Xiao-Ru Wang and Alfred E. Szmidt

Department of Forest Genetics and Plant Physiology, Swedish University of Agricultural Sciences


1. Introduction

Fungi are a large and diverse group of organisms. They are present, in a variety of forms, in almost every habitat. Fungi are often specific in their occurrence on particular types of host (or substrate) and ecological niche. Many microscopic fungi rarely come to our attention. For example, observations of endophytic fungi suggest that each species of vascular plant is affected by at least two to four species of endophyte that are specifically associated with the plant species (Bills 1996). Fungi may also become partners with higher plants and enter complex biological relationships with the host (Flor 1971; McDonald et al. 1989; Clay & Kover 1996; Thrall & Burdon 1997).

Plant pathogenic fungi exert a significant influence on agricultural, forest and other vegetative ecosystems. Crops over wide areas can be destroyed by devastating fungal diseases such as corn smut, potato blight, and black stem rust of wheat. Large areas of forest can experience similar destruction caused by shoot and needle blight, seed and root rot, and canker pathogens. However, the differences between long-lived tree species in forest ecosystems and the annual crops in intensively managed agroecosystems make the forest pathogenic fungi very different from crop pathogens in their occurrence, persistence, disease development and dispersal. Very often the interaction between pathogen and the host tree involves relatively long periods of intimate contact without apparent damage to the host. The pathogen can persist in asymptomatic hosts for years (Stanosz et al. 1997). Under stress, however, host physiology may shift in a manner that permits active development of the pathogen, or environmental conditions may alter to favor growth and reproduction of the pathogen. The pathogen’s presence is then often manifested by the rapid development of disease. This persistence of forest pathogens is in

marked contrast to many of the crop pathogens that go through annual recolonization cycles. These distinct characters of forest pathogens have profound effects on their population genetic structure in both time and space.

Much effort has been made to control fungal disease through selection and breeding programs, genetic modification of both host and pathogen, and introduction of resistant cultivars in agriculture and forestry (Bazzigher 1981; Namkoong 1991; Smalley & Guries 1993; Stukely & Crane 1994). The success of these projects depends largely on the genetic variability in the fungal population and the genetic systems through which they interact with the host and regulate their own genetic structure. Fungi possess a variety of mechanisms for introducing genetic variation in their life cycle, either during sexual reproduction or independently of it (Esser & Kuenen 1967; Brasier 1992; Kistler & Miao 1992). The resulting variability is significant for a number of reasons. It can affect the pathogen’s relationship with its host at many levels, and the genetic flexibility allows the fungi to adapt readily to changing environmental conditions, including the introduction of new host genotypes.

Many aspects of the biology of the fungi have important consequences at the population level. This applies to the mode of reproduction (i.e. the relative contributions of sexual and asexual, outcrossing and selfing mechanisms), to the hyphal anastomosis between genetically different individuals, and also to many details of the genetic transmission system itself (Brasier 1992; Glass & Kuldau 1992; Milgroom 1996). Some fungi are predominantly haploid in their vegetative phase, some are diploid, and some are dikaryotic. Fungal spores may be specialized for either local or long-distance dispersal via rain-splash, wind, or insect vectors. Thus, fungi make an interesting group of organisms for population biology studies.

Population studies of any organism with mixed modes of reproduction rely heavily on the ability to unambiguously identify sexually produced individuals and asexually produced clones. Classical mycological and pathological traits, such as morphological, physiological and disease characters, lack the resolution required for rigorously identifying individuals within a population, and this hampered fungal population studies for many years. Advances came with the development of various types of molecular markers. The advantage of molecular markers is the nearly unlimited number of polymorphic loci they can detect in individual genotypes for direct assessment of genetic variation in populations. Application of molecular markers has facilitated the investigation of evolutionary processes in a large number of crop and forest pathogenic fungi (e.g. Valent & Chumley 1991; Fry et al. 1992; Mitchell & Brasier 1994; Milgroom et al. 1996). Furthermore, the number and scope of these enquiries is expanding rapidly.

This paper briefly describes key characters of fungal reproductive biology and genetic systems that affect fungal population structure. A review of genetic markers suitable for population analysis follows, and finally the population genetic structure of forest pathogens is discussed in relation to factors contributing to population genetic changes.


2. Reproductive Biology


In the life cycle of most eukaryotic organisms there is an alternation between haploid and diploid phases. In most of the higher plants the haploid phase is restricted to just a few divisions during meiosis, and consists only of the gametes and/or gametophytes. During fertilization, the haploid nuclei join to form a diploid zygotic nucleus, which initiates the development of a new individual. The primary source of genetic variation in most organisms is sexual reproduction, in which meiotic recombination occurs. Two different recombination processes occur during meiosis: inter-chromosomal recombination (the reassortment of homologous chromosomes), and intra-chromosomal recombination (the mutual exchange of chromosomal parts by breakage and fusion as a result of crossing-over). New gene combinations arise as a result of sexual reproduction and may affect the overall fitness of the individuals.

