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Contrasting definitive hosts as determinants of thegenetic structure in a parasite with complex life cyclealong the south-eastern Pacific
Z. L �OPEZ,*† L. C �ARDENAS,‡ F. RUNIL‡ and M. T. GONZ �ALEZ*
*Instituto de Ciencias Naturales “Alexander Von Humboldt”, Facultad de Ciencias del Mar y Recursos Biol�ogicos, Universidad
de Antofagasta, Av. Angamos 601, P.O. Box 170, Antofagasta, Chile, †Programa Mag�ıster en Ecolog�ıa de Sistemas Acu�aticos,
Universidad de Antofagasta, Antofagasta, Chile, ‡Instituto de Ciencias Ambientales & Evolutivas, Facultad de Ciencias,
Universidad Austral de Chile, Independencia 641, P.O. Box 567, Valdivia, Chile
Abstract
The spatial genetic structure (and gene flow) of parasites with complex life cycles, such
as digeneans, has been attributed mainly to the dispersion ability of the most mobile
host, which most often corresponds to the definitive host (DH). In this study, we com-
pared the genetic structure and diversity of adult Neolebouria georgenascimentoi in two
fish species (DHs) that are extensively distributed along the south-eastern Pacific
(SEP). The analysis was based on the cytochrome oxidase subunit I gene sequences of
parasites collected between 23°S and 45°S. In total, 202 sequences of N. georgenasci-mentoi in Pinguipes chilensis isolated from nine sites and 136 sequences of Prolatilusjugularis from five sites were analysed. Our results showed that N. georgenascimentoiis a species complex that includes three different parasite species; however, in this
study, only lineage 1 and 2 found in P. chilensis and P. jugularis, respectively, were
studied because they are widely distributed along the coastline. Lineage 1 parasites
had two common haplotypes with wide distribution and unique haplotypes in north-
ern sites. Lineage 2 had only one common haplotype with wide distribution and a
large number of unique haplotypes with greater genetic diversity. Both lineages have
experienced recent population expansion. Only lineage 1 exhibited a genetic structure
that was mainly associated with a biogeographical break at approximately 30°S along
the SEP. Our finding suggests that host access to different prey (=intermediate hosts)
could affect the genetic structure of the parasite complex discovered here. Conse-
quently, difference between these patterns suggests that factors other than DH dis-
persal are involved in the genetic structure of autogenic parasites.
Keywords: digeneans, genetic diversity, parasites, phylogeography, population genetic struc-
ture, south-eastern Pacific
Received 28 April 2014; revision received 8 January 2015; accepted 14 January 2015
Introduction
The major factors affecting the genetic structure among
populations of free-living organisms as well as parasites
are gene flow, life history and, potentially, local adapta-
tion within populations (Criscione 2008; Dionne et al.
2008; Blasco-Costa & Poulin 2013). However, parasites
that possess complex life cycles (using one or more
intermediate hosts), such as trematodes, depend mostly
on the potential of the hosts to disperse due to the
small size and limited intrinsic mobility of the infective
stages of the parasites themselves (Blouin et al. 1995;
Criscione & Blouin 2004; Nieberding et al. 2008; Blasco-
Costa et al. 2012). The population structures of parasites
with complex life cycles are commonly determined by
the dispersion ability of the most mobile host, which
most likely corresponds to the definitive host (DH)Correspondence: Zambra L�opez, Fax: +56-55-2637631/804;
E-mail: [email protected]
© 2015 John Wiley & Sons Ltd
Molecular Ecology (2015) 24, 1060–1073 doi: 10.1111/mec.13080
Page 2
(Criscione & Blouin 2004; Criscione 2008; Keeney et al.
2009; Louhi et al. 2010; Blasco-Costa et al. 2012; Blasco-
Costa & Poulin 2013). The intermediate hosts of trema-
todes are generally invertebrates that possess limited
dispersal abilities (Thieltges et al. 2011; Keeney et al.
2009). In contrast, the DHs are often vertebrates, which
possess greater geographical dispersal capabilities
(Thieltges et al. 2011; Keeney et al. 2009). In addition,
some authors have proposed that host specificity might
affect parasite diversification (Nadler 1995; Criscione
et al. 2005) because gene flow might be facilitated or con-
strained by the number of host species that a parasite
can use (Nadler 1995; Blasco-Costa & Poulin 2013; Falk
& Perkins 2013). Based on the cytochrome oxidase sub-
unit I gene (COI), Johnson et al. (2002) concluded that
the lice species Physconelloides spp. and Columbicola spp.
exhibited genetic structures that were in concordance
with their host specificity. Physconelloides spp. exhibited
high host specificity and greater genetic differentiation
among localities than Columbicola spp., which is a more
generalist parasite (Johnson et al. 2002). Similarly, Falk &
Perkins (2013) (using 18S and COI) suggested that the
differences in population structure between two Nema-
toda species (Spauligodon anolis and Parapharyngodon cub-
ensis) are associated with a greater number of hosts,
providing more opportunities for dispersal.
Previous studies analysing population structures in
trematode parasites were performed mainly on small
spatial scales (5–400 km) in both marine and freshwa-
ter systems (Keeney et al. 2008, 2009; Steinauer et al.
2009; Blasco-Costa et al. 2012). Only one study was
conducted on an extensive spatial scale (approximately
700 km, covering four rivers) with autogenic (species
that mature in fishes, sensu Esch et al. 1988) and allo-
genic (species that mature in other vertebrates) trema-
todes; in this study, the allogenic parasite species,
which had a DH with high dispersal ability, did not
exhibit a population genetic structure (Criscione &
Blouin 2004). Additionally, Thieltges et al. (2011) analy-
sed the effect of dispersal capacity of the DH on the
ranges of European freshwater trematode fauna. The
authors did not find differences in range sizes among
trematode species using hosts with high (birds) and
limited dispersal capacity (e.g. fish), suggesting that the
host dispersal capacity for parasite dispersal on small
spatial scales is diminished by other factors acting on a
larger scale (Thieltges et al. 2011). In a recent meta-
analysis, Blasco-Costa & Poulin (2013) concluded that
the type of parasite life cycle (allogenic vs. autogenic)
is a better predictor of population genetic structure in
trematodes than the host geographical range. However,
their survey was focused on only parasites with a sin-
gle DH from freshwater or terrestrial environments,
highlighting the necessity of testing the effects of these
predictors on the dispersal opportunities and genetic
structure patterns of autogenic marine parasites infest-
ing one or several DHs.
