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Allogeneic transplantation of islets of Langerhans was facilitated by the cotransplantation of syngeneic myoblasts genetically engineered to express the Fas ligand (FasL). Composite grafting of allogeneic islets with syngeneic myoblasts expressing FasL protected the islet graft from immune rejection and maintained normoglycemia for more than 80 days in mice with streptozotocin-induced diabetes. Graft survival was not prolonged with composite grafts of unmodified myoblasts or Fas-expressing myoblasts. Islet allografts transplanted separately from FasL-expressing myoblasts into the contralateral kidney were rejected, as were similarly transplanted third-party thyroid allografts. Thus, the FasL signal provided site- and immune-specific protection of islet allografts., Immunological rejection of pancreatic islet allografts remains a major obstacle toward the application of such transplants in the treatment of diabetes mellitus. Interactions of Fas with its ligand (FasL) are [...]

To gain a deeper understanding of pancreatic β-cell development, we used iterative weighted gene correlation network analysis to calculate a gene co-expression network (GCN) from 11 temporally and genetically defined murine cell populations. The GCN, which contained 91 distinct modules, was then used to gain three new biological insights. First, we found that the clustered protocadherin genes are differentially expressed during pancreas development. Pcdhγ genes are preferentially expressed in pancreatic endoderm, Pcdhβ genes in nascent islets, and Pcdhα genes in mature β-cells. Second, after extracting sub-networks of transcriptional regulators for each developmental stage, we identified 81 zinc finger protein (ZFP) genes that are preferentially expressed during endocrine specification and β-cell maturation. Third, we used the GCN to select three ZFPs for further analysis by CRISPR mutagenesis of mice. Zfp800 null mice exhibited early postnatal lethality, and at E18.5 their pancreata exhibited a reduced number of pancreatic endocrine cells, alterations in exocrine cell morphology, and marked changes in expression of genes involved in protein translation, hormone secretion and developmental pathways in the pancreas. Together, our results suggest that developmentally oriented GCNs have utility for gaining new insights into gene regulation during organogenesis. [ABSTRACT FROM AUTHOR]

Background: Biobanking necessitates extensive integration of data to allow data analysis and specimen sharing. Ontologies have been demonstrated to be a promising approach in fostering better semantic integration of biobank-related data. Hitherto no ontology provided the coverage needed to capture a broad spectrum of biobank user scenarios. Methods: Based in the principles laid out by the Open Biological and Biomedical Ontologies Foundry two biobanking ontologies have been developed. These two ontologies were merged using a modular approach consistent with the initial development principles. The merging was facilitated by the fact that both ontologies use the same Upper Ontology and re-use classes from a similar set of pre-existing ontologies. Results: Based on the two previous ontologies the Ontology for Biobanking (http://purl.obolibrary.org/obo/obib.owl) was created. Due to the fact that there was no overlap between the two source ontologies the coverage of the resulting ontology is significantly larger than of the two source ontologies. The ontology is successfully used in managing biobank information of the Penn Medicine BioBank. Conclusions: Sharing development principles and Upper Ontologies facilitates subsequent merging of ontologies to achieve a broader coverage. [ABSTRACT FROM AUTHOR]

