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 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 Gene Expression Networks in the Drosophila Genetic Reference Panel

2019 ◽  
Author(s):  
Logan J. Everett ◽  
Wen Huang ◽  
Shanshan Zhou ◽  
Mary Anna Carbone ◽  
Richard F. Lyman ◽  
...  
Keyword(s):  
Gene Expression ◽  
Transposable Elements ◽  
Dna Sequences ◽  
Quantitative Trait ◽  
Regulatory Networks ◽  
Target Genes ◽  
Reference Panel ◽  
Modern Biology ◽  
Specific Expression ◽  
Drosophila Genetic Reference Panel

SummaryA major challenge in modern biology is to understand how naturally occurring variation in DNA sequences affects complex organismal traits through networks of intermediate molecular phenotypes. Here, we performed deep RNA sequencing of 200 Drosophila Genetic Reference Panel inbred lines with complete genome sequences, and mapped expression quantitative trait loci for annotated genes, novel transcribed regions (most of which are long noncoding RNAs), transposable elements and microbial species. We identified host variants that affect expression of transposable elements, independent of their copy number, as well as microbiome composition. We constructed sex-specific expression quantitative trait locus regulatory networks. These networks are enriched for novel transcribed regions and target genes in heterochromatin and euchromatic regions of reduced recombination, and genes regulating transposable element expression. This study provides new insights regarding the role of natural genetic variation in regulating gene expression and generates testable hypotheses for future functional analyses.

scholarly journals Accurate differential analysis of transcription factor activity from gene expression

2018 ◽  
Author(s):  
Viren Amin ◽  
Murat Can Cobanoglu
Keyword(s):  
Gene Expression ◽  
Transcription Factor ◽  
Gene Regulatory Networks ◽  
Regulatory Networks ◽  
Expression Data ◽  
Differential Analysis ◽  
Gene Regulatory ◽  
Context Specific ◽  
Tf Gene ◽  
Perturbation Estimation

AbstractWe present EPEE (Effector and Perturbation Estimation Engine), a method for differential analysis of transcription factor (TF) activity from gene expression data. EPEE addresses two principal challenges in the field, namely incorporating context-specific TF-gene regulatory networks, and accounting for the fact that TF activity inference is intrinsically coupled for all TFs that share targets. Our validations in well-studied immune and cancer contexts show that addressing the overlap challenge and using state-of-the-art regulatory networks enable EPEE to consistently produce accurate results. (Accessible at: https://github.com/Cobanoglu-Lab/EPEE)

scholarly journals nSARS-Cov-2, pulmonary edema and thrombosis: possible molecular insights using miRNA-gene circuits in regulatory networks

ExRNA ◽  
2020 ◽  
Vol 2 (1) ◽  
Author(s):  
P. Khurana ◽  
A. Gupta ◽  
R. Sugadev ◽  
Y. K. Sharma ◽  
R. Varshney ◽  
...  
Keyword(s):  
Pulmonary Edema ◽  
Antigen Presentation ◽  
Signaling Pathways ◽  
Regulatory Networks ◽  
Molecular Mechanisms ◽  
Mirna Gene ◽  
Protein Stabilization ◽  
Molecular Signature ◽  
Potential Candidate ◽  
Regulatory Circuits

Abstract Background Given the worldwide spread of the novel Severe Acute Respiratory Syndrome Coronavirus 2 (nSARS-CoV-2) infection pandemic situation, research to repurpose drugs, identify novel drug targets, vaccine candidates have created a new race to curb the disease. While the molecular signature of nSARS-CoV-2 is still under investigation, growing literature shows similarity among nSARS-CoV-2, pulmonary edema, and thromboembolic disorders due to common symptomatic features. A network medicine approach is used to to explore the molecular complexity of the disease and to uncover common molecular trajectories of edema and thrombosis with nSARS-CoV-2. Results and conclusion A comprehensive nSARS-CoV-2 responsive miRNA: Transcription Factor (TF): gene co-regulatory network was built using host-responsive miRNAs and it’s associated tripartite, Feed-Forward Loops (FFLs) regulatory circuits were identified. These regulatory circuits regulate signaling pathways like virus endocytosis, viral replication, inflammatory response, pulmonary vascularization, cell cycle control, virus spike protein stabilization, antigen presentation, etc. A unique miRNA-gene regulatory circuit containing a consortium of four hub FFL motifs is proposed to regulate the virus-endocytosis and antigen-presentation signaling pathways. These regulatory circuits also suggest potential correlations/similarity in the molecular mechanisms during nSARS-CoV-2 infection, pulmonary diseases and thromboembolic disorders and thus could pave way for repurposing of drugs. Some important miRNAs and genes have also been proposed as potential candidate markers. A detailed molecular snapshot of TGF signaling as the common pathway, that could play an important role in controlling common pathophysiologies among diseases, is also put forth.

scholarly journals Single-cell RNA-sequencing reveals widespread personalized, context-specific gene expression regulation in immune cells.

