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. 2014 Apr 25;4(11):2070–2081. doi: 10.1002/ece3.1033

Wider sampling reveals a non-sister relationship for geographically contiguous lineages of a marine mussel

Regina L Cunha 1,†, Katy R Nicastro 1,†, Joana Costa 1, Christopher D McQuaid 2, Ester A Serrão 1, Gerardo I Zardi 1,2
PMCID: PMC4201422  PMID: 25360249

Abstract

The accuracy of phylogenetic inference can be significantly improved by the addition of more taxa and by increasing the spatial coverage of sampling. In previous studies, the brown mussel Perna perna showed a sister–lineage relationship between eastern and western individuals contiguously distributed along the South African coastline. We used mitochondrial (COI) and nuclear (ITS) sequence data to further analyze phylogeographic patterns within P. perna. Significant expansion of the geographical coverage revealed an unexpected pattern. The western South African lineage shared the most recent common ancestor (MRCA) with specimens from Angola, Venezuela, and Namibia, whereas eastern South African specimens and Mozambique grouped together, indicating a non-sister relationship for the two South African lineages. Two plausible biogeographic scenarios to explain their origin were both supported by the hypotheses-testing analysis. One includes an Indo-Pacific origin for P. perna, dispersal into the Mediterranean and Atlantic through the Tethys seaway, followed by recent secondary contact after southward expansion of the western and eastern South African lineages. The other scenario (Out of South Africa) suggests an ancient vicariant divergence of the two lineages followed by their northward expansion. Nevertheless, the “Out of South Africa” hypothesis would require a more ancient divergence between the two lineages. Instead, our estimates indicated that they diverged very recently (310 kyr), providing a better support for an Indo-Pacific origin of the two South African lineages. The arrival of the MRCA of P. perna in Brazil was estimated at 10 [0–40] kyr. Thus, the hypothesis of a recent introduction in Brazil through hull fouling in wooden vessels involved in the transatlantic itineraries of the slave trade did not receive strong support, but given the range for this estimate, it could not be discarded. Wider geographic sampling of marine organisms shows that lineages with contiguous distributions need not share a common ancestry.

Keywords: Independent origin, Perna perna, phylogeographic patterns, wider sampling

Introduction

Increased taxon sampling recognizably improves phylogenetic inference (Hillis 1996) while in ecology, the understanding of distribution patterns depends critically on the scales at which observations are made (Wiens 1989; Rahbek 2005). The analysis of a small subset of species that are presumed to be representative can distort phylogenetic relationships (Tuinen et al. 2000; Murphy et al. 2001). This can be mitigated by large sequence data sets that improve the accuracy of phylogenetic estimation (Poe and Swofford 1999; Heath et al. 2008), but using only a few representatives from a particular group can produce misleading results and incorrect topologies even with increased sequence length (Zwickl and Hillis 2002; Heath et al. 2008).

Here, we evaluated the effect of increasing the scale of geographic sampling on the reconstruction of phylogenetic and phylogeographic patterns. As a model system, we used marine mussels of the genus Perna, focusing on the South African coastline, where three main biogeographic regions exist across a wide range of climatic and oceanographic conditions (Harrison 2002). These regions have been defined by the rocky shore biota and include a cool-temperate west coast, a warm-temperate south coast, and a subtropical east coast (Stephenson and Stephenson 1972; Emanuel et al. 1992). The genus Perna comprises three currently recognized species of intertidal mussels: P. perna, P. canaliculus, and P. viridis. A previous phylogenetic study of the genus based on the mitochondrial cytochrome oxidase subunit I (COI) gene and the internal transcribed spacers of the nuclear ribosomal RNA coding region (ITS) showed that a fourth putative species, P. picta, clustered within the P. perna clade and thus, was not a valid taxon (Wood et al. 2007).

Perna perna Linnaeus, 1758 has a wide distribution, occurring in warm-temperate regions of the Atlantic, Mediterranean Sea, and Indian Ocean, including the western and east coasts of South Africa, and has recently become invasive in the Gulf of Mexico ((Hicks and Tunnell 1993); Fig. 1). The absence of fossil records of P. perna in Brazil suggests a recent introduction in this area (Silva and Barros 2011), and it has been claimed that the presence of brown mussels in Brazil could have resulted from the hull fouling in wooden vessels involved in the transatlantic itineraries of the slave trade (Souza et al. 2008), the so-called “Slave Route” (Harris 2006).

