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Current Opinion in Virology Jun 2013Technological advances in genome-wide transcript analysis, referred to as the transcriptome, using microarrays and deep RNA sequencing methodologies are rapidly... (Review)
Review
Technological advances in genome-wide transcript analysis, referred to as the transcriptome, using microarrays and deep RNA sequencing methodologies are rapidly extending our understanding of the genetic content of the gammaherpesviruses (γHVs). These vast transcript analyses continue to uncover the complexity of coding transcripts due to alternative splicing, translation initiation and termination, as well as regulatory RNAs of the γHVs. A full assessment of the transcriptome requires that our analysis be extended to the virion and exosomes of infected cells since viral and host mRNAs, miRNAs, and other noncoding RNAs seem purposefully incorporated to exert function upon delivery to naïve cells. Understanding the regulation, biogenesis and function of the recently discovered transcripts will extend beyond pathogenesis and oncogenic events to offer key insights for basic RNA processes of the cell.
Topics: Gammaherpesvirinae; Gene Expression Profiling; Humans; Microarray Analysis; Sequence Analysis, RNA; Transcription, Genetic
PubMed: 23684513
DOI: 10.1016/j.coviro.2013.04.006 -
NeuroRx : the Journal of the American... Jul 2006Neurological disease (ND) is one of the greatest challenges facing our population, from medical, financial, and social perspectives. The application of new research... (Review)
Review
Neurological disease (ND) is one of the greatest challenges facing our population, from medical, financial, and social perspectives. The application of new research approaches to understand the underlying pathogenesis of ND is critical. In this article, we review the use of microarray analysis in Parkinson's disease (PD). Microarrays have tremendous power, simultaneously querying the expression of tens of thousands of genes from a given biological sample. Coupled with impressive advances in statistical tools for analyzing large, complex data sets, well-designed microarray experiments are poised to make a big impact in the field of ND. Parkinson's disease is a devastating neurodegenerative disease well suited to a systems-based microarray analysis. Genetic and environmental rodent models of PD emulate many of the cardinal features of human PD, providing the unique opportunity to compare gene expression profiles from different etiologies of the same disease. The elucidation of important gene expression patterns during disease will make possible identification of genetic susceptibility markers, biomarkers of disease progression, and new therapeutic targets.
Topics: Animals; Disease Models, Animal; Gene Expression; Humans; Microarray Analysis; Parkinson Disease
PubMed: 16815215
DOI: 10.1016/j.nurx.2006.05.008 -
BMC Genomics Oct 2011The growth of high-throughput technologies such as microarrays and next generation sequencing has been accompanied by active research in data analysis methodology,...
BACKGROUND
The growth of high-throughput technologies such as microarrays and next generation sequencing has been accompanied by active research in data analysis methodology, producing new analysis methods at a rapid pace. While most of the newly developed methods are freely available, their use requires substantial computational skills. In order to enable non-programming biologists to benefit from the method development in a timely manner, we have created the Chipster software.
RESULTS
Chipster (http://chipster.csc.fi/) brings a powerful collection of data analysis methods within the reach of bioscientists via its intuitive graphical user interface. Users can analyze and integrate different data types such as gene expression, miRNA and aCGH. The analysis functionality is complemented with rich interactive visualizations, allowing users to select datapoints and create new gene lists based on these selections. Importantly, users can save the performed analysis steps as reusable, automatic workflows, which can also be shared with other users. Being a versatile and easily extendable platform, Chipster can be used for microarray, proteomics and sequencing data. In this article we describe its comprehensive collection of analysis and visualization tools for microarray data using three case studies.
CONCLUSIONS
Chipster is a user-friendly analysis software for high-throughput data. Its intuitive graphical user interface enables biologists to access a powerful collection of data analysis and integration tools, and to visualize data interactively. Users can collaborate by sharing analysis sessions and workflows. Chipster is open source, and the server installation package is freely available.
