Ecology and Epidemiology
Genetic Analysis of Phytophthora nicotianae Populations from Different
Hosts Using Microsatellite Markers
Antonio Biasi, Frank N. Martin, Santa O. Cacciola, Gaetano Magnano di San Lio,
Niklaus J. Grünwald, and Leonardo Schena
First, fourth, and sixth authors: Dipartimento di Agraria, Università Mediterranea di Reggio Calabria, Località Feo di Vito, 89122 Reggio
Calabria, Italy; second author: United States Department of Agriculture–Agricultural Research Service (USDA-ARS), 1636 East Alisal Street,
Salinas, CA 93905; third author: Dipartimento di Agricoltura, Alimentazione e Ambiente, Università degli Studi, Via S. Sofia 100, 95123
Catania, Italy; and fifth author: Horticultural Crops Research Laboratory, USDA-ARS, Corvallis, OR.
Accepted for publication 15 April 2016.
ABSTRACT
Biasi, A., Martin, F. N., Cacciola, S. O., Magnano di San Lio, G.,
Grünwald, N. J., and Schena, L. 2016. Genetic analysis of Phytophthora
nicotianae populations from different hosts using microsatellite markers.
Phytopathology 106:1006-1014.
In all, 231 isolates of Phytophthora nicotianae representing 14 populations
from different host genera, including agricultural crops (Citrus, Nicotiana,
and Lycopersicon), potted ornamental species in nurseries (Lavandula,
Convolvulus, Myrtus, Correa, and Ruta), and other plant genera were
characterized using simple-sequence repeat markers. In total, 99 multilocus
genotypes (MLG) were identified, revealing a strong association between
genetic grouping and host of recovery, with most MLG being associated
with a single host genus. Significant differences in the structure of
populations were revealed but clonality prevailed in all populations.
Isolates from Citrus were found to be genetically related regardless of
In a recent survey to query the scientific community for their
ranking of plant-pathogenic oomycete species based on both scientific
and economic importance, Phytophthora nicotianae Breda de Haan
(P. parasitica Dastur) was listed eighth, and it is likely to gain
importance in the foreseeable future (Kamoun et al. 2015). This
oomycete is a soilborne plant pathogen with a wide host range
comprising more than 250 plant genera (Cline et al. 2008;
Panabières et al. 2016). It is particularly known for its damage on
the genera Nicotiana and Citrus, as the causal agent of black shank
and citrus root rot and gummosis, respectively, but it is responsible
for heavy losses on many other economically important crops such
as fruit trees and vegetable and ornamental crops (Erwin and
Ribeiro 1996; Ippolito et al. 2004; Moralejo et al. 2009). A number
of surveys revealed that P. nicotianae is one of the most common
pathogens in nurseries, especially on ornamental plants, where it
commonly completes several disease cycles per year due to the
repeated culture of different host species (Cacciola et al. 1997,
2001; Moralejo et al. 2009; Pane et al. 2005; Prigigallo et al. 2015,
2016; Reichard and White 2001). This pathogen produces various
types of propagules, including sporangia, chlamydospores, and
oospores, which can be formed when the mycelium of sexually
Corresponding author: L. Schena; E-mail address: lschena@unirc.it
*The e-Xtra logo stands for “electronic extra” and indicates that two supplementary
tables are published online.
http://dx.doi.org/10.1094/PHYTO-11-15-0299-R
This article is in the public domain and not copyrightable. It may be freely
reprinted with customary crediting of the source. The American Phytopathological
Society, 2016.
1006
PHYTOPATHOLOGY
their geographic origin and were characterized by high genetic uniformity and high inbreeding coefficients. Higher variability was observed
for other populations and a significant geographical structuring was
determined for isolates from Nicotiana. Detected differences were
related to the propagation and cultivation systems of different crops.
Isolates obtained from Citrus spp. are more likely to be distributed
worldwide with infected plant material whereas Nicotiana and Lycopersicon spp. are propagated by seed, which would not contribute to the spread
of the pathogen and result in a greater chance for geographic isolation
of lineages. With regard to ornamental species in nurseries, the high
genetic variation is likely the result of the admixture of diverse pathogen
genotypes through the trade of infected plant material from various
geographic origins, the presence of several hosts in the same nursery,
and genetic recombination through sexual reproduction of this heterothallic
species.
compatible mating types (A1 and A2) comes into contact. Sporangia
can germinate directly as mycelium or differentiate into zoospores
that are motile. Oospores constitute a potential source of genetic
variation and, with resting chlamydospores, contribute to survival
under unfavorable conditions in soil or within infected plant tissues.
P. nicotianae might be considered a candidate species for
studying migration pathways of Phytophthora spp. and other
soilborne pathogens on a global scale. Its polyphagia and prominence in nurseries of potted ornamentals and fruit tree species are
important factors that favor a rapid distribution on a global scale.
Indeed, the global nursery trade represents one of the most efficient
diffusion pathways for soilborne pathogens (Abad et al. 2014; Jung
et al. 2016; Moralejo et al. 2009; Olson and Benson 2011; Parke and
Grünwald 2012). Furthermore, the ornamental industry extensively
uses antioomycete chemicals that can hide the presence of the
pathogen and increase the risk of rapid spread of resistant strains to
new areas (Brasier 2008; Olson et al. 2013). Moreover, P. nicotianae
will likely benefit from the warming climate because its host range
is generally similar to other species of prime economic importance
such as P. infestans, P. capsici, and P. citrophthora but generally
requires warmer conditions than these other species (Erwin and
Ribeiro 1996; Kamoun et al. 2015).
Despite the great economic relevance of P. nicotianae, significant
information on the biology and ecology of this pathogen is still
lacking. Few studies are currently available on the genetic structure
of P. nicotianae populations and most of them were focused on
either specific hosts (mainly tobacco) or geographic areas. The
characterization of seven different populations from tobacco using a
random amplified polymorphic DNA polymerase chain reaction
(RAPD-PCR) approach revealed a high level of variability within a
population but no distinct genotypes were associated with specific
populations (Zhang et al. 2003). The same technique was used to
differentiate isolates causing black shank from isolates that did not
cause this disease (Zhang et al. 2001) and to identify markers linked
to the dominant black shank resistance gene (Johnson et al. 2002a).
Amplified fragment length polymorphism analysis enabled the
identification of six clonal lineages in a population from different
floricultural hosts and production sites (Lamour et al. 2003).
Sullivan and coworkers (2010) found that tobacco populations were
able to evolve and adapt to the host genotypes deployed in the field.
Recently, polymorphic mitochondrial and nuclear regions
were utilized to study genetic diversity in a worldwide collection
of P. nicotianae isolates (Mammella et al. 2011, 2013). Singlenucleotide polymorphisms (SNP) detected in both mitochondrial
and nuclear markers revealed a high level of dispersal of isolates and
a low geographic clustering of populations. Nonetheless, a specific
association was observed between the host of origin and genetic
cluster for some hosts and, thus, it was suggested that nursery
populations played an important role not only for increasing genetic
recombination within the species but also in terms of providing a
means of dispersal of genotypes worldwide via movement of infected
plant material. However, mitochondrial analyses conducted with an
outcrossing species such as P. nicotianae may produce incomplete
results, and the three nuclear markers investigated were not variable
enough to provide discrimination among closely related isolates
(Mammella et al. 2013).
Microsatellites, or simple-sequence repeats (SSR), are largely
accepted as a powerful molecular tool for investigating intraspecific
variability in a large number of eukaryotic species (Oliveira et al.
2006; Gonthier et al. 2015). In oomycetes, SSR have been used in a
number of important applications, including diagnosis and determination of mating type, genetic structure and disease dynamics,
and population genetics (Garnica et al. 2006; Schena et al. 2008).