Background: Atherosclerosis is a heterogeneously distributed disease of arteries in which the endothelium plays an important central role. Spatial transcriptome profiling of endothelium in pre-lesional arteries has demonstrated differential phenotypes primed for athero-susceptibility at hemodynamic sites associated with disturbed blood flow. DNA methylation is a powerful epigenetic regulator of endothelial transcription recently associated with flow characteristics. We investigated differential DNA methylation in flow region-specific aortic endothelial cells in vivo in adult domestic male and female swine. Results: Genome-wide DNA methylation was profiled in endothelial cells (EC) isolated from two robust locations of differing patho-susceptibility: − an athero-susceptible site located at the inner curvature of the aortic arch (AA) and an athero-protected region in the descending thoracic (DT) aorta. Complete methylated DNA immunoprecipitation sequencing (MeDIP-seq) identified over 5500 endothelial differentially methylated regions (DMRs). DMR density was significantly enriched in exons and 5’UTR sequences of annotated genes, 60 of which are linked to cardiovascular disease. The set of DMR-associated genes was enriched in transcriptional regulation, pattern specification HOX loci, oxidative stress and the ER stress adaptive pathway, all categories linked to athero-susceptible endothelium. Examination of the relationship between DMR and mRNA in HOXA genes demonstrated a significant inverse relationship between CpG island promoter methylation and gene expression. Methylation-specific PCR (MSP) confirmed differential CpG methylation of HOXA genes, the ER stress gene ATF4, inflammatory regulator microRNA-10a and ARHGAP25 that encodes a negative regulator of Rho GTPases involved in cytoskeleton remodeling. Gender-specific DMRs associated with ciliogenesis that may be linked to defects in cilia development were also identified in AA DMRs. Conclusions: An endothelial methylome analysis identifies epigenetic DMR characteristics associated with transcriptional regulation in regions of atherosusceptibility in swine aorta in vivo. The data represent the first methylome blueprint for spatio-temporal analyses of lesion susceptibility predisposing to endothelial dysfunction in complex flow environments in vivo. [ABSTRACT FROM AUTHOR]

ONE OF THE UNDERLYING PRINCIPLES OF scientific publication in peer-reviewed journals has been the requirement that the authors make available the data and materials necessary for a reader to reproduce [...]

High throughput sequencing has accelerated the determination of genome sequences for thousands of human infectious disease pathogens and dozens of their vectors. The scale and scope of these data are enabling genotype-phenotype association studies to identify genetic determinants of pathogen virulence and drug/insecticide resistance, and phylogenetic studies to track the origin and spread of disease outbreaks. To maximize the utility of genomic sequences for these purposes, it is essential that metadata about the pathogen/vector isolate characteristics be collected and made available in organized, clear, and consistent formats. Here we report the development of the GSCID/BRC Project and Sample Application Standard, developed by representatives of the Genome Sequencing Centers for Infectious Diseases (GSCIDs), the Bioinformatics Resource Centers (BRCs) for Infectious Diseases, and the U.S. National Institute of Allergy and Infectious Diseases (NIAID), part of the National Institutes of Health (NIH), informed by interactions with numerous collaborating scientists. It includes mapping to terms from other data standards initiatives, including the Genomic Standards Consortium’s minimal information (MIxS) and NCBI’s BioSample/BioProjects checklists and the Ontology for Biomedical Investigations (OBI). The standard includes data fields about characteristics of the organism or environmental source of the specimen, spatial-temporal information about the specimen isolation event, phenotypic characteristics of the pathogen/vector isolated, and project leadership and support. By modeling metadata fields into an ontology-based semantic framework and reusing existing ontologies and minimum information checklists, the application standard can be extended to support additional project-specific data fields and integrated with other data represented with comparable standards. The use of this metadata standard by all ongoing and future GSCID sequencing projects will provide a consistent representation of these data in the BRC resources and other repositories that leverage these data, allowing investigators to identify relevant genomic sequences and perform comparative genomics analyses that are both statistically meaningful and biologically relevant. [ABSTRACT FROM AUTHOR]

Background: Hematopoietic ontogeny is characterized by overlapping waves of primitive, fetal definitive, and adult definitive erythroid lineages. Our aim is to identify differences in the transcriptional control of these distinct erythroid cell maturation pathways by inferring and analyzing gene-interaction networks from lineage-specific expression datasets. Inferred networks are strongly connected and do not fit a scale-free model, making it difficult to identify essential regulators using the hub-essentiality standard. Results: We employed a semi-supervised machine learning approach to integrate measures of network topology with expression data to score gene essentiality. The algorithm was trained and tested on the adult and fetal definitive erythroid lineages. When applied to the primitive erythroid lineage, 144 high scoring transcription factors were found to be differentially expressed between the primitive and adult definitive erythroid lineages, including all expressed STAT-family members. Differential responses of primitive and definitive erythroblasts to a Stat3 inhibitor and IFNγ in vitro supported the results of the computational analysis. Further investigation of the original expression data revealed a striking signature of Stat1-related genes in the adult definitive erythroid network. Among the potential pathways known to utilize Stat1, interferon (IFN) signaling-related genes were expressed almost exclusively within the adult definitive erythroid network. Conclusions: In vitro results support the computational prediction that differential regulation and downstream effectors of STAT signaling are key factors that distinguish the transcriptional control of primitive and definitive erythroid cell maturation. [ABSTRACT FROM AUTHOR]

