Department of Entomology and Plant Pathology, University of Tennessee, 2505 E. J. Chapman Dr., Knoxville, TN 37996, USA.
Department of Biology, Indiana University-Purdue University Indianapolis, 723 W Michigan Street, SL 306, Indianapolis, IN 46202, USA.
J Med Entomol. 2024 May 13;61(3):554-566. doi: 10.1093/jme/tjad115.
The genetic structure of forensically important blow fly (Brauer & Bergenstamm) (Diptera: Calliphoridae) populations has remained elusive despite high relatedness within wild-caught samples. This research aimed to determine if the implementation of a high-resolution spatiotemporal sampling design would reveal latent genetic structure among blow fly populations and to elucidate any environmental impacts on observed patterns of genetic structure. Adult females of the black blow fly, Phormia regina (Meigen) (Diptera: Calliphoridae), were collected from 9 urban parks in Indiana, USA over 3 yr and genotyped at 6 polymorphic microsatellite loci. The data analysis involved 3 clustering methods: principal coordinate analysis (PCoA), discriminant analysis of principal components (DAPC), and STRUCTURE. While the PCoA did not uncover any discernible clustering patterns, the DAPC and STRUCTURE analyses yielded significant results, with 9 and 4 genetic clusters, respectively. Visualization of the STRUCTURE bar plot revealed N = 11 temporal demarcations indicating barriers to gene flow. An analysis of molecular variance of these STRUCTURE-inferred populations supported strong temporally driven genetic differentiation (FST = 0.048, F'ST = 0.664) relative to geographic differentiation (FST = 0.009, F'ST = 0.241). Integrated Nested Laplace Approximation and Boosted Regression Tree analyses revealed that collection timepoint and 4 main abiotic factors (temperature, humidity, precipitation, and wind speed) were associated with the genetic subdivisions observed for P. regina. A complex interplay between environmental conditions, the unique reproductive strategies of the blow fly, and the extensive dispersal abilities of these organisms likely drives the strong genetic structure of P. regina in the Midwestern US.
尽管在野外捕获的样本中存在高度亲缘关系,但法医重要蝇类(Brauer & Bergenstamm)(双翅目:Calliphoridae)种群的遗传结构仍然难以捉摸。本研究旨在确定实施高分辨率时空采样设计是否会揭示蝇类种群之间潜在的遗传结构,并阐明环境对观察到的遗传结构模式的任何影响。在美国印第安纳州的 9 个城市公园中,3 年来共收集了成年黑蝇(Phormia regina(Meigen)(双翅目:Calliphoridae)雌性,并在 6 个多态微卫星基因座上进行了基因分型。数据分析涉及 3 种聚类方法:主坐标分析(PCoA)、主成分判别分析(DAPC)和 STRUCTURE。虽然 PCoA 没有揭示出任何可识别的聚类模式,但 DAPC 和 STRUCTURE 分析产生了显著的结果,分别有 9 个和 4 个遗传聚类。STRUCTURE 条形图的可视化显示了 N = 11 个时间标记,表明存在基因流动的障碍。对这些 STRUCTURE 推断的种群进行的分子方差分析支持了强烈的时间驱动遗传分化(FST = 0.048,F'ST = 0.664)相对于地理分化(FST = 0.009,F'ST = 0.241)。集成嵌套拉普拉斯近似和增强回归树分析表明,收集时间点和 4 个主要非生物因素(温度、湿度、降水和风速)与观察到的 P. regina 遗传细分有关。环境条件、蝇类独特的繁殖策略以及这些生物广泛的扩散能力之间的复杂相互作用可能导致美国中西部 P. regina 具有强烈的遗传结构。