Fungi are lower eukaryotes in which the alternation of the haploid and diploid phase can be much more complex, and may involve undifferentiated hyphae, gametes, or gametangia, depending on the particular fungal species. In many fungi there can be a long period of time between plasmogamy – the fusion of gametes (N) or other sex cells, and karyogamy – the union of the haploid nuclei to form the zygote (2N) (Fig. 1). The diploid zygote further undergoes meiosis to restore the haploid state (N). The result of plasmogamy is a dikaryotic (N+N) phase. Although sexual reproductive cycles typically progress through haploid, dikaryotic and diploid phases, the relative length of each phase varies among species (Moore-Landecker 1990). In Phycomycetes, the meiosis seems to occur just before the formation of gametes. In such cases the fungal mycelium is diploid and more difficult to study genetically, especially with dominant markers, than when it is haploid. In many Basidiomycetes there is a delay between plasmogamy and karyogamy since the dikaryon that is established can grow for an extended period. In Ascomycetes, the dikaryotic phase is found only within the ascocarp. Karyogamy occurs in the young ascus cells and is immediately followed by meiosis, which results in either four or eight ascospores (Moore-Landecker 1990; Bos 1996a).


Fig. 1. Succession of events and nuclear stages in a typical fungal reproductive cycle. Some stages may not be present in certain groups of fungi and the length of each stage varies among species (From Moore-Landecker, 1990).


For any genetic analysis, it is important to know the genomic ploidy of the samples. This is directly related to the choice of experimental methods, and the interpretation and statistical analysis of data obtained with markers. Haploid tissue is easy to work with, and interpretation of the resulting marker patterns in relation to genotypes is straightforward. For dikaryotic tissues, depending on the nuclear types of the fused cell or hypha, they may behave in codominant marker analysis either like homozygotes, if the two nuclei are the same at the locus, or like heterozyogotes, with mixed patterns if the two nuclei are different at the locus. With dominant markers, genotypes of both diploid and dikaryotic tissues can be difficult to determine, since in both cases only the dominant allele at any specific locus will be detected.

In fungi, sexual cell fusion is restricted to compatible mating types. The concepts of homothallism and heterothallism are used to describe the most fundamental dichotomy in mating systems in fungi (similar to self-compatibility and self-incompatibility in plants), leading to inbreeding and outbreeding, respectively. The extent of population genetic variability is often directly related to the degree of inbreeding and outbreeding in the population. A homothallic fungus can complete its sexual reproductive cycle, the karyogamy and meiosis, without the necessity of introducing a second nuclear type or, if mating with a second partner should occur, there is no requirement that the nuclei represent different mating types (Raper 1960). Sexual reproduction in heterothallic fungi, however, requires the participation of different mating types. The recent cloning and sequencing of mating type genes has allowed the clarification of many molecular aspects regarding the regulation of the sexual cycle (see review by Glass & Kuldau 1992). Heterothallism has selective advantages over homothallism as it restricts inbreeding, while simultaneously increasing outbreeding and the potential for variability.


Not all fungi reproduce sexually: many rely entirely on asexual reproduction. Thus, asexual reproduction is the most important type of dispersion in many fungi and can occur through a number of modes, e.g. vegetative spread of mycelia or production of asexual spores, to produce varying distributions of identical genotypes within and among populations. Unlike sexual reproduction, meiosis never takes place in asexual reproduction. However, recombination can occur in the absence of sexual reproduction. This is made possible by heterokaryosis and the parasexual cycle (Pontecorvo 1956; Parmeter et al. 1963; Tinline & MacNeill 1969; Bos 1996b). Heterokaryosis describes the occurrence of different nuclear types in the same mycelium. Heterokaryons may originate from a hypha that has only a single nuclear type through mutation of a nucleus within the mycelium, or through somatic fusion of one hypha to another. Heterokaryon formation can introduce considerable genetic variation to the mycelium, and heterokaryons may contain the cytoplasm from different sources as well as genetically different nuclei.

The parasexual cycle is a sequence involving heterokaryon formation, fusion of different haploid nuclei to form diploid nuclei, and restoration of diploid nuclei to their haploid state (haploidization) in somatic cells (Tinline & MacNeill 1969; Bos 1996b). Haploidization involves a series of irregular mitotic divisions of the diploid nuclei which, in a few cases, may lead to balanced haploid nuclei (Bos 1996b). Mitotic crossing-over can occur in the diploid nuclei. All these phenomena will lead to new gene combinations from genes that were previously located in different nuclei. The recombinant haploid nuclei may segregate into asexual spores that differ genetically from the parent mycelium. Although the parasexual cycle is similar to sexual reproduction, it is less efficient in producing recombinant nuclei. Pontecorvo (1956) estimated that the initial frequency of mitotic crossing-over in nuclei is lower, by a factor of 500 - 1000 times, than that of meiotic crossing-over. In addition, the possibility of any single recombinant nucleus being isolated in a spore is also lower than in sexual reproduction, in which virtually every spore produced as a result of meiosis contains a recombinant nucleus (Moore-Landecker 1990).

During asexual growth, vegetative incompatibility loci regulate the ability of pairs of different strains to form heterokaryons. These loci control the capacity of an individual to distinguish self from nonself during vegetative growth. Genetic systems controlling vegetative incompatibility are reviewed in Glass & Kuldau (1992) and Leslie (1993). Many fungi have a complex vegetative incompatibility system that prevents hyphal anastomosis. For example, on a diseased elm bark only 150 cm2 in area, as many as 42 different vegetative compatibility groups (VCGs) of Ophiostoma novo-ulmi have been identified (Brasier 1996). Similarly, 49 isolates of Phomopsis from an elm outer-bark slab (ca. 15 x 20 cm) comprised 21 VCGs (Brayford 1990). The large number of VCGs found in natural populations of fungi suggest there is generally a very low rate of heterokaryon formation (Mylyk 1976; Perkins & Turner 1988). In further support of this conclusion, no two isolates from the same site were able to form heterokaryons in a natural population study of Neurospora crassa by Mylyk (1976). Thus, the importance of heterokaryon formation, or its prevention, in the population biology of fungi in natural environments remains to be elucidated.

