Genetic drift and host-mediated selection cause genetic differentiation among Gaeumannomyces graminis populations infecting cereals in southern Australia

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Mycol. Res. 105 (8) : 927–935 (August 2001). Printed in the United Kingdom.

Genetic drift and host-mediated selection cause genetic differentiation among Gaeumannomyces graminis populations infecting cereals in southern Australia

Paul R. HARVEY1*, Peter LANGRIDGE2 and Don R. MARSHALL3 " CSIRO Land and Water, PMB2, Glen Osmond, SA 5064, Australia. # Waite Agricultural Research Institute, University of Adelaide, Glen Osmond, SA 5064, Australia. $ Plant Breeding Institute, University of Sydney, NSW 2006, Australia. E-mail : paul.harvey!adl.clw.csiro.au Received 10 July 2000 ; accepted 16 March 2001.

Isolates of Gaeumannomyces graminis were sampled from 16 cereal crops throughout the cereal belt of southern Australia to determine the extent of genetic diversity and the scale of genetic differentiation among pathogen populations. Data from 13 isozyme and 4 RFLP loci differentiated 79 multilocus genotypes among the 320 isolates analysed. All 17 loci differed significantly in allele frequencies across all populations and significant levels of genetic differentiation were detected between most populations. Genetic differentiation among host groups was high (GST l 0n307) and groups of populations from barley, oats and wheat were significantly different. The average genetic identities among populations were low and populations formed genetically related groups based on similarities in recent cereal cropping histories and not geographical origins. Collectively, these analyses indicate restrictions to interpopulation gene flow within G. graminis and imply that population differentiation results from genetic drift and host-mediated selection by different cereal species.

INTRODUCTION Gaeumannomyces graminis is a soil-borne, haploid, ascomycete that parasitises a diverse range of cereals and grasses (Scott 1981). The species has been subdivided into three varieties on the basis of limited morphological characteristics and differences in host range (Walker 1972). Take-all, caused by the fungus G. graminis var. tritici (Ggt), is the most serious root disease of wheat and barley occurring throughout the cereal producing regions of southern Australia (Mussared 1996). G. graminis var. avenae (Gga) causes take-all disease in oats, wheat and barley, and generally has longer ascospores than Ggt (Walker 1972). G. graminis var. graminis (Ggg) colonises the roots of wheat and barley, but does not cause severe take-all in cereals. Ggg can be distinguished from Ggt and Gga by its characteristic lobed hyphopodia (Walker 1972). The uniform susceptibility of wheat to Ggt and Gga contrasts with the levels of resistance shown by the other temperate cereals. Barley generally shows an increased tolerance to infection and rye is considered to be moderately resistant, possibly due to high root concentrations of the hydroxamic acid DIBOA which inhibits the growth of Ggt (Wilkes, Marshall & Copeland 1999). Oats are also highly resistant to Ggt but susceptible to Gga. Oat roots synthesise * Corresponding author.

avenacins, antifungal compounds that are toxic to Ggt (Maizel, Burkhardt & Mitchell 1964). Gga isolates differ from Ggt in that they produce the enzyme avenacinase, which detoxifies avenacins and overcomes this resistance mechanism (Osbourn et al. 1991). The contrasting levels of disease resistance among its cereal hosts, imply that G. graminis populations may be influenced by shifts in host-mediated selection pressures. For example, cereal rotations involving non-susceptible (oats) and susceptible (wheat and barley) crops changed the abundance and genotypic composition of pathogen populations (Yeats, Fang & Parker 1986, Bateman et al. 1997, Carter et al. 1999), probably via selection of host-adapted pathogen genotypes. Consequently, populations of G. graminis parasitising different cereal species may show considerable genetic differentiation. Over the past decade DNA-based approaches have been used to identify varieties and pathological variants of G. graminis. These methods include RFLP analyses of mitochondrial (Henson 1989) and ribosomal DNA (rDNA) (O’Dell, Flavell & Hollins 1992, Ward & Afroki 1994, Tan & Wong 1996), randomly amplified polymorphic DNA (RAPD) (Fouly, Wilkinson & Domier 1996, Bryan, et al. 1999) and sequence differences in the internal transcribed spacer regions (ITS) of rRNA genes (Bryan, Daniels & Osbourn 1995). With some exceptions (O’Dell et al. 1992, Bateman et al. 1997), little research has been conducted to determine levels of genetic