Relevant studies have been conducted on several Phytophthora
spp., including P. infestans (Cooke and Lees 2004; Goss et al. 2014;
Li et al. 2013), P. alni (Ioos et al. 2007), P. ramorum (Goss et al. 2009;
Prospero et al. 2007), P. sojae (Stewart et al. 2014), and P. capsici (Hu
et al. 2013), as well as P. plurivora, P. multivora, and P. pini (Schoebel
et al. 2013, 2014). Furthermore, a set of nine specific SSR markers for
P. nicotianae has been recently developed (Biasi et al. 2015).
The objective of the present study was to genotype isolates of
P. nicotianae obtained from different hosts and geographic localities
using recently validated SSR markers (Biasi et al. 2015) to determine
whether there were associations of particular genotypes with host of
recovery or location of collection.
MATERIALS AND METHODS
Isolate sampling, identification, and mating type determination.
In total, 231 isolates of P. nicotianae were obtained from soil,
roots, and basal stem samples from different hosts and geographic
regions (Supplementary Table S1). Isolates were sampled from
six continents, although most of them were sourced from Italy
(n = 163), Vietnam (n = 36), the United States (n = 16), and Australia
(n = 6). Isolates were mainly obtained from Citrus spp. (n = 90),
several horticultural and ornamental crops (n = 121), and Nicotiana
spp. (n = 20). All isolates from ornamental cultures were sampled
from potted plants in nurseries.
Isolates were identified by means of morphological criteria and
sequencing of the internal transcribed spacer (ITS) region of the
ribosomal DNA. For ITS sequencing, total DNA was extracted as
described by Ippolito et al. (2002), amplified with the universal
primers ITS6 and ITS4, and sequenced with the same primers
using an external service (Macrogen). Isolates were determined to be
P. nicotianae based on their phylogenetic clustering with reference
isolates of the species (Robideau et al. 2011). Mating type was
determined by pairing each isolate with known A1 and A2 strains on
V8 juice agar medium, as described by Erwin and Ribeiro (1996).
SSR genotyping. Nine validated polymorphic SSR markers
were utilized to genotype isolates (Biasi et al. 2015). Forward primers
were labeled with the fluorescent dyes 6-FAM or HEX, while all
reverse primers were modified with a 59 PIG tail “GTTT” to reduce
the phenomenon of stutter peaks (Brownstein et al. 1996). Eight of the
nine forward primers were labeled with two different fluorophores
(HEX and 6-FAM) and assembled into four multiplex PCR sets for
simultaneous amplicon sizing (Table 1). Reaction mixtures and
amplification conditions were as described by Biasi et al. (2015).
The data were collected using the software Data Collection (v.2.0;
Applied Biosystems) and analyzed by Gene Mapper (v. 4.1; Applied
Biosystems) to derive the size of the labeled DNA fragments using
the GeneScan 500 LIZ Size Standard (Life Technologies).
Data analysis. Analysis focused on multilocus genotypes
(MLG) to infer genotypic diversity in populations. To perform
analyses, isolates were grouped according to the genus of the host
from which they were obtained. The R package poppr (Kamvar
et al. 2014) was used to calculate basic population statistics,
including (i) Stoddart and Taylor’s index, G = 1/Sip2i, where pi is
the observed frequency of ith genotype (Stoddart and Taylor 1988)
and the normalized G9 index which removes bias due to the sample
size (Chen et al. 1994), and it is particularly appropriate when
comparing populations showing high diversity; (ii) evenness, E5 =
(1/l) _ 1/eH9 _ 1, where l is Simpson’s index and H9 is ShannonWiener’s index; and (iii) Bruvo’s distance (Bruvo et al. 2004). E5 is
a preferred index of evenness because it is less dependent on the
number of genotypes in a sample (Grünwald et al. 2003). Bruvo’s
distance enabled the measurement of the genetic distances among
isolates by calculating the minimum distance across all combinations of possible pairs of alleles at a single locus and then
averaging that distance across all loci. Bruvo’s distance was
utilized to construct minimum spanning networks (MSN) to
graphically show the possible evolutionary relationships among
MLG. MSN contain a set of pairwise distances that describe the
degree of dissimilarity among individuals and allow inference of
population structure analogous to a phylogenetic analysis (Ronquist
and Huelsenbeck 2003; Salipante and Hall 2011). Lynch’s distances
(Lynch 1990) was used to perform a principal coordinate analysis
(PCA) using the R package POLYSAT (Clark and Jasieniuk 2011).
Lynch’s distance is a simple measure of similarity and corresponds to
two times the number of common alleles divided by the total number
of alleles of the two genotypes considered.
Furthermore, F statistics (FIS and FST) were calculated using the
software GENODIVE (Meirmans and van Tienderen 2004), in order
to quantify the level of divergence between observed and expected
heterozygosity. More specifically, the inbreeding coefficient FIS was
used to scale the deviation of genotypic frequencies from expected
panmictic frequencies in terms of heterozygous deficiency or excess.
The fixation index FST was used to examine the overall genetic
differentiation among populations.
TABLE 1. Number of alleles, range of amplicon size, and number of repeats
detected in the complete panel of Phytophthora nicotianae isolates analyzed in
the present study using a validated set of nine simple-sequence repeatsa
Locusb
P5(1)
P15(2)
P17(1)
P643(3)
P788(3)
P1129(4)
P1509(5)
P2039(4)
P2040(2)
a
b
Number of
alleles
Dye
Product
size (bp)
Number of
repeats
13
14
14
17
7
7
23
4
7
HEX
FAM
FAM
FAM
HEX
HEX
FAM
FAM
HEX
186–266
66–123
102–165
148–202
127–143
133–163
116–176
99–120
149–167
4–24
8–27
10–31
9–36
9–17
7–17
12–42
5–12
8–14
Biasi et al. (2015).
Each number in parentheses indicates the markers paired for multiplex
polymerase chain reaction.
Vol. 106, No. 9, 2016
1007
RESULTS
SSR genotyping. Considering all possible combinations among
investigated isolates and the nine SSR loci, only 2 of 2,079 amplicons (locus P1509 for isolates P1495 and M1f1h) could not be
sized because no amplification occurred (Supplementary Tables S1
and S2). In total, 99 MLG were detected among the 231 isolates and
most genotypes were observed only once or at low frequency. The
number of alleles at each locus varied from a minimum of 4 (locus
2039) to a maximum of 23 (locus P1509) while the number of
repeats ranged from 4 (locus P5) to 42 (locus P1509) (Table 1).
TABLE 2. List of multilocus genotypes (MLG) characterized in the present
study along with host and geographic origin of isolatesa
Nb
Host
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
1
1
4
1
1
3
1
1
1
1
1
2
1
1
8
1
3
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
1
1
2
1
1
2
3
1
1
1
1
1
1
1
1
1
1
1
1
3
1
1
1
1
1
1
2
2
46
47
48
1
1
19
49
50
1
1
Nicotiana tabacum
Myrtus communis
Lavandula stoechas
L. stoechas
Chamaleucium uncinatum
Convolvulus mauritanicus
C. mauritanicus
C. mauritanicus
Hebe × Veronica myrtifolia
L. officinalis
L. officinalis
M. communis
M. communis
Chamaleucium uncinatum
Ruta graveolens
R. graveolens
Lycopersicon esculentum (2);
R. graveolens (1)
L. esculentum
L. esculentum
Lavandula officinalis
L. officinalis
Capsicum annum
Citrus maxima
C. aurantium
C. aurantium
C. aurantium
C. aurantium
C. aurantium
C. aurantium
C. aurantium
C. aurantium
C. aurantium
Polygala myrtifolia
Lavandula sp.
