Characterization of genetic variability of Venezuelan equine encephalitis viruses

DOE PAGES

Gardner, Shea N.; McLoughlin, Kevin; Be, Nicholas A.; ...

2016-04-07

Venezuelan equine encephalitis virus (VEEV) is a mosquito-borne alphavirus that has caused large outbreaks of severe illness in both horses and humans. New approaches are needed to rapidly infer the origin of a newly discovered VEEV strain, estimate its equine amplification and resultant epidemic potential, and predict human virulence phenotype. We performed whole genome single nucleotide polymorphism (SNP) analysis of all available VEE antigenic complex genomes, verified that a SNP-based phylogeny accurately captured the features of a phylogenetic tree based on multiple sequence alignment, and developed a high resolution genome-wide SNP microarray. We used the microarray to analyze a broadmore » panel of VEEV isolates, found excellent concordance between array- and sequence-based SNP calls, genotyped unsequenced isolates, and placed them on a phylogeny with sequenced genomes. The microarray successfully genotyped VEEV directly from tissue samples of an infected mouse, bypassing the need for viral isolation, culture and genomic sequencing. Lastly, we identified genomic variants associated with serotypes and host species, revealing a complex relationship between genotype and phenotype.« less

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

PubMed

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

2009-06-01

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

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

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

Jaing, Crystal; Vergez, Lisa; Hinckley, Aubree

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 analyzedmore » 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.« less

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

PubMed

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

2008-06-18

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

Quantitative phenotyping via deep barcode sequencing

PubMed Central

Smith, Andrew M.; Heisler, Lawrence E.; Mellor, Joseph; Kaper, Fiona; Thompson, Michael J.; Chee, Mark; Roth, Frederick P.; Giaever, Guri; Nislow, Corey

2009-01-01

Next-generation DNA sequencing technologies have revolutionized diverse genomics applications, including de novo genome sequencing, SNP detection, chromatin immunoprecipitation, and transcriptome analysis. Here we apply deep sequencing to genome-scale fitness profiling to evaluate yeast strain collections in parallel. This method, Barcode analysis by Sequencing, or “Bar-seq,” outperforms the current benchmark barcode microarray assay in terms of both dynamic range and throughput. When applied to a complex chemogenomic assay, Bar-seq quantitatively identifies drug targets, with performance superior to the benchmark microarray assay. We also show that Bar-seq is well-suited for a multiplex format. We completely re-sequenced and re-annotated the yeast deletion collection using deep sequencing, found that ∼20% of the barcodes and common priming sequences varied from expectation, and used this revised list of barcode sequences to improve data quality. Together, this new assay and analysis routine provide a deep-sequencing-based toolkit for identifying gene–environment interactions on a genome-wide scale. PMID:19622793

Improved analytical methods for microarray-based genome-composition analysis

PubMed Central

Kim, Charles C; Joyce, Elizabeth A; Chan, Kaman; Falkow, Stanley

2002-01-01

Background Whereas genome sequencing has given us high-resolution pictures of many different species of bacteria, microarrays provide a means of obtaining information on genome composition for many strains of a given species. Genome-composition analysis using microarrays, or 'genomotyping', can be used to categorize genes into 'present' and 'divergent' categories based on the level of hybridization signal. This typically involves selecting a signal value that is used as a cutoff to discriminate present (high signal) and divergent (low signal) genes. Current methodology uses empirical determination of cutoffs for classification into these categories, but this methodology is subject to several problems that can result in the misclassification of many genes. Results We describe a method that depends on the shape of the signal-ratio distribution and does not require empirical determination of a cutoff. Moreover, the cutoff is determined on an array-to-array basis, accounting for variation in strain composition and hybridization quality. The algorithm also provides an estimate of the probability that any given gene is present, which provides a measure of confidence in the categorical assignments. Conclusions Many genes previously classified as present using static methods are in fact divergent on the basis of microarray signal; this is corrected by our algorithm. We have reassigned hundreds of genes from previous genomotyping studies of Helicobacter pylori and Campylobacter jejuni strains, and expect that the algorithm should be widely applicable to genomotyping data. PMID:12429064

Comprehensive performance comparison of high-resolution array platforms for genome-wide Copy Number Variation (CNV) analysis in humans.

PubMed

Haraksingh, Rajini R; Abyzov, Alexej; Urban, Alexander Eckehart

2017-04-24

High-resolution microarray technology is routinely used in basic research and clinical practice to efficiently detect copy number variants (CNVs) across the entire human genome. A new generation of arrays combining high probe densities with optimized designs will comprise essential tools for genome analysis in the coming years. We systematically compared the genome-wide CNV detection power of all 17 available array designs from the Affymetrix, Agilent, and Illumina platforms by hybridizing the well-characterized genome of 1000 Genomes Project subject NA12878 to all arrays, and performing data analysis using both manufacturer-recommended and platform-independent software. We benchmarked the resulting CNV call sets from each array using a gold standard set of CNVs for this genome derived from 1000 Genomes Project whole genome sequencing data. The arrays tested comprise both SNP and aCGH platforms with varying designs and contain between ~0.5 to ~4.6 million probes. Across the arrays CNV detection varied widely in number of CNV calls (4-489), CNV size range (~40 bp to ~8 Mbp), and percentage of non-validated CNVs (0-86%). We discovered strikingly strong effects of specific array design principles on performance. For example, some SNP array designs with the largest numbers of probes and extensive exonic coverage produced a considerable number of CNV calls that could not be validated, compared to designs with probe numbers that are sometimes an order of magnitude smaller. This effect was only partially ameliorated using different analysis software and optimizing data analysis parameters. High-resolution microarrays will continue to be used as reliable, cost- and time-efficient tools for CNV analysis. However, different applications tolerate different limitations in CNV detection. Our study quantified how these arrays differ in total number and size range of detected CNVs as well as sensitivity, and determined how each array balances these attributes. This analysis will inform appropriate array selection for future CNV studies, and allow better assessment of the CNV-analytical power of both published and ongoing array-based genomics studies. Furthermore, our findings emphasize the importance of concurrent use of multiple analysis algorithms and independent experimental validation in array-based CNV detection studies.

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

PubMed Central

2010-01-01

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

GStream: Improving SNP and CNV Coverage on Genome-Wide Association Studies

PubMed Central

Alonso, Arnald; Marsal, Sara; Tortosa, Raül; Canela-Xandri, Oriol; Julià, Antonio

2013-01-01

We present GStream, a method that combines genome-wide SNP and CNV genotyping in the Illumina microarray platform with unprecedented accuracy. This new method outperforms previous well-established SNP genotyping software. More importantly, the CNV calling algorithm of GStream dramatically improves the results obtained by previous state-of-the-art methods and yields an accuracy that is close to that obtained by purely CNV-oriented technologies like Comparative Genomic Hybridization (CGH). We demonstrate the superior performance of GStream using microarray data generated from HapMap samples. Using the reference CNV calls generated by the 1000 Genomes Project (1KGP) and well-known studies on whole genome CNV characterization based either on CGH or genotyping microarray technologies, we show that GStream can increase the number of reliably detected variants up to 25% compared to previously developed methods. Furthermore, the increased genome coverage provided by GStream allows the discovery of CNVs in close linkage disequilibrium with SNPs, previously associated with disease risk in published Genome-Wide Association Studies (GWAS). These results could provide important insights into the biological mechanism underlying the detected disease risk association. With GStream, large-scale GWAS will not only benefit from the combined genotyping of SNPs and CNVs at an unprecedented accuracy, but will also take advantage of the computational efficiency of the method. PMID:23844243

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

PubMed

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

2014-12-01

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

Thermodynamically optimal whole-genome tiling microarray design and validation.

PubMed

Cho, Hyejin; Chou, Hui-Hsien

2016-06-13

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

Knowledge-based analysis of microarrays for the discovery of transcriptional regulation relationships

PubMed Central

2010-01-01

Background The large amount of high-throughput genomic data has facilitated the discovery of the regulatory relationships between transcription factors and their target genes. While early methods for discovery of transcriptional regulation relationships from microarray data often focused on the high-throughput experimental data alone, more recent approaches have explored the integration of external knowledge bases of gene interactions. Results In this work, we develop an algorithm that provides improved performance in the prediction of transcriptional regulatory relationships by supplementing the analysis of microarray data with a new method of integrating information from an existing knowledge base. Using a well-known dataset of yeast microarrays and the Yeast Proteome Database, a comprehensive collection of known information of yeast genes, we show that knowledge-based predictions demonstrate better sensitivity and specificity in inferring new transcriptional interactions than predictions from microarray data alone. We also show that comprehensive, direct and high-quality knowledge bases provide better prediction performance. Comparison of our results with ChIP-chip data and growth fitness data suggests that our predicted genome-wide regulatory pairs in yeast are reasonable candidates for follow-up biological verification. Conclusion High quality, comprehensive, and direct knowledge bases, when combined with appropriate bioinformatic algorithms, can significantly improve the discovery of gene regulatory relationships from high throughput gene expression data. PMID:20122245

Knowledge-based analysis of microarrays for the discovery of transcriptional regulation relationships.

PubMed

Seok, Junhee; Kaushal, Amit; Davis, Ronald W; Xiao, Wenzhong

2010-01-18

The large amount of high-throughput genomic data has facilitated the discovery of the regulatory relationships between transcription factors and their target genes. While early methods for discovery of transcriptional regulation relationships from microarray data often focused on the high-throughput experimental data alone, more recent approaches have explored the integration of external knowledge bases of gene interactions. In this work, we develop an algorithm that provides improved performance in the prediction of transcriptional regulatory relationships by supplementing the analysis of microarray data with a new method of integrating information from an existing knowledge base. Using a well-known dataset of yeast microarrays and the Yeast Proteome Database, a comprehensive collection of known information of yeast genes, we show that knowledge-based predictions demonstrate better sensitivity and specificity in inferring new transcriptional interactions than predictions from microarray data alone. We also show that comprehensive, direct and high-quality knowledge bases provide better prediction performance. Comparison of our results with ChIP-chip data and growth fitness data suggests that our predicted genome-wide regulatory pairs in yeast are reasonable candidates for follow-up biological verification. High quality, comprehensive, and direct knowledge bases, when combined with appropriate bioinformatic algorithms, can significantly improve the discovery of gene regulatory relationships from high throughput gene expression data.

DNA methylation profiling using HpaII tiny fragment enrichment by ligation-mediated PCR (HELP)

PubMed Central

Suzuki, Masako; Greally, John M.

2010-01-01

The HELP assay is a technique that allows genome-wide analysis of cytosine methylation. Here we describe the assay, its relative strengths and weaknesses, and the transition of the assay from a microarray to massively-parallel sequencing-based foundation. PMID:20434563

Genome-Wide Screening of Genes Showing Altered Expression in Liver Metastases of Human Colorectal Cancers by cDNA Microarray1

PubMed Central

Yanagawa, Rempei; Furukawa, Yoichi; Tsunoda, Tatsuhiko; Kitahara, Osamu; Kameyama, Masao; Murata, Kohei; Ishikawa, Osamu; Nakamura, Yusuke

2001-01-01

Abstract 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. PMID:11687950

Genome-Wide Association Study of a Validated Case Definition of Gulf War Illness in a Population-Representative Sample

DTIC Science & Technology

2013-09-01

sequence dataset. All procedures were performed by personnel in the IIMT UT Southwestern Genomics and Microarray Core using standard protocols. More... sequencing run, samples were demultiplexed using standard algorithms in the Genomics and Microarray Core and processed into individual sample Illumina single... Sequencing (RNA-Seq), using Illumina’s multiplexing mRNA-Seq to generate full sequence libraries from the poly-A tailed RNA to a read depth of 30

A remark on copy number variation detection methods.

PubMed

Li, Shuo; Dou, Xialiang; Gao, Ruiqi; Ge, Xinzhou; Qian, Minping; Wan, Lin

2018-01-01

Copy number variations (CNVs) are gain and loss of DNA sequence of a genome. High throughput platforms such as microarrays and next generation sequencing technologies (NGS) have been applied for genome wide copy number losses. Although progress has been made in both approaches, the accuracy and consistency of CNV calling from the two platforms remain in dispute. In this study, we perform a deep analysis on copy number losses on 254 human DNA samples, which have both SNP microarray data and NGS data publicly available from Hapmap Project and 1000 Genomes Project respectively. We show that the copy number losses reported from Hapmap Project and 1000 Genome Project only have < 30% overlap, while these reports are required to have cross-platform (e.g. PCR, microarray and high-throughput sequencing) experimental supporting by their corresponding projects, even though state-of-art calling methods were employed. On the other hand, copy number losses are found directly from HapMap microarray data by an accurate algorithm, i.e. CNVhac, almost all of which have lower read mapping depth in NGS data; furthermore, 88% of which can be supported by the sequences with breakpoint in NGS data. Our results suggest the ability of microarray calling CNVs and the possible introduction of false negatives from the unessential requirement of the additional cross-platform supporting. The inconsistency of CNV reports from Hapmap Project and 1000 Genomes Project might result from the inadequate information containing in microarray data, the inconsistent detection criteria, or the filtration effect of cross-platform supporting. The statistical test on CNVs called from CNVhac show that the microarray data can offer reliable CNV reports, and majority of CNV candidates can be confirmed by raw sequences. Therefore, the CNV candidates given by a good caller could be highly reliable without cross-platform supporting, so additional experimental information should be applied in need instead of necessarily.

DNA microarrays: a powerful genomic tool for biomedical and clinical research

PubMed Central

Trevino, Victor; Falciani, Francesco; Barrera-Saldaña, Hugo A.

2007-01-01

Among the many benefits of the Human Genome Project are new and powerful tools such as the genome-wide hybridization devices referred as microarrays. Initially designed to measure gene transcriptional levels, microarray technologies are now used for comparing other genome features among individuals and their tissues and cells. Results provide valuable information on disease subcategories, disease prognosis, and treatment outcome. Likewise, reveal differences in genetic makeup, regulatory mechanisms and subtle variations are approaching the era of personalized medicine. To understand this powerful tool, its versatility and how it is dramatically changing the molecular approach to biomedical and clinical research, this review describes the technology, its applications, a didactic step-by-step review of a typical microarray protocol, and a real experiment. Finally, it calls the attention of the medical community to integrate multidisciplinary teams, to take advantage of this technology and its expanding applications that in a slide reveals our genetic inheritance and destiny. PMID:17660860

Effects of dietary plant-derived phytonutrients on the genome-wide profiles and coccidiosis resistance in the broiler chickens

USDA-ARS?s Scientific Manuscript database

The present study was conducted to investigate the effects of dietary plant-derived phytonutrients, carvacrol, cinnamaldehyde and Capsicum oleoresin, on the translational regulation of genes associated with immunology, physiology and metabolism using high-throughput microarray analysis and in vivo d...

Stress Sensors and Signal Transducers in Cyanobacteria

PubMed Central

Los, Dmitry A.; Zorina, Anna; Sinetova, Maria; Kryazhov, Sergey; Mironov, Kirill; Zinchenko, Vladislav V.

2010-01-01

In living cells, the perception of environmental stress and the subsequent transduction of stress signals are primary events in the acclimation to changes in the environment. Some molecular sensors and transducers of environmental stress cannot be identified by traditional and conventional methods. Based on genomic information, a systematic approach has been applied to the solution of this problem in cyanobacteria, involving mutagenesis of potential sensors and signal transducers in combination with DNA microarray analyses for the genome-wide expression of genes. Forty-five genes for the histidine kinases (Hiks), 12 genes for serine-threonine protein kinases (Spks), 42 genes for response regulators (Rres), seven genes for RNA polymerase sigma factors, and nearly 70 genes for transcription factors have been successfully inactivated by targeted mutagenesis in the unicellular cyanobacterium Synechocystis sp. PCC 6803. Screening of mutant libraries by genome-wide DNA microarray analysis under various stress and non-stress conditions has allowed identification of proteins that perceive and transduce signals of environmental stress. Here we summarize recent progress in the identification of sensory and regulatory systems, including Hiks, Rres, Spks, sigma factors, transcription factors, and the role of genomic DNA supercoiling in the regulation of the responses of cyanobacterial cells to various types of stress. PMID:22294932

Molecular Differentiation of Risk for Disease Progression: Delineating Stage-Specific Therapeutic Targets for Disease Management in Breast Cancer

DTIC Science & Technology

2006-07-01

Jeffrey S. S., Botstein D ., Brown P . O. Genome-wide analysis of DNA copy-number changes using cDNA microarrays. Nat. Genet., 23: 41-46, 1999 3...Duggan D . J., Bittner M., Chen Y., Meltzer P ., Trent J. M. Expression profiling using cDNA microarrays. Nat. Genet., 21: 10-14, 1999 4. Oh J. M...1999 5. Golub T. R., Slonim D . K., Tamayo P ., Huard C., Gaasenbeek M., Mesirov J. P ., Coller H., Loh M. L., Downing J. R., Caligiuri M. A

Next generation tools for genomic data generation, distribution, and visualization

PubMed Central

2010-01-01

Background With the rapidly falling cost and availability of high throughput sequencing and microarray technologies, the bottleneck for effectively using genomic analysis in the laboratory and clinic is shifting to one of effectively managing, analyzing, and sharing genomic data. Results Here we present three open-source, platform independent, software tools for generating, analyzing, distributing, and visualizing genomic data. These include a next generation sequencing/microarray LIMS and analysis project center (GNomEx); an application for annotating and programmatically distributing genomic data using the community vetted DAS/2 data exchange protocol (GenoPub); and a standalone Java Swing application (GWrap) that makes cutting edge command line analysis tools available to those who prefer graphical user interfaces. Both GNomEx and GenoPub use the rich client Flex/Flash web browser interface to interact with Java classes and a relational database on a remote server. Both employ a public-private user-group security model enabling controlled distribution of patient and unpublished data alongside public resources. As such, they function as genomic data repositories that can be accessed manually or programmatically through DAS/2-enabled client applications such as the Integrated Genome Browser. Conclusions These tools have gained wide use in our core facilities, research laboratories and clinics and are freely available for non-profit use. See http://sourceforge.net/projects/gnomex/, http://sourceforge.net/projects/genoviz/, and http://sourceforge.net/projects/useq. PMID:20828407

Privacy Preserving PCA on Distributed Bioinformatics Datasets

ERIC Educational Resources Information Center

Li, Xin

2011-01-01

In recent years, new bioinformatics technologies, such as gene expression microarray, genome-wide association study, proteomics, and metabolomics, have been widely used to simultaneously identify a huge number of human genomic/genetic biomarkers, generate a tremendously large amount of data, and dramatically increase the knowledge on human…

Library of molecular associations: curating the complex molecular basis of liver diseases.

PubMed

Buchkremer, Stefan; Hendel, Jasmin; Krupp, Markus; Weinmann, Arndt; Schlamp, Kai; Maass, Thorsten; Staib, Frank; Galle, Peter R; Teufel, Andreas

2010-03-20

Systems biology approaches offer novel insights into the development of chronic liver diseases. Current genomic databases supporting systems biology analyses are mostly based on microarray data. Although these data often cover genome wide expression, the validity of single microarray experiments remains questionable. However, for systems biology approaches addressing the interactions of molecular networks comprehensive but also highly validated data are necessary. We have therefore generated the first comprehensive database for published molecular associations in human liver diseases. It is based on PubMed published abstracts and aimed to close the gap between genome wide coverage of low validity from microarray data and individual highly validated data from PubMed. After an initial text mining process, the extracted abstracts were all manually validated to confirm content and potential genetic associations and may therefore be highly trusted. All data were stored in a publicly available database, Library of Molecular Associations http://www.medicalgenomics.org/databases/loma/news, currently holding approximately 1260 confirmed molecular associations for chronic liver diseases such as HCC, CCC, liver fibrosis, NASH/fatty liver disease, AIH, PBC, and PSC. We furthermore transformed these data into a powerful resource for molecular liver research by connecting them to multiple biomedical information resources. Together, this database is the first available database providing a comprehensive view and analysis options for published molecular associations on multiple liver diseases.

A comprehensive transcript index of the human genome generated using microarrays and computational approaches

PubMed Central

Schadt, Eric E; Edwards, Stephen W; GuhaThakurta, Debraj; Holder, Dan; Ying, Lisa; Svetnik, Vladimir; Leonardson, Amy; Hart, Kyle W; Russell, Archie; Li, Guoya; Cavet, Guy; Castle, John; McDonagh, Paul; Kan, Zhengyan; Chen, Ronghua; Kasarskis, Andrew; Margarint, Mihai; Caceres, Ramon M; Johnson, Jason M; Armour, Christopher D; Garrett-Engele, Philip W; Tsinoremas, Nicholas F; Shoemaker, Daniel D

2004-01-01

Background Computational and microarray-based experimental approaches were used to generate a comprehensive transcript index for the human genome. Oligonucleotide probes designed from approximately 50,000 known and predicted transcript sequences from the human genome were used to survey transcription from a diverse set of 60 tissues and cell lines using ink-jet microarrays. Further, expression activity over at least six conditions was more generally assessed using genomic tiling arrays consisting of probes tiled through a repeat-masked version of the genomic sequence making up chromosomes 20 and 22. Results The combination of microarray data with extensive genome annotations resulted in a set of 28,456 experimentally supported transcripts. This set of high-confidence transcripts represents the first experimentally driven annotation of the human genome. In addition, the results from genomic tiling suggest that a large amount of transcription exists outside of annotated regions of the genome and serves as an example of how this activity could be measured on a genome-wide scale. Conclusions These data represent one of the most comprehensive assessments of transcriptional activity in the human genome and provide an atlas of human gene expression over a unique set of gene predictions. Before the annotation of the human genome is considered complete, however, the previously unannotated transcriptional activity throughout the genome must be fully characterized. PMID:15461792

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

PubMed

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

2003-04-01

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

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

PubMed Central

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

2009-01-01

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

Gene expression profile of blood cells for the prediction of delayed cerebral ischemia after intracranial aneurysm rupture: a pilot study in humans.

PubMed

Baumann, Antoine; Devaux, Yvan; Audibert, Gérard; Zhang, Lu; Bracard, Serge; Colnat-Coulbois, Sophie; Klein, Olivier; Zannad, Faiez; Charpentier, Claire; Longrois, Dan; Mertes, Paul-Michel

2013-01-01

Delayed cerebral ischemia (DCI) is a potentially devastating complication after intracranial aneurysm rupture and its mechanisms remain poorly elucidated. Early identification of the patients prone to developing DCI after rupture may represent a major breakthrough in its prevention and treatment. The single gene approach of DCI has demonstrated interest in humans. We hypothesized that whole genome expression profile of blood cells may be useful for better comprehension and prediction of aneurysmal DCI. Over a 35-month period, 218 patients with aneurysm rupture were included in this study. DCI was defined as the occurrence of a new delayed neurological deficit occurring within 2 weeks after aneurysm rupture with evidence of ischemia either on perfusion-diffusion MRI, CT angiography or CT perfusion imaging, or with cerebral angiography. DCI patients were matched against controls based on 4 out of 5 criteria (age, sex, Fisher grade, aneurysm location and smoking status). Genome-wide expression analysis of blood cells obtained at admission was performed by microarrays. Transcriptomic analysis was performed using long oligonucleotide microarrays representing 25,000 genes. Quantitative PCR: 1 µg of total RNA extracted was reverse-transcribed, and the resulting cDNA was diluted 10-fold before performing quantitative PCR. Microarray data were first analyzed by 'Significance Analysis of Microarrays' software which includes the Benjamini correction for multiple testing. In a second step, microarray data fold change was compared using a two-tailed, paired t test. Analysis of receiver-operating characteristic (ROC) curves and the area under the ROC curves were used for prediction analysis. Logistic regression models were used to investigate the additive value of multiple biomarkers. A total of 16 patients demonstrated DCI. Significance Analysis of Microarrays software failed to retrieve significant genes, most probably because of the heterogeneity of the patients included in the microarray experiments and the small size of the DCI population sample. Standard two-tailed paired t test and C-statistic revealed significant associations between gene expression and the occurrence of DCI: in particular, the expression of neuroregulin 1 was 1.6-fold upregulated in patients with DCI (p = 0.01) and predicted DCI with an area under the ROC curve of 0.96. Logistic regression analyses revealed a significant association between neuroregulin 1 and DCI (odds ratio 1.46, 95% confidence interval 1.02-2.09, p = 0.02). This pilot study suggests that blood cells may be a reservoir of prognostic biomarkers of DCI in patients with intracranial aneurysm rupture. Despite an evident lack of power, this study elicited neuroregulin 1, a vasoreactivity-, inflammation- and angiogenesis-related gene, as a possible candidate predictor of DCI. Larger cohort studies are needed but genome-wide microarray-based studies are promising research tools for the understanding of DCI after intracranial aneurysm rupture. © 2013 S. Karger AG, Basel.

Integrated Analysis of Pharmacologic, Clinical, and SNP Microarray Data using Projection onto the Most Interesting Statistical Evidence with Adaptive Permutation Testing

PubMed Central

Pounds, Stan; Cao, Xueyuan; Cheng, Cheng; Yang, Jun; Campana, Dario; Evans, William E.; Pui, Ching-Hon; Relling, Mary V.

2010-01-01

Powerful methods for integrated analysis of multiple biological data sets are needed to maximize interpretation capacity and acquire meaningful knowledge. We recently developed Projection Onto the Most Interesting Statistical Evidence (PROMISE). PROMISE is a statistical procedure that incorporates prior knowledge about the biological relationships among endpoint variables into an integrated analysis of microarray gene expression data with multiple biological and clinical endpoints. Here, PROMISE is adapted to the integrated analysis of pharmacologic, clinical, and genome-wide genotype data that incorporating knowledge about the biological relationships among pharmacologic and clinical response data. An efficient permutation-testing algorithm is introduced so that statistical calculations are computationally feasible in this higher-dimension setting. The new method is applied to a pediatric leukemia data set. The results clearly indicate that PROMISE is a powerful statistical tool for identifying genomic features that exhibit a biologically meaningful pattern of association with multiple endpoint variables. PMID:21516175

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

PubMed

Flibotte, Stephane; Moerman, Donald G

2008-10-21

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. 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 degrees 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 quality when varying the oligonucleotide length between 50 and 70, and even when using an isothermal design strategy. We have determined experimentally the effects of varying several key oligonucleotide microarray design criteria for detection of deletions in C. elegans and humans with NimbleGen's CGH technology. Our oligonucleotide design recommendations should be applicable for CGH analysis in most species.

The genome-wide expression profile of Curcuma longa-treated cisplatin-stimulated HEK293 cells

PubMed Central

Sohn, Sung-Hwa; Ko, Eunjung; Chung, Hwan-Suck; Lee, Eun-Young; Kim, Sung-Hoon; Shin, Minkyu; Hong, Moochang; Bae, Hyunsu

2010-01-01

AIM The rhizome of turmeric, Curcuma longa (CL), is a herbal medicine used in many traditional prescriptions. It has previously been shown that CL treatment showed greater than 47% recovery from cisplatin-induced cell damage in human kidney HEK 293 cells. This study was conducted to evaluate the recovery mechanisms of CL that occur during cisplatin induced nephrotoxicity by examining the genome wide mRNA expression profiles of HEK 293 -cells. METHOD Recovery mechanisms of CL that occur during cisplatin-induced nephrotoxicity were determined by microarray, real-time PCR, immunofluorescent confocal microscopy and Western blot analysis. RESULTS The results of microarray analysis and real-time PCR revealed that NFκB pathway-related genes and apoptosis-related genes were down-regulated in CL-treated HEK 293 cells. In addition, immunofluorescent confocal microscopy and Western blot analysis revealed that NFκB p65 nuclear translocation was inhibited in CL-treated HEK 293 cells. Therefore, the mechanism responsible for the effects of CL on HEK 293 cells is closely associated with regulation of the NFκB pathway. CONCLUSION CL possesses novel therapeutic agents that can be used for the prevention or treatment of cisplatin-induced renal disorders. PMID:20840446

Toward a Genome-Wide Systems Biology Analysis of Host-Pathogen Interactions in Group A Streptococcus

PubMed Central

Musser, James M.; DeLeo, Frank R.

2005-01-01

Genome-wide analysis of microbial pathogens and molecular pathogenesis processes has become an area of considerable activity in the last 5 years. These studies have been made possible by several advances, including completion of the human genome sequence, publication of genome sequences for many human pathogens, development of microarray technology and high-throughput proteomics, and maturation of bioinformatics. Despite these advances, relatively little effort has been expended in the bacterial pathogenesis arena to develop and use integrated research platforms in a systems biology approach to enhance our understanding of disease processes. This review discusses progress made in exploiting an integrated genome-wide research platform to gain new knowledge about how the human bacterial pathogen group A Streptococcus causes disease. Results of these studies have provided many new avenues for basic pathogenesis research and translational research focused on development of an efficacious human vaccine and novel therapeutics. One goal in summarizing this line of study is to bring exciting new findings to the attention of the investigative pathology community. In addition, we hope the review will stimulate investigators to consider using analogous approaches for analysis of the molecular pathogenesis of other microbes. PMID:16314461

Issues in the analysis of oligonucleotide tiling microarrays for transcript mapping

NASA Technical Reports Server (NTRS)

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

2005-01-01

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

An efficient pseudomedian filter for tiling microrrays.

PubMed

Royce, Thomas E; Carriero, Nicholas J; Gerstein, Mark B

2007-06-07

Tiling microarrays are becoming an essential technology in the functional genomics toolbox. They have been applied to the tasks of novel transcript identification, elucidation of transcription factor binding sites, detection of methylated DNA and several other applications in several model organisms. These experiments are being conducted at increasingly finer resolutions as the microarray technology enjoys increasingly greater feature densities. The increased densities naturally lead to increased data analysis requirements. Specifically, the most widely employed algorithm for tiling array analysis involves smoothing observed signals by computing pseudomedians within sliding windows, a O(n2logn) calculation in each window. This poor time complexity is an issue for tiling array analysis and could prove to be a real bottleneck as tiling microarray experiments become grander in scope and finer in resolution. We therefore implemented Monahan's HLQEST algorithm that reduces the runtime complexity for computing the pseudomedian of n numbers to O(nlogn) from O(n2logn). For a representative tiling microarray dataset, this modification reduced the smoothing procedure's runtime by nearly 90%. We then leveraged the fact that elements within sliding windows remain largely unchanged in overlapping windows (as one slides across genomic space) to further reduce computation by an additional 43%. This was achieved by the application of skip lists to maintaining a sorted list of values from window to window. This sorted list could be maintained with simple O(log n) inserts and deletes. We illustrate the favorable scaling properties of our algorithms with both time complexity analysis and benchmarking on synthetic datasets. Tiling microarray analyses that rely upon a sliding window pseudomedian calculation can require many hours of computation. We have eased this requirement significantly by implementing efficient algorithms that scale well with genomic feature density. This result not only speeds the current standard analyses, but also makes possible ones where many iterations of the filter may be required, such as might be required in a bootstrap or parameter estimation setting. Source code and executables are available at http://tiling.gersteinlab.org/pseudomedian/.

An efficient pseudomedian filter for tiling microrrays

PubMed Central

Royce, Thomas E; Carriero, Nicholas J; Gerstein, Mark B

2007-01-01

Background Tiling microarrays are becoming an essential technology in the functional genomics toolbox. They have been applied to the tasks of novel transcript identification, elucidation of transcription factor binding sites, detection of methylated DNA and several other applications in several model organisms. These experiments are being conducted at increasingly finer resolutions as the microarray technology enjoys increasingly greater feature densities. The increased densities naturally lead to increased data analysis requirements. Specifically, the most widely employed algorithm for tiling array analysis involves smoothing observed signals by computing pseudomedians within sliding windows, a O(n2logn) calculation in each window. This poor time complexity is an issue for tiling array analysis and could prove to be a real bottleneck as tiling microarray experiments become grander in scope and finer in resolution. Results We therefore implemented Monahan's HLQEST algorithm that reduces the runtime complexity for computing the pseudomedian of n numbers to O(nlogn) from O(n2logn). For a representative tiling microarray dataset, this modification reduced the smoothing procedure's runtime by nearly 90%. We then leveraged the fact that elements within sliding windows remain largely unchanged in overlapping windows (as one slides across genomic space) to further reduce computation by an additional 43%. This was achieved by the application of skip lists to maintaining a sorted list of values from window to window. This sorted list could be maintained with simple O(log n) inserts and deletes. We illustrate the favorable scaling properties of our algorithms with both time complexity analysis and benchmarking on synthetic datasets. Conclusion Tiling microarray analyses that rely upon a sliding window pseudomedian calculation can require many hours of computation. We have eased this requirement significantly by implementing efficient algorithms that scale well with genomic feature density. This result not only speeds the current standard analyses, but also makes possible ones where many iterations of the filter may be required, such as might be required in a bootstrap or parameter estimation setting. Source code and executables are available at . PMID:17555595

sigReannot: an oligo-set re-annotation pipeline based on similarities with the Ensembl transcripts and Unigene clusters.

PubMed

Casel, Pierrot; Moreews, François; Lagarrigue, Sandrine; Klopp, Christophe

2009-07-16

Microarray is a powerful technology enabling to monitor tens of thousands of genes in a single experiment. Most microarrays are now using oligo-sets. The design of the oligo-nucleotides is time consuming and error prone. Genome wide microarray oligo-sets are designed using as large a set of transcripts as possible in order to monitor as many genes as possible. Depending on the genome sequencing state and on the assembly state the knowledge of the existing transcripts can be very different. This knowledge evolves with the different genome builds and gene builds. Once the design is done the microarrays are often used for several years. The biologists working in EADGENE expressed the need of up-to-dated annotation files for the oligo-sets they share including information about the orthologous genes of model species, the Gene Ontology, the corresponding pathways and the chromosomal location. The results of SigReannot on a chicken micro-array used in the EADGENE project compared to the initial annotations show that 23% of the oligo-nucleotide gene annotations were not confirmed, 2% were modified and 1% were added. The interest of this up-to-date annotation procedure is demonstrated through the analysis of real data previously published. SigReannot uses the oligo-nucleotide design procedure criteria to validate the probe-gene link and the Ensembl transcripts as reference for annotation. It therefore produces a high quality annotation based on reference gene sets.

A novel strategy of integrated microarray analysis identifies CENPA, CDK1 and CDC20 as a cluster of diagnostic biomarkers in lung adenocarcinoma.

PubMed

Liu, Wan-Ting; Wang, Yang; Zhang, Jing; Ye, Fei; Huang, Xiao-Hui; Li, Bin; He, Qing-Yu

2018-07-01

Lung adenocarcinoma (LAC) is the most lethal cancer and the leading cause of cancer-related death worldwide. The identification of meaningful clusters of co-expressed genes or representative biomarkers may help improve the accuracy of LAC diagnoses. Public databases, such as the Gene Expression Omnibus (GEO), provide rich resources of valuable information for clinics, however, the integration of multiple microarray datasets from various platforms and institutes remained a challenge. To determine potential indicators of LAC, we performed genome-wide relative significance (GWRS), genome-wide global significance (GWGS) and support vector machine (SVM) analyses progressively to identify robust gene biomarker signatures from 5 different microarray datasets that included 330 samples. The top 200 genes with robust signatures were selected for integrative analysis according to "guilt-by-association" methods, including protein-protein interaction (PPI) analysis and gene co-expression analysis. Of these 200 genes, only 10 genes showed both intensive PPI network and high gene co-expression correlation (r > 0.8). IPA analysis of this regulatory networks suggested that the cell cycle process is a crucial determinant of LAC. CENPA, as well as two linked hub genes CDK1 and CDC20, are determined to be potential indicators of LAC. Immunohistochemical staining showed that CENPA, CDK1 and CDC20 were highly expressed in LAC cancer tissue with co-expression patterns. A Cox regression model indicated that LAC patients with CENPA + /CDK1 + and CENPA + /CDC20 + were high-risk groups in terms of overall survival. In conclusion, our integrated microarray analysis demonstrated that CENPA, CDK1 and CDC20 might serve as novel cluster of prognostic biomarkers for LAC, and the cooperative unit of three genes provides a technically simple approach for identification of LAC patients. Copyright © 2018 Elsevier B.V. All rights reserved.

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

PubMed

Elingaramil, Sauli; Li, Xiaolong; He, Nongyue

2013-07-01

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

Transcriptome Profiling of In-Vivo Produced Bovine Pre-implantation Embryos Using Two-color Microarray Platform.

PubMed

Salehi, Reza; Tsoi, Stephen C M; Colazo, Marcos G; Ambrose, Divakar J; Robert, Claude; Dyck, Michael K

2017-01-30

Early embryonic loss is a large contributor to infertility in cattle. Moreover, bovine becomes an interesting model to study human preimplantation embryo development due to their similar developmental process. Although genetic factors are known to affect early embryonic development, the discovery of such factors has been a serious challenge. Microarray technology allows quantitative measurement and gene expression profiling of transcript levels on a genome-wide basis. One of the main decisions that have to be made when planning a microarray experiment is whether to use a one- or two-color approach. Two-color design increases technical replication, minimizes variability, improves sensitivity and accuracy as well as allows having loop designs, defining the common reference samples. Although microarray is a powerful biological tool, there are potential pitfalls that can attenuate its power. Hence, in this technical paper we demonstrate an optimized protocol for RNA extraction, amplification, labeling, hybridization of the labeled amplified RNA to the array, array scanning and data analysis using the two-color analysis strategy.

BIOMONITORING THE TOXICOGENOMIC RESPONSE TO ENDOCRINE DISRUPTING CHEMICALS IN HUMANS, LABORATORY SPECIES AND WILDLIFE

EPA Science Inventory

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

Genome-Wide Comparative In Silico Analysis of the RNA Helicase Gene Family in Zea mays and Glycine max: A Comparison with Arabidopsis and Oryza sativa

PubMed Central

Huang, Jinguang; Zheng, Chengchao

2013-01-01

RNA helicases are enzymes that are thought to unwind double-stranded RNA molecules in an energy-dependent fashion through the hydrolysis of NTP. RNA helicases are associated with all processes involving RNA molecules, including nuclear transcription, editing, splicing, ribosome biogenesis, RNA export, and organelle gene expression. The involvement of RNA helicase in response to stress and in plant growth and development has been reported previously. While their importance in Arabidopsis and Oryza sativa has been partially studied, the function of RNA helicase proteins is poorly understood in Zea mays and Glycine max. In this study, we identified a total of RNA helicase genes in Arabidopsis and other crop species genome by genome-wide comparative in silico analysis. We classified the RNA helicase genes into three subfamilies according to the structural features of the motif II region, such as DEAD-box, DEAH-box and DExD/H-box, and different species showed different patterns of alternative splicing. Secondly, chromosome location analysis showed that the RNA helicase protein genes were distributed across all chromosomes with different densities in the four species. Thirdly, phylogenetic tree analyses identified the relevant homologs of DEAD-box, DEAH-box and DExD/H-box RNA helicase proteins in each of the four species. Fourthly, microarray expression data showed that many of these predicted RNA helicase genes were expressed in different developmental stages and different tissues under normal growth conditions. Finally, real-time quantitative PCR analysis showed that the expression levels of 10 genes in Arabidopsis and 13 genes in Zea mays were in close agreement with the microarray expression data. To our knowledge, this is the first report of a comparative genome-wide analysis of the RNA helicase gene family in Arabidopsis, Oryza sativa, Zea mays and Glycine max. This study provides valuable information for understanding the classification and putative functions of the RNA helicase gene family in crop growth and development. PMID:24265739

Genome-wide comparative in silico analysis of the RNA helicase gene family in Zea mays and Glycine max: a comparison with Arabidopsis and Oryza sativa.

PubMed

Xu, Ruirui; Zhang, Shizhong; Huang, Jinguang; Zheng, Chengchao

2013-01-01

RNA helicases are enzymes that are thought to unwind double-stranded RNA molecules in an energy-dependent fashion through the hydrolysis of NTP. RNA helicases are associated with all processes involving RNA molecules, including nuclear transcription, editing, splicing, ribosome biogenesis, RNA export, and organelle gene expression. The involvement of RNA helicase in response to stress and in plant growth and development has been reported previously. While their importance in Arabidopsis and Oryza sativa has been partially studied, the function of RNA helicase proteins is poorly understood in Zea mays and Glycine max. In this study, we identified a total of RNA helicase genes in Arabidopsis and other crop species genome by genome-wide comparative in silico analysis. We classified the RNA helicase genes into three subfamilies according to the structural features of the motif II region, such as DEAD-box, DEAH-box and DExD/H-box, and different species showed different patterns of alternative splicing. Secondly, chromosome location analysis showed that the RNA helicase protein genes were distributed across all chromosomes with different densities in the four species. Thirdly, phylogenetic tree analyses identified the relevant homologs of DEAD-box, DEAH-box and DExD/H-box RNA helicase proteins in each of the four species. Fourthly, microarray expression data showed that many of these predicted RNA helicase genes were expressed in different developmental stages and different tissues under normal growth conditions. Finally, real-time quantitative PCR analysis showed that the expression levels of 10 genes in Arabidopsis and 13 genes in Zea mays were in close agreement with the microarray expression data. To our knowledge, this is the first report of a comparative genome-wide analysis of the RNA helicase gene family in Arabidopsis, Oryza sativa, Zea mays and Glycine max. This study provides valuable information for understanding the classification and putative functions of the RNA helicase gene family in crop growth and development.

Genome-wide transcriptional analysis of flagellar regeneration in Chlamydomonas reinhardtii identifies orthologs of ciliary disease genes

NASA Technical Reports Server (NTRS)

Stolc, Viktor; Samanta, Manoj Pratim; Tongprasit, Waraporn; Marshall, Wallace F.

2005-01-01

The important role that cilia and flagella play in human disease creates an urgent need to identify genes involved in ciliary assembly and function. The strong and specific induction of flagellar-coding genes during flagellar regeneration in Chlamydomonas reinhardtii suggests that transcriptional profiling of such cells would reveal new flagella-related genes. We have conducted a genome-wide analysis of RNA transcript levels during flagellar regeneration in Chlamydomonas by using maskless photolithography method-produced DNA oligonucleotide microarrays with unique probe sequences for all exons of the 19,803 predicted genes. This analysis represents previously uncharacterized whole-genome transcriptional activity profiling study in this important model organism. Analysis of strongly induced genes reveals a large set of known flagellar components and also identifies a number of important disease-related proteins as being involved with cilia and flagella, including the zebrafish polycystic kidney genes Qilin, Reptin, and Pontin, as well as the testis-expressed tubby-like protein TULP2.

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

USDA-ARS?s Scientific Manuscript database

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 wide...

Detecting discordance enrichment among a series of two-sample genome-wide expression data sets.

PubMed

Lai, Yinglei; Zhang, Fanni; Nayak, Tapan K; Modarres, Reza; Lee, Norman H; McCaffrey, Timothy A

2017-01-25

With the current microarray and RNA-seq technologies, two-sample genome-wide expression data have been widely collected in biological and medical studies. The related differential expression analysis and gene set enrichment analysis have been frequently conducted. Integrative analysis can be conducted when multiple data sets are available. In practice, discordant molecular behaviors among a series of data sets can be of biological and clinical interest. In this study, a statistical method is proposed for detecting discordance gene set enrichment. Our method is based on a two-level multivariate normal mixture model. It is statistically efficient with linearly increased parameter space when the number of data sets is increased. The model-based probability of discordance enrichment can be calculated for gene set detection. We apply our method to a microarray expression data set collected from forty-five matched tumor/non-tumor pairs of tissues for studying pancreatic cancer. We divided the data set into a series of non-overlapping subsets according to the tumor/non-tumor paired expression ratio of gene PNLIP (pancreatic lipase, recently shown it association with pancreatic cancer). The log-ratio ranges from a negative value (e.g. more expressed in non-tumor tissue) to a positive value (e.g. more expressed in tumor tissue). Our purpose is to understand whether any gene sets are enriched in discordant behaviors among these subsets (when the log-ratio is increased from negative to positive). We focus on KEGG pathways. The detected pathways will be useful for our further understanding of the role of gene PNLIP in pancreatic cancer research. Among the top list of detected pathways, the neuroactive ligand receptor interaction and olfactory transduction pathways are the most significant two. Then, we consider gene TP53 that is well-known for its role as tumor suppressor in cancer research. The log-ratio also ranges from a negative value (e.g. more expressed in non-tumor tissue) to a positive value (e.g. more expressed in tumor tissue). We divided the microarray data set again according to the expression ratio of gene TP53. After the discordance enrichment analysis, we observed overall similar results and the above two pathways are still the most significant detections. More interestingly, only these two pathways have been identified for their association with pancreatic cancer in a pathway analysis of genome-wide association study (GWAS) data. This study illustrates that some disease-related pathways can be enriched in discordant molecular behaviors when an important disease-related gene changes its expression. Our proposed statistical method is useful in the detection of these pathways. Furthermore, our method can also be applied to genome-wide expression data collected by the recent RNA-seq technology.

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

PubMed

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

2008-02-06

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

Threshold-free high-power methods for the ontological analysis of genome-wide gene-expression studies

PubMed Central

Nilsson, Björn; Håkansson, Petra; Johansson, Mikael; Nelander, Sven; Fioretos, Thoas

2007-01-01

Ontological analysis facilitates the interpretation of microarray data. Here we describe new ontological analysis methods which, unlike existing approaches, are threshold-free and statistically powerful. We perform extensive evaluations and introduce a new concept, detection spectra, to characterize methods. We show that different ontological analysis methods exhibit distinct detection spectra, and that it is critical to account for this diversity. Our results argue strongly against the continued use of existing methods, and provide directions towards an enhanced approach. PMID:17488501

Comprehensive Analysis of DNA Methylation Data with RnBeads

PubMed Central

Walter, Jörn; Lengauer, Thomas; Bock, Christoph

2014-01-01

RnBeads is a software tool for large-scale analysis and interpretation of DNA methylation data, providing a user-friendly analysis workflow that yields detailed hypertext reports (http://rnbeads.mpi-inf.mpg.de). Supported assays include whole genome bisulfite sequencing, reduced representation bisulfite sequencing, Infinium microarrays, and any other protocol that produces high-resolution DNA methylation data. Important applications of RnBeads include the analysis of epigenome-wide association studies and epigenetic biomarker discovery in cancer cohorts. PMID:25262207

Integrative ChIP-seq/Microarray Analysis Identifies a CTNNB1 Target Signature Enriched in Intestinal Stem Cells and Colon Cancer

PubMed Central

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

2014-01-01

Background Deregulation of canonical Wnt/CTNNB1 (beta-catenin) pathway is one of the earliest events in the pathogenesis of colon cancer. Mutations in APC or CTNNB1 are highly frequent in colon cancer and cause aberrant stabilization of CTNNB1, which activates the transcription of Wnt target genes by binding to chromatin via the TCF/LEF transcription factors. Here we report an integrative analysis of genome-wide chromatin occupancy of CTNNB1 by chromatin immunoprecipitation coupled with high-throughput sequencing (ChIP-seq) and gene expression profiling by microarray analysis upon RNAi-mediated knockdown of CTNNB1 in colon cancer cells. Results We observed 3629 CTNNB1 binding peaks across the genome and a significant correlation between CTNNB1 binding and knockdown-induced gene expression change. Our integrative analysis led to the discovery of a direct Wnt target signature composed of 162 genes. Gene ontology analysis of this signature revealed a significant enrichment of Wnt pathway genes, suggesting multiple feedback regulations of the pathway. We provide evidence that this gene signature partially overlaps with the Lgr5+ intestinal stem cell signature, and is significantly enriched in normal intestinal stem cells as well as in clinical colorectal cancer samples. Interestingly, while the expression of the CTNNB1 target gene set does not correlate with survival, elevated expression of negative feedback regulators within the signature predicts better prognosis. Conclusion Our data provide a genome-wide view of chromatin occupancy and gene regulation of Wnt/CTNNB1 signaling in colon cancer cells. PMID:24651522

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

PubMed

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

2014-01-01

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

Mobile Interspersed Repeats Are Major Structural Variants in the Human Genome

PubMed Central

Huang, Cheng Ran Lisa; Schneider, Anna M.; Lu, Yunqi; Niranjan, Tejasvi; Shen, Peilin; Robinson, Matoya A.; Steranka, Jared P.; Valle, David; Civin, Curt I.; Wang, Tao; Wheelan, Sarah J.; Ji, Hongkai; Boeke, Jef D.; Burns, Kathleen H.

2010-01-01

Summary Characterizing structural variants in the human genome is of great importance, but a genome wide analysis to detect interspersed repeats has not been done. Thus, the degree to which mobile DNAs contribute to genetic diversity, heritable disease, and oncogenesis remains speculative. We perform transposon insertion profiling by microarray (TIP-chip) to map human L1(Ta) retrotransposons (LINE-1 s) genome-wide. This identified numerous novel human L1(Ta) insertional polymorphisms with highly variant allelic frequencies. We also explored TIP-chip's usefulness to identify candidate alleles associated with different phenotypes in clinical cohorts. Our data suggest that the occurrence of new insertions is twice as high as previously estimated, and that these repeats are under-recognized as sources of human genomic and phenotypic diversity. We have just begun to probe the universe of human L1(Ta) polymorphisms, and as TIP-chip is applied to other insertions such as Alu SINEs, it will expand the catalog of genomic variants even further. PMID:20602999

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

ERIC Educational Resources Information Center

Grenville-Briggs, Laura J.; Stansfield, Ian

2011-01-01

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

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

PubMed

Chockalingam, Sriram; Aluru, Maneesha; Aluru, Srinivas

2016-09-19

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

Broad spectrum microarray for fingerprint-based bacterial species identification

PubMed Central

2010-01-01

Background Microarrays are powerful tools for DNA-based molecular diagnostics and identification of pathogens. Most target a limited range of organisms and are based on only one or a very few genes for specific identification. Such microarrays are limited to organisms for which specific probes are available, and often have difficulty discriminating closely related taxa. We have developed an alternative broad-spectrum microarray that employs hybridisation fingerprints generated by high-density anonymous markers distributed over the entire genome for identification based on comparison to a reference database. Results A high-density microarray carrying 95,000 unique 13-mer probes was designed. Optimized methods were developed to deliver reproducible hybridisation patterns that enabled confident discrimination of bacteria at the species, subspecies, and strain levels. High correlation coefficients were achieved between replicates. A sub-selection of 12,071 probes, determined by ANOVA and class prediction analysis, enabled the discrimination of all samples in our panel. Mismatch probe hybridisation was observed but was found to have no effect on the discriminatory capacity of our system. Conclusions These results indicate the potential of our genome chip for reliable identification of a wide range of bacterial taxa at the subspecies level without laborious prior sequencing and probe design. With its high resolution capacity, our proof-of-principle chip demonstrates great potential as a tool for molecular diagnostics of broad taxonomic groups. PMID:20163710

Microarray platform for omics analysis

NASA Astrophysics Data System (ADS)

Mecklenburg, Michael; Xie, Bin

2001-09-01

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

Molecular definition of the identity and activation of natural killer cells.

PubMed

Bezman, Natalie A; Kim, Charles C; Sun, Joseph C; Min-Oo, Gundula; Hendricks, Deborah W; Kamimura, Yosuke; Best, J Adam; Goldrath, Ananda W; Lanier, Lewis L

2012-10-01

Using whole-genome microarray data sets of the Immunological Genome Project, we demonstrate a closer transcriptional relationship between NK cells and T cells than between any other leukocytes, distinguished by their shared expression of genes encoding molecules with similar signaling functions. Whereas resting NK cells are known to share expression of a few genes with cytotoxic CD8(+) T cells, our transcriptome-wide analysis demonstrates that the commonalities extend to hundreds of genes, many encoding molecules with unknown functions. Resting NK cells demonstrate a 'preprimed' state compared with naive T cells, which allows NK cells to respond more rapidly to viral infection. Collectively, our data provide a global context for known and previously unknown molecular aspects of NK cell identity and function by delineating the genome-wide repertoire of gene expression of NK cells in various states.

Genetic diagnosis of developmental disorders in the DDD study: a scalable analysis of genome-wide research data.

PubMed

Wright, Caroline F; Fitzgerald, Tomas W; Jones, Wendy D; Clayton, Stephen; McRae, Jeremy F; van Kogelenberg, Margriet; King, Daniel A; Ambridge, Kirsty; Barrett, Daniel M; Bayzetinova, Tanya; Bevan, A Paul; Bragin, Eugene; Chatzimichali, Eleni A; Gribble, Susan; Jones, Philip; Krishnappa, Netravathi; Mason, Laura E; Miller, Ray; Morley, Katherine I; Parthiban, Vijaya; Prigmore, Elena; Rajan, Diana; Sifrim, Alejandro; Swaminathan, G Jawahar; Tivey, Adrian R; Middleton, Anna; Parker, Michael; Carter, Nigel P; Barrett, Jeffrey C; Hurles, Matthew E; FitzPatrick, David R; Firth, Helen V

2015-04-04

Human genome sequencing has transformed our understanding of genomic variation and its relevance to health and disease, and is now starting to enter clinical practice for the diagnosis of rare diseases. The question of whether and how some categories of genomic findings should be shared with individual research participants is currently a topic of international debate, and development of robust analytical workflows to identify and communicate clinically relevant variants is paramount. The Deciphering Developmental Disorders (DDD) study has developed a UK-wide patient recruitment network involving over 180 clinicians across all 24 regional genetics services, and has performed genome-wide microarray and whole exome sequencing on children with undiagnosed developmental disorders and their parents. After data analysis, pertinent genomic variants were returned to individual research participants via their local clinical genetics team. Around 80,000 genomic variants were identified from exome sequencing and microarray analysis in each individual, of which on average 400 were rare and predicted to be protein altering. By focusing only on de novo and segregating variants in known developmental disorder genes, we achieved a diagnostic yield of 27% among 1133 previously investigated yet undiagnosed children with developmental disorders, whilst minimising incidental findings. In families with developmentally normal parents, whole exome sequencing of the child and both parents resulted in a 10-fold reduction in the number of potential causal variants that needed clinical evaluation compared to sequencing only the child. Most diagnostic variants identified in known genes were novel and not present in current databases of known disease variation. Implementation of a robust translational genomics workflow is achievable within a large-scale rare disease research study to allow feedback of potentially diagnostic findings to clinicians and research participants. Systematic recording of relevant clinical data, curation of a gene-phenotype knowledge base, and development of clinical decision support software are needed in addition to automated exclusion of almost all variants, which is crucial for scalable prioritisation and review of possible diagnostic variants. However, the resource requirements of development and maintenance of a clinical reporting system within a research setting are substantial. Health Innovation Challenge Fund, a parallel funding partnership between the Wellcome Trust and the UK Department of Health. Copyright © 2015 Wright et al. Open Access article distributed under the terms of CC BY. Published by Elsevier Ltd. All rights reserved.

Genetic diagnosis of developmental disorders in the DDD study: a scalable analysis of genome-wide research data

PubMed Central

Wright, Caroline F; Fitzgerald, Tomas W; Jones, Wendy D; Clayton, Stephen; McRae, Jeremy F; van Kogelenberg, Margriet; King, Daniel A; Ambridge, Kirsty; Barrett, Daniel M; Bayzetinova, Tanya; Bevan, A Paul; Bragin, Eugene; Chatzimichali, Eleni A; Gribble, Susan; Jones, Philip; Krishnappa, Netravathi; Mason, Laura E; Miller, Ray; Morley, Katherine I; Parthiban, Vijaya; Prigmore, Elena; Rajan, Diana; Sifrim, Alejandro; Swaminathan, G Jawahar; Tivey, Adrian R; Middleton, Anna; Parker, Michael; Carter, Nigel P; Barrett, Jeffrey C; Hurles, Matthew E; FitzPatrick, David R; Firth, Helen V

2015-01-01

Summary Background Human genome sequencing has transformed our understanding of genomic variation and its relevance to health and disease, and is now starting to enter clinical practice for the diagnosis of rare diseases. The question of whether and how some categories of genomic findings should be shared with individual research participants is currently a topic of international debate, and development of robust analytical workflows to identify and communicate clinically relevant variants is paramount. Methods The Deciphering Developmental Disorders (DDD) study has developed a UK-wide patient recruitment network involving over 180 clinicians across all 24 regional genetics services, and has performed genome-wide microarray and whole exome sequencing on children with undiagnosed developmental disorders and their parents. After data analysis, pertinent genomic variants were returned to individual research participants via their local clinical genetics team. Findings Around 80 000 genomic variants were identified from exome sequencing and microarray analysis in each individual, of which on average 400 were rare and predicted to be protein altering. By focusing only on de novo and segregating variants in known developmental disorder genes, we achieved a diagnostic yield of 27% among 1133 previously investigated yet undiagnosed children with developmental disorders, whilst minimising incidental findings. In families with developmentally normal parents, whole exome sequencing of the child and both parents resulted in a 10-fold reduction in the number of potential causal variants that needed clinical evaluation compared to sequencing only the child. Most diagnostic variants identified in known genes were novel and not present in current databases of known disease variation. Interpretation Implementation of a robust translational genomics workflow is achievable within a large-scale rare disease research study to allow feedback of potentially diagnostic findings to clinicians and research participants. Systematic recording of relevant clinical data, curation of a gene–phenotype knowledge base, and development of clinical decision support software are needed in addition to automated exclusion of almost all variants, which is crucial for scalable prioritisation and review of possible diagnostic variants. However, the resource requirements of development and maintenance of a clinical reporting system within a research setting are substantial. Funding Health Innovation Challenge Fund, a parallel funding partnership between the Wellcome Trust and the UK Department of Health. PMID:25529582

NCBI GEO: archive for functional genomics data sets--10 years on.

PubMed

Barrett, Tanya; Troup, Dennis B; Wilhite, Stephen E; Ledoux, Pierre; Evangelista, Carlos; Kim, Irene F; Tomashevsky, Maxim; Marshall, Kimberly A; Phillippy, Katherine H; Sherman, Patti M; Muertter, Rolf N; Holko, Michelle; Ayanbule, Oluwabukunmi; Yefanov, Andrey; Soboleva, Alexandra

2011-01-01

A decade ago, the Gene Expression Omnibus (GEO) database was established at the National Center for Biotechnology Information (NCBI). The original objective of GEO was to serve as a public repository for high-throughput gene expression data generated mostly by microarray technology. However, the research community quickly applied microarrays to non-gene-expression studies, including examination of genome copy number variation and genome-wide profiling of DNA-binding proteins. Because the GEO database was designed with a flexible structure, it was possible to quickly adapt the repository to store these data types. More recently, as the microarray community switches to next-generation sequencing technologies, GEO has again adapted to host these data sets. Today, GEO stores over 20,000 microarray- and sequence-based functional genomics studies, and continues to handle the majority of direct high-throughput data submissions from the research community. Multiple mechanisms are provided to help users effectively search, browse, download and visualize the data at the level of individual genes or entire studies. This paper describes recent database enhancements, including new search and data representation tools, as well as a brief review of how the community uses GEO data. GEO is freely accessible at http://www.ncbi.nlm.nih.gov/geo/.

Genome-wide survey of human alternative pre-mRNA splicing with exon junction microarrays.

PubMed

Johnson, Jason M; Castle, John; Garrett-Engele, Philip; Kan, Zhengyan; Loerch, Patrick M; Armour, Christopher D; Santos, Ralph; Schadt, Eric E; Stoughton, Roland; Shoemaker, Daniel D

2003-12-19

Alternative pre-messenger RNA (pre-mRNA) splicing plays important roles in development, physiology, and disease, and more than half of human genes are alternatively spliced. To understand the biological roles and regulation of alternative splicing across different tissues and stages of development, systematic methods are needed. Here, we demonstrate the use of microarrays to monitor splicing at every exon-exon junction in more than 10,000 multi-exon human genes in 52 tissues and cell lines. These genome-wide data provide experimental evidence and tissue distributions for thousands of known and novel alternative splicing events. Adding to previous studies, the results indicate that at least 74% of human multi-exon genes are alternatively spliced.

Genome-wide identification, characterization, and expression profile of aquaporin gene family in flax (Linum usitatissimum)

PubMed Central

Shivaraj, S. M.; Deshmukh, Rupesh K.; Rai, Rhitu; Bélanger, Richard; Agrawal, Pawan K.; Dash, Prasanta K.

2017-01-01

Membrane intrinsic proteins (MIPs) form transmembrane channels and facilitate transport of myriad substrates across the cell membrane in many organisms. Majority of plant MIPs have water transporting ability and are commonly referred as aquaporins (AQPs). In the present study, we identified aquaporin coding genes in flax by genome-wide analysis, their structure, function and expression pattern by pan-genome exploration. Cross-genera phylogenetic analysis with known aquaporins from rice, arabidopsis, and poplar showed five subgroups of flax aquaporins representing 16 plasma membrane intrinsic proteins (PIPs), 17 tonoplast intrinsic proteins (TIPs), 13 NOD26-like intrinsic proteins (NIPs), 2 small basic intrinsic proteins (SIPs), and 3 uncharacterized intrinsic proteins (XIPs). Amongst aquaporins, PIPs contained hydrophilic aromatic arginine (ar/R) selective filter but TIP, NIP, SIP and XIP subfamilies mostly contained hydrophobic ar/R selective filter. Analysis of RNA-seq and microarray data revealed high expression of PIPs in multiple tissues, low expression of NIPs, and seed specific expression of TIP3 in flax. Exploration of aquaporin homologs in three closely related Linum species bienne, grandiflorum and leonii revealed presence of 49, 39 and 19 AQPs, respectively. The genome-wide identification of aquaporins, first in flax, provides insight to elucidate their physiological and developmental roles in flax. PMID:28447607

Genome-wide identification, characterization, and expression profile of aquaporin gene family in flax (Linum usitatissimum).

PubMed

Shivaraj, S M; Deshmukh, Rupesh K; Rai, Rhitu; Bélanger, Richard; Agrawal, Pawan K; Dash, Prasanta K

2017-04-27

Membrane intrinsic proteins (MIPs) form transmembrane channels and facilitate transport of myriad substrates across the cell membrane in many organisms. Majority of plant MIPs have water transporting ability and are commonly referred as aquaporins (AQPs). In the present study, we identified aquaporin coding genes in flax by genome-wide analysis, their structure, function and expression pattern by pan-genome exploration. Cross-genera phylogenetic analysis with known aquaporins from rice, arabidopsis, and poplar showed five subgroups of flax aquaporins representing 16 plasma membrane intrinsic proteins (PIPs), 17 tonoplast intrinsic proteins (TIPs), 13 NOD26-like intrinsic proteins (NIPs), 2 small basic intrinsic proteins (SIPs), and 3 uncharacterized intrinsic proteins (XIPs). Amongst aquaporins, PIPs contained hydrophilic aromatic arginine (ar/R) selective filter but TIP, NIP, SIP and XIP subfamilies mostly contained hydrophobic ar/R selective filter. Analysis of RNA-seq and microarray data revealed high expression of PIPs in multiple tissues, low expression of NIPs, and seed specific expression of TIP3 in flax. Exploration of aquaporin homologs in three closely related Linum species bienne, grandiflorum and leonii revealed presence of 49, 39 and 19 AQPs, respectively. The genome-wide identification of aquaporins, first in flax, provides insight to elucidate their physiological and developmental roles in flax.

Network Biomarkers of Bladder Cancer Based on a Genome-Wide Genetic and Epigenetic Network Derived from Next-Generation Sequencing Data.

PubMed

Li, Cheng-Wei; Chen, Bor-Sen

2016-01-01

Epigenetic and microRNA (miRNA) regulation are associated with carcinogenesis and the development of cancer. By using the available omics data, including those from next-generation sequencing (NGS), genome-wide methylation profiling, candidate integrated genetic and epigenetic network (IGEN) analysis, and drug response genome-wide microarray analysis, we constructed an IGEN system based on three coupling regression models that characterize protein-protein interaction networks (PPINs), gene regulatory networks (GRNs), miRNA regulatory networks (MRNs), and epigenetic regulatory networks (ERNs). By applying system identification method and principal genome-wide network projection (PGNP) to IGEN analysis, we identified the core network biomarkers to investigate bladder carcinogenic mechanisms and design multiple drug combinations for treating bladder cancer with minimal side-effects. The progression of DNA repair and cell proliferation in stage 1 bladder cancer ultimately results not only in the derepression of miR-200a and miR-200b but also in the regulation of the TNF pathway to metastasis-related genes or proteins, cell proliferation, and DNA repair in stage 4 bladder cancer. We designed a multiple drug combination comprising gefitinib, estradiol, yohimbine, and fulvestrant for treating stage 1 bladder cancer with minimal side-effects, and another multiple drug combination comprising gefitinib, estradiol, chlorpromazine, and LY294002 for treating stage 4 bladder cancer with minimal side-effects.

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

PubMed

Yamamoto, F; Yamamoto, M

2004-07-01

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

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

EPA Science Inventory

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

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

PubMed Central

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

2008-01-01

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

Genome-wide profiling of gene expression in the epididymis of alpha-chlorohydrin-induced infertile rats using an oligonucleotide microarray

PubMed Central

2010-01-01

Background As one of the chlorinated antifertility compounds, alpha-chlorohydrin (ACH) can inhibit glyceraldehyde-3-phosphate dehydrogenase (G3PDH) activity in epididymal sperm and affect sperm energy metabolism, maturation and fertilization, eventually leading to male infertility. Further studies demonstrated that the inhibitory effect of ACH on G3PDH is not only confined to epididymal sperm but also to the epididymis. Moreover, little investigation on gene expression changes in the epididymis after ACH treatment has been conducted. Therefore, gene expression studies may indicate new epididymal targets related to sperm maturation and fertility through the analysis of ACH-treated infertile animals. Methods Rats were treated with ACH for ten consecutive days, and then each male rat copulated with two female rats in proestrus. Then sperm maturation and other fertility parameters were analyzed. Furthermore, we identified epididymal-specific genes that are associated with fertility between control and ACH groups using an Affymetrix Rat 230 2.0 oligo-microarray. Finally, we performed RT-PCR analysis for several differentially expressed genes to validate the alteration in gene expression observed by oligonucleotide microarray. Results Among all the differentially expressed genes, we analyzed and screened the down-regulated genes associated with metabolism processes, which are considered the major targets of ACH action. Simultaneously, the genes that were up-regulated by chlorohydrin were detected. The genes that negatively regulate sperm maturation and fertility include apoptosis and immune-related genes and have not been reported previously. The overall results of PCR analysis for selected genes were consistent with the array data. Conclusions In this study, we have described the genome-wide profiles of gene expression in the epididymides of infertile rats induced by ACH, which could become potential epididymal specific targets for male contraception and infertility treatment. PMID:20409345

Genome-wide profiling of gene expression in the epididymis of alpha-chlorohydrin-induced infertile rats using an oligonucleotide microarray.

PubMed

Xie, Shuwu; Zhu, Yan; Ma, Li; Lu, Yingying; Zhou, Jieyun; Gui, Youlun; Cao, Lin

2010-04-22

As one of the chlorinated antifertility compounds, alpha-chlorohydrin (ACH) can inhibit glyceraldehyde-3-phosphate dehydrogenase (G3PDH) activity in epididymal sperm and affect sperm energy metabolism, maturation and fertilization, eventually leading to male infertility. Further studies demonstrated that the inhibitory effect of ACH on G3PDH is not only confined to epididymal sperm but also to the epididymis. Moreover, little investigation on gene expression changes in the epididymis after ACH treatment has been conducted. Therefore, gene expression studies may indicate new epididymal targets related to sperm maturation and fertility through the analysis of ACH-treated infertile animals. Rats were treated with ACH for ten consecutive days, and then each male rat copulated with two female rats in proestrus. Then sperm maturation and other fertility parameters were analyzed. Furthermore, we identified epididymal-specific genes that are associated with fertility between control and ACH groups using an Affymetrix Rat 230 2.0 oligo-microarray. Finally, we performed RT-PCR analysis for several differentially expressed genes to validate the alteration in gene expression observed by oligonucleotide microarray. Among all the differentially expressed genes, we analyzed and screened the down-regulated genes associated with metabolism processes, which are considered the major targets of ACH action. Simultaneously, the genes that were up-regulated by chlorohydrin were detected. The genes that negatively regulate sperm maturation and fertility include apoptosis and immune-related genes and have not been reported previously. The overall results of PCR analysis for selected genes were consistent with the array data. In this study, we have described the genome-wide profiles of gene expression in the epididymides of infertile rats induced by ACH, which could become potential epididymal specific targets for male contraception and infertility treatment.

arrayCGHbase: an analysis platform for comparative genomic hybridization microarrays

PubMed Central

Menten, Björn; Pattyn, Filip; De Preter, Katleen; Robbrecht, Piet; Michels, Evi; Buysse, Karen; Mortier, Geert; De Paepe, Anne; van Vooren, Steven; Vermeesch, Joris; Moreau, Yves; De Moor, Bart; Vermeulen, Stefan; Speleman, Frank; Vandesompele, Jo

2005-01-01

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 . PMID:15910681

The Diagnostic Yield of Array Comparative Genomic Hybridization Is High Regardless of Severity of Intellectual Disability/Developmental Delay in Children.

PubMed

D'Arrigo, Stefano; Gavazzi, Francesco; Alfei, Enrico; Zuffardi, Orsetta; Montomoli, Cristina; Corso, Barbara; Buzzi, Erika; Sciacca, Francesca L; Bulgheroni, Sara; Riva, Daria; Pantaleoni, Chiara

2016-05-01

Microarray-based comparative genomic hybridization is a method of molecular analysis that identifies chromosomal anomalies (or copy number variants) that correlate with clinical phenotypes. The aim of the present study was to apply a clinical score previously designated by de Vries to 329 patients with intellectual disability/developmental disorder (intellectual disability/developmental delay) referred to our tertiary center and to see whether the clinical factors are associated with a positive outcome of aCGH analyses. Another goal was to test the association between a positive microarray-based comparative genomic hybridization result and the severity of intellectual disability/developmental delay. Microarray-based comparative genomic hybridization identified structural chromosomal alterations responsible for the intellectual disability/developmental delay phenotype in 16% of our sample. Our study showed that causative copy number variants are frequently found even in cases of mild intellectual disability (30.77%). We want to emphasize the need to conduct microarray-based comparative genomic hybridization on all individuals with intellectual disability/developmental delay, regardless of the severity, because the degree of intellectual disability/developmental delay does not predict the diagnostic yield of microarray-based comparative genomic hybridization. © The Author(s) 2015.

Genome Consortium for Active Teaching: Meeting the Goals of BIO2010

PubMed Central

Ledbetter, Mary Lee S.; Hoopes, Laura L.M.; Eckdahl, Todd T.; Heyer, Laurie J.; Rosenwald, Anne; Fowlks, Edison; Tonidandel, Scott; Bucholtz, Brooke; Gottfried, Gail

2007-01-01

The Genome Consortium for Active Teaching (GCAT) facilitates the use of modern genomics methods in undergraduate education. Initially focused on microarray technology, but with an eye toward diversification, GCAT is a community working to improve the education of tomorrow's life science professionals. GCAT participants have access to affordable microarrays, microarray scanners, free software for data analysis, and faculty workshops. Microarrays provided by GCAT have been used by 141 faculty on 134 campuses, including 21 faculty that serve large numbers of underrepresented minority students. An estimated 9480 undergraduates a year will have access to microarrays by 2009 as a direct result of GCAT faculty workshops. Gains for students include significantly improved comprehension of topics in functional genomics and increased interest in research. Faculty reported improved access to new technology and gains in understanding thanks to their involvement with GCAT. GCAT's network of supportive colleagues encourages faculty to explore genomics through student research and to learn a new and complex method with their undergraduates. GCAT is meeting important goals of BIO2010 by making research methods accessible to undergraduates, training faculty in genomics and bioinformatics, integrating mathematics into the biology curriculum, and increasing participation by underrepresented minority students. PMID:17548873

Genome Consortium for Active Teaching: meeting the goals of BIO2010.

PubMed

Campbell, A Malcolm; Ledbetter, Mary Lee S; Hoopes, Laura L M; Eckdahl, Todd T; Heyer, Laurie J; Rosenwald, Anne; Fowlks, Edison; Tonidandel, Scott; Bucholtz, Brooke; Gottfried, Gail

2007-01-01

The Genome Consortium for Active Teaching (GCAT) facilitates the use of modern genomics methods in undergraduate education. Initially focused on microarray technology, but with an eye toward diversification, GCAT is a community working to improve the education of tomorrow's life science professionals. GCAT participants have access to affordable microarrays, microarray scanners, free software for data analysis, and faculty workshops. Microarrays provided by GCAT have been used by 141 faculty on 134 campuses, including 21 faculty that serve large numbers of underrepresented minority students. An estimated 9480 undergraduates a year will have access to microarrays by 2009 as a direct result of GCAT faculty workshops. Gains for students include significantly improved comprehension of topics in functional genomics and increased interest in research. Faculty reported improved access to new technology and gains in understanding thanks to their involvement with GCAT. GCAT's network of supportive colleagues encourages faculty to explore genomics through student research and to learn a new and complex method with their undergraduates. GCAT is meeting important goals of BIO2010 by making research methods accessible to undergraduates, training faculty in genomics and bioinformatics, integrating mathematics into the biology curriculum, and increasing participation by underrepresented minority students.

Genome-wide transcription analysis of histidine-related cataract in Atlantic salmon (Salmo salar L)

PubMed Central

Waagbø, Rune; Breck, Olav; Stavrum, Anne-Kristin; Petersen, Kjell; Olsvik, Pål A.

2009-01-01

Purpose Elevated levels of dietary histidine have previously been shown to prevent or mitigate cataract formation in farmed Atlantic salmon (Salmo salar L). The aim of this study was to shed light on the mechanisms by which histidine acts. Applying microarray analysis to the lens transcriptome, we screened for differentially expressed genes in search for a model explaining cataract development in Atlantic salmon and possible markers for early cataract diagnosis. Methods Adult Atlantic salmon (1.7 kg) were fed three standard commercial salmon diets only differing in the histidine content (9, 13, and 17 g histidine/kg diet) for four months. Individual cataract scores for both eyes were assessed by slit-lamp biomicroscopy. Lens N-acetyl histidine contents were measured by high performance liquid chromatography (HPLC). Total RNA extracted from whole lenses was analyzed using the GRASP 16K salmonid microarray. The microarray data were analyzed using J-Express Pro 2.7 and validated by quantitative real-time polymerase chain reaction (qRT–PCR). Results Fish developed cataracts with different severity in response to dietary histidine levels. Lens N-acetyl histidine contents reflected the dietary histidine levels and were negatively correlated to cataract scores. Significance analysis of microarrays (SAM) revealed 248 significantly up-regulated transcripts and 266 significantly down-regulated transcripts in fish that were fed a low level of histidine compared to fish fed a higher histidine level. Among the differentially expressed transcripts were metallothionein A and B as well as transcripts involved in lipid metabolism, carbohydrate metabolism, regulation of ion homeostasis, and protein degradation. Hierarchical clustering and correspondence analysis plot confirmed differences in gene expression between the feeding groups. The differentially expressed genes could be categorized as “early” and “late” responsive according to their expression pattern relative to progression in cataract formation. Conclusions Dietary histidine regimes affected cataract formation and lens gene expression in adult Atlantic salmon. Regulated transcripts selected from the results of this genome-wide transcription analysis might be used as possible biological markers for cataract development in Atlantic salmon. PMID:19597568

Microarray Analysis of LTR Retrotransposon Silencing Identifies Hdac1 as a Regulator of Retrotransposon Expression in Mouse Embryonic Stem Cells

PubMed Central

Madej, Monika J.; Taggart, Mary; Gautier, Philippe; Garcia-Perez, Jose Luis; Meehan, Richard R.; Adams, Ian R.

2012-01-01

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. PMID:22570599

Development of Transcriptomics-based Biomarkers for Selected Endocrine Disrupting Chemicals in Zebrafish (Danio rerio)

EPA Science Inventory

Genome-wide transcriptional profiling by microarrays provides a powerful platform for gene expression-based biomarker discovery. After their wide acceptance in human disease diagnosis, prognosis, and drug discovery, these gene signatures are increasingly being adopted for environ...

Development of transcriptomics-based biomarkers for selected endocrine disrupting chemicals in zebrafish (Danio rerio)

EPA Science Inventory

Genome-wide transcriptional profiling by microarrays provides a powerful platform for gene expression-based biomarker discovery. After their wide acceptance in human disease diagnosis, prognosis, and drug discovery, these gene signatures are increasingly being adopted for environ...

ChIP-chip.

PubMed

Kim, Tae Hoon; Dekker, Job

2018-05-01

ChIP-chip can be used to analyze protein-DNA interactions in a region-wide and genome-wide manner. DNA microarrays contain PCR products or oligonucleotide probes that are designed to represent genomic sequences. Identification of genomic sites that interact with a specific protein is based on competitive hybridization of the ChIP-enriched DNA and the input DNA to DNA microarrays. The ChIP-chip protocol can be divided into two main sections: Amplification of ChIP DNA and hybridization of ChIP DNA to arrays. A large amount of DNA is required to hybridize to DNA arrays, and hybridization to a set of multiple commercial arrays that represent the entire human genome requires two rounds of PCR amplifications. The relative hybridization intensity of ChIP DNA and that of the input DNA is used to determine whether the probe sequence is a potential site of protein-DNA interaction. Resolution of actual genomic sites bound by the protein is dependent on the size of the chromatin and on the genomic distance between the probes on the array. As with expression profiling using gene chips, ChIP-chip experiments require multiple replicates for reliable statistical measure of protein-DNA interactions. © 2018 Cold Spring Harbor Laboratory Press.

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

PubMed

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-bomb radiation may affect the increased amount of CNA as a hallmark of GIN and, subsequently, be associated with a higher histologic grade in breast cancer found in A-bomb survivors.

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

PubMed Central

2011-01-01

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 genome-wide aCGH analysis. Our results suggested that A-bomb radiation may affect the increased amount of CNA as a hallmark of GIN and, subsequently, be associated with a higher histologic grade in breast cancer found in A-bomb survivors. PMID:22152285

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

PubMed

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.

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

PubMed Central

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

Next-generation sequencing strategies enable routine detection of balanced chromosome rearrangements for clinical diagnostics and genetic research.

