Download Spatial and temporal patterns of genetic variation in the widespread

Molecular Ecology (2012)
doi: 10.1111/mec.12074
Spatial and temporal patterns of genetic variation in the
widespread antitropical deep-sea coral Paragorgia
arborea
S . H E R R E R A , * † T . M . S H A N K ‡ and J . A . S Á N C H E Z †
*Massachusetts Institute of Technology, Woods Hole Oceanographic Institution, Joint Program in Oceanography, 266 Woods
Hole Road, Woods Hole, MA 02543, USA, †Laboratorio de Biologia Molecular Marina (BIOMMAR), Departamento Ciencias
Biologicas, Universidad de los Andes, Carrera 1E No 18A – 10, Bogota, Colombia, ‡Biology Department, Woods Hole
Oceanographic Institution, 266 Woods Hole Road, Woods Hole, MA 02543, USA
Abstract
Numerous deep-sea species have apparent widespread and discontinuous distributions. Many of these are important foundation species, structuring hard-bottom benthic
ecosystems. Theoretically, differences in the genetic composition of their populations
vary geographically and with depth. Previous studies have examined the genetic diversity of some of these taxa in a regional context, suggesting that genetic differentiation
does not occur at scales of discrete features such as seamounts or canyons, but at larger
scales (e.g. ocean basins). However, to date, few studies have evaluated such diversity
throughout the known distribution of a putative deep-sea species. We utilized
sequences from seven mitochondrial gene regions and nuclear genetic variants of the
deep-sea coral Paragorgia arborea in a phylogeographic context to examine the global
patterns of genetic variation and their possible correlation with the spatial variables of
geographic position and depth. We also examined the compatibility of this morphospecies with the genealogical-phylospecies concept by examining specimens collected
worldwide. We show that the morphospecies P. arborea can be defined as a genealogical-phylospecies, in contrast to the hypothesis that P. arborea represents a cryptic
species complex. Genetic variation is correlated with geographic location at the basinscale level, but not with depth. Additionally, we present a phylogeographic hypothesis
in which P. arborea originates from the North Pacific, followed by colonization of the
Southern Hemisphere prior to migration to the North Atlantic. This hypothesis is
consistent with the latest ocean circulation model for the Miocene.
Keywords: coral, deep sea, DNA barcoding, phylogeography, species, widespread
Received 1 June 2012; revision received 28 August 2012; accepted 1 September 2012
Introduction
Several marine species, particularly from deep-sea environments, have apparent widespread yet discontinuous
distributions (e.g. review by Roberts et al. 2009; Bik et al.
2012). Various mechanisms have been suggested to
explain the apparent existence of such species, including
recent connectivity among populations mediated by
long-distance dispersal (Bucklin et al. 1987; France &
Correspondence: Juan A. Sánchez, Fax: +57 1 3394949*2817;
E-mail: [email protected]
© 2012 Blackwell Publishing Ltd
Kocher 1996; Darling et al. 2000; Won et al. 2003;
Pawlowski et al. 2007; Lecroq et al. 2009; Etter et al.
2011), large population sizes and similar selective pressures in a stable environment (Bisol et al. 1984; Brinkmeyer et al. 2003; Etter et al. 2011), relatively recent
events of colonization mediated by jump dispersal over
barriers (Darling et al. 2000; Etter et al. 2011), and cryptic
speciation (France & Kocher 1996; Howell et al. 2004). A
number of deep-sea coral morphospecies are among
these widespread species with discontinuous distributions, for example Lophelia pertusa, Solenosmilia variabilis
and Madrepora oculata (Roberts et al. 2009).
2 S . H E R R E R A , T . M . S H A N K and J . A . S Á N C H E Z
Deep-sea corals are some of the most conspicuous invertebrate inhabitants of hard-bottom benthic
environments worldwide. They are not only more
diverse, in terms of number of species, than their shallow counterparts (Cairns 2007), but also they play a
fundamental role as foundation species and ecosystem
engineers, creating three-dimensional habitats that are
occupied by a high diversity of associate species (BuhlMortensen & Mortensen 2005; Costello et al. 2005;
Etnoyer & Morgan 2007; Buhl-Mortensen et al. 2010;
Shank 2010). Coral ecosystems also support fisheries
(D’Onghia et al. 2011; Soeffker et al. 2011) and have
been identified as important sources of marine natural
products (Leal et al. 2012). Deep-sea corals have evolved
in a relatively stable and energy-poor environment; they
tend to have slow growth rates (Roberts et al. 2009; Sun
et al. 2010), great longevity (Roark et al. 2009) and
size-dependent fecundity (Cordes et al. 2001). These
characteristics make deep-sea coral ecosystems highly
susceptible to disturbance events, especially those generated by human activities, that is, bottom-trawling,
deep-sea mining, hydrocarbon extraction, waste disposal, climate change and ocean acidification (reviewed
in Ramirez-Llodra et al. 2011). The characterization of
spatial distribution patterns of genetic types is of fundamental importance to identify the factors that shape the
ranges of deep-sea taxa, and that ultimately drive biodiversity patterns in the ocean (McClain & Mincks 2010).
Widespread taxa thus can be used as models to understand how the effects of these factors operate at a global
scale. Such information provides critical baseline data
with which the potential effects of disturbances on
populations inhabiting earth’s largest biome can be
assessed.
A handful of studies have examined the genetic
diversity of deep-sea coral taxa in a regional context (Le
Goff-Vitry et al. 2004; Smith et al. 2004; Thoma et al.
2009; Morrison et al. 2011). These have suggested that
genetic differentiation does not seem to occur at small
geographic scales often associated with discrete features
such as individual seamounts or canyons, but presumably at larger scales, that is, broader oceanic regions.
However, no studies to date have evaluated such
hypotheses throughout the entire known distribution of
a putative deep-sea coral species (see Pante & Watling
2012; for a comparison between two distant regions).
In this study, we examined the spatial patterns of
genetic variation in the widespread bubblegum coral
Paragorgia arborea (Linnaeus, 1758) (Octocorallia: Paragorgiidae), which is one of the most prominent coral
morphospecies in cold-water sublittoral and bathyal
hard-substrate habitats.
Paragorgia arborea plays an important ecological role
generating microhabitats for numerous species; they are
the structural analog of large trees in a rain forest
(Buhl-Mortensen & Mortensen 2005; Metaxas & Davis
2005; Watanabe et al. 2009; Buhl-Mortensen et al. 2010).
Single colonies of P. arborea can harbour hundreds of
individuals from dozens of associated species (e.g.
ophiuroids, copepods, shrimp, anemones, polychaetes,
ostracods, barnacles, amphipods, hydroids and foraminiferans) (Buhl-Mortensen et al. 2010). The fauna associated with this coral can be two to three times richer
than the fauna associated with equivalent shallow-water
tropical gorgonians (Buhl-Mortensen & Mortensen 2004,
2005).
