Shi Leisheng, Wang Yan, Li Chong, Zhang Kunlin, Du Quansheng, Zhao Mei
CAS Key Laboratory of Mental Health, Institute of Psychology, Chinese Academy of Sciences, Beijing 100101, China.
University of Chinese Academy of Sciences, Beijing 101408, China.
Comput Struct Biotechnol J. 2021 Apr 19;19:2416-2422. doi: 10.1016/j.csbj.2021.04.027. eCollection 2021.
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 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.
成瘾是一种大脑可塑性适应不良的疾病,与众多基因表达的变化有关。如今,关于成瘾性物质诱导基因表达的高通量测序数据已广泛可得。因此,有必要建立一个资源库,用于全面注释那些因常见滥用物质而表现出差异表达的基因。于是,我们通过整合基因表达、基因-基因相互作用、基因-药物相互作用以及表观遗传调控注释,开发了AddictGene,该资源库涵盖了与7种常见滥用物质(包括酒精、尼古丁、可卡因、吗啡、海洛因、甲基苯丙胺和苯丙胺)相关的70156多个差异表达基因,涉及三个物种(人类、小鼠、大鼠)。我们还通过RT-PCR、Northern印迹和杂交等技术收集了1141个经实验验证的成瘾相关基因。AddictGene易于使用的网络界面(http://159.226.67.237/sun/addictgedb/)允许用户搜索和浏览他们感兴趣的差异表达基因的多维数据:1)从原始研究中提取的详细基因特异性信息;2)从NCBI中提取的特定基因的基本信息;3)与物质依赖和其他精神疾病相关的单核苷酸多态性;4)特定基因在其他精神疾病中的表达改变;5)感兴趣基因在31种主要和54种次要人体组织中的表达模式;6)感兴趣基因的功能注释;7)参与特定基因改变的表观遗传调节因子,包括组蛋白修饰和DNA甲基化;8)与感兴趣基因功能相关的蛋白质-蛋白质相互作用;9)潜在可药用性的药物-基因相互作用。AddictGene为研究人员提供了一个宝贵的资源库,用于研究成瘾的分子机制,并可能为药物滥用和复发的潜在治疗提供有价值的见解。