CSIRO PUBLISHING Australasian Plant Pathology, 2010, 39, 508–516 www.publish.csiro.au/journals/app

Genetic variation in Spilocaea oleagina populations from New Zealand olive groves

Friday O. Obanor A,B,C,D, Monika Walter B, E. Eirian Jones A, Judith Candy A and Marlene V. Jaspers A

AEcology Department, Faculty of Agriculture and Life Sciences, Lincoln University, Canterbury, New Zealand. BThe New Zealand Institute for Plant and Food Research Limited (Plant and Food Research), Canterbury Research Centre, PO Box 5, Lincoln 7640, New Zealand. CPresent address: CSIRO Plant Industry, 306 Carmody Road, St Lucia, Qld 4067, Australia. DCorresponding author. Email: [email protected]

Abstract. Olive leaf spot caused by the fungus, Spilocaea oleagina, is the most important leaf disease of olives in many olive-growing regions worldwide with yield losses of up to 20%. The genetic structure of S. oleagina populations was investigated with universally primed-polymerase chain reaction (UP-PCR) techniques. Ninety-eight S. oleagina isolates were collected from 12 known and 4 unknown cultivars from olive groves in five New Zealand regions. UP-PCR profiles based on 159 markers were used to compute genetic distances between pairs of individuals. Low levels of gene and genotypic diversity were detected in all populations, with 76% of the loci being polymorphic and with Nei’s diversity indices ranging from 0.0234 to 0.1393. Analysis of molecular variance showed small but significant (P = 0.001) variations among regions, although most of the molecular variability (87%) was found within populations. Clustered analysis showed no evidence of grouping according to geographic origin of the isolates. The low level of genetic diversity found within and among populations indicates that reproduction for this fungus is predominantly by asexual means and that any effective control strategies are likely to be useful in all or most New Zealand olive groves.

Additional keywords: Cycloconium oleagina, diversity, peacock spot.

Introduction leaves in winter, the main source of S. oleagina inoculum for Olive leaf spot (OLS), also called peacock spot, is caused by the primary infection in spring is the fresh sporulation from existing fungus, Spilocaea oleagina, Castagne (Hughes) (syn. leaf lesions (Guechi and Girre 1994). It has also been suggested Cycloconium oleagina). OLS is the most important leaf that fallen diseased leaves may contribute to new infections of disease of olive in many olive-growing countries such as Italy, OLS, with recommendations in France to collect and burn fallen Spain, the USA, South America, Australia, and New Zealand leaves (Bernès 1923); however, there is little evidence for fallen (Graniti 1993; Shabi et al. 1994; Teviotdale and Sibbett 1995; leaves being a significant source of inoculum. MacDonald et al. 2000). Since OLS has been known for over a The genetic diversity of a pathogen population is influenced by century in the Mediterranean countries of Italy, Spain, Israel and the relative contribution of asexual and sexual reproduction to Greece, which were the main sources of present day cultivated inoculum source of the pathogen. Generally, less genotypic olive trees in New Zealand, it is likely that they were the source of diversity is to be expected if asexually derived spores are the this pathogen. The disease causes severe defoliation resulting in main inoculum source, than if sexual spores are the main source of both reduced flower bud differentiation and fruit set in inoculum. This was demonstrated in a USA study that used subsequent years (Shabi et al. 1994). Between 1941 and 1949 isozyme markers to compare asexual and sexual reproduction severe outbreaks of OLS in California resulted in estimated yield in Puccinia graminis populations (Burdon and Roelfs 1985). The losses of up to 20% (Wilson and Ogawa 1979). authors reported very high genetic diversity in the sexual Lesions produced by the fungus are usually found on the upper populations, whereas there was a restricted array of isozyme surface of the leaf and are muddy green to almost black circular genotypes within the asexual population. The existence of a spots (Graniti 1993). Occasionally, under very wet conditions, sexual stage of S. oleagina has not been reported, and thus the small, sunken brown lesions can be found on the petioles, fruit role of sexual reproduction in the infection process of this peduncles and fruit. Once trees are infected, local spread of the pathogen remains unknown. fungus is by conidia being rain-splashed (Wilson and Miller Pathogen populations constantly adapt to changes in their 1949; Tenerini 1964; Laviola 1968) or carried by insects and wind environment in ways that may affect their ability to cause disease (De Marzo et al. 1993; Lops et al. 1993). Since olives retain their or to survive. In agricultural ecosystems, selection pressures that