PubMed

Talkowski, Michael E; Ernst, Carl; Heilbut, Adrian; Chiang, Colby; Hanscom, Carrie; Lindgren, Amelia; Kirby, Andrew; Liu, Shangtao; Muddukrishna, Bhavana; Ohsumi, Toshiro K; Shen, Yiping; Borowsky, Mark; Daly, Mark J; Morton, Cynthia C; Gusella, James F

2011-04-08

The contribution of balanced chromosomal rearrangements to complex disorders remains unclear because they are not detected routinely by genome-wide microarrays and clinical localization is imprecise. Failure to consider these events bypasses a potentially powerful complement to single nucleotide polymorphism and copy-number association approaches to complex disorders, where much of the heritability remains unexplained. To capitalize on this genetic resource, we have applied optimized sequencing and analysis strategies to test whether these potentially high-impact variants can be mapped at reasonable cost and throughput. By using a whole-genome multiplexing strategy, rearrangement breakpoints could be delineated at a fraction of the cost of standard sequencing. For rearrangements already mapped regionally by karyotyping and fluorescence in situ hybridization, a targeted approach enabled capture and sequencing of multiple breakpoints simultaneously. Importantly, this strategy permitted capture and unique alignment of up to 97% of repeat-masked sequences in the targeted regions. Genome-wide analyses estimate that only 3.7% of bases should be routinely omitted from genomic DNA capture experiments. Illustrating the power of these approaches, the rearrangement breakpoints were rapidly defined to base pair resolution and revealed unexpected sequence complexity, such as co-occurrence of inversion and translocation as an underlying feature of karyotypically balanced alterations. These findings have implications ranging from genome annotation to de novo assemblies and could enable sequencing screens for structural variations at a cost comparable to that of microarrays in standard clinical practice. Copyright © 2011 The American Society of Human Genetics. Published by Elsevier Inc. All rights reserved.

Genome-wide identification, classification, and expression analysis of the arabinogalactan protein gene family in rice (Oryza sativa L.)

PubMed Central

Zhao, Jie

2010-01-01

Arabinogalactan proteins (AGPs) comprise a family of hydroxyproline-rich glycoproteins that are implicated in plant growth and development. In this study, 69 AGPs are identified from the rice genome, including 13 classical AGPs, 15 arabinogalactan (AG) peptides, three non-classical AGPs, three early nodulin-like AGPs (eNod-like AGPs), eight non-specific lipid transfer protein-like AGPs (nsLTP-like AGPs), and 27 fasciclin-like AGPs (FLAs). The results from expressed sequence tags, microarrays, and massively parallel signature sequencing tags are used to analyse the expression of AGP-encoding genes, which is confirmed by real-time PCR. The results reveal that several rice AGP-encoding genes are predominantly expressed in anthers and display differential expression patterns in response to abscisic acid, gibberellic acid, and abiotic stresses. Based on the results obtained from this analysis, an attempt has been made to link the protein structures and expression patterns of rice AGP-encoding genes to their functions. Taken together, the genome-wide identification and expression analysis of the rice AGP gene family might facilitate further functional studies of rice AGPs. PMID:20423940

Genome-wide analysis of murine renal distal convoluted tubular cells for the target genes of mineralocorticoid receptor

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

Ueda, Kohei; Fujiki, Katsunori; Shirahige, Katsuhiko

Highlights: • We define a target gene of MR as that with MR-binding to the adjacent region of DNA. • We use ChIP-seq analysis in combination with microarray. • We, for the first time, explore the genome-wide binding profile of MR. • We reveal 5 genes as the direct target genes of MR in the renal epithelial cell-line. - Abstract: Background and objective: Mineralocorticoid receptor (MR) is a member of nuclear receptor family proteins and contributes to fluid homeostasis in the kidney. Although aldosterone-MR pathway induces several gene expressions in the kidney, it is often unclear whether the gene expressionsmore » are accompanied by direct regulations of MR through its binding to the regulatory region of each gene. The purpose of this study is to identify the direct target genes of MR in a murine distal convoluted tubular epithelial cell-line (mDCT). Methods: We analyzed the DNA samples of mDCT cells overexpressing 3xFLAG-hMR after treatment with 10{sup −7} M aldosterone for 1 h by chromatin immunoprecipitation with deep-sequence (ChIP-seq) and mRNA of the cell-line with treatment of 10{sup −7} M aldosterone for 3 h by microarray. Results: 3xFLAG-hMR overexpressed in mDCT cells accumulated in the nucleus in response to 10{sup −9} M aldosterone. Twenty-five genes were indicated as the candidate target genes of MR by ChIP-seq and microarray analyses. Five genes, Sgk1, Fkbp5, Rasl12, Tns1 and Tsc22d3 (Gilz), were validated as the direct target genes of MR by quantitative RT-qPCR and ChIP-qPCR. MR binding regions adjacent to Ctgf and Serpine1 were also validated. Conclusions: We, for the first time, captured the genome-wide distribution of MR in mDCT cells and, furthermore, identified five MR target genes in the cell-line. These results will contribute to further studies on the mechanisms of kidney diseases.« less

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

PubMed

Jain, K K

2001-02-01

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

Xylella fastidiosa gene expression analysis by DNA microarrays.

PubMed

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

2009-04-01

Xylella fastidiosa genome sequencing has generated valuable data by identifying genes acting either on metabolic pathways or in associated pathogenicity and virulence. Based on available information on these genes, new strategies for studying their expression patterns, such as microarray technology, were employed. A total of 2,600 primer pairs were synthesized and then used to generate fragments using the PCR technique. The arrays were hybridized against cDNAs labeled during reverse transcription reactions and which were obtained from bacteria grown under two different conditions (liquid XDM(2) and liquid BCYE). All data were statistically analyzed to verify which genes were differentially expressed. In addition to exploring conditions for X. fastidiosa genome-wide transcriptome analysis, the present work observed the differential expression of several classes of genes (energy, protein, amino acid and nucleotide metabolism, transport, degradation of substances, toxins and hypothetical proteins, among others). The understanding of expressed genes in these two different media will be useful in comprehending the metabolic characteristics of X. fastidiosa, and in evaluating how important certain genes are for the functioning and survival of these bacteria in plants.

Methods for Genome-Wide Analysis of Gene Expression Changes in Polyploids

PubMed Central

Wang, Jianlin; Lee, Jinsuk J.; Tian, Lu; Lee, Hyeon-Se; Chen, Meng; Rao, Sheetal; Wei, Edward N.; Doerge, R. W.; Comai, Luca; Jeffrey Chen, Z.

2007-01-01

Polyploidy is an evolutionary innovation, providing extra sets of genetic material for phenotypic variation and adaptation. It is predicted that changes of gene expression by genetic and epigenetic mechanisms are responsible for novel variation in nascent and established polyploids (Liu and Wendel, 2002; Osborn et al., 2003; Pikaard, 2001). Studying gene expression changes in allopolyploids is more complicated than in autopolyploids, because allopolyploids contain more than two sets of genomes originating from divergent, but related, species. Here we describe two methods that are applicable to the genome-wide analysis of gene expression differences resulting from genome duplication in autopolyploids or interactions between homoeologous genomes in allopolyploids. First, we describe an amplified fragment length polymorphism (AFLP)–complementary DNA (cDNA) display method that allows the discrimination of homoeologous loci based on restriction polymorphisms between the progenitors. Second, we describe microarray analyses that can be used to compare gene expression differences between the allopolyploids and respective progenitors using appropriate experimental design and statistical analysis. We demonstrate the utility of these two complementary methods and discuss the pros and cons of using the methods to analyze gene expression changes in autopolyploids and allopolyploids. Furthermore, we describe these methods in general terms to be of wider applicability for comparative gene expression in a variety of evolutionary, genetic, biological, and physiological contexts. PMID:15865985

Bombyx mori Transcription Factors: Genome-Wide Identification, Expression Profiles and Response to Pathogens by Microarray Analysis

PubMed Central

Huang, Lulin; Cheng, Tingcai; Xu, Pingzhen; Fang, Ting; Xia, Qingyou

2012-01-01

Transcription factors are present in all living organisms, and play vital roles in a wide range of biological processes. Studies of transcription factors will help reveal the complex regulation mechanism of organisms. So far, hundreds of domains have been identified that show transcription factor activity. Here, 281 reported transcription factor domains were used as seeds to search the transcription factors in genomes of Bombyx mori L. (Lepidoptera: Bombycidae) and four other model insects. Overall, 666 transcription factors including 36 basal factors and 630 other factors were identified in B. mori genome, which accounted for 4.56% of its genome. The silkworm transcription factors' expression profiles were investigated in relation to multiple tissues, developmental stages, sexual dimorphism, and responses to oral infection by pathogens and direct bacterial injection. These all provided rich clues for revealing the transcriptional regulation mechanism of silkworm organ differentiation, growth and development, sexual dimorphism, and response to pathogen infection. PMID:22943524

Large-scale chromatin immunoprecipitation with promoter sequence microarray analysis of the interaction of the NSs protein of Rift Valley fever virus with regulatory DNA regions of the host genome.

PubMed

Benferhat, Rima; Josse, Thibaut; Albaud, Benoit; Gentien, David; Mansuroglu, Zeyni; Marcato, Vasco; Souès, Sylvie; Le Bonniec, Bernard; Bouloy, Michèle; Bonnefoy, Eliette

2012-10-01

Rift Valley fever virus (RVFV) is a highly pathogenic Phlebovirus that infects humans and ruminants. Initially confined to Africa, RVFV has spread outside Africa and presently represents a high risk to other geographic regions. It is responsible for high fatality rates in sheep and cattle. In humans, RVFV can induce hepatitis, encephalitis, retinitis, or fatal hemorrhagic fever. The nonstructural NSs protein that is the major virulence factor is found in the nuclei of infected cells where it associates with cellular transcription factors and cofactors. In previous work, we have shown that NSs interacts with the promoter region of the beta interferon gene abnormally maintaining the promoter in a repressed state. In this work, we performed a genome-wide analysis of the interactions between NSs and the host genome using a genome-wide chromatin immunoprecipitation combined with promoter sequence microarray, the ChIP-on-chip technique. Several cellular promoter regions were identified as significantly interacting with NSs, and the establishment of NSs interactions with these regions was often found linked to deregulation of expression of the corresponding genes. Among annotated NSs-interacting genes were present not only genes regulating innate immunity and inflammation but also genes regulating cellular pathways that have not yet been identified as targeted by RVFV. Several of these pathways, such as cell adhesion, axonal guidance, development, and coagulation were closely related to RVFV-induced disorders. In particular, we show in this work that NSs targeted and modified the expression of genes coding for coagulation factors, demonstrating for the first time that this hemorrhagic virus impairs the host coagulation cascade at the transcriptional level.

Large-Scale Chromatin Immunoprecipitation with Promoter Sequence Microarray Analysis of the Interaction of the NSs Protein of Rift Valley Fever Virus with Regulatory DNA Regions of the Host Genome

PubMed Central

Benferhat, Rima; Josse, Thibaut; Albaud, Benoit; Gentien, David; Mansuroglu, Zeyni; Marcato, Vasco; Souès, Sylvie; Le Bonniec, Bernard

2012-01-01

Rift Valley fever virus (RVFV) is a highly pathogenic Phlebovirus that infects humans and ruminants. Initially confined to Africa, RVFV has spread outside Africa and presently represents a high risk to other geographic regions. It is responsible for high fatality rates in sheep and cattle. In humans, RVFV can induce hepatitis, encephalitis, retinitis, or fatal hemorrhagic fever. The nonstructural NSs protein that is the major virulence factor is found in the nuclei of infected cells where it associates with cellular transcription factors and cofactors. In previous work, we have shown that NSs interacts with the promoter region of the beta interferon gene abnormally maintaining the promoter in a repressed state. In this work, we performed a genome-wide analysis of the interactions between NSs and the host genome using a genome-wide chromatin immunoprecipitation combined with promoter sequence microarray, the ChIP-on-chip technique. Several cellular promoter regions were identified as significantly interacting with NSs, and the establishment of NSs interactions with these regions was often found linked to deregulation of expression of the corresponding genes. Among annotated NSs-interacting genes were present not only genes regulating innate immunity and inflammation but also genes regulating cellular pathways that have not yet been identified as targeted by RVFV. Several of these pathways, such as cell adhesion, axonal guidance, development, and coagulation were closely related to RVFV-induced disorders. In particular, we show in this work that NSs targeted and modified the expression of genes coding for coagulation factors, demonstrating for the first time that this hemorrhagic virus impairs the host coagulation cascade at the transcriptional level. PMID:22896612

NCBI GEO: archive for functional genomics data sets—10 years on

PubMed Central

Barrett, Tanya; Troup, Dennis B.; Wilhite, Stephen E.; Ledoux, Pierre; Evangelista, Carlos; Kim, Irene F.; Tomashevsky, Maxim; Marshall, Kimberly A.; Phillippy, Katherine H.; Sherman, Patti M.; Muertter, Rolf N.; Holko, Michelle; Ayanbule, Oluwabukunmi; Yefanov, Andrey; Soboleva, Alexandra

2011-01-01

A decade ago, the Gene Expression Omnibus (GEO) database was established at the National Center for Biotechnology Information (NCBI). The original objective of GEO was to serve as a public repository for high-throughput gene expression data generated mostly by microarray technology. However, the research community quickly applied microarrays to non-gene-expression studies, including examination of genome copy number variation and genome-wide profiling of DNA-binding proteins. Because the GEO database was designed with a flexible structure, it was possible to quickly adapt the repository to store these data types. More recently, as the microarray community switches to next-generation sequencing technologies, GEO has again adapted to host these data sets. Today, GEO stores over 20 000 microarray- and sequence-based functional genomics studies, and continues to handle the majority of direct high-throughput data submissions from the research community. Multiple mechanisms are provided to help users effectively search, browse, download and visualize the data at the level of individual genes or entire studies. This paper describes recent database enhancements, including new search and data representation tools, as well as a brief review of how the community uses GEO data. GEO is freely accessible at http://www.ncbi.nlm.nih.gov/geo/. PMID:21097893

Current and Emerging Technologies for the Analysis of the Genome-Wide and Locus-Specific DNA Methylation Patterns.

PubMed

Tost, Jörg

2016-01-01

DNA methylation is the most studied epigenetic modification, and altered DNA methylation patterns have been identified in cancer and more recently also in many other complex diseases. Furthermore, DNA methylation is influenced by a variety of environmental factors, and the analysis of DNA methylation patterns might allow deciphering previous exposure. Although a large number of techniques to study DNA methylation either genome-wide or at specific loci have been devised, they all are based on a limited number of principles for differentiating the methylation state, viz., methylation-specific/methylation-dependent restriction enzymes, antibodies or methyl-binding proteins, chemical-based enrichment, or bisulfite conversion. Second-generation sequencing has largely replaced microarrays as readout platform and is also becoming more popular for locus-specific DNA methylation analysis. In this chapter, the currently used methods for both genome-wide and locus-specific analysis of 5-methylcytosine and as its oxidative derivatives, such as 5-hydroxymethylcytosine, are reviewed in detail, and the advantages and limitations of each approach are discussed. Furthermore, emerging technologies avoiding PCR amplification and allowing a direct readout of DNA methylation are summarized, together with novel applications, such as the detection of DNA methylation in single cells or in circulating cell-free DNA.

Principles of gene microarray data analysis.

PubMed

Mocellin, Simone; Rossi, Carlo Riccardo

2007-01-01

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

GermOnline 4.0 is a genomics gateway for germline development, meiosis and the mitotic cell cycle.

PubMed

Lardenois, Aurélie; Gattiker, Alexandre; Collin, Olivier; Chalmel, Frédéric; Primig, Michael

2010-01-01

GermOnline 4.0 is a cross-species database portal focusing on high-throughput expression data relevant for germline development, the meiotic cell cycle and mitosis in healthy versus malignant cells. It is thus a source of information for life scientists as well as clinicians who are interested in gene expression and regulatory networks. The GermOnline gateway provides unlimited access to information produced with high-density oligonucleotide microarrays (3'-UTR GeneChips), genome-wide protein-DNA binding assays and protein-protein interaction studies in the context of Ensembl genome annotation. Samples used to produce high-throughput expression data and to carry out genome-wide in vivo DNA binding assays are annotated via the MIAME-compliant Multiomics Information Management and Annotation System (MIMAS 3.0). Furthermore, the Saccharomyces Genomics Viewer (SGV) was developed and integrated into the gateway. SGV is a visualization tool that outputs genome annotation and DNA-strand specific expression data produced with high-density oligonucleotide tiling microarrays (Sc_tlg GeneChips) which cover the complete budding yeast genome on both DNA strands. It facilitates the interpretation of expression levels and transcript structures determined for various cell types cultured under different growth and differentiation conditions. Database URL: www.germonline.org/

GermOnline 4.0 is a genomics gateway for germline development, meiosis and the mitotic cell cycle

PubMed Central

Lardenois, Aurélie; Gattiker, Alexandre; Collin, Olivier; Chalmel, Frédéric; Primig, Michael

2010-01-01

GermOnline 4.0 is a cross-species database portal focusing on high-throughput expression data relevant for germline development, the meiotic cell cycle and mitosis in healthy versus malignant cells. It is thus a source of information for life scientists as well as clinicians who are interested in gene expression and regulatory networks. The GermOnline gateway provides unlimited access to information produced with high-density oligonucleotide microarrays (3′-UTR GeneChips), genome-wide protein–DNA binding assays and protein–protein interaction studies in the context of Ensembl genome annotation. Samples used to produce high-throughput expression data and to carry out genome-wide in vivo DNA binding assays are annotated via the MIAME-compliant Multiomics Information Management and Annotation System (MIMAS 3.0). Furthermore, the Saccharomyces Genomics Viewer (SGV) was developed and integrated into the gateway. SGV is a visualization tool that outputs genome annotation and DNA-strand specific expression data produced with high-density oligonucleotide tiling microarrays (Sc_tlg GeneChips) which cover the complete budding yeast genome on both DNA strands. It facilitates the interpretation of expression levels and transcript structures determined for various cell types cultured under different growth and differentiation conditions. Database URL: www.germonline.org/ PMID:21149299

Genome image programs: visualization and interpretation of Escherichia coli microarray experiments.

PubMed

Zimmer, Daniel P; Paliy, Oleg; Thomas, Brian; Gyaneshwar, Prasad; Kustu, Sydney

2004-08-01

We have developed programs to facilitate analysis of microarray data in Escherichia coli. They fall into two categories: manipulation of microarray images and identification of known biological relationships among lists of genes. A program in the first category arranges spots from glass-slide DNA microarrays according to their position in the E. coli genome and displays them compactly in genome order. The resulting genome image is presented in a web browser with an image map that allows the user to identify genes in the reordered image. Another program in the first category aligns genome images from two or more experiments. These images assist in visualizing regions of the genome with common transcriptional control. Such regions include multigene operons and clusters of operons, which are easily identified as strings of adjacent, similarly colored spots. The images are also useful for assessing the overall quality of experiments. The second category of programs includes a database and a number of tools for displaying biological information about many E. coli genes simultaneously rather than one gene at a time, which facilitates identifying relationships among them. These programs have accelerated and enhanced our interpretation of results from E. coli DNA microarray experiments. Examples are given. Copyright 2004 Genetics Society of America

Development of a fluorescence-activated cell sorting method coupled with whole genome amplification to analyze minority and trace Dehalococcoides genomes in microbial communities.

PubMed

Lee, Patrick K H; Men, Yujie; Wang, Shanquan; He, Jianzhong; Alvarez-Cohen, Lisa

2015-02-03

Dehalococcoides mccartyi are functionally important bacteria that catalyze the reductive dechlorination of chlorinated ethenes. However, these anaerobic bacteria are fastidious to isolate, making downstream genomic characterization challenging. In order to facilitate genomic analysis, a fluorescence-activated cell sorting (FACS) method was developed in this study to separate D. mccartyi cells from a microbial community, and the DNA of the isolated cells was processed by whole genome amplification (WGA) and hybridized onto a D. mccartyi microarray for comparative genomics against four sequenced strains. First, FACS was successfully applied to a D. mccartyi isolate as positive control, and then microarray results verified that WGA from 10(6) cells or ∼1 ng of genomic DNA yielded high-quality coverage detecting nearly all genes across the genome. As expected, some inter- and intrasample variability in WGA was observed, but these biases were minimized by performing multiple parallel amplifications. Subsequent application of the FACS and WGA protocols to two enrichment cultures containing ∼10% and ∼1% D. mccartyi cells successfully enabled genomic analysis. As proof of concept, this study demonstrates that coupling FACS with WGA and microarrays is a promising tool to expedite genomic characterization of target strains in environmental communities where the relative concentrations are low.

Technological advances and genomics in metazoan parasites.

PubMed

Knox, D P

2004-02-01

Molecular biology has provided the means to identify parasite proteins, to define their function, patterns of expression and the means to produce them in quantity for subsequent functional analyses. Whole genome and expressed sequence tag programmes, and the parallel development of powerful bioinformatics tools, allow the execution of genome-wide between stage or species comparisons and meaningful gene-expression profiling. The latter can be undertaken with several new technologies such as DNA microarray and serial analysis of gene expression. Proteome analysis has come to the fore in recent years providing a crucial link between the gene and its protein product. RNA interference and ballistic gene transfer are exciting developments which can provide the means to precisely define the function of individual genes and, of importance in devising novel parasite control strategies, the effect that gene knockdown will have on parasite survival.

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

PubMed

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

2008-09-16

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

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

PubMed

Grenville-Briggs, Laura J; Stansfield, Ian

2011-01-01

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

Genome-wide molecular dissection of serotype M3 group A Streptococcus strains causing two epidemics of invasive infections.

PubMed

Beres, Stephen B; Sylva, Gail L; Sturdevant, Daniel E; Granville, Chanel N; Liu, Mengyao; Ricklefs, Stacy M; Whitney, Adeline R; Parkins, Larye D; Hoe, Nancy P; Adams, Gerald J; Low, Donald E; DeLeo, Frank R; McGeer, Allison; Musser, James M

2004-08-10

Molecular factors that contribute to the emergence of new virulent bacterial subclones and epidemics are poorly understood. We hypothesized that analysis of a population-based strain sample of serotype M3 group A Streptococcus (GAS) recovered from patients with invasive infection by using genome-wide investigative methods would provide new insight into this fundamental infectious disease problem. Serotype M3 GAS strains (n = 255) cultured from patients in Ontario, Canada, over 11 years and representing two distinct infection peaks were studied. Genetic diversity was indexed by pulsed-field gel electrophoresis, DNA-DNA microarray, whole-genome PCR scanning, prophage genotyping, targeted gene sequencing, and single-nucleotide polymorphism genotyping. All variation in gene content was attributable to acquisition or loss of prophages, a molecular process that generated unique combinations of proven or putative virulence genes. Distinct serotype M3 genotypes experienced rapid population expansion and caused infections that differed significantly in character and severity. Molecular genetic analysis, combined with immunologic studies, implicated a 4-aa duplication in the extreme N terminus of M protein as a factor contributing to an epidemic wave of serotype M3 invasive infections. This finding has implications for GAS vaccine research. Genome-wide analysis of population-based strain samples cultured from clinically well defined patients is crucial for understanding the molecular events underlying bacterial epidemics.

High-Resolution Genome-Wide Analysis of Irradiated (UV and γ-Rays) Diploid Yeast Cells Reveals a High Frequency of Genomic Loss of Heterozygosity (LOH) Events

PubMed Central

St. Charles, Jordan; Hazkani-Covo, Einat; Yin, Yi; Andersen, Sabrina L.; Dietrich, Fred S.; Greenwell, Patricia W.; Malc, Ewa; Mieczkowski, Piotr; Petes, Thomas D.

2012-01-01

In diploid eukaryotes, repair of double-stranded DNA breaks by homologous recombination often leads to loss of heterozygosity (LOH). Most previous studies of mitotic recombination in Saccharomyces cerevisiae have focused on a single chromosome or a single region of one chromosome at which LOH events can be selected. In this study, we used two techniques (single-nucleotide polymorphism microarrays and high-throughput DNA sequencing) to examine genome-wide LOH in a diploid yeast strain at a resolution averaging 1 kb. We examined both selected LOH events on chromosome V and unselected events throughout the genome in untreated cells and in cells treated with either γ-radiation or ultraviolet (UV) radiation. Our analysis shows the following: (1) spontaneous and damage-induced mitotic gene conversion tracts are more than three times larger than meiotic conversion tracts, and conversion tracts associated with crossovers are usually longer and more complex than those unassociated with crossovers; (2) most of the crossovers and conversions reflect the repair of two sister chromatids broken at the same position; and (3) both UV and γ-radiation efficiently induce LOH at doses of radiation that cause no significant loss of viability. Using high-throughput DNA sequencing, we also detected new mutations induced by γ-rays and UV. To our knowledge, our study represents the first high-resolution genome-wide analysis of DNA damage-induced LOH events performed in any eukaryote. PMID:22267500

An object model and database for functional genomics.

PubMed

Jones, Andrew; Hunt, Ela; Wastling, Jonathan M; Pizarro, Angel; Stoeckert, Christian J

2004-07-10

Large-scale functional genomics analysis is now feasible and presents significant challenges in data analysis, storage and querying. Data standards are required to enable the development of public data repositories and to improve data sharing. There is an established data format for microarrays (microarray gene expression markup language, MAGE-ML) and a draft standard for proteomics (PEDRo). We believe that all types of functional genomics experiments should be annotated in a consistent manner, and we hope to open up new ways of comparing multiple datasets used in functional genomics. We have created a functional genomics experiment object model (FGE-OM), developed from the microarray model, MAGE-OM and two models for proteomics, PEDRo and our own model (Gla-PSI-Glasgow Proposal for the Proteomics Standards Initiative). FGE-OM comprises three namespaces representing (i) the parts of the model common to all functional genomics experiments; (ii) microarray-specific components; and (iii) proteomics-specific components. We believe that FGE-OM should initiate discussion about the contents and structure of the next version of MAGE and the future of proteomics standards. A prototype database called RNA And Protein Abundance Database (RAPAD), based on FGE-OM, has been implemented and populated with data from microbial pathogenesis. FGE-OM and the RAPAD schema are available from http://www.gusdb.org/fge.html, along with a set of more detailed diagrams. RAPAD can be accessed by registration at the site.

DNA microarray unravels rapid changes in transcriptome of MK-801 treated rat brain

PubMed Central

Kobayashi, Yuka; Kulikova, Sofya P; Shibato, Junko; Rakwal, Randeep; Satoh, Hiroyuki; Pinault, Didier; Masuo, Yoshinori

2015-01-01

AIM: To investigate the impact of MK-801 on gene expression patterns genome wide in rat brain regions. METHODS: Rats were treated with an intraperitoneal injection of MK-801 [0.08 (low-dose) and 0.16 (high-dose) mg/kg] or NaCl (vehicle control). In a first series of experiment, the frontoparietal electrocorticogram was recorded 15 min before and 60 min after injection. In a second series of experiments, the whole brain of each animal was rapidly removed at 40 min post-injection, and different regions were separated: amygdala, cerebral cortex, hippocampus, hypothalamus, midbrain and ventral striatum on ice followed by DNA microarray (4 × 44 K whole rat genome chip) analysis. RESULTS: Spectral analysis revealed that a single systemic injection of MK-801 significantly and selectively augmented the power of baseline gamma frequency (30-80 Hz) oscillations in the frontoparietal electroencephalogram. DNA microarray analysis showed the largest number (up- and down- regulations) of gene expressions in the cerebral cortex (378), midbrain (376), hippocampus (375), ventral striatum (353), amygdala (301), and hypothalamus (201) under low-dose (0.08 mg/kg) of MK-801. Under high-dose (0.16 mg/kg), ventral striatum (811) showed the largest number of gene expression changes. Gene expression changes were functionally categorized to reveal expression of genes and function varies with each brain region. CONCLUSION: Acute MK-801 treatment increases synchrony of baseline gamma oscillations, and causes very early changes in gene expressions in six individual rat brain regions, a first report. PMID:26629322

The Rice B-Box Zinc Finger Gene Family: Genomic Identification, Characterization, Expression Profiling and Diurnal Analysis

PubMed Central

Huang, Jianyan; Zhao, Xiaobo; Weng, Xiaoyu; Wang, Lei; Xie, Weibo

2012-01-01

Background The B-box (BBX) -containing proteins are a class of zinc finger proteins that contain one or two B-box domains and play important roles in plant growth and development. The Arabidopsis BBX gene family has recently been re-identified and renamed. However, there has not been a genome-wide survey of the rice BBX (OsBBX) gene family until now. Methodology/Principal Findings In this study, we identified 30 rice BBX genes through a comprehensive bioinformatics analysis. Each gene was assigned a uniform nomenclature. We described the chromosome localizations, gene structures, protein domains, phylogenetic relationship, whole life-cycle expression profile and diurnal expression patterns of the OsBBX family members. Based on the phylogeny and domain constitution, the OsBBX gene family was classified into five subfamilies. The gene duplication analysis revealed that only chromosomal segmental duplication contributed to the expansion of the OsBBX gene family. The expression profile of the OsBBX genes was analyzed by Affymetrix GeneChip microarrays throughout the entire life-cycle of rice cultivar Zhenshan 97 (ZS97). In addition, microarray analysis was performed to obtain the expression patterns of these genes under light/dark conditions and after three phytohormone treatments. This analysis revealed that the expression patterns of the OsBBX genes could be classified into eight groups. Eight genes were regulated under the light/dark treatments, and eleven genes showed differential expression under at least one phytohormone treatment. Moreover, we verified the diurnal expression of the OsBBX genes using the data obtained from the Diurnal Project and qPCR analysis, and the results indicated that many of these genes had a diurnal expression pattern. Conclusions/Significance The combination of the genome-wide identification and the expression and diurnal analysis of the OsBBX gene family should facilitate additional functional studies of the OsBBX genes. PMID:23118960

Cloud-Scale Genomic Signals Processing for Robust Large-Scale Cancer Genomic Microarray Data Analysis.

PubMed

Harvey, Benjamin Simeon; Ji, Soo-Yeon

2017-01-01

As microarray data available to scientists continues to increase in size and complexity, it has become overwhelmingly important to find multiple ways to bring forth oncological inference to the bioinformatics community through the analysis of large-scale cancer genomic (LSCG) DNA and mRNA microarray data that is useful to scientists. Though there have been many attempts to elucidate the issue of bringing forth biological interpretation by means of wavelet preprocessing and classification, there has not been a research effort that focuses on a cloud-scale distributed parallel (CSDP) separable 1-D wavelet decomposition technique for denoising through differential expression thresholding and classification of LSCG microarray data. This research presents a novel methodology that utilizes a CSDP separable 1-D method for wavelet-based transformation in order to initialize a threshold which will retain significantly expressed genes through the denoising process for robust classification of cancer patients. Additionally, the overall study was implemented and encompassed within CSDP environment. The utilization of cloud computing and wavelet-based thresholding for denoising was used for the classification of samples within the Global Cancer Map, Cancer Cell Line Encyclopedia, and The Cancer Genome Atlas. The results proved that separable 1-D parallel distributed wavelet denoising in the cloud and differential expression thresholding increased the computational performance and enabled the generation of higher quality LSCG microarray datasets, which led to more accurate classification results.

Genome-wide analysis of a Wnt1-regulated transcriptional network implicates neurodegenerative pathways.

PubMed

Wexler, Eric M; Rosen, Ezra; Lu, Daning; Osborn, Gregory E; Martin, Elizabeth; Raybould, Helen; Geschwind, Daniel H

2011-10-04

Wnt proteins are critical to mammalian brain development and function. The canonical Wnt signaling pathway involves the stabilization and nuclear translocation of β-catenin; however, Wnt also signals through alternative, noncanonical pathways. To gain a systems-level, genome-wide view of Wnt signaling, we analyzed Wnt1-stimulated changes in gene expression by transcriptional microarray analysis in cultured human neural progenitor (hNP) cells at multiple time points over a 72-hour time course. We observed a widespread oscillatory-like pattern of changes in gene expression, involving components of both the canonical and the noncanonical Wnt signaling pathways. A higher-order, systems-level analysis that combined independent component analysis, waveform analysis, and mutual information-based network construction revealed effects on pathways related to cell death and neurodegenerative disease. Wnt effectors were tightly clustered with presenilin1 (PSEN1) and granulin (GRN), which cause dominantly inherited forms of Alzheimer's disease and frontotemporal dementia (FTD), respectively. We further explored a potential link between Wnt1 and GRN and found that Wnt1 decreased GRN expression by hNPs. Conversely, GRN knockdown increased WNT1 expression, demonstrating that Wnt and GRN reciprocally regulate each other. Finally, we provided in vivo validation of the in vitro findings by analyzing gene expression data from individuals with FTD. These unbiased and genome-wide analyses provide evidence for a connection between Wnt signaling and the transcriptional regulation of neurodegenerative disease genes.

Evaluation of chronic lymphocytic leukemia by oligonucleotide-based microarray analysis uncovers novel aberrations not detected by FISH or cytogenetic analysis

PubMed Central

2011-01-01

Background Cytogenetic evaluation is a key component of the diagnosis and prognosis of chronic lymphocytic leukemia (CLL). We performed oligonucleotide-based comparative genomic hybridization microarray analysis on 34 samples with CLL and known abnormal karyotypes previously determined by cytogenetics and/or fluorescence in situ hybridization (FISH). Results Using a custom designed microarray that targets >1800 genes involved in hematologic disease and other malignancies, we identified additional cryptic aberrations and novel findings in 59% of cases. These included gains and losses of genes associated with cell cycle regulation, apoptosis and susceptibility loci on 3p21.31, 5q35.2q35.3, 10q23.31q23.33, 11q22.3, and 22q11.23. Conclusions Our results show that microarray analysis will detect known aberrations, including microscopic and cryptic alterations. In addition, novel genomic changes will be uncovered that may become important prognostic predictors or treatment targets for CLL in the future. PMID:22087757

[Technology of analysis of epigenetic and structural changes of epithelial tumors genome with NotI-microarrays by the example of human chromosome].

PubMed

Pavlova, T V; Kashuba, V I; Muravenko, O V; Yenamandra, S P; Ivanova, T A; Zabarovskaia, V I; Rakhmanaliev, E R; Petrenko, L A; Pronina, I V; Loginov, V I; Iurkevich, O Iu; Kiselev, L L; Zelenin, A V; Zabarovskiĭ, E R

2009-01-01

New comparative genome hybridization technology on NotI-microarrays is presented (Karolinska Institute International Patent WO02/086163). The method is based on comparative genome hybridization of NotI-probes from tumor and normal genomic DNA with the principle of new DNA NotI-microarrays. Using this method 181 NotI linking loci from human chromosome 3 were analyzed in 200 malignant tumor samples from different organs: kidney, lung, breast, ovary, cervical, prostate. Most frequently (more than in 30%) aberrations--deletions, methylation,--were identified in NotI-sites located in MINT24, BHLHB2, RPL15, RARbeta1, ITGA9, RBSP3, VHL, ZIC4 genes, that suggests they probably are involved in cancer development. Methylation of these genomic loci was confirmed by methylation-specific PCR and bisulfite sequencing. The results demonstrate perspective of using this method to solve some oncogenomic problems.

High Quality Genomic Copy Number Data from Archival Formalin-Fixed Paraffin-Embedded Leiomyosarcoma: Optimisation of Universal Linkage System Labelling

PubMed Central

Salawu, Abdulazeez; Ul-Hassan, Aliya; Hammond, David; Fernando, Malee; Reed, Malcolm; Sisley, Karen

2012-01-01

Most soft tissue sarcomas are characterized by genetic instability and frequent genomic copy number aberrations that are not subtype-specific. Oligonucleotide microarray-based Comparative Genomic Hybridisation (array CGH) is an important technique used to map genome-wide copy number aberrations, but the traditional requirement for high-quality DNA typically obtained from fresh tissue has limited its use in sarcomas. Although large archives of Formalin-fixed Paraffin-embedded (FFPE) tumour samples are available for research, the degradative effects of formalin on DNA from these tissues has made labelling and analysis by array CGH technically challenging. The Universal Linkage System (ULS) may be used for a one-step chemical labelling of such degraded DNA. We have optimised the ULS labelling protocol to perform aCGH on archived FFPE leiomyosarcoma tissues using the 180k Agilent platform. Preservation age of samples ranged from a few months to seventeen years and the DNA showed a wide range of degradation (when visualised on agarose gels). Consistently high DNA labelling efficiency and low microarray probe-to-probe variation (as measured by the derivative log ratio spread) was seen. Comparison of paired fresh and FFPE samples from identical tumours showed good correlation of CNAs detected. Furthermore, the ability to macro-dissect FFPE samples permitted the detection of CNAs that were masked in fresh tissue. Aberrations were visually confirmed using Fluorescence in situ Hybridisation. These results suggest that archival FFPE tissue, with its relative abundance and attendant clinical data may be used for effective mapping for genomic copy number aberrations in such rare tumours as leiomyosarcoma and potentially unravel clues to tumour origins, progression and ultimately, targeted treatment. PMID:23209738

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

PubMed

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

2007-11-22

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

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

PubMed

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

2012-06-08

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

Differential gene expression related to Nora virus infection of Drosophila melanogaster

PubMed Central

Cordes, Ethan J.; Licking-Murray, Kellie D; Carlson, Kimberly A.

2013-01-01

Nora virus is a recently discovered RNA picorna-like virus that produces a persistent infection in Drosophila melanogaster, but the antiviral pathway or change in gene expression is unknown. We performed cDNA microarray analysis comparing the gene expression profiles of Nora virus infected and uninfected wild-type D. melanogaster. This analysis yielded 58 genes exhibiting a 1.5-fold change or greater and p-value less than 0.01. Of these genes, 46 were up-regulated and 12 down-regulated in response to infection. To validate the microarray results, qRT-PCR was performed with probes for Chorion protein 16 and Troponin C isoform 4, which show good correspondence with cDNA microarray results. Differential regulation of genes associated with Toll and immune-deficient pathways, cytoskeletal development, Janus Kinase-Signal Transducer and Activator of Transcription interactions, and a potential gut-specific innate immune response were found. This genome-wide expression profile of Nora virus infection of D. melanogaster can pinpoint genes of interest for further investigation of antiviral pathways employed, genetic mechanisms, sites of replication, viral persistence, and developmental effects. PMID:23603562

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

PubMed Central

2011-01-01

Background Understanding the genetic elements that contribute to key aspects of coffee biology will have an impact on future agronomical improvements for this economically important tree. During the past years, EST collections were generated in Coffee, opening the possibility to create new tools for functional genomics. Results The "PUCE CAFE" Project, organized by the scientific consortium NESTLE/IRD/CIRAD, has developed an oligo-based microarray using 15,721 unigenes derived from published coffee EST sequences mostly obtained from different stages of fruit development and leaves in Coffea Canephora (Robusta). Hybridizations for two independent experiments served to compare global gene expression profiles in three types of tissue matter (mature beans, leaves and flowers) in C. canephora as well as in the leaves of three different coffee species (C. canephora, C. eugenoides and C. arabica). Microarray construction, statistical analyses and validation by Q-PCR analysis are presented in this study. Conclusion We have generated the first 15 K coffee array during this PUCE CAFE project, granted by Génoplante (the French consortium for plant genomics). This new tool will help study functional genomics in a wide range of experiments on various plant tissues, such as analyzing bean maturation or resistance to pathogens or drought. Furthermore, the use of this array has proven to be valid in different coffee species (diploid or tetraploid), drastically enlarging its impact for high-throughput gene expression in the community of coffee research. PMID:21208403

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

PubMed

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

2011-01-05

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

LS-CAP: an algorithm for identifying cytogenetic aberrations in hepatocellular carcinoma using microarray data.

PubMed

He, Xianmin; Wei, Qing; Sun, Meiqian; Fu, Xuping; Fan, Sichang; Li, Yao

2006-05-01

Biological techniques such as Array-Comparative genomic hybridization (CGH), fluorescent in situ hybridization (FISH) and affymetrix single nucleotide pleomorphism (SNP) array have been used to detect cytogenetic aberrations. However, on genomic scale, these techniques are labor intensive and time consuming. Comparative genomic microarray analysis (CGMA) has been used to identify cytogenetic changes in hepatocellular carcinoma (HCC) using gene expression microarray data. However, CGMA algorithm can not give precise localization of aberrations, fails to identify small cytogenetic changes, and exhibits false negatives and positives. Locally un-weighted smoothing cytogenetic aberrations prediction (LS-CAP) based on local smoothing and binomial distribution can be expected to address these problems. LS-CAP algorithm was built and used on HCC microarray profiles. Eighteen cytogenetic abnormalities were identified, among them 5 were reported previously, and 12 were proven by CGH studies. LS-CAP effectively reduced the false negatives and positives, and precisely located small fragments with cytogenetic aberrations.

Inference of sigma factor controlled networks by using numerical modeling applied to microarray time series data of the germinating prokaryote.

PubMed

Strakova, Eva; Zikova, Alice; Vohradsky, Jiri

2014-01-01

A computational model of gene expression was applied to a novel test set of microarray time series measurements to reveal regulatory interactions between transcriptional regulators represented by 45 sigma factors and the genes expressed during germination of a prokaryote Streptomyces coelicolor. Using microarrays, the first 5.5 h of the process was recorded in 13 time points, which provided a database of gene expression time series on genome-wide scale. The computational modeling of the kinetic relations between the sigma factors, individual genes and genes clustered according to the similarity of their expression kinetics identified kinetically plausible sigma factor-controlled networks. Using genome sequence annotations, functional groups of genes that were predominantly controlled by specific sigma factors were identified. Using external binding data complementing the modeling approach, specific genes involved in the control of the studied process were identified and their function suggested.

GeoChip 3.0: A High Throughput Tool for Analyzing Microbial Community, Composition, Structure, and Functional Activity

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

He, Zhili; Deng, Ye; Nostrand, Joy Van

2010-05-17

Microarray-based genomic technology has been widely used for microbial community analysis, and it is expected that microarray-based genomic technologies will revolutionize the analysis of microbial community structure, function and dynamics. A new generation of functional gene arrays (GeoChip 3.0) has been developed, with 27,812 probes covering 56,990 gene variants from 292 functional gene families involved in carbon, nitrogen, phosphorus and sulfur cycles, energy metabolism, antibiotic resistance, metal resistance, and organic contaminant degradation. Those probes were derived from 2,744, 140, and 262 species for bacteria, archaea, and fungi, respectively. GeoChip 3.0 has several other distinct features, such as a common oligomore » reference standard (CORS) for data normalization and comparison, a software package for data management and future updating, and the gyrB gene for phylogenetic analysis. Our computational evaluation of probe specificity indicated that all designed probes had a high specificity to their corresponding targets. Also, experimental analysis with synthesized oligonucleotides and genomic DNAs showed that only 0.0036percent-0.025percent false positive rates were observed, suggesting that the designed probes are highly specific under the experimental conditions examined. In addition, GeoChip 3.0 was applied to analyze soil microbial communities in a multifactor grassland ecosystem in Minnesota, USA, which demonstrated that the structure, composition, and potential activity of soil microbial communities significantly changed with the plant species diversity. All results indicate that GeoChip 3.0 is a high throughput powerful tool for studying microbial community functional structure, and linking microbial communities to ecosystem processes and functioning. To our knowledge, GeoChip 3.0 is the most comprehensive microarrays currently available for studying microbial communities associated with geobiochemical cycling, global climate change, bioenergy, agricuture, land use, ecosystem management, environmental cleanup and restoration, bioreactor systems, and human health.« less

Independent evolution of neurotoxin and flagellar genetic loci in proteolytic Clostridium botulinum

PubMed Central

Carter, Andrew T; Paul, Catherine J; Mason, David R; Twine, Susan M; Alston, Mark J; Logan, Susan M; Austin, John W; Peck, Michael W

2009-01-01

Background Proteolytic Clostridium botulinum is the causative agent of botulism, a severe neuroparalytic illness. Given the severity of botulism, surprisingly little is known of the population structure, biology, phylogeny or evolution of C. botulinum. The recent determination of the genome sequence of C. botulinum has allowed comparative genomic indexing using a DNA microarray. Results Whole genome microarray analysis revealed that 63% of the coding sequences (CDSs) present in reference strain ATCC 3502 were common to all 61 widely-representative strains of proteolytic C. botulinum and the closely related C. sporogenes tested. This indicates a relatively stable genome. There was, however, evidence for recombination and genetic exchange, in particular within the neurotoxin gene and cluster (including transfer of neurotoxin genes to C. sporogenes), and the flagellar glycosylation island (FGI). These two loci appear to have evolved independently from each other, and from the remainder of the genetic complement. A number of strains were atypical; for example, while 10 out of 14 strains that formed type A1 toxin gave almost identical profiles in whole genome, neurotoxin cluster and FGI analyses, the other four strains showed divergent properties. Furthermore, a new neurotoxin sub-type (A5) has been discovered in strains from heroin-associated wound botulism cases. For the first time, differences in glycosylation profiles of the flagella could be linked to differences in the gene content of the FGI. Conclusion Proteolytic C. botulinum has a stable genome backbone containing specific regions of genetic heterogeneity. These include the neurotoxin gene cluster and the FGI, each having evolved independently of each other and the remainder of the genetic complement. Analysis of these genetic components provides a high degree of discrimination of strains of proteolytic C. botulinum, and is suitable for clinical and forensic investigations of botulism outbreaks. PMID:19298644

Independent evolution of neurotoxin and flagellar genetic loci in proteolytic Clostridium botulinum.

PubMed

Carter, Andrew T; Paul, Catherine J; Mason, David R; Twine, Susan M; Alston, Mark J; Logan, Susan M; Austin, John W; Peck, Michael W

2009-03-19

Proteolytic Clostridium botulinum is the causative agent of botulism, a severe neuroparalytic illness. Given the severity of botulism, surprisingly little is known of the population structure, biology, phylogeny or evolution of C. botulinum. The recent determination of the genome sequence of C. botulinum has allowed comparative genomic indexing using a DNA microarray. Whole genome microarray analysis revealed that 63% of the coding sequences (CDSs) present in reference strain ATCC 3502 were common to all 61 widely-representative strains of proteolytic C. botulinum and the closely related C. sporogenes tested. This indicates a relatively stable genome. There was, however, evidence for recombination and genetic exchange, in particular within the neurotoxin gene and cluster (including transfer of neurotoxin genes to C. sporogenes), and the flagellar glycosylation island (FGI). These two loci appear to have evolved independently from each other, and from the remainder of the genetic complement. A number of strains were atypical; for example, while 10 out of 14 strains that formed type A1 toxin gave almost identical profiles in whole genome, neurotoxin cluster and FGI analyses, the other four strains showed divergent properties. Furthermore, a new neurotoxin sub-type (A5) has been discovered in strains from heroin-associated wound botulism cases. For the first time, differences in glycosylation profiles of the flagella could be linked to differences in the gene content of the FGI. Proteolytic C. botulinum has a stable genome backbone containing specific regions of genetic heterogeneity. These include the neurotoxin gene cluster and the FGI, each having evolved independently of each other and the remainder of the genetic complement. Analysis of these genetic components provides a high degree of discrimination of strains of proteolytic C. botulinum, and is suitable for clinical and forensic investigations of botulism outbreaks.

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

PubMed

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

2006-07-21

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

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

PubMed Central

Awad, Ihab AB; Rees, Christian A; Hernandez-Boussard, Tina; Ball, Catherine A; Sherlock, Gavin

2004-01-01

Background Microarray-based comparative genome hybridization experiments generate data that can be mapped onto the genome. These data are interpreted more easily when represented graphically in a genomic context. Results We have developed Caryoscope, which is an open source Java application for visualizing microarray data from array comparative genome hybridization experiments in a genomic context. Caryoscope can read General Feature Format files (GFF files), as well as comma- and tab-delimited files, that define the genomic positions of the microarray reporters for which data are obtained. The microarray data can be browsed using an interactive, zoomable interface, which helps users identify regions of chromosomal deletion or amplification. The graphical representation of the data can be exported in a number of graphic formats, including publication-quality formats such as PostScript. Conclusion Caryoscope is a useful tool that can aid in the visualization, exploration and interpretation of microarray data in a genomic context. PMID:15488149

Genome Expression Pathway Analysis Tool – Analysis and visualization of microarray gene expression data under genomic, proteomic and metabolic context

PubMed Central

Weniger, Markus; Engelmann, Julia C; Schultz, Jörg

2007-01-01

Background Regulation of gene expression is relevant to many areas of biology and medicine, in the study of treatments, diseases, and developmental stages. Microarrays can be used to measure the expression level of thousands of mRNAs at the same time, allowing insight into or comparison of different cellular conditions. The data derived out of microarray experiments is highly dimensional and often noisy, and interpretation of the results can get intricate. Although programs for the statistical analysis of microarray data exist, most of them lack an integration of analysis results and biological interpretation. Results We have developed GEPAT, Genome Expression Pathway Analysis Tool, offering an analysis of gene expression data under genomic, proteomic and metabolic context. We provide an integration of statistical methods for data import and data analysis together with a biological interpretation for subsets of probes or single probes on the chip. GEPAT imports various types of oligonucleotide and cDNA array data formats. Different normalization methods can be applied to the data, afterwards data annotation is performed. After import, GEPAT offers various statistical data analysis methods, as hierarchical, k-means and PCA clustering, a linear model based t-test or chromosomal profile comparison. The results of the analysis can be interpreted by enrichment of biological terms, pathway analysis or interaction networks. Different biological databases are included, to give various information for each probe on the chip. GEPAT offers no linear work flow, but allows the usage of any subset of probes and samples as a start for a new data analysis. GEPAT relies on established data analysis packages, offers a modular approach for an easy extension, and can be run on a computer grid to allow a large number of users. It is freely available under the LGPL open source license for academic and commercial users at . Conclusion GEPAT is a modular, scalable and professional-grade software integrating analysis and interpretation of microarray gene expression data. An installation available for academic users can be found at . PMID:17543125

Genome-wide analyses of LINE–LINE-mediated nonallelic homologous recombination

PubMed Central

Startek, Michał; Szafranski, Przemyslaw; Gambin, Tomasz; Campbell, Ian M.; Hixson, Patricia; Shaw, Chad A.; Stankiewicz, Paweł; Gambin, Anna

2015-01-01

Nonallelic homologous recombination (NAHR), occurring between low-copy repeats (LCRs) >10 kb in size and sharing >97% DNA sequence identity, is responsible for the majority of recurrent genomic rearrangements in the human genome. Recent studies have shown that transposable elements (TEs) can also mediate recurrent deletions and translocations, indicating the features of substrates that mediate NAHR may be significantly less stringent than previously believed. Using >4 kb length and >95% sequence identity criteria, we analyzed of the genome-wide distribution of long interspersed element (LINE) retrotransposon and their potential to mediate NAHR. We identified 17 005 directly oriented LINE pairs located <10 Mbp from each other as potential NAHR substrates, placing 82.8% of the human genome at risk of LINE–LINE-mediated instability. Cross-referencing these regions with CNVs in the Baylor College of Medicine clinical chromosomal microarray database of 36 285 patients, we identified 516 CNVs potentially mediated by LINEs. Using long-range PCR of five different genomic regions in a total of 44 patients, we confirmed that the CNV breakpoints in each patient map within the LINE elements. To additionally assess the scale of LINE–LINE/NAHR phenomenon in the human genome, we tested DNA samples from six healthy individuals on a custom aCGH microarray targeting LINE elements predicted to mediate CNVs and identified 25 LINE–LINE rearrangements. Our data indicate that LINE–LINE-mediated NAHR is widespread and under-recognized, and is an important mechanism of structural rearrangement contributing to human genomic variability. PMID:25613453

Regulated mRNA Decay in Arabidopsis: A global analysis of differential control by hormones and the circadian clock

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

Green, Pamela J.

The long-term goal of this research was to better understand the influence of mRNA stability on gene regulation, particularly in response to hormones and the circadian clock. The primary aim of this project was to examine this using DNA microarrays, small RNA analysis and other approaches. We accomplished these objectives, although we were only able to detect small changes in mRNA stability in response to these stimuli. However, the work also contributed to a major breakthrough allowing the identification of small RNAs on a genomic scale in eukaryotes. Moreover, the project prompted us to develop a new way to analyzemore » mRNA decay genome wide. Thus, the research was hugely successful beyond our objectives.« less

[Genome-wide identification and expression analysis of auxin-related gene families in grape].

PubMed

Yuan, Hua-zhao; Zhao, Mi-zhen; Wu, Wei-min; Yu, Hong-Mei; Qian, Ya-ming; Wang, Zhuang-wei; Wang, Xi-cheng

2015-07-01

The auxin response gene family adjusts the auxin balance and the growth hormone signaling pathways in plants. Using bioinformatics methods, the auxin-response genes from the grape genome database are identified and their chromosomal location, gene collinearity and phylogenetic analysis are performed. Probable genes include 25 AUX_IAA, 19 ARF, 9 GH3 and 42 LBD genes, which are unevenly distributed on all 19 chromosomes and some of them formed distinct tandem duplicate gene clusters. The available grape microarray databases show that all of the auxin-response genes are expressed in fruit and leaf buds, and significant overexpressed during fruit color-changing, bud break and bud dormancy periods. This paper provides a resource for functional studies of auxin-response genes in grape leaf and fruit development.

Genome analysis of Legionella pneumophila strains using a mixed-genome microarray.

PubMed

Euser, Sjoerd M; Nagelkerke, Nico J; Schuren, Frank; Jansen, Ruud; Den Boer, Jeroen W

2012-01-01

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 methods that offer the ability to distinguish clinical from environmental strains could help to focus on more relevant (virulent) Legionella species in control efforts. Mixed-genome microarray data can be used to perform a comparative-genome analysis of strain collections, and advanced statistical approaches, such as the Random Forest algorithm are available to process these data. Microarray analysis was performed on a collection of 222 Legionella pneumophila strains, which included patient-derived strains from notified cases in The Netherlands in the period 2002-2006 and the environmental strains that were collected during the source investigation for those patients within the Dutch National Legionella Outbreak Detection Programme. The Random Forest algorithm combined with a logistic regression model was used to select predictive markers and to construct a predictive model that could discriminate between strains from different origin: clinical or environmental. Four genetic markers were selected that correctly predicted 96% of the clinical strains and 66% of the environmental strains collected within the Dutch National Legionella Outbreak Detection Programme. The Random Forest algorithm is well suited for the development of prediction models that use mixed-genome microarray data to discriminate between Legionella strains from different origin. The identification of these predictive genetic markers could offer the possibility to identify virulence factors within the Legionella genome, which in the future may be implemented in the daily practice of controlling Legionella in the public health environment.

Genome-wide Association Study of Obsessive-Compulsive Disorder

PubMed Central

Stewart, S Evelyn; Yu, Dongmei; Scharf, Jeremiah M; Neale, Benjamin M; Fagerness, Jesen A; Mathews, Carol A; Arnold, Paul D; Evans, Patrick D; Gamazon, Eric R; Osiecki, Lisa; McGrath, Lauren; Haddad, Stephen; Crane, Jacquelyn; Hezel, Dianne; Illman, Cornelia; Mayerfeld, Catherine; Konkashbaev, Anuar; Liu, Chunyu; Pluzhnikov, Anna; Tikhomirov, Anna; Edlund, Christopher K; Rauch, Scott L; Moessner, Rainald; Falkai, Peter; Maier, Wolfgang; Ruhrmann, Stephan; Grabe, Hans-Jörgen; Lennertz, Leonard; Wagner, Michael; Bellodi, Laura; Cavallini, Maria Cristina; Richter, Margaret A; Cook, Edwin H; Kennedy, James L; Rosenberg, David; Stein, Dan J; Hemmings, Sian MJ; Lochner, Christine; Azzam, Amin; Chavira, Denise A; Fournier, Eduardo; Garrido, Helena; Sheppard, Brooke; Umaña, Paul; Murphy, Dennis L; Wendland, Jens R; Veenstra-VanderWeele, Jeremy; Denys, Damiaan; Blom, Rianne; Deforce, Dieter; Van Nieuwerburgh, Filip; Westenberg, Herman GM; Walitza, Susanne; Egberts, Karin; Renner, Tobias; Miguel, Euripedes Constantino; Cappi, Carolina; Hounie, Ana G; Conceição do Rosário, Maria; Sampaio, Aline S; Vallada, Homero; Nicolini, Humberto; Lanzagorta, Nuria; Camarena, Beatriz; Delorme, Richard; Leboyer, Marion; Pato, Carlos N; Pato, Michele T; Voyiaziakis, Emanuel; Heutink, Peter; Cath, Danielle C; Posthuma, Danielle; Smit, Jan H; Samuels, Jack; Bienvenu, O Joseph; Cullen, Bernadette; Fyer, Abby J; Grados, Marco A; Greenberg, Benjamin D; McCracken, James T; Riddle, Mark A; Wang, Ying; Coric, Vladimir; Leckman, James F; Bloch, Michael; Pittenger, Christopher; Eapen, Valsamma; Black, Donald W; Ophoff, Roel A; Strengman, Eric; Cusi, Daniele; Turiel, Maurizio; Frau, Francesca; Macciardi, Fabio; Gibbs, J Raphael; Cookson, Mark R; Singleton, Andrew; Hardy, John; Crenshaw, Andrew T; Parkin, Melissa A; Mirel, Daniel B; Conti, David V; Purcell, Shaun; Nestadt, Gerald; Hanna, Gregory L; Jenike, Michael A; Knowles, James A; Cox, Nancy; Pauls, David L

2014-01-01

Obsessive-compulsive disorder (OCD) is a common, debilitating neuropsychiatric illness with complex genetic etiology. The International OCD Foundation Genetics Collaborative (IOCDF-GC) is a multi-national collaboration established to discover the genetic variation predisposing to OCD. A set of individuals affected with DSM-IV OCD, a subset of their parents, and unselected controls, were genotyped with several different Illumina SNP microarrays. After extensive data cleaning, 1,465 cases, 5,557 ancestry-matched controls and 400 complete trios remained, with a common set of 469,410 autosomal and 9,657 X-chromosome SNPs. Ancestry-stratified case-control association analyses were conducted for three genetically-defined subpopulations and combined in two meta-analyses, with and without the trio-based analysis. In the case-control analysis, the lowest two p-values were located within DLGAP1 (p=2.49×10-6 and p=3.44×10-6), a member of the neuronal postsynaptic density complex. In the trio analysis, rs6131295, near BTBD3, exceeded the genome-wide significance threshold with a p-value=3.84 × 10-8. However, when trios were meta-analyzed with the combined case-control samples, the p-value for this variant was 3.62×10-5, losing genome-wide significance. Although no SNPs were identified to be associated with OCD at a genome-wide significant level in the combined trio-case-control sample, a significant enrichment of methylation-QTLs (p<0.001) and frontal lobe eQTLs (p=0.001) was observed within the top-ranked SNPs (p<0.01) from the trio-case-control analysis, suggesting these top signals may have a broad role in gene expression in the brain, and possibly in the etiology of OCD. PMID:22889921

Detection of genome-wide copy number variants in myeloid malignancies using next-generation sequencing.

PubMed

Shen, Wei; Paxton, Christian N; Szankasi, Philippe; Longhurst, Maria; Schumacher, Jonathan A; Frizzell, Kimberly A; Sorrells, Shelly M; Clayton, Adam L; Jattani, Rakhi P; Patel, Jay L; Toydemir, Reha; Kelley, Todd W; Xu, Xinjie

2018-04-01

Genetic abnormalities, including copy number variants (CNV), copy number neutral loss of heterozygosity (CN-LOH) and gene mutations, underlie the pathogenesis of myeloid malignancies and serve as important diagnostic, prognostic and/or therapeutic markers. Currently, multiple testing strategies are required for comprehensive genetic testing in myeloid malignancies. The aim of this proof-of-principle study was to investigate the feasibility of combining detection of genome-wide large CNVs, CN-LOH and targeted gene mutations into a single assay using next-generation sequencing (NGS). For genome-wide CNV detection, we designed a single nucleotide polymorphism (SNP) sequencing backbone with 22 762 SNP regions evenly distributed across the entire genome. For targeted mutation detection, 62 frequently mutated genes in myeloid malignancies were targeted. We combined this SNP sequencing backbone with a targeted mutation panel, and sequenced 9 healthy individuals and 16 patients with myeloid malignancies using NGS. We detected 52 somatic CNVs, 11 instances of CN-LOH and 39 oncogenic mutations in the 16 patients with myeloid malignancies, and none in the 9 healthy individuals. All CNVs and CN-LOH were confirmed by SNP microarray analysis. We describe a genome-wide SNP sequencing backbone which allows for sensitive detection of genome-wide CNVs and CN-LOH using NGS. This proof-of-principle study has demonstrated that this strategy can provide more comprehensive genetic profiling for patients with myeloid malignancies using a single assay. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2018. All rights reserved. No commercial use is permitted unless otherwise expressly granted.

Computational tools for copy number variation (CNV) detection using next-generation sequencing data: features and perspectives.

PubMed

Zhao, Min; Wang, Qingguo; Wang, Quan; Jia, Peilin; Zhao, Zhongming

2013-01-01

Copy number variation (CNV) is a prevalent form of critical genetic variation that leads to an abnormal number of copies of large genomic regions in a cell. Microarray-based comparative genome hybridization (arrayCGH) or genotyping arrays have been standard technologies to detect large regions subject to copy number changes in genomes until most recently high-resolution sequence data can be analyzed by next-generation sequencing (NGS). During the last several years, NGS-based analysis has been widely applied to identify CNVs in both healthy and diseased individuals. Correspondingly, the strong demand for NGS-based CNV analyses has fuelled development of numerous computational methods and tools for CNV detection. In this article, we review the recent advances in computational methods pertaining to CNV detection using whole genome and whole exome sequencing data. Additionally, we discuss their strengths and weaknesses and suggest directions for future development.

Computational tools for copy number variation (CNV) detection using next-generation sequencing data: features and perspectives

PubMed Central

2013-01-01

Copy number variation (CNV) is a prevalent form of critical genetic variation that leads to an abnormal number of copies of large genomic regions in a cell. Microarray-based comparative genome hybridization (arrayCGH) or genotyping arrays have been standard technologies to detect large regions subject to copy number changes in genomes until most recently high-resolution sequence data can be analyzed by next-generation sequencing (NGS). During the last several years, NGS-based analysis has been widely applied to identify CNVs in both healthy and diseased individuals. Correspondingly, the strong demand for NGS-based CNV analyses has fuelled development of numerous computational methods and tools for CNV detection. In this article, we review the recent advances in computational methods pertaining to CNV detection using whole genome and whole exome sequencing data. Additionally, we discuss their strengths and weaknesses and suggest directions for future development. PMID:24564169

MobilomeFINDER: web-based tools for in silico and experimental discovery of bacterial genomic islands

PubMed Central

Ou, Hong-Yu; He, Xinyi; Harrison, Ewan M.; Kulasekara, Bridget R.; Thani, Ali Bin; Kadioglu, Aras; Lory, Stephen; Hinton, Jay C. D.; Barer, Michael R.; Rajakumar, Kumar

2007-01-01

MobilomeFINDER (http://mml.sjtu.edu.cn/MobilomeFINDER) is an interactive online tool that facilitates bacterial genomic island or ‘mobile genome’ (mobilome) discovery; it integrates the ArrayOme and tRNAcc software packages. ArrayOme utilizes a microarray-derived comparative genomic hybridization input data set to generate ‘inferred contigs’ produced by merging adjacent genes classified as ‘present’. Collectively these ‘fragments’ represent a hypothetical ‘microarray-visualized genome (MVG)’. ArrayOme permits recognition of discordances between physical genome and MVG sizes, thereby enabling identification of strains rich in microarray-elusive novel genes. Individual tRNAcc tools facilitate automated identification of genomic islands by comparative analysis of the contents and contexts of tRNA sites and other integration hotspots in closely related sequenced genomes. Accessory tools facilitate design of hotspot-flanking primers for in silico and/or wet-science-based interrogation of cognate loci in unsequenced strains and analysis of islands for features suggestive of foreign origins; island-specific and genome-contextual features are tabulated and represented in schematic and graphical forms. To date we have used MobilomeFINDER to analyse several Enterobacteriaceae, Pseudomonas aeruginosa and Streptococcus suis genomes. MobilomeFINDER enables high-throughput island identification and characterization through increased exploitation of emerging sequence data and PCR-based profiling of unsequenced test strains; subsequent targeted yeast recombination-based capture permits full-length sequencing and detailed functional studies of novel genomic islands. PMID:17537813

Genome-wide expressions in autologous eutopic and ectopic endometrium of fertile women with endometriosis.

PubMed

Khan, Meraj A; Sengupta, Jayasree; Mittal, Suneeta; Ghosh, Debabrata

2012-09-24

In order to obtain a lead of the pathophysiology of endometriosis, genome-wide expressional analyses of eutopic and ectopic endometrium have earlier been reported, however, the effects of stages of severity and phases of menstrual cycle on expressional profiles have not been examined. The effect of genetic heterogeneity and fertility history on transcriptional activity was also not considered. In the present study, a genome-wide expression analysis of autologous, paired eutopic and ectopic endometrial samples obtained from fertile women (n=18) suffering from moderate (stage 3; n=8) or severe (stage 4; n=10) ovarian endometriosis during proliferative (n=13) and secretory (n=5) phases of menstrual cycle was performed. Individual pure RNA samples were subjected to Agilent's Whole Human Genome 44K microarray experiments. Microarray data were validated (P<0.01) by estimating transcript copy numbers by performing real time RT-PCR of seven (7) arbitrarily selected genes in all samples. The data obtained were subjected to differential expression (DE) and differential co-expression (DC) analyses followed by networks and enrichment analysis, and gene set enrichment analysis (GSEA). The reproducibility of prediction based on GSEA implementation of DC results was assessed by examining the relative expressions of twenty eight (28) selected genes in RNA samples obtained from fresh pool of eutopic and ectopic samples from confirmed ovarian endometriosis patients with stages 3 and 4 (n=4/each) during proliferative and secretory (n=4/each) phases. Higher clustering effect of pairing (cluster distance, cd=0.1) in samples from same individuals on expressional arrays among eutopic and ectopic samples was observed as compared to that of clinical stages of severity (cd=0.5) and phases of menstrual cycle (cd=0.6). Post hoc analysis revealed anomaly in the expressional profiles of several genes associated with immunological, neuracrine and endocrine functions and gynecological cancers however with no overt oncogenic potential in endometriotic tissue. Dys-regulation of three (CLOCK, ESR1, and MYC) major transcription factors appeared to be significant causative factors in the pathogenesis of ovarian endometriosis. A novel cohort of twenty-eight (28) genes representing potential marker for ovarian endometriosis in fertile women was discovered. Dysfunctional expression of immuno-neuro-endocrine behaviour in endometrium appeared critical to endometriosis. Although no overt oncogenic potential was evident, several genes associated with gynecological cancers were observed to be high in the expressional profiles in endometriotic tissue.

A genome-wide analysis of the expansin genes in Malus × Domestica.

PubMed

Zhang, Shizhong; Xu, Ruirui; Gao, Zheng; Chen, Changtian; Jiang, Zesheng; Shu, Huairui

2014-04-01

Expansins were first identified as cell wall-loosening proteins; they are involved in regulating cell expansion, fruits softening and many other physiological processes. However, our knowledge about the expansin family members and their evolutionary relationships in fruit trees, such as apple, is limited. In this study, we identified 41 members of the expansin gene family in the genome of apple (Malus × Domestica L. Borkh). Phylogenetic analysis revealed that expansin genes in apple could be divided into four subfamilies according to their gene structures and protein motifs. By phylogenetic analysis of the expansins in five plants (Arabidopsis, rice, poplar, grape and apple), the expansins were divided into 17 subgroups. Our gene duplication analysis revealed that whole-genome and chromosomal-segment duplications contributed to the expansion of Mdexpansins. The microarray and expressed sequence tag (EST) data showed that 34 Mdexpansin genes could be divided into five groups by the EST analysis; they may also play different roles during fruit development. An expression model for MdEXPA16 and MdEXPA20 showed their potential role in developing fruit. Overall, our study provides useful data and novel insights into the functions and regulatory mechanisms of the expansin genes in apple, as well as their evolution and divergence. As the first step towards genome-wide analysis of the expansin genes in apple, our results have established a solid foundation for future studies on the function of the expansin genes in fruit development.

Interpretation of Genomic Data Questions and Answers

PubMed Central

Simon, Richard

2008-01-01

Using a question and answer format we describe important aspects of using genomic technologies in cancer research. The main challenges are not managing the mass of data, but rather the design, analysis and accurate reporting of studies that result in increased biological knowledge and medical utility. Many analysis issues address the use of expression microarrays but are also applicable to other whole genome assays. Microarray based clinical investigations have generated both unrealistic hyperbole and excessive skepticism. Genomic technologies are tremendously powerful and will play instrumental roles in elucidating the mechanisms of oncogenesis and in devlopingan era of predictive medicine in which treatments are tailored to individual tumors. Achieving these goals involves challenges in re-thinking many paradigms for the conduct of basic and clinical cancer research and for the organization of interdisciplinary collaboration. PMID:18582627

A short treatise concerning a musical approach for the interpretation of gene expression data

PubMed Central

Staege, Martin S.

2015-01-01

Recent technical developments allow the genome-wide and near-complete analysis of gene expression in a given sample, e.g. by usage of high-density DNA microarrays or next generation sequencing. The generated data structure is usually multi-dimensional and requires extensive processing not only for analysis but also for presentation of the results. Today, such data are usually presented graphically, e.g. in the form of heat maps. In the present paper, we propose an alternative form of analysis and presentation which is based on the transformation of gene expression data into sounds that are characterized by their frequency (pitch) and tone duration. Using DNA microarray data from a panel of neuroblastoma and Ewing sarcoma cell lines as well as from Hodgkin’s lymphoma cell lines and normal B cells, we demonstrate that this Gene Expression Music Algorithm (GEMusicA) can be used for discrimination between samples with different biology and for the characterization of differentially expressed genes. PMID:26472273

Identification of genomic aberrations in hemangioblastoma by droplet digital PCR and SNP microarray highlights novel candidate genes and pathways for pathogenesis.

PubMed

Mehrian-Shai, Ruty; Yalon, Michal; Moshe, Itai; Barshack, Iris; Nass, Dvorah; Jacob, Jasmine; Dor, Chen; Reichardt, Juergen K V; Constantini, Shlomi; Toren, Amos

2016-01-14

The genetic mechanisms underlying hemangioblastoma development are still largely unknown. We used high-resolution single nucleotide polymorphism microarrays and droplet digital PCR analysis to detect copy number variations (CNVs) in total of 45 hemangioblastoma tumors. We identified 94 CNVs with a median of 18 CNVs per sample. The most frequently gained regions were on chromosomes 1 (p36.32) and 7 (p11.2). These regions contain the EGFR and PRDM16 genes. Recurrent losses were located at chromosome 12 (q24.13), which includes the gene PTPN11. Our findings provide the first high-resolution genome-wide view of chromosomal changes in hemangioblastoma and identify 23 candidate genes: EGFR, PRDM16, PTPN11, HOXD11, HOXD13, FLT3, PTCH, FGFR1, FOXP1, GPC3, HOXC13, HOXC11, MKL1, CHEK2, IRF4, GPHN, IKZF1, RB1, HOXA9, and micro RNA, such as hsa-mir-196a-2 for hemangioblastoma pathogenesis. Furthermore, our data implicate that cell proliferation and angiogenesis promoting pathways may be involved in the molecular pathogenesis of hemangioblastoma.

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

PubMed

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

2018-05-18

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

Reverse Engineering of Genome-wide Gene Regulatory Networks from Gene Expression Data

PubMed Central

Liu, Zhi-Ping

2015-01-01

Transcriptional regulation plays vital roles in many fundamental biological processes. Reverse engineering of genome-wide regulatory networks from high-throughput transcriptomic data provides a promising way to characterize the global scenario of regulatory relationships between regulators and their targets. In this review, we summarize and categorize the main frameworks and methods currently available for inferring transcriptional regulatory networks from microarray gene expression profiling data. We overview each of strategies and introduce representative methods respectively. Their assumptions, advantages, shortcomings, and possible improvements and extensions are also clarified and commented. PMID:25937810

Genome-wide identification and characterisation of F-box family in maize.

PubMed

Jia, Fengjuan; Wu, Bingjiang; Li, Hui; Huang, Jinguang; Zheng, Chengchao

2013-11-01

F-box-containing proteins, as the key components of the protein degradation machinery, are widely distributed in higher plants and are considered as one of the largest known families of regulatory proteins. The F-box protein family plays a crucial role in plant growth and development and in response to biotic and abiotic stresses. However, systematic analysis of the F-box family in maize (Zea mays) has not been reported yet. In this paper, we identified and characterised the maize F-box genes in a genome-wide scale, including phylogenetic analysis, chromosome distribution, gene structure, promoter analysis and gene expression profiles. A total of 359 F-box genes were identified and divided into 15 subgroups by phylogenetic analysis. The F-box domain was relatively conserved, whereas additional motifs outside the F-box domain may indicate the functional diversification of maize F-box genes. These genes were unevenly distributed in ten maize chromosomes, suggesting that they expanded in the maize genome because of tandem and segmental duplication events. The expression profiles suggested that the maize F-box genes had temporal and spatial expression patterns. Putative cis-acting regulatory DNA elements involved in abiotic stresses were observed in maize F-box gene promoters. The gene expression profiles under abiotic stresses also suggested that some genes participated in stress responsive pathways. Furthermore, ten genes were chosen for quantitative real-time PCR analysis under drought stress and the results were consistent with the microarray data. This study has produced a comparative genomics analysis of the maize ZmFBX gene family that can be used in further studies to uncover their roles in maize growth and development.

Genome-wide identification and expression analysis of MAPK and MAPKK gene family in Malus domestica.

PubMed

Zhang, Shizhong; Xu, Ruirui; Luo, Xiaocui; Jiang, Zesheng; Shu, Huairui

2013-12-01

MAPK signal transduction modules play crucial roles in regulating many biological processes in plants, which are composed of three classes of hierarchically organized protein kinases, namely MAPKKKs, MAPKKs, and MAPKs. Although genome-wide analysis of this family has been carried out in some species, little is known about MAPK and MAPKK genes in apple (Malus domestica). In this study, a total of 26 putative apple MAPK genes (MdMPKs) and 9 putative apple MAPKK genes (MdMKKs) have been identified and located within the apple genome. Phylogenetic analysis revealed that MdMAPKs and MdMAPKKs could be divided into 4 subfamilies (groups A, B, C and D), respectively. The predicted MdMAPKs and MdMAPKKs were distributed across 13 out of 17 chromosomes with different densities. In addition, analysis of exon-intron junctions and of intron phase inside the predicted coding region of each candidate gene has revealed high levels of conservation within and between phylogenetic groups. According to the microarray and expressed sequence tag (EST) analysis, the different expression patterns indicate that they may play different roles during fruit development and rootstock-scion interaction process. Moreover, MAPK and MAPKK genes were performed expression profile analyses in different tissues (root, stem, leaf, flower and fruit), and all of the selected genes were expressed in at least one of the tissues tested, indicating that the MAPKs and MAPKKs are involved in various aspects of physiological and developmental processes of apple. To our knowledge, this is the first report of a genome-wide analysis of the apple MAPK and MAPKK gene family. This study provides valuable information for understanding the classification and putative functions of the MAPK signal in apple. © 2013.

Bacterial identification and subtyping using DNA microarray and DNA sequencing.

PubMed

Al-Khaldi, Sufian F; Mossoba, Magdi M; Allard, Marc M; Lienau, E Kurt; Brown, Eric D

2012-01-01

The era of fast and accurate discovery of biological sequence motifs in prokaryotic and eukaryotic cells is here. The co-evolution of direct genome sequencing and DNA microarray strategies not only will identify, isotype, and serotype pathogenic bacteria, but also it will aid in the discovery of new gene functions by detecting gene expressions in different diseases and environmental conditions. Microarray bacterial identification has made great advances in working with pure and mixed bacterial samples. The technological advances have moved beyond bacterial gene expression to include bacterial identification and isotyping. Application of new tools such as mid-infrared chemical imaging improves detection of hybridization in DNA microarrays. The research in this field is promising and future work will reveal the potential of infrared technology in bacterial identification. On the other hand, DNA sequencing by using 454 pyrosequencing is so cost effective that the promise of $1,000 per bacterial genome sequence is becoming a reality. Pyrosequencing technology is a simple to use technique that can produce accurate and quantitative analysis of DNA sequences with a great speed. The deposition of massive amounts of bacterial genomic information in databanks is creating fingerprint phylogenetic analysis that will ultimately replace several technologies such as Pulsed Field Gel Electrophoresis. In this chapter, we will review (1) the use of DNA microarray using fluorescence and infrared imaging detection for identification of pathogenic bacteria, and (2) use of pyrosequencing in DNA cluster analysis to fingerprint bacterial phylogenetic trees.

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

PubMed

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

2008-08-04

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

Implementation of Quality Management in Core Service Laboratories

PubMed Central

Creavalle, T.; Haque, K.; Raley, C.; Subleski, M.; Smith, M.W.; Hicks, B.

2010-01-01

CF-28 The Genetics and Genomics group of the Advanced Technology Program of SAIC-Frederick exists to bring innovative genomic expertise, tools and analysis to NCI and the scientific community. The Sequencing Facility (SF) provides next generation short read (Illumina) sequencing capacity to investigators using a streamlined production approach. The Laboratory of Molecular Technology (LMT) offers a wide range of genomics core services including microarray expression analysis, miRNA analysis, array comparative genome hybridization, long read (Roche) next generation sequencing, quantitative real time PCR, transgenic genotyping, Sanger sequencing, and clinical mutation detection services to investigators from across the NIH. As the technology supporting this genomic research becomes more complex, the need for basic quality processes within all aspects of the core service groups becomes critical. The Quality Management group works alongside members of these labs to establish or improve processes supporting operations control (equipment, reagent and materials management), process improvement (reengineering/optimization, automation, acceptance criteria for new technologies and tech transfer), and quality assurance and customer support (controlled documentation/SOPs, training, service deficiencies and continual improvement efforts). Implementation and expansion of quality programs within unregulated environments demonstrates SAIC-Frederick's dedication to providing the highest quality products and services to the NIH community.

[Clinical value of genome-wide high resolution chromosomal microarray analysis in etiological study of fetuses with congenital heart defects].

