Please use this identifier to cite or link to this item: http://hdl.handle.net/11667/243
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dc.contributorTinsley, Matthew C-
dc.contributor.otherBBSRC - Biotechnology and Biological Sciences Research Councilen_GB
dc.contributor.otherSão Paulo Research Foundation (FAPESP), Brazilen_GB
dc.contributor.otherVetenskapsrådet, Swedenen_GB
dc.contributor.otherCarl Trygger Foundation (20:63), Swedenen_GB
dc.creatorMangan, Rosie M-
dc.creatorTinsley, Matthew C-
dc.creatorFerrari, Ester-
dc.creatorPolanczyk, Ricardo Antônio-
dc.creatorBussière, Luc F-
dc.date.accessioned2025-01-28T09:22:11Z-
dc.date.available2025-01-28T09:22:11Z-
dc.date.created2024-
dc.identifier.urihttp://hdl.handle.net/11667/243-
dc.description.abstractPathogens often exert strong selection on host populations, yet considerable genetic variation for resistance persists. Environmental heterogeneity may cause fitness trade-offs that help prevent fixation of pathogen resistance alleles in wild host populations. Pathogens are extensively used in biocontrol, yet the risks of pest resistance evolution are frequently underappreciated, and the key drivers of fitness trade-offs for pathogen resistance remain unclear, both in natural and managed populations. We investigate whether pathogen identity or host diet has a stronger effect on the fitness of resistance alleles by quantifying genetic variation and covariation for pathogen resistance in an insect pest across distinct pathogen and plant diet combinations. We demonstrate substantial heritability, indicating considerable risks of biopesticide resistance. Contrary to conventional thinking in host-pathogen biology, we found no strong genetic trade-offs for surviving exposure to two different fungal pathogen species. However, changes in plant diet dramatically altered selection, revealing diet-mediated genetic trade-offs affecting pest survival. Our data suggest that trade-offs in traits not strictly related to pathogen defence could nevertheless maintain genetic variation in natural and agricultural landscapes.en_GB
dc.description.tableofcontentsThis submission contains (1) a csv file containing raw data: Quan_Gene_APRIL_12_2023_RM_LFB.csv (2) an R script file that will perform analysis: ManganetalGEIforrxiv.R (3) model objects derived from the script and data ManganBigModels.RData. These data were derived from experiments on larvae of the crop pest Helicoverpa armigera. The larvae were fed one of three leaf diets (Maize, Soybean, Tomato) and were exposed to one of three infection treatments (which simulated biopesticide exposure (Beauveria bassiana, Metarhizium anisopliae, Uninfected (oil) control). Larvae originated from different family lines with a know relatedness structure. This enables calculation of the genetic variance and covariances for survival in different diet-infection treatment groups.en_GB
dc.language.isoengen_GB
dc.publisherUniversity of Stirling, School of Natural Sciencesen_GB
dc.relationMangan, RM; Tinsley, MC; Ferrari, E; Polanczyk, RA; Bussière, LF (2025): Exploiting pathogen defence trade-offs to manage risks of crop pest evolution against biocontrol agents. Version 1. University of Stirling, School of Natural Sciences. Dataset, Collection, Software. http://hdl.handle.net/11667/243en_GB
dc.rightsRights covered by the standard CC-BY 4.0 licence: https://creativecommons.org/licenses/by/4.0/en_GB
dc.sourceLaboratory Experimentsen_GB
dc.subjectEvolutionen_GB
dc.subjectParasiteen_GB
dc.subject.classification::Agri-environmental scienceen_GB
dc.titleExploiting pathogen defence trade-offs to manage risks of crop pest evolution against biocontrol agentsen_GB
dc.typecollectionen_GB
dc.typedataseten_GB
dc.typesoftwareen_GB
dc.description.versionVersion 1en_GB
dc.contributor.emailmt18@stir.ac.uken_GB
dc.identifier.projectidBB/R022674/1en_GB
dc.identifier.projectidBB/S018956/1en_GB
dc.title.projectOvercoming insecticide resistance using diverse fungal pathogens and variable agricultural landscapesen_GB
dc.title.projectEnhancing Diversity to Overcome Resistance Evolutionen_GB
dc.contributor.affiliationUniversity of Stirling (BES)en_GB
dc.contributor.affiliationJúlio de Mesquita Filho State University of São Pauloen_GB
dc.contributor.affiliationThe University of Gothenburgen_GB
dc.identifier.wtid351316en_GB
dc.identifier.wtid972970en_GB
Appears in Collections:University of Stirling Research Data

Files in This Item:
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Quan_Gene_APRIL_12_2023_RM_LFB.csvRaw data file356.46 kBUnknownView/Open
ManganetalGEIforrxiv.RR script80.26 kBUnknownView/Open
ManganBigModels.RDataModel objects556.27 MBUnknownView/Open


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