Abstract
Plants produce diverse metabolites to cope with the challenges presented by complex and ever-changing environments. These challenges drive the diversification of specialized metabolites within and between plant species. However, we are just beginning to understand how frequently new alleles arise controlling specialized metabolite diversity and how the geographic distribution of these alleles may be structured by ecological and demographic pressures. Here, we measure the variation in specialized metabolites across a population of 797 natural Arabidopsis thaliana accessions. We show that a combination of geography, environmental parameters, demography and different genetic processes all combine to influence the specific chemotypes and their distribution. This showed that causal loci in specialized metabolism contain frequent independently generated alleles with patterns suggesting potential within-species convergence. This provides a new perspective about the complexity of the selective forces and mechanisms that shape the generation and distribution of allelic variation that may influence local adaptation.
Highlights
Continuous and dynamic change in a plants habitat/environment creates a complex system to which a plant must adapt
In this work we described Glucosinolate 90 (GSL) variation in seeds of a collection of 797 Arabidopsis thaliana natural accessions collected from different locations mainly in and around Europe
Using Arabidopsis QTL mapping populations and GWA, we have shown that the GS-AOP, Elong and OH loci determine seven discrete chemotypes, 3MSO, 4MSO, 3OHP, 4OHB, Allyl, 3-Butenyl, 2-OH-3-Butenyl (Figure 2), that can be readily assigned from GSLs phenotypic data (Brachi et al, 2015; Chan et al, 2011, 2010; D J Kliebenstein, Gershenzon, et al, 2001)
Summary
Continuous and dynamic change in a plants habitat/environment creates a complex system to which a plant must adapt. Individual specialized metabolites can defend the plant against some stressors while simultaneously making the plant more sensitive to other biotic or abiotic stresses (Agrawal, 2000; Bialy, Oleszek, Lewis, & Fenwick, 1990; Erb & Kliebenstein, 2020; Futuyma & Agrawal, 2009; Hu et al, 2018; Lankau, 2007; Opitz & Müller, 2009; Uremıs, Arslan, Sangun, Uygur, & Isler, 2009; Züst & Agrawal, 2017) These opposing effects create offsetting ecological benefits and costs for individual metabolites. Integrating these offsetting effects across dynamic environments involves multiple selective pressures that might contribute to shaping the genetic and metabolic variation within a species (Fan, Leong, & Last, 2019; R. Kerwin et al, 2015; Malcolm, 1994; Sønderby, Geu-Flores, & Halkier, 2010; Szakiel, Pączkowski, & Henry, 2011; Wentzell & Kliebenstein, 2008; Züst et al, 2012)
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