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

ABSTRACT: 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.

SUBMITTER: Diament A

PROVIDER: S-EPMC4862193 | biostudies-literature | 2016 May

REPOSITORIES: biostudies-literature

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

Diament Alon A Tuller Tamir T

Biology direct 20160510

<h4>Background</h4>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; n ...[more]

PMID: 27160013

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Project description:Members of the family Coronaviridae have the largest genomes of all RNA viruses, typically in the region of 30 kilobases. Several coronaviruses, such as Severe acute respiratory syndrome-related coronavirus (SARS-CoV) and Middle East respiratory syndrome-related coronavirus (MERS-CoV), are of medical importance, with high mortality rates and, in the case of SARS-CoV, significant pandemic potential. Other coronaviruses, such as Porcine epidemic diarrhea virus and Avian coronavirus, are important livestock pathogens. Ribosome profiling is a technique which exploits the capacity of the translating ribosome to protect around 30 nucleotides of mRNA from ribonuclease digestion. Ribosome-protected mRNA fragments are purified, subjected to deep sequencing and mapped back to the transcriptome to give a global "snap-shot" of translation. Parallel RNA sequencing allows normalization by transcript abundance. Here we apply ribosome profiling to cells infected with Murine coronavirus, mouse hepatitis virus, strain A59 (MHV-A59), a model coronavirus in the same genus as SARS-CoV and MERS-CoV. The data obtained allowed us to study the kinetics of virus transcription and translation with exquisite precision. We studied the timecourse of positive and negative-sense genomic and subgenomic viral RNA production and the relative translation efficiencies of the different virus ORFs. Virus mRNAs were not found to be translated more efficiently than host mRNAs; rather, virus translation dominates host translation at later time points due to high levels of virus transcripts. Triplet phasing of the profiling data allowed precise determination of translated reading frames and revealed several translated short open reading frames upstream of, or embedded within, known virus protein-coding regions. Ribosome pause sites were identified in the virus replicase polyprotein pp1a ORF and investigated experimentally. Contrary to expectations, ribosomes were not found to pause at the ribosomal frameshift site. To our knowledge this is the first application of ribosome profiling to an RNA virus.

Dataset Information

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

Publications

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

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