Ferrero Giulio, Cordero Francesca, Tarallo Sonia, Arigoni Maddalena, Riccardo Federica, Gallo Gaetano, Ronco Guglielmo, Allasia Marco, Kulkarni Neha, Matullo Giuseppe, Vineis Paolo, Calogero Raffaele A, Pardini Barbara, Naccarati Alessio
Department of Computer Science, University of Turin, Turin, Italy.
Department of Clinical and Biological Sciences, University of Turin, Turin, Italy.
Oncotarget. 2017 Dec 14;9(3):3097-3111. doi: 10.18632/oncotarget.23203. eCollection 2018 Jan 9.
The role of non-coding RNAs in different biological processes and diseases is continuously expanding. Next-generation sequencing together with the parallel improvement of bioinformatics analyses allows the accurate detection and quantification of an increasing number of RNA species. With the aim of exploring new potential biomarkers for disease classification, a clear overview of the expression levels of common/unique small RNA species among different biospecimens is necessary. However, except for miRNAs in plasma, there are no substantial indications about the pattern of expression of various small RNAs in multiple specimens among healthy humans. By analysing small RNA-sequencing data from 243 samples, we have identified and compared the most abundantly and uniformly expressed miRNAs and non-miRNA species of comparable size with the library preparation in four different specimens (plasma exosomes, stool, urine, and cervical scrapes). Eleven miRNAs were commonly detected among all different specimens while 231 miRNAs were globally unique across them. Classification analysis using these miRNAs provided an accuracy of 99.6% to recognize the sample types. piRNAs and tRNAs were the most represented non-miRNA small RNAs detected in all specimen types that were analysed, particularly in urine samples. With the present data, the most uniformly expressed small RNAs in each sample type were also identified. A signature of small RNAs for each specimen could represent a reference gene set in validation studies by RT-qPCR. Overall, the data reported hereby provide an insight of the constitution of the human miRNome and of other small non-coding RNAs in various specimens of healthy individuals.
非编码RNA在不同生物过程和疾病中的作用正在不断扩展。下一代测序技术以及生物信息学分析的同步改进,使得人们能够准确检测和定量越来越多的RNA种类。为了探索用于疾病分类的新潜在生物标志物,有必要清晰地了解不同生物样本中常见/独特小RNA种类的表达水平。然而,除了血浆中的miRNA外,对于健康人群多种样本中各种小RNA的表达模式,尚无实质性的研究报道。通过分析来自243个样本的小RNA测序数据,我们鉴定并比较了在四种不同样本(血浆外泌体、粪便、尿液和宫颈刮片)中与文库制备相当的大小下表达最丰富且最均匀的miRNA和非miRNA种类。在所有不同样本中均检测到11种miRNA,而在这些样本中共有231种miRNA是独特的。使用这些miRNA进行分类分析,识别样本类型的准确率达到了99.6%。piRNA和tRNA是在所有分析的样本类型中检测到的最具代表性的非miRNA小RNA,尤其是在尿液样本中。根据现有数据,我们还确定了每种样本类型中表达最均匀的小RNA。每种样本的小RNA特征可作为RT-qPCR验证研究中的参考基因集。总体而言,本文报道的数据为健康个体各种样本中人类miRNome和其他小非编码RNA的构成提供了见解。