|Title||Host-plant resistance to western flower thrips in Arabidopsis|
|Author(s)||Thoen, Manus P.M.|
|Source||Wageningen University. Promotor(en): Marcel Dicke; Harro Bouwmeester, co-promotor(en): Maarten Jongsma. - Wageningen : Wageningen University - ISBN 9789462578807 - 191|
Laboratory of Entomology
|Publication type||Dissertation, internally prepared|
|Availibility||Full text available from 2019-08-29|
|Keyword(s)||arabidopsis thaliana - host plants - insect pests - frankliniella occidentalis - defence mechanisms - pest resistance - genomics - genome analysis - host-seeking behaviour - optical tracking - data analysis - insect plant relations - waardplanten - insectenplagen - verdedigingsmechanismen - plaagresistentie - genomica - genoomanalyse - gedrag bij zoeken van een gastheer - optisch sporen - gegevensanalyse - insect-plant relaties|
|Categories||Insect-Plant Relations / Plant Defence, Plant Resistance|
Western flower thrips is a pest on a large variety of vegetable, fruit and ornamental crops. The damage these minute slender insects cause in agriculture through feeding and the transmission of tospoviruses requires a sustainable solution. Host-plant resistance is a cornerstone of Integrated Pest Management (IPM). Plants have many natural defense compounds and morphological features that aid in the protection against herbivorous insects. However, the molecular and physiological aspects that control host-plant resistance to thrips are largely unknown.
A novel and powerful tool to study host-plant resistance to insects in natural populations is genome-wide association (GWA) mapping. GWA mapping provides a comprehensive untargeted approach to explore the whole array of plant defense mechanisms. The development of high-throughput phenotyping (HTP) systems is a necessity when large plant panels need to be screened for host-plant resistance to insects. An automated video-tracking platform that could screen large plant panels for host-plant resistance to thrips, and dissect host-plant resistance to thrips in component traits related to thrips behavior, was developed. This phenotyping platform allows the screening for host-plant resistance against thrips in a parallel two-choice setup using EthoVision tracking software. The platform was used to establish host-plant preference of thrips with a large plant population of 345 wild Arabidopsis accessions (the Arabidopsis HapMap population) and the method was optimized with two extreme accessions from this population that differed in resistance to thrips. This method can be a reliable and effective high throughput phenotyping tool to assess host-plant resistance to thrips in large plant populations. EthoAnalysis, a novel software package was developed to improve the analyses of insect behavior. There were several benefits from using EthoAnalysis to analyze EthoVision data. The detailed event statistics that could be extracted from EthoAnalysis allows researchers to distinguish detailed differences in moving and feeding behavior of thrips. The potential of this additional information is discussed in the light of quantitative genetic studies.
Stress resistance was studied in the HapMap population on a total of 15 different biotic and abiotic stresses ranging from biotic stresses like insects and nematodes, to abiotic stresses like drought and salt. A multi-trait GWA study to unravel the genetic architecture underlying plant responses to the different stresses was performed. A genetic network in this study revealed little correlation between the plant responses to the different insect herbivores studied (aphids, whiteflies, thrips and caterpillars). For thrips resistance a weak positive correlation with resistance to drought stress and Botrytis, and a negative correlation with resistance to parasitic plants were observed. One of the surprising outcomes of this study was the absence of shared major QTLs for host-plant resistance and abiotic stress tolerance mechanisms. RESISTANCE METHYLATED GENE 1 (RMG1) was one of the candidate genes in this multi-trait GWA study that could be controlling shared resistance mechanisms against many different stresses in Arabidopsis. RMG1 is a nucleotide-binding site Leucine-rich repeat (NB-LRR) disease resistance protein and its potential relation to several resistance/tolerance traits was successfully demonstrated with T-DNA insertion lines.
The 15 stresses were used in a comparison with a metabolomics dataset on this Arabidopsis HapMap population. It was discovered that levels of certain aliphatic glucosinolates correlated positively with the levels of resistance to thrips. This correlation was further investigated with the screening of a RIL (Recombinant Inbred Line) population for resistance to thrips, several knockout mutants and the analysis of co-localization of GWA mapping results between glucosinolates genes and thrips resistance. In a GWA analysis, the C4 alkenyl glucosinolates that correlated the strongest with thrips resistance mapped to the genomic regions containing genes known to regulate the biosynthesis of these compounds. However, thrips resistance did not co-localize with any of the GSL genes, unless a correction for population stratification was omitted. Additional screening of a Cvi x Ler RIL population showed a QTL for thrips resistance on chromosome 2, but no co-localization with any known glucosinolate genes, nor with thrips resistance loci identified by GWA mapping. Knock-out mutants and overexpressors of glucosinolate synthesis genes could also not confirm a causal link between glucosinolates and resistance to thrips. It is possible that the crucial factors that control resistance to thrips may not have been present in sufficient quantities or in the right combinations in the mutants, RILs and NIL screened in this study. Alternatively, the correlation between thrips feeding damage and glucosinolate profiles could be based on independent geographical clines. More research should be conducted to assess which of these explanations is correct.
In the general discussion, the results from this thesis are discussed in a broader perspective. Some prototypes of new phenotyping platforms that could further aid screening for resistance to thrips in the future are presented. Natural variation in host-plant resistance to thrips is compared to the variation in host-plant resistance to aphids and caterpillars. The geographic distribution of host-plant resistance to thrips is not evident in the other insects, in line with the distribution of glucosinolate profiles and other climate factors. The chapter concludes with some suggestions for future research in the field of host-plant resistance to thrips.