bioRxivEvolutionary Biology
The complex genomic basis of rapid convergent adaptation to pesticides across continents in a fungal plant pathogen
F. Hartmann, T. Vonlanthen, N. K. Singh, M. C. McDonald, A. Milgate, D. Croll
Abstract
Convergent evolution leads to identical phenotypic traits in different species or populations. Convergence can be driven by standing variation allowing selection to favor identical alleles in parallel or the same mutations can arise independently. However, the molecular basis of such convergent adaptation remains often poorly resolved. Pesticide resistance in agricultural ecosystems is a hallmark of convergence in phenotypic traits. Here, we analyze the major fungal pathogen Zymoseptoria tritici causing serious losses on wheat and with parallel fungicide resistance emergence across continents. We sampled three population pairs each from a different continent spanning periods early and late in the application of fungicides. To identify causal loci for resistance, we combined knowledge from molecular genetics work and performed genome-wide association studies (GWAS) on a global set of isolates. We discovered yet unknown factors in azole resistance including membrane stability functions. We found strong support for the hotspot model of resistance evolution with parallel changes in a small set of loci but additional loci showed more population-specific allele frequency changes. Genome-wide scans of selection showed that half of all known resistance loci were overlapping a selective sweep region. Hence, the application of fungicides was one of the major selective agents acting on the pathogen over the past decades. Furthermore, loci identified through GWAS showed the highest overlap with selective sweep regions underlining the importance to map phenotypic trait variation in evolving populations. Our population genomic analyses showed that both de novo mutations and gene flow likely contributed to the parallel emergence of resistance.
- organism: fungi (other)
- assay: whole-genome sequencing
- research focus: variant calling
- research focus: gene regulatory network inference
- approach: statistical model
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