Population genomics of selectively neutral genetic structure and herbicide resistance in UK populations of Alopecurus myosuroides

BACKGROUND Alopecurus myosuroides (blackgrass) is a major weed in Europe with known resistance to multiple herbicide modes of action. In the UK, there is evidence that blackgrass has undergone a range expansion. In this paper, genotyping‐by‐sequencing and population‐level herbicide resistance phenotypes are used to explore spatial patterns of selectively neutral genetic variation and resistance. We also perform a preliminary genome‐wide association study and genomic prediction analysis to evaluate the potential of these approaches for investigating non‐target site herbicide resistance. RESULTS Blackgrass was collected from 47 fields across the British Isles and up to eight plants per field population (N = 369) were genotyped by RAD‐sequencing. 20,426 polymorphic loci were identified and used for population genetic analyses. Phenotypic assays revealed significant variation in herbicide resistance between populations. Population structure was weak (FST = 0.024‐0.048), but spatial patterns were consistent with an ongoing westward and northward range expansion. We detected strong and consistent Wahlund effects (FIS = 0.30). There were no spatial patterns of herbicide resistance or evidence for confounding with population structure. Using a combination of population‐level GWAS and genomic prediction we found that the top 20, 200, and 2,000 GWAS loci had higher predictive abilities for fenoxaprop resistance compared to all markers. CONCLUSION There is likely extensive human‐mediated gene flow between field populations of the weed, blackgrass at a national scale. The lack of confounding of adaptive and neutral genetic variation can enable future, more extensive GWAS analyses to identify the genetic architecture of evolved herbicide resistance

Sequence Characterization of Extra-Chromosomal Circular DNA Content in Multiple Blackgrass (Alopecurus myosuroides) Populations.

Alopecurus myosuroides (blackgrass) is a problematic weed of Western European winter wheat, and its success is largely due to widespread multiple-herbicide resistance. Previous analysis of F2 seed families derived from two distinct blackgrass populations exhibiting equivalent non-target site resistance (NTSR) phenotypes shows resistance is polygenic and evolves from standing genetic variation. Using a CIDER-seq pipeline, we show that herbicide-resistant (HR) and herbicide-sensitive (HS) F3 plants from these F2 seed families as well as the parent populations they were derived from carry extra-chromosomal circular DNA (eccDNA). We identify the similarities and differences in the coding structures within and between resistant and sensitive populations. Although the numbers and size of detected eccDNAs varied between the populations, comparisons between the HR and HS blackgrass populations identified shared and unique coding content, predicted genes, and functional protein domains. These include genes related to herbicide detoxification such as Cytochrome P450s, ATP-binding cassette transporters, and glutathione transferases including AmGSTF1. eccDNA content was mapped to the A. myosuroides reference genome, revealing genomic regions at the distal end of chromosome 5 and the near center of chromosomes 1 and 7 as regions with a high number of mapped eccDNA gene density. Mapping to 15 known herbicide-resistant QTL regions showed that the eccDNA coding sequences matched twelve, with four QTL matching HS coding sequences; only one region contained HR coding sequences. These findings establish that, like other pernicious weeds, blackgrass has eccDNAs that contain homologs of chromosomal genes, and these may contribute genetic heterogeneity and evolutionary innovation to rapidly adapt to abiotic stresses, including herbicide treatment

Novel and holistic approaches are required to realise allelopathic potential for weed management

Allelopathy, i.e. plant-plant inhibition via the release of secondary metabolites into the environment, has potential for the management of weeds by circumventing herbicide resistance. However, mechanisms underpinning allelopathy are notoriously difficult to elucidate, hindering real-world application either in the form of commercial bioherbicides or allelopathic crops. Such limited application is exemplified by evidence of limited knowledge of the potential benefits of allelopathy among end-users. Here, we examine potential applications of this phenomenon, paying attention to novel approaches and influential factors requiring greater consideration, with the intention of improving the reputation and uptake of allelopathy. Avenues to facilitate more effective allelochemical discovery are also considered, with a view to stimulating the identification of new compounds and allelopathic species. Synthesis and Applications: We conclude that tackling increasing weed pressure on agricultural productivity would benefit from greater integration of the phenomenon of allelopathy, which in turn would be greatly served by a multi-disciplinary and exhaustive approach, not just through more effective isolation of the interactions involved, but through greater consideration of factors which may influence them in the field, facilitating optimisation of their benefits for weed management

The blackgrass genome reveals patterns of non-parallel evolution of polygenic herbicide resistance

Globally, weedy plants are a major constraint to sustainable crop production. Much of the success of weeds rests with their ability to rapidly adapt in the face of human-mediated management of agroecosystems. Alopecurus myosuroides (blackgrass) is a widespread and impactful weed affecting agriculture in Europe. Here we report a chromosome-scale genome assembly of blackgrass and use this reference genome to explore the genomic/genetic basis of non-target site herbicide resistance (NTSR). Based on our analysis of F2 seed families derived from two distinct blackgrass populations with the same NTSR phenotype, we demonstrate that the trait is polygenic and evolves from standing genetic variation. We present evidence that selection for NTSR has signatures of both parallel and non-parallel evolution. There are parallel and non-parallel changes at the transcriptional level of several stress- and defense-responsive gene families. At the genomic level, however, the genetic loci underpinning NTSR are different (non-parallel) between seed families. We speculate that variation in the number, regulation and function of stress- and defense-related gene families enable weedy species to rapidly evolve NTSR via exaptation of genes within large multi-functional gene families. These results provide novel insights into the potential for, and nature of plant adaptation in rapidly changing environments

