A semi-parametric Bayesian model for unsupervised differential co-expression analysis

<p>Abstract</p> <p>Background</p> <p>Differential co-expression analysis is an emerging strategy for characterizing disease related dysregulation of gene expression regulatory networks. Given pre-defined sets of biological samples, such analysis aims at identifying genes that are co-expressed in one, but not in the other set of samples.</p> <p>Results</p> <p>We developed a novel probabilistic framework for jointly uncovering contexts (i.e. groups of samples) with specific co-expression patterns, and groups of genes with different co-expression patterns across such contexts. In contrast to current clustering and bi-clustering procedures, the implicit similarity measure in this model used for grouping biological samples is based on the clustering structure of genes within each sample and not on traditional measures of gene expression level similarities. Within this framework, biological samples with widely discordant expression patterns can be placed in the same context as long as the co-clustering structure of genes is concordant within these samples. To the best of our knowledge, this is the first method to date for unsupervised differential co-expression analysis in this generality. When applied to the problem of identifying molecular subtypes of breast cancer, our method identified reproducible patterns of differential co-expression across several independent expression datasets. Sample groupings induced by these patterns were highly informative of the disease outcome. Expression patterns of differentially co-expressed genes provided new insights into the complex nature of the ER<it>α </it>regulatory network.</p> <p>Conclusions</p> <p>We demonstrated that the use of the co-clustering structure as the similarity measure in the unsupervised analysis of sample gene expression profiles provides valuable information about expression regulatory networks.</p

WebGimm: An integrated web-based platform for cluster analysis, functional analysis, and interactive visualization of results

Cluster analysis methods have been extensively researched, but the adoption of new methods is often hindered by technical barriers in their implementation and use. WebGimm is a free cluster analysis web-service, and an open source general purpose clustering web-server infrastructure designed to facilitate easy deployment of integrated cluster analysis servers based on clustering and functional annotation algorithms implemented in R. Integrated functional analyses and interactive browsing of both, clustering structure and functional annotations provides a complete analytical environment for cluster analysis and interpretation of results. The Java Web Start client-based interface is modeled after the familiar cluster/treeview packages making its use intuitive to a wide array of biomedical researchers. For biomedical researchers, WebGimm provides an avenue to access state of the art clustering procedures. For Bioinformatics methods developers, WebGimm offers a convenient avenue to deploy their newly developed clustering methods. WebGimm server, software and manuals can be freely accessed at http://ClusterAnalysis.org/

Genomics Portals: integrative web-platform for mining genomics data

<p>Abstract</p> <p>Background</p> <p>A large amount of experimental data generated by modern high-throughput technologies is available through various public repositories. Our knowledge about molecular interaction networks, functional biological pathways and transcriptional regulatory modules is rapidly expanding, and is being organized in lists of functionally related genes. Jointly, these two sources of information hold a tremendous potential for gaining new insights into functioning of living systems.</p> <p>Results</p> <p>Genomics Portals platform integrates access to an extensive knowledge base and a large database of human, mouse, and rat genomics data with basic analytical visualization tools. It provides the context for analyzing and interpreting new experimental data and the tool for effective mining of a large number of publicly available genomics datasets stored in the back-end databases. The uniqueness of this platform lies in the volume and the diversity of genomics data that can be accessed and analyzed (gene expression, ChIP-chip, ChIP-seq, epigenomics, computationally predicted binding sites, etc), and the integration with an extensive knowledge base that can be used in such analysis.</p> <p>Conclusion</p> <p>The integrated access to primary genomics data, functional knowledge and analytical tools makes Genomics Portals platform a unique tool for interpreting results of new genomics experiments and for mining the vast amount of data stored in the Genomics Portals backend databases. Genomics Portals can be accessed and used freely at <url>http://GenomicsPortals.org</url>.</p

TNFR2 maintains adequate IL-12 production by dendritic cells in inflammatory responses by regulating endogenous TNF levels

