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, researchers from Harvard University and MIT combined ribosome profiling with a machine-learning approach to validate lncRNAs during zebrafish development in a high throughput manner. They found 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 revealed 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, their computational pipeline and ribosome profiling data provide a powerful resource for the identification of translated open reading frames during zebrafish development.
- Chew GL, Pauli A, Rinn JL, Regev A, Schier AF, Valen E. (2013) Ribosome profiling reveals resemblance between long non-coding RNAs and 5′ leaders of coding RNAs. Development [Epub ahead of print]. [abstract]