Population Genomics of Filamentous Plant Pathogens-A Brief Overview of Research Questions, Approaches, and Pitfalls

Pangenome graph analysis reveals extensive effector copy-number variation in spinach downy mildew

Plant pathogens adapt at speeds that challenge contemporary disease management strategies like the deployment of disease resistance genes. The strong evolutionary pressure to adapt, shapes pathogens' genomes, and comparative genomics has been instrumental in characterizing this process. With the aim to capture genomic variation at high resolution and study the processes contributing to adaptation, we here leverage an innovative, multi-genome method to construct and annotate the first pangenome graph of an oomycete plant pathogen. We expand on this approach by analysing the graph and creating synteny based single-copy orthogroups for all genes. We generated telomere-to-telomere genome assemblies of six genetically diverse isolates of the oomycete pathogen Peronospora effusa, the economically most important disease in cultivated spinach worldwide. The pangenome graph demonstrates that P. effusa genomes are highly conserved, both in chromosomal structure and gene content, and revealed the continued activity of transposable elements which are directly responsible for 80% of the observed variation between the isolates. While most genes are generally conserved, virulence related genes are highly variable between the isolates. Most of the variation is found in large gene clusters resulting from extensive copy-number expansion. Pangenome graph-based discovery can thus be effectively used to capture genomic variation at exceptional resolution, thereby providing a framework to study the biology and evolution of plant pathogens.

Association mapping with a diverse population of Puccinia graminis f. sp. tritici identified avirulence loci interacting with the barley Rpg1 stem rust resistance gene

BACKGROUND

Wheat stem rust, caused by Puccinia graminis f. sp. tritici (Pgt), is an important disease of barley and wheat. A diverse sexual Pgt population from the Pacific Northwest (PNW) region of the US contains a high proportion of individuals with virulence on the barley stem rust resistance (R) gene, Rpg1. However, the evolutionary mechanisms of this virulence on Rpg1 are mysterious considering that Rpg1 had not been deployed in the region and the gene had remained remarkably durable in the Midwestern US and prairie provinces of Canada.

METHODS AND RESULTS

To identify AvrRpg1 effectors, genome wide association studies (GWAS) were performed using 113 Pgt isolates collected from the PNW (n = 89 isolates) and Midwest (n = 24 isolates) regions of the US. Disease phenotype data were generated on two barley lines Morex and the Golden Promise transgenic (H228.2c) that carry the Rpg1 gene. Genotype data was generated by whole genome sequencing (WGS) of 96 isolates (PNW = 89 isolates and Midwest = 7 isolates) and RNA sequencing (RNAseq) data from 17 Midwestern isolates. Utilizing ~1.2 million SNPs generated from WGS and phenotype data (n = 96 isolates) on the transgenic line H228.2c, 53 marker trait associations (MTAs) were identified. Utilizing ~140 K common SNPs generated from combined analysis of WGS and RNAseq data, two significant MTAs were identified using the cv Morex phenotyping data. The 55 MTAs defined two distinct avirulence loci, on supercontig 2.30 and supercontig 2.11 of the Pgt reference genome of Pgt isolate CRL 75-36-700-3. The major avirulence locus designated AvrRpg1A was identified with the GWAS using both barley lines and was delimited to a 35 kb interval on supercontig 2.30 containing four candidate genes (PGTG_10878, PGTG_10884, PGTG_10885, and PGTG_10886). The minor avirulence locus designated AvrRpg1B identified with cv Morex contained a single candidate gene (PGTG_05433). AvrRpg1A haplotype analysis provided strong evidence that a dominant avirulence gene underlies the locus.

CONCLUSIONS

The association analysis identified strong candidate AvrRpg1 genes. Further analysis to validate the AvrRpg1 genes will fill knowledge gaps in our understanding of rust effector biology and the evolution and mechanism/s of Pgt virulence on Rpg1.