Australasian Plant Pathology Society 2010 10.1071/AP10013 0815-3191/10/060508 Genetic diversity of Spilocaea oleagina Australasian Plant Pathology 509 may affect success of pathogens include environmental changes, Materials and methods resistant plant varieties, applications of fungicides and fertilisers, Production of single-spore cultures and DNA extraction irrigation and crop rotation. Genotypic diversity that results from Ninety-eight isolates of S. oleagina representing 19 populations recombination during sexual reproduction can allow sexual (Table 1) were collected from 12 known and 4 unknown olive populations to be selected more rapidly, in response to cultivars in groves under organic or conventional olive selection pressures imposed by fungicides or resistant production systems in five regions in New Zealand (Fig. 1). cultivars, than asexual populations (McDonald 1997). A population was defined as a group of S. oleagina isolates MacHardy (1996) reported that for the closely related apple obtained from a single olive grove and separated from other scab pathogen, Venturia inaequalis, which reproduces grovesby at least 5km apart. Leaveswith sporulating lesions were sexually, the repeated use of fungicides, resulted in the collected from trees chosenat randomat least 10m apart, selecting emergence of new genotypic isolates that were fungicide only one lesion per tree to reduce the likelihood of clones. The resistant. A genetically diverse pathogen population could leaves were dried for 3 days on the bench at room temperature and develop resistance to a particular control measure more then stored at 4 C until required for producing the single-spore quickly than a homogeneous population making it necessary isolates, which were grown on chlortetracycline-amended olive to adopt a more integrated pest management system. An leaf extract agar (OLE) at 15 C and in the dark for 3–6 months investigation into genetic diversity of S. oleagina populations (Obanor et al. 2008). Approximately 0.25 g of mycelium was may improve current understanding of the potential outcomes that excised from cultures of each New Zealand isolate and placed in may be associated with its genetic variability. An important first PowerBead tubes (MO BIO Laboratories, Inc., Solana Beach, step is to study the genetic structure of isolates of S. oleagina. CA, USA). Total genomic DNA was extracted using a PowerSoil Although S. oleagina was first described by Boyer in 1891 DNA kit (MO BIO Laboratories, Inc.), according to the (Miller 1949), very little is known about the genetics of the manufacturer’s instructions. Total genomic DNA was also pathogen itself, probably due to its inability to sporulate in extracted from the mycelium of one isolate of V. inaequalis culture. Recently, the DNA sequences of the 18S 5.8S and for comparison. 28S rDNA genes (rDNA), and the internal transcribed spacer (ITS) region of this fungus have been determined (González- Species confirmation Lamothe et al. 2002). The non-coding ITS regions (ITS1 and fi ITS2) evolve faster than the coding regions, and thus may vary All isolates were identi ed to species level using a two-step between species and populations (McDonald 1997). Molecular screening process, involving a combination of morphological techniques such as random amplified polymorphic DNA (RAPD) (Graniti 1993) and molecular techniques (González-Lamothe fi markers and polymerase chain reaction–restriction length et al. 2002). Isolates were identi ed by their morphological polymorphism (PCR-RFLP) analysis of rDNA/ITS regions are and cultural characteristics when grown on potato dextrose now routinely employed for examining the genetic diversity and agar (Merck, Darmstadt, Germany) and OLE for 2 months fl causes of variations in virulence among plant pathogens. Tenzer under alternating periods of 12 h of uorescent light (35098 and Gessler (1997) found high genetic diversity within F18E/33 General Electric, Cleveland, OH, USA) and 12 h V. inaequalis populations but low differentiation among darkness. Colony morphology and pigmentation were different populations when analysing ITS regions using RAPD compared with the published descriptions of Graniti (1993). fi markers and PCR-RFLP. The identity of each isolate was con rmed by PCR using fi The universally primed-PCR (UP-PCR) technique is similar species-speci c primers, previously validated against Spanish fi to the traditional RAPD technique (Williams et al. 1990), isolates (González-Lamothe et al. 2002). PCR ampli cation of fi m but the method employs longer primers (15–20 nucleotides) the 18S rDNA region was performed in a nal volume of 25 l designed for higher annealing temperatures that provide containing 10 mM TRIS-HCl (pH 8.0), 1.5 mM MgCl2,50mM information for the fingerprinting of any organism (Bulat et al. KCl, 0.2 mM each of dATP, dCTP, dGTP and dTTP (Advanced 1998). As the UP-PCR primers selected for fungi primarily Biotechnologies Ltd, Epsom, Surrey, UK), 5 pmoles of primers target intergenic, more variable areas of the genome, this (Table 2), 1.25 units of Hotmaster Taq DNA polymerase – method is especially suitable for detecting intraspecific (Eppendorf, Hamburg, Germany), and 10 100 ng of total fi variation (Bulat et al. 1998). The main advantage of UP-PCR DNA. The ampli cation conditions using an ICycler Thermal Cycler (Bio-Rad Laboratories, Hercules, CA, USA) were as compared with RAPD is that the higher annealing temperatures follows: DNA denaturation at 94 C for 3 min, followed by 35 (52 56 C) result in a high degree of reproducibility and the generation of more complex banding patterns, which improves cycles of 94 C for 30 s, primer annealing at 55 C for 30 s, and fi the likelihood of identifying isolate-specific and pathotype- primer extension at 68 C for 30 s, witha nalextension at 68 C for m specific bands (Bulat et al. 1998; Lübeck et al. 1999). The 7min. The PCRproducts (4 l) wereseparated on 1% agarose gels UP-PCR technique has been successfully used in studying the (Sigma Chemical Co., St Louis, MO, USA) in TRIS-acetate- genetic diversity of other fungi, notably Trichoderma sp. EDTA (40 mM TBE; TRIS-acetate, 1 mM EDTA, pH 8.0), (Cumagun et al. 2000) and the grapevine pathogen stained with ethidium bromide and visualised using VersaDoc Phaeomoniella chlamydospora (Pottinger et al. 2002). Imaging Systems (Bio-Rad Laboratories). In this study, DNA extracted from New Zealand S. oleagina fi isolates was characterised using UP-PCR analysis to improve UP-PCR ampli cation understanding of genetic diversity of S. oleagina within New Eleven primers were screened for use in the UP-PCR analysis Zealand. against six S. oleagina isolates selected at random. Based on 510 Australasian Plant Pathology F. O. Obanor et al.

