Co-structure analysis and genetic associations reveal insights into pinworms (Trypanoxyuris) and primates (Alouatta palliata) microevolutionary dynamics

Abstract

Background
In parasitism arm race processes and red queen dynamics between host and parasites reciprocally mold many aspects of their genetics and evolution. We performed a parallel assessment of population genetics and demography of two species of pinworms with different degrees of host specificity ( Trypanoxyuris multilabiatus , species-specific; and T. minutus, genus-specific) and their host, the mantled howler monkey ( Alouatta palliata ), based on mitochondrial DNA sequences and microsatellite loci (these only for the host). Given that pinworms and primates have a close co-evolutionary history, covariation in several genetic aspects of their populations is expected.

Results
Mitochondrial DNA revealed two genetic clusters (West and East) in both pinworm species and howler monkeys, although population structure and genetic differentiation were stronger in the host, while genetic diversity was higher in pinworms than howler populations. Co-divergence tests showed no congruence between host and parasite phylogenies; nonetheless, a significant correlation was found between both pinworms and A. palliata genetic pairwise distances suggesting that the parasites’ gene flow is mediated by the host dispersal. Moreover, the parasite most infective and the host most susceptible haplotypes were also the most frequent, whereas the less divergent haplotypes tended to be either more infective (for pinworms) or more susceptible (for howlers). Finally, a positive correlation was found between pairwise p-distance of host haplotypes and that of their associated pinworm haplotypes.

Conclusion
The genetic configuration of pinworm populations appears to be molded by their own demography and life history traits in conjunction with the biology and evolutionary history of their hosts, including host genetic variation, social interactions, dispersal and biogeography. Similarity in patterns of genetic structure, differentiation and diversity is higher between howler monkeys and T. multilabiatus in comparison with T. minutus , highlighting the role of host-specificity in coevolving processes. Trypanoxyuris minutus exhibits genetic specificity towards the most frequent host haplotype as well as geographic specificity. Results suggest signals of potential local adaptation in pinworms and further support the notion of correlated evolution between pinworms and their primate hosts.

Full text

Solórzano‑Garcíaetal. BMC Ecol Evo (2021) 21:190
https://doi.org/10.1186/s12862‑021‑01924‑4
RESEARCH
Co‑structure analysis andgenetic
associations reveal insights intopinworms
(Trypanoxyuris) andprimates (Alouatta palliata)
microevolutionary dynamics
Brenda Solórzano‑García1,4 , Ella Vázquez‑Domínguez2* , Gerardo Pérez‑Ponce de León3,4 and
Daniel Piñero1
Abstract
Background: In parasitism arm race processes and red queen dynamics between host and parasites reciprocally
mold many aspects of their genetics and evolution. We performed a parallel assessment of population genetics
and demography of two species of pinworms with different degrees of host specificity (Trypanoxyuris multilabiatus,
species‑specific; and T. minutus, genus‑specific) and their host, the mantled howler monkey (Alouatta palliata), based
on mitochondrial DNA sequences and microsatellite loci (these only for the host). Given that pinworms and primates
have a close co‑evolutionary history, covariation in several genetic aspects of their populations is expected.
Results: Mitochondrial DNA revealed two genetic clusters (West and East) in both pinworm species and howler
monkeys, although population structure and genetic differentiation were stronger in the host, while genetic diversity
was higher in pinworms than howler populations. Co‑divergence tests showed no congruence between host and
parasite phylogenies; nonetheless, a significant correlation was found between both pinworms and A. palliata genetic
pairwise distances suggesting that the parasites’ gene flow is mediated by the host dispersal. Moreover, the parasite
most infective and the host most susceptible haplotypes were also the most frequent, whereas the less divergent
haplotypes tended to be either more infective (for pinworms) or more susceptible (for howlers). Finally, a positive cor‑
relation was found between pairwise p‑distance of host haplotypes and that of their associated pinworm haplotypes.
Conclusion: The genetic configuration of pinworm populations appears to be molded by their own demography
and life history traits in conjunction with the biology and evolutionary history of their hosts, including host genetic
variation, social interactions, dispersal and biogeography. Similarity in patterns of genetic structure, differentiation
and diversity is higher between howler monkeys and T. multilabiatus in comparison with T. minutus, highlighting the
role of host‑specificity in coevolving processes. Trypanoxyuris minutus exhibits genetic specificity towards the most
frequent host haplotype as well as geographic specificity. Results suggest signals of potential local adaptation in pin‑
worms and further support the notion of correlated evolution between pinworms and their primate hosts.
Keywords: Coevolution, Ecological interactions, Gene flow, Host–parasite associations, Host‑specificity, Parasitism
© The Author(s) 2021. Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which
permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the
original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or
other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line
to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory
regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this
licence, visit http:// creat iveco mmons. org/ licen ses/ by/4. 0/. The Creative Commons Public Domain Dedication waiver (http:// creat iveco
mmons. org/ publi cdoma in/ zero/1. 0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
Background
Ecological interactions drive evolutionary change,
where each member of the association acts as a natu-
ral selective agent to its counterpart. Coevolutionary
Open Access
BMC Ecology and Evolution
*Correspondence: evazquez@ecologia.unam.mx
2 Departamento de Ecología de la Biodiversidad, Instituto de Ecología,
Universidad Nacional Autónoma de México, 04510 Mexico City, Mexico
Full list of author information is available at the end of the article

Page 2 of 14
Solórzano‑Garcíaetal. BMC Ecol Evo (2021) 21:190
changes occurring among participants will be more or
less evident depending on the strength, frequency and
dependency of the interaction. Parasitism constitutes an
intimate association in which arm race processes and red
queen dynamics between host and parasites reciprocally
mold many aspects of their genetics, physiology, mor-
phology, behaviour, and life history traits [1–3]. Genetic
studies about host–parasite systems have documented
how the life cycle of the parasite and the degree of host
specificity, jointly with host population size and dispersal
capability, are key factors influencing the genetic struc-
ture of parasites and the potential to form coevolution-
ary associations [2, 4–8]. For instance, a study with bats
and their parasitic mite showed a tight link between
the genetic structure of the parasite and its host’s social
structure [9]. Also, the level of agreement between the
genetic patterns of host and parasite were related to the
level of host specificity in the Galapagos hawk and three
ectoparasites species, in which the highly specific louse
(Degeeriella regalis) showed congruent genetic structure
with the hawk, yielding insights about the host’s recent
evolutionary history [10]. Additionally, gene flow in para-
sites with complex life cycles can be markedly influenced
by the dispersal of the most vagile host [11], while strong
genetic drift has been observed in parasite populations
whose hosts have low dispersal abilities and small home
ranges [12]. Correlations between genetic distances of
host and parasite have also been observed in parasites
with complex life cycles involving free-living stages, like
Schistosoma mansoni and its definitive rat host [11], and
between the freshwater New Zealand snail (Potamopyr-
gus antipodarum) and its trematode parasite (Micro-
phallus sp.) [13]. Furthermore, a cophylogenetic study
evaluating the evolutionary histories of mammal hosts
and helminth parasites showed that the host’s phyloge-
netic history is a key driver of host–parasite associations
and parasite cross-species transmission potential [14].
Although evolutionary interactions between host and
parasites can be tight enough to yield correlated genetic
patterns and even cophylogenetic relationships and
cospeciation [14–16], concordance between host and
parasite microevolution is not always straightforward,
where asynchronous coevolutionary dynamics can arise,
promoting either local adaptation or maladaptation [17,
18]. Commonly, parasites are expected to be more locally
adapted than their hosts, exhibiting higher mean perfor-
mance in “home” hosts than in “away” hosts [19]. Uneven
dispersal rates between hosts and parasites are likely to
disrupt local adaptation processes [5, 20], resulting in
differing degrees of susceptibility/infectivity among host
and parasite populations. Hence, parallel assessments of
the evolutionary history and population genetics of host
and parasites are essential for the understanding of local
adaptation and host specificity, the evolution of virulence
and host resistance, as well as the emergence of evolu-
tionary associations in which both host and parasite suc-
cessfully coexist.
Studies about genetic relationships, divergence and
coevolutionary patterns between non-human primates
and their parasites have evaluated parasite host-specific-
ity and parasite diversification regarding host phylogeny,
predominantly with infectious disease agents and some
ectoparasites [21–25]. Here we explore the synchrony of
microevolutionary dynamics between a metazoan para-
site and its host, for which pinworms and non-human
primates represent a most suitable study system. Pin-
worms are parasitic nematodes with direct life cycle and
no free-living stage, their eggs survive only a few days
once released to the environment, and transmission
occurs mainly by direct contact [26]. ese features make
pinworms highly dependent on host movement for dis-
persion among host populations. Moreover, pinworms
are host-specific parasites showing a close coevolution-
ary history with their primate hosts, supported by cophy-
logenetic studies [27, 28] and by correlations between
parasite–host life history traits, including pinworm
body size and primate longevity and immune responses
[29, 30]. Consequently, one might expect covariation of
diverse genetic attributes such as diversity and differen-
tiation between pinworms and primate populations.
Mantled howler monkeys (Alouatta palliata) are
endangered primates, whose arboreal nature and pre-
dominant folivorous diet significantly limit their dispersal
capability across an unforested matrix [31]. is primate
species is distributed from western Ecuador and north-
ern Colombia to southeastern Mexico, where Mexican
howler monkeys represent the northernmost distribution
of primates in the American continent [32]. As a result of
intense habitat fragmentation throughout their distribu-
tion range in southeast Mexico, most of their populations
are isolated in forest remnants surrounded by anthropic
land use [33]. Alouatta palliata is parasitized by two
species of pinworms, Trypanoxyuris minutus which is
widely dispersed, found in several howler monkey spe-
cies including A. belzebul, A. caraya, A. guariba, A. pigra,
and A. seniculus [34]; and T. multilabiatus, which has
only been reported in A. palliata [35]. Both parasites are
highly prevalent in mantled howler populations in Mex-
ico and mixed infections are common [36].
We analysed the genetic diversity, genetic struc-
ture and demographic history of A. palliata and their
pinworms from across its geographic range in south-
east Mexico, using mitochondrial DNA (mtDNA) for
both host and parasites along with microsatellite data
only for the host. Given the biology and direct mode
of transmission of these parasites, with no vectors

