Browse
Submit Data
Databases
API
Help

Dataset Information

23 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

Multi-Omics Approach to Dissect the Mechanisms of Rexinoid Signaling in Myoblast Differentiation.

ABSTRACT: Stem cells represent a key resource in regenerative medicine, however, there is a critical need for pharmacological modulators to promote efficient conversion of stem cells into a myogenic lineage. We have previously shown that bexarotene, an agonist of retinoid X receptor (RXR) approved for cancer therapy, promotes the specification and differentiation of skeletal muscle progenitors. To decipher the molecular regulation of rexinoid signaling in myogenic differentiation, we have integrated RNA-seq transcription profiles with ChIP-seq of H4K8, H3K9, H3K18, H3K27 acetylation, and H3K27 methylation in addition to that of histone acetyl-transferase p300 in rexinoid-promoted myoblast differentiation. Here, we provide details regarding data collection, validation and omics integration analyses to offer strategies for future data application and replication. Our analyses also reveal molecular pathways underlying different patterns of gene expression and p300-associated histone acetylation at distinct chromatin states in rexinoid-enhanced myoblast differentiation. These datasets can be repurposed for future studies to examine the relationship between signaling molecules, chromatin modifiers and histone acetylation in myogenic regulation, providing a framework for discovery and functional characterization of muscle-specific loci.

SUBMITTER: Khilji S

PROVIDER: S-EPMC8484533 | biostudies-literature |

REPOSITORIES: biostudies-literature

ACCESS DATA

Json Xml

Similar Datasets

Integrating Multi-omics Data to Dissect Mechanisms of DNA repair Dysregulation in Breast Cancer.

Project description:DNA repair genes and pathways that are transcriptionally dysregulated in cancer provide the first line of evidence for the altered DNA repair status in tumours, and hence have been explored intensively as a source for biomarker discovery. The molecular mechanisms underlying DNA repair dysregulation, however, have not been systematically investigated in any cancer type. In this study, we performed a statistical analysis to dissect the roles of DNA copy number alteration (CNA), DNA methylation (DM) at gene promoter regions and the expression changes of transcription factors (TFs) in the differential expression of individual DNA repair genes in normal versus tumour breast samples. These gene-level results were summarised at pathway level to assess whether different DNA repair pathways are affected in distinct manners. Our results suggest that CNA and expression changes of TFs are major causes of DNA repair dysregulation in breast cancer, and that a subset of the identified TFs may exert global impacts on the dysregulation of multiple repair pathways. Our work hence provides novel insights into DNA repair dysregulation in breast cancer. These insights improve our understanding of the molecular basis of the DNA repair biomarkers identified thus far, and have potential to inform future biomarker discovery.

| S-EPMC5036051 | biostudies-literature

Signaling mechanisms in renal compensatory hypertrophy revealed by multi-omics.

Project description:Loss of a kidney results in compensatory growth of the remaining kidney, a phenomenon of considerable clinical importance. However, the mechanisms involved are largely unknown. Here, we use a multi-omic approach in a unilateral nephrectomy model in male mice to identify signaling processes associated with renal compensatory hypertrophy, demonstrating that the lipid-activated transcription factor peroxisome proliferator-activated receptor alpha (PPARα) is an important determinant of proximal tubule cell size and is a likely mediator of compensatory proximal tubule hypertrophy.

| S-EPMC10276015 | biostudies-literature

Multi-Omics Approach Identifies Molecular Mechanisms of Plant-Fungus Mycorrhizal Interaction.

Project description:In mycorrhizal symbiosis, plant roots form close, mutually beneficial interactions with soil fungi. Before this mycorrhizal interaction can be established however, plant roots must be capable of detecting potential beneficial fungal partners and initiating the gene expression patterns necessary to begin symbiosis. To predict a plant root-mycorrhizal fungi sensor systems, we analyzed in vitro experiments of Populus tremuloides (aspen tree) and Laccaria bicolor (mycorrhizal fungi) interaction and leveraged over 200 previously published transcriptomic experimental data sets, 159 experimentally validated plant transcription factor binding motifs, and more than 120-thousand experimentally validated protein-protein interactions to generate models of pre-mycorrhizal sensor systems in aspen root. These sensor mechanisms link extracellular signaling molecules with gene regulation through a network comprised of membrane receptors, signal cascade proteins, transcription factors, and transcription factor biding DNA motifs. Modeling predicted four pre-mycorrhizal sensor complexes in aspen that interact with 15 transcription factors to regulate the expression of 1184 genes in response to extracellular signals synthesized by Laccaria. Predicted extracellular signaling molecules include common signaling molecules such as phenylpropanoids, salicylate, and jasmonic acid. This multi-omic computational modeling approach for predicting the complex sensory networks yielded specific, testable biological hypotheses for mycorrhizal interaction signaling compounds, sensor complexes, and mechanisms of gene regulation.

| S-EPMC4717292 | biostudies-literature

Dynamic multi-omics and mechanistic modeling approach uncovers novel mechanisms of kidney fibrosis progression

