Plant Pathology (2008) 57, 540–551
Doi: 10.1111/j.1365-3059.2007.01779.x
Population structure and mating system of Ascochyta rabiei
in Tunisia: evidence for the recent introduction of mating
type 2
Blackwell Publishing Ltd
A. Rhaiema, M. Chérifa*, T. L. Peeverb and P. S. Dyerc
a
Laboratory of Plant Pathology, Institut National Agronomique de Tunisie, 43 Avenue Charles Nicolle, 1082 Cité Mahrajène, Tunis, Tunisia;
Department of Plant Pathology and Center for Reproductive Biology, Washington State University, Pullman, WA 99164-6430, USA; and
c
School of Biological Sciences, University of Nottingham, University Park, Nottingham, NG7 2RD, UK
b
The population structure of Ascochyta rabiei (teleomorph: Didymella rabiei) in Tunisia was estimated among five
populations sampled from the main chickpea growing regions using simple sequence repeat markers (SSR) and a mating
type (MAT) marker. Mating type 2 isolates (MAT1-2) had reduced genetic and genotypic diversity relative to mating type
1 isolates (MAT1-1). This result, coupled with previous observations of lower overall frequency and restricted geographical
distribution of MAT1-2 in Tunisia, and recent (2001) observation of the sexual stage, support the hypothesis of a recent
introduction of MAT1-2. Despite the presence of both mating types in Nabeul, Kef and Jendouba, the hypothesis of
random mating was rejected in these locations with multilocus gametic disequilibrium tests. Highly significant genetic
differentiation (θ = 0·32, GST = 0·28, P < 0·001) was detected among populations and genetic distance and cluster
analyses based on pooled allele frequencies revealed that populations from Nabeul and Kef were distinct from those in
Beja, Bizerte and Jendouba. More than 70% of total gene diversity (HT = 0·55) detected was attributable to variation
within populations compared to 28% among populations. This result, coupled with the occurrence of private alleles in
each population, suggests that gene flow is currently limited among populations, even those separated by short
geographic distances. The presence of two main genetic clusters was confirmed using Bayesian model-based population
structure analyses of multilocus genotypes (MLGs) without regard to geographic origin of samples. The presence of
MAT1-2 isolates in both clusters suggests at least two independent introductions of MAT1-2 into Tunisia that are likely
to be the result of importation and planting of infected chickpea seeds.
Keywords: ascochyta blight, chickpea, Didymella rabiei, genetic differentiation, population genetics, simple sequence
repeat markers
Introduction
Ascochyta blight, caused by Ascochyta rabiei (teleomorph
= Didymella rabiei), is one of the most serious diseases of
chickpea in many countries including Tunisia. The disease
can result in total crop loss in years with severe epidemics.
Fungicides are effective in controlling ascochyta blight but
are prohibitively expensive for resource-poor farmers.
Resistant cultivars are considered the best way to manage
this disease and much effort has been dedicated to
identifying resistant chickpea germplasm (Chen et al.,
2004a). The frequent occurrence of severe epidemics of
ascochyta blight in many regions on cultivars previously
*E-mail: [email protected]
[email protected]
Accepted 29 August 2007
540
thought to be resistant has led to the conclusion that no
chickpea germplasm has complete resistance to ascochyta
blight, but rather cultivars vary quantitatively in susceptibility/
resistance to the disease (Chen et al., 2004b). Pathogens
such as A. rabiei may evolve, increasing their virulence
and aggressiveness as a response to selection pressure
imposed by resistant cultivars. If resistant cultivars are to
be effective and durable, control methods should target
populations of pathogens rather than individuals
(McDonald, 1997). For this reason, it has become evident
that plant pathologists require a detailed knowledge of
genetic variation in pathogen populations that can be used
to guide resistance breeding (Milgroom & Peever, 2003).
Genetic structure refers to the amount and distribution
of genetic diversity within and among populations
(McDonald, 1997). It includes gene diversity and
genotype diversity and is controlled by five main
evolutionary forces: mutation, population size and
© 2008 The Authors
Journal compilation © 2008 BSPP
Population structure and mating system of Ascochyta rabiei
random genetic drift, gene and genotype flow, reproduction
and mating system, and selection (McDonald & Linde,
2002). Elucidating the genetic structure of a fungal
pathogen may reveal which forces have the greatest impact
on pathogen evolution. These studies can also reveal the
evolutionary history of the populations and give insight
into their potential to evolve (McDonald, 1997). In this
way, it may be possible to predict the ‘risk’ of pathogen
evolution, and assess this risk in order to improve control
strategies (McDonald & Linde, 2002). Knowledge of the
genetic structure of A. rabiei populations is important for
the effective breeding of ascochyta blight-resistant cultivars, for understanding the evolutionary processes leading
to breakdown of resistance genes, and to prevent the
development of fungicide resistance (Peever et al. 2004).
The genetic variation of A. rabiei has previously been
estimated using several marker systems including random
amplified polymorphic DNAs (RAPDs) (Chongo et al.,
2004), DNA fingerprinting with synthetic, tandemrepetitive oligonucleotide probes (Morjane et al., 1994),
and microsatellite-primed PCR (MP-PCR) (Geistlinger
et al., 1997). Twenty simple sequence repeat (SSR)
markers were developed by Geistlinger et al. (2000) and
these markers have been found to be more variable
than other types of molecular markers when applied to
A. rabiei (Peever et al., 2004). These markers have revealed
high levels of polymorphism among isolates from Tunisia,
USA, Pakistan, Syria and Turkey (Geistlinger et al., 2000;
Peever et al., 2004). Because of their hypervariability,
species-specificity, robustness and reproducibility, SSR
markers have become the marker system of choice for
population genetic studies of most organisms including
fungi (Geistlinger et al., 2000; Phan et al., 2003; Peever
et al., 2004). For example, the genetic structure of A. rabiei
has been determined in the Pacific Northwest of the USA
(Peever et al., 2004) and Australia (Phan et al., 2003).
