scholarly journals Three topological features of regulatory networks control life-essential and specialized subsystems

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Ivan Rodrigo Wolf ◽  
Rafael Plana Simões ◽  
Guilherme Targino Valente
Keyword(s):  
Regulatory Networks ◽  
High Probability ◽  
Target Genes ◽  
Evolutionary Process ◽  
Signal Propagation ◽  
Classification Model ◽  
Page Rank ◽  
Topological Features ◽  
Regulatory Systems ◽  
Low K

AbstractGene regulatory networks (GRNs) play key roles in development, phenotype plasticity, and evolution. Although graph theory has been used to explore GRNs, associations amongst topological features, transcription factors (TFs), and systems essentiality are poorly understood. Here we sought the relationship amongst the main GRN topological features that influence the control of essential and specific subsystems. We found that the Knn, page rank, and degree are the most relevant GRN features: the ones are conserved along the evolution and are also relevant in pluripotent cells. Interestingly, life-essential subsystems are governed mainly by TFs with intermediary Knn and high page rank or degree, whereas specialized subsystems are mainly regulated by TFs with low Knn. Hence, we suggest that the high probability of TFs be toured by a random signal, and the high probability of the signal propagation to target genes ensures the life-essential subsystems’ robustness. Gene/genome duplication is the main evolutionary process to rise Knn as the most relevant feature. Herein, we shed light on unexplored topological GRN features to assess how they are related to subsystems and how the duplications shaped the regulatory systems along the evolution. The classification model generated can be found here: https://github.com/ivanrwolf/NoC/.

scholarly journals Learning about Gene Regulatory Networks from Gene Deletion Experiments

2002 ◽  
Vol 3 (6) ◽  
pp. 499-503 ◽  
Author(s):  
Thomas Schlitt ◽  
Alvis Brazma
Keyword(s):  
Gene Regulatory Networks ◽  
Regulatory Networks ◽  
Gene Deletion ◽  
Deletion Mutants ◽  
Major Focus ◽  
Indirect Approach ◽  
Microarray Experiments ◽  
Topological Features ◽  
Regulatory Systems ◽  
Gene Regulatory

Gene regulatory networks are a major focus of interest in molecular biology. A crucial question is how complex regulatory systems are encoded and controlled by the genome. Three recent publications have raised the question of what can be learned about gene regulatory networks from microarray experiments on gene deletion mutants. Using this indirect approach, topological features such as connectivity and modularity have been studied.

scholarly journals Evolution Analyses of CAMTA Transcription Factor in Plants and Its Enhancing Effect on Cold-tolerance

2021 ◽  
Vol 12 ◽  
Author(s):  
Peixuan Xiao ◽  
Jia-Wu Feng ◽  
Xi-Tong Zhu ◽  
Junxiang Gao
Keyword(s):  
Transcription Factor ◽  
Cold Tolerance ◽  
Regulatory Networks ◽  
Target Genes ◽  
Higher Plants ◽  
Expression Patterns ◽  
Evolutionary Process ◽  
Functional Differentiation ◽  
Transcription Activator ◽  
Structure Variation

The calmodulin binding transcription activator (CAMTA) is a transcription factor that is widely present in eukaryotes with conserved structure. It contributes to the response to biotic and abiotic stresses and promotes the growth and development of plants. Although previous studies have investigated the number and function of CAMTAs in some species, there is still a lack of comprehensive understanding of the evolutionary process, phylogenetic relationship, expression patterns, and functions of CAMTAs in plants. Here we identified 465 CMATA genes from 112 plants and systematically studied the origin of CAMTA family, gene expansion, functional differentiation, gene structure, and conservative motif distribution. Based on these analyses, we presented the evidence that CAMTA family was originated from chlorophyta, and we speculated that CAMTA might experience obvious structure variation during its early evolution, and that the number of CAMTA genes might gradually increase in higher plants. To reveal potential functions of CAMTA genes, we analyzed the expression patterns of 12 representative species and found significant species specificity, tissue specificity, and developmental stage specificity of CAMTAs. The results also indicated that the CAMTA genes might promote the maturation and senescence. The expression levels and regulatory networks of CAMTAs revealed that CAMTAs could enhance cold tolerance of rice by regulating carbohydrate metabolism-related genes to accumulate carbohydrates or by modulating target genes together with other transcription factors. Our study provides an insight into the molecular evolution of CAMTA family and lays a foundation for further study of related biological functions.