Project description:Kidney fibrosis, characterized by excessive extracellular matrix (ECM) deposition, is a progressive disease that, despite affecting 10% of the population, lacks specific treatments and suitable biomarkers. Aimed at unraveling disease mechanisms and identifying potential therapeutic targets, this study presents a comprehensive, time-resolved multi-omics analysis of kidney fibrosis using an in vitro model system based on human kidney PDGFRβ+ mesenchymal cells. Using computational network modeling we integrated transcriptomics, proteomics, phosphoproteomics, and secretomics with imaging of the extracellular matrix (ECM). We quantified over 14,000 biomolecules across seven time points following TGF-β stimulation, revealing distinct temporal patterns in the expression and activity of known and potential novel renal fibrosis markers and modulators. The resulting time-resolved multi-omic network models allowed us to propose mechanisms related to fibrosis progression through early transcriptional reprogramming. Using siRNA knockdowns and phenotypic assays, we validated predictions and elucidated regulatory mechanisms underlying kidney fibrosis. Notably, we demonstrate that several early-activated transcription factors, including FLI1 and E2F1, act as negative regulators of collagen deposition and propose underlying molecular mechanisms. This work advances our understanding of the pathogenesis of kidney fibrosis and provides a valuable resource for the organ fibrosis research community.

2024-11-07 | E-MTAB-14521 | biostudies-arrayexpress

Complementary omics strategies to dissect p53 signaling networks under nutrient stress.

Project description:Signaling trough p53is a major cellular stress response mechanism and increases upon nutrient stresses such as starvation. Here, we show in a human hepatoma cell line that starvation leads to robust nuclear p53 stabilization. Using BioID, we determine the cytoplasmic p53 interaction network within the immediate-early starvation response and show that p53 is dissociated from several metabolic enzymes and the kinase PAK2 for which direct binding with the p53 DNA-binding domain was confirmed with NMR studies. Furthermore, proteomics after p53 immunoprecipitation (RIME) uncovered the nuclear interactome under prolonged starvation, where we confirmed the novel p53 interactors SORBS1 (insulin receptor signaling) and UGP2 (glycogen synthesis). Finally, transcriptomics after p53 re-expression revealed a distinct starvation-specific transcriptome response and suggested previously unknown nutrient-dependent p53 target genes. Together, our complementary approaches delineate several nodes of the p53 signaling cascade upon starvation, shedding new light on the mechanisms of p53 as nutrient stress sensor. Given the central role of p53 in cancer biology and the beneficial effects of fasting in cancer treatment, the identified interaction partners and networks could pinpoint novel pharmacologic targets to fine-tune p53 activity.

| S-EPMC9151573 | biostudies-literature

An integrated multi-omics approach to identify regulatory mechanisms in cancer metastatic processes.

Project description:BackgroundMetastatic progress is the primary cause of death in most cancers, yet the regulatory dynamics driving the cellular changes necessary for metastasis remain poorly understood. Multi-omics approaches hold great promise for addressing this challenge; however, current analysis tools have limited capabilities to systematically integrate transcriptomic, epigenomic, and cistromic information to accurately define the regulatory networks critical for metastasis.ResultsTo address this limitation, we use a purposefully generated cellular model of colon cancer invasiveness to generate multi-omics data, including expression, accessibility, and selected histone modification profiles, for increasing levels of invasiveness. We then adopt a rigorous probabilistic framework for joint inference from the resulting heterogeneous data, along with transcription factor binding profiles. Our approach uses probabilistic graphical models to leverage the functional information provided by specific epigenomic changes, models the influence of multiple transcription factors simultaneously, and automatically learns the activating or repressive roles of cis-regulatory events. Global analysis of these relationships reveals key transcription factors driving invasiveness, as well as their likely target genes. Disrupting the expression of one of the highly ranked transcription factors JunD, an AP-1 complex protein, confirms functional relevance to colon cancer cell migration and invasion. Transcriptomic profiling confirms key regulatory targets of JunD, and a gene signature derived from the model demonstrates strong prognostic potential in TCGA colorectal cancer data.ConclusionsOur work sheds new light into the complex molecular processes driving colon cancer metastasis and presents a statistically sound integrative approach to analyze multi-omics profiles of a dynamic biological process.

| S-EPMC7789593 | biostudies-literature

A multi-omics approach to visualize early neuronal differentiation from hESCs in 4D.

Project description:Neuronal differentiation of pluripotent stem cells is an established method to study physiology, disease, and medication safety. However, the sequence of events in human neuronal differentiation and the ability of in vitro models to recapitulate early brain development are poorly understood. We developed a protocol optimized for the study of early human brain development and neuropharmacological applications. We comprehensively characterized gene expression and epigenetic profiles at four timepoints, because the cells differentiate from embryonic stem cells towards a heterogeneous population of progenitors, immature and mature neurons bearing telencephalic signatures. A multi-omics roadmap of neuronal differentiation, combined with searchable interactive gene analysis tools, allows for extensive exploration of early neuronal development and the effect of medications.

| S-EPMC9593815 | biostudies-literature

A Multi-Omics Approach to Evaluate the Toxicity Mechanisms Associated with Silver Nanoparticles Exposure.

