DISSERTATION RESEARCH: Can the degree of mimicry predict levels of genetic structure among populations? A test using mimetic ground beetles

本项目将分析来自南美洲的一种新型模仿系统的遗传多样性的空间格局，以研究在模仿系统中驱动相似性的过程是否也能促进物种内部的多样性。模仿系统是研究生物多样性产生过程的优秀自然实验室，在模仿系统中，多个物种进化出相互相似性以减少捕食。拟态系统中的物种通常表现出不同的地理形态，这就提出了这种多样性是如何起源和维持的问题。解决这个问题将量化自然选择在促进和维持种群间遗传分化中的作用。此外，本研究将为利用形态性状预测遗传结构水平提供依据。后者对于保护目的特别有用，特别是在可能无法获得遗传数据的群体或系统中。这些目标将通过使用下一代测序数据对Ceroglossus属模拟甲虫进行精细尺度景观遗传研究来解决。样本将在具有不同地理形态和表型匹配水平的地区收集，并从两个或三个不同的物种中收集。颜色差异和遗传分化之间的相关性测试将告知模仿的选择是否会影响遗传结构的水平，而基于模型的人口统计学推断将提供严格的统计，以区分驱动这种模式的具体机制。该项目将鼓励与智利研究人员和学生合作，研究一种新的、迷人的模式系统。

This project will analyze spatial patterns of genetic diversity in a novel mimicry system from South America to investigate whether the processes driving resemblance in mimicry systems can also promote diversity within species. Mimicry systems, where multiple species evolve mutual resemblance to reduce predation, are excellent natural laboratories to study the processes generating biodiversity. Species in mimetic systems often exhibit diverse geographic morphologies, which raises questions about how this diversity originated and is maintained. Addressing this question will quantify the role of natural selection in promoting and maintaining genetic differentiation among populations. Additionally, this research will provide a basis for using morphological traits to predict levels of genetic structure. The later will be especially useful for conservation purposes, particularly in groups or systems in which genetic data might not be available.These goals will be addressed by conducting a fine scale landscape genetic study on mimetic beetles from the genus Ceroglossus using next generation sequencing data. Samples will be collected across areas with different geographic morphs and levels of phenotypic matching, and from two or three different species. Correlation tests between color differences and genetic differentiation will inform whether selection for mimicry can impact levels of genetic structure, whereas model-based demographic inferences will provide statistical rigor to distinguish between specific mechanisms driving such patterns. This project will encourage collaborative work with Chilean researchers and students on the study of a new and fascinating model system.