Page 3 of 14
Solórzano‑Garcíaetal. BMC Ecol Evo (2021) 21:190
or intermediary hosts that could influence parasite
genetic configuration other than howler monkeys, the
close evolutionary association between pinworms and
primates, in conjunction with the likely higher evolu-
tionary potential of the parasite compared to that of
their host, we predict: (1) higher genetic diversity and
stronger genetic structure in pinworms in comparison
with howler groups, given that the parasite’s larger
populations sizes and shorter generation times render
the effects on genetic patterns of habitat fragmenta-
tion and limited host dispersal more quickly detect-
able in parasites in comparison with the host; (2) a
positive association between genetic distances of host
and parasites, indicating that genetically similar host
populations harbour similar parasite populations, thus
implying a dependence of the pinworms gene flow on
primate movement; (3) concordant genealogical pat-
terns between host and parasites; and (4) signs of local
adaptation in the pinworm species; the last two predic-
tions are associated with both the host-specificity and
the coevolutionary hypothesis for pinworms and pri-
mates. In order to address this last point, we assessed
host–parasite mtDNA haplotype relationships and
evaluated how these associations relate to haplotype
divergence, parasite infectivity and host susceptibility.
Results
Genetic structure, dierentiation anddiversity inhost
andparasites
S results revealed two main genetic clusters
corresponding to West and East sampling localities in
both pinworm species and the howler monkey, although
the clustering is stronger in the host (Fig.1). e West
cluster comprises populations from Los Tuxtlas, Santa
Marta and Uxpanapa regions, whereas the East cluster
includes the Comalcalco and Pichucalco regions. Indi-
viduals from Agaltepec island (the howler semi-captive
population) were assigned to the West cluster for A.
palliata and T. multilabiatus, but to the East cluster for
T. minutus. A third cluster was evident only for howler
monkeys (mtDNA and microsatellites), further divid-
ing western localities into two genetic clusters (West a
and b; Fig.1). e AMOVA results showed that genetic
variability is distributed among clusters, with similar
values in howler monkeys (FCT = 0.256, p < 0.001) and T.
multilabiatus (FCT = 0.277, p = 0.07), while smaller in T.
minutus (FCT = 0.074, p = 0.005). Pairwise FST differentia-
tion was significant between all regions for howler mon-
keys and between West and East clusters for T. minutus,
whereas T. multilabiatus exhibited no significant differ-
entiation (Additional file1: Tables S1 and S2). At a local
scale, significant pairwise FST values between sampling
localities within the same region were observed only for
West a West b East
17.2° 18.1° 18.9°
-95.8° -94.8°-93.9°-93.0°-92.0°
17.2° 18.1° 18.9°
-95.8° -94.8° -93.9°-93.0°-92.0°
4
67
9
10
5
1
53
4
2
67
89
10
A)
B)
A. palliata
Mst
A. palliata
cyt-b
T. minutus
COI
T. multilabiatus
COI
K=3 K=2
|| |||
||
AND-tmtsM
T. minutus
mt-DNA
T. multilabiatus
mt-DNA
K=2
K=3
|| ||
||
A. palliata
(1)
TUX
(2,3,4)
SMT
(5)
AGA
(6,7)
UXP
(8,9)
CML
(10)
PCH
(4)
SMT
(5)
AGA
(6,7)
UXP
(9)
CML
(10)
PCH
REG
Fig. 1 Study site and population genetic structure of Alouatta palliata and its pinworms Trypanoxyuris minutus and T. multilabiatus. A Maps
showing sampling localities for host and the two parasite species; pie charts depict average per cluster assignment values in each population. B
Barplots of ancestry proportions (Structure results), based on mitochondrial cytochrome b (cyt-b) and microsatellites loci (Mst) for the host and on
mitochondrial cytochrome oxidase subunit 1 gene (COI) for the parasites, in the six studied regions: TUX = Los Tuxtlas (1. Montepio), SMT = Santa
Marta (2. Playa, 3. Mirador Pilapa, 4. La Valentina), AGA = Agaltepec island (5), UXP = Uxpanapa (6. Plan de Arroyo, 7. Murillo Vidal), CML = Comalcalco
(8. Hacienda la Luz, 9. Archaeological Site), PCH = Pichucalco (10); numbers correspond to locations in figure A

Page 4 of 14
Solórzano‑Garcíaetal. BMC Ecol Evo (2021) 21:190
howler monkeys (Additional file 1: TableS3). Isolation
by distance (mtDNA Mantel tests) was observed for both
pinworm species, while howler monkeys only showed
significant isolation by distance based on microsatellites
RST (Additional file1: Fig. S1).
Genetic variability based on mtDNA showed higher
haplotype and nucleotide diversity in the two pin-
worms species in comparison with the host (Additional
file1: TableS4). In all cases, the West cluster had higher
mtDNA diversity values than the East cluster; instead, no
differences were observed for the nuclear diversity in the
host. Genetic diversity is distinctly distributed in each
species as shown in the interpolation maps, although cer-
tain similarities can be identified with mtDNA (Fig. 2).
Overall, eastern groups tend to be less genetically diverse
compared to western ones, except for Santa Marta region
(SMT) that has markedly lower genetic diversity in T.
multilabiatus.
Correlation betweengenetic distances ofhost
andparasites
A significant positive correlation was found between
T. minutus and howler monkeys FST pairwise distances
(r = 0.53, p = 0.008); all other computed genetic dis-
tances showed no correlation (D-Jost: r = 0.12, p = 0.29;
Hedrick’s GST: r = 0.11, p = 0.29; Edw ards: r = 0.04,
p = 0.4) (Additional file1: Fig. S2). For T. multilabiatus
and howler monkeys, a positive correlation was found
between pairwise Hedrick’s GST (r = 0.64, p = 0.02) and
FST (r = 0.75, p = 0.02); D-Jost (r = 0.08 p = 0.42) and
Edward distances (r = 0.07, p = 0.5) were not significant
(Additional file1: Fig. S2).
Demographic history andgenealogies
e Bayesian skyline plots (BSPs) results supported
larger population sizes in parasites compared with those
of their host, exhibiting particular demographic histories
for each species. e howler monkey showed a gradual
population growth and recent population decline. Tryp-
anoxyuris minutus also showed a past continuous popu-
lation growth which seems to slow down more recently,
while a dynamic behaviour with a decreasing and final
increase trend towards the present was observed in T.
multilabiatus (Fig.3).
Regarding the haplotype evolutionary history, 19 dif-
ferent haplotypes were found in howler monkeys, 59 in
T. minutus and 8 in T. multilabiatus. e host median-
joining network differed in several aspects from that of
the pinworms. First, a most frequent haplotype, likely
ancestral, in the howler monkey network, present across
all regions except TUX and CML (Fig.3a). Instead, the
T. minutus genealogy resulted in a complex network
with many alternative paths between haplotypes and no
geographic concordance; the most parsimonious tree
showed few frequent haplotypes and many singletons,
most of them specific to certain localities (Fig.3b). Also,
-95.8° -94.8° -93.9° -93.0° -92.0°
17.2° 18.1° 18.9°
A) B)
D)
C)
high
low
Fig. 2 Interpolation maps showing the distribution of genetic diversity in the host and the two pinworm species across their range in Mexico.
A Alouatta palliata expected heterozygosity from microsatellite data; B A. palliata haplotype diversity (Hd) from cyt-b sequences; C Trypanoxyuris
minutus and D T. multilabiatus haplotype diversity (Hd) from COI sequence data. Black dots represent sampling localities

