Decoding Non-Target-Site Herbicide Resistance in Sunflower: The Beginning of the Story

Abstract

In the last years, many efforts have been made to develop sunflower cultivars showing important agronomical characteristics such as herbicide resistance. These approaches have been focused mainly on resistance to herbicides with the same mode of action, that is acetohydroxyacid synthase (AHAS) inhibitors. To date, four induced and natural AHAS mutations have been found that confer resistance to these herbicides and many of these alleles are being used for the production of sunflower hybrids resistant to herbicides and to develop different non-transgenic technologies for weed control. However, little is known about the bases of non-target-site-based resistance (NTSR) developing cross-resistance to herbicides with different modes of action in sunflower. These mechanisms diminish the number of active herbicide molecules that reach the target and are generally polygenic. Elucidating the nature of NTSR would allow evaluating maximal efficiency conditions for the herbicide and would enable to establish weed management strategies in sunflower crop. Nowadays, mining of NTSR genes can be more easily accomplished taking advantage of up-to-date omics-based approaches: high-throughput techniques involving genomics, transcriptomics, proteomics and metabolomics. Considering the difficulties in the discovery of new compounds with a broad spectrum of weed control, it results essential to broaden the use of former herbicides which are highly efficient and ecologically desirable. Full understanding of NTSR mechanisms in sunflower would allow detecting specific genes potentially useful as biotechnological tools for the phytoremediation of herbicides and modern plant breeding.

Stress response and detoxification mechanisms involved in non‐target‐site herbicide resistance in sunflower

“…In addition to target‐site resistance (TSR) mechanisms, Imisun sunflowers present non‐target‐site resistance (NTSR) to IMI herbicides (Breccia et al., 2017; Gil, Nestares, et al., 2018; Gil, Ochogavía, Vega, Felitti, & Nestares, 2018; Sala et al., 2012). Although TSR mechanisms in sunflower are well described (Breccia, Vega, Felitti, Picardi, & Nestares, 2013; Kolkman et al., 2004; Sala et al., 2012; Vega et al., 2009, 2012), the nature of NTSR mechanisms has not yet been fully characterized but could be related to xenobiotic metabolism (Gil & Nestares, 2019). Generally, NTSR involves polygenic control (Busi, Vila‐Aiub, & Powles, 2011; Petit, Duhieu, Boucansaud, & Délye, 2010), arises from stress response pathways already present in the plant (Délye, 2012), and includes constitutive and inducible effectors that develop resistance to herbicides with multiple modes of action.…”

“…The high number of P450s, GSTs, ABCs, and other detoxification gene families present in plant genomes increase the complexity of their individual characterization. In this context, high-throughput techniques such as global genome, transcriptome, and proteome sequencing represent a chance to decipher the complex genetic control in NTSR and to identify major genes at large scale (Gil & Nestares, 2019). Combining data provided by transcriptomic, proteomic, and metabolomic experiments may allow better understanding of some important physiological and molecular mechanisms unique to sunflower (Dimitrijevic & Horn, 2018).…”

Mechanistic understanding and sustainable management of non-target site herbicide resistance in modern day agriculture

“…Although NTSR development involves complex processes, a full understanding of NTSR mechanisms allows the detection of genes that can be used as biotechnological tools to develop herbicide-resistant (HR) and parasitic weeds-resistant crops (Gill, Nestares, 2019). Modern omicsbased technologies can play a vital role in mining of NTSR genes.…”

“…Modern omicsbased technologies can play a vital role in mining of NTSR genes. Identification of NTSR alleles procedure is achieved in three main stages; i) conducting controlled crosses of selected weed species and segregating resistant plants from sensitive progeny ii) using a combination of time course and omics analysis to identify phenotype-related differences in gene expression and iii) using NTSR markers and functional characterization methods to validate the candidate alleles (Gill, Nestares, 2019). Recently genome acquisitions enabled the identification of NTSR genes through genetic mapping (Gaines et al, 2020;Jamann et al, 2015).…”

“…However, most of these models are normative and based on assumptions that the cropping systems are predictable. New crop planning decision models need to shift from a single normative approach to the use of biophysical cropping plans which can address the complexity of cropping systems (Van Ittersum et al, 2008;Gill, Nestares, 2019). A transdisciplinary approach to herbicide resistance management is urgently needed since it builds a dynamic scientific framework that integrates biological, economic, environmental, and social systems on weeds exhibiting high evolution rates.…”