Table 1. Origin of the Spilocaea oleagina isolates used in this study

Isolate RegionA Cultivar PopulationB Isolate RegionA Cultivar PopulationB So1 Auckland Barnea 1 So34 Christchurch Manzanillo 5 So8 Auckland Barnea 1 So38 Christchurch Pendolino 5 So9 Auckland Barnea 1 So43 Christchurch Barnea 5 So11 Auckland Koroneiki 1 So44 Christchurch Barnea 5 So12 Auckland Koroneiki 1 So47 Christchurch Barnea 5 So13 Auckland Koroneiki 1 So30 Christchurch Picual 6 So14 Auckland Leccino 1 So39 Christchurch Picual 6 So15 Auckland Picual 1 So45 Christchurch Barnea 6 So16 Auckland Picual 1 So46 Christchurch Barnea 6 So17 Auckland Picual 1 So57 Christchurch Manzanillo 6 So4 Auckland Unknown 2 So42 Christchurch Unknown 7 So5 Auckland Unknown 2 So50 Christchurch SA Verdale 7 So6 Auckland Unknown 2 So51 Christchurch Barnea 7 So2 Auckland Leccino 3 So29 Christchurch Pendolino 8 So3 Auckland Picual 3 So40 Christchurch Unknown 8 So10 Auckland Barnea 3 So41 Christchurch Unknown 8 So18 Auckland Picual 3 So35 Christchurch SA Verdale 9 So19 Auckland J5 3 So36 Christchurch SA Verdale 9 So20 Auckland SA Verdale 3 So37 Christchurch Barnea 9 So21 Auckland SA Verdale 3 So48 Christchurch Manzanillo 9 So95 Blenheim UC 15 So52 Christchurch Barnea 9 So97 Blenheim Frantoio 15 So53 Christchurch Barnea 9 So91 Blenheim Leccino 16 So54 Christchurch Barnea 9 So93 Blenheim Picholine 16 So31 Masterton Barnea 10 So88 Blenheim Barnea 17 So58 Masterton Leccino 10 So89 Blenheim Barnea 17 So61 Masterton Picual 10 So94 Blenheim Picual 17 So71 Masterton Leccino 10 So98 Blenheim Pendolino 17 So74 Masterton Unknown 10 So80 Blenheim Barnea 18 So59 Masterton Leccino 11 So87 Blenheim Barnea 18 So60 Masterton Picual 11 So90 Blenheim Cornlea 18 So76 Masterton Unknown 11 So92 Blenheim Manzanillo 18 So77 Masterton Unknown 11 So81 Blenheim Barnea 19 So78 Masterton Unknown 11 So82 Blenheim Barnea 19 So79 Masterton Unknown 11 So83 Blenheim Barnea 19 So96 Masterton Unknown 11 So84 Blenheim Barnea 19 So62 Masterton Unknown 12 So85 Blenheim Manzanillo 19 So63 Masterton Unknown 12 So86 Blenheim Barnea 19 So64 Masterton Unknown 12 So23 Christchurch Barnea 4 So72 Masterton Manzanillo 12 So24 Christchurch Barnea 4 So73 Masterton Manzanillo 12 So27 Christchurch Manzanillo 4 So75 Masterton Unknown 12 So28 Christchurch Manzanillo 4 So7 Kapiti Leccino 13 So33 Christchurch Barnea 4 So22 Kapiti Unknown 13 So49 Christchurch Picholine 4 So65 Kapiti Pendolino 14 So55 Christchurch Manzanillo 4 So66 Kapiti Pendolino 14 So56 Christchurch Manzanillo 4 So67 Kapiti Pendolino 14 So25 Christchurch Frantoio 5 So68 Kapiti Pendolino 14 So26 Christchurch Leccino 5 So69 Kapiti Pendolino 14 So32 Christchurch Barnea 5 So70 Kapiti Pendolino 14 AAuckland, Masterton and Kapiti are on the North Island of New Zealand; Blenheim and Christchurch are on the South Island of New Zealand. BA population was defined as a group of S. oleagina isolates obtained from a single olive grove and separated from other groves by at least 5 km. banding patterns and intensities, five of the primers were selected designated DNA. Amplification was performed using a for use in this study (Table 2). UP-PCR reactions were performed Mastercycler Gradient apparatus (Eppendorf). The according to Lübeck et al.(1999) with modifications. Each amplification conditions were as follows: denaturation at 94C reaction volume was 25 ml with the following added to give for 2 min, 94C for 50 s, annealing at the specified temperature the final concentration indicated: 2.5 mM MgCl2, 0.2 mM each of (Table 2) for 2 min and primer extension at 72 C for 1 min dGTP, dCTP, dATP, and dTTP, 10 mM TRIS-HCl (pH 8.0), (4 cycles), then followed by 94C for 50 s, annealing at the 50 mM KCl, 0.2 mM dNTPs, 5 pmoles of primer (Table 2), 1.25 specified temperature for 90 s, and primer extension at 72C for units of Taq DNA polymerase (Eppendorf) and 10–50 ng of the 1 min (34 cycles), with a final extension at 72C for 10 min. Genetic diversity of Spilocaea oleagina Australasian Plant Pathology 511