M. communis
Convolvulus mauritanicus
C. mauritanicus
Lycopersicon esculentum
L. esculentum
L. esculentum
L. esculentum
L. esculentum
C. sinensis × P. trifoliata
Lavandula angustifolia
Capsicum annuum (1);
M. communis (1)
Lycopersicon esculentum
C. annuum
Citrus maxima (18);
C. reticulata (1)
C. sinensis × P. rifoliata
C. maxima
MLG
a
b
Geographic origin
Australia
Sardinia
Sicily
Sicily
Apulia
Apulia
Apulia
Apulia
Sicily
Apulia
Apulia
Sardinia
Sardinia
Sicily
Sicily
Sicily
Lazio (2); Sicily (1)
Lazio
Lazio
Sicily (1); Liguria (1)
Liguria
Spain
Mo Cay
Sicily
Sicily
Sicily
Sicily
Sicily
Tunisia
Sicily
Sicily
Sicily
Liguria
Apulia
Liguria
Apulia
Apulia
Spain
Lazio
Lazio
Sicily
Lazio
California
Piedmont
Calabria (1); Sicily (1)
Chile
Calabria
Mo Cay (10); Thot
Not (7); Dong Nai (2)
California
Mo Cay
(continued in next column)
Numbers within parentheses indicate isolates sharing the same MLG from
each host and geographic locality. Sicily, Apulia, Sardinia, Lazio, Liguria,
Piedmont, Calabria, and Sardinia are Italian regions and Mo Cay, Dong Nai,
Thot Not, Binh Duong, and Cao Phong are Vietnamese provinces.
Number of isolates.
1008
PHYTOPATHOLOGY
MLG52 was observed most frequently, because it was shared in
38 isolates, which were all recovered from Citrus spp. (Table 2). In
all, 6 of these isolates were collected from three different districts
in Vietnam, 1 from the Philippines, and 31 from three Italian regions
(27 in Sicily, 3 in Calabria, and 1 in Apulia). Interestingly, the
second most numerous MLG (MLG48) was also shared among
Citrus strains (n = 19), although most of them were obtained from a
single host species (Citrus maxima), with a single isolate sampled
from C. reticulata. All isolates with this MLG were recovered from
southern Vietnam. MLG71 and MLG66 were represented by 12 and
11 isolates, respectively, and all isolates of these genotypes were
recovered from the same geographic region (Sardinia, Italy) and host
TABLE 2. (continued from preceding column)
MLG
Nb
Host
Geographic origin
51
52
1
38
Mo Cay
Sicily (27); Calabria (3);
Binh Duong (2);
Cao Phong (2); Dong
Nai (2); Apulia (1);
Philippines (1)
53
54
55
56
57
58
59
60
61
62
1
1
2
1
1
1
1
1
1
6
63
64
65
1
2
6
66
67
68
69
70
71
72
73
74
11
1
1
3
1
12
1
1
2
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
5
1
3
1
1
1
1
1
1
1
2
1
1
1
1
1
1
1
1
10
1
2
1
1
2
C. maxima
C. sinensis × P. trifoliata (1);
C. aurantifolia (1);
C. aurantium (23);
C. jambhiri (1);
C. maxima (4);
C. medica (8)
C. aurantium
C. maxima
C. maxima
C. sinensis × P. trifoliate
M. communis
C. aurantium
C. aurantium
C. aurantium
C. aurantium
Lavandula officinalis (4);
P. myrtifolia (2)
L. officinalis
C. aurantium
Hebe × Veronica
buxifolia (2);
L. officinalis (4)
M. communis
M. communis
M. communis
M. communis
M. communis
M. communis
M. communis
Rosmarinus officinalis
Chamaleucium
uncinatum (1);
L. officinalis (1)
Dodonaea purpurea
N. tabacum
N. tabacum
N. tabacum
N. tabacum
N. tabacum
N. tabacum
N. tabacum
N. tabacum
N. tabacum
N. tabacum
Rosmarinus sp.
N. tabacum
N. tabacum
Citrus sp.
N. tabacum
N. tabacum
N. tabacum
N. tabacum
Correa reflexa
C. reflexa
Rosmarinus sp.
Citrus aurantium
C. aurantium
C. aurantium (1);
C. reticulata (1)
Sicily
Dong Nai
Dong Nai
California
Sardinia
Syria
Apulia
Apulia
Sicily
Sicily (4);
Liguria (2)
Sicily
Sicily
Sicily (6)
Sardinia
Sardinia
Sardinia
Sardinia
Sardinia
Sardinia
Sardinia
Sicily
Sicily
Sicily
Kentucky
Virginia
Australia
Australia
Australia
Australia
Australia
Virginia
Virginia
Virginia
Sicily
Kentucky
Georgia
Trinidad and Tobago
North Carolina
Georgia
Greece
Virginia
Sicily
Sicily
Sicily
Ham Yen
Ham Yen
Ham Yen (1),
Cao Phong (1)
(Myrtus spp.). Similarly, MLG94 was identified in 10 isolates from
the same region (Sicily, southern Italy) and host (Correa reflexa).
The great majority of MLG were associated with isolates from a
single host genus. Exceptions were observed in MLG17 (Ruta and
Lycopersicon), MLG45 (Myrtus and Capsicum), MLG62 (Polygala and Lavandula), MLG65 (Hebe and Lavandula), and ML74
(Chamaleucium and Lavandula).
Fifteen isolates showed unexpected ploidy; that is, more than two
alleles were detected in one or more SSR loci. For 14 of the isolates,
triploidy was identified in one of five loci (P15, P788, P1129,
P1509, and P2039), while tetraploidy was observed for locus P17 in
isolate Ph168; this isolate also was triploid for loci P15 and P1129.
All isolates were the only representatives in their MLG (MLG 1, 8,
9, 26, 29, 31, 32, 33, 40, 51, 53, 70, 88, and 92) with the exception of
MGL44, which had two isolates collected from the same host and
location.
Population genetic analysis. The 231 isolates sampled globally
were grouped into 14 populations according to the host genus
sampled or into 15 populations by geographic origin to determine
whether populations were differentiated by host or geographic
origin (Table 3). Analyses revealed a prevalence of clonal reproduction in P. nicotianae, with positive FIS values ranging from
0.260 to 1 (Table 3). This was particularly evident for isolates collected from Citrus spp. (FIS = 0.721), which represented the most
abundant group. MSN constructed using Bruvo’s distance (Bruvo
et al. 2004) revealed that isolates from Citrus constituted a distinct
group regardless of their geographic origin (Figs. 1 and 2). Two
subgroups, mainly represented by MLG48 (19 isolates) and MLG52
(38 isolates), were identified within the Citrus population. The first
subgroup contained exclusively isolates from Vietnam, while the
latter subgroup included isolates from three different continents
(Europe, North America, and Asia) (Figs. 1 and 2). The only Citrus
isolate outside of these groups was IMI268688 (MLG 89), which
grouped close to the tobacco isolates from Kentucky and Virginia
(MLG 76, 77, 83, 84, and 85). The A1 mating type occurred at high
frequency (82 of 90) in Citrus spp. and the A2 isolates were mainly
found in Vietnam (6 of 8). The PCA, based on Lynch’s distance,
further confirmed that isolates from Citrus spp. constituted a
separate cluster, independent of geographic provenance (Fig. 3). In
agreement between MSN and PCA, statistical analyses revealed a
higher level of uniformity (G9 = 0.049, E5 = 0.4, FIS = 0.72) in the
population from Citrus spp. (Table 3). Furthermore, FST values
showed a relevant genetic divergence among Citrus isolates and
other populations (Table 4).
