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Quantitative Biology

ISSN 2095-4689

ISSN 2095-4697(Online)

CN 10-1028/TM

邮发代号 80-971

Quantitative Biology  2022, Vol. 10 Issue (4): 321-332   https://doi.org/10.15302/J-QB-021-0284
  本期目录
The methodological challenge in high-throughput profiling and quantifying microRNAs
Mengya Chai, Xueyang Xiong, Huimin Wang, Lida Xu()
College of Life Science and Technology, Beijing University of Chemical Technology, Beijing 100029, China
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Abstract

Background: MicroRNAs (miRNAs) play an essential role in various biological processes and signaling pathways through the regulation of gene expression and genome stability. Recent data indicated that the next-generation sequencing (NGS)-based high-throughput quantification of miRNAs from biofluids provided exciting possibilities for discovering biomarkers of various diseases and might help promote the development of the early diagnosis of cancer. However, the complex process of library construction for sequencing always introduces bias, which may twist the actual expression levels of miRNAs and reach misleading conclusions.

Results: We discussed the deviation issue in each step during constructing miRNA sequencing libraries and suggested many strategies to generate high-quality data by avoiding or minimizing bias. For example, improvement of adapter design (a blocking element away from the ligation end, a randomized fragment adjacent to the ligation junction and UMI) and optimization of ligation conditions (a high concentration of PEG 8000, reasonable incubation temperature and time, and the selection of ligase) in adapter ligation, high-quality input RNA samples, removal of adapter dimer (solid phase reverse immobilization (SPRI) magnetic bead, locked nucleic acid (LNA) oligonucleotide, and Phi29 DNA polymerase), PCR (linear amplification, touch-down PCR), and product purification are essential factors for achieving high-quality sequencing data. Moreover, we described several protocols that exhibit significant advantages using combinatorial optimization and commercially available low-input miRNA library preparation kits.

Conclusions: Overall, our work provides the basis for unbiased high-throughput quantification of miRNAs. These data will help achieve optimal design involving miRNA profiling and provide reliable guidance for clinical diagnosis and treatment by significantly increasing the credibility of potential biomarkers.

Key wordsmicroRNA    next-generation sequencing    library preparation    bias
收稿日期: 2021-01-02      出版日期: 2022-12-27
Corresponding Author(s): Lida Xu   
 引用本文:   
. [J]. Quantitative Biology, 2022, 10(4): 321-332.
Mengya Chai, Xueyang Xiong, Huimin Wang, Lida Xu. The methodological challenge in high-throughput profiling and quantifying microRNAs. Quant. Biol., 2022, 10(4): 321-332.
 链接本文:  
https://academic.hep.com.cn/qb/CN/10.15302/J-QB-021-0284
https://academic.hep.com.cn/qb/CN/Y2022/V10/I4/321
Kit nameFeaturesRecommended input amount of RNA
Nextflex (Bioo Scientific/PerkinElmer)RNA ligase-based ligation; randomized adapters; PEG; bead-based size selection1 ng?2 μg total RNA or purified small RNA from 1?10 μg total RNA
NEBNext (NEB)RNA ligase-based ligation; PEG; gel-based size selection (Pippon-Pre)100 ng?1 μg total RNA
QIAseq (Qiagen)RNA ligase-based ligation; bead-based size selection; UMI incorporated at RT step1?500 ng total RNA
SMARTer (Takara Bio)A ligation-free “tailing approach”; 3′ polyadenylation and 5′ template switching; gel-based size selection (Pippon-Pre)1 ng?2 μg total RNA or small RNA
CATS Small RNA-Seq Kit (CATS)A ligation-free “tailing approach”; 3′ polyadenylation and 5′ template switchingAs less as 10 pg
Trilink Biotechnologies CleanTag Small RNA Library Prep Kit (CleanTag)RNA ligase-based ligation; bead-based size selection1?1000 ng
TailorMix microRNA Sample Preparation Kit Version 3 (TailorMix)RNA ligase-based ligation; PAGE-based size selectionAs little as 10 ng of total RNA
TruSeq (Illumina)RNA ligase-based ligation10?50 ng of purified miRNAs or 1 μg of total RNA
Tab.1  
Fig.1  
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