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16 results for “Phylogenetic uncertainty”
A Bayesian extension of phylogenetic generalized least squares (PGLS): incorporating uncertainty in the comparative study of trait relationships and evolutionary rates
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Ancient introgression in mouse lemurs (Microcebus:Cheirogaleidae) explains 20 years of phylogenetic uncertainty
<p>Mouse lemurs (genus <em>Microcebus</em>) are a clade of approximately 26 named species of small, nocturnal primates endemic to Madagascar. The genus radiated one and ten million years ago and is morphologically cryptic, with most species having been named within the past 20 years largely based on phylogenetic analysis of short fragments of mitochondrial data. More recent work has been focused on revisiting species designations with autosomal nuclear data using more sophisticated statistical approaches. The order of speciation events in <em>Microcebus </em>remains contentious, particularly with regard to the placement of the <em>M. ravelobensis </em>clade. We investigated support for previous phylogenetic hypotheses based on available whole-genome assemblies from six species and an outgroup. We recovered over 4,000 one-to-one orthologs from these assemblies and used concatenation and coalescent species tree methods to<em> </em>evaluate if differences between previous studies were due to methodological differences or to limitations from too few loci. Observed gene tree discordance was high with patterns inconsistent with incomplete lineage sorting alone. Therefore, we estimated phylogenetic networks to investigate ancient introgression events that may explain observed gene tree distributions and previous phylogenetic conflicts. A network model, invoking some role for introgressive hybridization in the early evolution of <em>Microcebus</em>, better characterizes phylogenetic relationships than does any binary species tree. Our results provide insights into the biogeographic history of a threatened and diverse group of primates while also highlighting an important role for phylogenetic network methods in resolving cases of phylogenetic uncertainty.</p>
Data from: Introgression underlies phylogenetic uncertainty but not parallel plumage evolution in a recent songbird radiation
<p class="MsoNormal"><span>Instances of parallel phenotypic evolution offer great opportunities to understand the evolutionary processes underlying phenotypic changes. However, confirming parallel phenotypic evolution and studying its causes requires a robust phylogenetic framework. One such example is the "black-and-white wagtails", a group of five species in the songbird genus </span><em><span>Motacilla</span></em><span>: one species, the White Wagtail (</span><em><span>M. alba</span></em><span>), shows wide intra-specific plumage variation, while the four others form two pairs of very similar-looking species (African Pied Wagtail </span><em><span>M. aguimp </span></em><span>+ Mekong Wagtail </span><em><span>M. samveasnae</span></em><span><em><span> </span></em>and Japanese Wagtail </span><em><span>M. grandis</span></em><span><em><span> </span></em>+ White-browed Wagtail </span><em><span>M. maderaspatensis</span></em><span>, respectively). However, the two species in each of these pairs were not recovered as sisters in previous phylogenetic inferences. Their relationships varied depending on the markers used, suggesting that gene tree heterogeneity might have hampered accurate phylogenetic inference. Here, we use whole genome resequencing data to explore the phylogenetic relationships within this group, with a special emphasis on characterizing the extent of gene tree heterogeneity and its underlying causes. We first used multispecies coalescent methods to generate a "complete evidence" phylogenetic hypothesis based on genome-wide variants, while accounting for incomplete lineage sorting and introgression. We then investigated the variation in phylogenetic signal across the genome, to quantify the extent of discordance across genomic regions, and test its underlying causes. We found that wagtail genomes are mosaics of regions supporting variable genealogies, because of ILS and inter-specific introgression. The most common topology across the genome, supporting </span><em><span>M. alba</span></em><span> and </span><em><span>M. aguimp</span></em><span> as sister species, appears to be influenced by ancient introgression. Additionally, we inferred another ancient introgression event, between </span><em><span>M. alba</span></em><span> and </span><em><span>M. grandis</span></em><span>. By combining results from multiple analyses, we propose a phylogenetic network for the black-and-white wagtails that confirms that similar phenotypes evolved in non-sister lineages, supporting parallel plumage evolution. Furthermore, the inferred reticulations do not connect species with similar plumage coloration, suggesting that introgression does not underlie parallel plumage evolution in this group. Our results demonstrate the importance of investigation of genome-wide patterns of gene tree heterogeneity to help understanding the mechanisms underlying phenotypic evolution.</span></p>
Data from: Introgression underlies phylogenetic uncertainty but not parallel plumage evolution in a recent songbird radiation
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Phylogenetic position and stratigraphic uncertainty of a new flexible crinoid from the Ordovician–Silurian boundary of Anticosti Island (Quebec, Canada)