A different population structure was observed for isolates from
Nicotiana spp. These isolates clustered into three different groups
(Fig. 1). Two of these groups were clearly associated with their
geographic origin because they contained only isolates from
Virginia and Kentucky (MLG 76, 77, 83, 84, and 85, all of which
are A2 mating type) or Australia (MLG 78, 79, 80, 81, and 82; all
except MLG82 were A1 mating type), respectively (Fig. 2). On the
other hand, a third group (MLG 87, 88, 90, 91, 92, and 93; both A1
and A2 mating types) included isolates from Georgia, North
Carolina, Kentucky, Virginia, and Greece (Fig. 2). According to
the G9 values observed, a significant lower genetic uniformity was
determined in the Nicotiana population (0.714) as compared with
the Citrus population. Furthermore, a higher level of variability was
found based on E5 (0.896) and FIS (0.26) coefficients (Table 3).
Isolates from Lycopersicon spp. were predominantly A1 and
were found to be more distantly related, with all but one (MLG 19)
distributed in the central part of the network connected by thin gray
lines, indicating a high genetic distance among isolates (Fig. 1).
This is reflected by this population having the highest values of G9
and E5 (0.833 and 0.952, respectively) among those analyzed (Table 3).
Furthermore, it had a significantly lower FIS (0.511) as compared with
the Citrus population, indicating a lower level of inbreeding.
A high genetic diversity was revealed for isolates from some of
the ornamental species. For example, the Lavandula population
(8 A1 and 14 A2 isolates) was separated into several genetically
distant groups, despite the fact that all isolates were recovered
from Italy (Figs. 1 and 2; Table 1). Similarly, isolates from genera
Convolvulus and Myrtus (both with all A2 isolates) clustered into
three and two genetically distant groups, respectively, although
they were recovered from single nurseries located in Apulia and
Sardinia, respectively. Statistical parameters confirmed a high level of
genetic variation (Table 3). Genetically uniform populations were
associated with isolates recovered from the ornamental species of
Correa and Ruta (Fig. 1; Tables 3 and 4). However, this result was
likely to be affected by the limited number of isolates examined (11
and 10, respectively) and the fact that all isolates were recovered
from the same nursery. Isolates from other plant genera were
represented by a limited number of samples, preventing an accurate
statistical analyses (Table 1). These isolates mainly scattered in the
central part of the MSN (Fig. 1).
DISCUSSION
In the present study, a set of nine polymorphic microsatellite
markers (Biasi et al. 2015) was used to analyze the genetic diversity within 231 isolates of P. nicotianae grouped into distinct
populations representing a wide host range and several geographic
locations. The selected markers proved to be very consistent, with
a percentage of amplification close to 100%; only 2 of 2,079
isolate–marker combinations did not produce an amplicon. In
contrast, considerably higher levels of failures in sizing amplicons
at SSR loci have been reported for other Phytophthora spp. For
example, two of the nine loci selected for the assessment of the
variability in P. infestans failed in producing positive amplification
with 30% of the isolates (Brurberg et al. 2011). Our analyses
further revealed a high level of polymorphism, with a total
number of 4 (locus P2039) and 23 (locus P1509) alleles detected
per locus. Unexpectedly, the number of bases in the repeat unit
was not inversely correlated with the number of genotypes
observed (Shinde et al. 2003). For example, the 4-bp motif analyzed
in the present study (locus P5) yielded 16 different alleles and
was more polymorphic than four other loci with a 3-bp motif.
Dinucleotides were the markers with the highest number of alleles.
On the whole, our data confirm that the selected markers were
appropriate for the accurate characterization of populations of
P. nicotianae. Furthermore, labeling primers for each locus with
different fluorophores (HEX and FAM) significantly increased the
throughput of the method and enabled fast, accurate, and costeffective genotyping (Biasi et al. 2015).
The genotyping of 231 isolates allowed identification of 99 MLG,
with a significant number of isolates exhibiting a unique genetic
fingerprint. Interestingly, an unexpected genetic framework for a
diploid organism like P. nicotianae was revealed by the detection of
16 examples of triploidy and 1 of tetraploidy. The presence of
polyploidy in P. nicotianae was previously observed by SNP analyses
TABLE 3. Origin, diversity statistics, and mating type frequency in Phytophthora nicotianae populations investigated in the present studya
Mating type
Population
N
MLG
G9
E5
FIS
A1
A2
ND
Convolvulus
Lycopersicon
Ruta
Correa
Nicotiana
Lavandula
Myrtus
Citrus
9
10
10
11
20
23
37
90
5
9
3
2
17
12
13
29
0.429
0.833
0.152
0.109
0.714
0.365
0.129
0.049
0.859
0.952
0.576
0.556
0.896
0.832
0.614
0.400
0.464
0.511
0.858
1
0.260
0.369
0.624
0.721
0
1
10
8
7
8
0
82
9
7
0
2
12
14
37
8
0
2
0
1
1
1
0
0
a
N = number of isolates, MLG = number of multilocus genotypes identified in
each population, G9 = normalized Stoddart and Taylor’s index, E5 =
evenness, FIS = inbreeding coefficient, and ND = not determined.
Vol. 106, No. 9, 2016
1009
(Mammella et al. 2013). It is possible that this variation in ploidy was
generated through sexual recombination because non-Mendelian
recombination patterns in progeny have been reported (Förster and
Coffey 1990). The characterization of P. cinnamomi using microsatellite markers also revealed a large proportion of non-Mendelian
inheritance (Dobrowolski et al. 2002). This aberrant nuclear genetic
condition was best explained by nondisjunction at meiosis in the
trisomic parents, because aneuploid progeny were also identified.
Ivors et al. (2006) observed conditions of trisomy for some isolates of
P. ramorum. Initially, they hypothesized that multiple alleles resulted
from horizontal gene transfer occurring after introgression of genes
from other Phytophthora spp.; however, the high homology of
flanking regions suggested that trisomy was due to gene duplication.
Examples of different levels of ploidy for SSR regions were also
documented for P. infestans (Brurberg et al. 2011; Goss et al. 2014;
Lees et al. 2006; van der Lee et al. 2001). In the present study, Bruvo’s
distances were utilized to construct MSN and evaluated for 14 or 15
populations identified according to the genera of the plant hosts or
geographic origin. The use of this function was important because it
enabled calculation of genetic distances without considering ploidy
of a locus and, thus, permitted interpretation of heterogeneous data
(Cooke et al. 2012).
Analyses revealed significant differences in the structure of
populations associated with different host species, although a
prevalence of clonality was observed for all populations. Furthermore, the most abundant MLG detected were associated with a
single host genus, suggesting a strong association among P. nicotianae
genotypes and select plant hosts. According to both MSN and
PCA analyses, Citrus isolates clustered together regardless of their
geographic origin. In agreement with this clustering, all indexes
used for statistical analyses confirmed a higher genetic uniformity
in this group. This Citrus population was characterized by a low
evenness (E5) value and by a heterozygote deficiency, especially when
compared with other populations. Furthermore, the index of association (FST) confirmed a clear separation of the Citrus population
that maintained its own genotypic uniqueness. These results are
Fig. 1. Minimum spanning network of Phytophthora nicotianae isolates describing the relationship among multilocus genotypes (MLG) detected based on their
host genus. Numbers along nodes and genus of origin correspond to MLG. Nodes represent unique MLG and are scaled proportionally to the number of individuals
sharing the same MLG. Thickness and black intensity of lines connecting nodes are inversely proportional to Bruvo’s distance (the larger the distance between two
nodes, the thinner and less black intense is the line that connects them).
