Genetic differentiation in Pyrenophora teres f. teres populations from Syria and Tunisia as assessed by AFLP markers

Abstract

Unlabelled:
To investigate the level of genetic differentiation and diversity among Pyrenophora teres isolate populations originating from different agro-ecological areas of Syria and Tunisia and to determine the potential of AFLP profiling in genotyping Pyrenophora teres f. teres. In this study, AFLP markers have been employed to identify patterns of population structure in 20 Pyrenophora teres f. teres populations from Syria and Tunisia. Ninety-four isolates were studied by the use of a protocol that involved stringent PCR amplification of fragments derived from digestion of genomic DNA with restriction enzymes EcoRI and MesI. Based on 401 amplified polymorphic DNA markers (AFLP), variance analyses indicated that most of the variation was partitioned within rather than between populations. Genotypic diversity (GD) was high for populations from Rihane, local landraces and different agro-ecological zones (GD = 0·75-0·86). There was high genetic differentiation among pathogen populations from different host populations in Syria (Gst = 0·31, ht = 0·190) and Tunisia (Gst = 0·39, ht = 0·263), which may be partly explained by the low gene flow around the areas sampled. A phenetic tree revealed three groups with high bootstrap values (55, 68, 76) and reflected the grouping of isolates based on host, or agro-ecological areas. AFLP profiling is an effective method for typing the genetically diverse pathogen Pyrenophora teres f. teres.

Significance and impact of the study:
The study represents a comparative analysis of the genetic diversity in P. teres isolates from two countries spanning two continents and also shows that several distinct P. teres genotypes may be found in a given environment. The implications of these findings for Pyrenophora teres f. teres evolutionary potential and net blotch-resistance breeding in Syria and Tunisia were also discussed.

Full text

ORIGINAL ARTICLE
Genetic differentiation in Pyrenophora teres f. teres
populations from Syria and Tunisia as assessed by AFLP
markers
A. Bouajila
1
, N. Zoghlami
1
, S. Murad
2
, M. Baum
2
, A. Ghorbel
1
and K. Nazari
2
1 Centre de Biotechnologie de Borj-C
edria, Hammam-Lif, Tunisia
2 International Center for Agricultural Research in the Dry Areas (ICARDA), Aleppo, Syria
Significance and Impact of the Study: The study represents a comparative analysis of the genetic diver-
sity in P. teres isolates from two countries spanning two continents and also shows that several distinct
P. teres genotypes may be found in a given environment. The implications of these findings for Pyreno-
phora teres f. teres evolutionary potential and net blotch-resistance breeding in Syria and Tunisia were
also discussed.
Keywords
AFLP, Barley, genetic diversity, net blotch,
Pyrenophora teres f. teres, Syria, Tunisia.
Correspondence
Aida Bouajila, CBBC- Biotechnology Center,
Centre de Biotechnologie de Borj-C
edria, BP
901, Hammam-Lif 2050, Tunisia.
E-mail: y.aida@yahoo.fr
2012/0686: received 16 April 2012, revised
10 October 2012 and accepted 14 October
2012
doi:10.1111/lam.12029
Abstract
To investigate the level of genetic differentiation and diversity among
Pyrenophora teres isolate populations originating from different agro-ecological
areas of Syria and Tunisia and to determine the potential of AFLP profiling in
genotyping Pyrenophora teres f. teres. In this study, AFLP markers have been
employed to identify patterns of population structure in 20 Pyrenophora teres f.
teres populations from Syria and Tunisia. Ninety-four isolates were studied by
the use of a protocol that involved stringent PCR amplification of fragments
derived from digestion of genomic DNA with restriction enzymes EcoRI and
MesI. Based on 401 amplified polymorphic DNA markers (AFLP), variance
analyses indicated that most of the variation was partitioned within rather than
between populations. Genotypic diversity (GD) was high for populations from
Rihane, local landraces and different agro-ecological zones (GD =075–086).
There was high genetic differentiation among pathogen populations from
different host populations in Syria (G
st
=031, ht =0190) and Tunisia
(G
st
=039, ht =0263), which may be partly explained by the low gene flow
around the areas sampled. A phenetic tree revealed three groups with high
bootstrap values (55, 68, 76) and reflected the grouping of isolates based on
host, or agro-ecological areas. AFLP profiling is an effective method for typing
the genetically diverse pathogen Pyrenophora teres f. teres.
Introduction
Pyrenophora teres Drechs. [anamorph: Drechslera teres
(Sacc.) Shoemaker], is a haploid ascomycete that causes
net blotch in barley (Smedegaard-Petersen 1971). This
persistent disease is common in all barley-growing regions
of the world and occurs typically in cool and humid areas.
However, it is a serious disease in the dry areas of North
Africa, the Middle East and Australia, and may cause up
to 40% loss in grain yield (Hovmoller et al. 2000;
Jayasena 2007; Jebbouj and El Yousfi 2010) in susceptible
barley cultivars under epidemic conditions (McLean et al.
2009). Two forms of the disease, the net form (P. teres f.
teres) and the spot form (P. teres f. maculata), were
described based on the symptoms in barley (Smedegaard-
Petersen 1971; McLean et al. 2009). The net form (P. teres
f. teres) is more common in North Africa and the Middle
East (Harrabi and Kamel 1990; Arabi et al. 2003).
Letters in Applied Microbiology 56, 389--400 ©2012 The Society for Applied Microbiology 389
Letters in Applied Microbiology ISSN 0266-8254