Page 5 of 14
Solórzano‑Garcíaetal. BMC Ecol Evo (2021) 21:190
the howler monkey haplotypes were connected by 1 to
8 mutational steps, while haplotypes of the pinworms
showed shorter connections (1 to 3 mutational steps),
except for one T. multilabiatus haplotype separated from
the rest by 18 mutational steps (Fig.3c). e codivergence
test showed no significant congruence between host and
parasite phylogenies (global test = 0.00014, p = 0.854),
suggesting random evolutionary associations between
howler monkey and T. minutus haplotypes.
Host susceptibility, parasite infectivity andhaplotypes
associations
e associations between howler and T. minutus hap-
lotypes along with their frequency are shown in Fig.4.
Eighty one percent of the T. minutus haplotypes (48/59)
were associated to single host haplotypes, most of them
specific to certain localities, whereas only 11 pinworm
haplotypes infected 2 or more host haplotypes, with a
mean of 1.3 host haplotypes infected by each pinworm
haplotype. Haplotype Hap5 was the most infective, para-
sitizing five different howler haplotypes. A positive cor-
relation was observed between infectivity and frequency,
with the most infective T. minutus haplotypes also being
the most frequent (ρ = 0.99, p < 0.001; Fig. 4). Regarding
the host, each howler haplotype was infected by a mean
of 4 different pinworm haplotypes (1–21), where the
most frequent haplotypes were also the most susceptible
(ρ = 0.87, p < 0.001; Fig.4).
A negative correlation was found between haplotype
infectivity/susceptibility and mean haplotype p-distance,
where less divergent haplotypes tend to be either more
infective (pinworm haplotypes associated to a larger
number of host haplotypes) (τ = 0.32, p = 0.002), or more
susceptible (howler haplotypes parasitized by a larger
number of pinworm haplotypes) (τ = 0.63, p < 0.001;
Additional file1: Fig. S3). When comparing haplotypes
that share host/parasite, p-distance is lower between pin-
worm haplotypes that parasitize the same host haplotype
than those infecting different host haplotypes (Fig. 5a,
b). e same occurred for howler monkeys, p-distance
between haplotypes sharing pinworm haplotypes was
lower than those parasitized by different T. minutus hap-
lotypes (Fig. 5c, d). Finally, a positive correlation was
found between host haplotypes pairwise p-distance and
the genetic distance of their associated pinworm hap-
lotypes, where similar host haplotypes tend to harbour
genetically similar pinworm haplotypes (Additional file1:
Fig. S4).
Fig. 3 Haplotype genealogical relationships and demographic history of A Alouatta palliata, B Trypanoxyuris minutus and C T. multilabiatus. Top:
median‑joining haplotype networks, colours correspond to sampled geographic regions in southeast Mexico. Bottom: Bayesian skyline plots
based on mtDNA showing changes in median female effective population sizes (Nef) through time. A Gradual population growth in howler
monkeys until ca. 8000 years ago, decreasing afterwards until reaching a most recent Nef of 60,000. B Continuous population growth in T. minutus
until ca. 250 years ago when the increase rate slowed down to a relatively constant trend (Nef from 1,303,500 to 1,347,000. C dynamic trend in T.
multilabiatus population growth, remaining constant until ca. 2000 years ago and then fluctuating by decreasing from 32,250 to 24,700, followed by
a rapid increase around 800 years ago up to 88,400, to a final decrease with a most recent Nef of 86,000

Page 6 of 14
Solórzano‑Garcíaetal. BMC Ecol Evo (2021) 21:190
Discussion
Here we present a co-structure analysis of the microevo-
lutionary dynamics of the coevolving system between
the mantled howler monkey Alouatta palliata and its
two parasitic pinworms, differing in their degree of host
specificity across the host’s distribution range in south-
eastern Mexico. e genetic and demographic patterns
we observed support the notion of correlated evolution
between pinworms and their primate host.
Host–parasite genetic patterns andmicroevolutionary
dynamics
e patterns of genetic structure, differentiation and
diversity are more similar between howler monkeys and
its host species-specific pinworm Trypanoxyuris multi-
labiatus than with T. minutus, the host genus-specific.
ese findings support the tight evolutionary associa-
tion previously suggested in a phylogenetic study where
divergence in T. multilabiatus follows mantled howler
monkey subspecies, while in T. minutus this pattern is
absent [37].
As predicted, genetic diversity was higher in both
pinworm species compared to that of the howler mon-
key. Although pinworms exhibit a haplodiploid mode of
reproduction [26], the high genetic diversity observed
in this and previous studies [38] suggests that sexual
reproduction in Trypanoxyuris might be more frequent
than asexual. Another alternative would be that, despite
having a predominantly asexual reproduction, the high
Hap1
Hap2
Hap3
Hap4
Hap5
Hap6
Hap7
Hap9
Hap10
Hap11
Hap12
Hap13
Hap14
Hap15
Hap16
Hap17
Hap18
Hap19
Hap20
Hap21
Hap22
Hap23
Hap24
Hap25
Hap26
Hap27
Hap28
Hap29
Hap30
Hap31
Hap32
Hap33
Hap34
Hap35
Hap36
Hap37
Hap38
Hap39
Hap40
Hap41
Hap42
Hap43
Hap44
Hap45
Hap46
Hap47
Hap48
Hap49
Hap50
Hap51
Hap52
Hap53
Hap54
Hap55
Hap56
Hap57
Hap58
Hap59
Hap1
Hap2
Hap3
Hap4
Hap5
Hap6
Hap7
Hap8
Hap9
Hap10
Hap11
Hap12
Hap13
Hap14
Hap15
Hap16
Hap17
Hap18
Hap19
Los Tuxtlas Santa Marta
Comalcalco Pichucalco
Uxpanapa
Agaltepec
West:
East:
T. minutus
A. palliata
Haplotype frequency
Infectivity
ρ = 0.99, p < 0.001
Susceptibility
Haplotype frequency
ρ = 0.87, p < 0.001
0
1
2
3
4
5
6
0
5
10
15
20
Frequency
Frequency
Fig. 4 Host/parasite haplotype associations between howler monkeys (Alouatta palliata) and pinworms (Trypanoxyuris minutus). Bars represent
haplotype frequency and lines indicate the associations among haplotypes. Colours correspond to geographic regions. Black lines depict
associations occurring in different regions. Top inset: Spearman correlation between T. minutus haplotype frequency and haplotype infectivity
(number of different host haplotypes associated to each pinworm haplotype). Bottom inset: Spearman correlation between A. palliata haplotype
frequency and vulnerability (number of different pinworm haplotypes co‑occurring within each host haplotype)