1010
PHYTOPATHOLOGY
particularly relevant considering that Citrus isolates were recovered
from several different countries and represented the most abundant
population analyzed in the present study. Our results are in agreement
with previous reports based on the analysis of mitochondrial and
nuclear SNP (Mammella et al. 2011, 2013). In this study, the majority
of Citrus isolates from Italy, California, Florida, Syria, Albania, and
the Philippines clustered in the same mitochondrial group and shared
at least one nuclear allele. The existence of a marked preference
among certain P. nicotianae genotypes for Citrus spp. is in agreement
with the great degree of virulence specialization seen in P. nicotianae
to a given host (Erwin and Ribeiro 1996). For instance, an isolate
from okra was not pathogenic to Citrus spp. and vice versa (Erwin
1964). Similarly, isolates from Citrus spp. were more virulent on
roots of rough lemon than isolates from petunia, tomato, walnut, silk
tree, jojoba, hibiscus, and peach, although, in another study, tomato
plants exhibited high susceptibility to many isolates, including Citrus
isolates (Bonnet et al. 1978; Matheron and Matejka 1990). Furthermore, a mating type (A1) was largely prevalent on Citrus, although
six and two isolates with A2 mating type were recovered in Vietnam
and Italy, respectively. The absence of a geographic clustering and the
concurrent existence of a significant correlation with the host could
be indicative of extensive migration of the isolates via plant material
or host adaptation. It can be speculated that P. nicotianae isolates have
been spread worldwide with infected plant material and, afterward,
lineages may have progressively diverged. In this context, a major
role seems to be played by the globalization of the nursery trade, with
particular emphasis on container-grown and bare root plants.
The identification of two subgroups within the Citrus population
may also be related to the considerations discussed above. Indeed,
one of the subgroups was represented by isolates exclusively recovered
from Vietnam, mainly from Citrus maxima, while the other subgroup
comprised isolates from several different countries and Citrus spp.
Considering that C. maxima (commonly named “pommelo”) is a
native species of Southeast Asia and that the introduction of plant
material of this species into Vietnam from other countries is very
limited, a specific coevolution of P. nicotianae with Citrus in Vietnam
Fig. 2. Minimum spanning network of Phytophthora nicotianae isolates describing the relationship among multilocus genotypes (MLG) detected based on their
country of origin. Numbers along nodes and country of origin correspond to MLG. Nodes represent unique MLG and are scaled proportionally to the number of
individuals sharing the same MLG. Thickness and black intensity of lines connecting nodes are inversely proportional to Bruvo’s distance (the larger the distance
between two nodes, the thinner and less black intense is the line that connects them).
Vol. 106, No. 9, 2016
1011
can be hypothesized. An understanding of this phenomenon could
allow unraveling of the molecular basis of interactions between host
and P. nicotianae, developing a picture of how life history traits of
both host and pathogen interaction shape evolutionary trajectories
(Burdon and Thrall 2009).
A marked association among molecular groups and host of
recovery was also revealed for isolates from Nicotiana, although a
different population structure was observed. Indeed, isolates clustered
into three genetically distinct groups, generally corresponding to
different geographic areas and, in agreement with the presence of both
mating types (7 A1 and 12 A2 isolates), a significantly lower genetic
uniformity was revealed. Although a preferential virulence association between Nicotiana spp. and P. nicotianae has been reported
(Colas et al. 1998), the commercial production system utilized for this
crop is likely to have played a role in determining its geographical
structuring. In fact, tobacco is propagated by seed, which does not
contribute to the spread of the pathogen, and plantlets are very rarely
transplanted into areas different from those in which they have
been produced. In this situation, different pathogen lineages can
evolve into geographically separated areas on their own host
because migration does not play a factor. Furthermore, the tobacco
population may have been shaped by cultivar resistance and other
control means. According to Sullivan and coworkers (2005), the
continuous planting of varieties with Php and Phl genes caused a
shift in pathogen population from race 0 to race 1. On the other
hand, prolonged cultivation of varieties with partial resistance to
all races may cause an increased level of pathogen aggressiveness
(Sullivan et al. 2005). Similarly, cultural practices, crop rotation,
and chemicals commonly used in integrated control approaches
have an impact on pathogen fitness and play a role in modeling
populations (Bittner and Mila 2016).
A similar situation may occur for isolates from Lycopersicon.
Indeed, isolates characterized in the present study were found to be
genetically related, although high genetic variation was revealed
within this population. Because tomato is propagated via seed and
transplants produced in nurseries are generally utilized in the same
area of production, the geographic isolation of lineages and their
separate coevolution with the host can be hypothesized.
High levels of genetic variation and low inbreeding coefficients
were observed for three of the analyzed populations from potted
ornamental species in nurseries (Lavandula, Convolvulus, and
Myrtus spp.). Although statistical analyses did not support a higher
variability when compared with Nicotiana and Lycopersicon populations, it must be highlighted that isolates from these ornamental
species were recovered from limited areas represented by few nurseries in Italy (Lavandula) or even single nurseries (Convolvulus and
Myrtus). The prevalence or the exclusive presence of the A2 mating type
in these populations deserves further investigation. Furthermore, the
high genetic uniformity revealed in two other ornamental genera (Correa
and Ruta) does not seem remarkable because of the limited number of
isolates, all recovered from the same nurseries. The production system of
nursery ornamentals is different from that of Citrus plants. Usually,
Citrus plants produced in nurseries are planted in commercial orchards.
In contrast, potted ornamental plants are produced in large production
nurseries and then distributed to smaller ones which, in turn, sell them to
retail garden centers or shops. As a consequence, new Phytophthora
genotypes are rapidly spread on a large scale. Several components may
determine the genetic variability of a pathogen population, including the
genetic variability of the original population or the introduction of a few
new genotypes from other populations (founder effect), mutations,
selection pressure by the host, and sexual recombination. In ornamental
nurseries, the cultivation of many plant species and varieties from
different geographic areas may favor the introduction of exotic new
Phytophthora spp., as demonstrated for P. ramorum (Goss et al. 2009;
Ivors et al. 2006; Vercauteren et al. 2011), and the intermixing of complementary mating types of heterothallic species, thus increasing the
Fig. 3. Principal coordinate analysis based on Lynch distances of Phytophthora nicotianae isolates analyzed in the present study according to the host genus of
origin.
TABLE 4. Genetic differentiation (pairwise FST) estimates of simple-sequence repeats for Phytophthora nicotianae isolates grouped by host genus
Host
Citrus
Convolvulus
Correa
Lavandula
Lycopersicon
Myrtus
Nicotiana
Ruta
Citrus
Convolvulus
Correa
Lavandula
Lycopersicon
Myrtus
Nicotiana
Ruta
…
0.138
0.073
0.090
0.116
0.085
0.094
0.125
…
…
0.25
0.023
0.037
0.053
0.051
0.060
…
…
…
0.059
0.058
0.084
0.066
0.087
…
…
…
…
0.037
0.041
0.042
0.048
…
…
…
…
…
0.067
0.051
0.043
…
…
…
…
…
…
0.059
0.087
…
…
…
…
…
…
…
0.073
…
…
…
…
…
…
…
…
1012
PHYTOPATHOLOGY
opportunity of sexual recombination. Furthermore, interspecific hybrids
of P. nicotianae are well documented (Faedda et al. 2013). Natural
hybrids of P. nicotianae and P. cactorum were first reported in The
Netherlands and they are now considered well established on several
hosts all over the world (Faedda et al. 2013; Man in‘t Veld et al. 1998;
Szigethy et al. 2013).
In agreement with the above considerations, the few MLG shared
by isolates from different plant hosts were detected in isolates
from the ornamental species (Polygala and Lavandula, Hebe and
Lavandula, and Chamaleucium and Lavandula) or in isolates from
ornamental and horticultural species (Ruta and Lycopersicon or
Myrtus and Capsicum). Furthermore, considering the total number
of analyzed isolates, a conspicuously higher number of MLG was
found in nurseries as compared with Citrus and tobacco.
