Detecting admixture in Anopheles malaria vectors

描述(申请人提供)：使用转基因蚊子根除人类疟疾需要制定蚊子释放策略，这将导致转基因因子的成功传播，而选择最佳策略关键取决于对蚊子种群之间遗传交换的了解。由于缺乏适用于该系统的数据和统计工具，评估疟疾按蚊的基因流动一直受到阻碍。这里提出的研究旨在开发新的计算方法，以检测撒哈拉以南非洲不同时间人类疟疾按蚊媒介种群之间的基因交换。目前的统计方法不适用于按蚊，不区分新旧基因交换，也不能应用于下一代测序技术数据，所有这些都是获得按蚊最近基因流动的有用估计所必需的。将开发一种新的方法来结合这些特征，并将应用于来自三个不同种群的按蚊的数据。这项研究的结果将对三个不同人口之间的基因交流的速度、方向和时间提供有价值的估计，这些信息对于制定最佳的根除疟疾战略至关重要。

DESCRIPTION (provided by applicant): Eradication of human malaria using genetically modified mosquitoes requires the development of mosquito release strategies that will result in successful spread of the transgenic factors, and choosing optimal strategies depends critically on knowledge of genetic exchange among mosquito populations. Assessing gene-flow in Anopheles malaria mosquitoes has been hampered by a lack of data and statistical tools appropriate for the system. The research proposed here aims to develop novel computational methods to detect genetic exchange at different times among populations of Anopheles mosquito vectors of human malaria in sub-Saharan Africa. Current statistical methods are not appropriate for Anopheles, do not distinguish between old and new genetic exchange, and cannot be applied to next-generation sequencing technology data, all of which are necessary to obtain useful estimates of recent gene-flow in Anopheles. A novel method will be developed to incorporate these features, and will be applied to data from three divergent populations of Anopheles. The results of this research will provide valuable estimates of the rate, direction and timing of genetic exchange among three divergent populations, information that is essential for developing optimal malaria eradication strategies.