Huntington disease (HD) is the most common neurogenetic disorder caused by expansion of the CAG repeat in the HTT gene; nevertheless, the molecular bases of the disease are not fully understood. Non-coding RNAs have demonstrated to be involved in the physiopathology of HD. However, the role of circRNAs has not been investigated. The aim of this study was to identify the circRNAs with differential expression in a murine cell line model of HD and to identify the biological pathways regulated by the differentially expressed circRNAs. CircRNA expression was analyzed through a microarray, which specifically detects circular species of RNA. The expression patterns between a murine cell line expressing mutant Huntingtin and cells expressing wild-type Huntingtin were compared. We predicted the miRNAs with binding sites for the differentially expressed circRNAs and the corresponding target genes for those miRNAs. Using the target genes, we performed a function enrichment analysis. We identified 23 circRNAs differentially expressed, 19 downregulated and four upregulated. Most of the downregulated circRNAs derive from the Rere gene. The dopaminergic synapse, MAPK, and long-term depression pathways were significantly enriched. The three identified pathways have been previously associated with the physiopathology of HD. The understanding of the circRNA-miRNA-mRNA network involved in the molecular mechanisms driving HD can lead us to identify novel biomarkers and potential therapeutic targets. To the best of our knowledge, this is the first study analyzing circRNAs in a model of Huntington disease.

亨廷顿病 (HD) 是由HTT中 CAG 重复序列扩增引起的最常见的神经遗传疾病基因; 然而，该疾病的分子基础尚未完全清楚。非编码 RNA 已被证明与 HD 的生理病理学有关。然而，尚未研究circRNA的作用。本研究的目的是鉴定 HD 小鼠细胞系模型中差异表达的 circRNA，并确定差异表达的 circRNA 调控的生物学通路。CircRNA 表达通过微阵列进行分析，该微阵列专门检测环状 RNA。比较了表达突变亨廷顿蛋白的鼠细胞系和表达野生型亨廷顿蛋白的细胞之间的表达模式。我们预测了具有差异表达 circRNA 结合位点的 miRNA 和这些 miRNA 的相应靶基因。使用目标基因，我们进行了功能丰富分析。我们鉴定了 23 个差异表达的 circRNA，19 个下调和 4 个上调。大多数下调的 circRNA 来源于雷基因。多巴胺能突触、MAPK 和长期抑郁通路显着丰富。三个已确定的途径以前与 HD 的病理生理学有关。对参与驱动 HD 的分子机制的 circRNA-miRNA-mRNA 网络的理解可以引导我们识别新的生物标志物和潜在的治疗靶点。据我们所知，这是第一项在亨廷顿病模型中分析 circRNA 的研究。