scholarly journals RNA Polymerase II Phosphorylation and Gene Expression Regulation

10.5772/48490 ◽  
2012 ◽  
Author(s):  
Olga Calvo ◽  
Alicia Garc
Keyword(s):  
Gene Expression ◽  
Rna Polymerase ◽  
Rna Polymerase Ii ◽  
Gene Expression Regulation ◽  
Expression Regulation

scholarly journals G-Quadruplex in Gene Encoding Large Subunit of Plant RNA Polymerase II: A Billion-Year-Old Story

2021 ◽  
Vol 22 (14) ◽  
pp. 7381
Author(s):  
Adriana Volná ◽  
Martin Bartas ◽  
Václav Karlický ◽  
Jakub Nezval ◽  
Kristýna Kundrátová ◽  
...  
Keyword(s):  
Gene Expression ◽  
Rna Polymerase ◽  
Rna Polymerase Ii ◽  
Gene Expression Regulation ◽  
Uv Light ◽  
Large Subunit ◽  
Expression Regulation ◽  
Gene Encoding ◽  
Additional Layer ◽  
G Quadruplex

G-quadruplexes have long been perceived as rare and physiologically unimportant nucleic acid structures. However, several studies have revealed their importance in molecular processes, suggesting their possible role in replication and gene expression regulation. Pathways involving G-quadruplexes are intensively studied, especially in the context of human diseases, while their involvement in gene expression regulation in plants remains largely unexplored. Here, we conducted a bioinformatic study and performed a complex circular dichroism measurement to identify a stable G-quadruplex in the gene RPB1, coding for the RNA polymerase II large subunit. We found that this G-quadruplex-forming locus is highly evolutionarily conserved amongst plants sensu lato (Archaeplastida) that share a common ancestor more than one billion years old. Finally, we discussed a new hypothesis regarding G-quadruplexes interacting with UV light in plants to potentially form an additional layer of the regulatory network.

Nutrient-regulated gene expression in eukaryotes

2006 ◽  
Vol 73 ◽  
pp. 85-96 ◽  
Author(s):  
Richard J. Reece ◽  
Laila Beynon ◽  
Stacey Holden ◽  
Amanda D. Hughes ◽  
Karine Rébora ◽  
...  
Keyword(s):  
Gene Expression ◽  
Rna Polymerase ◽  
Rna Polymerase Ii ◽  
Transcriptional Control ◽  
Direct Interaction ◽  
Signalling Pathways ◽  
A Cell ◽  
One Step ◽  
Higher Eukaryotes ◽  
Regulated Gene Expression

The recognition of changes in environmental conditions, and the ability to adapt to these changes, is essential for the viability of cells. There are numerous well characterized systems by which the presence or absence of an individual metabolite may be recognized by a cell. However, the recognition of a metabolite is just one step in a process that often results in changes in the expression of whole sets of genes required to respond to that metabolite. In higher eukaryotes, the signalling pathway between metabolite recognition and transcriptional control can be complex. Recent evidence from the relatively simple eukaryote yeast suggests that complex signalling pathways may be circumvented through the direct interaction between individual metabolites and regulators of RNA polymerase II-mediated transcription. Biochemical and structural analyses are beginning to unravel these elegant genetic control elements.

Gerea: Prediction Of Gene Expression Regulators From Transcriptome Profiling Data To Transition Networks

2021 ◽  
Vol 16 ◽  
Author(s):  
Min Yao ◽  
Caiyun Jiang ◽  
Chenglong Li ◽  
Yongxia Li ◽  
Shan Jiang ◽  
...  
Keyword(s):  
Gene Expression ◽  
Gene Networks ◽  
Target Gene ◽  
Gene Expression Regulation ◽  
Transcriptome Profiling ◽  
Expression Regulation ◽  
Mouse Gene ◽  
Mouse Gene Expression ◽  
Causality Inference ◽  
Identify Gene Expression

Background: Mammalian genes are regulated at the transcriptional and post-transcriptional levels. These mechanisms may involve the direct promotion or inhibition of transcription via a regulator or post-transcriptional regulation through factors such as micro (mi)RNAs. Objective: This study aimed to construct gene regulation relationships modulated by causality inference-based miRNA-(transition factor)-(target gene) networks and analyze gene expression data to identify gene expression regulators. Methods: Mouse gene expression regulation relationships were manually curated from literature using a text mining method which was then employed to generate miRNA-(transition factor)-(target gene) networks. An algorithm was then introduced to identify gene expression regulators from transcriptome profiling data by applying enrichment analysis to these networks. Results: A total of 22,271 mouse gene expression regulation relationships were curated for 4,018 genes and 242 miRNAs. GEREA software was developed to perform the integrated analyses. We applied the algorithm to transcriptome data for synthetic miR-155 oligo-treated mouse CD4+ T-cells and confirmed that miR-155 is an important network regulator. The software was also tested on publicly available transcriptional profiling data for Salmonella infection, resulting in the identification of miR-125b as an important regulator. Conclusion: The causality inference-based miRNA-(transition factor)-(target gene) networks serve as a novel resource for gene expression regulation research, and GEREA is an effective and useful adjunct to the currently available methods. The regulatory networks and the algorithm implemented in the GEREA software package are available under a free academic license at website : http://www.thua45.cn/gerea.

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