Paragorgia arborea has been reported from polar,
subpolar and subtropical regions of all of the world’s
oceans. This conspicuous and locally abundant species
can grow massive colonies, which can reach up to 8 m
in height (Sánchez 2005). Paragorgia arborea lives in
regions of high productivity (Sarmiento & Gruber 2006
depth-integrated primary production > 10 mol/C/m2/
year) and high export fluxes (Sarmiento & Gruber
2006 particle export at 100 m > 2 mol/C/m2/year), water
temperatures lower than 12 °C and relatively high
local current velocities of 5–30 cm/s (Mortensen &
Buhl-Mortensen 2004; Bryan & Metaxas 2006; Etnoyer &
Morgan 2007; Roberts et al. 2009; Watanabe et al. 2009).
The known distribution of P. arborea in the Northern
Hemisphere includes numerous observations in both
eastern and western North Atlantic waters and also in
the eastern and western North Pacific (WNP), from
Japan to the Aleutian Islands and to the Californian
seamounts. In the Southern Hemisphere, it has been
reported around the Crozet Islands, the Patagonian
Shelf and the western South Pacific off New Zealand
(Grasshoff 1979; Tendal 1992). Since the publication of
these records, both fishing pressure and scientific
research in the deep sea have increased significantly,
and the number of new records for this species has
increased in tandem. Some of these records can now be
found in biodiversity databases such as the Ocean
Biogeographic Information System (OBIS, http://www.
iobis.org) and Global Biodiversity Information Facility
(GBIF, http://data.gbif.org); however, many others
remain unconsolidated in scattered publications and
local databases. Thus, an updated picture of the global
distribution of this species is in order.
In this study, we provide an up-to-date summary of
the global distribution of P. arborea and genetic insights
into the global phylogeography of this species. By
examining the genealogy of mitochondrial and nuclear
genetic variants from specimens collected over nearly
its entire known distribution, we tested the compatibility of the morphospecies P. arborea with the genealogical-phylospecies concept. We evaluated the hypothesis
that the morphospecies P. arborea is a complex of
© 2012 Blackwell Publishing Ltd
PHYLOGEOGRAPHY OF DEEP-SEA CORAL PARAGORGIA ARBOREA 3
cryptic species in a barcoding framework. We also
examined the global patterns of genetic variation and
their possible correlation with the spatial variables of
geographic position and depth. We propose a scenario
that could explain the observed evolutionary and
present-day patterns in this and other species.
Methods
Global distribution
To illustrate the currently known global distribution of
Paragorgia arborea, we plotted on a gridded geographic
map all the unique records available to date from the
databases of the OBIS, the GBIF, the Smithsonian
Institution National Museum of Natural History
(http://www.mnh.si.edu/rc/), the Yale University
Peabody Museum of Natural History (www.peabody.
yale.edu), the Harvard University Museum of Comparative Zoology (www.mcz.harvard.edu), the Muséum
National d’Histoire Naturelle France (www.mnhn.fr),
the National Institute of Water & Atmospheric Research
(www.niwa.cri.nz) and several local databases and
publications (Bruntse & Tendal 2000; Wareham &
Edinger 2007; Mortensen et al. 2008; Roberts et al. 2008;
Hibberd & Moore 2009; Laptikhovsky 2011). Geographic
coordinates were reconstructed using Google Earth for
records with known collection locality, but no latitude
and longitude information. Similarly, missing depth
data were reconstructed using data from the global
GEBCO_08 30 arc-second grid.
Molecular methods
We analysed a total of 130 specimens of P. arborea available from various museum and laboratory collections
(see Table S1, Supporting information). The examined
material, collected since 1878, covers most to the known
geographic distribution as well as the entire depth distribution of P. arborea (see Table S1, and Figs S1–S4,
Supporting information for comparison). For more
details on the sequencing of old specimens, see the
Appendix S1 (Supporting information). Additional
material from other paragorgiid morphospecies was
included for comparisons. Total DNA was extracted
from dry or ethanol-preserved (70–96%) samples using
a CTAB–proteinase K–PCI protocol (Coffroth et al. 1992)
or using an automated extraction system (AutoGenprep
965; AutoGen Inc.) as described in the study by Herrera
et al. (2010). DNA was eluted in TE buffer and stored at
!70 °C.
Mutation rates in octocoral mitochondria are significantly lower than in most other organisms (Bilewitch &
Degnan 2011). The implication of this lower mutation
© 2012 Blackwell Publishing Ltd
rate is that mitochondrial markers in octocorals are useful to infer phylogeographic patterns and connectivity
at broader spatial and temporal scales. Thus, to maximize the amount of variability captured from the
genome of this organelle, we obtained sequences from
seven gene regions, amplified by five primer pairs (Herrera et al. 2010), adding up to approximately 3000 base
pairs (bp). These regions include the 3′-end of the
NADH dehydrogenase subunit 6 (nad6), the nad6-nad3
intergenic spacer (int), the 5′-end of the NADH dehydrogenase subunit 3 (nad3), the 3′-end of the cytochrome c
oxidase subunit I (cox1), the 5′-end of the DNA
mismatch repair protein – mutS – homolog (mtMutS),
two different regions of the large subunit ribosomal
RNA (16S) and the 5′-end of the NADH dehydrogenase
subunit 2 (nad2).
We also sequenced the nuclear ribosomal internal
transcribed spacer 2 (ITS2). In octocorals, ITS has been
assessed in a number of groups providing enough resolution for diverse phylogenetic inferences (Alcyoniidae
McFadden et al. 2001; McFadden & Hutchinson 2004;
Nephtheidae van Ofwegen & Groenenberg 2007). ITS2
has also provided enough resolution for intraspecific
and phylogeographic studies in Caribbean shallowwater octocorals (Sánchez et al. 2007; Gutiérrez-Rodriguez et al. 2009). Furthermore, ITS2 has also provided
valuable information for the analysis of genetic structure of deep-sea corals (Le Goff-Vitry et al. 2004; Miller
et al. 2011).
Polymerase chain reactions (PCR) and sequencing
reactions for mitochondrial gene regions were performed following the protocols used by Herrera et al.
(2010). ITS2 PCR amplicons, from a subset of 19 geographically representative individuals, were examined
to assess the possibility of intragenomic variants
through denaturing gradient gel electrophoresis
(DGGE). Gels contained 8% polyacrylamide, 19 TAE
buffer and a linear urea–formamide denaturing gradient
from 45% to 80%. The gels were pre-ran at 60 °C and
90 V for 30 min, followed by 13 h at 60 °C and 90 V.
Gels were stained with ethidium bromide for 15 min
and visualized using a Bio-Rad Chemidoc system. PCR
products from DGGE-excised bands were subsequently
cleaned and sequenced. Complementary chromatograms were assembled and edited using the SEQUENTM
CHER
4.8 software (Gene Codes Corp.).
