Population diversity and population genetics
Probably the most common objective in the study of P. infestans populations is to ensure that management practices, prediction tools and potato breeding strategies are appropriate for the contemporary pathogen population. The monitoring of A1 and A2 mating-type ratios is important to aid predictions of the extent of sexual recombination and thus the risk of long-lived oospores serving as primary inoculum sources. In addition to its epidemiological impact, sexual recombination is likely to increase the rate of pathogen adaptation (Barton & Charlesworth, 1998), thus reducing the predictability of disease management practices. Understanding the population biology of P. infestans and closely related taxa (e.g. P. phaseoli, P. ipomoeae and P. mirabilis) in ‘natural’ ecosystems and comparing it with populations on cultivated crops are further important goals of studies in South and Central America (e.g. Ordoñez et al., 2000; Flier et al., 2003). It is important to distinguish between studies of population diversity and population genetics; the former yield the raw data, to which the latter can be applied to answer questions on the fundamental mechanisms and processes of genetic change in populations (reviewed in Milgroom & Fry, 1997). Surveys are conducted by collecting isolates that represent a ‘snapshot’ of the overall population in time and space. Temporal and geographic variations in phenotypic and/or genotypic diversity are then examined and interpreted in relation to the scientific goals of the study. There are many examples of this type of study in which the sophistication of the analysis has advanced from phenotypic (Malcolmson, 1969; Shattock et al., 1977) to genotypic methods, such as analysis of isozymes (Shattock et al., 1986; Tooley et al., 1985), mtDNA and RG57 restriction fragment length polymorphism (RFLP) patterns (Goodwin et al., 1994), amplified fragment length polymorphisms (AFLPs) (Cooke et al., 2003; Flier et al., 2003) and, more recently, simple sequence repeats (SSRs) (Knapova & Gisi, 2002). With the exception of the already diverse populations at its centre of origin (Goodwin et al., 1992a), an overall trend of increasing diversity in P. infestans has been observed in many potato-growing regions of the world. Early studies described populations that were clonal or dominated by a few discrete lineages (Drenth et al., 1994; Goodwin et al., 1998; Cohen, 2002), whereas more recent analysis highlights the appearance of many new genotypes via migration and sexual recombination (e.g. Sujkowski et al., 1994; Goodwin et al., 1995a, 1998; Punja et al., 1998; Hermansen et al., 2000; Cooke et al., 2003).
Evaluating the evolutionary forces driving such population change and the practical significance to disease control remains difficult (Goodwin, 1997). Comparing regional studies to build up an international perspective of P. infestans population dynamics would be beneficial, but unfortunately has not proved possible. In part, the problem stems from the logistical difficulties of comparing data collected in different laboratories, but a more serious problem is the nature of the raw data. Mating type, RG57 loci and isozyme data have been central in elucidating the movement and displacement of major lineages (Goodwin et al., 1994) and data from more than 1500 isolates have yielded a valuable baseline description of the dominant lineages in many countries (Forbes et al., 1998). However, the data are not appropriate for the type of powerful population genetic analysis needed to critically examine P. infestans populations on this scale (Table 1). There is a clear need for both new markers and a new approach to interpreting fluxes in P. infestans populations.
The practical criteria that will encourage the uptake of any new marker and those necessary to ensure the data are appropriate for population genetic analysis are listed in Table 1. In terms of practicality, the methods should use commonly available technology, and be based on cost-effective, high-throughput, robust and freely available detailed protocols to ensure their widespread adoption. Population genetic analysis is typically based upon five to 15 unlinked, simply inherited and codominant markers (Harper et al., 2003; Maggioni et al., 2003; Chauvet et al., 2004). Codominance, meaning both alleles at a locus can be unambiguously resolved, is particularly important as it allows a more robust and powerful population genetic analysis.
