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Carcinogen-induced mouse models of liver cancer are used extensively to study the pathogenesis of the disease and have a critical role in validating candidate therapeutics. These models can recapitulate molecular and histological features of human disease. However, it is not known if the spectra of genomic alterations driving these mouse tumour genomes are comparable to those found in humans. Here, we provide a detailed characterisation of the exome-wide pattern of mutations in tumours from mice exposed to diethylnitrosamine (DEN), a commonly used model of hepatocellular carcinoma (HCC). DEN-initiated tumours had a high, uniform number of somatic single nucleotide variants (SNVs), with very few insertions, deletions or copy number alterations, consistent with the known genotoxic action of DEN. Exposure of hepatocytes to DEN left a reproducible mutational imprint in resulting tumour exomes which we could computationally reconstruct using six known COSMIC mutational signatures. The tumours carried a high diversity of low-incidence, non-synonymous point mutations in many oncogenes and tumour suppressors, reflecting the stochastic introduction of SNVs into the hepatocyte genome by the carcinogen. We identified four recurrently mutated genes that were putative oncogenic drivers of HCC in this model. Every neoplasm carried activating hotspot mutations either in codon 61 of Hras, in codon 584 of Braf or in codon 254 of Egfr. Truncating mutations of Apc occurred in 21% of neoplasms, which were exclusively carcinomas supporting a role for deregulation of Wnt/β-catenin signalling in cancer progression. Conclusion: Our study provides detailed insight into the mutational landscape of tumours arising in a commonly-used carcinogen model of hepatocellular carcinoma, facilitating the future use of this model to understand the human disease.

DNA methylation is an important mechanism by which gene transcription and hence cellular function are regulated. Here, we provide detailed functional genome-wide methylome maps of 5 primary peripheral blood leukocyte subsets including T cells, B cells, monocytes/macrophages, and neutrophils obtained from healthy individuals. A comparison of these methylomes revealed highly specific cell-lineage and cell-subset methylation profiles. DNA hypomethylation is known to be permissive for gene expression and we identified cell-subset-specific hypomethylated regions (HMRs) that strongly correlate with gene transcription levels suggesting these HMRs may regulate corresponding cell functions. Single-nucleotide polymorphisms associated with immune-mediated disease in genome-wide association studies preferentially localized to these cell-specific regulatory HMRs, offering insight into pathogenesis by highlighting cell subsets in which specific epigenetic changes may drive disease. Our data provide a valuable reference tool for researchers aiming to investigate the role of DNA methylation in regulating primary leukocyte function in health and immune-mediated disease.

Noncoding regulatory variants play a central role in the genetics of human diseases and in evolution. Here we measure allele-specific transcription factor binding occupancy of three liver-specific transcription factors between crosses of two inbred mouse strains to elucidate the regulatory mechanisms underlying transcription factor binding variations in mammals. Our results highlight the pre-eminence of cis-acting variants on transcription factor occupancy divergence. Transcription factor binding differences linked to cis-acting variants generally exhibit additive inheritance, while those linked to trans-acting variants are most often dominantly inherited. Cis-acting variants lead to local coordination of transcription factor occupancies that decay with distance; distal coordination is also observed and may be modulated by long-range chromatin contacts. Our results reveal the regulatory mechanisms that interplay to drive transcription factor occupancy, chromatin state, and gene expression in complex mammalian cell states., “Variation in the noncoding regulatory sequences in the genome plays important roles in human disease and evolution. Here, the authors use F1 mouse hybrids to shed light on the regulatory mechanisms mediating transcription factor binding, chromatin state and gene expression in mammalian cells.”

BACKGROUNDAntineutrophil cytoplasmic antibody (ANCA)-associated vasculitis is a severe condition encompassing two major syndromes: granulomatosis with polyangiitis (formerly known as Wegener's granulomatosis) and microscopic polyangiitis. Its cause is unknown, and there is debate about whether it is a single disease entity and what role ANCA plays in its pathogenesis. We investigated its genetic basis.METHODSA genomewide association study was performed in a discovery cohort of 1233 U. K. patients with ANCA-associated vasculitis and 5884 controls and was replicated in 1454 Northern European case patients and 1666 controls. Quality control, population stratification, and statistical analyses were performed according to standard criteria.RESULTSWe found both major-histocompatibility-complex (MHC) and non-MHC associations with ANCA-associated vasculitis and also that granulomatosis with polyangiitis and microscopic polyangiitis were genetically distinct. The strongest genetic associations were with the antigenic specificity of ANCA, not with the clinical syndrome. Anti-proteinase 3 ANCA was associated with HLA-DP and the genes encoding alpha(1)-antitrypsin (SERPINA1) and proteinase 3 (PRTN3) (P = 6.2x10(-89), P = 5.6x10(-12), and P = 2.6x10(-7), respectively). Anti-myeloperoxidase ANCA was associated with HLA-DQ (P = 2.1x10(-8)).CONCLUSIONSThis study confirms that the pathogenesis of ANCA-associated vasculitis has a genetic component, shows genetic distinctions between granulomatosis with polyangiitis and microscopic polyangiitis that are associated with ANCA specificity, and suggests that the response against the autoantigen proteinase 3 is a central pathogenic feature of proteinase 3 ANCA-associated vasculitis. These data provide preliminary support for the concept that proteinase 3 ANCA-associated vasculitis and myeloperoxidase ANCA-associated vasculitis are distinct autoimmune syndromes. (Funded by the British Heart Foundation and others.)