Whole-genome sequencing elucidates the species-wide diversity and evolution of fungicide resistance in the early blight pathogen Alternaria solani

Early blight of potato is caused by the fungal pathogen Alternaria solani and is an increasing problem worldwide. The primary strategy to control the disease is applying fungicides such as succinate dehydrogenase inhibitors (SDHI). SDHI-resistant strains, showing reduced sensitivity to treatments, appeared in Germany in 2013, shortly after the introduction of SDHIs. Two primary mutations in the SDH complex (SdhB-H278Y and SdhC-H134R) have been frequently found throughout Europe. How these resistances arose and spread, and whether they are linked to other genomic features, remains unknown. For this project, we performed whole-genome sequencing for 48 A. solani isolates from potato fields across Europe to better characterize the pathogen's genetic diversity in general and understand the development and spread of the genetic mutations that lead to SDHI resistance. The isolates can be grouped into seven genotypes. These genotypes do not show a geographical pattern but appear spread throughout Europe. We found clear evidence for recombination on the genome, and the observed admixtures might indicate a higher adaptive potential of the fungus than previously thought. Yet, we cannot link the observed recombination events to different Sdh mutations. The same Sdh mutations appear in different, non-admixed genetic backgrounds; therefore, we conclude they arose independently. Our research gives insights into the genetic diversity of A. solani on a genome level. The mixed occurrence of different genotypes, apparent admixture in the populations, and evidence for recombination indicate higher genomic complexity than anticipated. The conclusion that SDHI tolerance arose multiple times independently has important implications for future fungicide resistance management strategies. These should not solely focus on preventing the spread of isolates between locations but also on limiting population size and the selective pressure posed by fungicides in a given field to avoid the rise of new mutations in other genetic backgrounds.

Genetic Analysis of Plant Pathogens Natural Populations

Population genetics allow to address fundamental questions about the biology of plant pathogens. By testing specific hypotheses, population genetics provide insights into the population genetic variability of pathogens across different geographical areas, time, and associated plant hosts, as well as on the structure and differentiation of populations, and on the possibility that a population is introduced and from where it has originated. In this chapter, basic concepts of population genetics are introduced, as well as the five evolutionary factors affecting populations, that is, mutations, recombination, variation in population size, gene flow, and natural selection. A step-by-step workflow, from sampling to data analysis, on how to perform a genetic analysis of natural populations of plant pathogens is discussed. Increased knowledge of the population biology of pathogens is pivotal to improve management strategies of diseases in agricultural and forest ecosystems.

Genome-wide analysis of Claviceps paspali: insights into the secretome of the main species causing ergot disease in Paspalum spp

BACKGROUND

The phytopatogen Claviceps paspali is the causal agent of Ergot disease in Paspalum spp., which includes highly productive forage grasses such as P. dilatatum. This disease impacts dairy and beef production by affecting seed quality and producing mycotoxins that can affect performance in feeding animals. The molecular basis of pathogenicity of C. paspali remains unknown, which makes it more difficult to find solutions for this problem. Secreted proteins are related to fungi virulence and can manipulate plant immunity acting on different subcellular localizations. Therefore, identifying and characterizing secreted proteins in phytopathogenic fungi will provide a better understanding of how they overcome host defense and cause disease. The aim of this work is to analyze the whole genome sequences of three C. paspali isolates to obtain a comparative genome characterization based on possible secreted proteins and pathogenicity factors present in their genome. In planta RNA-seq analysis at an early stage of the interaction of C. paspali with P. dilatatum stigmas was also conducted in order to determine possible secreted proteins expressed in the infection process.

RESULTS

C. paspali isolates had compact genomes and secretome which accounted for 4.6-4.9% of the predicted proteomes. More than 50% of the predicted secretome had no homology to known proteins. RNA-Seq revealed that three protein-coding genes predicted as secreted have mayor expression changes during 1 dpi vs 4 dpi. Also, three of the first 10 highly expressed genes in both time points were predicted as effector-like. CAZyme-like proteins were found in the predicted secretome and the most abundant family could be associated to pectine degradation. Based on this, pectine could be a main component affected by the cell wall degrading enzymes of C. paspali.

CONCLUSIONS

Based on predictions from DNA sequence and RNA-seq, unique probable secreted proteins and probable pathogenicity factors were identified in C. paspali isolates. This information opens new avenues in the study of the biology of this fungus and how it modulates the interaction with its host. Knowledge of the diversity of the secretome and putative pathogenicity genes should facilitate future research in disease management of Claviceps spp.

Population Genomic- and Phylogenomic-Enabled Advances to Increase Insight Into Pathogen Biology and Epidemiology

Population genetics has been a key discipline in phytopathology for many years. The recent rise in cost-effective, high-throughput DNA sequencing technologies, allows sequencing of dozens, if not hundreds of specimens, turning population genetics into population genomics and opening up new, exciting opportunities as described in this Focus Issue. Without the limitations of genetic markers and the availability of whole or near whole-genome data, population genomics can give new insights into the biology, evolution and adaptation, and dissemination patterns of plant-associated microbes.