The role of master regulators in gene regulatory networks

Lemus, Enrique Hernández; López, K. Baca; Lemus, R.; García-Herrera, Rodrigo

doi:10.4279/pip.070011

Cited by 4 publications

(9 citation statements)

References 21 publications

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“…Gene regulatory network deconvolution from experimental data has been extensively used to unveil co-regulatory interactions between genes by looking out for patterns in their experimentally-measured mRNA expression levels 14,19 . Several correlation measures have been used to infer transcriptional interaction networks [30][31][32][33][34] .…”

Section: Network Constructionmentioning

confidence: 99%

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k-core genes underpin structural features of breast cancer

Dorantes-Gilardi

García-Cortés

Hernández‐Lemus

et al. 2021

Sci Rep

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Gene co-expression networks (GCNs) have been developed as relevant analytical tools for the study of the gene expression patterns behind complex phenotypes. Determining the association between structure and function in GCNs is a current challenge in biomedical research. Several structural differences between GCNs of breast cancer and healthy phenotypes have been reported. In a previous study, using co-expression multilayer networks, we have shown that there are abrupt differences in the connectivity patterns of the GCN of basal-like breast cancer between top co-expressed gene-pairs and the remaining gene-pairs. Here, we compared the top-100,000 interactions networks for the four breast cancer phenotypes (Luminal-A, Luminal-B, Her2+ and Basal), in terms of structural properties. For this purpose, we used the graph-theoretical k-core of a network (maximal sub-network with nodes of degree at least k). We developed a comprehensive analysis of the network k-core ($$k=30$$ k = 30 ) structures in cancer, and its relationship with biological functions. We found that in the Top-100,000-edges networks, the majority of interactions in breast cancer networks are intra-chromosome, meanwhile inter-chromosome interactions serve as connecting bridges between clusters. Moreover, core genes in the healthy network are strongly associated with processes such as metabolism and cell cycle. In breast cancer, only the core of Luminal A is related to those processes, and genes in its core are over-expressed. The intersection of the core nodes in all subtypes of cancer is composed only by genes in the chr8q24.3 region. This region has been observed to be highly amplified in several cancers before, and its appearance in the intersection of the four breast cancer k-cores, may suggest that local co-expression is a conserved phenomenon in cancer. Considering the many intricacies associated with these phenomena and the vast amount of research in epigenomic regulation which is currently undergoing, there is a need for further research on the epigenomic effects on the structure and function of gene co-expression networks in cancer.

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Section: Network Constructionmentioning

confidence: 99%

“…It is largely known that the maximum likelihood estimator of statistical dependency is mutual information (MI) [33][34][35][36] . For the construction of the five phenotype networks analyzed in this work, we used ARACNE 37 , an algorithm that quantifies the statistical dependence between pairs of genes.…”

Section: Network Constructionmentioning

confidence: 99%

k-core genes underpin structural features of breast cancer

Dorantes-Gilardi

García-Cortés

Hernández‐Lemus

et al. 2021

Sci Rep

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“…The high connectivity of these MRs allow them to participate in many FFL and FBL motifs and are studied to identify biomarkers for specific disease conditions, as discussed in Sec. 2.2.4 40 . Note that considerable effort has already gone into the analysis of the hierarchical structure of TRNs.…”

Section: Three Tier Topologymentioning

confidence: 99%

Motifs enable communication efficiency and fault-tolerance in transcriptional networks

Roy

Ghosh

Barua

et al. 2020

Sci Rep

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Analysis of the topology of transcriptional regulatory networks (TRNs) is an effective way to study the regulatory interactions between the transcription factors (TFs) and the target genes. TRNs are characterized by the abundance of motifs such as feed forward loops (FFLs), which contribute to their structural and functional properties. In this paper, we focus on the role of motifs (specifically, FFLs) in signal propagation in TRNs and the organization of the TRN topology with FFLs as building blocks. To this end, we classify nodes participating in FFLs (termed motif central nodes) into three distinct roles (namely, roles A, B and C), and contrast them with TRN nodes having high connectivity on the basis of their potential for information dissemination, using metrics such as network efficiency, path enumeration, epidemic models and standard graph centrality measures. We also present the notion of a three tier architecture and how it can help study the structural properties of TRN based on connectivity and clustering tendency of motif central nodes. Finally, we motivate the potential implication of the structural properties of motif centrality in design of efficient protocols of information routing in communication networks as well as their functional properties in global regulation and stress response to study specific disease conditions and identification of drug targets.

