A pangenomic approach to understanding the evolution of insecticide resistance

昆虫对杀虫剂抗药性的演变对许多重要农作物害虫和病媒的可持续控制构成了越来越大的威胁，威胁到全球粮食安全和人类健康。为了有效地对抗抗性，了解其潜在的基因组结构是至关重要的，包括支持抗性的遗传变异及其对表型的影响。在过去的二十年里，基因组测序技术的进步极大地促进了对杀虫剂抗性遗传基础的研究。然而，在影响抗性的遗传变异的类型和数量以及它们对表型的相对贡献方面，关键的知识差距仍然存在。许多理解上的缺陷与当前的范例有关，即使用单一的参考基因组作为大多数基因组分析的起点。这种方法意味着参考文献中没有出现的某些类型的遗传变异通常仍未被发现。这个问题对于包括存在-缺失变异(PAV)、拷贝数变异(CNV)和染色体重排在内的结构变异(SV)来说尤其严重，因此，这些变异被称为基因组的暗物质。未能有效地表征SV是很重要的，因为在人类中，SVS已被证明比任何其他类型的序列变体对每个核苷酸的基因组变化的影响更大。此外，我们和其他人的研究已经提供了明确的证据，表明SV可能是害虫抗药性进化过程中遗传变异的关键来源。本项目的总体目标是开发一种新的基因组分析范式，用于害虫抗药性等适应性性状的基因组分析。我们将利用测序技术的最新进展，结合一种特殊的生物资源，包括具有破坏性的作物害虫桃蚜的全球采样克隆的活体文库，以组装这种害虫的pangenome，即出现在一个物种中的所有DNA序列的集合。这一史无前例的资源将使我们能够首次描述全球农作物害虫物种的完整遗传变异谱，并解决有关昆虫基因组和SV在适应进化中的作用的多个关键知识空白。这些包括了解害虫种群中结构变异的盘根组的百分比，不同的SV类型之间的差异，多长时间和多少SV导致基因功能或表达的变化，以及至关重要的是，它们与关键表型性状(如抗药性)的总体相关性和贡献。我们的分析将集中在三种经常与杀虫剂抗性有关的SV类型上，包括CNV、PAV和染色体重排。然后，我们将测试在我们的蚜虫克隆文库中发现的全部遗传变异与杀虫剂抗性之间的关联。最后，我们将研究不同类型的SVS对基因表达和基因功能的影响，并使用功能方法验证选择的候选SVS在抗性中的作用。总之，这些分析将使我们能够以前所未有的方式从根本上和系统地询问杀虫剂抗性的遗传决定因素。在这个项目中产生的知识和工具将为我们理解为昆虫自然选择提供底物的遗传变异提供根本进展，并为制定可持续控制高度破坏性的全球分布的作物害虫的战略提供强大的资源。

The evolution of insect resistance to insecticides represents a growing threat to the sustainable control of many important insect crop pests and disease vectors, threatening global food security and human health. To effectively combat resistance, it is critically important to understand its underlying genomic architecture, including the genetic variants underpinning resistance and their affect on phenotype. Advances in genome sequencing technology over the last two decades have greatly facilitated investigation of the genetic basis of insecticide resistance. However, key knowledge gaps remain on the type and number of genetic variants affecting resistance and their relative contribution to phenotype. Many of these deficits in understanding relate to the current paradigm of using a single reference genome as the starting point for most genomic analyses. This approach means that certain types of genetic variation not present in the reference typically remain undiscovered. This problem is particularly acute for structural variation (SV) encompassing presence-absence variation (PAV), copy number variation (CNV) and chromosomal rearrangements, which, as a consequence, have been referred to as the 'dark matter' of the genome. The failure to effectively characterise SV is important, as in humans SVs have been shown to affect more of the genome per nucleotide change than any other class of sequence variant. Furthermore, research by ourselves and others has provided clear evidence that SV can be a key source of genetic variation in the evolution of insecticide resistance.The overarching objective of this project is to develop a new paradigm for the genomic analysis of adaptive traits such as insecticide resistance in pest insects. We will leverage recent advances in sequencing technology, in combination with an exceptional biological resource comprising a living library of globally sampled clones of the damaging aphid crop pest Myzus persicae, to assemble the pangenome, the collection of all the DNA sequences that occur in a species, of this pest. This unprecedented resource will allow us to characterise the complete spectrum of genetic variation in a global crop pest species for the first time, and address multiple key knowledge gaps on the insect pangenome and the role of SV in adaptive evolution. These include understanding the percentage of the pangenome that is structurally variant in pest populations and how this differs across different SV types, how often and how many SVs lead to changes in gene function or expression, and crucially, their overall relevance and contribution to key phenotypic traits such as insecticide resistance. Our analyses will focus on three types of SV that have been frequently implicated in insecticide resistance, comprising CNV, PAV and chromosomal rearrangements. We will then test for association between the full spectrum of genetic variation identified in our aphid clone library and insecticide resistance. Finally, we will examine the impact of different types of SVs on gene expression and gene function, and validate the role of a selection of candidate SVs in resistance using functional approaches. Together, these analyses will allow us to fundamentally and systematically interrogate the genetic determinants of insecticide resistance in a way that has never been previously possible.The knowledge and tools generated in this project will provide both fundamental advances in our understanding of the genetic variation that provides the substrate for natural selection in insects, and powerful resources to develop strategies for the sustainable control of highly damaging, globally distributed crop pests.