Evidence map›Paper›PMID 30399182›Full record

ArticlePloS one2018

Combining QTL mapping with transcriptome and metabolome profiling reveals a possible role for ABA signaling in resistance against the cabbage whitefly in cabbage.

Colette Broekgaarden, Koen T B Pelgrom, Johan Bucher, Nicole M van Dam, Katharine Grosser, Corné M J Pieterse, Martijn van Kaauwen, Greet Steenhuis, Roeland E Voorrips, Martin de Vos and 3 more

Open access · goldAbstract read
In one paragraph

Article in PloS one, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
2.0field-weighted citation impact, top 13% 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

6 citing papers in PubMed, 50 citations in OpenAlex.

  1. Article
  2. Genetic mapping and validation of QTL for whitefly resistance in cassava (Manihot esculenta Crantz).TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2025
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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

13 authors at 4 institutions in 2 countries.

Colette BroekgaardenPlant-Microbe Interactions, Department of Biology, Science4Life, Utrecht University, Utrecht, the Netherlands.ORCID 0000-0002-2468-6815
Koen T B PelgromWageningen UR Plant Breeding, Wageningen University and Research Centre, Wageningen, the Netherlands.
Johan BucherWageningen UR Plant Breeding, Wageningen University and Research Centre, Wageningen, the Netherlands.
Nicole M van DamGerman Centre for Integrative Biodiversity Research (iDiv) Halle-Jena-Leipzig, Leipzig, Germany.
Katharine GrosserGerman Centre for Integrative Biodiversity Research (iDiv) Halle-Jena-Leipzig, Leipzig, Germany.
Corné M J PietersePlant-Microbe Interactions, Department of Biology, Science4Life, Utrecht University, Utrecht, the Netherlands.ORCID 0000-0002-5473-4646
Martijn van KaauwenWageningen UR Plant Breeding, Wageningen University and Research Centre, Wageningen, the Netherlands.
Greet SteenhuisWageningen UR Plant Breeding, Wageningen University and Research Centre, Wageningen, the Netherlands.
Roeland E VoorripsWageningen UR Plant Breeding, Wageningen University and Research Centre, Wageningen, the Netherlands.
Martin de VosKeygene N.V., Wageningen, the Netherlands.
Ben VosmanWageningen UR Plant Breeding, Wageningen University and Research Centre, Wageningen, the Netherlands.
Anja WorrichGerman Centre for Integrative Biodiversity Research (iDiv) Halle-Jena-Leipzig, Leipzig, Germany.
Saskia C M van WeesPlant-Microbe Interactions, Department of Biology, Science4Life, Utrecht University, Utrecht, the Netherlands.
Wageningen University & Research · NLGerman Centre for Integrative Biodiversity Research · DEUtrecht University · NLKeyGene (Netherlands) · NL

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Whiteflies are among the world's most significant agricultural pests and chemical insecticides are extensively used to reduce crop damage to acceptable levels. However, nearly all insecticides pose a threat to the environment and alternative control methods, such as breeding of crop varieties that are inherently insect-resistant, are needed. Previously, a strong source of plant-age dependent resistance to the cabbage whitefly (Aleyrodes proletella) has been identified in the modern white cabbage (Brassica oleracea var. capitata) variety Rivera. However, nothing is known about the molecular mechanisms or the genes involved in this resistance. In the present study, a multidisciplinary approach combining transcriptome and metabolome profiling with genetic mapping was used to identify the molecular players of whitefly resistance in cabbage. Transcriptome profiles of young (susceptible) and older (resistant) Rivera plants were analyzed using RNA sequencing. While many genes involved in general processes were differentially expressed between both ages, several defense-related processes were overrepresented in the transcriptome profile of older plants. Hormone measurements revealed that jasmonic acid (JA) levels decreased upon whitefly infestation at both plant ages. Interestingly, abscisic acid (ABA) levels showed contrasting effects in response to whitefly infestation: ABA levels were reduced in young plants but induced in older plants upon whitefly feeding. Auxin levels were significantly lower in older plants compared with young plants, independent of whitefly presence, while glucosinolate levels were higher. Additionally, whitefly performance was monitored in an F2 population derived from a cross between Rivera and the susceptible white cabbage variety Christmas Drumhead. Significant QTL intervals were mapped on chromosome 2 and 9 for oviposition rate and whitefly adult survival, respectively. Several genes that were higher expressed in older plants and located in the identified QTL intervals were orthologous to Arabidopsis genes that have been related to ABA signaling, suggesting a role for ABA in the regulation of resistance towards whiteflies. Our results show that combining different omics approaches is a useful strategy to identify candidate genes underlying insect resistance.

Indexed as

Disease ResistanceAbscisic AcidAnimalsBrassicaChromosome MappingCrosses, GeneticGene Expression Regulation, PlantGlucosinolatesHemipteraMetabolomeMolecular Sequence AnnotationPhylogenyPlant DiseasesPlant Growth RegulatorsPlant LeavesPrincipal Component AnalysisAbscisic AcidGlucosinolatesPlant Growth Regulators

Identifiers

PMID30399182
PMCPMC6219772
OpenAlexW2900391797

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.