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Epitranscriptomic rRNA fingerprinting reveals tissue-of-origin and tumor-specific signatures

ABSTRACT: Mammalian ribosomal RNA (rRNA) molecules are highly abundant RNAs, decorated with over 220 different rRNA modifications, changing their chemical and biological properties. Previous works have shown that some types of rRNA modifications can be dynamically regulated; however, a comprehensive analysis of how the mammalian rRNA modification landscape is remodeled across time, cell types and upon disease conditions, remains largely unexplored. Here, we employ direct RNA nanopore sequencing to generate maps of human and mouse rRNA modifications across tissues, developmental stages, cell types and disease conditions. Our analyses reveal multiple rRNA sites that are differentially modified in a tissue- and/or developmental stage-specific manner. Notably, the adult brain exhibits the most distinct rRNA modification patterns, including previously unannotated rRNA modified sites. We then demonstrate that dynamic rRNA modification patterns can be used for tissue and cell type identification, which we hereby term ‘epitranscriptomic fingerprinting’. We then explored rRNA modification patterns in normal-tumor matched samples from lung cancer patients, finding that rRNA epitranscriptomic fingerprinting accurately classified clinical samples into normal and tumor groups from only 250 reads per sample, demonstrating the potential of rRNA modifications as diagnostic biomarkers, and revealing rRNA modifications as a rich source of information for tissue, cell type and disease identification.

ORGANISM(S): Mus musculus Homo sapiens

PROVIDER: GSE264668 | GEO | 2024/11/28

REPOSITORIES: GEO

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Project description:A broad diversity of modifications decorate RNA molecules. Originally conceived as static components, evidence is accumulating that some RNA modifications may be dynamic, contributing to cellular responses to external signals and environmental circumstances. A major difficulty in studying these modifications, however, is the need of tailored protocols to map each modification type individually. Here, we present a new approach that uses direct RNA nanopore sequencing to identify diverse RNA modification types present in native RNA molecules. First, we show that each RNA modification type results in a distinct and characteristic base-calling ‘error’ signature, which we validate using a battery of genetic strains lacking either pseudouridine (Ѱ) or 2’-O-methylation (Nm) modifications at known sites. We then demonstrate the value of these signatures for de novo transcriptome-wide prediction of Ѱ modifications, confirming known Ѱ-modified sites in rRNAs, snRNAs and mRNAs, as well as uncovering novel Ѱ sites including a previously unreported Pus4-dependent Ѱ modification in yeast mitochondrial rRNA, which we validate using orthogonal methods. To explore the dynamics of pseudouridylation across environmental stresses, we treat the cells with oxidative, cold and heat stresses, finding that yeast ribosomal rRNA modifications do not change upon environmental exposures. By contrast, our method reveals over a dozen novel heat-sensitive Ѱ-modified sites in snRNAs and snoRNAs, in addition to recovering previously reported sites. Finally, we develop a novel software, nanoRMS, which we show can estimate per-site modification stoichiometries from individual RNA molecules by identifying the reads with altered current intensity profiles, and quantify the RNA modification stoichiometry changes between two conditions. Our work demonstrates that Ѱ RNA modifications can be predicted de novo and in a quantitative manner using native RNA nanopore sequencing.

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Epitranscriptomic rRNA fingerprinting reveals tissue-of-origin and tumor-specific signatures

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