Genome-enabled analysis of plant-pathogen migration

Population Genetic Structure of the Rubber Tree Powdery Mildew Pathogen (Erysiphe quercicola) from China

In order to manage agricultural pathogens, it is crucial to understand the population structure underlying epidemics. Rubber tree powdery mildew, caused by Erysiphe quercicola, is a serious threat to rubber plantations worldwide, especially in subtropical environments including all rubber tree-growing regions in China. However, the population structure of the pathogen is uncertain. In this study, 16 polymorphic microsatellite markers were used to genotype powdery mildew samples from the main rubber tree-growing regions including Yunnan (YN), Hainan (HN), western Guangdong (WG), and eastern Guangdong (EG). YN had higher genotypic diversity (Simpson's indices), genotypic evenness, Nei's gene diversity, allelic richness, and private allelic richness than the other regions. Cluster analysis, discriminant analysis of principal components, pairwise divergence, and shared multilocus genotype analyses all showed that YN differed significantly from the other regions. The genetic differentiation was small among the other three regions (HN, WG, and EG). Analysis of molecular variance indicated that the variability among regions accounted for 22.37% of the total variability. Genetic differentiation was significantly positively correlated (Rxy = 0.772, P = 0.001) with geographic distance. Linkage equilibrium analysis suggested possible occurrence of sexual recombination although asexual reproduction predominates in E. quercicola. The results suggested that although significant genetic differentiation of E. quercicola occurred between YN and the other regions, pathogen populations from the other three regions lacked genetic differentiation.

Genomic analysis, trajectory tracking, and field surveys reveal sources and long-distance dispersal routes of wheat stripe rust pathogen in China

Identifying sources of phytopathogen inoculum and determining their contributions to disease outbreaks are essential for predicting disease development and establishing control strategies. Puccinia striiformis f. sp. tritici (Pst), the causal agent of wheat stripe rust, is an airborne fungal pathogen with rapid virulence variation that threatens wheat production through its long-distance migration. Because of wide variation in geographic features, climatic conditions, and wheat production systems, Pst sources and related dispersal routes in China are largely unclear. In the present study, we performed genomic analyses of 154 Pst isolates from all major wheat-growing regions in China to determine Pst population structure and diversity. Through trajectory tracking, historical migration studies, genetic introgression analyses, and field surveys, we investigated Pst sources and their contributions to wheat stripe rust epidemics. We identified Longnan, the Himalayan region, and the Guizhou Plateau, which contain the highest population genetic diversities, as the Pst sources in China. Pst from Longnan disseminates mainly to eastern Liupan Mountain, the Sichuan Basin, and eastern Qinghai; that from the Himalayan region spreads mainly to the Sichuan Basin and eastern Qinghai; and that from the Guizhou Plateau migrates mainly to the Sichuan Basin and the Central Plain. These findings improve our current understanding of wheat stripe rust epidemics in China and emphasize the need for managing stripe rust on a national scale.

Genetic Relationships of Puccinia striiformis f. sp. tritici in Southwestern and Northwestern China