2021 ◽  
Author(s):  
Roy Oelen ◽  
Dylan H. de Vries ◽  
Harm Brugge ◽  
Gracie Gordon ◽  
Martijn Vochteloo ◽  
...  
Keyword(s):  
Gene Expression ◽  
Single Cell ◽  
Lupus Erythematosus ◽  
Mononuclear Cells ◽  
Gene Expression Regulation ◽  
Specific Gene ◽  
Specific Expression ◽  
Peripheral Blood Mononuclear ◽  
Cell Type Specific Expression ◽  
Context Specific

Gene expression and its regulation can be context-dependent. To dissect this, using samples from 120 individuals, we single-cell RNA-sequenced 1.3M peripheral blood mononuclear cells exposed to three different pathogens at two time points or left unexposed. This revealed thousands of cell type-specific expression changes (eQTLs) and pathogen-induced expression changes (response QTLs) that are influenced by genetic variation. In monocytes, the strongest responder to pathogen stimulations, genetics also affected co-expression of 71.4% of these eQTL genes. For example, the pathogen recognition receptor CLEC12A showed many such co-expression interactions, but only in monocytes after 3h pathogen stimulation. Further analysis linked this to interferon-regulating transcription factors, a finding that we recapitulated in an independent cohort of patients with systemic lupus erythematosus, a condition characterized by increased interferon activity. Altogether, this study highlights the importance of context for gaining a better understanding of the mechanisms of gene regulation in health and disease.

scholarly journals Evaluating the Effect of 3′-UTR Variants in DICER1 and DROSHA on Their Tissue-Specific Expression by miRNA Target Prediction

2021 ◽  
Vol 43 (2) ◽  
pp. 605-617
Author(s):  
Dmitrii S. Bug ◽  
Artem V. Tishkov ◽  
Ivan S. Moiseev ◽  
Natalia V. Petukhova
Keyword(s):  
Gene Expression ◽  
Cancer Progression ◽  
Regulatory Networks ◽  
Mirna Target ◽  
Target Prediction ◽  
Specific Gene ◽  
Phenotypic Effect ◽  
Specific Expression ◽  
Form Complex ◽  
Tissue Specific

Untranslated gene regions (UTRs) play an important role in controlling gene expression. 3′-UTRs are primarily targeted by microRNA (miRNA) molecules that form complex gene regulatory networks. Cancer genomes are replete with non-coding mutations, many of which are connected to changes in tumor gene expression that accompany the development of cancer and are associated with resistance to therapy. Therefore, variants that occurred in 3′-UTR under cancer progression should be analysed to predict their phenotypic effect on gene expression, e.g., by evaluating their impact on miRNA target sites. Here, we analyze 3′-UTR variants in DICER1 and DROSHA genes in the context of myelodysplastic syndrome (MDS) development. The key features of this analysis include an assessment of both “canonical” and “non-canonical” types of mRNA-miRNA binding and tissue-specific profiling of miRNA interactions with wild-type and mutated genes. As a result, we obtained a list of DICER1 and DROSHA variants likely altering the miRNA sites and, therefore, potentially leading to the observed tissue-specific gene downregulation. All identified variants have low population frequency consistent with their potential association with pathology progression.

scholarly journals No Need to Stick Together to Be Connected: Multiple Types of Enhancers’ Networking

Cancers ◽  
2021 ◽  
Vol 13 (20) ◽  
pp. 5201
Author(s):  
Emanuele Vitale ◽  
Mila Gugnoni ◽  
Alessia Ciarrocchi
Keyword(s):  
Gene Expression ◽  
Gene Expression Regulation ◽  
Building Blocks ◽  
Regulatory Elements ◽  
Transcriptional Level ◽  
Independent Manner ◽  
Control Of Gene Expression ◽  
Cis Acting ◽  
Regulatory Circuits ◽  
Dna Elements

The control of gene expression at a transcriptional level requires a widespread landscape of regulatory elements. Central to these regulatory circuits are enhancers (ENHs), which are defined as cis-acting DNA elements able to increase the transcription of a target gene in a distance- and orientation-independent manner. ENHs are not independent functional elements but work in a complex and dynamic cooperative network, constituting the building blocks of multimodular domains of gene expression regulation. The information from each of these elements converges on the target promoter, contributing to improving the precision and sharpness of gene modulation. ENHs’ interplay varies in its nature and extent, ranging from an additive to redundant effect depending on contexts. Moving from super-enhancers that drive the high expression levels of identity genes, to shadow-enhancers, whose redundant functions contribute to buffering the variation in gene expression, this review aims to describe the different modalities of ENHs’ interaction and their role in the regulation of complex biological processes like cancer development.

