International Symposium on Cereal Leaf Blights 2019 | University College Dublin, Ireland | 22-24 May 2019

Predicting resistance: functional constraints and experimental evolution in Zymoseptoria tritici

Nichola Hawkins*
Rothamsted Research, UK

Bart Fraaije
Rothamsted Research, UK

Oral Presentation
Cultural Management, Fungicide Resistance and Epidemiology

Moore Auditorium, UCD O'Brien centre for Science
22 May 2019, 17:40

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One of the major obstacles to durable control of Zymoseptoria tritici has been its high adaptive potential, as shown through the evolution of resistance to multiple classes of fungicides as well as overcoming multiple host resistance genes.

We can therefore predict, for any new fungicide, that there is a risk of resistance evolving; but can the precise nature of resistance be predicted in advance? Predicting the form of resistance would allow diagnostics to be developed pre-emptively, and resistance management guidelines to take account of likely resistance levels and cross-resistance patterns. At a more fundamental level, this system can be used as a model to tell us about the predictability or otherwise of evolution in general. Is the evolutionary outcome highly dependent on the earlier steps, making it contingent on historical factors such as which fungicides were used when and which mutations appeared first? Or do functional constraints, such as the need for the fungicide target site to retain its original enzymatic activity, limit the evolutionary options such that any different pathways will soon converge on the same destination?

We make use of the functional genetic tools available in Z. tritici to investigate the functional constraints on target site evolution, constructing alternative haplotypes to test the viability of alternative evolutionary pathways. We also carry out experimental evolution, simulating different scenarios of fungicide use from different genetic starting points. We have also evaluated, in hindsight, the predictability of evolution in older fungicide classes for which resistance is already widespread, determining which factors are important for future predictions.