WebArray: an online platform for microarray data analysis

PubMed Central

Xia, Xiaoqin; McClelland, Michael; Wang, Yipeng

2005-01-01

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

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

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.

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

PubMed

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

2009-02-01

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

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.

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.

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.

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.

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.

Is this the real time for genomics?

PubMed

Guarnaccia, Maria; Gentile, Giulia; Alessi, Enrico; Schneider, Claudio; Petralia, Salvatore; Cavallaro, Sebastiano

2014-01-01

In the last decades, molecular biology has moved from gene-by-gene analysis to more complex studies using a genome-wide scale. Thanks to high-throughput genomic technologies, such as microarrays and next-generation sequencing, a huge amount of information has been generated, expanding our knowledge on the genetic basis of various diseases. Although some of this information could be transferred to clinical diagnostics, the technologies available are not suitable for this purpose. In this review, we will discuss the drawbacks associated with the use of traditional DNA microarrays in diagnostics, pointing out emerging platforms that could overcome these obstacles and offer a more reproducible, qualitative and quantitative multigenic analysis. New miniaturized and automated devices, called Lab-on-Chip, begin to integrate PCR and microarray on the same platform, offering integrated sample-to-result systems. The introduction of this kind of innovative devices may facilitate the transition of genome-based tests into clinical routine. Copyright © 2014. Published by Elsevier Inc.

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.

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.

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

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

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

Analysis of developmental gene conservation in the Actinomycetales using DNA/DNA microarray comparisons.

PubMed

Kirby, Ralph; Herron, Paul; Hoskisson, Paul

2011-02-01

Based on available genome sequences, Actinomycetales show significant gene synteny across a wide range of species and genera. In addition, many genera show varying degrees of complex morphological development. Using the presence of gene synteny as a basis, it is clear that an analysis of gene conservation across the Streptomyces and various other Actinomycetales will provide information on both the importance of genes and gene clusters and the evolution of morphogenesis in these bacteria. Genome sequencing, although becoming cheaper, is still relatively expensive for comparing large numbers of strains. Thus, a heterologous DNA/DNA microarray hybridization dataset based on a Streptomyces coelicolor microarray allows a cheaper and greater depth of analysis of gene conservation. This study, using both bioinformatical and microarray approaches, was able to classify genes previously identified as involved in morphogenesis in Streptomyces into various subgroups in terms of conservation across species and genera. This will allow the targeting of genes for further study based on their importance at the species level and at higher evolutionary 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 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.

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

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

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.

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.

Quantitative phenotyping via deep barcode sequencing.

PubMed

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

2009-10-01

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 approximately 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.

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

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

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.

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

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.

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.

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.

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.

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

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

PubMed Central

2012-01-01

Background The combination of chromatin immunoprecipitation with two-channel microarray technology enables genome-wide mapping of binding sites of DNA-interacting proteins (ChIP-on-chip) or sites with methylated CpG di-nucleotides (DNA methylation microarray). These powerful tools are the gateway to understanding gene transcription regulation. Since the goals of such studies, the sample preparation procedures, the microarray content and study design are all different from transcriptomics microarrays, the data pre-processing strategies traditionally applied to transcriptomics microarrays may not be appropriate. Particularly, the main challenge of the normalization of "regulation microarrays" is (i) to make the data of individual microarrays quantitatively comparable and (ii) to keep the signals of the enriched probes, representing DNA sequences from the precipitate, as distinguishable as possible from the signals of the un-enriched probes, representing DNA sequences largely absent from the precipitate. Results We compare several widely used normalization approaches (VSN, LOWESS, quantile, T-quantile, Tukey's biweight scaling, Peng's method) applied to a selection of regulation microarray datasets, ranging from DNA methylation to transcription factor binding and histone modification studies. Through comparison of the data distributions of control probes and gene promoter probes before and after normalization, and assessment of the power to identify known enriched genomic regions after normalization, we demonstrate that there are clear differences in performance between normalization procedures. Conclusion T-quantile normalization applied separately on the channels and Tukey's biweight scaling outperform other methods in terms of the conservation of enriched and un-enriched signal separation, as well as in identification of genomic regions known to be enriched. T-quantile normalization is preferable as it additionally improves comparability between microarrays. In contrast, popular normalization approaches like quantile, LOWESS, Peng's method and VSN normalization alter the data distributions of regulation microarrays to such an extent that using these approaches will impact the reliability of the downstream analysis substantially. PMID:22276688

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

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.

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

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

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.

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.

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.

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.

Expanding probe repertoire and improving reproducibility in human genomic hybridization

PubMed Central

Dorman, Stephanie N.; Shirley, Ben C.; Knoll, Joan H. M.; Rogan, Peter K.

2013-01-01

Diagnostic DNA hybridization relies on probes composed of single copy (sc) genomic sequences. Sc sequences in probe design ensure high specificity and avoid cross-hybridization to other regions of the genome, which could lead to ambiguous results that are difficult to interpret. We examine how the distribution and composition of repetitive sequences in the genome affects sc probe performance. A divide and conquer algorithm was implemented to design sc probes. With this approach, sc probes can include divergent repetitive elements, which hybridize to unique genomic targets under higher stringency experimental conditions. Genome-wide custom probe sets were created for fluorescent in situ hybridization (FISH) and microarray genomic hybridization. The scFISH probes were developed for detection of copy number changes within small tumour suppressor genes and oncogenes. The microarrays demonstrated increased reproducibility by eliminating cross-hybridization to repetitive sequences adjacent to probe targets. The genome-wide microarrays exhibited lower median coefficients of variation (17.8%) for two HapMap family trios. The coefficients of variations of commercial probes within 300 nt of a repetitive element were 48.3% higher than the nearest custom probe. Furthermore, the custom microarray called a chromosome 15q11.2q13 deletion more consistently. This method for sc probe design increases probe coverage for FISH and lowers variability in genomic microarrays. PMID:23376933

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

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.

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...

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

High-throughput microarray technology in diagnostics of enterobacteria based on genome-wide probe selection and regression analysis.

PubMed

Friedrich, Torben; Rahmann, Sven; Weigel, Wilfried; Rabsch, Wolfgang; Fruth, Angelika; Ron, Eliora; Gunzer, Florian; Dandekar, Thomas; Hacker, Jörg; Müller, Tobias; Dobrindt, Ulrich

2010-10-21

The Enterobacteriaceae comprise a large number of clinically relevant species with several individual subspecies. Overlapping virulence-associated gene pools and the high overall genome plasticity often interferes with correct enterobacterial strain typing and risk assessment. Array technology offers a fast, reproducible and standardisable means for bacterial typing and thus provides many advantages for bacterial diagnostics, risk assessment and surveillance. The development of highly discriminative broad-range microbial diagnostic microarrays remains a challenge, because of marked genome plasticity of many bacterial pathogens. We developed a DNA microarray for strain typing and detection of major antimicrobial resistance genes of clinically relevant enterobacteria. For this purpose, we applied a global genome-wide probe selection strategy on 32 available complete enterobacterial genomes combined with a regression model for pathogen classification. The discriminative power of the probe set was further tested in silico on 15 additional complete enterobacterial genome sequences. DNA microarrays based on the selected probes were used to type 92 clinical enterobacterial isolates. Phenotypic tests confirmed the array-based typing results and corroborate that the selected probes allowed correct typing and prediction of major antibiotic resistances of clinically relevant Enterobacteriaceae, including the subspecies level, e.g. the reliable distinction of different E. coli pathotypes. Our results demonstrate that the global probe selection approach based on longest common factor statistics as well as the design of a DNA microarray with a restricted set of discriminative probes enables robust discrimination of different enterobacterial variants and represents a proof of concept that can be adopted for diagnostics of a wide range of microbial pathogens. Our approach circumvents misclassifications arising from the application of virulence markers, which are highly affected by horizontal gene transfer. Moreover, a broad range of pathogens have been covered by an efficient probe set size enabling the design of high-throughput diagnostics.

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

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.

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.

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.

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.

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

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

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 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

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

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.

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.

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.

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

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 ...

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

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.

Spotting and validation of a genome wide oligonucleotide chip with duplicate measurement of each gene

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

Thomassen, Mads; Skov, Vibe; Eiriksdottir, Freyja

2006-06-16

The quality of DNA microarray based gene expression data relies on the reproducibility of several steps in a microarray experiment. We have developed a spotted genome wide microarray chip with oligonucleotides printed in duplicate in order to minimise undesirable biases, thereby optimising detection of true differential expression. The validation study design consisted of an assessment of the microarray chip performance using the MessageAmp and FairPlay labelling kits. Intraclass correlation coefficient (ICC) was used to demonstrate that MessageAmp was significantly more reproducible than FairPlay. Further examinations with MessageAmp revealed the applicability of the system. The linear range of the chips wasmore » three orders of magnitude, the precision was high, as 95% of measurements deviated less than 1.24-fold from the expected value, and the coefficient of variation for relative expression was 13.6%. Relative quantitation was more reproducible than absolute quantitation and substantial reduction of variance was attained with duplicate spotting. An analysis of variance (ANOVA) demonstrated no significant day-to-day variation.« less

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

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.

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

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.

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

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

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

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.

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.

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.

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.

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.

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

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.

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

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.

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.

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.

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

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.

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.

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.

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.

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).

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

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.

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.

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.

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.

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.

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.

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.

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

PubMed Central

2014-01-01

Background Genome-wide microarrays have been useful for predicting chemical-genetic interactions at the gene level. However, interpreting genome-wide microarray results can be overwhelming due to the vast output of gene expression data combined with off-target transcriptional responses many times induced by a drug treatment. This study demonstrates how experimental and computational methods can interact with each other, to arrive at more accurate predictions of drug-induced perturbations. We present a two-stage strategy that links microarray experimental testing and network training conditions to predict gene perturbations for a drug with a known mechanism of action in a well-studied organism. Results S. cerevisiae cells were treated with the antifungal, fluconazole, and expression profiling was conducted under different biological conditions using Affymetrix genome-wide microarrays. Transcripts were filtered with a formal network-based method, sparse simultaneous equation models and Lasso regression (SSEM-Lasso), under different network training conditions. Gene expression results were evaluated using both gene set and single gene target analyses, and the drug’s transcriptional effects were narrowed first by pathway and then by individual genes. Variables included: (i) Testing conditions – exposure time and concentration and (ii) Network training conditions – training compendium modifications. Two analyses of SSEM-Lasso output – gene set and single gene – were conducted to gain a better understanding of how SSEM-Lasso predicts perturbation targets. Conclusions This study demonstrates that genome-wide microarrays can be optimized using a two-stage strategy for a more in-depth understanding of how a cell manifests biological reactions to a drug treatment at the transcription level. Additionally, a more detailed understanding of how the statistical model, SSEM-Lasso, propagates perturbations through a network of gene regulatory interactions is achieved. PMID:24444313

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.

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

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.

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 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

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...

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...

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.

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.

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.

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

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

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.

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.

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.

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.

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 ( ...

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.

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/.

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.

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.

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

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.

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

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.

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

[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.

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

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

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

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.

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

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...

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...

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

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

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

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

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.

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

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

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

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.

Transcriptome analysis and related databases of Lactococcus lactis.

PubMed

Kuipers, Oscar P; de Jong, Anne; Baerends, Richard J S; van Hijum, Sacha A F T; Zomer, Aldert L; Karsens, Harma A; den Hengst, Chris D; Kramer, Naomi E; Buist, Girbe; Kok, Jan

2002-08-01

Several complete genome sequences of Lactococcus lactis and their annotations will become available in the near future, next to the already published genome sequence of L. lactis ssp. lactis IL 1403. This will allow intraspecies comparative genomics studies as well as functional genomics studies aimed at a better understanding of physiological processes and regulatory networks operating in lactococci. This paper describes the initial set-up of a DNA-microarray facility in our group, to enable transcriptome analysis of various Gram-positive bacteria, including a ssp. lactis and a ssp. cremoris strain of Lactococcus lactis. Moreover a global description will be given of the hardware and software requirements for such a set-up, highlighting the crucial integration of relevant bioinformatics tools and methods. This includes the development of MolGenIS, an information system for transcriptome data storage and retrieval, and LactococCye, a metabolic pathway/genome database of Lactococcus lactis.

Attomole-level Genomics with Single-molecule Direct DNA, cDNA and RNA Sequencing Technologies.

PubMed

Ozsolak, Fatih

2016-01-01

With the introduction of next-generation sequencing (NGS) technologies in 2005, the domination of microarrays in genomics quickly came to an end due to NGS's superior technical performance and cost advantages. By enabling genetic analysis capabilities that were not possible previously, NGS technologies have started to play an integral role in all areas of biomedical research. This chapter outlines the low-quantity DNA and cDNA sequencing capabilities and applications developed with the Helicos single molecule DNA sequencing technology.

Impact of genotyping errors on statistical power of association tests in genomic analyses: A case study

PubMed Central

Hou, Lin; Sun, Ning; Mane, Shrikant; Sayward, Fred; Rajeevan, Nallakkandi; Cheung, Kei-Hoi; Cho, Kelly; Pyarajan, Saiju; Aslan, Mihaela; Miller, Perry; Harvey, Philip D.; Gaziano, J. Michael; Concato, John; Zhao, Hongyu

2017-01-01

A key step in genomic studies is to assess high throughput measurements across millions of markers for each participant’s DNA, either using microarrays or sequencing techniques. Accurate genotype calling is essential for downstream statistical analysis of genotype-phenotype associations, and next generation sequencing (NGS) has recently become a more common approach in genomic studies. How the accuracy of variant calling in NGS-based studies affects downstream association analysis has not, however, been studied using empirical data in which both microarrays and NGS were available. In this article, we investigate the impact of variant calling errors on the statistical power to identify associations between single nucleotides and disease, and on associations between multiple rare variants and disease. Both differential and nondifferential genotyping errors are considered. Our results show that the power of burden tests for rare variants is strongly influenced by the specificity in variant calling, but is rather robust with regard to sensitivity. By using the variant calling accuracies estimated from a substudy of a Cooperative Studies Program project conducted by the Department of Veterans Affairs, we show that the power of association tests is mostly retained with commonly adopted variant calling pipelines. An R package, GWAS.PC, is provided to accommodate power analysis that takes account of genotyping errors (http://zhaocenter.org/software/). PMID:28019059

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

EPA Science Inventory

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

A new normalizing algorithm for BAC CGH arrays with quality control metrics.

PubMed

Miecznikowski, Jeffrey C; Gaile, Daniel P; Liu, Song; Shepherd, Lori; Nowak, Norma

2011-01-01

The main focus in pin-tip (or print-tip) microarray analysis is determining which probes, genes, or oligonucleotides are differentially expressed. Specifically in array comparative genomic hybridization (aCGH) experiments, researchers search for chromosomal imbalances in the genome. To model this data, scientists apply statistical methods to the structure of the experiment and assume that the data consist of the signal plus random noise. In this paper we propose "SmoothArray", a new method to preprocess comparative genomic hybridization (CGH) bacterial artificial chromosome (BAC) arrays and we show the effects on a cancer dataset. As part of our R software package "aCGHplus," this freely available algorithm removes the variation due to the intensity effects, pin/print-tip, the spatial location on the microarray chip, and the relative location from the well plate. removal of this variation improves the downstream analysis and subsequent inferences made on the data. Further, we present measures to evaluate the quality of the dataset according to the arrayer pins, 384-well plates, plate rows, and plate columns. We compare our method against competing methods using several metrics to measure the biological signal. With this novel normalization algorithm and quality control measures, the user can improve their inferences on datasets and pinpoint problems that may arise in their BAC aCGH technology.

COMPARISON OF COMPARATIVE GENOMIC HYBRIDIZATIONS TECHNOLOGIES ACROSS MICROARRAY PLATFORMS

EPA Science Inventory

Comparative Genomic Hybridization (CGH) measures DNA copy number differences between a reference genome and a test genome. The DNA samples are differentially labeled and hybridized to an immobilized substrate. In early CGH experiments, the DNA targets were hybridized to metaphase...

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.

A unique combination of 17pter trisomy and 21qter monosomy in a boy with developmental delay, severe intellectual disability, growth retardation and dysmorphisms.

PubMed

Zheng, Zhaojing; Yao, Ru-En; Geng, Juan; Jin, Xingming; Shen, Yongnian; Ying, Daming; Fu, Qihua; Yu, Yongguo

2013-03-10

Microduplication at 17p13.3 and microdeletion at 21q22 are both rare chromosomal aberrations. The presence of both genomic imbalances in one patient has not been previously reported in literature. In this study, we performed a molecular diagnostic testing with a whole genome microarray on a 3-year-old boy with developmental delay, mental retardation and multiple malformations. A routine G-banding karyotype analysis was performed using peripheral lymphocytes. Chromosome microarray analysis (CMA) was done using Affymetrix CytoScan™ HD array. Genomic imbalances were further confirmed by multiple ligation-dependent probe amplification (MLPA). The result of karyotyping was normal but CMA detected a 9.8 Mb microduplication at 17p13.3-13.1 (chr17: 1-9,875,545) and a 2.8 Mb microdeletion involving 21q22.3-qter (chr21: 45,239,077-48,097,372). The imbalances were due to a balanced translocation present in patient's mother. The patient was characterized with short stature, profound developmental delay, non-verbal, intellectual disability as well as craniofacial dysmorphism, subtle brain structural anomaly and sparse scalp hair. This is the first patient reported with a combination of a microduplication at 17p13.3-13.1 and a microdeletion at 21q22.3-qter. Both genomic imbalances were undetected by conventional karyotyping but were delineated with CMA test. Synergistic effect from the two rare genomic imbalances is likely responsible for the severe clinical phenotypes observed in this patient. Copyright © 2012 Elsevier B.V. All rights reserved.

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

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

PubMed Central

Thomas, E. V.; Phillippy, K. H.; Brahamsha, B.; Haaland, D. M.; Timlin, J. A.; Elbourne, L. D. H.; Palenik, B.; Paulsen, I. T.

2009-01-01

Until recently microarray experiments often involved relatively few arrays with only a single representation of each gene on each array. A complete genome microarray with multiple spots per gene (spread out spatially across the array) was developed in order to compare the gene expression of a marine cyanobacterium and a knockout mutant strain in a defined artificial seawater medium. Statistical methods were developed for analysis in the special situation of this case study where there is gene replication within an array and where relatively few arrays are used, which can be the case with current array technology. Due in part to the replication within an array, it was possible to detect very small changes in the levels of expression between the wild type and mutant strains. One interesting biological outcome of this experiment is the indication of the extent to which the phosphorus regulatory system of this cyanobacterium affects the expression of multiple genes beyond those strictly involved in phosphorus acquisition. PMID:19404483

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

DOE PAGES

Thomas, E. V.; Phillippy, K. H.; Brahamsha, B.; ...

2009-01-01

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

Customizing microarrays for neuroscience drug discovery.

PubMed

Girgenti, Matthew J; Newton, Samuel S

2007-08-01

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

Gene Expression Profiling of Gastric Cancer

PubMed Central

Marimuthu, Arivusudar; Jacob, Harrys K.C.; Jakharia, Aniruddha; Subbannayya, Yashwanth; Keerthikumar, Shivakumar; Kashyap, Manoj Kumar; Goel, Renu; Balakrishnan, Lavanya; Dwivedi, Sutopa; Pathare, Swapnali; Dikshit, Jyoti Bajpai; Maharudraiah, Jagadeesha; Singh, Sujay; Sameer Kumar, Ghantasala S; Vijayakumar, M.; Veerendra Kumar, Kariyanakatte Veeraiah; Premalatha, Chennagiri Shrinivasamurthy; Tata, Pramila; Hariharan, Ramesh; Roa, Juan Carlos; Prasad, T.S.K; Chaerkady, Raghothama; Kumar, Rekha Vijay; Pandey, Akhilesh

2015-01-01

Gastric cancer is the second leading cause of cancer death worldwide, both in men and women. A genomewide gene expression analysis was carried out to identify differentially expressed genes in gastric adenocarcinoma tissues as compared to adjacent normal tissues. We used Agilent’s whole human genome oligonucleotide microarray platform representing ~41,000 genes to carry out gene expression analysis. Two-color microarray analysis was employed to directly compare the expression of genes between tumor and normal tissues. Through this approach, we identified several previously known candidate genes along with a number of novel candidate genes in gastric cancer. Testican-1 (SPOCK1) was one of the novel molecules that was 10-fold upregulated in tumors. Using tissue microarrays, we validated the expression of testican-1 by immunohistochemical staining. It was overexpressed in 56% (160/282) of the cases tested. Pathway analysis led to the identification of several networks in which SPOCK1 was among the topmost networks of interacting genes. By gene enrichment analysis, we identified several genes involved in cell adhesion and cell proliferation to be significantly upregulated while those corresponding to metabolic pathways were significantly downregulated. The differentially expressed genes identified in this study are candidate biomarkers for gastric adenoacarcinoma. PMID:27030788

Transcriptome and secretome analyses of Phanerochaete chrysosporium reveal complex patterns of gene expression

Treesearch

Amber J. Vanden Wymelenberg; Jill A. Gaskell; Michael D. Mozuch; Philip J. Kersten; Grzegorz Sabat; Diego Martinez; Daniel Cullen

2009-01-01

The wood decay basidiomycete Phanerochaete chrysosporium was grown under standard ligninolytic or cellulolytic conditions and subjected to whole-genome expression microarray analysis and liquid chromatography-tandem mass spectrometry of extracellular proteins. A total of 545 genes were flagged on the basis of significant changes in transcript accumulation and/or...

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.

From genomes to vaccines: Leishmania as a model.

PubMed Central

Almeida, Renata; Norrish, Alan; Levick, Mark; Vetrie, David; Freeman, Tom; Vilo, Jaak; Ivens, Alasdair; Lange, Uta; Stober, Carmel; McCann, Sharon; Blackwell, Jenefer M

2002-01-01

The 35 Mb genome of Leishmania should be sequenced by late 2002. It contains approximately 8500 genes that will probably translate into more than 10 000 proteins. In the laboratory we have been piloting strategies to try to harness the power of the genome-proteome for rapid screening of new vaccine candidate. To this end, microarray analysis of 1094 unique genes identified using an EST analysis of 2091 cDNA clones from spliced leader libraries prepared from different developmental stages of Leishmania has been employed. The plan was to identify amastigote-expressed genes that could be used in high-throughput DNA-vaccine screens to identify potential new vaccine candidates. Despite the lack of transcriptional regulation that polycistronic transcription in Leishmania dictates, the data provide evidence for a high level of post-transcriptional regulation of RNA abundance during the developmental cycle of promastigotes in culture and in lesion-derived amastigotes of Leishmania major. This has provided 147 candidates from the 1094 unique genes that are specifically upregulated in amastigotes and are being used in vaccine studies. Using DNA vaccination, it was demonstrated that pooling strategies can work to identify protective vaccines, but it was found that some potentially protective antigens are masked by other disease-exacerbatory antigens in the pool. A total of 100 new vaccine candidates are currently being tested separately and in pools to extend this analysis, and to facilitate retrospective bioinformatic analysis to develop predictive algorithms for sequences that constitute potentially protective antigens. We are also working with other members of the Leishmania Genome Network to determine whether RNA expression determined by microarray analyses parallels expression at the protein level. We believe we are making good progress in developing strategies that will allow rapid translation of the sequence of Leishmania into potential interventions for disease control in humans. PMID:11839176

Characterization of regulatory pathways in Xylella fastidiosa: genes and phenotypes controlled by algU.

PubMed

Shi, Xiang Yang; Dumenyo, C Korsi; Hernandez-Martinez, Rufina; Azad, Hamid; Cooksey, Donald A

2007-11-01

Many virulence genes in plant bacterial pathogens are coordinately regulated by "global" regulatory genes. Conducting DNA microarray analysis of bacterial mutants of such genes, compared with the wild type, can help to refine the list of genes that may contribute to virulence in bacterial pathogens. The regulatory gene algU, with roles in stress response and regulation of the biosynthesis of the exopolysaccharide alginate in Pseudomonas aeruginosa and many other bacteria, has been extensively studied. The role of algU in Xylella fastidiosa, the cause of Pierce's disease of grapevines, was analyzed by mutation and whole-genome microarray analysis to define its involvement in aggregation, biofilm formation, and virulence. In this study, an algU::nptII mutant had reduced cell-cell aggregation, attachment, and biofilm formation and lower virulence in grapevines. Microarray analysis showed that 42 genes had significantly lower expression in the algU::nptII mutant than in the wild type. Among these are several genes that could contribute to cell aggregation and biofilm formation, as well as other physiological processes such as virulence, competition, and survival.

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.

Structure-related clustering of gene expression fingerprints of thp-1 cells exposed to smaller polycyclic aromatic hydrocarbons.

PubMed

Wan, B; Yarbrough, J W; Schultz, T W

2008-01-01

This study was undertaken to test the hypothesis that structurally similar PAHs induce similar gene expression profiles. THP-1 cells were exposed to a series of 12 selected PAHs at 50 microM for 24 hours and gene expressions profiles were analyzed using both unsupervised and supervised methods. Clustering analysis of gene expression profiles revealed that the 12 tested chemicals were grouped into five clusters. Within each cluster, the gene expression profiles are more similar to each other than to the ones outside the cluster. One-methylanthracene and 1-methylfluorene were found to have the most similar profiles; dibenzothiophene and dibenzofuran were found to share common profiles with fluorine. As expression pattern comparisons were expanded, similarity in genomic fingerprint dropped off dramatically. Prediction analysis of microarrays (PAM) based on the clustering pattern generated 49 predictor genes that can be used for sample discrimination. Moreover, a significant analysis of Microarrays (SAM) identified 598 genes being modulated by tested chemicals with a variety of biological processes, such as cell cycle, metabolism, and protein binding and KEGG pathways being significantly (p < 0.05) affected. It is feasible to distinguish structurally different PAHs based on their genomic fingerprints, which are mechanism based.

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

Applications of microarray technology in breast cancer research

PubMed Central

Cooper, Colin S

2001-01-01

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

Design of microarray experiments for genetical genomics studies.

PubMed

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

2006-10-01

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

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

PubMed Central

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

2009-01-01

Background The ability to generate transcriptional data on the scale of entire genomes has been a boon both in the improvement of biological understanding and in the amount of data generated. The latter, the amount of data generated, has implications when it comes to effective storage, analysis and sharing of these data. A number of software tools have been developed to store, analyze, and share microarray data. However, a majority of these tools do not offer all of these features nor do they specifically target the commonly used two color Agilent DNA microarray platform. Thus, the motivating factor for the development of EDGE3 was to incorporate the storage, analysis and sharing of microarray data in a manner that would provide a means for research groups to collaborate on Agilent-based microarray experiments without a large investment in software-related expenditures or extensive training of end-users. Results EDGE3 has been developed with two major functions in mind. The first function is to provide a workflow process for the generation of microarray data by a research laboratory or a microarray facility. The second is to store, analyze, and share microarray data in a manner that doesn't require complicated software. To satisfy the first function, EDGE3 has been developed as a means to establish a well defined experimental workflow and information system for microarray generation. To satisfy the second function, the software application utilized as the user interface of EDGE3 is a web browser. Within the web browser, a user is able to access the entire functionality, including, but not limited to, the ability to perform a number of bioinformatics based analyses, collaborate between research groups through a user-based security model, and access to the raw data files and quality control files generated by the software used to extract the signals from an array image. Conclusion Here, we present EDGE3, an open-source, web-based application that allows for the storage, analysis, and controlled sharing of transcription-based microarray data generated on the Agilent DNA platform. In addition, EDGE3 provides a means for managing RNA samples and arrays during the hybridization process. EDGE3 is freely available for download at . PMID:19732451

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

PubMed

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

2009-09-04

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

Micro-Analyzer: automatic preprocessing of Affymetrix microarray data.

