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Biol Direct. 2016 May 10;11:24. doi: 10.1186/s13062-016-0127-4.

Estimation of ribosome profiling performance and reproducibility at various levels of resolution.

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Biomedical Engineering Department, Tel Aviv University, Tel Aviv-Yafo, Israel.
Biomedical Engineering Department, Tel Aviv University, Tel Aviv-Yafo, Israel.
The Sagol School of Neuroscience, Tel Aviv University, Tel Aviv-Yafo, Israel.



Ribosome profiling (or Ribo-seq) is currently the most popular methodology for studying translation; it has been employed in recent years to decipher various fundamental gene expression regulation aspects. The main promise of the approach is its ability to detect ribosome densities over an entire transcriptome in high resolution of single codons. Indeed, dozens of ribo-seq studies have included results related to local ribosome densities in different parts of the transcript; nevertheless, the performance of Ribo-seq has yet to be quantitatively evaluated and reported in a large-scale multi-organismal and multi-protocol study of currently available datasets.


Here we provide the first objective evaluation of Ribo-seq at the resolution of a single nucleotide(s) using clear, interpretable measures, based on the analysis of 15 experiments, 6 organisms, and a total of 612, 961 transcripts. Our major conclusion is that the ability to infer signals of ribosomal densities at nucleotide scale is considerably lower than previously thought, as signals at this level are not reproduced well in experimental replicates. In addition, we provide various quantitative measures that connect the expected error rate with Ribo-seq analysis resolution.


The analysis of Ribo-seq data at the resolution of codons and nucleotides provides a challenging task, calls for task-specific statistical methods and further protocol improvements. We believe that our results are important for every researcher studying translation and specifically for researchers analyzing data generated by the Ribo-seq approach.


This article was reviewed by Dmitrij Frishman, Eugene Koonin and Frank Eisenhaber.


Next generation sequencing; Ribosome profiling; mRNA translation

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