PubMed

Wu, Xiaoli; Fu, Fang; Li, Ru; Pan, Min; Han, Jin; Zhen, Li; Yang, Xin; Zhang, Yongling; Li, Fatao; Liao, Can

2014-12-01

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. 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. (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 rates for isolated CHD and CHD with extra-cardiac structural abnormalities were 13% (9/68) and 25% (5/20), respectively (P > 0.05). The pCNV detection rates for simple and complicated CHD were 17% (10/58) and 13% (4/30), respectively (P > 0.05). (3) Eighteen fetuses (10.2%, 18/176) had abnormal karyotype results. (4) CMA test was performed in 88 fetuses. CNV detected in 8 fetuses were classified as VOUS initially. After parental microarray analysis, CNV in 5 fetuses were inherited and interpreted as benign. CNV in the other 3 fetuses (3%, 3/88) were remained unknown significance. CNV in 14 fetuses (16% ) were interpreted as pCNV. In fetuses with CHD and normal karyotype, the application of CMA could increase the detection rate of pCNV. Genome-wide CMA could be used as a regular tool in the prenatal diagnosis of fetuses with CHD and normal karyotype. This technology may benefit evaluation of fetal prognosis in prenatal genetic counselling.

Genome-Wide Identification, Evolutionary Expansion, and Expression Profile of Homeodomain-Leucine Zipper Gene Family in Poplar (Populus trichocarpa)

PubMed Central

Hu, Ruibo; Chi, Xiaoyuan; Chai, Guohua; Kong, Yingzhen; He, Guo; Wang, Xiaoyu; Shi, Dachuan; Zhang, Dongyuan; Zhou, Gongke

2012-01-01

Background Homeodomain-leucine zipper (HD-ZIP) proteins are plant-specific transcriptional factors known to play crucial roles in plant development. Although sequence phylogeny analysis of Populus HD-ZIPs was carried out in a previous study, no systematic analysis incorporating genome organization, gene structure, and expression compendium has been conducted in model tree species Populus thus far. Principal Findings In this study, a comprehensive analysis of Populus HD-ZIP gene family was performed. Sixty-three full-length HD-ZIP genes were found in Populus genome. These Populus HD-ZIP genes were phylogenetically clustered into four distinct subfamilies (HD-ZIP I–IV) and predominately distributed across 17 linkage groups (LG). Fifty genes from 25 Populus paralogous pairs were located in the duplicated blocks of Populus genome and then preferentially retained during the sequential evolutionary courses. Genomic organization analyses indicated that purifying selection has played a pivotal role in the retention and maintenance of Populus HD-ZIP gene family. Microarray analysis has shown that 21 Populus paralogous pairs have been differentially expressed across different tissues and under various stresses, with five paralogous pairs showing nearly identical expression patterns, 13 paralogous pairs being partially redundant and three paralogous pairs diversifying significantly. Quantitative real-time RT-PCR (qRT-PCR) analysis performed on 16 selected Populus HD-ZIP genes in different tissues and under both drought and salinity stresses confirms their tissue-specific and stress-inducible expression patterns. Conclusions Genomic organizations indicated that segmental duplications contributed significantly to the expansion of Populus HD-ZIP gene family. Exon/intron organization and conserved motif composition of Populus HD-ZIPs are highly conservative in the same subfamily, suggesting the members in the same subfamilies may also have conservative functionalities. Microarray and qRT-PCR analyses showed that 89% (56 out of 63) of Populus HD-ZIPs were duplicate genes that might have been retained by substantial subfunctionalization. Taken together, these observations may lay the foundation for future functional analysis of Populus HD-ZIP genes to unravel their biological roles. PMID:22359569

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

PubMed

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.

Autonomous system for Web-based microarray image analysis.

PubMed

Bozinov, Daniel

2003-12-01

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

eXframe: reusable framework for storage, analysis and visualization of genomics experiments

PubMed Central

2011-01-01

Background Genome-wide experiments are routinely conducted to measure gene expression, DNA-protein interactions and epigenetic status. Structured metadata for these experiments is imperative for a complete understanding of experimental conditions, to enable consistent data processing and to allow retrieval, comparison, and integration of experimental results. Even though several repositories have been developed for genomics data, only a few provide annotation of samples and assays using controlled vocabularies. Moreover, many of them are tailored for a single type of technology or measurement and do not support the integration of multiple data types. Results We have developed eXframe - a reusable web-based framework for genomics experiments that provides 1) the ability to publish structured data compliant with accepted standards 2) support for multiple data types including microarrays and next generation sequencing 3) query, analysis and visualization integration tools (enabled by consistent processing of the raw data and annotation of samples) and is available as open-source software. We present two case studies where this software is currently being used to build repositories of genomics experiments - one contains data from hematopoietic stem cells and another from Parkinson's disease patients. Conclusion The web-based framework eXframe offers structured annotation of experiments as well as uniform processing and storage of molecular data from microarray and next generation sequencing platforms. The framework allows users to query and integrate information across species, technologies, measurement types and experimental conditions. Our framework is reusable and freely modifiable - other groups or institutions can deploy their own custom web-based repositories based on this software. It is interoperable with the most important data formats in this domain. We hope that other groups will not only use eXframe, but also contribute their own useful modifications. PMID:22103807

Genomic and protein expression profiling identifies CDK6 as novel independent prognostic marker in medulloblastoma.

PubMed

Mendrzyk, Frank; Radlwimmer, Bernhard; Joos, Stefan; Kokocinski, Felix; Benner, Axel; Stange, Daniel E; Neben, Kai; Fiegler, Heike; Carter, Nigel P; Reifenberger, Guido; Korshunov, Andrey; Lichter, Peter

2005-12-01

Medulloblastoma is the most common malignant brain tumor in children. Despite multimodal aggressive treatment, nearly half of the patients die as a result of this tumor. Identification of molecular markers for prognosis and development of novel pathogenesis-based therapies depends crucially on a better understanding of medulloblastoma pathomechanisms. We performed genome-wide analysis of DNA copy number imbalances in 47 medulloblastomas using comparative genomic hybridization to large insert DNA microarrays (matrix-CGH). The expression of selected candidate genes identified by matrix-CGH was analyzed immunohistochemically on tissue microarrays representing medulloblastomas from 189 clinically well-documented patients. To identify novel prognostic markers, genomic findings and protein expression data were correlated to patient survival. Matrix-CGH analysis revealed frequent DNA copy number alterations of several novel candidate regions. Among these, gains at 17q23.2-qter (P < .01) and losses at 17p13.1 to 17p13.3 (P = .04) were significantly correlated to poor prognosis. Within 17q23.2-qter and 7q21.2, two of the most frequently gained chromosomal regions, confined amplicons were identified that contained the PPM1D and CDK6 genes, respectively. Immunohistochemistry revealed strong expression of PPM1D in 148 (88%) of 168 and CDK6 in 50 (30%) of 169 medulloblastomas. Overexpression of CDK6 correlated significantly with poor prognosis (P < .01) and represented an independent prognostic marker of overall survival on multivariate analysis (P = .02). We identified CDK6 as a novel molecular marker that can be determined by immunohistochemistry on routinely processed tissue specimens and may facilitate the prognostic assessment of medulloblastoma patients. Furthermore, increased protein-levels of PPM1D and CDK6 may link the TP53 and RB1 tumor suppressor pathways to medulloblastoma pathomechanisms.

Revealing impaired pathways in the an11 mutant by high-throughput characterization of Petunia axillaris and Petunia inflata transcriptomes.

PubMed

Zenoni, Sara; D'Agostino, Nunzio; Tornielli, Giovanni B; Quattrocchio, Francesca; Chiusano, Maria L; Koes, Ronald; Zethof, Jan; Guzzo, Flavia; Delledonne, Massimo; Frusciante, Luigi; Gerats, Tom; Pezzotti, Mario

2011-10-01

Petunia is an excellent model system, especially for genetic, physiological and molecular studies. Thus far, however, genome-wide expression analysis has been applied rarely because of the lack of sequence information. We applied next-generation sequencing to generate, through de novo read assembly, a large catalogue of transcripts for Petunia axillaris and Petunia inflata. On the basis of both transcriptomes, comprehensive microarray chips for gene expression analysis were established and used for the analysis of global- and organ-specific gene expression in Petunia axillaris and Petunia inflata and to explore the molecular basis of the seed coat defects in a Petunia hybrida mutant, anthocyanin 11 (an11), lacking a WD40-repeat (WDR) transcription regulator. Among the transcripts differentially expressed in an11 seeds compared with wild type, many expected targets of AN11 were found but also several interesting new candidates that might play a role in morphogenesis of the seed coat. Our results validate the combination of next-generation sequencing with microarray analyses strategies to identify the transcriptome of two petunia species without previous knowledge of their genome, and to develop comprehensive chips as useful tools for the analysis of gene expression in P. axillaris, P. inflata and P. hybrida. © 2011 The Authors. The Plant Journal © 2011 Blackwell Publishing Ltd.

Genome-wide polymorphisms and development of a microarray platform to detect genetic variations in Plasmodium yoelii.

PubMed

Nair, Sethu C; Pattaradilokrat, Sittiporn; Zilversmit, Martine M; Dommer, Jennifer; Nagarajan, Vijayaraj; Stephens, Melissa T; Xiao, Wenming; Tan, John C; Su, Xin-Zhuan

2014-01-01

The rodent malaria parasite Plasmodium yoelii is an important model for studying malaria immunity and pathogenesis. One approach for studying malaria disease phenotypes is genetic mapping, which requires typing a large number of genetic markers from multiple parasite strains and/or progeny from genetic crosses. Hundreds of microsatellite (MS) markers have been developed to genotype the P. yoelii genome; however, typing a large number of MS markers can be labor intensive, time consuming, and expensive. Thus, development of high-throughput genotyping tools such as DNA microarrays that enable rapid and accurate large-scale genotyping of the malaria parasite will be highly desirable. In this study, we sequenced the genomes of two P. yoelii strains (33X and N67) and obtained a large number of single nucleotide polymorphisms (SNPs). Based on the SNPs obtained, we designed sets of oligonucleotide probes to develop a microarray that could interrogate ∼11,000 SNPs across the 14 chromosomes of the parasite in a single hybridization. Results from hybridizations of DNA samples of five P. yoelii strains or cloned lines (17XNL, YM, 33X, N67 and N67C) and two progeny from a genetic cross (N67×17XNL) to the microarray showed that the array had a high call rate (∼97%) and accuracy (99.9%) in calling SNPs, providing a simple and reliable tool for typing the P. yoelii genome. Our data show that the P. yoelii genome is highly polymorphic, although isogenic pairs of parasites were also detected. Additionally, our results indicate that the 33X parasite is a progeny of 17XNL (or YM) and an unknown parasite. The highly accurate and reliable microarray developed in this study will greatly facilitate our ability to study the genetic basis of important traits and the disease it causes. Published by Elsevier B.V.

Importing MAGE-ML format microarray data into BioConductor.

PubMed

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

2004-12-12

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

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

PubMed

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.

Differential gene expression related to Nora virus infection of Drosophila melanogaster.

PubMed

Cordes, Ethan J; Licking-Murray, Kellie D; Carlson, Kimberly A

2013-08-01

Nora virus is a recently discovered RNA picorna-like virus that produces a persistent infection in Drosophila melanogaster, but the antiviral pathway or change in gene expression is unknown. We performed cDNA microarray analysis comparing the gene expression profiles of Nora virus infected and uninfected wild-type D. melanogaster. This analysis yielded 58 genes exhibiting a 1.5-fold change or greater and p-value less than 0.01. Of these genes, 46 were up-regulated and 12 down-regulated in response to infection. To validate the microarray results, qRT-PCR was performed with probes for Chorion protein 16 and Troponin C isoform 4, which show good correspondence with cDNA microarray results. Differential regulation of genes associated with Toll and immune-deficient pathways, cytoskeletal development, Janus Kinase-Signal Transducer and Activator of Transcription interactions, and a potential gut-specific innate immune response were found. This genome-wide expression profile of Nora virus infection of D. melanogaster can pinpoint genes of interest for further investigation of antiviral pathways employed, genetic mechanisms, sites of replication, viral persistence, and developmental effects. Copyright © 2013. Published by Elsevier B.V.

A genome-wide expression profile of salt-responsive genes in the apple rootstock Malus zumi.

PubMed

Li, Qingtian; Liu, Jia; Tan, Dunxian; Allan, Andrew C; Jiang, Yuzhuang; Xu, Xuefeng; Han, Zhenhai; Kong, Jin

2013-10-18

In some areas of cultivation, a lack of salt tolerance severely affects plant productivity. Apple, Malus x domestica Borkh., is sensitive to salt, and, as a perennial woody plant the mechanism of salt stress adaption will be different from that of annual herbal model plants, such as Arabidopsis. Malus zumi is a salt tolerant apple rootstock, which survives high salinity (up to 0.6% NaCl). To examine the mechanism underlying this tolerance, a genome-wide expression analysis was performed, using a cDNA library constructed from salt-treated seedlings of Malus zumi. A total of 15,000 cDNA clones were selected for microarray analysis. In total a group of 576 cDNAs, of which expression changed more than four-fold, were sequenced and 18 genes were selected to verify their expression pattern under salt stress by semi-quantitative RT-PCR. Our genome-wide expression analysis resulted in the isolation of 50 novel Malus genes and the elucidation of a new apple-specific mechanism of salt tolerance, including the stabilization of photosynthesis under stress, involvement of phenolic compounds, and sorbitol in ROS scavenging and osmoprotection. The promoter regions of 111 genes were analyzed by PlantCARE, suggesting an intensive cross-talking of abiotic stress in Malus zumi. An interaction network of salt responsive genes was constructed and molecular regulatory pathways of apple were deduced. Our research will contribute to gene function analysis and further the understanding of salt-tolerance mechanisms in fruit trees.

A Genome-Wide Expression Profile of Salt-Responsive Genes in the Apple Rootstock Malus zumi

PubMed Central

Li, Qingtian; Liu, Jia; Tan, Dunxian; Allan, Andrew C.; Jiang, Yuzhuang; Xu, Xuefeng; Han, Zhenhai; Kong, Jin

2013-01-01

In some areas of cultivation, a lack of salt tolerance severely affects plant productivity. Apple, Malus x domestica Borkh., is sensitive to salt, and, as a perennial woody plant the mechanism of salt stress adaption will be different from that of annual herbal model plants, such as Arabidopsis. Malus zumi is a salt tolerant apple rootstock, which survives high salinity (up to 0.6% NaCl). To examine the mechanism underlying this tolerance, a genome-wide expression analysis was performed, using a cDNA library constructed from salt-treated seedlings of Malus zumi. A total of 15,000 cDNA clones were selected for microarray analysis. In total a group of 576 cDNAs, of which expression changed more than four-fold, were sequenced and 18 genes were selected to verify their expression pattern under salt stress by semi-quantitative RT-PCR. Our genome-wide expression analysis resulted in the isolation of 50 novel Malus genes and the elucidation of a new apple-specific mechanism of salt tolerance, including the stabilization of photosynthesis under stress, involvement of phenolic compounds, and sorbitol in ROS scavenging and osmoprotection. The promoter regions of 111 genes were analyzed by PlantCARE, suggesting an intensive cross-talking of abiotic stress in Malus zumi. An interaction network of salt responsive genes was constructed and molecular regulatory pathways of apple were deduced. Our research will contribute to gene function analysis and further the understanding of salt-tolerance mechanisms in fruit trees. PMID:24145753

The Innate Immune Database (IIDB)

PubMed Central

Korb, Martin; Rust, Aistair G; Thorsson, Vesteinn; Battail, Christophe; Li, Bin; Hwang, Daehee; Kennedy, Kathleen A; Roach, Jared C; Rosenberger, Carrie M; Gilchrist, Mark; Zak, Daniel; Johnson, Carrie; Marzolf, Bruz; Aderem, Alan; Shmulevich, Ilya; Bolouri, Hamid

2008-01-01

Background As part of a National Institute of Allergy and Infectious Diseases funded collaborative project, we have performed over 150 microarray experiments measuring the response of C57/BL6 mouse bone marrow macrophages to toll-like receptor stimuli. These microarray expression profiles are available freely from our project web site . Here, we report the development of a database of computationally predicted transcription factor binding sites and related genomic features for a set of over 2000 murine immune genes of interest. Our database, which includes microarray co-expression clusters and a host of web-based query, analysis and visualization facilities, is available freely via the internet. It provides a broad resource to the research community, and a stepping stone towards the delineation of the network of transcriptional regulatory interactions underlying the integrated response of macrophages to pathogens. Description We constructed a database indexed on genes and annotations of the immediate surrounding genomic regions. To facilitate both gene-specific and systems biology oriented research, our database provides the means to analyze individual genes or an entire genomic locus. Although our focus to-date has been on mammalian toll-like receptor signaling pathways, our database structure is not limited to this subject, and is intended to be broadly applicable to immunology. By focusing on selected immune-active genes, we were able to perform computationally intensive expression and sequence analyses that would currently be prohibitive if applied to the entire genome. Using six complementary computational algorithms and methodologies, we identified transcription factor binding sites based on the Position Weight Matrices available in TRANSFAC. For one example transcription factor (ATF3) for which experimental data is available, over 50% of our predicted binding sites coincide with genome-wide chromatin immnuopreciptation (ChIP-chip) results. Our database can be interrogated via a web interface. Genomic annotations and binding site predictions can be automatically viewed with a customized version of the Argo genome browser. Conclusion We present the Innate Immune Database (IIDB) as a community resource for immunologists interested in gene regulatory systems underlying innate responses to pathogens. The database website can be freely accessed at . PMID:18321385

PageMan: an interactive ontology tool to generate, display, and annotate overview graphs for profiling experiments.

PubMed

Usadel, Björn; Nagel, Axel; Steinhauser, Dirk; Gibon, Yves; Bläsing, Oliver E; Redestig, Henning; Sreenivasulu, Nese; Krall, Leonard; Hannah, Matthew A; Poree, Fabien; Fernie, Alisdair R; Stitt, Mark

2006-12-18

Microarray technology has become a widely accepted and standardized tool in biology. The first microarray data analysis programs were developed to support pair-wise comparison. However, as microarray experiments have become more routine, large scale experiments have become more common, which investigate multiple time points or sets of mutants or transgenics. To extract biological information from such high-throughput expression data, it is necessary to develop efficient analytical platforms, which combine manually curated gene ontologies with efficient visualization and navigation tools. Currently, most tools focus on a few limited biological aspects, rather than offering a holistic, integrated analysis. Here we introduce PageMan, a multiplatform, user-friendly, and stand-alone software tool that annotates, investigates, and condenses high-throughput microarray data in the context of functional ontologies. It includes a GUI tool to transform different ontologies into a suitable format, enabling the user to compare and choose between different ontologies. It is equipped with several statistical modules for data analysis, including over-representation analysis and Wilcoxon statistical testing. Results are exported in a graphical format for direct use, or for further editing in graphics programs.PageMan provides a fast overview of single treatments, allows genome-level responses to be compared across several microarray experiments covering, for example, stress responses at multiple time points. This aids in searching for trait-specific changes in pathways using mutants or transgenics, analyzing development time-courses, and comparison between species. In a case study, we analyze the results of publicly available microarrays of multiple cold stress experiments using PageMan, and compare the results to a previously published meta-analysis.PageMan offers a complete user's guide, a web-based over-representation analysis as well as a tutorial, and is freely available at http://mapman.mpimp-golm.mpg.de/pageman/. PageMan allows multiple microarray experiments to be efficiently condensed into a single page graphical display. The flexible interface allows data to be quickly and easily visualized, facilitating comparisons within experiments and to published experiments, thus enabling researchers to gain a rapid overview of the biological responses in the experiments.

Genome-wide increase in histone H2A ubiquitylation in a mouse model of Huntington's disease.

PubMed

McFarland, Karen N; Das, Sudeshna; Sun, Ting Ting; Leyfer, Dmitri; Kim, Mee-Ohk; Xia, Eva; Sangrey, Gavin R; Kuhn, Alexandre; Luthi-Carter, Ruth; Clark, Timothy W; Sadri-Vakili, Ghazaleh; Cha, Jang-Ho J

2013-01-01

Huntington's disease (HD) is a neurodegenerative disorder with selective vulnerability of striatal neurons and involves extensive transcriptional dysregulation early in the disease process. Previous work in cell and mouse models has shown that histone modifications are altered in HD. Specifically, monoubiquitylated histone H2A (uH2A) is present at the promoters of downregulated genes which led to the hypothesis that uH2A plays a role in transcriptional silencing in HD. To broaden our view of uH2A function in transcription in HD, we examined genome-wide binding sites of uH2A in 12-week old striatal tissue from R6/2 transgenic HD mouse model. We used chromatin immunoprecipitation followed by genomic promoter microarray hybridization (ChIP-chip) and then interrogated how these binding sites correlate with transcribed genes. Our analysis reveals that, while uH2A levels are globally increased at the genome in the transgenic (TG) striatum, uH2A localization at a gene did not strongly correlate with the absence of its transcript. Furthermore, analysis of differential ubiquitylation in wild-type (WT) and TG striata did not reveal the expected enrichment of uH2A at genes with decreased expression in the TG striatum. This first description of genome-wide localization of uH2A in an HD model reveals that monoubiquitylation of histone H2A may not function at the level of the individual gene but may rather influence transcription through global chromatin structure.

Genome-Wide Identification and Expression Analysis of WRKY Transcription Factors under Multiple Stresses in Brassica napus

PubMed Central

He, Yajun; Mao, Shaoshuai; Gao, Yulong; Zhu, Liying; Wu, Daoming; Cui, Yixin; Li, Jiana; Qian, Wei

2016-01-01

WRKY transcription factors play important roles in responses to environmental stress stimuli. Using a genome-wide domain analysis, we identified 287 WRKY genes with 343 WRKY domains in the sequenced genome of Brassica napus, 139 in the A sub-genome and 148 in the C sub-genome. These genes were classified into eight groups based on phylogenetic analysis. In the 343 WRKY domains, a total of 26 members showed divergence in the WRKY domain, and 21 belonged to group I. This finding suggested that WRKY genes in group I are more active and variable compared with genes in other groups. Using genome-wide identification and analysis of the WRKY gene family in Brassica napus, we observed genome duplication, chromosomal/segmental duplications and tandem duplication. All of these duplications contributed to the expansion of the WRKY gene family. The duplicate segments that were detected indicated that genome duplication events occurred in the two diploid progenitors B. rapa and B. olearecea before they combined to form B. napus. Analysis of the public microarray database and EST database for B. napus indicated that 74 WRKY genes were induced or preferentially expressed under stress conditions. According to the public QTL data, we identified 77 WRKY genes in 31 QTL regions related to various stress tolerance. We further evaluated the expression of 26 BnaWRKY genes under multiple stresses by qRT-PCR. Most of the genes were induced by low temperature, salinity and drought stress, indicating that the WRKYs play important roles in B. napus stress responses. Further, three BnaWRKY genes were strongly responsive to the three multiple stresses simultaneously, which suggests that these 3 WRKY may have multi-functional roles in stress tolerance and can potentially be used in breeding new rapeseed cultivars. We also found six tandem repeat pairs exhibiting similar expression profiles under the various stress conditions, and three pairs were mapped in the stress related QTL regions, indicating tandem duplicate WRKYs in the adaptive responses to environmental stimuli during the evolution process. Our results provide a framework for future studies regarding the function of WRKY genes in response to stress in B. napus. PMID:27322342

Genome-Wide Identification and Expression Analysis of WRKY Transcription Factors under Multiple Stresses in Brassica napus.

PubMed

He, Yajun; Mao, Shaoshuai; Gao, Yulong; Zhu, Liying; Wu, Daoming; Cui, Yixin; Li, Jiana; Qian, Wei

2016-01-01

WRKY transcription factors play important roles in responses to environmental stress stimuli. Using a genome-wide domain analysis, we identified 287 WRKY genes with 343 WRKY domains in the sequenced genome of Brassica napus, 139 in the A sub-genome and 148 in the C sub-genome. These genes were classified into eight groups based on phylogenetic analysis. In the 343 WRKY domains, a total of 26 members showed divergence in the WRKY domain, and 21 belonged to group I. This finding suggested that WRKY genes in group I are more active and variable compared with genes in other groups. Using genome-wide identification and analysis of the WRKY gene family in Brassica napus, we observed genome duplication, chromosomal/segmental duplications and tandem duplication. All of these duplications contributed to the expansion of the WRKY gene family. The duplicate segments that were detected indicated that genome duplication events occurred in the two diploid progenitors B. rapa and B. olearecea before they combined to form B. napus. Analysis of the public microarray database and EST database for B. napus indicated that 74 WRKY genes were induced or preferentially expressed under stress conditions. According to the public QTL data, we identified 77 WRKY genes in 31 QTL regions related to various stress tolerance. We further evaluated the expression of 26 BnaWRKY genes under multiple stresses by qRT-PCR. Most of the genes were induced by low temperature, salinity and drought stress, indicating that the WRKYs play important roles in B. napus stress responses. Further, three BnaWRKY genes were strongly responsive to the three multiple stresses simultaneously, which suggests that these 3 WRKY may have multi-functional roles in stress tolerance and can potentially be used in breeding new rapeseed cultivars. We also found six tandem repeat pairs exhibiting similar expression profiles under the various stress conditions, and three pairs were mapped in the stress related QTL regions, indicating tandem duplicate WRKYs in the adaptive responses to environmental stimuli during the evolution process. Our results provide a framework for future studies regarding the function of WRKY genes in response to stress in B. napus.

SNP discovery and genotyping using Genotyping-by-Sequencing in Pekin ducks.

PubMed

Zhu, Feng; Cui, Qian-Qian; Hou, Zhuo-Cheng

2016-11-15

Genomic selection and genome-wide association studies need thousands to millions of SNPs. However, many non-model species do not have reference chips for detecting variation. Our goal was to develop and validate an inexpensive but effective method for detecting SNP variation. Genotyping by sequencing (GBS) can be a highly efficient strategy for genome-wide SNP detection, as an alternative to microarray chips. Here, we developed a GBS protocol for ducks and tested it to genotype 49 Pekin ducks. A total of 169,209 SNPs were identified from all animals, with a mean of 55,920 SNPs per individual. The average SNP density reached 1156 SNPs/MB. In this study, the first application of GBS to ducks, we demonstrate the power and simplicity of this method. GBS can be used for genetic studies in to provide an effective method for genome-wide SNP discovery.

Gene expression profiles in Parkinson disease prefrontal cortex implicate FOXO1 and genes under its transcriptional regulation.

PubMed

Dumitriu, Alexandra; Latourelle, Jeanne C; Hadzi, Tiffany C; Pankratz, Nathan; Garza, Dan; Miller, John P; Vance, Jeffery M; Foroud, Tatiana; Beach, Thomas G; Myers, Richard H

2012-06-01

Parkinson disease (PD) is a complex neurodegenerative disorder with largely unknown genetic mechanisms. While the degeneration of dopaminergic neurons in PD mainly takes place in the substantia nigra pars compacta (SN) region, other brain areas, including the prefrontal cortex, develop Lewy bodies, the neuropathological hallmark of PD. We generated and analyzed expression data from the prefrontal cortex Brodmann Area 9 (BA9) of 27 PD and 26 control samples using the 44K One-Color Agilent 60-mer Whole Human Genome Microarray. All samples were male, without significant Alzheimer disease pathology and with extensive pathological annotation available. 507 of the 39,122 analyzed expression probes were different between PD and control samples at false discovery rate (FDR) of 5%. One of the genes with significantly increased expression in PD was the forkhead box O1 (FOXO1) transcription factor. Notably, genes carrying the FoxO1 binding site were significantly enriched in the FDR-significant group of genes (177 genes covered by 189 probes), suggesting a role for FoxO1 upstream of the observed expression changes. Single-nucleotide polymorphisms (SNPs) selected from a recent meta-analysis of PD genome-wide association studies (GWAS) were successfully genotyped in 50 out of the 53 microarray brains, allowing a targeted expression-SNP (eSNP) analysis for 52 SNPs associated with PD affection at genome-wide significance and the 189 probes from FoxO1 regulated genes. A significant association was observed between a SNP in the cyclin G associated kinase (GAK) gene and a probe in the spermine oxidase (SMOX) gene. Further examination of the FOXO1 region in a meta-analysis of six available GWAS showed two SNPs significantly associated with age at onset of PD. These results implicate FOXO1 as a PD-relevant gene and warrant further functional analyses of its transcriptional regulatory mechanisms.

Gene Expression Profiles in Parkinson Disease Prefrontal Cortex Implicate FOXO1 and Genes under Its Transcriptional Regulation

PubMed Central

Dumitriu, Alexandra; Latourelle, Jeanne C.; Hadzi, Tiffany C.; Pankratz, Nathan; Garza, Dan; Miller, John P.; Vance, Jeffery M.; Foroud, Tatiana; Beach, Thomas G.; Myers, Richard H.

2012-01-01

Parkinson disease (PD) is a complex neurodegenerative disorder with largely unknown genetic mechanisms. While the degeneration of dopaminergic neurons in PD mainly takes place in the substantia nigra pars compacta (SN) region, other brain areas, including the prefrontal cortex, develop Lewy bodies, the neuropathological hallmark of PD. We generated and analyzed expression data from the prefrontal cortex Brodmann Area 9 (BA9) of 27 PD and 26 control samples using the 44K One-Color Agilent 60-mer Whole Human Genome Microarray. All samples were male, without significant Alzheimer disease pathology and with extensive pathological annotation available. 507 of the 39,122 analyzed expression probes were different between PD and control samples at false discovery rate (FDR) of 5%. One of the genes with significantly increased expression in PD was the forkhead box O1 (FOXO1) transcription factor. Notably, genes carrying the FoxO1 binding site were significantly enriched in the FDR–significant group of genes (177 genes covered by 189 probes), suggesting a role for FoxO1 upstream of the observed expression changes. Single-nucleotide polymorphisms (SNPs) selected from a recent meta-analysis of PD genome-wide association studies (GWAS) were successfully genotyped in 50 out of the 53 microarray brains, allowing a targeted expression–SNP (eSNP) analysis for 52 SNPs associated with PD affection at genome-wide significance and the 189 probes from FoxO1 regulated genes. A significant association was observed between a SNP in the cyclin G associated kinase (GAK) gene and a probe in the spermine oxidase (SMOX) gene. Further examination of the FOXO1 region in a meta-analysis of six available GWAS showed two SNPs significantly associated with age at onset of PD. These results implicate FOXO1 as a PD–relevant gene and warrant further functional analyses of its transcriptional regulatory mechanisms. PMID:22761592

MMASS: an optimized array-based method for assessing CpG island methylation.

PubMed

Ibrahim, Ashraf E K; Thorne, Natalie P; Baird, Katie; Barbosa-Morais, Nuno L; Tavaré, Simon; Collins, V Peter; Wyllie, Andrew H; Arends, Mark J; Brenton, James D

2006-01-01

We describe an optimized microarray method for identifying genome-wide CpG island methylation called microarray-based methylation assessment of single samples (MMASS) which directly compares methylated to unmethylated sequences within a single sample. To improve previous methods we used bioinformatic analysis to predict an optimized combination of methylation-sensitive enzymes that had the highest utility for CpG-island probes and different methods to produce unmethylated representations of test DNA for more sensitive detection of differential methylation by hybridization. Subtraction or methylation-dependent digestion with McrBC was used with optimized (MMASS-v2) or previously described (MMASS-v1, MMASS-sub) methylation-sensitive enzyme combinations and compared with a published McrBC method. Comparison was performed using DNA from the cell line HCT116. We show that the distribution of methylation microarray data is inherently skewed and requires exogenous spiked controls for normalization and that analysis of digestion of methylated and unmethylated control sequences together with linear fit models of replicate data showed superior statistical power for the MMASS-v2 method. Comparison with previous methylation data for HCT116 and validation of CpG islands from PXMP4, SFRP2, DCC, RARB and TSEN2 confirmed the accuracy of MMASS-v2 results. The MMASS-v2 method offers improved sensitivity and statistical power for high-throughput microarray identification of differential methylation.

Application of Whole Genome Expression Analysis to Assess Bacterial Responses to Environmental Conditions

NASA Astrophysics Data System (ADS)

Vukanti, R. V.; Mintz, E. M.; Leff, L. G.

2005-05-01

Bacterial responses to environmental signals are multifactorial and are coupled to changes in gene expression. An understanding of bacterial responses to environmental conditions is possible using microarray expression analysis. In this study, the utility of microarrays for examining changes in gene expression in Escherichia coli under different environmental conditions was assessed. RNA was isolated, hybridized to Affymetrix E. coli Genome 2.0 chips and analyzed using Affymetrix GCOS and Genespring software. Major limiting factors were obtaining enough quality RNA (107-108 cells to get 10μg RNA)and accounting for differences in growth rates under different conditions. Stabilization of RNA prior to isolation and taking extreme precautions while handling RNA were crucial. In addition, use of this method in ecological studies is limited by availability and cost of commercial arrays; choice of primers for cDNA synthesis, reproducibility, complexity of results generated and need to validate findings. This method may be more widely applicable with the development of better approaches for RNA recovery from environmental samples and increased number of available strain-specific arrays. Diligent experimental design and verification of results with real-time PCR or northern blots is needed. Overall, there is a great potential for use of this technology to discover mechanisms underlying organisms' responses to environmental conditions.

Profiling protein function with small molecule microarrays

PubMed Central

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

2002-01-01

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

Evaluation of high throughput gene expression platforms using a genomic biomarker signature for prediction of skin sensitization.

PubMed

Forreryd, Andy; Johansson, Henrik; Albrekt, Ann-Sofie; Lindstedt, Malin

2014-05-16

Allergic contact dermatitis (ACD) develops upon exposure to certain chemical compounds termed skin sensitizers. To reduce the occurrence of skin sensitizers, chemicals are regularly screened for their capacity to induce sensitization. The recently developed Genomic Allergen Rapid Detection (GARD) assay is an in vitro alternative to animal testing for identification of skin sensitizers, classifying chemicals by evaluating transcriptional levels of a genomic biomarker signature. During assay development and biomarker identification, genome-wide expression analysis was applied using microarrays covering approximately 30,000 transcripts. However, the microarray platform suffers from drawbacks in terms of low sample throughput, high cost per sample and time consuming protocols and is a limiting factor for adaption of GARD into a routine assay for screening of potential sensitizers. With the purpose to simplify assay procedures, improve technical parameters and increase sample throughput, we assessed the performance of three high throughput gene expression platforms--nCounter®, BioMark HD™ and OpenArray®--and correlated their performance metrics against our previously generated microarray data. We measured the levels of 30 transcripts from the GARD biomarker signature across 48 samples. Detection sensitivity, reproducibility, correlations and overall structure of gene expression measurements were compared across platforms. Gene expression data from all of the evaluated platforms could be used to classify most of the sensitizers from non-sensitizers in the GARD assay. Results also showed high data quality and acceptable reproducibility for all platforms but only medium to poor correlations of expression measurements across platforms. In addition, evaluated platforms were superior to the microarray platform in terms of cost efficiency, simplicity of protocols and sample throughput. We evaluated the performance of three non-array based platforms using a limited set of transcripts from the GARD biomarker signature. We demonstrated that it was possible to achieve acceptable discriminatory power in terms of separation between sensitizers and non-sensitizers in the GARD assay while reducing assay costs, simplify assay procedures and increase sample throughput by using an alternative platform, providing a first step towards the goal to prepare GARD for formal validation and adaption of the assay for industrial screening of potential sensitizers.

Identification and characterization of nuclear genes involved in photosynthesis in Populus

PubMed Central

2014-01-01

Background The gap between the real and potential photosynthetic rate under field conditions suggests that photosynthesis could potentially be improved. Nuclear genes provide possible targets for improving photosynthetic efficiency. Hence, genome-wide identification and characterization of the nuclear genes affecting photosynthetic traits in woody plants would provide key insights on genetic regulation of photosynthesis and identify candidate processes for improvement of photosynthesis. Results Using microarray and bulked segregant analysis strategies, we identified differentially expressed nuclear genes for photosynthesis traits in a segregating population of poplar. We identified 515 differentially expressed genes in this population (FC ≥ 2 or FC ≤ 0.5, P < 0.05), 163 up-regulated and 352 down-regulated. Real-time PCR expression analysis confirmed the microarray data. Singular Enrichment Analysis identified 48 significantly enriched GO terms for molecular functions (28), biological processes (18) and cell components (2). Furthermore, we selected six candidate genes for functional examination by a single-marker association approach, which demonstrated that 20 SNPs in five candidate genes significantly associated with photosynthetic traits, and the phenotypic variance explained by each SNP ranged from 2.3% to 12.6%. This revealed that regulation of photosynthesis by the nuclear genome mainly involves transport, metabolism and response to stimulus functions. Conclusions This study provides new genome-scale strategies for the discovery of potential candidate genes affecting photosynthesis in Populus, and for identification of the functions of genes involved in regulation of photosynthesis. This work also suggests that improving photosynthetic efficiency under field conditions will require the consideration of multiple factors, such as stress responses. PMID:24673936

HDBStat!: a platform-independent software suite for statistical analysis of high dimensional biology data.

PubMed

Trivedi, Prinal; Edwards, Jode W; Wang, Jelai; Gadbury, Gary L; Srinivasasainagendra, Vinodh; Zakharkin, Stanislav O; Kim, Kyoungmi; Mehta, Tapan; Brand, Jacob P L; Patki, Amit; Page, Grier P; Allison, David B

2005-04-06

Many efforts in microarray data analysis are focused on providing tools and methods for the qualitative analysis of microarray data. HDBStat! (High-Dimensional Biology-Statistics) is a software package designed for analysis of high dimensional biology data such as microarray data. It was initially developed for the analysis of microarray gene expression data, but it can also be used for some applications in proteomics and other aspects of genomics. HDBStat! provides statisticians and biologists a flexible and easy-to-use interface to analyze complex microarray data using a variety of methods for data preprocessing, quality control analysis and hypothesis testing. Results generated from data preprocessing methods, quality control analysis and hypothesis testing methods are output in the form of Excel CSV tables, graphs and an Html report summarizing data analysis. HDBStat! is a platform-independent software that is freely available to academic institutions and non-profit organizations. It can be downloaded from our website http://www.soph.uab.edu/ssg_content.asp?id=1164.

Equalizer reduces SNP bias in Affymetrix microarrays.

PubMed

Quigley, David

2015-07-30

Gene expression microarrays measure the levels of messenger ribonucleic acid (mRNA) in a sample using probe sequences that hybridize with transcribed regions. These probe sequences are designed using a reference genome for the relevant species. However, most model organisms and all humans have genomes that deviate from their reference. These variations, which include single nucleotide polymorphisms, insertions of additional nucleotides, and nucleotide deletions, can affect the microarray's performance. Genetic experiments comparing individuals bearing different population-associated single nucleotide polymorphisms that intersect microarray probes are therefore subject to systemic bias, as the reduction in binding efficiency due to a technical artifact is confounded with genetic differences between parental strains. This problem has been recognized for some time, and earlier methods of compensation have attempted to identify probes affected by genome variants using statistical models. These methods may require replicate microarray measurement of gene expression in the relevant tissue in inbred parental samples, which are not always available in model organisms and are never available in humans. By using sequence information for the genomes of organisms under investigation, potentially problematic probes can now be identified a priori. However, there is no published software tool that makes it easy to eliminate these probes from an annotation. I present equalizer, a software package that uses genome variant data to modify annotation files for the commonly used Affymetrix IVT and Gene/Exon platforms. These files can be used by any microarray normalization method for subsequent analysis. I demonstrate how use of equalizer on experiments mapping germline influence on gene expression in a genetic cross between two divergent mouse species and in human samples significantly reduces probe hybridization-induced bias, reducing false positive and false negative findings. The equalizer package reduces probe hybridization bias from experiments performed on the Affymetrix microarray platform, allowing accurate assessment of germline influence on gene expression.

BμG@Sbase—a microbial gene expression and comparative genomic database

PubMed Central

Witney, Adam A.; Waldron, Denise E.; Brooks, Lucy A.; Tyler, Richard H.; Withers, Michael; Stoker, Neil G.; Wren, Brendan W.; Butcher, Philip D.; Hinds, Jason

2012-01-01

The reducing cost of high-throughput functional genomic technologies is creating a deluge of high volume, complex data, placing the burden on bioinformatics resources and tool development. The Bacterial Microarray Group at St George's (BμG@S) has been at the forefront of bacterial microarray design and analysis for over a decade and while serving as a hub of a global network of microbial research groups has developed BμG@Sbase, a microbial gene expression and comparative genomic database. BμG@Sbase (http://bugs.sgul.ac.uk/bugsbase/) is a web-browsable, expertly curated, MIAME-compliant database that stores comprehensive experimental annotation and multiple raw and analysed data formats. Consistent annotation is enabled through a structured set of web forms, which guide the user through the process following a set of best practices and controlled vocabulary. The database currently contains 86 expertly curated publicly available data sets (with a further 124 not yet published) and full annotation information for 59 bacterial microarray designs. The data can be browsed and queried using an explorer-like interface; integrating intuitive tree diagrams to present complex experimental details clearly and concisely. Furthermore the modular design of the database will provide a robust platform for integrating other data types beyond microarrays into a more Systems analysis based future. PMID:21948792

BμG@Sbase--a microbial gene expression and comparative genomic database.

PubMed

Witney, Adam A; Waldron, Denise E; Brooks, Lucy A; Tyler, Richard H; Withers, Michael; Stoker, Neil G; Wren, Brendan W; Butcher, Philip D; Hinds, Jason

2012-01-01

The reducing cost of high-throughput functional genomic technologies is creating a deluge of high volume, complex data, placing the burden on bioinformatics resources and tool development. The Bacterial Microarray Group at St George's (BμG@S) has been at the forefront of bacterial microarray design and analysis for over a decade and while serving as a hub of a global network of microbial research groups has developed BμG@Sbase, a microbial gene expression and comparative genomic database. BμG@Sbase (http://bugs.sgul.ac.uk/bugsbase/) is a web-browsable, expertly curated, MIAME-compliant database that stores comprehensive experimental annotation and multiple raw and analysed data formats. Consistent annotation is enabled through a structured set of web forms, which guide the user through the process following a set of best practices and controlled vocabulary. The database currently contains 86 expertly curated publicly available data sets (with a further 124 not yet published) and full annotation information for 59 bacterial microarray designs. The data can be browsed and queried using an explorer-like interface; integrating intuitive tree diagrams to present complex experimental details clearly and concisely. Furthermore the modular design of the database will provide a robust platform for integrating other data types beyond microarrays into a more Systems analysis based future.

Recent molecular genetic studies and methodological issues in suicide research.

PubMed

Tsai, Shih-Jen; Hong, Chen-Jee; Liou, Ying-Jay

2011-06-01

Suicide behavior (SB) spans a spectrum ranging from suicidal ideation to suicide attempts and completed suicide. Strong evidence suggests a genetic susceptibility to SB, including familial heritability and common occurrence in twins. This review addresses recent molecular genetic studies in SB that include case-control association, genome gene-expression microarray, and genome-wide association (GWA). This work also reviews epigenetics in SB and pharmacogenetic studies of antidepressant-induced suicide. SB fulfills criteria for a complex genetic phenotype in which environmental factors interact with multiple genes to influence susceptibility. So far, case-control association approaches are still the mainstream in SB genetic studies, although whole genome gene-expression microarray and GWA studies have begun to emerge in recent years. Genetic association studies have suggested several genes (e.g., serotonin transporter, tryptophan hydroxylase 2, and brain-derived neurotrophic factor) related to SB, but not all reports support these findings. The case-control approach while useful is limited by present knowledge of disease pathophysiology. Genome-wide studies of gene expression and genetic variation are not constrained by our limited knowledge. However, the explanatory power and path to clinical translation of risk estimates for common variants reported in genome-wide association studies remain unclear because of the presence of rare and structural genetic variation. As whole genome sequencing becomes increasingly widespread, available genomic information will no longer be the limiting factor in applying genetics to clinical medicine. These approaches provide exciting new avenues to identify new candidate genes for SB genetic studies. The other limitation of genetic association is the lack of a consistent definition of the SB phenotype among studies, an inconsistency that hampers the comparability of the studies and data pooling. In summary, SB involves multiple genes interacting with non-genetic factors. A better understanding of the SB genes by combining whole genome approaches with case-control association studies, may potentially lead to developing effective screening, prevention, and management of SB. Copyright © 2010 Elsevier Inc. All rights reserved.

Proteomics and transcriptomics of the BABA-induced resistance response in potato using a novel functional annotation approach

PubMed Central

2014-01-01

Background Induced resistance (IR) can be part of a sustainable plant protection strategy against important plant diseases. β-aminobutyric acid (BABA) can induce resistance in a wide range of plants against several types of pathogens, including potato infected with Phytophthora infestans. However, the molecular mechanisms behind this are unclear and seem to be dependent on the system studied. To elucidate the defence responses activated by BABA in potato, a genome-wide transcript microarray analysis in combination with label-free quantitative proteomics analysis of the apoplast secretome were performed two days after treatment of the leaf canopy with BABA at two concentrations, 1 and 10 mM. Results Over 5000 transcripts were differentially expressed and over 90 secretome proteins changed in abundance indicating a massive activation of defence mechanisms with 10 mM BABA, the concentration effective against late blight disease. To aid analysis, we present a more comprehensive functional annotation of the microarray probes and gene models by retrieving information from orthologous gene families across 26 sequenced plant genomes. The new annotation provided GO terms to 8616 previously un-annotated probes. Conclusions BABA at 10 mM affected several processes related to plant hormones and amino acid metabolism. A major accumulation of PR proteins was also evident, and in the mevalonate pathway, genes involved in sterol biosynthesis were down-regulated, whereas several enzymes involved in the sesquiterpene phytoalexin biosynthesis were up-regulated. Interestingly, abscisic acid (ABA) responsive genes were not as clearly regulated by BABA in potato as previously reported in Arabidopsis. Together these findings provide candidates and markers for improved resistance in potato, one of the most important crops in the world. PMID:24773703

RubisCO Gene Clusters Found in a Metagenome Microarray from Acid Mine Drainage

PubMed Central

Guo, Xue; Yin, Huaqun; Cong, Jing; Dai, Zhimin; Liang, Yili

2013-01-01

The enzyme responsible for carbon dioxide fixation in the Calvin cycle, ribulose-1,5-bisphosphate carboxylase/oxygenase (RubisCO), is always detected as a phylogenetic marker to analyze the distribution and activity of autotrophic bacteria. However, such an approach provides no indication as to the significance of genomic content and organization. Horizontal transfers of RubisCO genes occurring in eubacteria and plastids may seriously affect the credibility of this approach. Here, we presented a new method to analyze the diversity and genomic content of RubisCO genes in acid mine drainage (AMD). A metagenome microarray containing 7,776 large-insertion fosmids was constructed to quickly screen genome fragments containing RubisCO form I large-subunit genes (cbbL). Forty-six cbbL-containing fosmids were detected, and six fosmids were fully sequenced. To evaluate the reliability of the metagenome microarray and understand the microbial community in AMD, the diversities of cbbL and the 16S rRNA gene were analyzed. Fosmid sequences revealed that the form I RubisCO gene cluster could be subdivided into form IA and IB RubisCO gene clusters in AMD, because of significant divergences in molecular phylogenetics and conservative genomic organization. Interestingly, the form I RubisCO gene cluster coexisted with the form II RubisCO gene cluster in one fosmid genomic fragment. Phylogenetic analyses revealed that horizontal transfers of RubisCO genes may occur widely in AMD, which makes the evolutionary history of RubisCO difficult to reconcile with organismal phylogeny. PMID:23335778

Genomic profiling of plasma cell disorders in a clinical setting: integration of microarray and FISH, after CD138 selection of bone marrow

PubMed Central

Berry, Nadine Kaye; Bain, Nicole L; Enjeti, Anoop K; Rowlings, Philip

2014-01-01

Aim To evaluate the role of whole genome comparative genomic hybridisation microarray (array-CGH) in detecting genomic imbalances as compared to conventional karyotype (GTG-analysis) or myeloma specific fluorescence in situ hybridisation (FISH) panel in a diagnostic setting for plasma cell dyscrasia (PCD). Methods A myeloma-specific interphase FISH (i-FISH) panel was carried out on CD138 PC-enriched bone marrow (BM) from 20 patients having BM biopsies for evaluation of PCD. Whole genome array-CGH was performed on reference (control) and neoplastic (test patient) genomic DNA extracted from CD138 PC-enriched BM and analysed. Results Comparison of techniques demonstrated a much higher detection rate of genomic imbalances using array-CGH. Genomic imbalances were detected in 1, 19 and 20 patients using GTG-analysis, i-FISH and array-CGH, respectively. Genomic rearrangements were detected in one patient using GTG-analysis and seven patients using i-FISH, while none were detected using array-CGH. I-FISH was the most sensitive method for detecting gene rearrangements and GTG-analysis was the least sensitive method overall. All copy number aberrations observed in GTG-analysis were detected using array-CGH and i-FISH. Conclusions We show that array-CGH performed on CD138-enriched PCs significantly improves the detection of clinically relevant and possibly novel genomic abnormalities in PCD, and thus could be considered as a standard diagnostic technique in combination with IGH rearrangement i-FISH. PMID:23969274

Genomic profiling of plasma cell disorders in a clinical setting: integration of microarray and FISH, after CD138 selection of bone marrow.

PubMed

Berry, Nadine Kaye; Bain, Nicole L; Enjeti, Anoop K; Rowlings, Philip

2014-01-01

To evaluate the role of whole genome comparative genomic hybridisation microarray (array-CGH) in detecting genomic imbalances as compared to conventional karyotype (GTG-analysis) or myeloma specific fluorescence in situ hybridisation (FISH) panel in a diagnostic setting for plasma cell dyscrasia (PCD). A myeloma-specific interphase FISH (i-FISH) panel was carried out on CD138 PC-enriched bone marrow (BM) from 20 patients having BM biopsies for evaluation of PCD. Whole genome array-CGH was performed on reference (control) and neoplastic (test patient) genomic DNA extracted from CD138 PC-enriched BM and analysed. Comparison of techniques demonstrated a much higher detection rate of genomic imbalances using array-CGH. Genomic imbalances were detected in 1, 19 and 20 patients using GTG-analysis, i-FISH and array-CGH, respectively. Genomic rearrangements were detected in one patient using GTG-analysis and seven patients using i-FISH, while none were detected using array-CGH. I-FISH was the most sensitive method for detecting gene rearrangements and GTG-analysis was the least sensitive method overall. All copy number aberrations observed in GTG-analysis were detected using array-CGH and i-FISH. We show that array-CGH performed on CD138-enriched PCs significantly improves the detection of clinically relevant and possibly novel genomic abnormalities in PCD, and thus could be considered as a standard diagnostic technique in combination with IGH rearrangement i-FISH.

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

PubMed Central

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

2009-01-01

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

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

PubMed

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

2018-01-01

Microarrays and RNA-seq are at the forefront of high throughput transcriptome analyses. Since these methodologies are based on different principles, there are concerns about the concordance of data between the two techniques. The concordance of RNA-seq and microarrays for genome-wide analysis of differential gene expression has not been rigorously assessed in clinically derived ligament tissues. To demonstrate the concordance between RNA-seq and microarrays and to assess potential benefits of RNA-seq over microarrays, we assessed differences in transcript expression in anterior cruciate ligament (ACL) tissues based on time-from-injury. ACL remnants were collected from patients with an ACL tear at the time of ACL reconstruction. RNA prepared from torn ACL remnants was subjected to Agilent microarrays (N = 24) and RNA-seq (N = 8). The correlation of biological replicates in RNA-seq and microarrays data was similar (0.98 vs. 0.97), demonstrating that each platform has high internal reproducibility. Correlations between the RNA-seq data and the individual microarrays were low, but correlations between the RNA-seq values and the geometric mean of the microarrays values were moderate. The cross-platform concordance for differentially expressed transcripts or enriched pathways was linearly correlated (r = 0.64). RNA-Seq was superior in detecting low abundance transcripts and differentiating biologically critical isoforms. Additional independent validation of transcript expression was undertaken using microfluidic PCR for selected genes. PCR data showed 100% concordance (in expression pattern) with RNA-seq and microarrays data. These findings demonstrate that RNA-seq has advantages over microarrays for transcriptome profiling of ligament tissues when available and affordable. Furthermore, these findings are likely transferable to other musculoskeletal tissues where tissue collection is challenging and cells are in low abundance. © 2017 Orthopaedic Research Society. Published by Wiley Periodicals, Inc. J Orthop Res 36:484-497, 2018. © 2017 Orthopaedic Research Society. Published by Wiley Periodicals, Inc.

Discovering time-lagged rules from microarray data using gene profile classifiers

PubMed Central

2011-01-01

Background Gene regulatory networks have an essential role in every process of life. In this regard, the amount of genome-wide time series data is becoming increasingly available, providing the opportunity to discover the time-delayed gene regulatory networks that govern the majority of these molecular processes. Results This paper aims at reconstructing gene regulatory networks from multiple genome-wide microarray time series datasets. In this sense, a new model-free algorithm called GRNCOP2 (Gene Regulatory Network inference by Combinatorial OPtimization 2), which is a significant evolution of the GRNCOP algorithm, was developed using combinatorial optimization of gene profile classifiers. The method is capable of inferring potential time-delay relationships with any span of time between genes from various time series datasets given as input. The proposed algorithm was applied to time series data composed of twenty yeast genes that are highly relevant for the cell-cycle study, and the results were compared against several related approaches. The outcomes have shown that GRNCOP2 outperforms the contrasted methods in terms of the proposed metrics, and that the results are consistent with previous biological knowledge. Additionally, a genome-wide study on multiple publicly available time series data was performed. In this case, the experimentation has exhibited the soundness and scalability of the new method which inferred highly-related statistically-significant gene associations. Conclusions A novel method for inferring time-delayed gene regulatory networks from genome-wide time series datasets is proposed in this paper. The method was carefully validated with several publicly available data sets. The results have demonstrated that the algorithm constitutes a usable model-free approach capable of predicting meaningful relationships between genes, revealing the time-trends of gene regulation. PMID:21524308

Microarray-Based Analysis of Subnanogram Quantities of Microbial Community DNAs by Using Whole-Community Genome Amplification†

PubMed Central

Wu, Liyou; Liu, Xueduan; Schadt, Christopher W.; Zhou, Jizhong

2006-01-01

Microarray technology provides the opportunity to identify thousands of microbial genes or populations simultaneously, but low microbial biomass often prevents application of this technology to many natural microbial communities. We developed a whole-community genome amplification-assisted microarray detection approach based on multiple displacement amplification. The representativeness of amplification was evaluated using several types of microarrays and quantitative indexes. Representative detection of individual genes or genomes was obtained with 1 to 100 ng DNA from individual or mixed genomes, in equal or unequal abundance, and with 1 to 500 ng community DNAs from groundwater. Lower concentrations of DNA (as low as 10 fg) could be detected, but the lower template concentrations affected the representativeness of amplification. Robust quantitative detection was also observed by significant linear relationships between signal intensities and initial DNA concentrations ranging from (i) 0.04 to 125 ng (r2 = 0.65 to 0.99) for DNA from pure cultures as detected by whole-genome open reading frame arrays, (ii) 0.1 to 1,000 ng (r2 = 0.91) for genomic DNA using community genome arrays, and (iii) 0.01 to 250 ng (r2 = 0.96 to 0.98) for community DNAs from ethanol-amended groundwater using 50-mer functional gene arrays. This method allowed us to investigate the oligotrophic microbial communities in groundwater contaminated with uranium and other metals. The results indicated that microorganisms containing genes involved in contaminant degradation and immobilization are present in these communities, that their spatial distribution is heterogeneous, and that microbial diversity is greatly reduced in the highly contaminated environment. PMID:16820490

Surface invasive cleavage assay on a maskless light-directed diamond DNA microarray for genome-wide human SNP mapping.

PubMed

Nie, Bei; Yang, Min; Fu, Weiling; Liang, Zhiqing

2015-07-07

The surface invasive cleavage assay, because of its innate accuracy and ability for self-signal amplification, provides a potential route for the mapping of hundreds of thousands of human SNP sites. However, its performance on a high density DNA array has not yet been established, due to the unusual "hairpin" probe design on the microarray and the lack of chemical stability of commercially available substrates. Here we present an applicable method to implement a nanocrystalline diamond thin film as an alternative substrate for fabricating an addressable DNA array using maskless light-directed photochemistry, producing the most chemically stable and biocompatible system for genetic analysis and enzymatic reactions. The surface invasive cleavage reaction, followed by degenerated primer ligation and post-rolling circle amplification is consecutively performed on the addressable diamond DNA array, accurately mapping SNP sites from PCR-amplified human genomic target DNA. Furthermore, a specially-designed DNA array containing dual probes in the same pixel is fabricated by following a reverse light-directed DNA synthesis protocol. This essentially enables us to decipher thousands of SNP alleles in a single-pot reaction by the simple addition of enzyme, target and reaction buffers.

Tissue-enriched expression profiles in Aedes aegypti identify hemocyte-specific transcriptome responses to infection

PubMed Central

Choi, Young-Jun; Fuchs, Jeremy F.; Mayhew, George F.; Yu, Helen E.; Christensen, Bruce M.

2012-01-01

Hemocytes are integral components of mosquito immune mechanisms such as phagocytosis, melanization, and production of antimicrobial peptides. However, our understanding of hemocyte-specific molecular processes and their contribution to shaping the host immune response remains limited. To better understand the immunophysiological features distinctive of hemocytes, we conducted genome-wide analysis of hemocyte-enriched transcripts, and examined how tissue-enriched expression patterns change with the immune status of the host. Our microarray data indicate that the hemocyte-enriched trascriptome is dynamic and context-dependent. Analysis of transcripts enriched after bacterial challenge in circulating hemocytes with respect to carcass added a dimension to evaluating infection-responsive genes and immune-related gene families. We resolved patterns of transcriptional change unique to hemocytes from those that are likely shared by other immune responsive tissues, and identified clusters of genes preferentially induced in hemocytes, likely reflecting their involvement in cell type specific functions. In addition, the study revealed conserved hemocyte-enriched molecular repertoires which might be implicated in core hemocyte function by cross-species meta-analysis of microarray expression data from Anopheles gambiae and Drosophila melanogaster. PMID:22796331

Development and experimental validation of a 20K Atlantic cod (Gadus morhua) oligonucleotide microarray based on a collection of over 150,000 ESTs.

PubMed

Booman, Marije; Borza, Tudor; Feng, Charles Y; Hori, Tiago S; Higgins, Brent; Culf, Adrian; Léger, Daniel; Chute, Ian C; Belkaid, Anissa; Rise, Marlies; Gamperl, A Kurt; Hubert, Sophie; Kimball, Jennifer; Ouellette, Rodney J; Johnson, Stewart C; Bowman, Sharen; Rise, Matthew L

2011-08-01

The collapse of Atlantic cod (Gadus morhua) wild populations strongly impacted the Atlantic cod fishery and led to the development of cod aquaculture. In order to improve aquaculture and broodstock quality, we need to gain knowledge of genes and pathways involved in Atlantic cod responses to pathogens and other stressors. The Atlantic Cod Genomics and Broodstock Development Project has generated over 150,000 expressed sequence tags from 42 cDNA libraries representing various tissues, developmental stages, and stimuli. We used this resource to develop an Atlantic cod oligonucleotide microarray containing 20,000 unique probes. Selection of sequences from the full range of cDNA libraries enables application of the microarray for a broad spectrum of Atlantic cod functional genomics studies. We included sequences that were highly abundant in suppression subtractive hybridization (SSH) libraries, which were enriched for transcripts responsive to pathogens or other stressors. These sequences represent genes that potentially play an important role in stress and/or immune responses, making the microarray particularly useful for studies of Atlantic cod gene expression responses to immune stimuli and other stressors. To demonstrate its value, we used the microarray to analyze the Atlantic cod spleen response to stimulation with formalin-killed, atypical Aeromonas salmonicida, resulting in a gene expression profile that indicates a strong innate immune response. These results were further validated by quantitative PCR analysis and comparison to results from previous analysis of an SSH library. This study shows that the Atlantic cod 20K oligonucleotide microarray is a valuable new tool for Atlantic cod functional genomics research.

Rice Phospholipase A Superfamily: Organization, Phylogenetic and Expression Analysis during Abiotic Stresses and Development

PubMed Central

Singh, Amarjeet; Baranwal, Vinay; Shankar, Alka; Kanwar, Poonam; Ranjan, Rajeev; Yadav, Sandeep; Pandey, Amita; Kapoor, Sanjay; Pandey, Girdhar K.

2012-01-01

Background Phospholipase A (PLA) is an important group of enzymes responsible for phospholipid hydrolysis in lipid signaling. PLAs have been implicated in abiotic stress signaling and developmental events in various plants species. Genome-wide analysis of PLA superfamily has been carried out in dicot plant Arabidopsis. A comprehensive genome-wide analysis of PLAs has not been presented yet in crop plant rice. Methodology/Principal Findings A comprehensive bioinformatics analysis identified a total of 31 PLA encoding genes in the rice genome, which are divided into three classes; phospholipase A1 (PLA1), patatin like phospholipases (pPLA) and low molecular weight secretory phospholipase A2 (sPLA2) based on their sequences and phylogeny. A subset of 10 rice PLAs exhibited chromosomal duplication, emphasizing the role of duplication in the expansion of this gene family in rice. Microarray expression profiling revealed a number of PLA members expressing differentially and significantly under abiotic stresses and reproductive development. Comparative expression analysis with Arabidopsis PLAs revealed a high degree of functional conservation between the orthologs in two plant species, which also indicated the vital role of PLAs in stress signaling and plant development across different plant species. Moreover, sub-cellular localization of a few candidates suggests their differential localization and functional role in the lipid signaling. Conclusion/Significance The comprehensive analysis and expression profiling would provide a critical platform for the functional characterization of the candidate PLA genes in crop plants. PMID:22363522

Estimating differential expression from multiple indicators

PubMed Central

Ilmjärv, Sten; Hundahl, Christian Ansgar; Reimets, Riin; Niitsoo, Margus; Kolde, Raivo; Vilo, Jaak; Vasar, Eero; Luuk, Hendrik

2014-01-01

Regardless of the advent of high-throughput sequencing, microarrays remain central in current biomedical research. Conventional microarray analysis pipelines apply data reduction before the estimation of differential expression, which is likely to render the estimates susceptible to noise from signal summarization and reduce statistical power. We present a probe-level framework, which capitalizes on the high number of concurrent measurements to provide more robust differential expression estimates. The framework naturally extends to various experimental designs and target categories (e.g. transcripts, genes, genomic regions) as well as small sample sizes. Benchmarking in relation to popular microarray and RNA-sequencing data-analysis pipelines indicated high and stable performance on the Microarray Quality Control dataset and in a cell-culture model of hypoxia. Experimental-data-exhibiting long-range epigenetic silencing of gene expression was used to demonstrate the efficacy of detecting differential expression of genomic regions, a level of analysis not embraced by conventional workflows. Finally, we designed and conducted an experiment to identify hypothermia-responsive genes in terms of monotonic time-response. As a novel insight, hypothermia-dependent up-regulation of multiple genes of two major antioxidant pathways was identified and verified by quantitative real-time PCR. PMID:24586062

Probing the Xenopus laevis inner ear transcriptome for biological function

PubMed Central

2012-01-01

Background The senses of hearing and balance depend upon mechanoreception, a process that originates in the inner ear and shares features across species. Amphibians have been widely used for physiological studies of mechanotransduction by sensory hair cells. In contrast, much less is known of the genetic basis of auditory and vestibular function in this class of animals. Among amphibians, the genus Xenopus is a well-characterized genetic and developmental model that offers unique opportunities for inner ear research because of the amphibian capacity for tissue and organ regeneration. For these reasons, we implemented a functional genomics approach as a means to undertake a large-scale analysis of the Xenopus laevis inner ear transcriptome through microarray analysis. Results Microarray analysis uncovered genes within the X. laevis inner ear transcriptome associated with inner ear function and impairment in other organisms, thereby supporting the inclusion of Xenopus in cross-species genetic studies of the inner ear. The use of gene categories (inner ear tissue; deafness; ion channels; ion transporters; transcription factors) facilitated the assignment of functional significance to probe set identifiers. We enhanced the biological relevance of our microarray data by using a variety of curation approaches to increase the annotation of the Affymetrix GeneChip® Xenopus laevis Genome array. In addition, annotation analysis revealed the prevalence of inner ear transcripts represented by probe set identifiers that lack functional characterization. Conclusions We identified an abundance of targets for genetic analysis of auditory and vestibular function. The orthologues to human genes with known inner ear function and the highly expressed transcripts that lack annotation are particularly interesting candidates for future analyses. We used informatics approaches to impart biologically relevant information to the Xenopus inner ear transcriptome, thereby addressing the impediment imposed by insufficient gene annotation. These findings heighten the relevance of Xenopus as a model organism for genetic investigations of inner ear organogenesis, morphogenesis, and regeneration. PMID:22676585

Statistical issues in signal extraction from microarrays

NASA Astrophysics Data System (ADS)

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

2001-06-01

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

Integrated analysis of copy number alteration and RNA expression profiles of cancer using a high-resolution whole-genome oligonucleotide array.

PubMed

Jung, Seung-Hyun; Shin, Seung-Hun; Yim, Seon-Hee; Choi, Hye-Sun; Lee, Sug-Hyung; Chung, Yeun-Jun

2009-07-31

Recently, microarray-based comparative genomic hybridization (array-CGH) has emerged as a very efficient technology with higher resolution for the genome-wide identification of copy number alterations (CNA). Although CNAs are thought to affect gene expression, there is no platform currently available for the integrated CNA-expression analysis. To achieve high-resolution copy number analysis integrated with expression profiles, we established human 30k oligoarray-based genome-wide copy number analysis system and explored the applicability of this system for integrated genome and transcriptome analysis using MDA-MB-231 cell line. We compared the CNAs detected by the oligoarray with those detected by the 3k BAC array for validation. The oligoarray identified the single copy difference more accurately and sensitively than the BAC array. Seventeen CNAs detected by both platforms in MDA-MB-231 such as gains of 5p15.33-13.1, 8q11.22-8q21.13, 17p11.2, and losses of 1p32.3, 8p23.3-8p11.21, and 9p21 were consistently identified in previous studies on breast cancer. There were 122 other small CNAs (mean size 1.79 mb) that were detected by oligoarray only, not by BAC-array. We performed genomic qPCR targeting 7 CNA regions, detected by oligoarray only, and one non-CNA region to validate the oligoarray CNA detection. All qPCR results were consistent with the oligoarray-CGH results. When we explored the possibility of combined interpretation of both DNA copy number and RNA expression profiles, mean DNA copy number and RNA expression levels showed a significant correlation. In conclusion, this 30k oligoarray-CGH system can be a reasonable choice for analyzing whole genome CNAs and RNA expression profiles at a lower cost.

Effects of Temperature on the Meiotic Recombination Landscape of the Yeast Saccharomyces cerevisiae.

PubMed

Zhang, Ke; Wu, Xue-Chang; Zheng, Dao-Qiong; Petes, Thomas D

2017-12-19

Although meiosis in warm-blooded organisms takes place in a narrow temperature range, meiosis in many organisms occurs over a wide variety of temperatures. We analyzed the properties of meiosis in the yeast Saccharomyces cerevisiae in cells sporulated at 14°C, 30°C, or 37°C. Using comparative-genomic-hybridization microarrays, we examined the distribution of Spo11-generated meiosis-specific double-stranded DNA breaks throughout the genome. Although there were between 300 and 400 regions of the genome with high levels of recombination (hot spots) observed at each temperature, only about 20% of these hot spots were found to have occurred independently of the temperature. In S. cerevisiae , regions near the telomeres and centromeres tend to have low levels of meiotic recombination. This tendency was observed in cells sporulated at 14°C and 30°C, but not at 37°C. Thus, the temperature of sporulation in yeast affects some global property of chromosome structure relevant to meiotic recombination. Using single-nucleotide polymorphism (SNP)-specific whole-genome microarrays, we also examined crossovers and their associated gene conversion events as well as gene conversion events that were unassociated with crossovers in all four spores of tetrads obtained by sporulation of diploids at 14°C, 30°C, or 37°C. Although tetrads from cells sporulated at 30°C had slightly (20%) more crossovers than those derived from cells sporulated at the other two temperatures, spore viability was good at all three temperatures. Thus, despite temperature-induced variation in the genetic maps, yeast cells produce viable haploid products at a wide variety of sporulation temperatures. IMPORTANCE In the yeast Saccharomyces cerevisiae , recombination is usually studied in cells that undergo meiosis at 25°C or 30°C. In a genome-wide analysis, we showed that the locations of genomic regions with high and low levels of meiotic recombination (hot spots and cold spots, respectively) differed dramatically in cells sporulated at 14°C, 30°C, and 37°C. Thus, in yeast, and likely in other non-warm-blooded organisms, genetic maps are strongly affected by the environment. Copyright © 2017 Zhang et al.

Tumor immunology.

PubMed

Mocellin, Simone; Lise, Mario; Nitti, Donato

2007-01-01

Advances in tumor immunology are supporting the clinical implementation of several immunological approaches to cancer in the clinical setting. However, the alternate success of current immunotherapeutic regimens underscores the fact that the molecular mechanisms underlying immune-mediated tumor rejection are still poorly understood. Given the complexity of the immune system network and the multidimensionality of tumor/host interactions, the comprehension of tumor immunology might greatly benefit from high-throughput microarray analysis, which can portrait the molecular kinetics of immune response on a genome-wide scale, thus accelerating the discovery pace and ultimately catalyzing the development of new hypotheses in cell biology. Although in its infancy, the implementation of microarray technology in tumor immunology studies has already provided investigators with novel data and intriguing new hypotheses on the molecular cascade leading to an effective immune response against cancer. Although the general principles of microarray-based gene profiling have rapidly spread in the scientific community, the need for mastering this technique to produce meaningful data and correctly interpret the enormous output of information generated by this technology is critical and represents a tremendous challenge for investigators, as outlined in the first section of this book. In the present Chapter, we report on some of the most significant results obtained with the application of DNA microarray in this oncology field.

Analysis of the Saccharomyces cerevisiae pan-genome reveals a pool of copy number variants distributed in diverse yeast strains from differing industrial environments.

PubMed

Dunn, Barbara; Richter, Chandra; Kvitek, Daniel J; Pugh, Tom; Sherlock, Gavin

2012-05-01

Although the budding yeast Saccharomyces cerevisiae is arguably one of the most well-studied organisms on earth, the genome-wide variation within this species--i.e., its "pan-genome"--has been less explored. We created a multispecies microarray platform containing probes covering the genomes of several Saccharomyces species: S. cerevisiae, including regions not found in the standard laboratory S288c strain, as well as the mitochondrial and 2-μm circle genomes-plus S. paradoxus, S. mikatae, S. kudriavzevii, S. uvarum, S. kluyveri, and S. castellii. We performed array-Comparative Genomic Hybridization (aCGH) on 83 different S. cerevisiae strains collected across a wide range of habitats; of these, 69 were commercial wine strains, while the remaining 14 were from a diverse set of other industrial and natural environments. We observed interspecific hybridization events, introgression events, and pervasive copy number variation (CNV) in all but a few of the strains. These CNVs were distributed throughout the strains such that they did not produce any clear phylogeny, suggesting extensive mating in both industrial and wild strains. To validate our results and to determine whether apparently similar introgressions and CNVs were identical by descent or recurrent, we also performed whole-genome sequencing on nine of these strains. These data may help pinpoint genomic regions involved in adaptation to different industrial milieus, as well as shed light on the course of domestication of S. cerevisiae.

Deciphering the Epigenetic Code: An Overview of DNA Methylation Analysis Methods

PubMed Central

Umer, Muhammad

2013-01-01

Abstract Significance: Methylation of cytosine in DNA is linked with gene regulation, and this has profound implications in development, normal biology, and disease conditions in many eukaryotic organisms. A wide range of methods and approaches exist for its identification, quantification, and mapping within the genome. While the earliest approaches were nonspecific and were at best useful for quantification of total methylated cytosines in the chunk of DNA, this field has seen considerable progress and development over the past decades. Recent Advances: Methods for DNA methylation analysis differ in their coverage and sensitivity, and the method of choice depends on the intended application and desired level of information. Potential results include global methyl cytosine content, degree of methylation at specific loci, or genome-wide methylation maps. Introduction of more advanced approaches to DNA methylation analysis, such as microarray platforms and massively parallel sequencing, has brought us closer to unveiling the whole methylome. Critical Issues: Sensitive quantification of DNA methylation from degraded and minute quantities of DNA and high-throughput DNA methylation mapping of single cells still remain a challenge. Future Directions: Developments in DNA sequencing technologies as well as the methods for identification and mapping of 5-hydroxymethylcytosine are expected to augment our current understanding of epigenomics. Here we present an overview of methodologies available for DNA methylation analysis with special focus on recent developments in genome-wide and high-throughput methods. While the application focus relates to cancer research, the methods are equally relevant to broader issues of epigenetics and redox science in this special forum. Antioxid. Redox Signal. 18, 1972–1986. PMID:23121567

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

Gentry, T.; Schadt, C.; Zhou, J.

Microarray technology has the unparalleled potential tosimultaneously determine the dynamics and/or activities of most, if notall, of the microbial populations in complex environments such as soilsand sediments. Researchers have developed several types of arrays thatcharacterize the microbial populations in these samples based on theirphylogenetic relatedness or functional genomic content. Several recentstudies have used these microarrays to investigate ecological issues;however, most have only analyzed a limited number of samples withrelatively few experiments utilizing the full high-throughput potentialof microarray analysis. This is due in part to the unique analyticalchallenges that these samples present with regard to sensitivity,specificity, quantitation, and data analysis. Thismore » review discussesspecific applications of microarrays to microbial ecology research alongwith some of the latest studies addressing the difficulties encounteredduring analysis of complex microbial communities within environmentalsamples. With continued development, microarray technology may ultimatelyachieve its potential for comprehensive, high-throughput characterizationof microbial populations in near real-time.« less

Whole-genome transcriptional analysis of heavy metal stresses inCaulobacter crescentus

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

Hu, Ping; Brodie, Eoin L.; Suzuki, Yohey

2005-09-21

The bacterium Caulobacter crescentus and related stalkbacterial species are known for their distinctive ability to live in lownutrient environments, a characteristic of most heavy metal contaminatedsites. Caulobacter crescentus is a model organism for studying cell cycleregulation with well developed genetics. We have identified the pathwaysresponding to heavy metal toxicity in C. crescentus to provide insightsfor possible application of Caulobacter to environmental restoration. Weexposed C. crescentus cells to four heavy metals (chromium, cadmium,selenium and uranium) and analyzed genome wide transcriptional activitiespost exposure using a Affymetrix GeneChip microarray. C. crescentusshowed surprisingly high tolerance to uranium, a possible mechanism forwhich may be formationmore » of extracellular calcium-uranium-phosphateprecipitates. The principal response to these metals was protectionagainst oxidative stress (up-regulation of manganese-dependent superoxidedismutase, sodA). Glutathione S-transferase, thioredoxin, glutaredoxinsand DNA repair enzymes responded most strongly to cadmium and chromate.The cadmium and chromium stress response also focused on reducing theintracellular metal concentration, with multiple efflux pumps employed toremove cadmium while a sulfate transporter was down-regulated to reducenon-specific uptake of chromium. Membrane proteins were also up-regulatedin response to most of the metals tested. A two-component signaltransduction system involved in the uranium response was identified.Several differentially regulated transcripts from regions previously notknown to encode proteins were identified, demonstrating the advantage ofevaluating the transcriptome using whole genome microarrays.« less

Next Generation Sequencing at the University of Chicago Genomics Core

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

Faber, Pieter

2013-04-24

The University of Chicago Genomics Core provides University of Chicago investigators (and external clients) access to State-of-the-Art genomics capabilities: next generation sequencing, Sanger sequencing / genotyping and micro-arrays (gene expression, genotyping, and methylation). The current presentation will highlight our capabilities in the area of ultra-high throughput sequencing analysis.

An anatomically comprehensive atlas of the adult human brain transcriptome

PubMed Central

Guillozet-Bongaarts, Angela L.; Shen, Elaine H.; Ng, Lydia; Miller, Jeremy A.; van de Lagemaat, Louie N.; Smith, Kimberly A.; Ebbert, Amanda; Riley, Zackery L.; Abajian, Chris; Beckmann, Christian F.; Bernard, Amy; Bertagnolli, Darren; Boe, Andrew F.; Cartagena, Preston M.; Chakravarty, M. Mallar; Chapin, Mike; Chong, Jimmy; Dalley, Rachel A.; David Daly, Barry; Dang, Chinh; Datta, Suvro; Dee, Nick; Dolbeare, Tim A.; Faber, Vance; Feng, David; Fowler, David R.; Goldy, Jeff; Gregor, Benjamin W.; Haradon, Zeb; Haynor, David R.; Hohmann, John G.; Horvath, Steve; Howard, Robert E.; Jeromin, Andreas; Jochim, Jayson M.; Kinnunen, Marty; Lau, Christopher; Lazarz, Evan T.; Lee, Changkyu; Lemon, Tracy A.; Li, Ling; Li, Yang; Morris, John A.; Overly, Caroline C.; Parker, Patrick D.; Parry, Sheana E.; Reding, Melissa; Royall, Joshua J.; Schulkin, Jay; Sequeira, Pedro Adolfo; Slaughterbeck, Clifford R.; Smith, Simon C.; Sodt, Andy J.; Sunkin, Susan M.; Swanson, Beryl E.; Vawter, Marquis P.; Williams, Derric; Wohnoutka, Paul; Zielke, H. Ronald; Geschwind, Daniel H.; Hof, Patrick R.; Smith, Stephen M.; Koch, Christof; Grant, Seth G. N.; Jones, Allan R.

