RustFungiV1, Main, Exploration, bibRecord, 000705

Comparative survey of the relative impact of mRNA features on local ribosome profiling read density.

Identifieur interne : 000705 ( Main/Exploration ); précédent : 000704; suivant : 000706

Comparative survey of the relative impact of mRNA features on local ribosome profiling read density.

Auteurs : Patrick B F. O'Connor [Irlande (pays)] ; Dmitry E. Andreev [Irlande (pays), Russie] ; Pavel V. Baranov [Irlande (pays)]

Source :

Nature communications [ 2041-1723 ] ; 2016.

RBID : pubmed:27698342

Descripteurs français

English descriptors

KwdEn :
- Animals (MeSH), Codon (MeSH), Computer Simulation (MeSH), Gene Expression Profiling (MeSH), Gene Expression Regulation (MeSH), High-Throughput Nucleotide Sequencing (MeSH), Humans (MeSH), Mice (MeSH), Models, Statistical (MeSH), Nucleic Acid Conformation (MeSH), Open Reading Frames (MeSH), Protein Biosynthesis (MeSH), RNA, Messenger (metabolism), Reproducibility of Results (MeSH), Ribosomes (chemistry), Ribosomes (ultrastructure), Yeasts (metabolism).
MESH :
- chemical , metabolism : RNA, Messenger.
- chemical : Codon.
- chemistry : Ribosomes.
- metabolism : Yeasts.
- ultrastructure : Ribosomes.
- Animals, Computer Simulation, Gene Expression Profiling, Gene Expression Regulation, High-Throughput Nucleotide Sequencing, Humans, Mice, Models, Statistical, Nucleic Acid Conformation, Open Reading Frames, Protein Biosynthesis, Reproducibility of Results.

Abstract

Ribosome profiling (Ribo-seq), a promising technology for exploring ribosome decoding rates, is characterized by the presence of infrequent high peaks in ribosome footprint density and by long alignment gaps. Here, to reduce the impact of data heterogeneity we introduce a simple normalization method, Ribo-seq Unit Step Transformation (RUST). RUST is robust and outperforms other normalization techniques in the presence of heterogeneous noise. We illustrate how RUST can be used for identifying mRNA sequence features that affect ribosome footprint densities globally. We show that a few parameters extracted with RUST are sufficient for predicting experimental densities with high accuracy. Importantly the application of RUST to 30 publicly available Ribo-seq data sets revealed a substantial variation in sequence determinants of ribosome footprint frequencies, questioning the reliability of Ribo-seq as an accurate representation of local ribosome densities without prior quality control. This emphasizes our incomplete understanding of how protocol parameters affect ribosome footprint densities.

DOI: 10.1038/ncomms12915
PubMed: 27698342
PubMed Central: PMC5059445

Affiliations:

Links toward previous steps (curation, corpus...)

to stream Main, to step Corpus: 000605
to stream Main, to step Curation: 000605

Le document en format XML

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<term>Biosynthèse des protéines (MeSH)</term>
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<front><div type="abstract" xml:lang="en">Ribosome profiling (Ribo-seq), a promising technology for exploring ribosome decoding rates, is characterized by the presence of infrequent high peaks in ribosome footprint density and by long alignment gaps. Here, to reduce the impact of data heterogeneity we introduce a simple normalization method, Ribo-seq Unit Step Transformation (RUST). RUST is robust and outperforms other normalization techniques in the presence of heterogeneous noise. We illustrate how RUST can be used for identifying mRNA sequence features that affect ribosome footprint densities globally. We show that a few parameters extracted with RUST are sufficient for predicting experimental densities with high accuracy. Importantly the application of RUST to 30 publicly available Ribo-seq data sets revealed a substantial variation in sequence determinants of ribosome footprint frequencies, questioning the reliability of Ribo-seq as an accurate representation of local ribosome densities without prior quality control. This emphasizes our incomplete understanding of how protocol parameters affect ribosome footprint densities.</div>
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Comparative survey of the relative impact of mRNA features on local ribosome profiling read density.

Comparative survey of the relative impact of mRNA features on local ribosome profiling read density.

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