Sepsis-induced immune reactions are reduced in TNF receptor 2 (TNFR2)-deficient mice as previously shown. In order to elucidate the underlying mechanisms, the functional integrity of myeloid cells of TNFR2-deficient mice was analyzed and compared to wild type (WT) mice. The capacity of dendritic cells to produce IL-12 was strongly impaired in TNF-deficient mice, mirroring impaired production of IL-12 by WT dendritic cells in sepsis or after LPS or TNF pre-treatment. In addition, TNFR2-deficient mice were refractory to LPS pre-treatment and also to hyper-sensitization by inactivated Propionibacterium acnes, indicating habituation to inflammatory stimuli by the immune response when TNFR2 is lacking. Constitutive expression of TNF mRNA in kidney, liver, spleen, colon and lung tissue, and the presence of soluble TNFR2 in urine of healthy WT mice supported the conclusion that TNF is continuously present in naïve mice and controlled by soluble TNFR2. In TNFR2-deficient mice endogenous TNF levels cannot be balanced and the continuous exposure to enhanced TNF levels impairs dendritic cell function. In conclusion, TNF pre-exposure suppresses secondary inflammatory reactions of myeloid cells; therefore, continuous control of endogenous TNF by soluble TNFR2 seems to be essential for the maintenance of adequate sensitivity to inflammatory stimuli

Correction to: HIF prolyl hydroxylase inhibition protects skeletal muscle from eccentric contraction induced injury

Following publication of the original article [1], the authors flagged that there is a discrepancy with the Availability of data and materials statement on page 12 of the article

HIF prolyl hydroxylase inhibition protects skeletal muscle from eccentric contraction-induced injury

BACKGROUND: In muscular dystrophy and old age, skeletal muscle repair is compromised leading to fibrosis and fatty tissue accumulation. Therefore, therapies that protect skeletal muscle or enhance repair would be valuable medical treatments. Hypoxia-inducible factors (HIFs) regulate gene transcription under conditions of low oxygen, and HIF target genes EPO and VEGF have been associated with muscle protection and repair. We tested the importance of HIF activation following skeletal muscle injury, in both a murine model and human volunteers, using prolyl hydroxylase inhibitors that stabilize and activate HIF. METHODS: Using a mouse eccentric limb injury model, we characterized the protective effects of prolyl hydroxylase inhibitor, GSK1120360A. We then extended these studies to examine the impact of EPO modulation and infiltrating immune cell populations on muscle protection. Finally, we extended this study with an experimental medicine approach using eccentric arm exercise in untrained volunteers to measure the muscle-protective effects of a clinical prolyl hydroxylase inhibitor, daprodustat. RESULTS: GSK1120360A dramatically prevented functional deficits and histological damage, while accelerating recovery after eccentric limb injury in mice. Surprisingly, this effect was independent of EPO, but required myeloid HIF1α-mediated iNOS activity. Treatment of healthy human volunteers with high-dose daprodustat reduced accumulation of circulating damage markers following eccentric arm exercise, although we did not observe any diminution of functional deficits with compound treatment. CONCLUSION: The results of these experiments highlight a novel skeletal muscle protective effect of prolyl hydroxylase inhibition via HIF-mediated expression of iNOS in macrophages. Partial recapitulation of these findings in healthy volunteers suggests elements of consistent pharmacology compared to responses in mice although there are clear differences between these two systems

Acute depletion of Tet1-dependent 5-hydroxymethylcytosine levels impairs LIF/Stat3 signaling and results in loss of embryonic stem cell identity

The TET family of FE(II) and 2-oxoglutarate-dependent enzymes (Tet1/2/3) promote DNA demethylation by converting 5-methylcytosine to 5-hydroxymethylcytosine (5hmC), which they further oxidize into 5-formylcytosine and 5-carboxylcytosine. Tet1 is robustly expressed in mouse embryonic stem cells (mESCs) and has been implicated in mESC maintenance. Here we demonstrate that, unlike genetic deletion, RNAi-mediated depletion of Tet1 in mESCs led to a significant reduction in 5hmC and loss of mESC identity. The differentiation phenotype due to Tet1 depletion positively correlated with the extent of 5hmC loss. Meta-analyses of genomic data sets suggested interaction between Tet1 and leukemia inhibitory factor (LIF) signaling. LIF signaling is known to promote self-renewal and pluripotency in mESCs partly by opposing MAPK/ERK-mediated differentiation. Withdrawal of LIF leads to differentiation of mESCs. We discovered that Tet1 depletion impaired LIF-dependent Stat3-mediated gene activation by affecting Stat3's ability to bind to its target sites on chromatin. Nanog overexpression or inhibition of MAPK/ERK signaling, both known to maintain mESCs in the absence of LIF, rescued Tet1 depletion, further supporting the dependence of LIF/Stat3 signaling on Tet1. These data support the conclusion that analysis of mESCs in the hours/days immediately following efficient Tet1 depletion reveals Tet1's normal physiological role in maintaining the pluripotent state that may be subject to homeostatic compensation in genetic models