Genetic variation in Gaeumannomyces graminis variation among field populations of G. graminis. Whilst analyses of the rDNA locus have resolved the intra-specific taxonomic status of isolates, they may not give an accurate representation of overall genetic variation within pathogen populations. RAPDs were used to assess variation at a range of loci (Fouly et al. 1996, Bryan et al. 1999), but amplification can be inconsistent and markers often show dominant inheritance (Devos & Gale 1992). Co-dominant molecular markers, such as isozymes and single-locus RFLPs, are preferred in population studies because they can be used to quantify allele frequencies, define the genetic structure of pathogen populations and determine the relative importance of sexual and asexual reproduction (Goodwin et al. 1992, Chen & McDonald 1996). Successful development of disease management programs for take-all can be supported by defining the genotypic and pathogenic composition of G. graminis populations and the mechanisms by which genetic variation arises and is distributed (Burdon & Silk 1997). The distribution of variation between ecogeographically-diverse locations and cereal hosts will provide much needed information on the genetic structure of G. graminis populations and the evolutionary consequences of interactions between pathogen and host. Consequently, the objectives of this study were to : (1) determine the extent and distribution of genetic diversity among populations and host species of G. graminis ; and (2) identify the mechanisms responsible for the maintenance and dissemination of this variation. MATERIALS AND METHODS Fungal isolates and culture conditions Populations of Gaeumannomyces graminis were sampled from barley, oat and wheat crops in southern Australia (Fig. 1). Plants were sampled by running random transects through fields and sampling at 10 m intervals. Root segments (2–3 cm) were surface sterilised and one segment per plant was plated on to the G. graminis selective medium SM-GGT3 (Juhnke, Mathre & Sands 1984). Plates were incubated in darkness at 22 mC and isolates were transferred to quarter-strength potatodextrose agar (PDA) plates supplemented with 100 mg l−" streptomycin sulphate. Thirty root isolates were obtained for each of the 16 populations (Fig. 1) and were stored at 4 m on PDA slopes and grown on the same medium at 22 m. Representative isolates are preserved in the CSIRO Land and Water culture collection (Glen Osmond, SA).

928 Richardson, Baverstock & Adams (1986). Approximately 5 µl of extract was loaded per lane and all gels were run at 4 m for 2 h under the conditions shown in Table 1. Thirty isolates per G. graminis population were analysed with each enzyme and Ggg isolate 51652 ( J. Walker) was used as a reference standard to calculate the relative mobility (Rf) values of alleles at each enzyme locus. Isolation of genomic DNA and construction of DNA probes Mycelia for DNA extractions were grown as described above. Mycelial mats were ground to a fine powder under liquid nitrogen, resuspended in 4 volumes of extraction buffer (100 m Tris, 100 m NaCl, 1 % SDS, 20 m EDTA, 100 m Na SO , pH 8n0) and DNA extractions were carried out as # $ described in Guidet et al. (1991). Genomic probes were constructed by cloning random PstI (Boehringer–Mannheim) DNA fragments, from Ggt isolate C3 (P. Wong), into the plasmid vector pUC19 using standard protocols (Sambrook, Fritsch & Maniatis 1989). Recombinant plasmid DNA was isolated from E. coli (DH5α) using the small-scale alkaline lysis method (Sambrook et al. 1989). Southern hybridisation Genomic DNAs were digested with restriction endonucleases BamHI, and HindIII (Boehringer Mannheim) and size fractionated by horizontal electrophoresis in 1 % agarose TAE (40 m Tris-acetate, 1 m Na EDTA, pH 7n8) gels. DNA was # transferred and fixed to Hybond-Nj nylon membranes according to the manufacturer’s instructions (Amersham Life Science, UK). Genomic DNA probes were labelled by randomly-primed Klenow extension with approx. 50 µCi [α−$#P]-dCTP (Sambrook et al. 1989). Membranes were prehybridised at 65 m for 4–6 h, labelled probe was added and DNA hybridisation conducted at 65 m overnight (Amersham Life Science). Membranes were washed at 65 m for 30 min in 2iSSC, 0n1 % SDS and repeated in 1iSSC, 0n1 % SDS and 0n5iSSC, 0n1 % SDS before being autoradiographed. Five different probes pG5 (0n7 kbp), pG26 (0n4 kbp), pG28 (0n4 kbp), pG30 (0n5 kbp) and pG202 (2n2 kbp) were used to analyse 20 isolates per G. graminis population. Isolates Ggt 800 (A. Rovira) and Gga 35793 ( J. Walker) were included on each gel and used as reference standards to assist comparisons between populations. RFLP markers were designated by the number of the DNA probe followed by the restriction enzyme (e.g. 5B for pG5 with BamHI).

