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Microarrays, Volume 2, Issue 2 (June 2013), Pages 34-169

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Research

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Open AccessArticle Gene Dosage Analysis in a Clinical Environment: Gene-Targeted Microarrays as the Platform-of-Choice
Microarrays 2013, 2(2), 51-62; doi:10.3390/microarrays2020051
Received: 6 February 2013 / Revised: 18 March 2013 / Accepted: 20 March 2013 / Published: 27 March 2013
Cited by 1 | PDF Full-text (324 KB) | HTML Full-text | XML Full-text
Abstract
The role of gene deletion and duplication in the aetiology of disease has become increasingly evident over the last decade. In addition to the classical deletion/duplication disorders diagnosed using molecular techniques, such as Duchenne Muscular Dystrophy and Charcot-Marie-Tooth Neuropathy Type 1A, the significance
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The role of gene deletion and duplication in the aetiology of disease has become increasingly evident over the last decade. In addition to the classical deletion/duplication disorders diagnosed using molecular techniques, such as Duchenne Muscular Dystrophy and Charcot-Marie-Tooth Neuropathy Type 1A, the significance of partial or whole gene deletions in the pathogenesis of a large number single-gene disorders is becoming more apparent. A variety of dosage analysis methods are available to the diagnostic laboratory but the widespread application of many of these techniques is limited by the expense of the kits/reagents and restrictive targeting to a particular gene or portion of a gene. These limitations are particularly important in the context of a small diagnostic laboratory with modest sample throughput. We have developed a gene-targeted, custom-designed comparative genomic hybridisation (CGH) array that allows twelve clinical samples to be interrogated simultaneously for exonic deletions/duplications within any gene (or panel of genes) on the array. We report here on the use of the array in the analysis of a series of clinical samples processed by our laboratory over a twelve-month period. The array has proven itself to be robust, flexible and highly suited to the diagnostic environment. Full article
(This article belongs to the Special Issue Feature Papers)
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Open AccessArticle Phenotypic MicroRNA Microarrays
Microarrays 2013, 2(2), 63-80; doi:10.3390/microarrays2020063
Received: 8 February 2013 / Revised: 20 March 2013 / Accepted: 25 March 2013 / Published: 3 April 2013
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Abstract
Microarray technology has become a very popular approach in cases where multiple experiments need to be conducted repeatedly or done with a variety of samples. In our lab, we are applying our high density spots microarray approach to microscopy visualization of the effects
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Microarray technology has become a very popular approach in cases where multiple experiments need to be conducted repeatedly or done with a variety of samples. In our lab, we are applying our high density spots microarray approach to microscopy visualization of the effects of transiently introduced siRNA or cDNA on cellular morphology or phenotype. In this publication, we are discussing the possibility of using this micro-scale high throughput process to study the role of microRNAs in the biology of selected cellular models. After reverse-transfection of microRNAs and siRNA, the cellular phenotype generated by microRNAs regulated NF-κB expression comparably to the siRNA. The ability to print microRNA molecules for reverse transfection into cells is opening up the wide horizon for the phenotypic high content screening of microRNA libraries using cellular disease models. Full article
(This article belongs to the Special Issue MicroRNA Microarrays)
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Open AccessArticle Expanding the Diversity of Imaging-Based RNAi Screen Applications Using Cell Spot Microarrays
Microarrays 2013, 2(2), 97-114; doi:10.3390/microarrays2020097
Received: 15 February 2013 / Revised: 2 April 2013 / Accepted: 7 April 2013 / Published: 11 April 2013
Cited by 3 | PDF Full-text (924 KB) | HTML Full-text | XML Full-text
Abstract
Over the past decade, great strides have been made in identifying gene aberrations and deregulated pathways that are associated with specific disease states. These association studies guide experimental studies aimed at identifying the aberrant genes and networks that cause the disease states. This
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Over the past decade, great strides have been made in identifying gene aberrations and deregulated pathways that are associated with specific disease states. These association studies guide experimental studies aimed at identifying the aberrant genes and networks that cause the disease states. This requires functional manipulation of these genes and networks in laboratory models of normal and diseased cells. One approach is to assess molecular and biological responses to high-throughput RNA interference (RNAi)-induced gene knockdown. These responses can be revealed by immunofluorescent staining for a molecular or cellular process of interest and quantified using fluorescence image analysis. These applications are typically performed in multiwell format, but are limited by high reagent costs and long plate processing times. These limitations can be mitigated by analyzing cells grown in cell spot microarray (CSMA) format. CSMAs are produced by growing cells on small (~200 mm diameter) spots with each spot carrying an siRNA with transfection reagent. The spacing between spots is only a few hundred micrometers, thus thousands of cell spots can be arranged on a single cell culture surface. These high-density cell cultures can be immunofluorescently stained with minimal reagent consumption and analyzed quickly using automated fluorescence microscopy platforms. This review covers basic aspects of imaging-based CSMA technology, describes a wide range of immunofluorescence assays that have already been implemented successfully for CSMA screening and suggests future directions for advanced RNAi screening experiments. Full article