Heterokaryosis and the parasexual cycle apparently occur in some filamentous Ascomycetes, Basidiomycetes and imperfect fungi (Caten 1981; Bos 1996b; Zeigler et al. 1997). Many heterokaryons of the root and butt rot fungus Heterobasidion annosum have been isolated from an infected Norway spruce (Picea abies) stand (Stenlid 1985), and parasexual DNA exchanges have been detected in the rice blast pathogen Magnaporthe grisea in field populations (Zeigler et al. 1997). However, in general, investigators have had difficulty in isolating heterokaryons from natural sources (Moore-Landecker 1990). Consequently, we have little direct evidence of the actual significance of heterokaryons and parasexual recombination in nature, or the extent to which information derived from laboratory studies can be applied to natural populations (Glass & Kuldau 1992). From the perspective of multilocus population structure, rare parasexual events may be indistinguishable from rare sexual recombination. However, a small amount of recombination, regardless of the mechanism, may have significant effects on population structure (Milgroom 1996; Zeigler et al. 1997; Kohli & Kohn 1998).

Vegetative (somatic) incompatibility (SI) as a genetic trait (Anagnostakis 1982; Adams et al. 1990; Hansen et al. 1993) has been widely used to determine the distribution of pathogen types and clones in forest studies (Shaw & Roth 1976; Kile 1983; Stenlid 1985; MarH ais et al. 1998). Several DNA analyses agree that SI groups are generally genets, i.e. mycelial individuals (Bae et al. 1994; Smith et al. 1994; Guillaumin et al. 1996; MarH ais et al. 1998). However, a comparative study on Suillus granulatus indicates that isolates shown to be the same by SI tests can display polymorphisms with molecular markers (Jacobson et al. 1993), suggesting that SI groups may not always fully reflect the distribution of genets. Nevertheless, if isolates from the field belong to the same SI group, it indicates, at least, that they have common alleles at the loci controlling somatic incompatibility (Leslie 1993), and they are probably more genetically similar than isolates of different SI groups. In populations of fungi with a high degree of inbreeding, it is possible that independent but closely related genets would have identical SI phenotypes (Jacobson et al. 1993; Guillaumin et al. 1996). In populations where outbreeding is more prevalent, SI testing may continue to be a useful method for similarity and population structure analyses, provided there is enough variation at the SI loci to allow reliable clone identifications (Stenlid 1985; Guillaumin et al. 1996; MarH ais et al. 1998).


The nuclear genomes of fungi are small. Haploid genome sizes reported for different groups of fungi range from 13 to 93 million nucleotide base pairs (Ullrich & Raper 1977; Lu 1996), making fungal genome size intermediate between that of prokaryotes and the higher eukaryotic plants and animals. Compared to higher plants and animals, fungal genomes have a much lower percentage of redundant DNA. Typically about 10 - 20% of the DNA in fungi is redundant, while as much as 80% of the DNA may be redundant in other eukaryotes (Brooks & Huang 1972; Dutta & Ojha 1972; Dutta 1974).

The recently published Yeast Genome Directory (supplement to Nature vol. 387, 1997) represents the first complete genetic sequence for an eukaryotic organism (Cherry et al. 1998; Mewes et al. 1998). The baker’s yeast, Saccharomyces cerevisiae, is a unicellular Ascomycete fungus. Its nuclear genome contains 16 chromosomes including 13.4 million bases. It has been shown that the S. cerevisiae genome displays significant redundancy, with 53 duplicated gene clusters among the 16 chromosomes. These duplicated regions represent more than 30% of the entire genome (Mewes et al. 1997). Markers targeting repetitive sequences can therefore simultaneously analyze many loci, providing the high resolution needed for individual identification and linkage mapping.

Fungi also have extrachromosomal genetic elements, the most important of which are found in the mitochondria. Mitochondrial (mt) genomes provide another source of genetic variability that is independent of sexual reproduction. It has been found, in some cases, that mtDNA can be transferred independently of the nuclear genome during unstable vegetative fusion (Collins & Saville 1990) and mtDNAs can also show recombination (Earl et al. 1981; Wolf 1996). MtDNA comprises 1 - 20% of the DNA occurring in fungal cells (Moore-Landecker 1990). The size of the mitochondrial genome varies widely among fungi, even among closely related species, and values ranging from about 17 to 121 kb have been reported (Zimmer et al. 1984; Scazzocchio 1987; Lu 1996). However, the genomic size of the majority of species studied lies between 30 and 80 kb (Gray 1989; Lu 1996).

The mitochondrial genome in fungi is usually uniparentally (maternally) inherited (Taylor 1986). Investigation of mtDNA divergence has contributed much to our understanding of fungal evolution (e.g. Moody & Tyler 1990; Bruns et al. 1991; Förster & Coffey 1993). The mtDNA is a useful tool for taxonomic studies because it is relatively small, making it possible to analyze the entire genome, and its composition is not complicated by the recombination that occurs regularly in nuclei as a result of sexual reproduction (Taylor 1986). The small genome size has made it possible to perform restriction analysis with multiple enzymes directly on mtDNAs from different isolates. Analysis of mtDNA variation has been used to discern subspecies, vegetative incompatibility groups and different populations (Gray 1989; Jacobson & Gordon 1990; Smith et al. 1990; Gordon et al. 1992).