Figure 1.

Figure 1

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Geographical distribution and sampling locations of the species within the genus Perna (P. viridis, P. perna and P. canaliculus) used in this study. Sampling location codes are further explained in Table 1. The inset shows the main oceanic currents in the studied area.

Phylogeographic studies focusing on South African coastal species (e.g., estuarine crustaceans (Teske et al. 2008, 2006), limpets (Ridgway et al. 2006), and intertidal mussels (Zardi et al. 2007, 2011)) have identified remarkable barriers to gene flow located at the borders of these biogeographic regions. Overall, the reconstructed phylogeographic patterns have included either cold-water (west) versus warm/subtropical (southeastern) or warm-temperate (south) versus subtropical (east) sister–lineage relationships (Ridgway et al. 2006; Teske et al. 2006, 2008). In South African P. perna, a western and an eastern lineages were identified (Zardi et al. 2007), suggesting that two sister lineages have diverged in response to sharp ecological/oceanographic barriers.

Phylogenetic and phylogeographic studies of P. perna have thus far comprised a smaller coverage of its geographic distribution, including either only specimens from Brazil, Venezuela, and the east coast of South Africa (Wood et al. 2007), or South African and Namibian specimens (Zardi et al. 2007). We expanded intraspecific sampling to evaluate whether the addition of specimens from almost the entire range of P. perna, and the inclusion of congeneric species, would affect interpretation of the phylogeography of the species, particularly the questions that remain unanswered regarding its colonization across the Southern Atlantic. We used the same molecular markers (COI and ITS) as Wood et al. (2007) to allow comparison. We also performed a Bayesian molecular clock dating analysis using two independent partitions (COI and ITS) and unlinked evolutionary models as implemented in Beast (Drummond et al. 2012) to date lineage-splitting events within the genus Perna.

Our goals were: (1) to assess the impact of increasing taxon and geographic extent of sampling on our perception of the genetic boundaries of a marine organism; (2) to date the main lineage-splitting events within the genus Perna, particularly focusing on the origin of the two South African lineages of P. perna, and (3) to test alternative hypotheses and establish a phylogeographic scenario for the origins of the two South African lineages.

Materials and Methods

Specimen collection, DNA extraction, amplification, and sequencing

A total of 31 specimens of the brown mussel P. perna were collected from eight different locations that included the Mediterranean, Gulf of Oman, Angola, Namibia, Mozambique, and South Africa (see Table 1 for further details). All specimens were preserved in 96% ethanol. Sequences of other species within the genus Perna (P. viridis and P. canaliculus) were retrieved from the GenBank (Table 1).

Table 1.

List of species used in this study, sample location, and GenBank accession numbers. In bold, sequences from this study

