Evidence map›Paper›PMID 20100801›Full record

ArticleNucleic acids research2010

Analysis of ribosome biogenesis factor-modules in yeast cells depleted from pre-ribosomes.

Juliane Merl, Steffen Jakob, Katrin Ridinger, Thomas Hierlmeier, Rainer Deutzmann, Philipp Milkereit, Herbert Tschochner

Open access · goldAbstract read
In one paragraph

Article in Nucleic acids research, 2010. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 26 papers.

0numbers the graph read from it
0cells of the map it votes in
26citing papers in PubMed
1.9field-weighted citation impact, top 15% 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

26 citing papers in PubMed, 38 citations in OpenAlex.

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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

7 authors at 1 institution in 1 country.

Juliane MerlInstitut für Biochemie, Genetik und Mikrobiologie, University of Regensburg, Universitätsstr. 31, 93053 Regensburg, Germany.
Steffen Jakob
Katrin Ridinger
Thomas Hierlmeier
Rainer Deutzmann
Philipp Milkereit
Herbert Tschochner
University of Regensburg · DE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Formation of eukaryotic ribosomes requires more than 150 biogenesis factors which transiently interact with the nascent ribosomal subunits. Previously, many pre-ribosomal intermediates could be distinguished by their protein composition and rRNA precursor (pre-rRNA) content. We purified complexes of ribosome biogenesis factors from yeast cells in which de novo synthesis of rRNA precursors was down-regulated by genetic means. We compared the protein composition of these largely pre-rRNA free assemblies with the one of analogous pre-ribosomal preparations by semi-quantitative mass spectrometry. The experimental setup minimizes the possibility that the analysed pre-rRNA free protein modules were derived from (partially) disrupted pre-ribosomal particles and provides thereby strong evidence for their pre-ribosome independent existence. In support of the validity of this approach (i) the predicted composition of the analysed protein modules was in agreement with previously described rRNA-free complexes and (ii) in most of the cases we could identify new candidate members of reported protein modules. An unexpected outcome of these analyses was that free large ribosomal subunits are associated with a specific set of ribosome biogenesis factors in cells where neo-production of nascent ribosomes was blocked. The data presented strengthen the idea that assembly of eukaryotic pre-ribosomal particles can result from transient association of distinct building blocks.

Indexed as

Fungal ProteinsRibosomal ProteinsRibosomesRNA, FungalRNA PrecursorsRNA, RibosomalYeastsFungal ProteinsRibosomal ProteinsRNA, FungalRNA PrecursorsRNA, Ribosomal

Identifiers

PMID20100801
PMCPMC2875017
OpenAlexW2018544138

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Registered trials

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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.