(This article belongs to the Special Issue MicroRNA Microarrays)
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Open AccessArticle A Flexible Microarray Data Simulation Model
Microarrays 2013, 2(2), 115-130; doi:10.3390/microarrays2020115
Received: 1 March 2013 / Revised: 7 April 2013 / Accepted: 15 April 2013 / Published: 17 April 2013
Cited by 3 | PDF Full-text (6658 KB) | HTML Full-text | XML Full-text
Abstract
Microarray technology allows monitoring of gene expression profiling at the genome level. This is useful in order to search for genes involved in a disease. The performances of the methods used to select interesting genes are most often judged after other analyzes (qPCR
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Microarray technology allows monitoring of gene expression profiling at the genome level. This is useful in order to search for genes involved in a disease. The performances of the methods used to select interesting genes are most often judged after other analyzes (qPCR validation, search in databases...), which are also subject to error. A good evaluation of gene selection methods is possible with data whose characteristics are known, that is to say, synthetic data. We propose a model to simulate microarray data with similar characteristics to the data commonly produced by current platforms. The parameters used in this model are described to allow the user to generate data with varying characteristics. In order to show the flexibility of the proposed model, a commented example is given and illustrated. An R package is available for immediate use. Full article
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Open AccessArticle Evaluation of Different Normalization and Analysis Procedures for Illumina Gene Expression Microarray Data Involving Small Changes
Microarrays 2013, 2(2), 131-152; doi:10.3390/microarrays2020131
Received: 25 March 2013 / Revised: 8 May 2013 / Accepted: 10 May 2013 / Published: 21 May 2013
Cited by 5 | PDF Full-text (789 KB) | HTML Full-text | XML Full-text
Abstract
While Illumina microarrays can be used successfully for detecting small gene expression changes due to their high degree of technical replicability, there is little information on how different normalization and differential expression analysis strategies affect outcomes. To evaluate this, we assessed concordance across
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While Illumina microarrays can be used successfully for detecting small gene expression changes due to their high degree of technical replicability, there is little information on how different normalization and differential expression analysis strategies affect outcomes. To evaluate this, we assessed concordance across gene lists generated by applying different combinations of normalization strategy and analytical approach to two Illumina datasets with modest expression changes. In addition to using traditional statistical approaches, we also tested an approach based on combinatorial optimization. We found that the choice of both normalization strategy and analytical approach considerably affected outcomes, in some cases leading to substantial differences in gene lists and subsequent pathway analysis results. Our findings suggest that important biological phenomena may be overlooked when there is a routine practice of using only one approach to investigate all microarray datasets. Analytical artefacts of this kind are likely to be especially relevant for datasets involving small fold changes, where inherent technical variation—if not adequately minimized by effective normalization—may overshadow true biological variation. This report provides some basic guidelines for optimizing outcomes when working with Illumina datasets involving small expression changes. Full article
(This article belongs to the Special Issue Feature Papers)
Open AccessArticle Microarray for Identification of the Chiropteran Host Species of Rabies Virus in Canada
Microarrays 2013, 2(2), 153-169; doi:10.3390/microarrays2020153
Received: 13 April 2013 / Revised: 17 May 2013 / Accepted: 17 May 2013 / Published: 31 May 2013
Cited by 1 | PDF Full-text (561 KB) | HTML Full-text | XML Full-text
Abstract
Species identification through genetic barcoding can augment traditional taxonomic methods, which rely on morphological features of the specimen. Such approaches are especially valuable when specimens are in poor condition or comprise very limited material, a situation that often applies to chiropteran (bat) specimens
