The genetics of behavioral resistance in Anopheles gambiae (M)

描述（由申请人提供）：疟疾控制主要依赖于两种广泛的控制方法；长效杀虫蚊帐（LLINs）和室内残留喷洒（IRS）。这两种方法都依赖于室内使用杀虫剂，并成功地针对在室内进食和休息的病媒。杀虫剂抗性和蚊虫行为变化对低剂量杀虫剂和高剂量杀虫剂的效果构成威胁。这种行为抵抗包括病媒转向户外叮咬和休息。虽然对杀虫剂抗性的生物学基础研究得很充分，但对行为抗性的遗传基础却一无所知。自2004年以来，在比奥科岛疟疾控制项目（BIMCP）下，对比奥科岛的疟疾媒介冈比亚按蚊(M)进行了IRS控制。这导致这种蚊子的行为转向户外寻找宿主。由于本品杀虫剂驱避力较低，且喷施后1个月与5个月室外叮咬率基本一致，本品推测本品种群的行为抗性具有较强的遗传基础。我们将使用DNA池和全基因组测序方法来绘制与印第安人户外咬人有关的位点。比奥科岛上的冈比亚人(M)。2009 - 2013年，作为BIMCP病媒监测的一部分，采用人落捕法采集了室外和室内叮蚊。将收集2009年和2013年的室外和室内样本并进行测序。这将产生大约200万个snp，用于识别在室外叮咬蚊子比室内叮咬蚊子出现频率高得多的等位基因。我们开发了一种新的模拟方法来建立错误发现率（=显著性阈值）。这种方法将确定控制后种群中宿主寻找行为变异的基因座。初步结果表明，我们将能够识别频率差异为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，确定在病媒控制后频率增加的基因座。结合遗传漂变和采样效应的模拟将提供错误的发现率，允许在正选择下识别位点。这两种方法将提供一份主要疟疾病媒中潜在行为抗性的候选基因座清单。这将是首次研究行为抵抗的生物学基础

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.