SimArray: a user-friendly and user-configurable microarray design tool.

BACKGROUND: Microarrays were first developed to assess gene expression but are now also used to map protein-binding sites and to assess allelic variation between individuals. Regardless of the intended application, efficient production and appropriate array design are key determinants of experimental success. Inefficient production can make larger-scale studies prohibitively expensive, whereas poor array design makes normalisation and data analysis problematic. RESULTS: We have developed a user-friendly tool, SimArray, which generates a randomised spot layout, computes a maximum meta-grid area, and estimates the print time, in response to user-specified design decisions. Selected parameters include: the number of probes to be printed; the microtitre plate format; the printing pin configuration, and the achievable spot density. SimArray is compatible with all current robotic spotters that employ 96-, 384- or 1536-well microtitre plates, and can be configured to reflect most production environments. Print time and maximum meta-grid area estimates facilitate evaluation of each array design for its suitability. Randomisation of the spot layout facilitates correction of systematic biases by normalisation. CONCLUSION: SimArray is intended to help both established researchers and those new to the microarray field to develop microarray designs with randomised spot layouts that are compatible with their specific production environment. SimArray is an open-source program and is available from http://www.flychip.org.uk/SimArray/.RIGHTS : This article is licensed under the BioMed Central licence at http://www.biomedcentral.com/about/license which is similar to the 'Creative Commons Attribution Licence'. In brief you may : copy, distribute, and display the work; make derivative works; or make commercial use of the work - under the following conditions: the original author must be given credit; for any reuse or distribution, it must be made clear to others what the license terms of this work are

Goulphar: rapid access and expertise for standard two-color microarray normalization methods

BACKGROUND: Raw data normalization is a critical step in microarray data analysis because it directly affects data interpretation. Most of the normalization methods currently used are included in the R/BioConductor packages but it is often difficult to identify the most appropriate method. Furthermore, the use of R commands for functions and graphics can introduce mistakes that are difficult to trace. We present here a script written in R that provides a flexible means of access to and monitoring of data normalization for two-color microarrays. This script combines the power of BioConductor and R analysis functions and reduces the amount of R programming required. RESULTS: Goulphar was developed in and runs using the R language and environment. It combines and extends functions found in BioConductor packages (limma and marray) to correct for dye biases and spatial artifacts. Goulphar provides a wide range of optional and customizable filters for excluding incorrect signals during the pre-processing step. It displays informative output plots, enabling the user to monitor the normalization process, and helps adapt the normalization method appropriately to the data. All these analyses and graphical outputs are presented in a single PDF report. CONCLUSION: Goulphar provides simple, rapid access to the power of the R/BioConductor statistical analysis packages, with precise control and visualization of the results obtained. Complete documentation, examples and online forms for setting script parameters are available from

Technical Variables in High-Throughput miRNA Expression Profiling: Much Work Remains to Be Done

MicroRNA (miRNA) gene expression profiling has provided important insights into plant and animal biology. However, there has not been ample published work about pitfalls associated with technical parameters in miRNA gene expression profiling. One source of pertinent information about technical variables in gene expression profiling is the separate and more well-established literature regarding mRNA expression profiling. However, many aspects of miRNA biochemistry are unique. For example, the cellular processing and compartmentation of miRNAs, the differential stability of specific miRNAs, and aspects of global miRNA expression regulation require specific consideration. Additional possible sources of systematic bias in miRNA expression studies include the differential impact of pre-analytical variables, substrate specificity of nucleic acid processing enzymes used in labeling and amplification, and issues regarding new miRNA discovery and annotation. We conclude that greater focus on technical parameters is required to bolster the validity, reliability, and cultural credibility of miRNA gene expression profiling studies

Estimation and correction of non-specific binding in a large-scale spike-in experiment

A combined statistical analysis using the MAS5 PM-MM, GC-NSB and PDNN methods to generate probeset values from microarray data results in an improved ability to detect differential expression and estimates of false discovery rates compared with the individual methods

nformation Theoretical Prediction of Alternative Splicing with Application to Type-2 Diabetes Mellitus.

