Identification and analysis of ribosome-associated lncRNAs using ribosome profiling data

Chao Zeng, Tsukasa Fukunaga, Michiaki Hamada

Research output: Contribution to journalArticle

8 Citations (Scopus)

Abstract

Background: Although the number of discovered long non-coding RNAs (lncRNAs) has increased dramatically, their biological roles have not been established. Many recent studies have used ribosome profiling data to assess the protein-coding capacity of lncRNAs. However, very little work has been done to identify ribosome-associated lncRNAs, here defined as lncRNAs interacting with ribosomes related to protein synthesis as well as other unclear biological functions. Results: On average, 39.17% of expressed lncRNAs were observed to interact with ribosomes in human and 48.16% in mouse. We developed the ribosomal association index (RAI), which quantifies the evidence for ribosomal associability of lncRNAs over various tissues and cell types, to catalog 691 and 409 lncRNAs that are robustly associated with ribosomes in human and mouse, respectively. Moreover, we identified 78 and 42 lncRNAs with a high probability of coding peptides in human and mouse, respectively. Compared with ribosome-free lncRNAs, ribosome-associated lncRNAs were observed to be more likely to be located in the cytoplasm and more sensitive to nonsense-mediated decay. Conclusion: Our results suggest that RAI can be used as an integrative and evidence-based tool for distinguishing between ribosome-associated and free lncRNAs, providing a valuable resource for the study of lncRNA functions.

Original languageEnglish
Article number414
JournalBMC Genomics
Volume19
Issue number1
DOIs
Publication statusPublished - 2018 May 29

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Keywords

  • LncRNA
  • Long noncoding RNA
  • Ribosome profiling
  • Ribosome-associated

ASJC Scopus subject areas

  • Biotechnology
  • Genetics

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