scholarly journals EPEN-21. IMPAIRED NEURONAL-GLIAL FATE SPECIFICATION IN PEDIATRIC EPENDYMOMA REVEALED BY SINGLE-CELL RNA-SEQ

2020 ◽  
Vol 22 (Supplement_3) ◽  
pp. iii311-iii312
Author(s):  
Bernhard Englinger ◽  
Johannes Gojo ◽  
Li Jiang ◽  
Jens M Hübner ◽  
McKenzie L Shaw ◽  
...  
Keyword(s):  
Dna Methylation ◽  
Single Cell ◽  
Regulatory Networks ◽  
Target Genes ◽  
Target Identification ◽  
Rna Seq ◽  
Cell Models ◽  
Pediatric Ependymoma ◽  
Glial Fate ◽  
Anatomic Locations

Abstract Ependymoma represents a heterogeneous disease affecting the entire neuraxis. Extensive molecular profiling efforts have identified molecular ependymoma subgroups based on DNA methylation. However, the intratumoral heterogeneity and developmental origins of these groups are only partially understood, and effective treatments are still lacking for about 50% of patients with high-risk tumors. We interrogated the cellular architecture of ependymoma using single cell/nucleus RNA-sequencing to analyze 24 tumor specimens across major molecular subgroups and anatomic locations. We additionally analyzed ten patient-derived ependymoma cell models and two patient-derived xenografts (PDXs). Interestingly, we identified an analogous cellular hierarchy across all ependymoma groups, originating from undifferentiated neural stem cell-like populations towards different degrees of impaired differentiation states comprising neuronal precursor-like, astro-glial-like, and ependymal-like tumor cells. While prognostically favorable ependymoma groups predominantly harbored differentiated cell populations, aggressive groups were enriched for undifferentiated subpopulations. Projection of transcriptomic signatures onto an independent bulk RNA-seq cohort stratified patient survival even within known molecular groups, thus refining the prognostic power of DNA methylation-based profiling. Furthermore, we identified novel potentially druggable targets including IGF- and FGF-signaling within poorly prognostic transcriptional programs. Ependymoma-derived cell models/PDXs widely recapitulated the transcriptional programs identified within fresh tumors and are leveraged to validate identified target genes in functional follow-up analyses. Taken together, our analyses reveal a developmental hierarchy and transcriptomic context underlying the biologically and clinically distinct behavior of ependymoma groups. The newly characterized cellular states and underlying regulatory networks could serve as basis for future therapeutic target identification and reveal biomarkers for clinical trials.

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 G1 arrest and differentiation can occur independently of Rb family function

2010 ◽  
Vol 191 (4) ◽  
pp. 809-825 ◽  
Author(s):  
Stacey E. Wirt ◽  
Adam S. Adler ◽  
Véronique Gebala ◽  
James M. Weimann ◽  
Bethany E. Schaffer ◽  
...  
Keyword(s):  
Cell Cycle ◽  
Mammalian Cells ◽  
Regulatory Networks ◽  
Target Genes ◽  
Family Members ◽  
Mouse Embryos ◽  
G1 Arrest ◽  
Cell Cycle Exit ◽  
Family Function ◽  
Rb Pathway

The ability of progenitor cells to exit the cell cycle is essential for proper embryonic development and homeostasis, but the mechanisms governing cell cycle exit are still not fully understood. Here, we tested the requirement for the retinoblastoma (Rb) protein and its family members p107 and p130 in G0/G1 arrest and differentiation in mammalian cells. We found that Rb family triple knockout (TKO) mouse embryos survive until days 9–11 of gestation. Strikingly, some TKO cells, including in epithelial and neural lineages, are able to exit the cell cycle in G0/G1 and differentiate in teratomas and in culture. This ability of TKO cells to arrest in G0/G1 is associated with the repression of key E2F target genes. Thus, G1 arrest is not always dependent on Rb family members, which illustrates the robustness of cell cycle regulatory networks during differentiation and allows for the identification of candidate pathways to inhibit the expansion of cancer cells with mutations in the Rb pathway.