3. Molecular Markers

The prerequisite of genetic analysis is to have tools that can discriminate between biological entities with different genetically-determined characters. Classically this has been done using morphological, pathogenic, mating type and physiological criteria to distinguish between species and races. With filamentous fungi, even discrimination at the species level using these traits can be very difficult and often gives erroneous results (Meyer et al. 1992). At even lower taxonomic levels, among isolates of a single species from different populations (which are likely to be very similar and to have overlapping traits), suitable distinguishing features may be difficult or impossible to find. Molecular markers, however, can be applied at these levels with great reliability, and they allow simultaneous measurement of variability at multiple loci in each individual tested. The methods for collecting molecular data for fungal evolutionary studies have been the subject of several recent reviews (Bruns et al. 1991; Kohn 1992; Goosen & Debets 1996). The nature and applications of different categories of markers are summarized below. Deciding which technique is most appropriate for addressing a particular question depends upon the extent of genetic polymorphism required to best answer the question, the analytical or statistical approaches available, and the time and material cost of possible techniques (Parker et al. 1998).


Allozymes are alternative enzyme forms encoded by different alleles at the same locus, which can be used as informative genetic markers. The literature on allozymes as genetic markers is extensive (Newton 1987; Micales & Bonde 1995). In diploid organisms, most allozymes exhibit standard codominant Mendelian inheritance. Multiple polymorphic loci can be surveyed and typically two or three alleles are detected at each locus. Randomly sampled allozyme loci are generally accepted to be of independent genetic origin. The analysis is economic and efficient for screening large numbers of isolates. When enough polymorphic loci are available for a given sample set, the technique can be a good source of useful characters for classifying organisms at population, race/type and species levels (Burdon & Roelfs 1985a; Leuchtmann & Clay 1989; Elias & Schneider 1992; Damaj et al. 1993; Goodwin et al. 1993). However, allozyme variations in many pathogenic fungi are low or nonexistent (Newton 1987). Thus, DNA-based markers are becoming a more common choice of data source for resolving genetic issues at a range of taxonomic levels.


The first DNA-based markers to be developed were RFLPs. An RFLP may be the result of length mutation, and/or point mutation at a restriction enzyme cleavage site at a given chromosomal location. RFLPs can be detected by analyzing restriction digests of genomic DNA through Southern hybridization. The probes used in RFLP analysis can be generated from cloned genomic, cDNA or mtDNA fragments, or from specific DNA segments amplified using polymerase chain reaction (PCR). Thus, depending on the probe used, RFLPs can be used to analyze mtDNA variation, ribosomal (r) DNA region variation, repetitive and single-copy sequence variations.

RFLPs are codominant markers. This makes them suitable for population genetic studies as well as for linkage map construction. By employing probes that detect multiple loci and dispersed repetitive sequences, the sensitivity of the RFLP method can be enhanced to fingerprinting resolution (Hamer 1991; Goodwin et al. 1992a; Zeze et al. 1996). In addition, synthetic simple repeat oligonucleotides can also be used as fingerprinting probes (Meyer et al. 1991). For the rice blast fungus Magnaporthe grisea, for instance, several dispersed repetitive sequences have been isolated and thoroughly characterized, and the markers derived from them have been widely used in pathotype diversity analysis and genetic mapping of the fungus (Hamer & Givan 1990; Hamer 1991; Levy et al. 1991).

Amplified fragment length polymorphism (AFLP) analysis (Zabeau & Vos 1993) is a new method that also offers fingerprinting resolution in fungi (Majer et al. 1996; Mueller et al. 1996). RFLPs can be converted to AFLPs by ligating adaptors for PCR amplification. The method offers the potential to detect large numbers of amplification products. Although this method does not target specific areas of the genome for marker identification, the large number of loci that can be analyzed in a single experiment greatly improves the chance of identifying markers linked to the chosen genetic locus (Vos et al. 1995). In plant studies it has become a favored tool for linkage mapping of resistant genes and other traits (Cervera et al. 1996; Keim et al. 1997; Voorrips et al. 1997).

DNA fingerprinting provides a powerful tool for population studies of asexually reproducing fungi because it can be used to distinguish different clonal lineages in populations with a high degree of certainty (McDonald & Martinez 1991; Goodwin et al. 1992a; Milgroom et al. 1992). However, the use of DNA fingerprinting beyond the identification of individuals, such as in estimation of divergence and quantitative measures of genetic diversity and similarity, must be done with caution. The problems may arise due to potential inter-dependence among characters in pairwise comparisons among isolates, and the difficulty of ascertaining allelism among fragments (Lynch 1990; Parker et al. 1998).

PCR-RFLPs. DNA hybridization-based RFLP analysis requires the isolation of large amounts of purified DNA. With PCR it becomes possible to analyze specific sequences from small amounts of tissue. The advantages of PCR-RFLP lie in its speed, sensitivity and specificity. PCR can be performed on crude DNA extracts with a pair of region-specific primers. Variation of the amplified fragment can be further analyzed by restriction enzyme digestion and electophoretic separation. The applications of PCR technology in fungal research are almost countless (Henson & French 1993). The regions most commonly examined by PCR-RFLP are the rDNA sequences.

