A computational platform for high-throughput analysis of RNA sequences and modifications by mass spectrometry

Samuel Wein, Byron Andrews, Timo Sachsenberg, Helena Santos-Rosa, Oliver Kohlbacher, Tony Kouzarides, Benjamin A. Garcia () and Hendrik Weisser ()
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Samuel Wein: University of Pennsylvania
Byron Andrews: STORM Therapeutics Limited, Moneta Building, Babraham Research Campus
Timo Sachsenberg: University of Tübingen
Helena Santos-Rosa: University of Cambridge
Oliver Kohlbacher: University of Tübingen
Tony Kouzarides: University of Cambridge
Benjamin A. Garcia: University of Pennsylvania
Hendrik Weisser: STORM Therapeutics Limited, Moneta Building, Babraham Research Campus

Nature Communications, 2020, vol. 11, issue 1, 1-12

Abstract: Abstract The field of epitranscriptomics continues to reveal how post-transcriptional modification of RNA affects a wide variety of biological phenomena. A pivotal challenge in this area is the identification of modified RNA residues within their sequence contexts. Mass spectrometry (MS) offers a comprehensive solution by using analogous approaches to shotgun proteomics. However, software support for the analysis of RNA MS data is inadequate at present and does not allow high-throughput processing. Existing software solutions lack the raw performance and statistical grounding to efficiently handle the numerous modifications found on RNA. We present a free and open-source database search engine for RNA MS data, called NucleicAcidSearchEngine (NASE), that addresses these shortcomings. We demonstrate the capability of NASE to reliably identify a wide range of modified RNA sequences in four original datasets of varying complexity. In human tRNA, we characterize over 20 different modification types simultaneously and find many cases of incomplete modification.

Date: 2020
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DOI: 10.1038/s41467-020-14665-7

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