GenBank accession no.
Species Code Location COI ITS
Perna perna Tunisia1 Tunisia – Bizerte KC691986 KC692016
Perna perna Tunisia2 Tunisia – Bizerte KC691987 KC692017
Perna perna Tunisia3 Tunisia – Bizerte KC691988 KC692018
Perna perna Tunisia4 Tunisia – Bizerte KC691989 –
Perna perna W South Africa1 South Africa – Gans Bay KC691990 KC692019
Perna perna W South Africa2 South Africa Gans Bay KC691991 KC692020
Perna perna W South Africa3 South Africa Gans Bay KC691992 –
Perna perna W South Africa4 South Africa Gans Bay KC691993 –
Perna perna W South Africa5 South Africa Plettenberg KC691994 KC692021
Perna perna W South Africa6 South Africa Plettenberg KC691995 KC692022
Perna perna W South Africa7 South Africa Plettenberg KC691996 KC692023
Perna perna W South Africa8 South Africa Plettenberg KC691997 KC692024
Perna perna E South Africa1 South Africa Umhlanga KC691998 KC692025
Perna perna E South Africa2 South Africa Umhlanga KC691999 KC692026
Perna perna E South Africa3 South Africa Umhlanga KC692000 KC692027
Perna perna E South Africa4 South Africa Umhlanga – KC692028
Perna perna E South Africa5 Eastern South Africa DQ917618 DQ924559
Perna perna E South Africa6 Eastern South Africa DQ917617 –
Perna perna E South Africa7 Eastern South Africa DQ917616 –
Perna perna Angola1 Angola – Luanda KC692001 KC692029
Perna perna Angola2 Angola – Luanda KC692002 KC692030
Perna perna Angola3 Angola – Luanda KC692003 –
Perna perna Angola4 Angola – Luanda KC692004 –
Perna perna Namibia1 Namibia – Swakopmund KC692005 KC692031
Perna perna Namibia2 Namibia – Swakopmund KC692006 KC692032
Perna perna Namibia3 Namibia – Swakopmund KC692007 –
Perna perna Namibia4 Namibia – Swakopmund KC692008 –
Perna perna Mozambique1 Mozambique – Punta D'Ouro KC692009 KC692033
Perna perna Mozambique2 Mozambique – Punta D'Ouro KC692010 KC692034
Perna perna Mozambique3 Mozambique – Punta D'Ouro KC692011 KC692035
Perna perna Mozambique4 Mozambique – Punta D'Ouro KC692012 KC692036
Perna perna Oman1 Oman – Muscat KC692013 KC692037
Perna perna Oman2 Oman – Muscat KC692014 KC692038
Perna perna Oman3 Oman – Muscat KC692015 –
Perna perna Venezuela1 Venezuela DQ917588 DQ924543
Perna perna Venezuela2 Venezuela DQ917587 DQ924542
Perna perna Brazil1 Brazil – Santa Catarina DQ917594 DQ924547
Perna perna Brazil2 Brazil – Santa Catarina DQ917593 –
Perna perna Brazil3 Brazil – São Paulo DQ917592 DQ924546
Perna perna Brazil4 Brazil – São Paulo DQ917591 DQ924545
Perna perna (former P. picta) Morocco1 Morocco DQ917603 –
Perna perna (former P. picta) Morocco2 Morocco DQ917602 –
Perna perna (former P. picta) Morocco3 Morocco DQ917601 –
Perna perna (former P. picta) Morocco4 Morocco DQ91760 –
Perna perna (former P. picta) Mauritania1 Mauritania DQ917597 DQ924548
Perna perna (former P. picta) Mauritania2 Mauritania DQ917596 –
Perna perna (former P. picta) Mauritania3 Mauritania DQ917595 –
Perna canaliculus New Zealand1 New Zealand DQ917607 DQ924551
Perna canaliculus New Zealand2 New Zealand DQ917613 DQ924556
Perna canaliculus New Zealand3 New Zealand DQ917608 DQ924552
Perna canaliculus New Zealand4 New Zealand DQ917609 DQ924553
Perna viridis India1 India DQ917612 DQ924555
Perna viridis India2 India DQ917611 DQ924554
Perna viridis India3 India DQ917610 –
Perna viridis India4 Southern India DQ917586 DQ924541
Perna viridis India5 Southern India DQ917585 DQ924540
Perna viridis Philippines1 Philippines DQ917599 DQ924550
Perna viridis Philippines2 Philippines DQ917598 DQ924549
Perna viridis Thailand1 Thailand DQ917590 DQ924544
Perna viridis Thailand2 Thailand DQ917589 –
Perna viridis Vietnam1 Vietnam DQ917584 DQ924539
Perna viridis Vietnam2 Vietnam DQ917583 DQ924538
Aulacomya atra maoriana – New Zealand DQ917614 DQ924558
Mytilus galloprovincialis – New Zealand DQ917605 –
Mytilus edulis – UK – Wales DQ917606 AY695798
Modiolus areolatus – New Zealand DQ917604 –
Xenostrobus pulex – New Zealand DQ917582 –
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Total genomic DNA was isolated from muscle tissue (foot) using the cetyltrimethylammonium bromide (CTAB) protocol (Doyle and Doyle 1987). Universal primers from Folmer et al. (1994) were used to amplify a portion (approximately 650 bp) of the mitochondrial COI gene. In addition, a partial fragment of ribosomal DNA spanning 18S, internal transcribed spacer 1 (ITS1), 5.8S, ITS2, and 28S rRNA was amplified using primers ITS5 (White et al. 1990) and ITS28 cc of Wagstaff and Garnock-Jones 1998. Amplification protocols for the ITS and COI fragments are described in Wood et al. 2007 and Zardi et al. 2007, respectively. Sequences were deposited in GeneBank under the accession numbers given in Table 1.