Reproductive systems affect the way alleles are
organized in individuals and genetic recombination leads
to increased genotypic diversity (Milgroom, 1996). The
mating systems of plant-pathogenic fungi can vary from
strict inbreeding to obligate outcrossing (McDonald &
Linde, 2002). Whereas asexual pathogen population
structures are clonal, sexually-reproducing populations
usually exhibit a high degree of genotype diversity that
may increase their potential for adaptation in a changing
environment and thus affect control strategies (McDonald
& Linde, 2002; Milgroom & Peever, 2003). Both asexual
reproduction via conidia and sexual reproduction via
ascospores are important in the life cycle of the pathogen
(Kaiser, 1992) and the predominance of one mode of
reproduction relative to the other can affect population
structure (Peever et al., 2004). Ascochyta rabiei conidia
are exuded from pycnidia in a cirrhus and are spread, over
relatively short distances (metres) via rain splash and these
propagules are responsible for secondary disease cycles
during the growing season of the crop (Nene & Reddy,
1987; Kaiser, 1992). Ascospores of the teleomorph D. rabiei
are windborne and dispersed over long distance (TraperoCasas et al., 1996) and are thought to be important
Plant Pathology (2008) 57, 540–551
541
sources of primary inoculum in areas where both mating
types occur (Trapero-Casas et al., 1996; Kaiser, 1997b;
Peever et al., 2004). Ascochyta rabiei has been spread around
the world by human activity and now can be found infecting
cool season-food legumes in most areas where they are
produced (Morrall & McKenzie, 1974; Kaiser, 1997a;
Peever et al., 2004). Much of this movement has likely
been the result of introduction of infected and/or infested
seed imported for agronomic evaluation (Morrall &
McKenzie, 1974; Kaiser, 1992; Peever et al., 2004) with
transmission from seed to seedling (Kimber et al., 2006).
Ascochyta blight is the most economically significant
biotic constraint to chickpea productivity in Tunisia, as it
is in many chickpea-growing regions of the world (Mlaiki
& Ben Hamadi, 1984). One hypothesis to explain why
Tunisian farmers have moved from winter to spring
sowing of chickpea is that ascochyta blight is yieldlimiting in winter cropping systems (Guillochon, 1940).
However, despite the fact that the chickpea culture and
ascochyta blight have been known for hundreds of years
in Tunisia, the sexual stage of the pathogen was not
observed before 2001 (Rhaiem et al., 2006). Based on
previous studies of mating type distribution and the
demonstration that environmental conditions are
conducive to teleomorph development throughout
Tunisia (Rhaiem et al., 2006, 2007), it is speculated that
MAT1-2 has only recently been introduced into Tunisia.
This hypothesis was tested by estimating the population
structure and mating system of A. rabiei in Tunisia using
six SSR markers and a mating type marker that are
genetically unlinked and were demonstrated to be
polymorphic in previous population studies with A. rabiei
(Phan et al., 2003; Peever et al., 2004). These markers
were used to genotype 123 isolates of A. rabiei sampled
from the five main chickpea growing regions in Tunisia
in order to: (i) determine the population structure of
A. rabiei in Tunisia, and (ii) determine the mating system
and importance of the sexual stage of the fungus in
Tunisia based on associations among alleles at these loci.
Materials and methods
Sampling
Isolates of A. rabiei were obtained from naturally infected
chickpea plants sampled from Nabeul, Beja, Bizerte, Kef
and Jendouba which represent the major chickpea
growing regions of Tunisia (Table 1, Fig. 1). Samples were
collected during May, June and July of 2002 and 2003.
Leaves, stems and pods showing symptoms of ascochyta
blight were randomly chosen every 10 metres along two
to five parallel transects separated by at least 10 m. A total
of 114 isolates were obtained. Nine additional reference
isolates, sampled from 1997 to 2002 in the same areas,
were provided by Dr Mohamed Kharrat, Institut National
de la Recherche Agronomique de Tunisie (INRAT)
(Table 1). For the purposes of this study, samples of
isolates from each of the five regions are referred to as
populations.
542
A. Rhaiem et al.
Location
Collection site
Date
Number of
fields sampled
Number
of isolates
Nabeul
Menzel Temime
Menzel Temime
Kelibia
Unknown
Tamazrat
Route of Bousalem
North of Beja
Route of Beja-Mateur
Oued Beja
Oued Beja
Ain Ghalel
Route of Oum Heni-Mateur
Oum Heni
Mateur
Krib
Oued Souani
Touiret
Bahia
Bousalem
Kodia
Oued Mliz
Oued Mliz
Fernena
Fernena
Route of Bousalem-Tabarka
2002
2003
2003
2003
2003
2003
2003
2003
2000
2000
2003
2003
2003
2003
2003
2003
2001
2001
2002
2002
1997
2000
2000
2003
2001
9
2
1
1
1
1
1
1
1
1
3
1
1
1
6
1
1
1
1
1
1
1
1
1
1
16
3
1
1
1
2
1
7
1
1
4
1
42
2
28
2
1
1
1
2
1
1
1
1
1
Beja
Bizerte
Kef
Jendouba
Table 1 Ascochyta rabiei isolates used in this
study
Figure 1 Map of Tunisia (a) with the five
chickpea-growing regions from which
Ascochyta rabiei isolates were sampled (b).
Populations where both mating types are
present are underlined.
