarrays developed in our laboratory to determine mutations in RET, β-catenin and K-ras genes. We also discuss the use of the Affymetrix GeneChip in mutation analysis. We review microarray gene expression analysis, including the classifying of such studies into four categories: class comparison, class prediction, class discovery and identification of biomarkers. PMID:20368836

  11. 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.

  12. Differential analysis for high density tiling microarray data

    Directory of Open Access Journals (Sweden)

    Kapranov Philipp

    2007-09-01

    Full Text Available Abstract Background High density oligonucleotide tiling arrays are an effective and powerful platform for conducting unbiased genome-wide studies. The ab initio probe selection method employed in tiling arrays is unbiased, and thus ensures consistent sampling across coding and non-coding regions of the genome. These arrays are being increasingly used to study the associated processes of transcription, transcription factor binding, chromatin structure and their association. Studies of differential expression and/or regulation provide critical insight into the mechanics of transcription and regulation that occurs during the developmental program of a cell. The time-course experiment, which comprises an in-vivo system and the proposed analyses, is used to determine if annotated and un-annotated portions of genome manifest coordinated differential response to the induced developmental program. Results We have proposed a novel approach, based on a piece-wise function – to analyze genome-wide differential response. This enables segmentation of the response based on protein-coding and non-coding regions; for genes the methodology also partitions differential response with a 5' versus 3' versus intra-genic bias. Conclusion The algorithm built upon the framework of Significance Analysis of Microarrays, uses a generalized logic to define regions/patterns of coordinated differential change. By not adhering to the gene-centric paradigm, discordant differential expression patterns between exons and introns have been identified at a FDR of less than 12 percent. A co-localization of differential binding between RNA Polymerase II and tetra-acetylated histone has been quantified at a p-value -13. The prototype R code has been made available as supplementary material [see Additional file 1]. Additional file 1 gsam_prototypercode.zip. File archive comprising of prototype R code for gSAM implementation including readme and examples. Click here for file

  13. Differential analysis for high density tiling microarray data.

    Science.gov (United States)

    Ghosh, Srinka; Hirsch, Heather A; Sekinger, Edward A; Kapranov, Philipp; Struhl, Kevin; Gingeras, Thomas R

    2007-09-24

    High density oligonucleotide tiling arrays are an effective and powerful platform for conducting unbiased genome-wide studies. The ab initio probe selection method employed in tiling arrays is unbiased, and thus ensures consistent sampling across coding and non-coding regions of the genome. These arrays are being increasingly used to study the associated processes of transcription, transcription factor binding, chromatin structure and their association. Studies of differential expression and/or regulation provide critical insight into the mechanics of transcription and regulation that occurs during the developmental program of a cell. The time-course experiment, which comprises an in-vivo system and the proposed analyses, is used to determine if annotated and un-annotated portions of genome manifest coordinated differential response to the induced developmental program. We have proposed a novel approach, based on a piece-wise function - to analyze genome-wide differential response. This enables segmentation of the response based on protein-coding and non-coding regions; for genes the methodology also partitions differential response with a 5' versus 3' versus intra-genic bias. The algorithm built upon the framework of Significance Analysis of Microarrays, uses a generalized logic to define regions/patterns of coordinated differential change. By not adhering to the gene-centric paradigm, discordant differential expression patterns between exons and introns have been identified at a FDR of less than 12 percent. A co-localization of differential binding between RNA Polymerase II and tetra-acetylated histone has been quantified at a p-value < 0.003; it is most significant at the 5' end of genes, at a p-value < 10-13. The prototype R code has been made available as supplementary material [see Additional file 1].

  14. Functional genomics in chickens: development of integrated-systems microarrays for transcriptional profiling and discovery of regulatory pathways.

    Science.gov (United States)

    Cogburn, L A; Wang, X; Carre, W; Rejto, L; Aggrey, S E; Duclos, M J; Simon, J; Porter, T E

    2004-01-01

    The genetic networks that govern the differentiation and growth of major tissues of economic importance in the chicken are largely unknown. Under a functional genomics project, our consortium has generated 30 609 expressed sequence tags (ESTs) and developed several chicken DNA microarrays, which represent the Chicken Metabolic/Somatic (10 K) and Neuroendocrine/Reproductive (8 K) Systems (http://udgenome.ags.udel.edu/cogburn/). One of the major challenges facing functional genomics is the development of mathematical models to reconstruct functional gene networks and regulatory pathways from vast volumes of microarray data. In initial studies with liver-specific microarrays (3.1 K), we have examined gene expression profiles in liver during the peri-hatch transition and during a strong metabolic perturbation-fasting and re-feeding-in divergently selected broiler chickens (fast vs. slow-growth lines). The expression of many genes controlling metabolic pathways is dramatically altered by these perturbations. Our analysis has revealed a large number of clusters of functionally related genes (mainly metabolic enzymes and transcription factors) that control major metabolic pathways. Currently, we are conducting transcriptional profiling studies of multiple tissues during development of two sets of divergently selected broiler chickens (fast vs. slow growing and fat vs. lean lines). Transcriptional profiling across multiple tissues should permit construction of a detailed genetic blueprint that illustrates the developmental events and hierarchy of genes that govern growth and development of chickens. This review will briefly describe the recent acquisition of chicken genomic resources (ESTs and microarrays) and our consortium's efforts to help launch the new era of functional genomics in the chicken.

  15. Glycan microarray analysis of Candida glabrata adhesin ligand specificity

    National Research Council Canada - National Science Library

    Zupancic, Margaret L; Frieman, Matthew; Smith, David; Alvarez, Richard A; Cummings, Richard D; Cormack, Brendan P

    2008-01-01

    ...) family responsible for mediating adherence to host cells. To better understand the mechanism by which the Epa proteins contribute to pathogenesis, we have used glycan microarray analysis to characterize their carbohydrate...

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

    Directory of Open Access Journals (Sweden)

    Cohen Aaron

    2009-02-01

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

  17. High-density rhesus macaque oligonucleotide microarray design using early-stage rhesus genome sequence information and human genome annotations

    Directory of Open Access Journals (Sweden)

    Magness Charles L

    2007-01-01

    Full Text Available Abstract Background Until recently, few genomic reagents specific for non-human primate research have been available. To address this need, we have constructed a macaque-specific high-density oligonucleotide microarray by using highly fragmented low-pass sequence contigs from the rhesus genome project together with the detailed sequence and exon structure of the human genome. Using this method, we designed oligonucleotide probes to over 17,000 distinct rhesus/human gene orthologs and increased by four-fold the number of available genes relative to our first-generation expressed sequence tag (EST-derived array. Results We constructed a database containing 248,000 exon sequences from 23,000 human RefSeq genes and compared each human exon with its best matching sequence in the January 2005 version of the rhesus genome project list of 486,000 DNA contigs. Best matching rhesus exon sequences for each of the 23,000 human genes were then concatenated in the proper order and orientation to produce a rhesus "virtual transcriptome." Microarray probes were designed, one per gene, to the region closest to the 3' untranslated region (UTR of each rhesus virtual transcript. Each probe was compared to a composite rhesus/human transcript database to test for cross-hybridization potential yielding a final probe set representing 18,296 rhesus/human gene orthologs, including transcript variants, and over 17,000 distinct genes. We hybridized mRNA from rhesus brain and spleen to both the EST- and genome-derived microarrays. Besides four-fold greater gene coverage, the genome-derived array also showed greater mean signal intensities for genes present on both arrays. Genome-derived probes showed 99.4% identity when compared to 4,767 rhesus GenBank sequence tag site (STS sequences indicating that early stage low-pass versions of complex genomes are of sufficient quality to yield valuable functional genomic information when combined with finished genome information from

  18. Identification of genes and genomic islands correlated with high pathogenicity in Streptococcus suis using whole genome tiling microarrays.

    Directory of Open Access Journals (Sweden)

    Xiao Zheng

    Full Text Available Streptococcus suis is an important zoonotic pathogen that can cause meningitis and sepsis in both pigs and humans. Infections in humans have been sporadic worldwide but two severe outbreaks occurred in China in recent years, while infections in pigs are a major problem in the swine industry. Some S. suis strains are more pathogenic than others with 2 sequence types (ST, ST1 and ST7, being well recognized as highly pathogenic. We analyzed 31 isolates from 23 serotypes and 25 STs by NimbleGen tiling microarray using the genome of a high pathogenicity (HP ST1 strain, GZ1, as reference and a new algorithm to detect gene content difference. The number of genes absent in a strain ranged from 49 to 225 with a total of 632 genes absent in at least one strain, while 1346 genes were found to be invariably present in all strains as the core genome of S. suis, accounting for 68% of the GZ1 genome. The majority of genes are located in chromosomal blocks with two or more contiguous genes. Sixty two blocks are absent in two or more strains and defined as regions of difference (RDs, among which 26 are putative genomic islands (GIs. Clustering and statistical analyses revealed that 8 RDs including 6 putative GIs and 21 genes within these RDs are significantly associated with HP. Three RDs encode known virulence related factors including the extracellular factor, the capsular polysaccharide and a SrtF pilus. The strains were divided into 5 groups based on population genetic analysis of multilocus sequence typing data and the distribution of the RDs among the groups revealed gain and loss of RDs in different groups. Our study elucidated the gene content diversity of S. suis and identified genes that potentially promote HP.

  19. In silico and microarray-based genomic approaches to identifying potential vaccine candidates against Leptospira interrogans

    Directory of Open Access Journals (Sweden)

    Jiang Xu-Cheng

    2006-11-01

    Full Text Available Abstract Background Currently available vaccines against leptospirosis are of low efficacy, have an unacceptable side-effect profile, do not induce long-term protection, and provide no cross-protection against the different serovars of pathogenic leptospira. The current major focus in leptospirosis research is to discover conserved protective antigens that may elicit longer-term protection against a broad range of Leptospira. There is a need to screen vaccine candidate genes in the genome of Leptospira interrogans. Results Bioinformatics, comparative genomic hybridization (CGH analysis and transcriptional analysis were used to identify vaccine candidates in the genome of L. interrogans serovar Lai strain #56601. Of a total of 4727 open reading frames (ORFs, 616 genes were predicted to encode surface-exposed proteins by P-CLASSIFIER combined with signal peptide prediction, α-helix transmembrane topology prediction, integral β-barrel outer membrane protein and lipoprotein prediction, as well as by retaining the genes shared by the two sequenced L. interrogans genomes and by subtracting genes with human homologues. A DNA microarray of L. interrogans strain #56601 was constructed for CGH analysis and transcriptome analysis in vitro. Three hundred and seven differential genes were identified in ten pathogenic serovars by CGH; 1427 genes had high transcriptional levels (Cy3 signal ≥ 342 and Cy5 signal ≥ 363.5, respectively. There were 565 genes in the intersection between the set encoding surface-exposed proteins and the set of 307 differential genes. The number of genes in the intersection between this set of 565 and the set of 1427 highly transcriptionally active genes was 226. These 226 genes were thus identified as putative vaccine candidates. The proteins encoded by these genes are not only potentially surface-exposed in the bacterium, but also conserved in two sequenced L. interrogans. Moreover, these genes are conserved among ten epidemic

  20. Experimental annotation of the human genome using microarray technology.

    Science.gov (United States)

    Shoemaker, D D; Schadt, E E; Armour, C D; He, Y D; Garrett-Engele, P; McDonagh, P D; Loerch, P M; Leonardson, A; Lum, P Y; Cavet, G; Wu, L F; Altschuler, S J; Edwards, S; King, J; Tsang, J S; Schimmack, G; Schelter, J M; Koch, J; Ziman, M; Marton, M J; Li, B; Cundiff, P; Ward, T; Castle, J; Krolewski, M; Meyer, M R; Mao, M; Burchard, J; Kidd, M J; Dai, H; Phillips, J W; Linsley, P S; Stoughton, R; Scherer, S; Boguski, M S

    2001-02-15

    The most important product of the sequencing of a genome is a complete, accurate catalogue of genes and their products, primarily messenger RNA transcripts and their cognate proteins. Such a catalogue cannot be constructed by computational annotation alone; it requires experimental validation on a genome scale. Using 'exon' and 'tiling' arrays fabricated by ink-jet oligonucleotide synthesis, we devised an experimental approach to validate and refine computational gene predictions and define full-length transcripts on the basis of co-regulated expression of their exons. These methods can provide more accurate gene numbers and allow the detection of mRNA splice variants and identification of the tissue- and disease-specific conditions under which genes are expressed. We apply our technique to chromosome 22q under 69 experimental condition pairs, and to the entire human genome under two experimental conditions. We discuss implications for more comprehensive, consistent and reliable genome annotation, more efficient, full-length complementary DNA cloning strategies and application to complex diseases.

  1. Weighted analysis of general microarray experiments

    Directory of Open Access Journals (Sweden)

    Kristiansson Erik

    2007-10-01

    Full Text Available Abstract Background In DNA microarray experiments, measurements from different biological samples are often assumed to be independent and to have identical variance. For many datasets these assumptions have been shown to be invalid and typically lead to too optimistic p-values. A method called WAME has been proposed where a variance is estimated for each sample and a covariance is estimated for each pair of samples. The current version of WAME is, however, limited to experiments with paired design, e.g. two-channel microarrays. Results The WAME procedure is extended to general microarray experiments, making it capable of handling both one- and two-channel datasets. Two public one-channel datasets are analysed and WAME detects both unequal variances and correlations. WAME is compared to other common methods: fold-change ranking, ordinary linear model with t-tests, LIMMA and weighted LIMMA. The p-value distributions are shown to differ greatly between the examined methods. In a resampling-based simulation study, the p-values generated by WAME are found to be substantially more correct than the alternatives when a relatively small proportion of the genes is regulated. WAME is also shown to have higher power than the other methods. WAME is available as an R-package. Conclusion The WAME procedure is generalized and the limitation to paired-design microarray datasets is removed. The examined other methods produce invalid p-values in many cases, while WAME is shown to produce essentially valid p-values when a relatively small proportion of genes is regulated. WAME is also shown to have higher power than the examined alternative methods.

  2. Integrating multiple genome annotation databases improves the interpretation of microarray gene expression data

    Directory of Open Access Journals (Sweden)

    Kennedy Breandan

    2010-01-01

    Full Text Available Abstract Background The Affymetrix GeneChip is a widely used gene expression profiling platform. Since the chips were originally designed, the genome databases and gene definitions have been considerably updated. Thus, more accurate interpretation of microarray data requires parallel updating of the specificity of GeneChip probes. We propose a new probe remapping protocol, using the zebrafish GeneChips as an example, by removing nonspecific probes, and grouping the probes into transcript level probe sets using an integrated zebrafish genome annotation. This genome annotation is based on combining transcript information from multiple databases. This new remapping protocol, especially the new genome annotation, is shown here to be an important factor in improving the interpretation of gene expression microarray data. Results Transcript data from the RefSeq, GenBank and Ensembl databases were downloaded from the UCSC genome browser, and integrated to generate a combined zebrafish genome annotation. Affymetrix probes were filtered and remapped according to the new annotation. The influence of transcript collection and gene definition methods was tested using two microarray data sets. Compared to remapping using a single database, this new remapping protocol results in up to 20% more probes being retained in the remapping, leading to approximately 1,000 more genes being detected. The differentially expressed gene lists are consequently increased by up to 30%. We are also able to detect up to three times more alternative splicing events. A small number of the bioinformatics predictions were confirmed using real-time PCR validation. Conclusions By combining gene definitions from multiple databases, it is possible to greatly increase the numbers of genes and splice variants that can be detected in microarray gene expression experiments.

  3. A 3800 gene microarray for cattle functional genomics: comparison of gene expression in spleen, placenta, and brain.

    Science.gov (United States)

    Band, Mark R; Olmstead, Colleen; Everts, Robin E; Liu, Zonglin L; Lewin, Harris A

    2002-05-01

    A cDNA microarray representing approximately 3800 cattle genes was created for functional genomic studies. The array elements were selected from > 7000 cDNA clones identified in a large-scale expressed sequence tag (EST) project that utilized spleen and normalized and subtracted placenta cDNA libraries. Sequence similarity searches of the 3820 ESTs represented on the array using BLASTN identified 3290 (86.1%) as putative human orthologs, with the remainder consisting of "novel" genes or highly divergent orthologs. Experiments were conducted with a prototype 768 gene microarray created from spleen cDNAs and with the 3800 gene array that included genes from spleen and placenta. The 768 gene array was used to profile RNA transcripts expressed by adult and fetal spleen. The 3800 gene array was used to profile transcripts expressed by adult brain and placenta. Microarray analysis of RNA extracted from fetal and adult spleen identified 29 genes that were differentially expressed two-fold or more. Transcriptional differences of two of these genes, IGJ and CTSS, were confirmed using TaqMan technology. The comparison of brain and placenta revealed 400 genes expressed at higher levels in brain and 72 genes expressed at higher levels in placenta. These results demonstrate the potential power of microarrays for understanding the molecular mechanisms of cattle development, disease resistance, nutrition, fertility and production traits.

  4. Mayday SeaSight: combined analysis of deep sequencing and microarray data.

    Directory of Open Access Journals (Sweden)

    Florian Battke

    Full Text Available Recently emerged deep sequencing technologies offer new high-throughput methods to quantify gene expression, epigenetic modifications and DNA-protein binding. From a computational point of view, the data is very different from that produced by the already established microarray technology, providing a new perspective on the samples under study and complementing microarray gene expression data. Software offering the integrated analysis of data from different technologies is of growing importance as new data emerge in systems biology studies. Mayday is an extensible platform for visual data exploration and interactive analysis and provides many methods for dissecting complex transcriptome datasets. We present Mayday SeaSight, an extension that allows to integrate data from different platforms such as deep sequencing and microarrays. It offers methods for computing expression values from mapped reads and raw microarray data, background correction and normalization and linking microarray probes to genomic coordinates. It is now possible to use Mayday's wealth of methods to analyze sequencing data and to combine data from different technologies in one analysis.

  5. Microarray analysis of potential genes in the pathogenesis of recurrent oral ulcer.

    Science.gov (United States)

    Han, Jingying; He, Zhiwei; Li, Kun; Hou, Lu

    2015-01-01

    Recurrent oral ulcer seriously threatens patients' daily life and health. This study investigated potential genes and pathways that participate in the pathogenesis of recurrent oral ulcer by high throughput bioinformatic analysis. RT-PCR and Western blot were applied to further verify screened interleukins effect. Recurrent oral ulcer related genes were collected from websites and papers, and further found out from Human Genome 280 6.0 microarray data. Each pathway of recurrent oral ulcer related genes were got through chip hybridization. RT-PCR was applied to test four recurrent oral ulcer related genes to verify the microarray data. Data transformation, scatter plot, clustering analysis, and expression pattern analysis were used to analyze recurrent oral ulcer related gene expression changes. Recurrent oral ulcer gene microarray was successfully established. Microarray showed that 551 genes involved in recurrent oral ulcer activity and 196 genes were recurrent oral ulcer related genes. Of them, 76 genes up-regulated, 62 genes down-regulated, and 58 genes up-/down-regulated. Total expression level up-regulated 752 times (60%) and down-regulated 485 times (40%). IL-2 plays an important role in the occurrence, development and recurrence of recurrent oral ulcer on the mRNA and protein levels. Gene microarray can be used to analyze potential genes and pathways in recurrent oral ulcer. IL-2 may be involved in the pathogenesis of recurrent oral ulcer.

  6. 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.

  7. DNA Microarray Technique

    Directory of Open Access Journals (Sweden)

    Thakare SP

    2012-11-01

    Full Text Available DNA Microarray is the emerging technique in Biotechnology. The many varieties of DNA microarray or DNA chip devices and systems are described along with their methods for fabrication and their use. It also includes screening and diagnostic applications. The DNA microarray hybridization applications include the important areas of gene expression analysis and genotyping for point mutations, single nucleotide polymorphisms (SNPs, and short tandem repeats (STRs. In addition to the many molecular biological and genomic research uses, this review covers applications of microarray devices and systems for pharmacogenomic research and drug discovery, infectious and genetic disease and cancer diagnostics, and forensic and genetic identification purposes.

  8. On the Statics for Micro-Array Data Analysis

    Science.gov (United States)

    Urushibara, Tomoko; Akasaka, Shizu; Ito, Makiko; Suzuki, Tomonori; Miyazaki, Satoru

    2010-01-01

    Recently after human genome sequence has been determined almost perfectly, more and more researchers have been studying genes in detail. Therefore, we are sure that accumulated gene information for human will be getting more important in the near future to develop customized medicine and to make gene interactions clear. Among plenty of information, micro array might be one of the most important analysis method for genes because it is the technique that can get big amount of the gene expressions data from one time experiment and also can be used for DNA isolation. To get the novel knowledge from micro array data, we need to enrich statistical tools for its data analysis. So far, many mathematical theories and definition have been proposing. However, many of those proposals are tested with strict conditions or customized to data for specific species. In this paper, we reviewed existing typical statistical methods for micro array analysis and discussed the repeatability of the analysis, construction the guideline with more general procedure. First we analyzed the micro array data for TG rats, with statistical methods of family-wise error rate (FWER) control approach and False Discovery Rate (FDR) control approach. As existing report, no significantly different gene could be detected with FWER control approach. On the other hand, we could find several genes significantly with FDR control approach even q=0.5. To find out the reliability of FDR control approach with micro array conditions, we have analyzed 2 more pieces of data from Gene Expression Omnibus (GEO) public database on the web site with SAM in addition to FWER and FDR control approaches. We could find a certain number of significantly different genes with BH method and SAM in the case of q=0.05. However, we have to note that the number and kinds of detected genes are different when we compare our result with the one from the published paper. Even if the same approach is used to analyze the same micro array

  9. Microarray analysis of the developing cortex.

    Science.gov (United States)

    Semeralul, Mawahib O; Boutros, Paul C; Likhodi, Olga; Okey, Allan B; Van Tol, Hubert H M; Wong, Albert H C

    2006-12-01

    Abnormal development of the prefrontal cortex (PFC) is associated with a number of neuropsychiatric disorders that have an onset in childhood or adolescence. Although the basic laminar structure of the PFC is established in utero, extensive remodeling continues into adolescence. To map the overall pattern of changes in cortical gene transcripts during postnatal development, we made serial measurements of mRNA levels in mouse PFC using oligonucleotide microarrays. We observed changes in mRNA transcripts consistent with known postnatal morphological and biochemical events. Overall, most transcripts that changed significantly showed a progressive decrease in abundance after birth, with the majority of change between postnatal weeks 2 and 4. Genes with cell proliferative, cytoskeletal, extracellular matrix, plasma membrane lipid/transport, protein folding, and regulatory functions had decreases in mRNA levels. Quantitative PCR verified the microarray results for six selected genes: DNA methyltransferase 3A (Dnmt3a), procollagen, type III, alpha 1 (Col3a1), solute carrier family 16 (monocarboxylic acid transporters), member 1 (Slc16a1), MARCKS-like 1 (Marcksl1), nidogen 1 (Nid1) and 3-hydroxybutyrate dehydrogenase (heart, mitochondrial) (Bdh).

  10. Glycan microarray analysis of Candida glabrata adhesin ligand specificity.

    Science.gov (United States)

    Zupancic, Margaret L; Frieman, Matthew; Smith, David; Alvarez, Richard A; Cummings, Richard D; Cormack, Brendan P

    2008-05-01

    The Candida glabrata genome encodes at least 23 members of the EPA (epithelial adhesin) family responsible for mediating adherence to host cells. To better understand the mechanism by which the Epa proteins contribute to pathogenesis, we have used glycan microarray analysis to characterize their carbohydrate-binding specificities. Using Saccharomyces cerevisiae strains surface-expressing the N-terminal ligand-binding domain of the Epa proteins, we found that the three Epa family members functionally identified as adhesins in Candida glabrata (Epa1, Epa6 and Epa7) bind to ligands containing a terminal galactose residue. However, the specificity of the three proteins for glycans within this class varies, with Epa6 having a broader specificity range than Epa1 or Epa7. This result is intriguing given the close homology between Epa6 and Epa7, which are 92% identical at the amino acid level. We have mapped a five-amino-acid region within the N-terminal ligand-binding domain that accounts for the difference in specificity of Epa6 and Epa7 and show that these residues contribute to adherence to both epithelial and endothelial cell lines in vitro.

  11. Transcript copy number estimation using a mouse whole-genome oligonucleotide microarray

    OpenAIRE

    Carter, Mark G.; Sharov, Alexei A; VanBuren, Vincent; Dudekula, Dawood B.; Carmack, Condie E; Nelson, Charlie; Ko, Minoru SH

    2005-01-01

    The ability to quantitatively measure the expression of all genes in a given tissue or cell with a single assay is an exciting promise of gene-expression profiling technology. An in situ-synthesized 60-mer oligonucleotide microarray designed to detect transcripts from all mouse genes was validated, as well as a set of exogenous RNA controls derived from the yeast genome (made freely available without restriction), which allow quantitative estimation of absolute endogenous transcript abundance.

  12. Transcript copy number estimation using a mouse whole-genome oligonucleotide microarray

    Science.gov (United States)

    Carter, Mark G; Sharov, Alexei A; VanBuren, Vincent; Dudekula, Dawood B; Carmack, Condie E; Nelson, Charlie; Ko, Minoru SH

    2005-01-01

    The ability to quantitatively measure the expression of all genes in a given tissue or cell with a single assay is an exciting promise of gene-expression profiling technology. An in situ-synthesized 60-mer oligonucleotide microarray designed to detect transcripts from all mouse genes was validated, as well as a set of exogenous RNA controls derived from the yeast genome (made freely available without restriction), which allow quantitative estimation of absolute endogenous transcript abundance. PMID:15998450

  13. Protein microarrays for systems biology

    Institute of Scientific and Technical Information of China (English)

    Lina Yang; Shujuan Guo; Yang Li; Shumin Zhou; Shengce Tao

    2011-01-01

    Systems biology holds the key for understanding biological systems on a system level. It eventually holds the key for the treatment and cure of complex diseases such as cancer,diabetes, obesity, mental disorders, and many others. The '-omics' technologies, such as genomics, transcriptomics,proteomics, and metabonomics, are among the major driving forces of systems biology. Featured as highthroughput, miniaturized, and capable of parallel analysis,protein microarrays have already become an important technology platform for systems biology, In this review, we will focus on the system level or global analysis of biological systems using protein microarrays. Four major types of protein microarrays will be discussed: proteome microarrays, antibody microarrays, reverse-phase protein arrays,and lectin microarrays. We will also discuss the challenges and future directions of protein microarray technologies and their applications for systems biology. We strongly believe that protein microarrays will soon become an indispensable and invaluable tool for systems biology.

  14. Detection of genome-wide polymorphisms in the AT-rich Plasmodium falciparum genome using a high-density microarray

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    Huyen Yentram

    2008-08-01

    Full Text Available Abstract Background Genetic mapping is a powerful method to identify mutations that cause drug resistance and other phenotypic changes in the human malaria parasite Plasmodium falciparum. For efficient mapping of a target gene, it is often necessary to genotype a large number of polymorphic markers. Currently, a community effort is underway to collect single nucleotide polymorphisms (SNP from the parasite genome. Here we evaluate polymorphism detection accuracy of a high-density 'tiling' microarray with 2.56 million probes by comparing single feature polymorphisms (SFP calls from the microarray with known SNP among parasite isolates. Results We found that probe GC content, SNP position in a probe, probe coverage, and signal ratio cutoff values were important factors for accurate detection of SFP in the parasite genome. We established a set of SFP calling parameters that could predict mSFP (SFP called by multiple overlapping probes with high accuracy (≥ 94% and identified 121,087 mSFP genome-wide from five parasite isolates including 40,354 unique mSFP (excluding those from multi-gene families and ~18,000 new mSFP, producing a genetic map with an average of one unique mSFP per 570 bp. Genomic copy number variation (CNV among the parasites was also cataloged and compared. Conclusion A large number of mSFP were discovered from the P. falciparum genome using a high-density microarray, most of which were in clusters of highly polymorphic genes at chromosome ends. Our method for accurate mSFP detection and the mSFP identified will greatly facilitate large-scale studies of genome variation in the P. falciparum parasite and provide useful resources for mapping important parasite traits.

  15. Biological networks to the analysis of microarray data

    Institute of Scientific and Technical Information of China (English)

    FANG Zhuo; LUO Qingming; ZHANG Guoqing; LI Yixue

    2006-01-01

    Microarray technology, which permits rapid and large-scale screening for patterns of gene expressions, usually generates a large amount of data. How to mine the biological meanings under these data is one of the main challenges in bioinformatics. Compared to the pure mathematical techniques, those methods incorporated with some prior biological knowledge generally bring better interpretations.Recently, a new analysis, in which the knowledge of biological networks such as metabolic network and protein interaction network is introduced, is widely applied to microarray data analysis. The microarray data analysis based on biological networks contains two main research aspects: identification of active components in biological networks and assessment of gene sets significance. In this paper, we briefly review the progress of these two categories of analyses, especially some representative methods.

  16. Whole-genome microarrays of fission yeast: characteristics, accuracy, reproducibility, and processing of array data

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    Chen Dongrong

    2003-07-01

    Full Text Available Abstract Background The genome of the fission yeast Schizosaccharomyces pombe has recently been sequenced, setting the stage for the post-genomic era of this increasingly popular model organism. We have built fission yeast microarrays, optimised protocols to improve array performance, and carried out experiments to assess various characteristics of microarrays. Results We designed PCR primers to amplify specific probes (180–500 bp for all known and predicted fission yeast genes, which are printed in duplicate onto separate regions of glass slides together with control elements (~13,000 spots/slide. Fluorescence signal intensities depended on the size and intragenic position of the array elements, whereas the signal ratios were largely independent of element properties. Only the coding strand is covalently linked to the slides, and our array elements can discriminate transcriptional direction. The microarrays can distinguish sequences with up to 70% identity, above which cross-hybridisation contributes to the signal intensity. We tested the accuracy of signal ratios and measured the reproducibility of array data caused by biological and technical factors. Because the technical variability is lower, it is best to use samples prepared from independent biological experiments to obtain repeated measurements with swapping of fluorochromes to prevent dye bias. We also developed a script that discards unreliable data and performs a normalization to correct spatial artefacts. Conclusions This paper provides data for several microarray properties that are rarely measured. The results define critical parameters for microarray design and experiments and provide a framework to optimise and interpret array data. Our arrays give reproducible and accurate expression ratios with high sensitivity. The scripts for primer design and initial data processing as well as primer sequences and detailed protocols are available from our website.

  17. Introduction to microarray technology.

    Science.gov (United States)

    Dufva, Martin

    2009-01-01

    DNA microarrays can be used for large number of application where high-throughput is needed. The ability to probe a sample for hundred to million different molecules at once has made DNA microarray one of the fastest growing techniques since its introduction about 15 years ago. Microarray technology can be used for large scale genotyping, gene expression profiling, comparative genomic hybridization and resequencing among other applications. Microarray technology is a complex mixture of numerous technology and research fields such as mechanics, microfabrication, chemistry, DNA behaviour, microfluidics, enzymology, optics and bioinformatics. This chapter will give an introduction to each five basic steps in microarray technology that includes fabrication, target preparation, hybridization, detection and data analysis. Basic concepts and nomenclature used in the field of microarray technology and their relationships will also be explained.

  18. Comparative genomics of Streptomyces avermitilis, Streptomyces cattleya, Streptomyces maritimus and Kitasatospora aureofaciens using a Streptomyces coelicolor microarray system.

    Science.gov (United States)

    Hsiao, Nai-Hua; Kirby, Ralph

    2008-01-01

    DNA/DNA microarray hybridization was used to compare the genome content of Streptomyces avermitilis, Streptomyces cattleya, Streptomyces maritimus and Kitasatospora aureofaciens with that of Streptomyces coelicolor A3(2). The array data showed an about 93% agreement with the genome sequence data available for S. avermitilis and also showed a number of trends in the genome structure for Streptomyces and closely related Kitasatospora. A core central region was well conserved, which might be predicted from previous research and this was linked to a low degree of gene conservation in the terminal regions of the linear chromosome across all four species. Between these regions there are two areas of intermediate gene conservation by microarray analysis where gene synteny is still detectable in S. avermitilis. Nonetheless, a range of conserved genes could be identified within the terminal regions. Variation in the genes involved in differentiation, transcription, DNA replication, etc. provides interesting insights into which genes in these categories are generally conserved and which are not. The results also provide target priorities for possible gene knockouts in a group of bacteria with a very large numbers of genes with unknown functions compared to most bacterial species.

  19. Application of Microarray-Based Comparative Genomic Hybridization in Prenatal and Postnatal Settings: Three Case Reports

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    Jing Liu

    2011-01-01

    Full Text Available Microarray-based comparative genomic hybridization (array CGH is a newly emerged molecular cytogenetic technique for rapid evaluation of the entire genome with sub-megabase resolution. It allows for the comprehensive investigation of thousands and millions of genomic loci at once and therefore enables the efficient detection of DNA copy number variations (a.k.a, cryptic genomic imbalances. The development and the clinical application of array CGH have revolutionized the diagnostic process in patients and has provided a clue to many unidentified or unexplained diseases which are suspected to have a genetic cause. In this paper, we present three clinical cases in both prenatal and postnatal settings. Among all, array CGH played a major discovery role to reveal the cryptic and/or complex nature of chromosome arrangements. By identifying the genetic causes responsible for the clinical observation in patients, array CGH has provided accurate diagnosis and appropriate clinical management in a timely and efficient manner.

  20. Comparative genomic profiling of Dutch clinical Bordetella pertussis isolates using DNA microarrays: Identification of genes absent from epidemic strains

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    van Gent Marjolein

    2008-06-01

    Full Text Available Abstract Background Whooping cough caused by Bordetella pertussis in humans, is re-emerging in many countries despite vaccination. Several studies have shown that significant shifts have occurred in the B. pertussis population resulting in antigenic divergence between vaccine strains and circulating strains and suggesting pathogen adaptation. In the Netherlands, the resurgence of pertussis is associated with the rise of B. pertussis strains with an altered promoter region for pertussis toxin (ptxP3. Results We used Multi-Locus Sequence Typing (MLST, Multiple-Locus Variable Number of Tandem Repeat Analysis (MLVA and microarray-based comparative genomic hybridization (CGH to characterize the ptxP3 strains associated with the Dutch epidemic. For CGH analysis, we developed an oligonucleotide (70-mers microarray consisting of 3,581 oligonucleotides representing 94% of the gene repertoire of the B. pertussis strain Tohama I. Nine different MLST profiles and 38 different MLVA types were found in the period 1993 to 2004. Forty-three Dutch clinical isolates were analyzed with CGH, 98 genes were found to be absent in at least one of the B. pertussis strains tested, these genes were clustered in 8 distinct regions of difference. Conclusion The presented MLST, MLVA and CGH-analysis identified distinctive characteristics of ptxP3 B. pertussis strains -the most prominent of which was a genomic deletion removing about 23,000 bp. We propose a model for the emergence of ptxP3 strains.

  1. Significance analysis of lexical bias in microarray data

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    Falkow Stanley

    2003-04-01

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

  2. Gene ARMADA: an integrated multi-analysis platform for microarray data implemented in MATLAB.

    Science.gov (United States)

    Chatziioannou, Aristotelis; Moulos, Panagiotis; Kolisis, Fragiskos N

    2009-10-27

    The microarray data analysis realm is ever growing through the development of various tools, open source and commercial. However there is absence of predefined rational algorithmic analysis workflows or batch standardized processing to incorporate all steps, from raw data import up to the derivation of significantly differentially expressed gene lists. This absence obfuscates the analytical procedure and obstructs the massive comparative processing of genomic microarray datasets. Moreover, the solutions provided, heavily depend on the programming skills of the user, whereas in the case of GUI embedded solutions, they do not provide direct support of various raw image analysis formats or a versatile and simultaneously flexible combination of signal processing methods. We describe here Gene ARMADA (Automated Robust MicroArray Data Analysis), a MATLAB implemented platform with a Graphical User Interface. This suite integrates all steps of microarray data analysis including automated data import, noise correction and filtering, normalization, statistical selection of differentially expressed genes, clustering, classification and annotation. In its current version, Gene ARMADA fully supports 2 coloured cDNA and Affymetrix oligonucleotide arrays, plus custom arrays for which experimental details are given in tabular form (Excel spreadsheet, comma separated values, tab-delimited text formats). It also supports the analysis of already processed results through its versatile import editor. Besides being fully automated, Gene ARMADA incorporates numerous functionalities of the Statistics and Bioinformatics Toolboxes of MATLAB. In addition, it provides numerous visualization and exploration tools plus customizable export data formats for seamless integration by other analysis tools or MATLAB, for further processing. Gene ARMADA requires MATLAB 7.4 (R2007a) or higher and is also distributed as a stand-alone application with MATLAB Component Runtime. Gene ARMADA provides a

  3. Parents' Experience with Pediatric Microarray: Transferrable Lessons in the Era of Genomic Counseling.

    Science.gov (United States)

    Hayeems, R Z; Babul-Hirji, R; Hoang, N; Weksberg, R; Shuman, C

    2016-04-01

    Advances in genome-based microarray and sequencing technologies hold tremendous promise for understanding, better-managing and/or preventing disease and disease-related risk. Chromosome microarray technology (array based comparative genomic hybridization [aCGH]) is widely utilized in pediatric care to inform diagnostic etiology and medical management. Less clear is how parents experience and perceive the value of this technology. This study explored parents' experiences with aCGH in the pediatric setting, focusing on how they make meaning of various types of test results. We conducted in-person or telephone-based semi-structured interviews with parents of 21 children who underwent aCGH testing in 2010. Transcripts were coded and analyzed thematically according to the principles of interpretive description. We learned that parents expect genomic tests to be of personal use; their experiences with aCGH results characterize this use as intrinsic in the test's ability to provide a much sought-after answer for their child's condition, and instrumental in its ability to guide care, access to services, and family planning. In addition, parents experience uncertainty regardless of whether aCGH results are of pathogenic, uncertain, or benign significance; this triggers frustration, fear, and hope. Findings reported herein better characterize the notion of personal utility and highlight the pervasive nature of uncertainty in the context of genomic testing. Empiric research that links pre-test counseling content and psychosocial outcomes is warranted to optimize patient care.

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

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    Deising Holger B

    2011-01-01

    Full Text Available Abstract Background The toxigenic fungal plant pathogen Fusarium graminearum compromises wheat production worldwide. Azole fungicides play a prominent role in controlling this pathogen. Sequencing of its genome stimulated the development of high-throughput technologies to study mechanisms of coping with fungicide stress and adaptation to fungicides at a previously unprecedented precision. DNA-microarrays have been used to analyze genome-wide gene expression patterns and uncovered complex transcriptional responses. A recently developed one-color multiplex array format allowed flexible, effective, and parallel examinations of eight RNA samples. Results We took advantage of the 8 × 15 k Agilent format to design, evaluate, and apply a novel microarray covering the whole F. graminearum genome to analyze transcriptional responses to azole fungicide treatment. Comparative statistical analysis of expression profiles uncovered 1058 genes that were significantly differentially expressed after azole-treatment. Quantitative RT-PCR analysis for 31 selected genes indicated high conformity to results from the microarray hybridization. Among the 596 genes with significantly increased transcript levels, analyses using GeneOntology and FunCat annotations detected the ergosterol-biosynthesis pathway genes as the category most significantly responding, confirming the mode-of-action of azole fungicides. Cyp51A, which is one of the three F. graminearum paralogs of Cyp51 encoding the target of azoles, was the most consistently differentially expressed gene of the entire study. A molecular phylogeny analyzing the relationships of the three CYP51 proteins in the context of 38 fungal genomes belonging to the Pezizomycotina indicated that CYP51C (FGSG_11024 groups with a new clade of CYP51 proteins. The transcriptional profiles for genes encoding ABC transporters and transcription factors suggested several involved in mechanisms alleviating the impact of the fungicide

  5. EST and microarray analysis of horn development in Onthophagus beetles

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    Tang Zuojian

    2009-10-01

    Full Text Available Abstract Background The origin of novel traits and their subsequent diversification represent central themes in evo-devo and evolutionary ecology. Here we explore the genetic and genomic basis of a class of traits that is both novel and highly diverse, in a group of organisms that is ecologically complex and experimentally tractable: horned beetles. Results We developed two high quality, normalized cDNA libraries for larval and pupal Onthophagus taurus and sequenced 3,488 ESTs that assembled into 451 contigs and 2,330 singletons. We present the annotation and a comparative analysis of the conservation of the sequences. Microarrays developed from the combined libraries were then used to contrast the transcriptome of developing primordia of head horns, prothoracic horns, and legs. Our experiments identify a first comprehensive list of candidate genes for the evolution and diversification of beetle horns. We find that developing horns and legs show many similarities as well as important differences in their transcription profiles, suggesting that the origin of horns was mediated partly, but not entirely, by the recruitment of genes involved in the formation of more traditional appendages such as legs. Furthermore, we find that horns developing from the head and prothorax differ in their transcription profiles to a degree that suggests that head and prothoracic horns are not serial homologs, but instead may have evolved independently from each other. Conclusion We have laid the foundation for a systematic analysis of the genetic basis of horned beetle development and diversification with the potential to contribute significantly to several major frontiers in evolutionary developmental biology.

  6. Extending the Interpretation of Gene Profiling Microarray Experiments to Pathway Analysis Through the Use of Gene Ontology Terms

    Science.gov (United States)

    Chatziioannou, Aristotelis; Moulos, Panagiotis

    Microarray technology allows the survey of gene expression at a global level by measuring mRNA abundance. However, the grand complexity characterizing a microarray experiment entails the development of computationally powerful tools apt for probing the biological problem studied. Here we propose a suite for flexible, adaptable to a wide range of possible needs of the biological end-user, data-driven interpretation of microarray experiments. The suite is implemented in MATLAB and is making use of two modules, able to perform all steps of typical microarray data analysis starting from data standardization and normalization up to statistical selection and pathway analysis utilizing Gene Ontology Term annotations for the species genomes interrogated, whereas due to its modular structure it is scalable thus enabling the incorporation or its seamless assembly with other existing tools.

  7. Independent component analysis of Alzheimer's DNA microarray gene expression data

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    Vanderburg Charles R

    2009-01-01

    Full Text Available Abstract Background Gene microarray technology is an effective tool to investigate the simultaneous activity of multiple cellular pathways from hundreds to thousands of genes. However, because data in the colossal amounts generated by DNA microarray technology are usually complex, noisy, high-dimensional, and often hindered by low statistical power, their exploitation is difficult. To overcome these problems, two kinds of unsupervised analysis methods for microarray data: principal component analysis (PCA and independent component analysis (ICA have been developed to accomplish the task. PCA projects the data into a new space spanned by the principal components that are mutually orthonormal to each other. The constraint of mutual orthogonality and second-order statistics technique within PCA algorithms, however, may not be applied to the biological systems studied. Extracting and characterizing the most informative features of the biological signals, however, require higher-order statistics. Results ICA is one of the unsupervised algorithms that can extract higher-order statistical structures from data and has been applied to DNA microarray gene expression data analysis. We performed FastICA method on DNA microarray gene expression data from Alzheimer's disease (AD hippocampal tissue samples and consequential gene clustering. Experimental results showed that the ICA method can improve the clustering results of AD samples and identify significant genes. More than 50 significant genes with high expression levels in severe AD were extracted, representing immunity-related protein, metal-related protein, membrane protein, lipoprotein, neuropeptide, cytoskeleton protein, cellular binding protein, and ribosomal protein. Within the aforementioned categories, our method also found 37 significant genes with low expression levels. Moreover, it is worth noting that some oncogenes and phosphorylation-related proteins are expressed in low levels. In

  8. Dynamic probe selection for studying microbial transcriptome with high-density genomic tiling microarrays

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    Chen Tsute

    2010-02-01

    Full Text Available Abstract Background Current commercial high-density oligonucleotide microarrays can hold millions of probe spots on a single microscopic glass slide and are ideal for studying the transcriptome of microbial genomes using a tiling probe design. This paper describes a comprehensive computational pipeline implemented specifically for designing tiling probe sets to study microbial transcriptome profiles. Results The pipeline identifies every possible probe sequence from both forward and reverse-complement strands of all DNA sequences in the target genome including circular or linear chromosomes and plasmids. Final probe sequence lengths are adjusted based on the maximal oligonucleotide synthesis cycles and best isothermality allowed. Optimal probes are then selected in two stages - sequential and gap-filling. In the sequential stage, probes are selected from sequence windows tiled alongside the genome. In the gap-filling stage, additional probes are selected from the largest gaps between adjacent probes that have already been selected, until a predefined number of probes is reached. Selection of the highest quality probe within each window and gap is based on five criteria: sequence uniqueness, probe self-annealing, melting temperature, oligonucleotide length, and probe position. Conclusions The probe selection pipeline evaluates global and local probe sequence properties and selects a set of probes dynamically and evenly distributed along the target genome. Unique to other similar methods, an exact number of non-redundant probes can be designed to utilize all the available probe spots on any chosen microarray platform. The pipeline can be applied to microbial genomes when designing high-density tiling arrays for comparative genomics, ChIP chip, gene expression and comprehensive transcriptome studies.