Follicular helper (T(FH)) cells provide crucial signals to germinal center B cells undergoing somatic hypermutation and selection that results in affinity maturation. Tight control of T(FH) numbers maintains self tolerance. We describe a population of Foxp3(+)Blimp-1(+)CD4(+) T cells constituting 10-25% of the CXCR5(high)PD-1(high)CD4(+) T cells found in the germinal center after immunization with protein antigens. These follicular regulatory T (T(FR)) cells share phenotypic characteristics with T(FH) and conventional Foxp3(+) regulatory T (T(reg)) cells yet are distinct from both. Similar to T(FH) cells, T(FR) cell development depends on Bcl-6, SLAM-associated protein (SAP), CD28 and B cells; however, T(FR) cells originate from thymic-derived Foxp3(+) precursors, not naive or T(FH) cells. T(FR) cells are suppressive in vitro and limit T(FH) cell and germinal center B cell numbers in vivo. In the absence of T(FR) cells, an outgrowth of non-antigen-specific B cells in germinal centers leads to fewer antigen-specific cells. Thus, the T(FH) differentiation pathway is co-opted by T(reg) cells to control the germinal center response.

ArrayExpress http://www.ebi.ac.uk/arrayexpress consists of three components: the ArrayExpress Repository--a public archive of functional genomics experiments and supporting data, the ArrayExpress Warehouse--a database of gene expression profiles and other bio-measurements and the ArrayExpress Atlas--a new summary database and meta-analytical tool of ranked gene expression across multiple experiments and different biological conditions. The Repository contains data from over 6000 experiments comprising approximately 200,000 assays, and the database doubles in size every 15 months. The majority of the data are array based, but other data types are included, most recently-ultra high-throughput sequencing transcriptomics and epigenetic data. The Warehouse and Atlas allow users to query for differentially expressed genes by gene names and properties, experimental conditions and sample properties, or a combination of both. In this update, we describe the ArrayExpress developments over the last two years.

UNLABELLED ArrayExpress is a public database for high throughput functional genomics data. ArrayExpress consists of two parts--the ArrayExpress Repository, which is a MIAME supportive public archive of microarray data, and the ArrayExpress Data Warehouse, which is a database of gene expression profiles selected from the repository and consistently re-annotated. Archived experiments can be queried by experiment attributes, such as keywords, species, array platform, authors, journals or accession numbers. Gene expression profiles can be queried by gene names and properties, such as Gene Ontology terms and gene expression profiles can be visualized. ArrayExpress is a rapidly growing database, currently it contains data from >50,000 hybridizations and >1,500,000 individual expression profiles. ArrayExpress supports community standards, including MIAME, MAGE-ML and more recently the proposal for a spreadsheet based data exchange format: MAGE-TAB. AVAILABILITY www.ebi.ac.uk/arrayexpress.

Summary:ArrayExpress is one of the largest public repositories of microarray datasets. R/Bioconductor provides a comprehensive suite of microarray analysis and integrative bioinformatics software. However, easy ways for importing datasets from ArrayExpress into R/Bioconductor have been lacking. Here, we present such a tool that is suitable for both interactive and automated use. Availability: The ArrayExpress package is available from the Bioconductor project at http://www.bioconductor.org. A users guide and examples are provided with the package. Contact: audrey@ebi.ac.uk Supplementary information: Supplementary data are available Bioinformatics online.