entered into a binary matrix and analysed using distance-based methods. PAUP software (PAUP 4.0b3a; Sinauer Associates, Sunderland, MA, USA) was used to construct a cladogram based on the Jaccard similarity coefficient and the neighbour-joining method (Tegli et al. 2000). Bootstrap analysis was based on 1000 permutations. The Jaccard similarity coefficient is calculated as Auckland Sj = x/(n – y), where x represents the number of 1–1 matches, y the number of 0–0 matches and n the total number of bands compared. The tree generated was drawn and edited using MrEnt version 2 (Zuccon and Zuccon 2008). Average gene diversity (H; Nei 1973) was calculated for each 2 UP-PCR cluster, where H = S(1 – S xk )/h, and x is the allele frequency of the kth UP-PCR allele, and h is the number of fi Kapiti UP-PCR loci. The presence or absence of a speci c band was Masterton interpreted as a positive or null allele, respectively. Nei’s measure of genetic differentiation, G (Nei 1973), was also calculated for Blenheim ST each region (Auckland, Blenheim, Christchurch, Kapiti and Masterton), where GST =(HT – HS)/HT. The gene diversity (expected heterozygosity; HT) over all loci was calculated as 2 HT = S(1 – S xk )/h, where x is the allele frequency of the kth Christchurch UP-PCR allele in the total population, and h is the number of loci. The subpopulation gene diversity (HS) over all loci was 2 calculated as HS = S(1 – S xik )/nh, where x is the allele frequency of the kth allele in the ith subpopulation, n is the number of subgroups, and h is the number of loci. A likelihood ratio Chi- square test (G2) was conducted with the null hypothesis of no difference in UP-PCR allele frequencies in the five subgroups. An estimate of gene flow (Nm) was calculated from GST values, where Nm = 0.5(1 – GST)/GST (McDermott and McDonald 1993). All genetic diversity parameters were calculated using the Fig. 1. Origin of the 19 populations of Spilocaea oleagina isolates collected software POPGENE version 1.32 (Yeh et al. 1999). from New Zealand in 2004 and 2005. Divergence among all sampled populations was assessed by an analysis of molecular variance (AMOVA; Excoffier et al. 1992), based on an Euclidean distance matrix between all pairs of fi UP-PCR ampli cation products were separated on 5% multilocus phenotypes. For this analysis, the total variance in the polyacrylamide gels in TBE. The gels were stained with UP-PCR dataset was partitioned into between-region, between- ethidium bromide and visualised using VersaDoc Imaging population and within-population components. Paired genetic Systems. distances among the 19 populations were estimated using FST (Wright 1951). The statistical significance of the variance UP-PCR analysis components of the AMOVA and the paired comparisons of Amplification profiles of the 98 S. oleagina isolates that were FST, were determined by nonparametric procedures using 1023 generated by the five selected UP-PCR primers were compared random permutations. The gametic phase linkage disequilibrium with each other, and bands of the DNA fragments were scored within S. oleagina populations was also calculated. The manually as present (1) or absent (0). Only the intense and probability test (Fisher’s exact test) for each contingency table reproducible bands were scored. The resulting dataset was was performed using the Markov chain method (Raymond and

Table 2. Species specific and universally primed (UP)-PCR primers used in this study

Primer Nucleotide sequence 50!30 Annealing temp. (C) Reference Species specific 18SF GCTTGTCTCAAAGATTAAGCC 55 González-Lamothe et al.(2002) 18SR CCTTGTTACGACGACTTTTACTTCC 55 UP-PCR AA2M2 CTGCGACCCAGAGCGG 50 Lübeck et al.(1998) AS4 TGTGGGCGCTCGACAC 55 Lübeck et al.(1998) AS15inv CATTGCTGGCGAATCGG 52 Cumagun et al.(2000) L15 GAGGGTGGCGGTTCT 52 Cumagun et al.(2000) L15/AS19 GAGGGTGGCGGCTAG 52 Lübeck et al.(1998) 512 Australasian Plant Pathology F. O. Obanor et al.