The south-eastern Pacific (SEP) coast presents two
major biogeographical breaks (Camus 2001; Thiel et al.
2007). The northern break is at approximately 30°S and
is characterized by an important shift in the diversity,
abundance and recruitment of several intertidal marine
invertebrate species (Broitman et al. 2001; Rivadeneira
et al. 2002). The southern break is located at approxi-
mately 42°S and has been recognized as a major biogeo-
graphical discontinuity (Camus 2001). At this latitude, a
divergence of the main oceanic currents (Humboldt and
Cape Horn current systems) occurs (Valdovinos et al.
2003). Several population genetic studies have recog-
nized genetic barriers among marine species along the
SEP. Most of these studies were focused on the break at
30°S where several free-living invertebrate species
showed a genetic break in this area (Zakas et al. 2009;
S�anchez et al. 2011; Brante et al. 2012; Varela & Haye
2012; Vilches et al. 2012; Haye et al. 2014). One study
showed that an intertidal gastropod has an additional
genetic break at 42°S (S�anchez et al. 2011). However, a
number of free-living invertebrate species have not
shown a genetic break along the SEP (C�ardenas et al.
2009a; Haye et al. 2014). No previous phylogeographical
studies have been performed on marine parasite spe-
cies. However, given that parasites are closely tied to
their host, parasites and their hosts might share similar
phylogeographical patterns (Nieberding et al. 2004; Cri-
scione et al. 2005; Criscione 2008). On the other hand,
the biogeographical patterns of prey are considered key
determinants of the endoparasite community structure
of the host (Gonz�alez et al. 2006). Along the SEP, each
biogeographical area is composed of particular commu-
nities of free-living organisms (Briggs 1974; Broitman
et al. 2001; Rivadeneira et al. 2002), which provide (or
make available) different prey species (intermediate
hosts) to the DH. Then, the geographical variations of
potential prey to the DH could affect the transmission
of parasite species and consequently the phylogeo-
graphical pattern in marine parasite species.
Here, we present the first study to compare the spa-
tial genetic diversity of one adult stage of a digenean
Opecoelidae (Neolebouria georgenascimentoi; Bray 2002)
that parasitizes two marine fish species, Pinguipes chilen-
sis and Prolatilus jugularis (Teleostei: Pinguipedidae),
which are distributed across different biogeographical
areas in the SEP. This digenean species was described
by Bray (2002), who indicated that this species parasitiz-
es the gastrointestinal tract of its two DH species. The
holotype was defined as a parasite of P. chilensis, and
the paratype was defined as a parasite of P. jugularis
(Bray 2002). The life cycle of this trematode species is
© 2015 John Wiley & Sons Ltd
GENETIC STRUCTURE OF DIGENEANS IN HOST FISHES 1061
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almost unknown, but digeneans have complex life
cycles involving at least two invertebrate hosts and hav-
ing short free-living stages (Rohde 2005). The adults of
Opecoelidae live in the digestive tract of marine and
freshwater fishes (Jousson & Bartoli 2000), and some
studies have shown that members of this family use
snails (Prosobranchia) as a first intermediate host,
shrimp (Crustacea) as a second intermediate host and a
fish as a definitive host (Meenakshi et al. 1993; Jousson
& Bartoli 2000; Yoshida & Urabe 2005). Pinguipes chilen-
sis (Valenciennes 1833) is distributed approximately
from Tumbes in Per�u (3°340S) to Magallanes in Chile
(52°090S) (Oyarz�un 2003), whereas Prolatilus jugularis
(Valenciennes 1833) is distributed from Huacho (Per�u,
11°060S) to Chilo�e (Chile, 43�300S) (Chirichigno 1998),
with sporadic records in Puerto Ays�en (45°240S)(Oyarz�un 2003). Pinguipes chilensis preferably inhabits
the nearshore rocky subtidal habitat associated with
Macrocystis pyrifera and Lessonia trabeculata kelps in the
northern Chile (Ortiz 2008). However, other authors
described this species inhabits associated with bare rock
covered with noncalcareous algae and sand-intermedi-
ate microhabitats (Fari~na et al. 2005; P�erez-Matus et al.
2007), and it is an active and generalist predator
(Gonz�alez & Oyarz�un 2003; Medina et al. 2004). On the
other hand, P. jugularis preferably inhabits the near-
shore rocky and sandy subtidal habitat (Angel & Ojeda
2001; Cort�es et al. 2012), and it is a second- or third-
order consumer in the food web of coastal environ-
ments (Cort�es et al. 2012). Although no information
about the potential adult mobility is available, the
degree of home fidelity of both fish species and data
from other species of the same family suggests limited
adult mobility and high home fidelity (e.g. Cole et al.
2000; Venerus et al. 2013).
Thus, the P. chilensis–P. jugularis–N. georgenascimentoi
system is an excellent model of a host–parasite system
to evaluate the effect of the geographical range of the
DHs on the spatial pattern of the genetic diversity in
marine autogenic parasites. We expect that the parasite
genetic diversity pattern of each DH reflects the geo-
graphical barriers to gene flow as described above for
some free-living organisms along the SEP. However, if
the host ecological differences that allow the host access
to different prey (=intermediate hosts) have an effect on
genetic structure, we expect to find genetic differentia-
tion between parasites from both DHs.
Materials and methods
Study area, fish sampling and parasite collection
Samples were obtained between 23°030S and 70°300Wand 44°440S-72°410W (Fig. 1), along 2300 km of marine
coastline. Between November 2011 and June 2013, sam-
ples of Pinguipes chilensis and Prolatilus jugularis were
obtained from local fishermen using autonomous (scuba)
or apnoea diving, and samples were immediately frozen
at -20°C. Fishes and their parasites were collected from 9
sites (Fig. 1 and Table 1). The fish were subsequently
thawed and dissected, and the parasites were recovered
according to a standardized protocol. We recovered all
specimens of N. georgenascimentoi, but retained an aver-
age of three parasites per fish for analysis, except in one
host from site 2, from which nine parasite specimens
Fig. 1 Localities sampled along the south-eastern Pacific. The
main biogeographical breaks are shown (30�S and 42�S).
