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Development of a DNA based diagnostic assay for the detection and differentiation of pathogenic fusarium… Donaldson, Gary C. 1999

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DEVELOPMENT OF A DNA BASED DIAGNOSTIC ASSAY FOR THE DETECTION AND DIFFERENTIATION OF PATHOGENIC FUSARIUM OXYSPORUMISOLATES FROM CONIFERS IN THE PACIFIC NORTHWEST by GARY C. DONALDSON B.Sc, University of British Columbia, 1990 A THESIS SUBMITTED IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF MASTER OF SCIENCE in THE FACULTY OF GRADUATE STUDIES Department of Plant Science We accept this thesis as conforming to the required standard THE UNIVERSITY OF BRITISH COLUMBIA April 1999 © Gary C. Donaldson, 1999 In presenting this thesis in partial fulfilment of the requirements for an advanced degree at the University of British Columbia, I agree that the Library shall make it freely available for reference and study. I further agree that permission for extensive copying of this thesis for scholarly purposes may be granted by the head of my department or by his or her representatives. It is understood that copying or publication of this thesis for financial gain shall not be allowed without my written permission. Department of FL/WT S&IE^Ck. The University of British Columbia Vancouver, Canada Date 99- 0 £ DE-6 (2/88) A b s t r a c t Fusarium oxysporum is commonly associated with a variety of diseases in bare-root conifer nurseries. The identification of F. oxysporum typically requires considerable expertise because of the morphological similarity of many Fusarium species. Furthermore, different isolates of F. oxysporum may or may not be pathogenic. Among pathogens, a large degree of variation in virulence occurs. There were two primary objectives of this work. The first was to continue the development of a previously described DNA-based diagnostic assay which relies on restriction fragment length polymorphisms (RFLPs) within the histone-H3 encoding gene to identify several Fusarium species, including F. oxysporum. The second was to expand the capabilities of the assay to differentiate pathogenic and nonpathogenic isolates of F. oxysporum, or at least opposite ends of the virulence spectrum. To confirm the utility of the DNA-based diagnostic, blind tests were performed using a variety of Fusarium species and fungi commonly isolated from nursery environments. Genetic diversity within tissue and soil subpopulations of F. oxysporum was examined at two nurseries in the state of Oregon to determine the degree of genetic differentiation among nursery populations. To screen for genetic markers associated with virulence, amplified fragment length polymorphisms (AFLPs) derived from 9 different primers were compared to the phenotype of 24 isolates of F. oxysporum selected for their high or low virulence. During the course of this work, evidence that suggests F. oxysporum is a complex of species has accumulated. Although this complicated the screening process, within the limited set of high and low virulence isolates studied, a large number of markers does allow separation of high and low virulence isolates. There is small, but significant, genetic differentiation of the Bend and Medford populations. The relatively low level of differentiation suggests that either the populations at the two sites originated from the same source, or contaminated material moves between the two sites. All of the available data suggest that F. oxysporum has a clonal population structure. Such a population is well suited to DNA-based diagnostic assays. ii Table of Contents Abstract ii Table of Contents iii List of Tables vi List of Figures vii Acknowledgements x Introduction 1 Chapter One An Introduction to Fusarium 4 Fusahum Taxonomy and Phylogeny 4 Fusarium as a Nursery Pathogen 6 Fusarium Molecular Genetics Research: An Overview 7 Chapter Two Materials and Methods 12 Culture Collection and Isolate Identification 12 Culture Maintenance and Storage 13 Molecular Methods 14 DNA Extraction Methods 14 Restriction Fragment Length Polymorphism (RFLP) Analysis 15 Blind Testing of the Histone-H3 RFLP Diagnostic Procedure 16 Amplified Fragment Length Polymorphism (AFLP) Analysis 17 AFLP Reproducibility Testing 20 Taguchi Optimization of the Polymerase Chain Reaction 21 DNA Sequencing and Analysis 22 Image Analysis of Amplified DNA Fragments in Agarose Gels 24 Pathogenicity Testing Procedure 24 iii Chapter Two Materials and Methods (continued) Genetic Analysis Methods 25 Genetic Similarity and Distance Calculations 25 Dendrogram Construction 27 Population Genetic Analysis 27 Chapter Three Results 31 Blind Test Identification of Fusarium species 31 AFLP Reproducibility Testing 33 Selection of a Genetic Distance Measure 36 Pathogenicity Testing Results 40 RFLP Analysis of High and Low Virulence Isolates of Fusarium oxysporum 44 AFLP Analysis of High and Low Virulence Isolates of Fusarium oxysporum 49 Sequence Analysis of the Histone-H3 Encoding Gene in High and Low Virulence Isolates of Fusarium oxysporum 53 Histone-H3 RFLP Analysis of Fusarium oxysporum Isolates from Medford and Bend 56 AFLP Analysis of Fusarium oxysporum Isolates from Medford and Bend 60 Chapter Four Discussion 69 Blind Test Identification of Fusarium Species 69 Scoring Errors, AFLP Reproducibility and Selection of a Genetic Distance Measure 69 Pathogenicity Testing 71 Dendrogram Construction 72 i v Chapter Four Discussion (continued) AFLP and RFLP Analysis of High and Low Virulence Fusarium oxysporum Isolates 73 Sequence Analysis of Histone-H3 Encoding Gene from Fusarium oxysporum Isolates 75 Population Structure of Fusarium oxysporum 75 Histone-H3 RFLP Analysis of Medford and Bend Fusarium oxysporum Isolates 75 AFLP Analysis of Medford and Bend Fusarium oxysporum Isolates 77 Chapter Five Conclusion 82 Bibliography ' 86 Appendix A: Bend and Medford Fusarium oxysporum isolates and N7-AFLP Haplotype 100 Appendix B: Histone-H3 RFLP Data from Fusarium oxysporum 108 Appendix C: Fusarium oxysporum Pathogenicity Assay Results 113 Appendix D: Fusarium Histone-H3 encoding Gene Sequence Alignment 118 v List of Tables Table 1: Oligonucleotides Used for Constructing Double-stranded Adapter Molecules 19 Table 2: AFLP Primers Screened on High and Low Virulence Fusarium oxysporum Isolates 20 Table 3: Taguchi Array for Three Levels at each of Four Parameters 21 Table 4: Similarity Coefficients Examined in this Study 26 Table 5: Fungal Isolates Used in PCR-RFLP Blind Test 31 Table 6: High and Low Virulence Fusarium oxysporum Isolates Analyzed using AFLPs and RFLPs 41 Table 7: Nucleotide Diversity in the Gene Encoding Histone-H3 among Fusarium spp. 56 Table 8: Measures of Diversity in Medford and Bend Populations of Fusarium oxysporum based on AFLP Data (a = 0.01) 60 Table 9: Mean Total Gene Diversity (HT), Mean Nursery Population Gene Diversity (Hs) and Mean Subpopulation Gene Diversity (Hc) Used to Calculate Nei's Coefficients of Gene Differentiation (Gcs, Gst) and corresponding Gene Flow Estimates (Nm) 62 Table 10: Analysis of Molecular Variance in Medford and Bend Populations of Fusarium oxysporum 64 Table 11: Pairwise Linkage Disequilibria among N7-AFLP Loci in Fusarium oxysporum from Bend Soil and Conifer Tissue 66 Table 12: Pairwise Linkage Disequilibria among N7-AFLP Loci in Fusarium oxysporum from Medford Soil and Conifer Tissue 67 Table 13: Brown's Multilocus Index of Association in Oregon Tissue and Soil Subpopulations of Fusarium oxysporum Based on AFLP Data 68 Table 14: Association between Histone-H3 Haplotypes and Phylogenetic Species 73 List of Figures Figure 1: Geographic Locations of Nurseries 12 Figure 2: Diagnostic Procedure Using RFLP Analysis of Histone-H3 PCR Product 17 Figure 3: Amplified Fragment Length Polymorphism Analysis 18 Figure 4: AFLP Reproducibility Under Varying Primer, Magnesium, dNTP and Template DNA Concentrations Using Two Different Taq Polymerases 33 Figure 5: AFLP Reproducibility Using Different DNA Extraction Methods and Restriction Digestion / Ligation Reaction Products 34 Figure 6: AFLP Reproducibility Using Different Thermal Cyclers 35 Figure 7: Polymerase Chain Reaction Temperature Profiles on Different Thermal Cyclers 36 Figure 8: Relationship between Dice and Jaccard Distance Measures 37 Figure 9: Relationship between Dice and Pearson' Phi Distance Measures 38 Figure 10: Relationship between Dice and Sokal & Sneath Distance Measures 38 Figure 11: Relationship between Dice and Excoffier Euclidean Distance Measures 39 Figure 12: Probability Plot of Dice Distance Values for High and Low Virulence Isolates 40 Figure 13: Percent Healthy Seedlings Three Weeks Post-Inoculation of High and Low Virulence Isolates 42 Figure 14: Varying Levels of Virulence in Four Isolates of Fusarium oxysporum 43 Figure 15: Histone-H3 and p-tubulin Amplification Products from Fusarium oxysporum 44 Figure 16: Neighbour-Joining Tree of High and Low Virulence Fusarium oxysporum Isolates Based on Histone-H3 and P-tubulin RFLP Data 45 List of Figures (continued) Figure 17: Neighbour-Joining Tree of High and Low Virulence Fusarium oxysporum Isolates Based on IGS-RFLP Data 46 Figure 18: Neighbour-Joining Tree of High and Low Virulence Fusarium oxysporum Isolates Based on Total RFLP Data 47 Figure 19: Principal Component Scores of High and Low Virulence Fusarium oxysporum Isolates Based on Total RFLP Data 48 Figure 20: Neighbour-Joining Tree of High and Low Virulence Fusarium oxysporum Isolates Based on AFLP Data Derived from Nine Primers 49 Figure 21: Principal Component Scores of High and Low Virulence Fusarium oxysporum Isolates Based on AFLP Data Showing Correlation with Histone-H3 Haplotypes 50 Figure 22: Principal Component Scores of High and Low Virulence Fusarium oxysporum Isolates Based on AFLP Data Showing Relationship with Geographical Origin 51 Figure 23: Principal Component Scores of High and Low Virulence Fusarium oxysporum Isolates Based on AFLP Data Showing Relationship with Virulence and Histone-H3 Haplotype 52 Figure 24: Neighbour-Joining Tree of High and Low Virulence Fusarium oxysporum Isolates Based on DNA Sequence Data from the Gene Encoding Histone-H3 54 Figure 25: Neighbour-Joining Tree of Fusarium Isolates Based on DNA Sequence Data from the Gene Encoding Histone-H3 55 Figure 26: Histone-H3 RFLP Haplotype Frequencies among Tissue and Soil Isolates at Bend and Medford Nurseries ' 57 viii List of Figures (continued) Figure 27: Histone-H3 RFLP Haplotype Frequencies and Confidence Intervals (a = 0.05) at Bend and Medford Nurseries Figure 28: Gene Diversity Confidence Intervals = 0.01) in Medford and Bend Populations of Fusarium oxysporum based on Histone-H3 RFLP Data Figure 29: Null Distribution of Genotypic Diversity Values in Relation to Observed Value in Fusarium oxysporum Acknowledgements For my beloved wife Andrea and my children Mike, Ashley and Damon who have sacrificed a considerable amount of family time and tolerated my obsessive computer use and frequent expletives. My wife Andrea has tended to the endless needs of a busy household with little help from me for some time now. Andrea, your strength of spirit inspires me. Mike and Ashley have earned my thanks for helping their mother around the house. You have both turned into exceptional young adults. Damon, you make me smile even on the darkest of days. For my father and mother, Morley and Gwen — you taught me everything I really needed to know. I hope I can pass some of those lessons along. None of this could have happened without your support, both moral and financial. My father-in-law Ken Barrett also contributed greatly to the completion of this project through several years of housing subsidies. And lastly for my grandfathers, William Coates and Gilbert Donaldson who taught me the value of history and heritage. I dedicate this work to all of you. I have acquired a great appreciation and admiration for my supervisory committee members Dr. N . Louise Glass, Dr. Paige E. Axelrood, and Dr. Robert J. Copeman. Dr. Glass got me started by giving me a job for which I was largely under-qualified, and helped me through my first Southern blots, restriction digests and agarose gels. One thing led to another, and before I knew it I was back in school. Al l of these individuals helped get someone with a less-than-spotless undergraduate academic record a chance in grad school. I hope I haven't disappointed them. I have only the highest praise for them as scientists and human beings. Thank you for sharing your knowledge. BC Research also deserves thanks for providing me with large amounts of workspace and more than ample camaraderie. My good friend Reed Radley was, and continues to be, a good source of humour, ideas, motivation, and lunch money, all of which eased even the most difficult tasks. I will hold dear many happy memories of scientific and philosophical discussions with Craig Newton (How do you pipette 32P?), Bob Gawley, Tarn Vo (What are you doing? Trying to make a living?), Dave Ellis and Margarita Gilbert (It's 9PM! Are you guys still here?). I would also like to thank the USDA Forest Service for funding this work. It has been a pleasure to work with all of the individuals who collaborated on the Forest Pest Management and Alternatives to Methyl Bromide projects. Many thanks to Jeff Stone and David Gemandt at Oregon State University, and Diane Hildebrand and Bob James of the USDA Forest Service. x Introduction Diseases caused by Fusarium species in bare-root conifer nurseries of the northwestern United States include seed rot, pre-emergence damping off, post-emergence damping off, cotyledon blight, and root rot (Bloomberg 1981), resulting in significant economic losses. Fusarium related pre- and post-emergence damping-off can destroy entire sowings, and seedling mortality of 20% to 50% is common (Bloomberg 1981). Fusarium oxysporum in particular probably causes more economic losses in agriculture than any other plant pathogen (Correll 1991). Methyl bromide soil fumigation is often used to control Fusarium, as well as a variety of other potentially harmful organisms. The effectiveness of methyl bromide against nematodes, weed and insect pests as well as fungal pathogens makes methyl bromide a preferred pest control option in many bare-root nurseries. The use of methyl bromide, however, has fallen out of favour with increasing concern about the ozone layer. Under the Clean Air Act, the US Environmental Protection Agency has prohibited the production and importation of methyl bromide starting January 1, 2001. Canadian regulatory agencies have imposed similar restrictions on the production and use of methyl bromide as a result of the 1991 Montreal Protocol Assessment. The impending removal of methyl bromide from the market has forced the development of other control measures. In order to develop new control agents, new pathogen monitoring technologies must be developed. New monitoring technology will allow the effectiveness of control agents to be assessed on individual fungal species. This project was a small part of a larger initiative funded by the USDA Forest Service to develop alternatives to methyl bromide fumigation in conifer nurseries. This technology development project focused on the management of soilborne seedling diseases in bare-root conifer nurseries. The goal of the overall project was to allow nurseries to produce quality seedlings with little or no use of soil fumigants. Primary concerns to be addressed included the 1 effectiveness of alternatives in preventing seedling mortality, long-term effects on the quality of seedlings produced, and the ease of implementing alternative control measures. Typically, only a small proportion of Fusarium species causes disease. In agricultural fields, the number of Fusarium propagules in a gram of soil often approaches 100,000 (Snyder 1981). Pathogenic Fusarium usually account for less than 10% of the total number of propagules per gram of soil, and hence soil counts of Fusarium are useless without pathogenicity tests (Snyder 1981). The highly similar morphological characteristics of all Fusarium species presently necessitate expert microscopic analysis, after isolation and growth on specialized media (Nelson et al. 1983). Further compounding the problem is the presence of a considerable degree of intraspecific variability, including both pathogenic and nonpathogenic isolates within a single species. This variability is illustrated by the existence of over 75 formae speciales of Fusarium oxysporum causing wilt diseases (Armstrong and Armstrong 1981). Many isolates of F. oxysporum are subdivided into formae speciales based on their virulence on a host or group of hosts (Correl 1991). Within formae speciales, races are defined based on virulence on a group of host cultivars. Fusarium oxysporum isolates from conifers have been shown to be particularly variable (Donaldson et al. 1995), and are frequently implicated as a significant disease agent in conifer nurseries (Bloomberg 1981; James 1985; Axelrood et al. 1995). At present, pathogenicity testing remains the only way of differentiating pathogenic and nonpathogenic F. oxysporum isolates. Unfortunately, pathogenicity testing is labour intensive, time consuming, and since so many protocols for pathogenicity testing exist, it is difficult to compare the results from different laboratories. A molecular technique for distinguishing pathogens and nonpathogens would be a key part of monitoring pathogenic isolates of F. oxysporum, and could provide an additional tool to stand with traditional pathogenicity testing. The development of a DNA-based molecular method for the differentiation of pathogenic and nonpathogenic F. oxysporum isolates associated with conifers was the ultimate goal of this work. 2 Methods that have high intraspecific resolution provide the best chances of locating a genetic marker associated with virulence. Hence, in the process of screening for virulence markers, considerable information about soil and tissue populations of F. oxysporum was also generated. To develop any DNA diagnostic, some information must be known about population structure of the organism in question. To this end, several important questions need to be answered. Are highly differentiated subpopulations present? How much variability is present within the population and within subpopulations? Will this level of variability be problematic when using the proposed diagnostic procedure? What defines a population? Can highly virulent pathogens be differentiated from weakly virulent or nonpathogenic isolates? 3 Chapter 1: Ah Introduction to Fusarium Fusarium Taxonomy and Phylogeny The taxonomic history of Fusarium began when the genus was first described by Link in the early nineteenth century. The modem landmark in Fusarium taxonomy came when Wollenweber and Reinking published "Die Fusarien" in 1935, after some 40 years of study (Gerlach 1981). Under this classification scheme the genus is divided into 16 sections and 65 species, which are further subdivided into 55 varieties and 22 forms. In 1940, Snyder and Hansen published some of their objections to Wollenweber and Reinking's system and suggested that all fomis belonging to the section Elegans be considered a single species: Fusarium oxysporum. Later publications by Snyder and Hansen in 1941 and 1945 reduced Wollenweber's 65 species down to nine. Messiaen and Cassini (1968), and Matuo (1972) published classification systems similar to that proposed by Snyder and Hansen, while Gerlach and Nirenberg (1982) expanded the genus to contain some 78 species. Nirenberg (1989) further expanded the genus to contain over 90 species. Other workers including Raillo (1950), Gordon (1952), Bilai (1955), Joffe (1974), Booth (1971), and Nelson, Toussoun, and Marasas (1983) adopted intermediary positions between the "splitting" of Wollenweber and Reinking and the "lumping" of Snyder and Hansen. Although many Fusarium species no longer appear to have a sexual stage, several anamorph-teleomorph connections have been made (Booth 1981). The known perfect states of all Fusarium species belong to the Hypocreaceae family in the order Sphaeriales. These include species within the genera Hypomyces, Nectria, Gibberella, and Calonectria. There is no known sexual stage for F. oxysporum, although phylogenetic evidence (Guadet et al. 1989; O'Donnell and Cigelnik 1997; O'Donnell etal. 1998) and serological evidence (Madoshing 1964) suggest that F. oxysporum previously had a perfect state in the genus Gibberella. 4 Taxonomy deals with the classification of species based on phenotypic or morphological traits, whereas phylogeny is concerned with the evolutionary relationships among different species. The absence of a sexual stage in many Fusarium species has led to a double taxonomic system for anamorphs and teleomorphs, rendering a proper phylogenetic reconstruction difficult. By examining genotypic characters rather than phenotypic ones, a complete phylogeny can be reconstructed. Guadet and coworkers (1989) examined the large subunits of ribosomal RNA sequences of 52 isolates of 8 Fusarium species. Their results show clear relationships between Fusarium section Martiella and the genus Nectria; section Spicarioides and the genus Calonectria; and the sections Elegans, Liseola, and Discolor with the genus Gibberella. The authors also noted that within F. oxysporum, F. oxysporum var. redolens can readily be differentiated from all other F. oxysporum by both macroconidial morphology, and rRNA sequences. O'Donnell (1996) is currently developing a DNA sequence database for all Fusarium species that will be used to construct a phylogenetically based classification scheme or phylogenetic species concept. A phylogenetic species, as defined by O'Donnell, is the smallest group of populations for which a unique genetic profile is fixed within the populations. O'Donnell has applied the phylogenetic species concept in the analysis of DNA sequence data from nuclear and mitochondrial rDNA, as well as a portion of the gene encoding p-tubulin. Analysis of sections Liseola and Martiella of Fusarium show a much larger number of species than any of the morphological classification systems. O'Donnell and associates (1997, 1998) have applied the phylogenetic species concept and suggested a reclassification of many species within the Gibberella fujikuroi and Fusarium oxysporum complexes. Most notably, within F. oxysporum, as defined by Nelson et al. (1983), O'Donnell has found five phylogenetic species (O'Donnell and Cigelnik 1997; O'Donnell et al. 1998). This has important implications for the present study. If Fusarium oxysporum is a species-complex, what effects would this have on population genetic analyses? 5 Fusarium as a Nursery Pathogen As early as 1892, Hartig (cited in Bloomberg 1981) recognized Fusarium as an important pathogen in forest nurseries. In 1901, Fusarium was reported as a seed destroying fungus in Canada, and in 1911 and 1914 the damping-off ability of Fusarium in conifer nurseries was recorded (Bloomberg 1981). Fusarium species have been documented to cause seed rot, pre- and post-emergence damping-off, cotyledon blight, and root rot (Bloomberg 1981). Diseases caused by Fusarium species in forest nurseries are found worldwide in all climatic regions and on all continents. Fusarium oxysporum is often implicated in nursery diseases and may account for 20% to 90% of all Fusarium isolates sampled in a conifer nursery at any given time. The frequency and severity of damage caused by Fusarium species varies widely among nurseries. Although some nurseries report consistent losses year after year, others report major losses some years and no losses in others. A variety of factors affecting disease development have been studied, including temperature, moisture, pH, light intensity, soil nutrients, soil type, host factors, microbial soil populations, and inoculum sources. Although it is usually difficult to separate the effects of one factor from the others, a number of important relationships have been discovered in the course of these studies. Positive correlations between temperature and disease severity have been noted (Bloomberg 1973; Hartley 1921; Wright etal. 1.963). Mortality rates are typically lower in less fertile nurseries, and increase with the addition of nitrogenous manures (Hartley 1921; Hartley and Pierce 1917; Salisbury 1954). Primary inoculum sources are diseased roots from previous crops and seed-bome spores (Bloomberg 1976; Landis 1976) Control of Fusarium in conifer nurseries is usually done by fumigation. Fumigation controls fungal pathogens such as Fusarium, Pythium, and Rhizoctonia, as well as nematode pests, insects, and problematic weeds. The effectiveness of fumigants against such a broad range of pests makes fumigation very economical. In North America, methyl bromide and chloropicrin are two of the most widely used fumigants (Stone et al. 1997). Soil and seed fungicides are also 6 used in many forest nurseries, but these are generally less effective than fumigation (Bloomberg 1981). Other alternatives to fumigation include cultural practices such as fallowing, cover crops, and organic amendments (Stone et al. 1997). Solarization and biological control (Peterson and Sutherland 1997) may also be viable alternatives to fumigation. Fusarium Molecular Genetics Research: An Overview Molecular methods have been used in studies with many fungal plant pathogens including, but not limited to, Phytophthora (Stammler et. al. 1993; Lee et al. 1993), Pythium (Martin 1991), Gaeumannomyces (Schesser et al. 1991; Elliott et al. 1993), Cochliobolus (Jones and Dunkle 1993), Colletotrichum (Hodson et al. 1993; Correll et al. 1993; Guthrie et al. 1992) as well as Fusarium. The development of DNA-based molecular methods for genomic analysis has allowed scientists to explore the relationships among species, populations, formae speciales, and races of fungi. Five DNA-based molecular methods have been widely used in characterizing plant pathogenic fungi: restriction fragment length polymorphisms (RFLPs); randomly amplified polymorphic DNAs (RAPDs); electrophoretic karyotyping; repetitive genomic DNA; and DNA sequencing. The molecular data may be analyzed using methods from population genetics to make inferences about fundamental aspects of fungal biology. Such molecular data are also useful in creating classification systems and reconstructing the evolutionary history of species. In the case of plant pathogenic Fusarium species, these methods have typically been used in conjunction with phenotypic observations such as vegetative compatibility group (VCG), pathogenicity, virulence, or host range. Considerable work has been done to develop molecular methods of differentiating Fusarium at the species and subspecies levels. Work by Guadet and workers (1989), Peterson and Logrieco (1991), O'Donnell and associates (1992, 1993, 1996, 1997, 1998), and Waalwijk and coworkers (1996a, b) has demonstrated the utility of rRNA and rDNA sequence analysis for differentiation at the species level. The DNA sequencing of other loci such as those encoding the 7 histone-H3 (Donaldson et al. unpublished) and p-tubulin (O'Donnell and Cigelnik 1997; O'Donnell et al. 1998) proteins has also proven useful in separating Fusarium species. Although DNA sequencing is the preferred method for phylogenetic studies, use for routine identification of many isolates has historically been relatively expensive. However, DNA sequencing continues to become more economical with technological advancements and widespread use. Electrophoretic karyotyping has also shown polymorphism in Fusarium at the species (Fekete et al. 1993) and subspecies levels (Kim et al. 1993a; Boehm et al. 1994; Xu et al. 1995). It remains unclear if species level polymorphisms are obscured by the high degree of subspecies polymorphisms. In F. oxysporum f. sp. niveumthere appears to be no association between karyotype and race or between karyotype and mitochondrial DNA haplotype (Kim et al. 1993a). In contrast, Boehm and coworkers (1994) reported a strong relationship between VCG and karyotype. Seventy-two percent of genome size variation could be explained by VCG groupings within F. oxysporum f. sp. cubense, suggesting that VCGs may represent clonal lineages. Xu and coworkers (1995) used electrophoretic karyotyping to explore variability within Gibberella fujikuroi mating populations (Fusarium section Liseola). Distinct karyotypes were observed for all mating populations. Isolates from the same mating population displayed similar karyotypes regardless of geographic or host origin. It was also noted that the smallest chromosome could be lost in laboratory culture following meiosis. Supernumerary B-chromosqmes, or dispensable chromosomes, have been observed in several fungi including Bremia lactucae (Francis and Michelmore 1993), Cochliobolus heterostrophus (Tzeng et al. 1992), and Magnaporthe grisea (Valent and Chumley 1991). Such chromosomes have also been found to carry genes for pathogenicity of Nectria haematococca (anamorph Fusarium solani) on pea (Miao et al. 1991; Kistler and Miao 1992). The association between B-chromosomes and pathogenicity in N. haematococca may indicate usefulness in electrophoretic karyotyping for the differentiation of some pathogenic and nonpathogenic isolates. 