Page 7 of 14
Solórzano‑Garcíaetal. BMC Ecol Evo (2021) 21:190
genetic variability might result from the large parasite
population sizes. Notably, genetic variation was also
higher in T. minutus than in T. multilabiatus, which
can be explained by the relationship between genetic
diversity and effective population size [39], given that
T. multilabiatus is markedly less abundant and with
an apparent restricted distribution—it has not been
found in the northernmost mantled howler popula-
tions of Los Tuxtlas [35]. Greater genetic diversity can
also be related to the degree of host specificity; that is,
a broader host spectrum in T. minutus could trigger not
only larger population sizes but also the need to adapt
to different host environments, hence higher genetic
variation. We acknowledge further evaluation is needed
because in this study the T. multilabiatus sample size
was small.
We predicted higher differentiation in the parasites due
to their dependent and more restricted migration. How-
ever, despite the presence of two genetic clusters (West
and East) in both parasites and their host, genetic struc-
ture and genetic differentiation, contrary to our predic-
tion, were stronger in the host than in both pinworms
species, in agreement with limited dispersal in the pri-
mate as previously documented for this species [40–42].
Mazé-Guilmo etal. [5] suggest that variables related to
host dispersal could be poor predictors of genetic pat-
terns in parasites, and that alternative factors like the
host’s and the parasite’s biology are also key drivers of the
codistribution of their genetic variation. Nonetheless, in
parasites with direct life cycles lacking free-living stages,
as is the case in pinworms, host and parasite concord-
ant pairwise genetic differentiation might be expected
[5]. We observed a positive correlation between genetic
distances of howler monkeys and both pinworm species
which indicates that genetically similar host populations
harbour genetically similar parasites, suggesting that pin-
worm gene flow is mediated by howler monkey dispersal.
Large population sizes in these parasites, as evidenced
by the demographic (BSP) results, might be counteract-
ing the effects of genetic drift, while higher gene flow in
the parasites can also contribute to their lower genetic
structure. Given that one howler individual can har-
bour a large number of pinworms (up to ~ 62,000 adult
pinworms have been counted in a howler monkey indi-
vidual [43]), the dispersal of just one monkey could sig-
nify a gene flow many times higher in magnitude among
pinworms populations compared to that of primates,
explaining the parasites’ higher gene flow despite its
0
0.002
0.004
0.006
0.008
0.01
0.012
T. minutus haplotypes
A. palliata
0
0.001
0.002
0.003
0.004
0.005
0.006
0.007
0.008
0.009
0.01
mean p-distance
mean p-distance
haplotypes
0.008
0.006
0.004
sharing host different host
* p = 0.01
sharing different
0.009
0.006
0.003
** p < 0.001
A) B)
C) D)
parasites parasites
Fig. 5 Mean genetic distance between haplotypes sharing host/parasite and those associated to different host/parasite haplotypes. A Line graphs
showing the mean p‑distance values between sharing (red) and differing host (light blue) for each Trypanoxyuris minutus haplotype. B Boxplot
showing the differences on p‑distance between pinworm haplotypes sharing and differing host haplotypes. C Line graphs showing the mean
p‑distance values between sharing and differing parasites for each Alouatta palliata haplotype. D Boxplot of the differences on p‑distance between
host haplotypes sharing and differing pinworm haplotypes. P values derived from Wilcoxon–Mann Whitney test

Page 8 of 14
Solórzano‑Garcíaetal. BMC Ecol Evo (2021) 21:190
dependency on host movement. Moreover, certain host
behaviour such as prospecting movements can favour
the dispersal of infection agents among host populations
without necessarily involving host genetic interchange
[44], rendering the correlation between host and parasite
gene flow less straightforward.
While an isolation by distance (IBD) pattern was
observed for the pinworms based on mitochondrial data,
for the howler monkey it was identified only with nuclear
data. e latter can be related to the historical dispersal
of howler monkeys, whereas the local genetic differentia-
tion and IBD observed with the genetically more variable
microsatellites loci could reflect a contemporary con-
straint in individual movement. e significant habitat
loss and landscape transformation derived from human
activities along the primate distribution has most likely
limited host dispersal between closer populations. Fur-
thermore, IBD in pinworms implies greater potential for
parasite transmission between adjacent howler monkey
populations due to spatial proximity that increases the
contact rates among host individuals. Indeed, inter-host
contact and proximity, animal movement and spatial
constrains imposed by a heterogenous landscape, all play
a critical role in parasite transmission dynamics in wild-
life populations [45–48]. For instance, the extent of phys-
ical contact between and within social groups has major
implications in primate epidemiology, easing the spread
of pathogens and parasites [49–51]. In fact, higher Tryp-
anoxyuris infection in howler monkeys has been associ-
ated to closer partner proximity [52].
e overall demographic and genetic architecture of
both pinworm species (high genetic diversity, high gene
flow, shorter generation time and large effective popu-
lation sizes) suggest higher evolutionary rates in the
parasites compared to their host. is is evident in the
haplotype genealogies where pinworms showed com-
plex networks formed by many unique haplotypes differ-
ing by few mutational steps, compared to the simple and
more structured haplotype network in the howler mon-
key. Even though cophylogenetic patterns between pin-
worms and their primate hosts have been documented
at macroevolutionary scales [27, 28, 37], the intraspe-
cific analyses we performed did not detect congruent
divergence among pinworms and howlers, suggesting
instead distinct diversification processes. Disparate rates
of molecular evolution have been documented in a host-
specific and coevolving host–parasite system (e.g. pocket
gophers and their chewing lice ectoparasites), with dif-
ferences in mutational rates and generation times as the
most plausible mechanisms accounting for the rate dis-
parities [53]. Considering that we sampled populations
along the northernmost portion of the Alouatta pal-
liata howler monkeys distribution (complete geographic
range encompassing from western Ecuador and northern
Colombia to southeast Mexico [32]), the higher rate of
evolutionary change in the parasite could be impeding
the detection of codivergent pinworm-howler patterns
at this narrow spatial scale. We predict this codivergent
pattern to be more evident at broader geographical scales
(i.e. the entire host distribution), where both host and
parasites have had a longer time to accumulate genetic
differences.
Genetic variants, infectivity, susceptibility andgeography
We aimed to further explore the genetic association
between pinworm and howler monkeys by using mtDNA
haplotype identity to assign genetic variants to host and
parasite individuals, enabling us to describe susceptibility
and infectivity traits based on the number of host–para-
site connections identified per haplotype. Accordingly,
hosts were considered more susceptible if they were par-
asitized by a greater number (diversity) of pinworm hap-
lotypes, whereas pinworms infectivity was defined by the
number of different host haplotypes in which each pin-
worm was found.
Overall, nearly each howler haplotype was parasitized
by more than one T. minutus genetic variant. Conversely,
only few pinworm haplotypes were found parasitizing
more than one host genetic variant, and most T. minutus
were associated to a single howler haplotype, suggesting
that T. minutus tends to adapt to one host genetic config-
uration. Selection can cause parasites to develop genetic
specificity towards a particular host genotype, usually
the most common, increasing its susceptibility [19, 39].
Our results agree, where the most frequent howler/pin-
worm haplotype was also the most susceptible/infective.
is genetic specificity could explain the frequent one-
to-one association between T. minutus and the howlers’
genetic variants, as well as the higher genetic similari-
ties between pinworm/host haplotypes that share hosts/
pinworms haplotypes, supporting that genetic similarity
among hosts might be a key factor for pinworm transmis-
sion and establishment. Additionally, these genetic asso-
ciations could be related with the parasite transmission
mode, where autoinfection and retroinfection are com-
mon mechanisms for pinworm acquisition [54, 55]. Both
mechanisms of transmission allow several generations of
pinworms of the same genetic pool to continue infecting
that individual host. is could hinder the spread of pin-
worm variants among host individuals within the popula-
tion, facilitating the development of specificity.
Our study also reveals that parasite genetic variants
are not evenly distributed across geographic regions,
and that only some pinworm haplotypes could be con-
sidered highly infective (being present in high frequency
in all studied localities). Additionally, host haplotypes

