EMT-Regulome: a database for EMT-related regulatory interactions, motifs and network.
Ontology highlight
ABSTRACT:
SUBMITTER: Zhao Z
PROVIDER: S-EPMC5520922 | biostudies-literature | 2017 Jun
REPOSITORIES: biostudies-literature
Publications
EMT-Regulome: a database for EMT-related regulatory interactions, motifs and network.
Zhao Zhangxiang Z Zhou Wenbin W Han Yue Y Peng Fuduan F Wang Ruiping R Yu Ruihan R Wang Chengyu C Liang Haihai H Guo Zheng Z Gu Yunyan Y
Cell death & disease 20170615 6
Similar Datasets
Project description:BackgroundAn important aspect of molecular interactions is the dynamics associated with growth conditions. Intuitively, not all possible interactions take place together all the time in a cell as only a subset of genes is expressed based on environmental conditions.ResultsLarge scale gene expression data of Escherichia coli was analyzed to understand the dynamics exhibited at expression level. A large compendium of gene expression datasets, which covers about 466 growth conditions, was used for the analysis. Using gene expression data, genes of E. coli were profiled into three classes: Widely expressed, Conditionally expressed and Rarely expressed. Further, dynamics associated with molecular interactions were analysed by studying changing importance of motifs in the composite networks across growth conditions.ConclusionsOur analysis of large scale gene expression data suggests conditional expression of genes which brings about befitting responses for a given growth environment. We observe a range of importance for network motifs across conditions which can be correlated with a specific function. Our study therefore suggests rewiring of molecular interactions driven by gene expression changes depending on the conditional needs.
| S-EPMC4015501 | biostudies-literature
Project description:Epithelial to mesenchymal transition (EMT) is the process whereby a polarized epithelial cell ceases to maintain cell-cell contacts, loses expression of characteristic epithelial cell markers, and acquires mesenchymal cell markers and properties such as motility, contractile ability, and invasiveness. A complex process that occurs during development and many disease states, EMT involves a plethora of transcription factors (TFs) and signaling pathways. Whilst great advances have been made in both our understanding of the progressive cell-fate changes during EMT and the gene regulatory networks that drive this process, there are still gaps in our knowledge. Epigenetic modifications are dynamic, chromatin modifying enzymes are vast and varied, transcription factors are pleiotropic, and signaling pathways are multifaceted and rarely act alone. Therefore, it is of great importance that we decipher and understand each intricate step of the process and how these players at different levels crosstalk with each other to successfully orchestrate EMT. A delicate balance and fine-tuned cooperation of gene regulatory mechanisms is required for EMT to occur successfully, and until we resolve the unknowns in this network, we cannot hope to develop effective therapies against diseases that involve aberrant EMT such as cancer. In this review, we focus on data that challenge these unknown entities underlying EMT, starting with EMT stimuli followed by intracellular signaling through to epigenetic mechanisms and chromatin remodeling.
| S-EPMC7235173 | biostudies-literature
Project description:The RNA Bricks database (http://iimcb.genesilico.pl/rnabricks), stores information about recurrent RNA 3D motifs and their interactions, found in experimentally determined RNA structures and in RNA-protein complexes. In contrast to other similar tools (RNA 3D Motif Atlas, RNA Frabase, Rloom) RNA motifs, i.e. 'RNA bricks' are presented in the molecular environment, in which they were determined, including RNA, protein, metal ions, water molecules and ligands. All nucleotide residues in RNA bricks are annotated with structural quality scores that describe real-space correlation coefficients with the electron density data (if available), backbone geometry and possible steric conflicts, which can be used to identify poorly modeled residues. The database is also equipped with an algorithm for 3D motif search and comparison. The algorithm compares spatial positions of backbone atoms of the user-provided query structure and of stored RNA motifs, without relying on sequence or secondary structure information. This enables the identification of local structural similarities among evolutionarily related and unrelated RNA molecules. Besides, the search utility enables searching 'RNA bricks' according to sequence similarity, and makes it possible to identify motifs with modified ribonucleotide residues at specific positions.
