Adaptive radiation is usually triggered by ecological opportunity, arising through (i) the colonization of a new habitat by its progenitor; (ii) the extinction of competitors; or (iii) the emergence of an evolutionary key innovation in the ancestral lineage. Support for the key innovation hypothesis is scarce, however, even in textbook examples of adaptive radiation. Antifreeze glycoproteins (AFGPs) have been proposed as putative key innovation for the adaptive radiation of notothenioid fishes in the ice-cold waters of Antarctica. A crucial prerequisite for this assumption is the concurrence of the notothenioid radiation with the onset of Antarctic sea ice conditions. Here, we use a fossil-calibrated multi-marker phylogeny of nothothenioid and related acanthomorph fishes to date AFGP emergence and the notothenioid radiation. All time-constraints are cross-validated to assess their reliability resulting in six powerful calibration points. We find that the notothenioid radiation began near the Oligocene-Miocene transition, which coincides with the increasing presence of Antarctic sea ice. Divergence dates of notothenioids are thus consistent with the key innovation hypothesis of AFGP. Early notothenioid divergences are furthermore congruent with vicariant speciation and the breakup of Gondwana.
Adaptive radiation is usually triggered by ecological opportunity, arising through (i) the colonization of a new habitat by its progenitor; (ii) the extinction of competitors; or (iii) the emergence of an evolutionary key innovation in the ancestral lineage. Support for the key innovation hypothesis is scarce, however, even in textbook examples of adaptive radiation. Antifreeze glycoproteins (AFGPs) have been proposed as putative key innovation for the adaptive radiation of notothenioid fishes in the ice-cold waters of Antarctica. A crucial prerequisite for this assumption is the concurrence of the notothenioid radiation with the onset of Antarctic sea ice conditions. Here, we use a fossil-calibrated multi-marker phylogeny of nothothenioid and related acanthomorph fishes to date AFGP emergence and the notothenioid radiation. All time-constraints are cross-validated to assess their reliability resulting in six powerful calibration points. We find that the notothenioid radiation began near the Oligocene-Miocene transition, which coincides with the increasing presence of Antarctic sea ice. Divergence dates of notothenioids are thus consistent with the key innovation hypothesis of AFGP. Early notothenioid divergences are furthermore congruent with vicariant speciation and the breakup of Gondwana.
Adaptive radiation - the evolution of ecological and phenotypic diversity within a
rapidly multiplying lineage - has been implicated in the genesis of a great portion
of the diversity of life [1], [2]. According to Schluter [2], an adaptive radiation is
characterized by rapid speciation, common ancestry, and a phenotype-environment
correlation, whereby phenotypes must actually be beneficial in their respective
environments. Adaptive radiation is often considered a consequence of ecological
opportunity [1],
[2] arising
through colonization of a new habitat with abundant niche-space, extinction of
antagonists, and/or the origin of a key innovation [3]. All three settings induce the
relaxation of selection pressure, which may promote diversification [3]. Key innovations
can lead to ecological opportunity either by enabling the exploitation of new
resources, or by boosting a clade's fitness relative to competing lineages. A
third type of key innovation does not generate ecological opportunity, but directly
enhances diversification rates by increasing the potential for reproductive
isolation or ecological specialization, e.g. by decreasing dispersal distance and
gene flow [4].
Corroboration of the key innovation hypothesis would, hence, involve the
identification of (ecological) mechanisms linking a putative key innovation to
increased speciation or decreased extinction rates, and comparative tests
correlating it with inflating diversity [4].So far, such tests have been applied to few key innovations only, and even the best
examples of animal adaptive radiations provide only scanty evidence in support of
the key innovation hypothesis. Two of the most prominent examples of adaptive
radiation, the Galapagos finches and Hawaiian honeycreepers, were, in fact, more
likely triggered by the arrival of the ancestral species on competitor-free islands
rather than by key innovations [5]. A number of key innovations have been proposed for the
radiations of cichlid fishes in the Great Lakes of East Africa, including a highly
variable pharyngeal jaw apparatus, egg-spots, and maternal mouth brooding behaviour
[6], [7]. However,
based on a comparative analysis of successful and failed cichlid radiations, the
role of all three traits as key innovations has been questioned [8]. Similarly,
the acquisition of pharyngeal jaws provides a weak explanation for increased
diversification rates in the radiation of labrid fishes [9]. A key innovation in Caribbean
Anolis lizards, on the other hand, appears to pass both the
ecological mechanism and comparative test: extended subdigital toe-pads enable
Anolis to climb narrow twigs, leaves and grass blades. The
resultant arborality distinguishes them from other iguanids. Toepads evolved at the
base of the anole phylogeny, and also occur in the second-most species rich family
of lizards, the Gekkonidae, thus linking its emergence with species richness [10].Another vertebrate adaptive radiation, which has drawn increasing interest in recent
years, has occurred on the isolated shelf areas surrounding the Antarctic continent
in the perciform fish suborder Notothenioidei. A total of 132 notothenioid species
are known to date, and new species are discovered at fast rates [11]. Nine species
belong to three early diverging families (Bovichtidae, Pseudaphritidae,
Eleginopidae) that occur almost exclusively outside Antarctic waters and are not
usually considered part of the radiation. The remaining 123 species in five families
are often referred to as the “Antarctic Clade”, which dominates the High
Antarctic ichthyofauna in terms of species number (76.6%) and biomass
(>90%) [11]. Notothenioids of the Antarctic Clade possess a wide
range of adaptations to the extreme Antarctic environment, including antifreeze
glycoproteins (AFGP) [12], retinal reorganization [13], and loss of heat shock
response [14].