It is critical that new markers are appropriate for comparison of isolates both within and between populations on local and intercontinental scales and can accommodate the problem of convergence while adequately describing the ever-expanding genotypic diversity. Convergence (or homoplasy) occurs when isolates of different genetic backgrounds share an identical fingerprint. Such apparent ‘identity’ occurs by chance alone, rather than common descent, and will confound genetic analysis. AFLP fingerprinting, for example, discriminates isolates considered identical based on RG57 fingerprint (Purvis et al., 2001) and two SSR markers (Knapova & Gisi, 2002). The converse, where a high proportion of isolates within a population have unique genetic fingerprints (e.g. Brurberg et al., 1999; Zwankhuizen et al., 2000; Cooke et al., 2003), results in an endlessly expanding list of defined genotypes. The currently adopted system of designating genotypes (Goodwin et al., 1994; Forbes et al., 1998) is based on a country code followed by a unique number for each new genotype, with subcategories for isolates presumed to have emerged within a genotype. As a growing feature of P. infestans populations is a ‘blurring’ of the boundaries of genetically distinct subpopulations, the number of genotypes that need to be described in this way is likely to increase exponentially and, in the longer term, this may not be a helpful approach. There are now many variants of the US1 lineage (e.g. Forbes et al., 1998; Reis et al., 2003) and at least 19 ‘US’ genotypes, some probably generated as recombinants of existing lineages (e.g. Gavino et al., 2000; Wangsomboondee et al., 2002). An accepted naming system is clearly needed for dominant subgroups of the population (i.e. asexual lineages), but it needs to be able to accommodate this increasing diversity.
A possible solution is a population approach in which the genotype of each new isolate is examined in the context of allele types, combinations and frequencies in series of populations hierarchically sampled at geographic scales ranging from a single leaf to a continent and, ideally, duplicated over time. Analysis using F-statistics (Hartl & Clark, 1997) and genetic distances (Goldstein & Pollock, 1997) yields detailed objective descriptions of the population structure and the relatedness of different subgroups. Other methods are applied to estimate effective population size, demographic history and the magnitude and direction of gene flow between populations (Hartl & Clark, 1997). Such accurate partitioning of genetic diversity will, for example, allow a critical examination of whether any new genotype is a subset of the local population (i.e. is derived from sexual recombination within the population) or is the result of migration, a novel mutation or recombination between populations. An international database of isolates genotyped using similar protocols is crucial to this approach. Linking existing and new population-based systems of nomenclature will be a major challenge, but will answer many key questions on the historical and contemporary patterns of migration of P. infestans; for example, what is the relationship between the US lineages and the populations currently dominant in Europe?
Phytophthora infestans populations are characterized by patchiness and high rates of extinction and recolonization from one season to the next (Fry et al., 1992). Such a metapopulation structure means that small-scale sampling in a single season is unlikely to yield a true picture of the population structure. More extensive sampling over time and space is needed and sample throughput is therefore important for any new marker system. The direct testing of sporangia from sporulating lesions without lengthy isolation procedures is an obvious way to increase throughput, particularly if key phenotypic tests can be converted into reliable molecular assays (see below). Another crucial means of achieving this scaled-up approach is the coordination of research groups involved in the study of P. infestans. The recent EU-funded Concerted Action project EUCABLIGHT (http://www.eucablight.org) aims to develop, harmonize and disseminate protocols and data on P. infestans populations within Europe and, in the longer term, worldwide.
As stated, the most powerful analysis tools rely on codominant data in which allele frequencies and distributions can be monitored over time. SSRs offer the greatest combination of required attributes for population analysis (see below and Table 1) and their potential should be explored more fully. The increasing use of such biomolecular markers has great potential, but a move away from simply cataloguing P. infestans variation and towards experiments with sampling strategies designed to test specific hypotheses, using such markers within a theoretical framework of population genetics, is needed. In the coming years, the tracking of allele frequencies and distributions over time will advance the understanding of the spatial and temporal dynamics of P. infestans populations, as well as helping to estimate gene flow and investigate the balance between the forces of natural selection and chance effects of genetic drift and migration. From these data, the processes driving population change and how it may best be managed to the benefit of long-term disease control can be considered. For this to be realized, a coordinated approach is needed, in which the strengths of the disciplines of plant pathology, population genetics, molecular ecology and epidemiology are combined.
Tracking isolates in epidemiological studies
A major goal of the population analyses detailed above is to infer the processes driving population change. The resultant hypotheses based on such ‘observational’ survey data will, however, require rigorous testing. Such testing is not easy; even the suggestion that ‘new’ genotypes have replaced ‘old’ types in the UK because of increased aggressiveness has proved surprisingly difficult to test experimentally (Day & Shattock, 1997). Empirical data are needed from which the relative fitness of different strains can be compared directly. High-throughput markers will facilitate rapid isolate discrimination and thus direct comparisons of the frequency of recovery of two or more preselected isolates during the course of field epidemics. A single genetic marker that discriminates the test strains would be sufficient, offering a higher throughput than equivalent studies based on allozymes (Legard et al., 1995; Lebreton et al., 1999). Direct fingerprinting of Plasmopara viticola lesions has been demonstrated (Gobbin et al., 2003) and work at SCRI showed that sporangia harvested from a single lesion or even single sporangia grown for a few days in a small volume of pea broth in a 96-well microplate yielded sufficient DNA for rapid PCR fingerprinting (Hussain, 2003).