PubMed

Guzzi, Pietro Hiram; Cannataro, Mario

2013-08-01

A current trend in genomics is the investigation of the cell mechanism using different technologies, in order to explain the relationship among genes, molecular processes and diseases. For instance, the combined use of gene-expression arrays and genomic arrays has been demonstrated as an effective instrument in clinical practice. Consequently, in a single experiment different kind of microarrays may be used, resulting in the production of different types of binary data (images and textual raw data). The analysis of microarray data requires an initial preprocessing phase, that makes raw data suitable for use on existing analysis platforms, such as the TIGR M4 (TM4) Suite. An additional challenge to be faced by emerging data analysis platforms is the ability to treat in a combined way those different microarray formats coupled with clinical data. In fact, resulting integrated data may include both numerical and symbolic data (e.g. gene expression and SNPs regarding molecular data), as well as temporal data (e.g. the response to a drug, time to progression and survival rate), regarding clinical data. Raw data preprocessing is a crucial step in analysis but is often performed in a manual and error prone way using different software tools. Thus novel, platform independent, and possibly open source tools enabling the semi-automatic preprocessing and annotation of different microarray data are needed. The paper presents Micro-Analyzer (Microarray Analyzer), a cross-platform tool for the automatic normalization, summarization and annotation of Affymetrix gene expression and SNP binary data. It represents the evolution of the μ-CS tool, extending the preprocessing to SNP arrays that were not allowed in μ-CS. The Micro-Analyzer is provided as a Java standalone tool and enables users to read, preprocess and analyse binary microarray data (gene expression and SNPs) by invoking TM4 platform. It avoids: (i) the manual invocation of external tools (e.g. the Affymetrix Power Tools), (ii) the manual loading of preprocessing libraries, and (iii) the management of intermediate files, such as results and metadata. Micro-Analyzer users can directly manage Affymetrix binary data without worrying about locating and invoking the proper preprocessing tools and chip-specific libraries. Moreover, users of the Micro-Analyzer tool can load the preprocessed data directly into the well-known TM4 platform, extending in such a way also the TM4 capabilities. Consequently, Micro Analyzer offers the following advantages: (i) it reduces possible errors in the preprocessing and further analysis phases, e.g. due to the incorrect choice of parameters or due to the use of old libraries, (ii) it enables the combined and centralized pre-processing of different arrays, (iii) it may enhance the quality of further analysis by storing the workflow, i.e. information about the preprocessing steps, and (iv) finally Micro-Analzyer is freely available as a standalone application at the project web site http://sourceforge.net/projects/microanalyzer/. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

Epigenomics

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 ( ...

Cloning

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 ( ...

Chromosomes

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 ( ...

Transcriptome

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 ( ...

Identification of PblB mediating galactose-specific adhesion in a successful Streptococcus pneumoniae clone

PubMed Central

Hsieh, Yu-Chia; Lin, Tzu-Lung; Lin, Che-Ming; Wang, Jin-Town

2015-01-01

The pneumococcal genome is variable and there are minimal data on the influence of the accessory genome on phenotype. Pneumococcal serotype 14 sequence type (ST) 46 had been the most prevalent clone causing pneumonia in children in Taiwan. A microarray was constructed using the genomic DNA of a clinical strain (NTUH-P15) of serotype 14 ST46. Using DNA hybridization, genomic variations in NTUH-P15 were compared to those of 3 control strains. Microarray analysis identified 7 genomic regions that had significant increases in hybridization signals in the NTUH-P15 strain compared to control strains. One of these regions encoded PblB, a phage-encoded virulence factor implicated (in Streptococcus mitis) in infective endocarditis. The isogenic pblB mutant decreased adherence to A549 human lung epithelial cell compared to wild-type NTUH-P15 strain (P = 0.01). Complementation with pblB restored the adherence. PblB is predicted to contain a galactose-binding domain-like region. Preincubation of NTUH-P15 with D-galactose resulted in decreases of adherence to A549 cell in a dose-dependent manner. Challenge of mice with NTUH-P15, isogenic pblB mutant and pblB complementation strains determined that PblB was required for bacterial persistence in the nasopharynx and lung. PblB, as an adhesin mediating the galactose-specific adhesion activity of pneumococci, promote pneumococcal clonal success. PMID:26193794

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

BRIC-17 Mapping Spaceflight-Induced Hypoxic Signaling and Response in Plants

NASA Technical Reports Server (NTRS)

Gilroy, Simon; Choi, Won-Gyu; Swanson, Sarah

2012-01-01

Goals of this work are: (1) Define global changes in gene expression patterns in Arabidopsis plants grown in microgravity using whole genome microarrays (2) Compare to mutants resistant to low oxygen challenge using whole genome microarrays Also measuring root and shoot size Outcomes from this research are: (1) Provide fundamental information on plant responses to the stresses inherent in spaceflight (2) Potential for informing on genetic strategies to engineer plants for optimal growth in space

Characterization of a novel Lactobacillus species closely related to Lactobacillus johnsonii using a combination of molecular and comparative genomics methods

PubMed Central

2010-01-01

Background 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. Results 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. Conclusion 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. PMID:20849602

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.

Estimation of low-dose radiation-responsive proteins in the absence of genomic instability in normal human fibroblast cells.

PubMed

Yim, Ji-Hye; Yun, Jung Mi; Kim, Ji Young; Nam, Seon Young; Kim, Cha Soon

2017-11-01

Low-dose radiation has various biological effects such as adaptive responses, low-dose hypersensitivity, as well as beneficial effects. However, little is known about the particular proteins involved in these effects. Here, we sought to identify low-dose radiation-responsive phosphoproteins in normal fibroblast cells. We assessed genomic instability and proliferation of fibroblast cells after γ-irradiation by γ-H2AX foci and micronucleus formation analyses and BrdU incorporation assay, respectively. We screened fibroblast cells 8 h after low-dose (0.05 Gy) γ-irradiation using Phospho Explorer Antibody Microarray and validated two differentially expressed phosphoproteins using Western blotting. Cell proliferation proceeded normally in the absence of genomic instability after low-dose γ-irradiation. Phospho antibody microarray analysis and Western blotting revealed increased expression of two phosphoproteins, phospho-NFκB (Ser536) and phospho-P70S6K (Ser418), 8 h after low-dose radiation. Our findings suggest that low-dose radiation of normal fibroblast cells activates the expression of phospho-NFκB (Ser536) and phospho-P70S6K (Ser418) in the absence of genomic instability. Therefore, these proteins may be involved in DNA damage repair processes.

Genetic Mapping

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 ( ...

Biological Pathways

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 ( ...

Use of homologous and heterologous gene expression profiling tools to characterize transcription dynamics during apple fruit maturation and ripening.

PubMed

Costa, Fabrizio; Alba, Rob; Schouten, Henk; Soglio, Valeria; Gianfranceschi, Luca; Serra, Sara; Musacchi, Stefano; Sansavini, Silviero; Costa, Guglielmo; Fei, Zhangjun; Giovannoni, James

2010-10-25

Fruit development, maturation and ripening consists of a complex series of biochemical and physiological changes that in climacteric fruits, including apple and tomato, are coordinated by the gaseous hormone ethylene. These changes lead to final fruit quality and understanding of the functional machinery underlying these processes is of both biological and practical importance. To date many reports have been made on the analysis of gene expression in apple. In this study we focused our investigation on the role of ethylene during apple maturation, specifically comparing transcriptomics of normal ripening with changes resulting from application of the hormone receptor competitor 1-methylcyclopropene. To gain insight into the molecular process regulating ripening in apple, and to compare to tomato (model species for ripening studies), we utilized both homologous and heterologous (tomato) microarray to profile transcriptome dynamics of genes involved in fruit development and ripening, emphasizing those which are ethylene regulated.The use of both types of microarrays facilitated transcriptome comparison between apple and tomato (for the later using data previously published and available at the TED: tomato expression database) and highlighted genes conserved during ripening of both species, which in turn represent a foundation for further comparative genomic studies. The cross-species analysis had the secondary aim of examining the efficiency of heterologous (specifically tomato) microarray hybridization for candidate gene identification as related to the ripening process. The resulting transcriptomics data revealed coordinated gene expression during fruit ripening of a subset of ripening-related and ethylene responsive genes, further facilitating the analysis of ethylene response during fruit maturation and ripening. Our combined strategy based on microarray hybridization enabled transcriptome characterization during normal climacteric apple ripening, as well as definition of ethylene-dependent transcriptome changes. Comparison with tomato fruit maturation and ethylene responsive transcriptome activity facilitated identification of putative conserved orthologous ripening-related genes, which serve as an initial set of candidates for assessing conservation of gene activity across genomes of fruit bearing plant species.

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.

Development and Comparison of Two Assay Formats for Parallel Detection of Four Biothreat Pathogens by Using Suspension Microarrays

PubMed Central

Janse, Ingmar; Bok, Jasper M.; Hamidjaja, Raditijo A.; Hodemaekers, Hennie M.; van Rotterdam, Bart J.

2012-01-01

Microarrays provide a powerful analytical tool for the simultaneous detection of multiple pathogens. We developed diagnostic suspension microarrays for sensitive and specific detection of the biothreat pathogens Bacillus anthracis, Yersinia pestis, Francisella tularensis and Coxiella burnetii. Two assay chemistries for amplification and labeling were developed, one method using direct hybridization and the other using target-specific primer extension, combined with hybridization to universal arrays. Asymmetric PCR products for both assay chemistries were produced by using a multiplex asymmetric PCR amplifying 16 DNA signatures (16-plex). The performances of both assay chemistries were compared and their advantages and disadvantages are discussed. The developed microarrays detected multiple signature sequences and an internal control which made it possible to confidently identify the targeted pathogens and assess their virulence potential. The microarrays were highly specific and detected various strains of the targeted pathogens. Detection limits for the different pathogen signatures were similar or slightly higher compared to real-time PCR. Probit analysis showed that even a few genomic copies could be detected with 95% confidence. The microarrays detected DNA from different pathogens mixed in different ratios and from spiked or naturally contaminated samples. The assays that were developed have a potential for application in surveillance and diagnostics. PMID:22355407

Development and comparison of two assay formats for parallel detection of four biothreat pathogens by using suspension microarrays.

PubMed

Janse, Ingmar; Bok, Jasper M; Hamidjaja, Raditijo A; Hodemaekers, Hennie M; van Rotterdam, Bart J

2012-01-01

Microarrays provide a powerful analytical tool for the simultaneous detection of multiple pathogens. We developed diagnostic suspension microarrays for sensitive and specific detection of the biothreat pathogens Bacillus anthracis, Yersinia pestis, Francisella tularensis and Coxiella burnetii. Two assay chemistries for amplification and labeling were developed, one method using direct hybridization and the other using target-specific primer extension, combined with hybridization to universal arrays. Asymmetric PCR products for both assay chemistries were produced by using a multiplex asymmetric PCR amplifying 16 DNA signatures (16-plex). The performances of both assay chemistries were compared and their advantages and disadvantages are discussed. The developed microarrays detected multiple signature sequences and an internal control which made it possible to confidently identify the targeted pathogens and assess their virulence potential. The microarrays were highly specific and detected various strains of the targeted pathogens. Detection limits for the different pathogen signatures were similar or slightly higher compared to real-time PCR. Probit analysis showed that even a few genomic copies could be detected with 95% confidence. The microarrays detected DNA from different pathogens mixed in different ratios and from spiked or naturally contaminated samples. The assays that were developed have a potential for application in surveillance and diagnostics.

Identification of genes associated with the long-gut-persistence phenotype of the probiotic Lactobacillus johnsonii strain NCC533 using a combination of genomics and transcriptome analysis.

PubMed

Denou, Emmanuel; Pridmore, Raymond David; Berger, Bernard; Panoff, Jean-Michel; Arigoni, Fabrizio; Brüssow, Harald

2008-05-01

Lactobacillus johnsonii strains NCC533 and ATCC 33200 (the type strain of this species) differed significantly in gut residence time (12 versus 5 days) after oral feeding to mice. Genes affecting the long gut residence time of the probiotic strain NCC533 were targeted for analysis. We hypothesized that genes specific for this strain, which are expressed during passage of the bacterium through the gut, affect the phenotype. When the DNA of the type strain was hybridized against a microarray of the sequenced NCC533 strain, we identified 233 genes that were specific for the long-gut-persistence isolate. Whole-genome transcription analysis of the NCC533 strain using the microarray format identified 174 genes that were strongly and consistently expressed in the jejunum of mice monocolonized with this strain. Fusion of the two microarray data sets identified three gene loci that were both expressed in vivo and specific to the long-gut-persistence isolate. The identified genes included LJ1027 and LJ1028, two glycosyltransferase genes in the exopolysaccharide synthesis operon; LJ1654 to LJ1656, encoding a sugar phosphotransferase system (PTS) transporter annotated as mannose PTS; and LJ1680, whose product shares 30% amino acid identity with immunoglobulin A proteases from pathogenic bacteria. Knockout mutants were tested in vivo. The experiments revealed that deletion of LJ1654 to LJ1656 and LJ1680 decreased the gut residence time, while a mutant with a deleted exopolysaccharide biosynthesis cluster had a slightly increased residence time.

DISC-BASED IMMUNOASSAY MICROARRAYS. (R825433)

EPA Science Inventory

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

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

PubMed

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

2015-06-01

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

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.

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

Bioinformatics approaches for cross-species liver cancer analysis based on microarray gene expression profiling

PubMed Central

Fang, H; Tong, W; Perkins, R; Shi, L; Hong, H; Cao, X; Xie, Q; Yim, SH; Ward, JM; Pitot, HC; Dragan, YP

2005-01-01

Background The completion of the sequencing of human, mouse and rat genomes and knowledge of cross-species gene homologies enables studies of differential gene expression in animal models. These types of studies have the potential to greatly enhance our understanding of diseases such as liver cancer in humans. Genes co-expressed across multiple species are most likely to have conserved functions. We have used various bioinformatics approaches to examine microarray expression profiles from liver neoplasms that arise in albumin-SV40 transgenic rats to elucidate genes, chromosome aberrations and pathways that might be associated with human liver cancer. Results In this study, we first identified 2223 differentially expressed genes by comparing gene expression profiles for two control, two adenoma and two carcinoma samples using an F-test. These genes were subsequently mapped to the rat chromosomes using a novel visualization tool, the Chromosome Plot. Using the same plot, we further mapped the significant genes to orthologous chromosomal locations in human and mouse. Many genes expressed in rat 1q that are amplified in rat liver cancer map to the human chromosomes 10, 11 and 19 and to the mouse chromosomes 7, 17 and 19, which have been implicated in studies of human and mouse liver cancer. Using Comparative Genomics Microarray Analysis (CGMA), we identified regions of potential aberrations in human. Lastly, a pathway analysis was conducted to predict altered human pathways based on statistical analysis and extrapolation from the rat data. All of the identified pathways have been known to be important in the etiology of human liver cancer, including cell cycle control, cell growth and differentiation, apoptosis, transcriptional regulation, and protein metabolism. Conclusion The study demonstrates that the hepatic gene expression profiles from the albumin-SV40 transgenic rat model revealed genes, pathways and chromosome alterations consistent with experimental and clinical research in human liver cancer. The bioinformatics tools presented in this paper are essential for cross species extrapolation and mapping of microarray data, its analysis and interpretation. PMID:16026603

DNA Microarray Wet Lab Simulation Brings Genomics into the High School Curriculum

ERIC Educational Resources Information Center

Campbell, A. Malcolm; Zanta, Carolyn A.; Heyer, Laurie J.; Kittinger, Ben; Gabric, Kathleen M.; Adler, Leslie

2006-01-01

We have developed a wet lab DNA microarray simulation as part of a complete DNA microarray module for high school students. The wet lab simulation has been field tested with high school students in Illinois and Maryland as well as in workshops with high school teachers from across the nation. Instead of using DNA, our simulation is based on pH…

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.

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

PubMed Central

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

2005-01-01

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

FindGDPs: fast identification of primers for labeling microbial transcriptomes for DNA microarray analysis

PubMed Central

Blick, Robert J.; Revel, Andrew T.; Hansen, Eric J.

2008-01-01

Summary FindGDPs is a program that uses a greedy algorithm to quickly identify a set of genome-directed primers that specifically anneal to all of the open reading frames in a genome and that do not exhibit full-length complementarity to the members of another user-supplied set of nucleotide sequences. Availability The program code is distributed under the GNU General Public License at http://www8.utsouthwestern.edu/utsw/cda/dept131456/files/159331.html Contact eric.hansen@utsouthwestern.edu PMID:15593406

Identifying novel glioma associated pathways based on systems biology level meta-analysis.

PubMed

Hu, Yangfan; Li, Jinquan; Yan, Wenying; Chen, Jiajia; Li, Yin; Hu, Guang; Shen, Bairong

2013-01-01

With recent advances in microarray technology, including genomics, proteomics, and metabolomics, it brings a great challenge for integrating this "-omics" data to analysis complex disease. Glioma is an extremely aggressive and lethal form of brain tumor, and thus the study of the molecule mechanism underlying glioma remains very important. To date, most studies focus on detecting the differentially expressed genes in glioma. However, the meta-analysis for pathway analysis based on multiple microarray datasets has not been systematically pursued. In this study, we therefore developed a systems biology based approach by integrating three types of omics data to identify common pathways in glioma. Firstly, the meta-analysis has been performed to study the overlapping of signatures at different levels based on the microarray gene expression data of glioma. Among these gene expression datasets, 12 pathways were found in GeneGO database that shared by four stages. Then, microRNA expression profiles and ChIP-seq data were integrated for the further pathway enrichment analysis. As a result, we suggest 5 of these pathways could be served as putative pathways in glioma. Among them, the pathway of TGF-beta-dependent induction of EMT via SMAD is of particular importance. Our results demonstrate that the meta-analysis based on systems biology level provide a more useful approach to study the molecule mechanism of complex disease. The integration of different types of omics data, including gene expression microarrays, microRNA and ChIP-seq data, suggest some common pathways correlated with glioma. These findings will offer useful potential candidates for targeted therapeutic intervention of glioma.

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

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

PubMed Central

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

2007-01-01

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

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.

Microbial Profiling of Combat Wound Infection through Detection Microarray and Next-Generation Sequencing

PubMed Central

Allen, Jonathan E.; Brown, Trevor S.; Gardner, Shea N.; McLoughlin, Kevin S.; Forsberg, Jonathan A.; Kirkup, Benjamin C.; Chromy, Brett A.; Luciw, Paul A.; Elster, Eric A.

2014-01-01

Combat wound healing and resolution are highly affected by the resident microbial flora. We therefore sought to achieve comprehensive detection of microbial populations in wounds using novel genomic technologies and bioinformatics analyses. We employed a microarray capable of detecting all sequenced pathogens for interrogation of 124 wound samples from extremity injuries in combat-injured U.S. service members. A subset of samples was also processed via next-generation sequencing and metagenomic analysis. Array analysis detected microbial targets in 51% of all wound samples, with Acinetobacter baumannii being the most frequently detected species. Multiple Pseudomonas species were also detected in tissue biopsy specimens. Detection of the Acinetobacter plasmid pRAY correlated significantly with wound failure, while detection of enteric-associated bacteria was associated significantly with successful healing. Whole-genome sequencing revealed broad microbial biodiversity between samples. The total wound bioburden did not associate significantly with wound outcome, although temporal shifts were observed over the course of treatment. Given that standard microbiological methods do not detect the full range of microbes in each wound, these data emphasize the importance of supplementation with molecular techniques for thorough characterization of wound-associated microbes. Future application of genomic protocols for assessing microbial content could allow application of specialized care through early and rapid identification and management of critical patterns in wound bioburden. PMID:24829242

High throughput gene expression profiling: a molecular approach to integrative physiology

PubMed Central

Liang, Mingyu; Cowley, Allen W; Greene, Andrew S

2004-01-01

Integrative physiology emphasizes the importance of understanding multiple pathways with overlapping, complementary, or opposing effects and their interactions in the context of intact organisms. The DNA microarray technology, the most commonly used method for high-throughput gene expression profiling, has been touted as an integrative tool that provides insights into regulatory pathways. However, the physiology community has been slow in acceptance of these techniques because of early failure in generating useful data and the lack of a cohesive theoretical framework in which experiments can be analysed. With recent advances in both technology and analysis, we propose a concept of multidimensional integration of physiology that incorporates data generated by DNA microarray and other functional, genomic, and proteomic approaches to achieve a truly integrative understanding of physiology. Analysis of several studies performed in simpler organisms or in mammalian model animals supports the feasibility of such multidimensional integration and demonstrates the power of DNA microarray as an indispensable molecular tool for such integration. Evaluation of DNA microarray techniques indicates that these techniques, despite limitations, have advanced to a point where the question-driven profiling research has become a feasible complement to the conventional, hypothesis-driven research. With a keen sense of homeostasis, global regulation, and quantitative analysis, integrative physiologists are uniquely positioned to apply these techniques to enhance the understanding of complex physiological functions. PMID:14678487

Comparative Analysis of CNV Calling Algorithms: Literature Survey and a Case Study Using Bovine High-Density SNP Data.

PubMed

Xu, Lingyang; Hou, Yali; Bickhart, Derek M; Song, Jiuzhou; Liu, George E

2013-06-25

Copy number variations (CNVs) are gains and losses of genomic sequence between two individuals of a species when compared to a reference genome. The data from single nucleotide polymorphism (SNP) microarrays are now routinely used for genotyping, but they also can be utilized for copy number detection. Substantial progress has been made in array design and CNV calling algorithms and at least 10 comparison studies in humans have been published to assess them. In this review, we first survey the literature on existing microarray platforms and CNV calling algorithms. We then examine a number of CNV calling tools to evaluate their impacts using bovine high-density SNP data. Large incongruities in the results from different CNV calling tools highlight the need for standardizing array data collection, quality assessment and experimental validation. Only after careful experimental design and rigorous data filtering can the impacts of CNVs on both normal phenotypic variability and disease susceptibility be fully revealed.

Meta-analysis methods for combining multiple expression profiles: comparisons, statistical characterization and an application guideline

PubMed Central

2013-01-01

Background As high-throughput genomic technologies become accurate and affordable, an increasing number of data sets have been accumulated in the public domain and genomic information integration and meta-analysis have become routine in biomedical research. In this paper, we focus on microarray meta-analysis, where multiple microarray studies with relevant biological hypotheses are combined in order to improve candidate marker detection. Many methods have been developed and applied in the literature, but their performance and properties have only been minimally investigated. There is currently no clear conclusion or guideline as to the proper choice of a meta-analysis method given an application; the decision essentially requires both statistical and biological considerations. Results We performed 12 microarray meta-analysis methods for combining multiple simulated expression profiles, and such methods can be categorized for different hypothesis setting purposes: (1) HS A : DE genes with non-zero effect sizes in all studies, (2) HS B : DE genes with non-zero effect sizes in one or more studies and (3) HS r : DE gene with non-zero effect in "majority" of studies. We then performed a comprehensive comparative analysis through six large-scale real applications using four quantitative statistical evaluation criteria: detection capability, biological association, stability and robustness. We elucidated hypothesis settings behind the methods and further apply multi-dimensional scaling (MDS) and an entropy measure to characterize the meta-analysis methods and data structure, respectively. Conclusions The aggregated results from the simulation study categorized the 12 methods into three hypothesis settings (HS A , HS B , and HS r ). Evaluation in real data and results from MDS and entropy analyses provided an insightful and practical guideline to the choice of the most suitable method in a given application. All source files for simulation and real data are available on the author’s publication website. PMID:24359104

Meta-analysis methods for combining multiple expression profiles: comparisons, statistical characterization and an application guideline.

PubMed

Chang, Lun-Ching; Lin, Hui-Min; Sibille, Etienne; Tseng, George C

2013-12-21

As high-throughput genomic technologies become accurate and affordable, an increasing number of data sets have been accumulated in the public domain and genomic information integration and meta-analysis have become routine in biomedical research. In this paper, we focus on microarray meta-analysis, where multiple microarray studies with relevant biological hypotheses are combined in order to improve candidate marker detection. Many methods have been developed and applied in the literature, but their performance and properties have only been minimally investigated. There is currently no clear conclusion or guideline as to the proper choice of a meta-analysis method given an application; the decision essentially requires both statistical and biological considerations. We performed 12 microarray meta-analysis methods for combining multiple simulated expression profiles, and such methods can be categorized for different hypothesis setting purposes: (1) HS(A): DE genes with non-zero effect sizes in all studies, (2) HS(B): DE genes with non-zero effect sizes in one or more studies and (3) HS(r): DE gene with non-zero effect in "majority" of studies. We then performed a comprehensive comparative analysis through six large-scale real applications using four quantitative statistical evaluation criteria: detection capability, biological association, stability and robustness. We elucidated hypothesis settings behind the methods and further apply multi-dimensional scaling (MDS) and an entropy measure to characterize the meta-analysis methods and data structure, respectively. The aggregated results from the simulation study categorized the 12 methods into three hypothesis settings (HS(A), HS(B), and HS(r)). Evaluation in real data and results from MDS and entropy analyses provided an insightful and practical guideline to the choice of the most suitable method in a given application. All source files for simulation and real data are available on the author's publication website.

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

PubMed Central

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

2008-01-01

Summary Methanosarcina acetivorans strain C2A is an acetate- and methanol-utilizing methane-producing organism for which the genome, the largest yet sequenced among the Archaea, reveals extensive physiological diversity. LC linear ion trap-FTICR mass spectrometry was employed to analyze acetate- vs. methanol-grown cells metabolically labeled with 14N vs. 15N, respectively, to obtain quantitative protein abundance ratios. DNA microarray analyses of acetate- vs. methanol-grown cells was also performed to determine gene expression ratios. The combined approaches were highly complementary, extending the physiological understanding of growth and methanogenesis. Of the 1081 proteins detected, 255 were ≥ 3-fold differentially abundant. DNA microarray analysis revealed 410 genes that were ≥ 2.5-fold differentially expressed of 1972 genes with detected expression. The ratios of differentially abundant proteins were in good agreement with expression ratios of the encoding genes. Taken together, the results suggest several novel roles for electron transport components specific to acetate-grown cells, including two flavodoxins each specific for growth on acetate or methanol. Protein abundance ratios indicated that duplicate CO dehydrogenase/acetyl-CoA complexes function in the conversion of acetate to methane. Surprisingly, the protein abundance and gene expression ratios indicated a general stress response in acetate- vs. methanol-grown cells that included enzymes specific for polyphosphate accumulation and oxidative stress. The microarray analysis identified transcripts of several genes encoding regulatory proteins with identity to the PhoU, MarR, GlnK, and TetR families commonly found in the Bacteria domain. An analysis of neighboring genes suggested roles in controlling phosphate metabolism (PhoU), ammonia assimilation (GlnK), and molybdopterin cofactor biosynthesis (TetR). Finally, the proteomic and microarray results suggested roles for two-component regulatory systems specific for each growth substrate. PMID:17269732

Global mapping of transposon location.

PubMed

Gabriel, Abram; Dapprich, Johannes; Kunkel, Mark; Gresham, David; Pratt, Stephen C; Dunham, Maitreya J

2006-12-15

Transposable genetic elements are ubiquitous, yet their presence or absence at any given position within a genome can vary between individual cells, tissues, or strains. Transposable elements have profound impacts on host genomes by altering gene expression, assisting in genomic rearrangements, causing insertional mutations, and serving as sources of phenotypic variation. Characterizing a genome's full complement of transposons requires whole genome sequencing, precluding simple studies of the impact of transposition on interindividual variation. Here, we describe a global mapping approach for identifying transposon locations in any genome, using a combination of transposon-specific DNA extraction and microarray-based comparative hybridization analysis. We use this approach to map the repertoire of endogenous transposons in different laboratory strains of Saccharomyces cerevisiae and demonstrate that transposons are a source of extensive genomic variation. We also apply this method to mapping bacterial transposon insertion sites in a yeast genomic library. This unique whole genome view of transposon location will facilitate our exploration of transposon dynamics, as well as defining bases for individual differences and adaptive potential.

Design and verification of a pangenome microarray oligonucleotide probe set for Dehalococcoides spp.

PubMed

Hug, Laura A; Salehi, Maryam; Nuin, Paulo; Tillier, Elisabeth R; Edwards, Elizabeth A

2011-08-01

Dehalococcoides spp. are an industrially relevant group of Chloroflexi bacteria capable of reductively dechlorinating contaminants in groundwater environments. Existing Dehalococcoides genomes revealed a high level of sequence identity within this group, including 98 to 100% 16S rRNA sequence identity between strains with diverse substrate specificities. Common molecular techniques for identification of microbial populations are often not applicable for distinguishing Dehalococcoides strains. Here we describe an oligonucleotide microarray probe set designed based on clustered Dehalococcoides genes from five different sources (strain DET195, CBDB1, BAV1, and VS genomes and the KB-1 metagenome). This "pangenome" probe set provides coverage of core Dehalococcoides genes as well as strain-specific genes while optimizing the potential for hybridization to closely related, previously unknown Dehalococcoides strains. The pangenome probe set was compared to probe sets designed independently for each of the five Dehalococcoides strains. The pangenome probe set demonstrated better predictability and higher detection of Dehalococcoides genes than strain-specific probe sets on nontarget strains with <99% average nucleotide identity. An in silico analysis of the expected probe hybridization against the recently released Dehalococcoides strain GT genome and additional KB-1 metagenome sequence data indicated that the pangenome probe set performs more robustly than the combined strain-specific probe sets in the detection of genes not included in the original design. The pangenome probe set represents a highly specific, universal tool for the detection and characterization of Dehalococcoides from contaminated sites. It has the potential to become a common platform for Dehalococcoides-focused research, allowing meaningful comparisons between microarray experiments regardless of the strain examined.

