Population genetic analysis is a powerful tool to understand how pathogens emerge and adapt. However, determining the genetic structure of populations requires complex knowledge on a range of subtle skills that are often not explicitly stated in book chapters or review articles on population genetics. What is a good sampling strategy? How many isolates should I sample? How do I include positive and negative controls in my molecular assays? What marker system should I use? This review will attempt to address many of these practical questions that are often not readily answered from reading books or reviews on the topic, but emerge from discussions with colleagues and from practical experience. A further complication for microbial or pathogen populations is the frequent observation of clonality or partial clonality. Clonality invariably makes analyses of population data difficult because many assumptions underlying the theory from which analysis methods were derived are often violated. This review provides practical guidance on how to navigate through the complex web of data analyses of pathogens that may violate typical population genetics assumptions. We also provide resources and examples for analysis in the R programming environment.

Invasive alien species often have reduced genetic diversity and must adapt to new environments. Given the success of many invasions, this is sometimes called the genetic paradox of invasion.Phytophthora ramorumis invasive, limited to asexual reproduction within four lineages, and presumed clonal. It is responsible for sudden oak death in the United States, sudden larch death in Europe, and ramorum blight in North America and Europe. We sequenced the genomes of 107 isolates to determine how this pathogen can overcome the invasion paradox. Mitotic recombination (MR) associated with transposons and low gene density has generated runs of homozygosity (ROH) affecting 2,698 genes, resulting in novel genotypic diversity within the lineages. One ROH enriched in effectors was fixed in the NA1 lineage. An independent ROH affected the same scaffold in the EU1 lineage, suggesting an MR hot spot and a selection target. Differences in host infection between EU1 isolates with and without the ROH suggest that they may differ in aggressiveness. Non-core regions (not shared by all lineages) had signatures of accelerated evolution and were enriched in putative pathogenicity genes and transposons. There was a striking pattern of gene loss, including all effectors, in the non-core EU2 genome. Positive selection was observed in 8.0% of RxLR and 18.8% of Crinkler effector genes compared with 0.9% of the core eukaryotic gene set. We conclude that theP. ramorumlineages are diverging via a rapidly evolving non-core genome and that the invasive asexual lineages are not clonal, but display genotypic diversity caused by MR.IMPORTANCEAlien species are often successful invaders in new environments, despite the introduction of a few isolates with a reduced genetic pool. This is called the genetic paradox of invasion. We found two mechanisms by which the invasive forest pathogen causing sudden oak and sudden larch death can evolve. Extensive mitotic recombination producing runs of homozygosity generates genotypic diversity even in the absence of sexual reproduction, and rapid turnover of genes in the non-core, or nonessential portion of genome not shared by all isolates, allows pathogenicity genes to evolve rapidly or be eliminated while retaining essential genes. Mitotic recombination events occur in genomic hot spots, resulting in similar ROH patterns in different isolates or groups; one ROH, independently generated in two different groups, was enriched in pathogenicity genes and may be a target for selection. This provides important insights into the evolution of invasive alien pathogens and their potential for adaptation and future persistence.

The ascomycete pathogen Sclerotinia sclerotiorum is a necrotrophic pathogen on over 400 known host plants, and is the causal agent of white mold on dry bean. Currently, there are no known cultivars of dry bean with complete resistance to white mold. For more than 20 years, bean breeders have been using white mold screening nurseries with natural populations of S. sclerotiorum to screen new cultivars for resistance. It is thus important to know if the genetic diversity in populations of S. sclerotiorum within these nurseries a) reflect the genetic diversity of the populations in the surrounding region and b) are stable over time. Furthermore, previous studies have investigated the correlation between mycelial compatibility groups (MCG) and multilocus haplotypes (MLH), but none have formally tested these patterns. We genotyped 366 isolates of S. sclerotiorum from producer fields and white mold screening nurseries surveyed over 10 years in 2003-2012 representing 11 states in the United States of America, Australia, France, and Mexico at 11 microsatellite loci resulting in 165 MLHs. Populations were loosely structured over space and time based on analysis of molecular variance and discriminant analysis of principal components, but not by cultivar, aggressiveness, or field source. Of all the regions tested, only Mexico (n=18) shared no MLHs with any other region. Using a bipartite network-based approach, we found no evidence that the MCGs accurately represent MLHs. Our study suggests that breeders should continue to test dry bean lines in several white mold screening nurseries across the US to account for both the phenotypic and genotypic variation that exists across regions.