Project description:Silver nanoparticles (AgNPs) are currently used in many different industrial, commercial and health fields, mainly due to their antibacterial properties. Due to this widespread use, humans and the environment are increasingly exposed to these types of nanoparticles, which is the reason why the evaluation of the potential toxicity associated with AgNPs is of great importance. Although some of the toxic effects induced by AgNPs have already been shown, the elucidation of more complete mechanisms is yet to be achieved. In this sense, and since the integration of metabolomics and transcriptomics approaches constitutes a very useful strategy, in the present study targeted and untargeted metabolomics and DNA microarrays assays have been combined to evaluate the molecular mechanisms involved in the toxicity induced by 10 nm AgNPs. The results have shown that AgNPs induce the synthesis of glutathione as a cellular defense mechanism to face the oxidative environment, while inducing the depletion of relevant molecules implicated in the synthesis of important antioxidants. In addition, it has been observed that AgNPs completely impair the intracellular energetic metabolism, especially affecting the production of adenosine triphosphate (ATP) and disrupting the tricarboxylic acids cycle. It has been demonstrated that AgNPs exposure also affects the glycolysis pathway. The effect on such pathway differs depending on the step of the cycle, which a significant increase in the levels of glucose as way to counterbalance the depleted levels of ATP.

| S-EPMC9146515 | biostudies-literature

Multi-omics intervention in <i>Setaria</i> to dissect climate-resilient traits: Progress and prospects.

Project description:Millets constitute a significant proportion of underutilized grasses and are well known for their climate resilience as well as excellent nutritional profiles. Among millets, foxtail millet (Setaria italica) and its wild relative green foxtail (S. viridis) are collectively regarded as models for studying broad-spectrum traits, including abiotic stress tolerance, C4 photosynthesis, biofuel, and nutritional traits. Since the genome sequence release, the crop has seen an exponential increase in omics studies to dissect agronomic, nutritional, biofuel, and climate-resilience traits. These studies have provided first-hand information on the structure, organization, evolution, and expression of several genes; however, knowledge of the precise roles of such genes and their products remains elusive. Several open-access databases have also been instituted to enable advanced scientific research on these important crops. In this context, the current review enumerates the contemporary trend of research on understanding the climate resilience and other essential traits in Setaria, the knowledge gap, and how the information could be translated for the crop improvement of related millets, biofuel crops, and cereals. Also, the review provides a roadmap for studying other underutilized crop species using Setaria as a model.

| S-EPMC9470963 | biostudies-literature

PERK Signaling Controls Myoblast Differentiation by Regulating MicroRNA Networks.

Project description:The unfolded protein response (UPR) plays important roles in various cells that have a high demand for protein folding, which are involved in the process of cell differentiation and development. Here, we separately knocked down the three sensors of the UPR in myoblasts and found that PERK knockdown led to a marked transformation in myoblasts from a fusiform to a rounded morphology, which suggests that PERK is required for early myoblast differentiation. Interestingly, knocking down PERK induced reprogramming of C2C12 myoblasts into stem-like cells by altering the miRNA networks associated with differentiation and stemness maintenance, and the PERK-ATF4 signaling pathway transactivated muscle differentiation-associated miRNAs in the early stage of myoblast differentiation. Furthermore, we identified Ppp1cc as a direct target gene of miR-128 regulated by the PERK signaling pathway and showed that its repression is critical for a feedback loop that regulates the activity of UPR-associated signaling pathways, leading to cell migration, cell fusion, endoplasmic reticulum expansion, and myotube formation during myoblast differentiation. Subsequently, we found that the RNA-binding protein ARPP21, encoded by the host gene of miR-128-2, antagonized miR-128 activity by competing with it to bind to the 3' untranslated region (UTR) of Ppp1cc to maintain the balance of the differentiation state. Together, these results reveal the crucial role of PERK signaling in myoblast maintenance and differentiation and identify the mechanism underlying the role of UPR signaling as a major regulator of miRNA networks during early differentiation of myoblasts.

| S-EPMC8193987 | biostudies-literature

OmicsDI is part of the ELIXIR infrastructure

OmicsDI is an Elixir interoperability service. Learn more ›

Tweets

OmicsDI Databases

PRIDE
PeptideAtlas
MassIVE
JPOST Repository
Physiome Model Repository

EGA
EVA
ENA
LINCS
PAXDB
Cell Collective

MetaboLights
Metabolomics Workbench
MetabolomeExpress
GNPS
BioModels
FAIRDOMHub

ArrayExpress
dbGaP
ExpressionAtlas
GEO
NODE

Information

Databases
Help
API
Contact us
Code on GitHub
Terms of use
Submit Data