scholarly journals Regulus, a transcriptional regulatory networks inference tool based on Semantic Web technologies

2021 ◽  
Author(s):  
Marine Louarn ◽  
Guillaume Collet ◽  
Eve Barre ◽  
Thierry Fest ◽  
Olivier Dameron ◽  
...  
Keyword(s):  
Gene Expression ◽  
Semantic Web ◽  
Regulatory Networks ◽  
Network Inference ◽  
Transcriptional Regulatory Networks ◽  
Semantic Web Technologies ◽  
Regulatory Regions ◽  
Web Technologies ◽  
Transcriptional Regulatory ◽  
Tf Gene

Motivation: Transcriptional regulation -a major field of investigation in life science- is performed by binding of specialized proteins called transcription factors (TF) to DNA in specific, context-dependent regulatory regions, leading to either activation or inhibition of gene expression. Relations between TF, regions and genes can be described as regulatory networks, which are basically knowledge graphs containing the relationships between the different entities. Current methods of transcriptional regulatory networks inference rarely use information about TF binding or regulatory regions, often require a large number of samples and most of time do not indicate if the TF-gene relation is an activation or an inhibition. The resulting networks may then contain inconsistent relations and the methods are not applicable for common experimental or clinical settings, where the number of samples is limited. Therefore, based on our previous experience of formalizing the Regulatory Circuits data-sets with Semantic Web Technologies, we decided to create a new tool for transcriptional networks inference, that could solve these issues. Results: Our tool, Regulus, provides candidate signed TF-gene relations computed from gene expressions, regulatory region activities and TF binding sites data, together with the genomic location of all entities. After creating expressions and activities patterns, data are integrated into a RDF endpoint. A dedicated SPARQL query retrieves all potential TF-region relations for a given gene expression pattern. These ternary TF-region-gene pattern relations are then filtered and signed using a logical consistency check translated from biological knowledge. Regulus compares favorably to its closest network inference method, provides signs which are consistent with public databases and, when applied to real biological data, identifies both known and potential new regulators. We also provide several means to more stringently filter the output regulators. Altogether, we propose a new tool devoted to transcriptional network inference in settings where samples are scarce and cell populations may be closely related.

scholarly journals Network Biology led identification of critical miRNA modules for High Altitude hypoxia and their potential as dietary supplements

2021 ◽  
Author(s):  
Apoorv Gupta ◽  
Sugadev R ◽  
Y K Sharma ◽  
Pankaj Khurana
Keyword(s):  
Network Analysis ◽  
High Altitude ◽  
Regulatory Networks ◽  
Sequence Similarity ◽  
Functional Module ◽  
Mammalian Species ◽  
Differentially Expressed ◽  
Mammalian Host ◽  
High Altitudes ◽  
Tf Gene

Abstract Early ascent to high altitude can cause severe damage to body functions and may lead to many fatal high-altitude disorders. To cope up with such conditions, the human body undergoes physiological and biochemical changes in order to adapt to extreme environmental conditions at high altitudes. Several microRNAs (miRNAs), Transcription Factors (TFs), and genes have been studied separately for their role in early adaptive molecular responses. We hypothesize that network analysis of miRNA-TF-gene co-regulatory networks of circulatory miRNAs (CmiRNAs) which are differentially expressed at high altitudes could reveal a complex regulatory functional module that might be controlling molecular adaptive responses at high altitude. A comprehensive and non-redundant list of differentially expressed human CmiRNAs during high altitude ascent was collated and 470 Feed-Forward Loops (FFLs) tripartite motifs were identified in the miRNA-TF-gene co-regulatory networks. Network analysis and K-means clustering identified 11 biologically overrepresented FFLs regulated by 8 miRNAs hsa-miR-335-5p, hsa-miR-26a-1-3p, hsa-miR-210-3p, hsa-miR-193b-3p, hsa-miR-17-5p, hsa-miR-16-5p, hsa-miR-5582-5p and hsa-miR-130a-3p. Pathway enrichment identified metabolism and inflammation as important hallmark responses responsible for high altitude adaptation. These miRNAs were evaluated for their supplementation from dietary sources. Phylogenetic analysis with 4 other mammalian and non-mammalian species showed that Bos taurus (cattle) milk could be a possible source of these dietary miRNAs. Exogenous miRNAs bta-mir-16-1, bta-mir-130a, bta-miR-335, and bta-miR-210 have >95% of sequence similarity and could become potential dietary miRNAs candidates. The sequence, structural properties, and high AGO2 binding efficiency of all these exogenous miRNAs show good serum stability and cellular uptake possibility in the mammalian host. Bta-miR-210 with highest Minimal Folding free Energy Index (MFEI) and highest Atomic Contact Energy (ACE) with AGO2 has the best potential to be a dietary supplement.

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