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

Mol Cell

Centre for Genomic Regulation (CRG), The Barcelona Institute of Science and Technology, Dr. Aiguader 88, Barcelona 08003, Spain; Universitat Pompeu Fabra (UPF), Barcelona 08003, Spain; ICREA, Passeig Lluís Companys 23, Barcelona 08010, Spain. Electronic address:

Published: January 2025

AI Article Synopsis

  • Mammalian ribosomal RNA (rRNA) has over 220 modifications, but how these modifications are regulated across tissues and conditions is still unclear.
  • Researchers used direct RNA sequencing to analyze rRNA modifications in humans and mice, discovering tissue- and developmental stage-specific modification patterns, including new sites not previously documented.
  • They established "epitranscriptomic fingerprinting," a method enabling accurate identification of tissues and tumor types, and showed that rRNA modification patterns could effectively distinguish normal and tumor samples in lung cancer patients with minimal data.

Article Abstract

Mammalian ribosomal RNA (rRNA) molecules are highly abundant RNAs, decorated with over 220 rRNA modifications. Previous works have shown that some rRNA modification types can be dynamically regulated; however, how and when the mammalian rRNA modification landscape is remodeled remains largely unexplored. Here, we employ direct RNA sequencing to chart the human and mouse rRNA epitranscriptome across tissues, developmental stages, cell types, and disease. Our analyses reveal multiple rRNA sites that are differentially modified in a tissue- and/or developmental stage-specific manner, including previously unannotated modified sites. We demonstrate that rRNA modification patterns can be used for tissue and cell-type identification, which we hereby term "epitranscriptomic fingerprinting." We then explore rRNA modification patterns in normal-tumor matched samples from lung cancer patients, finding that epitranscriptomic fingerprinting accurately classifies clinical samples into normal and tumor groups from only 250 reads per sample, demonstrating the potential of rRNA modifications as diagnostic biomarkers.

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Source
http://dx.doi.org/10.1016/j.molcel.2024.11.014DOI Listing

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