Next Generation Sequencing for Long Non-coding RNAs Profile for CD4+ T Cells in the Mouse Model of Acute Asthma
Next Generation Sequencing for Long Non-coding RNAs Profile for CD4+ T Cells in the Mouse Model of Acute Asthma
复制标题
急性哮喘小鼠模型中 CD4( ) T 细胞的长非编码 RNA 谱的下一代测序
DOI：
10.3389/fgene.2019.00545
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发表时间：
2019-06-07
影响因子：
3.7
通讯作者：
Zhang, Mingshun
中科院分区：
文献类型：
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作者：
Wang, Zhengxia;Ji, Ningfei;Zhang, Mingshun
背景和目的：虽然长链非编码RNA（lncRNA）与包括哮喘在内的许多疾病有关，但人们对哮喘中CD4（+）T细胞的lncRNA转录组知之甚少。本研究旨在探讨急性哮喘小鼠模型CD4+T细胞中的lncRNA谱。方法：对哮喘小鼠和对照小鼠的CD4+T细胞进行lncRNA和mRNA的新一代测序。进行基因本体论（GO）和京都基因和基因组百科全书（KEGG）通路分析来预测异常lncRNA的功能和信号通路。使用定量实时PCR（聚合酶链式反应）进一步测量所选的lncRNA，并通过荧光原位杂交（FISH）进行观察。通过 Pearson 相关系数和 Cytoscape 3.6 构建 IncRNA-mRNA 共表达网络。结果：新一代测序显示，与对照组相比，急性哮喘中有 36 个上调的 lncRNA 和 98 个下调的 lncRNA。 KEGG通路分析显示细胞因子-细胞因子受体相互作用具有最高的富集分数。构建了一个共表达网络，其中 23 个 lncRNA 和 301 个 mRNA 发生改变，形成总共 12424 个 lncRNA 和 mRNA 对。为了验证 RNA 测序结果，我们使用 qPCR 测量了 4 种不同的 lncRNA。哮喘 CD4+ T 细胞中 lncRNA fantom3_9230106C11 显着减少。生物信息学分析表明lncRNA fantom3_9230106C11具有与Th2分化相关的多种miRNA和转录因子相互作用的潜力。结论：本研究为哮喘中CD4+T细胞lncRNA的不同表达提供了第一个证据，并可作为进一步、更大规模的哮喘分子lncRNA功能深入分析的模板。
Background and Aims: Although long non-coding RNAs (lncRNAs) have been linked to many diseases including asthma, little is known about lncRNA transcriptomes of CD4(+) T cells in asthma. The present study aimed to explore the lncRNAs profile in the CD4(+)T cells from the mouse model of acute asthma.Methods: Next generation sequencing for lncRNAs and mRNAs was performed on CD4+T- cells from asthma and control mice. Gene ontology (GO) and kyoto encyclopedia of genes and genomes (KEGG) pathway analyses were performed to predict the functions and signal pathways for the aberrant lncRNAs. The selected lncRNAs were further measured using quantitative real-time PCR (polymerase chain reaction) and observed in the fluorescence in situ hybridization (FISH). The IncRNA-mRNA co-expression network was constructed via Pearson's correlation coefficient and Cytoscape 3.6.Results: Next generation sequencing revealed 36 up-regulated lncRNAs and 98 down-regulated lncRNAs in acute asthma compared with controls. KEGG pathway analysis showed that cytokine-cytokine receptor interaction had the highest enrichment scores. A co-expression network was constructed in which 23 lncRNAs and 301 mRNAs altered formed a total of 12424 lncRNA and mRNA pairs. To validate the RNA sequencing results, we measured the 4 different lncRNAs using qPCR. The lncRNA fantom3_9230106C11 was significantly reduced in CD4+ T cells of asthma. Bioinformatics analysis showed that lncRNA fantom3_9230106C11 had the potential to interact with many miRNAs and transcription factors related to Th2 differentiation.Conclusion: This study provided the first evidence for different expression of lncRNAs of CD4+T cells in asthma and may serve as a template for further, larger functional in-depth analyses regarding asthma molecular lncRNAs.