2014-01-01

Neuroanatomically precise, genome-wide maps of transcript distributions are critical resources to complement genomic sequence data and to correlate functional and genetic brain architecture. Here we describe the generation and analysis of a transcriptional atlas of the adult human brain, comprising extensive histological analysis and comprehensive microarray profiling of ~900 neuroanatomically precise subdivisions in two individuals. Transcriptional regulation varies enormously by anatomical location, with different regions and their constituent cell types displaying robust molecular signatures that are highly conserved between individuals. Analysis of differential gene expression and gene co-expression relationships demonstrates that brain-wide variation strongly reflects the distributions of major cell classes such as neurons, oligodendrocytes, astrocytes and microglia. Local neighbourhood relationships between fine anatomical subdivisions are associated with discrete neuronal subtypes and genes involved with synaptic transmission. The neocortex displays a relatively homogeneous transcriptional pattern, but with distinct features associated selectively with primary sensorimotor cortices and with enriched frontal lobe expression. Notably, the spatial topography of the neocortex is strongly reflected in its molecular topography— the closer two cortical regions, the more similar their transcriptomes. This freely accessible online data resource forms a high-resolution transcriptional baseline for neurogenetic studies of normal and abnormal human brain function. PMID:22996553

Histone Deacetylase Inhibition Promotes Osteoblast Maturation by Altering the Histone H4 Epigenome and Reduces Akt Phosphorylation*

PubMed Central

Dudakovic, Amel; Evans, Jared M.; Li, Ying; Middha, Sumit; McGee-Lawrence, Meghan E.; van Wijnen, Andre J.; Westendorf, Jennifer J.

2013-01-01

Bone has remarkable regenerative capacity, but this ability diminishes during aging. Histone deacetylase inhibitors (HDIs) promote terminal osteoblast differentiation and extracellular matrix production in culture. The epigenetic events altered by HDIs in osteoblasts may hold clues for the development of new anabolic treatments for osteoporosis and other conditions of low bone mass. To assess how HDIs affect the epigenome of committed osteoblasts, MC3T3 cells were treated with suberoylanilide hydroxamic acid (SAHA) and subjected to microarray gene expression profiling and high-throughput ChIP-Seq analysis. As expected, SAHA induced differentiation and matrix calcification of osteoblasts in vitro. ChIP-Seq analysis revealed that SAHA increased histone H4 acetylation genome-wide and in differentially regulated genes, except for the 500 bp upstream of transcriptional start sites. Pathway analysis indicated that SAHA increased the expression of insulin signaling modulators, including Slc9a3r1. SAHA decreased phosphorylation of insulin receptor β, Akt, and the Akt substrate FoxO1, resulting in FoxO1 stabilization. Thus, SAHA induces genome-wide H4 acetylation and modulates the insulin/Akt/FoxO1 signaling axis, whereas it promotes terminal osteoblast differentiation in vitro. PMID:23940046

CoryneRegNet: an ontology-based data warehouse of corynebacterial transcription factors and regulatory networks.

PubMed

Baumbach, Jan; Brinkrolf, Karina; Czaja, Lisa F; Rahmann, Sven; Tauch, Andreas

2006-02-14

The application of DNA microarray technology in post-genomic analysis of bacterial genome sequences has allowed the generation of huge amounts of data related to regulatory networks. This data along with literature-derived knowledge on regulation of gene expression has opened the way for genome-wide reconstruction of transcriptional regulatory networks. These large-scale reconstructions can be converted into in silico models of bacterial cells that allow a systematic analysis of network behavior in response to changing environmental conditions. CoryneRegNet was designed to facilitate the genome-wide reconstruction of transcriptional regulatory networks of corynebacteria relevant in biotechnology and human medicine. During the import and integration process of data derived from experimental studies or literature knowledge CoryneRegNet generates links to genome annotations, to identified transcription factors and to the corresponding cis-regulatory elements. CoryneRegNet is based on a multi-layered, hierarchical and modular concept of transcriptional regulation and was implemented by using the relational database management system MySQL and an ontology-based data structure. Reconstructed regulatory networks can be visualized by using the yFiles JAVA graph library. As an application example of CoryneRegNet, we have reconstructed the global transcriptional regulation of a cellular module involved in SOS and stress response of corynebacteria. CoryneRegNet is an ontology-based data warehouse that allows a pertinent data management of regulatory interactions along with the genome-scale reconstruction of transcriptional regulatory networks. These models can further be combined with metabolic networks to build integrated models of cellular function including both metabolism and its transcriptional regulation.

Analysis of baseline gene expression levels from ...

EPA Pesticide Factsheets

The use of gene expression profiling to predict chemical mode of action would be enhanced by better characterization of variance due to individual, environmental, and technical factors. Meta-analysis of microarray data from untreated or vehicle-treated animals within the control arm of toxicogenomics studies has yielded useful information on baseline fluctuations in gene expression. A dataset of control animal microarray expression data was assembled by a working group of the Health and Environmental Sciences Institute's Technical Committee on the Application of Genomics in Mechanism Based Risk Assessment in order to provide a public resource for assessments of variability in baseline gene expression. Data from over 500 Affymetrix microarrays from control rat liver and kidney were collected from 16 different institutions. Thirty-five biological and technical factors were obtained for each animal, describing a wide range of study characteristics, and a subset were evaluated in detail for their contribution to total variability using multivariate statistical and graphical techniques. The study factors that emerged as key sources of variability included gender, organ section, strain, and fasting state. These and other study factors were identified as key descriptors that should be included in the minimal information about a toxicogenomics study needed for interpretation of results by an independent source. Genes that are the most and least variable, gender-selectiv

Insights into the fluoride-resistant regulation mechanism of Acidithiobacillus ferrooxidans ATCC 23270 based on whole genome microarrays.

PubMed

Ma, Liyuan; Li, Qian; Shen, Li; Feng, Xue; Xiao, Yunhua; Tao, Jiemeng; Liang, Yili; Yin, Huaqun; Liu, Xueduan

2016-10-01

Acidophilic microorganisms involved in uranium bioleaching are usually suppressed by dissolved fluoride ions, eventually leading to reduced leaching efficiency. However, little is known about the regulation mechanisms of microbial resistance to fluoride. In this study, the resistance of Acidithiobacillus ferrooxidans ATCC 23270 to fluoride was investigated by detecting bacterial growth fluctuations and ferrous or sulfur oxidation. To explore the regulation mechanism, a whole genome microarray was used to profile the genome-wide expression. The fluoride tolerance of A. ferrooxidans cultured in the presence of FeSO4 was better than that cultured with the S(0) substrate. The differentially expressed gene categories closely related to fluoride tolerance included those involved in energy metabolism, cellular processes, protein synthesis, transport, the cell envelope, and binding proteins. This study highlights that the cellular ferrous oxidation ability was enhanced at the lower fluoride concentrations. An overview of the cellular regulation mechanisms of extremophiles to fluoride resistance is discussed.

Using Genome-Wide Expression Profiling to Define Gene Networks Relevant to the Study of Complex Traits: From RNA Integrity to Network Topology

PubMed Central

O'Brien, M.A.; Costin, B.N.; Miles, M.F.

2014-01-01

Postgenomic studies of the function of genes and their role in disease have now become an area of intense study since efforts to define the raw sequence material of the genome have largely been completed. The use of whole-genome approaches such as microarray expression profiling and, more recently, RNA-sequence analysis of transcript abundance has allowed an unprecedented look at the workings of the genome. However, the accurate derivation of such high-throughput data and their analysis in terms of biological function has been critical to truly leveraging the postgenomic revolution. This chapter will describe an approach that focuses on the use of gene networks to both organize and interpret genomic expression data. Such networks, derived from statistical analysis of large genomic datasets and the application of multiple bioinformatics data resources, poten-tially allow the identification of key control elements for networks associated with human disease, and thus may lead to derivation of novel therapeutic approaches. However, as discussed in this chapter, the leveraging of such networks cannot occur without a thorough understanding of the technical and statistical factors influencing the derivation of genomic expression data. Thus, while the catch phrase may be “it's the network … stupid,” the understanding of factors extending from RNA isolation to genomic profiling technique, multivariate statistics, and bioinformatics are all critical to defining fully useful gene networks for study of complex biology. PMID:23195313

Genome-wide analysis of DUF221 domain-containing gene family in Oryza species and identification of its salinity stress-responsive members in rice.

PubMed

Ganie, Showkat Ahmad; Pani, Dipti Ranjan; Mondal, Tapan Kumar

2017-01-01

DUF221 domain-containing genes (DDP genes) play important roles in developmental biology, hormone signalling transduction, and responses to abiotic stress. Therefore to understand their structural and evolutionary relationship, we did a genome-wide analysis of this important gene family in rice. Further, through comparative genomics, DDP genes from Oryza sativa subsp. (indica), nine different wild species of rice and Arabidopsis were also identified. We also found an expansion of the DDP gene families in rice and Arabidopsis which is due to the segmental duplication events in some of the gene family members. In general, a highly purifying selection was found acting on all the deduced paralogous and orthologous DDP gene pairs. The data from microarray and subsequent qRT-PCR analysis revealed that although several OsDDPs were differentially regulated under salinity stress, yet OsDDP6 was upregulated at all the developmental stages in salt tolerant rice genotype, FL478. Interestingly, OsDDP6 was found to be involved in proline metabolism pathway as indicated by protein network analysis. The diverse gene structures, varied transmembrane topologies and the differential expression patterns implied the functional diversity in DDP genes. Therefore, the comprehensive evolutionary analysis of DDP genes from different Oryza species and Arabidopsis performed in this study will provide the basis for further functional validation studies vis-à-vis DDP genes of rice and other plant species.

Genomic analysis of sleep deprivation reveals translational regulation in the hippocampus.

PubMed

Vecsey, Christopher G; Peixoto, Lucia; Choi, Jennifer H K; Wimmer, Mathieu; Jaganath, Devan; Hernandez, Pepe J; Blackwell, Jennifer; Meda, Karuna; Park, Alan J; Hannenhalli, Sridhar; Abel, Ted

2012-10-17

Sleep deprivation is a common problem of considerable health and economic impact in today's society. Sleep loss is associated with deleterious effects on cognitive functions such as memory and has a high comorbidity with many neurodegenerative and neuropsychiatric disorders. Therefore, it is crucial to understand the molecular basis of the effect of sleep deprivation in the brain. In this study, we combined genome-wide and traditional molecular biological approaches to determine the cellular and molecular impacts of sleep deprivation in the mouse hippocampus, a brain area crucial for many forms of memory. Microarray analysis examining the effects of 5 h of sleep deprivation on gene expression in the mouse hippocampus found 533 genes with altered expression. Bioinformatic analysis revealed that a prominent effect of sleep deprivation was to downregulate translation, potentially mediated through components of the insulin signaling pathway such as the mammalian target of rapamycin (mTOR), a key regulator of protein synthesis. Consistent with this analysis, sleep deprivation reduced levels of total and phosphorylated mTOR, and levels returned to baseline after 2.5 h of recovery sleep. Our findings represent the first genome-wide analysis of the effects of sleep deprivation on the mouse hippocampus, and they suggest that the detrimental effects of sleep deprivation may be mediated by reductions in protein synthesis via downregulation of mTOR. Because protein synthesis and mTOR activation are required for long-term memory formation, our study improves our understanding of the molecular mechanisms underlying the memory impairments induced by sleep deprivation.

Genome-wide analysis of DUF221 domain-containing gene family in Oryza species and identification of its salinity stress-responsive members in rice

PubMed Central

Ganie, Showkat Ahmad; Pani, Dipti Ranjan

2017-01-01

DUF221 domain-containing genes (DDP genes) play important roles in developmental biology, hormone signalling transduction, and responses to abiotic stress. Therefore to understand their structural and evolutionary relationship, we did a genome-wide analysis of this important gene family in rice. Further, through comparative genomics, DDP genes from Oryza sativa subsp. (indica), nine different wild species of rice and Arabidopsis were also identified. We also found an expansion of the DDP gene families in rice and Arabidopsis which is due to the segmental duplication events in some of the gene family members. In general, a highly purifying selection was found acting on all the deduced paralogous and orthologous DDP gene pairs. The data from microarray and subsequent qRT-PCR analysis revealed that although several OsDDPs were differentially regulated under salinity stress, yet OsDDP6 was upregulated at all the developmental stages in salt tolerant rice genotype, FL478. Interestingly, OsDDP6 was found to be involved in proline metabolism pathway as indicated by protein network analysis. The diverse gene structures, varied transmembrane topologies and the differential expression patterns implied the functional diversity in DDP genes. Therefore, the comprehensive evolutionary analysis of DDP genes from different Oryza species and Arabidopsis performed in this study will provide the basis for further functional validation studies vis-à-vis DDP genes of rice and other plant species. PMID:28846681

Use of Bayesian Networks to Probabilistically Model and Improve the Likelihood of Validation of Microarray Findings by RT-PCR

PubMed Central

English, Sangeeta B.; Shih, Shou-Ching; Ramoni, Marco F.; Smith, Lois E.; Butte, Atul J.

2014-01-01

Though genome-wide technologies, such as microarrays, are widely used, data from these methods are considered noisy; there is still varied success in downstream biological validation. We report a method that increases the likelihood of successfully validating microarray findings using real time RT-PCR, including genes at low expression levels and with small differences. We use a Bayesian network to identify the most relevant sources of noise based on the successes and failures in validation for an initial set of selected genes, and then improve our subsequent selection of genes for validation based on eliminating these sources of noise. The network displays the significant sources of noise in an experiment, and scores the likelihood of validation for every gene. We show how the method can significantly increase validation success rates. In conclusion, in this study, we have successfully added a new automated step to determine the contributory sources of noise that determine successful or unsuccessful downstream biological validation. PMID:18790084

Prediction of transcriptional regulatory elements for plant hormone responses based on microarray data

PubMed Central

2011-01-01

Background Phytohormones organize plant development and environmental adaptation through cell-to-cell signal transduction, and their action involves transcriptional activation. Recent international efforts to establish and maintain public databases of Arabidopsis microarray data have enabled the utilization of this data in the analysis of various phytohormone responses, providing genome-wide identification of promoters targeted by phytohormones. Results We utilized such microarray data for prediction of cis-regulatory elements with an octamer-based approach. Our test prediction of a drought-responsive RD29A promoter with the aid of microarray data for response to drought, ABA and overexpression of DREB1A, a key regulator of cold and drought response, provided reasonable results that fit with the experimentally identified regulatory elements. With this succession, we expanded the prediction to various phytohormone responses, including those for abscisic acid, auxin, cytokinin, ethylene, brassinosteroid, jasmonic acid, and salicylic acid, as well as for hydrogen peroxide, drought and DREB1A overexpression. Totally 622 promoters that are activated by phytohormones were subjected to the prediction. In addition, we have assigned putative functions to 53 octamers of the Regulatory Element Group (REG) that have been extracted as position-dependent cis-regulatory elements with the aid of their feature of preferential appearance in the promoter region. Conclusions Our prediction of Arabidopsis cis-regulatory elements for phytohormone responses provides guidance for experimental analysis of promoters to reveal the basis of the transcriptional network of phytohormone responses. PMID:21349196

4p terminal deletion and 11p subtelomeric duplication detected by genomic microarray in a patient with Wolf-Hirschhorn syndrome and an atypical phenotype.

PubMed

Stevenson, David A; Carey, John C; Cowley, Brett C; Bayrak-Toydemir, Pinar; Mao, Rong; Brothman, Arthur R

2004-12-01

We report a de novo cryptic 11p duplication found by genomic microarray with a cytogenetically detected 4p deletion. Terminal 4p deletions cause Wolf-Hirschhorn syndrome, but the phenotype probably was modified by the paternally derived 11p duplication. This emphasizes the clinical utility of genomic microarray.

Microarray data mining using Bioconductor packages.

PubMed

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

2009-07-16

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

Analysis of sensitivity and rapid hybridization of a multiplexed Microbial Detection Microarray

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

Thissen, James B.; McLoughlin, Kevin; Gardner, Shea

Microarrays have proven to be useful in rapid detection of many viruses and bacteria. Pathogen detection microarrays have been used to diagnose viral and bacterial infections in clinical samples and to evaluate the safety of biological drug materials. A multiplexed version of the Lawrence Livermore Microbial Detection Array (LLMDA) was developed and evaluated with minimum detectable concentrations for pure unamplified DNA viruses, along with mixtures of viral and bacterial DNA subjected to different whole genome amplification protocols. In addition the performance of the array was tested when hybridization time was reduced from 17 h to 1 h. The LLMDA wasmore » able to detect unamplified vaccinia virus DNA at a concentration of 14 fM, or 100,000 genome copies in 12 μL of sample. With amplification, positive identification was made with only 100 genome copies of input material. When tested against human stool samples from patients with acute gastroenteritis, the microarray detected common gastroenteritis viral and bacterial infections such as rotavirus and E. coli. Accurate detection was found but with a 4-fold drop in sensitivity for a 1 h compared to a 17 h hybridization. The array detected 2 ng (equivalent concentration of 15.6 fM) of labeled DNA from a virus with 1 h hybridization without any amplification, and was able to identify the components of a mixture of viruses and bacteria at species and in some cases strain level resolution. Sensitivity improved by three orders of magnitude with random whole genome amplification prior to hybridization; for instance, the array detected a DNA virus with only 20 fg or 100 genome copies as input. This multiplexed microarray is an efficient tool to analyze clinical and environmental samples for the presence of multiple viral and bacterial pathogens rapidly.« less

Analysis of sensitivity and rapid hybridization of a multiplexed Microbial Detection Microarray

DOE PAGES

Thissen, James B.; McLoughlin, Kevin; Gardner, Shea; ...

2014-06-01

Microarrays have proven to be useful in rapid detection of many viruses and bacteria. Pathogen detection microarrays have been used to diagnose viral and bacterial infections in clinical samples and to evaluate the safety of biological drug materials. A multiplexed version of the Lawrence Livermore Microbial Detection Array (LLMDA) was developed and evaluated with minimum detectable concentrations for pure unamplified DNA viruses, along with mixtures of viral and bacterial DNA subjected to different whole genome amplification protocols. In addition the performance of the array was tested when hybridization time was reduced from 17 h to 1 h. The LLMDA wasmore » able to detect unamplified vaccinia virus DNA at a concentration of 14 fM, or 100,000 genome copies in 12 μL of sample. With amplification, positive identification was made with only 100 genome copies of input material. When tested against human stool samples from patients with acute gastroenteritis, the microarray detected common gastroenteritis viral and bacterial infections such as rotavirus and E. coli. Accurate detection was found but with a 4-fold drop in sensitivity for a 1 h compared to a 17 h hybridization. The array detected 2 ng (equivalent concentration of 15.6 fM) of labeled DNA from a virus with 1 h hybridization without any amplification, and was able to identify the components of a mixture of viruses and bacteria at species and in some cases strain level resolution. Sensitivity improved by three orders of magnitude with random whole genome amplification prior to hybridization; for instance, the array detected a DNA virus with only 20 fg or 100 genome copies as input. This multiplexed microarray is an efficient tool to analyze clinical and environmental samples for the presence of multiple viral and bacterial pathogens rapidly.« less

Genome-wide identification of WRKY family genes and their response to cold stress in Vitis vinifera

PubMed Central

2014-01-01

Background WRKY transcription factors are one of the largest families of transcriptional regulators in plants. WRKY genes are not only found to play significant roles in biotic and abiotic stress response, but also regulate growth and development. Grapevine (Vitis vinifera) production is largely limited by stressful climate conditions such as cold stress and the role of WRKY genes in the survival of grapevine under these conditions remains unknown. Results We identified a total of 59 VvWRKYs from the V. vinifera genome, belonging to four subgroups according to conserved WRKY domains and zinc-finger structure. The majority of VvWRKYs were expressed in more than one tissue among the 7 tissues examined which included young leaves, mature leaves, tendril, stem apex, root, young fruits and ripe fruits. Publicly available microarray data suggested that a subset of VvWRKYs was activated in response to diverse stresses. Quantitative real-time PCR (qRT-PCR) results demonstrated that the expression levels of 36 VvWRKYs are changed following cold exposure. Comparative analysis was performed on data from publicly available microarray experiments, previous global transcriptome analysis studies, and qRT-PCR. We identified 15 VvWRKYs in at least two of these databases which may relate to cold stress. Among them, the transcription of three genes can be induced by exogenous ABA application, suggesting that they can be involved in an ABA-dependent signaling pathway in response to cold stress. Conclusions We identified 59 VvWRKYs from the V. vinifera genome and 15 of them showed cold stress-induced expression patterns. These genes represented candidate genes for future functional analysis of VvWRKYs involved in the low temperature-related signal pathways in grape. PMID:24755338

Genome-wide RNA profiling of long-lasting stem cell-like memory CD8 T cells induced by Yellow Fever vaccination in humans.

PubMed

Fuertes Marraco, Silvia A; Soneson, Charlotte; Delorenzi, Mauro; Speiser, Daniel E

2015-09-01

The live-attenuated Yellow Fever (YF) vaccine YF-17D induces a broad and polyfunctional CD8 T cell response in humans. Recently, we identified a population of stem cell-like memory CD8 T cells induced by YF-17D that persists at stable frequency for at least 25 years after vaccination. The YF-17D is thus a model system of human CD8 T cell biology that furthermore allows to track and study long-lasting and antigen-specific human memory CD8 T cells. Here, we describe in detail the sample characteristics and preparation of a microarray dataset acquired for genome-wide gene expression profiling of long-lasting YF-specific stem cell-like memory CD8 T cells, compared to the reference CD8 T cell differentiation subsets from total CD8 T cells. We also describe the quality controls, annotations and exploratory analyses of the dataset. The microarray data is available from the Gene Expression Omnibus (GEO) public repository with accession number GSE65804.

Use of transcriptome sequencing to understand the pistillate flowering in hickory (Carya cathayensis Sarg.).

PubMed

Huang, You-Jun; Liu, Li-Li; Huang, Jian-Qin; Wang, Zheng-Jia; Chen, Fang-Fang; Zhang, Qi-Xiang; Zheng, Bing-Song; Chen, Ming

2013-10-10

Different from herbaceous plants, the woody plants undergo a long-period vegetative stage to achieve floral transition. They then turn into seasonal plants, flowering annually. In this study, a preliminary model of gene regulations for seasonal pistillate flowering in hickory (Carya cathayensis) was proposed. The genome-wide dynamic transcriptome was characterized via the joint-approach of RNA sequencing and microarray analysis. Differential transcript abundance analysis uncovered the dynamic transcript abundance patterns of flowering correlated genes and their major functions based on Gene Ontology (GO) analysis. To explore pistillate flowering mechanism in hickory, a comprehensive flowering gene regulatory network based on Arabidopsis thaliana was constructed by additional literature mining. A total of 114 putative flowering or floral genes including 31 with differential transcript abundance were identified in hickory. The locations, functions and dynamic transcript abundances were analyzed in the gene regulatory networks. A genome-wide co-expression network for the putative flowering or floral genes shows three flowering regulatory modules corresponding to response to light abiotic stimulus, cold stress, and reproductive development process, respectively. Totally 27 potential flowering or floral genes were recruited which are meaningful to understand the hickory specific seasonal flowering mechanism better. Flowering event of pistillate flower bud in hickory is triggered by several pathways synchronously including the photoperiod, autonomous, vernalization, gibberellin, and sucrose pathway. Totally 27 potential flowering or floral genes were recruited from the genome-wide co-expression network function module analysis. Moreover, the analysis provides a potential FLC-like gene based vernalization pathway and an 'AC' model for pistillate flower development in hickory. This work provides an available framework for pistillate flower development in hickory, which is significant for insight into regulation of flowering and floral development of woody plants.

Use of transcriptome sequencing to understand the pistillate flowering in hickory (Carya cathayensis Sarg.)

PubMed Central

2013-01-01

Background Different from herbaceous plants, the woody plants undergo a long-period vegetative stage to achieve floral transition. They then turn into seasonal plants, flowering annually. In this study, a preliminary model of gene regulations for seasonal pistillate flowering in hickory (Carya cathayensis) was proposed. The genome-wide dynamic transcriptome was characterized via the joint-approach of RNA sequencing and microarray analysis. Results Differential transcript abundance analysis uncovered the dynamic transcript abundance patterns of flowering correlated genes and their major functions based on Gene Ontology (GO) analysis. To explore pistillate flowering mechanism in hickory, a comprehensive flowering gene regulatory network based on Arabidopsis thaliana was constructed by additional literature mining. A total of 114 putative flowering or floral genes including 31 with differential transcript abundance were identified in hickory. The locations, functions and dynamic transcript abundances were analyzed in the gene regulatory networks. A genome-wide co-expression network for the putative flowering or floral genes shows three flowering regulatory modules corresponding to response to light abiotic stimulus, cold stress, and reproductive development process, respectively. Totally 27 potential flowering or floral genes were recruited which are meaningful to understand the hickory specific seasonal flowering mechanism better. Conclusions Flowering event of pistillate flower bud in hickory is triggered by several pathways synchronously including the photoperiod, autonomous, vernalization, gibberellin, and sucrose pathway. Totally 27 potential flowering or floral genes were recruited from the genome-wide co-expression network function module analysis. Moreover, the analysis provides a potential FLC-like gene based vernalization pathway and an 'AC’ model for pistillate flower development in hickory. This work provides an available framework for pistillate flower development in hickory, which is significant for insight into regulation of flowering and floral development of woody plants. PMID:24106755

Genome-Wide Analysis of Long Noncoding RNA (lncRNA) Expression in Hepatoblastoma Tissues

PubMed Central

Xue, Ping; Cui, Ximao; Li, Kai; Zheng, Shan; He, Xianghuo; Dong, Kuiran

2014-01-01

Long noncoding RNAs (lncRNAs) have crucial roles in cancer biology. We performed a genome-wide analysis of lncRNA expression in hepatoblastoma tissues to identify novel targets for further study of hepatoblastoma. Hepatoblastoma and normal liver tissue samples were obtained from hepatoblastoma patients. The genome-wide analysis of lncRNA expression in these tissues was performed using a 4×180 K lncRNA microarray and Sureprint G3 Human lncRNA Chips. Quantitative RT-PCR (qRT-PCR) was performed to confirm these results. The differential expressions of lncRNAs and mRNAs were identified through fold-change filtering. Gene Ontology (GO) and pathway analyses were performed using the standard enrichment computation method. Associations between lncRNAs and adjacent protein-coding genes were determined through complex transcriptional loci analysis. We found that 2736 lncRNAs were differentially expressed in hepatoblastoma tissues. Among these, 1757 lncRNAs were upregulated more than two-fold relative to normal tissues and 979 lncRNAs were downregulated. Moreover, in hepatoblastoma there were 420 matched lncRNA-mRNA pairs for 120 differentially expressed lncRNAs, and 167 differentially expressed mRNAs. The co-expression network analysis predicted 252 network nodes and 420 connections between 120 lncRNAs and 132 coding genes. Within this co-expression network, 369 pairs were positive, and 51 pairs were negative. Lastly, qRT-PCR data verified six upregulated and downregulated lncRNAs in hepatoblastoma, plus endothelial cell-specific molecule 1 (ESM1) mRNA. Our results demonstrated that expression of these aberrant lncRNAs could respond to hepatoblastoma development. Further study of these lncRNAs could provide useful insight into hepatoblastoma biology. PMID:24465615

The importance of copy number variation in congenital heart disease

PubMed Central

Costain, Gregory; Silversides, Candice K; Bassett, Anne S

2016-01-01

Congenital heart disease (CHD) is the most common class of major malformations in humans. The historical association with large chromosomal abnormalities foreshadowed the role of submicroscopic rare copy number variations (CNVs) as important genetic causes of CHD. Recent studies have provided robust evidence for these structural variants as genome-wide contributors to all forms of CHD, including CHD that appears isolated without extra-cardiac features. Overall, a CNV-related molecular diagnosis can be made in up to one in eight patients with CHD. These include de novo and inherited variants at established (chromosome 22q11.2), emerging (chromosome 1q21.1), and novel loci across the genome. Variable expression of rare CNVs provides support for the notion of a genetic spectrum of CHD that crosses traditional anatomic classification boundaries. Clinical genetic testing using genome-wide technologies (e.g., chromosomal microarray analysis) is increasingly employed in prenatal, paediatric and adult settings. CNV discoveries in CHD have translated to changes to clinical management, prognostication and genetic counselling. The convergence of findings at individual gene and at pathway levels is shedding light on the mechanisms that govern human cardiac morphogenesis. These clinical and research advances are helping to inform whole-genome sequencing, the next logical step in delineating the genetic architecture of CHD. PMID:28706735

Gene Expression Analysis: Teaching Students to Do 30,000 Experiments at Once with Microarray

ERIC Educational Resources Information Center

Carvalho, Felicia I.; Johns, Christopher; Gillespie, Marc E.

2012-01-01

Genome scale experiments routinely produce large data sets that require computational analysis, yet there are few student-based labs that illustrate the design and execution of these experiments. In order for students to understand and participate in the genomic world, teaching labs must be available where students generate and analyze large data…

USE OF TRANSCRIPTIONAL COUPLING AND KEGG PATHWAY ANALYSIS OF GLOBAL GENE EXPRESSION TO REVEAL TRANSCRIPTIONAL CHANGES BETWEEN STATIONARY- AND LOG-PHASE SALMONELLA TYPHIMURIUM LT2

EPA Science Inventory

DNA microarray analysis is plagued by a lack of data reproducibility and by limits to the detectability of transcripts by hybridization. To mitigate these limitations, we employed transcriptional coupling within the S. typhimurium genome. This genome has 2664 transcriptionally co...

Genomic screening for targets regulated by berberine in breast cancer cells.

PubMed

Wen, Chun-Jie; Wu, Lan-Xiang; Fu, Li-Juan; Yu, Jing; Zhang, Yi-Wen; Zhang, Xue; Zhou, Hong-Hao

2013-01-01

Berberine, a common isoquinoline alkaloid, has been shown to possess anti-cancer activities. However, the underlying molecular mechanisms are still not completely understood. In the current study, we investigated the effects of berberine on cell growth, colony formation, cell cycle distribution, and whether it improved the anticancer efficiency of cisplatin and doxorubicin in human breast cancer estrogen receptor positive (ER+) MCF-7 cells and estrogen receptor negative (ER-) MDA-MB-231 cells. Notably, berberine treatment significantly inhibited cell growth and colony formation in the two cell lines, berberine in combination with cisplatin exerting synergistic growth inhibitory effects. Accompanied by decreased growth, berberine induced G1 phase arrest in MCF-7 but not MDA-MB-231 cells. To provide a more detailed understanding of the mechanisms of action of berberine, we performed genome-wide expression profiling of berberine-treated cells using cDNA microarrays. This revealed that there were 3,397 and 2,706 genes regulated by berberine in MCF-7 and MDA-MB-231 cells, respectively. Fene oncology (GO) analysis identified that many of the target genes were involved in regulation of the cell cycle, cell migration, apoptosis, and drug responses. To confirm the microarray data, qPCR analysis was conducted for 10 selected genes based on previously reported associations with breast cancer and GO analysis. In conclusion, berberine exhibits inhibitory effects on breast cancer cells proliferation, which is likely mediated by alteration of gene expression profiles.

Functional Analysis With a Barcoder Yeast Gene Overexpression System

PubMed Central

Douglas, Alison C.; Smith, Andrew M.; Sharifpoor, Sara; Yan, Zhun; Durbic, Tanja; Heisler, Lawrence E.; Lee, Anna Y.; Ryan, Owen; Göttert, Hendrikje; Surendra, Anu; van Dyk, Dewald; Giaever, Guri; Boone, Charles; Nislow, Corey; Andrews, Brenda J.

2012-01-01

Systematic analysis of gene overexpression phenotypes provides an insight into gene function, enzyme targets, and biological pathways. Here, we describe a novel functional genomics platform that enables a highly parallel and systematic assessment of overexpression phenotypes in pooled cultures. First, we constructed a genome-level collection of ~5100 yeast barcoder strains, each of which carries a unique barcode, enabling pooled fitness assays with a barcode microarray or sequencing readout. Second, we constructed a yeast open reading frame (ORF) galactose-induced overexpression array by generating a genome-wide set of yeast transformants, each of which carries an individual plasmid-born and sequence-verified ORF derived from the Saccharomyces cerevisiae full-length EXpression-ready (FLEX) collection. We combined these collections genetically using synthetic genetic array methodology, generating ~5100 strains, each of which is barcoded and overexpresses a specific ORF, a set we termed “barFLEX.” Additional synthetic genetic array allows the barFLEX collection to be moved into different genetic backgrounds. As a proof-of-principle, we describe the properties of the barFLEX overexpression collection and its application in synthetic dosage lethality studies under different environmental conditions. PMID:23050238

Genome-wide microarray analysis leads to identification of genes in response to herbicide, metribuzin in wheat leaves.

PubMed

Pilcher, Whitney; Zandkamiri, Hana; Arceneaux, Kelly; Harrison, Stephen; Baisakh, Niranjan

2017-01-01

Herbicides are an important component of weed management in wheat, particularly in the southeastern US where weeds actively compete with wheat throughout the winter for nutrients and reduce tillering and ultimately the yield of the crop. Some wheat varieties are sensitive to metribuzin, a low-cost non-selective herbicide, leading to leaf chlorosis, stand loss, and decreased yield. Knowledge of the genetics of herbicide tolerance in wheat is very limited and most new varieties have not been screened for metribuzin tolerance. The identification of genes associated with metribuzin tolerance will lead to the development of molecular markers for use in screening breeding lines for metribuzin tolerance. AGS 2035 and AGS 2060 were identified as resistant and sensitive to metribuzin in several previous field screening experiments as well as controlled condition screening of nine varieties in the present study. Genome-wide transcriptome profiling of the genes in AGS 2035 and AGS 2060 through microarray analysis identified 169 and 127 genes to be significantly (2-fold, P>0.01) up- and down-regulated, respectively in response to metribuzin. Functional annotation revealed that genes involved in cell wall biosynthesis, photosynthesis and sucrose metabolism were highly responsive to metribuzin application. (Semi)quantitative RT-PCR of seven selected differentially expressed genes (DEGs) indicated that a gene coding for alkaline alpha-galactosidase 2 (AAG2) was specifically expressed in resistant varieties only after one and two weeks of metribuzin application. Integration of the DEGs into our ongoing mapping effort and identification of the genes within the QTL region showing significant association with resistance in future will aid in development of functional markers for metribuzin resistance.

Statistical analysis of an RNA titration series evaluates microarray precision and sensitivity on a whole-array basis

PubMed Central

Holloway, Andrew J; Oshlack, Alicia; Diyagama, Dileepa S; Bowtell, David DL; Smyth, Gordon K

2006-01-01

Background Concerns are often raised about the accuracy of microarray technologies and the degree of cross-platform agreement, but there are yet no methods which can unambiguously evaluate precision and sensitivity for these technologies on a whole-array basis. Results A methodology is described for evaluating the precision and sensitivity of whole-genome gene expression technologies such as microarrays. The method consists of an easy-to-construct titration series of RNA samples and an associated statistical analysis using non-linear regression. The method evaluates the precision and responsiveness of each microarray platform on a whole-array basis, i.e., using all the probes, without the need to match probes across platforms. An experiment is conducted to assess and compare four widely used microarray platforms. All four platforms are shown to have satisfactory precision but the commercial platforms are superior for resolving differential expression for genes at lower expression levels. The effective precision of the two-color platforms is improved by allowing for probe-specific dye-effects in the statistical model. The methodology is used to compare three data extraction algorithms for the Affymetrix platforms, demonstrating poor performance for the commonly used proprietary algorithm relative to the other algorithms. For probes which can be matched across platforms, the cross-platform variability is decomposed into within-platform and between-platform components, showing that platform disagreement is almost entirely systematic rather than due to measurement variability. Conclusion The results demonstrate good precision and sensitivity for all the platforms, but highlight the need for improved probe annotation. They quantify the extent to which cross-platform measures can be expected to be less accurate than within-platform comparisons for predicting disease progression or outcome. PMID:17118209

Identification of transcribed sequences in Arabidopsis thaliana by using high-resolution genome tiling arrays

PubMed Central

Stolc, Viktor; Samanta, Manoj Pratim; Tongprasit, Waraporn; Sethi, Himanshu; Liang, Shoudan; Nelson, David C.; Hegeman, Adrian; Nelson, Clark; Rancour, David; Bednarek, Sebastian; Ulrich, Eldon L.; Zhao, Qin; Wrobel, Russell L.; Newman, Craig S.; Fox, Brian G.; Phillips, George N.; Markley, John L.; Sussman, Michael R.

2005-01-01

Using a maskless photolithography method, we produced DNA oligonucleotide microarrays with probe sequences tiled throughout the genome of the plant Arabidopsis thaliana. RNA expression was determined for the complete nuclear, mitochondrial, and chloroplast genomes by tiling 5 million 36-mer probes. These probes were hybridized to labeled mRNA isolated from liquid grown T87 cells, an undifferentiated Arabidopsis cell culture line. Transcripts were detected from at least 60% of the nearly 26,330 annotated genes, which included 151 predicted genes that were not identified previously by a similar genome-wide hybridization study on four different cell lines. In comparison with previously published results with 25-mer tiling arrays produced by chromium masking-based photolithography technique, 36-mer oligonucleotide probes were found to be more useful in identifying intron–exon boundaries. Using two-dimensional HPLC tandem mass spectrometry, a small-scale proteomic analysis was performed with the same cells. A large amount of strongly hybridizing RNA was found in regions “antisense” to known genes. Similarity of antisense activities between the 25-mer and 36-mer data sets suggests that it is a reproducible and inherent property of the experiments. Transcription activities were also detected for many of the intergenic regions and the small RNAs, including tRNA, small nuclear RNA, small nucleolar RNA, and microRNA. Expression of tRNAs correlates with genome-wide amino acid usage. PMID:15755812

Identification of transcribed sequences in Arabidopsis thaliana by using high-resolution genome tiling arrays

NASA Technical Reports Server (NTRS)

Stolc, Viktor; Samanta, Manoj Pratim; Tongprasit, Waraporn; Sethi, Himanshu; Liang, Shoudan; Nelson, David C.; Hegeman, Adrian; Nelson, Clark; Rancour, David; Bednarek, Sebastian;

Genome-wide identification and expression analysis of glutathione S-transferase gene family in tomato: Gaining an insight to their physiological and stress-specific roles

PubMed Central

Islam, Shiful; Rahman, Iffat Ara; Islam, Tahmina

2017-01-01

Glutathione S-transferase (GST) refers to one of the major detoxifying enzymes that plays an important role in different abiotic and biotic stress modulation pathways of plant. The present study aimed to a comprehensive genome-wide functional characterization of GST genes and proteins in tomato (Solanum lycopersicum L.). The whole genome sequence analysis revealed the presence of 90 GST genes in tomato, the largest GST gene family reported till date. Eight segmental duplicated gene pairs might contribute significantly to the expansion of SlGST gene family. Based on phylogenetic analysis of tomato, rice, and Arabidopsis GST proteins, GST family members could be further divided into ten classes. Members of each orthologous class showed high conservancy among themselves. Tau and lambda are the major classes of tomato; while tau and phi are the major classes for rice and Arabidopsis. Chromosomal localization revealed highly uneven distribution of SlGST genes in 13 different chromosomes, where chromosome 9 possessed the highest number of genes. Based on publicly available microarray data, expression analysis of 30 available SlGST genes exhibited a differential pattern in all the analyzed tissues and developmental stages. Moreover, most of the members showed highly induced expression in response to multiple biotic and abiotic stress inducers that could be harmonized with the increase in total GST enzyme activity under several stress conditions. Activity of tomato GST could be enhanced further by using some positive modulators (safeners) that have been predicted through molecular docking of SlGSTU5 and ligands. Moreover, tomato GST proteins are predicted to interact with a lot of other glutathione synthesizing and utilizing enzymes such as glutathione peroxidase, glutathione reductase, glutathione synthetase and γ-glutamyltransferase. This comprehensive genome-wide analysis and expression profiling would provide a rational platform and possibility to explore the versatile role of GST genes in crop engineering. PMID:29095889

Comprehensive Genomic Analysis and Expression Profiling of Phospholipase C Gene Family during Abiotic Stresses and Development in Rice

PubMed Central

Singh, Amarjeet; Kanwar, Poonam; Pandey, Amita; Tyagi, Akhilesh K.; Sopory, Sudhir K.; Kapoor, Sanjay; Pandey, Girdhar K.

2013-01-01

Background Phospholipase C (PLC) is one of the major lipid hydrolysing enzymes, implicated in lipid mediated signaling. PLCs have been found to play a significant role in abiotic stress triggered signaling and developmental processes in various plant species. Genome wide identification and expression analysis have been carried out for this gene family in Arabidopsis, yet not much has been accomplished in crop plant rice. Methodology/Principal Findings An exhaustive in-silico exploration of rice genome using various online databases and tools resulted in the identification of nine PLC encoding genes. Based on sequence, motif and phylogenetic analysis rice PLC gene family could be divided into phosphatidylinositol-specific PLCs (PI-PLCs) and phosphatidylcholine- PLCs (PC-PLC or NPC) classes with four and five members, respectively. A comparative analysis revealed that PLCs are conserved in Arabidopsis (dicots) and rice (monocot) at gene structure and protein level but they might have evolved through a separate evolutionary path. Transcript profiling using gene chip microarray and quantitative RT-PCR showed that most of the PLC members expressed significantly and differentially under abiotic stresses (salt, cold and drought) and during various developmental stages with condition/stage specific and overlapping expression. This finding suggested an important role of different rice PLC members in abiotic stress triggered signaling and plant development, which was also supported by the presence of relevant cis-regulatory elements in their promoters. Sub-cellular localization of few selected PLC members in Nicotiana benthamiana and onion epidermal cells has provided a clue about their site of action and functional behaviour. Conclusion/Significance The genome wide identification, structural and expression analysis and knowledge of sub-cellular localization of PLC gene family envisage the functional characterization of these genes in crop plants in near future. PMID:23638098

Comprehensive genomic analysis and expression profiling of phospholipase C gene family during abiotic stresses and development in rice.

PubMed

Singh, Amarjeet; Kanwar, Poonam; Pandey, Amita; Tyagi, Akhilesh K; Sopory, Sudhir K; Kapoor, Sanjay; Pandey, Girdhar K

2013-01-01

Phospholipase C (PLC) is one of the major lipid hydrolysing enzymes, implicated in lipid mediated signaling. PLCs have been found to play a significant role in abiotic stress triggered signaling and developmental processes in various plant species. Genome wide identification and expression analysis have been carried out for this gene family in Arabidopsis, yet not much has been accomplished in crop plant rice. An exhaustive in-silico exploration of rice genome using various online databases and tools resulted in the identification of nine PLC encoding genes. Based on sequence, motif and phylogenetic analysis rice PLC gene family could be divided into phosphatidylinositol-specific PLCs (PI-PLCs) and phosphatidylcholine- PLCs (PC-PLC or NPC) classes with four and five members, respectively. A comparative analysis revealed that PLCs are conserved in Arabidopsis (dicots) and rice (monocot) at gene structure and protein level but they might have evolved through a separate evolutionary path. Transcript profiling using gene chip microarray and quantitative RT-PCR showed that most of the PLC members expressed significantly and differentially under abiotic stresses (salt, cold and drought) and during various developmental stages with condition/stage specific and overlapping expression. This finding suggested an important role of different rice PLC members in abiotic stress triggered signaling and plant development, which was also supported by the presence of relevant cis-regulatory elements in their promoters. Sub-cellular localization of few selected PLC members in Nicotiana benthamiana and onion epidermal cells has provided a clue about their site of action and functional behaviour. The genome wide identification, structural and expression analysis and knowledge of sub-cellular localization of PLC gene family envisage the functional characterization of these genes in crop plants in near future.

Combined analysis of DNA methylome and transcriptome reveal novel candidate genes with susceptibility to bovine Staphylococcus aureus subclinical mastitis.

PubMed

Song, Minyan; He, Yanghua; Zhou, Huangkai; Zhang, Yi; Li, Xizhi; Yu, Ying

2016-07-14

Subclinical mastitis is a widely spread disease of lactating cows. Its major pathogen is Staphylococcus aureus (S. aureus). In this study, we performed genome-wide integrative analysis of DNA methylation and transcriptional expression to identify candidate genes and pathways relevant to bovine S. aureus subclinical mastitis. The genome-scale DNA methylation profiles of peripheral blood lymphocytes in cows with S. aureus subclinical mastitis (SA group) and healthy controls (CK) were generated by methylated DNA immunoprecipitation combined with microarrays. We identified 1078 differentially methylated genes in SA cows compared with the controls. By integrating DNA methylation and transcriptome data, 58 differentially methylated genes were shared with differently expressed genes, in which 20.7% distinctly hypermethylated genes showed down-regulated expression in SA versus CK, whereas 14.3% dramatically hypomethylated genes showed up-regulated expression. Integrated pathway analysis suggested that these genes were related to inflammation, ErbB signalling pathway and mismatch repair. Further functional analysis revealed that three genes, NRG1, MST1 and NAT9, were strongly correlated with the progression of S. aureus subclinical mastitis and could be used as powerful biomarkers for the improvement of bovine mastitis resistance. Our studies lay the groundwork for epigenetic modification and mechanistic studies on susceptibility of bovine mastitis.

Combined analysis of DNA methylome and transcriptome reveal novel candidate genes with susceptibility to bovine Staphylococcus aureus subclinical mastitis

PubMed Central

Song, Minyan; He, Yanghua; Zhou, Huangkai; Zhang, Yi; Li, Xizhi; Yu, Ying

2016-01-01

Subclinical mastitis is a widely spread disease of lactating cows. Its major pathogen is Staphylococcus aureus (S. aureus). In this study, we performed genome-wide integrative analysis of DNA methylation and transcriptional expression to identify candidate genes and pathways relevant to bovine S. aureus subclinical mastitis. The genome-scale DNA methylation profiles of peripheral blood lymphocytes in cows with S. aureus subclinical mastitis (SA group) and healthy controls (CK) were generated by methylated DNA immunoprecipitation combined with microarrays. We identified 1078 differentially methylated genes in SA cows compared with the controls. By integrating DNA methylation and transcriptome data, 58 differentially methylated genes were shared with differently expressed genes, in which 20.7% distinctly hypermethylated genes showed down-regulated expression in SA versus CK, whereas 14.3% dramatically hypomethylated genes showed up-regulated expression. Integrated pathway analysis suggested that these genes were related to inflammation, ErbB signalling pathway and mismatch repair. Further functional analysis revealed that three genes, NRG1, MST1 and NAT9, were strongly correlated with the progression of S. aureus subclinical mastitis and could be used as powerful biomarkers for the improvement of bovine mastitis resistance. Our studies lay the groundwork for epigenetic modification and mechanistic studies on susceptibility of bovine mastitis. PMID:27411928

Chemiluminescence microarrays in analytical chemistry: a critical review.

PubMed

Seidel, Michael; Niessner, Reinhard

2014-09-01

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

Characteristic Markers of the WNT Signaling Pathways Are Differentially Expressed in Osteoarthritic Cartilage

PubMed Central

Dehne, T.; Lindahl, A.; Brittberg, M.; Pruss, A.; Ringe, J.; Sittinger, M.; Karlsson, C.

2012-01-01

Objective: It is well known that expression of markers for WNT signaling is dysregulated in osteoarthritic (OA) bone. However, it is still not fully known if the expression of these markers also is affected in OA cartilage. The aim of this study was therefore to examine this issue. Methods: Human cartilage biopsies from OA and control donors were subjected to genome-wide oligonucleotide microarrays. Genes involved in WNT signaling were selected using the BioRetis database, KEGG pathway analysis was searched using DAVID software tools, and cluster analysis was performed using Genesis software. Results from the microarray analysis were verified using quantitative real-time PCR and immunohistochemistry. In order to study the impact of cytokines for the dysregulated WNT signaling, OA and control chondrocytes were stimulated with interleukin-1 and analyzed with real-time PCR for their expression of WNT-related genes. Results: Several WNT markers displayed a significantly altered expression in OA compared to normal cartilage. Interestingly, inhibitors of the canonical and planar cell polarity WNT signaling pathways displayed significantly increased expression in OA cartilage, while the Ca2+/WNT signaling pathway was activated. Both real-time PCR and immunohistochemistry verified the microarray results. Real-time PCR analysis demonstrated that interleukin-1 upregulated expression of important WNT markers. Conclusions: WNT signaling is significantly affected in OA cartilage. The result suggests that both the canonical and planar cell polarity WNT signaling pathways were partly inhibited while the Ca2+/WNT pathway was activated in OA cartilage. PMID:26069618

DNA microarray-mediated transcriptional profiling of avian pathogenic Escherichia coli O2 strain E058 during its infection of chicken.

PubMed

Gao, Qingqing; Xia, Le; Liu, Juanhua; Wang, Xiaobo; Gao, Song; Liu, Xiufan

2016-11-01

Avian pathogenic Escherichia coli (APEC) cause typical extraintestinal infections in poultry, including acute fatal septicemia, subacute pericarditis, and airsacculitis. These bacteria most often infect chickens, turkeys, ducks, and other avian species, and therefore pose a significant economic burden on the poultry industry worldwide. Few studies have analyzed the genome-wide transcriptional profile of APEC during infection in vivo. In this study, we examined the genome-wide transcriptional response of APEC O2 strain E058 in an in vivo chicken infection model to better understand the factors necessary for APEC colonization, growth, and survival in vivo. An Affymetrix multigenome DNA microarray, which contains most of the genomic open reading frames of E. coli K-12 strain MG1655, uropathogenic E. coli strain CFT073, and E. coli O157:H7 strain EDL 933, was used to profile the gene expression in APEC E058. We identified the in vivo transcriptional response of APEC E058 bacteria collected directly from the blood of infected chickens. Significant differences in expression levels were detected between the in vivo expression profile and the in vitro expression profile in LB medium. The genes highly expressed during infection were involved in metabolism, iron acquisition or transport, virulence, response to stress, and biological regulation. The reliability of the microarray data was confirmed by performing quantitative real-time PCR on 12 representative genes. Moreover, several significantly upregulated genes, including yjiY, sodA, phoB and spy, were selected to study their role in APEC pathogenesis. The data will help to better understand the mechanisms of APEC pathogenesis. Copyright © 2016 Elsevier Ltd. All rights reserved.

Evolution and structural diversification of Nictaba-like lectin genes in food crops with a focus on soybean (Glycine max).

PubMed

Van Holle, Sofie; Rougé, Pierre; Van Damme, Els J M

2017-03-01

The Nictaba family groups all proteins that show homology to Nictaba, the tobacco lectin. So far, Nictaba and an Arabidopsis thaliana homologue have been shown to be implicated in the plant stress response. The availability of more than 50 sequenced plant genomes provided the opportunity for a genome-wide identification of Nictaba -like genes in 15 species, representing members of the Fabaceae, Poaceae, Solanaceae, Musaceae, Arecaceae, Malvaceae and Rubiaceae. Additionally, phylogenetic relationships between the different species were explored. Furthermore, this study included domain organization analysis, searching for orthologous genes in the legume family and transcript profiling of the Nictaba -like lectin genes in soybean. Using a combination of BLASTp, InterPro analysis and hidden Markov models, the genomes of Medicago truncatula , Cicer arietinum , Lotus japonicus , Glycine max , Cajanus cajan , Phaseolus vulgaris , Theobroma cacao , Solanum lycopersicum , Solanum tuberosum , Coffea canephora , Oryza sativa , Zea mays, Sorghum bicolor , Musa acuminata and Elaeis guineensis were searched for Nictaba -like genes. Phylogenetic analysis was performed using RAxML and additional protein domains in the Nictaba-like sequences were identified using InterPro. Expression analysis of the soybean Nictaba -like genes was investigated using microarray data. Nictaba -like genes were identified in all studied species and analysis of the duplication events demonstrated that both tandem and segmental duplication contributed to the expansion of the Nictaba gene family in angiosperms. The single-domain Nictaba protein and the multi-domain F-box Nictaba architectures are ubiquitous among all analysed species and microarray analysis revealed differential expression patterns for all soybean Nictaba-like genes. Taken together, the comparative genomics data contributes to our understanding of the Nictaba -like gene family in species for which the occurrence of Nictaba domains had not yet been investigated. Given the ubiquitous nature of these genes, they have probably acquired new functions over time and are expected to take on various roles in plant development and defence. © The Author 2017. Published by Oxford University Press on behalf of the Annals of Botany Company. All rights reserved. For Permissions, please email: journals.permissions@oup.com

Fish and chips: Various methodologies demonstrate utility of a 16,006-gene salmonid microarray

PubMed Central

von Schalburg, Kristian R; Rise, Matthew L; Cooper, Glenn A; Brown, Gordon D; Gibbs, A Ross; Nelson, Colleen C; Davidson, William S; Koop, Ben F

2005-01-01

Background We have developed and fabricated a salmonid microarray containing cDNAs representing 16,006 genes. The genes spotted on the array have been stringently selected from Atlantic salmon and rainbow trout expressed sequence tag (EST) databases. The EST databases presently contain over 300,000 sequences from over 175 salmonid cDNA libraries derived from a wide variety of tissues and different developmental stages. In order to evaluate the utility of the microarray, a number of hybridization techniques and screening methods have been developed and tested. Results We have analyzed and evaluated the utility of a microarray containing 16,006 (16K) salmonid cDNAs in a variety of potential experimental settings. We quantified the amount of transcriptome binding that occurred in cross-species, organ complexity and intraspecific variation hybridization studies. We also developed a methodology to rapidly identify and confirm the contents of a bacterial artificial chromosome (BAC) library containing Atlantic salmon genomic DNA. Conclusion We validate and demonstrate the usefulness of the 16K microarray over a wide range of teleosts, even for transcriptome targets from species distantly related to salmonids. We show the potential of the use of the microarray in a variety of experimental settings through hybridization studies that examine the binding of targets derived from different organs and tissues. Intraspecific variation in transcriptome expression is evaluated and discussed. Finally, BAC hybridizations are demonstrated as a rapid and accurate means to identify gene content. PMID:16164747

Genomic resources for songbird research and their use in characterizing gene expression during brain development

PubMed Central

Li, XiaoChing; Wang, Xiu-Jie; Tannenhauser, Jonathan; Podell, Sheila; Mukherjee, Piali; Hertel, Moritz; Biane, Jeremy; Masuda, Shoko; Nottebohm, Fernando; Gaasterland, Terry

2007-01-01

Vocal learning and neuronal replacement have been studied extensively in songbirds, but until recently, few molecular and genomic tools for songbird research existed. Here we describe new molecular/genomic resources developed in our laboratory. We made cDNA libraries from zebra finch (Taeniopygia guttata) brains at different developmental stages. A total of 11,000 cDNA clones from these libraries, representing 5,866 unique gene transcripts, were randomly picked and sequenced from the 3′ ends. A web-based database was established for clone tracking, sequence analysis, and functional annotations. Our cDNA libraries were not normalized. Sequencing ESTs without normalization produced many developmental stage-specific sequences, yielding insights into patterns of gene expression at different stages of brain development. In particular, the cDNA library made from brains at posthatching day 30–50, corresponding to the period of rapid song system development and song learning, has the most diverse and richest set of genes expressed. We also identified five microRNAs whose sequences are highly conserved between zebra finch and other species. We printed cDNA microarrays and profiled gene expression in the high vocal center of both adult male zebra finches and canaries (Serinus canaria). Genes differentially expressed in the high vocal center were identified from the microarray hybridization results. Selected genes were validated by in situ hybridization. Networks among the regulated genes were also identified. These resources provide songbird biologists with tools for genome annotation, comparative genomics, and microarray gene expression analysis. PMID:17426146

DNA Microarray Highlights Nrf2-Mediated Neuron Protection Targeted by Wasabi-Derived Isothiocyanates in IMR-32 Cells

PubMed Central

Trio, Phoebe Zapanta; Fujisaki, Satoru; Tanigawa, Shunsuke; Hisanaga, Ayami; Sakao, Kozue; Hou, De-Xing

2016-01-01

6-(Methylsulfinyl)hexyl isothiocyanate (6-MSITC), 6-(methylthio)hexyl isothiocyanate (6-MTITC), and 4-(methylsulfinyl)butyl isothiocyanate (4-MSITC) are isothiocyanate (ITC) bioactive compounds from Japanese Wasabi. Previous in vivo studies highlighted the neuroprotective potential of ITCs since ITCs enhance the production of antioxidant-related enzymes. Thus, in this present study, a genome-wide DNA microarray analysis was designed to profile gene expression changes in a neuron cell line, IMR-32, stimulated by these ITCs. Among these ITCs, 6-MSITC caused the expression changes of most genes (263), of which 100 genes were upregulated and 163 genes were downregulated. Gene categorization showed that most of the differentially expressed genes are involved in oxidative stress response, and pathway analysis further revealed that Nrf2-mediated oxidative stress pathway is the top of the ITC-modulated signaling pathway. Finally, real-time polymerase chain reaction (PCR) and Western blotting confirmed the gene expression and protein products of the major targets by ITCs. Taken together, Wasabi-derived ITCs might target the Nrf2-mediated oxidative stress pathway to exert neuroprotective effects. PMID:27547033

DNA Microarray Highlights Nrf2-Mediated Neuron Protection Targeted by Wasabi-Derived Isothiocyanates in IMR-32 Cells.

PubMed

Trio, Phoebe Zapanta; Fujisaki, Satoru; Tanigawa, Shunsuke; Hisanaga, Ayami; Sakao, Kozue; Hou, De-Xing

2016-01-01

6-(Methylsulfinyl)hexyl isothiocyanate (6-MSITC), 6-(methylthio)hexyl isothiocyanate (6-MTITC), and 4-(methylsulfinyl)butyl isothiocyanate (4-MSITC) are isothiocyanate (ITC) bioactive compounds from Japanese Wasabi. Previous in vivo studies highlighted the neuroprotective potential of ITCs since ITCs enhance the production of antioxidant-related enzymes. Thus, in this present study, a genome-wide DNA microarray analysis was designed to profile gene expression changes in a neuron cell line, IMR-32, stimulated by these ITCs. Among these ITCs, 6-MSITC caused the expression changes of most genes (263), of which 100 genes were upregulated and 163 genes were downregulated. Gene categorization showed that most of the differentially expressed genes are involved in oxidative stress response, and pathway analysis further revealed that Nrf2-mediated oxidative stress pathway is the top of the ITC-modulated signaling pathway. Finally, real-time polymerase chain reaction (PCR) and Western blotting confirmed the gene expression and protein products of the major targets by ITCs. Taken together, Wasabi-derived ITCs might target the Nrf2-mediated oxidative stress pathway to exert neuroprotective effects.

Genome-Wide Association Study Identifies Novel Loci Associated With Diisocyanate-Induced Occupational Asthma

PubMed Central

Yucesoy, Berran; Kaufman, Kenneth M.; Lummus, Zana L.; Weirauch, Matthew T.; Zhang, Ge; Cartier, André; Boulet, Louis-Philippe; Sastre, Joaquin; Quirce, Santiago; Tarlo, Susan M.; Cruz, Maria-Jesus; Munoz, Xavier; Harley, John B.; Bernstein, David I.

2015-01-01

Diisocyanates, reactive chemicals used to produce polyurethane products, are the most common causes of occupational asthma. The aim of this study is to identify susceptibility gene variants that could contribute to the pathogenesis of diisocyanate asthma (DA) using a Genome-Wide Association Study (GWAS) approach. Genome-wide single nucleotide polymorphism (SNP) genotyping was performed in 74 diisocyanate-exposed workers with DA and 824 healthy controls using Omni-2.5 and Omni-5 SNP microarrays. We identified 11 SNPs that exceeded genome-wide significance; the strongest association was for the rs12913832 SNP located on chromosome 15, which has been mapped to the HERC2 gene (p = 6.94 × 10−14). Strong associations were also found for SNPs near the ODZ3 and CDH17 genes on chromosomes 4 and 8 (rs908084, p = 8.59 × 10−9 and rs2514805, p = 1.22 × 10−8, respectively). We also prioritized 38 SNPs with suggestive genome-wide significance (p < 1 × 10−6). Among them, 17 SNPs map to the PITPNC1, ACMSD, ZBTB16, ODZ3, and CDH17 gene loci. Functional genomics data indicate that 2 of the suggestive SNPs (rs2446823 and rs2446824) are located within putative binding sites for the CCAAT/Enhancer Binding Protein (CEBP) and Hepatocyte Nuclear Factor 4, Alpha transcription factors (TFs), respectively. This study identified SNPs mapping to the HERC2, CDH17, and ODZ3 genes as potential susceptibility loci for DA. Pathway analysis indicated that these genes are associated with antigen processing and presentation, and other immune pathways. Overlap of 2 suggestive SNPs with likely TF binding sites suggests possible roles in disruption of gene regulation. These results provide new insights into the genetic architecture of DA and serve as a basis for future functional and mechanistic studies. PMID:25918132

Time-course microarray analysis for identifying candidate genes involved in obesity-associated pathological changes in the mouse colon.

PubMed

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 log 2 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.

Wide screening of phage-displayed libraries identifies immune targets in planta.

PubMed

Rioja, Cristina; Van Wees, Saskia C; Charlton, Keith A; Pieterse, Corné M J; Lorenzo, Oscar; García-Sánchez, Susana

2013-01-01

Microbe-Associated Molecular Patterns and virulence effectors are recognized by plants as a first step to mount a defence response against potential pathogens. This recognition involves a large family of extracellular membrane receptors and other immune proteins located in different sub-cellular compartments. We have used phage-display technology to express and select for Arabidopsis proteins able to bind bacterial pathogens. To rapidly identify microbe-bound phage, we developed a monitoring method based on microarrays. This combined strategy allowed for a genome-wide screening of plant proteins involved in pathogen perception. Two phage libraries for high-throughput selection were constructed from cDNA of plants infected with Pseudomonas aeruginosa PA14, or from combined samples of the virulent isolate DC3000 of Pseudomonas syringae pv. tomato and its avirulent variant avrRpt2. These three pathosystems represent different degrees in the specificity of plant-microbe interactions. Libraries cover up to 2 × 10(7) different plant transcripts that can be displayed as functional proteins on the surface of T7 bacteriophage. A number of these were selected in a bio-panning assay for binding to Pseudomonas cells. Among the selected clones we isolated the ethylene response factor ATERF-1, which was able to bind the three bacterial strains in competition assays. ATERF-1 was rapidly exported from the nucleus upon infiltration of either alive or heat-killed Pseudomonas. Moreover, aterf-1 mutants exhibited enhanced susceptibility to infection. These findings suggest that ATERF-1 contains a microbe-recognition domain with a role in plant defence. To identify other putative pathogen-binding proteins on a genome-wide scale, the copy number of selected-vs.-total clones was compared by hybridizing phage cDNAs with Arabidopsis microarrays. Microarray analysis revealed a set of 472 candidates with significant fold change. Within this set defence-related genes, including well-known targets of bacterial effectors, are over-represented. Other genes non-previously related to defence can be associated through this study with general or strain-specific recognition of Pseudomonas.

Parallel human genome analysis: microarray-based expression monitoring of 1000 genes.

PubMed Central

Schena, M; Shalon, D; Heller, R; Chai, A; Brown, P O; Davis, R W

1996-01-01

Microarrays containing 1046 human cDNAs of unknown sequence were printed on glass with high-speed robotics. These 1.0-cm2 DNA "chips" were used to quantitatively monitor differential expression of the cognate human genes using a highly sensitive two-color hybridization assay. Array elements that displayed differential expression patterns under given experimental conditions were characterized by sequencing. The identification of known and novel heat shock and phorbol ester-regulated genes in human T cells demonstrates the sensitivity of the assay. Parallel gene analysis with microarrays provides a rapid and efficient method for large-scale human gene discovery. Images Fig. 1 Fig. 2 Fig. 3 PMID:8855227

Genomic paradigms for food-borne enteric pathogen analysis at the USFDA: case studies highlighting method utility, integration and resolution.

PubMed

Elkins, C A; Kotewicz, M L; Jackson, S A; Lacher, D W; Abu-Ali, G S; Patel, I R

2013-01-01

Modern risk control and food safety practices involving food-borne bacterial pathogens are benefiting from new genomic technologies for rapid, yet highly specific, strain characterisations. Within the United States Food and Drug Administration (USFDA) Center for Food Safety and Applied Nutrition (CFSAN), optical genome mapping and DNA microarray genotyping have been used for several years to quickly assess genomic architecture and gene content, respectively, for outbreak strain subtyping and to enhance retrospective trace-back analyses. The application and relative utility of each method varies with outbreak scenario and the suspect pathogen, with comparative analytical power enhanced by database scale and depth. Integration of these two technologies allows high-resolution scrutiny of the genomic landscapes of enteric food-borne pathogens with notable examples including Shiga toxin-producing Escherichia coli (STEC) and Salmonella enterica serovars from a variety of food commodities. Moreover, the recent application of whole genome sequencing technologies to food-borne pathogen outbreaks and surveillance has enhanced resolution to the single nucleotide scale. This new wealth of sequence data will support more refined next-generation custom microarray designs, targeted re-sequencing and "genomic signature recognition" approaches involving a combination of genes and single nucleotide polymorphism detection to distil strain-specific fingerprinting to a minimised scale. This paper examines the utility of microarrays and optical mapping in analysing outbreaks, reviews best practices and the limits of these technologies for pathogen differentiation, and it considers future integration with whole genome sequencing efforts.

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

PubMed

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

2003-10-01

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

Genome-wide analysis of the WRKY gene family in cotton.

PubMed

Dou, Lingling; Zhang, Xiaohong; Pang, Chaoyou; Song, Meizhen; Wei, Hengling; Fan, Shuli; Yu, Shuxun

2014-12-01

WRKY proteins are major transcription factors involved in regulating plant growth and development. Although many studies have focused on the functional identification of WRKY genes, our knowledge concerning many areas of WRKY gene biology is limited. For example, in cotton, the phylogenetic characteristics, global expression patterns, molecular mechanisms regulating expression, and target genes/pathways of WRKY genes are poorly characterized. Therefore, in this study, we present a genome-wide analysis of the WRKY gene family in cotton (Gossypium raimondii and Gossypium hirsutum). We identified 116 WRKY genes in G. raimondii from the completed genome sequence, and we cloned 102 WRKY genes in G. hirsutum. Chromosomal location analysis indicated that WRKY genes in G. raimondii evolved mainly from segmental duplication followed by tandem amplifications. Phylogenetic analysis of alga, bryophyte, lycophyta, monocot and eudicot WRKY domains revealed family member expansion with increasing complexity of the plant body. Microarray, expression profiling and qRT-PCR data revealed that WRKY genes in G. hirsutum may regulate the development of fibers, anthers, tissues (roots, stems, leaves and embryos), and are involved in the response to stresses. Expression analysis showed that most group II and III GhWRKY genes are highly expressed under diverse stresses. Group I members, representing the ancestral form, seem to be insensitive to abiotic stress, with low expression divergence. Our results indicate that cotton WRKY genes might have evolved by adaptive duplication, leading to sensitivity to diverse stresses. This study provides fundamental information to inform further analysis and understanding of WRKY gene functions in cotton species.

Restriction to gene flow is associated with changes in the molecular basis of pyrethroid resistance in the malaria vector Anopheles funestus

PubMed Central

Barnes, Kayla G.; Irving, Helen; Chiumia, Martin; Mzilahowa, Themba; Coleman, Michael; Hemingway, Janet; Wondji, Charles S.

2017-01-01

Resistance to pyrethroids, the sole insecticide class recommended for treating bed nets, threatens the control of major malaria vectors, including Anopheles funestus. Effective management of resistance requires an understanding of the dynamics and mechanisms driving resistance. Here, using genome-wide transcription and genetic diversity analyses, we show that a shift in the molecular basis of pyrethroid resistance in southern African populations of this species is associated with a restricted gene flow. Across the most highly endemic and densely populated regions in Malawi, An. funestus is resistant to pyrethroids, carbamates, and organochlorides. Genome-wide microarray-based transcription analysis identified overexpression of cytochrome P450 genes as the main mechanism driving this resistance. The most up-regulated genes include cytochrome P450s (CYP) CYP6P9a, CYP6P9b and CYP6M7. However, a significant shift in the overexpression profile of these genes was detected across a south/north transect, with CYP6P9a and CYP6P9b more highly overexpressed in the southern resistance front and CYP6M7 predominant in the northern front. A genome-wide genetic structure analysis of southern African populations of An. funestus from Zambia, Malawi, and Mozambique revealed a restriction of gene flow between populations, in line with the geographical variation observed in the transcriptomic analysis. Genetic polymorphism analysis of the three key resistance genes, CYP6P9a, CYP6P9b, and CYP6M7, support barriers to gene flow that are shaping the underlying molecular basis of pyrethroid resistance across southern Africa. This barrier to gene flow is likely to impact the design and implementation of resistance management strategies in the region. PMID:28003461

A pooling-based approach to mapping genetic variants associated with DNA methylation

PubMed Central

Kaplow, Irene M.; MacIsaac, Julia L.; Mah, Sarah M.; McEwen, Lisa M.; Kobor, Michael S.; Fraser, Hunter B.

2015-01-01

DNA methylation is an epigenetic modification that plays a key role in gene regulation. Previous studies have investigated its genetic basis by mapping genetic variants that are associated with DNA methylation at specific sites, but these have been limited to microarrays that cover <2% of the genome and cannot account for allele-specific methylation (ASM). Other studies have performed whole-genome bisulfite sequencing on a few individuals, but these lack statistical power to identify variants associated with DNA methylation. We present a novel approach in which bisulfite-treated DNA from many individuals is sequenced together in a single pool, resulting in a truly genome-wide map of DNA methylation. Compared to methods that do not account for ASM, our approach increases statistical power to detect associations while sharply reducing cost, effort, and experimental variability. As a proof of concept, we generated deep sequencing data from a pool of 60 human cell lines; we evaluated almost twice as many CpGs as the largest microarray studies and identified more than 2000 genetic variants associated with DNA methylation. We found that these variants are highly enriched for associations with chromatin accessibility and CTCF binding but are less likely to be associated with traits indirectly linked to DNA, such as gene expression and disease phenotypes. In summary, our approach allows genome-wide mapping of genetic variants associated with DNA methylation in any tissue of any species, without the need for individual-level genotype or methylation data. PMID:25910490

A pooling-based approach to mapping genetic variants associated with DNA methylation

DOE PAGES

Kaplow, Irene M.; MacIsaac, Julia L.; Mah, Sarah M.; ...

2015-04-24

DNA methylation is an epigenetic modification that plays a key role in gene regulation. Previous studies have investigated its genetic basis by mapping genetic variants that are associated with DNA methylation at specific sites, but these have been limited to microarrays that cover <2% of the genome and cannot account for allele-specific methylation (ASM). Other studies have performed whole-genome bisulfite sequencing on a few individuals, but these lack statistical power to identify variants associated with DNA methylation. We present a novel approach in which bisulfite-treated DNA from many individuals is sequenced together in a single pool, resulting in a trulymore » genome-wide map of DNA methylation. Compared to methods that do not account for ASM, our approach increases statistical power to detect associations while sharply reducing cost, effort, and experimental variability. As a proof of concept, we generated deep sequencing data from a pool of 60 human cell lines; we evaluated almost twice as many CpGs as the largest microarray studies and identified more than 2000 genetic variants associated with DNA methylation. Here we found that these variants are highly enriched for associations with chromatin accessibility and CTCF binding but are less likely to be associated with traits indirectly linked to DNA, such as gene expression and disease phenotypes. In summary, our approach allows genome-wide mapping of genetic variants associated with DNA methylation in any tissue of any species, without the need for individual-level genotype or methylation data.« less

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

Kaplow, Irene M.; MacIsaac, Julia L.; Mah, Sarah M.

DNA methylation is an epigenetic modification that plays a key role in gene regulation. Previous studies have investigated its genetic basis by mapping genetic variants that are associated with DNA methylation at specific sites, but these have been limited to microarrays that cover <2% of the genome and cannot account for allele-specific methylation (ASM). Other studies have performed whole-genome bisulfite sequencing on a few individuals, but these lack statistical power to identify variants associated with DNA methylation. We present a novel approach in which bisulfite-treated DNA from many individuals is sequenced together in a single pool, resulting in a trulymore » genome-wide map of DNA methylation. Compared to methods that do not account for ASM, our approach increases statistical power to detect associations while sharply reducing cost, effort, and experimental variability. As a proof of concept, we generated deep sequencing data from a pool of 60 human cell lines; we evaluated almost twice as many CpGs as the largest microarray studies and identified more than 2000 genetic variants associated with DNA methylation. Here we found that these variants are highly enriched for associations with chromatin accessibility and CTCF binding but are less likely to be associated with traits indirectly linked to DNA, such as gene expression and disease phenotypes. In summary, our approach allows genome-wide mapping of genetic variants associated with DNA methylation in any tissue of any species, without the need for individual-level genotype or methylation data.« less

Cloud-scale genomic signals processing classification analysis for gene expression microarray data.

PubMed

Harvey, Benjamin; Soo-Yeon Ji

2014-01-01

As microarray data available to scientists continues to increase in size and complexity, it has become overwhelmingly important to find multiple ways to bring inference though analysis of DNA/mRNA sequence data that is useful to scientists. Though there have been many attempts to elucidate the issue of bringing forth biological inference by means of wavelet preprocessing and classification, there has not been a research effort that focuses on a cloud-scale classification analysis of microarray data using Wavelet thresholding in a Cloud environment to identify significantly expressed features. This paper proposes a novel methodology that uses Wavelet based Denoising to initialize a threshold for determination of significantly expressed genes for classification. Additionally, this research was implemented and encompassed within cloud-based distributed processing environment. The utilization of Cloud computing and Wavelet thresholding was used for the classification 14 tumor classes from the Global Cancer Map (GCM). The results proved to be more accurate than using a predefined p-value for differential expression classification. This novel methodology analyzed Wavelet based threshold features of gene expression in a Cloud environment, furthermore classifying the expression of samples by analyzing gene patterns, which inform us of biological processes. Moreover, enabling researchers to face the present and forthcoming challenges that may arise in the analysis of data in functional genomics of large microarray datasets.

Integrated analysis of epigenomic and genomic changes by DNA methylation dependent mechanisms provides potential novel biomarkers for prostate cancer.

PubMed

White-Al Habeeb, Nicole M A; Ho, Linh T; Olkhov-Mitsel, Ekaterina; Kron, Ken; Pethe, Vaijayanti; Lehman, Melanie; Jovanovic, Lidija; Fleshner, Neil; van der Kwast, Theodorus; Nelson, Colleen C; Bapat, Bharati

2014-09-15

Epigenetic silencing mediated by CpG methylation is a common feature of many cancers. Characterizing aberrant DNA methylation changes associated with tumor progression may identify potential prognostic markers for prostate cancer (PCa). We treated two PCa cell lines, 22Rv1 and DU-145 with the demethylating agent 5-Aza 2'-deoxycitidine (DAC) and global methylation status was analyzed by performing methylation-sensitive restriction enzyme based differential methylation hybridization strategy followed by genome-wide CpG methylation array profiling. In addition, we examined gene expression changes using a custom microarray. Gene Set Enrichment Analysis (GSEA) identified the most significantly dysregulated pathways. In addition, we assessed methylation status of candidate genes that showed reduced CpG methylation and increased gene expression after DAC treatment, in Gleason score (GS) 8 vs. GS6 patients using three independent cohorts of patients; the publically available The Cancer Genome Atlas (TCGA) dataset, and two separate patient cohorts. Our analysis, by integrating methylation and gene expression in PCa cell lines, combined with patient tumor data, identified novel potential biomarkers for PCa patients. These markers may help elucidate the pathogenesis of PCa and represent potential prognostic markers for PCa patients.

Analysis of the Saccharomyces cerevisiae pan-genome reveals a pool of copy number variants distributed in diverse yeast strains from differing industrial environments

PubMed Central

Dunn, Barbara; Richter, Chandra; Kvitek, Daniel J.; Pugh, Tom; Sherlock, Gavin

2012-01-01

Although the budding yeast Saccharomyces cerevisiae is arguably one of the most well-studied organisms on earth, the genome-wide variation within this species—i.e., its “pan-genome”—has been less explored. We created a multispecies microarray platform containing probes covering the genomes of several Saccharomyces species: S. cerevisiae, including regions not found in the standard laboratory S288c strain, as well as the mitochondrial and 2-μm circle genomes–plus S. paradoxus, S. mikatae, S. kudriavzevii, S. uvarum, S. kluyveri, and S. castellii. We performed array-Comparative Genomic Hybridization (aCGH) on 83 different S. cerevisiae strains collected across a wide range of habitats; of these, 69 were commercial wine strains, while the remaining 14 were from a diverse set of other industrial and natural environments. We observed interspecific hybridization events, introgression events, and pervasive copy number variation (CNV) in all but a few of the strains. These CNVs were distributed throughout the strains such that they did not produce any clear phylogeny, suggesting extensive mating in both industrial and wild strains. To validate our results and to determine whether apparently similar introgressions and CNVs were identical by descent or recurrent, we also performed whole-genome sequencing on nine of these strains. These data may help pinpoint genomic regions involved in adaptation to different industrial milieus, as well as shed light on the course of domestication of S. cerevisiae. PMID:22369888

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

PubMed

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

2013-01-01

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

The future of microarray technology: networking the genome search.

PubMed

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

2005-10-01

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

CoryneRegNet: An ontology-based data warehouse of corynebacterial transcription factors and regulatory networks

PubMed Central

Baumbach, Jan; Brinkrolf, Karina; Czaja, Lisa F; Rahmann, Sven; Tauch, Andreas

2006-01-01

Background The application of DNA microarray technology in post-genomic analysis of bacterial genome sequences has allowed the generation of huge amounts of data related to regulatory networks. This data along with literature-derived knowledge on regulation of gene expression has opened the way for genome-wide reconstruction of transcriptional regulatory networks. These large-scale reconstructions can be converted into in silico models of bacterial cells that allow a systematic analysis of network behavior in response to changing environmental conditions. Description CoryneRegNet was designed to facilitate the genome-wide reconstruction of transcriptional regulatory networks of corynebacteria relevant in biotechnology and human medicine. During the import and integration process of data derived from experimental studies or literature knowledge CoryneRegNet generates links to genome annotations, to identified transcription factors and to the corresponding cis-regulatory elements. CoryneRegNet is based on a multi-layered, hierarchical and modular concept of transcriptional regulation and was implemented by using the relational database management system MySQL and an ontology-based data structure. Reconstructed regulatory networks can be visualized by using the yFiles JAVA graph library. As an application example of CoryneRegNet, we have reconstructed the global transcriptional regulation of a cellular module involved in SOS and stress response of corynebacteria. Conclusion CoryneRegNet is an ontology-based data warehouse that allows a pertinent data management of regulatory interactions along with the genome-scale reconstruction of transcriptional regulatory networks. These models can further be combined with metabolic networks to build integrated models of cellular function including both metabolism and its transcriptional regulation. PMID:16478536

DNA microarrays of baculovirus genomes: differential expression of viral genes in two susceptible insect cell lines.

