The genetics of behavioral resistance in Anopheles gambiae (M)

描述(申请人提供)：疟疾控制关键取决于两种广泛使用的控制方法：长效杀虫蚊帐(LLIN)和室内残留喷洒(IRS)。这两种方法都依赖于室内杀虫剂的应用，并成功地瞄准了在室内觅食和休息的媒介。LLINs和IRS的有效性受到杀虫剂耐药性和蚊子行为变化的威胁。这种行为抵抗包括将媒介转移到户外叮咬和休息。虽然杀虫剂抗性的生物学基础已经得到了很好的研究，但对行为抗性的遗传基础却知之甚少。自2004年以来，比奥科岛上的疟疾媒介冈比亚按蚊(M)根据比奥科岛疟疾控制项目(BIMCP)接受国税局的监管。这导致这种蚊子的行为转向了户外寻找寄主。由于百虫威在Bioko上使用的杀虫剂的驱避力较低，而且喷药后5个月的室外叮咬率相同，因此我们推测该种群的行为抗性具有很强的遗传基础。我们将使用DNA池和全基因组测序的方法来定位与户外叮咬有关的基因座。比奥科岛冈比亚亚科(M)种群。2009年至2013年，作为BIMCP媒介监测的一部分，使用人类着陆器收集了室外和室内叮咬蚊子。2009年和2013年的室外和室内样本将被汇集并测序。这将产生200万个SNPs，这些SNPs将被用来识别在室外蚊子和室内叮咬蚊子中出现频率明显更高的等位基因。我们开发了一种新的模拟方法来建立错误发现率(=显著阈值)。这种方法将确定控制后种群中寄主寻找行为变异的基因座。初步结果显示，我们将能够识别频率不同0.069的等位基因。此外，我们将通过比较2004年收集的干预前样本与2009年和2013年控制后的样本来确定在媒介生物控制后频率增加的基因座。结合遗传漂移和抽样效应的模拟将提供错误发现率，从而允许在正选择下识别基因座。这两种方法将提供一份主要疟疾媒介中潜在行为耐药性的候选基因座清单。这将是对行为抵抗的生物学基础的第一次研究 迈出了开发工具的第一步，以监控或对抗我们的 病媒控制工具。

DESCRIPTION (provided by applicant): Malaria control depends crucially on two widespread control methods; long-lasting insecticidal nets (LLINs) and indoor residual spraying (IRS). Both methods rely on the indoor application of insecticides, and successfully target vectors that feed and rest indoors. The efficacy of LLINs and IRS is threatened by insecticide resistance and changes in the mosquito's behavior. This behavioral resistance involves vectors shifting towards outdoor biting and resting. While the biological basis of insecticide resistance is well-studied, nothing is known about the genetic basis of behavioral resistance. The malaria vector Anopheles gambiae (M) on Bioko Island has been subjected to IRS under the Bioko Island Malaria Control Project (BIMCP) since 2004. This has resulted in a shift of this mosquito's behavior towards outdoor host seeking. Because the bendiocarb insecticide used on Bioko has low repellency, and because the outdoor biting rate was the same one vs. five months following spraying, we hypothesize that the behavioral resistance of this population has a strong genetic basis. We will use a DNA pooling and whole genome sequencing approach to map loci involved in outdoor biting in the An. gambiae (M) population on Bioko Island. Outdoor and indoor biting mosquitoes were collected using human landing catches as part of the vector monitoring of the BIMCP from 2009 to 2013. Outdoor and indoor samples from 2009 and 2013 will be pooled and sequenced. This will produce > 2,000,000 SNPs that will be used to identify alleles that occur at significantly higher frequency in the outdoor vs the indoor biting mosquitoes. We have developed a novel simulation approach for establishing the false discovery rate (=significance threshold). This approach will identify loci responsible for variation in host seeking behavior in post-control populations. Preliminary results show that we will be able to identify alleles that differ in frequency by 0.069. In addition, we will identify loci that increased in frequency followng the vector control by comparing pre-intervention samples collected in 2004 to post-control 2009 and 2013 samples. Simulations that incorporate genetic drift and sampling effects will provide the false discovery rate, allowing the identification of loci under positive selection. These two approaches will provide a list of candidate loci underlying behavioral resistance in a major malaria vector. This will be the first study into the biological basis of behavioral resistance and takes the first step towards developing the tools to monitor or counteract this major threat to our vector control tools.