Background: Genome sequencing of many eukaryotic pathogens and the volume of data available on public resources have created a clear requirement for a consistent vocabulary to describe the range of developmental forms of parasites. Consistent labeling of experimental data and external data, in databases and the literature, is essential for integration, cross database comparison, and knowledge discovery. The primary objective of this work was to develop a dynamic and controlled vocabulary that can be used for various parasites. The paper describes the Ontology for Parasite Lifecycle (OPL) and discusses its application in parasite research. Results: The OPL is based on the Basic Formal Ontology (BFO) and follows the rules set by the OBO Foundry consortium. The first version of the OPL models complex life cycle stage details of a range of parasites, such as Trypanosoma sp., Leishmaniasp.,Plasmodium sp., and Shicstosoma sp. In addition, the ontology also models necessary contextual details, such as host information, vector information, and anatomical locations. OPL is primarily designed to serve as a reference ontology for parasite life cycle stages that can be used for database annotation purposes and in the lab for data integration or information retrieval as exemplified in the application section below. Conclusion: OPL is freely available at http://purl.obolibrary.org/obo/opl.owl and has been submitted to the BioPortal site of NCBO and to the OBO Foundry. We believe that database and phenotype annotations using OPL will help run fundamental queries on databases to know more about gene functions and to find intervention targets for various parasites. The OPL is under continuous development and new parasites and/or terms are being added. [ABSTRACT FROM AUTHOR]

The ever-increasing scale of biological data sets, particularly those arising in the context of high-throughput technologies, requires the development of rich data exploration tools. In this article, we present AnnotCompute, an information discovery platform for repositories of functional genomics experiments such as ArrayExpress. Our system leverages semantic annotations of functional genomics experiments with controlled vocabulary and ontology terms, such as those from the MGED Ontology, to compute conceptual dissimilarities between pairs of experiments. These dissimilarities are then used to support two types of exploratory analysis-clustering and query-by-example. We show that our proposed dissimilarity measures correspond to a user's intuition about conceptual dissimilarity, and can be used to support effective query-by-example. We also evaluate the quality of clustering based on these measures. While AnnotCompute can support a richer data exploration experience, its effectiveness is limited in some cases, due to the quality of available annotations. Nonetheless, tools such as AnnotCompute may provide an incentive for richer annotations of experiments. Code is available for download at http://www.cbil.upenn.edu/downloads/AnnotCompute. [ABSTRACT FROM AUTHOR]

Background: Experimental descriptions are typically stored as free text without using standardized terminology, creating challenges in comparison, reproduction and analysis. These difficulties impose limitations on data exchange and information retrieval. Results: The Ontology for Biomedical Investigations (OBI), developed as a global, cross-community effort, provides a resource that represents biomedical investigations in an explicit and integrative framework. Here we detail three real-world applications of OBI, provide detailed modeling information and explain how to use OBI. Conclusion: We demonstrate how OBI can be applied to different biomedical investigations to both facilitate interpretation of the experimental process and increase the computational processing and integration within the Semantic Web. The logical definitions of the entities involved allow computers to unambiguously understand and integrate different biological experimental processes and their relevant components. Availability: OBI is available at http://purl.obolibrary.org/obo/obi/2009-11-02/obi.owl [ABSTRACT FROM AUTHOR]