Page 9 of 14
Solórzano‑Garcíaetal. BMC Ecol Evo (2021) 21:190
unique to a particular geographic region tend to harbour
pinworm variants also unique for that region. is geo-
graphic specificity [56] in T. minutus shows a roughly
northwest to southeast gradient where many of the
northernmost pinworm haplotypes of Los Tuxtlas are
also present in other regions. Comparatively, most of the
southeastern haplotypes (Comalcalco and Pichucalco)
are only found in that particular region. e history of
dispersion of howler monkeys across southern Mexico
helps explain this pattern, which followed a colonization
process from south to north [57], thus the northernmost
populations are the most recent [42]. During such range
expansion events, parasites can either travel with their
host into new locations or never reach the newly estab-
lished populations because they were lost in the process
or because the migrants did not carry the parasite with
them. e increasing northwest to southeast specific-
ity gradient observed in T. minutus suggests that howler
monkeys carried most of the pinworm genetic variants
as they dispersed towards northern regions. Also, that
only a fraction of pinworm haplotypes remained within
the already established host populations. erefore, most
recent host populations in the north still harbour a col-
lection of pinworm mitochondrial geographic variation.
Notably, the relationships between haplotype diver-
gence and parasite infectivity and host susceptibil-
ity, jointly with the parasite’s higher gene flow, suggest
potential local adaptation in pinworms. Local adapta-
tion, a higher mean fitness of populations in local envi-
ronments, is linked to the ability of each organism to
incorporate new genetic and phenotypic variants that
can confer some fitness advantage [20]. Host–parasite
systems induce constant evolutionary change in order to
overcome the selective pressures imposed by this antago-
nistic interaction. When parasites show higher evolu-
tionary rates and higher gene flow than their hosts, they
are expected to be locally adapted, performing better in
sympatric or home hosts than in allopatric or away hosts
[19, 58]. If we translate this into genetic terms, we expect
locally adapted parasites to be more infective to geneti-
cally similar hosts than to genetically different hosts (see
[59]). Indeed, we found that more divergent hosts were
less susceptible to be parasitized by different pinworms
haplotypes, suggesting higher performance of the parasite
(infectivity) in genetically similar hosts compared to dif-
fering ones. Considering that mtDNA divergence reflects
the accumulation of genetic differentiation along the host
and parasite historical associations, the genetic variation
observed likely echoes an advantage for the host but not
so much for the parasite, since most divergent T. minu-
tus haplotypes were less infective (associated to a smaller
number of host haplotypes). Although acquiring genetic
variation could favour parasite infectivity, it is suggested
that above certain threshold it could also increase host
resistance [20, 60]. Fluctuations between host–parasite
migration and mutation rates causes cycle oscillations of
infectivity and resistance via frequency dependent selec-
tion, and this may play a key role in local adaptation and
maladaptation dynamics, which in turn are fundamental
for host-parasite coevolution [18, 20, 61]. Hence, the fact
that similar howler monkey haplotypes harbour geneti-
cally similar T. minutus infrapopulations, further sug-
gests a correlated evolution in agreement with a highly
host-specific and evolutionary intimate system, as shown
by these pinworms and primate.
Parallel studies on host–parasite genetic arrangements,
although challenging, are growing attention and inter-
est. Our study, jointly with examples (as those mentioned
along the text) that encompass systems with different
degrees of host specificity and distinct parasite life cycles
and life history strategies, contribute to understanding
the transmission dynamics, the distribution of resist-
ant and virulence alleles, and the spread of disease. Also
enabling a better comprehension of the coevolutionary
process and their role in preserving genetic variation,
namely the persistence of host and parasite populations.
Furthermore, the use of conventional genetic techniques,
like in our study, has been of enormous value to uncover
relevant information about the evolutionary ecology
of hosts and parasites interactions. Incorporating high
throughput sequencing techniques and sampling across
the whole genome could certainly be of great value in
co-structure studies, by yielding detailed information on
the microevolutionary changes in pinworms and their
primate hosts, fostering a thorough understanding of the
genetic, ecological and evolutionary dynamics between
hosts and parasites [62].
Conclusions
Evolutionary processes of mantled howler monkey popu-
lations and their pinworms are indeed tightly linked. Our
mtDNA findings show that pinworm gene flow is medi-
ated by host dispersal, while at the same time no codi-
vergence was observed between pinworms and their
primate host. e high genetic diversity, high gene flow
and large effective population sizes showed by the two
pinworm species indicate higher evolutionary rates in the
parasites compared to their host. Additionally, genetic
structure, differentiation and diversity patterns show
higher similarity between howler monkeys and the host
species-specific pinworm T. multilabiatus than the host
genus-specific T. minutus, highlighting the role of host-
specificity in coevolving processes. Our findings show
that pinworms are more infective in the genetically simi-
lar host, whereas associations of host and parasite genetic
variants reveal both genetic specificity towards the most

Page 10 of 14
Solórzano‑Garcíaetal. BMC Ecol Evo (2021) 21:190
frequent host haplotype and geographic specificity in T.
minutus. Moreover, altogether these results suggest sig-
nals of local adaptation in the parasite, while the fact that
similar howler monkey haplotypes harbour genetically
similar T. minutus infrapopulations further supports the
notion of correlated evolution between pinworms and
their primate hosts.
Methods
Data collection
We sampled free-ranging mantled howler monkey groups
(Alouatta palliata) and their pinworms at ten sampling
localities across six geographic regions in southeast Mex-
ico, using non-invasive techniques (Fig.1). One locality,
Agaltepec island, harbours a semi-captive population of
howlers (AGA; Fig.1). We collected howler faecal sam-
ples right after deposition and placed them in 50ml tubes
with 100% ethanol. Before storing, we performed a mac-
roscopic examination of each faecal sample searching for
adult pinworms, which were removed with a fine paint
brush and placed in 1.5ml tubes with 100% ethanol. A
total of 105 pinworms (89 Trypanoxyuris minutus and 16
T. multilabiatus) were recovered from 58 howler monkey
individuals. Pinworm specimens were labelled with host
ID to be able to link host and parasite DNA. Host sam-
ples and pinworm specimens were stored at −20°C until
DNA processing.
Host andparasite genetic data
Howler monkey DNA was extracted using the Nor-
gen stool DNA isolation kit following manufacturer’s
instructions. For each individual host, we amplified a
964pb fragment from the mitochondrial cytochrome b
gene (cyt-b) and genotyped nine microsatellite mark-
ers. Details about host DNA amplification and genotyp-
ing (cyt-b and microsatellites loci) procedures are found
in Solórzano-García etal. [42]. For parasite DNA, indi-
vidual pinworms were digested overnight at 56°C in a
solution containing 10mM Tris–HCl (pH 7.6), 20mM
NaCl, 100mM EDTA (pH 8.0), 1% Sarkosyl, and 0.1mg/
ml proteinase K. DNA was extracted from the superna-
tant using the DNAzol® reagent (Molecular Research
Center, Cincinnati, OH) according to the manufacturer’s
instructions. A fragment of ~ 800bp of the mitochondrial
cytochrome oxidase subunit 1 gene (COI) was obtained
for each recovered pinworm of both species. For details
on pinworm DNA amplification procedures see Solór-
zano-García et al. [38]. Mitochondrial DNA (mtDNA)
alignments were built using Clustal Omega [63] via the
EMBL-EBI web interface [64]. As an additional accuracy
assessment, sequences were translated into amino acids
using MESQUITE v.3.2 [65] with the corresponding ver-
tebrate or invertebrate mitochondrial genetic code to
check for the presence of stop codons. Both primate host
and parasites mtDNA sequences are available in Gen-
Bank; associated microsatellite genotypes of primate host
are available at https:// doi. org/ 10. 5281/ zenodo. 45387 31
(Additional file1: TableS5).
Comparison ofhost andparasite genetic structure
We assessed genetic structure in host and parasites with
S v.2.3.4 [66], by testing clusters (K) from 1 to
6, running 20 replicates per K of 1,000,000 MCMC and
100,000 iterations as burnin under the admixture model.
e most probable number of clusters was estimated
using the Evanno method [67]; S results were
visualized using Pophelper v.2.3 in R [68]. Addition-
ally, an analysis of molecular variance (AMOVA) was
performed in Arlequin v.3.5.2.2 [69] to assess the level
of genetic differentiation among clusters, geographic
regions and sampling localities within regions, for host
and parasite mtDNA.
Because howler monkey movements are expected to be
higher among groups located in nearby forest fragments,
and dispersing individuals may carry pinworms with
them, we tested the isolation by distance hypothesis (IBD)
for the host and the two pinworm species with Mantel
tests, comparing genetic (mtDNA) and geographic dis-
tances. We estimated genetic distances between sam-
pling localities based on D-Jost [70], Hedrick’s GST [71],
and Edwards [72] with the package mmod v.1.3.3 [73] for
host and parasites; we also estimated conventional FST
with Arlequin. Geographic Euclidian distances between
sampling localities were calculated with Raster v.3.3
[74]. IBD patterns were also tested for host microsatel-
lite data based on RST and estimated in Arlequin. Mantel
tests were run with vegan v.2.5 [75] and IBD correlation
plots were built with MASS v.7.3 [76]. Next, in order to
test the hypothesis that parasite gene flow is mediated
by host dispersal, we examined the correlation between
mtDNA genetic distances of howler monkey populations
and those of their pinworms. Considering that pinworms
are directly transmitted host specific parasites, we would
expect dispersal of the parasite to be determined by that
of the host, hence two groups of howlers connected by
migration should harbour genetically similar pinworms.
Distribution ofgenetic diversity
Molecular diversity indices including the number of seg-
regating sites (S), haplotype diversity (Hd) and nucleo-
tide diversity (π) were obtained with DnaSP v.5 [77] for
howler monkey and pinworms per sampling locality and
genetic cluster (see “Results”). In addition, genetic diver-
sity estimates for host microsatellite data were estimated
as the average number of alleles (Na) and observed (Ho)
and expected heterozygosity (He) with Arlequin. e