Isozyme analysis Gaeumannomyces graminis mycelia were grown in 100 ml flasks containing 25 ml of Czapek–Dox medium without shaking at 22 m for 14–21 d. Approximately 200 mg of mycelia (fresh weight) was blotted dry, frozen in liquid nitrogen and ground into a viscous slurry in the presence of 0n2 ml extraction buffer (33 m Tris, 0n13 µ NADP, 0n1 % 2mercaptoethanol, 0n1 % Triton X-100, pH 7n0). Samples were centrifuged (11 600 g for 5 min) and the supernatant was chilled on ice. Cellogel (Chemetron : Milan) electrophoresis and enzyme staining protocols were conducted as described in

Statistical analyses of genetic diversity data With enzyme electrophoresis, a single band was resolved per isolate for each of the enzymes and banding patterns were consistent with the hypothesis of multiple alleles at individual genetic loci (as in Goodwin et al. 1993). In Southern hybridisations a single restriction fragment was detected per isolate with 26B, 28H and 30H, 2 fragments with 5B and 1–3 fragments with 202H. Each of these probe-enzyme combinations was defined as a different RFLP locus and individual restriction fragments (26B, 28H, 30H) or combinations of

P. R. Harvey, P. Langridge and D. R. Marshall

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N.T. QLD. W.A. S.A. N.S.W.

VIC.

Cereal Belt Oats Wheat Barley

0

600 km

Fig. 1. Sampling locations and host species of Gaeumannomyces graminis populations in the cereal belt of southern Australia.

fragments (5B, 202H) were treated as alleles at individual loci (as in Chen & McDonald 1996, Keller et al. 1997). Allele frequencies with each of the 13 isozyme and 5 RFLP loci were determined within each population, host group (barley, oat and wheat isolates) and the entire collection of Gaeumannomyces graminis isolates (480 and 320 isolates for isozyme and RFLP analyses respectively). Since infection of the current crop is primarily dependent on inoculum surviving in plant debris from the previous year (Hornby 1981, Sivasithamparam 1993), host groups were defined on the basis of the current and preceding cereal crop. Each host group contained equal numbers of isolates and comprised three G. graminis populations selected to cover the geographical range

of the pathogen (barley – BB, HS, MN ; oats – GM, HM, NN ; wheat – CV, MD, TW) (Fig. 1). Genetic diversity within each population (DS), host group (DH) and the total collection (DT) was quantified using the diversity index of Nei (Nei 1973) and expressed as the mean diversity over all isozyme and RFLP loci. Multilocus genotypes of each isolate were generated by combining the genotypes at 13 isozyme and 4 RFLP loci. Multilocus diversity (M) was calculated with the Shannon diversity index and values were normalised so that M ranges from 0 to 1 (Goodwin et al. 1993, Liu et al. 1996). Genetic differentiation among populations and host-based groups was estimated using Nei’s GST (Nei 1973), as described in Goodwin et al. (1993). Statistical comparisons between pairs

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Table 1. Isozymes used to document genetic diversity among Gaeumannomyces graminis populations and the buffer systems for best resolution of the bands.

Enzyme

Abbrev.

EC No.a

Buffer systemb

Aconitase Fumarase Glutamate-oxaloacetate transaminase Glucose-6-phosphate dehydrogenase Glucose-phosphate isomerase Glutathione reductase Hexokinase Isocitrate dehydrogenase Malate dehydrogenase Malic enzyme 6-Phosphogluconate dehydrogenase Phosphoglucomutase

ACON FUM GOT

4n2.1n3 4n2.1n2 2n6.1n1

1 1 1

G6PD

1n1.1n49

3

GPI

5n3.1n9

2

GSR HK IDH MDH ME 6PGD

1n6.4n2 2n7.1n1 1n1.1n42 1n1.1n37 1n1.1n40 1n1.1n44

2 1 1 2 2 3

PGM

2n7.5n1

2

Population isolates

Ggt Gga

Lane

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16

Kb 15.8 12.9

WP 5B

6.3

2.5 Genotype

c b c c c

c c c c c c a a b a a 9.1 7.5

WI 26 B

4.5 Genotype

a International Union of Biochemistry (1984), Enzyme Nomenclature Academic Press, New York. b 1–11n6 m NaHPO , 8n4 m NaH PO ; 2–15 m Tris, 5n0 m % # % Na EDTA, 10 m MgCl ; 3–100 m Tris, 1n0 m Na EDTA, 1n0 m # # # MgCl .