In fungi, as in other eukaryotes, rRNA genes are repeated up to several hundred times in a clustered manner. In each rDNA repeat, two internal transcribed spacers (ITS) separate the 18S, 5.8S and 28S rRNA genes. The rDNA sequences encoding 18S and 28S RNAs show slow evolutionary change and can thus be used to compare distantly related organisms (Bruns et al. 1992; Berbee & Taylor 1993; Simon et al. 1993; Begerow et al. 1997; Holst-Jensen et al. 1997). The ITS region and the intergenic spacer of the rDNA repeat evolve much faster and sequence differences in these regions frequently occur between closely-related species or even between populations of the same species (Buchko & Klassen 1990; Bernier et al. 1994; Erland et al. 1994; Lovic et al. 1995). Thus, analysis of the rDNA region is very useful for comparisons over a wide range of taxonomic levels and it has a high resolving power, depending on which part of the rDNA repeat is analyzed. The rDNA sequences have been determined for a large number of eukaryotes. This allows the design of primers that are specific for a group of species, genera, or families (Zazar et al. 1991; Simon et al. 1992; Gardes & Bruns 1993; Gargas & Depriest 1996; Tooley et al. 1997).


Variation within species can also be assayed using the RAPD method (Welsh & McClelland 1990; Williams et al. 1990), in which arbitrary short oligonucleotide primers, targeting unknown sequences in the genome, are used to generate amplification products that often show size polymorphisms within species. RAPD analysis offers the possibility of creating polymorphisms without any prior knowledge of the DNA sequences of the organism investigated. The patterns produced are highly polymorphic, allowing discrimination between isolates of a species if sufficient numbers of primers are screened.

The method is fast and economic for screening large numbers of samples. However, some researchers are critical of the sometimes poor reproducibility of RAPD patterns. In our laboratory, we find that once the optimal RAPD conditions for a given species are established, the method works well for fungal samples even on crude DNA extracts. The reproducibility within a laboratory is usually satisfactory (Tommerup et al. 1995). However, inter-laboratory comparison of RAPD patterns may not always be applicable since the RAPD patterns can be influenced by many technical factors (Penner et al. 1993). This implies that diagnostic RAPD markers specified purely by mobility/size may not be confirmed by another laboratory, thus posing uncertainty for data cross-referencing in race/type identifications. For any RAPD marker to be used as a diagnostic tool by a wider group of researchers, it is necessary to characterize it more thoroughly, through isolation, cloning and sequencing to generate either probes or specific primers for future applications.

The main limitation of RAPD analysis in population studies is the dominant character of RAPD markers. In the study of diploid organisms, homozygote AA can not be distinguished from heterozygote Aa, since both will give a RAPD pattern with a band, corresponding to A. Thus, allele frequencies and basic population genetic parameters can not be estimated directly. When only diploid material is available, frequencies of RAPD fragments are sometimes deduced from the frequency of the null homozygote, aa, assuming the population is in Hardy-Weinberg equilibrium. However, both theoretical modeling (Lynch & Milligan 1994) and empirical data (Isabel et al. 1995; Szmidt et al. 1996) have shown that this indirect approach may give very biased results, especially when the sample size is small. More individuals (2 - 10 times more), and more loci, are needed than for codominant marker analysis, to compensate for the lack of complete genotype information caused by dominance (Lynch & Milligan 1994). On the other hand, RAPD analysis is well suited to population studies in haploid organisms since there is no loss of genetic information caused by the dominant inheritance of the RAPDs. When stringency was applied to RAPD data scoring, most of the RAPD fragments in the haploid Gremmeniella abietina behaved as independent loci (Wang et al. 1997).


4. Population Genetic Variability: Patterns and Mechanisms


To understand the population biology of fungi, an appropriate sampling system is essential. The system used should consider the sampling scale, sample size and the number of markers used. Sampling schemes for particular studies should be adjusted according to the reproductive biology of the fungus, its vegetative growth and spore dispersal characters, as well as the aim of the study. For example, to reveal genotype/clone distribution patterns in natural environments one has to consider the dispersion mechanisms via sexual/asexual spores and mycelial growth characteristics. If asexual spores are dispersed only over short distances (e.g. on the scale of centimeters or meters), the clonal structure of a population may not be adequately represented if sampling is conducted at a macro scale. Thus, low-density sampling can prevent observation of spatial structure on a small scale (Milgroom & Lipari 1995). For fungi that propagate through mycelial growth, individuals can be mapped only through detailed systematic sampling.

For fungi, in the absence of prior knowledge of the scale of the population structure, samples should be collected in a systematic manner over a wide range of distances. Ideally this should cover sampling from within individual hosts to the nearest neighboring host, progressing to groups within a stand, and finally sampling different populations over a range of geographical distances. The sample size at each level should be adjusted, according to the purpose of the analysis, and should satisfy the statistical requirements for population inferences (Brown 1975; Lewontin 1995). Even for diagnostic applications it is important to survey a relatively large number of isolates before describing a molecular marker as being race or type specific. Without sufficient screening for the variation a race or type harbors, conclusions based on the diagnostic markers can be imprecise or erroneous.

Use of sufficient numbers of characters defends against the stochastic errors inherent in small data sets. More markers also give a more representative sampling of the genome and reduce linkage effects among loci. In clone/genotype identifications, the resolution power is decided by the number of polymorphic loci used, allele frequency and population size (Parker et al. 1998). The more marker loci are screened, the lower the probability of making a mistake due to chance factors. With 32 RAPD loci, most of the clones/genotypes in a field population of the conifer canker pathogen Gremmeniella abietina could be identified with only a 10-10 – 10-5 probability of error (Wang et al. 1997). With DNA fingerprinting consisting of 14 fragments, the probability of shared fingerprints occurring by chance among wheat glume blotch pathogen, Phaeosphaeria nodorum, samples from field populations was estimated to be ca. 10-9 (Keller et al. 1997). However, when using multilocus haplotypes based on seven RFLP loci, the probability that two randomly sampled isolates of P. nodorum would share the same multilocus haplotype by chance increased to 0.01 – 0.02 in the same populations (Keller et al. 1997).


