Special Issue "Feature Papers"

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A special issue of Microarrays (ISSN 2076-3905).

Deadline for manuscript submissions: closed (31 December 2012)

Special Issue Editor

Guest Editor
Prof. Dr. Ulrich Certa

Department of Molecular Toxicology, F. Hoffmann-La Roche AG, 4070 Basel, Switzerland
Phone: +41 61 688 53 40
Interests: pharmacogenomics; drug safety; transcriptional responses to drugs; copy-number variation; deep sequencing; genomic analysis of animal models

Special Issue Information

Dear Colleagues,

This is a collection of top quality papers published free of charge in Open Access form by the editorial board members, or those invited by the editorial office and the Editor-in-Chief. The papers should be long research papers (or review papers) with full and detailed summary of the author's own work done so far.

Prof. Dr. Ulrich Certa 
Guest Editor

Keywords

  • multiplex lab-on-a-chip
  • high-throughput screening
  • DNA microarrays, cDNA microarrays, oligonucleotide microarrays and SNP microarrays
  • MMChips, for surveillance of microRNA populations
  • Protein microarrays
  • Tissue microarrays
  • Cellular microarrays or transfection microarrays
  • Chemical compound microarrays
  • Antibody microarrays
  • Carbohydrate arrays (glycoarrays)
  • high throughput sequencing

Published Papers (8 papers)

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Research

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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) [...] Read more.
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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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 4 | 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 [...] Read more.
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 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 [...] Read more.
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 Testing a Microarray to Detect and Monitor Toxic Microalgae in Arcachon Bay in France
Microarrays 2013, 2(1), 1-23; doi:10.3390/microarrays2010001
Received: 27 November 2012 / Revised: 24 January 2013 / Accepted: 26 February 2013 / Published: 5 March 2013
Cited by 7 | PDF Full-text (626 KB) | HTML Full-text | XML Full-text
Abstract
Harmful algal blooms (HABs) occur worldwide, causing health problems and economic damages to fisheries and tourism. Monitoring agencies are therefore essential, yet monitoring is based only on time-consuming light microscopy, a level at which a correct identification can be limited by insufficient [...] Read more.
Harmful algal blooms (HABs) occur worldwide, causing health problems and economic damages to fisheries and tourism. Monitoring agencies are therefore essential, yet monitoring is based only on time-consuming light microscopy, a level at which a correct identification can be limited by insufficient morphological characters. The project MIDTAL (Microarray Detection of Toxic Algae)—an FP7-funded EU project—used rRNA genes (SSU and LSU) as a target on microarrays to identify toxic species. Furthermore, toxins were detected with a newly developed multiplex optical Surface Plasmon Resonance biosensor (Multi SPR) and compared with an enzyme-linked immunosorbent assay (ELISA). In this study, we demonstrate the latest generation of MIDTAL microarrays (version 3) and show the correlation between cell counts, detected toxin and microarray signals from field samples taken in Arcachon Bay in France in 2011. The MIDTAL microarray always detected more potentially toxic species than those detected by microscopic counts. The toxin detection was even more sensitive than both methods. Because of the universal nature of both toxin and species microarrays, they can be used to detect invasive species. Nevertheless, the MIDTAL microarray is not completely universal: first, because not all toxic species are on the chip, and second, because invasive species, such as Ostreopsis, already influence European coasts. Full article
(This article belongs to the Special Issue Feature Papers)
Open AccessArticle Development and Optimization of a Thrombin Sandwich Aptamer Microarray
Microarrays 2012, 1(2), 95-106; doi:10.3390/microarrays1020095
Received: 28 June 2012 / Revised: 26 July 2012 / Accepted: 7 August 2012 / Published: 8 August 2012
Cited by 4 | PDF Full-text (687 KB) | HTML Full-text | XML Full-text
Abstract
A sandwich microarray employing two distinct aptamers for human thrombin has been optimized for the detection of subnanomolar concentrations of the protein. The aptamer microarray demonstrates high specificity for thrombin, proving that a two-site binding assay with the TBA1 aptamer as capture [...] Read more.
A sandwich microarray employing two distinct aptamers for human thrombin has been optimized for the detection of subnanomolar concentrations of the protein. The aptamer microarray demonstrates high specificity for thrombin, proving that a two-site binding assay with the TBA1 aptamer as capture layer and the TBA2 aptamer as detection layer can ensure great specificity at times and conditions compatible with standard routine analysis of biological samples. Aptamer microarray sensitivity was evaluated directly by fluorescent analysis employing Cy5-labeled TBA2 and indirectly by the use of TBA2-biotin followed by detection with fluorescent streptavidin. Sub-nanomolar LODs were reached in all cases and in the presence of serum, demonstrating that the optimized aptamer microarray can identify thrombin by a low-cost, sensitive and specific method. Full article
(This article belongs to the Special Issue Feature Papers)
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Open AccessArticle Quality Visualization of Microarray Datasets Using Circos
Microarrays 2012, 1(2), 84-94; doi:10.3390/microarrays1020084
Received: 25 June 2012 / Revised: 25 July 2012 / Accepted: 3 August 2012 / Published: 7 August 2012
PDF Full-text (889 KB) | HTML Full-text | XML Full-text
Abstract
Quality control and normalization is considered the most important step in the analysis of microarray data. At present there are various methods available for quality assessments of microarray datasets. However there seems to be no standard visualization routine, which also depicts individual [...] Read more.
Quality control and normalization is considered the most important step in the analysis of microarray data. At present there are various methods available for quality assessments of microarray datasets. However there seems to be no standard visualization routine, which also depicts individual microarray quality. Here we present a convenient method for visualizing the results of standard quality control tests using Circos plots. In these plots various quality measurements are drawn in a circular fashion, thus allowing for visualization of the quality and all outliers of each distinct array within a microarray dataset. The proposed method is intended for use with the Affymetrix Human Genome platform (i.e., GPL 96, GPL570 and GPL571). Circos quality measurement plots are a convenient way for the initial quality estimate of Affymetrix datasets that are stored in publicly available databases. Full article
(This article belongs to the Special Issue Feature Papers)