One of the five Antarctic notothenioid families (Channichthyidae) even lives without
hemoglobin, which is unique among vertebrates [15]. Despite the loss of the swim
bladder in their presumably benthos-dwelling ancestor, multiple notothenioid
lineages have independently recolonized pelagic, semi-pelagic and cryopelagic
habitats. Subsequent adaptations in ossification, scale mineralization, and lipid
deposition led to a partial or full reaquisition of neutral buoyancy and a
phenotype-environment correlation that is characteristic for adaptive radiations
[2], [11]. Another
important phenotype-environment correlation exists between freezing avoidance and
water temperature [16].Antifreeze glycoproteins are present in almost all notothenioids of the Antarctic
Clade, enabling them to cope with the subzero temperatures of Antarctic waters [17]. The widespread
possession of AFGPs in the monophyletic Antarctic Clade, complete lack of AFGPs in
non-Antarctic sister groups, and their highly conserved chemical structure [15] suggest that
AFGPs evolved only once in notothenioids and that this occurred prior to the onset
of diversification in the Antarctic Clade [12], [17]. Therefore, it has been
hypothesized that AFGPs represent a key innovation that allowed notothenioids to
radiate at a time when Antarctic water temperatures dropped below zero, which
presumably led to the extinction of a great part of the previous Antarctic shelf
ichthyofauna [15]. Following Heard and Hauser [4] AFGPs would constitute a type I
key innovation if the resulting fitness advantage enabled notothenioids to replace
other clades, a type II key innovation if AFGPs allowed the invasion of previously
unoccupied sea ice-associated habitats, or a combination of both. A crucial
prerequisite for either hypothesis is the concurrence of the beginning of the
notothenioid radiation and the onset of Antarctic sea ice conditions.Cenozoic Antarctic water temperatures and the emergence of sea-ice in Antarctica can
be inferred from deep sea isotope records and sediment analysis of drill cores [18]–[21]. The timing of
the notothenioid radiation, on the other hand, is far less certain, which is in part
due to the paucity of fossils in Antarctica. Existing molecular clock calibrations
for notothenioids are based on few mitochondrial markers in combination with a
single putative, but debated, eleginopid fossil [22], biogeographic patterns [23], or the
presumed date of the perciform diversification [24]. Consequently, attempts to date
the beginning of the notothenioid radiation have led to a wide range of
contradicting results between 7 and 24 Ma [22], [25].Here we use a multi-marker (4599 bp, 6.53% missing data) phylogeny including
representatives of all notothenioid families plus 69 non-notothenioid fishes with
ten fossil and phylogeographic constraints to time-calibrate notothenioid
divergences and AFGP evolution.
Results
Tree Topology
Partitioned Maximum Likelihood and Bayesian phylogenetic analyses of 83
acanthomorph taxa using GARLI-PART, RAxML, and BEAST (Fig. 1, Fig. S2)
resulted in identical topologies with the exception of the position of
Antigonia capros, which was placed as sister group to
Lophiiformes and Tetraodontiformes in RAxML's optimal tree. The
phylogenetic placement of zeioids within Paracanthopterygii [26] and scarids
within Labridae [27], [28] was confirmed in all
analyses. Gasterosteiformes and Zoarcidae appeared within Scorpaeniformes, thus
rendering this order paraphyletic (albeit with low support values).