  9. Analysis of DNA strand-specific differential expression with high density tiling microarrays

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    Antequera Francisco

    2010-03-01

    Full Text Available Abstract Background DNA microarray technology allows the analysis of genome structure and dynamics at genome-wide scale. Expression microarrays (EMA contain probes for annotated open reading frames (ORF and are widely used for the analysis of differential gene expression. By contrast, tiling microarrays (TMA have a much higher probe density and provide unbiased genome-wide coverage. The purpose of this study was to develop a protocol to exploit the high resolution of TMAs for quantitative measurement of DNA strand-specific differential expression of annotated and non-annotated transcripts. Results We extensively filtered probes present in Affymetrix Genechip Yeast Genome 2.0 expression and GeneChip S. pombe 1.0FR tiling microarrays to generate custom Chip Description Files (CDF in order to compare their efficiency. We experimentally tested the potential of our approach by measuring the differential expression of 4904 genes in the yeast Schizosaccharomyces pombe growing under conditions of oxidative stress. The results showed a Pearson correlation coefficient of 0.943 between both platforms, indicating that TMAs are as reliable as EMAs for quantitative expression analysis. A significant advantage of TMAs over EMAs is the possibility of detecting non-annotated transcripts generated only under specific physiological conditions. To take full advantage of this property, we have used a target-labelling protocol that preserves the original polarity of the transcripts and, therefore, allows the strand-specific differential expression of non-annotated transcripts to be determined. By using a segmentation algorithm prior to generating the corresponding custom CDFs, we identified and quantitatively measured the expression of 510 transcripts longer than 180 nucleotides and not overlapping previously annotated ORFs that were differentially expressed at least 2-fold under oxidative stress. Conclusions We show that the information derived from TMA

  10. Informatics enhanced SNP microarray analysis of 30 miscarriage samples compared to routine cytogenetics.

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    Ruth B Lathi

    Full Text Available PURPOSE: The metaphase karyotype is often used as a diagnostic tool in the setting of early miscarriage; however this technique has several limitations. We evaluate a new technique for karyotyping that uses single nucleotide polymorphism microarrays (SNP. This technique was compared in a blinded, prospective fashion, to the traditional metaphase karyotype. METHODS: Patients undergoing dilation and curettage for first trimester miscarriage between February and August 2010 were enrolled. Samples of chorionic villi were equally divided and sent for microarray testing in parallel with routine cytogenetic testing. RESULTS: Thirty samples were analyzed, with only four discordant results. Discordant results occurred when the entire genome was duplicated or when a balanced rearrangement was present. Cytogenetic karyotyping took an average of 29 days while microarray-based karytoyping took an average of 12 days. CONCLUSIONS: Molecular karyotyping of POC after missed abortion using SNP microarray analysis allows for the ability to detect maternal cell contamination and provides rapid results with good concordance to standard cytogenetic analysis.

  11. Microarray gene expression analysis of uterosacral ligaments in uterine prolapse.

    Science.gov (United States)

    Ak, Handan; Zeybek, Burak; Atay, Sevcan; Askar, Niyazi; Akdemir, Ali; Aydin, Hikmet Hakan

    2016-11-01

    Pelvic organ prolapse (POP) is a major health problem that impairs the quality of life with a wide clinical spectrum. Since the uterosacral ligaments provide primary support for the uterus and the upper vagina, we hypothesize that the disruption of these ligaments may lead to a loss of support and eventually contribute to POP. In this study, we therefore investigated whether there are any differences in the transcription profile of uterosacral ligaments in patients with POP when compared to those of the control samples. Seventeen women with POP and 8 non-POP controls undergoing hysterectomy for benign conditions were included in the study. Affymetrix® Gene Chip microarrays (Human Hu 133 plus 2.0) were used for whole genome gene expression profiling analysis. There was 1 significantly down-regulated gene, NKX2-3 in patients with POP compared to the controls (p=4.28464e-013). KIF11 gene was found to be significantly down-regulated in patients with ≥3 deliveries compared to patients with <3 deliveries (p=0.0156237). UGT1A1 (p=2.43388e-005), SCARB1 (p=1.19001e-006) and NKX2-3 (p=2.17966e-013) genes were found to be significantly down-regulated in the premenopausal patients compared to the premenopausal controls. UGT1A1 gene was also found to be significantly down-regulated in the post menopausal patients compared to the postmenopausal controls (p=0.0005). This study provides evidence for a significant down-regulation of the genes that take role in cell cycle, proliferation and embryonic development along with cell adhesion process on the development of POP for the first time. Copyright © 2016 The Canadian Society of Clinical Chemists. Published by Elsevier Inc. All rights reserved.

  12. Comparative genomics of Streptomyces avermitilis, Streptomyces cattleya, Streptomyces maritimus and Kitasatospora aureofaciens using a Streptomyces coelicolor microarray system

    NARCIS (Netherlands)

    Hsiao, Nai-hua; Kirby, Ralph

    2008-01-01

    DNA/DNA microarray hybridization was used to compare the genome content of Streptomyces avermitilis, Streptomyces cattleya, Streptomyces maritimus and Kitasatospora aureofaciens with that of Streptomyces coelicolor A3(2). The array data showed an about 93% agreement with the genome sequence data ava

  13. Application of microarray analysis of foodborne Salmonella in poultry production: a review.

    Science.gov (United States)

    Ricke, Steven C; Khatiwara, Anita; Kwon, Young Min

    2013-09-01

    Salmonellosis in the United States is one of the most costly foodborne diseases. Given that Salmonella can originate from a wide variety of environments, reduction of this organism at all stages of poultry production is critical. Salmonella species can encounter various environmental stress conditions that can dramatically influence their survival and virulence. Previous knowledge of Salmonella species genomic regulation of metabolism and physiology in relation to poultry is based on limited information of a few well-characterized genes. Consequently, although there is some information about environmental signals that control Salmonella growth and pathogenesis, much still remains unknown. Advancements in DNA sequencing technologies revolutionized the way bacteria were studied and molecular tools such as microarrays have subsequently been used for comprehensive transcriptomic analysis of Salmonella. With microarray analysis, the expression levels of each single gene in the Salmonella genome can be directly assessed and previously unknown genetic systems that are required for Salmonella growth and survival in the poultry production cycle can be elucidated. This represents an opportunity for development of novel approaches for limiting Salmonella establishment in all phases of poultry production. In this review, recent advances in transcriptome-microarray technologies that are facilitating a better understanding of Salmonella biology in poultry production and processing are discussed.

  14. Genomic resources for the brown planthopper, Nilaparvata lugens: Transcriptome pyrosequencing and microarray design

    Institute of Scientific and Technical Information of China (English)

    Chris Bass; Martin Bay Hebsgaard; Joseph Hughes

    2012-01-01

    The brown planthopper,Nilaparvata lugens is a pest of cultivated rice throughout Asia and is controlled using insecticides and/or resistant rice varieties.This species has developed resistance to many classes of insecticide and biotypes have developed that are virulent against formerly resistant rice cultivars.Insects use a suite of detoxification enzymes,including cytochrome P450s,glutathione S-transferases and carboxyl/cholinesterases to defend themselves against plant secondary metabolites and pesticides.Pyrosequencing on the Roche 454-FLX platform was used to produce a substantial expressed sequence tag (EST) dataset to complement the existing Sanger sequenced ESTs in GenBank.A total of 78 959 reads were combined with the 37 392 publically available Sanger ESTs; these assembled into 8 911 contigs and 10 620 singletons.Analysis of the distribution of tentative unique genes (TUGs) with the gene ontology for biological processes and molecular functions suggests that the 454 and Sanger EST assembly is broadly representative of the N.lugens transcriptome.The brown planthopper transcriptome was found to contain 31 TUGs encoding P450s,nine encoding glutathione S-transferases and 26 encoding carboxyl/cholinesterases and many of these are putatively involved in the detoxification of xenobiotics.The Agilent eArray platform was used to construct an oligonucleotide microarray populated with probes for ~ 19 000 unigene sequences,including all those known to encode detoxification enzymes.The genomic resources developed in this study will be useful to the community studying this crop pest and will help elucidate the molecular mechanism underlying insecticide resistance and planthopper adaptation to resistant rice cultivars.

  15. Classification analysis of microarray data based on ontological engineering

    Institute of Scientific and Technical Information of China (English)

    LI Guo-qi; SHENG Huan-ye

    2007-01-01

    Background knowledge is important for data mining, especially in complicated situation. Ontological engineering is the successor of knowledge engineering. The sharable knowledge bases built on ontology can be used to provide background knowledge to direct the process of data mining. This paper gives a common introduction to the method and presents a practical analysis example using SVM (support vector machine) as the classifier. Gene Ontology and the accompanying annotations compose a big knowledge base, on which many researches have been carried out. Microarray dataset is the output of DNA chip.With the help of Gene Ontology we present a more elaborate analysis on microarray data than former researchers. The method can also be used in other fields with similar scenario.

  16. RL-SAGE and microarray analysis of the rice transcriptome after Rhizoctonia solani infection.

    Science.gov (United States)

    Venu, R C; Jia, Yulin; Gowda, Malali; Jia, Melissa H; Jantasuriyarat, Chatchawan; Stahlberg, Eric; Li, Huameng; Rhineheart, Andrew; Boddhireddy, Prashanth; Singh, Pratibha; Rutger, Neil; Kudrna, David; Wing, Rod; Nelson, James C; Wang, Guo-Liang

    2007-10-01

    Sheath blight caused by the fungal pathogen Rhizoctonia solani is an emerging problem in rice production worldwide. To elucidate the molecular basis of rice defense to the pathogen, RNA isolated from R. solani-infected leaves of Jasmine 85 was used for both RL-SAGE library construction and microarray hybridization. RL-SAGE sequence analysis identified 20,233 and 24,049 distinct tags from the control and inoculated libraries, respectively. Nearly half of the significant tags (> or =2 copies) from both libraries matched TIGR annotated genes and KOME full-length cDNAs. Among them, 42% represented sense and 7% antisense transcripts, respectively. Interestingly, 60% of the library-specific (> or =10 copies) and differentially expressed (>4.0-fold change) tags were novel transcripts matching genomic sequence but not annotated genes. About 70% of the genes identified in the SAGE libraries showed similar expression patterns (up or down-regulated) in the microarray data obtained from three biological replications. Some candidate RL-SAGE tags and microarray genes were located in known sheath blight QTL regions. The expression of ten differentially expressed RL-SAGE tags was confirmed with RT-PCR. The defense genes associated with resistance to R. solani identified in this study are useful genomic materials for further elucidation of the molecular basis of the defense response to R. solani and fine mapping of target sheath blight QTLs.

  17. Comparative genomics of Streptomyces avermitilis, Streptomyces cattleya, Streptomyces maritimus and Kitasatospora aureofaciens using a Streptomyces coelicolor microarray system

    OpenAIRE

    2007-01-01

    DNA/DNA microarray hybridization was used to compare the genome content of Streptomyces avermitilis, Streptomyces cattleya, Streptomyces maritimus and Kitasatospora aureofaciens with that of Streptomyces coelicolor A3(2). The array data showed an about 93% agreement with the genome sequence data available for S. avermitilis and also showed a number of trends in the genome structure for Streptomyces and closely related Kitasatospora. A core central region was well conserved, which might be pre...

  18. Membrane gene ontology bias in sequencing and microarray obtained by housekeeping-gene analysis.

    Science.gov (United States)

    Zhang, Yijuan; Akintola, Oluwafemi S; Liu, Ken J A; Sun, Bingyun

    2016-01-10

    Microarray (MA) and high-throughput sequencing are two commonly used detection systems for global gene expression profiling. Although these two systems are frequently used in parallel, the differences in their final results have not been examined thoroughly. Transcriptomic analysis of housekeeping (HK) genes provides a unique opportunity to reliably examine the technical difference between these two systems. We investigated here the structure, genome location, expression quantity, microarray probe coverage, as well as biological functions of differentially identified human HK genes by 9 MA and 6 sequencing studies. These in-depth analyses allowed us to discover, for the first time, a subset of transcripts encoding membrane, cell surface and nuclear proteins that were prone to differential identification by the two platforms. We hope that the discovery can aid the future development of these technologies for comprehensive transcriptomic studies. Copyright © 2015 Elsevier B.V. All rights reserved.

  19. Development and Use of Integrated Microarray-Based Genomic Technologies for Assessing Microbial Community Composition and Dynamics

    Energy Technology Data Exchange (ETDEWEB)

    Zhou, J.; Wu, L.; Gentry, T.; Schadt, C.; He, Z.; Li, X.

    2006-04-05

    To effectively monitor microbial populations involved in various important processes, a 50-mer-based oligonucleotide microarray was developed based on known genes and pathways involved in: biodegradation, metal resistance and reduction, denitrification, nitrification, nitrogen fixation, methane oxidation, methanogenesis, carbon polymer decomposition, and sulfate reduction. This array contains approximately 2000 unique and group-specific probes with <85% similarity to their non-target sequences. Based on artificial probes, our results showed that at hybridization conditions of 50 C and 50% formamide, the 50-mer microarray hybridization can differentiate sequences having <88% similarity. Specificity tests with representative pure cultures indicated that the designed probes on the arrays appeared to be specific to their corresponding target genes. Detection limits were about 5-10ng genomic DNA in the absence of background DNA, and 50-100ng ({approx}1.3{sup o} 10{sup 7} cells) in the presence background DNA. Strong linear relationships between signal intensity and target DNA and RNA concentration were observed (r{sup 2} = 0.95-0.99). Application of this microarray to naphthalene-amended enrichments and soil microcosms demonstrated that composition of the microflora varied depending on incubation conditions. While the naphthalene-degrading genes from Rhodococcus-type microorganisms were dominant in enrichments, the genes involved in naphthalene degradation from Gram-negative microorganisms such as Ralstonia, Comamonas, and Burkholderia were most abundant in the soil microcosms (as well as those for polyaromatic hydrocarbon and nitrotoluene degradation). Although naphthalene degradation is widely known and studied in Pseudomonas, Pseudomonas genes were not detected in either system. Real-time PCR analysis of 4 representative genes was consistent with microarray-based quantification (r{sup 2} = 0.95). Currently, we are also applying this microarray to the study of several

  20. Xenogenomics: Genomic Bioprospecting in Indigenous and Exotic Plants Through EST Discovery, cDNA Microarray-Based Expression Profiling and Functional Genomics

    Directory of Open Access Journals (Sweden)

    German C. Spangenberg

    2006-04-01

    Full Text Available To date, the overwhelming majority of genomics programs in plants have been directed at model or crop plant species, meaning that very little of the naturally occurring sequence diversity found in plants is available for characterization and exploitation. In contrast, ‘xenogenomics’ refers to the discovery and functional analysis of novel genes and alleles from indigenous and exotic species, permitting bioprospecting of biodiversity using high-throughput genomics experimental approaches. Such a program has been initiated to bioprospect for genetic determinants of abiotic stress tolerance in indigenous Australian flora and native Antarctic plants. Uniquely adapted Poaceae and Fabaceae species with enhanced tolerance to salt, drought, elevated soil aluminium concentration, and freezing stress have been identified, based primarily on their eco-physiology, and have been subjected to structural and functional genomics analyses. For each species, EST collections have been derived from plants subjected to appropriate abiotic stresses. Transcript profiling with spotted unigene cDNA micro-arrays has been used to identify genes that are transcriptionally modulated in response to abiotic stress. Candidate genes identified on the basis of sequence annotation or transcript profiling have been assayed in planta and other in vivo systems for their capacity to confer novel phenotypes. Comparative genomics analysis of novel genes and alleles identified in the xenogenomics target plant species has subsequently been undertaken with reference to key model and crop plants.

  1. 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.

  2. Coupled Two-Way Clustering Analysis of Gene Microarray Data

    CERN Document Server

    Getz, G; Domany, E

    2000-01-01

    We present a novel coupled two-way clustering approach to gene microarray data analysis. The main idea is to identify subsets of the genes and samples, such that when one of these is used to cluster the other, stable and significant partitions emerge. The search for such subsets is a computationally complex task: we present an algorithm, based on iterative clustering, which performs such a search. This analysis is especially suitable for gene microarray data, where the contributions of a variety of biological mechanisms to the gene expression levels are entangled in a large body of experimental data. The method was applied to two gene microarray data sets, on colon cancer and leukemia. By identifying relevant subsets of the data and focusing on them we were able to discover partitions and correlations that were masked and hidden when the full dataset was used in the analysis. Some of these partitions have clear biological interpretation; others can serve to identify possible directions for future research.

  3. Coupled two-way clustering analysis of gene microarray data

    Science.gov (United States)

    Getz, Gad; Levine, Erel; Domany, Eytan

    2000-10-01

    We present a coupled two-way clustering approach to gene microarray data analysis. The main idea is to identify subsets of the genes and samples, such that when one of these is used to cluster the other, stable and significant partitions emerge. The search for such subsets is a computationally complex task. We present an algorithm, based on iterative clustering, that performs such a search. This analysis is especially suitable for gene microarray data, where the contributions of a variety of biological mechanisms to the gene expression levels are entangled in a large body of experimental data. The method was applied to two gene microarray data sets, on colon cancer and leukemia. By identifying relevant subsets of the data and focusing on them we were able to discover partitions and correlations that were masked and hidden when the full dataset was used in the analysis. Some of these partitions have clear biological interpretation; others can serve to identify possible directions for future research.

  4. Microarray Analysis of the Developing Rat Mandible

    Institute of Scientific and Technical Information of China (English)

    Hideo KABURAGI; Naoyuki SUGANO; Maiko OSHIKAWA; Ryosuke KOSHI; Naoki SENDA; Kazuhiro KAWAMOTO; Koichi ITO

    2007-01-01

    To analyze the molecular events that occur in the developing mandible, we examined the expression of 8803 genes from samples taken at different time points during rat postnatal mandible development.Total RNA was extracted from the mandibles of 1-day-old, 1-week-old, and 2-week-old rats. Complementary RNA (cRNA) was synthesized from cDNA and biotinylated. Fragmented cRNA was hybridized to RGU34A GeneChip arrays. Among the 8803 genes tested, 4344 were detectable. We identified 148 genes with significantly increased expression, and 19 genes with significantly decreased expression. A comprehensive analysis appears to be an effective method of studying the complex process of development.

  5. Phospholipidosis in rats treated with amiodarone: serum biochemistry and whole genome micro-array analysis supporting the lipid traffic jam hypothesis and the subsequent rise of the biomarker BMP.

    Science.gov (United States)

    Mesens, Natalie; Desmidt, Miek; Verheyen, Geert R; Starckx, Sofie; Damsch, Siegrid; De Vries, Ronald; Verhemeldonck, Marc; Van Gompel, Jacky; Lampo, Ann; Lammens, Lieve

    2012-04-01

    To provide mechanistic insight in the induction of phospholipidosis and the appearance of the proposed biomarker di-docosahexaenoyl (C22:6)-bis(monoacylglycerol) phosphate (BMP), rats were treated with 150 mg/kg amiodarone for 12 consecutive days and analyzed at three different time points (day 4, 9, and 12). Biochemical analysis of the serum revealed a significant increase in cholesterol and phospholipids at the three time points. Bio-analysis on the serum and urine detected a time-dependent increase in BMP, as high as 10-fold compared to vehicle-treated animals on day 12. Paralleling these increases, micro-array analysis on the liver of treated rats identified cholesterol biosynthesis and glycerophospholipid metabolism as highly modulated pathways. This modulation indicates that during phospholipidosis-induction interactions take place between the cationic amphiphilic drug and phospholipids at the level of BMP-rich internal membranes of endosomes, impeding cholesterol sorting and leading to an accumulation of internal membranes, converting into multilamellar bodies. This process shows analogy to Niemann-Pick disease type C (NPC). Whereas the NPC-induced lipid traffic jam is situated at the cholesterol sorting proteins NPC1 and NPC2, the amiodarone-induced traffic jam is thought to be located at the BMP level, demonstrating its role in the mechanism of phospholipidosis-induction and its significance for use as a biomarker.

  6. Identification of candidate genes in osteoporosis by integrated microarray analysis

    Science.gov (United States)

    Li, J. J.; Wang, B. Q.; Yang, Y.; Li, D.

    2016-01-01

    Objectives In order to screen the altered gene expression profile in peripheral blood mononuclear cells of patients with osteoporosis, we performed an integrated analysis of the online microarray studies of osteoporosis. Methods We searched the Gene Expression Omnibus (GEO) database for microarray studies of peripheral blood mononuclear cells in patients with osteoporosis. Subsequently, we integrated gene expression data sets from multiple microarray studies to obtain differentially expressed genes (DEGs) between patients with osteoporosis and normal controls. Gene function analysis was performed to uncover the functions of identified DEGs. Results A total of three microarray studies were selected for integrated analysis. In all, 1125 genes were found to be significantly differentially expressed between osteoporosis patients and normal controls, with 373 upregulated and 752 downregulated genes. Positive regulation of the cellular amino metabolic process (gene ontology (GO): 0033240, false discovery rate (FDR) = 1.00E + 00) was significantly enriched under the GO category for biological processes, while for molecular functions, flavin adenine dinucleotide binding (GO: 0050660, FDR = 3.66E-01) and androgen receptor binding (GO: 0050681, FDR = 6.35E-01) were significantly enriched. DEGs were enriched in many osteoporosis-related signalling pathways, including those of mitogen-activated protein kinase (MAPK) and calcium. Protein-protein interaction (PPI) network analysis showed that the significant hub proteins contained ubiquitin specific peptidase 9, X-linked (Degree = 99), ubiquitin specific peptidase 19 (Degree = 57) and ubiquitin conjugating enzyme E2 B (Degree = 57). Conclusion Analysis of gene function of identified differentially expressed genes may expand our understanding of fundamental mechanisms leading to osteoporosis. Moreover, significantly enriched pathways, such as MAPK and calcium, may involve in osteoporosis through osteoblastic differentiation and

  7. Genome and Phenotype Microarray Analyses of Rhodococcus sp. BCP1 and Rhodococcus opacus R7: Genetic Determinants and Metabolic Abilities with Environmental Relevance

    Science.gov (United States)

    D’Ursi, Pasqualina; Milanesi, Luciano; Di Canito, Alessandra; Zampolli, Jessica; Collina, Elena; Decorosi, Francesca; Viti, Carlo; Fedi, Stefano; Presentato, Alessandro; Zannoni, Davide; Di Gennaro, Patrizia

    2015-01-01

    In this paper comparative genome and phenotype microarray analyses of Rhodococcus sp. BCP1 and Rhodococcus opacus R7 were performed. Rhodococcus sp. BCP1 was selected for its ability to grow on short-chain n-alkanes and R. opacus R7 was isolated for its ability to grow on naphthalene and on o-xylene. Results of genome comparison, including BCP1, R7, along with other Rhodococcus reference strains, showed that at least 30% of the genome of each strain presented unique sequences and only 50% of the predicted proteome was shared. To associate genomic features with metabolic capabilities of BCP1 and R7 strains, hundreds of different growth conditions were tested through Phenotype Microarray, by using Biolog plates and plates manually prepared with additional xenobiotic compounds. Around one-third of the surveyed carbon sources was utilized by both strains although R7 generally showed higher metabolic activity values compared to BCP1. Moreover, R7 showed broader range of nitrogen and sulphur sources. Phenotype Microarray data were combined with genomic analysis to genetically support the metabolic features of the two strains. The genome analysis allowed to identify some gene clusters involved in the metabolism of the main tested xenobiotic compounds. Results show that R7 contains multiple genes for the degradation of a large set of aromatic and PAHs compounds, while a lower variability in terms of genes predicted to be involved in aromatic degradation was found in BCP1. This genetic feature can be related to the strong genetic pressure exerted by the two different environment from which the two strains were isolated. According to this, in the BCP1 genome the smo gene cluster involved in the short-chain n-alkanes degradation, is included in one of the unique regions and it is not conserved in the Rhodococcus strains compared in this work. Data obtained underline the great potential of these two Rhodococcus spp. strains for biodegradation and environmental decontamination

  8. Genome and Phenotype Microarray Analyses of Rhodococcus sp. BCP1 and Rhodococcus opacus R7: Genetic Determinants and Metabolic Abilities with Environmental Relevance.

    Science.gov (United States)

    Orro, Alessandro; Cappelletti, Martina; D'Ursi, Pasqualina; Milanesi, Luciano; Di Canito, Alessandra; Zampolli, Jessica; Collina, Elena; Decorosi, Francesca; Viti, Carlo; Fedi, Stefano; Presentato, Alessandro; Zannoni, Davide; Di Gennaro, Patrizia

    2015-01-01

    In this paper comparative genome and phenotype microarray analyses of Rhodococcus sp. BCP1 and Rhodococcus opacus R7 were performed. Rhodococcus sp. BCP1 was selected for its ability to grow on short-chain n-alkanes and R. opacus R7 was isolated for its ability to grow on naphthalene and on o-xylene. Results of genome comparison, including BCP1, R7, along with other Rhodococcus reference strains, showed that at least 30% of the genome of each strain presented unique sequences and only 50% of the predicted proteome was shared. To associate genomic features with metabolic capabilities of BCP1 and R7 strains, hundreds of different growth conditions were tested through Phenotype Microarray, by using Biolog plates and plates manually prepared with additional xenobiotic compounds. Around one-third of the surveyed carbon sources was utilized by both strains although R7 generally showed higher metabolic activity values compared to BCP1. Moreover, R7 showed broader range of nitrogen and sulphur sources. Phenotype Microarray data were combined with genomic analysis to genetically support the metabolic features of the two strains. The genome analysis allowed to identify some gene clusters involved in the metabolism of the main tested xenobiotic compounds. Results show that R7 contains multiple genes for the degradation of a large set of aromatic and PAHs compounds, while a lower variability in terms of genes predicted to be involved in aromatic degradation was found in BCP1. This genetic feature can be related to the strong genetic pressure exerted by the two different environment from which the two strains were isolated. According to this, in the BCP1 genome the smo gene cluster involved in the short-chain n-alkanes degradation, is included in one of the unique regions and it is not conserved in the Rhodococcus strains compared in this work. Data obtained underline the great potential of these two Rhodococcus spp. strains for biodegradation and environmental decontamination

  9. Microarray karyotyping of commercial wine yeast strains reveals shared, as well as unique, genomic signatures

    Directory of Open Access Journals (Sweden)

    Levine R Paul

    2005-04-01

    Full Text Available Abstract Background Genetic differences between yeast strains used in wine-making may account for some of the variation seen in their fermentation properties and may also produce differing sensory characteristics in the final wine product itself. To investigate this, we have determined genomic differences among several Saccharomyces cerevisiae wine strains by using a "microarray karyotyping" (also known as "array-CGH" or "aCGH" technique. Results We have studied four commonly used commercial wine yeast strains, assaying three independent isolates from each strain. All four wine strains showed common differences with respect to the laboratory S. cerevisiae strain S288C, some of which may be specific to commercial wine yeasts. We observed very little intra-strain variation; i.e., the genomic karyotypes of different commercial isolates of the same strain looked very similar, although an exception to this was seen among the Montrachet isolates. A moderate amount of inter-strain genomic variation between the four wine strains was observed, mostly in the form of depletions or amplifications of single genes; these differences allowed unique identification of each strain. Many of the inter-strain differences appear to be in transporter genes, especially hexose transporters (HXT genes, metal ion sensors/transporters (CUP1, ZRT1, ENA genes, members of the major facilitator superfamily, and in genes involved in drug response (PDR3, SNQ1, QDR1, RDS1, AYT1, YAR068W. We therefore used halo assays to investigate the response of these strains to three different fungicidal drugs (cycloheximide, clotrimazole, sulfomethuron methyl. Strains with fewer copies of the CUP1 loci showed hypersensitivity to sulfomethuron methyl. Conclusion Microarray karyotyping is a useful tool for analyzing the genome structures of wine yeasts. Despite only small to moderate variations in gene copy numbers between different wine yeast strains and within different isolates of a given

  10. GenePublisher: automated analysis of DNA microarray data

    DEFF Research Database (Denmark)

    Knudsen, Steen; Workman, Christopher; Sicheritz-Ponten, T.

    2003-01-01

    GenePublisher, a system for automatic analysis of data from DNA microarray experiments, has been implemented with a web interface at http://www.cbs.dtu.dk/services/GenePublisher. Raw data are uploaded to the server together with aspecification of the data. The server performs normalization......, statistical analysis and visualization of the data. The results are run against databases of signal transduction pathways, metabolic pathways and promoter sequences in order to extract more information. The results of the entire analysis are summarized in report form and returned to the user....

  11. Tumour class prediction and discovery by microarray-based DNA methylation analysis

    OpenAIRE

    Adorján, Péter; Distler, Jürgen; Lipscher, Evelyne; Model, Fabian; Müller, Jürgen; Pelet, Cécile; Braun, Aron; Florl, Andrea R.; Gütig, David; Grabs, Gabi; Howe, André; Kursar, Mischo; Lesche, Ralf; Leu, Erik; Lewin, André

    2002-01-01

    Aberrant DNA methylation of CpG sites is among the earliest and most frequent alterations in cancer. Several studies suggest that aberrant methylation occurs in a tumour type-specific manner. However, large-scale analysis of candidate genes has so far been hampered by the lack of high throughput assays for methylation detection. We have developed the first microarray-based technique which allows genome-wide assessment of selected CpG dinucleotides as well as quantification of methylation at e...

  12. Structural and functional analysis of rice genome

    Indian Academy of Sciences (India)

    Akhilesh K. Tyagi; Jitendra P. Khurana; Paramjit Khurana; Saurabh Raghuvanshi; Anupama Gaur; Anita Kapur; Vikrant Gupta; Dibyendu Kumar; V. Ravi; Shubha Vij; Parul Khurana; Sulabha Sharma

    2004-04-01

    Rice is an excellent system for plant genomics as it represents a modest size genome of 430 Mb. It feeds more than half the population of the world. Draft sequences of the rice genome, derived by whole-genome shotgun approach at relatively low coverage (4–6 X), were published and the International Rice Genome Sequencing Project (IRGSP) declared high quality (>10 X), genetically anchored, phase 2 level sequence in 2002. In addition, phase 3 level finished sequence of chromosomes 1, 4 and 10 (out of 12 chromosomes of rice) has already been reported by scientists from IRGSP consortium. Various estimates of genes in rice place the number at > 50,000. Already, over 28,000 full-length cDNAs have been sequenced, most of which map to genetically anchored genome sequence. Such information is very useful in revealing novel features of macro- and micro-level synteny of rice genome with other cereals. Microarray analysis is unraveling the identity of rice genes expressing in temporal and spatial manner and should help target candidate genes useful for improving traits of agronomic importance. Simultaneously, functional analysis of rice genome has been initiated by marker-based characterization of useful genes and employing functional knock-outs created by mutation or gene tagging. Integration of this enormous information is expected to catalyze tremendous activity on basic and applied aspects of rice genomics.

  13. MmPalateMiRNA, an R package compendium illustrating analysis of miRNA microarray data.

    Science.gov (United States)

    Brock, Guy N; Mukhopadhyay, Partha; Pihur, Vasyl; Webb, Cynthia; Greene, Robert M; Pisano, M Michele

    2013-01-08

    MicroRNAs (miRNAs) constitute the largest family of noncoding RNAs involved in gene silencing and represent critical regulators of cell and tissue differentiation. Microarray expression profiling of miRNAs is an effective means of acquiring genome-level information of miRNA activation and inhibition, as well as the potential regulatory role that these genes play within a biological system. As with mRNA expression profiling arrays, miRNA microarrays come in a variety of platforms from numerous manufacturers, and there are a multitude of techniques available for reducing and analyzing these data. In this paper, we present an analysis of a typical two-color miRNA microarray experiment using publicly available packages from R and Bioconductor, the open-source software project for the analysis of genomic data. Covered topics include visualization, normalization, quality checking, differential expression, cluster analysis, miRNA target identification, and gene set enrichment analysis. Many of these tools carry-over from the analysis of mRNA microarrays, but with some notable differences that require special attention. The paper is presented as a "compendium" which, along with the accompanying R package MmPalateMiRNA, contains all of the experimental data and source code to reproduce the analyses contained in the paper. The compendium presented in this paper will provide investigators with an access point for applying the methods available in R and Bioconductor for analysis of their own miRNA array data.

  14. D-MaPs - DNA-microarray projects: web-based software for multi-platform microarray analysis

    Directory of Open Access Journals (Sweden)

    Marcelo F. Carazzolle

    2009-01-01

    Full Text Available The web application D-Maps provides a user-friendly interface to researchers performing studies based on microarrays. The program was developed to manage and process one- or two-color microarray data obtained from several platforms (currently, GeneTAC, ScanArray, CodeLink, NimbleGen and Affymetrix. Despite the availability of many algorithms and many software programs designed to perform microarray analysis on the internet, these usually require sophisticated knowledge of mathematics, statistics and computation. D-maps was developed to overcome the requirement of high performance computers or programming experience. D-Maps performs raw data processing, normalization and statistical analysis, allowing access to the analyzed data in text or graphical format. An original feature presented by D-Maps is GEO (Gene Expression Omnibus submission format service. The D-MaPs application was already used for analysis of oligonucleotide microarrays and PCR-spotted arrays (one- and two-color, laser and light scanner. In conclusion, D-Maps is a valuable tool for microarray research community, especially in the case of groups without a bioinformatic core.

  15. From RNA isolation to microarray analysis: Comparison of methods in FFPE tissues.

    Science.gov (United States)

    Belder, Nevin; Coskun, Öznur; Doganay Erdogan, Beyza; Ilk, Ozlem; Savas, Berna; Ensari, Arzu; Özdağ, Hilal

    2016-08-01

    Genome-wide gene expression profiling analysis of FFPE tissue samples is indispensable for cancer research and provides the opportunity to evaluate links between molecular and clinical information, however, working with FFPE samples is challenging due to extensive cross-linking, fragmentation and limited quantities of nucleic acid. Thus, processing of FFPE tissue samples from RNA extraction to microarray analysis still needs optimization. In this study, a modified deparaffinization protocol was conducted prior to RNA isolation. Trizol, Qiagen RNeasy FFPE and Arcturus PicoPure RNA Isolation kits were used in parallel to compare their impact on RNA isolation. We also evaluated the effect of two different cRNA/cDNA preparation and labeling protocols with two different array platforms (Affymetrix Human Genome U133 Plus 2.0 and U133_X3P) on the percentage of present calls. Our optimization study shows that the Qiagen RNeasy FFPE kit with modified deparaffinization step gives better results (RNA quantity and quality) than the other two isolation kits. The Ribo-SPIA protocol gave a significantly higher percentage of present calls than the 3' IVT cDNA amplification and labeling system. However, no significant differences were found between the two array platforms. Our study paves the way for future high-throughput transcriptional analysis by optimizing FFPE tissue sample processing from RNA isolation to microarray analysis. Copyright © 2016 Elsevier GmbH. All rights reserved.

  16. Global nutrient profiling by Phenotype MicroArrays: a tool complementing genomic and proteomic studies in conidial fungi*

    Science.gov (United States)

    Atanasova, Lea; Druzhinina, Irina S.

    2010-01-01

    Conidial fungi or molds and mildews are widely used in modern biotechnology as producers of antibiotics and other secondary metabolites, industrially important enzymes, chemicals and food. They are also important pathogens of animals including humans and agricultural crops. These various applications and extremely versatile natural phenotypes have led to the constantly growing list of complete genomes which are now available. Functional genomics and proteomics widely exploit the genomic information to study the cell-wide impact of altered genes on the phenotype of an organism and its function. This allows for global analysis of the information flow from DNA to RNA to protein, but it is usually not sufficient for the description of the global phenotype of an organism. More recently, Phenotype MicroArray (PM) technology has been introduced as a tool to characterize the metabolism of a (wild) fungal strain or a mutant. In this article, we review the background of PM applications for fungi and the methodic requirements to obtain reliable results. We also report examples of the versatility of this tool. PMID:20205302

  17. Science Letters: A robust statistical procedure to discover expression biomarkers using microarray genomic expression data

    Institute of Scientific and Technical Information of China (English)

    ZOU Yang-yun; YANG Jian; ZHU Jun

    2006-01-01

    Microarray has become increasingly popular biotechnology in biological and medical researches, and has been widely applied in classification of treatment subtypes using expression patterns of biomarkers. We developed a statistical procedure to identify expression biomarkers for treatment subtype classification by constructing an F-statistic based on Henderson method Ⅲ.Monte Carlo simulations were conducted to examine the robustness and efficiency of the proposed method. Simulation results showed that our method could provide satisfying power of identifying differentially expressed genes (DEGs) with false discovery rate (FDR) lower than the given type Ⅰ error rate. In addition, we analyzed a leukemia dataset collected from 38 leukemia patients with 27 samples diagnosed as acute lymphoblastic leukemia (ALL) and 11 samples as acute myeloid leukemia (AML). We compared our results with those from the methods of significance analysis of microarray (SAM) and microarray analysis of variance (MAANOVA). Among these three methods, only expression biomarkers identified by our method can precisely identify the three human acute leukemia subtypes.

  18. Clinical implementation of chromosomal microarray analysis: summary of 2513 postnatal cases.

    Directory of Open Access Journals (Sweden)

    Xinyan Lu

    Full Text Available BACKGROUND: Array Comparative Genomic Hybridization (a-CGH is a powerful molecular cytogenetic tool to detect genomic imbalances and study disease mechanism and pathogenesis. We report our experience with the clinical implementation of this high resolution human genome analysis, referred to as Chromosomal Microarray Analysis (CMA. METHODS AND FINDINGS: CMA was performed clinically on 2513 postnatal samples from patients referred with a variety of clinical phenotypes. The initial 775 samples were studied using CMA array version 4 and the remaining 1738 samples were analyzed with CMA version 5 containing expanded genomic coverage. Overall, CMA identified clinically relevant genomic imbalances in 8.5% of patients: 7.6% using V4 and 8.9% using V5. Among 117 cases referred for additional investigation of a known cytogenetically detectable rearrangement, CMA identified the majority (92.5% of the genomic imbalances. Importantly, abnormal CMA findings were observed in 5.2% of patients (98/1872 with normal karyotypes/FISH results, and V5, with expanded genomic coverage, enabled a higher detection rate in this category than V4. For cases without cytogenetic results available, 8.0% (42/524 abnormal CMA results were detected; again, V5 demonstrated an increased ability to detect abnormality. Improved diagnostic potential of CMA is illustrated by 90 cases identified with 51 cryptic microdeletions and 39 predicted apparent reciprocal microduplications in 13 specific chromosomal regions associated with 11 known genomic disorders. In addition, CMA identified copy number variations (CNVs of uncertain significance in 262 probands; however, parental studies usually facilitated clinical interpretation. Of these, 217 were interpreted as familial variants and 11 were determined to be de novo; the remaining 34 await parental studies to resolve the clinical significance. CONCLUSIONS: This large set of clinical results demonstrates the significantly improved sensitivity

  19. Development of a custom-designed, pan genomic DNA microarray to characterize strain-level diversity among Cronobacter spp.

    Directory of Open Access Journals (Sweden)

    Ben Davies Tall

    2015-04-01

    Full Text Available Cronobacter species cause infections in all age groups; however neonates are at highest risk and remain the most susceptible age group for life-threatening invasive disease. The genus contains seven species: C. sakazakii, C. malonaticus, C. turicensis C. muytjensii, C. dublinensis, C. universalis, and C. condimenti. Despite an abundance of published genomes of these species, genomics-based epidemiology of the genus is not well established. The gene content of a diverse group of 126 unique Cronobacter and taxonomically-related isolates was determined using a pan genomic-based DNA microarray as a genotyping tool and as a means to identify outbreak isolates for food safety, environmental, and clinical surveillance purposes. The microarray constitutes 19,287 independent genes representing 15 Cronobacter genomes and 18 plasmids and 2,371 virulence factor genes of phylogenetically-related Gram-negative bacteria. The Cronobacter microarray was able to distinguish the seven Cronobacter species from one another and from non-Cronobacter species; and within each species, strains grouped into distinct clusters based on their genomic diversity. These results also support the phylogenic divergence of the genus and clearly highlight the genomic diversity among each member of the genus. The current study establishes a powerful platform for further genomics research of this diverse genus, an important prerequisite towards the development of future countermeasures against this foodborne pathogen in the food safety and clinical arenas.

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

    Directory of Open Access Journals (Sweden)

    Malloch Gaynor

    2007-11-01

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

  1. Distinguishing bacterial pathogens of potato using a genome-wide microarray approach.

    Science.gov (United States)

    Aittamaa, M; Somervuo, P; Pirhonen, M; Mattinen, L; Nissinen, R; Auvinen, P; Valkonen, J P T

    2008-09-01

    A set of 9676 probes was designed for the most harmful bacterial pathogens of potato and tested in a microarray format. Gene-specific probes could be designed for all genes of Pectobacterium atrosepticum, c. 50% of the genes of Streptomyces scabies and c. 30% of the genes of Clavibacter michiganensis ssp. sepedonicus utilizing the whole-genome sequence information available. For Streptomyces turgidiscabies, 226 probes were designed according to the sequences of a pathogenicity island containing important virulence genes. In addition, probes were designed for the virulence-associated nip (necrosis-inducing protein) genes of P. atrosepticum, P. carotovorum and Dickeya dadantii and for the intergenic spacer (IGS) sequences of the 16S-23S rRNA gene region. Ralstonia solanacearum was not included in the study, because it is a quarantine organism and is not presently found in Finland, but a few probes were also designed for this species. The probes contained on average 40 target-specific nucleotides and were synthesized on the array in situ, organized as eight sub-arrays with an identical set of probes which could be used for hybridization with different samples. All bacteria were readily distinguished using a single channel system for signal detection. Nearly all of the c. 1000 probes designed for C. michiganensis ssp. sepedonicus, c. 50% and 40% of the c. 4000 probes designed for the genes of S. scabies and P. atrosepticum, respectively, and over 100 probes for S. turgidiscabies showed significant signals only with the respective species. P. atrosepticum, P. carotovorum and Dickeya strains were all detected with 110 common probes. By contrast, the strains of these species were found to differ in their signal profiles. Probes targeting the IGS region and nip genes could be used to place strains of Dickeya to two groups, which correlated with differences in virulence. Taken together, the approach of using a custom-designed, genome-wide microarray provided a robust means

  2. Integrated Microfluidic Devices for Automated Microarray-Based Gene Expression and Genotyping Analysis

    Science.gov (United States)

    Liu, Robin H.; Lodes, Mike; Fuji, H. Sho; Danley, David; McShea, Andrew

    Microarray assays typically involve multistage sample processing and fluidic handling, which are generally labor-intensive and time-consuming. Automation of these processes would improve robustness, reduce run-to-run and operator-to-operator variation, and reduce costs. In this chapter, a fully integrated and self-contained microfluidic biochip device that has been developed to automate the fluidic handling steps for microarray-based gene expression or genotyping analysis is presented. The device consists of a semiconductor-based CustomArray® chip with 12,000 features and a microfluidic cartridge. The CustomArray was manufactured using a semiconductor-based in situ synthesis technology. The micro-fluidic cartridge consists of microfluidic pumps, mixers, valves, fluid channels, and reagent storage chambers. Microarray hybridization and subsequent fluidic handling and reactions (including a number of washing and labeling steps) were performed in this fully automated and miniature device before fluorescent image scanning of the microarray chip. Electrochemical micropumps were integrated in the cartridge to provide pumping of liquid solutions. A micromixing technique based on gas bubbling generated by electrochemical micropumps was developed. Low-cost check valves were implemented in the cartridge to prevent cross-talk of the stored reagents. Gene expression study of the human leukemia cell line (K562) and genotyping detection and sequencing of influenza A subtypes have been demonstrated using this integrated biochip platform. For gene expression assays, the microfluidic CustomArray device detected sample RNAs with a concentration as low as 0.375 pM. Detection was quantitative over more than three orders of magnitude. Experiment also showed that chip-to-chip variability was low indicating that the integrated microfluidic devices eliminate manual fluidic handling steps that can be a significant source of variability in genomic analysis. The genotyping results showed

  3. Neural network analysis of lymphoma microarray data: prognosis and diagnosis near-perfect

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    Song Li

    2003-04-01

    Full Text Available Abstract Background Microarray chips are being rapidly deployed as a major tool in genomic research. To date most of the analysis of the enormous amount of information provided on these chips has relied on clustering techniques and other standard statistical procedures. These methods, particularly with regard to cancer patient prognosis, have generally been inadequate in providing the reduced gene subsets required for perfect classification. Results Networks trained on microarray data from DLBCL lymphoma patients have, for the first time, been able to predict the long-term survival of individual patients with 100% accuracy. Other networks were able to distinguish DLBCL lymphoma donors from other donors, including donors with other lymphomas, with 99% accuracy. Differentiating the trained network can narrow the gene profile to less than three dozen genes for each classification. Conclusions Here we show that artificial neural networks are a superior tool for digesting microarray data both with regard to making distinctions based on the data and with regard to providing very specific reference as to which genes were most important in making the correct distinction in each case.