Rousset 1995), with the number of steps in the Markov chain isolates amplified by UP-PCR primer AS4. Of the five primers, and number of dememorisation steps set at 10 000 and 1000, AS4 gave the highest numbers of reproducible bands, whereas respectively. An association between loci was considered AS15inv yielded the least number of bands. The five primers significantly different from zero if the exact test gave a generated a total of 159 reproducible bands from the 98 probability less than 0.05. AMOVA and linkage disequilibrium S. oleagina isolates of which 31 variable characters were analyses were conducted with Arlequin software (Excoffier parsimony-uninformative while 117 characters were et al. 1997). parsimony-informative. The total number of loci detected and the proportion of the loci that were polymorphic both varied from Results population to population (Table 3). The total number of loci Isolate confirmation detected in the populations ranged from 79 to 96 and the proportion of the polymorphic loci ranged from 10.2 to 72.8%. A 1.8-kb DNA fragment of 18S rDNA was amplified from all S. oleagina isolates using the specific primers (Table 2), with no band being observed from the closely related V. inaequalis Genetic diversity within and among populations isolate. Results for the population genetic diversity showed that populations 5 and 16 had the highest (0.1393) and lowest UP-PCR banding pattern (0.0234) genetic diversities, respectively (H; Nei 1973). The All the banding patterns for the 98 S. oleagina isolates from overall mean genetic diversity for all populations was 0.1322, the 19 populations in Christchurch, Blenheim, Masterton, Kapiti showing that the majority (86.8%) of the genotypes present within and Auckland, were generated using the UP-PCR primers the S. oleagina population were similar. Nevertheless, the (AA2M2, AS4, AS15inv, L15 and L15/AS19). Figure 2 proportion of polymorphic loci, Nei’s diversity indices found shows an example of the banding profiles of nine S. oleagina in populations 5 and 9 were similar; population 9 possessed the greatest proportion of unique polymorphisms (15.2%) compared M123456789M with population 5. Although there were several bands that were monomorphic within a population, none of them was exclusive 2 072 to the population for which the locus was fixed. When the populations were pooled within regions, the genetic structure 1 500 (GST) detected within the regions ranged from 0.1554 to 0.3077 on the average of the 121 polymorphic loci (Table 3). Significant differentiation (GST = 0.3077, P = 0.025; GST = 0.2604, P= 0.013) was seen only among the populations sampled from Blenheim (5) 600 and Christchurch (6), respectively. The AMOVA analysis indicated that ~87% of the variation in the data was from genetic variation within populations (Table 4). Only 3% of the variation could be attributed to differences among 300 populations, and 10% was due to regional differences. The proportion of the total variance values was only significant for between region and within population levels. Pairwise 200 differences varied from –0.279 to 0.516. The differentiation between populations was significant (P < 0.05) for only 25% Fig. 2. Universally primed-PCR banding profiles for Spilocaeca oleagina (43/171) of all pairwise comparisons. When considered as a generated with the primer AS4. Lanes 1–9 represent isolates So26, So54, single population, pairwise comparisons of 123 polymorphic So92, So36, So47, So72, So55, So23 and So31, respectively. The Invitrogen UP-PCR loci gave 2250 (30%) disequilibrium values that were 100-bp ladder is shown in lane M. significantly different from zero (Fisher’s exact test, P < 0.05).

