1.Role of microRNAs in endothelial function.
Xian-bing CHEN ; Si-dao ZHENG ; Hong-jin WU
Chinese Medical Journal 2013;126(9):1779-1786
2.Function of microRNAs in development of immune system and in regulation of immune response.
Qing-yun CHEN ; Qing-qing WANG
Journal of Zhejiang University. Medical sciences 2010;39(3):326-332
microRNAs function as effective molecules in regulation of many biological functions of organisms; in most case they regulate gene expression moderately. Emerging evidence suggests that microRNAs play a key role in the regulation of immunological functions including innate and adaptive immune responses. The research on microRNAs would be helpful in elucidation of the mechanisms of human immune system and in development of potential therapies based on microRNAs.
Gene Expression Regulation
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Humans
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Immune System
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physiology
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MicroRNAs
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genetics
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physiology
3.Pathways of flowering regulation in plants.
Yongping LIU ; Jing YANG ; Mingfeng YANG
Chinese Journal of Biotechnology 2015;31(11):1553-1566
Flowering, the floral transition from vegetative growth to reproductive growth, is induced by diverse endogenous and exogenous cues, such as photoperiod, temperature, hormones and age. Precise flowering time is critical to plant growth and evolution of species. The numerous renewal molecular and genetic results have revealed five flowering time pathways, including classical photoperiod pathway, vernalization pathway, autonomous pathway, gibberellins (GA) pathway and newly identified age pathway. These pathways take on relatively independent role, and involve extensive crosstalks and feedback loops. This review describes the complicated regulatory network of this floral transition to understand the molecular mechanism of flowering and provide references for further research in more plants.
Arabidopsis
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physiology
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Flowers
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physiology
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Gene Expression Regulation, Plant
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Gene Regulatory Networks
4.The study on the interleukin-8 (IL-8).
Wensheng ZHANG ; Huaiqing CHEN
Journal of Biomedical Engineering 2002;19(4):697-702
Interleukin-8 (IL-8), which is a member of C-X-C chemokine subfamily, is an important activator and chemoattractant for neutrophils and has been implicated in a variety of inflammatory diseases. Numerous reports show that various cells express IL-8 mRNA and produce IL-8 protein rapidly, including monocytes, T lymphocytes, neutrophils, fibroblasts, endothelial cells and epithelial cells. The human IL-8 gene has a length of 5191 bp and contains four exons separated by three introns. It maps to human chromosome 4q12-q21. The mRNA consists of a 101 bases 5' untranslated region, an open reading frame of 297 bases, and a long 3' untranslated region of 1.2 kb. The 5' flanking region of the IL-8 gene contains potential binding sites for several nuclear factors including activated protein-1 (AP-1), activated protein-2 (AP-2), nuclear factor-gene binding (NF-kappa B), nuclear factor-interleukin-6 (NF-IL-6, also calls CAAT/enhancer-binding proteins, C/EBP), IFN regulatory factor-1 (IRF-1), hepatocyte nuclear factor-1 (HNF-1), and so on. IL-8 gene expression is regulated initially at the level of gene transcription. The rapid induction of IL-8 gene expression is likely mediated by latent transcription factors that bind the IL-8 promoter. AP-1 and NF-IL-6 physically interact with NF-kappa B, and functional cooperativity among these factors appears to be critical for optimal IL-8 promoter activity in different cell types. The IL-8 receptor (IL-8R) is a dimeric glycoprotein consisting of a 59 KDa and a 67 KDa subunit. It has been given the name CDw128. It is expressed in many different cell types including those not responding to IL-8. The receptor density is approximately 20,000/cell in neutrophils, 1,040/cell in monocytes, and 300/cell in T-lymphocytes. The IL-8R is a member of the family of G-protein-coupled receptors. There are at least two different IL-8 receptor types (CXCR1 and CXCR2). The activities of IL-8 are not species-specific. IL-8 affects the adhesion of neutrophils to the endothelium and induces the transendothelial migration of neutrophils. IL-8 also exhibits in vitro chemotactic activities against of T-lymphocytes and basophils. IL-8 gene expression can be regulated by fluid shear stress, which may play an important role in the genesis and development of both inflammation and arterosclerosis.
