A Yeast Hybrid Provides Insight into the Evolution of Gene Expression Regulation

Science ◽  
2009 ◽  
Vol 324 (5927) ◽  
pp. 659-662 ◽  
Author(s):  
I. Tirosh ◽  
S. Reikhav ◽  
A. A. Levy ◽  
N. Barkai
Keyword(s):  
Gene Expression ◽  
Gene Expression Regulation ◽  
Expression Regulation ◽  
Yeast Hybrid ◽  
Insight Into

scholarly journals Insight into m 6 A methylation from occurrence to functions

Open Biology ◽  
2020 ◽  
Vol 10 (9) ◽  
pp. 200091
Author(s):  
Wenxiu Ru ◽  
Xiaoyan Zhang ◽  
Binglin Yue ◽  
Ao Qi ◽  
Xuemei Shen ◽  
...  
Keyword(s):  
Gene Expression ◽  
Gene Expression Regulation ◽  
Expression Regulation ◽  
Cancer Development ◽  
Regulatory Effect ◽  
Non Coding Rna ◽  
Reversible Modification ◽  
Regulatory Functions ◽  
Insight Into

RNA m 6 A methylation is a post-transcriptional modification that occurs at the nitrogen-6 position of adenine. This dynamically reversible modification is installed, removed and recognized by methyltransferases, demethylases and readers, respectively. This modification has been found in most eukaryotic mRNA, tRNA, rRNA and other non-coding RNA. Recent studies have revealed important regulatory functions of the m 6 A including effects on gene expression regulation, organism development and cancer development. In this review, we summarize the discovery and features of m 6 A, and briefly introduce the mammalian m 6 A writers, erasers and readers. Finally, we discuss progress in identifying additional functions of m 6 A and the outstanding questions about the regulatory effect of this widespread modification.

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.

scholarly journals RNAN6-methyladenosine methylation in post-transcriptional gene expression regulation

2015 ◽  
Vol 29 (13) ◽  
pp. 1343-1355 ◽  
Author(s):  
Yanan Yue ◽  
Jianzhao Liu ◽  
Chuan He
Keyword(s):  
Gene Expression ◽  
Gene Expression Regulation ◽  
Expression Regulation
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