scholarly journals Identification of COVID-19-relevant transcriptional regulatory networks and associated kinases as potential therapeutic targets

2020 ◽  
Author(s):  
Chen Su ◽  
Simon Rousseau ◽  
Amin Emad
Keyword(s):  
Epithelial Cells ◽  
Regulatory Networks ◽  
Therapeutic Targets ◽  
Airway Epithelial Cells ◽  
Regulatory Mechanisms ◽  
Interferon Response ◽  
Transcriptional Regulatory Networks ◽  
Transcriptional Regulatory ◽  
Transcriptional Regulatory Mechanisms ◽  
The Impact

ABSTRACTIdentification of transcriptional regulatory mechanisms and signaling networks involved in the response of host to infection by SARS-CoV-2 is a powerful approach that provides a systems biology view of gene expression programs involved in COVID-19 and may enable identification of novel therapeutic targets and strategies to mitigate the impact of this disease. In this study, we combined a series of recently developed computational tools to identify transcriptional regulatory networks involved in the response of epithelial cells to infection by SARS-CoV-2, and particularly regulatory mechanisms that are specific to this virus. In addition, using network-guided analyses, we identified signaling pathways that are associated with these networks and kinases that may regulate them. The results identified classical antiviral response pathways including Interferon response factors (IRFs), interferons (IFNs), and JAK-STAT signaling as key elements upregulated by SARS-CoV-2 in comparison to mock-treated cells. In addition, comparing SARS-Cov-2 infection of airway epithelial cells to other respiratory viruses identified pathways associated with regulation of inflammation (MAPK14) and immunity (BTK, MBX) that may contribute to exacerbate organ damage linked with complications of COVID-19. The regulatory networks identified herein reflect a combination of experimentally validated hits and novel pathways supporting the computational pipeline to quickly narrow down promising avenue of investigations when facing an emerging and novel disease such as COVID-19.

scholarly journals Identification of transcriptional regulatory network associated with response of host epithelial cells to SARS-CoV-2

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Chen Su ◽  
Simon Rousseau ◽  
Amin Emad
Keyword(s):  
Gene Expression ◽  
Epithelial Cells ◽  
Regulatory Network ◽  
Transcriptional Regulatory Network ◽  
Organ Damage ◽  
Host Cells ◽  
Regulatory Mechanisms ◽  
Transcriptional Regulatory ◽  
Transcriptional Regulatory Mechanisms ◽  
The Impact

AbstractIdentification of transcriptional regulatory mechanisms and signaling networks involved in the response of host cells to infection by SARS-CoV-2 is a powerful approach that provides a systems biology view of gene expression programs involved in COVID-19 and may enable the identification of novel therapeutic targets and strategies to mitigate the impact of this disease. In this study, our goal was to identify a transcriptional regulatory network that is associated with gene expression changes between samples infected by SARS-CoV-2 and those that are infected by other respiratory viruses to narrow the results on those enriched or specific to SARS-CoV-2. We combined a series of recently developed computational tools to identify transcriptional regulatory mechanisms involved in the response of epithelial cells to infection by SARS-CoV-2, and particularly regulatory mechanisms that are specific to this virus when compared to other viruses. In addition, using network-guided analyses, we identified kinases associated with this network. The results identified pathways associated with regulation of inflammation (MAPK14) and immunity (BTK, MBX) that may contribute to exacerbate organ damage linked with complications of COVID-19. The regulatory network identified herein reflects a combination of known hits and novel candidate pathways supporting the novel computational pipeline presented herein to quickly narrow down promising avenues of investigation when facing an emerging and novel disease such as COVID-19.

scholarly journals The nuclear receptor HNF4 drives a brush border gene program conserved across murine intestine, kidney, and embryonic yolk sac

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Lei Chen ◽  
Shirley Luo ◽  
Abigail Dupre ◽  
Roshan P. Vasoya ◽  
Aditya Parthasarathy ◽  
...  
Keyword(s):  
Brush Border ◽  
Regulatory Networks ◽  
Critical Role ◽  
Yolk Sac ◽  
Apical Surface ◽  
Transcriptional Regulatory Networks ◽  
Chromatin Looping ◽  
Multiple Organs ◽  
Transcriptional Regulatory ◽  
Transcriptional Regulatory Mechanisms