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

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    Daniel L Roden

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

  5. Identification of Differentially Expressed Genes in Pituitary Adenomas by Integrating Analysis of Microarray Data

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    Peng Zhao

    2015-01-01

    Full Text Available Pituitary adenomas, monoclonal in origin, are the most common intracranial neoplasms. Altered gene expression as well as somatic mutations is detected frequently in pituitary adenomas. The purpose of this study was to detect differentially expressed genes (DEGs and biological processes during tumor formation of pituitary adenomas. We performed an integrated analysis of publicly available GEO datasets of pituitary adenomas to identify DEGs between pituitary adenomas and normal control (NC tissues. Gene function analysis including Gene Ontology (GO, Kyoto Encyclopedia of Genes and Genomes (KEGG pathway enrichment analysis, and protein-protein interaction (PPI networks analysis was conducted to interpret the biological role of those DEGs. In this study we detected 3994 DEGs (2043 upregulated and 1951 downregulated in pituitary adenoma through an integrated analysis of 5 different microarray datasets. Gene function analysis revealed that the functions of those DEGs were highly correlated with the development of pituitary adenoma. This integrated analysis of microarray data identified some genes and pathways associated with pituitary adenoma, which may help to understand the pathology underlying pituitary adenoma and contribute to the successful identification of therapeutic targets for pituitary adenoma.

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

    Science.gov (United States)

    Tchagang, Alain B.; Tewfik, Ahmed H.

    2006-12-01

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

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

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    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.

  8. Microarray-Based Gene Expression Analysis for Veterinary Pathologists: A Review.

    Science.gov (United States)

    Raddatz, Barbara B; Spitzbarth, Ingo; Matheis, Katja A; Kalkuhl, Arno; Deschl, Ulrich; Baumgärtner, Wolfgang; Ulrich, Reiner

    2017-09-01

    High-throughput, genome-wide transcriptome analysis is now commonly used in all fields of life science research and is on the cusp of medical and veterinary diagnostic application. Transcriptomic methods such as microarrays and next-generation sequencing generate enormous amounts of data. The pathogenetic expertise acquired from understanding of general pathology provides veterinary pathologists with a profound background, which is essential in translating transcriptomic data into meaningful biological knowledge, thereby leading to a better understanding of underlying disease mechanisms. The scientific literature concerning high-throughput data-mining techniques usually addresses mathematicians or computer scientists as the target audience. In contrast, the present review provides the reader with a clear and systematic basis from a veterinary pathologist's perspective. Therefore, the aims are (1) to introduce the reader to the necessary methodological background; (2) to introduce the sequential steps commonly performed in a microarray analysis including quality control, annotation, normalization, selection of differentially expressed genes, clustering, gene ontology and pathway analysis, analysis of manually selected genes, and biomarker discovery; and (3) to provide references to publically available and user-friendly software suites. In summary, the data analysis methods presented within this review will enable veterinary pathologists to analyze high-throughput transcriptome data obtained from their own experiments, supplemental data that accompany scientific publications, or public repositories in order to obtain a more in-depth insight into underlying disease mechanisms.

  9. Multiple platform assessment of the EGF dependent transcriptome by microarray and deep tag sequencing analysis

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    Iraola Susana

    2011-06-01

    Full Text Available Abstract Background Epidermal Growth Factor (EGF is a key regulatory growth factor activating many processes relevant to normal development and disease, affecting cell proliferation and survival. Here we use a combined approach to study the EGF dependent transcriptome of HeLa cells by using multiple long oligonucleotide based microarray platforms (from Agilent, Operon, and Illumina in combination with digital gene expression profiling (DGE with the Illumina Genome Analyzer. Results By applying a procedure for cross-platform data meta-analysis based on RankProd and GlobalAncova tests, we establish a well validated gene set with transcript levels altered after EGF treatment. We use this robust gene list to build higher order networks of gene interaction by interconnecting associated networks, supporting and extending the important role of the EGF signaling pathway in cancer. In addition, we find an entirely new set of genes previously unrelated to the currently accepted EGF associated cellular functions. Conclusions We propose that the use of global genomic cross-validation derived from high content technologies (microarrays or deep sequencing can be used to generate more reliable datasets. This approach should help to improve the confidence of downstream in silico functional inference analyses based on high content data.

  10. Optimization of RNA Isolation from the Archaebacterium Methanosarcina Barkeri and Validation for Oligonucleotide Microarray Analysis

    Energy Technology Data Exchange (ETDEWEB)

    Culley, David E.; Kovacik, William P.; Brockman, Fred J.; Zhang, Weiwen

    2006-10-01

    ABSTRACT-The recent completion of a draft genome sequence for Methanosarcina barkeri has allowed the application of various high throughput post-genomics technologies, such as nucleic acid microarrays and mass spectrometry of proteins to detect global changes in transcription and translation that occur in response to experimental treatments...

  11. Dissection of the inflammatory bowel disease transcriptome using genome-wide cDNA microarrays.

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    Christine M Costello

    2005-08-01

    Full Text Available BACKGROUND: The differential pathophysiologic mechanisms that trigger and maintain the two forms of inflammatory bowel disease (IBD, Crohn disease (CD, and ulcerative colitis (UC are only partially understood. cDNA microarrays can be used to decipher gene regulation events at a genome-wide level and to identify novel unknown genes that might be involved in perpetuating inflammatory disease progression. METHODS AND FINDINGS: High-density cDNA microarrays representing 33,792 UniGene clusters were prepared. Biopsies were taken from the sigmoid colon of normal controls (n = 11, CD patients (n = 10 and UC patients (n = 10. 33P-radiolabeled cDNA from purified poly(A+ RNA extracted from biopsies (unpooled was hybridized to the arrays. We identified 500 and 272 transcripts differentially regulated in CD and UC, respectively. Interesting hits were independently verified by real-time PCR in a second sample of 100 individuals, and immunohistochemistry was used for exemplary localization. The main findings point to novel molecules important in abnormal immune regulation and the highly disturbed cell biology of colonic epithelial cells in IBD pathogenesis, e.g., CYLD (cylindromatosis, turban tumor syndrome and CDH11 (cadherin 11, type 2. By the nature of the array setup, many of the genes identified were to our knowledge previously uncharacterized, and prediction of the putative function of a subsection of these genes indicate that some could be involved in early events in disease pathophysiology. CONCLUSION: A comprehensive set of candidate genes not previously associated with IBD was revealed, which underlines the polygenic and complex nature of the disease. It points out substantial differences in pathophysiology between CD and UC. The multiple unknown genes identified may stimulate new research in the fields of barrier mechanisms and cell signalling in the context of IBD, and ultimately new therapeutic approaches.

  12. k-Nearest neighbor models for microarray gene expression analysis and clinical outcome prediction.

    Science.gov (United States)

    Parry, R M; Jones, W; Stokes, T H; Phan, J H; Moffitt, R A; Fang, H; Shi, L; Oberthuer, A; Fischer, M; Tong, W; Wang, M D

    2010-08-01

    In the clinical application of genomic data analysis and modeling, a number of factors contribute to the performance of disease classification and clinical outcome prediction. This study focuses on the k-nearest neighbor (KNN) modeling strategy and its clinical use. Although KNN is simple and clinically appealing, large performance variations were found among experienced data analysis teams in the MicroArray Quality Control Phase II (MAQC-II) project. For clinical end points and controls from breast cancer, neuroblastoma and multiple myeloma, we systematically generated 463,320 KNN models by varying feature ranking method, number of features, distance metric, number of neighbors, vote weighting and decision threshold. We identified factors that contribute to the MAQC-II project performance variation, and validated a KNN data analysis protocol using a newly generated clinical data set with 478 neuroblastoma patients. We interpreted the biological and practical significance of the derived KNN models, and compared their performance with existing clinical factors.

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

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    Primmer Craig R

    2009-09-01

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

  14. Identification of Novel Epithelial Ovarian Cancer Biomarkers by Cross-laboratory Microarray Analysis

    Institute of Scientific and Technical Information of China (English)

    蒋学锋; 朱涛; 杨洁; 李双; 叶双梅; 廖书杰; 孟力; 卢运萍; 马丁

    2010-01-01

    The purpose of this study was to pool information in epithelial ovarian cancer by combining studies using Affymetrix expression microarray datasets made at different laboratories to identify novel biomarkers.Epithelial microarray expression information across laboratories was screened and combined after preprocessing raw microarray data,then ANOVA and unpaired T test statistical analysis was performed for identifying differentially expressed genes(DEGs),followed by clustering and pathway analysis for these ...

  15. Optimization of Cyanine Dye Stability and Analysis of FRET Interaction on DNA Microarrays.

    Science.gov (United States)

    von der Haar, Marcel; Heuer, Christopher; Pähler, Martin; von der Haar, Kathrin; Lindner, Patrick; Scheper, Thomas; Stahl, Frank

    2016-11-30

    The application of DNA microarrays for high throughput analysis of genetic regulation is often limited by the fluorophores used as markers. The implementation of multi-scan techniques is limited by the fluorophores' susceptibility to photobleaching when exposed to the scanner laser light. This paper presents combined mechanical and chemical strategies which enhance the photostability of cyanine 3 and cyanine 5 as part of solid state DNA microarrays. These strategies are based on scanning the microarrays while the hybridized DNA is still in an aqueous solution with the presence of a reductive/oxidative system (ROXS). Furthermore, the experimental setup allows for the analysis and eventual normalization of Förster-resonance-energy-transfer (FRET) interaction of cyanine-3/cyanine-5 dye combinations on the microarray. These findings constitute a step towards standardization of microarray experiments and analysis and may help to increase the comparability of microarray experiment results between labs.

  16. Optimization of Cyanine Dye Stability and Analysis of FRET Interaction on DNA Microarrays

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    Marcel von der Haar

    2016-11-01

    Full Text Available The application of DNA microarrays for high throughput analysis of genetic regulation is often limited by the fluorophores used as markers. The implementation of multi-scan techniques is limited by the fluorophores’ susceptibility to photobleaching when exposed to the scanner laser light. This paper presents combined mechanical and chemical strategies which enhance the photostability of cyanine 3 and cyanine 5 as part of solid state DNA microarrays. These strategies are based on scanning the microarrays while the hybridized DNA is still in an aqueous solution with the presence of a reductive/oxidative system (ROXS. Furthermore, the experimental setup allows for the analysis and eventual normalization of Förster-resonance-energy-transfer (FRET interaction of cyanine-3/cyanine-5 dye combinations on the microarray. These findings constitute a step towards standardization of microarray experiments and analysis and may help to increase the comparability of microarray experiment results between labs.

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

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    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

  18. Microarray-based comparative genomic profiling of reference strains and selected Canadian field isolates of Actinobacillus pleuropneumoniae

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    MacInnes Janet I

    2009-02-01

    Full Text Available Abstract Background Actinobacillus pleuropneumoniae, the causative agent of porcine pleuropneumonia, is a highly contagious respiratory pathogen that causes severe losses to the swine industry worldwide. Current commercially-available vaccines are of limited value because they do not induce cross-serovar immunity and do not prevent development of the carrier state. Microarray-based comparative genomic hybridizations (M-CGH were used to estimate whole genomic diversity of representative Actinobacillus pleuropneumoniae strains. Our goal was to identify conserved genes, especially those predicted to encode outer membrane proteins and lipoproteins because of their potential for the development of more effective vaccines. Results Using hierarchical clustering, our M-CGH results showed that the majority of the genes in the genome of the serovar 5 A. pleuropneumoniae L20 strain were conserved in the reference strains of all 15 serovars and in representative field isolates. Fifty-eight conserved genes predicted to encode for outer membrane proteins or lipoproteins were identified. As well, there were several clusters of diverged or absent genes including those associated with capsule biosynthesis, toxin production as well as genes typically associated with mobile elements. Conclusion Although A. pleuropneumoniae strains are essentially clonal, M-CGH analysis of the reference strains of the fifteen serovars and representative field isolates revealed several classes of genes that were divergent or absent. Not surprisingly, these included genes associated with capsule biosynthesis as the capsule is associated with sero-specificity. Several of the conserved genes were identified as candidates for vaccine development, and we conclude that M-CGH is a valuable tool for reverse vaccinology.

  19. Microarray-based analysis for hepatocellular carcinoma: From gene expression profiling to new challenges

    Institute of Scientific and Technical Information of China (English)

    Yutaka Midorikawa; Masatoshi Makuuchi; Wei Tang; Hiroyuki Aburatani

    2007-01-01

    Accumulation of mutations and alterations in the expression of various genes result in carcinogenesis, and the development of microarray technology has enabled us to identify the comprehensive gene expression alterations in oncogenesis. Many studies have applied this technology for hepatocellular carcinoma (HCC), and identified a number of candidate genes useful as biomarkers in cancer staging, prediction of recurrence and prognosis, and treatment selection. Some of these target molecules have been used to develop new serum diagnostic markers and therapeutic targets against HCC to benefit patients. Previously, we compared gene expression profiling data with classification based on clinicopathological features, such as hepatitis viral infection or liver cancer progression. The next era of gene expression analysis will require systematic integration of expression profiles with other types of biological information, such as genomic locus, gene function, and sequence information. We have reported integration between expression profiles and locus information, which is effective in detecting structural genomic abnormalities, such as chromosomal gains and losses, in which we showed that gene expression profiles are subject to chromosomal bias. Furthermore, array-based comparative genomic hybridization analysis and allelic dosage analysis using genotyping arrays for HCC were also reviewed, with comparison of conventional methods.

  20. DNA microarrays for comparative genomic hybridization based on DOP-PCR amplification of BAC and PAC clones.

    Science.gov (United States)

    Fiegler, Heike; Carr, Philippa; Douglas, Eleanor J; Burford, Deborah C; Hunt, Sarah; Scott, Carol E; Smith, James; Vetrie, David; Gorman, Patricia; Tomlinson, Ian P M; Carter, Nigel P

    2003-04-01

    We have designed DOP-PCR primers specifically for the amplification of large insert clones for use in the construction of DNA microarrays. A bioinformatic approach was used to construct primers that were efficient in the general amplification of human DNA but were poor at amplifying E. coli DNA, a common contaminant of DNA preparations from large insert clones. We chose the three most selective primers for use in printing DNA microarrays. DNA combined from the amplification of large insert clones by use of these three primers and spotted onto glass slides showed more than a sixfold increase in the human to E. coli hybridization ratio when compared to the standard DOP-PCR primer, 6MW. The microarrays reproducibly delineated previously characterized gains and deletions in a cancer cell line and identified a small gain not detected by use of conventional CGH. We also describe a method for the bulk testing of the hybridization characteristics of chromosome-specific clones spotted on microarrays by use of DNA amplified from flow-sorted chromosomes. Finally, we describe a set of clones selected from the publicly available Golden Path of the human genome at 1-Mb intervals and a view in the Ensembl genome browser from which data required for the use of these clones in array CGH and other experiments can be downloaded across the Internet.

  1. Maize microarray annotation database

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    Berger Dave K

    2011-10-01

    Full Text Available Abstract Background Microarray technology has matured over the past fifteen years into a cost-effective solution with established data analysis protocols for global gene expression profiling. The Agilent-016047 maize 44 K microarray was custom-designed from EST sequences, but only reporter sequences with EST accession numbers are publicly available. The following information is lacking: (a reporter - gene model match, (b number of reporters per gene model, (c potential for cross hybridization, (d sense/antisense orientation of reporters, (e position of reporter on B73 genome sequence (for eQTL studies, and (f functional annotations of genes represented by reporters. To address this, we developed a strategy to annotate the Agilent-016047 maize microarray, and built a publicly accessible annotation database. Description Genomic annotation of the 42,034 reporters on the Agilent-016047 maize microarray was based on BLASTN results of the 60-mer reporter sequences and their corresponding ESTs against the maize B73 RefGen v2 "Working Gene Set" (WGS predicted transcripts and the genome sequence. The agreement between the EST, WGS transcript and gDNA BLASTN results were used to assign the reporters into six genomic annotation groups. These annotation groups were: (i "annotation by sense gene model" (23,668 reporters, (ii "annotation by antisense gene model" (4,330; (iii "annotation by gDNA" without a WGS transcript hit (1,549; (iv "annotation by EST", in which case the EST from which the reporter was designed, but not the reporter itself, has a WGS transcript hit (3,390; (v "ambiguous annotation" (2,608; and (vi "inconclusive annotation" (6,489. Functional annotations of reporters were obtained by BLASTX and Blast2GO analysis of corresponding WGS transcripts against GenBank. The annotations are available in the Maize Microarray Annotation Database http://MaizeArrayAnnot.bi.up.ac.za/, as well as through a GBrowse annotation file that can be uploaded to

  2. Microarray analysis of Neosartorya fischeri using different carbon sources, petroleum asphaltenes and glucose-peptone

    Science.gov (United States)

    Hernández-López, Edna L.; Ramírez-Puebla, Shamayim T.; Vazquez-Duhalt, Rafael

    2015-01-01

    Asphaltenes are considered as the most recalcitrant petroleum fraction and represent a big problem for the recovery, separation and processing of heavy oils and bitumens. Neosartorya fischeri is a saprophytic fungus that is able to grow using asphaltenes as the sole carbon source [1]. We performed transcription profiling using a custom designed microarray with the complete genome from N. fischeri NRRL 181 in order to identify genes related to the transformation of asphaltenes [1]. Data analysis was performed using the genArise software. Results showed that 287 genes were up-regulated and 118 were down-regulated. Here we describe experimental procedures and methods about our dataset (NCBI GEO accession number GSE68146) and describe the data analysis to identify different expression levels in N. fischeri using this recalcitrant carbon source. PMID:26484261

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

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    Craven Mark

    2009-09-01

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

  4. Development and validation of a Xanthomonas axonopodis pv. citri DNA microarray platform (XACarray generated from the shotgun libraries previously used in the sequencing of this bacterial genome

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    Zaini Paulo A

    2010-05-01

    Full Text Available Abstract Background From shotgun libraries used for the genomic sequencing of the phytopathogenic bacterium Xanthomonas axonopodis pv. citri (XAC, clones that were representative of the largest possible number of coding sequences (CDSs were selected to create a DNA microarray platform on glass slides (XACarray. The creation of the XACarray allowed for the establishment of a tool that is capable of providing data for the analysis of global genome expression in this organism. Findings The inserts from the selected clones were amplified by PCR with the universal oligonucleotide primers M13R and M13F. The obtained products were purified and fixed in duplicate on glass slides specific for use in DNA microarrays. The number of spots on the microarray totaled 6,144 and included 768 positive controls and 624 negative controls per slide. Validation of the platform was performed through hybridization of total DNA probes from XAC labeled with different fluorophores, Cy3 and Cy5. In this validation assay, 86% of all PCR products fixed on the glass slides were confirmed to present a hybridization signal greater than twice the standard deviation of the deviation of the global median signal-to-noise ration. Conclusions Our validation of the XACArray platform using DNA-DNA hybridization revealed that it can be used to evaluate the expression of 2,365 individual CDSs from all major functional categories, which corresponds to 52.7% of the annotated CDSs of the XAC genome. As a proof of concept, we used this platform in a previously work to verify the absence of genomic regions that could not be detected by sequencing in related strains of Xanthomonas.

  5. Preferences for results from genomic microarrays: comparing parents and health care providers.

    Science.gov (United States)

    Turbitt, E; Halliday, J L; Amor, D J; Metcalfe, S A

    2015-01-01

    Chromosomal microarray (CMA) testing is now performed frequently in paediatric care. Although CMAs improve diagnostic yields, they increase detection of variants of unknown and uncertain clinical significance (VUS). Understanding parents', paediatricians' and genetic health professionals' (GHPs) views regarding variant disclosure may reduce the potential for communication of unwanted information. A questionnaire was designed to compare disclosure preferences of these three groups in Australia. One hundred and forty-seven parents, 159 paediatricians and 69 GHPs hold similar views with at least 89% of respondents certainly or probably favouring disclosure of all categories of variants. However, some differences were observed between health care providers (HCPs: paediatricians and GHPs) and parents, who were less sure of their disclosure preferences. There was consensus among respondent groups that knowledge of a variant of certain clinical significance would provide more practical and emotional utility compared to VUS. Compared to HCPs, parents placed more emphasis on using knowledge of a VUS when considering future pregnancies (p exome/genome sequencing is integrated into clinical practice, the potential for differing views of parents and HCPs should be considered when developing guidelines for result disclosure.

  6. Unexpected structural complexity of supernumerary marker chromosomes characterized by microarray comparative genomic hybridization

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    Hing Anne V

    2008-04-01

    Full Text Available Abstract Background Supernumerary marker chromosomes (SMCs are structurally abnormal extra chromosomes that cannot be unambiguously identified by conventional banding techniques. In the past, SMCs have been characterized using a variety of different molecular cytogenetic techniques. Although these techniques can sometimes identify the chromosome of origin of SMCs, they are cumbersome to perform and are not available in many clinical cytogenetic laboratories. Furthermore, they cannot precisely determine the region or breakpoints of the chromosome(s involved. In this study, we describe four patients who possess one or more SMCs (a total of eight SMCs in all four patients that were characterized by microarray comparative genomic hybridization (array CGH. Results In at least one SMC from all four patients, array CGH uncovered unexpected complexity, in the form of complex rearrangements, that could have gone undetected using other molecular cytogenetic techniques. Although array CGH accurately defined the chromosome content of all but two minute SMCs, fluorescence in situ hybridization was necessary to determine the structure of the markers. Conclusion The increasing use of array CGH in clinical cytogenetic laboratories will provide an efficient method for more comprehensive characterization of SMCs. Improved SMC characterization, facilitated by array CGH, will allow for more accurate SMC/phenotype correlation.

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

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    Eils Roland

    2005-11-01

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

  8. The application of phenotypic microarray analysis to anti-fungal drug development.

    Science.gov (United States)

    Greetham, Darren; Lappin, David F; Rajendran, Ranjith; O'Donnell, Lindsay; Sherry, Leighann; Ramage, Gordon; Nile, Christopher

    2017-03-01

    Candida albicans metabolic activity in the presence and absence of acetylcholine was measured using phenotypic microarray analysis. Acetylcholine inhibited C. albicans biofilm formation by slowing metabolism independent of biofilm forming capabilities. Phenotypic microarray analysis can therefore be used for screening compound libraries for novel anti-fungal drugs and measuring antifungal resistance.

  9. Experimental Approaches to Microarray Analysis of Tumor Samples

    Science.gov (United States)

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

    2008-01-01

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

  10. Microarray analysis of Escherichia coli0157:H7

    Institute of Scientific and Technical Information of China (English)

    Hui-Ying Jin; Kai-Hua Tao; Yue-Xi Li; Fa-Qing Li; Su-Qin Li

    2005-01-01

    AIM: To establish the rapid, specific, and sensitive method for detecting O157:H7 with DNA microchips.METHODS: Specific oligonucleotide probes (26-28 nt) of bacterial antigenic and virulent genes of E. coli O157:H7 and other related pathogen genes were pre-synthesized and immobilized on a solid support to make microchips. The four genes encoding O157 somatic antigen (rfbE), H7 fiagellar antigen (fliC) and toxins (SLT1, SLT2) were monitored by multiplex PCR with four pairs of specific primers. Fluorescence-Cy3 labeled samples for hybridization were generated by PCR with Cy3-labeled single prime. Hybridization was performed for 60 min at 45 ℃. Microchip images were taken using a confocal fluorescent scanner.RESULTS: Twelve different bacterial strains were detected with various combinations of four virulent genes. All the O157:H7 strains yielded positive results by multiplex PCR.The size of the PCR products generated with these primers varied from 210 to 678 bp. All the rfbE/fliC/SLT1/SLT2 probes specifically recognized Cy3-labeled fluorescent samples from O157:H7 strains, or strains containing O157 and H7 genes. No cross hybridization of O157:H7 fluorescent samples occurred in other probes. Non-O157:H7 pathogens failed to yield any signal under comparable conditions. If the Cy3-labeled fluorescent product of O157 single PCR was diluted 50-fold, no signal was found in agarose gel electrophoresis, but a positive signal was found in microarray hybridization.CONCLUSION: Microarray analysis of O157:H7 is a rapid,specific, and efficient method for identification and detection of bacterial pathogens.

  11. Genome-wide peripheral blood leukocyte DNA methylation microarrays identified a single association with inflammatory bowel diseases

    DEFF Research Database (Denmark)

    Harris, R Alan; Nagy-Szakal, Dorottya; Pedersen, Natalia

    2012-01-01

    Crohn's disease (CD) and ulcerative colitis (UC) are common forms of inflammatory bowel disease (IBD). Monozygotic (MZ) twin discordance rates and epidemiologic data implicate that environmental changes and epigenetic factors may play a pathogenic role in IBD. DNA methylation (the methylation...... of cytosines within CpG dinucleotides) is an epigenetic modification, which can respond to environmental influences. We investigated whether DNA methylation might be connected with IBD in peripheral blood leukocyte (PBL) DNA by utilizing genome-wide microarrays....

  12. Genome and Phenotype Microarray Analyses of Rhodococcus sp. BCP1 and Rhodococcus opacus R7: Genetic Determinants and Metabolic Abilities with Environmental Relevance.

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    Alessandro Orro

    Full Text Available In this paper comparative genome and phenotype microarray analyses of Rhodococcus sp. BCP1 and Rhodococcus opacus R7 were performed. Rhodococcus sp. BCP1 was selected for its ability to grow on short-chain n-alkanes and R. opacus R7 was isolated for its ability to grow on naphthalene and on o-xylene. Results of genome comparison, including BCP1, R7, along with other Rhodococcus reference strains, showed that at least 30% of the genome of each strain presented unique sequences and only 50% of the predicted proteome was shared. To associate genomic features with metabolic capabilities of BCP1 and R7 strains, hundreds of different growth conditions were tested through Phenotype Microarray, by using Biolog plates and plates manually prepared with additional xenobiotic compounds. Around one-third of the surveyed carbon sources was utilized by both strains although R7 generally showed higher metabolic activity values compared to BCP1. Moreover, R7 showed broader range of nitrogen and sulphur sources. Phenotype Microarray data were combined with genomic analysis to genetically support the metabolic features of the two strains. The genome analysis allowed to identify some gene clusters involved in the metabolism of the main tested xenobiotic compounds. Results show that R7 contains multiple genes for the degradation of a large set of aromatic and PAHs compounds, while a lower variability in terms of genes predicted to be involved in aromatic degradation was found in BCP1. This genetic feature can be related to the strong genetic pressure exerted by the two different environment from which the two strains were isolated. According to this, in the BCP1 genome the smo gene cluster involved in the short-chain n-alkanes degradation, is included in one of the unique regions and it is not conserved in the Rhodococcus strains compared in this work. Data obtained underline the great potential of these two Rhodococcus spp. strains for biodegradation and

  13. Application of microarray analysis on computer cluster and cloud platforms.

    Science.gov (United States)

    Bernau, C; Boulesteix, A-L; Knaus, J

    2013-01-01

    Analysis of recent high-dimensional biological data tends to be computationally intensive as many common approaches such as resampling or permutation tests require the basic statistical analysis to be repeated many times. A crucial advantage of these methods is that they can be easily parallelized due to the computational independence of the resampling or permutation iterations, which has induced many statistics departments to establish their own computer clusters. An alternative is to rent computing resources in the cloud, e.g. at Amazon Web Services. In this article we analyze whether a selection of statistical projects, recently implemented at our department, can be efficiently realized on these cloud resources. Moreover, we illustrate an opportunity to combine computer cluster and cloud resources. In order to compare the efficiency of computer cluster and cloud implementations and their respective parallelizations we use microarray analysis procedures and compare their runtimes on the different platforms. Amazon Web Services provide various instance types which meet the particular needs of the different statistical projects we analyzed in this paper. Moreover, the network capacity is sufficient and the parallelization is comparable in efficiency to standard computer cluster implementations. Our results suggest that many statistical projects can be efficiently realized on cloud resources. It is important to mention, however, that workflows can change substantially as a result of a shift from computer cluster to cloud computing.

  14. Characterization of probiotic Escherichia coli isolates with a novel pan-genome microarray

    DEFF Research Database (Denmark)

    Willenbrock, Hanni; Hallin, Peter Fischer; Wassenaar, Trudy

    2007-01-01

    Background: Microarrays have recently emerged as a novel procedure to evaluate the genetic content of bacterial species. So far, microarrays have mostly covered single or few strains from the same species. However, with cheaper high-throughput sequencing techniques emerging, multiple strains of t...

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

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    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.

  16. ParaSAM: a parallelized version of the significance analysis of microarrays algorithm.

    Science.gov (United States)

    Sharma, Ashok; Zhao, Jieping; Podolsky, Robert; McIndoe, Richard A

    2010-06-01

    Significance analysis of microarrays (SAM) is a widely used permutation-based approach to identifying differentially expressed genes in microarray datasets. While SAM is freely available as an Excel plug-in and as an R-package, analyses are often limited for large datasets due to very high memory requirements. We have developed a parallelized version of the SAM algorithm called ParaSAM to overcome the memory limitations. This high performance multithreaded application provides the scientific community with an easy and manageable client-server Windows application with graphical user interface and does not require programming experience to run. The parallel nature of the application comes from the use of web services to perform the permutations. Our results indicate that ParaSAM is not only faster than the serial version, but also can analyze extremely large datasets that cannot be performed using existing implementations. A web version open to the public is available at http://bioanalysis.genomics.mcg.edu/parasam. For local installations, both the windows and web implementations of ParaSAM are available for free at http://www.amdcc.org/bioinformatics/software/parasam.aspx.

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

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    E. V. Thomas

    2009-01-01

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

  18. Age-Specific Gene Expression Profiles of Rhesus Monkey Ovaries Detected by Microarray Analysis

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    Hengxi Wei

    2015-01-01

    Full Text Available The biological function of human ovaries declines with age. To identify the potential molecular changes in ovarian aging, we performed genome-wide gene expression analysis by microarray of ovaries from young, middle-aged, and old rhesus monkeys. Microarray data was validated by quantitative real-time PCR. Results showed that a total of 503 (60 upregulated, 443 downregulated and 84 (downregulated genes were differentially expressed in old ovaries compared to young and middle-aged groups, respectively. No difference in gene expression was found between middle-aged and young groups. Differentially expressed genes were mainly enriched in cell and organelle, cellular and physiological process, binding, and catalytic activity. These genes were primarily associated with KEGG pathways of cell cycle, DNA replication and repair, oocyte meiosis and maturation, MAPK, TGF-beta, and p53 signaling pathway. Genes upregulated were involved in aging, defense response, oxidation reduction, and negative regulation of cellular process; genes downregulated have functions in reproduction, cell cycle, DNA and RNA process, macromolecular complex assembly, and positive regulation of macromolecule metabolic process. These findings show that monkey ovary undergoes substantial change in global transcription with age. Gene expression profiles are useful in understanding the mechanisms underlying ovarian aging and age-associated infertility in primates.

  19. Analysing breast cancer microarrays from African Americans using shrinkage-based discriminant analysis

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    Pang Herbert

    2010-10-01

    Full Text Available Abstract Breast cancer tumours among African Americans are usually more aggressive than those found in Caucasian populations. African-American patients with breast cancer also have higher mortality rates than Caucasian women. A better understanding of the disease aetiology of these breast cancers can help to improve and develop new methods for cancer prevention, diagnosis and treatment. The main goal of this project was to identify genes that help differentiate between oestrogen receptor-positive and -negative samples among a small group of African-American patients with breast cancer. Breast cancer microarrays from one of the largest genomic consortiums were analysed using 13 African-American and 201 Caucasian samples with oestrogen receptor status. We used a shrinkage-based classification method to identify genes that were informative in discriminating between oestrogen receptor-positive and -negative samples. Subset analysis and permutation were performed to obtain a set of genes unique to the African-American population. We identified a set of 156 probe sets, which gave a misclassification rate of 0.16 in distinguishing between oestrogen receptor-positive and -negative patients. The biological relevance of our findings was explored through literature-mining techniques and pathway mapping. An independent dataset was used to validate our findings and we found that the top ten genes mapped onto this dataset gave a misclassification rate of 0.15. The described method allows us best to utilise the information available from small sample size microarray data in the context of ethnic minorities.

  20. A Latent Variable Approach for Meta-Analysis of Gene Expression Data from Multiple Microarray Experiments

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    Chinnaiyan Arul M

    2007-09-01

    Full Text Available Abstract Background With the explosion in data generated using microarray technology by different investigators working on similar experiments, it is of interest to combine results across multiple studies. Results In this article, we describe a general probabilistic framework for combining high-throughput genomic data from several related microarray experiments using mixture models. A key feature of the model is the use of latent variables that represent quantities that can be combined across diverse platforms. We consider two methods for estimation of an index termed the probability of expression (POE. The first, reported in previous work by the authors, involves Markov Chain Monte Carlo (MCMC techniques. The second method is a faster algorithm based on the expectation-maximization (EM algorithm. The methods are illustrated with application to a meta-analysis of datasets for metastatic cancer. Conclusion The statistical methods described in the paper are available as an R package, metaArray 1.8.1, which is at Bioconductor, whose URL is http://www.bioconductor.org/.

  1. Microarray comparative genomic hybridization detection of chromosomal imbalances in uterine cervix carcinoma

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    García José

    2005-07-01

    Full Text Available Abstract Background Chromosomal Comparative Genomic Hybridization (CGH has been applied to all stages of cervical carcinoma progression, defining a specific pattern of chromosomal imbalances in this tumor. However, given its limited spatial resolution, chromosomal CGH has offered only general information regarding the possible genetic targets of DNA copy number changes. Methods In order to further define specific DNA copy number changes in cervical cancer, we analyzed 20 cervical samples (3 pre-malignant lesions, 10 invasive tumors, and 7 cell lines, using the GenoSensor microarray CGH system to define particular genetic targets that suffer copy number changes. Results The most common DNA gains detected by array CGH in the invasive samples were located at the RBP1-RBP2 (3q21-q22 genes, the sub-telomeric clone C84C11/T3 (5ptel, D5S23 (5p15.2 and the DAB2 gene (5p13 in 58.8% of the samples. The most common losses were found at the FHIT gene (3p14.2 in 47% of the samples, followed by deletions at D8S504 (8p23.3, CTDP1-SHGC- 145820 (18qtel, KIT (4q11-q12, D1S427-FAF1 (1p32.3, D9S325 (9qtel, EIF4E (eukaryotic translation initiation factor 4E, 4q24, RB1 (13q14, and DXS7132 (Xq12 present in 5/17 (29.4% of the samples. Conclusion Our results confirm the presence of a specific pattern of chromosomal imbalances in cervical carcinoma and define specific targets that are suffering DNA copy number changes in this neoplasm.

  2. Microarray comparative genomic hybridization detection of chromosomal imbalances in uterine cervix carcinoma

    Science.gov (United States)

    Hidalgo, Alfredo; Baudis, Michael; Petersen, Iver; Arreola, Hugo; Piña, Patricia; Vázquez-Ortiz, Guelaguetza; Hernández, Dulce; González, José; Lazos, Minerva; López, Ricardo; Pérez, Carlos; García, José; Vázquez, Karla; Alatorre, Brenda; Salcedo, Mauricio

    2005-01-01

    Background Chromosomal Comparative Genomic Hybridization (CGH) has been applied to all stages of cervical carcinoma progression, defining a specific pattern of chromosomal imbalances in this tumor. However, given its limited spatial resolution, chromosomal CGH has offered only general information regarding the possible genetic targets of DNA copy number changes. Methods In order to further define specific DNA copy number changes in cervical cancer, we analyzed 20 cervical samples (3 pre-malignant lesions, 10 invasive tumors, and 7 cell lines), using the GenoSensor microarray CGH system to define particular genetic targets that suffer copy number changes. Results The most common DNA gains detected by array CGH in the invasive samples were located at the RBP1-RBP2 (3q21-q22) genes, the sub-telomeric clone C84C11/T3 (5ptel), D5S23 (5p15.2) and the DAB2 gene (5p13) in 58.8% of the samples. The most common losses were found at the FHIT gene (3p14.2) in 47% of the samples, followed by deletions at D8S504 (8p23.3), CTDP1-SHGC- 145820 (18qtel), KIT (4q11-q12), D1S427-FAF1 (1p32.3), D9S325 (9qtel), EIF4E (eukaryotic translation initiation factor 4E, 4q24), RB1 (13q14), and DXS7132 (Xq12) present in 5/17 (29.4%) of the samples. Conclusion Our results confirm the presence of a specific pattern of chromosomal imbalances in cervical carcinoma and define specific targets that are suffering DNA copy number changes in this neoplasm. PMID:16004614

  3. Design and analysis of mismatch probes for long oligonucleotide microarrays

    Energy Technology Data Exchange (ETDEWEB)

    Deng, Ye; He, Zhili; Van Nostrand, Joy D.; Zhou, Jizhong

    2008-08-15

    Nonspecific hybridization is currently a major concern with microarray technology. One of most effective approaches to estimating nonspecific hybridizations in oligonucleotide microarrays is the utilization of mismatch probes; however, this approach has not been used for longer oligonucleotide probes. Here, an oligonucleotide microarray was constructed to evaluate and optimize parameters for 50-mer mismatch probe design. A perfect match (PM) and 28 mismatch (MM) probes were designed for each of ten target genes selected from three microorganisms. The microarrays were hybridized with synthesized complementary oligonucleotide targets at different temperatures (e.g., 42, 45 and 50 C). In general, the probes with evenly distributed mismatches were more distinguishable than those with randomly distributed mismatches. MM probes with 3, 4 and 5 mismatched nucleotides were differentiated for 50-mer oligonucleotide probes hybridized at 50, 45 and 42 C, respectively. Based on the experimental data generated from this study, a modified positional dependent nearest neighbor (MPDNN) model was constructed to adjust the thermodynamic parameters of matched and mismatched dimer nucleotides in the microarray environment. The MM probes with four flexible positional mismatches were designed using the newly established MPDNN model and the experimental results demonstrated that the redesigned MM probes could yield more consistent hybridizations. Conclusions: This study provides guidance on the design of MM probes for long oligonucleotides (e.g., 50 mers). The novel MPDNN model has improved the consistency for long MM probes, and this modeling method can potentially be used for the prediction of oligonucleotide microarray hybridizations.

  4. Design and analysis of mismatch probes for long oligonucleotide microarrays

    Energy Technology Data Exchange (ETDEWEB)

    Deng, Ye; He, Zhili; Van Nostrand, Joy D.; Zhou, Jizhong

    2008-08-15

    Nonspecific hybridization is currently a major concern with microarray technology. One of most effective approaches to estimating nonspecific hybridizations in oligonucleotide microarrays is the utilization of mismatch probes; however, this approach has not been used for longer oligonucleotide probes. Here, an oligonucleotide microarray was constructed to evaluate and optimize parameters for 50-mer mismatch probe design. A perfect match (PM) and 28 mismatch (MM) probes were designed for each of ten target genes selected from three microorganisms. The microarrays were hybridized with synthesized complementary oligonucleotide targets at different temperatures (e.g., 42, 45 and 50 C). In general, the probes with evenly distributed mismatches were more distinguishable than those with randomly distributed mismatches. MM probes with 3, 4 and 5 mismatched nucleotides were differentiated for 50-mer oligonucleotide probes hybridized at 50, 45 and 42 C, respectively. Based on the experimental data generated from this study, a modified positional dependent nearest neighbor (MPDNN) model was constructed to adjust the thermodynamic parameters of matched and mismatched dimer nucleotides in the microarray environment. The MM probes with four flexible positional mismatches were designed using the newly established MPDNN model and the experimental results demonstrated that the redesigned MM probes could yield more consistent hybridizations. Conclusions: This study provides guidance on the design of MM probes for long oligonucleotides (e.g., 50 mers). The novel MPDNN model has improved the consistency for long MM probes, and this modeling method can potentially be used for the prediction of oligonucleotide microarray hybridizations.

  5. Improved statistical analysis of budding yeast TAG microarrays revealed by defined spike-in pools.

    Science.gov (United States)

    Peyser, Brian D; Irizarry, Rafael A; Tiffany, Carol W; Chen, Ou; Yuan, Daniel S; Boeke, Jef D; Spencer, Forrest A

    2005-09-15

    Saccharomyces cerevisiae knockout collection TAG microarrays are an emergent platform for rapid, genome-wide functional characterization of yeast genes. TAG arrays report abundance of unique oligonucleotide 'TAG' sequences incorporated into each deletion mutation of the yeast knockout collection, allowing measurement of relative strain representation across experimental conditions for all knockout mutants simultaneously. One application of TAG arrays is to perform genome-wide synthetic lethality screens, known as synthetic lethality analyzed by microarray (SLAM). We designed a fully defined spike-in pool to resemble typical SLAM experiments and performed TAG microarray hybridizations. We describe a method for analyzing two-color array data to efficiently measure the differential knockout strain representation across two experimental conditions, and use the spike-in pool to show that the sensitivity and specificity of this method exceed typical current approaches.

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

    Science.gov (United States)

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

    2016-01-01

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

  7. 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.

  8. Microarray analysis of human epithelial cell responses to bacterial interaction.

    Science.gov (United States)

    Mans, Jeffrey J; Lamont, Richard J; Handfield, Martin

    2006-09-01

    Host-pathogen interactions are inherently complex and dynamic. The recent use of human microarrays has been invaluable to monitor the effects of various bacterial and viral pathogens upon host cell gene expression programs. This methodology has allowed the host response transcriptome of several cell lines to be studied on a global scale. To this point, the great majority of reports have focused on the response of immune cells, including macrophages and dendritic cells. These studies revealed that the immune response to microbial pathogens is tailored to different microbial challenges. Conversely, the paradigm for epithelial cells has--until recently--held that the epithelium mostly served as a relatively passive physical barrier to infection. It is now generally accepted that the epithelial barrier contributes more actively to signaling events in the immune response. In light of this shift, this review will compare transcriptional profiling data from studies that involved host-pathogen interactions occurring with epithelial cells. Experiments that defined both a common core response, as well as pathogen-specific host responses will be discussed. This review will also summarize the contributions that transcriptional profiling analysis has made to our understanding of bacterial physio-pathogensis of infection. This will include a discussion of how host transcriptional responses can be used to infer the function of virulence determinants from bacterial pathogens interacting with epithelial mucosa. In particular, we will expand upon the lessons that have been learned from gastro-intestinal and oral pathogens, as well as from members of the commensal flora.

  9. Carbohydrate microarrays

    DEFF Research Database (Denmark)

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

    2012-01-01

    -based technology has been widely employed for rapid analysis of the glycan binding properties of lectins and antibodies, the quantitative measurements of glycan-protein interactions, detection of cells and pathogens, identification of disease-related anti-glycan antibodies for diagnosis, and fast assessment...... 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.......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...

  10. Chromosomal microarray analysis in a girl with mental retardation and spina bifida.

    Science.gov (United States)

    Ben Abdallah, Inesse; Hannachi, Hanene; Soyah, Najla; Saad, Ali; Elghezal, Hatem

    2011-01-01

    Chromosomal imbalances comprise a major cause of mental retardation, particularly in association with congenital malformations and dysmorphic features. Chromosomal analysis using banded karyotyping is limited by the low resolution of this technique, and cryptic chromosomal rearrangements cannot be detected. We describe a 6-year-old girl with mental retardation, mild growth, congenital malformation, and facial anomalies. Chromosomal analysis with karyotyping produced normal results. Because the phenotype suggested chromosomal abnormality, microarray comparative genomic hybridization was used to search for a possible cryptic anomaly. A subtelomeric chromosomal imbalance, consisting of partial trisomy 2q35 and partial monosomy 3p26, was detected and confirmed using fluorescence in situ hybridization. This rearrangement was inherited from an equilibrated maternal t(2;3) reciprocal translocation. Comparative genomic hybridization array in similar situations is useful in detecting cryptic chromosomal rearrangements, identifying genes contained in deleted or duplicated regions, establishing a precise phenotype-genotype correlation, and offering unambiguous genetic counseling. Copyright © 2011 Elsevier Inc. All rights reserved.

  11. Matching of array CGH and gene expression microarray features for the purpose of integrative genomic analyses

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    van Wieringen Wessel N

    2012-05-01

    Full Text Available Abstract Background An increasing number of genomic studies interrogating more than one molecular level is published. Bioinformatics follows biological practice, and recent years have seen a surge in methodology for the integrative analysis of genomic data. Often such analyses require knowledge of which elements of one platform link to those of another. Although important, many integrative analyses do not or insufficiently detail the matching of the platforms. Results We describe, illustrate and discuss six matching procedures. They are implemented in the R-package sigaR (available from Bioconductor. The principles underlying the presented matching procedures are generic, and can be combined to form new matching approaches or be applied to the matching of other platforms. Illustration of the matching procedures on a variety of data sets reveals how the procedures differ in the use of the available data, and may even lead to different results for individual genes. Conclusions Matching of data from multiple genomics platforms is an important preprocessing step for many integrative bioinformatic analysis, for which we present six generic procedures, both old and new. They have been implemented in the R-package sigaR, available from Bioconductor.

