METHODS
Molecular taxon sampling
We obtained mitochondrial sequences from 35 individuals representing all 19
presumptive phylogenetic species within Pionus (table S2). Multiple individuals
representing the same basal taxa were included when possible, to assess intra-taxon
variability, and to determine if individuals belonging to each taxon are grouped together
in monophyletic clades. Sequences from seven individuals (representing the species P.
sordidus, P. mindoensis, P. antelius, P. saturatus, P. ponsi, and P. chalcopterus) were
obtained from skins (table S2). Other parrot species representing the closely related
genera Graydidascalus (G. brachyurus), Gypopsitta (G. barrabandi), Pionopsitta (P.
pileata), Hapalopsittaca (H. amazonina), Triclaria (T. malachitaceae), Amazona (A.
farinosa), and Amazona xanthops [which, according to the analysis of Russello & Amato
(2004), is not included in the genus Amazona] were included in the preliminary analyses.
As outgroups for the preliminary analyses we included three species belonging to more
distantly related genera of Neotropical parrots (Aratinga, Pyrrhura and Anodorhynchus)
(Miyaki et al. 1998; Tavares et al. 2004; Tavares et al. 2006; Ribas et al. 2005, 2006).
All sequences of individuals not belonging to Pionus were obtained in previous studies
(Tavares et al. 2004; Tavares et al. 2006; Ribas et al. 2005) and are deposited in
GenBank. For the final analyses, after confirming monophyly of Pionus, only Gypopsitta
barrabandi, Amazona farinosa, Amazona xanthops and Graydidascalus brachyurus were
included as outgroups.
DNA extraction, amplification, and sequencing
DNA extraction from blood samples was performed through incubation with proteinase
K and extraction using phenol-chlorophorm procedure. For tissue and skin samples, the
DNeasy tissue kit (Qiagen) was used. For the skin samples specific primers were
designed for amplifying fragments of 200 - 250 bp, with 30 - 50 bp of overlapping
between adjacent fragments. All primers used are shown in table S4.
Amplifications were performed in 40µl reactions containing: 2.0 µl DNA solution, 1x
PCR buffer (Promega), 2.5mM MgCl2, 0.8mM dNTPs, 0.5µM of each primer, and 2U of
Taq DNA polymerase (Promega). Annealing temperatures ranged from 50 to 54 degrees.
Amplification products were visualized by electrophoresis in 1.3% low-melting-agarose
gels run in TAE (Tris-acetate low-EDTA buffer, pH 7.8). The bands were cut from the
gel and used as templates for re-amplification reactions using the internal primers, under
the same conditions described above, but with higher annealing temperatures.
PCR products were purified with the QIAquick 96 PCR BioRobot kit (Qiagen) using the
BioRobot 9600 (Qiagen). Sequencing of the purified PCR products was performed with
the same primers used for the amplifications and re-amplifications using dRhod (Applied
Biosystems).
Amplifications from skin extractions were performed using HotStarTaq (Quiagen).
Amplification products were visualized by electrophoresis, and cleaned using Perfectprep
PCR Cleanup 96 (Eppendorf).
The cycle sequencing products were run on a 3100 Automated DNA Sequencer (PerkinElmer Applied Biosystems) following the ABI protocol.
Phylogenetic analyses
Sequence data from both the heavy and light strands were obtained. Sequences were
edited and corrected using Sequencher 4.1 (Gene Codes Corporation). Alignment was
performed manually using MacClade 4.0 (Maddison & Maddison 1999) and sequences
were translated to confirm the correct reading frame positions and to check for the
presence of stop codons.
The incongruence length difference test (ILD, Farris et al. 1995) implemented in
PAUP*4.0b10 (Swofford 2002) was performed to assess congruence in phylogenetic
signal between cyt b and ND2. The test excluded constant characters and ran for 1000
bootstrap replications. Independent analyses of the two datasets were also performed.
Another incongruence length difference test was used to compare the three codon
positions. Each gene was examined for evidence of saturation due to multiple
substitutions at each codon position by plotting the number of transition and transversion
substitutions against p-distances for each pairwise comparison. The uniformity of base
composition at each codon position was evaluated through a X2 test of homogeneity.
For the MP analyses, heuristic tree searches, tree bisection reconnection (TBR) branch
swapping, and 100 random addition sequence replications were employed. All characters
were equally weighted and all substitutions were included. The relative support for
inferred monophyletic groupings was determined using non-parametric bootstrapping
(Felsenstein 1985) with 1000 replications. MP analyses of the combined morphological
and molecular data were performed using PAUP* Ver.4.0b10 (Swofford 2002). For this
analysis, the 18 morphological characters were added to a molecular matrix containing
only one representative of each taxon.
