Contrasting definitive hosts as determinants of the ...ranges of European freshwater trematode fauna. The authors did not ﬁnd differences in range sizes among trematode species using

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

(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


GENETIC STRUCTURE OF DIGENEANS IN HOST FISHES 1061

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).


1062 Z. L �OPEZ ET AL.

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.



http://www.macrogen.com

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



http://www.cibiv.at/~greg/haploviewer

http://www.cibiv.at/~greg/haploviewer

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.



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.



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


(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


(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


(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


(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



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.



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.



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.



http://dx.doi.org/10.5061/dryad.4ft57








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