Croissant fertile and North Africa are primary centres
of barley diversity; however, a few improved varieties are
currently replacing a wide range of genetically heteroge-
neous barley landraces across the region. Some of these
varieties, for example Rihane, are susceptible to net
blotch, and high infection levels have been observed
across the region (Yahyaoui 2004). Reduction in yield
due to barley net blotch can be as high as 40%, and the
disease is currently one of the major constraints to barley
production in Syria and Tunisia (Yahyaoui 2004).
This can be attributed to the increasingly intensive pro-
duction, large monocultures of a few varieties and the
environmental conditions that are conducive for disease
development (Yahyaoui 2004). Resistant barley cultivars
could potentially form the basis of sustainable manage-
ment strategies for net blotch; however, knowledge of
P. teres population genetics is needed to understand dis-
ease epidemiology, and to effectively breed and use resis-
tant cultivars (McDonald and Linde 2002; McLean et al.
2009).
Pyrenophora teres is known for its high level of patho-
genic variation in several countries (Afanasenko and Lev-
itin 1979; Tekauz 1990; Steffenson and Webster 1992;
Gupta and Loughman 2001; Cromey and Parkes 2003;
Wu et al. 2003; Serenius 2006; Grewal et al. 2008; Silvar
et al. 2009), including Syria and Tunisia (Harrabi and Ka-
mel 1990; Arabi et al. 2003). Studies of P. teres popula-
tions using colony colour, isozymes, restriction fragment
length polymorphism (RFLP), amplified fragment length
polymorphism (AFLP) and simple sequence repeats (SSR)
revealed high genetic diversity within field populations of
the pathogen (Rau et al. 2003, 2005; Wu et al. 2003; Sere-
nius 2006; Keiper et al. 2007).
Information on the dispersal (gene flow) and mode of
reproduction of P. teres could influence current manage-
ment strategies for barley net blotch in Syria and Tunisia.
AFLP markers are well suited for studies that focus on
the role of selectively neutral evolutionary processes such
as mating system, genetic drift and gene flow (McDonald
and Linde 2002). A more complete understanding of the
genetic structure of P. teres f. teres populations in Syria
and Tunisia necessitates hierarchical sampling of a rela-
tively large number of isolates on different geographical
and spatial scales (Wu et al. 2003).
Genetic differentiation of geographically separated
pathogen populations has important implications for the
identification and deployment of disease resistance genes.
Barley is cultivated in Syria and Tunisia in widely varying
agro-ecological zones ranging from subhumid to semi-
arid, and one hypothesis is that P. teres f. teres popula-
tions in these areas are genetically differentiated. The
objectives of this study were, to (i) characterize the
amount and distribution of genetic variation within and
among populations of P. teres f. teres sampled in different
barley-growing areas of Syria and Tunisia and (ii) use this
information to infer the role of different evolutionary
forces on the pathogen population in the two countries.
Results
AFLP analysis
Combined analysis of AFLP data. A total of 401 discern-
ible and polymorphic AFLP bands were generated with
six primer combinations selected across the 94 isolates of
20 Syrian and Tunisian populations of Pyrenophora teres
f. teres (Table 2). Primers varied in their ability to detect
variation at both within and between populations. The
within-populations H
o
varied from 0127 for E11XM50
primer to 0195 for E11XM47 primer (Table 2).
On average over all primers, the Pyrenophora teres pop-
ulation from Attayet (Siliana, Tunisia) was the most
diverse based on several indices (Table 4). While the level
of within-population genetic diversity was lower among
the samples of population 5 (mean H
o
=0104). Even the
genetic diversity between Syrian populations ranged from
0128 to 0220 (Tables 1 and 4).
Genotypic diversity ranged from 075 (population 3,
population 7, population 8, population 14, population
15) to a maximum of 086 that was recorded at seven of
the twenty sites surveyed, indicating that at these sites,
every strain represented a distinct genotype.
The variance components of within and between popu-
lations detected with AMOVA were 7276 and 2724% of
the total variance, respectively, which were both signifi-
cant at P<0001 (Table 3). This was in approximate
agreement with results derived from H
o
index, in which
within- and between-population variations were 5661
and 4339%, respectively. It seems clear that while most
of the variation is partitioned within populations, there is
still considerable variation between populations.
Across all 20 populations, the number of polymorphic loci
at each population ranged from 63 (population 5) to 239
(population 12) and with a percentage of polymorphic loci
1571–5960%, respectively (Table 4). Average gene diversity
across Syrian and Tunisian populations ranged from 0104
(population 5) to 0261 (population 8) (Table 4).
Touiref (population 5) samples were the least variable
based on differences between isolates and Shannon’s
information index (Tables 1 and 4).
A matrix of pairwise F
st
values is presented in Table 5.
Values of F
st
ranged from 00053 (between populations
16 and 17) to 0637 (between populations 5 and 15).
Genetic differentiation was not significant only between
Tunisian populations: Barrage Meleg, Touiref and Ham-
rounia samples (0021, 00031, 00053, respectively)
390 Letters in Applied Microbiology 56, 389--400 ©2012 The Society for Applied Microbiology
Genetic diversity of Pyrenophora teres f. teres A. Bouajila et al.

Table 1 List of Pyrenophora teres f. teres ‘isolates’ used on this study collected from Syria and Tunisia
Code Reference/site
Populations code/collection site(district)/Geographic
position/Rainfall Host/row type/year collection
1 T1B1/TUN1 Popl/Testour 1 (Beja) HR, NW Rihane/6R/2009
2 T1D1/TUN2 Popl/Testour 1 (Beja) HR, NW Rihane/6R/2009
3 T1F1/TUN3 Popl/Testour 1 (Beja) HR, NW Rihane/6R/2009
4 T1C1/TUN71 Popl/Testour 1 (Beja) HR, NW Rihane/6R/2009
5 T1C2/TUN72 Popl/Testour 1 (Beja) HR, NW Rihane/6R/2009
6 T3C1/TUN4 Pop2/Teboursek 1 (Beja) HR, NW Rihane/6R/2009
7 T3F1/TUN5 Pop2/Teboursek 1 (Beja) HR, NW Rihane/6R/2009
8 T3H1/TUN6 Pop2/Teboursek 1 (Beja) HR, NW Rihane/6R/2009
9 T6A1/TUN7 Pop3/Bahra (Kef) MR, NW Local barley landrace/6R/2009
10 T6E1/TUN8 Pop3/Bahra (Kef) MR, NW Local barley landrace/6R/2009
11 T6G1/TUN9 Pop3/Bahra (Kef) MR, NW Local barley landrace/6R/2009
12 T6H1/TUN10 Pop3/Bahra (Kef) MR, NW Local barley landrace/6R/2009
13 T9A1/TUN11 Pop4/Barrage Maleg (Kef) MR, NW Local barley landrace/6R/2009
14 T9C1/TUN12 Pop4/Barrage Maleg (Kef) MR, NW Local barley landrace/6R/2009
15 T9D1/TUN13 Pop4/Barrage Maleg (Kef) MR, NW Local barley landrace/6R/2009
16 T9E1/TUN14 Pop4/Barrage Maleg (Kef) MR, NW Local barley landrace/6R/2009
17 T9H1/TUN15 Pop4/Barrage Maleg (Kef) MR, NW Local barley landrace/6R/2009
18 T14B1/TUN16 Pop5/Touiref (Kef) MR, NW Local barley landrace/6R/2009
19 T14B2/TUN17 Pop5/Touiref (Kef) MR, NW Local barley landrace/6R/2009
20 T14G1/TUN18 Pop5/Touiref (Kef) MR, NW Local barley landrace/6R/2009
21 T15F1/TUN19 Pop6/Gboulat (Siliana) MR, NW Local barley landrace/6R/2009
22 T15G1/TUN20 Pop6/Gboulat (Siliana) MR, NW Local barley landrace/6R/2009
23 T15G2/TUN21 Pop6/Gboulat (Siliana) MR, NW Local barley landrace/6R/2009
24 T15B1/TUN59 Pop6/Gboulat (Siliana) MR, NW Local barley landrace/6R/2009
25 T15D1/TUN60 Pop6/Gboulat (Siliana) MR, NW Local barley landrace/6R/2009
26 T15C1/TUN61 Pop6/Gboulat (Siliana) MR, NW Local barley landrace/6R/2009
27 T16A1/TUN22 Pop7/Mosrata (Siliana) MR, NW Rihane/6R/2009
28 T16B1/TUN23 Pop7/Mosrata (Siliana) MR, NW Rihane/6R/2009
29 T16E1/TUN24 Pop7/Mosrata (Siliana) MR, NW Rihane/6R/2009
30 T16H1/TUN25 Pop7/Mosrata (Siliana) MR, NW Rihane/6R/2009
31 T17C1/TUN26 Pop8/Attayet (Siliana) MR, NW Rihane/6R/2009
32 T17E1/TUN27 Pop8/Attayet (Siliana) MR, NW Rihane/6R/2009
33 T17F3/TUN28 Pop8/Attayet (Siliana) MR, NW Rihane/6R/2009
34 T17H1/TUN29 Pop8/Attayet (Siliana) MR, NW Rihane/6R/2009
35 T19A1/TUN30 Pop9/Sers (Kef) MR, NW Local barley landrace/6R/2009
36 T19B1/TUN31 Pop9/Sers (Kef) MR, NW Local barley landrace/6R/2009
37 T19E1/TUN32 Pop9/Sers (Kef) MR, NW Local barley landrace/6R/2009
38 T25A1/TUN33 PoplO/Sidi Mtir, Bouficha (Sousse) LR, C Local barley landrace/6R/2009
39 T25B2/TUN34 PoplO/Sidi Mtir, Bouficha (Sousse) LR, C Local barley landrace/6R/2009
40 T25C3/TUN62 PoplO/Sidi Mtir, Bouficha (Sousse) LR, C Local barley landrace/6R/2009
41 T28G1/TUN35 Popl 1/Hincha (Sfax) LR, S Local barley landrace/6R/2009
42 T28H1/TUN36 Popl 1/Hincha (Sfax) LR, S Local barley landrace/6R/2009
43 T28A1/TUN73 Popl 1/Hincha (Sfax) LR, S Local barley landrace/6R/2009
44 T28D1/TUN74 Popl 1/Hincha (Sfax) LR, S Local barley landrace/6R/2009
45 T28D2/TUN75 Popl 1/Hincha (Sfax) LR, S Local barley landrace/6R/2009
46 T28F1/TUN76 Popl 1/Hincha (Sfax) LR, S Local barley landrace/6R/2009
47 T51E2/TUN37 Popl2/Bir Mcharga (Zaghouan) MR,NE Rihane/6R/2009
48 T51C2/TUN63 Popl2/Bir Mcharga (Zaghouan) MR, NE Rihane/6R/2009
49 T51A2/TUN65 Popl2/Bir Mcharga (Zaghouan) MR, NE Rihane/6R/2009
50 T51F2/TUN66 Popl2/Bir Mcharga (Zaghouan) MR, NE Rihane/6R/2009
51 T51C1/TUN67 Popl2/Bir Mcharga (Zaghouan) MR, NE Rihane/6R/2009
52 T51D2//TUN68 Popl2/Bir Mcharga (Zaghouan) MR, NE Rihane/6R/2009
53 T51H1/TUN69 Popl2/Bir Mcharga (Zaghouan) MR, NE Rihane/6R/2009
54 T51H2/TUN70 Popl2/Bir Mcharga (Zaghouan) MR, NE Rihane/6R/2009
Letters in Applied Microbiology 56, 389--400 ©2012 The Society for Applied Microbiology 391
A. Bouajila et al. Genetic diversity of Pyrenophora teres f. teres