The genetic structure of populations has long been the central focus of population genetics. Genetic structure is to a large extent defined by spatial structure. In organisms with a mixed mode of reproduction, the observed population structure represents the outcome of both sexual and asexual reproduction as well as the prevalent dispersal mechanism. Selfing species generally show more spatial genetic structure than outcrossing species. Population structure has been successfully used to indicate the way root-infecting fungi spread within infected stands. If fungal dispersal from tree to tree occurs through mycelial growth and root contacts, the number of genets should be infrequent and occupy large areas, encompassing many trees. In contrast, if sexual spores are an important means of dispersal, genets should be frequent in number and occupy small areas, encompassing only one or a small number of trees (Rayner 1991; Anderson & Kohn 1995; MarH ais et al. 1998).

Various spatial structures have been found among the soilborne root-infecting pathogens. Vegetative growth was concluded to be prevalent for Phellinus weirii and Armillaria luteobubalina because they formed large foci in which only one or a few large genets were present (Kile 1983; Bae et al. 1994). Some Basidiomycete individuals are capable of mycelial spread through soil over a distance greater than 100 m and can maintain the structure for many decades (Shaw & Roth 1976; Anderson et al. 1979; Smith et al. 1992). Other Armillaria species use both basidiospores and vegetative growth to spread, and their population structure in infected stands can consist of a large number of genets (a few of which may attain a very large size), or just a few large genets (Kile 1986; Smith et al. 1994; Worrall 1994). On the other hand, basidiospores were deemed to be the main means of dispersal of Phaeolus schweinizii, Inonotus tomentosus and Collybia fusipes. This was because they comprised a large number of small genets, occupying narrow forest areas encompassing one or a small number of trees, (Barrett & Uscuplic 1971; Lewis & Hansen 1991; MarH ais et al. 1998). Similarly, in Norway spruce forest, the spread of Heterobasidion annosum through root contacts is not very effective, since one clone on average has contact with less than two trees (Stenlid 1987; Piri et al. 1990). Thus, the presence of a large number of small genets may suggest recent colonization by airborne basidiospores, whereas fewer, large individuals are indicative of more mature mycelial systems that have grown from point sources over long periods (Shaw & Roth 1976; Smith et al. 1992; Anderson & Kohn 1995).

In Ascomycete canker, pathogens that undergo both sexual and asexual reproduction, significant spatial structure has been detected at the fine local scale. In Cryphonectria parasitica (Milgroom & Lipari 1995) and G. abietina (Wang et al. 1997) nonrandom spatial patterns have been found within plots of infected stands. Identical genotypes were found either on the same tree or on immediately neighboring trees. This limited dispersal of clones suggests that the effective dispersal of asexual conidiospores, mainly via rain-splash dissemination, is limited to a few meters and has resulted in small, localized clusters of clones in the field. This spatial structure can be maintained over years. Stability of spatial patterns in these cases reflects the overlapping generation of long-lived fungal individuals in canker, which persist for several years (Milgroom & Lipari 1995). Although populations can be subdivided at fine scales, at larger scales population structure may become less pronounced, maintained by random mating. Clonal reproduction generates significant population structure only over very small spatial scales. Pathogen population structures over spatial scales larger than the individual trees or plots appear to be generated by sexual reproduction (Adams et al. 1990; Ennos & Swales 1991; Milgroom 1995; Saville et al. 1996; Wang 1997). Thus, despite local genotypic disequilibria, the widely dispersing sexual airborne spores provide a genetic link between populations. Even on the same tree, many unrelated isolates are found more often than an abundance of identical clones, indicating multiple infections by independent spores (Adams et al. 1990; Brayford 1990; Wang et al. 1997).

Selection is generally recognized to be a strong force in shaping pathogen population structures (Loegering 1951; Brasier 1995; Huang et al. 1995). If gene flow is substantial, genetic differentiation observed in gene and genotype frequencies and in adaptive traits among populations must be maintained by selection. However, inference of selection operating within and among populations from random molecular marker analysis has proven to be difficult. In a reciprocal transplant experiment on canker pathogen, Crumenulopsis sororia, Ennos & McConnell (1995) observed significant differences in the selective value of different populations of the fungus. The authors pointed out that small-scale environmental variation had a larger effect on the relative performance of the fungus than differences in the environment over long distances. This indicates the scale over which selective differences are likely to be found may be very small. When the limited dispersal and highly asexual reproduction of many fungal populations is coupled with very localized adaptive differentiation, the potential for selection to generate genetically isolated subpopulations adapted to very specific environmental conditions is very high (Brasier 1995; Ennos & McConnell 1995).


Genetic variability in a population can be measured in terms of gene and genotype diversity. Gene diversity is a function of the number and frequencies of alleles at each locus, h = 1- 3 xi2, where xi is the frequency of the i-th allele (Nei 1987). When multiple loci are sampled, mean gene diversity can be estimated across different loci. Genotype diversity is a function of the numbers and frequencies of multilocus genotypes. Genotype diversity can be quantified by a normalized Shannon´s diversity index as described in Goodwin et al. (1992b), Hs = - 3 Pi ln Pi' ln N, where Pi is the frequency of the i-th multilocus genotype and N is the sample size. Values for Hs range from 0 to 1. The maximum possible value for Hs occurs when each individual in a sample group has a different multilocus genotype.