Page 11 of 14
Solórzano‑Garcíaetal. BMC Ecol Evo (2021) 21:190
geographic distribution of genetic diversity was explored
by mapping the haplotype diversity of both host and
parasites, as well as the host expected heterozygosity
per sampling locality. We applied the Inverse Distance
Weighted interpolation method (IDW) to spatially
interpolate genetic diversity values between sampling
localities across the distribution of Alouatta palliata
in Mexico, using the Quantum Geographic Informa-
tion System QGIS 3.14.16. e resultant raster map was
clipped according to the host distribution polygon [78].
Demographic history andgenealogical analysis
We examined changes in population sizes over time by
constructing a Bayesian Skyline Plot (BSP) in BEAST
v.1.7.5 [79] for each pinworm species and howler mon-
keys. BSP analyses were run under the strict molecular
clock, one hundred million iterations, sampling model
parameters every 20,000 iterations with 10% burn-in.
We applied a mutation rate of 1.57 × 10–7 sub/site/gen-
eration, which is the mtDNA evolutionary rate of Caeno-
rhabditis elegans [80], and a generation time of 40days
for the two pinworm species [54, 81]. For the host, we
used a 1.25 × 10–7 sub/site/generation rate was, which
is the adapted primate cyt-b evolutionary rate with a
howler monkey generation time of 5years [82, 83]. Plots
and the performance of the MCMC process were visual-
ized in Tracer v 1.5. [84].
e genealogical relationships between haplotypes
were determined by unrooted median joining networks
in Network v.5 [85] for each pinworm species and their
primate host. When resulting networks were too com-
plex, we ran a maximum parsimony post-processing to
visualize the most parsimonious tree [86]. We tested a
codivergence scenario between host and parasite lin-
ages using the ParaFit approach [87]. Bayesian maximum
clade credibility trees of howler monkeys and Trypan-
oxyuris minutus haplotypes were built in MrBayes v.3.2.2
[88] and the CIPRES Science Gateway [89], including two
simultaneous MCMC runs, each for four million genera-
tions, sampling trees every 4000 generations, and 25%
burn-in. Patristic distance matrices of both host and par-
asite phylogenies were estimated with adephylo v.1.1 [90],
and the ParaFit test was run in ape v.5 [91].
Haplotype level analyses
Haplotype analyses were run only for T. minutus given
the small sample size we had for T. multilabiatus.
To further examine howler-pinworm association pat-
terns at the mtDNA level, we first identified (a) the host
haplotypes infected by various T. minutus haplotypes,
and (b) those infected by only one pinworm haplo-
type. Next, we estimated the genetic divergence (p-dis-
tance) between howler haplotypes that share pinworm
haplotypes and between those infected by unique pin-
worm haplotypes. e same strategy was followed for
the parasite, estimating genetic divergence between co-
occurring haplotypes and those found in only one host
haplotype. We performed Wilcoxon–Man Whitney
tests in R to assess if the haplotypes that shared host/
parasites were more like each other than to haplotypes
harbouring or infecting distinct host/parasites. We
also examined the relationship between susceptibility/
infectivity and haplotype frequency and divergence by
performing non-parametric correlation tests using the
package ggpubr v.0.4 [92]. e latter enables evaluating
if more common haplotypes were either more suscep-
tible (howler haplotypes associated to many different
pinworm haplotypes) or more infective (pinworm hap-
lotypes found in various host haplotypes), and to iden-
tify if more divergent haplotypes had an infective/
resistant advantage over genetically similar haplotypes.
Finally, we expected similar host haplotypes to harbour
similar pinworm haplotypes, thus we tested the correla-
tion between the genetic distance of the host and their
associated pinworm haplotypes.
Supplementary Information
The online version contains supplementary material available at https:// doi.
org/ 10. 1186/ s12862‑ 021‑ 01924‑4.
Additional le1. Additional Tables S1‑S5 and Figures S1–S4.
Acknowledgements
We thank Ruben Mateo and Pablo Gutiérrez for their help and support during
fieldwork, and Marco Solano de la Cruz for technical assistance. Authorities
from Hacienda La Luz, Parque Arqueológico Comalcalco and Natural Pro‑
tected Areas kindly granted permission for fieldwork and sample collection.
We truly appreciate insightful comments from the reviewers.
Authors’ contributions
BSG and EVD designed the study and performed fieldwork. BSG did the
molecular laboratory work and data analyses. All authors wrote the manu‑
script and agreed to submission. All authors read and approved the final
manuscript.
Funding
This study was funded by the Programa de Apoyo a Proyectos de Investi‑
gación e Innovación Tecnológica (PAPIIT‑UNAM IN202819) to EVD. A postdoc‑
toral scholarship was granted to BSG by DGAPA, UNAM.
Availability of data and materials
Both primate host and parasites mtDNA sequences are available in GenBank
(Additional file 1: Table S5); associated microsatellite genotypes of primate
host are available at https:// doi. org/ 10. 5281/ zenodo. 45387 31
Declarations
Ethics approval and consent to participate
This study was carried out in strict accordance with Mexican laws under col‑
lecting permit issued to EVD (Semarnat‑FAUT‑0168). Fieldwork was conducted
in accord with the American Society of Mammalogists guidelines for use of
wild mammal species [93].