(Table 5). The rest of values were all significant at
P<0001. This indicates that all populations may be con-
sidered different from each other, with population 5
being the most different from the others and populations
1, 4, 9 and 16 being the most similar. The overall F
st
across all the populations was 027.
The significant differentiation between populations was
also revealed in the clustering analysis (Fig. 1) and
reflected in the estimates of gene flow (N
m
) (Table 2).
Values of N
m
ranged from a moderate value of 084 to
a high value of 118, averaging 0653, which indicated
that Pyrenophora teres populations tend to differentiate
between the twenty studied populations.
The total variation among Pyrenophora teres was fur-
ther tested based on geographic countries (Syria, Tunisia)
(Table 2). Most of the total variation (6855%) was iden-
tified within Syrian populations, 40% was identified
among Tunisian populations. Although, genetic differen-
tiation was significant between countries (F
st
ranging
from 0126 to 0572), results show that the isolates of
P. teres are genetically more distinct across a wide
geographical area. Moderate gene flow was found in
Table 1 (continued)
Code Reference/site
Populations code/collection site(district)/Geographic
position/Rainfall Host/row type/year collection
55 T52A1/TUN38 Popl3/El fahs (Zagouhan) MR, NE Local barley landrace/6R/2009
56 T52B1/TUN39 Popl3/El fahs (Zagouhan) MR, NE Local barley landrace/6R/2009
57 T52C1/TUN40 Popl3/El fahs (Zagouhan) MR, NE Local barley landrace/6R/2009
58 T52D1/TUN41 Popl3/El fahs (Zagouhan) MR, NE Local barley landrace/6R/2009
59 T52D2/TUN42 Popl3/El fahs (Zagouhan) MR, NE Local barley landrace/6R/2009
60 T52E1/TUN43 Popl3/El fahs (Zagouhan) MR, NE Local barley landrace/6R/2009
61 T52H2/TUN44 Popl3/El fahs (Zagouhan) MR, NE Local barley landrace/6R/2009
62 T53B2/TUN45 Popl4/Saoif (Zagouhan) MR, NE Rihane/6R/2009
63 T53D1/TUN46 Pop14/Saoif (Zagouhan) MR, NE Rihane/6R/2009
64 T53F2/TUN47 Pop14/Saoif (Zagouhan) MR, NE Rihane/6R/2009
65 T53G3/TUN48 Pop14/Saoif (Zagouhan) MR, NE Rihane/6R/2009
66 T55A3/TUN49 Pop15/Mograne (Zagouhan) MR, NE Rihane/6R/2009
67 T55C2/TUN50 Pop15/Mograne (Zagouhan) MR, NE Rihane/6R/2009
68 T55D1/TUN51 Pop15/Mograne (Zagouhan) MR, NE Rihane/6R/2009
69 T55G1/TUN52 Pop15/Mograne (Zagouhan) MR, NE Rihane/6R/2009
70 T57B1/TUN53 Pop16/Souidia (Bizerte) HR, NN Rihane/6R/2009
71 T57B2/TUN54 Pop16/Souidia (Bizerte) HR, NN Rihane/6R/2009
72 T57C1/TUN55 Pop16/Souidia (Bizerte) HR, NN Rihane/6R/2009
73 T57A1/TUN77 Pop16/Souidia (Bizerte) HR, NN Rihane/6R/2009
74 T57H1/TUN78 Pop16/Souidia (Bizerte) HR, NN Rihane/6R/2009
75 T59B1/TUN56 Pop17/Hamrounia (Bizerte) HR,NN Rihane/6R/2009
76 T59H1/TUN57 Pop17/Hamrounia (Bizerte) HR,NN Rihane/6R/2009
77 T59E1/TUN64 Pop17/Hamrounia (Bizerte) HR,NN Rihane/6R/2009
78 T59G1/TUN79 Pop17/Hamrounia (Bizerte) HR, NN Rihane/6R/2009
79 S1/ICAPtr1 Pop18/Al Bab (ALEPPO) MR, N Local barley landrace/2R/1998
80 S2/ICAPtr2 Pop18/Al Bab (ALEPPO) MR, N Local barley landrace/2R/1998
81 S7/ICAPtr5 Pop18/Al Bab (ALEPPO) MR, N Local barley landrace/2R/1998
82 S3/ICAPtr3 Pop19/Mossaf (HAMA) MR, W Local barley landrace/2R/2003
83 S8/ICAPtr6 Pop19/Souran (HAMA) MR, W Local barley landrace/2R/2006
84 S10/ICAPtr7 Pop19/Al Gab (HAMA) MR, W Local barley landrace/2R/2009
85 S11/ICAPtr8 Pop19/Al Gab (HAMA) MR, W Local barley landrace/2R/2009
86 S12/ICAPtr9 Pop19/Al Gab (HAMA) MR, W Local barley landrace/2R/2009
87 S13/ICAPtr10 Pop19/Al Gab (HAMA) MR, W Local barley landrace/2R/2009
88 S14/ICAPtr11 Pop19/Al Gab (HAMA) MR, W Local barley landrace/2R/2009
89 S16/ICAPtr12 Pop20/ICR-Station (TARTOUS) HR, W Local barley landrace/?/2007
90 S17/ICAPtr13 Pop20/ICR-Station (TARTOUS) HR, W Local barley landrace/?/2007
91 S18/ICAPtr14 Pop20/ICR-Station (TARTOUS) HR, W Local barley landrace/?/2007
92 S19/ICAPtr15 Pop20/ICR-Station (TARTOUS) HR, W Local barley landrace/?/2007
93 S21/ICAPtr16 Pop20/ICR-Station (TARTOUS) HR, W Local barley landrace/?/2007
94 S23/ICAPtr17 Pop20/ICR-Station (TARTOUS) HR, W Local barley landrace/?/2007
392 Letters in Applied Microbiology 56, 389--400 ©2012 The Society for Applied Microbiology
Genetic diversity of Pyrenophora teres f. teres A. Bouajila et al.

