Saubin Méline, Stoeckel Solenn, Tellier Aurélien, Halkett Fabien
Université de Lorraine, INRAE, IAM, Nancy, France.
Professorship for Population Genetics, Department of Life Science Systems, School of Life Science, Technical University of Munich, Freising, Germany.
J Hered. 2025 Jan 3;116(1):62-77. doi: 10.1093/jhered/esae036.
Pathogen species are experiencing strong joint demographic and selective events, especially when they adapt to a new host, for example through overcoming plant resistance. Stochasticity in the founding event and the associated demographic variations hinder our understanding of the expected evolutionary trajectories and the genetic structure emerging at both neutral and selected loci. What would be the typical genetic signatures of such a rapid adaptation event is not elucidated. Here, we build a demogenetic model to monitor pathogen population dynamics and genetic evolution on two host compartments (susceptible and resistant). We design our model to fit two plant pathogen life cycles, "with" and "without" host alternation. Our aim is to draw a typology of eco-evolutionary dynamics. Using time-series clustering, we identify three main scenarios: 1) small variations in the pathogen population size and small changes in genetic structure, 2) a strong founder event on the resistant host that in turn leads to the emergence of genetic structure on the susceptible host, and 3) evolutionary rescue that results in a strong founder event on the resistant host, preceded by a bottleneck on the susceptible host. We pinpoint differences between life cycles with notably more evolutionary rescue "with" host alternation. Beyond the selective event itself, the demographic trajectory imposes specific changes in the genetic structure of the pathogen population. Most of these genetic changes are transient, with a signature of resistance overcoming that vanishes within a few years only. Considering time-series is therefore of utmost importance to accurately decipher pathogen evolution.
病原体物种正经历着强烈的联合种群统计学和选择事件,尤其是当它们适应新宿主时,例如通过克服植物抗性。奠基事件中的随机性以及相关的种群统计学变化阻碍了我们对预期进化轨迹以及在中性和选择位点出现的遗传结构的理解。这种快速适应事件的典型遗传特征尚未阐明。在此,我们构建了一个种群遗传学模型来监测病原体在两个宿主区室(感病和抗病)中的种群动态和遗传进化。我们设计模型以适应两种植物病原体的生命周期,即“有”和“没有”寄主交替的情况。我们的目标是绘制生态进化动态的类型学。通过时间序列聚类,我们识别出三种主要情况:1)病原体种群大小的微小变化和遗传结构的微小改变;2)在抗病宿主上发生强烈的奠基事件,进而导致在感病宿主上出现遗传结构;3)进化拯救,导致在抗病宿主上发生强烈的奠基事件,之前在感病宿主上经历瓶颈。我们明确了生命周期之间的差异,特别是在“有”寄主交替的情况下有更多的进化拯救。除了选择事件本身,种群统计学轨迹还会对病原体种群的遗传结构产生特定变化。这些遗传变化大多是短暂的,抗性克服的特征仅在几年内就会消失。因此,考虑时间序列对于准确解读病原体进化至关重要。