Background: The apicomplexans are a diverse phylum of parasites causing an assortment of diseases including malaria in a wide variety of animals and lymphoproliferation in cattle. Little is known about how these varied parasites regulate their transcriptional regulons. Even less is known about how regulon systems, consisting of transcription factors and target genes together with their associated biological process, evolve in these diverse parasites. Results: In order to obtain insights into the differences in transcriptional regulation between these parasites we compared the orthology profiles of putative malaria transcription factors across species and examined the enrichment patterns of four binding sites across eleven apicomplexans. About three-fifths of the factors are broadly conserved in several phylogenetic orders of sequenced apicomplexans. This observation suggests the existence of regulons whose regulation is conserved across this ancient phylum. Transcription factors not broadly conserved across the phylum are possibly involved in regulon systems that have diverged between species. Examining binding site enrichment patterns in light of transcription factor conservation patterns suggests a second mode via which regulon systems may diverge - rewiring of existing transcription factors and their associated binding sites in specific ways. Integrating binding sites with transcription factor conservation patterns also facilitated prediction of putative regulators for one of the binding sites. Conclusions: Even though transcription factors are underrepresented in apicomplexans, the distribution of these factors and their associated regulons reflect common and family-specific transcriptional regulatory processes. [ABSTRACT FROM AUTHOR]

Atherosclerosis originates as focal arterial lesions having a predictable distribution to regions of bifurcations, branches, and inner curvatures where blood flow characteristics are complex. Distinct endothelial phenotypes correlate with regional hemodynamics. We propose that systemic risk factors modify regional endothelial phenotype to influence focal susceptibility to atherosclerosis. Transcript profiles of freshly isolated endothelial cells from three atherosusceptible and three atheroprotected arterial regions in adult swine were analyzed to determine the initial prelesional effects of hypercholesterolemia on endothelial phenotypes in vivo. Cholesterol efflux transporter ATP-binding cassette transporter Al (ABCA1) was upregulated at all sites in response to short-term high-fat diet. Proinflammatory and antioxidative endothehal gene expression profiles were induced in atherosusceptible and atheroprotected regions, respectively. However, markers for endoplasmic reticulum stress, a signature of susceptible endothehial phenotype, were not further enhanced by brief hypercholesterolemia. Both region-specific and ubiquitous (ABCA1) phenotype changes were identified as early prelesional responses of the endothehium to hypercholesterolemia. [ABSTRACT FROM AUTHOR]

The article presents a research on comparative multi-site genomics relative to the arterial endothelial phenotype in atherosusceptible and atheroprotected regions. It profiles seven discrete arterial regions of isolated endothelial cells in normal swine. It determines the vivo endothelial phenotypes steady state in regions of adapting susceptibilities to atherosclerosis. Furthermore, it notes the number of chronic endothelial endoplasmic reticulum (ER) stress.

Background: Malaria-causing Plasmodium species exhibit marked differences including host choice and preference for invading particular cell types. The genetic bases of phenotypic differences between parasites can be understood, in part, by investigating constraints on gene expression and genic sequences, both coding and regulatory. Methodology/Principal Findings: We investigated the evolutionary constraints on sequence and expression of parasitic genes by applying comparative genomics approaches to 6 Plasmodium genomes and 2 genome-wide expression studies. We found that the coding regions of Plasmodium transcription factor and sexual development genes are relatively less constrained, as are those of genes encoding CCCH zinc fingers and invasion proteins, which all play important roles in these parasites. Transcription factors and genes with stage-restricted expression have conserved upstream regions and so do several gene classes critical to the parasite's lifestyle, namely, ion transport, invasion, chromatin assembly and CCCH zinc fingers. Additionally, a cross-species comparison of expression patterns revealed that Plasmodium-specific genes exhibit significant expression divergence. Conclusions/Significance: Overall, constraints on Plasmodium's protein coding regions confirm observations from other eukaryotes in that transcription factors are under relatively lower constraint. Proteins relevant to the parasite's unique lifestyle also have lower constraint on their coding regions. Greater conservation between Plasmodium species in terms of promoter motifs suggests tight regulatory control of lifestyle genes. However, an interspecies divergence in expression patterns of these genes suggests that either expression is controlled via genomic or epigenomic features not encoded in the proximal promoter sequence, or alternatively, the combinatorial interactions between motifs confer species-specific expression patterns. [ABSTRACT FROM AUTHOR]

