71,275 research outputs found
Coordinated actions of microRNAs with other epigenetic factors regulate skeletal muscle development and adaptation
Epigenetics plays a pivotal role in regulating gene expression in development, in response to cellular stress or in disease states, in virtually all cell types. MicroRNAs (miRNAs) are short, non-coding RNA molecules that mediate RNA silencing and regulate gene expression. miRNAs were discovered in 1993 and have been extensively studied ever since. They can be expressed in a tissue-specific manner and play a crucial role in tissue development and many biological processes. miRNAs are responsible for changes in the cell epigenome because of their ability to modulate gene expression post-transcriptionally. Recently, numerous studies have shown that miRNAs and other epigenetic factors can regulate each other or cooperate in regulating several biological processes. On the one hand, the expression of some miRNAs is silenced by DNA methylation, and histone modifications have been demonstrated to modulate miRNA expression in many cell types or disease states. On the other hand, miRNAs can directly target epigenetic factors, such as DNA methyltransferases or histone deacetylases, thus regulating chromatin structure. Moreover, several studies have reported coordinated actions between miRNAs and other epigenetic mechanisms to reinforce the regulation of gene expression. This paper reviews multiple interactions between miRNAs and epigenetic factors in skeletal muscle development and in response to stimuli or disease
Network-based approaches to explore complex biological systems towards network medicine
Network medicine relies on different types of networks: from the molecular level of protein–protein interactions to gene regulatory network and correlation studies of gene expression. Among network approaches based on the analysis of the topological properties of protein–protein interaction (PPI) networks, we discuss the widespread DIAMOnD (disease module detection) algorithm. Starting from the assumption that PPI networks can be viewed as maps where diseases can be identified with localized perturbation within a specific neighborhood (i.e., disease modules), DIAMOnD performs a systematic analysis of the human PPI network to uncover new disease-associated genes by exploiting the connectivity significance instead of connection density. The past few years have witnessed the increasing interest in understanding the molecular mechanism of post-transcriptional regulation with a special emphasis on non-coding RNAs since they are emerging as key regulators of many cellular processes in both physiological and pathological states. Recent findings show that coding genes are not the only targets that microRNAs interact with. In fact, there is a pool of different RNAs—including long non-coding RNAs (lncRNAs) —competing with each other to attract microRNAs for interactions, thus acting as competing endogenous RNAs (ceRNAs). The framework of regulatory networks provides a powerful tool to gather new insights into ceRNA regulatory mechanisms. Here, we describe a data-driven model recently developed to explore the lncRNA-associated ceRNA activity in breast invasive carcinoma. On the other hand, a very promising example of the co-expression network is the one implemented by the software SWIM (switch miner), which combines topological properties of correlation networks with gene expression data in order to identify a small pool of genes—called switch genes—critically associated with drastic changes in cell phenotype. Here, we describe SWIM tool along with its applications to cancer research and compare its predictions with DIAMOnD disease genes
Pathways and gene networks mediating the regulatory effects of cannabidiol, a nonpsychoactive cannabinoid, in autoimmune T cells.
BackgroundOur previous studies showed that the non-psychoactive cannabinoid, cannabidiol (CBD), ameliorates the clinical symptoms in mouse myelin oligodendrocyte glycoprotein (MOG)35-55-induced experimental autoimmune encephalomyelitis model of multiple sclerosis (MS) as well as decreases the memory MOG35-55-specific T cell (TMOG) proliferation and cytokine secretion including IL-17, a key autoimmune factor. The mechanisms of these activities are currently poorly understood.MethodsHerein, using microarray-based gene expression profiling, we describe gene networks and intracellular pathways involved in CBD-induced suppression of these activated memory TMOG cells. Encephalitogenic TMOG cells were stimulated with MOG35-55 in the presence of spleen-derived antigen presenting cells (APC) with or without CBD. mRNA of purified TMOG was then subjected to Illumina microarray analysis followed by ingenuity pathway analysis (IPA), weighted gene co-expression network analysis (WGCNA) and gene ontology (GO) elucidation of gene interactions. Results were validated using qPCR and ELISA assays.ResultsGene profiling showed that the CBD treatment suppresses the transcription of a large number of proinflammatory genes in activated TMOG. These include cytokines (Xcl1, Il3, Il12a, Il1b), cytokine receptors (Cxcr1, Ifngr1), transcription factors (Ier3, Atf3, Nr4a3, Crem), and TNF