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Species identification through genetic barcoding can augment traditional taxonomic methods, which rely on morphological features of the specimen. Such approaches are especially valuable when specimens are in poor condition or comprise very limited material, a situation that often applies to chiropteran (bat) specimens submitted to the Canadian Food Inspection Agency for rabies diagnosis. Coupled with phenotypic plasticity of many species and inconclusive taxonomic keys, species identification using only morphological traits can be challenging. In this study, a microarray assay with associated PCR of the mitochondrial cytochrome c oxidase subunit I (COI) gene was developed for differentiation of 14 bat species submitted to the Canadian Food Inspection Agency from 1985–2012 for rabies diagnosis. The assay was validated with a reference collection of DNA from 153 field samples, all of which had been barcoded previously. The COI gene from 152 samples which included multiple specimens of each target species were successfully amplified by PCR and accurately identified by the microarray. One sample that was severely decomposed failed to amplify with PCR primers developed in this study, but amplified weakly after switching to alternate primers and was accurately typed by the microarray. Thus, the chiropteran microarray was able to accurately differentiate between the 14 species of Canadian bats targeted. This PCR and microarray assay would allow unequivocal identification to species of most, if not all, bat specimens submitted for rabies diagnosis in Canada. Full article
(This article belongs to the Special Issue Feature Papers)
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Review

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Open AccessReview Challenges for MicroRNA Microarray Data Analysis
Microarrays 2013, 2(2), 34-50; doi:10.3390/microarrays2020034
Received: 20 February 2013 / Revised: 18 March 2013 / Accepted: 21 March 2013 / Published: 25 March 2013
Cited by 3 | PDF Full-text (272 KB) | HTML Full-text | XML Full-text
Abstract
Microarray is a high throughput discovery tool that has been broadly used for genomic research. Probe-target hybridization is the central concept of this technology to determine the relative abundance of nucleic acid sequences through fluorescence-based detection. In microarray experiments, variations of expression measurements
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Microarray is a high throughput discovery tool that has been broadly used for genomic research. Probe-target hybridization is the central concept of this technology to determine the relative abundance of nucleic acid sequences through fluorescence-based detection. In microarray experiments, variations of expression measurements can be attributed to many different sources that influence the stability and reproducibility of microarray platforms. Normalization is an essential step to reduce non-biological errors and to convert raw image data from multiple arrays (channels) to quality data for further analysis. In general, for the traditional microarray analysis, most established normalization methods are based on two assumptions: (1) the total number of target genes is large enough (>10,000); and (2) the expression level of the majority of genes is kept constant. However, microRNA (miRNA) arrays are usually spotted in low density, due to the fact that the total number of miRNAs is less than 2,000 and the majority of miRNAs are weakly or not expressed. As a result, normalization methods based on the above two assumptions are not applicable to miRNA profiling studies. In this review, we discuss a few representative microarray platforms on the market for miRNA profiling and compare the traditional methods with a few novel strategies specific for miRNA microarrays. Full article
(This article belongs to the Special Issue MicroRNA Microarrays)
Open AccessReview Comparative Analyses of MicroRNA Microarrays during Cardiogenesis: Functional Perspectives
Microarrays 2013, 2(2), 81-96; doi:10.3390/microarrays2020081
Received: 16 February 2013 / Revised: 14 March 2013 / Accepted: 21 March 2013 / Published: 3 April 2013
Cited by 2 | PDF Full-text (462 KB) | HTML Full-text | XML Full-text
Abstract
Cardiovascular development is a complex process in which several transcriptional pathways are operative, providing instructions to the developing cardiomyocytes, while coping with contraction and morphogenetic movements to shape the mature heart. The discovery of microRNAs has added a new layer of complexity to
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Cardiovascular development is a complex process in which several transcriptional pathways are operative, providing instructions to the developing cardiomyocytes, while coping with contraction and morphogenetic movements to shape the mature heart. The discovery of microRNAs has added a new layer of complexity to the molecular mechanisms governing the formation of the heart. Discrete genetic ablation of the microRNAs processing enzymes, such as Dicer and Drosha, has highlighted the functional roles of microRNAs during heart development. Importantly, selective deletion of a single microRNA, miR-1-2, results in an embryonic lethal phenotype in which both morphogenetic, as well as impaired conduction, phenotypes can be observed. In an effort to grasp the variability of microRNA expression during cardiac morphogenesis, we recently reported the dynamic expression profile during ventricular development, highlighting the importance of miR-27 on the regulation of a key cardiac transcription factor, Mef2c. In this review, we compare the microRNA expression profile in distinct models of cardiogenesis, such as ventricular chamber development, induced pluripotent stem cell (iPS)-derived cardiomyocytes and the aging heart. Importantly, out of 486 microRNAs assessed in the developing heart, 11% (55) displayed increased expression, many of which are also differentially expressed in distinct cardiogenetic experimental models, including iPS-derived cardiomyocytes. A review on the functional analyses of these differentially expressed microRNAs will be provided in the context of cardiac development, highlighting the resolution and power of microarrays analyses on the quest to decipher the most relevant microRNAs in the developing, aging and diseased heart. Full article
(This article belongs to the Special Issue MicroRNA Microarrays)

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