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Data from: Retracing the Hawaiian silversword radiation despite phylogenetic, biogeographic, and paleogeographic uncertainty
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Ancient introgression in mouse lemurs (Microcebus:Cheirogaleidae) explains 20 years of phylogenetic uncertainty
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Data from: The impact of reconstruction methods, phylogenetic uncertainty and branch lengths on inference of chromosome number evolution in American daisies (Melampodium, Asteraceae)
Chromosome number change (polyploidy and dysploidy) plays an important role in plant diversification and speciation. Investigating chromosome number evolution commonly entails ancestral state reconstruction performed within a phylogenetic framework, which is, however, prone to uncertainty, whose effects on evolutionary inferences are insufficiently understood. Using the chromosomally diverse plant genus Melampodium (Asteraceae) as model group, we assess the impact of reconstruction method (maximum parsimony, maximum likelihood, Bayesian methods), branch length model (phylograms versus chronograms) and phylogenetic uncertainty (topological and branch length uncertainty) on the inference of chromosome number evolution. We also address the suitability of the maximum clade credibility (MCC) tree as single representative topology for chromosome number reconstruction. Each of the listed factors causes considerable incongruence among chromosome number reconstructions. Discrepancies between inferences on the MCC tree from those made by integrating over a set of trees are moderate for ancestral chromosome numbers, but severe for the difference of chromosome gains and losses, a measure of the directionality of dysploidy. Therefore, reliance on single trees, such as the MCC tree, is strongly discouraged and model averaging, taking both phylogenetic and model uncertainty into account, is recommended. For studying chromosome number evolution, dedicated models implemented in the program ChromEvol and ordered maximum parsimony may be most appropriate. Chromosome number evolution in Melampodium follows a pattern of bidirectional dysploidy (starting from x = 11 to x = 9 and x = 14, respectively) with no prevailing direction.
Data from: Bayesian and likelihood phylogenetic reconstructions of morphological traits are not discordant when taking uncertainty into consideration: a comment on Puttick et al
Puttick et al. (2017 Proc. R. Soc. B 284, 20162290 (doi:10.1098/rspb.2016.2290)) performed a simulation study to compare accuracy among methods of inferring phylogeny from discrete morphological characters. They report that a Bayesian implementation of the Mk model (Lewis 2001 Syst. Biol. 50, 913–925 (doi:10.1080/106351501753462876)) was most accurate (but with low resolution), while a maximum-likelihood (ML) implementation of the same model was least accurate. They conclude by strongly advocating that Bayesian implementations of the Mk model should be the default method of analysis for such data. While we appreciate the authors' attempt to investigate the accuracy of alternative methods of analysis, their conclusion is based on an inappropriate comparison of the ML point estimate, which does not consider confidence, with the Bayesian consensus, which incorporates estimation credibility into the summary tree. Using simulation, we demonstrate that ML and Bayesian estimates are concordant when confidence and credibility are comparably reflected in summary trees, a result expected from statistical theory. We therefore disagree with the conclusions of Puttick et al. and consider their prescription of any default method to be poorly founded. Instead, we recommend caution and thoughtful consideration of the model or method being applied to a morphological dataset.
Data from: Phylogenetic uncertainty and taxonomic re-revisions: an example from the Australian short-necked turtles (Testudines: Chelidae)
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Data from: The impact of reconstruction methods, phylogenetic uncertainty and branch lengths on inference of chromosome number evolution in American daisies (Melampodium, Asteraceae)
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Data from: Bayesian and likelihood phylogenetic reconstructions of morphological traits are not discordant when taking uncertainty into consideration: a comment on Puttick et al
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Data from: Phylogenetic uncertainty revisited: implications for ecological analyses
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Data from: Genealogical working distributions for Bayesian model testing with phylogenetic uncertainty
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Data from: Generalized bootstrap supports for phylogenetic analyses of protein sequences incorporating alignment uncertainty
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Data for Santos Neves et. al Addressing the uncertainty of within-archipelago evolutionary history in phylogenetic data
<p>Phylogenetic data and checklists of Hawai'i spider fauna accompanying <em>Addressing the uncertainty of within-archipelago evolutionary history in phylogenetic data</em> (in prep).</p> <p> </p> <p> </p>
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