Deep characterization of blood cell miRNomes by NGS
Deep characterization of blood cell miRNomes by NGS
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DOI：
10.1007/s00018-016-2154-9
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发表时间：
2016-08-01
影响因子：
8
通讯作者：
Keller, Andreas
中科院分区：
文献类型：
--
作者：
Schwarz, Eva C.;Backes, Christina;Keller, Andreas
系统地了解影响细胞类型特异性 microRNA 图谱的不同因素对于最先进的生物标志物研究至关重要。我们对技术重复中不同细胞类型和不同分离方法的生物变异性和细胞类型模式随时间的变化进行了全面分析。上述参数的所有组合均已测量，产生了 108 个 miRNA 谱，并通过下一代测序进行评估。最大的 miRNA 变异性是由于个体差异 (34%)，其次是细胞类型 (23.4%) 和分离技术 (17.2%)。细胞 miRNA 组成随时间的变化是中等的 (< 3 %)，接近技术变化 (< 1 %)。 CD8 细胞观察到最大的变异性（包括技术和生物学变异），而 CD3 和 CD4 细胞则表现出明显较低的变异性。方差分析强调，51.5% 的 miRNA 受到纯化技术的显着影响。虽然 CD4 细胞受影响最小，但 CD8 细胞的 miRNA 谱尤其随细胞纯化方法的不同而波动。为了让研究人员能够访问配置文件并进一步分析测试条件，我们实现了动态网络资源。
A systematic understanding of different factors influencing cell type specific microRNA profiles is essential for state-of-the art biomarker research. We carried out a comprehensive analysis of the biological variability and changes in cell type pattern over time for different cell types and different isolation approaches in technical replicates. All combinations of the parameters mentioned above have been measured, resulting in 108 miRNA profiles that were evaluated by next-generation-sequencing. The largest miRNA variability was due to inter-individual differences (34 %), followed by the cell types (23.4 %) and the isolation technique (17.2 %). The change over time in cell miRNA composition was moderate (< 3 %) being close to the technical variations (< 1 %). Largest variability (including technical and biological variance) was observed for CD8 cells while CD3 and CD4 cells showed significantly lower variations. ANOVA highlighted that 51.5 % of all miRNAs were significantly influenced by the purification technique. While CD4 cells were least affected, especially miRNA profiles of CD8 cells were fluctuating depending on the cell purification approach. To provide researchers access to the profiles and to allow further analyses of the tested conditions we implemented a dynamic web resource.