Page 12 of 14
Solórzano‑Garcíaetal. BMC Ecol Evo (2021) 21:190
Consent for publication
Not applicable.
Competing interests
The authors declare that they have no competing interests.
Author details
1 Departamento de Ecología Evolutiva, Instituto de Ecología, Universidad
Nacional Autónoma de México, 04510 Mexico City, Mexico. 2 Departamento
de Ecología de la Biodiversidad, Instituto de Ecología, Universidad Nacional
Autónoma de México, 04510 Mexico City, Mexico. 3 Instituto de Biología, Uni‑
versidad Nacional Autónoma de México, 04510 Mexico City, Mexico. 4 Present
Address: Departamento de Sistemas y Procesos Naturales, Escuela Nacional
de Estudios Superiores ‑ Merida, Universidad Nacional Autónoma de México,
Yucatán, Mexico.
Received: 23 June 2021 Accepted: 13 October 2021
References
1. Gandon S, Buckling A, Decaestecker E, Day T. Host‑parasite coevolu‑
tion and patterns of adaptation across time and space. J Evol Biol.
2008;21:1861–6. https:// doi. org/ 10. 1111/j. 1420‑ 9101. 2008. 01598.x.
2. Blasco‑Costa I, Poulin R. Host traits explain the genetic structure of para‑
sites: a meta‑analysis. Parasitology. 2013;140:1316–22.
3. Barrett LG, Thrall PH, Burdon JJ, Linde CC. Life history determines genetic
structure and evolutionary potential of host‑parasite interactions. Trends
Ecol Evol. 2008;23:678–85. https:// doi. org/ 10. 1016/j. tree. 2008. 06. 017.
4. Criscione CD, Blouin MS. Life cycles shape parasite evolution: com‑
parative population genetics of salmon trematodes. Evolution (N Y).
2004;58:198–202.
5. Mazé‑Guilmo E, Blanchet S, Mccoy KD, Loot G. Host dispersal as the driver
of parasite genetic structure: a paradigm lost? Ecol Lett. 2016;19:336–47.
6. Johnson K, Williams B, Drowm D, Adams R, Clayton D. The population
genetics of host specificity: genetic differentiation in dove lice (Insecta:
Phthiraptera). Mol Ecol. 2002;11:25–38.
7. Lagrue C, Joannes A, Poulin R, Blasco‑costa I. Genetic structure and host–
parasite co‑divergence: evidence for trait‑specific local adaptation. Biol J
Linn Soc. 2016;118:344–58.
8. Criscione CD. Parasite co‑structure: broad and local scale approaches.
Parasite. 2008;15:439–43.
9. van Schaik J, Kerth G, Bruyndonckx N, Christe P. The effect of host social
system on parasite population genetic structure: comparative population
genetics of two ectoparasitic mites and their bat hosts. BMC Evol Biol.
2014;14:18. https:// doi. org/ 10. 1186/ 1471‑ 2148‑ 14‑ 18.
10. Whiteman NK, Kimball RT, Parker PG. Co‑phylogeography and compara‑
tive population genetics of the threatened Galápagos hawk and three
ectoparasite species: ecology shapes population histories within parasite
communities. Mol Ecol. 2007;16:4759–73.
11. Prugnolle F, Théron A, Pointier JP, Jabbour‑Zahab R, Jarne P, Durand P,
et al. Dispersal in a parasitic worm and its two hosts: consequence for
local adaptation. Evolution (N Y). 2005;59:296–303.
12. Blasco‑Costa I, Waters JM, Poulin R. Swimming against the current:
genetic structure, host mobility and the drift paradox in trematode
parasites. Mol Ecol. 2012;21:207–17.
13. Dybdahl F, Lively CM. The geography of coevolution: comparative
population structures for a snail and its trematode parasite. Evo.
1996;50:2264–75.
14. Pfenning‑Butterworth AC, Davies TJ, Cressler CE. Identifying co‑phyloge‑
netic hotspots for zoonotic disease. Philos Trans R Soc B. 2021. https:// doi.
org/ 10. 1098/ rstb. 2020. 0363.
15. Page R. Tangled trees. Phylogeny, cospeciation and coevolution. Chicago:
The University of Chicago Press; 2003.
16. Hoberg EP, Brooks DR, Siegel‑Causey D. Host‑parasite co‑speciation:
history, principles and prospects. In: Clayton DH, Moore J, editors. Host–
parasite evolution: general principles and avian models. Oxford: Oxford
University Press; 1997. p. 212–35.
17. Gandon S, Nuismer SL. Interactions between genetic drift, gene flow, and
selection mosaics drive parasite local adaptation. Am Nat. 2009;173:212–
24. https:// doi. org/ 10. 1086/ 593706.
18. Thompson JN, Nuismer SL, Gomulkiewicz R. Coevolution and maladapta‑
tion. Integr Comp Biol. 2002;42:381–7.
19. Greischar MA, Koskella B. A synthesis of experimental work on parasite
local adaptation. Ecol Lett. 2007;10:418–34.
20. Gandon S, Michalakis Y. Local adaptation, evolutionary potential and
host–parasite coevolution: interactions between migration, mutation,
population size and generation time. J Evol Biol. 2002;15:451–62.
21. Faust C, Dobson AP. Primate malarias: diversity, distribution and insights
for zoonotic Plasmodium. One Health. 2015;1:66–75. https:// doi. org/ 10.
1016/j. onehlt. 2015. 10. 001.
22. Reed DL, Toups MA, Light JE, Allen JM, Flannigan S. Lice and other para‑
sites as markers or primate evolutionari history. In: Huffman MA, Colin
CA, editors. Primate parasite ecology. The dynamics and study of host–
parasite relationships. Cambridge: Cambridge University Press; 2009. p.
231–50.
23. Cooper N, Griffin R, Franz M, Omotayo M, Nunn CL. Phylogenetic host
specificity and understanding parasite sharing in primates. Ecol Lett.
2012;15:1370–7.
24. Demanche C, Berthelemy M, Petit T, Polack B, Wakefield AE, Dei‑cas
E, et al. Phylogeny of Pneumocystis carinii from 18 primate species
confirms host specificity and suggests coevolution. J Clin Microbiol.
2001;39:2126–33.
25. Switzer WM, Salemi M, Shanmugam V, Gao F, Cong M, Kuiken C, et al.
Ancient co‑speciation of simian foamy viruses and primates. Nature.
2005;434:376–80.
26. Adamson ML. Evolutionary biology of the Oxyuridae (Nematoda): biofa‑
cies of a haplodiploid taxon. Adv Parasitol. 1989;28:175–228.
27. Brooks DR, Glen DR. Pinworms and primates: a case study in coevolution.
Proc Helminth Soc Wash. 1982;49:76–85.
28. Hugot JP. Primates and their pinworm parasites: the Cameron Hypothesis
revisited. Syst Biol. 1999;48:523–46.
29. Sorci G, Skarstein F, Morand S, Hugot JP. Correlated evolution between
host immunity and parasite life histories in primates and oxyurid para‑
sites. Proc R Soc B Biol Sci. 2003;270:2481–4.
30. Sorci G, Morand S, Hugot J. Host–parasite coevolution: comparative
evidence for covariation of life history traits in primates and oxyurid
parasites. Proc R Soc B. 1997;264:285–9.
31. Mandujano S, Escobedo‑Morales LA, Palacios‑Silva R. Movements of
Alouatta palliata among forest fragments in Los Tuxtlas, Mexico. Neotrop
Primates. 2004;12:126–31. https:// doi. org/ 10. 1896/ 1413‑ 4705. 12.3. 126.
32. Rylands AB, Groves CP, Mittermeier RA, Cortes‑Ortiz L, Hines J. Taxonomy
and distributions of Mesoamerican primates. In: Estrada A, Garber PA,
Pavelka M, Luecke L, editors. New perspectives in the study of Mesoa‑
merican primates: distribution, ecology, behavior and conservation. New
York: Springer; 2006. p. 29–79.
33. Cuarón AD, Shedden A, Rodríguez‑Luna E, de Grammont PC, Link A.
Alouatta palliata ssp. mexicana. The IUCN Red List of Threatened Species
2020. 2020.
34. Solórzano‑García B, Pérez‑Ponce de León G. Parasites of neotropical
primates: a review. Int J Primatol. 2018;39:155–82.
35. Solórzano‑García B, Nadler SA, Pérez‑Ponce de León G. Pinworm diversity
in free‑ranging howler monkeys (Alouatta spp.) in Mexico: morphological
and molecular evidence for two new Trypanoxyuris species (Nematoda:
Oxyuridae). Parasitol Int. 2016;65:401–11. https:// doi. org/ 10. 1016/j. parint.
2016. 05. 016.
36. Solórzano‑García B, Pérez‑Ponce de León G. Helminth parasites of howler
and spider monkeys in Mexico: insights into molecular diagnostic meth‑
ods and their importance for zoonotic diseases and host conservation.
Int J Parasitol Parasites Wildl. 2017;6:76–84.
37. Solórzano‑García B, Melin AD, Aureli F, Pérez‑Ponce de León G. Unveiling
patterns of genetic variation in parasite–host associations: an example
with pinworms and Neotropical primates. Parasitology. 2019;146:356–62.
38. Solórzano‑García B, Gasca‑Pineda J, Poulin R, Pérez‑Ponce de León G. Lack
of genetic structure in pinworm populations from New World primates in
forest fragments. Int J Parasitol. 2017;47:941–50.
39. Criscione CD, Poulin R, Blouin MS. Molecular ecology of parasites:
elucidating ecological and microevolutionary processes. Mol Ecol.
2005;14:2247–57.