Notothenioids were recovered as a sister group of a clade containing percids,
trachinoids, and Serranus atricauda. The highly supported
placement of the latter (Bayesian Posterior Probability (BPP) 1.0; Fig. S2,
Table
S1) is in accordance with previous phylogenetic hypotheses and
suggests polyphyly of serranids, with representatives of the family in close
phylogenetic affiliation with notothenioids, percids, and trachinoids [29], [30]. Removal of
S. atricauda from the data set affected the tree topology
only in the weakly supported position of Antigonia capros
(Table
S1). The notothenioids were covered by 14 (phylogenetically)
representative species. While this number might appear small in the context of
notothenioid phylogenetics and divergence rate estimates (which was, notably,
not the purpose of this study), it is absolutely balanced with respect to the
timing of their radiation and their relative coverage in the total dataset. Our
trees confirm the divergence of Bovichtidae prior to Pseudaphritidae, the
monophyly of the Antarctic Clade, the paraphyly of the family Nototheniidae
within the Antarctic Clade, and the interrelationships of derived notothenioid
families (Fig.
S2) [22], [31].
Figure 1
Time-calibrated phylogeny of acanthomorph fishes based on the
concatenated dataset of two mitochondrial and four nuclear genes, and
six calibration points (B, C, G, H, I, and J).
All nodes used for constraint cross-validation are labelled with letters
A–J, percid and notothenioid nodes are labelled with letters
V–Z. Insets indicate nodes labels within Paracanthopterygii,
Labridae, Lophiiformes, and Tetraodontiformes. Node bars show 95%
HPD.
Time-calibrated phylogeny of acanthomorph fishes based on the
concatenated dataset of two mitochondrial and four nuclear genes, and
six calibration points (B, C, G, H, I, and J).
All nodes used for constraint cross-validation are labelled with letters
A–J, percid and notothenioid nodes are labelled with letters
V–Z. Insets indicate nodes labels within Paracanthopterygii,
Labridae, Lophiiformes, and Tetraodontiformes. Node bars show 95%
HPD.
Cross-Validation of Time Constraints
We first cross-validated the available 10 calibration points in order to test for
their relative consistency. This step is important, as calibrations based on
fossil and geological data show various degrees of uncertainty [32]. When
estimated on the basis of all other constraints, five out of ten divergence
dates were concordant with the respective fossil age assignments (Fig. 2). The split between
gempylids and scombrids (node D; 79.2–18.4 Ma, 95% highest
probability density (HPD)) seems to postdate respective fossil findings and
suggest taxonomic or stratigraphic misinterpretations. The mean age estimate for
the polymixiid lineage (99.2 Ma) falls into the Cenomanian, as does the oldest
polymixiid fossil. Nevertheless, this constraint was excluded from further
analyses, as nearly half of its HPD (133.1–70.5 Ma) postdates the
Cenomanian. Age estimates for both cichlid and labrid divergences failed to
match phylogeographic calibrations, which were therefore excluded. Estimated on
the basis of nine constraints, the diversification of Percomorpha
(203.3–135.0 Ma) seems to predate the earliest euteleost fossils (150.9
Ma) [33].
However, after exclusion of constraints A, C, D, E, and F, re-estimation
resulted in younger percomorph divergence estimates (150.9–114.7 Ma),
being congruent with the euteleost fossil record.
Figure 2
Cross validation of all fossil and phylogeographic
constraints.
The dashed black line indicates the prior, as specified in all BEAST runs
including this constraint. The solid black line shows the marginal
densities of BPPs for each node when its constraint is relaxed and its
date estimated based on all other constraints. At this stage, only five
out of ten (B, G, H, I, J) nodes showed a good fit between prior and
posterior. A new BEAST analysis (‘-ACDEF’) was conducted,
using only constraints B, G, H, I, and J. Results of this analysis
(solid grey line) showed a good fit between prior and posterior for node
C, therefore node C was reincluded in a final BEAST run
(‘-ADEF’; dashed grey line).
Cross validation of all fossil and phylogeographic
constraints.
The dashed black line indicates the prior, as specified in all BEAST runs
including this constraint. The solid black line shows the marginal
densities of BPPs for each node when its constraint is relaxed and its
date estimated based on all other constraints. At this stage, only five
out of ten (B, G, H, I, J) nodes showed a good fit between prior and
posterior. A new BEAST analysis (‘-ACDEF’) was conducted,
using only constraints B, G, H, I, and J. Results of this analysis
(solid grey line) showed a good fit between prior and posterior for node
C, therefore node C was reincluded in a final BEAST run
(‘-ADEF’; dashed grey line).
Notothenioid Divergence Dates
According to cross-validation results, we estimated divergence dates of
notothenioids on the basis of six fossil constraints (nodes B, C, G, H, I, and
J; Fig. 3, Table S2).