Wheat stripe rust, caused by Puccinia striiformis f. sp. tritici (Pst), is a crucial disease for wheat worldwide and constantly threatens wheat production in southwestern and northwestern China, where the environment is a good fit for Pst oversummering and overwintering. However, the underlying genetic dynamics of spring epidemic Pst populations across large areas of continuous planting in the southwestern and northwestern regions are poorly understood. A total of 2,103 Pst isolates were sampled in the spring of 2019 from the two agroecosystems and grouped into three horizontal spatial scales (countywide, provincial, and regional subpopulations) and two vertical spatial scales that consisted of elevational and geomorphic subpopulations. A total of 776 multilocus genotypes were identified, with the highest genetic diversity found in the northern and Sichuan populations, particularly in the Ningxia and Sichuan Basins, while the lowest genetic diversity was found in the Yunnan and Guizhou populations. Multivariate discriminant analysis of principal components (DAPC) and STRUCTURE (STRUCTURE 2.3.4) analyses revealed variation in the genotypic compositions of the molecular groups on horizontal and vertical dimensions from north to south or vice versa and from low to high or vice versa, respectively. The regional neighbor-joining tree revealed three large spatial structures consisting of the southwestern, the northwestern, and the Xinjiang regions, while the Tibetan population connected the southwestern and northwestern regions. The isolates of the Sichuan Basin were scattered over the four quartiles by principal coordinate analysis, which indicated frequent genotype interchange with others. Greater genetic differentiation was observed between the southwestern and northwestern regions. Linkage equilibrium (P ≥ 0.05) was detected on different spatial scales, suggesting that Pst populations are using sexual reproduction or mixed reproduction (sexual and clonal reproduction) in southwestern and northwestern China. IMPORTANCE Understanding the epidemiology and population genetics of plant pathogens is crucial to formulate efficient predictions of disease outbreaks and achieve sustainable integrated disease management, especially for pathogens with migratory capability. Here, this study covers the genetic homogeneity and heterogeneity of different geographical Pst populations on broad to fine spatial scales from the key epidemic regions of the two agroecosystems in China, where wheat stripe rust occurs annually. We provide knowledge of the population genetics of Pst and reveal that, for instance, there is greater genetic diversity in northwestern China, there are close genetic relationships between Yunnan and Guizhou and between Gansu-Ningxia and Qinghai, and there are effects of altitude on genetic compositions, etc. All of these findings clarify the genetic relationships and expand the insights into the population dynamics and evolutionary mechanisms of Pst in southwestern and northwestern China, providing a theoretical basis for achieving sustainable control of wheat stripe rust in key epidemic regions.

Recombination-aware phylogeographic inference using the structured coalescent with ancestral recombination

Movement of individuals between populations or demes is often restricted, especially between geographically isolated populations. The structured coalescent provides an elegant theoretical framework for describing how movement between populations shapes the genealogical history of sampled individuals and thereby structures genetic variation within and between populations. However, in the presence of recombination an individual may inherit different regions of their genome from different parents, resulting in a mosaic of genealogical histories across the genome, which can be represented by an Ancestral Recombination Graph (ARG). In this case, different genomic regions may have different ancestral histories and so different histories of movement between populations. Recombination therefore poses an additional challenge to phylogeographic methods that aim to reconstruct the movement of individuals from genealogies, although also a potential benefit in that different loci may contain additional information about movement. Here, we introduce the Structured Coalescent with Ancestral Recombination (SCAR) model, which builds on recent approximations to the structured coalescent by incorporating recombination into the ancestry of sampled individuals. The SCAR model allows us to infer how the migration history of sampled individuals varies across the genome from ARGs, and improves estimation of key population genetic parameters such as population sizes, recombination rates and migration rates. Using the SCAR model, we explore the potential and limitations of phylogeographic inference using full ARGs. We then apply the SCAR to lineages of the recombining fungus Aspergillus flavus sampled across the United States to explore patterns of recombination and migration across the genome.

Plant-Microbe Interaction: Aboveground to Belowground, from the Good to the Bad

Soil health and fertility issues are constantly addressed in the agricultural industry. Through the continuous and prolonged use of chemical heavy agricultural systems, most agricultural lands have been impacted, resulting in plateaued or reduced productivity. As such, to invigorate the agricultural industry, we would have to resort to alternative practices that will restore soil health and fertility. Therefore, in recent decades, studies have been directed towards taking a Magellan voyage of the soil rhizosphere region, to identify the diversity, density, and microbial population structure of the soil, and predict possible ways to restore soil health. Microbes that inhabit this region possess niche functions, such as the stimulation or promotion of plant growth, disease suppression, management of toxicity, and the cycling and utilization of nutrients. Therefore, studies should be conducted to identify microbes or groups of organisms that have assigned niche functions. Based on the above, this article reviews the aboveground and below-ground microbiomes, their roles in plant immunity, physiological functions, and challenges and tools available in studying these organisms. The information collected over the years may contribute toward future applications, and in designing sustainable agriculture.