superfamily signaling molecules (Tnfsf11, Tnfsf14, Tnfrsf9, Tnfrsf18). "IL-17 differentiation" and "IL-6 and IL-10-signaling" were identified among the top processes affected by CBD. CBD increases a number of IFN-dependent transcripts (Rgs16, Mx2, Rsad2, Irf4, Ifit2, Ephx1, Ets2) known to execute anti-proliferative activities in T cells. Interestingly, certain MOG35-55 up-regulated transcripts were maintained at high levels in the presence of CBD, including transcription factors (Egr2, Egr1, Tbx21), cytokines (Csf2, Tnf, Ifng), and chemokines (Ccl3, Ccl4, Cxcl10) suggesting that CBD may promote exhaustion of memory TMOG cells. In addition, CBD enhanced the transcription of T cell co-inhibitory molecules (Btla, Lag3, Trat1, and CD69) known to interfere with T/APC interactions. Furthermore, CBD enhanced the transcription of oxidative stress modulators with potent anti-inflammatory activity that are controlled by Nfe2l2/Nrf2 (Mt1, Mt2a, Slc30a1, Hmox1).ConclusionsMicroarray-based gene expression profiling demonstrated that CBD exerts its immunoregulatory effects in activated memory TMOG cells via (a) suppressing proinflammatory Th17-related transcription, (b) by promoting T cell exhaustion/tolerance, (c) enhancing IFN-dependent anti-proliferative program, (d) hampering antigen presentation, and (d) inducing antioxidant milieu resolving inflammation. These findings put forward mechanism by which CBD exerts its anti-inflammatory effects as well as explain the beneficial role of CBD in pathological memory T cells and in autoimmune diseases
Mapping Dynamic Histone Acetylation Patterns to Gene Expression in Nanog-depleted Murine Embryonic Stem Cells
Embryonic stem cells (ESC) have the potential to self-renew indefinitely and
to differentiate into any of the three germ layers. The molecular mechanisms
for self-renewal, maintenance of pluripotency and lineage specification are
poorly understood, but recent results point to a key role for epigenetic
mechanisms. In this study, we focus on quantifying the impact of histone 3
acetylation (H3K9,14ac) on gene expression in murine embryonic stem cells. We
analyze genome-wide histone acetylation patterns and gene expression profiles
measured over the first five days of cell differentiation triggered by
silencing Nanog, a key transcription factor in ESC regulation. We explore the
temporal and spatial dynamics of histone acetylation data and its correlation
with gene expression using supervised and unsupervised statistical models. On a
genome-wide scale, changes in acetylation are significantly correlated to
changes in mRNA expression and, surprisingly, this coherence increases over
time. We quantify the predictive power of histone acetylation for gene
expression changes in a balanced cross-validation procedure. In an in-depth
study we focus on genes central to the regulatory network of Mouse ESC,
including those identified in a recent genome-wide RNAi screen and in the
PluriNet, a computationally derived stem cell signature. We find that compared
to the rest of the genome, ESC-specific genes show significantly more
acetylation signal and a much stronger decrease in acetylation over time, which
is often not reflected in an concordant expression change. These results shed
light on the complexity of the relationship between histone acetylation and
gene expression and are a step forward to dissect the multilayer regulatory
mechanisms that determine stem cell fate.Comment: accepted at PLoS Computational Biolog
Organellar carbon metabolism is co-ordinated with distinct developmental phases of secondary xylem
Subcellular compartmentation of plant biosynthetic pathways in the mitochondria and plastids requires coordinated regulation of nuclear encoded genes, and the role of these genes has been largely ignored by wood researchers. In this study, we constructed a targeted systems genetics coexpression network of xylogenesis in Eucalyptus using plastid and mitochondrial carbon metabolic genes and compared the resulting clusters to the aspen xylem developmental series. The constructed network clusters reveal the organization of transcriptional modules regulating subcellular metabolic functions in plastids and mitochondria. Overlapping genes between the plastid and mitochondrial networks implicate the common transcriptional regulation of carbon metabolism during xylem secondary growth. We show that the central processes of organellar carbon metabolism are distinctly coordinated across the developmental stages of wood formation and are specifically associated with primary growth and secondary cell wall deposition. We also demonstrate that, during xylogenesis, plastid-targeted carbon metabolism is partially regulated by the central clock for carbon allocation towards primary and secondary xylem growth, and we discuss these networks in the context of previously established associations with wood-related complex traits. This study provides a new resolution into the integration and transcriptional regulation of plastid- and mitochondrial-localized carbon metabolism during xylogenesis
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Finding New Cell Wall Regulatory Genes in Populus trichocarpa Using Multiple Lines of Evidence.