PubMed

Yamagishi, J; Isobe, R; Takebuchi, T; Bando, H

2003-03-01

We describe, for the first time, the generation of a viral DNA chip for simultaneous expression measurements of nearly all known open reading frames (ORFs) in the best-studied members of the family Baculoviridae, Autographa californica multiple nucleopolyhedrovirus (AcMNPV) and Bombyx mori nucleopolyhedrovirus (BmNPV). In this study, a viral DNA chip (Ac-BmNPV chip) was fabricated and used to characterize the viral gene expression profile for AcMNPV in different cell types. The viral chip is composed of microarrays of viral DNA prepared by robotic deposition of PCR-amplified viral DNA fragments on glass for ORFs in the NPV genome. Viral gene expression was monitored by hybridization to the DNA fragment microarrays with fluorescently labeled cDNAs prepared from infected Spodoptera frugiperda, Sf9 cells and Trichoplusia ni, TnHigh-Five cells, the latter a major producer of baculovirus and recombinant proteins. A comparison of expression profiles of known ORFs in AcMNPV elucidated six genes (ORF150, p10, pk2, and three late gene expression factor genes lef-3, p35 and lef- 6) the expression of each of which was regulated differently in the two cell lines. Most of these genes are known to be closely involved in the viral life cycle such as in DNA replication, late gene expression and the release of polyhedra from infected cells. These results imply that the differential expression of these viral genes accounts for the differences in viral replication between these two cell lines. Thus, these fabricated microarrays of NPV DNA which allow a rapid analysis of gene expression at the viral genome level should greatly speed the functional analysis of large genomes of NPV.

Framework for reanalysis of publicly available Affymetrix® GeneChip® data sets based on functional regions of interest.

PubMed

Saka, Ernur; Harrison, Benjamin J; West, Kirk; Petruska, Jeffrey C; Rouchka, Eric C

2017-12-06

Since the introduction of microarrays in 1995, researchers world-wide have used both commercial and custom-designed microarrays for understanding differential expression of transcribed genes. Public databases such as ArrayExpress and the Gene Expression Omnibus (GEO) have made millions of samples readily available. One main drawback to microarray data analysis involves the selection of probes to represent a specific transcript of interest, particularly in light of the fact that transcript-specific knowledge (notably alternative splicing) is dynamic in nature. We therefore developed a framework for reannotating and reassigning probe groups for Affymetrix® GeneChip® technology based on functional regions of interest. This framework addresses three issues of Affymetrix® GeneChip® data analyses: removing nonspecific probes, updating probe target mapping based on the latest genome knowledge and grouping probes into gene, transcript and region-based (UTR, individual exon, CDS) probe sets. Updated gene and transcript probe sets provide more specific analysis results based on current genomic and transcriptomic knowledge. The framework selects unique probes, aligns them to gene annotations and generates a custom Chip Description File (CDF). The analysis reveals only 87% of the Affymetrix® GeneChip® HG-U133 Plus 2 probes uniquely align to the current hg38 human assembly without mismatches. We also tested new mappings on the publicly available data series using rat and human data from GSE48611 and GSE72551 obtained from GEO, and illustrate that functional grouping allows for the subtle detection of regions of interest likely to have phenotypical consequences. Through reanalysis of the publicly available data series GSE48611 and GSE72551, we profiled the contribution of UTR and CDS regions to the gene expression levels globally. The comparison between region and gene based results indicated that the detected expressed genes by gene-based and region-based CDFs show high consistency and regions based results allows us to detection of changes in transcript formation.

Annotation of gene function in citrus using gene expression information and co-expression networks

PubMed Central

2014-01-01

Background The genus Citrus encompasses major cultivated plants such as sweet orange, mandarin, lemon and grapefruit, among the world’s most economically important fruit crops. With increasing volumes of transcriptomics data available for these species, Gene Co-expression Network (GCN) analysis is a viable option for predicting gene function at a genome-wide scale. GCN analysis is based on a “guilt-by-association” principle whereby genes encoding proteins involved in similar and/or related biological processes may exhibit similar expression patterns across diverse sets of experimental conditions. While bioinformatics resources such as GCN analysis are widely available for efficient gene function prediction in model plant species including Arabidopsis, soybean and rice, in citrus these tools are not yet developed. Results We have constructed a comprehensive GCN for citrus inferred from 297 publicly available Affymetrix Genechip Citrus Genome microarray datasets, providing gene co-expression relationships at a genome-wide scale (33,000 transcripts). The comprehensive citrus GCN consists of a global GCN (condition-independent) and four condition-dependent GCNs that survey the sweet orange species only, all citrus fruit tissues, all citrus leaf tissues, or stress-exposed plants. All of these GCNs are clustered using genome-wide, gene-centric (guide) and graph clustering algorithms for flexibility of gene function prediction. For each putative cluster, gene ontology (GO) enrichment and gene expression specificity analyses were performed to enhance gene function, expression and regulation pattern prediction. The guide-gene approach was used to infer novel roles of genes involved in disease susceptibility and vitamin C metabolism, and graph-clustering approaches were used to investigate isoprenoid/phenylpropanoid metabolism in citrus peel, and citric acid catabolism via the GABA shunt in citrus fruit. Conclusions Integration of citrus gene co-expression networks, functional enrichment analysis and gene expression information provide opportunities to infer gene function in citrus. We present a publicly accessible tool, Network Inference for Citrus Co-Expression (NICCE, http://citrus.adelaide.edu.au/nicce/home.aspx), for the gene co-expression analysis in citrus. PMID:25023870

Genome-Wide Analysis of the Sucrose Synthase Gene Family in Grape (Vitis vinifera): Structure, Evolution, and Expression Profiles

PubMed Central

Zhu, Xudong; Wang, Mengqi; Li, Xiaopeng; Jiu, Songtao; Wang, Chen; Fang, Jinggui

2017-01-01

Sucrose synthase (SS) is widely considered as the key enzyme involved in the plant sugar metabolism that is critical to plant growth and development, especially quality of the fruit. The members of SS gene family have been identified and characterized in multiple plant genomes. However, detailed information about this gene family is lacking in grapevine (Vitis vinifera L.). In this study, we performed a systematic analysis of the grape (V. vinifera) genome and reported that there are five SS genes (VvSS1–5) in the grape genome. Comparison of the structures of grape SS genes showed high structural conservation of grape SS genes, resulting from the selection pressures during the evolutionary process. The segmental duplication of grape SS genes contributed to this gene family expansion. The syntenic analyses between grape and soybean (Glycine max) demonstrated that these genes located in corresponding syntenic blocks arose before the divergence of grape and soybean. Phylogenetic analysis revealed distinct evolutionary paths for the grape SS genes. VvSS1/VvSS5, VvSS2/VvSS3 and VvSS4 originated from three ancient SS genes, which were generated by duplication events before the split of monocots and eudicots. Bioinformatics analysis of publicly available microarray data, which was validated by quantitative real-time reverse transcription PCR (qRT-PCR), revealed distinct temporal and spatial expression patterns of VvSS genes in various tissues, organs and developmental stages, as well as in response to biotic and abiotic stresses. Taken together, our results will be beneficial for further investigations into the functions of SS gene in the processes of grape resistance to environmental stresses. PMID:28350372

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

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

Zhou, J.; Wu, L.; Gentry, T.

2006-04-05

To effectively monitor microbial populations involved in various important processes, a 50-mer-based oligonucleotide microarray was developed based on known genes and pathways involved in: biodegradation, metal resistance and reduction, denitrification, nitrification, nitrogen fixation, methane oxidation, methanogenesis, carbon polymer decomposition, and sulfate reduction. This array contains approximately 2000 unique and group-specific probes with <85% similarity to their non-target sequences. Based on artificial probes, our results showed that at hybridization conditions of 50 C and 50% formamide, the 50-mer microarray hybridization can differentiate sequences having <88% similarity. Specificity tests with representative pure cultures indicated that the designed probes on the arrays appearedmore » to be specific to their corresponding target genes. Detection limits were about 5-10ng genomic DNA in the absence of background DNA, and 50-100ng ({approx}1.3{sup o} 10{sup 7} cells) in the presence background DNA. Strong linear relationships between signal intensity and target DNA and RNA concentration were observed (r{sup 2} = 0.95-0.99). Application of this microarray to naphthalene-amended enrichments and soil microcosms demonstrated that composition of the microflora varied depending on incubation conditions. While the naphthalene-degrading genes from Rhodococcus-type microorganisms were dominant in enrichments, the genes involved in naphthalene degradation from Gram-negative microorganisms such as Ralstonia, Comamonas, and Burkholderia were most abundant in the soil microcosms (as well as those for polyaromatic hydrocarbon and nitrotoluene degradation). Although naphthalene degradation is widely known and studied in Pseudomonas, Pseudomonas genes were not detected in either system. Real-time PCR analysis of 4 representative genes was consistent with microarray-based quantification (r{sup 2} = 0.95). Currently, we are also applying this microarray to the study of several different microbial communities and processes at the NABIR-FRC in Oak Ridge, TN. One project involves the monitoring of the development and dynamics of the microbial community of a fluidized bed reactor (FBR) used for reducing nitrate and the other project monitors microbial community responses to stimulation of uranium reducing populations via ethanol donor additions in situ and in a model system. Additionally, we are developing novel strategies for increasing microarray hybridization sensitivity. Finally, great improvements to our methods of probe design were made by the development of a new computer program, CommOligo. CommOligo designs unique and group-specific oligo probes for whole-genomes, metagenomes, and groups of environmental sequences and uses a new global alignment algorithm to design single or multiple probes for each gene or group. We are now using this program to design a more comprehensive functional gene array for environmental studies. Overall, our results indicate that the 50mer-based microarray technology has potential as a specific and quantitative tool to reveal the composition of microbial communities and their dynamics important to processes within contaminated environments.« less

Expression Profile of Long Noncoding RNAs in Human Earlobe Keloids: A Microarray Analysis

PubMed Central

Guo, Liang; Xu, Kai; Yan, Hongbo; Feng, Haifeng

2016-01-01

Background. Long noncoding RNAs (lncRNAs) play key roles in a wide range of biological processes and their deregulation results in human disease, including keloids. Earlobe keloid is a type of pathological skin scar, and the molecular pathogenesis of this disease remains largely unknown. Methods. In this study, microarray analysis was used to determine the expression profiles of lncRNAs and mRNAs between 3 pairs of earlobe keloid and normal specimens. Gene Ontology (GO) categories and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were performed to identify the main functions of the differentially expressed genes and earlobe keloid-related pathways. Results. A total of 2068 lncRNAs and 1511 mRNAs were differentially expressed between earlobe keloid and normal tissues. Among them, 1290 lncRNAs and 1092 mRNAs were upregulated, and 778 lncRNAs and 419 mRNAs were downregulated. Pathway analysis revealed that 24 pathways were correlated to the upregulated transcripts, while 11 pathways were associated with the downregulated transcripts. Conclusion. We characterized the expression profiles of lncRNA and mRNA in earlobe keloids and suggest that lncRNAs may serve as diagnostic biomarkers for the therapy of earlobe keloid. PMID:28101509

The PEPR GeneChip data warehouse, and implementation of a dynamic time series query tool (SGQT) with graphical interface.

PubMed

Chen, Josephine; Zhao, Po; Massaro, Donald; Clerch, Linda B; Almon, Richard R; DuBois, Debra C; Jusko, William J; Hoffman, Eric P

2004-01-01

Publicly accessible DNA databases (genome browsers) are rapidly accelerating post-genomic research (see http://www.genome.ucsc.edu/), with integrated genomic DNA, gene structure, EST/ splicing and cross-species ortholog data. DNA databases have relatively low dimensionality; the genome is a linear code that anchors all associated data. In contrast, RNA expression and protein databases need to be able to handle very high dimensional data, with time, tissue, cell type and genes, as interrelated variables. The high dimensionality of microarray expression profile data, and the lack of a standard experimental platform have complicated the development of web-accessible databases and analytical tools. We have designed and implemented a public resource of expression profile data containing 1024 human, mouse and rat Affymetrix GeneChip expression profiles, generated in the same laboratory, and subject to the same quality and procedural controls (Public Expression Profiling Resource; PEPR). Our Oracle-based PEPR data warehouse includes a novel time series query analysis tool (SGQT), enabling dynamic generation of graphs and spreadsheets showing the action of any transcript of interest over time. In this report, we demonstrate the utility of this tool using a 27 time point, in vivo muscle regeneration series. This data warehouse and associated analysis tools provides access to multidimensional microarray data through web-based interfaces, both for download of all types of raw data for independent analysis, and also for straightforward gene-based queries. Planned implementations of PEPR will include web-based remote entry of projects adhering to quality control and standard operating procedure (QC/SOP) criteria, and automated output of alternative probe set algorithms for each project (see http://microarray.cnmcresearch.org/pgadatatable.asp).

The PEPR GeneChip data warehouse, and implementation of a dynamic time series query tool (SGQT) with graphical interface

PubMed Central

Chen, Josephine; Zhao, Po; Massaro, Donald; Clerch, Linda B.; Almon, Richard R.; DuBois, Debra C.; Jusko, William J.; Hoffman, Eric P.

2004-01-01

Publicly accessible DNA databases (genome browsers) are rapidly accelerating post-genomic research (see http://www.genome.ucsc.edu/), with integrated genomic DNA, gene structure, EST/ splicing and cross-species ortholog data. DNA databases have relatively low dimensionality; the genome is a linear code that anchors all associated data. In contrast, RNA expression and protein databases need to be able to handle very high dimensional data, with time, tissue, cell type and genes, as interrelated variables. The high dimensionality of microarray expression profile data, and the lack of a standard experimental platform have complicated the development of web-accessible databases and analytical tools. We have designed and implemented a public resource of expression profile data containing 1024 human, mouse and rat Affymetrix GeneChip expression profiles, generated in the same laboratory, and subject to the same quality and procedural controls (Public Expression Profiling Resource; PEPR). Our Oracle-based PEPR data warehouse includes a novel time series query analysis tool (SGQT), enabling dynamic generation of graphs and spreadsheets showing the action of any transcript of interest over time. In this report, we demonstrate the utility of this tool using a 27 time point, in vivo muscle regeneration series. This data warehouse and associated analysis tools provides access to multidimensional microarray data through web-based interfaces, both for download of all types of raw data for independent analysis, and also for straightforward gene-based queries. Planned implementations of PEPR will include web-based remote entry of projects adhering to quality control and standard operating procedure (QC/SOP) criteria, and automated output of alternative probe set algorithms for each project (see http://microarray.cnmcresearch.org/pgadatatable.asp). PMID:14681485

NCBI GEO: mining millions of expression profiles--database and tools.

PubMed

Barrett, Tanya; Suzek, Tugba O; Troup, Dennis B; Wilhite, Stephen E; Ngau, Wing-Chi; Ledoux, Pierre; Rudnev, Dmitry; Lash, Alex E; Fujibuchi, Wataru; Edgar, Ron

2005-01-01

The Gene Expression Omnibus (GEO) at the National Center for Biotechnology Information (NCBI) is the largest fully public repository for high-throughput molecular abundance data, primarily gene expression data. The database has a flexible and open design that allows the submission, storage and retrieval of many data types. These data include microarray-based experiments measuring the abundance of mRNA, genomic DNA and protein molecules, as well as non-array-based technologies such as serial analysis of gene expression (SAGE) and mass spectrometry proteomic technology. GEO currently holds over 30,000 submissions representing approximately half a billion individual molecular abundance measurements, for over 100 organisms. Here, we describe recent database developments that facilitate effective mining and visualization of these data. Features are provided to examine data from both experiment- and gene-centric perspectives using user-friendly Web-based interfaces accessible to those without computational or microarray-related analytical expertise. The GEO database is publicly accessible through the World Wide Web at http://www.ncbi.nlm.nih.gov/geo.

Genome-wide identification and analysis of the B3 superfamily of transcription factors in Brassicaceae and major crop plants.

PubMed

Peng, Fred Y; Weselake, Randall J

2013-05-01

The plant-specific B3 superfamily of transcription factors has diverse functions in plant growth and development. Using a genome-wide domain analysis, we identified 92, 187, 58, 90, 81, 55, and 77 B3 transcription factor genes in the sequenced genome of Arabidopsis, Brassica rapa, castor bean (Ricinus communis), cocoa (Theobroma cacao), soybean (Glycine max), maize (Zea mays), and rice (Oryza sativa), respectively. The B3 superfamily has substantially expanded during the evolution in eudicots particularly in Brassicaceae, as compared to monocots in the analysis. We observed domain duplication in some of these B3 proteins, forming more complex domain architectures than currently understood. We found that the length of B3 domains exhibits a large variation, which may affect their exact number of α-helices and β-sheets in the core structure of B3 domains, and possibly have functional implications. Analysis of the public microarray data indicated that most of the B3 gene pairs encoding Arabidopsis-rice orthologs are preferentially expressed in different tissues, suggesting their different roles in these two species. Using ESTs in crops, we identified many B3 genes preferentially expressed in reproductive tissues. In a sequence-based quantitative trait loci analysis in rice and maize, we have found many B3 genes associated with traits such as grain yield, seed weight and number, and protein content. Our results provide a framework for future studies into the function of B3 genes in different phases of plant development, especially the ones related to traits in major crops.

In silico Microarray Probe Design for Diagnosis of Multiple Pathogens

DTIC Science & Technology

2008-10-21

enhancements to an existing single-genome pipeline that allows for efficient design of microarray probes common to groups of target genomes. The...for tens or even hundreds of related genomes in a single run. Hybridization results with an unsequenced B. pseudomallei strain indicate that the

A model of binding on DNA microarrays: understanding the combined effect of probe synthesis failure, cross-hybridization, DNA fragmentation and other experimental details of affymetrix arrays

PubMed Central

2012-01-01

Background DNA microarrays are used both for research and for diagnostics. In research, Affymetrix arrays are commonly used for genome wide association studies, resequencing, and for gene expression analysis. These arrays provide large amounts of data. This data is analyzed using statistical methods that quite often discard a large portion of the information. Most of the information that is lost comes from probes that systematically fail across chips and from batch effects. The aim of this study was to develop a comprehensive model for hybridization that predicts probe intensities for Affymetrix arrays and that could provide a basis for improved microarray analysis and probe development. The first part of the model calculates probe binding affinities to all the possible targets in the hybridization solution using the Langmuir isotherm. In the second part of the model we integrate details that are specific to each experiment and contribute to the differences between hybridization in solution and on the microarray. These details include fragmentation, wash stringency, temperature, salt concentration, and scanner settings. Furthermore, the model fits probe synthesis efficiency and target concentration parameters directly to the data. All the parameters used in the model have a well-established physical origin. Results For the 302 chips that were analyzed the mean correlation between expected and observed probe intensities was 0.701 with a range of 0.88 to 0.55. All available chips were included in the analysis regardless of the data quality. Our results show that batch effects arise from differences in probe synthesis, scanner settings, wash strength, and target fragmentation. We also show that probe synthesis efficiencies for different nucleotides are not uniform. Conclusions To date this is the most complete model for binding on microarrays. This is the first model that includes both probe synthesis efficiency and hybridization kinetics/cross-hybridization. These two factors are sequence dependent and have a large impact on probe intensity. The results presented here provide novel insight into the effect of probe synthesis errors on Affymetrix microarrays; furthermore, the algorithms developed in this work provide useful tools for the analysis of cross-hybridization, probe synthesis efficiency, fragmentation, wash stringency, temperature, and salt concentration on microarray intensities. PMID:23270536

A nonparametric mean-variance smoothing method to assess Arabidopsis cold stress transcriptional regulator CBF2 overexpression microarray data.

PubMed

Hu, Pingsha; Maiti, Tapabrata

2011-01-01

Microarray is a powerful tool for genome-wide gene expression analysis. In microarray expression data, often mean and variance have certain relationships. We present a non-parametric mean-variance smoothing method (NPMVS) to analyze differentially expressed genes. In this method, a nonlinear smoothing curve is fitted to estimate the relationship between mean and variance. Inference is then made upon shrinkage estimation of posterior means assuming variances are known. Different methods have been applied to simulated datasets, in which a variety of mean and variance relationships were imposed. The simulation study showed that NPMVS outperformed the other two popular shrinkage estimation methods in some mean-variance relationships; and NPMVS was competitive with the two methods in other relationships. A real biological dataset, in which a cold stress transcription factor gene, CBF2, was overexpressed, has also been analyzed with the three methods. Gene ontology and cis-element analysis showed that NPMVS identified more cold and stress responsive genes than the other two methods did. The good performance of NPMVS is mainly due to its shrinkage estimation for both means and variances. In addition, NPMVS exploits a non-parametric regression between mean and variance, instead of assuming a specific parametric relationship between mean and variance. The source code written in R is available from the authors on request.

A Nonparametric Mean-Variance Smoothing Method to Assess Arabidopsis Cold Stress Transcriptional Regulator CBF2 Overexpression Microarray Data

PubMed Central

Hu, Pingsha; Maiti, Tapabrata

2011-01-01

Microarray is a powerful tool for genome-wide gene expression analysis. In microarray expression data, often mean and variance have certain relationships. We present a non-parametric mean-variance smoothing method (NPMVS) to analyze differentially expressed genes. In this method, a nonlinear smoothing curve is fitted to estimate the relationship between mean and variance. Inference is then made upon shrinkage estimation of posterior means assuming variances are known. Different methods have been applied to simulated datasets, in which a variety of mean and variance relationships were imposed. The simulation study showed that NPMVS outperformed the other two popular shrinkage estimation methods in some mean-variance relationships; and NPMVS was competitive with the two methods in other relationships. A real biological dataset, in which a cold stress transcription factor gene, CBF2, was overexpressed, has also been analyzed with the three methods. Gene ontology and cis-element analysis showed that NPMVS identified more cold and stress responsive genes than the other two methods did. The good performance of NPMVS is mainly due to its shrinkage estimation for both means and variances. In addition, NPMVS exploits a non-parametric regression between mean and variance, instead of assuming a specific parametric relationship between mean and variance. The source code written in R is available from the authors on request. PMID:21611181

Genome-Wide Requirements for Resistance to Functionally Distinct DNA-Damaging Agents

PubMed Central

Proctor, Michael; Flaherty, Patrick; Jordan, Michael I; Arkin, Adam P; Davis, Ronald W; Nislow, Corey; Giaever, Guri

2005-01-01

The mechanistic and therapeutic differences in the cellular response to DNA-damaging compounds are not completely understood, despite intense study. To expand our knowledge of DNA damage, we assayed the effects of 12 closely related DNA-damaging agents on the complete pool of ~4,700 barcoded homozygous deletion strains of Saccharomyces cerevisiae. In our protocol, deletion strains are pooled together and grown competitively in the presence of compound. Relative strain sensitivity is determined by hybridization of PCR-amplified barcodes to an oligonucleotide array carrying the barcode complements. These screens identified genes in well-characterized DNA-damage-response pathways as well as genes whose role in the DNA-damage response had not been previously established. High-throughput individual growth analysis was used to independently confirm microarray results. Each compound produced a unique genome-wide profile. Analysis of these data allowed us to determine the relative importance of DNA-repair modules for resistance to each of the 12 profiled compounds. Clustering the data for 12 distinct compounds uncovered both known and novel functional interactions that comprise the DNA-damage response and allowed us to define the genetic determinants required for repair of interstrand cross-links. Further genetic analysis allowed determination of epistasis for one of these functional groups. PMID:16121259

Whole-exome analysis of foetal autopsy tissue reveals a frameshift mutation in OBSL1, consistent with a diagnosis of 3-M Syndrome.

PubMed

Marshall, Christian R; Farrell, Sandra A; Cushing, Donna; Paton, Tara; Stockley, Tracy L; Stavropoulos, Dimitri J; Ray, Peter N; Szego, Michael; Lau, Lynette; Pereira, Sergio L; Cohn, Ronald D; Wintle, Richard F; Abuzenadah, Adel M; Abu-Elmagd, Muhammad; Scherer, Stephen W

2015-01-01

We report a consanguineous couple that has experienced three consecutive pregnancy losses following the foetal ultrasound finding of short limbs. Post-termination examination revealed no skeletal dysplasia, but some subtle proximal limb shortening in two foetuses, and a spectrum of mildly dysmorphic features. Karyotype was normal in all three foetuses (46, XX) and comparative genomic hybridization microarray analysis detected no pathogenic copy number variants. Whole-exome sequencing and genome-wide homozygosity mapping revealed a previously reported frameshift mutation in the OBSL1 gene (c.1273insA p.T425nfsX40), consistent with a diagnosis of 3-M Syndrome 2 (OMIM #612921), which had not been anticipated from the clinical findings. Our study provides novel insight into the early clinical manifestations of this form of 3-M syndrome, and demonstrates the utility of whole exome sequencing as a tool for prenatal diagnosis in particular when there is a family history suggestive of a recurrent set of clinical symptoms.

New technology and resources for cryptococcal research

PubMed Central

Zhang, Nannan; Park, Yoon-Dong; Williamson, Peter R.

2014-01-01

Rapid advances in molecular biology and genome sequencing have enabled the generation of new technology and resources for cryptococcal research. RNAi-mediated specific gene knock down has become routine and more efficient by utilizing modified shRNA plasmids and convergent promoter RNAi constructs. This system was recently applied in a high-throughput screen to identify genes involved in host-pathogen interactions. Gene deletion efficiencies have also been improved by increasing rates of homologous recombination through a number of approaches, including a combination of double-joint PCR with split-marker transformation, the use of dominant selectable markers and the introduction of Cre-Loxp systems into Cryptococcus. Moreover, visualization of cryptococcal proteins has become more facile using fusions with codon-optimized fluorescent tags, such as green or red fluorescent proteins or, mCherry. Using recent genome-wide analytical tools, new transcriptional factors and regulatory proteins have been identified in novel virulence-related signaling pathways by employing microarray analysis, RNA-sequencing and proteomic analysis. PMID:25460849

Using Kepler for Tool Integration in Microarray Analysis Workflows.

PubMed

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

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

Sex genes for genomic analysis in human brain: internal controls for comparison of probe level data extraction.

PubMed Central

Galfalvy, Hanga C; Erraji-Benchekroun, Loubna; Smyrniotopoulos, Peggy; Pavlidis, Paul; Ellis, Steven P; Mann, J John; Sibille, Etienne; Arango, Victoria

2003-01-01

Background Genomic studies of complex tissues pose unique analytical challenges for assessment of data quality, performance of statistical methods used for data extraction, and detection of differentially expressed genes. Ideally, to assess the accuracy of gene expression analysis methods, one needs a set of genes which are known to be differentially expressed in the samples and which can be used as a "gold standard". We introduce the idea of using sex-chromosome genes as an alternative to spiked-in control genes or simulations for assessment of microarray data and analysis methods. Results Expression of sex-chromosome genes were used as true internal biological controls to compare alternate probe-level data extraction algorithms (Microarray Suite 5.0 [MAS5.0], Model Based Expression Index [MBEI] and Robust Multi-array Average [RMA]), to assess microarray data quality and to establish some statistical guidelines for analyzing large-scale gene expression. These approaches were implemented on a large new dataset of human brain samples. RMA-generated gene expression values were markedly less variable and more reliable than MAS5.0 and MBEI-derived values. A statistical technique controlling the false discovery rate was applied to adjust for multiple testing, as an alternative to the Bonferroni method, and showed no evidence of false negative results. Fourteen probesets, representing nine Y- and two X-chromosome linked genes, displayed significant sex differences in brain prefrontal cortex gene expression. Conclusion In this study, we have demonstrated the use of sex genes as true biological internal controls for genomic analysis of complex tissues, and suggested analytical guidelines for testing alternate oligonucleotide microarray data extraction protocols and for adjusting multiple statistical analysis of differentially expressed genes. Our results also provided evidence for sex differences in gene expression in the brain prefrontal cortex, supporting the notion of a putative direct role of sex-chromosome genes in differentiation and maintenance of sexual dimorphism of the central nervous system. Importantly, these analytical approaches are applicable to all microarray studies that include male and female human or animal subjects. PMID:12962547

Sex genes for genomic analysis in human brain: internal controls for comparison of probe level data extraction.

PubMed

Galfalvy, Hanga C; Erraji-Benchekroun, Loubna; Smyrniotopoulos, Peggy; Pavlidis, Paul; Ellis, Steven P; Mann, J John; Sibille, Etienne; Arango, Victoria

2003-09-08

Genomic studies of complex tissues pose unique analytical challenges for assessment of data quality, performance of statistical methods used for data extraction, and detection of differentially expressed genes. Ideally, to assess the accuracy of gene expression analysis methods, one needs a set of genes which are known to be differentially expressed in the samples and which can be used as a "gold standard". We introduce the idea of using sex-chromosome genes as an alternative to spiked-in control genes or simulations for assessment of microarray data and analysis methods. Expression of sex-chromosome genes were used as true internal biological controls to compare alternate probe-level data extraction algorithms (Microarray Suite 5.0 [MAS5.0], Model Based Expression Index [MBEI] and Robust Multi-array Average [RMA]), to assess microarray data quality and to establish some statistical guidelines for analyzing large-scale gene expression. These approaches were implemented on a large new dataset of human brain samples. RMA-generated gene expression values were markedly less variable and more reliable than MAS5.0 and MBEI-derived values. A statistical technique controlling the false discovery rate was applied to adjust for multiple testing, as an alternative to the Bonferroni method, and showed no evidence of false negative results. Fourteen probesets, representing nine Y- and two X-chromosome linked genes, displayed significant sex differences in brain prefrontal cortex gene expression. In this study, we have demonstrated the use of sex genes as true biological internal controls for genomic analysis of complex tissues, and suggested analytical guidelines for testing alternate oligonucleotide microarray data extraction protocols and for adjusting multiple statistical analysis of differentially expressed genes. Our results also provided evidence for sex differences in gene expression in the brain prefrontal cortex, supporting the notion of a putative direct role of sex-chromosome genes in differentiation and maintenance of sexual dimorphism of the central nervous system. Importantly, these analytical approaches are applicable to all microarray studies that include male and female human or animal subjects.

Identification of testis-specific male contraceptive targets: insights from transcriptional profiling of the cycle of the rat seminiferous epithelium and purified testicular cells.

PubMed

Johnston, Daniel S; Jelinsky, Scott A; Zhi, Yu; Finger, Joshua N; Kopf, Gregory S; Wright, William W

2007-12-01

In an effort to identify novel targets for the development of nonhormonal male contraceptives, genome-wide transcriptional profiling of the rat testis was performed. Specifically, enzymatically purified spermatogonia plus early spermatocyctes, pachytene spermatocytes, round spermatids, and Sertoli cells was analyzed along with microdissected rat seminiferous tubules at stages I, II-III, IV-V, VI, VIIa,b, VIIc,d, VIII, IX- XI, XII, XIII-XIV of the cycle of the seminiferous epithelium using RAE 230_2.0 microarrays. The combined analysis of these studies identified 16,971 expressed probe sets on the array. How these expression data, combined with additional bioinformatic data analysis and quantitative reverse transcriptase polymerase chain reaction (qRT-PCR) analysis, led to the identification of 58 genes that have 1000-fold higher expression transcriptionally in the testis when compared to over 20 other nonreproductive tissues is described. The products of these genes may play important roles in testicular and/or sperm function, and further investigation on their utility as nonhormonal contraceptive targets is warranted. Moreover, these microarray data have been used to expedite the identification of a mutation in RIKEN cDNA 2410004F06 gene as likely being responsible for spermatogenic failure in a line of infertile mice generated by N-ethyl-N-nitrosourea (ENU) mutagenesis. The microarray data and the qRT-PCR data described are available in the Mammalian Reproductive Genetics database (http://mrg.genetics.washington.edu/).

NRF2-regulated metabolic gene signature as a prognostic biomarker in non-small cell lung cancer

PubMed Central

Namani, Akhileshwar; Cui, Qin Qin; Wu, Yihe; Wang, Hongyan; Wang, Xiu Jun; Tang, Xiuwen

2017-01-01

Mutations in Kelch-like ECH-associated protein 1 (KEAP1) cause the aberrant activation of nuclear factor erythroid-derived 2-like 2 (NRF2), which leads to oncogenesis and drug resistance in lung cancer cells. Our study was designed to identify the genes involved in lung cancer progression targeted by NRF2. A series of microarray experiments in normal and cancer cells, as well as in animal models, have revealed regulatory genes downstream of NRF2 that are involved in wide variety of pathways. Specifically, we carried out individual and combinatorial microarray analysis of KEAP1 overexpression and NRF2 siRNA-knockdown in a KEAP1 mutant-A549 non-small cell lung cancer (NSCLC) cell line. As a result, we identified a list of genes which were mainly involved in metabolic functions in NSCLC by using functional annotation analysis. In addition, we carried out in silico analysis to characterize the antioxidant responsive element sequences in the promoter regions of known and putative NRF2-regulated metabolic genes. We further identified an NRF2-regulated metabolic gene signature (NRMGS) by correlating the microarray data with lung adenocarcinoma RNA-Seq gene expression data from The Cancer Genome Atlas followed by qRT-PCR validation, and finally showed that higher expression of the signature conferred a poor prognosis in 8 independent NSCLC cohorts. Our findings provide novel prognostic biomarkers for NSCLC. PMID:29050246

Genome-wide profiling of DNA-binding proteins using barcode-based multiplex Solexa sequencing.

PubMed

Raghav, Sunil Kumar; Deplancke, Bart

2012-01-01

Chromatin immunoprecipitation (ChIP) is a commonly used technique to detect the in vivo binding of proteins to DNA. ChIP is now routinely paired to microarray analysis (ChIP-chip) or next-generation sequencing (ChIP-Seq) to profile the DNA occupancy of proteins of interest on a genome-wide level. Because ChIP-chip introduces several biases, most notably due to the use of a fixed number of probes, ChIP-Seq has quickly become the method of choice as, depending on the sequencing depth, it is more sensitive, quantitative, and provides a greater binding site location resolution. With the ever increasing number of reads that can be generated per sequencing run, it has now become possible to analyze several samples simultaneously while maintaining sufficient sequence coverage, thus significantly reducing the cost per ChIP-Seq experiment. In this chapter, we provide a step-by-step guide on how to perform multiplexed ChIP-Seq analyses. As a proof-of-concept, we focus on the genome-wide profiling of RNA Polymerase II as measuring its DNA occupancy at different stages of any biological process can provide insights into the gene regulatory mechanisms involved. However, the protocol can also be used to perform multiplexed ChIP-Seq analyses of other DNA-binding proteins such as chromatin modifiers and transcription factors.

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

PubMed

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

2011-12-01

Chronic lymphocytic leukemia (CLL) is a clinically heterogeneous disease. The methods currently used for monitoring CLL and determining conditions for treatment are limited in their ability to predict disease progression, patient survival, and response to therapy. Although clonal diversity and the acquisition of new chromosomal abnormalities during the disease course (clonal evolution) have been associated with disease progression, their prognostic potential has been underappreciated because cytogenetic and fluorescence in situ hybridization (FISH) studies have a restricted ability to detect genomic abnormalities and clonal evolution. We hypothesized that whole genome analysis using high resolution single nucleotide polymorphism (SNP) microarrays would be useful to detect diversity and infer clonal evolution to offer prognostic information. In this study, we used the Infinium Omni1 BeadChip (Illumina, San Diego, CA) array for the analysis of genetic variation and percent mosaicism in 25 non-selected CLL patients to explore the prognostic value of the assessment of clonal diversity in patients with CLL. We calculated the percentage of mosaicism for each abnormality by applying a mathematical algorithm to the genotype frequency data and by manual determination using the Simulated DNA Copy Number (SiDCoN) tool, which was developed from a computer model of mosaicism. At least one genetic abnormality was identified in each case, and the SNP data was 98% concordant with FISH results. Clonal diversity, defined as the presence of two or more genetic abnormalities with differing percentages of mosaicism, was observed in 12 patients (48%), and the diversity correlated with the disease stage. Clonal diversity was present in most cases of advanced disease (Rai stages III and IV) or those with previous treatment, whereas 9 of 13 patients without detected clonal diversity were asymptomatic or clinically stable. In conclusion, SNP microarray studies with simultaneous evaluation of genomic alterations and mosaic distribution of clones can be used to assess apparent clonal evolution via analysis of clonal diversity. Since clonal evolution in CLL is strongly correlated with disease progression, whole genome SNP microarray analysis provides a new comprehensive and reliable prognostic tool for CLL patients. Copyright © 2011 Elsevier Inc. All rights reserved.

Evaluation of the efficacy of constitutional array-based comparative genomic hybridization in the diagnosis of aneuploidy using genomic and amplified DNA.

PubMed

Tan, Niap H; Palmer, Rodger; Wang, Rubin

2010-02-01

Array-based comparative genomic hybridization (array CGH) is a new molecular technique that has the potential to revolutionize cytogenetics. However, use of high resolution array CGH in the clinical setting is plagued by the problem of widespread copy number variations (CNV) in the human genome. Constitutional microarray, containing only clones that interrogate regions of known constitutional syndromes, may circumvent the dilemma of detecting CNV of unknown clinical significance. The present study investigated the efficacy of constitutional microarray in the diagnosis of trisomy. Test samples included genomic DNA from trisomic cell lines, amplification products of 50 ng of genomic DNA and whole genome amplification products of single cells. DNA amplification was achieved by means of multiple displacement amplification (MDA) over 16 h. The trisomic and sex chromosomes copy number imbalances in the genomic DNA were correctly identified by the constitutional microarrays. However, there was a failure to detect the trisomy in the amplification products of 50 ng of genomic DNA and whole genome amplification products of single cells. Using carefully selected clones, Spectral Genomics constitutional microarray was able to detect the chromosomal copy number imbalances in genomic DNA without the confounding effects of CNV. The diagnostic failure in amplified DNA samples could be attributed to the amplification process. The MDA duration of 16 h generated excessive amount of biases and shortening the duration might minimize the problem.

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

PubMed Central

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, 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. PMID:19656363

The Future of Genetics in Psychology and Psychiatry: Microarrays, Genome-Wide Association, and Non-Coding RNA

ERIC Educational Resources Information Center

Plomin, Robert; Davis, Oliver S. P.

2009-01-01

Background: Much of what we thought we knew about genetics needs to be modified in light of recent discoveries. What are the implications of these advances for identifying genes responsible for the high heritability of many behavioural disorders and dimensions in childhood? Methods: Although quantitative genetics such as twin studies will continue…

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

PubMed

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

2011-06-01

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

Integrating Microarray Analysis and the Soybean Genome to Understand the Soybean's Iron Deficiency Response

USDA-ARS?s Scientific Manuscript database

Transcriptional profiles of soybean (Glycine max, L. Merr) near isogenic lines Clark (PI548553, iron efficient) and IsoClark (PI547430, iron inefficient) were analyzed and compared using the Affymetrix® GeneChip® Soybean Genome Array. A comparison of plants grown under Fe-sufficient and Fe-limited ...

Decoherence in yeast cell populations and its implications for genome-wide expression noise.

PubMed

Briones, M R S; Bosco, F

2009-01-20

Gene expression "noise" is commonly defined as the stochastic variation of gene expression levels in different cells of the same population under identical growth conditions. Here, we tested whether this "noise" is amplified with time, as a consequence of decoherence in global gene expression profiles (genome-wide microarrays) of synchronized cells. The stochastic component of transcription causes fluctuations that tend to be amplified as time progresses, leading to a decay of correlations of expression profiles, in perfect analogy with elementary relaxation processes. Measuring decoherence, defined here as a decay in the auto-correlation function of yeast genome-wide expression profiles, we found a slowdown in the decay of correlations, opposite to what would be expected if, as in mixing systems, correlations decay exponentially as the equilibrium state is reached. Our results indicate that the populational variation in gene expression (noise) is a consequence of temporal decoherence, in which the slow decay of correlations is a signature of strong interdependence of the transcription dynamics of different genes.

Report for the NGFA-5 project.

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

Jaing, C; Jackson, P; Thissen, J

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. To effectively compare the sensitivity and specificity of the different genomic technologies, we used SNP TaqMan PCR, MLVA, microarray and high-throughput illumine and 454 sequencing to test various strains from B. anthracis, B. thuringiensis, BioWatch aerosol filter extracts or soil samples that were spiked with B. anthracis, and samples that were previously collected during DHS and EPAmore » environmental release exercises that were known to contain B. thuringiensis spores. The results of all the samples against the various assays are discussed in this report.« less

Filling gaps in PPAR-alpha signaling through comparative nutrigenomics analysis.

PubMed

Cavalieri, Duccio; Calura, Enrica; Romualdi, Chiara; Marchi, Emmanuela; Radonjic, Marijana; Van Ommen, Ben; Müller, Michael

2009-12-11

The application of high-throughput genomic tools in nutrition research is a widespread practice. However, it is becoming increasingly clear that the outcome of individual expression studies is insufficient for the comprehensive understanding of such a complex field. Currently, the availability of the large amounts of expression data in public repositories has opened up new challenges on microarray data analyses. We have focused on PPARalpha, a ligand-activated transcription factor functioning as fatty acid sensor controlling the gene expression regulation of a large set of genes in various metabolic organs such as liver, small intestine or heart. The function of PPARalpha is strictly connected to the function of its target genes and, although many of these have already been identified, major elements of its physiological function remain to be uncovered. To further investigate the function of PPARalpha, we have applied a cross-species meta-analysis approach to integrate sixteen microarray datasets studying high fat diet and PPARalpha signal perturbations in different organisms. We identified 164 genes (MDEGs) that were differentially expressed in a constant way in response to a high fat diet or to perturbations in PPARs signalling. In particular, we found five genes in yeast which were highly conserved and homologous of PPARalpha targets in mammals, potential candidates to be used as models for the equivalent mammalian genes. Moreover, a screening of the MDEGs for all known transcription factor binding sites and the comparison with a human genome-wide screening of Peroxisome Proliferating Response Elements (PPRE), enabled us to identify, 20 new potential candidate genes that show, both binding site, both change in expression in the condition studied. Lastly, we found a non random localization of the differentially expressed genes in the genome. The results presented are potentially of great interest to resume the currently available expression data, exploiting the power of in silico analysis filtered by evolutionary conservation. The analysis enabled us to indicate potential gene candidates that could fill in the gaps with regards to the signalling of PPARalpha and, moreover, the non-random localization of the differentially expressed genes in the genome, suggest that epigenetic mechanisms are of importance in the regulation of the transcription operated by PPARalpha.

Global gene expression analysis of peripheral blood mononuclear cells in rhesus monkey infants with CA16 infection-induced HFMD.

PubMed

Song, Jie; Hu, Yajie; Hu, Yunguang; Wang, Jingjing; Zhang, Xiaolong; Wang, Lichun; Guo, Lei; Wang, Yancui; Ning, Ruotong; Liao, Yun; Zhang, Ying; Zheng, Huiwen; Shi, Haijing; He, Zhanlong; Li, Qihan; Liu, Longding

2016-03-02

Coxsackievirus A16 (CA16) is a dominant pathogen that results in hand, foot, and mouth disease and causes outbreaks worldwide, particularly in the Asia-Pacific region. However, the underlying molecular mechanisms remain unclear. Our previous study has demonstrated that the basic CA16 pathogenic process was successfully mimicked in rhesus monkey infant. The present study focused on the global gene expression changes in peripheral blood mononuclear cells of rhesus monkey infants with hand, foot, and mouth disease induced by CA16 infection at different time points. Genome-wide expression analysis was performed with Agilent whole-genome microarrays and established bioinformatics tools. Nine hundred and forty-eight significant differentially expressed genes that were associated with 5 gene ontology categories, including cell communication, cell cycle, immune system process, regulation of transcription and metabolic process were identified. Subsequently, the mapping of genes related to the immune system process by PANTHER pathway analysis revealed the predominance of inflammation mediated by chemokine and cytokine signaling pathways and the interleukin signaling pathway. Ultimately, co-expressed genes and their networks were analyzed. The results revealed the gene expression profile of the immune system in response to CA16 in rhesus monkey infants and suggested that such an immune response was generated as a result of the positive mobilization of the immune system. This initial microarray study will provide insights into the molecular mechanism of CA16 infection and will facilitate the identification of biomarkers for the evaluation of vaccines against this virus. Copyright © 2016 Elsevier B.V. All rights reserved.

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

PubMed

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

2009-07-16

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

Chromosome 3p12.3-p14.2 and 3q26.2-q26.32 are genomic markers for prognosis of advanced nasopharyngeal carcinoma.

PubMed

Sheu, Jim Jinn-Chyuan; Lee, Chia-Huei; Ko, Jenq-Yuh; Tsao, George S W; Wu, Chung-Chun; Fang, Chih-Yeu; Tsai, Fuu-Jen; Hua, Chun-Hung; Chen, Chi-Long; Chen, Jen-Yang

2009-10-01

Nasopharyngeal carcinoma is an epithelial malignancy with a remarkable racial and geographic distribution. Previous cytogenetic studies have shown nasopharyngeal carcinoma to be characterized by gross genomic aberrations. However, identification of susceptible gene loci in advanced nasopharyngeal carcinoma has been poorly discussed. A genome-wide survey of gene copy number changes was initiated with two nasopharyngeal carcinoma cell lines by array-based comparative genomic hybridization analysis. These alterations were confirmed by a parallel analysis with the data from the gene expression microarray and were validated by quantitative PCR. Clinical association of the defined target genes was analyzed by fluorescence in situ hybridization on 48 metastatic tumors. A high percentage of genes were consistently altered in dosage and expression levels with gain on 3q26.2-q26.32 and losses on 3p12.3-p14.2 and 9p21.3-p23. Six candidate genes, GPR160 (3q26.2-q27), SKIL (3q26), ADAMTS9 (3p14.2-p14.3), LRIG1 (3p14), MPDZ (9p22-p24), and ADFP (9p22.1) were validated by quantitative PCR. Fluorescence in situ hybridization studies revealed amplification of GPR160 (in 25% of cases) and SKIL (33%); and deletion of ADAMTS9 (30%), LRIG1 (35%), MPDZ (15%), and ADFP (15%). Clinical association analyses indicated a poor survival rate with genetic alterations at the defined 3p deletion (P = 0.0012) and the 3q amplification regions (P = 0.0114). The combined microarray technologies suggested novel candidate oncogenes, amplification of GPR160 and SKIL at 3q26.2-q26.32, and deletion of tumor suppressor genes ADAMTS9 and LRIG1 at 3p12.3-p14.2. Altered expression of these genes may be responsible for malignant progression and could be used as potential markers for nasopharyngeal carcinoma.

Genome-wide expression profiling in pediatric septic shock

PubMed Central

Wong, Hector R.

2013-01-01

For nearly a decade, our research group has had the privilege of developing and mining a multi-center, microarray-based, genome-wide expression database of critically ill children (≤ 10 years of age) with septic shock. Using bioinformatic and systems biology approaches, the expression data generated through this discovery-oriented, exploratory approach have been leveraged for a variety of objectives, which will be reviewed. Fundamental observations include wide spread repression of gene programs corresponding to the adaptive immune system, and biologically significant differential patterns of gene expression across developmental age groups. The data have also identified gene expression-based subclasses of pediatric septic shock having clinically relevant phenotypic differences. The data have also been leveraged for the discovery of novel therapeutic targets, and for the discovery and development of novel stratification and diagnostic biomarkers. Almost a decade of genome-wide expression profiling in pediatric septic shock is now demonstrating tangible results. The studies have progressed from an initial discovery-oriented and exploratory phase, to a new phase where the data are being translated and applied to address several areas of clinical need. PMID:23329198

FDA Escherichia coli Identification (FDA-ECID) Microarray: a Pangenome Molecular Toolbox for Serotyping, Virulence Profiling, Molecular Epidemiology, and Phylogeny

PubMed Central

Patel, Isha R.; Gangiredla, Jayanthi; Lacher, David W.; Mammel, Mark K.; Jackson, Scott A.; Lampel, Keith A.

2016-01-01

ABSTRACT Most Escherichia coli strains are nonpathogenic. However, for clinical diagnosis and food safety analysis, current identification methods for pathogenic E. coli either are time-consuming and/or provide limited information. Here, we utilized a custom DNA microarray with informative genetic features extracted from 368 sequence sets for rapid and high-throughput pathogen identification. The FDA Escherichia coli Identification (FDA-ECID) platform contains three sets of molecularly informative features that together stratify strain identification and relatedness. First, 53 known flagellin alleles, 103 alleles of wzx and wzy, and 5 alleles of wzm provide molecular serotyping utility. Second, 41,932 probe sets representing the pan-genome of E. coli provide strain-level gene content information. Third, approximately 125,000 single nucleotide polymorphisms (SNPs) of available whole-genome sequences (WGS) were distilled to 9,984 SNPs capable of recapitulating the E. coli phylogeny. We analyzed 103 diverse E. coli strains with available WGS data, including those associated with past foodborne illnesses, to determine robustness and accuracy. The array was able to accurately identify the molecular O and H serotypes, potentially correcting serological failures and providing better resolution for H-nontypeable/nonmotile phenotypes. In addition, molecular risk assessment was possible with key virulence marker identifications. Epidemiologically, each strain had a unique comparative genomic fingerprint that was extended to an additional 507 food and clinical isolates. Finally, a 99.7% phylogenetic concordance was established between microarray analysis and WGS using SNP-level data for advanced genome typing. Our study demonstrates FDA-ECID as a powerful tool for epidemiology and molecular risk assessment with the capacity to profile the global landscape and diversity of E. coli. IMPORTANCE This study describes a robust, state-of-the-art platform developed from available whole-genome sequences of E. coli and Shigella spp. by distilling useful signatures for epidemiology and molecular risk assessment into one assay. The FDA-ECID microarray contains features that enable comprehensive molecular serotyping and virulence profiling along with genome-scale genotyping and SNP analysis. Hence, it is a molecular toolbox that stratifies strain identification and pathogenic potential in the contexts of epidemiology and phylogeny. We applied this tool to strains from food, environmental, and clinical sources, resulting in significantly greater phylogenetic and strain-specific resolution than previously reported for available typing methods. PMID:27037122

Developing a Drosophila Model of Schwannomatosis

DTIC Science & Technology

2013-02-01

Drosophila melanogaster has become an important model system for cancer studies. Reduced redundancy in the Drosophila genome compared with that of...of high-resolution deletion coverage of the Drosophila melanogaster genome . Nat. Genet. 36, 288-292. Pastor-Pareja, J. C., Wu, M. and Xu. T. (2008...microarray analysis of the entire Drosophila melanogaster genome and compared gene expression profiles of wild type, dCap-D3 and rbf1 mutant

Comparative genome analysis of a large Dutch Legionella pneumophila strain collection identifies five markers highly correlated with clinical strains

PubMed Central

2010-01-01

Background Discrimination between clinical and environmental strains within many bacterial species is currently underexplored. Genomic analyses have clearly shown the enormous variability in genome composition between different strains of a bacterial species. In this study we have used Legionella pneumophila, the causative agent of Legionnaire's disease, to search for genomic markers related to pathogenicity. During a large surveillance study in The Netherlands well-characterized patient-derived strains and environmental strains were collected. We have used a mixed-genome microarray to perform comparative-genome analysis of 257 strains from this collection. Results Microarray analysis indicated that 480 DNA markers (out of in total 3360 markers) showed clear variation in presence between individual strains and these were therefore selected for further analysis. Unsupervised statistical analysis of these markers showed the enormous genomic variation within the species but did not show any correlation with a pathogenic phenotype. We therefore used supervised statistical analysis to identify discriminating markers. Genetic programming was used both to identify predictive markers and to define their interrelationships. A model consisting of five markers was developed that together correctly predicted 100% of the clinical strains and 69% of the environmental strains. Conclusions A novel approach for identifying predictive markers enabling discrimination between clinical and environmental isolates of L. pneumophila is presented. Out of over 3000 possible markers, five were selected that together enabled correct prediction of all the clinical strains included in this study. This novel approach for identifying predictive markers can be applied to all bacterial species, allowing for better discrimination between strains well equipped to cause human disease and relatively harmless strains. PMID:20630115

Genome-Wide Identification, Evolution and Expression Analysis of mTERF Gene Family in Maize

PubMed Central

Zhao, Yanxin; Cai, Manjun; Zhang, Xiaobo; Li, Yurong; Zhang, Jianhua; Zhao, Hailiang; Kong, Fei; Zheng, Yonglian; Qiu, Fazhan

2014-01-01

Plant mitochondrial transcription termination factor (mTERF) genes comprise a large family with important roles in regulating organelle gene expression. In this study, a comprehensive database search yielded 31 potential mTERF genes in maize (Zea mays L.) and most of them were targeted to mitochondria or chloroplasts. Maize mTERF were divided into nine main groups based on phylogenetic analysis, and group IX represented the mitochondria and species-specific clade that diverged from other groups. Tandem and segmental duplication both contributed to the expansion of the mTERF gene family in the maize genome. Comprehensive expression analysis of these genes, using microarray data and RNA-seq data, revealed that these genes exhibit a variety of expression patterns. Environmental stimulus experiments revealed differential up or down-regulation expression of maize mTERF genes in seedlings exposed to light/dark, salts and plant hormones, respectively, suggesting various important roles of maize mTERF genes in light acclimation and stress-related responses. These results will be useful for elucidating the roles of mTERF genes in the growth, development and stress response of maize. PMID:24718683

A molecular scheme for improved characterization of human embryonic stem cell lines

PubMed Central

Josephson, Richard; Sykes, Gregory; Liu, Ying; Ording, Carol; Xu, Weining; Zeng, Xianmin; Shin, Soojung; Loring, Jeanne; Maitra, Anirban; Rao, Mahendra S; Auerbach, Jonathan M

2006-01-01

Background Human embryonic stem cells (hESC) offer a renewable source of a wide range of cell types for use in research and cell-based therapies to treat disease. Inspection of protein markers provides important information about the current state of the cells and data for subsequent manipulations. However, hESC must be routinely analyzed at the genomic level to guard against deleterious changes during extensive propagation, expansion, and manipulation in vitro. Results We found that short tandem repeat (STR) analysis, human leukocyte antigen (HLA) typing, single nucleotide polymorphism (SNP) genomic analysis, mitochondrial DNA sequencing, and gene expression analysis by microarray can be used to fully describe any hESC culture in terms of its identity, stability, and undifferentiated state. Conclusion Here we describe, using molecular biology alone, a comprehensive characterization of 17 different hESC lines. The use of amplified nucleic acids means that for the first time full characterization of hESC lines can be performed with little time investment and a minimum of material. The information thus gained will facilitate comparison of lines and replication of results between laboratories. PMID:16919167

Genomic diversity and population structure of three autochthonous Greek sheep breeds assessed with genome-wide DNA arrays.

PubMed

Michailidou, S; Tsangaris, G; Fthenakis, G C; Tzora, A; Skoufos, I; Karkabounas, S C; Banos, G; Argiriou, A; Arsenos, G

2018-06-01

In the present study, genome-wide genotyping was applied to characterize the genetic diversity and population structure of three autochthonous Greek breeds: Boutsko, Karagouniko and Chios. Dairy sheep are among the most significant livestock species in Greece numbering approximately 9 million animals which are characterized by large phenotypic variation and reared under various farming systems. A total of 96 animals were genotyped with the Illumina's OvineSNP50K microarray beadchip, to study the population structure of the breeds and develop a specialized panel of single-nucleotide polymorphisms (SNPs), which could distinguish one breed from the others. Quality control on the dataset resulted in 46,125 SNPs, which were used to evaluate the genetic structure of the breeds. Population structure was assessed through principal component analysis (PCA) and admixture analysis, whereas inbreeding was estimated based on runs of homozygosity (ROHs) coefficients, genomic relationship matrix inbreeding coefficients (F GRM ) and patterns of linkage disequilibrium (LD). Associations between SNPs and breeds were analyzed with different inheritance models, to identify SNPs that distinguish among the breeds. Results showed high levels of genetic heterogeneity in the three breeds. Genetic distances among breeds were modest, despite their different ancestries. Chios and Karagouniko breeds were more genetically related to each other compared to Boutsko. Analysis revealed 3802 candidate SNPs that can be used to identify two-breed crosses and purebred animals. The present study provides, for the first time, data on the genetic background of three Greek indigenous dairy sheep breeds as well as a specialized marker panel that can be applied for traceability purposes as well as targeted genetic improvement schemes and conservation programs.

Genome-wide analysis of family-1 UDP glycosyltransferases (UGT) and identification of UGT genes for FHB resistance in wheat (Triticum aestivum L.).

PubMed

He, Yi; Ahmad, Dawood; Zhang, Xu; Zhang, Yu; Wu, Lei; Jiang, Peng; Ma, Hongxiang

2018-04-19

Fusarium head blight (FHB), a devastating disease in wheat worldwide, results in yield loses and mycotoxin, such as deoxynivalenol (DON), accumulation in infected grains. DON also facilitates the pathogen colonization and spread of FHB symptoms during disease development. UDP-glycosyltransferase enzymes (UGTs) are known to contribute to detoxification and enhance FHB resistance by glycosylating DON into DON-3-glucoside (D3G) in wheat. However, a comprehensive investigation of wheat (Triticum aestivum) UGT genes is still lacking. In this study, we carried out a genome-wide analysis of family-1 UDP glycosyltransferases in wheat based on the PSPG conserved box that resulted in the identification of 179 putative UGT genes. The identified genes were clustered into 16 major phylogenetic groups with a lack of phylogenetic group K. The UGT genes were invariably distributed among all the chromosomes of the 3 genomes. At least 10 intron insertion events were found in the UGT sequences, where intron 4 was observed as the most conserved intron. The expression analysis of the wheat UGT genes using both online microarray data and quantitative real-time PCR verification suggested the distinct role of UGT genes in different tissues and developmental stages. The expression of many UGT genes was up-regulated after Fusarium graminearum inoculation, and six of the genes were further verified by RT-qPCR. We identified 179 UGT genes from wheat using the available sequenced wheat genome. This study provides useful insight into the phylogenetic structure, distribution, and expression patterns of family-1 UDP glycosyltransferases in wheat. The results also offer a foundation for future work aimed at elucidating the molecular mechanisms underlying the resistance to FHB and DON accumulation.

Comparison of sequencing-based methods to profile DNA methylation and identification of monoallelic epigenetic modifications

PubMed Central

Harris, R. Alan; Wang, Ting; Coarfa, Cristian; Nagarajan, Raman P.; Hong, Chibo; Downey, Sara L.; Johnson, Brett E.; Fouse, Shaun D.; Delaney, Allen; Zhao, Yongjun; Olshen, Adam; Ballinger, Tracy; Zhou, Xin; Forsberg, Kevin J.; Gu, Junchen; Echipare, Lorigail; O’Geen, Henriette; Lister, Ryan; Pelizzola, Mattia; Xi, Yuanxin; Epstein, Charles B.; Bernstein, Bradley E.; Hawkins, R. David; Ren, Bing; Chung, Wen-Yu; Gu, Hongcang; Bock, Christoph; Gnirke, Andreas; Zhang, Michael Q.; Haussler, David; Ecker, Joseph; Li, Wei; Farnham, Peggy J.; Waterland, Robert A.; Meissner, Alexander; Marra, Marco A.; Hirst, Martin; Milosavljevic, Aleksandar; Costello, Joseph F.

2010-01-01

Sequencing-based DNA methylation profiling methods are comprehensive and, as accuracy and affordability improve, will increasingly supplant microarrays for genome-scale analyses. Here, four sequencing-based methodologies were applied to biological replicates of human embryonic stem cells to compare their CpG coverage genome-wide and in transposons, resolution, cost, concordance and its relationship with CpG density and genomic context. The two bisulfite methods reached concordance of 82% for CpG methylation levels and 99% for non-CpG cytosine methylation levels. Using binary methylation calls, two enrichment methods were 99% concordant, while regions assessed by all four methods were 97% concordant. To achieve comprehensive methylome coverage while reducing cost, an approach integrating two complementary methods was examined. The integrative methylome profile along with histone methylation, RNA, and SNP profiles derived from the sequence reads allowed genome-wide assessment of allele-specific epigenetic states, identifying most known imprinted regions and new loci with monoallelic epigenetic marks and monoallelic expression. PMID:20852635

The contribution of the DNA microarray technology to gene expression profiling in Leishmania spp.: a retrospective.

PubMed

Alonso, Ana; Larraga, Vicente; Alcolea, Pedro J

2018-05-07

The first genome project of any living organism excluding viruses, the gammaproteobacteria Haemophilus influenzae, was completed in 1995. Until the last decade, genome sequencing was very tedious because genome survey sequences (GSS) and/or expressed sequence tags (ESTs) belonging to plasmid, cosmid and artificial chromosome genome libraries had to be sequenced and assembled in silico. Nowadays, no genome is completely assembled actually, because gaps and unassembled contigs are always remaining. However, most represent the whole genome of the organism of origin from a practical point of view. The first genome sequencing projects of trypanosomatid parasites were completed in 2005 following those strategies, and belong to Leishmania major, Trypanosoma cruzi and T. brucei. The functional genomics era rapidly developed on the basis of the microarray technology and has been evolving. In the case of the genus Leishmania, substantial biological information about differentiation in the digenetic life cycle of the parasite has been obtained. Later on, next generation sequencing has revolutionized genome sequencing and functional genomics, leading to more sensitive, accurate results by using much less resources. This new technology is more advantageous, but does not invalidate microarray results. In fact, promising vaccine candidates and drug targets have been found on the basis of microarray-based screening and preliminary proof-of-concept tests. Copyright © 2018. Published by Elsevier B.V.

Emerging Use of Gene Expression Microarrays in Plant Physiology

DOE PAGES

Wullschleger, Stan D.; Difazio, Stephen P.

2003-01-01

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

Gene expression analysis in rat lungs after intratracheal exposure to nanoparticles doped with cadmium

NASA Astrophysics Data System (ADS)

Coccini, Teresa; Fabbri, Marco; Roda, Elisa; Grazia Sacco, Maria; Manzo, Luigi; Gribaldo, Laura

2011-07-01

Silica nanoparticles (NPs) incorporating cadmium (Cd) have been developed for a range of potential application including drug delivery devices. Occupational Cd inhalation has been associated with emphysema, pulmonary fibrosis and lung tumours. Mechanistically, Cd can induce oxidative stress and mediate cell-signalling pathways that are involved in inflammation.This in vivo study aimed at investigating pulmonary molecular effects of NPs doped with Cd (NP-Cd, 1 mg/animal) compared to soluble CdCl2 (400 μg/animal), in Sprague Dawley rats treated intra-tracheally, 7 and 30 days after administration. NPs of silica containing Cd salt were prepared starting from commercial nano-size silica powder (HiSil™ T700 Degussa) with average pore size of 20 nm and surface area of 240 m2/g. Toxicogenomic analysis was performed by the DNA microarray technology (using Agilent Whole Rat Genome Microarray 4×44K) to evaluate changes in gene expression of the entire genome. These findings indicate that the whole genome analysis may represent a valuable approach to assess the whole spectrum of biological responses to cadmium containing nanomaterials.

Genome-wide high-resolution screening in Dupuytren's disease reveals common regions of DNA copy number alterations.

PubMed

Shih, Barbara B; Tassabehji, May; Watson, James S; McGrouther, Angus D; Bayat, Ardeshir

2010-07-01

Dupuytren's disease (DD) is a familial disorder with a high genetic susceptibility in white people; however, its etiopathogenesis remains unknown. Previous comparative genomic hybridization studies using lower-resolution, 44-k oligonucleotide-based arrays revealed no copy number variation (CNV) changes in DD. In this study, we used a higher-resolution genome-wide screening (next-generation microarrays) comprising 963,331 human sequences (3 kb spacing between probes) for whole genome DNA variation analysis. The objective was to detect cryptic chromosomal imbalances in DD. Agilent SurePrint G3 microarrays, one million format (Agilent Technologies, Santa Clara, CA), were used to detect CNV regions (CNVRs) in DNA extracted from nodules of 4 white men with DD (age, 69 +/- 4 y). Reference samples were from the DNA of 10 men who served as control patients. Copy number variations that were common to greater than 3 assessed DD individuals (p < .05) were selected as candidate loci for DD etiology. In addition, quantitative polymerase chain reactions (qPCR) assays were designed for selected CNVRs on DNA from 13 DD patients and 11 control patients. Independent t-tests and Fisher's exact tests were carried out for statistical analysis. Three novel CNVs previously unreported in the phenotypically normal population were detected in 3 DD cases, located at 10q22, 16p12.1, and 17p12. Nine polymorphic CNVRs potentially associated with DD were determined using our strategic selection criteria, locating to chromosomes 1q31, 6p21, 7p14, 8p11, 12p13, 14q11, 17q21 and 20p13. More than 3 of the DD cases tested had a CNVR located to a small region on 6p21 and 4 CNVRs within 6p21-22 of the human leukocyte antigen (HLA) genes. Three novel copy number alterations were observed in 3 unrelated patients with sporadic (no known family history) DD. Nine polymorphic CNVRs were found to be common among the DD cases. These variants might contain genes involved in DD formation, indicating that important gene networks expressed within the palmar fascia might contribute to genetic susceptibility of DD. Copyright 2010. Published by Elsevier Inc.

Microarray Technology for the Diagnosis of Fetal Chromosomal Aberrations: Which Platform Should We Use?

PubMed Central

Karampetsou, Evangelia; Morrogh, Deborah; Chitty, Lyn

2014-01-01

The advantage of microarray (array) over conventional karyotype for the diagnosis of fetal pathogenic chromosomal anomalies has prompted the use of microarrays in prenatal diagnostics. In this review we compare the performance of different array platforms (BAC, oligonucleotide CGH, SNP) and designs (targeted, whole genome, whole genome, and targeted, custom) and discuss their advantages and disadvantages in relation to prenatal testing. We also discuss the factors to consider when implementing a microarray testing service for the diagnosis of fetal chromosomal aberrations. PMID:26237396

eQTL Mapping Using RNA-seq Data

PubMed Central

Hu, Yijuan

2012-01-01

As RNA-seq is replacing gene expression microarrays to assess genome-wide transcription abundance, gene expression Quantitative Trait Locus (eQTL) studies using RNA-seq have emerged. RNA-seq delivers two novel features that are important for eQTL studies. First, it provides information on allele-specific expression (ASE), which is not available from gene expression microarrays. Second, it generates unprecedentedly rich data to study RNA-isoform expression. In this paper, we review current methods for eQTL mapping using ASE and discuss some future directions. We also review existing works that use RNA-seq data to study RNA-isoform expression and we discuss the gaps between these works and isoform-specific eQTL mapping. PMID:23667399

Transcriptome Analysis of PA Gain and Loss of Function Mutants.

PubMed

Marco, Francisco; Carrasco, Pedro

2018-01-01

Functional genomics has become a forefront methodology for plant science thanks to the widespread development of microarray technology. While technical difficulties associated with the process of obtaining raw expression data have been diminishing, allowing the appearance of tremendous amounts of transcriptome data in different databases, a common problem using "omic" technologies remains: the interpretation of these data and the inference of its biological meaning. In order to assist to this complex task, a wide variety of software tools have been developed. In this chapter we describe our current workflow of the application of some of these analyses. We have used it to compare the transcriptome of plants with differences in their polyamine levels.

Role of PELP1 in EGFR-ER Signaling Crosstalk in Ovarian Cancer Cells

DTIC Science & Technology

2009-04-01

expression of genes involved in metastasis using a focused microarray approach. We have used Human Tumor Metastasis Microarray (Oligo GE array from...ovarian cancer progression. Analysis of human genome databases and SAGE data suggested deregulation of PELP1 expression in ovarian cancer cells...PI3K, and STAT3 in the cytosol. PELP1/MNAR regulates meiosis via its interactions with heterotimeric Gbc protein, androgen receptor (AR), and by

Wavelet-based identification of DNA focal genomic aberrations from single nucleotide polymorphism arrays

PubMed Central

2011-01-01

Background Copy number aberrations (CNAs) are an important molecular signature in cancer initiation, development, and progression. However, these aberrations span a wide range of chromosomes, making it hard to distinguish cancer related genes from other genes that are not closely related to cancer but are located in broadly aberrant regions. With the current availability of high-resolution data sets such as single nucleotide polymorphism (SNP) microarrays, it has become an important issue to develop a computational method to detect driving genes related to cancer development located in the focal regions of CNAs. Results In this study, we introduce a novel method referred to as the wavelet-based identification of focal genomic aberrations (WIFA). The use of the wavelet analysis, because it is a multi-resolution approach, makes it possible to effectively identify focal genomic aberrations in broadly aberrant regions. The proposed method integrates multiple cancer samples so that it enables the detection of the consistent aberrations across multiple samples. We then apply this method to glioblastoma multiforme and lung cancer data sets from the SNP microarray platform. Through this process, we confirm the ability to detect previously known cancer related genes from both cancer types with high accuracy. Also, the application of this approach to a lung cancer data set identifies focal amplification regions that contain known oncogenes, though these regions are not reported using a recent CNAs detecting algorithm GISTIC: SMAD7 (chr18q21.1) and FGF10 (chr5p12). Conclusions Our results suggest that WIFA can be used to reveal cancer related genes in various cancer data sets. PMID:21569311

Identification and comparison of aberrant key regulatory networks in breast, colon, liver, lung, and stomach cancers through methylome database analysis.

PubMed

Kim, Byungtak; Kang, Seongeun; Jeong, Gookjoo; Park, Sung-Bin; Kim, Sun Jung

2014-01-01

Aberrant methylation of specific CpG sites at the promoter is widely responsible for genesis and development of various cancer types. Even though the microarray-based methylome analyzing techniques have contributed to the elucidation of the methylation change at the genome-wide level, the identification of key methylation markers or top regulatory networks appearing common in highly incident cancers through comparison analysis is still limited. In this study, we in silico performed the genome-wide methylation analysis on each 10 sets of normal and cancer pairs of five tissues: breast, colon, liver, lung, and stomach. The methylation array covers 27,578 CpG sites, corresponding to 14,495 genes, and significantly hypermethylated or hypomethylated genes in the cancer were collected (FDR adjusted p-value <0.05; methylation difference >0.3). Analysis of the dataset confirmed the methylation of previously known methylation markers and further identified novel methylation markers, such as GPX2, CLDN15, and KL. Cluster analysis using the methylome dataset resulted in a diagram with a bipartite mode distinguishing cancer cells from normal cells regardless of tissue types. The analysis further revealed that breast cancer was closest with lung cancer, whereas it was farthest from colon cancer. Pathway analysis identified that either the "cancer" related network or the "cancer" related bio-function appeared as the highest confidence in all the five cancers, whereas each cancer type represents its tissue-specific gene sets. Our results contribute toward understanding the essential abnormal epigenetic pathways involved in carcinogenesis. Further, the novel methylation markers could be applied to establish markers for cancer prognosis.

Replication dynamics of the yeast genome.

PubMed

Raghuraman, M K; Winzeler, E A; Collingwood, D; Hunt, S; Wodicka, L; Conway, A; Lockhart, D J; Davis, R W; Brewer, B J; Fangman, W L

2001-10-05

Oligonucleotide microarrays were used to map the detailed topography of chromosome replication in the budding yeast Saccharomyces cerevisiae. The times of replication of thousands of sites across the genome were determined by hybridizing replicated and unreplicated DNAs, isolated at different times in S phase, to the microarrays. Origin activations take place continuously throughout S phase but with most firings near mid-S phase. Rates of replication fork movement vary greatly from region to region in the genome. The two ends of each of the 16 chromosomes are highly correlated in their times of replication. This microarray approach is readily applicable to other organisms, including humans.

Hsf and Hsp gene families in Populus: genome-wide identification, organization and correlated expression during development and in stress responses.

PubMed

Zhang, Jin; Liu, Bobin; Li, Jianbo; Zhang, Li; Wang, Yan; Zheng, Huanquan; Lu, Mengzhu; Chen, Jun

2015-03-14

Heat shock proteins (Hsps) are molecular chaperones that are involved in many normal cellular processes and stress responses, and heat shock factors (Hsfs) are the transcriptional activators of Hsps. Hsfs and Hsps are widely coordinated in various biological processes. Although the roles of Hsfs and Hsps in stress responses have been well characterized in Arabidopsis, their roles in perennial woody species undergoing various environmental stresses remain unclear. Here, a comprehensive identification and analysis of Hsf and Hsp families in poplars is presented. In Populus trichocarpa, we identified 42 paralogous pairs, 66.7% resulting from a whole genome duplication. The gene structure and motif composition are relatively conserved in each subfamily. Microarray and quantitative real-time RT-PCR analyses showed that most of the Populus Hsf and Hsp genes are differentially expressed upon exposure to various stresses. A coexpression network between Populus Hsf and Hsp genes was generated based on their expression. Coordinated relationships were validated by transient overexpression and subsequent qPCR analyses. The comprehensive analysis indicates that different sets of PtHsps are downstream of particular PtHsfs and provides a basis for functional studies aimed at revealing the roles of these families in poplar development and stress responses.

Research resource: Tissue-specific transcriptomics and cistromics of nuclear receptor signaling: a web research resource.

PubMed

Ochsner, Scott A; Watkins, Christopher M; LaGrone, Benjamin S; Steffen, David L; McKenna, Neil J

2010-10-01

Nuclear receptors (NRs) are ligand-regulated transcription factors that recruit coregulators and other transcription factors to gene promoters to effect regulation of tissue-specific transcriptomes. The prodigious rate at which the NR signaling field has generated high content gene expression and, more recently, genome-wide location analysis datasets has not been matched by a committed effort to archiving this information for routine access by bench and clinical scientists. As a first step towards this goal, we searched the MEDLINE database for studies, which referenced either expression microarray and/or genome-wide location analysis datasets in which a NR or NR ligand was an experimental variable. A total of 1122 studies encompassing 325 unique organs, tissues, primary cells, and cell lines, 35 NRs, and 91 NR ligands were retrieved and annotated. The data were incorporated into a new section of the Nuclear Receptor Signaling Atlas Molecule Pages, Transcriptomics and Cistromics, for which we designed an intuitive, freely accessible user interface to browse the studies. Each study links to an abstract, the MEDLINE record, and, where available, Gene Expression Omnibus and ArrayExpress records. The resource will be updated on a regular basis to provide a current and comprehensive entrez into the sum of transcriptomic and cistromic research in this field.

Systems biology of cancer biomarker detection.

PubMed

Mitra, Sanga; Das, Smarajit; Chakrabarti, Jayprokas

2013-01-01

Cancer systems-biology is an ever-growing area of research due to explosion of data; how to mine these data and extract useful information is the problem. To have an insight on carcinogenesis one need to systematically mine several resources, such as databases, microarray and next-generation sequences. This review encompasses management and analysis of cancer data, databases construction and data deposition, whole transcriptome and genome comparison, analysing results from high throughput experiments to uncover cellular pathways and molecular interactions, and the design of effective algorithms to identify potential biomarkers. Recent technical advances such as ChIP-on-chip, ChIP-seq and RNA-seq can be applied to get epigenetic information transformed into a high-throughput endeavour to which systems biology and bioinformatics are making significant inroads. The data from ENCODE and GENCODE projects available through UCSC genome browser can be considered as benchmark for comparison and meta-analysis. A pipeline for integrating next generation sequencing data, microarray data, and putting them together with the existing database is discussed. The understanding of cancer genomics is changing the way we approach cancer diagnosis and treatment. To give a better understanding of utilizing available resources' we have chosen oral cancer to show how and what kind of analysis can be done. This review is a computational genomic primer that provides a bird's eye view of computational and bioinformatics' tools currently available to perform integrated genomic and system biology analyses of several carcinoma.

Global transgenerational gene expression dynamics in two newly synthesized allohexaploid wheat (Triticum aestivum) lines

PubMed Central

2012-01-01

Background Alteration in gene expression resulting from allopolyploidization is a prominent feature in plants, but its spectrum and extent are not fully known. Common wheat (Triticum aestivum) was formed via allohexaploidization about 10,000 years ago, and became the most important crop plant. To gain further insights into the genome-wide transcriptional dynamics associated with the onset of common wheat formation, we conducted microarray-based genome-wide gene expression analysis on two newly synthesized allohexaploid wheat lines with chromosomal stability and a genome constitution analogous to that of the present-day common wheat. Results Multi-color GISH (genomic in situ hybridization) was used to identify individual plants from two nascent allohexaploid wheat lines between Triticum turgidum (2n = 4x = 28; genome BBAA) and Aegilops tauschii (2n = 2x = 14; genome DD), which had a stable chromosomal constitution analogous to that of common wheat (2n = 6x = 42; genome BBAADD). Genome-wide analysis of gene expression was performed for these allohexaploid lines along with their parental plants from T. turgidum and Ae. tauschii, using the Affymetrix Gene Chip Wheat Genome-Array. Comparison with the parental plants coupled with inclusion of empirical mid-parent values (MPVs) revealed that whereas the great majority of genes showed the expected parental additivity, two major patterns of alteration in gene expression in the allohexaploid lines were identified: parental dominance expression and non-additive expression. Genes involved in each of the two altered expression patterns could be classified into three distinct groups, stochastic, heritable and persistent, based on their transgenerational heritability and inter-line conservation. Strikingly, whereas both altered patterns of gene expression showed a propensity of inheritance, identity of the involved genes was highly stochastic, consistent with the involvement of diverse Gene Ontology (GO) terms. Nonetheless, those genes showing non-additive expression exhibited a significant enrichment for vesicle-function. Conclusions Our results show that two patterns of global alteration in gene expression are conditioned by allohexaploidization in wheat, that is, parental dominance expression and non-additive expression. Both altered patterns of gene expression but not the identity of the genes involved are likely to play functional roles in stabilization and establishment of the newly formed allohexaploid plants, and hence, relevant to speciation and evolution of T. aestivum. PMID:22277161

EFEMP1 as a novel DNA methylation marker for prostate cancer: array-based DNA methylation and expression profiling.