8 Randomly amplified polymorphic DNAs (Williams et al. 1990; Welsh and McClelland 1990) have also been used extensively in the characterization of Fusarium species. This method has been used to differentiate formae speciales and races of Fusarium oxysporum (Grajal-Martin et al. 1993; Manulis et al. 1993; Assigbetse et al. 1994; Migheli and Cavallarin 1994) and other Fusarium species (Crowhurst et al. 1991; Ouellet and Seifert 1993; Voigt et al. 1995). The RAPD method has also been used to examine population variability (Bentley et al. 1995; Bulat et al. 1995) in Fusarium oxysporum, and to distinguish species of Fusarium (Schilling et al. 1996). The technique has the advantage of speed when dealing with large sample sizes, but has been widely criticized for a lack of reproducibility (MacPherson et al. 1993; Meunier and Grimont 1993; Muralidharan and Wakeland 1993; Penner et al. 1993; Ellsworth et al. 1994; He et al. 1994; Davin-Regli et al. 1995) unless precise protocols are followed (Micheli et al. 1994; Tommerup et al. 1995; Gallego and Martinez 1997). Restriction fragment length polymorphisms are useful for the differentiation of Fusarium species (Lodolo et al. 1993; Donaldson et al. 1995), intraspecific differentiation (Manicom et al. 1990), and for examining genetic diversity among populations (Correll et al. 1992; Woudt et al. 1995). Both nuclear (Flood et al. 1992; Appel and Gordon 1995; Woudt et al. 1995) and mitochondrial (Jacobson and Gordon 1990; Gordon and Okamoto 1992; Kim et al. 1992; Appel and Gordon 1994) RFLPs have been examined in these studies of F. oxysporum. Two approaches to RFLP analysis have been used. The traditional method uses labeled probes, often derived from a genomic library, to hybridize to restriction-endonuclease-digested DNAs fixed to a nylon membrane. This requires relatively large amounts of DNA and is quite time consuming. The polymerase chain reaction (PCR) allows specific fragments of DNA to be amplified and subsequently digested with restriction endonucleases. This method requires only small amounts of DNA, but has the disadvantage of requiring some sequence information in order to design primers to facilitate PCR. 9 Repetitive DNA elements are a feature found in all eukaryotic organisms. The function of this "junk DNA" has historically been rather mysterious, although increasing evidence suggests that repetitive elements are involved in protein recognition, transcriptional activation and chromatin structure (Zuckerkandl 1992). Among plant pathogenic fungi, repetitive DNA has been used to identify subpopulations of the rice blast fungus, Magnaporthe grisea (Hamer et al. 1989; Levy et al. 1991) and Erysiphe graminis (O'Dell et al. 1989). In both of these cases, the resolved subpopulations could be related to the pathogenic specialization of the fungi. Other work (McDonald and Martinez 1990; Milgroom et al. 1992) has further demonstrated the usefulness of the repetitive elements in elucidating population structure. Repetitive DNA sequences have also found utility in the intraspecific differentiation of Fusarium oxysporum. Kistler and coworkers (1991) used arbitrarily chosen genomic clones to identify repetitive sequences. When used in hybridizations to restriction-endonuclease-digested DNAs from 41 isolates of crucifer-infecting F. oxysporum, these probes provided unique banding profiles for each isolate. Parsimony analysis of the repetitive elements resulted in clear separation of each vegetative compatibility group. Namiki and coworkers (1994) also used genomic clones containing repetitive DNA as probes, which yielded 52 unique "fingerprints" from 56 isolates of cucurbit-infecting F. oxysporum. A dendrogram generated using repetitive DNA data showed major clusters corresponding to formae speciales. Edel and associates (1995) used a random genomic clone from F. oxysporum to prepare a chemiluminescent probe for screening Southern blots, as well as a PCR-based method of examining repetitive DNA to differentiate isolates of F. oxysporum. Both methods showed similar relationships among the isolates examined, but differed in their degree of resolution. Much of the work using molecular methods has been done in conjunction with vegetative compatibility group (VCG) testing. Vegetative compatibility is defined as the ability of two isolates to anastomose and form heterokaryons. Since members of different vegetative compatibility groups can not form heterokaryons, VCGs represent a form of reproductively 10 isolated groups. In many formae speciales of F. oxysporum, isolates from the same forma specialis typically belong to the same VCG or a small number of VCGs, and often share DNA and isozyme polymorphisms (Puhalla 1985; Bosland and Williams 1987; Katan and Katan 1988; Jacobson and Gordon 1988; Larkin et al. 1990). In some formae speciales, pathogens belong to a single VCG. In F. oxysporum f. sp. albedinis, a pathogen of date palm, all isolates belong to a single VCG, and RAPDs can clearly differentiate the pathogen from nonpathogenic isolates found in the rhizosphere (Fernandez and Tantaoui 1994). In some formae speciales, however, the relationship can be much more complex (Correll 1991), with a single race belonging to several VCGs, as in F. oxysporum f. sp. lycopersici (Elias and Schneider 1991) where a single race belongs to at least 41 different VCGs. This level of VCG diversity is unusual for a F. oxysporum pathogen, and is similar to the degree of VCG diversity found in nonpathogenic root colonizers (Correll et al. 1986) or soil saprophytes (Gerdemann and Finley 1951). This has led Correll (1991) to suggest that the diversity present in nonpathogenic Fusarium isolates, derived from soil and root tissue, is acted upon by mutation to generate novel pathogenic races which appear among isolates from different VCGs. 11 Chapter 2: Materials and Methods Culture Collection and Isolate Identification The isolates used in this study were provided by Dr. Jeff Stone (Oregon State University) or came from the BC Research collection (Appendices A and B, Table 5). Soil and tissue isolates obtained from Dr. Jeff Stone came from several different conifer nurseries in Oregon, Washington, Idaho and California, with the majority collected from two sites: Medford and Bend, Oregon (Figure 1). Isolates were collected from soil samples as well as host tissue samples of Pseudotsuga menziesii (Douglas-fir) and Pinus ponderosa (Ponderosa pine), from both symptomatic and asymptomatic seedlings between 1993 and 1996. Figure 1: Geographic Locations of Nurseries CALIF< Oregon isolates of F. oxysporum were initially identified morphologically by Dr. Jeff Stone or Dr. David Gernandt. Isolates in the BC Research culture collection were identified as 12 F. oxysporum based on microscopic morphology by Dr. Paige Axelrood or Dr. Keith Seifert. Isolates were further confirmed as F. oxysporum using AFLPs. Many of the isolates were also identified by means of histone-H3 RFLPs. The histone-H3 RFLP haplotype has previously been shown useful for differentiating Fusarium species (Donaldson et al. 1995). Blind test results, discussed later, indicate that the use of histone-H3 RFLP haplotypes for identification is highly accurate. Three-hundred-and-seventy-one Fusarium isolates were examined using either AFLPs or histone-H3 RFLPs. Two-hundred-and-sixty-seven F. oxysporum isolates from Medford and Bend nurseries were examined using AFLPs with primer N7 (N7-AFLPs). Of these, 125 were also examined for histone H3-RFLPs. C u l t u r e M a i n t e n a n c e a n d S t o r a g e Working cultures were prepared by growing the isolates on simple nutrient agar (SNA; Nirenberg 1981) for 2 weeks and then placing mycelium-covered agar plugs into sterile cryovials (Nalge, Rochester NY), each containing 1 mL of sterile distilled water. Working cultures were kept at room temperature. Storage cultures were kept in freezing media made with 25% glycerol and 0.1% agar in sterile distilled water. Storage cultures were kept at -80 °C, and were not used unless the working cultures became contaminated. Prior to storage, fungal isolates were grown on potato dextrose agar (PDA; Difco Laboratories, Detroit MI) for 1 week. Approximately 4 mL of freezing medium was added to each plate, and the agar surface of each plate was gently scraped with a sterile spatula to suspend conidia. Next, 1 mL of the conidial suspension was pipetted into two sterile cryovials, and allowed to sit at room temperature for 4 hours. The cryovials were then vortexed at low speed, and placed into a -20 °C freezer overnight. The following day, cryovials were separated into two complete sets and placed into two different freezers for storage at -80°C. 13 D N A Ext ract ion Template DNA for PCRs was obtained using three different methods (Cenis, 1992; Lee et al., 1988; Graham et al., 1994). The speed and simplicity of the Cenis (1992) protocol made it the method of choice, and a modification of this method of DNA extraction became standard procedure. Working cultures of Fusarium, stored in distilled water, were used to inoculate 1.5-mL vials containing 500 pL of potato dextrose broth (Difco Laboratories, Detroit MI). Inoculated vials were incubated for 72 hours at room temperature, the mycelium was then pelleted by centrifugation at 13000 RPM for 10 minutes, and the supernatant carefully removed using a pipettor. The mycelial pellet was then rinsed with 500 pL of TE buffer (10 mM Tris-HCl, 1 mM EDTA) and centrifuged again. After the removal of the TE buffer,' 300 uL of extraction buffer (50 mM Tris-HCl, 50 mM EDTA, 3% SDS) was added, and the mycelium was mechanically crushed using a custom-made stainless steel drill bit designed to closely fit cryovials (Sarstedt, St. Laurent PQ). Each mycelial pellet was crushed for at least 30 seconds, or until the suspension become visually homogenous. The drill bit was soaked in 95% ethanol and flamed between isolates to prevent crossover contamination. After the completion of grinding, 150 uL of 3M sodium acetate (pH 5.2) was added to each tube, and they were placed in a -20 °C freezer for 10 minutes. Tubes were then centrifuged for 10 minutes at 13000 RPM, and 400 uL of the supernatant was transferred to anew sterile tube (Bio-Rad Laboratories Ltd., Mississauga ON, Cat #223-9395), and an equal volume of isopropanol was added. Tubes were placed in a -20 °C freezer overnight to precipitate the DNA. The following day, tubes were centrifuged for 10 minutes at 13000 RPM, and the supernatants poured off and discarded. Next, 500 uL of ice-cold 70% ethanol was added to each tube to rinse,and tubes were centrifuged again, and the ethanol was poured off. Tubes were then placed in a speed-vac for 30 minutes, and the pellets were resuspended in 150 uL of T0.1E buffer (10 mM Tris-HCl, 0.1 mM EDTA). 14 Restr ict ion Fragment Length Polymorphism (RFLP) Analysis Genetic data were collected using two different methods. The first method of characterization was restriction fragment length polymorphism analysis. Primers designed for the histone-H3 gene and the p-tubulin gene (Glass and Donaldson 1995) were used to amplify enough DNA for subsequent digestions using different restriction endonucleases. Additional primers were used to amplify the intergenic spacer region (IGS) of ribosomal DNA (Appel and Gordon 1995, 1996). The restriction endonucleases used in the analysis of the histone-H3 PCR product included Nde II, Cfo I (Boehringer Mannheim, Laval, PQ), Mse I, and Nla III (New England Biolabs, Boston MA). Restriction digests of the p-tubulin PCR product were done using Cfo I, Rsa I, Sau 3AI (Boehringer Mannheim, Laval, PQ),Ma III, and Hae III (New England Biolabs, Boston MA). Restriction digests of IGS PCR products were done using the same enzymes as the P-tubulin PCR product, in addition to Alu I, andHpa II (Pharmacia Biotech, Baie d'Urfe PQ). Amplifications of the target genes were carried out in 25 to 100 uL reaction volumes using either an Ericomp Single Block® (San Diego CA) or an MJ Research Inc. PTC-100® (Watertown MA) thermal cycler. Reaction components included buffer and magnesium chloride (Promega, Nepean ON), deoxynucleotide phosphates (dNTPs; Boehringer Mannheim, Laval PQ) and Taq polymerase (Roche Diagnostic Systems, Mississauga ON). Primers were synthesized by the University of British Columbia Oligonucleotide Synthesis Laboratory (Vancouver BC). A l l reactions were executed as recommended by Roche, and used 0.4 uM of each primer, approximately 15 to 50 ng of template DNA, 200 uM of each dNTP, and 2.5 mM magnesium chloride. Positive control reactions contained genomic DNA from Neurospora crassa, and reactions containing no template DNA ensured that all reagents were free of contaminating template DNA. Al l reactions were set up in a flow hood, using aerosol resistant pipette tips, and basic aseptic techniques. The final step of Taq polymerase addition was typically carried out 15 after the reaction tubes were placed into the thermal cycler and heated to approximately 80°C. This procedure, known as "hot starting," helps reduce nonspecific primer binding and improves reaction fidelity (Ruano et al. 1991). Initial PCR cycling parameters consisted of an initial denaturation step at 95 °C for 2 minutes, followed by 40 cycles of: 94 °C for 1 minute; 60 °C for 1 minute; 72 °C for 1 minute. A final extension step then took place at 72 °C for 10 minutes. If no product was amplified, additional reactions were then performed with varying template levels or with reduced annealing temperatures of 50 to 60 °C. Restriction digests were done using 19 uL samples from successful PCRs, and 1 to 2 uL of enzyme (-10 U/uL). No additional buffer was required since the PCR buffer served as an adequate substitute. Al l digests were subsequently incubated at 37 °C for 6 hours. After restriction digests were completed, the products were separated by gel electrophoresis on 2% agarose and visualized under ultraviolet light after staining with ethidium bromide (Sambrook et al. 1989). Photographs were taken using Polaroid type 667 film (Polaroid Corp, Cambridge MA), and a Wratten #15 filter. Isolates were then assigned a haplotype using the results of the digests. Blind Testing of the Histone-H3 RFLP Diagnostic Procedure To assess the accuracy of the histone RFLP diagnostic procedure outlined in Figure 2, blind tests were conducted using a variety of Fusarium species as well as fungi commonly isolated from conifer nursery environments, such as Cylindrocarpon and Trichoderma. This diagnostic procedure had previously been used on a small number of isolates from six Fusarium species. This included 13 F. oxysporum isolates, 11 F. proliferatum isolates, IF. moniliforme isolates, 6 F. avenaceum isolates, 2 F. acuminatum isolates and a single isolate of F. sporotrichioides (Donaldson et al. 1995). The procedure relies on RFLPs located within the gene encoding histone-H3. Polymerase chain reactions were used to amplify the gene encoding histone-H3 (Glass and Donaldson 1995). Once amplified, the PCR products were digested with restriction endonucleases (Figure 2). Additional data was acquired from RFLP analysis of the 16 gene encoding histone-H4 if further confirmation of species identity was desired. Extraction of DNA, PCR amplifications and restriction endonuclease digestions were carried out as previously described. Figure 2: Diagnostic Procedure Using RFLP Analysis of Histone-H3 PCR Product Amplify the H3-1 target with PCR Digest the H3-1 product with Mbo Fusarium species Non-Fusarium species Digest H3-1 product with Cfo I 1, I F. mon/liforme F. oxysporum F. avenaceum F. proliferatum F. acuminatum Digest H3-1 products with Mse I and Nla III F. moniliforme F. oxysporum F. avenaceum F. acuminatum F. proliferatum Amplified Fragment Length Polymorphism (AFLP) Analyses The second method used for genetic characterization of isolates is a relatively new technique called amplified fragment length polymorphism analysis, (Zabeau and Vos 1992; Vos et al. 1995). The technique is similar in principle to randomly amplified polymorphic DNAs (Williams et al. 1990; Welsh & McClelland 1990), except that AFLPs rely on the ligation of known primer sequences, called adapters, to genomic DNA digested with a restriction endonuclease (Figure 3). The resulting restriction fragments therefore have a known sequence attached at both ends. Amplification of the target DNA sequences is therefore specific. This 17 procedure avoids the potential for artifactual variation often associated with RAPDs (Micheli et al. 1993; Ellsworth et al. 1993; Xu et al. 1995). Amplification uses a single primer that is complementary to the adapter sequence. Since all of the restriction fragments generated carry the same adapter attachment, PCR amplification would generate of smear of fragments. However, by adding between one and four randomly chosen bases to the primer sequence, the proportion of restriction fragments amplified can be varied. For example, by adding one additional base to the primer sequence, the number of restriction fragments amplified will be reduced to 1/16 of the original number. The use of two additional bases would reduce the number of amplified fragments by 1/256, and the use of three additional bases would reduce the number of amplified fragments by 1/4096. Hence by varying the restriction endonuclease used and length of the PCR primer, the complexity of the observed AFLP pattern can be increased or decreased depending on the degree of resolution desired. F i g u r e 3: A m p l i f i e d F r a g m e n t L e n g t h P o l y m o r p h i s m ( A F L P ) A n a l y s i s genomic DNA V77A double stranded DNA adapter mm PCR primer complementary to adapter sequence with an additonal 1-4 bases Double-stranded adapter molecules were prepared by combining equimolar amounts of oligonucleotides A l and A2 (Table 1) to make a 50 pmole/uL solution. After extraction, genomic DNA was completely digested withMsel, a restriction endonuclease with a 4 base 18 recognition site. Simultaneous digestion with Mse I, and ligation of double-stranded DNA adapter occurred in the reaction. Since theMs'e I recognition sequence is not recreated with the ligation of the adapter, both the restriction digestion and adapter ligation were performed in a single reaction. Each 20 uL restriction digestion-ligation reaction contained approximately 100 ng genomic DNA, 200 ng adapter, 4 \JMse I, 400 U of T4 ligase, 0.5 mM adenosine triphosphate, 2 mM dithiothreitol, and 100 ug/mL bovine serum albumin in lx Mse I reaction buffer. Al l reaction components were obtained from New England Biolabs (Boston MA) unless otherwise indicated. Reactions were incubated for 24 hours at 37 °C, and then left at room temperature for 2 hours before processing was continued. Table 1: Oligonucleotides Used for Constructing Double-stranded Adapter Molecules Oligon ucleotide Nucleotide Sequence Length (bp) Molecular Weight A l 5' -GACGATGAGTC CTGAG-3' 16 5192 A2 5' -TACTC AGGACTC AT-3' 14 4543 Prior to use in PCRs, the modified genomic DNA was ethanol precipitated in order to remove all excess adapter molecules, which could interfere with PCR amplification. This step effectively removes all DNA fragments less than 200 bp in length. Each restriction digestion-ligation reaction was increased to a volume of 100 uL with the addition of 80 uL of sterile distilled water. Next, 50 uL of 7.5 M ammonium acetate was added to each reaction, followed by the addition of 200 uL of ice-cold 95% ethanol. After mixing by gentle inversion, the samples were placed at -20 °C overnight. The following day, the samples were centrifuged for 10 minutes at 14000 RPM in a cold-room microfuge. The supernatant was decanted and the DNA pellet was rinsed with ice-cold 70% ethanol, vacuum dried for 30 minutes, and resuspended in 40 uL of TO. IE buffer (10 mM Tris-HCl, 0.1 mM EDTA). AFLP PCRs were carried out in a 50 uL reaction volume, using approximately 15 ng of template DNA, 100 uM of each dNTP, 2.5 mM of magnesium chloride and 1.0 uM of one of the 19 primers listed in Table 2. As with the histone-H3 PCRs, all AFLP reactions were prepared under sterile conditions, and reactions were heated to 80 °C prior to the addition of Taq polymerase. The cycling protocol for the AFLP PCRs began with a 2 minute denaturation at 95 °C. After this step, the following cycle protocol was repeated 40 times: 94 °C for 1 minute; 65 °C for 30 seconds; and 72 °C for 2.5 minutes. The annealing temperature was varied according to the melting temperature (Tm) of the primer being used. Melting temperature is defined as the temperature at which half of the helical structure of DNA is lost. In all cases, the PCR annealing temperature was set six degrees higher than the estimated T m of the oligonucleotide. The AFLP amplification products were then separated on 2% agarose gels, visualized and photographed as previously described. Gel photographs were scanned using a Hewlett-Packard ScanJet 3C/T and saved as tagged image format (TIF) files for later image analysis. T a b l e 2: A F L P P r i m e r s S c r e e n e d o n H i g h a n d L o w V i r u l e n c e Fusarium oxysporum I so la tes Primer Nucleotide Sequence Length (bp) Molecular Weight Tm(°C) N2 5 '-GATGAGTCCTGAGTAAAAT-3' 19 6166 52 N3 5 '-GATGAGTCCTGAGTAAAAG-3' 19 6166 54 N4 5 '-GATGAGTCCTGAGTAAAAC-3' 19 6166 54 N5 5 '-GATGAGTCCTGAGTAAAGC-3' 19 6166 56 N6 5 '-GATGAGTCCTGAGTAAGGC-3' 19 6166 58 N7 5 '-GATGAGTCCTGAGTAAGCG-3' 19 6166 58 N8 5 '-GATGAGTCCTGAGTAAAATA-3' 20 6490 54 N9 5 '-GATGAGTCCTGAGTAAAAGC-3' 20 6490 58 GP2 5' -GATGAGTCCTGAGTAAACA-3' 19 6166 54 Notes: T,„ values estimated using Tm=2(A+T) + 4(G+C); molecular weights calculated as 324.5 x Length (bp). AFLP R e p r o d u c i b i l i t y T e s t i n g Since AFLPs are a relatively new development in the field of molecular diagnostics, some work was required to confirm the robustness of the method. Three isolates of F. oxysporum were chosen at random, and DNA was extracted from each isolate using three different methods (Lee et al. 1989; Cenis 1992; Graham et al. 1994). Each extraction procedure was repeated 5 20 times for each isolate. Restriction digestion and adapter ligation reactions were performed as described above using each extraction product (3 isolates x 3 extraction methods x 5 reps = 45 restriction digestion and ligation reactions). In addition, 11 isolates of F. oxysporum were amplified on two different thermal cyclers (Ericomp SingleBlock® System, and MJ Research PTC-100®) to confirm that little or no variation in AFLP pattern is caused by machine-to-machine variation. Standard reaction conditions were used as previously described. Taguchi Optimization of the Polymerase Chain Reaction Polymerase chain reaction conditions were optimized for template DNA, dNTPs, magnesium chloride, and primer concentrations using Taguchi methods (Cobb and Clarkson 1994). Taguchi methods are often used to optimize industrial processes with a minimum number of experiments. To minimize the number of experiments, each factor was varied at three different levels (A, B and C in Table 3), and experiments are arranged in an orthogonal array. This allows four reaction variables, corresponding to primer, magnesium chloride, dNTP and template DNA concentrations, to be optimized in nine reactions (Table 3). Taguchi arrays can be conveniently created using SYSTAT® (SYSTAT 1994). Calculating the signal-to-noise ratio for each reaction in the experiment approximates the effects of individual components on amplification. Table 3: Taguchi Array for Three Levels at each of Four Parameters Reaction # Parameter 1 Parameter 2 Parameter 3 Parameter 4 1 A A A A 2 A B B B 3 A C C C 4 B A B C 5 B B C A 6 B C A B 7 C A C B 8 C B A C 9 C C B A 21 Since the goal of PCR is to create as much product as possible, Taguchi suggests the following quadratic loss function: SrVL = -10-log f \ y J where SNL is the signal-to-noise ratio, n is the number of levels at which each factor was set, and y is the yield of the reaction (Cobb and Clarkson 1994). Each reaction yield was quantified using Biolmage® software (Advanced Quantifier 1-D Match® 1996). Other, freely available, programs such as NIH Image will also quantify reaction products to allow an approximation of reaction yield. Pooling the yields of reactions sharing the same parameter level allowed calculation of SNL values for each reaction parameter at all three levels. For example, to calculate the SNL of the magnesium concentration parameter at the lowest level, the three reactions that contained low magnesium had their yields added together. After calculating all of the SNL values, optimal reaction conditions were estimated by using polynomial regression from the SNL values for each reaction parameter to obtain curves whose peaks represent reaction optima. Curve fitting was done using SlideWrite Plus® for Windows®(1995), using a second order polynomial equation. DNA Sequencing and Analysis The gene encoding the histone-H3 protein was amplified using PCR with primers previously described (Glass and Donaldson 1995). Successfully amplified DNA fragments were then purified using QIAQuick columns (QIAGEN Inc., Mississauga ON) and their concentrations determined by agarose gel electrophoresis of the samples with known quantities of lambda phage DNA. Sequencing reactions were done as recommended in the ABI PRISM Dye Terminator Cycle Sequencing Ready Reaction Kit instructions (Protocol P/N 402078, Revision A), with 3.2 pmoles of H3-la primer (Glass and Donaldson 1995), and 100 ng of purified PCR product in a total volume of 20 uL. Cycle sequencing was done using a MJ Research Inc. PTC-100® thermal 22 cycler with the following cycling parameters: 96°C for 30 seconds; 50 °C for 15 seconds; 60 °C for 4 minutes. This cycle was repeated 25 times and then ended with a 4 °C soak. After the completion of cycle sequencing, reactions were purified using Centri-Sep columns (Princeton Separations, Adelphia NJ) dried down in a speed-vac, and placed in a -20 °C freezer while awaiting final processing. Reactions were run on an ABI PRISM 373 Automated DNA Sequencer courtesy of Chris Radomski at Terragen Diversity. The resulting sequence traces and text files were transferred to an IBM compatible computer for editing using Chromas version 1.41 (McCarthy 1996) and a simple text editor. Ambiguous bases not identified by the ABI PRISM software were checked manually by referring to the base calling rules for AmpliTaq® FS (Huntley 1996). Edited DNA sequences were aligned using Clustal W (Thompson et al. 1994) with a gap penalty of 10 and a gap extension penalty of 0.05. The resulting alignment was manually inspected and then used to construct neighbour-joining trees with TreeCon for Windows, version 1.3b (Van de Peer and De Wachter 1994). The TreeCon program was configured to use Kimura's two-parameter model of DNA evolution (Kimura 1980) assuming a gamma distribution of nucleotide substitution rates among sites (Jin and Nei 1990), with the gamma distribution a parameter set to one. This model of DNA evolution treats transitions and transversions separately and assumes that the rate of nucleotide substitution varies according to the gamma distribution. A l l positions of the alignment were considered in the analysis except for insertions and deletions. Additional analyses were done using intron only and exon only subsets of the sequence data under the same conditions described above. Analysis of DNA sequence polymorphism and estimation of synonymous and nonsynonymous nucleotide diversity within intron and exon sequences were done with the freely available computer program DNASP, version 2.55 (Rozas andRozas 1995, 1997). 