Understanding the regulatory network controlling cell wall biosynthesis is of great interest in Populus trichocarpa, both because of its status as a model woody perennial and its importance for lignocellulosic products. We searched for genes with putatively unknown roles in regulating cell wall biosynthesis using an extended network-based Lines of Evidence (LOE) pipeline to combine multiple omics data sets in P. trichocarpa, including gene coexpression, gene comethylation, population level pairwise SNP correlations, and two distinct SNP-metabolite Genome Wide Association Study (GWAS) layers. By incorporating validation, ranking, and filtering approaches we produced a list of nine high priority gene candidates for involvement in the regulation of cell wall biosynthesis. We subsequently performed a detailed investigation of candidate gene GROWTH-REGULATING FACTOR 9 (PtGRF9). To investigate the role of PtGRF9 in regulating cell wall biosynthesis, we assessed the genome-wide connections of PtGRF9 and a paralog across data layers with functional enrichment analyses, predictive transcription factor binding site analysis, and an independent comparison to eQTN data. Our findings indicate that PtGRF9 likely affects the cell wall by directly repressing genes involved in cell wall biosynthesis, such as PtCCoAOMT and PtMYB.41, and indirectly by regulating homeobox genes. Furthermore, evidence suggests that PtGRF9 paralogs may act as transcriptional co-regulators that direct the global energy usage of the plant. Using our extended pipeline, we show multiple lines of evidence implicating the involvement of these genes in cell wall regulatory functions and demonstrate the value of this method for prioritizing candidate genes for experimental validation
Artificial Neural Network Inference (ANNI): A Study on Gene-Gene Interaction for Biomarkers in Childhood Sarcomas
Objective: To model the potential interaction between previously identified biomarkers in children sarcomas using artificial neural network inference (ANNI).
Method: To concisely demonstrate the biological interactions between correlated genes in an interaction network map, only 2 types of sarcomas in the children small round blue cell tumors (SRBCTs) dataset are discussed in this paper. A backpropagation neural network was used to model the potential interaction between genes. The prediction weights and signal directions were used to model the strengths of the interaction signals and the direction of the interaction link between genes. The ANN model was validated using Monte Carlo cross-validation to minimize the risk of over-fitting and to optimize generalization ability of the model.
Results: Strong connection links on certain genes (TNNT1 and FNDC5 in rhabdomyosarcoma (RMS); FCGRT and OLFM1 in Ewing’s sarcoma (EWS)) suggested their potency as central hubs in the interconnection of genes with different functionalities. The results showed that the RMS patients in this dataset are likely to be congenital and at low risk of cardiomyopathy development. The EWS patients are likely to be complicated by EWS-FLI fusion and deficiency in various signaling pathways, including Wnt, Fas/Rho and intracellular oxygen.
Conclusions: The ANN network inference approach and the examination of identified genes in the published literature within the context of the disease highlights the substantial influence of certain genes in sarcomas
HOXD8 exerts a tumor-suppressing role in colorectal cancer as an apoptotic inducer
Homeobox (HOX) genes are conserved transcription factors which determine the anterior-posterior body axis patterning. HOXD8 is a member of HOX genes deregulated in several tumors such as lung carcinoma, neuroblastoma, glioma and colorectal cancer (CRC) in a context-dependent manner. In CRC, HOXD8 is downregulated in cancer tissues and metastatic foci as compared to normal tissues. Whether HOXD8 acts as a tumor suppressor of malignant progression and metastasis is still unclear. Also, the underlying mechanism of its function including the downstream targets is totally unknown. Here, we clarified the lower expression of HOXD8 in clinical colorectal cancer vs. normal colon tissues. Also, we showed that stable expression of HOXD8 in colorectal cancer cells significantly reduced the cell proliferation, anchorage-independent growth and invasion. Further, using The Cancer Genome Atlas (TCGA), we identified the genes associated with HOXD8 in order to demonstrate its function as a suppressor or a promoter of colorectal carcinoma. Among inversely related genes, apoptotic inhibitors like STK38 kinase and MYC were shown to be negatively associated with HOXD8. We demonstrated the ability of HOXD8 to upregulate executioner caspases 6 & 7 and cleaved PARP, thus inducing the apoptotic events in colorectal cancer cells
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Long non-coding RNA profiling of human lymphoid progenitor cells reveals transcriptional divergence of B cell and T cell lineages.
To elucidate the transcriptional 'landscape' that regulates human lymphoid commitment during postnatal life, we used RNA sequencing to assemble the long non-coding transcriptome across human bone marrow and thymic progenitor cells spanning the earliest stages of B lymphoid and T lymphoid specification. Over 3,000 genes encoding previously unknown long non-coding RNAs (lncRNAs) were revealed through the analysis of these rare populations. Lymphoid commitment was characterized by lncRNA expression patterns that were highly stage specific and were more lineage specific than those of protein-coding genes. Protein-coding genes co-expressed with neighboring lncRNA genes showed enrichment for ontologies related to lymphoid differentiation. The exquisite cell-type specificity of global lncRNA expression patterns independently revealed new developmental relationships among the earliest progenitor cells in the human bone marrow and thymus
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