A method of comprehensive sequencing analysis of the small RNA fragmentome (RiboMarker).

Abstract

Small RNAs and RNA fragments (sRNAs) found in blood and other biofluids have emerged as promising biomarkers for cancer and other pathologies. Sequencing analysis of sRNAs representing the entire RNA fragmentome could improve understanding of their roles in cancer development and be used for discovery of new biomarkers, cancer detection, and personalized treatment management. Conventional methods of sRNA-seq library preparation are limited to detection of sRNAs with 5'-P and 3'-OH ends (sRNA Type 1) that represent only ∼10% of the whole RNA fragmentome, whereas sRNA Types having other termini are hidden. Although recently developed sRNA-seq methods provide detection of some or all hidden sRNAs, these methods cannot both detect all and distinguish between sRNAs of different RNA Types. Here we describe the RiboMarker approach for preparation of sRNA sequencing libraries that addresses these shortcomings. It uses distinctive enzymatic pretreatment(s) providing conversion between the RNA termini that can enrich for or deplete specific sRNA type(s) upfront of the universal method of library preparation. To monitor the efficacy of these pretreatments, we leveraged a pool of synthetic RNAs of different RNA Types and lengths spiked in brain or plasma RNA samples. This allows identification and analysis of relative abundance, sequencing profiles, and RNA Types of naturally occurring sRNAs representing different RNA classes. Using the RiboMarker approach, we demonstrated its capability to enhance the capacity and sensitivity of distinguishing between plasma RNA samples from different donors (simulating healthy individuals and cancer patients) by selecting and using sRNAs of specific RNA Type(s).