23 Image Analysis of Amplified DNA Fragments in Agarose Gels Image analysis was performed on an IBM compatible desktop computer using Biolmage® software (Advanced Quantifier 1-D Match®). Images were inverted and filtered to facilitate the analysis as recommended in the Biolmage® Users Manual. The image analysis software was then used to mark lanes within each scanned image and detect bands according to set threshold values for intensity and thickness. After assigning standard markers, the software accurately sizes all of the detected bands in the image. The recorded data were then output as binary strings representing the electrophoretic pattern of each isolate and then exported as a comma separated value file for further analysis. Pathogenicity Testing Procedure Pathogenicity testing was carried out using a modified version of the Magenta jar assay (Axelrood et al. 1995). Kimpak® paper (Kimberly-Clark, Mississauga ON) was cut into 6 cm x 6 cm squares, placed at the bottom of Magenta GA-7 jars (Magenta Corp., Chicago IL) and moistened with 15 mL of distilled water per jar. Lids were placed on jars and jars were autoclaved to create a sterile environment for testing. Douglas-fir seed (seedlot #16501), obtained from the British Columbia Ministry of Forests Seed Centre, was stratified prior to use. Imbibition of the seed was carried out under running tap water for 24 hours, after which the seed was rinsed with sterile distilled water and then placed on sterile paper towels in a laminar flow hood to remove excess water. Seeds were then placed into plastic screw-top containers and placed in a refrigerator at 4 °C for 3 to 4 weeks prior to use. Immediately before the assay, seeds were surface-sanitized in 30% hydrogen peroxide for 1 hour and rinsed 3 times with 400 mL of sterile distilled water. Inoculum for the pathogenicity assays was grown up on potato dextrose agar plates for 1 week. Conidia were harvested by adding 5 mL of sterile distilled water to the culture plate and 24 gently scraping the mycelia. The resulting suspension was then filtered through three layers of sterile cheesecloth to remove macroscopic particles of agar and mycelium. The spore density was adjusted to approximately 105 conidia/mL using a haemocytometer, and checked by dilution plating. Seeds were soaked in the appropriate inoculum for 15 minutes and then placed in the proper jars. Negative controls consisted of seeds soaked in sterile distilled water for 15 minutes before being placed into jars. Fusarium oxysporum isolate F41 was the positive control treatment and was isolated from Douglas-fir seed and previously shown to be virulent on Douglas-fir germinants (Axelrood et al. 1995). Eight seeds were placed in each jar and 8 jars were used for each treatment in all experiments. In order to prevent moisture loss, parafilm-M® (American National Can®, Greenwich CT) was used to seal each jar. Jars were completely randomized prior to placement in a growth chamber. Growth chambers (Conviron Inc., Winnipeg MB) were programmed for an 18 hour photoperiod with a temperature of 28 °C during the day and 22 °C at night. After 3 weeks, the jars were removed from the growth chamber and scored for disease. The seedlings were scored as healthy, nonemerged, or diseased. Statistical analyses of the data were performed with SYSTAT® for Windows® (SYSTAT® 1994) using Dunnett's one-sided test to compare the proportion of healthy seedlings between water control and test treatments. Fusarium oxysporum isolates were assigned to high, intermediate, or low virulence categories. Isolates placed in the high and low virulence categories were tested again, with two exceptions, to confirm their virulence status. Genetic Similarity and Distance Calculations Electrophoretic banding patterns of AFLPs and RFLPs were scored for the presence and absence of amplification products. The presence of a band was recorded as a "1" and the absence of a band was recorded as a "0". Pairwise genetic similarities between isolates were calculated from raw binary data using RAP Distance version 1.04 (Armstrong et al. 1994) and stored in the 25 form of similarity matrices. Genetic similarities were then converted to genetic distance using the formula D = 1 - S, where D is the genetic distance and 5 is the genetic similarity. Five similarity measures were calculated with a subset of the data to determine the relationships among different genetic distance estimates (Table 4). To examine the relationships among genetic distance values derived from different similarity coefficients, distance values were plotted against each other. After an examination of different genetic distance measures, the Dice similarity coefficient (SD) was selected for use. Pairwise genetic distances calculated from Dice similarity matrices were then used for dendrogram construction and multidimensional scaling (MDS). Principal component analysis (PCA) was directly from binary data, and was done using SYSTAT® for Windows® (SYSTAT® 1994). T a b l e 4: S i m i l a r i t y C o e f f i c i e n t s E x a m i n e d i n t h i s S t u d y Similarity Coefficient Reference(s) a Czekanowski 1913; Dice 1945; Nei and Li 1979 a a + b + c Jaccard 1901 sE - * - £ ) Excoffieretal. 1992 ss ad d~(a + b){a + c)(b + d){c + d) Sokal and Sneath 1963 SP ad-be *J(a + b)(a + c)(b + d)(c + d) Yule 1912 (Pearson's Phi) a = number of characters common to both x and y,b = number of characters present in x but absent in_y; c = number of characters present in y but absent in x; A = number of characters absent from x and y; n = total number of characters scored. 26 DeHdrogFaHT Construction Dendrograms were constructed using TreeCon for Windows® version 1.3b (Van de Peer 1994). This, package allows, a choice, among the^^neighbour-JQinirj^algorithm developed by Saitou and Nei (1987), as well as four clustering methods including the popular unweighted pair-group method using arithmetic averages (UPGMA). The ndghborrr j^oirring method was setected-as the methodof c h o i c e for several-reasons. Firs^ the neighbour j^ofnihg method makes no assumption of evolution- rate-constancy (i .e. a molecular clock) in contrast taclustering methods-such as UPGMA. Second, the neighbour-joining method is computationally simple and therefore relatively-fast compared toother methods, particularly when bootstrapping. Third, the results of simulation studies have suggested that the rteighbK)w-jc4rrirrg method is quite robust in comparison to other methods of dendrogram construction. Population Genetic Analysis Tadetermine if significant differences irireJative haplotype frequencies existed among subpopulatk>nsy confidence intervals-were constructed for each-category. The standard error of any given AFLP or H3-RFLFhaplotype frequency can be calculated as: V n where-7Z~ is the observed proportion of population belonging to any given category, and«-js the sample size (Samuels 1989). Hencey the 95% coiifidence intervaL can then be constructed as: 7t±\M0(SE.) For each nursery population, gene chversity for RFLP and AFLP loci was calculated usingNei's (1973) measure, defined as h9 = 1 - pf where/vis the frequency of the .f* allele withkLa given nursery population. Eor Mstone-H3 RFLP data, the variance of gene diversity was estimated as derived by Nei and Roychoudhury (1974, equation 12). The calculated variance 27 estimate was then used to construct confidence intervals. For AFLP data, each amplification product is considered a locus with two alleles indicated by presence or absence of the specified DNA fragment. The average hs over all loci in a nursery population (Hs) was then computed. In addition, the gene diversity for each tissue and soil subpopulation within each nursery was also computed as hc - 1 - ^ pf , where ps is the frequency of the i'h allele within a given tissue or soil subpopulation. The average he over all loci in a tissue or soil subpopulation (Hc) was then computed. The total gene diversity at each locus was calculated ashT = 1 - 2-tP-, where p.t is the frequency of the ith allele averaged over all subpopulations. Mean total gene diversity (HT) was then computed as hT averaged over all loci. To determine the degree of genetic differentiation of nursery populations relative to the total population of F. oxysporum, Nei's (1973) Q, was calculated as: ( H T - H S ) - 2X where Hs = and n„ is the number of subpopulations examined. This term can be regarded as the proportion of genetic diversity that can be attributed to differentiation between nursery populations. Similarly, the degree of genetic differentiation of soil and tissue subpopulations within a nursery relative to the nursery population was also computed as: GL = ( H s - H c ) An alternative method of estimating differentiation among subpopulations was also employed. Analysis of molecular variance (AMOVA; Excoffier et al. 1992) also allows one to determine the proportion of the total haplotypic variance that can be attributed to differences 28 among nursery sites, among populations within nursery sites, and within populations at nursery sites. The analysis of variance is performed on a matrix of squared distances between pairs of haplotypes. The Euclidean distance metric (Table 2) is typically used with AMOVA (Excoffier et al. 1992; Tajima and Nei 1981). This technique allows for estimation of § s t, and <|),c, analogues of Gst and Gcs, respectively. The significance of §t and § s c was tested using a nonparametric permutation approach (Excoffier et al. 1992) with 10000 permutations of the original distance matrix. With this procedure, the assumption of normality stipulated in analysis of variance is no longer necessary, nor is it necessary to assume equal variance among populations or groups of populations. Analysis of molecular variance was done using the AMOVA Version 1.55 program (Excoffier et al. 1992). This type of analysis has previously been used with RAPD data (Huff et al. 1993;Peakall etal. 1995). Linkage disequilibria values were calculated for each pair of AFLP marker alleles using the formula: Dab = pab - papb where Dab is linkage disequilibrium coefficient between alleles a and b; pab is the observed frequency of the alleles a and b together; and pa and pb are the observed frequencies of allele a and allele b respectively (Weir 1996). Linkage disequilibria values were standardized by dividing Dab by the maximum possible value of Dab (Weir 1996). Significance of linkage disequilibria values was determined using an exact test with a Markov chain approach (Slatkin 1990; Guo and Thomson 1992; Raymond and Rousset 1995) using Arlequin version 1.1 (Schneider et al. 1997). Multilpcus associations were examined and tested for significance using the method of Brown and others (1980). The summary statistic, IA, is referred to as the index of association, arid s2 k 2 is defined as: IA = —^ ~ 1 > where sk is the observed variance in the number of different loci in °* two randomly chosen individuals, and a\ is the expected variance under the null hypothesis of random mating. The variable &is the number of different loci in two randomly chosen haploid 29 individuals. Under random mating, 1A has an expected value of zero. The index of association is a measure of the deviation of population structure from panmixis. Although this test was originally used to test random mating hypotheses, it has since been used to test for sexual reproduction (Milgroom 1996; Burt et al. 1996; Geiser et al. 1994; Peever and Milgroom 1994; Pujol et al. 1993). Significance testing of the IA statistic was done by constructing an upper confidence limit for s% (Brown et al. 1980). Values exceeding this limit were considered significant. Genotypic diversity was calculated using the formula G = ^ — - where p is the frequency of the i'h multilocus genotype (Stoddart and Taylor 1988; Milgroom 1996). To standardize genotypic diversity values each was divided by sample size, making the value a proportion of the theoretical maximum. The variance in genotypic diversity of each 4 f K \ subpopulation was estimated using the formula: Var(G) = ~J^G2 \^G2 ILJP? where G is the estimate of genotypic diversity, TV is the sample size, pis the frequency of the i'h multilocus genotype, and AT is the total number of genotypes observed in the sample. The variance estimates were then used to construct confidence intervals to determine if there were significant differences between subpopulations of F. oxysporum. Since sexually reproducing organisms typically have greater genotypic diversity, this can also be used as a test for sexual reproduction. In this case, significance testing was performed by constructing a null distribution of genotypic diversity values by randomizing the total population data within columns (i.e. among isolates, but within markers). The observed value of genotypic diversity for the total F. oxysporum population was then compared to the null distribution created assuming random association among loci. 30 Chapter 3: Results Blind Test Identification of Fusarium Species Forty-five fungal isolates were examined by RFLP analysis of the genes encoding histones H3 and H4 (Table 5) to determine the accuracy of the histone RFLP identification diagnostic (Donaldson et al. 1995). The fungal isolates originated primarily in British Columbia and Oregon, although 2 isolates were collected in Colorado, and one in France. Fungal isolates were collected from roots, soil, air and nursery debris. Nineteen of the isolates tested were species never examined before, and in these cases, isolates could only be identified as Fusarium or non-Fusarium species. The remaining 26 isolates had to be identified to species level in order to be considered correct. Table 5: Fungal Isolates Used in PCR-RFLP Blind Test Blind IDU Isolate Code Genus/Species Isolation Source Origin 1 C2CUP5AB2 Cylindrocarpon cylindroides root/reforestation B.C. 2 FA5 F. sambucinum nursery air B.C. 3 F40 F. poae seed B.C. 4 FD4 F. heterosporum nursery debris B.C. 5 F67 F. proliferatum seed (lot 476) B.C. 6 FA3 F. avenaceum nursery air B.C. 7 T40 Trichoderma sp. root B.C. 8 CR3 Cylindrocarpon destructans root B.C. 9 F56 F. oxysporum Tex Baker cl4 Colorado 10 FR18 F. avenaceum root B.C. 11 NFC1 non-Fusarium contaminant root B.C. 12 FR3 F. sambucinum root B.C. 13 F35 F. lateritium seed B.C. 14 NFC4 non-Fusarium contaminant root B.C. 15 FD2 F. reticulatum nursery debris B.C. 16 FD3 F. sporotrichioides nursery debris B.C. 17 CR18231BQP non-Fusarium contaminant root B.C. 18 FD6 F. equeseti nursery debris B.C. 31 Table 5: Fungal Isolates Used in PCR-RFLP Blind Test (cont.) Blind ID# Isolate Code Genus/Species Isolation Source Origin 19 NFC5 non-Fusarium contaminant root B.C. 20 FR4 F. acuminatum root B.C. 21 FR5 F. avenaceum root B.C. 22 CR1 C. destructans root B.C. 23 FR6 F. oxysporum root B.C. 24 T41 Trichoderma sp. root B.C. 25 FR9 F. proliferatum root/reforestation B.C. 26 CR18341TAU non-Fusarium contaminant root B.C. 27 FRIO F. proliferatum root/reforestation B.C. 28 FR11 F. avenaceum root/reforestation B.C. 29 3138 F. oxysporum Douglas fir Oregon 30 F36 F. oxysporum seed B.C. 31 3050 F. moniliforme Pinus contorta root Oregon 32 F55 F. oxysporum Tex Baker c5 Colorado 33 CR6 C. cylindroides root B.C. 34 FA10 F. sporotrichioides nursery air B.C. 35 A3-8-1 F. proliferatum root B.C. 36 476-7-5 F. proliferatum seed B.C. 37 F047 F. oxysporum unknown France 38 C2CUN9AE C. destructans root/reforestation B.C. 39 C1J1N2CA C. cylindroides root/reforestation B.C. 40 Mx-G30-R3(l) F. oxysporum sugar pine roots Oregon 41 Mx-B27-R4(2) F. oxysporum root Oregon 42 M-I3-933 F. oxysporum soil Oregon 43 HN-54-931 F. oxysporum soil Oregon 44 LP-A2-931 F. oxysporum soil Oregon 45 BP-938 F. oxysporum soil Oregon Thirty-nine of 45 fungal isolates were correctly identified using the outlined diagnostic procedure (Figure 2). Eleven of the 12 F. oxysporum isolates in the blind test were correctly identified. Six isolates were incorrectly identified; including 4 species not previously examined (F. reticulatum FD2, F. sambucinum FR3, F. lateritium F35, and F. heterosporum FD4). The other misidentified isolates were F. oxysporum F36, and F. sporotrichioides FA10. 32 AFLP Reproducibility Testing Polymerase chain reactions performed over a very large range of parameter space show several differences, but are remarkably consistent considering the variation in reaction conditions. Figure 4 shows a series of reactions performed using 0.25 to 1.0 uM of primer, 2.5 to 4.0 mM of magnesium chloride, 100 to 300 uM of each dNTP, and approximately 2 to 40 ng of template DNA. Each of these reactions was performed using template DNA from the same restriction digestion and adapter ligation reaction. Initially, the Promega Taq polymerase gave more consistent results. Further experimentation showed that the Roche Taq polymerase is just as consistent if the Promega buffer is used. The only noteworthy difference between the Roche and Promega buffers is the presence of Triton X-100 detergent in the Promega buffer. Figure 4: AFLP Reproducibility Under Varying Primer, Magnesium, dNTP and Template DNA Concentrations Using Two Different Taq Polymerases 1 2 3 4 5 6 7 8 9 10 11 12 13 14 ii&m m m m „LII| IWM? ^ 5 ,*M&W&mmm m m m m mmm %mm mmm * ^ wm ***** • - - — ~ - — . — _ . „MSL_ WKm '•- IMP mm j i M N K wmw mmm mm Igjgp H O T , 8 S P S ! ? Lanes 1 and 14: Gibco/BRL 100 bp ladder; lanes 2-7, Promega Taq polymerase and buffer; lanes 8-13, Roche Tag polymerase and buffer. Reactions shown in lanes 2 and 8 contained 0.5 |iM primer, 200 u,M of each dNTP, 2.5 mM MgCl 2, and 8 ng of template DNA. Reactions shown in lanes 3 and 9 contained 0.5 u.M primer, 300 uM of each dNTP, 4.0 mM MgCl 2, and 40 ng of template DNA. Reactions shown in lanes 4 and 10 contained 1.0 uM primer, 300 u.M of each dNTP, 2.5 mM MgCl 2, and 2 ng of template DNA. Reactions shown in lanes 5 and 11 contained 0.25 uM primer, 100 uM of each dNTP, 2.5 mM MgCI2, and 40 ng of template DNA. Reactions shown in lanes 6 and 12 contained 0.25 u,M primer, 200 uM of each dNTP, 4.0 mM MgCl 2, and 2 ng of template DNA. Lane 13 contained a negative DNA control reaction with 0.5 uM primer, 200 u.M of each dNTP, 2.5 mM MgCl 2. 33 Amplifications using template DNA extracted using different methods and subjected to separate restriction digestion and adapter ligations display some minor differences (Figure 5). Note, however, that in each restriction digestion and ligation reaction, the amount of DNA was not measured, but added by volume (1.0 pL of genomic DNA), and presumed to be about 100 ng of genomic DNA. This is perhaps the most critical step of the process. If the ratio of adapter DNA to genomic DNA is not high enough, some restriction fragments may not have an adapter ligated, and would not be amplifiable. Only one of the 15 reactions (Figure 5, lane3) shows a result that would clearly lead to band scoring errors. Figure 5: AFLP Reproducibility Using Different DNA Extraction Methods and Restriction Digestion / Ligation Reaction Products 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 , , «MM> mm mm «Mk S i M l mm m0 <#*g* mm mm *»*• W mm tm mm •mv »,*. •»->« •mm mm mm ** <*»#> mm •m Lanes 1 and 18: 100 bp ladder standards. Lane 17: blank template control. Lanes 2-16: isolate Mx-DF-941B (SSI). Template DNA was extracted using 3 methods and subsequently used in 5 different restriction digestion-ligation reactions prior to PCRs. Lanes 2-6 used a cetyltrimethylammonium bromide (CTAB) protocol (Graham et al. 1994); lanes 7-11 used a phenol-chloroform extraction method (Lee et al. 1988); lanes 12-16 used a simple isopropanol precipitation method (Cenis 1992). See text for additional details. 34 Amplifications done using different brands of thermal cyclers also display good agreement with each other (Figure 6). Reactions done in the Ericomp machine used a mineral oil overlay, while reactions performed in the MJ-Research machine used a MicroSeal® cover without mineral oil. Both of these machines were programmed with the same reaction parameters. The MJ-Research thermal cycler employs a Peltier pump to heat and cool the reaction block. The Ericomp cycler uses an electric heating element and water-cooling. To record the thermal profile of each machine, a thermocouple was placed into a reaction tube containing a standard reaction volume and placed into the heating block. A typical PCR program was then run, and the temperature in the reaction tube was recorded at regular time intervals. The results are plotted in Figure 7. Differences in the design of the two machines resulted in some minor thermal profile deviations. Neither the differences between thermal cyclers nor the mineral oil overlay result in significant variation among any of the ten isolates tested. Figure 6: AFLP Reproducibility Using Different Thermal Cyclers Lanes 1, 12, and 23: Pharmacia 100 bp ladder. Lanes 2-11: AFLP-PCRs done in an MJ-Research PTC-100. Lanes 13-22: PCRs done in an Ericomp Single Block. 35 Figure 7: Polymerase Chain Reaction Temperature Profiles on Different Thermal Cyclers Ericomp MJ Research u 6 s H 120 150 Time (sec) Selection of a Genetic Distance Measure To construct dendrograms, the raw RFLP and AFLP data must be converted to distance matrices indicating the genetic distance between each pair of isolates. At least 18 different measures of genetic distance have been used by biologists (Armstrong et al. 1994). Gower (1985) has noted that most similarity coefficients are linearly or curvilinearly related. Nevertheless, within these distance measures, three major groups can be discerned (Armstrong et al. 1994). Following the recommendation of Armstrong and coworkers (1994), at least one representative from each of the three major groups was examined using a subset of the total data. The Dice and Jaccard coefficients belong to the first group. The relationship between the Dice 36 and Jaccard distance measures (Figure 8) is clearly the closest. In the context of band comparisons, it seems logical not to count shared absences as a similar character. In this respect either the Dice or Jaccard similarity coefficient is a reasonable choice. The only difference between the two measures is that double weight is given to shared bands with the Dice coefficient. The Dice and Jaccard similarity coefficients are probably the most widely used in biological studies. The second group contains both Pearson's phi (Figure 9) and the Sokal and Sneath (Figure 10) measures, both of which show intermediate levels correlation when compared to the Dice distance measure. Excoffier's Euclidean distance measure is a representative of the third group of similarity coefficients and shows the weakest correlation with the Dice coefficient, particularly for higher distance values (Figure 11). Plots of the considered distance measures against each other illustrate their close relationships (Figures 8-11), and this suggests that little information would be gained by using more than one distance metric. F i g u r e 8: R e l a t i o n s h i p b e t w e e n D i c e a n d J a c c a r d D i s t a n c e M e a s u r e s 0.9 .. 0 8 0 7 1 0 6 • - 0 5 Q -a 0 4 o 0 3 o ^ 02 0 1 • 1 • 0 -0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 Dice Distance 37 Figure 9 : Relationship between Dice and Pearson's Phi Distance Measures Figure 10: Relationship between Dice and Sokal & Sneath Distance Measures Q a O in 0.9 0.8 0.7 0.6 0.5 0.4 0.3 0.2 0.1 0 |!:::::::::::;:::;«i:iii;K :--:::^::.^fc:::::v^V: ->> f< » 4 • • 0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 Dice Distance 0.8 38 Figure 11: Relationship between Dice and Excoffier Euclidean Distance Measures o T 3 W i — CD \& o o >i W 160 140 120 100 80 60 40 20 0 • j i i «u>^ *• K • » WMMMMWM »*» . ::::™t::::-:::-:-:-:-:-::-::-::::::: w * • * * 4 • 0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 Dice Distance The Dice distance metric has a number of qualities that make it the preferred choice, including direct biological significance, which will be discussed in Chapter 4. In addition, analysis of the pairwise distance values produced by each distance measure showed that the Dice distance measure gave the best approximation to a normal distribution (Figure 12). This property was considered since many statistical analyses need an approximately normal distribution to be valid. Al l statistical tests and manipulations requiring a distance matrix used the Dice distance metric, with one exception. The Euclidean distance metric was used for the analysis of molecular variance (Chapter 3). Although the Dice distance measure may be used in AMOVA, the available software does not support the use of distance measures other than the Euclidean metric recommended by Excoffier and associates (1992). 39 Figure 12: Probability Plot of Dice Distance Values for High and Low Virulence Isolates Genetic Distance (Nei & Li 1979) Distribution of genetic distance values between pairs of isolates shown at top of figure. A normal distribution is shown at the right of the figure. Normally distributed data will appear as a straight line in a probability plot. Pathogenicity Testing Results The F. oxysporum isolates tested for pathogenicity originated at five different nursery sites (Medford, Bend Pine, Lucky Peak, Magalia, and Wind River), and consisted of both soil and tissue isolates. Tissue isolates came from both diseased and healthy Douglas-fir and Ponderosa pine seedlings. Seven experiments were done with approximately 17 isolates assayed in each experiment. From 118 assays done on Oregon tissue or soil isolates, the percentage of healthy seedlings ranged from 0% to 95%, with an average of 41% remaining healthy after 3 weeks. Disease frequency ranged between 0% and 100% with an average of 53.5%. Between 0% and 25% of seedlings did not emerge, and an average of 5.5% were nonemerged after 3 weeks. Positive controls showed combined disease and nonemergence levels ranging from 40% to 74%. 