scholarly journals CMTCN: a web tool for investigating cancer-specific microRNA and transcription factor co-regulatory networks

PeerJ ◽  
2018 ◽  
Vol 6 ◽  
pp. e5951 ◽  
Author(s):  
Ruijiang Li ◽  
Hebing Chen ◽  
Shuai Jiang ◽  
Wanying Li ◽  
Hao Li ◽  
...  
Keyword(s):  
Regulatory Networks ◽  
Target Genes ◽  
Gene Expression Regulation ◽  
Mirna Gene ◽  
Web Tool ◽  
Cancer Types ◽  
Regulatory Analysis ◽  
Tf Gene ◽  
User Friendly ◽  
Functional Analyses

Transcription factors (TFs) and microRNAs (miRNAs) are well-characterized trans-acting essential players in gene expression regulation. Growing evidence indicates that TFs and miRNAs can work cooperatively, and their dysregulation has been associated with many diseases including cancer. A unified picture of regulatory interactions of these regulators and their joint target genes would shed light on cancer studies. Although online resources developed to support probing of TF-gene and miRNA-gene interactions are available, online applications for miRNA-TF co-regulatory analysis, especially with a focus on cancers, are lacking. In light of this, we developed a web tool, namely CMTCN (freely available at http://www.cbportal.org/CMTCN), which constructs miRNA-TF co-regulatory networks and conducts comprehensive analyses within the context of particular cancer types. With its user-friendly provision of topological and functional analyses, CMTCN promises to be a reliable and indispensable web tool for biomedical studies.

scholarly journals HAHmiR.DB: A Server Platform For High Altitude Human miRNA-Gene Coregulatory Networks And Associated Regulatory-Circuits

2020 ◽  
Author(s):  
Apoorv Gupta ◽  
Ragumani Sugadev ◽  
Yogendra Kumar Sharma ◽  
Bhuvnesh Kumar ◽  
Pankaj Khurana
Keyword(s):  
Gene Expression ◽  
High Altitude ◽  
Regulatory Networks ◽  
Gene Expression Regulation ◽  
Mirna Gene ◽  
Adaptive Responses ◽  
Specific Expression ◽  
Regulatory Circuits ◽  
Rapid Ascent ◽  
Tf Gene

AbstractRapid ascent to High Altitude (HA) can cause severe damage to body organs and may lead to many fatal disorders. During induction to HA, human body undergoes various physiological, biochemical, hematological and molecular changes to adapt to the extreme environmental conditions. Many literature references hint that gene-expression-regulation and regulatory molecules like microRNAs (miRNAs) and Transcription Factors (TFs) control adaptive responses during HA-stress. These biomolecules are known to interact in a complex combinatorial manner to fine-tune the gene expression and help in controlling the molecular responses during this stress and ultimately help in acclimatization. HAHmiR.DB (High-Altitude Human miRNA Database) is a unique, comprehensive, curated collection of miRNAs that have been experimentally validated to be associated with HA-stress; their level of expression in different altitudes, fold change, experiment duration, biomarker association, disease and drug association, tissue-specific expression level, Gene Ontology (GO) and Kyoto Encyclopaedia of Gene and Genomes (KEGG) pathway associations. As a server platform it also uniquely constructs and analyses interactive miRNA-TF-Gene coregulatory networks and extracts regulatory-circuits/Feed Forward Loops (FFLs) using in-house scripts. These regulatory circuits help to offer mechanistic insights in complex regulatory mechanisms during HA stress. The server can also build these regulatory networks between two and more miRNAs of the database and also identify the regulatory-circuits from this network. Hence HAHmiR.DB is the first-of its-kind database in HA research which a reliable platform to explore, compare, analyse and retrieve miRNAs associated with HA stress, their coregulatory networks and FFL regulatory circuits. HAHmiR.DB is freely accessible at http://www.hahmirdb.in

scholarly journals HAHmiR.DB: a server platform for high-altitude human miRNA–gene coregulatory networks and associated regulatory circuits