Identification of transcription factors MYC and C/EBPβ mediated regulatory networks in heart failure based on GEO dataset

2020 ◽  
Author(s):  
Haiwei Wang ◽  
Xinrui Wang ◽  
Liangpu Xu ◽  
Hua Cao
Keyword(s):  
Heart Failure ◽  
Transcription Factors ◽  
Signaling Pathways ◽  
Signaling Pathway ◽  
Insulin Signaling ◽  
Regulatory Networks ◽  
Target Genes ◽  
Transcriptional Profiling ◽  
Insulin Signaling Pathway ◽  
Failing Heart

Abstract Background: Heart failure is one of leading cause of death worldwide. However, the transcriptional profiling of heart failure is unclear. Moreover, the signaling pathways and transcription factors involving the heart failure development also are largely unknown. Using published Gene Expression Omnibus (GEO) datasets, in the present study, we aim to comprehensively analyze the differentially expressed genes in failing heart tissues, and identified the critical signaling pathways and transcription factors involving heart failure development. Methods: The transcriptional profiling of heart failure was identified from previously published gene expression datasets deposited in GSE5406, GSE16499 and GSE68316. The enriched signaling pathways and transcription factors were analyzed using DAVID website and gene set enrichment analysis (GSEA) assay. The transcriptional networks were created by Cytoscape. Results: Compared with the normal heart tissues, 90 genes were particularly differentially expressed in failing heart tissues, and those genes were associated with multiple metabolism signaling pathways and insulin signaling pathway. Metabolism and insulin signaling pathway were both inactivated in failing heart tissues. Transcription factors MYC and C/EBPβ were both negatively associated with the expression profiling of failing heart tissues in GSEA assay. Moreover, compared with normal heart tissues, MYC and C/EBPβ were down regulated in failing heart tissues. Furthermore, MYC and C/EBPβ mediated downstream target genes were also decreased in failing heart tissues. MYC and C/EBPβ were positively correlated with each other. At last, we constructed MYC and C/EBPβ mediated regulatory networks in failing heart tissues, and identified the MYC and C/EBPβ target genes which had been reported involving the heart failure developmental progress. Conclusions: Our results suggested that metabolism pathways and insulin signaling pathway, transcription factors MYC and C/EBPβ played critical roles in heart failure developmental progress.

scholarly journals RTNduals: an R/Bioconductor package for analysis of co-regulation and inference of dual regulons

2019 ◽  
Vol 35 (24) ◽  
pp. 5357-5358
Author(s):  
Vinicius S Chagas ◽  
Clarice S Groeneveld ◽  
Kelin G Oliveira ◽  
Sheyla Trefflich ◽  
Rodrigo C de Almeida ◽  
...  
Keyword(s):  
Regulatory Networks ◽  
Target Genes ◽  
Supplementary Information ◽  
Transcriptional Networks ◽  
Bioconductor Package ◽  
Multiple Target ◽  
R Language ◽  
Downstream Effects ◽  
Bioconductor Project ◽  
General Method

Abstract Motivation Transcription factors (TFs) are key regulators of gene expression, and can activate or repress multiple target genes, forming regulatory units, or regulons. Understanding downstream effects of these regulators includes evaluating how TFs cooperate or compete within regulatory networks. Here we present RTNduals, an R/Bioconductor package that implements a general method for analyzing pairs of regulons. Results RTNduals identifies a dual regulon when the number of targets shared between a pair of regulators is statistically significant. The package extends the RTN (Reconstruction of Transcriptional Networks) package, and uses RTN transcriptional networks to identify significant co-regulatory associations between regulons. The Supplementary Information reports two case studies for TFs using the METABRIC and TCGA breast cancer cohorts. Availability and implementation RTNduals is written in the R language, and is available from the Bioconductor project at http://bioconductor.org/packages/RTNduals/. Supplementary information Supplementary data are available at Bioinformatics online.