#

of populations were made using jack-knife estimates of the mean and variance of GST (Weir & Cockerham 1984), as described in Brown et al. (1990). Chi-square tests were used to determine significant differences in the distributions of alleles among populations and host groups. Phenetic relationships among G. graminis populations were determined using Nei’s measure of genetic identity (Nei 1972), calculated from allele frequencies with the 13 isozyme and 4 RFLP loci. Data were analysed using the computer program Gendist (J. Felsenstein, University of Washington). Hierarchical cluster analysis (group average method) was used to group populations according to their genetic identities and phenetic relationships among populations were presented as dendrograms. RESULTS Genetic diversity analyses A single band was resolved per isolate with each of the isozyme loci and no null alleles were found at any loci (Fig. 2). Lane

1

2

3

4

5

6

7

8

9

Genotype

b

c

d

a

c

b

b

d

d

Fig. 2. Example of allelic variation at the phosphoglucomutase (PGM) locus among isolates of Gaeumannomyces graminis from 5 wheat populations. The genotype of each isolate is shown under the lanes. Lanes 1–9 : CV14, MN5, BT3, HM6, HM18, TW1, TW26, TW6, TW24.

a b c a a c c c a c c b c a b b 10.8

TM 28 H Genotype

6.0 a b b b b b b

b a

b b a b b b b 10.5

6.6

TW 202 H

3.6 3.3 Genotype c a

c c c b c a b c

c c

a b

b a

Fig. 3. Examples of genetic variation at RFLP loci 5B, 26B, 28H and 202H. Probes were hybridised to DNAs from Ggt 800 (lane 1), Gga 35793 (lane 2) and 14 Gaeumannomyces graminis isolates from wheat populations WP (5B), WI (26B), TM (28H) and TW (202H) (lanes 3–16). Populations were selected to show each of the alleles detected at the 4 RFLP loci and the genotype of each isolate is shown under the lanes.

There were 42 alleles among the 13 polymorphic enzymes used in the analysis of 480 Gaeumannomyces graminis isolates. Many of these enzymes form heterodimers when heterozygous in other organisms (Richardson et al. 1986), but no heterodimers were observed in any G. graminis isolates. These observations are consistent with the haploid state of the G. graminis vegetative mycelium. Populations were analysed with 5 genomic probes that were assumed to be hybridising to single RFLP loci. Restriction fragment profiles detected by individual probes were similar in intensity, mutually exclusive among isolates and were scored as allelic. There were 12 alleles among the 5 RFLP loci used in analysing 320 G. graminis isolates. With loci 26B, 28H and 30H only one restriction fragment was detected per isolate. The three 26B alleles were 9n1 kbp (a), 7n5 kbp (b) and 4n5 kbp (c) and the two 28H alleles were 10n8 kbp (a) and 6n0 kbp (b) (Fig. 3). Locus 30H was monomorphic across all 16 populations (6n7 kbp fragment) and was excluded from the analyses. Two restriction fragments were detected per isolate with locus 5B

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Table 2. Genetic (DS) and multilocus (MS) diversities within the 16 populations of Gaeumannomyces graminis, calculated from 13 isozyme and 4 RFLP loci. Isozyme

RFLP

Combined

Population

Average no. alleles per locus

Genetic diversity (DS)

Average no. alleles per locus

Genetic diversity (DS)

Genetic diversitya (DS)

No. of multilocus genotypesb

Multilocus diversity (MS)

WI TW BB HM CV MD WP MN BT DY GM HS WN TM JM NN Mean

1n9 2n0 1n7 2n2 1n2 1n4 1n4 1n9 1n7 1n6 1n5 1n4 1n6 1n2 1n2 1n1 1n6

0n291 0n282 0n133 0n311 0n040 0n126 0n096 0n288 0n216 0n164 0n104 0n085 0n150 0n063 0n023 0n021 0n150