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“…This evidence suggests that dysregulation of an elaborate gene network involved in multiple biologic processes that impair lymphocyte survival, rather than a single gene or process, likely instigates sarcoidosis-related lymphopenia. In this regard, transcriptomic networks that determine cell function and fate in health and disease primarily depend on the activation or repression of genes through the coordinated regulatory activity of transcription factors ( 35 – 38 ). However, the relevance of transcription factors in gene signatures derived from high-throughput transcriptomic differential expression analyses is often overlooked because of their relatively low and stable abundance as well as the inability of these analyses to determine transcription factor interactions with target genes ( 39 – 42 ).…”

Section: Introductionmentioning

confidence: 99%

Altered transcription factor targeting is associated with differential peripheral blood mononuclear cell proportions in sarcoidosis

et al. 2022

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IntroductionIn sarcoidosis, peripheral lymphopenia and anergy have been associated with increased inflammation and maladaptive immune activity, likely promoting development of chronic and progressive disease. However, the molecular mechanisms that lead to reduced lymphocyte proportions, particularly CD4+ T-cells, have not been fully elucidated. We posit that paradoxical peripheral lymphopenia is characterized by a dysregulated transcriptomic network associated with cell function and fate that results from altered transcription factor targeting activity.MethodsMessenger RNA-sequencing (mRNA-seq) was performed on peripheral blood mononuclear cells (PBMCs) from ACCESS study subjects with sarcoidosis and matched controls and findings validated on a sarcoidosis case-control cohort and a sarcoidosis case series. Preserved PBMC transcriptomic networks between case-control cohorts were assessed to establish cellular associations with gene modules and define regulatory targeting involved in sarcoidosis immune dysregulation utilizing weighted gene co-expression network analysis and differential transcription factor involvement analysis. Network centrality measures identified master transcriptional regulators of subnetworks related to cell proliferation and death. Predictive models of differential PBMC proportions constructed from ACCESS target gene expression corroborated the relationship between aberrant transcription factor regulatory activity and imputed and clinical PBMC populations in the validation cohorts.ResultsWe identified two unique and preserved gene modules significantly associated with sarcoidosis immune dysregulation. Strikingly, increased expression of a monocyte-driven, and not a lymphocyte-driven, gene module related to innate immunity and cell death was the best predictor of peripheral CD4+ T-cell proportions. Within the gene network of this monocyte-driven module, TLE3 and CBX8 were determined to be master regulators of the cell death subnetwork. A core gene signature of differentially over-expressed target genes of TLE3 and CBX8 involved in cellular communication and immune response regulation accurately predicted imputed and clinical monocyte expansion and CD4+ T-cell depletion.ConclusionsAltered transcriptional regulation associated with aberrant gene expression of a monocyte-driven transcriptional network likely influences lymphocyte function and survival. Although further investigation is warranted, this indicates that crosstalk between hyperactive monocytes and lymphocytes may instigate peripheral lymphopenia and underlie sarcoidosis immune dysregulation and pathogenesis. Future therapies selectively targeting master regulators, or their targets, may mitigate dysregulated immune processes in sarcoidosis and disease progression.

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The role of master regulators in gene regulatory networks

Cited by 4 publications

References 21 publications

k-core genes underpin structural features of breast cancer

k-core genes underpin structural features of breast cancer

Motifs enable communication efficiency and fault-tolerance in transcriptional networks

Altered transcription factor targeting is associated with differential peripheral blood mononuclear cell proportions in sarcoidosis

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