40 T a b l e 6: H i g h a n d L o w V i r u l e n c e F. oxysporum Isola tes A n a l y z e d u s i n g A F L P s a n d R F L P s Isolate Nursery Source Identifier Average Healthy M-C5-932 Medford soil MESH1 5.5% LP-A3-931 Lucky Peak soil LPSH2 12% BP-B-935 Bend Pine soil BPSH3 0.0% BP-B5D-935 Bend Pine soil BPSH4 0.0% BP-B-936 Bend Pine soil BPSH5 39% BP-B-931 Bend Pine soil BPSH6 6.3% M-A21-931 Medford soil MESH7 ' 0.0% Mx-G30-S3 Medford Ponderosa pine METH8 3.9% M-I3-933 Medford soil MESH9 0.0% Mx-28A-t3 Medford Ponderosa pine METH10 1.6% Mx-3-2(2) Medford soil MESH11 9.4% MA-5-1-931 Magalia soil MASH 12 23% WR-I6-931 Wind River soil WRSL1 85% LP-A2-931 Lucky Peak soil LPSL2 84% BP-5D-937 Bend Pine soil BPSL3 82% BP-F-935 Bend Pine soil BPSL4 80% BP-MB-932 Bend Pine soil BPSL5 66% BP-5D-931 Bend Pine soil BPSL6 59% Mx-B27-S5 Medford Douglas-fir METL7 85% M-I8-932 Medford soil MESL8 94% M-I6-932 Medford soil MESL9 88% Mx-28A-t2 Medford Douglas-fir METL10 67% M-A8-931 Medford soil MESL11 72% MA-1-1-931 Magalia soil MASL12 80% The first two characters of the identifier field indicate the nursery where the isolate was collected (ME = Medford, MA = Magalia, BP = Bend, LP = Lucky Peak, WR = Wind River); the third character of the identifier indicates the local source of the isolate (T = tissue, S = soil); the fourth character of the identifier indicates the virulence phenotype of the isolate (H = high virulence, L = low virulence); the numerical element uniquely identifies the isolate within the group of high or low virulence isolates. Average percentage of healthy seedlings was the mean of two assays, each containing 8 seeds per jar and 8 jars per treatment. In one case the positive control showed almost no disease (Appendix C, assay 9-7), but subsequent dilution plating of the inoculum indicated that either the inoculum had become nonviable or the concentration was greatly underestimated by haemocytometer count. The negative controls in each experiment showed incidence of nonemerged seedlings between 4% and 14%. In 4 out of 7 experiments, a low level of disease ranging between 2% and 6% was also observed in the negative controls. This disease was presumably caused by organisms that survived the hydrogen peroxide sanitization procedure. Overall, 22 of 72 isolates assayed 41 showed no significant difference in the number of healthy seedlings when compared to the water inoculated control. Although these 22 isolates could not be categorized as pathogens based on the results of pathogenicity assays, the power of the statistical test used precludes their designation as nonpathogens. A complete summary of all pathogenicity assays can be found in Appendix C. Because none of the isolates examined displayed zero disease in repeated pathogenicity assays, only highly virulent or weakly virulent isolates were selected for further AFLP and RFLP analysis. Intermediate levels of virulence were avoided in an attempt to achieve the greatest degree of genetic differentiation between high and low virulence isolates. Twenty-four isolates were selected for genetic analysis based on the results of pathogenicity testing (Table 6, Figure 13). Isolates were chosen to include a range of histone-H3 haplotypes and geographic locations. Figure 13: Percent Healthy Seedlings Three Weeks Post-Inoculation of High and Low Virulence Isolates 00 a 8 0 . 0 0 % 60.00% •S 1 X 40.oo% c Jill • • 1 |L • " 1 m i 1 1 i i MASHI: MESHl 1 METHK ME SIB METH8 MESH7 BPSH6 BPSHJ BPSH4 BPSH3 LPSH2 MESHl S I S to s E a £ 5 E | E B C P High/Low Virulence Isolate Isolate identifiers indicate the nursery where the isolate was collected (ME = Medford, M A = Magalia, BP = Bend, LP = Lucky Peak, WR = Wind River); the local source of the isolate (T = tissue, S = soil); and the virulence phenotype of the isolate (H = high virulence, L = low virulence). The numerical element in an isolate label uniquely identifies the isolate within the group of high or low virulence isolates. Average percentage of healthy seedlings was determined in two independent assays (shown adjacent to each other) each containing 8 seeds per jar and 8 jars per treatment. Two isolates, BPSH5 and MESL11, were tested only once. With two exceptions, each isolate was tested twice. The results of each pair of tests are summarized in Figure 13. High virulence isolates are shown in red, and low virulence isolates are shown in green. Twelve of the isolates were characterized as high virulence isolates (Table 6, 42 Figure 13) which left between 0% and 39% healthy seedlings, with an average of 8% healthy seedlings, 3 weeks post-inoculation. Another 12 isolates were characterized as low virulence isolates (Table 6, Figure 13). The low virulence isolates left between 59% and 94% healthy seedlings, with an average of 78% of the seedlings remaining healthy after 3 weeks. Figure 14: Varying Levels of Virulence in Four Isolates of Fusarium oxysporum Negative control = sterile distilled water; positive control = F41 Isolate 1 = M-I6-932; isolate 2 = M-I8-932; isolate 3 = Mx-28A-t2; isolate 4 = M-I3-933. Figure 14 shows four isolates of F. oxysporum compared to the positive (F. oxysporum F41) and negative (sterile distilled water) controls. In addition to a broad range of virulence, the most virulent isolates at the bottom right of Figure 14 also show a variety of disease phenotypes. While isolate #4 shows 100% post-emergence damping off, isolate #3 exhibits needle disease, and post-emergence damping off. Also of interest is the extensive sporulation of isolate #4 in 43 contrast to the relatively sparse sporulation of isolate #3. The heavy sporulation on the stem surface of the seedling may be important in aerial dispersal of the pathogen in the field. RFLP Analysis of High and Low Virulence Fusarium oxysporum Isolates Three loci were examined using restriction fragment length polymorphism analysis. These included the genes encoding histone-H3, P-tubulin, and the noncoding intergenic spacer region. The 520-bp histone amplicon (Figure 15, Panel A) yielded a totalof three haplotypes among the high and low virulence isolates using four restriction endonucleases. These RFLP haplotypes correspond to the three major clusters shown in the neighbour-joining tree in Figure 16. Similarly, the 1320-bp P-tubulin amplicon (Figure 15, Panel B) yielded two haplotypes using five restriction endonucleases. One P-tubulin haplotype (Figure 16, p-tubulin group A) corresponds perfectly to a histone-H3 haplotype (Figure 16, Histone group A), and the other P-tubulin haplotype (Figure 16, p-tubulin group B) is associated with the remaining two histone-H3 haplotypes (Figure 16, Histone groups B and C). Figure 15: Histone-H3 and P-tubulin Amplification Products from Fusarium oxysporum A B 800 bp • 500 bp -100 bp —-Panel A: histone-H3 PCR products from 9 isolates of Fusarium oxysporum. Panel B: p-tubulin PCR products from 7 different isolates of Fusarium oxysporum. 44 Each of the three groups in Figure 16 contains both high and low virulence isolates. No relationship between either the histone-H3 or p-tubulin RFLP data and virulence or isolation origin (i.e. tissue vs. soil), is evident. The neighbour-joining tree does group most of the Bend isolates into a single group, with the exception of BPSH4. Medford isolates occupy the other two, more closely related groups in the neighbour-joining tree. Two of the Medford isolates, MESH1 and METH8, are placed within the Bend group. The histone-H3 and p-tubulin RFLP data appear to show some degree of association with the geographic origin of the isolate, at least within this limited group of high and low virulence isolates. Figure 16: Neighbour-Joining Tree of High and Low Virulence Fusarium oxysporum Isolates Based on Histone-H3 and p-tubulin RFLP Data 91 BPSL3 LPSL2 METH8 BPSH6 BPSH5 BPSH3 BPSL5 BPSL4 BPSL6 LPSH2 MESH1 100 METL10 MESL8 MESH11 METH10 MESH7 BPSH4 99 METL7 WRSL1 MESL11 MESL9 MASL12 M A S H 12 MESH9 Kstone Group A B-tubulin Group A Kstone Group B Kstone Group C B-tubulin Group B Bootstrap values are shown as percentages of 1000 resampling steps; only bootstrap values above 60% are shown on the dendrogram. Distance bar shown at top left equals 0.1 units. Isolate identifiers indicate the nursery where the isolate was collected (ME = Medford, M A = Magalia, BP = Bend, LP = Lucky Peak, WR = Wind River); the local source of the isolate (T = tissue, S = soil); and the virulence phenotype of the isolate (H = high virulence, L = low virulence). The numerical element in an isolate label uniquely identifies the isolate within the group of high or low virulence isolates. 45 Seven restriction endonucleases were used to examine the IGS region, and each isolate displayed a unique haplotype. Groups of IGS-similar isolates again approximately corresponded to the histone-H3 haplotypes (Figure 17), and the neighbour-joining tree constructed from IGS-PvFLP data produced a basic structure very similar to the tree produced using the histone-H3 and P-tubulin data. The dendrogram indicates much more diversity within the IGS region compared to either the histone-H3 or p-tubulin encoding genes. The three IGS-RFLP groups in Figure 17 correspond exactly to the histone-H3 groups with the single exception of isolate BPSL4. Figure 17: Neighbour-Joining Tree of High and Low Virulence Fusarium oxysporum Isolates Based on IGS-RFLP Data 92 92 78i MESH9 BPSL4 1001 METL7 9 8 ^ MESL11 ~H MESL9 WRSL1 100; MASL12 _ MASH 12 . METH8 BPSH5 BPSH3 LPSL2 _ BPSH6 BPSL6 BPSL3 BPSL5 LPSH2 MESHl _ MESHl 1 MESH7 METH10 _ MESL8 METL10 BPSH4 IGS Group A IGS Group B IGS Group C Bootstrap values are shown as percentages of 1000 resampling steps; only bootstrap values above 60% are shown on the dendrogram. Distance bar shown at top left equals 0.1 units. Isolate identifiers indicate the nursery where the isolate was collected (ME = Medford, M A = Magalia, BP = Bend, LP = Lucky Peak, WR = Wind River); the local source of the isolate (T = tissue, S = soil); and the virulence phenotype of the isolate (H = high virulence, L = low virulence). The numerical element in an isolate label uniquely identifies the isolate within the group of high or low virulence isolates. 46 The neighbour-joining tree derived from all of the available RFLP data again shows one group containing most of the Bend isolates, with two other, more closely related groups containing most of the Medford isolates (Figure 18). As noted previously, there appears to be some geographical correlation, with the spatially closest sites being clustered together, except for the single Wind River isolate which groups with most of the Medford isolates. This is not surprising given that 90% of the isolates recovered from Bend displayed the group C histone-H3 RFLP profile (Figure 27). Al l three major groups within Figure 18 correspond to histone-H3 group or haplotype. Figure 18: Neighbour-Join ing Tree of H igh and Low Viru lence Fusarium oxysporum Isolates Based on Total R F L P Data 100 BPSH4 METLIO -MESL8 METH10 -MESH11 - M E S H 7 82 72 98^ MESL11 i_ MESL9 METL7 MESH9 WRSL1 100, MASL12 M A S H 12 BPSL4 60 r. METH8 BPSH5 BPSH3 lOCl LPSL2 BPSH6 _ B P S L 6 BPSL3 BPSL5 ^_ LPSH2 1MESH1 RFLP Group A RFLP Group B RFLP Group C Bootstrap values are shown as percentages of 1000 resampling steps; only bootstrap values above 60% are shown on the dendrogram. Distance bar shown at top left equals 0.1 units. Isolate identifiers indicate the nursery where the isolate was collected (ME = Medford, M A = Magalia, BP = Bend, LP = Lucky Peak, WR = Wind River); the local source of the isolate (T = tissue, S = soil); and the virulence phenotype of the isolate (H = high virulence, L = low virulence). The numerical element in an isolate label uniquely identifies the isolate within the group of high or low virulence isolates. 47 Figure 19 shows the principal component plot derived from the binary matrix of presence and absence data for restriction fragments. Principal component analysis does not require the construction of a similarity matrix and can be done directly from the raw data. Three components account for 65% of the observed variation in RFLP haplotypes. The first component accounts for 38%, the second component for 18% and the third component for 9% of the total observed variance. The PCA plot shows the same three groups as the dendrogram in Figure 16, with each group corresponding to a particular histone-H3 haplotype. Figure 19: Principal Component Scores of High and Low Virulence Fusarium oxysporum Isolates Based on Total RFLP Data H3 haplotype group assigned by RFLP analysis of the PCR product amplified using primers specific to the gene encoding histone-H3. 48 AFLP Analysis of High and Low Virulence Fusarium oxysporum Isolates The neighbour-joining tree shown in Figure 20 shows clustering of isolates into three major groups, which correspond almost perfectly to the histone-H3 haplotypes. This tree was constructed using data from all nine of the AFLP-PCR primers that were used (Table 2), comprising 319 markers. Polymerase chain reactions using each primer produced a series of amplification products, which were size separated by agarose gel electrophoresis. Each amplified fragment was interpreted as an independent genetic marker with two alleles. The presence and absence of each marker (i.e. allele) was recorded for all isolates. These raw data were summarized as a single distance matrix indicating the genetic distance between each pair of isolates. The neighbour-joining tree was then constructed from the genetic distance matrix. Figure 20: Neighbour-Joining Tree of High and Low Virulence Fusarium oxysporum Isolates Based on AFLP Data Derived from Nine Primers 97 79 80 95r MESH7 M E T L 1 0 80 87i 100r 66r 97 99 87^ -75 r 97! 65 r 73 - M E S L 8 BPSH4 METH10 MESH11 METH8 BPSL3 LPSL2 BPSL5 BPSL6 BPSL4 BPSH5 - LPSH2 BPSH6 BPSH3 MASH 12 MESH9 METL7 WRSL1 MASL12 MESLll MESL9 MESH1 AFLP Group A AFLP Group C AFLP Group B RFLP Group A RFLP Group C RFLP Group B Bootstrap values are shown as percentages of 1000 resampling steps; only bootstrap values above 60% are shown on the dendrogram. Distance bar shown at top left equals 0.1 units. Isolate identifiers indicate the nursery where the isolate was collected (ME = Medford, MA = Magalia, BP = Bend, LP = Lucky Peak, WR = Wind River); the local source of the isolate (T = tissue, S = soil); and the virulence phenotype of the isolate (H = high virulence, L = low virulence). The numerical element in an isolate label uniquely identifies the isolate within the group of high or low virulence isolates. 49 A large degree of geographical association appears to be evident, as with the neighbour-joining trees derived from RFLP data. Again, all of the Bend isolates are clustered together, with the exception of BPSH4. The other two major clusters contain all of the Medford isolates. Two isolates, METH8 and MESHl, are clustered differently in neighbour-joining trees produced by RFLP and AFLP data. These two isolates are placed in RFLP group C and AFLP group A. These two isolates are the last to be joined to other AFLP group A isolates in the Figure 20 dendrogram, and could be interpreted as a fourth group. Within the cluster containing the Bend and Lucky Peak isolates, there is perfect separation of the high and low virulence isolates. This may be related to the fact that the Bend site consists of approximately 90% histone group C isolates. The relationship of high and low virulence isolates from Medford is much less resolved. Figure 21: Principal Component Scores of High and Low Virulence Fusarium oxysporum Isolates Based on AFLP Data Showing Correlation with Histone-H3 Haplotypes 50 Principal component analysis of the high and low virulence AFLP data (Figure 21) shows a similar solution to that illustrated by the neighbour-joining tree in Figure 20. In contrast to cluster analysis which produce only two-dimensional dendrograms, principal component analysis offers multiple dimensions. The three major groups correspond with histone-H3 haplotype. Figure 22: Principal Component Scores of High and Low Virulence Fusarium oxysporum Isolates Based on AFLP Data Showing Relationship with Geographical Origin H3 haplotype group assigned by RFLP analysis of the PCR product amplified using primers specific to the gene encoding histone-H3. Three principal components account for nearly 40% of the total variance among AFLP haplotypes. The first component accounts for 17% of the total variance, and the second and third components are responsible for 13% and 9% of the total variance respectively. Figure 22 shows the same data as Figure 21, but with individual elements labeled by nursery of origin instead of 51 histone-H3 RFLP haplotype. The extra dimension provided by principal component analysis gives no additional insight into the apparent geographic association among isolates. Figure 23: Principal Component Scores of High and Low Virulence Fusarium oxysporum Isolates Based on AFLP Data Showing Relationship with Virulence and Histone-H3 Haplotype H3 haplotype group assigned by RFLP analysis of the PCR product amplified using primers specific to the gene encoding histone-H3. Figure 23 shows the same data as in Figures 21 and 22 with the high and low virulence isolates of each histone haplotype group denoted. In this case, the additional dimension offered in principal component analysis does give a better separation of high and low virulence isolates when compared to the neighbour-joining solution shown in Figure 20. Within each histone haplotype, high and low virulence isolates are loosely associated. At least within this limited group of isolates, the use of large numbers of genetic markers appears to show some association 52 of high and low virulence isolates within each histone haplotype group. Multidimensional scaling in three dimensions using the Dice distance matrix shows similar solutions as those produced through principal component analysis (data not shown). Sequence Analysis of the Histone-H3 Encoding Gene in High and Low Virulence Isolates Primers previously designed (Glass and Donaldson 1995) were used to amplify a 520 bp fragment using PCR (Figure 15, Panel A). These amplification products contain approximately 80% of the translated region of the gene that encodes the histone-H3 protein. It is not known if the histone-H3 encoding gene is a single copy nuclear gene in Fusarium species. None of the isolates examined for histone-H3 RFLPs ever displayed a haplotype that could have been associated with more than one copy of the gene. This does not exclude the possibility that the PCR primers used to amplify the gene encoding the histone-H3 are biased and amplify a specific copy of the gene. Since independent PCRs and subsequent restriction digests of the same isolates never showed different histone-H3 RFLP haplotypes, at the very least all the sequences amplified are orthologous. The same 24 isolates of F. oxysporum selected for previously described AFLP and RFLP analyses were used for sequencing (Table 6). The neighbour-joining tree produced using the DNA sequence data from the histone-H3 encoding gene is shown in Figure 24. Three distinct groups of F. oxysporum, labeled group A, B, and C are clearly visible in Figure 24 and are very well supported by bootstrapping. These groups are nearly identical to those previously observed using RFLP and AFLP analyses. Isolate BPSL4, which is placed in histone group C (Figure 16), and IGS group B (Figure 17), is placed in group C based on sequence data from the gene encoding histone-H3 (Figure 24). Sequence data indicate that the gene encoding histone-H3 in Fusarium species contains two introns. Two lines of evidence support this conclusion. First, both of the proposed introns are delineated by GT/AG splicing signals (Li 1997). Second, the removal of both of the proposed introns results in a contiguous transcript in the proper open reading frame which, when translated, 53 aligns perfectly with the Neurospora crassa histone-H3 peptide sequence; with only one exception — the leucine at position 92 of the N. crassa histone-H3 polypeptide is replaced with an alanine residue in F. oxysporum. The first intron is 83 bp in size, and begins 74 bp downstream of the initiation codon. The second intron is 59 bp in size and corresponds to the intron observed in the histone-H3 gene of Neurospora crassa (Woudt et al. 1983). Neighbour-joining trees produced using either exons only or introns only also show the same 3 major subgroups of F. oxysporum (data not shown). The basic local alignment search tool (BLAST; Altschul et al. 1990; Gish and States 1993) was used to check the nucleotide and translated peptide sequences of the introns for homology to known DNA or protein sequences. Results showed no significant homology between the intron sequences and any nucleotide or peptide sequence in currently available databases. F i g u r e 2 4 : N e i g h b o u r - J o i n i n g T r e e o f H i g h a n d L o w V i r u l e n c e Fusarium oxysporum I so la tes B a s e d o n D N A S e q u e n c e D a t a f r o m the G e n e E n c o d i n g H i s t o n e - H 3 F. oxysporum Group A F. oxysporum Group B F. oxysporum Group C N.crassa Bootstrap values are shown as percentages of 1000 resampling steps; for clarity, only bootstrap values above 90% are shown on the dendrogram. Distance bar shown at top left equals 0.1 units. Isolate identifiers indicate the nursery where the isolate was collected (ME = Medford, MA = Magalia, BP = Bend, LP = Lucky Peak, WR = Wind River); the local source of the isolate (T = tissue, S = soil); and the virulence phenotype of the isolate (H = high virulence, L = low virulence). The numerical element in an isolate label uniquely identifies the isolate within the group of high or low virulence isolates. 94 [ 100 METL10 METH10 MESL8 MESH 11 MESH7 BPSH4 93 99 . WRSL1 . MASL12 |i METL7 MASH 12 MESLll MESH9 99 METH8 BPSH5 LPSL2 BPSL4 BPSL3 BPSH6 BPSH3 MESH 1 BPSL5 LPSH2 _ BPSL6 54 Additional Fusarium species were sequenced to provide comparative distances among different species. The neighbour-joining tree shown in Figure 25 includes 11 other isolates from 4 other Fusarium species in addition to the F. oxysporum isolates selected for high and low virulence. As expected, the three histone haplotypes observed by RFLP analysis within the high and low virulence isolates of F. oxysporum are present. Note that the intraspecific distances among the three F. oxysporum groups are relatively large when compared to some of the interspecific distances in the dendrogram. This supports the claim of O'Donnell and coworkers (1996, 1997, 1998) that F. oxysporum is in fact a complex of phylogenetically distinct species. Figure 25: Neighbour-Join ing Tree of Fusarium Isolates Based on D N A Sequence Data f r o m the Gene Encoding Histone-H3 99 100 100 97 98 F. oxysporum METH8 F. oxysporum BPSH5 F. oxysporum BPSH3 F. oxysporum LPSL2 F. oxysporum BPSL4 F. oxysporum BPSL3 F. oxysporum BPSH6 F. oxysporum MESHl |_ F. oxysporum BPSL6 . F . oxysporum BPSL5 1 — F. oxysporum LPSH2 F. oxysporum WRSL1 I F. oxysporum MAS LI 2 1 F. oxysporum METL7 F. oxysporum MASH 12 5]i F. oxysporum MESL11 T F. oxysporum MESH9 100 F. oxysporum METL10 F. oxysporum METH 10 F. oxysporum MESL8 F. oxysporum MESHl 1 F. oxysporum MESHl F. oxysporum BPSH4 100rf-proliferatum 9'207F —\98 F. proliferatum 9112F I F. proliferatum FR9 100, F. moniliforme FM5 IF . moniliforme FM7 100,F. avenaceum F35 F. avenaceum F34 F. avenaceum F62 100 F.acuminatum 9226W Section Elegans Section Liseola acuminatum FR4 acuminatum F42 Neurospora crassa ] ection Roseum Section Gibbosum Bootstrap values are shown as percentages of 1000 resampling steps; for clarity, only bootstrap values of 85% or above are shown on the dendrogram. Distance bar shown at top left equals 0.1 units. Isolate identifiers indicate the nursery where the isolate was collected (ME = Medford, M A = Magalia, BP = Bend, LP = Lucky Peak, WR = Wind River); the local source of the isolate (T = tissue, S = soil); and the virulence phenotype of the isolate (H = high virulence, L = low virulence). The numerical element in an isolate label uniquely identifies the isolate within the group of high or low virulence isolates. 55 Nucleotide diversity (71) is defined as the average number of nucleotide differences per site between two sequences (Nei 1987, equations 10.5, 10.6 and 10.7). Not surprisingly, nearly all of the variation within the histone-H3 encoding gene occurs either within the introns, or at the third position of degenerate codons. Table 7 illustrates the relatively low nucleotide diversity of exons in comparison to introns. The average nucleotide diversity among nonsynonymous sites (7t a = 0.00122) is 100 times smaller than the average nucleotide diversity among synonymous sites (7t s = 0.12665). When both synonymous and noncoding sites are considered, the average nucleotide diversity is even greater (7^+ n = 0.15584). Table 7: Nucleotide Diversi ty (%) in the Gene Encoding H is tone -H3 among Fusarium species Gene Region Nucleotide Diversity Standard Deviation exon 1 0.07899 0.01329 intron 1 0 16279 0.01851 exon 2 0.02791 0.00328 intron 2 0 19121 0.02267 exon 3 0.03295 0.00340 Nucleotide diversity calculated as defined by Nei (1987). His tone -H3 RFLP Analysis of M e d f o r d and Bend Fusarium oxysporum Isolates One hundred and twenty-five Medford and Bend F. oxysporum isolates were examined at the histone-H3 locus using RFLPs. A total of 51 isolates were from Bend nursery, 25 from Ponderosa pine seedlings and 26 from soil. Seventy-four isolates were from Medford nursery, 28 from Ponderosa pine seedlings, 29 from Douglas fir seedlings, and 17 from soil. The histone-H3 RFLP data show that 92% of the isolates collected display a histone-H3 RFLP previously observed in F. oxysporum (Donaldson et al. 1995). The remaining 8% of the isolates may be Fusarium species other than F. oxysporum. For population genetic analyses, the total population was divided into tissue and soil subpopulations within each site population. Figure 26 shows the relative frequencies of histone-56 H3 RFLP haplotypes among tissue and soil isolates at Bend and Medford nurseries. A total of 6 histone-H3 haplotypes were found in F. oxysporum isolates surveyed using 4 restriction endonucleases. Haplotypes A through D (Figure 26) match previously described histone-H3 RFLPs (Donaldson et al. 1995). Haplotypes A, B, and C (Figure 26) account for nearly 93% of the isolates examined. Haplotype C was the most prevalent at both Bend and Medford nurseries. Figure 26 shows the distribution of histone-H3 haplotypes is similar between Bend tissue and soil subpopulations, but appears to differ between the Medford tissue and soil subpopulations. Figure 26: Histone-H3 RFLP Haplotype Frequencies among Tissue and Soil Isolates at Bend and Medford Nurseries 57 There is, however, no statistically significant difference between the Medford tissue and soil subpopulations in terms of the frequency of histone haplotypes. Confidence intervals (a = 0.05) indicate no difference in the frequency of histone haplotypes between tissue and soil subpopulations at either nursery site. Within the Medford tissue subpopulation there is also no significant difference in the frequency of histone haplotypes between Douglas-fir or Ponderosa pine hosts. Significant differences in histone haplotype frequencies are detectable between Medford and Bend nurseries (Figures 26, 27). Figure 27: Histone-H3 RFLP Haplotype Frequencies and Confidence Intervals (a = 0.05) at Bend and Medford Nurseries 1.2000 1.0000 0.8000 o c 3 0.6000 C r 0.4000 0.2000 0.0000 1 T I 1 1 . 4 * . • i B C D E Histone Haplotype I Bend I Medford Gene diversity at the histone-H3 locus was calculated for each site population and each soil and tissue subpopulation (Figure 28). Medford tissue isolates were collected from both 58 Douglas-fir and Ponderosa pine seedlings. Bend tissue isolates were collected only from Ponderosa pine. The overall gene diversity at the histone-H3 encoding locus, considering both tissue and soil isolates, is also shown in Figure 28. The histone-H3 RFLP data show that the Medford isolates have a much higher level of gene diversity than Bend isolates at the histone-H3 locus. Isolates from Bend tissue show much higher gene diversity at the histone-H3 locus than their soil counterparts. In contrast, there appears to be no significant difference in gene diversity between tissue and soil isolates in Medford. However, if the tissue isolates are further subdivided into those isolated from Ponderosa pine and those isolated from Douglas-fir, this changes. The Douglas-fir tissue subpopulation displays slightly lower gene diversity at the histone-H3 encoding locus than the Ponderosa pine and soil subpopulations at Medford. There is no significant difference between the Medford pine and soil isolates in gene diversity at the histone-H3 encoding locus. Figure 28: Gene Diversity Confidence Intervals (a = 0.01) in Medford and Bend Populations of Fusarium oxysporum based on Histone-H3 RFLP Data Overall Tissue Pine Fir Soil Origin Gene diversity calculated as defined by Nei (1973). 