Isolation, culturing and DNA extraction
Chickpea leaves, stems and pods infected with ascochyta
blight were cut into 4 to 10 mm2 pieces and surface-disinfected, placed on 2% water agar medium and incubated
at 20°C for 24 to 48 h. Following production of conidia,
infected tissues were removed and small cubes of water
agar with discharged conidia were excised and transferred
to chickpea medium (filtrate of 30 g chickpea seed boiled
for 30 min, 20 g L–1 sucrose, 20 g L–1 agar). Cultures were
incubated at 20°C in the dark for 5 to 7 days. When pure
colonies of A. rabiei were obtained, isolates were singlespored and stored at − 20°C. To provide mycelium for
DNA extraction, isolates were first cultivated on V8 juice
agar medium (200 mL V8 juice, 3 g CaCO3, 20 g agar,
800 mL distilled H2O) at 20°C for 10 to 15 days. Mycelium was scraped from the surface of the plates and used
to initiate cultures in 250 mL-flasks containing 50 mL of
liquid 2-YEG medium (2 g L–1 yeast extract, 10 g L–1
glucose). After 5–6 days on a rotary shaker at 175 rpm
and 20°C, mycelia were harvested from the flasks by
vacuum filtration with potassium phosphate buffer (0·1 m
K2HPO4, 0·1 m KH2PO4, pH 7), lyophilized in 9 cm-Petri
dishes and stored at –85°C. Mycelium of each isolate was
finely ground using liquid nitrogen and total genomic
DNA was extracted following the protocols of Murtagh
et al. (1999) and Lee & Taylor (1990) or using the
DNeasy® Plant Mini Kit (Qiagen Ltd). DNA concentrations
were estimated visually in 0·8% Agarose gels stained with
4 ng mL–1 ethidium bromide with uncut lambda DNA as
a standard.
Simple sequence repeat (SSR) markers
One hundred and twenty three Tunisian isolates of
A. rabiei were screened for variation at six SSR loci
Plant Pathology (2008) 57, 540–551
Population structure and mating system of Ascochyta rabiei
(Geistlinger et al., 2000). Variation at four of these loci,
plus the mating type locus (Barve et al., 2003), were used
to determine the population structure of A. rabiei in the
US Pacific Northwest (Peever et al., 2004). Two additional
loci (ArR01D, ArH06T) were subsequently determined to
be genetically unlinked to the previous four and also to the
mating type locus (TLP, unpublished data). PCR with the
A. rabiei SSR primer pairs was performed as described by
Peever et al. (2004) with the following modifications.
Amplification of the SSR loci was carried out in 25 µL
volumes containing 16 ng of genomic DNA, 1 × PCR
buffer (50 mm KCl, 10 mm Tris-HCl pH 9, 0·1% Triton
X-100) (Promega or New England Biolabs), 1 mm MgCl2
(Promega), 0·2 mm dNTPs (Life Sciences, Fermentas Inc.),
0·8 µm of 5′-fluorescent-labelled forward DNA primer
(Applied Biosystems), 0·8 µm of unlabelled reverse DNA
primer (Operon Biotechnologies) and 1U Taq polymerase
(New England Biolabs). Cycling conditions consisted of
an initial denaturation at 96°C for 1 min followed by 35
cycles of 96°C for 30 s, 57°C for 30 s and 70°C for 30 s.
All PCR were carried out in a Hybaid Omn-E thermocycler (Hybaid). Annealing temperatures were optimized for
each primer pair and ranged between 57 and 63°C with
some adjustment in annealing temperatures required with
labelled versus unlabeled primers. PCR amplicons were
separated on 1·7% agarose gels, stained with 400 µg mL–1
ethidium bromide in 1 × TBE buffer for 45 min at 6·7 V
cm–1. A 100 bp ladder (Life Sciences, Fermentas Inc.) was
run in the outer lanes of each gel as a size standard. All
markers were reproducible and clearly resolvable.
Scoring and sequencing of SSR alleles
Microsatellite alleles were scored on an ABI PRISM 3100
Capillary Sequencer (Applied Biosystems). Chromatograms were analysed using GeneScan v.3·7 (Applied
Biosystems) and GeneScan files were imported into
Genotyper v.3·7 (Applied Biosystems) for comparisons.
Representative alleles for each locus were sequenced on
both strands to determine the repeat motif for each allelic
class. The same primer pair developed by Geistlinger et al.
(2000), used to PCR-amplify locus ArH02T, was used for
Table 2 SSR-specific primers used for
sequencing representative allelic size classes
in Ascochyta rabiei
sequencing. New primer pairs producing larger amplicons
to facilitate sequencing were designed for ArR12D,
ArA06T, ArH05T, ArH06T and ArR01D (Table 2).
Primers (Operon Biotechnologies Inc.) were designed from
sequences deposited in GenBank (GenBank Accession
Nos. AJ246975, AJ246951, AJ246966, AJ246967 and
AJ246971 respectively) by Geistlinger et al. (2000) using
Primer 3 (Rozen & Skaletsky, 2000). PCR conditions
were re-optimized for the newly designed primer pairs
and annealing temperatures used ranged between 54 and
58°C. Sequence reactions and cycling sequence conditions
were performed as described by Peever et al. (2004).
Mating type marker
Mating type of each isolate was determined using the
MAT-specific PCR assay developed by Barve et al. (2003).
The MAT1-1-specific primer Sp21, a MAT1-2 specific
primer Tail 5, and a flanking region-specific primer
Com1 were combined in equal concentrations in a single
PCR reaction. PCR reactions were carried out in 25 µL
volumes containing 10 ng genomic DNA, 1 × PCR buffer
with 1·5 mm MgCl2 (ABgene), 0·2 mm dNTPs (Advanced
Biotechnologies Inc.), 1U Red Hot DNA Taq polymerase
(ABgene), 2 µm of each primer (Operon). Cycling conditions consisted of an initial denaturation at 94°C for
4 min followed by 45 cycles of 94°C for 45 s, 58°C for
45 s, 72°C for 1 min, and a final extension at 72°C
for 5 min. Amplified products were separated in 1%
agarose gels, stained with 400 µg mL–1 ethidium bromide.
A 100 bp DNA ladder (Invitrogen) was run in the outer
lanes of the gel as a size standard.