Tunisian populations N
m
<0756, while N
m
=1 in Syrian
populations.
Cluster polymorphism. The genetic distance among field
populations was estimated using Nei’s unbiased measure
of genetic distance (Nei 1978).
Cluster analysis based on UPGMA allowed a graphical
representation of genetic similarity among 94 isolates
from different sampling sites of Syria and Tunisia. Pyren-
ophora teres populations were grouped onto three main
clusters that were genetically very distant from each other
with bootstrap 55, 68, 76 (Fig. 1). Bootstrap values were
generally high, in 47 cases were the values >50 (Fig. 1).
There were two main clusters at the linkage distance level
of 037 that were well supported by bootstrap values of
100%. The first cluster contained two isolates ICAPtr 16
and ICAPtr 17 from Syrian populations Hama and Tar-
tous with bootstrap 76. The second cluster comprised 13
isolates from Aleppo, Hama and Tartous in Syria with
only three isolates from two areas of Tunisia namely
TUNPtr 59, 60, 76 (Gboulat, Siliana, NW), (Hincha, Sfax,
SE) (Table 1). The third cluster comprised most of the
Tunisian isolates (76 isolates) with only two isolates from
Syria (Hama) ICAPtr 12 and 13 (Fig. 1, Table 1).
Conversely, the obtained dendrogram revealed no
apparent association between geographical distance or
Table 2 Genetic diversity identified by six AFLP primers combinations
in 94 isolates from Syria and Tunisia
AFLP primer combinations H
t
H
s
G
st
N
m
E11XM47 0295 0194 0404 0985
E11XM50 0218 0127 0340 1180
E17XM47 0320 0172 0441 0866
E17XM50 0262 0147 0399 0845
E15XM47 0296 0169 0371 1085
E15 X M50 0266 0157 0382 1052
TUN pop (17pop, 78 isolates) 0263 0158 0398 0756
Syrian pop(3pop, 16 isolates) 0190 0130 0314 1092
All populations (20pop, 94 isolates 0272 0154 0433 0653
H
t
, Gene diversity totalled among populations; H
s
, Gene diversity
within populations; G
st
, Genetic differentiation between populations;
N
m
, Number of migrants.
Table 3 AMOVA analysis for the Pyrenophora teres f. teres populations
using 401 AFLP bands
Source of variation df
Sum of
squares
Variance
components
Variation
(%)
Among populations 19 2134373 15290*** 2724
Within populations 74 3022808 40848*** 7276
Total 93 5157181 56139
***P<0001.
Table 4 Molecular diversity estimates and its significance for Pyrenophora teres f. teres populations based on all isolates sampled from Syria and
Tunisia
TUN/Syr pop
Average of gene
diversity overall loci
Average of pairwise
differences F
ST
indices
Number of
polymorphic loci
% of polymorphic
loci Shannon’s index
TUN pop 1 0196 0119 78600 41064 0275 160 3990231
TUN pop 2 0221 0165 88666 53345 0284 133 3317 0211
TUN pop 3 0225 0148 90333 49725 0264 161 4014 0245
TUN pop 4 0198 0120 79400 41478 0274 171 4264 0237
TUN pop 5 0104 0079 42000 25455 036 63 1571 0100
TUN pop 6 0234 0136 94000 47348 0238 206 5137 0289
TUN pop 7 0258 0170 103833157103 0239 189 4713 0283
TUN pop 8 0261 0171 104833 57650 0237 195 4862 0287
TUN pop 9 02391 0179 96000 57728 0273 144 3591 0228
TUN pop 10 022210167 89333 53744 0283 134 3341 0212
TUN pop 11 0217 0126 87333 44015 0251 199 4962 0272
TUN pop 12 0217 0119 87321 42162 0243 239 5960 0294
TUN pop 13 02421 0136 97238 47774 0226 233 5810 0312
TUN pop 14 0143 0094 57666 31871 0323 109 2718 0159
TUN pop 15 0139 0092 56000 30960 0326 101 2518 0152
TUN pop 16 0199 0121 79800 41685 0273 168 4189 0236
TUN pop 17 0194 0127 77833 42893 0286 144 3591 0213
Syr pop 18 0128 0096 51333 31034 0345 77 1920 0122
Syr pop 19 0143 0081 57428 28356 0308 142 3541 0186
Syr pop20 0220 0128 88466 44581 0249 197 4912 0273
All populations 0227 0199 70347 39857 0286 158 3946 0227
F
st
, genetic differentiation between P. teres f. teres populations Shannon’s index, measures populations’ diversity in a community.
Letters in Applied Microbiology 56, 389--400 ©2012 The Society for Applied Microbiology 393
A. Bouajila et al. Genetic diversity of Pyrenophora teres f. teres

