Evidence map›Paper›PMID 30804892›Full record

ReviewFrontiers in microbiology2019

Manipulating Cellular Factors to Combat Viruses: A Case Study From the Plant Eukaryotic Translation Initiation Factors eIF4.

Corinne Schmitt-Keichinger

Open access · goldAbstract readReview
In one paragraph

Review in Frontiers in microbiology, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers.

0numbers the graph read from it
0cells of the map it votes in
23citing papers in PubMed
11.6field-weighted citation impact, top 2% 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

23 citing papers in PubMed, 65 citations in OpenAlex.

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  19. Viruses · 2021
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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

1 author at 1 institution in 1 country.

Corinne Schmitt-KeichingerUMR_A 1131 Santé de la Vigne et Qualité du Vin, INRA - Université de Strasbourg, Colmar, France.
Santé et Agroécologie du Vignoble · FR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Genes conferring resistance to plant viruses fall in two categories; the dominant genes that mostly code for proteins with a nucleotide binding site and leucine rich repeats (NBS-LRR), and that directly or indirectly, recognize viral avirulence factors (Avr), and the recessive genes. The latter provide a so-called recessive resistance. They represent roughly half of the known resistance genes and are alleles of genes that play an important role in the virus life cycle. Conversely, all cellular genes critical for the viral infection virtually represent recessive resistance genes. Based on the well-documented case of recessive resistance mediated by eukaryotic translation initiation factors of the 4E/4G family, this review is intended to summarize the possible approaches to control viruses via their host interactors. Classically, resistant crops have been developed through introgression of natural variants of the susceptibility factor from compatible relatives or by random mutagenesis and screening. Transgenic methods have also been applied to engineer improved crops by overexpressing the translation factor either in its natural form or after directed mutagenesis. More recently, innovative approaches like silencing or genome editing have proven their great potential in model and crop plants. The advantages and limits of these different strategies are discussed. This example illustrates the need to identify and characterize more host factors involved in virus multiplication and to assess their application potential in the control of viral diseases.

Indexed as

CRISPR/Cas9eIF4Eengineered resistancehairpinhost factorloss-of-susceptibilityrecessivevirus resistance

Identifiers

PMID30804892
PMCPMC6370628
OpenAlexW2915066455

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.