RNAi targeting GPR4 influences HMEC-1 gene expression by microarray analysis

PubMed Central

Ren, Juan; Zhang, Yuelang; Cai, Hui; Ma, Hongbing; Zhao, Dongli; Zhang, Xiaozhi; Li, Zongfang; Wang, Shufeng; Wang, Jiangsheng; Liu, Rui; Li, Yi; Qian, Jiansheng; Wei, Hongxia; Niu, Liying; Liu, Yan; Xiao, Lisha; Ding, Muyang; Jiang, Shiwen

2014-01-01

G-protein coupled receptor 4 (GPR4) belongs to a protein family comprised of 3 closely related G protein-coupled receptors. Recent studies have shown that GPR4 plays important roles in angiogenesis, proton sensing, and regulating tumor cells as an oncogenic gene. How GPR4 conducts its functions? Rare has been known. In order to detect the genes related to GPR4, microarray technology was employed. GPR4 is highly expressed in human vascular endothelial cell HMEC-1. Small interfering RNA against GPR4 was used to knockdown GPR4 expression in HMEC-1. Then RNA from the GPR4 knockdown cells and control cells were analyzed through genome microarray. Microarray results shown that among the whole genes and expressed sequence tags, 447 differentially expressed genes were identified, containing 318 up-regulated genes and 129 down-regulated genes. These genes whose expression dramatically changed may be involved in the GPR4 functions. These genes were related to cell apoptosis, cytoskeleton and signal transduction, cell proliferation, differentiation and cell-cycle regulation, gene transcription and translation and cell material and energy metabolism. PMID:24753754

Prediction of Microbial Infection of Cultured Cells Using DNA Microarray Gene-Expression Profiles of Host Responses

PubMed Central

Park, Yu Rang; Chung, Tae Su; Lee, Young Joo; Song, Yeong Wook; Lee, Eun Young; Sohn, Yeo Won; Song, Sukgil; Park, Woong Yang

2012-01-01

Infection by microorganisms may cause fatally erroneous interpretations in the biologic researches based on cell culture. The contamination by microorganism in the cell culture is quite frequent (5% to 35%). However, current approaches to identify the presence of contamination have many limitations such as high cost of time and labor, and difficulty in interpreting the result. In this paper, we propose a model to predict cell infection, using a microarray technique which gives an overview of the whole genome profile. By analysis of 62 microarray expression profiles under various experimental conditions altering cell type, source of infection and collection time, we discovered 5 marker genes, NM_005298, NM_016408, NM_014588, S76389, and NM_001853. In addition, we discovered two of these genes, S76389, and NM_001853, are involved in a Mycolplasma-specific infection process. We also suggest models to predict the source of infection, cell type or time after infection. We implemented a web based prediction tool in microarray data, named Prediction of Microbial Infection (http://www.snubi.org/software/PMI). PMID:23091307

Initial Genomics of the Human Nucleolus

PubMed Central

Németh, Attila; Conesa, Ana; Santoyo-Lopez, Javier; Medina, Ignacio; Montaner, David; Péterfia, Bálint; Solovei, Irina; Cremer, Thomas; Dopazo, Joaquin; Längst, Gernot

2010-01-01

We report for the first time the genomics of a nuclear compartment of the eukaryotic cell. 454 sequencing and microarray analysis revealed the pattern of nucleolus-associated chromatin domains (NADs) in the linear human genome and identified different gene families and certain satellite repeats as the major building blocks of NADs, which constitute about 4% of the genome. Bioinformatic evaluation showed that NAD–localized genes take part in specific biological processes, like the response to other organisms, odor perception, and tissue development. 3D FISH and immunofluorescence experiments illustrated the spatial distribution of NAD–specific chromatin within interphase nuclei and its alteration upon transcriptional changes. Altogether, our findings describe the nature of DNA sequences associated with the human nucleolus and provide insights into the function of the nucleolus in genome organization and establishment of nuclear architecture. PMID:20361057

Segmental Duplications and Copy-Number Variation in the Human Genome

PubMed Central

Sharp, Andrew J. ; Locke, Devin P. ; McGrath, Sean D. ; Cheng, Ze ; Bailey, Jeffrey A. ; Vallente, Rhea U. ; Pertz, Lisa M. ; Clark, Royden A. ; Schwartz, Stuart ; Segraves, Rick ; Oseroff, Vanessa V. ; Albertson, Donna G. ; Pinkel, Daniel ; Eichler, Evan E. 

2005-01-01

The human genome contains numerous blocks of highly homologous duplicated sequence. This higher-order architecture provides a substrate for recombination and recurrent chromosomal rearrangement associated with genomic disease. However, an assessment of the role of segmental duplications in normal variation has not yet been made. On the basis of the duplication architecture of the human genome, we defined a set of 130 potential rearrangement hotspots and constructed a targeted bacterial artificial chromosome (BAC) microarray (with 2,194 BACs) to assess copy-number variation in these regions by array comparative genomic hybridization. Using our segmental duplication BAC microarray, we screened a panel of 47 normal individuals, who represented populations from four continents, and we identified 119 regions of copy-number polymorphism (CNP), 73 of which were previously unreported. We observed an equal frequency of duplications and deletions, as well as a 4-fold enrichment of CNPs within hotspot regions, compared with control BACs (P < .000001), which suggests that segmental duplications are a major catalyst of large-scale variation in the human genome. Importantly, segmental duplications themselves were also significantly enriched >4-fold within regions of CNP. Almost without exception, CNPs were not confined to a single population, suggesting that these either are recurrent events, having occurred independently in multiple founders, or were present in early human populations. Our study demonstrates that segmental duplications define hotspots of chromosomal rearrangement, likely acting as mediators of normal variation as well as genomic disease, and it suggests that the consideration of genomic architecture can significantly improve the ascertainment of large-scale rearrangements. Our specialized segmental duplication BAC microarray and associated database of structural polymorphisms will provide an important resource for the future characterization of human genomic disorders. PMID:15918152

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

USDA-ARS?s Scientific Manuscript database

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

Controlled hydrostatic pressure stress downregulates the expression of ribosomal genes in preimplantation embryos: a possible protection mechanism?

PubMed

Bock, I; Raveh-Amit, H; Losonczi, E; Carstea, A C; Feher, A; Mashayekhi, K; Matyas, S; Dinnyes, A; Pribenszky, C

2016-04-01

The efficiency of various assisted reproductive techniques can be improved by preconditioning the gametes and embryos with sublethal hydrostatic pressure treatment. However, the underlying molecular mechanism responsible for this protective effect remains unknown and requires further investigation. Here, we studied the effect of optimised hydrostatic pressure treatment on the global gene expression of mouse oocytes after embryonic genome activation. Based on a gene expression microarray analysis, a significant effect of treatment was observed in 4-cell embryos derived from treated oocytes, revealing a transcriptional footprint of hydrostatic pressure-affected genes. Functional analysis identified numerous genes involved in protein synthesis that were downregulated in 4-cell embryos in response to hydrostatic pressure treatment, suggesting that regulation of translation has a major role in optimised hydrostatic pressure-induced stress tolerance. We present a comprehensive microarray analysis and further delineate a potential mechanism responsible for the protective effect of hydrostatic pressure treatment.

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.

Chromosomal Microarray Testing in 42 Korean Patients with Unexplained Developmental Delay, Intellectual Disability, Autism Spectrum Disorders, and Multiple Congenital Anomalies.

PubMed

Lee, Sun Ho; Song, Wung Joo

2017-09-01

Chromosomal microarray (CMA) is a high-resolution, high-throughput method of identifying submicroscopic genomic copy number variations (CNVs). CMA has been established as the first-line diagnostic test for individuals with developmental delay (DD), intellectual disability (ID), autism spectrum disorders (ASDs), and multiple congenital anomalies (MCAs). CMA analysis was performed in 42 Korean patients who had been diagnosed with unexplained DD, ID, ASDs, and MCAs. Clinically relevant CNVs were discovered in 28 patients. Variants of unknown significance were detected in 13 patients. The diagnostic yield was high (66.7%). CMA is a superior diagnostic tool compared with conventional karyotyping and fluorescent in situ hybridization.

A microarray whole-genome gene expression dataset in a rat model of inflammatory corneal angiogenesis.

PubMed

Mukwaya, Anthony; Lindvall, Jessica M; Xeroudaki, Maria; Peebo, Beatrice; Ali, Zaheer; Lennikov, Anton; Jensen, Lasse Dahl Ejby; Lagali, Neil

2016-11-22

In angiogenesis with concurrent inflammation, many pathways are activated, some linked to VEGF and others largely VEGF-independent. Pathways involving inflammatory mediators, chemokines, and micro-RNAs may play important roles in maintaining a pro-angiogenic environment or mediating angiogenic regression. Here, we describe a gene expression dataset to facilitate exploration of pro-angiogenic, pro-inflammatory, and remodelling/normalization-associated genes during both an active capillary sprouting phase, and in the restoration of an avascular phenotype. The dataset was generated by microarray analysis of the whole transcriptome in a rat model of suture-induced inflammatory corneal neovascularisation. Regions of active capillary sprout growth or regression in the cornea were harvested and total RNA extracted from four biological replicates per group. High quality RNA was obtained for gene expression analysis using microarrays. Fold change of selected genes was validated by qPCR, and protein expression was evaluated by immunohistochemistry. We provide a gene expression dataset that may be re-used to investigate corneal neovascularisation, and may also have implications in other contexts of inflammation-mediated angiogenesis.

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

SEURAT: visual analytics for the integrated analysis of microarray data.

PubMed

Gribov, Alexander; Sill, Martin; Lück, Sonja; Rücker, Frank; Döhner, Konstanze; Bullinger, Lars; Benner, Axel; Unwin, Antony

2010-06-03

In translational cancer research, gene expression data is collected together with clinical data and genomic data arising from other chip based high throughput technologies. Software tools for the joint analysis of such high dimensional data sets together with clinical data are required. We have developed an open source software tool which provides interactive visualization capability for the integrated analysis of high-dimensional gene expression data together with associated clinical data, array CGH data and SNP array data. The different data types are organized by a comprehensive data manager. Interactive tools are provided for all graphics: heatmaps, dendrograms, barcharts, histograms, eventcharts and a chromosome browser, which displays genetic variations along the genome. All graphics are dynamic and fully linked so that any object selected in a graphic will be highlighted in all other graphics. For exploratory data analysis the software provides unsupervised data analytics like clustering, seriation algorithms and biclustering algorithms. The SEURAT software meets the growing needs of researchers to perform joint analysis of gene expression, genomical and clinical data.

Investigating the Genome Diversity of B. cereus and Evolutionary Aspects of B. anthracis Emergence

PubMed Central

Papazisi, Leka; Rasko, David A.; Ratnayake, Shashikala; Bock, Geoff R.; Remortel, Brian G.; Appalla, Lakshmi; Liu, Jia; Dracheva, Tatiana; Braisted, John C.; Shallom, Shamira; Jarrahi, Benham; Snesrud, Erik; Ahn, Susie; Sun, Qiang; Rilstone, Jenifer; Økstad, Ole Andreas; Kolstø, Anne-Brit; Fleischmann, Robert D.; Peterson, Scott N.

2011-01-01

Here we report the use of a multi-genome DNA microarray to investigate the genome diversity of Bacillus cereus group members and elucidate the events associated with the emergence of B. anthracis the causative agent of anthrax–a lethal zoonotic disease. We initially performed directed genome sequencing of seven diverse B. cereus strains to identify novel sequences encoded in those genomes. The novel genes identified, combined with those publicly available, allowed the design of a “species” DNA microarray. Comparative genomic hybridization analyses of 41 strains indicates that substantial heterogeneity exists with respect to the genes comprising functional role categories. While the acquisition of the plasmid-encoded pathogenicity island (pXO1) and capsule genes (pXO2) represent a crucial landmark dictating the emergence of B. anthracis, the evolution of this species and its close relatives was associated with an overall a shift in the fraction of genes devoted to energy metabolism, cellular processes, transport, as well as virulence. PMID:21447378

"Set in Stone" or "Ray of Hope": Parents' Beliefs about Cause and Prognosis after Genomic Testing of Children Diagnosed with ASD

ERIC Educational Resources Information Center

Reiff, Marian; Bugos, Eva; Giarelli, Ellen; Bernhardt, Barbara A.; Spinner, Nancy B.; Sankar, Pamela L.; Mulchandani, Surabhi

2017-01-01

Despite increasing utilization of chromosomal microarray analysis (CMA) for autism spectrum disorders (ASD), limited information exists about how results influence parents' beliefs about etiology and prognosis. We conducted in-depth interviews and surveys with 57 parents of children with ASD who received CMA results categorized as pathogenic,…

Assessing copy number from exome sequencing and exome array CGH based on CNV spectrum in a large clinical cohort.

PubMed

Retterer, Kyle; Scuffins, Julie; Schmidt, Daniel; Lewis, Rachel; Pineda-Alvarez, Daniel; Stafford, Amanda; Schmidt, Lindsay; Warren, Stephanie; Gibellini, Federica; Kondakova, Anastasia; Blair, Amanda; Bale, Sherri; Matyakhina, Ludmila; Meck, Jeanne; Aradhya, Swaroop; Haverfield, Eden

2015-08-01

Detection of copy-number variation (CNV) is important for investigating many genetic disorders. Testing a large clinical cohort by array comparative genomic hybridization provides a deep perspective on the spectrum of pathogenic CNV. In this context, we describe a bioinformatics approach to extract CNV information from whole-exome sequencing and demonstrate its utility in clinical testing. Exon-focused arrays and whole-genome chromosomal microarray analysis were used to test 14,228 and 14,000 individuals, respectively. Based on these results, we developed an algorithm to detect deletions/duplications in whole-exome sequencing data and a novel whole-exome array. In the exon array cohort, we observed a positive detection rate of 2.4% (25 duplications, 318 deletions), of which 39% involved one or two exons. Chromosomal microarray analysis identified 3,345 CNVs affecting single genes (18%). We demonstrate that our whole-exome sequencing algorithm resolves CNVs of three or more exons. These results demonstrate the clinical utility of single-exon resolution in CNV assays. Our whole-exome sequencing algorithm approaches this resolution but is complemented by a whole-exome array to unambiguously identify intragenic CNVs and single-exon changes. These data illustrate the next advancements in CNV analysis through whole-exome sequencing and whole-exome array.Genet Med 17 8, 623-629.

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.

Efficient mutation identification in zebrafish by microarray capturing and next generation sequencing.

PubMed

Bontems, Franck; Baerlocher, Loic; Mehenni, Sabrina; Bahechar, Ilham; Farinelli, Laurent; Dosch, Roland

2011-02-18

Fish models like medaka, stickleback or zebrafish provide a valuable resource to study vertebrate genes. However, finding genetic variants e.g. mutations in the genome is still arduous. Here we used a combination of microarray capturing and next generation sequencing to identify the affected gene in the mozartkugelp11cv (mzlp11cv) mutant zebrafish. We discovered a 31-bp deletion in macf1 demonstrating the potential of this technique to efficiently isolate mutations in a vertebrate genome. Copyright © 2011 Elsevier Inc. All rights reserved.

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

NASA Astrophysics Data System (ADS)

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

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

Decoding genes with coexpression networks and metabolomics - 'majority report by precogs'.

PubMed

Saito, Kazuki; Hirai, Masami Y; Yonekura-Sakakibara, Keiko

2008-01-01

Following the sequencing of whole genomes of model plants, high-throughput decoding of gene function is a major challenge in modern plant biology. In view of remarkable technical advances in transcriptomics and metabolomics, integrated analysis of these 'omics' by data-mining informatics is an excellent tool for prediction and identification of gene function, particularly for genes involved in complicated metabolic pathways. The availability of Arabidopsis public transcriptome datasets containing data of >1000 microarrays reinforces the potential for prediction of gene function by transcriptome coexpression analysis. Here, we review the strategy of combining transcriptome and metabolome as a powerful technology for studying the functional genomics of model plants and also crop and medicinal plants.

Comparison of Comparative Genomic Hybridization Technologies across Microarray Platforms

EPA Science Inventory

In the 2007 Association of Biomolecular Resource Facilities (ABRF) Microarray Research Group (MARG) project, we analyzed HL-60 DNA with five platforms: Agilent, Affymetrix 500K, Affymetrix U133 Plus 2.0, Illumina, and RPCI 19K BAC arrays. Copy number variation (CNV) was analyzed ...

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.

Methylation-Sensitive Amplification Length Polymorphism (MS-AFLP) Microarrays for Epigenetic Analysis of Human Genomes.

PubMed

Alonso, Sergio; Suzuki, Koichi; Yamamoto, Fumiichiro; Perucho, Manuel

2018-01-01

Somatic, and in a minor scale also germ line, epigenetic aberrations are fundamental to carcinogenesis, cancer progression, and tumor phenotype. DNA methylation is the most extensively studied and arguably the best understood epigenetic mechanisms that become altered in cancer. Both somatic loss of methylation (hypomethylation) and gain of methylation (hypermethylation) are found in the genome of malignant cells. In general, the cancer cell epigenome is globally hypomethylated, while some regions-typically gene-associated CpG islands-become hypermethylated. Given the profound impact that DNA methylation exerts on the transcriptional profile and genomic stability of cancer cells, its characterization is essential to fully understand the complexity of cancer biology, improve tumor classification, and ultimately advance cancer patient management and treatment. A plethora of methods have been devised to analyze and quantify DNA methylation alterations. Several of the early-developed methods relied on the use of methylation-sensitive restriction enzymes, whose activity depends on the methylation status of their recognition sequences. Among these techniques, methylation-sensitive amplification length polymorphism (MS-AFLP) was developed in the early 2000s, and successfully adapted from its original gel electrophoresis fingerprinting format to a microarray format that notably increased its throughput and allowed the quantification of the methylation changes. This array-based platform interrogates over 9500 independent loci putatively amplified by the MS-AFLP technique, corresponding to the NotI sites mapped throughout the human genome.

Genetic Structures of Copy Number Variants Revealed by Genotyping Single Sperm

PubMed Central

Luo, Minjie; Cui, Xiangfeng; Fredman, David; Brookes, Anthony J.; Azaro, Marco A.; Greenawalt, Danielle M.; Hu, Guohong; Wang, Hui-Yun; Tereshchenko, Irina V.; Lin, Yong; Shentu, Yue; Gao, Richeng; Shen, Li; Li, Honghua

2009-01-01

Background Copy number variants (CNVs) occupy a significant portion of the human genome and may have important roles in meiotic recombination, human genome evolution and gene expression. Many genetic diseases may be underlain by CNVs. However, because of the presence of their multiple copies, variability in copy numbers and the diploidy of the human genome, detailed genetic structure of CNVs cannot be readily studied by available techniques. Methodology/Principal Findings Single sperm samples were used as the primary subjects for the study so that CNV haplotypes in the sperm donors could be studied individually. Forty-eight CNVs characterized in a previous study were analyzed using a microarray-based high-throughput genotyping method after multiplex amplification. Seventeen single nucleotide polymorphisms (SNPs) were also included as controls. Two single-base variants, either allelic or paralogous, could be discriminated for all markers. Microarray data were used to resolve SNP alleles and CNV haplotypes, to quantitatively assess the numbers and compositions of the paralogous segments in each CNV haplotype. Conclusions/Significance This is the first study of the genetic structure of CNVs on a large scale. Resulting information may help understand evolution of the human genome, gain insight into many genetic processes, and discriminate between CNVs and SNPs. The highly sensitive high-throughput experimental system with haploid sperm samples as subjects may be used to facilitate detailed large-scale CNV analysis. PMID:19384415

A-MADMAN: Annotation-based microarray data meta-analysis tool

PubMed Central

Bisognin, Andrea; Coppe, Alessandro; Ferrari, Francesco; Risso, Davide; Romualdi, Chiara; Bicciato, Silvio; Bortoluzzi, Stefania

2009-01-01

Background Publicly available datasets of microarray gene expression signals represent an unprecedented opportunity for extracting genomic relevant information and validating biological hypotheses. However, the exploitation of this exceptionally rich mine of information is still hampered by the lack of appropriate computational tools, able to overcome the critical issues raised by meta-analysis. Results This work presents A-MADMAN, an open source web application which allows the retrieval, annotation, organization and meta-analysis of gene expression datasets obtained from Gene Expression Omnibus. A-MADMAN addresses and resolves several open issues in the meta-analysis of gene expression data. Conclusion A-MADMAN allows i) the batch retrieval from Gene Expression Omnibus and the local organization of raw data files and of any related meta-information, ii) the re-annotation of samples to fix incomplete, or otherwise inadequate, metadata and to create user-defined batches of data, iii) the integrative analysis of data obtained from different Affymetrix platforms through custom chip definition files and meta-normalization. Software and documentation are available on-line at . PMID:19563634

The FDA's Experience with Emerging Genomics Technologies-Past, Present, and Future.

PubMed

Xu, Joshua; Thakkar, Shraddha; Gong, Binsheng; Tong, Weida

2016-07-01

The rapid advancement of emerging genomics technologies and their application for assessing safety and efficacy of FDA-regulated products require a high standard of reliability and robustness supporting regulatory decision-making in the FDA. To facilitate the regulatory application, the FDA implemented a novel data submission program, Voluntary Genomics Data Submission (VGDS), and also to engage the stakeholders. As part of the endeavor, for the past 10 years, the FDA has led an international consortium of regulatory agencies, academia, pharmaceutical companies, and genomics platform providers, which was named MicroArray Quality Control Consortium (MAQC), to address issues such as reproducibility, precision, specificity/sensitivity, and data interpretation. Three projects have been completed so far assessing these genomics technologies: gene expression microarrays, whole genome genotyping arrays, and whole transcriptome sequencing (i.e., RNA-seq). The resultant studies provide the basic parameters for fit-for-purpose application of these new data streams in regulatory environments, and the solutions have been made available to the public through peer-reviewed publications. The latest MAQC project is also called the SEquencing Quality Control (SEQC) project focused on next-generation sequencing. Using reference samples with built-in controls, SEQC studies have demonstrated that relative gene expression can be measured accurately and reliably across laboratories and RNA-seq platforms. Besides prediction performance comparable to microarrays in clinical settings and safety assessments, RNA-seq is shown to have better sensitivity for low expression and reveal novel transcriptomic features. Future effort of MAQC will be focused on quality control of whole genome sequencing and targeted sequencing.

The FDA’s Experience with Emerging Genomics Technologies—Past, Present, and Future

PubMed Central

Xu, Joshua; Thakkar, Shraddha; Gong, Binsheng; Tong, Weida

2016-01-01

The rapid advancement of emerging genomics technologies and their application for assessing safety and efficacy of FDA-regulated products require a high standard of reliability and robustness supporting regulatory decision-making in the FDA. To facilitate the regulatory application, the FDA implemented a novel data submission program, Voluntary Genomics Data Submission (VGDS), and also to engage the stakeholders. As part of the endeavor, for the past 10 years, the FDA has led an international consortium of regulatory agencies, academia, pharmaceutical companies, and genomics platform providers, which was named MicroArray Quality Control Consortium (MAQC), to address issues such as reproducibility, precision, specificity/sensitivity, and data interpretation. Three projects have been completed so far assessing these genomics technologies: gene expression microarrays, whole genome genotyping arrays, and whole transcriptome sequencing (i.e., RNA-seq). The resultant studies provide the basic parameters for fit-for-purpose application of these new data streams in regulatory environments, and the solutions have been made available to the public through peer-reviewed publications. The latest MAQC project is also called the SEquencing Quality Control (SEQC) project focused on next-generation sequencing. Using reference samples with built-in controls, SEQC studies have demonstrated that relative gene expression can be measured accurately and reliably across laboratories and RNA-seq platforms. Besides prediction performance comparable to microarrays in clinical settings and safety assessments, RNA-seq is shown to have better sensitivity for low expression and reveal novel transcriptomic features. Future effort of MAQC will be focused on quality control of whole genome sequencing and targeted sequencing. PMID:27116022

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.

ST2249-MRSA-III: a second major recombinant methicillin-resistant Staphylococcus aureus clone causing healthcare infection in the 1970s.

PubMed

Nimmo, G R; Steen, J A; Monecke, S; Ehricht, R; Slickers, P; Thomas, J C; Appleton, S; Goering, R V; Robinson, D A; Coombs, G W

2015-05-01

Typing of healthcare-associated methicillin-resistant Staphylococcus aureus (MRSA) from Australia in the 1970s revealed a novel clone, ST2249-MRSA-III (CC45), present from 1973 to 1979. This clone was present before the Australian epidemic caused by the recombinant clone, ST239-MRSA-III. This study aimed to characterize the genome of ST2249-MRSA-III to establish its relationship to other MRSA clones. DNA microarray analysis was conducted and a draft genome sequence of ST2249 was obtained. The recombinant structure of the ST2249 genome was revealed by comparisons to publicly available ST239 and ST45 genomes. Microarray analysis of genomic DNA of 13 ST2249 isolates showed gross similarities with the ST239 chromosome in a segment around the origin of replication and with ST45 for the remainder of the chromosome. Recombination breakpoints were precisely determined by the changing pattern of nucleotide polymorphisms in the genome sequence of ST2249 isolate SK1585 compared with ST239 and ST45. One breakpoint was identified to the right of oriC, between sites 1014 and 1065 of the gene D484_00045. Another was identified to the left of oriC, between sites 1185 and 1248 of D484_01632. These results indicate that ST2249 inherited approximately 35.3% of its chromosome from an ST239-like parent and 64.7% from an ST45-like parent. ST2249-MRSA-III resulted from a major recombination between parents that resemble ST239 and ST45. Although only limited Australian archival material is available, the oldest extant isolate of ST2249 predates the oldest Australian isolate of ST239 by 3 years. It is therefore plausible that these two recombinant clones were introduced into Australia separately. Copyright © 2015 European Society of Clinical Microbiology and Infectious Diseases. Published by Elsevier Ltd. All rights reserved.

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

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.

Molecular Genetics Information System (MOLGENIS): alternatives in developing local experimental genomics databases.

PubMed

Swertz, Morris A; De Brock, E O; Van Hijum, Sacha A F T; De Jong, Anne; Buist, Girbe; Baerends, Richard J S; Kok, Jan; Kuipers, Oscar P; Jansen, Ritsert C

2004-09-01

Genomic research laboratories need adequate infrastructure to support management of their data production and research workflow. But what makes infrastructure adequate? A lack of appropriate criteria makes any decision on buying or developing a system difficult. Here, we report on the decision process for the case of a molecular genetics group establishing a microarray laboratory. Five typical requirements for experimental genomics database systems were identified: (i) evolution ability to keep up with the fast developing genomics field; (ii) a suitable data model to deal with local diversity; (iii) suitable storage of data files in the system; (iv) easy exchange with other software; and (v) low maintenance costs. The computer scientists and the researchers of the local microarray laboratory considered alternative solutions for these five requirements and chose the following options: (i) use of automatic code generation; (ii) a customized data model based on standards; (iii) storage of datasets as black boxes instead of decomposing them in database tables; (iv) loosely linking to other programs for improved flexibility; and (v) a low-maintenance web-based user interface. Our team evaluated existing microarray databases and then decided to build a new system, Molecular Genetics Information System (MOLGENIS), implemented using code generation in a period of three months. This case can provide valuable insights and lessons to both software developers and a user community embarking on large-scale genomic projects. http://www.molgenis.nl

Enhancing Results of Microarray Hybridizations Through Microagitation

PubMed Central

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

2003-01-01

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

Line differences in Cor/Lea and fructan biosynthesis-related gene transcript accumulation are related to distinct freezing tolerance levels in synthetic wheat hexaploids.

