新疆棉花蚜虫-寄生蜂食物网结构的分子检测体系

为明确新疆棉花蚜虫-寄生蜂的食物网结构，通过设计新疆棉花蚜虫和寄生蜂的特异性引物，建立并优化可以在物种水平上开展棉花蚜虫-寄生蜂食物网结构分析的分子检测方法，该方法包括3个多重PCR检测体系（cMP1、cPriMP2和cHypMP3）和1个单一PCR（cSP1）检测体系，并应用建立的方法对采自库尔勒、阿克苏、昌吉的2 383头僵蚜样品进行分子检测。结果表明，4个体系的灵敏度均较高，其中蚜虫cMP1体系的检出限为500 DNA拷贝数，初级寄生蜂cPriMP2体系的检出限为5 000 DNA拷贝数，重寄生蜂cHypMP3和cSP1体系的DNA检出限分别为500拷贝数和100拷贝数。该方法能够快速且准确地鉴定4种棉花蚜虫、4种初级寄生蜂和7种重寄生蜂，特异性良好。使用该方法对供试僵蚜样品进行检测并成功绘制出新疆棉花蚜虫-初级寄生蜂-重寄生蜂食物网，定量分析了不同初级寄生蜂对蚜虫的寄生作用及重寄生蜂与初级寄生蜂之间形成的食物网络关系。表明所建立的分子检测方法可以用于评估不同种类寄生蜂在新疆棉花蚜虫种群控制中的生态功能，解析物种间的食物网关系。

A molecular detection approach for assessing cotton aphid-primary parasitoid-hyperparasitoid food webs in Xinjiang, China

In order to clarify the aphid-parasitoid food web structure in Xinjiang cotton fields, a molecular approach was developed and optimized based on the species-specific primers designed for cotton aphids and their parasitoids, which can be used for the aphid-parasitoid food web structure analysis at species-specific level. This molecular approach included three multiplex PCRs (cMP1, cPriMP2 and cHypMP3) and one singleplex PCR (cSP1). A total of 2 383 mummy samples, collected from different areas of Xinjiang, including Korla, Changji and Aksu, were detected by this approach.The results showed that, in the sensitivity detections, the detection limits were 500, 5 000, 500 and 100 DNA copies for aphid system cMP1, primary parasitoid system cPriMP2, hyperparasitoid systems cHypMP3 and cSP1, respectively. This molecular approach could be used for rapid and accurate identification of four aphid, four parasitoid and seven hyperparasitoid species in Xinjiang cotton fields. Based on the results of mummy samples, a tri-trophic aphid-primary parasitoid-hyperparasitoid food web was sketched, and the parasitism effect of each primary parasitoid and the interactions between different primary parasitoids and hyperparasitoids were analyzed quantitatively. The results indicated that the approach provided in the present study could be used for evaluating the ecological functions of various parasitoids in aphid population suppression and analyzing the food web interactions in Xinjiang.