Table 3. Nei’s(1973) measures of neutral genetic diversity, structure, and gene flow estimate calculated for all sampled populations of Spilocaea oleagina Values were calculated assuming random mating

A B C D Region Population size Sample size HT HS GST Nm Auckland 3 20 0.0764 0.0644 0.1573 2.678 Christchurch 6 34 0.1518 0.1122 0.2604 1.416 Kapiti 2 8 0.0584 0.0485 0.1703 2.435 Blenheim 5 18 0.1178 0.0815 0.3077 1.124 Masterton 3 18 0.0876 0.0740 0.1554 2.717 ATotal genetic diversity. BGenetic diversity within region. CNei’s coefficient of genetic differentiation. DEstimate of gene flow. Genetic diversity of Spilocaea oleagina Australasian Plant Pathology 513

Table 4. Hierarchical analysis of molecular variance for all Spilocaea oleagina populations The significance value was determined from 1023 permutations

Source of variation d.f. Sums of squares Variance component % total variation F-statistics P-value Between regions 5 146.64 1.161 10.1 0.1011 0.001 Between populations 13 152.91 0.355 3.1 0.0344 0.157 Within populations 79 786.66 9.957 86.8 0.1323 0.001

The total number of contingency tables (loci combinations) was of the pathogen into New Zealand or that local mutation occurred 123(123 – 1)/2 = 7503. over time. It is also possible that other factors such as parasexual Population differentiation on the basis of host cultivar was recombination may be occurring in the pathogen populations, as tested with isolates collected from Barnea (n = 4) and Manzanillo was reported to have had a major impact on the population (n = 3) olive trees grown in the same grove (population 9). Genetic structure of Rhynchosporium secalis (Newman and Owen differentiation tests revealed no significant difference (P = 0.315) 1985) and Magnaporthe grisea (Crawford et al. 1986; Zeigler in the allele frequencies between the two populations, and a very et al. 1997). Low to moderate genetic differentiation (GST = low level of differentiation was observed with the parameter FST 0.155–0.307) was found for S. oleagina populations among the for this population pair (FST = 0.088). regions. Low geographic population structure and overall low Individual isolates of S. oleagina clustered into six groups genetic diversity is expected for a disease that has emerged due to (A, B, C, D, E and F), which were independent of geographic recent introduction. origin in the rooted neighbour-joining cladogram generated from In this study, no evidence of population differentiation was the Jaccard-transformed similarity matrix (Fig. 3). However, found among the S. oleagina subpopulations analysed (GST = isolates collected from Christchurch olive groves appeared to 0.034, P = 0.157). Tenzer and Gessler (1997) also found low have greater genotypic diversity than the other populations. All differentiation (GST = 0.040) in Switzerland among different the isolates in group A were from the South Island (Christchurch populations of the closely related fungus, V. inaequalis, when and Blenheim) and the majority of the isolates from Christchurch analysing ITS regions and using RAPD markers. This was clustered in group B. explained by the history of apple growing in that country (Tenzer and Gessler 1997). In this study, the lack of differentiation found could be explained by subpopulations of Discussion S. oleagina being founded by a common source population after Our studies represent the first report on the genetic diversity of being introduced to New Zealand, with limited migration or S. oleagina. Overall, this study found low levels (13%) of genetic mutation among subpopulations to cause genetic variation in New Zealand S. oleagina population. Similar results differentiation from genetic drift (Goodwin et al. 1993). have been reported for other pathogenic fungi such as Hemileia Olive production in New Zealand is relatively new. The vastatrix (Gouveia et al. 2005), Discula destructive (Zhang and disease on present day