In conclusion, the present study provides an important advancement in our understanding of the population structure and
evolutionary history of P. nicotianae. Although new analyses focusing on specific hosts and on a larger number of isolates collected
with a hierarchical approach are necessary to accurately define
P. nicotianae genetic groups, a strong association among pathogen
genotypes and host species is clearly supported, suggesting that the
speciation process of this pathogen may be driven by host selection pressure and type of propagation. In general, it seems that host
specialization of a P. nicotianae population occurs more frequently
in intensive cropping systems. This finding, in agreement with the
data available on the host-specific virulence of P. nicotianae isolates
(Erwin and Ribeiro 1996; Taylor et al. 2012) and with previous
molecular data (Mammella et al. 2011, 2013), may suggest the need
for reconsideration of the concept of species and the consequent
identification of specific pathotypes or subspecies within P. nicotianae
sensu lato. Genome-wide analyses currently in progress on several
P. nicotianae strains of diverse origins may greatly contribute to
enabling a comparative analysis of genes that determine host range
(Kamoun et al. 2015). An analysis of the corresponding pathogenicity and virulence gene diversity may provide additional information necessary to draw firmer conclusions about factors involved
in host specialization.
ACKNOWLEDGMENTS
We thank B. Tyler, F. Panabières, and C. Russ for making available the
P. nicotianae genome sequences at https://olive.broadinstitute.org/projects/
phytophthora_parasitica prior to publication. Much of this work was conducted by A. Biasi while visiting the Martin lab and partially supported by
a grant from the California Department of Food and Agriculture (2012
California Specialty Crop Block Grant Program SCB12051) and by grant
FIRB 2010 (RBFR10PZ4N) from the Italian Ministry of Education,
University and Research. We thank Z. Kamvar for guidance in using poppr
and R for population genetic analysis.
LITERATURE CITED
Abad, Z. G., Abad, J. A., Cacciola, S. O., Pane, A., Faedda, R., Moralejo, E.,
Pérez-Sierra, A., Abad-Campos, P., Alvarez-Bernaola, L., Bakonyi, J., Józsa,
A., Herrero, M. L., Burgess, T. I., Cunnington, J. H., Smith, I. W., Balci, Y.,
Blomquist, C., Henricot, B., Denton, G., Spies, C., McLeod, A., Belbahri, L.,
Cooke, D. E. L., Kageyama, K., Uematsu, S., Kurbetli, I., and Değirmenci, K.
2014. Phytophthora niederhauserii sp. nov., a new polyphagous species
mostly isolated from ornamentals potted plants in twelve countries of five
continents. Mycologia 106:431-447.
Biasi, A., Martin, F. N., and Schena, L. 2015. Identification and validation of
polymorphic microsatellite loci for the analysis of Phytophthora nicotianae
populations. J. Microbiol. Methods 110:61-67.
Bittner, R. J., and Mila, A. L. 2016. Effects of oxathiapiprolin on Phytophthora nicotianae, the causal agent of black shank of tobacco. Crop Prot. 81:
57-64.
Bonnet, P., Maia, N., Tello-Marquina, J., and Venard, P. 1978. Pouvoir pathogène du Phytophthora parasitica (Dastur): Facteurs de variabilité et notion
de spécialisation parasitaire. Ann. Phytopathol. 2:15-29.
Brasier, C. M. 2008. The biosecurity threat to the UK and global environment
from international trade in plants. Plant Pathol. 57:792-808.
Brownstein, M. J., Carpten, J. D., and Smith, J. R. 1996. Modulation of nontemplated nucleotide addition by Taq DNA polymerase: Primer modifications that facilitate genotyping. Biotechniques 20:1004-6, 1008-10.
Brurberg, M. B., Elameen, A., Le, V. H., Nærstad, R., Hermansen, A.,
Lehtinen, A., Hannukkala, A., Nielsen, B., Hansen, J., Andersson, B., and
Yuen, J. 2011. Genetic analysis of Phytophthora infestans populations in the
Nordic European countries reveals high genetic variability. Fungal Biol. 115:
335-342.
Bruvo, R., Michiels, N. K., D’Souza, T. G., and Schulenburg, H. 2004. A
simple method for the calculation of microsatellite genotype distances
irrespective of ploidy level. Mol. Ecol. 13:2101-2106.
Burdon, J. J., and Thrall, P. H. 2009. Coevolution of plants and their pathogens
in natural habitats. Science 324:755-756.
Cacciola, S. O., Agosteo, G. E., Pennisi, A. M., Pane, A., and Pappalardo, P.
2001. Phytophthora species in nurseries of ornamental plants in southern
Italy. J. Plant Pathol. 83:231-235.
Cacciola, S. O., Pane, A., and Magnano di San Lio, G. 1997. Identification and
quantitative determination of Phytophthora species infecting ornamental
plants in nurseries. Pages 483-485 in: Diagnosis and Identification of Plant
Pathogens. H. W. Dehne, G. Adam, M. Diekman, J. Frahm, A. Mauler-Machnik,
and P. van Halteren, eds. Kluwer Academic Publishers, Dordrecht, The
Netherlands.
Chen, R. S., Boeger, J. M., and McDonald, B. A. 1994. Genetic stability in a
population of a plant pathogenic fungus over time. Mol. Ecol. 3:209-218.
Clark, L. V., and Jasieniuk, M. 2011. POLYSAT: An R package for polyploidy
microsatellite analysis. Mol. Ecol. Resour. 11:562-566.
Cline, E. T., Farr, D. F., and Rossman, A. Y. 2008. A synopsis of Phytophthora
with accurate scientific names, host range, and geographic distribution.
Online publication. Plant Health Prog. doi:10.1094/PHP-2008-0318-01RS
Colas, V., Lacourt, I., Ricci, P., Vanlerberghe-Masutti, F., Venard, P., Poupet, A.,
and Panabières, F. 1998. Diversity of virulence in Phytophthora parasitica on
tobacco, as reflected by nuclear RFLPs. Phytopathology 88:205-212.
Cooke, D. E. L., and Lees, A. K. 2004. Markers, old and new, for examining
Phytophthora infestans diversity. Plant Pathol. 53:692-704.
Cooke, D. E. L., Lees, A. K., Lasses, P., and Gronbech-Hansen, J. 2012.
Making sense of Phytophthora infestans diversity at national and international scales. Pages 37-44 in: Proc. Thirteenth EuroBlight Workshop,
St Petersburg, Russia.
Dobrowolski, M. P., Tommerup, I. C., Blakeman, H. D., and O’Brien, P. A.
2002. Non- Mendelian inheritance revealed in a genetic analysis of sexual
progeny of Phytophthora cinnamomi with microsatellite markers. Fungal
Genet. Biol. 35:197-212.
Erwin, D. C. 1964. A strain of Phytophthora parasitica from okra and its
sexual compatibility with isolates from citrus. Phytopathology 54:114-115.
Erwin, D. C., and Ribeiro, O. K. 1996. Phytophthora Diseases Worldwide.
American Phytopathological Society Press, St. Paul, MN.
Faedda, R., Cacciola, S. O., Pane, A., Szigethy, A., Bakonyi, J., Man in‘t Veld,
W., Martini, P., Schena, L., and Magnano di San Lio, G. 2013. Phytophthora × pelgrandis causes root and collar rot of Lavandula stoechas in Italy.
Plant Dis. 97:1091-1096.
Förster, H., and Coffey, M. D. 1990. Mating behavior of Phytophthora parasitica: Evidence for sexual recombination in oospores using DNA restriction fragment length polymorphisms as genetic markers. Exp. Mycol.