Sequence alignment and phylogenetic analyses

DNA sequences were aligned with Mafft v5 (Katoh and Toh 2010) using the auto option that automatically selects the appropriate strategy according to data size. To perform phylogenetic analyses, three different data sets were analyzed: (1) partial nucleotide sequences of the mitochondrial COI of 66 specimens representing three species of the genus Perna (P. perna, P. viridis, and P. canaliculus) and five out-groups (Mytilus edulis, M. galloprovincialis, Aulacomya atra maoriana, Modiolus areolatus, and Xenostrobus pulex – GenBank accession numbers in Table 1) produced an alignment of 623 base pairs (bp); (2) nuclear ITS sequences of 45 mussels representing the three Perna species and the out-group A. atra maoriana produced an alignment of 865 bp, and (3) a concatenated data set with partial nucleotide sequences of the mitochondrial COI and the nuclear sequences of 42 mussels representing the three Perna species and the outgroup Mytilus edulis produced an alignment of 1580 bp. The selection of out-group taxa was based on previous work by Wood et al. (2007).

The Akaike information criterion (AIC) (Akaike 1973) implemented in Modeltest v.3.7 (Posada and Crandall 1998) was used to determine the evolutionary models that best fitted the data sets. Bayesian inferences (BI) based on the three data sets were conducted with MrBayes v3.2.1 (Ronquist et al. 2012). Four Metropolis-coupled Markov chain Monte Carlo (MCMC) analyses were run for two million generations, and sampled every 100 generations. Two independent runs were performed for each data set. The three data sets were analyzed under the GTR+Γ, the best-fit model selected by Modeltest. The burn-in was set to 120,000 generations for the mitochondrial and nuclear data sets, and to 100,000 steps for the concatenated data set. Robustness of the inferred trees was evaluated using Bayesian posterior probabilities (BPPs). Maximum likelihood (ML) analyses were performed with PhyML v2.4.4 (Guindon and Gascuel 2003) using the three data sets and parameters obtained with Modeltest. The robustness of the inferred trees was tested by nonparametric bootstrapping (BP) using 1000 pseudoreplicates.

Testing alternative biogeographic scenarios

Approximately unbiased (AU) (Shimodaira 2002), the Kishino–Hasegawa (KH) (Kishino and Hasegawa 1989), and the Shimodaira–Hasegawa (SH) (Shimodaira and Hasegawa 1999) tests were used to evaluate different topologies representing alternative scenarios (see the discussion for further details on the alternative biogeographic scenarios) for the origin of P. perna in South Africa based on the ML topology obtained with the combined data set (42 taxa, 1488 bp). The null hypothesis is that the ML topology is identical to the alternative scenarios. Tests were performed using PaML (Yang 2007) and Consel (Shimodaira and Hasegawa 2001).

Dating analysis and species tree inference

We used a Bayesian relaxed molecular clock approach as implemented in Beast v1.7.4 (Drummond et al. 2012) to date lineage-splitting events within the genus Perna. We used a Yule tree prior that assumes a constant speciation rate among lineages. This method allows the incorporation of fossil uncertainties because it uses probabilistic calibration priors instead of point calibrations (Drummond et al. 2006).