Für die biomedizinische Grundlagenforschung ist es von besonderem Interesse, die Aktivität von Genen in verschiedenen Geweben eines Organismus zu bestimmen. Die Genaktivität wird hier bestimmt durch die Menge der direkten Produkte eines Gens, die Transkripte. Die Häufigkeit der Transkripte wird durch experimentelle Technologien quantifiziert und als Genexpression bezeichnet. Aber ein Gen produziert nicht immer nur ein Transkript, sondern kann mehrere Transkripte herstellen mittels der parallelen Kodierung, dem sogenannten alternativen Spleissen. Solch ein Mechanismus ist notwendig um die grosse Zahl an Proteinen und die verhältnismässig kleine Anzahl an Genen zu erklären: 25 000 Gene im Menschen gegenüber 20 000 im Fadenwurm caenorhabditis elegans. Alternatives Spleissen kontrolliert die Expression von verschiedenen Transkriptvarianten unter verschiedenen Bedingungen. Es ist nicht überraschend, dass auch kleine Fehler beim Spleissen pathologische Wirkung entfalten, d.h. Krankheiten auslösen können. Da Organismen wie der des Menschen etwa 25 000 verschiedene Gene besitzen, war es notwendig, für die Analyse der globalen Genexpression Hochdurchsatzmethoden zur Datengenerierung zu entwickeln. Mit dem alternativen Spleissen stehen all diesen Genen mehrere Transkripte gegenüber. Erst seit kurzem kann die notwendige Menge an Daten generiert werden durch Technologien wie z.Bsp. Microarrays oder Sequenzierungstechnologie der neuesten Generation. Gleichzeitig mit dem technischen Fortschritt müssen die Datenanalyseverfahren mithalten, um neuen Forschungsfragen zu entsprechen. Im Laufe dieser Arbeit wird eine Softwarepipeline vorgestellt für die Analyse von alternativem Spleissen sowie differentieller Genexpression. Sie wurde entwickelt und implementiert in der Programmiersprache und Statistik-Software R und BioConductor und umfasst die Schritte Qualitätskontrolle, Vorverarbeitung, statistische Auswertung der Expressionsveränderungen und Genmengenauswertung. Für die Erkennung von alternativem Spleissen wird die Informationstheorie in das Gebiet der Genexpression eingeführt. Die vorgestellte Lösung besteht aus einer Erweiterung der Shannon-Entropie auf die Erkennung veränderter Transkripthäufigkeiten und heisst ARH – Alternatives Spleissen Robuste Vorhersage mittels Entropie. Der Nutzen der entwickelten Methoden und Implementierungen wird aufgezeigt am Beispiel von Daten zum Typ-2 Diabetes Mellitus. Mittels Datenintegration und Metaanalyse von unterschiedlichen Datenquellen werden Markergene bestimmt mit Fokus auf differentielle Expression. Danach wird alternatives Spleissen untersucht mit speziellem Fokus auf die Markergene und funktionelle Genmengen, d.h. Stoffwechselwegen

Genetic regulatory networks in avian B cells

Biology is turning into an information science. The science of systems biology seeks to understand the genetic networks that govern organism development and functions. In this study the chicken was used as a model organism in the study of B cell regulatory factors. These studies open new avenues for plasma cell research by connecting the down regulation of the B cell gene expression program directly to the initiation of plasma cell differentiation. The unique advantages of the DT40 avian B cell model system, specifically its high homologous recombination rate, were utilized to study gene regulation in Pax5 knock out cell lines and to gain new insights into the B cell to plasma cell transitions that underlie the secretion of antibodies as part of the adaptive immune response. The Pax5 transcription factor is central to the commitment, development and maintenance of the B cell phenotype. Mice lacking the Pax5 gene have an arrest in development at the pro-B lymphocyte stage while DT40 cells have been derived from cells at a more mature stage of development. The DT40 Pax5-/- cells exhibited gene expression similarities with primary chicken plasma cells. The expression of the plasma cell transcription factors Blimp-1 and XBP-1 were significantly upregulated while the expression of the germinal centre factor BCL6 was diminished in Pax5-/- cells, and this alteration was normalized by Pax5 re-introduction. The Pax5-deficient cells further manifested substantially elevated secretion of IgM into the supernatant, another characteristic of plasma cells. These results for the first time indicated that the downregulation of the Pax5 gene in B cells promotes plasma cell differentiation. Cross-species meta-analysis of chicken and mouse Pax5 gene knockout studies uncovers genes and pathways whose regulatory relationship to Pax5 has remained unchanged for over 300 million years. Restriction of the hematopoietic stem cell fate to produce T, B and NK cell lineages is dependent on the Ikaros and its molecular partners, the closely related Helios and Aiolos. Ikaros family members are zinc finger proteins which act as transcriptional repressors while helping to activate lymphoid genes. Helios in mice is expressed from the hematopoietic stem cell level onwards, although later in development its expression seems to predominate in the T cell lineage. This study establishes the emergence and sequence of the chicken Ikaros family members. Helios expression in the bursa of Fabricius, germinal centres and B cell lines suggested a role for Helios in the avian B-cell lineage, too. Phylogenetic studies of the Ikaros family connect the expansion of the Ikaros family, and thus possibly the emergence of the adaptive immune system, with the second round of genome duplications originally proposed by Ohno. Paralogs that have arisen as a result of genome-wide duplications are sometimes termed ohnologs – Ikaros family proteins appear to fit that definition. This study highlighted the opportunities afforded by the genome sequencing efforts and somatic cell reverse genetics approaches using the DT40 cell line. The DT40 cell line and the avian model system promise to remain a fruitful model for mechanistic insight in the post-genomic era as well.Siirretty Doriast