AbstractThe brush border is comprised of microvilli surface protrusions on the apical surface of epithelia. This specialized structure greatly increases absorptive surface area and plays crucial roles in human health. However, transcriptional regulatory networks controlling brush border genes are not fully understood. Here, we identify that hepatocyte nuclear factor 4 (HNF4) transcription factor is a conserved and important regulator of brush border gene program in multiple organs, such as intestine, kidney and yolk sac. Compromised brush border gene signatures and impaired transport were observed in these tissues upon HNF4 loss. By ChIP-seq, we find HNF4 binds and activates brush border genes in the intestine and kidney. H3K4me3 HiChIP-seq identifies that HNF4 loss results in impaired chromatin looping between enhancers and promoters at gene loci of brush border genes, and instead enhanced chromatin looping at gene loci of stress fiber genes in the intestine. This study provides comprehensive transcriptional regulatory mechanisms and a functional demonstration of a critical role for HNF4 in brush border gene regulation across multiple murine epithelial tissues.

scholarly journals Inference of phenotype-relevant transcriptional regulatory networks elucidates cancer type-specific regulatory mechanisms in a pan-cancer study

2021 ◽  
Vol 7 (1) ◽  
Author(s):  
Amin Emad ◽  
Saurabh Sinha
Keyword(s):  
Regulatory Networks ◽  
Target Genes ◽  
Graphical Model ◽  
Activity Level ◽  
The Cancer Genome Atlas ◽  
Regulatory Mechanisms ◽  
Cancer Type ◽  
Transcriptional Regulatory Networks ◽  
Cancer Driver ◽  
Transcriptional Regulatory

AbstractReconstruction of transcriptional regulatory networks (TRNs) is a powerful approach to unravel the gene expression programs involved in healthy and disease states of a cell. However, these networks are usually reconstructed independent of the phenotypic (or clinical) properties of the samples. Therefore, they may confound regulatory mechanisms that are specifically related to a phenotypic property with more general mechanisms underlying the full complement of the analyzed samples. In this study, we develop a method called InPheRNo to identify “phenotype-relevant” TRNs. This method is based on a probabilistic graphical model that models the simultaneous effects of multiple transcription factors (TFs) on their target genes and the statistical relationship between the target genes’ expression and the phenotype. Extensive comparison of InPheRNo with related approaches using primary tumor samples of 18 cancer types from The Cancer Genome Atlas reveals that InPheRNo can accurately reconstruct cancer type-relevant TRNs and identify cancer driver TFs. In addition, survival analysis reveals that the activity level of TFs with many target genes could distinguish patients with poor prognosis from those with better prognosis.

scholarly journals Inference of phenotype-relevant transcriptional regulatory networks elucidates cancer type-specific regulatory mechanisms in a pan-cancer study

2018 ◽  
Author(s):  
Amin Emad ◽  
Saurabh Sinha
Keyword(s):  
Gene Expression ◽  
Regulatory Networks ◽  
Target Genes ◽  
Graphical Model ◽  
Activity Level ◽  
The Cancer Genome Atlas ◽  
Regulatory Mechanisms ◽  
Cancer Type ◽  
Transcriptional Regulatory Networks ◽  
Transcriptional Regulatory

ABSTRACTReconstruction of transcriptional regulatory networks (TRNs) is a powerful approach to unravel the gene expression programs involved in healthy and disease states of a cell. However, these networks are usually reconstructed independent of the phenotypic properties of the samples and therefore cannot identify regulatory mechanisms that are related to a phenotypic outcome of interest. In this study, we developed a new method called InPheRNo to identify ‘phenotype-relevant’ transcriptional regulatory networks. This method is based on a probabilistic graphical model whose conditional probability distributions model the simultaneous effects of multiple transcription factors (TFs) on their target genes as well as the statistical relationship between target gene expression and phenotype. Extensive comparison of InPheRNo with related approaches using primary tumor samples of 18 cancer types from The Cancer Genome Atlas revealed that InPheRNo can accurately reconstruct cancer type-relevant TRNs and identify cancer driver TFs. In addition, survival analysis revealed that the activity level of TFs with many target genes could distinguish patients with good prognosis from those with poor prognosis.

scholarly journals The Role of Non-Coding RNA in Congenital Heart Diseases

2019 ◽  
Vol 6 (2) ◽  
pp. 15 ◽  
Author(s):  
Angel Dueñas ◽  
Almudena Expósito ◽  
Amelia Aranega ◽  
Diego Franco
Keyword(s):  
Congenital Heart ◽  
Heart Diseases ◽  
Regulatory Mechanisms ◽  
Congenital Heart Diseases ◽  
Cardiovascular Development ◽  
Transcriptional Regulatory ◽  
Non Coding Rnas ◽  
Transcriptional Regulatory Mechanisms ◽  
The Impact

