Integration of the information from gene expression and metabolic fluxes for the analysis of the regulatory mechanisms in Synechocystis

2002 ◽  
Vol 58 (6) ◽  
pp. 813-822 ◽  
Author(s):  
Yang C. ◽  
Hua Q. ◽  
Shimizu K.
Keyword(s):  
Gene Expression ◽  
Regulatory Mechanisms ◽  
Metabolic Fluxes

tiRNAs & tRFs Biogenesis and Regulation of Diseases: A Review

2019 ◽  
Vol 26 (31) ◽  
pp. 5849-5861 ◽  
Author(s):  
Pan Jiang ◽  
Feng Yan
Keyword(s):  
Gene Expression ◽  
Protein Synthesis ◽  
Metabolic Diseases ◽  
Viral Infections ◽  
Regulatory Mechanisms ◽  
Biological Functions ◽  
Reverse Transcriptases ◽  
Dna Damage Responses ◽  
Potential Applications ◽  
Viral Reverse Transcriptases

tiRNAs & tRFs are a class of small molecular noncoding tRNA derived from precise processing of mature or precursor tRNAs. Most tiRNAs & tRFs described originate from nucleus-encoded tRNAs, and only a few tiRNAs and tRFs have been reported. They have been suggested to play important roles in inhibiting protein synthesis, regulating gene expression, priming viral reverse transcriptases, and the modulation of DNA damage responses. However, the regulatory mechanisms and potential function of tiRNAs & tRFs remain poorly understood. This review aims to describe tiRNAs & tRFs, including their structure, biological functions and subcellular localization. The regulatory roles of tiRNAs & tRFs in translation, neurodegeneration, metabolic diseases, viral infections, and carcinogenesis are also discussed in detail. Finally, the potential applications of these noncoding tRNAs as biomarkers and gene regulators in different diseases is also highlighted.

scholarly journals R2R3-MYB transcription factors, StmiR858 and sucrose mediate potato flavonol biosynthesis

2021 ◽  
Vol 8 (1) ◽  
Author(s):  
Sen Lin ◽  
Rajesh K. Singh ◽  
Moehninsi ◽  
Duroy A. Navarre
Keyword(s):  
Gene Expression ◽  
Abiotic Stress ◽  
Feedback Loop ◽  
Regulatory Mechanisms ◽  
Phenylpropanoid Metabolism ◽  
Biotic And Abiotic Stress ◽  
Health Promoting ◽  
Transient Overexpression ◽  
R2r3 Myb ◽  
R2r3 Myb Transcription Factors

AbstractFlavonols and other phenylpropanoids protect plants from biotic and abiotic stress and are dietarily desirable because of their health-promoting properties. The ability to develop new potatoes (Solanum tuberosum) with optimal types and amounts of phenylpropanoids is limited by lack of knowledge about the regulatory mechanisms. Exogenous sucrose increased flavonols, whereas overexpression of the MYB StAN1 induced sucrolytic gene expression. Heterologous StAN1 protein bound promoter fragments from sucrolytic genes (SUSY1 and INV1). Two additional MYBs and one microRNA were identified that regulated potato flavonols. Overexpression analysis showed MYB12A and C increased amounts of flavonols and other phenylpropanoids. Endogenous flavonol amounts in light-exposed organs were much higher those in the dark. Expression levels of StMYB12A and C were high in flowers but low in tubers. Transient overexpression of miR858 altered potato flavonol metabolism. Endogenous StmiR858 expression was much lower in flowers than leaves and correlated with flavonol amounts in these organs. Collectively, these findings support the hypothesis that sucrose, MYBs, and miRNA control potato phenylpropanoid metabolism in a finely tuned manner that includes a feedback loop between sucrose and StAN1. These findings will aid in the development of potatoes with phenylpropanoid profiles optimized for crop performance and human health.

scholarly journals Contribution of gene expression to metabolic fluxes in hypermetabolic livers induced through burn injury and cecal ligation and puncture in rats

