Genome-based diagnostics for monitoring and evaluation of insecticide resistance in Anopheles gambiae

 描述(申请人提供)：疟疾是撒哈拉以南非洲(SSA)死亡和发病的主要原因，也是该地区经济发展的最大障碍之一。疟疾是由按蚊传播的，控制这些蚊子的主要方法之一是使用化学杀虫剂。不幸的是，只有四种化学类别的杀虫剂获得许可用于控制蚊子，所有类别的杀虫剂都已出现抗药性，尽管抗药性的水平存在显著差异。这种抗药性对疟疾控制界最近在减少死亡和疟疾感染方面取得的进展构成了重大威胁。为了减少抗药性的影响，疟疾控制项目管理者需要知道他们的干预地区何时出现抗药性，并采取措施防止其传播，例如改用一种新的杀虫剂。最有效的方法是使用DNA标记，它可以在蚊子种群出现高频率之前检测到与抗性相关的标记的存在。这项提议的主要目标是通过为控制项目提供新的标记和地理校准的地图来预测它们对抗药性表型的影响，从而彻底改变SSA疟疾流行国家对杀虫剂耐药性的分子标记的应用。这个项目的统一主题是利用全基因组测序的力量来识别与杀虫剂抗性相关的基因/调控区域。我们将结合使用多种方法，包括对现有基因组数据库的计算机搜索；在东非和西非对疟疾蚊子进行大规模收集和抗药性筛选，以及实验室交叉实验，以确定罕见的抗药性相关变异。所有这些研究都将以惠康信托桑格研究所进行的广泛的全基因组测序为基础。该项目的一个主要次要成果将是向研究界发布这些基因组数据集，这将成为媒介生物学家的强大资源。一旦我们确定了与耐药性相关的DNA标记，我们将校准它们与耐药性的联系，然后绘制它们在SSA合作者网络提供的扩大蚊子集合中的频率和分布。我们将使用建模方法从这些数据中生成标记图，包括它们对关键环境变量的预测能力的敏感性。我们的项目将开发和应用新的生物信息学、实验室和田间方法，为当前和未来的杀虫剂识别DNA标记和相关的图谱资源，为防治计划提供长期的杀虫剂抗性管理工具。

 DESCRIPTION (provided by applicant): Malaria is a major cause of mortality and morbidity in Sub-Saharan Africa (SSA) and one of the biggest impediments to the economic development of the region. Malaria is transmitted by Anopheles mosquitoes and one of the major methods for controlling these mosquitoes is through the use of chemical insecticides. Unfortunately, there are only four chemical classes of insecticides licensed for used for mosquito control, and resistance has already emerged to all classes although with a marked difference in levels. This resistance is a major threat to the recent advances the malaria control community has made in reducing both deaths and malaria infections. To reduce the impact of resistance, malaria control program managers need to know when resistance is emerging in their intervention areas and put in place measures to prevent its spread e.g. switching to a new insecticide. The most effective way of doing this is through the use of DNA markers which can detect the presence of a resistance associated marker in a mosquito population before it reaches high frequency. It is the primary goal of this proposal to revolutionize the application of molecular markers for insecticide resistance across the malaria endemic countries of SSA by providing control programs with new markers and geographically-calibrated maps that predict their impact on resistance phenotypes. The unifying theme of this project is to exploit the power of whole genome sequencing to identify genes/regulatory regions that are associated with insecticide resistance. We will use a combination of approaches including computer-based searches of existing genome data bases; large scale collections and resistance screening of malaria mosquitoes in both East and West Africa, and laboratory crossing experiments to identify rare, resistance-associated variants. All these studies will be underpinned by extensive whole genome sequencing performed by the Wellcome Trust Sanger Institute. A major secondary outcome of this project will be the release of these genome data sets to the research community which will be a powerful resource for vector biologists. Once we have identified resistance-associated DNA markers we will calibrate their links with resistance and then map their frequencies and distributions in expanded collections of mosquitoes provided by a network of collaborators in SSA. We will use modelling approaches to produce marker maps from these data, including the sensitivity of their predictive power to key environmental variables. Our project will develop and apply new bioinformatic, laboratory and field methodologies to identify DNA markers and associated mapping resources for current and future insecticides, providing long-term insecticide resistance management tools for control programs.