© 2015 John Wiley & Sons Ltd
1062 Z. L �OPEZ ET AL.
Page 4
were used. The sampled parasites were stored in 95%
ethanol for subsequent DNA extraction.
The prevalence (number of fish infested with one or
more individuals of a determined parasite species
divided by the number of examined fish, expressed as
percentage) and mean intensity (mean number of a par-
ticular parasite species per fish, considering only
infested fish) were calculated (Bush et al. 1997).
DNA extraction, amplification, sequencing andalignment
The DNA of each individual was isolated following a
modified protocol based on Miller et al. (1988) involving
treatment with sodium dodecyl sulphate, digestion with
Proteinase K, NaCl protein precipitation and subsequent
ethanol precipitation of the DNA.
The V4 region of the SSU rRNA (V4 region) was ampli-
fied using the primers SB3a (50-GGAGGGCAAG
TCTGGTGC-30) and A27a (50-CCATACAAATGCCCCCG
TCTG-30) as described by Hall et al. (1999). The COI gene
was amplified using JB3 (50-TTTTTTGGGCATCCTG
AGGTTTAT-30) (Bowles et al. 1993) as the forward primer
and trem.cox1.rrnl (50-AATCATGATGCAAAAGGTA-30) ofKr�alov�a-Hromadov�a et al. (2001) as the reverse primer. All
PCRs were performed in a final volume of 35 lL containing
1X PCR buffer, 3 mM MgCl2, 0.2 mM of each dNTP, 0.4 pM
of each primer, 0.6X BSA, 3.5 lL of DNA concentrate, 0.025
units of GoTaq� DNA polymerase (Promega) and sufficient
H2O to reach the final 35 lL volume. For the V4 region, the
thermocycling programme included an initial denaturation
step (94 °C for 5 min), 35 cycles of amplification (94 °C for
30 s, 45 °C for 30 s and 72 °C for 3 min) and a final exten-
sion step (72 °C for 10 min) (Hall et al. 1999). The COI gene
was amplified using the following thermocycling profile: an
initial denaturation step (95 °C for 2 min), 40 cycles of
amplification (95 °C for 30 s, 48 °C for 40 s and 72 °C for
1 min) and a final extension step (72 °C for 10 min) (Leung
et al. 2009).
The PCR products were purified using E.Z.N.A. �
Cycle Pure PCR Purification Kit (Omega Bio-tek). The
purified PCR products were sequenced at Macrogen
Inc. Company, South Korea (www.macrogen.com)
using an ABI Prism 3730xl automated sequencer. Com-
plementary sequences were assembled and edited using
PROSEQ v2.9 (Filatov 2002). The fragments obtained were
aligned using the CLUSTAL 2 software package (Larkin
et al. 2007).
Distribution of Neolebouria georgenascimentoitaxonomic units
The V4 region was chosen due to the availability of
primers that universally amplify trematode DNA (Hall
Table 1 Population genetics summary statistics for both lineages (1 and 2) of Neolebouria georgenascimentoi from Pinguipes chilensis
and Prolatilus jugularis at each site and total
Site Coordinates (S–W) P (%) MI F N Nhap S He p Tajima’s D Fu’s FS
N. georgenascimentoi lineage 1
1a 23°030–70°300 60 3.6 6 8 6 10 0.929 (0.08) 0.004 (0.002) �1.51 �1.88
1b 23°210–70°360 75 2.7 8 12 8 13 0.849 (0.10) 0.004 (0.003) �1.33 �2.62
1c 23°290–70°310 60 3.8 8 13 10 17 0.923 (0.07) 0.005 (0.003) �1.44 �4.29*
2 29°570–71°200 81 3.6 18 30 22 30 0.945 (0.03) 0.033 (0.020) �2.34** �21.68**
3 36°430–73°060 54.4 6.7 17 32 20 26 0.929 (0.03) 0.026 (0.017) �2.35* �18.81**
4 39°480–73°140 34.5 2.5 14 24 15 16 0.920 (0.04) 0.024 (0.015) �1.94* �12.32**
5 41°300–72°480 88.9 31.5 8 16 6 7 0.733 (0.10) 0.020 (0.015) �0.61 �1.06
6 42°380–73°450 60 4.2 8 11 5 5 0.618 (0.16) 0.011 (0.009) �1.79* �2.31*
7 44°440–72°410 27.9 2.3 8 11 5 7 0.709 (0.14) 0.019 (0.014) �1.46 �1.03
Total 51.7 5.5 95 157 81 85 0.918 (0.02) 0.032 (0.019) �2.6** �26.72**
N. georgenascimentoi lineage 2
1b 23°210–70°360 21.7 4.6 4 5 5 19 1.000 (0.13) 0.098 (0.063) �1.07 �0.68
2 29°570–71°200 90.5 4.1 26 37 30 47 0.982 (0.01) 0.054 (0.030) �2.17* �25.64**
3 36°430–73°060 71.4 4 16 30 25 39 0.966 (0.03) 0.052 (0.029) �2.07* �22.27**
4 39°480–73°140 68.8 5.1 15 36 31 47 0.983 (0.02) 0.059 (0.033) �2.06* �25.57**
Total 68.8 4.3 61 108 83 88 0.977 (0.01) 0.058 (0.031) �2.34** �25.56**
P (%), prevalence; MI, mean intensity; F, number of fish used for the sequences obtained; N, number of sequences analysed; Nhap,
number of different haplotypes; S, number of polymorphic sites; He, haplotype diversity (standard deviation); p, nucleotide diversity
(standard deviation); Tajima’s D test (Tajima 1989) and Fu’s FS test (Fu 1997).
*Significant P-values (0.05).
