Hoffman Paula L, Saba Laura M, Vanderlinden Lauren A, Tabakoff Boris
Department of Pharmaceutical Sciences, Skaggs School of Pharmacy & Pharmaceutical Sciences, University of Colorado, Aurora, CO, 80045, USA.
Department of Pharmacology, University of Colorado School of Medicine, Aurora, CO, 80045, USA.
Mamm Genome. 2018 Feb;29(1-2):128-140. doi: 10.1007/s00335-017-9726-3. Epub 2017 Dec 1.
Ethyl alcohol is a toxin that, when consumed at high levels, produces organ damage and death. One way to prevent or ameliorate this damage in humans is to reduce the exposure of organs to alcohol by reducing alcohol ingestion. Both the propensity to consume large volumes of alcohol and the susceptibility of human organs to alcohol-induced damage exhibit a strong genetic influence. We have developed an integrative genetic/genomic approach to identify transcriptional networks that predispose complex traits, including propensity for alcohol consumption and propensity for alcohol-induced organ damage. In our approach, the phenotype is assessed in a panel of recombinant inbred (RI) rat strains, and quantitative trait locus (QTL) analysis is performed. Transcriptome data from tissues/organs of naïve RI rat strains are used to identify transcriptional networks using Weighted Gene Coexpression Network Analysis (WGCNA). Correlation of the first principal component of transcriptional coexpression modules with the phenotype across the rat strains, and overlap of QTLs for the phenotype and the QTLs for the coexpression modules (module eigengene QTL) provide the criteria for identification of the functionally related groups of genes that contribute to the phenotype (candidate modules). While we previously identified a brain transcriptional module whose QTL overlapped with a QTL for levels of alcohol consumption in HXB/BXH RI rat strains and 12 selected rat lines, this module did not account for all of the genetic variation in alcohol consumption. Our search for QTL overlap and correlation of coexpression modules with phenotype can, however, be applied to any organ in which the transcriptome has been measured, and this represents a holistic approach in the search for genetic contributors to complex traits. Previous work has implicated liver/brain interactions, particularly involving inflammatory/immune processes, as influencing alcohol consumption levels. We have now analyzed the liver transcriptome of the HXB/BXH RI rat panel in relation to the behavioral trait of alcohol consumption. We used RNA-Seq and microarray data to construct liver transcriptional networks, and identified a liver candidate transcriptional coexpression module that explained 24% of the genetic variance in voluntary alcohol consumption. The transcripts in this module focus attention on liver secretory products that influence inflammatory and immune signaling pathways. We propose that these liver secretory products can interact with brain mechanisms that affect alcohol consumption, and targeting these pathways provides a potential approach to reducing high levels of alcohol intake and also protecting the integrity of the liver and other organs.
乙醇是一种毒素,大量摄入时会导致器官损伤甚至死亡。在人类中,预防或减轻这种损伤的一种方法是通过减少酒精摄入量来降低器官对酒精的暴露。大量饮酒的倾向以及人体器官对酒精诱导损伤的易感性都受到强烈的遗传影响。我们开发了一种综合的遗传/基因组方法来识别导致复杂性状的转录网络,这些性状包括饮酒倾向和酒精诱导的器官损伤倾向。在我们的方法中,在一组重组近交(RI)大鼠品系中评估表型,并进行数量性状基因座(QTL)分析。使用加权基因共表达网络分析(WGCNA),利用来自未处理的RI大鼠品系的组织/器官的转录组数据来识别转录网络。转录共表达模块的第一主成分与大鼠品系间表型的相关性,以及表型的QTL与共表达模块的QTL(模块特征基因QTL)的重叠,为识别导致该表型的功能相关基因群(候选模块)提供了标准。虽然我们之前在HXB/BXH RI大鼠品系和12个选定的大鼠品系中鉴定出一个大脑转录模块,其QTL与酒精消耗水平的QTL重叠,但该模块并不能解释酒精消耗的所有遗传变异。然而,我们对QTL重叠以及共表达模块与表型相关性的搜索可以应用于任何已测量转录组的器官,这代表了一种寻找复杂性状遗传贡献者的整体方法。先前的研究表明肝脏/大脑相互作用,特别是涉及炎症/免疫过程,会影响酒精消耗水平。我们现在分析了HXB/BXH RI大鼠品系组的肝脏转录组与酒精消耗行为特征的关系。我们使用RNA测序和微阵列数据构建肝脏转录网络,并鉴定出一个肝脏候选转录共表达模块,该模块解释了自愿酒精消耗中24%的遗传变异。该模块中的转录本将注意力集中在影响炎症和免疫信号通路的肝脏分泌产物上。我们提出这些肝脏分泌产物可以与影响酒精消耗的大脑机制相互作用,针对这些通路提供了一种潜在的方法来减少高水平的酒精摄入,并保护肝脏和其他器官的完整性。