A survey of analysis software for array-comparative genomic hybridisation studies to detect copy number variation

Copy number variants (CNVs) create a major source of variation among individuals and populations. Array-based comparative genomic hybridisation (aCGH) is a powerful method used to detect and compare the copy numbers of DNA sequences at high resolution along the genome. In recent years, several informatics tools for accurate and efficient CNV detection and assessment have been developed. In this paper, most of the well known algorithms, analysis software and the limitations of that software will be briefly reviewed

Spatial and Temporal Analysis of Gene Expression during Growth and Fusion of the Mouse Facial Prominences

Orofacial malformations resulting from genetic and/or environmental causes are frequent human birth defects yet their etiology is often unclear because of insufficient information concerning the molecular, cellular and morphogenetic processes responsible for normal facial development. We have, therefore, derived a comprehensive expression dataset for mouse orofacial development, interrogating three distinct regions – the mandibular, maxillary and frontonasal prominences. To capture the dynamic changes in the transcriptome during face formation, we sampled five time points between E10.5–E12.5, spanning the developmental period from establishment of the prominences to their fusion to form the mature facial platform. Seven independent biological replicates were used for each sample ensuring robustness and quality of the dataset. Here, we provide a general overview of the dataset, characterizing aspects of gene expression changes at both the spatial and temporal level. Considerable coordinate regulation occurs across the three prominences during this period of facial growth and morphogenesis, with a switch from expression of genes involved in cell proliferation to those associated with differentiation. An accompanying shift in the expression of polycomb and trithorax genes presumably maintains appropriate patterns of gene expression in precursor or differentiated cells, respectively. Superimposed on the many coordinated changes are prominence-specific differences in the expression of genes encoding transcription factors, extracellular matrix components, and signaling molecules. Thus, the elaboration of each prominence will be driven by particular combinations of transcription factors coupled with specific cell:cell and cell:matrix interactions. The dataset also reveals several prominence-specific genes not previously associated with orofacial development, a subset of which we externally validate. Several of these latter genes are components of bidirectional transcription units that likely share cis-acting sequences with well-characterized genes. Overall, our studies provide a valuable resource for probing orofacial development and a robust dataset for bioinformatic analysis of spatial and temporal gene expression changes during embryogenesis

Innate Immune Response of Human Alveolar Macrophages during Influenza A Infection

Alveolar macrophages (AM) are one of the key cell types for initiating inflammatory and immune responses to influenza virus in the lung. However, the genome-wide changes in response to influenza infection in AM have not been defined. We performed gene profiling of human AM in response to H1N1 influenza A virus PR/8 using Affymetrix HG-U133 Plus 2.0 chips and verified the changes at both mRNA and protein levels by real-time RT-PCR and ELISA. We confirmed the response with a contemporary H3N2 influenza virus A/New York/238/2005 (NY/238). To understand the local cellular response, we also evaluated the impact of paracrine factors on virus-induced chemokine and cytokine secretion. In addition, we investigated the changes in the expression of macrophage receptors and uptake of pathogens after PR/8 infection. Although macrophages fail to release a large amount of infectious virus, we observed a robust induction of type I and type III interferons and several cytokines and chemokines following influenza infection. CXCL9, 10, and 11 were the most highly induced chemokines by influenza infection. UV-inactivation abolished virus-induced cytokine and chemokine response, with the exception of CXCL10. The contemporary influenza virus NY/238 infection of AM induced a similar response as PR/8. Inhibition of TNF and/or IL-1β activity significantly decreased the secretion of the proinflammatory chemokines CCL5 and CXCL8 by over 50%. PR/8 infection also significantly decreased mRNA levels of macrophage receptors including C-type lectin domain family 7 member A (CLEC7A), macrophage scavenger receptor 1 (MSR1), and CD36, and reduced uptake of zymosan. In conclusion, influenza infection induced an extensive proinflammatory response in human AM. Targeting local components of innate immune response might provide a strategy for controlling influenza A infection-induced proinflammatory response in vivo

R and Bioconductor solutions for alternative splicing detection

<p>Abstract</p> <p>The detection of alternative splicing using microarray technology involves multiple computational steps: normalisation, filtering, detection and visualisation. In this review, these analyses are approached using the R and Bioconductor open-source computation solution. There is some discussion on how to integrate different Bioconductor packages, and some of their major features are demonstrated. In addition, the Xmap Genome Browser is incorporated as an integral part of the analysis and annotation workflow.</p

A survey of analysis software for array-comparative genomic hybridisation studies to detect copy number variation

Abstract Copy number variants (CNVs) create a major source of variation among individuals and populations. Array-based comparative genomic hybridisation (aCGH) is a powerful method used to detect and compare the copy numbers of DNA sequences at high resolution along the genome. In recent years, several informatics tools for accurate and efficient CNV detection and assessment have been developed. In this paper, most of the well known algorithms, analysis software and the limitations of that software will be briefly reviewed.</p