Table 5 Genetic differentiation between Pyrenophora teres f. teres populations from Syria and Tunisia
TUN/Syr
pop
TUN
popl
TUN
pop2
TUN
pop3
TUN
pop4
TUN
pop5
TUN
pop6
TUN
pop7
TUN
pop8
TUN
pop9
TUN
pop10
TUN
pop11
TUN
pop12
TUN
pop13
TUN
pop14
TUN
pop15
TUN
pop16
TUN
pop17
Syr
pop18
Syr
pop19
TUN pop2 0152
TUN pop3 0316 0260
TUN pop4 0380 0333 (0003
TUN pop5 0539 0511 0115 (0003
TUN pop6 0150 0158 0145 0194 0325
TUN pop7 0155 0077 0074 0153 0286 0021
TUN pop8 0084 0073 0239 0314 0447 0102 0062
TUN pop9 0146 0136 0188 0249 0420 0095 0052 0003
TUN popl0 0206 0202 0084 0109 0302 0040 0022 0106 0004
TUN pop11 0206 0144 0278 0330 0468 0170 0129 0105 0201 0175
TUN pop12 0078 0201 0320 0384 0501 0164 0188 0116 0177 0217 0177
TUN pop13 0152 0124 0280 0340 0461 0166 0160 0087 0114 0179 0145 0156
TUN pop14 0158 0225 0374 0443 0629 0195 0209 0155 0153 0274 0213 0175 0005
TUN pop15 0213 0304 0392 0362 0637 0200 0249 0162 0227 0310 0252 0155 0190 0244
TUN pop16 0109 0198 0325 0396 0538 0156 0171 0119 0150 0221 0197 0046 0156 0179 0019
TUN pop17 0121 0220 0394 0423 0575 0175 0191 0115 0198 0249 0212 0044 0187 0215 0178 0005
TUN pop18 0484 0458 0351 0416 0590 0335 0324 0353 0436 0413 0397 0436 0412 0564 0552 0466 0496
TUN pop19 0510 0503 0383 0411 0512 0365 0355 0462 0470 0416 0451 0484 0477 0569 0572 0519 0534 0263
TUN pop20 0262 0212 0203 0269 0380 0126 0090 0192 0198 0160 0251 0251 0222 0298 0288 0255 0278 0241 0211
Significant pairwise (P<005), Abbreviations as in Table 1.
394 Letters in Applied Microbiology 56, 389--400 ©2012 The Society for Applied Microbiology
Genetic diversity of Pyrenophora teres f. teres A. Bouajila et al.

regional affiliation and the genetic distance between
the populations. Indeed, P. teres f. teres isolates obtained
from different sampling sites in the same area or country
did not cluster together (Fig. 2). The mean genetic dis-
tance of each of the 20 populations from all others ranged
from 0027 to 0325. The least genetic distance (0027)
was recorded between populations Bahra (Kef, NW Tuni-
sia) and Barrage Meleg (Kef, NW Tunisia), while popula-
tions Touiref (Kef, NW Tunisia) and Hamrounia (Bizerte,
NN Tunisia) were the most genetically distant (0325).
The 20 P. teres populations were grouped into two main
clusters that were genetically very distant from each other.
The cluster I was composed only by the Tunisian popula-
tions from 14 locations corresponding to different agro-
ecological zones (B
eja, Siliana, Kef, Zaghouan, Bizerte,
Sousse, Sfax). The cluster II contained, however, apart
from region Kef (Northwest Tunisia) that was represented
by a three field populations (Bahra, Barrage Meleg and
Touiref) and all Syrian populations (Fig. 2). None of the
individualized subclusters comprised field populations
from a single area, indicating considerable gene flow
between regional populations (e.g. populations T8, T11,
Cluster I
Cluster II
Cluster III
Cluster I
Cluster II
Cluster III
Figure 1 UPGMA phenogram of Pyrenophora teres f. teres based on the AFLP data. Numbers on branches are bootstrap values. The isolates are
designated by alphanumerics represent the origin (ICAPtr blue color represent isolates collected from Syria; TUNPtr: represent isolates sampled
from Tunisia), followed by the host (the red color, for cv. Rihane and black one for a landrace cultivar).
Figure 2 UPGMA dendrogram of twenty Pyrenophora teres f. teres populations from Syria and Tunisia based on the AFLP data. The populations
are designated by numerics (see Table 1). From P1 to P20: Tunisian and Syrian net blotch populations were represented on black and red, respec-
tively. Cluster I Tunisian populations 1(P1), 2(P2), 6(P6), 7(P7), 8(P8), 9(P9), 10(P10), 11(P11), 12(P12), 13(P13), 14(P14), 15(P15), 16(P16), and
Cluster II Syrian and Tunisian populations: 17(P17), 18(P18), 19(P19), 20(P20), 3(P3), 4(P4), 5(P5).
Letters in Applied Microbiology 56, 389--400 ©2012 The Society for Applied Microbiology 395
A. Bouajila et al. Genetic diversity of Pyrenophora teres f. teres

T13 and T14; T6, T7, T9 and T10; T15 and T1) (Fig. 2,
Table 1).
Discussion
Croissant fertile and North Africa are primary centres of
barley diversity, and many barley growers in Syria and
Tunisia still rely on genetically heterogeneous landraces,
some of which are derived from the seeds that were trans-
ferred from generation to generation (Ceccarelli et al.
1987; Zoghlami et al. 2011). If pathogenicity on barley
was acquired by a large number of genetically distinct
strains, then P. teres populations in Syria and Tunisia
have coevolved with many barley genotypes over a long
period of time, resulting in a diverse pathogen popula-
tion. It is, therefore, not surprising that all populations
exhibited a high degree of genotype diversity (08) within
a spatial scale of 1 m
2
.
In this study, the marker technology has been
employed to detect genetic variation and population
structure of Pyrenophora teres f. teres from Syria and
Tunisia and has once again demonstrated its usefulness in
gaining information quickly and usefully in breeding pro-
grammes.
AFLP markers, along with appropriate statistical proce-
dures are suitable for genetic variation analyses at both
intra- and interpopulation levels (Serenius et al. 2007;
Bentata et al. 2011).
The level of genetic diversity at AFLP markers detected
here (Hsp =0276) is comparable to or higher than,
diversity levels reported for pathogen when using bio-
chemical and molecular markers (Jonsson et al. 2000;
Zaki and Al-Masry 2008).
The genetic variation was maintained within rather
than between the studied populations (5833%) as
detected with AMOVA. Similarly, Serenius et al. (2007)
found that in Russian P. teres f. teres 20 and 80% of the
total variation was partitioned among and within popula-
tions, respectively. Leisova et al. (2005a,b) showed that
981% of genetic variance occurred within local popula-
tions and 19% was found among populations. However,
Bentata et al. (2011) revealed a high genetic variability
between the studied isolates in Morocco. The Syrian and
Tunisian isolates were highly variable and contributed
2724% of the total variation observed among all isolates
using AMOVA analysis. AMOVA analysis revealed significant
differences among populations and among samples within
population (P<0001) (Table 3).
Conversely, high genetic variability at population level
was detected. Indeed, a high number of polymorphic
markers was produced by the Tunisian population no. 12
(239 markers) and the Syrian population no. 20 (197
markers), respectively, with a percentage of polymorphic
loci 52 and 49% (Table 4). Also, 87 different haplotypes
were identified among the 94 isolates studied. In others
words, 87 isolates have specific genotypes, suggesting that
there is more genetic recombination, which may have
played a major role in genetic diversity of Syrian and
Tunisian Pyrenophora teres f. teres. In addition, the high
diversity might be either a result of a high mutation rate,
large population size or retrotransposons, which can all
contribute to diversity in asexually reproducing popula-
tions (McDonald and Linde 2002; Taylor et al. 2004).
These findings also indicated significant genetic subdi-
vision of the Syrian and Tunisian P. teres populations
according to F
st
values (F
st
=027, P<0001). The F
st
estimate is considered to be more biased than Φ
ST
for the
evaluation of differentiation coefficient for dominant
marker data and may suggest that the P. teres populations
analysed are moderately differentiated according to Wright’s
interpretation of F
st
values (Wright 1978).
As Syria is the primary centre of origin of Hordeum
species, it can therefore shelter old pathogen populations,
where mutation events occurring over a long period of
time have increased pathogen population diversity. This
was supported by the F
st
value (Table 4) that identified
Syria to have most of the variation identified elsewhere.
High diversity has also been observed in Fusarium grami-
nearum Schwabe [teleomorph (Gibberella zeae)(Schw-
ein.)] in West Asia and Southern Russia, which was
suggested to be the origin of F. graminearum, whereas the
Finnish F. graminearum isolates were significantly less
variable (Gagkaeva and Yli-Mattila 2004).
In the present study, genetic differentiation among the
20 field populations (sample size of 3–8 isolates) was high
(G
st
=0398) but dropped to 031 when Syrian field pop-
ulations were grouped together, and increase to 040 in
Tunisian field populations (Table 2). In fact, cereal patho-
gen populations are relatively old in Syria (Burdon and
Silk 1997; Khan and Tekauz 1982), and were likely estab-
lished by relatively few isolates. Migration via seed to
intra- and interareas in Syria, and therefore the diversity,
has remained comparatively high.
A moderate level of genetic differentiation was found
between the pathogen population from Tunisia and Syria
based on Nei’s genetic distances, high G
st
values with
N
m
=0653. Although, evidence for differentiation was
found in pairwise comparisons involving populations
from all other areas (F
st
=011–063), suggesting that the
‘geographic populations’ in this study are evolving inde-
pendently and hence may be considered not a part of the
same ‘genetic population’. The moderate differentiation
observed may have resulted from the rather small number
of isolates sampled in populations (8, 20) although boot-
strap tests of significance enabled us to estimate indices
of population differentiation with a reasonable degree of
396 Letters in Applied Microbiology 56, 389--400 ©2012 The Society for Applied Microbiology
Genetic diversity of Pyrenophora teres f. teres A. Bouajila et al.

