Changes in small non-coding RNA (sncRNA) expression have been implicated in the development and progression of cancers, neurological, and cardiovascular diseases. Using sncRNA as biomarkers requires precise and sensitive detection. High-throughput sequencing is a powerful tool for sncRNA characterization; however, library preparation methods often limit accuracy and sensitivity. Ligation-based methods often introduce bias, obscuring true sncRNA composition. Improvement in library preparation methods is essential for using sncRNAs as clinical biomarkers.
We developed a novel, ligation-based small RNA library preparation method with reduced bias and increased sncRNA detection. Libraries were made in one day using a streamlined protocol with bead-based size-selection and cleanup. This method was robust across a broad input range and challenging sample types such as formalin-fixed paraffin-embedded (FFPE) RNA. Even representation of sncRNAs was confirmed using a pool of synthetic miRNAs; ~90% of miRNAs were within 2-fold of expected values, compared to <30% with other methods. Additionally, miRNA detection was consistent using 0.5 ng to 1,000 ng of total RNA from human brain. This method also detected 2'-O-methylated sncRNAs, such as piRNAs and plant miRNAs, without any protocol modifications. Libraries from low-quality FFPE RNA (1–100 ng) yielded consistent results, demonstrating suitability for degraded samples.
Regardless of input or sample, this method showed robust capability to generate high quality libraries, increasing confidence in sncRNA detection and supporting their use as disease biomarkers.