RNA and protein biomarkers for detecting enhanced metabolic resistance to herbicides mesosulfuron-methyl and fenoxaprop-ethyl in black-grass (Alopecurus myosuroides)

BACKGROUND: The evolution of non-target site resistance (NTSR) to herbicides leads to a significant reduction in herbicide control of agricultural weed species. Detecting NTSR in weed populations prior to herbicide treatment would provide valuable information for effective weed control. While not all NTSR mechanisms have been fully identified, enhanced metabolic resistance (EMR) is one of the better studied, conferring tolerance through increased herbicide detoxification. Confirming EMR towards specific herbicides conventionally involves detecting metabolites of the active herbicide molecule in planta, but this approach is time consuming and requires access to well-equipped laboratories. RESULTS: In this study, we explore the potential of using molecular biomarkers to detect EMR before herbicide treatment in black-grass (Alopecurus myosuroides). We test the reliability of selected biomarkers to predict EMR, and survival after herbicide treatments in both reference and 27 field-derived black-grass populations collected from sites across the UK. The combined analysis of the constitutive expression of biomarkers, and metabolism studies confirmed three proteins namely, AmGSTF1, AmGSTU2 and AmOPR1, as differential biomarkers of EMR toward the herbicides fenoxaprop-ethyl and mesosulfuron in black-grass. CONCLUSION: Our findings demonstrate that there is potential to use molecular biomarkers to detect EMR toward specific herbicides in black-grass without reference to metabolism analysis. However, biomarker development must include testing at both transcript and protein levels in order to be reliable indicators of resistance. This work is a first step towards more robust resistance biomarker development, which could be expanded into other herbicide chemistries, for on-farm testing and monitoring EMR in uncharacterised black-grass populations

RNA and protein biomarkers for detecting enhanced metabolic resistance to herbicides mesosulfuron-methyl and fenoxaprop-ethyl in black-grass (<em>Alopecurus myosuroides</em>)

\ua9 2024 The Authors. Pest Management Science published by John Wiley &amp; Sons Ltd on behalf of Society of Chemical Industry. BACKGROUND: The evolution of non-target site resistance (NTSR) to herbicides leads to a significant reduction in herbicide control of agricultural weed species. Detecting NTSR in weed populations prior to herbicide treatment would provide valuable information for effective weed control. While not all NTSR mechanisms have been fully identified, enhanced metabolic resistance (EMR) is one of the better studied, conferring tolerance through increased herbicide detoxification. Confirming EMR towards specific herbicides conventionally involves detecting metabolites of the active herbicide molecule in planta, but this approach is time-consuming and requires access to well-equipped laboratories. RESULTS: In this study, we explored the potential of using molecular biomarkers to detect EMR before herbicide treatment in black-grass (Alopecurus myosuroides). We tested the reliability of selected biomarkers to predict EMR and survival after herbicide treatments in both reference and 27 field-derived black-grass populations collected from sites across the UK. The combined analysis of the constitutive expression of biomarkers and metabolism studies confirmed three proteins, namely, AmGSTF1, AmGSTU2 and AmOPR1, as differential biomarkers of EMR toward the herbicides fenoxaprop-ethyl and mesosulfuron in black-grass. CONCLUSION: Our findings demonstrate that there is potential to use molecular biomarkers to detect EMR toward specific herbicides in black-grass without reference to metabolism analysis. However, biomarker development must include testing at both transcript and protein levels in order to be reliable indicators of resistance. This work is a first step towards more robust resistance biomarker development, which could be expanded into other herbicide chemistries for on-farm testing and monitoring EMR in uncharacterised black-grass populations. \ua9 2024 The Authors. Pest Management Science published by John Wiley &amp; Sons Ltd on behalf of Society of Chemical Industry

The role of interspecific variability and herbicide pre-adaptation in the cinmethylin response of Alopecurus myosuroides

BACKGROUND: Cinmethylin is an inhibitor of plant fatty acid biosynthesis, with in-plant activity caused by its binding to fatty acid thioesterases (FAT). The recent registration of cinmethylin for pre-emergence herbicidal use in the UK represents a new mode of action (MOA) for control of the grassweed blackgrass (Alopecurus myosuroides). To date there is little published information on the extent of blackgrass’ inter-population variability in sensitivity to cinmethylin, nor on any potential effect of existing non-target-site resistance (NTSR) mechanisms on cinmethylin efficacy. RESULTS: Here we present a study of variability in cinmethylin sensitivity amongst 97 UK blackgrass populations. We demonstrate that under controlled conditions, a UK field-rate dose of 500 g ha-1 provides effective control of the tested populations. Nevertheless, we reveal significant inter-population variability at doses below this rate, with populations previously characterised as strongly NTSR displaying the lowest sensitivity to cinmethylin. Assessment of paired resistant “R” and sensitive “S” lines from standardised genetic backgrounds confirms that selection for NTSR to the acetyl-CoA-carboxylase inhibitor fenoxaprop, and the microtubule assembly inhibitor pendimethalin, simultaneously results in reduced sensitivity to cinmethylin at doses below 500 g ha-1. Whilst we find no resistance to the field-rate dose, we reveal that cinmethylin sensitivity can be further reduced through experimental selection with cinmethylin. CONCLUSION: Cinmethylin therefore represents a much-needed further MOA for blackgrass control, but needs to be carefully managed within a resistance monitoring and integrated weed management (IWM) framework to maximise the effective longevity of this compound