PubMed

Kim, Yong-June; Yoon, Hyung-Yoon; Kim, Seon-Kyu; Kim, Young-Won; Kim, Eun-Jung; Kim, Isaac Yi; Kim, Wun-Jae

2011-07-01

Abnormal DNA methylation is associated with many human cancers. The aim of the present study was to identify novel methylation markers in prostate cancer (PCa) by microarray analysis and to test whether these markers could discriminate normal and PCa cells. Microarray-based DNA methylation and gene expression profiling was carried out using a panel of PCa cell lines and a control normal prostate cell line. The methylation status of candidate genes in prostate cell lines was confirmed by real-time reverse transcriptase-PCR, bisulfite sequencing analysis, and treatment with a demethylation agent. DNA methylation and gene expression analysis in 203 human prostate specimens, including 106 PCa and 97 benign prostate hyperplasia (BPH), were carried out. Further validation using microarray gene expression data from the Gene Expression Omnibus (GEO) was carried out. Epidermal growth factor-containing fibulin-like extracellular matrix protein 1 (EFEMP1) was identified as a lead candidate methylation marker for PCa. The gene expression level of EFEMP1 was significantly higher in tissue samples from patients with BPH than in those with PCa (P < 0.001). The sensitivity and specificity of EFEMP1 methylation status in discriminating between PCa and BPH reached 95.3% (101 of 106) and 86.6% (84 of 97), respectively. From the GEO data set, we confirmed that the expression level of EFEMP1 was significantly different between PCa and BPH. Genome-wide characterization of DNA methylation profiles enabled the identification of EFEMP1 aberrant methylation patterns in PCa. EFEMP1 might be a useful indicator for the detection of PCa.

Impact of IQ on the diagnostic yield of chromosomal microarray in a community sample of adults with schizophrenia.

PubMed

Lowther, Chelsea; Merico, Daniele; Costain, Gregory; Waserman, Jack; Boyd, Kerry; Noor, Abdul; Speevak, Marsha; Stavropoulos, Dimitri J; Wei, John; Lionel, Anath C; Marshall, Christian R; Scherer, Stephen W; Bassett, Anne S

2017-11-30

Schizophrenia is a severe psychiatric disorder associated with IQ deficits. Rare copy number variations (CNVs) have been established to play an important role in the etiology of schizophrenia. Several of the large rare CNVs associated with schizophrenia have been shown to negatively affect IQ in population-based controls where no major neuropsychiatric disorder is reported. The aim of this study was to examine the diagnostic yield of microarray testing and the functional impact of genome-wide rare CNVs in a community ascertained cohort of adults with schizophrenia and low (< 85) or average (≥ 85) IQ. We recruited 546 adults of European ancestry with schizophrenia from six community psychiatric clinics in Canada. Each individual was assigned to the low or average IQ group based on standardized tests and/or educational attainment. We used rigorous methods to detect genome-wide rare CNVs from high-resolution microarray data. We compared the burden of rare CNVs classified as pathogenic or as a variant of unknown significance (VUS) between each of the IQ groups and the genome-wide burden and functional impact of rare CNVs after excluding individuals with a pathogenic CNV. There were 39/546 (7.1%; 95% confidence interval [CI] = 5.2-9.7%) schizophrenia participants with at least one pathogenic CNV detected, significantly more of whom were from the low IQ group (odds ratio [OR] = 5.01 [2.28-11.03], p = 0.0001). Secondary analyses revealed that individuals with schizophrenia and average IQ had the lowest yield of pathogenic CNVs (n = 9/325; 2.8%), followed by those with borderline intellectual functioning (n = 9/130; 6.9%), non-verbal learning disability (n = 6/29; 20.7%), and co-morbid intellectual disability (n = 15/62; 24.2%). There was no significant difference in the burden of rare CNVs classified as a VUS between any of the IQ subgroups. There was a significantly (p=0.002) increased burden of rare genic duplications in individuals with schizophrenia and low IQ that persisted after excluding individuals with a pathogenic CNV. Using high-resolution microarrays we were able to demonstrate for the first time that the burden of pathogenic CNVs in schizophrenia differs significantly between IQ subgroups. The results of this study have implications for clinical practice and may help inform future rare variant studies of schizophrenia using next-generation sequencing technologies.

GEOquery: a bridge between the Gene Expression Omnibus (GEO) and BioConductor.

PubMed

Davis, Sean; Meltzer, Paul S

2007-07-15

Microarray technology has become a standard molecular biology tool. Experimental data have been generated on a huge number of organisms, tissue types, treatment conditions and disease states. The Gene Expression Omnibus (Barrett et al., 2005), developed by the National Center for Bioinformatics (NCBI) at the National Institutes of Health is a repository of nearly 140,000 gene expression experiments. The BioConductor project (Gentleman et al., 2004) is an open-source and open-development software project built in the R statistical programming environment (R Development core Team, 2005) for the analysis and comprehension of genomic data. The tools contained in the BioConductor project represent many state-of-the-art methods for the analysis of microarray and genomics data. We have developed a software tool that allows access to the wealth of information within GEO directly from BioConductor, eliminating many the formatting and parsing problems that have made such analyses labor-intensive in the past. The software, called GEOquery, effectively establishes a bridge between GEO and BioConductor. Easy access to GEO data from BioConductor will likely lead to new analyses of GEO data using novel and rigorous statistical and bioinformatic tools. Facilitating analyses and meta-analyses of microarray data will increase the efficiency with which biologically important conclusions can be drawn from published genomic data. GEOquery is available as part of the BioConductor project.

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

PubMed

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

2006-09-20

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

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

PubMed Central

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

2006-01-01

Background High throughput gene expression profiling (GEP) is becoming a routine technique in life science laboratories. With experimental designs that repeatedly span thousands of genes and hundreds of samples, relying on a dedicated database infrastructure is no longer an option. GEP technology is a fast moving target, with new approaches constantly broadening the field diversity. This technology heterogeneity, compounded by the informatics complexity of GEP databases, means that software developments have so far focused on mainstream techniques, leaving less typical yet established techniques such as Nylon microarrays at best partially supported. Results MAF (MicroArray Facility) is the laboratory database system we have developed for managing the design, production and hybridization of spotted microarrays. Although it can support the widely used glass microarrays and oligo-chips, MAF was designed with the specific idiosyncrasies of Nylon based microarrays in mind. Notably single channel radioactive probes, microarray stripping and reuse, vector control hybridizations and spike-in controls are all natively supported by the software suite. MicroArray Facility is MIAME supportive and dynamically provides feedback on missing annotations to help users estimate effective MIAME compliance. Genomic data such as clone identifiers and gene symbols are also directly annotated by MAF software using standard public resources. The MAGE-ML data format is implemented for full data export. Journalized database operations (audit tracking), data anonymization, material traceability and user/project level confidentiality policies are also managed by MAF. Conclusion MicroArray Facility is a complete data management system for microarray producers and end-users. Particular care has been devoted to adequately model Nylon based microarrays. The MAF system, developed and implemented in both private and academic environments, has proved a robust solution for shared facilities and industry service providers alike. PMID:16987406

Genome-wide association study of preeclampsia detects novel maternal single nucleotide polymorphisms and copy-number variants in subsets of the Hyperglycemia and Adverse Pregnancy Outcome (HAPO) study cohort

PubMed Central

Zhao, Linlu; Bracken, Michael B.; DeWan, Andrew T.

2013-01-01

Summary A genome-wide association study was undertaken to identify maternal single nucleotide polymorphisms (SNPs) and copy-number variants (CNVs) associated with preeclampsia. Case-control analysis was performed on 1070 Afro-Caribbean (n=21 cases and 1049 controls) and 723 Hispanic (n=62 cases and 661 controls) mothers and 1257 mothers of European ancestry (n=50 cases and 1207 controls) from the Hyperglycemia and Adverse Pregnancy Outcome (HAPO) study. European ancestry subjects were genotyped on Illumina Human610-Quad and Afro-Caribbean and Hispanic subjects were genotyped on Illumina Human1M-Duo BeadChip microarrays. Genome-wide SNP data were analyzed using PLINK. CNVs were called using three detection algorithms (GNOSIS, PennCNV, and QuantiSNP), merged using CNVision, and then screened using stringent criteria. SNP and CNV findings were compared to those of the Study of Pregnancy Hypertension in Iowa (SOPHIA), an independent preeclampsia case-control dataset of Caucasian mothers (n=177 cases and 116 controls). A list of top SNPs were identified for each of the HAPO ethnic groups, but none reached Bonferroni-corrected significance. Novel candidate CNVs showing enrichment among preeclampsia cases were also identified in each of the three ethnic groups. Several variants were suggestively replicated in SOPHIA. The discovered SNPs and copy-number variable regions present interesting candidate genetic variants for preeclampsia that warrant further replication and investigation. PMID:23551011

Genome-wide screen of ovary-specific DNA methylation in polycystic ovary syndrome.

PubMed

Yu, Ying-Ying; Sun, Cui-Xiang; Liu, Yin-Kun; Li, Yan; Wang, Li; Zhang, Wei

2015-07-01

To compare genome-wide DNA methylation profiles in ovary tissue from women with polycystic ovary syndrome (PCOS) and healthy controls. Case-control study matched for age and body mass index. University-affiliated hospital. Ten women with PCOS who underwent ovarian drilling to induce ovulation and 10 healthy women who were undergoing laparoscopic sterilization, hysterectomy for benign conditions, diagnostic laparoscopy for pelvic pain, or oophorectomy for nonovarian indications. None. Genome-wide DNA methylation patterns determined by immunoprecipitation and microarray (MeDIP-chip) analysis. The methylation levels were statistically significantly higher in CpG island shores (CGI shores), which lie outside of core promoter regions, and lower within gene bodies in women with PCOS relative to the controls. In addition, high CpG content promoters were the most frequently hypermethylated promoters in PCOS ovaries but were more often hypomethylated in controls. Second, 872 CGIs, specifically methylated in PCOS, represented 342 genes that could be associated with various molecular functions, including protein binding, hormone activity, and transcription regulator activity. Finally, methylation differences were validated in seven genes by methylation-specific polymerase chain reaction. These genes correlated to several functional families related to the pathogenesis of PCOS and may be potential biomarkers for this disease. Our results demonstrated that epigenetic modification differs between PCOS and normal ovaries, which may help to further understand the pathophysiology of this disease. Copyright © 2015 American Society for Reproductive Medicine. Published by Elsevier Inc. All rights reserved.

Diversity Arrays Technology (DArT) Marker Platforms for Diversity Analysis and Linkage Mapping in a Complex Crop, the Octoploid Cultivated Strawberry (Fragaria × ananassa)

PubMed Central

Sánchez-Sevilla, José F.; Horvath, Aniko; Botella, Miguel A.; Gaston, Amèlia; Folta, Kevin; Kilian, Andrzej; Denoyes, Beatrice; Amaya, Iraida

2015-01-01

Cultivated strawberry (Fragaria × ananassa) is a genetically complex allo-octoploid crop with 28 pairs of chromosomes (2n = 8x = 56) for which a genome sequence is not yet available. The diploid Fragaria vesca is considered the donor species of one of the octoploid sub-genomes and its available genome sequence can be used as a reference for genomic studies. A wide number of strawberry cultivars are stored in ex situ germplasm collections world-wide but a number of previous studies have addressed the genetic diversity present within a limited number of these collections. Here, we report the development and application of two platforms based on the implementation of Diversity Array Technology (DArT) markers for high-throughput genotyping in strawberry. The first DArT microarray was used to evaluate the genetic diversity of 62 strawberry cultivars that represent a wide range of variation based on phenotype, geographical and temporal origin and pedigrees. A total of 603 DArT markers were used to evaluate the diversity and structure of the population and their cluster analyses revealed that these markers were highly efficient in classifying the accessions in groups based on historical, geographical and pedigree-based cues. The second DArTseq platform took benefit of the complexity reduction method optimized for strawberry and the development of next generation sequencing technologies. The strawberry DArTseq was used to generate a total of 9,386 SNP markers in the previously developed ‘232’ × ‘1392’ mapping population, of which, 4,242 high quality markers were further selected to saturate this map after several filtering steps. The high-throughput platforms here developed for genotyping strawberry will facilitate genome-wide characterizations of large accessions sets and complement other available options. PMID:26675207

Novel genetic tools for studying food-borne Salmonella.

PubMed

Andrews-Polymenis, Helene L; Santiviago, Carlos A; McClelland, Michael

2009-04-01

Nontyphoidal Salmonellae are highly prevalent food-borne pathogens. High-throughput sequencing of Salmonella genomes is expanding our knowledge of the evolution of serovars and epidemic isolates. Genome sequences have also allowed the creation of complete microarrays. Microarrays have improved the throughput of in vivo expression technology (IVET) used to uncover promoters active during infection. In another method, signature tagged mutagenesis (STM), pools of mutants are subjected to selection. Changes in the population are monitored on a microarray, revealing genes under selection. Complete genome sequences permit the construction of pools of targeted in-frame deletions that have improved STM by minimizing the number of clones and the polarity of each mutant. Together, genome sequences and the continuing development of new tools for functional genomics will drive a revolution in the understanding of Salmonellae in many different niches that are critical for food safety.

Identification of a gene module associated with BMD through the integration of network analysis and genome-wide association data.

PubMed

Farber, Charles R

2010-11-01

Bone mineral density (BMD) is influenced by a complex network of gene interactions; therefore, elucidating the relationships between genes and how those genes, in turn, influence BMD is critical for developing a comprehensive understanding of osteoporosis. To investigate the role of transcriptional networks in the regulation of BMD, we performed a weighted gene coexpression network analysis (WGCNA) using microarray expression data on monocytes from young individuals with low or high BMD. WGCNA groups genes into modules based on patterns of gene coexpression. and our analysis identified 11 gene modules. We observed that the overall expression of one module (referred to as module 9) was significantly higher in the low-BMD group (p = .03). Module 9 was highly enriched for genes belonging to the immune system-related gene ontology (GO) category "response to virus" (p = 7.6 × 10(-11)). Using publically available genome-wide association study data, we independently validated the importance of module 9 by demonstrating that highly connected module 9 hubs were more likely, relative to less highly connected genes, to be genetically associated with BMD. This study highlights the advantages of systems-level analyses to uncover coexpression modules associated with bone mass and suggests that particular monocyte expression patterns may mediate differences in BMD. © 2010 American Society for Bone and Mineral Research.

Novel applications of array comparative genomic hybridization in molecular diagnostics.

PubMed

Cheung, Sau W; Bi, Weimin

2018-05-31

In 2004, the implementation of array comparative genomic hybridization (array comparative genome hybridization [CGH]) into clinical practice marked a new milestone for genetic diagnosis. Array CGH and single-nucleotide polymorphism (SNP) arrays enable genome-wide detection of copy number changes in a high resolution, and therefore microarray has been recognized as the first-tier test for patients with intellectual disability or multiple congenital anomalies, and has also been applied prenatally for detection of clinically relevant copy number variations in the fetus. Area covered: In this review, the authors summarize the evolution of array CGH technology from their diagnostic laboratory, highlighting exonic SNP arrays developed in the past decade which detect small intragenic copy number changes as well as large DNA segments for the region of heterozygosity. The applications of array CGH to human diseases with different modes of inheritance with the emphasis on autosomal recessive disorders are discussed. Expert commentary: An exonic array is a powerful and most efficient clinical tool in detecting genome wide small copy number variants in both dominant and recessive disorders. However, whole-genome sequencing may become the single integrated platform for detection of copy number changes, single-nucleotide changes as well as balanced chromosomal rearrangements in the near future.

Approximate geodesic distances reveal biologically relevant structures in microarray data.

PubMed

Nilsson, Jens; Fioretos, Thoas; Höglund, Mattias; Fontes, Magnus

2004-04-12

Genome-wide gene expression measurements, as currently determined by the microarray technology, can be represented mathematically as points in a high-dimensional gene expression space. Genes interact with each other in regulatory networks, restricting the cellular gene expression profiles to a certain manifold, or surface, in gene expression space. To obtain knowledge about this manifold, various dimensionality reduction methods and distance metrics are used. For data points distributed on curved manifolds, a sensible distance measure would be the geodesic distance along the manifold. In this work, we examine whether an approximate geodesic distance measure captures biological similarities better than the traditionally used Euclidean distance. We computed approximate geodesic distances, determined by the Isomap algorithm, for one set of lymphoma and one set of lung cancer microarray samples. Compared with the ordinary Euclidean distance metric, this distance measure produced more instructive, biologically relevant, visualizations when applying multidimensional scaling. This suggests the Isomap algorithm as a promising tool for the interpretation of microarray data. Furthermore, the results demonstrate the benefit and importance of taking nonlinearities in gene expression data into account.

Tracing phylogenomic events leading to diversity of Haemophilus influenzae and the emergence of Brazilian Purpuric Fever (BPF)-associated clones

PubMed Central

Papazisi, Leka; Ratnayake, Shashikala; Remortel, Brian G.; Bock, Geoffrey R.; Liang, Wei; Saeed, Alexander I.; Liu, Jia; Fleischmann, Robert D.; Kilian, Mogens; Peterson, Scott N.

2010-01-01

Here we report the use of a multi-genome DNA microarray to elucidate the genomic events associated with the emergence of the clonal variants of H. influenzae biogroup aegyptius causing Brazilian Purpuric Fever (BPF), an important pediatric disease with a high mortality rate. We performed directed genome sequencing of strain HK1212 unique loci to construct a species DNA microarray. Comparative genome hybridization using this microarray enabled us to determine and compare gene complements, and infer reliable phylogenomic relationships among members of the species. The higher genomic variability observed in the genomes of BPF-related strains (clones) and their close relatives may be characterized by significant gene flux related to a subset of functional role categories. We found that the acquisition of a large number of virulence determinants featuring numerous cell membrane proteins coupled to the loss of genes involved in transport, central biosynthetic pathways and in particular, energy production pathways to be characteristics of the BPF genomic variants. PMID:20654709

Development of a Custom-Designed, Pan Genomic DNA Microarray to Characterize Strain-Level Diversity among Cronobacter spp.

PubMed Central

Tall, Ben Davies; Gangiredla, Jayanthi; Gopinath, Gopal R.; Yan, Qiongqiong; Chase, Hannah R.; Lee, Boram; Hwang, Seongeun; Trach, Larisa; Park, Eunbi; Yoo, YeonJoo; Chung, TaeJung; Jackson, Scott A.; Patel, Isha R.; Sathyamoorthy, Venugopal; Pava-Ripoll, Monica; Kotewicz, Michael L.; Carter, Laurenda; Iversen, Carol; Pagotto, Franco; Stephan, Roger; Lehner, Angelika; Fanning, Séamus; Grim, Christopher J.

2015-01-01

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:Cronobacter sakazakii, Cronobacter malonaticus, Cronobacter turicensis, Cronobacter muytjensii, Cronobacter dublinensis, Cronobacter universalis, and Cronobacter 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 toward the development of future countermeasures against this foodborne pathogen in the food safety and clinical arenas. PMID:25984509

Use of whole genome expression analysis in the toxicity screening of nanoparticles

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

Fröhlich, Eleonore, E-mail: eleonore.froehlich@medunigraz.at; Meindl, Claudia; Wagner, Karin

2014-10-15

The use of nanoparticles (NPs) offers exciting new options in technical and medical applications provided they do not cause adverse cellular effects. Cellular effects of NPs depend on particle parameters and exposure conditions. In this study, whole genome expression arrays were employed to identify the influence of particle size, cytotoxicity, protein coating, and surface functionalization of polystyrene particles as model particles and for short carbon nanotubes (CNTs) as particles with potential interest in medical treatment. Another aim of the study was to find out whether screening by microarray would identify other or additional targets than commonly used cell-based assays formore » NP action. Whole genome expression analysis and assays for cell viability, interleukin secretion, oxidative stress, and apoptosis were employed. Similar to conventional assays, microarray data identified inflammation, oxidative stress, and apoptosis as affected by NP treatment. Application of lower particle doses and presence of protein decreased the total number of regulated genes but did not markedly influence the top regulated genes. Cellular effects of CNTs were small; only carboxyl-functionalized single-walled CNTs caused appreciable regulation of genes. It can be concluded that regulated functions correlated well with results in cell-based assays. Presence of protein mitigated cytotoxicity but did not cause a different pattern of regulated processes. - Highlights: • Regulated functions were screened using whole genome expression assays. • Polystyrene particles regulated more genes than short carbon nanotubes. • Protein coating of polystyrene particles did not change regulation pattern. • Functions regulated by microarray were confirmed by cell-based assay.« less

Insights into the degradation capacities of Amycolatopsis tucumanensis DSM 45259 guided by microarray data.

PubMed

Bourguignon, Natalia; Bargiela, Rafael; Rojo, David; Chernikova, Tatyana N; de Rodas, Sara A López; García-Cantalejo, Jesús; Näther, Daniela J; Golyshin, Peter N; Barbas, Coral; Ferrero, Marcela; Ferrer, Manuel

2016-12-01

The analysis of catabolic capacities of microorganisms is currently often achieved by cultivation approaches and by the analysis of genomic or metagenomic datasets. Recently, a microarray system designed from curated key aromatic catabolic gene families and key alkane degradation genes was designed. The collection of genes in the microarray can be exploited to indicate whether a given microbe or microbial community is likely to be functionally connected with certain degradative phenotypes, without previous knowledge of genome data. Herein, this microarray was applied to capture new insights into the catabolic capacities of copper-resistant actinomycete Amycolatopsis tucumanensis DSM 45259. The array data support the presumptive ability of the DSM 45259 strain to utilize single alkanes (n-decane and n-tetradecane) and aromatics such as benzoate, phthalate and phenol as sole carbon sources, which was experimentally validated by cultivation and mass spectrometry. Interestingly, while in strain DSM 45259 alkB gene encoding an alkane hydroxylase is most likely highly similar to that found in other actinomycetes, the genes encoding benzoate 1,2-dioxygenase, phthalate 4,5-dioxygenase and phenol hydroxylase were homologous to proteobacterial genes. This suggests that strain DSM 45259 contains catabolic genes distantly related to those found in other actinomycetes. Together, this study not only provided new insight into the catabolic abilities of strain DSM 45259, but also suggests that this strain contains genes uncommon within actinomycetes.

Link between epigenomic alterations and genome-wide aberrant transcriptional response to allergen in dendritic cells conveying maternal asthma risk.

PubMed

Mikhaylova, Lyudmila; Zhang, Yiming; Kobzik, Lester; Fedulov, Alexey V

2013-01-01

We investigated the link between epigenome-wide methylation aberrations at birth and genomic transcriptional changes upon allergen sensitization that occur in the neonatal dendritic cells (DC) due to maternal asthma. We previously demonstrated that neonates of asthmatic mothers are born with a functional skew in splenic DCs that can be seen even in allergen-naïve pups and can convey allergy responses to normal recipients. However, minimal-to-no transcriptional or phenotypic changes were found to explain this alteration. Here we provide in-depth analysis of genome-wide DNA methylation profiles and RNA transcriptional (microarray) profiles before and after allergen sensitization. We identified differentially methylated and differentially expressed loci and performed manually-curated matching of methylation status of the key regulatory sequences (promoters and CpG islands) to expression of their respective transcripts before and after sensitization. We found that while allergen-naive DCs from asthma-at-risk neonates have minimal transcriptional change compared to controls, the methylation changes are extensive. The substantial transcriptional change only becomes evident upon allergen sensitization, when it occurs in multiple genes with the pre-existing epigenetic alterations. We demonstrate that maternal asthma leads to both hyper- and hypomethylation in neonatal DCs, and that both types of events at various loci significantly overlap with transcriptional responses to allergen. Pathway analysis indicates that approximately 1/2 of differentially expressed and differentially methylated genes directly interact in known networks involved in allergy and asthma processes. We conclude that congenital epigenetic changes in DCs are strongly linked to altered transcriptional responses to allergen and to early-life asthma origin. The findings are consistent with the emerging paradigm that asthma is a disease with underlying epigenetic changes.

Genome-Wide Analysis of Host Responses to Four Different Types of Microorganisms in Bombyx Mori (Lepidoptera: Bombycidae).

PubMed

Cheng, Tingcai; Lin, Ping; Huang, Lulin; Wu, Yuqian; Jin, Shengkai; Liu, Chun; Xia, Qingyou

2016-01-01

Several pathogenic microorganisms have been used to investigate the genome-wide transcriptional responses of Bombyx mori to infection. However, studies have so far each focused on one microorganism, and systematic genome-wide comparison of transcriptional responses to different pathogenic microorganisms has not been undertaken. Here, we surveyed transcriptional responses of B. mori to its natural bacterial, viral, and fungal pathogens, Bacillus bombyseptieus, B. mori nucleopolyhedrovirus (BmNPV), and Beauveria bassiana, respectively, and to nonpathogenic Escherichia coli, by microarray analysis. In total, the expression of 2,436, 1,804, 1,743, and 912 B. mori genes was modulated by infection with B. bombyseptieus, BmNPV, B. bassiana, and E. coli, respectively. Notably, the expression of 620, 400, 177, or 165 of these genes was only modulated by infection with B. bombyseptieus, BmNPV, B. bassiana, or E. coli, respectively. In contrast to the expression of genes related to juvenile hormone synthesis and metabolism, that of genes encoding juvenile hormone binding proteins was microorganism-specific. Three basal metabolic pathways were modulated by infection with any of the four microorganisms, and 3, 14, 5, and 2 metabolic pathways were specifically modulated by infection with B. bombyseptieus, BmNPV, B. bassiana, and E. coli, respectively. Interestingly, BmNPV infection modulated the JAK/STAT signaling pathway, whereas both the Imd and Toll signaling pathways were modulated by infection with B. bombyseptieus, B. bassiana, or E. coli These results elucidate potential molecular mechanisms of the host response to different microorganisms, and provide a foundation for further work on host-pathogen interaction. © The Author 2016. Published by Oxford University Press on behalf of the Entomological Society of America.

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

PubMed

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

2015-01-01

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

Genomic resources in fruit plants: an assessment of current status.

PubMed

Rai, Manoj K; Shekhawat, N S

2015-01-01

The availability of many genomic resources such as genome sequences, functional genomics resources including microarrays and RNA-seq, sufficient numbers of molecular markers, express sequence tags (ESTs) and high-density genetic maps is causing a rapid acceleration of genetics and genomic research of many fruit plants. This is leading to an increase in our knowledge of the genes that are linked to many horticultural and agronomically important traits. Recently, some progress has also been made on the identification and functional analysis of miRNAs in some fruit plants. This is one of the most active research fields in plant sciences. The last decade has witnessed development of genomic resources in many fruit plants such as apple, banana, citrus, grapes, papaya, pears, strawberry etc.; however, many of them are still not being exploited. Furthermore, owing to lack of resources, infrastructure and research facilities in many lesser-developed countries, development of genomic resources in many underutilized or less-studied fruit crops, which grow in these countries, is limited. Thus, research emphasis should be given to those fruit crops for which genomic resources are relatively scarce. The development of genomic databases of these less-studied fruit crops will enable biotechnologists to identify target genes that underlie key horticultural and agronomical traits. This review presents an overview of the current status of the development of genomic resources in fruit plants with the main emphasis being on genome sequencing, EST resources, functional genomics resources including microarray and RNA-seq, identification of quantitative trait loci and construction of genetic maps as well as efforts made on the identification and functional analysis of miRNAs in fruit plants.

Genome-wide discovery of novel and conserved microRNAs in white shrimp (Litopenaeus vannamei).

PubMed

Xi, Qian-Yun; Xiong, Yuan-Yan; Wang, Yuan-Mei; Cheng, Xiao; Qi, Qi-En; Shu, Gang; Wang, Song-Bo; Wang, Li-Na; Gao, Ping; Zhu, Xiao-Tong; Jiang, Qing-Yan; Zhang, Yong-Liang; Liu, Li

2015-01-01

Of late years, a large amount of conserved and species-specific microRNAs (miRNAs) have been performed on identification from species which are economically important but lack a full genome sequence. In this study, Solexa deep sequencing and cross-species miRNA microarray were used to detect miRNAs in white shrimp. We identified 239 conserved miRNAs, 14 miRNA* sequences and 20 novel miRNAs by bioinformatics analysis from 7,561,406 high-quality reads representing 325,370 distinct sequences. The all 20 novel miRNAs were species-specific in white shrimp and not homologous in other species. Using the conserved miRNAs from the miRBase database as a query set to search for homologs from shrimp expressed sequence tags (ESTs), 32 conserved computationally predicted miRNAs were discovered in shrimp. In addition, using microarray analysis in the shrimp fed with Panax ginseng polysaccharide complex, 151 conserved miRNAs were identified, 18 of which were significant up-expression, while 49 miRNAs were significant down-expression. In particular, qRT-PCR analysis was also performed for nine miRNAs in three shrimp tissues such as muscle, gill and hepatopancreas. Results showed that these miRNAs expression are tissue specific. Combining results of the three methods, we detected 20 novel and 394 conserved miRNAs. Verification with quantitative reverse transcription (qRT-PCR) and Northern blot showed a high confidentiality of data. The study provides the first comprehensive specific miRNA profile of white shrimp, which includes useful information for future investigations into the function of miRNAs in regulation of shrimp development and immunology.

Aberrant expression of long noncoding RNAs in cumulus cells isolated from PCOS patients.

PubMed

Huang, Xin; Hao, Cuifang; Bao, Hongchu; Wang, Meimei; Dai, Huangguan

2016-01-01

To describe the long noncoding RNA (lncRNA) profiles in cumulus cells isolated from polycystic ovary syndrome (PCOS) patients by employing a microarray and in-depth bioinformatics analysis. This information will help us understand the occurrence and development of PCOS. In this study, we used a microarray to describe lncRNA profiles in cumulus cells isolated from ten patients (five PCOS and five normal women). Several differentially expressed lncRNAs were chosen to validate the microarray results by quantitative RT-PCR (qRT-PCR). Then, the differentially expressed lncRNAs were classified into three subgroups (HOX loci lncRNA, enhancer-like lncRNA, and lincRNA) to deduce their potential features. Furthermore, a lncRNA/mRNA co-expression network was constructed by using the Cytoscape software (V2.8.3, http://www.cytoscape.org/ ). We observed that 623 lncRNAs and 260 messenger RNAs (mRNAs) were significantly up- or down-regulated (≥2-fold change), and these differences could be used to discriminate cumulus cells of PCOS from those of normal patients. Five differentially expressed lncRNAs (XLOC_011402, ENST00000454271, ENST00000433673, ENST00000450294, and ENST00000432431) were selected to validate the microarray results using quantitative RT-PCR (qRT-PCR). The qRT-PCR results were consistent with the microarray data. Further analysis indicated that many differentially expressed lncRNAs were transcribed from chromosome 2 and may act as enhancers to regulate their neighboring protein-coding genes. Forty-three lncRNAs and 29 mRNAs were used to construct the coding-non-coding gene co-expression network. Most pairs positively correlated, and one mRNA correlated with one or more lncRNAs. Our study is the first to determine genome-wide lncRNA expression patterns in cumulus cells isolated from PCOS patients by microarray. The results show that clusters of lncRNAs were aberrantly expressed in cumulus cells of PCOS patients compared with those of normal women, which revealed that lncRNAs differentially expressed in PCOS and normal women may contribute to the occurrence of PCOS and affect oocyte development.

Genome-wide analysis of the heat stress response in Zebu (Sahiwal) cattle.

PubMed

Mehla, Kusum; Magotra, Ankit; Choudhary, Jyoti; Singh, A K; Mohanty, A K; Upadhyay, R C; Srinivasan, Surendran; Gupta, Pankaj; Choudhary, Neelam; Antony, Bristo; Khan, Farheen

2014-01-10

Environmental-induced hyperthermia compromises animal production with drastic economic consequences to global animal agriculture and jeopardizes animal welfare. Heat stress is a major stressor that occurs as a result of an imbalance between heat production within the body and its dissipation and it affects animals at cellular, molecular and ecological levels. The molecular mechanism underlying the physiology of heat stress in the cattle remains undefined. The present study sought to evaluate mRNA expression profiles in the cattle blood in response to heat stress. In this study we report the genes that were differentially expressed in response to heat stress using global scale genome expression technology (Microarray). Four Sahiwal heifers were exposed to 42°C with 90% humidity for 4h followed by normothermia. Gene expression changes include activation of heat shock transcription factor 1 (HSF1), increased expression of heat shock proteins (HSP) and decreased expression and synthesis of other proteins, immune system activation via extracellular secretion of HSP. A cDNA microarray analysis found 140 transcripts to be up-regulated and 77 down-regulated in the cattle blood after heat treatment (P<0.05). But still a comprehensive explanation for the direction of fold change and the specific genes involved in response to acute heat stress still remains to be explored. These findings may provide insights into the underlying mechanism of physiology of heat stress in cattle. Understanding the biology and mechanisms of heat stress is critical to developing approaches to ameliorate current production issues for improving animal performance and agriculture economics. © 2013 Elsevier B.V. All rights reserved.

Effects of Temperature on the Meiotic Recombination Landscape of the Yeast Saccharomyces cerevisiae

PubMed Central

Zhang, Ke; Wu, Xue-Chang

2017-01-01

ABSTRACT Although meiosis in warm-blooded organisms takes place in a narrow temperature range, meiosis in many organisms occurs over a wide variety of temperatures. We analyzed the properties of meiosis in the yeast Saccharomyces cerevisiae in cells sporulated at 14°C, 30°C, or 37°C. Using comparative-genomic-hybridization microarrays, we examined the distribution of Spo11-generated meiosis-specific double-stranded DNA breaks throughout the genome. Although there were between 300 and 400 regions of the genome with high levels of recombination (hot spots) observed at each temperature, only about 20% of these hot spots were found to have occurred independently of the temperature. In S. cerevisiae, regions near the telomeres and centromeres tend to have low levels of meiotic recombination. This tendency was observed in cells sporulated at 14°C and 30°C, but not at 37°C. Thus, the temperature of sporulation in yeast affects some global property of chromosome structure relevant to meiotic recombination. Using single-nucleotide polymorphism (SNP)-specific whole-genome microarrays, we also examined crossovers and their associated gene conversion events as well as gene conversion events that were unassociated with crossovers in all four spores of tetrads obtained by sporulation of diploids at 14°C, 30°C, or 37°C. Although tetrads from cells sporulated at 30°C had slightly (20%) more crossovers than those derived from cells sporulated at the other two temperatures, spore viability was good at all three temperatures. Thus, despite temperature-induced variation in the genetic maps, yeast cells produce viable haploid products at a wide variety of sporulation temperatures. PMID:29259092

Development and assessment of whole-genome oligonucleotide microarrays to analyze an anaerobic microbial community and its responses to oxidative stress.

PubMed

Scholten, Johannes C M; Culley, David E; Nie, Lei; Munn, Kyle J; Chow, Lely; Brockman, Fred J; Zhang, Weiwen

2007-06-29

The application of DNA microarray technology to investigate multiple-species microbial communities presents great challenges. In this study, we reported the design and quality assessment of four whole genome oligonucleotide microarrays for two syntroph bacteria, Desulfovibrio vulgaris and Syntrophobacter fumaroxidans, and two archaeal methanogens, Methanosarcina barkeri, and Methanospirillum hungatei, and their application to analyze global gene expression in a four-species microbial community in response to oxidative stress. In order to minimize the possibility of cross-hybridization, cross-genome comparison was performed to assure all probes unique to each genome so that the microarrays could provide species-level resolution. Microarray quality was validated by the good reproducibility of experimental measurements of multiple biological and analytical replicates. This study showed that S. fumaroxidans and M. hungatei responded to the oxidative stress with up-regulation of several genes known to be involved in reactive oxygen species (ROS) detoxification, such as catalase and rubrerythrin in S. fumaroxidans and thioredoxin and heat shock protein Hsp20 in M. hungatei. However, D. vulgaris seemed to be less sensitive to the oxidative stress as a member of a four-species community, since no gene involved in ROS detoxification was up-regulated. Our work demonstrated the successful application of microarrays to a multiple-species microbial community, and our preliminary results indicated that this approach could provide novel insights on the metabolism within microbial communities.

A novel comparative pattern count analysis reveals a chronic ethanol-induced dynamic shift in immediate early NF-κB genome-wide promoter binding during liver regeneration.

PubMed

Kuttippurathu, Lakshmi; Patra, Biswanath; Hoek, Jan B; Vadigepalli, Rajanikanth

2016-03-01

Liver regeneration after partial hepatectomy is a clinically important process that is impaired by adaptation to chronic alcohol intake. We focused on the initial time points following partial hepatectomy (PHx) to analyze the genome-wide binding activity of NF-κB, a key immediate early regulator. We investigated the effect of chronic alcohol intake on immediate early NF-κB genome-wide localization, in the adapted state as well as in response to partial hepatectomy, using chromatin immunoprecipitation followed by promoter microarray analysis. We found many ethanol-specific NF-κB binding target promoters in the ethanol-adapted state, corresponding to the regulation of biosynthetic processes, oxidation-reduction and apoptosis. Partial hepatectomy induced a diet-independent shift in NF-κB binding loci relative to the transcription start sites. We employed a novel pattern count analysis to exhaustively enumerate and compare the number of promoters corresponding to the temporal binding patterns in ethanol and pair-fed control groups. The highest pattern count corresponded to promoters with NF-κB binding exclusively in the ethanol group at 1 h post PHx. This set was associated with the regulation of cell death, response to oxidative stress, histone modification, mitochondrial function, and metabolic processes. Integration with the global gene expression profiles to identify putative transcriptional consequences of NF-κB binding patterns revealed that several of ethanol-specific 1 h binding targets showed ethanol-specific differential expression through 6 h post PHx. Motif analysis yielded co-incident binding loci for STAT3, AP-1, CREB, C/EBP-β, PPAR-γ and C/EBP-α, likely participating in co-regulatory modules with NF-κB in shaping the immediate early response to PHx. We conclude that adaptation to chronic ethanol intake disrupts the NF-κB promoter binding landscape with consequences for the immediate early gene regulatory response to the acute challenge of PHx.

Identification of the TFII-I family target genes in the vertebrate genome.

PubMed

Chimge, Nyam-Osor; Makeyev, Aleksandr V; Ruddle, Frank H; Bayarsaihan, Dashzeveg

2008-07-01

GTF2I and GTF2IRD1 encode members of the TFII-I transcription factor family and are prime candidates in the Williams syndrome, a complex neurodevelopmental disorder. Our previous expression microarray studies implicated TFII-I proteins in the regulation of a number of genes critical in various aspects of cell physiology. Here, we combined bioinformatics and microarray results to identify TFII-I downstream targets in the vertebrate genome. These results were validated by chromatin immunoprecipitation and siRNA analysis. The collected evidence revealed the complexity of TFII-I-mediated processes that involve distinct regulatory networks. Altogether, these results lead to a better understanding of specific molecular events, some of which may be responsible for the Williams syndrome phenotype.

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

PubMed

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

2013-02-01

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

Research and development of biochip technologies in Taiwan

NASA Astrophysics Data System (ADS)

Ting, Solomon J.; Chiou, Arthur E. T.

2000-07-01

Recent advancements in several genome-sequencing projects have stimulated an enormous interest in microarray DNA chip technology, especially in the biomedical sciences and pharmaceutical industries. The DNA chips facilitated the miniaturization of conventional nucleic acid hybridizations, by either robotically spotting thousands of library cDNAs or in situ synthesis of high-density oligonucleotides onto solid supports. These innovations have found a wide range of applications in molecular biology, especially in studying gene expression and discovering new genes from the global view of genomic analysis. The research and development of this powerful tool has also received great attentions in Taiwan. In this paper, we report the current progresses of our DNA chip project, along with the current status of other biochip projects in Taiwan, such as protein chip, PCR chip, electrophoresis chip, olfactory chip, etc. The new development of biochip technologies integrates the biotechnology with the semiconductor processing, the micro- electro-mechanical, optoelectronic, and digital signal processing technologies. Most of these biochip technologies utilitze optical detection methods for data acquisition and analysis. The strengths and advantages of different approaches are compared and discussed in this report.

A comprehensive survey of the Plasmodium life cycle by genomic, transcriptomic, and proteomic analyses.

PubMed

Hall, Neil; Karras, Marianna; Raine, J Dale; Carlton, Jane M; Kooij, Taco W A; Berriman, Matthew; Florens, Laurence; Janssen, Christoph S; Pain, Arnab; Christophides, Georges K; James, Keith; Rutherford, Kim; Harris, Barbara; Harris, David; Churcher, Carol; Quail, Michael A; Ormond, Doug; Doggett, Jon; Trueman, Holly E; Mendoza, Jacqui; Bidwell, Shelby L; Rajandream, Marie-Adele; Carucci, Daniel J; Yates, John R; Kafatos, Fotis C; Janse, Chris J; Barrell, Bart; Turner, C Michael R; Waters, Andrew P; Sinden, Robert E

2005-01-07

Plasmodium berghei and Plasmodium chabaudi are widely used model malaria species. Comparison of their genomes, integrated with proteomic and microarray data, with the genomes of Plasmodium falciparum and Plasmodium yoelii revealed a conserved core of 4500 Plasmodium genes in the central regions of the 14 chromosomes and highlighted genes evolving rapidly because of stage-specific selective pressures. Four strategies for gene expression are apparent during the parasites' life cycle: (i) housekeeping; (ii) host-related; (iii) strategy-specific related to invasion, asexual replication, and sexual development; and (iv) stage-specific. We observed posttranscriptional gene silencing through translational repression of messenger RNA during sexual development, and a 47-base 3' untranslated region motif is implicated in this process.

Unraveling the Specific Ischemic Core and Penumbra Transcriptome in the Permanent Middle Cerebral Artery Occlusion Mouse Model Brain Treated with the Neuropeptide PACAP38

PubMed Central

Hori, Motohide; Nakamachi, Tomoya; Shibato, Junko; Rakwal, Randeep; Shioda, Seiji; Numazawa, Satoshi

2015-01-01

Our group has been systematically investigating the effects of the neuropeptide pituitary adenylate-cyclase activating polypeptide (PACAP) on the ischemic brain. To do so, we have established and utilized the permanent middle cerebral artery occlusion (PMCAO) mouse model, in which PACAP38 (1 pmol) injection is given intracerebroventrically and compared to a control saline (0.9% sodium chloride, NaCl) injection, to unravel genome-wide gene expression changes using a high-throughput DNA microarray analysis approach. In our previous studies, we have accumulated a large volume of data (gene inventory) from the whole brain (ipsilateral and contralateral hemispheres) after both PMCAO and post-PACAP38 injection. In our latest research, we have targeted specifically infarct or ischemic core (hereafter abbreviated IC) and penumbra (hereafter abbreviated P) post-PACAP38 injections in order to re-examine the transcriptome at 6 and 24 h post injection. The current study aims to delineate the specificity of expression and localization of differentially expressed molecular factors influenced by PACAP38 in the IC and P regions. Utilizing the mouse 4 × 44 K whole genome DNA chip we show numerous changes (≧/≦ 1.5/0.75-fold) at both 6 h (654 and 456, and 522 and 449 up- and down-regulated genes for IC and P, respectively) and 24 h (2568 and 2684, and 1947 and 1592 up- and down-regulated genes for IC and P, respectively) after PACAP38 treatment. Among the gene inventories obtained here, two genes, brain-derived neurotrophic factor (Bdnf) and transthyretin (Ttr) were found to be induced by PACAP38 treatment, which we had not been able to identify previously using the whole hemisphere transcriptome analysis. Using bioinformatics analysis by pathway- or specific-disease-state focused gene classifications and Ingenuity Pathway Analysis (IPA) the differentially expressed genes are functionally classified and discussed. Among these, we specifically discuss some novel and previously identified genes, such as alpha hemoglobin stabilizing protein (Ahsp), cathelicidin antimicrobial peptide (Camp), chemokines, interferon beta 1 (Ifnb1), and interleukin 6 (Il6) in context of PACAP38-mediated neuroprotection in the ischemic brain. Taken together, the DNA microarray analysis provides not only a great resource for further study, but also reinforces the importance of region-specific analyses in genome-wide identification of target molecular factors that might play a role in the neuroprotective function of PACAP38. PMID:27600210

Novel approach for deriving genome wide SNP analysis data from archived blood spots

PubMed Central

2012-01-01

Background The ability to transport and store DNA at room temperature in low volumes has the advantage of optimising cost, time and storage space. Blood spots on adapted filter papers are popular for this, with FTA (Flinders Technology Associates) Whatman™TM technology being one of the most recent. Plant material, plasmids, viral particles, bacteria and animal blood have been stored and transported successfully using this technology, however the method of porcine DNA extraction from FTA Whatman™TM cards is a relatively new approach, allowing nucleic acids to be ready for downstream applications such as PCR, whole genome amplification, sequencing and subsequent application to single nucleotide polymorphism microarrays has hitherto been under-explored. Findings DNA was extracted from FTA Whatman™TM cards (following adaptations of the manufacturer’s instructions), whole genome amplified and subsequently analysed to validate the integrity of the DNA for downstream SNP analysis. DNA was successfully extracted from 288/288 samples and amplified by WGA. Allele dropout post WGA, was observed in less than 2% of samples and there was no clear evidence of amplification bias nor contamination. Acceptable call rates on porcine SNP chips were also achieved using DNA extracted and amplified in this way. Conclusions DNA extracted from FTA Whatman cards is of a high enough quality and quantity following whole genomic amplification to perform meaningful SNP chip studies. PMID:22974252

Identifying molecular features for prostate cancer with Gleason 7 based on microarray gene expression profiles.

PubMed

Bălăcescu, Loredana; Bălăcescu, O; Crişan, N; Fetica, B; Petruţ, B; Bungărdean, Cătălina; Rus, Meda; Tudoran, Oana; Meurice, G; Irimie, Al; Dragoş, N; Berindan-Neagoe, Ioana

2011-01-01

Prostate cancer represents the first leading cause of cancer among western male population, with different clinical behavior ranging from indolent to metastatic disease. Although many molecules and deregulated pathways are known, the molecular mechanisms involved in the development of prostate cancer are not fully understood. The aim of this study was to explore the molecular variation underlying the prostate cancer, based on microarray analysis and bioinformatics approaches. Normal and prostate cancer tissues were collected by macrodissection from prostatectomy pieces. All prostate cancer specimens used in our study were Gleason score 7. Gene expression microarray (Agilent Technologies) was used for Whole Human Genome evaluation. The bioinformatics and functional analysis were based on Limma and Ingenuity software. The microarray analysis identified 1119 differentially expressed genes between prostate cancer and normal prostate, which were up- or down-regulated at least 2-fold. P-values were adjusted for multiple testing using Benjamini-Hochberg method with a false discovery rate of 0.01. These genes were analyzed with Ingenuity Pathway Analysis software and were established 23 genetic networks. Our microarray results provide new information regarding the molecular networks in prostate cancer stratified as Gleason 7. These data highlighted gene expression profiles for better understanding of prostate cancer progression.

Bioinformatics analysis of differentially expressed gene profiles associated with systemic lupus erythematosus

PubMed Central

Wu, Chengjiang; Zhao, Yangjing; Lin, Yu; Yang, Xinxin; Yan, Meina; Min, Yujiao; Pan, Zihui; Xia, Sheng; Shao, Qixiang

2018-01-01

DNA microarray and high-throughput sequencing have been widely used to identify the differentially expressed genes (DEGs) in systemic lupus erythematosus (SLE). However, the big data from gene microarrays are also challenging to work with in terms of analysis and processing. The presents study combined data from the microarray expression profile (GSE65391) and bioinformatics analysis to identify the key genes and cellular pathways in SLE. Gene ontology (GO) and cellular pathway enrichment analyses of DEGs were performed to investigate significantly enriched pathways. A protein-protein interaction network was constructed to determine the key genes in the occurrence and development of SLE. A total of 310 DEGs were identified in SLE, including 193 upregulated genes and 117 downregulated genes. GO analysis revealed that the most significant biological process of DEGs was immune system process. Kyoto Encyclopedia of Genes and Genome pathway analysis showed that these DEGs were enriched in signaling pathways associated with the immune system, including the RIG-I-like receptor signaling pathway, intestinal immune network for IgA production, antigen processing and presentation and the toll-like receptor signaling pathway. The current study screened the top 10 genes with higher degrees as hub genes, which included 2′-5′-oligoadenylate synthetase 1, MX dynamin like GTPase 2, interferon induced protein with tetratricopeptide repeats 1, interferon regulatory factor 7, interferon induced with helicase C domain 1, signal transducer and activator of transcription 1, ISG15 ubiquitin-like modifier, DExD/H-box helicase 58, interferon induced protein with tetratricopeptide repeats 3 and 2′-5′-oligoadenylate synthetase 2. Module analysis revealed that these hub genes were also involved in the RIG-I-like receptor signaling, cytosolic DNA-sensing, toll-like receptor signaling and ribosome biogenesis pathways. In addition, these hub genes, from different probe sets, exhibited significant co-expressed tendency in multi-experiment microarray datasets (P<0.01). In conclusion, these key genes and cellular pathways may improve the current understanding of the underlying mechanism of development of SLE. These key genes may be potential biomarkers of diagnosis, therapy and prognosis for SLE. PMID:29257335

Integrative Genome-Wide Gene Expression Profiling of Clear Cell Renal Cell Carcinoma in Czech Republic and in the United States

PubMed Central

Wozniak, Magdalena B.; Le Calvez-Kelm, Florence; Abedi-Ardekani, Behnoush; Byrnes, Graham; Durand, Geoffroy; Carreira, Christine; Michelon, Jocelyne; Janout, Vladimir; Holcatova, Ivana; Foretova, Lenka; Brisuda, Antonin; Lesueur, Fabienne; McKay, James; Brennan, Paul; Scelo, Ghislaine

2013-01-01

Gene expression microarray and next generation sequencing efforts on conventional, clear cell renal cell carcinoma (ccRCC) have been mostly performed in North American and Western European populations, while the highest incidence rates are found in Central/Eastern Europe. We conducted whole-genome expression profiling on 101 pairs of ccRCC tumours and adjacent non-tumour renal tissue from Czech patients recruited within the “K2 Study”, using the Illumina HumanHT-12 v4 Expression BeadChips to explore the molecular variations underlying the biological and clinical heterogeneity of this cancer. Differential expression analysis identified 1650 significant probes (fold change ≥2 and false discovery rate <0.05) mapping to 630 up- and 720 down-regulated unique genes. We performed similar statistical analysis on the RNA sequencing data of 65 ccRCC cases from the Cancer Genome Atlas (TCGA) project and identified 60% (402) of the downregulated and 74% (469) of the upregulated genes found in the K2 series. The biological characterization of the significantly deregulated genes demonstrated involvement of downregulated genes in metabolic and catabolic processes, excretion, oxidation reduction, ion transport and response to chemical stimulus, while simultaneously upregulated genes were associated with immune and inflammatory responses, response to hypoxia, stress, wounding, vasculature development and cell activation. Furthermore, genome-wide DNA methylation analysis of 317 TCGA ccRCC/adjacent non-tumour renal tissue pairs indicated that deregulation of approximately 7% of genes could be explained by epigenetic changes. Finally, survival analysis conducted on 89 K2 and 464 TCGA cases identified 8 genes associated with differential prognostic outcomes. In conclusion, a large proportion of ccRCC molecular characteristics were common to the two populations and several may have clinical implications when validated further through large clinical cohorts. PMID:23526956

Bioinformatic tools for inferring functional information from plant microarray data: tools for the first steps.

PubMed

Page, Grier P; Coulibaly, Issa

2008-01-01

Microarrays are a very powerful tool for quantifying the amount of RNA in samples; however, their ability to query essentially every gene in a genome, which can number in the tens of thousands, presents analytical and interpretative problems. As a result, a variety of software and web-based tools have been developed to help with these issues. This article highlights and reviews some of the tools for the first steps in the analysis of a microarray study. We have tried for a balance between free and commercial systems. We have organized the tools by topics including image processing tools (Section 2), power analysis tools (Section 3), image analysis tools (Section 4), database tools (Section 5), databases of functional information (Section 6), annotation tools (Section 7), statistical and data mining tools (Section 8), and dissemination tools (Section 9).

Development of microbial genome-probing microarrays using digital multiple displacement amplification of uncultivated microbial single cells.

PubMed

Chang, Ho-Won; Sung, Youlboong; Kim, Kyoung-Ho; Nam, Young-Do; Roh, Seong Woon; Kim, Min-Soo; Jeon, Che Ok; Bae, Jin-Woo

2008-08-15

A crucial problem in the use of previously developed genome-probing microarrays (GPM) has been the inability to use uncultivated bacterial genomes to take advantage of the high sensitivity and specificity of GPM in microbial detection and monitoring. We show here a method, digital multiple displacement amplification (MDA), to amplify and analyze various genomes obtained from single uncultivated bacterial cells. We used 15 genomes from key microbes involved in dichloromethane (DCM)-dechlorinating enrichment as microarray probes to uncover the bacterial population dynamics of samples without PCR amplification. Genomic DNA amplified from single cells originating from uncultured bacteria with 80.3-99.4% similarity to 16S rRNA genes of cultivated bacteria. The digital MDA-GPM method successfully monitored the dynamics of DCM-dechlorinating communities from different phases of enrichment status. Without a priori knowledge of microbial diversity, the digital MDA-GPM method could be designed to monitor most microbial populations in a given environmental sample.

Curcumin modulates DNA methylation in colorectal cancer cells.

PubMed

Link, Alexander; Balaguer, Francesc; Shen, Yan; Lozano, Juan Jose; Leung, Hon-Chiu E; Boland, C Richard; Goel, Ajay

2013-01-01

Recent evidence suggests that several dietary polyphenols may exert their chemopreventive effect through epigenetic modifications. Curcumin is one of the most widely studied dietary chemopreventive agents for colon cancer prevention, however, its effects on epigenetic alterations, particularly DNA methylation, remain unclear. Using systematic genome-wide approaches, we aimed to elucidate the effect of curcumin on DNA methylation alterations in colorectal cancer cells. To evaluate the effect of curcumin on DNA methylation, three CRC cell lines, HCT116, HT29 and RKO, were treated with curcumin. 5-aza-2'-deoxycytidine (5-aza-CdR) and trichostatin A treated cells were used as positive and negative controls for DNA methylation changes, respectively. Methylation status of LINE-1 repeat elements, DNA promoter methylation microarrays and gene expression arrays were used to assess global methylation and gene expression changes. Validation was performed using independent microarrays, quantitative bisulfite pyrosequencing, and qPCR. As expected, genome-wide methylation microarrays revealed significant DNA hypomethylation in 5-aza-CdR-treated cells (mean β-values of 0.12), however, non-significant changes in mean β-values were observed in curcumin-treated cells. In comparison to mock-treated cells, curcumin-induced DNA methylation alterations occurred in a time-dependent manner. In contrast to the generalized, non-specific global hypomethylation observed with 5-aza-CdR, curcumin treatment resulted in methylation changes at selected, partially-methylated loci, instead of fully-methylated CpG sites. DNA methylation alterations were supported by corresponding changes in gene expression at both up- and down-regulated genes in various CRC cell lines. Our data provide previously unrecognized evidence for curcumin-mediated DNA methylation alterations as a potential mechanism of colon cancer chemoprevention. In contrast to non-specific global hypomethylation induced by 5-aza-CdR, curcumin-induced methylation changes occurred only in a subset of partially-methylated genes, which provides additional mechanistic insights into the potent chemopreventive effect of this dietary nutraceutical.

Curcumin Modulates DNA Methylation in Colorectal Cancer Cells

PubMed Central

Link, Alexander; Balaguer, Francesc; Shen, Yan; Lozano, Juan Jose; Leung, Hon-Chiu E.; Boland, C. Richard; Goel, Ajay

2013-01-01

Aim Recent evidence suggests that several dietary polyphenols may exert their chemopreventive effect through epigenetic modifications. Curcumin is one of the most widely studied dietary chemopreventive agents for colon cancer prevention, however, its effects on epigenetic alterations, particularly DNA methylation, remain unclear. Using systematic genome-wide approaches, we aimed to elucidate the effect of curcumin on DNA methylation alterations in colorectal cancer cells. Materials and Methods To evaluate the effect of curcumin on DNA methylation, three CRC cell lines, HCT116, HT29 and RKO, were treated with curcumin. 5-aza-2′-deoxycytidine (5-aza-CdR) and trichostatin A treated cells were used as positive and negative controls for DNA methylation changes, respectively. Methylation status of LINE-1 repeat elements, DNA promoter methylation microarrays and gene expression arrays were used to assess global methylation and gene expression changes. Validation was performed using independent microarrays, quantitative bisulfite pyrosequencing, and qPCR. Results As expected, genome-wide methylation microarrays revealed significant DNA hypomethylation in 5-aza-CdR-treated cells (mean β-values of 0.12), however, non-significant changes in mean β-values were observed in curcumin-treated cells. In comparison to mock-treated cells, curcumin-induced DNA methylation alterations occurred in a time-dependent manner. In contrast to the generalized, non-specific global hypomethylation observed with 5-aza-CdR, curcumin treatment resulted in methylation changes at selected, partially-methylated loci, instead of fully-methylated CpG sites. DNA methylation alterations were supported by corresponding changes in gene expression at both up- and down-regulated genes in various CRC cell lines. Conclusions Our data provide previously unrecognized evidence for curcumin-mediated DNA methylation alterations as a potential mechanism of colon cancer chemoprevention. In contrast to non-specific global hypomethylation induced by 5-aza-CdR, curcumin-induced methylation changes occurred only in a subset of partially-methylated genes, which provides additional mechanistic insights into the potent chemopreventive effect of this dietary nutraceutical. PMID:23460897

Genomics of the Effect of Spinal Cord Stimulation on an Animal Model of Neuropathic Pain.

PubMed

Vallejo, Ricardo; Tilley, Dana M; Cedeño, David L; Kelley, Courtney A; DeMaegd, Margaret; Benyamin, Ramsin

2016-08-01

Few studies have evaluated single-gene changes modulated by spinal cord stimulation (SCS), providing a narrow understanding of molecular changes. Genomics allows for a robust analysis of holistic gene changes in response to stimulation. Rats were randomized into six groups to determine the effect of continuous SCS in uninjured and spared-nerve injury (SNI) animals. After behavioral assessment, tissues from the dorsal quadrant of the spinal cord (SC) and dorsal root ganglion (DRG) underwent full-genome microarray analyses. Weighted Gene Correlation Network Analysis (WGCNA), and Gene Ontology (GO) analysis identified similar expression patterns, molecular functions and biological processes for significant genes. Microarray analyses reported 20,985 gene probes in SC and 19,104 in DRG. WGCNA sorted 7449 SC and 4275 DRG gene probes into 29 and 9 modules, respectively. WGCNA provided significant modules from paired comparisons of experimental groups. GO analyses reported significant biological processes influenced by injury, as well as the presence of an electric field. The genes Tlr2, Cxcl16, and Cd68 were used to further validate the microarray based on significant response to SCS in SNI animals. They were up-regulated in the SC while both Tlr2 and Cd68 were up-regulated in the DRG. The process described provides highly significant interconnected genes and pathways responsive to injury and/or electric field in the SC and DRG. Genes in the SC respond significantly to the SCS in both injured and uninjured animals, while those in the DRG significantly responded to injury, and SCS in injured animals. © 2016 International Neuromodulation Society.

A fisheye viewer for microarray-based gene expression data

PubMed Central

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

2006-01-01

Background Microarray has been widely used to measure the relative amounts of every mRNA transcript from the genome in a single scan. Biologists have been accustomed to reading their experimental data directly from tables. However, microarray data are quite large and are stored in a series of files in a machine-readable format, so direct reading of the full data set is not feasible. The challenge is to design a user interface that allows biologists to usefully view large tables of raw microarray-based gene expression data. This paper presents one such interface – an electronic table (E-table) that uses fisheye distortion technology. Results The Fisheye Viewer for microarray-based gene expression data has been successfully developed to view MIAME data stored in the MAGE-ML format. The viewer can be downloaded from the project web site . The fisheye viewer was implemented in Java so that it could run on multiple platforms. We implemented the E-table by adapting JTable, a default table implementation in the Java Swing user interface library. Fisheye views use variable magnification to balance magnification for easy viewing and compression for maximizing the amount of data on the screen. Conclusion This Fisheye Viewer is a lightweight but useful tool for biologists to quickly overview the raw microarray-based gene expression data in an E-table. PMID:17038193

CNV-WebStore: online CNV analysis, storage and interpretation.

PubMed

Vandeweyer, Geert; Reyniers, Edwin; Wuyts, Wim; Rooms, Liesbeth; Kooy, R Frank

2011-01-05

Microarray technology allows the analysis of genomic aberrations at an ever increasing resolution, making functional interpretation of these vast amounts of data the main bottleneck in routine implementation of high resolution array platforms, and emphasising the need for a centralised and easy to use CNV data management and interpretation system. We present CNV-WebStore, an online platform to streamline the processing and downstream interpretation of microarray data in a clinical context, tailored towards but not limited to the Illumina BeadArray platform. Provided analysis tools include CNV analsyis, parent of origin and uniparental disomy detection. Interpretation tools include data visualisation, gene prioritisation, automated PubMed searching, linking data to several genome browsers and annotation of CNVs based on several public databases. Finally a module is provided for uniform reporting of results. CNV-WebStore is able to present copy number data in an intuitive way to both lab technicians and clinicians, making it a useful tool in daily clinical practice.

VirtualPlant: A Software Platform to Support Systems Biology Research1[W][OA

PubMed Central

Katari, Manpreet S.; Nowicki, Steve D.; Aceituno, Felipe F.; Nero, Damion; Kelfer, Jonathan; Thompson, Lee Parnell; Cabello, Juan M.; Davidson, Rebecca S.; Goldberg, Arthur P.; Shasha, Dennis E.; Coruzzi, Gloria M.; Gutiérrez, Rodrigo A.

2010-01-01

Data generation is no longer the limiting factor in advancing biological research. In addition, data integration, analysis, and interpretation have become key bottlenecks and challenges that biologists conducting genomic research face daily. To enable biologists to derive testable hypotheses from the increasing amount of genomic data, we have developed the VirtualPlant software platform. VirtualPlant enables scientists to visualize, integrate, and analyze genomic data from a systems biology perspective. VirtualPlant integrates genome-wide data concerning the known and predicted relationships among genes, proteins, and molecules, as well as genome-scale experimental measurements. VirtualPlant also provides visualization techniques that render multivariate information in visual formats that facilitate the extraction of biological concepts. Importantly, VirtualPlant helps biologists who are not trained in computer science to mine lists of genes, microarray experiments, and gene networks to address questions in plant biology, such as: What are the molecular mechanisms by which internal or external perturbations affect processes controlling growth and development? We illustrate the use of VirtualPlant with three case studies, ranging from querying a gene of interest to the identification of gene networks and regulatory hubs that control seed development. Whereas the VirtualPlant software was developed to mine Arabidopsis (Arabidopsis thaliana) genomic data, its data structures, algorithms, and visualization tools are designed in a species-independent way. VirtualPlant is freely available at www.virtualplant.org. PMID:20007449

Integrated Genomic and Network-Based Analyses of Complex Diseases and Human Disease Network.

PubMed

Al-Harazi, Olfat; Al Insaif, Sadiq; Al-Ajlan, Monirah A; Kaya, Namik; Dzimiri, Nduna; Colak, Dilek

2016-06-20

A disease phenotype generally reflects various pathobiological processes that interact in a complex network. The highly interconnected nature of the human protein interaction network (interactome) indicates that, at the molecular level, it is difficult to consider diseases as being independent of one another. Recently, genome-wide molecular measurements, data mining and bioinformatics approaches have provided the means to explore human diseases from a molecular basis. The exploration of diseases and a system of disease relationships based on the integration of genome-wide molecular data with the human interactome could offer a powerful perspective for understanding the molecular architecture of diseases. Recently, subnetwork markers have proven to be more robust and reliable than individual biomarker genes selected based on gene expression profiles alone, and achieve higher accuracy in disease classification. We have applied one of these methodologies to idiopathic dilated cardiomyopathy (IDCM) data that we have generated using a microarray and identified significant subnetworks associated with the disease. In this paper, we review the recent endeavours in this direction, and summarize the existing methodologies and computational tools for network-based analysis of complex diseases and molecular relationships among apparently different disorders and human disease network. We also discuss the future research trends and topics of this promising field. Copyright © 2015 Institute of Genetics and Developmental Biology, Chinese Academy of Sciences, and Genetics Society of China. Published by Elsevier Ltd. All rights reserved.

Rare genomic rearrangement in a boy with Williams-Beuren syndrome associated to XYY syndrome and intriguing behavior.

PubMed

Dutra, Roberta L; Piazzon, Flavia B; Zanardo, Évelin A; Costa, Thais Virginia Moura Machado; Montenegro, Marília M; Novo-Filho, Gil M; Dias, Alexandre T; Nascimento, Amom M; Kim, Chong Ae; Kulikowski, Leslie D

2015-12-01

Williams-Beuren syndrome (WBS) is caused by a hemizygous contiguous gene microdeletion of 1.55-1.84 Mb at 7q11.23 region. Approximately, 28 genes have been shown to contribute to classical phenotype of SWB with presence of dysmorphic facial features, supravalvular aortic stenosis (SVAS), intellectual disability, and overfriendliness. With the use of Microarray-based comparative genomic hybridization and other molecular cytogenetic techniques, is possible define with more accuracy partial or atypical deletion and refine the genotype-phenotype correlation. Here, we report on a rare genomic structural rearrangement in a boy with atypical deletion in 7q11.23 and XYY syndrome with characteristic clinical signs, but not sufficient for the diagnosis of WBS. Cytogenetic analysis of G-banding showed a karyotype 47,XYY. Analysis of DNA with the technique of MLPA (Multiplex Ligation-dependent Probe Amplification) using kits a combination of kits (P064, P036, P070, and P029) identified an atypical deletion on 7q11.23. In addition, high resolution SNP Oligonucleotide Microarray Analysis (SNP-array) confirmed the alterations found by MLPA and revealed others pathogenic CNVs, in the chromosomes 7 and X. The present report demonstrates an association not yet described in literature, between Williams-Beuren syndrome and 47,XYY. The identification of atypical deletion in 7q11.23 concomitant to additional pathogenic CNVs in others genomic regions allows a better comprehension of clinical consequences of atypical genomic rearrangements. © 2015 Wiley Periodicals, Inc.

Eotaxin-3 and a uniquely conserved gene-expression profile in eosinophilic esophagitis

PubMed Central

Blanchard, Carine; Wang, Ning; Stringer, Keith F.; Mishra, Anil; Fulkerson, Patricia C.; Abonia, J. Pablo; Jameson, Sean C.; Kirby, Cassie; Konikoff, Michael R.; Collins, Margaret H.; Cohen, Mitchell B.; Akers, Rachel; Hogan, Simon P.; Assa’ad, Amal H.; Putnam, Philip E.; Aronow, Bruce J.; Rothenberg, Marc E.

2006-01-01

Eosinophilic esophagitis (EE) is an emerging disorder with a poorly understood pathogenesis. In order to define disease mechanisms, we took an empirical approach analyzing esophageal tissue by a genome-wide microarray expression analysis. EE patients had a striking transcript signature involving 1% of the human genome that was remarkably conserved across sex, age, and allergic status and was distinct from that associated with non-EE chronic esophagitis. Notably, the gene encoding the eosinophil-specific chemoattractant eotaxin-3 (also known as CCL26) was the most highly induced gene in EE patients compared with its expression level in healthy individuals. Esophageal eotaxin-3 mRNA and protein levels strongly correlated with tissue eosinophilia and mastocytosis. Furthermore, a single-nucleotide polymorphism in the human eotaxin-3 gene was associated with disease susceptibility. Finally, mice deficient in the eotaxin receptor (also known as CCR3) were protected from experimental EE. These results implicate eotaxin-3 as a critical effector molecule for EE and provide insight into disease pathogenesis. PMID:16453027

A genome-wide perspective on the evolutionary history of enigmatic wolf-like canids

PubMed Central

vonHoldt, Bridgett M.; Pollinger, John P.; Earl, Dent A.; Knowles, James C.; Boyko, Adam R.; Parker, Heidi; Geffen, Eli; Pilot, Malgorzata; Jedrzejewski, Wlodzimierz; Jedrzejewska, Bogumila; Sidorovich, Vadim; Greco, Claudia; Randi, Ettore; Musiani, Marco; Kays, Roland; Bustamante, Carlos D.; Ostrander, Elaine A.; Novembre, John; Wayne, Robert K.

2011-01-01

High-throughput genotyping technologies developed for model species can potentially increase the resolution of demographic history and ancestry in wild relatives. We use a SNP genotyping microarray developed for the domestic dog to assay variation in over 48K loci in wolf-like species worldwide. Despite the high mobility of these large carnivores, we find distinct hierarchical population units within gray wolves and coyotes that correspond with geographic and ecologic differences among populations. Further, we test controversial theories about the ancestry of the Great Lakes wolf and red wolf using an analysis of haplotype blocks across all 38 canid autosomes. We find that these enigmatic canids are highly admixed varieties derived from gray wolves and coyotes, respectively. This divergent genomic history suggests that they do not have a shared recent ancestry as proposed by previous researchers. Interspecific hybridization, as well as the process of evolutionary divergence, may be responsible for the observed phenotypic distinction of both forms. Such admixture complicates decisions regarding endangered species restoration and protection. PMID:21566151

Automated detection system of single nucleotide polymorphisms using two kinds of functional magnetic nanoparticles

NASA Astrophysics Data System (ADS)

Liu, Hongna; Li, Song; Wang, Zhifei; Li, Zhiyang; Deng, Yan; Wang, Hua; Shi, Zhiyang; He, Nongyue

2008-11-01

Single nucleotide polymorphisms (SNPs) comprise the most abundant source of genetic variation in the human genome wide codominant SNPs identification. Therefore, large-scale codominant SNPs identification, especially for those associated with complex diseases, has induced the need for completely high-throughput and automated SNP genotyping method. Herein, we present an automated detection system of SNPs based on two kinds of functional magnetic nanoparticles (MNPs) and dual-color hybridization. The amido-modified MNPs (NH 2-MNPs) modified with APTES were used for DNA extraction from whole blood directly by electrostatic reaction, and followed by PCR, was successfully performed. Furthermore, biotinylated PCR products were captured on the streptavidin-coated MNPs (SA-MNPs) and interrogated by hybridization with a pair of dual-color probes to determine SNP, then the genotype of each sample can be simultaneously identified by scanning the microarray printed with the denatured fluorescent probes. This system provided a rapid, sensitive and highly versatile automated procedure that will greatly facilitate the analysis of different known SNPs in human genome.

Differentially regulated splice variants and systems biology analysis of Kaposi's sarcoma-associated herpesvirus-infected lymphatic endothelial cells.

PubMed

Chang, Ting-Yu; Wu, Yu-Hsuan; Cheng, Cheng-Chung; Wang, Hsei-Wei

2011-09-01

Alternative RNA splicing greatly increases proteome diversity, and the possibility of studying genome-wide alternative splicing (AS) events becomes available with the advent of high-throughput genomics tools devoted to this issue. Kaposi's sarcoma associated herpesvirus (KSHV) is the etiological agent of KS, a tumor of lymphatic endothelial cell (LEC) lineage, but little is known about the AS variations induced by KSHV. We analyzed KSHV-controlled AS using high-density microarrays capable of detecting all exons in the human genome. Splicing variants and altered exon-intron usage in infected LEC were found, and these correlated with protein domain modification. The different 3'-UTR used in new transcripts also help isoforms to escape microRNA-mediated surveillance. Exome-level analysis further revealed information that cannot be disclosed using classical gene-level profiling: a significant exon usage difference existed between LEC and CD34(+) precursor cells, and KSHV infection resulted in LEC-to-precursor, dedifferentiation-like exon level reprogramming. Our results demonstrate the application of exon arrays in systems biology research, and suggest the regulatory effects of AS in endothelial cells are far more complex than previously observed. This extra layer of molecular diversity helps to account for various aspects of endothelial biology, KSHV life cycle and disease pathogenesis that until now have been unexplored.

Copy number gain at 8q12.1-q22.1 is associated with a malignant tumor phenotype in salivary gland myoepitheliomas.

PubMed

Vékony, Hedy; Röser, Kerstin; Löning, Thomas; Ylstra, Bauke; Meijer, Gerrit A; van Wieringen, Wessel N; van de Wiel, Mark A; Carvalho, Beatriz; Kok, Klaas; Leemans, C René; van der Waal, Isaäc; Bloemena, Elisabeth

2009-02-01

Salivary gland myoepithelial tumors are relatively uncommon tumors with an unpredictable clinical course. More knowledge about their genetic profiles is necessary to identify novel predictors of disease. In this study, we subjected 27 primary tumors (15 myoepitheliomas and 12 myoepithelial carcinomas) to genome-wide microarray-based comparative genomic hybridization (array CGH). We set out to delineate known chromosomal aberrations in more detail and to unravel chromosomal differences between benign myoepitheliomas and myoepithelial carcinomas. Patterns of DNA copy number aberrations were analyzed by unsupervised hierarchical cluster analysis. Both benign and malignant tumors revealed a limited amount of chromosomal alterations (median of 5 and 7.5, respectively). In both tumor groups, high frequency gains (> or =20%) were found mainly at loci of growth factors and growth factor receptors (e.g., PDGF, FGF(R)s, and EGFR). In myoepitheliomas, high frequency losses (> or =20%) were detected at regions of proto-cadherins. Cluster analysis of the array CGH data identified three clusters. Differential copy numbers on chromosome arm 8q and chromosome 17 set the clusters apart. Cluster 1 contained a mixture of the two phenotypes (n = 10), cluster 2 included mostly benign tumors (n = 10), and cluster 3 only contained carcinomas (n = 7). Supervised analysis between malignant and benign tumors revealed a 36 Mbp-region at 8q being more frequently gained in malignant tumors (P = 0.007, FDR = 0.05). This is the first study investigating genomic differences between benign and malignant myoepithelial tumors of the salivary glands at a genomic level. Both unsupervised and supervised analysis of the genomic profiles revealed chromosome arm 8q to be involved in the malignant phenotype of salivary gland myoepitheliomas.

Tracing phylogenomic events leading to diversity of Haemophilus influenzae and the emergence of Brazilian Purpuric Fever (BPF)-associated clones.

PubMed

Papazisi, Leka; Ratnayake, Shashikala; Remortel, Brian G; Bock, Geoffrey R; Liang, Wei; Saeed, Alexander I; Liu, Jia; Fleischmann, Robert D; Kilian, Mogens; Peterson, Scott N

2010-11-01

Here we report the use of a multi-genome DNA microarray to elucidate the genomic events associated with the emergence of the clonal variants of Haemophilus influenzae biogroup aegyptius causing Brazilian Purpuric Fever (BPF), an important pediatric disease with a high mortality rate. We performed directed genome sequencing of strain HK1212 unique loci to construct a species DNA microarray. Comparative genome hybridization using this microarray enabled us to determine and compare gene complements, and infer reliable phylogenomic relationships among members of the species. The higher genomic variability observed in the genomes of BPF-related strains (clones) and their close relatives may be characterized by significant gene flux related to a subset of functional role categories. We found that the acquisition of a large number of virulence determinants featuring numerous cell membrane proteins coupled to the loss of genes involved in transport, central biosynthetic pathways and in particular, energy production pathways to be characteristics of the BPF genomic variants. Copyright © 2010 Elsevier Inc. All rights reserved.

Filling gaps in PPAR-alpha signaling through comparative nutrigenomics analysis

PubMed Central

2009-01-01

Background The application of high-throughput genomic tools in nutrition research is a widespread practice. However, it is becoming increasingly clear that the outcome of individual expression studies is insufficient for the comprehensive understanding of such a complex field. Currently, the availability of the large amounts of expression data in public repositories has opened up new challenges on microarray data analyses. We have focused on PPARα, a ligand-activated transcription factor functioning as fatty acid sensor controlling the gene expression regulation of a large set of genes in various metabolic organs such as liver, small intestine or heart. The function of PPARα is strictly connected to the function of its target genes and, although many of these have already been identified, major elements of its physiological function remain to be uncovered. To further investigate the function of PPARα, we have applied a cross-species meta-analysis approach to integrate sixteen microarray datasets studying high fat diet and PPARα signal perturbations in different organisms. Results We identified 164 genes (MDEGs) that were differentially expressed in a constant way in response to a high fat diet or to perturbations in PPARs signalling. In particular, we found five genes in yeast which were highly conserved and homologous of PPARα targets in mammals, potential candidates to be used as models for the equivalent mammalian genes. Moreover, a screening of the MDEGs for all known transcription factor binding sites and the comparison with a human genome-wide screening of Peroxisome Proliferating Response Elements (PPRE), enabled us to identify, 20 new potential candidate genes that show, both binding site, both change in expression in the condition studied. Lastly, we found a non random localization of the differentially expressed genes in the genome. Conclusion The results presented are potentially of great interest to resume the currently available expression data, exploiting the power of in silico analysis filtered by evolutionary conservation. The analysis enabled us to indicate potential gene candidates that could fill in the gaps with regards to the signalling of PPARα and, moreover, the non-random localization of the differentially expressed genes in the genome, suggest that epigenetic mechanisms are of importance in the regulation of the transcription operated by PPARα. PMID:20003344

Quantitative real-time polymerase chain reaction for the verification of genomic imbalances detected by microarray-based comparative genomic hybridization.

PubMed

Yu, Shihui; Kielt, Matthew; Stegner, Andrew L; Kibiryeva, Nataliya; Bittel, Douglas C; Cooley, Linda D

2009-12-01

The American College of Medical Genetics guidelines for microarray analysis for constitutional cytogenetic abnormalities require abnormal or ambiguous results from microarray-based comparative genomic hybridization (aCGH) analysis be confirmed by an alternative method. We employed quantitative real-time polymerase chain reaction (qPCR) technology using SYBR Green I reagents for confirmation of 93 abnormal aCGH results (50 deletions and 43 duplications) and 54 parental samples. A novel qPCR protocol using DNA sequences coding for X-linked lethal diseases in males for designing reference primers was established. Of the 81 sets of test primers used for confirmation of 93 abnormal copy number variants (CNVs) in 80 patients, 71 sets worked after the initial primer design (88%), 9 sets were redesigned once, and 1 set twice because of poor amplification. Fifty-four parental samples were tested using 33 sets of test primers to follow up 34 CNVs in 30 patients. Nineteen CNVs were confirmed as inherited, 13 were negative in both parents, and 2 were inconclusive due to a negative result in a single parent. The qPCR assessment clarified aCGH results in two cases and corrected a fluorescence in situ hybridization result in one case. Our data illustrate that qPCR methodology using SYBR Green I reagents is accurate, highly sensitive, specific, rapid, and cost-effective for verification of chromosomal imbalances detected by aCGH in the clinical setting.