PubMed

Yokota, Hirokazu; Iehisa, Julio C M; Shimosaka, Etsuo; Takumi, Shigeo

2015-03-15

In common wheat, cultivar differences in freezing tolerance are considered to be mainly due to allelic differences at two major loci controlling freezing tolerance. One of the two loci, Fr-2, is coincident with a cluster of genes encoding C-repeat binding factors (CBFs), which induce downstream Cor/Lea genes during cold acclimation. Here, we conducted microarray analysis to study comprehensive changes in gene expression profile under long-term low-temperature (LT) treatment and to identify other LT-responsive genes related to cold acclimation in leaves of seedlings and crown tissues of a synthetic hexaploid wheat line. The microarray analysis revealed marked up-regulation of a number of Cor/Lea genes and fructan biosynthesis-related genes under the long-term LT treatment. For validation of the microarray data, we selected four synthetic wheat lines that contain the A and B genomes from the tetraploid wheat cultivar Langdon and the diverse D genomes originating from different Aegilops tauschii accessions with distinct levels of freezing tolerance after cold acclimation. Quantitative RT-PCR showed increased transcript levels of the Cor/Lea, CBF, and fructan biosynthesis-related genes in more freezing-tolerant lines than in sensitive lines. After a 14-day LT treatment, a significant difference in fructan accumulation was observed among the four lines. Therefore, the fructan biosynthetic pathway is associated with cold acclimation in development of wheat freezing tolerance and is another pathway related to diversity in freezing tolerance, in addition to the CBF-mediated Cor/Lea expression pathway. Copyright © 2014 Elsevier GmbH. All rights reserved.

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 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.

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

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

Genomics of compositae weeds: EST libraries, microarrays, and evidence of introgression

USDA-ARS?s Scientific Manuscript database

• Premise of Study: Weeds cause considerable environmental and economic damage. However, genomic characterization of weeds has lagged behind that of model plants and crop species. Here we report on the development of genomic tools and resources for 11 weeds from the Compositae family that can serve ...

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...

Microarray Genomic Systems Development

DTIC Science & Technology

2008-06-01

11 species), Escherichia coli TOP10 (7 strains), and Geobacillus stearothermophilus . Using standard molecular biology methods, we isolated genomic...comparisons. Results: Different species of bacteria, including Escherichia coli, Bacillus bacteria, and Geobacillus stearothermophilus produce qualitatively...oligonucleotides to labelled genomic DNA from a set of test samples, including eleven Bacillus species, Geobacillus stearothermophilus , and seven Escherichia

Genome Consortium for Active Teaching: Meeting the Goals of BIO2010

ERIC Educational Resources Information Center

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…

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.

Optimization of cDNA microarrays procedures using criteria that do not rely on external standards.

PubMed

Bruland, Torunn; Anderssen, Endre; Doseth, Berit; Bergum, Hallgeir; Beisvag, Vidar; Laegreid, Astrid

2007-10-18

The measurement of gene expression using microarray technology is a complicated process in which a large number of factors can be varied. Due to the lack of standard calibration samples such as are used in traditional chemical analysis it may be a problem to evaluate whether changes done to the microarray procedure actually improve the identification of truly differentially expressed genes. The purpose of the present work is to report the optimization of several steps in the microarray process both in laboratory practices and in data processing using criteria that do not rely on external standards. We performed a cDNA microarry experiment including RNA from samples with high expected differential gene expression termed "high contrasts" (rat cell lines AR42J and NRK52E) compared to self-self hybridization, and optimized a pipeline to maximize the number of genes found to be differentially expressed in the "high contrasts" RNA samples by estimating the false discovery rate (FDR) using a null distribution obtained from the self-self experiment. The proposed high-contrast versus self-self method (HCSSM) requires only four microarrays per evaluation. The effects of blocking reagent dose, filtering, and background corrections methodologies were investigated. In our experiments a dose of 250 ng LNA (locked nucleic acid) dT blocker, no background correction and weight based filtering gave the largest number of differentially expressed genes. The choice of background correction method had a stronger impact on the estimated number of differentially expressed genes than the choice of filtering method. Cross platform microarray (Illumina) analysis was used to validate that the increase in the number of differentially expressed genes found by HCSSM was real. The results show that HCSSM can be a useful and simple approach to optimize microarray procedures without including external standards. Our optimizing method is highly applicable to both long oligo-probe microarrays which have become commonly used for well characterized organisms such as man, mouse and rat, as well as to cDNA microarrays which are still of importance for organisms with incomplete genome sequence information such as many bacteria, plants and fish.

Optimization of cDNA microarrays procedures using criteria that do not rely on external standards

PubMed Central

Bruland, Torunn; Anderssen, Endre; Doseth, Berit; Bergum, Hallgeir; Beisvag, Vidar; Lægreid, Astrid

2007-01-01

Background The measurement of gene expression using microarray technology is a complicated process in which a large number of factors can be varied. Due to the lack of standard calibration samples such as are used in traditional chemical analysis it may be a problem to evaluate whether changes done to the microarray procedure actually improve the identification of truly differentially expressed genes. The purpose of the present work is to report the optimization of several steps in the microarray process both in laboratory practices and in data processing using criteria that do not rely on external standards. Results We performed a cDNA microarry experiment including RNA from samples with high expected differential gene expression termed "high contrasts" (rat cell lines AR42J and NRK52E) compared to self-self hybridization, and optimized a pipeline to maximize the number of genes found to be differentially expressed in the "high contrasts" RNA samples by estimating the false discovery rate (FDR) using a null distribution obtained from the self-self experiment. The proposed high-contrast versus self-self method (HCSSM) requires only four microarrays per evaluation. The effects of blocking reagent dose, filtering, and background corrections methodologies were investigated. In our experiments a dose of 250 ng LNA (locked nucleic acid) dT blocker, no background correction and weight based filtering gave the largest number of differentially expressed genes. The choice of background correction method had a stronger impact on the estimated number of differentially expressed genes than the choice of filtering method. Cross platform microarray (Illumina) analysis was used to validate that the increase in the number of differentially expressed genes found by HCSSM was real. Conclusion The results show that HCSSM can be a useful and simple approach to optimize microarray procedures without including external standards. Our optimizing method is highly applicable to both long oligo-probe microarrays which have become commonly used for well characterized organisms such as man, mouse and rat, as well as to cDNA microarrays which are still of importance for organisms with incomplete genome sequence information such as many bacteria, plants and fish. PMID:17949480

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

Genomic profiling using array comparative genomic hybridization define distinct subtypes of diffuse large b-cell lymphoma: a review of the literature

PubMed Central

2012-01-01

Diffuse large B-cell lymphoma (DLBCL) is the most common type of non-Hodgkin Lymphoma comprising of greater than 30% of adult non-Hodgkin Lymphomas. DLBCL represents a diverse set of lymphomas, defined as diffuse proliferation of large B lymphoid cells. Numerous cytogenetic studies including karyotypes and fluorescent in situ hybridization (FISH), as well as morphological, biological, clinical, microarray and sequencing technologies have attempted to categorize DLBCL into morphological variants, molecular and immunophenotypic subgroups, as well as distinct disease entities. Despite such efforts, most lymphoma remains undistinguishable and falls into DLBCL, not otherwise specified (DLBCL-NOS). The advent of microarray-based studies (chromosome, RNA, gene expression, etc) has provided a plethora of high-resolution data that could potentially facilitate the finer classification of DLBCL. This review covers the microarray data currently published for DLBCL. We will focus on these types of data; 1) array based CGH; 2) classical CGH; and 3) gene expression profiling studies. The aims of this review were three-fold: (1) to catalog chromosome loci that are present in at least 20% or more of distinct DLBCL subtypes; a detailed list of gains and losses for different subtypes was generated in a table form to illustrate specific chromosome loci affected in selected subtypes; (2) to determine common and distinct copy number alterations among the different subtypes and based on this information, characteristic and similar chromosome loci for the different subtypes were depicted in two separate chromosome ideograms; and, (3) to list re-classified subtypes and those that remained indistinguishable after review of the microarray data. To the best of our knowledge, this is the first effort to compile and review available literatures on microarray analysis data and their practical utility in classifying DLBCL subtypes. Although conventional cytogenetic methods such as Karyotypes and FISH have played a major role in classification schemes of lymphomas, better classification models are clearly needed to further understanding the biology, disease outcome and therapeutic management of DLBCL. In summary, microarray data reviewed here can provide better subtype specific classifications models for DLBCL. PMID:22967872

Strategies to explore functional genomics data sets in NCBI's GEO database.

PubMed

Wilhite, Stephen E; Barrett, Tanya

2012-01-01

The Gene Expression Omnibus (GEO) database is a major repository that stores high-throughput functional genomics data sets that are generated using both microarray-based and sequence-based technologies. Data sets are submitted to GEO primarily by researchers who are publishing their results in journals that require original data to be made freely available for review and analysis. In addition to serving as a public archive for these data, GEO has a suite of tools that allow users to identify, analyze, and visualize data relevant to their specific interests. These tools include sample comparison applications, gene expression profile charts, data set clusters, genome browser tracks, and a powerful search engine that enables users to construct complex queries.

Strategies to Explore Functional Genomics Data Sets in NCBI’s GEO Database

PubMed Central

Wilhite, Stephen E.; Barrett, Tanya

2012-01-01

The Gene Expression Omnibus (GEO) database is a major repository that stores high-throughput functional genomics data sets that are generated using both microarray-based and sequence-based technologies. Data sets are submitted to GEO primarily by researchers who are publishing their results in journals that require original data to be made freely available for review and analysis. In addition to serving as a public archive for these data, GEO has a suite of tools that allow users to identify, analyze and visualize data relevant to their specific interests. These tools include sample comparison applications, gene expression profile charts, data set clusters, genome browser tracks, and a powerful search engine that enables users to construct complex queries. PMID:22130872

Transcriptomic profile of host response in mouse brain after exposure to plant toxin abrin.

PubMed

Bhaskar, A S Bala; Gupta, Nimesh; Rao, P V Lakshmana

2012-09-04

Abrin toxin is a plant glycoprotein, which is similar in structure and properties to ricin and is obtained from the seeds of Abrus precatorius (jequirity bean). Abrin is highly toxic, with an estimated human fatal dose of 0.1-1 μg/kg, and has caused death after accidental and intentional poisoning. Abrin is a potent biological toxin warfare agent. There are no chemical antidotes available against the toxin. Neurological symptoms like delirium, hallucinations, reduced consciousness and generalized seizures were reported in human poisoning cases. Death of a patient with symptoms of acute demyelinating encephalopathy with gastrointestinal bleeding due to ingestion of abrin seeds was reported in India. The aim of this study was to examine both dose and time-dependent transcriptional responses induced by abrin in the adult mouse brain. Mice (n=6) were exposed to 1 and 2 LD50 (2.83 and 5.66 μg/kg respectively) dose of abrin by intraperitoneal route and observed over 3 days. A subset of animals (n=3) were sacrificed at 1 and 2 day intervals for microarray and histopathology analysis. None of the 2 LD50 exposed animals survived till 3 days. The histopathological analysis showed the severe damage in brain and the infiltration of inflammatory cells in a dose and time dependent manner. The abrin exposure resulted in the induction of rapid immune and inflammatory response in brain. Clinical biochemistry parameters like lactate dehydrogenase, aspartate aminotransferase, urea and creatinine showed significant increase at 2-day 2 LD50 exposure. The whole genome microarray data revealed the significant regulation of various pathways like MAPK pathway, cytokine-cytokine receptor interaction, calcium signaling pathway, Jak-STAT signaling pathway and natural killer cell mediated toxicity. The comparison of differential gene expression at both the doses showed dose dependent effects of abrin toxicity. The real-time qRT-PCR analysis of selected genes supported the microarray data. This is the first report on host-gene response using whole genome microarray in an animal model after abrin exposure. The data generated provides leads for developing suitable medical counter measures against abrin poisoning. Copyright © 2012 Elsevier Ireland Ltd. All rights reserved.

Use of homologous and heterologous gene expression profiling tools to characterize transcription dynamics during apple fruit maturation and ripening

PubMed Central

2010-01-01

Background Fruit development, maturation and ripening consists of a complex series of biochemical and physiological changes that in climacteric fruits, including apple and tomato, are coordinated by the gaseous hormone ethylene. These changes lead to final fruit quality and understanding of the functional machinery underlying these processes is of both biological and practical importance. To date many reports have been made on the analysis of gene expression in apple. In this study we focused our investigation on the role of ethylene during apple maturation, specifically comparing transcriptomics of normal ripening with changes resulting from application of the hormone receptor competitor 1-Methylcyclopropene. Results To gain insight into the molecular process regulating ripening in apple, and to compare to tomato (model species for ripening studies), we utilized both homologous and heterologous (tomato) microarray to profile transcriptome dynamics of genes involved in fruit development and ripening, emphasizing those which are ethylene regulated. The use of both types of microarrays facilitated transcriptome comparison between apple and tomato (for the later using data previously published and available at the TED: tomato expression database) and highlighted genes conserved during ripening of both species, which in turn represent a foundation for further comparative genomic studies. The cross-species analysis had the secondary aim of examining the efficiency of heterologous (specifically tomato) microarray hybridization for candidate gene identification as related to the ripening process. The resulting transcriptomics data revealed coordinated gene expression during fruit ripening of a subset of ripening-related and ethylene responsive genes, further facilitating the analysis of ethylene response during fruit maturation and ripening. Conclusion Our combined strategy based on microarray hybridization enabled transcriptome characterization during normal climacteric apple ripening, as well as definition of ethylene-dependent transcriptome changes. Comparison with tomato fruit maturation and ethylene responsive transcriptome activity facilitated identification of putative conserved orthologous ripening-related genes, which serve as an initial set of candidates for assessing conservation of gene activity across genomes of fruit bearing plant species. PMID:20973957

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

PubMed Central

2011-01-01

Background Sporadic amyotrophic lateral sclerosis (sALS) is a motor neuron disease with poorly understood etiology. Results of gene expression profiling studies of whole blood from ALS patients have not been validated and are difficult to relate to ALS pathogenesis because gene expression profiles depend on the relative abundance of the different cell types present in whole blood. We conducted microarray analyses using Agilent Human Whole Genome 4 × 44k Arrays on a more homogeneous cell population, namely purified peripheral blood lymphocytes (PBLs), from ALS patients and healthy controls to identify molecular signatures possibly relevant to ALS pathogenesis. Methods Differentially expressed genes were determined by LIMMA (Linear Models for MicroArray) and SAM (Significance Analysis of Microarrays) analyses. The SAFE (Significance Analysis of Function and Expression) procedure was used to identify molecular pathway perturbations. Proteasome inhibition assays were conducted on cultured peripheral blood mononuclear cells (PBMCs) from ALS patients to confirm alteration of the Ubiquitin/Proteasome System (UPS). Results For the first time, using SAFE in a global gene ontology analysis (gene set size 5-100), we show significant perturbation of the KEGG (Kyoto Encyclopedia of Genes and Genomes) ALS pathway of motor neuron degeneration in PBLs from ALS patients. This was the only KEGG disease pathway significantly upregulated among 25, and contributing genes, including SOD1, represented 54% of the encoded proteins or protein complexes of the KEGG ALS pathway. Further SAFE analysis, including gene set sizes >100, showed that only neurodegenerative diseases (4 out of 34 disease pathways) including ALS were significantly upregulated. Changes in UBR2 expression correlated inversely with time since onset of disease and directly with ALSFRS-R, implying that UBR2 was increased early in the course of ALS. Cultured PBMCs from ALS patients accumulated more ubiquitinated proteins than PBMCs from healthy controls in a serum-dependent manner confirming changes in this pathway. Conclusions Our study indicates that PBLs from sALS patients are strong responders to systemic signals or local signals acquired by cell trafficking, representing changes in gene expression similar to those present in brain and spinal cord of sALS patients. PBLs may provide a useful means to study ALS pathogenesis. PMID:22027401

6.0 K microarray reveals differential transcriptomic responses in the dinoflagellate Prorocentrum minimum exposed to polychlorinated biphenyl (PCB).

PubMed

Wang, Hui; Guo, Ruoyu; Ki, Jang-Seu

2018-03-01

Endocrine disrupting chemicals (EDCs) have toxic effects on algae; however, their molecular genomic responses have not been sufficiently elucidated. Here, we evaluated genome-scaled responses of the dinoflagellate alga Prorocentrum minimum exposed to an EDC, polychlorinated biphenyl (PCB), using a 6.0 K microarray. Based on two-fold change cut-off, we identified that 609 genes (∼10.2%) responded to the PCB treatment. KEGG pathway analysis showed that differentially expressed genes (DEGs) were related to ribosomes, biosynthesis of amino acids, spliceosomes, and cellular processes. Many DEGs were involved in cell cycle progression, apoptosis, signal transduction, ion binding, and cellular transportation. In contrast, only a few genes related to photosynthesis and oxidative stress were expressed in response to PCB exposure. This was supported by that fact that there were no obvious changes in the photosynthetic efficiency and reactive oxygen species (ROS) production. These results suggest that PCB might not cause chloroplast and oxidative damage, but could lead to cell cycle arrest and apoptosis. In addition, various signal transduction and transport pathways might be disrupted in the cells, which could further contribute to cell death. These results expand the genomic understanding of the effects of EDCs on this dinoflagellate protist. Copyright © 2017 Elsevier Ltd. All rights reserved.

Ultrafiltration and Microarray for Detection of Microbial Source Tracking Marker and Pathogen Genes in Riverine and Marine Systems

PubMed Central

Li, Xiang; Harwood, Valerie J.; Nayak, Bina

2016-01-01

Pathogen identification and microbial source tracking (MST) to identify sources of fecal pollution improve evaluation of water quality. They contribute to improved assessment of human health risks and remediation of pollution sources. An MST microarray was used to simultaneously detect genes for multiple pathogens and indicators of fecal pollution in freshwater, marine water, sewage-contaminated freshwater and marine water, and treated wastewater. Dead-end ultrafiltration (DEUF) was used to concentrate organisms from water samples, yielding a recovery efficiency of >95% for Escherichia coli and human polyomavirus. Whole-genome amplification (WGA) increased gene copies from ultrafiltered samples and increased the sensitivity of the microarray. Viruses (adenovirus, bocavirus, hepatitis A virus, and human polyomaviruses) were detected in sewage-contaminated samples. Pathogens such as Legionella pneumophila, Shigella flexneri, and Campylobacter fetus were detected along with genes conferring resistance to aminoglycosides, beta-lactams, and tetracycline. Nonmetric dimensional analysis of MST marker genes grouped sewage-spiked freshwater and marine samples with sewage and apart from other fecal sources. The sensitivity (percent true positives) of the microarray probes for gene targets anticipated in sewage was 51 to 57% and was lower than the specificity (percent true negatives; 79 to 81%). A linear relationship between gene copies determined by quantitative PCR and microarray fluorescence was found, indicating the semiquantitative nature of the MST microarray. These results indicate that ultrafiltration coupled with WGA provides sufficient nucleic acids for detection of viruses, bacteria, protozoa, and antibiotic resistance genes by the microarray in applications ranging from beach monitoring to risk assessment. PMID:26729716

B-acute lymphoblastic leukemia and cystinuria in a patient with duplication 22q11.21 detected by chromosomal microarray analysis.

PubMed

Chang, Vivian Y; Quintero-Rivera, Fabiola; Baldwin, Erin E; Woo, Kathy; Martinez-Agosto, Julian A; Fu, Cecilia; Gomperts, Brigitte N

2011-03-01

Duplication 22q11.2 syndrome is the result of a microduplication of the same chromosomal region that is deleted in DiGeorge and Velocardiofacial syndromes. We describe a patient with dysmorphic features who was diagnosed with pre-B acute lymphoblastic leukemia, and developed cystinuria and pancreatitis during treatment. Duplication 22q11.2 has not been previously described in association with hematologic abnormalities. Chromosomal microarray technology was used to diagnose duplication 22q11.2 syndrome. In this era of advanced genomics, this technology has become an important method for helping to determine the molecular basis of diseases, best treatments and ultimately patient outcomes. Copyright © 2010 Wiley-Liss, Inc.

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

EPA Science Inventory

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

Cell cycle arrest and gene expression profiling of testis in mice exposed to fluoride.

PubMed

Su, Kai; Sun, Zilong; Niu, Ruiyan; Lei, Ying; Cheng, Jing; Wang, Jundong

2017-05-01

Exposure to fluoride results in low reproductive capacity; however, the mechanism underlying the impact of fluoride on male productive system still remains obscure. To assess the potential toxicity in testis of mice administrated with fluoride, global genome microarray and real-time PCR were performed to detect and identify the altered transcriptions. The results revealed that 763 differentially expressed genes were identified, including 330 up-regulated and 433 down-regulated genes, which were involved in spermatogenesis, apoptosis, DNA damage, DNA replication, and cell differentiation. Twelve differential expressed genes were selected to confirm the microarray results using real-time PCR, and the result kept the same tendency with that of microarray. Furthermore, compared with the control group, more apoptotic spermatogenic cells were observed in the fluoride group, and the spermatogonium were markedly increased in S phase and decreased in G2/M phase by fluoride. Our findings suggested global genome microarray provides an insight into the reproductive toxicity induced by fluoride, and several important biological clues for further investigations. © 2016 Wiley Periodicals, Inc. Environ Toxicol 32: 1558-1565, 2017. © 2016 Wiley Periodicals, Inc.

ArrayExpress update--trends in database growth and links to data analysis tools.

PubMed

Rustici, Gabriella; Kolesnikov, Nikolay; Brandizi, Marco; Burdett, Tony; Dylag, Miroslaw; Emam, Ibrahim; Farne, Anna; Hastings, Emma; Ison, Jon; Keays, Maria; Kurbatova, Natalja; Malone, James; Mani, Roby; Mupo, Annalisa; Pedro Pereira, Rui; Pilicheva, Ekaterina; Rung, Johan; Sharma, Anjan; Tang, Y Amy; Ternent, Tobias; Tikhonov, Andrew; Welter, Danielle; Williams, Eleanor; Brazma, Alvis; Parkinson, Helen; Sarkans, Ugis

2013-01-01

The ArrayExpress Archive of Functional Genomics Data (http://www.ebi.ac.uk/arrayexpress) is one of three international functional genomics public data repositories, alongside the Gene Expression Omnibus at NCBI and the DDBJ Omics Archive, supporting peer-reviewed publications. It accepts data generated by sequencing or array-based technologies and currently contains data from almost a million assays, from over 30 000 experiments. The proportion of sequencing-based submissions has grown significantly over the last 2 years and has reached, in 2012, 15% of all new data. All data are available from ArrayExpress in MAGE-TAB format, which allows robust linking to data analysis and visualization tools, including Bioconductor and GenomeSpace. Additionally, R objects, for microarray data, and binary alignment format files, for sequencing data, have been generated for a significant proportion of ArrayExpress data.

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.

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

Diseases and Molecular Diagnostics: A Step Closer to Precision Medicine.

PubMed

Dwivedi, Shailendra; Purohit, Purvi; Misra, Radhieka; Pareek, Puneet; Goel, Apul; Khattri, Sanjay; Pant, Kamlesh Kumar; Misra, Sanjeev; Sharma, Praveen

2017-10-01

The current advent of molecular technologies together with a multidisciplinary interplay of several fields led to the development of genomics, which concentrates on the detection of pathogenic events at the genome level. The structural and functional genomics approaches have now pinpointed the technical challenge in the exploration of disease-related genes and the recognition of their structural alterations or elucidation of gene function. Various promising technologies and diagnostic applications of structural genomics are currently preparing a large database of disease-genes, genetic alterations etc., by mutation scanning and DNA chip technology. Further the functional genomics also exploring the expression genetics (hybridization-, PCR- and sequence-based technologies), two-hybrid technology, next generation sequencing with Bioinformatics and computational biology. Advances in microarray "chip" technology as microarrays have allowed the parallel analysis of gene expression patterns of thousands of genes simultaneously. Sequence information collected from the genomes of many individuals is leading to the rapid discovery of single nucleotide polymorphisms or SNPs. Further advances of genetic engineering have also revolutionized immunoassay biotechnology via engineering of antibody-encoding genes and the phage display technology. The Biotechnology plays an important role in the development of diagnostic assays in response to an outbreak or critical disease response need. However, there is also need to pinpoint various obstacles and issues related to the commercialization and widespread dispersal of genetic knowledge derived from the exploitation of the biotechnology industry and the development and marketing of diagnostic services. Implementation of genetic criteria for patient selection and individual assessment of the risks and benefits of treatment emerges as a major challenge to the pharmaceutical industry. Thus this field is revolutionizing current era and further it may open new vistas in the field of disease management.

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.

MADGE: scalable distributed data management software for cDNA microarrays.

PubMed

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

2003-01-01

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

Whole mitochondrial genome screening in maternally inherited non-syndromic hearing impairment using a microarray resequencing mitochondrial DNA chip.

PubMed

Lévêque, Marianne; Marlin, Sandrine; Jonard, Laurence; Procaccio, Vincent; Reynier, Pascal; Amati-Bonneau, Patrizia; Baulande, Sylvain; Pierron, Denis; Lacombe, Didier; Duriez, Françoise; Francannet, Christine; Mom, Thierry; Journel, Hubert; Catros, Hélène; Drouin-Garraud, Valérie; Obstoy, Marie-Françoise; Dollfus, Hélène; Eliot, Marie-Madeleine; Faivre, Laurence; Duvillard, Christian; Couderc, Remy; Garabedian, Eréa-Noël; Petit, Christine; Feldmann, Delphine; Denoyelle, Françoise

2007-11-01

Mitochondrial DNA (mtDNA) mutations have been implicated in non-syndromic hearing loss either as primary or as predisposing factors. As only a part of the mitochondrial genome is usually explored in deafness, its prevalence is probably under-estimated. Among 1350 families with non-syndromic sensorineural hearing loss collected through a French collaborative network, we selected 29 large families with a clear maternal lineage and screened them for known mtDNA mutations in 12S rRNA, tRNASer(UCN) and tRNALeu(UUR) genes. When no mutation could be identified, a whole mitochondrial genome screening was performed, using a microarray resequencing chip: the MitoChip version 2.0 developed by Affymetrix Inc. Known mtDNA mutations was found in nine of the 29 families, which are described in the article: five with A1555G, two with the T7511C, one with 7472insC and one with A3243G mutation. In the remaining 20 families, the resequencing Mitochip detected 258 mitochondrial homoplasmic variants and 107 potentially heteroplasmic variants. Controls were made by direct sequencing on selected fragments and showed a high sensibility of the MitoChip but a low specificity, especially for heteroplasmic variations. An original analysis on the basis of species conservation, frequency and phylogenetic investigation was performed to select the more probably pathogenic variants. The entire genome analysis allowed us to identify five additional families with a putatively pathogenic mitochondrial variant: T669C, C1537T, G8078A, G12236A and G15077A. These results indicate that the new MitoChip platform is a rapid and valuable tool for identification of new mtDNA mutations in deafness.

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

A functional genomics tool for the Pacific bluefin tuna: Development of a 44K oligonucleotide microarray from whole-genome sequencing data for global transcriptome analysis.

PubMed

Yasuike, Motoshige; Fujiwara, Atushi; Nakamura, Yoji; Iwasaki, Yuki; Nishiki, Issei; Sugaya, Takuma; Shimizu, Akio; Sano, Motohiko; Kobayashi, Takanori; Ototake, Mitsuru

2016-02-01

Bluefin tunas are one of the most important fishery resources worldwide. Because of high market values, bluefin tuna farming has been rapidly growing during recent years. At present, the most common form of the tuna farming is based on the stocking of wild-caught fish. Therefore, concerns have been raised about the negative impact of the tuna farming on wild stocks. Recently, the Pacific bluefin tuna (PBT), Thunnus orientalis, has succeeded in completing the reproduction cycle under aquaculture conditions, but production bottlenecks remain to be solved because of very little biological information on bluefin tunas. Functional genomics approaches promise to rapidly increase our knowledge on biological processes in the bluefin tuna. Here, we describe the development of the first 44K PBT oligonucleotide microarray (oligo-array), based on whole-genome shotgun (WGS) sequencing and large-scale expressed sequence tags (ESTs) data. In addition, we also introduce an initial 44K PBT oligo-array experiment using in vitro grown peripheral blood leukocytes (PBLs) stimulated with immunostimulants such as lipopolysaccharide (LPS: a cell wall component of Gram-negative bacteria) or polyinosinic:polycytidylic acid (poly I:C: a synthetic mimic of viral infection). This pilot 44K PBT oligo-array analysis successfully addressed distinct immune processes between LPS- and poly I:C- stimulated PBLs. Thus, we expect that this oligo-array will provide an excellent opportunity to analyze global gene expression profiles for a better understanding of diseases and stress, as well as for reproduction, development and influence of nutrition on tuna aquaculture production. Copyright © 2015 The Authors. Published by Elsevier B.V. All rights reserved.