Transcriptional recapitulation and subversion of embryonic colon development by mouse colon tumor models and human colon cancer

Colon tumors from four independent mouse models and 100 human colorectal cancers all exhibited striking recapitulation of embryonic colon gene expression from embryonic days 13.5-18.5

Multi-trait analysis characterizes the genetics of thyroid function and identifies causal associations with clinical implications

To date only a fraction of the genetic footprint of thyroid function has been clarified. We report a genome-wide association study meta-analysis of thyroid function in up to 271,040 individuals of European ancestry, including reference range thyrotropin (TSH), free thyroxine (FT4), free and total triiodothyronine (T3), proxies for metabolism (T3/FT4 ratio) as well as dichotomized high and low TSH levels. We revealed 259 independent significant associations for TSH (61% novel), 85 for FT4 (67% novel), and 62 novel signals for the T3 related traits. The loci explained 14.1%, 6.0%, 9.5% and 1.1% of the total variation in TSH, FT4, total T3 and free T3 concentrations, respectively. Genetic correlations indicate that TSH associated loci reflect the thyroid function determined by free T3, whereas the FT4 associations represent the thyroid hormone metabolism. Polygenic risk score and Mendelian randomization analyses showed the effects of genetically determined variation in thyroid function on various clinical outcomes, including cardiovascular risk factors and diseases, autoimmune diseases, and cancer. In conclusion, our results improve the understanding of thyroid hormone physiology and highlight the pleiotropic effects of thyroid function on various diseases

Transcriptional recapitulation and subversion of embryonic colon development by mouse colon tumor models and human colon cancer

Abstract Background The expression of carcino-embryonic antigen by colorectal cancer is an example of oncogenic activation of embryonic gene expression. Hypothesizing that oncogenesis-recapitulating-ontogenesis may represent a broad programmatic commitment, we compared gene expression patterns of human colorectal cancers (CRCs) and mouse colon tumor models to those of mouse colon development embryonic days 13.5-18.5. Results We report here that 39 colon tumors from four independent mouse models and 100 human CRCs encompassing all clinical stages shared a striking recapitulation of embryonic colon gene expression. Compared to normal adult colon, all mouse and human tumors over-expressed a large cluster of genes highly enriched for functional association to the control of cell cycle progression, proliferation, and migration, including those encoding MYC, AKT2, PLK1 and SPARC. Mouse tumors positive for nuclear β-catenin shifted the shared embryonic pattern to that of early development. Human and mouse tumors differed from normal embryonic colon by their loss of expression modules enriched for tumor suppressors (EDNRB, HSPE, KIT and LSP1). Human CRC adenocarcinomas lost an additional suppressor module (IGFBP4, MAP4K1, PDGFRA, STAB1 and WNT4). Many human tumor samples also gained expression of a coordinately regulated module associated with advanced malignancy (ABCC1, FOXO3A, LIF, PIK3R1, PRNP, TNC, TIMP3 and VEGF). Conclusion Cross-species, developmental, and multi-model gene expression patterning comparisons provide an integrated and versatile framework for definition of transcriptional programs associated with oncogenesis. This approach also provides a general method for identifying pattern-specific biomarkers and therapeutic targets. This delineation and categorization of developmental and non-developmental activator and suppressor gene modules can thus facilitate the formulation of sophisticated hypotheses to evaluate potential synergistic effects of targeting within- and between-modules for next-generation combinatorial therapeutics and improved mouse models