The Functional Genomics Experiment data model (FuGE) has been developed to facilitate convergence of data standards for high-throughput, comprehensive analyses in biology. FuGE models the components of an experimental activity that are common across different technologies, including protocols, samples and data. FuGE provides a foundation for describing entire laboratory workflows and for the development of new data formats. The Microarray Gene Expression Data society and the Proteomics Standards Initiative have committed to using FuGE as the basis for defining their respective standards, and other standards groups, including the Metabolomics Standards Initiative, are evaluating FuGE in their development efforts. Adoption of FuGE by multiple standards bodies will enable uniform reporting of common parts of functional genomics workflows, simplify data-integration efforts and ease the burden on researchers seeking to fulfill multiple minimum reporting requirements. Such advances are important for transparent data management and mining in functional genomics and systems biology. [ABSTRACT FROM AUTHOR]

Genomic aberrations recurrent in a particular cancer type can be important prognostic markers for tumor progression. Typically in early tumorigenesis, cells incur a breakdown of the DNA replication machinery that results in an accumulation of genomic aberrations in the form of duplications, deletions, translocations, and other genomic alterations. Microarray methods allow for finer mapping of these aberrations than has previously been possible; however, data processing and analysis methods have not taken full advantage of this higher resolution. Attention has primarily been given to analysis on the single sample level, where multiple adjacent probes are necessarily used as replicates for the local region containing their target sequences. However, regions of concordant aberration can be short enough to be detected by only one, or very few, array elements. We describe a method called Multiple Sample Analysis for assessing the significance of concordant genomic aberrations across multiple experiments that does not require a-priori definition of aberration calls for each sample. If there are multiple samples, representing a class, then by exploiting the replication across samples our method can detect concordant aberrations at much higher resolution than can be derived from current single sample approaches. Additionally, this method provides a meaningful approach to addressing population-based questions such as determining important regions for a cancer subtype of interest or determining regions of copy number variation in a population. Multiple Sample Analysis also provides single sample aberration calls in the locations of significant concordance, producing high resolution calls per sample, in concordant regions. The approach is demonstrated on a dataset representing a challenging but important resource: breast tumors that have been formalin-fixed, paraffin-embedded, archived, and subsequently UV-laser capture microdissected and hybridized to two-channel BAC arrays using an amplification protocol. We demonstrate the accurate detection on simulated data, and on real datasets involving known regions of aberration within subtypes of breast cancer at a resolution consistent with that of the array. Similarly, we apply our method to previously published datasets, including a 250K SNP array, and verify known results as well as detect novel regions of concordant aberration. The algorithm has been fully implemented and tested and is freely available as a Java application at http://www.cbil.upenn.edu/MSA. [ABSTRACT FROM AUTHOR]

Background: Sharing of microarray data within the research community has been greatly facilitated by the development of the disclosure and communication standards MIAME and MAGEML 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. [ABSTRACT FROM AUTHOR]

Experiments involving high-throughput methods for measuring transcripts, proteins and metabolites constitute the area of functional genomics. These experiments are highly context dependent and require much more detail about the experimental design, sample and protocols used than in genomics. Functional genomics databases are needed that follow established and emerging standards. Functional genomic databases are not yet very common; however, there are a few focused on microbial genomes and a couple integrative systems are available for setting up functional genomics databases. [ABSTRACT FROM AUTHOR]

In an effort to understand the complexity of genomic responses within selectively vulnerable regions after experimental brain injury, we examined whether single apoptotic neurons from both the CA3 and dentate differed from those in an uninjured brain. The mRNA from individual active caspase 3(+)/terminal deoxynucleotidyl transferase-mediated biotinylated UTP nick end labeling [TUNEL(-)] and active caspase 3(+)/TUNEL(+) pyramidal and granule neurons in brain-injured mice were amplified and compared with those from nonlabeled neurons in uninjured brains. Gene analysis revealed that overall expression of mRNAs increased with activation of caspase 3 and decreased to below uninjured levels with TUNEL reactivity. Cell type specificity of the apoptotic response was observed with both regionally distinct expression of mRNAs and differences in those mRNAs that were maximally regulated. Immunohistochemical analysis for two of the most highly differentially expressed genes (prion and Sos2) demonstrated a correlation between the observed differential gene expression after traumatic brain injury and corresponding protein translation. [ABSTRACT FROM AUTHOR]

Focuses on the use of OrthoMCL method for identification of orthologous groups for eukaryotic genomes. Non-application of prokaryotic genome analysis method to eukaryotes; Features of OrthoMCL.