First historical genome of a crop bacterial pathogen from herbarium specimen: Insights into citrus canker emergence

Over the past decade, ancient genomics has been used in the study of various pathogens. In this context, herbarium specimens provide a precious source of dated and preserved DNA material, enabling a better understanding of plant disease emergences and pathogen evolutionary history. We report here the first historical genome of a crop bacterial pathogen, Xanthomonas citri pv. citri (Xci), obtained from an infected herbarium specimen dating back to 1937. Comparing the 1937 genome within a large set of modern genomes, we reconstructed their phylogenetic relationships and estimated evolutionary parameters using Bayesian tip-calibration inferences. The arrival of Xci in the South West Indian Ocean islands was dated to the 19th century, probably linked to human migrations following slavery abolishment. We also assessed the metagenomic community of the herbarium specimen, showed its authenticity using DNA damage patterns, and investigated its genomic features including functional SNPs and gene content, with a focus on virulence factors.

Genome Analysis of Erwinia amylovora Strains Responsible for a Fire Blight Outbreak in Korea

Erwinia amylovora is a plant-pathogenic bacterium that causes fire blight disease in Rosaceae plants. Since fire blight is highly contagious and results in serious losses once introduced, it is regulated as a quarantine disease. Recently, for the first time in East Asia, fire blight emerged in Korea with strains of E. amylovora being isolated from lesions of infected trees. Five of those strains were selected and subjected to whole-genome shotgun sequencing. Each strain had two circular replicons, a 3.8-Mb chromosome and a 28-kb plasmid. The genome sequences were compared with those of other E. amylovora strains isolated from different hosts or geographical regions. Genome synteny was analyzed and sequence variations including nucleotide substitutions, inversions, insertions, and deletions were detected. Analysis of the population genomic structure revealed that the five strains form a distinct structural group. Phylogenomic analysis was performed to infer the evolutionary relationships among E. amylovora strains, which indicated that the Korean isolates, all descended from a common ancestor, are closely related to a lineage of North American strains. These results provide useful information for understanding the genomic dynamics of E. amylovora strains including those in Korea, developing genetic markers for surveillance of the pathogen or diagnosis of the disease, and eventually developing measures to eradicate it.

Population Genomics Trace Clonal Diversification and Intercontinental Migration of an Emerging Fungal Pathogen of Boxwood

Boxwood blight was first documented in Europe, prior to its recent colonization of North America, where it continues to have significant negative impacts on the ornamental industry. Due to near genetic uniformity in the two sister species of fungal plant pathogens that cause boxwood blight, understanding historical disease emergence and predicting future outbreaks is limited. The goal of this research was to apply population genomics to understand the role of pathogen diversification and migration in disease emergence. Specifically, we tested whether the primary pathogen species Calonectria pseudonaviculata has remained genetically isolated from its European-limited sister species C. henricotiae, while diversifying into clonal lineages that have migrated among continents. Whole-genome sequencing identified 1,608 single-nucleotide polymorphisms (SNPs) in 67 C. pseudonaviculata isolates from four continents and 1,017 SNPs in 13 C. henricotiae isolates from Europe. Interspecific genetic differentiation and an absence of shared polymorphisms indicated lack of gene flow between the sister species. Tests for intraspecific genetic structure in C. pseudonaviculata identified four genetic clusters, three of which corresponded to monophyletic phylogenetic clades. Comparison of evolutionary divergence scenarios among the four genetic clusters using approximate Bayesian computation indicated that the two C. pseudonaviculata genetic clusters currently found in the United States were derived from different sources, one from the first genetic cluster found in Europe and the second from an unidentified population. Evidence for multiple introductions of this pathogen into the United States and intercontinental migration indicates that future introductions are likely to occur and should be considered in plant disease quarantine regulation.

