The relationship between cuticular lipids and associated gene expression in above ground organs of Thellungiella salsugineum (Pall.) Al-Shehbaz & Warwick

Plant Science ◽  
2019 ◽  
Vol 287 ◽  
pp. 110200
Author(s):  
Xiaojing Xu ◽  
Kun Xue ◽  
Shuai Tang ◽  
Junqing He ◽  
Buerbatu Song ◽  
...  
Keyword(s):  
Gene Expression ◽  
Cuticular Lipids ◽  
The Relationship

scholarly journals Endolysosomal Cation Channels and MITF in Melanocytes and Melanoma

Biomolecules ◽  
2021 ◽  
Vol 11 (7) ◽  
pp. 1021
Author(s):  
Carla Abrahamian ◽  
Christian Grimm
Keyword(s):  
Breast Cancer ◽  
Gene Expression ◽  
Transcription Factor ◽  
Convincing Evidence ◽  
Signaling Cascades ◽  
Cation Channels ◽  
Pore Channel ◽  
Different Types ◽  
Canonical Wnt ◽  
The Relationship

Microphthalmia-associated transcription factor (MITF) is the principal transcription factor regulating pivotal processes in melanoma cell development, growth, survival, proliferation, differentiation and invasion. In recent years, convincing evidence has been provided attesting key roles of endolysosomal cation channels, specifically TPCs and TRPMLs, in cancer, including breast cancer, glioblastoma, bladder cancer, hepatocellular carcinoma and melanoma. In this review, we provide a gene expression profile of these channels in different types of cancers and decipher their roles, in particular the roles of two-pore channel 2 (TPC2) and TRPML1 in melanocytes and melanoma. We specifically discuss the signaling cascades regulating MITF and the relationship between endolysosomal cation channels, MAPK, canonical Wnt/GSK3 pathways and MITF.

scholarly journals Study on the Relationship between the miRNA-centered ceRNA Regulatory Network and Fatigue

2021 ◽  
Author(s):  
Xingzhe Yang ◽  
Feng Li ◽  
Jie Ma ◽  
Yan Liu ◽  
Xuejiao Wang ◽  
...  
Keyword(s):  
Gene Expression ◽  
Gene Regulatory Network ◽  
Regulatory Network ◽  
Hot Spot ◽  
Genetic Research ◽  
Noncoding Rnas ◽  
Messenger Rnas ◽  
Effective Prevention ◽  
Gene Regulatory ◽  
The Relationship

AbstractIn recent years, the incidence of fatigue has been increasing, and the effective prevention and treatment of fatigue has become an urgent problem. As a result, the genetic research of fatigue has become a hot spot. Transcriptome-level regulation is the key link in the gene regulatory network. The transcriptome includes messenger RNAs (mRNAs) and noncoding RNAs (ncRNAs). MRNAs are common research targets in gene expression profiling. Noncoding RNAs, including miRNAs, lncRNAs, circRNAs and so on, have been developed rapidly. Studies have shown that miRNAs are closely related to the occurrence and development of fatigue. MiRNAs can regulate the immune inflammatory reaction in the central nervous system (CNS), regulate the transmission of nerve impulses and gene expression, regulate brain development and brain function, and participate in the occurrence and development of fatigue by regulating mitochondrial function and energy metabolism. LncRNAs can regulate dopaminergic neurons to participate in the occurrence and development of fatigue. This has certain value in the diagnosis of chronic fatigue syndrome (CFS). CircRNAs can participate in the occurrence and development of fatigue by regulating the NF-κB pathway, TNF-α and IL-1β. The ceRNA hypothesis posits that in addition to the function of miRNAs in unidirectional regulation, mRNAs, lncRNAs and circRNAs can regulate gene expression by competitive binding with miRNAs, forming a ceRNA regulatory network with miRNAs. Therefore, we suggest that the miRNA-centered ceRNA regulatory network is closely related to fatigue. At present, there are few studies on fatigue-related ncRNA genes, and most of these limited studies are on miRNAs in ncRNAs. However, there are a few studies on the relationship between lncRNAs, cirRNAs and fatigue. Less research is available on the pathogenesis of fatigue based on the ceRNA regulatory network. Therefore, exploring the complex mechanism of fatigue based on the ceRNA regulatory network is of great significance. In this review, we summarize the relationship between miRNAs, lncRNAs and circRNAs in ncRNAs and fatigue, and focus on exploring the regulatory role of the miRNA-centered ceRNA regulatory network in the occurrence and development of fatigue, in order to gain a comprehensive, in-depth and new understanding of the essence of the fatigue gene regulatory network.

scholarly journals The Relationship among Gene Expression, the Evolution of Gene Dosage, and the Rate of Protein Evolution

PLoS Genetics ◽  
2010 ◽  
Vol 6 (5) ◽  
pp. e1000944 ◽  
Author(s):  
Jean-François Gout ◽  
Daniel Kahn ◽  
Laurent Duret ◽  
Keyword(s):  
Gene Expression ◽  
Protein Evolution ◽  
Gene Dosage ◽  
The Relationship

scholarly journals H3 K79 dimethylation marks developmental activation of the β-globin gene but is reduced upon LCR-mediated high-level transcription