59 AFLP Analysis of Medford and Bend Fusarium oxysporum Isolates Two hundred-and-sixty-seven F. oxysporum isolates from Medford and Bend were examined for AFLPs using the N7 primer (Table 2). Of those 267 isolates, 159 were collected from Medford tissue, 36 from Medford soil, 39 from Bend tissue, and 33 from Bend soil. For the purpose of population genetic analyses, samples were divided into tissue and soil subpopulations within each site population. Average gene diversity and genotypic diversity were calculated for both site populations and each soil and tissue subpopulation (Table 8). Average gene diversity is often used synonymously with heterozygosity and is a measure of genie variation in a population. Average gene diversity, mathematically defined, is the probability that two randomly chosen genes are not identical (Nei 1973). The average gene diversity of the Medford population is nearly twice that of the Bend population. In this respect, the AFLP data agrees with the histone-H3 RFLP data. In contrast, there is no statistically significant difference in average gene diversity between soil and tissue isolates at either site. Table 8: Measures of Diversity in Medford and Bend Populations of Fusarium oxysporum based on AFLP Data (a = 0.01) Population Average Gene Diversity Genotypic Diversity Standardized Genotypic Diversity Medford 0.2567 1- 0 0326 19 0310.46 0 1007 ±0.0024 Medford tissue 0.2*14 + (10368 ly.27itu.59 0.1235 ±0.0038 Medford soil 0.2660 + 0.0801 12.00 ± 1.12 0.3333 ±0.0311 Bend 0.1327 + 0 0362 6 95 +. 0 30 0 0965 ± 0.0U54 Bend tissue 0.1396 ±0^0579 7.yo±0.77 0.2042 ±0.0198 Bend soil 0.1188 + 0.0507 5.21 + 0.49 0.1579 ±0.0149 Average gene diversity calculated as defined by Nei (1973). Genotypic diversity calculated as defined by Stoddart and Taylor (1988). Standardized genotypic diversity equivalent to genotypic diversity divided by sample size. Genotypic diversity is a measure of the quantity of unique genotypes in a population. In fungal population genetics, genotypic diversity has been used to assess the relative importance of sexual versus asexual reproduction (Milgroom et al. 1992; Peever and Milgroom 1994). Genotypic diversity values can vary from a minimum of one to a maximum of the population sample size. Genotypic diversity values were standardized to compare values from population 60 samples of different sizes. Dividing each genotypic diversity value by population sample size standardizes the value. Standardized genotypic diversity values are simply the proportion of possible genotypic diversity. Standardized genotypic diversity values show no statistically significant differences between Medford and Bend populations of F. oxysporum, but do show differences between tissue and soil subpopulations at each site (Table 8). Although the absolute values of genotypic diversity are greater in the tissue subpopulations at both Medford and Bend, the normalized values show that the Medford soil subpopulation has a higher level of genotypic diversity than the tissue subpopulation, but at Bend this relationship is reversed. The relatively ^ low values of standardized genotypic diversity in all subpopulations are consistent with the hypothesis that F. oxysporum undergoes little or no sexual reproduction. The mean total gene diversity (Hi), mean gene diversity between nursery populations (Hs), and mean subpopulation gene diversity of tissue and soil subpopulations within nursery sites (Hc) were used to calculate Nei's G e , and G„(Nei 1973; Yeh et al. 1997). Nei's Gx, in this hypothetical population structure is the proportion of total genetic variation due to differentiation between the Bend and Medford populations. Nei's Gcs is the proportion of total genetic variation due to differentiation between the soil and tissue subpopulations within each nursery site. Nei's Gcs and G.„, are analogous to Wright's Fsc and Fsl respectively (Wright 1951). Table 9 summarizes the Gs, values for each AFLP locus. Only one of the loci examined, N7-1000, was monomorphic. The low Gs, values indicate little differentiation of Medford and Bend nursery populations of F. oxysporum. Nevertheless, the confidence interval constructed for the multilocus G,, value indicates a significant degree of genetic differentiation between the Medford and Bend populations (Table 9). The confidence interval estimated for the multilocus Gc, value indicates there is no significant differentiation of the soil and tissue subpopulations within each nursery population (Table 9). The population structure analysis was also done using a fraction of 61 the total Medford tissue isolates to yield a similar sample size for tissue and soil isolates. Similar values of G.v, and Gc, were obtained in this analysis. Table 9: Mean Tota l Gene Diversi ty (HT), Mean Nursery Populat ion Gene Diversi ty (Hs), and Mean Subpopulat ion Gene Diversi ty (Hc) Used to Calculate Nei's Coefficients o f Gene Di f ferent ia t ion (Gcs, G,,) and corresponding Gene Flow Estimates (Nm) Locus Hf Hc Hs Gst Gcs NmfGJ* NmfGJ* N7-1300 0.2857 0.2565 0.2584 0.0953 0.0076 4.74 65.42 N7-1236 0.3054 0.2658 0.2705 0.1143 0.0175 3.87 28.05 N7-1000 0.0000 0.0000 0.0000 **** **** **** **** N7-823 0.0367 0.0364 0.0365 0.0047 0.0026 106.31 192.94 N7-763 0.2531 0.2358 0.2359 0.0679 0.0004 6.86 1221.62 N7-662 0.0355 0.0353 0.0354 0.0016 0.0052 321.26 95.68 N7-635 0.1551 0.1468 0.1512 0.0249 0.0293 19.58 16.54 N7-598 0.4269 0.3232 0.3257 0.2370 0.0077 1.60 64.59 N7-556 0.4181 0.3860 0.4021 0.0382 0.0402 12.60 11.93 N7-523 0.1686 0.1574 0.1659 0.0163 0.0514 30.26 9.22 N7-483 0.3775 0.3401 0.3537 0.0631 0.0384 7.42 12.51 N7-423 0.0711 0.0699 0.0710 0.0012 0.0150 407.56 32.87 N7-400 0.2408 0.2345 0.2371 0.0154 0.0108 32.03 45.74 N7-380 0.0675 0.0649 0.0651 0.0363 0.0027 - 13.29 181.65 N7-367 0.1563 0.1551 0.1559 0.0024 0.0048 209.72 102.83 N7-358 0.0094 0.0093 0.0093 0.0047 0.0095 105.00 52.00 N7-344 0.3340 0.3136 0.3171 0.0505 0.0112 9.39 44.33 N7-334 0.3875 0.3527 0.3601 0.0708 0.0203 6.55 24.09 N7-280 0.3143 0.2747 0.2755 0.1236 0.0026 3.54 190.20 N7-255 0.2427 0.2216 0.2234 0.0795 0.0079 5.79 62.63 Mean 0.2143 0.1940 0.1975 0.0784 0.0178 5.87 27.59 Std. Dev. 0.0203 0.0154 0.0162 +0.0264 ±0.0254 * Nm = estimate of gene flow from G,, or G„. E.g., Nm = 'A(\ - G.v;)/G,,, with n=267. Confidence intervals (a=0.05) for G„ and G, are shown in bold print. HT, Hc, Hs, G.„, and G„ calculated as defined by Nei (1973). Because of concerns that F. oxysporum is a species-complex, additional calculations of population differentiation were done using only histone haplotype C isolates. Histone-H3 RFLP haplotype C corresponds to at least one of the F. oxysporum type species (NRRL 22902) used by O'Donnell and coworkers (1997, 1998). The following histone-H3 RFLP haplotype C isolates were available: 24 isolates from Bend soil, 20 isolates from Bend tissue, 28 isolates from 62 Medford tissue, and 4 isolates from Medford soil. The small sample size of the Medford soil population in this case precluded a complete analysis. Values estimated for the coefficient of genetic differentiation between Bend and Medford populations (G.v, = 0.0356), and for the Bend tissue and soil subpopulations (G c, = 0.0384) were not significant. Average gene diversity values for the histone-H3 haplotype C group indicate no difference between the Medford (H= 0.1468 ± 0.0466) and Bend (H= 0.0878 ± 0.0386) populations or the tissue (H= 0.1023 ± 0.0675) and soil (H= 0.0694 ± 0.0494) subpopulations at Bend nursery at the 95% confidence level. The small sample sizes lead to relatively large confidence intervals, and the sample size of the Medford soil subpopulation in particular is too small to be useful. An alternative method of examining population structure was also employed. Excoffier and coworkers (1992) provide a technique similar to Nei's method of estimating population differentiation statistics. This method extends classical analysis of variance to calculate components of molecular variance at different hierarchical levels. The analysis of variance was performed on a matrix of squared molecular distances between individuals. The assumptions of classical analysis of variance hold here as well, and hence the hierarchical effects are assumed additive, random and independent. The analysis of molecular variance (AMOVA) method estimates population differentiation statistics based on the partitioning of variance within the hypothesized population structure. In contrast, Nei's measures of population differentiation are determined from the ratios of average subpopulation gene diversity to total gene diversity averaged over all subpopulations. The AMOVA method removes the need for nonlinear transformations of the original data, as well as many underlying assumptions with respect to the evolution of genetic markers (Excoffier et al. 1992). A nested analysis of molecular variance performed using AFLP data from Medford and Bend F. oxysporum isolates demonstrates that nearly 90% of molecular variance occurs within tissue or soil subpopulations (ac2). Approximately 9% of molecular variance can be attributed to 63 variance among nursery sites (cra2), and the remaining 1% of variance is attributed to variation among tissue and soil subpopulations within nurseries (o"i,2, Table 10). The partitioning of variance using AMOVA also allows the calculation of dp-statistics, analogous to Wright's F-statistics (Wright 1951; Weir and Cockerham 1984; Weir 1996). T a b l e 10: A n a l y s i s o f M o l e c u l a r V a r i a n c e i n M e d f o r d a n d B e n d P o p u l a t i o n s o f Fusarium oxysporum Variance Component Variance (% of total) Associated </>-Statistic P-value 0.238 (9.51%) <t>c,= 0.095 0.33515 0.027 ( 1.07%) <k= 0.012 0.07228 a c 2 2.240 (89.42%) dp,,= 0.106 <0.0001 Total variance in haplotypes is subdivided into three components: among nursery sites (a/); among tissue and soil subpopulations within nursery sites (ab2); and among individuals within soil or tissue subpopulations (ac2). P-value indicates the probability that a random value could be greater than or equal to the observed value of variance or <(> as determined by analysis of 10000 permutations. The statistical significance of variance components and their associated dp-statistics as estimated by permutation analysis is also shown in Table 10 (Excoffier et al. 1992). The P-values shown in Table 10 were calculated by constructing null distributions for each variance component and its associated dp-statistic. For rjc2 and dp.,.,, each individual was placed into a randomly chosen tissue/soil subpopulation. This process was repeated 10000 times to produce a null distribution. For o"t,2 and dp.vc, the null distribution was produced by permuting individuals within nursery populations without regard for tissue or soil subpopulation. For o a 2 and dpc.,, the null distribution was created by permuting whole tissue-soil subpopulations across nursery sites. Note that the molecular variance within tissue and soil subpopulations and dp.,, are highly significant. This indicates significant differentiation between the Medford and Bend populations of F. oxysporum. The dp.,., statistic can be used to estimate gene flow among populations, and is analogous to Nei's Gs, (Table 9) and Wright's Fxl. None of the other variance components or their associated dp-statistics is significant. The dp-statistics (dp.v, = 0.106; dp,c = 0.012) estimated by the AMOVA procedure are in good agreement with the Nei's differentiation statistics (G.v, = 0.0784; Gcs = 64 0.0178) calculated previously. Both pairs of statistics yield similar estimates of gene flow between nurseries (Nm (Gxl) = 5.9; Nm (<().„) = 4.2), and between subpopulations within nurseries (Nm (Gcs) = 27.6; Nm (<|>,c) = 41.2). Recall that Nm = '/2(1 - G„)/G,, where- <|>„ can be substituted for Gxt since both are measures of nursery population differentiation. Figure 29: Nu l l D is t r ibu t ion o f Genotypic Diversi ty Values in Relat ion to Observed Value in Fusarium oxysporum 30Cv Null Distribution of Genotypic Diversity 200k c O O 100r Observed Genotypic Diversity 0L I 0 . 2 5u •o o a-o T 3 CD 0.1 ro 0) 0 50 100 150 Genotypic Diversity '0.0 200 Genotypic diversity calculated as defined by Stoddart and Taylor (1988) using AFLP data for the total population of 267 isolates. Null distribution generated by permutation of binary data for all 267 isolates. Genotypic diversity was also calculated using the combined AFLP data from Bend and Medford populations. As a test for clonal structure, these data were then randomly permuted within loci, and values of genotypic diversity recalculated for each random permutation. This procedure is equivalent to assuming a random association among loci. The resulting distribution of genotypic diversity values in relation to the actual observed genotypic diversity is shown in Figure 29. The mean of the null distribution was 149, with a standard deviation of 11.7, and values ranging from a minimum of 112 to a maximum of 183. The observed value of genotypic 65 diversity among all 267 Oregon F. oxysporum isolates was 16.6, considerably outside the null distribution. The deviation of the observed genotypic diversity far outside the null distribution of genotypic diversity values may be interpreted as evidence for a clonal population structure. Linkage disequilibrium is expected given the previous evidence for clonal population structure. Linkage disequilibrium is defined as a state of nonrandom association between alleles of different genes (Hartl and Clark 1989). Arlequin version 1.1 (Schneider et al. 1997) was used to perform exact tests of pairwise linkage disequilibrium (Raymond and Rousset 1995) with a Markov chain length of 100000 and 1000 dememorization steps. Markov chains are essentially a shortcut for estimating exact probabilities on large data sets. The Arlequin program uses Markov chains to provide unbiased estimates of exact probabilities without the computational burden of performing Fisher's exact test for R x C contingency tables. As Raymond and Rousset (1995) note, even the most sophisticated statistical software which allows Fisher's exact test on R x C contingency tables cannot handle data sets typical of population studies. Table 11 : Pairwise L inkage Disequi l ibr ia among N7-AFLP Loci in Fusarium oxysporum f r o m Bend Soil and Tissue (P< 0.05) Locus 1 2 4 5 6 7 8 9 10 11 12 13 15 17 18 19 20 1 * + - - NP - + - - - - - - + + + + 2 + * - - NP - + - - - - - - + + + + 4 - - * - NP + 5 + + - * NP - + 6 - - + - * NP NP NP NP NP NP NP NP NP NP NP NP 7 * 8 + + - + - - * - - + - - - + + + + 9 * 10 - - - - + - - + * - - + - - - - -11 - - + - + - + - - * - - - - - - -12 NP NP NP NP NP NP NP NP NP NP * - - - - - -13 + + - + - - + - - - NP * - - - - -15 - - - - - - - - - - NP - - - - -17 + + - + - - + - - - NP + - * + + + 18 + + + + + - + - - - NP + - + * + + 19 + + - + - - + - - - NP + - + + * + 20 + + - + - + - - - - NP + - - + + * Notes: Bend soil is above the diagonal; Bend tissue is below the diagonal. A '+' indicates linkage disequilibrium between two markers (P < 0.05). A'-' indicates no significant linkage disequilibrium between two markers. NP indicates the pair of loci was not polymorphic. Any loci not included in the table were not polymorphic. 66 The results of exact tests for pairwise linkage disequilibria show significant (P < 0.05) linkage disequilibria in 25 of 120 pairwise comparisons (21%) in the Bend soil population. The Bend tissue population shows significant linkage disequilibria in 43 of 120 possible comparisons (36%). The Bend soil and tissue subpopulations share a similar pattern of linkage disequilibria, with 18 associations between AFLP markers common to both subpopulations (Table 11). Linkage disequilibria are also evident in the Medford subpopulations (Table 12). In the Medford soil population 37 of 136 possible comparisons (27%) indicate linkage disequilibria. In the Medford tissue population, 68 of 171 (40%) comparisons also indicate linkage disequilibria. Twenty-one of the comparisons where significant linkage disequilibria were detected are common to both tissue and soil subpopulations. Table 12: Pairwise L inkage Disequi l ibr ia among N7-AFLP Loci in Fusarium oxysporum f r o m M e d f o r d Soil and Tissue (P< 0.05) Locus 1 2 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 1 * + NP + + - - - - - - - NP + + + + 2 + * NP + - - + - - - - - - - NP + + + + 4 - + * NP NP NP NP NP NP NP NP NP NP NP NP NP NP NP NP 5 + + - * - - + - - - - - - - NP + + + + 6 - - - + * + NP 7 - - - - + * + - + - - - - - NP - - - -8 + + - + - - * - - + - - - - NP + + + + 9 + + + - - + * - + - - + - NP - - - -10 - - - - - + - - * - - - - - NP - - - -11 + + - + - + - - - * - - + - NP - - - -12 - - - - - + - - - - * - - . + NP - - - -13 + + - + - - + - - - - * - - NP - - + -14 - - - + + - - - - + + - * - NP - - - -15 + + - - - - + - - - - - + * NP - - - -16 - - - + - - - - - - - - + + * NP NP NP NP 17 + + - + - - + + - + - + - - - * + + + 18 + + - + - - + + - + - + - - - + * + + 19 + + - + - - + + - + - + - + - + + * + 20 + + - + - - + + - + + + + * Notes: Medford soil is above the diagonal; Medford tissue is below the diagonal. A '+' indicates linkage disequilibrium between two markers (P < 0.05). A'-' indicates no significant linkage disequilibrium between two markers. NP indicates the pair of loci was not polymorphic. Any loci not included in the table were not polymorphic. Another measure of linkage disequilibrium can be applied to populations as a whole, without the need for pairwise comparisons between loci. Brown and others (1980, 1981) have 67 proposed an index of association QA) which describes the degree of multilocus associations within a population as a function of the ratio of observed variance to expected variance in the number of different loci in two randomly chosen individuals. This makes comparing different populations more convenient, and mitigates potential problems of sample size (Brown 1975). Table 13 shows the calculated index of association for each subpopulation of F. oxysporum in this study. If alleles at different loci are independent, the index of association should be close to zero. Values greater than one indicate that the variance in heterozygous loci due to multilocus associations is more than double that due to polymorphism. Recall that k is the number of heterozygous loci observed in two haploid individuals, randomly chosen from the population. Table 13: Brown 's Mul t i locus Index of Association in Oregon Tissue and Soil Subpopulat ions of Fusarium oxysporum Based on A F L P Data Population Expected Variance cr£ Observed Variance s\ Index of Association IA Bend soil 1.85 ± 0.91 6.58 2.56 Bend tissue 2.03 + 0.90 6.62 2.26 Medford soil 3.24 + 1.46 12.47 2.85 Medford tissue 3.15 + 0.68 10.11 2.21 Index of association calculated as defined by Brown et al. (1980). The variable k is the number of heterzygous loci observed in two individuals randomly chosen from the population. In a randomly mating population, the index of association is expected to be zero. In all cases, the observed variance of k(sl) is well outside the 95% confidence interval for the expected variance of k (cr£) calculated under the assumption that allelic associations among loci are independent. This indicates significant deviation from the null hypothesis that allelic associations among loci are independent, and suggests that all of the subpopulations are clonal in nature, and recombination events are relatively infrequent. 68 Chapter 4: Discussion Bl ind Test Ident i f icat ion of Fusarium species The blind test procedure proved to be quite reliable, with nearly 90% accuracy in identifying Fusarium species. This demonstrates that the diagnostic as outlined in Figure 2, can identify F. oxysporum, F. avenaceum, F. acuminatum, F. proliferatum, and F. moniliforme isolates to the species level with reasonable accuracy. The accuracy of the diagnostic is likely to improve with user experience. An individual with considerable experience in Fusarium identification could easily outperform this diagnostic in terms of speed. However, the diagnostic is capable of differentiating at least five subgroups of F. oxysporum which appear to correspond with unique phylogenetic species within the F. oxysporum complex (O'Donnell and Cigelnik 1997; O'Donnell etal. 1998). Although it is clear that F. redolens (syn. F. oxysporum var. redolens) can be distinguished from F. oxysporum by morphological characters (Guadet et al. 1989; O'Donnell et al. 1998), differentiation of other species within the F. oxysporum complex may not be possible using morphology alone. Scoring Er ro rs , A F L P Reproducib i l i ty and Selection of a Genetic Distance Measure With respect to scoring errors, considerable difficulty arises in deciding exactly what constitutes a band with both RAPD and AFLP markers. Some workers have reported a relationship between error rate and relative amplification strength of a RAPD band (Weeden et al. 1992). Given the similarity of RAPD and AFLP markers, this suggests that only very strong amplification products should be used as markers for population studies. This was not done for two reasons. First, other workers have found no such relationship (Skroch and Nienhuis 1995b). More importantly, although sampling variance is inversely proportional to the number of markers scored, the variance of scoring error is independent of the number of markers scored (Skroch and 69 Nienhuis 1995b). Hence, using all of the available markers, even weakly amplified bands, is likely to give better estimates of population parameters despite scoring errors. The possibility of heterologous DNA fragments co-migrating does exist, although RAPD analysis of at least two plant genomes has shown this phenomenon occurs infrequently (Grattapaglia and Sederoff 1994). The second reason that all available markers were scored was the reproducibility of AFLP markers. Amplified fragment length polymorphisms are highly reproducible even under a relatively broad range of polymerase chain reaction parameters. Both RAPDs and AFLPs are commonly used for genetic screening, which often requires DNA extraction from a large number of samples. In order for many samples to be quickly processed, DNA extraction procedures are often relatively crude, making accurate DNA quantification difficult. The concentration of template DNA is perhaps the most difficult parameter to control when performing PCRs, and varying the template DNA concentration can lead to PCR artifacts with RAPDs. Broad ranges of template DNA, over at least two orders of magnitude,can be used in AFLP-PCRs without any effect on the banding pattern (Lin and Kuo 1995). The Dice distance measure was selected to construct distance matrices for three reasons. First, Lamboy (1994a, b) has shown that the Dice metric is relatively insensitive to scoring errors when compared to other commonly used metrics. Lamboy (1994a) also notes that only the Dice similarity coefficient has direct biological meaning. The Dice similarity coefficient is an estimate of the expected proportion of amplified fragments common to two isolates because they were inherited from a common ancestor. Second, analysis of the high and low virulence isolate data showed no differences in the structure of the neighbour-joining tree constructed using Dice, Jaccard, Excoffier, or Sokal and Sneath similarity coefficients. Third, analysis of the pairwise distance values produced by the Dice distance measure gave the best approximation to a normal distribution (Figure 12). Many statistical analyses require a normal distribution in order to be valid. Although an approximate normal distribution is not an absolute requirement for methods such as multidimensional scaling, it undoubtedly enhances the solution (Wilkinson et al. 1996). 