**P-values<0.001.
© 2015 John Wiley & Sons Ltd
GENETIC STRUCTURE OF DIGENEANS IN HOST FISHES 1063
Page 5
et al. 1999; Valdivia et al. 2010; Mu~noz et al. 2013); the
V4 region is commonly used to study trematode phy-
logeny and to identify operational taxonomic units and
species (Hall et al. 1999; Valdivia et al. 2010). Addition-
ally, the GenBank database contains many V4 region
sequences for several Digenea species, allowing further
comparisons and analyses. The COI gene has also been
used to determine taxonomic units and differentiation
at the species level, but this gene is always compared
with other, more conserved genes (Criscione & Blouin
2004; Miura et al. 2005).
To determine the distribution of the taxonomic units
in N. georgenascimentoi, data sets regarding the V4
region were analysed using maximum likelihood (ML),
neighbour-joining (NJ) and Bayesian inference (BI)
methods. ML and NJ analyses were performed using
the software package Mega v6 (Tamura et al. 2013), and
BI was performed using the software package Mr.
Bayes (Huelsenbeck & Ronquist 2001). To determine the
nodal support in ML and NJ, a 1000 bootstrap analysis
was used. For the ML and NJ analyses, the TN93 evolu-
tion model was used, and for the BI analyses, the
HKY+G model was used. Both models were chosen
according to the Akaike information criterion (AIC) as
implemented in Modeltest 3.7 (Posada & Crandall
1998). To estimate BI inference, posterior probabilities
were estimated over 50 000 000 generations via one run
of four simultaneous Markov chain Monte Carlo chains
with every 1000th tree saved. The first 5 000 000 genera-
tions (10% burn-in) were discarded as suggested by
Felsenstein (1985). Peracreadium idoneum (GenBank
Accession no AJ287558.1) was used as an outgroup spe-
cies and, Macvicaria macassarensis (AJ287533.1) was used
as a sister group (Olson et al. 2003).
The COI gene was used to aid in determining the
number of species using the approximation of delinea-
tion of species boundaries in the automatic barcode gap
discovery method (ABGD) (Puillandre et al. 2012).
These methods deliver species circumscriptions based
on patterns of pairwise genetic distances (ABGD), pro-
viding estimates of a maximum limit for intraspecific
genetic divergence and using this limit to group
sequences belonging to the same species (with lesser
divergences) from sequences belonging to different spe-
cies (with greater divergences) (Puillandre et al. 2012).
Genetic structure analysis using the COI gene
The number of unique haplotypes (Nhap), the number
of polymorphic sites (S), haplotype diversity (He) and
nucleotide diversity (p) were calculated for both lin-
eages (from each host species) at each sampling site
and over all sites (all individuals treated as one sample)
using ARLEQUIN v3.1 (Excoffier et al. 2005). Tajima’s D
(Tajima 1989) and Fu’s FS (Fu 1997) statistics were cal-
culated to assess the consistency of the observed genetic
variation based on a neutral model of evolution for
each sampling site and over all sites combined for each
host with 1000 permutations using ARLEQUIN v3.1. Signif-
icant deviations from neutrality can be a consequence
of selection (as well as population expansions or bottle-
necks) or demographic fluctuations. Fu’s FS statistic is
caused by selection and population expansions and is
highly sensitive to demographic expansions, which pro-
duce large negative values (Fu 1997).
Genetic population structures were examined for each
lineage (host) using an hierarchical analysis of molecu-
lar variance (AMOVA) as implemented in ARLEQUIN v3.1.
Genetic structure (ΦST estimate) was examined among
all sites. Genetic structure (ΦCT estimate) was also
examined among three regions separated by two bio-
geographical breaks (Camus 2001); these regions were
the ‘Peruvian Province (PP)’ (sites 1a, 1b and 1c), the
‘Intermediate Area (IA)’ (sites 2, 3 and 4) and the ‘Mag-
ellanic Province (MG)’ (sites 5, 6 and 7). Genetic struc-
ture (ΦSC estimate) was examined among sites within
these regions. The AIC of JMODELTEST version 3.7 (Posada
& Crandall 1998) was used to select the most appropri-
ate model of sequence evolution according to each DH
species. Based on this method, TPM2uf+I was the most
appropriate model for sequences from the host P. chil-
ensis, and TIM2 + I+G was the most appropriate model
for sequences from the host P. jugularis. However,
because these models are not implemented in ARLEQUIN
v3.1, the Tamura & Nei (1993) model with gamma dis-
tribution (a = 0.115 for P. chilensis and a = 0.016 for
P. jugularis) was used. The significance of genetic struc-
ture was determined based on 10 000 permutations
(Excoffier et al. 1992). Additionally, patterns of genetic
divergence were investigated using the spatial AMOVA
procedure and SAMOVA v.1.0 (Dupanloup et al. 2002) to
define the number of groups along the SEP populations
that are geographically and genetically homogeneous
and maximally differentiated from each population.
This method is based on a simulated annealing proce-
dure that aims to maximize the proportion of total
genetic variance due to differences among groups of
populations. Finally, the fixation index (ΦST) was calcu-
lated for pairwise comparisons between all collection
sites.
A haplotype network was constructed using HAPLO-
VIEWER (available at http://www.cibiv.at/~greg/haplo-
viewer) and a neighbour-joining tree reconstructed with
MEGA v6 for trematodes in both DHs. To distinguish his-
torical growth events and population declines, a mis-
match distribution analysis was performed at each
sampling site according to the studied DH and over
all sites with 1000 permutations; the analysis was
© 2015 John Wiley & Sons Ltd
1064 Z. L �OPEZ ET AL.
Page 6
performed using ARLEQUIN v3.1. To estimate the time
elapsed since the expansion, we used s = 2lt, where
t = time (in generations) and l = mutation rate/genera-
tion. The s parameter is an estimate of the time elapsed
after expansion in mutational units. If the divergence
rate per nucleotide and year (s = 2l, where l is the sub-
stitution rate per lineage) and the number of nucleo-
tides of the fragment analysed (1) are known, it is
possible to calculate the time when the expansion
occurred using the expression s = llt, as modified from
Harpending et al. (1993) and obtained by C�ardenas et al.