Data analysis
Gene diversity and genetic differentiation
Observed and effective numbers of alleles (Kimura &
Crow, 1964) and allele frequencies were estimated for
each SSR locus and the mating type locus in each
population using POPGENE Version 1·32 (Molecular
Biology and Biotechnology Centre, University of Alberta,
Edmonton, Canada). Homogeneity of allele frequencies
Locus
Accession
numbera
ArR12D
AJ246975
ArA06T
AJ246951
ArH05T
AJ246966
ArH06T
AJ246967
ArR01D
AJ246971
a
543
Primer sequence (5′→3′)
ACACTGAAATCCCTCGTGCTC
GTCAGACGACGGGCCTTG
GTATACGCTCCTTAAATTGCAACC
GGGTACTTTCTAGCACGCTGT
GGTCTTTGATTATTATGGAGTACCA
GAAGCCAATGTCGTCGGACT
CGGGCAAGCGTGCAACTCTC
TACCGCCTCGCCTGCTGCTG
GCGATTACGATCACGGTGTA
GTCCTAGCGCGTCAGCAG
Expected
size (bp)b
310
390
490
359
341
Accession numbers of sequences deposited in GenBank by Geistlinger et al. (2000).
Expected sizes of sequenced clones (Geistlinger et al., 2000).
b
Plant Pathology (2008) 57, 540–551
544
A. Rhaiem et al.
among populations was estimated using a chi-squared (χ2)
test and a likelihood ratio test (G2) in POPGENE. Differentiation among populations was tested using Weir’s θ
(Weir, 1996). The null hypothesis of no population
differentiation (θ = 0) was tested by comparing observed
θ values to values obtained from 1000 artificially
randomized datasets where multilocus genotypes were
permuted among populations using the programme
MULTILOCUS version 1·3 (Agapow & Burt, 2001).
Gene diversity (H) was estimated for each locus, within
each population (Nei, 1973). Gene diversity for the entire
population (all Tunisian locations) (HT), gene diversity
within population (HS) as well as Nei’s gene differentiation
or gene diversity attributable to differentiation among
populations (GST) were estimated (Nei, 1973) in POPGENE. Gene diversity of isolates of each mating type in
each population was compared using a Mann-Whitney
(U) non-parametric test for independent samples
implemented in STATISTICA (Kernel version 5·5, StatSoft,
Maisons-Alfort France).
Genotypic diversity
Genotypic diversity (D), was estimated according to the
formula D = n/ n − 1(1 − ∑ Pi2) (Pielou, 1969) implemented
in MULTILOCUS. The null hypothesis of zero genotypic
diversity was tested by comparing observed D values to
values in expected 1000 artificially randomized datasets
where individuals (multilocus genotypes) were permuted
within each population. Total number of unique genotypes
and the frequency of the most frequent genotype
occurring in each population were determined using
MULTILOCUS.
Cluster analyses
Nei’s unbiased measures of genetic identity and genetic
distances within and among populations were estimated
using POPGENE. Pooled allele frequencies within each
population were used to generate an unrooted phenogram
based on Nei’s standard distance (DS) clustered using the
unweighted pair group method with arithmetic averaging
(UPGMA). Data was subject to bootstrap resampling
with 1000 replications implemented in FREETREE v.
0·9·1·50 (Pavlicek et al., 1999). The consensus tree was
displayed using TREEVIEW v. 1·6·6 (Page, 1996). A Bayesian
model-based clustering method using multilocus genotype
data implemented in the STRUCTURE software package
Version 2·0 was used to infer population structure and
assign individuals to populations, adopting an admixture
model (Pritchard et al., 2000). Analysis was performed
using 105 burn-in replicates and a run length of 106
replicates. Log likelihood values and posterior probabilities
were estimated assuming one to seven population clusters
(K = 1, 2 ... 7). Three independent runs were performed
for each analysis in order to verify the convergence
of parameter estimates. Two different analyses were
performed using this model: (i) both SSR and MAT
markers were included and isolates were classified by
location in order to determine if the same genotypes were
present in the different locations; and (ii) analyses based
on SSR markers only, isolates were initially classified by
mating type in order to determine if SSR allele frequencies
differed significantly between the two mating types (MAT1-1
and MAT1-2).
Mating system
The index of association (IA) (Brown et al., 1980) as well
as multilocus gametic disequilibrium values (rd) and the
proportion of compatible pairs of loci were estimated
within each population as implemented in MULTILOCUS
(Agapow & Burt, 2001). The hypothesis of random
mating within populations (only estimated for samples
with n = 16 or greater and collected from a single location
during the same season) was tested based on the significance of IA and rd and using non-clone-corrected and
clone-corrected datasets. The null hypothesis of complete
panmixia was tested by comparing the observed IA or rd
values to datasets in which an infinite amount of
recombination has been generated by randomly shuffling
the alleles among individuals 1000 times independently
for each locus, and within each population (Agapow &
Burt, 2001).
Results
Genetic diversity
Each of the six SSR primer pairs produced a single
amplicon for each locus from each isolate as expected for
a haploid ascomycete fungus. Two to seventeen alleles
were detected per locus among all isolates. Sequencing of
representative alleles for each locus revealed the same
repeat motif for each allelic size class (Table 3). All loci
were polymorphic and differences of one to three base
pairs, which were confirmed by sequencing on both DNA
strands, could be detected among alleles using the
capillary sequencer. All SSR loci were polymorphic in the
Nabeul, Bizerte, Kef and Jendouba populations, while
ArR12D and ArA06T were monomorphic and ArH05T,
ArR01D, ArH06T and ArH02T polymorphic only in the
Beja population. Observed numbers of alleles per locus in
each population ranged from one to ten, and effective
numbers of alleles varied between one and seven (data not
shown). Sixty-four alleles were detected among the
Tunisian isolates, 36 (56%) of which were private (only
present in one location) (Slatkin, 1985). Nineteen alleles
were found exclusively in Kef, 14 in Nabeul, two in
Bizerte and one in Jendouba. Among the 64 alleles
detected, eleven (17%) occurred in two locations, six
(9%) occurred in three locations, five (8%) occurred in
four locations and six (9%) occurred in all populations
(data not shown).