Review

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Open AccessReview Integrated Amplification Microarrays for Infectious Disease Diagnostics
Microarrays 2012, 1(3), 107-124; doi:10.3390/microarrays1030107
Received: 24 September 2012 / Revised: 31 October 2012 / Accepted: 7 November 2012 / Published: 9 November 2012
Cited by 2 | PDF Full-text (458 KB) | HTML Full-text | XML Full-text
Abstract
This overview describes microarray-based tests that combine solution-phase amplification chemistry and microarray hybridization within a single microfluidic chamber. The integrated biochemical approach improves microarray workflow for diagnostic applications by reducing the number of steps and minimizing the potential for sample or amplicon [...] Read more.
This overview describes microarray-based tests that combine solution-phase amplification chemistry and microarray hybridization within a single microfluidic chamber. The integrated biochemical approach improves microarray workflow for diagnostic applications by reducing the number of steps and minimizing the potential for sample or amplicon cross-contamination. Examples described herein illustrate a basic, integrated approach for DNA and RNA genomes, and a simple consumable architecture for incorporating wash steps while retaining an entirely closed system. It is anticipated that integrated microarray biochemistry will provide an opportunity to significantly reduce the complexity and cost of microarray consumables, equipment, and workflow, which in turn will enable a broader spectrum of users to exploit the intrinsic multiplexing power of microarrays for infectious disease diagnostics. Full article
(This article belongs to the Special Issue Feature Papers)
Open AccessReview Data Analysis Strategies for Protein Microarrays
Microarrays 2012, 1(2), 64-83; doi:10.3390/microarrays1020064
Received: 13 June 2012 / Revised: 13 July 2012 / Accepted: 31 July 2012 / Published: 6 August 2012
Cited by 4 | PDF Full-text (618 KB) | HTML Full-text | XML Full-text
Abstract
Microarrays constitute a new platform which allows the discovery and characterization of proteins. According to different features, such as content, surface or detection system, there are many types of protein microarrays which can be applied for the identification of disease biomarkers and [...] Read more.
Microarrays constitute a new platform which allows the discovery and characterization of proteins. According to different features, such as content, surface or detection system, there are many types of protein microarrays which can be applied for the identification of disease biomarkers and the characterization of protein expression patterns. However, the analysis and interpretation of the amount of information generated by microarrays remain a challenge. Further data analysis strategies are essential to obtain representative and reproducible results. Therefore, the experimental design is key, since the number of samples and dyes, among others aspects, would define the appropriate analysis method to be used. In this sense, several algorithms have been proposed so far to overcome analytical difficulties derived from fluorescence overlapping and/or background noise. Each kind of microarray is developed to fulfill a specific purpose. Therefore, the selection of appropriate analytical and data analysis strategies is crucial to achieve successful biological conclusions. In the present review, we focus on current algorithms and main strategies for data interpretation. Full article
(This article belongs to the Special Issue Feature Papers)
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