70 P a t h o g e n i c i t y T e s t i n g Nearly 70% of the isolates assayed showed significantly more disease on Douglas-fir seedlings than the negative controls. As defined by pathogenicity testing, approximately 70% of the F. oxysporum isolates examined were pathogens. This is undoubtedly an underestimate since the statistical power of the pathogenicity testing procedure was rather limited. In some instances, even isolates that left only 60% of the seedlings healthy were not statistically different from the uninoculated water control (Appendix C). No relationship between the pathogenicity phenotype (i.e. root disease, needle disease, or damping-off) and AFLP or RFLP haplotype was observed. Approximately 70% of the isolates tested for pathogenicity were isolated from soil, and the remaining 30% were isolated from conifer tissue. Other workers have found nonpathogenic F. oxysporum to be abundant in soil. Appel and Gordon (1994) reported that approximately 40% of soil isolates from agricultural fields were nonpathogenic. The results reported here are similar, with 41 of 83 soil isolates (50%) showing no difference in comparison to negative controls. Thirty-three of 35 tissue isolates (94%) showed significant pathogenic ability. Other workers have shown that most isolates of F. oxysporum are avirulent on the plant from which they were isolated (Hendrix and Nielsen 1958; Katan 1971). Other work has focused on formae speciales that cause specific diseases, whereas in bare-root nurseries F. oxysporum causes awide variety of diseases. The complex of diseases appears to be general and comparatively nonspecific. This observation is supported by the fact that newly emerged or emerging seedlings are vulnerable to a variety of pathogens, many of which are capable of causing virtually identical disease symptoms. For example, several species of fungi commonly cause damping-off, including Pythium, Phytophthora and Rhizoctonia. Other less common causes of damping-off can include fungi in the genera Cercospora, Septoria, Mycosphaerella, Glomerella, Colletotrichum, Helminthsporium, Alternaria and Botrytis, as well as bacteria such as Xanthomonas and Pseudomonas (Agrios 1988). The general nature of the 71 disease-complex caused by F. oxysporum undoubtedly complicates the genetic differentiation of pathogens from nonpathogens. Dendrogram Construction Several simulation studies using DNA sequence data (Li et al. 1987; Sourdis and Nei 1988; Jin and Nei 1990; Kuhner and Felsenstein 1994) have indicated the neighbour-joining method is generally more accurate than the maximum-parsimony method, except when the number of nucleotide differences per site is small, and a large number of nucleotides are examined. Simulation studies have also demonstrated that, using sequence data, the neighbour-joining method performs nearly as well as maximum likelihood, but without the associated computational burden (Saitou and Imanishi 1989; Kuhner and Felsenstein 1994; Tateno et al. 1994). In addition, the neighbour-joining method has also been shown to be much more accurate at recovering the true phylogenetic tree than the widely used UPGMA method using either sequence or restriction site data (Saitou and Nei 1987; Hillis et al. 1994). Hillis and coworkers (1994) have also shown that the relative efficiencies of different methods in recovering the true phylogenetic tree depend on the type of data used. Furthermore, simulation studies performed by Hillis and coworkers (1994) have indicated that the neighbour-joining method outperforms parsimony methods, UPGMA, and maximum likelihood methods when restriction site data is used. This is of particular interest, since most of the data analyzed in this work is based on AFLPs and RFLPs. The presence or absence of restriction fragments is not the same as restriction site data, because restriction fragments do not evolve independently, and insertions or deletions can affect the restriction patterns of several enzymes all at once (Nei and Li 1979; Hillis et al. 1994). However, the presence or absence of specific fragments derived from AFLP analysis present a unique case. The loss of a specific fragment due to insertion, deletion, or point mutation is unlikely to cause any changes in other restriction fragments that can be amplified. In this 72 instance, it seems reasonable to assume that the fragments evolve independently, and regard such data as functionally equivalent to restriction site data. A F L P and R F L P Analysis of H igh and L o w Virulence Fusarium oxysporum Isolates Neighbour-joining trees constructed using both the AFLP and RFLP data show the same 3 major groups. These groups correspond to the histone-H3 haplotype. If F. oxysporum is in fact a species-complex (O'Donnell and Cigelnik 1997; O'Donnell et al. 1998), each histone-H3 haplotype may represent a phylogenetic species. The fact that the two independent data sets show the same basic dendrogram structure suggests thatF. oxysporum, as found in bare-root conifer nurseries, is a species-complex. Table 14 illustrates the associations between histone-H3 haplotype and phylogenetic species. Haplotypes A, C and D correspond to an as yet unnamed Fusarium species (BCRI P4C2P17A = NRRL 22900; BCRI 3139 = NRRL 22903), F. oxysporum (BCRI 90651 = NRRL 22902) and F. redolens (BCRI F30 = NRRL 22901), respectively as denoted by O'Donnell and associates (1998). Histone-H3 haplotypes B, E and F may correspond to the remaining phylogenetic species within the F. oxysporum complex (O'Donnell et al. 1998): F. nisikadoi (NRRL 25179), F. inflexum (NRRL 20433) and another unnamed Fusarium species (NRRL 25184), but this has not been confirmed. Table 14: Associations between Histone-H3 Haplotypes and Phylogenetic Species Histone-H3 Haplotype Phylogenetic Species (O'Donnell et al. 1998) A Fusarium sp. (NRRL 22900, 22903) B unknown C Fusarium oxysporum (NRRL 22902) D Fusarium redolens (NRRL 22901) E unknown F unknown None of the targets examined for RFLPs differentiated the high and low virulence groups. The histone-H3 and p-tubulin encoding genes showed relatively little polymorphism. This is 73 expected since both are highly conserved genes under considerable functional constraints. The noncoding IGS region of ribosomal DNA is presumably under less selection pressure than the DNA regions coding for essential proteins such as histone-H3 and p-tubulin, and this may partially explain the relatively high level of polymorphism. Appel and Gordon (1995) also observed a high level of haplotypic diversity in the IGS region of Fusarium oxysporum isolates, and suggested that homogenization of the rDNA tandem repeats occurs within individuals, through mitotic gene conversion and/or mitotic translocations, but that homogenization is not occurring at the population level. In species with infrequent or no sexual reproduction, a high level of haplotypic diversity is expected in the IGS region. Three-hundred-and-nineteen AFLP markers derived from 9 different primers were used to characterize the 24 high and low virulence isolates. The neighbour-joining tree (Figure 20) constructing using these data shows clean separation of high and low virulence isolates only within the group C isolates. The extra dimension offered by principal component analysis shows a more favourable solution (Figure 23) with grouping of high and low virulence jsolates within each histone haplotype group. The advantages of principal component analysis are twofold. First, PCA can be done directly on raw binary data without requiring the construction of a distance matrix. The fact that the raw data are not transformed and condensed into a distance matrix intuitively seems to allow more information to be retained. Second, both PCA and MDS can be done in multiple dimensions, which in some cases may provide better resolution than cluster analysis. Although these results look promising, it should be noted that the sample size of each haplotype group is too small to draw any absolute conclusions. For the purposes of a DNA diagnostic, screening isolates for a large number of molecular markers would be impractical. Some AFLP markers correlate well with the virulence phenotype in the tested isolates, but the sample size of 24 is far too small to attribute any statistical significance to these observations. Further testing with larger sample sizes could determine if a small number of AFLP markers would allow the separation of high and low virulence isolates within a histone haplotype group. 74 Sequence Analysis of Histone-H3 Encoding Gene from Fusarium oxysporum Isolates Available DNA sequence data from the histone-H3 encoding gene also show three groups within the high and low virulence isolates, with very high bootstrap support (Figure 24). Additional isolates of other Fusarium species were also sequenced, and the resulting neighbour-joining tree (Figure 25) shows relatively large intraspecific distances among the groups of F. oxysporum when compared to interspecific distances. This also suggests that F. oxysporum is a species-complex. Examination of the sequence data revealed two introns present in all of the Fusarium species sequenced. Nucleotide diversity varied greatly between coding and noncoding regions (Table 7). Since the substitution rate at different sites within the histone-H3 encoding gene varies considerably, a gamma distribution of substitution rates was assumed. Such variation is expected because the gene contains highly conserved regions with expectedly low substitution rates, and introns presumably with much higher substitution rates. Nei and Gojobori (1986) have found that the gamma distribution makes nucleotide substitutions nearly additive when the rate varies considerably among sites. This has been shown to greatly improve the reliability of neighbour-joining trees generated from sequence data (Jin and Nei 1990). Histone-H3 RFLP Analysis of Medford and Bend Fusarium oxysporum Isolates An examination of 125 isolates for RFLPs within the histone-H3 encoding gene confirms the utility of the DNA diagnostic procedure for identifying F. oxysporum: Al l of the F. oxysporum isolates examined displayed a total of only six histone-H3 haplotypes. In addition, the RFLP data may provide insights into the population structure of F. oxysporum at the Bend and Medford nursery sites. The frequency of specific haplotypes does not differ significantly between the tissue and soil subpopulations at either nursery (Figure 26). Within the Medford tissue isolates no significant difference in haplotype frequency was detected between isolates isolated from Douglas-fir and those isolated from Ponderosa pine. Significant differences in histone-H3 haplotype frequencies between the Medford and Bend populations are present (Figure 27). 75 Similarly, comparison of the two nursery populations indicates a difference between Medford and Bend populations in gene diversity at the histone-H3 encoding locus. This may be explained by the fact that Bend nursery grows primarily Ponderosa pine seedlings while the Medford nursery grows a variety of conifer species. The broader range of hosts available at Medford nursery may explain why the histone-H3 gene diversity at Medford is much higher than the gene diversity observed at Bend. Differences in climate and cultural practices at each nursery may also be a factor in histone-H3 gene diversity differences between the two sites. The climates of the two nursery sites differ noticeably, with Bend being relatively dry and often windy. With respect to cultural practices, each nursery generally uses different cover crops. Fumigation with a mixture of methyl bromide and chloropicrin is routine at Medford, while Bend nursery uses Dazomet regularly and a mixture of methyl bromide and chloropicrin only occasionally. The two nurseries also differ in age a great deal. Bend nursery was opened in 1948, and Medford nursery was opened in 1978. Both nurseries are surrounded by rural land (March 1999 e-mail correspondence with D. Hildebrand; unreferenced). A more perplexing issue is the contrast between the tissue and soil subpopulations at each nursery site. At the histone-H3 encoding locus the soil subpopulation of Bend has lower gene diversity than the tissue subpopulation, but the Medford soil subpopulation shows an intermediate level of gene diversity between the Douglas-fir and Ponderosa pine subpopulations. A number of explanations may be considered. Soil at the Bend nursery may be more suppressive than soil at Medford, and certain genotypes may be favored by selection. Another possibility is that any differences between tissue and soil with respect to gene diversity are artifacts of a species-complex in which some species are more adapted to tissue and others to soil. If this is the case, one might expect to find differences among subpopulations with respect to the frequency of histone-H3 haplotypes. Although no differences were detected, once the total sample is subdivided, the sample size of each subpopulation is relatively small. In any case, it is important to note that the gene encoding histone-H3 is only a single locus, and that this locus is under 76 selection. Selective forces may be different not only between nursery sites, but also between tissue and soil. A F L P Analysis of M e d f o r d and Bend Fusarium oxysporum Isolates Since only a single primer was used to characterize the Medford and Bend populations of F. oxysporum, some concerns may arise over the independence of loci sampled in this analysis. The same issue has been addressed with the use of RAPDs in population studies. Work by Skroch and Nienhuis (1995a) has shown that the independence of RAPD markers amplified using the same primer is equivalent to that of RAPD markers amplified using different primers. Given the similarity of the two methods, this seems likely to hold for AFLP markers as well. Both AFLP and RFLP data show a higher level of diversity in the Medford population. Although histone-H3 RFLP data show significant differences among tissue and soil subpopulations at both nurseries, the AFLP data show none. The difference between the histone-H3 RFLP and AFLP data may be attributable to the differences between the markers used. The gene diversity calculated from the histone-H3 encoding gene is derived from a single molecular marker that may be biased by the fact that each histone haplotype may represent a unique phylogenetic species. In contrast the AFLP data allowed an average gene diversity value to be calculated over twenty loci. The neutral theory of molecular evolution asserts that most of the polymorphisms observed at the molecular level are selectively neutral and have little or no effect on the survival and reproductive capability of an organism (Kimura 1983). If one subscribes to the neutral theory of molecular evolution, one can assume that the majority of AFLP markers are selectively neutral. In contrast, as one of the most highly conserved genes known, the histone-H3 locus is clearly under considerable selective constraint (Haiti and Clark 1989). The question arises, why should the Medford and Bend populations show a difference in average gene diversity, but no difference in standardized genotypic diversity? In a sexually reproducing organism, one would expect to see a higher genotypic diversity associated with 77 higher average gene diversity, but this is not the case for an organism that propagates asexually. In fact the ratio of these two diversity measures may be useful in estimating the relative importance of sexual versus asexual reproduction in other organisms. Furthermore, if the average gene diversity is estimated using only AFLP data from histone haplotype-C isolates, no significant difference is detected between the nursery sites. Another question concerns the genotypic diversity values of tissue and soil subpopulations at each nursery. The Medford soil subpopulation has a higher standardized genotypic diversity than the tissue subpopulation, but at Bend this relationship is reversed. This may be explained by the different composition of the populations within each site. Histone-H3 RFLP haplotypes appear to correspond to unique phylogenetic species within the F. oxysporum complex (Table 14) as defined by O'Donnell and others (1998). Hence, the differences in genotypic diversity may reflect differences in which phylogenetic species, within the F. oxysporum complex, are present in different subpopulations. It is also worth mentioning that as Stoddart and Taylor (1988) note, the estimate of genotypic diversity is biased and always underestimates the true genotypic diversity. The magnitude of this bias increases greatly when the sample size is small relative to the number of genotypes, since some genotypes would not be observed. The low level of differentiation (Gst= 0.078), as calculated from AFLP data, between the Medford and Bend populations of F. oxysporum is of particular interest. Many fungal populations have shown low levels of genetic differentiation (Leung and Williams 1986; Ennos and Swales 1991; McDermott et al. 1992; Boeger et al. 1993). Work by Gordon and coworkers (1992) has shown that while F. oxysporum population structure exists on a scale of tens of metres in native soil, no such structure is present in cultivated soil. The authors calculated a Gst value of 0.015 and determined that the proportion of mitochondrial DNA haplotype diversity attributable to population differentiation between native and cultivated soil was not significant. As these authors noted, the cultivation practices in most agricultural fields may result in sufficient mixing to greatly reduce or remove any small-scale population subdivision in soilborne fungi. Therefore, 78 for the purposes of this study, the total population was divided into nursery populations, which were further subdivided into tissue and soil subpopulations. In an asexually reproducing fungus one would expect mutation to cause the two nursery populations to diverge. Appel and Gordon (1994) compared populations of F. oxysporum f. sp. melonis from fields in California and Maryland and found highly differentiated populations. Other studies (Gordon and Okamoto 1992; Gordon et al. 1992) suggest that distance isolation has an important effect on population structure. Given that F. oxysporum has traditionally been thought of as a soilborne pathogen and since the sites are separated by the Cascade mountain range, the low level of differentiation between the Medford and Bend populations suggests that other forces are countering population differentiation. The use of common seed sources at both nurseries, movement of nursery material between nursery sites, or long-range dispersal of spores may facilitate the movement of enough spores to prevent divergence of the populations. Nursery populations probably move through cycles of near extinction and recolonization brought about by fumigation and other control measures. Recolonization of nursery sites from Fusarium on seed or seedlings brought into nurseries could explain the low level of differentiation between the Medford and Bend populations. The movement of only one individual per generation (i.e. Nm = 1) is sufficient to prevent significant differentiation of populations. The fact that Gordon and associates (1992) have found population subdivision in native soil on the scale of metres indicates long-range spore dispersal would not be sufficient to keep the Medford and Bend populations from differentiating. It is not clear if the population structure these authors observed in native soil could have been an artifact caused by the F. oxysporum species-complex. It is worth noting that soilborne Fusarium can be dispersed in air; a fact that is often overlooked (Burgess 1981). Fusarium oxysporum has been isolated from the atmosphere, and is likely dispersed by airborne soil or organic debris (Burgess 1981). On a small scale, Rowe et al. (1977) have shown that airborne microconidia of F. oxysporum f. sp. radicis-lycopersici are likely to have caused the recolonization of steamed soils in greenhouses. Recent work by Katan and coworkers (1997) provides evidence that aerial 79 dissemination of Fusarium oxysporum f. sp. lycopersici is an important part of pathogen dispersal. The authors noted thatF. oxysporum f. sp. lycopersici can form conidia on the surfaces of diseased tomato stems which can become airborne. In conifer nursery environments, several Fusarium species, including F. oxysporum, have been isolated from the atmosphere (Axelrood et al. 1993). Formation of conidia on the surfaces of diseased conifer seedlings was common during pathogenicity testing in this study (Figure 14). Other forces minimizing the genetic differentiation of the two populations could include selection. This seems unlikely since the two sites are very different with respect to available hosts. Furthermore, most AFLP markers are expected to be selectively neutral (Kimura 1983), and an accumulation of mutations and differences in selection are expected to cause the two populations to diverge. Alternatively, the lack of population differentiation may be due to past gene flow (Peever and Milgroom 1994; Slatkin 1985, 1987) or relatively recent introductions from a single source. Another complicating issue is the nature of F. oxysporum itself. Fusarium oxysporum sensu Snyder and Hansen, does appear to be a species-complex as suggested by O'Donnell and associates (1997, 1998). As previously noted, nearly 93% of the isolates sampled displayed H3 RFLP haplotype A, B, or C. The histone-H3 RFLP haplotype C was the most prevalent, accounting for 90% of the screened isolates from Bend and 45% of the isolates from Medford. Histone-H3 RFLP haplotype C corresponds to O'Donnell's (1997, 1998) F. oxysporum type isolate (NRRL 22902). Analysis of histone haplotype C isolates shows no significant differentiation between the Medford and Bend populations or the tissue and soil subpopulations within each site. A considerable degree of linkage disequilibrium was observed among many of the AFLP markers used to characterize the Medford and Bend populations of F. oxysporum. The observed linkage disequilibria may be caused by close physical proximity of genetic markers, selection favouring certain heterozygous genotypes, admixture of populations with differing gametic frequencies, or a clonal population structure. Although the close physical proximity of AFLP 80 markers cannot be ruled out, it is unlikely that such a high proportion of the markers would be linked by chance. Selection may be acting on some of the AFLP markers, but under the neutral theory of molecular evolution, most are expected to be selectively neutral. Population admixture may be a contributing factor, especially considering the possibility of a F. oxysporum species-complex. The high degree of linkage disequilibrium among AFLP markers is also consistent with a clonal population structure. 81 Chapter 5: Conclusion The development of any reliable DNA diagnostic procedure requires an intimate knowledge of the population genetic structure of the organism in question. If a species consists of highly differentiated subpopulations, the use a DNA diagnostic will likely be compromised. This is not the case with Fusarium oxysporum populations from coniferous hosts. Al l of the available data suggest that F. oxysporum is an asexual organism. Without the frequent recombination offered by sexual reproduction, subpopulations of the species diverge largely by mutation and selection. This makes F. oxysporum an excellent target for the use of a molecular diagnostic. Blind test results demonstrate that F. oxysporum can be differentiated from other Fusarium species with reasonable accuracy. Ideally, the diagnostic assay could be performed on total DNA extracts directly from plant tissue. This will require primers specific to the histone-H3 encoding gene in Fusarium and individual species within the genus. Direct PCR from infected plant tissue has been successful with a number of plant pathogens including Fusarium pathogens of rye and wheat (Schilling et al. 1996), Pythium (Levesque et al. 1994), Colletotrichum (Mills et al. 1992), Leptosphaeria (O'Gorman et al. 1994), Verticillium (Robb et al. 1994), Ophiosphaerella (Tisserat et al. 1994), and Cylindrocarpon (Hamelin et al. 1996). The more detailed analysis of a small group of isolates selected for a high or low virulence suggests that it may be possible to separate these two phenotypes using DNA-based methods. This will, however, require extensive sampling of each subpopulation within the F. oxysporum complex with a large number of genetic markers. The apparently clonal mode of reproduction within bare-root conifer nurseries suggests that there are relatively few genetic differences between high and low virulence isolates. Restriction fragment length polymorphisms in the histone-H3, p-tubulin and IGS regions consistently separate high and low virulence isolates into three categories. Amplified fragment length polymorphisms derived from nine primers duplicate these three categories almost exactly. The fact that this separation occurs independently 82 in all of the data sets as well as in a highly conserved locus, such as that encoding histone-H3, suggests that F. oxysporum, sensu Snyder and Hansen, is a species-complex as proposed by O'Donnell and coworkers (1997, 1998). The species-complex issue impairs the differentiation of high and low virulence isolates considerably. The first notable problem when examining a small number isolates for genotypic and phenotypic characters, is the decrease in effective sample size. Originally it was believed that 12 high virulence and 12 low virulence isolates of F. oxysporum had been selected for a detailed examination using RFLPs and AFLPs. If the original sample is actually three species, then effective sample size for each is approximately one-third, assuming equal representation of all three subgroups. This leaves far too few isolates to make any firm conclusions with respect to the differentiation of high and low virulence isolates. It is interesting to note, however, that in the case of principal component analysis or multidimensional scaling, there appears to be a weak association among isolates with the same virulence phenotype within each subgroup. Of course for a routine diagnostic capable of differentiating pathogens and nonpathogens or high and low virulence isolates, much more data would need to be screened to find a convenient number of markers associated with the virulence phenotype. Any such AFLP markers could be sequenced and examined in more detail, possibly leading to the development of specific PCR primers to differentiate the virulence phenotypes. The effects of a species-complex on population genetic parameters are less obvious, but given this likelihood, they should be interpreted with caution. In both the Medford and Bend populations, histone-H3 haplotype C predominates. Ninety percent of the Bend isolates sampled are from histone-H3 haplotype C. Forty-five percent of the Medford isolates sampled also displayed histone-H3 haplotype C. If the sampled population is in fact a species-complex, one may ask which histone group represents F. oxysporum. In other words, is histone haplotype C really F. oxysporum? Available evidence suggests this is the case. At least one of the Fusarium oxysporum type isolates examined by O'Donnell and coworkers (1998), NRRL 22902, displays 83 the group C histone haplotype. Hence, at the very least, the majority of the data are from the phylogenetic species F. oxysporum as defined by O'Donnell and associates (1998). Average gene diversity values estimated from AFLP data show significant differences between the Medford and Bend populations, but no differences between tissue and soil subpopulations within each nursery. Additional estimates of gene diversity using only the histone haplotype C isolates for which AFLP data were also available show no difference between the Medford and Bend populations. This suggests that differences in gene diversity calculated using the total data might have been skewed by the different elements of the F. oxysporum species-complex at each nursery. With respect to population structure, no significant genetic differentiation can be attributed to population structure within either nursery population. Significant differentiation was found between the Medford and Bend populations, but at an unexpectedly low level. If one assumes F. oxysporum is a species-complex in this case and estimates Gst using only the histone haplotype C isolates in the available AFLP data, the level of genetic variability between the two nurseries attributable to population differentiation becomes insignificant. In either case, the conclusion, that F. oxysporum is being introduced at both nursery sites from the same source or that contaminated material moves between nurseries, remains the same. The Bend nursery is no longer in production and now serves as a processing center for conifer cones. Seed is moved between the two nurseries, and both nurseries have probably grown the same seedlots at different times. Seedlings may have rarely moved between the two nurseries (March 1999 e-mail correspondence with D. Hildebrand; unreferenced). 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J Mol Evol 34:259-271. 