(2009a).
Isolation by distance was tested using the relationship
between genetic (FST⁄1-FST) (Rousset 1997) and geo-
graphical distance along SEP among all sites for each
lineage using a Mantel test (Mantel 1967) as imple-
mented in the Isolation by DISTANCE WEB SERVICE version
3.15 (Bohonak 2002; Jensen et al. 2005).
Results
DNA sequencing and identification of taxonomic unitsof Neolebouria georgenascimentoi
A total of 68 sequences (forward and reverse) of the V4
region from 34 specimens of N. georgenascimentoi were
examined: 16 individuals were obtained from P. chilen-
sis and 18 were obtained from P. jugularis (the
sequences were submitted to GenBank under access
numbers KJ527643–KJ527676, Table S1, Supporting in-
fromation). The total length of the analysed V4 region
sequences was 392 bp. The analysis to determine the
distribution of taxonomic units and/or number of spe-
cies revealed that N. georgenascimentoi could be classi-
fied into three lineages (Fig. 2). The first lineage
included specimens from P. chilensis found at sites 1a to
7 (lineage 1). The second lineage incorporates parasites
from P. jugularis found at sites 1b, 2, 3 and 4 (lineage
2). Finally, a third lineage was identified that included
parasites collected from P. jugularis at sites 1b, 2 and 5
(lineage 3) (Fig. 2). The genetic distance between lin-
eages 1 and 2 was 0.3%, the distance between lineages
1 and 3 was 0.5%, and the distance between lineages 2
and 3 was 0.8%. Within each lineage, no mutations
were detected; therefore, the genetic distance was 0%.
Similar tree topologies were obtained using the three
different methods (Fig. 2). Lineage 1 was closely related
to lineage 2 with a node support of 66% to ML and
61% to NJ and a posterior probability of 0.95 to BI
(Fig. 2).
DNA sequences comprising 739 bp of the COI gene
were analysed for 338 individuals of N. georgenascimen-
toi collected from P. chilensis (202 parasites) and P. jugu-
laris (136 parasites). Sequences were deposited at the
NCBI database with access numbers KJ527677 to
KJ528014 (Table S1, Supporting infromation). The
ABGD analysis showed a tri-modal pairwise genetic
distance (K2P) distribution with a clear and wide bar-
code gap located between 3 and 8% of genetic distance
and a second gap located between 11 and 14% of
genetic distance (Fig. 3a). Furthermore, the method
used detected three stable candidate species with esti-
mated prior maximum divergences of intraspecific
diversity (P) as large as 6% (Fig. 3b) (one-tail 95% confi-
dence interval). Notably, this result was consistent with
the three N. georgenascimentoi lineages found using the
phylogenetic analysis (Fig. 2).
Genetic structure analysis
In the population analysis, we incorporated sample lin-
eages 1 and 2 as shown in Fig. 2 because they are
widely distributed along the sampled hosts and coast-
line. Lineage 3 was restricted to a few sites (1b, 2 and
Fig. 2 Phylogenetic tree of 34 specimens of Neolebouria george-
nascimentoi obtained from the definitive hosts Pinguipes chilensis
(Pc) and Prolatilus jugularis (Pj) from sites 1a to 7 (s1a—s7)
based on maximum-likelihood analyses of the V4 region. Num-
bers along the branches indicate the percentages of support
values resulting from the different analyses in the order ML/
NJ/BI. Values lower than 50% are indicated by dashes or are
not indicated. The model for the ML and NJ trees (TN93) had
an -lnL score of 623.5784 and an Akaike information criterion
(AIC) of 1397.1567.
© 2015 John Wiley & Sons Ltd
GENETIC STRUCTURE OF DIGENEANS IN HOST FISHES 1065
Page 7
5); at site 1b and 5, individuals of lineage 3 were abun-
dant, but at site 2, only one individual was present.
Therefore, we decided to exclude this lineage from the
following analysis.
To analyse the genetic diversity and structure at the
component population level (i.e. all of the individuals
of a specified life-history phase at a particular place
and time, according Bush et al. 1997), we excluded
those sequences that were similar within an individual
fish from the analysis. Thus, 157 individuals from line-
age 1 and 108 individuals from lineage 2 were incorpo-
rated. Lineage 1 exhibited 85 polymorphic sites
segregating 81 different haplotypes, whereas lineage 2
contained 88 polymorphic sites segregating 83 haplo-
types (Table 1). Neutrality tests yielded nonsignificant
results for sites 1a, 1b, 1c, 5 and 7 in lineage 1 and for
site 1b in lineage 2. Neutrality tests were significant
for the entire data sets in lineages 1 and 2 (Table 1),
suggesting that selection, population expansion or bot-
tlenecks might be affecting the current genetic diversity.
Hierarchical AMOVA analysis revealed significant
genetic differentiation among lineage 1 (ΦCT = 0.17;
P-values � 0.05), and 17.08% of the genetic variance
was explained by the ‘PP’, ‘IA’ and ‘MP’ groupings
(Table 2). In contrast, hierarchical AMOVA analysis did
not reveal significant genetic differentiation among line-
age 2 (ΦCT = 0.05; P-values > 0.2) (see Table 2).
The data from lineage 1 are best explained using SAM-
OVA by assuming three groups of populations (/CT =0.256, P-values = 0.0068) (Table 2). For lineage 2, SAMOVA
analysis did not reveal an optimized aggregation. The
pairwise ΦST of lineage 1 exhibited significant differ-
ences among 25 out of 36 comparisons (P-values <0.05), and the sequences obtained from sites 1a, 1b and
1c were significantly different from the sequences
obtained from sites 2 to 7 (Table S2, Supporting infor-
mation). The pairwise ΦST for lineage 2 exhibited signif-
icant differences in 2 of 6 comparisons (P-values < 0.05)
(Table S2, Supporting information).
The haplotype network for lineage 1 (Fig. 4a)
revealed two common haplotypes, occurring at frequen-
cies of 27% (H23) and 11% (H25) along sites 2 to 7. The
haplotype H23 is located in the centre of the network,
suggesting that it could be the ancestral haplotype.