Sequences of each region were aligned independently
using MAFFT 6.8 (Katoh et al. 2002). The G-INS-i and
Q-INS-i algorithms (gap opening penalty = 1.53, offset
value = 0.07) were employed for the protein coding and
ribosomal regions, respectively. Secondary structures of
ribosomal regions were inferred to improve the alignments, following the protocols used in the study by
Herrera et al. (2010). To correct possible mistakes, all
4 S . H E R R E R A , T . M . S H A N K and J . A . S Á N C H E Z
alignments of protein coding sequences were visually
inspected and translated to amino acids in GENEIOUS 5.3
(Drummond et al. 2010), using the genetic code of
Hydra attenuata (Pont-Kindon et al. 2000). No unusual
stop codons or suspicious substitutions were identified,
suggesting that no nuclear pseudogenes were
sequenced (Lopez et al. 1994; Bensasson et al. 2001).
Mitochondrial sequences were concatenated for each
individual and treated as one single locus in most subsequent analyses, given that the mitochondrial genome
is assumed to be nonrecombining. Mitochondrial and
ITS2 genetic variants, with alignment gaps included as
an informative state (Giribet & Wheeler 1999), were
identified using DNASP 5.0 (Librado & Rozas 2009) and
will be referred hereafter as haplotypes.
Gene trees and molecular clock
To evaluate the compatibility of P. arborea with the
functional definition of genealogical-phylospecies sensu
De Queiroz (2007), that is, all alleles of a given locus in
individuals of P. arborea being ‘descended from a common ancestral allele not shared with those of other
species’ (Avise & Ball 1990; Baum & Shaw 1995), we
performed independent phylogenetic analyses of the
mitochondrial and ITS2 haplotypes. Homologous
sequences from eight other paragorgiid morphospecies
were included as outgroups (see Table S1, Supporting
information). Phylogenetic estimation was performed
using Bayesian inference (BI) in MRBAYES 3.12 (Huelsenbeck & Ronquist 2001; Ronquist & Huelsenbeck 2003)
as implemented in the CIPRES portal (http://www.phylo.
org). Most likely nucleotide substitution models were
selected for each region based on the Akaike Information Criteria (AIC) as implemented in JMODELTEST 2.0.
Models for the mitochondrial regions are shown in
Table S2 (Supporting information). The general time
reversible model with a gamma-distributed rate variation across sites (GTR+G) was selected for the ITS2.
Default prior distribution settings were assumed for all
parameters. Four independent analyses of 10 000 000
Monte Carlo Markov chain (MCMC) generations (94
chains) were run with a sampling frequency of 1000
generations (burn-in = 25%). Combined BI analysis of
the mitochondrial locus was performed with explicit
character partitions for each concatenated region, along
with their independently selected models of evolution.
To account for the rate variation among partitions (Marshall et al. 2006), we allowed the rates to vary under a
flat Dirichlet prior distribution (ratepr = variable). The
parameters of nucleotide frequencies, substitution rates,
gamma shape and invariant site proportion were
unlinked across partitions. MCMC runs were analysed
in the program TRACER 1.5 (Rambaut & Drummond
2007). Convergence was indicated by the ‘straight hairy
caterpillar’ (Drummond et al. 2007) shape of the stationary posterior-distribution trace (generations vs. log-likelihood) of each parameter. Other examined convergence
and mixing diagnostics included the standard deviation
of partition frequencies (<0.01), the potential scale
reduction factor (PSRF) (ca. 1.00), the effective sample
sizes (EES) (>200) and the similitude of posterior probabilities of specific nodes between different runs in the
program AWTY (http://ceb.csit.fsu.edu/awty) (Nylander
et al. 2008). High correlations between runs and no
obvious trends in the split frequency plots were
observed. Tree files for each run were combined, after
burn-in, using the program LOGCOMBINER v1.7.1 (Drummond et al. 2012). The most probable trees were
summarized into a maximum clade credibility tree
using TREEANNOTATOR v1.7.1 (Drummond et al. 2012).
A Bayesian-MCMC joint estimation of gene genealogy
and divergence times was performed in BEAST 1.7.1
(Drummond et al. 2012) for the mitochondrial marker
assuming the same substitution model mentioned
above. We assumed an uncorrelated relaxed lognormal
molecular clock model, which allows for the variation
in mutation rates among branches, with the Yule model
of constant speciation rate (Yule 1925; Gernhard 2008)
and the coalescent model of constant population size
(Kingman 1982), as the tree priors. Additional
sequences from specimens of the sister family, Coralliidae, were added to estimate divergence time within the
phylogeny as this family contains some of the few fossils available for Octocorallia. The coralliid node was
calibrated implementing a normal prior distribution for
the time to the most recent common ancestor (TMRCA)
with a mean of 83.5 million years before present (Myr
BP) and a standard deviation of 0.7, corresponding to
Campanian age stratum, in which the oldest known
fossil in this family has been found (Schlagintweit &
Gawlick 2009). Three MCMC independent analyses
were run for 30 000 000 generations with a sampling
frequency of 3000 (burn-in = 25%). Convergence diagnostics (generations plot and EES) were also examined
for the combined runs in TRACER 1.5 (Rambaut &
Drummond 2007) as mentioned above. The most probable trees were summarized into a maximum clade
credibility tree with median node heights using TREEANNOTATOR v1.7.1 (Drummond et al. 2012).
To infer the historical patterns of dispersal in
P. arborea, we used the Bayesian phylogeography
framework proposed by Lemey et al. (2009), as implemented in BEAST 1.7.1 (Drummond et al. 2012). We
mapped the geographic ocean region where each haplotype was sampled to the time-scaled mitochondrial
gene genealogy, which was inferred with the assumption of an uncorrelated relaxed lognormal molecular
© 2012 Blackwell Publishing Ltd
PHYLOGEOGRAPHY OF DEEP-SEA CORAL PARAGORGIA ARBOREA 5
clock and the coalescent constant-population-size tree
prior, as explained above. This framework allows the
reconstruction of discrete states of geographic location
for ancestral nodes by posterior probability estimation.
Barcoding and species delimitation
To test for the possibility of cryptic species in the morphospecies P. arborea, we calculated pairwise uncorrected distances among individuals of P. arborea and
other paragorgiid morphospecies for the mtMutS and
cox1 sequences, as proposed by McFadden et al. (2011),
in PAUP* 4.0b10 (Swofford 2002). Neighbour-joining trees
were built using the calculated distances. We also
examined the ITS2 secondary structures for the
presence of compensatory base changes (CBCs) using
the visualization program 4SALE (Seibel et al. 2006);
CBCs are altered pairings in a helix of the secondary
structure of the ITS2 RNA transcript, and empirical
work has suggested that they could be used as indicators of species boundaries in most metazoans (Muller
et al. 2007; Coleman 2009).