Evolutionary epidemiology predicts the emergence of glyphosate resistance in a major agricultural weed

The evolution of resistance to herbicides is a striking example of rapid, human-directed adaptation with major consequences for food production. Most studies of herbicide resistance are performed reactively and focus on post-hoc determination of resistance mechanisms following the evolution of field resistance. If the evolution of resistance can be anticipated however, pro-active management to slow or prevent resistance traits evolving can be advocated. We report a national-scale study that combines population monitoring, glyphosate sensitivity assays, quantitative genetics and epidemiological analyses to pro-actively identify the prerequisites for adaptive evolution (directional selection and heritable genetic variation) to the world’s most widely used herbicide (glyphosate) in a major, economically damaging weed species, Alopecurus myosuroides. Results highlighted pronounced, heritable variability in glyphosate sensitivity amongst UK A. myosuroides populations. We demonstrated a direct epidemiological link between historical glyphosate selection and current population-level sensitivity, and show that current field populations respond to further glyphosate selection. This study provides a novel, pro-active assessment of adaptive potential for herbicide resistance, and provides compelling evidence of directional selection for glyphosate insensitivity in advance of reports of field resistance. The epidemiological approach developed can provide a basis for further pro-active study of resistance evolution across pesticide resistance disciplines

A deep learning application to map weed spatial extent from unmanned aerial vehicles imagery

Weed infestation is a global threat to agricultural productivity, leading to low yields and financial losses. Weed detection, based on applying machine learning to imagery collected by Unmanned Aerial Vehicles (UAV) has shown potential in the past; however, validation on large data-sets (e.g., across a wide number of different fields) remains lacking, with few solutions actually made operational. Here, we demonstrate the feasibility of automatically detecting weeds in winter wheat fields based on deep learning methods applied to UAV data at scale. Focusing on black-grass (the most pernicious weed across northwest Europe), we show high performance (i.e., accuracy above 0.9) and highly statistically significant correlation (i.e., ro > 0.75 and p < 0.00001) between imagery-derived local and global weed maps and out-of-bag field survey data, collected by experts over 31 fields (205 hectares) in the UK. We demonstrate how the developed deep learning model can be made available via an easy-to-use docker container, with results accessible through an interactive dashboard. Using this approach, clickable weed maps can be created and deployed rapidly, allowing the user to explore actual model predictions for each field. This shows the potential for this approach to be used operationally and influence agronomic decision-making in the real world

Alterations in life-history associated with non-target-site herbicide resistance in Alopecurus myosuroides

The evolution of resistance to herbicides is a classic example of rapid contemporary adaptation in the face of a novel environmental stress. Evolutionary theory predicts that selection for resistance will be accompanied by fitness trade-offs in environments where the stress is absent. Alopecurus myosuroides, an autumn-germinating grass weed of cereal crops in North-West Europe, has evolved resistance to seven herbicide modes-of-action, making this an ideal species to examine the presence and magnitudes of such fitness costs. Here, we use two contrasting A. myosuroides phenotypes derived from a common genetic background, one with enhanced metabolism resistance to a commercial formulation of the sulfonylurea (ALS) actives mesosulfuron and iodosulfuron, and the other with susceptibility to these actives (S). Comparisons of plant establishment, growth, and reproductive potential were made under conditions of intraspecific competition, interspecific competition with wheat, and over a gradient of nitrogen deprivation. Herbicide dose response assays confirmed that the two lines had contrasting resistance phenotypes, with a 20-fold difference in resistance between them. Pleiotropic effects of resistance were observed during plant development, with R plants having a greater intraspecific competitive effect and longer tiller lengths than S plants during vegetative growth, but with S plants allocating proportionally more biomass to reproductive tissues during flowering. Direct evidence of a reproductive cost of resistance was evident in the nitrogen deprivation experiment with R plants producing 27 percent fewer seed heads per plant, and a corresponding 23 percent reduction in total seed head length. However, these direct effects of resistance on fecundity were not consistent across experiments. Our results demonstrate that a resistance phenotype based on enhanced herbicide metabolism has pleiotropic impacts on plant growth, development and resource partitioning but does not support the hypothesis that resistance is associated with a consistent reproductive fitness cost in this species. Given the continued difficulties associated with unequivocally detecting costs of herbicide resistance, we advocate future studies that adopt classical evolutionary quantitative genetics approaches to determine genetic correlations between resistance and fitness-related plant life history trait