Additionally, one common haplotype (H2) was con-
nected by one mutation at the central haplotype (H23)
at sites 1a, 1b and 1c (Fig. 4a). The following five addi-
tional haplotypes were shared between two sites: H5
(sites 1b and 2), H13 (sites 1a and 1c), H31 (sites 2 and
5), H45 (sites 3 and 4) and H74 (sites 5 and 6). All hapl-
otypes were connected by a maximum of eight muta-
tions (usually fewer). The haplotype network for
lineage 2 exhibited only one common haplotype (H5)
with a frequency of 15% (Fig. 4b) and a high number of
unique haplotypes. In fact, the genetic diversity was
highest in lineage 2 (P-values < 0.01). The following five
additional shared haplotypes were detected between
two sites: H6 (sites 2 and 4), H43 (sites 3 and 4), H48
(sites 3 and 4), H55 (sites 3 and 4) and H58 (sites 3 and
4). All haplotypes were connected by seven or fewer
mutations. The haplotype network of each lineage
exhibited a star-like structure with one central haplo-
type, suggesting that each lineage of trematode para-
sites had most likely undergone a recent population
expansion (Fig. 4). The mismatch distribution analysis
(Fig. 5) exhibited a unimodal distribution of pairwise
differences for lineage 1 and lineage 2, which is consis-
tent with a sudden population expansion model
(Fig. 5a). Based on a mutation rate of 2.5 e�8 per site
(Attwood et al. 2008) and assuming a generation time of
1 year, the onset of the most recent demographic expan-
sion in lineages 1 and 2 was estimated. The estimate of
(a)
(b)
Fig. 3 Distribution of pairwise distances for the COI gene and
automatic barcode gap discovery (ABGD). a) Frequency distri-
bution of K2P distances between haplotype pairs for the COI
gene. b) ABGD results showing the number of lineages
obtained for a range of prior maximum divergences of intra-
specific diversity. Dashed lines (a and b) indicate the upper
bound of estimated maximum limits for intraspecific genetic
divergences that resulted in two stable candidate species.
© 2015 John Wiley & Sons Ltd
1066 Z. L �OPEZ ET AL.
Page 8
s for the entire data set corresponded to an onset of
expansion of 127 000 (95% confidence interval = 98 000–150 000) years before present (bp) for lineage 1, whereas
for lineage 2, the expansion was calculated at
235 000 bp (95% confidence interval = 140 000–362 000).
Mantel tests revealed a significant correlation
between genetic and geographical distances for lineage
1 (r = 0.7742; P-values = 0.003) but not for lineage 2
(r = 0.2997; P-values = 0.292) (Fig. 6).
Discussion
Here, we describe the population genetic structure of
the digenean Neolebouria Neolebouria georgenascimentoi
that parasitizes two fish species distributed across the
SEP. Our results showed the occurrence of a species
complex with particular genetic lineages associated with
each DH (here, we reported the results for the two
main lineages: lineages 1 and 2). Lineage 1 associated
with Pinguipes chilensis and, showed a genetic break at
approximately 30�S, coincident with those breaks
described for free-living organisms along the SEP. In
contrast, lineage 2 that parasitized only Prolatilus jugu-
laris did not show evidence of genetic breaks along a
similar geographical area. Our finding suggests that a
host’s access to different prey (=intermediate hosts)
could affect the genetic structure of the parasite com-
plex discovered here.
Records of cryptic species are becoming more com-
mon as more studies utilize molecular markers (Crisci-
one & Blouin 2004; Criscione et al. 2005, 2011; Miura
et al. 2005; Falk & Perkins 2013). We demonstrated that
N. georgenascimentoi corresponds to a species complex
that includes at least three Neolebouria spp. (see Figs 2
and 3). Bray (2002) described N. georgenascimentoi para-
sitization of Prolatilus jugularis and Pinguipes chilensis;
the author reported little morphological variation in
this parasite between both hosts apart from finding a
Table 2 Result of AMOVA and SAMOVA for N. georgenascimentoi lineage 1 and lineage 2
Structure tested % Variation among group F statistic P-values
Neolebouria georgenascimentoi lineage 1
AMOVA
3 (Site 1a, Site 1b, Site 1c)
(Site 2, Site 3, Site 4) (Site 5, Site 6, Site 7)
17.08 ΦSC = 0.01554 0.10020
ΦST = 0.18362 <0.00001ΦCT = 0.17073 0.00426
3 (Site 1a, Site 1b, Site 1c)
(Site 2, Site 3, Site 4, Site 6) (Site 5, Site 7)
18.49 ΦSC = 0.01487 0.09030
ΦST = 0.19703 <0.00001ΦCT = 0.18491 0.00158
SAMOVA
2 (Site 1a, Site 1b, Site 1c)
(Site 2, Site 3, Site 4, Site 5, Site 6, Site 7)
25.56 ΦSC = 0.02436 0.04106
ΦST = 0.27376 <0.00001ΦCT = 0.25563 0.01466
3 (Site 1a) (Site 1b, Site 1c)
(Site 2, Site 3, Site 4, Site 5, Site 6, Site 7)
25.59 ΦSC = 0.01862 <0.00001
ΦST = 0.26977 <0.00001
ΦCT = 0.25591 0.00684
4 (Site 1a) (Site 1b, Site 1c)
(Site 2, Site 3, Site 4, Site 6, Site 7) (Site 5)
21.92 ΦSC = 0.0013 0.02737
ΦST = 0.22020 <0.00001ΦCT = 0.21919 0.00098
5 (Site 1a) (Site 1b, Site 1c)
(Site 2, Site 3, Site 4, Site 6) (Site 5) (Site 7)
20.03 ΦSC = -0.00559 <0.00001ΦST = 0.19582 <0.00001ΦCT = 0.20029 0.00196
Neolebouria georgenascimentoi lineage 2
AMOVA
2 (Site 1b) (Site 2, Site 3, Site 4) 5.52 ΦSC = 0.00293 0.21505
ΦST = 0.05799 0.08407
ΦCT = 0.05522 0.24927
SAMOVA
2 (Site 1b) (Site 2, Site 3, Site 4) 5.57 ΦSC = 0.0029 0.21114
ΦST = 0.05843 0.07722
ΦCT = 0.05570 0.24242
3 (Site 1b) (Site 2) (Site 3, Site 4) 3.40 ΦSC = -0.01520 0.99707
ΦST = 0.01935 0.05670
ΦCT = 0.03404 0.17595
© 2015 John Wiley & Sons Ltd
GENETIC STRUCTURE OF DIGENEANS IN HOST FISHES 1067
Page 9
distinctly greater number of ovarian follicles (lobes) in
parasites obtained from P. jugularis. However, parasites
from P. chilensis are longer and show higher fecundity
than those parasites collected from P. jugularis
(Gonz�alez et al. 2013). Currently, N. georgenascimentoi
has been recorded in only these two host species along
the Chilean coast (Mu~noz & Olmos 2008; Gonz�alez &
Oliva 2009), but our data strongly suggest the occur-
rence of cryptic (morphologically similar but genetically
distinct) species. Genetic subdivision among parasites
in different host species could arise through extrinsic or
intrinsic mechanisms (McCoy 2003). Here, the transmis-
sion and dispersal of parasites are important factors to
be considered (Criscione et al. 2005). In trematodes, ces-
todes and nematodes, these two processes occur pas-
sively by ingestion of an intermediate host, indicating
that not all local DH types will necessarily be available
to parasite individuals. If an infected sympatric DH
uses a different ecological niche (such as space and
food), separate parasite propagule pools that infect dif-
ferent intermediate hosts could form, resulting in
genetic isolation. In this case, the physical barrier is the
distance between the hosts, and this result could be
considered allopatric speciation (McCoy 2003).