We also used the coalescent-based species delimitation method described by Pons et al. (2006) and
Monaghan et al. (2009), as implemented in the SPLITS
R-package (available from http://r-forge.r-project.org/
projects/splits/). This likelihood method is based on a
general mixed Yule-coalescent (GMYC) model, which
estimates phylospecies boundaries in a clock-constrained calibrated tree by identifying increases in
branching rates (looking forward in time). Such
increases are assumed to be characteristic of transition
points between interspecific speciation–extinction processes and intraspecific coalescent processes, that is,
populations (Pons et al. 2006; Monaghan et al. 2009). Single- and multiple-threshold models with explicit and
upper and lower limits for the estimation of scaling
parameters (0 and 10, respectively) were used in the
analysis of the time-calibrated trees obtained with the
Yule and coalescent models tree priors.
Genetic variability
Genetic variability among individuals and populations
was measured for each locus according to the haplotype
diversity (h) and genetic diversity (average number of
pairwise differences hp) indices (Tajima 1983) using
ARLEQUIN 3.5 (Excoffier & Lischer 2010). Fu’s Fs statistic
was calculated to determine whether the observed
pattern of polymorphism was consistent with a neutral
model of evolution (Tajima 1989; Fu 1997). Global FST
statistics were calculated to evaluate for possible differentiation in the genetic composition among populations
worldwide. Pairwise comparisons of population differ© 2012 Blackwell Publishing Ltd
entiation were made in Arlequin and significance
values estimated after 1000 permutations. To visualize
the spatial patterns of genetic variation for each marker,
the specimens were colour-coded according to haplotype, their geographic collection coordinates were
plotted using IMAP v3.5 (Biovolution), and their collection depth was plotted on an X-Y scatter plot. To assess
the amount of variability in the populations of P. arborea that was represented in our samples, we generated
haplotype accumulation curves (Gotelli & Colwell 2001)
by calculating estimates of the mean and variance for
the number of accumulated haplotypes through 1000
random permutations, using the program R-package
SPIDER v1.1 (Brown et al. 2012).
Results
Global distribution
A total of 341 high-confidence geographic location
records of Paragorgia arborea were gathered (see Fig. S3,
Supporting information). Paragorgia arborea is an
antitropical taxon, occupying a band between 30° and
70° degrees of latitude in both hemispheres. These
bands are, in general, areas of high surface primary
productivity and export (Sarmiento & Gruber 2006).
Most records of P. arborea are from depths shallower
than 1000 m, indicating a preference for upper-bathyal
environments. Despite the fact that other coral species
that share part of their ranges with P. arborea have been
commonly observed in tropical and subtropical regions
(e.g. Lophelia pertusa and Madrepora oculata), P. arborea
has never been found in these areas. This suggests that
the currently known distribution of P. arborea is not a
result of undersampling at lower latitudes.
Molecular data
A total of 92 specimens were positively screened for the
mitochondrial marker. The concatenated mitochondrial
alignment for the morphospecies P. arborea had a length
of 2922 bp, of which 2881 were invariable sites (pairwise identity of 99.7%); eight sites were parsimonyinformative. The mean ungapped sequence length was
2917.9 bp (SD = 2.8 bp), with a range of 2910 and
2921 bp. The G-C content was 39.5%. The only noncoding region in the mitochondrial locus data set, the nad6nad3 intergenic spacer (int), contained one indel, but no
nucleotide substitutions. The ITS2 was successfully
sequenced for 48 specimens, of which 83% overlapped
with the mitochondrial set. The ITS2 alignment had a
length of 312 bp, of which 301 were invariable (pairwise
identity of 99.2%); 35 sites were parsimony-informative.
The mean ungapped sequence length for ITS2 was
6 S . H E R R E R A , T . M . S H A N K and J . A . S Á N C H E Z
282 bp (SD 0.9 bp), ranging between 280 and 284 bp.
The G-C content was 41.1%. No intragenomic variability
was revealed, using DGGE, in the ITS2. The predicted
secondary structure of ITS2 showed the characteristic
shape of a helicoidal ring with four helixes (Coleman
2007); stems III and IV were particularly long in this
species (Fig. S5, Supporting information). The number
of haplotypes and genetic diversity estimates for each
population with both loci are shown in Figs 1 and 2.
The nad6-int-nad3 region (hereafter referred as nad6 for
simplicity) contained most of the variable sites (21) and
the greatest number of haplotypes (11) found in the
individuals with complete mitochondrial data sets.
Haplotype differences were also located in the ITS2:
one at helix I, three at helix III and five at helix IV; the
remaining two were free nucleotides at the structure
main ring (Fig. S5, Supporting information).
Gene genealogies and phylogeographic history
Individual mitochondrial gene trees were largely congruent, although resolution was generally low (Fig. S6,
Supporting information). The inferred phylogeny based
on each independent loci (i.e. concatenated mitochondrial and ITS2) highly supported the monophyly of
P. arborea (Fig. 3) and had much greater clade resolution. Both Bayesian and neighbour-joining analyses
inferred the same evolutionary relationships. Branch
lengths were appreciably shorter within the clade of
P. arborea, when compared to the ones among morphospecies. Relationships within Paragorgia were not fully
resolved, particularly among Paragorgia wahine, Paragor-
gia yutlinux and Paragorgia sp. 1. The systematic
relationships of Paragorgia spp. are outside of the scope
of this study and will not be further discussed.
The time-scaled trees estimated assuming the coalescent model of constant population size had, in general,
shorter shallower and longer deeper branches than the
tree estimated assuming the Yule model of constant
speciation rate (Figs S7 and S8, Supporting information). Consequently, the time to the TMRCA of the
genus Paragorgia was estimated to be 61 Myr BP (95%
CI: 31–101) under the coalescent model and 54 Myr BP
(95% CI: 41–94) under the Yule model. The TMRCA of
P. arborea based on the coalescent model and the Yule
model was 10.1 Myr BP (95% CI: 4.4–18.8) and
14.1 Myr BP (95% CI: 6.7–26.3), respectively.
The Bayesian phylogeographic analysis indicates that
the lineage of P. arborea likely originated in the North
Pacific (posterior probability 0.38, see Fig. 4). Dispersal
to the South Pacific and subsequent colonization of
the North Atlantic likely occurred between the midMiocene and early Pliocene.