Our results support a late Cretaceous origin of Bovichtidae (node U, mean 71.4
Ma, 95% HPD 89.4–54.4 Ma), early Paleocene divergence of
Pseudaphritidae (node V, 63.0 Ma, 80.2–46.7 Ma), and a Mid-Eocene split
between Eleginopidae and the Antarctic Clade (node W, 42.9 Ma, 56.9–29.8
Ma). Mid-Eocene origin of the eleginopid lineage is congruent with the age of
the only fossil putatively assigned to Notothenioidei. Proeleginops
grandeastmanorum from the La Meseta Formation on Seymour Island
(dated to ∼40 Ma) was first described as a gadiform fossil [34], and
subsequently reinterpreted as an eleginopid [35]. While previous attempts
to date the notothenioid radiation used this fossil as a single calibration
point, our analysis deliberately excluded this constraint due to its debated
taxonomic assignment [22]. Nevertheless, the concordance between divergence
date estimates and fossil age corroborates the eleginopid interpretation of
P. grandeastmanorum. Radiation of the Antarctic Clade began
near the Oligocene-Miocene transition with the divergence of
Gobionotothen (node X, 23.9 Ma, 31.9–16.7 Ma) and was
quickly followed by further diversification within the Antarctic Clade (node Y,
21.4 Ma, 28.2–15.3 Ma). Correspondingly, support values for early
nototheniid divergences are low (node Y, Table S1), indicating rapid succession of
speciation events. Excluding G. gibberifrons from the data set
indicates that regardless of the exact topology of the Antarctic Clade, the
radiation was underway in the early Miocene (23.0 Ma, 30.5–16.1 Ma). This
is in agreement with previous age estimates (24.1±0.5 Ma) on the basis of
the putative eleginopid fossil P. grandeastmanorum and a
penalized likelihood molecular analysis approach [22]. Diversification of the four
most derived notothenioid families Harpagiferidae, Artedidraconidae,
Bathydraconidae, and Channichthyidae apparently began in the mid-Miocene (node
Z, 14.7 Ma, 20.0–9.9 Ma). Close agreement of percid divergence dates (node
T, 28.54–54.71 Ma) with biogeographical scenarios suggests that clades
closely related to notothenioids were dated reliably (Text S1).
All acanthomorph divergence date estimates are summarized in Table S2.
Notothenioid divergence date estimates are relatively robust to the set of
constraints used for our cross-validation (Table
S3).
Figure 3
Comparison of notothenioid divergence dates and geological
events.
Phylogenetic nodes are labelled with letters U-X according to Fig. 1. The
diversification of the Antarctic Clade (node X) coincides with an
increase in frequency of glacial extensions well onto the shelf, the
Mi-1 glacial event, the first occurences of sea-ice dependent diatoms in
Antarctic waters, and a sharp decline of atmospheric CO2
levels. Paleoc.:Paleocene, Oligoc.:Oligocene, Pl.:Pliocene,
P.:Pleistocene.
Comparison of notothenioid divergence dates and geological
events.
Phylogenetic nodes are labelled with letters U-X according to Fig. 1. The
diversification of the Antarctic Clade (node X) coincides with an
increase in frequency of glacial extensions well onto the shelf, the
Mi-1 glacial event, the first occurences of sea-ice dependent diatoms in
Antarctic waters, and a sharp decline of atmospheric CO2
levels. Paleoc.:Paleocene, Oligoc.:Oligocene, Pl.:Pliocene,
P.:Pleistocene.
Discussion
Antifreeze Glycoproteins are a Key Innovation
Bayesian Inference of acanthomorph divergence dates shows that the adaptive
radiation of Antarctic notothenioids, resulting in more than 120 morphologically
highly diverse species that dominate Antarctic waters, began near the
Oligocene-Miocene transition (mean 23.9 Ma, 95% HPD 31.9–16.7 Ma).
While large-scale continental glaciation may not have been permanent before the
middle Miocene climate transition (∼14 Ma) [36], [37], geological evidence
supports temporal presence of Antarctic sea ice already 24 Ma: Deep-sea oxygen
(δ18O) isotopes (Fig. 3) provide a reliable record of relative temperature changes
and demonstrate an overall cooling trend (∼14°C) since the early Eocene
[19].