Page 13 of 14
Solórzano‑Garcíaetal. BMC Ecol Evo (2021) 21:190
40. Jasso‑del Toro C, Márquez‑Valdelamar L, Mondragón‑Ceballos R. Diver‑
sidad genética en grupos de monos aulladores de manto (Alouatta
palliata mexicana) en la Reserva de la Biosfera Los Tuxtlas (Veracruz,
México). Rev Mex Biodivers. 2016;87:1069–79. https:// doi. org/ 10. 1016/j.
rmb. 2016. 07. 003.
41. Melo‑Carrillo A, Dunn JC, Cortés‑Ortiz L. Low genetic diversity and
limited genetic structure across the range of the critically endangered
Mexican howler monkey (Alouatta palliata mexicana). Am J Primatol.
2020;82:e23160.
42. Solórzano‑García B, Zubillaga D, Piñero D, Vázquez‑Domínguez E.
Conservation implications of living in forest remnants: inbreeding
and genetic structure of the northernmost mantled howler monkeys.
Biotropica. 2021. https:// doi. org/ 10. 1111/ btp. 12958.
43. Amato JFR, Amato SB, Calegaro‑Marques C, Bicca‑Marques JC. Tryp-
anoxyuris (Trypanoxyuris) minutus associated with the death of a wild
southern brown howler monkey, Alouatta guariba clamitans, in Rio
Grande Do Sul. Brazil Arq Inst Biol. 2002;69:99–102.
44. Boulinier T, Kada S, Ponchon A, Dupraz M, Dietrich M, Gamble A, et al.
Migration, prospecting, dispersal? What host movement matters for
infectious agent circulation? Integr Comp Biol. 2016;56:330–42.
45. White LA, Forester JD, Craft ME. Using contact networks to
explore mechanisms of parasite transmission in wildlife. Biol Rev.
2017;92:389–409.
46. Fofana AM, Hurford A. Mechanistic movement models to understand
epidemic spread. Philos Trans R Soc B. 2017;372:20160086.
47. Davis S, Abbasi B, Shah S, Telfer S, Begon M. Spatial analyses of wildlife
contact networks. J R Soc Interface. 2015;12:20141004.
48. Poulin R. The decay of similarity with geographical distance in parasite
communities of vertebrate hosts. J Biogeopgraphy. 2003;30:1609–15.
49. Rimbach R, Bisanzio D, Galvis N, Link A, Di FA, Gillespie TR. Brown spider
monkeys (Ateles hybridus): a model for differentiating the role of social
networks and physical contact on parasite transmission dynamics.
Philos Trans R Soc B. 2015;370:20140110.
50. Altizer S, Nunn CL, Thrall PH, Gittleman JL, Antonovics J, Cunningham
AA, et al. Social organization and parasite risk in mammals: integrating
theory and empirical studies. Annu Rev Ecol Evol Syst. 2003;34:517–47.
51. Rushmore J, Bisanzio D, Gillespie TR. Making new connections: insights
from primate—parasite networks. Trends Parasitol. 2017;33:547–60.
https:// doi. org/ 10. 1016/j. pt. 2017. 01. 013.
52. González‑Hernández M, Rangel‑Negrín A, Schoof VAM, Chapman CA,
Canales‑Espinosa D, Dias PAD. Transmission patterns of pinworms in
two sympatric congeneric primate species. Int J Primatol. 2014;35:445–
62. https:// doi. org/ 10. 1007/ s10764‑ 014‑ 9751‑y.
53. Hafner MS, Sudman PD, Villablanca FX, Spradling TA, Demastes JW,
Nadler SA. Disparate rates of molecular evolution in cospeciating hosts
and parasites. Science (80−). 1994;265:1087–90.
54. Burkhart CN, Burkhart CG. Assessment of frequency, transmission, and
genitourinary complications of enterobiasis (pinworms). Int J Dermatol.
2005;44:837–40.
55. Felt SA, White CE. Evaluation of a timed and repeated perianal tape test
for the detection of pinworms (Trypanoxyuris microon) in owl monkeys
(Aotus nancymae). J Med Primatol. 2005;34:209–14.
56. Poulin R, Krasnov BR, Mouillot D. Host specificity in phylogenetic and
geographic space. Trends Parasitol. 2011;27:355–61.
57. Cortés‑Ortiz L, Bermingham E, Rico C, Rodriguez‑Luna E, Sampaio I,
Ruiz‑Garcia M. Molecular systematics and biogeography of the Neo‑
tropical monkey genus, Alouatta. Mol Phylogenet Evol. 2003;26:64–81.
58. Gandon S, Capowiez Y, Dubois Y, Michalakis Y, Olivieri I. Local adapta‑
tion and gene‑for‑gene coevolution in a metapopulation model. Proc
R Soc B Biol Sci. 1996;263:1003–9.
59. Johnson P, Calhoun DM, Moss WE, McDevitt‑Galles T, Riepe TB, Hallas
JM, et al. The cost of travel: how dispersal ability limits local adaptation
in host–parasite interactions. J Evol Biol. 2021;34:512–24.
60. Dybdahl MF, Storfer A. Parasite local adaptation: red Queen versus
Suicide King. Trends Ecol Evol. 2003;18:523–30.
61. May RM, Anderson RM. Parasite–host coevolution. Parasitology.
1990;100:S89‑101.
62. Ebert D, Fields PD. Host–parasite co‑evolution and its genomic
signature. Nat Rev Genet. 2020;21:754–68. https:// doi. org/ 10. 1038/
s41576‑ 020‑ 0269‑1.
63. Sievers F, Wilm A, Dineen D, Gibson T, Karplus K, Li W, et al. Fast, scalable
generation of high‑quality protein multiple sequence alignments using
Clustal Omega. Mol Syst Biol. 2011;7:539.
64. Madeira F, Park Y, Lee J, Buso N, Tamer G, Madhusoodanan N, et al. The
EMBL‑EBI search and sequence analysis tools APIs in 2019. Nucleic Acids
Res. 2019;47:w636–41.
65. Maddison W, Maddison D. Mesquite: a modular system for evolutionary
analysis. 2011.
66. Pritchard JK, Donelly P. Inference of population structure using multilocus
genotype data. Genetics. 2000;155:945–59.
67. Evanno G, Regnaut S, Goudet J. Detecting the number of clusters of
individuals using the software STRU CTU RE: a simulation study. Mol Ecol.
2005;14:2611–20.
68. Francis RM. pophelper: an R package and web app to analyse and visual‑
ize population structure. Mol Ecol Resour. 2016. https:// doi. org/ 10. 1111/
1755‑ 0998. 12509.
69. Excoffier L, Laval G, Schneider S. Arlequin (version 3.0): an integrated
software package for population genetics data analysis. Evol Bioinforma.
2005;1:47–50.
70. Jost L. GST and its relatives do not measure differentiation. Mol Ecol.
2008;17:4015–26.
71. Hedrick PW. A standardized genetic differentiation measure. Evolution (N
Y). 2005;59:1633–8.
72. Edwards AWF. Distance between populations on the basis of gene
frequencies. Biometrics. 1971;27:873–81.
73. Winter DJ. MMOD: an R library for the calculation of population differen‑
tiation statistics. Mol Ecol Resour. 2012;12:1158–60.
74. Hijmans RJ. raster: geographic data analysis and modeling. R package
version 3.3–13. 2020. https:// cran.r‑ proje ct. org/ packa ge= raster% 0A.
75. Oksanen J, Blanchet FG, Friendly M, Kindt R, Legendre P, McGlinn D, et al.
vegan: Community Ecology Package. R package version 2.5–6. 2019.
76. Venables WN, Ripley BD. Modern applied statistics with S. 4th ed. New
York: Springer; 2002.
77. Rozas J, Sánchez‑DelBarrio JC, Messeguer X, Rozas R. DnaSP, DNA poly‑
morphism analyses by the coalescent and other methods. Bioinformatics.
2003;19:2496–7.
78. Ceballos G, Blanco S, González C, Martínes E. Alouatta palliata (Mono aul‑
lador, saraguato) delimitada, con base al Atlas Mastozoológico de México.
Distribución potencial. Catálogo de metadatos geográficos. Comisión
Nacional para el Conocimiento y Uso de la Biodiversidad. 2010.
79. Drummond AJ, Rambaut A, Shapiro B, Pybus OG. Bayesian coalescent
inference of past population dynamics from molecular sequences. Mol
Biol Evol. 2005;22:1185–92.
80. Denver DR, Morris K, Lynch M, Vassilieva LL, Thomas WK. High direct esti‑
mate of the mutation rate in the mitochondrial genome of Caenorhabdi-
tis elegans. Science (80−). 2000;289:2342–4.
81. Seung‑Yull C, Shin‑Yong K, Suk‑Il K, Chul‑Yong S. Effect of anthelmin‑
tics on the early stage of Enterobius vermiocularis. Korean J Parasitol.
1985;23:7–17.
82. Milton K, Lozier JD, Lacey EA. Genetic structure of an isolated popula‑
tion of mantled howler monkeys (Alouatta palliata) on Barro Colorado
Island, Panama. Conserv Genet. 2009;10:347–58. https:// doi. org/ 10. 1007/
s10592‑ 008‑ 9584‑3.
83. Ting N, Astaras C, Hearn G, Honarvar S, Corush J, Burrell AS, et al. Genetic
signatures of a demographic collapse in a large‑bodied forest dwelling
primate (Mandrillus leucophaeus). Ecol Evol. 2012;2:550–61.
84. Rambaut A, Suchard M, Drummond A. Tracer. 2013.
85. Bandelt HJ, Foster P, Röhl A. Median‑joining networks for inferring
intraspecific phylogenies. Mol Biol Evol. 1999;16:37–48.
86. Polzin T, Dabeschmand SV. On steiner trees and minimum spanning trees
in hypergraphs. Oper Res Lett. 2003;31:12–20.
87. Legendre P, Desdevises Y, Bazin E. A statistical test for host–parasite
coevolution. Syst Biol. 2002;51:217–34.
88. Ronquist F, Huelsenbeck JP. MrBayes 3: Bayesian phylogenetic inference
under mixed models. Bioinformatics. 2003;19:1572–4.
89. Miller M., Pfeiffer W, Schwartz T. Creating the CIPRES Science Gateway
for inference of large phylogenetic trees. In: Proceedings of the gateway
computing environments workshop. New Orleans; 2010. p. 1–8.
90. Jombart T, Balloux F, Dray S. adephylo: new tools for investigating the
phylogenetic signal in biological traits. Bioinformatics. 2010;26:1907–9.

Page 14 of 14
Solórzano‑Garcíaetal. BMC Ecol Evo (2021) 21:190
•
fast, convenient online submission
•
thorough peer review by experienced researchers in your field
•
rapid publication on acceptance
•
support for research data, including large and complex data types
•
gold Open Access which fosters wider collaboration and increased citations
maximum visibility for your research: over 100M website views per year
•
At BMC, research is always in progress.
Learn more biomedcentral.com/submissions
Ready to submit your research
Ready to submit your research
? Choose BMC and benefit from:
? Choose BMC and benefit from:
91. Paradis E, Schliep K. ape 5.0: an environment for modern phylogenetics
and evolutionary analyses in R. Bioinformatics. 2019;35:526–8.
92. Kassambara A. “ggplot2” based publication ready plots. 2020. https://
cran.r‑ proje ct. org/ packa ge= ggpubr.
93. Sikes RS, Gannon WL. The animal care and use committee of the Ameri‑
can Society of Mammalogists. Guidelines of the American Society of
Mammalogists for the use of wild mammals in research and education. J
Mammal. 2016;97:663–88.
Publisher’s Note
Springer Nature remains neutral with regard to jurisdictional claims in pub‑
lished maps and institutional affiliations.