The amount of genetic variation being maintained within a population may indicate how rapidly a pathogen can evolve and adapt to changing environments. It has emerged from genetic variability analysis based on molecular markers that many populations of sexually reproducing fungi possess a large amount of genetic variation even on a small scale. In G. abietina, the amount of gene diversity detected in an infected Pinus contorta stand was similar to that found in predominantly outcrossing plants with large effective population sizes (Wang 1997). A surprising amount of variation can be present even on a single host tree (Brayford 1990; Milgroom et al. 1992; Wang et al. 1997). This high degree of genetic variability present in fungal populations may originate from genetically diverse founder populations, from multiple sources of infection, from high somatic mutation rates, or from high degrees of sexual reproduction and outcrossing. Both somatic mutation and sexual reproduction can lead to increased genetic diversity in a population, and it is difficult to distinguish between the two phenomena at marker loci (Milgroom 1996). However, by analyzing the genetic similarity among multilocus genotypes it is possible to identify, at least tentatively, the main cause. Large numbers of unrelated genotypes indicate that other factors have stronger effects than mutation (Milgroom et al. 1992; Wang 1997; Kohli & Kohn 1998).

Sexual populations generally have greater genotype diversity than asexual populations. In addition, the degree of diversity can be indicative of whether the pathogen was introduced or native in origin. An example is Phytophthora cinnamomi in Australia, which has been found to have low genetic diversity: this is interpreted as the result of the comparatively recent introduction of the pathogen and its predominantly asexual reproduction (Old et al. 1984; 1988). Another two cases, also from Australia, are Puccinia graminis and P. recondita. Low levels of allozyme variability in these species have been attributed to the recent introduction of the pathogens to the continent, together with their low incidence of sexual reproduction (Burdon & Roelfs 1985b). Similarly, observation of increases in diversity of vegetative compatibility groups have been used to infer sexual reproduction in the Dutch elm disease pathogen Ophiostoma novo-ulmi in populations near epidemic fronts that had previously appeared to be clonal (Brasier 1988).

To estimate the contribution of sexual vs. asexual reproduction to population variability, genotype diversity and gametic disequilibria tests can be useful indicators (Milgroom 1996). Sexual reproduction produces recombinant genotypes and frequent recombination causes random association of alleles at different loci. In asexual organisms, all of the loci in the asexual progeny are completely associated, a state called gametic disequilibrium. In random mating populations, where genotype frequencies are not distorted by differential asexual reproduction, gametic equilibrium is to be expected (Burdon & Roelfs 1985a; Keller et al. 1997). Methods for gametic disequilibrium tests are described in Weir (1990). Gametic disequilibrium tests are particularly useful and statistically simple for haploid fungi since the vegetative tissue can be regarded as a gamete and thus gametic frequencies can be estimated from the vegetative phase. Several studies on pathogen fungi with alternating phases of sexual and asexual reproduction have revealed low levels of gametic disequilibrium in the non-clonal fraction of the populations, in agreement with the expectation for sexually reproducing, randomly mating populations (Milgroom et al. 1992; Chen & McDonald 1996; Wang 1997).

However, apart from asexual reproduction, there are several other processes affecting gametic disequilibrium such as selection, gene flow, drift, and linkage (see review by Milgroom 1996). Milgroom (1996) pointed out that when the random mating hypothesis is not rejected, it does not prove that the population reproduces sexually, it just suggests that recombination may regularly occur. In some cases, a low level of recombination can significantly affect population structure (Smith 1994). Thus, further lines of inquiry and analysis are required to obtain a fair estimate of the recombination rate, sexual contribution and other relevant factors. One informative analysis would be assessment of the mating system to determine the selfing and outcrossing rates. In Ascomycetes, this can be done by analyzing the haplotype composition of ascospores from individual asci (Ennos & Swales 1987; Milgroom et al. 1993). Nevertheless, regardless of the causes of gametic disequilibrium, frequent sexual phases will reduce nonrandom association unless other forces maintaining the state of disequilibrium are strong.


Gene diversity analyses are used to partition the diversity within and among populations to allow gene flow, genetic drift and selection pressures to be estimated. The evolutionary significance of these factors and their derivation from the distribution of genetic markers in populations are not discussed further here, but they have been reviewed by several authors recently, including Heywood (1991), McDermott & McDonald (1993) and Neigel (1997). The discussion in the following section is focused, instead, on some of the unique characters of the spread of forest pathogens.

One distinct character of forest pathogens is their ability to persist on asymptomatic host trees and forest sites for long periods. For example, it has often been observed that some root rot pathogens, like Armillaria species and H. annosum, have a much longer history at the studied site than the standing forest (Shaw & Roth 1976; Smith et al. 1994; Piri 1996). After cutting, H. annosum can survive for more than 30 years in stumps of infected Picea abies trees (Greig & Pratt 1976; Stenlid 1987; Piri 1996). These old stumps can serve as important sources of infection in subsequent tree generations either through root contacts to neighboring trees or as sources of spore production that may persist for decades (Stenlid 1987; Piri et al. 1990; Piri 1996). In infected Pinus resinosa and Pinus ponderosa stands, it seems that Armillaria genets found occupying large territories must sometimes have been established many decades before the current forest (Shaw & Roth 1976; Smith et al. 1994). Based on estimates concerning the mechanism of dispersion, speed of mycelial spread, and impact on tree growth, a number of simulation models have been developed for several root rot fungi. These models can be used to predict increases in the infected area, the rate of expansion of the infection, the risk of root disease passing between stands after clear cutting, and the reduction of volume growth in the forest (Menges & Loucks 1984; Shaw et al. 1985; Stenlid 1987). The persistence of forest pathogens in the relatively stable and undisturbed forest environment contrasts markedly with the more ephemeral pathogenic fungi on annual crops, where plants are recolonized by ascospores each growing season (Chen et al. 1994). In these cases, pathogen clones may occur from year to year in different locations (Anderson & Kohn 1995; Kohli et al. 1995).