Similarly, isotope levels of sedimentary alkenones reveal partial pressures of
paleoatmospheric carbon dioxide (pCO2; Fig. 3) and show a decrease
from the middle to late Eocene that led to rapid expansions of large continental
Antarctic ice sheets and widespread ice rafting as early as 34 Ma [18], [38], [39]. Numerical
climate models with explicit, dynamical representations of sea ice show that
moderate or full cenozoic glaciation of East Antarctica would have promoted
extensive sea ice formation at least in cold austral summer orbits with low
pCO2 levels (560 ppmv) [40]. Direct evidence for
continental glaciation and marine ice comes from cyclic glacimarine deposits in
offshore drill cores, showing that glacial extensions well onto the continental
shelf occurred repeatedly since the early Oligocene (Fig. 3) [20]. Furthermore, the long-term
presence of local sea ice is suggested by findings of sea ice-dependent diatoms
in lower Oligocene sediments [21]. Taken together, it is likely that Antarctic sea ice
has existed with seasonal, orbital, and local constraints since the early
Oligocene. Estimates for the onset of the Antarctic Circumpolar Current range
widely [41],
but its increasing strength presumably contributed to thermal isolation and
cooling of Antarctic waters by up to 4°C during the Oligocene and Miocene
[42]. Deep
sea oxygen isotope records and glacimarine sediments further indicate a major
period of global cooling and ice sheet expansion at the Oligocene-Miocene
transition (Mi-1 event, 24.1–23.7 Ma, Fig. 3) [43]. This exactly coincides with
our mean age estimate for the onset of the Antarctic notothenioid radiation
(23.9 Ma), which is characterized by the presence of AFGPs. Based on the highly
conserved chemical structure of AFGPs in nearly all notothenioids of the
Antarctic Clade [15], it is commonly assumed that AFGPs evolved only once,
before the notothenioid radiation [12], [17]. Members of the genus Patagonotothen
apparently lack AFGPs [17], which is – however – likely due to
secondary loss (as Patagonotothen is deeply nested within
AFGP-bearing nototheniids, it would otherwise require at least 6 independent
origins of notothenioid AFGPs [15], [31]). Hence, the key innovation hypothesis of AFGP is
consistent with our age estimate for the notothenioid radiation. Freezing
avoidance could have allowed notothenioids to invade new, ice-associated niches,
or to replace other clades subsequent to their extinction in a cooling
environment. Without doubt, selection pressures must have been substantial,
given that freezing avoidance is a matter of life and death in ice-laden
habitats [44].
Emergence of AFGPs could have proceeded in a step-wise manner that began with
accidental replication slippage in an intron of the ancestral trypsinogen gene
[12].
Subsequent duplications of Thr-Ala-Ala tripeptides could have endowed some
measures of freezing avoidance without immediate loss of trypsin activity [44].The key innovation hypothesis of AFGP would further be corroborated if similar
diversity was found in other clades that independently acquired freezing
avoidance [4].
Outside notothenioids, near-identical AFGPs have convergently evolved in Arctic
cod Boreogadus saida
[45] and other
taxa of the subfamily Gadinae [46], [47]. Apparently, cod AFGPs share a common origin that
dates back to the Miocene [48]. The subfamily consists of 23 species and may thus be
considered moderately species-rich. Type III antifreeze proteins (AFP) are found
in zoarcids of both Antarctic and Arctic waters, and supposedly predate the
bipolar distribution of zoarcids [47], [49]. With over 200 species,
the family Zoarcidae is indeed a highly diverse group [49], and surpasses even
notothenioids in species richness. However, AFPs have been identified in
comparatively few zoarcids to date [47], which may indicate
secondary losses in many taxa. Whether AFP played a role in the zoarcid
radiation remains to be elucidated. The distribution of type I AFPs over
phylogenetically distant clupeids, osmerids, and cottids of the northern
hemisphere provides a rare example of lateral gene flow in vertebrates [50] and
indicates strong selection pressures. However, none of these AFP-bearing taxa
have undergone substantial radiations. This could be due to external factors
that mask the effect of AF(G)P emergence in non-notothenioid taxa. Most adaptive
radiations occur in geographically confined areas, a potential prerequisite
[51]
that is satisfied for Antarctic continental shelves, but less so for Arctic
habitats. In addition, dispersal of zoarcids to Antarctica in the Miocene [49], when the
notothenioid diversification had already filled most available niche space,
could have limited their radiation.
Phylogeography of Notothenioid Lineages
Estimates of early notothenioid divergence dates support most aspects of the
phylogeographic scenario proposed by Balushkin [52]: The presence or even
endemism of three out of four bovichtid and pseudaphritid genera in Australia
suggests occurrence of the presumably benthic notothenioid ancestor [15] on South
Australian continental shelves in the late Cretaceous. Fragmentation of shelf
areas between Australia and New Zealand ∼70 Ma may have led to the
separation of bovichtids from the pseudaphritid ancestor and to initial
divergences within Bovichtidae. Extended pelagic larval durations could have
contributed to long-ranged eastward dispersal of bovichtids with paleogene
currents to South America and Tristan da Cunha [52]. The isolation of
pseudaphritids in Southern Australia and divergence of the Antarctic lineage are
presumably linked to the breakup of Australia and Antarctica. Separation between
both landmasses started between 125 and 90 Ma [53], however, shallow water
connections existed until ∼33.5 Ma [54], [55]. Vicariant speciation of
benthic lineages could have occurred anytime between these dates, being
supported by our age estimate of pseudaphritids (node V, 63.0 Ma,
80.3−46.7 Ma). Antarctic notothenioids then diversified into eleginopids
and the ancestor of the Antarctic Clade in the Eocene (node W, 42.9 Ma,
56.9−29.8 Ma). Past presence of eleginopids in Antarctica is indicated by
the fossil P. grandeastmanorum, presumably representing an
early member of the lineage [35]. Finally, a drop in water temperatures and the
increasing presence of sea ice in the Oligocene led to near-complete replacement
of the Eocene Antarctic ichthyofauna [15], migration of eleginopids
to South America, and adaptive radiation of the Antarctic Clade subsequent to
AFGP emergence.