ML analyses were performed using the parameters selected by ModelTest 3.7 (Posada &
Crandall 1998) using the Akaike Information Criterion (AIC). The model and parameter
estimates selected were used for the ML analyses, implemented using heuristic tree
search, TBR branch swapping and 10 random addition replicates. Support for nodes in
the ML tree was assessed by non-parametric bootstrapping (Felsenstein 1985) with 100
replications and 5 random addition replicates.
The Bayesian analyses were performed on the combined dataset using MrBayes v3.1.1
(Huelsenbeck & Ronquist 2001) and a mixed model approach to account for potential
difference in evolutionary model parameters between the two genes. Four simultaneous
Markov chains were run for 10,000,000 generations with trees being sampled every 1000
generations for a total of 10,000 trees. The ML scores became stable (stopped improving)
before the 1,000th tree, so that burnin was completed by the 1,000th tree, and 9,000 trees
were kept in each analysis. Three independent analyses were performed for the combined
dataset and the 27,000 sampled trees obtained were used to compute the posterior
probabilities of each node.
Molecular clock dating
The PL method was implemented in the program r8s 1.7 (Sanderson 2003) with the
Truncated Newton (TN) algorithm and using the topologies and branch lengths obtained
in the ML analyses, which were performed as described above. The best value for the
smoothing parameter was estimated through a cross validation procedure. The node
separating Nestor from all other parrots was fixed at 85 mya in the nuclear genes (RAG1
and RAG2) analyses. In the analysis of the mitochondrial matrix the basal node of Pionus
and the split between (Amazona, Graydidascalus) and Pionus were fixed according to the
results obtained on the RAG2 analysis. The RAG2 dates were used for calibrating the
mtDNA tree because of the more uniform sampling scheme of this dataset, when
compared to the RAG1 dataset, and because the RAG2 dataset included several Pionus
species and thus a date for the basal split inside the genus could be estimated.
To assess the sampling error of the time estimates in both nuclear and mitochondrial data
analyses, 100 bootstrapped matrices were constructed using the program CodonBootstrap
3.0b4 (J. P. Bollback, CodonBootstrap v3.0b4 Distributed by the author. Department of
Biology, University of Rochester, Rochester, NY, 2001). Branch lengths were estimated
in PAUP* from each bootstrapped dataset on the ML topology using likelihood
parameters estimated for the original matrices. The trees with branch lengths obtained
were analyzed in r8s 1.7 and the standard deviation for each node was determined using
the profile command.
For the Bayesian analysis the programs baseml (included on PAML 3.14; Yang 1997),
estbranches and mutidivtime (included in the Multidistribute package; Thorne and
Kishino 2002) were used. Model parameters for each dataset were estimated using
baseml with the F84 model. Branch lengths and their variance-covariance matrices were
then estimated using the program estbranches. These matrices were used as input to the
program multidivtime, that implements a Bayesian search using Markov chain Monte
Carlo to estimate a posterior distribution for the rates of evolution and divergence times.
For the nuclear genes analyses (RAG1 and RAG2) we set the mean and standard
deviation of the prior distribution for time separating the ingroup root from the present to
be 95 million years. We set lower and upper bounds of 82 and 85 mya on the node
uniting Nestor to the other parrot genera. To determine the mean and standard deviation
for the prior distribution of the rate of evolution we calculated the mean of the branch
lengths from ingroup root to the tips for all terminals, and divided it by 95 million years.
For the mitochondrial datasets we estimated model parameters in baseml and branch
lengths and their variance-covariance matrices in estbranches independently for each
gene (cyt b and ND2). The two outputs (one for each gene) were analyzed simultaneously
in multidivtime with a mean and standard error for the prior distribution for time
separating the ingroup root from the present of 21 million years, corresponding to the
estimate obtained in the RAG2 analysis for the divergence between Amazona,
Graydidascalus and Pionus. The mean and standard error for the prior distribution of the
rate of evolution were estimated as described for the nuclear datasets. The nodes
corresponding to the split between (Amazona, Graydidascalus) and Pionus, and the base
of Pionus were fixed at 13.3 mya and 6.9 mya, respectively, according to the results of
the RAG2 analysis. In both analyses the Markov chain was sampled 10.000 times with
100 cycles between samples. The first 100.000 were discarded as burnin.
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