Transcriptome-wide profiling of multiple RNA modifications simultaneously at single-base resolution
The breadth and importance of RNA modifications are growing rapidly as modified ribonucleotides can impact the sequence, structure, function, stability, and fate of RNAs and their interactions with other molecules. Therefore, knowing cellular RNA modifications at single-base resolution could provide...
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Veröffentlicht in: | Proceedings of the National Academy of Sciences - PNAS 2019-04, Vol.116 (14), p.6784-6789 |
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Sprache: | eng |
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Zusammenfassung: | The breadth and importance of RNA modifications are growing rapidly as modified ribonucleotides can impact the sequence, structure, function, stability, and fate of RNAs and their interactions with other molecules. Therefore, knowing cellular RNA modifications at single-base resolution could provide important information regarding cell status and fate. A current major limitation is the lack of methods that allow the reproducible profiling of multiple modifications simultaneously, transcriptome-wide and at single-base resolution. Here we developed RBS-Seq, a modification of RNA bisulfite sequencing that enables the sensitive and simultaneous detection of m⁵C, Ψ, and m¹A at single-base resolution transcriptome-wide. With RBS-Seq, m⁵C and m¹A are accurately detected based on known signature base mismatches and are detected here simultaneously along with Ψ sites that show a 1–2 base deletion. Structural analyses revealed the mechanism underlying the deletion signature, which involves Ψ-monobisulfite adduction, heat-induced ribose ring opening, and Mg2+-assisted reorientation, causing base-skipping during cDNA synthesis. Detection of each of these modifications through a unique chemistry allows high-precision mapping of all three modifications within the same RNA molecule, enabling covariation studies. Application of RBS-Seq on HeLa RNA revealed almost all known m⁵C, m¹A, and ψ sites in tRNAs and rRNAs and provided hundreds of new m⁵C and Ψ sites in noncoding RNAs and mRNAs. However, our results diverge greatly from earlier work, suggesting ∼10-fold fewer m⁵C sites in noncoding and coding RNAs and the absence of substantial m¹A in mRNAs. Taken together, the approaches and refined datasets in this work will greatly enable future epitranscriptome studies. |
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ISSN: | 0027-8424 1091-6490 |
DOI: | 10.1073/pnas.1817334116 |