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Cited by 274

The DOI matches its Crossref record; 10 of the 10 references it cites were found in a registry or an index.

Ribosome profiling reveals resemblance between long non-coding RNAs and 5′ leaders of coding RNAs

Open access
Chew, Guo-Liang, Pauli, Andrea, Rinn, John L., Regev, Aviv, Schier, Alexander F., Valen, Eivind·2013·Development

Abstract

Large-scale genomics and computational approaches have identified thousands of putative long non-coding RNAs (lncRNAs). It has been controversial, however, as to what fraction of these RNAs is truly non-coding. Here, we combine ribosome profiling with a machine-learning approach to validate lncRNAs during zebrafish development in a high throughput manner. We find that dozens of proposed lncRNAs are protein-coding contaminants and that many lncRNAs have ribosome profiles that resemble the 5′ leaders of coding RNAs. Analysis of ribosome profiling data from embryonic stem cells reveals similar properties for mammalian lncRNAs. These results clarify the annotation of developmental lncRNAs and suggest a potential role for translation in lncRNA regulation. In addition, our computational pipeline and ribosome profiling data provide a powerful resource for the identification of translated open reading frames during zebrafish development.

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Crossref · 10.1242/dev.098343

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Metadata

Authors
Chew, G.-L., Pauli, A., Rinn, J. L., Regev, A., Schier, A. F., & Valen, E.
Venue
Development
Published
2013-07-01
Volume
140
Issue
13
Pages
2828-2834
ISSN
  • 0950-1991 (ISSN-L)
  • 1477-9129
OpenAlex
W2092987085
Cited by
274
References
10
FWCI
12.51
Type
journal article
Language
en
Open access
green

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