Department of Behavioral Neuroscience, Oregon Health & Science University, Portland, Oregon.
Integrated Genomics Laboratory, Oregon Health & Science University, Portland, Oregon.
Alcohol Clin Exp Res. 2018 Aug;42(8):1454-1465. doi: 10.1111/acer.13777. Epub 2018 Jun 22.
Transcriptional differences between heterogeneous stock mice and high drinking-in-the-dark selected mouse lines have previously been described based on microarray technology coupled with network-based analysis. The network changes were reproducible in 2 independent selections and largely confined to 2 distinct network modules; in contrast, differential expression appeared more specific to each selected line. This study extends these results by utilizing RNA-Seq technology, allowing evaluation of the relationship between genetic risk and transcription of noncoding RNA (ncRNA); we additionally evaluate sex-specific transcriptional effects of selection.
Naïve mice (N = 24/group and sex) were utilized for gene expression analysis in the ventral striatum; the transcriptome was sequenced with the Illumina HiSeq platform. Differential gene expression and the weighted gene co-expression network analysis were implemented largely as described elsewhere, resulting in the identification of genes that change expression level or (co)variance structure.
Across both sexes, we detect selection effects on the extracellular matrix and synaptic signaling, although the identity of individual genes varies. A majority of nc RNAs cluster in a single module of relatively low density in both the male and female network. The most strongly differentially expressed transcript in both sexes was Gm22513, a small nuclear RNA with unknown function. Associated with selection, we also found a number of network hubs that change edge strength and connectivity. At the individual gene level, there are many sex-specific effects; however, at the annotation level, results are more concordant.
In addition to demonstrating sex-specific effects of selection on the transcriptome, the data point to the involvement of extracellular matrix genes as being associated with the binge drinking phenotype.
先前基于微阵列技术结合网络分析,描述了异质 stock 小鼠和高暗饮选择小鼠系之间的转录差异。网络变化在 2 个独立选择中具有重现性,并且主要局限于 2 个不同的网络模块;相比之下,差异表达似乎更特定于每个选择的线。本研究通过利用 RNA-Seq 技术扩展了这些结果,允许评估遗传风险与非编码 RNA(ncRNA)转录之间的关系;我们还评估了选择的性别特异性转录效应。
利用 naïve 小鼠(每组 24 只,雌雄各半)进行腹侧纹状体的基因表达分析;利用 Illumina HiSeq 平台对转录组进行测序。差异基因表达和加权基因共表达网络分析主要按照其他地方的描述进行,导致鉴定出表达水平或(共)方差结构变化的基因。
在两性中,我们都检测到了对细胞外基质和突触信号传递的选择效应,尽管个别基因的身份不同。大多数 ncRNA 在雄性和雌性网络中都聚集在一个相对密度较低的单一模块中。在两性中差异表达最显著的转录物是 Gm22513,一种具有未知功能的小核 RNA。与选择相关的是,我们还发现了许多网络枢纽,它们改变了边缘强度和连通性。在个体基因水平上,存在许多性别特异性效应;然而,在注释水平上,结果更为一致。
除了证明选择对转录组的性别特异性影响外,这些数据还表明细胞外基质基因的参与与狂欢饮酒表型有关。