Topics: Algorithms; Databases, Genetic; Gene Expression Regulation; MicroRNAs; Microarray Analysis; Software; User-Computer Interface
PubMed: 21999641
DOI: 10.1186/1471-2164-12-507 -
Poultry Science Sep 2013Salmonellosis in the United States is one of the most costly foodborne diseases. Given that Salmonella can originate from a wide variety of environments, reduction of... (Review)
Review
Salmonellosis in the United States is one of the most costly foodborne diseases. Given that Salmonella can originate from a wide variety of environments, reduction of this organism at all stages of poultry production is critical. Salmonella species can encounter various environmental stress conditions that can dramatically influence their survival and virulence. Previous knowledge of Salmonella species genomic regulation of metabolism and physiology in relation to poultry is based on limited information of a few well-characterized genes. Consequently, although there is some information about environmental signals that control Salmonella growth and pathogenesis, much still remains unknown. Advancements in DNA sequencing technologies revolutionized the way bacteria were studied and molecular tools such as microarrays have subsequently been used for comprehensive transcriptomic analysis of Salmonella. With microarray analysis, the expression levels of each single gene in the Salmonella genome can be directly assessed and previously unknown genetic systems that are required for Salmonella growth and survival in the poultry production cycle can be elucidated. This represents an opportunity for development of novel approaches for limiting Salmonella establishment in all phases of poultry production. In this review, recent advances in transcriptome-microarray technologies that are facilitating a better understanding of Salmonella biology in poultry production and processing are discussed.
Topics: Animal Husbandry; Animals; Gene Expression Profiling; Genome, Bacterial; Meat; Microarray Analysis; Poultry; Poultry Diseases; Salmonella; Salmonella Infections, Animal
PubMed: 23960105
DOI: 10.3382/ps.2012-02740 -
Research in Microbiology 2016Fungi cover a range of important ecological functions associated with nutrient and carbon cycling in leaf litter and soil. As a result, research on existing... (Review)
Review
Fungi cover a range of important ecological functions associated with nutrient and carbon cycling in leaf litter and soil. As a result, research on existing relationships between fungal functional diversity, decomposition rates and competition is of key interest. Indeed, availability of nutrients in soil is largely the consequence of organic matter degradation dynamics. The Biolog Phenotype MicroArrays™ (PM) system allows for the testing of fungi against many different carbon sources at any one time. The use and potential of the PM system as a tool for studying niche overlap and catabolic versatility of saprotrophic fungi is discussed here, and examples of its application are provided.
Topics: Fungi; Metabolic Networks and Pathways; Microarray Analysis; Phenotype
PubMed: 27283363
DOI: 10.1016/j.resmic.2016.05.008 -
BMC Bioinformatics Dec 2022The central role of proteins in diseases has made them increasingly attractive as therapeutic targets and indicators of cellular processes. Protein microarrays are...
BACKGROUND
The central role of proteins in diseases has made them increasingly attractive as therapeutic targets and indicators of cellular processes. Protein microarrays are emerging as an important means of characterising protein activity. Their accurate downstream analysis to produce biologically significant conclusions is largely dependent on proper pre-processing of extracted signal intensities. However, existing computational tools are not specifically tailored to the nature of these data and lack unanimity.
RESULTS
Here, we present the single-channel Protein Microarray Analysis Pipeline, a tailored computational tool for analysis of single-channel protein microarrays enabling biomarker identification, implemented in R, and as an interactive web application. We compared four existing background correction and normalization methods as well as three array filtering techniques, applied to four real datasets with two microarray designs, extracted using two software programs. The normexp, cyclic loess, and array weighting methods were most effective for background correction, normalization, and filtering respectively.
CONCLUSIONS
Thus, here we provided a versatile and effective pre-processing and differential analysis workflow for single-channel protein microarray data in form of an R script and web application ( https://metaomics.uct.ac.za/shinyapps/Pro-MAP/ .) for those not well versed in the R programming language.
Topics: Oligonucleotide Array Sequence Analysis; Protein Array Analysis; Software; Programming Languages; Workflow; Gene Expression Profiling
PubMed: 36494629
DOI: 10.1186/s12859-022-05095-x -
PloS One Jan 2011Recently emerged deep sequencing technologies offer new high-throughput methods to quantify gene expression, epigenetic modifications and DNA-protein binding. From a...
Recently emerged deep sequencing technologies offer new high-throughput methods to quantify gene expression, epigenetic modifications and DNA-protein binding. From a computational point of view, the data is very different from that produced by the already established microarray technology, providing a new perspective on the samples under study and complementing microarray gene expression data. Software offering the integrated analysis of data from different technologies is of growing importance as new data emerge in systems biology studies. Mayday is an extensible platform for visual data exploration and interactive analysis and provides many methods for dissecting complex transcriptome datasets. We present Mayday SeaSight, an extension that allows to integrate data from different platforms such as deep sequencing and microarrays. It offers methods for computing expression values from mapped reads and raw microarray data, background correction and normalization and linking microarray probes to genomic coordinates. It is now possible to use Mayday's wealth of methods to analyze sequencing data and to combine data from different technologies in one analysis.