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.

Evolutionary genomics of Staphylococcus aureus: insights into the origin of methicillin-resistant strains and the toxic shock syndrome epidemic.

PubMed

Fitzgerald, J R; Sturdevant, D E; Mackie, S M; Gill, S R; Musser, J M

2001-07-17

An emerging theme in medical microbiology is that extensive variation exists in gene content among strains of many pathogenic bacterial species. However, this topic has not been investigated on a genome scale with strains recovered from patients with well-defined clinical conditions. Staphylococcus aureus is a major human pathogen and also causes economically important infections in cows and sheep. A DNA microarray representing >90% of the S. aureus genome was used to characterize genomic diversity, evolutionary relationships, and virulence gene distribution among 36 strains of divergent clonal lineages, including methicillin-resistant strains and organisms causing toxic shock syndrome. Genetic variation in S. aureus is very extensive, with approximately 22% of the genome comprised of dispensable genetic material. Eighteen large regions of difference were identified, and 10 of these regions have genes that encode putative virulence factors or proteins mediating antibiotic resistance. We find that lateral gene transfer has played a fundamental role in the evolution of S. aureus. The mec gene has been horizontally transferred into distinct S. aureus chromosomal backgrounds at least five times, demonstrating that methicillin-resistant strains have evolved multiple independent times, rather than from a single ancestral strain. This finding resolves a long-standing controversy in S. aureus research. The epidemic of toxic shock syndrome that occurred in the 1970s was caused by a change in the host environment, rather than rapid geographic dissemination of a new hypervirulent strain. DNA microarray analysis of large samples of clinically characterized strains provides broad insights into evolution, pathogenesis, and disease emergence.

Detection of Bacillus anthracis DNA in Complex Soil and Air Samples Using Next-Generation Sequencing

PubMed Central

Be, Nicholas A.; Thissen, James B.; Gardner, Shea N.; McLoughlin, Kevin S.; Fofanov, Viacheslav Y.; Koshinsky, Heather; Ellingson, Sally R.; Brettin, Thomas S.; Jackson, Paul J.; Jaing, Crystal J.

2013-01-01

Bacillus anthracis is the potentially lethal etiologic agent of anthrax disease, and is a significant concern in the realm of biodefense. One of the cornerstones of an effective biodefense strategy is the ability to detect infectious agents with a high degree of sensitivity and specificity in the context of a complex sample background. The nature of the B. anthracis genome, however, renders specific detection difficult, due to close homology with B. cereus and B. thuringiensis. We therefore elected to determine the efficacy of next-generation sequencing analysis and microarrays for detection of B. anthracis in an environmental background. We applied next-generation sequencing to titrated genome copy numbers of B. anthracis in the presence of background nucleic acid extracted from aerosol and soil samples. We found next-generation sequencing to be capable of detecting as few as 10 genomic equivalents of B. anthracis DNA per nanogram of background nucleic acid. Detection was accomplished by mapping reads to either a defined subset of reference genomes or to the full GenBank database. Moreover, sequence data obtained from B. anthracis could be reliably distinguished from sequence data mapping to either B. cereus or B. thuringiensis. We also demonstrated the efficacy of a microbial census microarray in detecting B. anthracis in the same samples, representing a cost-effective and high-throughput approach, complementary to next-generation sequencing. Our results, in combination with the capacity of sequencing for providing insights into the genomic characteristics of complex and novel organisms, suggest that these platforms should be considered important components of a biosurveillance strategy. PMID:24039948

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

PubMed

Herold, Keith E; Rasooly, Avraham

2003-12-01

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

Functional genomic analysis of drug sensitivity pathways to guide adjuvant strategies in breast cancer

PubMed Central

Swanton, Charles; Szallasi, Zoltan; Brenton, James D; Downward, Julian

2008-01-01

The widespread introduction of high throughput RNA interference screening technology has revealed tumour drug sensitivity pathways to common cytotoxics such as paclitaxel, doxorubicin and 5-fluorouracil, targeted agents such as trastuzumab and inhibitors of AKT and Poly(ADP-ribose) polymerase (PARP) as well as endocrine therapies such as tamoxifen. Given the limited power of microarray signatures to predict therapeutic response in associative studies of small clinical trial cohorts, the use of functional genomic data combined with expression or sequence analysis of genes and microRNAs implicated in drug response in human tumours may provide a more robust method to guide adjuvant treatment strategies in breast cancer that are transferable across different expression platforms and patient cohorts. PMID:18986507

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

PubMed

Rao, Archana N; Grainger, David W

2014-04-01

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

BIOPHYSICAL PROPERTIES OF NUCLEIC ACIDS AT SURFACES RELEVANT TO MICROARRAY PERFORMANCE

PubMed Central

Rao, Archana N.; Grainger, David W.

2014-01-01

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

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.

Fabrication of high quality cDNA microarray using a small amount of cDNA.

PubMed

Park, Chan Hee; Jeong, Ha Jin; Jung, Jae Jun; Lee, Gui Yeon; Kim, Sang-Chul; Kim, Tae Soo; Yang, Sang Hwa; Chung, Hyun Cheol; Rha, Sun Young

2004-05-01

DNA microarray technology has become an essential part of biological research. It enables the genome-scale analysis of gene expression in various types of model systems. Manufacturing high quality cDNA microarrays of microdeposition type depends on some key factors including a printing device, spotting pins, glass slides, spotting solution, and humidity during spotting. UsingEthe Microgrid II TAS model printing device, this study defined the optimal conditions for producing high density, high quality cDNA microarrays with the least amount of cDNA product. It was observed that aminosilane-modified slides were superior to other types of surface modified-slides. A humidity of 30+/-3% in a closed environment and the overnight drying of the spotted slides gave the best conditions for arraying. In addition, the cDNA dissolved in 30% DMSO gave the optimal conditions for spotting compared to the 1X ArrayIt, 3X SSC and 50% DMSO. Lastly, cDNA in the concentration range of 100-300 ng/ micro l was determined to be best for arraying and post-processing. Currently, the printing system in this study yields reproducible 9000 spots with a spot size 150 mm diameter, and a 200 nm spot spacing.

'FloraArray' for screening of specific DNA probes representing the characteristics of a certain microbial community.

PubMed

Yokoi, Takahide; Kaku, Yoshiko; Suzuki, Hiroyuki; Ohta, Masayuki; Ikuta, Hajime; Isaka, Kazuichi; Sumino, Tatsuo; Wagatsuma, Masako

2007-08-01

To investigate uncharacterized microbial communities, a custom DNA microarray named 'FloraArray' was developed for screening specific probes that would represent the characteristics of a microbial community. The array was prepared by spotting 2000 plasmid DNAs from a genomic shotgun library of a sludge sample on a DNA microarray. By comparative hybridization of the array with two different samples of genomic DNA, one from the activated sludge and the other from a nonactivated sludge sample of an anaerobic ammonium oxidation (anammox) bacterial community, specific spots were visualized as a definite fluctuating profile in an MA (differential intensity ratio vs. spot intensity) plot. About 300 spots of the array accounted for the candidate probes to represent anammox reaction of the activated sludge. After sequence analysis of the probes and examination of the results of blastn searches against the reported anammox reference sequence, complete matches were found for 161 probes (58.3%) and >90% matches were found for 242 probes (87.1%). These results demonstrate that 'FloraArray' could be a useful tool for screening specific DNA molecules of unknown microbial communities.

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.

Global transcriptional analysis of psoriatic skin and blood confirms known disease-associated pathways and highlights novel genomic "hot spots" for differentially expressed genes.

PubMed

Coda, Alvin B; Icen, Murat; Smith, Jason R; Sinha, Animesh A

2012-07-01

There are major gaps in our knowledge regarding the exact mechanisms and genetic basis of psoriasis. To investigate the pathogenesis of psoriasis, gene expression in 10 skin (5 lesional, 5 nonlesional) and 11 blood (6 psoriatic, 5 nonpsoriatic) samples were examined using Affymetrix HG-U95A microarrays. We detected 535 (425 upregulated, 110 downregulated) DEGs in lesional skin at 1% false discovery rate (FDR). Combining nine microarray studies comparing lesional and nonlesional psoriatic skin, 34.5% of dysregulated genes were overlapped in multiple studies. We further identified 20 skin and 2 blood associated transcriptional "hot spots" at specified genomic locations. At 5% FDR, 11.8% skin and 10.4% blood DEGs in our study mapped to one of the 12 PSORS loci. DEGs that overlap with PSORS loci may offer prioritized targets for downstream genetic fine mapping studies. Novel DEG "hot spots" may provide new targets for defining susceptibility loci in future studies. Copyright © 2012 Elsevier Inc. All rights reserved.

Quantitative proteomic analysis in breast cancer.

PubMed

Tabchy, A; Hennessy, B T; Gonzalez-Angulo, A M; Bernstam, F M; Lu, Y; Mills, G B

2011-02-01

Much progress has recently been made in the genomic and transcriptional characterization of tumors. However, historically the characterization of cells at the protein level has suffered limitations in reproducibility, scalability and robustness. Recent technological advances have made it possible to accurately and reproducibly portray the global levels and active states of cellular proteins. Protein microarrays examine the native post-translational conformations of proteins including activated phosphorylated states, in a comprehensive high-throughput mode, and can map activated pathways and networks of proteins inside the cells. The reverse-phase protein microarray (RPPA) offers a unique opportunity to study signal transduction networks in small biological samples such as human biopsy material and can provide critical information for therapeutic decision-making and the monitoring of patients for targeted molecular medicine. By providing the key missing link to the story generated from genomic and gene expression characterization efforts, functional proteomics offer the promise of a comprehensive understanding of cancer. Several initial successes in breast cancer are showing that such information is clinically relevant. Copyright 2011 Prous Science, S.A.U. or its licensors. All rights reserved.

Characterization of a complex chromosomal rearrangement using chromosome, FISH, and microarray assays in a girl with multiple congenital abnormalities and developmental delay.

PubMed

Hemmat, Morteza; Yang, Xiaojing; Chan, Patricia; McGough, Robert A; Ross, Leslie; Mahon, Loretta W; Anguiano, Arturo L; Boris, Wang T; Elnaggar, Mohamed M; Wang, Jia-Chi J; Strom, Charles M; Boyar, Fatih Z

2014-01-01

Complex chromosomal rearrangements (CCRs) are balanced or unbalanced structural rearrangements involving three or more cytogenetic breakpoints on two or more chromosomal pairs. The phenotypic anomalies in such cases are attributed to gene disruption, superimposed cryptic imbalances in the genome, and/or position effects. We report a 14-year-old girl who presented with multiple congenital anomalies and developmental delay. Chromosome and FISH analysis indicated a highly complex chromosomal rearrangement involving three chromosomes (3, 7 and 12), seven breakpoints as a result of one inversion, two insertions, and two translocations forming three derivative chromosomes. Additionally, chromosomal microarray study (CMA) revealed two submicroscopic deletions at 3p12.3 (467 kb) and 12q13.12 (442 kb). We postulate that microdeletion within the ROBO1 gene at 3p12.3 may have played a role in the patient's developmental delay, since it has potential activity-dependent role in neurons. Additionally, factors other than genomic deletions such as loss of function or position effects may also contribute to the abnormal phenotype in our patient.

Methylation detection oligonucleotide microarray analysis: a high-resolution method for detection of CpG island methylation

PubMed Central

Kamalakaran, Sitharthan; Kendall, Jude; Zhao, Xiaoyue; Tang, Chunlao; Khan, Sohail; Ravi, Kandasamy; Auletta, Theresa; Riggs, Michael; Wang, Yun; Helland, Åslaug; Naume, Bjørn; Dimitrova, Nevenka; Børresen-Dale, Anne-Lise; Hicks, Jim; Lucito, Robert

2009-01-01

Methylation of CpG islands associated with genes can affect the expression of the proximal gene, and methylation of non-associated CpG islands correlates to genomic instability. This epigenetic modification has been shown to be important in many pathologies, from development and disease to cancer. We report the development of a novel high-resolution microarray that detects the methylation status of over 25 000 CpG islands in the human genome. Experiments were performed to demonstrate low system noise in the methodology and that the array probes have a high signal to noise ratio. Methylation measurements between different cell lines were validated demonstrating the accuracy of measurement. We then identified alterations in CpG islands, both those associated with gene promoters, as well as non-promoter-associated islands in a set of breast and ovarian tumors. We demonstrate that this methodology accurately identifies methylation profiles in cancer and in principle it can differentiate any CpG methylation alterations and can be adapted to analyze other species. PMID:19474344

Microarray analysis reveals overlapping and specific transcriptional responses to different plant hormones in rice

PubMed Central

Garg, Rohini; Tyagi, Akhilesh K.; Jain, Mukesh

2012-01-01

Hormones exert pleiotropic effects on plant growth and development throughout the life cycle. Many of these effects are mediated at molecular level via altering gene expression. In this study, we investigated the exogenous effect of plant hormones, including auxin, cytokinin, abscisic acid, ethylene, salicylic acid and jasmonic acid, on the transcription of rice genes at whole genome level using microarray. Our analysis identified a total of 4171 genes involved in several biological processes, whose expression was altered significantly in the presence of different hormones. Further, 28% of these genes exhibited overlapping transcriptional responses in the presence of any two hormones, indicating crosstalk among plant hormones. In addition, we identified genes showing only a particular hormone-specific response, which can be used as hormone-specific markers. The results of this study will facilitate further studies in hormone biology in rice. PMID:22827941

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

Innovative approach for transcriptomic analysis of obligate intracellular pathogen: selective capture of transcribed sequences of Ehrlichia ruminantium

PubMed Central

2009-01-01

Background Whole genome transcriptomic analysis is a powerful approach to elucidate the molecular mechanisms controlling the pathogenesis of obligate intracellular bacteria. However, the major hurdle resides in the low quantity of prokaryotic mRNAs extracted from host cells. Our model Ehrlichia ruminantium (ER), the causative agent of heartwater, is transmitted by tick Amblyomma variegatum. This bacterium affects wild and domestic ruminants and is present in Sub-Saharan Africa and the Caribbean islands. Because of its strictly intracellular location, which constitutes a limitation for its extensive study, the molecular mechanisms involved in its pathogenicity are still poorly understood. Results We successfully adapted the SCOTS method (Selective Capture of Transcribed Sequences) on the model Rickettsiales ER to capture mRNAs. Southern Blots and RT-PCR revealed an enrichment of ER's cDNAs and a diminution of ribosomal contaminants after three rounds of capture. qRT-PCR and whole-genome ER microarrays hybridizations demonstrated that SCOTS method introduced only a limited bias on gene expression. Indeed, we confirmed the differential gene expression between poorly and highly expressed genes before and after SCOTS captures. The comparative gene expression obtained from ER microarrays data, on samples before and after SCOTS at 96 hpi was significantly correlated (R2 = 0.7). Moreover, SCOTS method is crucial for microarrays analysis of ER, especially for early time points post-infection. There was low detection of transcripts for untreated samples whereas 24% and 70.7% were revealed for SCOTS samples at 24 and 96 hpi respectively. Conclusions We conclude that this SCOTS method has a key importance for the transcriptomic analysis of ER and can be potentially used for other Rickettsiales. This study constitutes the first step for further gene expression analyses that will lead to a better understanding of both ER pathogenicity and the adaptation of obligate intracellular bacteria to their environment. PMID:20034374

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.

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

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

What the Aspergillus genomes have told us.

PubMed

Nierman, W C; May, G; Kim, H S; Anderson, M J; Chen, D; Denning, D W

2005-05-01

The sequencing and annotation of the genomes of the first strains of Aspergillus nidulans, Aspergillus oryzae, and Aspergillus fumigatus will be seen in retrospect as a transformational event in Aspergillus biology. With this event the entire genetic composition of A. nidulans, the sexual experimental model organism of the genus Aspergillus, A. oryzae, the food biotechnology organism which is the product of centuries of cultivation, and A. fumigatus, the most common causative agent of invasive aspergillosis is now revealed to the extent that we are at present able to understand. Each genome exhibits a large set of genes common to the three as well as a much smaller set of genes unique to each. Moreover, these sequences serve as resources providing the major tool to expanding our understanding of the biology of each. Transcription profiling of A. fumigatus at high temperatures and comparative genomic hybridization between A. fumigatus and a closely related Aspergillus species provides microarray based examples of the beginning of functional analysis of the genomes of these organisms going forward from the genome sequence.

Microarray Analysis Gene Expression Profiles in Laryngeal Muscle After Recurrent Laryngeal Nerve Injury.

PubMed

Bijangi-Vishehsaraei, Khadijeh; Blum, Kevin; Zhang, Hongji; Safa, Ahmad R; Halum, Stacey L

2016-03-01

The pathophysiology of recurrent laryngeal nerve (RLN) transection injury is rare in that it is characteristically followed by a high degree of spontaneous reinnervation, with reinnervation of the laryngeal adductor complex (AC) preceding that of the abducting posterior cricoarytenoid (PCA) muscle. Here, we aim to elucidate the differentially expressed myogenic factors following RLN injury that may be at least partially responsible for the spontaneous reinnervation. F344 male rats underwent RLN injury (n = 12) or sham surgery (n = 12). One week after RLN injury, larynges were harvested following euthanasia. The mRNA was extracted from PCA and AC muscles bilaterally, and microarray analysis was performed using a full rat genome array. Microarray analysis of denervated AC and PCA muscles demonstrated dramatic differences in gene expression profiles, with 205 individual probes that were differentially expressed between the denervated AC and PCA muscles and only 14 genes with similar expression patterns. The differential expression patterns of the AC and PCA suggest different mechanisms of reinnervation. The PCA showed the gene patterns of Wallerian degeneration, while the AC expressed the gene patterns of reinnervation by adjacent axonal sprouting. This finding may reveal important therapeutic targets applicable to RLN and other peripheral nerve injuries. © The Author(s) 2015.

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

PhyloFlu, a DNA microarray for determining the phylogenetic origin of influenza A virus gene segments and the genomic fingerprint of viral strains.

PubMed

Paulin, Luis F; de los D Soto-Del Río, María; Sánchez, Iván; Hernández, Jesús; Gutiérrez-Ríos, Rosa M; López-Martínez, Irma; Wong-Chew, Rosa M; Parissi-Crivelli, Aurora; Isa, P; López, Susana; Arias, Carlos F

2014-03-01

Recent evidence suggests that most influenza A virus gene segments can contribute to the pathogenicity of the virus. In this regard, the hemagglutinin (HA) subtype of the circulating strains has been closely surveyed, but the reassortment of internal gene segments is usually not monitored as a potential source of an increased pathogenicity. In this work, an oligonucleotide DNA microarray (PhyloFlu) designed to determine the phylogenetic origins of the eight segments of the influenza virus genome was constructed and validated. Clades were defined for each segment and also for the 16 HA and 9 neuraminidase (NA) subtypes. Viral genetic material was amplified by reverse transcription-PCR (RT-PCR) with primers specific to the conserved 5' and 3' ends of the influenza A virus genes, followed by PCR amplification with random primers and Cy3 labeling. The microarray unambiguously determined the clades for all eight influenza virus genes in 74% (28/38) of the samples. The microarray was validated with reference strains from different animal origins, as well as from human, swine, and avian viruses from field or clinical samples. In most cases, the phylogenetic clade of each segment defined its animal host of origin. The genomic fingerprint deduced by the combined information of the individual clades allowed for the determination of the time and place that strains with the same genomic pattern were previously reported. PhyloFlu is useful for characterizing and surveying the genetic diversity and variation of animal viruses circulating in different environmental niches and for obtaining a more detailed surveillance and follow up of reassortant events that can potentially modify virus pathogenicity.

mRNA expression profiling of laser microbeam microdissected cells from slender embryonic structures.

PubMed

Scheidl, Stefan J; Nilsson, Sven; Kalén, Mattias; Hellström, Mats; Takemoto, Minoru; Håkansson, Joakim; Lindahl, Per

2002-03-01

Microarray hybridization has rapidly evolved as an important tool for genomic studies and studies of gene regulation at the transcriptome level. Expression profiles from homogenous samples such as yeast and mammalian cell cultures are currently extending our understanding of biology, whereas analyses of multicellular organisms are more difficult because of tissue complexity. The combination of laser microdissection, RNA amplification, and microarray hybridization has the potential to provide expression profiles from selected populations of cells in vivo. In this article, we present and evaluate an experimental procedure for global gene expression analysis of slender embryonic structures using laser microbeam microdissection and laser pressure catapulting. As a proof of principle, expression profiles from 1000 cells in the mouse embryonic (E9.5) dorsal aorta were generated and compared with profiles for captured mesenchymal cells located one cell diameter further away from the aortic lumen. A number of genes were overexpressed in the aorta, including 11 previously known markers for blood vessels. Among the blood vessel markers were endoglin, tie-2, PDGFB, and integrin-beta1, that are important regulators of blood vessel formation. This demonstrates that microarray analysis of laser microbeam micro-dissected cells is sufficiently sensitive for identifying genes with regulative functions.

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.

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

PubMed Central

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

2009-01-01

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

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

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

Tagmount, Abderrahmane; Wang, Mei; Lindquist, Erika

2010-01-27

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

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

PubMed

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

2016-12-01

The flat oyster, Ostrea edulis, is one of the main farmed oysters, not only in Europe but also in the United States and Canada. Bonamiosis due to the parasite Bonamia ostreae has been associated with high mortality episodes in this species. This parasite is an intracellular protozoan that infects haemocytes, the main cells involved in oyster defence. Due to the economical and ecological importance of flat oyster, genomic data are badly needed for genetic improvement of the species, but they are still very scarce. The objective of this study is to develop a sequence database, OedulisDB, with new genomic and transcriptomic resources, providing new data and convenient tools to improve our knowledge of the oyster's immune mechanisms. Transcriptomic and genomic sequences were obtained using 454 pyrosequencing and compiled into an O. edulis database, OedulisDB, consisting of two sets of 10,318 and 7159 unique sequences that represent the oyster's genome (WG) and de novo haemocyte transcriptome (HT), respectively. The flat oyster transcriptome was obtained from two strains (naïve and tolerant) challenged with B. ostreae, and from their corresponding non-challenged controls. Approximately 78.5% of 5619 HT unique sequences were successfully annotated by Blast search using public databases. A total of 984 sequences were identified as being related to immune response and several key immune genes were identified for the first time in flat oyster. Additionally, transcriptome information was used to design and validate the first oligo-microarray in flat oyster enriched with immune sequences from haemocytes. Our transcriptomic and genomic sequencing and subsequent annotation have largely increased the scarce resources available for this economically important species and have enabled us to develop an OedulisDB database and accompanying tools for gene expression analysis. This study represents the first attempt to characterize in depth the O. edulis haemocyte transcriptome in response to B. ostreae through massively sequencing and has aided to improve our knowledge of the immune mechanisms of flat oyster. The validated oligo-microarray and the establishment of a reference transcriptome will be useful for large-scale gene expression studies in this species. Copyright © 2016 Elsevier Ltd. All rights reserved.

Whole genome co-expression analysis of soybean cytochrome P450 genes identifies nodulation-specific P450 monooxygenases

PubMed Central

2010-01-01

Background Cytochrome P450 monooxygenases (P450s) catalyze oxidation of various substrates using oxygen and NAD(P)H. Plant P450s are involved in the biosynthesis of primary and secondary metabolites performing diverse biological functions. The recent availability of the soybean genome sequence allows us to identify and analyze soybean putative P450s at a genome scale. Co-expression analysis using an available soybean microarray and Illumina sequencing data provides clues for functional annotation of these enzymes. This approach is based on the assumption that genes that have similar expression patterns across a set of conditions may have a functional relationship. Results We have identified a total number of 332 full-length P450 genes and 378 pseudogenes from the soybean genome. From the full-length sequences, 195 genes belong to A-type, which could be further divided into 20 families. The remaining 137 genes belong to non-A type P450s and are classified into 28 families. A total of 178 probe sets were found to correspond to P450 genes on the Affymetrix soybean array. Out of these probe sets, 108 represented single genes. Using the 28 publicly available microarray libraries that contain organ-specific information, some tissue-specific P450s were identified. Similarly, stress responsive soybean P450s were retrieved from 99 microarray soybean libraries. We also utilized Illumina transcriptome sequencing technology to analyze the expressions of all 332 soybean P450 genes. This dataset contains total RNAs isolated from nodules, roots, root tips, leaves, flowers, green pods, apical meristem, mock-inoculated and Bradyrhizobium japonicum-infected root hair cells. The tissue-specific expression patterns of these P450 genes were analyzed and the expression of a representative set of genes were confirmed by qRT-PCR. We performed the co-expression analysis on many of the 108 P450 genes on the Affymetrix arrays. First we confirmed that CYP93C5 (an isoflavone synthase gene) is co-expressed with several genes encoding isoflavonoid-related metabolic enzymes. We then focused on nodulation-induced P450s and found that CYP728H1 was co-expressed with the genes involved in phenylpropanoid metabolism. Similarly, CYP736A34 was highly co-expressed with lipoxygenase, lectin and CYP83D1, all of which are involved in root and nodule development. Conclusions The genome scale analysis of P450s in soybean reveals many unique features of these important enzymes in this crop although the functions of most of them are largely unknown. Gene co-expression analysis proves to be a useful tool to infer the function of uncharacterized genes. Our work presented here could provide important leads toward functional genomics studies of soybean P450s and their regulatory network through the integration of reverse genetics, biochemistry, and metabolic profiling tools. The identification of nodule-specific P450s and their further exploitation may help us to better understand the intriguing process of soybean and rhizobium interaction. PMID:21062474

SEURAT: Visual analytics for the integrated analysis of microarray data

PubMed Central

2010-01-01

Background In translational cancer research, gene expression data is collected together with clinical data and genomic data arising from other chip based high throughput technologies. Software tools for the joint analysis of such high dimensional data sets together with clinical data are required. Results We have developed an open source software tool which provides interactive visualization capability for the integrated analysis of high-dimensional gene expression data together with associated clinical data, array CGH data and SNP array data. The different data types are organized by a comprehensive data manager. Interactive tools are provided for all graphics: heatmaps, dendrograms, barcharts, histograms, eventcharts and a chromosome browser, which displays genetic variations along the genome. All graphics are dynamic and fully linked so that any object selected in a graphic will be highlighted in all other graphics. For exploratory data analysis the software provides unsupervised data analytics like clustering, seriation algorithms and biclustering algorithms. Conclusions The SEURAT software meets the growing needs of researchers to perform joint analysis of gene expression, genomical and clinical data. PMID:20525257

Microarray analysis and draft genomes of two Escherichia coli 0157:H7 lineage II cattle isolates FRIK966 and FRIK2000 investigating lack of Shiga toxin expression

USDA-ARS?s Scientific Manuscript database

The existence of two separate lineages of Escherichia coli O157:H7 has previously been reported, and research indicates that lineage I might be more pathogenic towards human hosts than lineage II. We have previously shown that lineage I expresses higher levels of Shiga toxin 2 (Stx2). To evaluate w...

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.

AN ECOLOGICAL PERSPECTIVE OF GENOMICS: ASSESSING ECOLOGICAL RISK THROUGH PARTNERSHIPS

EPA Science Inventory

The application of new molecular biological tools to environmental toxicology was discussed at an international workshop attended by
approximately 60 government, academic, and industrial scientists. The sequencing of the human genome, development of microarrays and
DNA chip...

An Inexpensive Gel Electrophoresis-Based Polymerase Chain Reaction Method for Quantifying mRNA Levels

ERIC Educational Resources Information Center

Bradford, William D.; Cahoon, Laty; Freel, Sara R.; Hoopes, Laura L. Mays; Eckdahl, Todd T.

2005-01-01

In order to engage their students in a core methodology of the new genomics era, an everincreasing number of faculty at primarily undergraduate institutions are gaining access to microarray technology. Their students are conducting successful microarray experiments designed to address a variety of interesting questions. A next step in these…

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

A Discovery Resource of Rare Copy Number Variations in Individuals with Autism Spectrum Disorder

PubMed Central

Prasad, Aparna; Merico, Daniele; Thiruvahindrapuram, Bhooma; Wei, John; Lionel, Anath C.; Sato, Daisuke; Rickaby, Jessica; Lu, Chao; Szatmari, Peter; Roberts, Wendy; Fernandez, Bridget A.; Marshall, Christian R.; Hatchwell, Eli; Eis, Peggy S.; Scherer, Stephen W.