99 Appendix A : Bend and M e d f o r d Fusarium oxysporum isolates and N7-AFLP Haplotype I D Code Isolate Host Nursery Haplotype N7 B inary Haplotype BS36 BPx-P2-942 soil Bend Pine A 0Q100010110101000100 BS4 BPx-4-941 soil Bend Pine A K 00101011011001000100 BS5 BP-12-942 soil Bend Pine A K 00101011011001000100 BS7 BPx-18-941 soil Bend Pine A K 00101011011001000100 BS9 BPx-9-941 soil Bend Pine A K 00101011011001000100 BS14 BPB936 soil Bend Pine A K 00101011011001000100 BS15 BP938 soil Bend Pine A K 00101011011001000100 BS28 BPF-935 soil Bend Pine A K 00101011011001000100 BS30 BP-5D-937 soil Bend Pine A K 00101011011001000100 BS34 BPx-4-942 soil Bend Pine A K 00101011011001000100 BS43 BP-15-931B soil Bend Pine A K 00101011011001000100 BS13 BPx-28-941 soil Bend Pine AO 00101011011011000100 BS16 BPF936 soil Bend Pine AP 00101011011011100100 BS39 BP-3-932B soil Bend Pine AQ 00101011101001000100 BS42 BP-14-931B soil Bend Pine AR 00101011101011100100 BS1 BPx-5-942 soil Bend Pine A Y 00101011111001000100 BS2 BPx-1-941 soil Bend Pine A Y 00101011111001000100 BS11 BPx-6-942 soil Bend Pine A Y 00101011111001000100 BS12 BP-17-941 soil Bend Pine A Y 00101011111001000100 BS22 BP-MB-932 soil Bend Pine A Y 00101011111001000100 BS23 BPF-932 soil Bend Pine A Y 00101011111001000100 BS24 BPB-935 soil Bend Pine A Y 00101011111001000100 BS25 BPB-931 soil Bend Pine A Y 00101011111001000100 BS26 BP-5D-931 soil Bend Pine A Y 00101011111001000100 BS33 BPB-932 soil Bend Pine BA 00101011111001100100 BS38 BP-18-931B soil Bend Pine BA 00101011111001100100 BS3 BPx-28-942 soil Bend Pine BC 00101011111011000100 BS20 BP-MB-938 soil Bend Pine BC 00101011111011000100 BS21 B-5D-931 soil Bend Pine BC 00101011111011000100 BS32 BP-MB-939 soil Bend Pine BC 00101011111011000100 BS37 BP-24-931B soil Bend Pine BI 00111001111101000100 BS17 BP-5D-937 soil Bend Pine BY 11100010111001001011 BS29 BP-B5D-935 soil Bend Pine CG 11101010111001001011 BT29 BP-1BPP-962 tissue Bend Pine AG 00101011000001000100 BT31 BP-14EPP-962 tissue Bend Pine AG 00101011000001000100 BT8 BP-8EPP-961 tissue Bend Pine A K 00101011011001000100 100 Appendix A: Bend and Medford Fusarium oxysporum isolates and N7-AFLP Haplotype ID Code Isolate Host Nursery Haplotype N7 Binary Haplotype BT14 BP-11PP-962 tissue Bend Pine A K 00101011011001000100 BT16 BP-17PP-961 tissue Bend Pine A K 00101011011001000100 BT17 BP-17PP-962 tissue Bend Pine A K 00101011011001000100 BT24 BPx-PP-941B(SSl) tissue Bend Pine A K 00101011011001000100 BT25 BPx-PP-944B(SSl) tissue Bend Pine A K 00101011011001000100 BT42 BP-3PP-963B tissue Bend Pine A K 00101011011001000100 BT43 BP-8PP-961B tissue Bend Pine A K 00101011011001000100 BT44 BP-8PP-962B tissue Bend Pine A K 00101011011001000100 BT45 BP-8PP-963B tissue Bend Pine A K 001010110.11001000100 BT20 BP-17PP-963 tissue Bend Pine A M 00101011011001001000 BT18 BPx-PP-945B (SSI) tissue Bend Pine A N 00101011011001100100 BT41 BP-3PP-962B tissue Bend Pine AN 00101011011001100100 BT1 BP-5EPP-962 tissue Bend Pine AU 00101011110001000100 BT3 BP-5EPP-964 tissue Bend Pine A U 00101011110001000100 BT4 BP-5EPP-966 tissue Bend Pine A U 00101011110001000100 BT5 BP-6CPP-961 tissue Bend Pine AW 00101011110011000100 BT35 BP-1BPP-961 tissue Bend Pine A X 00101011111001000000 BT10 BP-10E-963 tissue Bend Pine A Y 00101011111001000100 BT12 BP-10EPP-963 tissue Bend Pine A Y 00101011111001000100 BT19 BPx-PP-9411B (SS2)tissue Bend Pine A Y 00101011111001000100 BT27 BPx-PP-948B tissue Bend Pine A Y 00101011111001000100 BT28 BPx-PP-9411 tissue Bend Pine A Y 00101011111001000100 BT32 BPx-PP-947B tissue Bend Pine A Y 00101011111001000100 BT37 BP-5EPP-961 tissue Bend Pine A Y 00101011111001000100 BT22 BP-19PP-962 tissue Bend Pine AZ 00101011111001001000 BT23 BP-10EPP-965 tissue Bend Pine AZ 00101011111001001000 BT34 BPx-PP-949B tissue Bend Pine AZ 00101011111001001000 BT36 BP-14EPP-961 tissue Bend Pine BA 00101011111001100100 BT38 BP-5EPP-965 tissue Bend Pine BC 00101011111011000100 BT39 BP-20PP-961 tissue Bend Pine BC 00101011111011000100 BT21 BP-19PP-961 tissue Bend Pine BD 00101011111011001000 BT40 BP-3PP-961B tissue Bend Pine BJ 00111110010001000000 BT2 BP-5EPP-963 tissue Bend Pine BX 11100010110011001010 BT33 BPx-PP-942B (SSI) tissue Bend Pine CA 11100010111011001011 BT6 BP-6CPP-962 tissue Bend Pine L 00101001110001000100 BT11 BP-10EPP-962 tissue Bend Pine L 00101001110001000100 MES5 M-I3-933 soil Medford AA 00101010110001000100 101 Appendix A : Bend and M e d f o r d Fusarium oxysporum isolates and N7-AFLP Haplotype I D Code Isolate Host Nursery Haplotype N7 B inary Haplotype MES6 M-I6-932 soil Medford AA 00101010110001000100 MES8 M-A8-931 soil Medford AA 00101010110001000100 M E S H M-I6-932 soil Medford AA 00101010110001000100 MES20 Mx-12-941 soil Medford A A 00101010110001000100 MES28 M-1-941 soil Medford A A 00101010110001000100 MES15 MX2-E25-933 soil Medford AE 00101010110001100100 MES1 M-A4-932 (SSI) soil Medford A K 00101011011001000100 MES4 Mx-6-944 soil Medford AS 00101011110000000110 MES19 Mx-3-943 soil Medford A X 00101011111001000000 MES12 MX2-E17-931 soil Medford A Y • 00101011111001000100 MES16 Mx-3-941 soil Medford A Y 00101011111001000100 MES18 Mx-9-941 soil Medford A Y 00101011111001000100 MES21 Mx-7-941 soil Medford A Y 00101011111001000100 MES35 M-12-942 soil Medford BG 00101101101001000100 MES17 Mx-6-941 soil Medford BL 01101011111001000100 MES10 M-I8-935 soil Medford B M 01101011111101000000 MES25 M-A21-931 soil Medford BT 11100000000100100011 MES26 Mx-2-l(l) soil Medford BW 11100010110001001011 MES2 M-E7-931 (SSI) soil Medford BY 11100010111001001011 MES7 Mx-3-2(2) soil Medford BY 11100010111001001011 MES13 MX2-E17-932 soil Medford BY 11100010111001001011 MES23 MX2-E17-931 soil Medford BY 11100010111001001011 MES24 M-B1-931 soil Medford BY 11100010111001001011 MES9 M-I8-932 soil Medford BZ 11100010111011001010 MES27 Mx-12-944 soil Medford BZ 11100010111011001010 MES36 M-13-931B soil Medford CE 11101010101001001011 MES39 M-26-941 soil Medford CE 11101010101001001011 MES22 MX2-E17-933 soil Medford CG 11101010111001001011 MES40 M-30-932B soil Medford K 00101001101001000100 MES41 M-30-931B soil Medford K 00101001101001000100 MES42 M-31-931B soil Medford K 00101001101001000100 MES32 M-7-942 soil Medford L 00101001110001000100 MES29 M-2-941 soil Medford M 00101001111001000100 MES30 M-3-944 soil Medford N 00101010010000000100 MES38 M-21-941 soil Medford W 00101010101001000100 MET 10 M-12DF-961 tissue Medford A A 00101010110001000100 MET35 Mx-DF-946(SS1) tissue Medford A A 00101010110001000100 102 Append ix A : Bend and M e d f o r d Fusarium oxysporum isolates and N7-AFLP Haplotype I D Code Isolate Host Nursery Haplotype N7 B inary Haplotype MET54 M-15DF-961 tissue Medford AA 00101010110001000100 MET56 M-22DF-962 tissue Medford AA 00101010110001000100 MET60 M-14DF-962 tissue Medford AA 00101010110001000100 MET79 M-28PP-962 tissue Medford AA 00101010110001000100 MET102 M-30DF-962 tissue Medford AA 00101010110001000100 MET115 M-26DF-961 tissue Medford A A 00101010110001000100 MET141 M-21DF-961B tissue Medford AA 00101010110001000100 MET142 M-21DF-962B tissue Medford A A 00101010110001000100 MET147 M-30DF-961B tissue Medford A A 00101010110001000100 MET 12 M-22DF-961 tissue Medford AB 00101010110001000101 MET5 Mx-PP-945R (Plot 5) tissue Medford AC 00101010110001000110 M E T H M-21DF-961 tissue Medford AC 00101010110001000110 M E T H M-27DF-961 tissue Medford AC 00101010110001000110 MET 16 M-5DF-961 tissue Medford AC 00101010110001000110 MET22 Mx-DF-948B (SS2) tissue Medford AC 00101010110001000110 MET42 M-25PP-961 tissue Medford AD 00101010110001001000 MET20 Mx-PP-945R(SSl) tissue Medford AF 00101010111001000110 MET94 M-27DF-961 tissue Medford A H 00101011001001000010 MET 18 Mx-PP-942R(SSl) tissue Medford A l 00101011010001000100 MET77 M-27PP-965 tissue Medford A l 00101011010001000100 MET90 M-25DF-961 tissue Medford A l 00101011010001000100 MET108 Mx-B27-R4(2) tissue Medford A l 00101011010001000100 MET150 M-5PP-961B tissue Medford A l 00101011010001000100 MET151 M-5PP-962B tissue Medford A l 00101011010001000100 MET76 M-27PP-963 tissue Medford AJ 00101011010011000100 MET3 Mx-PP-948R (Plot 1) tissue Medford A K 00101011011001000100 MET27 Mx-DF-9410(SS1) tissue Medford A K 00101011011001000100 MET100 M-29DF-961 tissue Medford A K 00101011011001000100 MET105 Mx-G30-R3(l) tissue Medford A K 00101011011001000100 MET116 M-26DF-963 tissue Medford A K 00101011011001000100 MET130 M-11DF-962B tissue Medford A K 00101011011001000100 MET133 M-15DF-962B tissue Medford A K 00101011011001000100 MET134 M-16DF-961B tissue Medford A K 00101011011001000100 MET135 M-16DF-962B tissue Medford A K 00101011011001000100 MET136 M-16DF-963B tissue Medford A K 00101011011001000100 MET137 M-16DF-964B tissue Medford A K 00101011011001000100 MET139 M-20DF-962B tissue Medford A K 00101011011001000100 103 Appendix A : Bend and M e d f o r d Fusarium oxysporum isolates and N7-AFLP Haplotype I D Code Isolate Host Nursery Haplotype N7 B inary Haplotype MET140 M-20DF-963B tissue Medford A K 00101011011001000100 MET148 M-18PP-962B tissue Medford A K 00101011011001000100 MET152 M-5PP-963B tissue Medford A K 00101011011001000100 MET155 M-13PP-962B tissue Medford A K 00101011011001000100 MET156 M-13PP-963B tissue Medford A K 00101011011001000100 MET157 M-13PP-964B tissue Medford A K 00101011011001000100 MET158 M-20PP-963B tissue Medford A K 00101011011001000100 MET159 M-20PP-964B tissue Medford A K 00101011011001000100 MET161 M-23PP-962B tissue Medford A K 00101011011001000100 MET163 M-C12-931 (SS2) tissue Medford A K 00101011011001000100 MET 19 Mx-DF-948 (SSI) tissue Medford AL 00101011011001000110 MET41 M-21PP-961 tissue Medford A M 00101011011001001000 MET93 M-26DF-964 tissue Medford AN 00101011011001100100 MET46 M-27PP-961 tissue Medford AT 00101011110000101000 MET82 M-30PP-962 tissue Medford A U 00101011110001000100 MET88 M-19DF-962 tissue Medford AU 00101011110001000100 MET91 M-25DF-962 tissue Medford AU 00101011110001000100 MET92 M-26DF-963 tissue Medford AU 00101011110001000100 MET101 M-30DF-961 tissue Medford AU 00101011110001000100 MET111 M-27PP-964 tissue Medford AU 00101011110001000100 MET30 Mx-DF-947B (SSI) tissue Medford A V 00101011110001100100 MET21 Mx-DF-945 (SSI) tissue Medford A Y 00101011111001000100 MET33 Mx-DF-949(SS1) tissue Medford A Y 00101011111001000100 MET34 Mx-DF-941B (SSI) tissue Medford A Y 00101011111001000100 MET53 M-5DF-964 tissue Medford A Y 00101011111001000100 MET66 Mx-DF-946B (SSI) tissue Medford A Y 00101011111001000100 MET67 Mx-PP-941B(SSl) tissue Medford A Y 00101011111001000100 MET81 M-29PP-961 tissue Medford A Y 00101011111001000100 MET87 M-19DF-961 tissue Medford A Y 00101011111001000100 MET98 Mx-B27-S2 tissue Medford A Y 00101011111001000100 MET103 M-26DF-962 tissue Medford A Y 00101011111001000100 MET112 M-30PP-961 tissue Medford A Y 00101011111001000100 MET114 M-25DF-963 tissue Medford A Y 00101011111001000100 MET146 M-29DF-962B tissue Medford A Y 00101011111001000100 MET36 M-18PP-962 tissue Medford AZ 00101011111001001000 MET38 M-19PP-963 tissue Medford AZ 00101011111001001000 MET40 M-20PP-962 tissue Medford AZ 00101011111001001000 104 Appendix A: Bend and Medford Fusarium oxysporum isolates and N7-AFLP Haplotype ID Code Isolate Host Nursery Haplotype N7 Binary Haplotype MET43 M-26PP-961 tissue Medford AZ 00101011111001001000 MET44 M-26PP-962 tissue Medford AZ 00101011111001001000 MET45 M-26PP-963 tissue Medford AZ 00101011111001001000 MET 17 M-25DF-962 tissue Medford B 00100010111011001010 MET31 Mx-DF-943 (SSI) tissue Medford BA 00101011111001100100 MET32 Mx-DF-941 (SS2) tissue Medford BA 00101011111001100100 MET39 M-19PP-964 tissue Medford BB 00101011111001101000 MET109 Mx-DF-944(SS1) tissue Medford BE 00101011111011100100 MET110 Mx-DF-942(SS1) tissue Medford BF 00101011111011101000 MET119 M-4DF-961B tissue Medford BH 00101101110001000100 MET28 Mx-DF-949B (SS2) tissue Medford BK 01101011010001000100 MET117 M-3DF-962B tissue Medford BK 01101011010001000100 MET143 M-23DF-961B tissue Medford BN 01111011110001000100 MET144 M-23DF-962B tissue Medford BO 01111011111001000100 MET 145 M-29DF-961B tissue Medford BP 01111011111101000100 MET89 M-21DF-961 tissue Medford BQ 10100010110011001010 MET4 Mx-PP-942R (Plot 1) tissue Medford BR 10100010111011001011 MET75 Mx-PP-947R(SSl) tissue Medford BR 10100010111011001011 MET47 M-27PP-962 tissue Medford BS 10101011010001001000 MET 122 M-4DF-964B tissue Medford BU 11100000111011001011 MET95 Mx-28A-t2 tissue Medford BV 11100010110000000011 MET2 Mx-G30-R2(l) (SSI) tissue Medford BY 11100010111001001011 MET6 Mx-PP-946R(SS3) tissue Medford BY 11100010111001001011 MET9 M-9DF-961 tissue Medford BY 11100010111001001011 MET 15 M-5DF-963 tissue Medford BY 11100010111001001011 MET24 Mx-DF-947 (SSI) tissue Medford BY 11100010111001001011 MET25 Mx-PP-946R (SS2) tissue Medford BY 11100010111001001011 MET26 Mx-DF-942B (SSI) tissue Medford BY 11100010111001001011 MET48 M-8DF-962 tissue Medford BY 11100010111001001011 MET52 M-18DF-961 tissue Medford BY 11100010111001001011 MET57 M-17DF-961 tissue Medford BY 11100010111001001011 MET59 M-7PP-961 tissue Medford BY 11100010111001001011 MET80 M-28PP-963 tissue Medford BY 11100010111001001011 MET104 M-28DF-961 tissue Medford BY 11100010111001001011 MET 125 M-8DF-963B tissue Medford BY 11100010111001001011 MET126 M-9DF-961B tissue Medford BY 11100010111001001011 105 Appendix A: Bend and Medford Fusarium oxysporum isolates and N7-AFLP Haplotype ID Code Isolate Host Nursery Haplotype N7 Binary Haplotype MET127 M-9DF-962B tissue Medford BY 11100010111001001011 MET153 M-5PP-964B tissue Medford BY 11100010111001001011 MET7 M-27DF-962 tissue Medford BZ 11100010111011001010 MET23 Mx-DF-941 (SSI) tissue Medford BZ 11100010111011001010 MET51 M-14DF-961 tissue Medford BZ 11100010111011001010 MET84 M-18DF-962 tissue Medford BZ 11100010111011001010 MET154 M-13PP-961B tissue Medford BZ l i ioooioii ionooioio MET 164 M-18PP-961B tissue Medford BZ 11100010111011001010 MET128 M-9DF-964B tissue Medford C 00100011011000100100 MET49 M-25DF-961 tissue Medford CA 11100010111011001011 MET118 M-3DF-963B tissue Medford CA 11100010111011001011 MET113 M-18DF-963 tissue Medford CB 11100011111011001011 MET62 Mx-DF-942B (SSI) tissue Medford CC 11100100110000000011 MET65 Mx-DF-945B (SSI) tissue Medford CD 11100110110110000000 MET96 Mx-28A-t3 tissue Medford CF 11101010110001010011 MET50 M-9DF-962 tissue Medford CG 11101010111001001011 MET58 M-16PP-962 tissue Medford CG 11101010111001001011 MET61 Mx-28A-t4 tissue Medford CG 11101010111001001011 MET 106 Mx-B27-S4 tissue Medford CG 11101010111001001011 MET78 M-28PP-961 tissue Medford D 00100011110000110100 MET86 M-18DF-965 tissue Medford E 00100011111000110100 MET121 M-4DF-963B tissue Medford F 00101000111001000110 MET64 Mx-DF-944B (SSI) tissue Medford G oqioiooioooooioooioo MET63 Mx-DF-943B (SS2) tissue Medford H 00101001010011100101 MET71 Mx-PP-944B (SS2) tissue Medford I 00101001010101000000 MET73 Mx-PP-946B (SSI) tissue Medford J 00101001010101000100 MET97 Mx-G30-S3 tissue Medford J 00101001010101000100 MET69 Mx-PP-942B (SSI) tissue Medford M 00101001111001000100 MET 129 M-11DF-961B tissue Medford 0 00101010010001000000 MET1 Mx-B27-R2(l)-1 tissue Medford P 00101010010001000100 MET107 Mx-B27-S5 tissue Medford P 00101010010001000100 MET162 M-23PP-963B tissue Medford P 00101010010001000100 MET37 M-19PP-961 tissue Medford Q 00101010010001001000 MET83 M-30PP-963 tissue Medford R 00101010010001100100 MET160 M-23PP-961B tissue Medford R 00101010010001100100 MET124 M-8DF-962B tissue Medford S 00101010010011000100 MET132 M-15DF-961B tissue Medford s 00101010010011000100 106 Appendix A: Bend and Medford Fusarium oxysporum isolates and N7-AFLP Haplotype ID Code Isolate Host Nursery Haplotype N7 Binary Haplotype MET138 M-20DF-961B tissue Medford T 00101010011001000100 MET131 M-11DF-963B tissue Medford U 00101010011011000000 MET68 Mx-PP-941R(SSl) tissue Medford V 00101010101001000010 MET 165 M-20PP-961B tissue Medford W 00101010101001000100 MET166 M-20PP-962B tissue Medford W 00101010101001000100 MET 167 M-9DF-963B tissue Medford W 00101010101001000100 MET55 M-16PP-961 tissue Medford X 00101010110000000100 MET149 M-18PP-963B tissue Medford X 00101010110000000100 MET29 Mx-PP-944R tissue Medford Y 00101010110001000000 MET74 Mx-PP-947B (SSI) tissue Medford Z 00101010110001000010 All isolates obtained from Dr. Jeff Stone, Oregon State University. First two letters of ID Code field indicate the nursery site where the isolate was collected (ME = Medford; BP = Bend); the third letter of the ID Code indicates whether the isolate was collected from tissue (T) or soil (S). The numerical part of the ID Code uniquely identifies the isolate among others from the same nursery and source (i.e. tissue vs. soil). 107 Appendix B: Histone-H3 RFLP Data from Fusarium oxysporum ID Code Nursery Site Host H3 RFLP H3 Binary Haplotype Prov/St Mx-DF-944 (SSI) Medford Douglas Fir BUBB 1001100010000101 OR BPx-PP-942B (SSI) Bend Pine Ponderosa Pine BUBU 1001100001110000 OR BPx-PP-949B (SSI) Bend Pine Ponderosa Pine BUBB 1001100010000101 OR Mx-DF-942(SS1) Medford Douglas Fir BUBB 1001100010000101 OR Mx-PP-942B (SSI) Medford Ponderosa Pine BUBB 1001100010000101 OR Mx-DF-948 (SSI) Medford Douglas Fir BUBB 1001100010000101 OR Mx-PP-945R(SSl) Medford Ponderosa Pine BUCD 10011Q0001100110 OR Mx-DF-945 (SSI) Medford Douglas Fir BUBB 1001100010000101 OR Mx-DF-948B (SS2) Medford Douglas Fir CUCD 0110100001100110 OR Mx-DF-941 (SSI) Medford Douglas Fir BUBU 1001100001110000 OR Mx-DF-947 (SSI) Medford Douglas Fir BUBU 1001100001110000 OR BPx-PP-945B (SSI) Bend Pine Ponderosa Pine BUBB 1001100010000101 OR Mx-PP-946R (SS2) Medford Ponderosa Pine BUBU 1001100001110000 OR Mx-DF-942B (SSI) Medford Douglas Fir BUBU 1001100001110000 OR Mx-DF-9410(SS1) Medford Douglas Fir BUBB 1001100010000101 OR Mx-DF-949B (SS2) Medford Douglas Fir BABB 1001011010000101 OR Mx-PP-944R(SSl) Medford Ponderosa Pine BUCD 1001100001100110 OR Mx-DF-947B (SSI) Medford Douglas Fir BUBB 1001100010000101 OR BPx-PP-9411B Bend Pine Ponderosa Pine BUBB 1001100010000101 OR Mx-DF-943 (SSI) Medford Douglas Fir BUBB 1001100010000101 OR Mx-DF-941 (SS2) Medford Douglas Fir BUBB 1001100010000101 OR Mx-DF-949 (SSI) Medford Douglas Fir BUBB 1001100010000101 OR Mx-DF-941B (SSI) Medford Douglas Fir BUBB 1001100010000101 OR Mx-DF-946(SS1) Medford Douglas Fir BUCD 1001100001100110 OR Mx-DF-9411 (SSI) Medford Douglas Fir BUBU 1001100001110000 OR Mx-DF-942B (SSI) Medford Douglas Fir BUBU 1001100001110000 OR Mx-DF-943B (SS2) Medford Douglas Fir CUCD 0110100001100110 OR Mx-DF-944B (SSI) Medford Douglas Fir BUBB 1001100010000101 OR Mx-DF-945B (SSI) Medford Douglas Fir BUBU 1001100001110000 OR Mx-DF-946B (SSI) Medford Douglas Fir BUBB 1001100010000101 OR Mx-PP-941B (SSI) Medford Ponderosa Pine BUBB 1001100010000101 OR Mx-PP-941R(SSl) Medford Ponderosa Pine CUCD 0110100001100110 OR Mx-PP-942B (SSI) Medford Ponderosa Pine BUBB 1001100010000101 OR Mx-PP-943B (SSI) Medford Ponderosa Pine BUBC 1001100010001000 OR Mx-PP-944B (SS2) Medford Ponderosa Pine BUBB 1001100010000101 OR Mx-PP-945B (SSI) Medford Ponderosa Pine BUBU 1001100001110000 OR 108 Appendix B: Histone-H3 RFLP Data from Fusarium oxysporum (cont.) ID Code Nursery Site Host H3 RFLP H3 Binary Haplotype Prov/St Mx-PP-946B (SSI) Medford Ponderosa Pine BUBB 1001100010000101 OR Mx-PP-947B (SSI) Medford Ponderosa Pine CUCD 0110100001100110 OR Mx-PP-947R(SSl) Medford Ponderosa Pine BUBU 1001100001110000 OR BPx-PP-941B (SSI) Bend Pine Ponderosa Pine BUBB 1001100010000101 OR BP-1BPP-961 Bend Pine Ponderosa Pine BUBB 1001100010000101 OR BP-1BPP-962 Bend Pine Ponderosa Pine BUBB 1001100010000101 OR BP-1BPP-963 Bend Pine Ponderosa Pine BUBC 1001100010001000 OR BP-14EPP-961 Bend Pine Ponderosa Pine BUBB 1001100010000101 OR BP-14EPP-962 Bend Pine Ponderosa Pine BUBB 1001100010000101 OR BP-2CPP-961 Bend Pine Ponderosa Pine BUBB 1001100010000101 OR BP-5EPP-961 Bend Pine Ponderosa Pine BUBB 1001100010000101 OR BP-5EPP-962 Bend Pine Ponderosa Pine BUBB 1001100010000101 OR BP-5EPP-963 Bend Pine Ponderosa Pine BUBU 1001100001110000 OR BP-5EPP-964 Bend Pine Ponderosa Pine BUBB 1001100010000101 OR BP-5EPP-965 Bend Pine Ponderosa Pine BUBB 1001100010000101 OR BP-5EPP-966 Bend Pine Ponderosa Pine BUBB 1001100010000101 OR BP-6CPP-961 Bend Pine Ponderosa Pine BUBB 1001100010000101 OR BP-6CPP-962 Bend Pine Ponderosa Pine BUBB 1001100010000101 OR BP-8EPP-961 Bend Pine Ponderosa Pine BUBB 1001100010000101 OR BP-20PP-961 Bend Pine Ponderosa Pine BUBB 1001100010000101 OR M-26PP-961 Medford Ponderosa Pine BUBB 1001100010000101 OR M-26PP-962 Medford Ponderosa Pine BUBB 1001100010000101 OR M-26PP-963 Medford Ponderosa Pine BUBB 1001100010000101 OR M-27PP-961 Medford Ponderosa Pine BUCD 1001100001100110 OR M-27PP-962 Medford Ponderosa Pine BABB 1001011010000101 OR M-27PP-963 Medford Ponderosa Pine BABB 1001011010000101 OR M-27PP-965 Medford Ponderosa Pine BUBB 1001100010000101 OR M-28PP-961 Medford Ponderosa Pine BABB 1001011010000101 OR M-28PP-962 Medford Ponderosa Pine BUCD 1001100001100110 OR M-28PP-963 Medford Ponderosa Pine BUBU 1001100001110000 OR M-29PP-961 Medford Ponderosa Pine BUBB 1001100010000101 OR M-30PP-962 Medford Ponderosa Pine BUCD 1001100001100110 OR M-30PP-963 Medford Ponderosa Pine BUCD 1001100001100110 OR BPx-PP-947B Bend Pine Ponderosa Pine BUBB 1001100010000101 OR BP-3PP-961B Bend Pine Ponderosa Pine BUCD 1001100001100110 OR BP-3PP-962B Bend Pine Ponderosa Pine BUBB 1001100010000101 OR BP-8PP-962B Bend Pine Ponderosa Pine BUBB 1001100010000101 OR 109 Appendix B: Histone-H3 RFLP Data from Fusarium oxysporum (cont.) ID Code Nursery Site Host H3 RFLP H3 Binary Haplotype Prov/St M-20DF-962B Medford Douglas Fir BUBB 1001100010000101 OR M-23DF-961B Medford Douglas Fir BABB 1001011010000101 OR M-29DF-961B Medford Douglas Fir BUBB 1001100010000101 OR WR-I6-931 Wind River soil BUCD 1001100001100110 WA HN-5-4-931 Humboldt soil BUCD 1001100001100110 CA Mx-28A-t2 Medford DF or PP BUBU 1001100001110000 OR Mx-28A-t3 Medford DF or PP BUBU 1001100001110000 OR M-I3-933 Medford soil BUCD 1001100001100110 OR WR-22-931 Wind River soil BUCD 1001100001100110 WA M-I6-932 Medford soil BUCD 1001100001100110 OR Mx-3-2(2) Medford soil BUBU 1001100001110000 OR M-A8-931 Medford soil BUCD 1001100001100110 OR M-I8-932 Medford soil BUBU 1001100001110000 OR Mx-G30-S3 Medford Ponderosa Pine BUBB 1001100010000101 OR LP-A3-931 Lucky Peak soil BUBB 1001100010000101 ID MA-1-1-931 Magalia soil BUCD 1001100001100110 CA M-I8-935 Medford soil BUBB 1001100010000101 OR Mx-B27-S2 Medford Douglas Fir BUBB 1001100010000101 OR WR-27-931 Wind River soil BUCD 1001100001100110 WA MA-5-1-931 Magalia soil BUCD 1001100001100110 CA MA-2-3-931 Magalia soil BUCD 1001100001100110 CA M-I6-932 Medford soil BUCD 1001100001100110 OR M-C5-932 Medford soil BUBB 1001100010000101 OR Mx-G30-R3(l) Medford Ponderosa Pine BUBB 1001100010000101 OR Mx-B27-S4 Medford Douglas Fir BUBU 1001100001110000 OR M-B1-931 Medford soil BUBU 1001100001110000 OR HN-4-4-931 Humboldt soil BUCD 1001100001100110 CA LP-A2-931 Lucky Peak soil BUBB 1001100010000101 ID M-A21-931 Medford soil BUBU 1001100001110000 OR Mx-B27-S5 Medford Douglas Fir BUCD 1001100001100110 OR Mx-B27-R4(2) Medford Douglas Fir BUBB 1001100010000101 OR Mx-2-l(l) Medford soil BUBU 1001100001110000 OR Mx-3-941 Medford soil BUBB 1001100010000101 OR Mx-6-941 Medford soil BABB 1001011010000101 OR Mx-9-941 Medford soil BUBB 1001100010000101 OR Mx-3-943 Medford soil BUBU 1001100001110000 OR Mx-12-941 Medford soil BUCD 1001100001100110 OR 110 Appendix B: Histone-H3 RFLP Data from Fusarium oxysporum (cont.) ID Code Nursery Site Host H3 RFLP H3 Binary Haplotype Prov/St Mx-7-941 Medford soil BUBB 1001100010000101 OR BP-MB-932 Bend Pine soil BUBB 1001100010000101 OR BPF-932 Bend Pine soil BUBB 1001100010000101 OR BPB-935 Bend Pine soil BUBB 1001100010000101 OR BPB-931 Bend Pine soil BUBB 1001100010000101 OR BP-5D-931 Bend Pine soil BUBB 1001100010000101 OR BPF-935 Bend Pine soil BUBB 1001100010000101 OR BP-B5D-935 Bend Pine soil BUBU 1001100001110000 OR BP-5D-937 Bend Pine soil BUBB 1001100010000101 OR BPx-1-941 Bend Pine soil BUBB 1001100010000101 OR BPx-28-942 Bend Pine soil BUBB 1001100010000101 OR BPx-4-942 Bend Pine soil BUBB 1001100010000101 OR BPx-4-941 Bend Pine soil BUBB 1001100010000101 OR BP-12-942 Bend Pine soil BUBB 1001100010000101 OR BPx-18-941 Bend Pine soil BUBB 1001100010000101 OR BP-17-941 Bend Pine soil BUBB 1001100010000101 OR BPx-28-941 Bend Pine soil BUBB 1001100010000101 OR BPx-15-941 Bend Pine soil BUBB 1001100010000101 OR BPx-9-941 Bend Pine soil BUBB 1001100010000101 OR BPx-6-942 Bend Pine soil BUBB 1001100010000101 OR BPx-P2-942 Bend Pine soil BUBB 1001100010000101 OR BPB-932 Bend Pine soil BUBB 1001100010000101 OR BP-MB-939 Bend Pine soil BUBB 1001100010000101 OR BPB-936 Bend Pine soil BUBB 1001100010000101 OR F20 Moscow Douglas Fir BBBB 1001000010000101 ID F21 Coeur d Alene Douglas Fir BUBB 1001100010000101 ID F30 Vancouver Douglas Fir BUBC 1001100010001000 BC F41 Alger Creek Douglas Fir BUCB 1001100001100101 BC F44 Cowichan Douglas Fir BUCD 1001100001100110 BC F71 Surrey Douglas Fir BUCD 1001100001100110 BC P4C2P17A Pemberton Douglas Fir BUBU 1001100001110000 BC C2CUP3A Chilliwack Douglas Fir BUCD 1001100001100110 BC 3139 Brooks Douglas Fir BUBU 1001100001110000 OR 9043B Coeur d'Alene Douglas Fir BUBB 1001100010000101 ID 90651 Moscow Douglas Fir BUBB 1001100010000101 ID BP-3-932B Bend Pine soil BUBB 1001100010000101 OR BP-14-93 IB Bend Pine soil BUBB 1001100010000101 OR 111 Appendix B: Histone-H3 RFLP Data from Fusarium oxysporum (cont.) ID Code Nursery Site Host H3 RFLP H3 Binary Haplotype Prov/St BP-15-931B Bend Pine soil BUBB 1001100010000101 OR The H3 RFLP field indicates the histone-H3 RFLP profile as defined by Donaldson et al. (1995) using the restriction enzymes Mbo I, Mse I, Cfo I, and Nla III. The H3 binary haplotype represents the presence or absence of specific restriction fragments after digestion with the aforementioned endonucleases. 112 Appendix C: Fusarium oxysporum Pathogenicity Assay Results Assay Isolate Source Heal thy Nonemerged Diseased Total Disease P-Value 7-1 WR-I6-931 soil 81.25% 3.13% 15.63% 18.75% 0.496 7-2 HN-5-4-931 soil 34.38% 1.56% 62.50% 64.06% 0.000 7-3 Mx-28A-t2 tissue 70.31% 1.56% 28.13% 29.69% 0.089 7-4 Mx-28A-t3 tissue 1.56% 6.25% 92.19% 98.44% 0.000 7-5 M-I3-933 soil 0.00% 4.69% 95.31% 100.00% 0.000 7-6 WR-22-931 soil 76.56% 4.69% 18.75% 23.44% 0.475 7-7 M-I6-932 soil 90.63% 4.69% 4.69% 9.38% 0.500 7-8 Mx-3-2(2) soil 4.69% 12.50% 82.81% 95.31% 0.000 7-9 M-A8-931 soil 71.88% 9.38% 15.63% 25.00% 0.117 7-10 M-I8-932 soil 93.75% 3.13% 3.13% 6.25% 0.444 7-11 F41 seed 37.50% 18.75% 43.75% 62.50% 0.000 7-12 water n/a 89.06% 10.94% 0.00% 10.94% 1.000 8-1 Mx-G30-S3 tissue 4.69% 12.50% 82.81% 95.31% 0.000 8-2 LP-A3-931 soil 10.94% 25.00% 64.06% 89.06% 0.000 8-3 MA-1-1-931 soil 78.13% 6.25% 15.63% 21.88% 0.493 8-4 M-I8-935 soil 0.00% 9.38% 90.63% 100.00% 0.000 8-5 Mx-B27-S2 tissue 42.19% 6.25% 51.56% 57.81% 0.000 8-6 WR-27-931 soil 14.06% 23.44% 62.50% 85.94% 0.000 8-7 MA-5-1-931 soil 21.88% 10.94% 67.19% 78.13% 0.000 8-8 Mx-B27-R5(l)-1 tissue 79.69% 7.81% 12.50% 20.31% 0.445 8-9 MA-2-3-931 soil 78.13% 4.69% 17.19% 21.88% 0.113 8-10 M-I6-932 soil 70.31% 14.06% 15.63% 29.69% 0.202 8-11 F41 seed 35.94% 4.69% 59.38% 64.06% 0.000 8-12 water n/a 94.64% 3.57% 1.79% 5.36% 1.000 Assay code is given in format #-#, where the first digit indicates experiment number, and the second digit indicates treatment number. Isolate codes listed as assigned by Jeff Stone and David Gemandt. Total disease calculated as the sum of diseased and nonemerged categories. The listed P-value was determined using a Dunnett's one-sided test comparing the proportion of healthy seedlings in the water control and isolate treatments. Positive control = F41; negative control = sterile distilled water. 113 Appendix C: Fusarium oxysporum Pathogenicity Assay Results (cont.) Assay Isolate Source Healthy Nonemerged Diseased Total Disease P-Value 9-1 M-C5-932 soil 3.13% 6.25% 90.63% 96.88% 0.000 9-2 Mx-G30-R3(l) tissue 54.69% 10.94% 34.38% 45.31% 0.064 9-3 Mx-B27-S4 tissue 32.81% 4.69% 62.50% 67.19% 0.000 9-4 M-B1-931 soil 32.81% 4.69% 62.50% 67.19% 0.000 9-5 HN-4-4-931 soil 73.44% 1.56% 25.00% 26.56% 0.493 9-6 LP-A2-931 soil 95.31% 4.69% 0.00% 4.69% 0.319 9-7 F41 seed 85.94% 9.38% 4.69% 14.06% 0.500 9-8 M-A21-931 soil 0.00% 9.38% 90.63% 100.00% 0.000 9-9 Mx-B27-S5 tissue 92.19% 3.13% 4.69% 7.81% 0.487 9-10 Mx-B27-R4(2) tissue 7.81% 6.25% 85.94% 92.19% 0.000 9-11 Mx-2-l(l) soil 45.31% 4.69% 50.00% 54.69% 0.003 9-12 water n/a 81.25% 12.50% 6.25% 18.75% 1.000 10-1 Mx-DF-941 tissue 42.19% 3.13% 54.69% 57.81% 0.007 10-2 Mx-DF-942 tissue 10.94% 4.69% 84.38% 89.06% 0.000 10-3 Mx-DF-943 tissue 50.00% 9.38% 40.63% 50.00% 0.039 10-4 Mx-DF-944 tissue 20.31% 6.25% 73.44% 79.69% 0.000 10-5 Mx-DF-945 tissue 1.56% 0.00% 98.44% 98.44% 0.000 10-6 Mx-DF-946 tissue 46.88% 3.13% 50.00% 53.13% 0.023 10-7 Mx-DF-947 tissue 3.13% 4.69% 92.19% 96.88% 0.000 10-8 Mx-DF-948 tissue 32.81% 4.69% 62.50% 67.19% 0.002 10-9 Mx-DF-949 tissue 0.00% 0.00% 100.00% 100.00% 0.000 10-10 Mx-DF-9410 tissue 35.94% 3.13% 60.94% 64.06% 0.002 10-11 Mx-DF-9411 tissue 14.06% 6.25% 79.69% 85.94% 0.000 10-12 Mx-DF-941B tissue 20.31% 4.69% 75.00% 79.69% 0.000 10-13 Mx-DF-942B tissue 0.00% 0.00% 100.00% 100.00% 0.000 10-14 Mx-DF-943B tissue 35.94% 0.00% 64.06% 64.06% 0.006 10-15 Mx-DF-944B tissue 0.00% 0.00% 100.00% 100.00% 0.000 10-16 Mx-DF-945 B tissue 0.00% 0.00% 100.00% 100.00% 0.000 10-17 Mx-DF-946B tissue 6.25% 4.69% 89.06% 93.75% 0.000 10-18 Mx-DF-947B tissue 10.94% 4.69% 84.38% 89.06% 0.000 10-19 Mx-DF-948B tissue 12.50% 3.13% 84.38% 87.50% 0.000 10-20 Mx-DF-949B tissue 34.38% 10.94% 54.69% 65.63% 0.001 10-21 LP-E1-931 soil 93.75% 4.69% 1.56% 6.25% 0.500 10-22 F41 seed 26.56% 0.00% 73.44% 73.44% 0.000 10-23 water n/a 85.94% 14.06% 0.00% 14.06% 1.000 Assay code is given in format #-#, where the first digit indicates experiment number, and the second digit indicates treatment number. Isolate codes listed as assigned by Jeff Stone and David Gernandt. Total disease calculated as the sum of diseased and nonemerged categories. The listed P-value was determined using a Dunnett's one-sided test comparing the proportion of healthy seedlings in the water control and isolate treatments. Positive control = F41; negative control = sterile distilled water. 