The coevolutionary dynamics of pleiotropic genetic architecture

项目摘要/摘要 宿主和寄生虫的共同进化是由基因突变介导的，这种突变允许一方获得相对于 其他的。由于宿主免疫系统承担着应对不断进化的寄生虫的主要负担，因此预计它将适应或 因应自然选择而多样化。然而，最近的种群遗传学分析仅来自各种动物分类群 部分证实了这一假设，揭示了先天免疫基因谱系之间缺乏适应性进化。 为期望干杯。我最近的研究表明，相当大比例的基因与先天免疫有关 在与人类、昆虫和植物一样广泛的分类群中，反应是多效性的，这意味着它们也在 其他生物特征，如发育和对非生物压力的反应。这一观察结果提出了以下可能性 基因产物用于发育和免疫功能之间的时间和进化紧张关系。 目前的共同进化理论在很大程度上未能解释寄主防御的遗传限制来源，阻碍了 将现有的共同进化模型转化为分子或系统水平上的进化动力学预测。 展望未来，我的实验室的一个主要研究重点将是探索多效性遗传结构在 宿主免疫系统在应对寄生虫压力时的进化能力。 为了实现这一长期目标，我的实验室将采用几种互补的方法。使用转录组数据，我们 将定义发育、应激和免疫途径基因之间的多效性的程度和动态 昆虫模式物种的多样性。我们将对这些昆虫物种进行全基因组进化遗传学分析，以 量化多效性和非多效性发育、免疫和应激反应的选择特征 相对于零预期的基因集。我们将建立免疫途径蛋白质网络的数学模型 拥有不同的属性-模块化、冗余性、复杂性、多变性-并允许它们与 寄生虫，量化适应环境的变化，以更好地了解限制或促进主机的网络结构 适应。同时，我们将利用面粉甲虫卡氏拟谷盗及其天然物种进行共同进化实验。 寄生虫。我们将在这些过程中操纵免疫和其他过程之间的多重拮抗的力量 通过将宿主-微生物的相互作用限制在特定的发育阶段或改变非生物胁迫条件的实验， 然后比较宿主-微生物相互作用结果的进化轨迹和遗传基础。 总之，这些研究途径将提供对一系列关于遗传程度的基本问题的洞察 基本生理过程之间的多效性，多效性对共同进化动力学的影响及其作用 宿主对寄生虫压力的适应中的免疫系统结构。对进化力量有更深入的了解 这种生物系统的形状对于预测人类病原体的进化具有重要意义，理解 自身免疫和败血症等疾病的起源，以及设计将副作用降至最低的治疗方法。

PROJECT SUMMARY/ABSTRACT The coevolution of hosts and parasites is mediated by genetic mutations that allow one side to gain an advantage over the other. As the host immune system bears the primary burden of responding to evolving parasites, it is expected to adapt or diversify in response to natural selection. However, recent population genetics analyses from a variety of animal taxa only partially bear out this hypothesis, revealing a paucity of adaptive evolution among innate immune gene repertoires relative to expectations. My recent work suggests that an appreciable proportion of genes associated with innate immune responses in taxa as broad as humans, insects and plants are pleiotropic, meaning that they also play unrelated roles in other organismal traits like development and the response to abiotic stress. This observation raises the possibility of temporal and evolutionary tension between the use of a gene product for developmental and immunological functions. Current coevolutionary theory largely fails to account for sources of genetic constraint on host defenses, impeding the translation of existing coevolutionary models into predictions for evolutionary dynamics at the molecular or system level. Moving forward, a major focus of research in my lab will be to explore the role of pleiotropic genetic architecture on the evolvability of host immune systems in response to parasite pressure. To tackle this long-term objective, my lab will employ several complementary approaches. Using transcriptome data, we will define the extent and dynamics of pleiotropy among developmental, stress, and immunological pathway genes in a variety of insect model species. We will perform genome-wide evolutionary genetics analyses in these insect species to quantify signatures of selection on pleiotropic and non-pleiotropic developmental, immunological, and stress response gene sets relative to null expectations. We will build mathematical models of immune pathway protein networks possessing different properties – modularity, redundancy, complexity, pleiotropy – and allow them to co-evolve with parasites, quantifying changes in fitness landscapes to better understand network structures that constrain or promote host adaptation. In parallel, we will run coevolution experiments using the flour beetle Tribolium castaneum and its natural parasites. We will manipulate the strength of pleiotropic antagonism among immunity and other processes in these experiments by limiting host-microbe interactions to a particular developmental stage or altering abiotic stress conditions, and then compare the evolutionary trajectories and genetic bases of host-microbe interaction outcomes. Together, these research avenues will provide insight into an array of fundamental questions about the extent of genetic pleiotropy among essential physiological processes, the influence of pleiotropy on coevolutionary dynamics, and the role of immune system architecture in host adaptation to parasite pressure. Gaining greater insight into the evolutionary forces that shape biological systems has important implications for predicting human pathogen evolution, understanding the origins of diseases like autoimmunity and sepsis, and designing therapeutic treatments that minimize side effects.