2012-01-01

The identification of rare inherited and de novo copy number variations (CNVs) in human subjects has proven a productive approach to highlight risk genes for autism spectrum disorder (ASD). A variety of microarrays are available to detect CNVs, including single-nucleotide polymorphism (SNP) arrays and comparative genomic hybridization (CGH) arrays. Here, we examine a cohort of 696 unrelated ASD cases using a high-resolution one-million feature CGH microarray, the majority of which were previously genotyped with SNP arrays. Our objective was to discover new CNVs in ASD cases that were not detected by SNP microarray analysis and to delineate novel ASD risk loci via combined analysis of CGH and SNP array data sets on the ASD cohort and CGH data on an additional 1000 control samples. Of the 615 ASD cases analyzed on both SNP and CGH arrays, we found that 13,572 of 21,346 (64%) of the CNVs were exclusively detected by the CGH array. Several of the CGH-specific CNVs are rare in population frequency and impact previously reported ASD genes (e.g., NRXN1, GRM8, DPYD), as well as novel ASD candidate genes (e.g., CIB2, DAPP1, SAE1), and all were inherited except for a de novo CNV in the GPHN gene. A functional enrichment test of gene-sets in ASD cases over controls revealed nucleotide metabolism as a potential novel pathway involved in ASD, which includes several candidate genes for follow-up (e.g., DPYD, UPB1, UPP1, TYMP). Finally, this extensively phenotyped and genotyped ASD clinical cohort serves as an invaluable resource for the next step of genome sequencing for complete genetic variation detection. PMID:23275889

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

Functional Genomic Approaches for the Study of Fetal/Placental Development in Swine with Special Emphasis on Imprinted Genes

USDA-ARS?s Scientific Manuscript database

The overall focus of this chapter will be the application of functional genomic approaches for the study of the imprinted gene family in swine. While there are varied definitions of “functional genomics” in general they focus on the application of genomic approaches such as DNA microarrays, single n...

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

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

NASA Astrophysics Data System (ADS)

Kikuchi, Shoshi

2009-02-01

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

Genomic evidence of reactive oxygen species elevation in papillary thyroid carcinoma with Hashimoto thyroiditis.

PubMed

Yi, Jin Wook; Park, Ji Yeon; Sung, Ji-Youn; Kwak, Sang Hyuk; Yu, Jihan; Chang, Ji Hyun; Kim, Jo-Heon; Ha, Sang Yun; Paik, Eun Kyung; Lee, Woo Seung; Kim, Su-Jin; Lee, Kyu Eun; Kim, Ju Han

2015-01-01

Elevated levels of reactive oxygen species (ROS) have been proposed as a risk factor for the development of papillary thyroid carcinoma (PTC) in patients with Hashimoto thyroiditis (HT). However, it has yet to be proven that the total levels of ROS are sufficiently increased to contribute to carcinogenesis. We hypothesized that if the ROS levels were increased in HT, ROS-related genes would also be differently expressed in PTC with HT. To find differentially expressed genes (DEGs) we analyzed data from the Cancer Genomic Atlas, gene expression data from RNA sequencing: 33 from normal thyroid tissue, 232 from PTC without HT, and 60 from PTC with HT. We prepared 402 ROS-related genes from three gene sets by genomic database searching. We also analyzed a public microarray data to validate our results. Thirty-three ROS related genes were up-regulated in PTC with HT, whereas there were only nine genes in PTC without HT (Chi-square p-value < 0.001). Mean log2 fold changes of up-regulated genes was 0.562 in HT group and 0.252 in PTC without HT group (t-test p-value = 0.001). In microarray data analysis, 12 of 32 ROS-related genes showed the same differential expression pattern with statistical significance. In gene ontology analysis, up-regulated ROS-related genes were related with ROS metabolism and apoptosis. Immune function-related and carcinogenesis-related gene sets were enriched only in HT group in Gene Set Enrichment Analysis. Our results suggested that ROS levels may be increased in PTC with HT. Increased levels of ROS may contribute to PTC development in patients with HT.

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.

PGMapper: a web-based tool linking phenotype to genes.

PubMed

Xiong, Qing; Qiu, Yuhui; Gu, Weikuan

2008-04-01

With the availability of whole genome sequence in many species, linkage analysis, positional cloning and microarray are gradually becoming powerful tools for investigating the links between phenotype and genotype or genes. However, in these methods, causative genes underlying a quantitative trait locus, or a disease, are usually located within a large genomic region or a large set of genes. Examining the function of every gene is very time consuming and needs to retrieve and integrate the information from multiple databases or genome resources. PGMapper is a software tool for automatically matching phenotype to genes from a defined genome region or a group of given genes by combining the mapping information from the Ensembl database and gene function information from the OMIM and PubMed databases. PGMapper is currently available for candidate gene search of human, mouse, rat, zebrafish and 12 other species. Available online at http://www.genediscovery.org/pgmapper/index.jsp.

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

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

PubMed Central

2009-01-01

Background Soybeans grown in the upper Midwestern United States often suffer from iron deficiency chlorosis, which results in yield loss at the end of the season. To better understand the effect of iron availability on soybean yield, we identified genes in two near isogenic lines with changes in expression patterns when plants were grown in iron sufficient and iron deficient conditions. Results Transcriptional profiles of soybean (Glycine max, L. Merr) near isogenic lines Clark (PI548553, iron efficient) and IsoClark (PI547430, iron inefficient) grown under Fe-sufficient and Fe-limited conditions were analyzed and compared using the Affymetrix® GeneChip® Soybean Genome Array. There were 835 candidate genes in the Clark (PI548553) genotype and 200 candidate genes in the IsoClark (PI547430) genotype putatively involved in soybean's iron stress response. Of these candidate genes, fifty-eight genes in the Clark genotype were identified with a genetic location within known iron efficiency QTL and 21 in the IsoClark genotype. The arrays also identified 170 single feature polymorphisms (SFPs) specific to either Clark or IsoClark. A sliding window analysis of the microarray data and the 7X genome assembly coupled with an iterative model of the data showed the candidate genes are clustered in the genome. An analysis of 5' untranslated regions in the promoter of candidate genes identified 11 conserved motifs in 248 differentially expressed genes, all from the Clark genotype, representing 129 clusters identified earlier, confirming the cluster analysis results. Conclusion These analyses have identified the first genes with expression patterns that are affected by iron stress and are located within QTL specific to iron deficiency stress. The genetic location and promoter motif analysis results support the hypothesis that the differentially expressed genes are co-regulated. The combined results of all analyses lead us to postulate iron inefficiency in soybean is a result of a mutation in a transcription factor(s), which controls the expression of genes required in inducing an iron stress response. PMID:19678937

Identification of Human Lineage-Specific Transcriptional Coregulators Enabled by a Glossary of Binding Modules and Tunable Genomic Backgrounds.

PubMed

Mariani, Luca; Weinand, Kathryn; Vedenko, Anastasia; Barrera, Luis A; Bulyk, Martha L

2017-09-27

Transcription factors (TFs) control cellular processes by binding specific DNA motifs to modulate gene expression. Motif enrichment analysis of regulatory regions can identify direct and indirect TF binding sites. Here, we created a glossary of 108 non-redundant TF-8mer "modules" of shared specificity for 671 metazoan TFs from publicly available and new universal protein binding microarray data. Analysis of 239 ENCODE TF chromatin immunoprecipitation sequencing datasets and associated RNA sequencing profiles suggest the 8mer modules are more precise than position weight matrices in identifying indirect binding motifs and their associated tethering TFs. We also developed GENRE (genomically equivalent negative regions), a tunable tool for construction of matched genomic background sequences for analysis of regulatory regions. GENRE outperformed four state-of-the-art approaches to background sequence construction. We used our TF-8mer glossary and GENRE in the analysis of the indirect binding motifs for the co-occurrence of tethering factors, suggesting novel TF-TF interactions. We anticipate that these tools will aid in elucidating tissue-specific gene-regulatory programs. Copyright © 2017 Elsevier Inc. All rights reserved.

Prognostic significance of TRIM24/TIF-1α gene expression in breast cancer.

PubMed

Chambon, Monique; Orsetti, Béatrice; Berthe, Marie-Laurence; Bascoul-Mollevi, Caroline; Rodriguez, Carmen; Duong, Vanessa; Gleizes, Michel; Thénot, Sandrine; Bibeau, Frédéric; Theillet, Charles; Cavaillès, Vincent

2011-04-01

In this study, we have analyzed the expression of TRIM24/TIF-1α, a negative regulator of various transcription factors (including nuclear receptors and p53) at the genomic, mRNA, and protein levels in human breast tumors. In breast cancer biopsy specimens, TRIM24/TIF-1α mRNA levels (assessed by Real-Time Quantitative PCR or microarray expression profiling) were increased as compared to normal breast tissues. At the genomic level, array comparative genomic hybridization analysis showed that the TRIM24/TIF-1α locus (7q34) exhibited both gains and losses that correlated with mRNA levels. By re-analyzing a series of 238 tumors, high levels of TRIM24/TIF-1α mRNA significantly correlated with various markers of poor prognosis (such as the molecular subtype) and were associated with worse overall survival. By using a rabbit polyclonal antibody for immunochemistry, the TRIM24/TIF-1α protein was detected in nuclei of normal luminal epithelial breast cells, but not in myoepithelial cells. Tissue microarray analysis confirmed that its expression was increased in epithelial cells from normal to breast infiltrating duct carcinoma and correlated with worse overall survival. Altogether, this work is the first study that shows that overexpression of the TRIM24/TIF-1α gene in breast cancer is associated with poor prognosis and worse survival, and it suggests that this transcription coregulator may play a role in mammary carcinogenesis and represent a novel prognostic marker. Copyright © 2011 American Society for Investigative Pathology. Published by Elsevier Inc. All rights reserved.

Automated array-based genomic profiling in chronic lymphocytic leukemia: Development of a clinical tool and discovery of recurrent genomic alterations

PubMed Central

Schwaenen, Carsten; Nessling, Michelle; Wessendorf, Swen; Salvi, Tatjana; Wrobel, Gunnar; Radlwimmer, Bernhard; Kestler, Hans A.; Haslinger, Christian; Stilgenbauer, Stephan; Döhner, Hartmut; Bentz, Martin; Lichter, Peter

2004-01-01

B cell chronic lymphocytic leukemia (B-CLL) is characterized by a highly variable clinical course. Recurrent chromosomal imbalances provide significant prognostic markers. Risk-adapted therapy based on genomic alterations has become an option that is currently being tested in clinical trials. To supply a robust tool for such large scale studies, we developed a comprehensive DNA microarray dedicated to the automated analysis of recurrent genomic imbalances in B-CLL by array-based comparative genomic hybridization (matrix–CGH). Validation of this chip in a series of 106 B-CLL cases revealed a high specificity and sensitivity that fulfils the criteria for application in clinical oncology. This chip is immediately applicable within clinical B-CLL treatment trials that evaluate whether B-CLL cases with distinct chromosomal abnormalities should be treated with chemotherapy of different intensities and/or stem cell transplantation. Through the control set of DNA fragments equally distributed over the genome, recurrent genomic imbalances were discovered: trisomy of chromosome 19 and gain of the MYCN oncogene correlating with an elevation of MYCN mRNA expression. PMID:14730057

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.

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.

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

AN ECOLOGICAL PERSPECTIVE OF GENOMICS: ASSESSING ECOLOGICAL RISK THROUGH PARTNERSHIPS

EPA Science Inventory

A workshop attended by approximately 60 scientists from around the world met to discuss the application of new molecular biology tools to issues in environmental toxicology and chemistry. With the sequencing of the human genome, development of microarrays and DNA chips, and devel...

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

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

GenomeCAT: a versatile tool for the analysis and integrative visualization of DNA copy number variants.

PubMed

Tebel, Katrin; Boldt, Vivien; Steininger, Anne; Port, Matthias; Ebert, Grit; Ullmann, Reinhard

2017-01-06

The analysis of DNA copy number variants (CNV) has increasing impact in the field of genetic diagnostics and research. However, the interpretation of CNV data derived from high resolution array CGH or NGS platforms is complicated by the considerable variability of the human genome. Therefore, tools for multidimensional data analysis and comparison of patient cohorts are needed to assist in the discrimination of clinically relevant CNVs from others. We developed GenomeCAT, a standalone Java application for the analysis and integrative visualization of CNVs. GenomeCAT is composed of three modules dedicated to the inspection of single cases, comparative analysis of multidimensional data and group comparisons aiming at the identification of recurrent aberrations in patients sharing the same phenotype, respectively. Its flexible import options ease the comparative analysis of own results derived from microarray or NGS platforms with data from literature or public depositories. Multidimensional data obtained from different experiment types can be merged into a common data matrix to enable common visualization and analysis. All results are stored in the integrated MySQL database, but can also be exported as tab delimited files for further statistical calculations in external programs. GenomeCAT offers a broad spectrum of visualization and analysis tools that assist in the evaluation of CNVs in the context of other experiment data and annotations. The use of GenomeCAT does not require any specialized computer skills. The various R packages implemented for data analysis are fully integrated into GenomeCATs graphical user interface and the installation process is supported by a wizard. The flexibility in terms of data import and export in combination with the ability to create a common data matrix makes the program also well suited as an interface between genomic data from heterogeneous sources and external software tools. Due to the modular architecture the functionality of GenomeCAT can be easily extended by further R packages or customized plug-ins to meet future requirements.

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

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.

Genomic imbalances in pediatric patients with chronic kidney disease.

PubMed

Verbitsky, Miguel; Sanna-Cherchi, Simone; Fasel, David A; Levy, Brynn; Kiryluk, Krzysztof; Wuttke, Matthias; Abraham, Alison G; Kaskel, Frederick; Köttgen, Anna; Warady, Bradley A; Furth, Susan L; Wong, Craig S; Gharavi, Ali G

2015-05-01

There is frequent uncertainty in the identification of specific etiologies of chronic kidney disease (CKD) in children. Recent studies indicate that chromosomal microarrays can identify rare genomic imbalances that can clarify the etiology of neurodevelopmental and cardiac disorders in children; however, the contribution of unsuspected genomic imbalance to the incidence of pediatric CKD is unknown. We performed chromosomal microarrays to detect genomic imbalances in children enrolled in the Chronic Kidney Disease in Children (CKiD) prospective cohort study, a longitudinal prospective multiethnic observational study of North American children with mild to moderate CKD. Patients with clinically detectable syndromic disease were excluded from evaluation. We compared 419 unrelated children enrolled in CKiD to multiethnic cohorts of 21,575 children and adults that had undergone microarray genotyping for studies unrelated to CKD. We identified diagnostic copy number disorders in 31 children with CKD (7.4% of the cohort). We detected 10 known pathogenic genomic disorders, including the 17q12 deletion HNF1 homeobox B (HNF1B) and triple X syndromes in 19 of 419 unrelated CKiD cases as compared with 98 of 21,575 control individuals (OR 10.8, P = 6.1 × 10⁻²⁰). In an additional 12 CKiD cases, we identified 12 likely pathogenic genomic imbalances that would be considered reportable in a clinical setting. These genomic imbalances were evenly distributed among patients diagnosed with congenital and noncongenital forms of CKD. In the vast majority of these cases, the genomic lesion was unsuspected based on the clinical assessment and either reclassified the disease or provided information that might have triggered additional clinical care, such as evaluation for metabolic or neuropsychiatric disease. A substantial proportion of children with CKD have an unsuspected genomic imbalance, suggesting genomic disorders as a risk factor for common forms of pediatric nephropathy. Detection of pathogenic imbalances has practical implications for personalized diagnosis and health monitoring in this population. ClinicalTrials.gov NCT00327860. This work was supported by the NIH, the National Institutes of Diabetes and Digestive and Kidney Diseases (NIDDK), the National Institute of Child Health and Human Development, and the National Heart, Lung, and Blood Institute.

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

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.

EuPathDB: the eukaryotic pathogen genomics database resource

PubMed Central

Aurrecoechea, Cristina; Barreto, Ana; Basenko, Evelina Y.; Brestelli, John; Brunk, Brian P.; Cade, Shon; Crouch, Kathryn; Doherty, Ryan; Falke, Dave; Fischer, Steve; Gajria, Bindu; Harb, Omar S.; Heiges, Mark; Hertz-Fowler, Christiane; Hu, Sufen; Iodice, John; Kissinger, Jessica C.; Lawrence, Cris; Li, Wei; Pinney, Deborah F.; Pulman, Jane A.; Roos, David S.; Shanmugasundram, Achchuthan; Silva-Franco, Fatima; Steinbiss, Sascha; Stoeckert, Christian J.; Spruill, Drew; Wang, Haiming; Warrenfeltz, Susanne; Zheng, Jie

2017-01-01

The Eukaryotic Pathogen Genomics Database Resource (EuPathDB, http://eupathdb.org) is a collection of databases covering 170+ eukaryotic pathogens (protists & fungi), along with relevant free-living and non-pathogenic species, and select pathogen hosts. To facilitate the discovery of meaningful biological relationships, the databases couple preconfigured searches with visualization and analysis tools for comprehensive data mining via intuitive graphical interfaces and APIs. All data are analyzed with the same workflows, including creation of gene orthology profiles, so data are easily compared across data sets, data types and organisms. EuPathDB is updated with numerous new analysis tools, features, data sets and data types. New tools include GO, metabolic pathway and word enrichment analyses plus an online workspace for analysis of personal, non-public, large-scale data. Expanded data content is mostly genomic and functional genomic data while new data types include protein microarray, metabolic pathways, compounds, quantitative proteomics, copy number variation, and polysomal transcriptomics. New features include consistent categorization of searches, data sets and genome browser tracks; redesigned gene pages; effective integration of alternative transcripts; and a EuPathDB Galaxy instance for private analyses of a user's data. Forthcoming upgrades include user workspaces for private integration of data with existing EuPathDB data and improved integration and presentation of host–pathogen interactions. PMID:27903906

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

Molecular Phylogenetic and Expression Analysis of the Complete WRKY Transcription Factor Family in Maize

PubMed Central

Wei, Kai-Fa; Chen, Juan; Chen, Yan-Feng; Wu, Ling-Juan; Xie, Dao-Xin

2012-01-01

The WRKY transcription factors function in plant growth and development, and response to the biotic and abiotic stresses. Although many studies have focused on the functional identification of the WRKY transcription factors, much less is known about molecular phylogenetic and global expression analysis of the complete WRKY family in maize. In this study, we identified 136 WRKY proteins coded by 119 genes in the B73 inbred line from the complete genome and named them in an orderly manner. Then, a comprehensive phylogenetic analysis of five species was performed to explore the origin and evolutionary patterns of these WRKY genes, and the result showed that gene duplication is the major driving force for the origin of new groups and subgroups and functional divergence during evolution. Chromosomal location analysis of maize WRKY genes indicated that 20 gene clusters are distributed unevenly in the genome. Microarray-based expression analysis has revealed that 131 WRKY transcripts encoded by 116 genes may participate in the regulation of maize growth and development. Among them, 102 transcripts are stably expressed with a coefficient of variation (CV) value of <15%. The remaining 29 transcripts produced by 25 WRKY genes with the CV value of >15% are further analysed to discover new organ- or tissue-specific genes. In addition, microarray analyses of transcriptional responses to drought stress and fungal infection showed that maize WRKY proteins are involved in stress responses. All these results contribute to a deep probing into the roles of WRKY transcription factors in maize growth and development and stress tolerance. PMID:22279089

Molecular phylogenetic and expression analysis of the complete WRKY transcription factor family in maize.

PubMed

Wei, Kai-Fa; Chen, Juan; Chen, Yan-Feng; Wu, Ling-Juan; Xie, Dao-Xin

2012-04-01

The WRKY transcription factors function in plant growth and development, and response to the biotic and abiotic stresses. Although many studies have focused on the functional identification of the WRKY transcription factors, much less is known about molecular phylogenetic and global expression analysis of the complete WRKY family in maize. In this study, we identified 136 WRKY proteins coded by 119 genes in the B73 inbred line from the complete genome and named them in an orderly manner. Then, a comprehensive phylogenetic analysis of five species was performed to explore the origin and evolutionary patterns of these WRKY genes, and the result showed that gene duplication is the major driving force for the origin of new groups and subgroups and functional divergence during evolution. Chromosomal location analysis of maize WRKY genes indicated that 20 gene clusters are distributed unevenly in the genome. Microarray-based expression analysis has revealed that 131 WRKY transcripts encoded by 116 genes may participate in the regulation of maize growth and development. Among them, 102 transcripts are stably expressed with a coefficient of variation (CV) value of <15%. The remaining 29 transcripts produced by 25 WRKY genes with the CV value of >15% are further analysed to discover new organ- or tissue-specific genes. In addition, microarray analyses of transcriptional responses to drought stress and fungal infection showed that maize WRKY proteins are involved in stress responses. All these results contribute to a deep probing into the roles of WRKY transcription factors in maize growth and development and stress tolerance.

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

Optimization of oligonucleotide arrays and RNA amplification protocols for analysis of transcript structure and alternative splicing.

PubMed

Castle, John; Garrett-Engele, Phil; Armour, Christopher D; Duenwald, Sven J; Loerch, Patrick M; Meyer, Michael R; Schadt, Eric E; Stoughton, Roland; Parrish, Mark L; Shoemaker, Daniel D; Johnson, Jason M

2003-01-01

Microarrays offer a high-resolution means for monitoring pre-mRNA splicing on a genomic scale. We have developed a novel, unbiased amplification protocol that permits labeling of entire transcripts. Also, hybridization conditions, probe characteristics, and analysis algorithms were optimized for detection of exons, exon-intron edges, and exon junctions. These optimized protocols can be used to detect small variations and isoform mixtures, map the tissue specificity of known human alternative isoforms, and provide a robust, scalable platform for high-throughput discovery of alternative splicing.

Optimization of oligonucleotide arrays and RNA amplification protocols for analysis of transcript structure and alternative splicing

PubMed Central

Castle, John; Garrett-Engele, Phil; Armour, Christopher D; Duenwald, Sven J; Loerch, Patrick M; Meyer, Michael R; Schadt, Eric E; Stoughton, Roland; Parrish, Mark L; Shoemaker, Daniel D; Johnson, Jason M

2003-01-01

Microarrays offer a high-resolution means for monitoring pre-mRNA splicing on a genomic scale. We have developed a novel, unbiased amplification protocol that permits labeling of entire transcripts. Also, hybridization conditions, probe characteristics, and analysis algorithms were optimized for detection of exons, exon-intron edges, and exon junctions. These optimized protocols can be used to detect small variations and isoform mixtures, map the tissue specificity of known human alternative isoforms, and provide a robust, scalable platform for high-throughput discovery of alternative splicing. PMID:14519201

Time-series RNA-seq analysis package (TRAP) and its application to the analysis of rice, Oryza sativa L. ssp. Japonica, upon drought stress.

PubMed

Jo, Kyuri; Kwon, Hawk-Bin; Kim, Sun

2014-06-01

Measuring expression levels of genes at the whole genome level can be useful for many purposes, especially for revealing biological pathways underlying specific phenotype conditions. When gene expression is measured over a time period, we have opportunities to understand how organisms react to stress conditions over time. Thus many biologists routinely measure whole genome level gene expressions at multiple time points. However, there are several technical difficulties for analyzing such whole genome expression data. In addition, these days gene expression data is often measured by using RNA-sequencing rather than microarray technologies and then analysis of expression data is much more complicated since the analysis process should start with mapping short reads and produce differentially activated pathways and also possibly interactions among pathways. In addition, many useful tools for analyzing microarray gene expression data are not applicable for the RNA-seq data. Thus a comprehensive package for analyzing time series transcriptome data is much needed. In this article, we present a comprehensive package, Time-series RNA-seq Analysis Package (TRAP), integrating all necessary tasks such as mapping short reads, measuring gene expression levels, finding differentially expressed genes (DEGs), clustering and pathway analysis for time-series data in a single environment. In addition to implementing useful algorithms that are not available for RNA-seq data, we extended existing pathway analysis methods, ORA and SPIA, for time series analysis and estimates statistical values for combined dataset by an advanced metric. TRAP also produces visual summary of pathway interactions. Gene expression change labeling, a practical clustering method used in TRAP, enables more accurate interpretation of the data when combined with pathway analysis. We applied our methods on a real dataset for the analysis of rice (Oryza sativa L. Japonica nipponbare) upon drought stress. The result showed that TRAP was able to detect pathways more accurately than several existing methods. TRAP is available at http://biohealth.snu.ac.kr/software/TRAP/. Copyright © 2014 Elsevier Inc. All rights reserved.

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…

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

PubMed

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

2003-01-01

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

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.

Application of nanostructured biochips for efficient cell transfection microarrays

NASA Astrophysics Data System (ADS)

Akkamsetty, Yamini; Hook, Andrew L.; Thissen, Helmut; Hayes, Jason P.; Voelcker, Nicolas H.

2007-01-01

Microarrays, high-throughput devices for genomic analysis, can be further improved by developing materials that are able to manipulate the interfacial behaviour of biomolecules. This is achieved both spatially and temporally by smart materials possessing both switchable and patterned surface properties. A system had been developed to spatially manipulate both DNA and cell growth based upon the surface modification of highly doped silicon by plasma polymerisation and polyethylene grafting followed by masked laser ablation for formation of a pattered surface with both bioactive and non-fouling regions. This platform has been successfully applied to transfected cell microarray applications with the parallel expression of genes by utilising its ability to direct and limit both DNA and cell attachment to specific sites. One of the greatest advantages of this system is its application to reverse transfection, whereupon by utilising the switchable adsorption and desorption of DNA using a voltage bias, the efficiency of cell transfection can be enhanced. However, it was shown that application of a voltage also reduces the viability of neuroblastoma cells grown on a plasma polymer surface, but not human embryonic kidney cells. This suggests that the application of a voltage may not only result in the desorption of bound DNA but may also affect attached cells. The characterisation of a DNA microarray by contact printing has also been investigated.

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

A Sorghum bicolor expression atlas reveals dynamic genotype-specific expression profiles for vegetative tissues of grain, sweet and bioenergy sorghums.

PubMed

Shakoor, Nadia; Nair, Ramesh; Crasta, Oswald; Morris, Geoffrey; Feltus, Alex; Kresovich, Stephen

2014-01-23

Effective improvement in sorghum crop development necessitates a genomics-based approach to identify functional genes and QTLs. Sequenced in 2009, a comprehensive annotation of the sorghum genome and the development of functional genomics resources is key to enable the discovery and deployment of regulatory and metabolic genes and gene networks for crop improvement. This study utilizes the first commercially available whole-transcriptome sorghum microarray (Sorgh-WTa520972F) to identify tissue and genotype-specific expression patterns for all identified Sorghum bicolor exons and UTRs. The genechip contains 1,026,373 probes covering 149,182 exons (27,577 genes) across the Sorghum bicolor nuclear, chloroplast, and mitochondrial genomes. Specific probesets were also included for putative non-coding RNAs that may play a role in gene regulation (e.g., microRNAs), and confirmed functional small RNAs in related species (maize and sugarcane) were also included in our array design. We generated expression data for 78 samples with a combination of four different tissue types (shoot, root, leaf and stem), two dissected stem tissues (pith and rind) and six diverse genotypes, which included 6 public sorghum lines (R159, Atlas, Fremont, PI152611, AR2400 and PI455230) representing grain, sweet, forage, and high biomass ideotypes. Here we present a summary of the microarray dataset, including analysis of tissue-specific gene expression profiles and associated expression profiles of relevant metabolic pathways. With an aim to enable identification and functional characterization of genes in sorghum, this expression atlas presents a new and valuable resource to the research community.