Mitochondrial COI (16 taxa, 617 bp) and nuclear ITS (16 taxa, 963 bp) data sets were treated as two independent loci with independent substitution models as selected by Modeltest (COI: TN93+Γ; ITS: GTR+Γ), but sharing a single tree partition. Two calibration points were provided by placing a lognormal prior distribution on the age estimate for the divergence between Perna and Mytilus (mean in real space: 0.47, log standard deviation = 0.423 and Offset = 37.2; interval: 40.4–37.2 myr) and between P. canaliculus and P. perna (mean in real space: 0.3, log standard deviation = 0.422 and Offset = 2.6; interval: 5.3–2.6 myr). The first calibration point was based on the approximate age of a fossil found in the Antarctic Peninsula, Seymour Island from the Lower Eocene [40.4–37.2] myr assigned to the genus Perna (Stilwell and Zinsmeister 1992). The second calibration was based on a fossil of P. canaliculus from the Pliocene [5.3–2.6] myr from New Zealand (Beu 2004).

MCMC analyses were run for 900,000,000 generations with a sample frequency of 10,000, following a discarded burn-in of 9,000,000 steps. The convergence to the stationary distributions was confirmed by inspection of the MCMC samples using Tracer v1.5 (Rambaut et al. 2013).

All dating analyses were performed on the CCmar Computational Cluster Facility (http://gyra.ualg.pt) at the University of Algarve.

Results

Phylogenetic relationships of Perna mussels

Potential scale reduction factors in Bayesian analyses (all data sets) were about 1.00, indicating convergence of the runs (Gelman and Rubin 1992). BI and ML analyses based on the concatenated dataset recovered identical topologies with the single exception that the relative phylogenetic position of P. viridis as the sister species to the remaining Perna received no statistical support in the latter. BI analysis based on the concatenated dataset recovered three well-supported clades within P. perna (Fig. 2), whereas only a single clade was recovered in the nuclear-based BI analyses (Material S2). The three clades included specimens from: (1) Tunisia, Morocco, Mauritania, and Brazil; (2) Venezuela, western South Africa, and Namibia, and (3) eastern South Africa and Mozambique. Specimens from Oman were recovered as the sister group of the remaining P. perna (Fig. 2).

Figure 2.

Figure 2

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Phylogenetic relationships of the currently recognized species within the genus Perna. The Bayesian topology based on a combined data set (mitochondrial COI and nuclear ITS) is shown. Numbers above and below nodes are ML bootstrap values and Bayesian posterior probabilities, respectively. Gray boxes indicate western and eastern South African lineages. The inset shows phylogeographic patterns of diversification within P. perna.

In the ML analyses based both on COI (Material S1) and nuclear (Material S2) data sets, the relative phylogenetic position of Oman individuals remained unresolved.

Testing alternative biogeographic scenarios

Results of AU, SH, and KH tests of alternative tree topologies are summarized in Table 2. All three tests rejected the alternative scenario that indicates a west-to-east colonization of the Atlantic, whereas the “Out of South Africa” (Fig. 3) hypothesis could not be rejected by any of the tests (P > 0.05).

Table 2.

Log-likelihood and P values of Approximately Unbiased (AU), Shimodaira–Hasegawa (SH), and Kishino–Hasegawa (KH) tests for each of the alternative biogeographic scenarios. The first topology corresponds to the optimal ML tree based on the concatenated data set. Topologies are rejected at the 5% significance level

Scenarios Alternative topologies −log L AU SH KH
ML tree (((clade1, clade2), clade3), clade4); 5885.8 0.944 0.973 0.929
“Out of South Africa” ((clade1, clade2), (clade3, clade4)); 5891.5 5.60E-02 4.20E-01 7.10E-02
West-to-east colonization (((((((WSA,BRA),NAM),(VEN,ANG)),(TUN,MAU)),ESA),OMA)); 5970.3 1.00E-06 4.00E-05 4.00E-05
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ANG, Angola; BRA, Brazil; ESA, eastern South Africa; MAU, Mauritania; NAM, Namibia; OMA, Oman; TUN, Tunisia; VEN, Venezuela; WSA, western South Africa.

Figure 3.

Figure 3

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Alternative biogeographic scenarios for the origins of the two South African Perna perna lineages.

Dating analyses

The ultrametric tree obtained from the Beast analysis showed effective sample size values >200, which indicates convergence of the runs. Age estimates showed narrow confidence intervals, which reflects the accuracy of the analysis.

