Small non-coding RNA profiling in human biofluids and surrogate tissues from healthy individuals: description of the diverse and most represented species.
Small non-coding RNA profiling in human biofluids and surrogate tissues from healthy individuals: description of the diverse and most represented species.
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DOI：
10.18632/oncotarget.23203
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发表时间：
2018-01-09
期刊：
影响因子：
--
通讯作者：
Naccarati A
中科院分区：
文献类型：
--
作者：
Ferrero G;Cordero F;Tarallo S;Arigoni M;Riccardo F;Gallo G;Ronco G;Allasia M;Kulkarni N;Matullo G;Vineis P;Calogero RA;Pardini B;Naccarati A
非编码rna在不同生物过程和疾病中的作用不断扩大。下一代测序与生物信息学分析的并行改进使得越来越多的RNA物种的准确检测和定量成为可能。为了探索新的潜在的疾病分类生物标志物，有必要对不同生物标本中常见/独特小RNA物种的表达水平进行清晰的概述。然而，除了血浆中的mirna外，各种小rna在健康人的多个标本中的表达模式没有实质性的迹象。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4个不同样本（血浆外泌体、粪便、尿液和宫颈刮擦）中最丰富和均匀表达的mirna和非mirna物种，这些物种与文库制备的大小相当。在所有不同的标本中，共有11种mirna被检测到，231种mirna在它们之间是全球唯一的。使用这些mirna进行分类分析，识别样品类型的准确率为99.6%。pirna和trna是在所分析的所有标本类型中检测到的最具代表性的非mirna小rna，特别是在尿液样本中。利用目前的数据，还确定了每种样品类型中表达最均匀的小rna。每个标本的小rna标记可以代表RT-qPCR验证研究中的参考基因集。总的来说，本文报道的数据提供了人类miRNome和其他小非编码rna在各种健康个体标本中的构成的见解。
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.
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影响因子：
14.9
作者：
Buschmann D;Haberberger A;Kirchner B;Spornraft M;Riedmaier I;Schelling G;Pfaffl MW
通讯作者：
Pfaffl MW
影响因子：
16.6
作者：
Freedman JE;Gerstein M;Mick E;Rozowsky J;Levy D;Kitchen R;Das S;Shah R;Danielson K;Beaulieu L;Navarro FC;Wang Y;Galeev TR;Holman A;Kwong RY;Murthy V;Tanriverdi SE;Koupenova-Zamor M;Mikhalev E;Tanriverdi K
通讯作者：
Tanriverdi K
影响因子：
10.3
作者：
Bergeron, Christine;Giorgi-Rossi, Paolo;Ronco, Guglielmo
通讯作者：
Ronco, Guglielmo
DOI：
10.1007/978-1-60327-005-2_3
发表时间：
2010-01-01
期刊：
PLANT MICRORNAS: METHODS AND PROTOCOLS
影响因子：
--
作者：
Accerbi, Monica;Schmidt, Skye A.;Green, Pamela J.
通讯作者：
Green, Pamela J.
影响因子：
3.7
作者：
Cordero F;Beccuti M;Arigoni M;Donatelli S;Calogero RA
通讯作者：
Calogero RA