2n5 2n3 2n5 2n0 1n8 1n5 2n0 1n5 1n3 1n0 1n0 1n3 1n8 2n0 1n0 1n0 1n6

0n365 0n358 0n244 0n093 0n181 0n200 0n270 0n174 0n024 0n000 0n000 0n024 0n111 0n159 0n000 0n000 0n138

0n308 0n300 0n159 0n259 0n074 0n144 0n137 0n261 0n171 0n126 0n079 0n070 0n141 0n085 0n018 0n016 0n147

10 6 8 8 6 5 6 6 6 3 3 4 4 3 1 1 5

0n687 0n585 0n546 0n505 0n499 0n467 0n458 0n424 0n397 0n273 0n273 0n236 0n236 0n213 0n000 0n000 0n362

Combined genetic diversity was calculated using 30 (isozyme) and 20 (RFLP) isolates per population. Multilocus genotypes (MLG) were determined using 20 isolates per population (isozyme and RFLP combined). All MLG were population-specific, except for JM and NN where all isolates shared the same genotype. There were 79 MLGs among the 320 isolates tested with a total multilocus diversity of MT l 0n654. a

b

Table 3. Mean coefficients of differentiation (GST) between populations of Gaeumannomyces graminis, using jack-knife procedures (Brown et al. 1990, Weir & Cockerham 1984). Estimates of GST are based on the distribution of variation at 4 RFLP and 13 isozyme loci. Numbers in bold indicate that GST is significantly different from zero at P 0n01. BT CV DY GM HM HS JM MD MN NN TM TW WI WN WP MN NN TM TW WI WN WP

0n477 0n382 0n573 0n608 0n389 0n357 0n706 0n447 0n215 0n708 0n571 0n245 0n403 0n575 0n408

0n563 0n662 0n706 0n491 0n536 0n764 0n421 0n351 0n769 0n665 0n266 0n269 0n631 0n358

0n727 0n754 0n537 0n585 0n862 0n487 0n277 0n862 0n745 0n335 0n390 0n724 0n578

0n447 0n232 0n726 0n490 0n665 0n540 0n472 0n444 0n448 0n522 0n390 0n660

0n317 0n767 0n497 0n657 0n548 0n506 0n476 0n484 0n567 0n352 0n692

0n546 0n295 0n513 0n402 0n295 0n233 0n347 0n401 0n252 0n481

0n862 0n458 0n337 0n867 0n744 0n294 0n279 0n717 0n603

0n762 0n636 0n074 0n476 0n555 0n641 0n356 0n781

BB

BT

CV

DY

GM

HM

HS

JM

0n255 0n765 0n651 0n176 0n335 0n638 0n507

0n639 0n533 0n155 0n461 0n531 0n295

0n469 0n559 0n641 0n350 0n786

0n442 0n558 0n389 0n671

0n227 0n471 0n338

0n492 0n303

0n613

MD

MN

NN

TM

TW

WI

WN

and one (2n5 kbp) was monomorphic for all G. graminis isolates. The three 5B alleles were 15n8j2n5 kbp (a), 12n9j2n5 kbp (b) and 6n3j2n5 kbp (c) (Fig. 3). Three alleles were also detected with locus 202H, with 1–3 restriction fragments per isolate, allele a (10n5 kbp), b (6n6j3n6 j3n3 kbp) and c (6n6j3n3 kbp) (Fig. 3).

The mean within-population genetic diversity with isozyme loci (DSi l 0n150) was similar to RFLP loci (DSr l 0n138), but levels of diversity detected with these techniques varied considerably within individual populations (Table 2). The lowest levels of RFLP diversity were within populations isolated from oats or exposed to this crop in the last growing

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Table 4. Tests for independence of allelic distributions ( χ#), levels of genetic diversity (DH) and genetic differentiation (GST) for 17 loci, among barley, oat and wheat populations of Gaeumannomyces graminis. χ# valuea

DHb

Locus

OatiWheat

OatiBarley

BarleyiWheat

Oat

Barley

Wheat

GSTc

5B 26B 28H 202H ACON FUM GOT-1 GOT-2 G6PD GPI GSR HK IDH MDH ME 6PGD PGM

132n410 127n109 156n150 127n342 32n826 2n526 204n645 2n526 13n863 34n052 67n657 7n074 40n504 9n987 157n888 137n418 123n227

146n224 149n904 156n150 142n279 4n462 2n798 106n471 5n246 0n097 4n427 156n081 8n525 47n629 9n987 132n722 134n860 84n956

