Cell-Type Specific Gene Regulation of Tyrosine Hydroxylase in the Central Nervous System

Author(s):  
Yoshinori Shimizu ◽  
Shuei Sugama ◽  
Byung Pil Cho ◽  
Tong H. Joh
1997 ◽  
Vol 69 (9) ◽  
pp. 1903-1910 ◽  
Author(s):  
T. Tai ◽  
Ikuo Kawashima ◽  
H. Ozawa ◽  
Masaharu Kotani ◽  
K. Ogura

2021 ◽  
Vol 22 (4) ◽  
pp. 1587
Author(s):  
Nuri Song ◽  
Da Yeon Jeong ◽  
Thai Hien Tu ◽  
Byong Seo Park ◽  
Hye Rim Yang ◽  
...  

Adiponectin, an adipose tissue-derived hormone, plays integral roles in lipid and glucose metabolism in peripheral tissues, such as the skeletal muscle, adipose tissue, and liver. Moreover, it has also been shown to have an impact on metabolic processes in the central nervous system. Astrocytes comprise the most abundant cell type in the central nervous system and actively participate in metabolic processes between blood vessels and neurons. However, the ability of adiponectin to control nutrient metabolism in astrocytes has not yet been fully elucidated. In this study, we investigated the effects of adiponectin on multiple metabolic processes in hypothalamic astrocytes. Adiponectin enhanced glucose uptake, glycolytic processes and fatty acid oxidation in cultured primary hypothalamic astrocytes. In line with these findings, we also found that adiponectin treatment effectively enhanced synthesis and release of monocarboxylates. Overall, these data suggested that adiponectin triggers catabolic processes in astrocytes, thereby enhancing nutrient availability in the hypothalamus.


2019 ◽  
Author(s):  
Cheynna Crowley ◽  
Yuchen Yang ◽  
Yunjiang Qiu ◽  
Benxia Hu ◽  
Armen Abnousi ◽  
...  

AbstractHi-C experiments have been widely adopted to study chromatin spatial organization, which plays an essential role in genome function. We have recently identified frequently interacting regions (FIREs) and found that they are closely associated with cell-type-specific gene regulation. However, computational tools for detecting FIREs from Hi-C data are still lacking. In this work, we present FIREcaller, a stand-alone, user-friendly R package for detecting FIREs from Hi-C data. FIREcaller takes raw Hi-C contact matrices as input, performs within-sample and cross-sample normalization, and outputs continuous FIRE scores, dichotomous FIREs, and super-FIREs. Applying FIREcaller to Hi-C data from various human tissues, we demonstrate that FIREs and super-FIREs identified, in a tissue-specific manner, are closely related to gene regulation, are enriched for enhancer-promoter (E-P) interactions, tend to overlap with regions exhibiting epigenomic signatures of cis-regulatory roles, and aid the interpretation or GWAS variants. The FIREcaller package is implemented in R and freely available at https://yunliweb.its.unc.edu/FIREcaller.Highlights– Frequently Interacting Regions (FIREs) can be used to identify tissue and cell-type-specific cis-regulatory regions.– An R software, FIREcaller, has been developed to identify FIREs and clustered FIREs into super-FIREs.


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