Genetic distances, CBCs and GMYC
Maximum uncorrected genetic distances among conspecifics and minimum uncorrected genetic distances
among congeners were used to measure the intraspecific and interspecific variation, respectively, of mtMutS
and cox1 sequences as in the study by McFadden et al.
(2011). The maximum distances within P. arborea, 0.3%
for mtMutS and 0.9% for cox1, were in general smaller
than the distances among morphospecies of Paragorgia,
Fig. 1 The global geographic distribution
of mitochondrial haplotypes in Paragorgia
arborea. The gene tree in the centre of the
figure shows the inferred relationships
among haplotypes. Each haplotype is
indicated by a different colour. Framed
circles represent individuals. Pie charts
indicate the frequency of haplotypes in
each population (global region): North
Atlantic (NA), South Atlantic (SA), South
Pacific (SP), western North Pacific (WNP)
and eastern North Pacific (ENP). The size
of each pie is proportional to the number
of samples from each population (n). The
number of haplotypes (H), haplotype
diversity (h), genetic diversity (hp) and
the Fu’s Fs statistic are also indicated.
© 2012 Blackwell Publishing Ltd
PHYLOGEOGRAPHY OF DEEP-SEA CORAL PARAGORGIA ARBOREA 7
Fig. 2 The global geographic distribution
of nuclear internal transcribed spacer 2
haplotypes in Paragorgia arborea. The
gene tree in the centre of the figure
shows the inferred relationships among
haplotypes. Each haplotype is indicated
by a different colour. Framed circles represent individuals. Pie charts indicate the
frequency of haplotypes in each population: North Atlantic (NA), South Indian
Ocean (SI), South Pacific (SP), western
North Pacific (WNP) and eastern North
Pacific (ENP). The size of each pie is
proportional to the number of samples
from each population (n). The number of
haplotypes (H), haplotype diversity (h),
genetic diversity (hp) and the Fu’s Fs
statistic are also indicated.
NP
NP
NP
NP
NP
NP
NP
NP
SP
SP
NP
SP
SA
NA
SP
SP
NA
NA
NA
Time (million years)
Fig. 3 Unrooted gene tree hypotheses for the mitochondrial
(top) and nuclear internal transcribed spacer 2 (bottom) markers in Paragorgia.
which ranged between 0.5–6.1% and 0–2.3% for mtMutS
and for cox1, respectively (Table S3, Supporting information). The minimum distances between P. arborea
© 2012 Blackwell Publishing Ltd
Fig. 4 Maximum clade credibility ultrametric time-scaled mitochondrial gene tree for Paragorgia arborea. Branch colours show
the most probable location states: North Atlantic (NA) in blue,
South Pacific (SP) in green, South Atlantic (SA) in violet and
North Pacific (NP) in orange. Pie charts show the posterior
probabilities of location states for each ancestral node (total pie
area = 1). The most probable location state of each node is also
indicated.
and the other morphospecies of Paragorgia ranged
between 1.8–5.1% for mtMutS and 0.6–1.8% for cox1. A
similar pattern was observed for ITS2 distances, 0.6% in
8 S . H E R R E R A , T . M . S H A N K and J . A . S Á N C H E Z
intraspecific comparisons within P. arborea (maximum
distances) and 3.3–7.4% in interspecific comparisons
among morphospecies of Paragorgia. The minimum
distances between P. arborea and the other morphospecies ranged between 3.3 and 5.6%. The predicted ITS2
secondary structure was essentially the same for all
haplotypes of P. arborea and no CBCs or hemi-CBCs
were observed.
A transition point between species- and populationlevel branching patterns was identified, by the singlethreshold GMYC method, at ca. 21 Myr BP for the
time-scaled mitochondrial gene genealogy estimated
with the Yule model tree prior (Fig. S7, Supporting
information). For the time-scaled gene genealogy estimated with the coalescent model tree prior, this transition point was inferred to be at ca. 16 Myr BP (Fig. S8,
Supporting information). In both cases, the GMYC
model showed a marginally significant (i.e. a = 0.05)
better fit to the data than the null model of uniform
coalescent branching rates (LR = 4.84, d.f. = 3, P = 0.18,
compared to LR = 5.84, d.f. = 3, P = 0.12, respectively).
The implementation of a multiple-threshold GMYC
model did not yield a significantly (i.e. a = 0.05) better
fit than the single-threshold GMYC for either case
(v2 = 2.55, d.f. = 3, P = 0.47 and v2 = 0.83, d.f. = 3,
P = 0.84, respectively).
Spatial patterns of genetic variation
Overall, in P. arborea, 16 haplotypes were defined based
on the mitochondrial locus and 11 based on the ITS2.
The genealogical relationships among haplotypes
inferred by the Bayesian inference did not reveal reciprocal monophyly of the specimens from Northern and
Southern Hemispheres, or from different oceans, for
example Pacific vs. Atlantic (Figs 1 and 2). In fact, a
number of haplotypes were shared across large
geographic spans.
Genetic diversity, as measured by the haplotype
diversity (h, the probability that two randomly chosen
haplotypes are different in a population sample) and
the average number of nucleotide differences between
all pairs of haplotypes in the sample (hp), was highest
in the western North Pacific Ocean (mitochondrial
h = 0.74, SD = 0.11, and hp = 7.44, SD = 0.11; nuclear
h = 0.75, SD = 0.14, and hp = 2.68, SD = 1.81) and South
Pacific Ocean (SP; mitochondrial h = 0.79, SD = 0.03,
and hp = 6.37, SD = 3.10; nuclear h = 0.73, SD = 0.09,
and hp = 1.64, SD = 1.15) regions, intermediate in the
North Atlantic Ocean (NA; mitochondrial h = 0.26,
SD = 0.12, and hp = 0.46, SD = 0.42; nuclear h = 0.71,
SD = 0.11, and hp = 1.02, SD = 0.82) and lowest in the
eastern North Pacific Ocean (ENP; mitochondrial
hp = 0.00; nuclear h = 0.49, SD = 0.18, and hp = 1.16,
SD = 0.91) (Figs 1 and 2). Overall, the relative levels of
genetic diversity for both loci were highly similar (see
Figs 1 and 2). No significant deviations from neutrality
were found in either locus (i.e. a = 0.05).