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

PubMed

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

2018-04-20

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

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

PubMed Central

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

2017-01-01

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

Network-Based Integration of GWAS and Gene Expression Identifies a HOX-Centric Network Associated with Serous Ovarian Cancer Risk.

PubMed

Kar, Siddhartha P; Tyrer, Jonathan P; Li, Qiyuan; Lawrenson, Kate; Aben, Katja K H; Anton-Culver, Hoda; Antonenkova, Natalia; Chenevix-Trench, Georgia; Baker, Helen; Bandera, Elisa V; Bean, Yukie T; Beckmann, Matthias W; Berchuck, Andrew; Bisogna, Maria; Bjørge, Line; Bogdanova, Natalia; Brinton, Louise; Brooks-Wilson, Angela; Butzow, Ralf; Campbell, Ian; Carty, Karen; Chang-Claude, Jenny; Chen, Yian Ann; Chen, Zhihua; Cook, Linda S; Cramer, Daniel; Cunningham, Julie M; Cybulski, Cezary; Dansonka-Mieszkowska, Agnieszka; Dennis, Joe; Dicks, Ed; Doherty, Jennifer A; Dörk, Thilo; du Bois, Andreas; Dürst, Matthias; Eccles, Diana; Easton, Douglas F; Edwards, Robert P; Ekici, Arif B; Fasching, Peter A; Fridley, Brooke L; Gao, Yu-Tang; Gentry-Maharaj, Aleksandra; Giles, Graham G; Glasspool, Rosalind; Goode, Ellen L; Goodman, Marc T; Grownwald, Jacek; Harrington, Patricia; Harter, Philipp; Hein, Alexander; Heitz, Florian; Hildebrandt, Michelle A T; Hillemanns, Peter; Hogdall, Estrid; Hogdall, Claus K; Hosono, Satoyo; Iversen, Edwin S; Jakubowska, Anna; Paul, James; Jensen, Allan; Ji, Bu-Tian; Karlan, Beth Y; Kjaer, Susanne K; Kelemen, Linda E; Kellar, Melissa; Kelley, Joseph; Kiemeney, Lambertus A; Krakstad, Camilla; Kupryjanczyk, Jolanta; Lambrechts, Diether; Lambrechts, Sandrina; Le, Nhu D; Lee, Alice W; Lele, Shashi; Leminen, Arto; Lester, Jenny; Levine, Douglas A; Liang, Dong; Lissowska, Jolanta; Lu, Karen; Lubinski, Jan; Lundvall, Lene; Massuger, Leon; Matsuo, Keitaro; McGuire, Valerie; McLaughlin, John R; McNeish, Iain A; Menon, Usha; Modugno, Francesmary; Moysich, Kirsten B; Narod, Steven A; Nedergaard, Lotte; Ness, Roberta B; Nevanlinna, Heli; Odunsi, Kunle; Olson, Sara H; Orlow, Irene; Orsulic, Sandra; Weber, Rachel Palmieri; Pearce, Celeste Leigh; Pejovic, Tanja; Pelttari, Liisa M; Permuth-Wey, Jennifer; Phelan, Catherine M; Pike, Malcolm C; Poole, Elizabeth M; Ramus, Susan J; Risch, Harvey A; Rosen, Barry; Rossing, Mary Anne; Rothstein, Joseph H; Rudolph, Anja; Runnebaum, Ingo B; Rzepecka, Iwona K; Salvesen, Helga B; Schildkraut, Joellen M; Schwaab, Ira; Shu, Xiao-Ou; Shvetsov, Yurii B; Siddiqui, Nadeem; Sieh, Weiva; Song, Honglin; Southey, Melissa C; Sucheston-Campbell, Lara E; Tangen, Ingvild L; Teo, Soo-Hwang; Terry, Kathryn L; Thompson, Pamela J; Timorek, Agnieszka; Tsai, Ya-Yu; Tworoger, Shelley S; van Altena, Anne M; Van Nieuwenhuysen, Els; Vergote, Ignace; Vierkant, Robert A; Wang-Gohrke, Shan; Walsh, Christine; Wentzensen, Nicolas; Whittemore, Alice S; Wicklund, Kristine G; Wilkens, Lynne R; Woo, Yin-Ling; Wu, Xifeng; Wu, Anna; Yang, Hannah; Zheng, Wei; Ziogas, Argyrios; Sellers, Thomas A; Monteiro, Alvaro N A; Freedman, Matthew L; Gayther, Simon A; Pharoah, Paul D P

2015-10-01

Genome-wide association studies (GWAS) have so far reported 12 loci associated with serous epithelial ovarian cancer (EOC) risk. We hypothesized that some of these loci function through nearby transcription factor (TF) genes and that putative target genes of these TFs as identified by coexpression may also be enriched for additional EOC risk associations. We selected TF genes within 1 Mb of the top signal at the 12 genome-wide significant risk loci. Mutual information, a form of correlation, was used to build networks of genes strongly coexpressed with each selected TF gene in the unified microarray dataset of 489 serous EOC tumors from The Cancer Genome Atlas. Genes represented in this dataset were subsequently ranked using a gene-level test based on results for germline SNPs from a serous EOC GWAS meta-analysis (2,196 cases/4,396 controls). Gene set enrichment analysis identified six networks centered on TF genes (HOXB2, HOXB5, HOXB6, HOXB7 at 17q21.32 and HOXD1, HOXD3 at 2q31) that were significantly enriched for genes from the risk-associated end of the ranked list (P < 0.05 and FDR < 0.05). These results were replicated (P < 0.05) using an independent association study (7,035 cases/21,693 controls). Genes underlying enrichment in the six networks were pooled into a combined network. We identified a HOX-centric network associated with serous EOC risk containing several genes with known or emerging roles in serous EOC development. Network analysis integrating large, context-specific datasets has the potential to offer mechanistic insights into cancer susceptibility and prioritize genes for experimental characterization. ©2015 American Association for Cancer Research.

Network-based integration of GWAS and gene expression identifies a HOX-centric network associated with serous ovarian cancer risk

PubMed Central

Kar, Siddhartha P.; Tyrer, Jonathan P.; Li, Qiyuan; Lawrenson, Kate; Aben, Katja K.H.; Anton-Culver, Hoda; Antonenkova, Natalia; Chenevix-Trench, Georgia; Baker, Helen; Bandera, Elisa V.; Bean, Yukie T.; Beckmann, Matthias W.; Berchuck, Andrew; Bisogna, Maria; Bjørge, Line; Bogdanova, Natalia; Brinton, Louise; Brooks-Wilson, Angela; Butzow, Ralf; Campbell, Ian; Carty, Karen; Chang-Claude, Jenny; Chen, Yian Ann; Chen, Zhihua; Cook, Linda S.; Cramer, Daniel; Cunningham, Julie M.; Cybulski, Cezary; Dansonka-Mieszkowska, Agnieszka; Dennis, Joe; Dicks, Ed; Doherty, Jennifer A.; Dörk, Thilo; du Bois, Andreas; Dürst, Matthias; Eccles, Diana; Easton, Douglas F.; Edwards, Robert P.; Ekici, Arif B.; Fasching, Peter A.; Fridley, Brooke L.; Gao, Yu-Tang; Gentry-Maharaj, Aleksandra; Giles, Graham G.; Glasspool, Rosalind; Goode, Ellen L.; Goodman, Marc T.; Grownwald, Jacek; Harrington, Patricia; Harter, Philipp; Hein, Alexander; Heitz, Florian; Hildebrandt, Michelle A.T.; Hillemanns, Peter; Hogdall, Estrid; Hogdall, Claus K.; Hosono, Satoyo; Iversen, Edwin S.; Jakubowska, Anna; Paul, James; Jensen, Allan; Ji, Bu-Tian; Karlan, Beth Y; Kjaer, Susanne K.; Kelemen, Linda E.; Kellar, Melissa; Kelley, Joseph; Kiemeney, Lambertus A.; Krakstad, Camilla; Kupryjanczyk, Jolanta; Lambrechts, Diether; Lambrechts, Sandrina; Le, Nhu D.; Lee, Alice W.; Lele, Shashi; Leminen, Arto; Lester, Jenny; Levine, Douglas A.; Liang, Dong; Lissowska, Jolanta; Lu, Karen; Lubinski, Jan; Lundvall, Lene; Massuger, Leon; Matsuo, Keitaro; McGuire, Valerie; McLaughlin, John R.; McNeish, Iain A.; Menon, Usha; Modugno, Francesmary; Moysich, Kirsten B.; Narod, Steven A.; Nedergaard, Lotte; Ness, Roberta B.; Nevanlinna, Heli; Odunsi, Kunle; Olson, Sara H.; Orlow, Irene; Orsulic, Sandra; Weber, Rachel Palmieri; Pearce, Celeste Leigh; Pejovic, Tanja; Pelttari, Liisa M.; Permuth-Wey, Jennifer; Phelan, Catherine M.; Pike, Malcolm C.; Poole, Elizabeth M.; Ramus, Susan J.; Risch, Harvey A.; Rosen, Barry; Rossing, Mary Anne; Rothstein, Joseph H.; Rudolph, Anja; Runnebaum, Ingo B.; Rzepecka, Iwona K.; Salvesen, Helga B.; Schildkraut, Joellen M.; Schwaab, Ira; Shu, Xiao-Ou; Shvetsov, Yurii B; Siddiqui, Nadeem; Sieh, Weiva; Song, Honglin; Southey, Melissa C.; Sucheston-Campbell, Lara E.; Tangen, Ingvild L.; Teo, Soo-Hwang; Terry, Kathryn L.; Thompson, Pamela J; Timorek, Agnieszka; Tsai, Ya-Yu; Tworoger, Shelley S.; van Altena, Anne M.; Van Nieuwenhuysen, Els; Vergote, Ignace; Vierkant, Robert A.; Wang-Gohrke, Shan; Walsh, Christine; Wentzensen, Nicolas; Whittemore, Alice S.; Wicklund, Kristine G.; Wilkens, Lynne R.; Woo, Yin-Ling; Wu, Xifeng; Wu, Anna; Yang, Hannah; Zheng, Wei; Ziogas, Argyrios; Sellers, Thomas A.; Monteiro, Alvaro N. A.; Freedman, Matthew L.; Gayther, Simon A.; Pharoah, Paul D. P.

2015-01-01

Background Genome-wide association studies (GWAS) have so far reported 12 loci associated with serous epithelial ovarian cancer (EOC) risk. We hypothesized that some of these loci function through nearby transcription factor (TF) genes and that putative target genes of these TFs as identified by co-expression may also be enriched for additional EOC risk associations. Methods We selected TF genes within 1 Mb of the top signal at the 12 genome-wide significant risk loci. Mutual information, a form of correlation, was used to build networks of genes strongly co-expressed with each selected TF gene in the unified microarray data set of 489 serous EOC tumors from The Cancer Genome Atlas. Genes represented in this data set were subsequently ranked using a gene-level test based on results for germline SNPs from a serous EOC GWAS meta-analysis (2,196 cases/4,396 controls). Results Gene set enrichment analysis identified six networks centered on TF genes (HOXB2, HOXB5, HOXB6, HOXB7 at 17q21.32 and HOXD1, HOXD3 at 2q31) that were significantly enriched for genes from the risk-associated end of the ranked list (P<0.05 and FDR<0.05). These results were replicated (P<0.05) using an independent association study (7,035 cases/21,693 controls). Genes underlying enrichment in the six networks were pooled into a combined network. Conclusion We identified a HOX-centric network associated with serous EOC risk containing several genes with known or emerging roles in serous EOC development. Impact Network analysis integrating large, context-specific data sets has the potential to offer mechanistic insights into cancer susceptibility and prioritize genes for experimental characterization. PMID:26209509

Comparative genomic characterization of citrus-associated Xylella fastidiosa strains.

PubMed

da Silva, Vivian S; Shida, Cláudio S; Rodrigues, Fabiana B; Ribeiro, Diógenes C D; de Souza, Alessandra A; Coletta-Filho, Helvécio D; Machado, Marcos A; Nunes, Luiz R; de Oliveira, Regina Costa

2007-12-21

The xylem-inhabiting bacterium Xylella fastidiosa (Xf) is the causal agent of Pierce's disease (PD) in vineyards and citrus variegated chlorosis (CVC) in orange trees. Both of these economically-devastating diseases are caused by distinct strains of this complex group of microorganisms, which has motivated researchers to conduct extensive genomic sequencing projects with Xf strains. This sequence information, along with other molecular tools, have been used to estimate the evolutionary history of the group and provide clues to understand the capacity of Xf to infect different hosts, causing a variety of symptoms. Nonetheless, although significant amounts of information have been generated from Xf strains, a large proportion of these efforts has concentrated on the study of North American strains, limiting our understanding about the genomic composition of South American strains - which is particularly important for CVC-associated strains. This paper describes the first genome-wide comparison among South American Xf strains, involving 6 distinct citrus-associated bacteria. Comparative analyses performed through a microarray-based approach allowed identification and characterization of large mobile genetic elements that seem to be exclusive to South American strains. Moreover, a large-scale sequencing effort, based on Suppressive Subtraction Hybridization (SSH), identified 290 new ORFs, distributed in 135 Groups of Orthologous Elements, throughout the genomes of these bacteria. Results from microarray-based comparisons provide further evidence concerning activity of horizontally transferred elements, reinforcing their importance as major mediators in the evolution of Xf. Moreover, the microarray-based genomic profiles showed similarity between Xf strains 9a5c and Fb7, which is unexpected, given the geographical and chronological differences associated with the isolation of these microorganisms. The newly identified ORFs, obtained by SSH, represent an approximately 10% increase in our current knowledge of the South American Xf gene pool and include new putative virulence factors, as well as novel potential markers for strain identification. Surprisingly, this list of novel elements include sequences previously believed to be unique to North American strains, pointing to the necessity of revising the list of specific markers that may be used for identification of distinct Xf strains.

Modulation of Differentiation Processes in Murine Embryonic Stem Cells Exposed to Parabolic Flight-Induced Acute Hypergravity and Microgravity.

PubMed

Acharya, Aviseka; Brungs, Sonja; Henry, Margit; Rotshteyn, Tamara; Singh Yaduvanshi, Nirmala; Wegener, Lucia; Jentzsch, Simon; Hescheler, Jürgen; Hemmersbach, Ruth; Boeuf, Helene; Sachinidis, Agapios

2018-06-15

Embryonic developmental studies under microgravity conditions in space are very limited. To study the effects of short-term altered gravity on embryonic development processes, we exposed mouse embryonic stem cells (mESCs) to phases of hypergravity and microgravity and studied the differentiation potential of the cells using wide-genome microarray analysis. During the 64th European Space Agency's parabolic flight campaign, mESCs were exposed to 31 parabolas. Each parabola comprised phases lasting 22 s of hypergravity, microgravity, and a repeat of hypergravity. On different parabolas, RNA was isolated for microarray analysis. After exposure to 31 parabolas, mESCs (P31 mESCs) were further differentiated under normal gravity (1 g) conditions for 12 days, producing P31 12-day embryoid bodies (EBs). After analysis of the microarrays, the differentially expressed genes were analyzed using different bioinformatic tools to identify developmental and nondevelopmental biological processes affected by conditions on the parabolic flight experiment. Our results demonstrated that several genes belonging to GOs associated with cell cycle and proliferation were downregulated in undifferentiated mESCs exposed to gravity changes. However, several genes belonging to developmental processes, such as vasculature development, kidney development, skin development, and to the TGF-β signaling pathway, were upregulated. Interestingly, similar enriched and suppressed GOs were obtained in P31 12-day EBs compared with ground control 12-day EBs. Our results show that undifferentiated mESCs exposed to alternate hypergravity and microgravity phases expressed several genes associated with developmental/differentiation and cell cycle processes, suggesting a transition from the undifferentiated pluripotent to a more differentiated stage of mESCs.

Knockdown of the schizophrenia susceptibility gene TCF4 alters gene expression and proliferation of progenitor cells from the developing human neocortex.

PubMed

Hill, Matthew J; Killick, Richard; Navarrete, Katherinne; Maruszak, Aleksandra; McLaughlin, Gemma M; Williams, Brenda P; Bray, Nicholas J

2017-05-01

Common variants in the TCF4 gene are among the most robustly supported genetic risk factors for schizophrenia. Rare TCF4 deletions and loss-of-function point mutations cause Pitt-Hopkins syndrome, a developmental disorder associated with severe intellectual disability. To explore molecular and cellular mechanisms by which TCF4 perturbation could interfere with human cortical development, we experimentally reduced the endogenous expression of TCF4 in a neural progenitor cell line derived from the developing human cerebral cortex using RNA interference. Effects on genome-wide gene expression were assessed by microarray, followed by Gene Ontology and pathway analysis of differentially expressed genes. We tested for genetic association between the set of differentially expressed genes and schizophrenia using genome-wide association study data from the Psychiatric Genomics Consortium and competitive gene set analysis (MAGMA). Effects on cell proliferation were assessed using high content imaging. Genes that were differentially expressed following TCF4 knockdown were highly enriched for involvement in the cell cycle. There was a nonsignificant trend for genetic association between the differentially expressed gene set and schizophrenia. Consistent with the gene expression data, TCF4 knockdown was associated with reduced proliferation of cortical progenitor cells in vitro. A detailed mechanistic explanation of how TCF4 knockdown alters human neural progenitor cell proliferation is not provided by this study. Our data indicate effects of TCF4 perturbation on human cortical progenitor cell proliferation, a process that could contribute to cognitive deficits in individuals with Pitt-Hopkins syndrome and risk for schizophrenia.

Genomic analysis of Fusarium verticillioides.

PubMed

Brown, D W; Butchko, R A E; Proctor, R H

2008-09-01

Fusarium verticillioides (teleomorph Gibberella moniliformis) can be either an endophyte of maize, causing no visible disease, or a pathogen-causing disease of ears, stalks, roots and seedlings. At any stage, this fungus can synthesize fumonisins, a family of mycotoxins structurally similar to the sphingolipid sphinganine. Ingestion of fumonisin-contaminated maize has been associated with a number of animal diseases, including cancer in rodents, and exposure has been correlated with human oesophageal cancer in some regions of the world, and some evidence suggests that fumonisins are a risk factor for neural tube defects. A primary goal of the authors' laboratory is to eliminate fumonisin contamination of maize and maize products. Understanding how and why these toxins are made and the F. verticillioides-maize disease process will allow one to develop novel strategies to limit tissue destruction (rot) and fumonisin production. To meet this goal, genomic sequence data, expressed sequence tags (ESTs) and microarrays are being used to identify F. verticillioides genes involved in the biosynthesis of toxins and plant pathogenesis. This paper describes the current status of F. verticillioides genomic resources and three approaches being used to mine microarray data from a wild-type strain cultured in liquid fumonisin production medium for 12, 24, 48, 72, 96 and 120h. Taken together, these approaches demonstrate the power of microarray technology to provide information on different biological processes.

Genome Wide Meta-analysis Highlights the Role of Genetic Variation in RARRES2 in the Regulation of Circulating Serum Chemerin

PubMed Central

Breitfeld, Jana; Marzi, Carola; Grallert, Harald; Gross, Arnd; Ladenvall, Claes; Schleinitz, Dorit; Krause, Kerstin; Kirsten, Holger; Laurila, Esa; Kriebel, Jennifer; Thorand, Barbara; Rathmann, Wolfgang; Groop, Leif; Prokopenko, Inga; Isomaa, Bo; Beutner, Frank; Kratzsch, Jürgen; Thiery, Joachim; Fasshauer, Mathias; Klöting, Nora; Gieger, Christian; Blüher, Matthias; Stumvoll, Michael; Kovacs, Peter

2014-01-01

Chemerin is an adipokine proposed to link obesity and chronic inflammation of adipose tissue. Genetic factors determining chemerin release from adipose tissue are yet unknown. We conducted a meta-analysis of genome-wide association studies (GWAS) for serum chemerin in three independent cohorts from Europe: Sorbs and KORA from Germany and PPP-Botnia from Finland (total N = 2,791). In addition, we measured mRNA expression of genes within the associated loci in peripheral mononuclear cells by micro-arrays, and within adipose tissue by quantitative RT-PCR and performed mRNA expression quantitative trait and expression-chemerin association studies to functionally substantiate our loci. Heritability estimate of circulating chemerin levels was 16.2% in the Sorbs cohort. Thirty single nucleotide polymorphisms (SNPs) at chromosome 7 within the retinoic acid receptor responder 2 (RARRES2)/Leucine Rich Repeat Containing (LRRC61) locus reached genome-wide significance (p<5.0×10−8) in the meta-analysis (the strongest evidence for association at rs7806429 with p = 7.8×10−14, beta = −0.067, explained variance 2.0%). All other SNPs within the cluster were in linkage disequilibrium with rs7806429 (minimum r2 = 0.43 in the Sorbs cohort). The results of the subgroup analyses of males and females were consistent with the results found in the total cohort. No significant SNP-sex interaction was observed. rs7806429 was associated with mRNA expression of RARRES2 in visceral adipose tissue in women (p<0.05 after adjusting for age and body mass index). In conclusion, the present meta-GWAS combined with mRNA expression studies highlights the role of genetic variation in the RARRES2 locus in the regulation of circulating chemerin concentrations. PMID:25521368

De Novo Deep Transcriptome Analysis of Medicinal Plants for Gene Discovery in Biosynthesis of Plant Natural Products.

PubMed

Han, R; Rai, A; Nakamura, M; Suzuki, H; Takahashi, H; Yamazaki, M; Saito, K

2016-01-01

Study on transcriptome, the entire pool of transcripts in an organism or single cells at certain physiological or pathological stage, is indispensable in unraveling the connection and regulation between DNA and protein. Before the advent of deep sequencing, microarray was the main approach to handle transcripts. Despite obvious shortcomings, including limited dynamic range and difficulties to compare the results from distinct experiments, microarray was widely applied. During the past decade, next-generation sequencing (NGS) has revolutionized our understanding of genomics in a fast, high-throughput, cost-effective, and tractable manner. By adopting NGS, efficiency and fruitful outcomes concerning the efforts to elucidate genes responsible for producing active compounds in medicinal plants were profoundly enhanced. The whole process involves steps, from the plant material sampling, to cDNA library preparation, to deep sequencing, and then bioinformatics takes over to assemble enormous-yet fragmentary-data from which to comb and extract information. The unprecedentedly rapid development of such technologies provides so many choices to facilitate the task, which can cause confusion when choosing the suitable methodology for specific purposes. Here, we review the general approaches for deep transcriptome analysis and then focus on their application in discovering biosynthetic pathways of medicinal plants that produce important secondary metabolites. © 2016 Elsevier Inc. All rights reserved.

A Practical Platform for Blood Biomarker Study by Using Global Gene Expression Profiling of Peripheral Whole Blood

PubMed Central

Schmid, Patrick; Yao, Hui; Galdzicki, Michal; Berger, Bonnie; Wu, Erxi; Kohane, Isaac S.

2009-01-01

Background Although microarray technology has become the most common method for studying global gene expression, a plethora of technical factors across the experiment contribute to the variable of genome gene expression profiling using peripheral whole blood. A practical platform needs to be established in order to obtain reliable and reproducible data to meet clinical requirements for biomarker study. Methods and Findings We applied peripheral whole blood samples with globin reduction and performed genome-wide transcriptome analysis using Illumina BeadChips. Real-time PCR was subsequently used to evaluate the quality of array data and elucidate the mode in which hemoglobin interferes in gene expression profiling. We demonstrated that, when applied in the context of standard microarray processing procedures, globin reduction results in a consistent and significant increase in the quality of beadarray data. When compared to their pre-globin reduction counterparts, post-globin reduction samples show improved detection statistics, lowered variance and increased sensitivity. More importantly, gender gene separation is remarkably clearer in post-globin reduction samples than in pre-globin reduction samples. Our study suggests that the poor data obtained from pre-globin reduction samples is the result of the high concentration of hemoglobin derived from red blood cells either interfering with target mRNA binding or giving the pseudo binding background signal. Conclusion We therefore recommend the combination of performing globin mRNA reduction in peripheral whole blood samples and hybridizing on Illumina BeadChips as the practical approach for biomarker study. PMID:19381341

Aberrant DNA methylation of miR-219 promoter in long-term night shiftworkers.

PubMed

Shi, Fengqin; Chen, Xinyi; Fu, Alan; Hansen, Johnni; Stevens, Richard; Tjonneland, Anne; Vogel, Ulla B; Zheng, Tongzhang; Zhu, Yong

2013-07-01

The idea that shiftwork may be carcinogenic in humans has gained widespread attention since the pioneering work linking shiftwork to breast cancer over two decades ago. However, the biomolecular consequences of long-term shiftwork exposure have not been fully explored. In this study, we performed a genome-wide CpG island methylation assay of microRNA (miRNA) promoters in long-term night shiftworkers and day workers. This analysis indicated that 50 CpG loci corresponding to 31 miRNAs were differentially methylated in night shiftworkers compared to day workers, including the circadian-relevant miR-219, the expression of which has been implicated in several cancers. A genome-wide expression microarray assay was carried out in a miR-219-overexpressed MCF-7 breast cancer cell line, which identified 319 differentially expressed transcripts. The identified transcriptional targets were analyzed for network and functional interrelatedness using the Ingenuity Pathway Analysis (IPA) software. Overexpression of miR-219 in MCF-7 breast cancer cells resulted in accentuated expression of apoptosis- and proliferation-related anti-viral immunodulators of the Jak-STAT and NF-κβ pathways. These findings suggest that long-term night shiftwork exposure may lead to the methylation-dependent downregulation of miR-219, which may in turn lead to the downregulation of immunomediated antitumor activity and increased breast cancer risk. © 2013 Wiley Periodicals, Inc.

Genome-wide STAT3 binding analysis after histone deacetylase inhibition reveals novel target genes in dendritic cells

PubMed Central

Sun, Yaping; Iyer, Matthew; McEachin, Richard; Zhao, Meng; Wu, Yi-Mi; Cao, Xuhong; Oravecz-Wilson, Katherine; Zajac, Cynthia; Mathewson, Nathan; Wu, Shin-Rong Julia; Rossi, Corinne; Toubai, Tomomi; Qin, Zhaohui S.; Chinnaiya, Arul M.; Reddy, Pavan

2016-01-01

STAT3 is a master transcriptional regulator that plays an important role in the induction of both immune activation and immune tolerance in dendritic cells (DCs). The transcriptional targets of STAT3 in promoting DC activation are becoming increasingly understood; however, the mechanisms underpinning its role in causing DC suppression remain largely unknown. To determine the functional gene targets of STAT3, we compared the genome-wide binding of STAT3 using ChIP-seq coupled with gene expression microarrays to determine STAT3-dependent gene regulation in DCs after histone deacetylase (HDAC) inhibition. HDAC inhibition boosted the ability of STAT3 to bind to distinct DNA targets and regulate gene expression. Among the top 500 STAT3 binding sites, the frequency of canonical motifs was significantly higher than that of non-canonical motifs. Functional analysis revealed that after treatment with an HDAC inhibitor, the upregulated STAT3 target genes were those that were primarily the negative regulators of pro-inflammatory cytokines and those in the IL-10 signaling pathway. The downregulated STAT3-dependent targets were those involved in immune effector processes and antigen processing/presentation. The expression and functional relevance of these genes were validated. Specifically, functional studies confirmed that the upregulation of IL-10Ra by STAT3 contributed to the suppressive function of DCs following HDAC inhibition. PMID:27866206

The response of macrophages to titanium particles is determined by macrophage polarization.

PubMed

Pajarinen, Jukka; Kouri, Vesa-Petteri; Jämsen, Eemeli; Li, Tian-Fang; Mandelin, Jami; Konttinen, Yrjö T

2013-11-01

Aseptic loosening of total joint replacements is driven by the reaction of macrophages to foreign body particles released from the implant. It was hypothesized that the macrophages' response to these particles is dependent, in addition to particle characteristics and contaminating biomolecules, on the state of macrophage polarization as determined by the local cytokine microenvironment. To test this hypothesis we differentiated M1 and M2 macrophages from human peripheral blood monocytes and compared their responses to titanium particles using genome-wide microarray analysis and a multiplex cytokine assay. In comparison to non-activated M0 macrophages, the overall chemotactic and inflammatory responses to titanium particles were greatly enhanced in M1 macrophages and effectively suppressed in M2 macrophages. In addition, the genome-wide approach revealed several novel, potentially osteolytic, particle-induced mediators, and signaling pathway analysis suggested the involvement of toll-like and nod-like receptor signaling in particle recognition. It is concluded that the magnitude of foreign body reaction caused by titanium particles is dependent on the state of macrophage polarization. Thus, by limiting the action of M1 polarizing factors, e.g. bacterial biofilm formation, in peri-implant tissues and promoting M2 macrophage polarization by biomaterial solutions or pharmacologically, it might be possible to restrict wear-particle-induced inflammation and osteolysis. Copyright © 2013 Acta Materialia Inc. Published by Elsevier Ltd. All rights reserved.

PExFInS: An Integrative Post-GWAS Explorer for Functional Indels and SNPs

PubMed Central

Cheng, Zhongshan; Chu, Hin; Fan, Yanhui; Li, Cun; Song, You-Qiang; Zhou, Jie; Yuen, Kwok-Yung

2015-01-01

Expression quantitative trait loci (eQTLs) mapping and linkage disequilibrium (LD) analysis have been widely employed to interpret findings of genome-wide association studies (GWAS). With the availability of deep sequencing data of 423 lymphoblastoid cell lines (LCLs) from six global populations and the microarray expression data, we performed eQTL analysis, identified more than 228 K SNP cis-eQTLs and 21 K indel cis-eQTLs and generated a LCL cis-eQTL database. We demonstrate that the percentages of population-shared and population-specific cis-eQTLs are comparable; while indel cis-eQTLs in the population-specific subsection make more contribution to gene expression variations than those in the population-shared subsection. We found cis-eQTLs, especially the population-shared cis-eQTLs are significantly enriched toward transcription start site. Moreover, the National Human Genome Research Institute cataloged GWAS SNPs are enriched for LCL cis-eQTLs. Specifically, 32.8% GWAS SNPs are LCL cis-eQTLs, among which 12.5% can be tagged by indel cis-eQTLs, suggesting the fundamental contribution of indel cis-eQTLs to GWAS association signals. To search for functional indels and SNPs tagging GWAS SNPs, a pipeline Post-GWAS Explorer for Functional Indels and SNPs (PExFInS) has been developed, integrating LD analysis, functional annotation from public databases, cis-eQTL mapping with our LCL cis-eQTL database and other published cis-eQTL datasets. PMID:26612672

Homogeneous versus heterogeneous probes for microbial ecological microarrays.

PubMed

Bae, Jin-Woo; Park, Yong-Ha

2006-07-01

Microbial ecological microarrays have been developed for investigating the composition and functions of microorganism communities in environmental niches. These arrays include microbial identification microarrays, which use oligonucleotides, gene fragments or microbial genomes as probes. In this article, the advantages and disadvantages of each type of probe are reviewed. Oligonucleotide probes are currently useful for probing uncultivated bacteria that are not amenable to gene fragment probing, whereas the functional gene fragments amplified randomly from microbial genomes require phylogenetic and hierarchical categorization before use as microbial identification probes, despite their high resolution for both specificity and sensitivity. Until more bacteria are sequenced and gene fragment probes are thoroughly validated, heterogeneous bacterial genome probes will provide a simple, sensitive and quantitative tool for exploring the ecosystem structure.

The Importance of Normalization on Large and Heterogeneous Microarray Datasets

EPA Science Inventory

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

Functional analysis of PGRP-LA in Drosophila immunity.

PubMed

Gendrin, Mathilde; Zaidman-Rémy, Anna; Broderick, Nichole A; Paredes, Juan; Poidevin, Mickaël; Roussel, Alain; Lemaitre, Bruno

2013-01-01

PeptidoGlycan Recognition Proteins (PGRPs) are key regulators of the insect innate antibacterial response. Even if they have been intensively studied, some of them have yet unknown functions. Here, we present a functional analysis of PGRP-LA, an as yet uncharacterized Drosophila PGRP. The PGRP-LA gene is located in cluster with PGRP-LC and PGRP-LF, which encode a receptor and a negative regulator of the Imd pathway, respectively. Structure predictions indicate that PGRP-LA would not bind to peptidoglycan, pointing to a regulatory role of this PGRP. PGRP-LA expression was enriched in barrier epithelia, but low in the fat body. Use of a newly generated PGRP-LA deficient mutant indicates that PGRP-LA is not required for the production of antimicrobial peptides by the fat body in response to a systemic infection. Focusing on the respiratory tract, where PGRP-LA is strongly expressed, we conducted a genome-wide microarray analysis of the tracheal immune response of wild-type, Relish, and PGRP-LA mutant larvae. Comparing our data to previous microarray studies, we report that a majority of genes regulated in the trachea upon infection differ from those induced in the gut or the fat body. Importantly, antimicrobial peptide gene expression was reduced in the tracheae of larvae and in the adult gut of PGRP-LA-deficient Drosophila upon oral bacterial infection. Together, our results suggest that PGRP-LA positively regulates the Imd pathway in barrier epithelia.

Using pathway modules as targets for assay development in xenobiotic screening

EPA Science Inventory

Toxicology and pharmaceutical research is increasingly making use of high throughout-screening (HTS) methods to assess the effects of chemicals on molecular pathways, cells and tissues. Whole-genome microarray analysis provides broad information on the response of biological syst...

Genomic analysis of soybean defense response to Sclerotinia sclerotiorum

USDA-ARS?s Scientific Manuscript database

We have conducted microarray studies on changes in soybean transcript levels in response to Sclerotinia sclerotiorum infection. These stem inoculations enabled us to identify genes that are differentially expressed in soybean plants in partially resistant versus susceptible varieties. We are expandi...

Pathogen profiling for disease management and surveillance.

PubMed

Sintchenko, Vitali; Iredell, Jonathan R; Gilbert, Gwendolyn L

2007-06-01

The usefulness of rapid pathogen genotyping is widely recognized, but its effective interpretation and application requires integration into clinical and public health decision-making. How can pathogen genotyping data best be translated to inform disease management and surveillance? Pathogen profiling integrates microbial genomics data into communicable disease control by consolidating phenotypic identity-based methods with DNA microarrays, proteomics, metabolomics and sequence-based typing. Sharing data on pathogen profiles should facilitate our understanding of transmission patterns and the dynamics of epidemics.

Genome-Wide Profiling of Humoral Immune Response to Coxiella burnetii Infection by Protein Microarray

DTIC Science & Technology

2010-01-01

mortality rate for Chronic Q fever to less than 1% [1, 4, 5]. Chronic infections may cause life-threatening endocarditis but may not show apparent...Houpikian, P., Tissot Dupont, H., Riss, J. M. et a/., Treatment of a fever endocarditis : comparison of 2 regimens containing doxycycline and ofloxacin...fever endocarditis . J. Infect. Dis. 1998, 178, 278-281. [7) Yu, X., Raoult, D., Serotyping Coxiella burnetii isolates from acute and chronic a fever

Genome-Wide Identification and Immune Response Analysis of Serine Protease Inhibitor Genes in the Silkworm, Bombyx mori

PubMed Central

Duan, Jun; Wang, Genhong; Wang, Lingyan; Li, Youshan; Xiang, Zhonghuai; Xia, Qingyou

2012-01-01

In most insect species, a variety of serine protease inhibitors (SPIs) have been found in multiple tissues, including integument, gonad, salivary gland, and hemolymph, and are required for preventing unwanted proteolysis. These SPIs belong to different families and have distinct inhibitory mechanisms. Herein, we predicted and characterized potential SPI genes based on the genome sequences of silkworm, Bombyx mori. As a result, a total of eighty SPI genes were identified in B. mori. These SPI genes contain 10 kinds of SPI domains, including serpin, Kunitz_BPTI, Kazal, TIL, amfpi, Bowman-Birk, Antistasin, WAP, Pacifastin, and alpha-macroglobulin. Sixty-three SPIs contain single SPI domain while the others have at least two inhibitor units. Some SPIs also contain non-inhibitor domains for protein-protein interactions, including EGF, ADAM_spacer, spondin_N, reeler, TSP_1 and other modules. Microarray analysis showed that fourteen SPI genes from lineage-specific TIL family and Group F of serpin family had enriched expression in the silk gland. The roles of SPIs in resisting pathogens were investigated in silkworms when they were infected by four pathogens. Microarray and qRT-PCR experiments revealed obvious up-regulation of 8, 4, 3 and 3 SPI genes after infection with Escherichia coli, Bacillus bombysepticus, Beauveria bassiana or B. mori nuclear polyhedrosis virus (BmNPV), respectively. On the contrary, 4, 11, 7 and 9 SPI genes were down-regulated after infection with E. coli, B. bombysepticus, B. bassiana or BmNPV, respectively. These results suggested that these SPI genes may be involved in resistance to pathogenic microorganisms. These findings may provide valuable information for further clarifying the roles of SPIs in the development, immune defence, and efficient synthesis of silk gland protein. PMID:22348050

Rapid genotyping with DNA micro-arrays for high-density linkage mapping and QTL mapping in common buckwheat (Fagopyrum esculentum Moench)

PubMed Central

Yabe, Shiori; Hara, Takashi; Ueno, Mariko; Enoki, Hiroyuki; Kimura, Tatsuro; Nishimura, Satoru; Yasui, Yasuo; Ohsawa, Ryo; Iwata, Hiroyoshi

2014-01-01

For genetic studies and genomics-assisted breeding, particularly of minor crops, a genotyping system that does not require a priori genomic information is preferable. Here, we demonstrated the potential of a novel array-based genotyping system for the rapid construction of high-density linkage map and quantitative trait loci (QTL) mapping. By using the system, we successfully constructed an accurate, high-density linkage map for common buckwheat (Fagopyrum esculentum Moench); the map was composed of 756 loci and included 8,884 markers. The number of linkage groups converged to eight, which is the basic number of chromosomes in common buckwheat. The sizes of the linkage groups of the P1 and P2 maps were 773.8 and 800.4 cM, respectively. The average interval between adjacent loci was 2.13 cM. The linkage map constructed here will be useful for the analysis of other common buckwheat populations. We also performed QTL mapping for main stem length and detected four QTL. It took 37 days to process 178 samples from DNA extraction to genotyping, indicating the system enables genotyping of genome-wide markers for a few hundred buckwheat plants before the plants mature. The novel system will be useful for genomics-assisted breeding in minor crops without a priori genomic information. PMID:25914583

Rapid genotyping with DNA micro-arrays for high-density linkage mapping and QTL mapping in common buckwheat (Fagopyrum esculentum Moench).

PubMed

Yabe, Shiori; Hara, Takashi; Ueno, Mariko; Enoki, Hiroyuki; Kimura, Tatsuro; Nishimura, Satoru; Yasui, Yasuo; Ohsawa, Ryo; Iwata, Hiroyoshi

2014-12-01

For genetic studies and genomics-assisted breeding, particularly of minor crops, a genotyping system that does not require a priori genomic information is preferable. Here, we demonstrated the potential of a novel array-based genotyping system for the rapid construction of high-density linkage map and quantitative trait loci (QTL) mapping. By using the system, we successfully constructed an accurate, high-density linkage map for common buckwheat (Fagopyrum esculentum Moench); the map was composed of 756 loci and included 8,884 markers. The number of linkage groups converged to eight, which is the basic number of chromosomes in common buckwheat. The sizes of the linkage groups of the P1 and P2 maps were 773.8 and 800.4 cM, respectively. The average interval between adjacent loci was 2.13 cM. The linkage map constructed here will be useful for the analysis of other common buckwheat populations. We also performed QTL mapping for main stem length and detected four QTL. It took 37 days to process 178 samples from DNA extraction to genotyping, indicating the system enables genotyping of genome-wide markers for a few hundred buckwheat plants before the plants mature. The novel system will be useful for genomics-assisted breeding in minor crops without a priori genomic information.

A Genomics Approach to Deciphering Lignin Biosynthesis in Switchgrass[W

PubMed Central

Shen, Hui; Mazarei, Mitra; Hisano, Hiroshi; Escamilla-Trevino, Luis; Fu, Chunxiang; Pu, Yunqiao; Rudis, Mary R.; Tang, Yuhong; Xiao, Xirong; Jackson, Lisa; Li, Guifen; Hernandez, Tim; Chen, Fang; Ragauskas, Arthur J.; Stewart, C. Neal; Wang, Zeng-Yu; Dixon, Richard A.

2013-01-01

It is necessary to overcome recalcitrance of the biomass to saccharification (sugar release) to make switchgrass (Panicum virgatum) economically viable as a feedstock for liquid biofuels. Lignin content correlates negatively with sugar release efficiency in switchgrass, but selecting the right gene candidates for engineering lignin biosynthesis in this tetraploid outcrossing species is not straightforward. To assist this endeavor, we have used an inducible switchgrass cell suspension system for studying lignin biosynthesis in response to exogenous brassinolide. By applying a combination of protein sequence phylogeny with whole-genome microarray analyses of induced cell cultures and developing stem internode sections, we have generated a list of candidate monolignol biosynthetic genes for switchgrass. Several genes that were strongly supported through our bioinformatics analysis as involved in lignin biosynthesis were confirmed by gene silencing studies, in which lignin levels were reduced as a result of targeting a single gene. However, candidate genes encoding enzymes involved in the early steps of the currently accepted monolignol biosynthesis pathway in dicots may have functionally redundant paralogues in switchgrass and therefore require further evaluation. This work provides a blueprint and resources for the systematic genome-wide study of the monolignol pathway in switchgrass, as well as other C4 monocot species. PMID:24285795

The Growing Importance of CNVs: New Insights for Detection and Clinical Interpretation

PubMed Central

Valsesia, Armand; Macé, Aurélien; Jacquemont, Sébastien; Beckmann, Jacques S.; Kutalik, Zoltán

2013-01-01

Differences between genomes can be due to single nucleotide variants, translocations, inversions, and copy number variants (CNVs, gain or loss of DNA). The latter can range from sub-microscopic events to complete chromosomal aneuploidies. Small CNVs are often benign but those larger than 500 kb are strongly associated with morbid consequences such as developmental disorders and cancer. Detecting CNVs within and between populations is essential to better understand the plasticity of our genome and to elucidate its possible contribution to disease. Hence there is a need for better-tailored and more robust tools for the detection and genome-wide analyses of CNVs. While a link between a given CNV and a disease may have often been established, the relative CNV contribution to disease progression and impact on drug response is not necessarily understood. In this review we discuss the progress, challenges, and limitations that occur at different stages of CNV analysis from the detection (using DNA microarrays and next-generation sequencing) and identification of recurrent CNVs to the association with phenotypes. We emphasize the importance of germline CNVs and propose strategies to aid clinicians to better interpret structural variations and assess their clinical implications. PMID:23750167

Characterization of a novel Lactobacillus species closely related to Lactobacillus johnsonii using a combination of molecular and comparative genomics methods.

PubMed

Sarmiento-Rubiano, Luz-Adriana; Berger, Bernard; Moine, Déborah; Zúñiga, Manuel; Pérez-Martínez, Gaspar; Yebra, María J

2010-09-17

Comparative genomic hybridization (CGH) constitutes a powerful tool for identification and characterization of bacterial strains. In this study we have applied this technique for the characterization of a number of Lactobacillus strains isolated from the intestinal content of rats fed with a diet supplemented with sorbitol. Phylogenetic analysis based on 16S rRNA gene, recA, pheS, pyrG and tuf sequences identified five bacterial strains isolated from the intestinal content of rats as belonging to the recently described Lactobacillus taiwanensis species. DNA-DNA hybridization experiments confirmed that these five strains are distinct but closely related to Lactobacillus johnsonii and Lactobacillus gasseri. A whole genome DNA microarray designed for the probiotic L. johnsonii strain NCC533 was used for CGH analysis of L. johnsonii ATCC 33200T, L. johnsonii BL261, L. gasseri ATCC 33323T and L. taiwanensis BL263. In these experiments, the fluorescence ratio distributions obtained with L. taiwanensis and L. gasseri showed characteristic inter-species profiles. The percentage of conserved L. johnsonii NCC533 genes was about 83% in the L. johnsonii strains comparisons and decreased to 51% and 47% for L. taiwanensis and L. gasseri, respectively. These results confirmed the separate status of L. taiwanensis from L. johnsonii at the level of species, and also that L. taiwanensis is closer to L. johnsonii than L. gasseri is to L. johnsonii. Conventional taxonomic analyses and microarray-based CGH analysis have been used for the identification and characterization of the newly species L. taiwanensis. The microarray-based CGH technology has been shown as a remarkable tool for the identification and fine discrimination between phylogenetically close species, and additionally provided insight into the adaptation of the strain L. taiwanensis BL263 to its ecological niche.

Digital microarray analysis for digital artifact genomics

NASA Astrophysics Data System (ADS)

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.

Screening for Intellectual Disability Using High-Resolution CMA Technology in a Retrospective Cohort from Central Brazil

PubMed Central

Pereira, Rodrigo Roncato; Pinto, Irene Plaza; Minasi, Lysa Bernardes; de Melo, Aldaires Vieira; da Cruz e Cunha, Damiana Mirian; Cruz, Alex Silva; Ribeiro, Cristiano Luiz; da Silva, Cláudio Carlos; de Melo e Silva, Daniela; da Cruz, Aparecido Divino

2014-01-01

Intellectual disability is a complex, variable, and heterogeneous disorder, representing a disabling condition diagnosed worldwide, and the etiologies are multiple and highly heterogeneous. Microscopic chromosomal abnormalities and well-characterized genetic conditions are the most common causes of intellectual disability. Chromosomal Microarray Analysis analyses have made it possible to identify putatively pathogenic copy number variation that could explain the molecular etiology of intellectual disability. The aim of the current study was to identify possible submicroscopic genomic alterations using a high-density chromosomal microarray in a retrospective cohort of patients with otherwise undiagnosable intellectual disabilities referred by doctors from the public health system in Central Brazil. The CytoScan HD technology was used to detect changes in the genome copy number variation of patients who had intellectual disability and a normal karyotype. The analysis detected 18 CNVs in 60% of patients. Pathogenic CNVs represented about 22%, so it was possible to propose the etiology of intellectual disability for these patients. Likely pathogenic and unknown clinical significance CNVs represented 28% and 50%, respectively. Inherited and de novo CNVs were equally distributed. We report the nature of CNVs in patients from Central Brazil, representing a population not yet screened by microarray technologies. PMID:25061755

Genome‐wide association study of facial emotion recognition in children and association with polygenic risk for mental health disorders

PubMed Central

Coleman, Jonathan R.I.; Lester, Kathryn J.; Keers, Robert; Munafò, Marcus R.; Breen, Gerome

2017-01-01

Emotion recognition is disrupted in many mental health disorders, which may reflect shared genetic aetiology between this trait and these disorders. We explored genetic influences on emotion recognition and the relationship between these influences and mental health phenotypes. Eight‐year‐old participants (n = 4,097) from the Avon Longitudinal Study of Parents and Children (ALSPAC) completed the Diagnostic Analysis of Non‐Verbal Accuracy (DANVA) faces test. Genome‐wide genotype data was available from the Illumina HumanHap550 Quad microarray. Genome‐wide association studies were performed to assess associations with recognition of individual emotions and emotion in general. Exploratory polygenic risk scoring was performed using published genomic data for schizophrenia, bipolar disorder, depression, autism spectrum disorder, anorexia, and anxiety disorders. No individual genetic variants were identified at conventional levels of significance in any analysis although several loci were associated at a level suggestive of significance. SNP‐chip heritability analyses did not identify a heritable component of variance for any phenotype. Polygenic scores were not associated with any phenotype. The effect sizes of variants influencing emotion recognition are likely to be small. Previous studies of emotion identification have yielded non‐zero estimates of SNP‐heritability. This discrepancy is likely due to differences in the measurement and analysis of the phenotype. PMID:28608620

Transcriptome analysis of salinity stress responses in common wheat using a 22k oligo-DNA microarray.

PubMed

Kawaura, Kanako; Mochida, Keiichi; Yamazaki, Yukiko; Ogihara, Yasunari

2006-04-01

In this study, we constructed a 22k wheat oligo-DNA microarray. A total of 148,676 expressed sequence tags of common wheat were collected from the database of the Wheat Genomics Consortium of Japan. These were grouped into 34,064 contigs, which were then used to design an oligonucleotide DNA microarray. Following a multistep selection of the sense strand, 21,939 60-mer oligo-DNA probes were selected for attachment on the microarray slide. This 22k oligo-DNA microarray was used to examine the transcriptional response of wheat to salt stress. More than 95% of the probes gave reproducible hybridization signals when targeted with RNAs extracted from salt-treated wheat shoots and roots. With the microarray, we identified 1,811 genes whose expressions changed more than 2-fold in response to salt. These included genes known to mediate response to salt, as well as unknown genes, and they were classified into 12 major groups by hierarchical clustering. These gene expression patterns were also confirmed by real-time reverse transcription-PCR. Many of the genes with unknown function were clustered together with genes known to be involved in response to salt stress. Thus, analysis of gene expression patterns combined with gene ontology should help identify the function of the unknown genes. Also, functional analysis of these wheat genes should provide new insight into the response to salt stress. Finally, these results indicate that the 22k oligo-DNA microarray is a reliable method for monitoring global gene expression patterns in wheat.

Genomic analysis of the host response to nervous necrosis virus in Atlantic cod (Gadus morhua) brain.

PubMed

Krasnov, Aleksei; Kileng, Øyvind; Skugor, Stanko; Jørgensen, Sven Martin; Afanasyev, Sergey; Timmerhaus, Gerrit; Sommer, Ann-Inger; Jensen, Ingvill

2013-07-01

Genome sequencing combined with transcriptome profiling promotes exploration of defence against pathogens and discovery of immune genes. Based on sequences from the recently released genome of Atlantic cod, a genome-wide oligonucleotide microarray (ACIQ-1) was designed and used for analyses of gene expression in the brain during infection with nervous necrosis virus (NNV). A challenge experiment with NNV was performed with Atlantic cod juveniles and brain samples from virus infected and uninfected fish were used for microarray analysis. Expression of virus induced genes increased at 5 days post challenge and persisted at stable level to the last sampling at 25 days post challenge. A large fraction of the up-regulated genes (546 features) were known or expected to have immune functions and most of these have not previously been characterized in Atlantic cod. Transcriptomic changes induced by the virus involved strong activation of genes associated with interferon and tumour necrosis factor related responses and acute inflammation. Up-regulation of genes involved in adaptive immunity suggested a rapid recruitment of B and T lymphocytes to the NNV infected brain. QPCR analyses of 15 candidate genes of innate immunity showed rapid induction by poly(I:C) in Atlantic cod larvae cells suggesting an antiviral role. Earliest and greatest expression changes after poly I:C stimulation was observed for interferon regulatory factors IRF4 and IRF7. Comparative studies between teleost species provided new knowledge about the evolution of innate antiviral immunity in fish. A number of genes is present or responds to viruses only in fish. Innate immunity of Atlantic cod is characterized by selective expansion of several medium-sized multigene families with ribose binding domains. An interesting finding was the high representation of three large gene families among the early antiviral genes, including tripartite motif proteins (TRIM) and proteins with PRY-SPRY and NACHT domains. The latter two with respectively 52 and 114 members in Atlantic cod have gone through expansions in different groups of fish. These proteins most likely have ligand binding properties and their propagation could be linked to the loss of MHC class II in the Atlantic cod genome. Copyright © 2013 Elsevier Ltd. All rights reserved.

Bacillus subtilis genome diversity.

PubMed

Earl, Ashlee M; Losick, Richard; Kolter, Roberto

2007-02-01

Microarray-based comparative genomic hybridization (M-CGH) is a powerful method for rapidly identifying regions of genome diversity among closely related organisms. We used M-CGH to examine the genome diversity of 17 strains belonging to the nonpathogenic species Bacillus subtilis. Our M-CGH results indicate that there is considerable genetic heterogeneity among members of this species; nearly one-third of Bsu168-specific genes exhibited variability, as measured by the microarray hybridization intensities. The variable loci include those encoding proteins involved in antibiotic production, cell wall synthesis, sporulation, and germination. The diversity in these genes may reflect this organism's ability to survive in diverse natural settings.

Sequencing ebola and marburg viruses genomes using microarrays.

PubMed

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

2016-08-01

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

Nutrient control of gene expression in Drosophila: microarray analysis of starvation and sugar-dependent response

PubMed Central

Zinke, Ingo; Schütz, Christina S.; Katzenberger, Jörg D.; Bauer, Matthias; Pankratz, Michael J.

2002-01-01

We have identified genes regulated by starvation and sugar signals in Drosophila larvae using whole-genome microarrays. Based on expression profiles in the two nutrient conditions, they were organized into different categories that reflect distinct physiological pathways mediating sugar and fat metabolism, and cell growth. In the category of genes regulated in sugar-fed, but not in starved, animals, there is an upregulation of genes encoding key enzymes of the fat biosynthesis pathway and a downregulation of genes encoding lipases. The highest and earliest activated gene upon sugar ingestion is sugarbabe, a zinc finger protein that is induced in the gut and the fat body. Identification of potential targets using microarrays suggests that sugarbabe functions to repress genes involved in dietary fat breakdown and absorption. The current analysis provides a basis for studying the genetic mechanisms underlying nutrient signalling. PMID:12426388

Finding Groups in Gene Expression Data

PubMed Central

2005-01-01

The vast potential of the genomic insight offered by microarray technologies has led to their widespread use since they were introduced a decade ago. Application areas include gene function discovery, disease diagnosis, and inferring regulatory networks. Microarray experiments enable large-scale, high-throughput investigations of gene activity and have thus provided the data analyst with a distinctive, high-dimensional field of study. Many questions in this field relate to finding subgroups of data profiles which are very similar. A popular type of exploratory tool for finding subgroups is cluster analysis, and many different flavors of algorithms have been used and indeed tailored for microarray data. Cluster analysis, however, implies a partitioning of the entire data set, and this does not always match the objective. Sometimes pattern discovery or bump hunting tools are more appropriate. This paper reviews these various tools for finding interesting subgroups. PMID:16046827

Genome sequence and comparative microarray analysis of serotype M18 group A Streptococcus strains associated with acute rheumatic fever outbreaks.

PubMed

Smoot, James C; Barbian, Kent D; Van Gompel, Jamie J; Smoot, Laura M; Chaussee, Michael S; Sylva, Gail L; Sturdevant, Daniel E; Ricklefs, Stacy M; Porcella, Stephen F; Parkins, Larye D; Beres, Stephen B; Campbell, David S; Smith, Todd M; Zhang, Qing; Kapur, Vivek; Daly, Judy A; Veasy, L George; Musser, James M

2002-04-02

Acute rheumatic fever (ARF), a sequelae of group A Streptococcus (GAS) infection, is the most common cause of preventable childhood heart disease worldwide. The molecular basis of ARF and the subsequent rheumatic heart disease are poorly understood. Serotype M18 GAS strains have been associated for decades with ARF outbreaks in the U.S. As a first step toward gaining new insight into ARF pathogenesis, we sequenced the genome of strain MGAS8232, a serotype M18 organism isolated from a patient with ARF. The genome is a circular chromosome of 1,895,017 bp, and it shares 1.7 Mb of closely related genetic material with strain SF370 (a sequenced serotype M1 strain). Strain MGAS8232 has 178 ORFs absent in SF370. Phages, phage-like elements, and insertion sequences are the major sources of variation between the genomes. The genomes of strain MGAS8232 and SF370 encode many of the same proven or putative virulence factors. Importantly, strain MGAS8232 has genes encoding many additional secreted proteins involved in human-GAS interactions, including streptococcal pyrogenic exotoxin A (scarlet fever toxin) and two uncharacterized pyrogenic exotoxin homologues, all phage-associated. DNA microarray analysis of 36 serotype M18 strains from diverse localities showed that most regions of variation were phages or phage-like elements. Two epidemics of ARF occurring 12 years apart in Salt Lake City, UT, were caused by serotype M18 strains that were genetically identical, or nearly so. Our analysis provides a critical foundation for accelerated research into ARF pathogenesis and a molecular framework to study the plasticity of GAS genomes.

Microarray-based comparative genomic hybridization analysis in neonates with congenital anomalies: detection of chromosomal imbalances.

PubMed

Emy Dorfman, Luiza; Leite, Júlio César L; Giugliani, Roberto; Riegel, Mariluce

2015-01-01

To identify chromosomal imbalances by whole-genome microarray-based comparative genomic hybridization (array-CGH) in DNA samples of neonates with congenital anomalies of unknown cause from a birth defects monitoring program at a public maternity hospital. A blind genomic analysis was performed retrospectively in 35 stored DNA samples of neonates born between July of 2011 and December of 2012. All potential DNA copy number variations detected (CNVs) were matched with those reported in public genomic databases, and their clinical significance was evaluated. Out of a total of 35 samples tested, 13 genomic imbalances were detected in 12/35 cases (34.3%). In 4/35 cases (11.4%), chromosomal imbalances could be defined as pathogenic; in 5/35 (14.3%) cases, DNA CNVs of uncertain clinical significance were identified; and in 4/35 cases (11.4%), normal variants were detected. Among the four cases with results considered causally related to the clinical findings, two of the four (50%) showed causative alterations already associated with well-defined microdeletion syndromes. In two of the four samples (50%), the chromosomal imbalances found, although predicted as pathogenic, had not been previously associated with recognized clinical entities. Array-CGH analysis allowed for a higher rate of detection of chromosomal anomalies, and this determination is especially valuable in neonates with congenital anomalies of unknown etiology, or in cases in which karyotype results cannot be obtained. Moreover, although the interpretation of the results must be refined, this method is a robust and precise tool that can be used in the first-line investigation of congenital anomalies, and should be considered for prospective/retrospective analyses of DNA samples by birth defect monitoring programs. Copyright © 2014 Sociedade Brasileira de Pediatria. Published by Elsevier Editora Ltda. All rights reserved.

The molecular genetic makeup of acute lymphoblastic leukemia | Office of Cancer Genomics

Cancer.gov

Abstract: Genomic profiling has transformed our understanding of the genetic basis of acute lymphoblastic leukemia (ALL). Recent years have seen a shift from microarray analysis and candidate gene sequencing to next-generation sequencing. Together, these approaches have shown that many ALL subtypes are characterized by constellations of structural rearrangements, submicroscopic DNA copy number alterations, and sequence mutations, several of which have clear implications for risk stratification and targeted therapeutic intervention.

Chromosomal microarray analysis as the first-tier test for the identification of pathogenic copy number variants in chromosome 9 pericentric regions and its challenge.

PubMed

Wang, Jia-Chi; Boyar, Fatih Z

2016-01-01

Chromosomal microarray analysis (CMA) has been recommended and practiced routinely in the large reference laboratories of U.S.A. as the first-tier test for the postnatal evaluation of individuals with intellectual disability, autism spectrum disorders, and/or multiple congenital anomalies. Using CMA as a diagnostic tool and without a routine setting of fluorescence in situ hybridization with labeled bacterial artificial chromosome probes (BAC-FISH) in the large reference laboratories becomes a challenge in the characterization of chromosome 9 pericentric region. This region has a very complex genomic structure and contains a variety of heterochromatic and euchromatic polymorphic variants. These variants were usually studied by G-banding, C-banding and BAC-FISH analysis. Chromosomal microarray analysis (CMA) was not recommended since it may lead to false positive results. Here, we presented a cohort of four cases, in which high-resolution CMA was used as the first-tier test or simultaneously with G-banding analysis on the proband to identify pathogenic copy number variants (CNVs) in the whole genome. CMA revealed large pathogenic CNVs from chromosome 9 in 3 cases which also revealed different G-banding patterns between the two chromosome 9 homologues. Although we demonstrated that high-resolution CMA played an important role in the identification of pathogenic copy number variants in chromosome 9 pericentric regions, the lack of BAC-FISH analysis or other useful tools renders significant challenges in the characterization of chromosome 9 pericentric regions. None; it is not a clinical trial, and the cases were retrospectively collected and analyzed.

Brief Guide to Genomics: DNA, Genes and Genomes

MedlinePlus

... Sheets A Brief Guide to Genomics About NHGRI Research About the International HapMap Project Biological Pathways Chromosome Abnormalities Chromosomes Cloning Comparative Genomics DNA Microarray Technology DNA Sequencing Deoxyribonucleic Acid ( ...

Effect of bodily fluids from honey bee (Apis mellifera) larvae on growth and genome-wide transcriptional response of the causal agent of American Foulbrood disease (Paenibacillus larvae).

PubMed

De Smet, Lina; De Koker, Dieter; Hawley, Alyse K; Foster, Leonard J; De Vos, Paul; de Graaf, Dirk C

2014-01-01

Paenibacillus larvae, the causal agent of American Foulbrood disease (AFB), affects honey bee health worldwide. The present study investigates the effect of bodily fluids from honey bee larvae on growth velocity and transcription for this Gram-positive, endospore-forming bacterium. It was observed that larval fluids accelerate the growth and lead to higher bacterial densities during stationary phase. The genome-wide transcriptional response of in vitro cultures of P. larvae to larval fluids was studied by microarray technology. Early responses of P. larvae to larval fluids are characterized by a general down-regulation of oligopeptide and sugar transporter genes, as well as by amino acid and carbohydrate metabolic genes, among others. Late responses are dominated by general down-regulation of sporulation genes and up-regulation of phage-related genes. A theoretical mechanism of carbon catabolite repression is discussed.

Ontology-based meta-analysis of global collections of high-throughput public data.

PubMed

Kupershmidt, Ilya; Su, Qiaojuan Jane; Grewal, Anoop; Sundaresh, Suman; Halperin, Inbal; Flynn, James; Shekar, Mamatha; Wang, Helen; Park, Jenny; Cui, Wenwu; Wall, Gregory D; Wisotzkey, Robert; Alag, Satnam; Akhtari, Saeid; Ronaghi, Mostafa

2010-09-29

The investigation of the interconnections between the molecular and genetic events that govern biological systems is essential if we are to understand the development of disease and design effective novel treatments. Microarray and next-generation sequencing technologies have the potential to provide this information. However, taking full advantage of these approaches requires that biological connections be made across large quantities of highly heterogeneous genomic datasets. Leveraging the increasingly huge quantities of genomic data in the public domain is fast becoming one of the key challenges in the research community today. We have developed a novel data mining framework that enables researchers to use this growing collection of public high-throughput data to investigate any set of genes or proteins. The connectivity between molecular states across thousands of heterogeneous datasets from microarrays and other genomic platforms is determined through a combination of rank-based enrichment statistics, meta-analyses, and biomedical ontologies. We address data quality concerns through dataset replication and meta-analysis and ensure that the majority of the findings are derived using multiple lines of evidence. As an example of our strategy and the utility of this framework, we apply our data mining approach to explore the biology of brown fat within the context of the thousands of publicly available gene expression datasets. Our work presents a practical strategy for organizing, mining, and correlating global collections of large-scale genomic data to explore normal and disease biology. Using a hypothesis-free approach, we demonstrate how a data-driven analysis across very large collections of genomic data can reveal novel discoveries and evidence to support existing hypothesis.

Identification of novel target genes involved in Indian Fanconi anemia patients using microarray.

PubMed

Shyamsunder, Pavithra; Ganesh, Kripa S; Vidyasekar, Prasanna; Mohan, Sheila; Verma, Rama Shanker

2013-12-01

Fanconi anemia (FA) is a genetic disorder characterized by progressive bone marrow failure and a predisposition to cancers. Mutations have been documented in 15 FA genes that participate in the FA-BRCA DNA repair pathway, a fundamental pathway in the development of the disease and the presentation of its characteristic symptoms. Certain symptoms such as oxygen sensitivity, hematological abnormalities and impaired immunity suggest that FA proteins could participate in or independently control other pathways as well. In this study, we identified 9 DNA repair genes that were down regulated in a genome wide analysis of 6 Indian Fanconi anemia patients. Functional clustering of a total of 233 dysregulated genes identified key biological processes that included regulation of transcription, DNA repair, cell cycle and chromosomal organization. Microarray data revealed the down regulation of ATXN3, ARID4A and ETS-1, which were validated by RTPCR in a subsequent sample set of 9 Indian FA patients. Here we report for the first time a gene expression profile of Fanconi anemia patients from the Indian population and a pool of genes that might aid in the acquisition and progression of the FA phenotype. © 2013 Elsevier B.V. All rights reserved.

Functional regression method for whole genome eQTL epistasis analysis with sequencing data.

PubMed

Xu, Kelin; Jin, Li; Xiong, Momiao

2017-05-18

Epistasis plays an essential rule in understanding the regulation mechanisms and is an essential component of the genetic architecture of the gene expressions. However, interaction analysis of gene expressions remains fundamentally unexplored due to great computational challenges and data availability. Due to variation in splicing, transcription start sites, polyadenylation sites, post-transcriptional RNA editing across the entire gene, and transcription rates of the cells, RNA-seq measurements generate large expression variability and collectively create the observed position level read count curves. A single number for measuring gene expression which is widely used for microarray measured gene expression analysis is highly unlikely to sufficiently account for large expression variation across the gene. Simultaneously analyzing epistatic architecture using the RNA-seq and whole genome sequencing (WGS) data poses enormous challenges. We develop a nonlinear functional regression model (FRGM) with functional responses where the position-level read counts within a gene are taken as a function of genomic position, and functional predictors where genotype profiles are viewed as a function of genomic position, for epistasis analysis with RNA-seq data. Instead of testing the interaction of all possible pair-wises SNPs, the FRGM takes a gene as a basic unit for epistasis analysis, which tests for the interaction of all possible pairs of genes and use all the information that can be accessed to collectively test interaction between all possible pairs of SNPs within two genome regions. By large-scale simulations, we demonstrate that the proposed FRGM for epistasis analysis can achieve the correct type 1 error and has higher power to detect the interactions between genes than the existing methods. The proposed methods are applied to the RNA-seq and WGS data from the 1000 Genome Project. The numbers of pairs of significantly interacting genes after Bonferroni correction identified using FRGM, RPKM and DESeq were 16,2361, 260 and 51, respectively, from the 350 European samples. The proposed FRGM for epistasis analysis of RNA-seq can capture isoform and position-level information and will have a broad application. Both simulations and real data analysis highlight the potential for the FRGM to be a good choice of the epistatic analysis with sequencing data.

Parallel processing of genomics data

NASA Astrophysics Data System (ADS)

Agapito, Giuseppe; Guzzi, Pietro Hiram; Cannataro, Mario

2016-10-01

The availability of high-throughput experimental platforms for the analysis of biological samples, such as mass spectrometry, microarrays and Next Generation Sequencing, have made possible to analyze a whole genome in a single experiment. Such platforms produce an enormous volume of data per single experiment, thus the analysis of this enormous flow of data poses several challenges in term of data storage, preprocessing, and analysis. To face those issues, efficient, possibly parallel, bioinformatics software needs to be used to preprocess and analyze data, for instance to highlight genetic variation associated with complex diseases. In this paper we present a parallel algorithm for the parallel preprocessing and statistical analysis of genomics data, able to face high dimension of data and resulting in good response time. The proposed system is able to find statistically significant biological markers able to discriminate classes of patients that respond to drugs in different ways. Experiments performed on real and synthetic genomic datasets show good speed-up and scalability.

Unraveling the Rat Intestine, Spleen and Liver Genome-Wide Transcriptome after the Oral Administration of Lavender Oil by a Two-Color Dye-Swap DNA Microarray Approach

PubMed Central

Kubo, Hiroko; Shibato, Junko; Saito, Tomomi; Ogawa, Tetsuo; Rakwal, Randeep; Shioda, Seiji

2015-01-01

The use of lavender oil (LO) – a commonly, used oil in aromatherapy, with well-defined volatile components linalool and linalyl acetate – in non-traditional medicine is increasing globally. To understand and demonstrate the potential positive effects of LO on the body, we have established an animal model in this current study, investigating the orally administered LO effects genome wide in the rat small intestine, spleen, and liver. The rats were administered LO at 5 mg/kg (usual therapeutic dose in humans) followed by the screening of differentially expressed genes in the tissues, using a 4×44-K whole-genome rat chip (Agilent microarray platform; Agilent Technologies, Palo Alto, CA, USA) in conjunction with a dye-swap approach, a novelty of this study. Fourteen days after LO treatment and compared with a control group (sham), a total of 156 and 154 up (≧ 1.5-fold)- and down (≦ 0.75-fold)-regulated genes, 174 and 66 up- (≧ 1.5-fold)- and down (≦ 0.75-fold)-regulated genes, and 222 and 322 up- (≧ 1.5-fold)- and down (≦ 0.75-fold)-regulated genes showed differential expression at the mRNA level in the small intestine, spleen and liver, respectively. The reverse transcription-polymerase chain reaction (RT-PCR) validation of highly up- and down-regulated genes confirmed the regulation of the Papd4, Lrp1b, Alb, Cyr61, Cyp2c, and Cxcl1 genes by LO as examples in these tissues. Using bioinformatics, including Ingenuity Pathway Analysis (IPA), differentially expressed genes were functionally categorized by their Gene Ontology (GO) and biological function and network analysis, revealing their diverse functions and potential roles in LO-mediated effects in rat. Further IPA analysis in particular unraveled the presence of novel genes, such as Papd4, Or8k5, Gprc5b, Taar5, Trpc6, Pld2 and Onecut3 (up-regulated top molecules) and Tnf, Slc45a4, Slc25a23 and Samt4 (down-regulated top molecules), to be influenced by LO treatment in the small intestine, spleen and liver, respectively. These results are the first such inventory of genes that are affected by lavender essential oil (LO) in an animal model, forming the basis for further in-depth bioinformatics and functional analyses and investigation. PMID:26161641

A HaemAtlas: characterizing gene expression in differentiated human blood cells.

PubMed

Watkins, Nicholas A; Gusnanto, Arief; de Bono, Bernard; De, Subhajyoti; Miranda-Saavedra, Diego; Hardie, Debbie L; Angenent, Will G J; Attwood, Antony P; Ellis, Peter D; Erber, Wendy; Foad, Nicola S; Garner, Stephen F; Isacke, Clare M; Jolley, Jennifer; Koch, Kerstin; Macaulay, Iain C; Morley, Sarah L; Rendon, Augusto; Rice, Kate M; Taylor, Niall; Thijssen-Timmer, Daphne C; Tijssen, Marloes R; van der Schoot, C Ellen; Wernisch, Lorenz; Winzer, Thilo; Dudbridge, Frank; Buckley, Christopher D; Langford, Cordelia F; Teichmann, Sarah; Göttgens, Berthold; Ouwehand, Willem H

2009-05-07

Hematopoiesis is a carefully controlled process that is regulated by complex networks of transcription factors that are, in part, controlled by signals resulting from ligand binding to cell-surface receptors. To further understand hematopoiesis, we have compared gene expression profiles of human erythroblasts, megakaryocytes, B cells, cytotoxic and helper T cells, natural killer cells, granulocytes, and monocytes using whole genome microarrays. A bioinformatics analysis of these data was performed focusing on transcription factors, immunoglobulin superfamily members, and lineage-specific transcripts. We observed that the numbers of lineage-specific genes varies by 2 orders of magnitude, ranging from 5 for cytotoxic T cells to 878 for granulocytes. In addition, we have identified novel coexpression patterns for key transcription factors involved in hematopoiesis (eg, GATA3-GFI1 and GATA2-KLF1). This study represents the most comprehensive analysis of gene expression in hematopoietic cells to date and has identified genes that play key roles in lineage commitment and cell function. The data, which are freely accessible, will be invaluable for future studies on hematopoiesis and the role of specific genes and will also aid the understanding of the recent genome-wide association studies.

A HaemAtlas: characterizing gene expression in differentiated human blood cells

PubMed Central

Gusnanto, Arief; de Bono, Bernard; De, Subhajyoti; Miranda-Saavedra, Diego; Hardie, Debbie L.; Angenent, Will G. J.; Attwood, Antony P.; Ellis, Peter D.; Erber, Wendy; Foad, Nicola S.; Garner, Stephen F.; Isacke, Clare M.; Jolley, Jennifer; Koch, Kerstin; Macaulay, Iain C.; Morley, Sarah L.; Rendon, Augusto; Rice, Kate M.; Taylor, Niall; Thijssen-Timmer, Daphne C.; Tijssen, Marloes R.; van der Schoot, C. Ellen; Wernisch, Lorenz; Winzer, Thilo; Dudbridge, Frank; Buckley, Christopher D.; Langford, Cordelia F.; Teichmann, Sarah; Göttgens, Berthold; Ouwehand, Willem H.

2009-01-01

Hematopoiesis is a carefully controlled process that is regulated by complex networks of transcription factors that are, in part, controlled by signals resulting from ligand binding to cell-surface receptors. To further understand hematopoiesis, we have compared gene expression profiles of human erythroblasts, megakaryocytes, B cells, cytotoxic and helper T cells, natural killer cells, granulocytes, and monocytes using whole genome microarrays. A bioinformatics analysis of these data was performed focusing on transcription factors, immunoglobulin superfamily members, and lineage-specific transcripts. We observed that the numbers of lineage-specific genes varies by 2 orders of magnitude, ranging from 5 for cytotoxic T cells to 878 for granulocytes. In addition, we have identified novel coexpression patterns for key transcription factors involved in hematopoiesis (eg, GATA3-GFI1 and GATA2-KLF1). This study represents the most comprehensive analysis of gene expression in hematopoietic cells to date and has identified genes that play key roles in lineage commitment and cell function. The data, which are freely accessible, will be invaluable for future studies on hematopoiesis and the role of specific genes and will also aid the understanding of the recent genome-wide association studies. PMID:19228925

Toxicogenomic investigation of Tetrahymena thermophila exposed to dichlorodiphenyltrichloroethane (DDT), tributyltin (TBT), and 2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD).

PubMed

Chang, Yue; Feng, LiFang; Miao, Wei

2011-07-01

Dichlorodiphenyltrichloroethane (DDT), tributyltin (TBT), and 2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD) are persistent in the environment and cause continuous toxic effects in humans and aquatic life. Tetrahymena thermophila has the potential for use as a model for research regarding toxicants. In this study, this organism was used to analyze a genome-wide microarray generated from cells exposed to DDT, TBT and TCDD. To accomplish this, genes differentially expressed when treated with each toxicant were identified, after which their functions were categorized using GO enrichment analysis. The results suggested that the responses of T. thermophila were similar to those of multicellular organisms. Additionally, the context likelihood of relatedness method (CLR) was applied to construct a TCDD-relevant network. The T-shaped network obtained could be functionally divided into two subnetworks. The general functions of both subnetworks were related to the epigenetic mechanism of TCDD. Based on analysis of the networks, a model of the TCDD effect on T. thermophila was inferred. Thus, Tetrahymena has the potential to be a good unicellular eukaryotic model for toxic mechanism research at the genome level.

Microarrays

ERIC Educational Resources Information Center

Plomin, Robert; Schalkwyk, Leonard C.

2007-01-01

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

Association of Protein Translation and Extracellular Matrix Gene Sets with Breast Cancer Metastasis: Findings Uncovered on Analysis of Multiple Publicly Available Datasets Using Individual Patient Data Approach.

PubMed

Chowdhury, Nilotpal; Sapru, Shantanu

2015-01-01

Microarray analysis has revolutionized the role of genomic prognostication in breast cancer. However, most studies are single series studies, and suffer from methodological problems. We sought to use a meta-analytic approach in combining multiple publicly available datasets, while correcting for batch effects, to reach a more robust oncogenomic analysis. The aim of the present study was to find gene sets associated with distant metastasis free survival (DMFS) in systemically untreated, node-negative breast cancer patients, from publicly available genomic microarray datasets. Four microarray series (having 742 patients) were selected after a systematic search and combined. Cox regression for each gene was done for the combined dataset (univariate, as well as multivariate - adjusted for expression of Cell cycle related genes) and for the 4 major molecular subtypes. The centre and microarray batch effects were adjusted by including them as random effects variables. The Cox regression coefficients for each analysis were then ranked and subjected to a Gene Set Enrichment Analysis (GSEA). Gene sets representing protein translation were independently negatively associated with metastasis in the Luminal A and Luminal B subtypes, but positively associated with metastasis in Basal tumors. Proteinaceous extracellular matrix (ECM) gene set expression was positively associated with metastasis, after adjustment for expression of cell cycle related genes on the combined dataset. Finally, the positive association of the proliferation-related genes with metastases was confirmed. To the best of our knowledge, the results depicting mixed prognostic significance of protein translation in breast cancer subtypes are being reported for the first time. We attribute this to our study combining multiple series and performing a more robust meta-analytic Cox regression modeling on the combined dataset, thus discovering 'hidden' associations. This methodology seems to yield new and interesting results and may be used as a tool to guide new research.

Association of Protein Translation and Extracellular Matrix Gene Sets with Breast Cancer Metastasis: Findings Uncovered on Analysis of Multiple Publicly Available Datasets Using Individual Patient Data Approach

PubMed Central

Chowdhury, Nilotpal; Sapru, Shantanu

2015-01-01

Introduction Microarray analysis has revolutionized the role of genomic prognostication in breast cancer. However, most studies are single series studies, and suffer from methodological problems. We sought to use a meta-analytic approach in combining multiple publicly available datasets, while correcting for batch effects, to reach a more robust oncogenomic analysis. Aim The aim of the present study was to find gene sets associated with distant metastasis free survival (DMFS) in systemically untreated, node-negative breast cancer patients, from publicly available genomic microarray datasets. Methods Four microarray series (having 742 patients) were selected after a systematic search and combined. Cox regression for each gene was done for the combined dataset (univariate, as well as multivariate – adjusted for expression of Cell cycle related genes) and for the 4 major molecular subtypes. The centre and microarray batch effects were adjusted by including them as random effects variables. The Cox regression coefficients for each analysis were then ranked and subjected to a Gene Set Enrichment Analysis (GSEA). Results Gene sets representing protein translation were independently negatively associated with metastasis in the Luminal A and Luminal B subtypes, but positively associated with metastasis in Basal tumors. Proteinaceous extracellular matrix (ECM) gene set expression was positively associated with metastasis, after adjustment for expression of cell cycle related genes on the combined dataset. Finally, the positive association of the proliferation-related genes with metastases was confirmed. Conclusion To the best of our knowledge, the results depicting mixed prognostic significance of protein translation in breast cancer subtypes are being reported for the first time. We attribute this to our study combining multiple series and performing a more robust meta-analytic Cox regression modeling on the combined dataset, thus discovering 'hidden' associations. This methodology seems to yield new and interesting results and may be used as a tool to guide new research. PMID:26080057

Widespread anti-sense transcription in apple is correlated with siRNA production and indicates a large potential for transcriptional and/or post-transcriptional control.