14:351-359.
Garnica, D. P., Pinzón, A. M., Quesada-Ocampo, L. M., Bernal, A. J., Barreto,
E., Grünwald, N. J., and Restrepo, S. 2006. Survey and analysis of microsatellites from transcript sequences in Phytophthora species: Frequency,
distribution, and potential as markers for the genus. BMC Genomics 7:245.
Gonthier, P., Sillo, F., Lagostina, E., Roccotelli, A., Cacciola, S. O., Stenlid, J.,
and Garbelotto, M. 2015. Selection processes in simple sequence repeats
suggest a correlation with their genomic location: Insights from a fungal
model system. BMC Genomics 16:1107.
Goss, E. M., Larsen, M., Chastagner, G. A., Givens, D. R., and Grünwald, N. J.
2009. Population genetic analysis infers migration pathways of Phytophthora ramorum in US nurseries. PLoS Pathog. 5:e1000583.
Goss, E. M., Tabima, J. F., Cooke, D. E. L., Restrepo, S., Fry, W. E., Forbes,
G. A., Fieland, V. J., Cardenas, M., and Grünwald, N. J. 2014. The Irish
potato famine pathogen Phytophthora infestans originated in central
Mexico rather than the Andes. Proc. Natl. Acad. Sci. USA 111:8791-8796.
Grünwald, 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.
Hu, J., Pang, Z., Bi, Y., Shao, J., Diao, Y., Guo, J., Liu, Y., Lu, H., Lamour, K.,
and Liu, X. 2013. Genetically diverse long-lived clonal lineages of Phytophthora capsici from pepper in Gansu, China. Phytopathology 103:920-926.
Ioos, R., Barrès, B., Andrieux, A., and Frey, P. 2007. Characterization of
microsatellite markers in the interspecific hybrid Phytophthora alni ssp.
alni, and cross-amplification with related taxa. Mol. Ecol. Notes 7:133-137.
Vol. 106, No. 9, 2016
1013
Ippolito, A., Schena, L., and Nigro, F. 2002. Detection of Phytophthora
nicotianae and P. cytrophthora in citrus roots and soils by nested PCR.
Eur. J. Plant Pathol. 108:855-868.
Ippolito, A., Schena, L., Nigro, F., Soleti Ligorio, V., and Yaseen, T. 2004.
Real-time detection of Phytophthora nicotianae and P. citrophthora in
citrus roots and soil. Eur. J. Plant Pathol. 110:833-843.
Ivors, K., Garbelotto, M., Vries, I. D. E., Ruyter-Spira, C., Hekkert, B. T.,
Rosenzweig, N., and Bonants, P. 2006. Microsatellite markers identify
three lineages o f Phytophthora ramorum in US nurseries, yet single
lineages in US forest and European nursery populations. Mol. Ecol. 15:
1493-1505.
Johnson, E. S., Wolff, M. F., Wernsman, E. A., and Rufty, R. C. 2002a.
Marker-assisted selection for resistance to black shank disease in tobacco.
Plant Dis. 86:1303-1309.
Jung, T., Orlikowski, L., Henricot, B., Abad-Campos, P., Aday, G.,
Aguı́n Casal, O., Bakony, J., Cacciola, S. O., Cech, T., Chavarriaga, D.,
Corcobado, T., Cravador, A., Decourcelle, T., Denton, G., Diamandis, S.,
Doğmus‚-Lehtijärvi, H. T., Franceschini, A., Ginetti, B., Green, S.,
Glavendekić, M., Hantula, J., Hartmann, G., Herrero, M., Ivic, D.,
Horta Jung, M., Lilja, A., Keca, N., Kramarets, V., Lyubenova, A.,
Machado, H., Magnano di San Lio, G., Mansilla Vázquez, P. J., Marçais, B.,
Matsiakh, I., Milenkovic, I., Moricca, S., Nagy, Z. Á., Nechwatal, J.,
Olsson, C., Oszako, T., Pane, A., Paplomatas, E. J., Pintos Varela, C.,
Prospero, S., Rial Martı́nez, C., Rigling, D., Robin, C., Rytkönen, A.,
Sánchez, M. E., Sanz Ros, A. V., Scanu, B., Schlenzig, A., Schumacher, J.,
Slavov, S., Soll, A., Sousa, E., Stenlid, J., Talgø, V., Tomic, Z., Tsopelas, P.,
Vannini, A., Vettraino, A. M., Wenneker, M., Woodward, S., and
Peréz-Sierra, A. 2016. Widespread Phytophthora infestations in European
nurseries put forest, semi-natural and horticultural ecosystems at high risk
of Phytophthora diseases. For. Pathol. 46:134-163.
Kamoun, S., Furzer, O., Jones, J. D. G., Judelson, H. S., Ali, G. S., Dalio,
R. J. D., Roy, S. G., Schena, L., Zambounis, A., Panabieres, F., Cahill, D.,
Ruocco, M., Figueiredo, A., Chen, X.-R., Hulvey, J., Stam, R., Lamour, K.,
Gijzen, M., Tyler, B. M., Grünwald, N. J., Mukhtar, M. S., Tome, D. F. A.,
Tor, M., Van den Ackerveken, G., McDowell, J., Daayf, F., Fry, W. E.,
Lindqvist-Kreuze, H., Meijer, H. J. G., Petre, B., Ristaino, J., Yoshida, K.,
Birch, P. R. J., and Govers, F. 2015. The top 10 oomycete pathogens in
molecular plant pathology. Mol. Plant Pathol. 16:413-434.
Kamvar, Z. N., Tabima, J. F., and Grünwald, N. J. 2014. Poppr: An R package
for genetic analysis of populations with clonal, partially clonal, and/or
sexual reproduction. PeerJ 2:e281.
Lamour, K. H., Daughtrey, M. L., Benson, D. M., Hwang, J., and Hausbeck,
M. K. 2003. Etiology of Phytophthora drechsleri and P. nicotianae
(=P. parasitica) diseases affecting floriculture crops. Plant Dis. 87:854-858.
Lees, A. K., Wattier, R., Shaw, D. S., Sullivan, L., Williams, N. A., and Cooke,
D. E. L. 2006. Novel microsatellite markers for the analysis of Phytophthora infestans populations. Plant Pathol. 55:311-319.
Li, Y., Cooke, D. E. L., Jacobsen, E., and van der Lee, T. 2013. Efficient
multiplex simple sequence repeat genotyping of the oomycete plant pathogen Phytophthora infestans. J. Microbiol. Methods 92:316-322.
Lynch, M. 1990. The similarity index and DNA fingerprinting. Mol. Biol.
Evol. 7:478-484.
Mammella, M. A., Cacciola, S. O., Martin, F., and Schena, L. 2011. Genetic
characterization of Phytophthora nicotianae by the analysis of polymorphic
regions of the mitochondrial DNA. Fungal Biol. 115:432-442.
Mammella, M. A., Martin, F. N., Cacciola, S. O., Coffey, M. D., Faedda, R.,
and Schena, L. 2013. Analyses of the population structure in a global
collection of Phytophthora nicotianae isolates inferred from mitochondrial
and nuclear DNA sequences. Phytopathology 103:610-622.
Man in‘t Veld, W. A., Veenbaas-Rijks, W. J., Ilieva, E., de Cock, A. W. A. M.,
Bonants, P. J. M., and Pieters, R. 1998. Natural hybrids of Phytophthora
nicotianae and P. cactorum demonstrated by isozyme analysis and random
amplified polymorphic DNA. Phytopathology 88:922-929.