Mitochondrial haplotypes m15 and m12 were shared
between the NA and SP regions, although their
frequencies were dissimilar (Fig. 1). Haplotype m15 was
the dominant form in the NA, with a frequency of 0.86,
whereas only one specimen was found having the m12
variant. In the SP, these haplotypes represented two of
the three most common ones, with frequencies of 0.26
for m15 and 0.31 for m12. The rest of the haplotypes in
these regions represented private alleles, that is, variants
exclusive to a particular area. The haplotype from the
single specimen from the South Atlantic Ocean (SA)
region was a private allele. No haplotypes from the
North Pacific Ocean (NP) were shared with other
regions. Within the NP region, there was a clear break
between western and eastern subregions, separated by
the Alaska Peninsula. All haplotypes within these
subregions represented private alleles. Two dominant
haplotypes were found in the WNP, m2 and m7, with
frequencies of 0.5 and 0.21, respectively. In the ENP,
there was a single haplotype. In the ITS2 data set,
regional differences were less pronounced than in the
mitochondrial data set but, similarly, the haplotype
frequencies varied greatly among regions (Fig. 2).
Haplotypes i1 and i6 had near-cosmopolitan distributions. Haplotype i1 was found within all regions with
frequencies of 0.23 (NA), 0.67 [South Indian Ocean (SI)],
0.07 (SP), 0.25 (WNP) and 0.09 (ENP). Haplotype i6 was
found in specimens from the NA, SP and ENP, with frequencies of 0.15, 0.07 and 0.73, respectively. Haplotype
i2 was shared between NA and SP, being dominant in
both regions, with frequencies of 0.54 and 0.43, respectively. Lastly, haplotype i5 was found in both the NA
(frequency = 0.09) and the SI (frequency = 0.33). Private
alleles were found in the Pacific, with high frequencies
in the SP (i7, frequency = 0.36) and the NWP (i8,
frequency = 0.5), but none were found in the NA or SI.
No detectable differentiation in the haplotype distributions could be explained by depth differences (Fig. 5).
Haplotype accumulation curves revealed that the
global mitochondrial and nuclear ITS2 diversities have
not been fully sampled, as indicated by the steep slopes
of both lines (Fig. S9, Supporting information). Both
markers showed similar levels of diversity at given
sampling efforts, ITS2 being slightly lower than the
mitochondrial. When the individual genes in the
mitochondrial data set were examined individually, it
was clear that there are significant differences in their
contributions to overall diversity estimates and that a
single one does not capture the diversity found in the
combined mitochondrial marker. By far, the gene that
© 2012 Blackwell Publishing Ltd
0
0
500
500
Depth (m)
Depth (m)
PHYLOGEOGRAPHY OF DEEP-SEA CORAL PARAGORGIA ARBOREA 9
1000
1500
1000
1500
1 2 3
5 6 7 8 9 10 11 12 13 14 15 16
Mitochondrial haplotype
1
2
3
4
5 6 7 8
ITS2 haplotype
9
10 11
Fig. 5 The distribution of mitochondrial (left) and nuclear internal transcribed spacer 2 ITS2 (right) haplotypes of Paragorgia arborea
with depth. Individuals are represented by dots. Each haplotype is indicated by a different colour, as in Figs 1 and 2. The prefix m
denotes mitochondrial haplotypes, and the prefix i denotes nuclear ITS2 haplotypes (haplotype numbers are equivalent to the ones
in Table S1, Supporting information).
captures the largest mitochondrial diversity in terms of
haplotypes in P. arborea is nad6 (11), followed by nad2
(6), mtMutS (5), 16S (4) and cox1 (3). The combination of
nad6 and 16S captures 14 haplotypes, and the addition
of nad2 to these two regions captures all 16 haplotypes
found in the combined mitochondrial marker.
Discussion
The data and analyses generated in this study showed
that the morphospecies Paragorgia arborea can be defined
as a genealogical-phylospecies, in contrast to the
hypothesis that P. arborea represents a cryptic species
complex. Genetic variation in this lineage is correlated
with geographic location at the basin-scale level, but
not with depth. We present a phylogeographic hypothesis for P. arborea in which this independently evolving
lineage originates from the North Pacific, followed by
colonization of the Southern Hemisphere prior to
migration to the North Atlantic. We argue that this
hypothesis is consistent with the latest ocean circulation
model for the Miocene.
A globally distinct evolving lineage?
The distinction among species, incipient species and
structured populations in many deep-sea invertebrates
remains contentious due to the difficulties in defining
the species boundaries for certain groups and to the
paucity of the genetic, ecological and taxonomic data
available to date (Vrijenhoek 2009; McFadden et al.
2011). Commonly used species concepts (e.g. biological
species concept) have been traditionally developed in
terrestrial models. However, the biological and ecological information required to apply such concepts to deepsea organisms (e.g. reproductive success, behaviour) is,
at this time, impracticable to obtain. It is now recognized
that a combination of morphologic and phylogenetic criterions is most practical to discern among deep-sea coral
species (e.g. Herrera et al. 2010; Pante & Watling 2012).
© 2012 Blackwell Publishing Ltd
Here, we examined, for the first time, the compatibility of traditional taxonomical identifications and molecular information in a putative deep-sea coral species
at a global scale. The mitochondrial and nuclear gene
trees have congruent topologies, showing that alleles of
P. arborea have a common ancestor not shared with
other paragorgiid morphospecies. Thus, the morphospecies P. arborea is compatible with the genealogicalphylospecies concept. Furthermore, the branch lengths
among haplotypes of P. arborea are much shorter than
the branches among other putative species, which is to
be expected for genetic variability within a phylospecies. The only consistent morphological variant corresponds to the populations found in the NP, which were
previously referred as Paragorgia pacifica Verrill, 1922
but synonymized with P. arborea by Grasshoff (1979).
Individuals from these populations seem to have
reduced sclerite size and ornamentation when compared to the characteristics that defined P. arborea prior
to Grasshoff synonymizing the two (Sánchez 2005).
Our data do not support P. pacifica as a valid species
(see discussion below); we rather suggest that it may
represent a subspecies. Taken together, this evidence
indicates that P. arborea is a globally distinct lineage,
implying that identifications based on morphology can
accurately distinguish this taxon.
A complex of cryptic species?
The presence of cryptic species complexes has been
detected in various presumed widespread marine morphospecies (e.g. clams Goffredi et al. 2003; isopods
Raupach et al. 2007; limpets Johnson et al. 2008; gastropods Duda et al. 2009; Vrijenhoek 2009). Despite being
morphological indistinguishable, cryptic species have
been detected through molecular data, on the basis of
genetic dissimilarity. Here, we tested for the possibility
of cryptic species within the specimens of P. arborea, by
analysing the pairwise uncorrected genetic distances
among haplotypes using a DNA barcoding framework
10 S . H E R R E R A , T . M . S H A N K and J . A . S Á N C H E Z
based on the cox1 and mtMutS gene regions (see
McFadden et al. 2011). Under this framework, pairwise
uncorrected distances greater than 1% for mtMutS or
cox1 genes can be confidently used to indicate cryptic
species (McFadden et al. 2011). Based on this threshold,
the maximum intraclade distances (0.3% for mtMutS
and 0.9% for cox1) among specimens of P. arborea do
not suggest the presence of cryptic species. These
distances are consistent with the intraspecific distances
found within other paragorgiid species, for example
0.8% for mtMutS in Sibogagorgia cauliflora (Herrera et al.