Materials and Methods
Phylogenetic Reconstruction
Four nuclear (myh6, Ptr, ENC1, tbr) and two mitochondrial (nd4, cyt
b) markers were PCR amplified and sequenced for 14
notothenioid and 53 related acanthomorph fish species, and complemented with
additional sequences from GenBank, Ensemble, and Genoscope to a total of 83 taxa
(Text
S2, Tables S4–S5). Phylogenetic analyses were conducted in
GARLI-PART v0.97 [56] and RAxML v7.26 [57], and node support was
assessed with nonparametric bootstraps. Detailed information on sample
collection, marker selection, PCR amplification, and phylogenetic inferences are
given in the Text S2, S3, S4, S5 and S6 and
Fig.
S1.
Time Constraints used for Dating
A total of eight fossil, and two phylogeographic constraints were chosen to
time-calibrate acanthomorph divergences. Following Benton & Donoghue [58], we
implemented time constraints for the origin of Tetraodontidae (node J;
Takifugu-Tetraodon divergence;
56.0−32.25 Ma) and for the split between Gasterosteiformes and
Tetraodontiformes (node G; 150.9−96.9 Ma). The minimum age for the
Gasterosteiformes-Tetraodontiformes divergence is derived from the oldest known
member of the tetraodontiform lineage, Plectocretacicus clarae,
which also represents the oldest known percomorph. Also, the maximum constraint
for divergence of gasterosteiform and tetraodontiform lineages is provided by
the earliest euteleost record, e.g. Tischlingerichthys viohli.
Therefore, we applied the same lower and upper bounds for the divergence of all
Percomorpha (not including Dicrolene introniger, as the
phylogenetic position of Ophidiiformes remains unclear [26]; node C). Uniform priors
between minimum and maximum age of divergence were used for these constraints.
In addition, we constrained five family divergences, which we expected to have
relatively early fossil records in at least one of the descending lineages
(Fig.
S3). Thus, our analysis accounted for polymixiid fossils from the
Cenomanian (node A; ≥93.5 Ma), a zeid fossil from the Thanetian (node B;
≥55.8 Ma), gempylid and scombrid fossils from the Danian (node D; ≥61.7
Ma), a chaunacid fossil from the Bartonian (node H; ≥37.2 Ma), and a
monacanthid fossil from the Ypresian (node I; ≥48.6 Ma). All used fossils are
referenced in detail in Text S7. Lognormal priors were assigned to
the above fossil constraints with hard lower bounds reflecting the age of the
respective fossil, and soft upper bounds (Table S5,
Fig. 2). Phylogeographic
constraints for cichlid and labrid divergences were derived from the breakup of
Gondwana, and from the closure of the connection between the Mediterranean and
the Indian Ocean. We added the separation of Africa and South America as
effective time constraint for the split between African and neotropical cichlids
(node E), assuming vicariant divergence. Seafloor spreading in the South
Atlantic started as early as 133 Myr ago [59] and a continuous
North/South Atlantic Ocean presumably existed ∼100 Myr ago [60], hence, we
applied a normally distributed prior between 121.8 and 98.2 Ma (95%
cumulative probability; mean: 110.0 Ma) to constrain cichlid divergence. The
split between Labrus and both Ctenolabrus and
Tautogolabrus (node F) represents the diversification of
the labrid tribe Labrini [27]. Based on molecular clock calibrations and fossil
evidence (Text
S7) showing that Labrini were present in the Mediterranean 14.0 Ma,
it has been suggested that the ancestor of Labrini migrated from the Indopacific
into the Mediterranean prior to the closure of this seaway, 20.5−19.5 Ma
[27].
Therefore, we constrained the diversification of Labrini with a uniform prior
between 20.5 and 14.0 Ma.
