The role of population and quantitative genetics and modern sequencing technologies to understand evolved herbicide resistance and weed fitness

Evolution of resistance to multiple herbicides with different sites of action and of nontarget site resistance (NTSR) often involves multiple genes. Thus, single-gene analyses, typical in studies of target site resistance, are not sufficient for understanding the genetic architecture and dynamics of NTSR and multiple resistance. The genetics of weed adaptation to varied agricultural environments is also generally expected to be polygenic. Recent advances in whole-genome sequencing as well as bioinformatic and statistical tools have made it possible to use population and quantitative genetics methods to expand our understanding of how resistance and other traits important for weed adaptation are genetically controlled at the individual and population levels, and to predict responses to selection pressure by herbicides and other environmental factors. The use of tools such as quantitative trait loci mapping, genome-wide association studies, and genomic prediction will allow pest management scientists to better explain how pests adapt to control tools and how specific genotypes thrive and spread across agroecosystems and other human-disturbed systems. The challenge will be to use this knowledge in developing integrated weed management systems that inhibit broad resistance to current and future weed-control methods. (c) 2020 The Authors.Pest Management Sciencepublished by John Wiley & Sons Ltd on behalf of Society of Chemical Industry.

Automated summary

The evolution of resistance to multiple herbicides and non-target site resistance often involves multiple genes, leading to a polygenic control of weed adaptation. Advances in whole-genome sequencing and bioinformatic tools have enabled a better understanding of genetic control of resistance and other important traits in weed adaptation, allowing for predictions of responses to selection pressure by herbicides and other environmental factors. The use of tools such as quantitative trait loci mapping and genomic prediction will help in explaining how pests adapt to control tools and how specific genotypes thrive and spread.