BBSRC-HGCA Black-grass Resistance Initiative

Unravelling herbicide resistance in black-grass from gene to field

In the advanced agricultural production systems of Northern Europe, weed control in cereal crops has become one of the greatest challenges to sustainable intensification, accounting for higher yield losses and greater input costs than all other biological constraints (pests and diseases). The most problematic weeds in cereals in Northern Europe are the wild grasses, notably black-grass (Alopecurus myosuroides), which has become steadily more difficult to control over the last 30 years due to the evolution of herbicide resistance. This resistance assumes two forms: 1) Target site resistance (TSR), whereby the weeds become highly tolerant of herbicides due to mutations in the proteins targeted by these chemicals rendering them less sensitive to inhibition by that herbicide mode of action. 2) Metabolic or multiple herbicide resistance (MHR) where weeds become more tolerant of a broad range of herbicides, irrespective of their chemistry or mode of action, due to a general enhancement in the ability to detoxify crop protection agents. While TSR is now quite well understood and can be countered by the rotational use of herbicides with differing modes of action, the molecular basis and evolutionary drivers which promote MHR are poorly understood and the associated grass weeds very difficult to control using conventional methods.

In this 4 year project, we are using a combination of molecular biology and biochemistry, ecology and evolution, modelling and integrated pest management to develop better tools to monitor and manage both TSR and MHR in black-grass under field conditions. The project represents a novel agri-systems approach, linking our latest understanding in the molecular biology of herbicide resistance to on farm monitoring and modelling based on a quantitative genetics approach to define the effectiveness of different intervention measures. Through a multidisciplinary consortium, we will integrate knowledge about MHR and TSR at the molecular and biochemical levels and relate this fundamental understanding to resistance phenotypes observed in the field. Selection and breeding experiments will examine the dynamics of selection for resistance, with the intention of determining the genetic architecture of MHR for the first time and its relation to other stresses and life history traits. Data from field monitoring and glasshouse studies will be integrated in ecological, evolutionary and management models with the ultimate aim to design novel management to prevent, delay or mitigate the evolution of herbicide resistance. Finally, the environmental and economic impacts of novel management will be explored. The project therefore has the primary goal of using state of the art approaches spanning molecular biology, weed science, modeling and agronomy to provide new resistance control measures within the life of the programme.


Core Project

Work Package 1: Molecular mechanisms underpinning the evolution of MHR in black-grass (2014-2018)

The primary output of the work package will be the generation of diagnostic tools which will allow herbicide resistance diagnostics and auditing in the field and the study of the evolutionary development of metabolic herbicide resistance (MHR) in the field. This work-package will address the following: 1) What is the level of variation in the MHR genotype and phenotype in different resistant black-grass populations and what can this tell us about the evolutionary origins of the trait? 2) Can this information be used to develop molecular diagnostic kits which can reliably identify MHR populations in the field and rapidly distinguish these from target site resistant weeds for control purposes? 3) How many stress-response pathways are activated during the acquisition of MHR and what is their relationship to endogenous signalling responses?

Who is involved? Rob Edwards (PI) and Paul Neve (CI)

Work Package 2: Black-grass population monitoring and resistance audit (2014-2018)

The primary output of the work package will be a baseline dataset on weed abundance, MHR and TSR status, and historical farm management. This work-package will address the following: 1) Conduct surveys to provide the long-term data for parameterising and validating models of black-grass dynamics. 2) Perform a resistance audit across the range of black-grass distribution for key herbicide modes of action.

Who is involved? Rob Freckleton (PI), Paul Neve (CI) and Rob Edwards (CI)

Work Package 3: Genetic architecture and inheritance of MHR (2014-2018)

Research on Australian populations of rigid ryegrass (Lolium rigidum) has clearly established that naive populations harbour significant additive genetic variation for MHR. In selection experiments, this standing variation can be selected and recombined to rapidly increase the herbicide resistance phenotype. Adaptation to herbicides is not cost-free and significant trade-offs between resistance and plant fitness in the absence of herbicide have been demonstrated. In this work package, evolutionary quantitative genetics approaches will be adopted to determine the heritability of non-target site herbicide resistance, as well as the genetic correlations between resistance and other fitness-related life history traits. This work-package will address the following: 1) Determine the quantitative genetic architecture of metabolic herbicide resistance in selected UK black-grass populations. 2) To explore trade-offs between defence (MHR/stress tolerance), growth and reproduction in black-grass populations.

Who is involved? Paul Neve (PI), Dylan Childs (CI), Rob Freckleton (CI), Jarrod Hadfield (CI) and Rob Edwards (CI)

Work Package 4: Eco-evolutionary modelling of black-grass populations (2015-2018)

The primary output of the work package will be a data-driven assessment of the evolutionary potential of black-grass populations for MHR evolution, enabling the wider implications of management to be addressed. A general model describing the density and size-/age-structured dynamics of local weed populations will underpin our analyses. This will couple two sub-models. The first will capture the among-year dynamics of the seed bank, derived from classic ecological models of annual weeds. This will allow us to evaluate the impact of historic patterns of selection on the evolutionary potential of the seed bank. The second sub-model will be based on the integral projection model, which describes the within-season dynamics of newly established weeds in terms of individual-level processes. This work-package will address the following: 1) Develop a novel integrated modelling framework to explore the joint eco-evolutionary dynamics of weed populations in agri-ecosystems. 2) Predict the management implications of interactions between ecological and evolutionary processes. 3) Evaluate the robustness of these predictions to assumptions about spatial processes, stochasticity and genetic architecture.

Who is involved? Dylan Childs (PI), Rob Freckleton (CI), Paul Neve (CI) and Jarrod Hadfield (CI)

Work Package 5: Assessing wider impacts of resistance and management (2016-2018)

The primary output of the work package will be potential solutions to resistance management that also minimize adverse economic or environmental impacts. To achieve this, we plan to explore the economic consequences of resistance management strategies using farm-scale cost-benefit analysis. Environmental impacts of resistance management strategies will be analysed using approaches that enable us to consider farmland biodiversity, water quality and greenhouse gas emissions. This work-package will address the following: 1) Develop future scenarios of land-use change and management, including potential strategies to minimize or reduce herbicide resistance. 2) Translate these scenarios into the land-use and management changes we would expect to see in the countryside. 3) Assess the potential impacts of these scenarios on herbicide resistance, farm economics and the environment. 4) Identify significant risks in terms of herbicide resistance, farm economics or the environment associated with each scenario, design management responses and re-assess risks.

Who is involved? Ken Norris (PI), Rob Freckleton (CI) and Dylan Childs (CI)
  • PI: Primary Investigators
  • CI: Co-Investigators
  • PP: Project Partners
  • PD: Post Doctoral Research Associates

Associated Research

Information about related projects and PhD studentships associated with the BBSRC-HGCA funded BGRI will be described here as the project develops.