Cardiovascular development is a complex developmental process starting with the formation of an early straight heart tube, followed by a rightward looping and the configuration of atrial and ventricular chambers. The subsequent step allows the separation of these cardiac chambers leading to the formation of a four-chambered organ. Impairment in any of these developmental processes invariably leads to cardiac defects. Importantly, our understanding of the developmental defects causing cardiac congenital heart diseases has largely increased over the last decades. The advent of the molecular era allowed to bridge morphogenetic with genetic defects and therefore our current understanding of the transcriptional regulation of cardiac morphogenesis has enormously increased. Moreover, the impact of environmental agents to genetic cascades has been demonstrated as well as of novel genomic mechanisms modulating gene regulation such as post-transcriptional regulatory mechanisms. Among post-transcriptional regulatory mechanisms, non-coding RNAs, including therein microRNAs and lncRNAs, are emerging to play pivotal roles. In this review, we summarize current knowledge on the functional role of non-coding RNAs in distinct congenital heart diseases, with particular emphasis on microRNAs and long non-coding RNAs.

Transcriptional Control of Parturition: Insights from Gene Regulation Studies in the Myometrium

2021 ◽  
Author(s):  
Nawrah Khader ◽  
Virlana M Shchuka ◽  
Oksana Shynlova ◽  
Jennifer A Mitchell
Keyword(s):  
Transcription Factors ◽  
Regulatory Networks ◽  
Transcriptional Control ◽  
Progesterone Receptors ◽  
Activator Protein 1 ◽  
Transcriptional Regulatory Networks ◽  
Regulatory Pathways ◽  
Transcriptional Regulatory ◽  
Mechanistic Basis ◽  
Labour Onset

Abstract The onset of labour is a culmination of a series of highly coordinated and preparatory physiological events that take place throughout the gestational period. In order to produce the associated contractions needed for fetal delivery, smooth muscle cells in the muscular layer of the uterus (i.e. myometrium) undergo a transition from quiescent to contractile phenotypes. Here, we present the current understanding of the roles transcription factors play in critical labour-associated gene expression changes as part of the molecular mechanistic basis for this transition. Consideration is given to both transcription factors that have been well-studied in a myometrial context, i.e. activator protein 1 (AP-1), progesterone receptors (PRs), estrogen receptors (ERs), and nuclear factor kappa B (NF-κB), as well as additional transcription factors whose gestational event-driving contributions have been demonstrated more recently. These transcription factors may form pregnancy- and labour- associated transcriptional regulatory networks in the myometrium to modulate the timing of labour onset. A more thorough understanding of the transcription factor-mediated, labour-promoting regulatory pathways holds promise for the development of new therapeutic treatments that can be used for the prevention of preterm labour in at-risk women.

scholarly journals Transcriptional Regulatory Networks Associate with Early Stages of Potato Virus X Infection of Solanum tuberosum

2021 ◽  
Vol 22 (6) ◽  
pp. 2837
Author(s):  
Venura Herath ◽  
Jeanmarie Verchot
Keyword(s):  
Potato Virus ◽  
Regulatory Networks ◽  
Potato Virus X ◽  
Early Response ◽  
Pathogen Resistance ◽  
Transcriptional Regulatory Networks ◽  
Unfolded Protein ◽  
Molecular Pattern ◽  
Transcriptional Regulatory ◽  
Protein Response

Potato virus X (PVX) belongs to genus Potexvirus. This study characterizes the cellular transcriptome responses to PVX infection in Russet potato at 2 and 3 days post infection (dpi). Among the 1242 differentially expressed genes (DEGs), 268 genes were upregulated, and 37 genes were downregulated at 2 dpi while 677 genes were upregulated, and 265 genes were downregulated at 3 dpi. DEGs related to signal transduction, stress response, and redox processes. Key stress related transcription factors were identified. Twenty-five pathogen resistance gene analogs linked to effector triggered immunity or pathogen-associated molecular pattern (PAMP)-triggered immunity were identified. Comparative analysis with Arabidopsis unfolded protein response (UPR) induced DEGs revealed genes associated with UPR and plasmodesmata transport that are likely needed to establish infection. In conclusion, this study provides an insight on major transcriptional regulatory networked involved in early response to PVX infection and establishment.

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