confidence (Gr€
unwald et al. 2003). This differentiation
may indicate local adaptation of P. teres to the high rain-
fall conditions of different areas in Syria and Tunisia
compared with the moderate or low rainfall conditions in
the more arid regions. Assuming that our AFLP data
accurately reflect the differentiation between these popula-
tions in Syria and Tunisia, they indicate that the identifi-
cation and deployment of net blotch-resistant varieties
would need to take into consideration these two different
regional populations. However, detailed analysis of gene
flow between areas using larger sample sizes and codomi-
nant markers is warranted to corroborate the moderate
population differentiation observed in this study. Knowl-
edge of pathotype distribution will also help determine
whether P. teres pathotypes in the country are geographi-
cally circumscribed (Bouajila et al. 2011).
The most probable explanation for the high genotype
diversity, moderate gene flow and high genetic differentia-
tion of the pathogen population in Syria and Tunisia is
sexual reproduction and air dispersal of ascospores. Forc-
ibly discharged ascospores become airborne and may
serve as primary inoculum over considerable distances
(Trail et al., 2002). Wind dispersal of ascospores enables
the migration of new genotypes into barley fields and
may facilitate the rapid dissemination of virulent mutants
across entire areas. Many studies showed the identifica-
tion of the telemorph and detection of sexual recombina-
tion in natural populations of P. teres (McLean et al.
2009).
The importance of genetic diversity and the potential
consequences associated with narrowing the genetic base
of cultivated barley has long been recognized by plant
pathologists and plant breeders. The potential for severe
net blotch epidemics has increased with the production of
modern homogenous, genetically uniform barley varieties
with specific genes for resistance to barley net blotch. The
high genetic diversity, the high gene flow and the poten-
tial for sexual recombination in Syria and Tunisian popu-
lations of P. teres mean that reliance on major gene
resistance is unlikely to be an appropriate breeding strat-
egy (McDonald and Linde 2002).
In conclusion, the existence of genetic variability
observed, can be explained by inter-regional and intrare-
gional gene flow between the Syrian and Tunisia isolates.
However, the durability of specific resistance genes may
be increased by the use of multiline cultivars, by combin-
ing (‘pyramiding’) different resistance genes. Syria
includes in Middle East, which is the centre of origin and
earliest knowledge of domestication for many cereal
crops. Increased knowledge of the population biology of
P. teres is likely to lead to better management of disease
in agricultural ecosystems. Recently, P. teres f. teres iso-
lates were differentially pathogenic. CI09214 and CI05401
cultivars were released as the most effective sources of
resistance in Syria and Tunisia (Bouajila et al. 2011) and
combined (pyramided) into elite varieties and by deploy-
ing many cultivars with different resistance genes in space
or time.
Materials and methods
Collection of P. teres isolates
In this study, 94 P. teres f. teres isolates were sampled
from barley-infected leaves from 20 locations (17 popula-
tions from Tunisia and three populations from Syria)
throughout the major barley-growing areas in Syria and
Tunisia (Table 1).
For the Tunisian isolates, leaf samples were collected
from naturally infected fields during the 2009 season
using the hierarchical sampling method described by
McDonald et al. (1999): one field population was sampled
at each location, drawing a composite sample from eight
circular spots of 1 m diameter each located along two
parallel transects (with four spots per transect). The two
transects and the collection sites (spots) along the tran-
sects were separated from the adjacent members by 10 m.
This field design allowed a total sampling area of 408 m
2
(12 934 m). Ten infected leaves were sampled from dif-
ferent plants or tillers in a circular sweep of each sam-
pling spot. Most collections were made from the northern
subhumid to semi-arid region (69 isolates), which is the
largest barley-growing area in Tunisia, and the rest from
the central (three isolates) and the southern regions (six
isolates) of the country.
Sixteen Syrian net blotch infected leaf samples were
collected from three locations covering the major barley-
growing areas in the northern subhumid to the semi-arid
region in North Western (three isolates), and Western
(13 isolates) Syria (Table 1) in springs of 1998, 2003,
2006, 2007 and 2009. Fields were sampled randomly along
major roads in the principal barley productions areas in
Syria (three populations).
Leaf samples were placed in paper envelopes, air-dried
at room temperature for 48 h and stored at 6°C until
required.
Single-spore isolation and inoculum production
Leaves showing typical net blotch symptoms were cut into
discs 5–10 mm in diameter, surface-sterilized in 90% eth-
anol for 10 s and in 1% NaCl for 60 s, rinsed twice in
sterile deionized water for 1 min each time, blotted, dried
and aseptically transferred to Potato dextrose agar (PDA)
plates. The plates were incubated at 20°C for several days
under alternating cycles of 12 h of near-ultraviolet (NUV)
Letters in Applied Microbiology 56, 389--400 ©2012 The Society for Applied Microbiology 397
A. Bouajila et al. Genetic diversity of Pyrenophora teres f. teres

