Optimization of a library preparation protocol for sequencing circulating plasma and serum microRNAs
https://doi.org/10.15829/1728-8800-2025-4557
EDN: DVGAAK
Abstract
Aim. To optimize a library preparation protocol for sequencing small non-coding ribonucleic acids (microRNAs) based on the commercial QIAseq miRNA UDI Library Kit to improve the quality of the obtained data.
Material and methods. Plasma and serum samples from four study participants were collected from the biobank collection of the National Medical Research Center for Therapeutic and Preventive Medicine. Ribonucleic acid (RNA) was isolated for each sample in parallel, using 200 and 300 µl aliquots. Two sequencing libraries were prepared from each RNA sample using the QIAseq miRNA UDI Library Kit by two manufacturer's protocol versions as follows: one for 1 ng of RNA with a reduced number of amplification cycles and one for 10 ng of RNA. Sequencing was performed on a NextSeq 550.
Results. When comparing groups of samples prepared using different protocol versions, there was a significant difference in the tags per million reads (TPM) per sample for human (ENCODE v47) and microRNA genes (p<0,001).
Conclusion. We showed that when using plasma and serum biosamples, the main parameter influencing higher microRNA sequencing rates is a reduction in the number of polymerase chain reaction cycles during library preparation.
About the Authors
A. V. KiselevaRussian Federation
Petroverigsky Lane, 10, bld. 3, Moscow, 101990
E. A. Sotnikova
Russian Federation
Petroverigsky Lane, 10, bld. 3, Moscow, 101990
A. A. Zharikova
Russian Federation
Petroverigsky Lane, 10, bld. 3, Moscow, 101990; Leninskiye Gory, 1, Moscow, 119234
V. A. Kutsenko
Russian Federation
Petroverigsky Lane, 10, bld. 3, Moscow, 101990
A. L. Borisova
Russian Federation
Petroverigsky Lane, 10, bld. 3, Moscow, 101990
S. A. Shalnova
Russian Federation
Petroverigsky Lane, 10, bld. 3, Moscow, 101990
A. I. Ershova
Russian Federation
Petroverigsky Lane, 10, bld. 3, Moscow, 101990
A. N. Meshkov
Russian Federation
Petroverigsky Lane, 10, bld. 3, Moscow, 101990
O. M. Drapkina
Russian Federation
Petroverigsky Lane, 10, bld. 3, Moscow, 101990
References
1. Matias-Garcia PR, Wilson R, Mussack V, et al. Impact of long-term storage and freeze-thawing on eight circulating microRNAs in plasma samples. PLoS One. 2020;15:e0227648. doi:10.1371/journal.pone.0227648.
2. O’Brien J, Hayder H, Zayed Y, et al. Overview of MicroRNA biogenesis, mechanisms of actions, and circulation. Front Endocrinol (Lausanne). 2018;9:402. doi:10.3389/fendo.2018.00402.
3. Mikhailina VI, Meshkov AN, Kiseleva AN, et al. MicroRNA as biomarkers of coronary artery disease in real-world practice. Cardiovascular Therapy and Prevention. 2024;23(12):4225. (In Russ.) doi:10.15829/1728-8800-2024-4225.
4. Kiseleva AV, Sotnikova EA, Kutsenko VA, et al. Circulating microRNAs and collateral circulation in coronary chronic total occlusion. Cardiovascular Therapy and Prevention. 2024;23(10): 4190. (In Russ.) doi:10.15829/1728-8800-2024-4190.
5. Wang J, Chen J, Sen S. MicroRNA as biomarkers and diagnostics. J Cell Physiol. 2016;231:25-30. doi:10.1002/jcp.25056.
6. Chan S-F, Cheng H, Goh KK-R, et al. Preanalytic Methodological Considerations and Sample Quality Control of Circulating miRNAs. J Mol Diagn. 2023;25:438-53. doi:10.1016/j.jmoldx.2023.03.005.
7. Sotnikova EA, Kiseleva AV, Meshkov AN. Effect of plasma and serum storage conditions on circulating microRNA levels. Cardiovascular Therapy and Prevention. 2024;23(11):4180. (In Russ.) doi:10.15829/1728-8800-2024-4180.
8. Sotnikova EA, Kiseleva AV, Meshkov AN. Preanalytical factors affecting the plasma and serum levels of circulating microRNAs. Cardiovascular Therapy and Prevention. 2024;23(11):4179. (In Russ.) doi:10.15829/1728-8800-2024-4179.
9. Suzuki K, Yamaguchi T, Kohda M, et al. Establishment of preanalytical conditions for microRNA profile analysis of clinical plasma samples. PLoS One. 2022;17:e0278927. doi:10.1371/journal.pone.0278927.
10. Androvic P, Benesova S, Rohlova E, et al. Small RNA-sequencing for analysis of circulating miRNAs: benchmark study. J Mol Diagn. 2022;24:386-94. doi:10.1016/j.jmoldx.2021.12.006.