Database ◽  
2020 ◽  
Vol 2020 ◽  
Author(s):  
Pankaj Khurana ◽  
Apoorv Gupta ◽  
Ragumani Sugadev ◽  
Yogendra Kumar Sharma ◽  
Bhuvnesh Kumar
Keyword(s):  
Gene Expression ◽  
High Altitude ◽  
Regulatory Networks ◽  
Gene Expression Regulation ◽  
Mirna Gene ◽  
The Body ◽  
Adaptive Responses ◽  
Specific Expression ◽  
Regulatory Circuits ◽  
Tf Gene

Abstract Around 140 million people live in high-altitude (HA) conditions! and even a larger number visit such places for tourism, adventure-seeking or sports training. Rapid ascent to HA can cause severe damage to the body organs and may lead to many fatal disorders. During induction to HA, human body undergoes various physiological, biochemical, hematological and molecular changes to adapt to the extreme environmental conditions. Several literature references hint that gene-expression-regulation and regulatory molecules like miRNAs and transcription factors (TFs) control adaptive responses during HA stress. These biomolecules are known to interact in a complex combinatorial manner to fine-tune the gene expression and help in controlling the molecular responses during this stress and ultimately help in acclimatization. High-Altitude Human miRNA Database (HAHmiR.DB) is a unique, comprehensive and curated collection of miRNAs that have been experimentally validated to be associated with HA stress, their level of expression in different altitudes, fold change, experiment duration, biomarker association, disease and drug association, tissue-specific expression level, Gene Ontology (GO) and Kyoto Encyclopaedia of Gene and Genomes (KEGG) pathway associations. As a server platform, it also uniquely constructs and analyses interactive miRNA–TF–gene coregulatory networks and extracts regulatory circuits/feed-forward loops (FFLs). These regulatory circuits help to offer mechanistic insights into complex regulatory mechanisms during HA stress. The server can also build these regulatory networks between two and more miRNAs of the database and also identify the regulatory circuits from this network. Hence, HAHmiR.DB is the first-of-its-kind database in HA research, which is a reliable platform to explore, compare, analyse and retrieve miRNAs associated with HA stress, their coregulatory networks and FFL regulatory-circuits. HAHmiR.DB is freely accessible at http://www.hahmirdb.in

scholarly journals Systematic characterization of somatic mutation-mediated microRNA regulatory network perturbations

2020 ◽  
Author(s):  
Xu Hua ◽  
Yongsheng Li ◽  
Li Guo ◽  
Min Xu ◽  
Dan Qi ◽  
...  
Keyword(s):  
Cancer Progression ◽  
Regulatory Networks ◽  
Target Genes ◽  
Rna Binding ◽  
Mirna Gene ◽  
Driver Mutations ◽  
Therapeutic Drug ◽  
Driver Gene ◽  
Linear Regression Method ◽  
Cancer Types

AbstractSomatic mutations are a major source of cancer development. Many driver mutations have been identified in protein coding regions. However, the function of mutations located in microRNAs (miRNAs) and their target binding sites along the human genome remains largely unknown. Here, we built comprehensive cancer-specific miRNA regulatory networks across 30 cancer types to systematically analyze the effect of mutations on miRNA related pathways. 3,518,261 mutations from 9,819 samples were mapped to miRNA-gene interactions (mGI), and mutations in miRNAs versus in their target genes show a mutually exclusive pattern in almost all cancer types. Using a linear regression method, we further identified 89 driver mutations in 14 cancer types that can significantly perturb miRNA regulatory networks. We find that driver mutations play their roles by altering RNA binding energy and the expression of target genes. Finally, we demonstrate that mutated driver gene targets are significantly down-regulated in cancer and function as tumor suppressors during cancer progression, suggesting potential miRNA candidates with significant clinical implications. We provide this data resource (CanVar-mGI) through a user-friendly, open-access web portal. Together, our results will facilitate novel non-coding biomarker identification and therapeutic drug design.

scholarly journals hTFtarget: a comprehensive database for regulations of human transcription factors and their targets

2019 ◽  
Author(s):  
Qiong Zhang
Keyword(s):  
Gene Expression ◽  
Transcription Factors ◽  
Dna Sequences ◽  
Chromatin Immunoprecipitation ◽  
Target Genes ◽  
Gene Expression Regulation ◽  
Epigenetic Modification ◽  
Wide Range ◽  
Chromatin Immunoprecipitation Sequencing ◽  
User Friendly