2010). However, the suggested threshold is unidirectional, meaning that distances smaller than 1% do not
imply the absence of species boundaries. Additional
genetic and biological data are needed to test for this
possibility. The uniformity of predicted ITS2 secondary
structures and the absence of CBCs or hemi-CBCs are
also consistent with intraspecific levels of variation
(Muller et al. 2007; Coleman 2009; Ruhl et al. 2010).
However, similar to the mitochondrial barcoding
threshold discussed above, this criterion is also unidirectional; thus, the absence of cryptic species is not
implied (Coleman 2009). Lastly, the branching transition
points inferred by the GMYC likelihood method
indicate that the lineage of P. arborea is independently
evolving with a branching pattern characteristic of a
population-level coalescent process (Figs S7 and S8,
Supporting information). In summary, the levels and
patterns of genetic variability in mitochondrial and ITS2
loci do not provide actual evidence for cryptic species
boundaries within P. arborea.
Global patterns of genetic variation
Genetic diversity in P. arborea is not randomly distributed, as it would be expected under a scenario of global
panmixia. It is highest at the ENP and SP populations
and lowest at WNP and NA populations, as indicated
by the haplotype diversity and the average pairwise differences among alleles (Figs 1 and 2). The significantly
high global FST value (0.61 for the mitochondrial locus
and 0.39 for the ITS2, see Table 1) indicates that there
are significant differences in the genetic composition
among worldwide populations, when defined at the
basin/regional scale. This is consistent with the results
from other studies of deep-sea corals (e.g. Smith et al.
2004; Thoma et al. 2009; Miller et al. 2011; Morrison et al.
2011). However, to test over scales smaller than regional
for genetic structuring, it will be necessary to examine
larger numbers of independent, highly variable markers
(e.g. Le Goff-Vitry et al. 2004 and Morrison et al. 2011).
Regional geographic differences were sorted out by
comparing the FST values of genetic differentiation
among populations (Table 1). The pairwise differences
Table 1 Global and pairwise FST values for the mitochondrial
(top) and nuclear ITS2 (bottom) markers among populations of
Paragorgia arborea
Mitochondrial
FST global
NA
SP
WNP
ENP
Nuclear ITS2
FST global
NA
SP
WNP
ENP
SI
0.61
NA
SP
WNP
0.27
0.67
0.98
0.39
0.67
0.74
ENP
0.39
NA
SP
WNP
ENP
0.16
0.47
0.27
0.13
0.51
0.43
0.31
0.48
0.24
0.26
SI
NA, North Atlantic; SA, South Atlantic; SP, South Pacific;
WNP, western North Pacific; ENP, eastern North Pacific; SI,
South Indian Ocean; ITS2, internal transcribed spacer 2.
All values are significant (i.e. a = 0.05).
among populations for both markers suggest strong
differentiation between the EPN population and all the
other populations, including the neighbouring WNP.
There is also a significant break between North and
South Pacific populations. South Pacific and North
Atlantic populations are the less dissimilar, which
suggests a more recent connection between them.
Gene genealogies of P. arborea showed no reciprocal
monophyly of alleles among populations. Two nonexclusive and equally plausible mechanisms could have
lead to this observed pattern: (i) gene flow between
populations for which recent connectivity could be
conceived given a temporal continuity of favourable
environmental conditions, and (ii) incomplete lineage
sorting caused by a rapid succession of divergence
events among populations, combined with large ancestral effective population sizes (Maddison 1997; Edwards
2009). The earliest, divergent lineage of alleles as well
as the highest genetic diversity was found in the WNP,
which lends support to the idea that P. arborea originated in this region.
The nuclear ITS2 showed signs of lower genetic
differentiation among populations than the mitochondrial locus. The effects of differing effective population
sizes on processes such as genetic drift and genetic
sweeps could explain this difference given that the mitochondrial genome has one quarter the effective population size of the nuclear genome (given that it is haploid
and assuming maternal inheritance only). Similarly, the
nuclear gene tree had much lower resolution compared
© 2012 Blackwell Publishing Ltd
P H Y L O G E O G R A P H Y O F D E E P - S E A C O R A L P A R A G O R G I A A R B O R E A 11
to the mitochondrial one, which is likely due to the
smaller number of phylogenetically informative sites
present in the short ITS2 sequence.
In contrast to patterns observed in other deep-sea
organisms (Cho & Shank 2010; Etter et al. 2011; Miller
et al. 2011), depth does not appear to be an important
large-scale structuring factor in populations of
P. arborea. This is perhaps not surprising given the
widespread distribution of this organism, which suggests that it is capable of living under a relatively broad
range of conditions. Alternatively, as mentioned above,
small-scale genetic structuring related to depth could be
revealed with higher-resolution markers.
The mitochondrial nad6 gene contained the greatest
amount diversity in terms of haplotypes in this data
set, that is, was the most variable mitochondrial marker.
This result contrasts with previous studies, in which the
mtMutS gene has been found to be significantly more
variable than any other mitochondrial gene region
(France & Hoover 2001; McFadden et al. 2004, 2010;
Herrera et al. 2010). We suggest that the levels of variation among different mitochondrial gene regions in
octocorals vary among taxa (see McFadden et al. 2010,
2011; Bilewitch & Degnan 2011), and thus, there is not a
single universal region that provides the largest amount
of variability. For the samples of P. arborea examined
here, we found that the combination of nad6 + 16S
+nad2 is the most informative. The nuclear ITS2 still
seems to be a good cost-effective alternative to detect
genetic variation among individuals, in the absence of
intragenomic variants.
Phylogeographic hypothesis
Here, we suggest a phylogeographic scenario in which
P. arborea originated in the North Pacific, possibly in
the WNP followed by colonization of the South Pacific
and spreading eastward around the Southern Hemisphere in a stepping stone fashion (possibly via the
Antarctic Circumpolar Current). The colonization of the
North Atlantic seems to have occurred through a more
recent dispersal event from the South Pacific, via the
Central American Seaway, or from the SA. Similarities
between other deep-sea coral taxa from the South
Pacific and the North Atlantic have been independently
observed (Thoma et al. 2009; Pante & Watling 2012),
which gives support to the idea of a more recent
connection between South Pacific and North Atlantic
deep-sea communities. This scenario is an alternative to
the trans-Arctic interchange hypothesis (Vermeij 1991),
which suggests a recent North Pacific and North
Atlantic connection as indicated by the distributions of
several shallow-water taxa (e.g. red algae Vanoppen
et al. 1995; asteroids, bivalves, gastropods, barnacles
© 2012 Blackwell Publishing Ltd
Wares & Cunningham 2001; seagrass Olsen et al. 2004;
cnidarians Govindarajan et al. 2005).
