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.

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.

What are Gene Regulatory Networks?

2010 ◽  
pp. 1-27 ◽  
Author(s):  
Alberto de la Fuente
Keyword(s):  
Gene Expression ◽  
Gene Regulatory Networks ◽  
Regulatory Networks ◽  
Network Models ◽  
Transcriptional Regulatory Networks ◽  
Biochemical Processes ◽  
Transcriptional Regulatory ◽  
Biochemical Systems ◽  
Gene Regulatory

This book deals with algorithms for inferring and analyzing Gene Regulatory Networks using mainly gene expression data. What precisely are the Gene Regulatory Networks that are inferred by such algorithms from this type of data? There is still much confusion in the current literature and it is important to start a book about computational methods for Gene Regulatory Networks with a definition that is as unambiguous as possible. In this chapter, I provide a definition and try to clearly explain what Gene Regulatory Networks are in terms of the underlying biochemical processes. To do the latter in a formal way, I will use a linear approximation to the in general non-linear kinetics underlying interactions in biochemical systems and show how a biochemical system can be ‘condensed’ into the more compact description of Gene Regulatory Networks. Important differences between the defined Gene Regulatory Networks and other network models for gene regulation, such as Transcriptional Regulatory Networks and Co-Expression Networks, will be highlighted.

scholarly journals Transcriptional regulatory networks underlying gene expression changes in Huntington's disease

2018 ◽  
Vol 14 (3) ◽  
Author(s):  
Seth A Ament ◽  
Jocelynn R Pearl ◽  
Jeffrey P Cantle ◽  
Robert M Bragg ◽  
Peter J Skene ◽  
...  
Keyword(s):  
Gene Expression ◽  
Huntington's Disease ◽  
Huntington’S Disease ◽  
Regulatory Networks ◽  
Transcriptional Regulatory Networks ◽  
Transcriptional Regulatory

scholarly journals Mechanisms and Evolution of Control Logic in Prokaryotic Transcriptional Regulation

2009 ◽  
Vol 73 (3) ◽  
pp. 481-509 ◽  
Author(s):  
Sacha A. F. T. van Hijum ◽  
Marnix H. Medema ◽  
Oscar P. Kuipers
Keyword(s):  
Gene Expression ◽  
Regulatory Networks ◽  
Regulation Of Gene Expression ◽  
Control Logic ◽  
Transcriptional Regulatory Networks ◽  
Regulatory Regions ◽  
Evolutionary Origins ◽  
Drive Gene Expression ◽  
Transcriptional Regulatory ◽  
Drive Gene

SUMMARY A major part of organismal complexity and versatility of prokaryotes resides in their ability to fine-tune gene expression to adequately respond to internal and external stimuli. Evolution has been very innovative in creating intricate mechanisms by which different regulatory signals operate and interact at promoters to drive gene expression. The regulation of target gene expression by transcription factors (TFs) is governed by control logic brought about by the interaction of regulators with TF binding sites (TFBSs) in cis-regulatory regions. A factor that in large part determines the strength of the response of a target to a given TF is motif stringency, the extent to which the TFBS fits the optimal TFBS sequence for a given TF. Advances in high-throughput technologies and computational genomics allow reconstruction of transcriptional regulatory networks in silico. To optimize the prediction of transcriptional regulatory networks, i.e., to separate direct regulation from indirect regulation, a thorough understanding of the control logic underlying the regulation of gene expression is required. This review summarizes the state of the art of the elements that determine the functionality of TFBSs by focusing on the molecular biological mechanisms and evolutionary origins of cis-regulatory regions.

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