Transcription factors (TFs) as key regulators play crucial roles in biological processes. The identification of TF-target regulatory relationships is a key step for revealing functions of TFs and their regulations on gene expression. The accumulated data of Chromatin immunoprecipitation sequencing (ChIP-Seq) provides great opportunities to discover the TF-target regulations across different conditions. In this study, we constructed a database named hTFtarget, which integrated huge human TF target resources (7,190 ChIP-Seq samples of 659 TFs and high confident TF binding sites of 699 TFs) and epigenetic modification information to predict accurate TF-target regulations. hTFtarget offers the following functions for users to explore TF-target regulations: 1) Browse or search general targets of a query TF across datasets; 2) Browse TF-target regulations for a query TF in a specific dataset or tissue; 3) Search potential TFs for a given target gene or ncRNA; 4) Investigate co-association between TFs in cell lines; 5) Explore potential co-regulations for given target genes or TFs; 6) Predict candidate TFBSs on given DNA sequences; 7) View ChIP-Seq peaks for different TFs and conditions in genome browser. hTFtarget provides a comprehensive, reliable and user-friendly resource for exploring human TF-target regulations, which will be very useful for a wide range of users in the TF and gene expression regulation community. hTFtarget is available at http://bioinfo.life.hust.edu.cn/hTFtarget.

scholarly journals Randomization Strategies Affect Motif Significance Analysis in TF-miRNA-Gene Regulatory Networks

2017 ◽  
Vol 14 (2) ◽  
Author(s):  
Sepideh Sadegh ◽  
Maryam Nazarieh ◽  
Christian Spaniol ◽  
Volkhard Helms
Keyword(s):  
Transcription Factors ◽  
Gene Regulatory Networks ◽  
Degree Distribution ◽  
Regulatory Networks ◽  
Target Genes ◽  
Mirna Gene ◽  
Biological Cells ◽  
Significance Analysis ◽  
Gene Regulatory ◽  
Randomized Networks

AbstractGene-regulatory networks are an abstract way of capturing the regulatory connectivity between transcription factors, microRNAs, and target genes in biological cells. Here, we address the problem of identifying enriched co-regulatory three-node motifs that are found significantly more often in real network than in randomized networks. First, we compare two randomization strategies, that either only conserve the degree distribution of the nodes’ in- and out-links, or that also conserve the degree distributions of different regulatory edge types. Then, we address the issue how convergence of randomization can be measured. We show that after at most 10 × |E| edge swappings, converged motif counts are obtained and the memory of initial edge identities is lost.

scholarly journals Critical microRNAs and regulatory motifs in cleft palate identified by a conserved miRNA–TF–gene network approach in humans and mice

2019 ◽  
Vol 21 (4) ◽  
pp. 1465-1478 ◽  
Author(s):  
Aimin Li ◽  
Peilin Jia ◽  
Saurav Mallik ◽  
Rong Fei ◽  
Hiroki Yoshioka ◽  
...  
Keyword(s):  
Cleft Palate ◽  
Regulatory Networks ◽  
Target Genes ◽  
Regulatory Mechanisms ◽  
Network Approach ◽  
Regulatory Motifs ◽  
Gene Regulatory ◽  
Regulatory Loop ◽  
Tf Gene ◽  
Human And Mouse

Abstract Cleft palate (CP) is the second most common congenital birth defect. The etiology of CP is complicated, with involvement of various genetic and environmental factors. To investigate the gene regulatory mechanisms, we designed a powerful regulatory analytical approach to identify the conserved regulatory networks in humans and mice, from which we identified critical microRNAs (miRNAs), target genes and regulatory motifs (miRNA–TF–gene) related to CP. Using our manually curated genes and miRNAs with evidence in CP in humans and mice, we constructed miRNA and transcription factor (TF) co-regulation networks for both humans and mice. A consensus regulatory loop (miR17/miR20a–FOXE1–PDGFRA) and eight miRNAs (miR-140, miR-17, miR-18a, miR-19a, miR-19b, miR-20a, miR-451a and miR-92a) were discovered in both humans and mice. The role of miR-140, which had the strongest association with CP, was investigated in both human and mouse palate cells. The overexpression of miR-140-5p, but not miR-140-3p, significantly inhibited cell proliferation. We further examined whether miR-140 overexpression could suppress the expression of its predicted target genes (BMP2, FGF9, PAX9 and PDGFRA). Our results indicated that miR-140-5p overexpression suppressed the expression of BMP2 and FGF9 in cultured human palate cells and Fgf9 and Pdgfra in cultured mouse palate cells. In summary, our conserved miRNA–TF–gene regulatory network approach is effective in detecting consensus miRNAs, motifs, and regulatory mechanisms in human and mouse CP.

