Evidence map›Paper›PMID 26824027›Full record

ArticleTranslation (Austin, Tex.)2013

PUNCH-P for global translatome profiling: Methodology, insights and comparison to other techniques.

Ranen Aviner, Tamar Geiger, Orna Elroy-Stein

Open access · bronzeAbstract read
In one paragraph

Article in Translation (Austin, Tex.), 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed
0.4field-weighted citation impact, top 33% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

11 citing papers in PubMed, 16 citations in OpenAlex.

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  9. Spatiotemporal Insights Into RNA-Organelle Interactions in Neurons.Frontiers in cell and developmental biology · 2021
    Review
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors at 2 institutions in 2 countries.

Ranen AvinerDepartment of Cell Research and Immunology; George S. Wise Faculty of Life Sciences; Tel Aviv University; Tel Aviv, Israel.
Tamar GeigerDepartment of Human Molecular Genetics and Biochemistry; Sackler Faculty of Medicine; Tel Aviv University, Tel Aviv, Israel.
Orna Elroy-SteinDepartment of Cell Research and Immunology; George S. Wise Faculty of Life Sciences; Tel Aviv University; Tel Aviv, Israel.
Tel Aviv University · ILArthur M. Sackler Gallery · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Regulation of mRNA translation is a major modulator of gene expression, allowing cells to fine tune protein levels during growth and differentiation and in response to physiological signals and environmental changes. Mass-spectrometry and RNA-sequencing methods now enable global profiling of the translatome, but these still involve significant analytical and economical limitations. We developed a novel system-wide proteomic approach for direct monitoring of translation, termed PUromycin-associated Nascent CHain Proteomics (PUNCH-P), which is based on the recovery of ribosome-nascent chain complexes from cells or tissues followed by incorporation of biotinylated puromycin into newly-synthesized proteins. Biotinylated proteins are then purified by streptavidin and analyzed by mass-spectrometry. Here we present an overview of PUNCH-P, describe other methodologies for global translatome profiling (pSILAC, BONCAT, TRAP/Ribo-tag, Ribo-seq) and provide conceptual comparisons between these methods. We also show how PUNCH-P data can be combined with mRNA measurements to determine relative translation efficiency for specific mRNAs.

Indexed as

cell cyclemass spectrometrynacent polypeptide chainsPUNCH-Ppuromycintranslatome

Identifiers

PMID26824027
PMCPMC4718054
OpenAlexW2329188228

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.