The response of a leukocyte to immune complexes (ICs) is modulated by receptors for the Fc region of IgG (FcγRs), and alterations in their affinity or function have been associated with risk of autoimmune diseases, including systemic lupus erythematosus (SLE). The low-affinity FcgR genomic locus is complex, containing regions of copy number variation (CNV) which can alter receptor expression and leukocyte responses to IgG. Combined paralogue ratio tests (PRTs) were used to distinguish three intervals within the FCGR locus which undergo CNV, and to determine FCGR gene copy number (CN). There were significant differences in FCGR3B and FCGR3A CNV profiles between Caucasian, East Asian and Kenyan populations. A previously noted association of low FCGR3B CN with SLE in Caucasians was supported [OR = 1.57 (1.08-2.27), P = 0.018], and replicated in Chinese [OR = 1.65 (1.25-2.18), P = 4 × 10 -4]. There was no association of FCGR3B CNV with vasculitis, nor with malarial or bacterial infection. Linkage disequilibrium (LD) between multi-allelic FCGR3B CNV and SLE-associated SNPs in the FCGR locus was defined for the first time. Despite LD between FCGR3B CNV and a variant in FcγRIIB (I232T) which abolishes inhibitory function, both reduced CN of FCGR3B and homozygosity of the FcγRIIB-232T allele were individually strongly associated with SLE risk. Thus CN of FCGR3B, which controls IC responses and uptake by neutrophils, and variations in FCGR2B, which controls factors such as antibody production and macrophage activation, are important in SLE pathogenesis. Further interpretations of contributions to pathogenesis by FcγRs must be made in the context of LD involving CNV regions. © The Author 2010. Published by Oxford University Press. All rights reserved., published_or_final_version

ObjectiveTo optimise a strategy for identifying gene expression signatures differentiating systemic lupus erythematosus (SLE) and antineutrophil cytoplasmic antibody-associated vasculitis that provide insight into disease pathogenesis and identify biomarkers.Methods44 vasculitis patients, 13 SLE patients and 25 age and sex-matched controls were enrolled. CD4 and CD8 T cells, B cells, monocytes and neutrophils were isolated from each patient and, together with unseparated peripheral blood mononuclear cells (PBMC), were hybridised to spotted oligonucleotide microarrays.ResultsUsing expression data obtained from purified cells a substantial number of differentially expressed genes were identified that were not detectable in the analysis of PBMC. Analysis of purified T cells identified a SLE-associated, CD4 T-cell signature consistent with type 1 interferon signalling driving the generation and survival of tissue homing T cells and thereby contributing to disease pathogenesis. Moreover, hierarchical clustering using expression data from purified monocytes provided significantly improved discrimination between the patient groups than that obtained using PBMC data, presumably because the differentially expressed genes reflect genuine differences in processes underlying disease pathogenesis.ConclusionAnalysis of leucocyte subsets enabled the identification of gene signatures of both pathogenic relevance and with better disease discrimination than those identified in PBMC. This approach thus provides substantial advantages in the search for diagnostic and prognostic biomarkers in autoimmune disease.

Summary: The MAGE-TAB format for microarray data representation and exchange has been proposed by the microarray community to replace the more complex MAGE-ML format. We present a suite of tools to support MAGE-TAB generation and validation, conversion between existing formats for data exchange, visualization of the experiment designs encoded by MAGE-TAB documents and the mining of such documents for semantic content. Availability: Software is available from http://tab2mage.sourceforge.net/ Contact: tfrayner@gmail.com

Background Sharing of microarray data within the research community has been greatly facilitated by the development of the disclosure and communication standards MIAME and MAGE-ML by the MGED Society. However, the complexity of the MAGE-ML format has made its use impractical for laboratories lacking dedicated bioinformatics support. Results We propose a simple tab-delimited, spreadsheet-based format, MAGE-TAB, which will become a part of the MAGE microarray data standard and can be used for annotating and communicating microarray data in a MIAME compliant fashion. Conclusion MAGE-TAB will enable laboratories without bioinformatics experience or support to manage, exchange and submit well-annotated microarray data in a standard format using a spreadsheet. The MAGE-TAB format is self-contained, and does not require an understanding of MAGE-ML or XML.

ArrayExpress is a new public database of microarray gene expression data at the EBI, which is a generic gene expression database designed to hold data from all microarray platforms. ArrayExpress uses the annotation standard Minimum Information About a Microarray Experiment (MIAME) and the associated XML data exchange format Microarray Gene Expression Markup Language (MAGE-ML) and it is designed to store well annotated data in a structured way. The ArrayExpress infrastructure consists of the database itself, data submissions in MAGE-ML format or via an online submission tool MIAMExpress, online database query interface, and the Expression Profiler online analysis tool. ArrayExpress accepts three types of submission, arrays, experiments and protocols, each of these is assigned an accession number. Help on data submission and annotation is provided by the curation team. The database can be queried on parameters such as author, laboratory, organism, experiment or array types. With an increasing number of organisations adopting MAGE-ML standard, the volume of submissions to ArrayExpress is increasing rapidly. The database can be accessed at http://www.ebi.ac.uk/arrayexpress.