A Sorghum bicolor expression atlas reveals dynamic genotype-specific expression profiles for vegetative tissues of grain, sweet and bioenergy sorghums

PubMed Central

2014-01-01

Background Effective improvement in sorghum crop development necessitates a genomics-based approach to identify functional genes and QTLs. Sequenced in 2009, a comprehensive annotation of the sorghum genome and the development of functional genomics resources is key to enable the discovery and deployment of regulatory and metabolic genes and gene networks for crop improvement. Results This study utilizes the first commercially available whole-transcriptome sorghum microarray (Sorgh-WTa520972F) to identify tissue and genotype-specific expression patterns for all identified Sorghum bicolor exons and UTRs. The genechip contains 1,026,373 probes covering 149,182 exons (27,577 genes) across the Sorghum bicolor nuclear, chloroplast, and mitochondrial genomes. Specific probesets were also included for putative non-coding RNAs that may play a role in gene regulation (e.g., microRNAs), and confirmed functional small RNAs in related species (maize and sugarcane) were also included in our array design. We generated expression data for 78 samples with a combination of four different tissue types (shoot, root, leaf and stem), two dissected stem tissues (pith and rind) and six diverse genotypes, which included 6 public sorghum lines (R159, Atlas, Fremont, PI152611, AR2400 and PI455230) representing grain, sweet, forage, and high biomass ideotypes. Conclusions Here we present a summary of the microarray dataset, including analysis of tissue-specific gene expression profiles and associated expression profiles of relevant metabolic pathways. With an aim to enable identification and functional characterization of genes in sorghum, this expression atlas presents a new and valuable resource to the research community. PMID:24456189

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

PubMed Central

Gouré, Julien; Findlay, Wendy A; Deslandes, Vincent; Bouevitch, Anne; Foote, Simon J; MacInnes, Janet I; Coulton, James W; Nash, John HE; Jacques, Mario

2009-01-01

Background Actinobacillus pleuropneumoniae, the causative agent of porcine pleuropneumonia, is a highly contagious respiratory pathogen that causes severe losses to the swine industry worldwide. Current commercially-available vaccines are of limited value because they do not induce cross-serovar immunity and do not prevent development of the carrier state. Microarray-based comparative genomic hybridizations (M-CGH) were used to estimate whole genomic diversity of representative Actinobacillus pleuropneumoniae strains. Our goal was to identify conserved genes, especially those predicted to encode outer membrane proteins and lipoproteins because of their potential for the development of more effective vaccines. Results Using hierarchical clustering, our M-CGH results showed that the majority of the genes in the genome of the serovar 5 A. pleuropneumoniae L20 strain were conserved in the reference strains of all 15 serovars and in representative field isolates. Fifty-eight conserved genes predicted to encode for outer membrane proteins or lipoproteins were identified. As well, there were several clusters of diverged or absent genes including those associated with capsule biosynthesis, toxin production as well as genes typically associated with mobile elements. Conclusion Although A. pleuropneumoniae strains are essentially clonal, M-CGH analysis of the reference strains of the fifteen serovars and representative field isolates revealed several classes of genes that were divergent or absent. Not surprisingly, these included genes associated with capsule biosynthesis as the capsule is associated with sero-specificity. Several of the conserved genes were identified as candidates for vaccine development, and we conclude that M-CGH is a valuable tool for reverse vaccinology. PMID:19239696

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.

Oligonucleotide microarray chip for the quantification of MS2, ΦX174, and adenoviruses on the multiplex analysis platform MCR 3.

PubMed

Lengger, Sandra; Otto, Johannes; Elsässer, Dennis; Schneider, Oliver; Tiehm, Andreas; Fleischer, Jens; Niessner, Reinhard; Seidel, Michael

2014-05-01

Pathogenic viruses are emerging contaminants in water which should be analyzed for water safety to preserve public health. A strategy was developed to quantify RNA and DNA viruses in parallel on chemiluminescence flow-through oligonucleotide microarrays. In order to show the proof of principle, bacteriophage MS2, ΦX174, and the human pathogenic adenovirus type 2 (hAdV2) were analyzed in spiked tap water samples on the analysis platform MCR 3. The chemiluminescence microarray imaging unit was equipped with a Peltier heater for a controlled heating of the flow cell. The efficiency and selectivity of DNA hybridization could be increased resulting in higher signal intensities and lower cross-reactivities of polymerase chain reaction (PCR) products from other viruses. The total analysis time for DNA/RNA extraction, cDNA synthesis for RNA viruses, polymerase chain reaction, single-strand separation, and oligonucleotide microarray analysis was performed in 4-4.5 h. The parallel quantification was possible in a concentration range of 9.6 × 10(5)-1.4 × 10(10) genomic units (GU)/mL for bacteriophage MS2, 1.4 × 10(5)-3.7 × 10(8) GU/mL for bacteriophage ΦX174, and 6.5 × 10(3)-1.2 × 10(5) for hAdV2, respectively, by using a measuring temperature of 40 °C. Detection limits could be calculated to 6.6 × 10(5) GU/mL for MS2, 5.3 × 10(3) GU/mL for ΦX174, and 1.5 × 10(2) GU/mL for hAdV2, respectively. Real samples of surface water and treated wastewater were tested. Generally, found concentrations of hAdV2, bacteriophage MS2, and ΦX174 were at the detection limit. Nevertheless, bacteriophages could be identified with similar results by means of quantitative PCR and oligonucleotide microarray analysis on the MCR 3.

College of American Pathologists/American College of Medical Genetics proficiency testing for constitutional cytogenomic microarray analysis.

PubMed

Brothman, Arthur R; Dolan, Michelle M; Goodman, Barbara K; Park, Jonathan P; Persons, Diane L; Saxe, Debra F; Tepperberg, James H; Tsuchiya, Karen D; Van Dyke, Daniel L; Wilson, Kathleen S; Wolff, Daynna J; Theil, Karl S

2011-09-01

To evaluate the feasibility of administering a newly established proficiency test offered through the College of American Pathologists and the American College of Medical Genetics for genomic copy number assessment by microarray analysis, and to determine the reproducibility and concordance among laboratory results from this test. Surveys were designed through the Cytogenetic Resource Committee of the two colleges to assess the ability of testing laboratories to process DNA samples provided and interpret results. Supplemental questions were asked with each Survey to determine laboratory practice trends. Twelve DNA specimens, representing 2 pilot and 10 Survey challenges, were distributed to as many as 74 different laboratories, yielding 493 individual responses. The mean consensus for matching result interpretations was 95.7%. Responses to supplemental questions indicate that the number of laboratories offering this testing is increasing, methods for analysis and evaluation are becoming standardized, and array platforms used are increasing in probe density. The College of American Pathologists/American College of Medical Genetics proficiency testing program for copy number assessment by cytogenomic microarray is a successful and efficient mechanism for assessing interlaboratory reproducibility. This will provide laboratories the opportunity to evaluate their performance and assure overall accuracy of patient results. The high level of concordance in laboratory responses across all testing platforms by multiple facilities highlights the robustness of this technology.

Viral pathogen discovery

PubMed Central

Chiu, Charles Y

2015-01-01

Viral pathogen discovery is of critical importance to clinical microbiology, infectious diseases, and public health. Genomic approaches for pathogen discovery, including consensus polymerase chain reaction (PCR), microarrays, and unbiased next-generation sequencing (NGS), have the capacity to comprehensively identify novel microbes present in clinical samples. Although numerous challenges remain to be addressed, including the bioinformatics analysis and interpretation of large datasets, these technologies have been successful in rapidly identifying emerging outbreak threats, screening vaccines and other biological products for microbial contamination, and discovering novel viruses associated with both acute and chronic illnesses. Downstream studies such as genome assembly, epidemiologic screening, and a culture system or animal model of infection are necessary to establish an association of a candidate pathogen with disease. PMID:23725672

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.

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.

Physicians’ Perspectives on the Uncertainties and Implications of Chromosomal Microarray Testing of Children and Families

PubMed Central

Reiff, Marian; Ross, Kathryn; Mulchandani, Surabhi; Propert, Kathleen Joy; Pyeritz, Reed E.; Spinner, Nancy B.; Bernhardt, Barbara A.

2012-01-01

Chromosomal microarray analysis (CMA) has improved the diagnostic rate of genomic disorders in pediatric populations, but can produce uncertain and unexpected findings. This paper explores clinicians’ perspectives and identifies challenges in effectively interpreting results and communicating with families about CMA. Responses to an online survey were obtained from 40 clinicians who had ordered CMA. Content included practice characteristics and perceptions, and queries about a hypothetical case involving uncertain and incidental findings. Data were analyzed using non-parametric statistical tests. Clinicians’ comfort levels differed significantly for explaining uncertain, abnormal, and normal CMA results, with lowest levels for uncertain results. Despite clinical guidelines recommending informed consent, many clinicians did not consider it pertinent to discuss the potential for CMA to reveal information concerning biological parentage or predisposition to late-onset disease, in a hypothetical case. Many non-genetics professionals ordering CMA did not feel equipped to interpret the results for patients, and articulated needs for education and access to genetics professionals. This exploratory study highlights key challenges in the practice of genomic medicine, and identifies needs for education, disseminated practice guidelines, and access to genetics professionals, especially when dealing with uncertain or unexpected findings. PMID:22989118

Characterization of a complex chromosomal rearrangement using chromosome, FISH, and microarray assays in a girl with multiple congenital abnormalities and developmental delay

PubMed Central

2014-01-01

Complex chromosomal rearrangements (CCRs) are balanced or unbalanced structural rearrangements involving three or more cytogenetic breakpoints on two or more chromosomal pairs. The phenotypic anomalies in such cases are attributed to gene disruption, superimposed cryptic imbalances in the genome, and/or position effects. We report a 14-year-old girl who presented with multiple congenital anomalies and developmental delay. Chromosome and FISH analysis indicated a highly complex chromosomal rearrangement involving three chromosomes (3, 7 and 12), seven breakpoints as a result of one inversion, two insertions, and two translocations forming three derivative chromosomes. Additionally, chromosomal microarray study (CMA) revealed two submicroscopic deletions at 3p12.3 (467 kb) and 12q13.12 (442 kb). We postulate that microdeletion within the ROBO1 gene at 3p12.3 may have played a role in the patient’s developmental delay, since it has potential activity-dependent role in neurons. Additionally, factors other than genomic deletions such as loss of function or position effects may also contribute to the abnormal phenotype in our patient. PMID:25478007

Development of the first oligonucleotide microarray for global gene expression profiling in guinea pigs: defining the transcription signature of infectious diseases.

PubMed

Jain, Ruchi; Dey, Bappaditya; Tyagi, Anil K

2012-10-02

The Guinea pig (Cavia porcellus) is one of the most extensively used animal models to study infectious diseases. However, despite its tremendous contribution towards understanding the establishment, progression and control of a number of diseases in general and tuberculosis in particular, the lack of fully annotated guinea pig genome sequence as well as appropriate molecular reagents has severely hampered detailed genetic and immunological analysis in this animal model. By employing the cross-species hybridization technique, we have developed an oligonucleotide microarray with 44,000 features assembled from different mammalian species, which to the best of our knowledge is the first attempt to employ microarray to study the global gene expression profile in guinea pigs. To validate and demonstrate the merit of this microarray, we have studied, as an example, the expression profile of guinea pig lungs during the advanced phase of M. tuberculosis infection. A significant upregulation of 1344 genes and a marked down regulation of 1856 genes in the lungs identified a disease signature of pulmonary tuberculosis infection. We report the development of first comprehensive microarray for studying the global gene expression profile in guinea pigs and validation of its usefulness with tuberculosis as a case study. An important gap in the area of infectious diseases has been addressed and a valuable molecular tool is provided to optimally harness the potential of guinea pig model to develop better vaccines and therapies against human diseases.

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.

The complete genome sequences of 65 Campylobacter jejuni and C. coli strains

USDA-ARS?s Scientific Manuscript database

Campylobacter jejuni (Cj) and C. coli (Cc) are genetically highly diverse based on various molecular methods including MLST, microarray-based comparisons and the whole genome sequences of a few strains. Cj and Cc diversity is also exhibited by variable capsular polysaccharides (CPS) that are the maj...

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

A gene expression signature associated with survival in metastatic melanoma

PubMed Central

Mandruzzato, Susanna; Callegaro, Andrea; Turcatel, Gianluca; Francescato, Samuela; Montesco, Maria C; Chiarion-Sileni, Vanna; Mocellin, Simone; Rossi, Carlo R; Bicciato, Silvio; Wang, Ena; Marincola, Francesco M; Zanovello, Paola

2006-01-01

Background Current clinical and histopathological criteria used to define the prognosis of melanoma patients are inadequate for accurate prediction of clinical outcome. We investigated whether genome screening by means of high-throughput gene microarray might provide clinically useful information on patient survival. Methods Forty-three tumor tissues from 38 patients with stage III and stage IV melanoma were profiled with a 17,500 element cDNA microarray. Expression data were analyzed using significance analysis of microarrays (SAM) to identify genes associated with patient survival, and supervised principal components (SPC) to determine survival prediction. Results SAM analysis revealed a set of 80 probes, corresponding to 70 genes, associated with survival, i.e. 45 probes characterizing longer and 35 shorter survival times, respectively. These transcripts were included in a survival prediction model designed using SPC and cross-validation which allowed identifying 30 predicting probes out of the 80 associated with survival. Conclusion The longer-survival group of genes included those expressed in immune cells, both innate and acquired, confirming the interplay between immunological mechanisms and the natural history of melanoma. Genes linked to immune cells were totally lacking in the poor-survival group, which was instead associated with a number of genes related to highly proliferative and invasive tumor cells. PMID:17129373

DNA microarray-based experimental strategy for trustworthy expression profiling of the hippocampal genes by astaxanthin supplementation in adult mouse

PubMed Central

Yook, Jang Soo; Shibato, Junko; Rakwal, Randeep; Soya, Hideaki

2015-01-01

Naturally occurring astaxantin (ASX) is one of the noticeable carotenoid and dietary supplement, which has strong antioxidant and anti-inflammatory properties, and neuroprotective effects in the brain through crossing the blood–brain barrier. Specially, we are interested in the role of ASX as a brain food. Although ASX has been suggested to have potential benefit to the brain function, the underlying molecular mechanisms and events mediating such effect remain unknown. Here we examined molecular factors in the hippocampus of adult mouse fed ASX diets (0.1% and 0.5% doses) using DNA microarray (Agilent 4 × 44 K whole mouse genome chip) analysis. In this study, we described in detail our experimental workflow and protocol, and validated quality controls with the housekeeping gene expression (Gapdh and Beta-actin) on the dye-swap based approach to advocate our microarray data, which have been uploaded to Gene Expression Omnibus (accession number GSE62197) as a gene resource for the scientific community. This data will also form an important basis for further detailed experiments and bioinformatics analysis with an aim to unravel the potential molecular pathways or mechanisms underlying the positive effects of ASX supplementation on the brain, in particular the hippocampus. PMID:26981356

mRNA Expression Profiling of Laser Microbeam Microdissected Cells from Slender Embryonic Structures

PubMed Central

Scheidl, Stefan J.; Nilsson, Sven; Kalén, Mattias; Hellström, Mats; Takemoto, Minoru; Håkansson, Joakim; Lindahl, Per

2002-01-01

Microarray hybridization has rapidly evolved as an important tool for genomic studies and studies of gene regulation at the transcriptome level. Expression profiles from homogenous samples such as yeast and mammalian cell cultures are currently extending our understanding of biology, whereas analyses of multicellular organisms are more difficult because of tissue complexity. The combination of laser microdissection, RNA amplification, and microarray hybridization has the potential to provide expression profiles from selected populations of cells in vivo. In this article, we present and evaluate an experimental procedure for global gene expression analysis of slender embryonic structures using laser microbeam microdissection and laser pressure catapulting. As a proof of principle, expression profiles from 1000 cells in the mouse embryonic (E9.5) dorsal aorta were generated and compared with profiles for captured mesenchymal cells located one cell diameter further away from the aortic lumen. A number of genes were overexpressed in the aorta, including 11 previously known markers for blood vessels. Among the blood vessel markers were endoglin, tie-2, PDGFB, and integrin-β1, that are important regulators of blood vessel formation. This demonstrates that microarray analysis of laser microbeam micro-dissected cells is sufficiently sensitive for identifying genes with regulative functions. PMID:11891179

Designing microarray and RNA-Seq experiments for greater systems biology discovery in modern plant genomics.

PubMed

Yang, Chuanping; Wei, Hairong

2015-02-01

Microarray and RNA-seq experiments have become an important part of modern genomics and systems biology. Obtaining meaningful biological data from these experiments is an arduous task that demands close attention to many details. Negligence at any step can lead to gene expression data containing inadequate or composite information that is recalcitrant for pattern extraction. Therefore, it is imperative to carefully consider experimental design before launching a time-consuming and costly experiment. Contemporarily, most genomics experiments have two objectives: (1) to generate two or more groups of comparable data for identifying differentially expressed genes, gene families, biological processes, or metabolic pathways under experimental conditions; (2) to build local gene regulatory networks and identify hierarchically important regulators governing biological processes and pathways of interest. Since the first objective aims to identify the active molecular identities and the second provides a basis for understanding the underlying molecular mechanisms through inferring causality relationships mediated by treatment, an optimal experiment is to produce biologically relevant and extractable data to meet both objectives without substantially increasing the cost. This review discusses the major issues that researchers commonly face when embarking on microarray or RNA-seq experiments and summarizes important aspects of experimental design, which aim to help researchers deliberate how to generate gene expression profiles with low background noise but with more interaction to facilitate novel biological discoveries in modern plant genomics. Copyright © 2015 The Author. Published by Elsevier Inc. All rights reserved.

Sparse representation and Bayesian detection of genome copy number alterations from microarray data.

PubMed

Pique-Regi, Roger; Monso-Varona, Jordi; Ortega, Antonio; Seeger, Robert C; Triche, Timothy J; Asgharzadeh, Shahab

2008-02-01

Genomic instability in cancer leads to abnormal genome copy number alterations (CNA) that are associated with the development and behavior of tumors. Advances in microarray technology have allowed for greater resolution in detection of DNA copy number changes (amplifications or deletions) across the genome. However, the increase in number of measured signals and accompanying noise from the array probes present a challenge in accurate and fast identification of breakpoints that define CNA. This article proposes a novel detection technique that exploits the use of piece wise constant (PWC) vectors to represent genome copy number and sparse Bayesian learning (SBL) to detect CNA breakpoints. First, a compact linear algebra representation for the genome copy number is developed from normalized probe intensities. Second, SBL is applied and optimized to infer locations where copy number changes occur. Third, a backward elimination (BE) procedure is used to rank the inferred breakpoints; and a cut-off point can be efficiently adjusted in this procedure to control for the false discovery rate (FDR). The performance of our algorithm is evaluated using simulated and real genome datasets and compared to other existing techniques. Our approach achieves the highest accuracy and lowest FDR while improving computational speed by several orders of magnitude. The proposed algorithm has been developed into a free standing software application (GADA, Genome Alteration Detection Algorithm). http://biron.usc.edu/~piquereg/GADA

Single-feature polymorphism discovery in the barley transcriptome

PubMed Central

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

2005-01-01

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

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

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

High-throughput multiplex HLA-typing by ligase detection reaction (LDR) and universal array (UA) approach.

PubMed

Consolandi, Clarissa

2009-01-01

One major goal of genetic research is to understand the role of genetic variation in living systems. In humans, by far the most common type of such variation involves differences in single DNA nucleotides, and is thus termed single nucleotide polymorphism (SNP). The need for improvement in throughput and reliability of traditional techniques makes it necessary to develop new technologies. Thus the past few years have witnessed an extraordinary surge of interest in DNA microarray technology. This new technology offers the first great hope for providing a systematic way to explore the genome. It permits a very rapid analysis of thousands genes for the purpose of gene discovery, sequencing, mapping, expression, and polymorphism detection. We generated a series of analytical tools to address the manufacturing, detection and data analysis components of a microarray experiment. In particular, we set up a universal array approach in combination with a PCR-LDR (polymerase chain reaction-ligation detection reaction) strategy for allele identification in the HLA gene.

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.

The MGED ontology: a framework for describing functional genomics experiments.

PubMed

Stoeckert, Christian J; Parkinson, Helen

2003-01-01

The Microarray Gene Expression Data (MGED) society was formed with an initial focus on experiments involving microarray technology. Despite the diversity of applications, there are common concepts used and a common need to capture experimental information in a standardized manner. In building the MGED ontology, it was recognized that it would be impractical to cover all the different types of experiments on all the different types of organisms by listing and defining all the types of organisms and their properties. Our solution was to create a framework for describing microarray experiments with an initial focus on the biological sample and its manipulation. For concepts that are common for many species, we could provide a manageable listing of controlled terms. For concepts that are species-specific or whose values cannot be readily listed, we created an 'OntologyEntry' concept that referenced an external resource. The MGED ontology is a work in progress that needs additional instances and particularly needs constraints to be added. The ontology currently covers the experimental sample and design, and we have begun capturing aspects of the microarrays themselves as well. The primary application of the ontology will be to develop forms for entering information into databases, and consequently allowing queries, taking advantage of the structure provided by the ontology. The application of an ontology of experimental conditions extends beyond microarray experiments and, as the scope of MGED includes other aspects of functional genomics, so too will the MGED ontology.

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

PubMed

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

2013-01-01

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

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

PubMed Central

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

2013-01-01

Outbreaks of human infection linked to the powdered infant formula (PIF) food chain and associated with the bacterium Cronobacter, are of concern to public health. These bacteria are regarded as opportunistic pathogens linked to life-threatening infections predominantly in neonates, with an under developed immune system. Monitoring the microbiological ecology of PIF production sites is an important step in attempting to limit the risk of contamination in the finished food product. Cronobacter species, like other microorganisms can adapt to the production environment. These organisms are known for their desiccation tolerance, a phenotype that can aid their survival in the production site and PIF itself. In evaluating the genome data currently available for Cronobacter species, no sequence information has been published describing a Cronobacter sakazakii isolate found to persist in a PIF production facility. Here we report on the complete genome sequence of one such isolate, Cronobacter sakazakii SP291 along with its phenotypic characteristics. The genome of C. sakazakii SP291 consists of a 4.3-Mb chromosome (56.9% GC) and three plasmids, denoted as pSP291-1, [118.1-kb (57.2% GC)], pSP291-2, [52.1-kb (49.2% GC)], and pSP291-3, [4.4-kb (54.0% GC)]. When C. sakazakii SP291 was compared to the reference C. sakazakii ATCC BAA-894, which is also of PIF origin, the annotated genome data identified two interesting functional categories, comprising of genes related to the bacterial stress response and resistance to antimicrobial and toxic compounds. Using a phenotypic microarray (PM), we provided a full metabolic profile comparing C. sakazakii SP291 and the previously sequenced C. sakazakii ATCC BAA-894. These data extend our understanding of the genome of this important neonatal pathogen and provides further insights into the genotypes associated with features that can contribute to its persistence in the PIF environment. PMID:24032028

Differential Adipose Tissue Gene Expression Profiles in Abacavir Treated Patients That May Contribute to the Understanding of Cardiovascular Risk: A Microarray Study

PubMed Central

Shahmanesh, Mohsen; Phillips, Kenneth; Boothby, Meg; Tomlinson, Jeremy W.

2015-01-01

Objective To compare changes in gene expression by microarray from subcutaneous adipose tissue from HIV treatment naïve patients treated with efavirenz based regimens containing abacavir (ABC), tenofovir (TDF) or zidovidine (AZT). Design Subcutaneous fat biopsies were obtained before, at 6- and 18–24-months after treatment, and from HIV negative controls. Groups were age, ethnicity, weight, biochemical profile, and pre-treatment CD4 count matched. Microarray data was generated using the Agilent Whole Human Genome Microarray. Identification of differentially expressed genes and genomic response pathways was performed using limma and gene set enrichment analysis. Results There were significant divergences between ABC and the other two groups 6 months after treatment in genes controlling cell adhesion and environmental information processing, with some convergence at 18–24 months. Compared to controls the ABC group, but not AZT or TDF showed enrichment of genes controlling adherence junction, at 6 months and 18–24 months (adjusted p<0.05) and focal adhesions and tight junction at 6 months (p<0.5). Genes controlling leukocyte transendothelial migration (p<0.05) and ECM-receptor interactions (p = 0.04) were over-expressed in ABC compared to TDF and AZT at 6 months but not at 18–24 months. Enrichment of pathways and individual genes controlling cell adhesion and environmental information processing were specifically dysregulated in the ABC group in comparison with other treatments. There was little difference between AZT and TDF. Conclusion After initiating treatment, there is divergence in the expression of genes controlling cell adhesion and environmental information processing between ABC and both TDF and AZT in subcutaneous adipose tissue. If similar changes are also taking place in other tissues including the coronary vasculature they may contribute to the increased risk of cardiovascular events reported in patients recently started on abacavir-containing regimens. PMID:25617630

Integrative Genome Comparison of Primary and Metastatic Melanomas

PubMed Central

Feng, Bin; Nazarian, Rosalynn M.; Bosenberg, Marcus; Wu, Min; Scott, Kenneth L.; Kwong, Lawrence N.; Xiao, Yonghong; Cordon-Cardo, Carlos; Granter, Scott R.; Ramaswamy, Sridhar; Golub, Todd; Duncan, Lyn M.; Wagner, Stephan N.; Brennan, Cameron; Chin, Lynda

2010-01-01

A cardinal feature of malignant melanoma is its metastatic propensity. An incomplete view of the genetic events driving metastatic progression has been a major barrier to rational development of effective therapeutics and prognostic diagnostics for melanoma patients. In this study, we conducted global genomic characterization of primary and metastatic melanomas to examine the genomic landscape associated with metastatic progression. In addition to uncovering three genomic subclasses of metastastic melanomas, we delineated 39 focal and recurrent regions of amplification and deletions, many of which encompassed resident genes that have not been implicated in cancer or metastasis. To identify progression-associated metastasis gene candidates, we applied a statistical approach, Integrative Genome Comparison (IGC), to define 32 genomic regions of interest that were significantly altered in metastatic relative to primary melanomas, encompassing 30 resident genes with statistically significant expression deregulation. Functional assays on a subset of these candidates, including MET, ASPM, AKAP9, IMP3, PRKCA, RPA3, and SCAP2, validated their pro-invasion activities in human melanoma cells. Validity of the IGC approach was further reinforced by tissue microarray analysis of Survivin showing significant increased protein expression in thick versus thin primary cutaneous melanomas, and a progression correlation with lymph node metastases. Together, these functional validation results and correlative analysis of human tissues support the thesis that integrated genomic and pathological analyses of staged melanomas provide a productive entry point for discovery of melanoma metastases genes. PMID:20520718

Evaluating reproducibility of differential expression discoveries in microarray studies by considering correlated molecular changes.

PubMed

Zhang, Min; Zhang, Lin; Zou, Jinfeng; Yao, Chen; Xiao, Hui; Liu, Qing; Wang, Jing; Wang, Dong; Wang, Chenguang; Guo, Zheng

2009-07-01

According to current consistency metrics such as percentage of overlapping genes (POG), lists of differentially expressed genes (DEGs) detected from different microarray studies for a complex disease are often highly inconsistent. This irreproducibility problem also exists in other high-throughput post-genomic areas such as proteomics and metabolism. A complex disease is often characterized with many coordinated molecular changes, which should be considered when evaluating the reproducibility of discovery lists from different studies. We proposed metrics percentage of overlapping genes-related (POGR) and normalized POGR (nPOGR) to evaluate the consistency between two DEG lists for a complex disease, considering correlated molecular changes rather than only counting gene overlaps between the lists. Based on microarray datasets of three diseases, we showed that though the POG scores for DEG lists from different studies for each disease are extremely low, the POGR and nPOGR scores can be rather high, suggesting that the apparently inconsistent DEG lists may be highly reproducible in the sense that they are actually significantly correlated. Observing different discovery results for a disease by the POGR and nPOGR scores will obviously reduce the uncertainty of the microarray studies. The proposed metrics could also be applicable in many other high-throughput post-genomic areas.

Optimized Probe Masking for Comparative Transcriptomics of Closely Related Species

PubMed Central

Poeschl, Yvonne; Delker, Carolin; Trenner, Jana; Ullrich, Kristian Karsten; Quint, Marcel; Grosse, Ivo

2013-01-01

Microarrays are commonly applied to study the transcriptome of specific species. However, many available microarrays are restricted to model organisms, and the design of custom microarrays for other species is often not feasible. Hence, transcriptomics approaches of non-model organisms as well as comparative transcriptomics studies among two or more species often make use of cost-intensive RNAseq studies or, alternatively, by hybridizing transcripts of a query species to a microarray of a closely related species. When analyzing these cross-species microarray expression data, differences in the transcriptome of the query species can cause problems, such as the following: (i) lower hybridization accuracy of probes due to mismatches or deletions, (ii) probes binding multiple transcripts of different genes, and (iii) probes binding transcripts of non-orthologous genes. So far, methods for (i) exist, but these neglect (ii) and (iii). Here, we propose an approach for comparative transcriptomics addressing problems (i) to (iii), which retains only transcript-specific probes binding transcripts of orthologous genes. We apply this approach to an Arabidopsis lyrata expression data set measured on a microarray designed for Arabidopsis thaliana, and compare it to two alternative approaches, a sequence-based approach and a genomic DNA hybridization-based approach. We investigate the number of retained probe sets, and we validate the resulting expression responses by qRT-PCR. We find that the proposed approach combines the benefit of sequence-based stringency and accuracy while allowing the expression analysis of much more genes than the alternative sequence-based approach. As an added benefit, the proposed approach requires probes to detect transcripts of orthologous genes only, which provides a superior base for biological interpretation of the measured expression responses. PMID:24260119

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

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.