Few studies have analysed diet in these fish species,
and therefore, studies comparing diets between the
species are not available to date. However, the existing
works reveal that P. chilensis is a generalist species that
preys on several species, such as crustacean, fishes,
annelids, mollusks, echinoderms and others (Moreno &
Flores 2002; Gonz�alez & Oyarz�un 2003; P�erez-Matus
et al. 2012; Cornejo-Acevedo et al. 2014). In the northern
range of Chile (between 21°S and 30°S), the primary
prey is crustaceans, principally Pilumnoides perlatus,
Petrolisthes sp. and Rhynchocinetes typus (P�erez-Matus
et al. 2012). At around 30�S, Moreno & Flores (2002)
described as the primary prey crustaceans specifically
Rhynchocinetes typus and Petrolisthes violaceus, whereas
in the southern range (at approximately 38 �S), the pri-
mary prey is the crustaceans Neomysis sp., followed by
unidentified crustaceans and Synalpheus spinifrons
(Gonz�alez & Oyarz�un 2003), and recently Cornejo-Acev-
edo et al. (2014) showed results from southern range (at
approximately 39�S) indicating that the primary prey
also is crustaceans mainly Homalaspis plana followed by
Taliepus dentatus.
The published evidence shows that P. jugularis preys
on a lower number of species, such as crustaceans,
annelids, platyhelminthes and nemertines; the primary
prey is the crustacean species Pagurus sp., followed by
the platyhelminth Thyttosoceros inca (Moreno & Flores
2002). Both fish species showed a minimum overlap of
(a) (b)
Fig. 4 Median-joining haplotype networks for a) Neolebouria georgenascimentoi lineage 1 from Pinguipes chilensis and b) N. georgenasci-
mentoi lineage 2 from Prolatilus jugularis. Each circle represents a haplotype, and the circled area represents haplotype frequency.
Small blue circle inserts in the branches represent inferred haplotypes that are not observed in the data or median vectors; all connec-
tions represent a single mutational step.
© 2015 John Wiley & Sons Ltd
1068 Z. L �OPEZ ET AL.
Page 10
prey, and they have minimized trophic competition
using different substrata; P chilensis preys on species
inhabiting rocky substrata, whereas P. jugularis preys
on species in sandy substrata (Moreno & Flores 2002).
In addition, with respect to the space utilization, P. chil-
ensis inhabits rocky and sand-intermediate environ-
ments with high home fidelity (Cole et al. 2000; Ortiz
2008; Venerus et al. 2013), whereas P. jugularis inhabits
the nearshore rocky and sandy subtidal habitat (Angel
& Ojeda 2001; Cort�es et al. 2012). However, P. jugularis
is captured as ‘bycatch’ of the demersal fisheries that
use trawl nets (Melo et al. 2007), suggesting that its
home fidelity could be less than P. chilensis, like was
reported for other Pinguipidae, the blue cod Parapercis
colias by D�ıaz-Guisado (2014); therefore, P. jugularis can
be classified as a species with moderate mobility. Con-
sequently, lineage 1 and lineage 2 N. georgenascimentoi
may be transmitted by different prey (=intermediate
hosts).
The population structure of trematodes has been
attributed to the dispersion ability of the most mobile
host, which most likely corresponds to the DH (Crisci-
one & Blouin 2004; Keeney et al. 2009; Blasco-Costa
et al. 2012). In this study, lineage 1 exhibited a genetic
break at approximately 30�S (between sites 1a–c and 2)
and approximately 42 S (sites 5 and 7); this finding was
consistent with the observed phylogeographical breaks
along the SEP for free-living organisms (Tellier et al.
2009; S�anchez et al. 2011; Brante et al. 2012; Haye et al.
2014). Further analysis including more sites might be
necessary to clarify the current influence of biogeo-
graphical barriers on the genetic structure of this trema-
tode species and/or the intermediate or DH.
Additionally, lineage 1 exhibited a clear pattern of isola-
tion by distance (see Fig. 6). This result supports the
existence of an oceanographic barrier across latitudes 23
and 30°S that could influence the genetic structure of
the host species, thus preventing parasite dispersion
among these sites (Criscione & Blouin 2007). Similar
biogeographical and phylogeographical patterns
between DHs and their hosts have been observed for
some parasite–host relationships (Wickstr€om et al. 2003;
Meinila et al. 2004; Criscione & Blouin 2007). Therefore,
the oceanographic barrier that affects the gene flow of
parasite transmission northward to 30�S most likely also
affects the genetic structure of the DH. However, this
hypothesis should be tested by conducting genetic
analyses of this host species.