Gene Expression Regulation
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Interleukin-8
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chemistry
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genetics
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physiology
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Receptors, Interleukin
5.Progress in research on genetic variations in miRNA regulatory pathway.
Zhen GUO ; Honghao ZHOU ; Wei ZHANG
Chinese Journal of Medical Genetics 2015;32(1):109-112
MicroRNAs (miRNAs) are a class of highly conserved small noncoding RNAs which can regulate gene expression by post-transcriptional degradation or translational repression. miRNAs are involved in the regulation of cell apoptosis, proliferation, differentiation and other physiological processes, and are closely related with development of cancer. More recently, it has been proposed that the presence of genetic variations in microRNA genes, their biogenesis pathway and target binding sites can affect the miRNA processing machinery and targeting, therefore have a significant genetic effect. Since polymorphisms in a miRNA regulatory pathway can result in the loss or gain of a miRNA function and can affect the expression of hundreds of genes, more and more evidence suggested a strong association of miRNA polymorphisms with disease progression, diagnosis and prognosis. Whether in the pathogenesis research of complex diseases or finding biomarkers for diagnosis and prognosis, polymorphisms in the miRNA regulatory pathway have an extremely important value for research.
Animals
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Gene Expression Regulation
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Genetic Variation
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Humans
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MicroRNAs
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genetics
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physiology
6.Microarray and proteomic analysis of brassinosteroid- and gibberellin-regulated gene and protein expression in rice.
Guangxiao YANG ; Setsuko KOMATSU
Genomics, Proteomics & Bioinformatics 2004;2(2):77-83
Brassinosteroid (BR) and gibberellin (GA) are two groups of plant growth regulators essential for normal plant growth and development. To gain insight into the molecular mechanism by which BR and GA regulate the growth and development of plants, especially the monocot plant rice, it is necessary to identify and analyze more genes and proteins that are regulated by them. With the availability of draft sequences of two major types, japonica and indica rice, it has become possible to analyze expression changes of genes and proteins at genome scale. In this review, we summarize rice functional genomic research by using microarray and proteomic approaches and our recent research results focusing on the comparison of cDNA microarray and proteomic analyses of BR- and GA-regulated gene and protein expression in rice. We believe our findings have important implications for understanding the mechanism by which BR and GA regulate the growth and development of rice.
Gene Expression Profiling
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Gene Expression Regulation, Plant
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physiology
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Gibberellins
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metabolism
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Oligonucleotide Array Sequence Analysis
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Oryza
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genetics
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physiology
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Proteomics
7.Application of nutrigenomics in clinical nutrition.
Gui-zhen HE ; Xiao-yu CUI ; Liang-guang DONG
Acta Academiae Medicinae Sinicae 2006;28(6):853-857
In the past decade, the focus of nutritional study shifted from epidemiology and physiology to molecular biology. Advanced research strategies and technologies including genomics, transcriptomics, proteomics, metabolomics, and system biology have been gradually applied in clinical nutrition. This article reviews the effects of nutrients on gene expressions, application of modern molecular biology in clinical nutrition, as well as the advances and challenges in recent years..
Amino Acids
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physiology
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Carbohydrates
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physiology
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Gene Expression Regulation
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Genomics
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Humans
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Nutritional Physiological Phenomena
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Proteomics
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Vitamins
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physiology
8.Construction and analysis of subtractive cDNA library of Phellodendron amurense under drought stress.
