Repeated origins, widespread gene flow, and allelic interactions of target-site herbicide resistance mutations
Abstract
Causal mutations and their frequency in agricultural fields are well-characterized for herbicide resistance. However, we still lack understanding of their evolutionary history: the extent of parallelism in the origins of target-site resistance (TSR), how long these mutations persist, how quickly they spread, and allelic interactions that mediate their selective advantage. We addressed these questions with genomic data from 18 agricultural populations of common waterhemp (Amaranthus tuberculatus), which we show to have undergone a massive expansion over the past century, with a contemporary effective population size (Ne) estimate of 8x107. We found variation at seven characterized TSR loci, two of which had multiple amino acid substitutions, and three of which were common. These three common resistance variants show parallelism in their mutational origins, with gene flow having shaped their distribution across the landscape. Allele age estimates supported a strong role of adaptation from de novo mutations, with a median allele age of 30 suggesting that most resistance alleles arose soon after the onset of herbicide use. However, resistant lineages varied in both their age and evidence for selection over two different timescales, implying considerable heterogeneity in the forces that govern their persistence. The evolutionary history of TSR has also been shaped by both intra- and inter-locus allelic interactions. We report a signal of extended haplotype competition between two common TSR alleles, and extreme linkage with genome-wide alleles with known functions in resistance adaptation. Together, this work reveals a remarkable example of spatial parallel evolution in a metapopulation, with important implications for the management of herbicide resistance.
Data availability
Sequencing data used in this paper were previously deposited in ENA under project number PRJEB31711, and reference genome is available on CoGe (reference ID = 54057). Code used to generate results in this paper is available at https://github.com/jkreinz/TSRevolution.
Article and author information
Author details
Funding
Natural Sciences and Engineering Research Council of Canada (PGS-D)
- Julia M Kreiner
Society for the Study of Evolution (Rosemary Grant Advanced Award)
- Julia M Kreiner
Natural Sciences and Engineering Research Council of Canada (Discovery Grant)
- John Stinchcombe
- Stephen Isaac Wright
Canada Research Chairs (Population Genomics)
- Stephen Isaac Wright
Max Planck Institute for Dynamics of Complex Technical Systems Magdeburg
- Detlef Weigel
The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.
Copyright
© 2022, Kreiner et al.
This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.
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