  12. Statistical approaches for the analysis of DNA methylation microarray data.

    Science.gov (United States)

    Siegmund, Kimberly D

    2011-06-01

    Following the rapid development and adoption in DNA methylation microarray assays, we are now experiencing a growth in the number of statistical tools to analyze the resulting large-scale data sets. As is the case for other microarray applications, biases caused by technical issues are of concern. Some of these issues are old (e.g., two-color dye bias and probe- and array-specific effects), while others are new (e.g., fragment length bias and bisulfite conversion efficiency). Here, I highlight characteristics of DNA methylation that suggest standard statistical tools developed for other data types may not be directly suitable. I then describe the microarray technologies most commonly in use, along with the methods used for preprocessing and obtaining a summary measure. I finish with a section describing downstream analyses of the data, focusing on methods that model percentage DNA methylation as the outcome, and methods for integrating DNA methylation with gene expression or genotype data.

  13. Microarray studies of genomic oxidative stress and cell cycle responses in obstructive sleep apnea.

    Science.gov (United States)

    Hoffmann, Michal S; Singh, Prachi; Wolk, Robert; Romero-Corral, Abel; Raghavakaimal, Sreekumar; Somers, Virend K

    2007-06-01

    Obstructive sleep apnea (OSA), the commonest form of sleep-disordered breathing, is characterized by recurrent episodes of intermittent hypoxia and sleep fragmentation. This study evaluated microarray measures of gene transcript levels in OSA subjects compared to age and BMI matched healthy controls. Measurements were obtained before and after: (a) a night of normal sleep in controls; and (b) a night of untreated apnea in OSA patients. All subjects underwent full polysomnography. mRNA from the whole blood samples was analyzed by HG-U133A and B Affymetrix GeneChip arrays using Spotfire 7.2 data analysis platform. After sleep in OSA patients, changes were noted in several genes involved in modulation of reactive oxygen species (ROS), including heme oxygenase 1, superoxide dismutase 1 and 2, and catalase. Changes were also observed in genes involved in cell growth, proliferation, and the cell cycle such as cell division cycle 25B, signaling lymphocyte activating molecule (SLAM), calgizzarin S100A11, B-cell translocation gene, Src-like adapter protein (SLAP), and eukaryotic translation initiation factor 4E binding protein 2. These overnight changes in OSA patients are suggestive of activation of several mechanisms to modulate, and adapt to, increased ROS developing in response to the frequent episodes of intermittent hypoxia.

  14. Prosecutor : parameter-free inference of gene function for prokaryotes using DNA microarray data, genomic context and multiple gene annotation sources

    NARCIS (Netherlands)

    Blom, E.J.; Breitling, R.; Hofstede, K.J.; Roerdink, J.B.T.M.; van Hijum, S.A F T; Kuipers, O.P.

    2008-01-01

    Background: Despite a plethora of functional genomic efforts, the function of many genes in sequenced genomes remains unknown. The increasing amount of microarray data for many species allows employing the guilt-by-association principle to predict function on a large scale: genes exhibiting similar

  15. Microarray analysis of genes affected by salt stress in tomato | Zhou ...

    African Journals Online (AJOL)

    Microarray analysis of genes affected by salt stress in tomato. ... African Journal of Environmental Science and Technology ... key enzyme genes in the metabolic pathways of carbohydrates, amino acids, and fatty acids, were also affected by ...

  16. Genome Array on Differentially Expressed Genes of Skin Tissue in Cashmere Goat at Early Anagen of Cashmere Growth Cycle Using DNA Microarray

    Institute of Scientific and Technical Information of China (English)

    DI Jiang; Marzeya Yasen; XU Xin-ming; Lazate Ainiwaer; ZHANG Yan-hua; TIAN Ke-chuan; YU Li-juan; WU Wei-wei; Hanikezi Tulafu; FU Xue-feng

    2014-01-01

    In order to study the molecular mechanism involved in cashmere regeneration, this study investigated the gene expression proifle of skin tissue at various stages of the cashmere growth cycle and screen differentially expressed genes at proangen in 10 cashmere goats at 2 years of age using agilent sheep oligo microarray. Signiifcance analysis of microarray (SAM) methods was used to identify the differentially expressed genes, Hierarchical clustering was performed to clarify these genes in association with different cashmere growth stages, and GO (Gene ontology) and the pathway analyses were con-ducted by a free web-based Molecular Annotation System3.0 (MAS 3.0). Approximately 10 200 probe sets were detected in skin tissue of 2-yr-old cashmere goat. After SAM analysis of the microarray data, totally 417 genes were shown to be differentially expressed at different cashmere growth stages, and 24 genes are signiifcantly up-regulated (21) or down-regulated (3) at proangen concurrently compared to angen and telogen. Hierarchical clustering analysis clearly distinguished the differentially expressed genes of each stage. GO analysis indicated that these altered genes at proangen were predominantly involved in collagen ifbril organization, integrin-mediated signaling pathway, cell-matrix adhesion, cell adhesion, transforming growth factor-β (TGF-β) receptor signaling pathway, regulation of cell growth. Kyoto encyclopedia of genes and genomes (KEGG) analysis showed that the signiifcant pathways involved mainly included focal adhesion and extracellular matrixc (ECM)-receptor interaction. Some important genes involved in these biological processes, such as COL1A1, COL1A2, COL3A1, SPARC, CYR61 and CTGF, were related to tissue remolding and repairing and detected by more than one probe with similar expression trends at different stages of cashmere growth cycle. The different expression of these genes may contribute to understanding the molecular mechanism of cashmere

  17. Whole Genome Comparison of Campylobacter jejuni Human Isolates Using a Low-Cost Microarray Reveals Extensive Genetic Diversity

    OpenAIRE

    2001-01-01

    Campylobacter jejuni is the leading cause of bacterial food-borne diarrhoeal disease throughout the world, and yet is still a poorly understood pathogen. Whole genome microarray comparisons of 11 C. jejuni strains of diverse origin identified genes in up to 30 NCTC 11168 loci ranging from 0.7 to 18.7 kb that are either absent or highly divergent in these isolates. Many of these regions are associated with the biosynthesis of surface structures including flagella, lipo-oligosaccharide, and the...

  18. Versatile High Throughput Microarray Analysis for Marine Glycobiology

    DEFF Research Database (Denmark)

    Asunción Salmeán, Armando

    to concept proof that is possible to use the Comprehensive Microarray Polymer Profiling (CoMPP) as a tool for other extracellular matrixes such as marine animals and not only for algal or plant cell walls. Thus, we discovered fucoidan and cellulose epitopes in several tissues of various marine animals from...

  19. Quantitative analysis of tumor mitochondrial RNA using microarray

    Institute of Scientific and Technical Information of China (English)

    Cheng-Bo Han; Xiao-Yun Mao; Yan Xin; Shao-Cheng Wang; Jia-Ming Ma; Yu-Jie Zhao

    2005-01-01

    AIM: To design a novel method to rapidly detect the quantitative alteration of mtRNA in patients with tumors.METHODS: Oligo 6.22 and Primer Premier 5.0 bio-soft were used to design 15 pairs of primers of mtRNA cDNA probes in light of the functional and structural property of mtDNA, and then RT-PCR amplification was used to produce 15 probes of mtRNA from one normal gastric mucosal tissue. Total RNA extracted from 9 gastric cancers and corresponding normal gastric mucosal tissues was reverse transcribed into cDNA labeled with fluorescein. The spotted mtDNA microarrays were made and hybridized. Finally,the microarrays were scanned with a GeneTACTM laser scanner to get the hybridized results. Northern blot was used to confirm the microarray results.RESULTS: The hybridized spots were distinct with clear and consistent backgrounds. After data was standardized according to the housekeeping genes, the results showed that the expression levels of some mitochondrial genes in gastric carcinoma were different from those in the corresponding non-cancerous regions.CONCLUSION: The mtDNA expression microarray can rapidly, massively and exactly detect the quantity of mtRNA in tissues and cells. In addition, the whole expressive information of mtRNA from a tumor patient on just one slide can be obtained using this method, providing an effective method to investigate the relationship between mtDNA expression and tumorigenesis.

  20. VIPR: A probabilistic algorithm for analysis of microbial detection microarrays

    Directory of Open Access Journals (Sweden)

    Holbrook Michael R

    2010-07-01

    Full Text Available Abstract Background All infectious disease oriented clinical diagnostic assays in use today focus on detecting the presence of a single, well defined target agent or a set of agents. In recent years, microarray-based diagnostics have been developed that greatly facilitate the highly parallel detection of multiple microbes that may be present in a given clinical specimen. While several algorithms have been described for interpretation of diagnostic microarrays, none of the existing approaches is capable of incorporating training data generated from positive control samples to improve performance. Results To specifically address this issue we have developed a novel interpretive algorithm, VIPR (Viral Identification using a PRobabilistic algorithm, which uses Bayesian inference to capitalize on empirical training data to optimize detection sensitivity. To illustrate this approach, we have focused on the detection of viruses that cause hemorrhagic fever (HF using a custom HF-virus microarray. VIPR was used to analyze 110 empirical microarray hybridizations generated from 33 distinct virus species. An accuracy of 94% was achieved as measured by leave-one-out cross validation. Conclusions VIPR outperformed previously described algorithms for this dataset. The VIPR algorithm has potential to be broadly applicable to clinical diagnostic settings, wherein positive controls are typically readily available for generation of training data.

  1. Microarray and cDNA sequence analysis of transcription during nerve-dependent limb regeneration

    Directory of Open Access Journals (Sweden)

    Bryant Susan V

    2009-01-01

    Full Text Available Abstract Background Microarray analysis and 454 cDNA sequencing were used to investigate a centuries-old problem in regenerative biology: the basis of nerve-dependent limb regeneration in salamanders. Innervated (NR and denervated (DL forelimbs of Mexican axolotls were amputated and transcripts were sampled after 0, 5, and 14 days of regeneration. Results Considerable similarity was observed between NR and DL transcriptional programs at 5 and 14 days post amputation (dpa. Genes with extracellular functions that are critical to wound healing were upregulated while muscle-specific genes were downregulated. Thus, many processes that are regulated during early limb regeneration do not depend upon nerve-derived factors. The majority of the transcriptional differences between NR and DL limbs were correlated with blastema formation; cell numbers increased in NR limbs after 5 dpa and this yielded distinct transcriptional signatures of cell proliferation in NR limbs at 14 dpa. These transcriptional signatures were not observed in DL limbs. Instead, gene expression changes within DL limbs suggest more diverse and protracted wound-healing responses. 454 cDNA sequencing complemented the microarray analysis by providing deeper sampling of transcriptional programs and associated biological processes. Assembly of new 454 cDNA sequences with existing expressed sequence tag (EST contigs from the Ambystoma EST database more than doubled (3935 to 9411 the number of non-redundant human-A. mexicanum orthologous sequences. Conclusion Many new candidate gene sequences were discovered for the first time and these will greatly enable future studies of wound healing, epigenetics, genome stability, and nerve-dependent blastema formation and outgrowth using the axolotl model.

  2. A web-based platform for rice microarray annotation and data analysis

    Institute of Scientific and Technical Information of China (English)

    2010-01-01

    Rice(Oryza sativa) feeds over half of the global population.A web-based integrated platform for rice microarray annotation and data analysis in various biological contexts is presented,which provides a convenient query for comprehensive annotation compared with similar databases.Coupled with existing rice microarray data,it provides online analysis methods from the perspective of bioinformatics.This comprehensive bioinformatics analysis platform is composed of five modules,including data retrieval,microarray annotation,sequence analysis,results visualization and data analysis.The BioChip module facilitates the retrieval of microarray data information via identifiers of "Probe Set ID","Locus ID" and "Analysis Name".The BioAnno module is used to annotate the gene or probe set based on the gene function,the domain information,the KEGG biochemical and regulatory pathways and the potential microRNA which regulates the genes.The BioSeq module lists all of the related sequence information by a microarray probe set.The BioView module provides various visual results for the microarray data.The BioAnaly module is used to analyze the rice microarray’s data set.

  3. Multiplexed, rapid detection of H5N1 using a PCR-free nanoparticle-based genomic microarray assay

    Directory of Open Access Journals (Sweden)

    Ragupathy Viswanath

    2010-10-01

    Full Text Available Abstract Background For more than a decade there has been increasing interest in the use of nanotechnology and microarray platforms for diagnostic applications. In this report, we describe a rapid and simple gold nanoparticle (NP-based genomic microarray assay for specific identification of avian influenza virus H5N1 and its discrimination from other major influenza A virus strains (H1N1, H3N2. Results Capture and intermediate oligonucleotides were designed based on the consensus sequences of the matrix (M gene of H1N1, H3N2 and H5N1 viruses, and sequences specific for the hemaglutinin (HA and neuraminidase (NA genes of the H5N1 virus. Viral RNA was detected within 2.5 hours using capture-target-intermediate oligonucleotide hybridization and gold NP-mediated silver staining in the absence of RNA fragmentation, target amplification, and enzymatic reactions. The lower limit of detection (LOD of the assay was less than 100 fM for purified PCR fragments and 103 TCID50 units for H5N1 viral RNA. Conclusions The NP-based microarray assay was able to detect and distinguish H5N1 sequences from those of major influenza A viruses (H1N1, H3N2. The new method described here may be useful for simultaneous detection and subtyping of major influenza A viruses.

  4. Cancer immunotherapy using novel tumor-associated antigenic peptides identified by genome-wide cDNA microarray analyses.

    Science.gov (United States)

    Nishimura, Yasuharu; Tomita, Yusuke; Yuno, Akira; Yoshitake, Yoshihiro; Shinohara, Masanori

    2015-05-01

    Recent genome-wide cDNA microarray analysis of gene expression profiles in comprehensive tumor types coupled with isolation of cancer tissues by laser-microbeam microdissection have revealed ideal tumor-associated antigens (TAAs) that are frequently overexpressed in various cancers including head and neck squamous cell cancer (HNSCC) and lung cancer, but not in most normal tissues except for testis, placenta, and fetal organs. Preclinical studies using HLA-transgenic mice and human T cells in vitro showed that TAA-derived CTL-epitope short peptides (SPs) are highly immunogenic and induce HLA-A2 or -A24-restricted CTLs. Based on the accumulated evidence, we carried out a phase II clinical trial of the TAA-SP vaccine in advanced 37 HNSCC patients. This study showed a significant induction of TAA-specific CTLs in the majority of patients without serious adverse effects. Importantly, clinical responses including a complete response were observed in this study. Another phase II clinical trial of therapeutic TAA-SP vaccine, designed to evaluate the ability of prevention of recurrence, is ongoing in HNSCC patients who have received curative operations. Further studies in human preclinical studies and in vivo studies using HLA class I transgenic mice showed TAA-derived long peptides (TAA-LPs) have the capacity to induce not only promiscuous HLA class II-restricted CD4(+) T helper type 1 cells but also tumor-specific CTLs through a cross-presentation mechanism. Moreover, we observed an augmentation of TAA-LP-specific T helper type 1 cell responses and tumor antigen-spreading in HNSCC patients vaccinated with TAA-SPs. This accumulated evidence suggests that therapeutic TAA-SPs and LPs vaccines may provide a promising cancer immunotherapy.

  5. Carbon ion irradiation of the human prostate cancer cell line PC3: a whole genome microarray study.

    Science.gov (United States)

    Suetens, Annelies; Moreels, Marjan; Quintens, Roel; Chiriotti, Sabina; Tabury, Kevin; Michaux, Arlette; Grégoire, Vincent; Baatout, Sarah

    2014-04-01

    Hadrontherapy is a form of external radiation therapy, which uses beams of charged particles such as carbon ions. Compared to conventional radiotherapy with photons, the main advantage of carbon ion therapy is the precise dose localization along with an increased biological effectiveness. The first results obtained from prostate cancer patients treated with carbon ion therapy showed good local tumor control and survival rates. In view of this advanced treatment modality we investigated the effects of irradiation with different beam qualities on gene expression changes in the PC3 prostate adenocarcinoma cell line. For this purpose, PC3 cells were irradiated with various doses (0.0, 0.5 and 2.0 Gy) of carbon ions (LET=33.7 keV/µm) at the beam of the Grand Accélérateur National d'Ions Lourds (Caen, France). Comparative experiments with X-rays were performed at the Belgian Nuclear Research Centre. Genome-wide gene expression was analyzed using microarrays. Our results show a downregulation in many genes involved in cell cycle and cell organization processes after 2.0 Gy irradiation. This effect was more pronounced after carbon ion irradiation compared with X-rays. Furthermore, we found a significant downregulation of many genes related to cell motility. Several of these changes were confirmed using qPCR. In addition, recurrence-free survival analysis of prostate cancer patients based on one of these motility genes (FN1) revealed that patients with low expression levels had a prolonged recurrence-free survival time, indicating that this gene may be a potential prognostic biomarker for prostate cancer. Understanding how different radiation qualities affect the cellular behavior of prostate cancer cells is important to improve the clinical outcome of cancer radiation therapy.

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

    Directory of Open Access Journals (Sweden)

    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

  7. Biolog phenotype microarrays.

    Science.gov (United States)

    Shea, April; Wolcott, Mark; Daefler, Simon; Rozak, David A

    2012-01-01

    Phenotype microarrays nicely complement traditional genomic, transcriptomic, and proteomic analysis by offering opportunities for researchers to ground microbial systems analysis and modeling in a broad yet quantitative assessment of the organism's physiological response to different metabolites and environments. Biolog phenotype assays achieve this by coupling tetrazolium dyes with minimally defined nutrients to measure the impact of hundreds of carbon, nitrogen, phosphorous, and sulfur sources on redox reactions that result from compound-induced effects on the electron transport chain. Over the years, we have used Biolog's reproducible and highly sensitive assays to distinguish closely related bacterial isolates, to understand their metabolic differences, and to model their metabolic behavior using flux balance analysis. This chapter describes Biolog phenotype microarray system components, reagents, and methods, particularly as they apply to bacterial identification, characterization, and metabolic analysis.

  8. Putative psychosis genes in the prefrontal cortex: combined analysis of gene expression microarrays

    Directory of Open Access Journals (Sweden)

    Yolken Robert H

    2008-11-01

    Full Text Available Abstract Background Recent studies have shown similarities between schizophrenia and bipolar disorder in phenotypes and in genotypes, and those studies have contributed to an ongoing re-evaluation of the traditional dichotomy between schizophrenia and bipolar disorder. Bipolar disorder with psychotic features may be closely related to schizophrenia and therefore, psychosis may be an alternative phenotype compared to the traditional diagnosis categories. Methods We performed a cross-study analysis of 7 gene expression microarrays that include both psychosis and non-psychosis subjects. These studies include over 400 microarray samples (163 individual subjects on 3 different Affymetrix microarray platforms. Results We found that 110 transcripts are differentially regulated (p Conclusion This study demonstrates the advantages of cross-study analysis in detecting consensus changes in gene expression across multiple microarray studies. Differential gene expression between individuals with and without psychosis suggests that psychosis may be a useful phenotypic variable to complement the traditional diagnosis categories.

  9. Filtering for increased power for microarray data analysis

    Directory of Open Access Journals (Sweden)

    Hess Ann M

    2009-01-01

    Full Text Available Abstract Background Due to the large number of hypothesis tests performed during the process of routine analysis of microarray data, a multiple testing adjustment is certainly warranted. However, when the number of tests is very large and the proportion of differentially expressed genes is relatively low, the use of a multiple testing adjustment can result in very low power to detect those genes which are truly differentially expressed. Filtering allows for a reduction in the number of tests and a corresponding increase in power. Common filtering methods include filtering by variance, average signal or MAS detection call (for Affymetrix arrays. We study the effects of filtering in combination with the Benjamini-Hochberg method for false discovery rate control and q-value for false discovery rate estimation. Results Three case studies are used to compare three different filtering methods in combination with the two false discovery rate methods and three different preprocessing methods. For the case studies considered, filtering by detection call and variance (on the original scale consistently led to an increase in the number of differentially expressed genes identified. On the other hand, filtering by variance on the log2 scale had a detrimental effect when paired with MAS5 or PLIER preprocessing methods, even when the testing was done on the log2 scale. A simulation study was done to further examine the effect of filtering by variance. We find that filtering by variance leads to higher power, often with a decrease in false discovery rate, when paired with either of the false discovery rate methods considered. This holds regardless of the proportion of genes which are differentially expressed or whether we assume dependence or independence among genes. Conclusion The case studies show that both detection call and variance filtering are viable methods of filtering which can increase the number of differentially expressed genes identified. The

  10. Direct Mutagenesis of Thousands of Genomic Targets using Microarray-derived Oligonucleotides

    DEFF Research Database (Denmark)

    Bonde, Mads; Kosuri, Sriram; Genee, Hans Jasper

    2015-01-01

    operons in E. coli using this method, which we call Microarray-Oligonucleotide (MO)-MAGE. The resulting mutant library was characterized by high-throughput sequencing to show that all attempted insertions were estimated to have occurred at an average frequency of 0.02 % per loci with 0.4 average...

  11. Microarray-based Comparative Genomic Indexing of the Cronobacter genus (Enterobacter sakazakii)

    Science.gov (United States)

    Cronobacter is a recently defined genus synonymous with Enterobacter sakazakii. This new genus currently comprises 6 genomospecies. To extend our understanding of the genetic relationship between Cronobacter sakazakii BAA-894 and the other species of this genus, microarray-based comparative genomi...

  12. Global microarray analysis of carbohydrate use in alkaliphilic hemicellulolytic bacterium Bacillus sp. N16-5.

    Directory of Open Access Journals (Sweden)

    Yajian Song

    Full Text Available The alkaliphilic hemicellulolytic bacterium Bacillus sp. N16-5 has a broad substrate spectrum and exhibits the capacity to utilize complex carbohydrates such as galactomannan, xylan, and pectin. In the monosaccharide mixture, sequential utilization by Bacillus sp. N16-5 was observed. Glucose appeared to be its preferential monosaccharide, followed by fructose, mannose, arabinose, xylose, and galactose. Global transcription profiles of the strain were determined separately for growth on six monosaccharides (glucose, fructose, mannose, galactose, arabinose, and xylose and four polysaccharides (galactomannan, xylan, pectin, and sodium carboxymethylcellulose using one-color microarrays. Numerous genes potentially related to polysaccharide degradation, sugar transport, and monosaccharide metabolism were found to respond to a specific substrate. Putative gene clusters for different carbohydrates were identified according to transcriptional patterns and genome annotation. Identification and analysis of these gene clusters contributed to pathway reconstruction for carbohydrate utilization in Bacillus sp. N16-5. Several genes encoding putative sugar transporters were highly expressed during growth on specific sugars, suggesting their functional roles. Two phosphoenolpyruvate-dependent phosphotransferase systems were identified as candidate transporters for mannose and fructose, and a major facilitator superfamily transporter was identified as a candidate transporter for arabinose and xylose. Five carbohydrate uptake transporter 1 family ATP-binding cassette transporters were predicted to participate in the uptake of hemicellulose and pectin degradation products. Collectively, microarray data improved the pathway reconstruction involved in carbohydrate utilization of Bacillus sp. N16-5 and revealed that the organism precisely regulates gene transcription in response to fluctuations in energy resources.

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

    Directory of Open Access Journals (Sweden)

    Aitman T

    2008-11-01

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

  14. Microarray expression analysis of epithelial ovarian cancer with distinct differentiation

    Institute of Scientific and Technical Information of China (English)

    2007-01-01

    To identify gene expression profiling in epithelial ovarian cancer and to explore its correlation with histopathology characterization and prognosis. Gene expression profiles were generated from 10 human ovarian frozen tissue specimens using Agilent Human 1A microarrays. Strikingly, clear differences of gene expression patterns were observed in ovarian cancer as compared to normal tissues. Unique gene profiles were observed in moderately and poorly differentiated epithelial ovarian cancer. It is concluded that different histopathology characterization likely exists extensive molecular heterogeneity.

  15. Self-assembled random arrays: high-performance imaging and genomics applications on a high-density microarray platform

    Science.gov (United States)

    Barker, David L.; Theriault, Greg; Che, Diping; Dickinson, Todd; Shen, Richard; Kain, Robert C.

    2003-07-01

    Illumina is developing a BeadArrayTM technology that supports SNP genotyping, mRNA expression analysis and protein expression analysis on the same platform. We use fiber-optic bundles with a density of approximately 40,000 fibers/mm2. At hte end of each fiber, a derivatized silica bead forms an array element for reading out a genotyping or expression assay data point. Each bead contains oligonucleotide probes that hybridize with high specificity to complementary sequences in a complex nucleic acid mixture. We derivatize the beads in bulk, pool them to form a quality-controlled source of microarray elements, and allow them to assemble spontaneously into pits etched into the end of each optical fiber bundle. We load our fiber bundles, containing 49,777 fibers, with up to 1520 different bead types. The presence of many beads of each type greatly improves the accuracy of each assay. As the final step in our manufacturing process, we decode the identity of each bead by a series of rapid hybridizations with fluroescent oligos. Decoding accuracy and the number of beads of each type is recorded for each array. Decoding also serves as a quality control procedure for the performance of each element in the array. To facilitate high-throughput analysis of many samples, the fiber bundles are arranged in an array matrix (SentrixTM arrays). Using a 96-bundle array matrix, up to 1520 assays can be performed on each of 96 samples simultaneously for a total of 145,920 assays. Using a 384-bundle array matrix, up to 583,680 assays can be performed simultaneously. The BeadArray platform is the highest density microarray in commercial use, requiring development of a high-performance array scanner. To meet this need, we developed the SherlockTM system, a laser-scanning confocal imaging system that automatically scans all 96 bundles of an array matrix at variable resolution down to 0.8 micron. The system scans with both 532 and 635 nm lasers simultaneously, collecting two fluorescence

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

    Energy Technology Data Exchange (ETDEWEB)

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

    2007-08-15

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

  17. Identification of candidate genes for congenital splay leg in piglets by alternative analysis of DNA microarray data

    Directory of Open Access Journals (Sweden)

    Steffen Maak, Diana Boettcher, Jens Tetens, Monika Wensch-Dorendorf, Gerd Nürnberg, Klaus Wimmers, Hermann H. Swalve, Georg Thaller

    2009-01-01

    Full Text Available The congenital splay leg syndrome in piglets is characterized by a temporarily impaired functionality of the hind leg muscles immediately after birth. Etiology and pathogenetic mechanisms for the disease are still not well understood. We compared genome wide gene expression of three hind leg muscles (M. adductores, M. gracilis and M. sartorius between affected piglets and their healthy littermates with the GeneChip® Porcine Genome Array (Affymetrix in order to identify candidate genes for the disease. Data analysis with standard algorithms revealed no significant differences between both groups. By application of an alternative approach, we identified 63 transcripts with differences in two muscles and 5 genes differing between the groups in three muscles. The expression of six selected genes (SQSTM1, SSRP1, DDIT4, ENAH, MAF, and PDK4 was investigated with SYBRGreen RT - Real time PCR. The differences obtained with the microarray analysis could be confirmed and demonstrate the validity of the alternative approach to microarray data analysis. Four genes with different expression levels in at least two muscles (SQSTM1, SSRP1, DDIT4, and MAF are assigned to transcriptional cascades related to cell death and may thus indicate pathways for further investigations on congenital splay leg in piglets.

  18. Overview of Microarray Analysis of Gene Expression and its Applications to Cervical Cancer Investigation

    Directory of Open Access Journals (Sweden)

    Angel Chao

    2007-12-01

    Full Text Available Cervical cancer is one of the leading female cancers in Taiwan and ranks as the fifth cause of cancer death in the female population. Human papillomavirus has been established as the causative agent for cervical neoplasia and cervical cancer. However, the tumor biology involved in the prognoses of different cell types in early cancers and tumor responses to radiation in advanced cancers remain largely unknown. The introduction of microarray technologies in the 1990s has provided genome-wide strategies for searching tens of thousands of genes simultaneously. In this review, we first summarize the two types of microarrays: oligonucleotides microarray and cDNA microarray. Then, we review the studies of functional genomics in cervical cancer. Gene expression studies that involved cervical cancer cell lines, cervical cells of cancer versus normal ectocervix, cancer tissues of different histology, radioresistant versus radiosensitive patients, and the combinatorial gene expression associated with chromosomal amplifications are discussed. In particular, CEACAM5, TACSTD1, S100P, and MSLN have shown to be upregulated in adenocarcinoma, and increased expression levels of CEACAM5 and TACSTD1 were significantly correlated with poorer patient outcomes. On the other hand, 35 genes, including apoptotic genes (e.g. BIK, TEGT, SSI-3, hypoxia-inducible genes (e.g. HIF1A, CA12, and tumor cell invasion and metastasis genes (e.g. CTSL, CTSB, PLAU, CD44, have been noted to echo the hypothesis that increased tumor hypoxia leads to radiation resistance in cervical cancer during radiation.

  19. Analysis of gene expression in resynthesized Brassica napus Allopolyploids using arabidopsis 70mer oligo microarrays.

    Directory of Open Access Journals (Sweden)

    Robert T Gaeta

    . Furthermore, our microarray analysis did not provide strong evidence that homoeologous rearrangements were a determinant of genome-wide nonadditive gene expression. In light of the inherent limitations of the Arabidopsis microarray to measure gene expression in polyploid Brassicas, further studies are warranted.

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

    Directory of Open Access Journals (Sweden)

    Joseph Andrews

    Full Text Available BACKGROUND: 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. METHODOLOGY/PRINCIPAL FINDINGS: 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. CONCLUSIONS/SIGNIFICANCE: Our approach allows more precisely profiling of functionally relevant epigenetic signatures that are associated with cancer

  1. Application of whole-genome and high-resolution chromosome microarray analysis for the investigation of fetuses with ultrasound abnormalities%全基因组高分辨率染色体微阵列分析在超声结构异常胎儿中的应用

    Institute of Scientific and Technical Information of China (English)

    张燕; 符芳; 李茹; 谢闺娥; 韩瑾; 潘敏; 甄理; 杨昕; 李东至

    2015-01-01

    Objective To assess the value of whole-genome high-resolution chromosome microarray analysis (CMA) for the investigation of fetuses with ultrasound abnormalities.Methods Whole genome high-resolution CytoScanHD array from Affymetrix was employed to investigate 651 fetuses with structural abnormalities detected by ultrasound,for whom standard G-banded chromosome analysis has revealed a normal karyotype.The fetuses were divided into a single malformation group (n=264) and a multiple malformations group (n=387).In total there were 130 chorionic villus samples,192 amniotic fluid samples and 329 cord blood samples.Extraction of fetal DNA and CMA experiment have followed the standard guidelines from the manufacturers.All copy number variations (CNVs) detected by CMA were confirmed by fluorescence in situ hybridization (FISH) or real-time polymerase chain reaction (RT-PCR).Results CMA analysis has detected genomic CNVs in 475 (73%) cases.Clinically significant CNVs were found in 11.5% (75/651) of fetuses,including two uniparental disomies (UPD) and two cryptic mosaicisms.Variations of unknown significance (VOUS) was found in 2.0% (13/651) of tested fetuses.Conclusion Above results have suggested that whole-genome and high-resolution CMA is valuable for the analysis of fetuses with structural abnormalities detected by ultrasound,which can increase the detection rate by approximately 11 %.CMA using single nucleotide polymorphism (SNP) array has the ability to detect UPD and low-level mosaicisms.Sufficient communication between technicians and genetic counselors,parental testing and comparison the results with in-house and relevant online databases can significantly reduce the rate of VOUS.%目的 探讨全基因组高分辨率染色体微阵列分析(chromosome microarray analysis,CMA)技术在先天性结构异常胎儿中的应用价值.方法 应用美国Affymetrix公司全基因组高分辨率CytoScanHD芯片对651例孕期超声检查提示先天性结构发育

  2. Prosecutor: parameter-free inference of gene function for prokaryotes using DNA microarray data, genomic context and multiple gene annotation sources

    Directory of Open Access Journals (Sweden)

    van Hijum Sacha AFT

    2008-10-01

    Full Text Available Abstract Background Despite a plethora of functional genomic efforts, the function of many genes in sequenced genomes remains unknown. The increasing amount of microarray data for many species allows employing the guilt-by-association principle to predict function on a large scale: genes exhibiting similar expression patterns are more likely to participate in shared biological processes. Results We developed Prosecutor, an application that enables researchers to rapidly infer gene function based on available gene expression data and functional annotations. Our parameter-free functional prediction method uses a sensitive algorithm to achieve a high association rate of linking genes with unknown function to annotated genes. Furthermore, Prosecutor utilizes additional biological information such as genomic context and known regulatory mechanisms that are specific for prokaryotes. We analyzed publicly available transcriptome data sets and used literature sources to validate putative functions suggested by Prosecutor. We supply the complete results of our analysis for 11 prokaryotic organisms on a dedicated website. Conclusion The Prosecutor software and supplementary datasets available at http://www.prosecutor.nl allow researchers working on any of the analyzed organisms to quickly identify the putative functions of their genes of interest. A de novo analysis allows new organisms to be studied.

  3. Hybridization kinetics analysis of an oligonucleotide microarray for microRNA detection

    Institute of Scientific and Technical Information of China (English)

    Botao Zhao; Shuo Ding; Wei Li; Youxin Jin

    2011-01-01

    MicroRNA (miRNA) microarrays have been successfully used for profiling miRNA expression in many physiological processes such as development, differentiation, oncogenesis,and other disease processes. Detecting miRNA by miRNA microarray is actually based on nucleic acid hybridization between target molecules and their corresponding complementary probes. Due to the small size and high degree of similarity among miRNA sequences, the hybridization condition must be carefully optimized to get specific and reliable signals. Previously, we reported a microarray platform to detect miRNA expression. In this study, we evaluated the sensitivity and specificity of our microarray platform. After systematic analysis, we determined an optimized hybridization condition with high sensitivity and specificity for miRNA detection. Our results would be helpful for other hybridization-based miRNA detection methods, such as northern blot and nuclease protection assay.

  4. Microarray and Proteomic Analysis of Brassinosteroid- and Gibberellin-Regulated Gene and Protein Expression in Rice

    Institute of Scientific and Technical Information of China (English)

    Guangxiao Yang; Setsuko Komatsu

    2004-01-01

    Brassinosteroid (BR) and gibberellin (GA) are two groups of plant growth regulators essential for normal plant growth and development. To gain insight into the molecular mechanism by which BR and GA regulate the growth and development of plants, especially the monocot plant rice, it is necessary to identify and analyze more genes and proteins that are regulated by them. With the availability of draft sequences of two major types, japonica and indica rice, it has become possible to analyze expression changes of genes and proteins at genome scale. In this review, we summarize rice functional genomic research by using microarray and proteomic approaches and our recent research results focusing on the comparison of cDNA microarray and proteomic analyses of BR- and GA-regulated gene and protein expression in rice. We believe our findings have important implications for understanding the mechanism by which BR and GA regulate the growth and development of rice.

  5. 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.

  6. 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.

  7. Microarray analysis reveals the actual specificity of enrichment media used for food safety assessment.

    Science.gov (United States)

    Kostić, Tanja; Stessl, Beatrix; Wagner, Martin; Sessitsch, Angela

    2011-06-01

    Microbial diagnostic microarrays are tools for simultaneous detection and identification of microorganisms in food, clinical, and environmental samples. In comparison to classic methods, microarray-based systems have the potential for high throughput, parallelism, and miniaturization. High specificity and high sensitivity of detection have been demonstrated. A microbial diagnostic microarray for the detection of the most relevant bacterial food- and waterborne pathogens and indicator organisms was developed and thoroughly validated. The microarray platform based on sequence-specific end labeling of oligonucleotides and the phylogenetically robust gyrB marker gene allowed a highly specific (resolution on genus and/or species level) and sensitive (0.1% relative and 10(4) CFU absolute sensitivity) detection of the target pathogens. In initial challenge studies of the applicability of microarray-based food analysis, we obtained results demonstrating the questionable specificity of standardized culture-dependent microbiological detection methods. Taking into consideration the importance of reliable food safety assessment methods, comprehensive performance assessment is essential. Results demonstrate the potential of this new pathogen diagnostic microarray to evaluate culture-based standard methods in microbiological food analysis.

  8. Spectrogram Analysis of Genomes

    Directory of Open Access Journals (Sweden)

    David Sussillo

    2004-01-01

    Full Text Available We performed frequency-domain analysis in the genomes of various organisms using tricolor spectrograms, identifying several types of distinct visual patterns characterizing specific DNA regions. We relate patterns and their frequency characteristics to the sequence characteristics of the DNA. At times, the spectrogram patterns could be related to the structure of the corresponding protein region by using various public databases such as GenBank. Some patterns are explained from the biological nature of the corresponding regions, which relate to chromosome structure and protein coding, and some patterns have yet unknown biological significance. We found biologically meaningful patterns, on the scale of millions of base pairs, to a few hundred base pairs. Chromosome-wide patterns include periodicities ranging from 2 to 300. The color of the spectrogram depends on the nucleotide content at specific frequencies, and therefore can be used as a local indicator of CG content and other measures of relative base content. Several smaller-scale patterns were found to represent different types of domains made up of various tandem repeats.

  9. DNA Microarray as Part of a Genomic-Assisted Breeding Approach

    DEFF Research Database (Denmark)

    Vincze, Éva; Bowra, Steve

    2010-01-01

    . tissue/pathway specific approaches using an example of focused microarray and how it follows predicted changes during grain development. We describe of an extension of the study to field grown material and conclude that such an approach is able to interpret differences in the gene expression profiles......In the struggle to achieve global food security, crop breeding retains an important role in crop production. A current trend is the diversification of the aims of crop production, to include an increased awareness of aspects and consequences of food quality. The added emphasis on food and feed...... and practical significances, fold changes, validation and possible additional regulatory mechanisms in gene expression. The subject of the fourth section is the applications of DNA microarrays to study of global gene expression during grain filling in monocot crops, especially barley. We compare large arrays vs...

  10. Microarray analysis of Neosartorya fischeri using different carbon sources, petroleum asphaltenes and glucose-peptone

    OpenAIRE

    Edna L. Hernández-López; Ramírez-Puebla, Shamayim T.; Rafael Vazquez-Duhalt

    2015-01-01

    Asphaltenes are considered as the most recalcitrant petroleum fraction and represent a big problem for the recovery, separation and processing of heavy oils and bitumens. Neosartorya fischeri is a saprophytic fungus that is able to grow using asphaltenes as the sole carbon source [1]. We performed transcription profiling using a custom designed microarray with the complete genome from N. fischeri NRRL 181 in order to identify genes related to the transformation of asphaltenes [1]. Data ana...

  11. 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.

  12. Determination of the relationship between group A streptococcal genome content, M type, and toxic shock syndrome by a mixed genome microarray.

    Science.gov (United States)

    Vlaminckx, Bart J M; Schuren, Frank H J; Montijn, Roy C; Caspers, Martien P M; Fluit, Ad C; Wannet, Wim J B; Schouls, Leo M; Verhoef, Jan; Jansen, Wouter T M

    2007-05-01

    Group A streptococci (GAS), or Streptococcus pyogenes, are associated with a remarkable variety of diseases, ranging from superficial infections to life-threatening diseases such as toxic-shock-like syndrome (TSS). GAS strains belonging to M types M1 and M3 are associated with TSS. This study aims to obtain insight into the gene profiles underlying different M types and disease manifestations. Genomic differences between 76 clinically well characterized GAS strains collected in The Netherlands were examined using a mixed-genome microarray. Inter-M-type genomic differences clearly outweighed intra-M-type genome variation. Phages were major contributors to observed genome diversification. We identified four novel genes, including two genes encoding fibronectin-binding-like proteins, which are highly specific to a subset of M types and thus may contribute to M-type-associated disease manifestations. All M12 strains were characterized by the unique absence of the citrate lyase complex and reduced growth under hypoxic, nutrient-deprived conditions. Furthermore, six virulence factors, including genes encoding a complement-inhibiting protein (sic), an exotoxin (speA), iron(III) binding factor, collagen binding factor (cpa), and fibrinogen binding factor (prt2-like), were unique to M1 and/or M3 strains. These virulence factors may contribute to the potential of these strains to cause TSS. Finally, in contrast to M-type-specific virulence profiles, we did not identify a common virulence profile among strains associated with TSS irrespective of their M type.

  13. THEME: a web tool for loop-design microarray data analysis.

    Science.gov (United States)

    Chen, Chaang-Ray; Shu, Wun-Yi; Tsai, Min-Lung; Cheng, Wei-Chung; Hsu, Ian C

    2012-02-01

    A number of recent studies have shown that loop-design is more efficient than reference control design. Data analysis for loop-design microarray experiments is commonly undertaken using linear models and statistical tests. These techniques require specialized knowledge in statistical programming. However, limited loop-design web-based tools are available. We have developed the THEME (Tsing Hua Engine of Microarray Experiment) that exploits all necessary data analysis tools for loop-design microarray studies. THEME allows users to construct linear models and to apply multiple user-defined statistical tests of hypotheses for detection of DEG (differentially expressed genes). Users can modify entries of design matrix for experimental design as well as that of contrast matrix for statistical tests of hypotheses. The output of multiple user-defined statistical tests of hypotheses, DEG lists, can be cross-validated. The web platform provides data assessment and visualization tools that significantly assist users when evaluating the performance of microarray experimental procedures. THEME is also a MIAME (Minimal Information About a Microarray Experiment) compliant system, which enables users to export formatted files for GEO (Gene Expression Omnibus) submission. THEME offers comprehensive web services to biologists for data analysis of loop-design microarray experiments. This web-based resource is especially useful for core facility service as well as collaboration projects when researchers are not at the same site. Data analysis procedures, starting from uploading raw data files to retrieving DEG lists, can be flexibly operated with natural workflows. These features make THEME a reliable and powerful on-line system for data analysis of loop-design microarrays. The THEME server is available at http://metadb.bmes.nthu.edu.tw/theme/.

  14. Genome-Wide Screening of Genes Showing Altered Expression in Liver Metastases of Human Colorectal Cancers by cDNA Microarray

    Directory of Open Access Journals (Sweden)

    Rempei Yanagawa

    2001-01-01

    Full Text Available In spite of intensive and increasingly successful attempts to determine the multiple steps involved in colorectal carcinogenesis, the mechanisms responsible for metastasis of colorectal tumors to the liver remain to be clarified. To identify genes that are candidates for involvement in the metastatic process, we analyzed genome-wide expression profiles of 10 primary colorectal cancers and their corresponding metastatic lesions by means of a cDNA microarray consisting of 9121 human genes. This analysis identified 40 genes whose expression was commonly upregulated in metastatic lesions, and 7 that were commonly downregulated. The upregulated genes encoded proteins involved in cell adhesion, or remodeling of the actin cytoskeleton. Investigation of the functions of more of the altered genes should improve our understanding of metastasis and may identify diagnostic markers and/or novel molecular targets for prevention or therapy of metastatic lesions.

  15. Variance estimation in the analysis of microarray data

    KAUST Repository

    Wang, Yuedong

    2009-04-01

    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 to the small number of replications. Various methods have been proposed in the literature to overcome this lack of degrees of freedom problem. In this context, it is commonly observed that the variance increases proportionally with the intensity level, which has led many researchers to assume that the variance is a function of the mean. Here we concentrate on estimation of the variance as a function of an unknown mean in two models: the constant coefficient of variation model and the quadratic variance-mean model. Because the means are unknown and estimated with few degrees of freedom, naive methods that use the sample mean in place of the true mean are generally biased because of the errors-in-variables phenomenon. We propose three methods for overcoming this bias. The first two are variations on the theme of the so-called heteroscedastic simulation-extrapolation estimator, modified to estimate the variance function consistently. The third class of estimators is entirely different, being based on semiparametric information calculations. Simulations show the power of our methods and their lack of bias compared with the naive method that ignores the measurement error. The methodology is illustrated by using microarray data from leukaemia patients.

  16. Combining metabolomic analysis and microarray gene expression analysis in the characterization of the medicinal plant Chelidonium majus L.

    Science.gov (United States)

    Orland, A; Knapp, K; König, G M; Ulrich-Merzenich, G; Knöß, W

    2014-10-15

    Even though herbal medicines have played an important role in disease management and health for many centuries, their present frequent use is challenged by the necessity to determine their complex composition and their multitarget mode of action. In the present study, modern methods were investigated towards their potential in the characterization of herbal substances. As a model the herbal substance Chelidonii herba was used, for which several reports on liver toxicities exist. Extracts of Chelidonii herba with different solvents were characterized phytochemically and functionally by experiments with HepG2 liver cells. Chelidonii herba was extracted with four solvents of different polarity (dichloromethane, water, ethanol, and ethanol 50% (V/V); four replicates each). The different extracts were characterized metabolomically by (1)H-NMR fingerprinting analysis and principal component analysis (PCA). The content of alkaloids was additionally determined by RP-HPLC. Functional characterization was achieved by the determination of cell proliferation and by transcriptomics techniques (Whole Genome Gene Expression Microarrays v2, Agilent Technologies) in HepG2 cells after exposure to the different extracts (four experimental replicates each). Based on data from (1)H-NMR fingerprints and RP-HPLC analyses the different extracts showed a divergent composition of constituents depending on the solvent used. HepG2 liver cells responded differentially to the four extracts. Microarray analysis revealed a significant regulation of genes and signal cascades related to biotransformation. Also liver-toxic signal cascades were activated. Neither the activated genes nor the proliferation response could be clearly related to the differing alkaloid content of the extracts. Different manufacturing processes lead to different herbal preparations. A systems biology approach combining a metabolomic plant analysis with a functional characterization by gene expression profiling in HepG2

  17. Identification of mycotoxigenic fungi using an oligonucleotide microarray

    CSIR Research Space (South Africa)

    Barros, E

    2013-01-01

    Full Text Available , numerous detection tools have been developed for the detection and analysis of various mycotoxigenic fungi. These include PCR-based assays and microarrays targeting different areas of the fungal genome depending on its application. This chapter describes...