| S-EPMC3965019 | biostudies-literature
Project description:BackgroundCellular functions are regulated by complex webs of interactions that might be schematically represented as networks. Two major examples are transcriptional regulatory networks, describing the interactions among transcription factors and their targets, and protein-protein interaction networks. Some patterns, dubbed motifs, have been found to be statistically over-represented when biological networks are compared to randomized versions thereof. Their function in vitro has been analyzed both experimentally and theoretically, but their functional role in vivo, that is, within the full network, and the resulting evolutionary pressures remain largely to be examined.ResultsWe investigated an integrated network of the yeast Saccharomyces cerevisiae comprising transcriptional and protein-protein interaction data. A comparative analysis was performed with respect to Candida glabrata, Kluyveromyces lactis, Debaryomyces hansenii and Yarrowia lipolytica, which belong to the same class of hemiascomycetes as S. cerevisiae but span a broad evolutionary range. Phylogenetic profiles of genes within different forms of the motifs show that they are not subject to any particular evolutionary pressure to preserve the corresponding interaction patterns. The functional role in vivo of the motifs was examined for those instances where enough biological information is available. In each case, the regulatory processes for the biological function under consideration were found to hinge on post-transcriptional regulatory mechanisms, rather than on the transcriptional regulation by network motifs.ConclusionThe overabundance of the network motifs does not have any immediate functional or evolutionary counterpart. A likely reason is that motifs within the networks are not isolated, that is, they strongly aggregate and have important edge and/or node sharing with the rest of the network.
| S-EPMC1088963 | biostudies-literature
Project description:Epithelial-mesenchymal transition (EMT) plays an important role in the development of hepatitis B virus (HBV)-related hepatocellular carcinoma (HCC). We hypothesized that germline variants in the major EMT regulatory genes (SNAIL1, ZEB1, ZEB2, TWIST1) may influence the development of HBV-related HCC. We included 421 cases of HBsAg-positive patients with HCC, 1371 cases of HBsAg-positive subjects without HCC [patients with chronic hepatitis B (CHB) or liver cirrhosis (LC)] and 618 cases of healthy controls in the case-control study. Genotype, allele, and haplotype associations in the major EMT regulatory genes were tested. Environment-gene and gene-gene interactions were analysed using the non-parametric model-free multifactor dimensionality reduction (MDR) method. The SNAIL1rs4647958T>C was associated with a significantly increased risk of both HCC (CT+CC vs. TT: OR=1.559; 95% confidence interval [CI], 1.073-2.264; P=0.020) and CHB+LC (CT+CC vs. TT: OR=1.509; 95% CI, 1.145-1.988; P=0.003). Carriers of the TWIST1rs2285681G>C (genotypes CT+CC) had an increased risk of HCC (CG+CC vs. GG: OR=1.407; 95% CI, 1.065-1.858; P=0.016). The ZEB2rs3806475T>C was associated with significantly increased risk of both HCC (P recessive =0.001) and CHB+LC (P recessive<0.001). The CG haplotype of the rs4647958/rs1543442 haplotype block was associated with significant differences between healthy subjects and HCC patients (P=0.0347). Meanwhile, the CT haplotype of the rs2285681/rs2285682 haplotype block was associated with significant differences between CHB+LC and HCC patients (P=0.0123). In MDR analysis, the combination of TWIST1rs2285681, ZEB2rs3806475, SNAIL1rs4647958 exhibited the most significant association with CHB+LC and Health control in the three-locus model. Our results suggest significant single-gene associations and environment-gene/gene-gene interactions of EMT-related genes with HBV-related HCC.
| S-EPMC8226114 | biostudies-literature
Project description:Elucidating the role of 3D architecture of DNA in gene regulation is crucial for understanding cell differentiation, tissue homeostasis and disease development. Among various chromatin conformation capture methods, HiChIP has received increasing attention for its significant improvement over other methods in profiling of regulatory (e.g. H3K27ac) and structural (e.g. cohesin) interactions. To facilitate the studies of 3D regulatory interactions, we developed a HiChIP interactions database, HiChIPdb (http://health.tsinghua.edu.cn/hichipdb/). The current version of HiChIPdb contains ∼262M annotated HiChIP interactions from 200 high-throughput HiChIP samples across 108 cell types. The functionalities of HiChIPdb include: (i) standardized categorization of HiChIP interactions in a hierarchical structure based on organ, tissue and cell line and (ii) comprehensive annotations of HiChIP interactions with regulatory genes and GWAS Catalog SNPs. To the best of our knowledge, HiChIPdb is the first comprehensive database that utilizes a unified pipeline to map the functional interactions across diverse cell types and tissues in different resolutions. We believe this database has the potential to advance cutting-edge research in regulatory mechanisms in development and disease by removing the barrier in data aggregation, preprocessing, and analysis.