Fingerprinting using a more comprehensive range of markers also has potential for larger-scale tracking of isolates with specific traits. For example, understanding the origin and spread of strains that have overcome novel host resistance, or developed resistance to an important fungicide, is fundamental to managing the risk that such strains pose. Such isolate tracking can also be used effectively to determine sources of primary inoculum (Zwankhuizen et al., 2000). The association between seedborne infection and subsequent field outbreaks, for example, is important to the understanding of infection pathways and control methods, as well as having commercial and regulatory implications. Similar approaches have been used to identify source populations in the surveillance of human pathogens (Fisher et al., 2002). Tracking of inoculum using powerful genetic markers will also add detail to the fascinating palaeogeographical reconstruction of the spread of P. infestans across the world (Ristaino et al., 2001) and may influence international quarantine issues in the context of contemporary pathogen movement.
SSRs offer the greatest potential for studies of comparative fitness, as multiple combinations of alleles are possible at each specific locus, thus increasing the likelihood of identifying unique test isolates for any given experiment. For tracking particular strains, or monitoring inoculum movement on a larger scale, SSRs again have the greatest potential to uniquely discriminate each strain. However, further work is needed to investigate whether the resolution offered by SSRs will be sufficient in populations with limited genetic diversity. If the specific mutation responsible for the change in phenotype is known, as in the case of QoI resistance in P. viticola (Gisi et al., 2002), the combined tracking of both selectable and neutral markers will yield the most useful data.
Phytophthora has a tremendous range of mechanisms for creating and maintaining genetic diversity (Brasier, 1992). However, the contribution of each mechanism to its adaptability under natural conditions remains poorly understood (Goodwin, 1997; Judelson, 1997b). In addition to conventional genetic recombination of A1 and A2 mating types, self-fertility (Smart et al., 1998), segregation of heterokaryons (Pipe et al., 2000), zoospore-mediated hyphal fusion (Judelson & Yang, 1998), mitotic recombination (Goodwin, 1997), polyploidy (Tooley & Therrien, 1991) and aneuploidy (Carter et al., 1999) have all been reported in P. infestans. Phenotypic variation during clonal reproduction (Caten & Jinks, 1968; Judelson, 1997a; Abu-El Samen et al., 2003) also remains poorly understood. Many phenotypic or genotypic markers have been used in the analysis of the above mechanisms, but a collection of well-characterized, PCR-based, codominant and, ideally, mapped markers such as single nucleotide polymorphisms (SNPs) or SSRs would be of great benefit in resolving such processes and their relative importance.
Mapping and functional analysis of genes
The isolation of genes responsible for key traits, such as avirulence, pathogenicity, fungicide resistance or mating type, is an important target in P. infestans research (Judelson, 1997b; Birch et al., 2003; Kamoun, 2003). Positional, or map-based, cloning approaches rely on a high density of mapped markers in a segregating population and, in the absence of genomic resources, randomly generated AFLPs and RAPDs proved the most appropriate markers (Judelson et al., 1995; van der Lee et al., 1997, 2001). There is an urgent need for a genome-wide set of high-density markers in P. infestans to aid gene discovery and allow approaches such as ‘natural selection mapping’ to be applied. Unique patterns of linkage disequilibrium were recently confirmed around the region responsible for warfarin resistance in natural rat populations under a strong selection pressure (Kohn et al., 2000). Such an approach could be used in P. infestans to identify key fitness-related genes. Whether the candidate gene is identified by the above methods or comparative genomics (Bos et al., 2003), a first step towards confirming its function requires genetic markers either tightly linked to or within the gene. Association genetics can then be used to examine the correspondence of the phenotypic trait and the linked marker in multiple isolates from natural populations or progeny from test crosses. Clearly, marker position is critical for such analysis and SNPs are likely to be the most valuable markers as they occur at a high frequency (Brumfield et al., 2003) and can precisely target the specific nucleotide responsible for the amino acid change (e.g. Bos et al., 2003).