light and 12 h of darkness. After 3–5 days, single conidia
were transferred with a needle, while looking through a
microscope, to fresh PDA plates and incubated for
2 weeks to induce growth of mycelia.
DNA extraction
Approximately 005 g of the freeze-dried fungal tissue was
ground into a fine powder in a 2-ml microfuge tube
using a mixer-mill. Total DNA from each fungal isolate
was extracted using a modified hexadecyltrimethylammo-
nium bromide (CTAB) extraction procedure (Bouajila
et al. 2007). Extracted DNA was resuspended in Tris–
EDTA buffer (10 mmol l
1
) and stored at 20°C. DNA
concentrations were estimated by spectrophotometry and/
or agarose gel electrophoresis. DNAs were run in a 08%
agarose gel to verify the quality and the concentration.
AFLP analysis
The AFLP procedure was performed with minor modifi-
cations according to the protocol of Vos et al. (1995).
Approximately 40-ng DNA was digested simultaneously
with EcoRI and MseI at 37°C for 4 h. The digested sam-
ples were incubated at 70°C for 15 min to inactivate the
restriction endonucleases. EcoRI and MseI adapters were
ligated to the digested samples at 20°C for 4 h. This was
performed to generate template DNA for amplification.
Pre-amplification was carried out with +1- primers each
carrying one selective nucleotide (EcoRI +A and
MseI +C) in a thermocycler for 30 cycles (94, 56 and
72°C/30 s). The amplification products were stored at
20°C. Selective amplification was carried out with EcoRI
+1 and 2- primers and MseI +3- primers and 5 llof
the diluted PCR products from the pre-amplification. Six
primer pair combinations were employed in this study
(Table 2). The PCR amplification was performed as fol-
lows: 12 cycles at 94°C for 30 s, 65°C for 30 s and 72°C
for 60 s, with annealing temperature lowered by 07°C
every cycle. This was followed by 23 cycles at 94°C for
30 s, 56°C for 30 s and 72°C for 60 s.
Gel analysis
The reaction products were mixed with equal volumes
of formamide loading buffer (95% formamide,
10 mmol l
1
EDTA, bromophenol blue and xylene cya-
nol), denaturated by incubating at 95°C for 5 min and
quickly cooled on ice. The products were analysed on 6%
denaturing polyacrylamide gels. The gel was run at con-
stant power (50–55 W) until the dye was about 2/3 down
the length of the gel. AFLP bands were visualized by silver
staining.
Data analysis
For AFLP analysis, bands were scored as 1 denoting pres-
ence or 0 denoting absence, and a matrix of AFLP pheno-
types was then assembled across all individuals and
populations. For each primer, the total number of bands
and the polymorphic ones were calculated.
The index of phenotypic diversity (H
o
), the average
diversity over all populations (H
pop
) and the mean diver-
sity at species level (H
sp
) were estimated as described by
Yeh and Boyle (1997). The component of within-popula-
tion diversity was estimated as H
pop
/H
sp
, and that of
between-population diversity as 1 H
pop
/H
sp
. All the
above calculations were undertaken by POPGENE 132
(Yeh and Boyle 1997).
A pairwise Euclidean distance matrix was generated
with the computer package AMOVA-PREP 101 (Miller
1998) and was then used as input for WINAMOVA 155 for
AMOVA analysis (Excoffier et al. 1992) to test whether pop-
ulations had differing amounts of AFLP variation.
The gene flow (Nm, number of migrants per genera-
tion) (Whitlock and McCauley 1999) was approximated
as: N
m
=(1/4) [(1/F
st
)–1], where F
st
(inbreeding index)
values were available from a matrix of pairwise combina-
tions produced by WINAMOVA.
The Shannon information index (H), which is com-
monly used to characterize populations’ diversity in a
community and accounts for both abundance and even-
ness of the populations that are present. It was calculated
using Popgene v131 software (Yeh et al. 1999) according
to the formula:
H=∑p
i
ln p
i
where (p
i
) represents the proportion of a population irel-
ative to the total number of the populations analysed at
AFLP markers.
A dendrogram among the populations was con-
structed with software Darwin (Version 50148) (http://
darwin.cirad.fr/darwin) using the matrix of pairwise F
st
values and the unweighted pair-group method with
arithmetical averages (UPGMA) (Sneath and Sokal 1973)
algorithm.
Acknowledgements
This investigation was cosponsored by ICARDA and the
Ministry of Higher Education and Scientific Research in
Tunisia.
References
Afanasenko, O.S. and Levitin, M.M. (1979) Population
structure of causal agent of barley net blotch. Race
identification. Mycol Phytopathol 13, 230–234.
398 Letters in Applied Microbiology 56, 389--400 ©2012 The Society for Applied Microbiology
Genetic diversity of Pyrenophora teres f. teres A. Bouajila et al.