  18. ArrayQuest: a web resource for the analysis of DNA microarray data

    Directory of Open Access Journals (Sweden)

    Barth Jeremy L

    2005-12-01

    Full Text Available Abstract Background Numerous microarray analysis programs have been created through the efforts of Open Source software development projects. Providing browser-based interfaces that allow these programs to be executed over the Internet enhances the applicability and utility of these analytic software tools. Results Here we present ArrayQuest, a web-based DNA microarray analysis process controller. Key features of ArrayQuest are that (1 it is capable of executing numerous analysis programs such as those written in R, BioPerl and C++; (2 new analysis programs can be added to ArrayQuest Methods Library at the request of users or developers; (3 input DNA microarray data can be selected from public databases (i.e., the Medical University of South Carolina (MUSC DNA Microarray Database or Gene Expression Omnibus (GEO or it can be uploaded to the ArrayQuest center-point web server into a password-protected area; and (4 analysis jobs are distributed across computers configured in a backend cluster. To demonstrate the utility of ArrayQuest we have populated the methods library with methods for analysis of Affymetrix DNA microarray data. Conclusion ArrayQuest enables browser-based implementation of DNA microarray data analysis programs that can be executed on a Linux-based platform. Importantly, ArrayQuest is a platform that will facilitate the distribution and implementation of new analysis algorithms and is therefore of use to both developers of analysis applications as well as users. ArrayQuest is freely available for use at http://proteogenomics.musc.edu/arrayquest.html.

  19. Chromosomal microarray analysis of consecutive individuals with autism spectrum disorders or learning disability presenting for genetic services.

    Science.gov (United States)

    Roberts, Jennifer L; Hovanes, Karine; Dasouki, Majed; Manzardo, Ann M; Butler, Merlin G

    2014-02-01

    Chromosomal microarray analysis is now commonly used in clinical practice to identify copy number variants (CNVs) in the human genome. We report our experience with the use of the 105 K and 180K oligonucleotide microarrays in 215 consecutive patients referred with either autism or autism spectrum disorders (ASD) or developmental delay/learning disability for genetic services at the University of Kansas Medical Center during the past 4 years (2009-2012). Of the 215 patients [140 males and 75 females (male/female ratio=1.87); 65 with ASD and 150 with learning disability], abnormal microarray results were seen in 45 individuals (21%) with a total of 49 CNVs. Of these findings, 32 represented a known diagnostic CNV contributing to the clinical presentation and 17 represented non-diagnostic CNVs (variants of unknown significance). Thirteen patients with ASD had a total of 14 CNVs, 6 CNVs recognized as diagnostic and 8 as non-diagnostic. The most common chromosome involved in the ASD group was chromosome 15. For those with a learning disability, 32 patients had a total of 35 CNVs. Twenty-six of the 35 CNVs were classified as a known diagnostic CNV, usually a deletion (n=20). Nine CNVs were classified as an unknown non-diagnostic CNV, usually a duplication (n=8). For the learning disability subgroup, chromosomes 2 and 22 were most involved. Thirteen out of 65 patients (20%) with ASD had a CNV compared with 32 out of 150 patients (21%) with a learning disability. The frequency of chromosomal microarray abnormalities compared by subject group or gender was not statistically different. A higher percentage of individuals with a learning disability had clinical findings of seizures, dysmorphic features and microcephaly, but not statistically significant. While both groups contained more males than females, a significantly higher percentage of males were present in the ASD group.

  20. Construction of an Ostrea edulis database from genomic and expressed sequence tags (ESTs) obtained from Bonamia ostreae infected haemocytes: Development of an immune-enriched oligo-microarray.

    Science.gov (United States)

    Pardo, Belén G; Álvarez-Dios, José Antonio; Cao, Asunción; Ramilo, Andrea; Gómez-Tato, Antonio; Planas, Josep V; Villalba, Antonio; Martínez, Paulino

    2016-12-01

    The flat oyster, Ostrea edulis, is one of the main farmed oysters, not only in Europe but also in the United States and Canada. Bonamiosis due to the parasite Bonamia ostreae has been associated with high mortality episodes in this species. This parasite is an intracellular protozoan that infects haemocytes, the main cells involved in oyster defence. Due to the economical and ecological importance of flat oyster, genomic data are badly needed for genetic improvement of the species, but they are still very scarce. The objective of this study is to develop a sequence database, OedulisDB, with new genomic and transcriptomic resources, providing new data and convenient tools to improve our knowledge of the oyster's immune mechanisms. Transcriptomic and genomic sequences were obtained using 454 pyrosequencing and compiled into an O. edulis database, OedulisDB, consisting of two sets of 10,318 and 7159 unique sequences that represent the oyster's genome (WG) and de novo haemocyte transcriptome (HT), respectively. The flat oyster transcriptome was obtained from two strains (naïve and tolerant) challenged with B. ostreae, and from their corresponding non-challenged controls. Approximately 78.5% of 5619 HT unique sequences were successfully annotated by Blast search using public databases. A total of 984 sequences were identified as being related to immune response and several key immune genes were identified for the first time in flat oyster. Additionally, transcriptome information was used to design and validate the first oligo-microarray in flat oyster enriched with immune sequences from haemocytes. Our transcriptomic and genomic sequencing and subsequent annotation have largely increased the scarce resources available for this economically important species and have enabled us to develop an OedulisDB database and accompanying tools for gene expression analysis. This study represents the first attempt to characterize in depth the O. edulis haemocyte transcriptome in

  1. The complete genome sequence and comparative genome analysis of the high pathogenicity Yersinia enterocolitica strain 8081.

    Directory of Open Access Journals (Sweden)

    Nicholas R Thomson

    2006-12-01

    Full Text Available The human enteropathogen, Yersinia enterocolitica, is a significant link in the range of Yersinia pathologies extending from mild gastroenteritis to bubonic plague. Comparison at the genomic level is a key step in our understanding of the genetic basis for this pathogenicity spectrum. Here we report the genome of Y. enterocolitica strain 8081 (serotype 0:8; biotype 1B and extensive microarray data relating to the genetic diversity of the Y. enterocolitica species. Our analysis reveals that the genome of Y. enterocolitica strain 8081 is a patchwork of horizontally acquired genetic loci, including a plasticity zone of 199 kb containing an extraordinarily high density of virulence genes. Microarray analysis has provided insights into species-specific Y. enterocolitica gene functions and the intraspecies differences between the high, low, and nonpathogenic Y. enterocolitica biotypes. Through comparative genome sequence analysis we provide new information on the evolution of the Yersinia. We identify numerous loci that represent ancestral clusters of genes potentially important in enteric survival and pathogenesis, which have been lost or are in the process of being lost, in the other sequenced Yersinia lineages. Our analysis also highlights large metabolic operons in Y. enterocolitica that are absent in the related enteropathogen, Yersinia pseudotuberculosis, indicating major differences in niche and nutrients used within the mammalian gut. These include clusters directing, the production of hydrogenases, tetrathionate respiration, cobalamin synthesis, and propanediol utilisation. Along with ancestral gene clusters, the genome of Y. enterocolitica has revealed species-specific and enteropathogen-specific loci. This has provided important insights into the pathology of this bacterium and, more broadly, into the evolution of the genus. Moreover, wider investigations looking at the patterns of gene loss and gain in the Yersinia have highlighted common

  2. FDA Bioinformatics Tool for Microbial Genomics Research on Molecular Characterization of Bacterial Foodborne Pathogens Using Microarrays

    Science.gov (United States)

    Background: Advances in microbial genomics and bioinformatics are offering greater insights into the emergence and spread of foodborne pathogens in outbreak scenarios. The Food and Drug Administration (FDA) has developed the genomics tool ArrayTrackTM, which provides extensive functionalities to man...

  3. Aligning ontologies and integrating textual evidence for pathway analysis of microarray data

    Energy Technology Data Exchange (ETDEWEB)

    Gopalan, Banu; Posse, Christian; Sanfilippo, Antonio P.; Stenzel-Poore, Mary; Stevens, S.L.; Castano, Jose; Beagley, Nathaniel; Riensche, Roderick M.; Baddeley, Bob; Simon, R.P.; Pustejovsky, James

    2006-10-08

    Expression arrays are introducing a paradigmatic change in biology by shifting experimental approaches from single gene studies to genome-level analysis, monitoring the ex-pression levels of several thousands of genes in parallel. The massive amounts of data obtained from the microarray data needs to be integrated and interpreted to infer biological meaning within the context of information-rich pathways. In this paper, we present a methodology that integrates textual information with annotations from cross-referenced ontolo-gies to map genes to pathways in a semi-automated way. We illustrate this approach and compare it favorably to other tools by analyzing the gene expression changes underlying the biological phenomena related to stroke. Stroke is the third leading cause of death and a major disabler in the United States. Through years of study, researchers have amassed a significant knowledge base about stroke, and this knowledge, coupled with new technologies, is providing a wealth of new scientific opportunities. The potential for neu-roprotective stroke therapy is enormous. However, the roles of neurogenesis, angiogenesis, and other proliferative re-sponses in the recovery process following ischemia and the molecular mechanisms that lead to these processes still need to be uncovered. Improved annotation of genomic and pro-teomic data, including annotation of pathways in which genes and proteins are involved, is required to facilitate their interpretation and clinical application. While our approach is not aimed at replacing existing curated pathway databases, it reveals multiple hidden relationships that are not evident with the way these databases analyze functional groupings of genes from the Gene Ontology.

  4. Microarray analysis of LTR retrotransposon silencing identifies Hdac1 as a regulator of retrotransposon expression in mouse embryonic stem cells.

    Directory of Open Access Journals (Sweden)

    Judith Reichmann

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

  5. Microarray-based analysis of IncA/C plasmid-associated genes from multidrug-resistant Salmonella enterica.

    Science.gov (United States)

    Lindsey, Rebecca L; Frye, Jonathan G; Fedorka-Cray, Paula J; Meinersmann, Richard J

    2011-10-01

    In the family Enterobacteriaceae, plasmids have been classified according to 27 incompatibility (Inc) or replicon types that are based on the inability of different plasmids with the same replication mechanism to coexist in the same cell. Certain replicon types such as IncA/C are associated with multidrug resistance (MDR). We developed a microarray that contains 286 unique 70-mer oligonucleotide probes based on sequences from five IncA/C plasmids: pYR1 (Yersinia ruckeri), pPIP1202 (Yersinia pestis), pP99-018 (Photobacterium damselae), pSN254 (Salmonella enterica serovar Newport), and pP91278 (Photobacterium damselae). DNA from 59 Salmonella enterica isolates was hybridized to the microarray and analyzed for the presence or absence of genes. These isolates represented 17 serovars from 14 different animal hosts and from different geographical regions in the United States. Qualitative cluster analysis was performed using CLUSTER 3.0 to group microarray hybridization results. We found that IncA/C plasmids occurred in two lineages distinguished by a major insertion-deletion (indel) region that contains genes encoding mostly hypothetical proteins. The most variable genes were represented by transposon-associated genes as well as four antimicrobial resistance genes (aphA, merP, merA, and aadA). Sixteen mercury resistance genes were identified and highly conserved, suggesting that mercury ion-related exposure is a stronger pressure than anticipated. We used these data to construct a core IncA/C genome and an accessory genome. The results of our studies suggest that the transfer of antimicrobial resistance determinants by transfer of IncA/C plasmids is somewhat less common than exchange within the plasmids orchestrated by transposable elements, such as transposons, integrating and conjugative elements (ICEs), and insertion sequence common regions (ISCRs), and thus pose less opportunity for exchange of antimicrobial resistance.

  6. Evaluation criteria of rat hepatocytes transcriptome analysis under the influence of interferon alpha by DNA microarray

    Directory of Open Access Journals (Sweden)

    Kuklin A. V.

    2013-10-01

    Full Text Available The changes induced in transcriptome of rat hepatocytes treated with interferon alpha (IFN during three and six hours were analyzed by DNA microarray. Aim. To conduct a stepwise analysis of the results of microarray experiment and to determine whether they meet/fail to the conventional requirements. Methods. The files obtained after scanning microarrays were subjected to the analysis in statistical environment R by Bioconductor’s packages «affy», «simpleaffy», «affyPLM» and BRB Array Tools software for paired T-test. Results. All microarrays had quality metrics lying within recommended ranges, passed quality control, were normalized and are comparable with each other. The T-test revealed 28 and 124 differentially expressed genes after three and six hours of cells cultivation with IFNα , respectively. Conclusions. The obtained data meet the conventional criteria of quality and are applicable for further evaluation of their biological significance. The R-codes used in this study can be used for the analysis of the microarrays data.

  7. Genomic comparison of Yersinia pestis and Yersinia pseudotuberculosis by combination of suppression subtractive hybridization and DNA microarray

    DEFF Research Database (Denmark)

    Wang, Xiaoyi; Zhou, Dongsheng; Qin, Long

    2006-01-01

    a combination of suppression subtractive hybridization (SSH) and comparative genomic hybridization with DNAs from a diverse panel of Y. pestis and Y. pseudotuberculosis strains. SSH followed by BLAST analysis revealed 112 SSH fragments specific to strain ATCC29833, compared to the genomic sequence data of Y...

  8. Genome-wide survey of cold stress regulated alternative splicing in Arabidopsis thaliana with tiling microarray.

    Directory of Open Access Journals (Sweden)

    Noam Leviatan

    Full Text Available Alternative splicing plays a major role in expanding the potential informational content of eukaryotic genomes. It is an important post-transcriptional regulatory mechanism that can increase protein diversity and affect mRNA stability. Alternative splicing is often regulated in a tissue-specific and stress-responsive manner. Cold stress, which adversely affects plant growth and development, regulates the transcription and splicing of plant splicing factors. This can affect the pre-mRNA processing of many genes. To identify cold regulated alternative splicing we applied Affymetrix Arabidopsis tiling arrays to survey the transcriptome under cold treatment conditions. A novel algorithm was used for detection of statistically relevant changes in intron expression within a transcript between control and cold growth conditions. A reverse transcription polymerase chain reaction (RT-PCR analysis of a number of randomly selected genes confirmed the changes in splicing patterns under cold stress predicted by tiling array. Our analysis revealed new types of cold responsive genes. While their expression level remains relatively unchanged under cold stress their splicing pattern shows detectable changes in the relative abundance of isoforms. The majority of cold regulated alternative splicing introduced a premature termination codon (PTC into the transcripts creating potential targets for degradation by the nonsense mediated mRNA decay (NMD process. A number of these genes were analyzed in NMD-defective mutants by RT-PCR and shown to evade NMD. This may result in new and truncated proteins with altered functions or dominant negative effects. The results indicate that cold affects both quantitative and qualitative aspects of gene expression.

  9. Genome-wide survey of cold stress regulated alternative splicing in Arabidopsis thaliana with tiling microarray.

    Science.gov (United States)

    Leviatan, Noam; Alkan, Noam; Leshkowitz, Dena; Fluhr, Robert

    2013-01-01

    Alternative splicing plays a major role in expanding the potential informational content of eukaryotic genomes. It is an important post-transcriptional regulatory mechanism that can increase protein diversity and affect mRNA stability. Alternative splicing is often regulated in a tissue-specific and stress-responsive manner. Cold stress, which adversely affects plant growth and development, regulates the transcription and splicing of plant splicing factors. This can affect the pre-mRNA processing of many genes. To identify cold regulated alternative splicing we applied Affymetrix Arabidopsis tiling arrays to survey the transcriptome under cold treatment conditions. A novel algorithm was used for detection of statistically relevant changes in intron expression within a transcript between control and cold growth conditions. A reverse transcription polymerase chain reaction (RT-PCR) analysis of a number of randomly selected genes confirmed the changes in splicing patterns under cold stress predicted by tiling array. Our analysis revealed new types of cold responsive genes. While their expression level remains relatively unchanged under cold stress their splicing pattern shows detectable changes in the relative abundance of isoforms. The majority of cold regulated alternative splicing introduced a premature termination codon (PTC) into the transcripts creating potential targets for degradation by the nonsense mediated mRNA decay (NMD) process. A number of these genes were analyzed in NMD-defective mutants by RT-PCR and shown to evade NMD. This may result in new and truncated proteins with altered functions or dominant negative effects. The results indicate that cold affects both quantitative and qualitative aspects of gene expression.

  10. 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.

  11. 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

    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....

  12. 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

    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...

  13. Whole genome sequence typing and microarray profiling of nasal and blood stream methicillin-resistant Staphylococcus aureus isolates: Clues to phylogeny and invasiveness.

    Science.gov (United States)

    Hamed, Mohamed; Nitsche-Schmitz, Daniel Patric; Ruffing, Ulla; Steglich, Matthias; Dordel, Janina; Nguyen, Duy; Brink, Jan-Hendrik; Chhatwal, Gursharan Singh; Herrmann, Mathias; Nübel, Ulrich; Helms, Volkhard; von Müller, Lutz

    2015-12-01

    Hospital-associated methicillin-resistant Staphylococcus aureus (MRSA) infections are frequently caused by predominant clusters of closely related isolates that cannot be discriminated by conventional diagnostic typing methods. Whole genome sequencing (WGS) and DNA microarray (MA) now allow for better discrimination within a prevalent clonal complex (CC). This single center exploratory study aims to distinguish invasive (blood stream infection) and non-invasive (nasal colonization) MRSA isolates of the same CC5 into phylogenetic- and virulence-associated genotypic subgroups by WGS and MA. A cohort of twelve blood stream and fifteen nasal MRSA isolates of CC5 (spa-types t003 and t504) was selected. Isolates were propagated at the same period of time from unrelated patients treated at the University of Saarland Medical Center, Germany. Rooted phylotyping based on WGS with core-genome single nucleotide polymorphism (SNP) analysis revealed two local clusters of closely related CC5 subgroups (t504 and Clade1 t003) which were separated from other local t003 isolates and from unrelated CC5 MRSA reference isolates of German origin. Phylogenetic subtyping was not associated with invasiveness when comparing blood stream and nasal isolates. Clustering based on MA profiles was not concordant with WGS phylotyping, but MA profiles may identify subgroups of isolates with nasal and blood stream origin. Among the new putative virulence associated genes identified by WGS, the strongest association with blood stream infections was shown for ebhB mutants. Analysis of the core-genome together with the accessory genome enables subtyping of closely related MRSA isolates according to phylogeny and presumably also to the potential virulence capacity of isolates.

  14. Identification of Chromosome Abnormalities in Subtelomeric Regions by Microarray Analysis: A Study of 5,380 Cases

    Science.gov (United States)

    Shao, Lina; Shaw, Chad A.; Lu, Xin-Yan; Sahoo, Trilochan; Bacino, Carlos A.; Lalani, Seema R.; Stankiewicz, Pawel; Yatsenko, Svetlana A.; Li, Yinfeng; Neill, Sarah; Pursley, Amber N.; Chinault, A. Craig; Patel, Ankita; Beaudet, Arthur L.; Lupski, James R.; Cheung, Sau W.

    2009-01-01

    Subtelomeric imbalances are a significant cause of congenital disorders. Screening for these abnormalities has traditionally utilized GTG-banding analysis, fluorescence in situ hybridization (FISH) assays, and multiplex ligation-dependent probe amplification. Microarray-based comparative genomic hybridization (array-CGH) is a relatively new technology that can identify microscopic and submicroscopic chromosomal imbalances. It has been proposed that an array with extended coverage at subtelomeric regions could characterize subtelomeric aberrations more efficiently in a single experiment. The targeted arrays for chromosome microarray analysis (CMA), developed by Baylor College of Medicine, have on average 12 BAC/PAC clones covering 10 Mb of each of the 41 subtelomeric regions. We screened 5,380 consecutive clinical patients using CMA. The most common reasons for referral included developmental delay (DD), and/or mental retardation (MR), dysmorphic features (DF), multiple congenital anomalies (MCA), seizure disorders (SD), and autistic, or other behavioral abnormalities. We found pathogenic rearrangements at subtelomeric regions in 236 patients (4.4%). Among these patients, 103 had a deletion, 58 had a duplication, 44 had an unbalanced translocation, and 31 had a complex rearrangement. The detection rates varied among patients with a normal karyotype analysis (2.98%), with an abnormal karyotype analysis (43.4%), and with an unavailable or no karyotype analysis (3.16%). Six patients out of 278 with a prior normal subtelomere-FISH analysis showed an abnormality including an interstitial deletion, two terminal deletions, two interstitial duplications, and a terminal duplication. In conclusion, genomic imbalances at subtelomeric regions contribute significantly to congenital disorders. Targeted array-CGH with extended coverage (up to 10 Mb) of subtelomeric regions will enhance the detection of subtelomeric imbalances, especially for submicroscopic imbalances. PMID

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

    Directory of Open Access Journals (Sweden)

    Danielle E Green

    2015-01-01

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

  16. Diagnostic and analytical applications of protein microarrays

    DEFF Research Database (Denmark)

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

    2005-01-01

    years. A genome-scale protein microarray has been demonstrated for identifying protein-protein interactions as well as for rapid identification of protein binding to a particular drug. Furthermore, protein microarrays have been shown as an efficient tool in cancer profiling, detection of bacteria...... and toxins, identification of allergen reactivity and autoantibodies. They have also demonstrated the ability to measure the absolute concentration of small molecules. Besides their capacity for parallel diagnostics, microarrays can be more sensitive than traditional methods such as enzyme...... and be amenable to automation or integrated into easy-to-use systems, such as micrototal analysis systems or point-of-care devices....

  17. Microarray analysis of microbiota of gingival lesions in noma patients.

    Directory of Open Access Journals (Sweden)

    Antoine Huyghe

    Full Text Available Noma (cancrum oris is a gangrenous disease of unknown etiology affecting the maxillo-facial region of young children in extremely limited resource countries. In an attempt to better understand the microbiological events occurring during this disease, we used phylogenetic and low-density microarrays targeting the 16S rRNA gene to characterize the gingival flora of acute noma and acute necrotizing gingivitis (ANG lesions, and compared them to healthy control subjects of the same geographical and social background. Our observations raise doubts about Fusobacterium necrophorum, a previously suspected causative agent of noma, as this species was not associated with noma lesions. Various oral pathogens were more abundant in noma lesions, notably Atopobium spp., Prevotella intermedia, Peptostreptococcus spp., Streptococcus pyogenes and Streptococcus anginosus. On the other hand, pathogens associated with periodontal diseases such as Aggregatibacter actinomycetemcomitans, Capnocytophaga spp., Porphyromonas spp. and Fusobacteriales were more abundant in healthy controls. Importantly, the overall loss of bacterial diversity observed in noma samples as well as its homology to that of ANG microbiota supports the hypothesis that ANG might be the immediate step preceding noma.

  18. DNA microarray analysis of genes differentially expressed in adipocyte differentiation

    Indian Academy of Sciences (India)

    Chunyan Yin; Yanfeng Xiao; Wei Zhang; Erdi Xu; Weihua Liu; Xiaoqing Yi; Ming Chang

    2014-06-01

    In the present study, the human liposarcoma cell line SW872 was used to identify global changes in gene expression profiles occurring during adipogenesis. We further explored some of the genes expressed during the late phase of adipocyte differentiation. These genes may play a major role in promoting excessive proliferation and accumulation of lipid droplets, which contribute to the development of obesity. By using microarray-based technology, we examined differential gene expression in early differentiated adipocytes and late differentiated adipocytes. Validated genes exhibited a ≥ 10-fold increase in the late phase of adipocyte differentiation by polymerase chain reaction (RT-PCR). Compared with undifferentiated preadipocytes, we found that 763 genes were increased in early differentiated adipocytes, and 667 genes were increased in later differentiated adipocytes. Furthermore, 21 genes were found being expressed 10-fold higher in the late phase of adipocyte differentiation. The results were in accordance with the RT-PCR test, which validated 11 genes, namely, CIDEC, PID1, LYRM1, ADD1, PPAR2, ANGPTL4, ADIPOQ, ACOX1, FIP1L1, MAP3K2 and PEX14. Most of these genes were found being expressed in the later phase of adipocyte differentiation involved in obesity-related diseases. The findings may help to better understand the mechanism of obesity and related diseases.

  19. Microarray Analysis of the Microflora of Root Caries in Elderly

    Science.gov (United States)

    Preza, Dorita; Olsen, Ingar; Willumsen, Tiril; Boches, Susan K.; Cotton, Sean L.; Grinde, Bjørn; Paster, Bruce J.

    2009-01-01

    Purpose The present study used a new 16S rRNA-based microarray with probes for over 300 bacterial species better define the bacterial profiles of healthy root surfaces and root caries (RC) in the elderly. Materials Supragingival plaque was collected from 20 healthy subjects (Controls) and from healthy and carious roots and carious dentin from 21 RC subjects (Patients). Results Collectively, 179 bacterial species and species groups were detected. A higher bacterial diversity was observed in the Controls as compared to Patients. Lactobacillus casei/paracasei/rhamnosus and Pseudoramibacter alactolyticus were notably associated with most root caries samples. Streptococcus mutans was detected more frequently in the infected dentin than in the other samples, but the difference was not significant. Actinomyces were found more frequently in Controls. Conclusion Actinomyces and S. mutans may play a limited role as pathogens of RC. The results from this study were in agreement with those of our previous study based on 16S rRNA gene sequencing with 72% of the species being detected with both methods. PMID:19039610

  20. DNA microarray analysis of genes differentially expressed in adipocyte differentiation.

    Science.gov (United States)

    Yin, Chunyan; Xiao, Yanfeng; Zhang, Wei; Xu, Erdi; Liu, Weihua; Yi, Xiaoqing; Chang, Ming

    2014-06-01

    In the present study, the human liposarcoma cell line SW872 was used to identify global changes in gene expression profiles occurring during adipogenesis. We further explored some of the genes expressed during the late phase of adipocyte differentiation. These genes may play a major role in promoting excessive proliferation and accumulation of lipid droplets, which contribute to the development of obesity. By using microarray-based technology, we examined differential gene expression in early differentiated adipocytes and late differentiated adipocytes. Validated genes exhibited a greater than or equal to 10-fold increase in the late phase of adipocyte differentiation by polymerase chain reaction (RT-PCR). Compared with undifferentiated preadipocytes, we found that 763 genes were increased in early differentiated adipocytes, and 667 genes were increased in later differentiated adipocytes. Furthermore, 21 genes were found being expressed 10-fold higher in the late phase of adipocyte differentiation. The results were in accordance with the RTPCR test, which validated 11 genes, namely, CIDEC, PID1, LYRM1, ADD1, PPAR?2, ANGPTL4, ADIPOQ, ACOX1, FIP1L1, MAP3K2 and PEX14. Most of these genes were found being expressed in the later phase of adipocyte differentiation involved in obesity-related diseases. The findings may help to better understand the mechanism of obesity and related diseases.

  1. Microarray analysis of microbiota of gingival lesions in noma patients.

    Science.gov (United States)

    Huyghe, Antoine; François, Patrice; Mombelli, Andrea; Tangomo, Manuela; Girard, Myriam; Baratti-Mayer, Denise; Bolivar, Ignacio; Pittet, Didier; Schrenzel, Jacques

    2013-01-01

    Noma (cancrum oris) is a gangrenous disease of unknown etiology affecting the maxillo-facial region of young children in extremely limited resource countries. In an attempt to better understand the microbiological events occurring during this disease, we used phylogenetic and low-density microarrays targeting the 16S rRNA gene to characterize the gingival flora of acute noma and acute necrotizing gingivitis (ANG) lesions, and compared them to healthy control subjects of the same geographical and social background. Our observations raise doubts about Fusobacterium necrophorum, a previously suspected causative agent of noma, as this species was not associated with noma lesions. Various oral pathogens were more abundant in noma lesions, notably Atopobium spp., Prevotella intermedia, Peptostreptococcus spp., Streptococcus pyogenes and Streptococcus anginosus. On the other hand, pathogens associated with periodontal diseases such as Aggregatibacter actinomycetemcomitans, Capnocytophaga spp., Porphyromonas spp. and Fusobacteriales were more abundant in healthy controls. Importantly, the overall loss of bacterial diversity observed in noma samples as well as its homology to that of ANG microbiota supports the hypothesis that ANG might be the immediate step preceding noma.

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

    Science.gov (United States)

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

    2010-05-21

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

  3. Microarray and KOG analysis of Acanthamoeba healyi genes up-regulated by mouse-brain passage.

    Science.gov (United States)

    Moon, Eun-Kyung; Xuan, Ying-Hua; Kong, Hyun-Hee

    2014-08-01

    Long-term cultivation in a laboratory could reduce the virulence of Acanthamoeba. To identify virulence factors of Acanthamoeba, the authors compared the transcription profiles of long-term cultivated Acanthamoeba healyi (OLD) and three times mouse-brain passaged A. healyi (MBP) using microarray analysis and eukaryotic orthologous group (KOG) assignments. Microarray analysis revealed that 601 genes were up-regulated by mouse-brain passage. The results of real-time PCR of 8 randomly selected genes up-regulated in the MBP strain confirmed microarray analysis findings. KOG assignments showed relatively higher percentages of the MBP strain up-regulated genes in T article (signal transduction mechanism), O article (posttranslational modification, protein turnover, chaperones), C article (energy production and conversion), and J article (translation, ribosomal structure and biogenesis). In particular, the MBP strain showed higher expressions of cysteine protease and metalloprotease. A comparison of KOG assignments by microarray analysis and previous EST (expressed sequence tags) analysis showed similar populations of up-regulated genes. These results provide important information regarding the identification of virulence factors of pathogenic Acanthamoeba.

  4. Rapid Diagnosis of Imprinting Disorders Involving Copy Number Variation and Uniparental Disomy Using Genome-Wide SNP Microarrays.

    Science.gov (United States)

    Liu, Weiqiang; Zhang, Rui; Wei, Jun; Zhang, Huimin; Yu, Guojiu; Li, Zhihua; Chen, Min; Sun, Xiaofang

    2015-01-01

    Imprinting disorders, such as Beckwith-Wiedemann syndrome (BWS), Prader-Willi syndrome (PWS) and Angelman syndrome (AS), can be detected via methylation analysis, methylation-specific multiplex ligation-dependent probe amplification (MS-MLPA), or other methods. In this study, we applied single nucleotide polymorphism (SNP)-based chromosomal microarray analysis to detect copy number variations (CNVs) and uniparental disomy (UPD) events in patients with suspected imprinting disorders. Of 4 patients, 2 had a 5.25-Mb microdeletion in the 15q11.2q13.2 region, 1 had a 38.4-Mb mosaic UPD in the 11p15.4 region, and 1 had a 60-Mb detectable UPD between regions 14q13.2 and 14q32.13. Although the 14q32.2 region was classified as normal by SNP array for the 14q13 UPD patient, it turned out to be a heterodisomic UPD by short tandem repeat marker analysis. MS-MLPA analysis was performed to validate the variations. In conclusion, SNP-based microarray is an efficient alternative method for quickly and precisely diagnosing PWS, AS, BWS, and other imprinted gene-associated disorders when considering aberrations due to CNVs and most types of UPD.

  5. BR 07-1 DEVELOPMENT OF THE CELL MICROARRAY FOR HIGH-THROUGHPUT ANALYSIS OF GUT MICROBIOTA.

    Science.gov (United States)

    Hong, Seong-Tshool

    2016-09-01

    The human intestine contains a massive and complex microbial community called gut microbiota. A typical human carries 100 trillion microbes in his/her body which is 10 times greater than the number of their host cells, i.e. whole number of human cells. A combined microbial genome constituting gut microbiota is well excess our own human genome. The microbial composition of gut microbiotata and its role on diseases became a booming area of research, presenting a new paradigm of opportunities for modern medicines. Recent evidences showed that gut microbiota acts as a very important determining factor for the development of almost all complex diseases such as primary hypertension, obesity, depression, diabetes, autism, asthma, bowl diseases, rheumatic arthritis, systemic lupus erythematosus, Crohn's disease, Parkinson's disease, Alzheimer's disease, epilepsy, schizophrenia, etc. In spite of the significant role of gut microbiota in the development of complex diseases, the elucidation of the mechanistic pathway on the development of complex diseases by gut microbiota is not moving forward as expected. Current methods to identify alteration of gut microbiota in patients and healthy controls are basically based on the metagenomic sequencings of DNA samples extracted from feces by using next-generation sequencing machines. Although the metagenomic sequencing approaches proved association of gut microbiota with various complex diseases, those methods failed to accurately pinpoint the etiological agents in gut microbiota for complex diseases. The metagenomic sequencing approaches are not only difficult to identify the etiological agent of complex diseases at species level but also difficult to use, requiring complex bioinformatic analyses, and expensive. To overcome the current challenges in analysis of gut microbiota, we developed a novel cell microarray to analyze the constituent microbial organisms of gut microbiota very accurately and fast by using a drop of blood. The

  6. Comparative Genome Analysis and Genome Evolution

    NARCIS (Netherlands)

    Snel, Berend

    2002-01-01

    This thesis described a collection of bioinformatic analyses on complete genome sequence data. We have studied the evolution of gene content and find that vertical inheritance dominates over horizontal gene trasnfer, even to the extent that we can use the gene content to make genome phylogenies. Usi

  7. Comparative Genome Analysis and Genome Evolution

    NARCIS (Netherlands)

    Snel, Berend

    2003-01-01

    This thesis described a collection of bioinformatic analyses on complete genome sequence data. We have studied the evolution of gene content and find that vertical inheritance dominates over horizontal gene trasnfer, even to the extent that we can use the gene content to make genome phylogenies. Usi

  8. Genomic analysis of stress response against arsenic in Caenorhabditis elegans.

    Directory of Open Access Journals (Sweden)

    Surasri N Sahu

    Full Text Available Arsenic, a known human carcinogen, is widely distributed around the world and found in particularly high concentrations in certain regions including Southwestern US, Eastern Europe, India, China, Taiwan and Mexico. Chronic arsenic poisoning affects millions of people worldwide and is associated with increased risk of many diseases including arthrosclerosis, diabetes and cancer. In this study, we explored genome level global responses to high and low levels of arsenic exposure in Caenorhabditis elegans using Affymetrix expression microarrays. This experimental design allows us to do microarray analysis of dose-response relationships of global gene expression patterns. High dose (0.03% exposure caused stronger global gene expression changes in comparison with low dose (0.003% exposure, suggesting a positive dose-response correlation. Biological processes such as oxidative stress, and iron metabolism, which were previously reported to be involved in arsenic toxicity studies using cultured cells, experimental animals, and humans, were found to be affected in C. elegans. We performed genome-wide gene expression comparisons between our microarray data and publicly available C. elegans microarray datasets of cadmium, and sediment exposure samples of German rivers Rhine and Elbe. Bioinformatics analysis of arsenic-responsive regulatory networks were done using FastMEDUSA program. FastMEDUSA analysis identified cancer-related genes, particularly genes associated with leukemia, such as dnj-11, which encodes a protein orthologous to the mammalian ZRF1/MIDA1/MPP11/DNAJC2 family of ribosome-associated molecular chaperones. We analyzed the protective functions of several of the identified genes using RNAi. Our study indicates that C. elegans could be a substitute model to study the mechanism of metal toxicity using high-throughput expression data and bioinformatics tools such as FastMEDUSA.

  9. Chromosomal Microarray Analysis in Fetuses with Growth Restriction and Normal Karyotype: A Systematic Review and Meta-Analysis.

    Science.gov (United States)

    Borrell, Antoni; Grande, Maribel; Pauta, Montse; Rodriguez-Revenga, Laia; Figueras, Francesc

    2017-09-09

    To perform a systematic review of the literature and a meta-analysis to estimate the incremental yield of chromosomal microarray analysis (CMA) over karyotyping in fetal growth restriction (FGR). This was a systematic review conducted in accordance with the PRISMA criteria. All articles identified in PubMed, Ovid Medline, and ISI Web of Knowledge (Web of Science) from January 2009 to November 2016 describing pathogenic copy number variants (CNVs) in fetuses with growth restriction were included. Case reports were excluded. Risk differences were pooled to estimate the overall and stratified CMA incremental yield. Ten studies with full data available met the inclusion criteria for analysis. Combined data from these studies revealed a 4% (95% confidence interval [CI] 1-6%) incremental yield of CMA over karyotyping in nonmalformed growth-restricted fetuses, and a 10% (95% CI 6-14%) incremental yield in FGR when associated with fetal malformations. The most frequently found pathogenic CNVs were 22q11.2 duplication, Xp22.3 deletion, and 7q11.23 deletion (Williams-Beuren syndrome), particularly in isolated FGR. The use of genomic CMA provides a 4% incremental yield of detecting pathogenic CNVs in fetuses with isolated growth restriction and normal karyotype. © 2017 S. Karger AG, Basel.

  10. Comparative analysis of Lactobacillus plantarum WCFS1 transcriptomes using DNA microarray and next generation sequencing technologies

    NARCIS (Netherlands)

    Leimena, M.M.; Wels, M.; Bongers, R.; Smid, E.J.; Zoetendal, E.G.; Kleerebezem, M.

    2012-01-01

    RNA sequencing is starting to compete with the use of DNA microarrays for transcription analysis in eukaryotes as well as in prokaryotes. Application of RNA sequencing in prokaryotes requires additional steps in the RNA preparation procedure to increase the relative abundance of mRNA and cannot

  11. Pathways analysis: combining microarray data and physiological data to study myogenesis

    NARCIS (Netherlands)

    Pas, te M.F.W.; Hulsegge, B.; Pool, M.H.

    2007-01-01

    Microarray experiments investigate the changes in the expression of the transcriptome of a tissue during biological processes such as development of the tissue. Analysis usually produces a list of up and down regulated genes. While this in itself mayhighlight important biological processes taking

  12. Tissue microarray analysis as a screening tool for neuroendocrine carcinoma of the breast

    DEFF Research Database (Denmark)

    Brask, Julie Benedicte; Talman, Maj-Lis Møller; Wielenga, Vera Timmermans

    2014-01-01

    by investigating the usefulness of tissue microarray (TMA) analysis as a screening tool. We present our findings with regard to sensitivity and specificity compared with whole-mount sections. The material consists of 240 cases of breast cancer divided into 20 TMA blocks that were all immunohistochemically stained...

  13. Microarray analysis of gender- and parasite-specific gene transcription in Strongyloides ratti

    NARCIS (Netherlands)

    Evans, Helen; Mello, Luciane V.; Fang, Yongxiang; Wit, Ernst; Thompson, Fiona J.; Viney, Mark E.; Paterson, Steve

    2008-01-01

    The molecular mechanisms by which parasitic nematodes reproduce and have adapted to life within a host are unclear. In the present study, microarray analysis was used to explore differential transcription among the different stages and sexes of Strongyloides ratti, a parasitic nematode of brown rats

  14. Gene expression analysis of strawberry achene and receptacle maturation using DNA microarrays

    NARCIS (Netherlands)

    Aharoni, A.; O'Connell, A.P.

    2002-01-01

    Large-scale, single pass sequencing and parallel gene expression analysis using DNA microarrays were employed for the comprehensive investigation of ripening in strawberry fruit. A total of 1701 cDNA clones (comprising 1100 strawberry ESTs and 601 unsequenced cDNAs) obtained from a strawberry (Fraga

  15. Scanometric analysis of DNA microarrays using DNA intercalator-conjugated gold nanoparticles.

    Science.gov (United States)

    Cho, Hyunmin; Jung, Juyeon; Chung, Bong Hyun

    2012-08-07

    We introduce a scanometric detection method for the analysis of DNA microarrays using DNA intercalator-conjugated gold nanoparticles that can be analyzed with the naked eye or with an optical scanner after the enhancement of the AuNPs. Moreover, we successfully detected a hemagglutinin-subtyping DNA array using this method.

  16. MicA microarray analysis of hepatotoxicity in vivo and in vitro

    NARCIS (Netherlands)

    Elferink, Marieke; Olinga, Peter; Draaisma, Annelies; Merema, M.T.; Bauerschmidt, Susanne; Polman, Jan; Schoonen, Willem; Groothuis, Geny

    2007-01-01

    In the process of drug discovery it is of great importance to develop methods to determine early markers for druginduced toxicity. The microarray technology, developed for the simultaneous analysis of a large number of genes, may be useful for the detection of toxicity in an early stage of the devel

  17. Diagnostic Yield of Chromosomal Microarray Analysis in an Autism Primary Care Practice: Which Guidelines to Implement?

    Science.gov (United States)

    McGrew, Susan G.; Peters, Brittany R.; Crittendon, Julie A.; Veenstra-VanderWeele, Jeremy

    2012-01-01

    Genetic testing is recommended for patients with ASD; however specific recommendations vary by specialty. American Academy of Pediatrics and American Academy of Neurology guidelines recommend G-banded karyotype and Fragile X DNA. The American College of Medical Genetics recommends Chromosomal Microarray Analysis (CMA). We determined the yield of…

  18. Microarray analysis of toxicogenomic effects of Ortho-phenylphenol in Staphylococcus aureus

    Directory of Open Access Journals (Sweden)

    Toghrol Freshteh

    2008-09-01

    Full Text Available Abstract Background Staphylococcus aureus (S. aureus, is responsible for many infectious diseases, ranging from benign skin infections to life-threatening endocarditis and toxic shock syndrome. Ortho-phenylphenol (OPP is an antimicrobial agent and an active ingredient of EPA-registered disinfectants with wide human exposure in various agricultural, hospital and veterinary disinfectant products. Despite many uses, an understanding of a cellular response to OPP and it's mechanism of action, targeted genes, and the connectivity between targeted genes and the rest of cell metabolism remains obscure. Results Herein, we performed a genome-wide transcriptome analysis of the cellular responses of S. aureus when exposed to 0.82 mM of OPP for 20 and 60 min. Our data indicated that OPP downregulated the biosynthesis of many amino acids, which are required for protein synthesis. In particular, the genes encoding the enzymes of the diaminopimelate (DAP pathway which results in lysine biosynthesis were significantly downregualted. Intriguingly, we revealed that the transcription of genes encoding ribosomal proteins was upregulated by OPP and at the same time, the genes encoding iron acquisition and transport were downregulated. The genes encoding virulence factors were upregulated and genes encoding phospholipids were downregulated upon 20 min exposure to OPP. Conclusion By using microarray analysis that enables us to simultaneously and globally examine the complete transcriptome during cellular responses, we have revealed novel information regarding the mode of action of OPP on Staphylococcus: OPP inhibits anabolism of many amino acids and highly downregulates the genes that encode the enzymes involved in the DAP pathway. Lysine and DAP are essential for building up the peptidoglycan cell wall. It was concluded that the mode of action of OPP is similar to the mechanism of action of some antibiotics. The discovery of this phenomenon provides useful

  19. κMicroarray analysis of relative gene expression stability for selection of internal reference genes in the rhesus macaque brain

    Directory of Open Access Journals (Sweden)

    Urbanski Henryk F

    2010-06-01

    Full Text Available Abstract Background Normalization of gene expression data refers to the comparison of expression values using reference standards that are consistent across all conditions of an experiment. In PCR studies, genes designated as "housekeeping genes" have been used as internal reference genes under the assumption that their expression is stable and independent of experimental conditions. However, verification of this assumption is rarely performed. Here we assess the use of gene microarray analysis to facilitate selection of internal reference sequences with higher expression stability across experimental conditions than can be expected using traditional selection methods. We recently demonstrated that relative gene expression from qRT-PCR data normalized using GAPDH, ALG9 and RPL13A expression values mirrored relative expression using quantile normalization in Robust Multichip Analysis (RMA on the Affymetrix® GeneChip® rhesus Macaque Genome Array. Having shown that qRT-PCR and Affymetrix® GeneChip® data from the same hormone replacement therapy (HRT study yielded concordant results, we used quantile-normalized gene microarray data to identify the most stably expressed among probe sets for prospective internal reference genes across three brain regions from the HRT study and an additional study of normally menstruating rhesus macaques (cycle study. Gene selection was limited to 575 previously published human "housekeeping" genes. Twelve animals were used per study, and three brain regions were analyzed from each animal. Gene expression stabilities were determined using geNorm, NormFinder and BestKeeper software packages. Results Sequences co-annotated for ribosomal protein S27a (RPS27A, and ubiquitin were among the most stably expressed under all conditions and selection criteria used for both studies. Higher annotation quality on the human GeneChip® facilitated more targeted analysis than could be accomplished using the rhesus GeneChip®. In

  20. Unraveling the rat blood genome-wide transcriptome after oral administration of lavender oil by a two-color dye-swap DNA microarray approach

    Directory of Open Access Journals (Sweden)

    Motohide Hori

    2016-06-01

    Full Text Available Lavender oil (LO is a commonly used essential oil in aromatherapy as non-traditional medicine. With an aim to demonstrate LO effects on the body, we have recently established an animal model investigating the influence of orally administered LO in rat tissues, genome-wide. In this brief, we investigate the effect of LO ingestion in the blood of rat. Rats were administered LO at usual therapeutic dose (5 mg/kg in humans, and following collection of the venous blood from the heart and extraction of total RNA, the differentially expressed genes were screened using a 4 × 44-K whole-genome rat chip (Agilent microarray platform; Agilent Technologies, Palo Alto, CA, USA in conjunction with a two-color dye-swap approach. A total of 834 differentially expressed genes in the blood were identified: 362 up-regulated and 472 down-regulated. These genes were functionally categorized using bioinformatics tools. The gene expression inventory of rat blood transcriptome under LO, a first report, has been deposited into the Gene Expression Omnibus (GEO: GSE67499. The data will be a valuable resource in examining the effects of natural products, and which could also serve as a human model for further functional analysis and investigation.