114 Appendix C: Fusarium oxysporum Pathogenicity Assay Results (cont.) Assay Isolate Source Healthy Nonemerged Diseased Total Disease P-Value 11-1 BP-MB-938 soil 51.56% 10.94% 37.50% 48.44% 0.013 11-2 B-5D-931 soil 64.06% 0.00% 34.38% 34.38% 0.223 11-3 BP-MB-932 soil 62.50% 9.38% 28.13% 37.50% 0.187 11-4 BP-F-932 soil 48.44% 1.56% 50.00% 51.56% 0.004 11-5 BP-B-935 soil 0.00% 0.00% 100.00% ' 100.00% 0.000 11-6 BP-B-931 soil 6.25% 3.13% 90.63% 93.75% 0.000 11-7 BP-5D-931 soil 64.06% 7.81% 28.13% 35.94% 0.166 11-8 BP-20W-Y4 soil 82.81% 1.56% 15.63% 17.19% 0.500 11-9 BP-F-935 soil 73.44% 0.00% 26.56% 26.56% 0.450 11-10 BP-B5D-935 soil 0.00% 0.00% 100.00% 100.00% 0.000 11-11 BP-5D-937 soil 87.50% 12.50% 0.00% 12.50% 0.500 11-12 BPx-10-941 soil 0.00% 0.00% 100.00% 100.00% 0.000 11-13 BPx-PP-947B tissue 90.63% 6.25% 3.13% 9.38% 0.500 11-14 BP-MB-939 soil 82.81% 4.69% 12.50% 17.19% 0.500 11-15 BP-B-932 soil 45.31% 3.13% 51.56% 54.69% 0.004 11-16 BPx-PP-948B tissue 7.81% 0.00% 92.19% 92.19% 0.000 11-17 BPx-PP-9411 tissue 40.63% 10.94% 48.44% 59.38% 0.001 11-18 BP-B-936 soil 39.06% 3.13% 57.81% 60.94% 0.001 11-19 BP-F-936 soil 59.38% 9.38% 31.25% 40.63% 0.090 11-20 BP-5D-937 soil 59.38% 6.25% 34.38% 40.63% 0.121 11-21 F41 seed 56.25% 6.25% 37.50% 43.75% 0.049 11-22 water n/a 87.50% 7.81% 4.69% 12.50% 1.000 Assay code is given in format #-#, where the first digit indicates experiment number, and the second digit indicates treatment number. Isolate codes listed as assigned by Jeff Stone and David Gernandt. Total disease calculated as the sum of diseased and nonemerged categories. The listed P-value was determined using a Dunnett's one-sided test comparing the proportion of healthy seedlings in the water control and isolate treatments. Positive control = F41; negative control = sterile distilled water. 115 Appendix C: Fusarium oxysporum Pathogenicity Assay Results (cont.) Assay Isolate Source Healthy Nonemerged Diseased Total Disease P-Value 12-1 WR-I6-931 soil 89.06% 3.13% 7.81% 10.94% 0.500 12-2 Mx-28A-t2 tissue 64.06% 9.38% 26.56% 35.94% 0.172 12-3 WR-22-931 soil 67.19% 4.69% 28.13% 32.81% 0.227 12-4 M-I6-932 soil 75.00% 9.38% 15.63% 25.00% 0.457 12-5 M-I8-932 soil 93.75% 6.25% 0.00% 6.25% 0.500 12-6 MA-1-1-931 soil 81.25% 4.69% 14.06% 18.75% 0.500 12-7 MA-2-3-931 soil 89.06% 4.69% 6.25% 10.94% 0.500 12-8 Mx-B27-S5 tissue 78.13% 9.38% 12.50% 21.88% 0.471 12-9 LP-A2-931 soil 71.88% 12.50% 15.63% 28.13% 0.322 12-10 HN-4-4-931 soil 35.94% 4.69% 59.38% 64.06% 0.001 12-11 Mx-G30-R3(l) tissue 43.75% 0.00% 54.69% 54.69% 0.008 12-12 M-I6-932 soil 84.38% 7.81% 7.81% 15.63% 0.500 12-13 BPx-PP-947B tissue 32.81% 17.19% 50.00% 67.19% 0.000 12-14 BP-5D-937 soil 46.88% 0.00% 53.13% • 53.13% 0.009 12-15 BPF-936 soil 67.19% 6.25% 26.56% 32.81% 0.287 12-16 BP-MB-939 soil 21.88% 15.63% 62.50% 78.13% 0.000 12-17 BPF-935 soil 85.94% 6.25% 7.81% 14.06% 0.500 12-18 BP-5D-937 soil 76.56% 3.13% 20.31% 23.44% 0.497 12-19 BP-5D-931 soil 53.13% 12.50% 34.38% 46.88% 0.025 12-20 BP-MB-932 soil 70.31% 9.38% 20.31% 29.69% 0.376 12-21 B5D-931 soil 76.56% 1.56% 21.88% 23.44% 0.496 12-22 BP-20W-Y4 soil 78.13% 0.00% 21.88% 21.88% 0.499 12-23 M-25PP-961 tissue 48.44% 9.38% 42.19% 51.56% 0.028 12-24 M-26PP-961 tissue 25.00% 10.94% 64.06% 75.00% 0.000 12-25 F41 seed 37.50% 9.38% 53.13% 62.50% 0.001 12-26 water n/a 90.63% 4.69% 4.69% 9.38% 1.000 Assay code is given in format #-#, where the first digit indicates experiment number, and the second digit indicates treatment number. Isolate codes listed as assigned by Jeff Stone and David Gernandt. Total disease calculated as the sum of diseased and nonemerged categories. The listed P-value was determined using a Dunnett's one-sided test comparing the proportion of healthy seedlings in the water control and isolate treatments. Positive control = F41; negative control = sterile distilled water. 116 Appendix C: Fusarium oxysporum Pathogenicity Assay Results (cont.) Assay Isolate Source Healthy Nonemerged Diseased Total Disease P-Value 13-1 LP-A3-931 soil 12.50% 3.13% 84.38% 87.50% 0.000 13-2 M-I8-935 soil 43.75% 1.56% 54.69% 56.25% 0.000 13-3 M-A21-931 soil 0.00% 0.00% 100.00% 100.00% 0.000 13-4 M-B27-R4(2) tissue 23.44% 10.94% 65.63% 76.56% 0.000 13-5 M-C5-932 soil 7.81% 3.13% 89.06% 92.19% 0.000 13-6 MA-5-1-931 soil 25.00% 7.81% 67.19% , 75.00% 0.000 13-7 WR-27-931 soil 71.88% 3.13% 25.00% 28.13% 0.067 13-8 Mx-28A-t3 tissue 1.56% 1.56% 96.88% 98.44% 0.000 13-9 BP-B-935 soil 0.00% 1.56% 98.44% 100.00% 0.000 13-10 BP-B-931 soil 6.25% 3.13% 90.63% 93.75% 0.000 13-11 BP-B5D-935 soil 0.00% 0.00% 100.00% 100.00% 0.000 13-12 BPx-PP-948B tissue 34.38% 3.13% 62.50% 65.63% 0.000 13-13 M-I3-933 soil 0.00% 1.56% 98.44% 100.00% 0.000 13-14 Mx-3-2(2) soil 14.06% 0.00% 85.94% 85.94% 0.000 13-15 Mx-G30-S3 tissue 3.13% 0.00% 96.88% 96.88% 0.000 13-16 Mx-DF-946B tissue 14.06% 6.25% 79.69% 85.94% 0.000 13-17 Mx-DF-945B tissue 0.00% 1.56% 98.44% 100.00% 0.000 13-18 Mx-DF-944B tissue 17.19% 0.00% 82.81% 82.81% 0.000 13-19 Mx-DF-946 tissue 71.88% 4.69% 23.44% 28.13% 0.066 13-20 Mx-DF-949 tissue 45.31% 3.13% 51.56% 54.69% 0.000 13-21 Mx-DF-943 tissue 57.81% 3.13% 39.06% 42.19% 0.002 13-22 Mx-DF-947 tissue 9.38% 7.81% 82.81% 90.63% 0.000 13-23 Mx-DF-945 tissue 32.81% 7.81% 59.38% • 67.19% 0.000 13-24 F41 seed 59.38% 3.13% 37.50% 40.63% 0.002 13-25 water n/a 95.31% 4.69% 0.00% 4.69% 1.000 Assay code is given in format where the first digit indicates experiment number, and the second digit indicates treatment number. Isolate codes listed as assigned by Jeff Stone and David Gernandt. Total disease calculated as the sum of diseased and nonemerged categories. The listed P-value was determined using a Dunnett's one-sided test comparing the proportion of healthy seedlings in the water control and isolate treatments. Positive control = F41; negative control = sterile distilled water. 117 Appendix D : Fusarium Histone-H3 encoding Gene Sequence Alignment N.eras F. oxy_] F. oxy_] F. oxy_l F. oxy F.oxy_ F. oxy_] F. oxy_] F. oxy_] F.oxy_ F.oxy_ F.oxyj F. oxy F. oxy F.oxy_ F.oxy_ F. oxy_ F. oxy_. F. oxy F. oxy F.oxy_ F. oxy F. oxy F. oxy F. pro F. pro_ F.pro_ F. mon F. mon F. acu F. acu F. acu F. ave F. ave F. ave sa h i l h i 2 h i 3 h i 4 h i 5 h i 6 h i 7 h i 8 h i 9 h i 10 h i l l h i 12 l o l 3 l o l 4 l o l 5 l o l 6 l o l 7 l o l 8 l o l 9 lo20 lo22 lo23 lo24 25 26 27 28 29 30 31 32 34 35 36 CAGCTCGCTTCCAAGGCT CAGCTCGCTTCCAAGGCCGGTAAGTCTTC-CCGCTGGCTTCCAAGGCCGGTAAGTCTTC-CAGCTCGCTTCCAAGGCCGGTAAGTCTTC-CAGCTCGCTTCAAAGGCTGGTAAGTCTTC-CAGCTCGCTTCCAAGGCCGGTAAGTCTTC-CAGCTCGCTTCCAAGGCCGGTAAGTCTTC-CAGCTCGCTTCCAAGGCTGGTAAGTCTTC-CAGCTCGCTTCCAAGGCCGGTAAGTCTTC-CAGCTCGCTTCCAAGGCCGGTAAGTCTTC-CAGCTCGCTTCCAAGGCTGGTAAGTCTTC-CAGCTCGCTTCCAAGGCTGGTAAGTCTTC-CAGCTCGCTTC CAAGGC C GGTAAGT C TT C -CAGCTCGCTTCCAAGGCCGGTAAGTCTTC-CAGCTCGCTTCCAAGGCCGGTAAGTCTTC-CAGC TC GCTTCCAAGGCC GGTAAGTC TT C -CAGCTCGCTTCCAAGGCCGGTAAGTCTTC-CAGCTCGCTTCCAAGGCCGGTAAGTCTTC-CAGCTCGCTTCCAAGGCCGGTAGGTCTTC-CAGCTCGCTTCCAAGGCCGGTAAGTCTTC-CAGCTCGCTTCCAAGGCTGGTAAGTCTTC-CAGCTCGCTTCCAAGGCTGGTAAGTCTTC-CAGCTCGCCAGCAAGGCCTGTAGCTCGCC-CAGCTCGCTTCCAAGGCCGGTAAGTCTTC-CAGCTCGCCTCTAAGGCTGGTAAGTCTTC-CAGCTCGCCTCTAAGGCTGGTAAGTCTTC-CAGCTCGCCTCTAAGGCTGGTAAGTCTTC-- A C C G - C G A C T T T A T C T C G A C G C G A C A C A --ACCGCGGACTTTATCTCGACGCGACACAG - A C C G - C G A C T T T A T C T C G A C G C G A C A C A --ACCGCG-ACTTCAACTCGACGCGACACG-- AC C GAC GAC T T TAT C T C GAC GC GAC AC A -- A C C G - C G A C T T T A T C T C G A C G C G A C A C A --ACCGCG-ACTTCAACTCGACGCGACACG-- AC C GAC GAC T T TAT C T C GAC GC GAC AC A -- C C CAAGGAATT CAT C T C GAC GC GACACAG -ACCGCGGACTTCAACTCGACGCGACACG-- AC C GC G - A C T T CAAC T C GAC GCGAC AC G -- ACC GAGGAC TT CAT C T C GAC GC GACACAG -ACCGAG-ACTTCATCTCGACGCGACACAC - ACC G - C GAC T T TAT C T C GAC GC GACACA-- A C C G - C G A C T T T A T C T C G A C G C G A C A C A -- ACCG-CGAC TTTATC TC GACGCGACACA--ACCGCGGACTTTATCTCGACGCGACACA--ACCAAGGACTTTATCTCGACGCGACACA--ACCGCG-ACTTCATCTCGACGCGACACAC -ACCGCG-ACTTCAACTCGACGCGACACG--ACCGCG-ACTTCAACTCGACGCGACACG--AGCAAGGACTTCATCTCGACGCGACACAG -ACCGCG-ACTTCATCTCGACGCGACACAC - A C C G C G - A C T T C A A C T C G A C G C G T G T C G --ACCGCG-ACTTCAACTCGACGCGACACG-- A C C G C G - A C T T C A A C T C G A C G C G T G T C G -CAGCTCGCTTCCAAGGCTGGTAAGTCTTCTCACCGCG-ACTTCAACCTGACGCGATACG-CAGCTCGCTTCCAAGGCTGGTAAGTCTTCTCACCGCG-ACTTCAACCTGACGCGATACG-C AGC T C GC T T C T AAGGC T GGTAAGTAC C T C AC C GCGAC TT GAC GC GAC AC G -CAGCTCGCTTCTAAGGCTGGTAAGTACCT C AC C GC GAC TT GAC GCGAC AC G -CAGCTCGCTTCTAAGGCTGGTAAGTACCT C ACCGCGACTTGACGCGACACG-CAGCTCGCCTCCAAGGCTGGTAAGTTCCT C AC C GC GAC TT GAC GCGAC AC G -CAGCTCGCTTCAAAGGCTGGTAAGTTCCT C AC C GC GAC T T GAC GC GAC AC G -CAGCTCGCTTCCAAGGCTGGTAAGTTTCT C ACCGCGACTTGACGCGACACG-N. crassa F.oxy_hil F.oxy_hi2 F.oxy_hi3 F.oxy_hi4 F.oxy_hi5 F.oxy_hi6 F.oxy_hi7 F.oxy_hi8 F.oxy_hi9 F.oxy_hil0 F . o x y _ h i l l F. oxy_hil2 F. oxy_lol3 F. oxy_lol4 F. oxy_lol5 F. oxy_lol6 F. oxy_lol7 F. oxy_lol8 F. oxy_lol9 F. oxy_lo20 F. oxy_lo22 C G T C T T G A — C A T C T T G A — C G T C T T G A — C G T C T T G G - -C G T C T T G A - -C G T C T T G A - -C G T C T T G G - -C G T C T T G A - -- G T C T T G A — C G T C T T G G — C G T C T T G G - -C G T C T T G A - -- G T C T T G A — C G T C T T G A - -C G T C T T G A - -C G T C T T G A - -C G T C T T G A - -CGTCTTGA— - G T C T T G A — C G T C T T G G - -C G T C T T G G - -- T AC AT AAAAAAC GT C A-- T AC AT AAAAAAC GT C A-- T AC AT AAAAAAC GT C A--TCCATCAAAAACATCA--TACATAAAAAACGTCA--TACATAAAAAACGTCA--TCCATCAAAAACATCA-- T AC ATAAAAAACGTC A--TATATCAAAAACGTCA-- T C CAT CAAAAAC AT C A--TCCATCAAAAACATCA--TATATCAAAAACGTCA--TATATCAAAAACGTCA-- TACATAAAAAAC GT CA--TACATAAAAAACGTCA--TACATAAAAAACGTCA--TACATAAAAAACGTCA--TACATAAAAAACGTCA--TATATCGAAAACGTCA-- T C CAT CAAAAAC AT C A--TCCATCAAAAACATCA-GCCCGCAAGTC • TAAC TAAC ATCATC AC CAACAGCC CGCAAGTC • T AAC TAAC AT CATC AC CAAC AGC C C GCAAGT C • TAAC TAAC AT CATC AC CAAC AGC C C GC AAGTC • T CAC TAAC TT CATCAC CAATAGC C C GCAAGT C • TAAC TAACAT CATCAC CAACAGC C C GCAAGTC • TAAC TAAC AT CATC AC CAAC AGC C C GCAAGT C • T CAC TAAC TT CAT CAC CAATAGCC C GCAAGTC • TAAC TAAC AT CATC AC CAAC AGC C CGCAAGTC • T C AC TAAC AT CATC AC CAAC AGCC C GCAAGTC - T CAC TAAC TT CAT CAC CAAT AGCC C GCAAGT C - T C AC TAAC TT CAT CAC CAATAGC C CGCAAGTC - T CAC TAAC AT CAT CAC CAAC AGC C CGCAAGTC - T CAC TAAC AT CATC AC CAACAGCC C GCAAGTC - TAAC TAAC AT CATC AC CAAC AGC C C GCAAGT C - TAAC TAACAT CATCAC CAACAGC C C GCAAGT C - TAAC TAAC AT CAT CAC CAAC AGC C C GCAAGTC - TAAC TAAC AT CAT CAC CAAC AGC C CGCAAGTC -TAACTAACATCATCACCAACAGCCCGCAAGTC -TCACTAACATCATCACCAACAGCCCGCAAGTC - T CAC TAAC TT CATCAC CAATAGC C C GCAAGT C -TCACTAACTTCATCACCAATAGCCCGCAAGTC i i i F . o x y _ l o 2 3 CGTCTTGA TAT AT CAAAAACGTC A - T C AC TAAC AT CAT C AC C AAC AGCC C GC AAGTC F . o x y _ l o 2 4 - G T C T T G A TAT AT CAAAAACGTC A - T C AC TAAC AT CAT C AC CAAC AGC C C GCAAGTC F . p r o _ 2 5 — C G T C G G GTAACCAAAAACATGA-CCACTAACTTCATCACCAACAGCCCGCAAGTC F . p r o _ 2 6 - - C G T C G G GTAAC CAAAAACATGA- C C AC TAAC TT C AT C AC CAAC AGC C C GCAAGTC F . p r o _ 2 7 - - C G T C G G GTAAC CAAAAACATGA- C C AC TAAC TT C AT C AC CAAC AGC C C GCAAGTC F . mon_2 8 CGTCTCGG TTCATCAAAAGCATCG-TCACTAACTTTATCACCAACAGCTCGCAAGTC F . mon_29 CGTCTCGG T TC AT CAAAAGC ATC G - T C AC TAAC TT TAT C AC CAAC AGC T C GCAAGTC F . acu_30 CGCCTT TCAATCAAGAACATCACTTACTGACATCGTCCTC AGCCCGCAAGTC F . acu_31 CGCCTT TCAATCAAGAACATCACTTACTGACATCGTCCTC AGCCCGCAAGTC F . acu_32 CGCCTT T C AAT C AAGAAC A T C AC T TAC T GAC AT C GT C C T C AGCCCGCAAGTC F . ave_34 CGCCTT TCAATTAAGAACATCATTTACTGACATCGTCTCC AGCCCGCAAGTC F . ave_35 CGCCTT TCAATCAAGAACATCACTTACTGACTTCGTCTTC AGCTCGCAAGTC F . ave_36 CGCCTT TCAATCAAGAACATCACTTACTGACTTCGTCCTC AGCCCGCAAGTC N . c r a s s a GGCCCCCTCCACCGGCGGTGTCAAGAAGCCCCACCGTTACAAGCCCGGTACCGTCGCTCT F . o x y _ h i 1 CGCCCCCTCTACCGGAGGTGTCAAGAAGCCTCACCGCTATAAGCCTGGTACCGTCGCTCT F . o x y _ h i 2 CGCCCCCTCTACCGGAGGTGTCAAGAAGCCTCACCGCTATAAGCCTGGTACCGTCGCTCT F . o x y _ h i 3 CGCCCCCTCTACCGGAGGTGTCAAGAAGCCTCACCGCTATAAGCCTGGTACCGTCGCTCT F . o x y _ h i 4 CGCCCCCTCTACCGGAGGTGTCAAGAAGCCTCACCGCTACAAGCCCGGTACCGTCGCTCT F . o x y _ h i 5 CGCCCCCTCTACCGGAGGTGTCAAGAAGCCTCACCGCTATAAGCCTGGTACCGTCGCTCT F . o x y _ h i 6 CGCCCCCTCTACCGGAGGTGTCAAGAAGCCTCACCGCTATAAGCCTGGTACCGTCGCTCT F . o x y _ h i 7 CGCCCCCTCTACCGGAGGTGTCAAGAAGCCTCACCGCTACAAGCCCGGTACCGTCGCTCT F . o x y _ h i 8 CGCCCCCTCTACCGGAGGTGTCAAGAAGCCTCACCGCTATAAGCCTGGTACCGTCGCTCT F . o x y _ h i 9 CGCCCCCTCTACCGGAGGTGTCAAGAAGCCTCACCGCTATAAGCCCGGTACCGTCGCTCT F . o x y _ h i 1 0 CGCCCCCTCTACCGGAGGTGTCAAGAAGCCTCACCGCTACAAGCCCGGTACCGTCGCTCT F . o x y _ h i l l CGCCCCCTCTACCGGAGGTGTCAAGAAGCCTCACCGCTACAAGCCCGGTACCGTCGCTCT F . o x y _ h i 1 2 CGCCCCCTCTACCGGAGGTGTCAAGAAGCCTCACCGCTATAAGCCCGGTACCGTCGCTCT F . o x y _ l o l 3 CGCCCCCTCTACCGGAGGTGTCAAGAAGCCTCACCGCTATAAGCCCGGTACCGTCGCTCT F . o x y _ l o l 4 CGCCCCCTCTACCGGAGGTGTCAAGAAGCCTCACCGCTATAAGCCTGGTACCGTCGCTCT F . O X y _ l o l 5 CGCCCCCTCTACCGGAGGTGTCAAGAAGCCTCACCGCTATAAGCCTGGTACCGTCGCTCT F . o x y _ l o l 6 CGCCCCCTCTACCGGAGGTGTCAAGAAGCCTCACCGCTATAAGCCTGGTACCGTCGCTCT F . o x y _ l o l 7 CGCCCCCTCTACCGGAGGTGTCAAGAAGCCTCACCGCTATAAGCCTGGTACCGTCGCTCT F . o x y _ l o l 8 CGCCCCCTCTACCGGAGGTGTCAAGAAGCCTCACCGCTATAAGCCTGGTACCGTCGCTCT F . o x y _ l o l 9 CGCCCCCTCTACCGGAGGTGTCAAGAAGCCTCACCGCTATAAGCCCGGTACCGTCGCTCT F . o x y _ l o 2 0 CGCCCCCTCTACCGGAGGTGTCAAGAAGCCTCACCGCTACAAGCCCGGTACCGTCGCTCT F . o x y _ l o 2 2 CGCCCCCTCTACCGGAGGTGTCAAGAAGCCTCACCGCTACAAGCCCGGTACCGTCGCTCT F . o x y _ l o 2 3 CGCCCCCTCTACCGGAGGTGTCAAGAAGCCTCACCGCTATAAGCCCGGTACCGTCGCTCT F . o x y _ l o 2 4 CGCCCCCTCTACCGGAGGTGTCAAGAAGCCTCACCGCTATAAGCCCGGTACCGTCGCTCT F . p r o _ 2 5 CGCCCCCTCTACCGGAGGTGTCAAGAAGCCTCACCGCTACAAGCCCGGTACCGTCGCTCT F . p r o _ 2 6 CGCCCCCTCTACCGGAGGTGTCAAGAAGCCTCACCGCTACAAGCCCGGTACCGTCGCTCT F . p r o _ 2 7 CGCCCCCTCTACCGGAGGTGTCAAGAAGCCTCACCGCTACAAGCCCGGTACCGTCGCTCT F .mon_2 8 CGCCCCCTCCACCGGAGGTGTCAAGAAGCCTCACCGCTACAAGCCCGGTACCGTCGCTCT F .mon_2 9 CGCCCCCTCCACCGGAGGTGTCAAGAAGCCTCACCGCTACAAGCCCGGTACCGTCGCTCT F . a c u _ 3 0 CGCCCCGTCTACCGGTGGTGTCAAGAAGCCTCACCGCTACAAGCCTGGTACCGTCGCTCT F . a c u _ 3 1 CGCCCCGTCTACCGGTGGTGTCAAGAAGCCTCACCGCTACAAGCCTGGTACCGTCGCTCT F . a c u _ 3 2 CGCCCCGTCTACCGGTGGTGTCAAGAAGCCTCACCGCTACAAGCCTGGTACCGTCGCTCT F . a v e _ 3 4 CGCCCCGTCTACCGGTGGTGTCAAGAAGCCTCACCGCTACAAGCCCGGTACCGTCGCTCT F . a v e _ 3 5 CGCCCCATCTACCGGTGGTGTCAAGAAGCCTCACCGCTACAAGCCCGGTACCGTCGCTCT F . a v e _ 3 6 CGCCCC GTCTAC CGGTGGTGTCAAGAAGC CTCACCGCTACAAGC CC GGTACCGTC GCTCT N . c r a s s a CCGTGAGATTCGTCGCTACCAGAAGTCCACTGAGCTTCTGATCCGCAAGCTCCCCTTCCA F . o x y _ h i 1 CCGTGAGATTCGACGATACCAGAAGTCGACCGAGCTCCTCATCCGAAAGCTCCCCTTCCA F . o x y _ h i 2 CCGTGAGATTCGACGATACCAGAAGTCGACCGAGCTCCTCATCCGAAAGCTCCCCTTCCA F . o x y _ h i 3 CCGTGAGATTCGACGATACCAGAAGTCGACCGAGCTCCTCATCCGAAAGCTCCCCTTCCA F . o x y _ h i 4 CCGTGAGATTCGACGATACCAGAAGTCGACTGAGCTCCTTATCCGAAAGCTCCCCTTCCA F . o x y _ h i 5 CCGTGAGATTCGACGATACCAGAAGTCGACCGAGCTCCTCATCCGAAAGCTCCCCTTCCA F . o x y _ h i 6 CCGTGAGATTCGACGATACCAGAAGTCGACCGAGCTCCTCATCCGAAAGCTCCCCTTCCA F . o x y _ h i 7 CCGTGAGATTCGACGATACCAGAAGTCGACTGAGCTCCTTATCCGAAAGCTCCCCTTCCA F . o x y _ h i 8 CCGTGAGATTCGACGATACCAGAAGTCGACCGAGCTCCTCATCCGAAAGCTCCCCTTCCA F . o x y _ h i 9 CCGTGAGATTCGACGATACCAGAAGTCGACCGAGCTCCTCATCCGAAAGCTCCCCTTCCA F . o x y _ h i 1 0 CCGTGAGATTCGACGATACCAGAAGTCGACTGAGCTCCTTATCCGAAAGCTCCCCTTCCA 119 F.oxy_hill CCGTGAGATTCGACGATACCAGAAGTCGACTGAGCTCCTTATCCGAAAGCTCCCCTTCCA F.oxy_hi12 CCGTGAGATTCGACGATACCAGAAGTCGACCGAGCTCCTCATCCGAAAGCTCCCCTTCCA F.oxy_lol3 CCGTGAGATTCGACGATACCAGAAGTCGACCGAGCTCCTCATCCGAAAGCTCCCCTTCCA F.oxy_lol4 CCGTGAGATTCGACGATACCAGAAGTCGACCGAGCTCCTCATCCGAAAGCTCCCCTTCCA F.oxy_lol5 CCGTGAGATTCGACGATACCAGAAGTCGACCGAGCTCCTCATCCGAAAGCTCCCCTTCCA F.oxy_lol6 CCGTGAGATTCGACGATACCAGAAGTCGACCGAGCTCCTCATCCGAAAGCTCCCCTTCCA F.oxy_lol7 CCGTGAGATTCGACGATACCAGAAGTCGACCGAGCTCCTCATCCGAAAGCTCCCCTTCCA F.oxy_lol8 CCGTGAGATTCGACGATACCAGAAGTCGACCGAGCTCCTCATCCGAAAGCTCCCCTTCCA F.oxy_lol9 CCGTGAGATTCGACGATACCAGAAGTCGACCGAGCTCCTCATCCGAAAGCTCCCCTTCCA F.oxy_lo2 0 CCGTGAGATTCGACGATACCAGAAGTCGACTGAGCTCCTTATCCGAAAGCTCCCCTTCCA F.oxy_lo22 CCGTGAGATTCGACGATACCAGAAGTCGACTGAGCTCCTTATCCGAAAGCTCCCCTTCCA F.oxy_lo23 CCGTGAGATTCGACGATACCAGAAGTCGACCGAGCTCCTCATCCGAAAGCTCCCCTTCCA F.oxy_lo2 4 CCGTGAGATTCGACGATACCAGAAGTCGACCGAGCTCCTCATCCGAAAGCTCCCCTTCCA F.pro_25 CCGTGAGATTCGACGATACCAGAAGTCGACCGAGCTCCTCATCCGAAAGCTCCCCTTCCA F.pro_2 6 CCGTGAGATTCGACGATACCAGAAGTCGACCGAGCTCCTCATCCGAAAGCTCCCCTTCCA F.pro_27 CCGTGAGATTCGACGATACCAGAAGTCGACCGAGCTCCTCATCCGAAAGCTCCCCTTCCA F.mon_2 8 CCGTGAGATTCGACGATACCAGAAGTCGACTGAGCTCCTCATCCGAAAGCTCCCCTTCCA F.mon_2 9 CCGTGAGATTCGACGATACCAGAAGTCGACTGAGCTCCTCATCCGAAAGCTCCCCTTCCA F.acu_30 CCGTGAGATTCGACGATACCAGAAGTCCACCGAGCTTCTCATCCGAAAGCTCCCCTTCCA F.acu_31 CCGTGAGATTCGACGATACCAGAAGTCCACCGAGCTTCTCATCCGAAAGCTCCCCTTCCA F.acu_32 CCGTGAGATTCGACGATACCAGAAGTCCACCGAGCTTCTCATCCGAAAGCTCCCCTTCCA F.ave_3 4 CCGTGAGATTCGACGATACCAGAAGTCCACCGAGCTTCTCATCCGAAAGCTCCCCTTCCA F.ave_35 CCGTGAGATTCGACGATACCAGAAGTCCACCGAGCTTCTCATCCGAAAGCTCCCCTTCCA F. ave 36 CCGTGAGATTCGACGATACCAGAAGTCCACCGAGCTTCTCATCCGAAAGCTCCCCTTCCA N crassa GCGTCTCGTAAGTTTATGATGCCTGTCCCCAACATGTCACTTTCCTTTCACGT-TGCTAA F oxy h i l GCGTCTGGTGAGCAC- — - C AC C AAT AT AC AT C--AATCAAC---ACTTGACATATACTAA F oxy "hi 2 GCGTCTGGTGAGCAC- — -CACCAATATACATC--AATCAAC— -ACTT GACATATACTAA F oxy "hi 3 GC GT CTGGTGAGCAC-— -CACCAATATACATC--AATCAAC---ACTTGACATATACTAA F oxy "hi 4 GCGTCTGGTAAGCAC- — -CACCCAT-TGCATC--AATCATC---ACTTGACACATACTAA F oxy "hi 5 GCGTCTGGTGAGCAC- — -CACCAATATACATC--AATCAAC— -ACTTGACATATACTAA F oxy "hi 6 GCGTCTGGTGAGCAC- — -CACCAATATACATC--AATCAAC---ACTTGACATATACTAA F oxy "hi 7 GCGTCTGGTAAGCAC- — -CACCCAT-TGCATC--AATCATC---ACTTGACACATACTAA F oxy h i 8 GCGTCTGGTGAGCAC- — -CACCAATATACATC--AATCAAC— -ACTTGACATATACTAA F oxy "hi 9 GCGCCTGGTGAGCAT- — -CACCAATATACATC--AACCATC— - CATTGACATATACTAA F oxy "hi 10 GCGTCTGGTAAGCAC- — -CACCCAT-TGCATC--AATCATC---ACTTGACACATACTAA F oxy " h i l l GCGTCTGGTAAGCAC- — -CACCCAT-TGCATC--AATCATC---ACTTGACACATACTAA F oxy "hi 12 GCGCCTGGTGAGCAT- — -CACCAATATACATC--AACCATC--- CATTGACATATACTAA F oxy "lol3 GCGCCTGGTGAGCAC- — -CACCAATATACATC--AACCATC--- CATTGACATATACTAA F oxy_ "lol4 GCGTCTGGT GAGCAC-— -CACCAATATACATC--AATCAAC— -ACTTGACATATACTAA F oxy "lol5 GC GT C T GGTGAGCAC-— -CACCAATATACAT C -AATCAAC---ACTTGACATATACTAA F oxy_ "lol6 GC GT C T GGTGAGCAC-— -CACCAATATACATC--AATCAAC---ACTTGACATATACTAA F oxy_ "lol7 GCGTCTGGTGAGCAC- — -CAC CAATATACATC -AATCAAC— -ACTTGACATATACTAA F oxy "lol8 GCGTCTGGTGAGCAC- — -CAC CAATATACAT C -AATCAAC— -ACTTGACATATACTAA F oxy "lol9 GCGCCTGGTGAGCAT- — -CACCAATATACATC--AACCATC---CATTGACATATACTAA F oxy "lo20 GC GT C T GGTAAGCAC-— -CACCCAT-TGCATC -AATCATC---ACTTGACACATACTAA F oxy lo22 GCGTCTGGTAAGCAC- — -CACCCAT-TGCATC -AATCATC— -ACTTGACACATACTAA F oxy "lo23 GCGCCTGGTGAGCAT- — -CAC CAATATACATC -AACCATC— -CATT GACATATACTAA F oxy "lo24 GCGCCTGGTGAGCAT- — -CACCAATATACATC -AACCATC---CATTGACATATACTAA F pro "25 GCGTCTGGTAAGCAT-— -CACCTGC-TACATT -CGTCACC— -GCTTGACGCATACTAA F pro 26 GC GT C T GGTAAGCAT-— -CACCTGC-TACATT -CGTCACC---GCTTGACGCATACTAA F pro 27 GCGTCTGGTAAGCAT-— -CACCTGC-TACATT -CGTCACC— -GCTTGACGCATACTAA F mon 28 GCGTCTGGTAAGCGC- — -CACCTGC-TTCATC -AACCACA---GCCT GACACATACTAA F mon 29 GCGTCTGGTAAGCGC- — -CACCTGC-TTCATC -AACCACA--- GCCTGACACATACTAA F acu 30 GC GT C T C GTAAGCAC-— -CGCC-ATATTTATT -CAACACGTTGCCTCAACATCTGCTAA F acu 31 GC GT C T C GTAAGCAC-— -CGCC-ATATTTATT -CAACACGTTGCCTCAACATCTGCTAA F acu 32 GC GT C T C GTAAGCAC-— -CGCC-ATATTTATT - CAAC AC GT T GC C TC AAC AT C T GC TAA F ave_ 34 GC GT C T C GTAAGCAT-— -CACC-ACATGAAC--CAACACGTTGTCTCAACATCTGCTAA F ave 35 GCGTCTCGTAAGCAT-— -CACC-GCATGAAC--CAACACATTGTCTCAACATCTGCTAA F ave 36 GCGTCTCGTAAGCAC-— -CACC-GCATTTACT -CAACACGTCGTCTCAACATCCGCTAA 120 N.crassa CGCGTCGCTACCCAGGTCCGTGAGATTGCCCAGGACTTCAAGTCCGACCTCCGCTTCCAG F.oxy_hi1 CATGAGACAAAC-AGGTTCGTGAGATTGCCCAGGACTTCAAGTCTGATCTCCGCTTCCAG F.oxy_hi2 CATGAGACAAAC-AGGTTCGTGAGATTGCCCAGGACTTCAAGTCTGATCTCCGCTTCCAG F.oxy_hi3 CATGAGACAAAC-AGGTTCGTGAGATTGCCCAGGACTTCAAGTCTGATCTCCGCTTCCAG F.oxy_hi 4 CATTCGACAAAC-AGGTCCGTGAGATTGCCCAGGACTTCAAGTCTGATCTCCGCTTCCAG F.oxy_hi 5 CATGAGACAAAC-AGGTTCGTGAGATTGCCCAGGACTTCAAGTCTGATCTCCGCTTCCAG F.oxy_hi 6 CATGAGACAAAC-AGGTTCGTGAGATTGCCCAGGACTTCAAGTCTGATCTCCGCTTCCAG F.oxy_hi7 CATTCGACAAAC-AGGTCCGTGAGATTGCCCAGGACTTCAAGTCTGATCTCCGCTTCCAG F.oxy_hi 8 CATGAGACAAAC-AGGTTCGTGAGATTGCCCAGGACTTCAAGTCTGATCTCCGCTTCCAG F.oxy_hi 9 CATGAGACAAAC-AGGTTCGTGAGATTGCCCAGGACTTCAAGTCTGATCTCCGCTTCCAG F.oxy_hi10 CATTCGACAAAC-AGGTCCGTGAGATTGCCCAGGACTTCAAGTCTGATCTCCGCTTCCAG F.oxy_hi11 CATTCGACAAAC-AGGTCCGTGAGATTGCCCAGGACTTCAAGTCTGATCTCCGCTTCCAG F.oxy_hi12 CATGAGACAAAC-AGGTTCGTGAGATTGCCCAGGACTTCAAGTCTGATCTCCGCTTCCAG F.oxy_lol3 CATGAGACAAAC-AGGTTCGTGAGATTGCCCAGGACTTCAAGTCTGATCTCCGCTTCCAG F.oxy_lol4 CATGAGACAAAC-AGGTTCGTGAGATTGCCCAGGACTTCAAGTCTGATCTCCGCTTCCAG F.oxy_lol5 CATGAGACAAAC-AGGTTCGTGAGATTGCCCAGGACTTCAAGTCTGATCTCCGCTTCCAG F.oxy_lol6 CATGAGACAAAC-AGGTTCGTGAGATTGCCCAGGACTTCAAGTCTGATCTCCGCTTCCAG F.oxy_lol7 CATGAGACAAAC-AGGTTCGTGAGATTGCCCAGGACTTCAAGTCTGATCTCCGCTTCCAG F.oxy_lol8 CATGAGACAAAC-AGGTTCGTGAGATTGCCCAGGACTTCAAGTCTGATCTCCGCTTCCAG F.oxy_lol9 CATGAGACAAAC-AGGTTCGTGAGATTGCCCAGGACTTCAAGTCTGATCTCCGCTTCCAG F.oxy_lo20 CATTCGACAAAC-AGGTCCGTGAGATTGCCCAGGACTTCAAGTCTGATCTCCGCTTCCAG F.oxy_lo22 CATTCGACAAAC-AGGTTCGTGAGATTGCCCAGGACTTCAAGTCTGATCTCCGCTTCCAG F.oxy_lo23 CATGAGACAAAC-AGGTTCGTGAGATTGCCCAGGACTTCAAGTCTGATCTCCGCTTCCAG F.oxy_lo2 4 CATGAGACAAAC-AGGTTCGTGAGATTGCCCAGGACTTCAAGTCTGATCTCCGCTTCCAG F.pro_25 CATTCGACGAAC-AGGTTCGTGAGATTGCCCAGGACTTCAAGTCTGATCTCCGCTTCCAG F.pro_2 6 CATTCGACGAAC-AGGTTCGTGAGATTGCCCAGGACTTCAAGTCTGATCTCCGCTTCCAG F.pro_27 CATTCGACGAAC-AGGTTCGTGAGATTGCCCAGGACTTCAAGTCTGATCTCCGCTTCCAG F.mon_28 CACTTGGTAAAC-AGGTCCGTGAGATCGCCCAGGACTTCAAGTCTGATCTCCGCTTCCAG F.mon_29 CACTTGGTAAAC-AGGTCCGTGAGATCGCCCAGGACTTCAAGTCTGATCTCCGCTTCCAG F. acu_30 CATACCCCGCAC-AGGTCCGTGAGATTGCACAGGACTTCAAGTCTGATCTCCGATTCCAG F. acu_31 CATACCCCGCAC-AGGTCCGTGAGATTGCACAGGACTTCAAGTCTGATCTCCGATTCCAG F. acu_32 CATACCCCGCAC-AGGTCCGTGAGATTGCACAGGACTTCAAGTCTGATCTCCGATTCCAG F.ave_34 CATACCACGAAC-AGGTCCGTGAGATTGCCCAGGACTTCAAGTCTGATCTCCGATTCCAG F.ave_35 CATGTCAC GAAC-AGGTC CGTGAGATTGCCCAGGAC TTCAAGTC TGAT CTCC GATTCC AG F.ave_3 6 CATACCCCGAAC-AGGTCCGTGAGATTGCCCAGGACTTCAAGTCTGATCTCCGATTCCAG N.crassa F.oxy_hil F.oxy_hi2 F. oxy_l F. oxy_ F. oxy F. oxy F. oxy_ F. oxy_hi h i 3 'hi 4 "hi 5 'hi 6 "hi 7 F. oxy F. oxy_: F. oxy_! F. oxy F. oxy_: hi 9 "hi 10 " h i l l 'hi 12 "lol3 F. oxy_ F. oxy_ 'lol4 "lol5 F. oxy_lol6 F. oxy_lol7 lol 8 l o l 9 'lo20 lo22 lo23 lo24 25 2 6 F. oxy_ F. oxy F. oxy F. oxy_ oxy_ oxy_ pro_ pro_ AGCTCTGCCATCGGCCTCCTCCAGGAGTCCGTCGAGTCTTACCTCGTCTCTCTCTTCGAG TCTTCTGCCATCGGTGCTCTCCAGGAGTCCGTTGAGTCCTACCTCGTCTCCCTCTTCGAG TCTTCTGCCATCGGTGCTCTCCAAGAGTCCGTTGAGTCCTACCTCGTCTCCCTCTTCGAG TCTTCTGCCATCGGTGCTCTCCAGGAGTCCGTTGAGTCCTACCTCGTCTCCCTCTTCGAG TCTTCTGCCATCGGTGCTCTCCAGGAGTCCGTCGAGTCTTACCTCGTCTCACTCTTCGAG TCTTCTGCCATCGGTGCTCTCCAGGAGTCCGTTGAGTCCTACCTCGTCTCCCTCTTCGAG TCTTCTGCCATCGGTGCTCTCCAGGAGTCCGTTGAGTCCTACCTCGTCTCCCTCTTCGAG TCTTCTGCCATCGGTGCTCTCCAGGAGTCCGTCGAGTCTTACCTCGTCTCACTCTTCGAG TCTTCTGCCATCGGTGCTCTCCAGGAGTCCGTTGAGTCCTACCTCGTCTCCCTCTTCGAG TCTTCTGCCATCGGTGCTCTCCAGGAGTCCGTTGAGTCCTACCTCGTCTCCCTCTTCGAA TCTTCTGCCATCGGTGCTCTCCAGGAGTCCGTCGAGTCTTACCTCGTCTCACTCTTCGAG TCTTCTGCCATCGGTGCTCTCCAGGAGTCCGTCGAGTCTTACCTCGTCTCACTCTTCGAG TCTTCTGCCATCGGTGCTCTCCAGGAGTCCGTTGAGTCCTACCTCGTCTCCCTCTTCGAG TCTTCTGCCATCGGTGCTCTCCAGGAGTCCGTTGAGTCCTACCTCGTCTCCCTCTTCGAG TCTTCTGCCATCGGTGCTCTCCAGGAGTCCGTTGAGTCCTACCTCGTCTCCCTCTTCGAG TCTTCTGCCATCGGTGCTCTCCAGGAGTCCGTTGAGTCCTACCTCGTCTCCCTCTTCGAG TCTTCTGCCATCGGTGCTCTCCAGGAGTCCGTTGAGTCCTACCTCGTCTCCCTCTTCGAG TCTTCTGCCATCGGTGCTCTCCAGGAGTCCGTTGAGTCCTACCTCGTCTCCCTCTTCGAG TCTTCTGCCATCGGTGCTCTCCAGGAGTCCGTTGAGTCCTACCTCGTCTCCCTCTTCGAG TCTTCTGCCATCGGTGCTCTCCAGGAGTCCGTTGAGTCCTACCTCGTCTCCCTCTTCGAG TCTTCTGCCATCGGTGCTCTCCAGGAGTCCGTCGAGTCTTACCTCGTCTCACTCTTCGAG TCTTCTGCCATCGGTGCTCTCCAGGAGTCCGTCGAATCTTACCTCGTCTCACTCTTCGAG TCTTCTGCCATCGGTGCTCTCCAGGAGTCCGTTGAGTCCTACCTCGTCTCCCTCTTCGAG TCTTCTGCCATCGGTGCTCTCCAGGAGTCCGTTGAGTCCTACCTCGTCTCCCTCTTCGAG TCTTCCGCCATCGGTGCTCTCCAGGAGTCCGTCGAGTCCTACCTCGTCTCCCTCTTTGAA TCTTCCGCCATCGGTGCTCTCCAGGAGTCTGTCGAGTCCTACCTCGTCTCCCTCTTTGAA 121 F.pro_27 TCTTCCGCCATCGGTGCTCTCCAGGAGTCCGTCGAGTCCTACCTCGTCTCCCTCTTTGAA F.mon_2 8 TCTTCTGCCATCGGTGCTCTCCAGGAGTCCGTCGAGTCTTACCTCGTCTCCCTCTTCGAG F.mon_29 TCTTCTGCCATCGGTGCTCTCCAGGAGTCCGTCGAGTCTTACCTCGTCTCCCTCTTCGAG F.acu_30 TCTTCCGCCATCGGTGCTCTTCAGGAGTCCGTCGAGTCTTACCTCGTCTCCCTCTTCGAG F.acu_31 TCTTCCGCCATCGGTGCTCTTCAGGAGTCCGTCGAGTCTTACCTCGTCTCCCTCTTCGAG F.acu_32 TCTTCCGCCATCGGTGCTCTTCAGGAGTCCGTCGAGTCTTACCTCGTCTCCCTCTTCGAG F.ave_34 TCTTCCGCTATCGGTGCTCTCCAGGAGTCCGTCGAGTCCTACCTCGTCTCCCTCTTCGAG F.ave_3S TCTTCCGCTATCGGTGCCCTCCAGGAGTCCGTCGAGTCCTACCTCGTCTCCCTCTTCGAG F.ave 36 TCTTCCGCCATCGGTGCTCTTCAGGAGTCCGTCGAGTCTTACCTCGTCTCCCTCTTCGAG N. crassa GACACCAACCTCTGCGCTATCCACGCTAAGCGTGTCACCATCCAGAGCAAGGACATCCAG F. oxy_hi 1 GACACCAACCTCTGCGCCATCCATGCCAAGCGTGTCACCATCCAATCCAAGGACATCCAG F.oxy_hi 2 GACACCAACCTCTGCGCCATCCATGCCAAGCGTGTCACCATCCAATCCAAGGACATCCAG F. oxy_hi3 GACACCAACCTCTGCGCCATCCATGCCAAGCGTGTCACCATCCAATCCAAGGACATCCAG F. oxy_hi 4 GACACCAACCTCTGCGCCATCCACGCCAAGCGTGTCACCATCCAGTCCAAGGACATCCAG F.oxy_hi 5 GACACCAACCTCTGCGCCATCCATGCCAAGCGTGTCACCATCCAATCCAAGGACATCCAG F.oxy_hi 6 GACACCAACCTCTGCGCCATCCATGCCAAGCGTGTCACCATCCAATCCAAGGACATCCAG F . oxy_hi7 GACACCAACCTCTGCGCCATCCACGCCAAGCGTGTCACCATCCAGTCCAAGGACATCCAG F . oxy_hi 8 GACACCAACCTCTGCGCCATCCATGCCAAGCGTGTCACCATCCAATCCAAGGACATCCAG F . oxy_hi9 GAAACAAACCTCTGCGCCATCCACGCCAAGCGTGTCACCATCCAATCCAAGGACATCCAG F.oxy_hi10 GACACCAACCTCTGCGCCATCCACGCCAAGCGTGTCACCATCCAGTCCAAGGACATCCAG F . oxy_hi 11 GACACCAACCTCTGCGCCATCCACGCCAAGCGTGTCACCATCCAGTCCAAGGACATCCAG F.oxy_hi12 GACACCAACCTCTGCGCCATCCACGCCAAGCGTGTCACCATCCAATCCAAGGACATCCAG F. oxy_lol3 GACACCAACCTCTGCGCCATCCACGCCAAGCGTGTCACCATCCAATCCAAGGACATCCAG F. oxy_lol4 GAC AC CAAC C T C T GCGCC AT C CAT GC C AAGC GTGTC AC CAT C C AAT C C AAGGAC AT C C AG F. oxy_lol5 GACACCAACCTCTGCGCCATCCATGCCAAGCGTGTCACCATCCAATCCAAGGACATCCAG F. oxy_lol6 GACACCAACCTCTGCGCCATCCATGCCAAGCGTGTCACCATCCAATCCAAGGACATCCAG F. oxy_lol7 GACACCAACCTCTGCGCCATCCATGCCAAGCGTGTCACCATCCAATCCAAGGACATCCAG F. oxy_lol8 GACACCAACCTCTGCGCCATCCATGCCAAGCGTGTCACCATCCAATCCAAGGACATCCAG F. oxy_lol9 GACACCAACCTCTGCGCCATCCACGCCAAGCGTGTCACCATCCAATCCAAGGACATCCAG F. oxy_lo20 GACACCAACCTCTGCGCCATCCACGCCAAGCGTGTCACCATCCAGTCCAAGGACATCCAG F. oxy_lo22 GACACCAACCTCTGCGCCATCCACGCCAAGCGTGTCACCATCCAGTCCAAGGACATCCAG F . oxy_lo23 GACACCAACCTCTGCGCCATCCACGCCAAGCGTGTCACCATCCAATCCAAGGACATCCAG F. oxy_lo2 4 GACACCAACCTCTGCGCCATCCACGCCAAGCGTGTCACCATCCAATCCAAGGACATCCAG F.pro_2 5 GACACCAATCTCTGTGCCATCCACGCCAAGCGTGTCACCATCCAATCCAAGGACATCCAG F.pro_2 6 GACACCAACCTCTGTGCCATCCACGCCAAGCGTGTCACCATCCAATCCAAGGACATCCAG F.pro_27 GACACCAATCTCTGTGCCATCCACGCCAAGCGTGTCACCATCCAATCCAAGGACATCCAG F.mon_2 8 GACACCAACCTCTGCGCCATCCATGCGAAGCGTGTTACCATCCAGTCAAAGGACATCCAG F.mon_2 9 GACACCAACCTCTGCGCCATCCATGCGAAGCGTGTTACCATCCAGTCAAAGGACATCCAG F . acu_30 GATACCAACCTCTGCGCCATCCACGCCAAGCGTGTCACCATCCAATCCAAGGACATCCAG F. acu_31 GATACCAACCTCTGCGCCATCCACGCCAAGCGTGTCACCATCCAATCCAAGGACATCCAG F.acu_32 GATACCAACCTCTGCGCCATCCACGCCAAGCGTGTCACCATCCAATCCAAGGACATCCAG F.ave_3 4 GATACCAACCTCTGCGCCATCCACGCCAAGCGTGTCACCATCCAGTCCAAGGACATCCAG F. ave_35 GATACCAACCTCTGCGCCATCCACGCCAAGCGTGTCACCATCCAGTCCAAGGACATCCAG F. ave 36 GATACCAACCTTTGCGCCATCCACGCCAAGCGTGTCACCATCCAGTCCAAGGACATCCAG N.crassa F.oxy_hil F.oxy_hi2 F.oxy_hi3 F.oxy_hi4 F.oxy_hi5 F.oxy_hi6 F.oxy_hi7 F.oxy_hi8 F.oxy_hi9 F.oxy_hil0 F.oxy_hill F.oxy_hil2 F.oxy_lol3 F.oxy_lol4 CTCGCCCG CTCGCCCG CTCGCCCG CTCGCCCG CTCGCCCG CTCGCCCG CTCGCCCG CTCGCCCG CTCGCCCG CTCGCCCG CTCGCCCG CTCGCCCG CTCGCCCG CTCGCCCG CTCGCCCG F.oxy_lol5 F.oxy_lol6 F.oxy_lol7 F.oxy_lol8 F.oxy_lol9 F.oxy_lo20 F.oxy_lo22 F.oxy_lo23 F.oxy_lo24 F.pro_25 F.pro_26 F.pro_27 F.mon_28 F.mon_29 F.acu_30 F.acu_31 F. acu_32 F.ave_3 4 F.ave_35 F.ave 3 6 CTCGCCCG CTCGCCCG CTCGCCCG CTCGCCCG CTCGCCCG CTCGCCCG CTCGCCCG CTCGCCCG CTCGCCCG CTCGCCCG CTCGCCCG CTCGCCCG CTCGCCCG CTCGCCCG CTCGCCCG CTCGCCCG CTCGCCCG CTCGCCCG CTCGCCCG CTCGCCCG 

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