Population structure
Significant heterogeneity in allele frequencies (P < 0·001)
was detected among the five populations. θ values ranged
from 0·17 and 0·48 for each locus and differentiation
Plant Pathology (2008) 57, 540–551
Population structure and mating system of Ascochyta rabiei
545
Table 3 Size and repeat motifs of sequenced SSR alleles of Ascochyta rabiei
Locusa
Number
of allelesb
ArH05T
Allelec
Sized
Repeat Motife
17
A
B
C
D
E
F
G
H
I
J
K
L
M
N
O
P
Q
180
182
185
188
191
194
200
212
215
236
239
242
255
320
336
353
394
(CTT)13
(CTT)14
nd
nd
(CTT)17
nd
(CTT)20
nd
nd
(CTT)32
nd
(CTT)34
nd
nd
nd
nd
nd
ArR12D
10
A
B
C
D
E
F
G
H
I
J
158
160
164
167
175
185
206
211
225
227
(CA)14
(CA)15
(CA)17
(CA)19
(CA)23
(CA)27
(CA)37
(CA)39
nd
(CA)49
ArR01D
3
A
B
C
162
187
195
(GTGTGTGG)0
(GTGTGTGG)2
(GTGTGTGG)3
ArH06T
15
A
B
C
D
E
F
G
H
I
J
K
L
M
N
O
148
155
167
170
173
176
181
187
190
193
228
231
234
245
248
(CAA)2(CAG)5CAACGA(CAA)7(CAG)6CAACGA(CAA)2CCAAAA(CAA)13
(CAA)2(CAG)5CAACGA(CAA)5(CAG)6CAACGA(CAA)2CCAAAA(CAA)15
(CAA)2(CAG)5CAACGA(CAA)7(CAG)6CAACGA(CAA)2CCAAAA(CAA)17
nd
nd
(CAA)2(CAG)5CAACGA(CAA)10(CAG)6CAACGA(CAA)2CCAAAA(CAA)17
nd
(CAA)2(CAG)5CAACGA(CAA)7(CAG)7CAACGA(CAA)2CCAAAA(CAA)23
nd
(CAA)2(CAG)6CAACGA(CAA)7(CAG)5CAACGA(CAA)2CCAAAA(CAA)25
(CAA)2(CAG)5CAACGA(CAA)7(CAG)6CAACGA(CAA)10(CAG)6CAACGA(CAA)2CCAAA(CAA)19
nd
nd
nd
(CAA)2(CAG)5CAACGA(CAA)7(CAG)6CAACGA(CAA)10(CAG)6CAACGA(CAA)2CCAAA(CAA)27
ArH02T
17
A
B
C
D
E
F
G
H
I
J
K
L
M
N
O
P
Q
265
279
282
285
297
300
303
309
312
315
324
327
330
333
336
342
345
(GAA)25 (GTA)6
(GAA)30(GTA)6
(GAA)31(GTA)6
(GAA)31(GTA)7
nd
(GAA)36(GTA)7
nd
(GAA)39(GTA)7
nd
(GAA)41(GTA)7
(GAA)45(GTA)6
nd
nd
(GAA)47(GTA)7
(GAA)48(GTA)7
(GAA)50(GTA)7
(GAA)52(GTA)6
ArA06T
2
A
B
132
157
(CAACAC)5(CAC)1
(CAACAC)7(N)6(CAC)3
a
SSR locus code (Geistlinger et al., 2000).
Total number of alleles detected for each locus.
c
Alleles coded by letter for each locus.
d
Size of amplicon in base pairs.
e
Repeat motif of sequenced allele (nd = not determined).
b
Plant Pathology (2008) 57, 540–551
546
A. Rhaiem et al.
Table 4 Gene diversity and differentiation among five populations of Ascochyta rabiei in Tunisia
Gene diversity by population
Locus
Nabeul
Beja
Bizerte
Kef
Jendouba
H Tc
HSd
c
GST
θf
ArH05T
ArR12D
ArR01D
ArH06T
ArH02T
ArA06T
MAT
Mean
0·82b
0·69
0·35
0·73
0·85
0·43
0·48
0·62
0·29
0·00
0·15
0·15
0·29
0·00
0·00
0·13
0·51
0·12
0·15
0·15
0·39
0·08
0·00
0·20
0·81
0·61
0·63
0·80
0·86
0·47
0·48
0·67
0·56
0·22
0·22
0·56
0·56
0·22
0·37
0·39
0·79
0·39
0·51
0·70
0·74
0·42
0·34
0·56
0·60
0·33
0·30
0·48
0·59
0·24
0·27
0·40
0·24
0·16
0·41
0·31
0·21
0·42
0·20
0·28
0·23***
0·17***
0·46***
0·39***
0·23***
0·48***
0·28***
0·32***
a
a
SSR locus (Geistlinger et al., 2000) or MAT locus (Barve et al., 2003).
Nei’s gene diversity within each population (Nei, 1973).
c
Gene diversity within the total population (Nei, 1973).
d
Mean gene diversity within populations (Nei, 1973).
e
Gene diversity attributable to differentiation among populations (Nei, 1973).
f
Population differentiation (Weir, 1996). Null hypothesis of no differentiation (θ = 0) was tested by comparing θ values from 1000 randomized data
sets to θ estimated from the observed data sets. ***P < 0·001.
b
among populations was significant as indicated by
randomization tests (Table 4). Gene diversities at each
SSR locus ranged from 0·34 to 0·79 and were higher in
Kef and Nabeul compared to Bizerte, Jendouba, and Beja
(Table 4). Gene diversity (HT) for the overall A. rabiei
Tunisian population based on both SSR and MAT markers
was estimated to be 0·56 with 28% attributable to differentiation among populations and 72% to variation within
populations (Table 4). The highest heterozygosities were
obtained for ArH05T and ArH02T. Forty-eight multilocus
genotypes (MLG) were identified among all isolates with
only three genotypes present in more than one location.
