Computational protocol: Molecular assessment of the phylogeny and biogeography of a recentlydiversified endemic group of South American canids (Mammalia: Carnivora:Canidae)

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Protocol publication

[…] Sequences were verified and corrected using Chromas (Technelysium) or Sequencher (Gene Codes Inc.), aligned using the ClustalW algorithm implemented in MEGA 6.0 () and visually checked. Sites or segments that could not be unambiguously aligned were excluded from all analyses. Initial sequence comparisons and assessments of variability, such as computing the number of variable sites and nucleotide diversity (π per nucleotide site, the probability that two randomly chosen homologous nucleotides are different in the sample) were performed in MEGA 6.0 using Kimura 2-parameter distances and 1000 bootstrap replicates. Estimates of gene diversity (h, the probability that two randomly chosen mtDNA lineages were different in the sample) were computed in Arlequin 3.11 () with 10,000 permutations to assess their variance.We reconstructed the phylogenetic relationships among Lycalopex haplotypes using the Bayesian approach implemented in Beast 1.8.0 (). We included only complete sequences (i.e. containing no missing data), so as to maximize the stability and reliability of the inferred phylogeny. We estimated the best-fit molecular model of evolution for this data set with Modeltest 3.6 (), using the Akaike Information Criterion. The selected model (GTR+G+I) was then incorporated in the analysis. We ran the Markov Chain Monte Carlo (MCMC) process in Beast for 100 million generations, with the data sampled every 1,000 steps, and discarding the initial 10% as burn-in.In addition to the phylogenetic analysis, we also investigated the relationships among Lycalopex haplotypes using a median-joining network approach, which was performed with Network 4.6.1.2 (Fluxus Technology). Since this method allows for ancestor-descendant relationships among haplotypes, as well as displays genealogical ambiguities more clearly than a tree-based approach, it is expected to be useful in the analysis of this recently diversified group. Moreover, since our data set included multiple individuals per species, we used this approach to assess species-level monophyly of mtDNA lineages, as well as instances of apparent ‘swaps' indicative of erroneous identification or inter-species hybridization (see Results).To estimate divergence times within this genus, we used two methods. In the first one, we performed a Bayesian estimation using Beast, assuming an uncorrelated lognormal relaxed molecular clock. This analysis was calibrated with the mean substitution rate (μ = 3.68x10-8/year) estimated for the same CR segment in canids by , based on available data from grey wolf and coyote. In the second method, we employed a population-genetic approach based on the equation dxy=2μT (), using the estimated mtDNA divergence (dxy as implemented in Mega, with K2P distances [a simpler model was incorporated here, relative to the Beast analyses, to minimize the variance around parameter estimates]) between species or groups of species, and the same substitution rate mentioned above. The divergence time between mtDNA lineages was calculated considering the 95% confidence interval (CI = ± 2SE) for all values of dxy. Using this interval for the calibration node, we obtained low, medium and fast substitution rate estimations (2.02x10-8, 3.68x10-8 and 5.34x10-8/year, respectively), which were then applied to the equivalent dxy interval estimated for each node. This approach allowed a conservative estimate of uncertainty in the dating of these rapid divergences, while providing a robust assessment of their overall temporal framework. […]

Pipeline specifications

Software tools Sequencher, Clustal W, MEGA, Arlequin, BEAST, ModelTest-NG
Applications Phylogenetics, Population genetic analysis
Organisms Homo sapiens