Perna viridis diverged from the remaining Perna species between 8.8 myr ago, and P. canaliculus at 4.5 myr (Fig. 4). The age of the most recent ancestor common to both South African lineages was estimated at 310 [200–500] kyr. The origin of the eastern and western South African lineages was estimated at 60 kyr. The age of the MRCA of the Brazilian lineage of P. perna was estimated at 10 [0–40] kyr.

Figure 4.

Figure 4

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Maximum clade credibility chronogram obtained with Beast showing divergence dates of main splitting events within the genus Perna. Age estimates were based on two partitions of the data set (mitochondrial COI and nuclear ITS) with independent evolutionary models (COI: TN93+Γ; ITS: GTR+Γ). Gray boxes indicate western and eastern South African lineages. The inset shows age estimates (in million years) of the splitting events within P. perna.

Discussion

The novel geographical coverage analyzed in this paper revealed a complex evolutionary history of Perna perna that would have been incorrectly inferred by analyses at regional scales that miss the global evolutionary history. The results suggest a non-sister relationship for the two South African lineages and anthropogenic introduction in Central and South America through the slave trade routes, resulting in a complex spatial mosaic of populations.

Effect of increasing geographic sampling on the reconstructed phylogenetic patterns

The most significant finding from our study is the existence of an independent origin for the eastern and western South African lineages of P. perna as they were not recovered as sister groups in any of the analyses performed here. Thus, setting these two lineages in a larger taxonomic and geographic context has completely altered our understanding of their evolutionary history.

Despite the relatively long larval period of the brown mussel P. perna (assumed to be similar to that of Mytilus edulis at 15–20 days with a maximum of 40 days, (Bayne 1975)), a strong phylogeographic break has been observed on the South African coastline, and interpreted as indicating a sister–lineage relationship between eastern and western populations (Zardi et al. 2007). Similar genetic discontinuities in other invertebrates have been found within this region, again interpreted as sister–lineage relationships (e.g., (Teske et al. 2007, 2006). Such patterns suggested differentiation across a sharp environmental barrier, but are also compatible with the alternative hypothesis that this area represents a contact zone between independently evolved lineages.

Using a wider context, our reconstructed major clades included a sister relationship between specimens from Tunisia, Mauritania, and Brazil (Clade 1) and western South Africa, Angola, Namibia, and Venezuela (Clade 2). Clade 3 was composed of specimens from eastern South Africa grouping together with Mozambique (Fig. 2). Given the geographical proximity of the two South African lineages, and previous results that showed a sister–lineage relationship between them (Zardi et al. 2007), this is a completely unexpected pattern. Thus far, all studies involving South African phylogeographic breaks either comprised representatives exclusively from this region (Grant et al. 1992; Ridgway et al. 2006; Teske et al. 2006, 2007) or also included specimens from Namibia (Zardi et al. 2007). The wider coverage of the geographic distribution of P. perna presented here revealed a very different phylogeographic pattern for the species. Further studies are required to determine whether extending the geographic coverage of sampling would yield similar results for other marine organisms.

Slave trade routes and present-day distribution of P. perna

The transatlantic slave trade started in the 15th century and lasted more than 500 years. More than 30 million people were exchanged between Africa and three continents (North and South America, and Europe). Slave trade routes during the 15th and 16th centuries were predominantly from northwestern Africa (Senegal and Gambia) to the Caribbean and Brazil (Beckles 2002; Harris 2006). In the following centuries (17th, 18th, and 19th), routes moved toward the South with intense slave trade between central west Africa (Angola, Equatorial Guinea, and Congo), Brazil and the Caribbean (Beckles 2002; Harris 2006).

If the introduction of P. perna to Brazil and the Caribbean (Venezuela) is to be explained by the “Slave Trade Route” hypothesis (Souza et al. 2008), based on the above itineraries, colonization of this area could have been either from northwestern Africa (Senegal and Gambia) or from central west Africa (Angola). To establish the following colonization pathways, some assumptions were made. Given the vicinity to Senegal, where most of the departures to the Caribbean region occurred, we assumed that P. perna from Mauritania could also have colonized the Caribbean (Venezuela). The same assumption is valid for Namibia due to its proximity to Angola.