Matheron, M. E., and Matejka, J. C. 1990. Differential virulence of Phytophthora parasitica recovered from citrus and other plants to rough lemon
and tomato. Plant Dis. 74:138-140.
Meirmans, P. G., and van Tienderen, P. H. 2004. GENOTYPE and GENODIVE:
Two programs for the analysis genetic diversity of asexual organisms. Mol.
Ecol. Notes 4:792-794.
Moralejo, E., Pérez-Sierra, A. M., Álvarez, L. A., Belbahri, L., Lefort, F., and
Descals, E. 2009. Multiple alien Phytophthora taxa discovered on diseased
ornamental plants in Spain. Plant Pathol. 58:100-110.
Oliveira, E. J., Padua, J. G., Zucchi, M. I., Vencovsky, R., and Carneiro Vieira,
M. L. 2006. Origin, evolution and genome distribution of microsatellites.
Genet. Mol. Biol. 29:294-307.
Olson, H. A., and Benson, D. M. 2011. Characterization of Phytophthora spp.
on floriculture crops in North Carolina. Plant Dis. 95:1013-1020.
Olson, H. A., Jeffers, S. N., Ivors, K. L., Steddom, K. C., Williams-Woodward,
J. L., Mmbaga, M. T., Benson, D. M., and Hong, C. X. 2013. Diversity and
1014
PHYTOPATHOLOGY
mefenoxam sensitivity of Phytophthora spp. associated with the ornamental
horticulture industry in the southeastern United States. Plant Dis. 97:86-92.
Panabières, F., Ali, G. S., Allagui, M. B., Dalio, R. J. D., Gudmestad, N. C.,
Kuhn, M. L., Roy, S. G., Schena, L., and Zampounis, A. 2016. Phytophthora nicotianae diseases worldwide: New knowledge of a long-recognised
pathogen. Phytopathol. Mediterr. 55:20-40.
Pane, A., Martini, P., Chimento, A., Rapetti, S., Savona, S., Grasso, F. M., and
Cacciola, S. O. 2005. Phytophthora species on ornamental plants in Italy.
(Abstr.) J. Plant Pathol. 87:301.
Parke, J. L., and Grünwald, N. J. 2012. A systems approach for management of
pests and pathogens of nursery crops. Plant Dis. 96:1236-1244.
Prigigallo, M. I., Abdelfattah, A., Cacciola, S. O., Faedda, R., Sanzani, S. M.,
Cooke, D. E. L., and Schena, L. 2016. Metabarcoding analysis of Phytophthora diversity using genus specific primers and 454 pyrosequencing.
Phytopathology 106:305-313.
Prigigallo, M. I., Mosca, S., Cacciola, S. O., Cooke, D. E. L., and Schena, L.
2015. Molecular analysis of Phytophthora diversity in nursery-grown ornamental and fruit plants. Plant Pathol. 64:1308-1319.
Prospero, S., Hansen, E. M., Grünwald, N. J., and Winton, L. M. 2007.
Population dynamics of the sudden oak death pathogen Phytophthora
ramorum in Oregon from 2001 to 2004. Mol. Ecol. 16:2958-2973.
Reichard, S. H., and White, P. 2001. Horticulture as a pathway of invasive
plant introductions in the United States. Bioscience 51:103-113.
Robideau, G. P., Arthur, W. A., De Cock, M., Coffey, M. D., Voglmayr, H.,
Brouwer, H., Bala, K., Chitty, D. W., Désaulniers, N., Eggertson, Q. A.,
Gachon, C. M. M., Hu, C. H., Kupper, F. C., Rintoul, T. L., Sarhan, E.,
Verstappen, E. C. P., Zhang, Y., Bonants, P. J. M., Ristaino, J. B., and
Lévesque, A. 2011. DNA barcoding of oomycetes with cytochrome c oxidase
subunit I and internal transcribed spacer. Mol. Ecol. Resour. 11:1002-1011.
Ronquist, F., and Huelsenbeck, J. P. 2003. MrBayes 3: Bayesian phylogenetic
inference under mixed models. Bioinformatics 19:1572-1574.
Salipante, S. J., and Hall, B. G. 2011. Inadequacies of Minimum Spanning
Trees in Molecular Epidemiology. J. Clin. Microbiol. 49:3568-3575.
Schena, L., Cardle, L., and Cooke, D. E. L. 2008. Use of genome sequence
data in the design and testing of SSR markers for Phytophthora species.
BMC Genomics 9:620.
Schoebel, C. N., Jung, E., and Prospero, S. 2013. Development of new polymorphic microsatellite markers for three closely related plant-pathogenic
Phytophthora species using 454-pyrosequencing and their potential applications. Phytopathology 103:1020-1027.
Schoebel, C. N., Stewart, J., Grünwald, N. J., Rigling, D., and Prospero, S.
2014. Population history and pathways of spread of the plant pathogen
Phytophthora plurivora. PLoS One 9:e85368.
Shinde, D., Lai, Y., Sun, F., and Arnheim, N. 2003. Taq DNA polymerase
slippage mutation rates measured by PCR and quasi-likelihood analysis:
(CA/GT)n and (A/T)n microsatellites. Nucleic Acids Res. 31:974-980.
Stewart, S., Abeysekara, N., and Robertson, A. E. 2014. Pathotype and genetic
shifts in a population of Phytophthora sojae under soybean cultivar rotation.
Plant Dis. 98:614-624.
Stoddart, J. A., and Taylor, J. F. 1988. Genotypic diversity: Estimation and
prediction in samples. Genetics 118:705-711.
Sullivan, M. J., Melton, T. A., and Shew, H. D. 2005. Managing the race
structure of Phytophthora parasitica var. nicotianae with variety rotation.
Plant Dis. 89:1285-1294.
Sullivan, M. J., Parks, E. J., Cubeta, M. A., Gallup, C. A., Melton, T. A.,
Moyer, J. W., and Shew, H. D. 2010. An assessment of the genetic diversity
in a field population of Phytophthora nicotianae with a changing race
structure. Plant Dis. 94:455-460.
Szigethy, A., Nagy, Z. Á., Vettraino, A. M., Józsa, A., Cacciola, S. O., Faedda,
R., and Bakonyi, J. 2013. First report of Phytophthora × pelgrandis causing
root rot and lower stem necrosis of common box, lavender and Port-Orfordcedar in Hungary. Plant Dis. 97:152.
Taylor, R. J., Pasche, J. S., Shew, H. D., Lannon, K. R., and Gudmestad, N. C.
2012. Tuber rot of potato caused by Phytophthora nicotianae: Isolate aggressiveness and cultivar susceptibility. Plant Dis. 96:693-704.
van der Lee, T., Robold, A., Testa, A., van’t Klooster, J. W., and Govers, F.
2001. Mapping of avirulence genes in Phytophthora infestans with amplified fragment length polymorphism markers selected by bulked segregant
analysis. Genetics 157:949-956.
Vercauteren, A., De Dobbelaere, I., Van Bockstaele, E., Maes, M., and Heungens,
K. 2010. Genotypic and phenotypic characterization of the European A2 isolates of Phytophthora ramorum. Eur. J. Plant Pathol. 129:621-635.
Zhang, X. G., Sun, W. X., Guo, L., Yu, J. F., and Chang, C. J. 2003. Genetic
and pathogenic variation among tobacco black shank strains of Phytophthora parasitica var. nicotianae from the main tobacco growing in China. J.
Phytopathol. 151:259-266.
Zhang, X. G., Zheng, G. S., Han, H. Y., Han, W., Shi, C. K., and Chang, C. J.
2001. RAPD-PCR for diagnosis of Phytophthora parasitica var. nicotianae
isolates which cause black shank on tobacco. J. Phytopathol. 149:569-574.