The Endocrine Pancreas Consortium was formed in late 1999 to derive and sequence cDNA libraries enriched for rare transcripts expressed in the mammalian endocrine pancreas. Over the past 3 years, the Consortium has generated 20 cDNA libraries from mouse and human pancreatic tissues and deposited >150,000 sequences into the public expressed sequence tag databases. A special effort was made to enrich for cDNAs from the endocrine pancreas by constructing libraries from isolated islets. In addition, we constructed a library in which fetal pancreas from Neurogenin 3 null mice, which consists of only exocrine and duct cells, was subtracted from fetal wild-type pancreas to enrich for the transcripts from the endocrine compartment. Sequence analysis showed that these clones cluster into 9,464 assembly groups (approximating unique transcripts) for the mouse and 13,910 for the human sequences. Of these, >4,300 were unique to Consortium libraries. We have assembled a core clone set containing one cDNA for each assembly group for the mouse and have constructed the corresponding microarray, termed "PancChip 4.0," which contains >9,000 nonredundant elements. We show that this PancChip is highly enriched for genes expressed in the endocrine pancreas. The mouse and human clone sets and corresponding arrays will be important resources for diabetes research. [ABSTRACT FROM AUTHOR]

Summary: Computational methods in molecular biology will increasingly depend on standards-based annotations that describe biological experiments in an unambiguous manner. Annotare is a software tool that enables biologists to easily annotate their high-throughput experiments, biomaterials and data in a standards-compliant way that facilitates meaningful search and analysis.Availability and Implementation: Annotare is available from http://code.google.com/p/annotare/ under the terms of the open-source MIT License (http://www.opensource.org/licenses/mit-license.php). It has been tested on both Mac and Windows.Contact: rshankar@stanford.edu [ABSTRACT FROM PUBLISHER]

Many thousands of proteins encoded by the genome of Plasmodium falciparum, the causal organism of the deadliest form of human malaria, are of unknown function. It is of utmost importance that these proteins be characterized if we are to develop combative strategies against malaria based on the biology of the parasite. In an attempt to infer protein function on a genome-wide scale, we computationally modeled the P. falciparum interactome, elucidating local and global functional relationships between gene products. The resulting interaction network, reconstructed by integrating in silico and experimental functional genomics data within a Bayesian framework, covers ∼68% of the parasite genome and provides functional inferences for more than 2000 uncharacterized proteins, based on their associations. Network reconstruction involved the use of a novel strategy, where we incorporated continuously updated, uniform reference priors in our Bayesian model. This method for generating interaction maps is thus also well suited for application to other genomes, where pre-existing interactome knowledge is sparse. Additionally, we superimposed this map on genomes of three apicomplexan pathogens--Plasmodium yoelii, Toxoplasma gondii, and Cryptosporidium parvum--describing relationships between these organisms based on retained functional linkages. This comparison provided a glimpse of the highly evolved nature of P. falciparum; for instance, a deficit of nearly 26% in terms of predicted interactions is observed against P. yoelii, because of missing ortholog partners in pairs of functionally linked proteins. [ABSTRACT FROM AUTHOR]

Serum response factor (SRF) binds a 1216-fold degenerate cis element known as the CArG box. CArG boxes are found primarily in muscle- and growth-factor-associated genes although the full spectrum of functional CArG elements in the genome (the CArGome) has yet to be defined. Here we describe a genome-wide screen to further define the functional mammalian CArGome. A computational approach involving comparative genomic analyses of human and mouse orthologous genes uncovered >100 hypothetical SRF-dependent genes, including 10 previously identified SRF targets, harboring a conserved CArG element within 4000 bp of the annotated transcription start site (TSS). We PCR-cloned 89 hypothetical SRF targets and subjected each of them to at least two of several validations including luciferase reporter, gel shift, chromatin immunoprecipitation, and mRNA expression following RNAi knockdown of SRF; 60189 (67%) of the targets were validated. Interestingly, 26 of the validated SRF target genes encode for cytoskeletal/contractile or adhesion proteins. RNAi knockdown of SRF diminishes expression of several SRF-dependent cytoskeletal genes and elicits an attending perturbation in the cytoarchitecture of both human and rodent cells. These data illustrate the power of integrating existing algorithms to interrogate the genome in a relatively unbiased fashion for cis-regulatory element discovery. In this manner, we have further expanded the mammalian CArGome with the discovery of an array of cyto-contractile genes that coordinate normal cytoskeletal homeostasis. We suggest one function of SRF is that of an ancient master regulator of the actin cytoskeleton. [ABSTRACT FROM AUTHOR]