Phylogeographic Approaches to Characterize the Emergence of Plant Pathogens

Phylogeography combines geographic information with phylogenetic and population genomic approaches to infer the evolutionary history of a species or population in a geographic context. This approach has been instrumental in understanding the emergence, spread, and evolution of a range of plant pathogens. In particular, phylogeography can address questions about where a pathogen originated, whether it is native or introduced, and when and how often introductions occurred. We review the theory, methods, and approaches underpinning phylogeographic inference and highlight applications providing novel insights into the emergence and spread of select pathogens. We hope that this review will be useful in assessing the power, pitfalls, and opportunities presented by various phylogeographic approaches.

Genomic biosurveillance of forest invasive alien enemies: A story written in code

The world's forests face unprecedented threats from invasive insects and pathogens that can cause large irreversible damage to the ecosystems. This threatens the world's capacity to provide long-term fiber supply and ecosystem services that range from carbon storage, nutrient cycling, and water and air purification, to soil preservation and maintenance of wildlife habitat. Reducing the threat of forest invasive alien species requires vigilant biosurveillance, the process of gathering, integrating, interpreting, and communicating essential information about pest and pathogen threats to achieve early detection and warning and to enable better decision-making. This process is challenging due to the diversity of invasive pests and pathogens that need to be identified, the diverse pathways of introduction, and the difficulty in assessing the risk of establishment. Genomics can provide powerful new solutions to biosurveillance. The process of invasion is a story written in four chapters: transport, introduction, establishment, and spread. The series of processes that lead to a successful invasion can leave behind a DNA signature that tells the story of an invasion. This signature can help us understand the dynamic, multistep process of invasion and inform management of current and future introductions. This review describes current and future application of genomic tools and pipelines that will provide accurate identification of pests and pathogens, assign outbreak or survey samples to putative sources to identify pathways of spread, and assess risk based on traits that impact the outbreak outcome.

Network Analysis: A Systems Framework to Address Grand Challenges in Plant Pathology

Plant pathology must address a number of challenges, most of which are characterized by complexity. Network analysis offers useful tools for addressing complex systems and an opportunity for synthesis within plant pathology and between it and relevant disciplines such as in the social sciences. We discuss applications of network analysis, which ultimately may be integrated together into more synthetic analyses of how to optimize plant disease management systems. The analysis of microbiome networks and tripartite phytobiome networks of host-vector-pathogen interactions offers promise for identifying biocontrol strategies and anticipating disease emergence. Linking epidemic network analysis with social network analysis will support strategies for sustainable agricultural development and for scaling up solutions for disease management. Statistical tools for evaluating networks, such as Bayesian network analysis and exponential random graph models, have been underused in plant pathology and are promising for informing strategies. We conclude with research priorities for network analysis applications in plant pathology.

Populations of Phytophthora rubi Show Little Differentiation and High Rates of Migration Among States in the Western United States

Population genetics is a powerful tool to understand patterns and evolutionary processes that are involved in plant-pathogen emergence and adaptation to agricultural ecosystems. We are interested in studying the population dynamics of Phytophthora rubi, the causal agent of Phytophthora root rot in raspberry. P. rubi is found in the western United States, where most of the fresh and processed raspberries are produced. We used genotyping-by-sequencing to characterize genetic diversity in populations of P. rubi sampled in the United States and other countries. Our results confirm that P. rubi is a monophyletic species with complete lineage sorting from its sister taxon P. fragariae. Overall, populations of P. rubi show low genetic diversity across the western United States. Demographic analyses suggest that populations of P. rubi from the western United States are the source of pathogen migration to Europe. We found no evidence for population differentiation at a global or regional (western United States) level. Finally, our results provide evidence of migration from California and Oregon into Washington. This report provides new insights into the evolution and structure of global and western United States populations of the raspberry pathogen P. rubi, indicating that human activity might be involved in moving the pathogen among regions and fields.