Demonstration of a novel Xp22.2 microdeletion as the cause of familial extreme skewing of X-inactivation utilizing case-parent trio SNP microarray analysis.

PubMed

Mason, Jane A; Aung, Hnin T; Nandini, Adayapalam; Woods, Rickie G; Fairbairn, David J; Rowell, John A; Young, David; Susman, Rachel D; Brown, Simon A; Hyland, Valentine J; Robertson, Jeremy D

2018-05-01

We report a kindred referred for molecular investigation of severe hemophilia A in a young female in which extremely skewed X-inactivation was observed in both the proband and her clinically normal mother. Bidirectional Sanger sequencing of all F8 gene coding regions and exon/intron boundaries was undertaken. Methylation-sensitive restriction enzymes were utilized to investigate skewed X-inactivation using both a classical human androgen receptor (HUMARA) assay, and a novel method targeting differential methylation patterns in multiple informative X-chromosome SNPs. Illumina Whole-Genome Infinium microarray analysis was performed in the case-parent trio (proband and both parents), and the proband's maternal grandmother. The proband was a cytogenetically normal female with severe hemophilia A resulting from a heterozygous F8 pathogenic variant inherited from her similarly affected father. No F8 mutation was identified in the proband's mother, however, both the proband and her mother both demonstrated completely skewed X-chromosome inactivation (100%) in association with a previously unreported 2.3 Mb deletion at Xp22.2. At least three disease-associated genes (FANCB, AP1S2, and PIGA) were contained within the deleted region. We hypothesize that true "extreme" skewing of X-inactivation (≥95%) is a rare occurrence, but when defined correctly there is a high probability of finding an X-chromosome disease-causing variant or larger deletion resulting in X-inactivation through a survival disadvantage or cell lethal mechanism. We postulate that the 2.3 Mb Xp22.2 deletion identified in our kindred arose de novo in the proband's mother (on the grandfather's homolog), and produced extreme skewing of X-inactivation via a "cell lethal" mechanism. We introduce a novel multitarget approach for X-inactivation analysis using multiple informative differentially methylated SNPs, as an alternative to the classical single locus (HUMARA) method. We propose that for females with unexplained severe phenotypic expression of an X-linked recessive disorder trio-SNP microarray should be undertaken in combination with X-inactivation analysis. © 2018 The Authors. Molecular Genetics & Genomic Medicine published by Wiley Periodicals, Inc.

ACTIVITIES TO DEVELOP AN INTERIM GUIDANCE FOR MICROARRAY-BASED ASSAYS FOR REGULATORY AND RISK ASSESSMENT APPLICATIONS AT EPA

EPA Science Inventory

Abstract for presentation. Advances in genomics will have significant implications for risk assessment policies and regulatory decision making. In 2002, EPA issued its lnterim Policy on Genomics which stated that such data may be considered in the decision making process, but tha...

A Universal Genome Array and Transcriptome Atlas for Brachypodium Distachyon

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

Mockler, Todd

Brachypodium distachyon is the premier experimental model grass platform and is related to candidate feedstock crops for bioethanol production. Based on the DOE-JGI Brachypodium Bd21 genome sequence and annotation we designed a whole genome DNA microarray platform. The quality of this array platform is unprecedented due to the exceptional quality of the Brachypodium genome assembly and annotation and the stringent probe selection criteria employed in the design. We worked with members of the international community and the bioinformatics/design team at Affymetrix at all stages in the development of the array. We used the Brachypodium arrays to interrogate the transcriptomes ofmore » plants grown in a variety of environmental conditions including diurnal and circadian light/temperature conditions and under a variety of environmental conditions. We examined the transciptional responses of Brachypodium seedlings subjected to various abiotic stresses including heat, cold, salt, and high intensity light. We generated a gene expression atlas representing various organs and developmental stages. The results of these efforts including all microarray datasets are published and available at online public databases.« less

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.

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

Genomic Analysis of Vaccine-Derived Poliovirus Strains in Stool Specimens by Combination of Full-Length PCR and Oligonucleotide Microarray Hybridization

PubMed Central

Laassri, Majid; Dragunsky, Eugenia; Enterline, Joan; Eremeeva, Tatiana; Ivanova, Olga; Lottenbach, Kathleen; Belshe, Robert; Chumakov, Konstantin

2005-01-01

Sabin strains of poliovirus used in the manufacture of oral poliovirus vaccine (OPV) are prone to genetic variations that occur during growth in cell cultures and the organisms of vaccine recipients. Such derivative viruses often have increased neurovirulence and transmissibility, and in some cases they can reestablish chains of transmission in human populations. Monitoring for vaccine-derived polioviruses is an important part of the worldwide campaign to eradicate poliomyelitis. Analysis of vaccine-derived polioviruses requires, as a first step, their isolation in cell cultures, which takes significant time and may yield viral stocks that are not fully representative of the strains present in the original sample. Here we demonstrate that full-length viral cDNA can be PCR amplified directly from stool samples and immediately subjected to genomic analysis by oligonucleotide microarray hybridization and nucleotide sequencing. Most fecal samples from healthy children who received OPV were found to contain variants of Sabin vaccine viruses. Sequence changes in the 5′ untranslated region were common, as were changes in the VP1-coding region, including changes in a major antigenic site. Analysis of stool samples taken from cases of acute flaccid paralysis revealed the presence of mixtures of recombinant polioviruses, in addition to the emergence of new sequence variants. Avoiding the need for cell culture isolation dramatically shortened the time needed for identification and analysis of vaccine-derived polioviruses and could be useful for preliminary screening of clinical samples. The amplified full-length viral cDNA can be archived and used to recover live virus for further virological studies. PMID:15956413

Transcriptome interrogation of human myometrium identifies differentially expressed sense-antisense pairs of protein-coding and long non-coding RNA genes in spontaneous labor at term.

PubMed

Romero, Roberto; Tarca, Adi L; Chaemsaithong, Piya; Miranda, Jezid; Chaiworapongsa, Tinnakorn; Jia, Hui; Hassan, Sonia S; Kalita, Cynthia A; Cai, Juan; Yeo, Lami; Lipovich, Leonard

2014-09-01

To identify differentially expressed long non-coding RNA (lncRNA) genes in human myometrium in women with spontaneous labor at term. Myometrium was obtained from women undergoing cesarean deliveries who were not in labor (n = 19) and women in spontaneous labor at term (n = 20). RNA was extracted and profiled using an Illumina® microarray platform. We have used computational approaches to bound the extent of long non-coding RNA representation on this platform, and to identify co-differentially expressed and correlated pairs of long non-coding RNA genes and protein-coding genes sharing the same genomic loci. We identified co-differential expression and correlation at two genomic loci that contain coding-lncRNA gene pairs: SOCS2-AK054607 and LMCD1-NR_024065 in women in spontaneous labor at term. This co-differential expression and correlation was validated by qRT-PCR, an experimental method completely independent of the microarray analysis. Intriguingly, one of the two lncRNA genes differentially expressed in term labor had a key genomic structure element, a splice site, that lacked evolutionary conservation beyond primates. We provide, for the first time, evidence for coordinated differential expression and correlation of cis-encoded antisense lncRNAs and protein-coding genes with known as well as novel roles in pregnancy in the myometrium of women in spontaneous labor at term.

Whole genome mRNA transcriptomics analysis reveals different modes of action of the diarrheic shellfish poisons okadaic acid and dinophysis toxin-1 versus azaspiracid-1 in Caco-2 cells.

PubMed

Bodero, Marcia; Hoogenboom, Ron L A P; Bovee, Toine F H; Portier, Liza; de Haan, Laura; Peijnenburg, Ad; Hendriksen, Peter J M

2018-02-01

A study with DNA microarrays was performed to investigate the effects of two diarrhetic and one azaspiracid shellfish poison, okadaic acid (OA), dinophysistoxin-1 (DTX-1) and azaspiracid-1 (AZA-1) respectively, on the whole-genome mRNA expression of undifferentiated intestinal Caco-2 cells. Previously, the most responding genes were used to develop a dedicated array tube test to screen shellfish samples on the presence of these toxins. In the present study the whole genome mRNA expression was analyzed in order to reveal modes of action and obtain hints on potential biomarkers suitable to be used in alternative bioassays. Effects on key genes in the most affected pathways and processes were confirmed by qPCR. OA and DTX-1 induced almost identical effects on mRNA expression, which strongly indicates that OA and DTX-1induce similar toxic effects. Biological interpretation of the microarray data indicates that both compounds induce hypoxia related pathways/processes, the unfolded protein response (UPR) and endoplasmic reticulum (ER) stress. The gene expression profile of AZA-1 is different and shows increased mRNA expression of genes involved in cholesterol synthesis and glycolysis, suggesting a different mode of action for this toxin. Future studies should reveal whether identified pathways provide suitable biomarkers for rapid detection of DSPs in shellfish. Copyright © 2017 The Authors. Published by Elsevier Ltd.. All rights reserved.

Visualization for genomics: the Microbial Genome Viewer.

PubMed

Kerkhoven, Robert; van Enckevort, Frank H J; Boekhorst, Jos; Molenaar, Douwe; Siezen, Roland J

2004-07-22

A Web-based visualization tool, the Microbial Genome Viewer, is presented that allows the user to combine complex genomic data in a highly interactive way. This Web tool enables the interactive generation of chromosome wheels and linear genome maps from genome annotation data stored in a MySQL database. The generated images are in scalable vector graphics (SVG) format, which is suitable for creating high-quality scalable images and dynamic Web representations. Gene-related data such as transcriptome and time-course microarray experiments can be superimposed on the maps for visual inspection. The Microbial Genome Viewer 1.0 is freely available at http://www.cmbi.kun.nl/MGV

Genotoxic Changes to Rodent Cells Exposed in Vitro to Tungsten, Nickel, Cobalt and Iron

DTIC Science & Technology

2014-03-10

SAR) 18. NUMBER OF PAGES 20 19a. NAME OF RESPONSIBLE PERSON a. REPORT unclassified b. ABSTRACT unclassified c . THIS PAGE unclassified...37 ° C in a humidified atmosphere of 5% CO2 in air. Cultures were routinely fed every 3–4 days, and passaged weekly. Experiments were conducted...Samples were stored at −80 ° C until needed. 2.4. Microarray Analysis RNA samples were sent to the Genomics Core of the Lerner Research Institute at the

A list of tables summarizing various Cmap analysis, from which the final tables in the manuscript are based on

EPA Pesticide Factsheets

Various Cmap analyses within and across species and microarray platforms conducted and summarized to generate the tables in the publication.This dataset is associated with the following publication:Wang , R., A. Biales , N. Garcia-Reyero, E. Perkins, D. Villeneuve, G. Ankley, and D. Bencic. Fish Connectivity Mapping: Linking Chemical Stressors by Their MOA-Driven Transcriptomic Profiles. BMC Genomics. BioMed Central Ltd, London, UK, 17(84): 1-20, (2016).

Conserved noncoding sequences conserve biological networks and influence genome evolution.

PubMed

Xie, Jianbo; Qian, Kecheng; Si, Jingna; Xiao, Liang; Ci, Dong; Zhang, Deqiang

2018-05-01

Comparative genomics approaches have identified numerous conserved cis-regulatory sequences near genes in plant genomes. Despite the identification of these conserved noncoding sequences (CNSs), our knowledge of their functional importance and selection remains limited. Here, we used a combination of DNA methylome analysis, microarray expression analyses, and functional annotation to study these sequences in the model tree Populus trichocarpa. Methylation in CG contexts and non-CG contexts was lower in CNSs, particularly CNSs in the 5'-upstream regions of genes, compared with other sites in the genome. We observed that CNSs are enriched in genes with transcription and binding functions, and this also associated with syntenic genes and those from whole-genome duplications, suggesting that cis-regulatory sequences play a key role in genome evolution. We detected a significant positive correlation between CNS number and protein interactions, suggesting that CNSs may have roles in the evolution and maintenance of biological networks. The divergence of CNSs indicates that duplication-degeneration-complementation drives the subfunctionalization of a proportion of duplicated genes from whole-genome duplication. Furthermore, population genomics confirmed that most CNSs are under strong purifying selection and only a small subset of CNSs shows evidence of adaptive evolution. These findings provide a foundation for future studies exploring these key genomic features in the maintenance of biological networks, local adaptation, and transcription.

Automation of complex assays: pharmacogenetics of warfarin dosing.

PubMed

Wu, Whei-Kuo; Hujsak, Paul G; Kureshy, Fareed

2007-10-01

AutoGenomics, Inc. (Carlsbad, CA, USA) have developed a multiplex microarray assay for genotyping both VKORC1 and CYP2C9 using the INFINITI(™) Analyzer. Multiple alleles in each DNA sample are analyzed by polymerase chain reaction amplification, followed by detection primer extension using the INFINITI Analyzer. The INFINITI Analyzer performs single-nucleotide polymorphism (SNP) analysis using universal oligonucleotides immobilized on the biochip. To genotype broader ethnic groups, genomic DNA from whole blood was tested for nine SNPs for VKORC1 and six for CYP2C9 genotypes. Information related to all 15 SNPs is needed to determine dosing of population of diverse ethnic origin. The INFINITI system provides genotyping information for same day dosing of warfarin.

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.

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

PubMed Central

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

2007-01-01

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

DNA Mismatch Repair Deficiency Promotes Genomic Instability in a Subset of Papillary Thyroid Cancers.

PubMed

Javid, Mahsa; Sasanakietkul, Thanyawat; Nicolson, Norman G; Gibson, Courtney E; Callender, Glenda G; Korah, Reju; Carling, Tobias

2018-02-01

Efficient DNA damage repair by MutL-homolog DNA mismatch repair (MMR) enzymes, MLH1, MLH3, PMS1 and PMS2, are required to maintain thyrocyte genomic integrity. We hypothesized that persistent oxidative stress and consequent transcriptional dysregulation observed in thyroid follicles will lead to MMR deficiency and potentiate papillary thyroid tumorigenesis. MMR gene expression was analyzed by targeted microarray in 18 papillary thyroid cancer (PTC), 9 paracarcinoma normal thyroid (PCNT) and 10 normal thyroid (NT) samples. The findings were validated by qRT-PCR, and in follicular thyroid cancers (FTC) and follicular thyroid adenomas (FTA) for comparison. FOXO transcription factor expression was also analyzed. Protein expression was assessed by immunohistochemistry. Genomic integrity was evaluated by whole-exome sequencing-derived read-depth analysis and Mann-Whitney U test. Clinical correlations were assessed using Fisher's exact and t tests. Microarray and qRT-PCR revealed reduced expression of all four MMR genes in PTC compared with PCNT and of PMS2 compared with NT. FTC and FTA showed upregulation in MLH1, MLH3 and PMS2. PMS2 protein expression correlated with the mRNA expression pattern. FOXO1 showed lower expression in PMS2-deficient PTCs (log2-fold change -1.72 vs. -0.55, U = 11, p < 0.05 two-tailed). Rate of LOH, a measure of genomic instability, was higher in PMS2-deficient PTCs (median 3 and 1, respectively; U = 26, p < 0.05 two-tailed). No correlation was noted between MMR deficiency and clinical characteristics. MMR deficiency, potentially promoted by FOXO1 suppression, may explain the etiology for PTC development in some patients. FTC and FTA retain MMR activity and are likely caused by a different tumorigenic pathway.

A Sorghum bicolor expression atlas reveals dynamic genotype-specific expression profiles for vegetative tissues of grain, sweet and bioenergy sorghums

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

Shakoor, N; Nair, R; Crasta, O

2014-01-23

Background: Effective improvement in sorghum crop development necessitates a genomics-based approach to identify functional genes and QTLs. Sequenced in 2009, a comprehensive annotation of the sorghum genome and the development of functional genomics resources is key to enable the discovery and deployment of regulatory and metabolic genes and gene networks for crop improvement. Results: This study utilizes the first commercially available whole-transcriptome sorghum microarray (Sorgh-WTa520972F) to identify tissue and genotype-specific expression patterns for all identified Sorghum bicolor exons and UTRs. The genechip contains 1,026,373 probes covering 149,182 exons (27,577 genes) across the Sorghum bicolor nuclear, chloroplast, and mitochondrial genomes. Specificmore » probesets were also included for putative non-coding RNAs that may play a role in gene regulation (e. g., microRNAs), and confirmed functional small RNAs in related species (maize and sugarcane) were also included in our array design. We generated expression data for 78 samples with a combination of four different tissue types (shoot, root, leaf and stem), two dissected stem tissues (pith and rind) and six diverse genotypes, which included 6 public sorghum lines (R159, Atlas, Fremont, PI152611, AR2400 and PI455230) representing grain, sweet, forage, and high biomass ideotypes. Conclusions: Here we present a summary of the microarray dataset, including analysis of tissue-specific gene expression profiles and associated expression profiles of relevant metabolic pathways. With an aim to enable identification and functional characterization of genes in sorghum, this expression atlas presents a new and valuable resource to the research community.« less

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

Review of Processing and Analytical Methods for Francisella ...

EPA Pesticide Factsheets

Journal Article The etiological agent of tularemia, Francisella tularensis, is a resilient organism within the environment and can be acquired many ways (infectious aerosols and dust, contaminated food and water, infected carcasses, and arthropod bites). However, isolating F. tularensis from environmental samples can be challenging due to its nutritionally fastidious and slow-growing nature. In order to determine the current state of the science regarding available processing and analytical methods for detection and recovery of F. tularensis from water and soil matrices, a review of the literature was conducted. During the review, analysis via culture, immunoassays, and genomic identification were the most commonly found methods for F. tularensis detection within environmental samples. Other methods included combined culture and genomic analysis for rapid quantification of viable microorganisms and use of one assay to identify multiple pathogens from a single sample. Gaps in the literature that were identified during this review suggest that further work to integrate culture and genomic identification would advance our ability to detect and to assess the viability of Francisella spp. The optimization of DNA extraction, whole genome amplification with inhibition-resistant polymerases, and multiagent microarray detection would also advance biothreat detection.

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

PubMed Central

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

2008-01-01

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

Quantification of viable and non-viable Legionella spp. by heterogeneous asymmetric recombinase polymerase amplification (haRPA) on a flow-based chemiluminescence microarray.

PubMed

Kober, Catharina; Niessner, Reinhard; Seidel, Michael

2018-02-15

Increasing numbers of legionellosis outbreaks within the last years have shown that Legionella are a growing challenge for public health. Molecular biological detection methods capable of rapidly identifying viable Legionella are important for the control of engineered water systems. The current gold standard based on culture methods takes up to 10 days to show positive results. For this reason, a flow-based chemiluminescence (CL) DNA microarray was developed that is able to quantify viable and non-viable Legionella spp. as well as Legionella pneumophila in one hour. An isothermal heterogeneous asymmetric recombinase polymerase amplification (haRPA) was carried out on flow-based CL DNA microarrays. Detection limits of 87 genomic units (GU) µL -1 and 26GUµL -1 for Legionella spp. and Legionella pneumophila, respectively, were achieved. In this work, it was shown for the first time that the combination of a propidium monoazide (PMA) treatment with haRPA, the so-called viability haRPA, is able to identify viable Legionella on DNA microarrays. Different proportions of viable and non-viable Legionella, shown with the example of L. pneumophila, ranging in a total concentration between 10 1 to 10 5 GUµL -1 were analyzed on the microarray analysis platform MCR 3. Recovery values for viable Legionella spp. were found between 81% and 133%. With the combination of these two methods, there is a chance to replace culture-based methods in the future for the monitoring of engineered water systems like condensation recooling plants. Copyright © 2017 Elsevier B.V. All rights reserved.

The GermOnline cross-species systems browser provides comprehensive information on genes and gene products relevant for sexual reproduction.

PubMed

Gattiker, Alexandre; Niederhauser-Wiederkehr, Christa; Moore, James; Hermida, Leandro; Primig, Michael

2007-01-01

We report a novel release of the GermOnline knowledgebase covering genes relevant for the cell cycle, gametogenesis and fertility. GermOnline was extended into a cross-species systems browser including information on DNA sequence annotation, gene expression and the function of gene products. The database covers eight model organisms and Homo sapiens, for which complete genome annotation data are available. The database is now built around a sophisticated genome browser (Ensembl), our own microarray information management and annotation system (MIMAS) used to extensively describe experimental data obtained with high-density oligonucleotide microarrays (GeneChips) and a comprehensive system for online editing of database entries (MediaWiki). The RNA data include results from classical microarrays as well as tiling arrays that yield information on RNA expression levels, transcript start sites and lengths as well as exon composition. Members of the research community are solicited to help GermOnline curators keep database entries on genes and gene products complete and accurate. The database is accessible at http://www.germonline.org/.

Chromosomal microarray analysis of Bulgarian patients with epilepsy and intellectual disability.

PubMed

Peycheva, Valentina; Kamenarova, Kunka; Ivanova, Neviana; Stamatov, Dimitar; Avdjieva-Tzavella, Daniela; Alexandrova, Iliana; Zhelyazkova, Sashka; Pacheva, Iliana; Dimova, Petya; Ivanov, Ivan; Litvinenko, Ivan; Bozhinova, Veneta; Tournev, Ivailo; Simeonov, Emil; Mitev, Vanyo; Jordanova, Albena; Kaneva, Radka

2018-08-15

High resolution chromosomal microarray analysis (CMA) has facilitated the identification of small chromosomal rearrangements throughout the genome, associated with various neurodevelopmental phenotypes, including ID/DD. Recently, it became evident that intellectual disability (ID)/developmental delay (DD) can occur with associated co-morbidities like epileptic seizures, autism and additional congenital anomalies. These observations require whole genome approach in order to detect the genetic causes of these complex disorders. In this study, we examined 92 patients of Bulgarian origin at age between 1 and 22 years with ID, generalized epilepsy, autistic signs and congenital anomalies. CMA was carried out using SurePrint G3 Human CGH Microarray Kit, 4 × 180 K and SurePrint G3 Unrestricted CGH ISCA v2, 4 × 180 K oligo platforms. Referral indications for selection of the patients were the presence of generalized refractory seizures disorders and co-morbid ID. Clearly pathogenic copy number variations (CNVs) were detected in eight patients (8.7%) from our cohort. Additionally, possibly pathogenic rearrangements of unclear clinical significance were detected in six individuals (6.5%), which make for an overall diagnostic yield of 15.2% among our cohort of patients. We report here the patients with clearly pathogenic CNVs, discuss the potential causality of the possibly pathogenic CNVs and make genotype - phenotype correlations. One novel possibly pathogenic heterozygous deletion in 15q22.31 region was detected in a case with ID/DD. Additionally, whole APBA2 gene duplication in 15q13.1 was found in three generations of a family with epilepsy, ID and psychiatric abnormalities. The results from this study allow us to define the genetic diagnosis in a subset of Bulgarian patients and improve the genetic counseling of the affected families. To our knowledge, this is the first aCGH evaluation of a Bulgarian cohort of children with epilepsy and ID so far. Copyright © 2018 Elsevier B.V. All rights reserved.

Microbial forensics: fiber optic microarray subtyping of Bacillus anthracis

NASA Astrophysics Data System (ADS)

Shepard, Jason R. E.

2009-05-01

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

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

Bioinformatics/biostatistics: microarray analysis.

PubMed

Eichler, Gabriel S

2012-01-01

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

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

Microarray slide hybridization using fluorescently labeled cDNA.

PubMed

Ares, Manuel

2014-01-01

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

Profiling of the yak skeletal muscle tissue gene expression and comparison with the domestic cattle by genome array.

PubMed

Wang, H B; Zan, L S; Zhang, Y Y

2014-01-01

Of all the mammals of the world, the yak lives at the highest altitude area of more than 3000 m. Comparison between yak and cattle of the low-altitude areas will be informative in studying animal adaptation to higher altitudes. To investigate the molecular mechanism involved in meat quality differences between the two Chinese special varieties Qinghai yak and Qinchuan cattle, 12 chemical-physical characteristics of the longissimus dorsi muscle related to meat quality were compared at the age of 36 months, and the gene expression profiles were constructed by utilizing the bovine genome array. Significant analysis of microarrays was used to identify the differentially expressed genes. Gene ontology and pathway analysis were performed by a free Web-based Molecular Annotation System 2.0. The results reveal ~11 000 probes representing about 10 000 genes that were detected in both the Qinghai yak and Qinchuan cattle. A total of 1922 genes were shown to be differentially expressed, 633 probes were upregulated and 1259 probes were downregulated in the muscle tissue of Qinghai yak that were mainly involved in ubiquitin-mediated proteolysis, muscle growth regulation, glucose metabolism, immune response and so on. Quantitative real-time PCR (qRT-PCR) was performed to validate some differentially expressed genes identified by microarray. Further analysis implied that animals living at a high altitude may supply energy by more active protein catabolism and glycolysis compared with those living in the plain areas. Our results establish the groundwork for further studies on yaks' meat quality and will be beneficial in improving the yaks' breeding by molecular biotechnology.

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.

Calibration and analysis of genome-based models for microbial ecology.

PubMed

Louca, Stilianos; Doebeli, Michael

2015-10-16

Microbial ecosystem modeling is complicated by the large number of unknown parameters and the lack of appropriate calibration tools. Here we present a novel computational framework for modeling microbial ecosystems, which combines genome-based model construction with statistical analysis and calibration to experimental data. Using this framework, we examined the dynamics of a community of Escherichia coli strains that emerged in laboratory evolution experiments, during which an ancestral strain diversified into two coexisting ecotypes. We constructed a microbial community model comprising the ancestral and the evolved strains, which we calibrated using separate monoculture experiments. Simulations reproduced the successional dynamics in the evolution experiments, and pathway activation patterns observed in microarray transcript profiles. Our approach yielded detailed insights into the metabolic processes that drove bacterial diversification, involving acetate cross-feeding and competition for organic carbon and oxygen. Our framework provides a missing link towards a data-driven mechanistic microbial ecology.

Ecology and genomics of Bacillus subtilis.

PubMed

Earl, Ashlee M; Losick, Richard; Kolter, Roberto

2008-06-01

Bacillus subtilis is a remarkably diverse bacterial species that is capable of growth within many environments. Recent microarray-based comparative genomic analyses have revealed that members of this species also exhibit considerable genomic diversity. The identification of strain-specific genes might explain how B. subtilis has become so broadly adapted. The goal of identifying ecologically adaptive genes could soon be realized with the imminent release of several new B. subtilis genome sequences. As we embark upon this exciting new era of B. subtilis comparative genomics we review what is currently known about the ecology and evolution of this species.

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.

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

PubMed

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

2005-10-01

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

NCBI GEO: archive for high-throughput functional genomic data.

PubMed

Barrett, Tanya; Troup, Dennis B; Wilhite, Stephen E; Ledoux, Pierre; Rudnev, Dmitry; Evangelista, Carlos; Kim, Irene F; Soboleva, Alexandra; Tomashevsky, Maxim; Marshall, Kimberly A; Phillippy, Katherine H; Sherman, Patti M; Muertter, Rolf N; Edgar, Ron

2009-01-01

The Gene Expression Omnibus (GEO) at the National Center for Biotechnology Information (NCBI) is the largest public repository for high-throughput gene expression data. Additionally, GEO hosts other categories of high-throughput functional genomic data, including those that examine genome copy number variations, chromatin structure, methylation status and transcription factor binding. These data are generated by the research community using high-throughput technologies like microarrays and, more recently, next-generation sequencing. The database has a flexible infrastructure that can capture fully annotated raw and processed data, enabling compliance with major community-derived scientific reporting standards such as 'Minimum Information About a Microarray Experiment' (MIAME). In addition to serving as a centralized data storage hub, GEO offers many tools and features that allow users to effectively explore, analyze and download expression data from both gene-centric and experiment-centric perspectives. This article summarizes the GEO repository structure, content and operating procedures, as well as recently introduced data mining features. GEO is freely accessible at http://www.ncbi.nlm.nih.gov/geo/.

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

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.

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.