AddictGene: An integrated knowledge base for differentially expressed genes associated with addictive substance

doi:10.1016/j.csbj.2021.04.027

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	AddictGene: An integrated knowledge base for differentially expressed genes associated with addictive substance
	Shi, Leisheng 1,2; Wang, Yan 1; Li, Chong 1,2; Zhang, Kunlin 1; Du, Quansheng 3; Zhao, Mei 1,2
通讯作者	Zhao, Mei(zhaomei@psych.ac.cn)
摘要	Addiction, a disorder of maladaptive brain plasticity, is associated with changes in numerous gene expressions. Nowadays, high-throughput sequencing data on addictive substance-induced gene expression have become widely available. A resource for comprehensive annotation of genes that show differential expression in response to commonly abused substances is necessary. So, we developed AddictGene by integrating gene expression, gene-gene interaction, gene-drug interaction and epigenetic regulatory annotation for over 70,156 items of differentially expressed genes associated with 7 commonly abused substances, including alcohol, nicotine, cocaine, morphine, heroin, methamphetamine, and amphetamine, across three species (human, mouse, rat). We also collected 1,141 addiction-related experimentally validated genes by techniques such as RT-PCR, northern blot and in situ hybridization. The easy-to-use web interface of AddictGene (http://159.226.67.237/sun/addictgedb/) allows users to search and browse multidimensional data on DEGs of their interest: 1) detailed gene-specific information extracted from the original studies; 2) basic information about the specific gene extracted from NCBI; 3) SNP associated with substance dependence and other psychiatry disorders; 4) expression alteration of specific gene in other psychiatric disorders; 5) expression patterns of interested gene across 31 primary and 54 secondary human tissues; 6) functional annotation of interested gene; 7) epigenetic regulators involved in the alteration of specific genes, including histone modifications and DNA methylation; 8) protein-protein interaction for functional linkage with interested gene; 9) drug-gene interaction for potential druggability. AddictGene offers a valuable repository for researchers to study the molecular mechanisms underlying addiction, and might provide valuable insights into potential therapies for drug abuse and relapse. (C) 2021 The Authors. Published by Elsevier B.V. on behalf of Research Network of Computational and Structural Biotechnology.
关键词	Drug dependence Gene expression Drug abuse Database Addiction
	2021
语种	英语
DOI	10.1016/j.csbj.2021.04.027
发表期刊	COMPUTATIONAL AND STRUCTURAL BIOTECHNOLOGY JOURNAL
ISSN	2001-0370
卷号	19 页码:2416-2422
收录类别	SCI
资助项目	National Natural Science Foundation of China[91132728] ; National Natural Science Foundation of China[31741062] ; National Natural Science Foundation of China[61401459] ; Key Laboratory of Mental Health, Institute of Psychology, Chinese Academy of Sciences
出版者	ELSEVIER
WOS关键词	NEUROPEPTIDE-Y ; MOLECULAR NEUROBIOLOGY ; TYROSINE-HYDROXYLASE ; NEUROTROPHIC FACTOR ; DNA METHYLATION ; CART PEPTIDE ; COCAINE ; ALCOHOL ; MORPHINE ; MECHANISMS
WOS研究方向	Biochemistry & Molecular Biology ; Biotechnology & Applied Microbiology
WOS类目	Biochemistry & Molecular Biology ; Biotechnology & Applied Microbiology
WOS记录号	WOS:000692620700011
资助机构	National Natural Science Foundation of China ; Key Laboratory of Mental Health, Institute of Psychology, Chinese Academy of Sciences
引用统计
文献类型	期刊论文
条目标识符	https://ir.psych.ac.cn/handle/311026/40170
通讯作者	Zhao, Mei
作者单位	1.Chinese Acad Sci, Inst Psychol, CAS Key Lab Mental Hlth, Beijing 100101, Peoples R China 2.Univ Chinese Acad Sci, Beijing 101408, Peoples R China 3.Natl Nat Sci Fdn China, Dept Life Sci, Beijing 100085, Peoples R China
推荐引用方式 GB/T 7714	Shi, Leisheng,Wang, Yan,Li, Chong,et al. AddictGene: An integrated knowledge base for differentially expressed genes associated with addictive substance[J]. COMPUTATIONAL AND STRUCTURAL BIOTECHNOLOGY JOURNAL,2021,19:2416-2422.
APA	Shi, Leisheng,Wang, Yan,Li, Chong,Zhang, Kunlin,Du, Quansheng,&Zhao, Mei.(2021).AddictGene: An integrated knowledge base for differentially expressed genes associated with addictive substance.COMPUTATIONAL AND STRUCTURAL BIOTECHNOLOGY JOURNAL,19,2416-2422.
MLA	Shi, Leisheng,et al."AddictGene: An integrated knowledge base for differentially expressed genes associated with addictive substance".COMPUTATIONAL AND STRUCTURAL BIOTECHNOLOGY JOURNAL 19(2021):2416-2422.