FFLtool: a web server for transcription factor and miRNA feed forward loop analysis in human

2019 ◽  
Vol 36 (8) ◽  
pp. 2605-2607 ◽  
Author(s):  
Gui-Yan Xie ◽  
Mengxuan Xia ◽  
Ya-Ru Miao ◽  
Mei Luo ◽  
Qiong Zhang ◽  
...  
Keyword(s):  
Regulatory Networks ◽  
Mirna Target ◽  
Target Genes ◽  
Gene Expression Regulation ◽  
Web Server ◽  
Supplementary Information ◽  
Mechanism Study ◽  
Loop Analysis ◽  
Feed Forward ◽  
Feed Forward Loop

Abstract Summary Transcription factors (TFs) and microRNAs (miRNAs) are two kinds of important regulators for transcriptional and post-transcriptional regulations. Understanding cross-talks between the two regulators and their targets is critical to reveal complex molecular regulatory mechanisms. Here, we developed FFLtool, a web server for detecting potential feed forward loop (FFL) of TF-miRNA-target regulation in human. In FFLtool, we integrated comprehensive regulations of TF-target and miRNA-target, and developed two functional modules: (i) The ‘FFL Analysis’ module can detect potential FFLs and internal regulatory networks in a user-defined gene set. FFLtool also provides three levels of evidence to illustrate the reliability for each FFL and enrichment functions for co-target genes of the same TF and miRNA; (ii) The ‘Browse FFLs’ module displays FFLs comprised of differentially or specifically expressed TFs and miRNAs and their target genes in cancers. FFLtool is a valuable resource for investigating gene expression regulation and mechanism study in biological processes and diseases. Availability and implementation FFLtool is available on http://bioinfo.life.hust.edu.cn/FFLtool/. Supplementary information Supplementary data are available at Bioinformatics online.

scholarly journals SEanalysis: a web tool for super-enhancer associated regulatory analysis

2019 ◽  
Vol 47 (W1) ◽  
pp. W248-W255 ◽  
Author(s):  
Feng-Cui Qian ◽  
Xue-Cang Li ◽  
Jin-Cheng Guo ◽  
Jian-Mei Zhao ◽  
Yan-Yu Li ◽  
...  
Keyword(s):  
Regulatory Networks ◽  
Sequence Motifs ◽  
Web Tool ◽  
Form Complex ◽  
Network Analyses ◽  
Super Enhancer ◽  
Transcriptional Regulatory ◽  
Regulatory Analysis ◽  
Or Genes ◽  
Binding Sequence

Abstract Super-enhancers (SEs) have prominent roles in biological and pathological processes through their unique transcriptional regulatory capability. To date, several SE databases have been developed by us and others. However, these existing databases do not provide downstream or upstream regulatory analyses of SEs. Pathways, transcription factors (TFs), SEs, and SE-associated genes form complex regulatory networks. Therefore, we designed a novel web server, SEanalysis, which provides comprehensive SE-associated regulatory network analyses. SEanalysis characterizes SE-associated genes, TFs binding to target SEs, and their upstream pathways. The current version of SEanalysis contains more than 330 000 SEs from more than 540 types of cells/tissues, 5042 TF ChIP-seq data generated from these cells/tissues, DNA-binding sequence motifs for ∼700 human TFs and 2880 pathways from 10 databases. SEanalysis supports searching by either SEs, samples, TFs, pathways or genes. The complex regulatory networks formed by these factors can be interactively visualized. In addition, we developed a customizable genome browser containing >6000 customizable tracks for visualization. The server is freely available at http://licpathway.net/SEanalysis.