PubMed

Celton, Jean-Marc; Gaillard, Sylvain; Bruneau, Maryline; Pelletier, Sandra; Aubourg, Sébastien; Martin-Magniette, Marie-Laure; Navarro, Lionel; Laurens, François; Renou, Jean-Pierre

2014-07-01

Characterizing the transcriptome of eukaryotic organisms is essential for studying gene regulation and its impact on phenotype. The realization that anti-sense (AS) and noncoding RNA transcription is pervasive in many genomes has emphasized our limited understanding of gene transcription and post-transcriptional regulation. Numerous mechanisms including convergent transcription, anti-correlated expression of sense and AS transcripts, and RNAi remain ill-defined. Here, we have combined microarray analysis and high-throughput sequencing of small RNAs (sRNAs) to unravel the complexity of transcriptional and potential post-transcriptional regulation in eight organs of apple (Malus × domestica). The percentage of AS transcript expression is higher than that identified in annual plants such as rice and Arabidopsis thaliana. Furthermore, we show that a majority of AS transcripts are transcribed beyond 3'UTR regions, and may cover a significant portion of the predicted sense transcripts. Finally we demonstrate at a genome-wide scale that anti-sense transcript expression is correlated with the presence of both short (21-23 nt) and long (> 30 nt) siRNAs, and that the sRNA coverage depth varies with the level of AS transcript expression. Our study provides a new insight on the functional role of anti-sense transcripts at the genome-wide level, and a new basis for the understanding of sRNA biogenesis in plants. © 2014 INRA. New Phytologist © 2014 New Phytologist Trust.

Transcriptional profiling of rat skeletal muscle hypertrophy under restriction of blood flow.

PubMed

Xu, Shouyu; Liu, Xueyun; Chen, Zhenhuang; Li, Gaoquan; Chen, Qin; Zhou, Guoqing; Ma, Ruijie; Yao, Xinmiao; Huang, Xiao

2016-12-15

Blood flow restriction (BFR) under low-intensity resistance training (LIRT) can produce similar effects upon muscles to that of high-intensity resistance training (HIRT) while overcoming many of the restrictions to HIRT that occurs in a clinical setting. However, the potential molecular mechanisms of BFR induced muscle hypertrophy remain largely unknown. Here, using a BFR rat model, we aim to better elucidate the mechanisms regulating muscle hypertrophy as induced by BFR and reveal possible clinical therapeutic targets for atrophy cases. We performed genome wide screening with microarray analysis to identify unique differentially expressed genes during rat muscle hypertrophy. We then successfully separated the differentially expressed genes from BRF treated soleus samples by comparing the Affymetrix rat Genome U34 2.0 array with the control. Using qRT-PCR and immunohistochemistry (IHC) we also analyzed other related differentially expressed genes. Results suggested that muscle hypertrophy induced by BFR is essentially regulated by the rate of protein turnover. Specifically, PI3K/AKT and MAPK pathways act as positive regulators in controlling protein synthesis where ubiquitin-proteasome acts as a negative regulator. This represents the first general genome wide level investigation of the gene expression profile in the rat soleus after BFR treatment. This may aid our understanding of the molecular mechanisms regulating and controlling muscle hypertrophy and provide support to the BFR strategies aiming to prevent muscle atrophy in a clinical setting. Copyright © 2016 Elsevier B.V. All rights reserved.

Development of an oligo DNA microarray for the European sea bass and its application to expression profiling of jaw deformity

PubMed Central

2010-01-01

Background The European sea bass (Dicentrarchus labrax) is a marine fish of great importance for fisheries and aquaculture. Functional genomics offers the possibility to discover the molecular mechanisms underlying productive traits in farmed fish, and a step towards the application of marker assisted selection methods in this species. To this end, we report here on the development of an oligo DNA microarray for D. labrax. Results A database consisting of 19,048 unique transcripts was constructed, of which 12,008 (63%) could be annotated by similarity and 4,692 received a GO functional annotation. Two non-overlapping 60mer probes were designed for each unique transcript and in-situ synthesized on glass slides using Agilent SurePrint™ technology. Probe design was positively completed for 19,035 target clusters; the oligo microarray was then applied to profile gene expression in mandibles and whole-heads of fish affected by prognathism, a skeletal malformation that strongly affects sea bass production. Statistical analysis identified 242 transcripts that are significantly down-regulated in deformed individuals compared to normal fish, with a significant enrichment in genes related to nervous system development and functioning. A set of genes spanning a wide dynamic range in gene expression level were selected for quantitative RT-PCR validation. Fold change correlation between microarray and qPCR data was always significant. Conclusions The microarray platform developed for the European sea bass has a high level of flexibility, reliability, and reproducibility. Despite the well known limitations in achieving a proper functional annotation in non-model species, sufficient information was obtained to identify biological processes that are significantly enriched among differentially expressed genes. New insights were obtained on putative mechanisms involved on mandibular prognathism, suggesting that bone/nervous system development might play a role in this phenomenon. PMID:20525278

Detecting novel genes with sparse arrays

PubMed Central

Haiminen, Niina; Smit, Bart; Rautio, Jari; Vitikainen, Marika; Wiebe, Marilyn; Martinez, Diego; Chee, Christine; Kunkel, Joe; Sanchez, Charles; Nelson, Mary Anne; Pakula, Tiina; Saloheimo, Markku; Penttilä, Merja; Kivioja, Teemu

2014-01-01

Species-specific genes play an important role in defining the phenotype of an organism. However, current gene prediction methods can only efficiently find genes that share features such as sequence similarity or general sequence characteristics with previously known genes. Novel sequencing methods and tiling arrays can be used to find genes without prior information and they have demonstrated that novel genes can still be found from extensively studied model organisms. Unfortunately, these methods are expensive and thus are not easily applicable, e.g., to finding genes that are expressed only in very specific conditions. We demonstrate a method for finding novel genes with sparse arrays, applying it on the 33.9 Mb genome of the filamentous fungus Trichoderma reesei. Our computational method does not require normalisations between arrays and it takes into account the multiple-testing problem typical for analysis of microarray data. In contrast to tiling arrays, that use overlapping probes, only one 25mer microarray oligonucleotide probe was used for every 100 b. Thus, only relatively little space on a microarray slide was required to cover the intergenic regions of a genome. The analysis was done as a by-product of a conventional microarray experiment with no additional costs. We found at least 23 good candidates for novel transcripts that could code for proteins and all of which were expressed at high levels. Candidate genes were found to neighbour ire1 and cre1 and many other regulatory genes. Our simple, low-cost method can easily be applied to finding novel species-specific genes without prior knowledge of their sequence properties. PMID:20691772

Using expression genetics to study the neurobiology of ethanol and alcoholism.

PubMed

Farris, Sean P; Wolen, Aaron R; Miles, Michael F

2010-01-01

Recent simultaneous progress in human and animal model genetics and the advent of microarray whole genome expression profiling have produced prodigious data sets on genetic loci, potential candidate genes, and differential gene expression related to alcoholism and ethanol behaviors. Validated target genes or gene networks functioning in alcoholism are still of meager proportions. Genetical genomics, which combines genetic analysis of both traditional phenotypes and whole genome expression data, offers a potential methodology for characterizing brain gene networks functioning in alcoholism. This chapter will describe concepts, approaches, and recent findings in the field of genetical genomics as it applies to alcohol research. Copyright 2010 Elsevier Inc. All rights reserved.

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

PubMed

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

2017-12-01

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

Systemic analysis of genome-wide expression profiles identified potential therapeutic targets of demethylation drugs for glioblastoma.

PubMed

Ning, Tongbo; Cui, Hao; Sun, Feng; Zou, Jidian

2017-09-05

Glioblastoma represents one of the most aggressive malignant brain tumors with high morbidity and motility. Demethylation drugs have been developed for its treatment with little efficacy has been observed. The purpose of this study was to screen therapeutic targets of demethylation drugs or bioactive molecules for glioblastoma through systemic bioinformatics analysis. We firstly downloaded genome-wide expression profiles from the Gene Expression Omnibus (GEO) and conducted the primary analysis through R software, mainly including preprocessing of raw microarray data, transformation between probe ID and gene symbol and identification of differential expression genes (DEGs). Secondly, functional enrichment analysis was conducted via the Database for Annotation, Visualization and Integrated Discovery (DAVID) to explore biological processes involved in the development of glioblastoma. Thirdly, we constructed protein-protein interaction (PPI) network of interested genes and conducted cross analysis for multi datasets to obtain potential therapeutic targets for glioblastoma. Finally, we further confirmed the therapeutic targets through real-time RT-PCR. As a result, biological processes that related to cancer development, amino metabolism, immune response and etc. were found to be significantly enriched in genes that differential expression in glioblastoma and regulated by 5'aza-dC. Besides, network and cross analysis identified ACAT2, UFC1 and CYB5R1 as novel therapeutic targets of demethylation drugs which also confirmed by real time RT-PCR. In conclusions, our study identified several biological processes and genes that involved in the development of glioblastoma and regulated by 5'aza-dC, which would be helpful for the treatment of glioblastoma. Copyright © 2017 Elsevier B.V. All rights reserved.

RNA transcriptional biosignature analysis for identifying febrile infants with serious bacterial infections in the emergency department: a feasibility study.

PubMed

Mahajan, Prashant; Kuppermann, Nathan; Suarez, Nicolas; Mejias, Asuncion; Casper, Charlie; Dean, J Michael; Ramilo, Octavio

2015-01-01

To develop the infrastructure and demonstrate the feasibility of conducting microarray-based RNA transcriptional profile analyses for the diagnosis of serious bacterial infections in febrile infants 60 days and younger in a multicenter pediatric emergency research network. We designed a prospective multicenter cohort study with the aim of enrolling more than 4000 febrile infants 60 days and younger. To ensure success of conducting complex genomic studies in emergency department (ED) settings, we established an infrastructure within the Pediatric Emergency Care Applied Research Network, including 21 sites, to evaluate RNA transcriptional profiles in young febrile infants. We developed a comprehensive manual of operations and trained site investigators to obtain and process blood samples for RNA extraction and genomic analyses. We created standard operating procedures for blood sample collection, processing, storage, shipping, and analyses. We planned to prospectively identify, enroll, and collect 1 mL blood samples for genomic analyses from eligible patients to identify logistical issues with study procedures. Finally, we planned to batch blood samples and determined RNA quantity and quality at the central microarray laboratory and organized data analysis with the Pediatric Emergency Care Applied Research Network data coordinating center. Below we report on establishment of the infrastructure and the feasibility success in the first year based on the enrollment of a limited number of patients. We successfully established the infrastructure at 21 EDs. Over the first 5 months we enrolled 79% (74 of 94) of eligible febrile infants. We were able to obtain and ship 1 mL of blood from 74% (55 of 74) of enrolled participants, with at least 1 sample per participating ED. The 55 samples were shipped and evaluated at the microarray laboratory, and 95% (52 of 55) of blood samples were of adequate quality and contained sufficient RNA for expression analysis. It is possible to create a robust infrastructure to conduct genomic studies in young febrile infants in the context of a multicenter pediatric ED research setting. The sufficient quantity and high quality of RNA obtained suggests that whole blood transcriptional profile analysis for the diagnostic evaluation of young febrile infants can be successfully performed in this setting.

Integrative prescreening in analysis of multiple cancer genomic studies

PubMed Central

2012-01-01

Background In high throughput cancer genomic studies, results from the analysis of single datasets often suffer from a lack of reproducibility because of small sample sizes. Integrative analysis can effectively pool and analyze multiple datasets and provides a cost effective way to improve reproducibility. In integrative analysis, simultaneously analyzing all genes profiled may incur high computational cost. A computationally affordable remedy is prescreening, which fits marginal models, can be conducted in a parallel manner, and has low computational cost. Results An integrative prescreening approach is developed for the analysis of multiple cancer genomic datasets. Simulation shows that the proposed integrative prescreening has better performance than alternatives, particularly including prescreening with individual datasets, an intensity approach and meta-analysis. We also analyze multiple microarray gene profiling studies on liver and pancreatic cancers using the proposed approach. Conclusions The proposed integrative prescreening provides an effective way to reduce the dimensionality in cancer genomic studies. It can be coupled with existing analysis methods to identify cancer markers. PMID:22799431

Gene response profiles for Daphnia pulex exposed to the environmental stressor cadmium reveals novel crustacean metallothioneins.

PubMed

Shaw, Joseph R; Colbourne, John K; Davey, Jennifer C; Glaholt, Stephen P; Hampton, Thomas H; Chen, Celia Y; Folt, Carol L; Hamilton, Joshua W

2007-12-21

Genomic research tools such as microarrays are proving to be important resources to study the complex regulation of genes that respond to environmental perturbations. A first generation cDNA microarray was developed for the environmental indicator species Daphnia pulex, to identify genes whose regulation is modulated following exposure to the metal stressor cadmium. Our experiments revealed interesting changes in gene transcription that suggest their biological roles and their potentially toxicological features in responding to this important environmental contaminant. Our microarray identified genes reported in the literature to be regulated in response to cadmium exposure, suggested functional attributes for genes that share no sequence similarity to proteins in the public databases, and pointed to genes that are likely members of expanded gene families in the Daphnia genome. Genes identified on the microarray also were associated with cadmium induced phenotypes and population-level outcomes that we experimentally determined. A subset of genes regulated in response to cadmium exposure was independently validated using quantitative-realtime (Q-RT)-PCR. These microarray studies led to the discovery of three genes coding for the metal detoxication protein metallothionein (MT). The gene structures and predicted translated sequences of D. pulex MTs clearly place them in this gene family. Yet, they share little homology with previously characterized MTs. The genomic information obtained from this study represents an important first step in characterizing microarray patterns that may be diagnostic to specific environmental contaminants and give insights into their toxicological mechanisms, while also providing a practical tool for evolutionary, ecological, and toxicological functional gene discovery studies. Advances in Daphnia genomics will enable the further development of this species as a model organism for the environmental sciences.

Gene response profiles for Daphnia pulex exposed to the environmental stressor cadmium reveals novel crustacean metallothioneins

PubMed Central

Shaw, Joseph R; Colbourne, John K; Davey, Jennifer C; Glaholt, Stephen P; Hampton, Thomas H; Chen, Celia Y; Folt, Carol L; Hamilton, Joshua W

2007-01-01

Background Genomic research tools such as microarrays are proving to be important resources to study the complex regulation of genes that respond to environmental perturbations. A first generation cDNA microarray was developed for the environmental indicator species Daphnia pulex, to identify genes whose regulation is modulated following exposure to the metal stressor cadmium. Our experiments revealed interesting changes in gene transcription that suggest their biological roles and their potentially toxicological features in responding to this important environmental contaminant. Results Our microarray identified genes reported in the literature to be regulated in response to cadmium exposure, suggested functional attributes for genes that share no sequence similarity to proteins in the public databases, and pointed to genes that are likely members of expanded gene families in the Daphnia genome. Genes identified on the microarray also were associated with cadmium induced phenotypes and population-level outcomes that we experimentally determined. A subset of genes regulated in response to cadmium exposure was independently validated using quantitative-realtime (Q-RT)-PCR. These microarray studies led to the discovery of three genes coding for the metal detoxication protein metallothionein (MT). The gene structures and predicted translated sequences of D. pulex MTs clearly place them in this gene family. Yet, they share little homology with previously characterized MTs. Conclusion The genomic information obtained from this study represents an important first step in characterizing microarray patterns that may be diagnostic to specific environmental contaminants and give insights into their toxicological mechanisms, while also providing a practical tool for evolutionary, ecological, and toxicological functional gene discovery studies. Advances in Daphnia genomics will enable the further development of this species as a model organism for the environmental sciences. PMID:18154678

Genome-wide identification and expression analysis of the B-box gene family in the Apple (Malus domestica Borkh.) genome.

PubMed

Liu, Xin; Li, Rong; Dai, Yaqing; Chen, Xuesen; Wang, Xiaoyun

2018-04-01

The B-box proteins (BBXs) are a family of zinc finger proteins containing one/two B-box domain(s). Compared with intensive studies of animal BBXs, investigations of the plant BBX family are limited, though some specific plant BBXs have been demonstrated to act as transcription factors in the regulation of flowering and photomorphogenesis. In this study, using a global search of the apple (Malus domestica Borkh.) genome, a total of 64 members of BBX (MdBBX) were identified. All the MdBBXs were divided into five groups based on the phylogenetic relationship, numbers of B-boxes contained and whether there was with an additional CCT domain. According to the characteristics of organ-specific expression, MdBBXs were divided into three groups based on the microarray information. An analysis of cis-acting elements showed that elements related to the stress response were prevalent in the promoter sequences of most MdBBXs. Twelve MdBBX members from different groups were randomly selected and exposed to abiotic stresses. Their expressions were up-regulated to some extent in the roots and leaves. Six among 12 MdBBXs were sensitive to osmotic pressure, salt, cold stress and exogenous abscisic acid treatment, with their expressions enhanced more than 20-fold. Our results suggested that MdBBXs may take part in response to abiotic stress.

D-Light on promoters: a client-server system for the analysis and visualization of cis-regulatory elements

PubMed Central

2013-01-01

Background The binding of transcription factors to DNA plays an essential role in the regulation of gene expression. Numerous experiments elucidated binding sequences which subsequently have been used to derive statistical models for predicting potential transcription factor binding sites (TFBS). The rapidly increasing number of genome sequence data requires sophisticated computational approaches to manage and query experimental and predicted TFBS data in the context of other epigenetic factors and across different organisms. Results We have developed D-Light, a novel client-server software package to store and query large amounts of TFBS data for any number of genomes. Users can add small-scale data to the server database and query them in a large scale, genome-wide promoter context. The client is implemented in Java and provides simple graphical user interfaces and data visualization. Here we also performed a statistical analysis showing what a user can expect for certain parameter settings and we illustrate the usage of D-Light with the help of a microarray data set. Conclusions D-Light is an easy to use software tool to integrate, store and query annotation data for promoters. A public D-Light server, the client and server software for local installation and the source code under GNU GPL license are available at http://biwww.che.sbg.ac.at/dlight. PMID:23617301

[Diagnosis of a case with Williams-Beuren syndrome with nephrocalcinosis using chromosome microarray analysis].

PubMed

Jin, S J; Liu, M; Long, W J; Luo, X P

2016-12-02

Objective: To explore the clinical phenotypes and the genetic cause for a boy with unexplained growth retardation, nephrocalcinosis, auditory anomalies and multi-organ/system developmental disorders. Method: Routine G-banding and chromosome microarray analysis were applied to a child with unexplained growth retardation, nephrocalcinosis, auditory anomalies and multi-organ/system developmental disorders treated in the Department of Pediatrics of Tongji Hospital Affiliated to Tongji Medical College of Huazhong University of Science and Technology in September 2015 and his parents to conduct the chromosomal karyotype analysis and the whole genome scanning. Deleted genes were searched in the Decipher and NCBI databases, and their relationships with the clinical phenotypes were analyzed. Result: A six-month-old boy was refered to us because of unexplained growth retardation and feeding intolerance.The affected child presented with abnormal manifestation such as special face, umbilical hernia, growth retardation, hypothyroidism, congenital heart disease, right ear sensorineural deafness, hypercalcemia and nephrocalcinosis. The child's karyotype was 46, XY, 16qh + , and his parents' karyotypes were normal. Chromosome microarray analysis revealed a 1 436 kb deletion on the 7q11.23(72701098_74136633) region of the child. This region included 23 protein-coding genes, which were reported to be corresponding to Williams-Beuren syndrome and its certain clinical phenotypes. His parents' results of chromosome microarray analysis were normal. Conclusion: A boy with characteristic manifestation of Williams-Beuren syndrome and rare nephrocalcinosis was diagnosed using chromosome microarray analysis. The deletion on the 7q11.23 might be related to the clinical phenotypes of Williams-Beuren syndrome, yet further studies are needed.

Transcriptome study of differential expression in schizophrenia

PubMed Central

Sanders, Alan R.; Göring, Harald H. H.; Duan, Jubao; Drigalenko, Eugene I.; Moy, Winton; Freda, Jessica; He, Deli; Shi, Jianxin; Gejman, Pablo V.

2013-01-01

Schizophrenia genome-wide association studies (GWAS) have identified common SNPs, rare copy number variants (CNVs) and a large polygenic contribution to illness risk, but biological mechanisms remain unclear. Bioinformatic analyses of significantly associated genetic variants point to a large role for regulatory variants. To identify gene expression abnormalities in schizophrenia, we generated whole-genome gene expression profiles using microarrays on lymphoblastoid cell lines (LCLs) from 413 cases and 446 controls. Regression analysis identified 95 transcripts differentially expressed by affection status at a genome-wide false discovery rate (FDR) of 0.05, while simultaneously controlling for confounding effects. These transcripts represented 89 genes with functions such as neurotransmission, gene regulation, cell cycle progression, differentiation, apoptosis, microRNA (miRNA) processing and immunity. This functional diversity is consistent with schizophrenia's likely significant pathophysiological heterogeneity. The overall enrichment of immune-related genes among those differentially expressed by affection status is consistent with hypothesized immune contributions to schizophrenia risk. The observed differential expression of extended major histocompatibility complex (xMHC) region histones (HIST1H2BD, HIST1H2BC, HIST1H2BH, HIST1H2BG and HIST1H4K) converges with the genetic evidence from GWAS, which find the xMHC to be the most significant susceptibility locus. Among the differentially expressed immune-related genes, B3GNT2 is implicated in autoimmune disorders previously tied to schizophrenia risk (rheumatoid arthritis and Graves’ disease), and DICER1 is pivotal in miRNA processing potentially linking to miRNA alterations in schizophrenia (e.g. MIR137, the second strongest GWAS finding). Our analysis provides novel candidate genes for further study to assess their potential contribution to schizophrenia. PMID:23904455

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

PubMed Central

Nookaew, Intawat; Papini, Marta; Pornputtapong, Natapol; Scalcinati, Gionata; Fagerberg, Linn; Uhlén, Matthias; Nielsen, Jens

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 with the Illumina platform, and to perform a cross-platform comparison based on the results obtained through Affymetrix microarray. As a case study for our work we, used the Saccharomyces cerevisiae strain CEN.PK 113-7D, grown under two different conditions (batch and chemostat). Here, we asses the influence of genetic variation on the estimation of gene expression level using three different aligners for read-mapping (Gsnap, Stampy and TopHat) on S288c genome, the capabilities of five different statistical methods to detect differential gene expression (baySeq, Cuffdiff, DESeq, edgeR and NOISeq) and we explored 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) for gene expression analysis and addresses the contribution of the different steps involved in the analysis of RNA-seq data. PMID:22965124

Consequences of reductive evolution for gene expression in an obligate endosymbiont.

PubMed

Wilcox, Jennifer L; Dunbar, Helen E; Wolfinger, Russell D; Moran, Nancy A

2003-06-01

The smallest cellular genomes are found in obligate symbiotic and pathogenic bacteria living within eukaryotic hosts. In comparison with large genomes of free-living relatives, these reduced genomes are rearranged and have lost most regulatory elements. To test whether reduced bacterial genomes incur reduced regulatory capacities, we used full-genome microarrays to evaluate transcriptional response to environmental stress in Buchnera aphidicola, the obligate endosymbiont of aphids. The 580 genes of the B. aphidicola genome represent a subset of the 4500 genes known from the related organism, Escherichia coli. Although over 20 orthologues of E. coli heat stress (HS) genes are retained by B. aphidicola, only five were differentially expressed after near-lethal heat stress treatments, and only modest shifts were observed. Analyses of upstream regulatory regions revealed loss or degradation of most HS (sigma32) promoters. Genomic rearrangements downstream of an intact HS promoter yielded upregulation of a functionally unrelated and an inactivated gene. Reanalyses of comparable experimental array data for E. coli and Bacillus subtilis revealed that genome-wide differential expression was significantly lower in B. aphidicola. Our demonstration of a diminished stress response validates reports of temperature sensitivity in B. aphidicola and suggests that this reduced bacterial genome exhibits transcriptional inflexibility.

Identification of hypertension-related genes through an integrated genomic-transcriptomic approach.

PubMed

Yagil, Chana; Hubner, Norbert; Monti, Jan; Schulz, Herbert; Sapojnikov, Marina; Luft, Friedrich C; Ganten, Detlev; Yagil, Yoram

2005-04-01

In search for the genetic basis of hypertension, we applied an integrated genomic-transcriptomic approach to identify genes involved in the pathogenesis of hypertension in the Sabra rat model of salt-susceptibility. In the genomic arm of the project, we previously detected in male rats two salt-susceptibility QTLs on chromosome 1, SS1a (D1Mgh2-D1Mit11; span 43.1 cM) and SS1b (D1Mit11-D1Mit4; span 18 cM). In the transcriptomic arm, we studied differential gene expression in kidneys of SBH/y and SBN/y rats that had been fed regular diet or salt-loaded. We used the Affymetrix Rat Genome RAE230 GeneChip and probed >30,000 transcripts. The research algorithm called for an initial genome-wide screen for differentially expressed transcripts between the study groups. This step was followed by cluster analysis based on 2x2 ANOVA to identify transcripts that were of relevance specifically to salt-sensitivity and hypertension and to salt-resistance. The two arms of the project were integrated by identifying those differentially expressed transcripts that showed an allele-specific hypertensive effect on salt-loading and that mapped within the defined boundaries of the salt-susceptibility QTLs on chromosome 1. The differentially expressed transcripts were confirmed by RT-PCR. Of the 2933 genes annotated to rat chromosome 1, 1102 genes were identified within the boundaries of the two blood pressure QTLs. The microarray identified 2470 transcripts that were differentially expressed between the study groups. Cluster analysis identified genome-wide 192 genes that were relevant to salt-susceptibility and/or hypertension, 19 of which mapped to chromosome 1. Eight of these genes mapped within the boundaries of QTLs SS1a and SS1b. RT-PCR confirmed 7 genes, leaving TcTex1, Myadm, Lisch7, Axl-like, Fah, PRC1-like, and Serpinh1. None of these genes has been implicated in hypertension before. These genes become henceforth targets for our continuing search for the genetic basis of hypertension.

Strand-specific transcriptome profiling with directly labeled RNA on genomic tiling microarrays

PubMed Central

2011-01-01

Background With lower manufacturing cost, high spot density, and flexible probe design, genomic tiling microarrays are ideal for comprehensive transcriptome studies. Typically, transcriptome profiling using microarrays involves reverse transcription, which converts RNA to cDNA. The cDNA is then labeled and hybridized to the probes on the arrays, thus the RNA signals are detected indirectly. Reverse transcription is known to generate artifactual cDNA, in particular the synthesis of second-strand cDNA, leading to false discovery of antisense RNA. To address this issue, we have developed an effective method using RNA that is directly labeled, thus by-passing the cDNA generation. This paper describes this method and its application to the mapping of transcriptome profiles. Results RNA extracted from laboratory cultures of Porphyromonas gingivalis was fluorescently labeled with an alkylation reagent and hybridized directly to probes on genomic tiling microarrays specifically designed for this periodontal pathogen. The generated transcriptome profile was strand-specific and produced signals close to background level in most antisense regions of the genome. In contrast, high levels of signal were detected in the antisense regions when the hybridization was done with cDNA. Five antisense areas were tested with independent strand-specific RT-PCR and none to negligible amplification was detected, indicating that the strong antisense cDNA signals were experimental artifacts. Conclusions An efficient method was developed for mapping transcriptome profiles specific to both coding strands of a bacterial genome. This method chemically labels and uses extracted RNA directly in microarray hybridization. The generated transcriptome profile was free of cDNA artifactual signals. In addition, this method requires fewer processing steps and is potentially more sensitive in detecting small amount of RNA compared to conventional end-labeling methods due to the incorporation of more fluorescent molecules per RNA fragment. PMID:21235785

Pathway Distiller - multisource biological pathway consolidation

PubMed Central

2012-01-01

Background One method to understand and evaluate an experiment that produces a large set of genes, such as a gene expression microarray analysis, is to identify overrepresentation or enrichment for biological pathways. Because pathways are able to functionally describe the set of genes, much effort has been made to collect curated biological pathways into publicly accessible databases. When combining disparate databases, highly related or redundant pathways exist, making their consolidation into pathway concepts essential. This will facilitate unbiased, comprehensive yet streamlined analysis of experiments that result in large gene sets. Methods After gene set enrichment finds representative pathways for large gene sets, pathways are consolidated into representative pathway concepts. Three complementary, but different methods of pathway consolidation are explored. Enrichment Consolidation combines the set of the pathways enriched for the signature gene list through iterative combining of enriched pathways with other pathways with similar signature gene sets; Weighted Consolidation utilizes a Protein-Protein Interaction network based gene-weighting approach that finds clusters of both enriched and non-enriched pathways limited to the experiments' resultant gene list; and finally the de novo Consolidation method uses several measurements of pathway similarity, that finds static pathway clusters independent of any given experiment. Results We demonstrate that the three consolidation methods provide unified yet different functional insights of a resultant gene set derived from a genome-wide profiling experiment. Results from the methods are presented, demonstrating their applications in biological studies and comparing with a pathway web-based framework that also combines several pathway databases. Additionally a web-based consolidation framework that encompasses all three methods discussed in this paper, Pathway Distiller (http://cbbiweb.uthscsa.edu/PathwayDistiller), is established to allow researchers access to the methods and example microarray data described in this manuscript, and the ability to analyze their own gene list by using our unique consolidation methods. Conclusions By combining several pathway systems, implementing different, but complementary pathway consolidation methods, and providing a user-friendly web-accessible tool, we have enabled users the ability to extract functional explanations of their genome wide experiments. PMID:23134636

Pathway Distiller - multisource biological pathway consolidation.

PubMed

Doderer, Mark S; Anguiano, Zachry; Suresh, Uthra; Dashnamoorthy, Ravi; Bishop, Alexander J R; Chen, Yidong

2012-01-01

One method to understand and evaluate an experiment that produces a large set of genes, such as a gene expression microarray analysis, is to identify overrepresentation or enrichment for biological pathways. Because pathways are able to functionally describe the set of genes, much effort has been made to collect curated biological pathways into publicly accessible databases. When combining disparate databases, highly related or redundant pathways exist, making their consolidation into pathway concepts essential. This will facilitate unbiased, comprehensive yet streamlined analysis of experiments that result in large gene sets. After gene set enrichment finds representative pathways for large gene sets, pathways are consolidated into representative pathway concepts. Three complementary, but different methods of pathway consolidation are explored. Enrichment Consolidation combines the set of the pathways enriched for the signature gene list through iterative combining of enriched pathways with other pathways with similar signature gene sets; Weighted Consolidation utilizes a Protein-Protein Interaction network based gene-weighting approach that finds clusters of both enriched and non-enriched pathways limited to the experiments' resultant gene list; and finally the de novo Consolidation method uses several measurements of pathway similarity, that finds static pathway clusters independent of any given experiment. We demonstrate that the three consolidation methods provide unified yet different functional insights of a resultant gene set derived from a genome-wide profiling experiment. Results from the methods are presented, demonstrating their applications in biological studies and comparing with a pathway web-based framework that also combines several pathway databases. Additionally a web-based consolidation framework that encompasses all three methods discussed in this paper, Pathway Distiller (http://cbbiweb.uthscsa.edu/PathwayDistiller), is established to allow researchers access to the methods and example microarray data described in this manuscript, and the ability to analyze their own gene list by using our unique consolidation methods. By combining several pathway systems, implementing different, but complementary pathway consolidation methods, and providing a user-friendly web-accessible tool, we have enabled users the ability to extract functional explanations of their genome wide experiments.

HYPOTHESIS SETTING AND ORDER STATISTIC FOR ROBUST GENOMIC META-ANALYSIS.

PubMed

Song, Chi; Tseng, George C

2014-01-01

Meta-analysis techniques have been widely developed and applied in genomic applications, especially for combining multiple transcriptomic studies. In this paper, we propose an order statistic of p-values ( r th ordered p-value, rOP) across combined studies as the test statistic. We illustrate different hypothesis settings that detect gene markers differentially expressed (DE) "in all studies", "in the majority of studies", or "in one or more studies", and specify rOP as a suitable method for detecting DE genes "in the majority of studies". We develop methods to estimate the parameter r in rOP for real applications. Statistical properties such as its asymptotic behavior and a one-sided testing correction for detecting markers of concordant expression changes are explored. Power calculation and simulation show better performance of rOP compared to classical Fisher's method, Stouffer's method, minimum p-value method and maximum p-value method under the focused hypothesis setting. Theoretically, rOP is found connected to the naïve vote counting method and can be viewed as a generalized form of vote counting with better statistical properties. The method is applied to three microarray meta-analysis examples including major depressive disorder, brain cancer and diabetes. The results demonstrate rOP as a more generalizable, robust and sensitive statistical framework to detect disease-related markers.

Genome-Wide Identification, Characterization and Expression Analysis of the Chalcone Synthase Family in Maize

PubMed Central

Han, Yahui; Ding, Ting; Su, Bo; Jiang, Haiyang

2016-01-01

Members of the chalcone synthase (CHS) family participate in the synthesis of a series of secondary metabolites in plants, fungi and bacteria. The metabolites play important roles in protecting land plants against various environmental stresses during the evolutionary process. Our research was conducted on comprehensive investigation of CHS genes in maize (Zea mays L.), including their phylogenetic relationships, gene structures, chromosomal locations and expression analysis. Fourteen CHS genes (ZmCHS01–14) were identified in the genome of maize, representing one of the largest numbers of CHS family members identified in one organism to date. The gene family was classified into four major classes (classes I–IV) based on their phylogenetic relationships. Most of them contained two exons and one intron. The 14 genes were unevenly located on six chromosomes. Two segmental duplication events were identified, which might contribute to the expansion of the maize CHS gene family to some extent. In addition, quantitative real-time PCR and microarray data analyses suggested that ZmCHS genes exhibited various expression patterns, indicating functional diversification of the ZmCHS genes. Our results will contribute to future studies of the complexity of the CHS gene family in maize and provide valuable information for the systematic analysis of the functions of the CHS gene family. PMID:26828478

Basic leucine zipper family in barley: genome-wide characterization of members and expression analysis.

PubMed

Pourabed, Ehsan; Ghane Golmohamadi, Farzan; Soleymani Monfared, Peyman; Razavi, Seyed Morteza; Shobbar, Zahra-Sadat

2015-01-01

The basic leucine zipper (bZIP) family is one of the largest and most diverse transcription factors in eukaryotes participating in many essential plant processes. We identified 141 bZIP proteins encoded by 89 genes from the Hordeum vulgare genome. HvbZIPs were classified into 11 groups based on their DNA-binding motif. Amino acid sequence alignment of the HvbZIPs basic-hinge regions revealed some highly conserved residues within each group. The leucine zipper heptads were analyzed predicting their dimerization properties. 34 conserved motifs were identified outside the bZIP domain. Phylogenetic analysis indicated that major diversification within the bZIP family predated the monocot/dicot divergence, although intra-species duplication and parallel evolution seems to be occurred afterward. Localization of HvbZIPs on the barley chromosomes revealed that different groups have been distributed on seven chromosomes of barley. Six types of intron pattern were detected within the basic-hinge regions. Most of the detected cis-elements in the promoter and UTR sequences were involved in seed development or abiotic stress response. Microarray data analysis revealed differential expression pattern of HvbZIPs in response to ABA treatment, drought, and cold stresses and during barley grain development and germination. This information would be helpful for functional characterization of bZIP transcription factors in barley.

Impairment of organ-specific T cell negative selection by diabetes susceptibility genes: genomic analysis by mRNA profiling.

PubMed

Liston, Adrian; Hardy, Kristine; Pittelkow, Yvonne; Wilson, Susan R; Makaroff, Lydia E; Fahrer, Aude M; Goodnow, Christopher C

2007-01-01

T cells in the thymus undergo opposing positive and negative selection processes so that the only T cells entering circulation are those bearing a T cell receptor (TCR) with a low affinity for self. The mechanism differentiating negative from positive selection is poorly understood, despite the fact that inherited defects in negative selection underlie organ-specific autoimmune disease in AIRE-deficient people and the non-obese diabetic (NOD) mouse strain Here we use homogeneous populations of T cells undergoing either positive or negative selection in vivo together with genome-wide transcription profiling on microarrays to identify the gene expression differences underlying negative selection to an Aire-dependent organ-specific antigen, including the upregulation of a genomic cluster in the cytogenetic band 2F. Analysis of defective negative selection in the autoimmune-prone NOD strain demonstrates a global impairment in the induction of the negative selection response gene set, but little difference in positive selection response genes. Combining expression differences with genetic linkage data, we identify differentially expressed candidate genes, including Bim, Bnip3, Smox, Pdrg1, Id1, Pdcd1, Ly6c, Pdia3, Trim30 and Trim12. The data provide a molecular map of the negative selection response in vivo and, by analysis of deviations from this pathway in the autoimmune susceptible NOD strain, suggest that susceptibility arises from small expression differences in genes acting at multiple points in the pathway between the TCR and cell death.

Impairment of organ-specific T cell negative selection by diabetes susceptibility genes: genomic analysis by mRNA profiling

PubMed Central

Liston, Adrian; Hardy, Kristine; Pittelkow, Yvonne; Wilson, Susan R; Makaroff, Lydia E; Fahrer, Aude M; Goodnow, Christopher C

2007-01-01

Background T cells in the thymus undergo opposing positive and negative selection processes so that the only T cells entering circulation are those bearing a T cell receptor (TCR) with a low affinity for self. The mechanism differentiating negative from positive selection is poorly understood, despite the fact that inherited defects in negative selection underlie organ-specific autoimmune disease in AIRE-deficient people and the non-obese diabetic (NOD) mouse strain Results Here we use homogeneous populations of T cells undergoing either positive or negative selection in vivo together with genome-wide transcription profiling on microarrays to identify the gene expression differences underlying negative selection to an Aire-dependent organ-specific antigen, including the upregulation of a genomic cluster in the cytogenetic band 2F. Analysis of defective negative selection in the autoimmune-prone NOD strain demonstrates a global impairment in the induction of the negative selection response gene set, but little difference in positive selection response genes. Combining expression differences with genetic linkage data, we identify differentially expressed candidate genes, including Bim, Bnip3, Smox, Pdrg1, Id1, Pdcd1, Ly6c, Pdia3, Trim30 and Trim12. Conclusion The data provide a molecular map of the negative selection response in vivo and, by analysis of deviations from this pathway in the autoimmune susceptible NOD strain, suggest that susceptibility arises from small expression differences in genes acting at multiple points in the pathway between the TCR and cell death. PMID:17239257

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

PubMed

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 highly adaptable, integrative, yet flexible tool which can be used for automated quality control, analysis, annotation and visualization of microarray data, constituting a starting point for further data interpretation and integration with numerous other tools.

Improved microarray methods for profiling the yeast knockout strain collection

PubMed Central

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

2005-01-01

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

Imputation-Based Genomic Coverage Assessments of Current Human Genotyping Arrays

PubMed Central

Nelson, Sarah C.; Doheny, Kimberly F.; Pugh, Elizabeth W.; Romm, Jane M.; Ling, Hua; Laurie, Cecelia A.; Browning, Sharon R.; Weir, Bruce S.; Laurie, Cathy C.

2013-01-01

Microarray single-nucleotide polymorphism genotyping, combined with imputation of untyped variants, has been widely adopted as an efficient means to interrogate variation across the human genome. “Genomic coverage” is the total proportion of genomic variation captured by an array, either by direct observation or through an indirect means such as linkage disequilibrium or imputation. We have performed imputation-based genomic coverage assessments of eight current genotyping arrays that assay from ~0.3 to ~5 million variants. Coverage was determined separately in each of the four continental ancestry groups in the 1000 Genomes Project phase 1 release. We used the subset of 1000 Genomes variants present on each array to impute the remaining variants and assessed coverage based on correlation between imputed and observed allelic dosages. More than 75% of common variants (minor allele frequency > 0.05) are covered by all arrays in all groups except for African ancestry, and up to ~90% in all ancestries for the highest density arrays. In contrast, less than 40% of less common variants (0.01 < minor allele frequency < 0.05) are covered by low density arrays in all ancestries and 50–80% in high density arrays, depending on ancestry. We also calculated genome-wide power to detect variant-trait association in a case-control design, across varying sample sizes, effect sizes, and minor allele frequency ranges, and compare these array-based power estimates with a hypothetical array that would type all variants in 1000 Genomes. These imputation-based genomic coverage and power analyses are intended as a practical guide to researchers planning genetic studies. PMID:23979933

A Human Lectin Microarray for Sperm Surface Glycosylation Analysis *

PubMed Central

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

2016-01-01

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

NAHR-mediated copy-number variants in a clinical population: mechanistic insights into both genomic disorders and Mendelizing traits.

PubMed

Dittwald, Piotr; Gambin, Tomasz; Szafranski, Przemyslaw; Li, Jian; Amato, Stephen; Divon, Michael Y; Rodríguez Rojas, Lisa Ximena; Elton, Lindsay E; Scott, Daryl A; Schaaf, Christian P; Torres-Martinez, Wilfredo; Stevens, Abby K; Rosenfeld, Jill A; Agadi, Satish; Francis, David; Kang, Sung-Hae L; Breman, Amy; Lalani, Seema R; Bacino, Carlos A; Bi, Weimin; Milosavljevic, Aleksandar; Beaudet, Arthur L; Patel, Ankita; Shaw, Chad A; Lupski, James R; Gambin, Anna; Cheung, Sau Wai; Stankiewicz, Pawel

2013-09-01

We delineated and analyzed directly oriented paralogous low-copy repeats (DP-LCRs) in the most recent version of the human haploid reference genome. The computationally defined DP-LCRs were cross-referenced with our chromosomal microarray analysis (CMA) database of 25,144 patients subjected to genome-wide assays. This computationally guided approach to the empirically derived large data set allowed us to investigate genomic rearrangement relative frequencies and identify new loci for recurrent nonallelic homologous recombination (NAHR)-mediated copy-number variants (CNVs). The most commonly observed recurrent CNVs were NPHP1 duplications (233), CHRNA7 duplications (175), and 22q11.21 deletions (DiGeorge/velocardiofacial syndrome, 166). In the ∼25% of CMA cases for which parental studies were available, we identified 190 de novo recurrent CNVs. In this group, the most frequently observed events were deletions of 22q11.21 (48), 16p11.2 (autism, 34), and 7q11.23 (Williams-Beuren syndrome, 11). Several features of DP-LCRs, including length, distance between NAHR substrate elements, DNA sequence identity (fraction matching), GC content, and concentration of the homologous recombination (HR) hot spot motif 5'-CCNCCNTNNCCNC-3', correlate with the frequencies of the recurrent CNVs events. Four novel adjacent DP-LCR-flanked and NAHR-prone regions, involving 2q12.2q13, were elucidated in association with novel genomic disorders. Our study quantitates genome architectural features responsible for NAHR-mediated genomic instability and further elucidates the role of NAHR in human disease.

Removing technical variability in RNA-seq data using conditional quantile normalization.

PubMed

Hansen, Kasper D; Irizarry, Rafael A; Wu, Zhijin

2012-04-01

The ability to measure gene expression on a genome-wide scale is one of the most promising accomplishments in molecular biology. Microarrays, the technology that first permitted this, were riddled with problems due to unwanted sources of variability. Many of these problems are now mitigated, after a decade's worth of statistical methodology development. The recently developed RNA sequencing (RNA-seq) technology has generated much excitement in part due to claims of reduced variability in comparison to microarrays. However, we show that RNA-seq data demonstrate unwanted and obscuring variability similar to what was first observed in microarrays. In particular, we find guanine-cytosine content (GC-content) has a strong sample-specific effect on gene expression measurements that, if left uncorrected, leads to false positives in downstream results. We also report on commonly observed data distortions that demonstrate the need for data normalization. Here, we describe a statistical methodology that improves precision by 42% without loss of accuracy. Our resulting conditional quantile normalization algorithm combines robust generalized regression to remove systematic bias introduced by deterministic features such as GC-content and quantile normalization to correct for global distortions.

Gene expression analysis of a porcine hepatocyte/bile duct in vitro differentiaion model

USDA-ARS?s Scientific Manuscript database

A serum-free, feeder-cell-dependent, inductive differentiation culture system of porcine hepatocytes and bile ductules was analyzed for differential gene expression on a porcine genome microarray. Primary cultures of baby pig hepatocytes (BPH) were matured in culture as a monolayer of hepatocytes w...

Cancer diagnosis marker extraction for soft tissue sarcomas based on gene expression profiling data by using projective adaptive resonance theory (PART) filtering method

PubMed Central

Takahashi, Hiro; Nemoto, Takeshi; Yoshida, Teruhiko; Honda, Hiroyuki; Hasegawa, Tadashi

2006-01-01

Background Recent advances in genome technologies have provided an excellent opportunity to determine the complete biological characteristics of neoplastic tissues, resulting in improved diagnosis and selection of treatment. To accomplish this objective, it is important to establish a sophisticated algorithm that can deal with large quantities of data such as gene expression profiles obtained by DNA microarray analysis. Results Previously, we developed the projective adaptive resonance theory (PART) filtering method as a gene filtering method. This is one of the clustering methods that can select specific genes for each subtype. In this study, we applied the PART filtering method to analyze microarray data that were obtained from soft tissue sarcoma (STS) patients for the extraction of subtype-specific genes. The performance of the filtering method was evaluated by comparison with other widely used methods, such as signal-to-noise, significance analysis of microarrays, and nearest shrunken centroids. In addition, various combinations of filtering and modeling methods were used to extract essential subtype-specific genes. The combination of the PART filtering method and boosting – the PART-BFCS method – showed the highest accuracy. Seven genes among the 15 genes that are frequently selected by this method – MIF, CYFIP2, HSPCB, TIMP3, LDHA, ABR, and RGS3 – are known prognostic marker genes for other tumors. These genes are candidate marker genes for the diagnosis of STS. Correlation analysis was performed to extract marker genes that were not selected by PART-BFCS. Sixteen genes among those extracted are also known prognostic marker genes for other tumors, and they could be candidate marker genes for the diagnosis of STS. Conclusion The procedure that consisted of two steps, such as the PART-BFCS and the correlation analysis, was proposed. The results suggest that novel diagnostic and therapeutic targets for STS can be extracted by a procedure that includes the PART filtering method. PMID:16948864

WholePathwayScope: a comprehensive pathway-based analysis tool for high-throughput data

PubMed Central

Yi, Ming; Horton, Jay D; Cohen, Jonathan C; Hobbs, Helen H; Stephens, Robert M

2006-01-01

Background Analysis of High Throughput (HTP) Data such as microarray and proteomics data has provided a powerful methodology to study patterns of gene regulation at genome scale. A major unresolved problem in the post-genomic era is to assemble the large amounts of data generated into a meaningful biological context. We have developed a comprehensive software tool, WholePathwayScope (WPS), for deriving biological insights from analysis of HTP data. Result WPS extracts gene lists with shared biological themes through color cue templates. WPS statistically evaluates global functional category enrichment of gene lists and pathway-level pattern enrichment of data. WPS incorporates well-known biological pathways from KEGG (Kyoto Encyclopedia of Genes and Genomes) and Biocarta, GO (Gene Ontology) terms as well as user-defined pathways or relevant gene clusters or groups, and explores gene-term relationships within the derived gene-term association networks (GTANs). WPS simultaneously compares multiple datasets within biological contexts either as pathways or as association networks. WPS also integrates Genetic Association Database and Partial MedGene Database for disease-association information. We have used this program to analyze and compare microarray and proteomics datasets derived from a variety of biological systems. Application examples demonstrated the capacity of WPS to significantly facilitate the analysis of HTP data for integrative discovery. Conclusion This tool represents a pathway-based platform for discovery integration to maximize analysis power. The tool is freely available at . PMID:16423281

Prediction of gene expression in embryonic structures of Drosophila melanogaster.

PubMed

Samsonova, Anastasia A; Niranjan, Mahesan; Russell, Steven; Brazma, Alvis

2007-07-01

Understanding how sets of genes are coordinately regulated in space and time to generate the diversity of cell types that characterise complex metazoans is a major challenge in modern biology. The use of high-throughput approaches, such as large-scale in situ hybridisation and genome-wide expression profiling via DNA microarrays, is beginning to provide insights into the complexities of development. However, in many organisms the collection and annotation of comprehensive in situ localisation data is a difficult and time-consuming task. Here, we present a widely applicable computational approach, integrating developmental time-course microarray data with annotated in situ hybridisation studies, that facilitates the de novo prediction of tissue-specific expression for genes that have no in vivo gene expression localisation data available. Using a classification approach, trained with data from microarray and in situ hybridisation studies of gene expression during Drosophila embryonic development, we made a set of predictions on the tissue-specific expression of Drosophila genes that have not been systematically characterised by in situ hybridisation experiments. The reliability of our predictions is confirmed by literature-derived annotations in FlyBase, by overrepresentation of Gene Ontology biological process annotations, and, in a selected set, by detailed gene-specific studies from the literature. Our novel organism-independent method will be of considerable utility in enriching the annotation of gene function and expression in complex multicellular organisms.

Prediction of Gene Expression in Embryonic Structures of Drosophila melanogaster

PubMed Central

Samsonova, Anastasia A; Niranjan, Mahesan; Russell, Steven; Brazma, Alvis

2007-01-01

Understanding how sets of genes are coordinately regulated in space and time to generate the diversity of cell types that characterise complex metazoans is a major challenge in modern biology. The use of high-throughput approaches, such as large-scale in situ hybridisation and genome-wide expression profiling via DNA microarrays, is beginning to provide insights into the complexities of development. However, in many organisms the collection and annotation of comprehensive in situ localisation data is a difficult and time-consuming task. Here, we present a widely applicable computational approach, integrating developmental time-course microarray data with annotated in situ hybridisation studies, that facilitates the de novo prediction of tissue-specific expression for genes that have no in vivo gene expression localisation data available. Using a classification approach, trained with data from microarray and in situ hybridisation studies of gene expression during Drosophila embryonic development, we made a set of predictions on the tissue-specific expression of Drosophila genes that have not been systematically characterised by in situ hybridisation experiments. The reliability of our predictions is confirmed by literature-derived annotations in FlyBase, by overrepresentation of Gene Ontology biological process annotations, and, in a selected set, by detailed gene-specific studies from the literature. Our novel organism-independent method will be of considerable utility in enriching the annotation of gene function and expression in complex multicellular organisms. PMID:17658945

Genome-wide methylation analysis identifies a core set of hypermethylated genes in CIMP-H colorectal cancer.

PubMed

McInnes, Tyler; Zou, Donghui; Rao, Dasari S; Munro, Francesca M; Phillips, Vicky L; McCall, John L; Black, Michael A; Reeve, Anthony E; Guilford, Parry J

2017-03-28

Aberrant DNA methylation profiles are a characteristic of all known cancer types, epitomized by the CpG island methylator phenotype (CIMP) in colorectal cancer (CRC). Hypermethylation has been observed at CpG islands throughout the genome, but it is unclear which factors determine whether an individual island becomes methylated in cancer. DNA methylation in CRC was analysed using the Illumina HumanMethylation450K array. Differentially methylated loci were identified using Significance Analysis of Microarrays (SAM) and the Wilcoxon Signed Rank (WSR) test. Unsupervised hierarchical clustering was used to identify methylation subtypes in CRC. In this study we characterized the DNA methylation profiles of 94 CRC tissues and their matched normal counterparts. Consistent with previous studies, unsupervized hierarchical clustering of genome-wide methylation data identified three subtypes within the tumour samples, designated CIMP-H, CIMP-L and CIMP-N, that showed high, low and very low methylation levels, respectively. Differential methylation between normal and tumour samples was analysed at the individual CpG level, and at the gene level. The distribution of hypermethylation in CIMP-N tumours showed high inter-tumour variability and appeared to be highly stochastic in nature, whereas CIMP-H tumours exhibited consistent hypermethylation at a subset of genes, in addition to a highly variable background of hypermethylated genes. EYA4, TFPI2 and TLX1 were hypermethylated in more than 90% of all tumours examined. One-hundred thirty-two genes were hypermethylated in 100% of CIMP-H tumours studied and these were highly enriched for functions relating to skeletal system development (Bonferroni adjusted p value =2.88E-15), segment specification (adjusted p value =9.62E-11), embryonic development (adjusted p value =1.52E-04), mesoderm development (adjusted p value =1.14E-20), and ectoderm development (adjusted p value =7.94E-16). Our genome-wide characterization of DNA methylation in colorectal cancer has identified 132 genes hypermethylated in 100% of CIMP-H samples. Three genes, EYA4, TLX1 and TFPI2 are hypermethylated in >90% of all tumour samples, regardless of CIMP subtype.

Heterologous oligonucleotide microarrays for transcriptomics in a non-model species; a proof-of-concept study of drought stress in Musa

PubMed Central

Davey, Mark W; Graham, Neil S; Vanholme, Bartel; Swennen, Rony; May, Sean T; Keulemans, Johan

2009-01-01

Background 'Systems-wide' approaches such as microarray RNA-profiling are ideally suited to the study of the complex overlapping responses of plants to biotic and abiotic stresses. However, commercial microarrays are only available for a limited number of plant species and development costs are so substantial as to be prohibitive for most research groups. Here we evaluate the use of cross-hybridisation to Affymetrix oligonucleotide GeneChip® microarrays to profile the response of the banana (Musa spp.) leaf transcriptome to drought stress using a genomic DNA (gDNA)-based probe-selection strategy to improve the efficiency of detection of differentially expressed Musa transcripts. Results Following cross-hybridisation of Musa gDNA to the Rice GeneChip® Genome Array, ~33,700 gene-specific probe-sets had a sufficiently high degree of homology to be retained for transcriptomic analyses. In a proof-of-concept approach, pooled RNA representing a single biological replicate of control and drought stressed leaves of the Musa cultivar 'Cachaco' were hybridised to the Affymetrix Rice Genome Array. A total of 2,910 Musa gene homologues with a >2-fold difference in expression levels were subsequently identified. These drought-responsive transcripts included many functional classes associated with plant biotic and abiotic stress responses, as well as a range of regulatory genes known to be involved in coordinating abiotic stress responses. This latter group included members of the ERF, DREB, MYB, bZIP and bHLH transcription factor families. Fifty-two of these drought-sensitive Musa transcripts were homologous to genes underlying QTLs for drought and cold tolerance in rice, including in 2 instances QTLs associated with a single underlying gene. The list of drought-responsive transcripts also included genes identified in publicly-available comparative transcriptomics experiments. Conclusion Our results demonstrate that despite the general paucity of nucleotide sequence data in Musa and only distant phylogenetic relations to rice, gDNA probe-based cross-hybridisation to the Rice GeneChip® is a highly promising strategy to study complex biological responses and illustrates the potential of such strategies for gene discovery in non-model species. PMID:19758430

Validation of isoleucine utilization targets in Plasmodium falciparum

PubMed Central

Istvan, Eva S.; Dharia, Neekesh V.; Bopp, Selina E.; Gluzman, Ilya; Winzeler, Elizabeth A.; Goldberg, Daniel E.

2011-01-01

Intraerythrocytic malaria parasites can obtain nearly their entire amino acid requirement by degrading host cell hemoglobin. The sole exception is isoleucine, which is not present in adult human hemoglobin and must be obtained exogenously. We evaluated two compounds for their potential to interfere with isoleucine utilization. Mupirocin, a clinically used antibacterial, kills Plasmodium falciparum parasites at nanomolar concentrations. Thiaisoleucine, an isoleucine analog, also has antimalarial activity. To identify targets of the two compounds, we selected parasites resistant to either mupirocin or thiaisoleucine. Mutants were analyzed by genome-wide high-density tiling microarrays, DNA sequencing, and copy number variation analysis. The genomes of three independent mupirocin-resistant parasite clones had all acquired either amplifications encompassing or SNPs within the chromosomally encoded organellar (apicoplast) isoleucyl-tRNA synthetase. Thiaisoleucine-resistant parasites had a mutation in the cytoplasmic isoleucyl-tRNA synthetase. The role of this mutation in thiaisoleucine resistance was confirmed by allelic replacement. This approach is generally useful for elucidation of new targets in P. falciparum. Our study shows that isoleucine utilization is an essential pathway that can be targeted for antimalarial drug development. PMID:21205898

Genome-wide analysis of coordinated transcript abundance during seed development in different Brassica rapa morphotypes.

PubMed

Basnet, Ram Kumar; Moreno-Pachon, Natalia; Lin, Ke; Bucher, Johan; Visser, Richard G F; Maliepaard, Chris; Bonnema, Guusje

2013-12-01

Brassica seeds are important as basic units of plant growth and sources of vegetable oil. Seed development is regulated by many dynamic metabolic processes controlled by complex networks of spatially and temporally expressed genes. We conducted a global microarray gene co-expression analysis by measuring transcript abundance of developing seeds from two diverse B. rapa morphotypes: a pak choi (leafy-type) and a yellow sarson (oil-type), and two of their doubled haploid (DH) progenies, (1) to study the timing of metabolic processes in developing seeds, (2) to explore the major transcriptional differences in developing seeds of the two morphotypes, and (3) to identify the optimum stage for a genetical genomics study in B. rapa seed. Seed developmental stages were similar in developing seeds of pak choi and yellow sarson of B. rapa; however, the colour of embryo and seed coat differed among these two morphotypes. In this study, most transcriptional changes occurred between 25 and 35 DAP, which shows that the timing of seed developmental processes in B. rapa is at later developmental stages than in the related species B. napus. Using a Weighted Gene Co-expression Network Analysis (WGCNA), we identified 47 "gene modules", of which 27 showed a significant association with temporal and/or genotypic variation. An additional hierarchical cluster analysis identified broad spectra of gene expression patterns during seed development. The predominant variation in gene expression was according to developmental stages rather than morphotype differences. Since lipids are the major storage compounds of Brassica seeds, we investigated in more detail the regulation of lipid metabolism. Four co-regulated gene clusters were identified with 17 putative cis-regulatory elements predicted in their 1000 bp upstream region, either specific or common to different lipid metabolic pathways. This is the first study of genome-wide profiling of transcript abundance during seed development in B. rapa. The identification of key physiological events, major expression patterns, and putative cis-regulatory elements provides useful information to construct gene regulatory networks in B. rapa developing seeds and provides a starting point for a genetical genomics study of seed quality traits.

Employing image processing techniques for cancer detection using microarray images.

PubMed

Dehghan Khalilabad, Nastaran; Hassanpour, Hamid

2017-02-01

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

Manufacturing of microarrays.

PubMed

Petersen, David W; Kawasaki, Ernest S

2007-01-01

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

A genome-scale map of expression for a mouse brain section obtained using voxelation

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

Chin, Mark H.; Geng, Alex B.; Khan, Arshad H.

Gene expression signatures in the mammalian brain hold the key to understanding neural development and neurological diseases. We have reconstructed 2- dimensional images of gene expression for 20,000 genes in a coronal slice of the mouse brain at the level of the striatum by using microarrays in combination with voxelation at a resolution of 1 mm3. Good reliability of the microarray results were confirmed using multiple replicates, subsequent quantitative RT-PCR voxelation, mass spectrometry voxelation and publicly available in situ hybridization data. Known and novel genes were identified with expression patterns localized to defined substructures within the brain. In addition, genesmore » with unexpected patterns were identified and cluster analysis identified a set of genes with a gradient of dorsal/ventral expression not restricted to known anatomical boundaries. The genome-scale maps of gene expression obtained using voxelation will be a valuable tool for the neuroscience community.« less

Taking the First Steps towards a Standard for Reporting on Phylogenies: Minimal Information about a Phylogenetic Analysis (MIAPA)

PubMed Central

LEEBENS-MACK, JIM; VISION, TODD; BRENNER, ERIC; BOWERS, JOHN E.; CANNON, STEVEN; CLEMENT, MARK J.; CUNNINGHAM, CLIFFORD W.; dePAMPHILIS, CLAUDE; deSALLE, ROB; DOYLE, JEFF J.; EISEN, JONATHAN A.; GU, XUN; HARSHMAN, JOHN; JANSEN, ROBERT K.; KELLOGG, ELIZABETH A.; KOONIN, EUGENE V.; MISHLER, BRENT D.; PHILIPPE, HERVÉ; PIRES, J. CHRIS; QIU, YIN-LONG; RHEE, SEUNG Y.; SJÖLANDER, KIMMEN; SOLTIS, DOUGLAS E.; SOLTIS, PAMELA S.; STEVENSON, DENNIS W.; WALL, KERR; WARNOW, TANDY; ZMASEK, CHRISTIAN

2011-01-01

In the eight years since phylogenomics was introduced as the intersection of genomics and phylogenetics, the field has provided fundamental insights into gene function, genome history and organismal relationships. The utility of phylogenomics is growing with the increase in the number and diversity of taxa for which whole genome and large transcriptome sequence sets are being generated. We assert that the synergy between genomic and phylogenetic perspectives in comparative biology would be enhanced by the development and refinement of minimal reporting standards for phylogenetic analyses. Encouraged by the development of the Minimum Information About a Microarray Experiment (MIAME) standard, we propose a similar roadmap for the development of a Minimal Information About a Phylogenetic Analysis (MIAPA) standard. Key in the successful development and implementation of such a standard will be broad participation by developers of phylogenetic analysis software, phylogenetic database developers, practitioners of phylogenomics, and journal editors. PMID:16901231

Microarray expression profiling and co-expression network analysis of circulating LncRNAs and mRNAs associated with neurotoxicity induced by BPA.

PubMed

Pang, Wei; Lian, Fu-Zhi; Leng, Xue; Wang, Shu-Min; Li, Yi-Bo; Wang, Zi-Yu; Li, Kai-Ren; Gao, Zhi-Xian; Jiang, Yu-Gang

2018-05-01

A growing body of evidence has shown bisphenol A (BPA), an estrogen-like industrial chemical, has adverse effects on the nervous system. In this study, we investigated the transcriptional behavior of long non-coding RNAs (lncRNAs) and mRNAs to provide the information to explore neurotoxic effects induced by BPA. By microarray expression profiling, we discovered 151 differentially expressed lncRNAs and 794 differentially expressed mRNAs in the BPA intervention group compared with the control group. Gene ontology analysis indicated the differentially expressed mRNAs were mainly involved in fundamental metabolic processes and physiological and pathological conditions, such as development, synaptic transmission, homeostasis, injury, and neuroinflammation responses. In the expression network of the BPA-induced group, a great number of nodes and connections were found in comparison to the control-derived network. We identified lncRNAs that were aberrantly expressed in the BPA group, among which, growth arrest specific 5 (GAS5) might participate in the BPA-induced neurotoxicity by regulating Jun, RAS, and other pathways indirectly through these differentially expressed genes. This study provides the first investigation of genome-wide lncRNA expression and correlation between lncRNA and mRNA expression in the BPA-induced neurotoxicity. Our results suggest that the elevated expression of lncRNAs is a major biomarker in the neurotoxicity induced by BPA.

Genome-Wide Gene Expression Analysis Shows AKAP13-Mediated PKD1 Signaling Regulates the Transcriptional Response to Cardiac Hypertrophy.

PubMed

Johnson, Keven R; Nicodemus-Johnson, Jessie; Spindler, Mathew J; Carnegie, Graeme K

2015-01-01

In the heart, scaffolding proteins such as A-Kinase Anchoring Proteins (AKAPs) play a crucial role in normal cellular function by serving as a signaling hub for multiple protein kinases including protein kinase D1 (PKD1). Under cardiac hypertrophic conditions AKAP13 anchored PKD1 activates the transcription factor MEF2 leading to subsequent fetal gene activation and hypertrophic response. We used an expression microarray to identify the global transcriptional response in the hearts of wild-type mice expressing the native form of AKAP13 compared to a gene-trap mouse model expressing a truncated form of AKAP13 that is unable to bind PKD1 (AKAP13-ΔPKD1). Microarray analysis showed that AKAP13-ΔPKD1 mice broadly failed to exhibit the transcriptional profile normally associated with compensatory cardiac hypertrophy following trans-aortic constriction (TAC). The identified differentially expressed genes in WT and AKAP13-ΔPKD1 hearts are vital for the compensatory hypertrophic response to pressure-overload and include myofilament, apoptotic, and cell growth/differentiation genes in addition to genes not previously identified as affected by AKAP13-anchored PKD1. Our results show that AKAP13-PKD1 signaling is critical for transcriptional regulation of key contractile, cell death, and metabolic pathways during the development of compensatory hypertrophy in vivo.

Genome-Wide Gene Expression Analysis Shows AKAP13-Mediated PKD1 Signaling Regulates the Transcriptional Response to Cardiac Hypertrophy

PubMed Central

Johnson, Keven R.; Nicodemus-Johnson, Jessie; Spindler, Mathew J.

2015-01-01

In the heart, scaffolding proteins such as A-Kinase Anchoring Proteins (AKAPs) play a crucial role in normal cellular function by serving as a signaling hub for multiple protein kinases including protein kinase D1 (PKD1). Under cardiac hypertrophic conditions AKAP13 anchored PKD1 activates the transcription factor MEF2 leading to subsequent fetal gene activation and hypertrophic response. We used an expression microarray to identify the global transcriptional response in the hearts of wild-type mice expressing the native form of AKAP13 compared to a gene-trap mouse model expressing a truncated form of AKAP13 that is unable to bind PKD1 (AKAP13-ΔPKD1). Microarray analysis showed that AKAP13-ΔPKD1 mice broadly failed to exhibit the transcriptional profile normally associated with compensatory cardiac hypertrophy following trans-aortic constriction (TAC). The identified differentially expressed genes in WT and AKAP13-ΔPKD1 hearts are vital for the compensatory hypertrophic response to pressure-overload and include myofilament, apoptotic, and cell growth/differentiation genes in addition to genes not previously identified as affected by AKAP13-anchored PKD1. Our results show that AKAP13-PKD1 signaling is critical for transcriptional regulation of key contractile, cell death, and metabolic pathways during the development of compensatory hypertrophy in vivo. PMID:26192751

Genome-wide direct target analysis reveals a role for SHORT-ROOT in root vascular patterning through cytokinin homeostasis.

PubMed

Cui, Hongchang; Hao, Yueling; Kovtun, Mikhail; Stolc, Viktor; Deng, Xing-Wang; Sakakibara, Hitoshi; Kojima, Mikiko

2011-11-01

SHORT-ROOT (SHR) is a key regulator of root growth and development in Arabidopsis (Arabidopsis thaliana). Made in the stele, the SHR protein moves into an adjacent cell layer, where it specifies endodermal cell fate; it is also essential for apical meristem maintenance, ground tissue patterning, vascular differentiation, and lateral root formation. Much has been learned about the mechanism by which SHR controls radial patterning, but how it regulates other aspects of root morphogenesis is still unclear. To dissect the SHR developmental pathway, we have determined the genome-wide locations of SHR direct targets using a chromatin immunoprecipitation followed by microarray analysis method. K-means clustering analysis not only identified additional quiescent center-specific SHR targets but also revealed a direct role for SHR in gene regulation in the pericycle and xylem. Using cell type-specific markers, we showed that in shr, the phloem and the phloem-associated pericycle expanded, whereas the xylem and xylem-associated pericycle diminished. Interestingly, we found that cytokinin level was elevated in shr and that exogenous cytokinin conferred a shr-like vascular patterning phenotype in wild-type root. By chromatin immunoprecipitation-polymerase chain reaction and reverse transcription-polymerase chain reaction assays, we showed that SHR regulates cytokinin homeostasis by directly controlling the transcription of cytokinin oxidase 3, a cytokinin catabolism enzyme preferentially expressed in the stele. Finally, overexpression of a cytokinin oxidase in shr alleviated its vascular patterning defect. On the basis of these results, we suggest that one mechanism by which SHR controls vascular patterning is the regulation of cytokinin homeostasis.

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

PubMed Central

2012-01-01

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. PMID:22433273

An experimental loop design for the detection of constitutional chromosomal aberrations by array CGH

PubMed Central

2009-01-01

Background Comparative genomic hybridization microarrays for the detection of constitutional chromosomal aberrations is the application of microarray technology coming fastest into routine clinical application. Through genotype-phenotype association, it is also an important technique towards the discovery of disease causing genes and genomewide functional annotation in human. When using a two-channel microarray of genomic DNA probes for array CGH, the basic setup consists in hybridizing a patient against a normal reference sample. Two major disadvantages of this setup are (1) the use of half of the resources to measure a (little informative) reference sample and (2) the possibility that deviating signals are caused by benign copy number variation in the "normal" reference instead of a patient aberration. Instead, we apply an experimental loop design that compares three patients in three hybridizations. Results We develop and compare two statistical methods (linear models of log ratios and mixed models of absolute measurements). In an analysis of 27 patients seen at our genetics center, we observed that the linear models of the log ratios are advantageous over the mixed models of the absolute intensities. Conclusion The loop design and the performance of the statistical analysis contribute to the quick adoption of array CGH as a routine diagnostic tool. They lower the detection limit of mosaicisms and improve the assignment of copy number variation for genetic association studies. PMID:19925645

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

PubMed Central

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

2011-01-01

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

An experimental loop design for the detection of constitutional chromosomal aberrations by array CGH.

PubMed

Allemeersch, Joke; Van Vooren, Steven; Hannes, Femke; De Moor, Bart; Vermeesch, Joris Robert; Moreau, Yves

2009-11-19

Comparative genomic hybridization microarrays for the detection of constitutional chromosomal aberrations is the application of microarray technology coming fastest into routine clinical application. Through genotype-phenotype association, it is also an important technique towards the discovery of disease causing genes and genomewide functional annotation in human. When using a two-channel microarray of genomic DNA probes for array CGH, the basic setup consists in hybridizing a patient against a normal reference sample. Two major disadvantages of this setup are (1) the use of half of the resources to measure a (little informative) reference sample and (2) the possibility that deviating signals are caused by benign copy number variation in the "normal" reference instead of a patient aberration. Instead, we apply an experimental loop design that compares three patients in three hybridizations. We develop and compare two statistical methods (linear models of log ratios and mixed models of absolute measurements). In an analysis of 27 patients seen at our genetics center, we observed that the linear models of the log ratios are advantageous over the mixed models of the absolute intensities. The loop design and the performance of the statistical analysis contribute to the quick adoption of array CGH as a routine diagnostic tool. They lower the detection limit of mosaicisms and improve the assignment of copy number variation for genetic association studies.

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

SacconePhD, Scott F; Chesler, Elissa J; Bierut, Laura J

Commercial SNP microarrays now provide comprehensive and affordable coverage of the human genome. However, some diseases have biologically relevant genomic regions that may require additional coverage. Addiction, for example, is thought to be influenced by complex interactions among many relevant genes and pathways. We have assembled a list of 486 biologically relevant genes nominated by a panel of experts on addiction. We then added 424 genes that showed evidence of association with addiction phenotypes through mouse QTL mappings and gene co-expression analysis. We demonstrate that there are a substantial number of SNPs in these genes that are not well representedmore » by commercial SNP platforms. We address this problem by introducing a publicly available SNP database for addiction. The database is annotated using numeric prioritization scores indicating the extent of biological relevance. The scores incorporate a number of factors such as SNP/gene functional properties (including synonymy and promoter regions), data from mouse systems genetics and measures of human/mouse evolutionary conservation. We then used HapMap genotyping data to determine if a SNP is tagged by a commercial microarray through linkage disequilibrium. This combination of biological prioritization scores and LD tagging annotation will enable addiction researchers to supplement commercial SNP microarrays to ensure comprehensive coverage of biologically relevant regions.« less

Genome-wide analysis and expression profile of the bZIP transcription factor gene family in grapevine (Vitis vinifera)

PubMed Central

2014-01-01

Background Basic leucine zipper (bZIP) transcription factor gene family is one of the largest and most diverse families in plants. Current studies have shown that the bZIP proteins regulate numerous growth and developmental processes and biotic and abiotic stress responses. Nonetheless, knowledge concerning the specific expression patterns and evolutionary history of plant bZIP family members remains very limited. Results We identified 55 bZIP transcription factor-encoding genes in the grapevine (Vitis vinifera) genome, and divided them into 10 groups according to the phylogenetic relationship with those in Arabidopsis. The chromosome distribution and the collinearity analyses suggest that expansion of the grapevine bZIP (VvbZIP) transcription factor family was greatly contributed by the segment/chromosomal duplications, which may be associated with the grapevine genome fusion events. Nine intron/exon structural patterns within the bZIP domain and the additional conserved motifs were identified among all VvbZIP proteins, and showed a high group-specificity. The predicted specificities on DNA-binding domains indicated that some highly conserved amino acid residues exist across each major group in the tree of land plant life. The expression patterns of VvbZIP genes across the grapevine gene expression atlas, based on microarray technology, suggest that VvbZIP genes are involved in grapevine organ development, especially seed development. Expression analysis based on qRT-PCR indicated that VvbZIP genes are extensively involved in drought- and heat-responses, with possibly different mechanisms. Conclusions The genome-wide identification, chromosome organization, gene structures, evolutionary and expression analyses of grapevine bZIP genes provide an overall insight of this gene family and their potential involvement in growth, development and stress responses. This will facilitate further research on the bZIP gene family regarding their evolutionary history and biological functions. PMID:24725365

Integrative Analysis Reveals Relationships of Genetic and Epigenetic Alterations in Osteosarcoma

PubMed Central

Skårn, Magne; Namløs, Heidi M.; Barragan-Polania, Ana H.; Cleton-Jansen, Anne-Marie; Serra, Massimo; Liestøl, Knut; Hogendoorn, Pancras C. W.; Hovig, Eivind; Myklebost, Ola; Meza-Zepeda, Leonardo A.

2012-01-01

Background Osteosarcomas are the most common non-haematological primary malignant tumours of bone, and all conventional osteosarcomas are high-grade tumours showing complex genomic aberrations. We have integrated genome-wide genetic and epigenetic profiles from the EuroBoNeT panel of 19 human osteosarcoma cell lines based on microarray technologies. Principal Findings The cell lines showed complex patterns of DNA copy number changes, where genomic copy number gains were significantly associated with gene-rich regions and losses with gene-poor regions. By integrating the datasets, 350 genes were identified as having two types of aberrations (gain/over-expression, hypo-methylation/over-expression, loss/under-expression or hyper-methylation/under-expression) using a recurrence threshold of 6/19 (>30%) cell lines. The genes showed in general alterations in either DNA copy number or DNA methylation, both within individual samples and across the sample panel. These 350 genes are involved in embryonic skeletal system development and morphogenesis, as well as remodelling of extracellular matrix. The aberrations of three selected genes, CXCL5, DLX5 and RUNX2, were validated in five cell lines and five tumour samples using PCR techniques. Several genes were hyper-methylated and under-expressed compared to normal osteoblasts, and expression could be reactivated by demethylation using 5-Aza-2′-deoxycytidine treatment for four genes tested; AKAP12, CXCL5, EFEMP1 and IL11RA. Globally, there was as expected a significant positive association between gain and over-expression, loss and under-expression as well as hyper-methylation and under-expression, but gain was also associated with hyper-methylation and under-expression, suggesting that hyper-methylation may oppose the effects of increased copy number for detrimental genes. Conclusions Integrative analysis of genome-wide genetic and epigenetic alterations identified dependencies and relationships between DNA copy number, DNA methylation and mRNA expression in osteosarcomas, contributing to better understanding of osteosarcoma biology. PMID:23144859

Integrated Analysis of Genome-wide Copy Number Alterations and Gene Expression in MSS, CIMP-negative Colon Cancer

PubMed Central

Loo, Lenora WM; Tiirikainen, Maarit; Cheng, Iona; Lum-Jones, Annette; Seifried, Ann; Church, James M; Gryfe, Robert; Weisenberger, Daniel J; Lindor, Noralane M; Gallinger, Steven; Haile, Robert W; Duggan, David J; Thibodeau, Stephen N; Casey, Graham; Le Marchand, Loïc

2014-01-01

Microsatellite stable (MSS), CpG island methylator phenotype (CIMP)-negative colorectal tumors, the most prevalent molecular subtype of colorectal cancer, are associated with extensive copy number alteration (CNA) events and aneuploidy. We report on the identification of characteristic recurrent CNA (with frequency >25%) events and associated gene expression profiles for a total of 40 paired tumor and adjacent normal colon tissues using genome-wide microarrays. We observed recurrent CNAs, namely gains at 1q, 7p, 7q, 8p12-11, 8q, 12p13, 13q, 20p, 20q, Xp, and Xq and losses at 1p36, 1p31, 1p21, 4p15-12, 4q12-35, 5q21-22, 6q26, 8p, 14q, 15q11-12, 17p, 18p, 18q, 21q21-22, and 22q. Within these genomic regions we identified 356 genes with significant differential expression (P<0.0001 and ±1.5 fold change) in the tumor compared to adjacent normal tissue. Gene ontology and pathway analyses indicated that many of these genes were involved in functional mechanisms that regulate cell cycle, cell death, and metabolism. An amplicon present in >70% of the tumor samples at 20q11-20q13 contained several cancer-related genes (AHCY, POFUT1, RPN2, TH1L and PRPF6) that were up-regulated and demonstrated a significant linear correlation (P<0.05) for gene dosage and gene expression. Copy number loss at 8p, a CNA associated with adenocarcinoma and poor prognosis, was observed in >50% of the tumor samples and demonstrated a significant linear correlation for gene dosage and gene expression for two potential tumor suppressor genes, MTUS1 (8p22) and PPP2CB (8p12). The results from our integration analysis illustrate the complex relationship between genomic alterations and gene expression in colon cancer. PMID:23341073