The colonization of Brazil from northwestern Africa is expected to generate a topology in which specimens from Brazil and Mauritania group together. Alternatively, if the colonization occurred from central west Africa, this is the expected phylogenetic tree: (Brazil, (Angola, Namibia)). If colonization of the Caribbean (Venezuela) was from northwestern Africa or from the central west Africa, the two possible topologies are: (Venezuela, Mauritania) or (Venezuela, (Angola, Namibia)), respectively.

Our phylogenies (Figs. 2 and 4) always revealed two clades: the first included Brazil and Mauritania (Clade 1); the second clade included Venezuela, Angola, Namibia, and western South Africa (Clade 2). Thus, our results indicate colonization of Brazil from Mauritania, which is consistent with one of the alternative scenarios (northwestern Africa – Mauritania vs. central west Africa – Angola). Our dating analyses (Fig. 4) estimated the origin of the MRCA of the Brazilian P. perna populations at about 10 kyr. This seems to contradict the hypothesis of a relatively recent (±500 years) introduction to Brazil. However, the confidence interval for this estimate was between 0 and 40 kyr, which encompasses the last 500 years. Given the different topologies obtained with Bayesian dating estimates or with BI analyses, the colonization of Venezuela remains uncertain.

There has been an increasing controversy regarding the estimation of mutation rates in recently diverged populations due to the existence of “time-dependency” that can cause an overestimation of rates (Ho et al. 2005, 2011). Consequently, given their recent divergence, our estimates for the P. perna lineages might be increased, making the recent introduction of the brown mussel to Brazil through the slave routes more plausible.

Biogeographic scenarios for the origin of the two South African lineages of P. perna

Our phylogenetic analyses suggest that the origin of the two South African lineages may be explained by more than one biogeographic scenario (Fig. 3).

  • Scenario (1): an Indo-Pacific origin for P. perna, dispersal into the Mediterranean and Atlantic through the Tethys seaway, and recent secondary contact after southward expansion of the western and eastern South African lineages.

  • Scenario (2), “Out of South Africa”: The occurrence of an historical vicariance event separated the two South African lineages, which then expanded northward into the Atlantic and Indo-Pacific.

  • Scenario (3): a west-to-east colonization of the Atlantic from the southern Indo-Pacific around Antarctica via the Antarctic Circumpolar Current (ACC) to South America, followed by expansion out of Brazil into southwestern Africa and the Mediterranean.

The rooted phylogeny from Figure 2 is consistent with an Indo-Pacific origin for P. perna and dispersal into the Mediterranean. The idea that the dispersal of Perna mussels between the Indo-Pacific and the Atlantic occurred through the Mediterranean by the Tethys seaway – scenario (1) – was previously proposed by Wood et al. (2007). According to our results, the MRCA of the genus occurred at 8.8 [6.7–11] myr (Fig. 4). This age estimate predates the final closure of the Tethys seaway, which remained intermittently open until the Late Miocene, 6.7 myr ago (Sonnenfeld 1985; Robba 1987). This would have allowed the colonization of the Atlantic through the Mediterranean before the closure of all connections.

Angolan and Namibian specimens grouped with the western South African lineage (clade 2), which is consistent with a southward expansion, but could also be interpreted as northward colonization. The simplest explanation for the presence of Perna in Venezuela is its introduction through the slave trade routes, as previously mentioned. The origin of the eastern South African lineage can be explained by southward dispersal from the Indian Ocean through the Agulhas Current. Our estimate for the origin of this lineage (60 kyr, Fig. 4) is consistent with the timing of the formation of this oceanographic system (5 myr ago, (Lutjeharms 2006)).

Scenario (2), in which remnants of an old vicariance event dispersed northwards into the Atlantic and the Indo-Pacific would require a sister relationship between the western and eastern South African lineages. Instead, clade 2 (western South Africa, Namibia, Angola, and Venezuela) grouped with clade 1 (Tunisia, Mauritania, and Brazil), which seems to reject this hypothesis. However, AU, SH, and KH tests indicated that the topology that supports this scenario is not significantly different from our ML topology representing the Indo-Pacific origin for the two South African lineages (Table 2 and Fig. 3) and thus, the “out of South Africa” hypothesis (scenario 2) is not rejected.