  1. Identification of gene clusters associated with host adaptation and antibiotic resistance in Chinese Staphylococcus aureus isolates by microarray-based comparative genomics.

    Directory of Open Access Journals (Sweden)

    Henan Li

    Full Text Available A comparative genomic microarray comprising 2,457 genes from two whole genomes of S. aureus was employed for the comparative genome hybridization analysis of 50 strains of divergent clonal lineages, including methicillin-resistant S. aureus (MRSA, methicillin-susceptible S. aureus (MSSA, and swine strains in China. Large-scale validation was confirmed via polymerase chain reaction in 160 representative clinical strains. All of the 50 strains were clustered into seven different complexes by phylogenetic tree analysis. Thirteen gene clusters were specific to different S. aureus clones. Ten gene clusters, including seven known (vSa3, vSa4, vSaα, vSaβ, Tn5801, and phage ϕSa3 and three novel (C8, C9, and C10 gene clusters, were specific to human MRSA. Notably, two global regulators, sarH2 and sarH3, at cluster C9 were specific to human MRSA, and plasmid pUB110 at cluster C10 was specific to swine MRSA. Three clusters known to be part of SCCmec, vSa4 or Tn5801, and vSaα as well as one novel gene cluster C12 with homology with Tn554 of S. epidermidis were identified as MRSA-specific gene clusters. The replacement of ST239-spa t037 with ST239-spa t030 in Beijing may be a result of its acquisition of vSa4, phage ϕSa1, and ϕSa3. In summary, thirteen critical gene clusters were identified to be contributors to the evolution of host specificity and antibiotic resistance in Chinese S. aureus.

  2. Candidate genes for the progression of malignant gliomas identified by microarray analysis.

    Science.gov (United States)

    Bozinov, Oliver; Köhler, Sylvia; Samans, Birgit; Benes, Ludwig; Miller, Dorothea; Ritter, Markus; Sure, Ulrich; Bertalanffy, Helmut

    2008-01-01

    Malignant astrocytomas of World Health Organization (WHO) grade III or IV have a reduced median survival time, and possible pathways have been described for the progression of anaplastic astrocytomas and glioblastomas, but the molecular basis of malignant astrocytoma progression is still poorly understood. Microarray analysis provides the chance to accelerate studies by comparison of the expression of thousands of genes in these tumours and consequently identify targeting genes. We compared the transcriptional profile of 4,608 genes in tumours of 15 patients including 6 anaplastic astrocytomas (WHO grade III) and 9 glioblastomas (WHO grade IV) using microarray analysis. The microarray data were corroborated by real-time reverse transcription-polymerase chain reaction analysis of two selected genes. We identified 166 gene alterations with a fold change of 2 and higher whose mRNA levels differed (absolute value of the t statistic of 1.96) between the two malignant glioma groups. Further analyses confirmed same transcription directions for Olig2 and IL-13Ralpha2 in anaplastic astrocytomas as compared to glioblastomas. Microarray analyses with a close binary question reveal numerous interesting candidate genes, which need further histochemical testing after selection for confirmation. IL-13Ralpha2 and Olig2 have been identified and confirmed to be interesting candidate genes whose differential expression likely plays a role in malignant progression of astrocytomas.

  3. A three-dimensional waveguide structure as a support for genomic and proteomic microarrays

    Science.gov (United States)

    Dertinger, Stephan K.; Kluehr, Marco; Elsner, Christian A.; Sauermann, Alexander; Rueffer, Kristin; Nicklaus, Petra M.; Thein, Kerstin

    2004-12-01

    In this paper we present a three-dimensional waveguide structure with unique optical and fluidic properties and demonstrate its application as a substrate for DNA microarrays. The structure is fabricated by thermal oxidation of a macroporous silicon membrane with a periodic pattern of discrete pores running perpendicular through the substrate. Partial oxidation generates a SiO2 membrane, but leaves a rectangular grid of silicon walls dividing the membrane into compartments. We show that the SiO2 walls act as optical waveguides and characterize their optical properties; modes can be launched using Koehler illumination. The silicon walls optically isolate adjacent compartments and prevent light from spreading laterally in the membrane. In a DNA hybridization experiment, the detection of 100 attomol of a Cy-3 labeled DNA fragment (17 oligonucleotides) has been achieved with a signal to noise ratio of > 3:1. We believe that even lower detection limits can be achieved by further tuning the optical parameters of the three-dimensional waveguide structure.

  4. Transcriptomic analysis of potato tuber development and tuber quality traits using microarray technology

    OpenAIRE

    Kloosterman, B.A.

    2006-01-01

    The potato crop is one of the most important food crops in the world and in order to understand how in potato plants the formation of potato tubers and the determination of different tuber quality traits are regulated, we need to identify and characterize the genes that are involved in regulating these processes. The aim of the research described in this PhD thesis was to implement a relatively new genomic tool (i.e. microarray technology) in an ongoing study to understand the process of pota...

  5. Transcriptome-Wide High-Density Microarray Analysis Reveals Differential Gene Transcription in Periprosthetic Tissue From Hips With Chronic Periprosthetic Joint Infection vs Aseptic Loosening.

    Science.gov (United States)

    Omar, Mohamed; Klawonn, Frank; Brand, Stephan; Stiesch, Meike; Krettek, Christian; Eberhard, Jörg

    2017-01-01

    Differentiating between periprosthetic hip infection and aseptic hip prosthesis loosening can be challenging, especially in patients with chronic infections. This study used whole-genome microarray analysis to investigate the transcriptomes of periprosthetic hip tissues to identify genes that are differentially transcripted between chronic periprosthetic hip infection and aseptic hip prosthesis loosening. In this pilot study, a total of 24 patients with either chronic periprosthetic hip infection (n = 12) or aseptic hip prosthesis loosening (n = 12) were analyzed. Periprosthetic hip infection was diagnosed based on modified criteria of the Musculoskeletal Infection Society. To evaluate differences in gene transcription, whole-genome microarray analysis was performed on the mRNA of periprosthetic tissue. Microarray analysis revealed differential gene transcription in periprosthetic hip tissue affected by chronic hip infection vs aseptic hip prosthesis loosening. A total of 39 genes had area under the curve values greater than 0.9 for diagnosing chronic periprosthetic hip infection; 5 genes had annotations relevant to infection and metabolism. The 39 genes also included 7 genes that were differentially transcribed but that have no apparent connection to immune response processes plus 27 genes with unknown function. Differences in gene transcription profiles might represent novel diagnostic targets that can be used to differentiate between chronic periprosthetic hip infections and aseptic hip prosthesis loosening. Secondary metabolites of differentially transcripted genes might serve as easily accessible markers for detecting chronic periprosthetic joint infection in future. Copyright © 2016 Elsevier Inc. All rights reserved.

  6. A whole-genome microarray reveals genetic diversity among Helicobacter pylori strains

    OpenAIRE

    Salama, Nina; Guillemin, Karen; McDaniel, Timothy K.; Sherlock, Gavin; Tompkins, Lucy; Falkow, Stanley

    2000-01-01

    Helicobacter pylori colonizes the stomach of half of the world's population, causing a wide spectrum of disease ranging from asymptomatic gastritis to ulcers to gastric cancer. Although the basis for these diverse clinical outcomes is not understood, more severe disease is associated with strains harboring a pathogenicity island. To characterize the genetic diversity of more and less virulent strains, we examined the genomic content of 15 H. pylori clinical isolate...

  7. Microarray and synchronization of neuronal differentiation with pathway changes in the Kyoto Encyclopedia of Genes and Genomes (KEGG) databank in nerve growth factor-treated PC12 cells.

    Science.gov (United States)

    Lin, Chih-Ming; Feng, Wayne

    2012-08-01

    The Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway database creates networks from interrelations between molecular biology and underlying chemical elements. This allows for analysis of biologic networks, genomic information, and higher-order functional information at a systems level. We performed microarray experiments and used the KEGG database, systems biology analysis, and annotation of pathway function to study nerve growth factor (NGF)-induced differentiation of PC12 cells. Cells were cultured to 70%-80% confluence, treated with NGF for 1 or 3 hours (h), and RNA was extracted. Stage 1 data analysis involved analysis of variance (ANOVA), and stage 2 involved cluster analysis and heat map generation. We identified 2020 NGF-induced PC12 genes (1038 at 1 h and 1554 at 3 h). Results showed changes in gene expression over time. We compared these genes with 6035 genes from the KEGG database. Cross-matching resulted in 830 genes. Among these, we identified 395 altered genes (155 at 1 h and 301 at 3 h; 2-fold increase from 1 h to 3 h). We identified 191 biologic pathways in the KEGG database; the top 15 showed correlations with neuronal differentiation (mitogen-activated protein kinase [MAPK] pathway: 35 genes at 1 h, 54 genes at 3 h; genes associated with axonal guidance: 12 at 1 h, 26 at 3 h; Wnt pathway: 16 at 1 h, 25 at 3 h; neurotrophin pathway: 4 at 1 h, 14 at 3 h). Thus, we identified changes in neuronal differentiation pathways with the KEGG database, which were synchronized with NGF-induced differentiation.

  8. Array2BIO: A Comprehensive Suite of Utilities for the Analysis of Microarray Data

    Energy Technology Data Exchange (ETDEWEB)

    Loots, G G; Chain, P G; Mabery, S; Rasley, A; Garcia, E; Ovcharenko, I

    2006-02-13

    We have developed an integrative and automated toolkit for the analysis of Affymetrix microarray data, named Array2BIO. It identifies groups of coexpressed genes using two complementary approaches--comparative analysis of signal versus control microarrays and clustering analysis of gene expression across different conditions. The identified genes are assigned to functional categories based on the Gene Ontology classification, and a detection of corresponding KEGG protein interaction pathways. Array2BIO reliably handles low-expressor genes and provides a set of statistical methods to quantify the odds of observations, including the Benjamini-Hochberg and Bonferroni multiple testing corrections. Automated interface with the ECR Browser provides evolutionary conservation analysis of identified gene loci while the interconnection with Creme allows high-throughput analysis of human promoter regions and prediction of gene regulatory elements that underlie the observed expression patterns. Array2BIO is publicly available at http://array2bio.dcode.org.

  9. 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.

  10. Microarray meta-analysis database (M2DB: a uniformly pre-processed, quality controlled, and manually curated human clinical microarray database

    Directory of Open Access Journals (Sweden)

    Cheng Wei-Chung

    2010-08-01

    Full Text Available Abstract Background Over the past decade, gene expression microarray studies have greatly expanded our knowledge of genetic mechanisms of human diseases. Meta-analysis of substantial amounts of accumulated data, by integrating valuable information from multiple studies, is becoming more important in microarray research. However, collecting data of special interest from public microarray repositories often present major practical problems. Moreover, including low-quality data may significantly reduce meta-analysis efficiency. Results M2DB is a human curated microarray database designed for easy querying, based on clinical information and for interactive retrieval of either raw or uniformly pre-processed data, along with a set of quality-control metrics. The database contains more than 10,000 previously published Affymetrix GeneChip arrays, performed using human clinical specimens. M2DB allows online querying according to a flexible combination of five clinical annotations describing disease state and sampling location. These annotations were manually curated by controlled vocabularies, based on information obtained from GEO, ArrayExpress, and published papers. For array-based assessment control, the online query provides sets of QC metrics, generated using three available QC algorithms. Arrays with poor data quality can easily be excluded from the query interface. The query provides values from two algorithms for gene-based filtering, and raw data and three kinds of pre-processed data for downloading. Conclusion M2DB utilizes a user-friendly interface for QC parameters, sample clinical annotations, and data formats to help users obtain clinical metadata. This database provides a lower entry threshold and an integrated process of meta-analysis. We hope that this research will promote further evolution of microarray meta-analysis.

  11. Evaluation of chronic lymphocytic leukemia by BAC-based microarray analysis

    Directory of Open Access Journals (Sweden)

    McDaniel Lisa D

    2011-02-01

    Full Text Available Abstract Background Chronic lymphocytic leukemia (CLL is a highly variable disease with life expectancies ranging from months to decades. Cytogenetic findings play an integral role in defining the prognostic significance and treatment for individual patients. Results We have evaluated 25 clinical cases from a tertiary cancer center that have an established diagnosis of CLL and for which there was prior cytogenetic and/or fluorescence in situ hybridization (FISH data. We performed microarray-based comparative genomic hybridization (aCGH using a bacterial artificial chromosome (BAC-based microarray designed for the detection of known constitutional genetic syndromes. In 15 of the 25 cases, aCGH detected all copy number imbalances identified by prior cytogenetic and/or FISH studies. For the majority of those not detected, the aberrations were present at low levels of mosaicism. Furthermore, for 15 of the 25 cases, additional abnormalities were detected. Four of those cases had deletions that mapped to intervals implicated in inherited predisposition to CLL. For most cases, aCGH was able to detect abnormalities present in as few as 10% of cells. Although changes in ploidy are not easily discernable by aCGH, results for two cases illustrate the detection of additional copy gains and losses present within a mosaic tetraploid cell population. Conclusions Our results illustrate the successful evaluation of CLL using a microarray optimized for the interrogation of inherited disorders and the identification of alterations with possible relevance to CLL susceptibility.

  12. On-Chip Isothermal Nucleic Acid Amplification on Flow-Based Chemiluminescence Microarray Analysis Platform for the Detection of Viruses and Bacteria.

    Science.gov (United States)

    Kunze, A; Dilcher, M; Abd El Wahed, A; Hufert, F; Niessner, R; Seidel, M

    2016-01-01

    This work presents an on-chip isothermal nucleic acid amplification test (iNAAT) for the multiplex amplification and detection of viral and bacterial DNA by a flow-based chemiluminescence microarray. In a principle study, on-chip recombinase polymerase amplification (RPA) on defined spots of a DNA microarray was used to spatially separate the amplification reaction of DNA from two viruses (Human adenovirus 41, Phi X 174) and the bacterium Enterococcus faecalis, which are relevant for water hygiene. By establishing the developed assay on the microarray analysis platform MCR 3, the automation of isothermal multiplex-amplification (39 °C, 40 min) and subsequent detection by chemiluminescence imaging was realized. Within 48 min, the microbes could be identified by the spot position on the microarray while the generated chemiluminescence signal correlated with the amount of applied microbe DNA. The limit of detection (LOD) determined for HAdV 41, Phi X 174, and E. faecalis was 35 GU/μL, 1 GU/μL, and 5 × 10(3) GU/μL (genomic units), which is comparable to the sensitivity reported for qPCR analysis, respectively. Moreover the simultaneous amplification and detection of DNA from all three microbes was possible. The presented assay shows that complex enzymatic reactions like an isothermal amplification can be performed in an easy-to-use experimental setup. Furthermore, iNAATs can be potent candidates for multipathogen detection in clinical, food, or environmental samples in routine or field monitoring approaches.

  13. Analysis of methylation microarray for tissue specific detection.

    Science.gov (United States)

    Muangsub, Tachapol; Samsuwan, Jarunya; Tongyoo, Pumipat; Kitkumthorn, Nakarin; Mutirangura, Apiwat

    2014-12-10

    The role of human DNA methylation has been extensively studied in genomic imprinting, X-inactivation, and disease. However, studies of tissue-specific methylation remain limited. In this study, we use bioinformatics methods to analyze methylation data and reveal loci that are exclusively methylated or unmethylated in individual tissues. We collect 39 previously published DNA methylation profiles using an Illumina® HumanMethylation 27 BeadChip Kit containing 22 common tissues and involving 27,578 CpG loci across the human genome. We found 86 positions of tissue specific methylation CpG (TSM) that encompass 34 hypermethylated TSMs (31 genes) and 52 hypomethylated TSMs (47 genes). Tissues were found to contain 1 to 25 TSM loci, with the majority in the liver (25), testis (18), and brain (16). Fewer TSM loci were found in the muscle (8), ovary (7), adrenal gland (3), pancreas (2-4), kidney, spleen, and stomach (1 each). TSMs are predominantly located 0-300 base pairs in the 3' direction after the transcription start site. Similar to known promoters of methylation, hypermethylated TSM genes suppress transcription, while hypomethylated TSMs allow gene transcription. The majority of hypermethylated TSM genes encode membrane proteins and receptors, while hypomethylated TSM genes primarily encode signal peptides and tissue-specific proteins. In summary, the database of TSM loci produced herein is useful for the selection of tissue-specific DNA markers as diagnostic tools, as well as for the further study of the mechanisms and roles of TSM. Copyright © 2014 Elsevier B.V. All rights reserved.

  14. Gene microarray data analysis using parallel point-symmetry-based clustering.

    Science.gov (United States)

    Sarkar, Anasua; Maulik, Ujjwal

    2015-01-01

    Identification of co-expressed genes is the central goal in microarray gene expression analysis. Point-symmetry-based clustering is an important unsupervised learning technique for recognising symmetrical convex- or non-convex-shaped clusters. To enable fast clustering of large microarray data, we propose a distributed time-efficient scalable approach for point-symmetry-based K-Means algorithm. A natural basis for analysing gene expression data using symmetry-based algorithm is to group together genes with similar symmetrical expression patterns. This new parallel implementation also satisfies linear speedup in timing without sacrificing the quality of clustering solution on large microarray data sets. The parallel point-symmetry-based K-Means algorithm is compared with another new parallel symmetry-based K-Means and existing parallel K-Means over eight artificial and benchmark microarray data sets, to demonstrate its superiority, in both timing and validity. The statistical analysis is also performed to establish the significance of this message-passing-interface based point-symmetry K-Means implementation. We also analysed the biological relevance of clustering solutions.

  15. Goober: a fully integrated and user-friendly microarray data management and analysis solution for core labs and bench biologists.

    Science.gov (United States)

    Luo, Wen; Gudipati, Murali; Jung, Kevin; Chen, Mao; Marschke, Keith B

    2009-08-23

    Despite the large number of software tools developed to address different areas of microarray data analysis, very few offer an all-in-one solution with little learning curve. For microarray core labs, there are even fewer software packages available to help with their routine but critical tasks, such as data quality control (QC) and inventory management. We have developed a simple-to-use web portal to allow bench biologists to analyze and query complicated microarray data and related biological pathways without prior training. Both experiment-based and gene-based analysis can be easily performed, even for the first-time user, through the intuitive multi-layer design and interactive graphic links. While being friendly to inexperienced users, most parameters in Goober can be easily adjusted via drop-down menus to allow advanced users to tailor their needs and perform more complicated analysis. Moreover, we have integrated graphic pathway analysis into the website to help users examine microarray data within the relevant biological content. Goober also contains features that cover most of the common tasks in microarray core labs, such as real time array QC, data loading, array usage and inventory tracking. Overall, Goober is a complete microarray solution to help biologists instantly discover valuable information from a microarray experiment and enhance the quality and productivity of microarray core labs. The whole package is freely available at http://sourceforge.net/projects/goober. A demo web server is available at http://www.goober-array.org.

  16. Comparative analysis of gene expression by microarray analysis of male and female flowers of Asparagus officinalis.

    Science.gov (United States)

    Gao, Wu-Jun; Li, Shu-Fen; Zhang, Guo-Jun; Wang, Ning-Na; Deng, Chuan-Liang; Lu, Long-Dou

    2013-01-01

    To identify rapidly a number of genes probably involved in sex determination and differentiation of the dioecious plant Asparagus officinalis, gene expression profiles in early flower development for male and female plants were investigated by microarray assay with 8,665 probes. In total, 638 male-biased and 543 female-biased genes were identified. These genes with biased-expression for male and female were involved in a variety of processes associated with molecular functions, cellular components, and biological processes, suggesting that a complex mechanism underlies the sex development of asparagus. Among the differentially expressed genes involved in the reproductive process, a number of genes associated with floral development were identified. Reverse transcription-PCR was performed for validation, and the results were largely consistent with those obtained by microarray analysis. The findings of this study might contribute to understanding of the molecular mechanisms of sex determination and differentiation in dioecious asparagus and provide a foundation for further studies of this plant.

  17. Rapid extraction of genomic DNA from saliva for HLA typing on microarray based on magnetic nanobeads

    Science.gov (United States)

    Xie, Xin; Zhang, Xu; Yu, Bingbin; Gao, Huafang; Zhang, Huan; Fei, Weiyang

    2004-09-01

    A series of simplified protocols are developed for extracting genomic DNA from saliva by using the magnetic nanobeads as absorbents. In these protocols, both the enrichment of the target cells and the adsorption of DNA can be achieved simultaneously by our functionally modified magnetic beads in one step, and the DNA-nanobeads complex can be used as PCR templates. HLA typing based on an oligonucleotide array was conducted by hybridization with the PCR products. The result shows that the protocols are robust and sensitive.

  18. Overlay tool for aCGHViewer: an analysis module built for aCGHViewer used to perform comparisons of data derived from different microarray platforms.

    Science.gov (United States)

    Lo, Ken C; Shankar, Ganesh; Turpaz, Yaron; Bailey, Dione; Rossi, Michael R; Burkhardt, Tania; Liang, Ping; Cowell, John K

    2007-08-08

    The Overlay Tool has been developed to combine high throughput data derived from various microarray platforms. This tool analyzes high-resolution correlations between gene expression changes and either copy number abnormalities (CNAs) or loss of heterozygosity events detected using array comparative genomic hybridization (aCGH). Using an overlay analysis which is designed to be performed using data from multiple microarray platforms on a single biological sample, the Overlay Tool identifies potentially important genes whose expression profiles are changed as a result of losses, gains and amplifications in the cancer genome. In addition, the Overlay Tool will incorporate loss of heterozygosity (LOH) probability data into this overlay procedure. To facilitate this analysis, we developed an application which computationally combines two or more high throughput datasets (e.g. aCGH/expression) into a single categorized dataset for visualization and interrogation using a gene-centric approach. As such, data from virtually any microarray platform can be incorporated without the need to remap entire datasets individually. The resultant categorized (overlay) data set can be conveniently viewed using our in-house visualization tool, aCGHViewer (Shankar et al. 2006), which serves as a conduit to public databases such as UCSC and NCBI, to rapidly investigate genes of interest.

  19. An oligo-based microarray offers novel transcriptomic approaches for the analysis of pathogen resistance and fruit quality traits in melon (Cucumis melo L.

    Directory of Open Access Journals (Sweden)

    Garcia-Mas Jordi

    2009-10-01

    Full Text Available Abstract Background Melon (Cucumis melo is a horticultural specie of significant nutritional value, which belongs to the Cucurbitaceae family, whose economic importance is second only to the Solanaceae. Its small genome of approx. 450 Mb coupled to the high genetic diversity has prompted the development of genetic tools in the last decade. However, the unprecedented existence of a transcriptomic approaches in melon, highlight the importance of designing new tools for high-throughput analysis of gene expression. Results We report the construction of an oligo-based microarray using a total of 17,510 unigenes derived from 33,418 high-quality melon ESTs. This chip is particularly enriched with genes that are expressed in fruit and during interaction with pathogens. Hybridizations for three independent experiments allowed the characterization of global gene expression profiles during fruit ripening, as well as in response to viral and fungal infections in plant cotyledons and roots, respectively. Microarray construction, statistical analyses and validation together with functional-enrichment analysis are presented in this study. Conclusion The platform validation and enrichment analyses shown in our study indicate that this oligo-based microarray is amenable for future genetic and functional genomic studies of a wide range of experimental conditions in melon.

  20. Towards standardization of microarray-based genotyping of Salmonella

    DEFF Research Database (Denmark)

    Löfström, Charlotta; Grønlund, Hugo Ahlm; Riber, Leise

    2010-01-01

    Genotyping is becoming an increasingly important tool to improve risk assessments of Salmonella. DNA microarray technology is a promising diagnostic tool that can provide high resolution genomic profile of many genes simultaneously. However, standardization of DNA microarray analysis is needed...... of Salmonella at two different laboratories. The low-density array contained 281 of 57-60-mer oligonucleotide probes for detecting a wide range of specific genomic markers associated with antibiotic resistance, cell envelope structures, mobile genetic elements and pathogenicity. Several test parameters...... for a decentralized and simple-to-implement DNA microarray as part of a pan-European source-attribution model for risk assessment of Salmonella....

  1. Discovery and analysis of pancreatic adenocarcinoma genes using cDNA microarrays

    Institute of Scientific and Technical Information of China (English)

    Gang Jin; Xian-Gui Hu; Kang Ying; Yan Tang; Rui Liu; Yi-Jie Zhang; Zai-Ping Jing; Yi Xie; Yu-Min Mao

    2005-01-01

    AIM: To study the pathogenetic processes and the role of gene expression by microarray analyses in expediting our understanding of the molecular pathophysiology of pancreatic adenocarcinoma, and to identify the novel cancer-associated genes.METHODS: Nine histologically defined pancreatic head adenocarcinoma specimens associated with clinical data were studied. Total RNA and mRNA were isolated and labeled by reverse transcription reaction with Cy5 and Cy3 for cDNA probe. The cDNA microarrays that represent a set of 4 096 human genes were hybridized with labeled cDNA probe and screened for molecular profiling analyses.RESULTS: Using this methodology, 184 genes were screened out for differences in gene expression level after nine couples of hybridizations. Of the 184 genes,87 were upregulated and 97 downregulated, including 11 novel human genes. In pancreatic adenocarcinoma tissue, several invasion and metastasis related genes showed their high expression levels, suggesting that poor prognosis of pancreatic adenocarcinoma might have a solid molecular biological basis.CONCLUSION: The application of cDNA microarray technique for analysis of gene expression patterns is a powerful strategy to identify novel cancer-associated genes, and to rapidly explore their role in clinical pancreatic adenocarcinoma. Microarray profiles provide us new insights into the carcinogenesis and invasive process of pancreatic adenocarcinoma. Our results suggest that a highly organized and structured process of tumor invasion exists in the pancreas.

  2. 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

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

    Science.gov (United States)

    Kong, Xiangrong; Mas, Valeria; Archer, Kellie J

    2008-02-26

    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. 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. 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 reported to be relevant to renal diseases. Further study on the

  4. From hybridization theory to microarray data analysis: performance evaluation

    Directory of Open Access Journals (Sweden)

    Berger Fabrice

    2011-12-01

    Full Text Available Abstract Background Several preprocessing methods are available for the analysis of Affymetrix Genechips arrays. The most popular algorithms analyze the measured fluorescence intensities with statistical methods. Here we focus on a novel algorithm, AffyILM, available from Bioconductor, which relies on inputs from hybridization thermodynamics and uses an extended Langmuir isotherm model to compute transcript concentrations. These concentrations are then employed in the statistical analysis. We compared the performance of AffyILM and other traditional methods both in the old and in the newest generation of GeneChips. Results Tissue mixture and Latin Square datasets (provided by Affymetrix were used to assess the performances of the differential expression analysis depending on the preprocessing strategy. A correlation analysis conducted on the tissue mixture data reveals that the median-polish algorithm allows to best summarize AffyILM concentrations computed at the probe-level. Those correlation results are equivalent to the best correlations observed using popular preprocessing methods relying on intensity values. The performances of each tested preprocessing algorithm were quantified using the Latin Square HG-U133A dataset, thanks to the comparison of differential analysis results with the list of spiked genes. The figures of merit generated illustrates that the performances associated to AffyILM(medianpolish, inferred from the present statistical analysis, are comparable to the best performing strategies previously reported. Conclusions Converting probe intensities to estimates of target concentrations prior to the statistical analysis, AffyILM(medianpolish is one of the best performing strategy currently available. Using hybridization theory, probe-level estimates of target concentrations should be identically distributed. In the future, a probe-level multivariate analysis of the concentrations should be compared to the univariate analysis of

  5. Clinical value of genome-wide high resolution chromosomal microarray analysis in etiological study of fetuses with congenital heart defects%染色体微阵列分析技术对先天性心脏病胎儿进行遗传病因学诊断的临床价值

    Institute of Scientific and Technical Information of China (English)

    吴晓丽; 符芳; 李茹; 潘敏; 韩瑾; 甄理; 杨昕; 张永玲; 李发涛

    2014-01-01

    的外周血进行CMA检测结果显示,其中5例胎儿CNV遗传自父母,为良性CNV;其余3例(3%,3/88)CNV的临床意义仍然无法明确.14例(16%)胎儿CNV结果为致病性CNV.结论 对染色体核型分析结果正常的CHD胎儿进行CMA检测,能额外发现部分致病性CNV;推荐在产前诊断的CHD胎儿中应用全基因组CMA技术作为常规分子诊断方法,更有助于遗传咨询中正确评估胎儿的预后.%Objective To explore the clinical value of genome-wide high resolution chromosomal microarray analysis (CMA) in etiological study of fetuses with congenital heart disease (CHD) diagnosed by fetal echocardiography.Methods A total of 176 fetuses diagnosed CHD by fetal echocardiography were analyzed,and invasive prenatal diagnosis was performed at Guangzhou Women and Children's Medical Center from January 2012 to January 2014.Among them,158 fetuses were proved to have normal karyotype,and 88 fetuses (50.0%,88/176) underwent CMA testing.The parental blood specimens were also collected for assisting the diagnosis of variants of uncertain clinical significance (VOUS).The 88 fetuses were divided into two groups:isolated CHD (n=68) and CHD with extra-cardiac structural abnormalities (n=20).The phenotypes of the two groups were subclassified.Copy number variations (CNV) were classified as benign CNV,pathogenic CNV (pCNV) or VOUS.Results (1) 58 fetuses (66%,58/88) were with simple CHD and 30 fetuses were with complicated CHD (34%,30/88).In the 45 fetuses with isolated and simple CHD,the pCNV detection rate was 11% (5/45).In the 23 fetuses with isolated and complicated CHD,the pCNV detection rate was 17% (4/23).In the 13 fetuses with simple CHD and extra-cardiac structural abnormalities,the pCNV detection rate was 5/13.In the 7 fetuses with complicated CHD and extra-cardiac structural abnormalities,the pCNV detection rate was 0.(2) The total detection rate for pCNV detection was 16% (14/88) in the 88 fetuses.The pCNV detection

  6. Whole genome comparison of Campylobacter jejuni human isolates using a low-cost microarray reveals extensive genetic diversity.

    Science.gov (United States)

    Dorrell, N; Mangan, J A; Laing, K G; Hinds, J; Linton, D; Al-Ghusein, H; Barrell, B G; Parkhill, J; Stoker, N G; Karlyshev, A V; Butcher, P D; Wren, B W

    2001-10-01

    Campylobacter jejuni is the leading cause of bacterial food-borne diarrhoeal disease throughout the world, and yet is still a poorly understood pathogen. Whole genome microarray comparisons of 11 C. jejuni strains of diverse origin identified genes in up to 30 NCTC 11168 loci ranging from 0.7 to 18.7 kb that are either absent or highly divergent in these isolates. Many of these regions are associated with the biosynthesis of surface structures including flagella, lipo-oligosaccharide, and the newly identified capsule. Other strain-variable genes of known function include those responsible for iron acquisition, DNA restriction/modification, and sialylation. In fact, at least 21% of genes in the sequenced strain appear dispensable as they are absent or highly divergent in one or more of the isolates tested, thus defining 1300 C. jejuni core genes. Such core genes contribute mainly to metabolic, biosynthetic, cellular, and regulatory processes, but many virulence determinants are also conserved. Comparison of the capsule biosynthesis locus revealed conservation of all the genes in this region in strains with the same Penner serotype as strain NCTC 11168. By contrast, between 5 and 17 NCTC 11168 genes in this region are either absent or highly divergent in strains of a different serotype from the sequenced strain, providing further evidence that the capsule accounts for Penner serotype specificity. These studies reveal extensive genetic diversity among C. jejuni strains and pave the way toward identifying correlates of pathogenicity and developing improved epidemiological tools for this problematic pathogen.

  7. A meta-analysis of public microarray data identifies gene regulatory pathways deregulated in peripheral blood mononuclear cells from individuals with Systemic Lupus Erythematosus compared to those without.

    Science.gov (United States)

    Kröger, Wendy; Mapiye, Darlington; Entfellner, Jean-Baka Domelevo; Tiffin, Nicki

    2016-11-15

    Systemic Lupus Erythematosus (SLE) is a complex, multi-systemic, autoimmune disease for which the underlying aetiological mechanisms are poorly understood. The genetic and molecular processes underlying lupus have been extensively investigated using a variety of -omics approaches, including genome-wide association studies, candidate gene studies and microarray experiments of differential gene expression in lupus samples compared to controls. This study analyses a combination of existing microarray data sets to identify differentially regulated genetic pathways that are dysregulated in human peripheral blood mononuclear cells from SLE patients compared to unaffected controls. Two statistical approaches, quantile discretisation and scaling, are used to combine publicly available expression microarray datasets and perform a meta-analysis of differentially expressed genes. Differentially expressed genes implicated in interferon signaling were identified by the meta-analysis, in agreement with the findings of the individual studies that generated the datasets used. In contrast to the individual studies, however, the meta-analysis and subsequent pathway analysis additionally highlighted TLR signaling, oxidative phosphorylation and diapedesis and adhesion regulatory networks as being differentially regulated in peripheral blood mononuclear cells (PBMCs) from SLE patients compared to controls. Our analysis demonstrates that it is possible to derive additional information from publicly available expression data using meta-analysis techniques, which is particularly relevant to research into rare diseases where sample numbers can be limiting.

  8. GEPAS, a web-based tool for microarray data analysis and interpretation

    Science.gov (United States)

    Tárraga, Joaquín; Medina, Ignacio; Carbonell, José; Huerta-Cepas, Jaime; Minguez, Pablo; Alloza, Eva; Al-Shahrour, Fátima; Vegas-Azcárate, Susana; Goetz, Stefan; Escobar, Pablo; Garcia-Garcia, Francisco; Conesa, Ana; Montaner, David; Dopazo, Joaquín

    2008-01-01

    Gene Expression Profile Analysis Suite (GEPAS) is one of the most complete and extensively used web-based packages for microarray data analysis. During its more than 5 years of activity it has continuously been updated to keep pace with the state-of-the-art in the changing microarray data analysis arena. GEPAS offers diverse analysis options that include well established as well as novel algorithms for normalization, gene selection, class prediction, clustering and functional profiling of the experiment. New options for time-course (or dose-response) experiments, microarray-based class prediction, new clustering methods and new tests for differential expression have been included. The new pipeliner module allows automating the execution of sequential analysis steps by means of a simple but powerful graphic interface. An extensive re-engineering of GEPAS has been carried out which includes the use of web services and Web 2.0 technology features, a new user interface with persistent sessions and a new extended database of gene identifiers. GEPAS is nowadays the most quoted web tool in its field and it is extensively used by researchers of many countries and its records indicate an average usage rate of 500 experiments per day. GEPAS, is available at http://www.gepas.org. PMID:18508806

  9. Genomic compositions and phylogenetic analysis of Shigella boydii subgroup

    Institute of Scientific and Technical Information of China (English)

    2006-01-01

    Comparative Genomic Hybridization (CGH) microarray analysis was used to compare the genomic compositions of all eighteen Shigella boydii serotype representative strains. The results indicated the genomic "backbone" of this subgroup contained 2552 ORFs homologous to nonpathogenic E. coli K12. Compared with the genome of K12199 ORFs were found to be absent in all S. boydii serotype representatives, including mainly outer membrane protein genes and O-antigen biosynthesis genes. Yet the specific ORFs of S. boydii subgroup contained basically bacteriophage genes and the function unknown (FUN) genes. Some iron metabolism, transport and type II secretion system related genes were found in most representative strains. According to the CGH phylogenetic analysis, the eighteen S. boydii serotype representatives were divided into four groups, in which serotype C13 strain was remarkably distinguished from the other serotype strains. This grouping result corresponded to the distribution of some metabolism related genes. Furthermore, the analysis of genome backbone genes, specific genes, and the phylogenetic trees allowed us to discover the evolution laws of S. boydii and to find out important clues to pathogenesis research, vaccination and the therapeutic medicine development.

  10. Tiling microarray analysis of rice chromosome 10 to identify the transcriptome and relate its expression to chromosomal architecture

    DEFF Research Database (Denmark)

    Li, Lei; Wang, Xiangfeng; Xia, Mian

    2005-01-01

    BACKGROUND: Sequencing and annotation of the genome of rice (Oryza sativa) have generated gene models in numbers that top all other fully sequenced species, with many lacking recognizable sequence homology to known genes. Experimental evaluation of these gene models and identification of new models...... definition of the heterochromatin and euchromatin domains. The heterochromatin domain appears to associate with distinct chromosome level transcriptional activities under normal and stress conditions. CONCLUSION: These results demonstrated the utility of genome tiling microarray in evaluating annotated rice...

  11. A flexible representation of omic knowledge for thorough analysis of microarray data

    Directory of Open Access Journals (Sweden)

    Demura Taku

    2006-03-01

    Full Text Available Abstract Background In order to understand microarray data reasonably in the context of other existing biological knowledge, it is necessary to conduct a thorough examination of the data utilizing every aspect of available omic knowledge libraries. So far, a number of bioinformatics tools have been developed. However, each of them is restricted to deal with one type of omic knowledge, e.g., pathways, interactions or gene ontology. Now that the varieties of omic knowledge are expanding, analysis tools need a way to deal with any type of omic knowledge. Hence, we have designed the Omic Space Markup Language (OSML that can represent a wide range of omic knowledge, and also, we have developed a tool named GSCope3, which can statistically analyze microarray data in comparison with the OSML-formatted omic knowledge data. Results In order to test the applicability of OSML to represent a variety of omic knowledge specifically useful for analysis of Arabidopsis thaliana microarray data, we have constructed a Biological Knowledge Library (BiKLi by converting eight different types of omic knowledge into OSML-formatted datasets. We applied GSCope3 and BiKLi to previously reported A. thaliana microarray data, so as to extract any additional insights from the data. As a result, we have discovered a new insight that lignin formation resists drought stress and activates transcription of many water channel genes to oppose drought stress; and most of the 20S proteasome subunit genes show similar expression profiles under drought stress. In addition to this novel discovery, similar findings previously reported were also quickly confirmed using GSCope3 and BiKLi. Conclusion GSCope3 can statistically analyze microarray data in the context of any OSML-represented omic knowledge. OSML is not restricted to a specific data type structure, but it can represent a wide range of omic knowledge. It allows us to convert new types of omic knowledge into datasets that can be

  12. Genomic DNA enrichment using sequence capture microarrays: a novel approach to discover sequence nucleotide polymorphisms (SNP in Brassica napus L.

    Directory of Open Access Journals (Sweden)

    Wayne E Clarke

    Full Text Available Targeted genomic selection methodologies, or sequence capture, allow for DNA enrichment and large-scale resequencing and characterization of natural genetic variation in species with complex genomes, such as rapeseed canola (Brassica napus L., AACC, 2n=38. The main goal of this project was to combine sequence capture with next generation sequencing (NGS to discover single nucleotide polymorphisms (SNPs in specific areas of the B. napus genome historically associated (via quantitative trait loci -QTL- analysis to traits of agronomical and nutritional importance. A 2.1 million feature sequence capture platform was designed to interrogate DNA sequence variation across 47 specific genomic regions, representing 51.2 Mb of the Brassica A and C genomes, in ten diverse rapeseed genotypes. All ten genotypes were sequenced using the 454 Life Sciences chemistry and to assess the effect of increased sequence depth, two genotypes were also sequenced using Illumina HiSeq chemistry. As a result, 589,367 potentially useful SNPs were identified. Analysis of sequence coverage indicated a four-fold increased representation of target regions, with 57% of the filtered SNPs falling within these regions. Sixty percent of discovered SNPs corresponded to transitions while 40% were transversions. Interestingly, fifty eight percent of the SNPs were found in genic regions while 42% were found in intergenic regions. Further, a high percentage of genic SNPs was found in exons (65% and 64% for the A and C genomes, respectively. Two different genotyping assays were used to validate the discovered SNPs. Validation rates ranged from 61.5% to 84% of tested SNPs, underpinning the effectiveness of this SNP discovery approach. Most importantly, the discovered SNPs were associated with agronomically important regions of the B. napus genome generating a novel data resource for research and breeding this crop species.

  13. New molecular phenotypes in the dst mutants of Arabidopsis revealed by DNA microarray analysis.

    Science.gov (United States)

    Pérez-Amador, M A; Lidder, P; Johnson, M A; Landgraf, J; Wisman, E; Green, P J

    2001-12-01

    In this study, DNA microarray analysis was used to expand our understanding of the dst1 mutant of Arabidopsis. The dst (downstream) mutants were isolated originally as specifically increasing the steady state level and the half-life of DST-containing transcripts. As such, txhey offer a unique opportunity to study rapid sequence-specific mRNA decay pathways in eukaryotes. These mutants show a threefold to fourfold increase in mRNA abundance for two transgenes and an endogenous gene, all containing DST elements, when examined by RNA gel blot analysis; however, they show no visible aberrant phenotype. Here, we use DNA microarrays to identify genes with altered expression levels in dst1 compared with the parental plants. In addition to verifying the increase in the transgene mRNA levels, which were used to isolate these mutants, we were able to identify new genes with altered mRNA abundance in dst1. RNA gel blot analysis confirmed the microarray data for all genes tested and also was used to catalog the first molecular differences in gene expression between the dst1 and dst2 mutants. These differences revealed previously unknown molecular phenotypes for the dst mutants that will be helpful in future analyses. Cluster analysis of genes altered in dst1 revealed new coexpression patterns that prompt new hypotheses regarding the nature of the dst1 mutation and a possible role of the DST-mediated mRNA decay pathway in plants.

  14. Microarray analysis of differentially expressed genes between cysts and trophozoites of Acanthamoeba castellanii.

    Science.gov (United States)

    Moon, Eun-Kyung; Xuan, Ying-Hua; Chung, Dong-Il; Hong, Yeonchul; Kong, Hyun-Hee

    2011-12-01

    Acanthamoeba infection is difficult to treat because of the resistance property of Acanthamoeba cyst against the host immune system, diverse antibiotics, and therapeutic agents. To identify encystation mediating factors of Acanthamoeba, we compared the transcription profile between cysts and trophozoites using microarray analysis. The DNA chip was composed of 12,544 genes based on expressed sequence tag (EST) from an Acanthamoeba ESTs database (DB) constructed in our laboratory, genetic information of Acanthamoeba from TBest DB, and all of Acanthamoeba related genes registered in the NCBI. Microarray analysis indicated that 701 genes showed higher expression than 2 folds in cysts than in trophozoites, and 859 genes were less expressed in cysts than in trophozoites. The results of real-time PCR analysis of randomly selected 9 genes of which expression was increased during cyst formation were coincided well with the microarray results. Eukaryotic orthologous groups (KOG) analysis showed an increment in T article (signal transduction mechanisms) and O article (posttranslational modification, protein turnover, and chaperones) whereas significant decrement of C article (energy production and conversion) during cyst formation. Especially, cystein proteinases showed high expression changes (282 folds) with significant increases in real-time PCR, suggesting a pivotal role of this proteinase in the cyst formation of Acanthamoeba. The present study provides important clues for the identification and characterization of encystation mediating factors of Acanthamoeba.

  15. The integrated microbial genome resource of analysis.

    Science.gov (United States)

    Checcucci, Alice; Mengoni, Alessio

    2015-01-01

    Integrated Microbial Genomes and Metagenomes (IMG) is a biocomputational system that allows to provide information and support for annotation and comparative analysis of microbial genomes and metagenomes. IMG has been developed by the US Department of Energy (DOE)-Joint Genome Institute (JGI). IMG platform contains both draft and complete genomes, sequenced by Joint Genome Institute and other public and available genomes. Genomes of strains belonging to Archaea, Bacteria, and Eukarya domains are present as well as those of viruses and plasmids. Here, we provide some essential features of IMG system and case study for pangenome analysis.

  16. Multi-membership gene regulation in pathway based microarray analysis

    OpenAIRE

    2011-01-01

    This article is available through the Brunel Open Access Publishing Fund. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Background: Gene expression analysis has been intensively researched for more than a decade. Recently, there has been elevated interest in the inte...

