Natural variation in wild tomato trichomes; selecting metabolites that contribute to insect resistance using a random forest approach

BMC Plant Biology

Frans M. van der Kloet¹  Bart André²  Ruy W. J. Kortbeek³  Robert C. Schuurink³  Petra M. Bleeker³  Aleksandra Muras³  Marc D. Galland³  Michel A. Haring³  Maurice Heilijgers³  Sacha A. F. T. van Hijum⁴ 

[1] Data Analysis Group, Swammerdam Institute for Life Sciences, University of Amsterdam, 1098 XH, Amsterdam, The Netherlands;Enza Zaden Research & Development B.V, Haling 1E, 1602 DB, Enkhuizen, The Netherlands;Green Life Science Research Cluster, Swammerdam Institute for Life Sciences, University of Amsterdam, 1098 XH, Amsterdam, The Netherlands;Radboud University Medical Center, Bacterial Genomics Group, Geert Grooteplein Zuid 26-28, 6525 GA, Nijmegen, The Netherlands;

关键词: Tomato;    Trichomes;    Specialised metabolites;    Insect resistance;    Whitefly;    Thrips;    Random forest;    Volatiles;    Acylsugars;   

DOI  :  10.1186/s12870-021-03070-x

来源: Springer

【 摘 要 】

BackgroundPlant-produced specialised metabolites are a powerful part of a plant’s first line of defence against herbivorous insects, bacteria and fungi. Wild ancestors of present-day cultivated tomato produce a plethora of acylsugars in their type-I/IV trichomes and volatiles in their type-VI trichomes that have a potential role in plant resistance against insects. However, metabolic profiles are often complex mixtures making identification of the functionally interesting metabolites challenging. Here, we aimed to identify specialised metabolites from a wide range of wild tomato genotypes that could explain resistance to vector insects whitefly (Bemisia tabaci) and Western flower thrips (Frankliniella occidentalis). We evaluated plant resistance, determined trichome density and obtained metabolite profiles of the glandular trichomes by LC-MS (acylsugars) and GC-MS (volatiles). Using a customised Random Forest learning algorithm, we determined the contribution of specific specialised metabolites to the resistance phenotypes observed.ResultsThe selected wild tomato accessions showed different levels of resistance to both whiteflies and thrips. Accessions resistant to one insect can be susceptible to another. Glandular trichome density is not necessarily a good predictor for plant resistance although the density of type-I/IV trichomes, related to the production of acylsugars, appears to correlate with whitefly resistance. For type VI-trichomes, however, it seems resistance is determined by the specific content of the glands. There is a strong qualitative and quantitative variation in the metabolite profiles between different accessions, even when they are from the same species. Out of 76 acylsugars found, the random forest algorithm linked two acylsugars (S3:15 and S3:21) to whitefly resistance, but none to thrips resistance. Out of 86 volatiles detected, the sesquiterpene α-humulene was linked to whitefly susceptible accessions instead. The algorithm did not link any specific metabolite to resistance against thrips, but monoterpenes α-phellandrene, α-terpinene and β-phellandrene/D-limonene were significantly associated with susceptible tomato accessions.ConclusionsWhiteflies and thrips are distinctly targeted by certain specialised metabolites found in wild tomatoes. The machine learning approach presented helped to identify features with efficacy toward the insect species studied. These acylsugar metabolites can be targets for breeding efforts towards the selection of insect-resistant cultivars.

【 授权许可】

CC BY