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AddictGene: An integrated knowledge base for differentially expressed genes associated with addictive substance
Shi, Leisheng1,2; Wang, Yan1; Li, Chong1,2; Zhang, Kunlin1; Du, Quansheng3; Zhao, Mei1,2
第一作者Shi, Leisheng
通讯作者邮箱zhaomei@psych.ac.cn (m. zhao)
心理所单位排序1
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.

关键词Drug dependence Gene expression Drug abuse Database Addiction
2021
DOI10.1016/j.csbj.2021.04.027
发表期刊Computational and Structural Biotechnology Journal
ISSN2001-0370
卷号19页码:2416-2422
期刊论文类型实证研究
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
Q分类Q1
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
被引频次:3[WOS]   [WOS记录]     [WOS相关记录]
文献类型期刊论文
条目标识符https://ir.psych.ac.cn/handle/311026/38849
专题中国科学院心理健康重点实验室
作者单位1.CAS Key Laboratory of Mental Health, Institute of Psychology, Chinese Academy of Sciences, Beijing; 100101, China
2.University of Chinese Academy of Sciences, Beijing; 101408, China
3.Department of Life Sciences, National Natural Science Foundation of China, Beijing; 100085, China
第一作者单位中国科学院心理研究所
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.
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