Presented here is a new approach to quantify spatial patterns of plant disease in complex fruit tree canopies using point pattern analysis. This work provides a framework for quantitative analysis of three-dimensional spatial patterns within the finite tree canopy, applicable to many fields of research.

Certain species of myxomycetes (plasmodial slime molds) are regularly present with mosses, lichens, and algae. Corticolous myxomycetes were previously studied in the tree canopy, and observations suggested that species occurrence is patchy and species abundance may increase with the presence of bryophytes and lichens. The purpose of this study was to quantify the association of corticolous myxomycete species with percent cover of epiphytes and with bark characteristics, such as water absorption, bark thickness, and bark pH. Study sites were located in three temperate forests in the southeastern USA. The doubled rope climbing method was used to collect bark from trees and grapevines in a vertical transect up to 15 m above ground level. Moist chambers (374) were used to culture myxomycetes for 32 d. The percent cover of lichens, bryophytes, myxobacteria, and filamentous fungi were estimated in five 2 cm × 2 cm quadrats for 187 sample sites. Results showed no association between percent cover of epiphytes and myxomycetes. Bark pH was the major factor influencing the occurrence of corticolous myxomycete species, and the patchy distribution of myxomycetes was attributed to the small plasmodium characteristic of most corticolous species.

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Pathogen exposure to sublethal doses of fungicides may result in mutations that may represent an important and largely overlooked mechanism of introducing new genetic variation into strictly clonal populations, including acquisition of fungicide resistance. We tested this hypothesis using the clonal plant pathogen, Sclerotinia sclerotiorum. Nine susceptible isolates were exposed independently to five commercial fungicides with different modes of action: boscalid (respiration inhibitor), iprodione (unclear mode of action), thiophanate methyl (inhibition of microtubulin synthesis) and azoxystrobin and pyraclostrobin (quinone outside inhibitors). Mycelium of each isolate was inoculated onto a fungicide gradient and sub-cultured from the 50–100% inhibition zone for 12 generations and experiment repeated. Mutational changes were assessed for all isolates at six neutral microsatellite (SSR) loci and for a subset of isolates using amplified fragment length polymorphisms (AFLPs). SSR analysis showed 12 of 85 fungicide-exposed isolates had a total of 127 stepwise mutations with 42 insertions and 85 deletions. Most stepwise deletions were in iprodione- and azoxystrobin-exposed isolates (n = 40/85 each). Estimated mutation rates were 1.7 to 60-fold higher for mutated loci compared to that expected under neutral conditions. AFLP genotyping of 33 isolates (16 non-exposed control and 17 fungicide exposed) generated 602 polymorphic alleles. Cluster analysis with principal coordinate analysis (PCoA) and discriminant analysis of principal components (DAPC) identified fungicide-exposed isolates as a distinct group from non-exposed control isolates (PhiPT = 0.15, P = 0.001). Dendrograms based on neighbor-joining also supported allelic variation associated with fungicide-exposure. Fungicide sensitivity of isolates measured throughout both experiments did not show consistent trends. For example, eight isolates exposed to boscalid had higher EC50 values at the end of the experiment, and when repeated, only one isolate had higher EC50 while most isolates showed no difference. Results of this support the hypothesis that sublethal fungicide stress increases mutation rates in a largely clonal plant pathogen under in vitro conditions. Collectively, this work will aid our understanding how non-lethal fungicide exposure may affect genomic variation, which may be an important mechanism of novel trait emergence, adaptation, and evolution for clonal organisms.

Accelerating the pace of microbiome science to enhance crop productivity and agroecosystem health will require transdisciplinary studies, comparisons among datasets, and synthetic analyses of research from diverse crop management contexts. However, despite the widespread availability of crop-associated microbiome data, variation in field sampling and laboratory processing methodologies, as well as metadata collection and reporting, significantly constrains the potential for integrative and comparative analyses. Here we discuss the need for agriculture-specific metadata standards for microbiome research, and propose a list of “required” and “desirable” metadata categories and ontologies essential to be included in a future minimum information metadata standards checklist for describing agricultural microbiome studies. We begin by briefly reviewing existing metadata standards relevant to agricultural microbiome research, and describe ongoing efforts to enhance the potential for integration of data across research studies. Our goal is not to delineate a fixed list of metadata requirements. Instead, we hope to advance the field by providing a starting point for discussion, and inspire researchers to adopt standardized procedures for collecting and reporting consistent and well-annotated metadata for agricultural microbiome research.