1n147 46n990 0n000 3n856 34n497 5n474 25n798 0n582 15n255 21n554 92n723 0n097 17n877 0n000 16n942 9n093 30n726

0n033 0n033 0n033 0n064 0n345 0n215 0n000 0n215 0n105 0n307 0n383 0n000 0n124 0n143 0n464 0n366 0n487

0n209 0n259 0n000 0n493 0n263 0n253 0n504 0n064 0n124 0n220 0n258 0n124 0n554 0n000 0n529 0n165 0n166

0n239 0n466 0n000 0n543 0n491 0n105 0n203 0n105 0n105 0n452 0n664 0n105 0n393 0n000 0n501 0n085 0n263

0n696 0n618 0n975 0n449 0n158 0n010 0n551 0n023 0n015 0n076 0n325 0n021 0n075 0n065 0n260 0n557 0n339

a b c

Bold numbers indicate significant differences between groups (P 0n01). Total gene diversities. Mean DH values : oat l 0n195, barley l 0n246, wheat l 0n278. Genetic differentiation across all three hosts. Mean GST l 0n307.

season, four of these five populations (DY, GM, JM and NN) being invariant at all RFLP loci (Table 2). There were 79 multilocus genotypes among the 320 G. graminis isolates, of which 78 were population-specific (Table 2) and 48 occurred more than once per population. Two populations (JM and NN) had only a single multilocus genotype (Table 2) and isolates from both populations were the same genotype. The total multilocus diversity within the collection was MT l 0n654 (Table 2).

and barley isolates showed significant differences (P 0n01) in the distribution of alleles at 88, 71 and 53 % of loci respectively (Table 4). Genetic differentiation between hostgroups was greater with RFLPs (mean GSTr l 0n685) than isozymes (mean GSTi l 0n190) and levels of differentiation between barley and wheat (0n106), oats and barley (0n415) and oats and wheat (0n432) were all significantly different from zero (P 0n01). Overall, the mean level of genetic differentiation for all loci across the 3 host groups was GST l 0n307. Genetic identities among G. graminis populations

Distribution of variation among populations and host groups The mean total genetic diversity with RFLP loci (DTr l 0n585) was greater than with isozyme loci (DTi l 0n403) and DT values for individual loci ranged between 0n085 (G6PD) and 0n741 (ME). The mean genetic diversity for all loci across all 16 populations was DT l 0n446. Similarly, mean genetic differentiation among populations (GST) was greater with RFLPs (0n777) compared with isozymes (0n539) and GST values for individual loci ranged between 0n106 (G6PD) and 0n978 (28H). Overall, the mean level of genetic differentiation for all 17 loci across all 16 populations was GST l 0n595. The majority of GST values between pairs of populations were significantly different from zero (P 0n01). Those not significantly different were BB vs MN, JM vs NN, and TW vs MD, MN and WI (Table 3). Chi-square tests showed that allele frequencies across all 16 Gaeumannomyces graminis populations were significantly different for all isozyme and RFLP loci (P 0n01). Populations were sorted into host-based groups and wheat isolates were the most diverse (DHw l 0n278), followed by barley (DHb l 0n246) and oats (DHo l 0n195) (Table 4). Chisquare tests between oat and wheat, oat and barley and wheat

Hierarchical cluster analyses of genetic identities with isozyme and RFLP loci separated the 16 populations into two primary groups and the composition of these groups was the same with both techniques (compare Fig. 4 a–b). There was no clear correlation between genetic identities and distance, since each of the primary phenetic groups contained populations of diverse geographical origins (cfr Fig. 1 with Fig. 4 a–b). For example, the CV and NN populations had a low genetic identity (mean I l 0n269) and were separated by a distance of only 250 km whereas, NN and GM were thousands of km apart but had a high genetic identity (mean I l 0n950). Cluster analyses indicated that phenetic grouping of G. graminis populations may be related to cropping history. For example, 5 of the 7 populations in one primary phenetic group were isolated from oats (NN) or exposed to this crop (DY, GM, HM, JM) in the previous year (Fig. 4 a–b). The remaining 9 populations were isolated from barley and wheat and formed the second primary phenetic group. Within this group, populations isolated from fields cropped to wheat or grass pastures in the current and previous season showed a closer relationship to each other, compared with those isolated from barley (BB, HS) or exposed to this crop (MN) in the previous year (Fig. 4 a–b).