scholarly journals Identification and Insilico Analysis of Retinoblastoma Serum microRNA Profile and Gene Targets towards Prediction of Novel Serum Biomarkers

2013 ◽  
Vol 7 ◽  
pp. BBI.S10501 ◽  
Author(s):  
Madhu Beta ◽  
Nalini Venkatesan ◽  
Madavan Vasudevan ◽  
Umashankar Vetrivel ◽  
Vikas Khetan ◽  
...  
Keyword(s):  
Regulatory Networks ◽  
Target Genes ◽  
Mirna Gene ◽  
Target Prediction ◽  
Fold Change ◽  
Serum Samples ◽  
Gene Target ◽  
Qrt Pcr ◽  
Serum Microrna ◽  
Oncogenic Mirnas

Retinoblastoma (RB) is a malignant tumor of the retina seen in children, and potential non invasive biomarkers are in need for rapid diagnosis and for prognosticating the therapy. This study was undertaken to identify the differentially expressed miRNAs in the serum of children with RB in comparison with the normal age matched serum, to analyze its concurrence with the existing RB tumor miRNA profile, to identify its novel gene targets specific to RB, and to study the expression of a few of the identified oncogenic miRNAs in the advanced stage primary RB patient's serum sample. MiRNA profiling was performed on 14 pooled serum from children with advanced RB and 14 normal age matched serum samples, wherein 21 miRNAs were found to be upregulated (fold change ≥ +2.0, P ≤ 0.05) and 24 to be downregulated (fold change ≤ –2.0, P ≤ 0.05). Furthermore, intersection of 59 significantly deregulated miRNAs identified from RB tumor profiles with that of miRNAs detected in serum profile revealed that 33 miRNAs had followed a similar deregulation pattern in RB serum. Later we validated a few of the miRNAs (miRNA 17-92) identified by microarray in the RB patient serum samples (n = 20) by using qRT-PCR. Expression of the oncogenic miRNAs, miR-17, miR-18a, and miR-20a by qRT-PCR was significant in the serum samples exploring the potential of serum miRNAs identification as noninvasive diagnosis. Moreover, from miRNA gene target prediction, key regulatory genes of cell proliferation, apoptosis, and positive and negative regulatory networks involved in RB progression were identified in the gene expression profile of RB tumors. Therefore, these identified miRNAs and their corresponding target genes could give insights on potential biomarkers and key events involved in the RB pathway.

scholarly journals NRF2-ome: An Integrated Web Resource to Discover Protein Interaction and Regulatory Networks of NRF2

2013 ◽  
Vol 2013 ◽  
pp. 1-9 ◽  
Author(s):  
Dénes Türei ◽  
Diána Papp ◽  
Dávid Fazekas ◽  
László Földvári-Nagy ◽  
Dezső Módos ◽  
...  
Keyword(s):  
Stress Responses ◽  
Regulatory Networks ◽  
Target Genes ◽  
Evaluation Tool ◽  
Xenobiotic Stress ◽  
Web Resource ◽  
File Formats ◽  
Online Resource ◽  
User Friendly ◽  
Signaling Interactions

NRF2 is the master transcriptional regulator of oxidative and xenobiotic stress responses. NRF2 has important roles in carcinogenesis, inflammation, and neurodegenerative diseases. We developed an online resource, NRF2-ome, to provide an integrated and systems-level database for NRF2. The database contains manually curated and predicted interactions of NRF2 as well as data from external interaction databases. We integrated NRF2 interactome with NRF2 target genes, NRF2 regulating TFs, and miRNAs. We connected NRF2-ome to signaling pathways to allow mapping upstream NRF2 regulatory components that could directly or indirectly influence NRF2 activity totaling 35,967 protein-protein and signaling interactions. The user-friendly website allows researchers without computational background to search, browse, and download the database. The database can be downloaded in SQL, CSV, BioPAX, SBML, PSI-MI, and in a Cytoscape CYS file formats. We illustrated the applicability of the website by suggesting a posttranscriptional negative feedback of NRF2 by MAFG protein and raised the possibility of a connection between NRF2 and the JAK/STAT pathway through STAT1 and STAT3. NRF2-ome can also be used as an evaluation tool to help researchers and drug developers to understand the hidden regulatory mechanisms in the complex network of NRF2.

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