scholarly journals Genome-scale bacterial transcriptional regulatory networks: reconstruction and integrated analysis with metabolic models

2013 ◽  
Vol 15 (4) ◽  
pp. 592-611 ◽  
Author(s):  
J. P. Faria ◽  
R. Overbeek ◽  
F. Xia ◽  
M. Rocha ◽  
I. Rocha ◽  
...  
Keyword(s):  
Regulatory Networks ◽  
Integrated Analysis ◽  
Transcriptional Regulatory Networks ◽  
Transcriptional Regulatory ◽  
Metabolic Models ◽  
Genome Scale

scholarly journals Systematic dissection of transcriptional regulatory networks by genome-scale and single-cell CRISPR screens

2021 ◽  
Vol 7 (27) ◽  
pp. eabf5733
Author(s):  
Rui Lopes ◽  
Kathleen Sprouffske ◽  
Caibin Sheng ◽  
Esther C. H. Uijttewaal ◽  
Adriana Emma Wesdorp ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Regulatory Networks ◽  
Essential Role ◽  
Regulatory Elements ◽  
Transcriptional Regulatory Networks ◽  
Transcriptional Regulatory Elements ◽  
Transcriptional Regulatory ◽  
Functional Relevance ◽  
Genome Scale ◽  
Transcription Program

Millions of putative transcriptional regulatory elements (TREs) have been cataloged in the human genome, yet their functional relevance in specific pathophysiological settings remains to be determined. This is critical to understand how oncogenic transcription factors (TFs) engage specific TREs to impose transcriptional programs underlying malignant phenotypes. Here, we combine cutting edge CRISPR screens and epigenomic profiling to functionally survey ≈15,000 TREs engaged by estrogen receptor (ER). We show that ER exerts its oncogenic role in breast cancer by engaging TREs enriched in GATA3, TFAP2C, and H3K27Ac signal. These TREs control critical downstream TFs, among which TFAP2C plays an essential role in ER-driven cell proliferation. Together, our work reveals novel insights into a critical oncogenic transcription program and provides a framework to map regulatory networks, enabling to dissect the function of the noncoding genome of cancer cells.

scholarly journals Analysis of next- and third-generation RNA-Seq data reveals the structures of alternative transcription units in bacterial genomes

2021 ◽  
Author(s):  
Qi Wang ◽  
Zhaoqian Liu ◽  
Bo Yan ◽  
Wen-Chi Chou ◽  
Laurence Ettwiller ◽  
...  
Keyword(s):  
Regulatory Networks ◽  
Programming Model ◽  
Third Generation ◽  
Rna Seq ◽  
Bacterial Genomes ◽  
Transcriptional Regulatory Networks ◽  
Computational Framework ◽  
Transcriptional Regulatory ◽  
Alternative Transcription ◽  
Genome Scale

ABSTRACTAlternative transcription units (ATUs) are dynamically encoded under different conditions or environmental stimuli in bacterial genomes, and genome-scale identification of ATUs is essential for studying the emergence of human diseases caused by bacterial organisms. However, it is unrealistic to identify all ATUs using experimental techniques, due to the complexity and dynamic nature of ATUs. Here we present the first-of-its-kind computational framework, named SeqATU, for genome-scale ATU prediction based on next-generation RNA-Seq data. The framework utilizes a convex quadratic programming model to seek an optimum expression combination of all of the to-be-identified ATUs. The predicted ATUs in E. coli reached a precision of 0.77/0.74 and a recall of 0.75/0.76 in the two RNA-Sequencing datasets compared with the benchmarked ATUs from third-generation RNA-Seq data. We believe that the ATUs identified by SeqATU can provide fundamental knowledge to guide the reconstruction of transcriptional regulatory networks in bacterial genomes.

scholarly journals A review of methods for the reconstruction and analysis of integrated genome-scale models of metabolism and regulation

2020 ◽  
Vol 48 (5) ◽  
pp. 1889-1903
Author(s):  
Fernando Cruz ◽  
José P. Faria ◽  
Miguel Rocha ◽  
Isabel Rocha ◽  
Oscar Dias
Keyword(s):  
Gene Expression ◽  
Regulatory Networks ◽  
Transcriptional Regulatory Networks ◽  
Flux Balance ◽  
Transcriptional Regulatory ◽  
Scale Models ◽  
Current Survey ◽  
Balance Analysis ◽  
Or Gene ◽  
Genome Scale

The current survey aims to describe the main methodologies for extending the reconstruction and analysis of genome-scale metabolic models and phenotype simulation with Flux Balance Analysis mathematical frameworks, via the integration of Transcriptional Regulatory Networks and/or gene expression data. Although the surveyed methods are aimed at improving phenotype simulations obtained from these models, the perspective of reconstructing integrated genome-scale models of metabolism and gene expression for diverse prokaryotes is still an open challenge.

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.

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