Unlike lineage 1, lineage 2 did not show any genetics
breaks along the SEP; lineage 2 recorded a higher hap-
lotype and nucleotide diversity than lineage 1, and only
one haplotype (H5) was widely shared (Fig. 4b). This
(a)
(b)
Fig. 6 Isolation by distance analysis. Relationship between
pairwise geographical distance and genetic distance (ΦST/1-ΦST) between sites for a) Neolebouria georgenascimentoi lineage 1
and b) N. georgenascimentoi lineage 2. Darker dots indicate the
relationship between sites 1a, 1b and 1c and the other sites.
(a)
(b)
Fig. 5 Pairwise mismatch distribution analysis of a) N. georgenasci-
mentoi lineage 1 and b)Neolebouria georgenascimentoi lineage 2.
© 2015 John Wiley & Sons Ltd
GENETIC STRUCTURE OF DIGENEANS IN HOST FISHES 1069
Page 11
lack of a genetic break pattern has also been observed
for some free-living organisms that inhabit this region
(C�ardenas et al. 2009a,b; Ib�a~nez et al. 2011). A lack of
genetic structure has also been recorded in endopara-
sites of freshwater organisms such as Cestoda (Ligula
intestinalis), which are present in cyprinid fish (the
intermediate hosts) (�Stefka et al. 2009), and allogenic
trematodes (Nanophyetus salmincola), which are present
in salmonids (the intermediate hosts) (Oncorhynchus
mykiss, O. clarki, O. kisutch and O. tshawytscha) (Crisci-
one & Blouin 2004). The DHs of these species are terres-
trial birds and mammals with high dispersion ability.
Considering that P. jugularis and P. chilensis present
similar geographical ranges (and most likely dispersal
patterns), lineage 2 may parasitize a widespread sec-
ondary intermediate host’s range, thus favouring its
genetic flow and the absence of parasite genetic struc-
ture in its host (Nadler 1995; Johnson et al. 2002; Falk &
Perkins 2013).
Species inhabiting the same biogeographical area can
present different and independent evolutionary histo-
ries (Poulin 2007). In this study, both lineages revealed
a star-like network in which the most common and cen-
tral haplotype, and therefore the most probable ances-
tral haplotype (Avise 2000; Hewitt 2000), is connected
by a few mutation steps to many haplotypes of lower
frequency. However, lineage 2 showed a larger number
of mutation steps in the network. Network and mis-
match distribution are consistent with a demographic
expansion that is associated with the colonization of
new geographical regions (Excoffier 2004) in both lin-
eages. According to coalescence theory (Slatkin & Hud-
son 1991), the present expansion pattern suggests an
expansion of the population from a limited number of
founders. The results of the coalescence-based demo-
graphic analysis are consistent with an expansion
growth model, and calculations reveal the onset of the
expansion of lineage 1 at approximately 120 000 years
(at the beginning of the Taratian Pleistocene) and the
onset of the expansion of lineage 2 at approximately
230 000 years (at the end of the Ionian Pleistocene).
In summary, in this first study of the spatial genetic
diversity patterns of a marine parasite on a large bio-
geographical scale (along the SEP), we found that
N. georgenascimentoi corresponds to a species complex
that includes three species. N. georgenascimentoi lineage
1 and lineage 2 revealed a recent population expansion,
given that they exhibited star-like structures and uni-
modal mismatch distributions. Only lineage 1 exhibited
a genetic structure that was mainly associated with a
biogeographical break at approximately 30°S (Camus
2001), suggesting the existence of several populations
along the SEP. The lack of a genetic structure in lineage
2 suggests that this species comprises a single large
population along the SEP. The difference between these
patterns suggests that factors other than DH dispersal
(e.g. wider range of intermediate hosts) are involved in
the genetic structure of the autogenic parasites.
Acknowledgements
We are grateful to Felipe Docmac to provide some fish samples
for this study. The authors express their thanks to E. Poulin,
the editor and the anonymous referees for their constructive
suggestions, which considerably improved the quality of the
paper. LC acknowledgement to the Millennium Nucleus
Center for the Study of Multiple drivers on Marine Socio-Eco-
logical Systems (MUSELS) by MINECON Project NC120086.
This research was partially supported by projects INNOVA
CORFO 09CNN14-5829, FONDECYT 11090149 and FONDE-
CYT 1130629 granted to MTG.
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Z.L. performed the research and molecular analyses
and wrote an earlier manuscript. L.C. and F.R. assisted
with the analytical tools. M.T.G. contributed to the
research design and assisted in data collection. L.C. and
M.T.G. revised and finalized the manuscript.
Data accessibility
- DNA sequences with V4 region: GenBank Accession
nos KJ527643 - KJ527676.
- DNA sequences with COI: GenBank Accession nos
KJ527677 - KJ528014.
Final DNA sequence assembly uploaded as online
supplemental material, Neolebouria-georgenascimentoi
V4 and Neolebouria-georgenascimentoi COI data input
files FASTA format: Dryad doi:10.5061/dryad.4 ft57
Phylogenetic trees resultant for construction Figure 2:
Neolebouria sp ML-TN93, Neolebouria sp NJ and Neol-
ebouria sp BI assembly uploaded as online supplemen-
tal material Newik format: Dryad doi:10.5061/
dryad.4 ft57. Data available from the Dryad Digital
Repository: http://doi.org/10.5061/dryad.NNNNN.
Supporting information
Additional supporting information may be found in the online ver-
sion of this article.
Table S1. Access numbers of sequences deposited in the NCBI
database, according at the lineage classified of Neolebouria spp.,
host, localities, years, number of fish, number of the individual
and sequence name.
Table S2. Pairwise analysis of molecular variance estimations
(ΦST estimates/ P-value) between sites for lineage 1 in the
lower matrix and lineage 2 in the upper matrix.
© 2015 John Wiley & Sons Ltd
GENETIC STRUCTURE OF DIGENEANS IN HOST FISHES 1073