Where are we going with genomics in plant pathogenic bacteria?

Genome sequencing is commonly used in research laboratories right now thanks to the rise of high-throughput sequencing with higher speed and output-to-cost ratios. Here, we summarized the application of genomics in different aspects of plant bacterial pathosystems. Genomics has been used in studying the mechanisms of plant-bacteria interactions, and host specificity. It also helps with taxonomy, study of non-cultured bacteria, identification of causal agent, single cell sequencing, population genetics, and meta-transcriptomic. Overall, genomics has significantly improved our understanding of plant-microbe interaction.

A Framework for Optimizing Phytosanitary Thresholds in Seed Systems

Seedborne pathogens and pests limit production in many agricultural systems. Quarantine programs help prevent the introduction of exotic pathogens into a country, but few regulations directly apply to reducing the reintroduction and spread of endemic pathogens. Use of phytosanitary thresholds helps limit the movement of pathogen inoculum through seed, but the costs associated with rejected seed lots can be prohibitive for voluntary implementation of phytosanitary thresholds. In this paper, we outline a framework to optimize thresholds for seedborne pathogens, balancing the cost of rejected seed lots and benefit of reduced inoculum levels. The method requires relatively small amounts of data, and the accuracy and robustness of the analysis improves over time as data accumulate from seed testing. We demonstrate the method first and illustrate it with a case study of seedborne oospores of Peronospora effusa, the causal agent of spinach downy mildew. A seed lot threshold of 0.23 oospores per seed could reduce the overall number of oospores entering the production system by 90% while removing 8% of seed lots destined for distribution. Alternative mitigation strategies may result in lower economic losses to seed producers, but have uncertain efficacy. We discuss future challenges and prospects for implementing this approach.

Best Practices for Population Genetic Analyses

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.

Exploiting Genetic Information to Trace Plant Virus Dispersal in Landscapes

During the past decade, knowledge of pathogen life history has greatly benefited from the advent and development of molecular epidemiology. This branch of epidemiology uses information on pathogen variation at the molecular level to gain insights into a pathogen's niche and evolution and to characterize pathogen dispersal within and between host populations. Here, we review molecular epidemiology approaches that have been developed to trace plant virus dispersal in landscapes. In particular, we highlight how virus molecular epidemiology, nourished with powerful sequencing technologies, can provide novel insights at the crossroads between the blooming fields of landscape genetics, phylogeography, and evolutionary epidemiology. We present existing approaches and their limitations and contributions to the understanding of plant virus epidemiology.

Development and Validation of Polymorphic Microsatellite Loci for the NA2 Lineage of Phytophthora ramorum from Whole Genome Sequence Data

Phytophthora ramorum is the causal agent of sudden oak death and sudden larch death, and is also responsible for causing ramorum blight on woody ornamental plants. Many microsatellite markers are available to characterize the genetic diversity and population structure of P. ramorum. However, only two markers are polymorphic in the NA2 lineage, which is predominant in Canadian nurseries. Microsatellite motifs were mined from whole-genome sequence data of six P. ramorum NA2 isolates. Of the 43 microsatellite primer pairs selected, 13 loci displayed different allele sizes among the four P. ramorum lineages, 10 loci displayed intralineage variation in the EU1, EU2, and/or NA1 lineages, and 12 microsatellites displayed polymorphism in the NA2 lineage. Genotyping of 272 P. ramorum NA2 isolates collected in nurseries in British Columbia, Canada, from 2004 to 2013 revealed 12 multilocus genotypes (MLGs). One MLG was dominant when examined over time and across sampling locations, and only a few mutations separated the 12 MLGs. The NA2 population observed in Canadian nurseries also showed no signs of sexual recombination, similar to what has been observed in previous studies. The markers developed in this study can be used to assess P. ramorum inter- and intralineage genetic diversity and generate a better understanding of the population structure and migration patterns of this important plant pathogen, especially for the lesser-characterized NA2 lineage.