2007 ◽  
Vol 97 (1) ◽  
pp. 118-137 ◽  
Author(s):  
Scott Banta ◽  
Murali Vemula ◽  
Tadaaki Yokoyama ◽  
Arul Jayaraman ◽  
François Berthiaume ◽  
...  
Keyword(s):  
Gene Expression ◽  
Burn Injury ◽  
Cecal Ligation ◽  
Cecal Ligation And Puncture ◽  
Metabolic Fluxes

Global regulatory mechanisms affect virulence gene expression in Bordetella pertussis

1995 ◽  
Vol 247 (1) ◽  
pp. 86-94 ◽  
Author(s):  
Heinke Graeff-Wohlleben ◽  
Heike Deppisch ◽  
Roy Gross
Keyword(s):  
Gene Expression ◽  
Bordetella Pertussis ◽  
Virulence Gene ◽  
Regulatory Mechanisms ◽  
Virulence Gene Expression

scholarly journals Involvement of microRNA in Solid Cancer: Role and Regulatory Mechanisms

Biomedicines ◽  
2021 ◽  
Vol 9 (4) ◽  
pp. 343
Author(s):  
Ying-Chin Lin ◽  
Tso-Hsiao Chen ◽  
Yu-Min Huang ◽  
Po-Li Wei ◽  
Jung-Chun Lin
Keyword(s):  
Gene Expression ◽  
Regulatory Mechanism ◽  
Transcriptional Factor ◽  
Regulatory Mechanisms ◽  
Solid Cancer ◽  
Detailed Knowledge ◽  
Altered Expression ◽  
Human Malignancy ◽  
Regulated Expression ◽  
Pivotal Mechanism

MicroRNAs (miRNAs) function as the post-transcriptional factor that finetunes the gene expression by targeting to the specific candidate. Mis-regulated expression of miRNAs consequently disturbs gene expression profile, which serves as the pivotal mechanism involved in initiation or progression of human malignancy. Cancer-relevant miRNA is potentially considered the therapeutic target or biomarker toward the precise treatment of cancer. Nevertheless, the regulatory mechanism underlying the altered expression of miRNA in cancer is largely uncovered. Detailed knowledge regarding the influence of miRNAs on solid cancer is critical for exploring its potential of clinical application. Herein, we elucidate the regulatory mechanism regarding how miRNA expression is manipulated and its impact on the pathogenesis of distinct solid cancer.

scholarly journals Genome-Wide Analysis of Glucocorticoid-Responsive Transcripts in the Hypothalamic Paraventricular Region of Male Rats

Endocrinology ◽  
2018 ◽  
Vol 160 (1) ◽  
pp. 38-54 ◽  
Author(s):  
Keiichi Itoi ◽  
Ikuko Motoike ◽  
Ying Liu ◽  
Sam Clokie ◽  
Yasumasa Iwasaki ◽  
...  
Keyword(s):  
Gene Expression ◽  
Target Genes ◽  
Receptor Gene ◽  
Male Rats ◽  
Regulatory Mechanisms ◽  
High Dose ◽  
Sequencing Analysis ◽  
Reverse Transcription Pcr ◽  
Genome Wide ◽  
A Genome

Abstract Glucocorticoids (GCs) are essential for stress adaptation, acting centrally and in the periphery. Corticotropin-releasing factor (CRF), a major regulator of adrenal GC synthesis, is produced in the paraventricular nucleus of the hypothalamus (PVH), which contains multiple neuroendocrine and preautonomic neurons. GCs may be involved in diverse regulatory mechanisms in the PVH, but the target genes of GCs are largely unexplored except for the CRF gene (Crh), a well-known target for GC negative feedback. Using a genome-wide RNA-sequencing analysis, we identified transcripts that changed in response to either high-dose corticosterone (Cort) exposure for 12 days (12-day high Cort), corticoid deprivation for 7 days (7-day ADX), or acute Cort administration. Among others, canonical GC target genes were upregulated prominently by 12-day high Cort. Crh was upregulated or downregulated most prominently by either 7-day ADX or 12-day high Cort, emphasizing the recognized feedback effects of GC on the hypothalamic-pituitary-adrenal (HPA) axis. Concomitant changes in vasopressin and apelin receptor gene expression are likely to contribute to HPA repression. In keeping with the pleotropic cellular actions of GCs, 7-day ADX downregulated numerous genes of a broad functional spectrum. The transcriptome response signature differed markedly between acute Cort injection and 12-day high Cort. Remarkably, six immediate early genes were upregulated 1 hour after Cort injection, which was confirmed by quantitative reverse transcription PCR and semiquantitative in situ hybridization. This study may provide a useful database for studying the regulatory mechanisms of GC-dependent gene expression and repression in the PVH.