cultivated olive trees originated from Blackwell 2002), and Trichoderma sp. (Cumagun et al. 2000) stock imported from overseas in the 19th century for using UP-PCR markers. It is known that the basic mechanisms ornamental purposes. Initially, only a single nursery was that generate variation in pathogen populations are mutation, involved in the propagation and distribution of the olive migration and recombination (asexual or sexual). This variation is plants. These plant materials were the initial sources of shaped by the forces of selection and genetic drift (McDermott primary inoculum for new infection. Of the different cultivars and McDonald 1993; Zeigler et al. 1995). It is possible that imported, Barnea, which is highly susceptible to OLS, was most because S. oleagina was recently introduced into olive groves in commonly propagated and grown in olive groves. Disease spread New Zealand, these forces have not acted sufficiently strongly to in the nursery and to olive groves resulted from inadequate produce substantial genotypic variation in the pathogen knowledge of effective disease control strategies and population. Fungal pathogen populations that are mainly management practices. The use of overhead irrigation systems asexual will display a high degree of clonality, with few in particular provided favourable conditions for pathogen genotypes present at relatively high frequencies. In contrast, development. Eventually, inoculum was spread over large random mating (sexual recombination) populations are distances through the distribution of OLS-infected plant expected to show a high degree of genotypic diversity (Burdon materials. An alternative explanation for the lack of and Roelfs 1985; Kohn 1995). Thus, the low genetic diversity differentiation among the pathogen populations among the suggests that an asexual mode of reproduction predominates regions could be that long-distance conidial dispersal allowed among S. oleagina populations in New Zealand, although the for enough migration and gene flow between populations to occurrence of a low level of sexual reproduction cannot be homogenise the allele frequencies (Slatkin 1987). However, excluded. this hypothesis is unlikely to be true because S. oleagina Molecular analysis revealed that most of the genetic variation conidial dispersal is likely to be limited to within groves and (87%) found was within the pathogen population. The variations between neighbouring groves, since it is known that conidia are among populations accounted for 3% while the regions accounted dispersed mainly by rain-splash (Graniti 1993; Guechi and Girre for 10% of the total genetic variation. The high proportion of the 1994). genetic diversity attributed to within S. oleagina populations Cluster analysis exhibits unstructured variability of this supports the hypothesis that there were multiple introductions pathogen with regard to geographical origin or host. 514 Australasian Plant Pathology F. O. Obanor et al.

Venturia inaequalis So23 So47 So87 So55 So95 A So57 So38 So24 So86 So32 So37 So82 So62 So27 So28 So26 So29 So51 So90 So56 So41 So42 So49 So94 So25 So39 B So43 So67 So76 So64 So60 So15 So50 So30 So80 So40 So89 So45 So53 So54 So35 So81 So44 So8 So70 So9 So58 So69 So73 So78 So72 So65 So61 C So77 So13 So75 So74 So66 So18 So78 So83 So21 So92 So1 So84 So31 So31 So96 So71 So85 So19 So14 So22 D So11 So12 So68 So7 So98 So4 So20 So5 So6 So2 So46 So48 So10 So59 E So17 So16 So63 So88 So52 So97 F So91 So93 So33 So36 So34 Fig. 3. Cladogram indicating the relationships between Spilocaea oleagina isolates based on universally primed-PCR analysis. The rooted tree was created using the neighbour-joining method (PAUP 4.0b3a; Sinauer Associates) with genetic distance values generated from the Jaccard-transformed similarity matrix. Genetic diversity of Spilocaea oleagina Australasian Plant Pathology 515

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