A - Papers appearing in refereed journals
Comont, D., Macgregor, D., Crook, L., Hull, R. I., Nguyen, L., Freckleton, R. P., Childs, D. Z. and Neve, P. 2022. Dissecting weed adaptation: fitness and trait correlations in herbicide resistant Alopecurus myosuroides. Pest Management Science. https://doi.org/10.1002/ps.6930
|Authors||Comont, D., Macgregor, D., Crook, L., Hull, R. I., Nguyen, L., Freckleton, R. P., Childs, D. Z. and Neve, P.|
BACKGROUND: Unravelling the genetic architecture of non-target-site resistance (NTSR) traits in weed populations can inform questions about the inheritance, trade-offs and fitness costs associated with these traits. Classical quantitative genetics approaches allow study of the genetic architecture of polygenic traits even where the genetic basis of adaptation remains unknown. These approaches have the potential to overcome some of the limitations of previous studies into the genetics and fitness of NTSR.
RESULTS: Using a quantitative genetic analysis of 400 pedigreed Alopecurus myosuroides seed families from nine field-collected populations, we found strong heritability for resistance to the ALS and ACCase inhibitors (h2 = 0.731 and 0.938 respectively), and evidence for shared additive genetic variance for resistance to these two different herbicide modes-of-action, rg = 0.34 (survival), 0.38 (biomass). We find no evidence for genetic correlations between life-history traits and herbicide resistance, indicating that resistance to these two modes of action is not associated with large fitness costs in blackgrass. We do, however, demonstrate that phenotypic variation in plant flowering characteristics is heritable: h2 = 0.213 (flower height), 0.529 (flower head number), 0.449 (time to flowering), and 0.372 (time to seed shed), demonstrating the potential for adaptation to other non-chemical management practices (e.g. mowing of flowering heads) now being adopted for blackgrass control.
CONCLUSION: These results highlight that quantitative genetics can provide important insight into the inheritance and genetic architecture of NTSR, and can be used alongside emerging molecular techniques to better understand the evolutionary and fitness landscape of herbicide resistance.
|Keywords||Quantitative genetics; Non-target-site; Fitness; Evolutionary potential; Herbicide resistance|
|Year of Publication||2022|
|Journal||Pest Management Science|
|Digital Object Identifier (DOI)||https://doi.org/10.1002/ps.6930|
|Open access||Published as ‘gold’ (paid) open access|
|Funder||Biotechnology and Biological Sciences Research Council|
|Agriculture and Horticulture Development Board|
|Funder project or code||Multiple Herbicide Resistance in Grass Weeds: from Genes to AgroEcosystems|
|BBSRC Strategic Programme in Smart Crop Protection|
|Accepted author manuscript|
|Online||18 Apr 2022|
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