Huimei WANG ; Yanbing WANG ; Yuangang ZU ; Lianhui SUN
Chinese Journal of Biotechnology 2008;24(2):198-202
With cDNA from Phellodendron amurense seedlings treated with drought stress as tester and cDNA from this plant in normal growth as driver, we construct cDNA subtracted library using suppression subtractive hybridization (SSH). In the library, the rate of recombination was 95%, the size of inserts was 300-800 bp. Two hundred and sixty-five new genes were obtained by DNA sequencing 816 positive clones picked randomly, and partitioned to 16 classes after nucleotide Blast and BlastX homological analysis against NT, NR, SWISSPROT, KEGG database. Forty-four drought stress associated genes, such as heat shock protein cognate 70, dehydration responsive protein 22, universal stress protein, metallothionein II, late embryogenesis abundant protein, were obtained, which made 16.6% of the overall genes. These genes included osmotic regulator, signal component regulatory protein and antioxidant enzyme. The research had established a basis for cloning stress resistance genes and further studying genes expression in P. amurense seedlings under drought stress.
Adaptation, Physiological
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genetics
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Cloning, Molecular
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Droughts
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Gene Expression
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Gene Expression Profiling
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Gene Library
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Nucleic Acid Hybridization
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methods
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Phellodendron
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genetics
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growth & development
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physiology
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Seedlings
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genetics
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physiology
9.Gene Regulatory Network Analysis for Triple-Negative Breast Neoplasms by Using Gene Expression Data.
Hee Chan JUNG ; Sung Hwan KIM ; Jeong Hoon LEE ; Ju Han KIM ; Sung Won HAN
Journal of Breast Cancer 2017;20(3):240-245
PURPOSE: To better identify the physiology of triple-negative breast neoplasm (TNBN), we analyzed the TNBN gene regulatory network using gene expression data. METHODS: We collected TNBN gene expression data from The Cancer Genome Atlas to construct a TNBN gene regulatory network using least absolute shrinkage and selection operator regression. In addition, we constructed a triple-positive breast neoplasm (TPBN) network for comparison. Furthermore, survival analysis based on gene expression levels and differentially expressed gene (DEG) analysis were carried out to support and compare the network analysis results, respectively. RESULTS: The TNBN gene regulatory network, which followed a power-law distribution, had 10,237 vertices and 17,773 edges, with an average vertex-to-vertex distance of 8.6. The genes ZDHHC20 and RAPGEF6 were identified by centrality analysis to be important vertices. However, in the DEG analysis, we could not find meaningful fold changes in ZDHHC20 and RAPGEF6 between the TPBN and TNBN gene expression data. In the multivariate survival analysis, the hazard ratio for ZDHHC20 and RAPGEF6 was 1.677 (1.192–2.357) and 1.676 (1.222–2.299), respectively. CONCLUSION: Our TNBN gene regulatory network was a scale-free one, which means that the network would be easily destroyed if the hub vertices were attacked. Thus, it is important to identify the hub vertices in the network analysis. In the TNBN gene regulatory network, ZDHHC20 and RAPGEF6 were found to be oncogenes. Further study of these genes could help to reveal a novel method for treating TNBN in the future.
Breast Neoplasms
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Gene Expression*
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Gene Regulatory Networks*
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Genome
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Methods
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Oncogenes
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Physiology
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Triple Negative Breast Neoplasms*
10.Gene locations may contribute to predicting gene regulatory relationships.
Jun MENG ; Wen-Yuan XU ; Xiao CHEN ; Tao LIN ; Xiao-Yu DENG
Journal of Zhejiang University. Science. B 2018;19(1):25-37
We propose that locations of genes on chromosomes can contribute to the prediction of gene regulatory relationships. We constructed a time-based gene regulatory network of zebrafish cardiogenesis on the basis of a spatio-temporal neighborhood method. Through the network, specific regulatory pathways and order of gene expression during zebrafish cardiogenesis were obtained. By comparing the order with locations of these genes on chromosomes, we discovered that there exists a reversal phenomenon between the order and order of gene locations. The discovery provides an inherent rule to instruct exploration of gene regulatory relationships. Specifically, the discovery can help to predict if regulatory relationships between genes exist and contribute to evaluating the correctness of discovered gene regulatory relationships.
Algorithms
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Animals
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Chromosome Mapping
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Chromosomes
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Gene Expression
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Gene Regulatory Networks
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Heart/physiology*
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Zebrafish/genetics*