The existence of pathogens in host trees may not be apparent for a long time, if they do not cause apparent damage to the host (Rayner 1991; Stanosz et al. 1997). Such infected but asymptomatic trees are common in natural forests. However, under favorable conditions permitting active development of the pathogen, or when hosts are under stress, the pathogen can rapidly develop a disease-causing virulence. An example of selective outbreak on maladapted hosts is the severe large-scale infection of the canker pathogen G. abietina on Pinus contorta introduced to Sweden from North America. In Sweden, G. abietina is commonly found on the two native forest species Pinus sylvestris and Picea abies (Barklund & Rowe 1981; Hellgren & Barklund 1992), but it seldom causes such severe damage as it does to the introduced host. Compared to the two native species, P. contorta appears to be less well adapted to the habitat, and more vulnerable to the pathogen (Karlman et al. 1994).

A similar case is associated with another conifer shoot blight and canker pathogen, Sphaeropsis sapinea. This pathogen occurs in coniferous forests throughout the world. In New Zealand, Australia and South Africa, it has caused significant economic damage in exotic pine plantations (Wright & Marks 1970; Chou 1976; Currie & Toes 1978; Zwolinski et al. 1990). Thus, introduction of plant species to new territory, which is a common practice in forestry, should consider the potential risk that weakly pathogenic fungi present in the environment may respond quite differently to the introduced species. Likewise, a less aggressive pathogen spreading to a new environment may cause surprisingly severe epidemics in native host species. Phytophthora spp., for instance, are now one of the most serious groups of plant pathogens in Australia, causing widespread pandemics in native vegetation (Wills 1993). Most of these pathogens have been introduced from other continents and have become widely distributed in Australia within relatively short periods of time (Irwin et al. 1995).

The intercontinental migration of the Dutch elm disease pathogen O. novo-ulmi and the chestnut blight fungus C. parasitica are well-known examples of large scale forest pathogen spread and destruction (Brasier 1986; Milgroom et al. 1996). C. parasitica had a disastrous effect on the American chestnut tree populations after it was introduced into the United States from Asia. The epidemic spread at a rate of ca. 37 km per year, and within 50 years, American chestnut trees covering about 3.6 million hectares had been destroyed (Anagnostakis 1987). O. novo-ulmi, the cause of the current pandemic of aggressive Dutch elm disease has spread widely across the northern hemisphere in the past few decades, and has replaced the less pathogenic O. ulmi, responsible for the first Dutch elm disease pandemic that began in the early 1920s to 1940s (Brasier 1988; Brasier 1991). At local epidemic fronts, the pathogen usually appears to be largely clonal. These frontal populations then become highly heterogeneous in just a few (6 – 10) years, to the extent that most isolates sampled are of a unique vegetative compatibility type (Brasier 1996). This rapid change in genetic structure suggests that the fungus has great potential for rapid evolution under intense selection. Such selection might occur during epidemic spread in geographically new and susceptible host populations, or under other environmental pressures.

Many cases of extensive dispersal of plant pathogens have been related to human activity and intercontinental movement of plants and raw materials. The wide-scale spread of the North American race of the Dutch elm disease pathogen in Europe, for instance, was most likely derived from the North American population via importation of diseased elm logs during the 1960s (Brasier & Gibbs 1973). Thus, human intervention presented opportunities for the pathogen to evolve in newly available niches through episodic selection (Rayner 1991; Brasier 1995). The fitness of offspring from a genet able to enter and develop in new niches may be undermined by sexual recombination. Thus, clonal reproduction of highly fitted genotypes would be initially favored. This seems to be the case in the epidemic front of the Dutch elm disease (Brasier 1988; Brasier 1996), and probably played a role in the extreme destructiveness of P. cinnamomi to the forest ecosystems in Australia (Podger 1972; Old et al. 1988). Another concern related to pathogen development is that in continuously changing environments, such as those affected by general climate warming, air pollution or changes in land usage, a pathogen may become more damaging. The fungus may increase in pathogenicity either directly, through becoming more active at higher temperatures, or indirectly through exploiting physiological stress effects in host trees. The co-evolved host-pathogen balance may therefore be seriously affected by ecological disturbances. Each host-pathogen system is a unique interacting complex. At present these risks to forest ecosystems, though clearly present, cannot be reliably predicted or assessed. However, one conclusion that can be safely deduced is that pathogens with short generation times and flexible reproductive strategies have major advantages over the forest trees they inhabit for evolving and adapting in unstable and disturbed ecosystems.



This paper was prepared during XRW´s stay in Japan as a STA fellow, sponsored by JISTEC/JRDC, Japan. XRW wishes to thank Drs. Y. Tsumura and K. Nagasaka, together with other colleagues at the Genetic Analysis Laboratory of the Forestry and Forest Products Research Institute, Japan, for their kind support and for providing office facilities. We are grateful to Dr. R.A. Ennos, Edinburgh University, for valuable comments on the manuscript. AES acknowledges financial support from SJFR, Sweden.



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by Alfred E. Szmidt