Insecticides are important for chemical control of arthropod pests in agricultural systems but select for resistance as an adaptive trait. Identifying the genetic mechanism(s) underpinning resistance can facilitate development of genetic markers, which can be used in monitoring programs. Moreover, understanding of genetic mechanisms in a broader population genetic context can be used to infer the origins of resistance, predict the dynamics of resistance evolution and evaluate the efficacy of different management strategies. Transitioning genetic information successfully into practical solutions requires overcoming two major hurdles. Firstly, genetic mechanisms must be identified to develop genetic markers. Secondly, routine use of genetic markers is required to build substantial spatio‐temporal data on the distribution and frequency of resistance alleles. In this study, we demonstrate large knowledge gaps on the genetic mechanisms of insecticide resistances in Australia using eight established arthropod pests important to the grains industry: Bemisia tabaci (silverleaf whitefly), Frankliniella occidentalis (western flower thrips), Halotydeus destructor (redlegged earth mite), Helicoverpa armigera (cotton bollworm), Myzus persicae (green peach aphid), Plutella xylostella (diamondback moth), Tetranychus urticae (two‐spotted spider mite) and Thrips tabaci (onion thrips). Many resistances have not been characterised at the genetic level in most pests, even for chemical MoA groups with a long history of use in Australia. Moreover, monitoring of resistance is spatio‐temporally patchy, which precludes examination of long‐term trends or predictive modelling. We suggest that leveraging cumulative global knowledge of resistances to develop a priori candidate genes, and incorporation of genomic approaches, can help overcome the hurdles of embracing genetic information in resistance management. We highlight the recently invasive Spodoptera frugiperda (fall armyworm) as a case study where genetic markers and genomic approaches should prove useful in rapidly assessing the risk of this species to the Australian grains industry and other agricultural commodities. The uptake of genetic information into management can only occur once its benefit to empower insecticide resistance research is fully realised. Ultimately, the road ahead requires amalgamation of multifaceted data (genes, environment and spatio‐temporal replication) to better understand and predict the dynamics of resistance evolution.

中文翻译：

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利用遗传信息增强澳大利亚抗药性研究的未来之路

杀虫剂对于农业系统中节肢动物害虫的化学控制很重要，但选择抗性为适应性状。确定支持抗性的遗传机制可以促进遗传标记的开发，这些遗传标记可用于监测程序。此外，在更广泛的种群遗传背景下对遗传机制的了解可用于推断抗药性的起源，预测抗药性进化的动态并评估不同管理策略的功效。成功地将遗传信息转化为实际解决方案需要克服两个主要障碍。首先，必须确定遗传机制以发展遗传标记。其次，需要常规使用遗传标记来建立有关抗性等位基因分布和频率的大量时空数据。在这项研究中，我们使用八种对谷物工业很重要的已建立的节肢动物害虫，证明了澳大利亚对杀虫剂抗性的遗传机制的大量知识空白：烟粉虱（银叶粉虱），西花蓟马（西花蓟马），Halotydeus析构函数（redlegged大地螨），棉铃虫（棉铃虫），桃蚜（桃蚜），小菜蛾（小菜蛾），棉叶螨（二斑叶螨）和蓟马烟粉（洋葱蓟马）。在大多数有害生物中，即使是在澳大利亚具有悠久历史的化学MoA组，也没有在遗传水平上鉴定出许多抗性。此外，对耐药性的监测在时间上是零散的，因此无法检查长期趋势或预测模型。我们建议利用累积的抗性全球知识来开发先验候选基因，并整合基因组方法，可以帮助克服在抗性管理中拥抱遗传信息的障碍。我们重点介绍最近入侵的斜纹夜蛾（Spodoptera frugiperda）（秋夜蛾）作为案例研究，其中遗传标记和基因组方法应被证明有助于快速评估该物种对澳大利亚谷物工业和其他农产品的风险。只有在充分认识到遗传信息赋予杀虫剂抗药性的好处后，才能将遗传信息纳入管理。最终，未来的道路要求融合多方面的数据（基因，环境和时空复制），以更好地理解和预测抗性进化的动态。