Thirty-five genotypes were present only once in the overall
population. Only one MLG (mating type 1) was detected
in all five populations (Table 5). Twenty-three genotypes
were observed in Kef, 13 in Nabeul, 10 in Bizerte, five in
Jendouba and four in Beja. Multilocus genotypes of
mating type MAT1-1 isolates did not completely overlap
those of mating type MAT1-2 isolates. The non-parametric
Mann-Whitney test for independent samples revealed that
gene diversity was significantly higher among mating
type MAT1-1 isolates compared to mating type MAT1-2
isolates (P < 0·05) (data not shown). Among the twentyfour MAT1-2 isolates, 12 unique MLG were detected,
with 11 found only in one location. Genotypic diversities
were significantly greater than 0 in all five populations
(P < 0·05) with P-values below 0·001 in Nabeul, Bizete
and Kef (Table 5). Plots of genotypic diversity vs. number
of loci revealed that the high values of genetic diversity
obtained in Nabeul, Kef and Jendouba population
have reached a plateau whereas scoring more loci is
likely to increase the genotypic diversity for the Beja and
Bizerte populations of the pathogen (data not shown).
Genotypic diversity in Nabeul, Kef and Jendouba
populations was higher than that observed in Beja and
Bizerte (Table 5).
Figure 2 Unrooted phenogram estimated among Tunisian Ascochyta
rabiei populations from the five main chickpea growing areas in Tunisia
(Nabeul, Beja, Bizerte, Kef and Jendouba) based on SSR and MAT
allele frequencies. The phenogram was generated based on Nei’s
standard distance (DS) and using the unweighted pair group method
with arithmetic averaging (UPGMA). Numbers at major branches
indicate the percentage occurrence of the cluster adjacent to the
branch in 1000 bootstrapped data sets.
The UPGMA phenogram estimated using pooled allele
frequencies in each population revealed two distinct
groups, each with high bootstrap support (Fig. 2). One
group contained the Nabeul and Kef populations and the
Plant Pathology (2008) 57, 540–551
Population structure and mating system of Ascochyta rabiei
547
Table 5 Occurrence of multilocus genotypes (MLG) among five populations of Ascochyta Rabiei in Tunisia
Populations
a
MLG
Nabeul
Beja
Bizerte
Kef
Jendouba
G1
G2
G3
G4
G5
G6
G7
G8
G9
G10
G11
G12
G13
G14-G19
G20; G21
G22-G27
G28-G46
G47; G48
Nib
Nuc
F md
De
×
–
–
×
×
×
×
×
×
–
–
–
–
×
–
–
–
–
22
13
5
0·935***
×
×
–
–
–
–
–
–
–
–
–
–
–
–
×
–
–
–
12
4
9
0·454*
×
×
–
–
–
–
–
–
–
×
×
–
–
–
–
×
–
–
49
10
28
0·643***
×
–
×
–
–
–
–
–
–
–
–
×
×
–
–
–
×
–
32
23
7
0·949***
×
×
–
–
–
–
–
–
–
–
–
–
×
–
–
–
–
×
8
5
4
0·785**
Total
occurrence
37
19
7
5
2
2
2
2
2
2
2
2
2
1
1
1
1
1
123
48
0·882***
a
Multilocus genotype (G1 to G48) based on alleles obtained at six SSR loci ArA06T, ArH02T, ArH05T, ArH06T, ArR01D, ArR12D and the MAT locus.
Total number of isolates sampled per population.
c
Number of unique multilocus genotypes in each population.
d
Frequency of the most common genotype.
e
Genotypic diversity (Pielou, 1969). Null hypothesis of no genotypic diversity was tested by comparing D-values obtained from 1000 randomized
data sets to those estimated from the observed data set. *0·01 < P < 0·05, **0·001 < P < 0·01, ***P < 0·001.
b
other the Bizerte, Jendouba and Beja populations. Within
this latter group, Beja could be differentiated from
Bizerte and Jendouba with 79% bootstrap support (Fig. 2).
STRUCTURE analysis revealed the highest posterior
probability for five populations among all isolates (Fig. 3a).
Eighty to 90% of the isolates in Bizerte, Beja and Jendouba
were assigned with high probability to population 1. The
remaining isolates (10–20%) were assigned to population
2, 3 or 4. Isolates from Nabeul and Kef were assigned to
five populations (1, 2, 3, 4, 5) with different probabilities.
Population 5 appears to be present with high probability
only in the Kef and Nabeul populations. STRUCTURE
results were consistent with those obtained using genetic
distance analysis of pooled allele frequencies. Two major
groups were identified in both analyses with substructuring evident within each major group. When the mating
type locus was removed from the STRUCTURE analysis,
two populations were revealed, one corresponding to
each mating type (Fig. 3b).
Mating system
The null hypothesis of random mating was rejected
(P < 0·01) in Nabeul, Kef and Bizerte based on multilocus
gametic disequilibrium tests (IA and rd) for both clonecorrected and non clone-corrected datasets (Table 6).
Plant Pathology (2008) 57, 540–551
Random mating was also rejected (P < 0·001) in Nabeul,
Bizerte and Kef based on the locus compatibility test with
the non clone-corrected samples but could not be rejected
(P > 0·05) in all of the clone-corrected populations. Random mating could not be rejected (P > 0·05) using the
mating type ratio test in Nabeul and Kef for both non
clone-corrected and clone-corrected datasets but was
consistently rejected in Bizerte (Table 6).
