L3R-seq: A long-read 3'RACE approach for deep quantitative analysis of RNA processing

Abstract

Long-read sequencing technologies offer the potential to capture multiple RNA processing events within single molecules, but standard protocols suffer from quantification biases and sequencing errors that limit their utility for precise analysis. Here, we describe Long-read 3 RACE-seq (L3R-seq), a targeted long-read sequencing method that ligates a unique molecular identifier (UMI)-containing adapter to the 3 end of RNA molecules prior to reverse transcription and PCR amplification. By grouping cDNA reads sharing the same UMI and generating a consensus sequence for each original RNA molecule, L3R-seq corrects random sequencing errors and mitigates PCR-duplicate-driven quantification biases. The method enables simultaneous, per-molecule analysis of RNA editing, 3 end cleavage and trimming, and polyadenylation status. Along with a step-by-step protocol for library preparation and sequencing with the Oxford Nanopore Technologies (ONT) platform, we describe an accompanying bioinformatic pipeline for consensus generation and extraction of RNA features. As an example, we apply L3R-seq to the mitochondrial mRNA ccmC from Arabidopsis thaliana, a transcript subject to extensive C-to-U editing and non-canonical 3 end processing. The workflow is readily adaptable to other RNAs targets and is transferable to the Pacific Biosciences (PacBio) platform.