Topics: Databases, Genetic; Gene Expression Profiling; High-Throughput Nucleotide Sequencing; Humans; Kidney; Liver; Male; Microarray Analysis; Oligonucleotide Array Sequence Analysis; Software
PubMed: 21305015
DOI: 10.1371/journal.pone.0016345 -
Analytical and Bioanalytical Chemistry Jul 2008Microarrays provide a powerful analytical tool for the simultaneous detection of multiple analytes in a single experiment. The specific affinity reaction of nucleic... (Review)
Review
Microarrays provide a powerful analytical tool for the simultaneous detection of multiple analytes in a single experiment. The specific affinity reaction of nucleic acids (hybridization) and antibodies towards antigens is the most common bioanalytical method for generating multiplexed quantitative results. Nucleic acid-based analysis is restricted to the detection of cells and viruses. Antibodies are more universal biomolecular receptors that selectively bind small molecules such as pesticides, small toxins, and pharmaceuticals and to biopolymers (e.g. toxins, allergens) and complex biological structures like bacterial cells and viruses. By producing an appropriate antibody, the corresponding antigenic analyte can be detected on a multiplexed immunoanalytical microarray. Food and water analysis along with clinical diagnostics constitute potential application fields for multiplexed analysis. Diverse fluorescence, chemiluminescence, electrochemical, and label-free microarray readout systems have been developed in the last decade. Some of them are constructed as flow-through microarrays by combination with a fluidic system. Microarrays have the potential to become widely accepted as a system for analytical applications, provided that robust and validated results on fully automated platforms are successfully generated. This review gives an overview of the current research on microarrays with the focus on automated systems and quantitative multiplexed applications.
Topics: Automation; Biosensing Techniques; Diagnostic Techniques and Procedures; Electrochemistry; Environmental Pollutants; Equipment Design; Food Analysis; Luminescence; Microarray Analysis; Reproducibility of Results; Sensitivity and Specificity
PubMed: 18504563
DOI: 10.1007/s00216-008-2039-3 -
BMC Bioinformatics Sep 2012Sporadic Amyotrophic Lateral Sclerosis (sALS) is a devastating, complex disease of unknown etiology. We studied this disease with microarray technology to capture as...
BACKGROUND
Sporadic Amyotrophic Lateral Sclerosis (sALS) is a devastating, complex disease of unknown etiology. We studied this disease with microarray technology to capture as much biological complexity as possible. The Affymetrix-focused BaFL pipeline takes into account problems with probes that arise from physical and biological properties, so we adapted it to handle the long-oligonucleotide probes on our arrays (hence LO-BaFL). The revised method was tested against a validated array experiment and then used in a meta-analysis of peripheral white blood cells from healthy control samples in two experiments. We predicted differentially expressed (DE) genes in our sALS data, combining the results obtained using the TM4 suite of tools with those from the LO-BaFL method. Those predictions were tested using qRT-PCR assays.
RESULTS
LO-BaFL filtering and DE testing accurately predicted previously validated DE genes in a published experiment on coronary artery disease (CAD). Filtering healthy control data from the sALS and CAD studies with LO-BaFL resulted in highly correlated expression levels across many genes. After bioinformatics analysis, twelve genes from the sALS DE gene list were selected for independent testing using qRT-PCR assays. High-quality RNA from six healthy Control and six sALS samples yielded the predicted differential expression for 7 genes: TARDBP, SKIV2L2, C12orf35, DYNLT1, ACTG1, B2M, and ILKAP. Four of the seven have been previously described in sALS studies, while ACTG1, B2M and ILKAP appear in the context of this disease for the first time. Supplementary material can be accessed at: http://webpages.uncc.edu/~cbaciu/LO-BaFL/supplementary_data.html.
CONCLUSION
LO-BaFL predicts DE results that are broadly similar to those of other methods. The small healthy control cohort in the sALS study is a reasonable foundation for predicting DE genes. Modifying the BaFL pipeline allowed us to remove noise and systematic errors, improving the power of this study, which had a small sample size. Each bioinformatics approach revealed DE genes not predicted by the other; subsequent PCR assays confirmed seven of twelve candidates, a relatively high success rate.
Topics: Amyotrophic Lateral Sclerosis; Data Interpretation, Statistical; Gene Expression Profiling; Humans; Leukocytes; Microarray Analysis; Oligonucleotide Array Sequence Analysis; Software
PubMed: 23006766
DOI: 10.1186/1471-2105-13-244 -
PLoS Computational Biology Oct 2009
Review
Topics: Computational Biology; Oligonucleotide Array Sequence Analysis
PubMed: 19876380
DOI: 10.1371/journal.pcbi.1000543