Discussion
Reduced genetic and genotypic diversity of MAT1-2 isolates, lack of gene flow between MAT1-1 and MAT1-2
isolates, and restricted distribution and lower overall frequency of MAT1-2 isolates (Rhaiem et al., 2007) all support the hypothesis that MAT1-2 of A. rabiei has recently
been introduced to Tunisia. The sexual stage, D. rabiei,
was only observed in Tunisia in 2001 despite many hundreds of years of chickpea cultivation (Rhaiem et al.,
2006), lending further support for the hypothesis of a
recent introduction of MAT1-2. Environmental conditions conducive to teleomorph development exist in all
chickpea growing areas of Tunisia (Rhaiem et al., 2006),
so lack of teleomorph development is likely attributable to
spatial separation of mating types, possibly on a very
small scale. Although both mating types occur in Nabeul,
548
A. Rhaiem et al.
Figure 3 Estimated membership coefficient for each individual Ascochyta rabiei isolate inferred with the highest posterior probability using
STRUCTURE analysis and based on SSR and MAT multilocus genotypes. Isolates are represented by single vertical bars divided into five coloured
segments (dark grey, white, grey, black and light grey) corresponding to the inferred membership fraction in population 1, 2, 3, 4 or 5. (a) Isolates
are classified by location. (b) Figure is split into two sections by mating type. Figs a and b were obtained with independent STRUCTURE analyses.
Therefore, the same colour between figures does not refer to the same population.
Table 6 Multilocus gametic disequilibrium, mating type ratios and tests for random mating within Ascochyta rabiei populations from Tunisia
Sample
N
ia
Nabeul
16
Bizerte
49
Kef
28
Nabeul-CCi
8
Bizerte-CC
12
Kef-CC
20
Compatibility of locib
Gametic disequilibriumc
Pr Comp
P
IA
P
rd
P
Ratiod
1·000g
(1·000)h
0·933
(0·952)
0·200
(0·286)
1·000
(1·000)
0·933
(0·952)
0·200
(0·286)
0·000
(0·000)
0·001
(0·001)
< 0·001
(< 0·001)
0·410
(0·062)
0·458
(0·466)
0·175
(0·007)
1·863
(1·845)
2·429
(2·429)
1·366
(1·461)
1·039
(0·675)
2·179
(2·170)
0·331
(0·339)
0·000
(0·000)
< 0·001
(< 0·001)
< 0·001
(< 0·001)
0·002
(0·031)
< 0·001
(< 0·001)
0·005
(0·004)
0·375
(0·311)
0·513
(0·513)
0·279
(0·248)
0·213
(0·116)
0·450
(0·450)
0·068
(0·058)
0·000
(0·000)
< 0·001
(< 0·001)
< 0·001
( < 0·001)
0·002
(0·031)
< 0·001
(< 0·001)
0·005
(0·004)
10:6
1·000
0·317
49:0
49·000
0·000
16:12
0·571
0·449
6:2
1·000
0·317
12:0
12·000
0·000
14:6
3·200
0·074
Mating type
χ2e
Pf
a
Number of isolates analyzed.
Proportion of compatible pairs of loci (Agapow & Burt, 2001). Null hypothesis of no gametic disequilibrium (Pr Comp = 0).
c
Two measures of gametic disequilibrium: IA, the index of association (Brown et al., 1980) and rd, the multilocus gametic disequilibrium (Agapow &
Burt, 2001). Null hypotheses of random mating (IA = 0; rd = 0).
d
Mating type 1 (MAT1-1): mating type 2 (MAT1-2).
e 2
χ -value for the test of 1:1 ratio.
f
Probability of greater χ2-value under the null hypothesis of 1:1 ratio (with 1 degree of freedom).
g
Values obtained with SSR loci only.
h
Values obtained when both SSR and MAT loci were included in the analysis.
i
-CC: clone-corrected datasets.
b
Kef and Jendouba (Rhaiem et al., 2007), these A. rabiei
populations do not appear to be freely recombining. The
ability to reject the hypothesis of random mating in
Nabeul, Kef and Jendouba, even after clone correction,
the skewed ratio of MAT1-2 compared to MAT1-1,
and the genetic differentiation between MAT1-1 and
MAT1-2 all indicate that recombination is limited in
Tunisia.
Plant Pathology (2008) 57, 540–551
Population structure and mating system of Ascochyta rabiei
The significantly reduced genetic and genotypic diversities observed among MAT1-2 isolates compared to
MAT1-1 isolates provide evidence for a restricted introduction of MAT1-2 isolates and possible genetic bottleneck. MAT1-2 isolates from several populations had
similar multilocus genotype (MLG) (i.e. only different
alleles at one locus) that may reflect a restricted introduction followed by one-step mutation of SSR loci within
populations. The predominance of asexual reproduction
in Tunisian A. rabiei populations may also explain the
restricted gene flow between populations, since A. rabiei
conidia are rarely distributed horizontally more than a
few metres from their source and much shorter distances
than ascospores (Kaiser, 1997b; Milgroom & Peever,
2003). There are many possible sources for the introduction
of MAT1-2 into Tunisia during the last ten years. Both
mating types have been reported in Turkey (Kaiser &
Küsmenoglu, 1997), Syria (Kaiser, 1997b) and Canada
(Armstrong et al., 2001). The importation of chickpeas
into Tunisia from these countries has almost doubled
between 1990 and 2000 (Anonymous, 2002). In support
of this observation, the Bayesian assignment analysis
showed that MAT1-2 isolates were subdivided into two
populations, which strengthens the hypothesis that at
least two independent introductions of this mating type
have occurred.