Under scenario (3), we would expect that specimens from Brazil would group with the western South African lineage, Angola, and Namibia. Instead, in both BI and ML analyses, Brazil clustered with Mauritania and Tunisia (clade 1, Figs. 2 and 4). Nevertheless, clade 1 is the sister group of clade 2 (western South Africa, Angola, and Namibia), which provides some support for a west-to-east colonization of the Atlantic via the ACC. However, the AU, KH, and SH tests clearly rejected the west-to-east colonization of the Atlantic (Table 2).

Conclusions

Our findings are significant by showing that the inclusion of a wider geographical range of sampling and of additional taxa resulted in a radical rethinking of the relationship between coexisting lineages of our study organism. We used mitochondrial and nuclear markers in our analyses, and the sampling strategy included almost the entire geographic distribution of P. perna. Previous studies of the brown mussel P. perna showed the existence of a sister–lineage relationship between specimens from eastern and western South Africa. In contrast, the reconstructed phylogenetic patterns presented here show an unexpected pattern in which the western lineage groups with Angola, Venezuela, and Namibia and shares the MRCA with specimens from Mauritania, Brazil, and Tunisia instead of grouping with eastern South African specimens.

Two plausible biogeographic scenarios can explain the origin of the western and eastern South African lineages. One includes a recent secondary contact in South Africa after southward expansion through the Tethys seaway. The other suggests an ancient vicariant event that caused the split between the two South African lineages followed by their northward dispersal into the Atlantic and Indo-Pacific basins. With present data is not possible to distinguish between these competing hypotheses, but we would expect a more ancient divergence between the eastern and western South African lineages according to the “Out of South Africa” scenario. Instead, we obtained a very recent estimate for the divergence between the two lineages, providing better support for the Indo-Pacific origin of the two South African lineages.

The hypothesis of a recent introduction in Brazil through hull fouling in wooden vessels involved in the transatlantic itineraries of the slave trade did not receive strong support, but could not be discarded.

Acknowledgments

This research was funded by project EXPL/BIA-BIC/1471/2012 to KRN from the Portuguese National Science Foundation (FCT) and supported by an award from the South Africa Research Chairs Initiative (SARChI) of the Department of Science and Technology. RLC and GIZ were supported by postdoctoral fellowships from FCT (SFRH/BPD/65830/2009 and SFRH/BPD/42007/2007, respectively). We are grateful to S. Dobretsov for kindly supplying specimens from Oman.

Conflict of Interest

None declared.

Supporting Information

Additional Supporting Information may be found in the online version of this article:

Material S1. Phylogenetic relationships of the currently recognized species within the genus Perna. The maximum likelihood topology of a mitochondrial data set (COI) is shown. Numbers above and below nodes correspond to ML bootstrap values and Bayesian posterior probabilities, respectively. Gray boxes indicate the three clades within P. perna recovered in this analysis. The inset shows phylogeographic patterns of diversification within P. perna.

ece30004-2070-sd1.pdf (85.7KB, pdf)

Material S2. Phylogenetic relationships of the currently recognized species within the genus Perna. The maximum likelihood topology of a nuclear data set (ITS) using the GTR+Γ evolutionary model is shown. Numbers above and below nodes correspond to ML bootstrap values and Bayesian posterior probabilities, respectively.

ece30004-2070-sd2.pdf (70.5KB, pdf)

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Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

Material S1. Phylogenetic relationships of the currently recognized species within the genus Perna. The maximum likelihood topology of a mitochondrial data set (COI) is shown. Numbers above and below nodes correspond to ML bootstrap values and Bayesian posterior probabilities, respectively. Gray boxes indicate the three clades within P. perna recovered in this analysis. The inset shows phylogeographic patterns of diversification within P. perna.

ece30004-2070-sd1.pdf (85.7KB, pdf)

Material S2. Phylogenetic relationships of the currently recognized species within the genus Perna. The maximum likelihood topology of a nuclear data set (ITS) using the GTR+Γ evolutionary model is shown. Numbers above and below nodes correspond to ML bootstrap values and Bayesian posterior probabilities, respectively.

ece30004-2070-sd2.pdf (70.5KB, pdf)

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