Addressing the Challenges of Pathogen Evolution on the World's Arable Crops

Advances in genomic and molecular technologies coupled with an increasing understanding of the fine structure of many resistance and infectivity genes, have opened up a new era of hope in controlling the many plant pathogens that continue to be a major source of loss in arable crops. Some new approaches are under consideration including the use of nonhost resistance and the targeting of critical developmental constraints. However, the major thrust of these genomic and molecular approaches is to enhance the identification of resistance genes, to increase their ease of manipulation through marker and gene editing technologies and to lock a range of resistance genes together in simply manipulable resistance gene cassettes. All these approaches essentially continue a strategy that assumes the ability to construct genetic-based resistance barriers that are insurmountable to target pathogens. Here we show how the recent advances in knowledge and marker technologies can be used to generate more durable disease resistance strategies that are based on broad evolutionary principles aimed at presenting pathogens with a shifting, landscape of fluctuating directional selection.

Plant Microbe Interactions in Post Genomic Era: Perspectives and Applications

Deciphering plant-microbe interactions is a promising aspect to understand the benefits and the pathogenic effect of microbes and crop improvement. The advancement in sequencing technologies and various 'omics' tool has impressively accelerated the research in biological sciences in this area. The recent and ongoing developments provide a unique approach to describing these intricate interactions and test hypotheses. In the present review, we discuss the role of plant-pathogen interaction in crop improvement. The plant innate immunity has always been an important aspect of research and leads to some interesting information like the adaptation of unique immune mechanisms of plants against pathogens. The development of new techniques in the post - genomic era has greatly enhanced our understanding of the regulation of plant defense mechanisms against pathogens. The present review also provides an overview of beneficial plant-microbe interactions with special reference to Agrobacterium tumefaciens-plant interactions where plant derived signal molecules and plant immune responses are important in pathogenicity and transformation efficiency. The construction of various Genome-scale metabolic models of microorganisms and plants presented a better understanding of all metabolic interactions activated during the interactions. This review also lists the emerging repertoire of phytopathogens and its impact on plant disease resistance. Outline of different aspects of plant-pathogen interactions is presented in this review to bridge the gap between plant microbial ecology and their immune responses.

Genome sequencing reveals a new lineage associated with lablab bean and genetic exchange between Xanthomonas axonopodis pv. phaseoli and Xanthomonas fuscans subsp. fuscans

Common bacterial blight is a devastating seed-borne disease of common beans that also occurs on other legume species including lablab and Lima beans. We sequenced and analyzed the genomes of 26 strains of Xanthomonas axonopodis pv. phaseoli and X. fuscans subsp. fuscans, the causative agents of this disease, collected over four decades and six continents. This revealed considerable genetic variation within both taxa, encompassing both single-nucleotide variants and differences in gene content, that could be exploited for tracking pathogen spread. The bacterial strain from Lima bean fell within the previously described Genetic Lineage 1, along with the pathovar type strain (NCPPB 3035). The strains from lablab represent a new, previously unknown genetic lineage closely related to strains of X. axonopodis pv. glycines. Finally, we identified more than 100 genes that appear to have been recently acquired by Xanthomonas axonopodis pv. phaseoli from X. fuscans subsp. fuscans.

Draft genome sequences of seven isolates of Phytophthora ramorum EU2 from Northern Ireland

Here we present draft-quality genome sequence assemblies for the oomycete Phytophthora ramorum genetic lineage EU2. We sequenced genomes of seven isolates collected in Northern Ireland between 2010 and 2012. Multiple genome sequences from P. ramorum EU2 will be valuable for identifying genetic variation within the clonal lineage that can be useful for tracking its spread.