Digital RNA sequencing using unique molecular identifiers enables ultrasensitive RNA mutation analysis

• Published in: Communications biology Vol. 7; no. 1; p. 249
• Main Authors: Luna Santamaría, Manuel, Andersson, Daniel, Parris, Toshima Z., Helou, Khalil, Österlund, Tobias, Ståhlberg, Anders
• Format: Journal Article
• Language: English
• Published: London Nature Publishing Group UK 01-03-2024; Nature Publishing Group; Nature Portfolio
• Subjects: 38/77; 45/23; 45/70; 45/91; 631/1647/514/1948; 631/1647/514/1949; 692/53/2421; 692/53/2422; 692/53/2423; Alleles; Biochemistry and Molecular Biology; Biokemi och molekylärbiologi; Biomedical and Life Sciences; Biopsy; DNA sequencing; Gene expression; Gene frequency; Life Sciences; Mutagenesis; Mutants; Mutation; Reproducibility; Reverse transcription; RNA editing
• ISSN: 2399-3642; 2399-3642
• DOI: 10.1038/s42003-024-05955-7

Mutation analysis is typically performed at the DNA level since most technical approaches are developed for DNA analysis. However, some applications, like transcriptional mutagenesis, RNA editing and gene expression analysis, require RNA analysis. Here, we combine reverse transcription and digital DNA sequencing to enable low error digital RNA sequencing. We evaluate yield, reproducibility, dynamic range and error correction rate for seven different reverse transcription conditions using multiplexed assays. The yield, reproducibility and error rate vary substantially between the specific conditions, where the yield differs 9.9-fold between the best and worst performing condition. Next, we show that error rates similar to DNA sequencing can be achieved for RNA using appropriate reverse transcription conditions, enabling detection of mutant allele frequencies <0.1% at RNA level. We also detect mutations at both DNA and RNA levels in tumor tissue using a breast cancer panel. Finally, we demonstrate that digital RNA sequencing can be applied to liquid biopsies, analyzing cell-free gene transcripts. In conclusion, we demonstrate that digital RNA sequencing is suitable for ultrasensitive RNA mutation analysis, enabling several basic research and clinical applications.
Digital RNA sequencing using unique molecular identifiers and well-performing reverse transcription allows detection of mutant allele frequencies < 0.1%.