Evidence map›Paper›PMID 22159587›Full record

ReviewCellular and molecular life sciences : CMLS2012

Principles of mRNA transport in yeast.

Roland Gerhard Heym, Dierk Niessing

Open access · hybridAbstract readReview
In one paragraph

Review in Cellular and molecular life sciences : CMLS, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 33 papers.

0numbers the graph read from it
0cells of the map it votes in
33citing papers in PubMed
3.1field-weighted citation impact, top 8% 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

33 citing papers in PubMed, 55 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

2 authors at 1 institution in 1 country.

Roland Gerhard HeymInstitute of Structural Biology, Helmholtz Zentrum München - German Research Center for Environmental Health, 81377, Munich, Germany.
Dierk Niessing
Helmholtz Zentrum München · DE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

mRNA localization and localized translation is a common mechanism by which cellular asymmetry is achieved. In higher eukaryotes the mRNA transport machinery is required for such diverse processes as stem cell division and neuronal plasticity. Because mRNA localization in metazoans is highly complex, studies at the molecular level have proven to be cumbersome. However, active mRNA transport has also been reported in fungi including Saccharomyces cerevisiae, Ustilago maydis and Candida albicans, in which these events are less difficult to study. Amongst them, budding yeast S. cerevisiae has yielded mechanistic insights that exceed our understanding of other mRNA localization events to date. In contrast to most reviews, we refrain here from summarizing mRNA localization events from different organisms. Instead we give an in-depth account of ASH1 mRNA localization in budding yeast. This approach is particularly suited to providing a more holistic view of the interconnection between the individual steps of mRNA localization, from transcriptional events to cytoplasmic mRNA transport and localized translation. Because of our advanced mechanistic understanding of mRNA localization in yeast, the present review may also be informative for scientists working, for example, on mRNA localization in embryogenesis or in neurons.

Indexed as

Cell DivisionCell NucleusEndoplasmic ReticulumRepressor ProteinsRNA-Binding ProteinsRNA, FungalRNA, MessengerRNA TransportSaccharomyces cerevisiaeSaccharomyces cerevisiae ProteinsASH1 protein, S cerevisiaeRepressor ProteinsRNA-Binding ProteinsRNA, FungalRNA, MessengerSaccharomyces cerevisiae ProteinsSHE2 protein, S cerevisiaeSHE3 protein, S cerevisiae

Identifiers

PMID22159587
PMCPMC3350770
OpenAlexW2027589247

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.