Blood ◽  
2008 ◽  
Vol 112 (2) ◽  
pp. 406-414 ◽  
Author(s):  
Tomoyuki Sawado ◽  
Jessica Halow ◽  
Hogune Im ◽  
Tobias Ragoczy ◽  
Emery H. Bresnick ◽  
...  
Keyword(s):  
Gene Expression ◽  
Transcriptional Activation ◽  
Globin Gene ◽  
Erythroid Differentiation ◽  
Genome Wide ◽  
Activation Of Transcription ◽  
High Level ◽  
The Relationship ◽  
Mutant Genes ◽  
Gene Expression Levels

Abstract Genome-wide analyses of the relationship between H3 K79 dimethylation and transcription have revealed contradictory results. To clarify this relationship at a single locus, we analyzed expression and H3 K79 modification levels of wild-type (WT) and transcriptionally impaired β-globin mutant genes during erythroid differentiation. Analysis of fractionated erythroid cells derived from WT/Δ locus control region (LCR) heterozygous mice reveals no significant H3 K79 dimethylation of the β-globin gene on either allele prior to activation of transcription. Upon transcriptional activation, H3 K79 di-methylation is observed along both WT and ΔLCR alleles, and both alleles are located in proximity to H3 K79 dimethylation nuclear foci. However, H3 K79 di-methylation is significantly increased along the ΔLCR allele compared with the WT allele. In addition, analysis of a partial LCR deletion mutant reveals that H3 K79 dimethylation is inversely correlated with β-globin gene expression levels. Thus, while our results support a link between H3 K79 dimethylation and gene expression, high levels of this mark are not essential for high level β-globin gene transcription. We propose that H3 K79 dimethylation is destabilized on a highly transcribed template.

scholarly journals HLF is a Potential Prognostic Biomarker in Head and Neck Squamous Cell Carcinoma Based on Bioinformatic Analysis and Experimental Validation

2021 ◽  
Author(s):  
Wei Fang ◽  
Di Wan ◽  
Jun Chen ◽  
Weiqun Ma ◽  
Zhen Luo ◽  
...  
Keyword(s):  
Gene Expression ◽  
Cell Culture ◽  
Squamous Cell Carcinoma ◽  
Cell Carcinoma ◽  
Squamous Cell ◽  
Poor Prognosis ◽  
Prognostic Biomarker ◽  
Neck Squamous Cell Carcinoma ◽  
Rt Pcr ◽  
The Relationship

Abstract BackgroundHead and neck squamous cell carcinoma (HNSCC) is one of the most frequent cancers worldwide, with an increasing incidence. However, the underlying molecular mechanisms of HNSCC are poorly understood.MethodIn this work, 5 original datasets (GSE23558, GSE13601, GSE30784, GSE9844, GSE78060) of Head and neck squamous cell carcinoma (HNSCC) were selected from Gene Expression Omnibus (GEO) database. To identify differentially expressed genes (DEGs) in HNSCC and adjacent tissues. The common DEGs were acquired by Venn diagram. The sensitivity and specificity of HLF were determined by Receiver operating characteristic curves (ROC). Then, In order to further confirm the relationship between HLF and HNSCC patient’s prognosis, the expression and survival analysis of HLF was performed by Gene Expression Profiling Interactive Analysis (GEPIA), Cell culture, reverse transcription polymerase chain reaction (RT-PCR), western blotting and immunohistochemical staining.ResultsSeventeen DEGs were screened from five sets of HNSCC functional gene expression series in GEO datasets. The low expression of HLF was indicated might be correlated with poor prognosis of HNSCC patients based on the bioinformatics analysis. According to the results of Cell culture, RT-PCR, western blotting, immunohistochemical staining, it was confirmed that the low level of HLF expression correlated with poor prognosis of HNSCC patients.ConclusionThe study effectively revealed useful information about the relationship of the low level of HLF expression and HNSCC. In summary, we identified HLF as a potential prognostic biomarker and therapeutic target for HNSCC.

scholarly journals Leveraging DNA methylation quantitative trait loci to characterize the relationship between methylomic variation, gene expression and complex traits

2018 ◽  
Author(s):  
Eilis Hannon ◽  
Tyler J Gorrie-Stone ◽  
Melissa C Smart ◽  
Joe Burrage ◽  
Amanda Hughes ◽  
...  
Keyword(s):  
Gene Expression ◽  
Dna Methylation ◽  
Genetic Variation ◽  
Quantitative Trait Loci ◽  
Quantitative Trait ◽  
Complex Traits ◽  
Common Genetic Variation ◽  
Online Data ◽  
The Relationship ◽  
Methylation Quantitative Trait Loci

ABSTRACTCharacterizing the complex relationship between genetic, epigenetic and transcriptomic variation has the potential to increase understanding about the mechanisms underpinning health and disease phenotypes. In this study, we describe the most comprehensive analysis of common genetic variation on DNA methylation (DNAm) to date, using the Illumina EPIC array to profile samples from the UK Household Longitudinal study. We identified 12,689,548 significant DNA methylation quantitative trait loci (mQTL) associations (P < 6.52x10-14) occurring between 2,907,234 genetic variants and 93,268 DNAm sites, including a large number not identified using previous DNAm-profiling methods. We demonstrate the utility of these data for interpreting the functional consequences of common genetic variation associated with > 60 human traits, using Summary data–based Mendelian Randomization (SMR) to identify 1,662 pleiotropic associations between 36 complex traits and 1,246 DNAm sites. We also use SMR to characterize the relationship between DNAm and gene expression, identifying 6,798 pleiotropic associations between 5,420 DNAm sites and the transcription of 1,702 genes. Our mQTL database and SMR results are available via a searchable online database (http://www.epigenomicslab.com/online-data-resources/) as a resource to the research community.

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