  17. Food Microbial Pathogen Detection and Analysis Using DNA Microarray Technologies

    OpenAIRE

    Rasooly, Avraham; Herold, Keith E.

    2008-01-01

    Culture-based methods used for microbial detection and identification are simple to use, relatively inexpensive, and sensitive. However, culture-based methods are too time-consuming for high-throughput testing and too tedious for analysis of samples with multiple organisms and provide little clinical information regarding the pathogen (e.g., antibiotic resistance genes, virulence factors, or strain subtype). DNA-based methods, such as polymerase chain reaction (PCR), overcome some these limit...

  18. High-Resolution Analysis of Gene Copy Number Alterations in Human Prostate Cancer Using CGH on cDNA Microarrays: Impact of Copy Number on Gene Expression

    Directory of Open Access Journals (Sweden)

    Maija Wolf

    2004-05-01

    Full Text Available Identification of target genes for genetic rearrangements in prostate cancer and the impact of copy number changes on gene expression are currently not well understood. Here, we applied high-resolution comparative genomic hybridization (CGH on cDNA microarrays for analysis of prostate cancer cell lines. CGH microarrays identified most of the alterations detected by classical chromosomal CGH, as well as a number of previously unreported alterations. Specific recurrent regions of gain (28 and loss (18 were found, their boundaries defined with sub-megabasepair accuracy. The most common changes included copy number decreases at 13% and gains at iq and 5p. Refined mapping identified several sites, such as at 13q (33-44, 49-51, 74-76 Mbp from the p-telomere, which matched with minimal regions of loss seen in extensive loss of heterozygosity mapping studies of large numbers of tumors. Previously unreported recurrent changes were found at 2p, 2q, 3p, 17q (losses, at 3q, 5p, 6p (gains. Integration of genomic and transcriptomic data revealed the role of individual candidate target genes for genomic alterations as well as a highly significant (P < .0001 overall association between copy number levels and the percentage of differentially expressed genes. Across the genome, the overall impact of copy number on gene expression levels was, to a large extent, attributable to low-level gains and losses of copy number, corresponding to common deletions and gains of often large chromosomal regions.

  19. Statistical analysis of efficient unbalanced factorial designs for two-color microarray experiments.

    Science.gov (United States)

    Tempelman, Robert J

    2008-01-01

    Experimental designs that efficiently embed a fixed effects treatment structure within a random effects design structure typically require a mixed-model approach to data analyses. Although mixed model software tailored for the analysis of two-color microarray data is increasingly available, much of this software is generally not capable of correctly analyzing the elaborate incomplete block designs that are being increasingly proposed and used for factorial treatment structures. That is, optimized designs are generally unbalanced as it pertains to various treatment comparisons, with different specifications of experimental variability often required for different treatment factors. This paper uses a publicly available microarray dataset, as based upon an efficient experimental design, to demonstrate a proper mixed model analysis of a typical unbalanced factorial design characterized by incomplete blocks and hierarchical levels of variability.

  20. TMA Navigator: network inference, patient stratification and survival analysis with tissue microarray data

    OpenAIRE

    Lubbock, A. L. R.; Katz, E; Harrison, D J; Overton, I M

    2013-01-01

    Scottish Funding Council (SFC) and the Chief Scientist’s Office (CSO) (to D.H.); Royal Society of Edinburgh Scottish Government Fellowship co-funded by Marie Curie Actions and the UK Medical Research Council (MRC) (to I.O.). Funding for open access charge: Royal Society of Edinburgh. Tissue microarrays (TMAs) allow multiplexed analysis of tissue samples and are frequently used to estimate biomarker protein expression in tumour biopsies. TMA Navigator (www.tmanavigator.org) is an open acces...

  1. Single primer amplification (SPA) of cDNA for microarray expression analysis

    OpenAIRE

    2003-01-01

    The potential of expression analysis using cDNA microarrays to address complex problems in a wide variety of biological contexts is now being realised. A limiting factor in such analyses is often the amount of RNA required, usually tens of micrograms. To address this problem researchers have turned to methods of improving detection sensitivity, either through increasing fluorescent signal output per mRNA molecule or increasing the amount of target available for labelling by use of an amplific...

  2. High Throughput Phenotypic Analysis of Mycobacterium tuberculosis and Mycobacterium bovis Strains' Metabolism Using Biolog Phenotype Microarrays

    OpenAIRE

    Khatri, Bhagwati; Fielder, Mark; Jones, Gareth; Newell, William; Abu-Oun, Manal; Wheeler, Paul R.

    2013-01-01

    Tuberculosis is a major human and animal disease of major importance worldwide. Genetically, the closely related strains within the Mycobacterium tuberculosis complex which cause disease are well-characterized but there is an urgent need better to understand their phenotypes. To search rapidly for metabolic differences, a working method using Biolog Phenotype MicroArray analysis was developed. Of 380 substrates surveyed, 71 permitted tetrazolium dye reduction, the readout over 7 days in the m...

  3. Review: DNA microarray technology and drug development

    Directory of Open Access Journals (Sweden)

    Sana Khan

    2010-01-01

    Full Text Available On the contrary to slow and non specific traditional drug discovery methods, DNA microarray technology could accelerate the identification of potential drugs for treating diseases like cancer, AIDS and provide fruitful results in the drug discovery. The technique provides efficient automation and maximum flexibility to the researchers and can test thousand compounds at a time. Scientists find DNA microarray useful in disease diagnosis, monitoring desired and adverse outcomes of therapeutic interventions, as well as, in the selection, assessment and quality con-trol of the potential drugs. In the current scenario, where new pathogens are expected every year, DNA microarray promises as an efficient technology to detect new organisms in a short time. Classification of carcinomas at the molecular level and prediction of how various types of tumor respond to different therapeutic agents can be made possible with the use of microarray analysis. Also, microarray technique can prove instrumental in personalized medicines development by providing microarray data of a patient which could be used for identifying diseases, treatment specific to individual and trailing disease prognosis. Microarray analysis could be beneficial in the area of molecular medicines for analysis of genetic variations and functions of genes in normal individuals and diseased conditions. The technique can give satisfactory results in single nucleotide polymorphism (SNP analysis and pharmacogenomics studies. The challenges that arise with the technology are high degree of variability with data obtained, frequent up gradation of methods and machines and lack of trained manpower. Despite this, DNA micro-array promises to be the next generation sequencer which could explain how organisms evolve and adapt looking at the whole genome. In a nutshell, Microarray technology makes it possible for molecular biologists to analyze simultaneously thousands of DNA samples and monitor their

  4. Clinical Presentation and Microarray Analysis of Peruvian Children with Atypical Development and/or Aberrant Behavior

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    Merlin G. Butler

    2014-01-01

    Full Text Available We report our experience with high resolution microarray analysis in infants and young children with developmental disability and/or aberrant behavior enrolled at the Centro Ann Sullivan del Peru in Lima, Peru, a low income country. Buccal cells were collected with cotton swabs from 233 participants for later DNA isolation and identification of copy number variation (deletions/duplications and regions of homozygosity (ROH for estimating consanguinity status in 15 infants and young children (12 males, 3 females; mean age ± SD = 28.1 m ±   7.9 m; age range 14 m–41 m randomly selected for microarray analysis. An adequate DNA yield was found in about one-half of the enrolled participants. Ten participants showed deletions or duplications containing candidate genes reported to impact behavior or cognitive development. Five children had ROHs which could have harbored recessive gene alleles contributing to their clinical presentation. The coefficient of inbreeding was calculated and three participants showed first-second cousin relationships, indicating consanguinity. Our preliminary study showed that DNA isolated from buccal cells using cotton swabs was suboptimal, but yet in a subset of participants the yield was adequate for high resolution microarray analysis and several genes were found that impact development and behavior and ROHs identified to determine consanguinity status.

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

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    Brazma Alvis

    2010-03-01

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

  6. Quality Visualization of Microarray Datasets Using Circos

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    Martin Koch

    2012-08-01

    Full Text Available Quality control and normalization is considered the most important step in the analysis of microarray data. At present there are various methods available for quality assessments of microarray datasets. However there seems to be no standard visualization routine, which also depicts individual microarray quality. Here we present a convenient method for visualizing the results of standard quality control tests using Circos plots. In these plots various quality measurements are drawn in a circular fashion, thus allowing for visualization of the quality and all outliers of each distinct array within a microarray dataset. The proposed method is intended for use with the Affymetrix Human Genome platform (i.e., GPL 96, GPL570 and GPL571. Circos quality measurement plots are a convenient way for the initial quality estimate of Affymetrix datasets that are stored in publicly available databases.

  7. Microarray analysis of a salamander hopeful monster reveals transcriptional signatures of paedomorphic brain development

    Science.gov (United States)

    2010-01-01

    Background The Mexican axolotl (Ambystoma mexicanum) is considered a hopeful monster because it exhibits an adaptive and derived mode of development - paedomorphosis - that has evolved rapidly and independently among tiger salamanders. Unlike related tiger salamanders that undergo metamorphosis, axolotls retain larval morphological traits into adulthood and thus present an adult body plan that differs dramatically from the ancestral (metamorphic) form. The basis of paedomorphic development was investigated by comparing temporal patterns of gene transcription between axolotl and tiger salamander larvae (Ambystoma tigrinum tigrinum) that typically undergo a metamorphosis. Results Transcript abundances from whole brain and pituitary were estimated via microarray analysis on four different days post hatching (42, 56, 70, 84 dph) and regression modeling was used to independently identify genes that were differentially expressed as a function of time in both species. Collectively, more differentially expressed genes (DEGs) were identified as unique to the axolotl (n = 76) and tiger salamander (n = 292) than were identified as shared (n = 108). All but two of the shared DEGs exhibited the same temporal pattern of expression and the unique genes tended to show greater changes later in the larval period when tiger salamander larvae were undergoing anatomical metamorphosis. A second, complementary analysis that directly compared the expression of 1320 genes between the species identified 409 genes that differed as a function of species or the interaction between time and species. Of these 409 DEGs, 84% exhibited higher abundances in tiger salamander larvae at all sampling times. Conclusions Many of the unique tiger salamander transcriptional responses are probably associated with metamorphic biological processes. However, the axolotl also showed unique patterns of transcription early in development. In particular, the axolotl showed a genome-wide reduction in mRNA abundance

  8. Microarray analysis of a salamander hopeful monster reveals transcriptional signatures of paedomorphic brain development

    Directory of Open Access Journals (Sweden)

    Putta Srikrishna

    2010-06-01

    Full Text Available Abstract Background The Mexican axolotl (Ambystoma mexicanum is considered a hopeful monster because it exhibits an adaptive and derived mode of development - paedomorphosis - that has evolved rapidly and independently among tiger salamanders. Unlike related tiger salamanders that undergo metamorphosis, axolotls retain larval morphological traits into adulthood and thus present an adult body plan that differs dramatically from the ancestral (metamorphic form. The basis of paedomorphic development was investigated by comparing temporal patterns of gene transcription between axolotl and tiger salamander larvae (Ambystoma tigrinum tigrinum that typically undergo a metamorphosis. Results Transcript abundances from whole brain and pituitary were estimated via microarray analysis on four different days post hatching (42, 56, 70, 84 dph and regression modeling was used to independently identify genes that were differentially expressed as a function of time in both species. Collectively, more differentially expressed genes (DEGs were identified as unique to the axolotl (n = 76 and tiger salamander (n = 292 than were identified as shared (n = 108. All but two of the shared DEGs exhibited the same temporal pattern of expression and the unique genes tended to show greater changes later in the larval period when tiger salamander larvae were undergoing anatomical metamorphosis. A second, complementary analysis that directly compared the expression of 1320 genes between the species identified 409 genes that differed as a function of species or the interaction between time and species. Of these 409 DEGs, 84% exhibited higher abundances in tiger salamander larvae at all sampling times. Conclusions Many of the unique tiger salamander transcriptional responses are probably associated with metamorphic biological processes. However, the axolotl also showed unique patterns of transcription early in development. In particular, the axolotl showed a genome

  9. An Xq22.3 duplication detected by comparative genomic hybridization microarray (Array-CGH) defines a new locus (FGS5) for FG syndrome.

    Science.gov (United States)

    Jehee, Fernanda Sarquis; Rosenberg, Carla; Krepischi-Santos, Ana Cristina; Kok, Fernando; Knijnenburg, Jeroen; Froyen, Guy; Vianna-Morgante, Angela M; Opitz, John M; Passos-Bueno, Maria Rita

    2005-12-15

    FG syndrome is an X-linked multiple congenital anomalies (MCA) syndrome. It has been mapped to four distinct loci FGS1-4, through linkage analysis (Xq13, Xp22.3, and Xp11.4-p11.3) and based on the breakpoints of an X chromosome inversion (Xq11:Xq28), but so far no gene has been identified. We describe a boy with FG syndrome who has an inherited duplication at band Xq22.3 detected by comparative genomic hybridization microarray (Array-CGH). These duplication maps outside all four loci described so far for FG syndrome, representing therefore a new locus, which we propose to be called FGS5. MID2, a gene closely related to MID1, which is known to be mutated in Opitz G/BBB syndrome, maps within the duplicated segment of our patient. Since FG and Opitz G/BBB syndromes share many manifestations we considered MID2 a candidate gene for FG syndrome. We also discuss the involvement of other potential genes within the duplicated segment and its relationship with clinical symptoms of our patient, as well as the laboratory abnormalities found in his mother, a carrier of the duplication.

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

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    Song Joon J

    2007-03-01

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

  11. Outcome-Driven Cluster Analysis with Application to Microarray Data.

    Directory of Open Access Journals (Sweden)

    Jessie J Hsu

    Full Text Available One goal of cluster analysis is to sort characteristics into groups (clusters so that those in the same group are more highly correlated to each other than they are to those in other groups. An example is the search for groups of genes whose expression of RNA is correlated in a population of patients. These genes would be of greater interest if their common level of RNA expression were additionally predictive of the clinical outcome. This issue arose in the context of a study of trauma patients on whom RNA samples were available. The question of interest was whether there were groups of genes that were behaving similarly, and whether each gene in the cluster would have a similar effect on who would recover. For this, we develop an algorithm to simultaneously assign characteristics (genes into groups of highly correlated genes that have the same effect on the outcome (recovery. We propose a random effects model where the genes within each group (cluster equal the sum of a random effect, specific to the observation and cluster, and an independent error term. The outcome variable is a linear combination of the random effects of each cluster. To fit the model, we implement a Markov chain Monte Carlo algorithm based on the likelihood of the observed data. We evaluate the effect of including outcome in the model through simulation studies and describe a strategy for prediction. These methods are applied to trauma data from the Inflammation and Host Response to Injury research program, revealing a clustering of the genes that are informed by the recovery outcome.

  12. Microarray gene expression profiling and analysis in renal cell carcinoma

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    Sadhukhan Provash

    2004-06-01

    Full Text Available Abstract Background Renal cell carcinoma (RCC is the most common cancer in adult kidney. The accuracy of current diagnosis and prognosis of the disease and the effectiveness of the treatment for the disease are limited by the poor understanding of the disease at the molecular level. To better understand the genetics and biology of RCC, we profiled the expression of 7,129 genes in both clear cell RCC tissue and cell lines using oligonucleotide arrays. Methods Total RNAs isolated from renal cell tumors, adjacent normal tissue and metastatic RCC cell lines were hybridized to affymatrix HuFL oligonucleotide arrays. Genes were categorized into different functional groups based on the description of the Gene Ontology Consortium and analyzed based on the gene expression levels. Gene expression profiles of the tissue and cell line samples were visualized and classified by singular value decomposition. Reverse transcription polymerase chain reaction was performed to confirm the expression alterations of selected genes in RCC. Results Selected genes were annotated based on biological processes and clustered into functional groups. The expression levels of genes in each group were also analyzed. Seventy-four commonly differentially expressed genes with more than five-fold changes in RCC tissues were identified. The expression alterations of selected genes from these seventy-four genes were further verified using reverse transcription polymerase chain reaction (RT-PCR. Detailed comparison of gene expression patterns in RCC tissue and RCC cell lines shows significant differences between the two types of samples, but many important expression patterns were preserved. Conclusions This is one of the initial studies that examine the functional ontology of a large number of genes in RCC. Extensive annotation, clustering and analysis of a large number of genes based on the gene functional ontology revealed many interesting gene expression patterns in RCC. Most

  13. Multicriteria Gene Screening for Analysis of Differential Expression with DNA Microarrays

    Directory of Open Access Journals (Sweden)

    Alfred O. Hero

    2004-01-01

    Full Text Available This paper introduces a statistical methodology for the identification of differentially expressed genes in DNA microarray experiments based on multiple criteria. These criteria are false discovery rate (FDR, variance-normalized differential expression levels (paired t statistics, and minimum acceptable difference (MAD. The methodology also provides a set of simultaneous FDR confidence intervals on the true expression differences. The analysis can be implemented as a two-stage algorithm in which there is an initial screen that controls only FDR, which is then followed by a second screen which controls both FDR and MAD. It can also be implemented by computing and thresholding the set of FDR P values for each gene that satisfies the MAD criterion. We illustrate the procedure to identify differentially expressed genes from a wild type versus knockout comparison of microarray data.

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

    DEFF Research Database (Denmark)

    Skov, Vibe

    2007-01-01

    Polycystic ovary syndrome (PCOS) affects 5-10 % of women during their reproductive age and the incidence of the disease is increasing worldwide. More than 50 % of women with PCOS are insulin resistant leading to an increased risk of type 2 diabetes (T2D) and cardiovascular diseases. However...... 1 and 2, the application of gene expression microarrays from Affymetrix was combined with global pathway analysis using GenMAPP and GSEA and subsequent validation by quantitative real-time PCR (q-RT-PCR). Impaired insulin-stimulated glucose metabolism in women with PCOS was associated with reduced...... comparable to other commercial and custom made microarrays and is a cost-effective alternative especially in larger epidemiological studies....

  15. Microarray based comparative genomic hybridization testing in deletion bearing patients with Angelman syndrome: genotype-phenotype correlations.

    Science.gov (United States)

    Sahoo, T; Peters, S U; Madduri, N S; Glaze, D G; German, J R; Bird, L M; Barbieri-Welge, R; Bichell, T J; Beaudet, A L; Bacino, C A

    2006-06-01

    Angelman syndrome (AS) is a neurodevelopmental disorder characterised by severe mental retardation, dysmorphic features, ataxia, seizures, and typical behavioural characteristics, including a happy sociable disposition. AS is caused by maternal deficiency of UBE3A (E6 associated protein ubiquitin protein ligase 3A gene), located in an imprinted region on chromosome 15q11-q13. Although there are four different molecular types of AS, deletions of the 15q11-q13 region account for approximately 70% of the AS patients. These deletions are usually detected by fluorescence in situ hybridisation studies. The deletions can also be subclassified based on their size into class I and class II, with the former being larger and encompassing the latter. We studied 22 patients with AS due to microdeletions using a microarray based comparative genomic hybridisation (array CGH) assay to define the deletions and analysed their phenotypic severity, especially expression of the autism phenotype, in order to establish clinical correlations. Overall, children with larger, class I deletions were significantly more likely to meet criteria for autism, had lower cognitive scores, and lower expressive language scores compared with children with smaller, class II deletions. Children with class I deletions also required more medications to control their seizures than did those in the class II group. There are four known genes (NIPA1, NIPA2, CYFIP1, & GCP5) that are affected by class I but not class II deletions, thus raising the possibility of a role for these genes in autism as well as the development of expressive language skills.

  16. A high-density Diversity Arrays Technology (DArT microarray for genome-wide genotyping in Eucalyptus

    Directory of Open Access Journals (Sweden)

    Myburg Alexander A

    2010-06-01

    Full Text Available Abstract Background A number of molecular marker technologies have allowed important advances in the understanding of the genetics and evolution of Eucalyptus, a genus that includes over 700 species, some of which are used worldwide in plantation forestry. Nevertheless, the average marker density achieved with current technologies remains at the level of a few hundred markers per population. Furthermore, the transferability of markers produced with most existing technology across species and pedigrees is usually very limited. High throughput, combined with wide genome coverage and high transferability are necessary to increase the resolution, speed and utility of molecular marker technology in eucalypts. We report the development of a high-density DArT genome profiling resource and demonstrate its potential for genome-wide diversity analysis and linkage mapping in several species of Eucalyptus. Findings After testing several genome complexity reduction methods we identified the PstI/TaqI method as the most effective for Eucalyptus and developed 18 genomic libraries from PstI/TaqI representations of 64 different Eucalyptus species. A total of 23,808 cloned DNA fragments were screened and 13,300 (56% were found to be polymorphic among 284 individuals. After a redundancy analysis, 6,528 markers were selected for the operational array and these were supplemented with 1,152 additional clones taken from a library made from the E. grandis tree whose genome has been sequenced. Performance validation for diversity studies revealed 4,752 polymorphic markers among 174 individuals. Additionally, 5,013 markers showed segregation when screened using six inter-specific mapping pedigrees, with an average of 2,211 polymorphic markers per pedigree and a minimum of 859 polymorphic markers that were shared between any two pedigrees. Conclusions This operational DArT array will deliver 1,000-2,000 polymorphic markers for linkage mapping in most eucalypt pedigrees

  17. Implementing an online tool for genome-wide validation of survival-associated biomarkers in ovarian-cancer using microarray data from 1287 patients

    DEFF Research Database (Denmark)

    Győrffy, Balázs; Lánczky, András; Szállási, Zoltán

    2012-01-01

    The validation of prognostic biomarkers in large independent patient cohorts is a major bottleneck in ovarian cancer research. We implemented an online tool to assess the prognostic value of the expression levels of all microarray-quantified genes in ovarian cancer patients. First, a database was...... biomarker validation platform that mines all available microarray data to assess the prognostic power of 22 277 genes in 1287 ovarian cancer patients. We specifically used this tool to evaluate the effect of 37 previously published biomarkers on ovarian cancer prognosis.......The validation of prognostic biomarkers in large independent patient cohorts is a major bottleneck in ovarian cancer research. We implemented an online tool to assess the prognostic value of the expression levels of all microarray-quantified genes in ovarian cancer patients. First, a database...... was set up using gene expression data and survival information of 1287 ovarian cancer patients downloaded from Gene Expression Omnibus and The Cancer Genome Atlas (Affymetrix HG-U133A, HG-U133A 2.0, and HG-U133 Plus 2.0 microarrays). After quality control and normalization, only probes present on all...

  18. Visualization and analysis of microarray and gene ontology data with treemaps

    Directory of Open Access Journals (Sweden)

    Babaria Ketan

    2004-06-01

    Full Text Available Abstract Background The increasing complexity of genomic data presents several challenges for biologists. Limited computer monitor views of data complexity and the dynamic nature of data in the midst of discovery increase the challenge of integrating experimental results with information resources. The use of Gene Ontology enables researchers to summarize results of quantitative analyses in this framework, but the limitations of typical browser presentation restrict data access. Results Here we describe extensions to the treemap design to visualize and query genome data. Treemaps are a space-filling visualization technique for hierarchical structures that show attributes of leaf nodes by size and color-coding. Treemaps enable users to rapidly compare sizes of nodes and sub-trees, and we use Gene Ontology categories, levels of RNA, and other quantitative attributes of DNA microarray experiments as examples. Our implementation of treemaps, Treemap 4.0, allows user-defined filtering to focus on the data of greatest interest, and these queried files can be exported for secondary analyses. Links to model system web pages from Treemap 4.0 enable users access to details about specific genes without leaving the query platform. Conclusions Treemaps allow users to view and query the data from an experiment on a single computer monitor screen. Treemap 4.0 can be used to visualize various genome data, and is particularly useful for revealing patterns and details within complex data sets.

  19. Development of a Feature and Template-Assisted Assembler and Application to the Analysis of a Foot-and-Mouth Disease Virus Genotyping Microarray

    Science.gov (United States)

    Rowland, Jessica M.; Grau, Frederic R.; McIntosh, Michael T.

    2017-01-01

    Several RT-PCR and genome sequencing strategies exist for the resolution of Foot-and-Mouth Disease virus (FMDV). While these approaches are relatively straightforward, they can be vulnerable to failure due to the unpredictable nature of FMDV genome sequence variations. Sequence independent single primer amplification (SISPA) followed by genotyping microarray offers an attractive unbiased approach to FMDV characterization. Here we describe a custom FMDV microarray and a companion feature and template-assisted assembler software (FAT-assembler) capable of resolving virus genome sequence using a moderate number of conserved microarray features. The results demonstrate that this approach may be used to rapidly characterize naturally occurring FMDV as well as an engineered chimeric strain of FMDV. The FAT-assembler, while applied to resolving FMDV genomes, represents a new bioinformatics approach that should be broadly applicable to interpreting microarray genotyping data for other viruses or target organisms. PMID:28045937

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

    Directory of Open Access Journals (Sweden)

    Jason H. Moore

    2007-01-01

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

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

    Directory of Open Access Journals (Sweden)

    Richardson Andrea L

    2011-10-01

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

  2. Protein Microarrays Technology and Its Application in Genome-Wide Posttranslational Modification%蛋白质芯片技术及其在全基因组翻译后修饰分析中的应用

    Institute of Scientific and Technical Information of China (English)

    眭维国; 王惠; 曹翠辉; 薛雯; 陈洁晶

    2013-01-01

    Protein microarrays technology is an important part in the current biological research. It can be used to study the interactions of protein-DNA,protein-ligand,protein-protein. In recent years,its application in the biochemical analysis of genome-wide has obtained remarkable achievement. Here is to make a review focusing on protein microarrays technology and its application in the analysis of genome-wide post-translational modification.%蛋白质芯片技术可用于研究蛋白质-DNA、蛋白质-配基和蛋白质与蛋白质之间的相互作用,是当前生物科学研究中的重要内容.近年来,运用蛋白质芯片技术对全基因组进行生物化学分析的应用取得令人瞩目的 成就.现着重总结蛋白质芯片技术及其在全基因组翻译后修饰分析中的应用.

  3. High-content single-cell analysis on-chip using a laser microarray scanner.

    Science.gov (United States)

    Zhou, Jing; Wu, Yu; Lee, Sang-Kwon; Fan, Rong

    2012-12-07

    High-content cellomic analysis is a powerful tool for rapid screening of cellular responses to extracellular cues and examination of intracellular signal transduction pathways at the single-cell level. In conjunction with microfluidics technology that provides unique advantages in sample processing and precise control of fluid delivery, it holds great potential to transform lab-on-a-chip systems for high-throughput cellular analysis. However, high-content imaging instruments are expensive, sophisticated, and not readily accessible. Herein, we report on a laser scanning cytometry approach that exploits a bench-top microarray scanner as an end-point reader to perform rapid and automated fluorescence imaging of cells cultured on a chip. Using high-content imaging analysis algorithms, we demonstrated multiplexed measurements of morphometric and proteomic parameters from all single cells. Our approach shows the improvement of both sensitivity and dynamic range by two orders of magnitude as compared to conventional epifluorescence microscopy. We applied this technology to high-throughput analysis of mesenchymal stem cells on an extracellular matrix protein array and characterization of heterotypic cell populations. This work demonstrates the feasibility of a laser microarray scanner for high-content cellomic analysis and opens up new opportunities to conduct informative cellular analysis and cell-based screening in the lab-on-a-chip systems.

  4. SIGMA2: A system for the integrative genomic multi-dimensional analysis of cancer genomes, epigenomes, and transcriptomes

    Directory of Open Access Journals (Sweden)

    MacAulay Calum

    2008-10-01

    Full Text Available Abstract Background High throughput microarray technologies have afforded the investigation of genomes, epigenomes, and transcriptomes at unprecedented resolution. However, software packages to handle, analyze, and visualize data from these multiple 'omics disciplines have not been adequately developed. Results Here, we present SIGMA2, a system for the integrative genomic multi-dimensional analysis of cancer genomes, epigenomes, and transcriptomes. Multi-dimensional datasets can be simultaneously visualized and analyzed with respect to each dimension, allowing combinatorial integration of the different assays belonging to the different 'omics. Conclusion The identification of genes altered at multiple levels such as copy number, loss of heterozygosity (LOH, DNA methylation and the detection of consequential changes in gene expression can be concertedly performed, establishing SIGMA2 as a novel tool to facilitate the high throughput systems biology analysis of cancer.

  5. Microarray analysis of RNA extracted from formalin-fixed, paraffin-embedded and matched fresh-frozen ovarian adenocarcinomas

    Directory of Open Access Journals (Sweden)

    Wu Thomas D

    2009-05-01

    Full Text Available Abstract Background Gene expression profiling of formalin-fixed, paraffin-embedded (FFPE samples represents a valuable approach for advancing oncology diagnostics and enhancing retrospective clinical studies; however, at present, this methodology still requires optimization and thus has not been extensively used. Here, we utilized thorough quality control methods to assess RNA extracted from FFPE samples and then compared it to RNA extracted from matched fresh-frozen (FF counterparts. We preformed genome-wide expression profiling of FF and FFPE ovarian serous adenocarcinoma sample pairs and compared their gene signatures to normal ovary samples. Methods RNA from FFPE samples was extracted using two different methods, Ambion and Agencourt, and its quality was determined by profiling starting total RNA on Bioanalyzer and by amplifying increasing size fragments of beta actin (ACTB and claudin 3 (CLDN3 by reverse-transcriptase polymerase chain reaction. Five matched FF and FFPE ovarian serous adenocarcinoma samples, as well as a set of normal ovary samples, were profiled using whole genome Agilent microarrays. Reproducibility of the FF and FFPE replicates was measured using Pearson correlation, whereas comparison between the FF and FFPE samples was done using a Z-score analysis. Results Data analysis showed high reproducibility of expression within each FF and FFPE method, whereas matched FF and FFPE pairs demonstrated lower similarity, emphasizing an inherent difference between the two sample types. Z-score analysis of matched FF and FFPE samples revealed good concordance of top 100 differentially expressed genes with the highest correlation of 0.84. Genes characteristic of ovarian serous adenocarcinoma, including a well known marker CLDN3, as well as potentially some novel markers, were identified by comparing gene expression profiles of ovarian adenocarcinoma to those of normal ovary. Conclusion Conclusively, we showed that systematic assessment

  6. Screening for candidate genes related to breast cancer with cDNA microarray analysis

    Institute of Scientific and Technical Information of China (English)

    Yu-Juan Xiang; Zhi-Gang Yu; Ming-Ming Guo; Qin-Ye Fu; Zhong-Bing Ma; De-Zong Gao; Qiang Zhang; Yu-Yang Li; Liang Li; Lu Liu; Chun-Miao Ye

    2015-01-01

    Objective: The aim of this study was to reveal the exact changes during the occurrence of breast cancer to explore significant new and promising genes or factors related to this disease. Methods: We compared the gene expression profiles of breast cancer tissues with its uninvolved normal breast tissues as controls using the cDNA microarray analysis in seven breast cancer patients. Further, one representative gene, named IFI30, was quanti-tatively analyzed by real-time PCR to confirm the result of the cDNA microarray analysis. Results: A total of 427 genes were identified with significantly differential expression, 221 genes were up-regulated and 206 genes were down-regulated. And the result of cDNA microarray analysis was validated by detection of IFI30 mRNA level changes by real-time PCR. Genes for cell proliferation, cell cycle, cell division, mitosis, apoptosis, and immune response were enriched in the up-regulated genes, while genes for cell adhesion, proteolysis, and transport were significantly enriched in the down-regulated genes in breast cancer tissues compared with normal breast tissues by a gene ontology analysis. Conclusion: Our present study revealed a range of differentially expressed genes between breast cancer tissues and normal breast tissues, and provide candidate genes for further study focusing on the pathogenesis and new biomarkers for breast cancer. Copyright © 2015, Chinese Medical Association Production. Production and hosting by Elsevier B.V. on behalf of KeAi Communications Co., Ltd. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).

  7. A two-genome microarray for the rice pathogens Xanthomonas oryzae pv. oryzae and X. oryzae pv. oryzicola and its use in the discovery of a difference in their regulation of hrp genes

    Directory of Open Access Journals (Sweden)

    Lin Ye

    2008-06-01

    Full Text Available Abstract Background Xanthomonas oryzae pv. oryzae (Xoo and X. oryzae pv. oryzicola (Xoc are bacterial pathogens of the worldwide staple and grass model, rice. Xoo and Xoc are closely related but Xoo invades rice vascular tissue to cause bacterial leaf blight, a serious disease of rice in many parts of the world, and Xoc colonizes the mesophyll parenchyma to cause bacterial leaf streak, a disease of emerging importance. Both pathogens depend on hrp genes for type III secretion to infect their host. We constructed a 50–70 mer oligonucleotide microarray based on available genome data for Xoo and Xoc and compared gene expression in Xoo strains PXO99A and Xoc strain BLS256 grown in the rich medium PSB vs. XOM2, a minimal medium previously reported to induce hrp genes in Xoo strain T7174. Results Three biological replicates of the microarray experiment to compare global gene expression in representative strains of Xoo and Xoc grown in PSB vs. XOM2 were carried out. The non-specific error rate and the correlation coefficients across biological replicates and among duplicate spots revealed that the microarray data were robust. 247 genes of Xoo and 39 genes of Xoc were differentially expressed in the two media with a false discovery rate of 5% and with a minimum fold-change of 1.75. Semi-quantitative-RT-PCR assays confirmed differential expression of each of 16 genes each for Xoo and Xoc selected for validation. The differentially expressed genes represent 17 functional categories. Conclusion We describe here the construction and validation of a two-genome microarray for the two pathovars of X. oryzae. Microarray analysis revealed that using representative strains, a greater number of Xoo genes than Xoc genes are differentially expressed in XOM2 relative to PSB, and that these include hrp genes and other genes important in interactions with rice. An exception was the rax genes, which are required for production of the host resistance elicitor AvrXa21

  8. Coronavirus Genomics and Bioinformatics Analysis

    Directory of Open Access Journals (Sweden)

    Kwok-Yung Yuen

    2010-08-01

    Full Text Available The drastic increase in the number of coronaviruses discovered and coronavirus genomes being sequenced have given us an unprecedented opportunity to perform genomics and bioinformatics analysis on this family of viruses. Coronaviruses possess the largest genomes (26.4 to 31.7 kb among all known RNA viruses, with G + C contents varying from 32% to 43%. Variable numbers of small ORFs are present between the various conserved genes (ORF1ab, spike, envelope, membrane and nucleocapsid and downstream to nucleocapsid gene in different coronavirus lineages. Phylogenetically, three genera, Alphacoronavirus, Betacoronavirus and Gammacoronavirus, with Betacoronavirus consisting of subgroups A, B, C and D, exist. A fourth genus, Deltacoronavirus, which includes bulbul coronavirus HKU11, thrush coronavirus HKU12 and munia coronavirus HKU13, is emerging. Molecular clock analysis using various gene loci revealed that the time of most recent common ancestor of human/civet SARS related coronavirus to be 1999-2002, with estimated substitution rate of 4´10-4 to 2´10-2 substitutions per site per year. Recombination in coronaviruses was most notable between different strains of murine hepatitis virus (MHV, between different strains of infectious bronchitis virus, between MHV and bovine coronavirus, between feline coronavirus (FCoV type I and canine coronavirus generating FCoV type II, and between the three genotypes of human coronavirus HKU1 (HCoV-HKU1. Codon usage bias in coronaviruses were observed, with HCoV-HKU1 showing the most extreme bias, and cytosine deamination and selection of CpG suppressed clones are the two major independent biological forces that shape such codon usage bias in coronaviruses.

  9. Identification of differentially expressed genes in mouse kidney after irradiation using microarray analysis.

    Science.gov (United States)

    Kruse, Jacqueline J C M; te Poele, Johannes A M; Velds, Arno; Kerkhoven, Ron M; Boersma, Liesbeth J; Russell, Nicola S; Stewart, Fiona A

    2004-01-01

    Irradiation of the kidney induces dose-dependent, progressive renal functional impairment, which is partly mediated by vascular damage. The molecular mechanisms underlying the development of radiation-induced nephropathy are unclear. Given the complexity of radiation-induced responses, microarrays may offer new opportunities to identify a wider range of genes involved in the development of radiation injury. The aim of the present study was to determine whether microarrays are a useful tool for identifying time-related changes in gene expression and potential mechanisms of radiation-induced nephropathy. Microarray experiments were performed using amplified RNA from irradiated mouse kidneys (1 x 16 Gy) and from sham-irradiated control tissue at different intervals (1-30 weeks) after irradiation. After normalization procedures (using information from straight-color, color-reverse and self-self experiments), the differentially expressed genes were identified. Control and repeat experiments were done to confirm that the observations were not artifacts of the array procedure (RNA amplification, probe synthesis, hybridizations and data analysis). To provide independent confirmation of microarray data, semi-quantitative PCR was performed on a selection of genes. At 1 week after irradiation (before the onset of vascular and functional damage), 16 genes were significantly up-regulated and 9 genes were down-regulated. During the period of developing nephropathy (10 to 20 weeks), 31 and 42 genes were up-regulated and 9 and 4 genes were down-regulated. At the later time of 30 weeks, the vast majority of differentially expressed genes (191 out of 203) were down-regulated. Potential genes of interest included TSA-1 (also known as Ly6e) and Jagged 1 (Jag1). Increased expression of TSA-1, a member of the Ly-6 family, has previously been reported in response to proteinuria. Jagged 1, a ligand for the Notch receptor, is known to play a role in angiogenesis, and is particularly

  10. Analysis of microarray leukemia data using an efficient MapReduce-based K-nearest-neighbor classifier.

    Science.gov (United States)

    Kumar, Mukesh; Rath, Nitish Kumar; Rath, Santanu Kumar

    2016-04-01

    Microarray-based gene expression profiling has emerged as an efficient technique for classification, prognosis, diagnosis, and treatment of cancer. Frequent changes in the behavior of this disease generates an enormous volume of data. Microarray data satisfies both the veracity and velocity properties of big data, as it keeps changing with time. Therefore, the analysis of microarray datasets in a small amount of time is essential. They often contain a large amount of expression, but only a fraction of it comprises genes that are significantly expressed. The precise identification of genes of interest that are responsible for causing cancer are imperative in microarray data analysis. Most existing schemes employ a two-phase process such as feature selection/extraction followed by classification. In this paper, various statistical methods (tests) based on MapReduce are proposed for selecting relevant features. After feature selection, a MapReduce-based K-nearest neighbor (mrKNN) classifier is also employed to classify microarray data. These algorithms are successfully implemented in a Hadoop framework. A comparative analysis is done on these MapReduce-based models using microarray datasets of various dimensions. From the obtained results, it is observed that these models consume much less execution time than conventional models in processing big data. Copyright © 2016 Elsevier Inc. All rights reserved.

  11. Microarray analysis of gene expression profiles in the bovine mammary gland during lactation

    Institute of Scientific and Technical Information of China (English)

    2010-01-01

    Mammary glands undergo functional and metabolic changes during virgin,lactation and dry periods.A total of 122 genes were identified as differentially expressed,including 79 up-regulated and 43 down-regulated genes during lactation compared with virgin and dry periods.Gene ontology analysis showed the functional classification of the up-regulated genes in lactation,including transport,biosynthetic process,signal transduction,catalytic activity,immune system process,cell death,and positive regulation of the developmental process.Microarray data clarified molecular events in bovine mammary gland lactation.

  12. Microarray analysis in caudal medulla of cattle orally challenged with bovine spongiform encephalopathy.

    Science.gov (United States)

    Almeida, L M; Basu, U; Williams, J L; Moore, S S; Guan, L L

    2011-10-25

    Bovine spongiform encephalopathy (BSE) is a fatal disorder in cattle characterized by progressive neurodegeneration of the central nervous system. We investigated the molecular mechanisms involved in neurodegeneration during prion infection through the identification of genes that are differentially expressed (DE) between experimentally infected and non-challenged cattle. Gene expression of caudal medulla from control and orally infected animals was compared by microarray analysis using 24,000 bovine oligonucleotides representing 16,846 different genes to identify DE genes associated with BSE disease. In total, 182 DE genes were identified between normal and BSE-infected tissues (>2.0-fold change, P bovine species.

  13. Time-course microarray analysis for identifying candidate genes involved in obesity-associated pathological changes in the mouse colon.

    Science.gov (United States)

    Bae, Yun Jung; Kim, Sung-Eun; Hong, Seong Yeon; Park, Taesun; Lee, Sang Gyu; Choi, Myung-Sook; Sung, Mi-Kyung

    2016-01-01

    Obesity is known to increase the risk of colorectal cancer. However, mechanisms underlying the pathogenesis of obesity-induced colorectal cancer are not completely understood. The purposes of this study were to identify differentially expressed genes in the colon of mice with diet-induced obesity and to select candidate genes as early markers of obesity-associated abnormal cell growth in the colon. C57BL/6N mice were fed normal diet (11% fat energy) or high-fat diet (40% fat energy) and were euthanized at different time points. Genome-wide expression profiles of the colon were determined at 2, 4, 8, and 12 weeks. Cluster analysis was performed using expression data of genes showing log2 fold change of ≥1 or ≤-1 (twofold change), based on time-dependent expression patterns, followed by virtual network analysis. High-fat diet-fed mice showed significant increase in body weight and total visceral fat weight over 12 weeks. Time-course microarray analysis showed that 50, 47, 36, and 411 genes were differentially expressed at 2, 4, 8, and 12 weeks, respectively. Ten cluster profiles representing distinguishable patterns of genes differentially expressed over time were determined. Cluster 4, which consisted of genes showing the most significant alterations in expression in response to high-fat diet over 12 weeks, included Apoa4 (apolipoprotein A-IV), Ppap2b (phosphatidic acid phosphatase type 2B), Cel (carboxyl ester lipase), and Clps (colipase, pancreatic), which interacted strongly with surrounding genes associated with colorectal cancer or obesity. Our data indicate that Apoa4, Ppap2b, Cel, and Clps are candidate early marker genes associated with obesity-related pathological changes in the colon. Genome-wide analyses performed in the present study provide new insights on selecting novel genes that may be associated with the development of diseases of the colon.

  14. A Therapeutic Targeting Identification from Microarray Data and Quantitative Network Analysis

    Directory of Open Access Journals (Sweden)

    Hongliang Hu

    2015-03-01

    Full Text Available Personalized therapy is “the right drug for the right patient at the right time”. Here we reported a case of personalized therapy using gene expression signature (GES related drug discovery to treat a patient with drug-resistant metastases from breast-tumor. Methods: After mRNA obtained from metastatic liver tissue was performed by microarray, GES of genomic profiles were uncovered by bioinformatics tool and targeting drugs related with GES were mined by drug-bank. Several targeting-drugs approved by FDA were selected to treat the patient. Results: 1198 genes were uncovered for the higher expression by two-fold to compare normal liver specimens in which 10 of mined genes were identified as set-1 GES for metastasis and 16 of genes were uncovered as set-2 directly for primary breast tumor. Drug-bank platform were used to discover drugs for target set-1/2 genes. Eventually, medropxyoprogesterone (MPA targeting set-I gene and doxorubicin targeting set-2 gene were selected for the patient because the two drugs have already been approved by FDA. After doxorubicin and MPA were administered, patient's metastatic-tumor showed complete response. Conclusions: We not only analyze genomic expression profiles but also discover sensitive compounds for drug-resistant tumor. We successfully select drugs approved by FDA to treat the patient.

  15. Differentiating pancreatic lesions by Microarray and QPCR analysis of pancreatic juice RNAs

    NARCIS (Netherlands)

    C.D. Rogers; N. Fukushima; N. Sato; C. Shi; N. Prasad; S.R. Hustinx; H. Matsubayashi; M. Canto; J.R. Eshleman; R.H. Hruban; M. Goggins

    2006-01-01

    Background: The gene expression profile of pancreatic cancer is significantly different from that of normal pancreas. Differences in gene expression are detectable using microarrays, but microarrays have traditionally been applied to pancreatic cancer tissue obtained from surgical resection. We hypo

  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-based technol...

  17. DEVELOPMENT OF NEW SEQUENCING TECHNOLOGIES AND THEIR APPLICATION IN GENOME ANALYSIS OF DOMESTIC ANIMALS

    Directory of Open Access Journals (Sweden)

    Kristina Gvozdanović

    2015-12-01

    Full Text Available Sequencing and detailed study of the genom of domestic animals began in the middle of the last century. It was primarily referred to development of the first generation sequencing methods, i.e. Sanger sequencing method. Next generation sequencing methods are currently the most common methods in the analysis of domestic animals genom. The application of these methods gave us up to 100 time more data in comparison with Sanger method. Analyses including RNA sequencing, genotyping of whole genome, immunoprecipitation associated with DNA microarrays, detection ofmutations and inherited diseases, sequencing ofthemitochondrial genome and many others have been conducted with development and application of new sequencing methods since 2005 until today. Application of new sequencing methods in the analysis ofdomestic animal genome provides better understanding of the genetic basis for important production traits which could help in improving the livestock production.

