five

Examination and comparison of the RNA extraction methods using mouse serum

收藏
NIAID Data Ecosystem2026-05-01 收录
下载链接:
https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE246437
下载链接
链接失效反馈
官方服务:
资源简介:
Serum miRNAs are considered useful as non-invasive biomarkers for various diseases, but the optimal method for extracting RNA from serum is currently unknown. In this study, several RNA extraction kits were used to determine which kit is the optimal method. RNA was extracted from the serum of 8-week-old C57BL/6NJcl male mice according to the protocol of each RNA extraction kit. The yield of extracted RNA samples was calculated and electrophoretic patterns were evaluated by Agilent bioanalyzer. Expression patterns of the extracted RNA samples were confirmed by Agilent mouse miRNA microarray. The results showed significant differences in RNA yields in the miRNeasy serum/plasma advanced kit, and mirVana™ PARIS™ RNA and Native Protein Purification Kit compared to almost all other samples. Furthermore, two peaks were identified in the miRNeasy serum/plasma advanced kit using small RNA kit of Agilent bioanalyzer, one at 20-40 nucleotides (nt) and the other around 40-100 nt whereas the other reagents had a single peak. In addition, a high correlation was observed between the two RNA extraction kits in microarray. These results suggest that the above two kits are suitable for miRNA extraction from mouse serum. RNAs were extracted using 200 μL of serum from 8-week-old C57BL/6NJcl male mice and 2 reagents: miRNeasy serum/plasma advanced kit (QIAGEN), and mirVana™ PARIS™ RNA and Native Protein Purification Kit (Thermo Fisher Scientific) according to each manufacturer’s protocol. In addition, RNAs were extracted using exoRNeasy midi kit (QIAGEN) to extract RNA from the aqueous layer of 200 μL of serum to which 700 μL of QIAzol Lysis Reagent (QIAGEN) was added and separated in two layers to determine the amount of total RNA in the serum.
创建时间:
2024-04-20
5,000+
优质数据集
54 个
任务类型
进入经典数据集
二维码
社区交流群

面向社区/商业的数据集话题

二维码
科研交流群

面向高校/科研机构的开源数据集话题

数据驱动未来

携手共赢发展

商业合作