Fluorescently guided workflow with rationally engineered 5' ligation adapters for high-sensitivity and low-bias small RNA sequencing

Authors

Barnes, S. A., Lovisek, D., Dzurcaninova, N., Carnecky, M., Birova, S., Cirkova, I., Matyasovsky, J., Szobi, A., Cekan, P.

Abstract

MicroRNAs (miRNAs) act as key regulators of gene expression across diverse cellular processes, and their precise quantification can provide unique insight into disease pathogenesis. High-throughput sequencing allows for comprehensive small RNA profiling; however, standard commercial library preparation workflows are challenged by issues of low sensitivity and representational bias, limiting reliable profiling, especially in scenarios where samples are scarce. Several structural studies have shown that this bias primarily arises due to sequence and secondary structure variations between miRNAs and adapters during enzyme-catalyzed biochemical reactions. In this work, we propose a new approach to ligation adapter engineering using a bioinformatic analysis of the human miRNome to rationally design structure-forcing 5 adapters, that physically override localized, unpredictable structural variations during the intermediate ligation state. We show that this approach combined with a practical fluorescence-guided workflow, utilizing a fluorescently-labeled 3 adapter and novel Fluorescent Ligation Rulers (FLRs) to guide precise band excision, can minimize representational bias and increase the sensitivity of small RNA sequencing from low-input biological matrices. In comprehensive benchmarks using a synthetic panel, this method significantly reduced bias and outperformed alternative commercial protocols. Finally, we demonstrate that this workflow enhances biomarker detection and library quality in challenging clinical matrices, especially in cerebrospinal fluid. Overall, this protocol enables highly accurate miRNome characterization and is well-suited for biomarker discovery in challenging sample types.

Preprint server: bioRxiv
The authors list and abstract were imported from bioRxiv on 10 Jul 2026.

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