Genetic analysis reveals long-standing population differentiation and high diversity in the rust pathogen Melampsora lini

• Published in: PLoS pathogens 2020-08, Vol.16 (8), p.e1008731-e1008731
• Main Authors: Susi, Hanna, Burdon, Jeremy J, Thrall, Peter H, Nemri, Adnane, Barrett, Luke G
• Format: Article
• Language: English
• Subjects: Adaptation; Asexual reproduction; Basidiomycota; Bayesian analysis; Biology and Life Sciences; Clustering; Demography; Differentiation; Distribution; Ecology and Environmental Sciences; Epidemics; Epidemiology; Flax; Fluctuations; Food; Gene polymorphism; Genes; Genetic analysis; Genetic aspects; Genetic structure; Genomes; Genotypes; Genotyping; Haplotypes; Infectious diseases; Infectivity; Linum marginale; Loci; Medicine and Health Sciences; Melampsora lini; Natural history; Natural populations; Nucleotide sequence; Pathogens; Phenotypes; Phenotypic variations; Polymorphism; Population; Population differentiation; Population dynamics; Population genetics; Population number; Populations; Reproduction (biology); Research and Analysis Methods; Rust fungi; Seasons; Single-nucleotide polymorphism; Variance analysis
• ISSN: 1553-7374; 1553-7366; 1553-7374
• DOI: 10.1371/journal.ppat.1008731

A priority for research on infectious disease is to understand how epidemiological and evolutionary processes interact to influence pathogen population dynamics and disease outcomes. However, little is understood about how population adaptation changes across time, how sexual vs. asexual reproduction contribute to the spread of pathogens in wild populations and how diversity measured with neutral and selectively important markers correlates across years. Here, we report results from a long-term study of epidemiological and genetic dynamics within several natural populations of the Linum marginale-Melampsora lini plant-pathogen interaction. Using pathogen isolates collected from three populations of wild flax (L. marginale) spanning 16 annual epidemics, we probe links between pathogen population dynamics, phenotypic variation for infectivity and genomic polymorphism. Pathogen genotyping was performed using 1567 genome-wide SNP loci and sequence data from two infectivity loci (AvrP123, AvrP4). Pathogen isolates were phenotyped for infectivity using a differential set. Patterns of epidemic development were assessed by conducting surveys of infection prevalence in one population (Kiandra) annually. Bayesian clustering analyses revealed host population and ecotype as key predictors of pathogen genetic structure. Despite strong fluctuations in pathogen population size and severe annual bottlenecks, analysis of molecular variance revealed that pathogen population differentiation was relatively stable over time. Annually, varying levels of clonal spread (0-44.8%) contributed to epidemics. However, within populations, temporal genetic composition was dynamic with rapid turnover of pathogen genotypes, despite the dominance of only four infectivity phenotypes across the entire study period. Furthermore, in the presence of strong fluctuations in population size and migration, spatial selection may maintain pathogen populations that, despite being phenotypically stable, are genetically highly dynamic.