scholarly journals Genetic influences on cell type specific gene expression and splicing during neurogenesis elucidate regulatory mechanisms of brain traits

2020 ◽  
Author(s):  
Nil Aygün ◽  
Angela L. Elwell ◽  
Dan Liang ◽  
Michael J. Lafferty ◽  
Kerry E. Cheek ◽  
...  
Keyword(s):  
Gene Expression ◽  
Regulatory Elements ◽  
Regulatory Mechanisms ◽  
Specific Gene ◽  
Cell Type ◽  
Specific Expression ◽  
Risk Variants ◽  
Allele Specific ◽  
Cell Type Specific ◽  
Regulatory Effects

SummaryInterpretation of the function of non-coding risk loci for neuropsychiatric disorders and brain-relevant traits via gene expression and alternative splicing is mainly performed in bulk post-mortem adult tissue. However, genetic risk loci are enriched in regulatory elements of cells present during neocortical differentiation, and regulatory effects of risk variants may be masked by heterogeneity in bulk tissue. Here, we map e/sQTLs and allele specific expression in primary human neural progenitors (n=85) and their sorted neuronal progeny (n=74). Using colocalization and TWAS, we uncover cell-type specific regulatory mechanisms underlying risk for these traits.

Regulatory mechanisms governing FGF-4 gene expression during mouse development

1997 ◽  
Vol 173 (2) ◽  
pp. 227-232 ◽  
Author(s):  
Claudio Basilico ◽  
Davide Ambrosetti ◽  
Diego Fraidenraich ◽  
Lisa Dailey
Keyword(s):  
Gene Expression ◽  
Regulatory Mechanisms ◽  
Mouse Development

Inducible gene expression: diverse regulatory mechanisms

2010 ◽  
Vol 11 (6) ◽  
pp. 426-437 ◽  
Author(s):  
Vikki M. Weake ◽  
Jerry L. Workman
Keyword(s):  
Gene Expression ◽  
Regulatory Mechanisms ◽  
Inducible Gene Expression ◽  
Inducible Gene

scholarly journals Causal Inference Engine: a platform for directional gene set enrichment analysis and inference of active transcriptional regulators

2019 ◽  
Author(s):  
Saman Farahmand ◽  
Corey O’Connor ◽  
Jill A Macoska ◽  
Kourosh Zarringhalam
Keyword(s):  
Gene Expression ◽  
Causal Inference ◽  
Gene Expression Data ◽  
Transcriptional Regulators ◽  
Regulatory Mechanisms ◽  
Gene Interactions ◽  
Expression Data ◽  
Inference Algorithms ◽  
Tf Gene ◽  
Mode Of Regulation

Abstract Inference of active regulatory mechanisms underlying specific molecular and environmental perturbations is essential for understanding cellular response. The success of inference algorithms relies on the quality and coverage of the underlying network of regulator–gene interactions. Several commercial platforms provide large and manually curated regulatory networks and functionality to perform inference on these networks. Adaptation of such platforms for open-source academic applications has been hindered by the lack of availability of accurate, high-coverage networks of regulatory interactions and integration of efficient causal inference algorithms. In this work, we present CIE, an integrated platform for causal inference of active regulatory mechanisms form differential gene expression data. Using a regularized Gaussian Graphical Model, we construct a transcriptional regulatory network by integrating publicly available ChIP-seq experiments with gene-expression data from tissue-specific RNA-seq experiments. Our GGM approach identifies high confidence transcription factor (TF)–gene interactions and annotates the interactions with information on mode of regulation (activation vs. repression). Benchmarks against manually curated databases of TF–gene interactions show that our method can accurately detect mode of regulation. We demonstrate the ability of our platform to identify active transcriptional regulators by using controlled in vitro overexpression and stem-cell differentiation studies and utilize our method to investigate transcriptional mechanisms of fibroblast phenotypic plasticity.

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