Peroxisome proliferator-activated receptor γ(PPARγ), a nuclear receptor and the target of anti-diabetic thiazolinedione drugs, is known as the master regulator of adipocyte biology. Although it regulates hundreds of adipocyte genes, PPARγ binding to endogenous genes has rarely been demonstrated. Here, utilizing chromatin immunoprecipitation (ChIP) coupled with whole genome tiling arrays, we identified 5299 genomic regions of PPARγ binding in mouse 3T3-L1 adipocytes. The consensus PPARγ/RXRα "DR-1"-binding motif was found at most of the sites, and ChIP for RXRα showed colocalization at nearly all locations tested. Bioinformatics analysis also revealed CCAAT/enhancer-binding protein (C/EBP)-binding motifs in the vicinity of most PPARγ-binding sites, and genome-wide analysis of C/EBPα binding demonstrated that it localized to 3350 of the locations bound by PPARγ. Importantly, most genes induced in adipogenesis were bound by both PPARγ and C/EBPα, while very few were PPARγ-specific. C/EBPβ also plays a role at many of these genes, such that both C/EBPα and β are required along with PPARγ for robust adipocyte-specific gene expression. Thus, PPARγ and C/EBP factors cooperatively orchestrate adipocyte biology by adjacent binding on an unanticipated scale. [ABSTRACT FROM AUTHOR]

The failure to expand functional pancreatic β-cell mass in response to increased metabolic demand is a hallmark of type 2 diabetes. Lineage tracing studies indicate that replication of existing β-cells is the principle mechanism for β-cell expansion in adult mice. Here we demonstrate that the proliferative response of β-cells is dependent on the orphan nuclear receptor hepatocyte nuclear factor-4α (HNF-4α), the gene that is mutated in Maturity-Onset Diabetes of the Young 1 (MODY1). Computational analysis of microarray expression profiles from isolated islets of mice lacking HNF-4α in pancreatic β-cells reveals that HNF-4α regulates selected genes in the β-cell, many of which are involved in proliferation. Using a physiological model of β-cell expansion, we show that HNF-4α is required for β-cell replication and the activation of the Ras/ERK signaling cascade in islets. This phenotype correlates with the down-regulation of suppression of tumorigenicity 5 (ST5) in HNF-4α mutants, which we identify as a novel regulator of ERK phosphorylation in β-cells and a direct transcriptional target of HNF-4α in vivo. Together, these results indicate that HNF-4α is essential for the physiological expansion of adult β-cell mass in response to increased metabolic demand. [ABSTRACT FROM AUTHOR]

Regions of gain and loss of genomic DNA occur in many cancers and can drive the genesis and progression of disease. These copy number aberrations (CNAs) can be detected at high resolution by using microarray-based techniques. However, robust statistical approaches are needed to identify nonrandom gains and losses across multiple experiments/samples. We have developed a method called Significance Testing for Aberrant Copy number (STAC) to address this need. STAC utilizes two complementary statistics in combination with a novel search strategy. The significance of both statistics is assessed, and P-values are assigned to each location on the genome by using a multiple testing corrected permutation approach. We validate our method by using two published cancer data sets. STAC identifies genomic alterations known to be of clinical and biological significance and provides statistical support for 85% of previously reported regions. Moreover, STAC identifies numerous additional regions of significant gain/loss in these data that warrant further investigation. The P-values provided by STAC can be used to prioritize regions for follow-up study in an unbiased fashion. We conclude that STAC is a powerful tool for identifying nonrandom genomic amplifications and deletions across multiple experiments. A Java version of STAC is freely available for download at http://cbil.upenn.edu/STAC. [ABSTRACT FROM AUTHOR]