  18. Use of culture, PCR analysis, and DNA microarrays for detection of Campylobacter jejuni and Campylobacter coli from chicken feces

    DEFF Research Database (Denmark)

    Keramas, Georgios; Bang, Dang Duong; Lund, Marianne

    2004-01-01

    A DNA microarray for detection of Campylobacter spp. was recently developed and applied to detect Campylobacter spp. directly from chicken feces. Sixty-five pooled chicken cloacal swab samples from 650 individual broiler chickens were included in the study. The results of Campylobacter sp....... detection obtained with DNA microarrays were compared to those obtained by conventional culture and gel electrophoresis. By conventional culture, 60% of the samples were positive for either Campylobacter jejuni or Campylobacter coli. By PCR and capillary electrophoresis, 95% of the samples were positive...... for Campylobacter spp., whereas with DNA microarrays all samples were positive for Campylobacter spp. By application of DNA microarray analysis, the isolates in 4 samples (6%) could not be identified to the species level, whereas by PCR-capillary electrophoresis, the isolates in 12 samples (19%) remained...

  19. 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.

  20. 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.

  1. Microarray analysis of differentially expressed genes regulating lipid metabolism during melanoma progression.

    Science.gov (United States)

    Sumantran, Venil N; Mishra, Pratik; Sudhakar, N

    2015-04-01

    A new hallmark of cancer involves acquisition of a lipogenic phenotype which promotes tumorigenesis. Little is known about lipid metabolism in melanomas. Therefore, we used BRB (Biometrics Research Branch) class comparison tool with multivariate analysis to identify differentially expressed genes in human cutaneous melanomas, compared with benign nevi and normal skin derived from the microarray dataset (GDS1375). The methods were validated by identifying known melanoma biomarkers (CITED1, FGFR2, PTPRF, LICAM, SPP1 and PHACTR1) in our results. Eighteen genes regulating metabolism of fatty acids, lipid second messengers and gangliosides were 2-9 fold upregulated in melanomas of GDS-1375. Out of the 18 genes, 13 were confirmed by KEGG pathway analysis and 10 were also significantly upregulated in human melanoma cell lines of NCI-60 Cell Miner database. Results showed that melanomas upregulated PPARGC1A transcription factor and its target genes regulating synthesis of fatty acids (SCD) and complex lipids (FABP3 and ACSL3). Melanoma also upregulated genes which prevented lipotoxicity (CPT2 and ACOT7) and regulated lipid second messengers, such as phosphatidic acid (AGPAT-4, PLD3) and inositol triphosphate (ITPKB, ITPR3). Genes for synthesis of pro-tumorigenic GM3 and GD3 gangliosides (UGCG, HEXA, ST3GAL5 and ST8SIA1) were also upregulated in melanoma. Overall, the microarray analysis of GDS-1375 dataset indicated that melanomas can become lipogenic by upregulating genes, leading to increase in fatty acid metabolism, metabolism of specific lipid second messengers, and ganglioside synthesis.

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

    Science.gov (United States)

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

    2012-01-01

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

  3. 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.

  4. Improved elucidation of biological processes linked to diabetic nephropathy by single probe-based microarray data analysis.

    Directory of Open Access Journals (Sweden)

    Clemens D Cohen

    Full Text Available BACKGROUND: Diabetic nephropathy (DN is a complex and chronic metabolic disease that evolves into a progressive fibrosing renal disorder. Effective transcriptomic profiling of slowly evolving disease processes such as DN can be problematic. The changes that occur are often subtle and can escape detection by conventional oligonucleotide DNA array analyses. METHODOLOGY/PRINCIPAL FINDINGS: We examined microdissected human renal tissue with or without DN using Affymetrix oligonucleotide microarrays (HG-U133A by standard Robust Multi-array Analysis (RMA. Subsequent gene ontology analysis by Database for Annotation, Visualization and Integrated Discovery (DAVID showed limited detection of biological processes previously identified as central mechanisms in the development of DN (e.g. inflammation and angiogenesis. This apparent lack of sensitivity may be associated with the gene-oriented averaging of oligonucleotide probe signals, as this includes signals from cross-hybridizing probes and gene annotation that is based on out of date genomic data. We then examined the same CEL file data using a different methodology to determine how well it could correlate transcriptomic data with observed biology. ChipInspector (CI is based on single probe analysis and de novo gene annotation that bypasses probe set definitions. Both methods, RMA and CI, used at default settings yielded comparable numbers of differentially regulated genes. However, when verified by RT-PCR, the single probe based analysis demonstrated reduced background noise with enhanced sensitivity and fewer false positives. CONCLUSIONS/SIGNIFICANCE: Using a single probe based analysis approach with de novo gene annotation allowed an improved representation of the biological processes linked to the development and progression of DN. The improved analysis was exemplified by the detection of Wnt signaling pathway activation in DN, a process not previously reported to be involved in this disease.

  5. A comprehensive comparison of RNA-Seq-based transcriptome analysis from reads to differential gene expression and cross-comparison with microarrays: a case study in Saccharomyces cerevisiae

    DEFF Research Database (Denmark)

    Nookaew, Intawat; Papini, Marta; Pornputtapong, Natapol

    2012-01-01

    RNA-seq, has recently become an attractive method of choice in the studies of transcriptomes, promising several advantages compared with microarrays. In this study, we sought to assess the contribution of the different analytical steps involved in the analysis of RNA-seq data generated...... the consistency between RNA-seq analysis using reference genome and de novo assembly approach. High reproducibility among biological replicates (correlation ≥0.99) and high consistency between the two platforms for analysis of gene expression levels (correlation ≥0.91) are reported. The results from differential...... gene expression identification derived from the different statistical methods, as well as their integrated analysis results based on gene ontology annotation are in good agreement. Overall, our study provides a useful and comprehensive comparison between the two platforms (RNA-seq and microrrays...

  6. Statistical methodology for the analysis of dye-switch microarray experiments

    Directory of Open Access Journals (Sweden)

    Mansouri-Attia Nadera

    2008-02-01

    Full Text Available Abstract Background In individually dye-balanced microarray designs, each biological sample is hybridized on two different slides, once with Cy3 and once with Cy5. While this strategy ensures an automatic correction of the gene-specific labelling bias, it also induces dependencies between log-ratio measurements that must be taken into account in the statistical analysis. Results We present two original statistical procedures for the statistical analysis of individually balanced designs. These procedures are compared with the usual ML and REML mixed model procedures proposed in most statistical toolboxes, on both simulated and real data. Conclusion The UP procedure we propose as an alternative to usual mixed model procedures is more efficient and significantly faster to compute. This result provides some useful guidelines for the analysis of complex designs.

  7. Microarray based gene expression analysis of murine brown and subcutaneous adipose tissue: significance with human.

    Science.gov (United States)

    Baboota, Ritesh K; Sarma, Siddhartha M; Boparai, Ravneet K; Kondepudi, Kanthi Kiran; Mantri, Shrikant; Bishnoi, Mahendra

    2015-01-01

    Two types of adipose tissues, white (WAT) and brown (BAT) are found in mammals. Increasingly novel strategies are being proposed for the treatment of obesity and its associated complications by altering amount and/or activity of BAT using mouse models. The present study was designed to: (a) investigate the differential expression of genes in LACA mice subcutaneous WAT (sWAT) and BAT using mouse DNA microarray, (b) to compare mouse differential gene expression with previously published human data; to understand any inter- species differences between the two and (c) to make a comparative assessment with C57BL/6 mouse strain. In mouse microarray studies, over 7003, 1176 and 401 probe sets showed more than two-fold, five-fold and ten-fold change respectively in differential expression between murine BAT and WAT. Microarray data was validated using quantitative RT-PCR of key genes showing high expression in BAT (Fabp3, Ucp1, Slc27a1) and sWAT (Ms4a1, H2-Ob, Bank1) or showing relatively low expression in BAT (Pgk1, Cox6b1) and sWAT (Slc20a1, Cd74). Multi-omic pathway analysis was employed to understand possible links between the organisms. When murine two fold data was compared with published human BAT and sWAT data, 90 genes showed parallel differential expression in both mouse and human. Out of these 90 genes, 46 showed same pattern of differential expression whereas the pattern was opposite for the remaining 44 genes. Based on our microarray results and its comparison with human data, we were able to identify genes (targets) (a) which can be studied in mouse model systems to extrapolate results to human (b) where caution should be exercised before extrapolation of murine data to human. Our study provides evidence for inter species (mouse vs human) differences in differential gene expression between sWAT and BAT. Critical understanding of this data may help in development of novel ways to engineer one form of adipose tissue to another using murine model with focus on

  8. SegMine workflows for semantic microarray data analysis in Orange4WS

    Directory of Open Access Journals (Sweden)

    Kulovesi Kimmo

    2011-10-01

    Full Text Available Abstract Background In experimental data analysis, bioinformatics researchers increasingly rely on tools that enable the composition and reuse of scientific workflows. The utility of current bioinformatics workflow environments can be significantly increased by offering advanced data mining services as workflow components. Such services can support, for instance, knowledge discovery from diverse distributed data and knowledge sources (such as GO, KEGG, PubMed, and experimental databases. Specifically, cutting-edge data analysis approaches, such as semantic data mining, link discovery, and visualization, have not yet been made available to researchers investigating complex biological datasets. Results We present a new methodology, SegMine, for semantic analysis of microarray data by exploiting general biological knowledge, and a new workflow environment, Orange4WS, with integrated support for web services in which the SegMine methodology is implemented. The SegMine methodology consists of two main steps. First, the semantic subgroup discovery algorithm is used to construct elaborate rules that identify enriched gene sets. Then, a link discovery service is used for the creation and visualization of new biological hypotheses. The utility of SegMine, implemented as a set of workflows in Orange4WS, is demonstrated in two microarray data analysis applications. In the analysis of senescence in human stem cells, the use of SegMine resulted in three novel research hypotheses that could improve understanding of the underlying mechanisms of senescence and identification of candidate marker genes. Conclusions Compared to the available data analysis systems, SegMine offers improved hypothesis generation and data interpretation for bioinformatics in an easy-to-use integrated workflow environment.

  9. SegMine workflows for semantic microarray data analysis in Orange4WS.

    Science.gov (United States)

    Podpečan, Vid; Lavrač, Nada; Mozetič, Igor; Novak, Petra Kralj; Trajkovski, Igor; Langohr, Laura; Kulovesi, Kimmo; Toivonen, Hannu; Petek, Marko; Motaln, Helena; Gruden, Kristina

    2011-10-26

    In experimental data analysis, bioinformatics researchers increasingly rely on tools that enable the composition and reuse of scientific workflows. The utility of current bioinformatics workflow environments can be significantly increased by offering advanced data mining services as workflow components. Such services can support, for instance, knowledge discovery from diverse distributed data and knowledge sources (such as GO, KEGG, PubMed, and experimental databases). Specifically, cutting-edge data analysis approaches, such as semantic data mining, link discovery, and visualization, have not yet been made available to researchers investigating complex biological datasets. We present a new methodology, SegMine, for semantic analysis of microarray data by exploiting general biological knowledge, and a new workflow environment, Orange4WS, with integrated support for web services in which the SegMine methodology is implemented. The SegMine methodology consists of two main steps. First, the semantic subgroup discovery algorithm is used to construct elaborate rules that identify enriched gene sets. Then, a link discovery service is used for the creation and visualization of new biological hypotheses. The utility of SegMine, implemented as a set of workflows in Orange4WS, is demonstrated in two microarray data analysis applications. In the analysis of senescence in human stem cells, the use of SegMine resulted in three novel research hypotheses that could improve understanding of the underlying mechanisms of senescence and identification of candidate marker genes. Compared to the available data analysis systems, SegMine offers improved hypothesis generation and data interpretation for bioinformatics in an easy-to-use integrated workflow environment.

  10. Empirical Evaluation of a New Method for Calculating Signal to Noise Ratio (SNR) for Microarray Data Analysis

    Energy Technology Data Exchange (ETDEWEB)

    Zhou, Jizhong; He, Zhili; Zhou, Jizhong

    2008-03-06

    Signal-to-noise-ratio (SNR) thresholds for microarray data analysis were experimentally determined with an oligonucleotide array that contained perfect match (PM) and mismatch (MM) probes based upon four genes from Shewanella oneidensis MR-1. A new SNR calculation, called signal to both standard deviations ratio (SSDR) was developed, and evaluated along with other two methods, signal to standard deviation ratio (SSR), and signal to background ratio (SBR). At a low stringency, the thresholds of SSR, SBR, and SSDR were 2.5, 1.60 and 0.80 with oligonucleotide and PCR amplicon as target templates, and 2.0, 1.60 and 0.70 with genomic DNA as target templates. Slightly higher thresholds were obtained at the high stringency condition. The thresholds of SSR and SSDR decreased with an increase in the complexity of targets (e.g., target types), and the presence of background DNA, and a decrease in the composition of targets, while SBR remained unchanged under all situations. The lowest percentage of false positives (FP) and false negatives (FN) was observed with the SSDR calculation method, suggesting that it may be a better SNR calculation for more accurate determination of SNR thresholds. Positive spots identified by SNR thresholds were verified by the Student t-test, and consistent results were observed. This study provides general guidance for users to select appropriate SNR thresholds for different samples under different hybridization conditions.

  11. Genomic resources for a commercial flatfish, the Senegalese sole (Solea senegalensis: EST sequencing, oligo microarray design, and development of the Soleamold bioinformatic platform

    Directory of Open Access Journals (Sweden)

    Planas Josep V

    2008-10-01

    Full Text Available Abstract Background The Senegalese sole, Solea senegalensis, is a highly prized flatfish of growing commercial interest for aquaculture in Southern Europe. However, despite the industrial production of Senegalese sole being hampered primarily by lack of information on the physiological mechanisms involved in reproduction, growth and immunity, very limited genomic information is available on this species. Results Sequencing of a S. senegalensis multi-tissue normalized cDNA library, from adult tissues (brain, stomach, intestine, liver, ovary, and testis, larval stages (pre-metamorphosis, metamorphosis, juvenile stages (post-metamorphosis, abnormal fish, and undifferentiated gonads, generated 10,185 expressed sequence tags (ESTs. Clones were sequenced from the 3'-end to identify isoform specific sequences. Assembly of the entire EST collection into contigs gave 5,208 unique sequences of which 1,769 (34% had matches in GenBank, thus showing a low level of redundancy. The sequence of the 5,208 unigenes was used to design and validate an oligonucleotide microarray representing 5,087 unique Senegalese sole transcripts. Finally, a novel interactive bioinformatic platform, Soleamold, was developed for the Senegalese sole EST collection as well as microarray and ISH data. Conclusion New genomic resources have been developed for S. senegalensis, an economically important fish in aquaculture, which include a collection of expressed genes, an oligonucleotide microarray, and a publicly available bioinformatic platform that can be used to study gene expression in this species. These resources will help elucidate transcriptional regulation in wild and captive Senegalese sole for optimization of its production under intensive culture conditions.

  12. Genomic resources for a commercial flatfish, the Senegalese sole (Solea senegalensis): EST sequencing, oligo microarray design, and development of the Soleamold bioinformatic platform

    Science.gov (United States)

    Cerdà, Joan; Mercadé, Jaume; Lozano, Juan José; Manchado, Manuel; Tingaud-Sequeira, Angèle; Astola, Antonio; Infante, Carlos; Halm, Silke; Viñas, Jordi; Castellana, Barbara; Asensio, Esther; Cañavate, Pedro; Martínez-Rodríguez, Gonzalo; Piferrer, Francesc; Planas, Josep V; Prat, Francesc; Yúfera, Manuel; Durany, Olga; Subirada, Francesc; Rosell, Elisabet; Maes, Tamara

    2008-01-01

    Background The Senegalese sole, Solea senegalensis, is a highly prized flatfish of growing commercial interest for aquaculture in Southern Europe. However, despite the industrial production of Senegalese sole being hampered primarily by lack of information on the physiological mechanisms involved in reproduction, growth and immunity, very limited genomic information is available on this species. Results Sequencing of a S. senegalensis multi-tissue normalized cDNA library, from adult tissues (brain, stomach, intestine, liver, ovary, and testis), larval stages (pre-metamorphosis, metamorphosis), juvenile stages (post-metamorphosis, abnormal fish), and undifferentiated gonads, generated 10,185 expressed sequence tags (ESTs). Clones were sequenced from the 3'-end to identify isoform specific sequences. Assembly of the entire EST collection into contigs gave 5,208 unique sequences of which 1,769 (34%) had matches in GenBank, thus showing a low level of redundancy. The sequence of the 5,208 unigenes was used to design and validate an oligonucleotide microarray representing 5,087 unique Senegalese sole transcripts. Finally, a novel interactive bioinformatic platform, Soleamold, was developed for the Senegalese sole EST collection as well as microarray and ISH data. Conclusion New genomic resources have been developed for S. senegalensis, an economically important fish in aquaculture, which include a collection of expressed genes, an oligonucleotide microarray, and a publicly available bioinformatic platform that can be used to study gene expression in this species. These resources will help elucidate transcriptional regulation in wild and captive Senegalese sole for optimization of its production under intensive culture conditions. PMID:18973667

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

    Directory of Open Access Journals (Sweden)

    Sunwoo Chun

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

  14. Genome Analysis of Legionella pneumophila Strains Using a Mixed-Genome Microarray

    NARCIS (Netherlands)

    Euser, S.M.; Nagelkerke, N.J.; Schuren, F.; Jansen, R.; Boer, J.W. den

    2012-01-01

    Background: Legionella, the causative agent for Legionnaires' disease, is ubiquitous in both natural and man-made aquatic environments. The distribution of Legionella genotypes within clinical strains is significantly different from that found in environmental strains. Developing novel genotypic met

  15. MICROARRAY ANALYSIS OF DIFFERENT GENE EXPRESSION OF HUMAN CERVICAL CANCER SUBCLONE CELL LINES

    Institute of Scientific and Technical Information of China (English)

    Chen Wei; Li Xu; Wang Xiang

    2006-01-01

    Objective To examine the differentially expressed invasion-related genes in two anchorage-independent uterine cervical carcinoma cell lines derived from the same patient using a cDNA array. Methods Two human uterine cervical carcinoma subclonal cell lines CS03 and CS07 derived from a single donor line CS1213 were established by limited dilution procedure. The two cDNA samples retro-transcribed from total RNA derived from CS03 and CS07 cells were screened by a cDNA microarray carrying 234 human cell-cycle related genes and 1011 human signal transduction and membrane receptor -associated genes, scanned with a ScanArray 3000 laser scanner. Results The cDNA microarray analysis showed that 12 genes in CS03 were up-regulated compared to CS07, and 24 genes in CS07 were up-regulated. The function of a number of differentially expressed genes was consistently associated with cell-cycle, cell proliferation, migration, apoptosis, signal transduction and tumor metastasis, including p34cdc2, TSC22, plasminogen activator inhibitor I (PAI-1)and desmosome associated protein(Pinin). Conclusion Multiple genes are differentially expressed in uterine cervical carcinoma cell lines even came from the same patient. It is suggested that these genes are involved in the different phenotypic characteristics and development of cervical carcinoma.

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

    Directory of Open Access Journals (Sweden)

    Fabi João Paulo

    2012-12-01

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

  17. Microarray analysis of differentially expressed genes in preeclamptic and normal placental tissues.

    Science.gov (United States)

    Ma, K; Lian, Y; Zhou, S; Hu, R; Xiong, Y; Ting, P; Xiong, Y; Li, X; Wang, X

    2014-01-01

    To detect the candidate genes for preeclampsia (PE). The gene expression profiles in preeclamptic and normal placental tissues were analyzed using cDNA microarray approach and the altered expression of important genes were further confirmed by real-time RT-PCR (reverse transcription polymerase chain reaction) technique. Total RNA was extracted from placental tissues of three cases with severe PE and from three cases with normal pregnancy. After scanning, differentially expressed genes were detected by software. In two experiments (the fluorescent labels were exchanged), a total of 111 differentially expressed genes were detected. In placental tissue ofpreeclamptic pregnancy, 68 differentially expressed genes were up-regulated, and 44 differentially expressed genes were down-regulated. Of these genes, 16 highly differentially expressed genes were confirmed by real-time fluorescent quantitative RT-PCR, and the result showed that the ratio of gene expression differences was comparable to that detected by cDNA microarray. The results of bioinformatic analysis showed that encoding products of differentially expressed genes were correlated to infiltration of placenta trophoblastic cells, immunomodulatory factors, pregnancy-associated plasma protein, signal transduction pathway, and cell adhesion. Further studies on the biological function and regulating mechanism of these genes will provide new clues for better understanding of etiology and pathogenesis of PE.

  18. Transcriptional Profiling of Hydrogen Production Metabolism of Rhodobacter capsulatus under Temperature Stress by Microarray Analysis

    Directory of Open Access Journals (Sweden)

    Muazzez Gürgan

    2015-06-01

    Full Text Available Biohydrogen is a clean and renewable form of hydrogen, which can be produced by photosynthetic bacteria in outdoor large-scale photobioreactors using sunlight. In this study, the transcriptional response of Rhodobacter capsulatus to cold (4 °C and heat (42 °C stress was studied using microarrays. Bacteria were grown in 30/2 acetate/glutamate medium at 30 °C for 48 h under continuous illumination. Then, cold and heat stresses were applied for two and six hours. Growth and hydrogen production were impaired under both stress conditions. Microarray chips for R. capsulatus were custom designed by Affymetrix (GeneChip®. TR_RCH2a520699F. The numbers of significantly changed genes were 328 and 293 out of 3685 genes under cold and heat stress, respectively. Our results indicate that temperature stress greatly affects the hydrogen production metabolisms of R. capsulatus. Specifically, the expression of genes that participate in nitrogen metabolism, photosynthesis and the electron transport system were induced by cold stress, while decreased by heat stress. Heat stress also resulted in down regulation of genes related to cell envelope, transporter and binding proteins. Transcriptome analysis and physiological results were consistent with each other. The results presented here may aid clarification of the genetic mechanisms for hydrogen production in purple non-sulfur (PNS bacteria under temperature stress.

  19. The microarray analysis for gene expression in haploids and diploids derived from twin-seedling rice

    Institute of Scientific and Technical Information of China (English)

    2008-01-01

    In this study, microarray technique was employed to analyze the gene expression at the RNA level between haploids and corresponding diploids derived from a rice twin-seedling line SARII-628. Differ- ent degrees of expression variations were observed in the plant after haploidization. The main results are as follows: (1) after haploidization, the ratio of the sensitive loci was 2.47% of the total loci designed on chip. Those loci were randomly distributed on the 12 pairs of rice chromosomes and the activated loci were more than the silenced ones. (2) Gene clusters on chromosome were observed for 33 se- quences. (3) GoPipe function classification for 575 sensitive loci revealed an involvement in the bio- logical process, cell component and molecular function. (4) RT-PCR generally validated the result from microarray with a coincidence rate of 83.78%. And for the randomly-selected activated or silenced loci in chip analysis, the coincidence rate was up to 91.86%.

  20. Application of the Taguchi method to the analysis of the deposition step in microarray production.

    Science.gov (United States)

    Severgnini, Marco; Pattini, Linda; Consolandi, Clarissa; Rizzi, Ermanno; Battaglia, Cristina; De Bellis, Gianluca; Cerutti, Sergio

    2006-09-01

    Every microarray experiment is affected by many possible sources of variability that may even corrupt biological evidence on analyzed sequences. We applied a "Taguchi method" strategy, based on the use of orthogonal arrays to optimize the deposition step of oligonucleotide sequences on glass slides. We chose three critical deposition parameters (humidity, surface, and buffer) at two levels each, in order to establish optimum settings. A L8 orthogonal array was used in order to monitor both the main effects and interactions on the deposition of a 25 mer oligonucleotide hybridized to its fluorescent-labeled complementary. Signal-background ratio and deposition homogeneity in terms of mean intensity and spot diameter were considered as significant outputs. An analysis of variance (ANOVA) was applied to raw data and to mean results for each slide and experimental run. Finally we calculated an overall evaluation coefficient to group together important outputs in one number. Environmental humidity and surface-buffer interaction were recognized as the most critical factors, for which a 50% humidity, associated to a chitosan-covered slide and a sodium phosphate + 25% dimethyl sulfoxide (DMSO) buffer gave best performances. Our results also suggested that Taguchi methods can be efficiently applied in optimization of microarray procedures.

  1. Microarray analysis of human monocytes infected with Francisella tularensis identifies new targets of host response subversion.

    Directory of Open Access Journals (Sweden)

    Jonathan P Butchar

    Full Text Available Francisella tularensis is a gram-negative facultative bacterium that causes the disease tularemia, even upon exposure to low numbers of bacteria. One critical characteristic of Francisella is its ability to dampen or subvert the host immune response. In order to help understand the mechanisms by which this occurs, we performed Affymetrix microarray analysis on transcripts from blood monocytes infected with the virulent Type A Schu S4 strain. Results showed that expression of several host response genes were reduced such as those associated with interferon signaling, Toll-like receptor signaling, autophagy and phagocytosis. When compared to microarrays from monocytes infected with the less virulent F. tularensis subsp. novicida, we found qualitative differences and also a general pattern of quantitatively reduced pro-inflammatory signaling pathway genes in the Schu S4 strain. Notably, the PI3K/Akt1 pathway appeared specifically down-regulated following Schu S4 infection and a concomitantly lower cytokine response was observed. This study identifies several new factors potentially important in host cell subversion by the virulent Type A F. tularensis that may serve as novel targets for drug discovery.

  2. Analysis of factorial time-course microarrays with application to a clinical study of burn injury.

    Science.gov (United States)

    Zhou, Baiyu; Xu, Weihong; Herndon, David; Tompkins, Ronald; Davis, Ronald; Xiao, Wenzhong; Wong, Wing Hung; Toner, Mehmet; Warren, H Shaw; Schoenfeld, David A; Rahme, Laurence; McDonald-Smith, Grace P; Hayden, Douglas; Mason, Philip; Fagan, Shawn; Yu, Yong-Ming; Cobb, J Perren; Remick, Daniel G; Mannick, John A; Lederer, James A; Gamelli, Richard L; Silver, Geoffrey M; West, Michael A; Shapiro, Michael B; Smith, Richard; Camp, David G; Qian, Weijun; Storey, John; Mindrinos, Michael; Tibshirani, Rob; Lowry, Stephen; Calvano, Steven; Chaudry, Irshad; West, Michael A; Cohen, Mitchell; Moore, Ernest E; Johnson, Jeffrey; Moldawer, Lyle L; Baker, Henry V; Efron, Philip A; Balis, Ulysses G J; Billiar, Timothy R; Ochoa, Juan B; Sperry, Jason L; Miller-Graziano, Carol L; De, Asit K; Bankey, Paul E; Finnerty, Celeste C; Jeschke, Marc G; Minei, Joseph P; Arnoldo, Brett D; Hunt, John L; Horton, Jureta; Cobb, J Perren; Brownstein, Bernard; Freeman, Bradley; Maier, Ronald V; Nathens, Avery B; Cuschieri, Joseph; Gibran, Nicole; Klein, Matthew; O'Keefe, Grant

    2010-06-01

    Time-course microarray experiments are capable of capturing dynamic gene expression profiles. It is important to study how these dynamic profiles depend on the multiple factors that characterize the experimental condition under which the time course is observed. Analytic methods are needed to simultaneously handle the time course and factorial structure in the data. We developed a method to evaluate factor effects by pooling information across the time course while accounting for multiple testing and nonnormality of the microarray data. The method effectively extracts gene-specific response features and models their dependency on the experimental factors. Both longitudinal and cross-sectional time-course data can be handled by our approach. The method was used to analyze the impact of age on the temporal gene response to burn injury in a large-scale clinical study. Our analysis reveals that 21% of the genes responsive to burn are age-specific, among which expressions of mitochondria and immunoglobulin genes are differentially perturbed in pediatric and adult patients by burn injury. These new findings in the body's response to burn injury between children and adults support further investigations of therapeutic options targeting specific age groups. The methodology proposed here has been implemented in R package "TANOVA" and submitted to the Comprehensive R Archive Network at http://www.r-project.org/. It is also available for download at http://gluegrant1.stanford.edu/TANOVA/.

  3. [Microarray analytic system for multiplex analysis by real-time polymerase chain reaction with reagents immobilized in microreactors].

    Science.gov (United States)

    Navolotskiĭ, D V; Perchik, A V; Mark'ianov, I A; Ganeev, A A; Sliadnev, M N

    2011-01-01

    A microarray analytic system that uses a silicon chip with immobilized in microreactor test-system for multiplex analysis of DNA by real-time polymerase chain reaction (RT-PCR) was developed and optimized. We suggested the method of immobilization of PCR-components of a test-system, chose the stabilizer, and conducted the optimization of the composition of reaction mixture to achieve permanent stability of a microarray. We conducted optimization of preparation of samples using magnetic sorbent and indicated that, with 2.6 x 10(4) copies/ml, 60 min are necessary to obtain positive identification including time for preparation of model probes. The abilities of the created system were demonstrated on the example of microarray analysis of samples with different content of DNA, low absolute limits of identification (20 DNA copies in microreactor), and high reproducibility of the analysis.

  4. Chromosomal Microarray Analysis of Consecutive Individuals with Autism Spectrum Disorders Using an Ultra-High Resolution Chromosomal Microarray Optimized for Neurodevelopmental Disorders

    Directory of Open Access Journals (Sweden)

    Karen S. Ho

    2016-12-01

    Full Text Available Copy number variants (CNVs detected by chromosomal microarray analysis (CMA significantly contribute to understanding the etiology of autism spectrum disorder (ASD and other related conditions. In recognition of the value of CMA testing and its impact on medical management, CMA is in medical guidelines as a first-tier test in the evaluation of children with these disorders. As CMA becomes adopted into routine care for these patients, it becomes increasingly important to report these clinical findings. This study summarizes the results of over 4 years of CMA testing by a CLIA-certified clinical testing laboratory. Using a 2.8 million probe microarray optimized for the detection of CNVs associated with neurodevelopmental disorders, we report an overall CNV detection rate of 28.1% in 10,351 consecutive patients, which rises to nearly 33% in cases without ASD, with only developmental delay/intellectual disability (DD/ID and/or multiple congenital anomalies (MCA. The overall detection rate for individuals with ASD is also significant at 24.4%. The detection rate and pathogenic yield of CMA vary significantly with the indications for testing, age, and gender, as well as the specialty of the ordering doctor. We note discrete differences in the most common recurrent CNVs found in individuals with or without a diagnosis of ASD.

  5. De novo Transcriptome Sequencing and Development of Abscission Zone-Specific Microarray as a New Molecular Tool for Analysis of Tomato Organ Abscission

    Science.gov (United States)

    Sundaresan, Srivignesh; Philosoph-Hadas, Sonia; Riov, Joseph; Mugasimangalam, Raja; Kuravadi, Nagesh A.; Kochanek, Bettina; Salim, Shoshana; Tucker, Mark L.; Meir, Shimon

    2016-01-01

    Abscission of flower pedicels and leaf petioles of tomato (Solanum lycopersicum) can be induced by flower removal or leaf deblading, respectively, which leads to auxin depletion, resulting in increased sensitivity of the abscission zone (AZ) to ethylene. However, the molecular mechanisms that drive the acquisition of abscission competence and its modulation by auxin gradients are not yet known. We used RNA-Sequencing (RNA-Seq) to obtain a comprehensive transcriptome of tomato flower AZ (FAZ) and leaf AZ (LAZ) during abscission. RNA-Seq was performed on a pool of total RNA extracted from tomato FAZ and LAZ, at different abscission stages, followed by de novo assembly. The assembled clusters contained transcripts that are already known in the Solanaceae (SOL) genomics and NCBI databases, and over 8823 identified novel tomato transcripts of varying sizes. An AZ-specific microarray, encompassing the novel transcripts identified in this study and all known transcripts from the SOL genomics and NCBI databases, was constructed to study the abscission process. Multiple probes for longer genes and key AZ-specific genes, including antisense probes for all transcripts, make this array a unique tool for studying abscission with a comprehensive set of transcripts, and for mining for naturally occurring antisense transcripts. We focused on comparing the global transcriptomes generated from the FAZ and the LAZ to establish the divergences and similarities in their transcriptional networks, and particularly to characterize the processes and transcriptional regulators enriched in gene clusters that are differentially regulated in these two AZs. This study is the first attempt to analyze the global gene expression in different AZs in tomato by combining the RNA-Seq technique with oligonucleotide microarrays. Our AZ-specific microarray chip provides a cost-effective approach for expression profiling and robust analysis of multiple samples in a rapid succession. PMID:26834766

  6. De novo transcriptome sequencing and development of abscission zone-specific microarray as a new molecular tool for analysis of tomato organ abscission

    Directory of Open Access Journals (Sweden)

    Srivignesh eSundaresan

    2016-01-01

    Full Text Available Abscission of flower pedicels and leaf petioles of tomato (Solanum lycopersicum can be induced by flower removal or leaf deblading, respectively, leading to auxin depletion, which results in increased sensitivity of the abscission zone (AZ to ethylene. However, the molecular mechanisms that drive the acquisition of abscission competence and its modulation by auxin gradients are not yet known. We used RNA-Sequencing (RNA-Seq to obtain the comprehensive transcriptome of tomato flower AZ (FAZ and leaf AZ (LAZ during abscission. RNA-Seq was performed on a pool of total RNA extracted from different abscission stages of tomato FAZ and LAZ, followed by de novo assembly. The assembled clusters contained transcripts that are already known in Solanaceae (SOL genomics database and NCBI databases, and over 8,823 identified novel tomato transcripts of varying sizes. An AZ-specific microarray, encompassing these novel transcripts identified in this study and all known transcripts from the SOL genomics and NCBI databases, was constructed to study the abscission process. Multiple probes for longer genes and key AZ-specific genes, including antisense probes for all transcripts, make this array a unique tool for studying abscission with a comprehensive set of transcripts, and for mining for naturally occurring antisense transcripts. We focused on comparing the global transcriptomes generated from the FAZ and the LAZ to establish the divergences and similarities in their transcriptional networks, and particularly to characterize the processes and transcriptional regulators enriched in gene clusters that are differentially regulated in these two AZs. This study is the first attempt to analyze the global gene expression in different AZs in tomato by combining the RNA-Seq technique with oligonucleotide microarrays. Our AZ-specific microarray chip provides a cost-effective approach for expression profiling and robust analysis of multiple samples in a rapid succession.

  7. INCLUSive: A web portal and service registry for microarray and regulatory sequence analysis.

    Science.gov (United States)

    Coessens, Bert; Thijs, Gert; Aerts, Stein; Marchal, Kathleen; De Smet, Frank; Engelen, Kristof; Glenisson, Patrick; Moreau, Yves; Mathys, Janick; De Moor, Bart

    2003-07-01

    INCLUSive is a suite of algorithms and tools for the analysis of gene expression data and the discovery of cis-regulatory sequence elements. The tools allow normalization, filtering and clustering of microarray data, functional scoring of gene clusters, sequence retrieval, and detection of known and unknown regulatory elements using probabilistic sequence models and Gibbs sampling. All tools are available via different web pages and as web services. The web pages are connected and integrated to reflect a methodology and facilitate complex analysis using different tools. The web services can be invoked using standard SOAP messaging. Example clients are available for download to invoke the services from a remote computer or to be integrated with other applications. All services are catalogued and described in a web service registry. The INCLUSive web portal is available for academic purposes at http://www.esat.kuleuven.ac.be/inclusive.

  8. Phytoremediation potential of Arabidopsis with reference to acrylamide and microarray analysis of acrylamide-response genes.

    Science.gov (United States)

    Gao, Jian-Jie; Peng, Ri-He; Zhu, Bo; Wang, Bo; Wang, Li-Juan; Xu, Jing; Sun, Miao; Yao, Quan-Hong

    2015-10-01

    Acrylamide (ACR) is a widely used industrial chemical. However, it is a dangerous compound because it showed neurotoxic effects in humans and act as reproductive toxicant and carcinogen in many animal species. In the environment, acrylamide has high soil mobility and may travel via groundwater. Phytoremediation is an effective method to remove the environmental pollutants, but the mechanism of plant response to acrylamide remains unknown. With the purpose of assessing remediation potentials of plants for acrylamide, we have examined acrylamide uptake by the model plant Arabidopsis grown on contaminated substrates with high performance liquid chromatography (HPLC) analysis. The result revealed that acrylamide could be absorbed and degraded by Arabidopsis. Further microarray analysis showed that 527 transcripts were up-regulated within 2-days under acrylamide exposure condition. We have found many potential acrylamide-induced genes playing a major role in plant metabolism and phytoremediation. Copyright © 2015 Elsevier Inc. All rights reserved.

  9. TagSmart: analysis and visualization for yeast mutant fitness data measured by tag microarrays

    Directory of Open Access Journals (Sweden)

    Xie Dan

    2007-04-01

    Full Text Available Abstract Background A nearly complete collection of gene-deletion mutants (96% of annotated open reading frames of the yeast Saccharomyces cerevisiae has been systematically constructed. Tag microarrays are widely used to measure the fitness of each mutant in a mutant mixture. The tag array experiments can have a complex experimental design, such as time course measurements and drug treatment with multiple dosages. Results TagSmart is a web application for analysis and visualization of Saccharomyces cerevisiae mutant fitness data measured by tag microarrays. It implements a robust statistical approach to assess the concentration differences among S. cerevisiae mutant strains. It also provides an interactive environment for data analysis and visualization. TagSmart has the following advantages over previously described analysis procedures: 1 it is user-friendly software rather than merely a description of analytical procedure; 2 It can handle complicated experimental designs, such as multiple time points and treatment with multiple dosages; 3 it has higher sensitivity and specificity; 4 It allows users to mask out "bad" tags in the analysis. Two biological tests were performed to illustrate the performance of TagSmart. First, we generated titration mixtures of mutant strains, in which the relative concentration of each strain was controlled. We used tag microarrays to measure the numbers of tag copies in each titration mixture. The data was analyzed with TagSmart and the result showed high precision and recall. Second, TagSmart was applied to a dataset in which heterozygous deletion strain mixture pools were treated with a new drug, Cincreasin. TagSmart identified 53 mutant strains as sensitive to Cincreasin treatment. We individually tested each identified mutant, and found 52 out of the 53 predicted mutants were indeed sensitive to Cincreasin. Conclusion TagSmart is provided "as is" to analyze tag array data produced by Affymetrix and Agilent

  10. Microarray analysis and barcoded pyrosequencing provide consistent microbial profiles depending on the source of human intestinal samples

    NARCIS (Netherlands)

    Bogert, van den B.; Vos, de W.M.; Zoetendal, E.G.; Kleerebezem, M.

    2011-01-01

    Large-scale and in-depth characterization of the intestinal microbiota necessitates application of high-throughput 16S rRNA gene-based technologies, such as barcoded pyrosequencing and phylogenetic microarray analysis. In this study, the two techniques were compared and contrasted for analysis of th

  11. Classifying Genomic Sequences by Sequence Feature Analysis

    Institute of Scientific and Technical Information of China (English)

    Zhi-Hua Liu; Dian Jiao; Xiao Sun

    2005-01-01

    Traditional sequence analysis depends on sequence alignment. In this study, we analyzed various functional regions of the human genome based on sequence features, including word frequency, dinucleotide relative abundance, and base-base correlation. We analyzed the human chromosome 22 and classified the upstream,exon, intron, downstream, and intergenic regions by principal component analysis and discriminant analysis of these features. The results show that we could classify the functional regions of genome based on sequence feature and discriminant analysis.

  12. Microarchitecture of a MultiCore SoC for Data Analysis of a Lab-on-Chip Microarray

    Directory of Open Access Journals (Sweden)

    S. Blionas

    2008-07-01

    Full Text Available This paper presents a reconfigurable architecture of a lab-on-chip (LoC microarray device capable to process data either in genotyping or in gene expression applications in a fraction of the time that is required by the usual software methods running on a standard computer. The entire LoC consists of a microfluidics part for the sample preparation and hybridization, a microsystem part including the application specific array of sensors for the electronic detection, and finally a reconfigurable processing part for the data analysis. The proposed data processing and analysis electronic module are an embedded multicore reconfigurable system-on-chip designed to analyze data from the forthcoming high-density oligonucleotide microarrays. The proposed architecture employs reconfigurable technology and has the capacity to process data from microarrays of various sizes from small size ones used in genotyping up to large-scale gene expression arrays. Additionally, the embedded processing cores feature reconfigurable circuitry for implementing the intense part of the processing, supplementing the various computational needs of the diverse applications for microarray real-time data processing and for a scalable reconfigurable architecture to handle also the future high-density microarrays.

  13. Automated detection of regions of interest for tissue microarray experiments: an image texture analysis

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    Tözeren Aydin

    2007-03-01

    Full Text Available Abstract Background Recent research with tissue microarrays led to a rapid progress toward quantifying the expressions of large sets of biomarkers in normal and diseased tissue. However, standard procedures for sampling tissue for molecular profiling have not yet been established. Methods This study presents a high throughput analysis of texture heterogeneity on breast tissue images for the purpose of identifying regions of interest in the tissue for molecular profiling via tissue microarray technology. Image texture of breast histology slides was described in terms of three parameters: the percentage of area occupied in an image block by chromatin (B, percentage occupied by stroma-like regions (P, and a statistical heterogeneity index H commonly used in image analysis. Texture parameters were defined and computed for each of the thousands of image blocks in our dataset using both the gray scale and color segmentation. The image blocks were then classified into three categories using the texture feature parameters in a novel statistical learning algorithm. These categories are as follows: image blocks specific to normal breast tissue, blocks specific to cancerous tissue, and those image blocks that are non-specific to normal and disease states. Results Gray scale and color segmentation techniques led to identification of same regions in histology slides as cancer-specific. Moreover the image blocks identified as cancer-specific belonged to those cell crowded regions in whole section image slides that were marked by two pathologists as regions of interest for further histological studies. Conclusion These results indicate the high efficiency of our automated method for identifying pathologic regions of interest on histology slides. Automation of critical region identification will help minimize the inter-rater variability among different raters (pathologists as hundreds of tumors that are used to develop an array have typically been evaluated

  14. Microarray-based analysis of differential gene expression between infective and noninfective larvae of Strongyloides stercoralis.

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    Roshan Ramanathan

    Full Text Available BACKGROUND: Differences between noninfective first-stage (L1 and infective third-stage (L3i larvae of parasitic nematode Strongyloides stercoralis at the molecular level are relatively uncharacterized. DNA microarrays were developed and utilized for this purpose. METHODS AND FINDINGS: Oligonucleotide hybridization probes for the array were designed to bind 3,571 putative mRNA transcripts predicted by analysis of 11,335 expressed sequence tags (ESTs obtained as part of the Nematode EST project. RNA obtained from S. stercoralis L3i and L1 was co-hybridized to each array after labeling the individual samples with different fluorescent tags. Bioinformatic predictions of gene function were developed using a novel cDNA Annotation System software. We identified 935 differentially expressed genes (469 L3i-biased; 466 L1-biased having two-fold expression differences or greater and microarray signals with a p value<0.01. Based on a functional analysis, L1 larvae have a larger number of genes putatively involved in transcription (p = 0.004, and L3i larvae have biased expression of putative heat shock proteins (such as hsp-90. Genes with products known to be immunoreactive in S. stercoralis-infected humans (such as SsIR and NIE had L3i biased expression. Abundantly expressed L3i contigs of interest included S. stercoralis orthologs of cytochrome oxidase ucr 2.1 and hsp-90, which may be potential chemotherapeutic targets. The S. stercoralis ortholog of fatty acid and retinol binding protein-1, successfully used in a vaccine against Ancylostoma ceylanicum, was identified among the 25 most highly expressed L3i genes. The sperm-containing glycoprotein domain, utilized in a vaccine against the nematode Cooperia punctata, was exclusively found in L3i biased genes and may be a valuable S. stercoralis target of interest. CONCLUSIONS: A new DNA microarray tool for the examination of S. stercoralis biology has been developed and provides new and valuable insights

  15. Microarray Study of Pathway Analysis Expression Profile Associated with MicroRNA-29a with Regard to Murine Cholestatic Liver Injuries

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    Sung-Chou Li

    2016-03-01

    Full Text Available Accumulating evidence demonstrates that microRNA-29 (miR-29 expression is prominently decreased in patients with hepatic fibrosis, which consequently stimulates hepatic stellate cells’ (HSCs activation. We used a cDNA microarray study to gain a more comprehensive understanding of genome-wide gene expressions by adjusting miR-29a expression in a bile duct-ligation (BDL animal model. Methods: Using miR-29a transgenic mice and wild-type littermates and applying the BDL mouse model, we characterized the function of miR-29a with regard to cholestatic liver fibrosis. Pathway enrichment analysis and/or specific validation were performed for differentially expressed genes found within the comparisons. Results: Analysis of the microarray data identified a number of differentially expressed genes due to the miR-29a transgene, BDL, or both. Additional pathway enrichment analysis revealed that TGF-β signaling had a significantly differential activated pathway depending on the occurrence of miR-29a overexpression or the lack thereof. Furthermore, overexpression was found to elicit changes in Wnt/β-catenin after BDL. Conclusion: This study verified that an elevated miR-29a level could alleviate liver fibrosis caused by cholestasis. Furthermore, the protective effects of miR-29a correlate with the downregulation of TGF-β and associated with Wnt/β-catenin signal pathway following BDL.