Arabi, M.I.E., Al-Safadi, B. and Charbaji, T. (2003) Pathogenic
variation among isolates of Pyrenophora teres, the causal
agent of barley net blotch. J Phytopathol 151, 376–382.
Bentata, F., Labhilili, M., El Aissami, A., Bary, S., Yeslem, C.H.
and Ibijbijen, J. (2011) Analysis of diversity genetic of
Moroccan net blotch populations using amplified fragment
length polymorphism (AFLP) markers. Afr J Biotechnol 10,
7548–7554.
Bouajila, A., Abang, M., Haouas, S., Udupa, S., Rezgui, S.,
Baum, M. and Yahyaoui, A. (2007) Genetic diversity of
Rhynchosporium secalis in Tunisia as revealed by
pathotype, AFLP, and microsatellite analyses.
Mycopathologia 163, 281–294.
Bouajila, A., Zoghlami, N., Al-Ahmed, M., Baum, M., Ghorbel,
A. and Nazari, K. (2011) Comparative virulence of
Pyrenophora teres f. teres from Syria and Tunisia and
screening for resistance sources in barley: implications for
breeding. Lett Appl Microbiol 53, 489–502.
Burdon, J.J. and Silk, J. (1997) Sources and patterns of diversity
in plant pathogenic fungi. Phytopathology 87, 664–669.
Ceccarelli, S., Grando, S. and van Leur, J.A.G. (1987) Genetic
diversity in barley landraces from Syria and Jordan.
Euphytica 36, 389–405.
Cromey, M.G. and Parkes, R.A. (2003) Pathogenic variation in
Drechslera teres in New Zealand. N Z Plant Prot 56, 251–
256.
Excoffier, L., Smouse, P.E. and Quattro, J.M. (1992) Analysis
of molecular variance inferred from metric distances
among DNA haplotypes: application to human
mitochondria DNA restriction sites. Genetics 131, 479–491.
Gagkaeva, T.Y. and Yli-Mattila, T. (2004) Genetic diversity of
Fusarium graminearum in Europe and Asia. Eur J Plant
Pathol 110, 551–562.
Grewal, T.S., Rossnagel, B.G. and Scoles, G.J. (2008) The
utility of molecular markers for net blotch resistance
across geographic regions. Crop Sci 48, 2321–2333.
Gr€
unwald, N.J., Goodwin, S.B., Milgroom, M.G. and Fry, W.E.
(2003) Analysis of genotypic diversity data for populations
of microorganisms. Phytopathology 93, 738–746.
Gupta, S. and Loughman, R. (2001) Current virulence of
Pyrenophora teres on barley in Western Australia. Plant Dis
85, 960–966.
Harrabi, M. and Kamel, A. (1990) Virulence spectrum to
barley in some isolates of Pyrenophora teres from the
Mediterranean region. Plant Dis 74, 230–232.
Hovmoller, M.S., Caffier, V., Jalli, M., Andersen, O.,
Besenhofer, G., Czembor, J.H., Dreiseitl, A., Felsenstein, F.
et al. (2000) The European barley powdery mildew
virulence survey and disease nursery 1993–1999. Agronomie
20, 729–743.
Jayasena, K.W., Van Burgel, A., Tanaka, K., Majewski, J. and
Loughman, R. (2007) Yield reduction in barley in relation
to spot-type net blotch. Australas Plant Pathol 36, 429–433.
Jebbouj, R. and El Yousfi, B. (2010) An integrated multivariate
approach to net blotch of barley: virulence quantification,
pathotyping and a breeding strategy for disease resistance.
Eur J Plant Pathol 127, 521–544.
Jonsson, R., Sail, T. and Bryngelsson, T. (2000) Genetic
diversity for random amplified polymorphic DNA (RAPD)
markers in two Swedish populations of Pyrenophora teres.
Can J Plant Pathol 22, 258–264.
Keiper, F.J., Capio, E., Grcic, M. and Wallwork, H. (2007)
Development of sequence-tagged microsatellites for the
barley net blotch pathogen, Pyrenophora teres.Mol Ecol
Notes 7, 664–666.
Khan, T.N. and Tekauz, A. (1982) Occurrence and
pathogenicity of Drechslera teres isolates causing spot-type
symptoms on barley in Western Australia. Plant Dis 66,
423–425.
Leisova, L., Minarikova, V., Kucera, L. and Ovesna, J. (2005a)
AFLP-based PCR markers that differentiate spot and Net
forms of Pyrenophora teres.Seed Pathol 54,66–73.
Leisova, L., Minarikova, V., Kucera, L. and Ovesna, J. (2005b)
Genetic Diversity of Pyrenophora teres isolates have
detected by AFLP Analysis. Phytopathol J 153, 569–578.
McDonald, B.A. and Linde, C. (2002) Pathogen population
genetics, evolutionary potential and durable resistance.
Annu Rev Phytopathol 40, 349–379.
McDonald, B.A., Zhan, J. and Burdon, J.J. (1999) Genetic
structure of Rhynchosporium secalis in Australia.
Phytopathology 89, 639–645.
McLean, M.S., Barbara, J.H. and Hollaway, G.J. (2009)
Epidemiology and control of spot form of net blotch
(Pyrenophora teres f.sp. maculata) of barley: a review. Crop
Past Sci 60, 303–315.
Miller, M.P. (1998) AMOVA-PREP 1.01: a program for the
preparation of AMOVA input files from dominant-
markers raw data. Northern Arizona University, Flagstaff,
AZ.
Nei, M (1978) Estimation of average heterozygosity and
genetic distance from a small number of samples. Genetics
89, 583–90.
Rau, D., Brown, A.H.D. and Brubaker, C. (2003) Population
genetic structure of Pyrenophora teres Drechs. The causal
agent of Net blotch in Sardinian landraces of barley
(Hordeum vulgare L.). Theor Appl Genet 106, 947–959.
Rau, D., Maier, F.J., Papa, R., Brown, A.H.D., Balmas, V.,
Saba, E., Schaefer, W. and Attene, G. (2005) Isolation and
characterization of the mating-type locus of the barley
pathogen Pyrenophora teres and frequencies of mating-type
idiomorphs within and among fungal populations
collected from barley landraces. Genome 48, 855–869.
Serenius, M. (2006) Population Structure of Pyrenophora teres,
the Causal Agent of Net Blotch of Barley, PhD Thesis.
Finland: MTT Agrifood Research Finland.
Serenius, M., Manninen, O., Wallwork, H. and Williams, K. (2007)
Genetic differentiation in Pyrenophora teres populations
measured with AFLP markers. Mycol Res 111,213–223.
Silvar, C., Casas, A.M., Kopahnke, D., Habekub, A., Schweizer,
G., Gracia, M.P., Lasa, J.M., Ciudad, F.J. et al. (2009)
Letters in Applied Microbiology 56, 389--400 ©2012 The Society for Applied Microbiology 399
A. Bouajila et al. Genetic diversity of Pyrenophora teres f. teres

Screening the Spanish Barley Core Collection for disease
resistance. Plant Breed 129,45–52.
Smedegaard-Petersen, V. (1971) Pyrenophora teres f.sp.
maculata f.sp. nov. and Pyrenophora teres f.sp. teres on
barley in Denmark. Yearbook of the Royal Veterinary
and Agricultural University. Copenhagen, Denmark:
Royal Veterinary and Agricultural University, pp. 124–
144.
Sneath, P.H.A. and Sokal, R.R. (1973) Numerical Taxonomy,
Freeman, San Francisco.
Steffenson, B.J. and Webster, R.K. (1992) Pathotype diversity
of Pyrenophora teres f. teres on barley. Phytopathology 82,
170–177.
Taylor, E.J.A., Konstantinova, P., Leigh, F., Bates, J.A. and Lee,
D. (2004) Gypsylike retrotransposons in Pyrenophora:an
abundant and informative class of molecular markers.
Genome 47, 519–525.
Tekauz, A. (1990) Characterization and distribution of
pathogenic variation in Pyrenophora teres f. teres and P.
teres f. maculata from western Canada. Can J Plant Pathol
12, 141–148.
Trail, F., Xu, H., Loranger, R. and Gadoury, D. (2002)
Physiological and environmental aspects of ascospore
discharge in Gibberella zeae (anamorph Fusarium
graminicearum). Mycologia 94, 181–189.
Vos, P., Hogers, R., Bleeker, M., Reijans, M., Van der Lee, T.,
Hornes, M., Frijters, A., Pot, J. et al. (1995) AFLP: a new
technique for DNA fingerprinting. Nucleic Acids Res 23,
4407–4414.
Whitlock, M. and McCauley, D.E. (1999) Indirect measures of
gene flow and migration: Fst6¼ 1 (4Nm +1). Heredity 82,
117–125.
Wright, S. (1978) Evolution and the Genetic of Populations
Variability Within and Among Natural Populations, Vol. 4.
Chicago: University of Chicago Press.
Wu, H.L., Steffenson, B.J., Oleson, A.E. and Zhong, S. (2003)
Genetic variation for virulence and RFLP markers in
Pyrenophora teres.Can J Plant Pathol 25,82–90.
Yahyaoui, A.H. (2004) Occurrence of barley leaf blights in
Central Western Asia and North Africa. In Meeting the
challenges of barley blights. Proc 2nd Intern Workshop on
Barley Leaf Blights 7–11 April 2002, ed. Yahyaoui, A.H.,
Brader, L., Tekauz, A., Wallwork, H. and Steffenson, B.
pp. 13–18. Aleppo, Syria: ICARDA.
Yeh, F.C. and Boyle, T.J.B. (1997) Population genetic analysis
of co-dominant and dominant markers and quantitative
traits. Belg J Bot 129, 157.
Yeh, F.C., Yang, R.C. and Boyle, T. (1999) Popgene version
1.31. Microsoft Window-based Freeware for Population
Genetic Analysis. Distributed by F. Yeh. University of
Alberta, Edmonton, Canada.
Zaki, K.I. and Al-Masry, A.I.S. (2008) Detection of biochemical
genetic markers for net blotch disease resistance and barley
grain yield. Egypt J Phytopathol 36,1–17.
Zoghlami, N., Bouagila, A., Lamine, M., Hajri, H. and
Ghorbel, A. (2011) Population genetic structure analysis in
endangered Hordeum vulgare landraces from Tunisia:
conservation strategies. Afr J Biotechnol 10, 10344–10351.
400 Letters in Applied Microbiology 56, 389--400 ©2012 The Society for Applied Microbiology
Genetic diversity of Pyrenophora teres f. teres A. Bouajila et al.