Paragorgia arborea shares a similar phylogeographic
history and genetic diversity patterns with the spiny
dogfish Squalus acanthias (Verissimo et al. 2010) and the
bryozoan Membranipora membranacea (Schwaninger
2008), both of which have modern antitropical distributions. The time of divergence between the WNP and
South Pacific populations of the spiny dogfish has been
estimated to be around 7.8 Myr BP and approximately
13.3 Myr BP (9.9–21.9) for the bryozoan, which is comparable to our estimates of 4.5 Myr BP (95% CI = 2.0–
8.3 using the coalescent model) and 8.1 Myr BP (95%
CI = 3.6–15.3 using the Yule model) for P. arborea
(Fig. 4, Figs S7 and S8, Supporting information). The
timing of colonization of the North Atlantic has been
estimated to be between 3.6 and 5.3 Myr BP for the
dogfish, 6.2 Myr BP (95% CI = 4.6–10.2) for the bryozoan and between 1.7 Myr BP (95% CI = 0.4–3.6) and
4.0 Myr BP (95% CI = 1.3–8.3) for P. arborea. The similar
and independently estimated times for these events
give support to the idea that a common set of oceanographic conditions in the Miocene and early Pliocene
lead to the current distributions of these species. The
latest Miocene ocean circulation models (Butzin et al.
2011) indicate that there was a dominant southward
horizontal flow that carried deep waters from the WNP
to the South Pacific, passing along the eastern side of
the New Zealand landmass, during the mid- to late
Miocene (~5–15 Myr BP). This flow decreased during
the late Miocene. The Antarctic Circumpolar Current
started to develop during the mid- to late Eocene (ca. 37
–40 Myr BP) (Scher 2006) and thus was already well
established as the dominant feature of ocean circulation
during the Miocene, transporting massive amounts of water
eastward. At the same time, during the mid-Miocene,
the deep-water formation in the North Atlantic and its
southward flow were absent or weak, likely due to the
dominant barotropic water flux from the Pacific to the
Atlantic. The formation of deep water in this time period mainly took place in the Southern Ocean. Deepwater formation in the North Atlantic and the dominant
southward flow, as we know them today, were later
established during the late Miocene as the Central
American Seaway closed (Butzin et al. 2011). Evolutionary migrations inferred from genetic diversity patterns
presented here for P. arborea are consistent with this
history of ocean circulation. Historical changes in the
global patterns of ocean circulation and climate may
have caused shifts in the habitat and thus the distribution of P. arborea. Widespread ocean cooling during glacial periods in the late Miocene–early Pliocene (Mercer
& Sutter 1982) and throughout the Quaternary (Ehlers
et al. 2011) could have aided the trans-equatorial
12 S . H E R R E R A , T . M . S H A N K and J . A . S Á N C H E Z
exchange by increasing the area of suitable habitat for
stepping stone populations towards the tropics (McIntyre et al. 1989). Isolated relict low-latitude populations
might still exist. We hypothesize that the described set
of conditions could explain the current distribution
patterns of many other marine taxa (e.g. deep-sea coral
associates, such as ophiuroids and chirostylid crabs)
and thus might have played an important role shaping
extant deep-sea faunal diversity.
Acknowledgements
Support for this study was generously provided by a
mini-grant from the Global Census of Marine Life on
Seamounts Project (CenSeam) to J.A.S. and S.H., a grant from
the Facultad de Ciencias, Department of Biological Sciences of
the Universidad de los Andes to J.A.S, the National Systematics Laboratory of NOAA’s National Marine Fisheries Service,
a Smithsonian Graduate Student Fellowship to S.H., an award
from the Systematics Research Fund of the Systematics Association and the Linnean Society of London to S.H., and a Grantin-Aid of Research from the Sigma Xi Research Society to S.H.
We are especially thankful to S.D. Cairns, A.G. Collins, C.L.
Agudelo, N. Ardila, L. Dueñas, A. Ormos, J. Hunt, L. Weigt,
L. Monroy, M. Herrera and M. Sangrey for their generous
support, assistance and advise. Laboratory work was performed at the Laboratories of Analytical Biology NMNH,
Smithsonian Institution and BIOMMAR, Universidad de los
Andes. Samples were generously provided by P. Alderslade
(CSIRO), A. Andouche (MNHN), A. Andrews (MLML), A.
Baco (FSU), A. Baldinger (MCZ), J. A. Boutillier (DFO), S.D.
Cairns (USNM), S. Davies (DFO), M. Eriksson (UUZM), Y.
Imahara (WPMNH), D. Janussen (SMF), E. Lazo-Wasem
(YPM), P. Lozouet (MNHN), L. Lundsten (MBARI), S. Mills
(NIWA), K. Schnabel (NIWA), and B. Stone (NOAA), D. Tracey (NIWA), and R. Weber (Te Papa Tongarewa). We also
thank J. McDermott, N. Roterman and C. Munro for their
comments on earlier versions of the manuscript. We are grateful for the helpful input from the editor and two anonymous
reviewers.
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Data accessibility
Sample information and locations are provided as
supporting information in Table S1 (Supporting information).
DNA sequences are available in GenBank and accession numbers appear in Table S1 (Supporting information).
DNA sequence alignments are available in DRYAD
doi:10.5061/dryad.ns23j.
Supporting information
Additional Supporting Information may be found in the online version of this article.
Appendix S1 Sequencing of old samples.
Table S1 Collection and sequence information for the specimens used in this study.
Table S2 Nucleotide substitution models for mitochondrial
gene partitions, as selected by the AIC criterion in JMODELTEST.
Table S3 Interspecific and intraspecific (i.e. coalescent depths)
uncorrected pairwise distances (%) among haplotypes of species of Paragorgia and Sibogagorgia.
Fig. S1 Sampling location of specimens of Paragorgia arborea
examined in this study.
Fig. S2 Depth distribution of samples shown in Fig. S1 (Supporting information).
Fig. S3 The revised geographic distribution of Paragorgia arborea.
Fig. S4 Depth distribution of records shown in Fig. S3 (Supporting information).
Fig. S5 Predicted ITS2 secondary structure of Paragorgia arborea.
Fig. S6 Individual mitochondrial gene tree hypotheses in Paragorgia.
Fig. S7 Fit of the GMYC single-threshold model to the mitochondrial time-calibrated gene tree generated with the Yule
model tree prior.
Fig. S8 Fit of the GMYC single-threshold model to the mitochondrial time-calibrated gene tree generated with the coalescent model tree prior.
Fig. S9 Haplotype accumulation curves in Paragorgia arborea.