P. R. Harvey, P. Langridge and D. R. Marshall

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A CV MN BB HS MD TW WI BT WP WN JM NN TM GM HM DY 1.0

0.9

0.8

0.7

0.6

0.5

Genetic identity B CV WP MD TW WI BT MN BB HS

Distribution of variation among populations

WN HM DY JM GM NN TM 1.0

cereal crop, implying little sexual recombination between isolates in the field. Heterokaryosis and parasexual recombination may contribute to the high levels of haplotype diversity within G. graminis, as has been suggested for the rice blast fungus Magnaporthe grisea (DT l 0n61) (Xia et al. 1993). Most of the isozymes used in analysing G. graminis populations produce heterodimeric bands in heterokaryotic isolates (Goodwin 1997). In this study, every isolate produced only a single band for each enzyme locus, indicating that these isolates were not heterokaryotic. In addition, attempts to produce heterokaryons between genetically different isolates of G. graminis were unsuccessful and numerous vegetative incompatibility groups probably exist (Musker 1994). These results suggest that parasexual recombination is likely to be a rare event and does not generate much variation within G. graminis. Mutation may account for the high heterogeneity observed among G. graminis populations. As the pathogen is haploid, any non-lethal mutations which do arise will directly contribute to the overall diversity within populations. Assuming that sexual crossing between isolates is infrequent and that only clonally related isolates are likely to be vegetatively compatible (Musker 1994), populations of G. graminis may exist as a series of clonally reproducing lines, with genetic variation arising through mutation. This clonal sectoring of pathogen populations has previously been proposed for G. graminis (O’Dell et al. 1992) and is supported here by the low average number of multilocus genotypes in individual populations and within the collection as a whole.

0.9 0.8 0.7 0.6

0.5

0.4 0.3 0.2

0.1 0.0

Genetic identity

Fig. 4. Dendrogram showing the genetic identities among 16 Gaeumannomyces graminis populations for 13 isozyme loci (a) and 4 RFLP loci (b).

DISCUSSION Gaeumannomyces graminis is a haploid homothallic fungus and the frequency of outcrossing is likely to be low. As selffertilisation will result in ascospore progeny with the same genotype as the parental strain (Asher 1981), G. graminis was expected to be highly inbred and relatively homogeneous. Consequently, the high level of genetic variation within the species (DT l 0n446) was somewhat unexpected. Sexual recombination between isolates of Ggt has been shown to occur in vitro (Blanch, Asher & Burnett 1981, Pilgeram & Henson 1992). However, O’Dell et al. (1992) showed consistent genetic differences between rye-infecting (R) and non rye-infecting (N) isolates of Ggt existing in the same

Populations of Gaeumannomyces graminis had significantly different allele frequencies for all isozyme and RFLP loci and all but one of the multilocus genotypes were populationspecific. These data suggest that gene flow was restricted among populations and is supported by the significant levels of genetic differentiation between pairs of populations and the high overall level of GST among all 16 populations (0n595). This value is much greater than those for the wind-dispersed foliar pathogens Mycosphaerella graminicola (0n039) (Boeger et al. 1993) and Phaeosphaeria nodorum (0n03) (Keller et al. 1997). As G. graminis is soil-borne, dispersal is probably limited relative to these foliar pathogens and consequently this pathogen displays higher levels of population differentiation. Since ascospores become inviable after a few days of dry conditions and are considered to be epidemiologically insignificant within the cereal belt of southern Australia (Hornby 1981), migration of individuals may be restricted to wind dispersal of fine particles of infected plant materials. The levels of genetic differentiation among populations suggest however, that the frequency of successful establishment in new locations is low. Genetic drift is one explanation for the significant genetic differentiation between G. graminis populations and its two main causes are seasonal fluctuations in population size due to unfavourable environmental conditions and founder effects (Goodwin 1997). Microbial antagonism of saprophytically surviving inoculum (Rovira & Wildermuth 1981), changes in