| S-EPMC9825415 | biostudies-literature
Project description:Linear motifs (LMs), used by a subset of all protein-protein interactions (PPIs), bind to globular receptors or domains and play an important role in signaling networks. LMPID (Linear Motif mediated Protein Interaction Database) is a manually curated database which provides comprehensive experimentally validated information about the LMs mediating PPIs from all organisms on a single platform. About 2200 entries have been compiled by detailed manual curation of PubMed abstracts, of which about 1000 LM entries were being annotated for the first time, as compared with the Eukaryotic LM resource. The users can submit their query through a user-friendly search page and browse the data in the alphabetical order of the bait gene names and according to the domains interacting with the LM. LMPID is freely accessible at http://bicresources.jcbose. ac.in/ssaha4/lmpid and contains 1750 unique LM instances found within 1181 baits interacting with 552 prey proteins. In summary, LMPID is an attempt to enrich the existing repertoire of resources available for studying the LMs implicated in PPIs and may help in understanding the patterns of LMs binding to a specific domain and develop prediction model to identify novel LMs specific to a domain and further able to predict inhibitors/modulators of PPI of interest.
| S-EPMC4360622 | biostudies-literature
Project description:The reconstruction of transcriptional regulatory networks (TRNs) is a long-standing challenge in human genetics. Numerous computational methods have been developed to infer regulatory interactions between human transcriptional factors (TFs) and target genes from high-throughput data, and their performance evaluation requires gold-standard interactions. Here we present a database of literature-curated human TF-target interactions, TRRUST (transcriptional regulatory relationships unravelled by sentence-based text-mining, http://www.grnpedia.org/trrust), which currently contains 8,015 interactions between 748 TF genes and 1,975 non-TF genes. A sentence-based text-mining approach was employed for efficient manual curation of regulatory interactions from approximately 20 million Medline abstracts. To the best of our knowledge, TRRUST is the largest publicly available database of literature-curated human TF-target interactions to date. TRRUST also has several useful features: i) information about the mode-of-regulation; ii) tests for target modularity of a query TF; iii) tests for TF cooperativity of a query target; iv) inferences about cooperating TFs of a query TF; and v) prioritizing associated pathways and diseases with a query TF. We observed high enrichment of TF-target pairs in TRRUST for top-scored interactions inferred from high-throughput data, which suggests that TRRUST provides a reliable benchmark for the computational reconstruction of human TRNs.
| S-EPMC4464350 | biostudies-literature
Project description:The hematopoietic system is a distributed tissue that consists of functionally distinct cell types continuously produced through hematopoietic stem cell (HSC) differentiation. Combining genomic and phenotypic data with high-content experiments, we have built a directional cell-cell communication network between 12 cell types isolated from human umbilical cord blood. Network structure analysis revealed that ligand production is cell type dependent, whereas ligand binding is promiscuous. Consequently, additional control strategies such as cell frequency modulation and compartmentalization were needed to achieve specificity in HSC fate regulation. Incorporating the in vitro effects (quiescence, self-renewal, proliferation, or differentiation) of 27 HSC binding ligands into the topology of the cell-cell communication network allowed coding of cell type-dependent feedback regulation of HSC fate. Pathway enrichment analysis identified intracellular regulatory motifs enriched in these cell type- and ligand-coupled responses. This study uncovers cellular mechanisms of hematopoietic cell feedback in HSC fate regulation, provides insight into the design principles of the human hematopoietic system, and serves as a foundation for the analysis of intercellular regulation in multicellular systems.
| S-EPMC4299490 | biostudies-literature
Project description:The Epithelial to Mesenchymal Transition (EMT) regulates cell plasticity during embryonic development and in disease. It is dynamically orchestrated by transcription factors (EMT-TFs), including Snail, Zeb, Twist and Prrx, all activated by TGF-β among other signals. Here we find that Snail1 and Prrx1, which respectively associate with gain or loss of stem-like properties and with bad or good prognosis in cancer patients, are expressed in complementary patterns during vertebrate development and in cancer. We show that this complementarity is established through a feedback loop in which Snail1 directly represses Prrx1, and Prrx1, through direct activation of the miR-15 family, attenuates the expression of Snail1. We also describe how this gene regulatory network can establish a hierarchical temporal expression of Snail1 and Prrx1 during EMT and validate its existence in vitro and in vivo, providing a mechanism to switch and select different EMT programs with important implications in development and disease.
| S-EPMC6848104 | biostudies-literature