Dating of Acanthomorph Divergences
In order to date notothenioid and non-notothenioid acanthomorph divergences, we
generated time-calibrated phylogenies with BEAST v1.5.3 [61]. All BEAST runs were
performed using mitochondrial and nuclear sequence alignments as separate
partitions with unlinked substitution models. We employed a relaxed molecular
clock model with branch rates drawn independently from a lognormal distribution
[62],
ten time constraints (Table S5), and the reconstructed birth-death
process [63]
as a tree prior (see Fig. S4 for substitution rates). The
applicability of relaxed molecular clocks for cold-adapted organisms is
discussed in Text S8. After optimization of operators according to preliminary
run results, three different substitution models were implemented and evaluated.
We included the codon position-based
HKY112+CP112+Γ112 model [64], in which
all parameters are estimated independently for the first two and for the third
codon positions. We also added the
GTR112+CP112+Γ112 model,
using the same partitions. In a third set, we implemented HKY+I+Γ
for the first two mitochondrial codon positions, TVM+Γ for the third
mitochondrial codon position, K80+I+Γ for the first nuclear codon
position, and GTR+Γ for the third nuclear codon position, as selected
by BIC. For each of the three setting, we performed 20 independent analyses of
20 million generations each, discarding the first 2 million generations of every
replicate as burnin. Replicate results were combined in LogCombiner v1.5.3 after
removing the burnin. Convergence of run replicates was confirmed by effective
sample sizes (ESS) >1200 for all parameters and by visual inspection of
traces within and between replicates in Tracer v1.5. Substitution models were
evaluated on the basis of Bayes Factors, again, as implemented in Tracer [65]. Bayes
Factors provided ‘very strong’ [66] evidence that the
substitution model combination selected by BIC was better-fitting than both the
HKY112+CP112+Γ112 (log 10 BF
350.6) and GTR112+CP112+Γ112 (log
10 BF 276.0) models, and thus the BIC combination was used for all subsequent
analyses. In order to assess the reliability of every individual time
constraint, we conducted a cross-validation, whereby we relaxed constraints one
by one, and estimated divergence dates of relaxed constraints based on all other
constraints (Fig. 2). BEAST
runs were conducted as described above, but using 5 run replicates per
cross-validation. We found good fit of posterior and prior distributions for
constraints B, G, H, I, and J. Subsequently, 20 run replicates were performed
with identical settings, but excluding the five unreliable constraints A, C, D,
E, and F (run ‘-ACDEF’ in Fig. 2). Posterior distributions of excluded
constraints were again compared to their assumed prior distributions. After
exclution of five constraints, node C (divergence of Percomorpha) provided
adequate fit of posterior probability distribution to its suggested bounds [58], and was
thus reincluded for yet another run with 20 independent replicates and unchanged
settings (run ‘-ADEF’ in Fig. 2 and Tables
S1–S2). ESS values for this run were >900 for
all parameters. As for GARLI-PART and RAxML analyses, the last run was repeated
after removal of Serranus atricauda from the dataset
(‘-ADEF -Serranus atricauda’ in Fig. 2 and Tables
S1–S2), which had no impact on tree topology and
little influence on node support (on average -0.19 BPP, Table S1)
and divergence date estimates (average difference 0.57%, Table S2).
All molecular data sets to date [22], [23], [31] failed to assign a reliable phylogenetic position to
G. gibberifrons (node Y, BPP 0.64), thus indicating rapid
divergence at the beginning of the notothenioid radiation. We also repeated the
analysis without G. gibberifrons (8 replicates, unchanged
settings) to obtain a minimum age estimate for the diversification of the
Antarctic Clade that is robust to topological uncertainties. Maximum clade
credibility trees were produced using TreeAnnotator v1.5.3.Partitioned ML consensus tree of full mitochondrial genomes (A), and best ML
phylogenies of single mitochondrial markers (B-D), estimated with RAxML.
Sequence data were taken from [3], [4], [6]. Markers ND4 (B) and
cyt b (C) phylogenies show better agreement with the full
mitogenome topology than other markers of comparable sequence length
(D).(EPS)Click here for additional data file.Partitioned ML phylogeny of 83 acanthomorph fishes, based on the concatenated
dataset of two mitochondrial (ND4, cyt b) and four nuclear
genes (myh6, Ptr, ENC1, tbr). Tree topology and branch lengths are as
estimated using GARLI-PART, and near-identical topologies were recovered
with RAxML and BEAST analyses. Filled circles indicate > 98% BS
support (as calculated with GARLI-PART) and > 0.99 BPP (according to
BEAST run ‘-ADEF’), white circles represent nodes with BS
support > 80% and >0.90 BPP. Split circles indicate different
levels of BS (left half) and BPP (right half) support. All node support
values are summarized in Table S3. Nodes that were used for fossil
and phylogeographic constraints are labelled with letters A–J, basal
percid and notothenioid nodes are labelled with letters T–Z.(EPS)Click here for additional data file.Partitioned BI phylogeny, based on the concatenated data set, reduced to
family level. Node heights correspond to mean age estimates. The time scale
is divided into phanerozoic stages (grey shades), and the presence of
skeletal (black bars) or otolith fossils (dark grey bars) in a stage is
plotted on top of family branches. Unless otherwise noted, all fossil
information is taken from [22]. Fossils with questionable taxonomic or
stratigraphic assignments are indicated by dashed bars. Numbers in brackets
indicate the number of species included in this study and the total number
of species per family [31]. 1) Fossil used to constrain node D,
however cross-validation results suggest unreliability of this constraint.