scholarly journals Identifying genetic modulators of the connectivity between transcription factors and their transcriptional targets

2016 ◽  
Vol 113 (13) ◽  
pp. E1835-E1843 ◽  
Author(s):  
Mina Fazlollahi ◽  
Ivor Muroff ◽  
Eunjee Lee ◽  
Helen C. Causton ◽  
Harmen J. Bussemaker
Keyword(s):  
Gene Expression ◽  
Transcription Factors ◽  
Gene Regulatory Networks ◽  
Regulatory Networks ◽  
Target Genes ◽  
Regulation Of Gene Expression ◽  
Nonsynonymous Mutation ◽  
Gene Regulatory ◽  
Genetic Modulators

Regulation of gene expression by transcription factors (TFs) is highly dependent on genetic background and interactions with cofactors. Identifying specific context factors is a major challenge that requires new approaches. Here we show that exploiting natural variation is a potent strategy for probing functional interactions within gene regulatory networks. We developed an algorithm to identify genetic polymorphisms that modulate the regulatory connectivity between specific transcription factors and their target genes in vivo. As a proof of principle, we mapped connectivity quantitative trait loci (cQTLs) using parallel genotype and gene expression data for segregants from a cross between two strains of the yeast Saccharomyces cerevisiae. We identified a nonsynonymous mutation in the DIG2 gene as a cQTL for the transcription factor Ste12p and confirmed this prediction empirically. We also identified three polymorphisms in TAF13 as putative modulators of regulation by Gcn4p. Our method has potential for revealing how genetic differences among individuals influence gene regulatory networks in any organism for which gene expression and genotype data are available along with information on binding preferences for transcription factors.

scholarly journals How, with whom and when: an overview of CD147-mediated regulatory networks influencing matrix metalloproteinase activity

2016 ◽  
Vol 36 (1) ◽  
Author(s):  
G. Daniel Grass ◽  
Bryan P. Toole
Keyword(s):  
Matrix Metalloproteinase ◽  
Regulatory Networks ◽  
Protein Transport ◽  
Distant Metastases ◽  
Drug Transporter ◽  
Regulatory Systems ◽  
Membrane Bound ◽  
Membrane Type ◽  
Tumour Initiation ◽  
Metalloproteinase Activity

Matrix metalloproteinases (MMPs) comprise a family of 23 zinc-dependent enzymes involved in various pathologic and physiologic processes. In cancer, MMPs contribute to processes from tumour initiation to establishment of distant metastases. Complex signalling and protein transport networks regulate MMP synthesis, cell surface presentation and release. Earlier attempts to disrupt MMP activity in patients have proven to be intolerable and with underwhelming clinical efficacy; thus targeting ancillary proteins that regulate MMP activity may be a useful therapeutic approach. Extracellular matrix metalloproteinase inducer (EMMPRIN) was originally characterized as a factor present on lung cancer cells, which stimulated collagenase (MMP-1) production in fibroblasts. Subsequent studies demonstrated that EMMPRIN was identical with several other protein factors, including basigin (Bsg), all of which are now commonly termed CD147. CD147 modulates the synthesis and activity of soluble and membrane-bound [membrane-type MMPs (MT-MMPs)] in various contexts via homophilic/heterophilic cell interactions, vesicular shedding or cell-autonomous processes. CD147 also participates in inflammation, nutrient and drug transporter activity, microbial pathology and developmental processes. Despite the hundreds of manuscripts demonstrating CD147-mediated MMP regulation, the molecular underpinnings governing this process have not been fully elucidated. The present review summarizes our present knowledge of the complex regulatory systems influencing CD147 biology and provides a framework to understand how CD147 may influence MMP activity.

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