11. Coenen-Stass AML, Magen I, Brooks T, et al. Evaluation of methodologies for microRNA biomarker detection by next generation sequencing. RNA Biol. 2018;15:1133-45. doi:10.1080/15476286.2018.1514236.
12. Hasby F, Bachmann J, Wang C, et al. Adapter dilution and input optimization for Qiagen QIAseq miRNA Library kit. bioRxiv. 2025. doi:10.1101/2025.04.30.651388.
13. Benesova S, Kubista M, Valihrach L. Small RNA-sequencing: Approaches and considerations for miRNA analysis. Diagnostics (Basel). 2021;11:964. doi:10.3390/diagnostics11060964.
14. Barberán-Soler S, Vo JM, Hogans RE, et al. Decreasing miRNA sequencing bias using a single adapter and circularization approach. Genome Biol. 2018;19:105. doi:10.1186/s13059-018-1488-z.
15. Herbert ZT, Thimmapuram J, Xie S, et al. Multisite evaluation of next-generation methods for small RNA quantification. J Biomol Tech. 2020;31:47-56. doi:10.7171/jbt.20-3102-001.
16. Wong RKY, MacMahon M, Woodside JV, et al. A comparison of RNA extraction and sequencing protocols for detection of small RNAs in plasma. BMC Genomics. 2019;20:446. doi:10.1186/s12864-019-5826-7.
17. Heinicke F, Zhong X, Zucknick M, et al. Systematic assessment of commercially available low-input miRNA library preparation kits. RNA Biol. 2020;17:75-86. doi:10.1080/15476286.2019.1667741.
18. Rodgers O, Watson CJ, Waterfield T. MiRNA library preparation optimisation for low-concentration and low-volume paediatric plasma samples. Noncoding RNA. 2025;11. doi:10.3390/ncrna11010011.
19. Kopylova OV, Ershova AI, Pokrovskaya MS, et al. Population-nosological research biobank of the National Medical Research Center for Therapy and Preventive Medicine: analysis of biosamples, principles of collecting and storing information. Cardiovascular Therapy and Prevention. 2022;20(8):3119. (In Russ.) doi:10.15829/1728-8800-2021-3119.
20. Smith T, Heger A, Sudbery I. UMI-tools: modeling sequencing errors in Unique Molecular Identifiers to improve quantification accuracy. Genome Res. 2017;27:491-9. doi:10.1101/gr.209601.116.
21. Martin M. Cutadapt removes adapter sequences from high-throughput sequencing reads. EMBnet J. 2011;17:10. doi:10.14806/ej.17.1.200.
22. Dobin A, Davis CA, Schlesinger F, et al. STAR: ultrafast universal RNA-seq aligner. Bioinformatics. 2013;29:15-21. doi:10.1093/bioinformatics/bts635.
23. Danecek P, Bonfield JK, Liddle J, et al. Twelve years of SAMtools and BCFtools. GigaScience. 2021;10:giab008. doi:10.1093/gigascience/giab008.
24. Liao Y, Smyth GK, Shi W. featureCounts: an efficient general purpose program for assigning sequence reads to genomic features. Bioinformatics. 2014;30:923-30. doi:10.1093/bioinformatics/btt656.
25. ENCODE Project Consortium. An integrated encyclopedia of DNA elements in the human genome. Nature. 2012;489:57-74. doi:10.1038/nature11247.
26. Wickham H. Ggplot2: Elegant graphics for data analysis. New York, NY: Springer; 2009. ISBN: 978-0-387-98141-3.
27. Grieco GE, Sebastiani G, Fignani D, et al. Protocol to analyze circulating small non-coding RNAs by high-throughput RNA sequencing from human plasma samples. STAR Protoc. 2021;2: 100606. doi:10.1016/j.xpro.2021.100606.
Supplementary files
What is already known about the subject?
- Next-generation sequencing provides high sensitivity and specificity, as well as the ability to quantify and detect new small non-coding ribonucleic acids (microRNAs).
- Library preparation for microRNA sequencing can significantly impact the results obtained, including the coverage and profile of detected microRNAs.
What might this study add?
- When using low miRNA content biosamples in research, optimization of the sequencing library preparation protocol can significantly improve the results obtained.
Review
For citations:
Kiseleva A.V., Sotnikova E.A., Zharikova A.A., Kutsenko V.A., Borisova A.L., Shalnova S.A., Ershova A.I., Meshkov A.N., Drapkina O.M. Optimization of a library preparation protocol for sequencing circulating plasma and serum microRNAs. Cardiovascular Therapy and Prevention. 2025;24(11):4557. (In Russ.) https://doi.org/10.15829/1728-8800-2025-4557. EDN: DVGAAK
JATS XML

















