Genetic variation in Gaeumannomyces graminis seasonal conditions (Sivasithamparam 1993) and shifts in host species (Bateman et al. 1997, Clarke et al. 1999) all cause significant reductions in the sizes of G. graminis populations. When numbers decrease and subsequently recover, populations pass through evolutionary bottlenecks and are likely to contain a lower genotypic diversity compared to the original population (Goodwin 1997). Genetic differentiation between populations of G. graminis may have resulted from genetic drift due to limited gene flow and localised reductions in the size and diversity of populations, as has been hypothesised for Cryphonectria parasitica (Liu et al. 1996). When a limited number of individuals establish a new population, it generally shows reduced genetic diversity compared with the population of origin and is said to exhibit a founder effect (Goodwin 1997). Such events may account for the NN and JM populations being comprised of the same multilocus genotype. Since these were the only populations to share a common multilocus genotype and given the apparent infrequency of inter-population gene flow, G. graminis populations probably arise only rarely from founder events. In general, the widespread reports of severe take-all in the first wheat crops after clearing native grasslands (Sivasithamparam 1993) and the high level of genetic diversity within G. graminis indicate that the pathogen is indigenous to Australia and probably was not introduced as a small founder population with cereal cropping. Distribution of genetic variation among host-groups Disease resistant hosts, such as oats and rye, are expected to apply intense host-mediated selection pressures upon Gaeumannomyces graminis populations, resulting in reductions in size and diversity in the recovering populations (Bateman et al. 1997, Carter et al. 1999). In this study the mean genetic differentiation among host-groups was high (GST l 0n307) and significant levels of differentiation were observed between populations from barley, oats and wheat. These results suggest that these cereals apply varying degrees of selection pressures and can have significant effects on the genotypic composition of G. graminis populations. If the intensity of host-mediated selection varies over space and time it can lead to considerable genetic differentiation between populations (Burdon & Silk 1997). Selection may therefore cause increased population differentiation above that resulting from genetic drift alone (Goodwin 1997). Oat-infecting isolates of G. graminis are widespread throughout cereal crops in southern Australia and were isolated in higher frequencies from oat crops and wheat following oats, compared with successive wheat or barley crops (Yeats et al. 1986). Carter et al. (1999) showed that avenacin concentrations in oat rhizospheres were inhibitory to Ggt, with the majority of isolates from consecutive oat crops and from wheat crops after oats being resistant to this compound. These results imply that oats select out avenacin resistant Gga pathotypes and suppress susceptible Ggt, causing shifts in the pathogenic and genotypic composition of G. graminis populations infecting subsequent cereal crops. In this study, host groups were defined on the basis of the current and preceding cereal crop and therefore, populations

934 isolated from oats (NN), or exposed to an oat crop in the previous year (DY, GM, HM and JM), are hypothesised to be Gga and\or avenacin resistant oat-infecting variants of Ggt (Yeats et al. 1986). The majority of isolates among these five populations (98 %) had the same multilocus RFLP genotype as Gga isolate 35793 and all five populations showed high genetic identities with both isozyme and RFLP analyses, despite having originated from three different geographical regions within southern Australia. These data suggest that oat cropping has resulted in the selection of genetically homogeneous, avenacin resistant pathogen genotypes and may cause genetic differentiation among G. graminis populations not recently exposed to this host. Barley shows a greater tolerance to infection by G. graminis compared with wheat (Scott 1981) and may apply weak selective pressures upon pathogen populations. When populations were sorted into host-based groups, barley populations (BB, HS and MN) showed significant levels of genetic differentiation to both wheat- and oat-based groups and also showed high genetic identities despite their considerable geographic separation. Bateman et al. (1997) also showed differences in the frequencies of Ggt genotypes parasitising barley compared with wheat and triticale. Collectively, these data imply that barley may also select out genotypes better adapted to parasitising this host, possibly resulting in genetic differentiation among G. graminis populations from other cereal species. In conclusion, significant levels of genetic differentiation among G. graminis populations and low genetic identities between geographically close populations implied low levels of inter-population gene flow. Significant genetic differentiation were also observed between populations from different cereal species, suggesting a sub-division of G. graminis populations into host-based groups, presumably resulting from host-mediated selection and infrequent sexual recombination between host-adapted pathotypes. These analyses suggest that random genetic drift, combined with shifts in the intensities of host-mediated selection pressures cause genetic differentiation among G. graminis populations. Consequently, populations may be comprised of a series of host-adapted clonal lines that vary in abundance and distribution in response to different crop management practices. Determining how rapidly G. graminis populations change in response to different cereal species will require monitoring of their genetic and pathogenic composition in response to crop rotation strategies at individual locations. A C K N O W L E D G E M E N TS This research was supported financially by the Australian Grains Research and Development Corporation (GRDC).

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