As Gempylidae could be nested within Scombridae [25], fossils may have
been misinterpreted. 2) [32], [33]
3) According to Santini & Tyler [34], the oldest
tetraodontid is Archaeotetraodon winterbottomi from the
Rupelian. Eotetraodon pygmaeus, previously assigned to
Tetraodontidae [22], has been moved to the family Triodontidae
4) [35], [36].(EPS)Click here for additional data file.Partitioned BI phylogeny of 83 acanthomorph fishes, based on the concatenated
data set. Branch lengths are according to mean estimates of node ages (Table
S4). Branch colors indicates substitution rates.(EPS)Click here for additional data file.Node support given as BS and BPP values for partitioned ML and BI
phylogenetic reconstructions. Nodes marked with * were recovered in best
ML tree topologies, but were not included in BS consensus trees. Nodes
marked with. Nodes were labelled as in Fig.
S2. BEAST analyses were based on six fossil constraints (run
‘-ADEF’). Exclusion of Serranus atricauda from
the data set had little effect on node support.(DOC)Click here for additional data file.Divergence date estimates, estimated in BEAST on the basis of six reliable
fossil calibrations (run ‘-ADEF’). For this analysis, time
constraints were applied to nodes marked with *. Labels refer to nodes
in Fig.
S2. Exclusion of Serranus atricauda from the
data set had negligible effects on age estimates. All dates are given in
Ma.(DOC)Click here for additional data file.Estimates for the onset of the radiation of the AFGP-bearing Antarctic Clade
(node X) when individual node constraints were removed during the constraint
cross-validation. All dates are given in Ma.(DOC)Click here for additional data file.Genbank accession numbers for all sequences used for phylogenetic analyses.
Sequences HM049934-HM050270 were produced as part of this study. *
Nuclear T. rubripes and T. nigroviridis
sequences were extracted from Ensembl (www.ensembl.org) and
Genoscope (www.genoscope.cns.fr) genome browsers (Table
S2).(DOC)Click here for additional data file.Ensembl and Genoscope identifiers of Takifugu rubripes and
Tetraodon nigroviridis sequences. T.
rubripes Ensembl identifiers were taken from [5], while
T. nigroviridis Genoscope identifiers and sequences
were found by BLAT-search against the T. nigroviridis
genome, using the entire T. rubripes sequences as search
templates.(DOC)Click here for additional data file.(DOC)Click here for additional data file.(DOC)Click here for additional data file.(DOC)Click here for additional data file.(DOC)Click here for additional data file.(DOC)Click here for additional data file.(DOC)Click here for additional data file.(DOC)Click here for additional data file.(DOC)Click here for additional data file.
Authors: T R Naish; K J Woolfe; P J Barrett; G S Wilson; C Atkins; S M Bohaty; C J Bücker; M Claps; F J Davey; G B Dunbar; A G Dunn; C R Fielding; F Florindo; M J Hannah; D M Harwood; S A Henrys; L A Krissek; M Lavelle; J van Der Meer; W C McIntosh; F Niessen; S Passchier; R D Powell; A P Roberts; L Sagnotti; R P Scherer; C P Strong; F Talarico; K L Verosub; G Villa; D K Watkins; P N Webb; T Wonik Journal: Nature Date: 2001-10-18 Impact factor: 49.962
Authors: Thomas J Near; Alex Dornburg; Kristen L Kuhn; Joseph T Eastman; Jillian N Pennington; Tomaso Patarnello; Lorenzo Zane; Daniel A Fernández; Christopher D Jones Journal: Proc Natl Acad Sci U S A Date: 2012-02-13 Impact factor: 11.205
Authors: Glenn Litsios; Carrie A Sims; Rafael O Wüest; Peter B Pearman; Niklaus E Zimmermann; Nicolas Salamin Journal: BMC Evol Biol Date: 2012-11-02 Impact factor: 3.260