Only one MLG (mating type 1) was common to all five
populations in Tunisia. Higher frequencies of this MLG
were detected in Bizerte (57%), Jendouba (50%) and Beja
(17%) compared to Nabeul (5%) and Kef (8%). The
presence of this MLG in the five Tunisian populations
sampled for this study and one isolate sampled from
Jendouba in 1997 may suggest dispersal of this genotype
from a common source population, most likely by seed,
and its establishment in the different chickpea growing
areas. Restricted migration of A. rabiei among populations in Tunisia can be attributed to limited exchange of
seed among regions, since 90% of seeds used by Tunisian
farmers come from their own fields or from local small
markets in the same region (Ghanmi, 2001). In the
Maghreb countries in general, and in Tunisia in particular,
the use of certified seed is limited and almost all certified
chickpea seed is imported from outside the country.
Chickpeas imported for consumption are also likely to be
used by some farmers as seed. Importation of chickpea
seed has increased from 400 Mt in 1993 to 19 000 Mt in
2003 (FAO, 2004) and chickpeas have been imported
from many countries including Egypt, Syria, Morocco,
Turkey, Canada, Mexico, Lebanon and Iran (Anonymous,
2005). Chickpea seed is rarely exchanged between regions
in Tunisia, regardless of whether they come from farmers’
own production, from local markets or imported from
outside the country.
Based on the ability to reject the hypothesis of random
mating in Nabeul, Kef and Jendouba, these genotypically
diverse populations are likely to be derived from seedborne inoculum or local spread via conidia. The coexistence
of both mating types in these locations and eventual
introduction of MAT1-2 into all areas of Tunisia will
Plant Pathology (2008) 57, 540–551
549
result in changes in the epidemiology of ascochyta blight.
Environmental conditions are conducive to development
of the sexual stage throughout Tunisia (Rhaiem et al.,
2006) so appearance of the sexual stage in these areas will
presumably be driven by migration of MAT1-2 into these
locations. The occurrence of the teleomorph in Tunisia
will lead to important changes in the epidemiology of
the disease such as long distance dispersal by ascospores
(Milgroom & Peever, 2003), and by affecting survival of
the pathogen (Kaiser, 1992). Genetic recombination
through the sexual stage may also result in new genotypes
better adapted to resistant chickpea germplasm. Pathogens that possess a mixed reproduction system with at
least one sexual cycle per growing season are considered
to pose the greatest risk for overcoming resistance genes
(McDonald & Linde, 2002). The coexistence of both
sexual and asexual reproduction has been shown to play
an important role in the epidemiology and population
biology of several plant pathogenic fungi (Chen et al.,
2002; Bennett et al., 2005) including A. rabiei (TraperoCasas & Kaiser, 1992; Trapero-Casas et al., 1996;
Armstrong et al., 2001; Galloway & MacLeod, 2003;
Milgroom & Peever, 2003; Bayraktar et al., 2007).
Highly significant genetic differentiation was detected
among A. rabiei populations sampled from five representative chickpea-growing regions of Tunisia. The genetic
differentiation revealed here with six SSR markers and the
mating type marker was significantly higher than that
detected by Peever et al. (2004) among A. rabiei populations
sampled from the US Pacific Northwest and by Phan et al.
(2003) among A. rabiei isolates from Syria, US and Canada
and Australia using the same markers. In Tunisia, where
chickpea has been cultivated for hundreds of years and
ascochyta blight may have been present for much of this
time, the high level of differentiation observed among
A. rabiei populations relative to Australia, Canada and
the USA may not be unexpected. Genetic drift may have
had much more time and many more generations to
operate in Tunisia compared to other areas where A.
rabiei has been more recently introduced. Increased drift
may also be favoured by the specific attributes of Tunisian
agroecosystems. Relatively small fields are cultivated by
Tunisian farmers and such fields may harbour smaller
populations of A. rabiei compared to regions where largerscale agriculture is practiced. In such agroecosystems with
patchy distributions of host and pathogen, random genetic
drift may play a more important role in shaping population
structure. Selection by host cultivar is another possible
explanation for the differentiation observed among
Tunisian A. rabiei populations. Researchers in Tunisia
have identified new sources of resistance to ascochyta
blight in chickpea by screening chickpea germplasm that
is adapted to Tunisian agriculture. Some of these cultivars
have been released to farmers (Halila & Harrabi, 1990).
Unfortunately, no records are available regarding the
frequency with which these cultivars are being grown in
these regions. Access to this kind of data, coupled with
knowledge of how these cultivars respond to different
genotypes of A. rabiei present in Tunisia, might allow
550
A. Rhaiem et al.
inferences to be made regarding potential selection by
host cultivar and how this might be influencing population
structure.
Genetic distance analyses based on pooled allele
frequencies within populations or model-based Bayesian
assignment revealed two main clusters of isolates in
Tunisia. The Kef and Nabeul populations were distinct
from those of Beja, Jendouba and Bizerte. A preliminary
population structure analysis using ten RAPD primers
with 40 A. rabiei isolates representative of these same
chickpea growing regions of Tunisia revealed a similar
structure (Rhaiem et al., 2007). Restricted migration of
A. rabiei among different chickpea-growing regions of
Tunisia is supported by the high number of ‘private’ alleles
detected in each population and by the high number of
multilocus genotypes (MLG) specific to each location. In
addition, high local variability of the pathogen was detected
within single fields. The genetic similarity observed
among isolates from Beja, Bizerte and Jendouba may be
due to geographic proximity and gene flow or to founding
of these populations from a common source population.
The strong genetic differentiation observed among the five
Tunisian populations, which are geographically adjacent,
was very different from that reported by Phan et al. (2003)
in Australia where high genetic similarity was found
between A. rabiei Australian populations separated by
large geographical distances. This lack of diversity was
attributed to a founder effect whereby the pathogen was
recently introduced into widely geographically separated
chickpea growing areas in Australia (Taylor & Ford,
2006).
Acknowledgements
This work was funded in part by the European Union
project Ascorab, INCO-DEV (Contract Nº. ICA4-CT
2000-30003). We thank Dr Richard N. Strange for his
support for this project.
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